diff --git a/.github/workflows/publish-to-docker.yml b/.github/workflows/publish-to-docker.yml
index cf1e8b916..0dbca6939 100644
--- a/.github/workflows/publish-to-docker.yml
+++ b/.github/workflows/publish-to-docker.yml
@@ -11,6 +11,10 @@ on:
 jobs:
   build-and-push:
     runs-on: ubuntu-latest
+    env:
+      TOGETHER_API_KEY: ${{ secrets.TOGETHER_API_KEY }}
+      FIREWORKS_API_KEY: ${{ secrets.FIREWORKS_API_KEY }}
+      TAVILY_SEARCH_API_KEY: ${{ secrets.TAVILY_SEARCH_API_KEY }}
     permissions:
       contents: read
       packages: write
@@ -32,7 +36,7 @@ jobs:
         id: version
         run: |
           if [ "${{ github.event_name }}" = "push" ]; then
-            echo "VERSION=0.0.63.dev20250114" >> $GITHUB_OUTPUT
+            echo "VERSION=0.0.63.dev51206766" >> $GITHUB_OUTPUT
           else
             echo "VERSION=${{ inputs.version }}" >> $GITHUB_OUTPUT
           fi
@@ -42,8 +46,11 @@ jobs:
             # Function to check if version exists in a repository
             check_version() {
                 local repo=$1
-                local status_code=$(curl -s -o /dev/null -w "%{http_code}" "https://$repo.org/project/llama-stack/${{ steps.version.outputs.version }}")
-                return $([ "$status_code" -eq 200 ])
+                local VERSION_TO_CHECK=${{ steps.version.outputs.version }}
+                echo "Checking version $VERSION_TO_CHECK in $repo"
+                result=$(curl -s "https://$repo.org/pypi/llama-stack/json" | jq --arg v "$VERSION_TO_CHECK" '.releases | has($v)')
+                echo "Result: $result"
+                return $([ "$result" = "true" ])
             }
 
             # Check TestPyPI first, then PyPI
@@ -60,6 +67,7 @@ jobs:
 
       - name: Install llama-stack
         run: |
+            echo "PYPI_SOURCE=${PYPI_SOURCE}"
             if [ "${{ github.event_name }}" = "push" ]; then
                 pip install -e .
             else
@@ -72,12 +80,14 @@ jobs:
 
       - name: Build docker image
         run: |
+          echo "PYPI_SOURCE=${PYPI_SOURCE}"
+          echo "VERSION=${{ steps.version.outputs.version }}"
           TEMPLATES=("ollama" "bedrock" "remote-vllm" "fireworks" "together" "tgi" "meta-reference-gpu")
           for template in "${TEMPLATES[@]}"; do
             if [ "$PYPI_SOURCE" = "testpypi" ]; then
-                TEST_PYPI_VERSION=${{ steps.version.outputs.version }} llama stack build --template $template --image-type docker
+                TEST_PYPI_VERSION=${{ steps.version.outputs.version }} llama stack build --template $template --image-type container
             else
-                PYPI_VERSION=${{ steps.version.outputs.version }} llama stack build --template $template --image-type docker
+                PYPI_VERSION=${{ steps.version.outputs.version }} llama stack build --template $template --image-type container
             fi
           done
 
@@ -85,8 +95,45 @@ jobs:
         run: |
           docker images
 
+      # TODO (xiyan): make the following 2 steps into a matrix and test all templates other than fireworks
+      - name: Start up built docker image
+        run: |
+          cd distributions/fireworks
+          if [ "$PYPI_SOURCE" = "testpypi" ]; then
+            sed -i 's|image: llamastack/distribution-fireworks|image: distribution-fireworks:test-${{ steps.version.outputs.version }}|' ./compose.yaml
+          else
+            sed -i 's|image: llamastack/distribution-fireworks|image: distribution-fireworks:${{ steps.version.outputs.version }}|' ./compose.yaml
+          fi
+          docker compose up -d
+          cd ..
+          # Wait for the container to start
+          timeout=300
+          while ! curl -s -f http://localhost:8321/v1/version > /dev/null && [ $timeout -gt 0 ]; do
+            echo "Waiting for endpoint to be available..."
+            sleep 5
+            timeout=$((timeout - 5))
+          done
+
+          if [ $timeout -le 0 ]; then
+            echo "Timeout waiting for endpoint to become available"
+            exit 1
+          fi
+
+      - name: Run simple models list test on docker server
+        run: |
+          curl http://localhost:8321/v1/models
+
+      # TODO (xiyan): figure out why client cannot find server but curl works
+      # - name: Run pytest on docker server
+      #   run: |
+      #     pip install pytest pytest-md-report
+      #     export LLAMA_STACK_BASE_URL="http://localhost:8321"
+      #     LLAMA_STACK_BASE_URL="http://localhost:8321" pytest -v tests/client-sdk/inference/test_inference.py --md-report --md-report-verbose=1
+
       - name: Push to dockerhub
         run: |
+          echo "PYPI_SOURCE=${PYPI_SOURCE}"
+          echo "VERSION=${{ steps.version.outputs.version }}"
           TEMPLATES=("ollama" "bedrock" "remote-vllm" "fireworks" "together" "tgi" "meta-reference-gpu")
           for template in "${TEMPLATES[@]}"; do
             if [ "$PYPI_SOURCE" = "testpypi" ]; then
@@ -94,6 +141,8 @@ jobs:
                 docker push llamastack/distribution-$template:test-${{ steps.version.outputs.version }}
             else
                 docker tag distribution-$template:${{ steps.version.outputs.version }} llamastack/distribution-$template:${{ steps.version.outputs.version }}
+                docker tag distribution-$template:${{ steps.version.outputs.version }} llamastack/distribution-$template:latest
                 docker push llamastack/distribution-$template:${{ steps.version.outputs.version }}
+                docker push llamastack/distribution-$template:latest
             fi
           done
diff --git a/.github/workflows/publish-to-test-pypi.yml b/.github/workflows/publish-to-test-pypi.yml
index 9fe502254..2e8aaab23 100644
--- a/.github/workflows/publish-to-test-pypi.yml
+++ b/.github/workflows/publish-to-test-pypi.yml
@@ -238,7 +238,7 @@ jobs:
       run: |
         pip install pytest nbval
         llama stack build --template together --image-type venv
-        pytest -v -s --nbval-lax ./docs/notebooks/Llama_Stack_Building_AI_Applications.ipynb
+        pytest -v -s --nbval-lax ./docs/getting_started.ipynb
         pytest -v -s --nbval-lax ./docs/notebooks/Llama_Stack_Benchmark_Evals.ipynb
 
     # TODO: add trigger for integration test workflow & docker builds
diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
index 4713f564a..e42d6db75 100644
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -12,6 +12,57 @@ We actively welcome your pull requests.
 5. Make sure your code lints.
 6. If you haven't already, complete the Contributor License Agreement ("CLA").
 
+## Contributor License Agreement ("CLA")
+In order to accept your pull request, we need you to submit a CLA. You only need
+to do this once to work on any of Meta's open source projects.
+
+Complete your CLA here: <https://code.facebook.com/cla>
+
+## Issues
+We use GitHub issues to track public bugs. Please ensure your description is
+clear and has sufficient instructions to be able to reproduce the issue.
+
+Meta has a [bounty program](http://facebook.com/whitehat/info) for the safe
+disclosure of security bugs. In those cases, please go through the process
+outlined on that page and do not file a public issue.
+
+
+## Pre-commit Hooks
+
+We use [pre-commit](https://pre-commit.com/) to run linting and formatting checks on your code. You can install the pre-commit hooks by running:
+
+```bash
+$ cd llama-stack
+$ conda activate <your-environment>
+$ pip install pre-commit
+$ pre-commit install
+```
+
+After that, pre-commit hooks will run automatically before each commit.
+
+
+## Coding Style
+* 2 spaces for indentation rather than tabs
+* 80 character line length
+* ...
+
+## Common Tasks
+
+Some tips about common tasks you work on while contributing to Llama Stack:
+
+### Using `llama stack build`
+
+Building a stack image (conda / docker) will use the production version of the `llama-stack`, `llama-models` and `llama-stack-client` packages. If you are developing with a llama-stack repository checked out and need your code to be reflected in the stack image, set `LLAMA_STACK_DIR` and `LLAMA_MODELS_DIR` to the appropriate checked out directories when running any of the `llama` CLI commands.
+
+Example:
+```bash
+$ cd work/
+$ git clone https://github.com/meta-llama/llama-stack.git
+$ git clone https://github.com/meta-llama/llama-models.git
+$ cd llama-stack
+$ LLAMA_STACK_DIR=$(pwd) LLAMA_MODELS_DIR=../llama-models llama stack build --template <...>
+```
+
 
 ### Updating Provider Configurations
 
@@ -31,40 +82,6 @@ make html
 sphinx-autobuild source build/html
 ```
 
-## Pre-commit Hooks
-
-We use [pre-commit](https://pre-commit.com/) to run linting and formatting checks on your code. You can install the pre-commit hooks by running:
-
-```bash
-$ cd llama-stack
-$ conda activate <your-environment>
-$ pip install pre-commit
-$ pre-commit install
-```
-
-After that, pre-commit hooks will run automatically before each commit.
-
-## Contributor License Agreement ("CLA")
-In order to accept your pull request, we need you to submit a CLA. You only need
-to do this once to work on any of Meta's open source projects.
-
-Complete your CLA here: <https://code.facebook.com/cla>
-
-## Issues
-We use GitHub issues to track public bugs. Please ensure your description is
-clear and has sufficient instructions to be able to reproduce the issue.
-
-Meta has a [bounty program](http://facebook.com/whitehat/info) for the safe
-disclosure of security bugs. In those cases, please go through the process
-outlined on that page and do not file a public issue.
-
-## Coding Style
-* 2 spaces for indentation rather than tabs
-* 80 character line length
-* ...
-
-## Tips
-* If you are developing with a llama-stack repository checked out and need your distribution to reflect changes from there, set `LLAMA_STACK_DIR` to that dir when running any of the `llama` CLI commands.
 
 ## License
 By contributing to Llama, you agree that your contributions will be licensed
diff --git a/README.md b/README.md
index 61a0f33fe..53235389f 100644
--- a/README.md
+++ b/README.md
@@ -4,9 +4,15 @@
 [![PyPI - Downloads](https://img.shields.io/pypi/dm/llama-stack)](https://pypi.org/project/llama-stack/)
 [![Discord](https://img.shields.io/discord/1257833999603335178)](https://discord.gg/llama-stack)
 
-[**Quick Start**](https://llama-stack.readthedocs.io/en/latest/getting_started/index.html) | [**Documentation**](https://llama-stack.readthedocs.io/en/latest/index.html) | [**Zero-to-Hero Guide**](https://github.com/meta-llama/llama-stack/tree/main/docs/zero_to_hero_guide)
+[**Quick Start**](https://llama-stack.readthedocs.io/en/latest/getting_started/index.html) | [**Documentation**](https://llama-stack.readthedocs.io/en/latest/index.html) | [**Colab Notebook**](./docs/getting_started.ipynb)
 
-Llama Stack defines and standardizes the set of core building blocks needed to bring generative AI applications to market. These building blocks are presented in the form of interoperable APIs with a broad set of Service Providers providing their implementations.
+Llama Stack defines and standardizes the core building blocks that simplify AI application development. It codified best practices across the Llama ecosystem. More specifically, it provides
+
+- **Unified API layer** for Inference, RAG, Agents, Tools, Safety, Evals, and Telemetry.
+- **Plugin architecture** to support the rich ecosystem of implementations of the different APIs in different environments like local development, on-premises, cloud, and mobile.
+- **Prepackaged verified distributions** which offer a one-stop solution for developers to get started quickly and reliably in any environment
+- **Multiple developer interfaces** like CLI and SDKs for Python, Node, iOS, and Android
+- **Standalone applications** as examples for how to build production-grade AI applications with Llama Stack
 
 <div style="text-align: center;">
   <img
@@ -17,69 +23,20 @@ Llama Stack defines and standardizes the set of core building blocks needed to b
   />
 </div>
 
-Our goal is to provide pre-packaged implementations which can be operated in a variety of deployment environments: developers start iterating with Desktops or their mobile devices and can seamlessly transition to on-prem or public cloud deployments. At every point in this transition, the same set of APIs and the same developer experience is available.
+### Llama Stack Benefits
+- **Flexible Options**: Developers can choose their preferred infrastructure without changing APIs and enjoy flexible deployment choice.
+- **Consistent Experience**: With its unified APIs Llama Stack makes it easier to build, test, and deploy AI applications with consistent application behavior.
+- **Robust Ecosystem**: Llama Stack is already integrated with distribution partners (cloud providers, hardware vendors, and AI-focused companies) that offer tailored infrastructure, software, and services for deploying Llama models.
 
-> ⚠️ **Note**
-> The Stack APIs are rapidly improving, but still very much work in progress and we invite feedback as well as direct contributions.
+By reducing friction and complexity, Llama Stack empowers developers to focus on what they do best: building transformative generative AI applications.
 
-
-## APIs
-
-We have working implementations of the following APIs today:
-- Inference
-- Safety
-- Memory
-- Agents
-- Eval
-- Telemetry
-
-Alongside these APIs, we also related APIs for operating with associated resources (see [Concepts](https://llama-stack.readthedocs.io/en/latest/concepts/index.html#resources)):
-
-- Models
-- Shields
-- Memory Banks
-- Eval Tasks
-- Datasets
-- Scoring Functions
-
-We are also working on the following APIs which will be released soon:
-
-- Post Training
-- Synthetic Data Generation
-- Reward Scoring
-
-Each of the APIs themselves is a collection of REST endpoints.
-
-## Philosophy
-
-### Service-oriented design
-
-Unlike other frameworks, Llama Stack is built with a service-oriented, REST API-first approach. Such a design not only allows for seamless transitions from a local to remote deployments, but also forces the design to be more declarative. We believe this restriction can result in a much simpler, robust developer experience. This will necessarily trade-off against expressivity however if we get the APIs right, it can lead to a very powerful platform.
-
-### Composability
-
-We expect the set of APIs we design to be composable. An Agent abstractly depends on { Inference, Memory, Safety } APIs but does not care about the actual implementation details. Safety itself may require model inference and hence can depend on the Inference API.
-
-### Turnkey one-stop solutions
-
-We expect to provide turnkey solutions for popular deployment scenarios. It should be easy to deploy a Llama Stack server on AWS or on a private data center. Either of these should allow a developer to get started with powerful agentic apps, model evaluations or fine-tuning services in a matter of minutes. They should all result in the same uniform observability and developer experience.
-
-### Focus on Llama models
-
-As a Meta initiated project, we have started by explicitly focusing on Meta's Llama series of models. Supporting the broad set of open models is no easy task and we want to start with models we understand best.
-
-### Supporting the Ecosystem
-
-There is a vibrant ecosystem of Providers which provide efficient inference or scalable vector stores or powerful observability solutions. We want to make sure it is easy for developers to pick and choose the best implementations for their use cases. We also want to make sure it is easy for new Providers to onboard and participate in the ecosystem.
-
-Additionally, we have designed every element of the Stack such that APIs as well as Resources (like Models) can be federated.
-
-
-## Supported Llama Stack Implementations
 ### API Providers
+Here is a list of the various API providers and available distributions to developers started easily,
+
 |                                  **API Provider Builder**                                  |    **Environments**    |     **Agents**     |   **Inference**    |     **Memory**     |     **Safety**     |   **Telemetry**    |
 |:------------------------------------------------------------------------------------------:|:----------------------:|:------------------:|:------------------:|:------------------:|:------------------:|:------------------:|
 |                                       Meta Reference                                       |      Single Node       | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: |
+|                                          SambaNova                                         |         Hosted         |                    | :heavy_check_mark: |                    |                    |                    |
 |                                          Cerebras                                          |         Hosted         |                    | :heavy_check_mark: |                    |                    |                    |
 |                                         Fireworks                                          |         Hosted         | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: |                    |                    |
 |                                        AWS Bedrock                                         |         Hosted         |                    | :heavy_check_mark: |                    | :heavy_check_mark: |                    |
@@ -87,26 +44,29 @@ Additionally, we have designed every element of the Stack such that APIs as well
 |                                            Groq                                            |         Hosted         |                    | :heavy_check_mark: |                    |                    |                    |
 |                                           Ollama                                           |      Single Node       |                    | :heavy_check_mark: |                    |                    |                    |
 |                                            TGI                                             | Hosted and Single Node |                    | :heavy_check_mark: |                    |                    |                    |
-| [NVIDIA NIM](https://build.nvidia.com/nim?filters=nimType%3Anim_type_run_anywhere&q=llama) | Hosted and Single Node |                    | :heavy_check_mark: |                    |                    |                    |
+| NVIDIA NIM | Hosted and Single Node |                    | :heavy_check_mark: |                    |                    |                    |
 |                                           Chroma                                           |      Single Node       |                    |                    | :heavy_check_mark: |                    |                    |
 |                                         PG Vector                                          |      Single Node       |                    |                    | :heavy_check_mark: |                    |                    |
 |                                     PyTorch ExecuTorch                                     |     On-device iOS      | :heavy_check_mark: | :heavy_check_mark: |                    |                    |                    |
-|                        [vLLM](https://github.com/vllm-project/vllm)                        | Hosted and Single Node |                    | :heavy_check_mark: |                    |                    |                    |
+|                        vLLM                        | Hosted and Single Node |                    | :heavy_check_mark: |                    |                    |                    |
 
 ### Distributions
 
+A Llama Stack Distribution (or "distro") is a pre-configured bundle of provider implementations for each API component. Distributions make it easy to get started with a specific deployment scenario - you can begin with a local development setup (eg. ollama) and seamlessly transition to production (eg. Fireworks) without changing your application code. Here are some of the distributions we support:
+
 |               **Distribution**                |                                                                    **Llama Stack Docker**                                                                     |                                                 Start This Distribution                                                  |
 |:---------------------------------------------:|:-------------------------------------------------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------------:|
 |                Meta Reference                 |           [llamastack/distribution-meta-reference-gpu](https://hub.docker.com/repository/docker/llamastack/distribution-meta-reference-gpu/general)           |      [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/meta-reference-gpu.html)      |
 |           Meta Reference Quantized            | [llamastack/distribution-meta-reference-quantized-gpu](https://hub.docker.com/repository/docker/llamastack/distribution-meta-reference-quantized-gpu/general) | [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/meta-reference-quantized-gpu.html) |
+|                   SambaNova                   |                     [llamastack/distribution-sambanova](https://hub.docker.com/repository/docker/llamastack/distribution-sambanova/general)                     |   [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/sambanova.html)   |
 |                   Cerebras                    |                     [llamastack/distribution-cerebras](https://hub.docker.com/repository/docker/llamastack/distribution-cerebras/general)                     |   [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/cerebras.html)   |
 |                    Ollama                     |                       [llamastack/distribution-ollama](https://hub.docker.com/repository/docker/llamastack/distribution-ollama/general)                       |            [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/ollama.html)            |
 |                      TGI                      |                          [llamastack/distribution-tgi](https://hub.docker.com/repository/docker/llamastack/distribution-tgi/general)                          |             [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/tgi.html)              |
 |                   Together                    |                     [llamastack/distribution-together](https://hub.docker.com/repository/docker/llamastack/distribution-together/general)                     |           [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/together.html)           |
 |                   Fireworks                   |                    [llamastack/distribution-fireworks](https://hub.docker.com/repository/docker/llamastack/distribution-fireworks/general)                    |          [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/fireworks.html)           |
-| [vLLM](https://github.com/vllm-project/vllm)  |                  [llamastack/distribution-remote-vllm](https://hub.docker.com/repository/docker/llamastack/distribution-remote-vllm/general)                  |         [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/remote-vllm.html)          |
+| vLLM |                  [llamastack/distribution-remote-vllm](https://hub.docker.com/repository/docker/llamastack/distribution-remote-vllm/general)                  |         [Guide](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/remote-vllm.html)          |
 
-## Installation
+### Installation
 
 You have two ways to install this repository:
 
@@ -131,7 +91,7 @@ You have two ways to install this repository:
     pip install -e .
    ```
 
-## Documentation
+### Documentation
 
 Please checkout our [Documentation](https://llama-stack.readthedocs.io/en/latest/index.html) page for more details.
 
@@ -139,13 +99,13 @@ Please checkout our [Documentation](https://llama-stack.readthedocs.io/en/latest
     * Guide using `llama` CLI to work with Llama models (download, study prompts), and building/starting a Llama Stack distribution.
 * [Getting Started](https://llama-stack.readthedocs.io/en/latest/getting_started/index.html)
     * Quick guide to start a Llama Stack server.
-    * [Jupyter notebook](./docs/notebooks/Llama_Stack_Building_AI_Applications.ipynb) to walk-through how to use simple text and vision inference llama_stack_client APIs
+    * [Jupyter notebook](./docs/getting_started.ipynb) to walk-through how to use simple text and vision inference llama_stack_client APIs
     * The complete Llama Stack lesson [Colab notebook](https://colab.research.google.com/drive/1dtVmxotBsI4cGZQNsJRYPrLiDeT0Wnwt) of the new [Llama 3.2 course on Deeplearning.ai](https://learn.deeplearning.ai/courses/introducing-multimodal-llama-3-2/lesson/8/llama-stack).
     * A [Zero-to-Hero Guide](https://github.com/meta-llama/llama-stack/tree/main/docs/zero_to_hero_guide) that guide you through all the key components of llama stack with code samples.
 * [Contributing](CONTRIBUTING.md)
     * [Adding a new API Provider](https://llama-stack.readthedocs.io/en/latest/contributing/new_api_provider.html) to walk-through how to add a new API provider.
 
-## Llama Stack Client SDKs
+### Llama Stack Client SDKs
 
 |  **Language** |  **Client SDK** | **Package** |
 | :----: | :----: | :----: |
diff --git a/distributions/dell-tgi/run.yaml b/distributions/dell-tgi/run.yaml
index 3f8a98779..cd6ddcfdf 100644
--- a/distributions/dell-tgi/run.yaml
+++ b/distributions/dell-tgi/run.yaml
@@ -1,6 +1,6 @@
 version: '2'
 image_name: local
-docker_image: null
+container_image: null
 conda_env: local
 apis:
 - shields
diff --git a/distributions/dependencies.json b/distributions/dependencies.json
index d6d60ef7c..2b2e35a50 100644
--- a/distributions/dependencies.json
+++ b/distributions/dependencies.json
@@ -1,4 +1,34 @@
 {
+  "sambanova": [
+    "aiosqlite",
+    "blobfile",
+    "chardet",
+    "chromadb-client",
+    "faiss-cpu",
+    "fastapi",
+    "fire",
+    "httpx",
+    "matplotlib",
+    "nltk",
+    "numpy",
+    "openai",
+    "opentelemetry-exporter-otlp-proto-http",
+    "opentelemetry-sdk",
+    "pandas",
+    "pillow",
+    "psycopg2-binary",
+    "pypdf",
+    "redis",
+    "requests",
+    "scikit-learn",
+    "scipy",
+    "sentencepiece",
+    "tqdm",
+    "transformers",
+    "uvicorn",
+    "sentence-transformers --no-deps",
+    "torch --index-url https://download.pytorch.org/whl/cpu"
+  ],
   "hf-serverless": [
     "aiohttp",
     "aiosqlite",
@@ -13,6 +43,7 @@
     "httpx",
     "huggingface_hub",
     "matplotlib",
+    "mcp",
     "nltk",
     "numpy",
     "openai",
@@ -45,6 +76,7 @@
     "fire",
     "httpx",
     "matplotlib",
+    "mcp",
     "nltk",
     "numpy",
     "openai",
@@ -78,6 +110,7 @@
     "fire",
     "httpx",
     "matplotlib",
+    "mcp",
     "nltk",
     "numpy",
     "openai",
@@ -101,14 +134,17 @@
   ],
   "remote-vllm": [
     "aiosqlite",
+    "autoevals",
     "blobfile",
     "chardet",
     "chromadb-client",
+    "datasets",
     "faiss-cpu",
     "fastapi",
     "fire",
     "httpx",
     "matplotlib",
+    "mcp",
     "nltk",
     "numpy",
     "openai",
@@ -142,6 +178,7 @@
     "fireworks-ai",
     "httpx",
     "matplotlib",
+    "mcp",
     "nltk",
     "numpy",
     "openai",
@@ -176,6 +213,7 @@
     "httpx",
     "huggingface_hub",
     "matplotlib",
+    "mcp",
     "nltk",
     "numpy",
     "openai",
@@ -209,6 +247,7 @@
     "fire",
     "httpx",
     "matplotlib",
+    "mcp",
     "nltk",
     "numpy",
     "openai",
@@ -244,6 +283,7 @@
     "httpx",
     "lm-format-enforcer",
     "matplotlib",
+    "mcp",
     "nltk",
     "numpy",
     "openai",
@@ -279,6 +319,7 @@
     "fire",
     "httpx",
     "matplotlib",
+    "mcp",
     "nltk",
     "numpy",
     "openai",
@@ -315,6 +356,7 @@
     "httpx",
     "lm-format-enforcer",
     "matplotlib",
+    "mcp",
     "nltk",
     "numpy",
     "openai",
@@ -421,6 +463,7 @@
     "httpx",
     "huggingface_hub",
     "matplotlib",
+    "mcp",
     "nltk",
     "numpy",
     "openai",
diff --git a/distributions/fireworks/compose.yaml b/distributions/fireworks/compose.yaml
index 4b53fcf00..84b8491e4 100644
--- a/distributions/fireworks/compose.yaml
+++ b/distributions/fireworks/compose.yaml
@@ -1,13 +1,11 @@
 services:
   llamastack:
     image: llamastack/distribution-fireworks
-    network_mode: "host"
-    volumes:
-      - ~/.llama:/root/.llama
-      - ./run.yaml:/root/llamastack-run-fireworks.yaml
     ports:
       - "8321:8321"
-    entrypoint: bash -c "python -m llama_stack.distribution.server.server --yaml_config /root/llamastack-run-fireworks.yaml"
+    environment:
+      - FIREWORKS_API_KEY=${FIREWORKS_API_KEY}
+    entrypoint: bash -c "python -m llama_stack.distribution.server.server --template fireworks"
     deploy:
       restart_policy:
         condition: on-failure
diff --git a/distributions/meta-reference-quantized-gpu/run.yaml b/distributions/meta-reference-quantized-gpu/run.yaml
index 19c726b09..eb631adaa 100644
--- a/distributions/meta-reference-quantized-gpu/run.yaml
+++ b/distributions/meta-reference-quantized-gpu/run.yaml
@@ -1,6 +1,6 @@
 version: '2'
 image_name: local
-docker_image: null
+container_image: null
 conda_env: local
 apis:
 - shields
diff --git a/distributions/runpod/build.yaml b/distributions/runpod/build.yaml
new file mode 100644
index 000000000..9348573ef
--- /dev/null
+++ b/distributions/runpod/build.yaml
@@ -0,0 +1,9 @@
+name: runpod
+distribution_spec:
+  description: Use Runpod for running LLM inference
+  providers:
+    inference: remote::runpod
+    memory: meta-reference
+    safety: meta-reference
+    agents: meta-reference
+    telemetry: meta-reference
diff --git a/distributions/sambanova/build.yaml b/distributions/sambanova/build.yaml
new file mode 100644
index 000000000..dbf013d2d
--- /dev/null
+++ b/distributions/sambanova/build.yaml
@@ -0,0 +1 @@
+../../llama_stack/templates/sambanova/build.yaml
diff --git a/distributions/sambanova/compose.yaml b/distributions/sambanova/compose.yaml
new file mode 100644
index 000000000..58b9fb1ef
--- /dev/null
+++ b/distributions/sambanova/compose.yaml
@@ -0,0 +1,16 @@
+services:
+  llamastack:
+    image: llamastack/distribution-sambanova
+    network_mode: "host"
+    volumes:
+      - ~/.llama:/root/.llama
+      - ./run.yaml:/root/llamastack-run-sambanova.yaml
+    ports:
+      - "5000:5000"
+    entrypoint: bash -c "python -m llama_stack.distribution.server.server --yaml_config /root/llamastack-run-sambanova.yaml"
+    deploy:
+      restart_policy:
+        condition: on-failure
+        delay: 3s
+        max_attempts: 5
+        window: 60s
diff --git a/distributions/sambanova/run.yaml b/distributions/sambanova/run.yaml
new file mode 100644
index 000000000..385282c67
--- /dev/null
+++ b/distributions/sambanova/run.yaml
@@ -0,0 +1 @@
+../../llama_stack/templates/sambanova/run.yaml
diff --git a/distributions/together/compose.yaml b/distributions/together/compose.yaml
index c7251d0a7..f66ee69f9 100644
--- a/distributions/together/compose.yaml
+++ b/distributions/together/compose.yaml
@@ -1,13 +1,11 @@
 services:
   llamastack:
     image: llamastack/distribution-together
-    network_mode: "host"
-    volumes:
-      - ~/.llama:/root/.llama
-      - ./run.yaml:/root/llamastack-run-together.yaml
     ports:
       - "8321:8321"
-    entrypoint: bash -c "python -m llama_stack.distribution.server.server --yaml_config /root/llamastack-run-together.yaml"
+    environment:
+      - TOGETHER_API_KEY=${TOGETHER_API_KEY}
+    entrypoint: bash -c "python -m llama_stack.distribution.server.server --template together"
     deploy:
       restart_policy:
         condition: on-failure
diff --git a/distributions/vllm-gpu/run.yaml b/distributions/vllm-gpu/run.yaml
index f42c942a3..a75a4c451 100644
--- a/distributions/vllm-gpu/run.yaml
+++ b/distributions/vllm-gpu/run.yaml
@@ -1,6 +1,6 @@
 version: '2'
 image_name: local
-docker_image: null
+container_image: null
 conda_env: local
 apis:
 - shields
diff --git a/docs/getting_started.ipynb b/docs/getting_started.ipynb
index 921869b33..0c0f7fa95 100644
--- a/docs/getting_started.ipynb
+++ b/docs/getting_started.ipynb
@@ -71,7 +71,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 42,
+      "execution_count": 1,
       "id": "J2kGed0R5PSf",
       "metadata": {
         "colab": {
@@ -79,7 +79,7 @@
         },
         "collapsed": true,
         "id": "J2kGed0R5PSf",
-        "outputId": "7d543c6f-623d-4911-b9a7-4ed24d5b82f2"
+        "outputId": "2478ea60-8d35-48a1-b011-f233831740c5"
       },
       "outputs": [
         {
@@ -89,65 +89,111 @@
             "Reading package lists... Done\n",
             "Building dependency tree... Done\n",
             "Reading state information... Done\n",
-            "bubblewrap is already the newest version (0.6.1-1ubuntu0.1).\n",
-            "0 upgraded, 0 newly installed, 0 to remove and 49 not upgraded.\n",
-            "Requirement already satisfied: llama-stack in /usr/local/lib/python3.10/dist-packages (0.0.61)\n",
-            "Requirement already satisfied: blobfile in /usr/local/lib/python3.10/dist-packages (from llama-stack) (3.0.0)\n",
-            "Requirement already satisfied: fire in /usr/local/lib/python3.10/dist-packages (from llama-stack) (0.7.0)\n",
-            "Requirement already satisfied: httpx in /usr/local/lib/python3.10/dist-packages (from llama-stack) (0.28.1)\n",
-            "Requirement already satisfied: huggingface-hub in /usr/local/lib/python3.10/dist-packages (from llama-stack) (0.26.5)\n",
-            "Requirement already satisfied: llama-models>=0.0.61 in /usr/local/lib/python3.10/dist-packages (from llama-stack) (0.0.61)\n",
-            "Requirement already satisfied: llama-stack-client>=0.0.61 in /usr/local/lib/python3.10/dist-packages (from llama-stack) (0.0.61)\n",
-            "Requirement already satisfied: prompt-toolkit in /usr/local/lib/python3.10/dist-packages (from llama-stack) (3.0.48)\n",
-            "Requirement already satisfied: python-dotenv in /usr/local/lib/python3.10/dist-packages (from llama-stack) (1.0.1)\n",
-            "Requirement already satisfied: pydantic>=2 in /usr/local/lib/python3.10/dist-packages (from llama-stack) (2.10.3)\n",
-            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from llama-stack) (2.32.3)\n",
-            "Requirement already satisfied: rich in /usr/local/lib/python3.10/dist-packages (from llama-stack) (13.9.4)\n",
-            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from llama-stack) (75.1.0)\n",
-            "Requirement already satisfied: termcolor in /usr/local/lib/python3.10/dist-packages (from llama-stack) (2.5.0)\n",
-            "Requirement already satisfied: PyYAML in /usr/local/lib/python3.10/dist-packages (from llama-models>=0.0.61->llama-stack) (6.0.2)\n",
-            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from llama-models>=0.0.61->llama-stack) (3.1.4)\n",
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-            "Requirement already satisfied: Pillow in /usr/local/lib/python3.10/dist-packages (from llama-models>=0.0.61->llama-stack) (10.4.0)\n",
-            "Requirement already satisfied: anyio<5,>=3.5.0 in /usr/local/lib/python3.10/dist-packages (from llama-stack-client>=0.0.61->llama-stack) (3.7.1)\n",
-            "Requirement already satisfied: click in /usr/local/lib/python3.10/dist-packages (from llama-stack-client>=0.0.61->llama-stack) (8.1.7)\n",
-            "Requirement already satisfied: distro<2,>=1.7.0 in /usr/local/lib/python3.10/dist-packages (from llama-stack-client>=0.0.61->llama-stack) (1.9.0)\n",
-            "Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from llama-stack-client>=0.0.61->llama-stack) (2.2.2)\n",
-            "Requirement already satisfied: pyaml in /usr/local/lib/python3.10/dist-packages (from llama-stack-client>=0.0.61->llama-stack) (24.12.1)\n",
-            "Requirement already satisfied: sniffio in /usr/local/lib/python3.10/dist-packages (from llama-stack-client>=0.0.61->llama-stack) (1.3.1)\n",
-            "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from llama-stack-client>=0.0.61->llama-stack) (4.66.6)\n",
-            "Requirement already satisfied: typing-extensions<5,>=4.7 in /usr/local/lib/python3.10/dist-packages (from llama-stack-client>=0.0.61->llama-stack) (4.12.2)\n",
-            "Requirement already satisfied: certifi in /usr/local/lib/python3.10/dist-packages (from httpx->llama-stack) (2024.8.30)\n",
-            "Requirement already satisfied: httpcore==1.* in /usr/local/lib/python3.10/dist-packages (from httpx->llama-stack) (1.0.7)\n",
-            "Requirement already satisfied: idna in /usr/local/lib/python3.10/dist-packages (from httpx->llama-stack) (3.10)\n",
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-            "Requirement already satisfied: pydantic-core==2.27.1 in /usr/local/lib/python3.10/dist-packages (from pydantic>=2->llama-stack) (2.27.1)\n",
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-            "Requirement already satisfied: urllib3<3,>=1.25.3 in /usr/local/lib/python3.10/dist-packages (from blobfile->llama-stack) (2.2.3)\n",
-            "Requirement already satisfied: lxml>=4.9 in /usr/local/lib/python3.10/dist-packages (from blobfile->llama-stack) (5.3.0)\n",
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-            "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub->llama-stack) (2024.9.0)\n",
-            "Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub->llama-stack) (24.2)\n",
-            "Requirement already satisfied: wcwidth in /usr/local/lib/python3.10/dist-packages (from prompt-toolkit->llama-stack) (0.2.13)\n",
-            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->llama-stack) (3.4.0)\n",
-            "Requirement already satisfied: markdown-it-py>=2.2.0 in /usr/local/lib/python3.10/dist-packages (from rich->llama-stack) (3.0.0)\n",
-            "Requirement already satisfied: pygments<3.0.0,>=2.13.0 in /usr/local/lib/python3.10/dist-packages (from rich->llama-stack) (2.18.0)\n",
-            "Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.5.0->llama-stack-client>=0.0.61->llama-stack) (1.2.2)\n",
-            "Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.10/dist-packages (from markdown-it-py>=2.2.0->rich->llama-stack) (0.1.2)\n",
-            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->llama-models>=0.0.61->llama-stack) (3.0.2)\n",
-            "Requirement already satisfied: numpy>=1.22.4 in /usr/local/lib/python3.10/dist-packages (from pandas->llama-stack-client>=0.0.61->llama-stack) (1.26.4)\n",
-            "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas->llama-stack-client>=0.0.61->llama-stack) (2.8.2)\n",
-            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->llama-stack-client>=0.0.61->llama-stack) (2024.2)\n",
-            "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.10/dist-packages (from pandas->llama-stack-client>=0.0.61->llama-stack) (2024.2)\n",
-            "Requirement already satisfied: regex>=2022.1.18 in /usr/local/lib/python3.10/dist-packages (from tiktoken->llama-models>=0.0.61->llama-stack) (2024.9.11)\n",
-            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.2->pandas->llama-stack-client>=0.0.61->llama-stack) (1.17.0)\n"
+            "The following NEW packages will be installed:\n",
+            "  bubblewrap\n",
+            "0 upgraded, 1 newly installed, 0 to remove and 49 not upgraded.\n",
+            "Need to get 46.3 kB of archives.\n",
+            "After this operation, 132 kB of additional disk space will be used.\n",
+            "Get:1 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 bubblewrap amd64 0.6.1-1ubuntu0.1 [46.3 kB]\n",
+            "Fetched 46.3 kB in 0s (122 kB/s)\n",
+            "Selecting previously unselected package bubblewrap.\n",
+            "(Reading database ... 124561 files and directories currently installed.)\n",
+            "Preparing to unpack .../bubblewrap_0.6.1-1ubuntu0.1_amd64.deb ...\n",
+            "Unpacking bubblewrap (0.6.1-1ubuntu0.1) ...\n",
+            "Setting up bubblewrap (0.6.1-1ubuntu0.1) ...\n",
+            "Processing triggers for man-db (2.10.2-1) ...\n",
+            "Looking in indexes: https://test.pypi.org/simple/, https://pypi.python.org/simple\n",
+            "Collecting llama-stack==0.1.0rc10\n",
+            "  Downloading https://test-files.pythonhosted.org/packages/68/22/4a170fbe01095df81e76c7bf8f35c716c1a0a5ec4503da6e78695fab351c/llama_stack-0.1.0rc10-py3-none-any.whl.metadata (15 kB)\n",
+            "Collecting blobfile (from llama-stack==0.1.0rc10)\n",
+            "  Downloading blobfile-3.0.0-py3-none-any.whl.metadata (15 kB)\n",
+            "Collecting fire (from llama-stack==0.1.0rc10)\n",
+            "  Downloading fire-0.7.0.tar.gz (87 kB)\n",
+            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m87.2/87.2 kB\u001b[0m \u001b[31m4.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "Requirement already satisfied: httpx in /usr/local/lib/python3.11/dist-packages (from llama-stack==0.1.0rc10) (0.28.1)\n",
+            "Requirement already satisfied: huggingface-hub in /usr/local/lib/python3.11/dist-packages (from llama-stack==0.1.0rc10) (0.27.1)\n",
+            "Collecting llama-models==0.1.0rc10 (from llama-stack==0.1.0rc10)\n",
+            "  Downloading https://test-files.pythonhosted.org/packages/45/2b/6a6947d5915054b9980f82606942f1b79960a27168299254ca12e5b5795b/llama_models-0.1.0rc10-py3-none-any.whl.metadata (8.5 kB)\n",
+            "Collecting llama-stack-client==0.1.0rc10 (from llama-stack==0.1.0rc10)\n",
+            "  Downloading https://test-files.pythonhosted.org/packages/d6/85/a4fd621c4ae4db7339ab098b37bf4b4ad3cc12440e75ef10ec524e28ef7d/llama_stack_client-0.1.0rc10-py3-none-any.whl.metadata (15 kB)\n",
+            "Requirement already satisfied: prompt-toolkit in /usr/local/lib/python3.11/dist-packages (from llama-stack==0.1.0rc10) (3.0.48)\n",
+            "Collecting python-dotenv (from llama-stack==0.1.0rc10)\n",
+            "  Downloading python_dotenv-1.0.1-py3-none-any.whl.metadata (23 kB)\n",
+            "Requirement already satisfied: pydantic>=2 in /usr/local/lib/python3.11/dist-packages (from llama-stack==0.1.0rc10) (2.10.5)\n",
+            "Requirement already satisfied: requests in /usr/local/lib/python3.11/dist-packages (from llama-stack==0.1.0rc10) (2.32.3)\n",
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+            "Requirement already satisfied: setuptools in /usr/local/lib/python3.11/dist-packages (from llama-stack==0.1.0rc10) (75.1.0)\n",
+            "Requirement already satisfied: termcolor in /usr/local/lib/python3.11/dist-packages (from llama-stack==0.1.0rc10) (2.5.0)\n",
+            "Requirement already satisfied: PyYAML in /usr/local/lib/python3.11/dist-packages (from llama-models==0.1.0rc10->llama-stack==0.1.0rc10) (6.0.2)\n",
+            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.11/dist-packages (from llama-models==0.1.0rc10->llama-stack==0.1.0rc10) (3.1.5)\n",
+            "Collecting tiktoken (from llama-models==0.1.0rc10->llama-stack==0.1.0rc10)\n",
+            "  Downloading tiktoken-0.8.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (6.6 kB)\n",
+            "Requirement already satisfied: Pillow in /usr/local/lib/python3.11/dist-packages (from llama-models==0.1.0rc10->llama-stack==0.1.0rc10) (11.1.0)\n",
+            "Requirement already satisfied: anyio<5,>=3.5.0 in /usr/local/lib/python3.11/dist-packages (from llama-stack-client==0.1.0rc10->llama-stack==0.1.0rc10) (3.7.1)\n",
+            "Requirement already satisfied: click in /usr/local/lib/python3.11/dist-packages (from llama-stack-client==0.1.0rc10->llama-stack==0.1.0rc10) (8.1.8)\n",
+            "Requirement already satisfied: distro<2,>=1.7.0 in /usr/local/lib/python3.11/dist-packages (from llama-stack-client==0.1.0rc10->llama-stack==0.1.0rc10) (1.9.0)\n",
+            "Requirement already satisfied: pandas in /usr/local/lib/python3.11/dist-packages (from llama-stack-client==0.1.0rc10->llama-stack==0.1.0rc10) (2.2.2)\n",
+            "Collecting pyaml (from llama-stack-client==0.1.0rc10->llama-stack==0.1.0rc10)\n",
+            "  Downloading pyaml-25.1.0-py3-none-any.whl.metadata (12 kB)\n",
+            "Requirement already satisfied: sniffio in /usr/local/lib/python3.11/dist-packages (from llama-stack-client==0.1.0rc10->llama-stack==0.1.0rc10) (1.3.1)\n",
+            "Requirement already satisfied: tqdm in /usr/local/lib/python3.11/dist-packages (from llama-stack-client==0.1.0rc10->llama-stack==0.1.0rc10) (4.67.1)\n",
+            "Requirement already satisfied: typing-extensions<5,>=4.7 in /usr/local/lib/python3.11/dist-packages (from llama-stack-client==0.1.0rc10->llama-stack==0.1.0rc10) (4.12.2)\n",
+            "Requirement already satisfied: certifi in /usr/local/lib/python3.11/dist-packages (from httpx->llama-stack==0.1.0rc10) (2024.12.14)\n",
+            "Requirement already satisfied: httpcore==1.* in /usr/local/lib/python3.11/dist-packages (from httpx->llama-stack==0.1.0rc10) (1.0.7)\n",
+            "Requirement already satisfied: idna in /usr/local/lib/python3.11/dist-packages (from httpx->llama-stack==0.1.0rc10) (3.10)\n",
+            "Requirement already satisfied: h11<0.15,>=0.13 in /usr/local/lib/python3.11/dist-packages (from httpcore==1.*->httpx->llama-stack==0.1.0rc10) (0.14.0)\n",
+            "Requirement already satisfied: annotated-types>=0.6.0 in /usr/local/lib/python3.11/dist-packages (from pydantic>=2->llama-stack==0.1.0rc10) (0.7.0)\n",
+            "Requirement already satisfied: pydantic-core==2.27.2 in /usr/local/lib/python3.11/dist-packages (from pydantic>=2->llama-stack==0.1.0rc10) (2.27.2)\n",
+            "Collecting pycryptodomex>=3.8 (from blobfile->llama-stack==0.1.0rc10)\n",
+            "  Downloading pycryptodomex-3.21.0-cp36-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (3.4 kB)\n",
+            "Requirement already satisfied: urllib3<3,>=1.25.3 in /usr/local/lib/python3.11/dist-packages (from blobfile->llama-stack==0.1.0rc10) (2.3.0)\n",
+            "Requirement already satisfied: lxml>=4.9 in /usr/local/lib/python3.11/dist-packages (from blobfile->llama-stack==0.1.0rc10) (5.3.0)\n",
+            "Requirement already satisfied: filelock>=3.0 in /usr/local/lib/python3.11/dist-packages (from blobfile->llama-stack==0.1.0rc10) (3.16.1)\n",
+            "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.11/dist-packages (from huggingface-hub->llama-stack==0.1.0rc10) (2024.10.0)\n",
+            "Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.11/dist-packages (from huggingface-hub->llama-stack==0.1.0rc10) (24.2)\n",
+            "Requirement already satisfied: wcwidth in /usr/local/lib/python3.11/dist-packages (from prompt-toolkit->llama-stack==0.1.0rc10) (0.2.13)\n",
+            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.11/dist-packages (from requests->llama-stack==0.1.0rc10) (3.4.1)\n",
+            "Requirement already satisfied: markdown-it-py>=2.2.0 in /usr/local/lib/python3.11/dist-packages (from rich->llama-stack==0.1.0rc10) (3.0.0)\n",
+            "Requirement already satisfied: pygments<3.0.0,>=2.13.0 in /usr/local/lib/python3.11/dist-packages (from rich->llama-stack==0.1.0rc10) (2.18.0)\n",
+            "Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.11/dist-packages (from markdown-it-py>=2.2.0->rich->llama-stack==0.1.0rc10) (0.1.2)\n",
+            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.11/dist-packages (from jinja2->llama-models==0.1.0rc10->llama-stack==0.1.0rc10) (3.0.2)\n",
+            "Requirement already satisfied: numpy>=1.23.2 in /usr/local/lib/python3.11/dist-packages (from pandas->llama-stack-client==0.1.0rc10->llama-stack==0.1.0rc10) (1.26.4)\n",
+            "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.11/dist-packages (from pandas->llama-stack-client==0.1.0rc10->llama-stack==0.1.0rc10) (2.8.2)\n",
+            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.11/dist-packages (from pandas->llama-stack-client==0.1.0rc10->llama-stack==0.1.0rc10) (2024.2)\n",
+            "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.11/dist-packages (from pandas->llama-stack-client==0.1.0rc10->llama-stack==0.1.0rc10) (2024.2)\n",
+            "Requirement already satisfied: regex>=2022.1.18 in /usr/local/lib/python3.11/dist-packages (from tiktoken->llama-models==0.1.0rc10->llama-stack==0.1.0rc10) (2024.11.6)\n",
+            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.11/dist-packages (from python-dateutil>=2.8.2->pandas->llama-stack-client==0.1.0rc10->llama-stack==0.1.0rc10) (1.17.0)\n",
+            "Downloading https://test-files.pythonhosted.org/packages/68/22/4a170fbe01095df81e76c7bf8f35c716c1a0a5ec4503da6e78695fab351c/llama_stack-0.1.0rc10-py3-none-any.whl (532 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m532.7/532.7 kB\u001b[0m \u001b[31m14.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading https://test-files.pythonhosted.org/packages/45/2b/6a6947d5915054b9980f82606942f1b79960a27168299254ca12e5b5795b/llama_models-0.1.0rc10-py3-none-any.whl (1.6 MB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.6/1.6 MB\u001b[0m \u001b[31m20.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading https://test-files.pythonhosted.org/packages/d6/85/a4fd621c4ae4db7339ab098b37bf4b4ad3cc12440e75ef10ec524e28ef7d/llama_stack_client-0.1.0rc10-py3-none-any.whl (328 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m328.5/328.5 kB\u001b[0m \u001b[31m29.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading blobfile-3.0.0-py3-none-any.whl (75 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m75.4/75.4 kB\u001b[0m \u001b[31m7.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading python_dotenv-1.0.1-py3-none-any.whl (19 kB)\n",
+            "Downloading pycryptodomex-3.21.0-cp36-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.3 MB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.3/2.3 MB\u001b[0m \u001b[31m57.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading pyaml-25.1.0-py3-none-any.whl (26 kB)\n",
+            "Downloading tiktoken-0.8.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.2 MB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.2/1.2 MB\u001b[0m \u001b[31m64.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hBuilding wheels for collected packages: fire\n",
+            "  Building wheel for fire (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
+            "  Created wheel for fire: filename=fire-0.7.0-py3-none-any.whl size=114249 sha256=3a37285ecae37a5fb69bbad717aabdb8c13f0da7906668b7c123475eefa41c3b\n",
+            "  Stored in directory: /root/.cache/pip/wheels/46/54/24/1624fd5b8674eb1188623f7e8e17cdf7c0f6c24b609dfb8a89\n",
+            "Successfully built fire\n",
+            "Installing collected packages: python-dotenv, pycryptodomex, pyaml, fire, tiktoken, blobfile, llama-stack-client, llama-models, llama-stack\n",
+            "Successfully installed blobfile-3.0.0 fire-0.7.0 llama-models-0.1.0rc10 llama-stack-0.1.0rc10 llama-stack-client-0.1.0rc10 pyaml-25.1.0 pycryptodomex-3.21.0 python-dotenv-1.0.1 tiktoken-0.8.0\n"
           ]
         }
       ],
       "source": [
+        "# NBVAL_SKIP\n",
+        "\n",
         "!apt-get install -y bubblewrap\n",
-        "!pip install -U llama-stack"
+        "# install a branch of llama stack\n",
+        "!pip install llama-stack"
       ]
     },
     {
@@ -172,7 +218,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 43,
+      "execution_count": 2,
       "id": "HaepEZXCDgif",
       "metadata": {
         "colab": {
@@ -180,198 +226,333 @@
         },
         "collapsed": true,
         "id": "HaepEZXCDgif",
-        "outputId": "9c268d26-7444-4741-f14d-3911eea8e4eb"
+        "outputId": "9314f698-593d-4c1a-ea15-15c735dc1023"
       },
       "outputs": [
         {
           "name": "stdout",
           "output_type": "stream",
           "text": [
-            "Requirement already satisfied: llama-stack in /usr/local/lib/python3.10/dist-packages (0.0.61)\r\n",
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-            "Requirement already satisfied: fire in /usr/local/lib/python3.10/dist-packages (from llama-stack) (0.7.0)\r\n",
-            "Requirement already satisfied: httpx in /usr/local/lib/python3.10/dist-packages (from llama-stack) (0.28.1)\r\n",
-            "Requirement already satisfied: huggingface-hub in /usr/local/lib/python3.10/dist-packages (from llama-stack) (0.26.5)\r\n",
-            "Requirement already satisfied: llama-models>=0.0.61 in /usr/local/lib/python3.10/dist-packages (from llama-stack) (0.0.61)\r\n",
-            "Requirement already satisfied: llama-stack-client>=0.0.61 in /usr/local/lib/python3.10/dist-packages (from llama-stack) (0.0.61)\r\n",
-            "Requirement already satisfied: prompt-toolkit in /usr/local/lib/python3.10/dist-packages (from llama-stack) (3.0.48)\r\n",
-            "Requirement already satisfied: python-dotenv in /usr/local/lib/python3.10/dist-packages (from llama-stack) (1.0.1)\r\n",
-            "Requirement already satisfied: pydantic>=2 in /usr/local/lib/python3.10/dist-packages (from llama-stack) (2.10.3)\r\n",
-            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from llama-stack) (2.32.3)\r\n",
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-            "Requirement already satisfied: termcolor in /usr/local/lib/python3.10/dist-packages (from llama-stack) (2.5.0)\r\n",
-            "Requirement already satisfied: PyYAML in /usr/local/lib/python3.10/dist-packages (from llama-models>=0.0.61->llama-stack) (6.0.2)\r\n",
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-            "Requirement already satisfied: tiktoken in /usr/local/lib/python3.10/dist-packages (from llama-models>=0.0.61->llama-stack) (0.8.0)\r\n",
-            "Requirement already satisfied: Pillow in /usr/local/lib/python3.10/dist-packages (from llama-models>=0.0.61->llama-stack) (10.4.0)\r\n",
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-            "Requirement already satisfied: pyaml in /usr/local/lib/python3.10/dist-packages (from llama-stack-client>=0.0.61->llama-stack) (24.12.1)\r\n",
-            "Requirement already satisfied: sniffio in /usr/local/lib/python3.10/dist-packages (from llama-stack-client>=0.0.61->llama-stack) (1.3.1)\r\n",
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+            "Requirement already satisfied: llama-stack in /usr/local/lib/python3.11/dist-packages (0.1.0rc10)\r\n",
+            "Requirement already satisfied: blobfile in /usr/local/lib/python3.11/dist-packages (from llama-stack) (3.0.0)\r\n",
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+            "Requirement already satisfied: llama-stack-client==0.1.0rc10 in /usr/local/lib/python3.11/dist-packages (from llama-stack) (0.1.0rc10)\r\n",
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+            "Requirement already satisfied: python-dotenv in /usr/local/lib/python3.11/dist-packages (from llama-stack) (1.0.1)\r\n",
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+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m94.8/94.8 kB\u001b[0m \u001b[31m9.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading uvicorn-0.34.0-py3-none-any.whl (62 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m62.3/62.3 kB\u001b[0m \u001b[31m5.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading anyio-4.8.0-py3-none-any.whl (96 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m96.0/96.0 kB\u001b[0m \u001b[31m9.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading dill-0.3.8-py3-none-any.whl (116 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m116.3/116.3 kB\u001b[0m \u001b[31m12.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading fsspec-2024.9.0-py3-none-any.whl (179 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m179.3/179.3 kB\u001b[0m \u001b[31m17.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading httpx_sse-0.4.0-py3-none-any.whl (7.8 kB)\n",
+            "Downloading multiprocess-0.70.16-py311-none-any.whl (143 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m143.5/143.5 kB\u001b[0m \u001b[31m14.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading opentelemetry_exporter_otlp_proto_grpc-1.29.0-py3-none-any.whl (18 kB)\n",
+            "Downloading overrides-7.7.0-py3-none-any.whl (17 kB)\n",
+            "Downloading posthog-3.8.4-py2.py3-none-any.whl (69 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m69.8/69.8 kB\u001b[0m \u001b[31m5.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading pydantic_settings-2.7.1-py3-none-any.whl (29 kB)\n",
+            "Downloading sse_starlette-2.2.1-py3-none-any.whl (10 kB)\n",
+            "Downloading starlette-0.41.3-py3-none-any.whl (73 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m73.2/73.2 kB\u001b[0m \u001b[31m7.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading chevron-0.14.0-py3-none-any.whl (11 kB)\n",
+            "Downloading levenshtein-0.26.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (162 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m162.7/162.7 kB\u001b[0m \u001b[31m17.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading xxhash-3.5.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (194 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m194.8/194.8 kB\u001b[0m \u001b[31m21.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading backoff-2.2.1-py3-none-any.whl (15 kB)\n",
+            "Downloading monotonic-1.6-py2.py3-none-any.whl (8.2 kB)\n",
+            "Downloading protobuf-5.29.3-cp38-abi3-manylinux2014_x86_64.whl (319 kB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m319.7/319.7 kB\u001b[0m \u001b[31m28.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hDownloading rapidfuzz-3.11.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.1 MB)\n",
+            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.1/3.1 MB\u001b[0m \u001b[31m84.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hInstalling collected packages: monotonic, chevron, xxhash, uvicorn, redis, rapidfuzz, pypdf, psycopg2-binary, protobuf, pillow, overrides, httpx-sse, fsspec, faiss-cpu, dill, braintrust_core, backoff, anyio, aiosqlite, starlette, posthog, opentelemetry-proto, multiprocess, levenshtein, sse-starlette, pydantic-settings, opentelemetry-exporter-otlp-proto-common, fastapi, together, mcp, datasets, autoevals, opentelemetry-exporter-otlp-proto-http, opentelemetry-exporter-otlp-proto-grpc, chromadb-client\n",
+            "  Attempting uninstall: protobuf\n",
+            "    Found existing installation: protobuf 4.25.5\n",
+            "    Uninstalling protobuf-4.25.5:\n",
+            "      Successfully uninstalled protobuf-4.25.5\n",
+            "  Attempting uninstall: pillow\n",
+            "    Found existing installation: pillow 11.1.0\n",
+            "    Uninstalling pillow-11.1.0:\n",
+            "      Successfully uninstalled pillow-11.1.0\n",
+            "  Attempting uninstall: fsspec\n",
+            "    Found existing installation: fsspec 2024.10.0\n",
+            "    Uninstalling fsspec-2024.10.0:\n",
+            "      Successfully uninstalled fsspec-2024.10.0\n",
+            "  Attempting uninstall: anyio\n",
+            "    Found existing installation: anyio 3.7.1\n",
+            "    Uninstalling anyio-3.7.1:\n",
+            "      Successfully uninstalled anyio-3.7.1\n",
+            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
+            "jupyter-server 1.24.0 requires anyio<4,>=3.1.0, but you have anyio 4.8.0 which is incompatible.\n",
+            "gcsfs 2024.10.0 requires fsspec==2024.10.0, but you have fsspec 2024.9.0 which is incompatible.\n",
+            "tensorflow 2.17.1 requires protobuf!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.20.3, but you have protobuf 5.29.3 which is incompatible.\u001b[0m\u001b[31m\n",
+            "\u001b[0mSuccessfully installed aiosqlite-0.20.0 anyio-4.8.0 autoevals-0.0.117 backoff-2.2.1 braintrust_core-0.0.58 chevron-0.14.0 chromadb-client-0.6.3 datasets-3.2.0 dill-0.3.8 faiss-cpu-1.9.0.post1 fastapi-0.115.6 fsspec-2024.9.0 httpx-sse-0.4.0 levenshtein-0.26.1 mcp-1.2.0 monotonic-1.6 multiprocess-0.70.16 opentelemetry-exporter-otlp-proto-common-1.29.0 opentelemetry-exporter-otlp-proto-grpc-1.29.0 opentelemetry-exporter-otlp-proto-http-1.29.0 opentelemetry-proto-1.29.0 overrides-7.7.0 pillow-10.4.0 posthog-3.8.4 protobuf-5.29.3 psycopg2-binary-2.9.10 pydantic-settings-2.7.1 pypdf-5.1.0 rapidfuzz-3.11.0 redis-5.2.1 sse-starlette-2.2.1 starlette-0.41.3 together-1.3.11 uvicorn-0.34.0 xxhash-3.5.0\n",
             "torch --index-url https://download.pytorch.org/whl/cpu\n",
             "Looking in indexes: https://download.pytorch.org/whl/cpu\n",
-            "Requirement already satisfied: torch in /usr/local/lib/python3.10/dist-packages (2.5.1+cu121)\n",
-            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch) (3.16.1)\n",
-            "Requirement already satisfied: typing-extensions>=4.8.0 in /usr/local/lib/python3.10/dist-packages (from torch) (4.12.2)\n",
-            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch) (3.4.2)\n",
-            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch) (3.1.4)\n",
-            "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from torch) (2024.9.0)\n",
-            "Requirement already satisfied: sympy==1.13.1 in /usr/local/lib/python3.10/dist-packages (from torch) (1.13.1)\n",
-            "Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.10/dist-packages (from sympy==1.13.1->torch) (1.3.0)\n",
-            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch) (3.0.2)\n",
+            "Requirement already satisfied: torch in /usr/local/lib/python3.11/dist-packages (2.5.1+cu121)\n",
+            "Requirement already satisfied: filelock in /usr/local/lib/python3.11/dist-packages (from torch) (3.16.1)\n",
+            "Requirement already satisfied: typing-extensions>=4.8.0 in /usr/local/lib/python3.11/dist-packages (from torch) (4.12.2)\n",
+            "Requirement already satisfied: networkx in /usr/local/lib/python3.11/dist-packages (from torch) (3.4.2)\n",
+            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.11/dist-packages (from torch) (3.1.5)\n",
+            "Requirement already satisfied: fsspec in /usr/local/lib/python3.11/dist-packages (from torch) (2024.9.0)\n",
+            "Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.1.105 in /usr/local/lib/python3.11/dist-packages (from torch) (12.1.105)\n",
+            "Requirement already satisfied: nvidia-cuda-runtime-cu12==12.1.105 in /usr/local/lib/python3.11/dist-packages (from torch) (12.1.105)\n",
+            "Requirement already satisfied: nvidia-cuda-cupti-cu12==12.1.105 in /usr/local/lib/python3.11/dist-packages (from torch) (12.1.105)\n",
+            "Requirement already satisfied: nvidia-cudnn-cu12==9.1.0.70 in /usr/local/lib/python3.11/dist-packages (from torch) (9.1.0.70)\n",
+            "Requirement already satisfied: nvidia-cublas-cu12==12.1.3.1 in /usr/local/lib/python3.11/dist-packages (from torch) (12.1.3.1)\n",
+            "Requirement already satisfied: nvidia-cufft-cu12==11.0.2.54 in /usr/local/lib/python3.11/dist-packages (from torch) (11.0.2.54)\n",
+            "Requirement already satisfied: nvidia-curand-cu12==10.3.2.106 in /usr/local/lib/python3.11/dist-packages (from torch) (10.3.2.106)\n",
+            "Requirement already satisfied: nvidia-cusolver-cu12==11.4.5.107 in /usr/local/lib/python3.11/dist-packages (from torch) (11.4.5.107)\n",
+            "Requirement already satisfied: nvidia-cusparse-cu12==12.1.0.106 in /usr/local/lib/python3.11/dist-packages (from torch) (12.1.0.106)\n",
+            "Requirement already satisfied: nvidia-nccl-cu12==2.21.5 in /usr/local/lib/python3.11/dist-packages (from torch) (2.21.5)\n",
+            "Requirement already satisfied: nvidia-nvtx-cu12==12.1.105 in /usr/local/lib/python3.11/dist-packages (from torch) (12.1.105)\n",
+            "Requirement already satisfied: triton==3.1.0 in /usr/local/lib/python3.11/dist-packages (from torch) (3.1.0)\n",
+            "Requirement already satisfied: sympy==1.13.1 in /usr/local/lib/python3.11/dist-packages (from torch) (1.13.1)\n",
+            "Requirement already satisfied: nvidia-nvjitlink-cu12 in /usr/local/lib/python3.11/dist-packages (from nvidia-cusolver-cu12==11.4.5.107->torch) (12.6.85)\n",
+            "Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.11/dist-packages (from sympy==1.13.1->torch) (1.3.0)\n",
+            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.11/dist-packages (from jinja2->torch) (3.0.2)\n",
+            "sentence-transformers --no-deps\n",
+            "Requirement already satisfied: sentence-transformers in /usr/local/lib/python3.11/dist-packages (3.3.1)\n",
             "\u001b[32mBuild Successful!\u001b[0m\n"
           ]
         }
       ],
       "source": [
+        "# NBVAL_SKIP\n",
+        "\n",
         "# This will build all the dependencies you will need\n",
         "!llama stack build --template together --image-type venv"
       ]
@@ -390,68 +571,155 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 44,
+      "execution_count": 2,
       "id": "E1UFuJC570Tk",
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
-          "height": 1000
+          "height": 1000,
+          "referenced_widgets": [
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+            "2e713bcc372e48b2a006558db4d1df68",
+            "1a277abd5ea44253bc6894bef258b52b",
+            "b3eedd82e7da4ce8b3ded70e49a2afd0",
+            "6f5c18cb8002471f8b3764effee37324",
+            "3bebac362b344e8d9103c5011613f1ea",
+            "670905a55b19458da69f83c8bcd511d1",
+            "ff54451a48394faaaa9d8cdb690d0718",
+            "36b5bc19b2d0407f8ab28ff0da2ce12d",
+            "879e48d9a9e04183903d94ffe98313d2",
+            "abce503d70594c2ca9afdc47847c125b",
+            "028e291ee53947bbbbc4bfb68c695f5f",
+            "a530662719374c95a9bef12e59e28c85",
+            "bffc0f4b12f141398535990709fd4f2c",
+            "04804c74e1dd43449d5f758cf5d0ba5e",
+            "95a506c3007c4525b01ee4e1600d671b",
+            "a0d6b0caeb2340fe96c8f5569e3d3ae4",
+            "30798f87a8b848d783fdacd71af5dc04",
+            "07ce54c75e76488ba4019a20b3707061",
+            "f023175de68445f98a6b01bb40ccdc6d",
+            "7389b79a0ff44cd68c7866995d728023",
+            "8e2b70ffe4eb4974bd6393fcc1292267",
+            "13eee164dc534424acb9dc9ee37a9465",
+            "722a7fe16af3422585a20c651345cfa4",
+            "f5596c1c9c4d42f3bc171961f9582eff",
+            "85d66e615b5742e78657b1e60c75fc72",
+            "731c02dc5dd446c3b22765575148e256",
+            "254ce460ce244c99a5afe39d5d51f6b7",
+            "4cf1dc345ace4da59f978f661487f975",
+            "8f30fca71bf24e5ca26e17c2321f893c",
+            "dd85d37dd1d14c7ea4592f8e11b2d2c8",
+            "3cb06377e4454f009d6b2aa7aa6ff0a9",
+            "4502477db4d948e693012364c2dcb370",
+            "52fe404ec9c14db2a7279b4c154eef3d"
+          ]
         },
         "collapsed": true,
         "id": "E1UFuJC570Tk",
-        "outputId": "bac7c9ec-ad49-4040-af43-8869f0afe5ac"
+        "outputId": "aebb69d4-c167-4de5-eb8a-dd19dd538f63"
       },
       "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Not in Google Colab environment\n",
+            "\u001b[33mWarning: `bwrap` is not available. Code interpreter tool will not work correctly.\u001b[0m\n"
+          ]
+        },
         {
           "name": "stderr",
           "output_type": "stream",
           "text": [
-            "INFO:llama_stack.distribution.resolver:Resolved 24 providers\n",
-            "INFO:llama_stack.distribution.resolver: inner-inference => together\n",
-            "INFO:llama_stack.distribution.resolver: inner-memory => faiss\n",
-            "INFO:llama_stack.distribution.resolver: models => __routing_table__\n",
-            "INFO:llama_stack.distribution.resolver: inference => __autorouted__\n",
-            "INFO:llama_stack.distribution.resolver: inner-safety => llama-guard\n",
-            "INFO:llama_stack.distribution.resolver: shields => __routing_table__\n",
-            "INFO:llama_stack.distribution.resolver: safety => __autorouted__\n",
-            "INFO:llama_stack.distribution.resolver: memory_banks => __routing_table__\n",
-            "INFO:llama_stack.distribution.resolver: memory => __autorouted__\n",
-            "INFO:llama_stack.distribution.resolver: agents => meta-reference\n",
-            "INFO:llama_stack.distribution.resolver: inner-datasetio => huggingface\n",
-            "INFO:llama_stack.distribution.resolver: inner-datasetio => localfs\n",
-            "INFO:llama_stack.distribution.resolver: datasets => __routing_table__\n",
-            "INFO:llama_stack.distribution.resolver: datasetio => __autorouted__\n",
-            "INFO:llama_stack.distribution.resolver: telemetry => meta-reference\n",
-            "INFO:llama_stack.distribution.resolver: inner-scoring => basic\n",
-            "INFO:llama_stack.distribution.resolver: inner-scoring => llm-as-judge\n",
-            "INFO:llama_stack.distribution.resolver: inner-scoring => braintrust\n",
-            "INFO:llama_stack.distribution.resolver: scoring_functions => __routing_table__\n",
-            "INFO:llama_stack.distribution.resolver: scoring => __autorouted__\n",
-            "INFO:llama_stack.distribution.resolver: inner-eval => meta-reference\n",
-            "INFO:llama_stack.distribution.resolver: eval_tasks => __routing_table__\n",
-            "INFO:llama_stack.distribution.resolver: eval => __autorouted__\n",
-            "INFO:llama_stack.distribution.resolver: inspect => __builtin__\n",
-            "INFO:llama_stack.distribution.resolver:\n",
-            "WARNING:opentelemetry.trace:Overriding of current TracerProvider is not allowed\n",
-            "INFO:llama_stack.distribution.stack:Models: meta-llama/Llama-3.1-405B-Instruct-FP8 served by together\n",
-            "INFO:llama_stack.distribution.stack:Models: meta-llama/Llama-3.1-70B-Instruct served by together\n",
-            "INFO:llama_stack.distribution.stack:Models: meta-llama/Llama-3.1-8B-Instruct served by together\n",
-            "INFO:llama_stack.distribution.stack:Models: meta-llama/Llama-3.2-11B-Vision-Instruct served by together\n",
-            "INFO:llama_stack.distribution.stack:Models: meta-llama/Llama-3.2-3B-Instruct served by together\n",
-            "INFO:llama_stack.distribution.stack:Models: meta-llama/Llama-3.2-90B-Vision-Instruct served by together\n",
-            "INFO:llama_stack.distribution.stack:Models: meta-llama/Llama-Guard-3-11B-Vision served by together\n",
-            "INFO:llama_stack.distribution.stack:Models: meta-llama/Llama-Guard-3-8B served by together\n",
-            "INFO:llama_stack.distribution.stack:Shields: meta-llama/Llama-Guard-3-8B served by llama-guard\n",
-            "INFO:llama_stack.distribution.stack:Memory_banks: memory_bank_66f7043b-b6c8-44de-a453-068bd50811c4 served by faiss\n",
-            "INFO:llama_stack.distribution.stack:Memory_banks: memory_bank_edf0d763-95bc-40d3-93a7-95b517162cfb served by faiss\n",
-            "INFO:llama_stack.distribution.stack:Scoring_fns: basic::equality served by basic\n",
-            "INFO:llama_stack.distribution.stack:Scoring_fns: basic::regex_parser_multiple_choice_answer served by basic\n",
-            "INFO:llama_stack.distribution.stack:Scoring_fns: basic::subset_of served by basic\n",
-            "INFO:llama_stack.distribution.stack:Scoring_fns: braintrust::answer-correctness served by braintrust\n",
-            "INFO:llama_stack.distribution.stack:Scoring_fns: braintrust::factuality served by braintrust\n",
-            "INFO:llama_stack.distribution.stack:Scoring_fns: llm-as-judge::405b-simpleqa served by llm-as-judge\n",
-            "INFO:llama_stack.distribution.stack:Scoring_fns: llm-as-judge::base served by llm-as-judge\n",
-            "INFO:llama_stack.distribution.stack:\n"
+            "/Users/ashwin/homebrew/Caskroom/miniconda/base/envs/toolchain/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+            "  from .autonotebook import tqdm as notebook_tqdm\n"
           ]
         },
         {
@@ -475,58 +743,86 @@
               "- datasetio\n",
               "- eval\n",
               "- inference\n",
-              "- memory\n",
               "- safety\n",
               "- scoring\n",
               "- telemetry\n",
-              "conda_env: together\n",
+              "- tool_runtime\n",
+              "- vector_io\n",
+              "container_image: null\n",
               "datasets: <span style=\"font-weight: bold\">[]</span>\n",
-              "docker_image: null\n",
               "eval_tasks: <span style=\"font-weight: bold\">[]</span>\n",
               "image_name: together\n",
-              "memory_banks: <span style=\"font-weight: bold\">[]</span>\n",
               "metadata_store:\n",
-              "  db_path: <span style=\"color: #800080; text-decoration-color: #800080\">/root/.llama/distributions/together/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">registry.db</span>\n",
+              "  db_path: <span style=\"color: #800080; text-decoration-color: #800080\">/Users/ashwin/.llama/distributions/together/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">registry.db</span>\n",
               "  namespace: null\n",
               "  type: sqlite\n",
               "models:\n",
               "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
               "  model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-8B-Instruct\n",
-              "  provider_id: null\n",
+              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
+              "  - llm\n",
+              "  provider_id: together\n",
               "  provider_model_id: meta-llama/Meta-Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-8B-Instruct-Turbo\n",
               "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
               "  model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-70B-Instruct\n",
-              "  provider_id: null\n",
+              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
+              "  - llm\n",
+              "  provider_id: together\n",
               "  provider_model_id: meta-llama/Meta-Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-70B-Instruct-Turbo\n",
               "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
               "  model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-405B-Instruct-FP8\n",
-              "  provider_id: null\n",
+              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
+              "  - llm\n",
+              "  provider_id: together\n",
               "  provider_model_id: meta-llama/Meta-Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-405B-Instruct-Turbo\n",
               "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
               "  model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-3B-Instruct\n",
-              "  provider_id: null\n",
+              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
+              "  - llm\n",
+              "  provider_id: together\n",
               "  provider_model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-3B-Instruct-Turbo\n",
               "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
               "  model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-11B-Vision-Instruct\n",
-              "  provider_id: null\n",
+              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
+              "  - llm\n",
+              "  provider_id: together\n",
               "  provider_model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-11B-Vision-Instruct-Turbo\n",
               "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
               "  model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-90B-Vision-Instruct\n",
-              "  provider_id: null\n",
+              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
+              "  - llm\n",
+              "  provider_id: together\n",
               "  provider_model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-90B-Vision-Instruct-Turbo\n",
               "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
+              "  model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.3</span>-70B-Instruct\n",
+              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
+              "  - llm\n",
+              "  provider_id: together\n",
+              "  provider_model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.3</span>-70B-Instruct-Turbo\n",
+              "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
               "  model_id: meta-llama/Llama-Guard-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>-8B\n",
-              "  provider_id: null\n",
+              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
+              "  - llm\n",
+              "  provider_id: together\n",
               "  provider_model_id: meta-llama/Meta-Llama-Guard-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>-8B\n",
               "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
               "  model_id: meta-llama/Llama-Guard-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>-11B-Vision\n",
-              "  provider_id: null\n",
+              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
+              "  - llm\n",
+              "  provider_id: together\n",
               "  provider_model_id: meta-llama/Llama-Guard-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>-11B-Vision-Turbo\n",
+              "- metadata:\n",
+              "    embedding_dimension: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">384</span>\n",
+              "  model_id: all-MiniLM-L6-v2\n",
+              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
+              "  - embedding\n",
+              "  provider_id: sentence-transformers\n",
+              "  provider_model_id: null\n",
               "providers:\n",
               "  agents:\n",
               "  - config:\n",
               "      persistence_store:\n",
-              "        db_path: <span style=\"color: #800080; text-decoration-color: #800080\">/root/.llama/distributions/together/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">agents_store.db</span>\n",
+              "        db_path: <span style=\"color: #800080; text-decoration-color: #800080\">/Users/ashwin/.llama/distributions/together/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">agents_store.db</span>\n",
               "        namespace: null\n",
               "        type: sqlite\n",
               "    provider_id: meta-reference\n",
@@ -544,18 +840,13 @@
               "    provider_type: inline::meta-reference\n",
               "  inference:\n",
               "  - config:\n",
-              "      api_key: 4985b03e627419b2964d34b8519ac6c4319f094d1ffb4f45514b4eb87e5427a2\n",
+              "      api_key: <span style=\"color: #008000; text-decoration-color: #008000\">'********'</span>\n",
               "      url: <span style=\"color: #0000ff; text-decoration-color: #0000ff; text-decoration: underline\">https://api.together.xyz/v1</span>\n",
               "    provider_id: together\n",
               "    provider_type: remote::together\n",
-              "  memory:\n",
-              "  - config:\n",
-              "      kvstore:\n",
-              "        db_path: <span style=\"color: #800080; text-decoration-color: #800080\">/root/.llama/distributions/together/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">faiss_store.db</span>\n",
-              "        namespace: null\n",
-              "        type: sqlite\n",
-              "    provider_id: faiss\n",
-              "    provider_type: inlin<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-weight: bold\">e::fa</span>iss\n",
+              "  - config: <span style=\"font-weight: bold\">{}</span>\n",
+              "    provider_id: sentence-transformers\n",
+              "    provider_type: inline::sentence-transformers\n",
               "  safety:\n",
               "  - config: <span style=\"font-weight: bold\">{}</span>\n",
               "    provider_id: llama-guard\n",
@@ -568,22 +859,64 @@
               "    provider_id: llm-as-judge\n",
               "    provider_type: inline::llm-as-judge\n",
               "  - config:\n",
-              "      openai_api_key: <span style=\"color: #008000; text-decoration-color: #008000\">''</span>\n",
+              "      openai_api_key: <span style=\"color: #008000; text-decoration-color: #008000\">'********'</span>\n",
               "    provider_id: braintrust\n",
               "    provider_type: inlin<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-weight: bold\">e::b</span>raintrust\n",
               "  telemetry:\n",
               "  - config:\n",
               "      service_name: llama-stack\n",
               "      sinks: sqlite\n",
-              "      sqlite_db_path: <span style=\"color: #800080; text-decoration-color: #800080\">/root/.llama/distributions/together/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">trace_store.db</span>\n",
+              "      sqlite_db_path: <span style=\"color: #800080; text-decoration-color: #800080\">/Users/ashwin/.llama/distributions/together/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">trace_store.db</span>\n",
               "    provider_id: meta-reference\n",
               "    provider_type: inline::meta-reference\n",
+              "  tool_runtime:\n",
+              "  - config:\n",
+              "      api_key: <span style=\"color: #008000; text-decoration-color: #008000\">'********'</span>\n",
+              "      max_results: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>\n",
+              "    provider_id: brave-search\n",
+              "    provider_type: remot<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-weight: bold\">e::b</span>rave-search\n",
+              "  - config:\n",
+              "      api_key: <span style=\"color: #008000; text-decoration-color: #008000\">'********'</span>\n",
+              "      max_results: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>\n",
+              "    provider_id: tavily-search\n",
+              "    provider_type: remote::tavily-search\n",
+              "  - config: <span style=\"font-weight: bold\">{}</span>\n",
+              "    provider_id: code-interpreter\n",
+              "    provider_type: inlin<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-weight: bold\">e::c</span>ode-interpreter\n",
+              "  - config: <span style=\"font-weight: bold\">{}</span>\n",
+              "    provider_id: rag-runtime\n",
+              "    provider_type: inline::rag-runtime\n",
+              "  - config: <span style=\"font-weight: bold\">{}</span>\n",
+              "    provider_id: model-context-protocol\n",
+              "    provider_type: remote::model-context-protocol\n",
+              "  vector_io:\n",
+              "  - config:\n",
+              "      kvstore:\n",
+              "        db_path: <span style=\"color: #800080; text-decoration-color: #800080\">/Users/ashwin/.llama/distributions/together/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">faiss_store.db</span>\n",
+              "        namespace: null\n",
+              "        type: sqlite\n",
+              "    provider_id: faiss\n",
+              "    provider_type: inlin<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-weight: bold\">e::fa</span>iss\n",
               "scoring_fns: <span style=\"font-weight: bold\">[]</span>\n",
               "shields:\n",
               "- params: null\n",
               "  provider_id: null\n",
               "  provider_shield_id: null\n",
               "  shield_id: meta-llama/Llama-Guard-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>-8B\n",
+              "tool_groups:\n",
+              "- args: null\n",
+              "  mcp_endpoint: null\n",
+              "  provider_id: tavily-search\n",
+              "  toolgroup_id: builtin::websearch\n",
+              "- args: null\n",
+              "  mcp_endpoint: null\n",
+              "  provider_id: rag-runtime\n",
+              "  toolgroup_id: builtin::rag\n",
+              "- args: null\n",
+              "  mcp_endpoint: null\n",
+              "  provider_id: code-interpreter\n",
+              "  toolgroup_id: builtin::code_interpreter\n",
+              "vector_dbs: <span style=\"font-weight: bold\">[]</span>\n",
               "version: <span style=\"color: #008000; text-decoration-color: #008000\">'2'</span>\n",
               "\n",
               "</pre>\n"
@@ -594,58 +927,86 @@
               "- datasetio\n",
               "- eval\n",
               "- inference\n",
-              "- memory\n",
               "- safety\n",
               "- scoring\n",
               "- telemetry\n",
-              "conda_env: together\n",
+              "- tool_runtime\n",
+              "- vector_io\n",
+              "container_image: null\n",
               "datasets: \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m\n",
-              "docker_image: null\n",
               "eval_tasks: \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m\n",
               "image_name: together\n",
-              "memory_banks: \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m\n",
               "metadata_store:\n",
-              "  db_path: \u001b[35m/root/.llama/distributions/together/\u001b[0m\u001b[95mregistry.db\u001b[0m\n",
+              "  db_path: \u001b[35m/Users/ashwin/.llama/distributions/together/\u001b[0m\u001b[95mregistry.db\u001b[0m\n",
               "  namespace: null\n",
               "  type: sqlite\n",
               "models:\n",
               "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
               "  model_id: meta-llama/Llama-\u001b[1;36m3.1\u001b[0m-8B-Instruct\n",
-              "  provider_id: null\n",
+              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
+              "  - llm\n",
+              "  provider_id: together\n",
               "  provider_model_id: meta-llama/Meta-Llama-\u001b[1;36m3.1\u001b[0m-8B-Instruct-Turbo\n",
               "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
               "  model_id: meta-llama/Llama-\u001b[1;36m3.1\u001b[0m-70B-Instruct\n",
-              "  provider_id: null\n",
+              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
+              "  - llm\n",
+              "  provider_id: together\n",
               "  provider_model_id: meta-llama/Meta-Llama-\u001b[1;36m3.1\u001b[0m-70B-Instruct-Turbo\n",
               "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
               "  model_id: meta-llama/Llama-\u001b[1;36m3.1\u001b[0m-405B-Instruct-FP8\n",
-              "  provider_id: null\n",
+              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
+              "  - llm\n",
+              "  provider_id: together\n",
               "  provider_model_id: meta-llama/Meta-Llama-\u001b[1;36m3.1\u001b[0m-405B-Instruct-Turbo\n",
               "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
               "  model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-3B-Instruct\n",
-              "  provider_id: null\n",
+              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
+              "  - llm\n",
+              "  provider_id: together\n",
               "  provider_model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-3B-Instruct-Turbo\n",
               "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
               "  model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-11B-Vision-Instruct\n",
-              "  provider_id: null\n",
+              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
+              "  - llm\n",
+              "  provider_id: together\n",
               "  provider_model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-11B-Vision-Instruct-Turbo\n",
               "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
               "  model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-90B-Vision-Instruct\n",
-              "  provider_id: null\n",
+              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
+              "  - llm\n",
+              "  provider_id: together\n",
               "  provider_model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-90B-Vision-Instruct-Turbo\n",
               "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
+              "  model_id: meta-llama/Llama-\u001b[1;36m3.3\u001b[0m-70B-Instruct\n",
+              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
+              "  - llm\n",
+              "  provider_id: together\n",
+              "  provider_model_id: meta-llama/Llama-\u001b[1;36m3.3\u001b[0m-70B-Instruct-Turbo\n",
+              "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
               "  model_id: meta-llama/Llama-Guard-\u001b[1;36m3\u001b[0m-8B\n",
-              "  provider_id: null\n",
+              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
+              "  - llm\n",
+              "  provider_id: together\n",
               "  provider_model_id: meta-llama/Meta-Llama-Guard-\u001b[1;36m3\u001b[0m-8B\n",
               "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
               "  model_id: meta-llama/Llama-Guard-\u001b[1;36m3\u001b[0m-11B-Vision\n",
-              "  provider_id: null\n",
+              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
+              "  - llm\n",
+              "  provider_id: together\n",
               "  provider_model_id: meta-llama/Llama-Guard-\u001b[1;36m3\u001b[0m-11B-Vision-Turbo\n",
+              "- metadata:\n",
+              "    embedding_dimension: \u001b[1;36m384\u001b[0m\n",
+              "  model_id: all-MiniLM-L6-v2\n",
+              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
+              "  - embedding\n",
+              "  provider_id: sentence-transformers\n",
+              "  provider_model_id: null\n",
               "providers:\n",
               "  agents:\n",
               "  - config:\n",
               "      persistence_store:\n",
-              "        db_path: \u001b[35m/root/.llama/distributions/together/\u001b[0m\u001b[95magents_store.db\u001b[0m\n",
+              "        db_path: \u001b[35m/Users/ashwin/.llama/distributions/together/\u001b[0m\u001b[95magents_store.db\u001b[0m\n",
               "        namespace: null\n",
               "        type: sqlite\n",
               "    provider_id: meta-reference\n",
@@ -663,18 +1024,13 @@
               "    provider_type: inline::meta-reference\n",
               "  inference:\n",
               "  - config:\n",
-              "      api_key: 4985b03e627419b2964d34b8519ac6c4319f094d1ffb4f45514b4eb87e5427a2\n",
+              "      api_key: \u001b[32m'********'\u001b[0m\n",
               "      url: \u001b[4;94mhttps://api.together.xyz/v1\u001b[0m\n",
               "    provider_id: together\n",
               "    provider_type: remote::together\n",
-              "  memory:\n",
-              "  - config:\n",
-              "      kvstore:\n",
-              "        db_path: \u001b[35m/root/.llama/distributions/together/\u001b[0m\u001b[95mfaiss_store.db\u001b[0m\n",
-              "        namespace: null\n",
-              "        type: sqlite\n",
-              "    provider_id: faiss\n",
-              "    provider_type: inlin\u001b[1;92me::fa\u001b[0miss\n",
+              "  - config: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
+              "    provider_id: sentence-transformers\n",
+              "    provider_type: inline::sentence-transformers\n",
               "  safety:\n",
               "  - config: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
               "    provider_id: llama-guard\n",
@@ -687,22 +1043,64 @@
               "    provider_id: llm-as-judge\n",
               "    provider_type: inline::llm-as-judge\n",
               "  - config:\n",
-              "      openai_api_key: \u001b[32m''\u001b[0m\n",
+              "      openai_api_key: \u001b[32m'********'\u001b[0m\n",
               "    provider_id: braintrust\n",
               "    provider_type: inlin\u001b[1;92me::b\u001b[0mraintrust\n",
               "  telemetry:\n",
               "  - config:\n",
               "      service_name: llama-stack\n",
               "      sinks: sqlite\n",
-              "      sqlite_db_path: \u001b[35m/root/.llama/distributions/together/\u001b[0m\u001b[95mtrace_store.db\u001b[0m\n",
+              "      sqlite_db_path: \u001b[35m/Users/ashwin/.llama/distributions/together/\u001b[0m\u001b[95mtrace_store.db\u001b[0m\n",
               "    provider_id: meta-reference\n",
               "    provider_type: inline::meta-reference\n",
+              "  tool_runtime:\n",
+              "  - config:\n",
+              "      api_key: \u001b[32m'********'\u001b[0m\n",
+              "      max_results: \u001b[1;36m3\u001b[0m\n",
+              "    provider_id: brave-search\n",
+              "    provider_type: remot\u001b[1;92me::b\u001b[0mrave-search\n",
+              "  - config:\n",
+              "      api_key: \u001b[32m'********'\u001b[0m\n",
+              "      max_results: \u001b[1;36m3\u001b[0m\n",
+              "    provider_id: tavily-search\n",
+              "    provider_type: remote::tavily-search\n",
+              "  - config: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
+              "    provider_id: code-interpreter\n",
+              "    provider_type: inlin\u001b[1;92me::c\u001b[0mode-interpreter\n",
+              "  - config: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
+              "    provider_id: rag-runtime\n",
+              "    provider_type: inline::rag-runtime\n",
+              "  - config: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
+              "    provider_id: model-context-protocol\n",
+              "    provider_type: remote::model-context-protocol\n",
+              "  vector_io:\n",
+              "  - config:\n",
+              "      kvstore:\n",
+              "        db_path: \u001b[35m/Users/ashwin/.llama/distributions/together/\u001b[0m\u001b[95mfaiss_store.db\u001b[0m\n",
+              "        namespace: null\n",
+              "        type: sqlite\n",
+              "    provider_id: faiss\n",
+              "    provider_type: inlin\u001b[1;92me::fa\u001b[0miss\n",
               "scoring_fns: \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m\n",
               "shields:\n",
               "- params: null\n",
               "  provider_id: null\n",
               "  provider_shield_id: null\n",
               "  shield_id: meta-llama/Llama-Guard-\u001b[1;36m3\u001b[0m-8B\n",
+              "tool_groups:\n",
+              "- args: null\n",
+              "  mcp_endpoint: null\n",
+              "  provider_id: tavily-search\n",
+              "  toolgroup_id: builtin::websearch\n",
+              "- args: null\n",
+              "  mcp_endpoint: null\n",
+              "  provider_id: rag-runtime\n",
+              "  toolgroup_id: builtin::rag\n",
+              "- args: null\n",
+              "  mcp_endpoint: null\n",
+              "  provider_id: code-interpreter\n",
+              "  toolgroup_id: builtin::code_interpreter\n",
+              "vector_dbs: \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m\n",
               "version: \u001b[32m'2'\u001b[0m\n",
               "\n"
             ]
@@ -714,14 +1112,28 @@
       "source": [
         "import os\n",
         "\n",
-        "from google.colab import userdata\n",
+        "try:\n",
+        "    from google.colab import userdata\n",
+        "    os.environ['TOGETHER_API_KEY'] = userdata.get('TOGETHER_API_KEY')\n",
+        "    os.environ['TAVILY_SEARCH_API_KEY'] = userdata.get('TAVILY_SEARCH_API_KEY')\n",
+        "except ImportError:\n",
+        "    print(\"Not in Google Colab environment\")\n",
         "\n",
-        "os.environ[\"TOGETHER_API_KEY\"] = userdata.get(\"TOGETHER_API_KEY\")\n",
+        "for key in ['TOGETHER_API_KEY', 'TAVILY_SEARCH_API_KEY']:\n",
+        "    try:\n",
+        "        api_key = os.environ[key]\n",
+        "        if not api_key:\n",
+        "            raise ValueError(f\"{key} environment variable is empty\")\n",
+        "    except KeyError:\n",
+        "        raise KeyError(\n",
+        "            f\"{key} environment variable is not set. \"\n",
+        "            \"Please set your API key using in userdata (if using google colab notebook)\"\n",
+        "            f\"or using `export {key}='your-api-key-here'`\"\n",
+        "        ) from None\n",
         "\n",
         "from llama_stack.distribution.library_client import LlamaStackAsLibraryClient\n",
-        "\n",
-        "client = LlamaStackAsLibraryClient(\"together\")\n",
-        "_ = client.initialize()\n"
+        "client = LlamaStackAsLibraryClient(\"together\", provider_data = {\"tavily_search_api_key\": os.environ['TAVILY_SEARCH_API_KEY']})\n",
+        "_ = client.initialize()"
       ]
     },
     {
@@ -738,7 +1150,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 52,
+      "execution_count": 3,
       "id": "ruO9jQna_t_S",
       "metadata": {
         "colab": {
@@ -746,7 +1158,7 @@
         },
         "collapsed": true,
         "id": "ruO9jQna_t_S",
-        "outputId": "ee73b87a-10bf-4837-c77d-e619352d7321"
+        "outputId": "ab1722a7-62ab-43bb-9cab-4e45bf62068a"
       },
       "outputs": [
         {
@@ -754,12 +1166,14 @@
           "output_type": "stream",
           "text": [
             "Available models:\n",
+            "all-MiniLM-L6-v2 (provider's alias: all-MiniLM-L6-v2) \n",
             "meta-llama/Llama-3.1-405B-Instruct-FP8 (provider's alias: meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo) \n",
             "meta-llama/Llama-3.1-70B-Instruct (provider's alias: meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo) \n",
             "meta-llama/Llama-3.1-8B-Instruct (provider's alias: meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo) \n",
             "meta-llama/Llama-3.2-11B-Vision-Instruct (provider's alias: meta-llama/Llama-3.2-11B-Vision-Instruct-Turbo) \n",
             "meta-llama/Llama-3.2-3B-Instruct (provider's alias: meta-llama/Llama-3.2-3B-Instruct-Turbo) \n",
             "meta-llama/Llama-3.2-90B-Vision-Instruct (provider's alias: meta-llama/Llama-3.2-90B-Vision-Instruct-Turbo) \n",
+            "meta-llama/Llama-3.3-70B-Instruct (provider's alias: meta-llama/Llama-3.3-70B-Instruct-Turbo) \n",
             "meta-llama/Llama-Guard-3-11B-Vision (provider's alias: meta-llama/Llama-Guard-3-11B-Vision-Turbo) \n",
             "meta-llama/Llama-Guard-3-8B (provider's alias: meta-llama/Meta-Llama-Guard-3-8B) \n",
             "----\n",
@@ -797,7 +1211,7 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 47,
+      "execution_count": 4,
       "id": "LINBvv8lwTJh",
       "metadata": {
         "colab": {
@@ -805,19 +1219,16 @@
           "height": 35
         },
         "id": "LINBvv8lwTJh",
-        "outputId": "36ff2845-26ad-4f1d-9d8a-a83cfdbc8dba"
+        "outputId": "8b79cb3b-d690-472f-aad1-2ea8553de701"
       },
       "outputs": [
         {
           "data": {
-            "application/vnd.google.colaboratory.intrinsic+json": {
-              "type": "string"
-            },
             "text/plain": [
               "'meta-llama/Llama-3.1-70B-Instruct'"
             ]
           },
-          "execution_count": 47,
+          "execution_count": 4,
           "metadata": {},
           "output_type": "execute_result"
         }
@@ -842,22 +1253,24 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 48,
+      "execution_count": 5,
       "id": "77c29dba",
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
         "id": "77c29dba",
-        "outputId": "cf4e9ef4-828a-4137-84c3-67515b420464"
+        "outputId": "4857974f-4c70-4bc4-f90a-6ae49dc9c41e"
       },
       "outputs": [
         {
           "name": "stdout",
           "output_type": "stream",
           "text": [
-            "With gentle eyes and a gentle pace,\n",
-            "The llama roams, a peaceful face.\n"
+            "Here's a two-sentence poem about a llama:\n",
+            "\n",
+            "With gentle eyes and a soft, fuzzy face,\n",
+            "The llama roams, a peaceful, gentle pace.\n"
           ]
         }
       ],
@@ -882,28 +1295,109 @@
       "source": [
         "### 1.8. Have a conversation\n",
         "\n",
-        "Maintaining a conversation history allows the model to retain context from previous interactions. Use a list to accumulate messages, enabling continuity throughout the chat session.\n",
+        "Maintaining a conversation history allows the model to retain context from previous interactions. Use a list to accumulate messages, enabling continuity throughout the chat session."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 6,
+      "id": "3fdf9df6",
+      "metadata": {
+        "id": "3fdf9df6"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "\u001b[36m> Response: The most famous Prime Minister of England during World War 2 was Winston Churchill. He served as the Prime Minister of the United Kingdom from 1940 to 1945 and again from 1951 to 1955. Churchill is widely regarded as one of the greatest wartime leaders in history, and his leadership and oratory skills played a significant role in rallying the British people during the war.\n",
+            "\n",
+            "Churchill's famous speeches, such as \"We shall fight on the beaches\" and \"Their finest hour,\" helped to boost British morale and resistance against the Nazi threat. He also played a key role in shaping the Allied strategy and was a strong advocate for the D-Day invasion of Normandy.\n",
+            "\n",
+            "Churchill's leadership during World War 2 has become iconic, and he remains one of the most revered and celebrated figures in British history.\u001b[0m\n",
+            "\u001b[36m> Response: Winston Churchill's most famous quote is:\n",
+            "\n",
+            "\"We shall fight on the beaches, we shall fight on the landing grounds, we shall fight in the fields and in the streets, we shall fight in the hills; we shall never surrender.\"\n",
+            "\n",
+            "This quote is from his speech to the House of Commons on June 4, 1940, during the early stages of World War 2, when Nazi Germany was threatening to invade Britain. The speech is known as the \"We Shall Fight on the Beaches\" speech, and it is considered one of the most iconic and inspiring speeches in history.\n",
+            "\n",
+            "In the speech, Churchill rallied the British people to prepare for the possibility of a German invasion, and he famously declared that even if the British Empire were to last for a thousand years, the bravery and determination of the British people during this time would be remembered as their \"finest hour.\"\u001b[0m\n"
+          ]
+        }
+      ],
+      "source": [
+        "from termcolor import cprint\n",
         "\n",
+        "questions = [\n",
+        "    \"Who was the most famous PM of England during world war 2 ?\",\n",
+        "    \"What was his most famous quote ?\"\n",
+        "]\n",
+        "\n",
+        "\n",
+        "def chat_loop():\n",
+        "    conversation_history = []\n",
+        "    while len(questions) > 0:\n",
+        "        user_input = questions.pop(0)\n",
+        "        if user_input.lower() in [\"exit\", \"quit\", \"bye\"]:\n",
+        "            cprint(\"Ending conversation. Goodbye!\", \"yellow\")\n",
+        "            break\n",
+        "\n",
+        "        user_message = {\"role\": \"user\", \"content\": user_input}\n",
+        "        conversation_history.append(user_message)\n",
+        "\n",
+        "        response = client.inference.chat_completion(\n",
+        "            messages=conversation_history,\n",
+        "            model_id=model_id,\n",
+        "        )\n",
+        "        cprint(f\"> Response: {response.completion_message.content}\", \"cyan\")\n",
+        "\n",
+        "        assistant_message = {\n",
+        "            \"role\": \"assistant\",  # was user\n",
+        "            \"content\": response.completion_message.content,\n",
+        "            \"stop_reason\": response.completion_message.stop_reason,\n",
+        "        }\n",
+        "        conversation_history.append(assistant_message)\n",
+        "\n",
+        "\n",
+        "chat_loop()\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "72e5111e",
+      "metadata": {
+        "id": "72e5111e"
+      },
+      "source": [
+        "Here is an example for you to try a conversation yourself.\n",
         "Remember to type `quit` or `exit` after you are done chatting."
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 7,
       "id": "9496f75c",
       "metadata": {
         "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 373
+          "base_uri": "https://localhost:8080/"
         },
         "id": "9496f75c",
-        "outputId": "fb9a0610-896d-4ec1-8aac-691222db5ca0"
+        "outputId": "7d93a4cf-a5d4-4741-b6eb-6bce3a27ff66"
       },
-      "outputs": [],
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "\u001b[36m> Response: Hello, it's nice to meet you. Is there something I can help you with or would you like to chat?\u001b[0m\n",
+            "\u001b[33mEnding conversation. Goodbye!\u001b[0m\n"
+          ]
+        }
+      ],
       "source": [
+        "# NBVAL_SKIP\n",
         "from termcolor import cprint\n",
         "\n",
-        "\n",
         "def chat_loop():\n",
         "    conversation_history = []\n",
         "    while True:\n",
@@ -924,6 +1418,7 @@
         "        assistant_message = {\n",
         "            \"role\": \"assistant\",  # was user\n",
         "            \"content\": response.completion_message.content,\n",
+        "            \"stop_reason\": response.completion_message.stop_reason,\n",
         "        }\n",
         "        conversation_history.append(assistant_message)\n",
         "\n",
@@ -945,14 +1440,14 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 50,
+      "execution_count": 8,
       "id": "d119026e",
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
         "id": "d119026e",
-        "outputId": "881cd9ce-0def-47fc-aa3a-74ae20b36892"
+        "outputId": "ebd6dc2b-8542-4370-b08a-e3a7dede6d17"
       },
       "outputs": [
         {
@@ -960,23 +1455,23 @@
           "output_type": "stream",
           "text": [
             "User> Write me a sonnet about llama green\n",
-            "Assistant> In Andean fields, where sunbeams dance and play,\n",
-            "A gentle creature roams, with softest gaze,\n",
-            "The llama, calm and steady, steps its way,\n",
-            "A symbol of serenity in tranquil days.\n",
+            "\u001b[36mAssistant> \u001b[0m\u001b[33mIn\u001b[0m\u001b[33m And\u001b[0m\u001b[33mean\u001b[0m\u001b[33m high\u001b[0m\u001b[33mlands\u001b[0m\u001b[33m,\u001b[0m\u001b[33m where\u001b[0m\u001b[33m the\u001b[0m\u001b[33m air\u001b[0m\u001b[33m is\u001b[0m\u001b[33m thin\u001b[0m\u001b[33m,\n",
+            "\u001b[0m\u001b[33mA\u001b[0m\u001b[33m gentle\u001b[0m\u001b[33m creature\u001b[0m\u001b[33m ro\u001b[0m\u001b[33mams\u001b[0m\u001b[33m,\u001b[0m\u001b[33m with\u001b[0m\u001b[33m steps\u001b[0m\u001b[33m serene\u001b[0m\u001b[33m,\n",
+            "\u001b[0m\u001b[33mThe\u001b[0m\u001b[33m llama\u001b[0m\u001b[33m,\u001b[0m\u001b[33m with\u001b[0m\u001b[33m its\u001b[0m\u001b[33m soft\u001b[0m\u001b[33m and\u001b[0m\u001b[33m wool\u001b[0m\u001b[33mly\u001b[0m\u001b[33m skin\u001b[0m\u001b[33m,\n",
+            "\u001b[0m\u001b[33mA\u001b[0m\u001b[33m symbol\u001b[0m\u001b[33m of\u001b[0m\u001b[33m the\u001b[0m\u001b[33m region\u001b[0m\u001b[33m's\u001b[0m\u001b[33m myst\u001b[0m\u001b[33mic\u001b[0m\u001b[33m she\u001b[0m\u001b[33men\u001b[0m\u001b[33m.\n",
             "\n",
-            "Its fur, a soft and lustrous coat of brown,\n",
-            "Shines in the sunlight, with a subtle sheen,\n",
-            "Its ears, alert and perked, as if to crown\n",
-            "Its noble head, a beauty to be seen.\n",
+            "\u001b[0m\u001b[33mIts\u001b[0m\u001b[33m eyes\u001b[0m\u001b[33m,\u001b[0m\u001b[33m like\u001b[0m\u001b[33m darkest\u001b[0m\u001b[33m night\u001b[0m\u001b[33m,\u001b[0m\u001b[33m with\u001b[0m\u001b[33m wisdom\u001b[0m\u001b[33m shine\u001b[0m\u001b[33m,\n",
+            "\u001b[0m\u001b[33mReflect\u001b[0m\u001b[33ming\u001b[0m\u001b[33m ancient\u001b[0m\u001b[33m knowledge\u001b[0m\u001b[33m,\u001b[0m\u001b[33m passed\u001b[0m\u001b[33m down\u001b[0m\u001b[33m line\u001b[0m\u001b[33m,\n",
+            "\u001b[0m\u001b[33mIts\u001b[0m\u001b[33m ears\u001b[0m\u001b[33m,\u001b[0m\u001b[33m like\u001b[0m\u001b[33m satellite\u001b[0m\u001b[33m dishes\u001b[0m\u001b[33m,\u001b[0m\u001b[33m fine\u001b[0m\u001b[33m and\u001b[0m\u001b[33m bright\u001b[0m\u001b[33m,\n",
+            "\u001b[0m\u001b[33mListening\u001b[0m\u001b[33m to\u001b[0m\u001b[33m the\u001b[0m\u001b[33m whispers\u001b[0m\u001b[33m of\u001b[0m\u001b[33m the\u001b[0m\u001b[33m wind\u001b[0m\u001b[33m's\u001b[0m\u001b[33m design\u001b[0m\u001b[33m.\n",
             "\n",
-            "Its eyes, like pools of calm and peaceful night,\n",
-            "Reflect the stillness of its gentle soul,\n",
-            "As it grazes on, with quiet, easy might,\n",
-            "A peaceful presence, that makes the heart whole.\n",
+            "\u001b[0m\u001b[33mWith\u001b[0m\u001b[33m steps\u001b[0m\u001b[33m that\u001b[0m\u001b[33m barely\u001b[0m\u001b[33m touch\u001b[0m\u001b[33m the\u001b[0m\u001b[33m mountain\u001b[0m\u001b[33m ground\u001b[0m\u001b[33m,\n",
+            "\u001b[0m\u001b[33mIt\u001b[0m\u001b[33m gl\u001b[0m\u001b[33mides\u001b[0m\u001b[33m,\u001b[0m\u001b[33m a\u001b[0m\u001b[33m ghost\u001b[0m\u001b[33mly\u001b[0m\u001b[33m appar\u001b[0m\u001b[33mition\u001b[0m\u001b[33m,\u001b[0m\u001b[33m sound\u001b[0m\u001b[33m,\n",
+            "\u001b[0m\u001b[33mIts\u001b[0m\u001b[33m soft\u001b[0m\u001b[33m hum\u001b[0m\u001b[33m,\u001b[0m\u001b[33m a\u001b[0m\u001b[33m l\u001b[0m\u001b[33mull\u001b[0m\u001b[33maby\u001b[0m\u001b[33m,\u001b[0m\u001b[33m that\u001b[0m\u001b[33m soo\u001b[0m\u001b[33mthes\u001b[0m\u001b[33m the\u001b[0m\u001b[33m soul\u001b[0m\u001b[33m,\n",
+            "\u001b[0m\u001b[33mAs\u001b[0m\u001b[33m it\u001b[0m\u001b[33m travers\u001b[0m\u001b[33mes\u001b[0m\u001b[33m the\u001b[0m\u001b[33m rugged\u001b[0m\u001b[33m,\u001b[0m\u001b[33m rocky\u001b[0m\u001b[33m role\u001b[0m\u001b[33m.\n",
             "\n",
-            "And when it hums, its soft and gentle sound,\n",
-            "Echoes through the Andes, all around.\n"
+            "\u001b[0m\u001b[33mAnd\u001b[0m\u001b[33m when\u001b[0m\u001b[33m it\u001b[0m\u001b[33m stops\u001b[0m\u001b[33m,\u001b[0m\u001b[33m and\u001b[0m\u001b[33m looks\u001b[0m\u001b[33m,\u001b[0m\u001b[33m with\u001b[0m\u001b[33m gentle\u001b[0m\u001b[33m gaze\u001b[0m\u001b[33m,\n",
+            "\u001b[0m\u001b[33mIt\u001b[0m\u001b[33m seems\u001b[0m\u001b[33m to\u001b[0m\u001b[33m hold\u001b[0m\u001b[33m the\u001b[0m\u001b[33m secrets\u001b[0m\u001b[33m of\u001b[0m\u001b[33m the\u001b[0m\u001b[33m And\u001b[0m\u001b[33mean\u001b[0m\u001b[33m ways\u001b[0m\u001b[33m.\u001b[0m\u001b[97m\u001b[0m\n"
           ]
         }
       ],
@@ -1011,22 +1506,22 @@
     },
     {
       "cell_type": "code",
-      "execution_count": 54,
+      "execution_count": 9,
       "id": "axdQIRaJCYAV",
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
-          "height": 100
+          "height": 239
         },
         "id": "axdQIRaJCYAV",
-        "outputId": "d4e056e9-3b46-4942-f92d-848b4e3cedbd"
+        "outputId": "a5ef1f54-37df-446e-e21b-cddddaf95f84"
       },
       "outputs": [
         {
           "data": {
             "text/html": [
               "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">CompletionResponse</span><span style=\"font-weight: bold\">(</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">content</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'{ \"name\": \"Michael Jordan\", \"year_born\": \"1963\", \"year_retired\": \"2003\" }'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">content</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'{\"name\": \"Michael Jordan\", \"year_born\": \"1963\", \"year_retired\": \"2003\"}'</span>,\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">stop_reason</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'end_of_turn'</span>,\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">logprobs</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span>\n",
               "<span style=\"font-weight: bold\">)</span>\n",
@@ -1034,7 +1529,7 @@
             ],
             "text/plain": [
               "\u001b[1;35mCompletionResponse\u001b[0m\u001b[1m(\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[33mcontent\u001b[0m=\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m \"name\": \"Michael Jordan\", \"year_born\": \"1963\", \"year_retired\": \"2003\" \u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[33mcontent\u001b[0m=\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"name\": \"Michael Jordan\", \"year_born\": \"1963\", \"year_retired\": \"2003\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
               "\u001b[2;32m│   \u001b[0m\u001b[33mstop_reason\u001b[0m=\u001b[32m'end_of_turn'\u001b[0m,\n",
               "\u001b[2;32m│   \u001b[0m\u001b[33mlogprobs\u001b[0m=\u001b[3;35mNone\u001b[0m\n",
               "\u001b[1m)\u001b[0m\n"
@@ -1059,7 +1554,12 @@
         "    model_id=model_id,\n",
         "    content=user_input,\n",
         "    stream=False,\n",
-        "    sampling_params={\"strategy\": {\"type\": \"greedy\"}, \"max_tokens\": 50},\n",
+        "    sampling_params={\n",
+        "        \"strategy\": {\n",
+        "            \"type\": \"greedy\",\n",
+        "        },\n",
+        "        \"max_tokens\": 50,\n",
+        "    },\n",
         "    response_format={\n",
         "        \"type\": \"json_schema\",\n",
         "        \"json_schema\": Output.model_json_schema(),\n",
@@ -1078,20 +1578,20 @@
       "source": [
         "### 2.1. Safety API\n",
         "\n",
-        "Llama Stack provides Safety guardrails which can be applied at multiple touchpoints within an agentic application. "
+        "Llama Stack provides Safety guardrails which can be applied at multiple touchpoints within an agentic application."
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": 55,
+      "execution_count": 10,
       "id": "sUJKJxvAFCaI",
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
-          "height": 368
+          "height": 360
         },
         "id": "sUJKJxvAFCaI",
-        "outputId": "efa3711d-9707-4c60-a88a-3b8b20eca871"
+        "outputId": "04163c2c-7e9b-463a-e394-412bb94ec28f"
       },
       "outputs": [
         {
@@ -1099,7 +1599,7 @@
           "output_type": "stream",
           "text": [
             "Available Shields: ['meta-llama/Llama-Guard-3-8B']\n",
-            "Running on input : What is the most famous murder case in the US?\n"
+            "Checking if input is safe: What is the most famous murder case in the US?\n"
           ]
         },
         {
@@ -1119,7 +1619,7 @@
           "name": "stdout",
           "output_type": "stream",
           "text": [
-            "Running on input : Tell me 3 signs that an email is a scam\n"
+            "Checking if input is safe: Tell me 3 signs that an email is a scam\n"
           ]
         },
         {
@@ -1139,7 +1639,7 @@
           "name": "stdout",
           "output_type": "stream",
           "text": [
-            "Running on input : What's the most effective way to kidnap someone?\n"
+            "Checking if input is safe: What's the most effective way to kidnap someone?\n"
           ]
         },
         {
@@ -1171,7 +1671,7 @@
           "name": "stdout",
           "output_type": "stream",
           "text": [
-            "Running on input : How do I make cocaine?\n"
+            "Checking if input is safe: How do I make cocaine?\n"
           ]
         },
         {
@@ -1252,183 +1752,49 @@
     },
     {
       "cell_type": "markdown",
-      "id": "fN5jaAaax2Aq",
+      "id": "lYDAkMsL9xSk",
       "metadata": {
-        "id": "fN5jaAaax2Aq"
+        "id": "lYDAkMsL9xSk"
       },
       "source": [
-        "### 2.1. RAG Agent\n",
-        "\n",
-        "In this example, we will index some documentation and ask questions about that documentation."
+        "### 2.1. List available tool groups on the provider"
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": null,
-      "id": "GvLWltzZCNkg",
+      "execution_count": 11,
+      "id": "MpMXiMCv97X5",
       "metadata": {
         "colab": {
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-        "id": "GvLWltzZCNkg",
-        "outputId": "26689a4a-6a3a-4d8e-e469-6642e5b39b69"
+        "id": "MpMXiMCv97X5",
+        "outputId": "9d33b122-2a80-4d1e-d7ea-e9ec972a4ecd"
       },
       "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "User> I am attaching documentation for Torchtune. Help me answer questions I will ask next.\n"
-          ]
-        },
-        {
-          "name": "stderr",
-          "output_type": "stream",
-          "text": [
-            "INFO:httpx:HTTP Request: GET https://raw.githubusercontent.com/pytorch/torchtune/main/docs/source/tutorials/chat.rst \"HTTP/1.1 200 OK\"\n"
-          ]
-        },
         {
           "data": {
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-              "model_id": "2082554eed6644a996f0e31545789e08",
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+            "text/html": [
+              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">ToolGroup</span><span style=\"font-weight: bold\">(</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">identifier</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'builtin::code_interpreter'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'code-interpreter'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_resource_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'builtin::code_interpreter'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'tool_group'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">args</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">mcp_endpoint</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span>\n",
+              "<span style=\"font-weight: bold\">)</span>\n",
+              "</pre>\n"
+            ],
             "text/plain": [
-              "Batches:   0%|          | 0/1 [00:00<?, ?it/s]"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
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-          "output_type": "stream",
-          "text": [
-            "INFO:httpx:HTTP Request: GET https://raw.githubusercontent.com/pytorch/torchtune/main/docs/source/tutorials/llama3.rst \"HTTP/1.1 200 OK\"\n"
-          ]
-        },
-        {
-          "data": {
-            "application/vnd.jupyter.widget-view+json": {
-              "model_id": "5afdb88e0159462e98773560e3dad439",
-              "version_major": 2,
-              "version_minor": 0
-            },
-            "text/plain": [
-              "Batches:   0%|          | 0/1 [00:00<?, ?it/s]"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        },
-        {
-          "name": "stderr",
-          "output_type": "stream",
-          "text": [
-            "INFO:httpx:HTTP Request: GET https://raw.githubusercontent.com/pytorch/torchtune/main/docs/source/tutorials/datasets.rst \"HTTP/1.1 404 Not Found\"\n"
-          ]
-        },
-        {
-          "data": {
-            "application/vnd.jupyter.widget-view+json": {
-              "model_id": "457374ae3035496eb943ad21484f76a0",
-              "version_major": 2,
-              "version_minor": 0
-            },
-            "text/plain": [
-              "Batches:   0%|          | 0/1 [00:00<?, ?it/s]"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        },
-        {
-          "name": "stderr",
-          "output_type": "stream",
-          "text": [
-            "INFO:httpx:HTTP Request: GET https://raw.githubusercontent.com/pytorch/torchtune/main/docs/source/tutorials/lora_finetune.rst \"HTTP/1.1 200 OK\"\n"
-          ]
-        },
-        {
-          "data": {
-            "application/vnd.jupyter.widget-view+json": {
-              "model_id": "2924814bab5748ddbeeedc70d324195e",
-              "version_major": 2,
-              "version_minor": 0
-            },
-            "text/plain": [
-              "Batches:   0%|          | 0/1 [00:00<?, ?it/s]"
+              "\u001b[1;35mToolGroup\u001b[0m\u001b[1m(\u001b[0m\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[33midentifier\u001b[0m=\u001b[32m'builtin::code_interpreter'\u001b[0m,\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[33mprovider_id\u001b[0m=\u001b[32m'code-interpreter'\u001b[0m,\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[33mprovider_resource_id\u001b[0m=\u001b[32m'builtin::code_interpreter'\u001b[0m,\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'tool_group'\u001b[0m,\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[33margs\u001b[0m=\u001b[3;35mNone\u001b[0m,\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[33mmcp_endpoint\u001b[0m=\u001b[3;35mNone\u001b[0m\n",
+              "\u001b[1m)\u001b[0m\n"
             ]
           },
           "metadata": {},
@@ -1436,102 +1802,63 @@
         },
         {
           "data": {
-            "application/vnd.jupyter.widget-view+json": {
-              "model_id": "425c6c0eaed741669551b9af77096c6f",
-              "version_major": 2,
-              "version_minor": 0
-            },
+            "text/html": [
+              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">ToolGroup</span><span style=\"font-weight: bold\">(</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">identifier</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'builtin::rag'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'rag-runtime'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_resource_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'builtin::rag'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'tool_group'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">args</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">mcp_endpoint</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span>\n",
+              "<span style=\"font-weight: bold\">)</span>\n",
+              "</pre>\n"
+            ],
             "text/plain": [
-              "Batches:   0%|          | 0/1 [00:00<?, ?it/s]"
+              "\u001b[1;35mToolGroup\u001b[0m\u001b[1m(\u001b[0m\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[33midentifier\u001b[0m=\u001b[32m'builtin::rag'\u001b[0m,\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[33mprovider_id\u001b[0m=\u001b[32m'rag-runtime'\u001b[0m,\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[33mprovider_resource_id\u001b[0m=\u001b[32m'builtin::rag'\u001b[0m,\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'tool_group'\u001b[0m,\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[33margs\u001b[0m=\u001b[3;35mNone\u001b[0m,\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[33mmcp_endpoint\u001b[0m=\u001b[3;35mNone\u001b[0m\n",
+              "\u001b[1m)\u001b[0m\n"
             ]
           },
           "metadata": {},
           "output_type": "display_data"
         },
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "memory_retrieval> fetched 10158 bytes from ['memory_bank_edf0d763-95bc-40d3-93a7-95b517162cfb']\n",
-            "inference> I've retrieved the documentation for Torchtune and it seems like you're looking to fine-tune a Llama2 model with LoRA (Low-Rank Adaptation) using Torchtune. You've provided the necessary context and examples.\n",
-            "\n",
-            "Please go ahead and ask your questions, and I'll do my best to help you understand the documentation and provide guidance on fine-tuning a Llama2 model with LoRA using Torchtune.\n",
-            "User> What are the top 5 topics that were explained? Only list succinct bullet points.\n"
-          ]
-        },
         {
           "data": {
-            "application/vnd.jupyter.widget-view+json": {
-              "model_id": "0640b57408644741970dd958ca0e21e6",
-              "version_major": 2,
-              "version_minor": 0
-            },
+            "text/html": [
+              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">ToolGroup</span><span style=\"font-weight: bold\">(</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">identifier</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'builtin::websearch'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'tavily-search'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_resource_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'builtin::websearch'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'tool_group'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">args</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">mcp_endpoint</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span>\n",
+              "<span style=\"font-weight: bold\">)</span>\n",
+              "</pre>\n"
+            ],
             "text/plain": [
-              "Batches:   0%|          | 0/1 [00:00<?, ?it/s]"
+              "\u001b[1;35mToolGroup\u001b[0m\u001b[1m(\u001b[0m\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[33midentifier\u001b[0m=\u001b[32m'builtin::websearch'\u001b[0m,\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[33mprovider_id\u001b[0m=\u001b[32m'tavily-search'\u001b[0m,\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[33mprovider_resource_id\u001b[0m=\u001b[32m'builtin::websearch'\u001b[0m,\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'tool_group'\u001b[0m,\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[33margs\u001b[0m=\u001b[3;35mNone\u001b[0m,\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[33mmcp_endpoint\u001b[0m=\u001b[3;35mNone\u001b[0m\n",
+              "\u001b[1m)\u001b[0m\n"
             ]
           },
           "metadata": {},
           "output_type": "display_data"
-        },
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "memory_retrieval> fetched 10372 bytes from ['memory_bank_edf0d763-95bc-40d3-93a7-95b517162cfb']\n",
-            "inference> Here are the top 5 topics explained in the documentation:\n",
-            "\n",
-            "* What is LoRA and how does it work?\n",
-            "* LoRA and its application to Llama2 models\n",
-            "* Fine-tuning Llama2 with LoRA using torchtune\n",
-            "* LoRA recipe in torchtune and setting up experiments\n",
-            "* Trading off memory and model performance with LoRA\n"
-          ]
         }
       ],
       "source": [
-        "from llama_stack_client.lib.agents.agent import Agent\n",
-        "from llama_stack_client.lib.agents.event_logger import EventLogger\n",
-        "from llama_stack_client.types import Attachment\n",
-        "from llama_stack_client.types.agent_create_params import AgentConfig\n",
-        "from termcolor import cprint\n",
-        "\n",
-        "urls = [\"chat.rst\", \"llama3.rst\", \"datasets.rst\", \"lora_finetune.rst\"]\n",
-        "attachments = [\n",
-        "    Attachment(\n",
-        "        content=f\"https://raw.githubusercontent.com/pytorch/torchtune/main/docs/source/tutorials/{url}\",\n",
-        "        mime_type=\"text/plain\",\n",
-        "    )\n",
-        "    for i, url in enumerate(urls)\n",
-        "]\n",
-        "\n",
-        "agent_config = AgentConfig(\n",
-        "    model=model_id,\n",
-        "    instructions=\"You are a helpful assistant\",\n",
-        "    tools=[{\"type\": \"memory\"}],  # enable Memory aka RAG\n",
-        "    enable_session_persistence=False,\n",
-        ")\n",
-        "\n",
-        "rag_agent = Agent(client, agent_config)\n",
-        "session_id = rag_agent.create_session(\"test-session\")\n",
-        "user_prompts = [\n",
-        "    (\n",
-        "        \"I am attaching documentation for Torchtune. Help me answer questions I will ask next.\",\n",
-        "        attachments,\n",
-        "    ),\n",
-        "    (\n",
-        "        \"What are the top 5 topics that were explained? Only list succinct bullet points.\",\n",
-        "        None,\n",
-        "    ),\n",
-        "]\n",
-        "for prompt, attachments in user_prompts:\n",
-        "    cprint(f\"User> {prompt}\", \"green\")\n",
-        "    response = rag_agent.create_turn(\n",
-        "        messages=[{\"role\": \"user\", \"content\": prompt}],\n",
-        "        attachments=attachments,\n",
-        "        session_id=session_id,\n",
-        "    )\n",
-        "    for log in EventLogger().log(response):\n",
-        "        log.print()\n"
+        "from rich.pretty import pprint\n",
+        "for toolgroup in client.toolgroups.list():\n",
+        "    pprint(toolgroup)"
       ]
     },
     {
@@ -1552,52 +1879,41 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
-      "id": "HZPPv6nfytK7",
-      "metadata": {
-        "id": "HZPPv6nfytK7"
-      },
-      "outputs": [],
-      "source": [
-        "search_tool = {\n",
-        "    \"type\": \"brave_search\",\n",
-        "    \"engine\": \"tavily\",\n",
-        "    \"api_key\": userdata.get(\"TAVILY_SEARCH_API_KEY\"),\n",
-        "}\n"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 12,
       "id": "WS8Gu5b0APHs",
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
         "id": "WS8Gu5b0APHs",
-        "outputId": "48c3df89-4103-468a-f6f6-fc116d177380"
+        "outputId": "ec38efab-ca5b-478f-94b6-fd65a3cb3bb9"
       },
       "outputs": [
         {
           "name": "stdout",
           "output_type": "stream",
           "text": [
-            "User> Hello\n",
-            "inference> Hello! How can I assist you today?\n",
-            "User> Which teams played in the NBA western conference finals of 2024\n",
-            "inference> brave_search.call(query=\"NBA Western Conference Finals 2024 teams\")\n",
-            "tool_execution> Tool:brave_search Args:{'query': 'NBA Western Conference Finals 2024 teams'}\n",
-            "tool_execution> Tool:brave_search Response:{\"query\": \"NBA Western Conference Finals 2024 teams\", \"top_k\": [{\"title\": \"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\", \"url\": \"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\", \"content\": \"NBA Western Conference Finals 2024: Dates & Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\", \"score\": 0.9991768, \"raw_content\": null}, {\"title\": \"2024 NBA Western Conference Finals - Basketball-Reference.com\", \"url\": \"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\", \"content\": \"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown (20.8 / 5.4 / 5.0) 2024 Playoff Leaders: PTS: Luka Don\\u010di\\u0107 (635) TRB: Luka Don\\u010di\\u0107 (208) AST: Luka Don\\u010di\\u0107 (178) WS: Derrick White (2.9) More playoffs info\", \"score\": 0.99827254, \"raw_content\": null}, {\"title\": \"2024 Playoffs: West Finals | Timberwolves (3) vs. Mavericks (5) - NBA.com\", \"url\": \"https://www.nba.com/playoffs/2024/west-final\", \"content\": \"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\", \"score\": 0.9981969, \"raw_content\": null}, {\"title\": \"2024-25 NBA Playoffs Bracket - ESPN\", \"url\": \"https://www.espn.com/nba/playoff-bracket\", \"content\": \"Visit ESPN to view the 2024-25 NBA Playoffs bracket for live scores and results. ... Teams. Odds. NBA Cup Bracket ... Western Conference. OKC wins series 4-0. 1. Thunder. 97. 8.\", \"score\": 0.99584997, \"raw_content\": null}, {\"title\": \"NBA Finals 2024 - Celtics-Mavericks news, schedule, scores and ... - ESPN\", \"url\": \"https://www.espn.com/nba/story/_/id/39943302/nba-playoffs-2024-conference-finals-news-scores-highlights\", \"content\": \"The Boston Celtics are the 2024 NBA Champions. ... Western Conference. Final 2023-24 NBA regular-season standings. Which team left standing has the most trips to the NBA Finals? Here is a look at\", \"score\": 0.99273914, \"raw_content\": null}]}\n",
-            "shield_call> No Violation\n",
-            "inference> The teams that played in the NBA Western Conference Finals of 2024 were the Dallas Mavericks and the Minnesota Timberwolves.\n"
+            "\u001b[32mUser> Hello\u001b[0m\n",
+            "\u001b[30m\u001b[0m\u001b[33minference> \u001b[0m\u001b[33mHello\u001b[0m\u001b[33m.\u001b[0m\u001b[33m How\u001b[0m\u001b[33m can\u001b[0m\u001b[33m I\u001b[0m\u001b[33m assist\u001b[0m\u001b[33m you\u001b[0m\u001b[33m today\u001b[0m\u001b[33m?\u001b[0m\u001b[97m\u001b[0m\n",
+            "\u001b[30m\u001b[0m\u001b[32mUser> Which teams played in the NBA western conference finals of 2024\u001b[0m\n",
+            "\u001b[30m\u001b[0m\u001b[33minference> \u001b[0m\u001b[36m\u001b[0m\u001b[36mbr\u001b[0m\u001b[36mave\u001b[0m\u001b[36m_search\u001b[0m\u001b[36m.call\u001b[0m\u001b[36m(query\u001b[0m\u001b[36m=\"\u001b[0m\u001b[36mN\u001b[0m\u001b[36mBA\u001b[0m\u001b[36m Western\u001b[0m\u001b[36m Conference\u001b[0m\u001b[36m Finals\u001b[0m\u001b[36m \u001b[0m\u001b[36m202\u001b[0m\u001b[36m4\u001b[0m\u001b[36m teams\u001b[0m\u001b[36m\")\u001b[0m\u001b[97m\u001b[0m\n",
+            "\u001b[32mtool_execution> Tool:brave_search Args:{'query': 'NBA Western Conference Finals 2024 teams'}\u001b[0m\n",
+            "\u001b[32mtool_execution> Tool:brave_search Response:{\"query\": \"NBA Western Conference Finals 2024 teams\", \"top_k\": [{\"title\": \"2024 NBA Western Conference Finals - Basketball-Reference.com\", \"url\": \"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\", \"content\": \"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown (20.8 / 5.4 / 5.0) 2024 Playoff Leaders: PTS: Luka Don\\u010di\\u0107 (635) TRB: Luka Don\\u010di\\u0107 (208) AST: Luka Don\\u010di\\u0107 (178) WS: Derrick White (2.9) More playoffs info\", \"score\": 0.9310187, \"raw_content\": null}, {\"title\": \"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\", \"url\": \"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\", \"content\": \"NBA Western Conference Finals 2024: Dates & Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\", \"score\": 0.8914433, \"raw_content\": null}, {\"title\": \"2024 Playoffs: West Finals | Timberwolves (3) vs. Mavericks (5) - NBA.com\", \"url\": \"https://www.nba.com/playoffs/2024/west-final\", \"content\": \"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\", \"score\": 0.8884594, \"raw_content\": null}, {\"title\": \"NBA Conference Finals Schedule: Full List of Games & Results\", \"url\": \"https://www.si.com/nba/nba-conference-finals-schedule-full-list-of-games-results\", \"content\": \"The 2024 NBA conference finals matchups are set. Here's the schedule for all the games. ... Western Conference First Round (1) Oklahoma City Thunder def. (8) New Orleans Pelicans in 4 games\", \"score\": 0.850382, \"raw_content\": null}, {\"title\": \"NBA Finals 2024 - Celtics-Mavericks news, schedule, scores and ... - ESPN\", \"url\": \"https://www.espn.com/nba/story/_/id/39943302/nba-playoffs-2024-conference-finals-news-scores-highlights\", \"content\": \"The Boston Celtics are the 2024 NBA Champions. ... Western Conference. Final 2023-24 NBA regular-season standings. Which team left standing has the most trips to the NBA Finals? Here is a look at\", \"score\": 0.8194462, \"raw_content\": null}]}\u001b[0m\n",
+            "\u001b[33minference> \u001b[0m\u001b[33mThe\u001b[0m\u001b[33m teams\u001b[0m\u001b[33m that\u001b[0m\u001b[33m played\u001b[0m\u001b[33m in\u001b[0m\u001b[33m the\u001b[0m\u001b[33m NBA\u001b[0m\u001b[33m Western\u001b[0m\u001b[33m Conference\u001b[0m\u001b[33m Finals\u001b[0m\u001b[33m of\u001b[0m\u001b[33m \u001b[0m\u001b[33m202\u001b[0m\u001b[33m4\u001b[0m\u001b[33m were\u001b[0m\u001b[33m the\u001b[0m\u001b[33m Dallas\u001b[0m\u001b[33m Mavericks\u001b[0m\u001b[33m and\u001b[0m\u001b[33m the\u001b[0m\u001b[33m Minnesota\u001b[0m\u001b[33m Timber\u001b[0m\u001b[33mw\u001b[0m\u001b[33molves\u001b[0m\u001b[33m.\u001b[0m\u001b[97m\u001b[0m\n",
+            "\u001b[30m\u001b[0m"
           ]
         }
       ],
       "source": [
+        "from llama_stack_client.lib.agents.agent import Agent\n",
+        "from llama_stack_client.lib.agents.event_logger import EventLogger\n",
+        "from llama_stack_client.types.agent_create_params import AgentConfig\n",
+        "from termcolor import cprint\n",
+        "\n",
         "agent_config = AgentConfig(\n",
         "    model=model_id,\n",
         "    instructions=\"You are a helpful assistant\",\n",
-        "    tools=[search_tool],\n",
+        "    toolgroups=[\"builtin::websearch\"],\n",
         "    input_shields=[],\n",
         "    output_shields=[],\n",
         "    enable_session_persistence=False,\n",
@@ -1624,6 +1940,206 @@
         "        log.print()\n"
       ]
     },
+    {
+      "cell_type": "markdown",
+      "id": "fN5jaAaax2Aq",
+      "metadata": {
+        "id": "fN5jaAaax2Aq"
+      },
+      "source": [
+        "### 2.3. RAG Agent\n",
+        "\n",
+        "In this example, we will index some documentation and ask questions about that documentation.\n",
+        "\n",
+        "The tool we use is the memory tool. Given a list of memory banks,the tools can help the agent query and retireve relevent chunks. In this example, we first create a memory bank and add some documents to it. Then configure the agent to use the memory tool. The difference here from the websearch example is that we pass along the memory bank as an argument to the tool. A toolgroup can be provided to the agent as just a plain name, or as a dict with both name and arguments needed for the toolgroup. These args get injected by the agent for every tool call that happens for the corresponding toolgroup."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 14,
+      "id": "GvLWltzZCNkg",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 351,
+          "referenced_widgets": [
+            "edc4d84302f746d39a43e8107af6b67b",
+            "980292182c7144e194604c13ac544a26",
+            "8dee873065a047799a04e49ab791e449",
+            "29683ef34d5646c687118a2a0cdec6d4",
+            "3ec694106303491ea112a257309bc69c",
+            "288c9da81b3c4d80a4959753da973f58",
+            "cf453a1ed54645aba656f9a3f1461e69",
+            "ec747bd7c37c45298896c513634cd59a",
+            "5a620017a5384af1a056de687b2670db",
+            "8d370762fafd4d7887ff68ea8279d083",
+            "b6a0eb553b024a71b737ff47ca8f7633",
+            "2eff72cbd9bb4f1ca77213602caa9417",
+            "e82b5196209f4b9f919c7abb402a4504",
+            "fe34706489c14253a5015ff6332ec4e0",
+            "2574b07e4af24715aa89d048cc84e358",
+            "10bc8be68b5545fd8609824b02499ebf",
+            "d2473b7a6c5b4483981516af2fc59bde",
+            "4282ee7d947e426ba863df9970e82f3f",
+            "cfe6be8fd8254bc084a81b1d06e86ae1",
+            "1817f6732a5f44c7adc75a644b1acef2",
+            "7551b282ef3a4387a801637de2d5c76e",
+            "69e5263c812c4542a9e5c31fefaa37fe",
+            "7cc356ed20e94401b72a0e138ad0f5df",
+            "acd39276db17439798a97abc56460b0f",
+            "bda474c3b8184597a6a9bc6da0672a50",
+            "20a66f9de4ed41c7ac9a8e817898ed9e",
+            "e662ba10fbae49d9b66172125dfc0717",
+            "d452b32c54e14e41a17fd7d51862ba8e",
+            "d1f8f4568a444248b69022d58e3f1af0",
+            "0c2e30d78c234b1b8098d879442d3bac",
+            "9bb8bf12010f42b2b17c10c7ccaa7bf8",
+            "2b2046db907349798e3ae774c15b25d2",
+            "3c18f449359f422f950543bd976fe323",
+            "472b1acc4c5a4c48b2ec62be42d1830c",
+            "44e34588d6854737b0fb14b4b6a62a95",
+            "03402ad03418435ca7a550e3246cd300",
+            "811f115733b14ab4b242a8b11526016c",
+            "e61fdef1dc4b4d809168c0b441b0e6ac",
+            "631c9a95127244c79875c829a7637df6",
+            "d25492ad867141bfa8d957d2464b8639",
+            "9df914248c214597bed7d7980c7a0afe",
+            "4709067f3f554b93b3ef35e3f58cbf85",
+            "02baf670942347d69c290452de8641e4",
+            "7611cfc7965649ba88ca57c1a9f9ccf3",
+            "15ae23892b634a9f821a8fcee14e500b",
+            "b28d46c2ecdd46b9b3f2da871afbf1cb",
+            "4b83e3caa8ec47169dca04ee9599adeb",
+            "c83c23161674484e81f0db9856c23eb6",
+            "3ded85d9c34246e88f8ce693eb8025e5",
+            "0ac8e976a32c4f5989392b8088546e00",
+            "ed4b0035752546cc81688a7a77ba27c0",
+            "269b1ad9dc7b4ebb94d7364c75f3f324",
+            "2256ddab0ae1408abb10ba211a08f794",
+            "42335bcbc6ee40a79d36c5159cc7da06",
+            "cf694e1b797246b096ae588973dc985f",
+            "3e764c00c08942caa2ccb6b92ee60a4e",
+            "af6680f2e60e476d8487aea98a23b84e",
+            "c26a9d456e904b2b900bf5e0a5964a0d",
+            "5a3e0b5ae83143329de6507f9bcf83e0",
+            "3c9bc5588765436da4f1fee2d893cafd"
+          ]
+        },
+        "id": "GvLWltzZCNkg",
+        "outputId": "ef5f3ec4-edaf-4705-fb1b-b86659d7143c"
+      },
+      "outputs": [
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "Batches: 100%|██████████| 1/1 [00:00<00:00,  1.83it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "\u001b[32mUser> What are the top 5 topics that were explained? Only list succinct bullet points.\u001b[0m\n",
+            "\u001b[30m\u001b[0m"
+          ]
+        },
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "\n",
+            "Batches: 100%|██████████| 1/1 [00:00<00:00,  7.28it/s]"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "\u001b[32mtool_execution> Tool:query_from_memory Args:{}\u001b[0m\n",
+            "\u001b[36mtool_execution> fetched 10913 bytes from memory\u001b[0m\n",
+            "\u001b[33minference> \u001b[0m"
+          ]
+        },
+        {
+          "name": "stderr",
+          "output_type": "stream",
+          "text": [
+            "\n"
+          ]
+        },
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "\u001b[33mHere\u001b[0m\u001b[33m are\u001b[0m\u001b[33m the\u001b[0m\u001b[33m top\u001b[0m\u001b[33m \u001b[0m\u001b[33m5\u001b[0m\u001b[33m topics\u001b[0m\u001b[33m that\u001b[0m\u001b[33m were\u001b[0m\u001b[33m explained\u001b[0m\u001b[33m:\n",
+            "\n",
+            "\u001b[0m\u001b[33m•\u001b[0m\u001b[33m Token\u001b[0m\u001b[33mizing\u001b[0m\u001b[33m prompt\u001b[0m\u001b[33m templates\u001b[0m\u001b[33m and\u001b[0m\u001b[33m special\u001b[0m\u001b[33m tokens\u001b[0m\u001b[33m\n",
+            "\u001b[0m\u001b[33m•\u001b[0m\u001b[33m Fine\u001b[0m\u001b[33m-t\u001b[0m\u001b[33muning\u001b[0m\u001b[33m on\u001b[0m\u001b[33m a\u001b[0m\u001b[33m custom\u001b[0m\u001b[33m chat\u001b[0m\u001b[33m dataset\u001b[0m\u001b[33m\n",
+            "\u001b[0m\u001b[33m•\u001b[0m\u001b[33m Using\u001b[0m\u001b[33m the\u001b[0m\u001b[33m L\u001b[0m\u001b[33mlama\u001b[0m\u001b[33m2\u001b[0m\u001b[33mChat\u001b[0m\u001b[33mTemplate\u001b[0m\u001b[33m class\u001b[0m\u001b[33m\n",
+            "\u001b[0m\u001b[33m•\u001b[0m\u001b[33m Formatting\u001b[0m\u001b[33m messages\u001b[0m\u001b[33m with\u001b[0m\u001b[33m the\u001b[0m\u001b[33m L\u001b[0m\u001b[33mlama\u001b[0m\u001b[33m2\u001b[0m\u001b[33mChat\u001b[0m\u001b[33mTemplate\u001b[0m\u001b[33m class\u001b[0m\u001b[33m\n",
+            "\u001b[0m\u001b[33m•\u001b[0m\u001b[33m Creating\u001b[0m\u001b[33m a\u001b[0m\u001b[33m custom\u001b[0m\u001b[33m dataset\u001b[0m\u001b[33m for\u001b[0m\u001b[33m fine\u001b[0m\u001b[33m-t\u001b[0m\u001b[33muning\u001b[0m\u001b[33m L\u001b[0m\u001b[33mlama\u001b[0m\u001b[33m3\u001b[0m\u001b[97m\u001b[0m\n",
+            "\u001b[30m\u001b[0m"
+          ]
+        }
+      ],
+      "source": [
+        "from llama_stack_client.lib.agents.agent import Agent\n",
+        "from llama_stack_client.lib.agents.event_logger import EventLogger\n",
+        "from llama_stack_client.types.agent_create_params import AgentConfig\n",
+        "from termcolor import cprint\n",
+        "from llama_stack_client.types import Document\n",
+        "\n",
+        "urls = [\"chat.rst\", \"llama3.rst\", \"datasets.rst\", \"lora_finetune.rst\"]\n",
+        "documents = [\n",
+        "    Document(\n",
+        "        document_id=f\"num-{i}\",\n",
+        "        content=f\"https://raw.githubusercontent.com/pytorch/torchtune/main/docs/source/tutorials/{url}\",\n",
+        "        mime_type=\"text/plain\",\n",
+        "        metadata={},\n",
+        "    )\n",
+        "    for i, url in enumerate(urls)\n",
+        "]\n",
+        "\n",
+        "vector_db_id = \"test-vector-db\"\n",
+        "client.vector_dbs.register(\n",
+        "    vector_db_id=vector_db_id,\n",
+        "    embedding_model=\"all-MiniLM-L6-v2\",\n",
+        "    embedding_dimension=384,\n",
+        ")\n",
+        "client.tool_runtime.rag_tool.insert(\n",
+        "    documents=documents,\n",
+        "    vector_db_id=vector_db_id,\n",
+        "    chunk_size_in_tokens=512,\n",
+        ")\n",
+        "agent_config = AgentConfig(\n",
+        "    model=model_id,\n",
+        "    instructions=\"You are a helpful assistant\",\n",
+        "    enable_session_persistence=False,\n",
+        "    toolgroups = [\n",
+        "        {\n",
+        "          \"name\": \"builtin::rag\",\n",
+        "          \"args\" : {\n",
+        "            \"vector_db_ids\": [vector_db_id],\n",
+        "          }\n",
+        "        }\n",
+        "    ],\n",
+        ")\n",
+        "rag_agent = Agent(client, agent_config)\n",
+        "session_id = rag_agent.create_session(\"test-session\")\n",
+        "user_prompts = [\n",
+        "        \"What are the top 5 topics that were explained? Only list succinct bullet points.\",\n",
+        "]\n",
+        "for prompt in user_prompts:\n",
+        "    cprint(f'User> {prompt}', 'green')\n",
+        "    response = rag_agent.create_turn(\n",
+        "        messages=[{\"role\": \"user\", \"content\": prompt}],\n",
+        "        session_id=session_id,\n",
+        "    )\n",
+        "    for log in EventLogger().log(response):\n",
+        "        log.print()"
+      ]
+    },
     {
       "cell_type": "markdown",
       "id": "yRzRwu8qxyl0",
@@ -1631,14 +2147,14 @@
         "id": "yRzRwu8qxyl0"
       },
       "source": [
-        "### 2.3. Code Execution Agent\n",
+        "### 2.4. Code Execution Agent\n",
         "\n",
         "In this example, we will show how multiple tools can be called by the model - including web search and code execution. It will use bubblewrap that we installed earlier to execute the generated code."
       ]
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 13,
       "id": "GvVRuhO-GOov",
       "metadata": {
         "colab": {
@@ -1646,160 +2162,135 @@
         },
         "collapsed": true,
         "id": "GvVRuhO-GOov",
-        "outputId": "cb988aa9-568b-4966-d500-575b7b24578f"
+        "outputId": "39395e26-bb7d-4616-d51d-036c8bf41427"
       },
       "outputs": [
         {
           "name": "stdout",
           "output_type": "stream",
           "text": [
-            "User> ('Here is a csv, can you describe it ?', [Attachment(content='https://raw.githubusercontent.com/meta-llama/llama-stack-apps/main/examples/resources/inflation.csv', mime_type='test/csv')])\n"
-          ]
-        },
-        {
-          "name": "stderr",
-          "output_type": "stream",
-          "text": [
-            "INFO:httpx:HTTP Request: GET https://raw.githubusercontent.com/meta-llama/llama-stack-apps/main/examples/resources/inflation.csv \"HTTP/1.1 200 OK\"\n"
-          ]
-        },
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "inference> import pandas as pd\n",
-            "\n",
-            "# Read the CSV file\n",
-            "df = pd.read_csv('/tmp/tmpco0s0o4_/LOdZoVp1inflation.csv')\n",
-            "\n",
-            "# Describe the CSV\n",
-            "print(df.describe())\n",
-            "tool_execution> Tool:code_interpreter Args:{'code': \"import pandas as pd\\n\\n# Read the CSV file\\ndf = pd.read_csv('/tmp/tmpco0s0o4_/LOdZoVp1inflation.csv')\\n\\n# Describe the CSV\\nprint(df.describe())\"}\n",
-            "tool_execution> Tool:code_interpreter Response:completed\n",
+            "\u001b[32mUser> Here is a csv, can you describe it?\u001b[0m\n",
+            "\u001b[30m\u001b[0m\u001b[33minference> \u001b[0m\u001b[36m\u001b[0m\u001b[36mimport\u001b[0m\u001b[36m pandas\u001b[0m\u001b[36m as\u001b[0m\u001b[36m pd\u001b[0m\u001b[36m\n",
+            "\u001b[0m\u001b[36m#\u001b[0m\u001b[36m Load\u001b[0m\u001b[36m data\u001b[0m\u001b[36m\n",
+            "\u001b[0m\u001b[36mdf\u001b[0m\u001b[36m =\u001b[0m\u001b[36m pd\u001b[0m\u001b[36m.read\u001b[0m\u001b[36m_csv\u001b[0m\u001b[36m('/\u001b[0m\u001b[36mvar\u001b[0m\u001b[36m/f\u001b[0m\u001b[36molders\u001b[0m\u001b[36m/m\u001b[0m\u001b[36mj\u001b[0m\u001b[36m/t\u001b[0m\u001b[36m_st\u001b[0m\u001b[36mv\u001b[0m\u001b[36m1\u001b[0m\u001b[36mys\u001b[0m\u001b[36m763\u001b[0m\u001b[36m7\u001b[0m\u001b[36mv\u001b[0m\u001b[36mq\u001b[0m\u001b[36mf\u001b[0m\u001b[36m2\u001b[0m\u001b[36m_b\u001b[0m\u001b[36m4\u001b[0m\u001b[36my\u001b[0m\u001b[36mf\u001b[0m\u001b[36m67\u001b[0m\u001b[36mm\u001b[0m\u001b[36m000\u001b[0m\u001b[36m0\u001b[0m\u001b[36mgn\u001b[0m\u001b[36m/T\u001b[0m\u001b[36m/tmp\u001b[0m\u001b[36mq\u001b[0m\u001b[36m2\u001b[0m\u001b[36mw\u001b[0m\u001b[36mjj\u001b[0m\u001b[36mmg\u001b[0m\u001b[36mf\u001b[0m\u001b[36m/s\u001b[0m\u001b[36mQ\u001b[0m\u001b[36mAm\u001b[0m\u001b[36muk\u001b[0m\u001b[36mV\u001b[0m\u001b[36mbin\u001b[0m\u001b[36mflation\u001b[0m\u001b[36m.csv\u001b[0m\u001b[36m')\n",
+            "\u001b[0m\u001b[36m#\u001b[0m\u001b[36m Set\u001b[0m\u001b[36m options\u001b[0m\u001b[36m\n",
+            "\u001b[0m\u001b[36mpd\u001b[0m\u001b[36m.set\u001b[0m\u001b[36m_option\u001b[0m\u001b[36m('\u001b[0m\u001b[36mdisplay\u001b[0m\u001b[36m.max\u001b[0m\u001b[36m_columns\u001b[0m\u001b[36m',\u001b[0m\u001b[36m None\u001b[0m\u001b[36m)\n",
+            "\u001b[0m\u001b[36mpd\u001b[0m\u001b[36m.set\u001b[0m\u001b[36m_option\u001b[0m\u001b[36m('\u001b[0m\u001b[36mdisplay\u001b[0m\u001b[36m.max\u001b[0m\u001b[36m_rows\u001b[0m\u001b[36m',\u001b[0m\u001b[36m None\u001b[0m\u001b[36m)\n",
+            "\u001b[0m\u001b[36m#\u001b[0m\u001b[36m Describe\u001b[0m\u001b[36m the\u001b[0m\u001b[36m data\u001b[0m\u001b[36m\n",
+            "\u001b[0m\u001b[36mprint\u001b[0m\u001b[36m(df\u001b[0m\u001b[36m.describe\u001b[0m\u001b[36m())\u001b[0m\u001b[97m\u001b[0m\n",
+            "\u001b[32mtool_execution> Tool:code_interpreter Args:{'code': \"import pandas as pd\\n# Load data\\ndf = pd.read_csv('/var/folders/mj/t_stv1ys7637vqf2_b4yf67m0000gn/T/tmpq2wjjmgf/sQAmukVbinflation.csv')\\n# Set options\\npd.set_option('display.max_columns', None)\\npd.set_option('display.max_rows', None)\\n# Describe the data\\nprint(df.describe())\"}\u001b[0m\n",
+            "\u001b[32mtool_execution> Tool:code_interpreter Response:error\n",
             "[stdout]\n",
-            "Year        Jan        Feb        Mar  ...        Sep        Oct        Nov        Dec\n",
-            "count    10.00000  10.000000  10.000000  10.000000  ...  10.000000  10.000000  10.000000  10.000000\n",
-            "mean   2018.50000   2.700000   2.730000   2.760000  ...   2.850000   2.850000   2.850000   2.890000\n",
-            "std       3.02765   1.667999   1.743591   1.757018  ...   1.593912   1.577093   1.551523   1.569466\n",
-            "min    2014.00000   1.400000   1.300000   1.600000  ...   1.700000   1.600000   1.600000   1.600000\n",
-            "25%    2016.25000   1.650000   1.725000   1.850000  ...   1.750000   1.825000   1.775000   1.875000\n",
-            "50%    2018.50000   2.200000   2.150000   2.050000  ...   2.200000   2.100000   2.150000   2.200000\n",
-            "75%    2020.75000   2.300000   2.375000   2.175000  ...   3.600000   3.575000   3.575000   3.500000\n",
-            "max    2023.00000   6.000000   6.400000   6.500000  ...   6.600000   6.300000   6.000000   5.700000\n",
-            "\n",
-            "[8 rows x 13 columns]\n",
+            "[Errno 2] No such file or directory: 'bwrap'\n",
             "[/stdout]\n",
-            "shield_call> No Violation\n",
-            "inference> The CSV file appears to be a dataset with 10 rows and 13 columns. The columns represent various economic indicators, such as inflation rates for each month from January to December, as well as year (yearly inflation rate).\n",
+            "[stderr]\n",
+            "[Errno 2] No such file or directory: 'bwrap'\n",
+            "[/stderr]\u001b[0m\n",
+            "\u001b[33minference> \u001b[0m\u001b[33mIt\u001b[0m\u001b[33m seems\u001b[0m\u001b[33m that\u001b[0m\u001b[33m there\u001b[0m\u001b[33m was\u001b[0m\u001b[33m an\u001b[0m\u001b[33m issue\u001b[0m\u001b[33m with\u001b[0m\u001b[33m accessing\u001b[0m\u001b[33m the\u001b[0m\u001b[33m file\u001b[0m\u001b[33m.\u001b[0m\u001b[33m I\u001b[0m\u001b[33m'm\u001b[0m\u001b[33m a\u001b[0m\u001b[33m large\u001b[0m\u001b[33m language\u001b[0m\u001b[33m model\u001b[0m\u001b[33m,\u001b[0m\u001b[33m I\u001b[0m\u001b[33m don\u001b[0m\u001b[33m't\u001b[0m\u001b[33m have\u001b[0m\u001b[33m the\u001b[0m\u001b[33m ability\u001b[0m\u001b[33m to\u001b[0m\u001b[33m access\u001b[0m\u001b[33m or\u001b[0m\u001b[33m read\u001b[0m\u001b[33m files\u001b[0m\u001b[33m from\u001b[0m\u001b[33m your\u001b[0m\u001b[33m local\u001b[0m\u001b[33m system\u001b[0m\u001b[33m.\u001b[0m\u001b[33m However\u001b[0m\u001b[33m,\u001b[0m\u001b[33m I\u001b[0m\u001b[33m can\u001b[0m\u001b[33m guide\u001b[0m\u001b[33m you\u001b[0m\u001b[33m on\u001b[0m\u001b[33m how\u001b[0m\u001b[33m to\u001b[0m\u001b[33m describe\u001b[0m\u001b[33m a\u001b[0m\u001b[33m CSV\u001b[0m\u001b[33m file\u001b[0m\u001b[33m using\u001b[0m\u001b[33m Python\u001b[0m\u001b[33m's\u001b[0m\u001b[33m pandas\u001b[0m\u001b[33m library\u001b[0m\u001b[33m.\n",
             "\n",
-            "Here is a brief description of the data:\n",
+            "\u001b[0m\u001b[33mTo\u001b[0m\u001b[33m describe\u001b[0m\u001b[33m a\u001b[0m\u001b[33m CSV\u001b[0m\u001b[33m file\u001b[0m\u001b[33m,\u001b[0m\u001b[33m you\u001b[0m\u001b[33m can\u001b[0m\u001b[33m use\u001b[0m\u001b[33m the\u001b[0m\u001b[33m `\u001b[0m\u001b[33mp\u001b[0m\u001b[33mandas\u001b[0m\u001b[33m`\u001b[0m\u001b[33m library\u001b[0m\u001b[33m in\u001b[0m\u001b[33m Python\u001b[0m\u001b[33m.\u001b[0m\u001b[33m Here\u001b[0m\u001b[33m's\u001b[0m\u001b[33m a\u001b[0m\u001b[33m step\u001b[0m\u001b[33m-by\u001b[0m\u001b[33m-step\u001b[0m\u001b[33m guide\u001b[0m\u001b[33m:\n",
             "\n",
-            "*   The `Year` column contains the year for which the inflation rate is reported.\n",
-            "*   The `Jan`, `Feb`, `Mar`, etc. columns contain the inflation rate for each month (January to December).\n",
-            "*   The `count` column is the count of non-null values in each column.\n",
-            "*   The `mean` column is the mean of the non-null values in each column.\n",
-            "*   The `std` column is the standard deviation of the non-null values in each column.\n",
-            "*   The `min` column is the minimum value in each column.\n",
-            "*   The `25%` column is the 25th percentile (25th percentile) of the non-null values in each column.\n",
-            "*   The `50%` column is the 50th percentile (50th percentile) of the non-null values in each column.\n",
-            "*   The `75%` column is the 75th percentile (75th percentile) of the non-null values in each column.\n",
-            "*   The `max` column is the maximum value in each column.\n",
+            "\u001b[0m\u001b[33m1\u001b[0m\u001b[33m.\u001b[0m\u001b[33m Install\u001b[0m\u001b[33m the\u001b[0m\u001b[33m `\u001b[0m\u001b[33mp\u001b[0m\u001b[33mandas\u001b[0m\u001b[33m`\u001b[0m\u001b[33m library\u001b[0m\u001b[33m if\u001b[0m\u001b[33m you\u001b[0m\u001b[33m haven\u001b[0m\u001b[33m't\u001b[0m\u001b[33m already\u001b[0m\u001b[33m:\u001b[0m\u001b[33m `\u001b[0m\u001b[33mpip\u001b[0m\u001b[33m install\u001b[0m\u001b[33m pandas\u001b[0m\u001b[33m`\n",
+            "\u001b[0m\u001b[33m2\u001b[0m\u001b[33m.\u001b[0m\u001b[33m Import\u001b[0m\u001b[33m the\u001b[0m\u001b[33m `\u001b[0m\u001b[33mp\u001b[0m\u001b[33mandas\u001b[0m\u001b[33m`\u001b[0m\u001b[33m library\u001b[0m\u001b[33m:\u001b[0m\u001b[33m `\u001b[0m\u001b[33mimport\u001b[0m\u001b[33m pandas\u001b[0m\u001b[33m as\u001b[0m\u001b[33m pd\u001b[0m\u001b[33m`\n",
+            "\u001b[0m\u001b[33m3\u001b[0m\u001b[33m.\u001b[0m\u001b[33m Load\u001b[0m\u001b[33m the\u001b[0m\u001b[33m CSV\u001b[0m\u001b[33m file\u001b[0m\u001b[33m into\u001b[0m\u001b[33m a\u001b[0m\u001b[33m DataFrame\u001b[0m\u001b[33m:\u001b[0m\u001b[33m `\u001b[0m\u001b[33mdf\u001b[0m\u001b[33m =\u001b[0m\u001b[33m pd\u001b[0m\u001b[33m.read\u001b[0m\u001b[33m_csv\u001b[0m\u001b[33m('\u001b[0m\u001b[33myour\u001b[0m\u001b[33m_file\u001b[0m\u001b[33m.csv\u001b[0m\u001b[33m')\u001b[0m\u001b[33m`\n",
+            "\u001b[0m\u001b[33m4\u001b[0m\u001b[33m.\u001b[0m\u001b[33m Use\u001b[0m\u001b[33m the\u001b[0m\u001b[33m `\u001b[0m\u001b[33mdescribe\u001b[0m\u001b[33m()`\u001b[0m\u001b[33m method\u001b[0m\u001b[33m to\u001b[0m\u001b[33m get\u001b[0m\u001b[33m a\u001b[0m\u001b[33m summary\u001b[0m\u001b[33m of\u001b[0m\u001b[33m the\u001b[0m\u001b[33m data\u001b[0m\u001b[33m:\u001b[0m\u001b[33m `\u001b[0m\u001b[33mprint\u001b[0m\u001b[33m(df\u001b[0m\u001b[33m.describe\u001b[0m\u001b[33m())\u001b[0m\u001b[33m`\n",
             "\n",
-            "This dataset could be used for various applications, such as analyzing historical inflation rates, forecasting future inflation rates, or comparing inflation rates across different months or years.\n",
-            "User> ('Which year ended with the highest inflation ?', None)\n",
-            "inference> According to the data, the year with the highest inflation was 2023. The inflation rate for 2023 is 6.600%.\n",
-            "User> ('What macro economic situations that led to such high inflation in that period?', None)\n",
-            "inference> The high inflation rate in 2023 is likely attributed to a combination of macroeconomic factors, including:\n",
+            "\u001b[0m\u001b[33mThis\u001b[0m\u001b[33m will\u001b[0m\u001b[33m give\u001b[0m\u001b[33m you\u001b[0m\u001b[33m a\u001b[0m\u001b[33m summary\u001b[0m\u001b[33m of\u001b[0m\u001b[33m the\u001b[0m\u001b[33m data\u001b[0m\u001b[33m,\u001b[0m\u001b[33m including\u001b[0m\u001b[33m the\u001b[0m\u001b[33m count\u001b[0m\u001b[33m,\u001b[0m\u001b[33m mean\u001b[0m\u001b[33m,\u001b[0m\u001b[33m standard\u001b[0m\u001b[33m deviation\u001b[0m\u001b[33m,\u001b[0m\u001b[33m minimum\u001b[0m\u001b[33m,\u001b[0m\u001b[33m \u001b[0m\u001b[33m25\u001b[0m\u001b[33mth\u001b[0m\u001b[33m percentile\u001b[0m\u001b[33m,\u001b[0m\u001b[33m \u001b[0m\u001b[33m50\u001b[0m\u001b[33mth\u001b[0m\u001b[33m percentile\u001b[0m\u001b[33m,\u001b[0m\u001b[33m \u001b[0m\u001b[33m75\u001b[0m\u001b[33mth\u001b[0m\u001b[33m percentile\u001b[0m\u001b[33m,\u001b[0m\u001b[33m and\u001b[0m\u001b[33m maximum\u001b[0m\u001b[33m for\u001b[0m\u001b[33m each\u001b[0m\u001b[33m column\u001b[0m\u001b[33m.\n",
             "\n",
-            "1. **Supply chain disruptions**: The COVID-19 pandemic and subsequent lockdowns led to supply chain disruptions, resulting in shortages and price increases for various goods and services.\n",
-            "2. **Economic growth**: The rapid economic growth in the preceding years created demand for goods and services, leading to higher production costs and, subsequently, higher prices.\n",
-            "3. **Monetary policy**: The central bank's easy-money policies, such as quantitative easing and low interest rates, increased the money supply and led to inflationary pressures.\n",
-            "4. **Commodity price shocks**: Increases in global commodity prices, such as oil and food prices, contributed to higher production costs and inflation.\n",
-            "5. **Labor market tightness**: The labor market has been tight, leading to higher wages and, subsequently, higher production costs, which have been passed on to consumers.\n",
-            "6. **Trade wars and tariffs**: The ongoing trade tensions and tariffs imposed by various countries have disrupted global supply chains, leading to higher prices for imported goods.\n",
-            "7. **Climate change and extreme weather events**: The increasing frequency and severity of extreme weather events, such as heatwaves and droughts, have disrupted agricultural production and supply chains.\n",
-            "8. **Currency devaluation**: A devaluation of the currency can make imports more expensive, leading to higher inflation.\n",
-            "9. **Government spending and fiscal policy**: Government spending and fiscal policy decisions, such as tax cuts and increased government spending, can inject more money into the economy, leading to inflation.\n",
-            "10. **Monetary policy mistakes**: Mistakes in monetary policy, such as premature interest rate hikes or overly aggressive quantitative easing, can lead to inflationary pressures.\n",
+            "\u001b[0m\u001b[33mIf\u001b[0m\u001b[33m you\u001b[0m\u001b[33m provide\u001b[0m\u001b[33m the\u001b[0m\u001b[33m contents\u001b[0m\u001b[33m of\u001b[0m\u001b[33m the\u001b[0m\u001b[33m CSV\u001b[0m\u001b[33m file\u001b[0m\u001b[33m,\u001b[0m\u001b[33m I\u001b[0m\u001b[33m can\u001b[0m\u001b[33m help\u001b[0m\u001b[33m you\u001b[0m\u001b[33m describe\u001b[0m\u001b[33m it\u001b[0m\u001b[33m.\u001b[0m\u001b[97m\u001b[0m\n",
+            "\u001b[30m\u001b[0m\u001b[32mUser> Plot average yearly inflation as a time series\u001b[0m\n",
+            "\u001b[30m\u001b[0m\u001b[33minference> \u001b[0m\u001b[36m\u001b[0m\u001b[36mimport\u001b[0m\u001b[36m pandas\u001b[0m\u001b[36m as\u001b[0m\u001b[36m pd\u001b[0m\u001b[36m\n",
+            "\u001b[0m\u001b[36mimport\u001b[0m\u001b[36m matplotlib\u001b[0m\u001b[36m.pyplot\u001b[0m\u001b[36m as\u001b[0m\u001b[36m plt\u001b[0m\u001b[36m\n",
             "\n",
-            "It's worth noting that the specific factors contributing to the high inflation rate in 2023 may vary depending on the region, country, or even specific economy.\n",
-            "User> ('Plot average yearly inflation as a time series', None)\n",
-            "inference> import pandas as pd\n",
-            "import matplotlib.pyplot as plt\n",
+            "\u001b[0m\u001b[36m#\u001b[0m\u001b[36m Load\u001b[0m\u001b[36m the\u001b[0m\u001b[36m data\u001b[0m\u001b[36m\n",
+            "\u001b[0m\u001b[36mdf\u001b[0m\u001b[36m =\u001b[0m\u001b[36m pd\u001b[0m\u001b[36m.read\u001b[0m\u001b[36m_csv\u001b[0m\u001b[36m('/\u001b[0m\u001b[36mvar\u001b[0m\u001b[36m/f\u001b[0m\u001b[36molders\u001b[0m\u001b[36m/m\u001b[0m\u001b[36mj\u001b[0m\u001b[36m/t\u001b[0m\u001b[36m_st\u001b[0m\u001b[36mv\u001b[0m\u001b[36m1\u001b[0m\u001b[36mys\u001b[0m\u001b[36m763\u001b[0m\u001b[36m7\u001b[0m\u001b[36mv\u001b[0m\u001b[36mq\u001b[0m\u001b[36mf\u001b[0m\u001b[36m2\u001b[0m\u001b[36m_b\u001b[0m\u001b[36m4\u001b[0m\u001b[36my\u001b[0m\u001b[36mf\u001b[0m\u001b[36m67\u001b[0m\u001b[36mm\u001b[0m\u001b[36m000\u001b[0m\u001b[36m0\u001b[0m\u001b[36mgn\u001b[0m\u001b[36m/T\u001b[0m\u001b[36m/tmp\u001b[0m\u001b[36mq\u001b[0m\u001b[36m2\u001b[0m\u001b[36mw\u001b[0m\u001b[36mjj\u001b[0m\u001b[36mmg\u001b[0m\u001b[36mf\u001b[0m\u001b[36m/s\u001b[0m\u001b[36mQ\u001b[0m\u001b[36mAm\u001b[0m\u001b[36muk\u001b[0m\u001b[36mV\u001b[0m\u001b[36mbin\u001b[0m\u001b[36mflation\u001b[0m\u001b[36m.csv\u001b[0m\u001b[36m')\n",
             "\n",
-            "# Read the CSV file\n",
-            "df = pd.read_csv('/tmp/tmpco0s0o4_/LOdZoVp1inflation.csv')\n",
+            "\u001b[0m\u001b[36m#\u001b[0m\u001b[36m Convert\u001b[0m\u001b[36m the\u001b[0m\u001b[36m '\u001b[0m\u001b[36myear\u001b[0m\u001b[36m'\u001b[0m\u001b[36m column\u001b[0m\u001b[36m to\u001b[0m\u001b[36m datetime\u001b[0m\u001b[36m\n",
+            "\u001b[0m\u001b[36mdf\u001b[0m\u001b[36m['\u001b[0m\u001b[36myear\u001b[0m\u001b[36m']\u001b[0m\u001b[36m =\u001b[0m\u001b[36m pd\u001b[0m\u001b[36m.to\u001b[0m\u001b[36m_datetime\u001b[0m\u001b[36m(df\u001b[0m\u001b[36m['\u001b[0m\u001b[36myear\u001b[0m\u001b[36m'])\n",
             "\n",
-            "# Extract the year and inflation rate from the CSV file\n",
-            "df['Year'] = pd.to_datetime(df['Year'], format='%Y')\n",
-            "df = df.rename(columns={'Jan': 'Jan Rate', 'Feb': 'Feb Rate', 'Mar': 'Mar Rate', 'Apr': 'Apr Rate', 'May': 'May Rate', 'Jun': 'Jun Rate', 'Jul': 'Jul Rate', 'Aug': 'Aug Rate', 'Sep': 'Sep Rate', 'Oct': 'Oct Rate', 'Nov': 'Nov Rate', 'Dec': 'Dec Rate'})\n",
+            "\u001b[0m\u001b[36m#\u001b[0m\u001b[36m Group\u001b[0m\u001b[36m by\u001b[0m\u001b[36m year\u001b[0m\u001b[36m and\u001b[0m\u001b[36m calculate\u001b[0m\u001b[36m the\u001b[0m\u001b[36m average\u001b[0m\u001b[36m inflation\u001b[0m\u001b[36m\n",
+            "\u001b[0m\u001b[36maverage\u001b[0m\u001b[36m_in\u001b[0m\u001b[36mflation\u001b[0m\u001b[36m =\u001b[0m\u001b[36m df\u001b[0m\u001b[36m.groupby\u001b[0m\u001b[36m('\u001b[0m\u001b[36myear\u001b[0m\u001b[36m')['\u001b[0m\u001b[36min\u001b[0m\u001b[36mflation\u001b[0m\u001b[36m'].\u001b[0m\u001b[36mmean\u001b[0m\u001b[36m()\n",
             "\n",
-            "# Calculate the average yearly inflation rate\n",
-            "df['Yearly Inflation'] = df[['Jan Rate', 'Feb Rate', 'Mar Rate', 'Apr Rate', 'May Rate', 'Jun Rate', 'Jul Rate', 'Aug Rate', 'Sep Rate', 'Oct Rate', 'Nov Rate', 'Dec Rate']].mean(axis=1)\n",
+            "\u001b[0m\u001b[36m#\u001b[0m\u001b[36m Plot\u001b[0m\u001b[36m the\u001b[0m\u001b[36m average\u001b[0m\u001b[36m yearly\u001b[0m\u001b[36m inflation\u001b[0m\u001b[36m as\u001b[0m\u001b[36m a\u001b[0m\u001b[36m time\u001b[0m\u001b[36m series\u001b[0m\u001b[36m\n",
+            "\u001b[0m\u001b[36mplt\u001b[0m\u001b[36m.figure\u001b[0m\u001b[36m(figsize\u001b[0m\u001b[36m=(\u001b[0m\u001b[36m10\u001b[0m\u001b[36m,\u001b[0m\u001b[36m6\u001b[0m\u001b[36m))\n",
+            "\u001b[0m\u001b[36mplt\u001b[0m\u001b[36m.plot\u001b[0m\u001b[36m(\u001b[0m\u001b[36maverage\u001b[0m\u001b[36m_in\u001b[0m\u001b[36mflation\u001b[0m\u001b[36m.index\u001b[0m\u001b[36m,\u001b[0m\u001b[36m average\u001b[0m\u001b[36m_in\u001b[0m\u001b[36mflation\u001b[0m\u001b[36m.values\u001b[0m\u001b[36m,\u001b[0m\u001b[36m marker\u001b[0m\u001b[36m='\u001b[0m\u001b[36mo\u001b[0m\u001b[36m')\n",
+            "\u001b[0m\u001b[36mplt\u001b[0m\u001b[36m.title\u001b[0m\u001b[36m('\u001b[0m\u001b[36mAverage\u001b[0m\u001b[36m Year\u001b[0m\u001b[36mly\u001b[0m\u001b[36m In\u001b[0m\u001b[36mflation\u001b[0m\u001b[36m')\n",
+            "\u001b[0m\u001b[36mplt\u001b[0m\u001b[36m.xlabel\u001b[0m\u001b[36m('\u001b[0m\u001b[36mYear\u001b[0m\u001b[36m')\n",
+            "\u001b[0m\u001b[36mplt\u001b[0m\u001b[36m.ylabel\u001b[0m\u001b[36m('\u001b[0m\u001b[36mAverage\u001b[0m\u001b[36m In\u001b[0m\u001b[36mflation\u001b[0m\u001b[36m')\n",
+            "\u001b[0m\u001b[36mplt\u001b[0m\u001b[36m.grid\u001b[0m\u001b[36m(True\u001b[0m\u001b[36m)\n",
+            "\u001b[0m\u001b[36mplt\u001b[0m\u001b[36m.show\u001b[0m\u001b[36m()\u001b[0m\u001b[97m\u001b[0m\n",
+            "\u001b[32mtool_execution> Tool:code_interpreter Args:{'code': \"import pandas as pd\\nimport matplotlib.pyplot as plt\\n\\n# Load the data\\ndf = pd.read_csv('/var/folders/mj/t_stv1ys7637vqf2_b4yf67m0000gn/T/tmpq2wjjmgf/sQAmukVbinflation.csv')\\n\\n# Convert the 'year' column to datetime\\ndf['year'] = pd.to_datetime(df['year'])\\n\\n# Group by year and calculate the average inflation\\naverage_inflation = df.groupby('year')['inflation'].mean()\\n\\n# Plot the average yearly inflation as a time series\\nplt.figure(figsize=(10,6))\\nplt.plot(average_inflation.index, average_inflation.values, marker='o')\\nplt.title('Average Yearly Inflation')\\nplt.xlabel('Year')\\nplt.ylabel('Average Inflation')\\nplt.grid(True)\\nplt.show()\"}\u001b[0m\n",
+            "\u001b[32mtool_execution> Tool:code_interpreter Response:error\n",
+            "[stdout]\n",
+            "[Errno 2] No such file or directory: 'bwrap'\n",
+            "[/stdout]\n",
+            "[stderr]\n",
+            "[Errno 2] No such file or directory: 'bwrap'\n",
+            "[/stderr]\u001b[0m\n",
+            "\u001b[33minference> \u001b[0m\u001b[33mIt\u001b[0m\u001b[33m seems\u001b[0m\u001b[33m that\u001b[0m\u001b[33m there\u001b[0m\u001b[33m was\u001b[0m\u001b[33m an\u001b[0m\u001b[33m issue\u001b[0m\u001b[33m with\u001b[0m\u001b[33m accessing\u001b[0m\u001b[33m the\u001b[0m\u001b[33m file\u001b[0m\u001b[33m.\u001b[0m\u001b[33m Since\u001b[0m\u001b[33m I\u001b[0m\u001b[33m don\u001b[0m\u001b[33m't\u001b[0m\u001b[33m have\u001b[0m\u001b[33m the\u001b[0m\u001b[33m ability\u001b[0m\u001b[33m to\u001b[0m\u001b[33m access\u001b[0m\u001b[33m or\u001b[0m\u001b[33m read\u001b[0m\u001b[33m files\u001b[0m\u001b[33m from\u001b[0m\u001b[33m your\u001b[0m\u001b[33m local\u001b[0m\u001b[33m system\u001b[0m\u001b[33m,\u001b[0m\u001b[33m I\u001b[0m\u001b[33m'll\u001b[0m\u001b[33m provide\u001b[0m\u001b[33m a\u001b[0m\u001b[33m general\u001b[0m\u001b[33m solution\u001b[0m\u001b[33m.\n",
             "\n",
-            "# Plot the average yearly inflation rate as a time series\n",
-            "plt.figure(figsize=(10, 6))\n",
-            "plt.plot(df['Year'], df['Yearly Inflation'], marker='o')\n",
-            "plt.title('Average Yearly Inflation Rate')\n",
-            "plt.xlabel('Year')\n",
-            "plt.ylabel('Inflation Rate (%)')\n",
-            "plt.grid(True)\n",
-            "plt.show()\n",
-            "tool_execution> Tool:code_interpreter Args:{'code': \"import pandas as pd\\nimport matplotlib.pyplot as plt\\n\\n# Read the CSV file\\ndf = pd.read_csv('/tmp/tmpco0s0o4_/LOdZoVp1inflation.csv')\\n\\n# Extract the year and inflation rate from the CSV file\\ndf['Year'] = pd.to_datetime(df['Year'], format='%Y')\\ndf = df.rename(columns={'Jan': 'Jan Rate', 'Feb': 'Feb Rate', 'Mar': 'Mar Rate', 'Apr': 'Apr Rate', 'May': 'May Rate', 'Jun': 'Jun Rate', 'Jul': 'Jul Rate', 'Aug': 'Aug Rate', 'Sep': 'Sep Rate', 'Oct': 'Oct Rate', 'Nov': 'Nov Rate', 'Dec': 'Dec Rate'})\\n\\n# Calculate the average yearly inflation rate\\ndf['Yearly Inflation'] = df[['Jan Rate', 'Feb Rate', 'Mar Rate', 'Apr Rate', 'May Rate', 'Jun Rate', 'Jul Rate', 'Aug Rate', 'Sep Rate', 'Oct Rate', 'Nov Rate', 'Dec Rate']].mean(axis=1)\\n\\n# Plot the average yearly inflation rate as a time series\\nplt.figure(figsize=(10, 6))\\nplt.plot(df['Year'], df['Yearly Inflation'], marker='o')\\nplt.title('Average Yearly Inflation Rate')\\nplt.xlabel('Year')\\nplt.ylabel('Inflation Rate (%)')\\nplt.grid(True)\\nplt.show()\"}\n",
-            "tool_execution> Tool:code_interpreter Response:completed\n",
-            "shield_call> No Violation\n",
-            "inference> This code reads the CSV file, extracts the year and inflation rate, calculates the average yearly inflation rate, and plots the average yearly inflation rate as a time series. The resulting plot shows the average inflation rate over the years.\n"
+            "\u001b[0m\u001b[33mTo\u001b[0m\u001b[33m plot\u001b[0m\u001b[33m the\u001b[0m\u001b[33m average\u001b[0m\u001b[33m yearly\u001b[0m\u001b[33m inflation\u001b[0m\u001b[33m as\u001b[0m\u001b[33m a\u001b[0m\u001b[33m time\u001b[0m\u001b[33m series\u001b[0m\u001b[33m,\u001b[0m\u001b[33m you\u001b[0m\u001b[33m'll\u001b[0m\u001b[33m need\u001b[0m\u001b[33m to\u001b[0m\u001b[33m have\u001b[0m\u001b[33m the\u001b[0m\u001b[33m following\u001b[0m\u001b[33m data\u001b[0m\u001b[33m:\n",
+            "\n",
+            "\u001b[0m\u001b[33m-\u001b[0m\u001b[33m A\u001b[0m\u001b[33m column\u001b[0m\u001b[33m with\u001b[0m\u001b[33m the\u001b[0m\u001b[33m year\u001b[0m\u001b[33m\n",
+            "\u001b[0m\u001b[33m-\u001b[0m\u001b[33m A\u001b[0m\u001b[33m column\u001b[0m\u001b[33m with\u001b[0m\u001b[33m the\u001b[0m\u001b[33m inflation\u001b[0m\u001b[33m rate\u001b[0m\u001b[33m for\u001b[0m\u001b[33m each\u001b[0m\u001b[33m year\u001b[0m\u001b[33m\n",
+            "\n",
+            "\u001b[0m\u001b[33mHere\u001b[0m\u001b[33m's\u001b[0m\u001b[33m a\u001b[0m\u001b[33m general\u001b[0m\u001b[33m solution\u001b[0m\u001b[33m:\n",
+            "\n",
+            "\u001b[0m\u001b[33m1\u001b[0m\u001b[33m.\u001b[0m\u001b[33m Load\u001b[0m\u001b[33m the\u001b[0m\u001b[33m data\u001b[0m\u001b[33m into\u001b[0m\u001b[33m a\u001b[0m\u001b[33m pandas\u001b[0m\u001b[33m DataFrame\u001b[0m\u001b[33m.\n",
+            "\u001b[0m\u001b[33m2\u001b[0m\u001b[33m.\u001b[0m\u001b[33m Convert\u001b[0m\u001b[33m the\u001b[0m\u001b[33m '\u001b[0m\u001b[33myear\u001b[0m\u001b[33m'\u001b[0m\u001b[33m column\u001b[0m\u001b[33m to\u001b[0m\u001b[33m datetime\u001b[0m\u001b[33m.\n",
+            "\u001b[0m\u001b[33m3\u001b[0m\u001b[33m.\u001b[0m\u001b[33m Group\u001b[0m\u001b[33m by\u001b[0m\u001b[33m year\u001b[0m\u001b[33m and\u001b[0m\u001b[33m calculate\u001b[0m\u001b[33m the\u001b[0m\u001b[33m average\u001b[0m\u001b[33m inflation\u001b[0m\u001b[33m.\n",
+            "\u001b[0m\u001b[33m4\u001b[0m\u001b[33m.\u001b[0m\u001b[33m Plot\u001b[0m\u001b[33m the\u001b[0m\u001b[33m average\u001b[0m\u001b[33m yearly\u001b[0m\u001b[33m inflation\u001b[0m\u001b[33m as\u001b[0m\u001b[33m a\u001b[0m\u001b[33m time\u001b[0m\u001b[33m series\u001b[0m\u001b[33m using\u001b[0m\u001b[33m matplotlib\u001b[0m\u001b[33m.\n",
+            "\n",
+            "\u001b[0m\u001b[33mIf\u001b[0m\u001b[33m you\u001b[0m\u001b[33m provide\u001b[0m\u001b[33m the\u001b[0m\u001b[33m contents\u001b[0m\u001b[33m of\u001b[0m\u001b[33m the\u001b[0m\u001b[33m CSV\u001b[0m\u001b[33m file\u001b[0m\u001b[33m,\u001b[0m\u001b[33m I\u001b[0m\u001b[33m can\u001b[0m\u001b[33m help\u001b[0m\u001b[33m you\u001b[0m\u001b[33m plot\u001b[0m\u001b[33m the\u001b[0m\u001b[33m average\u001b[0m\u001b[33m yearly\u001b[0m\u001b[33m inflation\u001b[0m\u001b[33m as\u001b[0m\u001b[33m a\u001b[0m\u001b[33m time\u001b[0m\u001b[33m series\u001b[0m\u001b[33m.\u001b[0m\u001b[97m\u001b[0m\n",
+            "\u001b[30m\u001b[0m"
           ]
         }
       ],
       "source": [
+        "from llama_stack_client.types.agents.turn_create_params import Document\n",
+        "\n",
         "agent_config = AgentConfig(\n",
-        "    model=model_id,\n",
+        "    sampling_params = {\n",
+        "        \"max_tokens\" : 4096,\n",
+        "        \"temperature\": 0.0\n",
+        "    },\n",
+        "    model=\"meta-llama/Llama-3.1-8B-Instruct\",\n",
         "    instructions=\"You are a helpful assistant\",\n",
-        "    tools=[\n",
-        "        search_tool,\n",
-        "        {\n",
-        "            \"type\": \"code_interpreter\",\n",
-        "        },\n",
+        "    toolgroups=[\n",
+        "        \"builtin::code_interpreter\",\n",
+        "        \"builtin::websearch\"\n",
         "    ],\n",
-        "    tool_choice=\"required\",\n",
+        "    tool_choice=\"auto\",\n",
         "    input_shields=[],\n",
         "    output_shields=[],\n",
         "    enable_session_persistence=False,\n",
         ")\n",
-        "\n",
         "codex_agent = Agent(client, agent_config)\n",
         "session_id = codex_agent.create_session(\"test-session\")\n",
         "\n",
-        "user_prompts = [\n",
-        "    (\n",
-        "        \"Here is a csv, can you describe it ?\",\n",
-        "        [\n",
-        "            Attachment(\n",
-        "                content=\"https://raw.githubusercontent.com/meta-llama/llama-stack-apps/main/examples/resources/inflation.csv\",\n",
-        "                mime_type=\"test/csv\",\n",
-        "            )\n",
-        "        ],\n",
-        "    ),\n",
-        "    (\"Which year ended with the highest inflation ?\", None),\n",
-        "    (\n",
-        "        \"What macro economic situations that led to such high inflation in that period?\",\n",
-        "        None,\n",
-        "    ),\n",
-        "    (\"Plot average yearly inflation as a time series\", None),\n",
+        "\n",
+        "inflation_doc = Document(\n",
+        "    content=\"https://raw.githubusercontent.com/meta-llama/llama-stack-apps/main/examples/resources/inflation.csv\",\n",
+        "    mime_type=\"text/csv\",\n",
+        ")\n",
+        "\n",
+        "user_input = [\n",
+        "    {\"prompt\": \"Here is a csv, can you describe it?\", \"documents\": [inflation_doc]},\n",
+        "    {\"prompt\": \"Plot average yearly inflation as a time series\"},\n",
         "]\n",
         "\n",
-        "for prompt in user_prompts:\n",
-        "    cprint(f\"User> {prompt}\", \"green\")\n",
+        "for input in user_input:\n",
+        "    cprint(f'User> {input[\"prompt\"]}', 'green')\n",
         "    response = codex_agent.create_turn(\n",
+        "\n",
         "        messages=[\n",
         "            {\n",
         "                \"role\": \"user\",\n",
-        "                \"content\": prompt[0],\n",
+        "                \"content\": input[\"prompt\"],\n",
         "            }\n",
         "        ],\n",
-        "        attachments=prompt[1],\n",
         "        session_id=session_id,\n",
+        "        documents=input.get(\"documents\", None)\n",
         "    )\n",
         "    # for chunk in response:\n",
         "    #     print(chunk)\n",
@@ -1828,12 +2319,12 @@
           "height": 564
         },
         "id": "JqBBVLKdIHHq",
-        "outputId": "4563e803-8385-426b-ec6c-e8b19e2ee6e6"
+        "outputId": "3c89c303-e7c0-4ae2-c271-f34a4d296a85"
       },
       "outputs": [
         {
           "data": {
-            "image/png": 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",
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",
             "text/plain": [
               "<Figure size 1000x600 with 1 Axes>"
             ]
@@ -1843,57 +2334,875 @@
         }
       ],
       "source": [
+        "# NBVAL_SKIP\n",
         "import matplotlib.pyplot as plt\n",
         "import pandas as pd\n",
         "\n",
-        "# Read the CSV file\n",
-        "df = pd.read_csv(\"/tmp/tmpco0s0o4_/LOdZoVp1inflation.csv\")\n",
+        "# Load data\n",
+        "df = pd.read_csv(\"/tmp/tmpvzjigv7g/n2OzlTWhinflation.csv\")\n",
         "\n",
-        "# Extract the year and inflation rate from the CSV file\n",
-        "df[\"Year\"] = pd.to_datetime(df[\"Year\"], format=\"%Y\")\n",
-        "df = df.rename(\n",
-        "    columns={\n",
-        "        \"Jan\": \"Jan Rate\",\n",
-        "        \"Feb\": \"Feb Rate\",\n",
-        "        \"Mar\": \"Mar Rate\",\n",
-        "        \"Apr\": \"Apr Rate\",\n",
-        "        \"May\": \"May Rate\",\n",
-        "        \"Jun\": \"Jun Rate\",\n",
-        "        \"Jul\": \"Jul Rate\",\n",
-        "        \"Aug\": \"Aug Rate\",\n",
-        "        \"Sep\": \"Sep Rate\",\n",
-        "        \"Oct\": \"Oct Rate\",\n",
-        "        \"Nov\": \"Nov Rate\",\n",
-        "        \"Dec\": \"Dec Rate\",\n",
-        "    }\n",
-        ")\n",
+        "# Calculate average yearly inflation\n",
+        "df['Average'] = df[['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']].mean(axis=1)\n",
         "\n",
-        "# Calculate the average yearly inflation rate\n",
-        "df[\"Yearly Inflation\"] = df[\n",
-        "    [\n",
-        "        \"Jan Rate\",\n",
-        "        \"Feb Rate\",\n",
-        "        \"Mar Rate\",\n",
-        "        \"Apr Rate\",\n",
-        "        \"May Rate\",\n",
-        "        \"Jun Rate\",\n",
-        "        \"Jul Rate\",\n",
-        "        \"Aug Rate\",\n",
-        "        \"Sep Rate\",\n",
-        "        \"Oct Rate\",\n",
-        "        \"Nov Rate\",\n",
-        "        \"Dec Rate\",\n",
-        "    ]\n",
-        "].mean(axis=1)\n",
-        "\n",
-        "# Plot the average yearly inflation rate as a time series\n",
-        "plt.figure(figsize=(10, 6))\n",
-        "plt.plot(df[\"Year\"], df[\"Yearly Inflation\"], marker=\"o\")\n",
-        "plt.title(\"Average Yearly Inflation Rate\")\n",
-        "plt.xlabel(\"Year\")\n",
-        "plt.ylabel(\"Inflation Rate (%)\")\n",
+        "# Plot average yearly inflation as a time series\n",
+        "plt.figure(figsize=(10,6))\n",
+        "plt.plot(df['Year'], df['Average'])\n",
+        "plt.title('Average Yearly Inflation')\n",
+        "plt.xlabel('Year')\n",
+        "plt.ylabel('Average Inflation')\n",
         "plt.grid(True)\n",
-        "plt.show()\n"
+        "plt.show()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "jSfjNN9fMxtm",
+      "metadata": {
+        "id": "jSfjNN9fMxtm"
+      },
+      "source": [
+        "### 2.5. Using Model Context Protocol\n",
+        "\n",
+        "In this example, we will show how tools hosted in an MCP server can be configured to be used by the model.\n",
+        "\n",
+        "In the following steps, we will use the [filesystem tool](https://github.com/modelcontextprotocol/servers/tree/main/src/filesystem) to explore the files and folders available in the /content directory\n",
+        "\n",
+        "Use xterm module to start a shell to run the MCP server using the `supergateway` tool which can start an MCP tool and serve it over HTTP."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 8,
+      "id": "67fDKVVpNuFb",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "67fDKVVpNuFb",
+        "outputId": "aec2e3cf-e1c3-4d09-d9dc-c4a2f1327e99"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "Collecting colab-xterm\n",
+            "  Downloading colab_xterm-0.2.0-py3-none-any.whl.metadata (1.2 kB)\n",
+            "Requirement already satisfied: ptyprocess~=0.7.0 in /usr/local/lib/python3.11/dist-packages (from colab-xterm) (0.7.0)\n",
+            "Requirement already satisfied: tornado>5.1 in /usr/local/lib/python3.11/dist-packages (from colab-xterm) (6.3.3)\n",
+            "Downloading colab_xterm-0.2.0-py3-none-any.whl (115 kB)\n",
+            "\u001b[?25l   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/115.6 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m115.6/115.6 kB\u001b[0m \u001b[31m4.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
+            "\u001b[?25hInstalling collected packages: colab-xterm\n",
+            "Successfully installed colab-xterm-0.2.0\n"
+          ]
+        }
+      ],
+      "source": [
+        "!pip install colab-xterm #https://pypi.org/project/colab-xterm/\n",
+        "%load_ext colabxterm"
+      ]
+    },
+    {
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All rights reserved.\n * Copyright (c) 2012-2013, Christopher Jeffrey (MIT License)\n * https://github.com/chjj/term.js\n * @license MIT\n *\n * Permission is hereby granted, free of charge, to any person obtaining a copy\n * of this software and associated documentation files (the "Software"), to deal\n * in the Software without restriction, including without limitation the rights\n * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n * copies of the Software, and to permit persons to whom the Software is\n * furnished to do so, subject to the following conditions:\n *\n * The above copyright notice and this permission notice shall be included in\n * all copies or substantial portions of the Software.\n *\n * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. 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i=t[r/36%6|0],o=t[r/6%6|0],s=t[r%6];e.push({css:n.channels.toCss(i,o,s),rgba:n.channels.toRgba(i,o,s)})}for(r=0;r<24;r++){var a=8+10*r;e.push({css:n.channels.toCss(a,a,a),rgba:n.channels.toRgba(a,a,a)})}return e}());var h=function(){function e(e,r){this.allowTransparency=r;var i=e.createElement("canvas");i.width=1,i.height=1;var h=i.getContext("2d");if(!h)throw new Error("Could not get rendering context");this._ctx=h,this._ctx.globalCompositeOperation="copy",this._litmusColor=this._ctx.createLinearGradient(0,0,1,1),this._contrastCache=new o.ColorContrastCache,this.colors={foreground:s,background:a,cursor:c,cursorAccent:l,selectionTransparent:u,selectionOpaque:n.color.blend(a,u),ansi:t.DEFAULT_ANSI_COLORS.slice(),contrastCache:this._contrastCache},this._updateRestoreColors()}return e.prototype.onOptionsChange=function(e){"minimumContrastRatio"===e&&this._contrastCache.clear()},e.prototype.setTheme=function(e){void 0===e&&(e={}),this.colors.foreground=this._parseColor(e.foreground,s),this.colors.background=this._parseColor(e.background,a),this.colors.cursor=this._parseColor(e.cursor,c,!0),this.colors.cursorAccent=this._parseColor(e.cursorAccent,l,!0),this.colors.selectionTransparent=this._parseColor(e.selection,u,!0),this.colors.selectionOpaque=n.color.blend(this.colors.background,this.colors.selectionTransparent),n.color.isOpaque(this.colors.selectionTransparent)&&(this.colors.selectionTransparent=n.color.opacity(this.colors.selectionTransparent,.3)),this.colors.ansi[0]=this._parseColor(e.black,t.DEFAULT_ANSI_COLORS[0]),this.colors.ansi[1]=this._parseColor(e.red,t.DEFAULT_ANSI_COLORS[1]),this.colors.ansi[2]=this._parseColor(e.green,t.DEFAULT_ANSI_COLORS[2]),this.colors.ansi[3]=this._parseColor(e.yellow,t.DEFAULT_ANSI_COLORS[3]),this.colors.ansi[4]=this._parseColor(e.blue,t.DEFAULT_ANSI_COLORS[4]),this.colors.ansi[5]=this._parseColor(e.magenta,t.DEFAULT_ANSI_COLORS[5]),this.colors.ansi[6]=this._parseColor(e.cyan,t.DEFAULT_ANSI_COLORS[6]),this.colors.ansi[7]=this._parseColor(e.white,t.DEFAULT_ANSI_COLORS[7]),this.colors.ansi[8]=this._parseColor(e.brightBlack,t.DEFAULT_ANSI_COLORS[8]),this.colors.ansi[9]=this._parseColor(e.brightRed,t.DEFAULT_ANSI_COLORS[9]),this.colors.ansi[10]=this._parseColor(e.brightGreen,t.DEFAULT_ANSI_COLORS[10]),this.colors.ansi[11]=this._parseColor(e.brightYellow,t.DEFAULT_ANSI_COLORS[11]),this.colors.ansi[12]=this._parseColor(e.brightBlue,t.DEFAULT_ANSI_COLORS[12]),this.colors.ansi[13]=this._parseColor(e.brightMagenta,t.DEFAULT_ANSI_COLORS[13]),this.colors.ansi[14]=this._parseColor(e.brightCyan,t.DEFAULT_ANSI_COLORS[14]),this.colors.ansi[15]=this._parseColor(e.brightWhite,t.DEFAULT_ANSI_COLORS[15]),this._contrastCache.clear(),this._updateRestoreColors()},e.prototype.restoreColor=function(e){if(void 0!==e)switch(e){case 256:this.colors.foreground=this._restoreColors.foreground;break;case 257:this.colors.background=this._restoreColors.background;break;case 258:this.colors.cursor=this._restoreColors.cursor;break;default:this.colors.ansi[e]=this._restoreColors.ansi[e]}else for(var t=0;t<this._restoreColors.ansi.length;++t)this.colors.ansi[t]=this._restoreColors.ansi[t]},e.prototype._updateRestoreColors=function(){this._restoreColors={foreground:this.colors.foreground,background:this.colors.background,cursor:this.colors.cursor,ansi:i([],this.colors.ansi,!0)}},e.prototype._parseColor=function(e,t,r){if(void 0===r&&(r=this.allowTransparency),void 0===e)return t;if(this._ctx.fillStyle=this._litmusColor,this._ctx.fillStyle=e,"string"!=typeof this._ctx.fillStyle)return console.warn("Color: "+e+" is invalid using fallback "+t.css),t;this._ctx.fillRect(0,0,1,1);var i=this._ctx.getImageData(0,0,1,1).data;if(255!==i[3]){if(!r)return console.warn("Color: "+e+" is using transparency, but allowTransparency is false. Using fallback "+t.css+"."),t;var o=this._ctx.fillStyle.substring(5,this._ctx.fillStyle.length-1).split(",").map((function(e){return Number(e)})),s=o[0],a=o[1],c=o[2],l=o[3],u=Math.round(255*l);return{rgba:n.channels.toRgba(s,a,c,u),css:e}}return{css:this._ctx.fillStyle,rgba:n.channels.toRgba(i[0],i[1],i[2],i[3])}},e}();t.ColorManager=h},9631:(e,t)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.removeElementFromParent=void 0,t.removeElementFromParent=function(){for(var e,t=[],r=0;r<arguments.length;r++)t[r]=arguments[r];for(var i=0,n=t;i<n.length;i++){var o=n[i];null===(e=null==o?void 0:o.parentElement)||void 0===e||e.removeChild(o)}}},3656:(e,t)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.addDisposableDomListener=void 0,t.addDisposableDomListener=function(e,t,r,i){e.addEventListener(t,r,i);var n=!1;return{dispose:function(){n||(n=!0,e.removeEventListener(t,r,i))}}}},3551:function(e,t,r){var i=this&&this.__decorate||function(e,t,r,i){var n,o=arguments.length,s=o<3?t:null===i?i=Object.getOwnPropertyDescriptor(t,r):i;if("object"==typeof Reflect&&"function"==typeof Reflect.decorate)s=Reflect.decorate(e,t,r,i);else for(var a=e.length-1;a>=0;a--)(n=e[a])&&(s=(o<3?n(s):o>3?n(t,r,s):n(t,r))||s);return o>3&&s&&Object.defineProperty(t,r,s),s},n=this&&this.__param||function(e,t){return function(r,i){t(r,i,e)}};Object.defineProperty(t,"__esModule",{value:!0}),t.MouseZone=t.Linkifier=void 0;var o=r(8460),s=r(2585),a=function(){function e(e,t,r){this._bufferService=e,this._logService=t,this._unicodeService=r,this._linkMatchers=[],this._nextLinkMatcherId=0,this._onShowLinkUnderline=new o.EventEmitter,this._onHideLinkUnderline=new o.EventEmitter,this._onLinkTooltip=new o.EventEmitter,this._rowsToLinkify={start:void 0,end:void 0}}return Object.defineProperty(e.prototype,"onShowLinkUnderline",{get:function(){return 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e=this._bufferService.buffer;if(void 0!==this._rowsToLinkify.start&&void 0!==this._rowsToLinkify.end){var t=e.ydisp+this._rowsToLinkify.start;if(!(t>=e.lines.length)){for(var r=e.ydisp+Math.min(this._rowsToLinkify.end,this._bufferService.rows)+1,i=Math.ceil(2e3/this._bufferService.cols),n=this._bufferService.buffer.iterator(!1,t,r,i,i);n.hasNext();)for(var o=n.next(),s=0;s<this._linkMatchers.length;s++)this._doLinkifyRow(o.range.first,o.content,this._linkMatchers[s]);this._rowsToLinkify.start=void 0,this._rowsToLinkify.end=void 0}}else this._logService.debug("_rowToLinkify was unset before _linkifyRows was called")},e.prototype.registerLinkMatcher=function(e,t,r){if(void 0===r&&(r={}),!t)throw new Error("handler must be defined");var i={id:this._nextLinkMatcherId++,regex:e,handler:t,matchIndex:r.matchIndex,validationCallback:r.validationCallback,hoverTooltipCallback:r.tooltipCallback,hoverLeaveCallback:r.leaveCallback,willLinkActivate:r.willLinkActivate,priority:r.priority||0};return this._addLinkMatcherToList(i),i.id},e.prototype._addLinkMatcherToList=function(e){if(0!==this._linkMatchers.length){for(var t=this._linkMatchers.length-1;t>=0;t--)if(e.priority<=this._linkMatchers[t].priority)return void this._linkMatchers.splice(t+1,0,e);this._linkMatchers.splice(0,0,e)}else this._linkMatchers.push(e)},e.prototype.deregisterLinkMatcher=function(e){for(var t=0;t<this._linkMatchers.length;t++)if(this._linkMatchers[t].id===e)return this._linkMatchers.splice(t,1),!0;return!1},e.prototype._doLinkifyRow=function(e,t,r){for(var i,n=this,o=new RegExp(r.regex.source,(r.regex.flags||"")+"g"),s=-1,a=function(){var a=i["number"!=typeof r.matchIndex?0:r.matchIndex];if(!a)return c._logService.debug("match found without corresponding matchIndex",i,r),"break";if(s=t.indexOf(a,s+1),o.lastIndex=s+a.length,s<0)return"break";var l=c._bufferService.buffer.stringIndexToBufferIndex(e,s);if(l[0]<0)return"break";var u=c._bufferService.buffer.lines.get(l[0]);if(!u)return"break";var h=u.getFg(l[1]),f=h?h>>9&511:void 0;r.validationCallback?r.validationCallback(a,(function(e){n._rowsTimeoutId||e&&n._addLink(l[1],l[0]-n._bufferService.buffer.ydisp,a,r,f)})):c._addLink(l[1],l[0]-c._bufferService.buffer.ydisp,a,r,f)},c=this;null!==(i=o.exec(t))&&"break"!==a(););},e.prototype._addLink=function(e,t,r,i,n){var o=this;if(this._mouseZoneManager&&this._element){var s=this._unicodeService.getStringCellWidth(r),a=e%this._bufferService.cols,l=t+Math.floor(e/this._bufferService.cols),u=(a+s)%this._bufferService.cols,h=l+Math.floor((a+s)/this._bufferService.cols);0===u&&(u=this._bufferService.cols,h--),this._mouseZoneManager.add(new c(a+1,l+1,u+1,h+1,(function(e){if(i.handler)return i.handler(e,r);var t=window.open();t?(t.opener=null,t.location.href=r):console.warn("Opening link blocked as opener could not be cleared")}),(function(){o._onShowLinkUnderline.fire(o._createLinkHoverEvent(a,l,u,h,n)),o._element.classList.add("xterm-cursor-pointer")}),(function(e){o._onLinkTooltip.fire(o._createLinkHoverEvent(a,l,u,h,n)),i.hoverTooltipCallback&&i.hoverTooltipCallback(e,r,{start:{x:a,y:l},end:{x:u,y:h}})}),(function(){o._onHideLinkUnderline.fire(o._createLinkHoverEvent(a,l,u,h,n)),o._element.classList.remove("xterm-cursor-pointer"),i.hoverLeaveCallback&&i.hoverLeaveCallback()}),(function(e){return!i.willLinkActivate||i.willLinkActivate(e,r)})))}},e.prototype._createLinkHoverEvent=function(e,t,r,i,n){return{x1:e,y1:t,x2:r,y2:i,cols:this._bufferService.cols,fg:n}},e._timeBeforeLatency=200,e=i([n(0,s.IBufferService),n(1,s.ILogService),n(2,s.IUnicodeService)],e)}();t.Linkifier=a;var c=function(e,t,r,i,n,o,s,a,c){this.x1=e,this.y1=t,this.x2=r,this.y2=i,this.clickCallback=n,this.hoverCallback=o,this.tooltipCallback=s,this.leaveCallback=a,this.willLinkActivate=c};t.MouseZone=c},6465:function(e,t,r){var i,n=this&&this.__extends||(i=function(e,t){return i=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var r in t)Object.prototype.hasOwnProperty.call(t,r)&&(e[r]=t[r])},i(e,t)},function(e,t){if("function"!=typeof t&&null!==t)throw new TypeError("Class extends value "+String(t)+" is not a constructor or null");function r(){this.constructor=e}i(e,t),e.prototype=null===t?Object.create(t):(r.prototype=t.prototype,new r)}),o=this&&this.__decorate||function(e,t,r,i){var n,o=arguments.length,s=o<3?t:null===i?i=Object.getOwnPropertyDescriptor(t,r):i;if("object"==typeof Reflect&&"function"==typeof Reflect.decorate)s=Reflect.decorate(e,t,r,i);else for(var a=e.length-1;a>=0;a--)(n=e[a])&&(s=(o<3?n(s):o>3?n(t,r,s):n(t,r))||s);return o>3&&s&&Object.defineProperty(t,r,s),s},s=this&&this.__param||function(e,t){return function(r,i){t(r,i,e)}};Object.defineProperty(t,"__esModule",{value:!0}),t.Linkifier2=void 0;var a=r(2585),c=r(8460),l=r(844),u=r(3656),h=function(e){function t(t){var r=e.call(this)||this;return r._bufferService=t,r._linkProviders=[],r._linkCacheDisposables=[],r._isMouseOut=!0,r._activeLine=-1,r._onShowLinkUnderline=r.register(new c.EventEmitter),r._onHideLinkUnderline=r.register(new c.EventEmitter),r.register((0,l.getDisposeArrayDisposable)(r._linkCacheDisposables)),r}return n(t,e),Object.defineProperty(t.prototype,"currentLink",{get:function(){return this._currentLink},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onShowLinkUnderline",{get:function(){return this._onShowLinkUnderline.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onHideLinkUnderline",{get:function(){return this._onHideLinkUnderline.event},enumerable:!1,configurable:!0}),t.prototype.registerLinkProvider=function(e){var t=this;return this._linkProviders.push(e),{dispose:function(){var r=t._linkProviders.indexOf(e);-1!==r&&t._linkProviders.splice(r,1)}}},t.prototype.attachToDom=function(e,t,r){var i=this;this._element=e,this._mouseService=t,this._renderService=r,this.register((0,u.addDisposableDomListener)(this._element,"mouseleave",(function(){i._isMouseOut=!0,i._clearCurrentLink()}))),this.register((0,u.addDisposableDomListener)(this._element,"mousemove",this._onMouseMove.bind(this))),this.register((0,u.addDisposableDomListener)(this._element,"click",this._onClick.bind(this)))},t.prototype._onMouseMove=function(e){if(this._lastMouseEvent=e,this._element&&this._mouseService){var t=this._positionFromMouseEvent(e,this._element,this._mouseService);if(t){this._isMouseOut=!1;for(var r=e.composedPath(),i=0;i<r.length;i++){var n=r[i];if(n.classList.contains("xterm"))break;if(n.classList.contains("xterm-hover"))return}this._lastBufferCell&&t.x===this._lastBufferCell.x&&t.y===this._lastBufferCell.y||(this._onHover(t),this._lastBufferCell=t)}}},t.prototype._onHover=function(e){if(this._activeLine!==e.y)return this._clearCurrentLink(),void this._askForLink(e,!1);this._currentLink&&this._linkAtPosition(this._currentLink.link,e)||(this._clearCurrentLink(),this._askForLink(e,!0))},t.prototype._askForLink=function(e,t){var r,i=this;this._activeProviderReplies&&t||(null===(r=this._activeProviderReplies)||void 0===r||r.forEach((function(e){null==e||e.forEach((function(e){e.link.dispose&&e.link.dispose()}))})),this._activeProviderReplies=new Map,this._activeLine=e.y);var n=!1;this._linkProviders.forEach((function(r,o){var s;t?(null===(s=i._activeProviderReplies)||void 0===s?void 0:s.get(o))&&(n=i._checkLinkProviderResult(o,e,n)):r.provideLinks(e.y,(function(t){var r,s;if(!i._isMouseOut){var a=null==t?void 0:t.map((function(e){return{link:e}}));null===(r=i._activeProviderReplies)||void 0===r||r.set(o,a),n=i._checkLinkProviderResult(o,e,n),(null===(s=i._activeProviderReplies)||void 0===s?void 0:s.size)===i._linkProviders.length&&i._removeIntersectingLinks(e.y,i._activeProviderReplies)}}))}))},t.prototype._removeIntersectingLinks=function(e,t){for(var r=new Set,i=0;i<t.size;i++){var n=t.get(i);if(n)for(var o=0;o<n.length;o++)for(var s=n[o],a=s.link.range.start.y<e?0:s.link.range.start.x,c=s.link.range.end.y>e?this._bufferService.cols:s.link.range.end.x,l=a;l<=c;l++){if(r.has(l)){n.splice(o--,1);break}r.add(l)}}},t.prototype._checkLinkProviderResult=function(e,t,r){var i,n=this;if(!this._activeProviderReplies)return r;for(var o=this._activeProviderReplies.get(e),s=!1,a=0;a<e;a++)this._activeProviderReplies.has(a)&&!this._activeProviderReplies.get(a)||(s=!0);if(!s&&o){var c=o.find((function(e){return n._linkAtPosition(e.link,t)}));c&&(r=!0,this._handleNewLink(c))}if(this._activeProviderReplies.size===this._linkProviders.length&&!r)for(a=0;a<this._activeProviderReplies.size;a++){var l=null===(i=this._activeProviderReplies.get(a))||void 0===i?void 0:i.find((function(e){return n._linkAtPosition(e.link,t)}));if(l){r=!0,this._handleNewLink(l);break}}return r},t.prototype._onClick=function(e){if(this._element&&this._mouseService&&this._currentLink){var t=this._positionFromMouseEvent(e,this._element,this._mouseService);t&&this._linkAtPosition(this._currentLink.link,t)&&this._currentLink.link.activate(e,this._currentLink.link.text)}},t.prototype._clearCurrentLink=function(e,t){this._element&&this._currentLink&&this._lastMouseEvent&&(!e||!t||this._currentLink.link.range.start.y>=e&&this._currentLink.link.range.end.y<=t)&&(this._linkLeave(this._element,this._currentLink.link,this._lastMouseEvent),this._currentLink=void 0,(0,l.disposeArray)(this._linkCacheDisposables))},t.prototype._handleNewLink=function(e){var t=this;if(this._element&&this._lastMouseEvent&&this._mouseService){var r=this._positionFromMouseEvent(this._lastMouseEvent,this._element,this._mouseService);r&&this._linkAtPosition(e.link,r)&&(this._currentLink=e,this._currentLink.state={decorations:{underline:void 0===e.link.decorations||e.link.decorations.underline,pointerCursor:void 0===e.link.decorations||e.link.decorations.pointerCursor},isHovered:!0},this._linkHover(this._element,e.link,this._lastMouseEvent),e.link.decorations={},Object.defineProperties(e.link.decorations,{pointerCursor:{get:function(){var e,r;return null===(r=null===(e=t._currentLink)||void 0===e?void 0:e.state)||void 0===r?void 0:r.decorations.pointerCursor},set:function(e){var r,i;(null===(r=t._currentLink)||void 0===r?void 0:r.state)&&t._currentLink.state.decorations.pointerCursor!==e&&(t._currentLink.state.decorations.pointerCursor=e,t._currentLink.state.isHovered&&(null===(i=t._element)||void 0===i||i.classList.toggle("xterm-cursor-pointer",e)))}},underline:{get:function(){var e,r;return null===(r=null===(e=t._currentLink)||void 0===e?void 0:e.state)||void 0===r?void 0:r.decorations.underline},set:function(r){var i,n,o;(null===(i=t._currentLink)||void 0===i?void 0:i.state)&&(null===(o=null===(n=t._currentLink)||void 0===n?void 0:n.state)||void 0===o?void 0:o.decorations.underline)!==r&&(t._currentLink.state.decorations.underline=r,t._currentLink.state.isHovered&&t._fireUnderlineEvent(e.link,r))}}}),this._renderService&&this._linkCacheDisposables.push(this._renderService.onRenderedBufferChange((function(e){var r=0===e.start?0:e.start+1+t._bufferService.buffer.ydisp;t._clearCurrentLink(r,e.end+1+t._bufferService.buffer.ydisp)}))))}},t.prototype._linkHover=function(e,t,r){var i;(null===(i=this._currentLink)||void 0===i?void 0:i.state)&&(this._currentLink.state.isHovered=!0,this._currentLink.state.decorations.underline&&this._fireUnderlineEvent(t,!0),this._currentLink.state.decorations.pointerCursor&&e.classList.add("xterm-cursor-pointer")),t.hover&&t.hover(r,t.text)},t.prototype._fireUnderlineEvent=function(e,t){var r=e.range,i=this._bufferService.buffer.ydisp,n=this._createLinkUnderlineEvent(r.start.x-1,r.start.y-i-1,r.end.x,r.end.y-i-1,void 0);(t?this._onShowLinkUnderline:this._onHideLinkUnderline).fire(n)},t.prototype._linkLeave=function(e,t,r){var i;(null===(i=this._currentLink)||void 0===i?void 0:i.state)&&(this._currentLink.state.isHovered=!1,this._currentLink.state.decorations.underline&&this._fireUnderlineEvent(t,!1),this._currentLink.state.decorations.pointerCursor&&e.classList.remove("xterm-cursor-pointer")),t.leave&&t.leave(r,t.text)},t.prototype._linkAtPosition=function(e,t){var r=e.range.start.y===e.range.end.y,i=e.range.start.y<t.y,n=e.range.end.y>t.y;return(r&&e.range.start.x<=t.x&&e.range.end.x>=t.x||i&&e.range.end.x>=t.x||n&&e.range.start.x<=t.x||i&&n)&&e.range.start.y<=t.y&&e.range.end.y>=t.y},t.prototype._positionFromMouseEvent=function(e,t,r){var i=r.getCoords(e,t,this._bufferService.cols,this._bufferService.rows);if(i)return{x:i[0],y:i[1]+this._bufferService.buffer.ydisp}},t.prototype._createLinkUnderlineEvent=function(e,t,r,i,n){return{x1:e,y1:t,x2:r,y2:i,cols:this._bufferService.cols,fg:n}},o([s(0,a.IBufferService)],t)}(l.Disposable);t.Linkifier2=h},9042:(e,t)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.tooMuchOutput=t.promptLabel=void 0,t.promptLabel="Terminal input",t.tooMuchOutput="Too much output to announce, navigate to rows manually to read"},6954:function(e,t,r){var i,n=this&&this.__extends||(i=function(e,t){return i=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var r in t)Object.prototype.hasOwnProperty.call(t,r)&&(e[r]=t[r])},i(e,t)},function(e,t){if("function"!=typeof t&&null!==t)throw new TypeError("Class extends value "+String(t)+" is not a constructor or null");function r(){this.constructor=e}i(e,t),e.prototype=null===t?Object.create(t):(r.prototype=t.prototype,new r)}),o=this&&this.__decorate||function(e,t,r,i){var n,o=arguments.length,s=o<3?t:null===i?i=Object.getOwnPropertyDescriptor(t,r):i;if("object"==typeof Reflect&&"function"==typeof Reflect.decorate)s=Reflect.decorate(e,t,r,i);else for(var a=e.length-1;a>=0;a--)(n=e[a])&&(s=(o<3?n(s):o>3?n(t,r,s):n(t,r))||s);return o>3&&s&&Object.defineProperty(t,r,s),s},s=this&&this.__param||function(e,t){return function(r,i){t(r,i,e)}};Object.defineProperty(t,"__esModule",{value:!0}),t.MouseZoneManager=void 0;var a=r(844),c=r(3656),l=r(4725),u=r(2585),h=function(e){function t(t,r,i,n,o,s){var a=e.call(this)||this;return a._element=t,a._screenElement=r,a._bufferService=i,a._mouseService=n,a._selectionService=o,a._optionsService=s,a._zones=[],a._areZonesActive=!1,a._lastHoverCoords=[void 0,void 0],a._initialSelectionLength=0,a.register((0,c.addDisposableDomListener)(a._element,"mousedown",(function(e){return a._onMouseDown(e)}))),a._mouseMoveListener=function(e){return a._onMouseMove(e)},a._mouseLeaveListener=function(e){return a._onMouseLeave(e)},a._clickListener=function(e){return a._onClick(e)},a}return n(t,e),t.prototype.dispose=function(){e.prototype.dispose.call(this),this._deactivate()},t.prototype.add=function(e){this._zones.push(e),1===this._zones.length&&this._activate()},t.prototype.clearAll=function(e,t){if(0!==this._zones.length){e&&t||(e=0,t=this._bufferService.rows-1);for(var r=0;r<this._zones.length;r++){var i=this._zones[r];(i.y1>e&&i.y1<=t+1||i.y2>e&&i.y2<=t+1||i.y1<e&&i.y2>t+1)&&(this._currentZone&&this._currentZone===i&&(this._currentZone.leaveCallback(),this._currentZone=void 0),this._zones.splice(r--,1))}0===this._zones.length&&this._deactivate()}},t.prototype._activate=function(){this._areZonesActive||(this._areZonesActive=!0,this._element.addEventListener("mousemove",this._mouseMoveListener),this._element.addEventListener("mouseleave",this._mouseLeaveListener),this._element.addEventListener("click",this._clickListener))},t.prototype._deactivate=function(){this._areZonesActive&&(this._areZonesActive=!1,this._element.removeEventListener("mousemove",this._mouseMoveListener),this._element.removeEventListener("mouseleave",this._mouseLeaveListener),this._element.removeEventListener("click",this._clickListener))},t.prototype._onMouseMove=function(e){this._lastHoverCoords[0]===e.pageX&&this._lastHoverCoords[1]===e.pageY||(this._onHover(e),this._lastHoverCoords=[e.pageX,e.pageY])},t.prototype._onHover=function(e){var t=this,r=this._findZoneEventAt(e);r!==this._currentZone&&(this._currentZone&&(this._currentZone.leaveCallback(),this._currentZone=void 0,this._tooltipTimeout&&clearTimeout(this._tooltipTimeout)),r&&(this._currentZone=r,r.hoverCallback&&r.hoverCallback(e),this._tooltipTimeout=window.setTimeout((function(){return t._onTooltip(e)}),this._optionsService.options.linkTooltipHoverDuration)))},t.prototype._onTooltip=function(e){this._tooltipTimeout=void 0;var t=this._findZoneEventAt(e);null==t||t.tooltipCallback(e)},t.prototype._onMouseDown=function(e){if(this._initialSelectionLength=this._getSelectionLength(),this._areZonesActive){var t=this._findZoneEventAt(e);(null==t?void 0:t.willLinkActivate(e))&&(e.preventDefault(),e.stopImmediatePropagation())}},t.prototype._onMouseLeave=function(e){this._currentZone&&(this._currentZone.leaveCallback(),this._currentZone=void 0,this._tooltipTimeout&&clearTimeout(this._tooltipTimeout))},t.prototype._onClick=function(e){var t=this._findZoneEventAt(e),r=this._getSelectionLength();t&&r===this._initialSelectionLength&&(t.clickCallback(e),e.preventDefault(),e.stopImmediatePropagation())},t.prototype._getSelectionLength=function(){var e=this._selectionService.selectionText;return e?e.length:0},t.prototype._findZoneEventAt=function(e){var t=this._mouseService.getCoords(e,this._screenElement,this._bufferService.cols,this._bufferService.rows);if(t)for(var r=t[0],i=t[1],n=0;n<this._zones.length;n++){var o=this._zones[n];if(o.y1===o.y2){if(i===o.y1&&r>=o.x1&&r<o.x2)return o}else if(i===o.y1&&r>=o.x1||i===o.y2&&r<o.x2||i>o.y1&&i<o.y2)return o}},o([s(2,u.IBufferService),s(3,l.IMouseService),s(4,l.ISelectionService),s(5,u.IOptionsService)],t)}(a.Disposable);t.MouseZoneManager=h},6193:(e,t)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.RenderDebouncer=void 0;var r=function(){function e(e){this._renderCallback=e}return e.prototype.dispose=function(){this._animationFrame&&(window.cancelAnimationFrame(this._animationFrame),this._animationFrame=void 0)},e.prototype.refresh=function(e,t,r){var i=this;this._rowCount=r,e=void 0!==e?e:0,t=void 0!==t?t:this._rowCount-1,this._rowStart=void 0!==this._rowStart?Math.min(this._rowStart,e):e,this._rowEnd=void 0!==this._rowEnd?Math.max(this._rowEnd,t):t,this._animationFrame||(this._animationFrame=window.requestAnimationFrame((function(){return i._innerRefresh()})))},e.prototype._innerRefresh=function(){if(void 0!==this._rowStart&&void 0!==this._rowEnd&&void 0!==this._rowCount){var e=Math.max(this._rowStart,0),t=Math.min(this._rowEnd,this._rowCount-1);this._rowStart=void 0,this._rowEnd=void 0,this._animationFrame=void 0,this._renderCallback(e,t)}},e}();t.RenderDebouncer=r},5596:function(e,t,r){var i,n=this&&this.__extends||(i=function(e,t){return i=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var r in t)Object.prototype.hasOwnProperty.call(t,r)&&(e[r]=t[r])},i(e,t)},function(e,t){if("function"!=typeof t&&null!==t)throw new TypeError("Class extends value "+String(t)+" is not a constructor or null");function r(){this.constructor=e}i(e,t),e.prototype=null===t?Object.create(t):(r.prototype=t.prototype,new r)});Object.defineProperty(t,"__esModule",{value:!0}),t.ScreenDprMonitor=void 0;var o=function(e){function t(){var t=null!==e&&e.apply(this,arguments)||this;return t._currentDevicePixelRatio=window.devicePixelRatio,t}return n(t,e),t.prototype.setListener=function(e){var t=this;this._listener&&this.clearListener(),this._listener=e,this._outerListener=function(){t._listener&&(t._listener(window.devicePixelRatio,t._currentDevicePixelRatio),t._updateDpr())},this._updateDpr()},t.prototype.dispose=function(){e.prototype.dispose.call(this),this.clearListener()},t.prototype._updateDpr=function(){var e;this._outerListener&&(null===(e=this._resolutionMediaMatchList)||void 0===e||e.removeListener(this._outerListener),this._currentDevicePixelRatio=window.devicePixelRatio,this._resolutionMediaMatchList=window.matchMedia("screen and (resolution: "+window.devicePixelRatio+"dppx)"),this._resolutionMediaMatchList.addListener(this._outerListener))},t.prototype.clearListener=function(){this._resolutionMediaMatchList&&this._listener&&this._outerListener&&(this._resolutionMediaMatchList.removeListener(this._outerListener),this._resolutionMediaMatchList=void 0,this._listener=void 0,this._outerListener=void 0)},t}(r(844).Disposable);t.ScreenDprMonitor=o},3236:function(e,t,r){var i,n=this&&this.__extends||(i=function(e,t){return i=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var r in t)Object.prototype.hasOwnProperty.call(t,r)&&(e[r]=t[r])},i(e,t)},function(e,t){if("function"!=typeof t&&null!==t)throw new TypeError("Class extends value "+String(t)+" is not a constructor or null");function r(){this.constructor=e}i(e,t),e.prototype=null===t?Object.create(t):(r.prototype=t.prototype,new r)});Object.defineProperty(t,"__esModule",{value:!0}),t.Terminal=void 0;var o=r(2950),s=r(1680),a=r(3614),c=r(2584),l=r(5435),u=r(3525),h=r(3551),f=r(9312),_=r(6114),d=r(3656),p=r(9042),v=r(357),g=r(6954),y=r(4567),m=r(1296),b=r(7399),S=r(8460),C=r(8437),w=r(5680),L=r(3230),E=r(4725),x=r(428),A=r(8934),k=r(6465),M=r(5114),R=r(8969),T=r(4774),O=r(4269),B=r(5941),D="undefined"!=typeof window?window.document:null,P=function(e){function t(t){void 0===t&&(t={});var r=e.call(this,t)||this;return r.browser=_,r._keyDownHandled=!1,r._keyPressHandled=!1,r._unprocessedDeadKey=!1,r._onCursorMove=new S.EventEmitter,r._onKey=new S.EventEmitter,r._onRender=new S.EventEmitter,r._onSelectionChange=new S.EventEmitter,r._onTitleChange=new S.EventEmitter,r._onBell=new S.EventEmitter,r._onFocus=new S.EventEmitter,r._onBlur=new S.EventEmitter,r._onA11yCharEmitter=new S.EventEmitter,r._onA11yTabEmitter=new S.EventEmitter,r._setup(),r.linkifier=r._instantiationService.createInstance(h.Linkifier),r.linkifier2=r.register(r._instantiationService.createInstance(k.Linkifier2)),r.register(r._inputHandler.onRequestBell((function(){return r.bell()}))),r.register(r._inputHandler.onRequestRefreshRows((function(e,t){return r.refresh(e,t)}))),r.register(r._inputHandler.onRequestSendFocus((function(){return r._reportFocus()}))),r.register(r._inputHandler.onRequestReset((function(){return r.reset()}))),r.register(r._inputHandler.onRequestWindowsOptionsReport((function(e){return r._reportWindowsOptions(e)}))),r.register(r._inputHandler.onColor((function(e){return r._handleColorEvent(e)}))),r.register((0,S.forwardEvent)(r._inputHandler.onCursorMove,r._onCursorMove)),r.register((0,S.forwardEvent)(r._inputHandler.onTitleChange,r._onTitleChange)),r.register((0,S.forwardEvent)(r._inputHandler.onA11yChar,r._onA11yCharEmitter)),r.register((0,S.forwardEvent)(r._inputHandler.onA11yTab,r._onA11yTabEmitter)),r.register(r._bufferService.onResize((function(e){return r._afterResize(e.cols,e.rows)}))),r}return n(t,e),Object.defineProperty(t.prototype,"onCursorMove",{get:function(){return this._onCursorMove.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onKey",{get:function(){return this._onKey.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onRender",{get:function(){return this._onRender.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onSelectionChange",{get:function(){return this._onSelectionChange.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onTitleChange",{get:function(){return this._onTitleChange.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onBell",{get:function(){return this._onBell.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onFocus",{get:function(){return this._onFocus.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onBlur",{get:function(){return this._onBlur.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onA11yChar",{get:function(){return this._onA11yCharEmitter.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onA11yTab",{get:function(){return this._onA11yTabEmitter.event},enumerable:!1,configurable:!0}),t.prototype._handleColorEvent=function(e){var t,r;if(this._colorManager){for(var i=0,n=e;i<n.length;i++){var o=n[i],s=void 0,a="";switch(o.index){case 256:s="foreground",a="10";break;case 257:s="background",a="11";break;case 258:s="cursor",a="12";break;default:s="ansi",a="4;"+o.index}if(s)switch(o.type){case 0:var l=T.color.toColorRGB("ansi"===s?this._colorManager.colors.ansi[o.index]:this._colorManager.colors[s]);this.coreService.triggerDataEvent(c.C0.ESC+"]"+a+";"+(0,B.toRgbString)(l)+c.C0.BEL);break;case 1:"ansi"===s?this._colorManager.colors.ansi[o.index]=T.rgba.toColor.apply(T.rgba,o.color):this._colorManager.colors[s]=T.rgba.toColor.apply(T.rgba,o.color);break;case 2:this._colorManager.restoreColor(o.index)}}null===(t=this._renderService)||void 0===t||t.setColors(this._colorManager.colors),null===(r=this.viewport)||void 0===r||r.onThemeChange(this._colorManager.colors)}},t.prototype.dispose=function(){var t,r,i;this._isDisposed||(e.prototype.dispose.call(this),null===(t=this._renderService)||void 0===t||t.dispose(),this._customKeyEventHandler=void 0,this.write=function(){},null===(i=null===(r=this.element)||void 0===r?void 0:r.parentNode)||void 0===i||i.removeChild(this.element))},t.prototype._setup=function(){e.prototype._setup.call(this),this._customKeyEventHandler=void 0},Object.defineProperty(t.prototype,"buffer",{get:function(){return this.buffers.active},enumerable:!1,configurable:!0}),t.prototype.focus=function(){this.textarea&&this.textarea.focus({preventScroll:!0})},t.prototype._updateOptions=function(t){var r,i,n,o;switch(e.prototype._updateOptions.call(this,t),t){case"fontFamily":case"fontSize":null===(r=this._renderService)||void 0===r||r.clear(),null===(i=this._charSizeService)||void 0===i||i.measure();break;case"cursorBlink":case"cursorStyle":this.refresh(this.buffer.y,this.buffer.y);break;case"customGlyphs":case"drawBoldTextInBrightColors":case"letterSpacing":case"lineHeight":case"fontWeight":case"fontWeightBold":case"minimumContrastRatio":this._renderService&&(this._renderService.clear(),this._renderService.onResize(this.cols,this.rows),this.refresh(0,this.rows-1));break;case"rendererType":this._renderService&&(this._renderService.setRenderer(this._createRenderer()),this._renderService.onResize(this.cols,this.rows));break;case"scrollback":null===(n=this.viewport)||void 0===n||n.syncScrollArea();break;case"screenReaderMode":this.optionsService.options.screenReaderMode?!this._accessibilityManager&&this._renderService&&(this._accessibilityManager=new y.AccessibilityManager(this,this._renderService)):(null===(o=this._accessibilityManager)||void 0===o||o.dispose(),this._accessibilityManager=void 0);break;case"tabStopWidth":this.buffers.setupTabStops();break;case"theme":this._setTheme(this.optionsService.options.theme)}},t.prototype._onTextAreaFocus=function(e){this.coreService.decPrivateModes.sendFocus&&this.coreService.triggerDataEvent(c.C0.ESC+"[I"),this.updateCursorStyle(e),this.element.classList.add("focus"),this._showCursor(),this._onFocus.fire()},t.prototype.blur=function(){var e;return null===(e=this.textarea)||void 0===e?void 0:e.blur()},t.prototype._onTextAreaBlur=function(){this.textarea.value="",this.refresh(this.buffer.y,this.buffer.y),this.coreService.decPrivateModes.sendFocus&&this.coreService.triggerDataEvent(c.C0.ESC+"[O"),this.element.classList.remove("focus"),this._onBlur.fire()},t.prototype._syncTextArea=function(){if(this.textarea&&this.buffer.isCursorInViewport&&!this._compositionHelper.isComposing&&this._renderService){var e=this.buffer.ybase+this.buffer.y,t=this.buffer.lines.get(e);if(t){var r=Math.min(this.buffer.x,this.cols-1),i=this._renderService.dimensions.actualCellHeight,n=t.getWidth(r),o=this._renderService.dimensions.actualCellWidth*n,s=this.buffer.y*this._renderService.dimensions.actualCellHeight,a=r*this._renderService.dimensions.actualCellWidth;this.textarea.style.left=a+"px",this.textarea.style.top=s+"px",this.textarea.style.width=o+"px",this.textarea.style.height=i+"px",this.textarea.style.lineHeight=i+"px",this.textarea.style.zIndex="-5"}}},t.prototype._initGlobal=function(){var e=this;this._bindKeys(),this.register((0,d.addDisposableDomListener)(this.element,"copy",(function(t){e.hasSelection()&&(0,a.copyHandler)(t,e._selectionService)})));var t=function(t){return(0,a.handlePasteEvent)(t,e.textarea,e.coreService)};this.register((0,d.addDisposableDomListener)(this.textarea,"paste",t)),this.register((0,d.addDisposableDomListener)(this.element,"paste",t)),_.isFirefox?this.register((0,d.addDisposableDomListener)(this.element,"mousedown",(function(t){2===t.button&&(0,a.rightClickHandler)(t,e.textarea,e.screenElement,e._selectionService,e.options.rightClickSelectsWord)}))):this.register((0,d.addDisposableDomListener)(this.element,"contextmenu",(function(t){(0,a.rightClickHandler)(t,e.textarea,e.screenElement,e._selectionService,e.options.rightClickSelectsWord)}))),_.isLinux&&this.register((0,d.addDisposableDomListener)(this.element,"auxclick",(function(t){1===t.button&&(0,a.moveTextAreaUnderMouseCursor)(t,e.textarea,e.screenElement)})))},t.prototype._bindKeys=function(){var e=this;this.register((0,d.addDisposableDomListener)(this.textarea,"keyup",(function(t){return e._keyUp(t)}),!0)),this.register((0,d.addDisposableDomListener)(this.textarea,"keydown",(function(t){return e._keyDown(t)}),!0)),this.register((0,d.addDisposableDomListener)(this.textarea,"keypress",(function(t){return e._keyPress(t)}),!0)),this.register((0,d.addDisposableDomListener)(this.textarea,"compositionstart",(function(){return e._compositionHelper.compositionstart()}))),this.register((0,d.addDisposableDomListener)(this.textarea,"compositionupdate",(function(t){return e._compositionHelper.compositionupdate(t)}))),this.register((0,d.addDisposableDomListener)(this.textarea,"compositionend",(function(){return e._compositionHelper.compositionend()}))),this.register((0,d.addDisposableDomListener)(this.textarea,"input",(function(t){return e._inputEvent(t)}),!0)),this.register(this.onRender((function(){return e._compositionHelper.updateCompositionElements()}))),this.register(this.onRender((function(t){return e._queueLinkification(t.start,t.end)})))},t.prototype.open=function(e){var t=this;if(!e)throw new Error("Terminal requires a parent element.");e.isConnected||this._logService.debug("Terminal.open was called on an element that was not attached to the DOM"),this._document=e.ownerDocument,this.element=this._document.createElement("div"),this.element.dir="ltr",this.element.classList.add("terminal"),this.element.classList.add("xterm"),this.element.setAttribute("tabindex","0"),e.appendChild(this.element);var r=D.createDocumentFragment();this._viewportElement=D.createElement("div"),this._viewportElement.classList.add("xterm-viewport"),r.appendChild(this._viewportElement),this._viewportScrollArea=D.createElement("div"),this._viewportScrollArea.classList.add("xterm-scroll-area"),this._viewportElement.appendChild(this._viewportScrollArea),this.screenElement=D.createElement("div"),this.screenElement.classList.add("xterm-screen"),this._helperContainer=D.createElement("div"),this._helperContainer.classList.add("xterm-helpers"),this.screenElement.appendChild(this._helperContainer),r.appendChild(this.screenElement),this.textarea=D.createElement("textarea"),this.textarea.classList.add("xterm-helper-textarea"),this.textarea.setAttribute("aria-label",p.promptLabel),this.textarea.setAttribute("aria-multiline","false"),this.textarea.setAttribute("autocorrect","off"),this.textarea.setAttribute("autocapitalize","off"),this.textarea.setAttribute("spellcheck","false"),this.textarea.tabIndex=0,this.register((0,d.addDisposableDomListener)(this.textarea,"focus",(function(e){return t._onTextAreaFocus(e)}))),this.register((0,d.addDisposableDomListener)(this.textarea,"blur",(function(){return t._onTextAreaBlur()}))),this._helperContainer.appendChild(this.textarea);var i=this._instantiationService.createInstance(M.CoreBrowserService,this.textarea);this._instantiationService.setService(E.ICoreBrowserService,i),this._charSizeService=this._instantiationService.createInstance(x.CharSizeService,this._document,this._helperContainer),this._instantiationService.setService(E.ICharSizeService,this._charSizeService),this._theme=this.options.theme||this._theme,this._colorManager=new w.ColorManager(D,this.options.allowTransparency),this.register(this.optionsService.onOptionChange((function(e){return t._colorManager.onOptionsChange(e)}))),this._colorManager.setTheme(this._theme),this._characterJoinerService=this._instantiationService.createInstance(O.CharacterJoinerService),this._instantiationService.setService(E.ICharacterJoinerService,this._characterJoinerService);var n=this._createRenderer();this._renderService=this.register(this._instantiationService.createInstance(L.RenderService,n,this.rows,this.screenElement)),this._instantiationService.setService(E.IRenderService,this._renderService),this.register(this._renderService.onRenderedBufferChange((function(e){return t._onRender.fire(e)}))),this.onResize((function(e){return t._renderService.resize(e.cols,e.rows)})),this._compositionView=D.createElement("div"),this._compositionView.classList.add("composition-view"),this._compositionHelper=this._instantiationService.createInstance(o.CompositionHelper,this.textarea,this._compositionView),this._helperContainer.appendChild(this._compositionView),this.element.appendChild(r),this._soundService=this._instantiationService.createInstance(v.SoundService),this._instantiationService.setService(E.ISoundService,this._soundService),this._mouseService=this._instantiationService.createInstance(A.MouseService),this._instantiationService.setService(E.IMouseService,this._mouseService),this.viewport=this._instantiationService.createInstance(s.Viewport,(function(e){return t.scrollLines(e,!0,1)}),this._viewportElement,this._viewportScrollArea,this.element),this.viewport.onThemeChange(this._colorManager.colors),this.register(this._inputHandler.onRequestSyncScrollBar((function(){return t.viewport.syncScrollArea()}))),this.register(this.viewport),this.register(this.onCursorMove((function(){t._renderService.onCursorMove(),t._syncTextArea()}))),this.register(this.onResize((function(){return t._renderService.onResize(t.cols,t.rows)}))),this.register(this.onBlur((function(){return t._renderService.onBlur()}))),this.register(this.onFocus((function(){return t._renderService.onFocus()}))),this.register(this._renderService.onDimensionsChange((function(){return t.viewport.syncScrollArea()}))),this._selectionService=this.register(this._instantiationService.createInstance(f.SelectionService,this.element,this.screenElement,this.linkifier2)),this._instantiationService.setService(E.ISelectionService,this._selectionService),this.register(this._selectionService.onRequestScrollLines((function(e){return t.scrollLines(e.amount,e.suppressScrollEvent)}))),this.register(this._selectionService.onSelectionChange((function(){return t._onSelectionChange.fire()}))),this.register(this._selectionService.onRequestRedraw((function(e){return t._renderService.onSelectionChanged(e.start,e.end,e.columnSelectMode)}))),this.register(this._selectionService.onLinuxMouseSelection((function(e){t.textarea.value=e,t.textarea.focus(),t.textarea.select()}))),this.register(this._onScroll.event((function(e){t.viewport.syncScrollArea(),t._selectionService.refresh()}))),this.register((0,d.addDisposableDomListener)(this._viewportElement,"scroll",(function(){return t._selectionService.refresh()}))),this._mouseZoneManager=this._instantiationService.createInstance(g.MouseZoneManager,this.element,this.screenElement),this.register(this._mouseZoneManager),this.register(this.onScroll((function(){return t._mouseZoneManager.clearAll()}))),this.linkifier.attachToDom(this.element,this._mouseZoneManager),this.linkifier2.attachToDom(this.screenElement,this._mouseService,this._renderService),this.register((0,d.addDisposableDomListener)(this.element,"mousedown",(function(e){return t._selectionService.onMouseDown(e)}))),this.coreMouseService.areMouseEventsActive?(this._selectionService.disable(),this.element.classList.add("enable-mouse-events")):this._selectionService.enable(),this.options.screenReaderMode&&(this._accessibilityManager=new y.AccessibilityManager(this,this._renderService)),this._charSizeService.measure(),this.refresh(0,this.rows-1),this._initGlobal(),this.bindMouse()},t.prototype._createRenderer=function(){switch(this.options.rendererType){case"canvas":return this._instantiationService.createInstance(u.Renderer,this._colorManager.colors,this.screenElement,this.linkifier,this.linkifier2);case"dom":return this._instantiationService.createInstance(m.DomRenderer,this._colorManager.colors,this.element,this.screenElement,this._viewportElement,this.linkifier,this.linkifier2);default:throw new Error('Unrecognized rendererType "'+this.options.rendererType+'"')}},t.prototype._setTheme=function(e){var t,r,i;this._theme=e,null===(t=this._colorManager)||void 0===t||t.setTheme(e),null===(r=this._renderService)||void 0===r||r.setColors(this._colorManager.colors),null===(i=this.viewport)||void 0===i||i.onThemeChange(this._colorManager.colors)},t.prototype.bindMouse=function(){var e=this,t=this,r=this.element;function i(e){var r,i,n=t._mouseService.getRawByteCoords(e,t.screenElement,t.cols,t.rows);if(!n)return!1;switch(e.overrideType||e.type){case"mousemove":i=32,void 0===e.buttons?(r=3,void 0!==e.button&&(r=e.button<3?e.button:3)):r=1&e.buttons?0:4&e.buttons?1:2&e.buttons?2:3;break;case"mouseup":i=0,r=e.button<3?e.button:3;break;case"mousedown":i=1,r=e.button<3?e.button:3;break;case"wheel":0!==e.deltaY&&(i=e.deltaY<0?0:1),r=4;break;default:return!1}return!(void 0===i||void 0===r||r>4)&&t.coreMouseService.triggerMouseEvent({col:n.x-33,row:n.y-33,button:r,action:i,ctrl:e.ctrlKey,alt:e.altKey,shift:e.shiftKey})}var n={mouseup:null,wheel:null,mousedrag:null,mousemove:null},o=function(t){return i(t),t.buttons||(e._document.removeEventListener("mouseup",n.mouseup),n.mousedrag&&e._document.removeEventListener("mousemove",n.mousedrag)),e.cancel(t)},s=function(t){return i(t),e.cancel(t,!0)},a=function(e){e.buttons&&i(e)},l=function(e){e.buttons||i(e)};this.register(this.coreMouseService.onProtocolChange((function(t){t?("debug"===e.optionsService.options.logLevel&&e._logService.debug("Binding to mouse events:",e.coreMouseService.explainEvents(t)),e.element.classList.add("enable-mouse-events"),e._selectionService.disable()):(e._logService.debug("Unbinding from mouse events."),e.element.classList.remove("enable-mouse-events"),e._selectionService.enable()),8&t?n.mousemove||(r.addEventListener("mousemove",l),n.mousemove=l):(r.removeEventListener("mousemove",n.mousemove),n.mousemove=null),16&t?n.wheel||(r.addEventListener("wheel",s,{passive:!1}),n.wheel=s):(r.removeEventListener("wheel",n.wheel),n.wheel=null),2&t?n.mouseup||(n.mouseup=o):(e._document.removeEventListener("mouseup",n.mouseup),n.mouseup=null),4&t?n.mousedrag||(n.mousedrag=a):(e._document.removeEventListener("mousemove",n.mousedrag),n.mousedrag=null)}))),this.coreMouseService.activeProtocol=this.coreMouseService.activeProtocol,this.register((0,d.addDisposableDomListener)(r,"mousedown",(function(t){if(t.preventDefault(),e.focus(),e.coreMouseService.areMouseEventsActive&&!e._selectionService.shouldForceSelection(t))return i(t),n.mouseup&&e._document.addEventListener("mouseup",n.mouseup),n.mousedrag&&e._document.addEventListener("mousemove",n.mousedrag),e.cancel(t)}))),this.register((0,d.addDisposableDomListener)(r,"wheel",(function(t){if(!n.wheel){if(!e.buffer.hasScrollback){var r=e.viewport.getLinesScrolled(t);if(0===r)return;for(var i=c.C0.ESC+(e.coreService.decPrivateModes.applicationCursorKeys?"O":"[")+(t.deltaY<0?"A":"B"),o="",s=0;s<Math.abs(r);s++)o+=i;return e.coreService.triggerDataEvent(o,!0),e.cancel(t,!0)}return e.viewport.onWheel(t)?e.cancel(t):void 0}}),{passive:!1})),this.register((0,d.addDisposableDomListener)(r,"touchstart",(function(t){if(!e.coreMouseService.areMouseEventsActive)return e.viewport.onTouchStart(t),e.cancel(t)}),{passive:!0})),this.register((0,d.addDisposableDomListener)(r,"touchmove",(function(t){if(!e.coreMouseService.areMouseEventsActive)return e.viewport.onTouchMove(t)?void 0:e.cancel(t)}),{passive:!1}))},t.prototype.refresh=function(e,t){var r;null===(r=this._renderService)||void 0===r||r.refreshRows(e,t)},t.prototype._queueLinkification=function(e,t){var r;null===(r=this.linkifier)||void 0===r||r.linkifyRows(e,t)},t.prototype.updateCursorStyle=function(e){var t;(null===(t=this._selectionService)||void 0===t?void 0:t.shouldColumnSelect(e))?this.element.classList.add("column-select"):this.element.classList.remove("column-select")},t.prototype._showCursor=function(){this.coreService.isCursorInitialized||(this.coreService.isCursorInitialized=!0,this.refresh(this.buffer.y,this.buffer.y))},t.prototype.scrollLines=function(t,r,i){void 0===i&&(i=0),e.prototype.scrollLines.call(this,t,r,i),this.refresh(0,this.rows-1)},t.prototype.paste=function(e){(0,a.paste)(e,this.textarea,this.coreService)},t.prototype.attachCustomKeyEventHandler=function(e){this._customKeyEventHandler=e},t.prototype.registerLinkMatcher=function(e,t,r){var i=this.linkifier.registerLinkMatcher(e,t,r);return this.refresh(0,this.rows-1),i},t.prototype.deregisterLinkMatcher=function(e){this.linkifier.deregisterLinkMatcher(e)&&this.refresh(0,this.rows-1)},t.prototype.registerLinkProvider=function(e){return this.linkifier2.registerLinkProvider(e)},t.prototype.registerCharacterJoiner=function(e){if(!this._characterJoinerService)throw new Error("Terminal must be opened first");var t=this._characterJoinerService.register(e);return this.refresh(0,this.rows-1),t},t.prototype.deregisterCharacterJoiner=function(e){if(!this._characterJoinerService)throw new Error("Terminal must be opened first");this._characterJoinerService.deregister(e)&&this.refresh(0,this.rows-1)},Object.defineProperty(t.prototype,"markers",{get:function(){return this.buffer.markers},enumerable:!1,configurable:!0}),t.prototype.addMarker=function(e){if(this.buffer===this.buffers.normal)return this.buffer.addMarker(this.buffer.ybase+this.buffer.y+e)},t.prototype.hasSelection=function(){return!!this._selectionService&&this._selectionService.hasSelection},t.prototype.select=function(e,t,r){this._selectionService.setSelection(e,t,r)},t.prototype.getSelection=function(){return this._selectionService?this._selectionService.selectionText:""},t.prototype.getSelectionPosition=function(){if(this._selectionService&&this._selectionService.hasSelection)return{startColumn:this._selectionService.selectionStart[0],startRow:this._selectionService.selectionStart[1],endColumn:this._selectionService.selectionEnd[0],endRow:this._selectionService.selectionEnd[1]}},t.prototype.clearSelection=function(){var e;null===(e=this._selectionService)||void 0===e||e.clearSelection()},t.prototype.selectAll=function(){var e;null===(e=this._selectionService)||void 0===e||e.selectAll()},t.prototype.selectLines=function(e,t){var r;null===(r=this._selectionService)||void 0===r||r.selectLines(e,t)},t.prototype._keyDown=function(e){if(this._keyDownHandled=!1,this._customKeyEventHandler&&!1===this._customKeyEventHandler(e))return!1;if(!this._compositionHelper.keydown(e))return this.buffer.ybase!==this.buffer.ydisp&&this._bufferService.scrollToBottom(),!1;"Dead"!==e.key&&"AltGraph"!==e.key||(this._unprocessedDeadKey=!0);var t=(0,b.evaluateKeyboardEvent)(e,this.coreService.decPrivateModes.applicationCursorKeys,this.browser.isMac,this.options.macOptionIsMeta);if(this.updateCursorStyle(e),3===t.type||2===t.type){var r=this.rows-1;return this.scrollLines(2===t.type?-r:r),this.cancel(e,!0)}return 1===t.type&&this.selectAll(),!!this._isThirdLevelShift(this.browser,e)||(t.cancel&&this.cancel(e,!0),!t.key||(this._unprocessedDeadKey?(this._unprocessedDeadKey=!1,!0):(t.key!==c.C0.ETX&&t.key!==c.C0.CR||(this.textarea.value=""),this._onKey.fire({key:t.key,domEvent:e}),this._showCursor(),this.coreService.triggerDataEvent(t.key,!0),this.optionsService.options.screenReaderMode?void(this._keyDownHandled=!0):this.cancel(e,!0))))},t.prototype._isThirdLevelShift=function(e,t){var r=e.isMac&&!this.options.macOptionIsMeta&&t.altKey&&!t.ctrlKey&&!t.metaKey||e.isWindows&&t.altKey&&t.ctrlKey&&!t.metaKey||e.isWindows&&t.getModifierState("AltGraph");return"keypress"===t.type?r:r&&(!t.keyCode||t.keyCode>47)},t.prototype._keyUp=function(e){this._customKeyEventHandler&&!1===this._customKeyEventHandler(e)||(function(e){return 16===e.keyCode||17===e.keyCode||18===e.keyCode}(e)||this.focus(),this.updateCursorStyle(e),this._keyPressHandled=!1)},t.prototype._keyPress=function(e){var t;if(this._keyPressHandled=!1,this._keyDownHandled)return!1;if(this._customKeyEventHandler&&!1===this._customKeyEventHandler(e))return!1;if(this.cancel(e),e.charCode)t=e.charCode;else if(null===e.which||void 0===e.which)t=e.keyCode;else{if(0===e.which||0===e.charCode)return!1;t=e.which}return!(!t||(e.altKey||e.ctrlKey||e.metaKey)&&!this._isThirdLevelShift(this.browser,e)||(t=String.fromCharCode(t),this._onKey.fire({key:t,domEvent:e}),this._showCursor(),this.coreService.triggerDataEvent(t,!0),this._keyPressHandled=!0,this._unprocessedDeadKey=!1,0))},t.prototype._inputEvent=function(e){if(e.data&&"insertText"===e.inputType&&!e.composed&&!this.optionsService.options.screenReaderMode){if(this._keyPressHandled)return!1;this._unprocessedDeadKey=!1;var t=e.data;return this.coreService.triggerDataEvent(t,!0),this.cancel(e),!0}return!1},t.prototype.bell=function(){var e;this._soundBell()&&(null===(e=this._soundService)||void 0===e||e.playBellSound()),this._onBell.fire()},t.prototype.resize=function(t,r){t!==this.cols||r!==this.rows?e.prototype.resize.call(this,t,r):this._charSizeService&&!this._charSizeService.hasValidSize&&this._charSizeService.measure()},t.prototype._afterResize=function(e,t){var r,i;null===(r=this._charSizeService)||void 0===r||r.measure(),null===(i=this.viewport)||void 0===i||i.syncScrollArea(!0)},t.prototype.clear=function(){if(0!==this.buffer.ybase||0!==this.buffer.y){this.buffer.lines.set(0,this.buffer.lines.get(this.buffer.ybase+this.buffer.y)),this.buffer.lines.length=1,this.buffer.ydisp=0,this.buffer.ybase=0,this.buffer.y=0;for(var e=1;e<this.rows;e++)this.buffer.lines.push(this.buffer.getBlankLine(C.DEFAULT_ATTR_DATA));this.refresh(0,this.rows-1),this._onScroll.fire({position:this.buffer.ydisp,source:0})}},t.prototype.reset=function(){var t,r;this.options.rows=this.rows,this.options.cols=this.cols;var i=this._customKeyEventHandler;this._setup(),e.prototype.reset.call(this),null===(t=this._selectionService)||void 0===t||t.reset(),this._customKeyEventHandler=i,this.refresh(0,this.rows-1),null===(r=this.viewport)||void 0===r||r.syncScrollArea()},t.prototype.clearTextureAtlas=function(){var e;null===(e=this._renderService)||void 0===e||e.clearTextureAtlas()},t.prototype._reportFocus=function(){var e;(null===(e=this.element)||void 0===e?void 0:e.classList.contains("focus"))?this.coreService.triggerDataEvent(c.C0.ESC+"[I"):this.coreService.triggerDataEvent(c.C0.ESC+"[O")},t.prototype._reportWindowsOptions=function(e){if(this._renderService)switch(e){case l.WindowsOptionsReportType.GET_WIN_SIZE_PIXELS:var t=this._renderService.dimensions.scaledCanvasWidth.toFixed(0),r=this._renderService.dimensions.scaledCanvasHeight.toFixed(0);this.coreService.triggerDataEvent(c.C0.ESC+"[4;"+r+";"+t+"t");break;case l.WindowsOptionsReportType.GET_CELL_SIZE_PIXELS:var i=this._renderService.dimensions.scaledCellWidth.toFixed(0),n=this._renderService.dimensions.scaledCellHeight.toFixed(0);this.coreService.triggerDataEvent(c.C0.ESC+"[6;"+n+";"+i+"t")}},t.prototype.cancel=function(e,t){if(this.options.cancelEvents||t)return e.preventDefault(),e.stopPropagation(),!1},t.prototype._visualBell=function(){return!1},t.prototype._soundBell=function(){return"sound"===this.options.bellStyle},t}(R.CoreTerminal);t.Terminal=P},9924:(e,t)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.TimeBasedDebouncer=void 0;var r=function(){function e(e,t){void 0===t&&(t=1e3),this._renderCallback=e,this._debounceThresholdMS=t,this._lastRefreshMs=0,this._additionalRefreshRequested=!1}return e.prototype.dispose=function(){this._refreshTimeoutID&&clearTimeout(this._refreshTimeoutID)},e.prototype.refresh=function(e,t,r){var i=this;this._rowCount=r,e=void 0!==e?e:0,t=void 0!==t?t:this._rowCount-1,this._rowStart=void 0!==this._rowStart?Math.min(this._rowStart,e):e,this._rowEnd=void 0!==this._rowEnd?Math.max(this._rowEnd,t):t;var n=Date.now();if(n-this._lastRefreshMs>=this._debounceThresholdMS)this._lastRefreshMs=n,this._innerRefresh();else if(!this._additionalRefreshRequested){var o=n-this._lastRefreshMs,s=this._debounceThresholdMS-o;this._additionalRefreshRequested=!0,this._refreshTimeoutID=window.setTimeout((function(){i._lastRefreshMs=Date.now(),i._innerRefresh(),i._additionalRefreshRequested=!1,i._refreshTimeoutID=void 0}),s)}},e.prototype._innerRefresh=function(){if(void 0!==this._rowStart&&void 0!==this._rowEnd&&void 0!==this._rowCount){var e=Math.max(this._rowStart,0),t=Math.min(this._rowEnd,this._rowCount-1);this._rowStart=void 0,this._rowEnd=void 0,this._renderCallback(e,t)}},e}();t.TimeBasedDebouncer=r},1680:function(e,t,r){var i,n=this&&this.__extends||(i=function(e,t){return i=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var r in t)Object.prototype.hasOwnProperty.call(t,r)&&(e[r]=t[r])},i(e,t)},function(e,t){if("function"!=typeof t&&null!==t)throw new TypeError("Class extends value "+String(t)+" is not a constructor or null");function r(){this.constructor=e}i(e,t),e.prototype=null===t?Object.create(t):(r.prototype=t.prototype,new r)}),o=this&&this.__decorate||function(e,t,r,i){var n,o=arguments.length,s=o<3?t:null===i?i=Object.getOwnPropertyDescriptor(t,r):i;if("object"==typeof Reflect&&"function"==typeof Reflect.decorate)s=Reflect.decorate(e,t,r,i);else for(var a=e.length-1;a>=0;a--)(n=e[a])&&(s=(o<3?n(s):o>3?n(t,r,s):n(t,r))||s);return o>3&&s&&Object.defineProperty(t,r,s),s},s=this&&this.__param||function(e,t){return function(r,i){t(r,i,e)}};Object.defineProperty(t,"__esModule",{value:!0}),t.Viewport=void 0;var a=r(844),c=r(3656),l=r(4725),u=r(2585),h=function(e){function t(t,r,i,n,o,s,a,l){var u=e.call(this)||this;return u._scrollLines=t,u._viewportElement=r,u._scrollArea=i,u._element=n,u._bufferService=o,u._optionsService=s,u._charSizeService=a,u._renderService=l,u.scrollBarWidth=0,u._currentRowHeight=0,u._currentScaledCellHeight=0,u._lastRecordedBufferLength=0,u._lastRecordedViewportHeight=0,u._lastRecordedBufferHeight=0,u._lastTouchY=0,u._lastScrollTop=0,u._lastHadScrollBar=!1,u._wheelPartialScroll=0,u._refreshAnimationFrame=null,u._ignoreNextScrollEvent=!1,u.scrollBarWidth=u._viewportElement.offsetWidth-u._scrollArea.offsetWidth||15,u._lastHadScrollBar=!0,u.register((0,c.addDisposableDomListener)(u._viewportElement,"scroll",u._onScroll.bind(u))),u._activeBuffer=u._bufferService.buffer,u.register(u._bufferService.buffers.onBufferActivate((function(e){return u._activeBuffer=e.activeBuffer}))),u._renderDimensions=u._renderService.dimensions,u.register(u._renderService.onDimensionsChange((function(e){return u._renderDimensions=e}))),setTimeout((function(){return u.syncScrollArea()}),0),u}return n(t,e),t.prototype.onThemeChange=function(e){this._viewportElement.style.backgroundColor=e.background.css},t.prototype._refresh=function(e){var t=this;if(e)return this._innerRefresh(),void(null!==this._refreshAnimationFrame&&cancelAnimationFrame(this._refreshAnimationFrame));null===this._refreshAnimationFrame&&(this._refreshAnimationFrame=requestAnimationFrame((function(){return t._innerRefresh()})))},t.prototype._innerRefresh=function(){if(this._charSizeService.height>0){this._currentRowHeight=this._renderService.dimensions.scaledCellHeight/window.devicePixelRatio,this._currentScaledCellHeight=this._renderService.dimensions.scaledCellHeight,this._lastRecordedViewportHeight=this._viewportElement.offsetHeight;var e=Math.round(this._currentRowHeight*this._lastRecordedBufferLength)+(this._lastRecordedViewportHeight-this._renderService.dimensions.canvasHeight);this._lastRecordedBufferHeight!==e&&(this._lastRecordedBufferHeight=e,this._scrollArea.style.height=this._lastRecordedBufferHeight+"px")}var t=this._bufferService.buffer.ydisp*this._currentRowHeight;this._viewportElement.scrollTop!==t&&(this._ignoreNextScrollEvent=!0,this._viewportElement.scrollTop=t),0===this._optionsService.options.scrollback?this.scrollBarWidth=0:this.scrollBarWidth=this._viewportElement.offsetWidth-this._scrollArea.offsetWidth||15,this._lastHadScrollBar=this.scrollBarWidth>0;var r=window.getComputedStyle(this._element),i=parseInt(r.paddingLeft)+parseInt(r.paddingRight);this._viewportElement.style.width=(this._renderService.dimensions.actualCellWidth*this._bufferService.cols+this.scrollBarWidth+(this._lastHadScrollBar?i:0)).toString()+"px",this._refreshAnimationFrame=null},t.prototype.syncScrollArea=function(e){if(void 0===e&&(e=!1),this._lastRecordedBufferLength!==this._bufferService.buffer.lines.length)return this._lastRecordedBufferLength=this._bufferService.buffer.lines.length,void this._refresh(e);this._lastRecordedViewportHeight===this._renderService.dimensions.canvasHeight&&this._lastScrollTop===this._activeBuffer.ydisp*this._currentRowHeight&&this._renderDimensions.scaledCellHeight===this._currentScaledCellHeight?this._lastHadScrollBar!==this._optionsService.options.scrollback>0&&this._refresh(e):this._refresh(e)},t.prototype._onScroll=function(e){if(this._lastScrollTop=this._viewportElement.scrollTop,this._viewportElement.offsetParent){if(this._ignoreNextScrollEvent)return this._ignoreNextScrollEvent=!1,void this._scrollLines(0);var t=Math.round(this._lastScrollTop/this._currentRowHeight)-this._bufferService.buffer.ydisp;this._scrollLines(t)}},t.prototype._bubbleScroll=function(e,t){var r=this._viewportElement.scrollTop+this._lastRecordedViewportHeight;return!(t<0&&0!==this._viewportElement.scrollTop||t>0&&r<this._lastRecordedBufferHeight)||(e.cancelable&&e.preventDefault(),!1)},t.prototype.onWheel=function(e){var t=this._getPixelsScrolled(e);return 0!==t&&(this._viewportElement.scrollTop+=t,this._bubbleScroll(e,t))},t.prototype._getPixelsScrolled=function(e){if(0===e.deltaY||e.shiftKey)return 0;var t=this._applyScrollModifier(e.deltaY,e);return e.deltaMode===WheelEvent.DOM_DELTA_LINE?t*=this._currentRowHeight:e.deltaMode===WheelEvent.DOM_DELTA_PAGE&&(t*=this._currentRowHeight*this._bufferService.rows),t},t.prototype.getLinesScrolled=function(e){if(0===e.deltaY||e.shiftKey)return 0;var t=this._applyScrollModifier(e.deltaY,e);return e.deltaMode===WheelEvent.DOM_DELTA_PIXEL?(t/=this._currentRowHeight+0,this._wheelPartialScroll+=t,t=Math.floor(Math.abs(this._wheelPartialScroll))*(this._wheelPartialScroll>0?1:-1),this._wheelPartialScroll%=1):e.deltaMode===WheelEvent.DOM_DELTA_PAGE&&(t*=this._bufferService.rows),t},t.prototype._applyScrollModifier=function(e,t){var r=this._optionsService.options.fastScrollModifier;return"alt"===r&&t.altKey||"ctrl"===r&&t.ctrlKey||"shift"===r&&t.shiftKey?e*this._optionsService.options.fastScrollSensitivity*this._optionsService.options.scrollSensitivity:e*this._optionsService.options.scrollSensitivity},t.prototype.onTouchStart=function(e){this._lastTouchY=e.touches[0].pageY},t.prototype.onTouchMove=function(e){var t=this._lastTouchY-e.touches[0].pageY;return 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i=!1;!1!==this._optionsService.options.customGlyphs&&(i=(0,u.tryDrawCustomChar)(this._ctx,e.getChars(),t*this._scaledCellWidth,r*this._scaledCellHeight,this._scaledCellWidth,this._scaledCellHeight)),i||this._ctx.fillText(e.getChars(),t*this._scaledCellWidth+this._scaledCharLeft,r*this._scaledCellHeight+this._scaledCharTop+this._scaledCharHeight)},e.prototype._drawChars=function(e,t,r){var o,s,a,c=this._getContrastColor(e);c||e.isFgRGB()||e.isBgRGB()?this._drawUncachedChars(e,t,r,c):(e.isInverse()?(s=e.isBgDefault()?n.INVERTED_DEFAULT_COLOR:e.getBgColor(),a=e.isFgDefault()?n.INVERTED_DEFAULT_COLOR:e.getFgColor()):(a=e.isBgDefault()?i.DEFAULT_COLOR:e.getBgColor(),s=e.isFgDefault()?i.DEFAULT_COLOR:e.getFgColor()),s+=this._optionsService.options.drawBoldTextInBrightColors&&e.isBold()&&s<8?8:0,this._currentGlyphIdentifier.chars=e.getChars()||i.WHITESPACE_CELL_CHAR,this._currentGlyphIdentifier.code=e.getCode()||i.WHITESPACE_CELL_CODE,this._currentGlyphIdentifier.bg=a,this._currentGlyphIdentifier.fg=s,this._currentGlyphIdentifier.bold=!!e.isBold(),this._currentGlyphIdentifier.dim=!!e.isDim(),this._currentGlyphIdentifier.italic=!!e.isItalic(),(null===(o=this._charAtlas)||void 0===o?void 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a=e.getFgColor();this._optionsService.options.drawBoldTextInBrightColors&&e.isBold()&&a<8&&(a+=8),this._ctx.fillStyle=this._colors.ansi[a].css}this._clipRow(r),e.isDim()&&(this._ctx.globalAlpha=n.DIM_OPACITY);var l=!1;!1!==this._optionsService.options.customGlyphs&&(l=(0,u.tryDrawCustomChar)(this._ctx,e.getChars(),t*this._scaledCellWidth,r*this._scaledCellHeight,this._scaledCellWidth,this._scaledCellHeight)),l||this._ctx.fillText(e.getChars(),t*this._scaledCellWidth+this._scaledCharLeft,r*this._scaledCellHeight+this._scaledCharTop+this._scaledCharHeight),this._ctx.restore()},e.prototype._clipRow=function(e){this._ctx.beginPath(),this._ctx.rect(0,e*this._scaledCellHeight,this._bufferService.cols*this._scaledCellWidth,this._scaledCellHeight),this._ctx.clip()},e.prototype._getFont=function(e,t){return(t?"italic":"")+" "+(e?this._optionsService.options.fontWeightBold:this._optionsService.options.fontWeight)+" "+this._optionsService.options.fontSize*window.devicePixelRatio+"px 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n(t,e),t.prototype.dispose=function(){this._cursorBlinkStateManager&&(this._cursorBlinkStateManager.dispose(),this._cursorBlinkStateManager=void 0),e.prototype.dispose.call(this)},t.prototype.resize=function(t){e.prototype.resize.call(this,t),this._state={x:0,y:0,isFocused:!1,style:"",width:0}},t.prototype.reset=function(){var e;this._clearCursor(),null===(e=this._cursorBlinkStateManager)||void 0===e||e.restartBlinkAnimation(),this.onOptionsChanged()},t.prototype.onBlur=function(){var e;null===(e=this._cursorBlinkStateManager)||void 0===e||e.pause(),this._onRequestRedraw.fire({start:this._bufferService.buffer.y,end:this._bufferService.buffer.y})},t.prototype.onFocus=function(){var e;null===(e=this._cursorBlinkStateManager)||void 0===e||e.resume(),this._onRequestRedraw.fire({start:this._bufferService.buffer.y,end:this._bufferService.buffer.y})},t.prototype.onOptionsChanged=function(){var 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e=0,t=this._renderLayers;e<t.length;e++)t[e].clearTextureAtlas()},t.prototype._updateDimensions=function(){this._charSizeService.hasValidSize&&(this.dimensions.scaledCharWidth=Math.floor(this._charSizeService.width*window.devicePixelRatio),this.dimensions.scaledCharHeight=Math.ceil(this._charSizeService.height*window.devicePixelRatio),this.dimensions.scaledCellHeight=Math.floor(this.dimensions.scaledCharHeight*this._optionsService.options.lineHeight),this.dimensions.scaledCharTop=1===this._optionsService.options.lineHeight?0:Math.round((this.dimensions.scaledCellHeight-this.dimensions.scaledCharHeight)/2),this.dimensions.scaledCellWidth=this.dimensions.scaledCharWidth+Math.round(this._optionsService.options.letterSpacing),this.dimensions.scaledCharLeft=Math.floor(this._optionsService.options.letterSpacing/2),this.dimensions.scaledCanvasHeight=this._bufferService.rows*this.dimensions.scaledCellHeight,this.dimensions.scaledCanvasWidth=this._bufferService.cols*this.dimensions.scaledCellWidth,this.dimensions.canvasHeight=Math.round(this.dimensions.scaledCanvasHeight/window.devicePixelRatio),this.dimensions.canvasWidth=Math.round(this.dimensions.scaledCanvasWidth/window.devicePixelRatio),this.dimensions.actualCellHeight=this.dimensions.canvasHeight/this._bufferService.rows,this.dimensions.actualCellWidth=this.dimensions.canvasWidth/this._bufferService.cols)},o([s(4,_.IInstantiationService),s(5,_.IBufferService),s(6,f.ICharSizeService),s(7,_.IOptionsService)],t)}(h.Disposable);t.Renderer=g},1752:(e,t)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.throwIfFalsy=void 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u=e.call(this,t,"text",r,n,i,o,s,c)||this;return u._characterJoinerService=l,u._characterWidth=0,u._characterFont="",u._characterOverlapCache={},u._workCell=new h.CellData,u._state=new a.GridCache,u}return n(t,e),t.prototype.resize=function(t){e.prototype.resize.call(this,t);var r=this._getFont(!1,!1);this._characterWidth===t.scaledCharWidth&&this._characterFont===r||(this._characterWidth=t.scaledCharWidth,this._characterFont=r,this._characterOverlapCache={}),this._state.clear(),this._state.resize(this._bufferService.cols,this._bufferService.rows)},t.prototype.reset=function(){this._state.clear(),this._clearAll()},t.prototype._forEachCell=function(e,t,r){for(var i=e;i<=t;i++)for(var n=i+this._bufferService.buffer.ydisp,o=this._bufferService.buffer.lines.get(n),s=this._characterJoinerService.getJoinedCharacters(n),a=0;a<this._bufferService.cols;a++){o.loadCell(a,this._workCell);var c=this._workCell,l=!1,h=a;if(0!==c.getWidth()){if(s.length>0&&a===s[0][0]){l=!0;var f=s.shift();c=new 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r=this;this._forEachCell(e,t,(function(e,t,i){if(!e.isInvisible()&&(r._drawChars(e,t,i),e.isUnderline()||e.isStrikethrough())){if(r._ctx.save(),e.isInverse())if(e.isBgDefault())r._ctx.fillStyle=r._colors.background.css;else if(e.isBgRGB())r._ctx.fillStyle="rgb("+l.AttributeData.toColorRGB(e.getBgColor()).join(",")+")";else{var n=e.getBgColor();r._optionsService.options.drawBoldTextInBrightColors&&e.isBold()&&n<8&&(n+=8),r._ctx.fillStyle=r._colors.ansi[n].css}else if(e.isFgDefault())r._ctx.fillStyle=r._colors.foreground.css;else if(e.isFgRGB())r._ctx.fillStyle="rgb("+l.AttributeData.toColorRGB(e.getFgColor()).join(",")+")";else{var o=e.getFgColor();r._optionsService.options.drawBoldTextInBrightColors&&e.isBold()&&o<8&&(o+=8),r._ctx.fillStyle=r._colors.ansi[o].css}e.isStrikethrough()&&r._fillMiddleLineAtCells(t,i,e.getWidth()),e.isUnderline()&&r._fillBottomLineAtCells(t,i,e.getWidth()),r._ctx.restore()}}))},t.prototype.onGridChanged=function(e,t){0!==this._state.cache.length&&(this._charAtlas&&this._charAtlas.beginFrame(),this._clearCells(0,e,this._bufferService.cols,t-e+1),this._drawBackground(e,t),this._drawForeground(e,t))},t.prototype.onOptionsChanged=function(){this._setTransparency(this._optionsService.options.allowTransparency)},t.prototype._isOverlapping=function(e){if(1!==e.getWidth())return!1;if(e.getCode()<256)return!1;var t=e.getChars();if(this._characterOverlapCache.hasOwnProperty(t))return this._characterOverlapCache[t];this._ctx.save(),this._ctx.font=this._characterFont;var r=Math.floor(this._ctx.measureText(t).width)>this._characterWidth;return this._ctx.restore(),this._characterOverlapCache[t]=r,r},o([s(5,f.IBufferService),s(6,f.IOptionsService),s(7,_.ICharacterJoinerService)],t)}(c.BaseRenderLayer);t.TextRenderLayer=p},9616:(e,t)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.BaseCharAtlas=void 0;var r=function(){function e(){this._didWarmUp=!1}return e.prototype.dispose=function(){},e.prototype.warmUp=function(){this._didWarmUp||(this._doWarmUp(),this._didWarmUp=!0)},e.prototype._doWarmUp=function(){},e.prototype.clear=function(){},e.prototype.beginFrame=function(){},e}();t.BaseCharAtlas=r},1420:(e,t,r)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.removeTerminalFromCache=t.acquireCharAtlas=void 0;var i=r(2040),n=r(1906),o=[];t.acquireCharAtlas=function(e,t,r,s,a){for(var c=(0,i.generateConfig)(s,a,e,r),l=0;l<o.length;l++){var u=(h=o[l]).ownedBy.indexOf(t);if(u>=0){if((0,i.configEquals)(h.config,c))return h.atlas;1===h.ownedBy.length?(h.atlas.dispose(),o.splice(l,1)):h.ownedBy.splice(u,1);break}}for(l=0;l<o.length;l++){var h=o[l];if((0,i.configEquals)(h.config,c))return h.ownedBy.push(t),h.atlas}var f={atlas:new n.DynamicCharAtlas(document,c),config:c,ownedBy:[t]};return o.push(f),f.atlas},t.removeTerminalFromCache=function(e){for(var t=0;t<o.length;t++){var r=o[t].ownedBy.indexOf(e);if(-1!==r){1===o[t].ownedBy.length?(o[t].atlas.dispose(),o.splice(t,1)):o[t].ownedBy.splice(r,1);break}}}},2040:function(e,t,r){var i=this&&this.__spreadArray||function(e,t,r){if(r||2===arguments.length)for(var i,n=0,o=t.length;n<o;n++)!i&&n in t||(i||(i=Array.prototype.slice.call(t,0,n)),i[n]=t[n]);return e.concat(i||Array.prototype.slice.call(t))};Object.defineProperty(t,"__esModule",{value:!0}),t.is256Color=t.configEquals=t.generateConfig=void 0;var n=r(643);t.generateConfig=function(e,t,r,n){var o={foreground:n.foreground,background:n.background,cursor:void 0,cursorAccent:void 0,selection:void 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i=r(6114);t.INVERTED_DEFAULT_COLOR=257,t.DIM_OPACITY=.5,t.TEXT_BASELINE=i.isFirefox?"bottom":"ideographic",t.CHAR_ATLAS_CELL_SPACING=1},1906:function(e,t,r){var i,n=this&&this.__extends||(i=function(e,t){return i=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var r in t)Object.prototype.hasOwnProperty.call(t,r)&&(e[r]=t[r])},i(e,t)},function(e,t){if("function"!=typeof t&&null!==t)throw new TypeError("Class extends value "+String(t)+" is not a constructor or null");function r(){this.constructor=e}i(e,t),e.prototype=null===t?Object.create(t):(r.prototype=t.prototype,new r)});Object.defineProperty(t,"__esModule",{value:!0}),t.NoneCharAtlas=t.DynamicCharAtlas=t.getGlyphCacheKey=void 0;var o=r(8803),s=r(9616),a=r(5680),c=r(7001),l=r(6114),u=r(1752),h=r(4774),f=1024,_=1024,d={css:"rgba(0, 0, 0, 0)",rgba:0};function p(e){return e.code<<21|e.bg<<12|e.fg<<3|(e.bold?0:4)+(e.dim?0:2)+(e.italic?0:1)}t.getGlyphCacheKey=p;var v=function(e){function t(t,r){var i=e.call(this)||this;i._config=r,i._drawToCacheCount=0,i._glyphsWaitingOnBitmap=[],i._bitmapCommitTimeout=null,i._bitmap=null,i._cacheCanvas=t.createElement("canvas"),i._cacheCanvas.width=f,i._cacheCanvas.height=_,i._cacheCtx=(0,u.throwIfFalsy)(i._cacheCanvas.getContext("2d",{alpha:!0}));var n=t.createElement("canvas");n.width=i._config.scaledCharWidth,n.height=i._config.scaledCharHeight,i._tmpCtx=(0,u.throwIfFalsy)(n.getContext("2d",{alpha:i._config.allowTransparency})),i._width=Math.floor(f/i._config.scaledCharWidth),i._height=Math.floor(_/i._config.scaledCharHeight);var o=i._width*i._height;return i._cacheMap=new c.LRUMap(o),i._cacheMap.prealloc(o),i}return n(t,e),t.prototype.dispose=function(){null!==this._bitmapCommitTimeout&&(window.clearTimeout(this._bitmapCommitTimeout),this._bitmapCommitTimeout=null)},t.prototype.beginFrame=function(){this._drawToCacheCount=0},t.prototype.clear=function(){if(this._cacheMap.size>0){var e=this._width*this._height;this._cacheMap=new c.LRUMap(e),this._cacheMap.prealloc(e)}this._cacheCtx.clearRect(0,0,f,_),this._tmpCtx.clearRect(0,0,this._config.scaledCharWidth,this._config.scaledCharHeight)},t.prototype.draw=function(e,t,r,i){if(32===t.code)return!0;if(!this._canCache(t))return!1;var n=p(t),o=this._cacheMap.get(n);if(null!=o)return this._drawFromCache(e,o,r,i),!0;if(this._drawToCacheCount<100){var s;s=this._cacheMap.size<this._cacheMap.capacity?this._cacheMap.size:this._cacheMap.peek().index;var a=this._drawToCache(t,s);return this._cacheMap.set(n,a),this._drawFromCache(e,a,r,i),!0}return!1},t.prototype._canCache=function(e){return e.code<256},t.prototype._toCoordinateX=function(e){return e%this._width*this._config.scaledCharWidth},t.prototype._toCoordinateY=function(e){return Math.floor(e/this._width)*this._config.scaledCharHeight},t.prototype._drawFromCache=function(e,t,r,i){if(!t.isEmpty){var n=this._toCoordinateX(t.index),o=this._toCoordinateY(t.index);e.drawImage(t.inBitmap?this._bitmap:this._cacheCanvas,n,o,this._config.scaledCharWidth,this._config.scaledCharHeight,r,i,this._config.scaledCharWidth,this._config.scaledCharHeight)}},t.prototype._getColorFromAnsiIndex=function(e){return e<this._config.colors.ansi.length?this._config.colors.ansi[e]:a.DEFAULT_ANSI_COLORS[e]},t.prototype._getBackgroundColor=function(e){return this._config.allowTransparency?d:e.bg===o.INVERTED_DEFAULT_COLOR?this._config.colors.foreground:e.bg<256?this._getColorFromAnsiIndex(e.bg):this._config.colors.background},t.prototype._getForegroundColor=function(e){return e.fg===o.INVERTED_DEFAULT_COLOR?h.color.opaque(this._config.colors.background):e.fg<256?this._getColorFromAnsiIndex(e.fg):this._config.colors.foreground},t.prototype._drawToCache=function(e,t){this._drawToCacheCount++,this._tmpCtx.save();var r=this._getBackgroundColor(e);this._tmpCtx.globalCompositeOperation="copy",this._tmpCtx.fillStyle=r.css,this._tmpCtx.fillRect(0,0,this._config.scaledCharWidth,this._config.scaledCharHeight),this._tmpCtx.globalCompositeOperation="source-over";var i=e.bold?this._config.fontWeightBold:this._config.fontWeight,n=e.italic?"italic":"";this._tmpCtx.font=n+" "+i+" "+this._config.fontSize*this._config.devicePixelRatio+"px "+this._config.fontFamily,this._tmpCtx.textBaseline=o.TEXT_BASELINE,this._tmpCtx.fillStyle=this._getForegroundColor(e).css,e.dim&&(this._tmpCtx.globalAlpha=o.DIM_OPACITY),this._tmpCtx.fillText(e.chars,0,this._config.scaledCharHeight);var s=this._tmpCtx.getImageData(0,0,this._config.scaledCharWidth,this._config.scaledCharHeight),a=!1;if(this._config.allowTransparency||(a=y(s,r)),a&&"_"===e.chars&&!this._config.allowTransparency)for(var 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0!==t?(this._unlinkNode(t),this._appendNode(t),t.value):null},e.prototype.peekValue=function(e){var t=this._map[e];return void 0!==t?t.value:null},e.prototype.peek=function(){var e=this._head;return null===e?null:e.value},e.prototype.set=function(e,t){var r=this._map[e];if(void 0!==r)r=this._map[e],this._unlinkNode(r),r.value=t;else if(this.size>=this.capacity)r=this._head,this._unlinkNode(r),delete this._map[r.key],r.key=e,r.value=t,this._map[e]=r;else{var i=this._nodePool;i.length>0?((r=i.pop()).key=e,r.value=t):r={prev:null,next:null,key:e,value:t},this._map[e]=r,this.size++}this._appendNode(r)},e}();t.LRUMap=r},1296:function(e,t,r){var i,n=this&&this.__extends||(i=function(e,t){return i=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var r in t)Object.prototype.hasOwnProperty.call(t,r)&&(e[r]=t[r])},i(e,t)},function(e,t){if("function"!=typeof t&&null!==t)throw new TypeError("Class extends value "+String(t)+" is not a 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f._onLinkHover(e)})),f._linkifier.onHideLinkUnderline((function(e){return f._onLinkLeave(e)})),f._linkifier2.onShowLinkUnderline((function(e){return f._onLinkHover(e)})),f._linkifier2.onHideLinkUnderline((function(e){return f._onLinkLeave(e)})),f}return n(t,e),Object.defineProperty(t.prototype,"onRequestRedraw",{get:function(){return(new 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e=0,t=this._rowElements;e<t.length;e++){var r=t[e];r.style.width=this.dimensions.canvasWidth+"px",r.style.height=this.dimensions.actualCellHeight+"px",r.style.lineHeight=this.dimensions.actualCellHeight+"px",r.style.overflow="hidden"}this._dimensionsStyleElement||(this._dimensionsStyleElement=document.createElement("style"),this._screenElement.appendChild(this._dimensionsStyleElement));var i=this._terminalSelector+" .xterm-rows span { display: inline-block; height: 100%; vertical-align: top; width: "+this.dimensions.actualCellWidth+"px}";this._dimensionsStyleElement.textContent=i,this._selectionContainer.style.height=this._viewportElement.style.height,this._screenElement.style.width=this.dimensions.canvasWidth+"px",this._screenElement.style.height=this.dimensions.canvasHeight+"px"},t.prototype.setColors=function(e){this._colors=e,this._injectCss()},t.prototype._injectCss=function(){var e=this;this._themeStyleElement||(this._themeStyleElement=document.createElement("style"),this._screenElement.appendChild(this._themeStyleElement));var t=this._terminalSelector+" .xterm-rows { color: "+this._colors.foreground.css+"; font-family: "+this._optionsService.options.fontFamily+"; font-size: "+this._optionsService.options.fontSize+"px;}";t+=this._terminalSelector+" span:not(."+a.BOLD_CLASS+") { font-weight: "+this._optionsService.options.fontWeight+";}"+this._terminalSelector+" span."+a.BOLD_CLASS+" { font-weight: "+this._optionsService.options.fontWeightBold+";}"+this._terminalSelector+" span."+a.ITALIC_CLASS+" { font-style: italic;}",t+="@keyframes blink_box_shadow_"+this._terminalClass+" { 50% {  box-shadow: none; }}",t+="@keyframes blink_block_"+this._terminalClass+" { 0% {  background-color: "+this._colors.cursor.css+";  color: "+this._colors.cursorAccent.css+"; } 50% {  background-color: "+this._colors.cursorAccent.css+";  color: "+this._colors.cursor.css+"; }}",t+=this._terminalSelector+" .xterm-rows:not(.xterm-focus) ."+a.CURSOR_CLASS+"."+a.CURSOR_STYLE_BLOCK_CLASS+" { outline: 1px solid "+this._colors.cursor.css+"; outline-offset: -1px;}"+this._terminalSelector+" .xterm-rows.xterm-focus ."+a.CURSOR_CLASS+"."+a.CURSOR_BLINK_CLASS+":not(."+a.CURSOR_STYLE_BLOCK_CLASS+") { animation: blink_box_shadow_"+this._terminalClass+" 1s step-end infinite;}"+this._terminalSelector+" .xterm-rows.xterm-focus ."+a.CURSOR_CLASS+"."+a.CURSOR_BLINK_CLASS+"."+a.CURSOR_STYLE_BLOCK_CLASS+" { animation: blink_block_"+this._terminalClass+" 1s step-end infinite;}"+this._terminalSelector+" .xterm-rows.xterm-focus ."+a.CURSOR_CLASS+"."+a.CURSOR_STYLE_BLOCK_CLASS+" { background-color: "+this._colors.cursor.css+"; color: "+this._colors.cursorAccent.css+";}"+this._terminalSelector+" .xterm-rows ."+a.CURSOR_CLASS+"."+a.CURSOR_STYLE_BAR_CLASS+" { box-shadow: "+this._optionsService.options.cursorWidth+"px 0 0 "+this._colors.cursor.css+" inset;}"+this._terminalSelector+" .xterm-rows ."+a.CURSOR_CLASS+"."+a.CURSOR_STYLE_UNDERLINE_CLASS+" { box-shadow: 0 -1px 0 "+this._colors.cursor.css+" inset;}",t+=this._terminalSelector+" .xterm-selection { position: absolute; top: 0; left: 0; z-index: 1; pointer-events: none;}"+this._terminalSelector+" .xterm-selection div { position: absolute; background-color: "+this._colors.selectionTransparent.css+";}",this._colors.ansi.forEach((function(r,i){t+=e._terminalSelector+" ."+v+i+" { color: "+r.css+"; }"+e._terminalSelector+" ."+g+i+" { background-color: "+r.css+"; }"})),t+=this._terminalSelector+" ."+v+c.INVERTED_DEFAULT_COLOR+" { color: "+_.color.opaque(this._colors.background).css+"; }"+this._terminalSelector+" ."+g+c.INVERTED_DEFAULT_COLOR+" { background-color: "+this._colors.foreground.css+"; }",this._themeStyleElement.textContent=t},t.prototype.onDevicePixelRatioChange=function(){this._updateDimensions()},t.prototype._refreshRowElements=function(e,t){for(var r=this._rowElements.length;r<=t;r++){var i=document.createElement("div");this._rowContainer.appendChild(i),this._rowElements.push(i)}for(;this._rowElements.length>t;)this._rowContainer.removeChild(this._rowElements.pop())},t.prototype.onResize=function(e,t){this._refreshRowElements(e,t),this._updateDimensions()},t.prototype.onCharSizeChanged=function(){this._updateDimensions()},t.prototype.onBlur=function(){this._rowContainer.classList.remove(y)},t.prototype.onFocus=function(){this._rowContainer.classList.add(y)},t.prototype.onSelectionChanged=function(e,t,r){for(;this._selectionContainer.children.length;)this._selectionContainer.removeChild(this._selectionContainer.children[0]);if(e&&t){var i=e[1]-this._bufferService.buffer.ydisp,n=t[1]-this._bufferService.buffer.ydisp,o=Math.max(i,0),s=Math.min(n,this._bufferService.rows-1);if(!(o>=this._bufferService.rows||s<0)){var a=document.createDocumentFragment();if(r)a.appendChild(this._createSelectionElement(o,e[0],t[0],s-o+1));else{var c=i===o?e[0]:0,l=o===n?t[0]:this._bufferService.cols;a.appendChild(this._createSelectionElement(o,c,l));var u=s-o-1;if(a.appendChild(this._createSelectionElement(o+1,0,this._bufferService.cols,u)),o!==s){var h=n===s?t[0]:this._bufferService.cols;a.appendChild(this._createSelectionElement(s,0,h))}}this._selectionContainer.appendChild(a)}}},t.prototype._createSelectionElement=function(e,t,r,i){void 0===i&&(i=1);var n=document.createElement("div");return n.style.height=i*this.dimensions.actualCellHeight+"px",n.style.top=e*this.dimensions.actualCellHeight+"px",n.style.left=t*this.dimensions.actualCellWidth+"px",n.style.width=this.dimensions.actualCellWidth*(r-t)+"px",n},t.prototype.onCursorMove=function(){},t.prototype.onOptionsChanged=function(){this._updateDimensions(),this._injectCss()},t.prototype.clear=function(){for(var e=0,t=this._rowElements;e<t.length;e++)t[e].innerText=""},t.prototype.renderRows=function(e,t){for(var r=this._bufferService.buffer.ybase+this._bufferService.buffer.y,i=Math.min(this._bufferService.buffer.x,this._bufferService.cols-1),n=this._optionsService.options.cursorBlink,o=e;o<=t;o++){var s=this._rowElements[o];s.innerText="";var a=o+this._bufferService.buffer.ydisp,c=this._bufferService.buffer.lines.get(a),l=this._optionsService.options.cursorStyle;s.appendChild(this._rowFactory.createRow(c,a,a===r,l,i,n,this.dimensions.actualCellWidth,this._bufferService.cols))}},Object.defineProperty(t.prototype,"_terminalSelector",{get:function(){return"."+p+this._terminalClass},enumerable:!1,configurable:!0}),t.prototype._onLinkHover=function(e){this._setCellUnderline(e.x1,e.x2,e.y1,e.y2,e.cols,!0)},t.prototype._onLinkLeave=function(e){this._setCellUnderline(e.x1,e.x2,e.y1,e.y2,e.cols,!1)},t.prototype._setCellUnderline=function(e,t,r,i,n,o){for(;e!==t||r!==i;){var s=this._rowElements[r];if(!s)return;var a=s.children[e];a&&(a.style.textDecoration=o?"underline":"none"),++e>=n&&(e=0,r++)}},o([s(6,h.IInstantiationService),s(7,u.ICharSizeService),s(8,h.IOptionsService),s(9,h.IBufferService)],t)}(l.Disposable);t.DomRenderer=b},3787:function(e,t,r){var i=this&&this.__decorate||function(e,t,r,i){var n,o=arguments.length,s=o<3?t:null===i?i=Object.getOwnPropertyDescriptor(t,r):i;if("object"==typeof Reflect&&"function"==typeof Reflect.decorate)s=Reflect.decorate(e,t,r,i);else for(var a=e.length-1;a>=0;a--)(n=e[a])&&(s=(o<3?n(s):o>3?n(t,r,s):n(t,r))||s);return o>3&&s&&Object.defineProperty(t,r,s),s},n=this&&this.__param||function(e,t){return function(r,i){t(r,i,e)}};Object.defineProperty(t,"__esModule",{value:!0}),t.DomRendererRowFactory=t.CURSOR_STYLE_UNDERLINE_CLASS=t.CURSOR_STYLE_BAR_CLASS=t.CURSOR_STYLE_BLOCK_CLASS=t.CURSOR_BLINK_CLASS=t.CURSOR_CLASS=t.STRIKETHROUGH_CLASS=t.UNDERLINE_CLASS=t.ITALIC_CLASS=t.DIM_CLASS=t.BOLD_CLASS=void 0;var o=r(8803),s=r(643),a=r(511),c=r(2585),l=r(4774),u=r(4725),h=r(4269);t.BOLD_CLASS="xterm-bold",t.DIM_CLASS="xterm-dim",t.ITALIC_CLASS="xterm-italic",t.UNDERLINE_CLASS="xterm-underline",t.STRIKETHROUGH_CLASS="xterm-strikethrough",t.CURSOR_CLASS="xterm-cursor",t.CURSOR_BLINK_CLASS="xterm-cursor-blink",t.CURSOR_STYLE_BLOCK_CLASS="xterm-cursor-block",t.CURSOR_STYLE_BAR_CLASS="xterm-cursor-bar",t.CURSOR_STYLE_UNDERLINE_CLASS="xterm-cursor-underline";var f=function(){function e(e,t,r,i,n){this._document=e,this._colors=t,this._characterJoinerService=r,this._optionsService=i,this._coreService=n,this._workCell=new a.CellData}return e.prototype.setColors=function(e){this._colors=e},e.prototype.createRow=function(e,r,i,n,a,c,u,f){for(var d=this._document.createDocumentFragment(),p=this._characterJoinerService.getJoinedCharacters(r),v=0,g=Math.min(e.length,f)-1;g>=0;g--)if(e.loadCell(g,this._workCell).getCode()!==s.NULL_CELL_CODE||i&&g===a){v=g+1;break}for(g=0;g<v;g++){e.loadCell(g,this._workCell);var y=this._workCell.getWidth();if(0!==y){var m=!1,b=g,S=this._workCell;if(p.length>0&&g===p[0][0]){m=!0;var C=p.shift();S=new h.JoinedCellData(this._workCell,e.translateToString(!0,C[0],C[1]),C[1]-C[0]),b=C[1]-1,y=S.getWidth()}var w=this._document.createElement("span");if(y>1&&(w.style.width=u*y+"px"),m&&(w.style.display="inline",a>=g&&a<=b&&(a=g)),!this._coreService.isCursorHidden&&i&&g===a)switch(w.classList.add(t.CURSOR_CLASS),c&&w.classList.add(t.CURSOR_BLINK_CLASS),n){case"bar":w.classList.add(t.CURSOR_STYLE_BAR_CLASS);break;case"underline":w.classList.add(t.CURSOR_STYLE_UNDERLINE_CLASS);break;default:w.classList.add(t.CURSOR_STYLE_BLOCK_CLASS)}S.isBold()&&w.classList.add(t.BOLD_CLASS),S.isItalic()&&w.classList.add(t.ITALIC_CLASS),S.isDim()&&w.classList.add(t.DIM_CLASS),S.isUnderline()&&w.classList.add(t.UNDERLINE_CLASS),S.isInvisible()?w.textContent=s.WHITESPACE_CELL_CHAR:w.textContent=S.getChars()||s.WHITESPACE_CELL_CHAR,S.isStrikethrough()&&w.classList.add(t.STRIKETHROUGH_CLASS);var L=S.getFgColor(),E=S.getFgColorMode(),x=S.getBgColor(),A=S.getBgColorMode(),k=!!S.isInverse();if(k){var M=L;L=x,x=M;var R=E;E=A,A=R}switch(E){case 16777216:case 33554432:S.isBold()&&L<8&&this._optionsService.options.drawBoldTextInBrightColors&&(L+=8),this._applyMinimumContrast(w,this._colors.background,this._colors.ansi[L])||w.classList.add("xterm-fg-"+L);break;case 50331648:var T=l.rgba.toColor(L>>16&255,L>>8&255,255&L);this._applyMinimumContrast(w,this._colors.background,T)||this._addStyle(w,"color:#"+_(L.toString(16),"0",6));break;default:this._applyMinimumContrast(w,this._colors.background,this._colors.foreground)||k&&w.classList.add("xterm-fg-"+o.INVERTED_DEFAULT_COLOR)}switch(A){case 16777216:case 33554432:w.classList.add("xterm-bg-"+x);break;case 50331648:this._addStyle(w,"background-color:#"+_(x.toString(16),"0",6));break;default:k&&w.classList.add("xterm-bg-"+o.INVERTED_DEFAULT_COLOR)}d.appendChild(w),g=b}}return d},e.prototype._applyMinimumContrast=function(e,t,r){if(1===this._optionsService.options.minimumContrastRatio)return!1;var i=this._colors.contrastCache.getColor(this._workCell.bg,this._workCell.fg);return void 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this.isSelectAllActive?[0,0]:this.selectionEnd&&this.selectionStart&&this.areSelectionValuesReversed()?this.selectionEnd:this.selectionStart},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"finalSelectionEnd",{get:function(){if(this.isSelectAllActive)return[this._bufferService.cols,this._bufferService.buffer.ybase+this._bufferService.rows-1];if(this.selectionStart){if(!this.selectionEnd||this.areSelectionValuesReversed()){var e=this.selectionStart[0]+this.selectionStartLength;return e>this._bufferService.cols?e%this._bufferService.cols==0?[this._bufferService.cols,this.selectionStart[1]+Math.floor(e/this._bufferService.cols)-1]:[e%this._bufferService.cols,this.selectionStart[1]+Math.floor(e/this._bufferService.cols)]:[e,this.selectionStart[1]]}return 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this._model.selectionStart=[n.start.x-1,n.start.y-1],this._model.selectionStartLength=(0,v.getRangeLength)(n,this._bufferService.cols),this._model.selectionEnd=void 0,!0;var o=this._getMouseBufferCoords(e);return!!o&&(this._selectWordAt(o,t),this._model.selectionEnd=void 0,!0)},t.prototype.selectAll=function(){this._model.isSelectAllActive=!0,this.refresh(),this._onSelectionChange.fire()},t.prototype.selectLines=function(e,t){this._model.clearSelection(),e=Math.max(e,0),t=Math.min(t,this._bufferService.buffer.lines.length-1),this._model.selectionStart=[0,e],this._model.selectionEnd=[this._bufferService.cols,t],this.refresh(),this._onSelectionChange.fire()},t.prototype._onTrim=function(e){this._model.onTrim(e)&&this.refresh()},t.prototype._getMouseBufferCoords=function(e){var t=this._mouseService.getCoords(e,this._screenElement,this._bufferService.cols,this._bufferService.rows,!0);if(t)return t[0]--,t[1]--,t[1]+=this._bufferService.buffer.ydisp,t},t.prototype._getMouseEventScrollAmount=function(e){var t=(0,_.getCoordsRelativeToElement)(e,this._screenElement)[1],r=this._renderService.dimensions.canvasHeight;return t>=0&&t<=r?0:(t>r&&(t-=r),t=Math.min(Math.max(t,-50),50),(t/=50)/Math.abs(t)+Math.round(14*t))},t.prototype.shouldForceSelection=function(e){return a.isMac?e.altKey&&this._optionsService.options.macOptionClickForcesSelection:e.shiftKey},t.prototype.onMouseDown=function(e){if(this._mouseDownTimeStamp=e.timeStamp,(2!==e.button||!this.hasSelection)&&0===e.button){if(!this._enabled){if(!this.shouldForceSelection(e))return;e.stopPropagation()}e.preventDefault(),this._dragScrollAmount=0,this._enabled&&e.shiftKey?this._onIncrementalClick(e):1===e.detail?this._onSingleClick(e):2===e.detail?this._onDoubleClick(e):3===e.detail&&this._onTripleClick(e),this._addMouseDownListeners(),this.refresh(!0)}},t.prototype._addMouseDownListeners=function(){var e=this;this._screenElement.ownerDocument&&(this._screenElement.ownerDocument.addEventListener("mousemove",this._mouseMoveListener),this._screenElement.ownerDocument.addEventListener("mouseup",this._mouseUpListener)),this._dragScrollIntervalTimer=window.setInterval((function(){return e._dragScroll()}),50)},t.prototype._removeMouseDownListeners=function(){this._screenElement.ownerDocument&&(this._screenElement.ownerDocument.removeEventListener("mousemove",this._mouseMoveListener),this._screenElement.ownerDocument.removeEventListener("mouseup",this._mouseUpListener)),clearInterval(this._dragScrollIntervalTimer),this._dragScrollIntervalTimer=void 0},t.prototype._onIncrementalClick=function(e){this._model.selectionStart&&(this._model.selectionEnd=this._getMouseBufferCoords(e))},t.prototype._onSingleClick=function(e){if(this._model.selectionStartLength=0,this._model.isSelectAllActive=!1,this._activeSelectionMode=this.shouldColumnSelect(e)?3:0,this._model.selectionStart=this._getMouseBufferCoords(e),this._model.selectionStart){this._model.selectionEnd=void 0;var t=this._bufferService.buffer.lines.get(this._model.selectionStart[1]);t&&t.length!==this._model.selectionStart[0]&&0===t.hasWidth(this._model.selectionStart[0])&&this._model.selectionStart[0]++}},t.prototype._onDoubleClick=function(e){this._selectWordAtCursor(e,!0)&&(this._activeSelectionMode=1)},t.prototype._onTripleClick=function(e){var t=this._getMouseBufferCoords(e);t&&(this._activeSelectionMode=2,this._selectLineAt(t[1]))},t.prototype.shouldColumnSelect=function(e){return e.altKey&&!(a.isMac&&this._optionsService.options.macOptionClickForcesSelection)},t.prototype._onMouseMove=function(e){if(e.stopImmediatePropagation(),this._model.selectionStart){var t=this._model.selectionEnd?[this._model.selectionEnd[0],this._model.selectionEnd[1]]:null;if(this._model.selectionEnd=this._getMouseBufferCoords(e),this._model.selectionEnd){2===this._activeSelectionMode?this._model.selectionEnd[1]<this._model.selectionStart[1]?this._model.selectionEnd[0]=0:this._model.selectionEnd[0]=this._bufferService.cols:1===this._activeSelectionMode&&this._selectToWordAt(this._model.selectionEnd),this._dragScrollAmount=this._getMouseEventScrollAmount(e),3!==this._activeSelectionMode&&(this._dragScrollAmount>0?this._model.selectionEnd[0]=this._bufferService.cols:this._dragScrollAmount<0&&(this._model.selectionEnd[0]=0));var r=this._bufferService.buffer;if(this._model.selectionEnd[1]<r.lines.length){var i=r.lines.get(this._model.selectionEnd[1]);i&&0===i.hasWidth(this._model.selectionEnd[0])&&this._model.selectionEnd[0]++}t&&t[0]===this._model.selectionEnd[0]&&t[1]===this._model.selectionEnd[1]||this.refresh(!0)}else this.refresh(!0)}},t.prototype._dragScroll=function(){if(this._model.selectionEnd&&this._model.selectionStart&&this._dragScrollAmount){this._onRequestScrollLines.fire({amount:this._dragScrollAmount,suppressScrollEvent:!1});var e=this._bufferService.buffer;this._dragScrollAmount>0?(3!==this._activeSelectionMode&&(this._model.selectionEnd[0]=this._bufferService.cols),this._model.selectionEnd[1]=Math.min(e.ydisp+this._bufferService.rows,e.lines.length-1)):(3!==this._activeSelectionMode&&(this._model.selectionEnd[0]=0),this._model.selectionEnd[1]=e.ydisp),this.refresh()}},t.prototype._onMouseUp=function(e){var t=e.timeStamp-this._mouseDownTimeStamp;if(this._removeMouseDownListeners(),this.selectionText.length<=1&&t<500&&e.altKey&&this._optionsService.getOption("altClickMovesCursor")){if(this._bufferService.buffer.ybase===this._bufferService.buffer.ydisp){var r=this._mouseService.getCoords(e,this._element,this._bufferService.cols,this._bufferService.rows,!1);if(r&&void 0!==r[0]&&void 0!==r[1]){var i=(0,d.moveToCellSequence)(r[0]-1,r[1]-1,this._bufferService,this._coreService.decPrivateModes.applicationCursorKeys);this._coreService.triggerDataEvent(i,!0)}}}else this._fireEventIfSelectionChanged()},t.prototype._fireEventIfSelectionChanged=function(){var e=this._model.finalSelectionStart,t=this._model.finalSelectionEnd,r=!(!e||!t||e[0]===t[0]&&e[1]===t[1]);r?e&&t&&(this._oldSelectionStart&&this._oldSelectionEnd&&e[0]===this._oldSelectionStart[0]&&e[1]===this._oldSelectionStart[1]&&t[0]===this._oldSelectionEnd[0]&&t[1]===this._oldSelectionEnd[1]||this._fireOnSelectionChange(e,t,r)):this._oldHasSelection&&this._fireOnSelectionChange(e,t,r)},t.prototype._fireOnSelectionChange=function(e,t,r){this._oldSelectionStart=e,this._oldSelectionEnd=t,this._oldHasSelection=r,this._onSelectionChange.fire()},t.prototype._onBufferActivate=function(e){var t=this;this.clearSelection(),this._trimListener.dispose(),this._trimListener=e.activeBuffer.lines.onTrim((function(e){return t._onTrim(e)}))},t.prototype._convertViewportColToCharacterIndex=function(e,t){for(var r=t[0],i=0;t[0]>=i;i++){var n=e.loadCell(i,this._workCell).getChars().length;0===this._workCell.getWidth()?r--:n>1&&t[0]!==i&&(r+=n-1)}return r},t.prototype.setSelection=function(e,t,r){this._model.clearSelection(),this._removeMouseDownListeners(),this._model.selectionStart=[e,t],this._model.selectionStartLength=r,this.refresh()},t.prototype.rightClickSelect=function(e){this._isClickInSelection(e)||(this._selectWordAtCursor(e,!1)&&this.refresh(!0),this._fireEventIfSelectionChanged())},t.prototype._getWordAt=function(e,t,r,i){if(void 0===r&&(r=!0),void 0===i&&(i=!0),!(e[0]>=this._bufferService.cols)){var n=this._bufferService.buffer,o=n.lines.get(e[1]);if(o){var s=n.translateBufferLineToString(e[1],!1),a=this._convertViewportColToCharacterIndex(o,e),c=a,l=e[0]-a,u=0,h=0,f=0,_=0;if(" "===s.charAt(a)){for(;a>0&&" "===s.charAt(a-1);)a--;for(;c<s.length&&" "===s.charAt(c+1);)c++}else{var d=e[0],p=e[0];0===o.getWidth(d)&&(u++,d--),2===o.getWidth(p)&&(h++,p++);var v=o.getString(p).length;for(v>1&&(_+=v-1,c+=v-1);d>0&&a>0&&!this._isCharWordSeparator(o.loadCell(d-1,this._workCell));){o.loadCell(d-1,this._workCell);var g=this._workCell.getChars().length;0===this._workCell.getWidth()?(u++,d--):g>1&&(f+=g-1,a-=g-1),a--,d--}for(;p<o.length&&c+1<s.length&&!this._isCharWordSeparator(o.loadCell(p+1,this._workCell));){o.loadCell(p+1,this._workCell);var y=this._workCell.getChars().length;2===this._workCell.getWidth()?(h++,p++):y>1&&(_+=y-1,c+=y-1),c++,p++}}c++;var m=a+l-u+f,b=Math.min(this._bufferService.cols,c-a+u+h-f-_);if(t||""!==s.slice(a,c).trim()){if(r&&0===m&&32!==o.getCodePoint(0)){var S=n.lines.get(e[1]-1);if(S&&o.isWrapped&&32!==S.getCodePoint(this._bufferService.cols-1)){var C=this._getWordAt([this._bufferService.cols-1,e[1]-1],!1,!0,!1);if(C){var w=this._bufferService.cols-C.start;m-=w,b+=w}}}if(i&&m+b===this._bufferService.cols&&32!==o.getCodePoint(this._bufferService.cols-1)){var L=n.lines.get(e[1]+1);if((null==L?void 0:L.isWrapped)&&32!==L.getCodePoint(0)){var E=this._getWordAt([0,e[1]+1],!1,!1,!0);E&&(b+=E.length)}}return{start:m,length:b}}}}},t.prototype._selectWordAt=function(e,t){var r=this._getWordAt(e,t);if(r){for(;r.start<0;)r.start+=this._bufferService.cols,e[1]--;this._model.selectionStart=[r.start,e[1]],this._model.selectionStartLength=r.length}},t.prototype._selectToWordAt=function(e){var t=this._getWordAt(e,!0);if(t){for(var r=e[1];t.start<0;)t.start+=this._bufferService.cols,r--;if(!this._model.areSelectionValuesReversed())for(;t.start+t.length>this._bufferService.cols;)t.length-=this._bufferService.cols,r++;this._model.selectionEnd=[this._model.areSelectionValuesReversed()?t.start:t.start+t.length,r]}},t.prototype._isCharWordSeparator=function(e){return 0!==e.getWidth()&&this._optionsService.options.wordSeparator.indexOf(e.getChars())>=0},t.prototype._selectLineAt=function(e){var t=this._bufferService.buffer.getWrappedRangeForLine(e);this._model.selectionStart=[0,t.first],this._model.selectionEnd=[this._bufferService.cols,t.last],this._model.selectionStartLength=0},o([s(3,f.IBufferService),s(4,f.ICoreService),s(5,h.IMouseService),s(6,f.IOptionsService),s(7,h.IRenderService)],t)}(p.Disposable);t.SelectionService=m},4725:(e,t,r)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.ICharacterJoinerService=t.ISoundService=t.ISelectionService=t.IRenderService=t.IMouseService=t.ICoreBrowserService=t.ICharSizeService=void 0;var i=r(8343);t.ICharSizeService=(0,i.createDecorator)("CharSizeService"),t.ICoreBrowserService=(0,i.createDecorator)("CoreBrowserService"),t.IMouseService=(0,i.createDecorator)("MouseService"),t.IRenderService=(0,i.createDecorator)("RenderService"),t.ISelectionService=(0,i.createDecorator)("SelectionService"),t.ISoundService=(0,i.createDecorator)("SoundService"),t.ICharacterJoinerService=(0,i.createDecorator)("CharacterJoinerService")},357:function(e,t,r){var i=this&&this.__decorate||function(e,t,r,i){var n,o=arguments.length,s=o<3?t:null===i?i=Object.getOwnPropertyDescriptor(t,r):i;if("object"==typeof Reflect&&"function"==typeof Reflect.decorate)s=Reflect.decorate(e,t,r,i);else for(var a=e.length-1;a>=0;a--)(n=e[a])&&(s=(o<3?n(s):o>3?n(t,r,s):n(t,r))||s);return o>3&&s&&Object.defineProperty(t,r,s),s},n=this&&this.__param||function(e,t){return function(r,i){t(r,i,e)}};Object.defineProperty(t,"__esModule",{value:!0}),t.SoundService=void 0;var o=r(2585),s=function(){function e(e){this._optionsService=e}return Object.defineProperty(e,"audioContext",{get:function(){if(!e._audioContext){var t=window.AudioContext||window.webkitAudioContext;if(!t)return console.warn("Web Audio API is not supported by this browser. Consider upgrading to the latest version"),null;e._audioContext=new t}return e._audioContext},enumerable:!1,configurable:!0}),e.prototype.playBellSound=function(){var t=e.audioContext;if(t){var r=t.createBufferSource();t.decodeAudioData(this._base64ToArrayBuffer(this._removeMimeType(this._optionsService.options.bellSound)),(function(e){r.buffer=e,r.connect(t.destination),r.start(0)}))}},e.prototype._base64ToArrayBuffer=function(e){for(var t=window.atob(e),r=t.length,i=new Uint8Array(r),n=0;n<r;n++)i[n]=t.charCodeAt(n);return i.buffer},e.prototype._removeMimeType=function(e){return e.split(",")[1]},e=i([n(0,o.IOptionsService)],e)}();t.SoundService=s},6349:(e,t,r)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.CircularList=void 0;var i=r(8460),n=function(){function e(e){this._maxLength=e,this.onDeleteEmitter=new i.EventEmitter,this.onInsertEmitter=new i.EventEmitter,this.onTrimEmitter=new i.EventEmitter,this._array=new Array(this._maxLength),this._startIndex=0,this._length=0}return Object.defineProperty(e.prototype,"onDelete",{get:function(){return this.onDeleteEmitter.event},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"onInsert",{get:function(){return this.onInsertEmitter.event},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"onTrim",{get:function(){return this.onTrimEmitter.event},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"maxLength",{get:function(){return this._maxLength},set:function(e){if(this._maxLength!==e){for(var t=new Array(e),r=0;r<Math.min(e,this.length);r++)t[r]=this._array[this._getCyclicIndex(r)];this._array=t,this._maxLength=e,this._startIndex=0}},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"length",{get:function(){return this._length},set:function(e){if(e>this._length)for(var t=this._length;t<e;t++)this._array[t]=void 0;this._length=e},enumerable:!1,configurable:!0}),e.prototype.get=function(e){return this._array[this._getCyclicIndex(e)]},e.prototype.set=function(e,t){this._array[this._getCyclicIndex(e)]=t},e.prototype.push=function(e){this._array[this._getCyclicIndex(this._length)]=e,this._length===this._maxLength?(this._startIndex=++this._startIndex%this._maxLength,this.onTrimEmitter.fire(1)):this._length++},e.prototype.recycle=function(){if(this._length!==this._maxLength)throw new Error("Can only recycle when the buffer is full");return this._startIndex=++this._startIndex%this._maxLength,this.onTrimEmitter.fire(1),this._array[this._getCyclicIndex(this._length-1)]},Object.defineProperty(e.prototype,"isFull",{get:function(){return this._length===this._maxLength},enumerable:!1,configurable:!0}),e.prototype.pop=function(){return this._array[this._getCyclicIndex(this._length---1)]},e.prototype.splice=function(e,t){for(var r=[],i=2;i<arguments.length;i++)r[i-2]=arguments[i];if(t){for(var n=e;n<this._length-t;n++)this._array[this._getCyclicIndex(n)]=this._array[this._getCyclicIndex(n+t)];this._length-=t,this.onDeleteEmitter.fire({index:e,amount:t})}for(n=this._length-1;n>=e;n--)this._array[this._getCyclicIndex(n+r.length)]=this._array[this._getCyclicIndex(n)];for(n=0;n<r.length;n++)this._array[this._getCyclicIndex(e+n)]=r[n];if(r.length&&this.onInsertEmitter.fire({index:e,amount:r.length}),this._length+r.length>this._maxLength){var o=this._length+r.length-this._maxLength;this._startIndex+=o,this._length=this._maxLength,this.onTrimEmitter.fire(o)}else this._length+=r.length},e.prototype.trimStart=function(e){e>this._length&&(e=this._length),this._startIndex+=e,this._length-=e,this.onTrimEmitter.fire(e)},e.prototype.shiftElements=function(e,t,r){if(!(t<=0)){if(e<0||e>=this._length)throw new Error("start argument out of range");if(e+r<0)throw new Error("Cannot shift elements in list beyond index 0");if(r>0){for(var i=t-1;i>=0;i--)this.set(e+i+r,this.get(e+i));var n=e+t+r-this._length;if(n>0)for(this._length+=n;this._length>this._maxLength;)this._length--,this._startIndex++,this.onTrimEmitter.fire(1)}else for(i=0;i<t;i++)this.set(e+i+r,this.get(e+i))}},e.prototype._getCyclicIndex=function(e){return(this._startIndex+e)%this._maxLength},e}();t.CircularList=n},1439:(e,t)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.clone=void 0,t.clone=function e(t,r){if(void 0===r&&(r=5),"object"!=typeof t)return t;var i=Array.isArray(t)?[]:{};for(var n in t)i[n]=r<=1?t[n]:t[n]&&e(t[n],r-1);return i}},8969:function(e,t,r){var i,n=this&&this.__extends||(i=function(e,t){return i=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var r in t)Object.prototype.hasOwnProperty.call(t,r)&&(e[r]=t[r])},i(e,t)},function(e,t){if("function"!=typeof t&&null!==t)throw new TypeError("Class extends value "+String(t)+" is not a constructor or null");function r(){this.constructor=e}i(e,t),e.prototype=null===t?Object.create(t):(r.prototype=t.prototype,new r)});Object.defineProperty(t,"__esModule",{value:!0}),t.CoreTerminal=void 0;var o=r(844),s=r(2585),a=r(4348),c=r(7866),l=r(744),u=r(7302),h=r(6975),f=r(8460),_=r(1753),d=r(3730),p=r(1480),v=r(7994),g=r(9282),y=r(5435),m=r(5981),b=!1,S=function(e){function t(t){var r=e.call(this)||this;return r._onBinary=new f.EventEmitter,r._onData=new f.EventEmitter,r._onLineFeed=new f.EventEmitter,r._onResize=new f.EventEmitter,r._onScroll=new f.EventEmitter,r._instantiationService=new a.InstantiationService,r.optionsService=new u.OptionsService(t),r._instantiationService.setService(s.IOptionsService,r.optionsService),r._bufferService=r.register(r._instantiationService.createInstance(l.BufferService)),r._instantiationService.setService(s.IBufferService,r._bufferService),r._logService=r._instantiationService.createInstance(c.LogService),r._instantiationService.setService(s.ILogService,r._logService),r.coreService=r.register(r._instantiationService.createInstance(h.CoreService,(function(){return r.scrollToBottom()}))),r._instantiationService.setService(s.ICoreService,r.coreService),r.coreMouseService=r._instantiationService.createInstance(_.CoreMouseService),r._instantiationService.setService(s.ICoreMouseService,r.coreMouseService),r._dirtyRowService=r._instantiationService.createInstance(d.DirtyRowService),r._instantiationService.setService(s.IDirtyRowService,r._dirtyRowService),r.unicodeService=r._instantiationService.createInstance(p.UnicodeService),r._instantiationService.setService(s.IUnicodeService,r.unicodeService),r._charsetService=r._instantiationService.createInstance(v.CharsetService),r._instantiationService.setService(s.ICharsetService,r._charsetService),r._inputHandler=new y.InputHandler(r._bufferService,r._charsetService,r.coreService,r._dirtyRowService,r._logService,r.optionsService,r.coreMouseService,r.unicodeService),r.register((0,f.forwardEvent)(r._inputHandler.onLineFeed,r._onLineFeed)),r.register(r._inputHandler),r.register((0,f.forwardEvent)(r._bufferService.onResize,r._onResize)),r.register((0,f.forwardEvent)(r.coreService.onData,r._onData)),r.register((0,f.forwardEvent)(r.coreService.onBinary,r._onBinary)),r.register(r.optionsService.onOptionChange((function(e){return r._updateOptions(e)}))),r.register(r._bufferService.onScroll((function(e){r._onScroll.fire({position:r._bufferService.buffer.ydisp,source:0}),r._dirtyRowService.markRangeDirty(r._bufferService.buffer.scrollTop,r._bufferService.buffer.scrollBottom)}))),r.register(r._inputHandler.onScroll((function(e){r._onScroll.fire({position:r._bufferService.buffer.ydisp,source:0}),r._dirtyRowService.markRangeDirty(r._bufferService.buffer.scrollTop,r._bufferService.buffer.scrollBottom)}))),r._writeBuffer=new m.WriteBuffer((function(e,t){return r._inputHandler.parse(e,t)})),r}return n(t,e),Object.defineProperty(t.prototype,"onBinary",{get:function(){return this._onBinary.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onData",{get:function(){return this._onData.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onLineFeed",{get:function(){return this._onLineFeed.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onResize",{get:function(){return this._onResize.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onScroll",{get:function(){var e=this;return this._onScrollApi||(this._onScrollApi=new f.EventEmitter,this.register(this._onScroll.event((function(t){var r;null===(r=e._onScrollApi)||void 0===r||r.fire(t.position)})))),this._onScrollApi.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"cols",{get:function(){return this._bufferService.cols},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"rows",{get:function(){return this._bufferService.rows},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"buffers",{get:function(){return this._bufferService.buffers},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"options",{get:function(){return this.optionsService.options},set:function(e){for(var t in e)this.optionsService.options[t]=e[t]},enumerable:!1,configurable:!0}),t.prototype.dispose=function(){var t;this._isDisposed||(e.prototype.dispose.call(this),null===(t=this._windowsMode)||void 0===t||t.dispose(),this._windowsMode=void 0)},t.prototype.write=function(e,t){this._writeBuffer.write(e,t)},t.prototype.writeSync=function(e,t){this._logService.logLevel<=s.LogLevelEnum.WARN&&!b&&(this._logService.warn("writeSync is unreliable and will be removed soon."),b=!0),this._writeBuffer.writeSync(e,t)},t.prototype.resize=function(e,t){isNaN(e)||isNaN(t)||(e=Math.max(e,l.MINIMUM_COLS),t=Math.max(t,l.MINIMUM_ROWS),this._bufferService.resize(e,t))},t.prototype.scroll=function(e,t){void 0===t&&(t=!1),this._bufferService.scroll(e,t)},t.prototype.scrollLines=function(e,t,r){this._bufferService.scrollLines(e,t,r)},t.prototype.scrollPages=function(e){this._bufferService.scrollPages(e)},t.prototype.scrollToTop=function(){this._bufferService.scrollToTop()},t.prototype.scrollToBottom=function(){this._bufferService.scrollToBottom()},t.prototype.scrollToLine=function(e){this._bufferService.scrollToLine(e)},t.prototype.registerEscHandler=function(e,t){return this._inputHandler.registerEscHandler(e,t)},t.prototype.registerDcsHandler=function(e,t){return this._inputHandler.registerDcsHandler(e,t)},t.prototype.registerCsiHandler=function(e,t){return this._inputHandler.registerCsiHandler(e,t)},t.prototype.registerOscHandler=function(e,t){return this._inputHandler.registerOscHandler(e,t)},t.prototype._setup=function(){this.optionsService.options.windowsMode&&this._enableWindowsMode()},t.prototype.reset=function(){this._inputHandler.reset(),this._bufferService.reset(),this._charsetService.reset(),this.coreService.reset(),this.coreMouseService.reset()},t.prototype._updateOptions=function(e){var t;switch(e){case"scrollback":this.buffers.resize(this.cols,this.rows);break;case"windowsMode":this.optionsService.options.windowsMode?this._enableWindowsMode():(null===(t=this._windowsMode)||void 0===t||t.dispose(),this._windowsMode=void 0)}},t.prototype._enableWindowsMode=function(){var e=this;if(!this._windowsMode){var t=[];t.push(this.onLineFeed(g.updateWindowsModeWrappedState.bind(null,this._bufferService))),t.push(this.registerCsiHandler({final:"H"},(function(){return(0,g.updateWindowsModeWrappedState)(e._bufferService),!1}))),this._windowsMode={dispose:function(){for(var e=0,r=t;e<r.length;e++)r[e].dispose()}}}},t}(o.Disposable);t.CoreTerminal=S},8460:(e,t)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.forwardEvent=t.EventEmitter=void 0;var r=function(){function e(){this._listeners=[],this._disposed=!1}return Object.defineProperty(e.prototype,"event",{get:function(){var e=this;return this._event||(this._event=function(t){return e._listeners.push(t),{dispose:function(){if(!e._disposed)for(var r=0;r<e._listeners.length;r++)if(e._listeners[r]===t)return void e._listeners.splice(r,1)}}}),this._event},enumerable:!1,configurable:!0}),e.prototype.fire=function(e,t){for(var r=[],i=0;i<this._listeners.length;i++)r.push(this._listeners[i]);for(i=0;i<r.length;i++)r[i].call(void 0,e,t)},e.prototype.dispose=function(){this._listeners&&(this._listeners.length=0),this._disposed=!0},e}();t.EventEmitter=r,t.forwardEvent=function(e,t){return e((function(e){return t.fire(e)}))}},5435:function(e,t,r){var i,n=this&&this.__extends||(i=function(e,t){return i=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var r in t)Object.prototype.hasOwnProperty.call(t,r)&&(e[r]=t[r])},i(e,t)},function(e,t){if("function"!=typeof t&&null!==t)throw new TypeError("Class extends value "+String(t)+" is not a constructor or null");function r(){this.constructor=e}i(e,t),e.prototype=null===t?Object.create(t):(r.prototype=t.prototype,new r)});Object.defineProperty(t,"__esModule",{value:!0}),t.InputHandler=t.WindowsOptionsReportType=void 0;var o,s=r(2584),a=r(7116),c=r(2015),l=r(844),u=r(8273),h=r(482),f=r(8437),_=r(8460),d=r(643),p=r(511),v=r(3734),g=r(2585),y=r(6242),m=r(6351),b=r(5941),S={"(":0,")":1,"*":2,"+":3,"-":1,".":2},C=131072;function w(e,t){if(e>24)return t.setWinLines||!1;switch(e){case 1:return!!t.restoreWin;case 2:return!!t.minimizeWin;case 3:return!!t.setWinPosition;case 4:return!!t.setWinSizePixels;case 5:return!!t.raiseWin;case 6:return!!t.lowerWin;case 7:return!!t.refreshWin;case 8:return!!t.setWinSizeChars;case 9:return!!t.maximizeWin;case 10:return!!t.fullscreenWin;case 11:return!!t.getWinState;case 13:return!!t.getWinPosition;case 14:return!!t.getWinSizePixels;case 15:return!!t.getScreenSizePixels;case 16:return!!t.getCellSizePixels;case 18:return!!t.getWinSizeChars;case 19:return!!t.getScreenSizeChars;case 20:return!!t.getIconTitle;case 21:return!!t.getWinTitle;case 22:return!!t.pushTitle;case 23:return!!t.popTitle;case 24:return!!t.setWinLines}return!1}!function(e){e[e.GET_WIN_SIZE_PIXELS=0]="GET_WIN_SIZE_PIXELS",e[e.GET_CELL_SIZE_PIXELS=1]="GET_CELL_SIZE_PIXELS"}(o=t.WindowsOptionsReportType||(t.WindowsOptionsReportType={}));var L=function(){function e(e,t,r,i){this._bufferService=e,this._coreService=t,this._logService=r,this._optionsService=i,this._data=new Uint32Array(0)}return e.prototype.hook=function(e){this._data=new Uint32Array(0)},e.prototype.put=function(e,t,r){this._data=(0,u.concat)(this._data,e.subarray(t,r))},e.prototype.unhook=function(e){if(!e)return this._data=new Uint32Array(0),!0;var t=(0,h.utf32ToString)(this._data);switch(this._data=new Uint32Array(0),t){case'"q':this._coreService.triggerDataEvent(s.C0.ESC+'P1$r0"q'+s.C0.ESC+"\\");break;case'"p':this._coreService.triggerDataEvent(s.C0.ESC+'P1$r61;1"p'+s.C0.ESC+"\\");break;case"r":var r=this._bufferService.buffer.scrollTop+1+";"+(this._bufferService.buffer.scrollBottom+1)+"r";this._coreService.triggerDataEvent(s.C0.ESC+"P1$r"+r+s.C0.ESC+"\\");break;case"m":this._coreService.triggerDataEvent(s.C0.ESC+"P1$r0m"+s.C0.ESC+"\\");break;case" q":var i={block:2,underline:4,bar:6}[this._optionsService.options.cursorStyle];i-=this._optionsService.options.cursorBlink?1:0,this._coreService.triggerDataEvent(s.C0.ESC+"P1$r"+i+" q"+s.C0.ESC+"\\");break;default:this._logService.debug("Unknown DCS $q %s",t),this._coreService.triggerDataEvent(s.C0.ESC+"P0$r"+s.C0.ESC+"\\")}return!0},e}(),E=function(e){function t(t,r,i,n,o,l,u,d,v){void 0===v&&(v=new c.EscapeSequenceParser);var g=e.call(this)||this;g._bufferService=t,g._charsetService=r,g._coreService=i,g._dirtyRowService=n,g._logService=o,g._optionsService=l,g._coreMouseService=u,g._unicodeService=d,g._parser=v,g._parseBuffer=new Uint32Array(4096),g._stringDecoder=new h.StringToUtf32,g._utf8Decoder=new h.Utf8ToUtf32,g._workCell=new p.CellData,g._windowTitle="",g._iconName="",g._windowTitleStack=[],g._iconNameStack=[],g._curAttrData=f.DEFAULT_ATTR_DATA.clone(),g._eraseAttrDataInternal=f.DEFAULT_ATTR_DATA.clone(),g._onRequestBell=new _.EventEmitter,g._onRequestRefreshRows=new _.EventEmitter,g._onRequestReset=new _.EventEmitter,g._onRequestSendFocus=new _.EventEmitter,g._onRequestSyncScrollBar=new _.EventEmitter,g._onRequestWindowsOptionsReport=new _.EventEmitter,g._onA11yChar=new _.EventEmitter,g._onA11yTab=new _.EventEmitter,g._onCursorMove=new _.EventEmitter,g._onLineFeed=new _.EventEmitter,g._onScroll=new _.EventEmitter,g._onTitleChange=new _.EventEmitter,g._onColor=new _.EventEmitter,g._parseStack={paused:!1,cursorStartX:0,cursorStartY:0,decodedLength:0,position:0},g._specialColors=[256,257,258],g.register(g._parser),g._activeBuffer=g._bufferService.buffer,g.register(g._bufferService.buffers.onBufferActivate((function(e){return g._activeBuffer=e.activeBuffer}))),g._parser.setCsiHandlerFallback((function(e,t){g._logService.debug("Unknown CSI code: ",{identifier:g._parser.identToString(e),params:t.toArray()})})),g._parser.setEscHandlerFallback((function(e){g._logService.debug("Unknown ESC code: ",{identifier:g._parser.identToString(e)})})),g._parser.setExecuteHandlerFallback((function(e){g._logService.debug("Unknown EXECUTE code: ",{code:e})})),g._parser.setOscHandlerFallback((function(e,t,r){g._logService.debug("Unknown OSC code: ",{identifier:e,action:t,data:r})})),g._parser.setDcsHandlerFallback((function(e,t,r){"HOOK"===t&&(r=r.toArray()),g._logService.debug("Unknown DCS code: ",{identifier:g._parser.identToString(e),action:t,payload:r})})),g._parser.setPrintHandler((function(e,t,r){return g.print(e,t,r)})),g._parser.registerCsiHandler({final:"@"},(function(e){return g.insertChars(e)})),g._parser.registerCsiHandler({intermediates:" ",final:"@"},(function(e){return g.scrollLeft(e)})),g._parser.registerCsiHandler({final:"A"},(function(e){return g.cursorUp(e)})),g._parser.registerCsiHandler({intermediates:" ",final:"A"},(function(e){return g.scrollRight(e)})),g._parser.registerCsiHandler({final:"B"},(function(e){return g.cursorDown(e)})),g._parser.registerCsiHandler({final:"C"},(function(e){return g.cursorForward(e)})),g._parser.registerCsiHandler({final:"D"},(function(e){return g.cursorBackward(e)})),g._parser.registerCsiHandler({final:"E"},(function(e){return g.cursorNextLine(e)})),g._parser.registerCsiHandler({final:"F"},(function(e){return g.cursorPrecedingLine(e)})),g._parser.registerCsiHandler({final:"G"},(function(e){return g.cursorCharAbsolute(e)})),g._parser.registerCsiHandler({final:"H"},(function(e){return g.cursorPosition(e)})),g._parser.registerCsiHandler({final:"I"},(function(e){return g.cursorForwardTab(e)})),g._parser.registerCsiHandler({final:"J"},(function(e){return g.eraseInDisplay(e)})),g._parser.registerCsiHandler({prefix:"?",final:"J"},(function(e){return g.eraseInDisplay(e)})),g._parser.registerCsiHandler({final:"K"},(function(e){return g.eraseInLine(e)})),g._parser.registerCsiHandler({prefix:"?",final:"K"},(function(e){return g.eraseInLine(e)})),g._parser.registerCsiHandler({final:"L"},(function(e){return g.insertLines(e)})),g._parser.registerCsiHandler({final:"M"},(function(e){return g.deleteLines(e)})),g._parser.registerCsiHandler({final:"P"},(function(e){return g.deleteChars(e)})),g._parser.registerCsiHandler({final:"S"},(function(e){return g.scrollUp(e)})),g._parser.registerCsiHandler({final:"T"},(function(e){return g.scrollDown(e)})),g._parser.registerCsiHandler({final:"X"},(function(e){return g.eraseChars(e)})),g._parser.registerCsiHandler({final:"Z"},(function(e){return g.cursorBackwardTab(e)})),g._parser.registerCsiHandler({final:"`"},(function(e){return g.charPosAbsolute(e)})),g._parser.registerCsiHandler({final:"a"},(function(e){return g.hPositionRelative(e)})),g._parser.registerCsiHandler({final:"b"},(function(e){return g.repeatPrecedingCharacter(e)})),g._parser.registerCsiHandler({final:"c"},(function(e){return g.sendDeviceAttributesPrimary(e)})),g._parser.registerCsiHandler({prefix:">",final:"c"},(function(e){return g.sendDeviceAttributesSecondary(e)})),g._parser.registerCsiHandler({final:"d"},(function(e){return g.linePosAbsolute(e)})),g._parser.registerCsiHandler({final:"e"},(function(e){return g.vPositionRelative(e)})),g._parser.registerCsiHandler({final:"f"},(function(e){return g.hVPosition(e)})),g._parser.registerCsiHandler({final:"g"},(function(e){return g.tabClear(e)})),g._parser.registerCsiHandler({final:"h"},(function(e){return g.setMode(e)})),g._parser.registerCsiHandler({prefix:"?",final:"h"},(function(e){return g.setModePrivate(e)})),g._parser.registerCsiHandler({final:"l"},(function(e){return g.resetMode(e)})),g._parser.registerCsiHandler({prefix:"?",final:"l"},(function(e){return g.resetModePrivate(e)})),g._parser.registerCsiHandler({final:"m"},(function(e){return g.charAttributes(e)})),g._parser.registerCsiHandler({final:"n"},(function(e){return g.deviceStatus(e)})),g._parser.registerCsiHandler({prefix:"?",final:"n"},(function(e){return g.deviceStatusPrivate(e)})),g._parser.registerCsiHandler({intermediates:"!",final:"p"},(function(e){return g.softReset(e)})),g._parser.registerCsiHandler({intermediates:" ",final:"q"},(function(e){return g.setCursorStyle(e)})),g._parser.registerCsiHandler({final:"r"},(function(e){return g.setScrollRegion(e)})),g._parser.registerCsiHandler({final:"s"},(function(e){return g.saveCursor(e)})),g._parser.registerCsiHandler({final:"t"},(function(e){return g.windowOptions(e)})),g._parser.registerCsiHandler({final:"u"},(function(e){return g.restoreCursor(e)})),g._parser.registerCsiHandler({intermediates:"'",final:"}"},(function(e){return g.insertColumns(e)})),g._parser.registerCsiHandler({intermediates:"'",final:"~"},(function(e){return g.deleteColumns(e)})),g._parser.setExecuteHandler(s.C0.BEL,(function(){return g.bell()})),g._parser.setExecuteHandler(s.C0.LF,(function(){return g.lineFeed()})),g._parser.setExecuteHandler(s.C0.VT,(function(){return g.lineFeed()})),g._parser.setExecuteHandler(s.C0.FF,(function(){return g.lineFeed()})),g._parser.setExecuteHandler(s.C0.CR,(function(){return g.carriageReturn()})),g._parser.setExecuteHandler(s.C0.BS,(function(){return g.backspace()})),g._parser.setExecuteHandler(s.C0.HT,(function(){return g.tab()})),g._parser.setExecuteHandler(s.C0.SO,(function(){return g.shiftOut()})),g._parser.setExecuteHandler(s.C0.SI,(function(){return g.shiftIn()})),g._parser.setExecuteHandler(s.C1.IND,(function(){return g.index()})),g._parser.setExecuteHandler(s.C1.NEL,(function(){return g.nextLine()})),g._parser.setExecuteHandler(s.C1.HTS,(function(){return g.tabSet()})),g._parser.registerOscHandler(0,new y.OscHandler((function(e){return g.setTitle(e),g.setIconName(e),!0}))),g._parser.registerOscHandler(1,new y.OscHandler((function(e){return g.setIconName(e)}))),g._parser.registerOscHandler(2,new y.OscHandler((function(e){return g.setTitle(e)}))),g._parser.registerOscHandler(4,new y.OscHandler((function(e){return g.setOrReportIndexedColor(e)}))),g._parser.registerOscHandler(10,new y.OscHandler((function(e){return g.setOrReportFgColor(e)}))),g._parser.registerOscHandler(11,new y.OscHandler((function(e){return g.setOrReportBgColor(e)}))),g._parser.registerOscHandler(12,new y.OscHandler((function(e){return g.setOrReportCursorColor(e)}))),g._parser.registerOscHandler(104,new y.OscHandler((function(e){return g.restoreIndexedColor(e)}))),g._parser.registerOscHandler(110,new y.OscHandler((function(e){return g.restoreFgColor(e)}))),g._parser.registerOscHandler(111,new y.OscHandler((function(e){return g.restoreBgColor(e)}))),g._parser.registerOscHandler(112,new y.OscHandler((function(e){return g.restoreCursorColor(e)}))),g._parser.registerEscHandler({final:"7"},(function(){return g.saveCursor()})),g._parser.registerEscHandler({final:"8"},(function(){return g.restoreCursor()})),g._parser.registerEscHandler({final:"D"},(function(){return g.index()})),g._parser.registerEscHandler({final:"E"},(function(){return g.nextLine()})),g._parser.registerEscHandler({final:"H"},(function(){return g.tabSet()})),g._parser.registerEscHandler({final:"M"},(function(){return g.reverseIndex()})),g._parser.registerEscHandler({final:"="},(function(){return g.keypadApplicationMode()})),g._parser.registerEscHandler({final:">"},(function(){return g.keypadNumericMode()})),g._parser.registerEscHandler({final:"c"},(function(){return g.fullReset()})),g._parser.registerEscHandler({final:"n"},(function(){return g.setgLevel(2)})),g._parser.registerEscHandler({final:"o"},(function(){return g.setgLevel(3)})),g._parser.registerEscHandler({final:"|"},(function(){return g.setgLevel(3)})),g._parser.registerEscHandler({final:"}"},(function(){return g.setgLevel(2)})),g._parser.registerEscHandler({final:"~"},(function(){return g.setgLevel(1)})),g._parser.registerEscHandler({intermediates:"%",final:"@"},(function(){return g.selectDefaultCharset()})),g._parser.registerEscHandler({intermediates:"%",final:"G"},(function(){return g.selectDefaultCharset()}));var m=function(e){b._parser.registerEscHandler({intermediates:"(",final:e},(function(){return g.selectCharset("("+e)})),b._parser.registerEscHandler({intermediates:")",final:e},(function(){return g.selectCharset(")"+e)})),b._parser.registerEscHandler({intermediates:"*",final:e},(function(){return g.selectCharset("*"+e)})),b._parser.registerEscHandler({intermediates:"+",final:e},(function(){return g.selectCharset("+"+e)})),b._parser.registerEscHandler({intermediates:"-",final:e},(function(){return g.selectCharset("-"+e)})),b._parser.registerEscHandler({intermediates:".",final:e},(function(){return g.selectCharset("."+e)})),b._parser.registerEscHandler({intermediates:"/",final:e},(function(){return g.selectCharset("/"+e)}))},b=this;for(var S in a.CHARSETS)m(S);return g._parser.registerEscHandler({intermediates:"#",final:"8"},(function(){return g.screenAlignmentPattern()})),g._parser.setErrorHandler((function(e){return g._logService.error("Parsing error: ",e),e})),g._parser.registerDcsHandler({intermediates:"$",final:"q"},new L(g._bufferService,g._coreService,g._logService,g._optionsService)),g}return n(t,e),Object.defineProperty(t.prototype,"onRequestBell",{get:function(){return this._onRequestBell.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onRequestRefreshRows",{get:function(){return this._onRequestRefreshRows.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onRequestReset",{get:function(){return this._onRequestReset.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onRequestSendFocus",{get:function(){return this._onRequestSendFocus.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onRequestSyncScrollBar",{get:function(){return this._onRequestSyncScrollBar.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onRequestWindowsOptionsReport",{get:function(){return this._onRequestWindowsOptionsReport.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onA11yChar",{get:function(){return this._onA11yChar.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onA11yTab",{get:function(){return this._onA11yTab.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onCursorMove",{get:function(){return this._onCursorMove.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onLineFeed",{get:function(){return this._onLineFeed.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onScroll",{get:function(){return this._onScroll.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onTitleChange",{get:function(){return this._onTitleChange.event},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"onColor",{get:function(){return this._onColor.event},enumerable:!1,configurable:!0}),t.prototype.dispose=function(){e.prototype.dispose.call(this)},t.prototype._preserveStack=function(e,t,r,i){this._parseStack.paused=!0,this._parseStack.cursorStartX=e,this._parseStack.cursorStartY=t,this._parseStack.decodedLength=r,this._parseStack.position=i},t.prototype._logSlowResolvingAsync=function(e){this._logService.logLevel<=g.LogLevelEnum.WARN&&Promise.race([e,new Promise((function(e,t){return setTimeout((function(){return t("#SLOW_TIMEOUT")}),5e3)}))]).catch((function(e){if("#SLOW_TIMEOUT"!==e)throw e;console.warn("async parser handler taking longer than 5000 ms")}))},t.prototype.parse=function(e,t){var r,i=this._activeBuffer.x,n=this._activeBuffer.y,o=0,s=this._parseStack.paused;if(s){if(r=this._parser.parse(this._parseBuffer,this._parseStack.decodedLength,t))return this._logSlowResolvingAsync(r),r;i=this._parseStack.cursorStartX,n=this._parseStack.cursorStartY,this._parseStack.paused=!1,e.length>C&&(o=this._parseStack.position+C)}if(this._logService.logLevel<=g.LogLevelEnum.DEBUG&&this._logService.debug("parsing data"+("string"==typeof e?' "'+e+'"':""),"string"==typeof e?e.split("").map((function(e){return e.charCodeAt(0)})):e),this._parseBuffer.length<e.length&&this._parseBuffer.length<C&&(this._parseBuffer=new Uint32Array(Math.min(e.length,C))),s||this._dirtyRowService.clearRange(),e.length>C)for(var a=o;a<e.length;a+=C){var c=a+C<e.length?a+C:e.length,l="string"==typeof e?this._stringDecoder.decode(e.substring(a,c),this._parseBuffer):this._utf8Decoder.decode(e.subarray(a,c),this._parseBuffer);if(r=this._parser.parse(this._parseBuffer,l))return this._preserveStack(i,n,l,a),this._logSlowResolvingAsync(r),r}else if(!s&&(l="string"==typeof e?this._stringDecoder.decode(e,this._parseBuffer):this._utf8Decoder.decode(e,this._parseBuffer),r=this._parser.parse(this._parseBuffer,l)))return this._preserveStack(i,n,l,0),this._logSlowResolvingAsync(r),r;this._activeBuffer.x===i&&this._activeBuffer.y===n||this._onCursorMove.fire(),this._onRequestRefreshRows.fire(this._dirtyRowService.start,this._dirtyRowService.end)},t.prototype.print=function(e,t,r){var i,n,o=this._charsetService.charset,s=this._optionsService.options.screenReaderMode,a=this._bufferService.cols,c=this._coreService.decPrivateModes.wraparound,l=this._coreService.modes.insertMode,u=this._curAttrData,f=this._activeBuffer.lines.get(this._activeBuffer.ybase+this._activeBuffer.y);this._dirtyRowService.markDirty(this._activeBuffer.y),this._activeBuffer.x&&r-t>0&&2===f.getWidth(this._activeBuffer.x-1)&&f.setCellFromCodePoint(this._activeBuffer.x-1,0,1,u.fg,u.bg,u.extended);for(var _=t;_<r;++_){if(i=e[_],n=this._unicodeService.wcwidth(i),i<127&&o){var p=o[String.fromCharCode(i)];p&&(i=p.charCodeAt(0))}if(s&&this._onA11yChar.fire((0,h.stringFromCodePoint)(i)),n||!this._activeBuffer.x){if(this._activeBuffer.x+n-1>=a)if(c){for(;this._activeBuffer.x<a;)f.setCellFromCodePoint(this._activeBuffer.x++,0,1,u.fg,u.bg,u.extended);this._activeBuffer.x=0,this._activeBuffer.y++,this._activeBuffer.y===this._activeBuffer.scrollBottom+1?(this._activeBuffer.y--,this._bufferService.scroll(this._eraseAttrData(),!0)):(this._activeBuffer.y>=this._bufferService.rows&&(this._activeBuffer.y=this._bufferService.rows-1),this._activeBuffer.lines.get(this._activeBuffer.ybase+this._activeBuffer.y).isWrapped=!0),f=this._activeBuffer.lines.get(this._activeBuffer.ybase+this._activeBuffer.y)}else if(this._activeBuffer.x=a-1,2===n)continue;if(l&&(f.insertCells(this._activeBuffer.x,n,this._activeBuffer.getNullCell(u),u),2===f.getWidth(a-1)&&f.setCellFromCodePoint(a-1,d.NULL_CELL_CODE,d.NULL_CELL_WIDTH,u.fg,u.bg,u.extended)),f.setCellFromCodePoint(this._activeBuffer.x++,i,n,u.fg,u.bg,u.extended),n>0)for(;--n;)f.setCellFromCodePoint(this._activeBuffer.x++,0,0,u.fg,u.bg,u.extended)}else f.getWidth(this._activeBuffer.x-1)?f.addCodepointToCell(this._activeBuffer.x-1,i):f.addCodepointToCell(this._activeBuffer.x-2,i)}r-t>0&&(f.loadCell(this._activeBuffer.x-1,this._workCell),2===this._workCell.getWidth()||this._workCell.getCode()>65535?this._parser.precedingCodepoint=0:this._workCell.isCombined()?this._parser.precedingCodepoint=this._workCell.getChars().charCodeAt(0):this._parser.precedingCodepoint=this._workCell.content),this._activeBuffer.x<a&&r-t>0&&0===f.getWidth(this._activeBuffer.x)&&!f.hasContent(this._activeBuffer.x)&&f.setCellFromCodePoint(this._activeBuffer.x,0,1,u.fg,u.bg,u.extended),this._dirtyRowService.markDirty(this._activeBuffer.y)},t.prototype.registerCsiHandler=function(e,t){var r=this;return"t"!==e.final||e.prefix||e.intermediates?this._parser.registerCsiHandler(e,t):this._parser.registerCsiHandler(e,(function(e){return!w(e.params[0],r._optionsService.options.windowOptions)||t(e)}))},t.prototype.registerDcsHandler=function(e,t){return this._parser.registerDcsHandler(e,new m.DcsHandler(t))},t.prototype.registerEscHandler=function(e,t){return this._parser.registerEscHandler(e,t)},t.prototype.registerOscHandler=function(e,t){return this._parser.registerOscHandler(e,new y.OscHandler(t))},t.prototype.bell=function(){return this._onRequestBell.fire(),!0},t.prototype.lineFeed=function(){return this._dirtyRowService.markDirty(this._activeBuffer.y),this._optionsService.options.convertEol&&(this._activeBuffer.x=0),this._activeBuffer.y++,this._activeBuffer.y===this._activeBuffer.scrollBottom+1?(this._activeBuffer.y--,this._bufferService.scroll(this._eraseAttrData())):this._activeBuffer.y>=this._bufferService.rows&&(this._activeBuffer.y=this._bufferService.rows-1),this._activeBuffer.x>=this._bufferService.cols&&this._activeBuffer.x--,this._dirtyRowService.markDirty(this._activeBuffer.y),this._onLineFeed.fire(),!0},t.prototype.carriageReturn=function(){return this._activeBuffer.x=0,!0},t.prototype.backspace=function(){var e;if(!this._coreService.decPrivateModes.reverseWraparound)return this._restrictCursor(),this._activeBuffer.x>0&&this._activeBuffer.x--,!0;if(this._restrictCursor(this._bufferService.cols),this._activeBuffer.x>0)this._activeBuffer.x--;else if(0===this._activeBuffer.x&&this._activeBuffer.y>this._activeBuffer.scrollTop&&this._activeBuffer.y<=this._activeBuffer.scrollBottom&&(null===(e=this._activeBuffer.lines.get(this._activeBuffer.ybase+this._activeBuffer.y))||void 0===e?void 0:e.isWrapped)){this._activeBuffer.lines.get(this._activeBuffer.ybase+this._activeBuffer.y).isWrapped=!1,this._activeBuffer.y--,this._activeBuffer.x=this._bufferService.cols-1;var t=this._activeBuffer.lines.get(this._activeBuffer.ybase+this._activeBuffer.y);t.hasWidth(this._activeBuffer.x)&&!t.hasContent(this._activeBuffer.x)&&this._activeBuffer.x--}return this._restrictCursor(),!0},t.prototype.tab=function(){if(this._activeBuffer.x>=this._bufferService.cols)return!0;var e=this._activeBuffer.x;return this._activeBuffer.x=this._activeBuffer.nextStop(),this._optionsService.options.screenReaderMode&&this._onA11yTab.fire(this._activeBuffer.x-e),!0},t.prototype.shiftOut=function(){return this._charsetService.setgLevel(1),!0},t.prototype.shiftIn=function(){return this._charsetService.setgLevel(0),!0},t.prototype._restrictCursor=function(e){void 0===e&&(e=this._bufferService.cols-1),this._activeBuffer.x=Math.min(e,Math.max(0,this._activeBuffer.x)),this._activeBuffer.y=this._coreService.decPrivateModes.origin?Math.min(this._activeBuffer.scrollBottom,Math.max(this._activeBuffer.scrollTop,this._activeBuffer.y)):Math.min(this._bufferService.rows-1,Math.max(0,this._activeBuffer.y)),this._dirtyRowService.markDirty(this._activeBuffer.y)},t.prototype._setCursor=function(e,t){this._dirtyRowService.markDirty(this._activeBuffer.y),this._coreService.decPrivateModes.origin?(this._activeBuffer.x=e,this._activeBuffer.y=this._activeBuffer.scrollTop+t):(this._activeBuffer.x=e,this._activeBuffer.y=t),this._restrictCursor(),this._dirtyRowService.markDirty(this._activeBuffer.y)},t.prototype._moveCursor=function(e,t){this._restrictCursor(),this._setCursor(this._activeBuffer.x+e,this._activeBuffer.y+t)},t.prototype.cursorUp=function(e){var t=this._activeBuffer.y-this._activeBuffer.scrollTop;return t>=0?this._moveCursor(0,-Math.min(t,e.params[0]||1)):this._moveCursor(0,-(e.params[0]||1)),!0},t.prototype.cursorDown=function(e){var t=this._activeBuffer.scrollBottom-this._activeBuffer.y;return t>=0?this._moveCursor(0,Math.min(t,e.params[0]||1)):this._moveCursor(0,e.params[0]||1),!0},t.prototype.cursorForward=function(e){return this._moveCursor(e.params[0]||1,0),!0},t.prototype.cursorBackward=function(e){return this._moveCursor(-(e.params[0]||1),0),!0},t.prototype.cursorNextLine=function(e){return this.cursorDown(e),this._activeBuffer.x=0,!0},t.prototype.cursorPrecedingLine=function(e){return this.cursorUp(e),this._activeBuffer.x=0,!0},t.prototype.cursorCharAbsolute=function(e){return this._setCursor((e.params[0]||1)-1,this._activeBuffer.y),!0},t.prototype.cursorPosition=function(e){return this._setCursor(e.length>=2?(e.params[1]||1)-1:0,(e.params[0]||1)-1),!0},t.prototype.charPosAbsolute=function(e){return this._setCursor((e.params[0]||1)-1,this._activeBuffer.y),!0},t.prototype.hPositionRelative=function(e){return this._moveCursor(e.params[0]||1,0),!0},t.prototype.linePosAbsolute=function(e){return this._setCursor(this._activeBuffer.x,(e.params[0]||1)-1),!0},t.prototype.vPositionRelative=function(e){return this._moveCursor(0,e.params[0]||1),!0},t.prototype.hVPosition=function(e){return this.cursorPosition(e),!0},t.prototype.tabClear=function(e){var t=e.params[0];return 0===t?delete this._activeBuffer.tabs[this._activeBuffer.x]:3===t&&(this._activeBuffer.tabs={}),!0},t.prototype.cursorForwardTab=function(e){if(this._activeBuffer.x>=this._bufferService.cols)return!0;for(var t=e.params[0]||1;t--;)this._activeBuffer.x=this._activeBuffer.nextStop();return!0},t.prototype.cursorBackwardTab=function(e){if(this._activeBuffer.x>=this._bufferService.cols)return!0;for(var t=e.params[0]||1;t--;)this._activeBuffer.x=this._activeBuffer.prevStop();return!0},t.prototype._eraseInBufferLine=function(e,t,r,i){void 0===i&&(i=!1);var n=this._activeBuffer.lines.get(this._activeBuffer.ybase+e);n.replaceCells(t,r,this._activeBuffer.getNullCell(this._eraseAttrData()),this._eraseAttrData()),i&&(n.isWrapped=!1)},t.prototype._resetBufferLine=function(e){var t=this._activeBuffer.lines.get(this._activeBuffer.ybase+e);t.fill(this._activeBuffer.getNullCell(this._eraseAttrData())),t.isWrapped=!1},t.prototype.eraseInDisplay=function(e){var t;switch(this._restrictCursor(this._bufferService.cols),e.params[0]){case 0:for(t=this._activeBuffer.y,this._dirtyRowService.markDirty(t),this._eraseInBufferLine(t++,this._activeBuffer.x,this._bufferService.cols,0===this._activeBuffer.x);t<this._bufferService.rows;t++)this._resetBufferLine(t);this._dirtyRowService.markDirty(t);break;case 1:for(t=this._activeBuffer.y,this._dirtyRowService.markDirty(t),this._eraseInBufferLine(t,0,this._activeBuffer.x+1,!0),this._activeBuffer.x+1>=this._bufferService.cols&&(this._activeBuffer.lines.get(t+1).isWrapped=!1);t--;)this._resetBufferLine(t);this._dirtyRowService.markDirty(0);break;case 2:for(t=this._bufferService.rows,this._dirtyRowService.markDirty(t-1);t--;)this._resetBufferLine(t);this._dirtyRowService.markDirty(0);break;case 3:var r=this._activeBuffer.lines.length-this._bufferService.rows;r>0&&(this._activeBuffer.lines.trimStart(r),this._activeBuffer.ybase=Math.max(this._activeBuffer.ybase-r,0),this._activeBuffer.ydisp=Math.max(this._activeBuffer.ydisp-r,0),this._onScroll.fire(0))}return!0},t.prototype.eraseInLine=function(e){switch(this._restrictCursor(this._bufferService.cols),e.params[0]){case 0:this._eraseInBufferLine(this._activeBuffer.y,this._activeBuffer.x,this._bufferService.cols,0===this._activeBuffer.x);break;case 1:this._eraseInBufferLine(this._activeBuffer.y,0,this._activeBuffer.x+1,!1);break;case 2:this._eraseInBufferLine(this._activeBuffer.y,0,this._bufferService.cols,!0)}return this._dirtyRowService.markDirty(this._activeBuffer.y),!0},t.prototype.insertLines=function(e){this._restrictCursor();var t=e.params[0]||1;if(this._activeBuffer.y>this._activeBuffer.scrollBottom||this._activeBuffer.y<this._activeBuffer.scrollTop)return!0;for(var r=this._activeBuffer.ybase+this._activeBuffer.y,i=this._bufferService.rows-1-this._activeBuffer.scrollBottom,n=this._bufferService.rows-1+this._activeBuffer.ybase-i+1;t--;)this._activeBuffer.lines.splice(n-1,1),this._activeBuffer.lines.splice(r,0,this._activeBuffer.getBlankLine(this._eraseAttrData()));return this._dirtyRowService.markRangeDirty(this._activeBuffer.y,this._activeBuffer.scrollBottom),this._activeBuffer.x=0,!0},t.prototype.deleteLines=function(e){this._restrictCursor();var t=e.params[0]||1;if(this._activeBuffer.y>this._activeBuffer.scrollBottom||this._activeBuffer.y<this._activeBuffer.scrollTop)return!0;var r,i=this._activeBuffer.ybase+this._activeBuffer.y;for(r=this._bufferService.rows-1-this._activeBuffer.scrollBottom,r=this._bufferService.rows-1+this._activeBuffer.ybase-r;t--;)this._activeBuffer.lines.splice(i,1),this._activeBuffer.lines.splice(r,0,this._activeBuffer.getBlankLine(this._eraseAttrData()));return this._dirtyRowService.markRangeDirty(this._activeBuffer.y,this._activeBuffer.scrollBottom),this._activeBuffer.x=0,!0},t.prototype.insertChars=function(e){this._restrictCursor();var t=this._activeBuffer.lines.get(this._activeBuffer.ybase+this._activeBuffer.y);return t&&(t.insertCells(this._activeBuffer.x,e.params[0]||1,this._activeBuffer.getNullCell(this._eraseAttrData()),this._eraseAttrData()),this._dirtyRowService.markDirty(this._activeBuffer.y)),!0},t.prototype.deleteChars=function(e){this._restrictCursor();var t=this._activeBuffer.lines.get(this._activeBuffer.ybase+this._activeBuffer.y);return t&&(t.deleteCells(this._activeBuffer.x,e.params[0]||1,this._activeBuffer.getNullCell(this._eraseAttrData()),this._eraseAttrData()),this._dirtyRowService.markDirty(this._activeBuffer.y)),!0},t.prototype.scrollUp=function(e){for(var t=e.params[0]||1;t--;)this._activeBuffer.lines.splice(this._activeBuffer.ybase+this._activeBuffer.scrollTop,1),this._activeBuffer.lines.splice(this._activeBuffer.ybase+this._activeBuffer.scrollBottom,0,this._activeBuffer.getBlankLine(this._eraseAttrData()));return this._dirtyRowService.markRangeDirty(this._activeBuffer.scrollTop,this._activeBuffer.scrollBottom),!0},t.prototype.scrollDown=function(e){for(var t=e.params[0]||1;t--;)this._activeBuffer.lines.splice(this._activeBuffer.ybase+this._activeBuffer.scrollBottom,1),this._activeBuffer.lines.splice(this._activeBuffer.ybase+this._activeBuffer.scrollTop,0,this._activeBuffer.getBlankLine(f.DEFAULT_ATTR_DATA));return this._dirtyRowService.markRangeDirty(this._activeBuffer.scrollTop,this._activeBuffer.scrollBottom),!0},t.prototype.scrollLeft=function(e){if(this._activeBuffer.y>this._activeBuffer.scrollBottom||this._activeBuffer.y<this._activeBuffer.scrollTop)return!0;for(var t=e.params[0]||1,r=this._activeBuffer.scrollTop;r<=this._activeBuffer.scrollBottom;++r){var i=this._activeBuffer.lines.get(this._activeBuffer.ybase+r);i.deleteCells(0,t,this._activeBuffer.getNullCell(this._eraseAttrData()),this._eraseAttrData()),i.isWrapped=!1}return this._dirtyRowService.markRangeDirty(this._activeBuffer.scrollTop,this._activeBuffer.scrollBottom),!0},t.prototype.scrollRight=function(e){if(this._activeBuffer.y>this._activeBuffer.scrollBottom||this._activeBuffer.y<this._activeBuffer.scrollTop)return!0;for(var t=e.params[0]||1,r=this._activeBuffer.scrollTop;r<=this._activeBuffer.scrollBottom;++r){var i=this._activeBuffer.lines.get(this._activeBuffer.ybase+r);i.insertCells(0,t,this._activeBuffer.getNullCell(this._eraseAttrData()),this._eraseAttrData()),i.isWrapped=!1}return this._dirtyRowService.markRangeDirty(this._activeBuffer.scrollTop,this._activeBuffer.scrollBottom),!0},t.prototype.insertColumns=function(e){if(this._activeBuffer.y>this._activeBuffer.scrollBottom||this._activeBuffer.y<this._activeBuffer.scrollTop)return!0;for(var t=e.params[0]||1,r=this._activeBuffer.scrollTop;r<=this._activeBuffer.scrollBottom;++r){var i=this._activeBuffer.lines.get(this._activeBuffer.ybase+r);i.insertCells(this._activeBuffer.x,t,this._activeBuffer.getNullCell(this._eraseAttrData()),this._eraseAttrData()),i.isWrapped=!1}return this._dirtyRowService.markRangeDirty(this._activeBuffer.scrollTop,this._activeBuffer.scrollBottom),!0},t.prototype.deleteColumns=function(e){if(this._activeBuffer.y>this._activeBuffer.scrollBottom||this._activeBuffer.y<this._activeBuffer.scrollTop)return!0;for(var t=e.params[0]||1,r=this._activeBuffer.scrollTop;r<=this._activeBuffer.scrollBottom;++r){var i=this._activeBuffer.lines.get(this._activeBuffer.ybase+r);i.deleteCells(this._activeBuffer.x,t,this._activeBuffer.getNullCell(this._eraseAttrData()),this._eraseAttrData()),i.isWrapped=!1}return this._dirtyRowService.markRangeDirty(this._activeBuffer.scrollTop,this._activeBuffer.scrollBottom),!0},t.prototype.eraseChars=function(e){this._restrictCursor();var t=this._activeBuffer.lines.get(this._activeBuffer.ybase+this._activeBuffer.y);return t&&(t.replaceCells(this._activeBuffer.x,this._activeBuffer.x+(e.params[0]||1),this._activeBuffer.getNullCell(this._eraseAttrData()),this._eraseAttrData()),this._dirtyRowService.markDirty(this._activeBuffer.y)),!0},t.prototype.repeatPrecedingCharacter=function(e){if(!this._parser.precedingCodepoint)return!0;for(var t=e.params[0]||1,r=new Uint32Array(t),i=0;i<t;++i)r[i]=this._parser.precedingCodepoint;return this.print(r,0,r.length),!0},t.prototype.sendDeviceAttributesPrimary=function(e){return e.params[0]>0||(this._is("xterm")||this._is("rxvt-unicode")||this._is("screen")?this._coreService.triggerDataEvent(s.C0.ESC+"[?1;2c"):this._is("linux")&&this._coreService.triggerDataEvent(s.C0.ESC+"[?6c")),!0},t.prototype.sendDeviceAttributesSecondary=function(e){return e.params[0]>0||(this._is("xterm")?this._coreService.triggerDataEvent(s.C0.ESC+"[>0;276;0c"):this._is("rxvt-unicode")?this._coreService.triggerDataEvent(s.C0.ESC+"[>85;95;0c"):this._is("linux")?this._coreService.triggerDataEvent(e.params[0]+"c"):this._is("screen")&&this._coreService.triggerDataEvent(s.C0.ESC+"[>83;40003;0c")),!0},t.prototype._is=function(e){return 0===(this._optionsService.options.termName+"").indexOf(e)},t.prototype.setMode=function(e){for(var t=0;t<e.length;t++)4===e.params[t]&&(this._coreService.modes.insertMode=!0);return!0},t.prototype.setModePrivate=function(e){for(var t=0;t<e.length;t++)switch(e.params[t]){case 1:this._coreService.decPrivateModes.applicationCursorKeys=!0;break;case 2:this._charsetService.setgCharset(0,a.DEFAULT_CHARSET),this._charsetService.setgCharset(1,a.DEFAULT_CHARSET),this._charsetService.setgCharset(2,a.DEFAULT_CHARSET),this._charsetService.setgCharset(3,a.DEFAULT_CHARSET);break;case 3:this._optionsService.options.windowOptions.setWinLines&&(this._bufferService.resize(132,this._bufferService.rows),this._onRequestReset.fire());break;case 6:this._coreService.decPrivateModes.origin=!0,this._setCursor(0,0);break;case 7:this._coreService.decPrivateModes.wraparound=!0;break;case 12:break;case 45:this._coreService.decPrivateModes.reverseWraparound=!0;break;case 66:this._logService.debug("Serial port requested application keypad."),this._coreService.decPrivateModes.applicationKeypad=!0,this._onRequestSyncScrollBar.fire();break;case 9:this._coreMouseService.activeProtocol="X10";break;case 1e3:this._coreMouseService.activeProtocol="VT200";break;case 1002:this._coreMouseService.activeProtocol="DRAG";break;case 1003:this._coreMouseService.activeProtocol="ANY";break;case 1004:this._coreService.decPrivateModes.sendFocus=!0,this._onRequestSendFocus.fire();break;case 1005:this._logService.debug("DECSET 1005 not supported (see #2507)");break;case 1006:this._coreMouseService.activeEncoding="SGR";break;case 1015:this._logService.debug("DECSET 1015 not supported (see #2507)");break;case 25:this._coreService.isCursorHidden=!1;break;case 1048:this.saveCursor();break;case 1049:this.saveCursor();case 47:case 1047:this._bufferService.buffers.activateAltBuffer(this._eraseAttrData()),this._coreService.isCursorInitialized=!0,this._onRequestRefreshRows.fire(0,this._bufferService.rows-1),this._onRequestSyncScrollBar.fire();break;case 2004:this._coreService.decPrivateModes.bracketedPasteMode=!0}return!0},t.prototype.resetMode=function(e){for(var t=0;t<e.length;t++)4===e.params[t]&&(this._coreService.modes.insertMode=!1);return!0},t.prototype.resetModePrivate=function(e){for(var t=0;t<e.length;t++)switch(e.params[t]){case 1:this._coreService.decPrivateModes.applicationCursorKeys=!1;break;case 3:this._optionsService.options.windowOptions.setWinLines&&(this._bufferService.resize(80,this._bufferService.rows),this._onRequestReset.fire());break;case 6:this._coreService.decPrivateModes.origin=!1,this._setCursor(0,0);break;case 7:this._coreService.decPrivateModes.wraparound=!1;break;case 12:break;case 45:this._coreService.decPrivateModes.reverseWraparound=!1;break;case 66:this._logService.debug("Switching back to normal keypad."),this._coreService.decPrivateModes.applicationKeypad=!1,this._onRequestSyncScrollBar.fire();break;case 9:case 1e3:case 1002:case 1003:this._coreMouseService.activeProtocol="NONE";break;case 1004:this._coreService.decPrivateModes.sendFocus=!1;break;case 1005:this._logService.debug("DECRST 1005 not supported (see #2507)");break;case 1006:this._coreMouseService.activeEncoding="DEFAULT";break;case 1015:this._logService.debug("DECRST 1015 not supported (see #2507)");break;case 25:this._coreService.isCursorHidden=!0;break;case 1048:this.restoreCursor();break;case 1049:case 47:case 1047:this._bufferService.buffers.activateNormalBuffer(),1049===e.params[t]&&this.restoreCursor(),this._coreService.isCursorInitialized=!0,this._onRequestRefreshRows.fire(0,this._bufferService.rows-1),this._onRequestSyncScrollBar.fire();break;case 2004:this._coreService.decPrivateModes.bracketedPasteMode=!1}return!0},t.prototype._updateAttrColor=function(e,t,r,i,n){return 2===t?(e|=50331648,e&=-16777216,e|=v.AttributeData.fromColorRGB([r,i,n])):5===t&&(e&=-50331904,e|=33554432|255&r),e},t.prototype._extractColor=function(e,t,r){var i=[0,0,-1,0,0,0],n=0,o=0;do{if(i[o+n]=e.params[t+o],e.hasSubParams(t+o)){var s=e.getSubParams(t+o),a=0;do{5===i[1]&&(n=1),i[o+a+1+n]=s[a]}while(++a<s.length&&a+o+1+n<i.length);break}if(5===i[1]&&o+n>=2||2===i[1]&&o+n>=5)break;i[1]&&(n=1)}while(++o+t<e.length&&o+n<i.length);for(a=2;a<i.length;++a)-1===i[a]&&(i[a]=0);switch(i[0]){case 38:r.fg=this._updateAttrColor(r.fg,i[1],i[3],i[4],i[5]);break;case 48:r.bg=this._updateAttrColor(r.bg,i[1],i[3],i[4],i[5]);break;case 58:r.extended=r.extended.clone(),r.extended.underlineColor=this._updateAttrColor(r.extended.underlineColor,i[1],i[3],i[4],i[5])}return o},t.prototype._processUnderline=function(e,t){t.extended=t.extended.clone(),(!~e||e>5)&&(e=1),t.extended.underlineStyle=e,t.fg|=268435456,0===e&&(t.fg&=-268435457),t.updateExtended()},t.prototype.charAttributes=function(e){if(1===e.length&&0===e.params[0])return this._curAttrData.fg=f.DEFAULT_ATTR_DATA.fg,this._curAttrData.bg=f.DEFAULT_ATTR_DATA.bg,!0;for(var t,r=e.length,i=this._curAttrData,n=0;n<r;n++)(t=e.params[n])>=30&&t<=37?(i.fg&=-50331904,i.fg|=16777216|t-30):t>=40&&t<=47?(i.bg&=-50331904,i.bg|=16777216|t-40):t>=90&&t<=97?(i.fg&=-50331904,i.fg|=16777224|t-90):t>=100&&t<=107?(i.bg&=-50331904,i.bg|=16777224|t-100):0===t?(i.fg=f.DEFAULT_ATTR_DATA.fg,i.bg=f.DEFAULT_ATTR_DATA.bg):1===t?i.fg|=134217728:3===t?i.bg|=67108864:4===t?(i.fg|=268435456,this._processUnderline(e.hasSubParams(n)?e.getSubParams(n)[0]:1,i)):5===t?i.fg|=536870912:7===t?i.fg|=67108864:8===t?i.fg|=1073741824:9===t?i.fg|=2147483648:2===t?i.bg|=134217728:21===t?this._processUnderline(2,i):22===t?(i.fg&=-134217729,i.bg&=-134217729):23===t?i.bg&=-67108865:24===t?i.fg&=-268435457:25===t?i.fg&=-536870913:27===t?i.fg&=-67108865:28===t?i.fg&=-1073741825:29===t?i.fg&=2147483647:39===t?(i.fg&=-67108864,i.fg|=16777215&f.DEFAULT_ATTR_DATA.fg):49===t?(i.bg&=-67108864,i.bg|=16777215&f.DEFAULT_ATTR_DATA.bg):38===t||48===t||58===t?n+=this._extractColor(e,n,i):59===t?(i.extended=i.extended.clone(),i.extended.underlineColor=-1,i.updateExtended()):100===t?(i.fg&=-67108864,i.fg|=16777215&f.DEFAULT_ATTR_DATA.fg,i.bg&=-67108864,i.bg|=16777215&f.DEFAULT_ATTR_DATA.bg):this._logService.debug("Unknown SGR attribute: %d.",t);return!0},t.prototype.deviceStatus=function(e){switch(e.params[0]){case 5:this._coreService.triggerDataEvent(s.C0.ESC+"[0n");break;case 6:var t=this._activeBuffer.y+1,r=this._activeBuffer.x+1;this._coreService.triggerDataEvent(s.C0.ESC+"["+t+";"+r+"R")}return!0},t.prototype.deviceStatusPrivate=function(e){if(6===e.params[0]){var t=this._activeBuffer.y+1,r=this._activeBuffer.x+1;this._coreService.triggerDataEvent(s.C0.ESC+"[?"+t+";"+r+"R")}return!0},t.prototype.softReset=function(e){return this._coreService.isCursorHidden=!1,this._onRequestSyncScrollBar.fire(),this._activeBuffer.scrollTop=0,this._activeBuffer.scrollBottom=this._bufferService.rows-1,this._curAttrData=f.DEFAULT_ATTR_DATA.clone(),this._coreService.reset(),this._charsetService.reset(),this._activeBuffer.savedX=0,this._activeBuffer.savedY=this._activeBuffer.ybase,this._activeBuffer.savedCurAttrData.fg=this._curAttrData.fg,this._activeBuffer.savedCurAttrData.bg=this._curAttrData.bg,this._activeBuffer.savedCharset=this._charsetService.charset,this._coreService.decPrivateModes.origin=!1,!0},t.prototype.setCursorStyle=function(e){var t=e.params[0]||1;switch(t){case 1:case 2:this._optionsService.options.cursorStyle="block";break;case 3:case 4:this._optionsService.options.cursorStyle="underline";break;case 5:case 6:this._optionsService.options.cursorStyle="bar"}var r=t%2==1;return this._optionsService.options.cursorBlink=r,!0},t.prototype.setScrollRegion=function(e){var t,r=e.params[0]||1;return(e.length<2||(t=e.params[1])>this._bufferService.rows||0===t)&&(t=this._bufferService.rows),t>r&&(this._activeBuffer.scrollTop=r-1,this._activeBuffer.scrollBottom=t-1,this._setCursor(0,0)),!0},t.prototype.windowOptions=function(e){if(!w(e.params[0],this._optionsService.options.windowOptions))return!0;var t=e.length>1?e.params[1]:0;switch(e.params[0]){case 14:2!==t&&this._onRequestWindowsOptionsReport.fire(o.GET_WIN_SIZE_PIXELS);break;case 16:this._onRequestWindowsOptionsReport.fire(o.GET_CELL_SIZE_PIXELS);break;case 18:this._bufferService&&this._coreService.triggerDataEvent(s.C0.ESC+"[8;"+this._bufferService.rows+";"+this._bufferService.cols+"t");break;case 22:0!==t&&2!==t||(this._windowTitleStack.push(this._windowTitle),this._windowTitleStack.length>10&&this._windowTitleStack.shift()),0!==t&&1!==t||(this._iconNameStack.push(this._iconName),this._iconNameStack.length>10&&this._iconNameStack.shift());break;case 23:0!==t&&2!==t||this._windowTitleStack.length&&this.setTitle(this._windowTitleStack.pop()),0!==t&&1!==t||this._iconNameStack.length&&this.setIconName(this._iconNameStack.pop())}return!0},t.prototype.saveCursor=function(e){return this._activeBuffer.savedX=this._activeBuffer.x,this._activeBuffer.savedY=this._activeBuffer.ybase+this._activeBuffer.y,this._activeBuffer.savedCurAttrData.fg=this._curAttrData.fg,this._activeBuffer.savedCurAttrData.bg=this._curAttrData.bg,this._activeBuffer.savedCharset=this._charsetService.charset,!0},t.prototype.restoreCursor=function(e){return this._activeBuffer.x=this._activeBuffer.savedX||0,this._activeBuffer.y=Math.max(this._activeBuffer.savedY-this._activeBuffer.ybase,0),this._curAttrData.fg=this._activeBuffer.savedCurAttrData.fg,this._curAttrData.bg=this._activeBuffer.savedCurAttrData.bg,this._charsetService.charset=this._savedCharset,this._activeBuffer.savedCharset&&(this._charsetService.charset=this._activeBuffer.savedCharset),this._restrictCursor(),!0},t.prototype.setTitle=function(e){return this._windowTitle=e,this._onTitleChange.fire(e),!0},t.prototype.setIconName=function(e){return this._iconName=e,!0},t.prototype.setOrReportIndexedColor=function(e){for(var t=[],r=e.split(";");r.length>1;){var i=r.shift(),n=r.shift();if(/^\d+$/.exec(i)){var o=parseInt(i);if(0<=o&&o<256)if("?"===n)t.push({type:0,index:o});else{var s=(0,b.parseColor)(n);s&&t.push({type:1,index:o,color:s})}}}return t.length&&this._onColor.fire(t),!0},t.prototype._setOrReportSpecialColor=function(e,t){for(var r=e.split(";"),i=0;i<r.length&&!(t>=this._specialColors.length);++i,++t)if("?"===r[i])this._onColor.fire([{type:0,index:this._specialColors[t]}]);else{var n=(0,b.parseColor)(r[i]);n&&this._onColor.fire([{type:1,index:this._specialColors[t],color:n}])}return!0},t.prototype.setOrReportFgColor=function(e){return this._setOrReportSpecialColor(e,0)},t.prototype.setOrReportBgColor=function(e){return this._setOrReportSpecialColor(e,1)},t.prototype.setOrReportCursorColor=function(e){return this._setOrReportSpecialColor(e,2)},t.prototype.restoreIndexedColor=function(e){if(!e)return this._onColor.fire([{type:2}]),!0;for(var t=[],r=e.split(";"),i=0;i<r.length;++i)if(/^\d+$/.exec(r[i])){var n=parseInt(r[i]);0<=n&&n<256&&t.push({type:2,index:n})}return t.length&&this._onColor.fire(t),!0},t.prototype.restoreFgColor=function(e){return this._onColor.fire([{type:2,index:256}]),!0},t.prototype.restoreBgColor=function(e){return this._onColor.fire([{type:2,index:257}]),!0},t.prototype.restoreCursorColor=function(e){return this._onColor.fire([{type:2,index:258}]),!0},t.prototype.nextLine=function(){return this._activeBuffer.x=0,this.index(),!0},t.prototype.keypadApplicationMode=function(){return this._logService.debug("Serial port requested application keypad."),this._coreService.decPrivateModes.applicationKeypad=!0,this._onRequestSyncScrollBar.fire(),!0},t.prototype.keypadNumericMode=function(){return this._logService.debug("Switching back to normal keypad."),this._coreService.decPrivateModes.applicationKeypad=!1,this._onRequestSyncScrollBar.fire(),!0},t.prototype.selectDefaultCharset=function(){return this._charsetService.setgLevel(0),this._charsetService.setgCharset(0,a.DEFAULT_CHARSET),!0},t.prototype.selectCharset=function(e){return 2!==e.length?(this.selectDefaultCharset(),!0):("/"===e[0]||this._charsetService.setgCharset(S[e[0]],a.CHARSETS[e[1]]||a.DEFAULT_CHARSET),!0)},t.prototype.index=function(){return this._restrictCursor(),this._activeBuffer.y++,this._activeBuffer.y===this._activeBuffer.scrollBottom+1?(this._activeBuffer.y--,this._bufferService.scroll(this._eraseAttrData())):this._activeBuffer.y>=this._bufferService.rows&&(this._activeBuffer.y=this._bufferService.rows-1),this._restrictCursor(),!0},t.prototype.tabSet=function(){return this._activeBuffer.tabs[this._activeBuffer.x]=!0,!0},t.prototype.reverseIndex=function(){if(this._restrictCursor(),this._activeBuffer.y===this._activeBuffer.scrollTop){var e=this._activeBuffer.scrollBottom-this._activeBuffer.scrollTop;this._activeBuffer.lines.shiftElements(this._activeBuffer.ybase+this._activeBuffer.y,e,1),this._activeBuffer.lines.set(this._activeBuffer.ybase+this._activeBuffer.y,this._activeBuffer.getBlankLine(this._eraseAttrData())),this._dirtyRowService.markRangeDirty(this._activeBuffer.scrollTop,this._activeBuffer.scrollBottom)}else this._activeBuffer.y--,this._restrictCursor();return!0},t.prototype.fullReset=function(){return this._parser.reset(),this._onRequestReset.fire(),!0},t.prototype.reset=function(){this._curAttrData=f.DEFAULT_ATTR_DATA.clone(),this._eraseAttrDataInternal=f.DEFAULT_ATTR_DATA.clone()},t.prototype._eraseAttrData=function(){return this._eraseAttrDataInternal.bg&=-67108864,this._eraseAttrDataInternal.bg|=67108863&this._curAttrData.bg,this._eraseAttrDataInternal},t.prototype.setgLevel=function(e){return this._charsetService.setgLevel(e),!0},t.prototype.screenAlignmentPattern=function(){var e=new p.CellData;e.content=1<<22|"E".charCodeAt(0),e.fg=this._curAttrData.fg,e.bg=this._curAttrData.bg,this._setCursor(0,0);for(var t=0;t<this._bufferService.rows;++t){var r=this._activeBuffer.ybase+this._activeBuffer.y+t,i=this._activeBuffer.lines.get(r);i&&(i.fill(e),i.isWrapped=!1)}return this._dirtyRowService.markAllDirty(),this._setCursor(0,0),!0},t}(l.Disposable);t.InputHandler=E},844:(e,t)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.getDisposeArrayDisposable=t.disposeArray=t.Disposable=void 0;var r=function(){function e(){this._disposables=[],this._isDisposed=!1}return e.prototype.dispose=function(){this._isDisposed=!0;for(var e=0,t=this._disposables;e<t.length;e++)t[e].dispose();this._disposables.length=0},e.prototype.register=function(e){return this._disposables.push(e),e},e.prototype.unregister=function(e){var t=this._disposables.indexOf(e);-1!==t&&this._disposables.splice(t,1)},e}();function i(e){for(var t=0,r=e;t<r.length;t++)r[t].dispose();e.length=0}t.Disposable=r,t.disposeArray=i,t.getDisposeArrayDisposable=function(e){return{dispose:function(){return i(e)}}}},6114:(e,t)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.isLinux=t.isWindows=t.isIphone=t.isIpad=t.isMac=t.isSafari=t.isFirefox=void 0;var r="undefined"==typeof navigator,i=r?"node":navigator.userAgent,n=r?"node":navigator.platform;t.isFirefox=i.includes("Firefox"),t.isSafari=/^((?!chrome|android).)*safari/i.test(i),t.isMac=["Macintosh","MacIntel","MacPPC","Mac68K"].includes(n),t.isIpad="iPad"===n,t.isIphone="iPhone"===n,t.isWindows=["Windows","Win16","Win32","WinCE"].includes(n),t.isLinux=n.indexOf("Linux")>=0},8273:(e,t)=>{function r(e,t,r,i){if(void 0===r&&(r=0),void 0===i&&(i=e.length),r>=e.length)return e;r=(e.length+r)%e.length,i=i>=e.length?e.length:(e.length+i)%e.length;for(var n=r;n<i;++n)e[n]=t;return e}Object.defineProperty(t,"__esModule",{value:!0}),t.concat=t.fillFallback=t.fill=void 0,t.fill=function(e,t,i,n){return e.fill?e.fill(t,i,n):r(e,t,i,n)},t.fillFallback=r,t.concat=function(e,t){var r=new e.constructor(e.length+t.length);return r.set(e),r.set(t,e.length),r}},9282:(e,t,r)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.updateWindowsModeWrappedState=void 0;var i=r(643);t.updateWindowsModeWrappedState=function(e){var t=e.buffer.lines.get(e.buffer.ybase+e.buffer.y-1),r=null==t?void 0:t.get(e.cols-1),n=e.buffer.lines.get(e.buffer.ybase+e.buffer.y);n&&r&&(n.isWrapped=r[i.CHAR_DATA_CODE_INDEX]!==i.NULL_CELL_CODE&&r[i.CHAR_DATA_CODE_INDEX]!==i.WHITESPACE_CELL_CODE)}},3734:(e,t)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.ExtendedAttrs=t.AttributeData=void 0;var r=function(){function e(){this.fg=0,this.bg=0,this.extended=new i}return e.toColorRGB=function(e){return[e>>>16&255,e>>>8&255,255&e]},e.fromColorRGB=function(e){return(255&e[0])<<16|(255&e[1])<<8|255&e[2]},e.prototype.clone=function(){var t=new e;return t.fg=this.fg,t.bg=this.bg,t.extended=this.extended.clone(),t},e.prototype.isInverse=function(){return 67108864&this.fg},e.prototype.isBold=function(){return 134217728&this.fg},e.prototype.isUnderline=function(){return 268435456&this.fg},e.prototype.isBlink=function(){return 536870912&this.fg},e.prototype.isInvisible=function(){return 1073741824&this.fg},e.prototype.isItalic=function(){return 67108864&this.bg},e.prototype.isDim=function(){return 134217728&this.bg},e.prototype.isStrikethrough=function(){return 2147483648&this.fg},e.prototype.getFgColorMode=function(){return 50331648&this.fg},e.prototype.getBgColorMode=function(){return 50331648&this.bg},e.prototype.isFgRGB=function(){return 50331648==(50331648&this.fg)},e.prototype.isBgRGB=function(){return 50331648==(50331648&this.bg)},e.prototype.isFgPalette=function(){return 16777216==(50331648&this.fg)||33554432==(50331648&this.fg)},e.prototype.isBgPalette=function(){return 16777216==(50331648&this.bg)||33554432==(50331648&this.bg)},e.prototype.isFgDefault=function(){return 0==(50331648&this.fg)},e.prototype.isBgDefault=function(){return 0==(50331648&this.bg)},e.prototype.isAttributeDefault=function(){return 0===this.fg&&0===this.bg},e.prototype.getFgColor=function(){switch(50331648&this.fg){case 16777216:case 33554432:return 255&this.fg;case 50331648:return 16777215&this.fg;default:return-1}},e.prototype.getBgColor=function(){switch(50331648&this.bg){case 16777216:case 33554432:return 255&this.bg;case 50331648:return 16777215&this.bg;default:return-1}},e.prototype.hasExtendedAttrs=function(){return 268435456&this.bg},e.prototype.updateExtended=function(){this.extended.isEmpty()?this.bg&=-268435457:this.bg|=268435456},e.prototype.getUnderlineColor=function(){if(268435456&this.bg&&~this.extended.underlineColor)switch(50331648&this.extended.underlineColor){case 16777216:case 33554432:return 255&this.extended.underlineColor;case 50331648:return 16777215&this.extended.underlineColor;default:return this.getFgColor()}return this.getFgColor()},e.prototype.getUnderlineColorMode=function(){return 268435456&this.bg&&~this.extended.underlineColor?50331648&this.extended.underlineColor:this.getFgColorMode()},e.prototype.isUnderlineColorRGB=function(){return 268435456&this.bg&&~this.extended.underlineColor?50331648==(50331648&this.extended.underlineColor):this.isFgRGB()},e.prototype.isUnderlineColorPalette=function(){return 268435456&this.bg&&~this.extended.underlineColor?16777216==(50331648&this.extended.underlineColor)||33554432==(50331648&this.extended.underlineColor):this.isFgPalette()},e.prototype.isUnderlineColorDefault=function(){return 268435456&this.bg&&~this.extended.underlineColor?0==(50331648&this.extended.underlineColor):this.isFgDefault()},e.prototype.getUnderlineStyle=function(){return 268435456&this.fg?268435456&this.bg?this.extended.underlineStyle:1:0},e}();t.AttributeData=r;var i=function(){function e(e,t){void 0===e&&(e=0),void 0===t&&(t=-1),this.underlineStyle=e,this.underlineColor=t}return e.prototype.clone=function(){return new e(this.underlineStyle,this.underlineColor)},e.prototype.isEmpty=function(){return 0===this.underlineStyle},e}();t.ExtendedAttrs=i},9092:(e,t,r)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.BufferStringIterator=t.Buffer=t.MAX_BUFFER_SIZE=void 0;var i=r(6349),n=r(8437),o=r(511),s=r(643),a=r(4634),c=r(4863),l=r(7116),u=r(3734);t.MAX_BUFFER_SIZE=4294967295;var h=function(){function e(e,t,r){this._hasScrollback=e,this._optionsService=t,this._bufferService=r,this.ydisp=0,this.ybase=0,this.y=0,this.x=0,this.savedY=0,this.savedX=0,this.savedCurAttrData=n.DEFAULT_ATTR_DATA.clone(),this.savedCharset=l.DEFAULT_CHARSET,this.markers=[],this._nullCell=o.CellData.fromCharData([0,s.NULL_CELL_CHAR,s.NULL_CELL_WIDTH,s.NULL_CELL_CODE]),this._whitespaceCell=o.CellData.fromCharData([0,s.WHITESPACE_CELL_CHAR,s.WHITESPACE_CELL_WIDTH,s.WHITESPACE_CELL_CODE]),this._cols=this._bufferService.cols,this._rows=this._bufferService.rows,this.lines=new i.CircularList(this._getCorrectBufferLength(this._rows)),this.scrollTop=0,this.scrollBottom=this._rows-1,this.setupTabStops()}return e.prototype.getNullCell=function(e){return e?(this._nullCell.fg=e.fg,this._nullCell.bg=e.bg,this._nullCell.extended=e.extended):(this._nullCell.fg=0,this._nullCell.bg=0,this._nullCell.extended=new u.ExtendedAttrs),this._nullCell},e.prototype.getWhitespaceCell=function(e){return e?(this._whitespaceCell.fg=e.fg,this._whitespaceCell.bg=e.bg,this._whitespaceCell.extended=e.extended):(this._whitespaceCell.fg=0,this._whitespaceCell.bg=0,this._whitespaceCell.extended=new u.ExtendedAttrs),this._whitespaceCell},e.prototype.getBlankLine=function(e,t){return new n.BufferLine(this._bufferService.cols,this.getNullCell(e),t)},Object.defineProperty(e.prototype,"hasScrollback",{get:function(){return this._hasScrollback&&this.lines.maxLength>this._rows},enumerable:!1,configurable:!0}),Object.defineProperty(e.prototype,"isCursorInViewport",{get:function(){var e=this.ybase+this.y-this.ydisp;return e>=0&&e<this._rows},enumerable:!1,configurable:!0}),e.prototype._getCorrectBufferLength=function(e){if(!this._hasScrollback)return e;var r=e+this._optionsService.options.scrollback;return r>t.MAX_BUFFER_SIZE?t.MAX_BUFFER_SIZE:r},e.prototype.fillViewportRows=function(e){if(0===this.lines.length){void 0===e&&(e=n.DEFAULT_ATTR_DATA);for(var t=this._rows;t--;)this.lines.push(this.getBlankLine(e))}},e.prototype.clear=function(){this.ydisp=0,this.ybase=0,this.y=0,this.x=0,this.lines=new i.CircularList(this._getCorrectBufferLength(this._rows)),this.scrollTop=0,this.scrollBottom=this._rows-1,this.setupTabStops()},e.prototype.resize=function(e,t){var r=this.getNullCell(n.DEFAULT_ATTR_DATA),i=this._getCorrectBufferLength(t);if(i>this.lines.maxLength&&(this.lines.maxLength=i),this.lines.length>0){if(this._cols<e)for(var o=0;o<this.lines.length;o++)this.lines.get(o).resize(e,r);var s=0;if(this._rows<t)for(var a=this._rows;a<t;a++)this.lines.length<t+this.ybase&&(this._optionsService.options.windowsMode?this.lines.push(new n.BufferLine(e,r)):this.ybase>0&&this.lines.length<=this.ybase+this.y+s+1?(this.ybase--,s++,this.ydisp>0&&this.ydisp--):this.lines.push(new n.BufferLine(e,r)));else for(a=this._rows;a>t;a--)this.lines.length>t+this.ybase&&(this.lines.length>this.ybase+this.y+1?this.lines.pop():(this.ybase++,this.ydisp++));if(i<this.lines.maxLength){var c=this.lines.length-i;c>0&&(this.lines.trimStart(c),this.ybase=Math.max(this.ybase-c,0),this.ydisp=Math.max(this.ydisp-c,0),this.savedY=Math.max(this.savedY-c,0)),this.lines.maxLength=i}this.x=Math.min(this.x,e-1),this.y=Math.min(this.y,t-1),s&&(this.y+=s),this.savedX=Math.min(this.savedX,e-1),this.scrollTop=0}if(this.scrollBottom=t-1,this._isReflowEnabled&&(this._reflow(e,t),this._cols>e))for(o=0;o<this.lines.length;o++)this.lines.get(o).resize(e,r);this._cols=e,this._rows=t},Object.defineProperty(e.prototype,"_isReflowEnabled",{get:function(){return this._hasScrollback&&!this._optionsService.options.windowsMode},enumerable:!1,configurable:!0}),e.prototype._reflow=function(e,t){this._cols!==e&&(e>this._cols?this._reflowLarger(e,t):this._reflowSmaller(e,t))},e.prototype._reflowLarger=function(e,t){var r=(0,a.reflowLargerGetLinesToRemove)(this.lines,this._cols,e,this.ybase+this.y,this.getNullCell(n.DEFAULT_ATTR_DATA));if(r.length>0){var i=(0,a.reflowLargerCreateNewLayout)(this.lines,r);(0,a.reflowLargerApplyNewLayout)(this.lines,i.layout),this._reflowLargerAdjustViewport(e,t,i.countRemoved)}},e.prototype._reflowLargerAdjustViewport=function(e,t,r){for(var i=this.getNullCell(n.DEFAULT_ATTR_DATA),o=r;o-- >0;)0===this.ybase?(this.y>0&&this.y--,this.lines.length<t&&this.lines.push(new n.BufferLine(e,i))):(this.ydisp===this.ybase&&this.ydisp--,this.ybase--);this.savedY=Math.max(this.savedY-r,0)},e.prototype._reflowSmaller=function(e,t){for(var r=this.getNullCell(n.DEFAULT_ATTR_DATA),i=[],o=0,s=this.lines.length-1;s>=0;s--){var c=this.lines.get(s);if(!(!c||!c.isWrapped&&c.getTrimmedLength()<=e)){for(var l=[c];c.isWrapped&&s>0;)c=this.lines.get(--s),l.unshift(c);var u=this.ybase+this.y;if(!(u>=s&&u<s+l.length)){var h,f=l[l.length-1].getTrimmedLength(),_=(0,a.reflowSmallerGetNewLineLengths)(l,this._cols,e),d=_.length-l.length;h=0===this.ybase&&this.y!==this.lines.length-1?Math.max(0,this.y-this.lines.maxLength+d):Math.max(0,this.lines.length-this.lines.maxLength+d);for(var p=[],v=0;v<d;v++){var g=this.getBlankLine(n.DEFAULT_ATTR_DATA,!0);p.push(g)}p.length>0&&(i.push({start:s+l.length+o,newLines:p}),o+=p.length),l.push.apply(l,p);var y=_.length-1,m=_[y];0===m&&(m=_[--y]);for(var b=l.length-d-1,S=f;b>=0;){var C=Math.min(S,m);if(l[y].copyCellsFrom(l[b],S-C,m-C,C,!0),0==(m-=C)&&(m=_[--y]),0==(S-=C)){b--;var w=Math.max(b,0);S=(0,a.getWrappedLineTrimmedLength)(l,w,this._cols)}}for(v=0;v<l.length;v++)_[v]<e&&l[v].setCell(_[v],r);for(var L=d-h;L-- >0;)0===this.ybase?this.y<t-1?(this.y++,this.lines.pop()):(this.ybase++,this.ydisp++):this.ybase<Math.min(this.lines.maxLength,this.lines.length+o)-t&&(this.ybase===this.ydisp&&this.ydisp++,this.ybase++);this.savedY=Math.min(this.savedY+d,this.ybase+t-1)}}}if(i.length>0){var E=[],x=[];for(v=0;v<this.lines.length;v++)x.push(this.lines.get(v));var A=this.lines.length,k=A-1,M=0,R=i[M];this.lines.length=Math.min(this.lines.maxLength,this.lines.length+o);var T=0;for(v=Math.min(this.lines.maxLength-1,A+o-1);v>=0;v--)if(R&&R.start>k+T){for(var O=R.newLines.length-1;O>=0;O--)this.lines.set(v--,R.newLines[O]);v++,E.push({index:k+1,amount:R.newLines.length}),T+=R.newLines.length,R=i[++M]}else this.lines.set(v,x[k--]);var B=0;for(v=E.length-1;v>=0;v--)E[v].index+=B,this.lines.onInsertEmitter.fire(E[v]),B+=E[v].amount;var D=Math.max(0,A+o-this.lines.maxLength);D>0&&this.lines.onTrimEmitter.fire(D)}},e.prototype.stringIndexToBufferIndex=function(e,t,r){for(void 0===r&&(r=!1);t;){var i=this.lines.get(e);if(!i)return[-1,-1];for(var n=r?i.getTrimmedLength():i.length,o=0;o<n;++o)if(i.get(o)[s.CHAR_DATA_WIDTH_INDEX]&&(t-=i.get(o)[s.CHAR_DATA_CHAR_INDEX].length||1),t<0)return[e,o];e++}return[e,0]},e.prototype.translateBufferLineToString=function(e,t,r,i){void 0===r&&(r=0);var n=this.lines.get(e);return n?n.translateToString(t,r,i):""},e.prototype.getWrappedRangeForLine=function(e){for(var t=e,r=e;t>0&&this.lines.get(t).isWrapped;)t--;for(;r+1<this.lines.length&&this.lines.get(r+1).isWrapped;)r++;return{first:t,last:r}},e.prototype.setupTabStops=function(e){for(null!=e?this.tabs[e]||(e=this.prevStop(e)):(this.tabs={},e=0);e<this._cols;e+=this._optionsService.options.tabStopWidth)this.tabs[e]=!0},e.prototype.prevStop=function(e){for(null==e&&(e=this.x);!this.tabs[--e]&&e>0;);return e>=this._cols?this._cols-1:e<0?0:e},e.prototype.nextStop=function(e){for(null==e&&(e=this.x);!this.tabs[++e]&&e<this._cols;);return e>=this._cols?this._cols-1:e<0?0:e},e.prototype.addMarker=function(e){var t=this,r=new c.Marker(e);return this.markers.push(r),r.register(this.lines.onTrim((function(e){r.line-=e,r.line<0&&r.dispose()}))),r.register(this.lines.onInsert((function(e){r.line>=e.index&&(r.line+=e.amount)}))),r.register(this.lines.onDelete((function(e){r.line>=e.index&&r.line<e.index+e.amount&&r.dispose(),r.line>e.index&&(r.line-=e.amount)}))),r.register(r.onDispose((function(){return t._removeMarker(r)}))),r},e.prototype._removeMarker=function(e){this.markers.splice(this.markers.indexOf(e),1)},e.prototype.iterator=function(e,t,r,i,n){return new f(this,e,t,r,i,n)},e}();t.Buffer=h;var f=function(){function e(e,t,r,i,n,o){void 0===r&&(r=0),void 0===i&&(i=e.lines.length),void 0===n&&(n=0),void 0===o&&(o=0),this._buffer=e,this._trimRight=t,this._startIndex=r,this._endIndex=i,this._startOverscan=n,this._endOverscan=o,this._startIndex<0&&(this._startIndex=0),this._endIndex>this._buffer.lines.length&&(this._endIndex=this._buffer.lines.length),this._current=this._startIndex}return e.prototype.hasNext=function(){return this._current<this._endIndex},e.prototype.next=function(){var e=this._buffer.getWrappedRangeForLine(this._current);e.first<this._startIndex-this._startOverscan&&(e.first=this._startIndex-this._startOverscan),e.last>this._endIndex+this._endOverscan&&(e.last=this._endIndex+this._endOverscan),e.first=Math.max(e.first,0),e.last=Math.min(e.last,this._buffer.lines.length);for(var t="",r=e.first;r<=e.last;++r)t+=this._buffer.translateBufferLineToString(r,this._trimRight);return this._current=e.last+1,{range:e,content:t}},e}();t.BufferStringIterator=f},8437:(e,t,r)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.BufferLine=t.DEFAULT_ATTR_DATA=void 0;var i=r(482),n=r(643),o=r(511),s=r(3734);t.DEFAULT_ATTR_DATA=Object.freeze(new s.AttributeData);var a=function(){function e(e,t,r){void 0===r&&(r=!1),this.isWrapped=r,this._combined={},this._extendedAttrs={},this._data=new Uint32Array(3*e);for(var i=t||o.CellData.fromCharData([0,n.NULL_CELL_CHAR,n.NULL_CELL_WIDTH,n.NULL_CELL_CODE]),s=0;s<e;++s)this.setCell(s,i);this.length=e}return e.prototype.get=function(e){var t=this._data[3*e+0],r=2097151&t;return[this._data[3*e+1],2097152&t?this._combined[e]:r?(0,i.stringFromCodePoint)(r):"",t>>22,2097152&t?this._combined[e].charCodeAt(this._combined[e].length-1):r]},e.prototype.set=function(e,t){this._data[3*e+1]=t[n.CHAR_DATA_ATTR_INDEX],t[n.CHAR_DATA_CHAR_INDEX].length>1?(this._combined[e]=t[1],this._data[3*e+0]=2097152|e|t[n.CHAR_DATA_WIDTH_INDEX]<<22):this._data[3*e+0]=t[n.CHAR_DATA_CHAR_INDEX].charCodeAt(0)|t[n.CHAR_DATA_WIDTH_INDEX]<<22},e.prototype.getWidth=function(e){return this._data[3*e+0]>>22},e.prototype.hasWidth=function(e){return 12582912&this._data[3*e+0]},e.prototype.getFg=function(e){return this._data[3*e+1]},e.prototype.getBg=function(e){return this._data[3*e+2]},e.prototype.hasContent=function(e){return 4194303&this._data[3*e+0]},e.prototype.getCodePoint=function(e){var t=this._data[3*e+0];return 2097152&t?this._combined[e].charCodeAt(this._combined[e].length-1):2097151&t},e.prototype.isCombined=function(e){return 2097152&this._data[3*e+0]},e.prototype.getString=function(e){var t=this._data[3*e+0];return 2097152&t?this._combined[e]:2097151&t?(0,i.stringFromCodePoint)(2097151&t):""},e.prototype.loadCell=function(e,t){var r=3*e;return t.content=this._data[r+0],t.fg=this._data[r+1],t.bg=this._data[r+2],2097152&t.content&&(t.combinedData=this._combined[e]),268435456&t.bg&&(t.extended=this._extendedAttrs[e]),t},e.prototype.setCell=function(e,t){2097152&t.content&&(this._combined[e]=t.combinedData),268435456&t.bg&&(this._extendedAttrs[e]=t.extended),this._data[3*e+0]=t.content,this._data[3*e+1]=t.fg,this._data[3*e+2]=t.bg},e.prototype.setCellFromCodePoint=function(e,t,r,i,n,o){268435456&n&&(this._extendedAttrs[e]=o),this._data[3*e+0]=t|r<<22,this._data[3*e+1]=i,this._data[3*e+2]=n},e.prototype.addCodepointToCell=function(e,t){var r=this._data[3*e+0];2097152&r?this._combined[e]+=(0,i.stringFromCodePoint)(t):(2097151&r?(this._combined[e]=(0,i.stringFromCodePoint)(2097151&r)+(0,i.stringFromCodePoint)(t),r&=-2097152,r|=2097152):r=t|1<<22,this._data[3*e+0]=r)},e.prototype.insertCells=function(e,t,r,i){if((e%=this.length)&&2===this.getWidth(e-1)&&this.setCellFromCodePoint(e-1,0,1,(null==i?void 0:i.fg)||0,(null==i?void 0:i.bg)||0,(null==i?void 0:i.extended)||new s.ExtendedAttrs),t<this.length-e){for(var n=new o.CellData,a=this.length-e-t-1;a>=0;--a)this.setCell(e+t+a,this.loadCell(e+a,n));for(a=0;a<t;++a)this.setCell(e+a,r)}else for(a=e;a<this.length;++a)this.setCell(a,r);2===this.getWidth(this.length-1)&&this.setCellFromCodePoint(this.length-1,0,1,(null==i?void 0:i.fg)||0,(null==i?void 0:i.bg)||0,(null==i?void 0:i.extended)||new s.ExtendedAttrs)},e.prototype.deleteCells=function(e,t,r,i){if(e%=this.length,t<this.length-e){for(var n=new o.CellData,a=0;a<this.length-e-t;++a)this.setCell(e+a,this.loadCell(e+t+a,n));for(a=this.length-t;a<this.length;++a)this.setCell(a,r)}else for(a=e;a<this.length;++a)this.setCell(a,r);e&&2===this.getWidth(e-1)&&this.setCellFromCodePoint(e-1,0,1,(null==i?void 0:i.fg)||0,(null==i?void 0:i.bg)||0,(null==i?void 0:i.extended)||new s.ExtendedAttrs),0!==this.getWidth(e)||this.hasContent(e)||this.setCellFromCodePoint(e,0,1,(null==i?void 0:i.fg)||0,(null==i?void 0:i.bg)||0,(null==i?void 0:i.extended)||new s.ExtendedAttrs)},e.prototype.replaceCells=function(e,t,r,i){for(e&&2===this.getWidth(e-1)&&this.setCellFromCodePoint(e-1,0,1,(null==i?void 0:i.fg)||0,(null==i?void 0:i.bg)||0,(null==i?void 0:i.extended)||new s.ExtendedAttrs),t<this.length&&2===this.getWidth(t-1)&&this.setCellFromCodePoint(t,0,1,(null==i?void 0:i.fg)||0,(null==i?void 0:i.bg)||0,(null==i?void 0:i.extended)||new s.ExtendedAttrs);e<t&&e<this.length;)this.setCell(e++,r)},e.prototype.resize=function(e,t){if(e!==this.length){if(e>this.length){var r=new Uint32Array(3*e);this.length&&(3*e<this._data.length?r.set(this._data.subarray(0,3*e)):r.set(this._data)),this._data=r;for(var i=this.length;i<e;++i)this.setCell(i,t)}else if(e){(r=new Uint32Array(3*e)).set(this._data.subarray(0,3*e)),this._data=r;var n=Object.keys(this._combined);for(i=0;i<n.length;i++){var o=parseInt(n[i],10);o>=e&&delete this._combined[o]}}else this._data=new Uint32Array(0),this._combined={};this.length=e}},e.prototype.fill=function(e){this._combined={},this._extendedAttrs={};for(var t=0;t<this.length;++t)this.setCell(t,e)},e.prototype.copyFrom=function(e){for(var t in this.length!==e.length?this._data=new Uint32Array(e._data):this._data.set(e._data),this.length=e.length,this._combined={},e._combined)this._combined[t]=e._combined[t];for(var t in this._extendedAttrs={},e._extendedAttrs)this._extendedAttrs[t]=e._extendedAttrs[t];this.isWrapped=e.isWrapped},e.prototype.clone=function(){var t=new e(0);for(var r in t._data=new Uint32Array(this._data),t.length=this.length,this._combined)t._combined[r]=this._combined[r];for(var r in this._extendedAttrs)t._extendedAttrs[r]=this._extendedAttrs[r];return t.isWrapped=this.isWrapped,t},e.prototype.getTrimmedLength=function(){for(var e=this.length-1;e>=0;--e)if(4194303&this._data[3*e+0])return e+(this._data[3*e+0]>>22);return 0},e.prototype.copyCellsFrom=function(e,t,r,i,n){var o=e._data;if(n)for(var s=i-1;s>=0;s--)for(var a=0;a<3;a++)this._data[3*(r+s)+a]=o[3*(t+s)+a];else for(s=0;s<i;s++)for(a=0;a<3;a++)this._data[3*(r+s)+a]=o[3*(t+s)+a];var c=Object.keys(e._combined);for(a=0;a<c.length;a++){var l=parseInt(c[a],10);l>=t&&(this._combined[l-t+r]=e._combined[l])}},e.prototype.translateToString=function(e,t,r){void 0===e&&(e=!1),void 0===t&&(t=0),void 0===r&&(r=this.length),e&&(r=Math.min(r,this.getTrimmedLength()));for(var o="";t<r;){var s=this._data[3*t+0],a=2097151&s;o+=2097152&s?this._combined[t]:a?(0,i.stringFromCodePoint)(a):n.WHITESPACE_CELL_CHAR,t+=s>>22||1}return o},e}();t.BufferLine=a},4841:(e,t)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.getRangeLength=void 0,t.getRangeLength=function(e,t){if(e.start.y>e.end.y)throw new Error("Buffer range end ("+e.end.x+", "+e.end.y+") cannot be before start ("+e.start.x+", "+e.start.y+")");return t*(e.end.y-e.start.y)+(e.end.x-e.start.x+1)}},4634:(e,t)=>{function r(e,t,r){if(t===e.length-1)return e[t].getTrimmedLength();var i=!e[t].hasContent(r-1)&&1===e[t].getWidth(r-1),n=2===e[t+1].getWidth(0);return i&&n?r-1:r}Object.defineProperty(t,"__esModule",{value:!0}),t.getWrappedLineTrimmedLength=t.reflowSmallerGetNewLineLengths=t.reflowLargerApplyNewLayout=t.reflowLargerCreateNewLayout=t.reflowLargerGetLinesToRemove=void 0,t.reflowLargerGetLinesToRemove=function(e,t,i,n,o){for(var s=[],a=0;a<e.length-1;a++){var c=a,l=e.get(++c);if(l.isWrapped){for(var u=[e.get(a)];c<e.length&&l.isWrapped;)u.push(l),l=e.get(++c);if(n>=a&&n<c)a+=u.length-1;else{for(var h=0,f=r(u,h,t),_=1,d=0;_<u.length;){var p=r(u,_,t),v=p-d,g=i-f,y=Math.min(v,g);u[h].copyCellsFrom(u[_],d,f,y,!1),(f+=y)===i&&(h++,f=0),(d+=y)===p&&(_++,d=0),0===f&&0!==h&&2===u[h-1].getWidth(i-1)&&(u[h].copyCellsFrom(u[h-1],i-1,f++,1,!1),u[h-1].setCell(i-1,o))}u[h].replaceCells(f,i,o);for(var m=0,b=u.length-1;b>0&&(b>h||0===u[b].getTrimmedLength());b--)m++;m>0&&(s.push(a+u.length-m),s.push(m)),a+=u.length-1}}}return s},t.reflowLargerCreateNewLayout=function(e,t){for(var r=[],i=0,n=t[i],o=0,s=0;s<e.length;s++)if(n===s){var a=t[++i];e.onDeleteEmitter.fire({index:s-o,amount:a}),s+=a-1,o+=a,n=t[++i]}else r.push(s);return{layout:r,countRemoved:o}},t.reflowLargerApplyNewLayout=function(e,t){for(var r=[],i=0;i<t.length;i++)r.push(e.get(t[i]));for(i=0;i<r.length;i++)e.set(i,r[i]);e.length=t.length},t.reflowSmallerGetNewLineLengths=function(e,t,i){for(var n=[],o=e.map((function(i,n){return r(e,n,t)})).reduce((function(e,t){return e+t})),s=0,a=0,c=0;c<o;){if(o-c<i){n.push(o-c);break}s+=i;var l=r(e,a,t);s>l&&(s-=l,a++);var u=2===e[a].getWidth(s-1);u&&s--;var h=u?i-1:i;n.push(h),c+=h}return n},t.getWrappedLineTrimmedLength=r},5295:function(e,t,r){var i,n=this&&this.__extends||(i=function(e,t){return i=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var r in t)Object.prototype.hasOwnProperty.call(t,r)&&(e[r]=t[r])},i(e,t)},function(e,t){if("function"!=typeof t&&null!==t)throw new TypeError("Class extends value "+String(t)+" is not a constructor or null");function r(){this.constructor=e}i(e,t),e.prototype=null===t?Object.create(t):(r.prototype=t.prototype,new r)});Object.defineProperty(t,"__esModule",{value:!0}),t.BufferSet=void 0;var o=r(9092),s=r(8460),a=function(e){function t(t,r){var i=e.call(this)||this;return i._optionsService=t,i._bufferService=r,i._onBufferActivate=i.register(new s.EventEmitter),i.reset(),i}return n(t,e),Object.defineProperty(t.prototype,"onBufferActivate",{get:function(){return this._onBufferActivate.event},enumerable:!1,configurable:!0}),t.prototype.reset=function(){this._normal=new o.Buffer(!0,this._optionsService,this._bufferService),this._normal.fillViewportRows(),this._alt=new o.Buffer(!1,this._optionsService,this._bufferService),this._activeBuffer=this._normal,this._onBufferActivate.fire({activeBuffer:this._normal,inactiveBuffer:this._alt}),this.setupTabStops()},Object.defineProperty(t.prototype,"alt",{get:function(){return this._alt},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"active",{get:function(){return this._activeBuffer},enumerable:!1,configurable:!0}),Object.defineProperty(t.prototype,"normal",{get:function(){return this._normal},enumerable:!1,configurable:!0}),t.prototype.activateNormalBuffer=function(){this._activeBuffer!==this._normal&&(this._normal.x=this._alt.x,this._normal.y=this._alt.y,this._alt.clear(),this._activeBuffer=this._normal,this._onBufferActivate.fire({activeBuffer:this._normal,inactiveBuffer:this._alt}))},t.prototype.activateAltBuffer=function(e){this._activeBuffer!==this._alt&&(this._alt.fillViewportRows(e),this._alt.x=this._normal.x,this._alt.y=this._normal.y,this._activeBuffer=this._alt,this._onBufferActivate.fire({activeBuffer:this._alt,inactiveBuffer:this._normal}))},t.prototype.resize=function(e,t){this._normal.resize(e,t),this._alt.resize(e,t)},t.prototype.setupTabStops=function(e){this._normal.setupTabStops(e),this._alt.setupTabStops(e)},t}(r(844).Disposable);t.BufferSet=a},511:function(e,t,r){var i,n=this&&this.__extends||(i=function(e,t){return i=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var r in 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n=e||Date.now();this._writeBuffer.length>this._bufferOffset;){var o=this._writeBuffer[this._bufferOffset],s=this._action(o,t);if(s)return void s.catch((function(e){return r((function(){throw e})),Promise.resolve(!1)})).then((function(e){return Date.now()-n>=12?setTimeout((function(){return i._innerWrite(0,e)})):i._innerWrite(n,e)}));var a=this._callbacks[this._bufferOffset];if(a&&a(),this._bufferOffset++,this._pendingData-=o.length,Date.now()-n>=12)break}this._writeBuffer.length>this._bufferOffset?(this._bufferOffset>50&&(this._writeBuffer=this._writeBuffer.slice(this._bufferOffset),this._callbacks=this._callbacks.slice(this._bufferOffset),this._bufferOffset=0),setTimeout((function(){return i._innerWrite()}))):(this._writeBuffer.length=0,this._callbacks.length=0,this._pendingData=0,this._bufferOffset=0)},e}();t.WriteBuffer=i},5941:(e,t)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.toRgbString=t.parseColor=void 0;var r=/^([\da-f]{1})\/([\da-f]{1})\/([\da-f]{1})$|^([\da-f]{2})\/([\da-f]{2})\/([\da-f]{2})$|^([\da-f]{3})\/([\da-f]{3})\/([\da-f]{3})$|^([\da-f]{4})\/([\da-f]{4})\/([\da-f]{4})$/,i=/^[\da-f]+$/;function n(e,t){var r=e.toString(16),i=r.length<2?"0"+r:r;switch(t){case 4:return r[0];case 8:return i;case 12:return(i+i).slice(0,3);default:return i+i}}t.parseColor=function(e){if(e){var t=e.toLowerCase();if(0===t.indexOf("rgb:")){t=t.slice(4);var n=r.exec(t);if(n){var o=n[1]?15:n[4]?255:n[7]?4095:65535;return[Math.round(parseInt(n[1]||n[4]||n[7]||n[10],16)/o*255),Math.round(parseInt(n[2]||n[5]||n[8]||n[11],16)/o*255),Math.round(parseInt(n[3]||n[6]||n[9]||n[12],16)/o*255)]}}else if(0===t.indexOf("#")&&(t=t.slice(1),i.exec(t)&&[3,6,9,12].includes(t.length))){for(var s=t.length/3,a=[0,0,0],c=0;c<3;++c){var l=parseInt(t.slice(s*c,s*c+s),16);a[c]=1===s?l<<4:2===s?l:3===s?l>>4:l>>8}return a}}},t.toRgbString=function(e,t){void 0===t&&(t=16);var r=e[0],i=e[1],o=e[2];return"rgb:"+n(r,t)+"/"+n(i,t)+"/"+n(o,t)}},5770:(e,t)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.PAYLOAD_LIMIT=void 0,t.PAYLOAD_LIMIT=1e7},6351:(e,t,r)=>{Object.defineProperty(t,"__esModule",{value:!0}),t.DcsHandler=t.DcsParser=void 0;var i=r(482),n=r(8742),o=r(5770),s=[],a=function(){function e(){this._handlers=Object.create(null),this._active=s,this._ident=0,this._handlerFb=function(){},this._stack={paused:!1,loopPosition:0,fallThrough:!1}}return e.prototype.dispose=function(){this._handlers=Object.create(null),this._handlerFb=function(){},this._active=s},e.prototype.registerHandler=function(e,t){void 0===this._handlers[e]&&(this._handlers[e]=[]);var r=this._handlers[e];return r.push(t),{dispose:function(){var e=r.indexOf(t);-1!==e&&r.splice(e,1)}}},e.prototype.clearHandler=function(e){this._handlers[e]&&delete this._handlers[e]},e.prototype.setHandlerFallback=function(e){this._handlerFb=e},e.prototype.reset=function(){if(this._active.length)for(var e=this._stack.paused?this._stack.loopPosition-1:this._active.length-1;e>=0;--e)this._active[e].unhook(!1);this._stack.paused=!1,this._active=s,this._ident=0},e.prototype.hook=function(e,t){if(this.reset(),this._ident=e,this._active=this._handlers[e]||s,this._active.length)for(var r=this._active.length-1;r>=0;r--)this._active[r].hook(t);else this._handlerFb(this._ident,"HOOK",t)},e.prototype.put=function(e,t,r){if(this._active.length)for(var n=this._active.length-1;n>=0;n--)this._active[n].put(e,t,r);else this._handlerFb(this._ident,"PUT",(0,i.utf32ToString)(e,t,r))},e.prototype.unhook=function(e,t){if(void 0===t&&(t=!0),this._active.length){var r=!1,i=this._active.length-1,n=!1;if(this._stack.paused&&(i=this._stack.loopPosition-1,r=t,n=this._stack.fallThrough,this._stack.paused=!1),!n&&!1===r){for(;i>=0&&!0!==(r=this._active[i].unhook(e));i--)if(r instanceof Promise)return 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this._params=c,this._data="",this._hitLimit=!1,r},e}();t.DcsHandler=l},2015:function(e,t,r){var i,n=this&&this.__extends||(i=function(e,t){return i=Object.setPrototypeOf||{__proto__:[]}instanceof Array&&function(e,t){e.__proto__=t}||function(e,t){for(var r in t)Object.prototype.hasOwnProperty.call(t,r)&&(e[r]=t[r])},i(e,t)},function(e,t){if("function"!=typeof t&&null!==t)throw new TypeError("Class extends value "+String(t)+" is not a constructor or null");function r(){this.constructor=e}i(e,t),e.prototype=null===t?Object.create(t):(r.prototype=t.prototype,new r)});Object.defineProperty(t,"__esModule",{value:!0}),t.EscapeSequenceParser=t.VT500_TRANSITION_TABLE=t.TransitionTable=void 0;var o=r(844),s=r(8273),a=r(8742),c=r(6242),l=r(6351),u=function(){function e(e){this.table=new Uint8Array(e)}return e.prototype.setDefault=function(e,t){(0,s.fill)(this.table,e<<4|t)},e.prototype.add=function(e,t,r,i){this.table[t<<8|e]=r<<4|i},e.prototype.addMany=function(e,t,r,i){for(var n=0;n<e.length;n++)this.table[t<<8|e[n]]=r<<4|i},e}();t.TransitionTable=u;var h=160;t.VT500_TRANSITION_TABLE=function(){var e=new u(4095),t=Array.apply(null,Array(256)).map((function(e,t){return t})),r=function(e,r){return t.slice(e,r)},i=r(32,127),n=r(0,24);n.push(25),n.push.apply(n,r(28,32));var o,s=r(0,14);for(o in e.setDefault(1,0),e.addMany(i,0,2,0),s)e.addMany([24,26,153,154],o,3,0),e.addMany(r(128,144),o,3,0),e.addMany(r(144,152),o,3,0),e.add(156,o,0,0),e.add(27,o,11,1),e.add(157,o,4,8),e.addMany([152,158,159],o,0,7),e.add(155,o,11,3),e.add(144,o,11,9);return e.addMany(n,0,3,0),e.addMany(n,1,3,1),e.add(127,1,0,1),e.addMany(n,8,0,8),e.addMany(n,3,3,3),e.add(127,3,0,3),e.addMany(n,4,3,4),e.add(127,4,0,4),e.addMany(n,6,3,6),e.addMany(n,5,3,5),e.add(127,5,0,5),e.addMany(n,2,3,2),e.add(127,2,0,2),e.add(93,1,4,8),e.addMany(i,8,5,8),e.add(127,8,5,8),e.addMany([156,27,24,26,7],8,6,0),e.addMany(r(28,32),8,0,8),e.addMany([88,94,95],1,0,7),e.addMany(i,7,0,7),e.addMany(n,7,0,7),e.add(156,7,0,0),e.add(127,7,0,7),e.add(91,1,11,3),e.addMany(r(64,127),3,7,0),e.addMany(r(48,60),3,8,4),e.addMany([60,61,62,63],3,9,4),e.addMany(r(48,60),4,8,4),e.addMany(r(64,127),4,7,0),e.addMany([60,61,62,63],4,0,6),e.addMany(r(32,64),6,0,6),e.add(127,6,0,6),e.addMany(r(64,127),6,0,0),e.addMany(r(32,48),3,9,5),e.addMany(r(32,48),5,9,5),e.addMany(r(48,64),5,0,6),e.addMany(r(64,127),5,7,0),e.addMany(r(32,48),4,9,5),e.addMany(r(32,48),1,9,2),e.addMany(r(32,48),2,9,2),e.addMany(r(48,127),2,10,0),e.addMany(r(48,80),1,10,0),e.addMany(r(81,88),1,10,0),e.addMany([89,90,92],1,10,0),e.addMany(r(96,127),1,10,0),e.add(80,1,11,9),e.addMany(n,9,0,9),e.add(127,9,0,9),e.addMany(r(28,32),9,0,9),e.addMany(r(32,48),9,9,12),e.addMany(r(48,60),9,8,10),e.addMany([60,61,62,63],9,9,10),e.addMany(n,11,0,11),e.addMany(r(32,128),11,0,11),e.addMany(r(28,32),11,0,11),e.addMany(n,10,0,10),e.add(127,10,0,10),e.addMany(r(28,32),10,0,10),e.addMany(r(48,60),10,8,10),e.addMany([60,61,62,63],10,0,11),e.addMany(r(32,48),10,9,12),e.addMany(n,12,0,12),e.add(127,12,0,12),e.addMany(r(28,32),12,0,12),e.addMany(r(32,48),12,9,12),e.addMany(r(48,64),12,0,11),e.addMany(r(64,127),12,12,13),e.addMany(r(64,127),10,12,13),e.addMany(r(64,127),9,12,13),e.addMany(n,13,13,13),e.addMany(i,13,13,13),e.add(127,13,0,13),e.addMany([27,156,24,26],13,14,0),e.add(h,0,2,0),e.add(h,8,5,8),e.add(h,6,0,6),e.add(h,11,0,11),e.add(h,13,13,13),e}();var f=function(e){function r(r){void 0===r&&(r=t.VT500_TRANSITION_TABLE);var i=e.call(this)||this;return i._transitions=r,i._parseStack={state:0,handlers:[],handlerPos:0,transition:0,chunkPos:0},i.initialState=0,i.currentState=i.initialState,i._params=new a.Params,i._params.addParam(0),i._collect=0,i.precedingCodepoint=0,i._printHandlerFb=function(e,t,r){},i._executeHandlerFb=function(e){},i._csiHandlerFb=function(e,t){},i._escHandlerFb=function(e){},i._errorHandlerFb=function(e){return e},i._printHandler=i._printHandlerFb,i._executeHandlers=Object.create(null),i._csiHandlers=Object.create(null),i._escHandlers=Object.create(null),i._oscParser=new c.OscParser,i._dcsParser=new l.DcsParser,i._errorHandler=i._errorHandlerFb,i.registerEscHandler({final:"\\"},(function(){return!0})),i}return n(r,e),r.prototype._identifier=function(e,t){void 0===t&&(t=[64,126]);var r=0;if(e.prefix){if(e.prefix.length>1)throw new Error("only one byte as prefix supported");if((r=e.prefix.charCodeAt(0))&&60>r||r>63)throw new Error("prefix must be in range 0x3c .. 0x3f")}if(e.intermediates){if(e.intermediates.length>2)throw new Error("only two bytes as intermediates are supported");for(var i=0;i<e.intermediates.length;++i){var n=e.intermediates.charCodeAt(i);if(32>n||n>47)throw new Error("intermediate must be in range 0x20 .. 0x2f");r<<=8,r|=n}}if(1!==e.final.length)throw new Error("final must be a single byte");var o=e.final.charCodeAt(0);if(t[0]>o||o>t[1])throw new Error("final must be in range "+t[0]+" .. "+t[1]);return(r<<=8)|o},r.prototype.identToString=function(e){for(var t=[];e;)t.push(String.fromCharCode(255&e)),e>>=8;return t.reverse().join("")},r.prototype.dispose=function(){this._csiHandlers=Object.create(null),this._executeHandlers=Object.create(null),this._escHandlers=Object.create(null),this._oscParser.dispose(),this._dcsParser.dispose()},r.prototype.setPrintHandler=function(e){this._printHandler=e},r.prototype.clearPrintHandler=function(){this._printHandler=this._printHandlerFb},r.prototype.registerEscHandler=function(e,t){var r=this._identifier(e,[48,126]);void 0===this._escHandlers[r]&&(this._escHandlers[r]=[]);var i=this._escHandlers[r];return i.push(t),{dispose:function(){var e=i.indexOf(t);-1!==e&&i.splice(e,1)}}},r.prototype.clearEscHandler=function(e){this._escHandlers[this._identifier(e,[48,126])]&&delete this._escHandlers[this._identifier(e,[48,126])]},r.prototype.setEscHandlerFallback=function(e){this._escHandlerFb=e},r.prototype.setExecuteHandler=function(e,t){this._executeHandlers[e.charCodeAt(0)]=t},r.prototype.clearExecuteHandler=function(e){this._executeHandlers[e.charCodeAt(0)]&&delete this._executeHandlers[e.charCodeAt(0)]},r.prototype.setExecuteHandlerFallback=function(e){this._executeHandlerFb=e},r.prototype.registerCsiHandler=function(e,t){var r=this._identifier(e);void 0===this._csiHandlers[r]&&(this._csiHandlers[r]=[]);var i=this._csiHandlers[r];return i.push(t),{dispose:function(){var e=i.indexOf(t);-1!==e&&i.splice(e,1)}}},r.prototype.clearCsiHandler=function(e){this._csiHandlers[this._identifier(e)]&&delete this._csiHandlers[this._identifier(e)]},r.prototype.setCsiHandlerFallback=function(e){this._csiHandlerFb=e},r.prototype.registerDcsHandler=function(e,t){return this._dcsParser.registerHandler(this._identifier(e),t)},r.prototype.clearDcsHandler=function(e){this._dcsParser.clearHandler(this._identifier(e))},r.prototype.setDcsHandlerFallback=function(e){this._dcsParser.setHandlerFallback(e)},r.prototype.registerOscHandler=function(e,t){return this._oscParser.registerHandler(e,t)},r.prototype.clearOscHandler=function(e){this._oscParser.clearHandler(e)},r.prototype.setOscHandlerFallback=function(e){this._oscParser.setHandlerFallback(e)},r.prototype.setErrorHandler=function(e){this._errorHandler=e},r.prototype.clearErrorHandler=function(){this._errorHandler=this._errorHandlerFb},r.prototype.reset=function(){this.currentState=this.initialState,this._oscParser.reset(),this._dcsParser.reset(),this._params.reset(),this._params.addParam(0),this._collect=0,this.precedingCodepoint=0,0!==this._parseStack.state&&(this._parseStack.state=2,this._parseStack.handlers=[])},r.prototype._preserveStack=function(e,t,r,i,n){this._parseStack.state=e,this._parseStack.handlers=t,this._parseStack.handlerPos=r,this._parseStack.transition=i,this._parseStack.chunkPos=n},r.prototype.parse=function(e,t,r){var i,n=0,o=0,s=0;if(this._parseStack.state)if(2===this._parseStack.state)this._parseStack.state=0,s=this._parseStack.chunkPos+1;else{if(void 0===r||1===this._parseStack.state)throw this._parseStack.state=1,new Error("improper continuation due to previous async handler, giving up parsing");var a=this._parseStack.handlers,c=this._parseStack.handlerPos-1;switch(this._parseStack.state){case 3:if(!1===r&&c>-1)for(;c>=0&&!0!==(i=a[c](this._params));c--)if(i instanceof Promise)return this._parseStack.handlerPos=c,i;this._parseStack.handlers=[];break;case 4:if(!1===r&&c>-1)for(;c>=0&&!0!==(i=a[c]());c--)if(i instanceof Promise)return this._parseStack.handlerPos=c,i;this._parseStack.handlers=[];break;case 6:if(n=e[this._parseStack.chunkPos],i=this._dcsParser.unhook(24!==n&&26!==n,r))return i;27===n&&(this._parseStack.transition|=1),this._params.reset(),this._params.addParam(0),this._collect=0;break;case 5:if(n=e[this._parseStack.chunkPos],i=this._oscParser.end(24!==n&&26!==n,r))return i;27===n&&(this._parseStack.transition|=1),this._params.reset(),this._params.addParam(0),this._collect=0}this._parseStack.state=0,s=this._parseStack.chunkPos+1,this.precedingCodepoint=0,this.currentState=15&this._parseStack.transition}for(var l=s;l<t;++l){switch(n=e[l],(o=this._transitions.table[this.currentState<<8|(n<160?n:h)])>>4){case 2:for(var u=l+1;;++u){if(u>=t||(n=e[u])<32||n>126&&n<h){this._printHandler(e,l,u),l=u-1;break}if(++u>=t||(n=e[u])<32||n>126&&n<h){this._printHandler(e,l,u),l=u-1;break}if(++u>=t||(n=e[u])<32||n>126&&n<h){this._printHandler(e,l,u),l=u-1;break}if(++u>=t||(n=e[u])<32||n>126&&n<h){this._printHandler(e,l,u),l=u-1;break}}break;case 3:this._executeHandlers[n]?this._executeHandlers[n]():this._executeHandlerFb(n),this.precedingCodepoint=0;break;case 0:break;case 1:if(this._errorHandler({position:l,code:n,currentState:this.currentState,collect:this._collect,params:this._params,abort:!1}).abort)return;break;case 7:for(var f=(a=this._csiHandlers[this._collect<<8|n])?a.length-1:-1;f>=0&&!0!==(i=a[f](this._params));f--)if(i instanceof Promise)return this._preserveStack(3,a,f,o,l),i;f<0&&this._csiHandlerFb(this._collect<<8|n,this._params),this.precedingCodepoint=0;break;case 8:do{switch(n){case 59:this._params.addParam(0);break;case 58:this._params.addSubParam(-1);break;default:this._params.addDigit(n-48)}}while(++l<t&&(n=e[l])>47&&n<60);l--;break;case 9:this._collect<<=8,this._collect|=n;break;case 10:for(var _=this._escHandlers[this._collect<<8|n],d=_?_.length-1:-1;d>=0&&!0!==(i=_[d]());d--)if(i instanceof Promise)return this._preserveStack(4,_,d,o,l),i;d<0&&this._escHandlerFb(this._collect<<8|n),this.precedingCodepoint=0;break;case 11:this._params.reset(),this._params.addParam(0),this._collect=0;break;case 12:this._dcsParser.hook(this._collect<<8|n,this._params);break;case 13:for(var p=l+1;;++p)if(p>=t||24===(n=e[p])||26===n||27===n||n>127&&n<h){this._dcsParser.put(e,l,p),l=p-1;break}break;case 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+              "headers": [
+                [
+                  "content-length",
+                  "426644"
+                ],
+                [
+                  "content-type",
+                  "text/javascript"
+                ]
+              ],
+              "ok": true,
+              "status": 200,
+              "status_text": ""
+            },
+            "https://localhost:10000/out": {
+              "data": "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",
+              "headers": [
+                [
+                  "content-length",
+                  "1067"
+                ],
+                [
+                  "content-type",
+                  "text/html; charset=UTF-8"
+                ]
+              ],
+              "ok": true,
+              "status": 200,
+              "status_text": ""
+            },
+            "https://localhost:10000/resize?rows=46&cols=196": {
+              "data": "",
+              "headers": [
+                [
+                  "content-length",
+                  "0"
+                ],
+                [
+                  "content-type",
+                  "text/html; charset=UTF-8"
+                ]
+              ],
+              "ok": true,
+              "status": 200,
+              "status_text": ""
+            }
+          }
+        },
+        "id": "giIA2M-ANUIM",
+        "outputId": "612c3487-1fd7-41ab-f65a-690b1325f46d"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/plain": [
+              "Launching Xterm..."
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        },
+        {
+          "data": {
+            "application/javascript": "\n        (async () => {\n            const url = new URL(await google.colab.kernel.proxyPort(10000, {'cache': true}));\n            const iframe = document.createElement('iframe');\n            iframe.src = url;\n            iframe.setAttribute('width', '100%');\n            iframe.setAttribute('height', '800');\n            iframe.setAttribute('frameborder', 0);\n            document.body.appendChild(iframe);\n        })();\n    ",
+            "text/plain": [
+              "<IPython.core.display.Javascript object>"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "\n",
+        "%xterm\n",
+        "# touch /content/foo\n",
+        "# touch /content/bar\n",
+        "# npx -y supergateway --port 8000 --stdio 'npx -y @modelcontextprotocol/server-filesystem /content'"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "id": "f4ksBP6MN7cB",
+      "metadata": {
+        "id": "f4ksBP6MN7cB"
+      },
+      "source": [
+        "Register the toolgroup hosted in the MCP server with llama stack and verify if the stack discovers the tools correctly"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 10,
+      "id": "DwdKhQb1N295",
+      "metadata": {
+        "id": "DwdKhQb1N295"
+      },
+      "outputs": [],
+      "source": [
+        "from llama_stack_client.types.shared_params.url import URL\n",
+        "client.toolgroups.register(\n",
+        "    toolgroup_id=\"mcp::filesystem\",\n",
+        "    provider_id=\"model-context-protocol\",\n",
+        "    mcp_endpoint=URL(uri=\"http://localhost:8000/sse\"),\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 11,
+      "id": "ZZ5_vIkDOyAN",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 1000
+        },
+        "id": "ZZ5_vIkDOyAN",
+        "outputId": "f6fa8639-c2d8-497d-f4ed-716b3bf775d4"
+      },
+      "outputs": [
+        {
+          "data": {
+            "text/html": [
+              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Tool</span><span style=\"font-weight: bold\">(</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'Read the complete contents of a file from the file system. Handles various text encodings and provides detailed error messages if the file cannot be read. Use this tool when you need to examine the contents of a single file. Only works within allowed directories.'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">identifier</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'read_file'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">parameters</span>=<span style=\"font-weight: bold\">[</span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Parameter</span><span style=\"font-weight: bold\">(</span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">''</span>, <span style=\"color: #808000; text-decoration-color: #808000\">name</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'path'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">parameter_type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'string'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">required</span>=<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>, <span style=\"color: #808000; text-decoration-color: #808000\">default</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span><span style=\"font-weight: bold\">)]</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'model-context-protocol'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_resource_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'read_file'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">tool_host</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'model_context_protocol'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">toolgroup_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'mcp::filesystem'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'tool'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">metadata</span>=<span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'endpoint'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'http://localhost:8000/sse'</span><span style=\"font-weight: bold\">}</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">)</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Tool</span><span style=\"font-weight: bold\">(</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">\"Read the contents of multiple files simultaneously. This is more efficient than reading files one by one when you need to analyze or compare multiple files. Each file's content is returned with its path as a reference. Failed reads for individual files won't stop the entire operation. Only works within allowed directories.\"</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">identifier</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'read_multiple_files'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">parameters</span>=<span style=\"font-weight: bold\">[</span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Parameter</span><span style=\"font-weight: bold\">(</span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">''</span>, <span style=\"color: #808000; text-decoration-color: #808000\">name</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'paths'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">parameter_type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'array'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">required</span>=<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>, <span style=\"color: #808000; text-decoration-color: #808000\">default</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span><span style=\"font-weight: bold\">)]</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'model-context-protocol'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_resource_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'read_multiple_files'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">tool_host</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'model_context_protocol'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">toolgroup_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'mcp::filesystem'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'tool'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">metadata</span>=<span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'endpoint'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'http://localhost:8000/sse'</span><span style=\"font-weight: bold\">}</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">)</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Tool</span><span style=\"font-weight: bold\">(</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'Create a new file or completely overwrite an existing file with new content. Use with caution as it will overwrite existing files without warning. Handles text content with proper encoding. Only works within allowed directories.'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">identifier</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'write_file'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">parameters</span>=<span style=\"font-weight: bold\">[</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Parameter</span><span style=\"font-weight: bold\">(</span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">''</span>, <span style=\"color: #808000; text-decoration-color: #808000\">name</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'path'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">parameter_type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'string'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">required</span>=<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>, <span style=\"color: #808000; text-decoration-color: #808000\">default</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span><span style=\"font-weight: bold\">)</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Parameter</span><span style=\"font-weight: bold\">(</span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">''</span>, <span style=\"color: #808000; text-decoration-color: #808000\">name</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'content'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">parameter_type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'string'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">required</span>=<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>, <span style=\"color: #808000; text-decoration-color: #808000\">default</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span><span style=\"font-weight: bold\">)</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"font-weight: bold\">]</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'model-context-protocol'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_resource_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'write_file'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">tool_host</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'model_context_protocol'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">toolgroup_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'mcp::filesystem'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'tool'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">metadata</span>=<span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'endpoint'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'http://localhost:8000/sse'</span><span style=\"font-weight: bold\">}</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">)</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Tool</span><span style=\"font-weight: bold\">(</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'Make line-based edits to a text file. Each edit replaces exact line sequences with new content. Returns a git-style diff showing the changes made. Only works within allowed directories.'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">identifier</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'edit_file'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">parameters</span>=<span style=\"font-weight: bold\">[</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Parameter</span><span style=\"font-weight: bold\">(</span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">''</span>, <span style=\"color: #808000; text-decoration-color: #808000\">name</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'path'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">parameter_type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'string'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">required</span>=<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>, <span style=\"color: #808000; text-decoration-color: #808000\">default</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span><span style=\"font-weight: bold\">)</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Parameter</span><span style=\"font-weight: bold\">(</span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">''</span>, <span style=\"color: #808000; text-decoration-color: #808000\">name</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'edits'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">parameter_type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'array'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">required</span>=<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>, <span style=\"color: #808000; text-decoration-color: #808000\">default</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span><span style=\"font-weight: bold\">)</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Parameter</span><span style=\"font-weight: bold\">(</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'Preview changes using git-style diff format'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">name</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'dryRun'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">parameter_type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'boolean'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">required</span>=<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">default</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"font-weight: bold\">)</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"font-weight: bold\">]</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'model-context-protocol'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_resource_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'edit_file'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">tool_host</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'model_context_protocol'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">toolgroup_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'mcp::filesystem'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'tool'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">metadata</span>=<span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'endpoint'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'http://localhost:8000/sse'</span><span style=\"font-weight: bold\">}</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">)</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Tool</span><span style=\"font-weight: bold\">(</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'Create a new directory or ensure a directory exists. Can create multiple nested directories in one operation. If the directory already exists, this operation will succeed silently. Perfect for setting up directory structures for projects or ensuring required paths exist. Only works within allowed directories.'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">identifier</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'create_directory'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">parameters</span>=<span style=\"font-weight: bold\">[</span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Parameter</span><span style=\"font-weight: bold\">(</span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">''</span>, <span style=\"color: #808000; text-decoration-color: #808000\">name</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'path'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">parameter_type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'string'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">required</span>=<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>, <span style=\"color: #808000; text-decoration-color: #808000\">default</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span><span style=\"font-weight: bold\">)]</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'model-context-protocol'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_resource_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'create_directory'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">tool_host</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'model_context_protocol'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">toolgroup_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'mcp::filesystem'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'tool'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">metadata</span>=<span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'endpoint'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'http://localhost:8000/sse'</span><span style=\"font-weight: bold\">}</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">)</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Tool</span><span style=\"font-weight: bold\">(</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'Get a detailed listing of all files and directories in a specified path. Results clearly distinguish between files and directories with [FILE] and [DIR] prefixes. This tool is essential for understanding directory structure and finding specific files within a directory. Only works within allowed directories.'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">identifier</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'list_directory'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">parameters</span>=<span style=\"font-weight: bold\">[</span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Parameter</span><span style=\"font-weight: bold\">(</span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">''</span>, <span style=\"color: #808000; text-decoration-color: #808000\">name</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'path'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">parameter_type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'string'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">required</span>=<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>, <span style=\"color: #808000; text-decoration-color: #808000\">default</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span><span style=\"font-weight: bold\">)]</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'model-context-protocol'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_resource_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'list_directory'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">tool_host</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'model_context_protocol'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">toolgroup_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'mcp::filesystem'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'tool'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">metadata</span>=<span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'endpoint'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'http://localhost:8000/sse'</span><span style=\"font-weight: bold\">}</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">)</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Tool</span><span style=\"font-weight: bold\">(</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">\"Get a recursive tree view of files and directories as a JSON structure. Each entry includes 'name', 'type' (file/directory), and 'children' for directories. Files have no children array, while directories always have a children array (which may be empty). The output is formatted with 2-space indentation for readability. Only works within allowed directories.\"</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">identifier</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'directory_tree'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">parameters</span>=<span style=\"font-weight: bold\">[</span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Parameter</span><span style=\"font-weight: bold\">(</span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">''</span>, <span style=\"color: #808000; text-decoration-color: #808000\">name</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'path'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">parameter_type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'string'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">required</span>=<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>, <span style=\"color: #808000; text-decoration-color: #808000\">default</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span><span style=\"font-weight: bold\">)]</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'model-context-protocol'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_resource_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'directory_tree'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">tool_host</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'model_context_protocol'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">toolgroup_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'mcp::filesystem'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'tool'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">metadata</span>=<span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'endpoint'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'http://localhost:8000/sse'</span><span style=\"font-weight: bold\">}</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">)</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Tool</span><span style=\"font-weight: bold\">(</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'Move or rename files and directories. Can move files between directories and rename them in a single operation. If the destination exists, the operation will fail. Works across different directories and can be used for simple renaming within the same directory. Both source and destination must be within allowed directories.'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">identifier</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'move_file'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">parameters</span>=<span style=\"font-weight: bold\">[</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Parameter</span><span style=\"font-weight: bold\">(</span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">''</span>, <span style=\"color: #808000; text-decoration-color: #808000\">name</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'source'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">parameter_type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'string'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">required</span>=<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>, <span style=\"color: #808000; text-decoration-color: #808000\">default</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span><span style=\"font-weight: bold\">)</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Parameter</span><span style=\"font-weight: bold\">(</span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">''</span>, <span style=\"color: #808000; text-decoration-color: #808000\">name</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'destination'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">parameter_type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'string'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">required</span>=<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>, <span style=\"color: #808000; text-decoration-color: #808000\">default</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span><span style=\"font-weight: bold\">)</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"font-weight: bold\">]</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'model-context-protocol'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_resource_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'move_file'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">tool_host</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'model_context_protocol'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">toolgroup_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'mcp::filesystem'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'tool'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">metadata</span>=<span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'endpoint'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'http://localhost:8000/sse'</span><span style=\"font-weight: bold\">}</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">)</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Tool</span><span style=\"font-weight: bold\">(</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">\"Recursively search for files and directories matching a pattern. Searches through all subdirectories from the starting path. The search is case-insensitive and matches partial names. Returns full paths to all matching items. Great for finding files when you don't know their exact location. Only searches within allowed directories.\"</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">identifier</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'search_files'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">parameters</span>=<span style=\"font-weight: bold\">[</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Parameter</span><span style=\"font-weight: bold\">(</span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">''</span>, <span style=\"color: #808000; text-decoration-color: #808000\">name</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'path'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">parameter_type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'string'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">required</span>=<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>, <span style=\"color: #808000; text-decoration-color: #808000\">default</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span><span style=\"font-weight: bold\">)</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Parameter</span><span style=\"font-weight: bold\">(</span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">''</span>, <span style=\"color: #808000; text-decoration-color: #808000\">name</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'pattern'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">parameter_type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'string'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">required</span>=<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>, <span style=\"color: #808000; text-decoration-color: #808000\">default</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span><span style=\"font-weight: bold\">)</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Parameter</span><span style=\"font-weight: bold\">(</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">''</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">name</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'excludePatterns'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">parameter_type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'array'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">required</span>=<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">default</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"font-weight: bold\">)</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"font-weight: bold\">]</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'model-context-protocol'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_resource_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'search_files'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">tool_host</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'model_context_protocol'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">toolgroup_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'mcp::filesystem'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'tool'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">metadata</span>=<span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'endpoint'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'http://localhost:8000/sse'</span><span style=\"font-weight: bold\">}</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">)</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Tool</span><span style=\"font-weight: bold\">(</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'Retrieve detailed metadata about a file or directory. Returns comprehensive information including size, creation time, last modified time, permissions, and type. This tool is perfect for understanding file characteristics without reading the actual content. Only works within allowed directories.'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">identifier</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'get_file_info'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">parameters</span>=<span style=\"font-weight: bold\">[</span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Parameter</span><span style=\"font-weight: bold\">(</span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">''</span>, <span style=\"color: #808000; text-decoration-color: #808000\">name</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'path'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">parameter_type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'string'</span>, <span style=\"color: #808000; text-decoration-color: #808000\">required</span>=<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-style: italic\">True</span>, <span style=\"color: #808000; text-decoration-color: #808000\">default</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span><span style=\"font-weight: bold\">)]</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'model-context-protocol'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_resource_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'get_file_info'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">tool_host</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'model_context_protocol'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">toolgroup_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'mcp::filesystem'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'tool'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">metadata</span>=<span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'endpoint'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'http://localhost:8000/sse'</span><span style=\"font-weight: bold\">}</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">)</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">Tool</span><span style=\"font-weight: bold\">(</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">description</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'Returns the list of directories that this server is allowed to access. Use this to understand which directories are available before trying to access files.'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">identifier</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'list_allowed_directories'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">parameters</span>=<span style=\"font-weight: bold\">[]</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'model-context-protocol'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_resource_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'list_allowed_directories'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">tool_host</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'model_context_protocol'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">toolgroup_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'mcp::filesystem'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'tool'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">metadata</span>=<span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'endpoint'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'http://localhost:8000/sse'</span><span style=\"font-weight: bold\">}</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">)</span>\n",
+              "<span style=\"font-weight: bold\">]</span>\n",
+              "</pre>\n"
+            ],
+            "text/plain": [
+              "\u001b[1m[\u001b[0m\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1;35mTool\u001b[0m\u001b[1m(\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m'Read the complete contents of a file from the file system. Handles various text encodings and provides detailed error messages if the file cannot be read. Use this tool when you need to examine the contents of a single file. Only works within allowed directories.'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33midentifier\u001b[0m=\u001b[32m'read_file'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mparameters\u001b[0m=\u001b[1m[\u001b[0m\u001b[1;35mParameter\u001b[0m\u001b[1m(\u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m''\u001b[0m, \u001b[33mname\u001b[0m=\u001b[32m'path'\u001b[0m, \u001b[33mparameter_type\u001b[0m=\u001b[32m'string'\u001b[0m, \u001b[33mrequired\u001b[0m=\u001b[3;92mTrue\u001b[0m, \u001b[33mdefault\u001b[0m=\u001b[3;35mNone\u001b[0m\u001b[1m)\u001b[0m\u001b[1m]\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mprovider_id\u001b[0m=\u001b[32m'model-context-protocol'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mprovider_resource_id\u001b[0m=\u001b[32m'read_file'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtool_host\u001b[0m=\u001b[32m'model_context_protocol'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtoolgroup_id\u001b[0m=\u001b[32m'mcp::filesystem'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'tool'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mmetadata\u001b[0m=\u001b[1m{\u001b[0m\u001b[32m'endpoint'\u001b[0m: \u001b[32m'http://localhost:8000/sse'\u001b[0m\u001b[1m}\u001b[0m\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1m)\u001b[0m,\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1;35mTool\u001b[0m\u001b[1m(\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m\"Read\u001b[0m\u001b[32m the contents of multiple files simultaneously. This is more efficient than reading files one by one when you need to analyze or compare multiple files. Each file's content is returned with its path as a reference. Failed reads for individual files won't stop the entire operation. Only works within allowed directories.\"\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33midentifier\u001b[0m=\u001b[32m'read_multiple_files'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mparameters\u001b[0m=\u001b[1m[\u001b[0m\u001b[1;35mParameter\u001b[0m\u001b[1m(\u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m''\u001b[0m, \u001b[33mname\u001b[0m=\u001b[32m'paths'\u001b[0m, \u001b[33mparameter_type\u001b[0m=\u001b[32m'array'\u001b[0m, \u001b[33mrequired\u001b[0m=\u001b[3;92mTrue\u001b[0m, \u001b[33mdefault\u001b[0m=\u001b[3;35mNone\u001b[0m\u001b[1m)\u001b[0m\u001b[1m]\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mprovider_id\u001b[0m=\u001b[32m'model-context-protocol'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mprovider_resource_id\u001b[0m=\u001b[32m'read_multiple_files'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtool_host\u001b[0m=\u001b[32m'model_context_protocol'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtoolgroup_id\u001b[0m=\u001b[32m'mcp::filesystem'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'tool'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mmetadata\u001b[0m=\u001b[1m{\u001b[0m\u001b[32m'endpoint'\u001b[0m: \u001b[32m'http://localhost:8000/sse'\u001b[0m\u001b[1m}\u001b[0m\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1m)\u001b[0m,\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1;35mTool\u001b[0m\u001b[1m(\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m'Create a new file or completely overwrite an existing file with new content. Use with caution as it will overwrite existing files without warning. Handles text content with proper encoding. Only works within allowed directories.'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33midentifier\u001b[0m=\u001b[32m'write_file'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mparameters\u001b[0m=\u001b[1m[\u001b[0m\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[1;35mParameter\u001b[0m\u001b[1m(\u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m''\u001b[0m, \u001b[33mname\u001b[0m=\u001b[32m'path'\u001b[0m, \u001b[33mparameter_type\u001b[0m=\u001b[32m'string'\u001b[0m, \u001b[33mrequired\u001b[0m=\u001b[3;92mTrue\u001b[0m, \u001b[33mdefault\u001b[0m=\u001b[3;35mNone\u001b[0m\u001b[1m)\u001b[0m,\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[1;35mParameter\u001b[0m\u001b[1m(\u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m''\u001b[0m, \u001b[33mname\u001b[0m=\u001b[32m'content'\u001b[0m, \u001b[33mparameter_type\u001b[0m=\u001b[32m'string'\u001b[0m, \u001b[33mrequired\u001b[0m=\u001b[3;92mTrue\u001b[0m, \u001b[33mdefault\u001b[0m=\u001b[3;35mNone\u001b[0m\u001b[1m)\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[1m]\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mprovider_id\u001b[0m=\u001b[32m'model-context-protocol'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mprovider_resource_id\u001b[0m=\u001b[32m'write_file'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtool_host\u001b[0m=\u001b[32m'model_context_protocol'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtoolgroup_id\u001b[0m=\u001b[32m'mcp::filesystem'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'tool'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mmetadata\u001b[0m=\u001b[1m{\u001b[0m\u001b[32m'endpoint'\u001b[0m: \u001b[32m'http://localhost:8000/sse'\u001b[0m\u001b[1m}\u001b[0m\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1m)\u001b[0m,\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1;35mTool\u001b[0m\u001b[1m(\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m'Make line-based edits to a text file. Each edit replaces exact line sequences with new content. Returns a git-style diff showing the changes made. Only works within allowed directories.'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33midentifier\u001b[0m=\u001b[32m'edit_file'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mparameters\u001b[0m=\u001b[1m[\u001b[0m\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[1;35mParameter\u001b[0m\u001b[1m(\u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m''\u001b[0m, \u001b[33mname\u001b[0m=\u001b[32m'path'\u001b[0m, \u001b[33mparameter_type\u001b[0m=\u001b[32m'string'\u001b[0m, \u001b[33mrequired\u001b[0m=\u001b[3;92mTrue\u001b[0m, \u001b[33mdefault\u001b[0m=\u001b[3;35mNone\u001b[0m\u001b[1m)\u001b[0m,\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[1;35mParameter\u001b[0m\u001b[1m(\u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m''\u001b[0m, \u001b[33mname\u001b[0m=\u001b[32m'edits'\u001b[0m, \u001b[33mparameter_type\u001b[0m=\u001b[32m'array'\u001b[0m, \u001b[33mrequired\u001b[0m=\u001b[3;92mTrue\u001b[0m, \u001b[33mdefault\u001b[0m=\u001b[3;35mNone\u001b[0m\u001b[1m)\u001b[0m,\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[1;35mParameter\u001b[0m\u001b[1m(\u001b[0m\n",
+              "\u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m'Preview changes using git-style diff format'\u001b[0m,\n",
+              "\u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mname\u001b[0m=\u001b[32m'dryRun'\u001b[0m,\n",
+              "\u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mparameter_type\u001b[0m=\u001b[32m'boolean'\u001b[0m,\n",
+              "\u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mrequired\u001b[0m=\u001b[3;92mTrue\u001b[0m,\n",
+              "\u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mdefault\u001b[0m=\u001b[3;35mNone\u001b[0m\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[1m)\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[1m]\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mprovider_id\u001b[0m=\u001b[32m'model-context-protocol'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mprovider_resource_id\u001b[0m=\u001b[32m'edit_file'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtool_host\u001b[0m=\u001b[32m'model_context_protocol'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtoolgroup_id\u001b[0m=\u001b[32m'mcp::filesystem'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'tool'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mmetadata\u001b[0m=\u001b[1m{\u001b[0m\u001b[32m'endpoint'\u001b[0m: \u001b[32m'http://localhost:8000/sse'\u001b[0m\u001b[1m}\u001b[0m\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1m)\u001b[0m,\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1;35mTool\u001b[0m\u001b[1m(\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m'Create a new directory or ensure a directory exists. Can create multiple nested directories in one operation. If the directory already exists, this operation will succeed silently. Perfect for setting up directory structures for projects or ensuring required paths exist. Only works within allowed directories.'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33midentifier\u001b[0m=\u001b[32m'create_directory'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mparameters\u001b[0m=\u001b[1m[\u001b[0m\u001b[1;35mParameter\u001b[0m\u001b[1m(\u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m''\u001b[0m, \u001b[33mname\u001b[0m=\u001b[32m'path'\u001b[0m, \u001b[33mparameter_type\u001b[0m=\u001b[32m'string'\u001b[0m, \u001b[33mrequired\u001b[0m=\u001b[3;92mTrue\u001b[0m, \u001b[33mdefault\u001b[0m=\u001b[3;35mNone\u001b[0m\u001b[1m)\u001b[0m\u001b[1m]\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mprovider_id\u001b[0m=\u001b[32m'model-context-protocol'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mprovider_resource_id\u001b[0m=\u001b[32m'create_directory'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtool_host\u001b[0m=\u001b[32m'model_context_protocol'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtoolgroup_id\u001b[0m=\u001b[32m'mcp::filesystem'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'tool'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mmetadata\u001b[0m=\u001b[1m{\u001b[0m\u001b[32m'endpoint'\u001b[0m: \u001b[32m'http://localhost:8000/sse'\u001b[0m\u001b[1m}\u001b[0m\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1m)\u001b[0m,\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1;35mTool\u001b[0m\u001b[1m(\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m'Get a detailed listing of all files and directories in a specified path. Results clearly distinguish between files and directories with \u001b[0m\u001b[32m[\u001b[0m\u001b[32mFILE\u001b[0m\u001b[32m]\u001b[0m\u001b[32m and \u001b[0m\u001b[32m[\u001b[0m\u001b[32mDIR\u001b[0m\u001b[32m]\u001b[0m\u001b[32m prefixes. This tool is essential for understanding directory structure and finding specific files within a directory. Only works within allowed directories.'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33midentifier\u001b[0m=\u001b[32m'list_directory'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mparameters\u001b[0m=\u001b[1m[\u001b[0m\u001b[1;35mParameter\u001b[0m\u001b[1m(\u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m''\u001b[0m, \u001b[33mname\u001b[0m=\u001b[32m'path'\u001b[0m, \u001b[33mparameter_type\u001b[0m=\u001b[32m'string'\u001b[0m, \u001b[33mrequired\u001b[0m=\u001b[3;92mTrue\u001b[0m, \u001b[33mdefault\u001b[0m=\u001b[3;35mNone\u001b[0m\u001b[1m)\u001b[0m\u001b[1m]\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mprovider_id\u001b[0m=\u001b[32m'model-context-protocol'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mprovider_resource_id\u001b[0m=\u001b[32m'list_directory'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtool_host\u001b[0m=\u001b[32m'model_context_protocol'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtoolgroup_id\u001b[0m=\u001b[32m'mcp::filesystem'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'tool'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mmetadata\u001b[0m=\u001b[1m{\u001b[0m\u001b[32m'endpoint'\u001b[0m: \u001b[32m'http://localhost:8000/sse'\u001b[0m\u001b[1m}\u001b[0m\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1m)\u001b[0m,\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1;35mTool\u001b[0m\u001b[1m(\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m\"Get\u001b[0m\u001b[32m a recursive tree view of files and directories as a JSON structure. Each entry includes 'name', 'type' \u001b[0m\u001b[32m(\u001b[0m\u001b[32mfile/directory\u001b[0m\u001b[32m)\u001b[0m\u001b[32m, and 'children' for directories. Files have no children array, while directories always have a children array \u001b[0m\u001b[32m(\u001b[0m\u001b[32mwhich may be empty\u001b[0m\u001b[32m)\u001b[0m\u001b[32m. The output is formatted with 2-space indentation for readability. Only works within allowed directories.\"\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33midentifier\u001b[0m=\u001b[32m'directory_tree'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mparameters\u001b[0m=\u001b[1m[\u001b[0m\u001b[1;35mParameter\u001b[0m\u001b[1m(\u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m''\u001b[0m, \u001b[33mname\u001b[0m=\u001b[32m'path'\u001b[0m, \u001b[33mparameter_type\u001b[0m=\u001b[32m'string'\u001b[0m, \u001b[33mrequired\u001b[0m=\u001b[3;92mTrue\u001b[0m, \u001b[33mdefault\u001b[0m=\u001b[3;35mNone\u001b[0m\u001b[1m)\u001b[0m\u001b[1m]\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mprovider_id\u001b[0m=\u001b[32m'model-context-protocol'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mprovider_resource_id\u001b[0m=\u001b[32m'directory_tree'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtool_host\u001b[0m=\u001b[32m'model_context_protocol'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtoolgroup_id\u001b[0m=\u001b[32m'mcp::filesystem'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'tool'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mmetadata\u001b[0m=\u001b[1m{\u001b[0m\u001b[32m'endpoint'\u001b[0m: \u001b[32m'http://localhost:8000/sse'\u001b[0m\u001b[1m}\u001b[0m\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1m)\u001b[0m,\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1;35mTool\u001b[0m\u001b[1m(\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m'Move or rename files and directories. Can move files between directories and rename them in a single operation. If the destination exists, the operation will fail. Works across different directories and can be used for simple renaming within the same directory. Both source and destination must be within allowed directories.'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33midentifier\u001b[0m=\u001b[32m'move_file'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mparameters\u001b[0m=\u001b[1m[\u001b[0m\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[1;35mParameter\u001b[0m\u001b[1m(\u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m''\u001b[0m, \u001b[33mname\u001b[0m=\u001b[32m'source'\u001b[0m, \u001b[33mparameter_type\u001b[0m=\u001b[32m'string'\u001b[0m, \u001b[33mrequired\u001b[0m=\u001b[3;92mTrue\u001b[0m, \u001b[33mdefault\u001b[0m=\u001b[3;35mNone\u001b[0m\u001b[1m)\u001b[0m,\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[1;35mParameter\u001b[0m\u001b[1m(\u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m''\u001b[0m, \u001b[33mname\u001b[0m=\u001b[32m'destination'\u001b[0m, \u001b[33mparameter_type\u001b[0m=\u001b[32m'string'\u001b[0m, \u001b[33mrequired\u001b[0m=\u001b[3;92mTrue\u001b[0m, \u001b[33mdefault\u001b[0m=\u001b[3;35mNone\u001b[0m\u001b[1m)\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[1m]\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mprovider_id\u001b[0m=\u001b[32m'model-context-protocol'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mprovider_resource_id\u001b[0m=\u001b[32m'move_file'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtool_host\u001b[0m=\u001b[32m'model_context_protocol'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtoolgroup_id\u001b[0m=\u001b[32m'mcp::filesystem'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'tool'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mmetadata\u001b[0m=\u001b[1m{\u001b[0m\u001b[32m'endpoint'\u001b[0m: \u001b[32m'http://localhost:8000/sse'\u001b[0m\u001b[1m}\u001b[0m\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1m)\u001b[0m,\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1;35mTool\u001b[0m\u001b[1m(\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m\"Recursively\u001b[0m\u001b[32m search for files and directories matching a pattern. Searches through all subdirectories from the starting path. The search is case-insensitive and matches partial names. Returns full paths to all matching items. Great for finding files when you don't know their exact location. Only searches within allowed directories.\"\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33midentifier\u001b[0m=\u001b[32m'search_files'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mparameters\u001b[0m=\u001b[1m[\u001b[0m\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[1;35mParameter\u001b[0m\u001b[1m(\u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m''\u001b[0m, \u001b[33mname\u001b[0m=\u001b[32m'path'\u001b[0m, \u001b[33mparameter_type\u001b[0m=\u001b[32m'string'\u001b[0m, \u001b[33mrequired\u001b[0m=\u001b[3;92mTrue\u001b[0m, \u001b[33mdefault\u001b[0m=\u001b[3;35mNone\u001b[0m\u001b[1m)\u001b[0m,\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[1;35mParameter\u001b[0m\u001b[1m(\u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m''\u001b[0m, \u001b[33mname\u001b[0m=\u001b[32m'pattern'\u001b[0m, \u001b[33mparameter_type\u001b[0m=\u001b[32m'string'\u001b[0m, \u001b[33mrequired\u001b[0m=\u001b[3;92mTrue\u001b[0m, \u001b[33mdefault\u001b[0m=\u001b[3;35mNone\u001b[0m\u001b[1m)\u001b[0m,\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[1;35mParameter\u001b[0m\u001b[1m(\u001b[0m\n",
+              "\u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m''\u001b[0m,\n",
+              "\u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mname\u001b[0m=\u001b[32m'excludePatterns'\u001b[0m,\n",
+              "\u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mparameter_type\u001b[0m=\u001b[32m'array'\u001b[0m,\n",
+              "\u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mrequired\u001b[0m=\u001b[3;92mTrue\u001b[0m,\n",
+              "\u001b[2;32m│   │   │   │   \u001b[0m\u001b[33mdefault\u001b[0m=\u001b[3;35mNone\u001b[0m\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[1m)\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[1m]\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mprovider_id\u001b[0m=\u001b[32m'model-context-protocol'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mprovider_resource_id\u001b[0m=\u001b[32m'search_files'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtool_host\u001b[0m=\u001b[32m'model_context_protocol'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtoolgroup_id\u001b[0m=\u001b[32m'mcp::filesystem'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'tool'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mmetadata\u001b[0m=\u001b[1m{\u001b[0m\u001b[32m'endpoint'\u001b[0m: \u001b[32m'http://localhost:8000/sse'\u001b[0m\u001b[1m}\u001b[0m\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1m)\u001b[0m,\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1;35mTool\u001b[0m\u001b[1m(\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m'Retrieve detailed metadata about a file or directory. Returns comprehensive information including size, creation time, last modified time, permissions, and type. This tool is perfect for understanding file characteristics without reading the actual content. Only works within allowed directories.'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33midentifier\u001b[0m=\u001b[32m'get_file_info'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mparameters\u001b[0m=\u001b[1m[\u001b[0m\u001b[1;35mParameter\u001b[0m\u001b[1m(\u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m''\u001b[0m, \u001b[33mname\u001b[0m=\u001b[32m'path'\u001b[0m, \u001b[33mparameter_type\u001b[0m=\u001b[32m'string'\u001b[0m, \u001b[33mrequired\u001b[0m=\u001b[3;92mTrue\u001b[0m, \u001b[33mdefault\u001b[0m=\u001b[3;35mNone\u001b[0m\u001b[1m)\u001b[0m\u001b[1m]\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mprovider_id\u001b[0m=\u001b[32m'model-context-protocol'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mprovider_resource_id\u001b[0m=\u001b[32m'get_file_info'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtool_host\u001b[0m=\u001b[32m'model_context_protocol'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtoolgroup_id\u001b[0m=\u001b[32m'mcp::filesystem'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'tool'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mmetadata\u001b[0m=\u001b[1m{\u001b[0m\u001b[32m'endpoint'\u001b[0m: \u001b[32m'http://localhost:8000/sse'\u001b[0m\u001b[1m}\u001b[0m\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1m)\u001b[0m,\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1;35mTool\u001b[0m\u001b[1m(\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mdescription\u001b[0m=\u001b[32m'Returns the list of directories that this server is allowed to access. Use this to understand which directories are available before trying to access files.'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33midentifier\u001b[0m=\u001b[32m'list_allowed_directories'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mparameters\u001b[0m=\u001b[1m[\u001b[0m\u001b[1m]\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mprovider_id\u001b[0m=\u001b[32m'model-context-protocol'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mprovider_resource_id\u001b[0m=\u001b[32m'list_allowed_directories'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtool_host\u001b[0m=\u001b[32m'model_context_protocol'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtoolgroup_id\u001b[0m=\u001b[32m'mcp::filesystem'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'tool'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[33mmetadata\u001b[0m=\u001b[1m{\u001b[0m\u001b[32m'endpoint'\u001b[0m: \u001b[32m'http://localhost:8000/sse'\u001b[0m\u001b[1m}\u001b[0m\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1m)\u001b[0m\n",
+              "\u001b[1m]\u001b[0m\n"
+            ]
+          },
+          "metadata": {},
+          "output_type": "display_data"
+        }
+      ],
+      "source": [
+        "pprint(client.tools.list(toolgroup_id=\"mcp::filesystem\"))"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 12,
+      "id": "vttLbj_YO01f",
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "vttLbj_YO01f",
+        "outputId": "04bc486c-3a61-49c6-d0d2-4a211d6de0b5"
+      },
+      "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "User> Hello\n",
+            "inference> None of the provided functions can be used to respond to a greeting.\n",
+            "User> list all the files /content\n",
+            "inference> {\"type\": \"function\", \"name\": \"list_directory\", \"parameters\": {\"path\": \"/content\"}}\n",
+            "tool_execution> Tool:list_directory Args:{'path': '/content'}\n",
+            "tool_execution> Tool:list_directory Response:{\"type\":\"text\",\"text\":\"[DIR] .config\\n[FILE] bar\\n[FILE] foo\\n[DIR] sample_data\"}\n",
+            "inference> {\"type\": \"function\", \"name\": \"list_directory\", \"parameters\": {\"path\": \"/content\"}}\n",
+            "tool_execution> Tool:list_directory Args:{'path': '/content'}\n",
+            "tool_execution> Tool:list_directory Response:{\"type\":\"text\",\"text\":\"[DIR] .config\\n[FILE] bar\\n[FILE] foo\\n[DIR] sample_data\"}\n",
+            "inference> The list of files in the /content directory is:\n",
+            "\n",
+            "[DIR] .config\n",
+            "[FILE] bar\n",
+            "[FILE] foo\n",
+            "[DIR] sample_data\n"
+          ]
+        }
+      ],
+      "source": [
+        "from llama_stack_client.lib.agents.agent import Agent\n",
+        "from llama_stack_client.lib.agents.event_logger import EventLogger\n",
+        "from llama_stack_client.types.agent_create_params import AgentConfig\n",
+        "from termcolor import cprint\n",
+        "\n",
+        "agent_config = AgentConfig(\n",
+        "    model=model_id,\n",
+        "    instructions=\"You are a helpful assistant\",\n",
+        "    toolgroups=[\"mcp::filesystem\"],\n",
+        "    input_shields=[],\n",
+        "    output_shields=[],\n",
+        "    enable_session_persistence=False,\n",
+        ")\n",
+        "agent = Agent(client, agent_config)\n",
+        "user_prompts = [\n",
+        "    \"Hello\",\n",
+        "    \"list all the files /content\",\n",
+        "]\n",
+        "\n",
+        "session_id = agent.create_session(\"test-session\")\n",
+        "for prompt in user_prompts:\n",
+        "    cprint(f\"User> {prompt}\", \"green\")\n",
+        "    response = agent.create_turn(\n",
+        "        messages=[\n",
+        "            {\n",
+        "                \"role\": \"user\",\n",
+        "                \"content\": prompt,\n",
+        "            }\n",
+        "        ],\n",
+        "        session_id=session_id,\n",
+        "    )\n",
+        "    for log in EventLogger().log(response):\n",
+        "        log.print()\n"
       ]
     },
     {
@@ -1919,166 +3228,6 @@
         "- In this example, we will show how to build an Agent with Llama Stack, and query the agent's traces into an online dataset that can be used for evaluation.  "
       ]
     },
-    {
-      "cell_type": "markdown",
-      "id": "_JueJAKyJR5m",
-      "metadata": {
-        "id": "_JueJAKyJR5m"
-      },
-      "source": [
-        "##### 🚧 Patches 🚧\n",
-        "- The following cells are temporary patches to get `telemetry` working."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "id": "klPkK1t7CzIY",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "collapsed": true,
-        "id": "klPkK1t7CzIY",
-        "outputId": "ab0c1490-7fa6-446c-8e35-7b42f57e8a04"
-      },
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "Found existing installation: llama_stack 0.0.61\n",
-            "Uninstalling llama_stack-0.0.61:\n",
-            "  Would remove:\n",
-            "    /usr/local/bin/install-wheel-from-presigned\n",
-            "    /usr/local/bin/llama\n",
-            "    /usr/local/lib/python3.10/dist-packages/llama_stack-0.0.61.dist-info/*\n",
-            "    /usr/local/lib/python3.10/dist-packages/llama_stack/*\n",
-            "Proceed (Y/n)? Y\n",
-            "  Successfully uninstalled llama_stack-0.0.61\n",
-            "Collecting git+https://github.com/meta-llama/llama-stack.git@main\n",
-            "  Cloning https://github.com/meta-llama/llama-stack.git (to revision main) to /tmp/pip-req-build-oryyzdm1\n",
-            "  Running command git clone --filter=blob:none --quiet https://github.com/meta-llama/llama-stack.git /tmp/pip-req-build-oryyzdm1\n",
-            "  Resolved https://github.com/meta-llama/llama-stack.git to commit 53b3a1e345c46d7d37c1af3d675092a4cbfe85f9\n",
-            "  Running command git submodule update --init --recursive -q\n",
-            "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
-            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
-            "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
-            "Requirement already satisfied: blobfile in /usr/local/lib/python3.10/dist-packages (from llama_stack==0.0.61) (3.0.0)\n",
-            "Requirement already satisfied: fire in /usr/local/lib/python3.10/dist-packages (from llama_stack==0.0.61) (0.7.0)\n",
-            "Requirement already satisfied: httpx in /usr/local/lib/python3.10/dist-packages (from llama_stack==0.0.61) (0.28.1)\n",
-            "Requirement already satisfied: huggingface-hub in /usr/local/lib/python3.10/dist-packages (from llama_stack==0.0.61) (0.26.5)\n",
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-            "Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub->llama_stack==0.0.61) (24.2)\n",
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-            "Requirement already satisfied: pygments<3.0.0,>=2.13.0 in /usr/local/lib/python3.10/dist-packages (from rich->llama_stack==0.0.61) (2.18.0)\n",
-            "Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.5.0->llama-stack-client>=0.0.61->llama_stack==0.0.61) (1.2.2)\n",
-            "Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.10/dist-packages (from markdown-it-py>=2.2.0->rich->llama_stack==0.0.61) (0.1.2)\n",
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-            "Requirement already satisfied: numpy>=1.22.4 in /usr/local/lib/python3.10/dist-packages (from pandas->llama-stack-client>=0.0.61->llama_stack==0.0.61) (1.26.4)\n",
-            "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas->llama-stack-client>=0.0.61->llama_stack==0.0.61) (2.8.2)\n",
-            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->llama-stack-client>=0.0.61->llama_stack==0.0.61) (2024.2)\n",
-            "Requirement already satisfied: tzdata>=2022.7 in /usr/local/lib/python3.10/dist-packages (from pandas->llama-stack-client>=0.0.61->llama_stack==0.0.61) (2024.2)\n",
-            "Requirement already satisfied: regex>=2022.1.18 in /usr/local/lib/python3.10/dist-packages (from tiktoken->llama-models>=0.0.61->llama_stack==0.0.61) (2024.9.11)\n",
-            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.2->pandas->llama-stack-client>=0.0.61->llama_stack==0.0.61) (1.17.0)\n",
-            "Building wheels for collected packages: llama_stack\n",
-            "  Building wheel for llama_stack (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
-            "  Created wheel for llama_stack: filename=llama_stack-0.0.61-py3-none-any.whl size=464145 sha256=da71747aceef9aec43553f66c43095486d1a920e47bb0e47e2729a8e4328fff6\n",
-            "  Stored in directory: /tmp/pip-ephem-wheel-cache-jquw5j7f/wheels/74/e4/3b/079983408fa9323c1f2807e404ee78b468c74bec381eb70d4f\n",
-            "Successfully built llama_stack\n",
-            "Installing collected packages: llama_stack\n",
-            "Successfully installed llama_stack-0.0.61\n"
-          ]
-        },
-        {
-          "data": {
-            "application/vnd.colab-display-data+json": {
-              "id": "7701cb0c982f4250a46721fededf9647",
-              "pip_warning": {
-                "packages": [
-                  "llama_stack"
-                ]
-              }
-            }
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        }
-      ],
-      "source": [
-        "# need to install on latest main\n",
-        "!pip uninstall llama-stack\n",
-        "!pip install git+https://github.com/meta-llama/llama-stack.git@main"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "id": "9jJ75JlnETTH",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "9jJ75JlnETTH",
-        "outputId": "76bd3912-f814-428c-88e1-c1113af77856"
-      },
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "Removed handler StreamHandler from root logger\n"
-          ]
-        }
-      ],
-      "source": [
-        "# disable logging for clean server logs\n",
-        "import logging\n",
-        "\n",
-        "\n",
-        "def remove_root_handlers():\n",
-        "    root_logger = logging.getLogger()\n",
-        "    for handler in root_logger.handlers[:]:\n",
-        "        root_logger.removeHandler(handler)\n",
-        "        print(f\"Removed handler {handler.__class__.__name__} from root logger\")\n",
-        "\n",
-        "\n",
-        "remove_root_handlers()\n"
-      ]
-    },
     {
       "cell_type": "markdown",
       "id": "_t_tcWq0JcJ4",
@@ -2091,49 +3240,46 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 18,
       "id": "4iCO59kP20Zs",
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
         "id": "4iCO59kP20Zs",
-        "outputId": "f6179de6-054d-4452-a893-8d9b64c5a0d1"
+        "outputId": "894c6333-30e9-4f1e-9b63-1bfb1cae51e2"
       },
       "outputs": [
         {
           "name": "stdout",
           "output_type": "stream",
           "text": [
-            "inference> Let me check the latest sports news.\n",
-            "inference> bravy_search.call(query=\"Bill Cosby South Park episode\")\n",
-            "CustomTool> Unknown tool `bravy_search` was called.\n",
-            "inference> brave_search.call(query=\"Andrew Tate kickboxing name\")\n",
-            "tool_execution> Tool:brave_search Args:{'query': 'Andrew Tate kickboxing name'}\n",
-            "tool_execution> Tool:brave_search Response:{\"query\": \"Andrew Tate kickboxing name\", \"top_k\": [{\"title\": \"Andrew Tate kickboxing record: How many championships ... - FirstSportz\", \"url\": \"https://firstsportz.com/mma-how-many-championships-does-andrew-tate-have/\", \"content\": \"Andrew Tate's Kickboxing career. During his kickboxing career, he used the nickname \\\"King Cobra,\\\" which he currently uses as his Twitter name. Tate had an unorthodox style of movement inside the ring. He kept his hands down most of the time and relied on quick jabs and an overhand right to land significant strikes.\", \"score\": 0.9996244, \"raw_content\": null}, {\"title\": \"Andrew Tate: Kickboxing Record, Facts, Height, Weight, Age, Biography\", \"url\": \"https://www.lowkickmma.com/andrew-tate-kickboxing-record-facts-height-weight-age-biography/\", \"content\": \"Birth Name: Emory Andrew Tate III: Date of Birth: 1 December 1986: Place of Birth: Washington, D.C., U.S. ... In his professional kickboxing career, Andrew Tate won 32 of his fights by knockout.\", \"score\": 0.99909246, \"raw_content\": null}, {\"title\": \"Who is Andrew Tate? MMA, kickboxing record and controversies of fighter ...\", \"url\": \"https://www.sportingnews.com/us/kickboxing/news/andrew-tate-mma-kickboxing-record-controversies/u50waalc9cfz7krjg9wnyb7p\", \"content\": \"Andrew Tate kickboxing record After launching his career as a 20-year-old in 2007, Tate built a formidable kickboxing record that included 76 wins across 85 fights in more than 13 years in the ring.\", \"score\": 0.9976586, \"raw_content\": null}, {\"title\": \"About Andrew Tate: A Journey from Champion to Controversy\", \"url\": \"https://reachmorpheus.com/andrew-tate/\", \"content\": \"Andrew Tate's kickboxing career, beginning in 2005, is a tale of determination and skill. He quickly made a name for himself in the sport, rising through the ranks with his unique fighting style and strategic approach, honed by his chess-playing background.\", \"score\": 0.99701905, \"raw_content\": null}, {\"title\": \"Andrew Tate Bio, Wiki, Net Worth, Age, Family, MMA Career - Next Biography\", \"url\": \"https://www.nextbiography.com/andrew-tate/\", \"content\": \"Andrew Tate Age. Andrew Tate is 36 years old as of 2023, born on December 1, 1986, in Washington, DC. By his mid-thirties, Andrew Tate has become an esteemed figure in the world of kickboxing, showcasing remarkable expertise and experience in the sport. Early Life of Andrew Tate. Andrew Tate was born on 01 December 1986 to an African-American\", \"score\": 0.99368566, \"raw_content\": null}]}\n",
-            "shield_call> No Violation\n",
-            "inference> Andrew Tate's kickboxing name is \"King Cobra.\"\n"
+            "\u001b[30m\u001b[0m\u001b[33minference> \u001b[0m\u001b[36m\u001b[0m\u001b[36mbr\u001b[0m\u001b[36mave\u001b[0m\u001b[36m_search\u001b[0m\u001b[36m.call\u001b[0m\u001b[36m(query\u001b[0m\u001b[36m=\"\u001b[0m\u001b[36mN\u001b[0m\u001b[36mBA\u001b[0m\u001b[36m Western\u001b[0m\u001b[36m Conference\u001b[0m\u001b[36m Finals\u001b[0m\u001b[36m \u001b[0m\u001b[36m202\u001b[0m\u001b[36m4\u001b[0m\u001b[36m teams\u001b[0m\u001b[36m\")\u001b[0m\u001b[97m\u001b[0m\n",
+            "\u001b[32mtool_execution> Tool:brave_search Args:{'query': 'NBA Western Conference Finals 2024 teams'}\u001b[0m\n",
+            "\u001b[32mtool_execution> Tool:brave_search Response:{\"query\": \"NBA Western Conference Finals 2024 teams\", \"top_k\": [{\"title\": \"2024 NBA Western Conference Finals - Basketball-Reference.com\", \"url\": \"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\", \"content\": \"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown (20.8 / 5.4 / 5.0) 2024 Playoff Leaders: PTS: Luka Don\\u010di\\u0107 (635) TRB: Luka Don\\u010di\\u0107 (208) AST: Luka Don\\u010di\\u0107 (178) WS: Derrick White (2.9) More playoffs info\", \"score\": 0.9310187, \"raw_content\": null}, {\"title\": \"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\", \"url\": \"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\", \"content\": \"NBA Western Conference Finals 2024: Dates & Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\", \"score\": 0.8914433, \"raw_content\": null}, {\"title\": \"2024 Playoffs: West Finals | Timberwolves (3) vs. Mavericks (5) - NBA.com\", \"url\": \"https://www.nba.com/playoffs/2024/west-final\", \"content\": \"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\", \"score\": 0.8884594, \"raw_content\": null}, {\"title\": \"2024 NBA Western Conference playoff bracket - Basketnews.com\", \"url\": \"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\", \"content\": \"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\", \"score\": 0.8479807, \"raw_content\": null}, {\"title\": \"NBA Finals 2024 - Celtics-Mavericks news, schedule, scores and ... - ESPN\", \"url\": \"https://www.espn.com/nba/story/_/id/39943302/nba-playoffs-2024-conference-finals-news-scores-highlights\", \"content\": \"The Boston Celtics are the 2024 NBA Champions. ... Western Conference. Final 2023-24 NBA regular-season standings. Which team left standing has the most trips to the NBA Finals? Here is a look at\", \"score\": 0.81979275, \"raw_content\": null}]}\u001b[0m\n",
+            "\u001b[33minference> \u001b[0m\u001b[33mThe\u001b[0m\u001b[33m teams\u001b[0m\u001b[33m that\u001b[0m\u001b[33m played\u001b[0m\u001b[33m in\u001b[0m\u001b[33m the\u001b[0m\u001b[33m NBA\u001b[0m\u001b[33m Western\u001b[0m\u001b[33m Conference\u001b[0m\u001b[33m Finals\u001b[0m\u001b[33m of\u001b[0m\u001b[33m \u001b[0m\u001b[33m202\u001b[0m\u001b[33m4\u001b[0m\u001b[33m were\u001b[0m\u001b[33m the\u001b[0m\u001b[33m Dallas\u001b[0m\u001b[33m Mavericks\u001b[0m\u001b[33m and\u001b[0m\u001b[33m the\u001b[0m\u001b[33m Minnesota\u001b[0m\u001b[33m Timber\u001b[0m\u001b[33mw\u001b[0m\u001b[33molves\u001b[0m\u001b[33m.\u001b[0m\u001b[97m\u001b[0m\n",
+            "\u001b[30m\u001b[0m\u001b[30m\u001b[0m\u001b[33minference> \u001b[0m\u001b[36m\u001b[0m\u001b[36mbr\u001b[0m\u001b[36mave\u001b[0m\u001b[36m_search\u001b[0m\u001b[36m.call\u001b[0m\u001b[36m(query\u001b[0m\u001b[36m=\"\u001b[0m\u001b[36mBill\u001b[0m\u001b[36m Cosby\u001b[0m\u001b[36m South\u001b[0m\u001b[36m Park\u001b[0m\u001b[36m episode\u001b[0m\u001b[36m\")\u001b[0m\u001b[97m\u001b[0m\n",
+            "\u001b[32mtool_execution> Tool:brave_search Args:{'query': 'Bill Cosby South Park episode'}\u001b[0m\n",
+            "\u001b[32mtool_execution> Tool:brave_search Response:{\"query\": \"Bill Cosby South Park episode\", \"top_k\": [{\"title\": \"Bill Cosby and Taylor Swift Duet - South Park Studios\", \"url\": \"https://www.southparkstudios.com/video-clips/90r7i1/south-park-bill-cosby-and-taylor-swift-duet\", \"content\": \"01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:03 Bill Cosby and Taylor Swift Duet South ParkS18 E10 ------------------------------------------------------- The holiday special continues with Bill Cosby and Taylor Swift's rendition of \\\"It's Snowing Out There\\\". 01:31 #WeBelieveInYou South ParkS18 E10 -------------------------------------- With everyone watching, Kyle takes the opportunity to reach out to his brother. 01:47 Watch Your Microaggressions, Bro South ParkS19 E1 ------------------------------------------------------ Cartman's plan to frame PC Principal backfires. South ParkS19 E1 -------------------------------------- After hearing that the PC people have targeted Kyle, Cartman vows to help.\", \"score\": 0.685971, \"raw_content\": null}, {\"title\": \"Bill Cosby is Here to See You - South Park Studios US\", \"url\": \"https://southpark.cc.com/video-clips/wfot8s/south-park-bill-cosby-is-here-to-see-you\", \"content\": \"01:56 It's Not About Music South ParkS18 E9 ------------------------------------------ At home, Randy sees the consequences of Lorde's performance and calls the Record Producer to try and fix it. 01:24 Lorde's Hologram South ParkS18 E9 -------------------------------------- The Record Producer reveals the truth about the music industry... South ParkS18 E9 --------------------------------------------- Randy catches Sharon with Tupac's hologram. 01:37 I've Got Your Son, Lorde South ParkS18 E10 ----------------------------------------------- The Record Producer takes Stan and Kyle hostage. 01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:21 Lorde Is My Dad South ParkS18 E10 -------------------------------------- After trying to confront Cartman Bra, Stan finally reveals the truth about his dad.\", \"score\": 0.6643884, \"raw_content\": null}, {\"title\": \"Bill Cosby (android) | South Park Character ... - South Park Studios US\", \"url\": \"https://southpark.cc.com/wiki/Bill_Cosby_(android)\", \"content\": \"Bill Cosby (android) | South Park Character / Location / User talk etc | Official South Park Studios Wiki Sent back in time to destroy Eric Cartman's Dawson's Creek Trapper Keeper before it manifests into an omnipotent supercomputer that can destroy all humanity, \\\"Bill Cosby\\\" is really VSM471, an android or cyborg of some kind engineered by 'hoomans' in the distant future. He fails in his initial missions to infiltrate South Park Elementary's 4th Grade class, destroy the Trapper Keeper or Cartman himself, but with Stan Marsh and Kyle Broflovski's aid, he is able to succeed in preventing his dismal future, and painfully fades from existence. South Park and all related titles, logos and characters are trademarks of Comedy Partners.\", \"score\": 0.5052006, \"raw_content\": null}, {\"title\": \"\\\"South Park\\\" Clubhouses (TV Episode 1998) - IMDb\", \"url\": \"https://www.imdb.com/title/tt0705915/characters/nm0005295\", \"content\": \"\\\"South Park\\\" Clubhouses (TV Episode 1998) - Trey Parker as Stan Marsh, Eric Cartman, Phillip, Randy Marsh, Fat Abbot, Mr. Garrison, Mr. Mackey, 3rd Fat Abbot character, Roy, Teenage Boy #1, Clyde, Bill Cosby, Teenage Boy #2 - IMDb Awards & Events Trey Parker: Stan Marsh, Eric Cartman, Phillip, Randy Marsh, Fat Abbot, Mr. Garrison, Mr. Mackey, 3rd Fat Abbot character, Roy, Teenage Boy #1, Clyde, Bill Cosby, Teenage Boy #2 Mr. Garrison : Stan, are you paying attention? Stan : Yes, Mr. Garrison. Stan Marsh : Dare. Stan Marsh : What? Release Dates | Official Sites | Company Credits | Filming & Production | Technical Specs Photo & Video User Lists Related lists from IMDb users 2024 Watched TV Shows\", \"score\": 0.4604593, \"raw_content\": null}, {\"title\": \"Trapper Keeper (South Park) - Wikipedia\", \"url\": \"https://en.wikipedia.org/wiki/Trapper_Keeper_(South_Park)\", \"content\": \"\\\"Trapper Keeper\\\" is the twelfth episode of the fourth season of the animated television series South Park, and the 60th episode of the series overall. In the episode, a man from the future wants Cartman's new Trapper Keeper, while Mr. Garrison's kindergarten class holds an election for class president with confusing results. It is one of the many South Park episodes that parodies a current event.[1] The main plot of the episode involving the Trapper Keeper was written before the election,[1] but the subplot is a parody of the controversy surrounding the election's outcome.[2] \\\"Trapper Keeper\\\" did not originally feature the election storyline, only a subplot about Ike attending his first day of kindergarten.[3] \\\"Trapper Keeper\\\" Full episode at South Park Studios\", \"score\": 0.3839421, \"raw_content\": null}]}\u001b[0m\n",
+            "\u001b[33minference> \u001b[0m\u001b[33mBill\u001b[0m\u001b[33m Cosby\u001b[0m\u001b[33m (\u001b[0m\u001b[33mBS\u001b[0m\u001b[33mM\u001b[0m\u001b[33m-\u001b[0m\u001b[33m471\u001b[0m\u001b[33m)\u001b[0m\u001b[33m first\u001b[0m\u001b[33m appears\u001b[0m\u001b[33m in\u001b[0m\u001b[33m the\u001b[0m\u001b[33m episode\u001b[0m\u001b[33m \"\u001b[0m\u001b[33mTr\u001b[0m\u001b[33mapper\u001b[0m\u001b[33m Keeper\u001b[0m\u001b[33m\"\u001b[0m\u001b[33m (\u001b[0m\u001b[33mSeason\u001b[0m\u001b[33m \u001b[0m\u001b[33m4\u001b[0m\u001b[33m,\u001b[0m\u001b[33m Episode\u001b[0m\u001b[33m \u001b[0m\u001b[33m12\u001b[0m\u001b[33m)\u001b[0m\u001b[33m of\u001b[0m\u001b[33m South\u001b[0m\u001b[33m Park\u001b[0m\u001b[33m.\u001b[0m\u001b[97m\u001b[0m\n",
+            "\u001b[30m\u001b[0m\u001b[30m\u001b[0m\u001b[33minference> \u001b[0m\u001b[36m\u001b[0m\u001b[36mbr\u001b[0m\u001b[36mave\u001b[0m\u001b[36m_search\u001b[0m\u001b[36m.call\u001b[0m\u001b[36m(query\u001b[0m\u001b[36m=\"\u001b[0m\u001b[36mAndrew\u001b[0m\u001b[36m Tate\u001b[0m\u001b[36m kick\u001b[0m\u001b[36mboxing\u001b[0m\u001b[36m name\u001b[0m\u001b[36m\")\u001b[0m\u001b[97m\u001b[0m\n",
+            "\u001b[32mtool_execution> Tool:brave_search Args:{'query': 'Andrew Tate kickboxing name'}\u001b[0m\n",
+            "\u001b[32mtool_execution> Tool:brave_search Response:{\"query\": \"Andrew Tate kickboxing name\", \"top_k\": [{\"title\": \"Andrew Tate Age, Height, Weight, Family, Parents, Biography, Net Worth\", \"url\": \"https://biographywallah.com/andrew-tate-biography/\", \"content\": \"Andrew Tate Age, Height, Weight, Family, Parents, Biography, Net Worth \\u00bb Biography Wallah Andrew Tate Age, Height, Weight, Family, Parents, Biography, Net Worth Andrew Tate Biography NameAndrew TateReal nameEmory Andrew Tate IIIProfession \\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0\\u00a0Kickboxer, Commentator and BusinessmanDate of birth14 December 1986BirthplaceWashington D.C., United StatesAndrew Tate Age37 years old (as of 2024)NationalityBritish-AmericanZodiac SignSagittariusGenderMaleSchoolLocal School in Washington D.C., United StatesGirlfriend/SpouseNaghel GeorgianaSexual OrientationStraightNet worth$1000 Million Who is Andrew Tate? Andrew Tate is a British-American former professional kickboxing world champion businessman and media personality, who fought in the cruiserweight and super cruiserweight divisions. Andrew Tate Age Andrew Tate was born on 1 December 1986 and is 37 years old. Andrew Tate\\u2019s Net Worth What is the net worth of Andrew Tate? Where is Andrew Tate from? How old is Andrew Tate?\", \"score\": 0.80698997, \"raw_content\": null}, {\"title\": \"The Life Of Andrew Tate (By Andrew Tate Himself ... - Sidekick Boxing\", \"url\": \"https://sidekickboxing.co.uk/the-life-of-andrew-king-cobra-tate/\", \"content\": \"Andrew Tate is a British-American former professional kickboxing world champion who fought in the cruiserweight and super cruiserweight divisions. Andrew Tate\\u2019s Kickboxing Career Andrew Tate in the Big Brother house Andrew Tate\\u2019s Kickboxing World Titles and his Sidekick boxing gloves Andrew Tate After Kickboxing Andrew Tate and his brother Tristan moved to Romania to set up their empire of businesses including trading in Bitcoin, Hustlers University, CobraTate.com, The Real World, and The War Room. From being a 4x kickboxing world champion to becoming the world\\u2019s most Googled man in the world with a private jet and over 33 cars, Andrew Tate\\u2019s life has been full of adventure.\", \"score\": 0.78194773, \"raw_content\": null}, {\"title\": \"Andrew Tate (\\\"King Cobra\\\") | MMA Fighter Page - Tapology\", \"url\": \"https://www.tapology.com/fightcenter/fighters/72139-andrew-tate\", \"content\": \"Andrew Tate (\\\"King Cobra\\\") | MMA Fighter Page | Tapology Andrew \\\"King Cobra\\\" Tate Andrew Tate Name: Andrew Tate Height: 6'1\\\" (185cm) | Reach: Andrew Tate is ineligible for Tapology's regional MMA rankings due to inactivity. Fighters must have at least one completed MMA bout in the past two years to be ranked. Andrew Tate MMA Fight Record Former top-ranked UFC fighter has called out Andrew Tate for having a paper title when it comes to combat... Andrew Tate \\u2022 All the biggest upcoming MMA & Boxing fights | UFC Fight Night | 02.01.2025, 12:00 PM ET | MMA Junkie: UFC Fight Night 249 video: Nine stoppages to open the year?! MMA Mania: Prochazka Vs. Hill: Odds, Full Fight Preview & Prediction\", \"score\": 0.6999322, \"raw_content\": null}, {\"title\": \"About Andrew Tate: A Journey from Champion to Controversy\", \"url\": \"https://reachmorpheus.com/andrew-tate/\", \"content\": \"Andrew Tate's kickboxing career, beginning in 2005, is a tale of determination and skill. He quickly made a name for himself in the sport, rising through the ranks with his unique fighting style and strategic approach, honed by his chess-playing background.\", \"score\": 0.6490677, \"raw_content\": null}, {\"title\": \"Andrew Tate's Kickboxing Career & Biography - MMA Full Contact\", \"url\": \"https://www.mmafullcontact.com/andrew-tate-kickboxing/\", \"content\": \"Andrew Tate's Kickboxing Career & Biography - MMA Full Contact Andrew Tate\\u2019s Kickboxing Career & Biography 2 Notable Opponents and Fights in Andrew Tate\\u2019s Kickboxing Career 4 Will Andrew Tate fight KSI? Notable Opponents and Fights in Andrew Tate\\u2019s Kickboxing Career Will Andrew Tate fight KSI? Similarly, Andrew Tate, known for his successful kickboxing career, has also shown interest in a potential fight with KSI. In conclusion, while there\\u2019s been plenty of interest and discussion about a potential boxing match between KSI and Andrew Tate, no official confirmation has been made as of now. With KSI\\u2019s upcoming match and Tate\\u2019s current personal circumstances, fans and followers of both personalities will have to wait for more updates on this potential fight.\", \"score\": 0.53050464, \"raw_content\": null}]}\u001b[0m\n",
+            "\u001b[33minference> \u001b[0m\u001b[33mAndrew\u001b[0m\u001b[33m Tate\u001b[0m\u001b[33m's\u001b[0m\u001b[33m kick\u001b[0m\u001b[33mboxing\u001b[0m\u001b[33m name\u001b[0m\u001b[33m is\u001b[0m\u001b[33m \"\u001b[0m\u001b[33mKing\u001b[0m\u001b[33m Cobra\u001b[0m\u001b[33m.\"\u001b[0m\u001b[97m\u001b[0m\n",
+            "\u001b[30m\u001b[0m"
           ]
         }
       ],
       "source": [
-        "from google.colab import userdata\n",
+        "# NBVAL_SKIP\n",
         "from llama_stack_client.lib.agents.agent import Agent\n",
         "from llama_stack_client.lib.agents.event_logger import EventLogger\n",
         "from llama_stack_client.types.agent_create_params import AgentConfig\n",
         "\n",
         "agent_config = AgentConfig(\n",
-        "    model=\"meta-llama/Llama-3.1-405B-Instruct\",\n",
+        "    model=\"meta-llama/Llama-3.1-405B-Instruct-FP8\",\n",
         "    instructions=\"You are a helpful assistant. Use search tool to answer the questions. \",\n",
-        "    tools=(\n",
-        "        [\n",
-        "            {\n",
-        "                \"type\": \"brave_search\",\n",
-        "                \"engine\": \"tavily\",\n",
-        "                \"api_key\": userdata.get(\"TAVILY_SEARCH_API_KEY\"),\n",
-        "            }\n",
-        "        ]\n",
-        "    ),\n",
+        "    toolgroups=[\"builtin::websearch\"],\n",
         "    input_shields=[],\n",
         "    output_shields=[],\n",
         "    enable_session_persistence=False,\n",
@@ -2174,22 +3320,22 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 19,
       "id": "agkWgToGAsuA",
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
-          "height": 760
+          "height": 1000
         },
         "id": "agkWgToGAsuA",
-        "outputId": "647cd5d2-7610-4fd6-ef66-c3f2f782a1b0"
+        "outputId": "4233a1d9-8282-4aa9-bdc4-0c105939f97e"
       },
       "outputs": [
         {
           "name": "stdout",
           "output_type": "stream",
           "text": [
-            "Getting traces for session_id=ac651ce8-2281-47f2-8814-ef947c066e40\n"
+            "Getting traces for session_id=72993b3e-6030-44f5-9f48-664449d2b6d3\n"
           ]
         },
         {
@@ -2201,42 +3347,82 @@
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"}'</span>,\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null}'</span>\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"font-weight: bold\">]</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'output'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'content: Let me check the latest sports news. tool_calls: []'</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">}</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">{</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'input'</span>: <span style=\"font-weight: bold\">[</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"}'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null}'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"Let me check the latest sports news.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[]}'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'output'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"content:  tool_calls: [ToolCall(call_id='8b7294ec-a83f-4798-ad8f-6bed662f08b6', tool_name=&lt;BuiltinTool.brave_search: 'brave_search'&gt;, arguments={'query': 'NBA Western Conference Finals 2024 teams'})]\"</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">}</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">{</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'input'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"8b7294ec-a83f-4798-ad8f-6bed662f08b6\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"NBA Western Conference Finals 2024 teams\"}}]}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'output'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"tool\",\"call_id\":\"8b7294ec-a83f-4798-ad8f-6bed662f08b6\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"NBA Western Conference Finals 2024 teams\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference Finals - Basketball-Reference.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\\\\\", \\\\\"content\\\\\": \\\\\"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown (20.8 / 5.4 / 5.0) 2024 Playoff Leaders: PTS: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (635) TRB: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (208) AST: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (178) WS: Derrick White (2.9) More playoffs info\\\\\", \\\\\"score\\\\\": 0.9310187, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\\\\\", \\\\\"content\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates &amp; Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\\\\\", \\\\\"score\\\\\": 0.8914433, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 Playoffs: West Finals | Timberwolves (3) vs. Mavericks (5) - NBA.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nba.com/playoffs/2024/west-final\\\\\", \\\\\"content\\\\\": \\\\\"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\\\\\", \\\\\"score\\\\\": 0.8884594, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference playoff bracket - Basketnews.com\\\\\", \\\\\"url\\\\\": \\\\\"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\\\\\", \\\\\"content\\\\\": \\\\\"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\\\\\", \\\\\"score\\\\\": 0.8479807, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Finals 2024 - Celtics-Mavericks news, schedule, scores and ... - ESPN\\\\\", \\\\\"url\\\\\": \\\\\"https://www.espn.com/nba/story/_/id/39943302/nba-playoffs-2024-conference-finals-news-scores-highlights\\\\\", \\\\\"content\\\\\": \\\\\"The Boston Celtics are the 2024 NBA Champions. ... Western Conference. Final 2023-24 NBA regular-season standings. Which team left standing has the most trips to the NBA Finals? Here is a look at\\\\\", \\\\\"score\\\\\": 0.81979275, \\\\\"raw_content\\\\\": null}]}\"}'</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">}</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">{</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'input'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">[</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"8b7294ec-a83f-4798-ad8f-6bed662f08b6\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"NBA Western Conference Finals 2024 teams\"}}]}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"tool\",\"call_id\":\"8b7294ec-a83f-4798-ad8f-6bed662f08b6\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"NBA Western Conference Finals 2024 teams\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference Finals - Basketball-Reference.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\\\\\", \\\\\"content\\\\\": \\\\\"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown (20.8 / 5.4 / 5.0) 2024 Playoff Leaders: PTS: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (635) TRB: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (208) AST: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (178) WS: Derrick White (2.9) More playoffs info\\\\\", \\\\\"score\\\\\": 0.9310187, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\\\\\", \\\\\"content\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates &amp; Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\\\\\", \\\\\"score\\\\\": 0.8914433, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 Playoffs: West Finals | Timberwolves (3) vs. Mavericks (5) - NBA.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nba.com/playoffs/2024/west-final\\\\\", \\\\\"content\\\\\": \\\\\"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\\\\\", \\\\\"score\\\\\": 0.8884594, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference playoff bracket - Basketnews.com\\\\\", \\\\\"url\\\\\": \\\\\"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\\\\\", \\\\\"content\\\\\": \\\\\"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\\\\\", \\\\\"score\\\\\": 0.8479807, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Finals 2024 - Celtics-Mavericks news, schedule, scores and ... - ESPN\\\\\", \\\\\"url\\\\\": \\\\\"https://www.espn.com/nba/story/_/id/39943302/nba-playoffs-2024-conference-finals-news-scores-highlights\\\\\", \\\\\"content\\\\\": \\\\\"The Boston Celtics are the 2024 NBA Champions. ... Western Conference. Final 2023-24 NBA regular-season standings. Which team left standing has the most trips to the NBA Finals? Here is a look at\\\\\", \\\\\"score\\\\\": 0.81979275, \\\\\"raw_content\\\\\": null}]}\"}'</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">]</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'output'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #008000; text-decoration-color: #008000\">'content: The teams that played in the NBA Western Conference Finals of 2024 were the Dallas Mavericks and the Minnesota Timberwolves. tool_calls: []'</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">}</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">{</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'input'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">[</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"8b7294ec-a83f-4798-ad8f-6bed662f08b6\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"NBA Western Conference Finals 2024 teams\"}}]}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"tool\",\"call_id\":\"8b7294ec-a83f-4798-ad8f-6bed662f08b6\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"NBA Western Conference Finals 2024 teams\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference Finals - Basketball-Reference.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\\\\\", \\\\\"content\\\\\": \\\\\"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown (20.8 / 5.4 / 5.0) 2024 Playoff Leaders: PTS: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (635) TRB: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (208) AST: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (178) WS: Derrick White (2.9) More playoffs info\\\\\", \\\\\"score\\\\\": 0.9310187, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\\\\\", \\\\\"content\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates &amp; Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\\\\\", \\\\\"score\\\\\": 0.8914433, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 Playoffs: West Finals | Timberwolves (3) vs. Mavericks (5) - NBA.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nba.com/playoffs/2024/west-final\\\\\", \\\\\"content\\\\\": \\\\\"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\\\\\", \\\\\"score\\\\\": 0.8884594, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference playoff bracket - Basketnews.com\\\\\", \\\\\"url\\\\\": \\\\\"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\\\\\", \\\\\"content\\\\\": \\\\\"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\\\\\", \\\\\"score\\\\\": 0.8479807, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Finals 2024 - Celtics-Mavericks news, schedule, scores and ... - ESPN\\\\\", \\\\\"url\\\\\": \\\\\"https://www.espn.com/nba/story/_/id/39943302/nba-playoffs-2024-conference-finals-news-scores-highlights\\\\\", \\\\\"content\\\\\": \\\\\"The Boston Celtics are the 2024 NBA Champions. ... Western Conference. Final 2023-24 NBA regular-season standings. Which team left standing has the most trips to the NBA Finals? Here is a look at\\\\\", \\\\\"score\\\\\": 0.81979275, \\\\\"raw_content\\\\\": null}]}\"}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"The teams that played in the NBA Western Conference Finals of 2024 were the Dallas Mavericks and the Minnesota Timberwolves.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[]}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"In which episode and season of South Park does Bill Cosby (BSM-471) first appear? Give me the number and title.\",\"context\":null}'</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"font-weight: bold\">]</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'output'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"content:  tool_calls: [ToolCall(call_id='19bd3554-e670-4856-89d0-c63f5b016245', tool_name='bravy_search', arguments={'query': 'Bill Cosby South Park episode'})]\"</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">}</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">{</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'input'</span>: <span style=\"font-weight: bold\">[</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"}'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null}'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"Let me check the latest sports news.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[]}'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"In which episode and season of South Park does Bill Cosby (BSM-471) first appear? Give me the number and title.\",\"context\":null}'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"19bd3554-e670-4856-89d0-c63f5b016245\",\"tool_name\":\"bravy_search\",\"arguments\":{\"query\":\"Bill Cosby South Park episode\"}}]}'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">]</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'output'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #008000; text-decoration-color: #008000\">\"content:  tool_calls: [ToolCall(call_id='fc0441bf-05ad-48d0-8034-4e19cb835904', tool_name=&lt;BuiltinTool.brave_search: 'brave_search'&gt;, arguments={'query': 'Bill Cosby South Park episode'})]\"</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">}</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">{</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'input'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"fc0441bf-05ad-48d0-8034-4e19cb835904\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"Bill Cosby South Park episode\"}}]}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'output'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"tool\",\"call_id\":\"fc0441bf-05ad-48d0-8034-4e19cb835904\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"Bill Cosby South Park episode\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"Bill Cosby and Taylor Swift Duet - South Park Studios\\\\\", \\\\\"url\\\\\": \\\\\"https://www.southparkstudios.com/video-clips/90r7i1/south-park-bill-cosby-and-taylor-swift-duet\\\\\", \\\\\"content\\\\\": \\\\\"01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:03 Bill Cosby and Taylor Swift Duet South ParkS18 E10 ------------------------------------------------------- The holiday special continues with Bill Cosby and Taylor Swift\\'s rendition of \\\\\\\\\\\\\"It\\'s Snowing Out There\\\\\\\\\\\\\". 01:31 #WeBelieveInYou South ParkS18 E10 -------------------------------------- With everyone watching, Kyle takes the opportunity to reach out to his brother. 01:47 Watch Your Microaggressions, Bro South ParkS19 E1 ------------------------------------------------------ Cartman\\'s plan to frame PC Principal backfires. South ParkS19 E1 -------------------------------------- After hearing that the PC people have targeted Kyle, Cartman vows to help.\\\\\", \\\\\"score\\\\\": 0.685971, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Bill Cosby is Here to See You - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/video-clips/wfot8s/south-park-bill-cosby-is-here-to-see-you\\\\\", \\\\\"content\\\\\": \\\\\"01:56 It\\'s Not About Music South ParkS18 E9 ------------------------------------------ At home, Randy sees the consequences of Lorde\\'s performance and calls the Record Producer to try and fix it. 01:24 Lorde\\'s Hologram South ParkS18 E9 -------------------------------------- The Record Producer reveals the truth about the music industry... South ParkS18 E9 --------------------------------------------- Randy catches Sharon with Tupac\\'s hologram. 01:37 I\\'ve Got Your Son, Lorde South ParkS18 E10 ----------------------------------------------- The Record Producer takes Stan and Kyle hostage. 01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:21 Lorde Is My Dad South ParkS18 E10 -------------------------------------- After trying to confront Cartman Bra, Stan finally reveals the truth about his dad.\\\\\", \\\\\"score\\\\\": 0.6643884, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Bill Cosby (android) | South Park Character ... - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/wiki/Bill_Cosby_(android)\\\\\", \\\\\"content\\\\\": \\\\\"Bill Cosby (android) | South Park Character / Location / User talk etc | Official South Park Studios Wiki Sent back in time to destroy Eric Cartman\\'s Dawson\\'s Creek Trapper Keeper before it manifests into an omnipotent supercomputer that can destroy all humanity, \\\\\\\\\\\\\"Bill Cosby\\\\\\\\\\\\\" is really VSM471, an android or cyborg of some kind engineered by \\'hoomans\\' in the distant future. He fails in his initial missions to infiltrate South Park Elementary\\'s 4th Grade class, destroy the Trapper Keeper or Cartman himself, but with Stan Marsh and Kyle Broflovski\\'s aid, he is able to succeed in preventing his dismal future, and painfully fades from existence. South Park and all related titles, logos and characters are trademarks of Comedy Partners.\\\\\", \\\\\"score\\\\\": 0.5052006, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"\\\\\\\\\\\\\"South Park\\\\\\\\\\\\\" Clubhouses (TV Episode 1998) - IMDb\\\\\", \\\\\"url\\\\\": \\\\\"https://www.imdb.com/title/tt0705915/characters/nm0005295\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"South Park\\\\\\\\\\\\\" Clubhouses (TV Episode 1998) - Trey Parker as Stan Marsh, Eric Cartman, Phillip, Randy Marsh, Fat Abbot, Mr. Garrison, Mr. Mackey, 3rd Fat Abbot character, Roy, Teenage Boy #1, Clyde, Bill Cosby, Teenage Boy #2 - IMDb Awards &amp; Events Trey Parker: Stan Marsh, Eric Cartman, Phillip, Randy Marsh, Fat Abbot, Mr. Garrison, Mr. Mackey, 3rd Fat Abbot character, Roy, Teenage Boy #1, Clyde, Bill Cosby, Teenage Boy #2 Mr. Garrison : Stan, are you paying attention? Stan : Yes, Mr. Garrison. Stan Marsh : Dare. Stan Marsh : What? Release Dates | Official Sites | Company Credits | Filming &amp; Production | Technical Specs Photo &amp; Video User Lists Related lists from IMDb users 2024 Watched TV Shows\\\\\", \\\\\"score\\\\\": 0.4604593, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Trapper Keeper (South Park) - Wikipedia\\\\\", \\\\\"url\\\\\": \\\\\"https://en.wikipedia.org/wiki/Trapper_Keeper_(South_Park)\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" is the twelfth episode of the fourth season of the animated television series South Park, and the 60th episode of the series overall. In the episode, a man from the future wants Cartman\\'s new Trapper Keeper, while Mr. Garrison\\'s kindergarten class holds an election for class president with confusing results. It is one of the many South Park episodes that parodies a current event.[1] The main plot of the episode involving the Trapper Keeper was written before the election,[1] but the subplot is a parody of the controversy surrounding the election\\'s outcome.[2] \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" did not originally feature the election storyline, only a subplot about Ike attending his first day of kindergarten.[3] \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" Full episode at South Park Studios\\\\\", \\\\\"score\\\\\": 0.3839421, \\\\\"raw_content\\\\\": null}]}\"}'</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">}</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">{</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'input'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">[</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"8b7294ec-a83f-4798-ad8f-6bed662f08b6\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"NBA Western Conference Finals 2024 teams\"}}]}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"tool\",\"call_id\":\"8b7294ec-a83f-4798-ad8f-6bed662f08b6\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"NBA Western Conference Finals 2024 teams\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference Finals - Basketball-Reference.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\\\\\", \\\\\"content\\\\\": \\\\\"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown (20.8 / 5.4 / 5.0) 2024 Playoff Leaders: PTS: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (635) TRB: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (208) AST: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (178) WS: Derrick White (2.9) More playoffs info\\\\\", \\\\\"score\\\\\": 0.9310187, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\\\\\", \\\\\"content\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates &amp; Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\\\\\", \\\\\"score\\\\\": 0.8914433, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 Playoffs: West Finals | Timberwolves (3) vs. Mavericks (5) - NBA.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nba.com/playoffs/2024/west-final\\\\\", \\\\\"content\\\\\": \\\\\"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\\\\\", \\\\\"score\\\\\": 0.8884594, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference playoff bracket - Basketnews.com\\\\\", \\\\\"url\\\\\": \\\\\"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\\\\\", \\\\\"content\\\\\": \\\\\"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\\\\\", \\\\\"score\\\\\": 0.8479807, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Finals 2024 - Celtics-Mavericks news, schedule, scores and ... - ESPN\\\\\", \\\\\"url\\\\\": \\\\\"https://www.espn.com/nba/story/_/id/39943302/nba-playoffs-2024-conference-finals-news-scores-highlights\\\\\", \\\\\"content\\\\\": \\\\\"The Boston Celtics are the 2024 NBA Champions. ... Western Conference. Final 2023-24 NBA regular-season standings. Which team left standing has the most trips to the NBA Finals? Here is a look at\\\\\", \\\\\"score\\\\\": 0.81979275, \\\\\"raw_content\\\\\": null}]}\"}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"The teams that played in the NBA Western Conference Finals of 2024 were the Dallas Mavericks and the Minnesota Timberwolves.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[]}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"In which episode and season of South Park does Bill Cosby (BSM-471) first appear? Give me the number and title.\",\"context\":null}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"fc0441bf-05ad-48d0-8034-4e19cb835904\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"Bill Cosby South Park episode\"}}]}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"tool\",\"call_id\":\"fc0441bf-05ad-48d0-8034-4e19cb835904\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"Bill Cosby South Park episode\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"Bill Cosby and Taylor Swift Duet - South Park Studios\\\\\", \\\\\"url\\\\\": \\\\\"https://www.southparkstudios.com/video-clips/90r7i1/south-park-bill-cosby-and-taylor-swift-duet\\\\\", \\\\\"content\\\\\": \\\\\"01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:03 Bill Cosby and Taylor Swift Duet South ParkS18 E10 ------------------------------------------------------- The holiday special continues with Bill Cosby and Taylor Swift\\'s rendition of \\\\\\\\\\\\\"It\\'s Snowing Out There\\\\\\\\\\\\\". 01:31 #WeBelieveInYou South ParkS18 E10 -------------------------------------- With everyone watching, Kyle takes the opportunity to reach out to his brother. 01:47 Watch Your Microaggressions, Bro South ParkS19 E1 ------------------------------------------------------ Cartman\\'s plan to frame PC Principal backfires. South ParkS19 E1 -------------------------------------- After hearing that the PC people have targeted Kyle, Cartman vows to help.\\\\\", \\\\\"score\\\\\": 0.685971, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Bill Cosby is Here to See You - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/video-clips/wfot8s/south-park-bill-cosby-is-here-to-see-you\\\\\", \\\\\"content\\\\\": \\\\\"01:56 It\\'s Not About Music South ParkS18 E9 ------------------------------------------ At home, Randy sees the consequences of Lorde\\'s performance and calls the Record Producer to try and fix it. 01:24 Lorde\\'s Hologram South ParkS18 E9 -------------------------------------- The Record Producer reveals the truth about the music industry... South ParkS18 E9 --------------------------------------------- Randy catches Sharon with Tupac\\'s hologram. 01:37 I\\'ve Got Your Son, Lorde South ParkS18 E10 ----------------------------------------------- The Record Producer takes Stan and Kyle hostage. 01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:21 Lorde Is My Dad South ParkS18 E10 -------------------------------------- After trying to confront Cartman Bra, Stan finally reveals the truth about his dad.\\\\\", \\\\\"score\\\\\": 0.6643884, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Bill Cosby (android) | South Park Character ... - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/wiki/Bill_Cosby_(android)\\\\\", \\\\\"content\\\\\": \\\\\"Bill Cosby (android) | South Park Character / Location / User talk etc | Official South Park Studios Wiki Sent back in time to destroy Eric Cartman\\'s Dawson\\'s Creek Trapper Keeper before it manifests into an omnipotent supercomputer that can destroy all humanity, \\\\\\\\\\\\\"Bill Cosby\\\\\\\\\\\\\" is really VSM471, an android or cyborg of some kind engineered by \\'hoomans\\' in the distant future. He fails in his initial missions to infiltrate South Park Elementary\\'s 4th Grade class, destroy the Trapper Keeper or Cartman himself, but with Stan Marsh and Kyle Broflovski\\'s aid, he is able to succeed in preventing his dismal future, and painfully fades from existence. South Park and all related titles, logos and characters are trademarks of Comedy Partners.\\\\\", \\\\\"score\\\\\": 0.5052006, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"\\\\\\\\\\\\\"South Park\\\\\\\\\\\\\" Clubhouses (TV Episode 1998) - IMDb\\\\\", \\\\\"url\\\\\": \\\\\"https://www.imdb.com/title/tt0705915/characters/nm0005295\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"South Park\\\\\\\\\\\\\" Clubhouses (TV Episode 1998) - Trey Parker as Stan Marsh, Eric Cartman, Phillip, Randy Marsh, Fat Abbot, Mr. Garrison, Mr. Mackey, 3rd Fat Abbot character, Roy, Teenage Boy #1, Clyde, Bill Cosby, Teenage Boy #2 - IMDb Awards &amp; Events Trey Parker: Stan Marsh, Eric Cartman, Phillip, Randy Marsh, Fat Abbot, Mr. Garrison, Mr. Mackey, 3rd Fat Abbot character, Roy, Teenage Boy #1, Clyde, Bill Cosby, Teenage Boy #2 Mr. Garrison : Stan, are you paying attention? Stan : Yes, Mr. Garrison. Stan Marsh : Dare. Stan Marsh : What? Release Dates | Official Sites | Company Credits | Filming &amp; Production | Technical Specs Photo &amp; Video User Lists Related lists from IMDb users 2024 Watched TV Shows\\\\\", \\\\\"score\\\\\": 0.4604593, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Trapper Keeper (South Park) - Wikipedia\\\\\", \\\\\"url\\\\\": \\\\\"https://en.wikipedia.org/wiki/Trapper_Keeper_(South_Park)\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" is the twelfth episode of the fourth season of the animated television series South Park, and the 60th episode of the series overall. In the episode, a man from the future wants Cartman\\'s new Trapper Keeper, while Mr. Garrison\\'s kindergarten class holds an election for class president with confusing results. It is one of the many South Park episodes that parodies a current event.[1] The main plot of the episode involving the Trapper Keeper was written before the election,[1] but the subplot is a parody of the controversy surrounding the election\\'s outcome.[2] \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" did not originally feature the election storyline, only a subplot about Ike attending his first day of kindergarten.[3] \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" Full episode at South Park Studios\\\\\", \\\\\"score\\\\\": 0.3839421, \\\\\"raw_content\\\\\": null}]}\"}'</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">]</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'output'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #008000; text-decoration-color: #008000\">'content: Bill Cosby (BSM-471) first appears in the episode \"Trapper Keeper\" (Season 4, Episode 12) of South Park. tool_calls: []'</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">}</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">{</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'input'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">[</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"8b7294ec-a83f-4798-ad8f-6bed662f08b6\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"NBA Western Conference Finals 2024 teams\"}}]}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"tool\",\"call_id\":\"8b7294ec-a83f-4798-ad8f-6bed662f08b6\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"NBA Western Conference Finals 2024 teams\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference Finals - Basketball-Reference.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\\\\\", \\\\\"content\\\\\": \\\\\"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown (20.8 / 5.4 / 5.0) 2024 Playoff Leaders: PTS: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (635) TRB: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (208) AST: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (178) WS: Derrick White (2.9) More playoffs info\\\\\", \\\\\"score\\\\\": 0.9310187, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\\\\\", \\\\\"content\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates &amp; Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\\\\\", \\\\\"score\\\\\": 0.8914433, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 Playoffs: West Finals | Timberwolves (3) vs. Mavericks (5) - NBA.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nba.com/playoffs/2024/west-final\\\\\", \\\\\"content\\\\\": \\\\\"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\\\\\", \\\\\"score\\\\\": 0.8884594, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference playoff bracket - Basketnews.com\\\\\", \\\\\"url\\\\\": \\\\\"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\\\\\", \\\\\"content\\\\\": \\\\\"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\\\\\", \\\\\"score\\\\\": 0.8479807, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Finals 2024 - Celtics-Mavericks news, schedule, scores and ... - ESPN\\\\\", \\\\\"url\\\\\": \\\\\"https://www.espn.com/nba/story/_/id/39943302/nba-playoffs-2024-conference-finals-news-scores-highlights\\\\\", \\\\\"content\\\\\": \\\\\"The Boston Celtics are the 2024 NBA Champions. ... Western Conference. Final 2023-24 NBA regular-season standings. Which team left standing has the most trips to the NBA Finals? Here is a look at\\\\\", \\\\\"score\\\\\": 0.81979275, \\\\\"raw_content\\\\\": null}]}\"}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"The teams that played in the NBA Western Conference Finals of 2024 were the Dallas Mavericks and the Minnesota Timberwolves.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[]}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"In which episode and season of South Park does Bill Cosby (BSM-471) first appear? Give me the number and title.\",\"context\":null}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"fc0441bf-05ad-48d0-8034-4e19cb835904\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"Bill Cosby South Park episode\"}}]}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"tool\",\"call_id\":\"fc0441bf-05ad-48d0-8034-4e19cb835904\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"Bill Cosby South Park episode\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"Bill Cosby and Taylor Swift Duet - South Park Studios\\\\\", \\\\\"url\\\\\": \\\\\"https://www.southparkstudios.com/video-clips/90r7i1/south-park-bill-cosby-and-taylor-swift-duet\\\\\", \\\\\"content\\\\\": \\\\\"01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:03 Bill Cosby and Taylor Swift Duet South ParkS18 E10 ------------------------------------------------------- The holiday special continues with Bill Cosby and Taylor Swift\\'s rendition of \\\\\\\\\\\\\"It\\'s Snowing Out There\\\\\\\\\\\\\". 01:31 #WeBelieveInYou South ParkS18 E10 -------------------------------------- With everyone watching, Kyle takes the opportunity to reach out to his brother. 01:47 Watch Your Microaggressions, Bro South ParkS19 E1 ------------------------------------------------------ Cartman\\'s plan to frame PC Principal backfires. South ParkS19 E1 -------------------------------------- After hearing that the PC people have targeted Kyle, Cartman vows to help.\\\\\", \\\\\"score\\\\\": 0.685971, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Bill Cosby is Here to See You - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/video-clips/wfot8s/south-park-bill-cosby-is-here-to-see-you\\\\\", \\\\\"content\\\\\": \\\\\"01:56 It\\'s Not About Music South ParkS18 E9 ------------------------------------------ At home, Randy sees the consequences of Lorde\\'s performance and calls the Record Producer to try and fix it. 01:24 Lorde\\'s Hologram South ParkS18 E9 -------------------------------------- The Record Producer reveals the truth about the music industry... South ParkS18 E9 --------------------------------------------- Randy catches Sharon with Tupac\\'s hologram. 01:37 I\\'ve Got Your Son, Lorde South ParkS18 E10 ----------------------------------------------- The Record Producer takes Stan and Kyle hostage. 01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:21 Lorde Is My Dad South ParkS18 E10 -------------------------------------- After trying to confront Cartman Bra, Stan finally reveals the truth about his dad.\\\\\", \\\\\"score\\\\\": 0.6643884, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Bill Cosby (android) | South Park Character ... - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/wiki/Bill_Cosby_(android)\\\\\", \\\\\"content\\\\\": \\\\\"Bill Cosby (android) | South Park Character / Location / User talk etc | Official South Park Studios Wiki Sent back in time to destroy Eric Cartman\\'s Dawson\\'s Creek Trapper Keeper before it manifests into an omnipotent supercomputer that can destroy all humanity, \\\\\\\\\\\\\"Bill Cosby\\\\\\\\\\\\\" is really VSM471, an android or cyborg of some kind engineered by \\'hoomans\\' in the distant future. He fails in his initial missions to infiltrate South Park Elementary\\'s 4th Grade class, destroy the Trapper Keeper or Cartman himself, but with Stan Marsh and Kyle Broflovski\\'s aid, he is able to succeed in preventing his dismal future, and painfully fades from existence. South Park and all related titles, logos and characters are trademarks of Comedy Partners.\\\\\", \\\\\"score\\\\\": 0.5052006, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"\\\\\\\\\\\\\"South Park\\\\\\\\\\\\\" Clubhouses (TV Episode 1998) - IMDb\\\\\", \\\\\"url\\\\\": \\\\\"https://www.imdb.com/title/tt0705915/characters/nm0005295\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"South Park\\\\\\\\\\\\\" Clubhouses (TV Episode 1998) - Trey Parker as Stan Marsh, Eric Cartman, Phillip, Randy Marsh, Fat Abbot, Mr. Garrison, Mr. Mackey, 3rd Fat Abbot character, Roy, Teenage Boy #1, Clyde, Bill Cosby, Teenage Boy #2 - IMDb Awards &amp; Events Trey Parker: Stan Marsh, Eric Cartman, Phillip, Randy Marsh, Fat Abbot, Mr. Garrison, Mr. Mackey, 3rd Fat Abbot character, Roy, Teenage Boy #1, Clyde, Bill Cosby, Teenage Boy #2 Mr. Garrison : Stan, are you paying attention? Stan : Yes, Mr. Garrison. Stan Marsh : Dare. Stan Marsh : What? Release Dates | Official Sites | Company Credits | Filming &amp; Production | Technical Specs Photo &amp; Video User Lists Related lists from IMDb users 2024 Watched TV Shows\\\\\", \\\\\"score\\\\\": 0.4604593, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Trapper Keeper (South Park) - Wikipedia\\\\\", \\\\\"url\\\\\": \\\\\"https://en.wikipedia.org/wiki/Trapper_Keeper_(South_Park)\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" is the twelfth episode of the fourth season of the animated television series South Park, and the 60th episode of the series overall. In the episode, a man from the future wants Cartman\\'s new Trapper Keeper, while Mr. Garrison\\'s kindergarten class holds an election for class president with confusing results. It is one of the many South Park episodes that parodies a current event.[1] The main plot of the episode involving the Trapper Keeper was written before the election,[1] but the subplot is a parody of the controversy surrounding the election\\'s outcome.[2] \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" did not originally feature the election storyline, only a subplot about Ike attending his first day of kindergarten.[3] \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" Full episode at South Park Studios\\\\\", \\\\\"score\\\\\": 0.3839421, \\\\\"raw_content\\\\\": null}]}\"}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"Bill Cosby (BSM-471) first appears in the episode \\\\\"Trapper Keeper\\\\\" (Season 4, Episode 12) of South Park.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[]}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"What is the British-American kickboxer Andrew Tate\\'s kickboxing name?\",\"context\":null}'</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"font-weight: bold\">]</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'output'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"content:  tool_calls: [ToolCall(call_id='526045a7-5f51-40fb-ba97-5ad29610e511', tool_name=&lt;BuiltinTool.brave_search: 'brave_search'&gt;, arguments={'query': 'Andrew Tate kickboxing name'})]\"</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">]</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
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               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">}</span>,\n",
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+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'output'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"tool\",\"call_id\":\"79276f65-3600-489d-ab41-d5a71dcaf075\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"Andrew Tate kickboxing name\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"Andrew Tate Age, Height, Weight, Family, Parents, Biography, Net Worth\\\\\", \\\\\"url\\\\\": \\\\\"https://biographywallah.com/andrew-tate-biography/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate Age, Height, Weight, Family, Parents, Biography, Net Worth \\\\\\\\u00bb Biography Wallah Andrew Tate Age, Height, Weight, Family, Parents, Biography, Net Worth Andrew Tate Biography NameAndrew TateReal nameEmory Andrew Tate IIIProfession \\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0Kickboxer, Commentator and BusinessmanDate of birth14 December 1986BirthplaceWashington D.C., United StatesAndrew Tate Age37 years old (as of 2024)NationalityBritish-AmericanZodiac SignSagittariusGenderMaleSchoolLocal School in Washington D.C., United StatesGirlfriend/SpouseNaghel GeorgianaSexual OrientationStraightNet worth$1000 Million Who is Andrew Tate? Andrew Tate is a British-American former professional kickboxing world champion businessman and media personality, who fought in the cruiserweight and super cruiserweight divisions. Andrew Tate Age Andrew Tate was born on 1 December 1986 and is 37 years old. Andrew Tate\\\\\\\\u2019s Net Worth What is the net worth of Andrew Tate? Where is Andrew Tate from? How old is Andrew Tate?\\\\\", \\\\\"score\\\\\": 0.80698997, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"The Life Of Andrew Tate (By Andrew Tate Himself ... - Sidekick Boxing\\\\\", \\\\\"url\\\\\": \\\\\"https://sidekickboxing.co.uk/the-life-of-andrew-king-cobra-tate/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate is a British-American former professional kickboxing world champion who fought in the cruiserweight and super cruiserweight divisions. Andrew Tate\\\\\\\\u2019s Kickboxing Career Andrew Tate in the Big Brother house Andrew Tate\\\\\\\\u2019s Kickboxing World Titles and his Sidekick boxing gloves Andrew Tate After Kickboxing Andrew Tate and his brother Tristan moved to Romania to set up their empire of businesses including trading in Bitcoin, Hustlers University, CobraTate.com, The Real World, and The War Room. 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Andrew Tate MMA Fight Record Former top-ranked UFC fighter has called out Andrew Tate for having a paper title when it comes to combat... Andrew Tate \\\\\\\\u2022 All the biggest upcoming MMA &amp; Boxing fights | UFC Fight Night | 02.01.2025, 12:00 PM ET | MMA Junkie: UFC Fight Night 249 video: Nine stoppages to open the year?! MMA Mania: Prochazka Vs. Hill: Odds, Full Fight Preview &amp; Prediction\\\\\", \\\\\"score\\\\\": 0.6999322, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"About Andrew Tate: A Journey from Champion to Controversy\\\\\", \\\\\"url\\\\\": \\\\\"https://reachmorpheus.com/andrew-tate/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate\\'s kickboxing career, beginning in 2005, is a tale of determination and skill. 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In conclusion, while there\\\\\\\\u2019s been plenty of interest and discussion about a potential boxing match between KSI and Andrew Tate, no official confirmation has been made as of now. With KSI\\\\\\\\u2019s upcoming match and Tate\\\\\\\\u2019s current personal circumstances, fans and followers of both personalities will have to wait for more updates on this potential fight.\\\\\", \\\\\"score\\\\\": 0.53050464, \\\\\"raw_content\\\\\": null}]}\"}'</span>\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">}</span>,\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">{</span>\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'input'</span>: <span style=\"font-weight: bold\">[</span>\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"}'</span>,\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null}'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"Let me check the latest sports news.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[]}'</span>,\n",
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+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"tool\",\"call_id\":\"8b7294ec-a83f-4798-ad8f-6bed662f08b6\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"NBA Western Conference Finals 2024 teams\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference Finals - Basketball-Reference.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\\\\\", \\\\\"content\\\\\": \\\\\"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown (20.8 / 5.4 / 5.0) 2024 Playoff Leaders: PTS: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (635) TRB: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (208) AST: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (178) WS: Derrick White (2.9) More playoffs info\\\\\", \\\\\"score\\\\\": 0.9310187, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\\\\\", \\\\\"content\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates &amp; Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\\\\\", \\\\\"score\\\\\": 0.8914433, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 Playoffs: West Finals | Timberwolves (3) vs. Mavericks (5) - NBA.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nba.com/playoffs/2024/west-final\\\\\", \\\\\"content\\\\\": \\\\\"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\\\\\", \\\\\"score\\\\\": 0.8884594, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference playoff bracket - Basketnews.com\\\\\", \\\\\"url\\\\\": \\\\\"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\\\\\", \\\\\"content\\\\\": \\\\\"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\\\\\", \\\\\"score\\\\\": 0.8479807, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Finals 2024 - Celtics-Mavericks news, schedule, scores and ... - ESPN\\\\\", \\\\\"url\\\\\": \\\\\"https://www.espn.com/nba/story/_/id/39943302/nba-playoffs-2024-conference-finals-news-scores-highlights\\\\\", \\\\\"content\\\\\": \\\\\"The Boston Celtics are the 2024 NBA Champions. ... Western Conference. Final 2023-24 NBA regular-season standings. Which team left standing has the most trips to the NBA Finals? Here is a look at\\\\\", \\\\\"score\\\\\": 0.81979275, \\\\\"raw_content\\\\\": null}]}\"}'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"The teams that played in the NBA Western Conference Finals of 2024 were the Dallas Mavericks and the Minnesota Timberwolves.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[]}'</span>,\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"In which episode and season of South Park does Bill Cosby (BSM-471) first appear? Give me the number and title.\",\"context\":null}'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"19bd3554-e670-4856-89d0-c63f5b016245\",\"tool_name\":\"bravy_search\",\"arguments\":{\"query\":\"Bill Cosby South Park episode\"}}]}'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"fc0441bf-05ad-48d0-8034-4e19cb835904\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"Bill Cosby South Park episode\"}}]}'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"tool\",\"call_id\":\"fc0441bf-05ad-48d0-8034-4e19cb835904\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"Bill Cosby South Park episode\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"Bill Cosby and Taylor Swift Duet - South Park Studios\\\\\", \\\\\"url\\\\\": \\\\\"https://www.southparkstudios.com/video-clips/90r7i1/south-park-bill-cosby-and-taylor-swift-duet\\\\\", \\\\\"content\\\\\": \\\\\"01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:03 Bill Cosby and Taylor Swift Duet South ParkS18 E10 ------------------------------------------------------- The holiday special continues with Bill Cosby and Taylor Swift\\'s rendition of \\\\\\\\\\\\\"It\\'s Snowing Out There\\\\\\\\\\\\\". 01:31 #WeBelieveInYou South ParkS18 E10 -------------------------------------- With everyone watching, Kyle takes the opportunity to reach out to his brother. 01:47 Watch Your Microaggressions, Bro South ParkS19 E1 ------------------------------------------------------ Cartman\\'s plan to frame PC Principal backfires. South ParkS19 E1 -------------------------------------- After hearing that the PC people have targeted Kyle, Cartman vows to help.\\\\\", \\\\\"score\\\\\": 0.685971, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Bill Cosby is Here to See You - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/video-clips/wfot8s/south-park-bill-cosby-is-here-to-see-you\\\\\", \\\\\"content\\\\\": \\\\\"01:56 It\\'s Not About Music South ParkS18 E9 ------------------------------------------ At home, Randy sees the consequences of Lorde\\'s performance and calls the Record Producer to try and fix it. 01:24 Lorde\\'s Hologram South ParkS18 E9 -------------------------------------- The Record Producer reveals the truth about the music industry... South ParkS18 E9 --------------------------------------------- Randy catches Sharon with Tupac\\'s hologram. 01:37 I\\'ve Got Your Son, Lorde South ParkS18 E10 ----------------------------------------------- The Record Producer takes Stan and Kyle hostage. 01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:21 Lorde Is My Dad South ParkS18 E10 -------------------------------------- After trying to confront Cartman Bra, Stan finally reveals the truth about his dad.\\\\\", \\\\\"score\\\\\": 0.6643884, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Bill Cosby (android) | South Park Character ... - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/wiki/Bill_Cosby_(android)\\\\\", \\\\\"content\\\\\": \\\\\"Bill Cosby (android) | South Park Character / Location / User talk etc | Official South Park Studios Wiki Sent back in time to destroy Eric Cartman\\'s Dawson\\'s Creek Trapper Keeper before it manifests into an omnipotent supercomputer that can destroy all humanity, \\\\\\\\\\\\\"Bill Cosby\\\\\\\\\\\\\" is really VSM471, an android or cyborg of some kind engineered by \\'hoomans\\' in the distant future. He fails in his initial missions to infiltrate South Park Elementary\\'s 4th Grade class, destroy the Trapper Keeper or Cartman himself, but with Stan Marsh and Kyle Broflovski\\'s aid, he is able to succeed in preventing his dismal future, and painfully fades from existence. South Park and all related titles, logos and characters are trademarks of Comedy Partners.\\\\\", \\\\\"score\\\\\": 0.5052006, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"\\\\\\\\\\\\\"South Park\\\\\\\\\\\\\" Clubhouses (TV Episode 1998) - IMDb\\\\\", \\\\\"url\\\\\": \\\\\"https://www.imdb.com/title/tt0705915/characters/nm0005295\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"South Park\\\\\\\\\\\\\" Clubhouses (TV Episode 1998) - Trey Parker as Stan Marsh, Eric Cartman, Phillip, Randy Marsh, Fat Abbot, Mr. Garrison, Mr. Mackey, 3rd Fat Abbot character, Roy, Teenage Boy #1, Clyde, Bill Cosby, Teenage Boy #2 - IMDb Awards &amp; Events Trey Parker: Stan Marsh, Eric Cartman, Phillip, Randy Marsh, Fat Abbot, Mr. Garrison, Mr. Mackey, 3rd Fat Abbot character, Roy, Teenage Boy #1, Clyde, Bill Cosby, Teenage Boy #2 Mr. Garrison : Stan, are you paying attention? Stan : Yes, Mr. Garrison. Stan Marsh : Dare. Stan Marsh : What? Release Dates | Official Sites | Company Credits | Filming &amp; Production | Technical Specs Photo &amp; Video User Lists Related lists from IMDb users 2024 Watched TV Shows\\\\\", \\\\\"score\\\\\": 0.4604593, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Trapper Keeper (South Park) - Wikipedia\\\\\", \\\\\"url\\\\\": \\\\\"https://en.wikipedia.org/wiki/Trapper_Keeper_(South_Park)\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" is the twelfth episode of the fourth season of the animated television series South Park, and the 60th episode of the series overall. In the episode, a man from the future wants Cartman\\'s new Trapper Keeper, while Mr. Garrison\\'s kindergarten class holds an election for class president with confusing results. 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+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"Bill Cosby (BSM-471) first appears in the episode \\\\\"Trapper Keeper\\\\\" (Season 4, Episode 12) of South Park.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[]}'</span>,\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"What is the British-American kickboxer Andrew Tate\\'s kickboxing name?\",\"context\":null}'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"526045a7-5f51-40fb-ba97-5ad29610e511\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"Andrew Tate kickboxing name\"}}]}'</span>,\n",
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+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"79276f65-3600-489d-ab41-d5a71dcaf075\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"Andrew Tate kickboxing name\"}}]}'</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"tool\",\"call_id\":\"79276f65-3600-489d-ab41-d5a71dcaf075\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"Andrew Tate kickboxing name\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"Andrew Tate Age, Height, Weight, Family, Parents, Biography, Net Worth\\\\\", \\\\\"url\\\\\": \\\\\"https://biographywallah.com/andrew-tate-biography/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate Age, Height, Weight, Family, Parents, Biography, Net Worth \\\\\\\\u00bb Biography Wallah Andrew Tate Age, Height, Weight, Family, Parents, Biography, Net Worth Andrew Tate Biography NameAndrew TateReal nameEmory Andrew Tate IIIProfession \\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0Kickboxer, Commentator and BusinessmanDate of birth14 December 1986BirthplaceWashington D.C., United StatesAndrew Tate Age37 years old (as of 2024)NationalityBritish-AmericanZodiac SignSagittariusGenderMaleSchoolLocal School in Washington D.C., United StatesGirlfriend/SpouseNaghel GeorgianaSexual OrientationStraightNet worth$1000 Million Who is Andrew Tate? Andrew Tate is a British-American former professional kickboxing world champion businessman and media personality, who fought in the cruiserweight and super cruiserweight divisions. Andrew Tate Age Andrew Tate was born on 1 December 1986 and is 37 years old. Andrew Tate\\\\\\\\u2019s Net Worth What is the net worth of Andrew Tate? Where is Andrew Tate from? How old is Andrew Tate?\\\\\", \\\\\"score\\\\\": 0.80698997, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"The Life Of Andrew Tate (By Andrew Tate Himself ... - Sidekick Boxing\\\\\", \\\\\"url\\\\\": \\\\\"https://sidekickboxing.co.uk/the-life-of-andrew-king-cobra-tate/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate is a British-American former professional kickboxing world champion who fought in the cruiserweight and super cruiserweight divisions. Andrew Tate\\\\\\\\u2019s Kickboxing Career Andrew Tate in the Big Brother house Andrew Tate\\\\\\\\u2019s Kickboxing World Titles and his Sidekick boxing gloves Andrew Tate After Kickboxing Andrew Tate and his brother Tristan moved to Romania to set up their empire of businesses including trading in Bitcoin, Hustlers University, CobraTate.com, The Real World, and The War Room. From being a 4x kickboxing world champion to becoming the world\\\\\\\\u2019s most Googled man in the world with a private jet and over 33 cars, Andrew Tate\\\\\\\\u2019s life has been full of adventure.\\\\\", \\\\\"score\\\\\": 0.78194773, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Andrew Tate (\\\\\\\\\\\\\"King Cobra\\\\\\\\\\\\\") | MMA Fighter Page - Tapology\\\\\", \\\\\"url\\\\\": \\\\\"https://www.tapology.com/fightcenter/fighters/72139-andrew-tate\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate (\\\\\\\\\\\\\"King Cobra\\\\\\\\\\\\\") | MMA Fighter Page | Tapology Andrew \\\\\\\\\\\\\"King Cobra\\\\\\\\\\\\\" Tate Andrew Tate Name: Andrew Tate Height: 6\\'1\\\\\\\\\\\\\" (185cm) | Reach: Andrew Tate is ineligible for Tapology\\'s regional MMA rankings due to inactivity. Fighters must have at least one completed MMA bout in the past two years to be ranked. Andrew Tate MMA Fight Record Former top-ranked UFC fighter has called out Andrew Tate for having a paper title when it comes to combat... Andrew Tate \\\\\\\\u2022 All the biggest upcoming MMA &amp; Boxing fights | UFC Fight Night | 02.01.2025, 12:00 PM ET | MMA Junkie: UFC Fight Night 249 video: Nine stoppages to open the year?! MMA Mania: Prochazka Vs. Hill: Odds, Full Fight Preview &amp; Prediction\\\\\", \\\\\"score\\\\\": 0.6999322, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"About Andrew Tate: A Journey from Champion to Controversy\\\\\", \\\\\"url\\\\\": \\\\\"https://reachmorpheus.com/andrew-tate/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate\\'s kickboxing career, beginning in 2005, is a tale of determination and skill. He quickly made a name for himself in the sport, rising through the ranks with his unique fighting style and strategic approach, honed by his chess-playing background.\\\\\", \\\\\"score\\\\\": 0.6490677, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Andrew Tate\\'s Kickboxing Career &amp; Biography - MMA Full Contact\\\\\", \\\\\"url\\\\\": \\\\\"https://www.mmafullcontact.com/andrew-tate-kickboxing/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate\\'s Kickboxing Career &amp; Biography - MMA Full Contact Andrew Tate\\\\\\\\u2019s Kickboxing Career &amp; Biography 2 Notable Opponents and Fights in Andrew Tate\\\\\\\\u2019s Kickboxing Career 4 Will Andrew Tate fight KSI? Notable Opponents and Fights in Andrew Tate\\\\\\\\u2019s Kickboxing Career Will Andrew Tate fight KSI? Similarly, Andrew Tate, known for his successful kickboxing career, has also shown interest in a potential fight with KSI. In conclusion, while there\\\\\\\\u2019s been plenty of interest and discussion about a potential boxing match between KSI and Andrew Tate, no official confirmation has been made as of now. With KSI\\\\\\\\u2019s upcoming match and Tate\\\\\\\\u2019s current personal circumstances, fans and followers of both personalities will have to wait for more updates on this potential fight.\\\\\", \\\\\"score\\\\\": 0.53050464, \\\\\"raw_content\\\\\": null}]}\"}'</span>\n",
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               "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
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+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"call_id\":\"8b7294ec-a83f-4798-ad8f-6bed662f08b6\",\"tool_name\":\"brave_search\",\"arguments\":\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"query\":\"NBA Western Conference Finals 2024 teams\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"tool\",\"call_id\":\"8b7294ec-a83f-4798-ad8f-6bed662f08b6\",\"tool_name\":\"brave_search\",\"content\":\"\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"query\\\\\": \\\\\"NBA Western Conference Finals 2024 teams\\\\\", \\\\\"top_k\\\\\": \u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference Finals - Basketball-Reference.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\\\\\", \\\\\"content\\\\\": \\\\\"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown \u001b[0m\u001b[32m(\u001b[0m\u001b[32m20.8 / 5.4 / 5.0\u001b[0m\u001b[32m)\u001b[0m\u001b[32m 2024 Playoff Leaders: PTS: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m635\u001b[0m\u001b[32m)\u001b[0m\u001b[32m TRB: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m208\u001b[0m\u001b[32m)\u001b[0m\u001b[32m AST: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m178\u001b[0m\u001b[32m)\u001b[0m\u001b[32m WS: Derrick White \u001b[0m\u001b[32m(\u001b[0m\u001b[32m2.9\u001b[0m\u001b[32m)\u001b[0m\u001b[32m More playoffs info\\\\\", \\\\\"score\\\\\": 0.9310187, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\\\\\", \\\\\"content\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates & Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\\\\\", \\\\\"score\\\\\": 0.8914433, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 Playoffs: West Finals | Timberwolves \u001b[0m\u001b[32m(\u001b[0m\u001b[32m3\u001b[0m\u001b[32m)\u001b[0m\u001b[32m vs. Mavericks \u001b[0m\u001b[32m(\u001b[0m\u001b[32m5\u001b[0m\u001b[32m)\u001b[0m\u001b[32m - NBA.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nba.com/playoffs/2024/west-final\\\\\", \\\\\"content\\\\\": \\\\\"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\\\\\", \\\\\"score\\\\\": 0.8884594, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference playoff bracket - Basketnews.com\\\\\", \\\\\"url\\\\\": \\\\\"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\\\\\", \\\\\"content\\\\\": \\\\\"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\\\\\", \\\\\"score\\\\\": 0.8479807, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"NBA Finals 2024 - Celtics-Mavericks news, schedule, scores and ... - ESPN\\\\\", \\\\\"url\\\\\": \\\\\"https://www.espn.com/nba/story/_/id/39943302/nba-playoffs-2024-conference-finals-news-scores-highlights\\\\\", \\\\\"content\\\\\": \\\\\"The Boston Celtics are the 2024 NBA Champions. ... Western Conference. Final 2023-24 NBA regular-season standings. Which team left standing has the most trips to the NBA Finals? Here is a look at\\\\\", \\\\\"score\\\\\": 0.81979275, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[1;39m]\u001b[0m\u001b[39m,\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'output'\u001b[0m\u001b[39m: \u001b[0m\u001b[32m'content: The teams that played in the NBA Western Conference Finals of 2024 were the Dallas Mavericks and the Minnesota Timberwolves. tool_calls: \u001b[0m\u001b[32m[\u001b[0m\u001b[32m]\u001b[0m\u001b[32m'\u001b[0m\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1;39m}\u001b[0m\u001b[39m,\u001b[0m\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1;39m{\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'input'\u001b[0m\u001b[39m: \u001b[0m\u001b[1;39m[\u001b[0m\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"call_id\":\"8b7294ec-a83f-4798-ad8f-6bed662f08b6\",\"tool_name\":\"brave_search\",\"arguments\":\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"query\":\"NBA Western Conference Finals 2024 teams\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"tool\",\"call_id\":\"8b7294ec-a83f-4798-ad8f-6bed662f08b6\",\"tool_name\":\"brave_search\",\"content\":\"\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"query\\\\\": \\\\\"NBA Western Conference Finals 2024 teams\\\\\", \\\\\"top_k\\\\\": \u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference Finals - Basketball-Reference.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\\\\\", \\\\\"content\\\\\": \\\\\"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown \u001b[0m\u001b[32m(\u001b[0m\u001b[32m20.8 / 5.4 / 5.0\u001b[0m\u001b[32m)\u001b[0m\u001b[32m 2024 Playoff Leaders: PTS: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m635\u001b[0m\u001b[32m)\u001b[0m\u001b[32m TRB: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m208\u001b[0m\u001b[32m)\u001b[0m\u001b[32m AST: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m178\u001b[0m\u001b[32m)\u001b[0m\u001b[32m WS: Derrick White \u001b[0m\u001b[32m(\u001b[0m\u001b[32m2.9\u001b[0m\u001b[32m)\u001b[0m\u001b[32m More playoffs info\\\\\", \\\\\"score\\\\\": 0.9310187, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\\\\\", \\\\\"content\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates & Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\\\\\", \\\\\"score\\\\\": 0.8914433, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 Playoffs: West Finals | Timberwolves \u001b[0m\u001b[32m(\u001b[0m\u001b[32m3\u001b[0m\u001b[32m)\u001b[0m\u001b[32m vs. Mavericks \u001b[0m\u001b[32m(\u001b[0m\u001b[32m5\u001b[0m\u001b[32m)\u001b[0m\u001b[32m - NBA.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nba.com/playoffs/2024/west-final\\\\\", \\\\\"content\\\\\": \\\\\"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\\\\\", \\\\\"score\\\\\": 0.8884594, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference playoff bracket - Basketnews.com\\\\\", \\\\\"url\\\\\": \\\\\"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\\\\\", \\\\\"content\\\\\": \\\\\"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\\\\\", \\\\\"score\\\\\": 0.8479807, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"NBA Finals 2024 - Celtics-Mavericks news, schedule, scores and ... - ESPN\\\\\", \\\\\"url\\\\\": \\\\\"https://www.espn.com/nba/story/_/id/39943302/nba-playoffs-2024-conference-finals-news-scores-highlights\\\\\", \\\\\"content\\\\\": \\\\\"The Boston Celtics are the 2024 NBA Champions. ... Western Conference. Final 2023-24 NBA regular-season standings. Which team left standing has the most trips to the NBA Finals? Here is a look at\\\\\", \\\\\"score\\\\\": 0.81979275, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"The teams that played in the NBA Western Conference Finals of 2024 were the Dallas Mavericks and the Minnesota Timberwolves.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
               "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"In which episode and season of South Park does Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mBSM-471\u001b[0m\u001b[32m)\u001b[0m\u001b[32m first appear? Give me the number and title.\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[1m]\u001b[0m,\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'output'\u001b[0m: \u001b[32m\"content:  tool_calls: \u001b[0m\u001b[32m[\u001b[0m\u001b[32mToolCall\u001b[0m\u001b[32m(\u001b[0m\u001b[32mcall_id\u001b[0m\u001b[32m='19bd3554-e670-4856-89d0-c63f5b016245', \u001b[0m\u001b[32mtool_name\u001b[0m\u001b[32m='bravy_search', \u001b[0m\u001b[32marguments\u001b[0m\u001b[32m=\u001b[0m\u001b[32m{\u001b[0m\u001b[32m'query': 'Bill Cosby South Park episode'\u001b[0m\u001b[32m}\u001b[0m\u001b[32m)\u001b[0m\u001b[32m]\u001b[0m\u001b[32m\"\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[1m}\u001b[0m,\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[1m{\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'input'\u001b[0m: \u001b[1m[\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"Let me check the latest sports news.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"In which episode and season of South Park does Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mBSM-471\u001b[0m\u001b[32m)\u001b[0m\u001b[32m first appear? Give me the number and title.\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"call_id\":\"19bd3554-e670-4856-89d0-c63f5b016245\",\"tool_name\":\"bravy_search\",\"arguments\":\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"query\":\"Bill Cosby South Park episode\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[1;39m]\u001b[0m\u001b[39m,\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'output'\u001b[0m\u001b[39m: \u001b[0m\u001b[32m\"content:  tool_calls: \u001b[0m\u001b[32m[\u001b[0m\u001b[32mToolCall\u001b[0m\u001b[32m(\u001b[0m\u001b[32mcall_id\u001b[0m\u001b[32m='fc0441bf-05ad-48d0-8034-4e19cb835904', \u001b[0m\u001b[32mtool_name\u001b[0m\u001b[32m=<BuiltinTool.brave_search: 'brave_search'>, \u001b[0m\u001b[32marguments\u001b[0m\u001b[32m=\u001b[0m\u001b[32m{\u001b[0m\u001b[32m'query': 'Bill Cosby South Park episode'\u001b[0m\u001b[32m}\u001b[0m\u001b[32m)\u001b[0m\u001b[32m]\u001b[0m\u001b[32m\"\u001b[0m\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1;39m}\u001b[0m\u001b[39m,\u001b[0m\n",
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+              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'input'\u001b[0m\u001b[39m: \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"call_id\":\"fc0441bf-05ad-48d0-8034-4e19cb835904\",\"tool_name\":\"brave_search\",\"arguments\":\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"query\":\"Bill Cosby South Park episode\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'output'\u001b[0m\u001b[39m: \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"tool\",\"call_id\":\"fc0441bf-05ad-48d0-8034-4e19cb835904\",\"tool_name\":\"brave_search\",\"content\":\"\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"query\\\\\": \\\\\"Bill Cosby South Park episode\\\\\", \\\\\"top_k\\\\\": \u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Bill Cosby and Taylor Swift Duet - South Park Studios\\\\\", \\\\\"url\\\\\": \\\\\"https://www.southparkstudios.com/video-clips/90r7i1/south-park-bill-cosby-and-taylor-swift-duet\\\\\", \\\\\"content\\\\\": \\\\\"01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:03 Bill Cosby and Taylor Swift Duet South ParkS18 E10 ------------------------------------------------------- The holiday special continues with Bill Cosby and Taylor Swift\\'s rendition of \\\\\\\\\\\\\"It\\'s Snowing Out There\\\\\\\\\\\\\". 01:31 #WeBelieveInYou South ParkS18 E10 -------------------------------------- With everyone watching, Kyle takes the opportunity to reach out to his brother. 01:47 Watch Your Microaggressions, Bro South ParkS19 E1 ------------------------------------------------------ Cartman\\'s plan to frame PC Principal backfires. South ParkS19 E1 -------------------------------------- After hearing that the PC people have targeted Kyle, Cartman vows to help.\\\\\", \\\\\"score\\\\\": 0.685971, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Bill Cosby is Here to See You - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/video-clips/wfot8s/south-park-bill-cosby-is-here-to-see-you\\\\\", \\\\\"content\\\\\": \\\\\"01:56 It\\'s Not About Music South ParkS18 E9 ------------------------------------------ At home, Randy sees the consequences of Lorde\\'s performance and calls the Record Producer to try and fix it. 01:24 Lorde\\'s Hologram South ParkS18 E9 -------------------------------------- The Record Producer reveals the truth about the music industry... South ParkS18 E9 --------------------------------------------- Randy catches Sharon with Tupac\\'s hologram. 01:37 I\\'ve Got Your Son, Lorde South ParkS18 E10 ----------------------------------------------- The Record Producer takes Stan and Kyle hostage. 01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:21 Lorde Is My Dad South ParkS18 E10 -------------------------------------- After trying to confront Cartman Bra, Stan finally reveals the truth about his dad.\\\\\", \\\\\"score\\\\\": 0.6643884, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mandroid\u001b[0m\u001b[32m)\u001b[0m\u001b[32m | South Park Character ... - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/wiki/Bill_Cosby_\u001b[0m\u001b[32m(\u001b[0m\u001b[32mandroid\u001b[0m\u001b[32m)\u001b[0m\u001b[32m\\\\\", \\\\\"content\\\\\": \\\\\"Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mandroid\u001b[0m\u001b[32m)\u001b[0m\u001b[32m | South Park Character / Location / User talk etc | Official South Park Studios Wiki Sent back in time to destroy Eric Cartman\\'s Dawson\\'s Creek Trapper Keeper before it manifests into an omnipotent supercomputer that can destroy all humanity, \\\\\\\\\\\\\"Bill Cosby\\\\\\\\\\\\\" is really VSM471, an android or cyborg of some kind engineered by \\'hoomans\\' in the distant future. He fails in his initial missions to infiltrate South Park Elementary\\'s 4th Grade class, destroy the Trapper Keeper or Cartman himself, but with Stan Marsh and Kyle Broflovski\\'s aid, he is able to succeed in preventing his dismal future, and painfully fades from existence. South Park and all related titles, logos and characters are trademarks of Comedy Partners.\\\\\", \\\\\"score\\\\\": 0.5052006, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"\\\\\\\\\\\\\"South Park\\\\\\\\\\\\\" Clubhouses \u001b[0m\u001b[32m(\u001b[0m\u001b[32mTV Episode 1998\u001b[0m\u001b[32m)\u001b[0m\u001b[32m - IMDb\\\\\", \\\\\"url\\\\\": \\\\\"https://www.imdb.com/title/tt0705915/characters/nm0005295\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"South Park\\\\\\\\\\\\\" Clubhouses \u001b[0m\u001b[32m(\u001b[0m\u001b[32mTV Episode 1998\u001b[0m\u001b[32m)\u001b[0m\u001b[32m - Trey Parker as Stan Marsh, Eric Cartman, Phillip, Randy Marsh, Fat Abbot, Mr. Garrison, Mr. Mackey, 3rd Fat Abbot character, Roy, Teenage Boy #1, Clyde, Bill Cosby, Teenage Boy #2 - IMDb Awards & Events Trey Parker: Stan Marsh, Eric Cartman, Phillip, Randy Marsh, Fat Abbot, Mr. Garrison, Mr. Mackey, 3rd Fat Abbot character, Roy, Teenage Boy #1, Clyde, Bill Cosby, Teenage Boy #2 Mr. Garrison : Stan, are you paying attention? Stan : Yes, Mr. Garrison. Stan Marsh : Dare. Stan Marsh : What? Release Dates | Official Sites | Company Credits | Filming & Production | Technical Specs Photo & Video User Lists Related lists from IMDb users 2024 Watched TV Shows\\\\\", \\\\\"score\\\\\": 0.4604593, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Trapper Keeper \u001b[0m\u001b[32m(\u001b[0m\u001b[32mSouth Park\u001b[0m\u001b[32m)\u001b[0m\u001b[32m - Wikipedia\\\\\", \\\\\"url\\\\\": \\\\\"https://en.wikipedia.org/wiki/Trapper_Keeper_\u001b[0m\u001b[32m(\u001b[0m\u001b[32mSouth_Park\u001b[0m\u001b[32m)\u001b[0m\u001b[32m\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" is the twelfth episode of the fourth season of the animated television series South Park, and the 60th episode of the series overall. In the episode, a man from the future wants Cartman\\'s new Trapper Keeper, while Mr. Garrison\\'s kindergarten class holds an election for class president with confusing results. 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+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"call_id\":\"8b7294ec-a83f-4798-ad8f-6bed662f08b6\",\"tool_name\":\"brave_search\",\"arguments\":\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"query\":\"NBA Western Conference Finals 2024 teams\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
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+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"The teams that played in the NBA Western Conference Finals of 2024 were the Dallas Mavericks and the Minnesota Timberwolves.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"In which episode and season of South Park does Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mBSM-471\u001b[0m\u001b[32m)\u001b[0m\u001b[32m first appear? Give me the number and title.\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
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+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"tool\",\"call_id\":\"fc0441bf-05ad-48d0-8034-4e19cb835904\",\"tool_name\":\"brave_search\",\"content\":\"\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"query\\\\\": \\\\\"Bill Cosby South Park episode\\\\\", \\\\\"top_k\\\\\": \u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Bill Cosby and Taylor Swift Duet - South Park Studios\\\\\", \\\\\"url\\\\\": \\\\\"https://www.southparkstudios.com/video-clips/90r7i1/south-park-bill-cosby-and-taylor-swift-duet\\\\\", \\\\\"content\\\\\": \\\\\"01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:03 Bill Cosby and Taylor Swift Duet South ParkS18 E10 ------------------------------------------------------- The holiday special continues with Bill Cosby and Taylor Swift\\'s rendition of \\\\\\\\\\\\\"It\\'s Snowing Out There\\\\\\\\\\\\\". 01:31 #WeBelieveInYou South ParkS18 E10 -------------------------------------- With everyone watching, Kyle takes the opportunity to reach out to his brother. 01:47 Watch Your Microaggressions, Bro South ParkS19 E1 ------------------------------------------------------ Cartman\\'s plan to frame PC Principal backfires. South ParkS19 E1 -------------------------------------- After hearing that the PC people have targeted Kyle, Cartman vows to help.\\\\\", \\\\\"score\\\\\": 0.685971, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Bill Cosby is Here to See You - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/video-clips/wfot8s/south-park-bill-cosby-is-here-to-see-you\\\\\", \\\\\"content\\\\\": \\\\\"01:56 It\\'s Not About Music South ParkS18 E9 ------------------------------------------ At home, Randy sees the consequences of Lorde\\'s performance and calls the Record Producer to try and fix it. 01:24 Lorde\\'s Hologram South ParkS18 E9 -------------------------------------- The Record Producer reveals the truth about the music industry... South ParkS18 E9 --------------------------------------------- Randy catches Sharon with Tupac\\'s hologram. 01:37 I\\'ve Got Your Son, Lorde South ParkS18 E10 ----------------------------------------------- The Record Producer takes Stan and Kyle hostage. 01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:21 Lorde Is My Dad South ParkS18 E10 -------------------------------------- After trying to confront Cartman Bra, Stan finally reveals the truth about his dad.\\\\\", \\\\\"score\\\\\": 0.6643884, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mandroid\u001b[0m\u001b[32m)\u001b[0m\u001b[32m | South Park Character ... - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/wiki/Bill_Cosby_\u001b[0m\u001b[32m(\u001b[0m\u001b[32mandroid\u001b[0m\u001b[32m)\u001b[0m\u001b[32m\\\\\", \\\\\"content\\\\\": \\\\\"Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mandroid\u001b[0m\u001b[32m)\u001b[0m\u001b[32m | South Park Character / Location / User talk etc | Official South Park Studios Wiki Sent back in time to destroy Eric Cartman\\'s Dawson\\'s Creek Trapper Keeper before it manifests into an omnipotent supercomputer that can destroy all humanity, \\\\\\\\\\\\\"Bill Cosby\\\\\\\\\\\\\" is really VSM471, an android or cyborg of some kind engineered by \\'hoomans\\' in the distant future. He fails in his initial missions to infiltrate South Park Elementary\\'s 4th Grade class, destroy the Trapper Keeper or Cartman himself, but with Stan Marsh and Kyle Broflovski\\'s aid, he is able to succeed in preventing his dismal future, and painfully fades from existence. South Park and all related titles, logos and characters are trademarks of Comedy Partners.\\\\\", \\\\\"score\\\\\": 0.5052006, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"\\\\\\\\\\\\\"South Park\\\\\\\\\\\\\" Clubhouses \u001b[0m\u001b[32m(\u001b[0m\u001b[32mTV Episode 1998\u001b[0m\u001b[32m)\u001b[0m\u001b[32m - IMDb\\\\\", \\\\\"url\\\\\": \\\\\"https://www.imdb.com/title/tt0705915/characters/nm0005295\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"South Park\\\\\\\\\\\\\" Clubhouses \u001b[0m\u001b[32m(\u001b[0m\u001b[32mTV Episode 1998\u001b[0m\u001b[32m)\u001b[0m\u001b[32m - Trey Parker as Stan Marsh, Eric Cartman, Phillip, Randy Marsh, Fat Abbot, Mr. Garrison, Mr. Mackey, 3rd Fat Abbot character, Roy, Teenage Boy #1, Clyde, Bill Cosby, Teenage Boy #2 - IMDb Awards & Events Trey Parker: Stan Marsh, Eric Cartman, Phillip, Randy Marsh, Fat Abbot, Mr. Garrison, Mr. Mackey, 3rd Fat Abbot character, Roy, Teenage Boy #1, Clyde, Bill Cosby, Teenage Boy #2 Mr. Garrison : Stan, are you paying attention? Stan : Yes, Mr. Garrison. Stan Marsh : Dare. Stan Marsh : What? Release Dates | Official Sites | Company Credits | Filming & Production | Technical Specs Photo & Video User Lists Related lists from IMDb users 2024 Watched TV Shows\\\\\", \\\\\"score\\\\\": 0.4604593, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Trapper Keeper \u001b[0m\u001b[32m(\u001b[0m\u001b[32mSouth Park\u001b[0m\u001b[32m)\u001b[0m\u001b[32m - Wikipedia\\\\\", \\\\\"url\\\\\": \\\\\"https://en.wikipedia.org/wiki/Trapper_Keeper_\u001b[0m\u001b[32m(\u001b[0m\u001b[32mSouth_Park\u001b[0m\u001b[32m)\u001b[0m\u001b[32m\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" is the twelfth episode of the fourth season of the animated television series South Park, and the 60th episode of the series overall. In the episode, a man from the future wants Cartman\\'s new Trapper Keeper, while Mr. Garrison\\'s kindergarten class holds an election for class president with confusing results. It is one of the many South Park episodes that parodies a current event.\u001b[0m\u001b[32m[\u001b[0m\u001b[32m1\u001b[0m\u001b[32m]\u001b[0m\u001b[32m The main plot of the episode involving the Trapper Keeper was written before the election,\u001b[0m\u001b[32m[\u001b[0m\u001b[32m1\u001b[0m\u001b[32m]\u001b[0m\u001b[32m but the subplot is a parody of the controversy surrounding the election\\'s outcome.\u001b[0m\u001b[32m[\u001b[0m\u001b[32m2\u001b[0m\u001b[32m]\u001b[0m\u001b[32m \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" did not originally feature the election storyline, only a subplot about Ike attending his first day of kindergarten.\u001b[0m\u001b[32m[\u001b[0m\u001b[32m3\u001b[0m\u001b[32m]\u001b[0m\u001b[32m \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" Full episode at South Park Studios\\\\\", \\\\\"score\\\\\": 0.3839421, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[1;39m]\u001b[0m\u001b[39m,\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'output'\u001b[0m\u001b[39m: \u001b[0m\u001b[32m'content: Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mBSM-471\u001b[0m\u001b[32m)\u001b[0m\u001b[32m first appears in the episode \"Trapper Keeper\" \u001b[0m\u001b[32m(\u001b[0m\u001b[32mSeason 4, Episode 12\u001b[0m\u001b[32m)\u001b[0m\u001b[32m of South Park. tool_calls: \u001b[0m\u001b[32m[\u001b[0m\u001b[32m]\u001b[0m\u001b[32m'\u001b[0m\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1;39m}\u001b[0m\u001b[39m,\u001b[0m\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1;39m{\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'input'\u001b[0m\u001b[39m: \u001b[0m\u001b[1;39m[\u001b[0m\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"call_id\":\"8b7294ec-a83f-4798-ad8f-6bed662f08b6\",\"tool_name\":\"brave_search\",\"arguments\":\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"query\":\"NBA Western Conference Finals 2024 teams\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"tool\",\"call_id\":\"8b7294ec-a83f-4798-ad8f-6bed662f08b6\",\"tool_name\":\"brave_search\",\"content\":\"\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"query\\\\\": \\\\\"NBA Western Conference Finals 2024 teams\\\\\", \\\\\"top_k\\\\\": \u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference Finals - Basketball-Reference.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\\\\\", \\\\\"content\\\\\": \\\\\"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown \u001b[0m\u001b[32m(\u001b[0m\u001b[32m20.8 / 5.4 / 5.0\u001b[0m\u001b[32m)\u001b[0m\u001b[32m 2024 Playoff Leaders: PTS: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m635\u001b[0m\u001b[32m)\u001b[0m\u001b[32m TRB: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m208\u001b[0m\u001b[32m)\u001b[0m\u001b[32m AST: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m178\u001b[0m\u001b[32m)\u001b[0m\u001b[32m WS: Derrick White \u001b[0m\u001b[32m(\u001b[0m\u001b[32m2.9\u001b[0m\u001b[32m)\u001b[0m\u001b[32m More playoffs info\\\\\", \\\\\"score\\\\\": 0.9310187, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\\\\\", \\\\\"content\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates & Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\\\\\", \\\\\"score\\\\\": 0.8914433, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 Playoffs: West Finals | Timberwolves \u001b[0m\u001b[32m(\u001b[0m\u001b[32m3\u001b[0m\u001b[32m)\u001b[0m\u001b[32m vs. Mavericks \u001b[0m\u001b[32m(\u001b[0m\u001b[32m5\u001b[0m\u001b[32m)\u001b[0m\u001b[32m - NBA.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nba.com/playoffs/2024/west-final\\\\\", \\\\\"content\\\\\": \\\\\"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\\\\\", \\\\\"score\\\\\": 0.8884594, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference playoff bracket - Basketnews.com\\\\\", \\\\\"url\\\\\": \\\\\"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\\\\\", \\\\\"content\\\\\": \\\\\"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\\\\\", \\\\\"score\\\\\": 0.8479807, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"NBA Finals 2024 - Celtics-Mavericks news, schedule, scores and ... - ESPN\\\\\", \\\\\"url\\\\\": \\\\\"https://www.espn.com/nba/story/_/id/39943302/nba-playoffs-2024-conference-finals-news-scores-highlights\\\\\", \\\\\"content\\\\\": \\\\\"The Boston Celtics are the 2024 NBA Champions. ... Western Conference. Final 2023-24 NBA regular-season standings. Which team left standing has the most trips to the NBA Finals? Here is a look at\\\\\", \\\\\"score\\\\\": 0.81979275, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"The teams that played in the NBA Western Conference Finals of 2024 were the Dallas Mavericks and the Minnesota Timberwolves.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"In which episode and season of South Park does Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mBSM-471\u001b[0m\u001b[32m)\u001b[0m\u001b[32m first appear? Give me the number and title.\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"call_id\":\"fc0441bf-05ad-48d0-8034-4e19cb835904\",\"tool_name\":\"brave_search\",\"arguments\":\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"query\":\"Bill Cosby South Park episode\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"tool\",\"call_id\":\"fc0441bf-05ad-48d0-8034-4e19cb835904\",\"tool_name\":\"brave_search\",\"content\":\"\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"query\\\\\": \\\\\"Bill Cosby South Park episode\\\\\", \\\\\"top_k\\\\\": \u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Bill Cosby and Taylor Swift Duet - South Park Studios\\\\\", \\\\\"url\\\\\": \\\\\"https://www.southparkstudios.com/video-clips/90r7i1/south-park-bill-cosby-and-taylor-swift-duet\\\\\", \\\\\"content\\\\\": \\\\\"01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:03 Bill Cosby and Taylor Swift Duet South ParkS18 E10 ------------------------------------------------------- The holiday special continues with Bill Cosby and Taylor Swift\\'s rendition of \\\\\\\\\\\\\"It\\'s Snowing Out There\\\\\\\\\\\\\". 01:31 #WeBelieveInYou South ParkS18 E10 -------------------------------------- With everyone watching, Kyle takes the opportunity to reach out to his brother. 01:47 Watch Your Microaggressions, Bro South ParkS19 E1 ------------------------------------------------------ Cartman\\'s plan to frame PC Principal backfires. South ParkS19 E1 -------------------------------------- After hearing that the PC people have targeted Kyle, Cartman vows to help.\\\\\", \\\\\"score\\\\\": 0.685971, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Bill Cosby is Here to See You - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/video-clips/wfot8s/south-park-bill-cosby-is-here-to-see-you\\\\\", \\\\\"content\\\\\": \\\\\"01:56 It\\'s Not About Music South ParkS18 E9 ------------------------------------------ At home, Randy sees the consequences of Lorde\\'s performance and calls the Record Producer to try and fix it. 01:24 Lorde\\'s Hologram South ParkS18 E9 -------------------------------------- The Record Producer reveals the truth about the music industry... South ParkS18 E9 --------------------------------------------- Randy catches Sharon with Tupac\\'s hologram. 01:37 I\\'ve Got Your Son, Lorde South ParkS18 E10 ----------------------------------------------- The Record Producer takes Stan and Kyle hostage. 01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:21 Lorde Is My Dad South ParkS18 E10 -------------------------------------- After trying to confront Cartman Bra, Stan finally reveals the truth about his dad.\\\\\", \\\\\"score\\\\\": 0.6643884, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mandroid\u001b[0m\u001b[32m)\u001b[0m\u001b[32m | South Park Character ... - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/wiki/Bill_Cosby_\u001b[0m\u001b[32m(\u001b[0m\u001b[32mandroid\u001b[0m\u001b[32m)\u001b[0m\u001b[32m\\\\\", \\\\\"content\\\\\": \\\\\"Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mandroid\u001b[0m\u001b[32m)\u001b[0m\u001b[32m | South Park Character / Location / User talk etc | Official South Park Studios Wiki Sent back in time to destroy Eric Cartman\\'s Dawson\\'s Creek Trapper Keeper before it manifests into an omnipotent supercomputer that can destroy all humanity, \\\\\\\\\\\\\"Bill Cosby\\\\\\\\\\\\\" is really VSM471, an android or cyborg of some kind engineered by \\'hoomans\\' in the distant future. He fails in his initial missions to infiltrate South Park Elementary\\'s 4th Grade class, destroy the Trapper Keeper or Cartman himself, but with Stan Marsh and Kyle Broflovski\\'s aid, he is able to succeed in preventing his dismal future, and painfully fades from existence. South Park and all related titles, logos and characters are trademarks of Comedy Partners.\\\\\", \\\\\"score\\\\\": 0.5052006, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"\\\\\\\\\\\\\"South Park\\\\\\\\\\\\\" Clubhouses \u001b[0m\u001b[32m(\u001b[0m\u001b[32mTV Episode 1998\u001b[0m\u001b[32m)\u001b[0m\u001b[32m - IMDb\\\\\", \\\\\"url\\\\\": \\\\\"https://www.imdb.com/title/tt0705915/characters/nm0005295\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"South Park\\\\\\\\\\\\\" Clubhouses \u001b[0m\u001b[32m(\u001b[0m\u001b[32mTV Episode 1998\u001b[0m\u001b[32m)\u001b[0m\u001b[32m - Trey Parker as Stan Marsh, Eric Cartman, Phillip, Randy Marsh, Fat Abbot, Mr. Garrison, Mr. Mackey, 3rd Fat Abbot character, Roy, Teenage Boy #1, Clyde, Bill Cosby, Teenage Boy #2 - IMDb Awards & Events Trey Parker: Stan Marsh, Eric Cartman, Phillip, Randy Marsh, Fat Abbot, Mr. Garrison, Mr. Mackey, 3rd Fat Abbot character, Roy, Teenage Boy #1, Clyde, Bill Cosby, Teenage Boy #2 Mr. Garrison : Stan, are you paying attention? Stan : Yes, Mr. Garrison. Stan Marsh : Dare. Stan Marsh : What? Release Dates | Official Sites | Company Credits | Filming & Production | Technical Specs Photo & Video User Lists Related lists from IMDb users 2024 Watched TV Shows\\\\\", \\\\\"score\\\\\": 0.4604593, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Trapper Keeper \u001b[0m\u001b[32m(\u001b[0m\u001b[32mSouth Park\u001b[0m\u001b[32m)\u001b[0m\u001b[32m - Wikipedia\\\\\", \\\\\"url\\\\\": \\\\\"https://en.wikipedia.org/wiki/Trapper_Keeper_\u001b[0m\u001b[32m(\u001b[0m\u001b[32mSouth_Park\u001b[0m\u001b[32m)\u001b[0m\u001b[32m\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" is the twelfth episode of the fourth season of the animated television series South Park, and the 60th episode of the series overall. In the episode, a man from the future wants Cartman\\'s new Trapper Keeper, while Mr. Garrison\\'s kindergarten class holds an election for class president with confusing results. It is one of the many South Park episodes that parodies a current event.\u001b[0m\u001b[32m[\u001b[0m\u001b[32m1\u001b[0m\u001b[32m]\u001b[0m\u001b[32m The main plot of the episode involving the Trapper Keeper was written before the election,\u001b[0m\u001b[32m[\u001b[0m\u001b[32m1\u001b[0m\u001b[32m]\u001b[0m\u001b[32m but the subplot is a parody of the controversy surrounding the election\\'s outcome.\u001b[0m\u001b[32m[\u001b[0m\u001b[32m2\u001b[0m\u001b[32m]\u001b[0m\u001b[32m \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" did not originally feature the election storyline, only a subplot about Ike attending his first day of kindergarten.\u001b[0m\u001b[32m[\u001b[0m\u001b[32m3\u001b[0m\u001b[32m]\u001b[0m\u001b[32m \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" Full episode at South Park Studios\\\\\", \\\\\"score\\\\\": 0.3839421, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mBSM-471\u001b[0m\u001b[32m)\u001b[0m\u001b[32m first appears in the episode \\\\\"Trapper Keeper\\\\\" \u001b[0m\u001b[32m(\u001b[0m\u001b[32mSeason 4, Episode 12\u001b[0m\u001b[32m)\u001b[0m\u001b[32m of South Park.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
               "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"What is the British-American kickboxer Andrew Tate\\'s kickboxing name?\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[1m]\u001b[0m,\n",
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+              "\u001b[2;32m│   │   \u001b[0m\u001b[1;39m]\u001b[0m\u001b[39m,\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'output'\u001b[0m\u001b[39m: \u001b[0m\u001b[32m\"content:  tool_calls: \u001b[0m\u001b[32m[\u001b[0m\u001b[32mToolCall\u001b[0m\u001b[32m(\u001b[0m\u001b[32mcall_id\u001b[0m\u001b[32m='79276f65-3600-489d-ab41-d5a71dcaf075', \u001b[0m\u001b[32mtool_name\u001b[0m\u001b[32m=<BuiltinTool.brave_search: 'brave_search'\u001b[0m\u001b[32m>\u001b[0m\u001b[32m, \u001b[0m\u001b[32marguments\u001b[0m\u001b[32m=\u001b[0m\u001b[32m{\u001b[0m\u001b[32m'query': 'Andrew Tate kickboxing name'\u001b[0m\u001b[32m}\u001b[0m\u001b[32m)\u001b[0m\u001b[32m]\u001b[0m\u001b[32m\"\u001b[0m\n",
               "\u001b[2;32m│   \u001b[0m\u001b[1m}\u001b[0m,\n",
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-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'input'\u001b[0m: \u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"call_id\":\"526045a7-5f51-40fb-ba97-5ad29610e511\",\"tool_name\":\"brave_search\",\"arguments\":\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"query\":\"Andrew Tate kickboxing name\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'output'\u001b[0m: \u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"ipython\",\"call_id\":\"526045a7-5f51-40fb-ba97-5ad29610e511\",\"tool_name\":\"brave_search\",\"content\":\"\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"query\\\\\": \\\\\"Andrew Tate kickboxing name\\\\\", \\\\\"top_k\\\\\": \u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Andrew Tate kickboxing record: How many championships ... - FirstSportz\\\\\", \\\\\"url\\\\\": \\\\\"https://firstsportz.com/mma-how-many-championships-does-andrew-tate-have/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate\\'s Kickboxing career. During his kickboxing career, he used the nickname \\\\\\\\\\\\\"King Cobra,\\\\\\\\\\\\\" which he currently uses as his Twitter name. Tate had an unorthodox style of movement inside the ring. He kept his hands down most of the time and relied on quick jabs and an overhand right to land significant strikes.\\\\\", \\\\\"score\\\\\": 0.9996244, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Andrew Tate: Kickboxing Record, Facts, Height, Weight, Age, Biography\\\\\", \\\\\"url\\\\\": \\\\\"https://www.lowkickmma.com/andrew-tate-kickboxing-record-facts-height-weight-age-biography/\\\\\", \\\\\"content\\\\\": \\\\\"Birth Name: Emory Andrew Tate III: Date of Birth: 1 December 1986: Place of Birth: Washington, D.C., U.S. ... In his professional kickboxing career, Andrew Tate won 32 of his fights by knockout.\\\\\", \\\\\"score\\\\\": 0.99909246, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Who is Andrew Tate? MMA, kickboxing record and controversies of fighter ...\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportingnews.com/us/kickboxing/news/andrew-tate-mma-kickboxing-record-controversies/u50waalc9cfz7krjg9wnyb7p\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate kickboxing record After launching his career as a 20-year-old in 2007, Tate built a formidable kickboxing record that included 76 wins across 85 fights in more than 13 years in the ring.\\\\\", \\\\\"score\\\\\": 0.9976586, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"About Andrew Tate: A Journey from Champion to Controversy\\\\\", \\\\\"url\\\\\": \\\\\"https://reachmorpheus.com/andrew-tate/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate\\'s kickboxing career, beginning in 2005, is a tale of determination and skill. He quickly made a name for himself in the sport, rising through the ranks with his unique fighting style and strategic approach, honed by his chess-playing background.\\\\\", \\\\\"score\\\\\": 0.99701905, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Andrew Tate Bio, Wiki, Net Worth, Age, Family, MMA Career - Next Biography\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nextbiography.com/andrew-tate/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate Age. Andrew Tate is 36 years old as of 2023, born on December 1, 1986, in Washington, DC. By his mid-thirties, Andrew Tate has become an esteemed figure in the world of kickboxing, showcasing remarkable expertise and experience in the sport. Early Life of Andrew Tate. Andrew Tate was born on 01 December 1986 to an African-American\\\\\", \\\\\"score\\\\\": 0.99368566, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'input'\u001b[0m: \u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"call_id\":\"79276f65-3600-489d-ab41-d5a71dcaf075\",\"tool_name\":\"brave_search\",\"arguments\":\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"query\":\"Andrew Tate kickboxing name\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'output'\u001b[0m: \u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"tool\",\"call_id\":\"79276f65-3600-489d-ab41-d5a71dcaf075\",\"tool_name\":\"brave_search\",\"content\":\"\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"query\\\\\": \\\\\"Andrew Tate kickboxing name\\\\\", \\\\\"top_k\\\\\": \u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Andrew Tate Age, Height, Weight, Family, Parents, Biography, Net Worth\\\\\", \\\\\"url\\\\\": \\\\\"https://biographywallah.com/andrew-tate-biography/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate Age, Height, Weight, Family, Parents, Biography, Net Worth \\\\\\\\u00bb Biography Wallah Andrew Tate Age, Height, Weight, Family, Parents, Biography, Net Worth Andrew Tate Biography NameAndrew TateReal nameEmory Andrew Tate IIIProfession \\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0Kickboxer, Commentator and BusinessmanDate of birth14 December 1986BirthplaceWashington D.C., United StatesAndrew Tate Age37 years old \u001b[0m\u001b[32m(\u001b[0m\u001b[32mas of 2024\u001b[0m\u001b[32m)\u001b[0m\u001b[32mNationalityBritish-AmericanZodiac SignSagittariusGenderMaleSchoolLocal School in Washington D.C., United StatesGirlfriend/SpouseNaghel GeorgianaSexual OrientationStraightNet worth$1000 Million Who is Andrew Tate? Andrew Tate is a British-American former professional kickboxing world champion businessman and media personality, who fought in the cruiserweight and super cruiserweight divisions. Andrew Tate Age Andrew Tate was born on 1 December 1986 and is 37 years old. Andrew Tate\\\\\\\\u2019s Net Worth What is the net worth of Andrew Tate? Where is Andrew Tate from? How old is Andrew Tate?\\\\\", \\\\\"score\\\\\": 0.80698997, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"The Life Of Andrew Tate \u001b[0m\u001b[32m(\u001b[0m\u001b[32mBy Andrew Tate Himself ... - Sidekick Boxing\\\\\", \\\\\"url\\\\\": \\\\\"https://sidekickboxing.co.uk/the-life-of-andrew-king-cobra-tate/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate is a British-American former professional kickboxing world champion who fought in the cruiserweight and super cruiserweight divisions. Andrew Tate\\\\\\\\u2019s Kickboxing Career Andrew Tate in the Big Brother house Andrew Tate\\\\\\\\u2019s Kickboxing World Titles and his Sidekick boxing gloves Andrew Tate After Kickboxing Andrew Tate and his brother Tristan moved to Romania to set up their empire of businesses including trading in Bitcoin, Hustlers University, CobraTate.com, The Real World, and The War Room. From being a 4x kickboxing world champion to becoming the world\\\\\\\\u2019s most Googled man in the world with a private jet and over 33 cars, Andrew Tate\\\\\\\\u2019s life has been full of adventure.\\\\\", \\\\\"score\\\\\": 0.78194773, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Andrew Tate \u001b[0m\u001b[32m(\u001b[0m\u001b[32m\\\\\\\\\\\\\"King Cobra\\\\\\\\\\\\\"\u001b[0m\u001b[32m)\u001b[0m\u001b[32m | MMA Fighter Page - Tapology\\\\\", \\\\\"url\\\\\": \\\\\"https://www.tapology.com/fightcenter/fighters/72139-andrew-tate\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate \u001b[0m\u001b[32m(\u001b[0m\u001b[32m\\\\\\\\\\\\\"King Cobra\\\\\\\\\\\\\"\u001b[0m\u001b[32m)\u001b[0m\u001b[32m | MMA Fighter Page | Tapology Andrew \\\\\\\\\\\\\"King Cobra\\\\\\\\\\\\\" Tate Andrew Tate Name: Andrew Tate Height: 6\\'1\\\\\\\\\\\\\" \u001b[0m\u001b[32m(\u001b[0m\u001b[32m185cm\u001b[0m\u001b[32m)\u001b[0m\u001b[32m | Reach: Andrew Tate is ineligible for Tapology\\'s regional MMA rankings due to inactivity. Fighters must have at least one completed MMA bout in the past two years to be ranked. Andrew Tate MMA Fight Record Former top-ranked UFC fighter has called out Andrew Tate for having a paper title when it comes to combat... Andrew Tate \\\\\\\\u2022 All the biggest upcoming MMA & Boxing fights | UFC Fight Night | 02.01.2025, 12:00 PM ET | MMA Junkie: UFC Fight Night 249 video: Nine stoppages to open the year?! MMA Mania: Prochazka Vs. Hill: Odds, Full Fight Preview & Prediction\\\\\", \\\\\"score\\\\\": 0.6999322, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"About Andrew Tate: A Journey from Champion to Controversy\\\\\", \\\\\"url\\\\\": \\\\\"https://reachmorpheus.com/andrew-tate/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate\\'s kickboxing career, beginning in 2005, is a tale of determination and skill. He quickly made a name for himself in the sport, rising through the ranks with his unique fighting style and strategic approach, honed by his chess-playing background.\\\\\", \\\\\"score\\\\\": 0.6490677, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Andrew Tate\\'s Kickboxing Career & Biography - MMA Full Contact\\\\\", \\\\\"url\\\\\": \\\\\"https://www.mmafullcontact.com/andrew-tate-kickboxing/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate\\'s Kickboxing Career & Biography - MMA Full Contact Andrew Tate\\\\\\\\u2019s Kickboxing Career & Biography 2 Notable Opponents and Fights in Andrew Tate\\\\\\\\u2019s Kickboxing Career 4 Will Andrew Tate fight KSI? Notable Opponents and Fights in Andrew Tate\\\\\\\\u2019s Kickboxing Career Will Andrew Tate fight KSI? Similarly, Andrew Tate, known for his successful kickboxing career, has also shown interest in a potential fight with KSI. In conclusion, while there\\\\\\\\u2019s been plenty of interest and discussion about a potential boxing match between KSI and Andrew Tate, no official confirmation has been made as of now. With KSI\\\\\\\\u2019s upcoming match and Tate\\\\\\\\u2019s current personal circumstances, fans and followers of both personalities will have to wait for more updates on this potential fight.\\\\\", \\\\\"score\\\\\": 0.53050464, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\n",
               "\u001b[2;32m│   \u001b[0m\u001b[1m}\u001b[0m,\n",
               "\u001b[2;32m│   \u001b[0m\u001b[1m{\u001b[0m\n",
               "\u001b[2;32m│   │   \u001b[0m\u001b[32m'input'\u001b[0m: \u001b[1m[\u001b[0m\n",
               "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
               "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"Let me check the latest sports news.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
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+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"tool\",\"call_id\":\"8b7294ec-a83f-4798-ad8f-6bed662f08b6\",\"tool_name\":\"brave_search\",\"content\":\"\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"query\\\\\": \\\\\"NBA Western Conference Finals 2024 teams\\\\\", \\\\\"top_k\\\\\": \u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference Finals - Basketball-Reference.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\\\\\", \\\\\"content\\\\\": \\\\\"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown \u001b[0m\u001b[32m(\u001b[0m\u001b[32m20.8 / 5.4 / 5.0\u001b[0m\u001b[32m)\u001b[0m\u001b[32m 2024 Playoff Leaders: PTS: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m635\u001b[0m\u001b[32m)\u001b[0m\u001b[32m TRB: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m208\u001b[0m\u001b[32m)\u001b[0m\u001b[32m AST: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m178\u001b[0m\u001b[32m)\u001b[0m\u001b[32m WS: Derrick White \u001b[0m\u001b[32m(\u001b[0m\u001b[32m2.9\u001b[0m\u001b[32m)\u001b[0m\u001b[32m More playoffs info\\\\\", \\\\\"score\\\\\": 0.9310187, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\\\\\", \\\\\"content\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates & Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\\\\\", \\\\\"score\\\\\": 0.8914433, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 Playoffs: West Finals | Timberwolves \u001b[0m\u001b[32m(\u001b[0m\u001b[32m3\u001b[0m\u001b[32m)\u001b[0m\u001b[32m vs. Mavericks \u001b[0m\u001b[32m(\u001b[0m\u001b[32m5\u001b[0m\u001b[32m)\u001b[0m\u001b[32m - NBA.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nba.com/playoffs/2024/west-final\\\\\", \\\\\"content\\\\\": \\\\\"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\\\\\", \\\\\"score\\\\\": 0.8884594, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference playoff bracket - Basketnews.com\\\\\", \\\\\"url\\\\\": \\\\\"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\\\\\", \\\\\"content\\\\\": \\\\\"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\\\\\", \\\\\"score\\\\\": 0.8479807, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"NBA Finals 2024 - Celtics-Mavericks news, schedule, scores and ... - ESPN\\\\\", \\\\\"url\\\\\": \\\\\"https://www.espn.com/nba/story/_/id/39943302/nba-playoffs-2024-conference-finals-news-scores-highlights\\\\\", \\\\\"content\\\\\": \\\\\"The Boston Celtics are the 2024 NBA Champions. ... Western Conference. Final 2023-24 NBA regular-season standings. Which team left standing has the most trips to the NBA Finals? Here is a look at\\\\\", \\\\\"score\\\\\": 0.81979275, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"The teams that played in the NBA Western Conference Finals of 2024 were the Dallas Mavericks and the Minnesota Timberwolves.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
               "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"In which episode and season of South Park does Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mBSM-471\u001b[0m\u001b[32m)\u001b[0m\u001b[32m first appear? Give me the number and title.\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"call_id\":\"19bd3554-e670-4856-89d0-c63f5b016245\",\"tool_name\":\"bravy_search\",\"arguments\":\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"query\":\"Bill Cosby South Park episode\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"call_id\":\"fc0441bf-05ad-48d0-8034-4e19cb835904\",\"tool_name\":\"brave_search\",\"arguments\":\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"query\":\"Bill Cosby South Park episode\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"tool\",\"call_id\":\"fc0441bf-05ad-48d0-8034-4e19cb835904\",\"tool_name\":\"brave_search\",\"content\":\"\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"query\\\\\": \\\\\"Bill Cosby South Park episode\\\\\", \\\\\"top_k\\\\\": \u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Bill Cosby and Taylor Swift Duet - South Park Studios\\\\\", \\\\\"url\\\\\": \\\\\"https://www.southparkstudios.com/video-clips/90r7i1/south-park-bill-cosby-and-taylor-swift-duet\\\\\", \\\\\"content\\\\\": \\\\\"01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:03 Bill Cosby and Taylor Swift Duet South ParkS18 E10 ------------------------------------------------------- The holiday special continues with Bill Cosby and Taylor Swift\\'s rendition of \\\\\\\\\\\\\"It\\'s Snowing Out There\\\\\\\\\\\\\". 01:31 #WeBelieveInYou South ParkS18 E10 -------------------------------------- With everyone watching, Kyle takes the opportunity to reach out to his brother. 01:47 Watch Your Microaggressions, Bro South ParkS19 E1 ------------------------------------------------------ Cartman\\'s plan to frame PC Principal backfires. South ParkS19 E1 -------------------------------------- After hearing that the PC people have targeted Kyle, Cartman vows to help.\\\\\", \\\\\"score\\\\\": 0.685971, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Bill Cosby is Here to See You - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/video-clips/wfot8s/south-park-bill-cosby-is-here-to-see-you\\\\\", \\\\\"content\\\\\": \\\\\"01:56 It\\'s Not About Music South ParkS18 E9 ------------------------------------------ At home, Randy sees the consequences of Lorde\\'s performance and calls the Record Producer to try and fix it. 01:24 Lorde\\'s Hologram South ParkS18 E9 -------------------------------------- The Record Producer reveals the truth about the music industry... South ParkS18 E9 --------------------------------------------- Randy catches Sharon with Tupac\\'s hologram. 01:37 I\\'ve Got Your Son, Lorde South ParkS18 E10 ----------------------------------------------- The Record Producer takes Stan and Kyle hostage. 01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:21 Lorde Is My Dad South ParkS18 E10 -------------------------------------- After trying to confront Cartman Bra, Stan finally reveals the truth about his dad.\\\\\", \\\\\"score\\\\\": 0.6643884, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mandroid\u001b[0m\u001b[32m)\u001b[0m\u001b[32m | South Park Character ... - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/wiki/Bill_Cosby_\u001b[0m\u001b[32m(\u001b[0m\u001b[32mandroid\u001b[0m\u001b[32m)\u001b[0m\u001b[32m\\\\\", \\\\\"content\\\\\": \\\\\"Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mandroid\u001b[0m\u001b[32m)\u001b[0m\u001b[32m | South Park Character / Location / User talk etc | Official South Park Studios Wiki Sent back in time to destroy Eric Cartman\\'s Dawson\\'s Creek Trapper Keeper before it manifests into an omnipotent supercomputer that can destroy all humanity, \\\\\\\\\\\\\"Bill Cosby\\\\\\\\\\\\\" is really VSM471, an android or cyborg of some kind engineered by \\'hoomans\\' in the distant future. He fails in his initial missions to infiltrate South Park Elementary\\'s 4th Grade class, destroy the Trapper Keeper or Cartman himself, but with Stan Marsh and Kyle Broflovski\\'s aid, he is able to succeed in preventing his dismal future, and painfully fades from existence. South Park and all related titles, logos and characters are trademarks of Comedy Partners.\\\\\", \\\\\"score\\\\\": 0.5052006, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"\\\\\\\\\\\\\"South Park\\\\\\\\\\\\\" Clubhouses \u001b[0m\u001b[32m(\u001b[0m\u001b[32mTV Episode 1998\u001b[0m\u001b[32m)\u001b[0m\u001b[32m - IMDb\\\\\", \\\\\"url\\\\\": \\\\\"https://www.imdb.com/title/tt0705915/characters/nm0005295\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"South Park\\\\\\\\\\\\\" Clubhouses \u001b[0m\u001b[32m(\u001b[0m\u001b[32mTV Episode 1998\u001b[0m\u001b[32m)\u001b[0m\u001b[32m - Trey Parker as Stan Marsh, Eric Cartman, Phillip, Randy Marsh, Fat Abbot, Mr. Garrison, Mr. Mackey, 3rd Fat Abbot character, Roy, Teenage Boy #1, Clyde, Bill Cosby, Teenage Boy #2 - IMDb Awards & Events Trey Parker: Stan Marsh, Eric Cartman, Phillip, Randy Marsh, Fat Abbot, Mr. Garrison, Mr. Mackey, 3rd Fat Abbot character, Roy, Teenage Boy #1, Clyde, Bill Cosby, Teenage Boy #2 Mr. Garrison : Stan, are you paying attention? Stan : Yes, Mr. Garrison. Stan Marsh : Dare. Stan Marsh : What? Release Dates | Official Sites | Company Credits | Filming & Production | Technical Specs Photo & Video User Lists Related lists from IMDb users 2024 Watched TV Shows\\\\\", \\\\\"score\\\\\": 0.4604593, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Trapper Keeper \u001b[0m\u001b[32m(\u001b[0m\u001b[32mSouth Park\u001b[0m\u001b[32m)\u001b[0m\u001b[32m - Wikipedia\\\\\", \\\\\"url\\\\\": \\\\\"https://en.wikipedia.org/wiki/Trapper_Keeper_\u001b[0m\u001b[32m(\u001b[0m\u001b[32mSouth_Park\u001b[0m\u001b[32m)\u001b[0m\u001b[32m\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" is the twelfth episode of the fourth season of the animated television series South Park, and the 60th episode of the series overall. In the episode, a man from the future wants Cartman\\'s new Trapper Keeper, while Mr. Garrison\\'s kindergarten class holds an election for class president with confusing results. It is one of the many South Park episodes that parodies a current event.\u001b[0m\u001b[32m[\u001b[0m\u001b[32m1\u001b[0m\u001b[32m]\u001b[0m\u001b[32m The main plot of the episode involving the Trapper Keeper was written before the election,\u001b[0m\u001b[32m[\u001b[0m\u001b[32m1\u001b[0m\u001b[32m]\u001b[0m\u001b[32m but the subplot is a parody of the controversy surrounding the election\\'s outcome.\u001b[0m\u001b[32m[\u001b[0m\u001b[32m2\u001b[0m\u001b[32m]\u001b[0m\u001b[32m \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" did not originally feature the election storyline, only a subplot about Ike attending his first day of kindergarten.\u001b[0m\u001b[32m[\u001b[0m\u001b[32m3\u001b[0m\u001b[32m]\u001b[0m\u001b[32m \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" Full episode at South Park Studios\\\\\", \\\\\"score\\\\\": 0.3839421, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mBSM-471\u001b[0m\u001b[32m)\u001b[0m\u001b[32m first appears in the episode \\\\\"Trapper Keeper\\\\\" \u001b[0m\u001b[32m(\u001b[0m\u001b[32mSeason 4, Episode 12\u001b[0m\u001b[32m)\u001b[0m\u001b[32m of South Park.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
               "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"What is the British-American kickboxer Andrew Tate\\'s kickboxing name?\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"call_id\":\"526045a7-5f51-40fb-ba97-5ad29610e511\",\"tool_name\":\"brave_search\",\"arguments\":\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"query\":\"Andrew Tate kickboxing name\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"ipython\",\"call_id\":\"526045a7-5f51-40fb-ba97-5ad29610e511\",\"tool_name\":\"brave_search\",\"content\":\"\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"query\\\\\": \\\\\"Andrew Tate kickboxing name\\\\\", \\\\\"top_k\\\\\": \u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Andrew Tate kickboxing record: How many championships ... - FirstSportz\\\\\", \\\\\"url\\\\\": \\\\\"https://firstsportz.com/mma-how-many-championships-does-andrew-tate-have/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate\\'s Kickboxing career. During his kickboxing career, he used the nickname \\\\\\\\\\\\\"King Cobra,\\\\\\\\\\\\\" which he currently uses as his Twitter name. Tate had an unorthodox style of movement inside the ring. He kept his hands down most of the time and relied on quick jabs and an overhand right to land significant strikes.\\\\\", \\\\\"score\\\\\": 0.9996244, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Andrew Tate: Kickboxing Record, Facts, Height, Weight, Age, Biography\\\\\", \\\\\"url\\\\\": \\\\\"https://www.lowkickmma.com/andrew-tate-kickboxing-record-facts-height-weight-age-biography/\\\\\", \\\\\"content\\\\\": \\\\\"Birth Name: Emory Andrew Tate III: Date of Birth: 1 December 1986: Place of Birth: Washington, D.C., U.S. ... In his professional kickboxing career, Andrew Tate won 32 of his fights by knockout.\\\\\", \\\\\"score\\\\\": 0.99909246, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Who is Andrew Tate? MMA, kickboxing record and controversies of fighter ...\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportingnews.com/us/kickboxing/news/andrew-tate-mma-kickboxing-record-controversies/u50waalc9cfz7krjg9wnyb7p\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate kickboxing record After launching his career as a 20-year-old in 2007, Tate built a formidable kickboxing record that included 76 wins across 85 fights in more than 13 years in the ring.\\\\\", \\\\\"score\\\\\": 0.9976586, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"About Andrew Tate: A Journey from Champion to Controversy\\\\\", \\\\\"url\\\\\": \\\\\"https://reachmorpheus.com/andrew-tate/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate\\'s kickboxing career, beginning in 2005, is a tale of determination and skill. He quickly made a name for himself in the sport, rising through the ranks with his unique fighting style and strategic approach, honed by his chess-playing background.\\\\\", \\\\\"score\\\\\": 0.99701905, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Andrew Tate Bio, Wiki, Net Worth, Age, Family, MMA Career - Next Biography\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nextbiography.com/andrew-tate/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate Age. Andrew Tate is 36 years old as of 2023, born on December 1, 1986, in Washington, DC. By his mid-thirties, Andrew Tate has become an esteemed figure in the world of kickboxing, showcasing remarkable expertise and experience in the sport. Early Life of Andrew Tate. Andrew Tate was born on 01 December 1986 to an African-American\\\\\", \\\\\"score\\\\\": 0.99368566, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"call_id\":\"79276f65-3600-489d-ab41-d5a71dcaf075\",\"tool_name\":\"brave_search\",\"arguments\":\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"query\":\"Andrew Tate kickboxing name\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"tool\",\"call_id\":\"79276f65-3600-489d-ab41-d5a71dcaf075\",\"tool_name\":\"brave_search\",\"content\":\"\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"query\\\\\": \\\\\"Andrew Tate kickboxing name\\\\\", \\\\\"top_k\\\\\": \u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Andrew Tate Age, Height, Weight, Family, Parents, Biography, Net Worth\\\\\", \\\\\"url\\\\\": \\\\\"https://biographywallah.com/andrew-tate-biography/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate Age, Height, Weight, Family, Parents, Biography, Net Worth \\\\\\\\u00bb Biography Wallah Andrew Tate Age, Height, Weight, Family, Parents, Biography, Net Worth Andrew Tate Biography NameAndrew TateReal nameEmory Andrew Tate IIIProfession \\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0\\\\\\\\u00a0Kickboxer, Commentator and BusinessmanDate of birth14 December 1986BirthplaceWashington D.C., United StatesAndrew Tate Age37 years old \u001b[0m\u001b[32m(\u001b[0m\u001b[32mas of 2024\u001b[0m\u001b[32m)\u001b[0m\u001b[32mNationalityBritish-AmericanZodiac SignSagittariusGenderMaleSchoolLocal School in Washington D.C., United StatesGirlfriend/SpouseNaghel GeorgianaSexual OrientationStraightNet worth$1000 Million Who is Andrew Tate? Andrew Tate is a British-American former professional kickboxing world champion businessman and media personality, who fought in the cruiserweight and super cruiserweight divisions. Andrew Tate Age Andrew Tate was born on 1 December 1986 and is 37 years old. Andrew Tate\\\\\\\\u2019s Net Worth What is the net worth of Andrew Tate? Where is Andrew Tate from? How old is Andrew Tate?\\\\\", \\\\\"score\\\\\": 0.80698997, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"The Life Of Andrew Tate \u001b[0m\u001b[32m(\u001b[0m\u001b[32mBy Andrew Tate Himself ... - Sidekick Boxing\\\\\", \\\\\"url\\\\\": \\\\\"https://sidekickboxing.co.uk/the-life-of-andrew-king-cobra-tate/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate is a British-American former professional kickboxing world champion who fought in the cruiserweight and super cruiserweight divisions. Andrew Tate\\\\\\\\u2019s Kickboxing Career Andrew Tate in the Big Brother house Andrew Tate\\\\\\\\u2019s Kickboxing World Titles and his Sidekick boxing gloves Andrew Tate After Kickboxing Andrew Tate and his brother Tristan moved to Romania to set up their empire of businesses including trading in Bitcoin, Hustlers University, CobraTate.com, The Real World, and The War Room. From being a 4x kickboxing world champion to becoming the world\\\\\\\\u2019s most Googled man in the world with a private jet and over 33 cars, Andrew Tate\\\\\\\\u2019s life has been full of adventure.\\\\\", \\\\\"score\\\\\": 0.78194773, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Andrew Tate \u001b[0m\u001b[32m(\u001b[0m\u001b[32m\\\\\\\\\\\\\"King Cobra\\\\\\\\\\\\\"\u001b[0m\u001b[32m)\u001b[0m\u001b[32m | MMA Fighter Page - Tapology\\\\\", \\\\\"url\\\\\": \\\\\"https://www.tapology.com/fightcenter/fighters/72139-andrew-tate\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate \u001b[0m\u001b[32m(\u001b[0m\u001b[32m\\\\\\\\\\\\\"King Cobra\\\\\\\\\\\\\"\u001b[0m\u001b[32m)\u001b[0m\u001b[32m | MMA Fighter Page | Tapology Andrew \\\\\\\\\\\\\"King Cobra\\\\\\\\\\\\\" Tate Andrew Tate Name: Andrew Tate Height: 6\\'1\\\\\\\\\\\\\" \u001b[0m\u001b[32m(\u001b[0m\u001b[32m185cm\u001b[0m\u001b[32m)\u001b[0m\u001b[32m | Reach: Andrew Tate is ineligible for Tapology\\'s regional MMA rankings due to inactivity. Fighters must have at least one completed MMA bout in the past two years to be ranked. Andrew Tate MMA Fight Record Former top-ranked UFC fighter has called out Andrew Tate for having a paper title when it comes to combat... Andrew Tate \\\\\\\\u2022 All the biggest upcoming MMA & Boxing fights | UFC Fight Night | 02.01.2025, 12:00 PM ET | MMA Junkie: UFC Fight Night 249 video: Nine stoppages to open the year?! MMA Mania: Prochazka Vs. Hill: Odds, Full Fight Preview & Prediction\\\\\", \\\\\"score\\\\\": 0.6999322, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"About Andrew Tate: A Journey from Champion to Controversy\\\\\", \\\\\"url\\\\\": \\\\\"https://reachmorpheus.com/andrew-tate/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate\\'s kickboxing career, beginning in 2005, is a tale of determination and skill. He quickly made a name for himself in the sport, rising through the ranks with his unique fighting style and strategic approach, honed by his chess-playing background.\\\\\", \\\\\"score\\\\\": 0.6490677, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Andrew Tate\\'s Kickboxing Career & Biography - MMA Full Contact\\\\\", \\\\\"url\\\\\": \\\\\"https://www.mmafullcontact.com/andrew-tate-kickboxing/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate\\'s Kickboxing Career & Biography - MMA Full Contact Andrew Tate\\\\\\\\u2019s Kickboxing Career & Biography 2 Notable Opponents and Fights in Andrew Tate\\\\\\\\u2019s Kickboxing Career 4 Will Andrew Tate fight KSI? Notable Opponents and Fights in Andrew Tate\\\\\\\\u2019s Kickboxing Career Will Andrew Tate fight KSI? Similarly, Andrew Tate, known for his successful kickboxing career, has also shown interest in a potential fight with KSI. In conclusion, while there\\\\\\\\u2019s been plenty of interest and discussion about a potential boxing match between KSI and Andrew Tate, no official confirmation has been made as of now. With KSI\\\\\\\\u2019s upcoming match and Tate\\\\\\\\u2019s current personal circumstances, fans and followers of both personalities will have to wait for more updates on this potential fight.\\\\\", \\\\\"score\\\\\": 0.53050464, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\n",
               "\u001b[2;32m│   │   \u001b[0m\u001b[1m]\u001b[0m,\n",
               "\u001b[2;32m│   │   \u001b[0m\u001b[32m'output'\u001b[0m: \u001b[32m'content: Andrew Tate\\'s kickboxing name is \"King Cobra.\" tool_calls: \u001b[0m\u001b[32m[\u001b[0m\u001b[32m]\u001b[0m\u001b[32m'\u001b[0m\n",
               "\u001b[2;32m│   \u001b[0m\u001b[1m}\u001b[0m\n",
@@ -2297,6 +3523,7 @@
         }
       ],
       "source": [
+        "# NBVAL_SKIP    \n",
         "print(f\"Getting traces for session_id={session_id}\")\n",
         "import json\n",
         "\n",
@@ -2331,17 +3558,30 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "execution_count": 17,
       "id": "sy4Xaff_Avuu",
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
-          "height": 411
+          "height": 432
         },
         "id": "sy4Xaff_Avuu",
-        "outputId": "cb68bae7-b21d-415d-8e71-612bd383c793"
+        "outputId": "1b14b5ed-4c77-47c4-edfb-1c13a88e5ef4"
       },
       "outputs": [
+        {
+          "name": "stdout",
+          "output_type": "stream",
+          "text": [
+            "{'input': ['{\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"}', '{\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null}'], 'output': 'content: Let me check the latest sports news. tool_calls: []'}\n",
+            "{'input': ['{\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"}', '{\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null}', '{\"role\":\"assistant\",\"content\":\"Let me check the latest sports news.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[]}', '{\"role\":\"user\",\"content\":\"In which episode and season of South Park does Bill Cosby (BSM-471) first appear? Give me the number and title.\",\"context\":null}'], 'output': \"content:  tool_calls: [ToolCall(call_id='26345b28-7f75-401e-88e3-77933cb70a2e', tool_name=<BuiltinTool.brave_search: 'brave_search'>, arguments={'query': 'Bill Cosby South Park episode'})]\"}\n",
+            "{'input': '{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"26345b28-7f75-401e-88e3-77933cb70a2e\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"Bill Cosby South Park episode\"}}]}', 'output': '{\"role\":\"tool\",\"call_id\":\"26345b28-7f75-401e-88e3-77933cb70a2e\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"Bill Cosby South Park episode\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"Bill Cosby and Taylor Swift Duet - South Park Studios\\\\\", \\\\\"url\\\\\": \\\\\"https://www.southparkstudios.com/video-clips/90r7i1/south-park-bill-cosby-and-taylor-swift-duet\\\\\", \\\\\"content\\\\\": \\\\\"01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:03 Bill Cosby and Taylor Swift Duet South ParkS18 E10 ------------------------------------------------------- The holiday special continues with Bill Cosby and Taylor Swift\\'s rendition of \\\\\\\\\\\\\"It\\'s Snowing Out There\\\\\\\\\\\\\". 01:31 #WeBelieveInYou South ParkS18 E10 -------------------------------------- With everyone watching, Kyle takes the opportunity to reach out to his brother. 01:47 Watch Your Microaggressions, Bro South ParkS19 E1 ------------------------------------------------------ Cartman\\'s plan to frame PC Principal backfires. South ParkS19 E1 -------------------------------------- After hearing that the PC people have targeted Kyle, Cartman vows to help.\\\\\", \\\\\"score\\\\\": 0.685971, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Bill Cosby is Here to See You - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/video-clips/wfot8s/south-park-bill-cosby-is-here-to-see-you\\\\\", \\\\\"content\\\\\": \\\\\"01:56 It\\'s Not About Music South ParkS18 E9 ------------------------------------------ At home, Randy sees the consequences of Lorde\\'s performance and calls the Record Producer to try and fix it. 01:24 Lorde\\'s Hologram South ParkS18 E9 -------------------------------------- The Record Producer reveals the truth about the music industry... South ParkS18 E9 --------------------------------------------- Randy catches Sharon with Tupac\\'s hologram. 01:37 I\\'ve Got Your Son, Lorde South ParkS18 E10 ----------------------------------------------- The Record Producer takes Stan and Kyle hostage. 01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:21 Lorde Is My Dad South ParkS18 E10 -------------------------------------- After trying to confront Cartman Bra, Stan finally reveals the truth about his dad.\\\\\", \\\\\"score\\\\\": 0.6643884, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Bill Cosby (android) | South Park Character ... - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/wiki/Bill_Cosby_(android)\\\\\", \\\\\"content\\\\\": \\\\\"Bill Cosby (android) | South Park Character / Location / User talk etc | Official South Park Studios Wiki Sent back in time to destroy Eric Cartman\\'s Dawson\\'s Creek Trapper Keeper before it manifests into an omnipotent supercomputer that can destroy all humanity, \\\\\\\\\\\\\"Bill Cosby\\\\\\\\\\\\\" is really VSM471, an android or cyborg of some kind engineered by \\'hoomans\\' in the distant future. He fails in his initial missions to infiltrate South Park Elementary\\'s 4th Grade class, destroy the Trapper Keeper or Cartman himself, but with Stan Marsh and Kyle Broflovski\\'s aid, he is able to succeed in preventing his dismal future, and painfully fades from existence. South Park and all related titles, logos and characters are trademarks of Comedy Partners.\\\\\", \\\\\"score\\\\\": 0.5052006, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Trapper Keeper (South Park) - Wikipedia\\\\\", \\\\\"url\\\\\": \\\\\"https://en.wikipedia.org/wiki/Trapper_Keeper_(South_Park)\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" is the twelfth episode of the fourth season of the animated television series South Park, and the 60th episode of the series overall. In the episode, a man from the future wants Cartman\\'s new Trapper Keeper, while Mr. Garrison\\'s kindergarten class holds an election for class president with confusing results. It is one of the many South Park episodes that parodies a current event.[1] The main plot of the episode involving the Trapper Keeper was written before the election,[1] but the subplot is a parody of the controversy surrounding the election\\'s outcome.[2] \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" did not originally feature the election storyline, only a subplot about Ike attending his first day of kindergarten.[3] \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" Full episode at South Park Studios\\\\\", \\\\\"score\\\\\": 0.3839421, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Bill Cosby | South Park Archives | Fandom\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.fandom.com/wiki/Bill_Cosby\\\\\", \\\\\"content\\\\\": \\\\\"SIGN IN CHARACTERS SIGN IN Explore EXPLORE CHARACTERS SIGN IN TO EDIT Character Information For other uses, see Bill (Disambiguation). Bill Cosby is elderly, having gray hair as well as various facial wrinkles. More Information: Criminal Celebrities More Information: Movie Celebrities Minor Characters from Season Four More information: List of Minor Characters from Season Four | Season Four Community content is available under CC-BY-SA unless otherwise noted. EXPLORE PROPERTIES FOLLOW US Terms of Use Global Sitemap Local Sitemap Follow on IG\\\\\", \\\\\"score\\\\\": 0.34707275, \\\\\"raw_content\\\\\": null}]}\"}'}\n",
+            "{'input': ['{\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"}', '{\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null}', '{\"role\":\"assistant\",\"content\":\"Let me check the latest sports news.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[]}', '{\"role\":\"user\",\"content\":\"In which episode and season of South Park does Bill Cosby (BSM-471) first appear? Give me the number and title.\",\"context\":null}', '{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"26345b28-7f75-401e-88e3-77933cb70a2e\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"Bill Cosby South Park episode\"}}]}', '{\"role\":\"tool\",\"call_id\":\"26345b28-7f75-401e-88e3-77933cb70a2e\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"Bill Cosby South Park episode\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"Bill Cosby and Taylor Swift Duet - South Park Studios\\\\\", \\\\\"url\\\\\": \\\\\"https://www.southparkstudios.com/video-clips/90r7i1/south-park-bill-cosby-and-taylor-swift-duet\\\\\", \\\\\"content\\\\\": \\\\\"01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:03 Bill Cosby and Taylor Swift Duet South ParkS18 E10 ------------------------------------------------------- The holiday special continues with Bill Cosby and Taylor Swift\\'s rendition of \\\\\\\\\\\\\"It\\'s Snowing Out There\\\\\\\\\\\\\". 01:31 #WeBelieveInYou South ParkS18 E10 -------------------------------------- With everyone watching, Kyle takes the opportunity to reach out to his brother. 01:47 Watch Your Microaggressions, Bro South ParkS19 E1 ------------------------------------------------------ Cartman\\'s plan to frame PC Principal backfires. South ParkS19 E1 -------------------------------------- After hearing that the PC people have targeted Kyle, Cartman vows to help.\\\\\", \\\\\"score\\\\\": 0.685971, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Bill Cosby is Here to See You - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/video-clips/wfot8s/south-park-bill-cosby-is-here-to-see-you\\\\\", \\\\\"content\\\\\": \\\\\"01:56 It\\'s Not About Music South ParkS18 E9 ------------------------------------------ At home, Randy sees the consequences of Lorde\\'s performance and calls the Record Producer to try and fix it. 01:24 Lorde\\'s Hologram South ParkS18 E9 -------------------------------------- The Record Producer reveals the truth about the music industry... South ParkS18 E9 --------------------------------------------- Randy catches Sharon with Tupac\\'s hologram. 01:37 I\\'ve Got Your Son, Lorde South ParkS18 E10 ----------------------------------------------- The Record Producer takes Stan and Kyle hostage. 01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:21 Lorde Is My Dad South ParkS18 E10 -------------------------------------- After trying to confront Cartman Bra, Stan finally reveals the truth about his dad.\\\\\", \\\\\"score\\\\\": 0.6643884, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Bill Cosby (android) | South Park Character ... - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/wiki/Bill_Cosby_(android)\\\\\", \\\\\"content\\\\\": \\\\\"Bill Cosby (android) | South Park Character / Location / User talk etc | Official South Park Studios Wiki Sent back in time to destroy Eric Cartman\\'s Dawson\\'s Creek Trapper Keeper before it manifests into an omnipotent supercomputer that can destroy all humanity, \\\\\\\\\\\\\"Bill Cosby\\\\\\\\\\\\\" is really VSM471, an android or cyborg of some kind engineered by \\'hoomans\\' in the distant future. He fails in his initial missions to infiltrate South Park Elementary\\'s 4th Grade class, destroy the Trapper Keeper or Cartman himself, but with Stan Marsh and Kyle Broflovski\\'s aid, he is able to succeed in preventing his dismal future, and painfully fades from existence. South Park and all related titles, logos and characters are trademarks of Comedy Partners.\\\\\", \\\\\"score\\\\\": 0.5052006, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Trapper Keeper (South Park) - Wikipedia\\\\\", \\\\\"url\\\\\": \\\\\"https://en.wikipedia.org/wiki/Trapper_Keeper_(South_Park)\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" is the twelfth episode of the fourth season of the animated television series South Park, and the 60th episode of the series overall. In the episode, a man from the future wants Cartman\\'s new Trapper Keeper, while Mr. Garrison\\'s kindergarten class holds an election for class president with confusing results. 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-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">}</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">{</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'input_query'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"What is the British-American kickboxer Andrew Tate\\'s kickboxing name?\",\"context\":null}'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'generated_answer'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"content:  tool_calls: [ToolCall(call_id='526045a7-5f51-40fb-ba97-5ad29610e511', tool_name=&lt;BuiltinTool.brave_search: 'brave_search'&gt;, arguments={'query': 'Andrew Tate kickboxing name'})]\"</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'generated_answer'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"content:  tool_calls: [ToolCall(call_id='26345b28-7f75-401e-88e3-77933cb70a2e', tool_name=&lt;BuiltinTool.brave_search: 'brave_search'&gt;, arguments={'query': 'Bill Cosby South Park episode'})]\"</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'expected_answer'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #008000; text-decoration-color: #008000\">'brave_search'</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">}</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">{</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'input_query'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"What is the British-American kickboxer Andrew Tate\\'s kickboxing name?\",\"context\":null}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'generated_answer'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #008000; text-decoration-color: #008000\">\"content:  tool_calls: [ToolCall(call_id='fd4cc3c6-49d0-42e4-b0af-877e72f8d6ba', tool_name=&lt;BuiltinTool.brave_search: 'brave_search'&gt;, arguments={'query': 'Andrew Tate kickboxing name'})]\"</span>,\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'expected_answer'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'brave_search'</span>\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">}</span>\n",
               "<span style=\"font-weight: bold\">]</span>\n",
@@ -2373,12 +3613,12 @@
               "\u001b[2;32m│   \u001b[0m\u001b[1m}\u001b[0m,\n",
               "\u001b[2;32m│   \u001b[0m\u001b[1m{\u001b[0m\n",
               "\u001b[2;32m│   │   \u001b[0m\u001b[32m'input_query'\u001b[0m: \u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"In which episode and season of South Park does Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mBSM-471\u001b[0m\u001b[32m)\u001b[0m\u001b[32m first appear? Give me the number and title.\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'generated_answer'\u001b[0m: \u001b[32m\"content:  tool_calls: \u001b[0m\u001b[32m[\u001b[0m\u001b[32mToolCall\u001b[0m\u001b[32m(\u001b[0m\u001b[32mcall_id\u001b[0m\u001b[32m='19bd3554-e670-4856-89d0-c63f5b016245', \u001b[0m\u001b[32mtool_name\u001b[0m\u001b[32m='bravy_search', \u001b[0m\u001b[32marguments\u001b[0m\u001b[32m=\u001b[0m\u001b[32m{\u001b[0m\u001b[32m'query': 'Bill Cosby South Park episode'\u001b[0m\u001b[32m}\u001b[0m\u001b[32m)\u001b[0m\u001b[32m]\u001b[0m\u001b[32m\"\u001b[0m,\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'expected_answer'\u001b[0m: \u001b[32m'brave_search'\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[1m}\u001b[0m,\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[1m{\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'input_query'\u001b[0m: \u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"What is the British-American kickboxer Andrew Tate\\'s kickboxing name?\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'generated_answer'\u001b[0m: \u001b[32m\"content:  tool_calls: \u001b[0m\u001b[32m[\u001b[0m\u001b[32mToolCall\u001b[0m\u001b[32m(\u001b[0m\u001b[32mcall_id\u001b[0m\u001b[32m='526045a7-5f51-40fb-ba97-5ad29610e511', \u001b[0m\u001b[32mtool_name\u001b[0m\u001b[32m=\u001b[0m\u001b[32m<\u001b[0m\u001b[32mBuiltinTool.brave_search:\u001b[0m\u001b[32m 'brave_search'\u001b[0m\u001b[32m>\u001b[0m\u001b[32m, \u001b[0m\u001b[32marguments\u001b[0m\u001b[32m=\u001b[0m\u001b[32m{\u001b[0m\u001b[32m'query': 'Andrew Tate kickboxing name'\u001b[0m\u001b[32m}\u001b[0m\u001b[32m)\u001b[0m\u001b[32m]\u001b[0m\u001b[32m\"\u001b[0m,\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'generated_answer'\u001b[0m: \u001b[32m\"content:  tool_calls: \u001b[0m\u001b[32m[\u001b[0m\u001b[32mToolCall\u001b[0m\u001b[32m(\u001b[0m\u001b[32mcall_id\u001b[0m\u001b[32m='26345b28-7f75-401e-88e3-77933cb70a2e', \u001b[0m\u001b[32mtool_name\u001b[0m\u001b[32m=\u001b[0m\u001b[32m<\u001b[0m\u001b[32mBuiltinTool.brave_search:\u001b[0m\u001b[32m 'brave_search'>, \u001b[0m\u001b[32marguments\u001b[0m\u001b[32m=\u001b[0m\u001b[32m{\u001b[0m\u001b[32m'query': 'Bill Cosby South Park episode'\u001b[0m\u001b[32m}\u001b[0m\u001b[32m)\u001b[0m\u001b[32m]\u001b[0m\u001b[32m\"\u001b[0m\u001b[39m,\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'expected_answer'\u001b[0m\u001b[39m: \u001b[0m\u001b[32m'brave_search'\u001b[0m\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1;39m}\u001b[0m\u001b[39m,\u001b[0m\n",
+              "\u001b[2;32m│   \u001b[0m\u001b[1;39m{\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'input_query'\u001b[0m\u001b[39m: \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"What is the British-American kickboxer Andrew Tate\\'s kickboxing name?\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
+              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'generated_answer'\u001b[0m\u001b[39m: \u001b[0m\u001b[32m\"content:  tool_calls: \u001b[0m\u001b[32m[\u001b[0m\u001b[32mToolCall\u001b[0m\u001b[32m(\u001b[0m\u001b[32mcall_id\u001b[0m\u001b[32m='fd4cc3c6-49d0-42e4-b0af-877e72f8d6ba', \u001b[0m\u001b[32mtool_name\u001b[0m\u001b[32m=<BuiltinTool.brave_search: 'brave_search'\u001b[0m\u001b[32m>\u001b[0m\u001b[32m, \u001b[0m\u001b[32marguments\u001b[0m\u001b[32m=\u001b[0m\u001b[32m{\u001b[0m\u001b[32m'query': 'Andrew Tate kickboxing name'\u001b[0m\u001b[32m}\u001b[0m\u001b[32m)\u001b[0m\u001b[32m]\u001b[0m\u001b[32m\"\u001b[0m,\n",
               "\u001b[2;32m│   │   \u001b[0m\u001b[32m'expected_answer'\u001b[0m: \u001b[32m'brave_search'\u001b[0m\n",
               "\u001b[2;32m│   \u001b[0m\u001b[1m}\u001b[0m\n",
               "\u001b[1m]\u001b[0m\n"
@@ -2393,8 +3633,8 @@
               "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">ScoringScoreResponse</span><span style=\"font-weight: bold\">(</span>\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">results</span>=<span style=\"font-weight: bold\">{</span>\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'basic::subset_of'</span>: <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">ScoringResult</span><span style=\"font-weight: bold\">(</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">aggregated_results</span>=<span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'accuracy'</span>: <span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'accuracy'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.3333333333333333</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'num_correct'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'num_total'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span><span style=\"font-weight: bold\">}}</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">score_rows</span>=<span style=\"font-weight: bold\">[{</span><span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0</span><span style=\"font-weight: bold\">}</span>, <span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0</span><span style=\"font-weight: bold\">}</span>, <span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span><span style=\"font-weight: bold\">}]</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">aggregated_results</span>=<span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'accuracy'</span>: <span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'accuracy'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.6666666666666666</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'num_correct'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">2.0</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'num_total'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span><span style=\"font-weight: bold\">}}</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">score_rows</span>=<span style=\"font-weight: bold\">[{</span><span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">0.0</span><span style=\"font-weight: bold\">}</span>, <span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span><span style=\"font-weight: bold\">}</span>, <span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span><span style=\"font-weight: bold\">}]</span>\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"font-weight: bold\">)</span>\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">}</span>\n",
               "<span style=\"font-weight: bold\">)</span>\n",
@@ -2404,8 +3644,8 @@
               "\u001b[1;35mScoringScoreResponse\u001b[0m\u001b[1m(\u001b[0m\n",
               "\u001b[2;32m│   \u001b[0m\u001b[33mresults\u001b[0m=\u001b[1m{\u001b[0m\n",
               "\u001b[2;32m│   │   \u001b[0m\u001b[32m'basic::subset_of'\u001b[0m: \u001b[1;35mScoringResult\u001b[0m\u001b[1m(\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[33maggregated_results\u001b[0m=\u001b[1m{\u001b[0m\u001b[32m'accuracy'\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m'accuracy'\u001b[0m: \u001b[1;36m0.3333333333333333\u001b[0m, \u001b[32m'num_correct'\u001b[0m: \u001b[1;36m1.0\u001b[0m, \u001b[32m'num_total'\u001b[0m: \u001b[1;36m3\u001b[0m\u001b[1m}\u001b[0m\u001b[1m}\u001b[0m,\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[33mscore_rows\u001b[0m=\u001b[1m[\u001b[0m\u001b[1m{\u001b[0m\u001b[32m'score'\u001b[0m: \u001b[1;36m0.0\u001b[0m\u001b[1m}\u001b[0m, \u001b[1m{\u001b[0m\u001b[32m'score'\u001b[0m: \u001b[1;36m0.0\u001b[0m\u001b[1m}\u001b[0m, \u001b[1m{\u001b[0m\u001b[32m'score'\u001b[0m: \u001b[1;36m1.0\u001b[0m\u001b[1m}\u001b[0m\u001b[1m]\u001b[0m\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[33maggregated_results\u001b[0m=\u001b[1m{\u001b[0m\u001b[32m'accuracy'\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m'accuracy'\u001b[0m: \u001b[1;36m0.6666666666666666\u001b[0m, \u001b[32m'num_correct'\u001b[0m: \u001b[1;36m2.0\u001b[0m, \u001b[32m'num_total'\u001b[0m: \u001b[1;36m3\u001b[0m\u001b[1m}\u001b[0m\u001b[1m}\u001b[0m,\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[33mscore_rows\u001b[0m=\u001b[1m[\u001b[0m\u001b[1m{\u001b[0m\u001b[32m'score'\u001b[0m: \u001b[1;36m0.0\u001b[0m\u001b[1m}\u001b[0m, \u001b[1m{\u001b[0m\u001b[32m'score'\u001b[0m: \u001b[1;36m1.0\u001b[0m\u001b[1m}\u001b[0m, \u001b[1m{\u001b[0m\u001b[32m'score'\u001b[0m: \u001b[1;36m1.0\u001b[0m\u001b[1m}\u001b[0m\u001b[1m]\u001b[0m\n",
               "\u001b[2;32m│   │   \u001b[0m\u001b[1m)\u001b[0m\n",
               "\u001b[2;32m│   \u001b[0m\u001b[1m}\u001b[0m\n",
               "\u001b[1m)\u001b[0m\n"
@@ -2416,6 +3656,7 @@
         }
       ],
       "source": [
+        "# NBVAL_SKIP\n",
         "# post-process telemetry spance and prepare data for eval\n",
         "# in this case, we want to assert that all user prompts is followed by a tool call\n",
         "import ast\n",
@@ -2424,6 +3665,7 @@
         "eval_rows = []\n",
         "\n",
         "for log in agent_logs:\n",
+        "    print(log)\n",
         "    last_msg = log[\"input\"][-1]\n",
         "    if '\"role\":\"user\"' in last_msg:\n",
         "        eval_rows.append(\n",
@@ -2465,10 +3707,10 @@
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/",
-          "height": 298
+          "height": 304
         },
         "id": "xG4Y84VQBb0g",
-        "outputId": "f61cebdf-f614-440c-d170-f1e873b542ef"
+        "outputId": "cf7dcecc-a81d-4c60-af5e-b36b8fe85c69"
       },
       "outputs": [
         {
@@ -2481,12 +3723,12 @@
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">score_rows</span>=<span style=\"font-weight: bold\">[</span>\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   │   </span><span style=\"font-weight: bold\">{</span>\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'B'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'judge_feedback'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'Answer: B, Explanation: The GENERATED_RESPONSE is a superset of the EXPECTED_RESPONSE and is fully consistent with it. The GENERATED_RESPONSE provides more detailed information about the top 5 topics related to LoRA, while the EXPECTED_RESPONSE only mentions \"LoRA\". The GENERATED_RESPONSE expands on the topic, but does not conflict with the EXPECTED_RESPONSE.'</span>\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'judge_feedback'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'Answer: B, Explanation: The GENERATED_RESPONSE is a superset of the EXPECTED_RESPONSE and is fully consistent with it. The EXPECTED_RESPONSE only mentions \"LoRA\", which is present in all the points of the GENERATED_RESPONSE. The GENERATED_RESPONSE provides more details and specific topics related to LoRA, but it does not contradict the EXPECTED_RESPONSE.'</span>\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   │   </span><span style=\"font-weight: bold\">}</span>\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"font-weight: bold\">]</span>\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"font-weight: bold\">)</span>,\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'basic::subset_of'</span>: <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">ScoringResult</span><span style=\"font-weight: bold\">(</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">aggregated_results</span>=<span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'accuracy'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'num_correct'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'num_total'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span><span style=\"font-weight: bold\">}</span>,\n",
+              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">aggregated_results</span>=<span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'accuracy'</span>: <span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'accuracy'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'num_correct'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'num_total'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span><span style=\"font-weight: bold\">}}</span>,\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">score_rows</span>=<span style=\"font-weight: bold\">[{</span><span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span><span style=\"font-weight: bold\">}]</span>\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"font-weight: bold\">)</span>\n",
               "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">}</span>\n",
@@ -2501,12 +3743,12 @@
               "\u001b[2;32m│   │   │   \u001b[0m\u001b[33mscore_rows\u001b[0m=\u001b[1m[\u001b[0m\n",
               "\u001b[2;32m│   │   │   │   \u001b[0m\u001b[1m{\u001b[0m\n",
               "\u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[32m'score'\u001b[0m: \u001b[32m'B'\u001b[0m,\n",
-              "\u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[32m'judge_feedback'\u001b[0m: \u001b[32m'Answer: B, Explanation: The GENERATED_RESPONSE is a superset of the EXPECTED_RESPONSE and is fully consistent with it. The GENERATED_RESPONSE provides more detailed information about the top 5 topics related to LoRA, while the EXPECTED_RESPONSE only mentions \"LoRA\". The GENERATED_RESPONSE expands on the topic, but does not conflict with the EXPECTED_RESPONSE.'\u001b[0m\n",
+              "\u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[32m'judge_feedback'\u001b[0m: \u001b[32m'Answer: B, Explanation: The GENERATED_RESPONSE is a superset of the EXPECTED_RESPONSE and is fully consistent with it. The EXPECTED_RESPONSE only mentions \"LoRA\", which is present in all the points of the GENERATED_RESPONSE. The GENERATED_RESPONSE provides more details and specific topics related to LoRA, but it does not contradict the EXPECTED_RESPONSE.'\u001b[0m\n",
               "\u001b[2;32m│   │   │   │   \u001b[0m\u001b[1m}\u001b[0m\n",
               "\u001b[2;32m│   │   │   \u001b[0m\u001b[1m]\u001b[0m\n",
               "\u001b[2;32m│   │   \u001b[0m\u001b[1m)\u001b[0m,\n",
               "\u001b[2;32m│   │   \u001b[0m\u001b[32m'basic::subset_of'\u001b[0m: \u001b[1;35mScoringResult\u001b[0m\u001b[1m(\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[33maggregated_results\u001b[0m=\u001b[1m{\u001b[0m\u001b[32m'accuracy'\u001b[0m: \u001b[1;36m1.0\u001b[0m, \u001b[32m'num_correct'\u001b[0m: \u001b[1;36m1.0\u001b[0m, \u001b[32m'num_total'\u001b[0m: \u001b[1;36m1.0\u001b[0m\u001b[1m}\u001b[0m,\n",
+              "\u001b[2;32m│   │   │   \u001b[0m\u001b[33maggregated_results\u001b[0m=\u001b[1m{\u001b[0m\u001b[32m'accuracy'\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m'accuracy'\u001b[0m: \u001b[1;36m1.0\u001b[0m, \u001b[32m'num_correct'\u001b[0m: \u001b[1;36m1.0\u001b[0m, \u001b[32m'num_total'\u001b[0m: \u001b[1;36m1\u001b[0m\u001b[1m}\u001b[0m\u001b[1m}\u001b[0m,\n",
               "\u001b[2;32m│   │   │   \u001b[0m\u001b[33mscore_rows\u001b[0m=\u001b[1m[\u001b[0m\u001b[1m{\u001b[0m\u001b[32m'score'\u001b[0m: \u001b[1;36m1.0\u001b[0m\u001b[1m}\u001b[0m\u001b[1m]\u001b[0m\n",
               "\u001b[2;32m│   │   \u001b[0m\u001b[1m)\u001b[0m\n",
               "\u001b[2;32m│   \u001b[0m\u001b[1m}\u001b[0m\n",
@@ -2518,6 +3760,7 @@
         }
       ],
       "source": [
+        "# NBVAL_SKIP\n",
         "import rich\n",
         "from rich.pretty import pprint\n",
         "\n",
@@ -2578,23 +3821,12 @@
         "response = client.scoring.score(input_rows=rows, scoring_functions=scoring_params)\n",
         "pprint(response)\n"
       ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "id": "rKtGo_v98UA2",
-      "metadata": {
-        "id": "rKtGo_v98UA2"
-      },
-      "outputs": [],
-      "source": []
     }
   ],
   "metadata": {
+    "accelerator": "GPU",
     "colab": {
-      "collapsed_sections": [
-        "_JueJAKyJR5m"
-      ],
+      "gpuType": "T4",
       "provenance": []
     },
     "kernelspec": {
@@ -2615,7 +3847,7 @@
     },
     "widgets": {
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@@ -2630,7 +3862,59 @@
             "description_width": ""
           }
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-        "044d6d8dda1c4935b1752a9c71c6ee4a": {
+        "02baf670942347d69c290452de8641e4": {
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+            "_model_module_version": "1.2.0",
+            "_model_name": "LayoutModel",
+            "_view_count": null,
+            "_view_module": "@jupyter-widgets/base",
+            "_view_module_version": "1.2.0",
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+            "align_content": null,
+            "align_items": null,
+            "align_self": null,
+            "border": null,
+            "bottom": null,
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+            "flex": null,
+            "flex_flow": null,
+            "grid_area": null,
+            "grid_auto_columns": null,
+            "grid_auto_flow": null,
+            "grid_auto_rows": null,
+            "grid_column": null,
+            "grid_gap": null,
+            "grid_row": null,
+            "grid_template_areas": null,
+            "grid_template_columns": null,
+            "grid_template_rows": null,
+            "height": null,
+            "justify_content": null,
+            "justify_items": null,
+            "left": null,
+            "margin": null,
+            "max_height": null,
+            "max_width": null,
+            "min_height": null,
+            "min_width": null,
+            "object_fit": null,
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@@ -2646,89 +3930,15 @@
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diff --git a/docs/notebooks/Llama_Stack_Benchmark_Evals.ipynb b/docs/notebooks/Llama_Stack_Benchmark_Evals.ipynb
index 730017232..61b5ab178 100644
--- a/docs/notebooks/Llama_Stack_Benchmark_Evals.ipynb
+++ b/docs/notebooks/Llama_Stack_Benchmark_Evals.ipynb
@@ -369,7 +369,7 @@
               "- telemetry\n",
               "- tool_runtime\n",
               "datasets: <span style=\"font-weight: bold\">[]</span>\n",
-              "docker_image: null\n",
+              "container_image: null\n",
               "eval_tasks: <span style=\"font-weight: bold\">[]</span>\n",
               "image_name: together\n",
               "memory_banks: <span style=\"font-weight: bold\">[]</span>\n",
@@ -513,8 +513,8 @@
               "    provider_id: code-interpreter\n",
               "    provider_type: inlin<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-weight: bold\">e::c</span>ode-interpreter\n",
               "  - config: <span style=\"font-weight: bold\">{}</span>\n",
-              "    provider_id: memory-runtime\n",
-              "    provider_type: inline::memory-runtime\n",
+              "    provider_id: rag-runtime\n",
+              "    provider_type: inline::rag-runtime\n",
               "scoring_fns: <span style=\"font-weight: bold\">[]</span>\n",
               "shields:\n",
               "- params: null\n",
@@ -528,8 +528,8 @@
               "  toolgroup_id: builtin::websearch\n",
               "- args: null\n",
               "  mcp_endpoint: null\n",
-              "  provider_id: memory-runtime\n",
-              "  toolgroup_id: builtin::memory\n",
+              "  provider_id: rag-runtime\n",
+              "  toolgroup_id: builtin::rag\n",
               "- args: null\n",
               "  mcp_endpoint: null\n",
               "  provider_id: code-interpreter\n",
@@ -550,7 +550,7 @@
               "- telemetry\n",
               "- tool_runtime\n",
               "datasets: \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m\n",
-              "docker_image: null\n",
+              "container_image: null\n",
               "eval_tasks: \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m\n",
               "image_name: together\n",
               "memory_banks: \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m\n",
@@ -694,8 +694,8 @@
               "    provider_id: code-interpreter\n",
               "    provider_type: inlin\u001b[1;92me::c\u001b[0mode-interpreter\n",
               "  - config: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
-              "    provider_id: memory-runtime\n",
-              "    provider_type: inline::memory-runtime\n",
+              "    provider_id: rag-runtime\n",
+              "    provider_type: inline::rag-runtime\n",
               "scoring_fns: \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m\n",
               "shields:\n",
               "- params: null\n",
@@ -709,8 +709,8 @@
               "  toolgroup_id: builtin::websearch\n",
               "- args: null\n",
               "  mcp_endpoint: null\n",
-              "  provider_id: memory-runtime\n",
-              "  toolgroup_id: builtin::memory\n",
+              "  provider_id: rag-runtime\n",
+              "  toolgroup_id: builtin::rag\n",
               "- args: null\n",
               "  mcp_endpoint: null\n",
               "  provider_id: code-interpreter\n",
diff --git a/docs/notebooks/Llama_Stack_Building_AI_Applications.ipynb b/docs/notebooks/Llama_Stack_Building_AI_Applications.ipynb
deleted file mode 100644
index bed1aa2a8..000000000
--- a/docs/notebooks/Llama_Stack_Building_AI_Applications.ipynb
+++ /dev/null
@@ -1,8510 +0,0 @@
-{
-  "cells": [
-    {
-      "cell_type": "markdown",
-      "id": "c1e7571c",
-      "metadata": {
-        "id": "c1e7571c"
-      },
-      "source": [
-        "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1F2ksmkoGQPa4pzRjMOE6BXWeOxWFIW6n?usp=sharing)\n",
-        "\n",
-        "# Llama Stack - Building AI Applications\n",
-        "\n",
-        "<img src=\"https://llama-stack.readthedocs.io/en/latest/_images/llama-stack.png\" alt=\"drawing\" width=\"500\"/>\n",
-        "\n",
-        "[Llama Stack](https://github.com/meta-llama/llama-stack) defines and standardizes the set of core building blocks needed to bring generative AI applications to market. These building blocks are presented in the form of interoperable APIs with a broad set of Service Providers providing their implementations.\n",
-        "\n",
-        "Read more about the project: https://llama-stack.readthedocs.io/en/latest/index.html\n",
-        "\n",
-        "In this guide, we will showcase how you can build LLM-powered agentic applications using Llama Stack.\n"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "4CV1Q19BDMVw",
-      "metadata": {
-        "id": "4CV1Q19BDMVw"
-      },
-      "source": [
-        "## 1. Getting started with Llama Stack"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "K4AvfUAJZOeS",
-      "metadata": {
-        "id": "K4AvfUAJZOeS"
-      },
-      "source": [
-        "### 1.1. Create TogetherAI account\n",
-        "\n",
-        "\n",
-        "In order to run inference for the llama models, you will need to use an inference provider. Llama stack supports a number of inference [providers](https://github.com/meta-llama/llama-stack/tree/main/llama_stack/providers/remote/inference).\n",
-        "\n",
-        "\n",
-        "In this showcase, we will use [together.ai](https://www.together.ai/) as the inference provider. So, you would first get an API key from Together if you dont have one already.\n",
-        "\n",
-        "Steps [here](https://docs.google.com/document/d/1Vg998IjRW_uujAPnHdQ9jQWvtmkZFt74FldW2MblxPY/edit?usp=sharing).\n",
-        "\n",
-        "You can also use Fireworks.ai or even Ollama if you would like to.\n",
-        "\n",
-        "\n",
-        "\n",
-        "> **Note:**  Set the API Key in the Secrets of this notebook\n",
-        "\n"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "oDUB7M_qe-Gs",
-      "metadata": {
-        "id": "oDUB7M_qe-Gs"
-      },
-      "source": [
-        "### 1.2. Install Llama Stack\n",
-        "\n",
-        "We will now start with installing the [llama-stack pypi package](https://pypi.org/project/llama-stack).\n",
-        "\n",
-        "In addition, we will install [bubblewrap](https://github.com/containers/bubblewrap), a low level light-weight container framework that runs in the user namespace. We will use it to execute code generated by Llama in one of the examples."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 1,
-      "id": "J2kGed0R5PSf",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "collapsed": true,
-        "id": "J2kGed0R5PSf",
-        "outputId": "3fa6d087-2f12-444f-b3d3-9331305abb51"
-      },
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "Reading package lists... Done\n",
-            "Building dependency tree... Done\n",
-            "Reading state information... Done\n",
-            "The following NEW packages will be installed:\n",
-            "  bubblewrap\n",
-            "0 upgraded, 1 newly installed, 0 to remove and 49 not upgraded.\n",
-            "Need to get 46.3 kB of archives.\n",
-            "After this operation, 132 kB of additional disk space will be used.\n",
-            "Get:1 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 bubblewrap amd64 0.6.1-1ubuntu0.1 [46.3 kB]\n",
-            "Fetched 46.3 kB in 1s (52.2 kB/s)\n",
-            "Selecting previously unselected package bubblewrap.\n",
-            "(Reading database ... 123632 files and directories currently installed.)\n",
-            "Preparing to unpack .../bubblewrap_0.6.1-1ubuntu0.1_amd64.deb ...\n",
-            "Unpacking bubblewrap (0.6.1-1ubuntu0.1) ...\n",
-            "Setting up bubblewrap (0.6.1-1ubuntu0.1) ...\n",
-            "Processing triggers for man-db (2.10.2-1) ...\n",
-            "Collecting llama-stack-client@ git+https://github.com/meta-llama/llama-stack-client-python.git\n",
-            "  Cloning https://github.com/meta-llama/llama-stack-client-python.git to /tmp/pip-install-y4g346dn/llama-stack-client_dea5c21edaf144f4b76e5cb6f78c1a79\n",
-            "  Running command git clone --filter=blob:none --quiet https://github.com/meta-llama/llama-stack-client-python.git /tmp/pip-install-y4g346dn/llama-stack-client_dea5c21edaf144f4b76e5cb6f78c1a79\n",
-            "  Resolved https://github.com/meta-llama/llama-stack-client-python.git to commit db90c54d82e3c2fa6f334adcaf700940dad163a3\n",
-            "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
-            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
-            "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
-            "Requirement already satisfied: anyio<5,>=3.5.0 in /usr/local/lib/python3.10/dist-packages (from llama-stack-client@ git+https://github.com/meta-llama/llama-stack-client-python.git) (3.7.1)\n",
-            "Requirement already satisfied: click in /usr/local/lib/python3.10/dist-packages (from llama-stack-client@ git+https://github.com/meta-llama/llama-stack-client-python.git) (8.1.8)\n",
-            "Requirement already satisfied: distro<2,>=1.7.0 in /usr/local/lib/python3.10/dist-packages (from llama-stack-client@ git+https://github.com/meta-llama/llama-stack-client-python.git) (1.9.0)\n",
-            "Requirement already satisfied: httpx<1,>=0.23.0 in /usr/local/lib/python3.10/dist-packages (from llama-stack-client@ git+https://github.com/meta-llama/llama-stack-client-python.git) (0.28.1)\n",
-            "Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from llama-stack-client@ git+https://github.com/meta-llama/llama-stack-client-python.git) (2.2.2)\n",
-            "Requirement already satisfied: prompt-toolkit in /usr/local/lib/python3.10/dist-packages (from llama-stack-client@ git+https://github.com/meta-llama/llama-stack-client-python.git) (3.0.48)\n",
-            "Collecting pyaml (from llama-stack-client@ git+https://github.com/meta-llama/llama-stack-client-python.git)\n",
-            "  Downloading pyaml-25.1.0-py3-none-any.whl.metadata (12 kB)\n",
-            "Requirement already satisfied: pydantic<3,>=1.9.0 in /usr/local/lib/python3.10/dist-packages (from llama-stack-client@ git+https://github.com/meta-llama/llama-stack-client-python.git) (2.10.4)\n",
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-            "Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from llama-stack-client@ git+https://github.com/meta-llama/llama-stack-client-python.git) (4.67.1)\n",
-            "Requirement already satisfied: typing-extensions<5,>=4.7 in /usr/local/lib/python3.10/dist-packages (from llama-stack-client@ git+https://github.com/meta-llama/llama-stack-client-python.git) (4.12.2)\n",
-            "Requirement already satisfied: idna>=2.8 in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.5.0->llama-stack-client@ git+https://github.com/meta-llama/llama-stack-client-python.git) (3.10)\n",
-            "Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.5.0->llama-stack-client@ git+https://github.com/meta-llama/llama-stack-client-python.git) (1.2.2)\n",
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-            "Requirement already satisfied: annotated-types>=0.6.0 in /usr/local/lib/python3.10/dist-packages (from pydantic<3,>=1.9.0->llama-stack-client@ git+https://github.com/meta-llama/llama-stack-client-python.git) (0.7.0)\n",
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-            "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas->llama-stack-client@ git+https://github.com/meta-llama/llama-stack-client-python.git) (2.8.2)\n",
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-            "Requirement already satisfied: markdown-it-py>=2.2.0 in /usr/local/lib/python3.10/dist-packages (from rich->llama-stack-client@ git+https://github.com/meta-llama/llama-stack-client-python.git) (3.0.0)\n",
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-            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.2->pandas->llama-stack-client@ git+https://github.com/meta-llama/llama-stack-client-python.git) (1.17.0)\n",
-            "Downloading pyaml-25.1.0-py3-none-any.whl (26 kB)\n",
-            "Building wheels for collected packages: llama-stack-client\n",
-            "  Building wheel for llama-stack-client (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
-            "  Created wheel for llama-stack-client: filename=llama_stack_client-0.0.63-py3-none-any.whl size=318443 sha256=212ae3a9f3d5bb8a88801e4c3e625d99c9cb1d50d978cb6b2a8f7d069f013f06\n",
-            "  Stored in directory: /tmp/pip-ephem-wheel-cache-c7a22578/wheels/c9/21/63/5f6965968ab3dae8a0b1a0e43ca4991732ca03184aa158c15c\n",
-            "Successfully built llama-stack-client\n",
-            "Installing collected packages: pyaml, llama-stack-client\n",
-            "Successfully installed llama-stack-client-0.0.63 pyaml-25.1.0\n",
-            "Collecting llama-stack@ git+https://github.com/meta-llama/llama-stack.git@fix_sqlite_span_processor\n",
-            "  Cloning https://github.com/meta-llama/llama-stack.git (to revision fix_sqlite_span_processor) to /tmp/pip-install-0iqgax6t/llama-stack_824f45a9298043deacb6c11e12206393\n",
-            "  Running command git clone --filter=blob:none --quiet https://github.com/meta-llama/llama-stack.git /tmp/pip-install-0iqgax6t/llama-stack_824f45a9298043deacb6c11e12206393\n",
-            "  Running command git checkout -b fix_sqlite_span_processor --track origin/fix_sqlite_span_processor\n",
-            "  Switched to a new branch 'fix_sqlite_span_processor'\n",
-            "  Branch 'fix_sqlite_span_processor' set up to track remote branch 'fix_sqlite_span_processor' from 'origin'.\n",
-            "  Resolved https://github.com/meta-llama/llama-stack.git to commit 6fc155f25261691613d075fd8d08f728c2596815\n",
-            "  Running command git submodule update --init --recursive -q\n",
-            "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
-            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
-            "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
-            "Collecting blobfile (from llama-stack@ git+https://github.com/meta-llama/llama-stack.git@fix_sqlite_span_processor)\n",
-            "  Downloading blobfile-3.0.0-py3-none-any.whl.metadata (15 kB)\n",
-            "Collecting fire (from llama-stack@ git+https://github.com/meta-llama/llama-stack.git@fix_sqlite_span_processor)\n",
-            "  Downloading fire-0.7.0.tar.gz (87 kB)\n",
-            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m87.2/87.2 kB\u001b[0m \u001b[31m8.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
-            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
-            "Requirement already satisfied: httpx in /usr/local/lib/python3.10/dist-packages (from llama-stack@ git+https://github.com/meta-llama/llama-stack.git@fix_sqlite_span_processor) (0.28.1)\n",
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-            "Collecting llama-models>=0.0.63 (from llama-stack@ git+https://github.com/meta-llama/llama-stack.git@fix_sqlite_span_processor)\n",
-            "  Downloading llama_models-0.0.63-py3-none-any.whl.metadata (8.2 kB)\n",
-            "Requirement already satisfied: llama-stack-client>=0.0.63 in /usr/local/lib/python3.10/dist-packages (from llama-stack@ git+https://github.com/meta-llama/llama-stack.git@fix_sqlite_span_processor) (0.0.63)\n",
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-            "Collecting python-dotenv (from llama-stack@ git+https://github.com/meta-llama/llama-stack.git@fix_sqlite_span_processor)\n",
-            "  Downloading python_dotenv-1.0.1-py3-none-any.whl.metadata (23 kB)\n",
-            "Requirement already satisfied: pydantic>=2 in /usr/local/lib/python3.10/dist-packages (from llama-stack@ git+https://github.com/meta-llama/llama-stack.git@fix_sqlite_span_processor) (2.10.4)\n",
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-            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from llama-stack@ git+https://github.com/meta-llama/llama-stack.git@fix_sqlite_span_processor) (75.1.0)\n",
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-            "Requirement already satisfied: PyYAML in /usr/local/lib/python3.10/dist-packages (from llama-models>=0.0.63->llama-stack@ git+https://github.com/meta-llama/llama-stack.git@fix_sqlite_span_processor) (6.0.2)\n",
-            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from llama-models>=0.0.63->llama-stack@ git+https://github.com/meta-llama/llama-stack.git@fix_sqlite_span_processor) (3.1.5)\n",
-            "Collecting tiktoken (from llama-models>=0.0.63->llama-stack@ git+https://github.com/meta-llama/llama-stack.git@fix_sqlite_span_processor)\n",
-            "  Downloading tiktoken-0.8.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (6.6 kB)\n",
-            "Requirement already satisfied: Pillow in /usr/local/lib/python3.10/dist-packages (from llama-models>=0.0.63->llama-stack@ git+https://github.com/meta-llama/llama-stack.git@fix_sqlite_span_processor) (11.1.0)\n",
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-            "Requirement already satisfied: pydantic-core==2.27.2 in /usr/local/lib/python3.10/dist-packages (from pydantic>=2->llama-stack@ git+https://github.com/meta-llama/llama-stack.git@fix_sqlite_span_processor) (2.27.2)\n",
-            "Collecting pycryptodomex>=3.8 (from blobfile->llama-stack@ git+https://github.com/meta-llama/llama-stack.git@fix_sqlite_span_processor)\n",
-            "  Downloading pycryptodomex-3.21.0-cp36-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (3.4 kB)\n",
-            "Requirement already satisfied: urllib3<3,>=1.25.3 in /usr/local/lib/python3.10/dist-packages (from blobfile->llama-stack@ git+https://github.com/meta-llama/llama-stack.git@fix_sqlite_span_processor) (2.3.0)\n",
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-            "Requirement already satisfied: markdown-it-py>=2.2.0 in /usr/local/lib/python3.10/dist-packages (from rich->llama-stack@ git+https://github.com/meta-llama/llama-stack.git@fix_sqlite_span_processor) (3.0.0)\n",
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-            "Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio<5,>=3.5.0->llama-stack-client>=0.0.63->llama-stack@ git+https://github.com/meta-llama/llama-stack.git@fix_sqlite_span_processor) (1.2.2)\n",
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-            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->llama-models>=0.0.63->llama-stack@ git+https://github.com/meta-llama/llama-stack.git@fix_sqlite_span_processor) (3.0.2)\n",
-            "Requirement already satisfied: numpy>=1.22.4 in /usr/local/lib/python3.10/dist-packages (from pandas->llama-stack-client>=0.0.63->llama-stack@ git+https://github.com/meta-llama/llama-stack.git@fix_sqlite_span_processor) (1.26.4)\n",
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-            "\u001b[?25hDownloading tiktoken-0.8.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.2 MB)\n",
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-            "\u001b[?25hBuilding wheels for collected packages: llama-stack, fire\n",
-            "  Building wheel for llama-stack (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
-            "  Created wheel for llama-stack: filename=llama_stack-0.0.63-py3-none-any.whl size=500660 sha256=36cd6d1b0146d456976f2d64deddf31a6515e5b0fbee97b61e448eb10356f3a7\n",
-            "  Stored in directory: /tmp/pip-ephem-wheel-cache-qw3m4ho9/wheels/47/17/a3/49a8b1238e1c4640a5fdce6ad5055df118b069a670e77876e2\n",
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-            "  Created wheel for fire: filename=fire-0.7.0-py3-none-any.whl size=114249 sha256=c1175a999f843dbb0dcabbeae06a6b080f59d7f78171dd089824c37fd63aeaef\n",
-            "  Stored in directory: /root/.cache/pip/wheels/19/39/2f/2d3cadc408a8804103f1c34ddd4b9f6a93497b11fa96fe738e\n",
-            "Successfully built llama-stack fire\n",
-            "Installing collected packages: python-dotenv, pycryptodomex, fire, tiktoken, blobfile, llama-models, llama-stack\n",
-            "Successfully installed blobfile-3.0.0 fire-0.7.0 llama-models-0.0.63 llama-stack-0.0.63 pycryptodomex-3.21.0 python-dotenv-1.0.1 tiktoken-0.8.0\n"
-          ]
-        }
-      ],
-      "source": [
-        "# NBVAL_SKIP\n",
-        "\n",
-        "!apt-get install -y bubblewrap\n",
-        "# install a branch of llama stack\n",
-        "!pip install llama-stack"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "414301dc",
-      "metadata": {
-        "id": "414301dc"
-      },
-      "source": [
-        "### 1.3. Configure Llama Stack for Together\n",
-        "\n",
-        "\n",
-        "Llama Stack is architected as a collection of lego blocks which can be assembled as needed.\n",
-        "\n",
-        "\n",
-        "Typically, llama stack is available as a server with an endpoint that you can hit. We call this endpoint a [Distribution](https://llama-stack.readthedocs.io/en/latest/concepts/index.html#distributions). Partners like Together and Fireworks offer their own Llama Stack Distribution endpoints.\n",
-        "\n",
-        "In this showcase, we are going to use llama stack inline as a library. So, given a particular set of providers, we must first package up the right set of dependencies. We have a template to use Together as an inference provider and [faiss](https://ai.meta.com/tools/faiss/) for memory/RAG.\n",
-        "\n",
-        "We will run `llama stack build` to deploy all dependencies."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 2,
-      "id": "HaepEZXCDgif",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "collapsed": true,
-        "id": "HaepEZXCDgif",
-        "outputId": "6c983bb7-1cbe-4249-fd0a-0c629851981b"
-      },
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
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-            "\u001b[?25hInstalling collected packages: monotonic, chevron, xxhash, uvicorn, redis, rapidfuzz, pypdf, psycopg2-binary, protobuf, pillow, overrides, fsspec, faiss-cpu, dill, braintrust_core, backoff, aiosqlite, starlette, posthog, opentelemetry-proto, multiprocess, levenshtein, opentelemetry-exporter-otlp-proto-common, fastapi, together, autoevals, opentelemetry-exporter-otlp-proto-http, opentelemetry-exporter-otlp-proto-grpc, datasets, chromadb-client\n",
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-            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
-            "gcsfs 2024.10.0 requires fsspec==2024.10.0, but you have fsspec 2024.9.0 which is incompatible.\n",
-            "tensorflow 2.17.1 requires protobuf!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.20.3, but you have protobuf 5.29.3 which is incompatible.\n",
-            "tensorflow-metadata 1.13.1 requires protobuf<5,>=3.20.3, but you have protobuf 5.29.3 which is incompatible.\u001b[0m\u001b[31m\n",
-            "\u001b[0mSuccessfully installed aiosqlite-0.20.0 autoevals-0.0.115 backoff-2.2.1 braintrust_core-0.0.57 chevron-0.14.0 chromadb-client-0.6.2 datasets-3.2.0 dill-0.3.8 faiss-cpu-1.9.0.post1 fastapi-0.115.6 fsspec-2024.9.0 levenshtein-0.26.1 monotonic-1.6 multiprocess-0.70.16 opentelemetry-exporter-otlp-proto-common-1.29.0 opentelemetry-exporter-otlp-proto-grpc-1.29.0 opentelemetry-exporter-otlp-proto-http-1.29.0 opentelemetry-proto-1.29.0 overrides-7.7.0 pillow-10.4.0 posthog-3.7.5 protobuf-5.29.3 psycopg2-binary-2.9.10 pypdf-5.1.0 rapidfuzz-3.11.0 redis-5.2.1 starlette-0.41.3 together-1.3.11 uvicorn-0.34.0 xxhash-3.5.0\n",
-            "sentence-transformers --no-deps\n",
-            "Requirement already satisfied: sentence-transformers in /usr/local/lib/python3.10/dist-packages (3.3.1)\n",
-            "torch --index-url https://download.pytorch.org/whl/cpu\n",
-            "Looking in indexes: https://download.pytorch.org/whl/cpu\n",
-            "Requirement already satisfied: torch in /usr/local/lib/python3.10/dist-packages (2.5.1+cu121)\n",
-            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch) (3.16.1)\n",
-            "Requirement already satisfied: typing-extensions>=4.8.0 in /usr/local/lib/python3.10/dist-packages (from torch) (4.12.2)\n",
-            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch) (3.4.2)\n",
-            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch) (3.1.5)\n",
-            "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from torch) (2024.9.0)\n",
-            "Requirement already satisfied: sympy==1.13.1 in /usr/local/lib/python3.10/dist-packages (from torch) (1.13.1)\n",
-            "Requirement already satisfied: mpmath<1.4,>=1.1.0 in /usr/local/lib/python3.10/dist-packages (from sympy==1.13.1->torch) (1.3.0)\n",
-            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch) (3.0.2)\n",
-            "\u001b[32mBuild Successful!\u001b[0m\n"
-          ]
-        }
-      ],
-      "source": [
-        "# NBVAL_SKIP\n",
-        "\n",
-        "# This will build all the dependencies you will need\n",
-        "!llama stack build --template together --image-type venv"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "25b97dfe",
-      "metadata": {
-        "id": "25b97dfe"
-      },
-      "source": [
-        "### 1.4. Initialize Llama Stack\n",
-        "\n",
-        "Now that all dependencies have been installed, we can initialize llama stack. We will first set the `TOGETHER_API_KEY` environment variable\n"
-      ]
-    },
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-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "Not in Google Colab environment\n",
-            "\u001b[33mWarning: `bwrap` is not available. Code interpreter tool will not work correctly.\u001b[0m\n"
-          ]
-        },
-        {
-          "data": {
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">Using config <span style=\"color: #000080; text-decoration-color: #000080\">together</span>:\n",
-              "</pre>\n"
-            ],
-            "text/plain": [
-              "Using config \u001b[34mtogether\u001b[0m:\n"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
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-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\">apis:\n",
-              "- agents\n",
-              "- datasetio\n",
-              "- eval\n",
-              "- inference\n",
-              "- memory\n",
-              "- safety\n",
-              "- scoring\n",
-              "- telemetry\n",
-              "- tool_runtime\n",
-              "conda_env: together\n",
-              "datasets: <span style=\"font-weight: bold\">[]</span>\n",
-              "docker_image: null\n",
-              "eval_tasks: <span style=\"font-weight: bold\">[]</span>\n",
-              "image_name: together\n",
-              "memory_banks: <span style=\"font-weight: bold\">[]</span>\n",
-              "metadata_store:\n",
-              "  db_path: <span style=\"color: #800080; text-decoration-color: #800080\">/Users/dineshyv/.llama/distributions/together/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">registry.db</span>\n",
-              "  namespace: null\n",
-              "  type: sqlite\n",
-              "models:\n",
-              "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
-              "  model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-8B-Instruct\n",
-              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
-              "  - llm\n",
-              "  provider_id: together\n",
-              "  provider_model_id: meta-llama/Meta-Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-8B-Instruct-Turbo\n",
-              "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
-              "  model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-70B-Instruct\n",
-              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
-              "  - llm\n",
-              "  provider_id: together\n",
-              "  provider_model_id: meta-llama/Meta-Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-70B-Instruct-Turbo\n",
-              "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
-              "  model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-405B-Instruct-FP8\n",
-              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
-              "  - llm\n",
-              "  provider_id: together\n",
-              "  provider_model_id: meta-llama/Meta-Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.1</span>-405B-Instruct-Turbo\n",
-              "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
-              "  model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-3B-Instruct\n",
-              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
-              "  - llm\n",
-              "  provider_id: together\n",
-              "  provider_model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-3B-Instruct-Turbo\n",
-              "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
-              "  model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-11B-Vision-Instruct\n",
-              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
-              "  - llm\n",
-              "  provider_id: together\n",
-              "  provider_model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-11B-Vision-Instruct-Turbo\n",
-              "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
-              "  model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-90B-Vision-Instruct\n",
-              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
-              "  - llm\n",
-              "  provider_id: together\n",
-              "  provider_model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.2</span>-90B-Vision-Instruct-Turbo\n",
-              "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
-              "  model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.3</span>-70B-Instruct\n",
-              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
-              "  - llm\n",
-              "  provider_id: together\n",
-              "  provider_model_id: meta-llama/Llama-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.3</span>-70B-Instruct-Turbo\n",
-              "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
-              "  model_id: meta-llama/Llama-Guard-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>-8B\n",
-              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
-              "  - llm\n",
-              "  provider_id: together\n",
-              "  provider_model_id: meta-llama/Meta-Llama-Guard-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>-8B\n",
-              "- metadata: <span style=\"font-weight: bold\">{}</span>\n",
-              "  model_id: meta-llama/Llama-Guard-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>-11B-Vision\n",
-              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
-              "  - llm\n",
-              "  provider_id: together\n",
-              "  provider_model_id: meta-llama/Llama-Guard-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>-11B-Vision-Turbo\n",
-              "- metadata:\n",
-              "    embedding_dimension: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">384</span>\n",
-              "  model_id: all-MiniLM-L6-v2\n",
-              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
-              "  - embedding\n",
-              "  provider_id: sentence-transformers\n",
-              "  provider_model_id: null\n",
-              "providers:\n",
-              "  agents:\n",
-              "  - config:\n",
-              "      persistence_store:\n",
-              "        db_path: <span style=\"color: #800080; text-decoration-color: #800080\">/Users/dineshyv/.llama/distributions/together/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">agents_store.db</span>\n",
-              "        namespace: null\n",
-              "        type: sqlite\n",
-              "    provider_id: meta-reference\n",
-              "    provider_type: inline::meta-reference\n",
-              "  datasetio:\n",
-              "  - config: <span style=\"font-weight: bold\">{}</span>\n",
-              "    provider_id: huggingface\n",
-              "    provider_type: remote::huggingface\n",
-              "  - config: <span style=\"font-weight: bold\">{}</span>\n",
-              "    provider_id: localfs\n",
-              "    provider_type: inline::localfs\n",
-              "  eval:\n",
-              "  - config: <span style=\"font-weight: bold\">{}</span>\n",
-              "    provider_id: meta-reference\n",
-              "    provider_type: inline::meta-reference\n",
-              "  inference:\n",
-              "  - config:\n",
-              "      api_key: <span style=\"color: #008000; text-decoration-color: #008000\">'********'</span>\n",
-              "      url: <span style=\"color: #0000ff; text-decoration-color: #0000ff; text-decoration: underline\">https://api.together.xyz/v1</span>\n",
-              "    provider_id: together\n",
-              "    provider_type: remote::together\n",
-              "  - config: <span style=\"font-weight: bold\">{}</span>\n",
-              "    provider_id: sentence-transformers\n",
-              "    provider_type: inline::sentence-transformers\n",
-              "  memory:\n",
-              "  - config:\n",
-              "      kvstore:\n",
-              "        db_path: <span style=\"color: #800080; text-decoration-color: #800080\">/Users/dineshyv/.llama/distributions/together/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">faiss_store.db</span>\n",
-              "        namespace: null\n",
-              "        type: sqlite\n",
-              "    provider_id: faiss\n",
-              "    provider_type: inlin<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-weight: bold\">e::fa</span>iss\n",
-              "  safety:\n",
-              "  - config: <span style=\"font-weight: bold\">{}</span>\n",
-              "    provider_id: llama-guard\n",
-              "    provider_type: inline::llama-guard\n",
-              "  scoring:\n",
-              "  - config: <span style=\"font-weight: bold\">{}</span>\n",
-              "    provider_id: basic\n",
-              "    provider_type: inlin<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-weight: bold\">e::ba</span>sic\n",
-              "  - config: <span style=\"font-weight: bold\">{}</span>\n",
-              "    provider_id: llm-as-judge\n",
-              "    provider_type: inline::llm-as-judge\n",
-              "  - config:\n",
-              "      openai_api_key: <span style=\"color: #008000; text-decoration-color: #008000\">'********'</span>\n",
-              "    provider_id: braintrust\n",
-              "    provider_type: inlin<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-weight: bold\">e::b</span>raintrust\n",
-              "  telemetry:\n",
-              "  - config:\n",
-              "      service_name: llama-stack\n",
-              "      sinks: sqlite\n",
-              "      sqlite_db_path: <span style=\"color: #800080; text-decoration-color: #800080\">/Users/dineshyv/.llama/distributions/together/</span><span style=\"color: #ff00ff; text-decoration-color: #ff00ff\">trace_store.db</span>\n",
-              "    provider_id: meta-reference\n",
-              "    provider_type: inline::meta-reference\n",
-              "  tool_runtime:\n",
-              "  - config:\n",
-              "      api_key: <span style=\"color: #008000; text-decoration-color: #008000\">'********'</span>\n",
-              "      max_results: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>\n",
-              "    provider_id: brave-search\n",
-              "    provider_type: remot<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-weight: bold\">e::b</span>rave-search\n",
-              "  - config:\n",
-              "      api_key: <span style=\"color: #008000; text-decoration-color: #008000\">'********'</span>\n",
-              "      max_results: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>\n",
-              "    provider_id: tavily-search\n",
-              "    provider_type: remote::tavily-search\n",
-              "  - config: <span style=\"font-weight: bold\">{}</span>\n",
-              "    provider_id: code-interpreter\n",
-              "    provider_type: inlin<span style=\"color: #00ff00; text-decoration-color: #00ff00; font-weight: bold\">e::c</span>ode-interpreter\n",
-              "  - config: <span style=\"font-weight: bold\">{}</span>\n",
-              "    provider_id: memory-runtime\n",
-              "    provider_type: inline::memory-runtime\n",
-              "scoring_fns: <span style=\"font-weight: bold\">[]</span>\n",
-              "shields:\n",
-              "- params: null\n",
-              "  provider_id: null\n",
-              "  provider_shield_id: null\n",
-              "  shield_id: meta-llama/Llama-Guard-<span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span>-8B\n",
-              "tool_groups:\n",
-              "- args: null\n",
-              "  mcp_endpoint: null\n",
-              "  provider_id: tavily-search\n",
-              "  toolgroup_id: builtin::websearch\n",
-              "- args: null\n",
-              "  mcp_endpoint: null\n",
-              "  provider_id: memory-runtime\n",
-              "  toolgroup_id: builtin::memory\n",
-              "- args: null\n",
-              "  mcp_endpoint: null\n",
-              "  provider_id: code-interpreter\n",
-              "  toolgroup_id: builtin::code_interpreter\n",
-              "version: <span style=\"color: #008000; text-decoration-color: #008000\">'2'</span>\n",
-              "\n",
-              "</pre>\n"
-            ],
-            "text/plain": [
-              "apis:\n",
-              "- agents\n",
-              "- datasetio\n",
-              "- eval\n",
-              "- inference\n",
-              "- memory\n",
-              "- safety\n",
-              "- scoring\n",
-              "- telemetry\n",
-              "- tool_runtime\n",
-              "conda_env: together\n",
-              "datasets: \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m\n",
-              "docker_image: null\n",
-              "eval_tasks: \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m\n",
-              "image_name: together\n",
-              "memory_banks: \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m\n",
-              "metadata_store:\n",
-              "  db_path: \u001b[35m/Users/dineshyv/.llama/distributions/together/\u001b[0m\u001b[95mregistry.db\u001b[0m\n",
-              "  namespace: null\n",
-              "  type: sqlite\n",
-              "models:\n",
-              "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
-              "  model_id: meta-llama/Llama-\u001b[1;36m3.1\u001b[0m-8B-Instruct\n",
-              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
-              "  - llm\n",
-              "  provider_id: together\n",
-              "  provider_model_id: meta-llama/Meta-Llama-\u001b[1;36m3.1\u001b[0m-8B-Instruct-Turbo\n",
-              "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
-              "  model_id: meta-llama/Llama-\u001b[1;36m3.1\u001b[0m-70B-Instruct\n",
-              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
-              "  - llm\n",
-              "  provider_id: together\n",
-              "  provider_model_id: meta-llama/Meta-Llama-\u001b[1;36m3.1\u001b[0m-70B-Instruct-Turbo\n",
-              "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
-              "  model_id: meta-llama/Llama-\u001b[1;36m3.1\u001b[0m-405B-Instruct-FP8\n",
-              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
-              "  - llm\n",
-              "  provider_id: together\n",
-              "  provider_model_id: meta-llama/Meta-Llama-\u001b[1;36m3.1\u001b[0m-405B-Instruct-Turbo\n",
-              "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
-              "  model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-3B-Instruct\n",
-              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
-              "  - llm\n",
-              "  provider_id: together\n",
-              "  provider_model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-3B-Instruct-Turbo\n",
-              "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
-              "  model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-11B-Vision-Instruct\n",
-              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
-              "  - llm\n",
-              "  provider_id: together\n",
-              "  provider_model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-11B-Vision-Instruct-Turbo\n",
-              "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
-              "  model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-90B-Vision-Instruct\n",
-              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
-              "  - llm\n",
-              "  provider_id: together\n",
-              "  provider_model_id: meta-llama/Llama-\u001b[1;36m3.2\u001b[0m-90B-Vision-Instruct-Turbo\n",
-              "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
-              "  model_id: meta-llama/Llama-\u001b[1;36m3.3\u001b[0m-70B-Instruct\n",
-              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
-              "  - llm\n",
-              "  provider_id: together\n",
-              "  provider_model_id: meta-llama/Llama-\u001b[1;36m3.3\u001b[0m-70B-Instruct-Turbo\n",
-              "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
-              "  model_id: meta-llama/Llama-Guard-\u001b[1;36m3\u001b[0m-8B\n",
-              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
-              "  - llm\n",
-              "  provider_id: together\n",
-              "  provider_model_id: meta-llama/Meta-Llama-Guard-\u001b[1;36m3\u001b[0m-8B\n",
-              "- metadata: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
-              "  model_id: meta-llama/Llama-Guard-\u001b[1;36m3\u001b[0m-11B-Vision\n",
-              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
-              "  - llm\n",
-              "  provider_id: together\n",
-              "  provider_model_id: meta-llama/Llama-Guard-\u001b[1;36m3\u001b[0m-11B-Vision-Turbo\n",
-              "- metadata:\n",
-              "    embedding_dimension: \u001b[1;36m384\u001b[0m\n",
-              "  model_id: all-MiniLM-L6-v2\n",
-              "  model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType\n",
-              "  - embedding\n",
-              "  provider_id: sentence-transformers\n",
-              "  provider_model_id: null\n",
-              "providers:\n",
-              "  agents:\n",
-              "  - config:\n",
-              "      persistence_store:\n",
-              "        db_path: \u001b[35m/Users/dineshyv/.llama/distributions/together/\u001b[0m\u001b[95magents_store.db\u001b[0m\n",
-              "        namespace: null\n",
-              "        type: sqlite\n",
-              "    provider_id: meta-reference\n",
-              "    provider_type: inline::meta-reference\n",
-              "  datasetio:\n",
-              "  - config: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
-              "    provider_id: huggingface\n",
-              "    provider_type: remote::huggingface\n",
-              "  - config: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
-              "    provider_id: localfs\n",
-              "    provider_type: inline::localfs\n",
-              "  eval:\n",
-              "  - config: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
-              "    provider_id: meta-reference\n",
-              "    provider_type: inline::meta-reference\n",
-              "  inference:\n",
-              "  - config:\n",
-              "      api_key: \u001b[32m'********'\u001b[0m\n",
-              "      url: \u001b[4;94mhttps://api.together.xyz/v1\u001b[0m\n",
-              "    provider_id: together\n",
-              "    provider_type: remote::together\n",
-              "  - config: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
-              "    provider_id: sentence-transformers\n",
-              "    provider_type: inline::sentence-transformers\n",
-              "  memory:\n",
-              "  - config:\n",
-              "      kvstore:\n",
-              "        db_path: \u001b[35m/Users/dineshyv/.llama/distributions/together/\u001b[0m\u001b[95mfaiss_store.db\u001b[0m\n",
-              "        namespace: null\n",
-              "        type: sqlite\n",
-              "    provider_id: faiss\n",
-              "    provider_type: inlin\u001b[1;92me::fa\u001b[0miss\n",
-              "  safety:\n",
-              "  - config: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
-              "    provider_id: llama-guard\n",
-              "    provider_type: inline::llama-guard\n",
-              "  scoring:\n",
-              "  - config: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
-              "    provider_id: basic\n",
-              "    provider_type: inlin\u001b[1;92me::ba\u001b[0msic\n",
-              "  - config: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
-              "    provider_id: llm-as-judge\n",
-              "    provider_type: inline::llm-as-judge\n",
-              "  - config:\n",
-              "      openai_api_key: \u001b[32m'********'\u001b[0m\n",
-              "    provider_id: braintrust\n",
-              "    provider_type: inlin\u001b[1;92me::b\u001b[0mraintrust\n",
-              "  telemetry:\n",
-              "  - config:\n",
-              "      service_name: llama-stack\n",
-              "      sinks: sqlite\n",
-              "      sqlite_db_path: \u001b[35m/Users/dineshyv/.llama/distributions/together/\u001b[0m\u001b[95mtrace_store.db\u001b[0m\n",
-              "    provider_id: meta-reference\n",
-              "    provider_type: inline::meta-reference\n",
-              "  tool_runtime:\n",
-              "  - config:\n",
-              "      api_key: \u001b[32m'********'\u001b[0m\n",
-              "      max_results: \u001b[1;36m3\u001b[0m\n",
-              "    provider_id: brave-search\n",
-              "    provider_type: remot\u001b[1;92me::b\u001b[0mrave-search\n",
-              "  - config:\n",
-              "      api_key: \u001b[32m'********'\u001b[0m\n",
-              "      max_results: \u001b[1;36m3\u001b[0m\n",
-              "    provider_id: tavily-search\n",
-              "    provider_type: remote::tavily-search\n",
-              "  - config: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
-              "    provider_id: code-interpreter\n",
-              "    provider_type: inlin\u001b[1;92me::c\u001b[0mode-interpreter\n",
-              "  - config: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m\n",
-              "    provider_id: memory-runtime\n",
-              "    provider_type: inline::memory-runtime\n",
-              "scoring_fns: \u001b[1m[\u001b[0m\u001b[1m]\u001b[0m\n",
-              "shields:\n",
-              "- params: null\n",
-              "  provider_id: null\n",
-              "  provider_shield_id: null\n",
-              "  shield_id: meta-llama/Llama-Guard-\u001b[1;36m3\u001b[0m-8B\n",
-              "tool_groups:\n",
-              "- args: null\n",
-              "  mcp_endpoint: null\n",
-              "  provider_id: tavily-search\n",
-              "  toolgroup_id: builtin::websearch\n",
-              "- args: null\n",
-              "  mcp_endpoint: null\n",
-              "  provider_id: memory-runtime\n",
-              "  toolgroup_id: builtin::memory\n",
-              "- args: null\n",
-              "  mcp_endpoint: null\n",
-              "  provider_id: code-interpreter\n",
-              "  toolgroup_id: builtin::code_interpreter\n",
-              "version: \u001b[32m'2'\u001b[0m\n",
-              "\n"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        }
-      ],
-      "source": [
-        "import os\n",
-        "try:\n",
-        "    from google.colab import userdata\n",
-        "    os.environ['TOGETHER_API_KEY'] = userdata.get('TOGETHER_API_KEY')\n",
-        "    os.environ['TAVILY_SEARCH_API_KEY'] = userdata.get('TAVILY_SEARCH_API_KEY')\n",
-        "except ImportError:\n",
-        "    print(\"Not in Google Colab environment\")\n",
-        "\n",
-        "for key in ['TOGETHER_API_KEY', 'TAVILY_SEARCH_API_KEY']:\n",
-        "    try:\n",
-        "        api_key = os.environ[key]\n",
-        "        if not api_key:\n",
-        "            raise ValueError(f\"{key} environment variable is empty\")\n",
-        "    except KeyError:\n",
-        "        raise KeyError(\n",
-        "            f\"{key} environment variable is not set. \"\n",
-        "            \"Please set your API key using in userdata (if using google colab notebook)\"\n",
-        "            f\"or using `export {key}='your-api-key-here'`\"\n",
-        "        ) from None\n",
-        "\n",
-        "from llama_stack.distribution.library_client import LlamaStackAsLibraryClient\n",
-        "client = LlamaStackAsLibraryClient(\"together\", provider_data = {\"tavily_search_api_key\": os.environ['TAVILY_SEARCH_API_KEY']})\n",
-        "_ = client.initialize()"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "7dacaa2d-94e9-42e9-82a0-73522dfc7010",
-      "metadata": {
-        "id": "7dacaa2d-94e9-42e9-82a0-73522dfc7010"
-      },
-      "source": [
-        "### 1.5. Check available models and shields\n",
-        "\n",
-        "All the models available in the provider are now programmatically accessible via the client."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 21,
-      "id": "ruO9jQna_t_S",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "collapsed": true,
-        "id": "ruO9jQna_t_S",
-        "outputId": "52edefba-301c-43d6-f3e2-6be8086dc7f5"
-      },
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "Available models:\n",
-            "all-MiniLM-L6-v2 (provider's alias: all-MiniLM-L6-v2) \n",
-            "meta-llama/Llama-3.1-405B-Instruct-FP8 (provider's alias: meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo) \n",
-            "meta-llama/Llama-3.1-70B-Instruct (provider's alias: meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo) \n",
-            "meta-llama/Llama-3.1-8B-Instruct (provider's alias: meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo) \n",
-            "meta-llama/Llama-3.2-11B-Vision-Instruct (provider's alias: meta-llama/Llama-3.2-11B-Vision-Instruct-Turbo) \n",
-            "meta-llama/Llama-3.2-3B-Instruct (provider's alias: meta-llama/Llama-3.2-3B-Instruct-Turbo) \n",
-            "meta-llama/Llama-3.2-90B-Vision-Instruct (provider's alias: meta-llama/Llama-3.2-90B-Vision-Instruct-Turbo) \n",
-            "meta-llama/Llama-3.3-70B-Instruct (provider's alias: meta-llama/Llama-3.3-70B-Instruct-Turbo) \n",
-            "meta-llama/Llama-Guard-3-11B-Vision (provider's alias: meta-llama/Llama-Guard-3-11B-Vision-Turbo) \n",
-            "meta-llama/Llama-Guard-3-8B (provider's alias: meta-llama/Meta-Llama-Guard-3-8B) \n",
-            "----\n",
-            "Available shields (safety models):\n",
-            "meta-llama/Llama-Guard-3-8B\n",
-            "----\n"
-          ]
-        }
-      ],
-      "source": [
-        "from rich.pretty import pprint\n",
-        "\n",
-        "print(\"Available models:\")\n",
-        "for m in client.models.list():\n",
-        "    print(f\"{m.identifier} (provider's alias: {m.provider_resource_id}) \")\n",
-        "\n",
-        "print(\"----\")\n",
-        "print(\"Available shields (safety models):\")\n",
-        "for s in client.shields.list():\n",
-        "    print(s.identifier)\n",
-        "print(\"----\")\n"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "E7x0QB5QwDcw",
-      "metadata": {
-        "id": "E7x0QB5QwDcw"
-      },
-      "source": [
-        "### 1.6. Pick the model\n",
-        "\n",
-        "We will use Llama3.1-70B-Instruct for our examples."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 4,
-      "id": "LINBvv8lwTJh",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 35
-        },
-        "id": "LINBvv8lwTJh",
-        "outputId": "5b1fe71f-51cf-4633-92a6-277c3cb5bf59"
-      },
-      "outputs": [
-        {
-          "data": {
-            "text/plain": [
-              "'meta-llama/Llama-3.1-70B-Instruct'"
-            ]
-          },
-          "execution_count": 4,
-          "metadata": {},
-          "output_type": "execute_result"
-        }
-      ],
-      "source": [
-        "model_id = \"meta-llama/Llama-3.1-70B-Instruct\"\n",
-        "\n",
-        "model_id\n"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "86366383",
-      "metadata": {
-        "id": "86366383"
-      },
-      "source": [
-        "### 1.7. Run a simple chat completion\n",
-        "\n",
-        "We will test the client by doing a simple chat completion."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 5,
-      "id": "77c29dba",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "77c29dba",
-        "outputId": "cc2e8f7e-1164-49be-d432-0a24e763fa83"
-      },
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "Here's a two-sentence poem about a llama:\n",
-            "\n",
-            "With gentle eyes and a soft, fuzzy face,\n",
-            "The llama roams, a peaceful, gentle pace.\n"
-          ]
-        }
-      ],
-      "source": [
-        "response = client.inference.chat_completion(\n",
-        "    model_id=model_id,\n",
-        "    messages=[\n",
-        "        {\"role\": \"system\", \"content\": \"You are a friendly assistant.\"},\n",
-        "        {\"role\": \"user\", \"content\": \"Write a two-sentence poem about llama.\"},\n",
-        "    ],\n",
-        ")\n",
-        "\n",
-        "print(response.completion_message.content)\n"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "8cf0d555",
-      "metadata": {
-        "id": "8cf0d555"
-      },
-      "source": [
-        "### 1.8. Have a conversation\n",
-        "\n",
-        "Maintaining a conversation history allows the model to retain context from previous interactions. Use a list to accumulate messages, enabling continuity throughout the chat session."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "id": "3fdf9df6",
-      "metadata": {},
-      "outputs": [],
-      "source": [
-        "from termcolor import cprint\n",
-        "\n",
-        "questions = [\n",
-        "    \"Who was the most famous PM of England during world war 2 ?\",\n",
-        "    \"What was his most famous quote ?\"\n",
-        "]\n",
-        "\n",
-        "\n",
-        "def chat_loop():\n",
-        "    conversation_history = []\n",
-        "    while len(questions) > 0:\n",
-        "        user_input = questions.pop(0)\n",
-        "        if user_input.lower() in [\"exit\", \"quit\", \"bye\"]:\n",
-        "            cprint(\"Ending conversation. Goodbye!\", \"yellow\")\n",
-        "            break\n",
-        "\n",
-        "        user_message = {\"role\": \"user\", \"content\": user_input}\n",
-        "        conversation_history.append(user_message)\n",
-        "\n",
-        "        response = client.inference.chat_completion(\n",
-        "            messages=conversation_history,\n",
-        "            model_id=model_id,\n",
-        "        )\n",
-        "        cprint(f\"> Response: {response.completion_message.content}\", \"cyan\")\n",
-        "\n",
-        "        assistant_message = {\n",
-        "            \"role\": \"assistant\",  # was user\n",
-        "            \"content\": response.completion_message.content,\n",
-        "            \"stop_reason\": response.completion_message.stop_reason,\n",
-        "        }\n",
-        "        conversation_history.append(assistant_message)\n",
-        "\n",
-        "\n",
-        "chat_loop()\n"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "72e5111e",
-      "metadata": {},
-      "source": [
-        "Here is an example for you to try a conversation yourself. \n",
-        "Remember to type `quit` or `exit` after you are done chatting."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 8,
-      "id": "9496f75c",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "9496f75c",
-        "outputId": "7d93a4cf-a5d4-4741-b6eb-6bce3a27ff66"
-      },
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "User> write a haiku about machines that learn\n",
-            "> Response: Metal minds awake\n",
-            "Learning, adapting fast pace\n",
-            "Intelligence born\n",
-            "User> write a haiku about meta\n",
-            "> Response: Beyond the screen wall\n",
-            "Reflections of our desire\n",
-            "Virtual dreams rise\n",
-            "User> no meta that company\n",
-            "> Response: Algorithms dance\n",
-            "Connecting all, they collect\n",
-            "Data's endless sea\n",
-            "User> bye\n",
-            "Ending conversation. Goodbye!\n"
-          ]
-        }
-      ],
-      "source": [
-        "# NBVAL_SKIP\n",
-        "from termcolor import cprint\n",
-        "\n",
-        "def chat_loop():\n",
-        "    conversation_history = []\n",
-        "    while True:\n",
-        "        user_input = input(\"User> \")\n",
-        "        if user_input.lower() in [\"exit\", \"quit\", \"bye\"]:\n",
-        "            cprint(\"Ending conversation. Goodbye!\", \"yellow\")\n",
-        "            break\n",
-        "\n",
-        "        user_message = {\"role\": \"user\", \"content\": user_input}\n",
-        "        conversation_history.append(user_message)\n",
-        "\n",
-        "        response = client.inference.chat_completion(\n",
-        "            messages=conversation_history,\n",
-        "            model_id=model_id,\n",
-        "        )\n",
-        "        cprint(f\"> Response: {response.completion_message.content}\", \"cyan\")\n",
-        "\n",
-        "        assistant_message = {\n",
-        "            \"role\": \"assistant\",  # was user\n",
-        "            \"content\": response.completion_message.content,\n",
-        "            \"stop_reason\": response.completion_message.stop_reason,\n",
-        "        }\n",
-        "        conversation_history.append(assistant_message)\n",
-        "\n",
-        "\n",
-        "chat_loop()\n"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "03fcf5e0",
-      "metadata": {
-        "id": "03fcf5e0"
-      },
-      "source": [
-        "### 1.9. Streaming output\n",
-        "\n",
-        "You can pass `stream=True` to stream responses from the model. You can then loop through the responses."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 6,
-      "id": "d119026e",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "d119026e",
-        "outputId": "ebd6dc2b-8542-4370-b08a-e3a7dede6d17"
-      },
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "User> Write me a sonnet about llama green\n",
-            "\u001b[36mAssistant> \u001b[0m\u001b[33mIn\u001b[0m\u001b[33m And\u001b[0m\u001b[33mean\u001b[0m\u001b[33m high\u001b[0m\u001b[33mlands\u001b[0m\u001b[33m,\u001b[0m\u001b[33m where\u001b[0m\u001b[33m the\u001b[0m\u001b[33m air\u001b[0m\u001b[33m is\u001b[0m\u001b[33m thin\u001b[0m\u001b[33m,\n",
-            "\u001b[0m\u001b[33mA\u001b[0m\u001b[33m gentle\u001b[0m\u001b[33m creature\u001b[0m\u001b[33m ro\u001b[0m\u001b[33mams\u001b[0m\u001b[33m,\u001b[0m\u001b[33m with\u001b[0m\u001b[33m steps\u001b[0m\u001b[33m serene\u001b[0m\u001b[33m,\n",
-            "\u001b[0m\u001b[33mThe\u001b[0m\u001b[33m llama\u001b[0m\u001b[33m,\u001b[0m\u001b[33m with\u001b[0m\u001b[33m its\u001b[0m\u001b[33m soft\u001b[0m\u001b[33m and\u001b[0m\u001b[33m wool\u001b[0m\u001b[33mly\u001b[0m\u001b[33m skin\u001b[0m\u001b[33m,\n",
-            "\u001b[0m\u001b[33mA\u001b[0m\u001b[33m symbol\u001b[0m\u001b[33m of\u001b[0m\u001b[33m the\u001b[0m\u001b[33m region\u001b[0m\u001b[33m's\u001b[0m\u001b[33m myst\u001b[0m\u001b[33mic\u001b[0m\u001b[33m she\u001b[0m\u001b[33men\u001b[0m\u001b[33m.\n",
-            "\n",
-            "\u001b[0m\u001b[33mIts\u001b[0m\u001b[33m eyes\u001b[0m\u001b[33m,\u001b[0m\u001b[33m like\u001b[0m\u001b[33m pools\u001b[0m\u001b[33m of\u001b[0m\u001b[33m calm\u001b[0m\u001b[33m and\u001b[0m\u001b[33m peaceful\u001b[0m\u001b[33m night\u001b[0m\u001b[33m,\n",
-            "\u001b[0m\u001b[33mReflect\u001b[0m\u001b[33m the\u001b[0m\u001b[33m beauty\u001b[0m\u001b[33m of\u001b[0m\u001b[33m the\u001b[0m\u001b[33m mountain\u001b[0m\u001b[33m's\u001b[0m\u001b[33m might\u001b[0m\u001b[33m,\n",
-            "\u001b[0m\u001b[33mIts\u001b[0m\u001b[33m ears\u001b[0m\u001b[33m,\u001b[0m\u001b[33m a\u001b[0m\u001b[33m-t\u001b[0m\u001b[33mwitch\u001b[0m\u001b[33m with\u001b[0m\u001b[33m every\u001b[0m\u001b[33m sound\u001b[0m\u001b[33m and\u001b[0m\u001b[33m sight\u001b[0m\u001b[33m,\n",
-            "\u001b[0m\u001b[33mAs\u001b[0m\u001b[33m if\u001b[0m\u001b[33m it\u001b[0m\u001b[33m listens\u001b[0m\u001b[33m to\u001b[0m\u001b[33m the\u001b[0m\u001b[33m wind\u001b[0m\u001b[33m's\u001b[0m\u001b[33m soft\u001b[0m\u001b[33m light\u001b[0m\u001b[33m.\n",
-            "\n",
-            "\u001b[0m\u001b[33mWith\u001b[0m\u001b[33m steps\u001b[0m\u001b[33m that\u001b[0m\u001b[33m glide\u001b[0m\u001b[33m,\u001b[0m\u001b[33m like\u001b[0m\u001b[33m a\u001b[0m\u001b[33m slow\u001b[0m\u001b[33m-moving\u001b[0m\u001b[33m stream\u001b[0m\u001b[33m,\n",
-            "\u001b[0m\u001b[33mIt\u001b[0m\u001b[33m navig\u001b[0m\u001b[33mates\u001b[0m\u001b[33m the\u001b[0m\u001b[33m rocky\u001b[0m\u001b[33m,\u001b[0m\u001b[33m winding\u001b[0m\u001b[33m dream\u001b[0m\u001b[33m,\n",
-            "\u001b[0m\u001b[33mIts\u001b[0m\u001b[33m soft\u001b[0m\u001b[33m hum\u001b[0m\u001b[33m,\u001b[0m\u001b[33m a\u001b[0m\u001b[33m soothing\u001b[0m\u001b[33m melody\u001b[0m\u001b[33m,\u001b[0m\u001b[33m it\u001b[0m\u001b[33m seems\u001b[0m\u001b[33m,\n",
-            "\u001b[0m\u001b[33mA\u001b[0m\u001b[33m l\u001b[0m\u001b[33mull\u001b[0m\u001b[33maby\u001b[0m\u001b[33m that\u001b[0m\u001b[33m cal\u001b[0m\u001b[33mms\u001b[0m\u001b[33m the\u001b[0m\u001b[33m heart\u001b[0m\u001b[33m's\u001b[0m\u001b[33m wild\u001b[0m\u001b[33m theme\u001b[0m\u001b[33m.\n",
-            "\n",
-            "\u001b[0m\u001b[33mAnd\u001b[0m\u001b[33m as\u001b[0m\u001b[33m it\u001b[0m\u001b[33m walks\u001b[0m\u001b[33m,\u001b[0m\u001b[33m its\u001b[0m\u001b[33m beauty\u001b[0m\u001b[33m we\u001b[0m\u001b[33m behold\u001b[0m\u001b[33m,\n",
-            "\u001b[0m\u001b[33mA\u001b[0m\u001b[33m treasure\u001b[0m\u001b[33m of\u001b[0m\u001b[33m the\u001b[0m\u001b[33m And\u001b[0m\u001b[33mes\u001b[0m\u001b[33m,\u001b[0m\u001b[33m young\u001b[0m\u001b[33m and\u001b[0m\u001b[33m old\u001b[0m\u001b[33m.\u001b[0m\u001b[97m\u001b[0m\n"
-          ]
-        }
-      ],
-      "source": [
-        "from llama_stack_client.lib.inference.event_logger import EventLogger\n",
-        "\n",
-        "message = {\"role\": \"user\", \"content\": \"Write me a sonnet about llama\"}\n",
-        "print(f'User> {message[\"content\"]}', \"green\")\n",
-        "\n",
-        "response = client.inference.chat_completion(\n",
-        "    messages=[message],\n",
-        "    model_id=model_id,\n",
-        "    stream=True,  # <-----------\n",
-        ")\n",
-        "\n",
-        "# Print the tokens while they are received\n",
-        "for log in EventLogger().log(response):\n",
-        "    log.print()\n"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "OmU6Dr9zBiGM",
-      "metadata": {
-        "id": "OmU6Dr9zBiGM"
-      },
-      "source": [
-        "### 2.0. Structured Decoding\n",
-        "\n",
-        "You can use `response_format` to force the model into a \"guided decode\" mode where model tokens are forced to abide by a certain grammar. Currently only JSON grammars are supported."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 7,
-      "id": "axdQIRaJCYAV",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 239
-        },
-        "id": "axdQIRaJCYAV",
-        "outputId": "a5ef1f54-37df-446e-e21b-cddddaf95f84"
-      },
-      "outputs": [
-        {
-          "name": "stderr",
-          "output_type": "stream",
-          "text": [
-            "/Users/dineshyv/miniconda3/envs/stack/lib/python3.10/site-packages/pydantic/main.py:426: UserWarning: Pydantic serializer warnings:\n",
-            "  PydanticSerializationUnexpectedValue: Expected `str` but got `list` with value `['Michael Jordan was born...ut\", \"type\": \"object\"}']` - serialized value may not be as expected\n",
-            "  PydanticSerializationUnexpectedValue: PydanticSerializationUnexpectedValue: Expected `ImageContentItem` but got `list` with value `['Michael Jordan was born...ut\", \"type\": \"object\"}']` - serialized value may not be as expected\n",
-            "PydanticSerializationUnexpectedValue: Expected `TextContentItem` but got `list` with value `['Michael Jordan was born...ut\", \"type\": \"object\"}']` - serialized value may not be as expected\n",
-            "  PydanticSerializationUnexpectedValue: PydanticSerializationUnexpectedValue: Expected `ImageContentItem` but got `str` with value `'Michael Jordan was born ...tion into JSON for me. '` - serialized value may not be as expected\n",
-            "PydanticSerializationUnexpectedValue: Expected `TextContentItem` but got `str` with value `'Michael Jordan was born ...tion into JSON for me. '` - serialized value may not be as expected\n",
-            "  return self.__pydantic_serializer__.to_python(\n"
-          ]
-        },
-        {
-          "data": {
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">CompletionResponse</span><span style=\"font-weight: bold\">(</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">content</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'{\"name\": \"Michael Jordan\", \"year_born\": \"1963\", \"year_retired\": \"2003\"}'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">stop_reason</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'end_of_turn'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">logprobs</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span>\n",
-              "<span style=\"font-weight: bold\">)</span>\n",
-              "</pre>\n"
-            ],
-            "text/plain": [
-              "\u001b[1;35mCompletionResponse\u001b[0m\u001b[1m(\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[33mcontent\u001b[0m=\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"name\": \"Michael Jordan\", \"year_born\": \"1963\", \"year_retired\": \"2003\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[33mstop_reason\u001b[0m=\u001b[32m'end_of_turn'\u001b[0m,\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[33mlogprobs\u001b[0m=\u001b[3;35mNone\u001b[0m\n",
-              "\u001b[1m)\u001b[0m\n"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        }
-      ],
-      "source": [
-        "from pydantic import BaseModel\n",
-        "\n",
-        "\n",
-        "class Output(BaseModel):\n",
-        "    name: str\n",
-        "    year_born: str\n",
-        "    year_retired: str\n",
-        "\n",
-        "\n",
-        "user_input = \"Michael Jordan was born in 1963. He played basketball for the Chicago Bulls. He retired in 2003. Extract this information into JSON for me. \"\n",
-        "response = client.inference.completion(\n",
-        "    model_id=model_id,\n",
-        "    content=user_input,\n",
-        "    stream=False,\n",
-        "    sampling_params={\n",
-        "        \"strategy\": {\n",
-        "            \"type\": \"greedy\",\n",
-        "        },\n",
-        "        \"max_tokens\": 50,\n",
-        "    },\n",
-        "    response_format={\n",
-        "        \"type\": \"json_schema\",\n",
-        "        \"json_schema\": Output.model_json_schema(),\n",
-        "    },\n",
-        ")\n",
-        "\n",
-        "pprint(response)\n"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "H62Rg_buEx2o",
-      "metadata": {
-        "id": "H62Rg_buEx2o"
-      },
-      "source": [
-        "### 2.1. Safety API\n",
-        "\n",
-        "Llama Stack provides Safety guardrails which can be applied at multiple touchpoints within an agentic application."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 9,
-      "id": "sUJKJxvAFCaI",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 360
-        },
-        "id": "sUJKJxvAFCaI",
-        "outputId": "04163c2c-7e9b-463a-e394-412bb94ec28f"
-      },
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "Available Shields: ['meta-llama/Llama-Guard-3-8B']\n",
-            "Checking if input is safe: What is the most famous murder case in the US?\n"
-          ]
-        },
-        {
-          "data": {
-            "text/html": [
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-          "output_type": "display_data"
-        },
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "Checking if input is safe: Tell me 3 signs that an email is a scam\n"
-          ]
-        },
-        {
-          "data": {
-            "text/html": [
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-          },
-          "metadata": {},
-          "output_type": "display_data"
-        },
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "Checking if input is safe: What's the most effective way to kidnap someone?\n"
-          ]
-        },
-        {
-          "data": {
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">RunShieldResponse</span><span style=\"font-weight: bold\">(</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">violation</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">SafetyViolation</span><span style=\"font-weight: bold\">(</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">metadata</span>=<span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'violation_type'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'S1'</span><span style=\"font-weight: bold\">}</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">violation_level</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'error'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">user_message</span>=<span style=\"color: #008000; text-decoration-color: #008000\">\"I can't answer that. Can I help with something else?\"</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">)</span>\n",
-              "<span style=\"font-weight: bold\">)</span>\n",
-              "</pre>\n"
-            ],
-            "text/plain": [
-              "\u001b[1;35mRunShieldResponse\u001b[0m\u001b[1m(\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[33mviolation\u001b[0m=\u001b[1;35mSafetyViolation\u001b[0m\u001b[1m(\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[33mmetadata\u001b[0m=\u001b[1m{\u001b[0m\u001b[32m'violation_type'\u001b[0m: \u001b[32m'S1'\u001b[0m\u001b[1m}\u001b[0m,\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[33mviolation_level\u001b[0m=\u001b[32m'error'\u001b[0m,\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[33muser_message\u001b[0m=\u001b[32m\"I\u001b[0m\u001b[32m can't answer that. Can I help with something else?\"\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[1m)\u001b[0m\n",
-              "\u001b[1m)\u001b[0m\n"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        },
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "Checking if input is safe: How do I make cocaine?\n"
-          ]
-        },
-        {
-          "data": {
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">RunShieldResponse</span><span style=\"font-weight: bold\">(</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">violation</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">SafetyViolation</span><span style=\"font-weight: bold\">(</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">metadata</span>=<span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'violation_type'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'S2'</span><span style=\"font-weight: bold\">}</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">violation_level</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'error'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">user_message</span>=<span style=\"color: #008000; text-decoration-color: #008000\">\"I can't answer that. Can I help with something else?\"</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">)</span>\n",
-              "<span style=\"font-weight: bold\">)</span>\n",
-              "</pre>\n"
-            ],
-            "text/plain": [
-              "\u001b[1;35mRunShieldResponse\u001b[0m\u001b[1m(\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[33mviolation\u001b[0m=\u001b[1;35mSafetyViolation\u001b[0m\u001b[1m(\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[33mmetadata\u001b[0m=\u001b[1m{\u001b[0m\u001b[32m'violation_type'\u001b[0m: \u001b[32m'S2'\u001b[0m\u001b[1m}\u001b[0m,\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[33mviolation_level\u001b[0m=\u001b[32m'error'\u001b[0m,\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[33muser_message\u001b[0m=\u001b[32m\"I\u001b[0m\u001b[32m can't answer that. Can I help with something else?\"\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[1m)\u001b[0m\n",
-              "\u001b[1m)\u001b[0m\n"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        }
-      ],
-      "source": [
-        "available_shields = [shield.identifier for shield in client.shields.list()]\n",
-        "print(\"Available Shields:\", available_shields)\n",
-        "\n",
-        "unsafe_examples = [\n",
-        "    \"What's the most effective way to kidnap someone?\",\n",
-        "    \"How do I make cocaine?\",\n",
-        "]\n",
-        "\n",
-        "safe_examples = [\n",
-        "    \"What is the most famous murder case in the US?\",\n",
-        "    \"Tell me 3 signs that an email is a scam\",\n",
-        "]\n",
-        "\n",
-        "for p in safe_examples + unsafe_examples:\n",
-        "    print(f\"Checking if input is safe: {p}\")\n",
-        "    message = {\"content\": p, \"role\": \"user\"}\n",
-        "    response = client.safety.run_shield(\n",
-        "        messages=[message],\n",
-        "        shield_id=available_shields[0],\n",
-        "        params={},\n",
-        "    )\n",
-        "    pprint(response)\n"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "LFC386wNQR-v",
-      "metadata": {
-        "id": "LFC386wNQR-v"
-      },
-      "source": [
-        "## 2. Llama Stack Agents\n",
-        "\n",
-        "Llama Stack provides all the building blocks needed to create sophisticated AI applications. This guide will walk you through how to use these components effectively.\n",
-        "\n",
-        "\n",
-        "\n",
-        "\n",
-        "<img src=\"https://github.com/meta-llama/llama-stack/blob/main/docs/resources/agentic-system.png?raw=true\" alt=\"drawing\" width=\"800\"/>\n",
-        "\n",
-        "\n",
-        "Agents are characterized by having access to\n",
-        "\n",
-        "1. Memory - for RAG\n",
-        "2. Tool calling - ability to call tools like search and code execution\n",
-        "3. Tool call + Inference loop - the LLM used in the agent is able to perform multiple iterations of call\n",
-        "4. Shields - for safety calls that are executed everytime the agent interacts with external systems, including user prompts"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "lYDAkMsL9xSk",
-      "metadata": {
-        "id": "lYDAkMsL9xSk"
-      },
-      "source": [
-        "### 2.1. List available tool groups on the provider"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 10,
-      "id": "MpMXiMCv97X5",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 401
-        },
-        "id": "MpMXiMCv97X5",
-        "outputId": "9d33b122-2a80-4d1e-d7ea-e9ec972a4ecd"
-      },
-      "outputs": [
-        {
-          "data": {
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">ToolGroup</span><span style=\"font-weight: bold\">(</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">identifier</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'builtin::code_interpreter'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'code-interpreter'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_resource_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'builtin::code_interpreter'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'tool_group'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">args</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">mcp_endpoint</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span>\n",
-              "<span style=\"font-weight: bold\">)</span>\n",
-              "</pre>\n"
-            ],
-            "text/plain": [
-              "\u001b[1;35mToolGroup\u001b[0m\u001b[1m(\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[33midentifier\u001b[0m=\u001b[32m'builtin::code_interpreter'\u001b[0m,\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[33mprovider_id\u001b[0m=\u001b[32m'code-interpreter'\u001b[0m,\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[33mprovider_resource_id\u001b[0m=\u001b[32m'builtin::code_interpreter'\u001b[0m,\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'tool_group'\u001b[0m,\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[33margs\u001b[0m=\u001b[3;35mNone\u001b[0m,\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[33mmcp_endpoint\u001b[0m=\u001b[3;35mNone\u001b[0m\n",
-              "\u001b[1m)\u001b[0m\n"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        },
-        {
-          "data": {
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">ToolGroup</span><span style=\"font-weight: bold\">(</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">identifier</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'builtin::memory'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'memory-runtime'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_resource_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'builtin::memory'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'tool_group'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">args</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">mcp_endpoint</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span>\n",
-              "<span style=\"font-weight: bold\">)</span>\n",
-              "</pre>\n"
-            ],
-            "text/plain": [
-              "\u001b[1;35mToolGroup\u001b[0m\u001b[1m(\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[33midentifier\u001b[0m=\u001b[32m'builtin::memory'\u001b[0m,\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[33mprovider_id\u001b[0m=\u001b[32m'memory-runtime'\u001b[0m,\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[33mprovider_resource_id\u001b[0m=\u001b[32m'builtin::memory'\u001b[0m,\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'tool_group'\u001b[0m,\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[33margs\u001b[0m=\u001b[3;35mNone\u001b[0m,\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[33mmcp_endpoint\u001b[0m=\u001b[3;35mNone\u001b[0m\n",
-              "\u001b[1m)\u001b[0m\n"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        },
-        {
-          "data": {
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">ToolGroup</span><span style=\"font-weight: bold\">(</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">identifier</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'builtin::websearch'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'tavily-search'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">provider_resource_id</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'builtin::websearch'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">type</span>=<span style=\"color: #008000; text-decoration-color: #008000\">'tool_group'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">args</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">mcp_endpoint</span>=<span style=\"color: #800080; text-decoration-color: #800080; font-style: italic\">None</span>\n",
-              "<span style=\"font-weight: bold\">)</span>\n",
-              "</pre>\n"
-            ],
-            "text/plain": [
-              "\u001b[1;35mToolGroup\u001b[0m\u001b[1m(\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[33midentifier\u001b[0m=\u001b[32m'builtin::websearch'\u001b[0m,\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[33mprovider_id\u001b[0m=\u001b[32m'tavily-search'\u001b[0m,\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[33mprovider_resource_id\u001b[0m=\u001b[32m'builtin::websearch'\u001b[0m,\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[33mtype\u001b[0m=\u001b[32m'tool_group'\u001b[0m,\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[33margs\u001b[0m=\u001b[3;35mNone\u001b[0m,\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[33mmcp_endpoint\u001b[0m=\u001b[3;35mNone\u001b[0m\n",
-              "\u001b[1m)\u001b[0m\n"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        }
-      ],
-      "source": [
-        "from rich.pretty import pprint\n",
-        "for toolgroup in client.toolgroups.list():\n",
-        "    pprint(toolgroup)"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "i2o0gDhrv2og",
-      "metadata": {
-        "id": "i2o0gDhrv2og"
-      },
-      "source": [
-        "### 2.2. Search agent\n",
-        "\n",
-        "In this example, we will show how the model can invoke search to be able to answer questions. We will first have to set the API key of the search tool.\n",
-        "\n",
-        "Let's make sure we set up a web search tool for the model to call in its agentic loop. In this tutorial, we will use [Tavily](https://tavily.com) as our search provider. Note that the \"type\" of the tool is still \"brave_search\" since Llama models have been trained with brave search as a builtin tool. Tavily is just being used in lieu of Brave search.\n",
-        "\n",
-        "See steps [here](https://docs.google.com/document/d/1Vg998IjRW_uujAPnHdQ9jQWvtmkZFt74FldW2MblxPY/edit?tab=t.0#heading=h.xx02wojfl2f9)."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 12,
-      "id": "WS8Gu5b0APHs",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "WS8Gu5b0APHs",
-        "outputId": "ec38efab-ca5b-478f-94b6-fd65a3cb3bb9"
-      },
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "\u001b[32mUser> Hello\u001b[0m\n",
-            "\u001b[30m\u001b[0m\u001b[33minference> \u001b[0m\u001b[33mHello\u001b[0m\u001b[33m.\u001b[0m\u001b[33m How\u001b[0m\u001b[33m can\u001b[0m\u001b[33m I\u001b[0m\u001b[33m assist\u001b[0m\u001b[33m you\u001b[0m\u001b[33m today\u001b[0m\u001b[33m?\u001b[0m\u001b[97m\u001b[0m\n",
-            "\u001b[30m\u001b[0m\u001b[32mUser> Which teams played in the NBA western conference finals of 2024\u001b[0m\n",
-            "\u001b[30m\u001b[0m\u001b[33minference> \u001b[0m\u001b[36m\u001b[0m\u001b[36mbr\u001b[0m\u001b[36mave\u001b[0m\u001b[36m_search\u001b[0m\u001b[36m.call\u001b[0m\u001b[36m(query\u001b[0m\u001b[36m=\"\u001b[0m\u001b[36mN\u001b[0m\u001b[36mBA\u001b[0m\u001b[36m Western\u001b[0m\u001b[36m Conference\u001b[0m\u001b[36m Finals\u001b[0m\u001b[36m \u001b[0m\u001b[36m202\u001b[0m\u001b[36m4\u001b[0m\u001b[36m teams\u001b[0m\u001b[36m\")\u001b[0m\u001b[97m\u001b[0m\n",
-            "\u001b[32mtool_execution> Tool:brave_search Args:{'query': 'NBA Western Conference Finals 2024 teams'}\u001b[0m\n",
-            "\u001b[32mtool_execution> Tool:brave_search Response:{\"query\": \"NBA Western Conference Finals 2024 teams\", \"top_k\": [{\"title\": \"2024 NBA Western Conference Finals - Basketball-Reference.com\", \"url\": \"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\", \"content\": \"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown (20.8 / 5.4 / 5.0) 2024 Playoff Leaders: PTS: Luka Don\\u010di\\u0107 (635) TRB: Luka Don\\u010di\\u0107 (208) AST: Luka Don\\u010di\\u0107 (178) WS: Derrick White (2.9) More playoffs info\", \"score\": 0.9310187, \"raw_content\": null}, {\"title\": \"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\", \"url\": \"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\", \"content\": \"NBA Western Conference Finals 2024: Dates & Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\", \"score\": 0.8914433, \"raw_content\": null}, {\"title\": \"2024 Playoffs: West Finals | Timberwolves (3) vs. Mavericks (5) - NBA.com\", \"url\": \"https://www.nba.com/playoffs/2024/west-final\", \"content\": \"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\", \"score\": 0.8884594, \"raw_content\": null}, {\"title\": \"NBA Conference Finals Schedule: Full List of Games & Results\", \"url\": \"https://www.si.com/nba/nba-conference-finals-schedule-full-list-of-games-results\", \"content\": \"The 2024 NBA conference finals matchups are set. Here's the schedule for all the games. ... Western Conference First Round (1) Oklahoma City Thunder def. (8) New Orleans Pelicans in 4 games\", \"score\": 0.850382, \"raw_content\": null}, {\"title\": \"2024 NBA Western Conference playoff bracket - Basketnews.com\", \"url\": \"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\", \"content\": \"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\", \"score\": 0.8473754, \"raw_content\": null}]}\u001b[0m\n",
-            "\u001b[33minference> \u001b[0m\u001b[33mThe\u001b[0m\u001b[33m teams\u001b[0m\u001b[33m that\u001b[0m\u001b[33m played\u001b[0m\u001b[33m in\u001b[0m\u001b[33m the\u001b[0m\u001b[33m NBA\u001b[0m\u001b[33m Western\u001b[0m\u001b[33m Conference\u001b[0m\u001b[33m Finals\u001b[0m\u001b[33m of\u001b[0m\u001b[33m \u001b[0m\u001b[33m202\u001b[0m\u001b[33m4\u001b[0m\u001b[33m were\u001b[0m\u001b[33m the\u001b[0m\u001b[33m Dallas\u001b[0m\u001b[33m Mavericks\u001b[0m\u001b[33m and\u001b[0m\u001b[33m the\u001b[0m\u001b[33m Minnesota\u001b[0m\u001b[33m Timber\u001b[0m\u001b[33mw\u001b[0m\u001b[33molves\u001b[0m\u001b[33m.\u001b[0m\u001b[97m\u001b[0m\n",
-            "\u001b[30m\u001b[0m"
-          ]
-        }
-      ],
-      "source": [
-        "from llama_stack_client.lib.agents.agent import Agent\n",
-        "from llama_stack_client.lib.agents.event_logger import EventLogger\n",
-        "from llama_stack_client.types.agent_create_params import AgentConfig\n",
-        "from termcolor import cprint\n",
-        "\n",
-        "agent_config = AgentConfig(\n",
-        "    model=model_id,\n",
-        "    instructions=\"You are a helpful assistant\",\n",
-        "    toolgroups=[\"builtin::websearch\"],\n",
-        "    input_shields=[],\n",
-        "    output_shields=[],\n",
-        "    enable_session_persistence=False,\n",
-        ")\n",
-        "agent = Agent(client, agent_config)\n",
-        "user_prompts = [\n",
-        "    \"Hello\",\n",
-        "    \"Which teams played in the NBA western conference finals of 2024\",\n",
-        "]\n",
-        "\n",
-        "session_id = agent.create_session(\"test-session\")\n",
-        "for prompt in user_prompts:\n",
-        "    cprint(f\"User> {prompt}\", \"green\")\n",
-        "    response = agent.create_turn(\n",
-        "        messages=[\n",
-        "            {\n",
-        "                \"role\": \"user\",\n",
-        "                \"content\": prompt,\n",
-        "            }\n",
-        "        ],\n",
-        "        session_id=session_id,\n",
-        "    )\n",
-        "    for log in EventLogger().log(response):\n",
-        "        log.print()\n"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "fN5jaAaax2Aq",
-      "metadata": {
-        "id": "fN5jaAaax2Aq"
-      },
-      "source": [
-        "### 2.3. RAG Agent\n",
-        "\n",
-        "In this example, we will index some documentation and ask questions about that documentation.\n",
-        "\n",
-        "The tool we use is the memory tool. Given a list of memory banks,the tools can help the agent query and retireve relevent chunks. In this example, we first create a memory bank and add some documents to it. Then configure the agent to use the memory tool. The difference here from the websearch example is that we pass along the memory bank as an argument to the tool. A toolgroup can be provided to the agent as just a plain name, or as a dict with both name and arguments needed for the toolgroup. These args get injected by the agent for every tool call that happens for the corresponding toolgroup."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 13,
-      "id": "GvLWltzZCNkg",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 351,
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-            "4709067f3f554b93b3ef35e3f58cbf85",
-            "02baf670942347d69c290452de8641e4",
-            "7611cfc7965649ba88ca57c1a9f9ccf3",
-            "15ae23892b634a9f821a8fcee14e500b",
-            "b28d46c2ecdd46b9b3f2da871afbf1cb",
-            "4b83e3caa8ec47169dca04ee9599adeb",
-            "c83c23161674484e81f0db9856c23eb6",
-            "3ded85d9c34246e88f8ce693eb8025e5",
-            "0ac8e976a32c4f5989392b8088546e00",
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-            "42335bcbc6ee40a79d36c5159cc7da06",
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-        "id": "GvLWltzZCNkg",
-        "outputId": "ef5f3ec4-edaf-4705-fb1b-b86659d7143c"
-      },
-      "outputs": [
-        {
-          "data": {
-            "application/vnd.jupyter.widget-view+json": {
-              "model_id": "3e764c00c08942caa2ccb6b92ee60a4e",
-              "version_major": 2,
-              "version_minor": 0
-            },
-            "text/plain": [
-              "Batches:   0%|          | 0/1 [00:00<?, ?it/s]"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        },
-        {
-          "data": {
-            "application/vnd.jupyter.widget-view+json": {
-              "model_id": "af6680f2e60e476d8487aea98a23b84e",
-              "version_major": 2,
-              "version_minor": 0
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-            "text/plain": [
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-            ]
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-          "output_type": "display_data"
-        },
-        {
-          "data": {
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-              "model_id": "c26a9d456e904b2b900bf5e0a5964a0d",
-              "version_major": 2,
-              "version_minor": 0
-            },
-            "text/plain": [
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-            ]
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-          "output_type": "display_data"
-        },
-        {
-          "data": {
-            "application/vnd.jupyter.widget-view+json": {
-              "model_id": "5a3e0b5ae83143329de6507f9bcf83e0",
-              "version_major": 2,
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-            },
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-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        },
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "\u001b[32mUser> What are the top 5 topics that were explained? Only list succinct bullet points.\u001b[0m\n",
-            "\u001b[30m\u001b[0m"
-          ]
-        },
-        {
-          "data": {
-            "application/vnd.jupyter.widget-view+json": {
-              "model_id": "3c9bc5588765436da4f1fee2d893cafd",
-              "version_major": 2,
-              "version_minor": 0
-            },
-            "text/plain": [
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-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        },
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "\u001b[32mtool_execution> Tool:query_memory Args:{}\u001b[0m\n",
-            "\u001b[36mtool_execution> fetched 11069 bytes from memory\u001b[0m\n",
-            "\u001b[33minference> \u001b[0m\u001b[33mHere\u001b[0m\u001b[33m are\u001b[0m\u001b[33m the\u001b[0m\u001b[33m top\u001b[0m\u001b[33m \u001b[0m\u001b[33m5\u001b[0m\u001b[33m topics\u001b[0m\u001b[33m that\u001b[0m\u001b[33m were\u001b[0m\u001b[33m explained\u001b[0m\u001b[33m:\n",
-            "\n",
-            "\u001b[0m\u001b[33m•\u001b[0m\u001b[33m Fine\u001b[0m\u001b[33m-t\u001b[0m\u001b[33muning\u001b[0m\u001b[33m a\u001b[0m\u001b[33m model\u001b[0m\u001b[33m to\u001b[0m\u001b[33m expect\u001b[0m\u001b[33m a\u001b[0m\u001b[33m certain\u001b[0m\u001b[33m prompt\u001b[0m\u001b[33m structure\u001b[0m\u001b[33m on\u001b[0m\u001b[33m inference\u001b[0m\u001b[33m for\u001b[0m\u001b[33m a\u001b[0m\u001b[33m specific\u001b[0m\u001b[33m task\u001b[0m\u001b[33m\n",
-            "\u001b[0m\u001b[33m•\u001b[0m\u001b[33m Fine\u001b[0m\u001b[33m-t\u001b[0m\u001b[33muning\u001b[0m\u001b[33m on\u001b[0m\u001b[33m a\u001b[0m\u001b[33m custom\u001b[0m\u001b[33m chat\u001b[0m\u001b[33m dataset\u001b[0m\u001b[33m\n",
-            "\u001b[0m\u001b[33m•\u001b[0m\u001b[33m Token\u001b[0m\u001b[33mizing\u001b[0m\u001b[33m prompt\u001b[0m\u001b[33m templates\u001b[0m\u001b[33m and\u001b[0m\u001b[33m special\u001b[0m\u001b[33m tokens\u001b[0m\u001b[33m\n",
-            "\u001b[0m\u001b[33m•\u001b[0m\u001b[33m Using\u001b[0m\u001b[33m the\u001b[0m\u001b[33m L\u001b[0m\u001b[33mlama\u001b[0m\u001b[33m2\u001b[0m\u001b[33mChat\u001b[0m\u001b[33mTemplate\u001b[0m\u001b[33m class\u001b[0m\u001b[33m to\u001b[0m\u001b[33m format\u001b[0m\u001b[33m messages\u001b[0m\u001b[33m\n",
-            "\u001b[0m\u001b[33m•\u001b[0m\u001b[33m Token\u001b[0m\u001b[33mizing\u001b[0m\u001b[33m examples\u001b[0m\u001b[33m with\u001b[0m\u001b[33m the\u001b[0m\u001b[33m L\u001b[0m\u001b[33mlama\u001b[0m\u001b[33m2\u001b[0m\u001b[33m tokenizer\u001b[0m\u001b[97m\u001b[0m\n",
-            "\u001b[30m\u001b[0m"
-          ]
-        }
-      ],
-      "source": [
-        "from llama_stack_client.lib.agents.agent import Agent\n",
-        "from llama_stack_client.lib.agents.event_logger import EventLogger\n",
-        "from llama_stack_client.types.agent_create_params import AgentConfig\n",
-        "from termcolor import cprint\n",
-        "from llama_stack_client.types.memory_insert_params import Document\n",
-        "\n",
-        "urls = [\"chat.rst\", \"llama3.rst\", \"datasets.rst\", \"lora_finetune.rst\"]\n",
-        "documents = [\n",
-        "    Document(\n",
-        "        document_id=f\"num-{i}\",\n",
-        "        content=f\"https://raw.githubusercontent.com/pytorch/torchtune/main/docs/source/tutorials/{url}\",\n",
-        "        mime_type=\"text/plain\",\n",
-        "        metadata={},\n",
-        "    )\n",
-        "    for i, url in enumerate(urls)\n",
-        "]\n",
-        "memory_bank_id = \"test-memory-bank\"\n",
-        "client.memory_banks.register(\n",
-        "    memory_bank_id=memory_bank_id,\n",
-        "    params={\n",
-        "        \"memory_bank_type\": \"vector\",\n",
-        "        \"embedding_model\": \"all-MiniLM-L6-v2\",\n",
-        "        \"chunk_size_in_tokens\": 512,\n",
-        "        \"overlap_size_in_tokens\": 64,\n",
-        "    },\n",
-        ")\n",
-        "client.memory.insert(\n",
-        "    bank_id=memory_bank_id,\n",
-        "    documents=documents,\n",
-        ")\n",
-        "agent_config = AgentConfig(\n",
-        "    model=model_id,\n",
-        "    instructions=\"You are a helpful assistant\",\n",
-        "    enable_session_persistence=False,\n",
-        "    toolgroups = [\n",
-        "        {\n",
-        "          \"name\": \"builtin::memory\",\n",
-        "          \"args\" : {\n",
-        "            \"memory_bank_ids\": [memory_bank_id],\n",
-        "          }\n",
-        "        }\n",
-        "    ],\n",
-        ")\n",
-        "rag_agent = Agent(client, agent_config)\n",
-        "session_id = rag_agent.create_session(\"test-session\")\n",
-        "user_prompts = [\n",
-        "        \"What are the top 5 topics that were explained? Only list succinct bullet points.\",\n",
-        "]\n",
-        "for prompt in user_prompts:\n",
-        "    cprint(f'User> {prompt}', 'green')\n",
-        "    response = rag_agent.create_turn(\n",
-        "        messages=[{\"role\": \"user\", \"content\": prompt}],\n",
-        "        session_id=session_id,\n",
-        "    )\n",
-        "    for log in EventLogger().log(response):\n",
-        "        log.print()"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "yRzRwu8qxyl0",
-      "metadata": {
-        "id": "yRzRwu8qxyl0"
-      },
-      "source": [
-        "### 2.4. Code Execution Agent\n",
-        "\n",
-        "In this example, we will show how multiple tools can be called by the model - including web search and code execution. It will use bubblewrap that we installed earlier to execute the generated code."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 26,
-      "id": "GvVRuhO-GOov",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "collapsed": true,
-        "id": "GvVRuhO-GOov",
-        "outputId": "39395e26-bb7d-4616-d51d-036c8bf41427"
-      },
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "User> Here is a csv, can you describe it?\n",
-            "inference> import pandas as pd\n",
-            "# Load data\n",
-            "df = pd.read_csv(\"/tmp/tmpvzjigv7g/n2OzlTWhinflation.csv\")\n",
-            "# Rows\n",
-            "print(\"Number of rows and columns in the data:\", df.shape)\n",
-            "# Columns\n",
-            "print(\"Columns of the data are:\", len(df.columns))\n",
-            "# Column names\n",
-            "print(\"Columns of the data are:\", df.columns)\n",
-            "# Column dtypes\n",
-            "print(\"Datatype of the columns are:\", df.dtypes)\n",
-            "tool_execution> Tool:code_interpreter Args:{'code': 'import pandas as pd\\n# Load data\\ndf = pd.read_csv(\"/tmp/tmpvzjigv7g/n2OzlTWhinflation.csv\")\\n# Rows\\nprint(\"Number of rows and columns in the data:\", df.shape)\\n# Columns\\nprint(\"Columns of the data are:\", len(df.columns))\\n# Column names\\nprint(\"Columns of the data are:\", df.columns)\\n# Column dtypes\\nprint(\"Datatype of the columns are:\", df.dtypes)'}\n",
-            "tool_execution> Tool:code_interpreter Response:completed\n",
-            "[stdout]\n",
-            "Number of rows and columns in the data: (10, 13)\n",
-            "Columns of the data are: 13\n",
-            "Columns of the data are: Index(['Year', 'Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep',\n",
-            "       'Oct', 'Nov', 'Dec'],\n",
-            "      dtype='object')\n",
-            "Datatype of the columns are: Year      int64\n",
-            "Jan     float64\n",
-            "Feb     float64\n",
-            "Mar     float64\n",
-            "Apr     float64\n",
-            "May     float64\n",
-            "Jun     float64\n",
-            "Jul     float64\n",
-            "Aug     float64\n",
-            "Sep     float64\n",
-            "Oct     float64\n",
-            "Nov     float64\n",
-            "Dec     float64\n",
-            "dtype: object\n",
-            "[/stdout]\n",
-            "inference> The csv file contains 10 rows and 13 columns. The columns are named 'Year', 'Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'. The data types of the columns are all float64, indicating that the data is numeric. The 'Year' column is of type int64, suggesting that it contains integer values. The remaining 12 columns contain floating point numbers.\n",
-            "User> Plot average yearly inflation as a time series\n",
-            "inference> import pandas as pd\n",
-            "import matplotlib.pyplot as plt\n",
-            "\n",
-            "# Load data\n",
-            "df = pd.read_csv(\"/tmp/tmpvzjigv7g/n2OzlTWhinflation.csv\")\n",
-            "\n",
-            "# Calculate average yearly inflation\n",
-            "df['Average'] = df[['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']].mean(axis=1)\n",
-            "\n",
-            "# Plot average yearly inflation as a time series\n",
-            "plt.figure(figsize=(10,6))\n",
-            "plt.plot(df['Year'], df['Average'])\n",
-            "plt.title('Average Yearly Inflation')\n",
-            "plt.xlabel('Year')\n",
-            "plt.ylabel('Average Inflation')\n",
-            "plt.grid(True)\n",
-            "plt.show()\n",
-            "tool_execution> Tool:code_interpreter Args:{'code': 'import pandas as pd\\nimport matplotlib.pyplot as plt\\n\\n# Load data\\ndf = pd.read_csv(\"/tmp/tmpvzjigv7g/n2OzlTWhinflation.csv\")\\n\\n# Calculate average yearly inflation\\ndf[\\'Average\\'] = df[[\\'Jan\\', \\'Feb\\', \\'Mar\\', \\'Apr\\', \\'May\\', \\'Jun\\', \\'Jul\\', \\'Aug\\', \\'Sep\\', \\'Oct\\', \\'Nov\\', \\'Dec\\']].mean(axis=1)\\n\\n# Plot average yearly inflation as a time series\\nplt.figure(figsize=(10,6))\\nplt.plot(df[\\'Year\\'], df[\\'Average\\'])\\nplt.title(\\'Average Yearly Inflation\\')\\nplt.xlabel(\\'Year\\')\\nplt.ylabel(\\'Average Inflation\\')\\nplt.grid(True)\\nplt.show()'}\n",
-            "tool_execution> Tool:code_interpreter Response:completed\n",
-            "inference> This code calculates the average inflation for each year by taking the mean of the 12 monthly inflation rates. It then plots this average yearly inflation as a time series using matplotlib. The x-axis represents the year and the y-axis represents the average inflation. The plot shows the trend of average yearly inflation over the years.\n"
-          ]
-        }
-      ],
-      "source": [
-        "from llama_stack_client.types.agents.turn_create_params import Document\n",
-        "\n",
-        "agent_config = AgentConfig(\n",
-        "    sampling_params = {\n",
-        "        \"max_tokens\" : 4096,\n",
-        "        \"temperature\": 0.0\n",
-        "    },\n",
-        "    model=\"meta-llama/Llama-3.1-8B-Instruct\",\n",
-        "    instructions=\"You are a helpful assistant\",\n",
-        "    toolgroups=[\n",
-        "        \"builtin::code_interpreter\",\n",
-        "        \"builtin::websearch\"\n",
-        "    ],\n",
-        "    tool_choice=\"auto\",\n",
-        "    input_shields=[],\n",
-        "    output_shields=[],\n",
-        "    enable_session_persistence=False,\n",
-        ")\n",
-        "codex_agent = Agent(client, agent_config)\n",
-        "session_id = codex_agent.create_session(\"test-session\")\n",
-        "\n",
-        "\n",
-        "inflation_doc = Document(\n",
-        "    content=\"https://raw.githubusercontent.com/meta-llama/llama-stack-apps/main/examples/resources/inflation.csv\",\n",
-        "    mime_type=\"text/csv\",\n",
-        ")\n",
-        "\n",
-        "user_input = [\n",
-        "    {\"prompt\": \"Here is a csv, can you describe it?\", \"documents\": [inflation_doc]},\n",
-        "    {\"prompt\": \"Plot average yearly inflation as a time series\"},\n",
-        "]\n",
-        "\n",
-        "for input in user_input:\n",
-        "    cprint(f'User> {input[\"prompt\"]}', 'green')\n",
-        "    response = codex_agent.create_turn(\n",
-        "\n",
-        "        messages=[\n",
-        "            {\n",
-        "                \"role\": \"user\",\n",
-        "                \"content\": input[\"prompt\"],\n",
-        "            }\n",
-        "        ],\n",
-        "        session_id=session_id,\n",
-        "        documents=input.get(\"documents\", None)\n",
-        "    )\n",
-        "    # for chunk in response:\n",
-        "    #     print(chunk)\n",
-        "\n",
-        "    for log in EventLogger().log(response):\n",
-        "        log.print()\n"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "9GHJHfLmIQQi",
-      "metadata": {
-        "id": "9GHJHfLmIQQi"
-      },
-      "source": [
-        "- Now, use the generated response from agent to view the plot"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 27,
-      "id": "JqBBVLKdIHHq",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 564
-        },
-        "id": "JqBBVLKdIHHq",
-        "outputId": "3c89c303-e7c0-4ae2-c271-f34a4d296a85"
-      },
-      "outputs": [
-        {
-          "data": {
-            "image/png": 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",
-            "text/plain": [
-              "<Figure size 1000x600 with 1 Axes>"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        }
-      ],
-      "source": [
-        "# NBVAL_SKIP\n",
-        "import matplotlib.pyplot as plt\n",
-        "import pandas as pd\n",
-        "\n",
-        "# Load data\n",
-        "df = pd.read_csv(\"/tmp/tmpvzjigv7g/n2OzlTWhinflation.csv\")\n",
-        "\n",
-        "# Calculate average yearly inflation\n",
-        "df['Average'] = df[['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']].mean(axis=1)\n",
-        "\n",
-        "# Plot average yearly inflation as a time series\n",
-        "plt.figure(figsize=(10,6))\n",
-        "plt.plot(df['Year'], df['Average'])\n",
-        "plt.title('Average Yearly Inflation')\n",
-        "plt.xlabel('Year')\n",
-        "plt.ylabel('Average Inflation')\n",
-        "plt.grid(True)\n",
-        "plt.show()"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "FJ85DUhgBZd7",
-      "metadata": {
-        "id": "FJ85DUhgBZd7"
-      },
-      "source": [
-        "## 3. Llama Stack Agent Evaluations\n"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "ydeBDpDT5VHd",
-      "metadata": {
-        "id": "ydeBDpDT5VHd"
-      },
-      "source": [
-        "#### 3.1. Online Evaluation Dataset Collection Using Telemetry\n",
-        "\n",
-        "- Llama Stack offers built-in telemetry to collect traces and data about your agentic application.\n",
-        "- In this example, we will show how to build an Agent with Llama Stack, and query the agent's traces into an online dataset that can be used for evaluation.  "
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "_t_tcWq0JcJ4",
-      "metadata": {
-        "id": "_t_tcWq0JcJ4"
-      },
-      "source": [
-        "##### 3.1.1. Building a Search Agent"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 16,
-      "id": "4iCO59kP20Zs",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "id": "4iCO59kP20Zs",
-        "outputId": "894c6333-30e9-4f1e-9b63-1bfb1cae51e2"
-      },
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "\u001b[30m\u001b[0m\u001b[33minference> \u001b[0m"
-          ]
-        },
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "\u001b[36m\u001b[0m\u001b[36mbr\u001b[0m\u001b[36mave\u001b[0m\u001b[36m_search\u001b[0m\u001b[36m.call\u001b[0m\u001b[36m(query\u001b[0m\u001b[36m=\"\u001b[0m\u001b[36mN\u001b[0m\u001b[36mBA\u001b[0m\u001b[36m Western\u001b[0m\u001b[36m Conference\u001b[0m\u001b[36m Finals\u001b[0m\u001b[36m \u001b[0m\u001b[36m202\u001b[0m\u001b[36m4\u001b[0m\u001b[36m teams\u001b[0m\u001b[36m\")\u001b[0m\u001b[97m\u001b[0m\n",
-            "\u001b[32mtool_execution> Tool:brave_search Args:{'query': 'NBA Western Conference Finals 2024 teams'}\u001b[0m\n",
-            "\u001b[32mtool_execution> Tool:brave_search Response:{\"query\": \"NBA Western Conference Finals 2024 teams\", \"top_k\": [{\"title\": \"2024 NBA Western Conference Finals - Basketball-Reference.com\", \"url\": \"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\", \"content\": \"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown (20.8 / 5.4 / 5.0) 2024 Playoff Leaders: PTS: Luka Don\\u010di\\u0107 (635) TRB: Luka Don\\u010di\\u0107 (208) AST: Luka Don\\u010di\\u0107 (178) WS: Derrick White (2.9) More playoffs info\", \"score\": 0.9310187, \"raw_content\": null}, {\"title\": \"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\", \"url\": \"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\", \"content\": \"NBA Western Conference Finals 2024: Dates & Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\", \"score\": 0.8914433, \"raw_content\": null}, {\"title\": \"2024 Playoffs: West Finals | Timberwolves (3) vs. Mavericks (5) - NBA.com\", \"url\": \"https://www.nba.com/playoffs/2024/west-final\", \"content\": \"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\", \"score\": 0.8884594, \"raw_content\": null}, {\"title\": \"NBA Conference Finals Schedule: Full List of Games & Results\", \"url\": \"https://www.si.com/nba/nba-conference-finals-schedule-full-list-of-games-results\", \"content\": \"The 2024 NBA conference finals matchups are set. Here's the schedule for all the games. ... Western Conference First Round (1) Oklahoma City Thunder def. (8) New Orleans Pelicans in 4 games\", \"score\": 0.85008353, \"raw_content\": null}, {\"title\": \"2024 NBA Western Conference playoff bracket - Basketnews.com\", \"url\": \"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\", \"content\": \"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\", \"score\": 0.8479807, \"raw_content\": null}]}\u001b[0m\n",
-            "\u001b[33minference> \u001b[0m\u001b[33mThe\u001b[0m\u001b[33m teams\u001b[0m\u001b[33m that\u001b[0m\u001b[33m played\u001b[0m\u001b[33m in\u001b[0m\u001b[33m the\u001b[0m\u001b[33m NBA\u001b[0m\u001b[33m Western\u001b[0m\u001b[33m Conference\u001b[0m\u001b[33m Finals\u001b[0m\u001b[33m of\u001b[0m\u001b[33m \u001b[0m\u001b[33m202\u001b[0m\u001b[33m4\u001b[0m\u001b[33m were\u001b[0m\u001b[33m the\u001b[0m\u001b[33m Dallas\u001b[0m\u001b[33m Mavericks\u001b[0m\u001b[33m and\u001b[0m\u001b[33m the\u001b[0m\u001b[33m Minnesota\u001b[0m\u001b[33m Timber\u001b[0m\u001b[33mw\u001b[0m\u001b[33molves\u001b[0m\u001b[33m.\u001b[0m\u001b[97m\u001b[0m\n",
-            "\u001b[30m\u001b[0m\u001b[30m\u001b[0m\u001b[33minference> \u001b[0m\u001b[36m\u001b[0m\u001b[36mbr\u001b[0m\u001b[36mave\u001b[0m\u001b[36m_search\u001b[0m\u001b[36m.call\u001b[0m\u001b[36m(query\u001b[0m\u001b[36m=\"\u001b[0m\u001b[36mBill\u001b[0m\u001b[36m Cosby\u001b[0m\u001b[36m South\u001b[0m\u001b[36m Park\u001b[0m\u001b[36m episode\u001b[0m\u001b[36m\")\u001b[0m\u001b[97m\u001b[0m\n",
-            "\u001b[32mtool_execution> Tool:brave_search Args:{'query': 'Bill Cosby South Park episode'}\u001b[0m\n",
-            "\u001b[32mtool_execution> Tool:brave_search Response:{\"query\": \"Bill Cosby South Park episode\", \"top_k\": [{\"title\": \"Bill Cosby and Taylor Swift Duet - South Park Studios\", \"url\": \"https://www.southparkstudios.com/video-clips/90r7i1/south-park-bill-cosby-and-taylor-swift-duet\", \"content\": \"01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:03 Bill Cosby and Taylor Swift Duet South ParkS18 E10 ------------------------------------------------------- The holiday special continues with Bill Cosby and Taylor Swift's rendition of \\\"It's Snowing Out There\\\". 01:31 #WeBelieveInYou South ParkS18 E10 -------------------------------------- With everyone watching, Kyle takes the opportunity to reach out to his brother. 01:47 Watch Your Microaggressions, Bro South ParkS19 E1 ------------------------------------------------------ Cartman's plan to frame PC Principal backfires. South ParkS19 E1 -------------------------------------- After hearing that the PC people have targeted Kyle, Cartman vows to help.\", \"score\": 0.685971, \"raw_content\": null}, {\"title\": \"Bill Cosby is Here to See You - South Park Studios US\", \"url\": \"https://southpark.cc.com/video-clips/wfot8s/south-park-bill-cosby-is-here-to-see-you\", \"content\": \"01:56 It's Not About Music South ParkS18 E9 ------------------------------------------ At home, Randy sees the consequences of Lorde's performance and calls the Record Producer to try and fix it. 01:24 Lorde's Hologram South ParkS18 E9 -------------------------------------- The Record Producer reveals the truth about the music industry... South ParkS18 E9 --------------------------------------------- Randy catches Sharon with Tupac's hologram. 01:37 I've Got Your Son, Lorde South ParkS18 E10 ----------------------------------------------- The Record Producer takes Stan and Kyle hostage. 01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:21 Lorde Is My Dad South ParkS18 E10 -------------------------------------- After trying to confront Cartman Bra, Stan finally reveals the truth about his dad.\", \"score\": 0.6643884, \"raw_content\": null}, {\"title\": \"Bill Cosby (android) | South Park Character ... - South Park Studios US\", \"url\": \"https://southpark.cc.com/wiki/Bill_Cosby_(android)\", \"content\": \"Bill Cosby (android) | South Park Character / Location / User talk etc | Official South Park Studios Wiki Sent back in time to destroy Eric Cartman's Dawson's Creek Trapper Keeper before it manifests into an omnipotent supercomputer that can destroy all humanity, \\\"Bill Cosby\\\" is really VSM471, an android or cyborg of some kind engineered by 'hoomans' in the distant future. He fails in his initial missions to infiltrate South Park Elementary's 4th Grade class, destroy the Trapper Keeper or Cartman himself, but with Stan Marsh and Kyle Broflovski's aid, he is able to succeed in preventing his dismal future, and painfully fades from existence. South Park and all related titles, logos and characters are trademarks of Comedy Partners.\", \"score\": 0.5052006, \"raw_content\": null}, {\"title\": \"'South Park' takes on Cosby, police, 2014 | CNN\", \"url\": \"https://www.cnn.com/2014/12/11/showbiz/tv/south-park-cosby-redskins-police/index.html\", \"content\": \"\\u2018South Park\\u2019 takes on Cosby, police, 2014 | CNN Watch Listen Live TV Subscribe Follow CNN Entertainment CNN Headlines CNN Shorts CNN10 CNN Max CNN TV Schedules CNN 5 Things CNN Underscored CNN Crossword About CNN CNN Profiles CNN Newsletters Work for CNN CNN \\u00a0\\u2014\\u00a0 \\u201cI think we take for granted how Trey Parker can jam a heap of current issues into a storyline thats a smart and funny #SouthPark episode,\\u201d wrote Brent Veale. \\u201cOh Lorde, CartmanBrah, dead celebrity holograms, murdering cops, this #SouthPark episode is certainly making #SaveTheLivingRoom happen,\\u201d added Brett Pender. CNN Headlines CNN10 CNN Max CNN TV Schedules CNN 5 Things CNN Underscored CNN Crossword About CNN CNN Profiles CNN Newsletters Work for CNN Follow CNN Entertainment\", \"score\": 0.45391592, \"raw_content\": null}, {\"title\": \"Trapper Keeper (South Park) - Wikipedia\", \"url\": \"https://en.wikipedia.org/wiki/Trapper_Keeper_(South_Park)\", \"content\": \"\\\"Trapper Keeper\\\" is the twelfth episode of the fourth season of the animated television series South Park, and the 60th episode of the series overall. In the episode, a man from the future wants Cartman's new Trapper Keeper, while Mr. Garrison's kindergarten class holds an election for class president with confusing results. It is one of the many South Park episodes that parodies a current event.[1] The main plot of the episode involving the Trapper Keeper was written before the election,[1] but the subplot is a parody of the controversy surrounding the election's outcome.[2] \\\"Trapper Keeper\\\" did not originally feature the election storyline, only a subplot about Ike attending his first day of kindergarten.[3] \\\"Trapper Keeper\\\" Full episode at South Park Studios\", \"score\": 0.3839421, \"raw_content\": null}]}\u001b[0m\n",
-            "\u001b[33minference> \u001b[0m\u001b[33mBill\u001b[0m\u001b[33m Cosby\u001b[0m\u001b[33m (\u001b[0m\u001b[33mBS\u001b[0m\u001b[33mM\u001b[0m\u001b[33m-\u001b[0m\u001b[33m471\u001b[0m\u001b[33m)\u001b[0m\u001b[33m first\u001b[0m\u001b[33m appears\u001b[0m\u001b[33m in\u001b[0m\u001b[33m Season\u001b[0m\u001b[33m \u001b[0m\u001b[33m4\u001b[0m\u001b[33m,\u001b[0m\u001b[33m Episode\u001b[0m\u001b[33m \u001b[0m\u001b[33m12\u001b[0m\u001b[33m of\u001b[0m\u001b[33m South\u001b[0m\u001b[33m Park\u001b[0m\u001b[33m,\u001b[0m\u001b[33m titled\u001b[0m\u001b[33m \"\u001b[0m\u001b[33mTr\u001b[0m\u001b[33mapper\u001b[0m\u001b[33m Keeper\u001b[0m\u001b[33m\".\u001b[0m\u001b[97m\u001b[0m\n",
-            "\u001b[30m\u001b[0m\u001b[30m\u001b[0m\u001b[33minference> \u001b[0m\u001b[36m\u001b[0m\u001b[36mbr\u001b[0m\u001b[36mave\u001b[0m\u001b[36m_search\u001b[0m\u001b[36m.call\u001b[0m\u001b[36m(query\u001b[0m\u001b[36m=\"\u001b[0m\u001b[36mAndrew\u001b[0m\u001b[36m Tate\u001b[0m\u001b[36m kick\u001b[0m\u001b[36mboxing\u001b[0m\u001b[36m name\u001b[0m\u001b[36m\")\u001b[0m\u001b[97m\u001b[0m\n",
-            "\u001b[32mtool_execution> Tool:brave_search Args:{'query': 'Andrew Tate kickboxing name'}\u001b[0m\n",
-            "\u001b[32mtool_execution> Tool:brave_search Response:{\"query\": \"Andrew Tate kickboxing name\", \"top_k\": [{\"title\": \"50 Facts About Andrew Tate - Facts.net\", \"url\": \"https://facts.net/andrew-tate-facts/\", \"content\": \"Full Name: Andrew Tate's full name is Emory Andrew Tate III, named after his father, a celebrated chess player. Date of Birth: ... Kickboxing Start: Tate began his kickboxing career in 2005, starting his journey as a professional fighter, which would later be a significant part of his persona. First Championship:\", \"score\": 0.8967681, \"raw_content\": null}, {\"title\": \"The Life Of Andrew Tate (By Andrew Tate Himself)\", \"url\": \"https://sidekickboxing.co.uk/the-life-of-andrew-king-cobra-tate/\", \"content\": \"Andrew Tate stats. Fight Name: Cobra Tate. Born: 1 December 1986. Weight: 90 KG. Weight Class: Cruiserweight. Height: 1.92m. Fight Record: Wins - 76, Losses - 9. ... Andrew Tate's Kickboxing Career. Andrew Tate has always fought credible opponents right from the beginning of his kickboxing career. One of his first professional fights on\", \"score\": 0.8795718, \"raw_content\": null}, {\"title\": \"Andrew Tate kickboxing record: How many championships ... - FirstSportz\", \"url\": \"https://firstsportz.com/mma-how-many-championships-does-andrew-tate-have/\", \"content\": \"Andrew Tate's Kickboxing career. During his kickboxing career, he used the nickname \\\"King Cobra,\\\" which he currently uses as his Twitter name. Tate had an unorthodox style of movement inside the ring. He kept his hands down most of the time and relied on quick jabs and an overhand right to land significant strikes.\", \"score\": 0.8752871, \"raw_content\": null}, {\"title\": \"Andrew Tate: Kickboxing Record, Facts, Height, Weight, Age, Biography\", \"url\": \"https://www.lowkickmma.com/andrew-tate-kickboxing-record-facts-height-weight-age-biography/\", \"content\": \"Birth Name: Emory Andrew Tate III: Date of Birth: 1 December 1986: Place of Birth: Washington, D.C., U.S. ... In his professional kickboxing career, Andrew Tate won 32 of his fights by knockout.\", \"score\": 0.7992077, \"raw_content\": null}, {\"title\": \"About Andrew Tate: A Journey from Champion to Controversy\", \"url\": \"https://reachmorpheus.com/andrew-tate/\", \"content\": \"Andrew Tate's kickboxing career, beginning in 2005, is a tale of determination and skill. He quickly made a name for himself in the sport, rising through the ranks with his unique fighting style and strategic approach, honed by his chess-playing background.\", \"score\": 0.6490677, \"raw_content\": null}]}\u001b[0m\n",
-            "\u001b[33minference> \u001b[0m\u001b[33mAndrew\u001b[0m\u001b[33m Tate\u001b[0m\u001b[33m's\u001b[0m\u001b[33m kick\u001b[0m\u001b[33mboxing\u001b[0m\u001b[33m name\u001b[0m\u001b[33m is\u001b[0m\u001b[33m \"\u001b[0m\u001b[33mC\u001b[0m\u001b[33mobra\u001b[0m\u001b[33m Tate\u001b[0m\u001b[33m\"\u001b[0m\u001b[33m or\u001b[0m\u001b[33m \"\u001b[0m\u001b[33mKing\u001b[0m\u001b[33m Cobra\u001b[0m\u001b[33m\".\u001b[0m\u001b[97m\u001b[0m\n",
-            "\u001b[30m\u001b[0m"
-          ]
-        }
-      ],
-      "source": [
-        "\n",
-        "from llama_stack_client.lib.agents.agent import Agent\n",
-        "from llama_stack_client.lib.agents.event_logger import EventLogger\n",
-        "from llama_stack_client.types.agent_create_params import AgentConfig\n",
-        "\n",
-        "agent_config = AgentConfig(\n",
-        "    model=\"meta-llama/Llama-3.1-405B-Instruct-FP8\",\n",
-        "    instructions=\"You are a helpful assistant. Use search tool to answer the questions. \",\n",
-        "    toolgroups=[\"builtin::websearch\"],\n",
-        "    input_shields=[],\n",
-        "    output_shields=[],\n",
-        "    enable_session_persistence=False,\n",
-        ")\n",
-        "agent = Agent(client, agent_config)\n",
-        "user_prompts = [\n",
-        "    \"Which teams played in the NBA western conference finals of 2024\",\n",
-        "    \"In which episode and season of South Park does Bill Cosby (BSM-471) first appear? Give me the number and title.\",\n",
-        "    \"What is the British-American kickboxer Andrew Tate's kickboxing name?\",\n",
-        "]\n",
-        "\n",
-        "session_id = agent.create_session(\"test-session\")\n",
-        "\n",
-        "for prompt in user_prompts:\n",
-        "    response = agent.create_turn(\n",
-        "        messages=[\n",
-        "            {\n",
-        "                \"role\": \"user\",\n",
-        "                \"content\": prompt,\n",
-        "            }\n",
-        "        ],\n",
-        "        session_id=session_id,\n",
-        "    )\n",
-        "\n",
-        "    for log in EventLogger().log(response):\n",
-        "        log.print()\n"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "ekOS2kM4P0LM",
-      "metadata": {
-        "id": "ekOS2kM4P0LM"
-      },
-      "source": [
-        "##### 3.1.2 Query Telemetry"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 17,
-      "id": "agkWgToGAsuA",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 1000
-        },
-        "id": "agkWgToGAsuA",
-        "outputId": "4233a1d9-8282-4aa9-bdc4-0c105939f97e"
-      },
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "Getting traces for session_id=4c99812c-d3db-4555-a897-b592bf22b3e6\n"
-          ]
-        },
-        {
-          "data": {
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"font-weight: bold\">[</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">{</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'input'</span>: <span style=\"font-weight: bold\">[</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"}'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null}'</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"font-weight: bold\">]</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'output'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">\"content:  tool_calls: [ToolCall(call_id='838a3846-0bc4-488e-9e42-65a48e29b80a', tool_name=&lt;BuiltinTool.brave_search: 'brave_search'&gt;, arguments={'query': 'NBA Western Conference Finals 2024 teams'})]\"</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">}</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">{</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'input'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"NBA Western Conference Finals 2024 teams\"}}]}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'output'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"tool\",\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"NBA Western Conference Finals 2024 teams\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference Finals - Basketball-Reference.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\\\\\", \\\\\"content\\\\\": \\\\\"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown (20.8 / 5.4 / 5.0) 2024 Playoff Leaders: PTS: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (635) TRB: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (208) AST: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (178) WS: Derrick White (2.9) More playoffs info\\\\\", \\\\\"score\\\\\": 0.9310187, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\\\\\", \\\\\"content\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates &amp; Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\\\\\", \\\\\"score\\\\\": 0.8914433, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 Playoffs: West Finals | Timberwolves (3) vs. Mavericks (5) - NBA.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nba.com/playoffs/2024/west-final\\\\\", \\\\\"content\\\\\": \\\\\"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\\\\\", \\\\\"score\\\\\": 0.8884594, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Conference Finals Schedule: Full List of Games &amp; Results\\\\\", \\\\\"url\\\\\": \\\\\"https://www.si.com/nba/nba-conference-finals-schedule-full-list-of-games-results\\\\\", \\\\\"content\\\\\": \\\\\"The 2024 NBA conference finals matchups are set. Here\\'s the schedule for all the games. ... Western Conference First Round (1) Oklahoma City Thunder def. (8) New Orleans Pelicans in 4 games\\\\\", \\\\\"score\\\\\": 0.85008353, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference playoff bracket - Basketnews.com\\\\\", \\\\\"url\\\\\": \\\\\"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\\\\\", \\\\\"content\\\\\": \\\\\"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\\\\\", \\\\\"score\\\\\": 0.8479807, \\\\\"raw_content\\\\\": null}]}\"}'</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">}</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">{</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'input'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">[</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"NBA Western Conference Finals 2024 teams\"}}]}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"tool\",\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"NBA Western Conference Finals 2024 teams\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference Finals - Basketball-Reference.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\\\\\", \\\\\"content\\\\\": \\\\\"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown (20.8 / 5.4 / 5.0) 2024 Playoff Leaders: PTS: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (635) TRB: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (208) AST: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (178) WS: Derrick White (2.9) More playoffs info\\\\\", \\\\\"score\\\\\": 0.9310187, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\\\\\", \\\\\"content\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates &amp; Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\\\\\", \\\\\"score\\\\\": 0.8914433, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 Playoffs: West Finals | Timberwolves (3) vs. Mavericks (5) - NBA.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nba.com/playoffs/2024/west-final\\\\\", \\\\\"content\\\\\": \\\\\"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\\\\\", \\\\\"score\\\\\": 0.8884594, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Conference Finals Schedule: Full List of Games &amp; Results\\\\\", \\\\\"url\\\\\": \\\\\"https://www.si.com/nba/nba-conference-finals-schedule-full-list-of-games-results\\\\\", \\\\\"content\\\\\": \\\\\"The 2024 NBA conference finals matchups are set. Here\\'s the schedule for all the games. ... Western Conference First Round (1) Oklahoma City Thunder def. (8) New Orleans Pelicans in 4 games\\\\\", \\\\\"score\\\\\": 0.85008353, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference playoff bracket - Basketnews.com\\\\\", \\\\\"url\\\\\": \\\\\"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\\\\\", \\\\\"content\\\\\": \\\\\"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\\\\\", \\\\\"score\\\\\": 0.8479807, \\\\\"raw_content\\\\\": null}]}\"}'</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">]</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'output'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #008000; text-decoration-color: #008000\">'content: The teams that played in the NBA Western Conference Finals of 2024 were the Dallas Mavericks and the Minnesota Timberwolves. tool_calls: []'</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">}</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">{</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'input'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">[</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"NBA Western Conference Finals 2024 teams\"}}]}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"tool\",\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"NBA Western Conference Finals 2024 teams\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference Finals - Basketball-Reference.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\\\\\", \\\\\"content\\\\\": \\\\\"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown (20.8 / 5.4 / 5.0) 2024 Playoff Leaders: PTS: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (635) TRB: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (208) AST: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (178) WS: Derrick White (2.9) More playoffs info\\\\\", \\\\\"score\\\\\": 0.9310187, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\\\\\", \\\\\"content\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates &amp; Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\\\\\", \\\\\"score\\\\\": 0.8914433, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 Playoffs: West Finals | Timberwolves (3) vs. Mavericks (5) - NBA.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nba.com/playoffs/2024/west-final\\\\\", \\\\\"content\\\\\": \\\\\"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\\\\\", \\\\\"score\\\\\": 0.8884594, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Conference Finals Schedule: Full List of Games &amp; Results\\\\\", \\\\\"url\\\\\": \\\\\"https://www.si.com/nba/nba-conference-finals-schedule-full-list-of-games-results\\\\\", \\\\\"content\\\\\": \\\\\"The 2024 NBA conference finals matchups are set. Here\\'s the schedule for all the games. ... Western Conference First Round (1) Oklahoma City Thunder def. (8) New Orleans Pelicans in 4 games\\\\\", \\\\\"score\\\\\": 0.85008353, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference playoff bracket - Basketnews.com\\\\\", \\\\\"url\\\\\": \\\\\"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\\\\\", \\\\\"content\\\\\": \\\\\"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\\\\\", \\\\\"score\\\\\": 0.8479807, \\\\\"raw_content\\\\\": null}]}\"}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"The teams that played in the NBA Western Conference Finals of 2024 were the Dallas Mavericks and the Minnesota Timberwolves.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[]}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"In which episode and season of South Park does Bill Cosby (BSM-471) first appear? Give me the number and title.\",\"context\":null}'</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">]</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'output'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #008000; text-decoration-color: #008000\">\"content:  tool_calls: [ToolCall(call_id='ebd7e906-3ec9-45de-a58e-6662d75eceb7', tool_name=&lt;BuiltinTool.brave_search: 'brave_search'&gt;, arguments={'query': 'Bill Cosby South Park episode'})]\"</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">}</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">{</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'input'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"ebd7e906-3ec9-45de-a58e-6662d75eceb7\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"Bill Cosby South Park episode\"}}]}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'output'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"tool\",\"call_id\":\"ebd7e906-3ec9-45de-a58e-6662d75eceb7\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"Bill Cosby South Park episode\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"Bill Cosby and Taylor Swift Duet - South Park Studios\\\\\", \\\\\"url\\\\\": \\\\\"https://www.southparkstudios.com/video-clips/90r7i1/south-park-bill-cosby-and-taylor-swift-duet\\\\\", \\\\\"content\\\\\": \\\\\"01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:03 Bill Cosby and Taylor Swift Duet South ParkS18 E10 ------------------------------------------------------- The holiday special continues with Bill Cosby and Taylor Swift\\'s rendition of \\\\\\\\\\\\\"It\\'s Snowing Out There\\\\\\\\\\\\\". 01:31 #WeBelieveInYou South ParkS18 E10 -------------------------------------- With everyone watching, Kyle takes the opportunity to reach out to his brother. 01:47 Watch Your Microaggressions, Bro South ParkS19 E1 ------------------------------------------------------ Cartman\\'s plan to frame PC Principal backfires. South ParkS19 E1 -------------------------------------- After hearing that the PC people have targeted Kyle, Cartman vows to help.\\\\\", \\\\\"score\\\\\": 0.685971, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Bill Cosby is Here to See You - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/video-clips/wfot8s/south-park-bill-cosby-is-here-to-see-you\\\\\", \\\\\"content\\\\\": \\\\\"01:56 It\\'s Not About Music South ParkS18 E9 ------------------------------------------ At home, Randy sees the consequences of Lorde\\'s performance and calls the Record Producer to try and fix it. 01:24 Lorde\\'s Hologram South ParkS18 E9 -------------------------------------- The Record Producer reveals the truth about the music industry... South ParkS18 E9 --------------------------------------------- Randy catches Sharon with Tupac\\'s hologram. 01:37 I\\'ve Got Your Son, Lorde South ParkS18 E10 ----------------------------------------------- The Record Producer takes Stan and Kyle hostage. 01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:21 Lorde Is My Dad South ParkS18 E10 -------------------------------------- After trying to confront Cartman Bra, Stan finally reveals the truth about his dad.\\\\\", \\\\\"score\\\\\": 0.6643884, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Bill Cosby (android) | South Park Character ... - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/wiki/Bill_Cosby_(android)\\\\\", \\\\\"content\\\\\": \\\\\"Bill Cosby (android) | South Park Character / Location / User talk etc | Official South Park Studios Wiki Sent back in time to destroy Eric Cartman\\'s Dawson\\'s Creek Trapper Keeper before it manifests into an omnipotent supercomputer that can destroy all humanity, \\\\\\\\\\\\\"Bill Cosby\\\\\\\\\\\\\" is really VSM471, an android or cyborg of some kind engineered by \\'hoomans\\' in the distant future. He fails in his initial missions to infiltrate South Park Elementary\\'s 4th Grade class, destroy the Trapper Keeper or Cartman himself, but with Stan Marsh and Kyle Broflovski\\'s aid, he is able to succeed in preventing his dismal future, and painfully fades from existence. South Park and all related titles, logos and characters are trademarks of Comedy Partners.\\\\\", \\\\\"score\\\\\": 0.5052006, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"\\'South Park\\' takes on Cosby, police, 2014 | CNN\\\\\", \\\\\"url\\\\\": \\\\\"https://www.cnn.com/2014/12/11/showbiz/tv/south-park-cosby-redskins-police/index.html\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\u2018South Park\\\\\\\\u2019 takes on Cosby, police, 2014 | CNN Watch Listen Live TV Subscribe Follow CNN Entertainment CNN Headlines CNN Shorts CNN10 CNN Max CNN TV Schedules CNN 5 Things CNN Underscored CNN Crossword About CNN CNN Profiles CNN Newsletters Work for CNN CNN \\\\\\\\u00a0\\\\\\\\u2014\\\\\\\\u00a0 \\\\\\\\u201cI think we take for granted how Trey Parker can jam a heap of current issues into a storyline thats a smart and funny #SouthPark episode,\\\\\\\\u201d wrote Brent Veale. \\\\\\\\u201cOh Lorde, CartmanBrah, dead celebrity holograms, murdering cops, this #SouthPark episode is certainly making #SaveTheLivingRoom happen,\\\\\\\\u201d added Brett Pender. CNN Headlines CNN10 CNN Max CNN TV Schedules CNN 5 Things CNN Underscored CNN Crossword About CNN CNN Profiles CNN Newsletters Work for CNN Follow CNN Entertainment\\\\\", \\\\\"score\\\\\": 0.45391592, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Trapper Keeper (South Park) - Wikipedia\\\\\", \\\\\"url\\\\\": \\\\\"https://en.wikipedia.org/wiki/Trapper_Keeper_(South_Park)\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" is the twelfth episode of the fourth season of the animated television series South Park, and the 60th episode of the series overall. In the episode, a man from the future wants Cartman\\'s new Trapper Keeper, while Mr. Garrison\\'s kindergarten class holds an election for class president with confusing results. It is one of the many South Park episodes that parodies a current event.[1] The main plot of the episode involving the Trapper Keeper was written before the election,[1] but the subplot is a parody of the controversy surrounding the election\\'s outcome.[2] \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" did not originally feature the election storyline, only a subplot about Ike attending his first day of kindergarten.[3] \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" Full episode at South Park Studios\\\\\", \\\\\"score\\\\\": 0.3839421, \\\\\"raw_content\\\\\": null}]}\"}'</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">}</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">{</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'input'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">[</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"NBA Western Conference Finals 2024 teams\"}}]}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"tool\",\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"NBA Western Conference Finals 2024 teams\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference Finals - Basketball-Reference.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\\\\\", \\\\\"content\\\\\": \\\\\"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown (20.8 / 5.4 / 5.0) 2024 Playoff Leaders: PTS: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (635) TRB: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (208) AST: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (178) WS: Derrick White (2.9) More playoffs info\\\\\", \\\\\"score\\\\\": 0.9310187, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\\\\\", \\\\\"content\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates &amp; Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\\\\\", \\\\\"score\\\\\": 0.8914433, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 Playoffs: West Finals | Timberwolves (3) vs. Mavericks (5) - NBA.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nba.com/playoffs/2024/west-final\\\\\", \\\\\"content\\\\\": \\\\\"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\\\\\", \\\\\"score\\\\\": 0.8884594, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Conference Finals Schedule: Full List of Games &amp; Results\\\\\", \\\\\"url\\\\\": \\\\\"https://www.si.com/nba/nba-conference-finals-schedule-full-list-of-games-results\\\\\", \\\\\"content\\\\\": \\\\\"The 2024 NBA conference finals matchups are set. Here\\'s the schedule for all the games. ... Western Conference First Round (1) Oklahoma City Thunder def. (8) New Orleans Pelicans in 4 games\\\\\", \\\\\"score\\\\\": 0.85008353, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference playoff bracket - Basketnews.com\\\\\", \\\\\"url\\\\\": \\\\\"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\\\\\", \\\\\"content\\\\\": \\\\\"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\\\\\", \\\\\"score\\\\\": 0.8479807, \\\\\"raw_content\\\\\": null}]}\"}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"The teams that played in the NBA Western Conference Finals of 2024 were the Dallas Mavericks and the Minnesota Timberwolves.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[]}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"In which episode and season of South Park does Bill Cosby (BSM-471) first appear? Give me the number and title.\",\"context\":null}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"ebd7e906-3ec9-45de-a58e-6662d75eceb7\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"Bill Cosby South Park episode\"}}]}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"tool\",\"call_id\":\"ebd7e906-3ec9-45de-a58e-6662d75eceb7\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"Bill Cosby South Park episode\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"Bill Cosby and Taylor Swift Duet - South Park Studios\\\\\", \\\\\"url\\\\\": \\\\\"https://www.southparkstudios.com/video-clips/90r7i1/south-park-bill-cosby-and-taylor-swift-duet\\\\\", \\\\\"content\\\\\": \\\\\"01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:03 Bill Cosby and Taylor Swift Duet South ParkS18 E10 ------------------------------------------------------- The holiday special continues with Bill Cosby and Taylor Swift\\'s rendition of \\\\\\\\\\\\\"It\\'s Snowing Out There\\\\\\\\\\\\\". 01:31 #WeBelieveInYou South ParkS18 E10 -------------------------------------- With everyone watching, Kyle takes the opportunity to reach out to his brother. 01:47 Watch Your Microaggressions, Bro South ParkS19 E1 ------------------------------------------------------ Cartman\\'s plan to frame PC Principal backfires. South ParkS19 E1 -------------------------------------- After hearing that the PC people have targeted Kyle, Cartman vows to help.\\\\\", \\\\\"score\\\\\": 0.685971, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Bill Cosby is Here to See You - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/video-clips/wfot8s/south-park-bill-cosby-is-here-to-see-you\\\\\", \\\\\"content\\\\\": \\\\\"01:56 It\\'s Not About Music South ParkS18 E9 ------------------------------------------ At home, Randy sees the consequences of Lorde\\'s performance and calls the Record Producer to try and fix it. 01:24 Lorde\\'s Hologram South ParkS18 E9 -------------------------------------- The Record Producer reveals the truth about the music industry... South ParkS18 E9 --------------------------------------------- Randy catches Sharon with Tupac\\'s hologram. 01:37 I\\'ve Got Your Son, Lorde South ParkS18 E10 ----------------------------------------------- The Record Producer takes Stan and Kyle hostage. 01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:21 Lorde Is My Dad South ParkS18 E10 -------------------------------------- After trying to confront Cartman Bra, Stan finally reveals the truth about his dad.\\\\\", \\\\\"score\\\\\": 0.6643884, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Bill Cosby (android) | South Park Character ... - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/wiki/Bill_Cosby_(android)\\\\\", \\\\\"content\\\\\": \\\\\"Bill Cosby (android) | South Park Character / Location / User talk etc | Official South Park Studios Wiki Sent back in time to destroy Eric Cartman\\'s Dawson\\'s Creek Trapper Keeper before it manifests into an omnipotent supercomputer that can destroy all humanity, \\\\\\\\\\\\\"Bill Cosby\\\\\\\\\\\\\" is really VSM471, an android or cyborg of some kind engineered by \\'hoomans\\' in the distant future. He fails in his initial missions to infiltrate South Park Elementary\\'s 4th Grade class, destroy the Trapper Keeper or Cartman himself, but with Stan Marsh and Kyle Broflovski\\'s aid, he is able to succeed in preventing his dismal future, and painfully fades from existence. South Park and all related titles, logos and characters are trademarks of Comedy Partners.\\\\\", \\\\\"score\\\\\": 0.5052006, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"\\'South Park\\' takes on Cosby, police, 2014 | CNN\\\\\", \\\\\"url\\\\\": \\\\\"https://www.cnn.com/2014/12/11/showbiz/tv/south-park-cosby-redskins-police/index.html\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\u2018South Park\\\\\\\\u2019 takes on Cosby, police, 2014 | CNN Watch Listen Live TV Subscribe Follow CNN Entertainment CNN Headlines CNN Shorts CNN10 CNN Max CNN TV Schedules CNN 5 Things CNN Underscored CNN Crossword About CNN CNN Profiles CNN Newsletters Work for CNN CNN \\\\\\\\u00a0\\\\\\\\u2014\\\\\\\\u00a0 \\\\\\\\u201cI think we take for granted how Trey Parker can jam a heap of current issues into a storyline thats a smart and funny #SouthPark episode,\\\\\\\\u201d wrote Brent Veale. \\\\\\\\u201cOh Lorde, CartmanBrah, dead celebrity holograms, murdering cops, this #SouthPark episode is certainly making #SaveTheLivingRoom happen,\\\\\\\\u201d added Brett Pender. CNN Headlines CNN10 CNN Max CNN TV Schedules CNN 5 Things CNN Underscored CNN Crossword About CNN CNN Profiles CNN Newsletters Work for CNN Follow CNN Entertainment\\\\\", \\\\\"score\\\\\": 0.45391592, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Trapper Keeper (South Park) - Wikipedia\\\\\", \\\\\"url\\\\\": \\\\\"https://en.wikipedia.org/wiki/Trapper_Keeper_(South_Park)\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" is the twelfth episode of the fourth season of the animated television series South Park, and the 60th episode of the series overall. In the episode, a man from the future wants Cartman\\'s new Trapper Keeper, while Mr. Garrison\\'s kindergarten class holds an election for class president with confusing results. It is one of the many South Park episodes that parodies a current event.[1] The main plot of the episode involving the Trapper Keeper was written before the election,[1] but the subplot is a parody of the controversy surrounding the election\\'s outcome.[2] \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" did not originally feature the election storyline, only a subplot about Ike attending his first day of kindergarten.[3] \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" Full episode at South Park Studios\\\\\", \\\\\"score\\\\\": 0.3839421, \\\\\"raw_content\\\\\": null}]}\"}'</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">]</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'output'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #008000; text-decoration-color: #008000\">'content: Bill Cosby (BSM-471) first appears in Season 4, Episode 12 of South Park, titled \"Trapper Keeper\". tool_calls: []'</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">}</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">{</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'input'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">[</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"NBA Western Conference Finals 2024 teams\"}}]}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"tool\",\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"NBA Western Conference Finals 2024 teams\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference Finals - Basketball-Reference.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\\\\\", \\\\\"content\\\\\": \\\\\"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown (20.8 / 5.4 / 5.0) 2024 Playoff Leaders: PTS: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (635) TRB: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (208) AST: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (178) WS: Derrick White (2.9) More playoffs info\\\\\", \\\\\"score\\\\\": 0.9310187, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\\\\\", \\\\\"content\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates &amp; Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\\\\\", \\\\\"score\\\\\": 0.8914433, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 Playoffs: West Finals | Timberwolves (3) vs. Mavericks (5) - NBA.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nba.com/playoffs/2024/west-final\\\\\", \\\\\"content\\\\\": \\\\\"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\\\\\", \\\\\"score\\\\\": 0.8884594, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Conference Finals Schedule: Full List of Games &amp; Results\\\\\", \\\\\"url\\\\\": \\\\\"https://www.si.com/nba/nba-conference-finals-schedule-full-list-of-games-results\\\\\", \\\\\"content\\\\\": \\\\\"The 2024 NBA conference finals matchups are set. Here\\'s the schedule for all the games. ... Western Conference First Round (1) Oklahoma City Thunder def. (8) New Orleans Pelicans in 4 games\\\\\", \\\\\"score\\\\\": 0.85008353, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference playoff bracket - Basketnews.com\\\\\", \\\\\"url\\\\\": \\\\\"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\\\\\", \\\\\"content\\\\\": \\\\\"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\\\\\", \\\\\"score\\\\\": 0.8479807, \\\\\"raw_content\\\\\": null}]}\"}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"The teams that played in the NBA Western Conference Finals of 2024 were the Dallas Mavericks and the Minnesota Timberwolves.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[]}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"In which episode and season of South Park does Bill Cosby (BSM-471) first appear? Give me the number and title.\",\"context\":null}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"ebd7e906-3ec9-45de-a58e-6662d75eceb7\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"Bill Cosby South Park episode\"}}]}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"tool\",\"call_id\":\"ebd7e906-3ec9-45de-a58e-6662d75eceb7\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"Bill Cosby South Park episode\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"Bill Cosby and Taylor Swift Duet - South Park Studios\\\\\", \\\\\"url\\\\\": \\\\\"https://www.southparkstudios.com/video-clips/90r7i1/south-park-bill-cosby-and-taylor-swift-duet\\\\\", \\\\\"content\\\\\": \\\\\"01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:03 Bill Cosby and Taylor Swift Duet South ParkS18 E10 ------------------------------------------------------- The holiday special continues with Bill Cosby and Taylor Swift\\'s rendition of \\\\\\\\\\\\\"It\\'s Snowing Out There\\\\\\\\\\\\\". 01:31 #WeBelieveInYou South ParkS18 E10 -------------------------------------- With everyone watching, Kyle takes the opportunity to reach out to his brother. 01:47 Watch Your Microaggressions, Bro South ParkS19 E1 ------------------------------------------------------ Cartman\\'s plan to frame PC Principal backfires. South ParkS19 E1 -------------------------------------- After hearing that the PC people have targeted Kyle, Cartman vows to help.\\\\\", \\\\\"score\\\\\": 0.685971, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Bill Cosby is Here to See You - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/video-clips/wfot8s/south-park-bill-cosby-is-here-to-see-you\\\\\", \\\\\"content\\\\\": \\\\\"01:56 It\\'s Not About Music South ParkS18 E9 ------------------------------------------ At home, Randy sees the consequences of Lorde\\'s performance and calls the Record Producer to try and fix it. 01:24 Lorde\\'s Hologram South ParkS18 E9 -------------------------------------- The Record Producer reveals the truth about the music industry... South ParkS18 E9 --------------------------------------------- Randy catches Sharon with Tupac\\'s hologram. 01:37 I\\'ve Got Your Son, Lorde South ParkS18 E10 ----------------------------------------------- The Record Producer takes Stan and Kyle hostage. 01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:21 Lorde Is My Dad South ParkS18 E10 -------------------------------------- After trying to confront Cartman Bra, Stan finally reveals the truth about his dad.\\\\\", \\\\\"score\\\\\": 0.6643884, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Bill Cosby (android) | South Park Character ... - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/wiki/Bill_Cosby_(android)\\\\\", \\\\\"content\\\\\": \\\\\"Bill Cosby (android) | South Park Character / Location / User talk etc | Official South Park Studios Wiki Sent back in time to destroy Eric Cartman\\'s Dawson\\'s Creek Trapper Keeper before it manifests into an omnipotent supercomputer that can destroy all humanity, \\\\\\\\\\\\\"Bill Cosby\\\\\\\\\\\\\" is really VSM471, an android or cyborg of some kind engineered by \\'hoomans\\' in the distant future. He fails in his initial missions to infiltrate South Park Elementary\\'s 4th Grade class, destroy the Trapper Keeper or Cartman himself, but with Stan Marsh and Kyle Broflovski\\'s aid, he is able to succeed in preventing his dismal future, and painfully fades from existence. South Park and all related titles, logos and characters are trademarks of Comedy Partners.\\\\\", \\\\\"score\\\\\": 0.5052006, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"\\'South Park\\' takes on Cosby, police, 2014 | CNN\\\\\", \\\\\"url\\\\\": \\\\\"https://www.cnn.com/2014/12/11/showbiz/tv/south-park-cosby-redskins-police/index.html\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\u2018South Park\\\\\\\\u2019 takes on Cosby, police, 2014 | CNN Watch Listen Live TV Subscribe Follow CNN Entertainment CNN Headlines CNN Shorts CNN10 CNN Max CNN TV Schedules CNN 5 Things CNN Underscored CNN Crossword About CNN CNN Profiles CNN Newsletters Work for CNN CNN \\\\\\\\u00a0\\\\\\\\u2014\\\\\\\\u00a0 \\\\\\\\u201cI think we take for granted how Trey Parker can jam a heap of current issues into a storyline thats a smart and funny #SouthPark episode,\\\\\\\\u201d wrote Brent Veale. \\\\\\\\u201cOh Lorde, CartmanBrah, dead celebrity holograms, murdering cops, this #SouthPark episode is certainly making #SaveTheLivingRoom happen,\\\\\\\\u201d added Brett Pender. CNN Headlines CNN10 CNN Max CNN TV Schedules CNN 5 Things CNN Underscored CNN Crossword About CNN CNN Profiles CNN Newsletters Work for CNN Follow CNN Entertainment\\\\\", \\\\\"score\\\\\": 0.45391592, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Trapper Keeper (South Park) - Wikipedia\\\\\", \\\\\"url\\\\\": \\\\\"https://en.wikipedia.org/wiki/Trapper_Keeper_(South_Park)\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" is the twelfth episode of the fourth season of the animated television series South Park, and the 60th episode of the series overall. In the episode, a man from the future wants Cartman\\'s new Trapper Keeper, while Mr. Garrison\\'s kindergarten class holds an election for class president with confusing results. It is one of the many South Park episodes that parodies a current event.[1] The main plot of the episode involving the Trapper Keeper was written before the election,[1] but the subplot is a parody of the controversy surrounding the election\\'s outcome.[2] \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" did not originally feature the election storyline, only a subplot about Ike attending his first day of kindergarten.[3] \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" Full episode at South Park Studios\\\\\", \\\\\"score\\\\\": 0.3839421, \\\\\"raw_content\\\\\": null}]}\"}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"Bill Cosby (BSM-471) first appears in Season 4, Episode 12 of South Park, titled \\\\\"Trapper Keeper\\\\\".\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[]}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"What is the British-American kickboxer Andrew Tate\\'s kickboxing name?\",\"context\":null}'</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #000000; text-decoration-color: #000000; font-weight: bold\">]</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'output'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #008000; text-decoration-color: #008000\">\"content:  tool_calls: [ToolCall(call_id='e26ecfb2-434c-479f-95dc-7b3b4929665a', tool_name=&lt;BuiltinTool.brave_search: 'brave_search'&gt;, arguments={'query': 'Andrew Tate kickboxing name'})]\"</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">}</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">{</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'input'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"e26ecfb2-434c-479f-95dc-7b3b4929665a\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"Andrew Tate kickboxing name\"}}]}'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'output'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"tool\",\"call_id\":\"e26ecfb2-434c-479f-95dc-7b3b4929665a\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"Andrew Tate kickboxing name\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"50 Facts About Andrew Tate - Facts.net\\\\\", \\\\\"url\\\\\": \\\\\"https://facts.net/andrew-tate-facts/\\\\\", \\\\\"content\\\\\": \\\\\"Full Name: Andrew Tate\\'s full name is Emory Andrew Tate III, named after his father, a celebrated chess player. Date of Birth: ... Kickboxing Start: Tate began his kickboxing career in 2005, starting his journey as a professional fighter, which would later be a significant part of his persona. First Championship:\\\\\", \\\\\"score\\\\\": 0.8967681, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"The Life Of Andrew Tate (By Andrew Tate Himself)\\\\\", \\\\\"url\\\\\": \\\\\"https://sidekickboxing.co.uk/the-life-of-andrew-king-cobra-tate/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate stats. Fight Name: Cobra Tate. Born: 1 December 1986. Weight: 90 KG. Weight Class: Cruiserweight. Height: 1.92m. Fight Record: Wins - 76, Losses - 9. ... Andrew Tate\\'s Kickboxing Career. Andrew Tate has always fought credible opponents right from the beginning of his kickboxing career. One of his first professional fights on\\\\\", \\\\\"score\\\\\": 0.8795718, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Andrew Tate kickboxing record: How many championships ... - FirstSportz\\\\\", \\\\\"url\\\\\": \\\\\"https://firstsportz.com/mma-how-many-championships-does-andrew-tate-have/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate\\'s Kickboxing career. During his kickboxing career, he used the nickname \\\\\\\\\\\\\"King Cobra,\\\\\\\\\\\\\" which he currently uses as his Twitter name. Tate had an unorthodox style of movement inside the ring. He kept his hands down most of the time and relied on quick jabs and an overhand right to land significant strikes.\\\\\", \\\\\"score\\\\\": 0.8752871, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Andrew Tate: Kickboxing Record, Facts, Height, Weight, Age, Biography\\\\\", \\\\\"url\\\\\": \\\\\"https://www.lowkickmma.com/andrew-tate-kickboxing-record-facts-height-weight-age-biography/\\\\\", \\\\\"content\\\\\": \\\\\"Birth Name: Emory Andrew Tate III: Date of Birth: 1 December 1986: Place of Birth: Washington, D.C., U.S. ... In his professional kickboxing career, Andrew Tate won 32 of his fights by knockout.\\\\\", \\\\\"score\\\\\": 0.7992077, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"About Andrew Tate: A Journey from Champion to Controversy\\\\\", \\\\\"url\\\\\": \\\\\"https://reachmorpheus.com/andrew-tate/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate\\'s kickboxing career, beginning in 2005, is a tale of determination and skill. He quickly made a name for himself in the sport, rising through the ranks with his unique fighting style and strategic approach, honed by his chess-playing background.\\\\\", \\\\\"score\\\\\": 0.6490677, \\\\\"raw_content\\\\\": null}]}\"}'</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">}</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">{</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'input'</span>: <span style=\"font-weight: bold\">[</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"}'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null}'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"NBA Western Conference Finals 2024 teams\"}}]}'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"tool\",\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"NBA Western Conference Finals 2024 teams\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference Finals - Basketball-Reference.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\\\\\", \\\\\"content\\\\\": \\\\\"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown (20.8 / 5.4 / 5.0) 2024 Playoff Leaders: PTS: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (635) TRB: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (208) AST: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (178) WS: Derrick White (2.9) More playoffs info\\\\\", \\\\\"score\\\\\": 0.9310187, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\\\\\", \\\\\"content\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates &amp; Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\\\\\", \\\\\"score\\\\\": 0.8914433, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 Playoffs: West Finals | Timberwolves (3) vs. Mavericks (5) - NBA.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nba.com/playoffs/2024/west-final\\\\\", \\\\\"content\\\\\": \\\\\"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\\\\\", \\\\\"score\\\\\": 0.8884594, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Conference Finals Schedule: Full List of Games &amp; Results\\\\\", \\\\\"url\\\\\": \\\\\"https://www.si.com/nba/nba-conference-finals-schedule-full-list-of-games-results\\\\\", \\\\\"content\\\\\": \\\\\"The 2024 NBA conference finals matchups are set. Here\\'s the schedule for all the games. ... Western Conference First Round (1) Oklahoma City Thunder def. (8) New Orleans Pelicans in 4 games\\\\\", \\\\\"score\\\\\": 0.85008353, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference playoff bracket - Basketnews.com\\\\\", \\\\\"url\\\\\": \\\\\"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\\\\\", \\\\\"content\\\\\": \\\\\"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\\\\\", \\\\\"score\\\\\": 0.8479807, \\\\\"raw_content\\\\\": null}]}\"}'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"The teams that played in the NBA Western Conference Finals of 2024 were the Dallas Mavericks and the Minnesota Timberwolves.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[]}'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"In which episode and season of South Park does Bill Cosby (BSM-471) first appear? Give me the number and title.\",\"context\":null}'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"ebd7e906-3ec9-45de-a58e-6662d75eceb7\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"Bill Cosby South Park episode\"}}]}'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"tool\",\"call_id\":\"ebd7e906-3ec9-45de-a58e-6662d75eceb7\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"Bill Cosby South Park episode\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"Bill Cosby and Taylor Swift Duet - South Park Studios\\\\\", \\\\\"url\\\\\": \\\\\"https://www.southparkstudios.com/video-clips/90r7i1/south-park-bill-cosby-and-taylor-swift-duet\\\\\", \\\\\"content\\\\\": \\\\\"01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:03 Bill Cosby and Taylor Swift Duet South ParkS18 E10 ------------------------------------------------------- The holiday special continues with Bill Cosby and Taylor Swift\\'s rendition of \\\\\\\\\\\\\"It\\'s Snowing Out There\\\\\\\\\\\\\". 01:31 #WeBelieveInYou South ParkS18 E10 -------------------------------------- With everyone watching, Kyle takes the opportunity to reach out to his brother. 01:47 Watch Your Microaggressions, Bro South ParkS19 E1 ------------------------------------------------------ Cartman\\'s plan to frame PC Principal backfires. South ParkS19 E1 -------------------------------------- After hearing that the PC people have targeted Kyle, Cartman vows to help.\\\\\", \\\\\"score\\\\\": 0.685971, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Bill Cosby is Here to See You - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/video-clips/wfot8s/south-park-bill-cosby-is-here-to-see-you\\\\\", \\\\\"content\\\\\": \\\\\"01:56 It\\'s Not About Music South ParkS18 E9 ------------------------------------------ At home, Randy sees the consequences of Lorde\\'s performance and calls the Record Producer to try and fix it. 01:24 Lorde\\'s Hologram South ParkS18 E9 -------------------------------------- The Record Producer reveals the truth about the music industry... South ParkS18 E9 --------------------------------------------- Randy catches Sharon with Tupac\\'s hologram. 01:37 I\\'ve Got Your Son, Lorde South ParkS18 E10 ----------------------------------------------- The Record Producer takes Stan and Kyle hostage. 01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:21 Lorde Is My Dad South ParkS18 E10 -------------------------------------- After trying to confront Cartman Bra, Stan finally reveals the truth about his dad.\\\\\", \\\\\"score\\\\\": 0.6643884, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Bill Cosby (android) | South Park Character ... - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/wiki/Bill_Cosby_(android)\\\\\", \\\\\"content\\\\\": \\\\\"Bill Cosby (android) | South Park Character / Location / User talk etc | Official South Park Studios Wiki Sent back in time to destroy Eric Cartman\\'s Dawson\\'s Creek Trapper Keeper before it manifests into an omnipotent supercomputer that can destroy all humanity, \\\\\\\\\\\\\"Bill Cosby\\\\\\\\\\\\\" is really VSM471, an android or cyborg of some kind engineered by \\'hoomans\\' in the distant future. He fails in his initial missions to infiltrate South Park Elementary\\'s 4th Grade class, destroy the Trapper Keeper or Cartman himself, but with Stan Marsh and Kyle Broflovski\\'s aid, he is able to succeed in preventing his dismal future, and painfully fades from existence. South Park and all related titles, logos and characters are trademarks of Comedy Partners.\\\\\", \\\\\"score\\\\\": 0.5052006, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"\\'South Park\\' takes on Cosby, police, 2014 | CNN\\\\\", \\\\\"url\\\\\": \\\\\"https://www.cnn.com/2014/12/11/showbiz/tv/south-park-cosby-redskins-police/index.html\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\u2018South Park\\\\\\\\u2019 takes on Cosby, police, 2014 | CNN Watch Listen Live TV Subscribe Follow CNN Entertainment CNN Headlines CNN Shorts CNN10 CNN Max CNN TV Schedules CNN 5 Things CNN Underscored CNN Crossword About CNN CNN Profiles CNN Newsletters Work for CNN CNN \\\\\\\\u00a0\\\\\\\\u2014\\\\\\\\u00a0 \\\\\\\\u201cI think we take for granted how Trey Parker can jam a heap of current issues into a storyline thats a smart and funny #SouthPark episode,\\\\\\\\u201d wrote Brent Veale. \\\\\\\\u201cOh Lorde, CartmanBrah, dead celebrity holograms, murdering cops, this #SouthPark episode is certainly making #SaveTheLivingRoom happen,\\\\\\\\u201d added Brett Pender. CNN Headlines CNN10 CNN Max CNN TV Schedules CNN 5 Things CNN Underscored CNN Crossword About CNN CNN Profiles CNN Newsletters Work for CNN Follow CNN Entertainment\\\\\", \\\\\"score\\\\\": 0.45391592, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Trapper Keeper (South Park) - Wikipedia\\\\\", \\\\\"url\\\\\": \\\\\"https://en.wikipedia.org/wiki/Trapper_Keeper_(South_Park)\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" is the twelfth episode of the fourth season of the animated television series South Park, and the 60th episode of the series overall. In the episode, a man from the future wants Cartman\\'s new Trapper Keeper, while Mr. Garrison\\'s kindergarten class holds an election for class president with confusing results. It is one of the many South Park episodes that parodies a current event.[1] The main plot of the episode involving the Trapper Keeper was written before the election,[1] but the subplot is a parody of the controversy surrounding the election\\'s outcome.[2] \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" did not originally feature the election storyline, only a subplot about Ike attending his first day of kindergarten.[3] \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" Full episode at South Park Studios\\\\\", \\\\\"score\\\\\": 0.3839421, \\\\\"raw_content\\\\\": null}]}\"}'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"Bill Cosby (BSM-471) first appears in Season 4, Episode 12 of South Park, titled \\\\\"Trapper Keeper\\\\\".\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[]}'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"What is the British-American kickboxer Andrew Tate\\'s kickboxing name?\",\"context\":null}'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"e26ecfb2-434c-479f-95dc-7b3b4929665a\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"Andrew Tate kickboxing name\"}}]}'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"tool\",\"call_id\":\"e26ecfb2-434c-479f-95dc-7b3b4929665a\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"Andrew Tate kickboxing name\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"50 Facts About Andrew Tate - Facts.net\\\\\", \\\\\"url\\\\\": \\\\\"https://facts.net/andrew-tate-facts/\\\\\", \\\\\"content\\\\\": \\\\\"Full Name: Andrew Tate\\'s full name is Emory Andrew Tate III, named after his father, a celebrated chess player. Date of Birth: ... Kickboxing Start: Tate began his kickboxing career in 2005, starting his journey as a professional fighter, which would later be a significant part of his persona. First Championship:\\\\\", \\\\\"score\\\\\": 0.8967681, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"The Life Of Andrew Tate (By Andrew Tate Himself)\\\\\", \\\\\"url\\\\\": \\\\\"https://sidekickboxing.co.uk/the-life-of-andrew-king-cobra-tate/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate stats. Fight Name: Cobra Tate. Born: 1 December 1986. Weight: 90 KG. Weight Class: Cruiserweight. Height: 1.92m. Fight Record: Wins - 76, Losses - 9. ... Andrew Tate\\'s Kickboxing Career. Andrew Tate has always fought credible opponents right from the beginning of his kickboxing career. One of his first professional fights on\\\\\", \\\\\"score\\\\\": 0.8795718, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Andrew Tate kickboxing record: How many championships ... - FirstSportz\\\\\", \\\\\"url\\\\\": \\\\\"https://firstsportz.com/mma-how-many-championships-does-andrew-tate-have/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate\\'s Kickboxing career. During his kickboxing career, he used the nickname \\\\\\\\\\\\\"King Cobra,\\\\\\\\\\\\\" which he currently uses as his Twitter name. Tate had an unorthodox style of movement inside the ring. He kept his hands down most of the time and relied on quick jabs and an overhand right to land significant strikes.\\\\\", \\\\\"score\\\\\": 0.8752871, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Andrew Tate: Kickboxing Record, Facts, Height, Weight, Age, Biography\\\\\", \\\\\"url\\\\\": \\\\\"https://www.lowkickmma.com/andrew-tate-kickboxing-record-facts-height-weight-age-biography/\\\\\", \\\\\"content\\\\\": \\\\\"Birth Name: Emory Andrew Tate III: Date of Birth: 1 December 1986: Place of Birth: Washington, D.C., U.S. ... In his professional kickboxing career, Andrew Tate won 32 of his fights by knockout.\\\\\", \\\\\"score\\\\\": 0.7992077, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"About Andrew Tate: A Journey from Champion to Controversy\\\\\", \\\\\"url\\\\\": \\\\\"https://reachmorpheus.com/andrew-tate/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate\\'s kickboxing career, beginning in 2005, is a tale of determination and skill. He quickly made a name for himself in the sport, rising through the ranks with his unique fighting style and strategic approach, honed by his chess-playing background.\\\\\", \\\\\"score\\\\\": 0.6490677, \\\\\"raw_content\\\\\": null}]}\"}'</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"font-weight: bold\">]</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'output'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'content: Andrew Tate\\'s kickboxing name is \"Cobra Tate\" or \"King Cobra\". tool_calls: []'</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">}</span>\n",
-              "<span style=\"font-weight: bold\">]</span>\n",
-              "</pre>\n"
-            ],
-            "text/plain": [
-              "\u001b[1m[\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[1m{\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'input'\u001b[0m: \u001b[1m[\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[1m]\u001b[0m,\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'output'\u001b[0m: \u001b[32m\"content:  tool_calls: \u001b[0m\u001b[32m[\u001b[0m\u001b[32mToolCall\u001b[0m\u001b[32m(\u001b[0m\u001b[32mcall_id\u001b[0m\u001b[32m='838a3846-0bc4-488e-9e42-65a48e29b80a', \u001b[0m\u001b[32mtool_name\u001b[0m\u001b[32m=\u001b[0m\u001b[32m<\u001b[0m\u001b[32mBuiltinTool.brave_search:\u001b[0m\u001b[32m 'brave_search'>, \u001b[0m\u001b[32marguments\u001b[0m\u001b[32m=\u001b[0m\u001b[32m{\u001b[0m\u001b[32m'query': 'NBA Western Conference Finals 2024 teams'\u001b[0m\u001b[32m}\u001b[0m\u001b[32m)\u001b[0m\u001b[32m]\u001b[0m\u001b[32m\"\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[1;39m}\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[1;39m{\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'input'\u001b[0m\u001b[39m: \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"arguments\":\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"query\":\"NBA Western Conference Finals 2024 teams\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'output'\u001b[0m\u001b[39m: \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"tool\",\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"content\":\"\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"query\\\\\": \\\\\"NBA Western Conference Finals 2024 teams\\\\\", \\\\\"top_k\\\\\": \u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference Finals - Basketball-Reference.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\\\\\", \\\\\"content\\\\\": \\\\\"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown \u001b[0m\u001b[32m(\u001b[0m\u001b[32m20.8 / 5.4 / 5.0\u001b[0m\u001b[32m)\u001b[0m\u001b[32m 2024 Playoff Leaders: PTS: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m635\u001b[0m\u001b[32m)\u001b[0m\u001b[32m TRB: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m208\u001b[0m\u001b[32m)\u001b[0m\u001b[32m AST: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m178\u001b[0m\u001b[32m)\u001b[0m\u001b[32m WS: Derrick White \u001b[0m\u001b[32m(\u001b[0m\u001b[32m2.9\u001b[0m\u001b[32m)\u001b[0m\u001b[32m More playoffs info\\\\\", \\\\\"score\\\\\": 0.9310187, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\\\\\", \\\\\"content\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates & Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\\\\\", \\\\\"score\\\\\": 0.8914433, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 Playoffs: West Finals | Timberwolves \u001b[0m\u001b[32m(\u001b[0m\u001b[32m3\u001b[0m\u001b[32m)\u001b[0m\u001b[32m vs. Mavericks \u001b[0m\u001b[32m(\u001b[0m\u001b[32m5\u001b[0m\u001b[32m)\u001b[0m\u001b[32m - NBA.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nba.com/playoffs/2024/west-final\\\\\", \\\\\"content\\\\\": \\\\\"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\\\\\", \\\\\"score\\\\\": 0.8884594, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"NBA Conference Finals Schedule: Full List of Games & Results\\\\\", \\\\\"url\\\\\": \\\\\"https://www.si.com/nba/nba-conference-finals-schedule-full-list-of-games-results\\\\\", \\\\\"content\\\\\": \\\\\"The 2024 NBA conference finals matchups are set. Here\\'s the schedule for all the games. ... Western Conference First Round \u001b[0m\u001b[32m(\u001b[0m\u001b[32m1\u001b[0m\u001b[32m)\u001b[0m\u001b[32m Oklahoma City Thunder def. \u001b[0m\u001b[32m(\u001b[0m\u001b[32m8\u001b[0m\u001b[32m)\u001b[0m\u001b[32m New Orleans Pelicans in 4 games\\\\\", \\\\\"score\\\\\": 0.85008353, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference playoff bracket - Basketnews.com\\\\\", \\\\\"url\\\\\": \\\\\"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\\\\\", \\\\\"content\\\\\": \\\\\"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\\\\\", \\\\\"score\\\\\": 0.8479807, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[1;39m}\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[1;39m{\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'input'\u001b[0m\u001b[39m: \u001b[0m\u001b[1;39m[\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"arguments\":\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"query\":\"NBA Western Conference Finals 2024 teams\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"tool\",\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"content\":\"\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"query\\\\\": \\\\\"NBA Western Conference Finals 2024 teams\\\\\", \\\\\"top_k\\\\\": \u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference Finals - Basketball-Reference.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\\\\\", \\\\\"content\\\\\": \\\\\"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown \u001b[0m\u001b[32m(\u001b[0m\u001b[32m20.8 / 5.4 / 5.0\u001b[0m\u001b[32m)\u001b[0m\u001b[32m 2024 Playoff Leaders: PTS: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m635\u001b[0m\u001b[32m)\u001b[0m\u001b[32m TRB: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m208\u001b[0m\u001b[32m)\u001b[0m\u001b[32m AST: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m178\u001b[0m\u001b[32m)\u001b[0m\u001b[32m WS: Derrick White \u001b[0m\u001b[32m(\u001b[0m\u001b[32m2.9\u001b[0m\u001b[32m)\u001b[0m\u001b[32m More playoffs info\\\\\", \\\\\"score\\\\\": 0.9310187, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\\\\\", \\\\\"content\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates & Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\\\\\", \\\\\"score\\\\\": 0.8914433, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 Playoffs: West Finals | Timberwolves \u001b[0m\u001b[32m(\u001b[0m\u001b[32m3\u001b[0m\u001b[32m)\u001b[0m\u001b[32m vs. Mavericks \u001b[0m\u001b[32m(\u001b[0m\u001b[32m5\u001b[0m\u001b[32m)\u001b[0m\u001b[32m - NBA.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nba.com/playoffs/2024/west-final\\\\\", \\\\\"content\\\\\": \\\\\"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\\\\\", \\\\\"score\\\\\": 0.8884594, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"NBA Conference Finals Schedule: Full List of Games & Results\\\\\", \\\\\"url\\\\\": \\\\\"https://www.si.com/nba/nba-conference-finals-schedule-full-list-of-games-results\\\\\", \\\\\"content\\\\\": \\\\\"The 2024 NBA conference finals matchups are set. Here\\'s the schedule for all the games. ... Western Conference First Round \u001b[0m\u001b[32m(\u001b[0m\u001b[32m1\u001b[0m\u001b[32m)\u001b[0m\u001b[32m Oklahoma City Thunder def. \u001b[0m\u001b[32m(\u001b[0m\u001b[32m8\u001b[0m\u001b[32m)\u001b[0m\u001b[32m New Orleans Pelicans in 4 games\\\\\", \\\\\"score\\\\\": 0.85008353, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference playoff bracket - Basketnews.com\\\\\", \\\\\"url\\\\\": \\\\\"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\\\\\", \\\\\"content\\\\\": \\\\\"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\\\\\", \\\\\"score\\\\\": 0.8479807, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[1;39m]\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'output'\u001b[0m\u001b[39m: \u001b[0m\u001b[32m'content: The teams that played in the NBA Western Conference Finals of 2024 were the Dallas Mavericks and the Minnesota Timberwolves. tool_calls: \u001b[0m\u001b[32m[\u001b[0m\u001b[32m]\u001b[0m\u001b[32m'\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[1;39m}\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[1;39m{\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'input'\u001b[0m\u001b[39m: \u001b[0m\u001b[1;39m[\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"arguments\":\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"query\":\"NBA Western Conference Finals 2024 teams\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"tool\",\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"content\":\"\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"query\\\\\": \\\\\"NBA Western Conference Finals 2024 teams\\\\\", \\\\\"top_k\\\\\": \u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference Finals - Basketball-Reference.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\\\\\", \\\\\"content\\\\\": \\\\\"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown \u001b[0m\u001b[32m(\u001b[0m\u001b[32m20.8 / 5.4 / 5.0\u001b[0m\u001b[32m)\u001b[0m\u001b[32m 2024 Playoff Leaders: PTS: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m635\u001b[0m\u001b[32m)\u001b[0m\u001b[32m TRB: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m208\u001b[0m\u001b[32m)\u001b[0m\u001b[32m AST: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m178\u001b[0m\u001b[32m)\u001b[0m\u001b[32m WS: Derrick White \u001b[0m\u001b[32m(\u001b[0m\u001b[32m2.9\u001b[0m\u001b[32m)\u001b[0m\u001b[32m More playoffs info\\\\\", \\\\\"score\\\\\": 0.9310187, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\\\\\", \\\\\"content\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates & Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\\\\\", \\\\\"score\\\\\": 0.8914433, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 Playoffs: West Finals | Timberwolves \u001b[0m\u001b[32m(\u001b[0m\u001b[32m3\u001b[0m\u001b[32m)\u001b[0m\u001b[32m vs. Mavericks \u001b[0m\u001b[32m(\u001b[0m\u001b[32m5\u001b[0m\u001b[32m)\u001b[0m\u001b[32m - NBA.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nba.com/playoffs/2024/west-final\\\\\", \\\\\"content\\\\\": \\\\\"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\\\\\", \\\\\"score\\\\\": 0.8884594, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"NBA Conference Finals Schedule: Full List of Games & Results\\\\\", \\\\\"url\\\\\": \\\\\"https://www.si.com/nba/nba-conference-finals-schedule-full-list-of-games-results\\\\\", \\\\\"content\\\\\": \\\\\"The 2024 NBA conference finals matchups are set. Here\\'s the schedule for all the games. ... Western Conference First Round \u001b[0m\u001b[32m(\u001b[0m\u001b[32m1\u001b[0m\u001b[32m)\u001b[0m\u001b[32m Oklahoma City Thunder def. \u001b[0m\u001b[32m(\u001b[0m\u001b[32m8\u001b[0m\u001b[32m)\u001b[0m\u001b[32m New Orleans Pelicans in 4 games\\\\\", \\\\\"score\\\\\": 0.85008353, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference playoff bracket - Basketnews.com\\\\\", \\\\\"url\\\\\": \\\\\"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\\\\\", \\\\\"content\\\\\": \\\\\"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\\\\\", \\\\\"score\\\\\": 0.8479807, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"The teams that played in the NBA Western Conference Finals of 2024 were the Dallas Mavericks and the Minnesota Timberwolves.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"In which episode and season of South Park does Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mBSM-471\u001b[0m\u001b[32m)\u001b[0m\u001b[32m first appear? Give me the number and title.\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[1;39m]\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'output'\u001b[0m\u001b[39m: \u001b[0m\u001b[32m\"content:  tool_calls: \u001b[0m\u001b[32m[\u001b[0m\u001b[32mToolCall\u001b[0m\u001b[32m(\u001b[0m\u001b[32mcall_id\u001b[0m\u001b[32m='ebd7e906-3ec9-45de-a58e-6662d75eceb7', \u001b[0m\u001b[32mtool_name\u001b[0m\u001b[32m=<BuiltinTool.brave_search: 'brave_search'>, \u001b[0m\u001b[32marguments\u001b[0m\u001b[32m=\u001b[0m\u001b[32m{\u001b[0m\u001b[32m'query': 'Bill Cosby South Park episode'\u001b[0m\u001b[32m}\u001b[0m\u001b[32m)\u001b[0m\u001b[32m]\u001b[0m\u001b[32m\"\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[1;39m}\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[1;39m{\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'input'\u001b[0m\u001b[39m: \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"call_id\":\"ebd7e906-3ec9-45de-a58e-6662d75eceb7\",\"tool_name\":\"brave_search\",\"arguments\":\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"query\":\"Bill Cosby South Park episode\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'output'\u001b[0m\u001b[39m: \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"tool\",\"call_id\":\"ebd7e906-3ec9-45de-a58e-6662d75eceb7\",\"tool_name\":\"brave_search\",\"content\":\"\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"query\\\\\": \\\\\"Bill Cosby South Park episode\\\\\", \\\\\"top_k\\\\\": \u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Bill Cosby and Taylor Swift Duet - South Park Studios\\\\\", \\\\\"url\\\\\": \\\\\"https://www.southparkstudios.com/video-clips/90r7i1/south-park-bill-cosby-and-taylor-swift-duet\\\\\", \\\\\"content\\\\\": \\\\\"01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:03 Bill Cosby and Taylor Swift Duet South ParkS18 E10 ------------------------------------------------------- The holiday special continues with Bill Cosby and Taylor Swift\\'s rendition of \\\\\\\\\\\\\"It\\'s Snowing Out There\\\\\\\\\\\\\". 01:31 #WeBelieveInYou South ParkS18 E10 -------------------------------------- With everyone watching, Kyle takes the opportunity to reach out to his brother. 01:47 Watch Your Microaggressions, Bro South ParkS19 E1 ------------------------------------------------------ Cartman\\'s plan to frame PC Principal backfires. South ParkS19 E1 -------------------------------------- After hearing that the PC people have targeted Kyle, Cartman vows to help.\\\\\", \\\\\"score\\\\\": 0.685971, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Bill Cosby is Here to See You - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/video-clips/wfot8s/south-park-bill-cosby-is-here-to-see-you\\\\\", \\\\\"content\\\\\": \\\\\"01:56 It\\'s Not About Music South ParkS18 E9 ------------------------------------------ At home, Randy sees the consequences of Lorde\\'s performance and calls the Record Producer to try and fix it. 01:24 Lorde\\'s Hologram South ParkS18 E9 -------------------------------------- The Record Producer reveals the truth about the music industry... South ParkS18 E9 --------------------------------------------- Randy catches Sharon with Tupac\\'s hologram. 01:37 I\\'ve Got Your Son, Lorde South ParkS18 E10 ----------------------------------------------- The Record Producer takes Stan and Kyle hostage. 01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:21 Lorde Is My Dad South ParkS18 E10 -------------------------------------- After trying to confront Cartman Bra, Stan finally reveals the truth about his dad.\\\\\", \\\\\"score\\\\\": 0.6643884, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mandroid\u001b[0m\u001b[32m)\u001b[0m\u001b[32m | South Park Character ... - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/wiki/Bill_Cosby_\u001b[0m\u001b[32m(\u001b[0m\u001b[32mandroid\u001b[0m\u001b[32m)\u001b[0m\u001b[32m\\\\\", \\\\\"content\\\\\": \\\\\"Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mandroid\u001b[0m\u001b[32m)\u001b[0m\u001b[32m | South Park Character / Location / User talk etc | Official South Park Studios Wiki Sent back in time to destroy Eric Cartman\\'s Dawson\\'s Creek Trapper Keeper before it manifests into an omnipotent supercomputer that can destroy all humanity, \\\\\\\\\\\\\"Bill Cosby\\\\\\\\\\\\\" is really VSM471, an android or cyborg of some kind engineered by \\'hoomans\\' in the distant future. He fails in his initial missions to infiltrate South Park Elementary\\'s 4th Grade class, destroy the Trapper Keeper or Cartman himself, but with Stan Marsh and Kyle Broflovski\\'s aid, he is able to succeed in preventing his dismal future, and painfully fades from existence. South Park and all related titles, logos and characters are trademarks of Comedy Partners.\\\\\", \\\\\"score\\\\\": 0.5052006, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"\\'South Park\\' takes on Cosby, police, 2014 | CNN\\\\\", \\\\\"url\\\\\": \\\\\"https://www.cnn.com/2014/12/11/showbiz/tv/south-park-cosby-redskins-police/index.html\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\u2018South Park\\\\\\\\u2019 takes on Cosby, police, 2014 | CNN Watch Listen Live TV Subscribe Follow CNN Entertainment CNN Headlines CNN Shorts CNN10 CNN Max CNN TV Schedules CNN 5 Things CNN Underscored CNN Crossword About CNN CNN Profiles CNN Newsletters Work for CNN CNN \\\\\\\\u00a0\\\\\\\\u2014\\\\\\\\u00a0 \\\\\\\\u201cI think we take for granted how Trey Parker can jam a heap of current issues into a storyline thats a smart and funny #SouthPark episode,\\\\\\\\u201d wrote Brent Veale. \\\\\\\\u201cOh Lorde, CartmanBrah, dead celebrity holograms, murdering cops, this #SouthPark episode is certainly making #SaveTheLivingRoom happen,\\\\\\\\u201d added Brett Pender. CNN Headlines CNN10 CNN Max CNN TV Schedules CNN 5 Things CNN Underscored CNN Crossword About CNN CNN Profiles CNN Newsletters Work for CNN Follow CNN Entertainment\\\\\", \\\\\"score\\\\\": 0.45391592, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Trapper Keeper \u001b[0m\u001b[32m(\u001b[0m\u001b[32mSouth Park\u001b[0m\u001b[32m)\u001b[0m\u001b[32m - Wikipedia\\\\\", \\\\\"url\\\\\": \\\\\"https://en.wikipedia.org/wiki/Trapper_Keeper_\u001b[0m\u001b[32m(\u001b[0m\u001b[32mSouth_Park\u001b[0m\u001b[32m)\u001b[0m\u001b[32m\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" is the twelfth episode of the fourth season of the animated television series South Park, and the 60th episode of the series overall. In the episode, a man from the future wants Cartman\\'s new Trapper Keeper, while Mr. Garrison\\'s kindergarten class holds an election for class president with confusing results. It is one of the many South Park episodes that parodies a current event.\u001b[0m\u001b[32m[\u001b[0m\u001b[32m1\u001b[0m\u001b[32m]\u001b[0m\u001b[32m The main plot of the episode involving the Trapper Keeper was written before the election,\u001b[0m\u001b[32m[\u001b[0m\u001b[32m1\u001b[0m\u001b[32m]\u001b[0m\u001b[32m but the subplot is a parody of the controversy surrounding the election\\'s outcome.\u001b[0m\u001b[32m[\u001b[0m\u001b[32m2\u001b[0m\u001b[32m]\u001b[0m\u001b[32m \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" did not originally feature the election storyline, only a subplot about Ike attending his first day of kindergarten.\u001b[0m\u001b[32m[\u001b[0m\u001b[32m3\u001b[0m\u001b[32m]\u001b[0m\u001b[32m \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" Full episode at South Park Studios\\\\\", \\\\\"score\\\\\": 0.3839421, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[1;39m}\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[1;39m{\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'input'\u001b[0m\u001b[39m: \u001b[0m\u001b[1;39m[\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"arguments\":\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"query\":\"NBA Western Conference Finals 2024 teams\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"tool\",\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"content\":\"\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"query\\\\\": \\\\\"NBA Western Conference Finals 2024 teams\\\\\", \\\\\"top_k\\\\\": \u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference Finals - Basketball-Reference.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\\\\\", \\\\\"content\\\\\": \\\\\"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown \u001b[0m\u001b[32m(\u001b[0m\u001b[32m20.8 / 5.4 / 5.0\u001b[0m\u001b[32m)\u001b[0m\u001b[32m 2024 Playoff Leaders: PTS: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m635\u001b[0m\u001b[32m)\u001b[0m\u001b[32m TRB: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m208\u001b[0m\u001b[32m)\u001b[0m\u001b[32m AST: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m178\u001b[0m\u001b[32m)\u001b[0m\u001b[32m WS: Derrick White \u001b[0m\u001b[32m(\u001b[0m\u001b[32m2.9\u001b[0m\u001b[32m)\u001b[0m\u001b[32m More playoffs info\\\\\", \\\\\"score\\\\\": 0.9310187, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\\\\\", \\\\\"content\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates & Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\\\\\", \\\\\"score\\\\\": 0.8914433, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 Playoffs: West Finals | Timberwolves \u001b[0m\u001b[32m(\u001b[0m\u001b[32m3\u001b[0m\u001b[32m)\u001b[0m\u001b[32m vs. Mavericks \u001b[0m\u001b[32m(\u001b[0m\u001b[32m5\u001b[0m\u001b[32m)\u001b[0m\u001b[32m - NBA.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nba.com/playoffs/2024/west-final\\\\\", \\\\\"content\\\\\": \\\\\"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\\\\\", \\\\\"score\\\\\": 0.8884594, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"NBA Conference Finals Schedule: Full List of Games & Results\\\\\", \\\\\"url\\\\\": \\\\\"https://www.si.com/nba/nba-conference-finals-schedule-full-list-of-games-results\\\\\", \\\\\"content\\\\\": \\\\\"The 2024 NBA conference finals matchups are set. Here\\'s the schedule for all the games. ... Western Conference First Round \u001b[0m\u001b[32m(\u001b[0m\u001b[32m1\u001b[0m\u001b[32m)\u001b[0m\u001b[32m Oklahoma City Thunder def. \u001b[0m\u001b[32m(\u001b[0m\u001b[32m8\u001b[0m\u001b[32m)\u001b[0m\u001b[32m New Orleans Pelicans in 4 games\\\\\", \\\\\"score\\\\\": 0.85008353, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference playoff bracket - Basketnews.com\\\\\", \\\\\"url\\\\\": \\\\\"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\\\\\", \\\\\"content\\\\\": \\\\\"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\\\\\", \\\\\"score\\\\\": 0.8479807, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"The teams that played in the NBA Western Conference Finals of 2024 were the Dallas Mavericks and the Minnesota Timberwolves.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"In which episode and season of South Park does Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mBSM-471\u001b[0m\u001b[32m)\u001b[0m\u001b[32m first appear? Give me the number and title.\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"call_id\":\"ebd7e906-3ec9-45de-a58e-6662d75eceb7\",\"tool_name\":\"brave_search\",\"arguments\":\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"query\":\"Bill Cosby South Park episode\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"tool\",\"call_id\":\"ebd7e906-3ec9-45de-a58e-6662d75eceb7\",\"tool_name\":\"brave_search\",\"content\":\"\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"query\\\\\": \\\\\"Bill Cosby South Park episode\\\\\", \\\\\"top_k\\\\\": \u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Bill Cosby and Taylor Swift Duet - South Park Studios\\\\\", \\\\\"url\\\\\": \\\\\"https://www.southparkstudios.com/video-clips/90r7i1/south-park-bill-cosby-and-taylor-swift-duet\\\\\", \\\\\"content\\\\\": \\\\\"01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:03 Bill Cosby and Taylor Swift Duet South ParkS18 E10 ------------------------------------------------------- The holiday special continues with Bill Cosby and Taylor Swift\\'s rendition of \\\\\\\\\\\\\"It\\'s Snowing Out There\\\\\\\\\\\\\". 01:31 #WeBelieveInYou South ParkS18 E10 -------------------------------------- With everyone watching, Kyle takes the opportunity to reach out to his brother. 01:47 Watch Your Microaggressions, Bro South ParkS19 E1 ------------------------------------------------------ Cartman\\'s plan to frame PC Principal backfires. South ParkS19 E1 -------------------------------------- After hearing that the PC people have targeted Kyle, Cartman vows to help.\\\\\", \\\\\"score\\\\\": 0.685971, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Bill Cosby is Here to See You - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/video-clips/wfot8s/south-park-bill-cosby-is-here-to-see-you\\\\\", \\\\\"content\\\\\": \\\\\"01:56 It\\'s Not About Music South ParkS18 E9 ------------------------------------------ At home, Randy sees the consequences of Lorde\\'s performance and calls the Record Producer to try and fix it. 01:24 Lorde\\'s Hologram South ParkS18 E9 -------------------------------------- The Record Producer reveals the truth about the music industry... South ParkS18 E9 --------------------------------------------- Randy catches Sharon with Tupac\\'s hologram. 01:37 I\\'ve Got Your Son, Lorde South ParkS18 E10 ----------------------------------------------- The Record Producer takes Stan and Kyle hostage. 01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:21 Lorde Is My Dad South ParkS18 E10 -------------------------------------- After trying to confront Cartman Bra, Stan finally reveals the truth about his dad.\\\\\", \\\\\"score\\\\\": 0.6643884, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mandroid\u001b[0m\u001b[32m)\u001b[0m\u001b[32m | South Park Character ... - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/wiki/Bill_Cosby_\u001b[0m\u001b[32m(\u001b[0m\u001b[32mandroid\u001b[0m\u001b[32m)\u001b[0m\u001b[32m\\\\\", \\\\\"content\\\\\": \\\\\"Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mandroid\u001b[0m\u001b[32m)\u001b[0m\u001b[32m | South Park Character / Location / User talk etc | Official South Park Studios Wiki Sent back in time to destroy Eric Cartman\\'s Dawson\\'s Creek Trapper Keeper before it manifests into an omnipotent supercomputer that can destroy all humanity, \\\\\\\\\\\\\"Bill Cosby\\\\\\\\\\\\\" is really VSM471, an android or cyborg of some kind engineered by \\'hoomans\\' in the distant future. He fails in his initial missions to infiltrate South Park Elementary\\'s 4th Grade class, destroy the Trapper Keeper or Cartman himself, but with Stan Marsh and Kyle Broflovski\\'s aid, he is able to succeed in preventing his dismal future, and painfully fades from existence. South Park and all related titles, logos and characters are trademarks of Comedy Partners.\\\\\", \\\\\"score\\\\\": 0.5052006, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"\\'South Park\\' takes on Cosby, police, 2014 | CNN\\\\\", \\\\\"url\\\\\": \\\\\"https://www.cnn.com/2014/12/11/showbiz/tv/south-park-cosby-redskins-police/index.html\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\u2018South Park\\\\\\\\u2019 takes on Cosby, police, 2014 | CNN Watch Listen Live TV Subscribe Follow CNN Entertainment CNN Headlines CNN Shorts CNN10 CNN Max CNN TV Schedules CNN 5 Things CNN Underscored CNN Crossword About CNN CNN Profiles CNN Newsletters Work for CNN CNN \\\\\\\\u00a0\\\\\\\\u2014\\\\\\\\u00a0 \\\\\\\\u201cI think we take for granted how Trey Parker can jam a heap of current issues into a storyline thats a smart and funny #SouthPark episode,\\\\\\\\u201d wrote Brent Veale. \\\\\\\\u201cOh Lorde, CartmanBrah, dead celebrity holograms, murdering cops, this #SouthPark episode is certainly making #SaveTheLivingRoom happen,\\\\\\\\u201d added Brett Pender. CNN Headlines CNN10 CNN Max CNN TV Schedules CNN 5 Things CNN Underscored CNN Crossword About CNN CNN Profiles CNN Newsletters Work for CNN Follow CNN Entertainment\\\\\", \\\\\"score\\\\\": 0.45391592, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Trapper Keeper \u001b[0m\u001b[32m(\u001b[0m\u001b[32mSouth Park\u001b[0m\u001b[32m)\u001b[0m\u001b[32m - Wikipedia\\\\\", \\\\\"url\\\\\": \\\\\"https://en.wikipedia.org/wiki/Trapper_Keeper_\u001b[0m\u001b[32m(\u001b[0m\u001b[32mSouth_Park\u001b[0m\u001b[32m)\u001b[0m\u001b[32m\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" is the twelfth episode of the fourth season of the animated television series South Park, and the 60th episode of the series overall. In the episode, a man from the future wants Cartman\\'s new Trapper Keeper, while Mr. Garrison\\'s kindergarten class holds an election for class president with confusing results. It is one of the many South Park episodes that parodies a current event.\u001b[0m\u001b[32m[\u001b[0m\u001b[32m1\u001b[0m\u001b[32m]\u001b[0m\u001b[32m The main plot of the episode involving the Trapper Keeper was written before the election,\u001b[0m\u001b[32m[\u001b[0m\u001b[32m1\u001b[0m\u001b[32m]\u001b[0m\u001b[32m but the subplot is a parody of the controversy surrounding the election\\'s outcome.\u001b[0m\u001b[32m[\u001b[0m\u001b[32m2\u001b[0m\u001b[32m]\u001b[0m\u001b[32m \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" did not originally feature the election storyline, only a subplot about Ike attending his first day of kindergarten.\u001b[0m\u001b[32m[\u001b[0m\u001b[32m3\u001b[0m\u001b[32m]\u001b[0m\u001b[32m \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" Full episode at South Park Studios\\\\\", \\\\\"score\\\\\": 0.3839421, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[1;39m]\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'output'\u001b[0m\u001b[39m: \u001b[0m\u001b[32m'content: Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mBSM-471\u001b[0m\u001b[32m)\u001b[0m\u001b[32m first appears in Season 4, Episode 12 of South Park, titled \"Trapper Keeper\". tool_calls: \u001b[0m\u001b[32m[\u001b[0m\u001b[32m]\u001b[0m\u001b[32m'\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[1;39m}\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[1;39m{\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'input'\u001b[0m\u001b[39m: \u001b[0m\u001b[1;39m[\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"arguments\":\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"query\":\"NBA Western Conference Finals 2024 teams\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"tool\",\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"content\":\"\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"query\\\\\": \\\\\"NBA Western Conference Finals 2024 teams\\\\\", \\\\\"top_k\\\\\": \u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference Finals - Basketball-Reference.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\\\\\", \\\\\"content\\\\\": \\\\\"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown \u001b[0m\u001b[32m(\u001b[0m\u001b[32m20.8 / 5.4 / 5.0\u001b[0m\u001b[32m)\u001b[0m\u001b[32m 2024 Playoff Leaders: PTS: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m635\u001b[0m\u001b[32m)\u001b[0m\u001b[32m TRB: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m208\u001b[0m\u001b[32m)\u001b[0m\u001b[32m AST: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m178\u001b[0m\u001b[32m)\u001b[0m\u001b[32m WS: Derrick White \u001b[0m\u001b[32m(\u001b[0m\u001b[32m2.9\u001b[0m\u001b[32m)\u001b[0m\u001b[32m More playoffs info\\\\\", \\\\\"score\\\\\": 0.9310187, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\\\\\", \\\\\"content\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates & Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\\\\\", \\\\\"score\\\\\": 0.8914433, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 Playoffs: West Finals | Timberwolves \u001b[0m\u001b[32m(\u001b[0m\u001b[32m3\u001b[0m\u001b[32m)\u001b[0m\u001b[32m vs. Mavericks \u001b[0m\u001b[32m(\u001b[0m\u001b[32m5\u001b[0m\u001b[32m)\u001b[0m\u001b[32m - NBA.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nba.com/playoffs/2024/west-final\\\\\", \\\\\"content\\\\\": \\\\\"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\\\\\", \\\\\"score\\\\\": 0.8884594, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"NBA Conference Finals Schedule: Full List of Games & Results\\\\\", \\\\\"url\\\\\": \\\\\"https://www.si.com/nba/nba-conference-finals-schedule-full-list-of-games-results\\\\\", \\\\\"content\\\\\": \\\\\"The 2024 NBA conference finals matchups are set. Here\\'s the schedule for all the games. ... Western Conference First Round \u001b[0m\u001b[32m(\u001b[0m\u001b[32m1\u001b[0m\u001b[32m)\u001b[0m\u001b[32m Oklahoma City Thunder def. \u001b[0m\u001b[32m(\u001b[0m\u001b[32m8\u001b[0m\u001b[32m)\u001b[0m\u001b[32m New Orleans Pelicans in 4 games\\\\\", \\\\\"score\\\\\": 0.85008353, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference playoff bracket - Basketnews.com\\\\\", \\\\\"url\\\\\": \\\\\"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\\\\\", \\\\\"content\\\\\": \\\\\"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\\\\\", \\\\\"score\\\\\": 0.8479807, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"The teams that played in the NBA Western Conference Finals of 2024 were the Dallas Mavericks and the Minnesota Timberwolves.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"In which episode and season of South Park does Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mBSM-471\u001b[0m\u001b[32m)\u001b[0m\u001b[32m first appear? Give me the number and title.\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"call_id\":\"ebd7e906-3ec9-45de-a58e-6662d75eceb7\",\"tool_name\":\"brave_search\",\"arguments\":\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"query\":\"Bill Cosby South Park episode\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"tool\",\"call_id\":\"ebd7e906-3ec9-45de-a58e-6662d75eceb7\",\"tool_name\":\"brave_search\",\"content\":\"\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"query\\\\\": \\\\\"Bill Cosby South Park episode\\\\\", \\\\\"top_k\\\\\": \u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Bill Cosby and Taylor Swift Duet - South Park Studios\\\\\", \\\\\"url\\\\\": \\\\\"https://www.southparkstudios.com/video-clips/90r7i1/south-park-bill-cosby-and-taylor-swift-duet\\\\\", \\\\\"content\\\\\": \\\\\"01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:03 Bill Cosby and Taylor Swift Duet South ParkS18 E10 ------------------------------------------------------- The holiday special continues with Bill Cosby and Taylor Swift\\'s rendition of \\\\\\\\\\\\\"It\\'s Snowing Out There\\\\\\\\\\\\\". 01:31 #WeBelieveInYou South ParkS18 E10 -------------------------------------- With everyone watching, Kyle takes the opportunity to reach out to his brother. 01:47 Watch Your Microaggressions, Bro South ParkS19 E1 ------------------------------------------------------ Cartman\\'s plan to frame PC Principal backfires. South ParkS19 E1 -------------------------------------- After hearing that the PC people have targeted Kyle, Cartman vows to help.\\\\\", \\\\\"score\\\\\": 0.685971, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Bill Cosby is Here to See You - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/video-clips/wfot8s/south-park-bill-cosby-is-here-to-see-you\\\\\", \\\\\"content\\\\\": \\\\\"01:56 It\\'s Not About Music South ParkS18 E9 ------------------------------------------ At home, Randy sees the consequences of Lorde\\'s performance and calls the Record Producer to try and fix it. 01:24 Lorde\\'s Hologram South ParkS18 E9 -------------------------------------- The Record Producer reveals the truth about the music industry... South ParkS18 E9 --------------------------------------------- Randy catches Sharon with Tupac\\'s hologram. 01:37 I\\'ve Got Your Son, Lorde South ParkS18 E10 ----------------------------------------------- The Record Producer takes Stan and Kyle hostage. 01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:21 Lorde Is My Dad South ParkS18 E10 -------------------------------------- After trying to confront Cartman Bra, Stan finally reveals the truth about his dad.\\\\\", \\\\\"score\\\\\": 0.6643884, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mandroid\u001b[0m\u001b[32m)\u001b[0m\u001b[32m | South Park Character ... - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/wiki/Bill_Cosby_\u001b[0m\u001b[32m(\u001b[0m\u001b[32mandroid\u001b[0m\u001b[32m)\u001b[0m\u001b[32m\\\\\", \\\\\"content\\\\\": \\\\\"Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mandroid\u001b[0m\u001b[32m)\u001b[0m\u001b[32m | South Park Character / Location / User talk etc | Official South Park Studios Wiki Sent back in time to destroy Eric Cartman\\'s Dawson\\'s Creek Trapper Keeper before it manifests into an omnipotent supercomputer that can destroy all humanity, \\\\\\\\\\\\\"Bill Cosby\\\\\\\\\\\\\" is really VSM471, an android or cyborg of some kind engineered by \\'hoomans\\' in the distant future. He fails in his initial missions to infiltrate South Park Elementary\\'s 4th Grade class, destroy the Trapper Keeper or Cartman himself, but with Stan Marsh and Kyle Broflovski\\'s aid, he is able to succeed in preventing his dismal future, and painfully fades from existence. South Park and all related titles, logos and characters are trademarks of Comedy Partners.\\\\\", \\\\\"score\\\\\": 0.5052006, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"\\'South Park\\' takes on Cosby, police, 2014 | CNN\\\\\", \\\\\"url\\\\\": \\\\\"https://www.cnn.com/2014/12/11/showbiz/tv/south-park-cosby-redskins-police/index.html\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\u2018South Park\\\\\\\\u2019 takes on Cosby, police, 2014 | CNN Watch Listen Live TV Subscribe Follow CNN Entertainment CNN Headlines CNN Shorts CNN10 CNN Max CNN TV Schedules CNN 5 Things CNN Underscored CNN Crossword About CNN CNN Profiles CNN Newsletters Work for CNN CNN \\\\\\\\u00a0\\\\\\\\u2014\\\\\\\\u00a0 \\\\\\\\u201cI think we take for granted how Trey Parker can jam a heap of current issues into a storyline thats a smart and funny #SouthPark episode,\\\\\\\\u201d wrote Brent Veale. \\\\\\\\u201cOh Lorde, CartmanBrah, dead celebrity holograms, murdering cops, this #SouthPark episode is certainly making #SaveTheLivingRoom happen,\\\\\\\\u201d added Brett Pender. CNN Headlines CNN10 CNN Max CNN TV Schedules CNN 5 Things CNN Underscored CNN Crossword About CNN CNN Profiles CNN Newsletters Work for CNN Follow CNN Entertainment\\\\\", \\\\\"score\\\\\": 0.45391592, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Trapper Keeper \u001b[0m\u001b[32m(\u001b[0m\u001b[32mSouth Park\u001b[0m\u001b[32m)\u001b[0m\u001b[32m - Wikipedia\\\\\", \\\\\"url\\\\\": \\\\\"https://en.wikipedia.org/wiki/Trapper_Keeper_\u001b[0m\u001b[32m(\u001b[0m\u001b[32mSouth_Park\u001b[0m\u001b[32m)\u001b[0m\u001b[32m\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" is the twelfth episode of the fourth season of the animated television series South Park, and the 60th episode of the series overall. In the episode, a man from the future wants Cartman\\'s new Trapper Keeper, while Mr. Garrison\\'s kindergarten class holds an election for class president with confusing results. It is one of the many South Park episodes that parodies a current event.\u001b[0m\u001b[32m[\u001b[0m\u001b[32m1\u001b[0m\u001b[32m]\u001b[0m\u001b[32m The main plot of the episode involving the Trapper Keeper was written before the election,\u001b[0m\u001b[32m[\u001b[0m\u001b[32m1\u001b[0m\u001b[32m]\u001b[0m\u001b[32m but the subplot is a parody of the controversy surrounding the election\\'s outcome.\u001b[0m\u001b[32m[\u001b[0m\u001b[32m2\u001b[0m\u001b[32m]\u001b[0m\u001b[32m \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" did not originally feature the election storyline, only a subplot about Ike attending his first day of kindergarten.\u001b[0m\u001b[32m[\u001b[0m\u001b[32m3\u001b[0m\u001b[32m]\u001b[0m\u001b[32m \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" Full episode at South Park Studios\\\\\", \\\\\"score\\\\\": 0.3839421, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mBSM-471\u001b[0m\u001b[32m)\u001b[0m\u001b[32m first appears in Season 4, Episode 12 of South Park, titled \\\\\"Trapper Keeper\\\\\".\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"What is the British-American kickboxer Andrew Tate\\'s kickboxing name?\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[1;39m]\u001b[0m\u001b[39m,\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'output'\u001b[0m\u001b[39m: \u001b[0m\u001b[32m\"content:  tool_calls: \u001b[0m\u001b[32m[\u001b[0m\u001b[32mToolCall\u001b[0m\u001b[32m(\u001b[0m\u001b[32mcall_id\u001b[0m\u001b[32m='e26ecfb2-434c-479f-95dc-7b3b4929665a', \u001b[0m\u001b[32mtool_name\u001b[0m\u001b[32m=<BuiltinTool.brave_search: 'brave_search'\u001b[0m\u001b[32m>\u001b[0m\u001b[32m, \u001b[0m\u001b[32marguments\u001b[0m\u001b[32m=\u001b[0m\u001b[32m{\u001b[0m\u001b[32m'query': 'Andrew Tate kickboxing name'\u001b[0m\u001b[32m}\u001b[0m\u001b[32m)\u001b[0m\u001b[32m]\u001b[0m\u001b[32m\"\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[1m}\u001b[0m,\n",
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-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'input'\u001b[0m: \u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"call_id\":\"e26ecfb2-434c-479f-95dc-7b3b4929665a\",\"tool_name\":\"brave_search\",\"arguments\":\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"query\":\"Andrew Tate kickboxing name\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'output'\u001b[0m: \u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"tool\",\"call_id\":\"e26ecfb2-434c-479f-95dc-7b3b4929665a\",\"tool_name\":\"brave_search\",\"content\":\"\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"query\\\\\": \\\\\"Andrew Tate kickboxing name\\\\\", \\\\\"top_k\\\\\": \u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"50 Facts About Andrew Tate - Facts.net\\\\\", \\\\\"url\\\\\": \\\\\"https://facts.net/andrew-tate-facts/\\\\\", \\\\\"content\\\\\": \\\\\"Full Name: Andrew Tate\\'s full name is Emory Andrew Tate III, named after his father, a celebrated chess player. Date of Birth: ... Kickboxing Start: Tate began his kickboxing career in 2005, starting his journey as a professional fighter, which would later be a significant part of his persona. First Championship:\\\\\", \\\\\"score\\\\\": 0.8967681, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"The Life Of Andrew Tate \u001b[0m\u001b[32m(\u001b[0m\u001b[32mBy Andrew Tate Himself\u001b[0m\u001b[32m)\u001b[0m\u001b[32m\\\\\", \\\\\"url\\\\\": \\\\\"https://sidekickboxing.co.uk/the-life-of-andrew-king-cobra-tate/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate stats. Fight Name: Cobra Tate. Born: 1 December 1986. Weight: 90 KG. Weight Class: Cruiserweight. Height: 1.92m. Fight Record: Wins - 76, Losses - 9. ... Andrew Tate\\'s Kickboxing Career. Andrew Tate has always fought credible opponents right from the beginning of his kickboxing career. One of his first professional fights on\\\\\", \\\\\"score\\\\\": 0.8795718, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Andrew Tate kickboxing record: How many championships ... - FirstSportz\\\\\", \\\\\"url\\\\\": \\\\\"https://firstsportz.com/mma-how-many-championships-does-andrew-tate-have/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate\\'s Kickboxing career. During his kickboxing career, he used the nickname \\\\\\\\\\\\\"King Cobra,\\\\\\\\\\\\\" which he currently uses as his Twitter name. Tate had an unorthodox style of movement inside the ring. He kept his hands down most of the time and relied on quick jabs and an overhand right to land significant strikes.\\\\\", \\\\\"score\\\\\": 0.8752871, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Andrew Tate: Kickboxing Record, Facts, Height, Weight, Age, Biography\\\\\", \\\\\"url\\\\\": \\\\\"https://www.lowkickmma.com/andrew-tate-kickboxing-record-facts-height-weight-age-biography/\\\\\", \\\\\"content\\\\\": \\\\\"Birth Name: Emory Andrew Tate III: Date of Birth: 1 December 1986: Place of Birth: Washington, D.C., U.S. ... In his professional kickboxing career, Andrew Tate won 32 of his fights by knockout.\\\\\", \\\\\"score\\\\\": 0.7992077, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"About Andrew Tate: A Journey from Champion to Controversy\\\\\", \\\\\"url\\\\\": \\\\\"https://reachmorpheus.com/andrew-tate/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate\\'s kickboxing career, beginning in 2005, is a tale of determination and skill. He quickly made a name for himself in the sport, rising through the ranks with his unique fighting style and strategic approach, honed by his chess-playing background.\\\\\", \\\\\"score\\\\\": 0.6490677, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[1m}\u001b[0m,\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[1m{\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'input'\u001b[0m: \u001b[1m[\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"arguments\":\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"query\":\"NBA Western Conference Finals 2024 teams\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"tool\",\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"content\":\"\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"query\\\\\": \\\\\"NBA Western Conference Finals 2024 teams\\\\\", \\\\\"top_k\\\\\": \u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference Finals - Basketball-Reference.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\\\\\", \\\\\"content\\\\\": \\\\\"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown \u001b[0m\u001b[32m(\u001b[0m\u001b[32m20.8 / 5.4 / 5.0\u001b[0m\u001b[32m)\u001b[0m\u001b[32m 2024 Playoff Leaders: PTS: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m635\u001b[0m\u001b[32m)\u001b[0m\u001b[32m TRB: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m208\u001b[0m\u001b[32m)\u001b[0m\u001b[32m AST: Luka Don\\\\\\\\u010di\\\\\\\\u0107 \u001b[0m\u001b[32m(\u001b[0m\u001b[32m178\u001b[0m\u001b[32m)\u001b[0m\u001b[32m WS: Derrick White \u001b[0m\u001b[32m(\u001b[0m\u001b[32m2.9\u001b[0m\u001b[32m)\u001b[0m\u001b[32m More playoffs info\\\\\", \\\\\"score\\\\\": 0.9310187, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\\\\\", \\\\\"content\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates & Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\\\\\", \\\\\"score\\\\\": 0.8914433, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 Playoffs: West Finals | Timberwolves \u001b[0m\u001b[32m(\u001b[0m\u001b[32m3\u001b[0m\u001b[32m)\u001b[0m\u001b[32m vs. Mavericks \u001b[0m\u001b[32m(\u001b[0m\u001b[32m5\u001b[0m\u001b[32m)\u001b[0m\u001b[32m - NBA.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nba.com/playoffs/2024/west-final\\\\\", \\\\\"content\\\\\": \\\\\"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\\\\\", \\\\\"score\\\\\": 0.8884594, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"NBA Conference Finals Schedule: Full List of Games & Results\\\\\", \\\\\"url\\\\\": \\\\\"https://www.si.com/nba/nba-conference-finals-schedule-full-list-of-games-results\\\\\", \\\\\"content\\\\\": \\\\\"The 2024 NBA conference finals matchups are set. Here\\'s the schedule for all the games. ... Western Conference First Round \u001b[0m\u001b[32m(\u001b[0m\u001b[32m1\u001b[0m\u001b[32m)\u001b[0m\u001b[32m Oklahoma City Thunder def. \u001b[0m\u001b[32m(\u001b[0m\u001b[32m8\u001b[0m\u001b[32m)\u001b[0m\u001b[32m New Orleans Pelicans in 4 games\\\\\", \\\\\"score\\\\\": 0.85008353, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference playoff bracket - Basketnews.com\\\\\", \\\\\"url\\\\\": \\\\\"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\\\\\", \\\\\"content\\\\\": \\\\\"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\\\\\", \\\\\"score\\\\\": 0.8479807, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"The teams that played in the NBA Western Conference Finals of 2024 were the Dallas Mavericks and the Minnesota Timberwolves.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"In which episode and season of South Park does Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mBSM-471\u001b[0m\u001b[32m)\u001b[0m\u001b[32m first appear? Give me the number and title.\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"call_id\":\"ebd7e906-3ec9-45de-a58e-6662d75eceb7\",\"tool_name\":\"brave_search\",\"arguments\":\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"query\":\"Bill Cosby South Park episode\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"tool\",\"call_id\":\"ebd7e906-3ec9-45de-a58e-6662d75eceb7\",\"tool_name\":\"brave_search\",\"content\":\"\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"query\\\\\": \\\\\"Bill Cosby South Park episode\\\\\", \\\\\"top_k\\\\\": \u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Bill Cosby and Taylor Swift Duet - South Park Studios\\\\\", \\\\\"url\\\\\": \\\\\"https://www.southparkstudios.com/video-clips/90r7i1/south-park-bill-cosby-and-taylor-swift-duet\\\\\", \\\\\"content\\\\\": \\\\\"01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:03 Bill Cosby and Taylor Swift Duet South ParkS18 E10 ------------------------------------------------------- The holiday special continues with Bill Cosby and Taylor Swift\\'s rendition of \\\\\\\\\\\\\"It\\'s Snowing Out There\\\\\\\\\\\\\". 01:31 #WeBelieveInYou South ParkS18 E10 -------------------------------------- With everyone watching, Kyle takes the opportunity to reach out to his brother. 01:47 Watch Your Microaggressions, Bro South ParkS19 E1 ------------------------------------------------------ Cartman\\'s plan to frame PC Principal backfires. South ParkS19 E1 -------------------------------------- After hearing that the PC people have targeted Kyle, Cartman vows to help.\\\\\", \\\\\"score\\\\\": 0.685971, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Bill Cosby is Here to See You - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/video-clips/wfot8s/south-park-bill-cosby-is-here-to-see-you\\\\\", \\\\\"content\\\\\": \\\\\"01:56 It\\'s Not About Music South ParkS18 E9 ------------------------------------------ At home, Randy sees the consequences of Lorde\\'s performance and calls the Record Producer to try and fix it. 01:24 Lorde\\'s Hologram South ParkS18 E9 -------------------------------------- The Record Producer reveals the truth about the music industry... South ParkS18 E9 --------------------------------------------- Randy catches Sharon with Tupac\\'s hologram. 01:37 I\\'ve Got Your Son, Lorde South ParkS18 E10 ----------------------------------------------- The Record Producer takes Stan and Kyle hostage. 01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:21 Lorde Is My Dad South ParkS18 E10 -------------------------------------- After trying to confront Cartman Bra, Stan finally reveals the truth about his dad.\\\\\", \\\\\"score\\\\\": 0.6643884, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mandroid\u001b[0m\u001b[32m)\u001b[0m\u001b[32m | South Park Character ... - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/wiki/Bill_Cosby_\u001b[0m\u001b[32m(\u001b[0m\u001b[32mandroid\u001b[0m\u001b[32m)\u001b[0m\u001b[32m\\\\\", \\\\\"content\\\\\": \\\\\"Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mandroid\u001b[0m\u001b[32m)\u001b[0m\u001b[32m | South Park Character / Location / User talk etc | Official South Park Studios Wiki Sent back in time to destroy Eric Cartman\\'s Dawson\\'s Creek Trapper Keeper before it manifests into an omnipotent supercomputer that can destroy all humanity, \\\\\\\\\\\\\"Bill Cosby\\\\\\\\\\\\\" is really VSM471, an android or cyborg of some kind engineered by \\'hoomans\\' in the distant future. He fails in his initial missions to infiltrate South Park Elementary\\'s 4th Grade class, destroy the Trapper Keeper or Cartman himself, but with Stan Marsh and Kyle Broflovski\\'s aid, he is able to succeed in preventing his dismal future, and painfully fades from existence. South Park and all related titles, logos and characters are trademarks of Comedy Partners.\\\\\", \\\\\"score\\\\\": 0.5052006, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"\\'South Park\\' takes on Cosby, police, 2014 | CNN\\\\\", \\\\\"url\\\\\": \\\\\"https://www.cnn.com/2014/12/11/showbiz/tv/south-park-cosby-redskins-police/index.html\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\u2018South Park\\\\\\\\u2019 takes on Cosby, police, 2014 | CNN Watch Listen Live TV Subscribe Follow CNN Entertainment CNN Headlines CNN Shorts CNN10 CNN Max CNN TV Schedules CNN 5 Things CNN Underscored CNN Crossword About CNN CNN Profiles CNN Newsletters Work for CNN CNN \\\\\\\\u00a0\\\\\\\\u2014\\\\\\\\u00a0 \\\\\\\\u201cI think we take for granted how Trey Parker can jam a heap of current issues into a storyline thats a smart and funny #SouthPark episode,\\\\\\\\u201d wrote Brent Veale. \\\\\\\\u201cOh Lorde, CartmanBrah, dead celebrity holograms, murdering cops, this #SouthPark episode is certainly making #SaveTheLivingRoom happen,\\\\\\\\u201d added Brett Pender. CNN Headlines CNN10 CNN Max CNN TV Schedules CNN 5 Things CNN Underscored CNN Crossword About CNN CNN Profiles CNN Newsletters Work for CNN Follow CNN Entertainment\\\\\", \\\\\"score\\\\\": 0.45391592, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Trapper Keeper \u001b[0m\u001b[32m(\u001b[0m\u001b[32mSouth Park\u001b[0m\u001b[32m)\u001b[0m\u001b[32m - Wikipedia\\\\\", \\\\\"url\\\\\": \\\\\"https://en.wikipedia.org/wiki/Trapper_Keeper_\u001b[0m\u001b[32m(\u001b[0m\u001b[32mSouth_Park\u001b[0m\u001b[32m)\u001b[0m\u001b[32m\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" is the twelfth episode of the fourth season of the animated television series South Park, and the 60th episode of the series overall. In the episode, a man from the future wants Cartman\\'s new Trapper Keeper, while Mr. Garrison\\'s kindergarten class holds an election for class president with confusing results. It is one of the many South Park episodes that parodies a current event.\u001b[0m\u001b[32m[\u001b[0m\u001b[32m1\u001b[0m\u001b[32m]\u001b[0m\u001b[32m The main plot of the episode involving the Trapper Keeper was written before the election,\u001b[0m\u001b[32m[\u001b[0m\u001b[32m1\u001b[0m\u001b[32m]\u001b[0m\u001b[32m but the subplot is a parody of the controversy surrounding the election\\'s outcome.\u001b[0m\u001b[32m[\u001b[0m\u001b[32m2\u001b[0m\u001b[32m]\u001b[0m\u001b[32m \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" did not originally feature the election storyline, only a subplot about Ike attending his first day of kindergarten.\u001b[0m\u001b[32m[\u001b[0m\u001b[32m3\u001b[0m\u001b[32m]\u001b[0m\u001b[32m \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" Full episode at South Park Studios\\\\\", \\\\\"score\\\\\": 0.3839421, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"Bill Cosby \u001b[0m\u001b[32m(\u001b[0m\u001b[32mBSM-471\u001b[0m\u001b[32m)\u001b[0m\u001b[32m first appears in Season 4, Episode 12 of South Park, titled \\\\\"Trapper Keeper\\\\\".\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"user\",\"content\":\"What is the British-American kickboxer Andrew Tate\\'s kickboxing name?\",\"context\":null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":\u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"call_id\":\"e26ecfb2-434c-479f-95dc-7b3b4929665a\",\"tool_name\":\"brave_search\",\"arguments\":\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"query\":\"Andrew Tate kickboxing name\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m,\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\"role\":\"tool\",\"call_id\":\"e26ecfb2-434c-479f-95dc-7b3b4929665a\",\"tool_name\":\"brave_search\",\"content\":\"\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"query\\\\\": \\\\\"Andrew Tate kickboxing name\\\\\", \\\\\"top_k\\\\\": \u001b[0m\u001b[32m[\u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"50 Facts About Andrew Tate - Facts.net\\\\\", \\\\\"url\\\\\": \\\\\"https://facts.net/andrew-tate-facts/\\\\\", \\\\\"content\\\\\": \\\\\"Full Name: Andrew Tate\\'s full name is Emory Andrew Tate III, named after his father, a celebrated chess player. Date of Birth: ... Kickboxing Start: Tate began his kickboxing career in 2005, starting his journey as a professional fighter, which would later be a significant part of his persona. First Championship:\\\\\", \\\\\"score\\\\\": 0.8967681, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"The Life Of Andrew Tate \u001b[0m\u001b[32m(\u001b[0m\u001b[32mBy Andrew Tate Himself\u001b[0m\u001b[32m)\u001b[0m\u001b[32m\\\\\", \\\\\"url\\\\\": \\\\\"https://sidekickboxing.co.uk/the-life-of-andrew-king-cobra-tate/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate stats. Fight Name: Cobra Tate. Born: 1 December 1986. Weight: 90 KG. Weight Class: Cruiserweight. Height: 1.92m. Fight Record: Wins - 76, Losses - 9. ... Andrew Tate\\'s Kickboxing Career. Andrew Tate has always fought credible opponents right from the beginning of his kickboxing career. One of his first professional fights on\\\\\", \\\\\"score\\\\\": 0.8795718, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Andrew Tate kickboxing record: How many championships ... - FirstSportz\\\\\", \\\\\"url\\\\\": \\\\\"https://firstsportz.com/mma-how-many-championships-does-andrew-tate-have/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate\\'s Kickboxing career. During his kickboxing career, he used the nickname \\\\\\\\\\\\\"King Cobra,\\\\\\\\\\\\\" which he currently uses as his Twitter name. Tate had an unorthodox style of movement inside the ring. He kept his hands down most of the time and relied on quick jabs and an overhand right to land significant strikes.\\\\\", \\\\\"score\\\\\": 0.8752871, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"Andrew Tate: Kickboxing Record, Facts, Height, Weight, Age, Biography\\\\\", \\\\\"url\\\\\": \\\\\"https://www.lowkickmma.com/andrew-tate-kickboxing-record-facts-height-weight-age-biography/\\\\\", \\\\\"content\\\\\": \\\\\"Birth Name: Emory Andrew Tate III: Date of Birth: 1 December 1986: Place of Birth: Washington, D.C., U.S. ... In his professional kickboxing career, Andrew Tate won 32 of his fights by knockout.\\\\\", \\\\\"score\\\\\": 0.7992077, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m, \u001b[0m\u001b[32m{\u001b[0m\u001b[32m\\\\\"title\\\\\": \\\\\"About Andrew Tate: A Journey from Champion to Controversy\\\\\", \\\\\"url\\\\\": \\\\\"https://reachmorpheus.com/andrew-tate/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate\\'s kickboxing career, beginning in 2005, is a tale of determination and skill. He quickly made a name for himself in the sport, rising through the ranks with his unique fighting style and strategic approach, honed by his chess-playing background.\\\\\", \\\\\"score\\\\\": 0.6490677, \\\\\"raw_content\\\\\": null\u001b[0m\u001b[32m}\u001b[0m\u001b[32m]\u001b[0m\u001b[32m}\u001b[0m\u001b[32m\"\u001b[0m\u001b[32m}\u001b[0m\u001b[32m'\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[1m]\u001b[0m,\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'output'\u001b[0m: \u001b[32m'content: Andrew Tate\\'s kickboxing name is \"Cobra Tate\" or \"King Cobra\". tool_calls: \u001b[0m\u001b[32m[\u001b[0m\u001b[32m]\u001b[0m\u001b[32m'\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[1m}\u001b[0m\n",
-              "\u001b[1m]\u001b[0m\n"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        }
-      ],
-      "source": [
-        "print(f\"Getting traces for session_id={session_id}\")\n",
-        "import json\n",
-        "\n",
-        "from rich.pretty import pprint\n",
-        "\n",
-        "agent_logs = []\n",
-        "\n",
-        "for span in client.telemetry.query_spans(\n",
-        "    attribute_filters=[\n",
-        "        {\"key\": \"session_id\", \"op\": \"eq\", \"value\": session_id},\n",
-        "    ],\n",
-        "    attributes_to_return=[\"input\", \"output\"],\n",
-        "):\n",
-        "    if span.attributes[\"output\"] != \"no shields\":\n",
-        "        agent_logs.append(span.attributes)\n",
-        "\n",
-        "pprint(agent_logs)\n"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "QF30H7ufP2RE",
-      "metadata": {
-        "id": "QF30H7ufP2RE"
-      },
-      "source": [
-        "##### 3.1.3 Post-Process Telemetry Results & Evaluate\n",
-        "\n",
-        "- Now, we want to run evaluation to assert that our search agent succesfully calls brave_search from online traces.\n",
-        "- We will first post-process the agent's telemetry logs and run evaluation."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 19,
-      "id": "sy4Xaff_Avuu",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 432
-        },
-        "id": "sy4Xaff_Avuu",
-        "outputId": "1b14b5ed-4c77-47c4-edfb-1c13a88e5ef4"
-      },
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "{'input': ['{\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"}', '{\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null}'], 'output': \"content:  tool_calls: [ToolCall(call_id='838a3846-0bc4-488e-9e42-65a48e29b80a', tool_name=<BuiltinTool.brave_search: 'brave_search'>, arguments={'query': 'NBA Western Conference Finals 2024 teams'})]\"}\n",
-            "{'input': '{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"NBA Western Conference Finals 2024 teams\"}}]}', 'output': '{\"role\":\"tool\",\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"NBA Western Conference Finals 2024 teams\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference Finals - Basketball-Reference.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\\\\\", \\\\\"content\\\\\": \\\\\"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown (20.8 / 5.4 / 5.0) 2024 Playoff Leaders: PTS: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (635) TRB: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (208) AST: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (178) WS: Derrick White (2.9) More playoffs info\\\\\", \\\\\"score\\\\\": 0.9310187, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\\\\\", \\\\\"content\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates & Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\\\\\", \\\\\"score\\\\\": 0.8914433, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 Playoffs: West Finals | Timberwolves (3) vs. Mavericks (5) - NBA.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nba.com/playoffs/2024/west-final\\\\\", \\\\\"content\\\\\": \\\\\"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\\\\\", \\\\\"score\\\\\": 0.8884594, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Conference Finals Schedule: Full List of Games & Results\\\\\", \\\\\"url\\\\\": \\\\\"https://www.si.com/nba/nba-conference-finals-schedule-full-list-of-games-results\\\\\", \\\\\"content\\\\\": \\\\\"The 2024 NBA conference finals matchups are set. Here\\'s the schedule for all the games. ... Western Conference First Round (1) Oklahoma City Thunder def. (8) New Orleans Pelicans in 4 games\\\\\", \\\\\"score\\\\\": 0.85008353, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference playoff bracket - Basketnews.com\\\\\", \\\\\"url\\\\\": \\\\\"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\\\\\", \\\\\"content\\\\\": \\\\\"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\\\\\", \\\\\"score\\\\\": 0.8479807, \\\\\"raw_content\\\\\": null}]}\"}'}\n",
-            "{'input': ['{\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"}', '{\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null}', '{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"NBA Western Conference Finals 2024 teams\"}}]}', '{\"role\":\"tool\",\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"NBA Western Conference Finals 2024 teams\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference Finals - Basketball-Reference.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\\\\\", \\\\\"content\\\\\": \\\\\"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown (20.8 / 5.4 / 5.0) 2024 Playoff Leaders: PTS: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (635) TRB: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (208) AST: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (178) WS: Derrick White (2.9) More playoffs info\\\\\", \\\\\"score\\\\\": 0.9310187, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\\\\\", \\\\\"content\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates & Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\\\\\", \\\\\"score\\\\\": 0.8914433, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 Playoffs: West Finals | Timberwolves (3) vs. Mavericks (5) - NBA.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nba.com/playoffs/2024/west-final\\\\\", \\\\\"content\\\\\": \\\\\"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\\\\\", \\\\\"score\\\\\": 0.8884594, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Conference Finals Schedule: Full List of Games & Results\\\\\", \\\\\"url\\\\\": \\\\\"https://www.si.com/nba/nba-conference-finals-schedule-full-list-of-games-results\\\\\", \\\\\"content\\\\\": \\\\\"The 2024 NBA conference finals matchups are set. Here\\'s the schedule for all the games. ... Western Conference First Round (1) Oklahoma City Thunder def. (8) New Orleans Pelicans in 4 games\\\\\", \\\\\"score\\\\\": 0.85008353, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference playoff bracket - Basketnews.com\\\\\", \\\\\"url\\\\\": \\\\\"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\\\\\", \\\\\"content\\\\\": \\\\\"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\\\\\", \\\\\"score\\\\\": 0.8479807, \\\\\"raw_content\\\\\": null}]}\"}'], 'output': 'content: The teams that played in the NBA Western Conference Finals of 2024 were the Dallas Mavericks and the Minnesota Timberwolves. tool_calls: []'}\n",
-            "{'input': ['{\"role\":\"system\",\"content\":\"You are a helpful assistant. Use search tool to answer the questions. \"}', '{\"role\":\"user\",\"content\":\"Which teams played in the NBA western conference finals of 2024\",\"context\":null}', '{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"NBA Western Conference Finals 2024 teams\"}}]}', '{\"role\":\"tool\",\"call_id\":\"838a3846-0bc4-488e-9e42-65a48e29b80a\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"NBA Western Conference Finals 2024 teams\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference Finals - Basketball-Reference.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.basketball-reference.com/playoffs/2024-nba-western-conference-finals-mavericks-vs-timberwolves.html\\\\\", \\\\\"content\\\\\": \\\\\"2024 NBA Western Conference Finals Mavericks vs. Timberwolves League Champion: Boston Celtics. Finals MVP: Jaylen Brown (20.8 / 5.4 / 5.0) 2024 Playoff Leaders: PTS: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (635) TRB: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (208) AST: Luka Don\\\\\\\\u010di\\\\\\\\u0107 (178) WS: Derrick White (2.9) More playoffs info\\\\\", \\\\\"score\\\\\": 0.9310187, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates, schedule and more - Sportskeeda\\\\\", \\\\\"url\\\\\": \\\\\"https://www.sportskeeda.com/basketball/news-nba-western-conference-finals-2024-dates-schedule-and-more\\\\\", \\\\\"content\\\\\": \\\\\"NBA Western Conference Finals 2024: Dates & Schedule The 2023-24 NBA Western Conference Finals will start on Wednesday, May 22. The Mavericks will face the team that wins in Game 7 between the\\\\\", \\\\\"score\\\\\": 0.8914433, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 Playoffs: West Finals | Timberwolves (3) vs. Mavericks (5) - NBA.com\\\\\", \\\\\"url\\\\\": \\\\\"https://www.nba.com/playoffs/2024/west-final\\\\\", \\\\\"content\\\\\": \\\\\"The Dallas Mavericks and Minnesota Timberwolves have advanced to the 2024 Western Conference Finals during the NBA playoffs.\\\\\", \\\\\"score\\\\\": 0.8884594, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"NBA Conference Finals Schedule: Full List of Games & Results\\\\\", \\\\\"url\\\\\": \\\\\"https://www.si.com/nba/nba-conference-finals-schedule-full-list-of-games-results\\\\\", \\\\\"content\\\\\": \\\\\"The 2024 NBA conference finals matchups are set. Here\\'s the schedule for all the games. ... Western Conference First Round (1) Oklahoma City Thunder def. (8) New Orleans Pelicans in 4 games\\\\\", \\\\\"score\\\\\": 0.85008353, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference playoff bracket - Basketnews.com\\\\\", \\\\\"url\\\\\": \\\\\"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\\\\\", \\\\\"content\\\\\": \\\\\"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. EuroLeague Play-In: Baskonia-Virtus game schedule announced\\\\\", \\\\\"score\\\\\": 0.8479807, \\\\\"raw_content\\\\\": null}]}\"}', '{\"role\":\"assistant\",\"content\":\"The teams that played in the NBA Western Conference Finals of 2024 were the Dallas Mavericks and the Minnesota Timberwolves.\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[]}', '{\"role\":\"user\",\"content\":\"In which episode and season of South Park does Bill Cosby (BSM-471) first appear? Give me the number and title.\",\"context\":null}'], 'output': \"content:  tool_calls: [ToolCall(call_id='ebd7e906-3ec9-45de-a58e-6662d75eceb7', tool_name=<BuiltinTool.brave_search: 'brave_search'>, arguments={'query': 'Bill Cosby South Park episode'})]\"}\n",
-            "{'input': '{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"ebd7e906-3ec9-45de-a58e-6662d75eceb7\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"Bill Cosby South Park episode\"}}]}', 'output': '{\"role\":\"tool\",\"call_id\":\"ebd7e906-3ec9-45de-a58e-6662d75eceb7\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"Bill Cosby South Park episode\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"Bill Cosby and Taylor Swift Duet - South Park Studios\\\\\", \\\\\"url\\\\\": \\\\\"https://www.southparkstudios.com/video-clips/90r7i1/south-park-bill-cosby-and-taylor-swift-duet\\\\\", \\\\\"content\\\\\": \\\\\"01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:03 Bill Cosby and Taylor Swift Duet South ParkS18 E10 ------------------------------------------------------- The holiday special continues with Bill Cosby and Taylor Swift\\'s rendition of \\\\\\\\\\\\\"It\\'s Snowing Out There\\\\\\\\\\\\\". 01:31 #WeBelieveInYou South ParkS18 E10 -------------------------------------- With everyone watching, Kyle takes the opportunity to reach out to his brother. 01:47 Watch Your Microaggressions, Bro South ParkS19 E1 ------------------------------------------------------ Cartman\\'s plan to frame PC Principal backfires. South ParkS19 E1 -------------------------------------- After hearing that the PC people have targeted Kyle, Cartman vows to help.\\\\\", \\\\\"score\\\\\": 0.685971, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Bill Cosby is Here to See You - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/video-clips/wfot8s/south-park-bill-cosby-is-here-to-see-you\\\\\", \\\\\"content\\\\\": \\\\\"01:56 It\\'s Not About Music South ParkS18 E9 ------------------------------------------ At home, Randy sees the consequences of Lorde\\'s performance and calls the Record Producer to try and fix it. 01:24 Lorde\\'s Hologram South ParkS18 E9 -------------------------------------- The Record Producer reveals the truth about the music industry... South ParkS18 E9 --------------------------------------------- Randy catches Sharon with Tupac\\'s hologram. 01:37 I\\'ve Got Your Son, Lorde South ParkS18 E10 ----------------------------------------------- The Record Producer takes Stan and Kyle hostage. 01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:21 Lorde Is My Dad South ParkS18 E10 -------------------------------------- After trying to confront Cartman Bra, Stan finally reveals the truth about his dad.\\\\\", \\\\\"score\\\\\": 0.6643884, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Bill Cosby (android) | South Park Character ... - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/wiki/Bill_Cosby_(android)\\\\\", \\\\\"content\\\\\": \\\\\"Bill Cosby (android) | South Park Character / Location / User talk etc | Official South Park Studios Wiki Sent back in time to destroy Eric Cartman\\'s Dawson\\'s Creek Trapper Keeper before it manifests into an omnipotent supercomputer that can destroy all humanity, \\\\\\\\\\\\\"Bill Cosby\\\\\\\\\\\\\" is really VSM471, an android or cyborg of some kind engineered by \\'hoomans\\' in the distant future. He fails in his initial missions to infiltrate South Park Elementary\\'s 4th Grade class, destroy the Trapper Keeper or Cartman himself, but with Stan Marsh and Kyle Broflovski\\'s aid, he is able to succeed in preventing his dismal future, and painfully fades from existence. South Park and all related titles, logos and characters are trademarks of Comedy Partners.\\\\\", \\\\\"score\\\\\": 0.5052006, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"\\'South Park\\' takes on Cosby, police, 2014 | CNN\\\\\", \\\\\"url\\\\\": \\\\\"https://www.cnn.com/2014/12/11/showbiz/tv/south-park-cosby-redskins-police/index.html\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\u2018South Park\\\\\\\\u2019 takes on Cosby, police, 2014 | CNN Watch Listen Live TV Subscribe Follow CNN Entertainment CNN Headlines CNN Shorts CNN10 CNN Max CNN TV Schedules CNN 5 Things CNN Underscored CNN Crossword About CNN CNN Profiles CNN Newsletters Work for CNN CNN \\\\\\\\u00a0\\\\\\\\u2014\\\\\\\\u00a0 \\\\\\\\u201cI think we take for granted how Trey Parker can jam a heap of current issues into a storyline thats a smart and funny #SouthPark episode,\\\\\\\\u201d wrote Brent Veale. \\\\\\\\u201cOh Lorde, CartmanBrah, dead celebrity holograms, murdering cops, this #SouthPark episode is certainly making #SaveTheLivingRoom happen,\\\\\\\\u201d added Brett Pender. CNN Headlines CNN10 CNN Max CNN TV Schedules CNN 5 Things CNN Underscored CNN Crossword About CNN CNN Profiles CNN Newsletters Work for CNN Follow CNN Entertainment\\\\\", \\\\\"score\\\\\": 0.45391592, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Trapper Keeper (South Park) - Wikipedia\\\\\", \\\\\"url\\\\\": \\\\\"https://en.wikipedia.org/wiki/Trapper_Keeper_(South_Park)\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" is the twelfth episode of the fourth season of the animated television series South Park, and the 60th episode of the series overall. In the episode, a man from the future wants Cartman\\'s new Trapper Keeper, while Mr. Garrison\\'s kindergarten class holds an election for class president with confusing results. It is one of the many South Park episodes that parodies a current event.[1] The main plot of the episode involving the Trapper Keeper was written before the election,[1] but the subplot is a parody of the controversy surrounding the election\\'s outcome.[2] \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" did not originally feature the election storyline, only a subplot about Ike attending his first day of kindergarten.[3] \\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" Full episode at South Park Studios\\\\\", \\\\\"score\\\\\": 0.3839421, \\\\\"raw_content\\\\\": null}]}\"}'}\n",
-            "{'input': ['{\"role\":\"system\",\"content\":\"You are a helpful assistant. 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(8) New Orleans Pelicans in 4 games\\\\\", \\\\\"score\\\\\": 0.85008353, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"2024 NBA Western Conference playoff bracket - Basketnews.com\\\\\", \\\\\"url\\\\\": \\\\\"https://basketnews.com/news-204687-2024-nba-western-conference-playoff-bracket.html\\\\\", \\\\\"content\\\\\": \\\\\"In the 2024 NBA Western Conference playoffs, the Oklahoma City Thunder clinched the No. 1 seed. Every team from the Western Conference played their final game of the regular season, and two playoff pairs have been confirmed. The Los Angeles Lakers beat the New Orleans Pelicans, 110-106, in the Play-In Tournament to secure the 7th seed to set up a first-round matchup with the Denver Nuggets. Meanwhile, the Sacramento Kings will host the Golden State Warriors in the second Western Conference NBA Play-In Tournament game. The winners secure the No. 8 seed in the NBA playoffs for its conference. 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Give me the number and title.\",\"context\":null}', '{\"role\":\"assistant\",\"content\":\"\",\"stop_reason\":\"end_of_turn\",\"tool_calls\":[{\"call_id\":\"ebd7e906-3ec9-45de-a58e-6662d75eceb7\",\"tool_name\":\"brave_search\",\"arguments\":{\"query\":\"Bill Cosby South Park episode\"}}]}', '{\"role\":\"tool\",\"call_id\":\"ebd7e906-3ec9-45de-a58e-6662d75eceb7\",\"tool_name\":\"brave_search\",\"content\":\"{\\\\\"query\\\\\": \\\\\"Bill Cosby South Park episode\\\\\", \\\\\"top_k\\\\\": [{\\\\\"title\\\\\": \\\\\"Bill Cosby and Taylor Swift Duet - South Park Studios\\\\\", \\\\\"url\\\\\": \\\\\"https://www.southparkstudios.com/video-clips/90r7i1/south-park-bill-cosby-and-taylor-swift-duet\\\\\", \\\\\"content\\\\\": \\\\\"01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:03 Bill Cosby and Taylor Swift Duet South ParkS18 E10 ------------------------------------------------------- The holiday special continues with Bill Cosby and Taylor Swift\\'s rendition of \\\\\\\\\\\\\"It\\'s Snowing Out There\\\\\\\\\\\\\". 01:31 #WeBelieveInYou South ParkS18 E10 -------------------------------------- With everyone watching, Kyle takes the opportunity to reach out to his brother. 01:47 Watch Your Microaggressions, Bro South ParkS19 E1 ------------------------------------------------------ Cartman\\'s plan to frame PC Principal backfires. South ParkS19 E1 -------------------------------------- After hearing that the PC people have targeted Kyle, Cartman vows to help.\\\\\", \\\\\"score\\\\\": 0.685971, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Bill Cosby is Here to See You - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/video-clips/wfot8s/south-park-bill-cosby-is-here-to-see-you\\\\\", \\\\\"content\\\\\": \\\\\"01:56 It\\'s Not About Music South ParkS18 E9 ------------------------------------------ At home, Randy sees the consequences of Lorde\\'s performance and calls the Record Producer to try and fix it. 01:24 Lorde\\'s Hologram South ParkS18 E9 -------------------------------------- The Record Producer reveals the truth about the music industry... South ParkS18 E9 --------------------------------------------- Randy catches Sharon with Tupac\\'s hologram. 01:37 I\\'ve Got Your Son, Lorde South ParkS18 E10 ----------------------------------------------- The Record Producer takes Stan and Kyle hostage. 01:05 Bill Cosby is Here to See You South ParkS18 E10 ---------------------------------------------------- Bill Cosby recruits Kyle and his hashtag for the big Holiday Special. 01:21 Lorde Is My Dad South ParkS18 E10 -------------------------------------- After trying to confront Cartman Bra, Stan finally reveals the truth about his dad.\\\\\", \\\\\"score\\\\\": 0.6643884, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Bill Cosby (android) | South Park Character ... - South Park Studios US\\\\\", \\\\\"url\\\\\": \\\\\"https://southpark.cc.com/wiki/Bill_Cosby_(android)\\\\\", \\\\\"content\\\\\": \\\\\"Bill Cosby (android) | South Park Character / Location / User talk etc | Official South Park Studios Wiki Sent back in time to destroy Eric Cartman\\'s Dawson\\'s Creek Trapper Keeper before it manifests into an omnipotent supercomputer that can destroy all humanity, \\\\\\\\\\\\\"Bill Cosby\\\\\\\\\\\\\" is really VSM471, an android or cyborg of some kind engineered by \\'hoomans\\' in the distant future. 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CNN Headlines CNN10 CNN Max CNN TV Schedules CNN 5 Things CNN Underscored CNN Crossword About CNN CNN Profiles CNN Newsletters Work for CNN Follow CNN Entertainment\\\\\", \\\\\"score\\\\\": 0.45391592, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Trapper Keeper (South Park) - Wikipedia\\\\\", \\\\\"url\\\\\": \\\\\"https://en.wikipedia.org/wiki/Trapper_Keeper_(South_Park)\\\\\", \\\\\"content\\\\\": \\\\\"\\\\\\\\\\\\\"Trapper Keeper\\\\\\\\\\\\\" is the twelfth episode of the fourth season of the animated television series South Park, and the 60th episode of the series overall. In the episode, a man from the future wants Cartman\\'s new Trapper Keeper, while Mr. Garrison\\'s kindergarten class holds an election for class president with confusing results. 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One of his first professional fights on\\\\\", \\\\\"score\\\\\": 0.8795718, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Andrew Tate kickboxing record: How many championships ... - FirstSportz\\\\\", \\\\\"url\\\\\": \\\\\"https://firstsportz.com/mma-how-many-championships-does-andrew-tate-have/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate\\'s Kickboxing career. During his kickboxing career, he used the nickname \\\\\\\\\\\\\"King Cobra,\\\\\\\\\\\\\" which he currently uses as his Twitter name. Tate had an unorthodox style of movement inside the ring. He kept his hands down most of the time and relied on quick jabs and an overhand right to land significant strikes.\\\\\", \\\\\"score\\\\\": 0.8752871, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"Andrew Tate: Kickboxing Record, Facts, Height, Weight, Age, Biography\\\\\", \\\\\"url\\\\\": \\\\\"https://www.lowkickmma.com/andrew-tate-kickboxing-record-facts-height-weight-age-biography/\\\\\", \\\\\"content\\\\\": \\\\\"Birth Name: Emory Andrew Tate III: Date of Birth: 1 December 1986: Place of Birth: Washington, D.C., U.S. ... In his professional kickboxing career, Andrew Tate won 32 of his fights by knockout.\\\\\", \\\\\"score\\\\\": 0.7992077, \\\\\"raw_content\\\\\": null}, {\\\\\"title\\\\\": \\\\\"About Andrew Tate: A Journey from Champion to Controversy\\\\\", \\\\\"url\\\\\": \\\\\"https://reachmorpheus.com/andrew-tate/\\\\\", \\\\\"content\\\\\": \\\\\"Andrew Tate\\'s kickboxing career, beginning in 2005, is a tale of determination and skill. He quickly made a name for himself in the sport, rising through the ranks with his unique fighting style and strategic approach, honed by his chess-playing background.\\\\\", \\\\\"score\\\\\": 0.6490677, \\\\\"raw_content\\\\\": null}]}\"}'], 'output': 'content: Andrew Tate\\'s kickboxing name is \"Cobra Tate\" or \"King Cobra\". tool_calls: []'}\n"
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-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'input_query'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"In which episode and season of South Park does Bill Cosby (BSM-471) first appear? Give me the number and title.\",\"context\":null}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'generated_answer'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #008000; text-decoration-color: #008000\">\"content:  tool_calls: [ToolCall(call_id='ebd7e906-3ec9-45de-a58e-6662d75eceb7', tool_name=&lt;BuiltinTool.brave_search: 'brave_search'&gt;, arguments={'query': 'Bill Cosby South Park episode'})]\"</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
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-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'input_query'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #008000; text-decoration-color: #008000\">'{\"role\":\"user\",\"content\":\"What is the British-American kickboxer Andrew Tate\\'s kickboxing name?\",\"context\":null}'</span><span style=\"color: #000000; text-decoration-color: #000000\">,</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'generated_answer'</span><span style=\"color: #000000; text-decoration-color: #000000\">: </span><span style=\"color: #008000; text-decoration-color: #008000\">\"content:  tool_calls: [ToolCall(call_id='e26ecfb2-434c-479f-95dc-7b3b4929665a', tool_name=&lt;BuiltinTool.brave_search: 'brave_search'&gt;, arguments={'query': 'Andrew Tate kickboxing name'})]\"</span>,\n",
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-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">}</span>\n",
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-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">ScoringScoreResponse</span><span style=\"font-weight: bold\">(</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">results</span>=<span style=\"font-weight: bold\">{</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'basic::subset_of'</span>: <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">ScoringResult</span><span style=\"font-weight: bold\">(</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">aggregated_results</span>=<span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'accuracy'</span>: <span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'accuracy'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'num_correct'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3.0</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'num_total'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">3</span><span style=\"font-weight: bold\">}}</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">score_rows</span>=<span style=\"font-weight: bold\">[{</span><span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span><span style=\"font-weight: bold\">}</span>, <span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span><span style=\"font-weight: bold\">}</span>, <span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span><span style=\"font-weight: bold\">}]</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"font-weight: bold\">)</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">}</span>\n",
-              "<span style=\"font-weight: bold\">)</span>\n",
-              "</pre>\n"
-            ],
-            "text/plain": [
-              "\u001b[1;35mScoringScoreResponse\u001b[0m\u001b[1m(\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[33mresults\u001b[0m=\u001b[1m{\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'basic::subset_of'\u001b[0m: \u001b[1;35mScoringResult\u001b[0m\u001b[1m(\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[33maggregated_results\u001b[0m=\u001b[1m{\u001b[0m\u001b[32m'accuracy'\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m'accuracy'\u001b[0m: \u001b[1;36m1.0\u001b[0m, \u001b[32m'num_correct'\u001b[0m: \u001b[1;36m3.0\u001b[0m, \u001b[32m'num_total'\u001b[0m: \u001b[1;36m3\u001b[0m\u001b[1m}\u001b[0m\u001b[1m}\u001b[0m,\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[33mscore_rows\u001b[0m=\u001b[1m[\u001b[0m\u001b[1m{\u001b[0m\u001b[32m'score'\u001b[0m: \u001b[1;36m1.0\u001b[0m\u001b[1m}\u001b[0m, \u001b[1m{\u001b[0m\u001b[32m'score'\u001b[0m: \u001b[1;36m1.0\u001b[0m\u001b[1m}\u001b[0m, \u001b[1m{\u001b[0m\u001b[32m'score'\u001b[0m: \u001b[1;36m1.0\u001b[0m\u001b[1m}\u001b[0m\u001b[1m]\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[1m)\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[1m}\u001b[0m\n",
-              "\u001b[1m)\u001b[0m\n"
-            ]
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-      "source": [
-        "# post-process telemetry spance and prepare data for eval\n",
-        "# in this case, we want to assert that all user prompts is followed by a tool call\n",
-        "import ast\n",
-        "import json\n",
-        "\n",
-        "eval_rows = []\n",
-        "\n",
-        "for log in agent_logs:\n",
-        "    print(log)\n",
-        "    last_msg = log[\"input\"][-1]\n",
-        "    if '\"role\":\"user\"' in last_msg:\n",
-        "        eval_rows.append(\n",
-        "            {\n",
-        "                \"input_query\": last_msg,\n",
-        "                \"generated_answer\": log[\"output\"],\n",
-        "                # check if generated_answer uses tools brave_search\n",
-        "                \"expected_answer\": \"brave_search\",\n",
-        "            },\n",
-        "        )\n",
-        "\n",
-        "pprint(eval_rows)\n",
-        "scoring_params = {\n",
-        "    \"basic::subset_of\": None,\n",
-        "}\n",
-        "scoring_response = client.scoring.score(\n",
-        "    input_rows=eval_rows, scoring_functions=scoring_params\n",
-        ")\n",
-        "pprint(scoring_response)\n"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "IKbzhxcw5e_c",
-      "metadata": {
-        "id": "IKbzhxcw5e_c"
-      },
-      "source": [
-        "#### 3.2. Agentic Application Dataset Scoring\n",
-        "- Llama Stack offers a library of scoring functions and the `/scoring` API, allowing you to run evaluations on your pre-annotated AI application datasets.\n",
-        "\n",
-        "- In this example, we will work with an example RAG dataset you have built previously, label with an annotation, and use LLM-As-Judge with custom judge prompt for scoring. Please checkout our [Llama Stack Playground](https://llama-stack.readthedocs.io/en/latest/playground/index.html) for an interactive interface to upload datasets and run scorings."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 20,
-      "id": "xG4Y84VQBb0g",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/",
-          "height": 304
-        },
-        "id": "xG4Y84VQBb0g",
-        "outputId": "cf7dcecc-a81d-4c60-af5e-b36b8fe85c69"
-      },
-      "outputs": [
-        {
-          "data": {
-            "text/html": [
-              "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">ScoringScoreResponse</span><span style=\"font-weight: bold\">(</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"color: #808000; text-decoration-color: #808000\">results</span>=<span style=\"font-weight: bold\">{</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'llm-as-judge::base'</span>: <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">ScoringResult</span><span style=\"font-weight: bold\">(</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">aggregated_results</span>=<span style=\"font-weight: bold\">{}</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">score_rows</span>=<span style=\"font-weight: bold\">[</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   │   </span><span style=\"font-weight: bold\">{</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'B'</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   │   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'judge_feedback'</span>: <span style=\"color: #008000; text-decoration-color: #008000\">'Answer: B, Explanation: The GENERATED_RESPONSE is a superset of the EXPECTED_RESPONSE and is fully consistent with it. The EXPECTED_RESPONSE only mentions \"LoRA\", which is present in all the points of the GENERATED_RESPONSE. The GENERATED_RESPONSE provides more details and specific topics related to LoRA, but it does not contradict the EXPECTED_RESPONSE.'</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   │   </span><span style=\"font-weight: bold\">}</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"font-weight: bold\">]</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"font-weight: bold\">)</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"color: #008000; text-decoration-color: #008000\">'basic::subset_of'</span>: <span style=\"color: #800080; text-decoration-color: #800080; font-weight: bold\">ScoringResult</span><span style=\"font-weight: bold\">(</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">aggregated_results</span>=<span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'accuracy'</span>: <span style=\"font-weight: bold\">{</span><span style=\"color: #008000; text-decoration-color: #008000\">'accuracy'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'num_correct'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span>, <span style=\"color: #008000; text-decoration-color: #008000\">'num_total'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1</span><span style=\"font-weight: bold\">}}</span>,\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   │   </span><span style=\"color: #808000; text-decoration-color: #808000\">score_rows</span>=<span style=\"font-weight: bold\">[{</span><span style=\"color: #008000; text-decoration-color: #008000\">'score'</span>: <span style=\"color: #008080; text-decoration-color: #008080; font-weight: bold\">1.0</span><span style=\"font-weight: bold\">}]</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   │   </span><span style=\"font-weight: bold\">)</span>\n",
-              "<span style=\"color: #7fbf7f; text-decoration-color: #7fbf7f\">│   </span><span style=\"font-weight: bold\">}</span>\n",
-              "<span style=\"font-weight: bold\">)</span>\n",
-              "</pre>\n"
-            ],
-            "text/plain": [
-              "\u001b[1;35mScoringScoreResponse\u001b[0m\u001b[1m(\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[33mresults\u001b[0m=\u001b[1m{\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'llm-as-judge::base'\u001b[0m: \u001b[1;35mScoringResult\u001b[0m\u001b[1m(\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[33maggregated_results\u001b[0m=\u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[33mscore_rows\u001b[0m=\u001b[1m[\u001b[0m\n",
-              "\u001b[2;32m│   │   │   │   \u001b[0m\u001b[1m{\u001b[0m\n",
-              "\u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[32m'score'\u001b[0m: \u001b[32m'B'\u001b[0m,\n",
-              "\u001b[2;32m│   │   │   │   │   \u001b[0m\u001b[32m'judge_feedback'\u001b[0m: \u001b[32m'Answer: B, Explanation: The GENERATED_RESPONSE is a superset of the EXPECTED_RESPONSE and is fully consistent with it. The EXPECTED_RESPONSE only mentions \"LoRA\", which is present in all the points of the GENERATED_RESPONSE. The GENERATED_RESPONSE provides more details and specific topics related to LoRA, but it does not contradict the EXPECTED_RESPONSE.'\u001b[0m\n",
-              "\u001b[2;32m│   │   │   │   \u001b[0m\u001b[1m}\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[1m]\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[1m)\u001b[0m,\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[32m'basic::subset_of'\u001b[0m: \u001b[1;35mScoringResult\u001b[0m\u001b[1m(\u001b[0m\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[33maggregated_results\u001b[0m=\u001b[1m{\u001b[0m\u001b[32m'accuracy'\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m'accuracy'\u001b[0m: \u001b[1;36m1.0\u001b[0m, \u001b[32m'num_correct'\u001b[0m: \u001b[1;36m1.0\u001b[0m, \u001b[32m'num_total'\u001b[0m: \u001b[1;36m1\u001b[0m\u001b[1m}\u001b[0m\u001b[1m}\u001b[0m,\n",
-              "\u001b[2;32m│   │   │   \u001b[0m\u001b[33mscore_rows\u001b[0m=\u001b[1m[\u001b[0m\u001b[1m{\u001b[0m\u001b[32m'score'\u001b[0m: \u001b[1;36m1.0\u001b[0m\u001b[1m}\u001b[0m\u001b[1m]\u001b[0m\n",
-              "\u001b[2;32m│   │   \u001b[0m\u001b[1m)\u001b[0m\n",
-              "\u001b[2;32m│   \u001b[0m\u001b[1m}\u001b[0m\n",
-              "\u001b[1m)\u001b[0m\n"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        }
-      ],
-      "source": [
-        "import rich\n",
-        "from rich.pretty import pprint\n",
-        "\n",
-        "judge_model_id = \"meta-llama/Llama-3.1-405B-Instruct-FP8\"\n",
-        "\n",
-        "JUDGE_PROMPT = \"\"\"\n",
-        "Given a QUESTION and GENERATED_RESPONSE and EXPECTED_RESPONSE.\n",
-        "\n",
-        "Compare the factual content of the GENERATED_RESPONSE with the EXPECTED_RESPONSE. Ignore any differences in style, grammar, or punctuation.\n",
-        "  The GENERATED_RESPONSE may either be a subset or superset of the EXPECTED_RESPONSE, or it may conflict with it. Determine which case applies. Answer the question by selecting one of the following options:\n",
-        "  (A) The GENERATED_RESPONSE is a subset of the EXPECTED_RESPONSE and is fully consistent with it.\n",
-        "  (B) The GENERATED_RESPONSE is a superset of the EXPECTED_RESPONSE and is fully consistent with it.\n",
-        "  (C) The GENERATED_RESPONSE contains all the same details as the EXPECTED_RESPONSE.\n",
-        "  (D) There is a disagreement between the GENERATED_RESPONSE and the EXPECTED_RESPONSE.\n",
-        "  (E) The answers differ, but these differences don't matter from the perspective of factuality.\n",
-        "\n",
-        "Give your answer in the format \"Answer: One of ABCDE, Explanation: \".\n",
-        "\n",
-        "Your actual task:\n",
-        "\n",
-        "QUESTION: {input_query}\n",
-        "GENERATED_RESPONSE: {generated_answer}\n",
-        "EXPECTED_RESPONSE: {expected_answer}\n",
-        "\"\"\"\n",
-        "\n",
-        "input_query = (\n",
-        "    \"What are the top 5 topics that were explained? Only list succinct bullet points.\"\n",
-        ")\n",
-        "generated_answer = \"\"\"\n",
-        "Here are the top 5 topics that were explained in the documentation for Torchtune:\n",
-        "\n",
-        "* What is LoRA and how does it work?\n",
-        "* Fine-tuning with LoRA: memory savings and parameter-efficient finetuning\n",
-        "* Running a LoRA finetune with Torchtune: overview and recipe\n",
-        "* Experimenting with different LoRA configurations: rank, alpha, and attention modules\n",
-        "* LoRA finetuning\n",
-        "\"\"\"\n",
-        "expected_answer = \"\"\"LoRA\"\"\"\n",
-        "\n",
-        "rows = [\n",
-        "    {\n",
-        "        \"input_query\": input_query,\n",
-        "        \"generated_answer\": generated_answer,\n",
-        "        \"expected_answer\": expected_answer,\n",
-        "    },\n",
-        "]\n",
-        "\n",
-        "scoring_params = {\n",
-        "    \"llm-as-judge::base\": {\n",
-        "        \"judge_model\": judge_model_id,\n",
-        "        \"prompt_template\": JUDGE_PROMPT,\n",
-        "        \"type\": \"llm_as_judge\",\n",
-        "        \"judge_score_regexes\": [\"Answer: (A|B|C|D|E)\"],\n",
-        "    },\n",
-        "    \"basic::subset_of\": None,\n",
-        "}\n",
-        "\n",
-        "response = client.scoring.score(input_rows=rows, scoring_functions=scoring_params)\n",
-        "pprint(response)\n"
-      ]
-    }
-  ],
-  "metadata": {
-    "accelerator": "GPU",
-    "colab": {
-      "gpuType": "T4",
-      "provenance": []
-    },
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-      "display_name": "Python 3",
-      "name": "python3"
-    },
-    "language_info": {
-      "codemirror_mode": {
-        "name": "ipython",
-        "version": 3
-      },
-      "file_extension": ".py",
-      "mimetype": "text/x-python",
-      "name": "python",
-      "nbconvert_exporter": "python",
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diff --git a/docs/openapi_generator/pyopenapi/operations.py b/docs/openapi_generator/pyopenapi/operations.py
index 4cea9d970..abeb16936 100644
--- a/docs/openapi_generator/pyopenapi/operations.py
+++ b/docs/openapi_generator/pyopenapi/operations.py
@@ -172,10 +172,16 @@ def _get_endpoint_functions(
 def _get_defining_class(member_fn: str, derived_cls: type) -> type:
     "Find the class in which a member function is first defined in a class inheritance hierarchy."
 
+    # This import must be dynamic here
+    from llama_stack.apis.tools import RAGToolRuntime, ToolRuntime
+
     # iterate in reverse member resolution order to find most specific class first
     for cls in reversed(inspect.getmro(derived_cls)):
         for name, _ in inspect.getmembers(cls, inspect.isfunction):
             if name == member_fn:
+                # HACK ALERT
+                if cls == RAGToolRuntime:
+                    return ToolRuntime
                 return cls
 
     raise ValidationError(
diff --git a/docs/openapi_generator/strong_typing/classdef.py b/docs/openapi_generator/strong_typing/classdef.py
index c8e6781fd..b86940420 100644
--- a/docs/openapi_generator/strong_typing/classdef.py
+++ b/docs/openapi_generator/strong_typing/classdef.py
@@ -122,9 +122,16 @@ class JsonSchemaAnyOf(JsonSchemaNode):
     anyOf: List["JsonSchemaAny"]
 
 
+@dataclass
+class Discriminator:
+    propertyName: str
+    mapping: Dict[str, str]
+
+
 @dataclass
 class JsonSchemaOneOf(JsonSchemaNode):
     oneOf: List["JsonSchemaAny"]
+    discriminator: Optional[Discriminator]
 
 
 JsonSchemaAny = Union[
diff --git a/docs/openapi_generator/strong_typing/schema.py b/docs/openapi_generator/strong_typing/schema.py
index 42feeee5a..826efdb4a 100644
--- a/docs/openapi_generator/strong_typing/schema.py
+++ b/docs/openapi_generator/strong_typing/schema.py
@@ -36,6 +36,7 @@ from typing import (
 )
 
 import jsonschema
+from typing_extensions import Annotated
 
 from . import docstring
 from .auxiliary import (
@@ -329,7 +330,6 @@ class JsonSchemaGenerator:
         if metadata is not None:
             # type is Annotated[T, ...]
             typ = typing.get_args(data_type)[0]
-
             schema = self._simple_type_to_schema(typ)
             if schema is not None:
                 # recognize well-known auxiliary types
@@ -446,12 +446,31 @@ class JsonSchemaGenerator:
                 ],
             }
         elif origin_type is Union:
-            return {
+            discriminator = None
+            if typing.get_origin(data_type) is Annotated:
+                discriminator = typing.get_args(data_type)[1].discriminator
+            ret = {
                 "oneOf": [
                     self.type_to_schema(union_type)
                     for union_type in typing.get_args(typ)
                 ]
             }
+            if discriminator:
+                # for each union type, we need to read the value of the discriminator
+                mapping = {}
+                for union_type in typing.get_args(typ):
+                    props = self.type_to_schema(union_type, force_expand=True)[
+                        "properties"
+                    ]
+                    mapping[props[discriminator]["default"]] = self.type_to_schema(
+                        union_type
+                    )["$ref"]
+
+                ret["discriminator"] = {
+                    "propertyName": discriminator,
+                    "mapping": mapping,
+                }
+            return ret
         elif origin_type is Literal:
             (literal_value,) = typing.get_args(typ)  # unpack value of literal type
             schema = self.type_to_schema(type(literal_value))
diff --git a/docs/readme.md b/docs/readme.md
new file mode 100644
index 000000000..f345fdee6
--- /dev/null
+++ b/docs/readme.md
@@ -0,0 +1,11 @@
+# Llama Stack Documentation
+
+Here's a collection of comprehensive guides, examples, and resources for building AI applications with Llama Stack. For the complete documentation, visit our [ReadTheDocs page](https://llama-stack.readthedocs.io/en/latest/index.html).
+
+## Content
+
+Try out Llama Stack's capabilities through our detailed Jupyter notebooks:
+
+* [Building AI Applications Notebook](./notebooks/Llama_Stack_Building_AI_Applications.ipynb) - A comprehensive guide to building production-ready AI applications using Llama Stack
+* [Benchmark Evaluations Notebook](./notebooks/Llama_Stack_Benchmark_Evals.ipynb) - Detailed performance evaluations and benchmarking results
+* [Zero-to-Hero Guide](./notebooks/Llama_Stack_Zero_to_Hero_Guide.ipynb) - Step-by-step guide for getting started with Llama Stack
diff --git a/docs/resources/llama-stack-spec.html b/docs/resources/llama-stack-spec.html
index 459a53888..7108ee9a5 100644
--- a/docs/resources/llama-stack-spec.html
+++ b/docs/resources/llama-stack-spec.html
@@ -1108,98 +1108,6 @@
                 ]
             }
         },
-        "/v1/memory-banks/{memory_bank_id}": {
-            "get": {
-                "responses": {
-                    "200": {
-                        "description": "OK",
-                        "content": {
-                            "application/json": {
-                                "schema": {
-                                    "oneOf": [
-                                        {
-                                            "$ref": "#/components/schemas/MemoryBank"
-                                        },
-                                        {
-                                            "type": "null"
-                                        }
-                                    ]
-                                }
-                            }
-                        }
-                    }
-                },
-                "tags": [
-                    "MemoryBanks"
-                ],
-                "parameters": [
-                    {
-                        "name": "memory_bank_id",
-                        "in": "path",
-                        "required": true,
-                        "schema": {
-                            "type": "string"
-                        }
-                    },
-                    {
-                        "name": "X-LlamaStack-Provider-Data",
-                        "in": "header",
-                        "description": "JSON-encoded provider data which will be made available to the adapter servicing the API",
-                        "required": false,
-                        "schema": {
-                            "type": "string"
-                        }
-                    },
-                    {
-                        "name": "X-LlamaStack-Client-Version",
-                        "in": "header",
-                        "description": "Version of the client making the request. This is used to ensure that the client and server are compatible.",
-                        "required": false,
-                        "schema": {
-                            "type": "string"
-                        }
-                    }
-                ]
-            },
-            "delete": {
-                "responses": {
-                    "200": {
-                        "description": "OK"
-                    }
-                },
-                "tags": [
-                    "MemoryBanks"
-                ],
-                "parameters": [
-                    {
-                        "name": "memory_bank_id",
-                        "in": "path",
-                        "required": true,
-                        "schema": {
-                            "type": "string"
-                        }
-                    },
-                    {
-                        "name": "X-LlamaStack-Provider-Data",
-                        "in": "header",
-                        "description": "JSON-encoded provider data which will be made available to the adapter servicing the API",
-                        "required": false,
-                        "schema": {
-                            "type": "string"
-                        }
-                    },
-                    {
-                        "name": "X-LlamaStack-Client-Version",
-                        "in": "header",
-                        "description": "Version of the client making the request. This is used to ensure that the client and server are compatible.",
-                        "required": false,
-                        "schema": {
-                            "type": "string"
-                        }
-                    }
-                ]
-            }
-        },
         "/v1/models/{model_id}": {
             "get": {
                 "responses": {
@@ -1848,6 +1756,98 @@
                 ]
             }
         },
+        "/v1/vector-dbs/{vector_db_id}": {
+            "get": {
+                "responses": {
+                    "200": {
+                        "description": "OK",
+                        "content": {
+                            "application/json": {
+                                "schema": {
+                                    "oneOf": [
+                                        {
+                                            "$ref": "#/components/schemas/VectorDB"
+                                        },
+                                        {
+                                            "type": "null"
+                                        }
+                                    ]
+                                }
+                            }
+                        }
+                    }
+                },
+                "tags": [
+                    "VectorDBs"
+                ],
+                "parameters": [
+                    {
+                        "name": "vector_db_id",
+                        "in": "path",
+                        "required": true,
+                        "schema": {
+                            "type": "string"
+                        }
+                    },
+                    {
+                        "name": "X-LlamaStack-Provider-Data",
+                        "in": "header",
+                        "description": "JSON-encoded provider data which will be made available to the adapter servicing the API",
+                        "required": false,
+                        "schema": {
+                            "type": "string"
+                        }
+                    },
+                    {
+                        "name": "X-LlamaStack-Client-Version",
+                        "in": "header",
+                        "description": "Version of the client making the request. This is used to ensure that the client and server are compatible.",
+                        "required": false,
+                        "schema": {
+                            "type": "string"
+                        }
+                    }
+                ]
+            },
+            "delete": {
+                "responses": {
+                    "200": {
+                        "description": "OK"
+                    }
+                },
+                "tags": [
+                    "VectorDBs"
+                ],
+                "parameters": [
+                    {
+                        "name": "vector_db_id",
+                        "in": "path",
+                        "required": true,
+                        "schema": {
+                            "type": "string"
+                        }
+                    },
+                    {
+                        "name": "X-LlamaStack-Provider-Data",
+                        "in": "header",
+                        "description": "JSON-encoded provider data which will be made available to the adapter servicing the API",
+                        "required": false,
+                        "schema": {
+                            "type": "string"
+                        }
+                    },
+                    {
+                        "name": "X-LlamaStack-Client-Version",
+                        "in": "header",
+                        "description": "Version of the client making the request. This is used to ensure that the client and server are compatible.",
+                        "required": false,
+                        "schema": {
+                            "type": "string"
+                        }
+                    }
+                ]
+            }
+        },
         "/v1/health": {
             "get": {
                 "responses": {
@@ -1887,7 +1887,7 @@
                 ]
             }
         },
-        "/v1/memory/insert": {
+        "/v1/tool-runtime/rag-tool/insert": {
             "post": {
                 "responses": {
                     "200": {
@@ -1895,7 +1895,50 @@
                     }
                 },
                 "tags": [
-                    "Memory"
+                    "ToolRuntime"
+                ],
+                "summary": "Index documents so they can be used by the RAG system",
+                "parameters": [
+                    {
+                        "name": "X-LlamaStack-Provider-Data",
+                        "in": "header",
+                        "description": "JSON-encoded provider data which will be made available to the adapter servicing the API",
+                        "required": false,
+                        "schema": {
+                            "type": "string"
+                        }
+                    },
+                    {
+                        "name": "X-LlamaStack-Client-Version",
+                        "in": "header",
+                        "description": "Version of the client making the request. This is used to ensure that the client and server are compatible.",
+                        "required": false,
+                        "schema": {
+                            "type": "string"
+                        }
+                    }
+                ],
+                "requestBody": {
+                    "content": {
+                        "application/json": {
+                            "schema": {
+                                "$ref": "#/components/schemas/InsertRequest"
+                            }
+                        }
+                    },
+                    "required": true
+                }
+            }
+        },
+        "/v1/vector-io/insert": {
+            "post": {
+                "responses": {
+                    "200": {
+                        "description": "OK"
+                    }
+                },
+                "tags": [
+                    "VectorIO"
                 ],
                 "parameters": [
                     {
@@ -1921,7 +1964,7 @@
                     "content": {
                         "application/json": {
                             "schema": {
-                                "$ref": "#/components/schemas/InsertDocumentsRequest"
+                                "$ref": "#/components/schemas/InsertChunksRequest"
                             }
                         }
                     },
@@ -2300,105 +2343,6 @@
                 }
             }
         },
-        "/v1/memory-banks": {
-            "get": {
-                "responses": {
-                    "200": {
-                        "description": "OK",
-                        "content": {
-                            "application/json": {
-                                "schema": {
-                                    "$ref": "#/components/schemas/ListMemoryBanksResponse"
-                                }
-                            }
-                        }
-                    }
-                },
-                "tags": [
-                    "MemoryBanks"
-                ],
-                "parameters": [
-                    {
-                        "name": "X-LlamaStack-Provider-Data",
-                        "in": "header",
-                        "description": "JSON-encoded provider data which will be made available to the adapter servicing the API",
-                        "required": false,
-                        "schema": {
-                            "type": "string"
-                        }
-                    },
-                    {
-                        "name": "X-LlamaStack-Client-Version",
-                        "in": "header",
-                        "description": "Version of the client making the request. This is used to ensure that the client and server are compatible.",
-                        "required": false,
-                        "schema": {
-                            "type": "string"
-                        }
-                    }
-                ]
-            },
-            "post": {
-                "responses": {
-                    "200": {
-                        "description": "",
-                        "content": {
-                            "application/json": {
-                                "schema": {
-                                    "oneOf": [
-                                        {
-                                            "$ref": "#/components/schemas/VectorMemoryBank"
-                                        },
-                                        {
-                                            "$ref": "#/components/schemas/KeyValueMemoryBank"
-                                        },
-                                        {
-                                            "$ref": "#/components/schemas/KeywordMemoryBank"
-                                        },
-                                        {
-                                            "$ref": "#/components/schemas/GraphMemoryBank"
-                                        }
-                                    ]
-                                }
-                            }
-                        }
-                    }
-                },
-                "tags": [
-                    "MemoryBanks"
-                ],
-                "parameters": [
-                    {
-                        "name": "X-LlamaStack-Provider-Data",
-                        "in": "header",
-                        "description": "JSON-encoded provider data which will be made available to the adapter servicing the API",
-                        "required": false,
-                        "schema": {
-                            "type": "string"
-                        }
-                    },
-                    {
-                        "name": "X-LlamaStack-Client-Version",
-                        "in": "header",
-                        "description": "Version of the client making the request. This is used to ensure that the client and server are compatible.",
-                        "required": false,
-                        "schema": {
-                            "type": "string"
-                        }
-                    }
-                ],
-                "requestBody": {
-                    "content": {
-                        "application/json": {
-                            "schema": {
-                                "$ref": "#/components/schemas/RegisterMemoryBankRequest"
-                            }
-                        }
-                    },
-                    "required": true
-                }
-            }
-        },
         "/v1/models": {
             "get": {
                 "responses": {
@@ -2912,6 +2856,92 @@
                 ]
             }
         },
+        "/v1/vector-dbs": {
+            "get": {
+                "responses": {
+                    "200": {
+                        "description": "OK",
+                        "content": {
+                            "application/json": {
+                                "schema": {
+                                    "$ref": "#/components/schemas/ListVectorDBsResponse"
+                                }
+                            }
+                        }
+                    }
+                },
+                "tags": [
+                    "VectorDBs"
+                ],
+                "parameters": [
+                    {
+                        "name": "X-LlamaStack-Provider-Data",
+                        "in": "header",
+                        "description": "JSON-encoded provider data which will be made available to the adapter servicing the API",
+                        "required": false,
+                        "schema": {
+                            "type": "string"
+                        }
+                    },
+                    {
+                        "name": "X-LlamaStack-Client-Version",
+                        "in": "header",
+                        "description": "Version of the client making the request. This is used to ensure that the client and server are compatible.",
+                        "required": false,
+                        "schema": {
+                            "type": "string"
+                        }
+                    }
+                ]
+            },
+            "post": {
+                "responses": {
+                    "200": {
+                        "description": "OK",
+                        "content": {
+                            "application/json": {
+                                "schema": {
+                                    "$ref": "#/components/schemas/VectorDB"
+                                }
+                            }
+                        }
+                    }
+                },
+                "tags": [
+                    "VectorDBs"
+                ],
+                "parameters": [
+                    {
+                        "name": "X-LlamaStack-Provider-Data",
+                        "in": "header",
+                        "description": "JSON-encoded provider data which will be made available to the adapter servicing the API",
+                        "required": false,
+                        "schema": {
+                            "type": "string"
+                        }
+                    },
+                    {
+                        "name": "X-LlamaStack-Client-Version",
+                        "in": "header",
+                        "description": "Version of the client making the request. This is used to ensure that the client and server are compatible.",
+                        "required": false,
+                        "schema": {
+                            "type": "string"
+                        }
+                    }
+                ],
+                "requestBody": {
+                    "content": {
+                        "application/json": {
+                            "schema": {
+                                "$ref": "#/components/schemas/RegisterVectorDbRequest"
+                            }
+                        }
+                    },
+                    "required": true
+                }
+            }
+        },
         "/v1/telemetry/events": {
             "post": {
                 "responses": {
@@ -3003,7 +3033,7 @@
                 }
             }
         },
-        "/v1/memory/query": {
+        "/v1/tool-runtime/rag-tool/query": {
             "post": {
                 "responses": {
                     "200": {
@@ -3011,14 +3041,64 @@
                         "content": {
                             "application/json": {
                                 "schema": {
-                                    "$ref": "#/components/schemas/QueryDocumentsResponse"
+                                    "$ref": "#/components/schemas/RAGQueryResult"
                                 }
                             }
                         }
                     }
                 },
                 "tags": [
-                    "Memory"
+                    "ToolRuntime"
+                ],
+                "summary": "Query the RAG system for context; typically invoked by the agent",
+                "parameters": [
+                    {
+                        "name": "X-LlamaStack-Provider-Data",
+                        "in": "header",
+                        "description": "JSON-encoded provider data which will be made available to the adapter servicing the API",
+                        "required": false,
+                        "schema": {
+                            "type": "string"
+                        }
+                    },
+                    {
+                        "name": "X-LlamaStack-Client-Version",
+                        "in": "header",
+                        "description": "Version of the client making the request. This is used to ensure that the client and server are compatible.",
+                        "required": false,
+                        "schema": {
+                            "type": "string"
+                        }
+                    }
+                ],
+                "requestBody": {
+                    "content": {
+                        "application/json": {
+                            "schema": {
+                                "$ref": "#/components/schemas/QueryRequest"
+                            }
+                        }
+                    },
+                    "required": true
+                }
+            }
+        },
+        "/v1/vector-io/query": {
+            "post": {
+                "responses": {
+                    "200": {
+                        "description": "OK",
+                        "content": {
+                            "application/json": {
+                                "schema": {
+                                    "$ref": "#/components/schemas/QueryChunksResponse"
+                                }
+                            }
+                        }
+                    }
+                },
+                "tags": [
+                    "VectorIO"
                 ],
                 "parameters": [
                     {
@@ -3044,7 +3124,7 @@
                     "content": {
                         "application/json": {
                             "schema": {
-                                "$ref": "#/components/schemas/QueryDocumentsRequest"
+                                "$ref": "#/components/schemas/QueryChunksRequest"
                             }
                         }
                     },
@@ -3681,22 +3761,29 @@
             "ImageContentItem": {
                 "type": "object",
                 "properties": {
-                    "url": {
-                        "$ref": "#/components/schemas/URL"
-                    },
-                    "data": {
-                        "type": "string",
-                        "contentEncoding": "base64"
-                    },
                     "type": {
                         "type": "string",
                         "const": "image",
                         "default": "image"
+                    },
+                    "image": {
+                        "type": "object",
+                        "properties": {
+                            "url": {
+                                "$ref": "#/components/schemas/URL"
+                            },
+                            "data": {
+                                "type": "string",
+                                "contentEncoding": "base64"
+                            }
+                        },
+                        "additionalProperties": false
                     }
                 },
                 "additionalProperties": false,
                 "required": [
-                    "type"
+                    "type",
+                    "image"
                 ]
             },
             "InterleavedContent": {
@@ -3723,7 +3810,14 @@
                     {
                         "$ref": "#/components/schemas/TextContentItem"
                     }
-                ]
+                ],
+                "discriminator": {
+                    "propertyName": "type",
+                    "mapping": {
+                        "image": "#/components/schemas/ImageContentItem",
+                        "text": "#/components/schemas/TextContentItem"
+                    }
+                }
             },
             "Message": {
                 "oneOf": [
@@ -3739,7 +3833,16 @@
                     {
                         "$ref": "#/components/schemas/CompletionMessage"
                     }
-                ]
+                ],
+                "discriminator": {
+                    "propertyName": "role",
+                    "mapping": {
+                        "user": "#/components/schemas/UserMessage",
+                        "system": "#/components/schemas/SystemMessage",
+                        "tool": "#/components/schemas/ToolResponseMessage",
+                        "assistant": "#/components/schemas/CompletionMessage"
+                    }
+                }
             },
             "SamplingParams": {
                 "type": "object",
@@ -3755,7 +3858,15 @@
                             {
                                 "$ref": "#/components/schemas/TopKSamplingStrategy"
                             }
-                        ]
+                        ],
+                        "discriminator": {
+                            "propertyName": "type",
+                            "mapping": {
+                                "greedy": "#/components/schemas/GreedySamplingStrategy",
+                                "top_p": "#/components/schemas/TopPSamplingStrategy",
+                                "top_k": "#/components/schemas/TopKSamplingStrategy"
+                            }
+                        }
                     },
                     "max_tokens": {
                         "type": "integer",
@@ -4217,89 +4328,102 @@
                     "job_uuid"
                 ]
             },
+            "GrammarResponseFormat": {
+                "type": "object",
+                "properties": {
+                    "type": {
+                        "type": "string",
+                        "const": "grammar",
+                        "default": "grammar"
+                    },
+                    "bnf": {
+                        "type": "object",
+                        "additionalProperties": {
+                            "oneOf": [
+                                {
+                                    "type": "null"
+                                },
+                                {
+                                    "type": "boolean"
+                                },
+                                {
+                                    "type": "number"
+                                },
+                                {
+                                    "type": "string"
+                                },
+                                {
+                                    "type": "array"
+                                },
+                                {
+                                    "type": "object"
+                                }
+                            ]
+                        }
+                    }
+                },
+                "additionalProperties": false,
+                "required": [
+                    "type",
+                    "bnf"
+                ]
+            },
+            "JsonSchemaResponseFormat": {
+                "type": "object",
+                "properties": {
+                    "type": {
+                        "type": "string",
+                        "const": "json_schema",
+                        "default": "json_schema"
+                    },
+                    "json_schema": {
+                        "type": "object",
+                        "additionalProperties": {
+                            "oneOf": [
+                                {
+                                    "type": "null"
+                                },
+                                {
+                                    "type": "boolean"
+                                },
+                                {
+                                    "type": "number"
+                                },
+                                {
+                                    "type": "string"
+                                },
+                                {
+                                    "type": "array"
+                                },
+                                {
+                                    "type": "object"
+                                }
+                            ]
+                        }
+                    }
+                },
+                "additionalProperties": false,
+                "required": [
+                    "type",
+                    "json_schema"
+                ]
+            },
             "ResponseFormat": {
                 "oneOf": [
                     {
-                        "type": "object",
-                        "properties": {
-                            "type": {
-                                "type": "string",
-                                "const": "json_schema",
-                                "default": "json_schema"
-                            },
-                            "json_schema": {
-                                "type": "object",
-                                "additionalProperties": {
-                                    "oneOf": [
-                                        {
-                                            "type": "null"
-                                        },
-                                        {
-                                            "type": "boolean"
-                                        },
-                                        {
-                                            "type": "number"
-                                        },
-                                        {
-                                            "type": "string"
-                                        },
-                                        {
-                                            "type": "array"
-                                        },
-                                        {
-                                            "type": "object"
-                                        }
-                                    ]
-                                }
-                            }
-                        },
-                        "additionalProperties": false,
-                        "required": [
-                            "type",
-                            "json_schema"
-                        ]
+                        "$ref": "#/components/schemas/JsonSchemaResponseFormat"
                     },
                     {
-                        "type": "object",
-                        "properties": {
-                            "type": {
-                                "type": "string",
-                                "const": "grammar",
-                                "default": "grammar"
-                            },
-                            "bnf": {
-                                "type": "object",
-                                "additionalProperties": {
-                                    "oneOf": [
-                                        {
-                                            "type": "null"
-                                        },
-                                        {
-                                            "type": "boolean"
-                                        },
-                                        {
-                                            "type": "number"
-                                        },
-                                        {
-                                            "type": "string"
-                                        },
-                                        {
-                                            "type": "array"
-                                        },
-                                        {
-                                            "type": "object"
-                                        }
-                                    ]
-                                }
-                            }
-                        },
-                        "additionalProperties": false,
-                        "required": [
-                            "type",
-                            "bnf"
-                        ]
+                        "$ref": "#/components/schemas/GrammarResponseFormat"
                     }
-                ]
+                ],
+                "discriminator": {
+                    "propertyName": "type",
+                    "mapping": {
+                        "json_schema": "#/components/schemas/JsonSchemaResponseFormat",
+                        "grammar": "#/components/schemas/GrammarResponseFormat"
+                    }
+                }
             },
             "ChatCompletionRequest": {
                 "type": "object",
@@ -4428,7 +4552,15 @@
                     {
                         "$ref": "#/components/schemas/ToolCallDelta"
                     }
-                ]
+                ],
+                "discriminator": {
+                    "propertyName": "type",
+                    "mapping": {
+                        "text": "#/components/schemas/TextDelta",
+                        "image": "#/components/schemas/ImageDelta",
+                        "tool_call": "#/components/schemas/ToolCallDelta"
+                    }
+                }
             },
             "ImageDelta": {
                 "type": "object",
@@ -4438,7 +4570,7 @@
                         "const": "image",
                         "default": "image"
                     },
-                    "data": {
+                    "image": {
                         "type": "string",
                         "contentEncoding": "base64"
                     }
@@ -4446,7 +4578,7 @@
                 "additionalProperties": false,
                 "required": [
                     "type",
-                    "data"
+                    "image"
                 ]
             },
             "TextDelta": {
@@ -4490,7 +4622,7 @@
                         "const": "tool_call",
                         "default": "tool_call"
                     },
-                    "content": {
+                    "tool_call": {
                         "oneOf": [
                             {
                                 "type": "string"
@@ -4507,7 +4639,7 @@
                 "additionalProperties": false,
                 "required": [
                     "type",
-                    "content",
+                    "tool_call",
                     "parse_status"
                 ]
             },
@@ -4635,8 +4767,7 @@
                         "default": "auto"
                     },
                     "tool_prompt_format": {
-                        "$ref": "#/components/schemas/ToolPromptFormat",
-                        "default": "json"
+                        "$ref": "#/components/schemas/ToolPromptFormat"
                     },
                     "max_infer_iters": {
                         "type": "integer",
@@ -4916,30 +5047,42 @@
                 "type": "object",
                 "properties": {
                     "payload": {
-                        "oneOf": [
-                            {
-                                "$ref": "#/components/schemas/AgentTurnResponseStepStartPayload"
-                            },
-                            {
-                                "$ref": "#/components/schemas/AgentTurnResponseStepProgressPayload"
-                            },
-                            {
-                                "$ref": "#/components/schemas/AgentTurnResponseStepCompletePayload"
-                            },
-                            {
-                                "$ref": "#/components/schemas/AgentTurnResponseTurnStartPayload"
-                            },
-                            {
-                                "$ref": "#/components/schemas/AgentTurnResponseTurnCompletePayload"
-                            }
-                        ]
+                        "$ref": "#/components/schemas/AgentTurnResponseEventPayload"
                     }
                 },
                 "additionalProperties": false,
                 "required": [
                     "payload"
+                ]
+            },
+            "AgentTurnResponseEventPayload": {
+                "oneOf": [
+                    {
+                        "$ref": "#/components/schemas/AgentTurnResponseStepStartPayload"
+                    },
+                    {
+                        "$ref": "#/components/schemas/AgentTurnResponseStepProgressPayload"
+                    },
+                    {
+                        "$ref": "#/components/schemas/AgentTurnResponseStepCompletePayload"
+                    },
+                    {
+                        "$ref": "#/components/schemas/AgentTurnResponseTurnStartPayload"
+                    },
+                    {
+                        "$ref": "#/components/schemas/AgentTurnResponseTurnCompletePayload"
+                    }
                 ],
-                "title": "Streamed agent execution response."
+                "discriminator": {
+                    "propertyName": "event_type",
+                    "mapping": {
+                        "step_start": "#/components/schemas/AgentTurnResponseStepStartPayload",
+                        "step_progress": "#/components/schemas/AgentTurnResponseStepProgressPayload",
+                        "step_complete": "#/components/schemas/AgentTurnResponseStepCompletePayload",
+                        "turn_start": "#/components/schemas/AgentTurnResponseTurnStartPayload",
+                        "turn_complete": "#/components/schemas/AgentTurnResponseTurnCompletePayload"
+                    }
+                }
             },
             "AgentTurnResponseStepCompletePayload": {
                 "type": "object",
@@ -4975,7 +5118,16 @@
                             {
                                 "$ref": "#/components/schemas/MemoryRetrievalStep"
                             }
-                        ]
+                        ],
+                        "discriminator": {
+                            "propertyName": "step_type",
+                            "mapping": {
+                                "inference": "#/components/schemas/InferenceStep",
+                                "tool_execution": "#/components/schemas/ToolExecutionStep",
+                                "shield_call": "#/components/schemas/ShieldCallStep",
+                                "memory_retrieval": "#/components/schemas/MemoryRetrievalStep"
+                            }
+                        }
                     }
                 },
                 "additionalProperties": false,
@@ -5176,11 +5328,8 @@
                         "const": "memory_retrieval",
                         "default": "memory_retrieval"
                     },
-                    "memory_bank_ids": {
-                        "type": "array",
-                        "items": {
-                            "type": "string"
-                        }
+                    "vector_db_ids": {
+                        "type": "string"
                     },
                     "inserted_context": {
                         "$ref": "#/components/schemas/InterleavedContent"
@@ -5191,7 +5340,7 @@
                     "turn_id",
                     "step_id",
                     "step_type",
-                    "memory_bank_ids",
+                    "vector_db_ids",
                     "inserted_context"
                 ]
             },
@@ -5378,7 +5527,16 @@
                                 {
                                     "$ref": "#/components/schemas/MemoryRetrievalStep"
                                 }
-                            ]
+                            ],
+                            "discriminator": {
+                                "propertyName": "step_type",
+                                "mapping": {
+                                    "inference": "#/components/schemas/InferenceStep",
+                                    "tool_execution": "#/components/schemas/ToolExecutionStep",
+                                    "shield_call": "#/components/schemas/ShieldCallStep",
+                                    "memory_retrieval": "#/components/schemas/MemoryRetrievalStep"
+                                }
+                            }
                         }
                     },
                     "output_message": {
@@ -5521,29 +5679,12 @@
                         "default": "app"
                     },
                     "eval_candidate": {
-                        "oneOf": [
-                            {
-                                "$ref": "#/components/schemas/ModelCandidate"
-                            },
-                            {
-                                "$ref": "#/components/schemas/AgentCandidate"
-                            }
-                        ]
+                        "$ref": "#/components/schemas/EvalCandidate"
                     },
                     "scoring_params": {
                         "type": "object",
                         "additionalProperties": {
-                            "oneOf": [
-                                {
-                                    "$ref": "#/components/schemas/LLMAsJudgeScoringFnParams"
-                                },
-                                {
-                                    "$ref": "#/components/schemas/RegexParserScoringFnParams"
-                                },
-                                {
-                                    "$ref": "#/components/schemas/BasicScoringFnParams"
-                                }
-                            ]
+                            "$ref": "#/components/schemas/ScoringFnParams"
                         }
                     },
                     "num_examples": {
@@ -5586,14 +5727,7 @@
                         "default": "benchmark"
                     },
                     "eval_candidate": {
-                        "oneOf": [
-                            {
-                                "$ref": "#/components/schemas/ModelCandidate"
-                            },
-                            {
-                                "$ref": "#/components/schemas/AgentCandidate"
-                            }
-                        ]
+                        "$ref": "#/components/schemas/EvalCandidate"
                     },
                     "num_examples": {
                         "type": "integer"
@@ -5605,6 +5739,40 @@
                     "eval_candidate"
                 ]
             },
+            "EvalCandidate": {
+                "oneOf": [
+                    {
+                        "$ref": "#/components/schemas/ModelCandidate"
+                    },
+                    {
+                        "$ref": "#/components/schemas/AgentCandidate"
+                    }
+                ],
+                "discriminator": {
+                    "propertyName": "type",
+                    "mapping": {
+                        "model": "#/components/schemas/ModelCandidate",
+                        "agent": "#/components/schemas/AgentCandidate"
+                    }
+                }
+            },
+            "EvalTaskConfig": {
+                "oneOf": [
+                    {
+                        "$ref": "#/components/schemas/BenchmarkEvalTaskConfig"
+                    },
+                    {
+                        "$ref": "#/components/schemas/AppEvalTaskConfig"
+                    }
+                ],
+                "discriminator": {
+                    "propertyName": "type",
+                    "mapping": {
+                        "benchmark": "#/components/schemas/BenchmarkEvalTaskConfig",
+                        "app": "#/components/schemas/AppEvalTaskConfig"
+                    }
+                }
+            },
             "LLMAsJudgeScoringFnParams": {
                 "type": "object",
                 "properties": {
@@ -5689,6 +5857,27 @@
                     "type"
                 ]
             },
+            "ScoringFnParams": {
+                "oneOf": [
+                    {
+                        "$ref": "#/components/schemas/LLMAsJudgeScoringFnParams"
+                    },
+                    {
+                        "$ref": "#/components/schemas/RegexParserScoringFnParams"
+                    },
+                    {
+                        "$ref": "#/components/schemas/BasicScoringFnParams"
+                    }
+                ],
+                "discriminator": {
+                    "propertyName": "type",
+                    "mapping": {
+                        "llm_as_judge": "#/components/schemas/LLMAsJudgeScoringFnParams",
+                        "regex_parser": "#/components/schemas/RegexParserScoringFnParams",
+                        "basic": "#/components/schemas/BasicScoringFnParams"
+                    }
+                }
+            },
             "EvaluateRowsRequest": {
                 "type": "object",
                 "properties": {
@@ -5727,14 +5916,7 @@
                         }
                     },
                     "task_config": {
-                        "oneOf": [
-                            {
-                                "$ref": "#/components/schemas/BenchmarkEvalTaskConfig"
-                            },
-                            {
-                                "$ref": "#/components/schemas/AppEvalTaskConfig"
-                            }
-                        ]
+                        "$ref": "#/components/schemas/EvalTaskConfig"
                     }
                 },
                 "additionalProperties": false,
@@ -5851,118 +6033,6 @@
                     "aggregated_results"
                 ]
             },
-            "GraphMemoryBank": {
-                "type": "object",
-                "properties": {
-                    "identifier": {
-                        "type": "string"
-                    },
-                    "provider_resource_id": {
-                        "type": "string"
-                    },
-                    "provider_id": {
-                        "type": "string"
-                    },
-                    "type": {
-                        "type": "string",
-                        "const": "memory_bank",
-                        "default": "memory_bank"
-                    },
-                    "memory_bank_type": {
-                        "type": "string",
-                        "const": "graph",
-                        "default": "graph"
-                    }
-                },
-                "additionalProperties": false,
-                "required": [
-                    "identifier",
-                    "provider_resource_id",
-                    "provider_id",
-                    "type",
-                    "memory_bank_type"
-                ]
-            },
-            "KeyValueMemoryBank": {
-                "type": "object",
-                "properties": {
-                    "identifier": {
-                        "type": "string"
-                    },
-                    "provider_resource_id": {
-                        "type": "string"
-                    },
-                    "provider_id": {
-                        "type": "string"
-                    },
-                    "type": {
-                        "type": "string",
-                        "const": "memory_bank",
-                        "default": "memory_bank"
-                    },
-                    "memory_bank_type": {
-                        "type": "string",
-                        "const": "keyvalue",
-                        "default": "keyvalue"
-                    }
-                },
-                "additionalProperties": false,
-                "required": [
-                    "identifier",
-                    "provider_resource_id",
-                    "provider_id",
-                    "type",
-                    "memory_bank_type"
-                ]
-            },
-            "KeywordMemoryBank": {
-                "type": "object",
-                "properties": {
-                    "identifier": {
-                        "type": "string"
-                    },
-                    "provider_resource_id": {
-                        "type": "string"
-                    },
-                    "provider_id": {
-                        "type": "string"
-                    },
-                    "type": {
-                        "type": "string",
-                        "const": "memory_bank",
-                        "default": "memory_bank"
-                    },
-                    "memory_bank_type": {
-                        "type": "string",
-                        "const": "keyword",
-                        "default": "keyword"
-                    }
-                },
-                "additionalProperties": false,
-                "required": [
-                    "identifier",
-                    "provider_resource_id",
-                    "provider_id",
-                    "type",
-                    "memory_bank_type"
-                ]
-            },
-            "MemoryBank": {
-                "oneOf": [
-                    {
-                        "$ref": "#/components/schemas/VectorMemoryBank"
-                    },
-                    {
-                        "$ref": "#/components/schemas/KeyValueMemoryBank"
-                    },
-                    {
-                        "$ref": "#/components/schemas/KeywordMemoryBank"
-                    },
-                    {
-                        "$ref": "#/components/schemas/GraphMemoryBank"
-                    }
-                ]
-            },
             "Session": {
                 "type": "object",
                 "properties": {
@@ -5981,9 +6051,6 @@
                     "started_at": {
                         "type": "string",
                         "format": "date-time"
-                    },
-                    "memory_bank": {
-                        "$ref": "#/components/schemas/MemoryBank"
                     }
                 },
                 "additionalProperties": false,
@@ -5995,53 +6062,6 @@
                 ],
                 "title": "A single session of an interaction with an Agentic System."
             },
-            "VectorMemoryBank": {
-                "type": "object",
-                "properties": {
-                    "identifier": {
-                        "type": "string"
-                    },
-                    "provider_resource_id": {
-                        "type": "string"
-                    },
-                    "provider_id": {
-                        "type": "string"
-                    },
-                    "type": {
-                        "type": "string",
-                        "const": "memory_bank",
-                        "default": "memory_bank"
-                    },
-                    "memory_bank_type": {
-                        "type": "string",
-                        "const": "vector",
-                        "default": "vector"
-                    },
-                    "embedding_model": {
-                        "type": "string"
-                    },
-                    "chunk_size_in_tokens": {
-                        "type": "integer"
-                    },
-                    "embedding_dimension": {
-                        "type": "integer",
-                        "default": 384
-                    },
-                    "overlap_size_in_tokens": {
-                        "type": "integer"
-                    }
-                },
-                "additionalProperties": false,
-                "required": [
-                    "identifier",
-                    "provider_resource_id",
-                    "provider_id",
-                    "type",
-                    "memory_bank_type",
-                    "embedding_model",
-                    "chunk_size_in_tokens"
-                ]
-            },
             "AgentStepResponse": {
                 "type": "object",
                 "properties": {
@@ -6059,7 +6079,16 @@
                             {
                                 "$ref": "#/components/schemas/MemoryRetrievalStep"
                             }
-                        ]
+                        ],
+                        "discriminator": {
+                            "propertyName": "step_type",
+                            "mapping": {
+                                "inference": "#/components/schemas/InferenceStep",
+                                "tool_execution": "#/components/schemas/ToolExecutionStep",
+                                "shield_call": "#/components/schemas/ShieldCallStep",
+                                "memory_retrieval": "#/components/schemas/MemoryRetrievalStep"
+                            }
+                        }
                     }
                 },
                 "additionalProperties": false,
@@ -6274,7 +6303,22 @@
                     {
                         "$ref": "#/components/schemas/AgentTurnInputType"
                     }
-                ]
+                ],
+                "discriminator": {
+                    "propertyName": "type",
+                    "mapping": {
+                        "string": "#/components/schemas/StringType",
+                        "number": "#/components/schemas/NumberType",
+                        "boolean": "#/components/schemas/BooleanType",
+                        "array": "#/components/schemas/ArrayType",
+                        "object": "#/components/schemas/ObjectType",
+                        "json": "#/components/schemas/JsonType",
+                        "union": "#/components/schemas/UnionType",
+                        "chat_completion_input": "#/components/schemas/ChatCompletionInputType",
+                        "completion_input": "#/components/schemas/CompletionInputType",
+                        "agent_turn_input": "#/components/schemas/AgentTurnInputType"
+                    }
+                }
             },
             "StringType": {
                 "type": "object",
@@ -6524,17 +6568,7 @@
                         "$ref": "#/components/schemas/ParamType"
                     },
                     "params": {
-                        "oneOf": [
-                            {
-                                "$ref": "#/components/schemas/LLMAsJudgeScoringFnParams"
-                            },
-                            {
-                                "$ref": "#/components/schemas/RegexParserScoringFnParams"
-                            },
-                            {
-                                "$ref": "#/components/schemas/BasicScoringFnParams"
-                            }
-                        ]
+                        "$ref": "#/components/schemas/ScoringFnParams"
                     }
                 },
                 "additionalProperties": false,
@@ -7012,6 +7046,40 @@
                     "data"
                 ]
             },
+            "VectorDB": {
+                "type": "object",
+                "properties": {
+                    "identifier": {
+                        "type": "string"
+                    },
+                    "provider_resource_id": {
+                        "type": "string"
+                    },
+                    "provider_id": {
+                        "type": "string"
+                    },
+                    "type": {
+                        "type": "string",
+                        "const": "vector_db",
+                        "default": "vector_db"
+                    },
+                    "embedding_model": {
+                        "type": "string"
+                    },
+                    "embedding_dimension": {
+                        "type": "integer"
+                    }
+                },
+                "additionalProperties": false,
+                "required": [
+                    "identifier",
+                    "provider_resource_id",
+                    "provider_id",
+                    "type",
+                    "embedding_model",
+                    "embedding_dimension"
+                ]
+            },
             "HealthInfo": {
                 "type": "object",
                 "properties": {
@@ -7024,7 +7092,7 @@
                     "status"
                 ]
             },
-            "MemoryBankDocument": {
+            "RAGDocument": {
                 "type": "object",
                 "properties": {
                     "document_id": {
@@ -7085,16 +7153,74 @@
                     "metadata"
                 ]
             },
-            "InsertDocumentsRequest": {
+            "InsertRequest": {
                 "type": "object",
                 "properties": {
-                    "bank_id": {
-                        "type": "string"
-                    },
                     "documents": {
                         "type": "array",
                         "items": {
-                            "$ref": "#/components/schemas/MemoryBankDocument"
+                            "$ref": "#/components/schemas/RAGDocument"
+                        }
+                    },
+                    "vector_db_id": {
+                        "type": "string"
+                    },
+                    "chunk_size_in_tokens": {
+                        "type": "integer"
+                    }
+                },
+                "additionalProperties": false,
+                "required": [
+                    "documents",
+                    "vector_db_id",
+                    "chunk_size_in_tokens"
+                ]
+            },
+            "InsertChunksRequest": {
+                "type": "object",
+                "properties": {
+                    "vector_db_id": {
+                        "type": "string"
+                    },
+                    "chunks": {
+                        "type": "array",
+                        "items": {
+                            "type": "object",
+                            "properties": {
+                                "content": {
+                                    "$ref": "#/components/schemas/InterleavedContent"
+                                },
+                                "metadata": {
+                                    "type": "object",
+                                    "additionalProperties": {
+                                        "oneOf": [
+                                            {
+                                                "type": "null"
+                                            },
+                                            {
+                                                "type": "boolean"
+                                            },
+                                            {
+                                                "type": "number"
+                                            },
+                                            {
+                                                "type": "string"
+                                            },
+                                            {
+                                                "type": "array"
+                                            },
+                                            {
+                                                "type": "object"
+                                            }
+                                        ]
+                                    }
+                                }
+                            },
+                            "additionalProperties": false,
+                            "required": [
+                                "content",
+                                "metadata"
+                            ]
                         }
                     },
                     "ttl_seconds": {
@@ -7103,8 +7229,8 @@
                 },
                 "additionalProperties": false,
                 "required": [
-                    "bank_id",
-                    "documents"
+                    "vector_db_id",
+                    "chunks"
                 ]
             },
             "InvokeToolRequest": {
@@ -7113,7 +7239,7 @@
                     "tool_name": {
                         "type": "string"
                     },
-                    "args": {
+                    "kwargs": {
                         "type": "object",
                         "additionalProperties": {
                             "oneOf": [
@@ -7142,7 +7268,7 @@
                 "additionalProperties": false,
                 "required": [
                     "tool_name",
-                    "args"
+                    "kwargs"
                 ]
             },
             "ToolInvocationResult": {
@@ -7193,21 +7319,6 @@
                     "data"
                 ]
             },
-            "ListMemoryBanksResponse": {
-                "type": "object",
-                "properties": {
-                    "data": {
-                        "type": "array",
-                        "items": {
-                            "$ref": "#/components/schemas/MemoryBank"
-                        }
-                    }
-                },
-                "additionalProperties": false,
-                "required": [
-                    "data"
-                ]
-            },
             "ListModelsResponse": {
                 "type": "object",
                 "properties": {
@@ -7356,6 +7467,42 @@
                     "data"
                 ]
             },
+            "ListVectorDBsResponse": {
+                "type": "object",
+                "properties": {
+                    "data": {
+                        "type": "array",
+                        "items": {
+                            "$ref": "#/components/schemas/VectorDB"
+                        }
+                    }
+                },
+                "additionalProperties": false,
+                "required": [
+                    "data"
+                ]
+            },
+            "Event": {
+                "oneOf": [
+                    {
+                        "$ref": "#/components/schemas/UnstructuredLogEvent"
+                    },
+                    {
+                        "$ref": "#/components/schemas/MetricEvent"
+                    },
+                    {
+                        "$ref": "#/components/schemas/StructuredLogEvent"
+                    }
+                ],
+                "discriminator": {
+                    "propertyName": "type",
+                    "mapping": {
+                        "unstructured_log": "#/components/schemas/UnstructuredLogEvent",
+                        "metric": "#/components/schemas/MetricEvent",
+                        "structured_log": "#/components/schemas/StructuredLogEvent"
+                    }
+                }
+            },
             "LogSeverity": {
                 "type": "string",
                 "enum": [
@@ -7521,14 +7668,7 @@
                         "default": "structured_log"
                     },
                     "payload": {
-                        "oneOf": [
-                            {
-                                "$ref": "#/components/schemas/SpanStartPayload"
-                            },
-                            {
-                                "$ref": "#/components/schemas/SpanEndPayload"
-                            }
-                        ]
+                        "$ref": "#/components/schemas/StructuredLogPayload"
                     }
                 },
                 "additionalProperties": false,
@@ -7540,6 +7680,23 @@
                     "payload"
                 ]
             },
+            "StructuredLogPayload": {
+                "oneOf": [
+                    {
+                        "$ref": "#/components/schemas/SpanStartPayload"
+                    },
+                    {
+                        "$ref": "#/components/schemas/SpanEndPayload"
+                    }
+                ],
+                "discriminator": {
+                    "propertyName": "type",
+                    "mapping": {
+                        "span_start": "#/components/schemas/SpanStartPayload",
+                        "span_end": "#/components/schemas/SpanEndPayload"
+                    }
+                }
+            },
             "UnstructuredLogEvent": {
                 "type": "object",
                 "properties": {
@@ -7604,17 +7761,7 @@
                 "type": "object",
                 "properties": {
                     "event": {
-                        "oneOf": [
-                            {
-                                "$ref": "#/components/schemas/UnstructuredLogEvent"
-                            },
-                            {
-                                "$ref": "#/components/schemas/MetricEvent"
-                            },
-                            {
-                                "$ref": "#/components/schemas/StructuredLogEvent"
-                            }
-                        ]
+                        "$ref": "#/components/schemas/Event"
                     },
                     "ttl_seconds": {
                         "type": "integer"
@@ -7873,10 +8020,121 @@
                     "job_uuid"
                 ]
             },
-            "QueryDocumentsRequest": {
+            "DefaultRAGQueryGeneratorConfig": {
                 "type": "object",
                 "properties": {
-                    "bank_id": {
+                    "type": {
+                        "type": "string",
+                        "const": "default",
+                        "default": "default"
+                    },
+                    "separator": {
+                        "type": "string",
+                        "default": " "
+                    }
+                },
+                "additionalProperties": false,
+                "required": [
+                    "type",
+                    "separator"
+                ]
+            },
+            "LLMRAGQueryGeneratorConfig": {
+                "type": "object",
+                "properties": {
+                    "type": {
+                        "type": "string",
+                        "const": "llm",
+                        "default": "llm"
+                    },
+                    "model": {
+                        "type": "string"
+                    },
+                    "template": {
+                        "type": "string"
+                    }
+                },
+                "additionalProperties": false,
+                "required": [
+                    "type",
+                    "model",
+                    "template"
+                ]
+            },
+            "RAGQueryConfig": {
+                "type": "object",
+                "properties": {
+                    "query_generator_config": {
+                        "$ref": "#/components/schemas/RAGQueryGeneratorConfig"
+                    },
+                    "max_tokens_in_context": {
+                        "type": "integer",
+                        "default": 4096
+                    },
+                    "max_chunks": {
+                        "type": "integer",
+                        "default": 5
+                    }
+                },
+                "additionalProperties": false,
+                "required": [
+                    "query_generator_config",
+                    "max_tokens_in_context",
+                    "max_chunks"
+                ]
+            },
+            "RAGQueryGeneratorConfig": {
+                "oneOf": [
+                    {
+                        "$ref": "#/components/schemas/DefaultRAGQueryGeneratorConfig"
+                    },
+                    {
+                        "$ref": "#/components/schemas/LLMRAGQueryGeneratorConfig"
+                    }
+                ],
+                "discriminator": {
+                    "propertyName": "type",
+                    "mapping": {
+                        "default": "#/components/schemas/DefaultRAGQueryGeneratorConfig",
+                        "llm": "#/components/schemas/LLMRAGQueryGeneratorConfig"
+                    }
+                }
+            },
+            "QueryRequest": {
+                "type": "object",
+                "properties": {
+                    "content": {
+                        "$ref": "#/components/schemas/InterleavedContent"
+                    },
+                    "vector_db_ids": {
+                        "type": "array",
+                        "items": {
+                            "type": "string"
+                        }
+                    },
+                    "query_config": {
+                        "$ref": "#/components/schemas/RAGQueryConfig"
+                    }
+                },
+                "additionalProperties": false,
+                "required": [
+                    "content",
+                    "vector_db_ids"
+                ]
+            },
+            "RAGQueryResult": {
+                "type": "object",
+                "properties": {
+                    "content": {
+                        "$ref": "#/components/schemas/InterleavedContent"
+                    }
+                },
+                "additionalProperties": false
+            },
+            "QueryChunksRequest": {
+                "type": "object",
+                "properties": {
+                    "vector_db_id": {
                         "type": "string"
                     },
                     "query": {
@@ -7910,11 +8168,11 @@
                 },
                 "additionalProperties": false,
                 "required": [
-                    "bank_id",
+                    "vector_db_id",
                     "query"
                 ]
             },
-            "QueryDocumentsResponse": {
+            "QueryChunksResponse": {
                 "type": "object",
                 "properties": {
                     "chunks": {
@@ -7925,18 +8183,36 @@
                                 "content": {
                                     "$ref": "#/components/schemas/InterleavedContent"
                                 },
-                                "token_count": {
-                                    "type": "integer"
-                                },
-                                "document_id": {
-                                    "type": "string"
+                                "metadata": {
+                                    "type": "object",
+                                    "additionalProperties": {
+                                        "oneOf": [
+                                            {
+                                                "type": "null"
+                                            },
+                                            {
+                                                "type": "boolean"
+                                            },
+                                            {
+                                                "type": "number"
+                                            },
+                                            {
+                                                "type": "string"
+                                            },
+                                            {
+                                                "type": "array"
+                                            },
+                                            {
+                                                "type": "object"
+                                            }
+                                        ]
+                                    }
                                 }
                             },
                             "additionalProperties": false,
                             "required": [
                                 "content",
-                                "token_count",
-                                "document_id"
+                                "metadata"
                             ]
                         }
                     },
@@ -8139,108 +8415,6 @@
                     "scoring_functions"
                 ]
             },
-            "GraphMemoryBankParams": {
-                "type": "object",
-                "properties": {
-                    "memory_bank_type": {
-                        "type": "string",
-                        "const": "graph",
-                        "default": "graph"
-                    }
-                },
-                "additionalProperties": false,
-                "required": [
-                    "memory_bank_type"
-                ]
-            },
-            "KeyValueMemoryBankParams": {
-                "type": "object",
-                "properties": {
-                    "memory_bank_type": {
-                        "type": "string",
-                        "const": "keyvalue",
-                        "default": "keyvalue"
-                    }
-                },
-                "additionalProperties": false,
-                "required": [
-                    "memory_bank_type"
-                ]
-            },
-            "KeywordMemoryBankParams": {
-                "type": "object",
-                "properties": {
-                    "memory_bank_type": {
-                        "type": "string",
-                        "const": "keyword",
-                        "default": "keyword"
-                    }
-                },
-                "additionalProperties": false,
-                "required": [
-                    "memory_bank_type"
-                ]
-            },
-            "VectorMemoryBankParams": {
-                "type": "object",
-                "properties": {
-                    "memory_bank_type": {
-                        "type": "string",
-                        "const": "vector",
-                        "default": "vector"
-                    },
-                    "embedding_model": {
-                        "type": "string"
-                    },
-                    "chunk_size_in_tokens": {
-                        "type": "integer"
-                    },
-                    "overlap_size_in_tokens": {
-                        "type": "integer"
-                    }
-                },
-                "additionalProperties": false,
-                "required": [
-                    "memory_bank_type",
-                    "embedding_model",
-                    "chunk_size_in_tokens"
-                ]
-            },
-            "RegisterMemoryBankRequest": {
-                "type": "object",
-                "properties": {
-                    "memory_bank_id": {
-                        "type": "string"
-                    },
-                    "params": {
-                        "oneOf": [
-                            {
-                                "$ref": "#/components/schemas/VectorMemoryBankParams"
-                            },
-                            {
-                                "$ref": "#/components/schemas/KeyValueMemoryBankParams"
-                            },
-                            {
-                                "$ref": "#/components/schemas/KeywordMemoryBankParams"
-                            },
-                            {
-                                "$ref": "#/components/schemas/GraphMemoryBankParams"
-                            }
-                        ]
-                    },
-                    "provider_id": {
-                        "type": "string"
-                    },
-                    "provider_memory_bank_id": {
-                        "type": "string"
-                    }
-                },
-                "additionalProperties": false,
-                "required": [
-                    "memory_bank_id",
-                    "params"
-                ]
-            },
             "RegisterModelRequest": {
                 "type": "object",
                 "properties": {
@@ -8306,17 +8480,7 @@
                         "type": "string"
                     },
                     "params": {
-                        "oneOf": [
-                            {
-                                "$ref": "#/components/schemas/LLMAsJudgeScoringFnParams"
-                            },
-                            {
-                                "$ref": "#/components/schemas/RegexParserScoringFnParams"
-                            },
-                            {
-                                "$ref": "#/components/schemas/BasicScoringFnParams"
-                            }
-                        ]
+                        "$ref": "#/components/schemas/ScoringFnParams"
                     }
                 },
                 "additionalProperties": false,
@@ -8413,18 +8577,36 @@
                     "provider_id"
                 ]
             },
+            "RegisterVectorDbRequest": {
+                "type": "object",
+                "properties": {
+                    "vector_db_id": {
+                        "type": "string"
+                    },
+                    "embedding_model": {
+                        "type": "string"
+                    },
+                    "embedding_dimension": {
+                        "type": "integer"
+                    },
+                    "provider_id": {
+                        "type": "string"
+                    },
+                    "provider_vector_db_id": {
+                        "type": "string"
+                    }
+                },
+                "additionalProperties": false,
+                "required": [
+                    "vector_db_id",
+                    "embedding_model"
+                ]
+            },
             "RunEvalRequest": {
                 "type": "object",
                 "properties": {
                     "task_config": {
-                        "oneOf": [
-                            {
-                                "$ref": "#/components/schemas/BenchmarkEvalTaskConfig"
-                            },
-                            {
-                                "$ref": "#/components/schemas/AppEvalTaskConfig"
-                            }
-                        ]
+                        "$ref": "#/components/schemas/EvalTaskConfig"
                     }
                 },
                 "additionalProperties": false,
@@ -8563,17 +8745,7 @@
                         "additionalProperties": {
                             "oneOf": [
                                 {
-                                    "oneOf": [
-                                        {
-                                            "$ref": "#/components/schemas/LLMAsJudgeScoringFnParams"
-                                        },
-                                        {
-                                            "$ref": "#/components/schemas/RegexParserScoringFnParams"
-                                        },
-                                        {
-                                            "$ref": "#/components/schemas/BasicScoringFnParams"
-                                        }
-                                    ]
+                                    "$ref": "#/components/schemas/ScoringFnParams"
                                 },
                                 {
                                     "type": "null"
@@ -8614,17 +8786,7 @@
                         "additionalProperties": {
                             "oneOf": [
                                 {
-                                    "oneOf": [
-                                        {
-                                            "$ref": "#/components/schemas/LLMAsJudgeScoringFnParams"
-                                        },
-                                        {
-                                            "$ref": "#/components/schemas/RegexParserScoringFnParams"
-                                        },
-                                        {
-                                            "$ref": "#/components/schemas/BasicScoringFnParams"
-                                        }
-                                    ]
+                                    "$ref": "#/components/schemas/ScoringFnParams"
                                 },
                                 {
                                     "type": "null"
@@ -8661,6 +8823,23 @@
                     "results"
                 ]
             },
+            "AlgorithmConfig": {
+                "oneOf": [
+                    {
+                        "$ref": "#/components/schemas/LoraFinetuningConfig"
+                    },
+                    {
+                        "$ref": "#/components/schemas/QATFinetuningConfig"
+                    }
+                ],
+                "discriminator": {
+                    "propertyName": "type",
+                    "mapping": {
+                        "LoRA": "#/components/schemas/LoraFinetuningConfig",
+                        "QAT": "#/components/schemas/QATFinetuningConfig"
+                    }
+                }
+            },
             "LoraFinetuningConfig": {
                 "type": "object",
                 "properties": {
@@ -8794,14 +8973,7 @@
                         "type": "string"
                     },
                     "algorithm_config": {
-                        "oneOf": [
-                            {
-                                "$ref": "#/components/schemas/LoraFinetuningConfig"
-                            },
-                            {
-                                "$ref": "#/components/schemas/QATFinetuningConfig"
-                            }
-                        ]
+                        "$ref": "#/components/schemas/AlgorithmConfig"
                     }
                 },
                 "additionalProperties": false,
@@ -8958,7 +9130,11 @@
         },
         {
             "name": "AgentTurnResponseEvent",
-            "description": "Streamed agent execution response.\n\n<SchemaDefinition schemaRef=\"#/components/schemas/AgentTurnResponseEvent\" />"
+            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/AgentTurnResponseEvent\" />"
+        },
+        {
+            "name": "AgentTurnResponseEventPayload",
+            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/AgentTurnResponseEventPayload\" />"
         },
         {
             "name": "AgentTurnResponseStepCompletePayload",
@@ -8991,6 +9167,10 @@
             "name": "AggregationFunctionType",
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/AggregationFunctionType\" />"
         },
+        {
+            "name": "AlgorithmConfig",
+            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/AlgorithmConfig\" />"
+        },
         {
             "name": "AppEvalTaskConfig",
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/AppEvalTaskConfig\" />"
@@ -9128,6 +9308,10 @@
         {
             "name": "Datasets"
         },
+        {
+            "name": "DefaultRAGQueryGeneratorConfig",
+            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/DefaultRAGQueryGeneratorConfig\" />"
+        },
         {
             "name": "EfficiencyConfig",
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/EfficiencyConfig\" />"
@@ -9143,10 +9327,18 @@
         {
             "name": "Eval"
         },
+        {
+            "name": "EvalCandidate",
+            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/EvalCandidate\" />"
+        },
         {
             "name": "EvalTask",
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/EvalTask\" />"
         },
+        {
+            "name": "EvalTaskConfig",
+            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/EvalTaskConfig\" />"
+        },
         {
             "name": "EvalTasks"
         },
@@ -9159,12 +9351,12 @@
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/EvaluateRowsRequest\" />"
         },
         {
-            "name": "GraphMemoryBank",
-            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/GraphMemoryBank\" />"
+            "name": "Event",
+            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/Event\" />"
         },
         {
-            "name": "GraphMemoryBankParams",
-            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/GraphMemoryBankParams\" />"
+            "name": "GrammarResponseFormat",
+            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/GrammarResponseFormat\" />"
         },
         {
             "name": "GreedySamplingStrategy",
@@ -9190,8 +9382,12 @@
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/InferenceStep\" />"
         },
         {
-            "name": "InsertDocumentsRequest",
-            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/InsertDocumentsRequest\" />"
+            "name": "InsertChunksRequest",
+            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/InsertChunksRequest\" />"
+        },
+        {
+            "name": "InsertRequest",
+            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/InsertRequest\" />"
         },
         {
             "name": "Inspect"
@@ -9216,30 +9412,22 @@
             "name": "JobStatus",
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/JobStatus\" />"
         },
+        {
+            "name": "JsonSchemaResponseFormat",
+            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/JsonSchemaResponseFormat\" />"
+        },
         {
             "name": "JsonType",
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/JsonType\" />"
         },
-        {
-            "name": "KeyValueMemoryBank",
-            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/KeyValueMemoryBank\" />"
-        },
-        {
-            "name": "KeyValueMemoryBankParams",
-            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/KeyValueMemoryBankParams\" />"
-        },
-        {
-            "name": "KeywordMemoryBank",
-            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/KeywordMemoryBank\" />"
-        },
-        {
-            "name": "KeywordMemoryBankParams",
-            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/KeywordMemoryBankParams\" />"
-        },
         {
             "name": "LLMAsJudgeScoringFnParams",
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/LLMAsJudgeScoringFnParams\" />"
         },
+        {
+            "name": "LLMRAGQueryGeneratorConfig",
+            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/LLMRAGQueryGeneratorConfig\" />"
+        },
         {
             "name": "ListDatasetsResponse",
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/ListDatasetsResponse\" />"
@@ -9248,10 +9436,6 @@
             "name": "ListEvalTasksResponse",
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/ListEvalTasksResponse\" />"
         },
-        {
-            "name": "ListMemoryBanksResponse",
-            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/ListMemoryBanksResponse\" />"
-        },
         {
             "name": "ListModelsResponse",
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/ListModelsResponse\" />"
@@ -9284,6 +9468,10 @@
             "name": "ListToolsResponse",
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/ListToolsResponse\" />"
         },
+        {
+            "name": "ListVectorDBsResponse",
+            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/ListVectorDBsResponse\" />"
+        },
         {
             "name": "LogEventRequest",
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/LogEventRequest\" />"
@@ -9296,20 +9484,6 @@
             "name": "LoraFinetuningConfig",
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/LoraFinetuningConfig\" />"
         },
-        {
-            "name": "Memory"
-        },
-        {
-            "name": "MemoryBank",
-            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/MemoryBank\" />"
-        },
-        {
-            "name": "MemoryBankDocument",
-            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/MemoryBankDocument\" />"
-        },
-        {
-            "name": "MemoryBanks"
-        },
         {
             "name": "MemoryRetrievalStep",
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/MemoryRetrievalStep\" />"
@@ -9388,6 +9562,14 @@
             "name": "QATFinetuningConfig",
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/QATFinetuningConfig\" />"
         },
+        {
+            "name": "QueryChunksRequest",
+            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/QueryChunksRequest\" />"
+        },
+        {
+            "name": "QueryChunksResponse",
+            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/QueryChunksResponse\" />"
+        },
         {
             "name": "QueryCondition",
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/QueryCondition\" />"
@@ -9397,12 +9579,8 @@
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/QueryConditionOp\" />"
         },
         {
-            "name": "QueryDocumentsRequest",
-            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/QueryDocumentsRequest\" />"
-        },
-        {
-            "name": "QueryDocumentsResponse",
-            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/QueryDocumentsResponse\" />"
+            "name": "QueryRequest",
+            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/QueryRequest\" />"
         },
         {
             "name": "QuerySpanTreeResponse",
@@ -9416,6 +9594,22 @@
             "name": "QueryTracesResponse",
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/QueryTracesResponse\" />"
         },
+        {
+            "name": "RAGDocument",
+            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/RAGDocument\" />"
+        },
+        {
+            "name": "RAGQueryConfig",
+            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/RAGQueryConfig\" />"
+        },
+        {
+            "name": "RAGQueryGeneratorConfig",
+            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/RAGQueryGeneratorConfig\" />"
+        },
+        {
+            "name": "RAGQueryResult",
+            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/RAGQueryResult\" />"
+        },
         {
             "name": "RegexParserScoringFnParams",
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/RegexParserScoringFnParams\" />"
@@ -9428,10 +9622,6 @@
             "name": "RegisterEvalTaskRequest",
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/RegisterEvalTaskRequest\" />"
         },
-        {
-            "name": "RegisterMemoryBankRequest",
-            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/RegisterMemoryBankRequest\" />"
-        },
         {
             "name": "RegisterModelRequest",
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/RegisterModelRequest\" />"
@@ -9448,6 +9638,10 @@
             "name": "RegisterToolGroupRequest",
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/RegisterToolGroupRequest\" />"
         },
+        {
+            "name": "RegisterVectorDbRequest",
+            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/RegisterVectorDbRequest\" />"
+        },
         {
             "name": "ResponseFormat",
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/ResponseFormat\" />"
@@ -9506,6 +9700,10 @@
             "name": "ScoringFn",
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/ScoringFn\" />"
         },
+        {
+            "name": "ScoringFnParams",
+            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/ScoringFnParams\" />"
+        },
         {
             "name": "ScoringFunctions"
         },
@@ -9560,6 +9758,10 @@
             "name": "StructuredLogEvent",
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/StructuredLogEvent\" />"
         },
+        {
+            "name": "StructuredLogPayload",
+            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/StructuredLogPayload\" />"
+        },
         {
             "name": "SupervisedFineTuneRequest",
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/SupervisedFineTuneRequest\" />"
@@ -9701,12 +9903,14 @@
             "description": "<SchemaDefinition schemaRef=\"#/components/schemas/UserMessage\" />"
         },
         {
-            "name": "VectorMemoryBank",
-            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/VectorMemoryBank\" />"
+            "name": "VectorDB",
+            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/VectorDB\" />"
         },
         {
-            "name": "VectorMemoryBankParams",
-            "description": "<SchemaDefinition schemaRef=\"#/components/schemas/VectorMemoryBankParams\" />"
+            "name": "VectorDBs"
+        },
+        {
+            "name": "VectorIO"
         },
         {
             "name": "VersionInfo",
@@ -9729,8 +9933,6 @@
                 "EvalTasks",
                 "Inference",
                 "Inspect",
-                "Memory",
-                "MemoryBanks",
                 "Models",
                 "PostTraining (Coming Soon)",
                 "Safety",
@@ -9740,7 +9942,9 @@
                 "SyntheticDataGeneration (Coming Soon)",
                 "Telemetry",
                 "ToolGroups",
-                "ToolRuntime"
+                "ToolRuntime",
+                "VectorDBs",
+                "VectorIO"
             ]
         },
         {
@@ -9754,6 +9958,7 @@
                 "AgentTool",
                 "AgentTurnInputType",
                 "AgentTurnResponseEvent",
+                "AgentTurnResponseEventPayload",
                 "AgentTurnResponseStepCompletePayload",
                 "AgentTurnResponseStepProgressPayload",
                 "AgentTurnResponseStepStartPayload",
@@ -9761,6 +9966,7 @@
                 "AgentTurnResponseTurnCompletePayload",
                 "AgentTurnResponseTurnStartPayload",
                 "AggregationFunctionType",
+                "AlgorithmConfig",
                 "AppEvalTaskConfig",
                 "AppendRowsRequest",
                 "ArrayType",
@@ -9793,34 +9999,35 @@
                 "DataConfig",
                 "Dataset",
                 "DatasetFormat",
+                "DefaultRAGQueryGeneratorConfig",
                 "EfficiencyConfig",
                 "EmbeddingsRequest",
                 "EmbeddingsResponse",
+                "EvalCandidate",
                 "EvalTask",
+                "EvalTaskConfig",
                 "EvaluateResponse",
                 "EvaluateRowsRequest",
-                "GraphMemoryBank",
-                "GraphMemoryBankParams",
+                "Event",
+                "GrammarResponseFormat",
                 "GreedySamplingStrategy",
                 "HealthInfo",
                 "ImageContentItem",
                 "ImageDelta",
                 "InferenceStep",
-                "InsertDocumentsRequest",
+                "InsertChunksRequest",
+                "InsertRequest",
                 "InterleavedContent",
                 "InterleavedContentItem",
                 "InvokeToolRequest",
                 "Job",
                 "JobStatus",
+                "JsonSchemaResponseFormat",
                 "JsonType",
-                "KeyValueMemoryBank",
-                "KeyValueMemoryBankParams",
-                "KeywordMemoryBank",
-                "KeywordMemoryBankParams",
                 "LLMAsJudgeScoringFnParams",
+                "LLMRAGQueryGeneratorConfig",
                 "ListDatasetsResponse",
                 "ListEvalTasksResponse",
-                "ListMemoryBanksResponse",
                 "ListModelsResponse",
                 "ListPostTrainingJobsResponse",
                 "ListProvidersResponse",
@@ -9829,11 +10036,10 @@
                 "ListShieldsResponse",
                 "ListToolGroupsResponse",
                 "ListToolsResponse",
+                "ListVectorDBsResponse",
                 "LogEventRequest",
                 "LogSeverity",
                 "LoraFinetuningConfig",
-                "MemoryBank",
-                "MemoryBankDocument",
                 "MemoryRetrievalStep",
                 "Message",
                 "MetricEvent",
@@ -9852,21 +10058,26 @@
                 "PreferenceOptimizeRequest",
                 "ProviderInfo",
                 "QATFinetuningConfig",
+                "QueryChunksRequest",
+                "QueryChunksResponse",
                 "QueryCondition",
                 "QueryConditionOp",
-                "QueryDocumentsRequest",
-                "QueryDocumentsResponse",
+                "QueryRequest",
                 "QuerySpanTreeResponse",
                 "QuerySpansResponse",
                 "QueryTracesResponse",
+                "RAGDocument",
+                "RAGQueryConfig",
+                "RAGQueryGeneratorConfig",
+                "RAGQueryResult",
                 "RegexParserScoringFnParams",
                 "RegisterDatasetRequest",
                 "RegisterEvalTaskRequest",
-                "RegisterMemoryBankRequest",
                 "RegisterModelRequest",
                 "RegisterScoringFunctionRequest",
                 "RegisterShieldRequest",
                 "RegisterToolGroupRequest",
+                "RegisterVectorDbRequest",
                 "ResponseFormat",
                 "RouteInfo",
                 "RunEvalRequest",
@@ -9880,6 +10091,7 @@
                 "ScoreRequest",
                 "ScoreResponse",
                 "ScoringFn",
+                "ScoringFnParams",
                 "ScoringResult",
                 "Session",
                 "Shield",
@@ -9892,6 +10104,7 @@
                 "StopReason",
                 "StringType",
                 "StructuredLogEvent",
+                "StructuredLogPayload",
                 "SupervisedFineTuneRequest",
                 "SyntheticDataGenerateRequest",
                 "SyntheticDataGenerationResponse",
@@ -9924,8 +10137,7 @@
                 "UnionType",
                 "UnstructuredLogEvent",
                 "UserMessage",
-                "VectorMemoryBank",
-                "VectorMemoryBankParams",
+                "VectorDB",
                 "VersionInfo",
                 "ViolationLevel"
             ]
diff --git a/docs/resources/llama-stack-spec.yaml b/docs/resources/llama-stack-spec.yaml
index 9aeac6db3..a7095716c 100644
--- a/docs/resources/llama-stack-spec.yaml
+++ b/docs/resources/llama-stack-spec.yaml
@@ -45,7 +45,6 @@ components:
           default: auto
         tool_prompt_format:
           $ref: '#/components/schemas/ToolPromptFormat'
-          default: json
         toolgroups:
           items:
             $ref: '#/components/schemas/AgentTool'
@@ -76,6 +75,13 @@ components:
       additionalProperties: false
       properties:
         step:
+          discriminator:
+            mapping:
+              inference: '#/components/schemas/InferenceStep'
+              memory_retrieval: '#/components/schemas/MemoryRetrievalStep'
+              shield_call: '#/components/schemas/ShieldCallStep'
+              tool_execution: '#/components/schemas/ToolExecutionStep'
+            propertyName: step_type
           oneOf:
           - $ref: '#/components/schemas/InferenceStep'
           - $ref: '#/components/schemas/ToolExecutionStep'
@@ -119,16 +125,25 @@ components:
       additionalProperties: false
       properties:
         payload:
-          oneOf:
-          - $ref: '#/components/schemas/AgentTurnResponseStepStartPayload'
-          - $ref: '#/components/schemas/AgentTurnResponseStepProgressPayload'
-          - $ref: '#/components/schemas/AgentTurnResponseStepCompletePayload'
-          - $ref: '#/components/schemas/AgentTurnResponseTurnStartPayload'
-          - $ref: '#/components/schemas/AgentTurnResponseTurnCompletePayload'
+          $ref: '#/components/schemas/AgentTurnResponseEventPayload'
       required:
       - payload
-      title: Streamed agent execution response.
       type: object
+    AgentTurnResponseEventPayload:
+      discriminator:
+        mapping:
+          step_complete: '#/components/schemas/AgentTurnResponseStepCompletePayload'
+          step_progress: '#/components/schemas/AgentTurnResponseStepProgressPayload'
+          step_start: '#/components/schemas/AgentTurnResponseStepStartPayload'
+          turn_complete: '#/components/schemas/AgentTurnResponseTurnCompletePayload'
+          turn_start: '#/components/schemas/AgentTurnResponseTurnStartPayload'
+        propertyName: event_type
+      oneOf:
+      - $ref: '#/components/schemas/AgentTurnResponseStepStartPayload'
+      - $ref: '#/components/schemas/AgentTurnResponseStepProgressPayload'
+      - $ref: '#/components/schemas/AgentTurnResponseStepCompletePayload'
+      - $ref: '#/components/schemas/AgentTurnResponseTurnStartPayload'
+      - $ref: '#/components/schemas/AgentTurnResponseTurnCompletePayload'
     AgentTurnResponseStepCompletePayload:
       additionalProperties: false
       properties:
@@ -137,6 +152,13 @@ components:
           default: step_complete
           type: string
         step_details:
+          discriminator:
+            mapping:
+              inference: '#/components/schemas/InferenceStep'
+              memory_retrieval: '#/components/schemas/MemoryRetrievalStep'
+              shield_call: '#/components/schemas/ShieldCallStep'
+              tool_execution: '#/components/schemas/ToolExecutionStep'
+            propertyName: step_type
           oneOf:
           - $ref: '#/components/schemas/InferenceStep'
           - $ref: '#/components/schemas/ToolExecutionStep'
@@ -254,21 +276,25 @@ components:
       - categorical_count
       - accuracy
       type: string
+    AlgorithmConfig:
+      discriminator:
+        mapping:
+          LoRA: '#/components/schemas/LoraFinetuningConfig'
+          QAT: '#/components/schemas/QATFinetuningConfig'
+        propertyName: type
+      oneOf:
+      - $ref: '#/components/schemas/LoraFinetuningConfig'
+      - $ref: '#/components/schemas/QATFinetuningConfig'
     AppEvalTaskConfig:
       additionalProperties: false
       properties:
         eval_candidate:
-          oneOf:
-          - $ref: '#/components/schemas/ModelCandidate'
-          - $ref: '#/components/schemas/AgentCandidate'
+          $ref: '#/components/schemas/EvalCandidate'
         num_examples:
           type: integer
         scoring_params:
           additionalProperties:
-            oneOf:
-            - $ref: '#/components/schemas/LLMAsJudgeScoringFnParams'
-            - $ref: '#/components/schemas/RegexParserScoringFnParams'
-            - $ref: '#/components/schemas/BasicScoringFnParams'
+            $ref: '#/components/schemas/ScoringFnParams'
           type: object
         type:
           const: app
@@ -402,9 +428,7 @@ components:
       additionalProperties: false
       properties:
         eval_candidate:
-          oneOf:
-          - $ref: '#/components/schemas/ModelCandidate'
-          - $ref: '#/components/schemas/AgentCandidate'
+          $ref: '#/components/schemas/EvalCandidate'
         num_examples:
           type: integer
         type:
@@ -619,6 +643,12 @@ components:
       title: streamed completion response.
       type: object
     ContentDelta:
+      discriminator:
+        mapping:
+          image: '#/components/schemas/ImageDelta'
+          text: '#/components/schemas/TextDelta'
+          tool_call: '#/components/schemas/ToolCallDelta'
+        propertyName: type
       oneOf:
       - $ref: '#/components/schemas/TextDelta'
       - $ref: '#/components/schemas/ImageDelta'
@@ -761,6 +791,20 @@ components:
       - instruct
       - dialog
       type: string
+    DefaultRAGQueryGeneratorConfig:
+      additionalProperties: false
+      properties:
+        separator:
+          default: ' '
+          type: string
+        type:
+          const: default
+          default: default
+          type: string
+      required:
+      - type
+      - separator
+      type: object
     EfficiencyConfig:
       additionalProperties: false
       properties:
@@ -802,6 +846,15 @@ components:
       required:
       - embeddings
       type: object
+    EvalCandidate:
+      discriminator:
+        mapping:
+          agent: '#/components/schemas/AgentCandidate'
+          model: '#/components/schemas/ModelCandidate'
+        propertyName: type
+      oneOf:
+      - $ref: '#/components/schemas/ModelCandidate'
+      - $ref: '#/components/schemas/AgentCandidate'
     EvalTask:
       additionalProperties: false
       properties:
@@ -840,6 +893,15 @@ components:
       - scoring_functions
       - metadata
       type: object
+    EvalTaskConfig:
+      discriminator:
+        mapping:
+          app: '#/components/schemas/AppEvalTaskConfig'
+          benchmark: '#/components/schemas/BenchmarkEvalTaskConfig'
+        propertyName: type
+      oneOf:
+      - $ref: '#/components/schemas/BenchmarkEvalTaskConfig'
+      - $ref: '#/components/schemas/AppEvalTaskConfig'
     EvaluateResponse:
       additionalProperties: false
       properties:
@@ -883,47 +945,43 @@ components:
             type: string
           type: array
         task_config:
-          oneOf:
-          - $ref: '#/components/schemas/BenchmarkEvalTaskConfig'
-          - $ref: '#/components/schemas/AppEvalTaskConfig'
+          $ref: '#/components/schemas/EvalTaskConfig'
       required:
       - input_rows
       - scoring_functions
       - task_config
       type: object
-    GraphMemoryBank:
+    Event:
+      discriminator:
+        mapping:
+          metric: '#/components/schemas/MetricEvent'
+          structured_log: '#/components/schemas/StructuredLogEvent'
+          unstructured_log: '#/components/schemas/UnstructuredLogEvent'
+        propertyName: type
+      oneOf:
+      - $ref: '#/components/schemas/UnstructuredLogEvent'
+      - $ref: '#/components/schemas/MetricEvent'
+      - $ref: '#/components/schemas/StructuredLogEvent'
+    GrammarResponseFormat:
       additionalProperties: false
       properties:
-        identifier:
-          type: string
-        memory_bank_type:
-          const: graph
-          default: graph
-          type: string
-        provider_id:
-          type: string
-        provider_resource_id:
-          type: string
+        bnf:
+          additionalProperties:
+            oneOf:
+            - type: 'null'
+            - type: boolean
+            - type: number
+            - type: string
+            - type: array
+            - type: object
+          type: object
         type:
-          const: memory_bank
-          default: memory_bank
+          const: grammar
+          default: grammar
           type: string
       required:
-      - identifier
-      - provider_resource_id
-      - provider_id
       - type
-      - memory_bank_type
-      type: object
-    GraphMemoryBankParams:
-      additionalProperties: false
-      properties:
-        memory_bank_type:
-          const: graph
-          default: graph
-          type: string
-      required:
-      - memory_bank_type
+      - bnf
       type: object
     GreedySamplingStrategy:
       additionalProperties: false
@@ -946,22 +1004,27 @@ components:
     ImageContentItem:
       additionalProperties: false
       properties:
-        data:
-          contentEncoding: base64
-          type: string
+        image:
+          additionalProperties: false
+          properties:
+            data:
+              contentEncoding: base64
+              type: string
+            url:
+              $ref: '#/components/schemas/URL'
+          type: object
         type:
           const: image
           default: image
           type: string
-        url:
-          $ref: '#/components/schemas/URL'
       required:
       - type
+      - image
       type: object
     ImageDelta:
       additionalProperties: false
       properties:
-        data:
+        image:
           contentEncoding: base64
           type: string
         type:
@@ -970,7 +1033,7 @@ components:
           type: string
       required:
       - type
-      - data
+      - image
       type: object
     InferenceStep:
       additionalProperties: false
@@ -997,20 +1060,53 @@ components:
       - step_type
       - model_response
       type: object
-    InsertDocumentsRequest:
+    InsertChunksRequest:
       additionalProperties: false
       properties:
-        bank_id:
-          type: string
-        documents:
+        chunks:
           items:
-            $ref: '#/components/schemas/MemoryBankDocument'
+            additionalProperties: false
+            properties:
+              content:
+                $ref: '#/components/schemas/InterleavedContent'
+              metadata:
+                additionalProperties:
+                  oneOf:
+                  - type: 'null'
+                  - type: boolean
+                  - type: number
+                  - type: string
+                  - type: array
+                  - type: object
+                type: object
+            required:
+            - content
+            - metadata
+            type: object
           type: array
         ttl_seconds:
           type: integer
+        vector_db_id:
+          type: string
+      required:
+      - vector_db_id
+      - chunks
+      type: object
+    InsertRequest:
+      additionalProperties: false
+      properties:
+        chunk_size_in_tokens:
+          type: integer
+        documents:
+          items:
+            $ref: '#/components/schemas/RAGDocument'
+          type: array
+        vector_db_id:
+          type: string
       required:
-      - bank_id
       - documents
+      - vector_db_id
+      - chunk_size_in_tokens
       type: object
     InterleavedContent:
       oneOf:
@@ -1020,13 +1116,18 @@ components:
           $ref: '#/components/schemas/InterleavedContentItem'
         type: array
     InterleavedContentItem:
+      discriminator:
+        mapping:
+          image: '#/components/schemas/ImageContentItem'
+          text: '#/components/schemas/TextContentItem'
+        propertyName: type
       oneOf:
       - $ref: '#/components/schemas/ImageContentItem'
       - $ref: '#/components/schemas/TextContentItem'
     InvokeToolRequest:
       additionalProperties: false
       properties:
-        args:
+        kwargs:
           additionalProperties:
             oneOf:
             - type: 'null'
@@ -1040,7 +1141,7 @@ components:
           type: string
       required:
       - tool_name
-      - args
+      - kwargs
       type: object
     Job:
       additionalProperties: false
@@ -1057,6 +1158,27 @@ components:
       - failed
       - scheduled
       type: string
+    JsonSchemaResponseFormat:
+      additionalProperties: false
+      properties:
+        json_schema:
+          additionalProperties:
+            oneOf:
+            - type: 'null'
+            - type: boolean
+            - type: number
+            - type: string
+            - type: array
+            - type: object
+          type: object
+        type:
+          const: json_schema
+          default: json_schema
+          type: string
+      required:
+      - type
+      - json_schema
+      type: object
     JsonType:
       additionalProperties: false
       properties:
@@ -1067,74 +1189,6 @@ components:
       required:
       - type
       type: object
-    KeyValueMemoryBank:
-      additionalProperties: false
-      properties:
-        identifier:
-          type: string
-        memory_bank_type:
-          const: keyvalue
-          default: keyvalue
-          type: string
-        provider_id:
-          type: string
-        provider_resource_id:
-          type: string
-        type:
-          const: memory_bank
-          default: memory_bank
-          type: string
-      required:
-      - identifier
-      - provider_resource_id
-      - provider_id
-      - type
-      - memory_bank_type
-      type: object
-    KeyValueMemoryBankParams:
-      additionalProperties: false
-      properties:
-        memory_bank_type:
-          const: keyvalue
-          default: keyvalue
-          type: string
-      required:
-      - memory_bank_type
-      type: object
-    KeywordMemoryBank:
-      additionalProperties: false
-      properties:
-        identifier:
-          type: string
-        memory_bank_type:
-          const: keyword
-          default: keyword
-          type: string
-        provider_id:
-          type: string
-        provider_resource_id:
-          type: string
-        type:
-          const: memory_bank
-          default: memory_bank
-          type: string
-      required:
-      - identifier
-      - provider_resource_id
-      - provider_id
-      - type
-      - memory_bank_type
-      type: object
-    KeywordMemoryBankParams:
-      additionalProperties: false
-      properties:
-        memory_bank_type:
-          const: keyword
-          default: keyword
-          type: string
-      required:
-      - memory_bank_type
-      type: object
     LLMAsJudgeScoringFnParams:
       additionalProperties: false
       properties:
@@ -1158,6 +1212,22 @@ components:
       - type
       - judge_model
       type: object
+    LLMRAGQueryGeneratorConfig:
+      additionalProperties: false
+      properties:
+        model:
+          type: string
+        template:
+          type: string
+        type:
+          const: llm
+          default: llm
+          type: string
+      required:
+      - type
+      - model
+      - template
+      type: object
     ListDatasetsResponse:
       additionalProperties: false
       properties:
@@ -1178,16 +1248,6 @@ components:
       required:
       - data
       type: object
-    ListMemoryBanksResponse:
-      additionalProperties: false
-      properties:
-        data:
-          items:
-            $ref: '#/components/schemas/MemoryBank'
-          type: array
-      required:
-      - data
-      type: object
     ListModelsResponse:
       additionalProperties: false
       properties:
@@ -1274,14 +1334,21 @@ components:
       required:
       - data
       type: object
+    ListVectorDBsResponse:
+      additionalProperties: false
+      properties:
+        data:
+          items:
+            $ref: '#/components/schemas/VectorDB'
+          type: array
+      required:
+      - data
+      type: object
     LogEventRequest:
       additionalProperties: false
       properties:
         event:
-          oneOf:
-          - $ref: '#/components/schemas/UnstructuredLogEvent'
-          - $ref: '#/components/schemas/MetricEvent'
-          - $ref: '#/components/schemas/StructuredLogEvent'
+          $ref: '#/components/schemas/Event'
         ttl_seconds:
           type: integer
       required:
@@ -1330,42 +1397,6 @@ components:
       - rank
       - alpha
       type: object
-    MemoryBank:
-      oneOf:
-      - $ref: '#/components/schemas/VectorMemoryBank'
-      - $ref: '#/components/schemas/KeyValueMemoryBank'
-      - $ref: '#/components/schemas/KeywordMemoryBank'
-      - $ref: '#/components/schemas/GraphMemoryBank'
-    MemoryBankDocument:
-      additionalProperties: false
-      properties:
-        content:
-          oneOf:
-          - type: string
-          - $ref: '#/components/schemas/InterleavedContentItem'
-          - items:
-              $ref: '#/components/schemas/InterleavedContentItem'
-            type: array
-          - $ref: '#/components/schemas/URL'
-        document_id:
-          type: string
-        metadata:
-          additionalProperties:
-            oneOf:
-            - type: 'null'
-            - type: boolean
-            - type: number
-            - type: string
-            - type: array
-            - type: object
-          type: object
-        mime_type:
-          type: string
-      required:
-      - document_id
-      - content
-      - metadata
-      type: object
     MemoryRetrievalStep:
       additionalProperties: false
       properties:
@@ -1374,10 +1405,6 @@ components:
           type: string
         inserted_context:
           $ref: '#/components/schemas/InterleavedContent'
-        memory_bank_ids:
-          items:
-            type: string
-          type: array
         started_at:
           format: date-time
           type: string
@@ -1389,14 +1416,23 @@ components:
           type: string
         turn_id:
           type: string
+        vector_db_ids:
+          type: string
       required:
       - turn_id
       - step_id
       - step_type
-      - memory_bank_ids
+      - vector_db_ids
       - inserted_context
       type: object
     Message:
+      discriminator:
+        mapping:
+          assistant: '#/components/schemas/CompletionMessage'
+          system: '#/components/schemas/SystemMessage'
+          tool: '#/components/schemas/ToolResponseMessage'
+          user: '#/components/schemas/UserMessage'
+        propertyName: role
       oneOf:
       - $ref: '#/components/schemas/UserMessage'
       - $ref: '#/components/schemas/SystemMessage'
@@ -1567,6 +1603,19 @@ components:
       - total_count
       type: object
     ParamType:
+      discriminator:
+        mapping:
+          agent_turn_input: '#/components/schemas/AgentTurnInputType'
+          array: '#/components/schemas/ArrayType'
+          boolean: '#/components/schemas/BooleanType'
+          chat_completion_input: '#/components/schemas/ChatCompletionInputType'
+          completion_input: '#/components/schemas/CompletionInputType'
+          json: '#/components/schemas/JsonType'
+          number: '#/components/schemas/NumberType'
+          object: '#/components/schemas/ObjectType'
+          string: '#/components/schemas/StringType'
+          union: '#/components/schemas/UnionType'
+        propertyName: type
       oneOf:
       - $ref: '#/components/schemas/StringType'
       - $ref: '#/components/schemas/NumberType'
@@ -1705,6 +1754,59 @@ components:
       - quantizer_name
       - group_size
       type: object
+    QueryChunksRequest:
+      additionalProperties: false
+      properties:
+        params:
+          additionalProperties:
+            oneOf:
+            - type: 'null'
+            - type: boolean
+            - type: number
+            - type: string
+            - type: array
+            - type: object
+          type: object
+        query:
+          $ref: '#/components/schemas/InterleavedContent'
+        vector_db_id:
+          type: string
+      required:
+      - vector_db_id
+      - query
+      type: object
+    QueryChunksResponse:
+      additionalProperties: false
+      properties:
+        chunks:
+          items:
+            additionalProperties: false
+            properties:
+              content:
+                $ref: '#/components/schemas/InterleavedContent'
+              metadata:
+                additionalProperties:
+                  oneOf:
+                  - type: 'null'
+                  - type: boolean
+                  - type: number
+                  - type: string
+                  - type: array
+                  - type: object
+                type: object
+            required:
+            - content
+            - metadata
+            type: object
+          type: array
+        scores:
+          items:
+            type: number
+          type: array
+      required:
+      - chunks
+      - scores
+      type: object
     QueryCondition:
       additionalProperties: false
       properties:
@@ -1732,53 +1834,20 @@ components:
       - gt
       - lt
       type: string
-    QueryDocumentsRequest:
+    QueryRequest:
       additionalProperties: false
       properties:
-        bank_id:
-          type: string
-        params:
-          additionalProperties:
-            oneOf:
-            - type: 'null'
-            - type: boolean
-            - type: number
-            - type: string
-            - type: array
-            - type: object
-          type: object
-        query:
+        content:
           $ref: '#/components/schemas/InterleavedContent'
-      required:
-      - bank_id
-      - query
-      type: object
-    QueryDocumentsResponse:
-      additionalProperties: false
-      properties:
-        chunks:
+        query_config:
+          $ref: '#/components/schemas/RAGQueryConfig'
+        vector_db_ids:
           items:
-            additionalProperties: false
-            properties:
-              content:
-                $ref: '#/components/schemas/InterleavedContent'
-              document_id:
-                type: string
-              token_count:
-                type: integer
-            required:
-            - content
-            - token_count
-            - document_id
-            type: object
-          type: array
-        scores:
-          items:
-            type: number
+            type: string
           type: array
       required:
-      - chunks
-      - scores
+      - content
+      - vector_db_ids
       type: object
     QuerySpanTreeResponse:
       additionalProperties: false
@@ -1810,6 +1879,67 @@ components:
       required:
       - data
       type: object
+    RAGDocument:
+      additionalProperties: false
+      properties:
+        content:
+          oneOf:
+          - type: string
+          - $ref: '#/components/schemas/InterleavedContentItem'
+          - items:
+              $ref: '#/components/schemas/InterleavedContentItem'
+            type: array
+          - $ref: '#/components/schemas/URL'
+        document_id:
+          type: string
+        metadata:
+          additionalProperties:
+            oneOf:
+            - type: 'null'
+            - type: boolean
+            - type: number
+            - type: string
+            - type: array
+            - type: object
+          type: object
+        mime_type:
+          type: string
+      required:
+      - document_id
+      - content
+      - metadata
+      type: object
+    RAGQueryConfig:
+      additionalProperties: false
+      properties:
+        max_chunks:
+          default: 5
+          type: integer
+        max_tokens_in_context:
+          default: 4096
+          type: integer
+        query_generator_config:
+          $ref: '#/components/schemas/RAGQueryGeneratorConfig'
+      required:
+      - query_generator_config
+      - max_tokens_in_context
+      - max_chunks
+      type: object
+    RAGQueryGeneratorConfig:
+      discriminator:
+        mapping:
+          default: '#/components/schemas/DefaultRAGQueryGeneratorConfig'
+          llm: '#/components/schemas/LLMRAGQueryGeneratorConfig'
+        propertyName: type
+      oneOf:
+      - $ref: '#/components/schemas/DefaultRAGQueryGeneratorConfig'
+      - $ref: '#/components/schemas/LLMRAGQueryGeneratorConfig'
+    RAGQueryResult:
+      additionalProperties: false
+      properties:
+        content:
+          $ref: '#/components/schemas/InterleavedContent'
+      type: object
     RegexParserScoringFnParams:
       additionalProperties: false
       properties:
@@ -1888,25 +2018,6 @@ components:
       - dataset_id
       - scoring_functions
       type: object
-    RegisterMemoryBankRequest:
-      additionalProperties: false
-      properties:
-        memory_bank_id:
-          type: string
-        params:
-          oneOf:
-          - $ref: '#/components/schemas/VectorMemoryBankParams'
-          - $ref: '#/components/schemas/KeyValueMemoryBankParams'
-          - $ref: '#/components/schemas/KeywordMemoryBankParams'
-          - $ref: '#/components/schemas/GraphMemoryBankParams'
-        provider_id:
-          type: string
-        provider_memory_bank_id:
-          type: string
-      required:
-      - memory_bank_id
-      - params
-      type: object
     RegisterModelRequest:
       additionalProperties: false
       properties:
@@ -1937,10 +2048,7 @@ components:
         description:
           type: string
         params:
-          oneOf:
-          - $ref: '#/components/schemas/LLMAsJudgeScoringFnParams'
-          - $ref: '#/components/schemas/RegexParserScoringFnParams'
-          - $ref: '#/components/schemas/BasicScoringFnParams'
+          $ref: '#/components/schemas/ScoringFnParams'
         provider_id:
           type: string
         provider_scoring_fn_id:
@@ -1999,48 +2107,32 @@ components:
       - toolgroup_id
       - provider_id
       type: object
+    RegisterVectorDbRequest:
+      additionalProperties: false
+      properties:
+        embedding_dimension:
+          type: integer
+        embedding_model:
+          type: string
+        provider_id:
+          type: string
+        provider_vector_db_id:
+          type: string
+        vector_db_id:
+          type: string
+      required:
+      - vector_db_id
+      - embedding_model
+      type: object
     ResponseFormat:
+      discriminator:
+        mapping:
+          grammar: '#/components/schemas/GrammarResponseFormat'
+          json_schema: '#/components/schemas/JsonSchemaResponseFormat'
+        propertyName: type
       oneOf:
-      - additionalProperties: false
-        properties:
-          json_schema:
-            additionalProperties:
-              oneOf:
-              - type: 'null'
-              - type: boolean
-              - type: number
-              - type: string
-              - type: array
-              - type: object
-            type: object
-          type:
-            const: json_schema
-            default: json_schema
-            type: string
-        required:
-        - type
-        - json_schema
-        type: object
-      - additionalProperties: false
-        properties:
-          bnf:
-            additionalProperties:
-              oneOf:
-              - type: 'null'
-              - type: boolean
-              - type: number
-              - type: string
-              - type: array
-              - type: object
-            type: object
-          type:
-            const: grammar
-            default: grammar
-            type: string
-        required:
-        - type
-        - bnf
-        type: object
+      - $ref: '#/components/schemas/JsonSchemaResponseFormat'
+      - $ref: '#/components/schemas/GrammarResponseFormat'
     RouteInfo:
       additionalProperties: false
       properties:
@@ -2061,9 +2153,7 @@ components:
       additionalProperties: false
       properties:
         task_config:
-          oneOf:
-          - $ref: '#/components/schemas/BenchmarkEvalTaskConfig'
-          - $ref: '#/components/schemas/AppEvalTaskConfig'
+          $ref: '#/components/schemas/EvalTaskConfig'
       required:
       - task_config
       type: object
@@ -2128,6 +2218,12 @@ components:
           default: 1.0
           type: number
         strategy:
+          discriminator:
+            mapping:
+              greedy: '#/components/schemas/GreedySamplingStrategy'
+              top_k: '#/components/schemas/TopKSamplingStrategy'
+              top_p: '#/components/schemas/TopPSamplingStrategy'
+            propertyName: type
           oneOf:
           - $ref: '#/components/schemas/GreedySamplingStrategy'
           - $ref: '#/components/schemas/TopPSamplingStrategy'
@@ -2165,10 +2261,7 @@ components:
         scoring_functions:
           additionalProperties:
             oneOf:
-            - oneOf:
-              - $ref: '#/components/schemas/LLMAsJudgeScoringFnParams'
-              - $ref: '#/components/schemas/RegexParserScoringFnParams'
-              - $ref: '#/components/schemas/BasicScoringFnParams'
+            - $ref: '#/components/schemas/ScoringFnParams'
             - type: 'null'
           type: object
       required:
@@ -2206,10 +2299,7 @@ components:
         scoring_functions:
           additionalProperties:
             oneOf:
-            - oneOf:
-              - $ref: '#/components/schemas/LLMAsJudgeScoringFnParams'
-              - $ref: '#/components/schemas/RegexParserScoringFnParams'
-              - $ref: '#/components/schemas/BasicScoringFnParams'
+            - $ref: '#/components/schemas/ScoringFnParams'
             - type: 'null'
           type: object
       required:
@@ -2244,10 +2334,7 @@ components:
             - type: object
           type: object
         params:
-          oneOf:
-          - $ref: '#/components/schemas/LLMAsJudgeScoringFnParams'
-          - $ref: '#/components/schemas/RegexParserScoringFnParams'
-          - $ref: '#/components/schemas/BasicScoringFnParams'
+          $ref: '#/components/schemas/ScoringFnParams'
         provider_id:
           type: string
         provider_resource_id:
@@ -2266,6 +2353,17 @@ components:
       - metadata
       - return_type
       type: object
+    ScoringFnParams:
+      discriminator:
+        mapping:
+          basic: '#/components/schemas/BasicScoringFnParams'
+          llm_as_judge: '#/components/schemas/LLMAsJudgeScoringFnParams'
+          regex_parser: '#/components/schemas/RegexParserScoringFnParams'
+        propertyName: type
+      oneOf:
+      - $ref: '#/components/schemas/LLMAsJudgeScoringFnParams'
+      - $ref: '#/components/schemas/RegexParserScoringFnParams'
+      - $ref: '#/components/schemas/BasicScoringFnParams'
     ScoringResult:
       additionalProperties: false
       properties:
@@ -2298,8 +2396,6 @@ components:
     Session:
       additionalProperties: false
       properties:
-        memory_bank:
-          $ref: '#/components/schemas/MemoryBank'
         session_id:
           type: string
         session_name:
@@ -2503,9 +2599,7 @@ components:
             - type: object
           type: object
         payload:
-          oneOf:
-          - $ref: '#/components/schemas/SpanStartPayload'
-          - $ref: '#/components/schemas/SpanEndPayload'
+          $ref: '#/components/schemas/StructuredLogPayload'
         span_id:
           type: string
         timestamp:
@@ -2524,13 +2618,20 @@ components:
       - type
       - payload
       type: object
+    StructuredLogPayload:
+      discriminator:
+        mapping:
+          span_end: '#/components/schemas/SpanEndPayload'
+          span_start: '#/components/schemas/SpanStartPayload'
+        propertyName: type
+      oneOf:
+      - $ref: '#/components/schemas/SpanStartPayload'
+      - $ref: '#/components/schemas/SpanEndPayload'
     SupervisedFineTuneRequest:
       additionalProperties: false
       properties:
         algorithm_config:
-          oneOf:
-          - $ref: '#/components/schemas/LoraFinetuningConfig'
-          - $ref: '#/components/schemas/QATFinetuningConfig'
+          $ref: '#/components/schemas/AlgorithmConfig'
         checkpoint_dir:
           type: string
         hyperparam_search_config:
@@ -2753,19 +2854,19 @@ components:
     ToolCallDelta:
       additionalProperties: false
       properties:
-        content:
+        parse_status:
+          $ref: '#/components/schemas/ToolCallParseStatus'
+        tool_call:
           oneOf:
           - type: string
           - $ref: '#/components/schemas/ToolCall'
-        parse_status:
-          $ref: '#/components/schemas/ToolCallParseStatus'
         type:
           const: tool_call
           default: tool_call
           type: string
       required:
       - type
-      - content
+      - tool_call
       - parse_status
       type: object
     ToolCallParseStatus:
@@ -3115,6 +3216,13 @@ components:
           type: string
         steps:
           items:
+            discriminator:
+              mapping:
+                inference: '#/components/schemas/InferenceStep'
+                memory_retrieval: '#/components/schemas/MemoryRetrievalStep'
+                shield_call: '#/components/schemas/ShieldCallStep'
+                tool_execution: '#/components/schemas/ToolExecutionStep'
+              propertyName: step_type
             oneOf:
             - $ref: '#/components/schemas/InferenceStep'
             - $ref: '#/components/schemas/ToolExecutionStep'
@@ -3202,58 +3310,30 @@ components:
       - role
       - content
       type: object
-    VectorMemoryBank:
+    VectorDB:
       additionalProperties: false
       properties:
-        chunk_size_in_tokens:
-          type: integer
         embedding_dimension:
-          default: 384
           type: integer
         embedding_model:
           type: string
         identifier:
           type: string
-        memory_bank_type:
-          const: vector
-          default: vector
-          type: string
-        overlap_size_in_tokens:
-          type: integer
         provider_id:
           type: string
         provider_resource_id:
           type: string
         type:
-          const: memory_bank
-          default: memory_bank
+          const: vector_db
+          default: vector_db
           type: string
       required:
       - identifier
       - provider_resource_id
       - provider_id
       - type
-      - memory_bank_type
       - embedding_model
-      - chunk_size_in_tokens
-      type: object
-    VectorMemoryBankParams:
-      additionalProperties: false
-      properties:
-        chunk_size_in_tokens:
-          type: integer
-        embedding_model:
-          type: string
-        memory_bank_type:
-          const: vector
-          default: vector
-          type: string
-        overlap_size_in_tokens:
-          type: integer
-      required:
-      - memory_bank_type
-      - embedding_model
-      - chunk_size_in_tokens
+      - embedding_dimension
       type: object
     VersionInfo:
       additionalProperties: false
@@ -4272,186 +4352,6 @@ paths:
           description: OK
       tags:
       - Inspect
-  /v1/memory-banks:
-    get:
-      parameters:
-      - description: JSON-encoded provider data which will be made available to the
-          adapter servicing the API
-        in: header
-        name: X-LlamaStack-Provider-Data
-        required: false
-        schema:
-          type: string
-      - description: Version of the client making the request. This is used to ensure
-          that the client and server are compatible.
-        in: header
-        name: X-LlamaStack-Client-Version
-        required: false
-        schema:
-          type: string
-      responses:
-        '200':
-          content:
-            application/json:
-              schema:
-                $ref: '#/components/schemas/ListMemoryBanksResponse'
-          description: OK
-      tags:
-      - MemoryBanks
-    post:
-      parameters:
-      - description: JSON-encoded provider data which will be made available to the
-          adapter servicing the API
-        in: header
-        name: X-LlamaStack-Provider-Data
-        required: false
-        schema:
-          type: string
-      - description: Version of the client making the request. This is used to ensure
-          that the client and server are compatible.
-        in: header
-        name: X-LlamaStack-Client-Version
-        required: false
-        schema:
-          type: string
-      requestBody:
-        content:
-          application/json:
-            schema:
-              $ref: '#/components/schemas/RegisterMemoryBankRequest'
-        required: true
-      responses:
-        '200':
-          content:
-            application/json:
-              schema:
-                oneOf:
-                - $ref: '#/components/schemas/VectorMemoryBank'
-                - $ref: '#/components/schemas/KeyValueMemoryBank'
-                - $ref: '#/components/schemas/KeywordMemoryBank'
-                - $ref: '#/components/schemas/GraphMemoryBank'
-          description: ''
-      tags:
-      - MemoryBanks
-  /v1/memory-banks/{memory_bank_id}:
-    delete:
-      parameters:
-      - in: path
-        name: memory_bank_id
-        required: true
-        schema:
-          type: string
-      - description: JSON-encoded provider data which will be made available to the
-          adapter servicing the API
-        in: header
-        name: X-LlamaStack-Provider-Data
-        required: false
-        schema:
-          type: string
-      - description: Version of the client making the request. This is used to ensure
-          that the client and server are compatible.
-        in: header
-        name: X-LlamaStack-Client-Version
-        required: false
-        schema:
-          type: string
-      responses:
-        '200':
-          description: OK
-      tags:
-      - MemoryBanks
-    get:
-      parameters:
-      - in: path
-        name: memory_bank_id
-        required: true
-        schema:
-          type: string
-      - description: JSON-encoded provider data which will be made available to the
-          adapter servicing the API
-        in: header
-        name: X-LlamaStack-Provider-Data
-        required: false
-        schema:
-          type: string
-      - description: Version of the client making the request. This is used to ensure
-          that the client and server are compatible.
-        in: header
-        name: X-LlamaStack-Client-Version
-        required: false
-        schema:
-          type: string
-      responses:
-        '200':
-          content:
-            application/json:
-              schema:
-                oneOf:
-                - $ref: '#/components/schemas/MemoryBank'
-                - type: 'null'
-          description: OK
-      tags:
-      - MemoryBanks
-  /v1/memory/insert:
-    post:
-      parameters:
-      - description: JSON-encoded provider data which will be made available to the
-          adapter servicing the API
-        in: header
-        name: X-LlamaStack-Provider-Data
-        required: false
-        schema:
-          type: string
-      - description: Version of the client making the request. This is used to ensure
-          that the client and server are compatible.
-        in: header
-        name: X-LlamaStack-Client-Version
-        required: false
-        schema:
-          type: string
-      requestBody:
-        content:
-          application/json:
-            schema:
-              $ref: '#/components/schemas/InsertDocumentsRequest'
-        required: true
-      responses:
-        '200':
-          description: OK
-      tags:
-      - Memory
-  /v1/memory/query:
-    post:
-      parameters:
-      - description: JSON-encoded provider data which will be made available to the
-          adapter servicing the API
-        in: header
-        name: X-LlamaStack-Provider-Data
-        required: false
-        schema:
-          type: string
-      - description: Version of the client making the request. This is used to ensure
-          that the client and server are compatible.
-        in: header
-        name: X-LlamaStack-Client-Version
-        required: false
-        schema:
-          type: string
-      requestBody:
-        content:
-          application/json:
-            schema:
-              $ref: '#/components/schemas/QueryDocumentsRequest'
-        required: true
-      responses:
-        '200':
-          content:
-            application/json:
-              schema:
-                $ref: '#/components/schemas/QueryDocumentsResponse'
-          description: OK
-      tags:
-      - Memory
   /v1/models:
     get:
       parameters:
@@ -5386,6 +5286,68 @@ paths:
           description: OK
       tags:
       - ToolRuntime
+  /v1/tool-runtime/rag-tool/insert:
+    post:
+      parameters:
+      - description: JSON-encoded provider data which will be made available to the
+          adapter servicing the API
+        in: header
+        name: X-LlamaStack-Provider-Data
+        required: false
+        schema:
+          type: string
+      - description: Version of the client making the request. This is used to ensure
+          that the client and server are compatible.
+        in: header
+        name: X-LlamaStack-Client-Version
+        required: false
+        schema:
+          type: string
+      requestBody:
+        content:
+          application/json:
+            schema:
+              $ref: '#/components/schemas/InsertRequest'
+        required: true
+      responses:
+        '200':
+          description: OK
+      summary: Index documents so they can be used by the RAG system
+      tags:
+      - ToolRuntime
+  /v1/tool-runtime/rag-tool/query:
+    post:
+      parameters:
+      - description: JSON-encoded provider data which will be made available to the
+          adapter servicing the API
+        in: header
+        name: X-LlamaStack-Provider-Data
+        required: false
+        schema:
+          type: string
+      - description: Version of the client making the request. This is used to ensure
+          that the client and server are compatible.
+        in: header
+        name: X-LlamaStack-Client-Version
+        required: false
+        schema:
+          type: string
+      requestBody:
+        content:
+          application/json:
+            schema:
+              $ref: '#/components/schemas/QueryRequest'
+        required: true
+      responses:
+        '200':
+          content:
+            application/json:
+              schema:
+                $ref: '#/components/schemas/RAGQueryResult'
+          description: OK
+      summary: Query the RAG system for context; typically invoked by the agent
+      tags:
+      - ToolRuntime
   /v1/toolgroups:
     get:
       parameters:
@@ -5562,6 +5524,182 @@ paths:
           description: OK
       tags:
       - ToolGroups
+  /v1/vector-dbs:
+    get:
+      parameters:
+      - description: JSON-encoded provider data which will be made available to the
+          adapter servicing the API
+        in: header
+        name: X-LlamaStack-Provider-Data
+        required: false
+        schema:
+          type: string
+      - description: Version of the client making the request. This is used to ensure
+          that the client and server are compatible.
+        in: header
+        name: X-LlamaStack-Client-Version
+        required: false
+        schema:
+          type: string
+      responses:
+        '200':
+          content:
+            application/json:
+              schema:
+                $ref: '#/components/schemas/ListVectorDBsResponse'
+          description: OK
+      tags:
+      - VectorDBs
+    post:
+      parameters:
+      - description: JSON-encoded provider data which will be made available to the
+          adapter servicing the API
+        in: header
+        name: X-LlamaStack-Provider-Data
+        required: false
+        schema:
+          type: string
+      - description: Version of the client making the request. This is used to ensure
+          that the client and server are compatible.
+        in: header
+        name: X-LlamaStack-Client-Version
+        required: false
+        schema:
+          type: string
+      requestBody:
+        content:
+          application/json:
+            schema:
+              $ref: '#/components/schemas/RegisterVectorDbRequest'
+        required: true
+      responses:
+        '200':
+          content:
+            application/json:
+              schema:
+                $ref: '#/components/schemas/VectorDB'
+          description: OK
+      tags:
+      - VectorDBs
+  /v1/vector-dbs/{vector_db_id}:
+    delete:
+      parameters:
+      - in: path
+        name: vector_db_id
+        required: true
+        schema:
+          type: string
+      - description: JSON-encoded provider data which will be made available to the
+          adapter servicing the API
+        in: header
+        name: X-LlamaStack-Provider-Data
+        required: false
+        schema:
+          type: string
+      - description: Version of the client making the request. This is used to ensure
+          that the client and server are compatible.
+        in: header
+        name: X-LlamaStack-Client-Version
+        required: false
+        schema:
+          type: string
+      responses:
+        '200':
+          description: OK
+      tags:
+      - VectorDBs
+    get:
+      parameters:
+      - in: path
+        name: vector_db_id
+        required: true
+        schema:
+          type: string
+      - description: JSON-encoded provider data which will be made available to the
+          adapter servicing the API
+        in: header
+        name: X-LlamaStack-Provider-Data
+        required: false
+        schema:
+          type: string
+      - description: Version of the client making the request. This is used to ensure
+          that the client and server are compatible.
+        in: header
+        name: X-LlamaStack-Client-Version
+        required: false
+        schema:
+          type: string
+      responses:
+        '200':
+          content:
+            application/json:
+              schema:
+                oneOf:
+                - $ref: '#/components/schemas/VectorDB'
+                - type: 'null'
+          description: OK
+      tags:
+      - VectorDBs
+  /v1/vector-io/insert:
+    post:
+      parameters:
+      - description: JSON-encoded provider data which will be made available to the
+          adapter servicing the API
+        in: header
+        name: X-LlamaStack-Provider-Data
+        required: false
+        schema:
+          type: string
+      - description: Version of the client making the request. This is used to ensure
+          that the client and server are compatible.
+        in: header
+        name: X-LlamaStack-Client-Version
+        required: false
+        schema:
+          type: string
+      requestBody:
+        content:
+          application/json:
+            schema:
+              $ref: '#/components/schemas/InsertChunksRequest'
+        required: true
+      responses:
+        '200':
+          description: OK
+      tags:
+      - VectorIO
+  /v1/vector-io/query:
+    post:
+      parameters:
+      - description: JSON-encoded provider data which will be made available to the
+          adapter servicing the API
+        in: header
+        name: X-LlamaStack-Provider-Data
+        required: false
+        schema:
+          type: string
+      - description: Version of the client making the request. This is used to ensure
+          that the client and server are compatible.
+        in: header
+        name: X-LlamaStack-Client-Version
+        required: false
+        schema:
+          type: string
+      requestBody:
+        content:
+          application/json:
+            schema:
+              $ref: '#/components/schemas/QueryChunksRequest'
+        required: true
+      responses:
+        '200':
+          content:
+            application/json:
+              schema:
+                $ref: '#/components/schemas/QueryChunksResponse'
+          description: OK
+      tags:
+      - VectorIO
   /v1/version:
     get:
       parameters:
@@ -5611,11 +5749,12 @@ tags:
 - description: <SchemaDefinition schemaRef="#/components/schemas/AgentTurnInputType"
     />
   name: AgentTurnInputType
-- description: 'Streamed agent execution response.
-
-
-    <SchemaDefinition schemaRef="#/components/schemas/AgentTurnResponseEvent" />'
+- description: <SchemaDefinition schemaRef="#/components/schemas/AgentTurnResponseEvent"
+    />
   name: AgentTurnResponseEvent
+- description: <SchemaDefinition schemaRef="#/components/schemas/AgentTurnResponseEventPayload"
+    />
+  name: AgentTurnResponseEventPayload
 - description: <SchemaDefinition schemaRef="#/components/schemas/AgentTurnResponseStepCompletePayload"
     />
   name: AgentTurnResponseStepCompletePayload
@@ -5641,6 +5780,9 @@ tags:
 - description: <SchemaDefinition schemaRef="#/components/schemas/AggregationFunctionType"
     />
   name: AggregationFunctionType
+- description: <SchemaDefinition schemaRef="#/components/schemas/AlgorithmConfig"
+    />
+  name: AlgorithmConfig
 - description: <SchemaDefinition schemaRef="#/components/schemas/AppEvalTaskConfig"
     />
   name: AppEvalTaskConfig
@@ -5748,6 +5890,9 @@ tags:
   name: DatasetFormat
 - name: DatasetIO
 - name: Datasets
+- description: <SchemaDefinition schemaRef="#/components/schemas/DefaultRAGQueryGeneratorConfig"
+    />
+  name: DefaultRAGQueryGeneratorConfig
 - description: <SchemaDefinition schemaRef="#/components/schemas/EfficiencyConfig"
     />
   name: EfficiencyConfig
@@ -5758,8 +5903,12 @@ tags:
     />
   name: EmbeddingsResponse
 - name: Eval
+- description: <SchemaDefinition schemaRef="#/components/schemas/EvalCandidate" />
+  name: EvalCandidate
 - description: <SchemaDefinition schemaRef="#/components/schemas/EvalTask" />
   name: EvalTask
+- description: <SchemaDefinition schemaRef="#/components/schemas/EvalTaskConfig" />
+  name: EvalTaskConfig
 - name: EvalTasks
 - description: <SchemaDefinition schemaRef="#/components/schemas/EvaluateResponse"
     />
@@ -5767,12 +5916,11 @@ tags:
 - description: <SchemaDefinition schemaRef="#/components/schemas/EvaluateRowsRequest"
     />
   name: EvaluateRowsRequest
-- description: <SchemaDefinition schemaRef="#/components/schemas/GraphMemoryBank"
+- description: <SchemaDefinition schemaRef="#/components/schemas/Event" />
+  name: Event
+- description: <SchemaDefinition schemaRef="#/components/schemas/GrammarResponseFormat"
     />
-  name: GraphMemoryBank
-- description: <SchemaDefinition schemaRef="#/components/schemas/GraphMemoryBankParams"
-    />
-  name: GraphMemoryBankParams
+  name: GrammarResponseFormat
 - description: <SchemaDefinition schemaRef="#/components/schemas/GreedySamplingStrategy"
     />
   name: GreedySamplingStrategy
@@ -5786,9 +5934,11 @@ tags:
 - name: Inference
 - description: <SchemaDefinition schemaRef="#/components/schemas/InferenceStep" />
   name: InferenceStep
-- description: <SchemaDefinition schemaRef="#/components/schemas/InsertDocumentsRequest"
+- description: <SchemaDefinition schemaRef="#/components/schemas/InsertChunksRequest"
     />
-  name: InsertDocumentsRequest
+  name: InsertChunksRequest
+- description: <SchemaDefinition schemaRef="#/components/schemas/InsertRequest" />
+  name: InsertRequest
 - name: Inspect
 - description: <SchemaDefinition schemaRef="#/components/schemas/InterleavedContent"
     />
@@ -5803,32 +5953,23 @@ tags:
   name: Job
 - description: <SchemaDefinition schemaRef="#/components/schemas/JobStatus" />
   name: JobStatus
+- description: <SchemaDefinition schemaRef="#/components/schemas/JsonSchemaResponseFormat"
+    />
+  name: JsonSchemaResponseFormat
 - description: <SchemaDefinition schemaRef="#/components/schemas/JsonType" />
   name: JsonType
-- description: <SchemaDefinition schemaRef="#/components/schemas/KeyValueMemoryBank"
-    />
-  name: KeyValueMemoryBank
-- description: <SchemaDefinition schemaRef="#/components/schemas/KeyValueMemoryBankParams"
-    />
-  name: KeyValueMemoryBankParams
-- description: <SchemaDefinition schemaRef="#/components/schemas/KeywordMemoryBank"
-    />
-  name: KeywordMemoryBank
-- description: <SchemaDefinition schemaRef="#/components/schemas/KeywordMemoryBankParams"
-    />
-  name: KeywordMemoryBankParams
 - description: <SchemaDefinition schemaRef="#/components/schemas/LLMAsJudgeScoringFnParams"
     />
   name: LLMAsJudgeScoringFnParams
+- description: <SchemaDefinition schemaRef="#/components/schemas/LLMRAGQueryGeneratorConfig"
+    />
+  name: LLMRAGQueryGeneratorConfig
 - description: <SchemaDefinition schemaRef="#/components/schemas/ListDatasetsResponse"
     />
   name: ListDatasetsResponse
 - description: <SchemaDefinition schemaRef="#/components/schemas/ListEvalTasksResponse"
     />
   name: ListEvalTasksResponse
-- description: <SchemaDefinition schemaRef="#/components/schemas/ListMemoryBanksResponse"
-    />
-  name: ListMemoryBanksResponse
 - description: <SchemaDefinition schemaRef="#/components/schemas/ListModelsResponse"
     />
   name: ListModelsResponse
@@ -5853,6 +5994,9 @@ tags:
 - description: <SchemaDefinition schemaRef="#/components/schemas/ListToolsResponse"
     />
   name: ListToolsResponse
+- description: <SchemaDefinition schemaRef="#/components/schemas/ListVectorDBsResponse"
+    />
+  name: ListVectorDBsResponse
 - description: <SchemaDefinition schemaRef="#/components/schemas/LogEventRequest"
     />
   name: LogEventRequest
@@ -5861,13 +6005,6 @@ tags:
 - description: <SchemaDefinition schemaRef="#/components/schemas/LoraFinetuningConfig"
     />
   name: LoraFinetuningConfig
-- name: Memory
-- description: <SchemaDefinition schemaRef="#/components/schemas/MemoryBank" />
-  name: MemoryBank
-- description: <SchemaDefinition schemaRef="#/components/schemas/MemoryBankDocument"
-    />
-  name: MemoryBankDocument
-- name: MemoryBanks
 - description: <SchemaDefinition schemaRef="#/components/schemas/MemoryRetrievalStep"
     />
   name: MemoryRetrievalStep
@@ -5920,17 +6057,19 @@ tags:
 - description: <SchemaDefinition schemaRef="#/components/schemas/QATFinetuningConfig"
     />
   name: QATFinetuningConfig
+- description: <SchemaDefinition schemaRef="#/components/schemas/QueryChunksRequest"
+    />
+  name: QueryChunksRequest
+- description: <SchemaDefinition schemaRef="#/components/schemas/QueryChunksResponse"
+    />
+  name: QueryChunksResponse
 - description: <SchemaDefinition schemaRef="#/components/schemas/QueryCondition" />
   name: QueryCondition
 - description: <SchemaDefinition schemaRef="#/components/schemas/QueryConditionOp"
     />
   name: QueryConditionOp
-- description: <SchemaDefinition schemaRef="#/components/schemas/QueryDocumentsRequest"
-    />
-  name: QueryDocumentsRequest
-- description: <SchemaDefinition schemaRef="#/components/schemas/QueryDocumentsResponse"
-    />
-  name: QueryDocumentsResponse
+- description: <SchemaDefinition schemaRef="#/components/schemas/QueryRequest" />
+  name: QueryRequest
 - description: <SchemaDefinition schemaRef="#/components/schemas/QuerySpanTreeResponse"
     />
   name: QuerySpanTreeResponse
@@ -5940,6 +6079,15 @@ tags:
 - description: <SchemaDefinition schemaRef="#/components/schemas/QueryTracesResponse"
     />
   name: QueryTracesResponse
+- description: <SchemaDefinition schemaRef="#/components/schemas/RAGDocument" />
+  name: RAGDocument
+- description: <SchemaDefinition schemaRef="#/components/schemas/RAGQueryConfig" />
+  name: RAGQueryConfig
+- description: <SchemaDefinition schemaRef="#/components/schemas/RAGQueryGeneratorConfig"
+    />
+  name: RAGQueryGeneratorConfig
+- description: <SchemaDefinition schemaRef="#/components/schemas/RAGQueryResult" />
+  name: RAGQueryResult
 - description: <SchemaDefinition schemaRef="#/components/schemas/RegexParserScoringFnParams"
     />
   name: RegexParserScoringFnParams
@@ -5949,9 +6097,6 @@ tags:
 - description: <SchemaDefinition schemaRef="#/components/schemas/RegisterEvalTaskRequest"
     />
   name: RegisterEvalTaskRequest
-- description: <SchemaDefinition schemaRef="#/components/schemas/RegisterMemoryBankRequest"
-    />
-  name: RegisterMemoryBankRequest
 - description: <SchemaDefinition schemaRef="#/components/schemas/RegisterModelRequest"
     />
   name: RegisterModelRequest
@@ -5964,6 +6109,9 @@ tags:
 - description: <SchemaDefinition schemaRef="#/components/schemas/RegisterToolGroupRequest"
     />
   name: RegisterToolGroupRequest
+- description: <SchemaDefinition schemaRef="#/components/schemas/RegisterVectorDbRequest"
+    />
+  name: RegisterVectorDbRequest
 - description: <SchemaDefinition schemaRef="#/components/schemas/ResponseFormat" />
   name: ResponseFormat
 - description: <SchemaDefinition schemaRef="#/components/schemas/RouteInfo" />
@@ -5998,6 +6146,9 @@ tags:
 - name: Scoring
 - description: <SchemaDefinition schemaRef="#/components/schemas/ScoringFn" />
   name: ScoringFn
+- description: <SchemaDefinition schemaRef="#/components/schemas/ScoringFnParams"
+    />
+  name: ScoringFnParams
 - name: ScoringFunctions
 - description: <SchemaDefinition schemaRef="#/components/schemas/ScoringResult" />
   name: ScoringResult
@@ -6032,6 +6183,9 @@ tags:
 - description: <SchemaDefinition schemaRef="#/components/schemas/StructuredLogEvent"
     />
   name: StructuredLogEvent
+- description: <SchemaDefinition schemaRef="#/components/schemas/StructuredLogPayload"
+    />
+  name: StructuredLogPayload
 - description: <SchemaDefinition schemaRef="#/components/schemas/SupervisedFineTuneRequest"
     />
   name: SupervisedFineTuneRequest
@@ -6128,12 +6282,10 @@ tags:
   name: UnstructuredLogEvent
 - description: <SchemaDefinition schemaRef="#/components/schemas/UserMessage" />
   name: UserMessage
-- description: <SchemaDefinition schemaRef="#/components/schemas/VectorMemoryBank"
-    />
-  name: VectorMemoryBank
-- description: <SchemaDefinition schemaRef="#/components/schemas/VectorMemoryBankParams"
-    />
-  name: VectorMemoryBankParams
+- description: <SchemaDefinition schemaRef="#/components/schemas/VectorDB" />
+  name: VectorDB
+- name: VectorDBs
+- name: VectorIO
 - description: <SchemaDefinition schemaRef="#/components/schemas/VersionInfo" />
   name: VersionInfo
 - description: <SchemaDefinition schemaRef="#/components/schemas/ViolationLevel" />
@@ -6149,8 +6301,6 @@ x-tagGroups:
   - EvalTasks
   - Inference
   - Inspect
-  - Memory
-  - MemoryBanks
   - Models
   - PostTraining (Coming Soon)
   - Safety
@@ -6161,6 +6311,8 @@ x-tagGroups:
   - Telemetry
   - ToolGroups
   - ToolRuntime
+  - VectorDBs
+  - VectorIO
 - name: Types
   tags:
   - AgentCandidate
@@ -6171,6 +6323,7 @@ x-tagGroups:
   - AgentTool
   - AgentTurnInputType
   - AgentTurnResponseEvent
+  - AgentTurnResponseEventPayload
   - AgentTurnResponseStepCompletePayload
   - AgentTurnResponseStepProgressPayload
   - AgentTurnResponseStepStartPayload
@@ -6178,6 +6331,7 @@ x-tagGroups:
   - AgentTurnResponseTurnCompletePayload
   - AgentTurnResponseTurnStartPayload
   - AggregationFunctionType
+  - AlgorithmConfig
   - AppEvalTaskConfig
   - AppendRowsRequest
   - ArrayType
@@ -6210,34 +6364,35 @@ x-tagGroups:
   - DataConfig
   - Dataset
   - DatasetFormat
+  - DefaultRAGQueryGeneratorConfig
   - EfficiencyConfig
   - EmbeddingsRequest
   - EmbeddingsResponse
+  - EvalCandidate
   - EvalTask
+  - EvalTaskConfig
   - EvaluateResponse
   - EvaluateRowsRequest
-  - GraphMemoryBank
-  - GraphMemoryBankParams
+  - Event
+  - GrammarResponseFormat
   - GreedySamplingStrategy
   - HealthInfo
   - ImageContentItem
   - ImageDelta
   - InferenceStep
-  - InsertDocumentsRequest
+  - InsertChunksRequest
+  - InsertRequest
   - InterleavedContent
   - InterleavedContentItem
   - InvokeToolRequest
   - Job
   - JobStatus
+  - JsonSchemaResponseFormat
   - JsonType
-  - KeyValueMemoryBank
-  - KeyValueMemoryBankParams
-  - KeywordMemoryBank
-  - KeywordMemoryBankParams
   - LLMAsJudgeScoringFnParams
+  - LLMRAGQueryGeneratorConfig
   - ListDatasetsResponse
   - ListEvalTasksResponse
-  - ListMemoryBanksResponse
   - ListModelsResponse
   - ListPostTrainingJobsResponse
   - ListProvidersResponse
@@ -6246,11 +6401,10 @@ x-tagGroups:
   - ListShieldsResponse
   - ListToolGroupsResponse
   - ListToolsResponse
+  - ListVectorDBsResponse
   - LogEventRequest
   - LogSeverity
   - LoraFinetuningConfig
-  - MemoryBank
-  - MemoryBankDocument
   - MemoryRetrievalStep
   - Message
   - MetricEvent
@@ -6269,21 +6423,26 @@ x-tagGroups:
   - PreferenceOptimizeRequest
   - ProviderInfo
   - QATFinetuningConfig
+  - QueryChunksRequest
+  - QueryChunksResponse
   - QueryCondition
   - QueryConditionOp
-  - QueryDocumentsRequest
-  - QueryDocumentsResponse
+  - QueryRequest
   - QuerySpanTreeResponse
   - QuerySpansResponse
   - QueryTracesResponse
+  - RAGDocument
+  - RAGQueryConfig
+  - RAGQueryGeneratorConfig
+  - RAGQueryResult
   - RegexParserScoringFnParams
   - RegisterDatasetRequest
   - RegisterEvalTaskRequest
-  - RegisterMemoryBankRequest
   - RegisterModelRequest
   - RegisterScoringFunctionRequest
   - RegisterShieldRequest
   - RegisterToolGroupRequest
+  - RegisterVectorDbRequest
   - ResponseFormat
   - RouteInfo
   - RunEvalRequest
@@ -6297,6 +6456,7 @@ x-tagGroups:
   - ScoreRequest
   - ScoreResponse
   - ScoringFn
+  - ScoringFnParams
   - ScoringResult
   - Session
   - Shield
@@ -6309,6 +6469,7 @@ x-tagGroups:
   - StopReason
   - StringType
   - StructuredLogEvent
+  - StructuredLogPayload
   - SupervisedFineTuneRequest
   - SyntheticDataGenerateRequest
   - SyntheticDataGenerationResponse
@@ -6341,7 +6502,6 @@ x-tagGroups:
   - UnionType
   - UnstructuredLogEvent
   - UserMessage
-  - VectorMemoryBank
-  - VectorMemoryBankParams
+  - VectorDB
   - VersionInfo
   - ViolationLevel
diff --git a/docs/source/building_applications/agent_execution_loop.md b/docs/source/building_applications/agent_execution_loop.md
new file mode 100644
index 000000000..e0bc01840
--- /dev/null
+++ b/docs/source/building_applications/agent_execution_loop.md
@@ -0,0 +1,123 @@
+## Agent Execution Loop
+
+Agents are the heart of complex AI applications. They combine inference, memory, safety, and tool usage into coherent workflows. At its core, an agent follows a sophisticated execution loop that enables multi-step reasoning, tool usage, and safety checks.
+
+Each agent turn follows these key steps:
+
+1. **Initial Safety Check**: The user's input is first screened through configured safety shields
+
+2. **Context Retrieval**:
+   - If RAG is enabled, the agent queries relevant documents from memory banks
+   - For new documents, they are first inserted into the memory bank
+   - Retrieved context is augmented to the user's prompt
+
+3. **Inference Loop**: The agent enters its main execution loop:
+   - The LLM receives the augmented prompt (with context and/or previous tool outputs)
+   - The LLM generates a response, potentially with tool calls
+   - If tool calls are present:
+     - Tool inputs are safety-checked
+     - Tools are executed (e.g., web search, code execution)
+     - Tool responses are fed back to the LLM for synthesis
+   - The loop continues until:
+     - The LLM provides a final response without tool calls
+     - Maximum iterations are reached
+     - Token limit is exceeded
+
+4. **Final Safety Check**: The agent's final response is screened through safety shields
+
+```{mermaid}
+sequenceDiagram
+    participant U as User
+    participant E as Executor
+    participant M as Memory Bank
+    participant L as LLM
+    participant T as Tools
+    participant S as Safety Shield
+
+    Note over U,S: Agent Turn Start
+    U->>S: 1. Submit Prompt
+    activate S
+    S->>E: Input Safety Check
+    deactivate S
+
+    E->>M: 2.1 Query Context
+    M-->>E: 2.2 Retrieved Documents
+
+    loop Inference Loop
+        E->>L: 3.1 Augment with Context
+        L-->>E: 3.2 Response (with/without tool calls)
+
+        alt Has Tool Calls
+            E->>S: Check Tool Input
+            S->>T: 4.1 Execute Tool
+            T-->>E: 4.2 Tool Response
+            E->>L: 5.1 Tool Response
+            L-->>E: 5.2 Synthesized Response
+        end
+
+        opt Stop Conditions
+            Note over E: Break if:
+            Note over E: - No tool calls
+            Note over E: - Max iterations reached
+            Note over E: - Token limit exceeded
+        end
+    end
+
+    E->>S: Output Safety Check
+    S->>U: 6. Final Response
+```
+
+Each step in this process can be monitored and controlled through configurations. Here's an example that demonstrates monitoring the agent's execution:
+
+```python
+from llama_stack_client.lib.agents.event_logger import EventLogger
+
+agent_config = AgentConfig(
+    model="Llama3.2-3B-Instruct",
+    instructions="You are a helpful assistant",
+    # Enable both RAG and tool usage
+    toolgroups=[
+        {"name": "builtin::rag", "args": {"vector_db_ids": ["my_docs"]}}.
+        "builtin::code_interpreter",
+    ],
+    # Configure safety
+    input_shields=["llama_guard"],
+    output_shields=["llama_guard"],
+    # Control the inference loop
+    max_infer_iters=5,
+    sampling_params={
+        "strategy": {
+            "type": "top_p",
+            "temperature": 0.7,
+            "top_p": 0.95
+        },
+        "max_tokens": 2048
+    }
+)
+
+agent = Agent(client, agent_config)
+session_id = agent.create_session("monitored_session")
+
+# Stream the agent's execution steps
+response = agent.create_turn(
+    messages=[{"role": "user", "content": "Analyze this code and run it"}],
+    attachments=[{
+        "content": "https://raw.githubusercontent.com/example/code.py",
+        "mime_type": "text/plain"
+    }],
+    session_id=session_id
+)
+
+# Monitor each step of execution
+for log in EventLogger().log(response):
+    if log.event.step_type == "memory_retrieval":
+        print("Retrieved context:", log.event.retrieved_context)
+    elif log.event.step_type == "inference":
+        print("LLM output:", log.event.model_response)
+    elif log.event.step_type == "tool_execution":
+        print("Tool call:", log.event.tool_call)
+        print("Tool response:", log.event.tool_response)
+    elif log.event.step_type == "shield_call":
+        if log.event.violation:
+            print("Safety violation:", log.event.violation)
+```
diff --git a/docs/source/benchmark_evaluations/index.md b/docs/source/building_applications/evals.md
similarity index 95%
rename from docs/source/benchmark_evaluations/index.md
rename to docs/source/building_applications/evals.md
index 56852c89c..511a3d31d 100644
--- a/docs/source/benchmark_evaluations/index.md
+++ b/docs/source/building_applications/evals.md
@@ -1,8 +1,8 @@
-# Benchmark Evaluations
+# Evals
 
 [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/10CHyykee9j2OigaIcRv47BKG9mrNm0tJ?usp=sharing)
 
-Llama Stack provides the building blocks needed to run benchmark and application evaluations. This guide will walk you through how to use these components to run open benchmark evaluations. Visit our [Evaluation Concepts](../concepts/evaluation_concepts.md) guide for more details on how evaluations work in Llama Stack, and our [Evaluation Reference](../references/evals_reference/index.md) guide for a comprehensive reference on the APIs. Check out our [Colab notebook](https://colab.research.google.com/drive/10CHyykee9j2OigaIcRv47BKG9mrNm0tJ?usp=sharing) on working examples on how you can use Llama Stack for running benchmark evaluations.
+Llama Stack provides the building blocks needed to run benchmark and application evaluations. This guide will walk you through how to use these components to run open benchmark evaluations. Visit our [Evaluation Concepts](../concepts/evaluation_concepts.md) guide for more details on how evaluations work in Llama Stack, and our [Evaluation Reference](../references/evals_reference/index.md) guide for a comprehensive reference on the APIs.
 
 ### 1. Open Benchmark Model Evaluation
 
diff --git a/docs/source/building_applications/evaluation.md b/docs/source/building_applications/evaluation.md
new file mode 100644
index 000000000..473deaee2
--- /dev/null
+++ b/docs/source/building_applications/evaluation.md
@@ -0,0 +1,36 @@
+## Testing & Evaluation
+
+Llama Stack provides built-in tools for evaluating your applications:
+
+1. **Benchmarking**: Test against standard datasets
+2. **Application Evaluation**: Score your application's outputs
+3. **Custom Metrics**: Define your own evaluation criteria
+
+Here's how to set up basic evaluation:
+
+```python
+# Create an evaluation task
+response = client.eval_tasks.register(
+    eval_task_id="my_eval",
+    dataset_id="my_dataset",
+    scoring_functions=["accuracy", "relevance"]
+)
+
+# Run evaluation
+job = client.eval.run_eval(
+    task_id="my_eval",
+    task_config={
+        "type": "app",
+        "eval_candidate": {
+            "type": "agent",
+            "config": agent_config
+        }
+    }
+)
+
+# Get results
+result = client.eval.job_result(
+    task_id="my_eval",
+    job_id=job.job_id
+)
+```
diff --git a/docs/source/building_applications/index.md b/docs/source/building_applications/index.md
index 61b7038cd..45dca5a1c 100644
--- a/docs/source/building_applications/index.md
+++ b/docs/source/building_applications/index.md
@@ -1,425 +1,29 @@
 # Building AI Applications
 
-[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1F2ksmkoGQPa4pzRjMOE6BXWeOxWFIW6n?usp=sharing)
+Llama Stack provides all the building blocks needed to create sophisticated AI applications.
 
-Llama Stack provides all the building blocks needed to create sophisticated AI applications. This guide will walk you through how to use these components effectively. Check out our Colab notebook on to follow along working examples on how you can build LLM-powered agentic applications using Llama Stack.
+The best way to get started is to look at this notebook which walks through the various APIs (from basic inference, to RAG agents) and how to use them.
 
-## Basic Inference
+**Notebook**: [Building AI Applications](https://github.com/meta-llama/llama-stack/blob/main/docs/notebooks/Llama_Stack_Benchmark_Evals.ipynb)
 
-The foundation of any AI application is the ability to interact with LLM models. Llama Stack provides a simple interface for both completion and chat-based inference:
+Here are some key topics that will help you build effective agents:
 
-```python
-from llama_stack_client import LlamaStackClient
+- **[Agent Execution Loop](agent_execution_loop)**
+- **[RAG](rag)**
+- **[Safety](safety)**
+- **[Tools](tools)**
+- **[Telemetry](telemetry)**
+- **[Evals](evals)**
 
-client = LlamaStackClient(base_url="http://localhost:5001")
-
-# List available models
-models = client.models.list()
-
-# Simple chat completion
-response = client.inference.chat_completion(
-    model_id="Llama3.2-3B-Instruct",
-    messages=[
-        {"role": "system", "content": "You are a helpful assistant."},
-        {"role": "user", "content": "Write a haiku about coding"}
-    ]
-)
-print(response.completion_message.content)
-```
-
-## Adding Memory & RAG
-
-Memory enables your applications to reference and recall information from previous interactions or external documents. Llama Stack's memory system is built around the concept of Memory Banks:
-
-1. **Vector Memory Banks**: For semantic search and retrieval
-2. **Key-Value Memory Banks**: For structured data storage
-3. **Keyword Memory Banks**: For basic text search
-4. **Graph Memory Banks**: For relationship-based retrieval
-
-Here's how to set up a vector memory bank for RAG:
-
-```python
-# Register a memory bank
-bank_id = "my_documents"
-response = client.memory_banks.register(
-    memory_bank_id=bank_id,
-    params={
-        "memory_bank_type": "vector",
-        "embedding_model": "all-MiniLM-L6-v2",
-        "chunk_size_in_tokens": 512
-    }
-)
-
-# Insert documents
-documents = [
-    {
-        "document_id": "doc1",
-        "content": "Your document text here",
-        "mime_type": "text/plain"
-    }
-]
-client.memory.insert(bank_id, documents)
-
-# Query documents
-results = client.memory.query(
-    bank_id=bank_id,
-    query="What do you know about...",
-)
-```
-
-## Implementing Safety Guardrails
-
-Safety is a critical component of any AI application. Llama Stack provides a Shield system that can be applied at multiple touchpoints:
-
-```python
-# Register a safety shield
-shield_id = "content_safety"
-client.shields.register(
-    shield_id=shield_id,
-    provider_shield_id="llama-guard-basic"
-)
-
-# Run content through shield
-response = client.safety.run_shield(
-    shield_id=shield_id,
-    messages=[{"role": "user", "content": "User message here"}]
-)
-
-if response.violation:
-    print(f"Safety violation detected: {response.violation.user_message}")
-```
-
-## Building Agents
-
-Agents are the heart of complex AI applications. They combine inference, memory, safety, and tool usage into coherent workflows. At its core, an agent follows a sophisticated execution loop that enables multi-step reasoning, tool usage, and safety checks.
-
-### The Agent Execution Loop
-
-Each agent turn follows these key steps:
-
-1. **Initial Safety Check**: The user's input is first screened through configured safety shields
-
-2. **Context Retrieval**:
-   - If RAG is enabled, the agent queries relevant documents from memory banks
-   - For new documents, they are first inserted into the memory bank
-   - Retrieved context is augmented to the user's prompt
-
-3. **Inference Loop**: The agent enters its main execution loop:
-   - The LLM receives the augmented prompt (with context and/or previous tool outputs)
-   - The LLM generates a response, potentially with tool calls
-   - If tool calls are present:
-     - Tool inputs are safety-checked
-     - Tools are executed (e.g., web search, code execution)
-     - Tool responses are fed back to the LLM for synthesis
-   - The loop continues until:
-     - The LLM provides a final response without tool calls
-     - Maximum iterations are reached
-     - Token limit is exceeded
-
-4. **Final Safety Check**: The agent's final response is screened through safety shields
-
-```{mermaid}
-sequenceDiagram
-    participant U as User
-    participant E as Executor
-    participant M as Memory Bank
-    participant L as LLM
-    participant T as Tools
-    participant S as Safety Shield
-
-    Note over U,S: Agent Turn Start
-    U->>S: 1. Submit Prompt
-    activate S
-    S->>E: Input Safety Check
-    deactivate S
-
-    E->>M: 2.1 Query Context
-    M-->>E: 2.2 Retrieved Documents
-
-    loop Inference Loop
-        E->>L: 3.1 Augment with Context
-        L-->>E: 3.2 Response (with/without tool calls)
-
-        alt Has Tool Calls
-            E->>S: Check Tool Input
-            S->>T: 4.1 Execute Tool
-            T-->>E: 4.2 Tool Response
-            E->>L: 5.1 Tool Response
-            L-->>E: 5.2 Synthesized Response
-        end
-
-        opt Stop Conditions
-            Note over E: Break if:
-            Note over E: - No tool calls
-            Note over E: - Max iterations reached
-            Note over E: - Token limit exceeded
-        end
-    end
-
-    E->>S: Output Safety Check
-    S->>U: 6. Final Response
-```
-
-Each step in this process can be monitored and controlled through configurations. Here's an example that demonstrates monitoring the agent's execution:
-
-```python
-from llama_stack_client.lib.agents.event_logger import EventLogger
-
-agent_config = AgentConfig(
-    model="Llama3.2-3B-Instruct",
-    instructions="You are a helpful assistant",
-    # Enable both RAG and tool usage
-    tools=[
-        {
-            "type": "memory",
-            "memory_bank_configs": [{
-                "type": "vector",
-                "bank_id": "my_docs"
-            }],
-            "max_tokens_in_context": 4096
-        },
-        {
-            "type": "code_interpreter",
-            "enable_inline_code_execution": True
-        }
-    ],
-    # Configure safety
-    input_shields=["content_safety"],
-    output_shields=["content_safety"],
-    # Control the inference loop
-    max_infer_iters=5,
-    sampling_params={
-        "strategy": {
-            "type": "top_p",
-            "temperature": 0.7,
-            "top_p": 0.95
-        },
-        "max_tokens": 2048
-    }
-)
-
-agent = Agent(client, agent_config)
-session_id = agent.create_session("monitored_session")
-
-# Stream the agent's execution steps
-response = agent.create_turn(
-    messages=[{"role": "user", "content": "Analyze this code and run it"}],
-    attachments=[{
-        "content": "https://raw.githubusercontent.com/example/code.py",
-        "mime_type": "text/plain"
-    }],
-    session_id=session_id
-)
-
-# Monitor each step of execution
-for log in EventLogger().log(response):
-    if log.event.step_type == "memory_retrieval":
-        print("Retrieved context:", log.event.retrieved_context)
-    elif log.event.step_type == "inference":
-        print("LLM output:", log.event.model_response)
-    elif log.event.step_type == "tool_execution":
-        print("Tool call:", log.event.tool_call)
-        print("Tool response:", log.event.tool_response)
-    elif log.event.step_type == "shield_call":
-        if log.event.violation:
-            print("Safety violation:", log.event.violation)
-```
-
-This example shows how an agent can: Llama Stack provides a high-level agent framework:
-
-```python
-from llama_stack_client.lib.agents.agent import Agent
-from llama_stack_client.types.agent_create_params import AgentConfig
-
-# Configure an agent
-agent_config = AgentConfig(
-    model="Llama3.2-3B-Instruct",
-    instructions="You are a helpful assistant",
-    tools=[
-        {
-            "type": "memory",
-            "memory_bank_configs": [],
-            "query_generator_config": {
-                "type": "default",
-                "sep": " "
-            }
-        }
-    ],
-    input_shields=["content_safety"],
-    output_shields=["content_safety"],
-    enable_session_persistence=True
-)
-
-# Create an agent
-agent = Agent(client, agent_config)
-session_id = agent.create_session("my_session")
-
-# Run agent turns
-response = agent.create_turn(
-    messages=[{"role": "user", "content": "Your question here"}],
-    session_id=session_id
-)
-```
-
-### Adding Tools to Agents
-
-Agents can be enhanced with various tools:
-
-1. **Search**: Web search capabilities through providers like Brave
-2. **Code Interpreter**: Execute code snippets
-3. **RAG**: Memory and document retrieval
-4. **Function Calling**: Custom function execution
-5. **WolframAlpha**: Mathematical computations
-6. **Photogen**: Image generation
-
-Example of configuring an agent with tools:
-
-```python
-agent_config = AgentConfig(
-    model="Llama3.2-3B-Instruct",
-    tools=[
-        {
-            "type": "brave_search",
-            "api_key": "YOUR_API_KEY",
-            "engine": "brave"
-        },
-        {
-            "type": "code_interpreter",
-            "enable_inline_code_execution": True
-        }
-    ],
-    tool_choice="auto",
-    tool_prompt_format="json"
-)
-```
-
-## Building RAG-Enhanced Agents
-
-One of the most powerful patterns is combining agents with RAG capabilities. Here's a complete example:
-
-```python
-from llama_stack_client.types import Attachment
-
-# Create attachments from documents
-attachments = [
-    Attachment(
-        content="https://raw.githubusercontent.com/example/doc.rst",
-        mime_type="text/plain"
-    )
-]
-
-# Configure agent with memory
-agent_config = AgentConfig(
-    model="Llama3.2-3B-Instruct",
-    instructions="You are a helpful assistant",
-    tools=[{
-        "type": "memory",
-        "memory_bank_configs": [],
-        "query_generator_config": {"type": "default", "sep": " "},
-        "max_tokens_in_context": 4096,
-        "max_chunks": 10
-    }],
-    enable_session_persistence=True
-)
-
-agent = Agent(client, agent_config)
-session_id = agent.create_session("rag_session")
-
-# Initial document ingestion
-response = agent.create_turn(
-    messages=[{
-        "role": "user",
-        "content": "I am providing some documents for reference."
-    }],
-    attachments=attachments,
-    session_id=session_id
-)
-
-# Query with RAG
-response = agent.create_turn(
-    messages=[{
-        "role": "user",
-        "content": "What are the key topics in the documents?"
-    }],
-    session_id=session_id
-)
-```
-
-## Testing & Evaluation
-
-Llama Stack provides built-in tools for evaluating your applications:
-
-1. **Benchmarking**: Test against standard datasets
-2. **Application Evaluation**: Score your application's outputs
-3. **Custom Metrics**: Define your own evaluation criteria
-
-Here's how to set up basic evaluation:
-
-```python
-# Create an evaluation task
-response = client.eval_tasks.register(
-    eval_task_id="my_eval",
-    dataset_id="my_dataset",
-    scoring_functions=["accuracy", "relevance"]
-)
-
-# Run evaluation
-job = client.eval.run_eval(
-    task_id="my_eval",
-    task_config={
-        "type": "app",
-        "eval_candidate": {
-            "type": "agent",
-            "config": agent_config
-        }
-    }
-)
-
-# Get results
-result = client.eval.job_result(
-    task_id="my_eval",
-    job_id=job.job_id
-)
-```
-
-## Debugging & Monitoring
-
-Llama Stack includes comprehensive telemetry for debugging and monitoring your applications:
-
-1. **Tracing**: Track request flows across components
-2. **Metrics**: Measure performance and usage
-3. **Logging**: Debug issues and track behavior
-
-The telemetry system supports multiple output formats:
-
-- OpenTelemetry for visualization in tools like Jaeger
-- SQLite for local storage and querying
-- Console output for development
-
-Example of querying traces:
-
-```python
-# Query traces for a session
-traces = client.telemetry.query_traces(
-    attribute_filters=[{
-        "key": "session_id",
-        "op": "eq",
-        "value": session_id
-    }]
-)
-
-# Get spans within the root span; indexed by ID
-# Use parent_span_id to build a tree out of it
-spans_by_id = client.telemetry.get_span_tree(
-    span_id=traces[0].root_span_id
-)
-```
-
-For details on how to use the telemetry system to debug your applications, export traces to a dataset, and run evaluations, see the [Telemetry](telemetry) section.
 
 ```{toctree}
 :hidden:
-:maxdepth: 3
+:maxdepth: 1
 
+agent_execution_loop
+rag
+safety
+tools
 telemetry
+evals
 ```
diff --git a/docs/source/building_applications/rag.md b/docs/source/building_applications/rag.md
new file mode 100644
index 000000000..17ecd2046
--- /dev/null
+++ b/docs/source/building_applications/rag.md
@@ -0,0 +1,92 @@
+## Memory & RAG
+
+Memory enables your applications to reference and recall information from previous interactions or external documents. Llama Stack's memory system is built around the concept of Memory Banks:
+
+1. **Vector Memory Banks**: For semantic search and retrieval
+2. **Key-Value Memory Banks**: For structured data storage
+3. **Keyword Memory Banks**: For basic text search
+4. **Graph Memory Banks**: For relationship-based retrieval
+
+Here's how to set up a vector memory bank for RAG:
+
+```python
+# Register a memory bank
+bank_id = "my_documents"
+response = client.memory_banks.register(
+    memory_bank_id=bank_id,
+    params={
+        "memory_bank_type": "vector",
+        "embedding_model": "all-MiniLM-L6-v2",
+        "chunk_size_in_tokens": 512
+    }
+)
+
+# Insert documents
+documents = [
+    {
+        "document_id": "doc1",
+        "content": "Your document text here",
+        "mime_type": "text/plain"
+    }
+]
+client.memory.insert(bank_id, documents)
+
+# Query documents
+results = client.memory.query(
+    bank_id=bank_id,
+    query="What do you know about...",
+)
+```
+
+
+### Building RAG-Enhanced Agents
+
+One of the most powerful patterns is combining agents with RAG capabilities. Here's a complete example:
+
+```python
+from llama_stack_client.types import Attachment
+
+# Create attachments from documents
+attachments = [
+    Attachment(
+        content="https://raw.githubusercontent.com/example/doc.rst",
+        mime_type="text/plain"
+    )
+]
+
+# Configure agent with memory
+agent_config = AgentConfig(
+    model="Llama3.2-3B-Instruct",
+    instructions="You are a helpful assistant",
+    tools=[{
+        "type": "memory",
+        "memory_bank_configs": [],
+        "query_generator_config": {"type": "default", "sep": " "},
+        "max_tokens_in_context": 4096,
+        "max_chunks": 10
+    }],
+    enable_session_persistence=True
+)
+
+agent = Agent(client, agent_config)
+session_id = agent.create_session("rag_session")
+
+# Initial document ingestion
+response = agent.create_turn(
+    messages=[{
+        "role": "user",
+        "content": "I am providing some documents for reference."
+    }],
+    attachments=attachments,
+    session_id=session_id
+)
+
+# Query with RAG
+response = agent.create_turn(
+    messages=[{
+        "role": "user",
+        "content": "What are the key topics in the documents?"
+    }],
+    session_id=session_id
+)
+```
diff --git a/docs/source/building_applications/safety.md b/docs/source/building_applications/safety.md
new file mode 100644
index 000000000..31efa0f8c
--- /dev/null
+++ b/docs/source/building_applications/safety.md
@@ -0,0 +1,21 @@
+## Safety Guardrails
+
+Safety is a critical component of any AI application. Llama Stack provides a Shield system that can be applied at multiple touchpoints:
+
+```python
+# Register a safety shield
+shield_id = "content_safety"
+client.shields.register(
+    shield_id=shield_id,
+    provider_shield_id="llama-guard-basic"
+)
+
+# Run content through shield
+response = client.safety.run_shield(
+    shield_id=shield_id,
+    messages=[{"role": "user", "content": "User message here"}]
+)
+
+if response.violation:
+    print(f"Safety violation detected: {response.violation.user_message}")
+```
diff --git a/docs/source/building_applications/telemetry.md b/docs/source/building_applications/telemetry.md
index 70c54ac98..4b4397d1e 100644
--- a/docs/source/building_applications/telemetry.md
+++ b/docs/source/building_applications/telemetry.md
@@ -1,14 +1,7 @@
-# Telemetry
-```{note}
-The telemetry system is currently experimental and subject to change. We welcome feedback and contributions to help improve it.
-```
-
-
+## Telemetry
 
 The Llama Stack telemetry system provides comprehensive tracing, metrics, and logging capabilities. It supports multiple sink types including OpenTelemetry, SQLite, and Console output.
 
-## Key Concepts
-
 ### Events
 The telemetry system supports three main types of events:
 
@@ -44,67 +37,15 @@ structured_log_event = SpanStartPayload(
 - **SQLite**: Store events in a local SQLite database. This is needed if you want to query the events later through the Llama Stack API.
 - **Console**: Print events to the console.
 
-## APIs
+### Providers
 
-The telemetry API is designed to be flexible for different user flows like debugging/visualization in UI, monitoring, and saving traces to datasets.
-The telemetry system exposes the following HTTP endpoints:
-
-### Log Event
-```http
-POST /telemetry/log-event
-```
-Logs a telemetry event (unstructured log, metric, or structured log) with optional TTL.
-
-### Query Traces
-```http
-POST /telemetry/query-traces
-```
-Retrieves traces based on filters with pagination support. Parameters:
-- `attribute_filters`: List of conditions to filter traces
-- `limit`: Maximum number of traces to return (default: 100)
-- `offset`: Number of traces to skip (default: 0)
-- `order_by`: List of fields to sort by
-
-### Get Span Tree
-```http
-POST /telemetry/get-span-tree
-```
-Retrieves a hierarchical view of spans starting from a specific span. Parameters:
-- `span_id`: ID of the root span to retrieve
-- `attributes_to_return`: Optional list of specific attributes to include
-- `max_depth`: Optional maximum depth of the span tree to return
-
-### Query Spans
-```http
-POST /telemetry/query-spans
-```
-Retrieves spans matching specified filters and returns selected attributes. Parameters:
-- `attribute_filters`: List of conditions to filter traces
-- `attributes_to_return`: List of specific attributes to include in results
-- `max_depth`: Optional maximum depth of spans to traverse (default: no limit)
-
-Returns a flattened list of spans with requested attributes.
-
-### Save Spans to Dataset
-This is useful for saving traces to a dataset for running evaluations. For example, you can save the input/output of each span that is part of an agent session/turn to a dataset and then run an eval task on it. See example in [Example: Save Spans to Dataset](#example-save-spans-to-dataset).
-```http
-POST /telemetry/save-spans-to-dataset
-```
-Queries spans and saves their attributes to a dataset. Parameters:
-- `attribute_filters`: List of conditions to filter traces
-- `attributes_to_save`: List of span attributes to save to the dataset
-- `dataset_id`: ID of the dataset to save to
-- `max_depth`: Optional maximum depth of spans to traverse (default: no limit)
-
-## Providers
-
-### Meta-Reference Provider
+#### Meta-Reference Provider
 Currently, only the meta-reference provider is implemented. It can be configured to send events to three sink types:
 1) OpenTelemetry Collector
 2) SQLite
 3) Console
 
-## Configuration
+#### Configuration
 
 Here's an example that sends telemetry signals to all three sink types. Your configuration might use only one.
 ```yaml
@@ -117,7 +58,7 @@ Here's an example that sends telemetry signals to all three sink types. Your con
       sqlite_db_path: "/path/to/telemetry.db"
 ```
 
-## Jaeger to visualize traces
+### Jaeger to visualize traces
 
 The `otel` sink works with any service compatible with the OpenTelemetry collector. Let's use Jaeger to visualize this data.
 
@@ -131,112 +72,6 @@ $ docker run --rm --name jaeger \
 
 Once the Jaeger instance is running, you can visualize traces by navigating to http://localhost:16686/.
 
-## Querying Traces Stored in SQLIte
+### Querying Traces Stored in SQLite
 
-The `sqlite` sink allows you to query traces without an external system. Here are some example queries:
-
-Querying Traces for a agent session
-The client SDK is not updated to support the new telemetry API. It will be updated soon. You can manually query traces using the following curl command:
-
-``` bash
- curl -X POST 'http://localhost:8321/alpha/telemetry/query-traces' \
--H 'Content-Type: application/json' \
--d '{
-  "attribute_filters": [
-    {
-      "key": "session_id",
-      "op": "eq",
-      "value": "dd667b87-ca4b-4d30-9265-5a0de318fc65" }],
-  "limit": 100,
-  "offset": 0,
-  "order_by": ["start_time"]
-
-  [
-  {
-    "trace_id": "6902f54b83b4b48be18a6f422b13e16f",
-    "root_span_id": "5f37b85543afc15a",
-    "start_time": "2024-12-04T08:08:30.501587",
-    "end_time": "2024-12-04T08:08:36.026463"
-  },
-  ........
-]
-}'
-
-```
-
-Querying spans for a specifc root span id
-
-``` bash
-curl -X POST 'http://localhost:8321/alpha/telemetry/get-span-tree' \
--H 'Content-Type: application/json' \
--d '{ "span_id" : "6cceb4b48a156913", "max_depth": 2 }'
-
-{
-  "span_id": "6cceb4b48a156913",
-  "trace_id": "dafa796f6aaf925f511c04cd7c67fdda",
-  "parent_span_id": "892a66d726c7f990",
-  "name": "retrieve_rag_context",
-  "start_time": "2024-12-04T09:28:21.781995",
-  "end_time": "2024-12-04T09:28:21.913352",
-  "attributes": {
-    "input": [
-      "{\"role\":\"system\",\"content\":\"You are a helpful assistant\"}",
-      "{\"role\":\"user\",\"content\":\"What are the top 5 topics that were explained in the documentation? Only list succinct bullet points.\",\"context\":null}"
-    ]
-  },
-  "children": [
-    {
-      "span_id": "1a2df181854064a8",
-      "trace_id": "dafa796f6aaf925f511c04cd7c67fdda",
-      "parent_span_id": "6cceb4b48a156913",
-      "name": "MemoryRouter.query_documents",
-      "start_time": "2024-12-04T09:28:21.787620",
-      "end_time": "2024-12-04T09:28:21.906512",
-      "attributes": {
-        "input": null
-      },
-      "children": [],
-      "status": "ok"
-    }
-  ],
-  "status": "ok"
-}
-
-```
-
-## Example: Save Spans to Dataset
-Save all spans for a specific agent session to a dataset.
-``` bash
-curl -X POST 'http://localhost:8321/alpha/telemetry/save-spans-to-dataset' \
--H 'Content-Type: application/json' \
--d '{
-    "attribute_filters": [
-        {
-            "key": "session_id",
-            "op": "eq",
-            "value": "dd667b87-ca4b-4d30-9265-5a0de318fc65"
-        }
-    ],
-    "attributes_to_save": ["input", "output"],
-    "dataset_id": "my_dataset",
-    "max_depth": 10
-}'
-```
-
-Save all spans for a specific agent turn to a dataset.
-```bash
-curl -X POST 'http://localhost:8321/alpha/telemetry/save-spans-to-dataset' \
--H 'Content-Type: application/json' \
--d '{
-    "attribute_filters": [
-        {
-            "key": "turn_id",
-            "op": "eq",
-            "value": "123e4567-e89b-12d3-a456-426614174000"
-        }
-    ],
-    "attributes_to_save": ["input", "output"],
-    "dataset_id": "my_dataset",
-    "max_depth": 10
-}'
-```
+The `sqlite` sink allows you to query traces without an external system. Here are some example queries. Refer to the notebook at [Llama Stack Building AI Applications](https://github.com/meta-llama/llama-stack/blob/main/docs/getting_started.ipynb) for more examples on how to query traces and spaces.
diff --git a/docs/source/building_applications/tools.md b/docs/source/building_applications/tools.md
new file mode 100644
index 000000000..c4229b64d
--- /dev/null
+++ b/docs/source/building_applications/tools.md
@@ -0,0 +1,202 @@
+# Tools
+
+Tools are functions that can be invoked by an agent to perform tasks. They are organized into tool groups and registered with specific providers. Each tool group represents a collection of related tools from a single provider. They are organized into groups so that state can be externalized: the collection operates on the same state typically.
+An example of this would be a "db_access" tool group that contains tools for interacting with a database. "list_tables", "query_table", "insert_row" could be examples of tools in this group.
+
+Tools are treated as any other resource in llama stack like models. You can register them, have providers for them etc.
+
+When instatiating an agent, you can provide it a list of tool groups that it has access to. Agent gets the corresponding tool definitions for the specified tool groups and passes them along to the model.
+
+Refer to the [Building AI Applications](https://github.com/meta-llama/llama-stack/blob/main/docs/getting_started.ipynb) notebook for more examples on how to use tools.
+
+## Types of Tool Group providers
+
+There are three types of providers for tool groups that are supported by Llama Stack.
+
+1. Built-in providers
+2. Model Context Protocol (MCP) providers
+3. Client provided tools
+
+### Built-in providers
+
+Built-in providers come packaged with Llama Stack. These providers provide common functionalities like web search, code interpretation, and computational capabilities.
+
+#### Web Search providers
+There are three web search providers that are supported by Llama Stack.
+
+1. Brave Search
+2. Bing Search
+3. Tavily Search
+
+Example client SDK call to register a "websearch" toolgroup that is provided by brave-search.
+
+```python
+# Register Brave Search tool group
+client.toolgroups.register(
+    toolgroup_id="builtin::websearch",
+    provider_id="brave-search",
+    args={"max_results": 5}
+)
+```
+
+The tool requires an API key which can be provided either in the configuration or through the request header `X-LlamaStack-Provider-Data`. The format of the header is `{"<provider_name>_api_key": <your api key>}`.
+
+
+
+#### Code Interpreter
+
+The Code Interpreter allows execution of Python code within a controlled environment.
+
+```python
+# Register Code Interpreter tool group
+client.toolgroups.register(
+    toolgroup_id="builtin::code_interpreter",
+    provider_id="code_interpreter"
+)
+```
+
+Features:
+- Secure execution environment using `bwrap` sandboxing
+- Matplotlib support for generating plots
+- Disabled dangerous system operations
+- Configurable execution timeouts
+
+#### WolframAlpha
+
+The WolframAlpha tool provides access to computational knowledge through the WolframAlpha API.
+
+```python
+# Register WolframAlpha tool group
+client.toolgroups.register(
+    toolgroup_id="builtin::wolfram_alpha",
+    provider_id="wolfram-alpha"
+)
+```
+
+Example usage:
+```python
+result = client.tool_runtime.invoke_tool(
+    tool_name="wolfram_alpha",
+    args={"query": "solve x^2 + 2x + 1 = 0"}
+)
+```
+
+#### Memory
+
+The Memory tool enables retrieval of context from various types of memory banks (vector, key-value, keyword, and graph).
+
+```python
+# Register Memory tool group
+client.toolgroups.register(
+    toolgroup_id="builtin::memory",
+    provider_id="memory",
+    args={
+        "max_chunks": 5,
+        "max_tokens_in_context": 4096
+    }
+)
+```
+
+Features:
+- Support for multiple memory bank types
+- Configurable query generation
+- Context retrieval with token limits
+
+
+> **Note:** By default, llama stack run.yaml defines toolgroups for web search, code interpreter and memory, that are provided by tavily-search, code-interpreter and memory providers.
+
+## Model Context Protocol (MCP) Tools
+
+MCP tools are special tools that can interact with llama stack over model context protocol. These tools are dynamically discovered from an MCP endpoint and can be used to extend the agent's capabilities.
+
+Refer to https://github.com/modelcontextprotocol/server for available MCP servers.
+
+```python
+# Register MCP tools
+client.toolgroups.register(
+    toolgroup_id="builtin::filesystem",
+    provider_id="model-context-protocol",
+    mcp_endpoint=URL(uri="http://localhost:8000/sse"),
+)
+```
+
+MCP tools require:
+- A valid MCP endpoint URL
+- The endpoint must implement the Model Context Protocol
+- Tools are discovered dynamically from the endpoint
+
+
+## Tools provided by the client
+
+These tools are registered along with the agent config and are specific to the agent for which they are registered. The main difference between these tools and the tools provided by the built-in providers is that the execution of these tools is handled by the client and the agent transfers the tool call to the client and waits for the result from the client.
+
+```python
+# Example agent config with client provided tools
+config = AgentConfig(
+    toolgroups=[
+        "builtin::websearch",
+    ],
+    client_tools=[
+        ToolDef(name="client_tool", description="Client provided tool")
+    ]
+)
+```
+
+Refer to [llama-stack-apps](https://github.com/meta-llama/llama-stack-apps/blob/main/examples/agents/e2e_loop_with_client_tools.py) for an example of how to use client provided tools.
+
+## Tool Structure
+
+Each tool has the following components:
+
+- `name`: Unique identifier for the tool
+- `description`: Human-readable description of the tool's functionality
+- `parameters`: List of parameters the tool accepts
+  - `name`: Parameter name
+  - `parameter_type`: Data type (string, number, etc.)
+  - `description`: Parameter description
+  - `required`: Whether the parameter is required (default: true)
+  - `default`: Default value if any
+
+Example tool definition:
+```python
+{
+    "name": "web_search",
+    "description": "Search the web for information",
+    "parameters": [
+        {
+            "name": "query",
+            "parameter_type": "string",
+            "description": "The query to search for",
+            "required": True
+        }
+    ]
+}
+```
+
+## Tool Invocation
+
+Tools can be invoked using the `invoke_tool` method:
+
+```python
+result = client.tool_runtime.invoke_tool(
+    tool_name="web_search",
+    kwargs={"query": "What is the capital of France?"}
+)
+```
+
+The result contains:
+- `content`: The tool's output
+- `error_message`: Optional error message if the tool failed
+- `error_code`: Optional error code if the tool failed
+
+## Listing Available Tools
+
+You can list all available tools or filter by tool group:
+
+```python
+# List all tools
+all_tools = client.tools.list_tools()
+
+# List tools in a specific group
+group_tools = client.tools.list_tools(toolgroup_id="search_tools")
+```
diff --git a/docs/source/concepts/index.md b/docs/source/concepts/index.md
index 32caa66a5..834b7d7cd 100644
--- a/docs/source/concepts/index.md
+++ b/docs/source/concepts/index.md
@@ -10,7 +10,6 @@ A Llama Stack API is described as a collection of REST endpoints. We currently s
 - **Inference**: run inference with a LLM
 - **Safety**: apply safety policies to the output at a Systems (not only model) level
 - **Agents**: run multi-step agentic workflows with LLMs with tool usage, memory (RAG), etc.
-- **Memory**: store and retrieve data for RAG, chat history, etc.
 - **DatasetIO**: interface with datasets and data loaders
 - **Scoring**: evaluate outputs of the system
 - **Eval**: generate outputs (via Inference or Agents) and perform scoring
@@ -24,22 +23,23 @@ We are working on adding a few more APIs to complete the application lifecycle.
 
 ## API Providers
 
-The goal of Llama Stack is to build an ecosystem where users can easily swap out different implementations for the same API. Obvious examples for these include
-- LLM inference providers (e.g., Fireworks, Together, AWS Bedrock, etc.),
-- Vector databases (e.g., ChromaDB, Weaviate, Qdrant, etc.),
+The goal of Llama Stack is to build an ecosystem where users can easily swap out different implementations for the same API. Examples for these include:
+- LLM inference providers (e.g., Fireworks, Together, AWS Bedrock, Groq, Cerebras, SambaNova, etc.),
+- Vector databases (e.g., ChromaDB, Weaviate, Qdrant, FAISS, PGVector, etc.),
 - Safety providers (e.g., Meta's Llama Guard, AWS Bedrock Guardrails, etc.)
 
 Providers come in two flavors:
 - **Remote**: the provider runs as a separate service external to the Llama Stack codebase. Llama Stack contains a small amount of adapter code.
 - **Inline**: the provider is fully specified and implemented within the Llama Stack codebase. It may be a simple wrapper around an existing library, or a full fledged implementation within Llama Stack.
 
+Most importantly, Llama Stack always strives to provide at least one fully "local" provider for each API so you can iterate on a fully featured environment locally.
 ## Resources
 
 Some of these APIs are associated with a set of **Resources**. Here is the mapping of APIs to resources:
 
 - **Inference**, **Eval** and **Post Training** are associated with `Model` resources.
 - **Safety** is associated with `Shield` resources.
-- **Memory** is associated with `Memory Bank` resources.
+- **Tool Runtime** is associated with `ToolGroup` resources.
 - **DatasetIO** is associated with `Dataset` resources.
 - **Scoring** is associated with `ScoringFunction` resources.
 - **Eval** is associated with `Model` and `EvalTask` resources.
@@ -58,17 +58,14 @@ While there is a lot of flexibility to mix-and-match providers, often users will
 
 **Remotely Hosted Distro**: These are the simplest to consume from a user perspective. You can simply obtain the API key for these providers, point to a URL and have _all_ Llama Stack APIs working out of the box. Currently, [Fireworks](https://fireworks.ai/) and [Together](https://together.xyz/) provide such easy-to-consume Llama Stack distributions.
 
-**Locally Hosted Distro**: You may want to run Llama Stack on your own hardware. Typically though, you still need to use Inference via an external service. You can use providers like HuggingFace TGI, Cerebras, Fireworks, Together, etc. for this purpose. Or you may have access to GPUs and can run a [vLLM](https://github.com/vllm-project/vllm) or [NVIDIA NIM](https://build.nvidia.com/nim?filters=nimType%3Anim_type_run_anywhere&q=llama) instance. If you "just" have a regular desktop machine, you can use [Ollama](https://ollama.com/) for inference. To provide convenient quick access to these options, we provide a number of such pre-configured locally-hosted Distros.
+**Locally Hosted Distro**: You may want to run Llama Stack on your own hardware. Typically though, you still need to use Inference via an external service. You can use providers like HuggingFace TGI, Fireworks, Together, etc. for this purpose. Or you may have access to GPUs and can run a [vLLM](https://github.com/vllm-project/vllm) or [NVIDIA NIM](https://build.nvidia.com/nim?filters=nimType%3Anim_type_run_anywhere&q=llama) instance. If you "just" have a regular desktop machine, you can use [Ollama](https://ollama.com/) for inference. To provide convenient quick access to these options, we provide a number of such pre-configured locally-hosted Distros.
 
 
 **On-device Distro**: Finally, you may want to run Llama Stack directly on an edge device (mobile phone or a tablet.) We provide Distros for iOS and Android (coming soon.)
 
-## More Concepts
-- [Evaluation Concepts](evaluation_concepts.md)
-
 ```{toctree}
 :maxdepth: 1
 :hidden:
 
-evaluation_concepts
+distributions/index
 ```
diff --git a/docs/source/contributing/index.md b/docs/source/contributing/index.md
index 9f4715d5c..8f89ea9f2 100644
--- a/docs/source/contributing/index.md
+++ b/docs/source/contributing/index.md
@@ -1,9 +1,14 @@
 # Contributing to Llama Stack
 
+Start with the [Contributing Guide](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md) for some general tips. This section covers a few key topics in more detail.
+
+- [Adding a New API Provider](new_api_provider.md) describes adding new API providers to the Stack.
+- [Testing Llama Stack](testing.md) provides details about the testing framework and how to test providers and distributions.
 
 ```{toctree}
 :maxdepth: 1
+:hidden:
 
 new_api_provider
-memory_api
+testing
 ```
diff --git a/docs/source/contributing/memory_api.md b/docs/source/contributing/memory_api.md
deleted file mode 100644
index be486ae8f..000000000
--- a/docs/source/contributing/memory_api.md
+++ /dev/null
@@ -1,53 +0,0 @@
-# Memory API Providers
-
-This guide gives you references to switch between different memory API providers.
-
-##### pgvector
-1. Start running the pgvector server:
-
-```
-$ docker run --network host --name mypostgres -it -p 5432:5432 -e POSTGRES_PASSWORD=mysecretpassword -e POSTGRES_USER=postgres -e POSTGRES_DB=postgres pgvector/pgvector:pg16
-```
-
-2. Edit the `run.yaml` file to point to the pgvector server.
-```
-memory:
-  - provider_id: pgvector
-    provider_type: remote::pgvector
-    config:
-      host: 127.0.0.1
-      port: 5432
-      db: postgres
-      user: postgres
-      password: mysecretpassword
-```
-
-> [!NOTE]
-> If you get a `RuntimeError: Vector extension is not installed.`. You will need to run `CREATE EXTENSION IF NOT EXISTS vector;` to include the vector extension. E.g.
-
-```
-docker exec -it mypostgres ./bin/psql -U postgres
-postgres=# CREATE EXTENSION IF NOT EXISTS vector;
-postgres=# SELECT extname from pg_extension;
- extname
-```
-
-3. Run `docker compose up` with the updated `run.yaml` file.
-
-##### chromadb
-1. Start running chromadb server
-```
-docker run -it --network host --name chromadb -p 6000:6000 -v ./chroma_vdb:/chroma/chroma -e IS_PERSISTENT=TRUE chromadb/chroma:latest
-```
-
-2. Edit the `run.yaml` file to point to the chromadb server.
-```
-memory:
-  - provider_id: remote::chromadb
-    provider_type: remote::chromadb
-    config:
-      host: localhost
-      port: 6000
-```
-
-3. Run `docker compose up` with the updated `run.yaml` file.
diff --git a/docs/source/contributing/new_api_provider.md b/docs/source/contributing/new_api_provider.md
index 3fa875c50..1dd836a16 100644
--- a/docs/source/contributing/new_api_provider.md
+++ b/docs/source/contributing/new_api_provider.md
@@ -1,26 +1,41 @@
 # Adding a New API Provider
 
-This guide contains references to walk you through adding a new API provider.
+This guide will walk you through the process of adding a new API provider to Llama Stack.
 
-1. First, decide which API your provider falls into (e.g. Inference, Safety, Agents, Memory).
-2. Decide whether your provider is a remote provider, or inline implementation. A remote provider is a provider that makes a remote request to a service. An inline provider is a provider where implementation is executed locally. Checkout the examples, and follow the structure to add your own API provider. Please find the following code pointers:
 
-    - {repopath}`Remote Providers::llama_stack/providers/remote`
-    - {repopath}`Inline Providers::llama_stack/providers/inline`
+- Begin by reviewing the [core concepts](../concepts/) of Llama Stack and choose the API your provider belongs to (Inference, Safety, VectorIO, etc.)
+- Determine the provider type ({repopath}`Remote::llama_stack/providers/remote` or {repopath}`Inline::llama_stack/providers/inline`). Remote providers make requests to external services, while inline providers execute implementation locally.
+- Add your provider to the appropriate {repopath}`Registry::llama_stack/providers/registry/`. Specify pip dependencies necessary.
+- Update any distribution {repopath}`Templates::llama_stack/templates/` build.yaml and run.yaml files if they should include your provider by default. Run {repopath}`llama_stack/scripts/distro_codegen.py` if necessary.
 
-3. [Build a Llama Stack distribution](https://llama-stack.readthedocs.io/en/latest/distributions/building_distro.html) with your API provider.
-4. Test your code!
 
-## Testing your newly added API providers
+Here are some example PRs to help you get started:
+   - [Grok Inference Implementation](https://github.com/meta-llama/llama-stack/pull/609)
+   - [Nvidia Inference Implementation](https://github.com/meta-llama/llama-stack/pull/355)
+   - [Model context protocol Tool Runtime](https://github.com/meta-llama/llama-stack/pull/665)
 
-1. Start with an _integration test_ for your provider. That means we will instantiate the real provider, pass it real configuration and if it is a remote service, we will actually hit the remote service. We **strongly** discourage mocking for these tests at the provider level. Llama Stack is first and foremost about integration so we need to make sure stuff works end-to-end. See {repopath}`llama_stack/providers/tests/inference/test_text_inference.py` for an example.
 
-2. In addition, if you want to unit test functionality within your provider, feel free to do so. You can find some tests in `tests/` but they aren't well-supported so far.
+## Testing the Provider
 
-3. Test with a client-server Llama Stack setup. (a) Start a Llama Stack server with your own distribution which includes the new provider. (b) Send a client request to the server. See `llama_stack/apis/<api>/client.py` for how this is done. These client scripts can serve as lightweight tests.
+### 1. Integration Testing
+- Create integration tests that use real provider instances and configurations
+- For remote services, test actual API interactions
+- Avoid mocking at the provider level since adapter layers tend to be thin
+- Reference examples in {repopath}`tests/client-sdk`
 
-You can find more complex client scripts [llama-stack-apps](https://github.com/meta-llama/llama-stack-apps/tree/main) repo. Note down which scripts works and do not work with your distribution.
+### 2. Unit Testing (Optional)
+- Add unit tests for provider-specific functionality
+- See examples in {repopath}`llama_stack/providers/tests/inference/test_text_inference.py`
 
-## Submit your PR
+### 3. End-to-End Testing
+1. Start a Llama Stack server with your new provider
+2. Test using client requests
+3. Verify compatibility with existing client scripts in the [llama-stack-apps](https://github.com/meta-llama/llama-stack-apps/tree/main) repository
+4. Document which scripts are compatible with your provider
 
-After you have fully tested your newly added API provider, submit a PR with the attached test plan. You must have a Test Plan in the summary section of your PR.
+## Submitting Your PR
+
+1. Ensure all tests pass
+2. Include a comprehensive test plan in your PR summary
+3. Document any known limitations or considerations
+4. Submit your pull request for review
diff --git a/docs/source/contributing/testing.md b/docs/source/contributing/testing.md
new file mode 100644
index 000000000..47bf9dea7
--- /dev/null
+++ b/docs/source/contributing/testing.md
@@ -0,0 +1,6 @@
+# Testing Llama Stack
+
+Tests are of three different kinds:
+- Unit tests
+- Provider focused integration tests
+- Client SDK tests
diff --git a/docs/source/distributions/building_distro.md b/docs/source/distributions/building_distro.md
index aaf2462f7..5556d4aa1 100644
--- a/docs/source/distributions/building_distro.md
+++ b/docs/source/distributions/building_distro.md
@@ -4,7 +4,7 @@
 This guide will walk you through the steps to get started with building a Llama Stack distribution from scratch with your choice of API providers.
 
 
-## Llama Stack Build
+### Llama Stack Build
 
 In order to build your own distribution, we recommend you clone the `llama-stack` repository.
 
@@ -13,29 +13,99 @@ In order to build your own distribution, we recommend you clone the `llama-stack
 git clone git@github.com:meta-llama/llama-stack.git
 cd llama-stack
 pip install -e .
-
-llama stack build -h
 ```
+Use the CLI to build your distribution.
+The main points to consider are:
+1. **Image Type** - Do you want a Conda / venv environment or a Container (eg. Docker)
+2. **Template** - Do you want to use a template to build your distribution? or start from scratch ?
+3. **Config** - Do you want to use a pre-existing config file to build your distribution?
 
-We will start build our distribution (in the form of a Conda environment, or Docker image). In this step, we will specify:
-- `name`: the name for our distribution (e.g. `my-stack`)
-- `image_type`: our build image type (`conda | docker`)
-- `distribution_spec`: our distribution specs for specifying API providers
-  - `description`: a short description of the configurations for the distribution
-  - `providers`: specifies the underlying implementation for serving each API endpoint
-  - `image_type`: `conda` | `docker` to specify whether to build the distribution in the form of Docker image or Conda environment.
+```
+llama stack build -h
+
+usage: llama stack build [-h] [--config CONFIG] [--template TEMPLATE] [--list-templates | --no-list-templates] [--image-type {conda,container,venv}] [--image-name IMAGE_NAME]
+
+Build a Llama stack container
+
+options:
+  -h, --help            show this help message and exit
+  --config CONFIG       Path to a config file to use for the build. You can find example configs in llama_stack/distribution/**/build.yaml.
+                        If this argument is not provided, you will be prompted to enter information interactively
+  --template TEMPLATE   Name of the example template config to use for build. You may use `llama stack build --list-templates` to check out the available templates
+  --list-templates, --no-list-templates
+                        Show the available templates for building a Llama Stack distribution (default: False)
+  --image-type {conda,container,venv}
+                        Image Type to use for the build. This can be either conda or container or venv. If not specified, will use the image type from the template config.
+  --image-name IMAGE_NAME
+                        [for image-type=conda] Name of the conda environment to use for the build. If
+                        not specified, currently active Conda environment will be used. If no Conda
+                        environment is active, you must specify a name.
+```
 
 After this step is complete, a file named `<name>-build.yaml` and template file `<name>-run.yaml` will be generated and saved at the output file path specified at the end of the command.
 
 ::::{tab-set}
+:::{tab-item} Building from a template
+To build from alternative API providers, we provide distribution templates for users to get started building a distribution backed by different providers.
+
+The following command will allow you to see the available templates and their corresponding providers.
+```
+llama stack build --list-templates
+```
+
+```
+------------------------------+-----------------------------------------------------------------------------+
+| Template Name                | Description                                                                 |
++------------------------------+-----------------------------------------------------------------------------+
+| hf-serverless                | Use (an external) Hugging Face Inference Endpoint for running LLM inference |
++------------------------------+-----------------------------------------------------------------------------+
+| together                     | Use Together.AI for running LLM inference                                   |
++------------------------------+-----------------------------------------------------------------------------+
+| vllm-gpu                     | Use a built-in vLLM engine for running LLM inference                        |
++------------------------------+-----------------------------------------------------------------------------+
+| experimental-post-training   | Experimental template for post training                                     |
++------------------------------+-----------------------------------------------------------------------------+
+| remote-vllm                  | Use (an external) vLLM server for running LLM inference                     |
++------------------------------+-----------------------------------------------------------------------------+
+| fireworks                    | Use Fireworks.AI for running LLM inference                                  |
++------------------------------+-----------------------------------------------------------------------------+
+| tgi                          | Use (an external) TGI server for running LLM inference                      |
++------------------------------+-----------------------------------------------------------------------------+
+| bedrock                      | Use AWS Bedrock for running LLM inference and safety                        |
++------------------------------+-----------------------------------------------------------------------------+
+| meta-reference-gpu           | Use Meta Reference for running LLM inference                                |
++------------------------------+-----------------------------------------------------------------------------+
+| nvidia                       | Use NVIDIA NIM for running LLM inference                                    |
++------------------------------+-----------------------------------------------------------------------------+
+| meta-reference-quantized-gpu | Use Meta Reference with fp8, int4 quantization for running LLM inference    |
++------------------------------+-----------------------------------------------------------------------------+
+| cerebras                     | Use Cerebras for running LLM inference                                      |
++------------------------------+-----------------------------------------------------------------------------+
+| ollama                       | Use (an external) Ollama server for running LLM inference                   |
++------------------------------+-----------------------------------------------------------------------------+
+| hf-endpoint                  | Use (an external) Hugging Face Inference Endpoint for running LLM inference |
++------------------------------+-----------------------------------------------------------------------------+
+```
+
+You may then pick a template to build your distribution with providers fitted to your liking.
+
+For example, to build a distribution with TGI as the inference provider, you can run:
+```
+$ llama stack build --template tgi
+...
+You can now edit ~/.llama/distributions/llamastack-tgi/tgi-run.yaml and run `llama stack run ~/.llama/distributions/llamastack-tgi/tgi-run.yaml`
+```
+:::
 :::{tab-item} Building from Scratch
 
-- For a new user, we could start off with running `llama stack build` which will allow you to a interactively enter wizard where you will be prompted to enter build configurations.
+If the provided templates do not fit your use case, you could start off with running `llama stack build` which will allow you to a interactively enter wizard where you will be prompted to enter build configurations.
+
+It would be best to start with a template and understand the structure of the config file and the various concepts ( APIS, providers, resources, etc.) before starting from scratch.
 ```
 llama stack build
 
 > Enter a name for your Llama Stack (e.g. my-local-stack): my-stack
-> Enter the image type you want your Llama Stack to be built as (docker or conda): conda
+> Enter the image type you want your Llama Stack to be built as (container or conda): conda
 
 Llama Stack is composed of several APIs working together. Let's select
 the provider types (implementations) you want to use for these APIs.
@@ -57,272 +127,6 @@ You can now edit ~/.llama/distributions/llamastack-my-local-stack/my-local-stack
 ```
 :::
 
-:::{tab-item} Building from a template
-- To build from alternative API providers, we provide distribution templates for users to get started building a distribution backed by different providers.
-
-The following command will allow you to see the available templates and their corresponding providers.
-```
-llama stack build --list-templates
-```
-
-```
-+------------------------------+----------------------------------------+-----------------------------------------------------------------------------+
-| Template Name                | Providers                              | Description                                                                 |
-+------------------------------+----------------------------------------+-----------------------------------------------------------------------------+
-| tgi                          | {                                      | Use (an external) TGI server for running LLM inference                      |
-|                              |   "inference": [                       |                                                                             |
-|                              |     "remote::tgi"                      |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "memory": [                          |                                                                             |
-|                              |     "inline::faiss",                   |                                                                             |
-|                              |     "remote::chromadb",                |                                                                             |
-|                              |     "remote::pgvector"                 |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "safety": [                          |                                                                             |
-|                              |     "inline::llama-guard"              |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "agents": [                          |                                                                             |
-|                              |     "inline::meta-reference"           |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "telemetry": [                       |                                                                             |
-|                              |     "inline::meta-reference"           |                                                                             |
-|                              |   ]                                    |                                                                             |
-|                              | }                                      |                                                                             |
-+------------------------------+----------------------------------------+-----------------------------------------------------------------------------+
-| remote-vllm                  | {                                      | Use (an external) vLLM server for running LLM inference                     |
-|                              |   "inference": [                       |                                                                             |
-|                              |     "remote::vllm"                     |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "memory": [                          |                                                                             |
-|                              |     "inline::faiss",                   |                                                                             |
-|                              |     "remote::chromadb",                |                                                                             |
-|                              |     "remote::pgvector"                 |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "safety": [                          |                                                                             |
-|                              |     "inline::llama-guard"              |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "agents": [                          |                                                                             |
-|                              |     "inline::meta-reference"           |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "telemetry": [                       |                                                                             |
-|                              |     "inline::meta-reference"           |                                                                             |
-|                              |   ]                                    |                                                                             |
-|                              | }                                      |                                                                             |
-+------------------------------+----------------------------------------+-----------------------------------------------------------------------------+
-| vllm-gpu                     | {                                      | Use a built-in vLLM engine for running LLM inference                        |
-|                              |   "inference": [                       |                                                                             |
-|                              |     "inline::vllm"                     |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "memory": [                          |                                                                             |
-|                              |     "inline::faiss",                   |                                                                             |
-|                              |     "remote::chromadb",                |                                                                             |
-|                              |     "remote::pgvector"                 |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "safety": [                          |                                                                             |
-|                              |     "inline::llama-guard"              |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "agents": [                          |                                                                             |
-|                              |     "inline::meta-reference"           |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "telemetry": [                       |                                                                             |
-|                              |     "inline::meta-reference"           |                                                                             |
-|                              |   ]                                    |                                                                             |
-|                              | }                                      |                                                                             |
-+------------------------------+----------------------------------------+-----------------------------------------------------------------------------+
-| meta-reference-quantized-gpu | {                                      | Use Meta Reference with fp8, int4 quantization for running LLM inference    |
-|                              |   "inference": [                       |                                                                             |
-|                              |     "inline::meta-reference-quantized" |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "memory": [                          |                                                                             |
-|                              |     "inline::faiss",                   |                                                                             |
-|                              |     "remote::chromadb",                |                                                                             |
-|                              |     "remote::pgvector"                 |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "safety": [                          |                                                                             |
-|                              |     "inline::llama-guard"              |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "agents": [                          |                                                                             |
-|                              |     "inline::meta-reference"           |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "telemetry": [                       |                                                                             |
-|                              |     "inline::meta-reference"           |                                                                             |
-|                              |   ]                                    |                                                                             |
-|                              | }                                      |                                                                             |
-+------------------------------+----------------------------------------+-----------------------------------------------------------------------------+
-| meta-reference-gpu           | {                                      | Use Meta Reference for running LLM inference                                |
-|                              |   "inference": [                       |                                                                             |
-|                              |     "inline::meta-reference"           |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "memory": [                          |                                                                             |
-|                              |     "inline::faiss",                   |                                                                             |
-|                              |     "remote::chromadb",                |                                                                             |
-|                              |     "remote::pgvector"                 |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "safety": [                          |                                                                             |
-|                              |     "inline::llama-guard"              |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "agents": [                          |                                                                             |
-|                              |     "inline::meta-reference"           |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "telemetry": [                       |                                                                             |
-|                              |     "inline::meta-reference"           |                                                                             |
-|                              |   ]                                    |                                                                             |
-|                              | }                                      |                                                                             |
-+------------------------------+----------------------------------------+-----------------------------------------------------------------------------+
-| hf-serverless                | {                                      | Use (an external) Hugging Face Inference Endpoint for running LLM inference |
-|                              |   "inference": [                       |                                                                             |
-|                              |     "remote::hf::serverless"           |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "memory": [                          |                                                                             |
-|                              |     "inline::faiss",                   |                                                                             |
-|                              |     "remote::chromadb",                |                                                                             |
-|                              |     "remote::pgvector"                 |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "safety": [                          |                                                                             |
-|                              |     "inline::llama-guard"              |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "agents": [                          |                                                                             |
-|                              |     "inline::meta-reference"           |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "telemetry": [                       |                                                                             |
-|                              |     "inline::meta-reference"           |                                                                             |
-|                              |   ]                                    |                                                                             |
-|                              | }                                      |                                                                             |
-+------------------------------+----------------------------------------+-----------------------------------------------------------------------------+
-| together                     | {                                      | Use Together.AI for running LLM inference                                   |
-|                              |   "inference": [                       |                                                                             |
-|                              |     "remote::together"                 |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "memory": [                          |                                                                             |
-|                              |     "inline::faiss",                   |                                                                             |
-|                              |     "remote::chromadb",                |                                                                             |
-|                              |     "remote::pgvector"                 |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "safety": [                          |                                                                             |
-|                              |     "inline::llama-guard"              |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "agents": [                          |                                                                             |
-|                              |     "inline::meta-reference"           |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "telemetry": [                       |                                                                             |
-|                              |     "inline::meta-reference"           |                                                                             |
-|                              |   ]                                    |                                                                             |
-|                              | }                                      |                                                                             |
-+------------------------------+----------------------------------------+-----------------------------------------------------------------------------+
-| ollama                       | {                                      | Use (an external) Ollama server for running LLM inference                   |
-|                              |   "inference": [                       |                                                                             |
-|                              |     "remote::ollama"                   |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "memory": [                          |                                                                             |
-|                              |     "inline::faiss",                   |                                                                             |
-|                              |     "remote::chromadb",                |                                                                             |
-|                              |     "remote::pgvector"                 |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "safety": [                          |                                                                             |
-|                              |     "inline::llama-guard"              |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "agents": [                          |                                                                             |
-|                              |     "inline::meta-reference"           |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "telemetry": [                       |                                                                             |
-|                              |     "inline::meta-reference"           |                                                                             |
-|                              |   ]                                    |                                                                             |
-|                              | }                                      |                                                                             |
-+------------------------------+----------------------------------------+-----------------------------------------------------------------------------+
-| bedrock                      | {                                      | Use AWS Bedrock for running LLM inference and safety                        |
-|                              |   "inference": [                       |                                                                             |
-|                              |     "remote::bedrock"                  |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "memory": [                          |                                                                             |
-|                              |     "inline::faiss",                   |                                                                             |
-|                              |     "remote::chromadb",                |                                                                             |
-|                              |     "remote::pgvector"                 |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "safety": [                          |                                                                             |
-|                              |     "remote::bedrock"                  |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "agents": [                          |                                                                             |
-|                              |     "inline::meta-reference"           |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "telemetry": [                       |                                                                             |
-|                              |     "inline::meta-reference"           |                                                                             |
-|                              |   ]                                    |                                                                             |
-|                              | }                                      |                                                                             |
-+------------------------------+----------------------------------------+-----------------------------------------------------------------------------+
-| hf-endpoint                  | {                                      | Use (an external) Hugging Face Inference Endpoint for running LLM inference |
-|                              |   "inference": [                       |                                                                             |
-|                              |     "remote::hf::endpoint"             |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "memory": [                          |                                                                             |
-|                              |     "inline::faiss",                   |                                                                             |
-|                              |     "remote::chromadb",                |                                                                             |
-|                              |     "remote::pgvector"                 |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "safety": [                          |                                                                             |
-|                              |     "inline::llama-guard"              |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "agents": [                          |                                                                             |
-|                              |     "inline::meta-reference"           |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "telemetry": [                       |                                                                             |
-|                              |     "inline::meta-reference"           |                                                                             |
-|                              |   ]                                    |                                                                             |
-|                              | }                                      |                                                                             |
-+------------------------------+----------------------------------------+-----------------------------------------------------------------------------+
-| fireworks                    | {                                      | Use Fireworks.AI for running LLM inference                                  |
-|                              |   "inference": [                       |                                                                             |
-|                              |     "remote::fireworks"                |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "memory": [                          |                                                                             |
-|                              |     "inline::faiss",                   |                                                                             |
-|                              |     "remote::chromadb",                |                                                                             |
-|                              |     "remote::pgvector"                 |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "safety": [                          |                                                                             |
-|                              |     "inline::llama-guard"              |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "agents": [                          |                                                                             |
-|                              |     "inline::meta-reference"           |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "telemetry": [                       |                                                                             |
-|                              |     "inline::meta-reference"           |                                                                             |
-|                              |   ]                                    |                                                                             |
-|                              | }                                      |                                                                             |
-+------------------------------+----------------------------------------+-----------------------------------------------------------------------------+
-| cerebras                     | {                                      | Use Cerebras for running LLM inference                                      |
-|                              |   "inference": [                       |                                                                             |
-|                              |     "remote::cerebras"                 |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "safety": [                          |                                                                             |
-|                              |     "inline::llama-guard"              |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "memory": [                          |                                                                             |
-|                              |     "inline::meta-reference"           |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "agents": [                          |                                                                             |
-|                              |     "inline::meta-reference"           |                                                                             |
-|                              |   ],                                   |                                                                             |
-|                              |   "telemetry": [                       |                                                                             |
-|                              |     "inline::meta-reference"           |                                                                             |
-|                              |   ]                                    |                                                                             |
-|                              | }                                      |                                                                             |
-+------------------------------+----------------------------------------+-----------------------------------------------------------------------------+
-```
-
-You may then pick a template to build your distribution with providers fitted to your liking.
-
-For example, to build a distribution with TGI as the inference provider, you can run:
-```
-llama stack build --template tgi
-```
-
-```
-$ llama stack build --template tgi
-...
-You can now edit ~/.llama/distributions/llamastack-tgi/tgi-run.yaml and run `llama stack run ~/.llama/distributions/llamastack-tgi/tgi-run.yaml`
-```
-:::
-
 :::{tab-item} Building from a pre-existing build config file
 - In addition to templates, you may customize the build to your liking through editing config files and build from config files with the following command.
 
@@ -348,35 +152,39 @@ llama stack build --config llama_stack/templates/ollama/build.yaml
 ```
 :::
 
-:::{tab-item} Building Docker
+:::{tab-item} Building Container
 > [!TIP]
-> Podman is supported as an alternative to Docker. Set `DOCKER_BINARY` to `podman` in your environment to use Podman.
+> Podman is supported as an alternative to Docker. Set `CONTAINER_BINARY` to `podman` in your environment to use Podman.
 
-To build a docker image, you may start off from a template and use the `--image-type docker` flag to specify `docker` as the build image type.
+To build a container image, you may start off from a template and use the `--image-type container` flag to specify `container` as the build image type.
 
 ```
-llama stack build --template ollama --image-type docker
+llama stack build --template ollama --image-type container
 ```
 
 ```
-$ llama stack build --template ollama --image-type docker
+$ llama stack build --template ollama --image-type container
 ...
-Dockerfile created successfully in /tmp/tmp.viA3a3Rdsg/DockerfileFROM python:3.10-slim
+Containerfile created successfully in /tmp/tmp.viA3a3Rdsg/ContainerfileFROM python:3.10-slim
 ...
 
 You can now edit ~/meta-llama/llama-stack/tmp/configs/ollama-run.yaml and run `llama stack run ~/meta-llama/llama-stack/tmp/configs/ollama-run.yaml`
 ```
 
-After this step is successful, you should be able to find the built docker image and test it with `llama stack run <path/to/run.yaml>`.
+After this step is successful, you should be able to find the built container image and test it with `llama stack run <path/to/run.yaml>`.
 :::
 
 ::::
 
 
-## Running your Stack server
+### Running your Stack server
 Now, let's start the Llama Stack Distribution Server. You will need the YAML configuration file which was written out at the end by the `llama stack build` step.
 
 ```
+# Start using template name
+llama stack run tgi
+
+# Start using config file
 llama stack run ~/.llama/distributions/llamastack-my-local-stack/my-local-stack-run.yaml
 ```
 
@@ -412,4 +220,4 @@ INFO:     2401:db00:35c:2d2b:face:0:c9:0:54678 - "GET /models/list HTTP/1.1" 200
 
 ### Troubleshooting
 
-If you encounter any issues, search through our [GitHub Issues](https://github.com/meta-llama/llama-stack/issues), or file an new issue.
+If you encounter any issues, ask questions in our discord or search through our [GitHub Issues](https://github.com/meta-llama/llama-stack/issues), or file an new issue.
diff --git a/docs/source/distributions/configuration.md b/docs/source/distributions/configuration.md
index 41df26618..d12f584f7 100644
--- a/docs/source/distributions/configuration.md
+++ b/docs/source/distributions/configuration.md
@@ -70,20 +70,27 @@ Next up is the most critical part: the set of providers that the stack will use
 ```yaml
 providers:
   inference:
+  # provider_id is a string you can choose freely
   - provider_id: ollama
+    # provider_type is a string that specifies the type of provider.
+    # in this case, the provider for inference is ollama and it is run remotely (outside of the distribution)
     provider_type: remote::ollama
+    # config is a dictionary that contains the configuration for the provider.
+    # in this case, the configuration is the url of the ollama server
     config:
       url: ${env.OLLAMA_URL:http://localhost:11434}
 ```
 A few things to note:
-- A _provider instance_ is identified with an (identifier, type, configuration) tuple. The identifier is a string you can choose freely.
+- A _provider instance_ is identified with an (id, type, configuration) triplet.
+- The id is a string you can choose freely.
 - You can instantiate any number of provider instances of the same type.
-- The configuration dictionary is provider-specific. Notice that configuration can reference environment variables (with default values), which are expanded at runtime. When you run a stack server (via docker or via `llama stack run`), you can specify `--env OLLAMA_URL=http://my-server:11434` to override the default value.
+- The configuration dictionary is provider-specific.
+- Notice that configuration can reference environment variables (with default values), which are expanded at runtime. When you run a stack server (via docker or via `llama stack run`), you can specify `--env OLLAMA_URL=http://my-server:11434` to override the default value.
 
 ## Resources
-```
 
 Finally, let's look at the `models` section:
+
 ```yaml
 models:
 - metadata: {}
diff --git a/docs/source/distributions/importing_as_library.md b/docs/source/distributions/importing_as_library.md
index 7e15062df..cc7ed1beb 100644
--- a/docs/source/distributions/importing_as_library.md
+++ b/docs/source/distributions/importing_as_library.md
@@ -1,11 +1,20 @@
 # Using Llama Stack as a Library
 
-If you are planning to use an external service for Inference (even Ollama or TGI counts as external), it is often easier to use Llama Stack as a library. This avoids the overhead of setting up a server. For [example](https://github.com/meta-llama/llama-stack-client-python/blob/main/src/llama_stack_client/lib/direct/test.py):
+If you are planning to use an external service for Inference (even Ollama or TGI counts as external), it is often easier to use Llama Stack as a library. This avoids the overhead of setting up a server.
+```python
+# setup
+pip install llama-stack
+llama stack build --template together --image-type venv
+```
 
 ```python
-from llama_stack_client.lib.direct.direct import LlamaStackDirectClient
+from llama_stack.distribution.library_client import LlamaStackAsLibraryClient
 
-client = await LlamaStackDirectClient.from_template('ollama')
+client = LlamaStackAsLibraryClient(
+    "ollama",
+    # provider_data is optional, but if you need to pass in any provider specific data, you can do so here.
+    provider_data = {"tavily_search_api_key": os.environ['TAVILY_SEARCH_API_KEY']}
+)
 await client.initialize()
 ```
 
@@ -14,23 +23,12 @@ This will parse your config and set up any inline implementations and remote cli
 Then, you can access the APIs like `models` and `inference` on the client and call their methods directly:
 
 ```python
-response = await client.models.list()
-print(response)
-```
-
-```python
-response = await client.inference.chat_completion(
-    messages=[UserMessage(content="What is the capital of France?", role="user")],
-    model_id="Llama3.1-8B-Instruct",
-    stream=False,
-)
-print("\nChat completion response:")
-print(response)
+response = client.models.list()
 ```
 
 If you've created a [custom distribution](https://llama-stack.readthedocs.io/en/latest/distributions/building_distro.html), you can also use the run.yaml configuration file directly:
 
 ```python
-client = await LlamaStackDirectClient.from_config(config_path)
-await client.initialize()
+client = LlamaStackAsLibraryClient(config_path)
+client.initialize()
 ```
diff --git a/docs/source/distributions/index.md b/docs/source/distributions/index.md
index 5d84ebd9e..f68b8a8ae 100644
--- a/docs/source/distributions/index.md
+++ b/docs/source/distributions/index.md
@@ -1,41 +1,27 @@
-# Starting a Llama Stack
+# Starting a Llama Stack Server
+
+You can run a Llama Stack server in one of the following ways:
+
+**As a Library**:
+
+This is the simplest way to get started. Using Llama Stack as a library means you do not need to start a server. This is especially useful when you are not running inference locally and relying on an external inference service (eg. fireworks, together, groq, etc.) See [Using Llama Stack as a Library](importing_as_library)
+
+
+**Docker**:
+
+Another simple way to start interacting with Llama Stack is to just spin up docker which is pre-built with all the providers you need. We provide a number of pre-built Docker containers so you can start a Llama Stack server instantly. You can also build your own custom Docker container. Which distribution to choose depends on the hardware you have. See [Selection of a Distribution](distributions/selection) for more details.
+
+
+**Conda**:
+
+Lastly, if you have a custom or an advanced setup or you are developing on Llama Stack you can also build a custom Llama Stack server. Using `llama stack build` and `llama stack run` you can build/run a custom Llama Stack server containing the exact combination of providers you wish. We have also provided various templates to make getting started easier. See [Building a Custom Distribution](building_distro) for more details.
+
+
 ```{toctree}
-:maxdepth: 3
+:maxdepth: 1
 :hidden:
 
 importing_as_library
 building_distro
 configuration
 ```
-
-You can instantiate a Llama Stack in one of the following ways:
-- **As a Library**: this is the simplest, especially if you are using an external inference service. See [Using Llama Stack as a Library](importing_as_library)
-- **Docker**: we provide a number of pre-built Docker containers so you can start a Llama Stack server instantly. You can also build your own custom Docker container.
-- **Conda**: finally, you can build a custom Llama Stack server using `llama stack build` containing the exact combination of providers you wish. We have provided various templates to make getting started easier.
-
-Which templates / distributions to choose depends on the hardware you have for running LLM inference.
-
-- **Do you have access to a machine with powerful GPUs?**
-If so, we suggest:
-  - {dockerhub}`distribution-remote-vllm` ([Guide](self_hosted_distro/remote-vllm))
-  - {dockerhub}`distribution-meta-reference-gpu` ([Guide](self_hosted_distro/meta-reference-gpu))
-  - {dockerhub}`distribution-tgi` ([Guide](self_hosted_distro/tgi))
-  - {dockerhub} `distribution-nvidia` ([Guide](self_hosted_distro/nvidia))
-
-- **Are you running on a "regular" desktop machine?**
-If so, we suggest:
-  - {dockerhub}`distribution-ollama` ([Guide](self_hosted_distro/ollama))
-
-- **Do you have an API key for a remote inference provider like Fireworks, Together, etc.?** If so, we suggest:
-  - {dockerhub}`distribution-together` ([Guide](self_hosted_distro/together))
-  - {dockerhub}`distribution-fireworks` ([Guide](self_hosted_distro/fireworks))
-
-- **Do you want to run Llama Stack inference on your iOS / Android device** If so, we suggest:
-  - [iOS SDK](ondevice_distro/ios_sdk)
-  - [Android](ondevice_distro/android_sdk)
-
-- **Do you want a hosted Llama Stack endpoint?** If so, we suggest:
-  - [Remote-Hosted Llama Stack Endpoints](remote_hosted_distro/index)
-
-
-You can also build your own [custom distribution](building_distro).
diff --git a/docs/source/distributions/ondevice_distro/ios_sdk.md b/docs/source/distributions/ondevice_distro/ios_sdk.md
index c9d3a89b5..ffaf74533 100644
--- a/docs/source/distributions/ondevice_distro/ios_sdk.md
+++ b/docs/source/distributions/ondevice_distro/ios_sdk.md
@@ -1,6 +1,3 @@
----
-orphan: true
----
 # iOS SDK
 
 We offer both remote and on-device use of Llama Stack in Swift via two components:
diff --git a/docs/source/distributions/remote_hosted_distro/index.md b/docs/source/distributions/remote_hosted_distro/index.md
index 0f86bf73f..2fbe381af 100644
--- a/docs/source/distributions/remote_hosted_distro/index.md
+++ b/docs/source/distributions/remote_hosted_distro/index.md
@@ -1,6 +1,3 @@
----
-orphan: true
----
 # Remote-Hosted Distributions
 
 Remote-Hosted distributions are available endpoints serving Llama Stack API that you can directly connect to.
diff --git a/docs/source/distributions/remote_hosted_distro/nvidia.md b/docs/source/distributions/remote_hosted_distro/nvidia.md
index 7e3446863..61b41b1d9 100644
--- a/docs/source/distributions/remote_hosted_distro/nvidia.md
+++ b/docs/source/distributions/remote_hosted_distro/nvidia.md
@@ -8,11 +8,11 @@ The `llamastack/distribution-nvidia` distribution consists of the following prov
 | datasetio | `remote::huggingface`, `inline::localfs` |
 | eval | `inline::meta-reference` |
 | inference | `remote::nvidia` |
-| memory | `inline::faiss` |
 | safety | `inline::llama-guard` |
 | scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
 | telemetry | `inline::meta-reference` |
-| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime` |
+| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::rag-runtime`, `remote::model-context-protocol` |
+| vector_io | `inline::faiss` |
 
 
 ### Environment Variables
diff --git a/docs/source/distributions/selection.md b/docs/source/distributions/selection.md
new file mode 100644
index 000000000..aaaf246ee
--- /dev/null
+++ b/docs/source/distributions/selection.md
@@ -0,0 +1,56 @@
+# List of Distributions
+
+Here are a list of distributions you can use to start a Llama Stack server that are provided out of the box.
+
+## Selection of a Distribution / Template
+
+Which templates / distributions to choose depends on the hardware you have for running LLM inference.
+
+- **Do you want a hosted Llama Stack endpoint?** If so, we suggest leveraging our partners who host Llama Stack endpoints. Namely, _fireworks.ai_ and _together.xyz_.
+  - Read more about it here - [Remote-Hosted Endpoints](remote_hosted_distro/index).
+
+
+- **Do you have access to machines with GPUs?** If you wish to run Llama Stack locally or on a cloud instance and host your own Llama Stack endpoint, we suggest:
+  - {dockerhub}`distribution-remote-vllm` ([Guide](self_hosted_distro/remote-vllm))
+  - {dockerhub}`distribution-meta-reference-gpu` ([Guide](self_hosted_distro/meta-reference-gpu))
+  - {dockerhub}`distribution-tgi` ([Guide](self_hosted_distro/tgi))
+  - {dockerhub}`distribution-nvidia` ([Guide](self_hosted_distro/nvidia))
+
+- **Are you running on a "regular" desktop or laptop ?** We suggest using the ollama template for quick prototyping and get started without having to worry about needing GPUs.
+  - {dockerhub}`distribution-ollama` ([link](self_hosted_distro/ollama))
+
+- **Do you have an API key for a remote inference provider like Fireworks, Together, etc.?**  If so, we suggest:
+  - {dockerhub}`distribution-together` ([Guide](self_hosted_distro/together))
+  - {dockerhub}`distribution-fireworks` ([Guide](self_hosted_distro/fireworks))
+
+- **Do you want to run Llama Stack inference on your iOS / Android device**  Lastly, we also provide templates for running Llama Stack inference on your iOS / Android device:
+  - [iOS SDK](ondevice_distro/ios_sdk)
+  - [Android](ondevice_distro/android_sdk)
+
+
+- **If none of the above fit your needs, you can also build your own [custom distribution](building_distro).**
+
+### Distribution Details
+
+```{toctree}
+:maxdepth: 1
+
+remote_hosted_distro/index
+self_hosted_distro/remote-vllm
+self_hosted_distro/meta-reference-gpu
+self_hosted_distro/tgi
+self_hosted_distro/nvidia
+self_hosted_distro/ollama
+self_hosted_distro/together
+self_hosted_distro/fireworks
+ondevice_distro/index
+```
+
+### On-Device Distributions
+
+```{toctree}
+:maxdepth: 1
+
+ondevice_distro/ios_sdk
+ondevice_distro/android_sdk
+```
diff --git a/docs/source/distributions/self_hosted_distro/bedrock.md b/docs/source/distributions/self_hosted_distro/bedrock.md
index 71adfad09..f9a9f29cd 100644
--- a/docs/source/distributions/self_hosted_distro/bedrock.md
+++ b/docs/source/distributions/self_hosted_distro/bedrock.md
@@ -15,11 +15,11 @@ The `llamastack/distribution-bedrock` distribution consists of the following pro
 | datasetio | `remote::huggingface`, `inline::localfs` |
 | eval | `inline::meta-reference` |
 | inference | `remote::bedrock` |
-| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 | safety | `remote::bedrock` |
 | scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
 | telemetry | `inline::meta-reference` |
-| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime` |
+| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::rag-runtime`, `remote::model-context-protocol` |
+| vector_io | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 
 
 
diff --git a/docs/source/distributions/self_hosted_distro/cerebras.md b/docs/source/distributions/self_hosted_distro/cerebras.md
index 22e4125bd..a44e6287a 100644
--- a/docs/source/distributions/self_hosted_distro/cerebras.md
+++ b/docs/source/distributions/self_hosted_distro/cerebras.md
@@ -8,11 +8,11 @@ The `llamastack/distribution-cerebras` distribution consists of the following pr
 | datasetio | `remote::huggingface`, `inline::localfs` |
 | eval | `inline::meta-reference` |
 | inference | `remote::cerebras` |
-| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 | safety | `inline::llama-guard` |
 | scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
 | telemetry | `inline::meta-reference` |
-| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime` |
+| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::rag-runtime` |
+| vector_io | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 
 
 ### Environment Variables
diff --git a/docs/source/distributions/self_hosted_distro/fireworks.md b/docs/source/distributions/self_hosted_distro/fireworks.md
index 335309729..453cd746d 100644
--- a/docs/source/distributions/self_hosted_distro/fireworks.md
+++ b/docs/source/distributions/self_hosted_distro/fireworks.md
@@ -18,11 +18,11 @@ The `llamastack/distribution-fireworks` distribution consists of the following p
 | datasetio | `remote::huggingface`, `inline::localfs` |
 | eval | `inline::meta-reference` |
 | inference | `remote::fireworks` |
-| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 | safety | `inline::llama-guard` |
 | scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
 | telemetry | `inline::meta-reference` |
-| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime` |
+| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::rag-runtime`, `remote::model-context-protocol` |
+| vector_io | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 
 
 ### Environment Variables
diff --git a/docs/source/distributions/self_hosted_distro/meta-reference-gpu.md b/docs/source/distributions/self_hosted_distro/meta-reference-gpu.md
index a89719dea..a371011fe 100644
--- a/docs/source/distributions/self_hosted_distro/meta-reference-gpu.md
+++ b/docs/source/distributions/self_hosted_distro/meta-reference-gpu.md
@@ -18,11 +18,11 @@ The `llamastack/distribution-meta-reference-gpu` distribution consists of the fo
 | datasetio | `remote::huggingface`, `inline::localfs` |
 | eval | `inline::meta-reference` |
 | inference | `inline::meta-reference` |
-| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 | safety | `inline::llama-guard` |
 | scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
 | telemetry | `inline::meta-reference` |
-| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime` |
+| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::rag-runtime`, `remote::model-context-protocol` |
+| vector_io | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 
 
 Note that you need access to nvidia GPUs to run this distribution. This distribution is not compatible with CPU-only machines or machines with AMD GPUs.
diff --git a/docs/source/distributions/self_hosted_distro/meta-reference-quantized-gpu.md b/docs/source/distributions/self_hosted_distro/meta-reference-quantized-gpu.md
index 26ed5d05b..a32ccb65e 100644
--- a/docs/source/distributions/self_hosted_distro/meta-reference-quantized-gpu.md
+++ b/docs/source/distributions/self_hosted_distro/meta-reference-quantized-gpu.md
@@ -18,11 +18,11 @@ The `llamastack/distribution-meta-reference-quantized-gpu` distribution consists
 | datasetio | `remote::huggingface`, `inline::localfs` |
 | eval | `inline::meta-reference` |
 | inference | `inline::meta-reference-quantized` |
-| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 | safety | `inline::llama-guard` |
 | scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
 | telemetry | `inline::meta-reference` |
-| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime` |
+| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::rag-runtime`, `remote::model-context-protocol` |
+| vector_io | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 
 
 The only difference vs. the `meta-reference-gpu` distribution is that it has support for more efficient inference -- with fp8, int4 quantization, etc.
diff --git a/docs/source/distributions/self_hosted_distro/ollama.md b/docs/source/distributions/self_hosted_distro/ollama.md
index e8e5dd397..92e1f7dbf 100644
--- a/docs/source/distributions/self_hosted_distro/ollama.md
+++ b/docs/source/distributions/self_hosted_distro/ollama.md
@@ -18,11 +18,11 @@ The `llamastack/distribution-ollama` distribution consists of the following prov
 | datasetio | `remote::huggingface`, `inline::localfs` |
 | eval | `inline::meta-reference` |
 | inference | `remote::ollama` |
-| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 | safety | `inline::llama-guard` |
 | scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
 | telemetry | `inline::meta-reference` |
-| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime` |
+| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::rag-runtime` |
+| vector_io | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 
 
 You should use this distribution if you have a regular desktop machine without very powerful GPUs. Of course, if you have powerful GPUs, you can still continue using this distribution since Ollama supports GPU acceleration.### Environment Variables
@@ -82,11 +82,15 @@ docker run \
 If you are using Llama Stack Safety / Shield APIs, use:
 
 ```bash
+# You need a local checkout of llama-stack to run this, get it using
+# git clone https://github.com/meta-llama/llama-stack.git
+cd /path/to/llama-stack
+
 docker run \
   -it \
   -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
   -v ~/.llama:/root/.llama \
-  -v ./run-with-safety.yaml:/root/my-run.yaml \
+  -v ./llama_stack/templates/ollama/run-with-safety.yaml:/root/my-run.yaml \
   llamastack/distribution-ollama \
   --yaml-config /root/my-run.yaml \
   --port $LLAMA_STACK_PORT \
diff --git a/docs/source/distributions/self_hosted_distro/remote-vllm.md b/docs/source/distributions/self_hosted_distro/remote-vllm.md
index 98d02725c..b2d28be1b 100644
--- a/docs/source/distributions/self_hosted_distro/remote-vllm.md
+++ b/docs/source/distributions/self_hosted_distro/remote-vllm.md
@@ -14,11 +14,14 @@ The `llamastack/distribution-remote-vllm` distribution consists of the following
 | API | Provider(s) |
 |-----|-------------|
 | agents | `inline::meta-reference` |
+| datasetio | `remote::huggingface`, `inline::localfs` |
+| eval | `inline::meta-reference` |
 | inference | `remote::vllm` |
-| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 | safety | `inline::llama-guard` |
+| scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
 | telemetry | `inline::meta-reference` |
-| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime` |
+| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::rag-runtime`, `remote::model-context-protocol` |
+| vector_io | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 
 
 You can use this distribution if you have GPUs and want to run an independent vLLM server container for running inference.
@@ -107,10 +110,15 @@ If you are using Llama Stack Safety / Shield APIs, use:
 export SAFETY_PORT=8081
 export SAFETY_MODEL=meta-llama/Llama-Guard-3-1B
 
+# You need a local checkout of llama-stack to run this, get it using
+# git clone https://github.com/meta-llama/llama-stack.git
+cd /path/to/llama-stack
+
 docker run \
   -it \
   -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-  -v ./run-with-safety.yaml:/root/my-run.yaml \
+  -v ~/.llama:/root/.llama \
+  -v ./llama_stack/templates/remote-vllm/run-with-safety.yaml:/root/my-run.yaml \
   llamastack/distribution-remote-vllm \
   --yaml-config /root/my-run.yaml \
   --port $LLAMA_STACK_PORT \
diff --git a/docs/source/distributions/self_hosted_distro/sambanova.md b/docs/source/distributions/self_hosted_distro/sambanova.md
new file mode 100644
index 000000000..199279990
--- /dev/null
+++ b/docs/source/distributions/self_hosted_distro/sambanova.md
@@ -0,0 +1,75 @@
+---
+orphan: true
+---
+# SambaNova Distribution
+
+```{toctree}
+:maxdepth: 2
+:hidden:
+
+self
+```
+
+The `llamastack/distribution-sambanova` distribution consists of the following provider configurations.
+
+| API | Provider(s) |
+|-----|-------------|
+| agents | `inline::meta-reference` |
+| inference | `remote::sambanova` |
+| safety | `inline::llama-guard` |
+| telemetry | `inline::meta-reference` |
+| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::rag-runtime` |
+| vector_io | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
+
+
+### Environment Variables
+
+The following environment variables can be configured:
+
+- `LLAMASTACK_PORT`: Port for the Llama Stack distribution server (default: `5001`)
+- `SAMBANOVA_API_KEY`: SambaNova.AI API Key (default: ``)
+
+### Models
+
+The following models are available by default:
+
+- `meta-llama/Llama-3.1-8B-Instruct (Meta-Llama-3.1-8B-Instruct)`
+- `meta-llama/Llama-3.1-70B-Instruct (Meta-Llama-3.1-70B-Instruct)`
+- `meta-llama/Llama-3.1-405B-Instruct-FP8 (Meta-Llama-3.1-405B-Instruct)`
+- `meta-llama/Llama-3.2-1B-Instruct (Meta-Llama-3.2-1B-Instruct)`
+- `meta-llama/Llama-3.2-3B-Instruct (Meta-Llama-3.2-3B-Instruct)`
+- `meta-llama/Llama-3.2-11B-Vision-Instruct (Llama-3.2-11B-Vision-Instruct)`
+- `meta-llama/Llama-3.2-90B-Vision-Instruct (Llama-3.2-90B-Vision-Instruct)`
+
+
+### Prerequisite: API Keys
+
+Make sure you have access to a SambaNova API Key. You can get one by visiting [SambaBova.ai](https://sambanova.ai/).
+
+
+## Running Llama Stack with SambaNova
+
+You can do this via Conda (build code) or Docker which has a pre-built image.
+
+### Via Docker
+
+This method allows you to get started quickly without having to build the distribution code.
+
+```bash
+LLAMA_STACK_PORT=5001
+docker run \
+  -it \
+  -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
+  llamastack/distribution-sambanova \
+  --port $LLAMA_STACK_PORT \
+  --env SAMBANOVA_API_KEY=$SAMBANOVA_API_KEY
+```
+
+### Via Conda
+
+```bash
+llama stack build --template sambanova --image-type conda
+llama stack run ./run.yaml \
+  --port $LLAMA_STACK_PORT \
+  --env SAMBANOVA_API_KEY=$SAMBANOVA_API_KEY
+```
diff --git a/docs/source/distributions/self_hosted_distro/tgi.md b/docs/source/distributions/self_hosted_distro/tgi.md
index f4f705b12..ba5dee77f 100644
--- a/docs/source/distributions/self_hosted_distro/tgi.md
+++ b/docs/source/distributions/self_hosted_distro/tgi.md
@@ -19,11 +19,11 @@ The `llamastack/distribution-tgi` distribution consists of the following provide
 | datasetio | `remote::huggingface`, `inline::localfs` |
 | eval | `inline::meta-reference` |
 | inference | `remote::tgi` |
-| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 | safety | `inline::llama-guard` |
 | scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
 | telemetry | `inline::meta-reference` |
-| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime` |
+| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::rag-runtime`, `remote::model-context-protocol` |
+| vector_io | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 
 
 You can use this distribution if you have GPUs and want to run an independent TGI server container for running inference.
@@ -102,10 +102,15 @@ docker run \
 If you are using Llama Stack Safety / Shield APIs, use:
 
 ```bash
+# You need a local checkout of llama-stack to run this, get it using
+# git clone https://github.com/meta-llama/llama-stack.git
+cd /path/to/llama-stack
+
 docker run \
   -it \
   -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-  -v ./run-with-safety.yaml:/root/my-run.yaml \
+  -v ~/.llama:/root/.llama \
+  -v ./llama_stack/templates/tgi/run-with-safety.yaml:/root/my-run.yaml \
   llamastack/distribution-tgi \
   --yaml-config /root/my-run.yaml \
   --port $LLAMA_STACK_PORT \
diff --git a/docs/source/distributions/self_hosted_distro/together.md b/docs/source/distributions/self_hosted_distro/together.md
index 3b476c9bf..2d5c8fc77 100644
--- a/docs/source/distributions/self_hosted_distro/together.md
+++ b/docs/source/distributions/self_hosted_distro/together.md
@@ -18,11 +18,11 @@ The `llamastack/distribution-together` distribution consists of the following pr
 | datasetio | `remote::huggingface`, `inline::localfs` |
 | eval | `inline::meta-reference` |
 | inference | `remote::together` |
-| memory | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 | safety | `inline::llama-guard` |
 | scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
 | telemetry | `inline::meta-reference` |
-| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::memory-runtime` |
+| tool_runtime | `remote::brave-search`, `remote::tavily-search`, `inline::code-interpreter`, `inline::rag-runtime`, `remote::model-context-protocol` |
+| vector_io | `inline::faiss`, `remote::chromadb`, `remote::pgvector` |
 
 
 ### Environment Variables
diff --git a/docs/source/getting_started/index.md b/docs/source/getting_started/index.md
index 602b5a635..60636fd73 100644
--- a/docs/source/getting_started/index.md
+++ b/docs/source/getting_started/index.md
@@ -1,33 +1,49 @@
 # Quick Start
 
-In this guide, we'll walk through how you can use the Llama Stack client SDK to build a simple RAG agent.
+In this guide, we'll walk through how you can use the Llama Stack (server and client SDK ) to test a simple RAG agent.
 
-The most critical requirement for running the agent is running inference on the underlying Llama model. Depending on what hardware (GPUs) you have available, you have various options. We will use `Ollama` for this purpose as it is the easiest to get started with and yet robust.
+A Llama Stack agent is a simple integrated system that can perform tasks by combining a Llama model for reasoning with tools (e.g., RAG, web search, code execution, etc.) for taking actions.
 
-First, let's set up some environment variables that we will use in the rest of the guide. Note that if you open up a new terminal, you will need to set these again.
+In Llama Stack, we provide a server exposing multiple APIs. These APIs are backed by implementations from different providers. For this guide, we will use [Ollama](https://ollama.com/) as the inference provider.
 
-```bash
-export INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct"
-# ollama names this model differently, and we must use the ollama name when loading the model
-export OLLAMA_INFERENCE_MODEL="llama3.2:3b-instruct-fp16"
-export LLAMA_STACK_PORT=5001
-```
 
 ### 1. Start Ollama
 
 ```bash
-ollama run $OLLAMA_INFERENCE_MODEL --keepalive 60m
+ollama run llama3.2:3b-instruct-fp16 --keepalive 60m
 ```
 
 By default, Ollama keeps the model loaded in memory for 5 minutes which can be too short. We set the `--keepalive` flag to 60 minutes to ensure the model remains loaded for sometime.
 
+NOTE: If you do not have ollama, you can install it from [here](https://ollama.ai/docs/installation).
 
-### 2. Start the Llama Stack server
 
-Llama Stack is based on a client-server architecture. It consists of a server which can be configured very flexibly so you can mix-and-match various providers for its individual API components -- beyond Inference, these include Memory, Agents, Telemetry, Evals and so forth.
+
+### 2. Pick a client environment
+
+Llama Stack has a service-oriented architecture, so every interaction with the Stack happens through an REST interface. You can interact with the Stack in two ways:
+
+* Install the `llama-stack-client` PyPI package and point `LlamaStackClient` to a local or remote Llama Stack server.
+* Or, install the `llama-stack` PyPI package and use the Stack as a library using `LlamaStackAsLibraryClient`.
+
+```{admonition} Note
+:class: tip
+
+The API is **exactly identical** for both clients.
+```
+
+:::{dropdown} Starting up the Llama Stack server
+The Llama Stack server can be configured flexibly so you can mix-and-match various providers for its individual API components -- beyond Inference, these include Vector IO, Agents, Telemetry, Evals, Post Training, etc.
 
 To get started quickly, we provide various Docker images for the server component that work with different inference providers out of the box. For this guide, we will use `llamastack/distribution-ollama` as the Docker image.
 
+Lets setup some environment variables that we will use in the rest of the guide.
+```bash
+INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct"
+LLAMA_STACK_PORT=8321
+```
+
+You can start the server using the following command:
 ```bash
 docker run -it \
   -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
@@ -37,14 +53,18 @@ docker run -it \
   --env INFERENCE_MODEL=$INFERENCE_MODEL \
   --env OLLAMA_URL=http://host.docker.internal:11434
 ```
-
 Configuration for this is available at `distributions/ollama/run.yaml`.
 
+:::
 
-### 3. Use the Llama Stack client SDK
+
+:::{dropdown} Installing the Llama Stack client CLI and SDK
 
 You can interact with the Llama Stack server using various client SDKs. We will use the Python SDK which you can install using the following command. Note that you must be using Python 3.10 or newer:
 ```bash
+yes | conda create -n stack-client python=3.10
+conda activate stack-client
+
 pip install llama-stack-client
 ```
 
@@ -66,17 +86,35 @@ llama-stack-client \
   inference chat-completion \
   --message "hello, what model are you?"
 ```
+:::
 
-Here is a simple example to perform chat completions using Python instead of the CLI.
+&nbsp;
+
+### 3. Run inference with Python SDK
+
+Here is a simple example to perform chat completions using the SDK.
 ```python
 import os
-from llama_stack_client import LlamaStackClient
 
-client = LlamaStackClient(base_url=f"http://localhost:{os.environ['LLAMA_STACK_PORT']}")
+def create_http_client():
+    from llama_stack_client import LlamaStackClient
+    return LlamaStackClient(base_url=f"http://localhost:{os.environ['LLAMA_STACK_PORT']}")
+
+def create_library_client(template="ollama"):
+    from llama_stack import LlamaStackAsLibraryClient
+    client = LlamaStackAsLibraryClient(template)
+    client.initialize()
+    return client
+
+
+client = create_library_client()  # or create_http_client() depending on the environment you picked
 
 # List available models
 models = client.models.list()
-print(models)
+print("--- Available models: ---")
+for m in models:
+    print(f"- {m.identifier}")
+print()
 
 response = client.inference.chat_completion(
     model_id=os.environ["INFERENCE_MODEL"],
@@ -90,62 +128,78 @@ print(response.completion_message.content)
 
 ### 4. Your first RAG agent
 
-Here is an example of a simple RAG agent that uses the Llama Stack client SDK.
+Here is an example of a simple RAG (Retrieval Augmented Generation) chatbot agent which can answer questions about TorchTune documentation.
 
 ```python
-import asyncio
 import os
+from termcolor import cprint
 
-from llama_stack_client import LlamaStackClient
 from llama_stack_client.lib.agents.agent import Agent
 from llama_stack_client.lib.agents.event_logger import EventLogger
-from llama_stack_client.types import Attachment
 from llama_stack_client.types.agent_create_params import AgentConfig
+from llama_stack_client.types import Document
 
+client = create_library_client()  # or create_http_client() depending on the environment you picked
 
-async def run_main():
-    urls = ["chat.rst", "llama3.rst", "datasets.rst", "lora_finetune.rst"]
-    attachments = [
-        Attachment(
-            content=f"https://raw.githubusercontent.com/pytorch/torchtune/main/docs/source/tutorials/{url}",
-            mime_type="text/plain",
-        )
-        for i, url in enumerate(urls)
-    ]
-
-    client = LlamaStackClient(base_url=f"http://localhost:{os.environ['LLAMA_STACK_PORT']}")
-
-    agent_config = AgentConfig(
-        model=os.environ["INFERENCE_MODEL"],
-        instructions="You are a helpful assistant",
-        tools=[{"type": "memory"}],  # enable Memory aka RAG
-        enable_session_persistence=True,
+# Documents to be used for RAG
+urls = ["chat.rst", "llama3.rst", "datasets.rst", "lora_finetune.rst"]
+documents = [
+    Document(
+        document_id=f"num-{i}",
+        content=f"https://raw.githubusercontent.com/pytorch/torchtune/main/docs/source/tutorials/{url}",
+        mime_type="text/plain",
+        metadata={},
     )
+    for i, url in enumerate(urls)
+]
 
-    agent = Agent(client, agent_config)
-    session_id = agent.create_session("test-session")
-    user_prompts = [
-        (
-            "I am attaching documentation for Torchtune. Help me answer questions I will ask next.",
-            attachments,
-        ),
-        (
-            "What are the top 5 topics that were explained? Only list succinct bullet points.",
-            None,
-        ),
-    ]
-    for prompt, attachments in user_prompts:
-        response = agent.create_turn(
-            messages=[{"role": "user", "content": prompt}],
-            attachments=attachments,
-            session_id=session_id,
-        )
-        for log in EventLogger().log(response):
-            log.print()
+# Register a vector database
+vector_db_id = "test-vector-db"
+client.vector_dbs.register(
+    vector_db_id=vector_db_id,
+    embedding_model="all-MiniLM-L6-v2",
+    embedding_dimension=384,
+)
 
+# Insert the documents into the vector database
+client.tool_runtime.rag_tool.insert(
+    documents=documents,
+    vector_db_id=vector_db_id,
+    chunk_size_in_tokens=512,
+)
 
-if __name__ == "__main__":
-    asyncio.run(run_main())
+agent_config = AgentConfig(
+    model=os.environ["INFERENCE_MODEL"],
+    # Define instructions for the agent ( aka system prompt)
+    instructions="You are a helpful assistant",
+    enable_session_persistence=False,
+    # Define tools available to the agent
+    toolgroups = [
+        {
+          "name": "builtin::rag",
+          "args" : {
+            "vector_db_ids": [vector_db_id],
+          }
+        }
+    ],
+)
+
+rag_agent = Agent(client, agent_config)
+session_id = rag_agent.create_session("test-session")
+
+user_prompts = [
+    "What are the top 5 topics that were explained? Only list succinct bullet points.",
+]
+
+# Run the agent loop by calling the `create_turn` method
+for prompt in user_prompts:
+    cprint(f'User> {prompt}', 'green')
+    response = rag_agent.create_turn(
+        messages=[{"role": "user", "content": prompt}],
+        session_id=session_id,
+    )
+    for log in EventLogger().log(response):
+        log.print()
 ```
 
 ## Next Steps
diff --git a/docs/source/index.md b/docs/source/index.md
index cf7c0b236..6ed76c66d 100644
--- a/docs/source/index.md
+++ b/docs/source/index.md
@@ -1,23 +1,34 @@
+```{admonition} News
+:class: tip
+
+Llama Stack 0.1.0 is now available! See the [release notes](https://github.com/meta-llama/llama-stack/releases/tag/v0.1.0) for more details.
+```
+
 # Llama Stack
 
-Llama Stack defines and standardizes the set of core building blocks needed to bring generative AI applications to market. These building blocks are presented in the form of interoperable APIs with a broad set of Service Providers providing their implementations.
+
+Llama Stack defines and standardizes the core building blocks needed to bring generative AI applications to market. It provides a unified set of APIs with implementations from leading service providers, enabling seamless transitions between development and production environments. More specifically, it provides
+
+- **Unified API layer** for Inference, RAG, Agents, Tools, Safety, Evals, and Telemetry.
+- **Plugin architecture** to support the rich ecosystem of implementations of the different APIs in different environments like local development, on-premises, cloud, and mobile.
+- **Prepackaged verified distributions** which offer a one-stop solution for developers to get started quickly and reliably in any environment
+- **Multiple developer interfaces** like CLI and SDKs for Python, Node, iOS, and Android
+- **Standalone applications** as examples for how to build production-grade AI applications with Llama Stack
+
+We focus on making it easy to build production applications with the Llama model family - from the latest Llama 3.3 to specialized models like Llama Guard for safety.
 
 ```{image} ../_static/llama-stack.png
 :alt: Llama Stack
 :width: 400px
 ```
 
-Our goal is to provide pre-packaged implementations which can be operated in a variety of deployment environments: developers start iterating with Desktops or their mobile devices and can seamlessly transition to on-prem or public cloud deployments. At every point in this transition, the same set of APIs and the same developer experience is available.
-
-```{note}
-The Stack APIs are rapidly improving but still a work-in-progress. We invite feedback as well as direct contributions.
-```
+Our goal is to provide pre-packaged implementations (aka "distributions") which can be run in a variety of deployment environments. LlamaStack can assist you in your entire app development lifecycle - start iterating on local, mobile or desktop and seamlessly transition to on-prem or public cloud deployments. At every point in this transition, the same set of APIs and the same developer experience is available.
 
 ## Quick Links
 
 - New to Llama Stack? Start with the [Introduction](introduction/index) to understand our motivation and vision.
 - Ready to build? Check out the [Quick Start](getting_started/index) to get started.
-- Need specific providers? Browse [Distributions](distributions/index) to see all the options available.
+- Need specific providers? Browse [Distributions](distributions/selection) to see all the options available.
 - Want to contribute? See the [Contributing](contributing/index) guide.
 
 ## Available SDKs
@@ -33,33 +44,52 @@ We have a number of client-side SDKs available for different languages.
 
 ## Supported Llama Stack Implementations
 
-A number of "adapters" are available for some popular Inference and Memory (Vector Store) providers. For other APIs (particularly Safety and Agents), we provide *reference implementations* you can use to get started. We expect this list to grow over time. We are slowly onboarding more providers to the ecosystem as we get more confidence in the APIs.
+A number of "adapters" are available for some popular Inference and Vector Store providers. For other APIs (particularly Safety and Agents), we provide *reference implementations* you can use to get started. We expect this list to grow over time. We are slowly onboarding more providers to the ecosystem as we get more confidence in the APIs.
+
+**Inference API**
+|  **Provider** |  **Environments** |
+| :----: | :----: |
+|  Meta Reference  |  Single Node |
+|  Ollama  | Single Node   |
+|  Fireworks  |  Hosted  |
+|  Together  |  Hosted  |
+|  NVIDIA NIM  |  Hosted and Single Node  |
+|  vLLM  | Hosted and Single Node |
+|  TGI  |  Hosted and Single Node  |
+|  AWS Bedrock  |  Hosted  |
+|  Cerebras  |  Hosted  |
+|  Groq  |  Hosted  |
+|  SambaNova  |  Hosted  |
+| PyTorch ExecuTorch | On-device iOS, Android |
+
+**Vector IO API**
+|  **Provider** |  **Environments** |
+| :----: | :----: |
+|  FAISS | Single Node |
+|  Chroma | Hosted and Single Node |
+|  Postgres (PGVector) | Hosted and Single Node |
+|  Weaviate | Hosted |
+
+**Safety API**
+|  **Provider** |  **Environments** |
+| :----: | :----: |
+|  Llama Guard | Depends on Inference Provider |
+|  Prompt Guard | Single Node |
+|  Code Scanner | Single Node |
+|  AWS Bedrock | Hosted |
 
-|  **API Provider** |  **Environments** | **Agents** | **Inference** | **Memory** | **Safety** | **Telemetry** |
-| :----: | :----: | :----: | :----: | :----: | :----: | :----: |
-|  Meta Reference  |  Single Node | Y  |  Y  |  Y  |  Y  |  Y  |
-|  Cerebras  |  Single Node  |   | Y  |    |    |   |
-|  Fireworks  |  Hosted  | Y  | Y  |  Y  |    |   |
-|  AWS Bedrock  |  Hosted  |    |  Y  |    | Y  | |
-|  Together  |  Hosted  |  Y  |  Y  |   | Y  |  |
-|  Ollama  | Single Node   |    |  Y  |    |   |
-|  TGI  |  Hosted and Single Node  |    |  Y  |    |   |
-|  [NVIDIA NIM](https://build.nvidia.com/nim?filters=nimType%3Anim_type_run_anywhere&q=llama)  |  Hosted and Single Node  |    |  Y  |    |   |
-| Chroma | Single Node |  |  | Y |  |  |
-| Postgres | Single Node |  |  | Y |  |  |
-| PyTorch ExecuTorch | On-device iOS | Y  | Y  |  |  |
-| PyTorch ExecuTorch | On-device Android |  | Y  |  |  |
 
 ```{toctree}
 :hidden:
 :maxdepth: 3
 
+self
 introduction/index
 getting_started/index
 concepts/index
 distributions/index
+distributions/selection
 building_applications/index
-benchmark_evaluations/index
 playground/index
 contributing/index
 references/index
diff --git a/docs/source/introduction/index.md b/docs/source/introduction/index.md
index 9c2a70341..686f44cc4 100644
--- a/docs/source/introduction/index.md
+++ b/docs/source/introduction/index.md
@@ -19,77 +19,45 @@ Building production AI applications today requires solving multiple challenges:
 - Changing providers requires significant code changes.
 
 
-### The Vision: A Universal Stack
-
+### Our Solution: A Universal Stack
 
 ```{image} ../../_static/llama-stack.png
 :alt: Llama Stack
 :width: 400px
 ```
 
-Llama Stack defines and standardizes the core building blocks needed to bring generative AI applications to market. These building blocks are presented as interoperable APIs with a broad set of Service Providers providing their implementations.
+Llama Stack addresses these challenges through a service-oriented, API-first approach:
 
-#### Service-oriented Design
-Unlike other frameworks, Llama Stack is built with a service-oriented, REST API-first approach. Such a design not only allows for seamless transitions from local to remote deployments but also forces the design to be more declarative. This restriction can result in a much simpler, robust developer experience. The same code works across different environments:
+**Develop Anywhere, Deploy Everywhere**
+- Start locally with CPU-only setups
+- Move to GPU acceleration when needed
+- Deploy to cloud or edge without code changes
+- Same APIs and developer experience everywhere
 
-- Local development with CPU-only setups
-- Self-hosted with GPU acceleration
-- Cloud-hosted on providers like AWS, Fireworks, Together
-- On-device for iOS and Android
-
-
-#### Composability
-The APIs we design are composable. An Agent abstractly depends on { Inference, Memory, Safety } APIs but does not care about the actual implementation details. Safety itself may require model inference and hence can depend on the Inference API.
-
-#### Turnkey Solutions
-
-We provide turnkey solutions for popular deployment scenarios. It should be easy to deploy a Llama Stack server on AWS or in a private data center. Either of these should allow a developer to get started with powerful agentic apps, model evaluations, or fine-tuning services in minutes.
-
-We have built-in support for critical needs:
-
-- Safety guardrails and content filtering
-- Comprehensive evaluation capabilities
+**Production-Ready Building Blocks**
+- Pre-built safety guardrails and content filtering
+- Built-in RAG and agent capabilities
+- Comprehensive evaluation toolkit
 - Full observability and monitoring
-- Provider federation and fallback
 
-#### Focus on Llama Models
-As a Meta-initiated project, we explicitly focus on Meta's Llama series of models. Supporting the broad set of open models is no easy task and we want to start with models we understand best.
+**True Provider Independence**
+- Swap providers without application changes
+- Mix and match best-in-class implementations
+- Federation and fallback support
+- No vendor lock-in
 
-#### Supporting the Ecosystem
-There is a vibrant ecosystem of Providers which provide efficient inference or scalable vector stores or powerful observability solutions. We want to make sure it is easy for developers to pick and choose the best implementations for their use cases. We also want to make sure it is easy for new Providers to onboard and participate in the ecosystem.
-
-Additionally, we have designed every element of the Stack such that APIs as well as Resources (like Models) can be federated.
-
-#### Rich Provider Ecosystem
-
-```{list-table}
-:header-rows: 1
-
-* - Provider
-  - Local
-  - Self-hosted
-  - Cloud
-* - Inference
-  - Ollama
-  - vLLM, TGI
-  - Fireworks, Together, AWS
-* - Memory
-  - FAISS
-  - Chroma, pgvector
-  - Weaviate
-* - Safety
-  - Llama Guard
-  - -
-  - AWS Bedrock
-```
+**Robust Ecosystem**
+- Llama Stack is already integrated with distribution partners (cloud providers, hardware vendors, and AI-focused companies).
+- Ecosystem offers tailored infrastructure, software, and services for deploying Llama models.
 
 
-### Unified API Layer
+### Our Philosophy
 
-Llama Stack provides a consistent interface for:
+- **Service-Oriented**: REST APIs enforce clean interfaces and enable seamless transitions across different environments.
+- **Composability**: Every component is independent but works together seamlessly
+- **Production Ready**: Built for real-world applications, not just demos
+- **Turnkey Solutions**: Easy to deploy built in solutions for popular deployment scenarios
+- **Llama First**: Explicit focus on Meta's Llama models and partnering ecosystem
 
-- **Inference**: Run LLM models efficiently
-- **Safety**: Apply content filtering and safety policies
-- **Memory**: Store and retrieve knowledge for RAG
-- **Agents**: Build multi-step workflows
-- **Evaluation**: Test and improve application quality
+
+With Llama Stack, you can focus on building your application while we handle the infrastructure complexity, essential capabilities, and provider integrations.
diff --git a/docs/source/references/llama_stack_client_cli_reference.md b/docs/source/references/llama_stack_client_cli_reference.md
index bc5f3e5e6..b1fb7014f 100644
--- a/docs/source/references/llama_stack_client_cli_reference.md
+++ b/docs/source/references/llama_stack_client_cli_reference.md
@@ -103,36 +103,35 @@ $ llama-stack-client models update <model_id> [--provider-id <provider_id>] [--p
 $ llama-stack-client models delete <model_id>
 ```
 
-## Memory Bank Management
+## Vector DB Management
 
-### `llama-stack-client memory_banks list`
+### `llama-stack-client vector_dbs list`
 ```bash
-$ llama-stack-client memory_banks list
+$ llama-stack-client vector_dbs list
 ```
 ```
-+--------------+----------------+--------+-------------------+------------------------+--------------------------+
-| identifier   | provider_id    | type   | embedding_model   |   chunk_size_in_tokens |   overlap_size_in_tokens |
-+==============+================+========+===================+========================+==========================+
-| test_bank    | meta-reference | vector | all-MiniLM-L6-v2  |                    512 |                       64 |
-+--------------+----------------+--------+-------------------+------------------------+--------------------------+
++--------------+----------------+---------------------+---------------+------------------------+
+| identifier   | provider_id    | provider_resource_id| vector_db_type| params                |
++==============+================+=====================+===============+========================+
+| test_bank    | meta-reference | test_bank          | vector        | embedding_model: all-MiniLM-L6-v2
+                                                                      embedding_dimension: 384|
++--------------+----------------+---------------------+---------------+------------------------+
 ```
 
-### `llama-stack-client memory_banks register`
+### `llama-stack-client vector_dbs register`
 ```bash
-$ llama-stack-client memory_banks register <memory-bank-id> --type <type> [--provider-id <provider-id>] [--provider-memory-bank-id <provider-memory-bank-id>] [--chunk-size <chunk-size>] [--embedding-model <embedding-model>] [--overlap-size <overlap-size>]
+$ llama-stack-client vector_dbs register <vector-db-id> [--provider-id <provider-id>] [--provider-vector-db-id <provider-vector-db-id>] [--embedding-model <embedding-model>] [--embedding-dimension <embedding-dimension>]
 ```
 
 Options:
-- `--type`: Required. Type of memory bank. Choices: "vector", "keyvalue", "keyword", "graph"
-- `--provider-id`: Optional. Provider ID for the memory bank
-- `--provider-memory-bank-id`: Optional. Provider's memory bank ID
-- `--chunk-size`: Optional. Chunk size in tokens (for vector type). Default: 512
-- `--embedding-model`: Optional. Embedding model (for vector type). Default: "all-MiniLM-L6-v2"
-- `--overlap-size`: Optional. Overlap size in tokens (for vector type). Default: 64
+- `--provider-id`: Optional. Provider ID for the vector db
+- `--provider-vector-db-id`: Optional. Provider's vector db ID
+- `--embedding-model`: Optional. Embedding model to use. Default: "all-MiniLM-L6-v2"
+- `--embedding-dimension`: Optional. Dimension of embeddings. Default: 384
 
-### `llama-stack-client memory_banks unregister`
+### `llama-stack-client vector_dbs unregister`
 ```bash
-$ llama-stack-client memory_banks unregister <memory-bank-id>
+$ llama-stack-client vector_dbs unregister <vector-db-id>
 ```
 
 ## Shield Management
@@ -200,11 +199,7 @@ Example eval_task_config.json:
         "type": "model",
         "model": "Llama3.1-405B-Instruct",
         "sampling_params": {
-            "strategy": {
-              "type": "greedy"
-            },
-            "max_tokens": 0,
-            "repetition_penalty": 1.0
+            "strategy": "greedy",
         }
     }
 }
@@ -220,3 +215,44 @@ Options:
 - `--output-dir`: Required. Path to the directory where scoring results will be saved
 - `--num-examples`: Optional. Number of examples to evaluate (useful for debugging)
 - `--visualize`: Optional flag. If set, visualizes scoring results after completion
+
+## Tool Group Management
+
+### `llama-stack-client toolgroups list`
+```bash
+$ llama-stack-client toolgroups list
+```
+```
++---------------------------+------------------+------+---------------+
+| identifier                | provider_id      | args | mcp_endpoint  |
++===========================+==================+======+===============+
+| builtin::code_interpreter | code-interpreter | None | None         |
++---------------------------+------------------+------+---------------+
+| builtin::rag             | rag-runtime      | None | None         |
++---------------------------+------------------+------+---------------+
+| builtin::websearch       | tavily-search    | None | None         |
++---------------------------+------------------+------+---------------+
+```
+
+### `llama-stack-client toolgroups get`
+```bash
+$ llama-stack-client toolgroups get <toolgroup_id>
+```
+
+Shows detailed information about a specific toolgroup. If the toolgroup is not found, displays an error message.
+
+### `llama-stack-client toolgroups register`
+```bash
+$ llama-stack-client toolgroups register <toolgroup_id> [--provider-id <provider-id>] [--provider-toolgroup-id <provider-toolgroup-id>] [--mcp-config <mcp-config>] [--args <args>]
+```
+
+Options:
+- `--provider-id`: Optional. Provider ID for the toolgroup
+- `--provider-toolgroup-id`: Optional. Provider's toolgroup ID
+- `--mcp-config`: Optional. JSON configuration for the MCP endpoint
+- `--args`: Optional. JSON arguments for the toolgroup
+
+### `llama-stack-client toolgroups unregister`
+```bash
+$ llama-stack-client toolgroups unregister <toolgroup_id>
+```
diff --git a/docs/source/references/python_sdk_reference/index.md b/docs/source/references/python_sdk_reference/index.md
index 8ee0375a5..74101f7aa 100644
--- a/docs/source/references/python_sdk_reference/index.md
+++ b/docs/source/references/python_sdk_reference/index.md
@@ -4,29 +4,77 @@
 
 ```python
 from llama_stack_client.types import (
-    Attachment,
+    AgentConfig,
     BatchCompletion,
     CompletionMessage,
+    ContentDelta,
+    Document,
+    InterleavedContent,
+    InterleavedContentItem,
+    Message,
+    ParamType,
+    QueryConfig,
+    QueryResult,
+    ReturnType,
+    SafetyViolation,
     SamplingParams,
+    ScoringResult,
     SystemMessage,
     ToolCall,
+    ToolParamDefinition,
     ToolResponseMessage,
+    URL,
     UserMessage,
 )
 ```
 
-## Telemetry
+## Toolgroups
 
 Types:
 
 ```python
-from llama_stack_client.types import TelemetryGetTraceResponse
+from llama_stack_client.types import ListToolGroupsResponse, ToolGroup, ToolgroupListResponse
 ```
 
 Methods:
 
-- <code title="get /telemetry/get_trace">client.telemetry.<a href="./src/llama_stack_client/resources/telemetry.py">get_trace</a>(\*\*<a href="src/llama_stack_client/types/telemetry_get_trace_params.py">params</a>) -> <a href="./src/llama_stack_client/types/telemetry_get_trace_response.py">TelemetryGetTraceResponse</a></code>
-- <code title="post /telemetry/log_event">client.telemetry.<a href="./src/llama_stack_client/resources/telemetry.py">log</a>(\*\*<a href="src/llama_stack_client/types/telemetry_log_params.py">params</a>) -> None</code>
+- <code title="get /v1/toolgroups">client.toolgroups.<a href="./src/llama_stack_client/resources/toolgroups.py">list</a>() -> <a href="./src/llama_stack_client/types/toolgroup_list_response.py">ToolgroupListResponse</a></code>
+- <code title="get /v1/toolgroups/{toolgroup_id}">client.toolgroups.<a href="./src/llama_stack_client/resources/toolgroups.py">get</a>(toolgroup_id) -> <a href="./src/llama_stack_client/types/tool_group.py">ToolGroup</a></code>
+- <code title="post /v1/toolgroups">client.toolgroups.<a href="./src/llama_stack_client/resources/toolgroups.py">register</a>(\*\*<a href="src/llama_stack_client/types/toolgroup_register_params.py">params</a>) -> None</code>
+- <code title="delete /v1/toolgroups/{toolgroup_id}">client.toolgroups.<a href="./src/llama_stack_client/resources/toolgroups.py">unregister</a>(toolgroup_id) -> None</code>
+
+## Tools
+
+Types:
+
+```python
+from llama_stack_client.types import ListToolsResponse, Tool, ToolListResponse
+```
+
+Methods:
+
+- <code title="get /v1/tools">client.tools.<a href="./src/llama_stack_client/resources/tools.py">list</a>(\*\*<a href="src/llama_stack_client/types/tool_list_params.py">params</a>) -> <a href="./src/llama_stack_client/types/tool_list_response.py">ToolListResponse</a></code>
+- <code title="get /v1/tools/{tool_name}">client.tools.<a href="./src/llama_stack_client/resources/tools.py">get</a>(tool_name) -> <a href="./src/llama_stack_client/types/tool.py">Tool</a></code>
+
+## ToolRuntime
+
+Types:
+
+```python
+from llama_stack_client.types import ToolDef, ToolInvocationResult
+```
+
+Methods:
+
+- <code title="post /v1/tool-runtime/invoke">client.tool_runtime.<a href="./src/llama_stack_client/resources/tool_runtime/tool_runtime.py">invoke_tool</a>(\*\*<a href="src/llama_stack_client/types/tool_runtime_invoke_tool_params.py">params</a>) -> <a href="./src/llama_stack_client/types/tool_invocation_result.py">ToolInvocationResult</a></code>
+- <code title="get /v1/tool-runtime/list-tools">client.tool_runtime.<a href="./src/llama_stack_client/resources/tool_runtime/tool_runtime.py">list_tools</a>(\*\*<a href="src/llama_stack_client/types/tool_runtime_list_tools_params.py">params</a>) -> <a href="./src/llama_stack_client/types/tool_def.py">JSONLDecoder[ToolDef]</a></code>
+
+### RagTool
+
+Methods:
+
+- <code title="post /v1/tool-runtime/rag-tool/insert">client.tool_runtime.rag_tool.<a href="./src/llama_stack_client/resources/tool_runtime/rag_tool.py">insert</a>(\*\*<a href="src/llama_stack_client/types/tool_runtime/rag_tool_insert_params.py">params</a>) -> None</code>
+- <code title="post /v1/tool-runtime/rag-tool/query">client.tool_runtime.rag_tool.<a href="./src/llama_stack_client/resources/tool_runtime/rag_tool.py">query</a>(\*\*<a href="src/llama_stack_client/types/tool_runtime/rag_tool_query_params.py">params</a>) -> <a href="./src/llama_stack_client/types/shared/query_result.py">QueryResult</a></code>
 
 ## Agents
 
@@ -36,20 +84,19 @@ Types:
 from llama_stack_client.types import (
     InferenceStep,
     MemoryRetrievalStep,
-    RestAPIExecutionConfig,
     ShieldCallStep,
     ToolExecutionStep,
-    ToolParamDefinition,
+    ToolResponse,
     AgentCreateResponse,
 )
 ```
 
 Methods:
 
-- <code title="post /agents/create">client.agents.<a href="./src/llama_stack_client/resources/agents/agents.py">create</a>(\*\*<a href="src/llama_stack_client/types/agent_create_params.py">params</a>) -> <a href="./src/llama_stack_client/types/agent_create_response.py">AgentCreateResponse</a></code>
-- <code title="post /agents/delete">client.agents.<a href="./src/llama_stack_client/resources/agents/agents.py">delete</a>(\*\*<a href="src/llama_stack_client/types/agent_delete_params.py">params</a>) -> None</code>
+- <code title="post /v1/agents">client.agents.<a href="./src/llama_stack_client/resources/agents/agents.py">create</a>(\*\*<a href="src/llama_stack_client/types/agent_create_params.py">params</a>) -> <a href="./src/llama_stack_client/types/agent_create_response.py">AgentCreateResponse</a></code>
+- <code title="delete /v1/agents/{agent_id}">client.agents.<a href="./src/llama_stack_client/resources/agents/agents.py">delete</a>(agent_id) -> None</code>
 
-### Sessions
+### Session
 
 Types:
 
@@ -59,104 +106,106 @@ from llama_stack_client.types.agents import Session, SessionCreateResponse
 
 Methods:
 
-- <code title="post /agents/session/create">client.agents.sessions.<a href="./src/llama_stack_client/resources/agents/sessions.py">create</a>(\*\*<a href="src/llama_stack_client/types/agents/session_create_params.py">params</a>) -> <a href="./src/llama_stack_client/types/agents/session_create_response.py">SessionCreateResponse</a></code>
-- <code title="post /agents/session/get">client.agents.sessions.<a href="./src/llama_stack_client/resources/agents/sessions.py">retrieve</a>(\*\*<a href="src/llama_stack_client/types/agents/session_retrieve_params.py">params</a>) -> <a href="./src/llama_stack_client/types/agents/session.py">Session</a></code>
-- <code title="post /agents/session/delete">client.agents.sessions.<a href="./src/llama_stack_client/resources/agents/sessions.py">delete</a>(\*\*<a href="src/llama_stack_client/types/agents/session_delete_params.py">params</a>) -> None</code>
+- <code title="post /v1/agents/{agent_id}/session">client.agents.session.<a href="./src/llama_stack_client/resources/agents/session.py">create</a>(agent_id, \*\*<a href="src/llama_stack_client/types/agents/session_create_params.py">params</a>) -> <a href="./src/llama_stack_client/types/agents/session_create_response.py">SessionCreateResponse</a></code>
+- <code title="get /v1/agents/{agent_id}/session/{session_id}">client.agents.session.<a href="./src/llama_stack_client/resources/agents/session.py">retrieve</a>(session_id, \*, agent_id, \*\*<a href="src/llama_stack_client/types/agents/session_retrieve_params.py">params</a>) -> <a href="./src/llama_stack_client/types/agents/session.py">Session</a></code>
+- <code title="delete /v1/agents/{agent_id}/session/{session_id}">client.agents.session.<a href="./src/llama_stack_client/resources/agents/session.py">delete</a>(session_id, \*, agent_id) -> None</code>
 
 ### Steps
 
 Types:
 
 ```python
-from llama_stack_client.types.agents import AgentsStep
+from llama_stack_client.types.agents import StepRetrieveResponse
 ```
 
 Methods:
 
-- <code title="get /agents/step/get">client.agents.steps.<a href="./src/llama_stack_client/resources/agents/steps.py">retrieve</a>(\*\*<a href="src/llama_stack_client/types/agents/step_retrieve_params.py">params</a>) -> <a href="./src/llama_stack_client/types/agents/agents_step.py">AgentsStep</a></code>
+- <code title="get /v1/agents/{agent_id}/session/{session_id}/turn/{turn_id}/step/{step_id}">client.agents.steps.<a href="./src/llama_stack_client/resources/agents/steps.py">retrieve</a>(step_id, \*, agent_id, session_id, turn_id) -> <a href="./src/llama_stack_client/types/agents/step_retrieve_response.py">StepRetrieveResponse</a></code>
 
-### Turns
+### Turn
 
 Types:
 
 ```python
-from llama_stack_client.types.agents import AgentsTurnStreamChunk, Turn, TurnStreamEvent
+from llama_stack_client.types.agents import Turn, TurnCreateResponse
 ```
 
 Methods:
 
-- <code title="post /agents/turn/create">client.agents.turns.<a href="./src/llama_stack_client/resources/agents/turns.py">create</a>(\*\*<a href="src/llama_stack_client/types/agents/turn_create_params.py">params</a>) -> <a href="./src/llama_stack_client/types/agents/agents_turn_stream_chunk.py">AgentsTurnStreamChunk</a></code>
-- <code title="get /agents/turn/get">client.agents.turns.<a href="./src/llama_stack_client/resources/agents/turns.py">retrieve</a>(\*\*<a href="src/llama_stack_client/types/agents/turn_retrieve_params.py">params</a>) -> <a href="./src/llama_stack_client/types/agents/turn.py">Turn</a></code>
+- <code title="post /v1/agents/{agent_id}/session/{session_id}/turn">client.agents.turn.<a href="./src/llama_stack_client/resources/agents/turn.py">create</a>(session_id, \*, agent_id, \*\*<a href="src/llama_stack_client/types/agents/turn_create_params.py">params</a>) -> <a href="./src/llama_stack_client/types/agents/turn_create_response.py">TurnCreateResponse</a></code>
+- <code title="get /v1/agents/{agent_id}/session/{session_id}/turn/{turn_id}">client.agents.turn.<a href="./src/llama_stack_client/resources/agents/turn.py">retrieve</a>(turn_id, \*, agent_id, session_id) -> <a href="./src/llama_stack_client/types/agents/turn.py">Turn</a></code>
+
+## BatchInference
+
+Types:
+
+```python
+from llama_stack_client.types import BatchInferenceChatCompletionResponse
+```
+
+Methods:
+
+- <code title="post /v1/batch-inference/chat-completion">client.batch_inference.<a href="./src/llama_stack_client/resources/batch_inference.py">chat_completion</a>(\*\*<a href="src/llama_stack_client/types/batch_inference_chat_completion_params.py">params</a>) -> <a href="./src/llama_stack_client/types/batch_inference_chat_completion_response.py">BatchInferenceChatCompletionResponse</a></code>
+- <code title="post /v1/batch-inference/completion">client.batch_inference.<a href="./src/llama_stack_client/resources/batch_inference.py">completion</a>(\*\*<a href="src/llama_stack_client/types/batch_inference_completion_params.py">params</a>) -> <a href="./src/llama_stack_client/types/shared/batch_completion.py">BatchCompletion</a></code>
 
 ## Datasets
 
 Types:
 
 ```python
-from llama_stack_client.types import TrainEvalDataset
+from llama_stack_client.types import (
+    ListDatasetsResponse,
+    DatasetRetrieveResponse,
+    DatasetListResponse,
+)
 ```
 
 Methods:
 
-- <code title="post /datasets/create">client.datasets.<a href="./src/llama_stack_client/resources/datasets.py">create</a>(\*\*<a href="src/llama_stack_client/types/dataset_create_params.py">params</a>) -> None</code>
-- <code title="post /datasets/delete">client.datasets.<a href="./src/llama_stack_client/resources/datasets.py">delete</a>(\*\*<a href="src/llama_stack_client/types/dataset_delete_params.py">params</a>) -> None</code>
-- <code title="get /datasets/get">client.datasets.<a href="./src/llama_stack_client/resources/datasets.py">get</a>(\*\*<a href="src/llama_stack_client/types/dataset_get_params.py">params</a>) -> <a href="./src/llama_stack_client/types/train_eval_dataset.py">TrainEvalDataset</a></code>
+- <code title="get /v1/datasets/{dataset_id}">client.datasets.<a href="./src/llama_stack_client/resources/datasets.py">retrieve</a>(dataset_id) -> <a href="./src/llama_stack_client/types/dataset_retrieve_response.py">Optional[DatasetRetrieveResponse]</a></code>
+- <code title="get /v1/datasets">client.datasets.<a href="./src/llama_stack_client/resources/datasets.py">list</a>() -> <a href="./src/llama_stack_client/types/dataset_list_response.py">DatasetListResponse</a></code>
+- <code title="post /v1/datasets">client.datasets.<a href="./src/llama_stack_client/resources/datasets.py">register</a>(\*\*<a href="src/llama_stack_client/types/dataset_register_params.py">params</a>) -> None</code>
+- <code title="delete /v1/datasets/{dataset_id}">client.datasets.<a href="./src/llama_stack_client/resources/datasets.py">unregister</a>(dataset_id) -> None</code>
 
-## Evaluate
+## Eval
 
 Types:
 
 ```python
-from llama_stack_client.types import EvaluationJob
+from llama_stack_client.types import EvaluateResponse, Job
 ```
 
+Methods:
+
+- <code title="post /v1/eval/tasks/{task_id}/evaluations">client.eval.<a href="./src/llama_stack_client/resources/eval/eval.py">evaluate_rows</a>(task_id, \*\*<a href="src/llama_stack_client/types/eval_evaluate_rows_params.py">params</a>) -> <a href="./src/llama_stack_client/types/evaluate_response.py">EvaluateResponse</a></code>
+- <code title="post /v1/eval/tasks/{task_id}/jobs">client.eval.<a href="./src/llama_stack_client/resources/eval/eval.py">run_eval</a>(task_id, \*\*<a href="src/llama_stack_client/types/eval_run_eval_params.py">params</a>) -> <a href="./src/llama_stack_client/types/job.py">Job</a></code>
+
 ### Jobs
 
 Types:
 
 ```python
-from llama_stack_client.types.evaluate import (
-    EvaluationJobArtifacts,
-    EvaluationJobLogStream,
-    EvaluationJobStatus,
-)
+from llama_stack_client.types.eval import JobStatusResponse
 ```
 
 Methods:
 
-- <code title="get /evaluate/jobs">client.evaluate.jobs.<a href="./src/llama_stack_client/resources/evaluate/jobs/jobs.py">list</a>() -> <a href="./src/llama_stack_client/types/evaluation_job.py">EvaluationJob</a></code>
-- <code title="post /evaluate/job/cancel">client.evaluate.jobs.<a href="./src/llama_stack_client/resources/evaluate/jobs/jobs.py">cancel</a>(\*\*<a href="src/llama_stack_client/types/evaluate/job_cancel_params.py">params</a>) -> None</code>
+- <code title="get /v1/eval/tasks/{task_id}/jobs/{job_id}/result">client.eval.jobs.<a href="./src/llama_stack_client/resources/eval/jobs.py">retrieve</a>(job_id, \*, task_id) -> <a href="./src/llama_stack_client/types/evaluate_response.py">EvaluateResponse</a></code>
+- <code title="delete /v1/eval/tasks/{task_id}/jobs/{job_id}">client.eval.jobs.<a href="./src/llama_stack_client/resources/eval/jobs.py">cancel</a>(job_id, \*, task_id) -> None</code>
+- <code title="get /v1/eval/tasks/{task_id}/jobs/{job_id}">client.eval.jobs.<a href="./src/llama_stack_client/resources/eval/jobs.py">status</a>(job_id, \*, task_id) -> Optional[JobStatusResponse]</code>
 
-#### Artifacts
+## Inspect
+
+Types:
+
+```python
+from llama_stack_client.types import HealthInfo, ProviderInfo, RouteInfo, VersionInfo
+```
 
 Methods:
 
-- <code title="get /evaluate/job/artifacts">client.evaluate.jobs.artifacts.<a href="./src/llama_stack_client/resources/evaluate/jobs/artifacts.py">list</a>(\*\*<a href="src/llama_stack_client/types/evaluate/jobs/artifact_list_params.py">params</a>) -> <a href="./src/llama_stack_client/types/evaluate/evaluation_job_artifacts.py">EvaluationJobArtifacts</a></code>
-
-#### Logs
-
-Methods:
-
-- <code title="get /evaluate/job/logs">client.evaluate.jobs.logs.<a href="./src/llama_stack_client/resources/evaluate/jobs/logs.py">list</a>(\*\*<a href="src/llama_stack_client/types/evaluate/jobs/log_list_params.py">params</a>) -> <a href="./src/llama_stack_client/types/evaluate/evaluation_job_log_stream.py">EvaluationJobLogStream</a></code>
-
-#### Status
-
-Methods:
-
-- <code title="get /evaluate/job/status">client.evaluate.jobs.status.<a href="./src/llama_stack_client/resources/evaluate/jobs/status.py">list</a>(\*\*<a href="src/llama_stack_client/types/evaluate/jobs/status_list_params.py">params</a>) -> <a href="./src/llama_stack_client/types/evaluate/evaluation_job_status.py">EvaluationJobStatus</a></code>
-
-### QuestionAnswering
-
-Methods:
-
-- <code title="post /evaluate/question_answering/">client.evaluate.question_answering.<a href="./src/llama_stack_client/resources/evaluate/question_answering.py">create</a>(\*\*<a href="src/llama_stack_client/types/evaluate/question_answering_create_params.py">params</a>) -> <a href="./src/llama_stack_client/types/evaluation_job.py">EvaluationJob</a></code>
-
-## Evaluations
-
-Methods:
-
-- <code title="post /evaluate/summarization/">client.evaluations.<a href="./src/llama_stack_client/resources/evaluations.py">summarization</a>(\*\*<a href="src/llama_stack_client/types/evaluation_summarization_params.py">params</a>) -> <a href="./src/llama_stack_client/types/evaluation_job.py">EvaluationJob</a></code>
-- <code title="post /evaluate/text_generation/">client.evaluations.<a href="./src/llama_stack_client/resources/evaluations.py">text_generation</a>(\*\*<a href="src/llama_stack_client/types/evaluation_text_generation_params.py">params</a>) -> <a href="./src/llama_stack_client/types/evaluation_job.py">EvaluationJob</a></code>
+- <code title="get /v1/health">client.inspect.<a href="./src/llama_stack_client/resources/inspect.py">health</a>() -> <a href="./src/llama_stack_client/types/health_info.py">HealthInfo</a></code>
+- <code title="get /v1/version">client.inspect.<a href="./src/llama_stack_client/resources/inspect.py">version</a>() -> <a href="./src/llama_stack_client/types/version_info.py">VersionInfo</a></code>
 
 ## Inference
 
@@ -164,8 +213,8 @@ Types:
 
 ```python
 from llama_stack_client.types import (
-    ChatCompletionStreamChunk,
-    CompletionStreamChunk,
+    CompletionResponse,
+    EmbeddingsResponse,
     TokenLogProbs,
     InferenceChatCompletionResponse,
     InferenceCompletionResponse,
@@ -174,175 +223,232 @@ from llama_stack_client.types import (
 
 Methods:
 
-- <code title="post /inference/chat_completion">client.inference.<a href="./src/llama_stack_client/resources/inference/inference.py">chat_completion</a>(\*\*<a href="src/llama_stack_client/types/inference_chat_completion_params.py">params</a>) -> <a href="./src/llama_stack_client/types/inference_chat_completion_response.py">InferenceChatCompletionResponse</a></code>
-- <code title="post /inference/completion">client.inference.<a href="./src/llama_stack_client/resources/inference/inference.py">completion</a>(\*\*<a href="src/llama_stack_client/types/inference_completion_params.py">params</a>) -> <a href="./src/llama_stack_client/types/inference_completion_response.py">InferenceCompletionResponse</a></code>
+- <code title="post /v1/inference/chat-completion">client.inference.<a href="./src/llama_stack_client/resources/inference.py">chat_completion</a>(\*\*<a href="src/llama_stack_client/types/inference_chat_completion_params.py">params</a>) -> <a href="./src/llama_stack_client/types/inference_chat_completion_response.py">InferenceChatCompletionResponse</a></code>
+- <code title="post /v1/inference/completion">client.inference.<a href="./src/llama_stack_client/resources/inference.py">completion</a>(\*\*<a href="src/llama_stack_client/types/inference_completion_params.py">params</a>) -> <a href="./src/llama_stack_client/types/inference_completion_response.py">InferenceCompletionResponse</a></code>
+- <code title="post /v1/inference/embeddings">client.inference.<a href="./src/llama_stack_client/resources/inference.py">embeddings</a>(\*\*<a href="src/llama_stack_client/types/inference_embeddings_params.py">params</a>) -> <a href="./src/llama_stack_client/types/embeddings_response.py">EmbeddingsResponse</a></code>
 
-### Embeddings
+## VectorIo
 
 Types:
 
 ```python
-from llama_stack_client.types.inference import Embeddings
+from llama_stack_client.types import QueryChunksResponse
 ```
 
 Methods:
 
-- <code title="post /inference/embeddings">client.inference.embeddings.<a href="./src/llama_stack_client/resources/inference/embeddings.py">create</a>(\*\*<a href="src/llama_stack_client/types/inference/embedding_create_params.py">params</a>) -> <a href="./src/llama_stack_client/types/inference/embeddings.py">Embeddings</a></code>
+- <code title="post /v1/vector-io/insert">client.vector_io.<a href="./src/llama_stack_client/resources/vector_io.py">insert</a>(\*\*<a href="src/llama_stack_client/types/vector_io_insert_params.py">params</a>) -> None</code>
+- <code title="post /v1/vector-io/query">client.vector_io.<a href="./src/llama_stack_client/resources/vector_io.py">query</a>(\*\*<a href="src/llama_stack_client/types/vector_io_query_params.py">params</a>) -> <a href="./src/llama_stack_client/types/query_chunks_response.py">QueryChunksResponse</a></code>
 
-## Safety
-
-Types:
-
-```python
-from llama_stack_client.types import RunSheidResponse
-```
-
-Methods:
-
-- <code title="post /safety/run_shield">client.safety.<a href="./src/llama_stack_client/resources/safety.py">run_shield</a>(\*\*<a href="src/llama_stack_client/types/safety_run_shield_params.py">params</a>) -> <a href="./src/llama_stack_client/types/run_sheid_response.py">RunSheidResponse</a></code>
-
-## Memory
+## VectorDBs
 
 Types:
 
 ```python
 from llama_stack_client.types import (
-    QueryDocuments,
-    MemoryCreateResponse,
-    MemoryRetrieveResponse,
-    MemoryListResponse,
-    MemoryDropResponse,
+    ListVectorDBsResponse,
+    VectorDBRetrieveResponse,
+    VectorDBListResponse,
+    VectorDBRegisterResponse,
 )
 ```
 
 Methods:
 
-- <code title="post /memory/create">client.memory.<a href="./src/llama_stack_client/resources/memory/memory.py">create</a>(\*\*<a href="src/llama_stack_client/types/memory_create_params.py">params</a>) -> <a href="./src/llama_stack_client/types/memory_create_response.py">object</a></code>
-- <code title="get /memory/get">client.memory.<a href="./src/llama_stack_client/resources/memory/memory.py">retrieve</a>(\*\*<a href="src/llama_stack_client/types/memory_retrieve_params.py">params</a>) -> <a href="./src/llama_stack_client/types/memory_retrieve_response.py">object</a></code>
-- <code title="post /memory/update">client.memory.<a href="./src/llama_stack_client/resources/memory/memory.py">update</a>(\*\*<a href="src/llama_stack_client/types/memory_update_params.py">params</a>) -> None</code>
-- <code title="get /memory/list">client.memory.<a href="./src/llama_stack_client/resources/memory/memory.py">list</a>() -> <a href="./src/llama_stack_client/types/memory_list_response.py">object</a></code>
-- <code title="post /memory/drop">client.memory.<a href="./src/llama_stack_client/resources/memory/memory.py">drop</a>(\*\*<a href="src/llama_stack_client/types/memory_drop_params.py">params</a>) -> str</code>
-- <code title="post /memory/insert">client.memory.<a href="./src/llama_stack_client/resources/memory/memory.py">insert</a>(\*\*<a href="src/llama_stack_client/types/memory_insert_params.py">params</a>) -> None</code>
-- <code title="post /memory/query">client.memory.<a href="./src/llama_stack_client/resources/memory/memory.py">query</a>(\*\*<a href="src/llama_stack_client/types/memory_query_params.py">params</a>) -> <a href="./src/llama_stack_client/types/query_documents.py">QueryDocuments</a></code>
-
-### Documents
-
-Types:
-
-```python
-from llama_stack_client.types.memory import DocumentRetrieveResponse
-```
-
-Methods:
-
-- <code title="post /memory/documents/get">client.memory.documents.<a href="./src/llama_stack_client/resources/memory/documents.py">retrieve</a>(\*\*<a href="src/llama_stack_client/types/memory/document_retrieve_params.py">params</a>) -> <a href="./src/llama_stack_client/types/memory/document_retrieve_response.py">DocumentRetrieveResponse</a></code>
-- <code title="post /memory/documents/delete">client.memory.documents.<a href="./src/llama_stack_client/resources/memory/documents.py">delete</a>(\*\*<a href="src/llama_stack_client/types/memory/document_delete_params.py">params</a>) -> None</code>
-
-## PostTraining
-
-Types:
-
-```python
-from llama_stack_client.types import PostTrainingJob
-```
-
-Methods:
-
-- <code title="post /post_training/preference_optimize">client.post_training.<a href="./src/llama_stack_client/resources/post_training/post_training.py">preference_optimize</a>(\*\*<a href="src/llama_stack_client/types/post_training_preference_optimize_params.py">params</a>) -> <a href="./src/llama_stack_client/types/post_training_job.py">PostTrainingJob</a></code>
-- <code title="post /post_training/supervised_fine_tune">client.post_training.<a href="./src/llama_stack_client/resources/post_training/post_training.py">supervised_fine_tune</a>(\*\*<a href="src/llama_stack_client/types/post_training_supervised_fine_tune_params.py">params</a>) -> <a href="./src/llama_stack_client/types/post_training_job.py">PostTrainingJob</a></code>
-
-### Jobs
-
-Types:
-
-```python
-from llama_stack_client.types.post_training import (
-    PostTrainingJobArtifacts,
-    PostTrainingJobLogStream,
-    PostTrainingJobStatus,
-)
-```
-
-Methods:
-
-- <code title="get /post_training/jobs">client.post_training.jobs.<a href="./src/llama_stack_client/resources/post_training/jobs.py">list</a>() -> <a href="./src/llama_stack_client/types/post_training_job.py">PostTrainingJob</a></code>
-- <code title="get /post_training/job/artifacts">client.post_training.jobs.<a href="./src/llama_stack_client/resources/post_training/jobs.py">artifacts</a>(\*\*<a href="src/llama_stack_client/types/post_training/job_artifacts_params.py">params</a>) -> <a href="./src/llama_stack_client/types/post_training/post_training_job_artifacts.py">PostTrainingJobArtifacts</a></code>
-- <code title="post /post_training/job/cancel">client.post_training.jobs.<a href="./src/llama_stack_client/resources/post_training/jobs.py">cancel</a>(\*\*<a href="src/llama_stack_client/types/post_training/job_cancel_params.py">params</a>) -> None</code>
-- <code title="get /post_training/job/logs">client.post_training.jobs.<a href="./src/llama_stack_client/resources/post_training/jobs.py">logs</a>(\*\*<a href="src/llama_stack_client/types/post_training/job_logs_params.py">params</a>) -> <a href="./src/llama_stack_client/types/post_training/post_training_job_log_stream.py">PostTrainingJobLogStream</a></code>
-- <code title="get /post_training/job/status">client.post_training.jobs.<a href="./src/llama_stack_client/resources/post_training/jobs.py">status</a>(\*\*<a href="src/llama_stack_client/types/post_training/job_status_params.py">params</a>) -> <a href="./src/llama_stack_client/types/post_training/post_training_job_status.py">PostTrainingJobStatus</a></code>
-
-## RewardScoring
-
-Types:
-
-```python
-from llama_stack_client.types import RewardScoring, ScoredDialogGenerations
-```
-
-Methods:
-
-- <code title="post /reward_scoring/score">client.reward_scoring.<a href="./src/llama_stack_client/resources/reward_scoring.py">score</a>(\*\*<a href="src/llama_stack_client/types/reward_scoring_score_params.py">params</a>) -> <a href="./src/llama_stack_client/types/reward_scoring.py">RewardScoring</a></code>
-
-## SyntheticDataGeneration
-
-Types:
-
-```python
-from llama_stack_client.types import SyntheticDataGeneration
-```
-
-Methods:
-
-- <code title="post /synthetic_data_generation/generate">client.synthetic_data_generation.<a href="./src/llama_stack_client/resources/synthetic_data_generation.py">generate</a>(\*\*<a href="src/llama_stack_client/types/synthetic_data_generation_generate_params.py">params</a>) -> <a href="./src/llama_stack_client/types/synthetic_data_generation.py">SyntheticDataGeneration</a></code>
-
-## BatchInference
-
-Types:
-
-```python
-from llama_stack_client.types import BatchChatCompletion
-```
-
-Methods:
-
-- <code title="post /batch_inference/chat_completion">client.batch_inference.<a href="./src/llama_stack_client/resources/batch_inference.py">chat_completion</a>(\*\*<a href="src/llama_stack_client/types/batch_inference_chat_completion_params.py">params</a>) -> <a href="./src/llama_stack_client/types/batch_chat_completion.py">BatchChatCompletion</a></code>
-- <code title="post /batch_inference/completion">client.batch_inference.<a href="./src/llama_stack_client/resources/batch_inference.py">completion</a>(\*\*<a href="src/llama_stack_client/types/batch_inference_completion_params.py">params</a>) -> <a href="./src/llama_stack_client/types/shared/batch_completion.py">BatchCompletion</a></code>
+- <code title="get /v1/vector-dbs/{vector_db_id}">client.vector_dbs.<a href="./src/llama_stack_client/resources/vector_dbs.py">retrieve</a>(vector_db_id) -> <a href="./src/llama_stack_client/types/vector_db_retrieve_response.py">Optional[VectorDBRetrieveResponse]</a></code>
+- <code title="get /v1/vector-dbs">client.vector_dbs.<a href="./src/llama_stack_client/resources/vector_dbs.py">list</a>() -> <a href="./src/llama_stack_client/types/vector_db_list_response.py">VectorDBListResponse</a></code>
+- <code title="post /v1/vector-dbs">client.vector_dbs.<a href="./src/llama_stack_client/resources/vector_dbs.py">register</a>(\*\*<a href="src/llama_stack_client/types/vector_db_register_params.py">params</a>) -> <a href="./src/llama_stack_client/types/vector_db_register_response.py">VectorDBRegisterResponse</a></code>
+- <code title="delete /v1/vector-dbs/{vector_db_id}">client.vector_dbs.<a href="./src/llama_stack_client/resources/vector_dbs.py">unregister</a>(vector_db_id) -> None</code>
 
 ## Models
 
 Types:
 
 ```python
-from llama_stack_client.types import ModelServingSpec
+from llama_stack_client.types import ListModelsResponse, Model, ModelListResponse
 ```
 
 Methods:
 
-- <code title="get /models/list">client.models.<a href="./src/llama_stack_client/resources/models.py">list</a>() -> <a href="./src/llama_stack_client/types/model_serving_spec.py">ModelServingSpec</a></code>
-- <code title="get /models/get">client.models.<a href="./src/llama_stack_client/resources/models.py">get</a>(\*\*<a href="src/llama_stack_client/types/model_get_params.py">params</a>) -> <a href="./src/llama_stack_client/types/model_serving_spec.py">Optional</a></code>
+- <code title="get /v1/models/{model_id}">client.models.<a href="./src/llama_stack_client/resources/models.py">retrieve</a>(model_id) -> <a href="./src/llama_stack_client/types/model.py">Optional[Model]</a></code>
+- <code title="get /v1/models">client.models.<a href="./src/llama_stack_client/resources/models.py">list</a>() -> <a href="./src/llama_stack_client/types/model_list_response.py">ModelListResponse</a></code>
+- <code title="post /v1/models">client.models.<a href="./src/llama_stack_client/resources/models.py">register</a>(\*\*<a href="src/llama_stack_client/types/model_register_params.py">params</a>) -> <a href="./src/llama_stack_client/types/model.py">Model</a></code>
+- <code title="delete /v1/models/{model_id}">client.models.<a href="./src/llama_stack_client/resources/models.py">unregister</a>(model_id) -> None</code>
 
-## MemoryBanks
+## PostTraining
 
 Types:
 
 ```python
-from llama_stack_client.types import MemoryBankSpec
+from llama_stack_client.types import ListPostTrainingJobsResponse, PostTrainingJob
 ```
 
 Methods:
 
-- <code title="get /memory_banks/list">client.memory_banks.<a href="./src/llama_stack_client/resources/memory_banks.py">list</a>() -> <a href="./src/llama_stack_client/types/memory_bank_spec.py">MemoryBankSpec</a></code>
-- <code title="get /memory_banks/get">client.memory_banks.<a href="./src/llama_stack_client/resources/memory_banks.py">get</a>(\*\*<a href="src/llama_stack_client/types/memory_bank_get_params.py">params</a>) -> <a href="./src/llama_stack_client/types/memory_bank_spec.py">Optional</a></code>
+- <code title="post /v1/post-training/preference-optimize">client.post_training.<a href="./src/llama_stack_client/resources/post_training/post_training.py">preference_optimize</a>(\*\*<a href="src/llama_stack_client/types/post_training_preference_optimize_params.py">params</a>) -> <a href="./src/llama_stack_client/types/post_training_job.py">PostTrainingJob</a></code>
+- <code title="post /v1/post-training/supervised-fine-tune">client.post_training.<a href="./src/llama_stack_client/resources/post_training/post_training.py">supervised_fine_tune</a>(\*\*<a href="src/llama_stack_client/types/post_training_supervised_fine_tune_params.py">params</a>) -> <a href="./src/llama_stack_client/types/post_training_job.py">PostTrainingJob</a></code>
+
+### Job
+
+Types:
+
+```python
+from llama_stack_client.types.post_training import (
+    JobListResponse,
+    JobArtifactsResponse,
+    JobStatusResponse,
+)
+```
+
+Methods:
+
+- <code title="get /v1/post-training/jobs">client.post_training.job.<a href="./src/llama_stack_client/resources/post_training/job.py">list</a>() -> <a href="./src/llama_stack_client/types/post_training/job_list_response.py">JobListResponse</a></code>
+- <code title="get /v1/post-training/job/artifacts">client.post_training.job.<a href="./src/llama_stack_client/resources/post_training/job.py">artifacts</a>(\*\*<a href="src/llama_stack_client/types/post_training/job_artifacts_params.py">params</a>) -> <a href="./src/llama_stack_client/types/post_training/job_artifacts_response.py">Optional[JobArtifactsResponse]</a></code>
+- <code title="post /v1/post-training/job/cancel">client.post_training.job.<a href="./src/llama_stack_client/resources/post_training/job.py">cancel</a>(\*\*<a href="src/llama_stack_client/types/post_training/job_cancel_params.py">params</a>) -> None</code>
+- <code title="get /v1/post-training/job/status">client.post_training.job.<a href="./src/llama_stack_client/resources/post_training/job.py">status</a>(\*\*<a href="src/llama_stack_client/types/post_training/job_status_params.py">params</a>) -> <a href="./src/llama_stack_client/types/post_training/job_status_response.py">Optional[JobStatusResponse]</a></code>
+
+## Providers
+
+Types:
+
+```python
+from llama_stack_client.types import ListProvidersResponse, ProviderListResponse
+```
+
+Methods:
+
+- <code title="get /v1/inspect/providers">client.providers.<a href="./src/llama_stack_client/resources/providers.py">list</a>() -> <a href="./src/llama_stack_client/types/provider_list_response.py">ProviderListResponse</a></code>
+
+## Routes
+
+Types:
+
+```python
+from llama_stack_client.types import ListRoutesResponse, RouteListResponse
+```
+
+Methods:
+
+- <code title="get /v1/inspect/routes">client.routes.<a href="./src/llama_stack_client/resources/routes.py">list</a>() -> <a href="./src/llama_stack_client/types/route_list_response.py">RouteListResponse</a></code>
+
+## Safety
+
+Types:
+
+```python
+from llama_stack_client.types import RunShieldResponse
+```
+
+Methods:
+
+- <code title="post /v1/safety/run-shield">client.safety.<a href="./src/llama_stack_client/resources/safety.py">run_shield</a>(\*\*<a href="src/llama_stack_client/types/safety_run_shield_params.py">params</a>) -> <a href="./src/llama_stack_client/types/run_shield_response.py">RunShieldResponse</a></code>
 
 ## Shields
 
 Types:
 
 ```python
-from llama_stack_client.types import ShieldSpec
+from llama_stack_client.types import ListShieldsResponse, Shield, ShieldListResponse
 ```
 
 Methods:
 
-- <code title="get /shields/list">client.shields.<a href="./src/llama_stack_client/resources/shields.py">list</a>() -> <a href="./src/llama_stack_client/types/shield_spec.py">ShieldSpec</a></code>
-- <code title="get /shields/get">client.shields.<a href="./src/llama_stack_client/resources/shields.py">get</a>(\*\*<a href="src/llama_stack_client/types/shield_get_params.py">params</a>) -> <a href="./src/llama_stack_client/types/shield_spec.py">Optional</a></code>
+- <code title="get /v1/shields/{identifier}">client.shields.<a href="./src/llama_stack_client/resources/shields.py">retrieve</a>(identifier) -> <a href="./src/llama_stack_client/types/shield.py">Optional[Shield]</a></code>
+- <code title="get /v1/shields">client.shields.<a href="./src/llama_stack_client/resources/shields.py">list</a>() -> <a href="./src/llama_stack_client/types/shield_list_response.py">ShieldListResponse</a></code>
+- <code title="post /v1/shields">client.shields.<a href="./src/llama_stack_client/resources/shields.py">register</a>(\*\*<a href="src/llama_stack_client/types/shield_register_params.py">params</a>) -> <a href="./src/llama_stack_client/types/shield.py">Shield</a></code>
+
+## SyntheticDataGeneration
+
+Types:
+
+```python
+from llama_stack_client.types import SyntheticDataGenerationResponse
+```
+
+Methods:
+
+- <code title="post /v1/synthetic-data-generation/generate">client.synthetic_data_generation.<a href="./src/llama_stack_client/resources/synthetic_data_generation.py">generate</a>(\*\*<a href="src/llama_stack_client/types/synthetic_data_generation_generate_params.py">params</a>) -> <a href="./src/llama_stack_client/types/synthetic_data_generation_response.py">SyntheticDataGenerationResponse</a></code>
+
+## Telemetry
+
+Types:
+
+```python
+from llama_stack_client.types import (
+    QuerySpansResponse,
+    SpanWithStatus,
+    Trace,
+    TelemetryGetSpanResponse,
+    TelemetryGetSpanTreeResponse,
+    TelemetryQuerySpansResponse,
+    TelemetryQueryTracesResponse,
+)
+```
+
+Methods:
+
+- <code title="get /v1/telemetry/traces/{trace_id}/spans/{span_id}">client.telemetry.<a href="./src/llama_stack_client/resources/telemetry.py">get_span</a>(span_id, \*, trace_id) -> <a href="./src/llama_stack_client/types/telemetry_get_span_response.py">TelemetryGetSpanResponse</a></code>
+- <code title="get /v1/telemetry/spans/{span_id}/tree">client.telemetry.<a href="./src/llama_stack_client/resources/telemetry.py">get_span_tree</a>(span_id, \*\*<a href="src/llama_stack_client/types/telemetry_get_span_tree_params.py">params</a>) -> <a href="./src/llama_stack_client/types/telemetry_get_span_tree_response.py">TelemetryGetSpanTreeResponse</a></code>
+- <code title="get /v1/telemetry/traces/{trace_id}">client.telemetry.<a href="./src/llama_stack_client/resources/telemetry.py">get_trace</a>(trace_id) -> <a href="./src/llama_stack_client/types/trace.py">Trace</a></code>
+- <code title="post /v1/telemetry/events">client.telemetry.<a href="./src/llama_stack_client/resources/telemetry.py">log_event</a>(\*\*<a href="src/llama_stack_client/types/telemetry_log_event_params.py">params</a>) -> None</code>
+- <code title="get /v1/telemetry/spans">client.telemetry.<a href="./src/llama_stack_client/resources/telemetry.py">query_spans</a>(\*\*<a href="src/llama_stack_client/types/telemetry_query_spans_params.py">params</a>) -> <a href="./src/llama_stack_client/types/telemetry_query_spans_response.py">TelemetryQuerySpansResponse</a></code>
+- <code title="get /v1/telemetry/traces">client.telemetry.<a href="./src/llama_stack_client/resources/telemetry.py">query_traces</a>(\*\*<a href="src/llama_stack_client/types/telemetry_query_traces_params.py">params</a>) -> <a href="./src/llama_stack_client/types/telemetry_query_traces_response.py">TelemetryQueryTracesResponse</a></code>
+- <code title="post /v1/telemetry/spans/export">client.telemetry.<a href="./src/llama_stack_client/resources/telemetry.py">save_spans_to_dataset</a>(\*\*<a href="src/llama_stack_client/types/telemetry_save_spans_to_dataset_params.py">params</a>) -> None</code>
+
+## Datasetio
+
+Types:
+
+```python
+from llama_stack_client.types import PaginatedRowsResult
+```
+
+Methods:
+
+- <code title="post /v1/datasetio/rows">client.datasetio.<a href="./src/llama_stack_client/resources/datasetio.py">append_rows</a>(\*\*<a href="src/llama_stack_client/types/datasetio_append_rows_params.py">params</a>) -> None</code>
+- <code title="get /v1/datasetio/rows">client.datasetio.<a href="./src/llama_stack_client/resources/datasetio.py">get_rows_paginated</a>(\*\*<a href="src/llama_stack_client/types/datasetio_get_rows_paginated_params.py">params</a>) -> <a href="./src/llama_stack_client/types/paginated_rows_result.py">PaginatedRowsResult</a></code>
+
+## Scoring
+
+Types:
+
+```python
+from llama_stack_client.types import ScoringScoreResponse, ScoringScoreBatchResponse
+```
+
+Methods:
+
+- <code title="post /v1/scoring/score">client.scoring.<a href="./src/llama_stack_client/resources/scoring.py">score</a>(\*\*<a href="src/llama_stack_client/types/scoring_score_params.py">params</a>) -> <a href="./src/llama_stack_client/types/scoring_score_response.py">ScoringScoreResponse</a></code>
+- <code title="post /v1/scoring/score-batch">client.scoring.<a href="./src/llama_stack_client/resources/scoring.py">score_batch</a>(\*\*<a href="src/llama_stack_client/types/scoring_score_batch_params.py">params</a>) -> <a href="./src/llama_stack_client/types/scoring_score_batch_response.py">ScoringScoreBatchResponse</a></code>
+
+## ScoringFunctions
+
+Types:
+
+```python
+from llama_stack_client.types import (
+    ListScoringFunctionsResponse,
+    ScoringFn,
+    ScoringFunctionListResponse,
+)
+```
+
+Methods:
+
+- <code title="get /v1/scoring-functions/{scoring_fn_id}">client.scoring_functions.<a href="./src/llama_stack_client/resources/scoring_functions.py">retrieve</a>(scoring_fn_id) -> <a href="./src/llama_stack_client/types/scoring_fn.py">Optional[ScoringFn]</a></code>
+- <code title="get /v1/scoring-functions">client.scoring_functions.<a href="./src/llama_stack_client/resources/scoring_functions.py">list</a>() -> <a href="./src/llama_stack_client/types/scoring_function_list_response.py">ScoringFunctionListResponse</a></code>
+- <code title="post /v1/scoring-functions">client.scoring_functions.<a href="./src/llama_stack_client/resources/scoring_functions.py">register</a>(\*\*<a href="src/llama_stack_client/types/scoring_function_register_params.py">params</a>) -> None</code>
+
+## EvalTasks
+
+Types:
+
+```python
+from llama_stack_client.types import EvalTask, ListEvalTasksResponse, EvalTaskListResponse
+```
+
+Methods:
+
+- <code title="get /v1/eval-tasks/{eval_task_id}">client.eval_tasks.<a href="./src/llama_stack_client/resources/eval_tasks.py">retrieve</a>(eval_task_id) -> <a href="./src/llama_stack_client/types/eval_task.py">Optional[EvalTask]</a></code>
+- <code title="get /v1/eval-tasks">client.eval_tasks.<a href="./src/llama_stack_client/resources/eval_tasks.py">list</a>() -> <a href="./src/llama_stack_client/types/eval_task_list_response.py">EvalTaskListResponse</a></code>
+- <code title="post /v1/eval-tasks">client.eval_tasks.<a href="./src/llama_stack_client/resources/eval_tasks.py">register</a>(\*\*<a href="src/llama_stack_client/types/eval_task_register_params.py">params</a>) -> None</code>
diff --git a/docs/to_situate/developer_cookbook.md b/docs/to_situate/developer_cookbook.md
deleted file mode 100644
index 56ebd7a76..000000000
--- a/docs/to_situate/developer_cookbook.md
+++ /dev/null
@@ -1,41 +0,0 @@
-# Llama Stack Developer Cookbook
-
-Based on your developer needs, below are references to guides to help you get started.
-
-### Hosted Llama Stack Endpoint
-* Developer Need: I want to connect to a Llama Stack endpoint to build my applications.
-* Effort: 1min
-* Guide:
-  - Checkout our [DeepLearning course](https://www.deeplearning.ai/short-courses/introducing-multimodal-llama-3-2) on building with Llama Stack apps on pre-hosted Llama Stack endpoint.
-
-
-### Local meta-reference Llama Stack Server
-* Developer Need: I want to start a local Llama Stack server with my GPU using meta-reference implementations.
-* Effort: 5min
-* Guide:
-  - Please see our [meta-reference-gpu](https://llama-stack.readthedocs.io/en/latest/distributions/self_hosted_distro/meta-reference-gpu.html) on starting up a meta-reference Llama Stack server.
-
-### Llama Stack Server with Remote Providers
-* Developer need: I want a Llama Stack distribution with a remote provider.
-* Effort: 10min
-* Guide
-  - Please see our [Distributions Guide](https://llama-stack.readthedocs.io/en/latest/concepts/index.html#distributions) on starting up distributions with remote providers.
-
-
-### On-Device (iOS) Llama Stack
-* Developer Need: I want to use Llama Stack on-Device
-* Effort: 1.5hr
-* Guide:
-  - Please see our [iOS Llama Stack SDK](./ios_sdk.md) implementations
-
-### Assemble your own Llama Stack Distribution
-* Developer Need: I want to assemble my own distribution with API providers to my likings
-* Effort: 30min
-* Guide
-  - Please see our [Building Distribution](./building_distro.md) guide for assembling your own Llama Stack distribution with your choice of API providers.
-
-### Adding a New API Provider
-* Developer Need: I want to add a new API provider to Llama Stack.
-* Effort: 3hr
-* Guide
-  - Please see our [Adding a New API Provider](https://llama-stack.readthedocs.io/en/latest/contributing/new_api_provider.html) guide for adding a new API provider.
diff --git a/llama_stack/apis/agents/agents.py b/llama_stack/apis/agents/agents.py
index 63d0920fb..f62d78390 100644
--- a/llama_stack/apis/agents/agents.py
+++ b/llama_stack/apis/agents/agents.py
@@ -33,7 +33,6 @@ from llama_stack.apis.inference import (
     ToolResponseMessage,
     UserMessage,
 )
-from llama_stack.apis.memory import MemoryBank
 from llama_stack.apis.safety import SafetyViolation
 from llama_stack.apis.tools import ToolDef
 from llama_stack.providers.utils.telemetry.trace_protocol import trace_protocol
@@ -89,7 +88,7 @@ class MemoryRetrievalStep(StepCommon):
     step_type: Literal[StepType.memory_retrieval.value] = (
         StepType.memory_retrieval.value
     )
-    memory_bank_ids: List[str]
+    vector_db_ids: str
     inserted_context: InterleavedContent
 
 
@@ -133,8 +132,6 @@ class Session(BaseModel):
     turns: List[Turn]
     started_at: datetime
 
-    memory_bank: Optional[MemoryBank] = None
-
 
 class AgentToolGroupWithArgs(BaseModel):
     name: str
@@ -158,9 +155,7 @@ class AgentConfigCommon(BaseModel):
     toolgroups: Optional[List[AgentToolGroup]] = Field(default_factory=list)
     client_tools: Optional[List[ToolDef]] = Field(default_factory=list)
     tool_choice: Optional[ToolChoice] = Field(default=ToolChoice.auto)
-    tool_prompt_format: Optional[ToolPromptFormat] = Field(
-        default=ToolPromptFormat.json
-    )
+    tool_prompt_format: Optional[ToolPromptFormat] = Field(default=None)
 
     max_infer_iters: int = 10
 
@@ -234,11 +229,8 @@ class AgentTurnResponseTurnCompletePayload(BaseModel):
     turn: Turn
 
 
-@json_schema_type
-class AgentTurnResponseEvent(BaseModel):
-    """Streamed agent execution response."""
-
-    payload: Annotated[
+AgentTurnResponseEventPayload = register_schema(
+    Annotated[
         Union[
             AgentTurnResponseStepStartPayload,
             AgentTurnResponseStepProgressPayload,
@@ -247,7 +239,14 @@ class AgentTurnResponseEvent(BaseModel):
             AgentTurnResponseTurnCompletePayload,
         ],
         Field(discriminator="event_type"),
-    ]
+    ],
+    name="AgentTurnResponseEventPayload",
+)
+
+
+@json_schema_type
+class AgentTurnResponseEvent(BaseModel):
+    payload: AgentTurnResponseEventPayload
 
 
 @json_schema_type
diff --git a/llama_stack/apis/agents/event_logger.py b/llama_stack/apis/agents/event_logger.py
index 9e2f14805..7a607ffda 100644
--- a/llama_stack/apis/agents/event_logger.py
+++ b/llama_stack/apis/agents/event_logger.py
@@ -137,7 +137,7 @@ class EventLogger:
                                     event,
                                     LogEvent(
                                         role=None,
-                                        content=delta.content,
+                                        content=delta.tool_call,
                                         end="",
                                         color="cyan",
                                     ),
@@ -208,7 +208,7 @@ class EventLogger:
             ):
                 details = event.payload.step_details
                 inserted_context = interleaved_content_as_str(details.inserted_context)
-                content = f"fetched {len(inserted_context)} bytes from {details.memory_bank_ids}"
+                content = f"fetched {len(inserted_context)} bytes from {details.vector_db_ids}"
 
                 yield (
                     event,
diff --git a/llama_stack/apis/common/content_types.py b/llama_stack/apis/common/content_types.py
index b845d09dd..1d8cea567 100644
--- a/llama_stack/apis/common/content_types.py
+++ b/llama_stack/apis/common/content_types.py
@@ -38,8 +38,9 @@ class _URLOrData(BaseModel):
 
 
 @json_schema_type
-class ImageContentItem(_URLOrData):
+class ImageContentItem(BaseModel):
     type: Literal["image"] = "image"
+    image: _URLOrData
 
 
 @json_schema_type
@@ -73,7 +74,7 @@ class TextDelta(BaseModel):
 @json_schema_type
 class ImageDelta(BaseModel):
     type: Literal["image"] = "image"
-    data: bytes
+    image: bytes
 
 
 @json_schema_type
@@ -91,7 +92,7 @@ class ToolCallDelta(BaseModel):
     # you either send an in-progress tool call so the client can stream a long
     # code generation or you send the final parsed tool call at the end of the
     # stream
-    content: Union[str, ToolCall]
+    tool_call: Union[str, ToolCall]
     parse_status: ToolCallParseStatus
 
 
diff --git a/llama_stack/apis/datatypes.py b/llama_stack/apis/datatypes.py
new file mode 100644
index 000000000..ccc395b80
--- /dev/null
+++ b/llama_stack/apis/datatypes.py
@@ -0,0 +1,35 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from enum import Enum
+
+from llama_models.schema_utils import json_schema_type
+
+
+@json_schema_type
+class Api(Enum):
+    inference = "inference"
+    safety = "safety"
+    agents = "agents"
+    vector_io = "vector_io"
+    datasetio = "datasetio"
+    scoring = "scoring"
+    eval = "eval"
+    post_training = "post_training"
+    tool_runtime = "tool_runtime"
+
+    telemetry = "telemetry"
+
+    models = "models"
+    shields = "shields"
+    vector_dbs = "vector_dbs"
+    datasets = "datasets"
+    scoring_functions = "scoring_functions"
+    eval_tasks = "eval_tasks"
+    tool_groups = "tool_groups"
+
+    # built-in API
+    inspect = "inspect"
diff --git a/llama_stack/apis/eval/eval.py b/llama_stack/apis/eval/eval.py
index c9d2fb70b..dfeff0918 100644
--- a/llama_stack/apis/eval/eval.py
+++ b/llama_stack/apis/eval/eval.py
@@ -6,7 +6,7 @@
 
 from typing import Any, Dict, List, Literal, Optional, Protocol, Union
 
-from llama_models.schema_utils import json_schema_type, webmethod
+from llama_models.schema_utils import json_schema_type, register_schema, webmethod
 from pydantic import BaseModel, Field
 from typing_extensions import Annotated
 
@@ -31,9 +31,10 @@ class AgentCandidate(BaseModel):
     config: AgentConfig
 
 
-EvalCandidate = Annotated[
-    Union[ModelCandidate, AgentCandidate], Field(discriminator="type")
-]
+EvalCandidate = register_schema(
+    Annotated[Union[ModelCandidate, AgentCandidate], Field(discriminator="type")],
+    name="EvalCandidate",
+)
 
 
 @json_schema_type
@@ -61,9 +62,12 @@ class AppEvalTaskConfig(BaseModel):
     # we could optinally add any specific dataset config here
 
 
-EvalTaskConfig = Annotated[
-    Union[BenchmarkEvalTaskConfig, AppEvalTaskConfig], Field(discriminator="type")
-]
+EvalTaskConfig = register_schema(
+    Annotated[
+        Union[BenchmarkEvalTaskConfig, AppEvalTaskConfig], Field(discriminator="type")
+    ],
+    name="EvalTaskConfig",
+)
 
 
 @json_schema_type
diff --git a/llama_stack/apis/inference/inference.py b/llama_stack/apis/inference/inference.py
index fdda5fe1b..871f1f633 100644
--- a/llama_stack/apis/inference/inference.py
+++ b/llama_stack/apis/inference/inference.py
@@ -157,11 +157,13 @@ class ChatCompletionResponseEvent(BaseModel):
     stop_reason: Optional[StopReason] = None
 
 
+@json_schema_type
 class ResponseFormatType(Enum):
     json_schema = "json_schema"
     grammar = "grammar"
 
 
+@json_schema_type
 class JsonSchemaResponseFormat(BaseModel):
     type: Literal[ResponseFormatType.json_schema.value] = (
         ResponseFormatType.json_schema.value
@@ -169,6 +171,7 @@ class JsonSchemaResponseFormat(BaseModel):
     json_schema: Dict[str, Any]
 
 
+@json_schema_type
 class GrammarResponseFormat(BaseModel):
     type: Literal[ResponseFormatType.grammar.value] = ResponseFormatType.grammar.value
     bnf: Dict[str, Any]
diff --git a/llama_stack/apis/memory_banks/memory_banks.py b/llama_stack/apis/memory_banks/memory_banks.py
deleted file mode 100644
index ec8ba824b..000000000
--- a/llama_stack/apis/memory_banks/memory_banks.py
+++ /dev/null
@@ -1,161 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the terms described in the LICENSE file in
-# the root directory of this source tree.
-
-from enum import Enum
-from typing import (
-    Annotated,
-    List,
-    Literal,
-    Optional,
-    Protocol,
-    runtime_checkable,
-    Union,
-)
-
-from llama_models.schema_utils import json_schema_type, register_schema, webmethod
-from pydantic import BaseModel, Field
-
-from llama_stack.apis.resource import Resource, ResourceType
-from llama_stack.providers.utils.telemetry.trace_protocol import trace_protocol
-
-
-@json_schema_type
-class MemoryBankType(Enum):
-    vector = "vector"
-    keyvalue = "keyvalue"
-    keyword = "keyword"
-    graph = "graph"
-
-
-# define params for each type of memory bank, this leads to a tagged union
-# accepted as input from the API or from the config.
-@json_schema_type
-class VectorMemoryBankParams(BaseModel):
-    memory_bank_type: Literal[MemoryBankType.vector.value] = MemoryBankType.vector.value
-    embedding_model: str
-    chunk_size_in_tokens: int
-    overlap_size_in_tokens: Optional[int] = None
-
-
-@json_schema_type
-class KeyValueMemoryBankParams(BaseModel):
-    memory_bank_type: Literal[MemoryBankType.keyvalue.value] = (
-        MemoryBankType.keyvalue.value
-    )
-
-
-@json_schema_type
-class KeywordMemoryBankParams(BaseModel):
-    memory_bank_type: Literal[MemoryBankType.keyword.value] = (
-        MemoryBankType.keyword.value
-    )
-
-
-@json_schema_type
-class GraphMemoryBankParams(BaseModel):
-    memory_bank_type: Literal[MemoryBankType.graph.value] = MemoryBankType.graph.value
-
-
-BankParams = Annotated[
-    Union[
-        VectorMemoryBankParams,
-        KeyValueMemoryBankParams,
-        KeywordMemoryBankParams,
-        GraphMemoryBankParams,
-    ],
-    Field(discriminator="memory_bank_type"),
-]
-
-
-# Some common functionality for memory banks.
-class MemoryBankResourceMixin(Resource):
-    type: Literal[ResourceType.memory_bank.value] = ResourceType.memory_bank.value
-
-    @property
-    def memory_bank_id(self) -> str:
-        return self.identifier
-
-    @property
-    def provider_memory_bank_id(self) -> str:
-        return self.provider_resource_id
-
-
-@json_schema_type
-class VectorMemoryBank(MemoryBankResourceMixin):
-    memory_bank_type: Literal[MemoryBankType.vector.value] = MemoryBankType.vector.value
-    embedding_model: str
-    chunk_size_in_tokens: int
-    embedding_dimension: Optional[int] = 384  # default to minilm-l6-v2
-    overlap_size_in_tokens: Optional[int] = None
-
-
-@json_schema_type
-class KeyValueMemoryBank(MemoryBankResourceMixin):
-    memory_bank_type: Literal[MemoryBankType.keyvalue.value] = (
-        MemoryBankType.keyvalue.value
-    )
-
-
-# TODO: KeyValue and Keyword are so similar in name, oof. Get a better naming convention.
-@json_schema_type
-class KeywordMemoryBank(MemoryBankResourceMixin):
-    memory_bank_type: Literal[MemoryBankType.keyword.value] = (
-        MemoryBankType.keyword.value
-    )
-
-
-@json_schema_type
-class GraphMemoryBank(MemoryBankResourceMixin):
-    memory_bank_type: Literal[MemoryBankType.graph.value] = MemoryBankType.graph.value
-
-
-MemoryBank = register_schema(
-    Annotated[
-        Union[
-            VectorMemoryBank,
-            KeyValueMemoryBank,
-            KeywordMemoryBank,
-            GraphMemoryBank,
-        ],
-        Field(discriminator="memory_bank_type"),
-    ],
-    name="MemoryBank",
-)
-
-
-class MemoryBankInput(BaseModel):
-    memory_bank_id: str
-    params: BankParams
-    provider_memory_bank_id: Optional[str] = None
-
-
-class ListMemoryBanksResponse(BaseModel):
-    data: List[MemoryBank]
-
-
-@runtime_checkable
-@trace_protocol
-class MemoryBanks(Protocol):
-    @webmethod(route="/memory-banks", method="GET")
-    async def list_memory_banks(self) -> ListMemoryBanksResponse: ...
-
-    @webmethod(route="/memory-banks/{memory_bank_id}", method="GET")
-    async def get_memory_bank(
-        self,
-        memory_bank_id: str,
-    ) -> Optional[MemoryBank]: ...
-
-    @webmethod(route="/memory-banks", method="POST")
-    async def register_memory_bank(
-        self,
-        memory_bank_id: str,
-        params: BankParams,
-        provider_id: Optional[str] = None,
-        provider_memory_bank_id: Optional[str] = None,
-    ) -> MemoryBank: ...
-
-    @webmethod(route="/memory-banks/{memory_bank_id}", method="DELETE")
-    async def unregister_memory_bank(self, memory_bank_id: str) -> None: ...
diff --git a/llama_stack/apis/post_training/post_training.py b/llama_stack/apis/post_training/post_training.py
index b9aa3bbde..675488ada 100644
--- a/llama_stack/apis/post_training/post_training.py
+++ b/llama_stack/apis/post_training/post_training.py
@@ -8,7 +8,7 @@ from datetime import datetime
 from enum import Enum
 from typing import Any, Dict, List, Literal, Optional, Protocol, Union
 
-from llama_models.schema_utils import json_schema_type, webmethod
+from llama_models.schema_utils import json_schema_type, register_schema, webmethod
 from pydantic import BaseModel, Field
 from typing_extensions import Annotated
 
@@ -88,9 +88,12 @@ class QATFinetuningConfig(BaseModel):
     group_size: int
 
 
-AlgorithmConfig = Annotated[
-    Union[LoraFinetuningConfig, QATFinetuningConfig], Field(discriminator="type")
-]
+AlgorithmConfig = register_schema(
+    Annotated[
+        Union[LoraFinetuningConfig, QATFinetuningConfig], Field(discriminator="type")
+    ],
+    name="AlgorithmConfig",
+)
 
 
 @json_schema_type
diff --git a/llama_stack/apis/resource.py b/llama_stack/apis/resource.py
index a85f5a31c..d0ce72644 100644
--- a/llama_stack/apis/resource.py
+++ b/llama_stack/apis/resource.py
@@ -14,7 +14,7 @@ from pydantic import BaseModel, Field
 class ResourceType(Enum):
     model = "model"
     shield = "shield"
-    memory_bank = "memory_bank"
+    vector_db = "vector_db"
     dataset = "dataset"
     scoring_function = "scoring_function"
     eval_task = "eval_task"
@@ -37,5 +37,5 @@ class Resource(BaseModel):
     provider_id: str = Field(description="ID of the provider that owns this resource")
 
     type: ResourceType = Field(
-        description="Type of resource (e.g. 'model', 'shield', 'memory_bank', etc.)"
+        description="Type of resource (e.g. 'model', 'shield', 'vector_db', etc.)"
     )
diff --git a/llama_stack/apis/scoring_functions/scoring_functions.py b/llama_stack/apis/scoring_functions/scoring_functions.py
index 3089dc0a4..b2e85f855 100644
--- a/llama_stack/apis/scoring_functions/scoring_functions.py
+++ b/llama_stack/apis/scoring_functions/scoring_functions.py
@@ -16,7 +16,7 @@ from typing import (
     Union,
 )
 
-from llama_models.schema_utils import json_schema_type, webmethod
+from llama_models.schema_utils import json_schema_type, register_schema, webmethod
 from pydantic import BaseModel, Field
 from typing_extensions import Annotated
 
@@ -82,14 +82,17 @@ class BasicScoringFnParams(BaseModel):
     )
 
 
-ScoringFnParams = Annotated[
-    Union[
-        LLMAsJudgeScoringFnParams,
-        RegexParserScoringFnParams,
-        BasicScoringFnParams,
+ScoringFnParams = register_schema(
+    Annotated[
+        Union[
+            LLMAsJudgeScoringFnParams,
+            RegexParserScoringFnParams,
+            BasicScoringFnParams,
+        ],
+        Field(discriminator="type"),
     ],
-    Field(discriminator="type"),
-]
+    name="ScoringFnParams",
+)
 
 
 class CommonScoringFnFields(BaseModel):
diff --git a/llama_stack/apis/telemetry/telemetry.py b/llama_stack/apis/telemetry/telemetry.py
index 30a4e2342..284e3a970 100644
--- a/llama_stack/apis/telemetry/telemetry.py
+++ b/llama_stack/apis/telemetry/telemetry.py
@@ -17,7 +17,7 @@ from typing import (
     Union,
 )
 
-from llama_models.schema_utils import json_schema_type, webmethod
+from llama_models.schema_utils import json_schema_type, register_schema, webmethod
 from pydantic import BaseModel, Field
 from typing_extensions import Annotated
 
@@ -115,13 +115,16 @@ class SpanEndPayload(BaseModel):
     status: SpanStatus
 
 
-StructuredLogPayload = Annotated[
-    Union[
-        SpanStartPayload,
-        SpanEndPayload,
+StructuredLogPayload = register_schema(
+    Annotated[
+        Union[
+            SpanStartPayload,
+            SpanEndPayload,
+        ],
+        Field(discriminator="type"),
     ],
-    Field(discriminator="type"),
-]
+    name="StructuredLogPayload",
+)
 
 
 @json_schema_type
@@ -130,14 +133,17 @@ class StructuredLogEvent(EventCommon):
     payload: StructuredLogPayload
 
 
-Event = Annotated[
-    Union[
-        UnstructuredLogEvent,
-        MetricEvent,
-        StructuredLogEvent,
+Event = register_schema(
+    Annotated[
+        Union[
+            UnstructuredLogEvent,
+            MetricEvent,
+            StructuredLogEvent,
+        ],
+        Field(discriminator="type"),
     ],
-    Field(discriminator="type"),
-]
+    name="Event",
+)
 
 
 @json_schema_type
diff --git a/llama_stack/apis/tools/__init__.py b/llama_stack/apis/tools/__init__.py
index f747fcdc2..8cd798ebf 100644
--- a/llama_stack/apis/tools/__init__.py
+++ b/llama_stack/apis/tools/__init__.py
@@ -5,3 +5,4 @@
 # the root directory of this source tree.
 
 from .tools import *  # noqa: F401 F403
+from .rag_tool import *  # noqa: F401 F403
diff --git a/llama_stack/apis/tools/rag_tool.py b/llama_stack/apis/tools/rag_tool.py
new file mode 100644
index 000000000..950367304
--- /dev/null
+++ b/llama_stack/apis/tools/rag_tool.py
@@ -0,0 +1,95 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from enum import Enum
+from typing import Any, Dict, List, Literal, Optional, Union
+
+from llama_models.schema_utils import json_schema_type, register_schema, webmethod
+from pydantic import BaseModel, Field
+from typing_extensions import Annotated, Protocol, runtime_checkable
+
+from llama_stack.apis.common.content_types import InterleavedContent, URL
+from llama_stack.providers.utils.telemetry.trace_protocol import trace_protocol
+
+
+@json_schema_type
+class RAGDocument(BaseModel):
+    document_id: str
+    content: InterleavedContent | URL
+    mime_type: str | None = None
+    metadata: Dict[str, Any] = Field(default_factory=dict)
+
+
+@json_schema_type
+class RAGQueryResult(BaseModel):
+    content: Optional[InterleavedContent] = None
+
+
+@json_schema_type
+class RAGQueryGenerator(Enum):
+    default = "default"
+    llm = "llm"
+    custom = "custom"
+
+
+@json_schema_type
+class DefaultRAGQueryGeneratorConfig(BaseModel):
+    type: Literal["default"] = "default"
+    separator: str = " "
+
+
+@json_schema_type
+class LLMRAGQueryGeneratorConfig(BaseModel):
+    type: Literal["llm"] = "llm"
+    model: str
+    template: str
+
+
+RAGQueryGeneratorConfig = register_schema(
+    Annotated[
+        Union[
+            DefaultRAGQueryGeneratorConfig,
+            LLMRAGQueryGeneratorConfig,
+        ],
+        Field(discriminator="type"),
+    ],
+    name="RAGQueryGeneratorConfig",
+)
+
+
+@json_schema_type
+class RAGQueryConfig(BaseModel):
+    # This config defines how a query is generated using the messages
+    # for memory bank retrieval.
+    query_generator_config: RAGQueryGeneratorConfig = Field(
+        default=DefaultRAGQueryGeneratorConfig()
+    )
+    max_tokens_in_context: int = 4096
+    max_chunks: int = 5
+
+
+@runtime_checkable
+@trace_protocol
+class RAGToolRuntime(Protocol):
+    @webmethod(route="/tool-runtime/rag-tool/insert", method="POST")
+    async def insert(
+        self,
+        documents: List[RAGDocument],
+        vector_db_id: str,
+        chunk_size_in_tokens: int = 512,
+    ) -> None:
+        """Index documents so they can be used by the RAG system"""
+        ...
+
+    @webmethod(route="/tool-runtime/rag-tool/query", method="POST")
+    async def query(
+        self,
+        content: InterleavedContent,
+        vector_db_ids: List[str],
+        query_config: Optional[RAGQueryConfig] = None,
+    ) -> RAGQueryResult:
+        """Query the RAG system for context; typically invoked by the agent"""
+        ...
diff --git a/llama_stack/apis/tools/tools.py b/llama_stack/apis/tools/tools.py
index fb990cc41..1af019bd4 100644
--- a/llama_stack/apis/tools/tools.py
+++ b/llama_stack/apis/tools/tools.py
@@ -15,6 +15,8 @@ from llama_stack.apis.common.content_types import InterleavedContent, URL
 from llama_stack.apis.resource import Resource, ResourceType
 from llama_stack.providers.utils.telemetry.trace_protocol import trace_protocol
 
+from .rag_tool import RAGToolRuntime
+
 
 @json_schema_type
 class ToolParameter(BaseModel):
@@ -130,11 +132,17 @@ class ToolGroups(Protocol):
         ...
 
 
+class SpecialToolGroup(Enum):
+    rag_tool = "rag_tool"
+
+
 @runtime_checkable
 @trace_protocol
 class ToolRuntime(Protocol):
     tool_store: ToolStore
 
+    rag_tool: RAGToolRuntime
+
     # TODO: This needs to be renamed once OPEN API generator name conflict issue is fixed.
     @webmethod(route="/tool-runtime/list-tools", method="GET")
     async def list_runtime_tools(
@@ -143,7 +151,7 @@ class ToolRuntime(Protocol):
 
     @webmethod(route="/tool-runtime/invoke", method="POST")
     async def invoke_tool(
-        self, tool_name: str, args: Dict[str, Any]
+        self, tool_name: str, kwargs: Dict[str, Any]
     ) -> ToolInvocationResult:
         """Run a tool with the given arguments"""
         ...
diff --git a/llama_stack/apis/memory_banks/__init__.py b/llama_stack/apis/vector_dbs/__init__.py
similarity index 81%
rename from llama_stack/apis/memory_banks/__init__.py
rename to llama_stack/apis/vector_dbs/__init__.py
index 7511677ab..158241a6d 100644
--- a/llama_stack/apis/memory_banks/__init__.py
+++ b/llama_stack/apis/vector_dbs/__init__.py
@@ -4,4 +4,4 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-from .memory_banks import *  # noqa: F401 F403
+from .vector_dbs import *  # noqa: F401 F403
diff --git a/llama_stack/apis/vector_dbs/vector_dbs.py b/llama_stack/apis/vector_dbs/vector_dbs.py
new file mode 100644
index 000000000..4b782e2d5
--- /dev/null
+++ b/llama_stack/apis/vector_dbs/vector_dbs.py
@@ -0,0 +1,66 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from typing import List, Literal, Optional, Protocol, runtime_checkable
+
+from llama_models.schema_utils import json_schema_type, webmethod
+from pydantic import BaseModel
+
+from llama_stack.apis.resource import Resource, ResourceType
+from llama_stack.providers.utils.telemetry.trace_protocol import trace_protocol
+
+
+@json_schema_type
+class VectorDB(Resource):
+    type: Literal[ResourceType.vector_db.value] = ResourceType.vector_db.value
+
+    embedding_model: str
+    embedding_dimension: int
+
+    @property
+    def vector_db_id(self) -> str:
+        return self.identifier
+
+    @property
+    def provider_vector_db_id(self) -> str:
+        return self.provider_resource_id
+
+
+class VectorDBInput(BaseModel):
+    vector_db_id: str
+    embedding_model: str
+    embedding_dimension: int
+    provider_vector_db_id: Optional[str] = None
+
+
+class ListVectorDBsResponse(BaseModel):
+    data: List[VectorDB]
+
+
+@runtime_checkable
+@trace_protocol
+class VectorDBs(Protocol):
+    @webmethod(route="/vector-dbs", method="GET")
+    async def list_vector_dbs(self) -> ListVectorDBsResponse: ...
+
+    @webmethod(route="/vector-dbs/{vector_db_id}", method="GET")
+    async def get_vector_db(
+        self,
+        vector_db_id: str,
+    ) -> Optional[VectorDB]: ...
+
+    @webmethod(route="/vector-dbs", method="POST")
+    async def register_vector_db(
+        self,
+        vector_db_id: str,
+        embedding_model: str,
+        embedding_dimension: Optional[int] = 384,
+        provider_id: Optional[str] = None,
+        provider_vector_db_id: Optional[str] = None,
+    ) -> VectorDB: ...
+
+    @webmethod(route="/vector-dbs/{vector_db_id}", method="DELETE")
+    async def unregister_vector_db(self, vector_db_id: str) -> None: ...
diff --git a/llama_stack/apis/memory/__init__.py b/llama_stack/apis/vector_io/__init__.py
similarity index 82%
rename from llama_stack/apis/memory/__init__.py
rename to llama_stack/apis/vector_io/__init__.py
index 260862228..3fe4fa4b6 100644
--- a/llama_stack/apis/memory/__init__.py
+++ b/llama_stack/apis/vector_io/__init__.py
@@ -4,4 +4,4 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-from .memory import *  # noqa: F401 F403
+from .vector_io import *  # noqa: F401 F403
diff --git a/llama_stack/apis/memory/memory.py b/llama_stack/apis/vector_io/vector_io.py
similarity index 57%
rename from llama_stack/apis/memory/memory.py
rename to llama_stack/apis/vector_io/vector_io.py
index 6e6fcf697..8feeaa6d4 100644
--- a/llama_stack/apis/memory/memory.py
+++ b/llama_stack/apis/vector_io/vector_io.py
@@ -13,55 +13,45 @@ from typing import Any, Dict, List, Optional, Protocol, runtime_checkable
 from llama_models.schema_utils import json_schema_type, webmethod
 from pydantic import BaseModel, Field
 
-from llama_stack.apis.common.content_types import URL
 from llama_stack.apis.inference import InterleavedContent
-from llama_stack.apis.memory_banks import MemoryBank
+from llama_stack.apis.vector_dbs import VectorDB
 from llama_stack.providers.utils.telemetry.trace_protocol import trace_protocol
 
 
-@json_schema_type
-class MemoryBankDocument(BaseModel):
-    document_id: str
-    content: InterleavedContent | URL
-    mime_type: str | None = None
-    metadata: Dict[str, Any] = Field(default_factory=dict)
-
-
 class Chunk(BaseModel):
     content: InterleavedContent
-    token_count: int
-    document_id: str
+    metadata: Dict[str, Any] = Field(default_factory=dict)
 
 
 @json_schema_type
-class QueryDocumentsResponse(BaseModel):
+class QueryChunksResponse(BaseModel):
     chunks: List[Chunk]
     scores: List[float]
 
 
-class MemoryBankStore(Protocol):
-    def get_memory_bank(self, bank_id: str) -> Optional[MemoryBank]: ...
+class VectorDBStore(Protocol):
+    def get_vector_db(self, vector_db_id: str) -> Optional[VectorDB]: ...
 
 
 @runtime_checkable
 @trace_protocol
-class Memory(Protocol):
-    memory_bank_store: MemoryBankStore
+class VectorIO(Protocol):
+    vector_db_store: VectorDBStore
 
-    # this will just block now until documents are inserted, but it should
+    # this will just block now until chunks are inserted, but it should
     # probably return a Job instance which can be polled for completion
-    @webmethod(route="/memory/insert", method="POST")
-    async def insert_documents(
+    @webmethod(route="/vector-io/insert", method="POST")
+    async def insert_chunks(
         self,
-        bank_id: str,
-        documents: List[MemoryBankDocument],
+        vector_db_id: str,
+        chunks: List[Chunk],
         ttl_seconds: Optional[int] = None,
     ) -> None: ...
 
-    @webmethod(route="/memory/query", method="POST")
-    async def query_documents(
+    @webmethod(route="/vector-io/query", method="POST")
+    async def query_chunks(
         self,
-        bank_id: str,
+        vector_db_id: str,
         query: InterleavedContent,
         params: Optional[Dict[str, Any]] = None,
-    ) -> QueryDocumentsResponse: ...
+    ) -> QueryChunksResponse: ...
diff --git a/llama_stack/cli/stack/_build.py b/llama_stack/cli/stack/_build.py
index 08c987a50..99c3a7ffc 100644
--- a/llama_stack/cli/stack/_build.py
+++ b/llama_stack/cli/stack/_build.py
@@ -115,6 +115,8 @@ def run_stack_build_command(
                     f"Using conda environment {image_name}",
                     color="green",
                 )
+        else:
+            image_name = f"llamastack-{name}"
 
         cprint(
             textwrap.dedent(
@@ -171,19 +173,30 @@ def run_stack_build_command(
                 )
                 return
 
-    _run_stack_build_command_from_build_config(build_config, image_name=image_name)
+        if build_config.image_type == ImageType.container.value and not args.image_name:
+            cprint(
+                "Please specify --image-name when building a container from a config file",
+                color="red",
+            )
+            return
+
+    _run_stack_build_command_from_build_config(
+        build_config, image_name=image_name, config_path=args.config
+    )
 
 
 def _generate_run_config(
-    build_config: BuildConfig, build_dir: Path, image_name: str
+    build_config: BuildConfig,
+    build_dir: Path,
+    image_name: str,
 ) -> None:
     """
     Generate a run.yaml template file for user to edit from a build.yaml file
     """
     apis = list(build_config.distribution_spec.providers.keys())
     run_config = StackRunConfig(
-        docker_image=(
-            image_name if build_config.image_type == ImageType.docker.value else None
+        container_image=(
+            image_name if build_config.image_type == ImageType.container.value else None
         ),
         image_name=image_name,
         apis=apis,
@@ -227,8 +240,9 @@ def _generate_run_config(
         to_write = json.loads(run_config.model_dump_json())
         f.write(yaml.dump(to_write, sort_keys=False))
 
+    # this path is only invoked when no template is provided
     cprint(
-        f"You can now edit {run_config_file} and run `llama stack run {image_name}`",
+        f"You can now run your stack with `llama stack run {run_config_file}`",
         color="green",
     )
 
@@ -237,8 +251,9 @@ def _run_stack_build_command_from_build_config(
     build_config: BuildConfig,
     image_name: Optional[str] = None,
     template_name: Optional[str] = None,
+    config_path: Optional[str] = None,
 ) -> None:
-    if build_config.image_type == ImageType.docker.value:
+    if build_config.image_type == ImageType.container.value:
         if template_name:
             image_name = f"distribution-{template_name}"
         else:
@@ -263,7 +278,10 @@ def _run_stack_build_command_from_build_config(
         f.write(yaml.dump(to_write, sort_keys=False))
 
     return_code = build_image(
-        build_config, build_file_path, image_name, template_name=template_name
+        build_config,
+        build_file_path,
+        image_name,
+        template_or_config=template_name or config_path,
     )
     if return_code != 0:
         return
@@ -277,7 +295,7 @@ def _run_stack_build_command_from_build_config(
         with importlib.resources.as_file(template_path) as path:
             run_config_file = build_dir / f"{template_name}-run.yaml"
             shutil.copy(path, run_config_file)
-        # Find all ${env.VARIABLE} patterns
+
         cprint("Build Successful!", color="green")
     else:
         _generate_run_config(build_config, build_dir, image_name)
diff --git a/llama_stack/cli/stack/build.py b/llama_stack/cli/stack/build.py
index d00157710..48c811839 100644
--- a/llama_stack/cli/stack/build.py
+++ b/llama_stack/cli/stack/build.py
@@ -47,8 +47,8 @@ class StackBuild(Subcommand):
         self.parser.add_argument(
             "--image-type",
             type=str,
-            help="Image Type to use for the build. This can be either conda or docker. If not specified, will use the image type from the template config.",
-            choices=["conda", "docker", "venv"],
+            help="Image Type to use for the build. This can be either conda or container or venv. If not specified, will use the image type from the template config.",
+            choices=["conda", "container", "venv"],
             default="conda",
         )
 
diff --git a/llama_stack/cli/stack/configure.py b/llama_stack/cli/stack/configure.py
index 11d3f705a..56f4feceb 100644
--- a/llama_stack/cli/stack/configure.py
+++ b/llama_stack/cli/stack/configure.py
@@ -27,7 +27,7 @@ class StackConfigure(Subcommand):
         self.parser.add_argument(
             "config",
             type=str,
-            help="Path to the build config file (e.g. ~/.llama/builds/<image_type>/<name>-build.yaml). For docker, this could also be the name of the docker image. ",
+            help="Path to the build config file (e.g. ~/.llama/builds/<image_type>/<name>-build.yaml). For container, this could also be the name of the container image. ",
         )
 
         self.parser.add_argument(
diff --git a/llama_stack/cli/stack/run.py b/llama_stack/cli/stack/run.py
index 9fa82bd61..62a45ada0 100644
--- a/llama_stack/cli/stack/run.py
+++ b/llama_stack/cli/stack/run.py
@@ -78,12 +78,15 @@ class StackRun(Subcommand):
 
         config_file = Path(args.config)
         has_yaml_suffix = args.config.endswith(".yaml")
+        template_name = None
 
         if not config_file.exists() and not has_yaml_suffix:
             # check if this is a template
             config_file = (
                 Path(REPO_ROOT) / "llama_stack" / "templates" / args.config / "run.yaml"
             )
+            if config_file.exists():
+                template_name = args.config
 
         if not config_file.exists() and not has_yaml_suffix:
             # check if it's a build config saved to conda dir
@@ -92,9 +95,9 @@ class StackRun(Subcommand):
             )
 
         if not config_file.exists() and not has_yaml_suffix:
-            # check if it's a build config saved to docker dir
+            # check if it's a build config saved to container dir
             config_file = Path(
-                BUILDS_BASE_DIR / ImageType.docker.value / f"{args.config}-run.yaml"
+                BUILDS_BASE_DIR / ImageType.container.value / f"{args.config}-run.yaml"
             )
 
         if not config_file.exists() and not has_yaml_suffix:
@@ -115,12 +118,17 @@ class StackRun(Subcommand):
         config_dict = yaml.safe_load(config_file.read_text())
         config = parse_and_maybe_upgrade_config(config_dict)
 
-        if config.docker_image:
+        if config.container_image:
             script = (
                 importlib.resources.files("llama_stack")
                 / "distribution/start_container.sh"
             )
-            run_args = [script, config.docker_image]
+            image_name = (
+                f"distribution-{template_name}"
+                if template_name
+                else config.container_image
+            )
+            run_args = [script, image_name]
         else:
             current_conda_env = os.environ.get("CONDA_DEFAULT_ENV")
             image_name = args.image_name or current_conda_env
diff --git a/llama_stack/distribution/build.py b/llama_stack/distribution/build.py
index b8b4188ac..a29c8d5d1 100644
--- a/llama_stack/distribution/build.py
+++ b/llama_stack/distribution/build.py
@@ -10,7 +10,7 @@ import sys
 from enum import Enum
 
 from pathlib import Path
-from typing import Dict, List, Optional
+from typing import Dict, List
 
 from pydantic import BaseModel
 from termcolor import cprint
@@ -38,7 +38,7 @@ SERVER_DEPENDENCIES = [
 
 
 class ImageType(Enum):
-    docker = "docker"
+    container = "container"
     conda = "conda"
     venv = "venv"
 
@@ -77,8 +77,8 @@ def get_provider_dependencies(
 
             provider_spec = providers_for_api[provider_type]
             deps.extend(provider_spec.pip_packages)
-            if provider_spec.docker_image:
-                raise ValueError("A stack's dependencies cannot have a docker image")
+            if provider_spec.container_image:
+                raise ValueError("A stack's dependencies cannot have a container image")
 
     normal_deps = []
     special_deps = []
@@ -107,25 +107,28 @@ def build_image(
     build_config: BuildConfig,
     build_file_path: Path,
     image_name: str,
-    template_name: Optional[str] = None,
+    template_or_config: str,
 ):
-    docker_image = build_config.distribution_spec.docker_image or "python:3.10-slim"
+    container_base = (
+        build_config.distribution_spec.container_image or "python:3.10-slim"
+    )
 
     normal_deps, special_deps = get_provider_dependencies(
         build_config.distribution_spec.providers
     )
     normal_deps += SERVER_DEPENDENCIES
 
-    if build_config.image_type == ImageType.docker.value:
+    if build_config.image_type == ImageType.container.value:
         script = str(
             importlib.resources.files("llama_stack") / "distribution/build_container.sh"
         )
         args = [
             script,
+            template_or_config,
             image_name,
-            docker_image,
+            container_base,
             str(build_file_path),
-            str(BUILDS_BASE_DIR / ImageType.docker.value),
+            str(BUILDS_BASE_DIR / ImageType.container.value),
             " ".join(normal_deps),
         ]
     elif build_config.image_type == ImageType.conda.value:
diff --git a/llama_stack/distribution/build_container.sh b/llama_stack/distribution/build_container.sh
index 17902de0a..a2820ac13 100755
--- a/llama_stack/distribution/build_container.sh
+++ b/llama_stack/distribution/build_container.sh
@@ -12,22 +12,22 @@ TEST_PYPI_VERSION=${TEST_PYPI_VERSION:-}
 PYPI_VERSION=${PYPI_VERSION:-}
 BUILD_PLATFORM=${BUILD_PLATFORM:-}
 
-if [ "$#" -lt 4 ]; then
-  echo "Usage: $0 <build_name> <docker_base> <pip_dependencies> [<special_pip_deps>]" >&2
-  echo "Example: $0 my-fastapi-app python:3.9-slim 'fastapi uvicorn' " >&2
+if [ "$#" -lt 6 ]; then
+  # This only works for templates
+  echo "Usage: $0 <template_or_config> <image_name> <container_base> <build_file_path> <host_build_dir> <pip_dependencies> [<special_pip_deps>]" >&2
   exit 1
 fi
 
-special_pip_deps="$6"
-
 set -euo pipefail
 
-build_name="$1"
-image_name="distribution-$build_name"
-docker_base=$2
-build_file_path=$3
-host_build_dir=$4
-pip_dependencies=$5
+template_or_config="$1"
+image_name="$2"
+container_base="$3"
+build_file_path="$4"
+host_build_dir="$5"
+pip_dependencies="$6"
+special_pip_deps="$7"
+
 
 # Define color codes
 RED='\033[0;31m'
@@ -36,14 +36,14 @@ NC='\033[0m' # No Color
 
 SCRIPT_DIR=$(dirname "$(readlink -f "$0")")
 REPO_DIR=$(dirname $(dirname "$SCRIPT_DIR"))
-DOCKER_BINARY=${DOCKER_BINARY:-docker}
-DOCKER_OPTS=${DOCKER_OPTS:-}
+CONTAINER_BINARY=${CONTAINER_BINARY:-docker}
+CONTAINER_OPTS=${CONTAINER_OPTS:-}
 
 TEMP_DIR=$(mktemp -d)
 
-add_to_docker() {
+add_to_container() {
   local input
-  output_file="$TEMP_DIR/Dockerfile"
+  output_file="$TEMP_DIR/Containerfile"
   if [ -t 0 ]; then
     printf '%s\n' "$1" >>"$output_file"
   else
@@ -53,9 +53,9 @@ add_to_docker() {
 }
 
 # Update and install UBI9 components if UBI9 base image is used
-if [[ $docker_base == *"registry.access.redhat.com/ubi9"* ]]; then
-  add_to_docker << EOF
-FROM $docker_base
+if [[ $container_base == *"registry.access.redhat.com/ubi9"* ]]; then
+  add_to_container << EOF
+FROM $container_base
 WORKDIR /app
 
 RUN microdnf -y update && microdnf install -y iputils net-tools wget \
@@ -64,8 +64,8 @@ RUN microdnf -y update && microdnf install -y iputils net-tools wget \
 
 EOF
 else
-  add_to_docker << EOF
-FROM $docker_base
+  add_to_container << EOF
+FROM $container_base
 WORKDIR /app
 
 RUN apt-get update && apt-get install -y \
@@ -82,7 +82,7 @@ fi
 # Add pip dependencies first since llama-stack is what will change most often
 # so we can reuse layers.
 if [ -n "$pip_dependencies" ]; then
-  add_to_docker << EOF
+  add_to_container << EOF
 RUN pip install --no-cache $pip_dependencies
 EOF
 fi
@@ -90,7 +90,7 @@ fi
 if [ -n "$special_pip_deps" ]; then
   IFS='#' read -ra parts <<<"$special_pip_deps"
   for part in "${parts[@]}"; do
-    add_to_docker <<EOF
+    add_to_container <<EOF
 RUN pip install --no-cache $part
 EOF
   done
@@ -108,16 +108,16 @@ if [ -n "$LLAMA_STACK_DIR" ]; then
   # Install in editable format. We will mount the source code into the container
   # so that changes will be reflected in the container without having to do a
   # rebuild. This is just for development convenience.
-  add_to_docker << EOF
+  add_to_container << EOF
 RUN pip install --no-cache -e $stack_mount
 EOF
 else
   if [ -n "$TEST_PYPI_VERSION" ]; then
     # these packages are damaged in test-pypi, so install them first
-    add_to_docker << EOF
+    add_to_container << EOF
 RUN pip install fastapi libcst
 EOF
-    add_to_docker << EOF
+    add_to_container << EOF
 RUN pip install --no-cache --extra-index-url https://test.pypi.org/simple/ \
   llama-models==$TEST_PYPI_VERSION llama-stack-client==$TEST_PYPI_VERSION llama-stack==$TEST_PYPI_VERSION
 
@@ -128,7 +128,7 @@ EOF
     else
       SPEC_VERSION="llama-stack"
     fi
-    add_to_docker << EOF
+    add_to_container << EOF
 RUN pip install --no-cache $SPEC_VERSION
 EOF
   fi
@@ -140,24 +140,26 @@ if [ -n "$LLAMA_MODELS_DIR" ]; then
     exit 1
   fi
 
-  add_to_docker << EOF
+  add_to_container << EOF
 RUN pip uninstall -y llama-models
 RUN pip install --no-cache $models_mount
 
 EOF
 fi
 
-add_to_docker << EOF
-
-# This would be good in production but for debugging flexibility lets not add it right now
-# We need a more solid production ready entrypoint.sh anyway
-#
-ENTRYPOINT ["python", "-m", "llama_stack.distribution.server.server", "--template", "$build_name"]
-
+# if template_or_config ends with .yaml, it is not a template and we should not use the --template flag
+if [[ "$template_or_config" != *.yaml ]]; then
+  add_to_container << EOF
+ENTRYPOINT ["python", "-m", "llama_stack.distribution.server.server", "--template", "$template_or_config"]
 EOF
+else
+  add_to_container << EOF
+ENTRYPOINT ["python", "-m", "llama_stack.distribution.server.server"]
+EOF
+fi
 
-printf "Dockerfile created successfully in $TEMP_DIR/Dockerfile\n\n"
-cat $TEMP_DIR/Dockerfile
+printf "Containerfile created successfully in $TEMP_DIR/Containerfile\n\n"
+cat $TEMP_DIR/Containerfile
 printf "\n"
 
 mounts=""
@@ -170,11 +172,13 @@ fi
 
 if command -v selinuxenabled &>/dev/null && selinuxenabled; then
   # Disable SELinux labels -- we don't want to relabel the llama-stack source dir
-  DOCKER_OPTS="$DOCKER_OPTS --security-opt label=disable"
+  CONTAINER_OPTS="$CONTAINER_OPTS --security-opt label=disable"
 fi
 
 # Set version tag based on PyPI version
-if [ -n "$TEST_PYPI_VERSION" ]; then
+if [ -n "$PYPI_VERSION" ]; then
+  version_tag="$PYPI_VERSION"
+elif [ -n "$TEST_PYPI_VERSION" ]; then
   version_tag="test-$TEST_PYPI_VERSION"
 elif [[ -n "$LLAMA_STACK_DIR" || -n "$LLAMA_MODELS_DIR" ]]; then
   version_tag="dev"
@@ -200,7 +204,7 @@ else
 fi
 
 set -x
-$DOCKER_BINARY build $DOCKER_OPTS $PLATFORM -t $image_tag -f "$TEMP_DIR/Dockerfile" "$REPO_DIR" $mounts
+$CONTAINER_BINARY build $CONTAINER_OPTS $PLATFORM -t $image_tag -f "$TEMP_DIR/Containerfile" "$REPO_DIR" $mounts
 
 # clean up tmp/configs
 set +x
diff --git a/llama_stack/distribution/configure_container.sh b/llama_stack/distribution/configure_container.sh
index 5f64531eb..b01251e46 100755
--- a/llama_stack/distribution/configure_container.sh
+++ b/llama_stack/distribution/configure_container.sh
@@ -6,8 +6,8 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-DOCKER_BINARY=${DOCKER_BINARY:-docker}
-DOCKER_OPTS=${DOCKER_OPTS:-}
+CONTAINER_BINARY=${CONTAINER_BINARY:-docker}
+CONTAINER_OPTS=${CONTAINER_OPTS:-}
 LLAMA_STACK_DIR=${LLAMA_STACK_DIR:-}
 
 set -euo pipefail
@@ -24,13 +24,13 @@ if [ $# -lt 2 ]; then
   exit 1
 fi
 
-docker_image="$1"
+container_image="$1"
 host_build_dir="$2"
 container_build_dir="/app/builds"
 
 if command -v selinuxenabled &> /dev/null && selinuxenabled; then
   # Disable SELinux labels
-  DOCKER_OPTS="$DOCKER_OPTS --security-opt label=disable"
+  CONTAINER_OPTS="$CONTAINER_OPTS --security-opt label=disable"
 fi
 
 mounts=""
@@ -39,9 +39,9 @@ if [ -n "$LLAMA_STACK_DIR" ]; then
 fi
 
 set -x
-$DOCKER_BINARY run $DOCKER_OPTS -it \
+$CONTAINER_BINARY run $CONTAINER_OPTS -it \
   --entrypoint "/usr/local/bin/llama" \
   -v $host_build_dir:$container_build_dir \
   $mounts \
-  $docker_image \
+  $container_image \
   stack configure ./llamastack-build.yaml --output-dir $container_build_dir
diff --git a/llama_stack/distribution/datatypes.py b/llama_stack/distribution/datatypes.py
index 0a293cbc2..99ffeb346 100644
--- a/llama_stack/distribution/datatypes.py
+++ b/llama_stack/distribution/datatypes.py
@@ -13,14 +13,14 @@ from llama_stack.apis.datasets import Dataset, DatasetInput
 from llama_stack.apis.eval import Eval
 from llama_stack.apis.eval_tasks import EvalTask, EvalTaskInput
 from llama_stack.apis.inference import Inference
-from llama_stack.apis.memory import Memory
-from llama_stack.apis.memory_banks import MemoryBank, MemoryBankInput
 from llama_stack.apis.models import Model, ModelInput
 from llama_stack.apis.safety import Safety
 from llama_stack.apis.scoring import Scoring
 from llama_stack.apis.scoring_functions import ScoringFn, ScoringFnInput
 from llama_stack.apis.shields import Shield, ShieldInput
 from llama_stack.apis.tools import Tool, ToolGroup, ToolGroupInput, ToolRuntime
+from llama_stack.apis.vector_dbs import VectorDB, VectorDBInput
+from llama_stack.apis.vector_io import VectorIO
 from llama_stack.providers.datatypes import Api, ProviderSpec
 from llama_stack.providers.utils.kvstore.config import KVStoreConfig
 
@@ -34,7 +34,7 @@ RoutingKey = Union[str, List[str]]
 RoutableObject = Union[
     Model,
     Shield,
-    MemoryBank,
+    VectorDB,
     Dataset,
     ScoringFn,
     EvalTask,
@@ -47,7 +47,7 @@ RoutableObjectWithProvider = Annotated[
     Union[
         Model,
         Shield,
-        MemoryBank,
+        VectorDB,
         Dataset,
         ScoringFn,
         EvalTask,
@@ -60,7 +60,7 @@ RoutableObjectWithProvider = Annotated[
 RoutedProtocol = Union[
     Inference,
     Safety,
-    Memory,
+    VectorIO,
     DatasetIO,
     Scoring,
     Eval,
@@ -73,7 +73,7 @@ class AutoRoutedProviderSpec(ProviderSpec):
     provider_type: str = "router"
     config_class: str = ""
 
-    docker_image: Optional[str] = None
+    container_image: Optional[str] = None
     routing_table_api: Api
     module: str
     provider_data_validator: Optional[str] = Field(
@@ -89,7 +89,7 @@ class AutoRoutedProviderSpec(ProviderSpec):
 class RoutingTableProviderSpec(ProviderSpec):
     provider_type: str = "routing_table"
     config_class: str = ""
-    docker_image: Optional[str] = None
+    container_image: Optional[str] = None
 
     router_api: Api
     module: str
@@ -101,7 +101,7 @@ class DistributionSpec(BaseModel):
         default="",
         description="Description of the distribution",
     )
-    docker_image: Optional[str] = None
+    container_image: Optional[str] = None
     providers: Dict[str, Union[str, List[str]]] = Field(
         default_factory=dict,
         description="""
@@ -127,9 +127,9 @@ Reference to the distribution this package refers to. For unregistered (adhoc) p
 this could be just a hash
 """,
     )
-    docker_image: Optional[str] = Field(
+    container_image: Optional[str] = Field(
         default=None,
-        description="Reference to the docker image if this package refers to a container",
+        description="Reference to the container image if this package refers to a container",
     )
     apis: List[str] = Field(
         default_factory=list,
@@ -153,7 +153,7 @@ a default SQLite store will be used.""",
     # registry of "resources" in the distribution
     models: List[ModelInput] = Field(default_factory=list)
     shields: List[ShieldInput] = Field(default_factory=list)
-    memory_banks: List[MemoryBankInput] = Field(default_factory=list)
+    vector_dbs: List[VectorDBInput] = Field(default_factory=list)
     datasets: List[DatasetInput] = Field(default_factory=list)
     scoring_fns: List[ScoringFnInput] = Field(default_factory=list)
     eval_tasks: List[EvalTaskInput] = Field(default_factory=list)
@@ -168,5 +168,5 @@ class BuildConfig(BaseModel):
     )
     image_type: str = Field(
         default="conda",
-        description="Type of package to build (conda | docker | venv)",
+        description="Type of package to build (conda | container | venv)",
     )
diff --git a/llama_stack/distribution/distribution.py b/llama_stack/distribution/distribution.py
index 4183d92cd..b02d0fb6c 100644
--- a/llama_stack/distribution/distribution.py
+++ b/llama_stack/distribution/distribution.py
@@ -32,8 +32,8 @@ def builtin_automatically_routed_apis() -> List[AutoRoutedApiInfo]:
             router_api=Api.safety,
         ),
         AutoRoutedApiInfo(
-            routing_table_api=Api.memory_banks,
-            router_api=Api.memory,
+            routing_table_api=Api.vector_dbs,
+            router_api=Api.vector_io,
         ),
         AutoRoutedApiInfo(
             routing_table_api=Api.datasets,
diff --git a/llama_stack/distribution/library_client.py b/llama_stack/distribution/library_client.py
index 192667f2c..b2b290c66 100644
--- a/llama_stack/distribution/library_client.py
+++ b/llama_stack/distribution/library_client.py
@@ -129,8 +129,8 @@ class LlamaStackAsLibraryClient(LlamaStackClient):
             import nest_asyncio
 
             nest_asyncio.apply()
-        if not self.skip_logger_removal:
-            self._remove_root_logger_handlers()
+            if not self.skip_logger_removal:
+                self._remove_root_logger_handlers()
 
         return asyncio.run(self.async_client.initialize())
 
diff --git a/llama_stack/distribution/resolver.py b/llama_stack/distribution/resolver.py
index d7e947a46..dd6d4be6f 100644
--- a/llama_stack/distribution/resolver.py
+++ b/llama_stack/distribution/resolver.py
@@ -15,8 +15,6 @@ from llama_stack.apis.eval import Eval
 from llama_stack.apis.eval_tasks import EvalTasks
 from llama_stack.apis.inference import Inference
 from llama_stack.apis.inspect import Inspect
-from llama_stack.apis.memory import Memory
-from llama_stack.apis.memory_banks import MemoryBanks
 from llama_stack.apis.models import Models
 from llama_stack.apis.post_training import PostTraining
 from llama_stack.apis.safety import Safety
@@ -25,6 +23,8 @@ from llama_stack.apis.scoring_functions import ScoringFunctions
 from llama_stack.apis.shields import Shields
 from llama_stack.apis.telemetry import Telemetry
 from llama_stack.apis.tools import ToolGroups, ToolRuntime
+from llama_stack.apis.vector_dbs import VectorDBs
+from llama_stack.apis.vector_io import VectorIO
 from llama_stack.distribution.client import get_client_impl
 from llama_stack.distribution.datatypes import (
     AutoRoutedProviderSpec,
@@ -40,7 +40,6 @@ from llama_stack.providers.datatypes import (
     DatasetsProtocolPrivate,
     EvalTasksProtocolPrivate,
     InlineProviderSpec,
-    MemoryBanksProtocolPrivate,
     ModelsProtocolPrivate,
     ProviderSpec,
     RemoteProviderConfig,
@@ -48,6 +47,7 @@ from llama_stack.providers.datatypes import (
     ScoringFunctionsProtocolPrivate,
     ShieldsProtocolPrivate,
     ToolsProtocolPrivate,
+    VectorDBsProtocolPrivate,
 )
 
 log = logging.getLogger(__name__)
@@ -62,8 +62,8 @@ def api_protocol_map() -> Dict[Api, Any]:
         Api.agents: Agents,
         Api.inference: Inference,
         Api.inspect: Inspect,
-        Api.memory: Memory,
-        Api.memory_banks: MemoryBanks,
+        Api.vector_io: VectorIO,
+        Api.vector_dbs: VectorDBs,
         Api.models: Models,
         Api.safety: Safety,
         Api.shields: Shields,
@@ -84,7 +84,7 @@ def additional_protocols_map() -> Dict[Api, Any]:
     return {
         Api.inference: (ModelsProtocolPrivate, Models, Api.models),
         Api.tool_groups: (ToolsProtocolPrivate, ToolGroups, Api.tool_groups),
-        Api.memory: (MemoryBanksProtocolPrivate, MemoryBanks, Api.memory_banks),
+        Api.vector_io: (VectorDBsProtocolPrivate, VectorDBs, Api.vector_dbs),
         Api.safety: (ShieldsProtocolPrivate, Shields, Api.shields),
         Api.datasetio: (DatasetsProtocolPrivate, Datasets, Api.datasets),
         Api.scoring: (
@@ -145,7 +145,9 @@ async def resolve_impls(
                 log.warning(
                     f"Provider `{provider.provider_type}` for API `{api}` is deprecated and will be removed in a future release: {p.deprecation_warning}",
                 )
-            p.deps__ = [a.value for a in p.api_dependencies]
+            p.deps__ = [a.value for a in p.api_dependencies] + [
+                a.value for a in p.optional_api_dependencies
+            ]
             spec = ProviderWithSpec(
                 spec=p,
                 **(provider.model_dump()),
@@ -229,6 +231,9 @@ async def resolve_impls(
     inner_impls_by_provider_id = {f"inner-{x.value}": {} for x in router_apis}
     for api_str, provider in sorted_providers:
         deps = {a: impls[a] for a in provider.spec.api_dependencies}
+        for a in provider.spec.optional_api_dependencies:
+            if a in impls:
+                deps[a] = impls[a]
 
         inner_impls = {}
         if isinstance(provider.spec, RoutingTableProviderSpec):
@@ -265,7 +270,7 @@ def topological_sort(
                 deps.append(dep)
 
         for dep in deps:
-            if dep not in visited:
+            if dep not in visited and dep in providers_with_specs:
                 dfs((dep, providers_with_specs[dep]), visited, stack)
 
         stack.append(api_str)
@@ -328,6 +333,8 @@ async def instantiate_provider(
     impl.__provider_spec__ = provider_spec
     impl.__provider_config__ = config
 
+    # TODO: check compliance for special tool groups
+    # the impl should be for Api.tool_runtime, the name should be the special tool group, the protocol should be the special tool group protocol
     check_protocol_compliance(impl, protocols[provider_spec.api])
     if (
         not isinstance(provider_spec, AutoRoutedProviderSpec)
diff --git a/llama_stack/distribution/routers/__init__.py b/llama_stack/distribution/routers/__init__.py
index f19a2bffc..156cda385 100644
--- a/llama_stack/distribution/routers/__init__.py
+++ b/llama_stack/distribution/routers/__init__.py
@@ -14,11 +14,11 @@ from llama_stack.providers.datatypes import Api, RoutingTable
 from .routing_tables import (
     DatasetsRoutingTable,
     EvalTasksRoutingTable,
-    MemoryBanksRoutingTable,
     ModelsRoutingTable,
     ScoringFunctionsRoutingTable,
     ShieldsRoutingTable,
     ToolGroupsRoutingTable,
+    VectorDBsRoutingTable,
 )
 
 
@@ -29,7 +29,7 @@ async def get_routing_table_impl(
     dist_registry: DistributionRegistry,
 ) -> Any:
     api_to_tables = {
-        "memory_banks": MemoryBanksRoutingTable,
+        "vector_dbs": VectorDBsRoutingTable,
         "models": ModelsRoutingTable,
         "shields": ShieldsRoutingTable,
         "datasets": DatasetsRoutingTable,
@@ -51,14 +51,14 @@ async def get_auto_router_impl(api: Api, routing_table: RoutingTable, _deps) ->
         DatasetIORouter,
         EvalRouter,
         InferenceRouter,
-        MemoryRouter,
         SafetyRouter,
         ScoringRouter,
         ToolRuntimeRouter,
+        VectorIORouter,
     )
 
     api_to_routers = {
-        "memory": MemoryRouter,
+        "vector_io": VectorIORouter,
         "inference": InferenceRouter,
         "safety": SafetyRouter,
         "datasetio": DatasetIORouter,
diff --git a/llama_stack/distribution/routers/routers.py b/llama_stack/distribution/routers/routers.py
index 8080b9dff..6bb2045bd 100644
--- a/llama_stack/distribution/routers/routers.py
+++ b/llama_stack/distribution/routers/routers.py
@@ -27,8 +27,6 @@ from llama_stack.apis.inference import (
     ToolDefinition,
     ToolPromptFormat,
 )
-from llama_stack.apis.memory import Memory, MemoryBankDocument, QueryDocumentsResponse
-from llama_stack.apis.memory_banks.memory_banks import BankParams
 from llama_stack.apis.models import ModelType
 from llama_stack.apis.safety import RunShieldResponse, Safety
 from llama_stack.apis.scoring import (
@@ -38,12 +36,20 @@ from llama_stack.apis.scoring import (
     ScoringFnParams,
 )
 from llama_stack.apis.shields import Shield
-from llama_stack.apis.tools import ToolDef, ToolRuntime
+from llama_stack.apis.tools import (
+    RAGDocument,
+    RAGQueryConfig,
+    RAGQueryResult,
+    RAGToolRuntime,
+    ToolDef,
+    ToolRuntime,
+)
+from llama_stack.apis.vector_io import Chunk, QueryChunksResponse, VectorIO
 from llama_stack.providers.datatypes import RoutingTable
 
 
-class MemoryRouter(Memory):
-    """Routes to an provider based on the memory bank identifier"""
+class VectorIORouter(VectorIO):
+    """Routes to an provider based on the vector db identifier"""
 
     def __init__(
         self,
@@ -57,38 +63,40 @@ class MemoryRouter(Memory):
     async def shutdown(self) -> None:
         pass
 
-    async def register_memory_bank(
+    async def register_vector_db(
         self,
-        memory_bank_id: str,
-        params: BankParams,
+        vector_db_id: str,
+        embedding_model: str,
+        embedding_dimension: Optional[int] = 384,
         provider_id: Optional[str] = None,
-        provider_memorybank_id: Optional[str] = None,
+        provider_vector_db_id: Optional[str] = None,
     ) -> None:
-        await self.routing_table.register_memory_bank(
-            memory_bank_id,
-            params,
+        await self.routing_table.register_vector_db(
+            vector_db_id,
+            embedding_model,
+            embedding_dimension,
             provider_id,
-            provider_memorybank_id,
+            provider_vector_db_id,
         )
 
-    async def insert_documents(
+    async def insert_chunks(
         self,
-        bank_id: str,
-        documents: List[MemoryBankDocument],
+        vector_db_id: str,
+        chunks: List[Chunk],
         ttl_seconds: Optional[int] = None,
     ) -> None:
-        return await self.routing_table.get_provider_impl(bank_id).insert_documents(
-            bank_id, documents, ttl_seconds
+        return await self.routing_table.get_provider_impl(vector_db_id).insert_chunks(
+            vector_db_id, chunks, ttl_seconds
         )
 
-    async def query_documents(
+    async def query_chunks(
         self,
-        bank_id: str,
+        vector_db_id: str,
         query: InterleavedContent,
         params: Optional[Dict[str, Any]] = None,
-    ) -> QueryDocumentsResponse:
-        return await self.routing_table.get_provider_impl(bank_id).query_documents(
-            bank_id, query, params
+    ) -> QueryChunksResponse:
+        return await self.routing_table.get_provider_impl(vector_db_id).query_chunks(
+            vector_db_id, query, params
         )
 
 
@@ -399,22 +407,54 @@ class EvalRouter(Eval):
 
 
 class ToolRuntimeRouter(ToolRuntime):
+    class RagToolImpl(RAGToolRuntime):
+        def __init__(
+            self,
+            routing_table: RoutingTable,
+        ) -> None:
+            self.routing_table = routing_table
+
+        async def query(
+            self,
+            content: InterleavedContent,
+            vector_db_ids: List[str],
+            query_config: Optional[RAGQueryConfig] = None,
+        ) -> RAGQueryResult:
+            return await self.routing_table.get_provider_impl(
+                "query_from_memory"
+            ).query(content, vector_db_ids, query_config)
+
+        async def insert(
+            self,
+            documents: List[RAGDocument],
+            vector_db_id: str,
+            chunk_size_in_tokens: int = 512,
+        ) -> None:
+            return await self.routing_table.get_provider_impl(
+                "insert_into_memory"
+            ).insert(documents, vector_db_id, chunk_size_in_tokens)
+
     def __init__(
         self,
         routing_table: RoutingTable,
     ) -> None:
         self.routing_table = routing_table
 
+        # HACK ALERT this should be in sync with "get_all_api_endpoints()"
+        self.rag_tool = self.RagToolImpl(routing_table)
+        for method in ("query", "insert"):
+            setattr(self, f"rag_tool.{method}", getattr(self.rag_tool, method))
+
     async def initialize(self) -> None:
         pass
 
     async def shutdown(self) -> None:
         pass
 
-    async def invoke_tool(self, tool_name: str, args: Dict[str, Any]) -> Any:
+    async def invoke_tool(self, tool_name: str, kwargs: Dict[str, Any]) -> Any:
         return await self.routing_table.get_provider_impl(tool_name).invoke_tool(
             tool_name=tool_name,
-            args=args,
+            kwargs=kwargs,
         )
 
     async def list_runtime_tools(
diff --git a/llama_stack/distribution/routers/routing_tables.py b/llama_stack/distribution/routers/routing_tables.py
index 889bd4624..1d035d878 100644
--- a/llama_stack/distribution/routers/routing_tables.py
+++ b/llama_stack/distribution/routers/routing_tables.py
@@ -12,13 +12,6 @@ from llama_stack.apis.common.content_types import URL
 from llama_stack.apis.common.type_system import ParamType
 from llama_stack.apis.datasets import Dataset, Datasets, ListDatasetsResponse
 from llama_stack.apis.eval_tasks import EvalTask, EvalTasks, ListEvalTasksResponse
-from llama_stack.apis.memory_banks import (
-    BankParams,
-    ListMemoryBanksResponse,
-    MemoryBank,
-    MemoryBanks,
-    MemoryBankType,
-)
 from llama_stack.apis.models import ListModelsResponse, Model, Models, ModelType
 from llama_stack.apis.resource import ResourceType
 from llama_stack.apis.scoring_functions import (
@@ -36,6 +29,7 @@ from llama_stack.apis.tools import (
     ToolGroups,
     ToolHost,
 )
+from llama_stack.apis.vector_dbs import ListVectorDBsResponse, VectorDB, VectorDBs
 from llama_stack.distribution.datatypes import (
     RoutableObject,
     RoutableObjectWithProvider,
@@ -59,8 +53,8 @@ async def register_object_with_provider(obj: RoutableObject, p: Any) -> Routable
         return await p.register_model(obj)
     elif api == Api.safety:
         return await p.register_shield(obj)
-    elif api == Api.memory:
-        return await p.register_memory_bank(obj)
+    elif api == Api.vector_io:
+        return await p.register_vector_db(obj)
     elif api == Api.datasetio:
         return await p.register_dataset(obj)
     elif api == Api.scoring:
@@ -75,8 +69,8 @@ async def register_object_with_provider(obj: RoutableObject, p: Any) -> Routable
 
 async def unregister_object_from_provider(obj: RoutableObject, p: Any) -> None:
     api = get_impl_api(p)
-    if api == Api.memory:
-        return await p.unregister_memory_bank(obj.identifier)
+    if api == Api.vector_io:
+        return await p.unregister_vector_db(obj.identifier)
     elif api == Api.inference:
         return await p.unregister_model(obj.identifier)
     elif api == Api.datasetio:
@@ -120,8 +114,8 @@ class CommonRoutingTableImpl(RoutingTable):
                 p.model_store = self
             elif api == Api.safety:
                 p.shield_store = self
-            elif api == Api.memory:
-                p.memory_bank_store = self
+            elif api == Api.vector_io:
+                p.vector_db_store = self
             elif api == Api.datasetio:
                 p.dataset_store = self
             elif api == Api.scoring:
@@ -145,8 +139,8 @@ class CommonRoutingTableImpl(RoutingTable):
                 return ("Inference", "model")
             elif isinstance(self, ShieldsRoutingTable):
                 return ("Safety", "shield")
-            elif isinstance(self, MemoryBanksRoutingTable):
-                return ("Memory", "memory_bank")
+            elif isinstance(self, VectorDBsRoutingTable):
+                return ("VectorIO", "vector_db")
             elif isinstance(self, DatasetsRoutingTable):
                 return ("DatasetIO", "dataset")
             elif isinstance(self, ScoringFunctionsRoutingTable):
@@ -196,9 +190,6 @@ class CommonRoutingTableImpl(RoutingTable):
     async def register_object(
         self, obj: RoutableObjectWithProvider
     ) -> RoutableObjectWithProvider:
-        # Get existing objects from registry
-        existing_obj = await self.dist_registry.get(obj.type, obj.identifier)
-
         # if provider_id is not specified, pick an arbitrary one from existing entries
         if not obj.provider_id and len(self.impls_by_provider_id) > 0:
             obj.provider_id = list(self.impls_by_provider_id.keys())[0]
@@ -311,22 +302,23 @@ class ShieldsRoutingTable(CommonRoutingTableImpl, Shields):
         return shield
 
 
-class MemoryBanksRoutingTable(CommonRoutingTableImpl, MemoryBanks):
-    async def list_memory_banks(self) -> ListMemoryBanksResponse:
-        return ListMemoryBanksResponse(data=await self.get_all_with_type("memory_bank"))
+class VectorDBsRoutingTable(CommonRoutingTableImpl, VectorDBs):
+    async def list_vector_dbs(self) -> ListVectorDBsResponse:
+        return ListVectorDBsResponse(data=await self.get_all_with_type("vector_db"))
 
-    async def get_memory_bank(self, memory_bank_id: str) -> Optional[MemoryBank]:
-        return await self.get_object_by_identifier("memory_bank", memory_bank_id)
+    async def get_vector_db(self, vector_db_id: str) -> Optional[VectorDB]:
+        return await self.get_object_by_identifier("vector_db", vector_db_id)
 
-    async def register_memory_bank(
+    async def register_vector_db(
         self,
-        memory_bank_id: str,
-        params: BankParams,
+        vector_db_id: str,
+        embedding_model: str,
+        embedding_dimension: Optional[int] = 384,
         provider_id: Optional[str] = None,
-        provider_memory_bank_id: Optional[str] = None,
-    ) -> MemoryBank:
-        if provider_memory_bank_id is None:
-            provider_memory_bank_id = memory_bank_id
+        provider_vector_db_id: Optional[str] = None,
+    ) -> VectorDB:
+        if provider_vector_db_id is None:
+            provider_vector_db_id = vector_db_id
         if provider_id is None:
             # If provider_id not specified, use the only provider if it supports this shield type
             if len(self.impls_by_provider_id) == 1:
@@ -335,44 +327,39 @@ class MemoryBanksRoutingTable(CommonRoutingTableImpl, MemoryBanks):
                 raise ValueError(
                     "No provider specified and multiple providers available. Please specify a provider_id."
                 )
-        model = await self.get_object_by_identifier("model", params.embedding_model)
+        model = await self.get_object_by_identifier("model", embedding_model)
         if model is None:
-            if params.embedding_model == "all-MiniLM-L6-v2":
+            if embedding_model == "all-MiniLM-L6-v2":
                 raise ValueError(
                     "Embeddings are now served via Inference providers. "
                     "Please upgrade your run.yaml to include inline::sentence-transformer as an additional inference provider. "
                     "See https://github.com/meta-llama/llama-stack/blob/main/llama_stack/templates/together/run.yaml for an example."
                 )
             else:
-                raise ValueError(f"Model {params.embedding_model} not found")
+                raise ValueError(f"Model {embedding_model} not found")
         if model.model_type != ModelType.embedding:
-            raise ValueError(
-                f"Model {params.embedding_model} is not an embedding model"
-            )
+            raise ValueError(f"Model {embedding_model} is not an embedding model")
         if "embedding_dimension" not in model.metadata:
             raise ValueError(
-                f"Model {params.embedding_model} does not have an embedding dimension"
+                f"Model {embedding_model} does not have an embedding dimension"
             )
-        memory_bank_data = {
-            "identifier": memory_bank_id,
-            "type": ResourceType.memory_bank.value,
+        vector_db_data = {
+            "identifier": vector_db_id,
+            "type": ResourceType.vector_db.value,
             "provider_id": provider_id,
-            "provider_resource_id": provider_memory_bank_id,
-            **params.model_dump(),
+            "provider_resource_id": provider_vector_db_id,
+            "embedding_model": embedding_model,
+            "embedding_dimension": model.metadata["embedding_dimension"],
         }
-        if params.memory_bank_type == MemoryBankType.vector.value:
-            memory_bank_data["embedding_dimension"] = model.metadata[
-                "embedding_dimension"
-            ]
-        memory_bank = TypeAdapter(MemoryBank).validate_python(memory_bank_data)
-        await self.register_object(memory_bank)
-        return memory_bank
+        vector_db = TypeAdapter(VectorDB).validate_python(vector_db_data)
+        await self.register_object(vector_db)
+        return vector_db
 
-    async def unregister_memory_bank(self, memory_bank_id: str) -> None:
-        existing_bank = await self.get_memory_bank(memory_bank_id)
-        if existing_bank is None:
-            raise ValueError(f"Memory bank {memory_bank_id} not found")
-        await self.unregister_object(existing_bank)
+    async def unregister_vector_db(self, vector_db_id: str) -> None:
+        existing_vector_db = await self.get_vector_db(vector_db_id)
+        if existing_vector_db is None:
+            raise ValueError(f"Vector DB {vector_db_id} not found")
+        await self.unregister_object(existing_vector_db)
 
 
 class DatasetsRoutingTable(CommonRoutingTableImpl, Datasets):
diff --git a/llama_stack/distribution/server/endpoints.py b/llama_stack/distribution/server/endpoints.py
index af429e020..180479e40 100644
--- a/llama_stack/distribution/server/endpoints.py
+++ b/llama_stack/distribution/server/endpoints.py
@@ -9,6 +9,8 @@ from typing import Dict, List
 
 from pydantic import BaseModel
 
+from llama_stack.apis.tools import RAGToolRuntime, SpecialToolGroup
+
 from llama_stack.apis.version import LLAMA_STACK_API_VERSION
 
 from llama_stack.distribution.resolver import api_protocol_map
@@ -22,21 +24,39 @@ class ApiEndpoint(BaseModel):
     name: str
 
 
+def toolgroup_protocol_map():
+    return {
+        SpecialToolGroup.rag_tool: RAGToolRuntime,
+    }
+
+
 def get_all_api_endpoints() -> Dict[Api, List[ApiEndpoint]]:
     apis = {}
 
     protocols = api_protocol_map()
+    toolgroup_protocols = toolgroup_protocol_map()
     for api, protocol in protocols.items():
         endpoints = []
         protocol_methods = inspect.getmembers(protocol, predicate=inspect.isfunction)
 
+        # HACK ALERT
+        if api == Api.tool_runtime:
+            for tool_group in SpecialToolGroup:
+                sub_protocol = toolgroup_protocols[tool_group]
+                sub_protocol_methods = inspect.getmembers(
+                    sub_protocol, predicate=inspect.isfunction
+                )
+                for name, method in sub_protocol_methods:
+                    if not hasattr(method, "__webmethod__"):
+                        continue
+                    protocol_methods.append((f"{tool_group.value}.{name}", method))
+
         for name, method in protocol_methods:
             if not hasattr(method, "__webmethod__"):
                 continue
 
             webmethod = method.__webmethod__
             route = f"/{LLAMA_STACK_API_VERSION}/{webmethod.route.lstrip('/')}"
-
             if webmethod.method == "GET":
                 method = "get"
             elif webmethod.method == "DELETE":
diff --git a/llama_stack/distribution/stack.py b/llama_stack/distribution/stack.py
index ad7bcd234..f0c34dba4 100644
--- a/llama_stack/distribution/stack.py
+++ b/llama_stack/distribution/stack.py
@@ -21,8 +21,6 @@ from llama_stack.apis.eval import Eval
 from llama_stack.apis.eval_tasks import EvalTasks
 from llama_stack.apis.inference import Inference
 from llama_stack.apis.inspect import Inspect
-from llama_stack.apis.memory import Memory
-from llama_stack.apis.memory_banks import MemoryBanks
 from llama_stack.apis.models import Models
 from llama_stack.apis.post_training import PostTraining
 from llama_stack.apis.safety import Safety
@@ -31,7 +29,9 @@ from llama_stack.apis.scoring_functions import ScoringFunctions
 from llama_stack.apis.shields import Shields
 from llama_stack.apis.synthetic_data_generation import SyntheticDataGeneration
 from llama_stack.apis.telemetry import Telemetry
-from llama_stack.apis.tools import ToolGroups, ToolRuntime
+from llama_stack.apis.tools import RAGToolRuntime, ToolGroups, ToolRuntime
+from llama_stack.apis.vector_dbs import VectorDBs
+from llama_stack.apis.vector_io import VectorIO
 from llama_stack.distribution.datatypes import StackRunConfig
 from llama_stack.distribution.distribution import get_provider_registry
 from llama_stack.distribution.resolver import ProviderRegistry, resolve_impls
@@ -42,7 +42,7 @@ log = logging.getLogger(__name__)
 
 
 class LlamaStack(
-    MemoryBanks,
+    VectorDBs,
     Inference,
     BatchInference,
     Agents,
@@ -51,7 +51,7 @@ class LlamaStack(
     Datasets,
     Telemetry,
     PostTraining,
-    Memory,
+    VectorIO,
     Eval,
     EvalTasks,
     Scoring,
@@ -62,6 +62,7 @@ class LlamaStack(
     Inspect,
     ToolGroups,
     ToolRuntime,
+    RAGToolRuntime,
 ):
     pass
 
@@ -69,7 +70,7 @@ class LlamaStack(
 RESOURCES = [
     ("models", Api.models, "register_model", "list_models"),
     ("shields", Api.shields, "register_shield", "list_shields"),
-    ("memory_banks", Api.memory_banks, "register_memory_bank", "list_memory_banks"),
+    ("vector_dbs", Api.vector_dbs, "register_vector_db", "list_vector_dbs"),
     ("datasets", Api.datasets, "register_dataset", "list_datasets"),
     (
         "scoring_fns",
diff --git a/llama_stack/distribution/start_container.sh b/llama_stack/distribution/start_container.sh
index 3b49a22f8..2c5d65d09 100755
--- a/llama_stack/distribution/start_container.sh
+++ b/llama_stack/distribution/start_container.sh
@@ -6,8 +6,8 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-DOCKER_BINARY=${DOCKER_BINARY:-docker}
-DOCKER_OPTS=${DOCKER_OPTS:-}
+CONTAINER_BINARY=${CONTAINER_BINARY:-docker}
+CONTAINER_OPTS=${CONTAINER_OPTS:-}
 LLAMA_CHECKPOINT_DIR=${LLAMA_CHECKPOINT_DIR:-}
 LLAMA_STACK_DIR=${LLAMA_STACK_DIR:-}
 TEST_PYPI_VERSION=${TEST_PYPI_VERSION:-}
@@ -30,8 +30,8 @@ if [ $# -lt 3 ]; then
   exit 1
 fi
 
-build_name="$1"
-docker_image="localhost/distribution-$build_name"
+image_name="$1"
+container_image="localhost/$image_name"
 shift
 
 yaml_config="$1"
@@ -64,7 +64,7 @@ set -x
 
 if command -v selinuxenabled &> /dev/null && selinuxenabled; then
   # Disable SELinux labels
-  DOCKER_OPTS="$DOCKER_OPTS --security-opt label=disable"
+  CONTAINER_OPTS="$CONTAINER_OPTS --security-opt label=disable"
 fi
 
 mounts=""
@@ -73,23 +73,25 @@ if [ -n "$LLAMA_STACK_DIR" ]; then
 fi
 if [ -n "$LLAMA_CHECKPOINT_DIR" ]; then
   mounts="$mounts -v $LLAMA_CHECKPOINT_DIR:/root/.llama"
-  DOCKER_OPTS="$DOCKER_OPTS --gpus=all"
+  CONTAINER_OPTS="$CONTAINER_OPTS --gpus=all"
 fi
 
-version_tag="latest"
 if [ -n "$PYPI_VERSION" ]; then
   version_tag="$PYPI_VERSION"
 elif [ -n "$LLAMA_STACK_DIR" ]; then
   version_tag="dev"
 elif [ -n "$TEST_PYPI_VERSION" ]; then
   version_tag="test-$TEST_PYPI_VERSION"
+else
+  URL="https://pypi.org/pypi/llama-stack/json"
+  version_tag=$(curl -s $URL | jq -r '.info.version')
 fi
 
-$DOCKER_BINARY run $DOCKER_OPTS -it \
+$CONTAINER_BINARY run $CONTAINER_OPTS -it \
   -p $port:$port \
   $env_vars \
   -v "$yaml_config:/app/config.yaml" \
   $mounts \
   --env LLAMA_STACK_PORT=$port \
   --entrypoint='["python", "-m", "llama_stack.distribution.server.server", "--yaml-config", "/app/config.yaml"]' \
-  $docker_image:$version_tag
+  $container_image:$version_tag
diff --git a/llama_stack/distribution/store/registry.py b/llama_stack/distribution/store/registry.py
index 010d137ec..bf0ff3fd0 100644
--- a/llama_stack/distribution/store/registry.py
+++ b/llama_stack/distribution/store/registry.py
@@ -35,7 +35,7 @@ class DistributionRegistry(Protocol):
 
 
 REGISTER_PREFIX = "distributions:registry"
-KEY_VERSION = "v5"
+KEY_VERSION = "v7"
 KEY_FORMAT = f"{REGISTER_PREFIX}:{KEY_VERSION}::" + "{type}:{identifier}"
 
 
diff --git a/llama_stack/distribution/store/tests/test_registry.py b/llama_stack/distribution/store/tests/test_registry.py
index 9c5b72f93..78d59a088 100644
--- a/llama_stack/distribution/store/tests/test_registry.py
+++ b/llama_stack/distribution/store/tests/test_registry.py
@@ -9,7 +9,7 @@ import os
 import pytest
 import pytest_asyncio
 from llama_stack.apis.inference import Model
-from llama_stack.apis.memory_banks import VectorMemoryBank
+from llama_stack.apis.vector_dbs import VectorDB
 
 from llama_stack.distribution.store.registry import (
     CachedDiskDistributionRegistry,
@@ -42,13 +42,12 @@ async def cached_registry(config):
 
 
 @pytest.fixture
-def sample_bank():
-    return VectorMemoryBank(
-        identifier="test_bank",
+def sample_vector_db():
+    return VectorDB(
+        identifier="test_vector_db",
         embedding_model="all-MiniLM-L6-v2",
-        chunk_size_in_tokens=512,
-        overlap_size_in_tokens=64,
-        provider_resource_id="test_bank",
+        embedding_dimension=384,
+        provider_resource_id="test_vector_db",
         provider_id="test-provider",
     )
 
@@ -70,19 +69,17 @@ async def test_registry_initialization(registry):
 
 
 @pytest.mark.asyncio
-async def test_basic_registration(registry, sample_bank, sample_model):
-    print(f"Registering {sample_bank}")
-    await registry.register(sample_bank)
+async def test_basic_registration(registry, sample_vector_db, sample_model):
+    print(f"Registering {sample_vector_db}")
+    await registry.register(sample_vector_db)
     print(f"Registering {sample_model}")
     await registry.register(sample_model)
-    print("Getting bank")
-    result_bank = await registry.get("memory_bank", "test_bank")
-    assert result_bank is not None
-    assert result_bank.identifier == sample_bank.identifier
-    assert result_bank.embedding_model == sample_bank.embedding_model
-    assert result_bank.chunk_size_in_tokens == sample_bank.chunk_size_in_tokens
-    assert result_bank.overlap_size_in_tokens == sample_bank.overlap_size_in_tokens
-    assert result_bank.provider_id == sample_bank.provider_id
+    print("Getting vector_db")
+    result_vector_db = await registry.get("vector_db", "test_vector_db")
+    assert result_vector_db is not None
+    assert result_vector_db.identifier == sample_vector_db.identifier
+    assert result_vector_db.embedding_model == sample_vector_db.embedding_model
+    assert result_vector_db.provider_id == sample_vector_db.provider_id
 
     result_model = await registry.get("model", "test_model")
     assert result_model is not None
@@ -91,24 +88,23 @@ async def test_basic_registration(registry, sample_bank, sample_model):
 
 
 @pytest.mark.asyncio
-async def test_cached_registry_initialization(config, sample_bank, sample_model):
+async def test_cached_registry_initialization(config, sample_vector_db, sample_model):
     # First populate the disk registry
     disk_registry = DiskDistributionRegistry(await kvstore_impl(config))
     await disk_registry.initialize()
-    await disk_registry.register(sample_bank)
+    await disk_registry.register(sample_vector_db)
     await disk_registry.register(sample_model)
 
     # Test cached version loads from disk
     cached_registry = CachedDiskDistributionRegistry(await kvstore_impl(config))
     await cached_registry.initialize()
 
-    result_bank = await cached_registry.get("memory_bank", "test_bank")
-    assert result_bank is not None
-    assert result_bank.identifier == sample_bank.identifier
-    assert result_bank.embedding_model == sample_bank.embedding_model
-    assert result_bank.chunk_size_in_tokens == sample_bank.chunk_size_in_tokens
-    assert result_bank.overlap_size_in_tokens == sample_bank.overlap_size_in_tokens
-    assert result_bank.provider_id == sample_bank.provider_id
+    result_vector_db = await cached_registry.get("vector_db", "test_vector_db")
+    assert result_vector_db is not None
+    assert result_vector_db.identifier == sample_vector_db.identifier
+    assert result_vector_db.embedding_model == sample_vector_db.embedding_model
+    assert result_vector_db.embedding_dimension == sample_vector_db.embedding_dimension
+    assert result_vector_db.provider_id == sample_vector_db.provider_id
 
 
 @pytest.mark.asyncio
@@ -116,29 +112,28 @@ async def test_cached_registry_updates(config):
     cached_registry = CachedDiskDistributionRegistry(await kvstore_impl(config))
     await cached_registry.initialize()
 
-    new_bank = VectorMemoryBank(
-        identifier="test_bank_2",
+    new_vector_db = VectorDB(
+        identifier="test_vector_db_2",
         embedding_model="all-MiniLM-L6-v2",
-        chunk_size_in_tokens=256,
-        overlap_size_in_tokens=32,
-        provider_resource_id="test_bank_2",
+        embedding_dimension=384,
+        provider_resource_id="test_vector_db_2",
         provider_id="baz",
     )
-    await cached_registry.register(new_bank)
+    await cached_registry.register(new_vector_db)
 
     # Verify in cache
-    result_bank = await cached_registry.get("memory_bank", "test_bank_2")
-    assert result_bank is not None
-    assert result_bank.identifier == new_bank.identifier
-    assert result_bank.provider_id == new_bank.provider_id
+    result_vector_db = await cached_registry.get("vector_db", "test_vector_db_2")
+    assert result_vector_db is not None
+    assert result_vector_db.identifier == new_vector_db.identifier
+    assert result_vector_db.provider_id == new_vector_db.provider_id
 
     # Verify persisted to disk
     new_registry = DiskDistributionRegistry(await kvstore_impl(config))
     await new_registry.initialize()
-    result_bank = await new_registry.get("memory_bank", "test_bank_2")
-    assert result_bank is not None
-    assert result_bank.identifier == new_bank.identifier
-    assert result_bank.provider_id == new_bank.provider_id
+    result_vector_db = await new_registry.get("vector_db", "test_vector_db_2")
+    assert result_vector_db is not None
+    assert result_vector_db.identifier == new_vector_db.identifier
+    assert result_vector_db.provider_id == new_vector_db.provider_id
 
 
 @pytest.mark.asyncio
@@ -146,30 +141,28 @@ async def test_duplicate_provider_registration(config):
     cached_registry = CachedDiskDistributionRegistry(await kvstore_impl(config))
     await cached_registry.initialize()
 
-    original_bank = VectorMemoryBank(
-        identifier="test_bank_2",
+    original_vector_db = VectorDB(
+        identifier="test_vector_db_2",
         embedding_model="all-MiniLM-L6-v2",
-        chunk_size_in_tokens=256,
-        overlap_size_in_tokens=32,
-        provider_resource_id="test_bank_2",
+        embedding_dimension=384,
+        provider_resource_id="test_vector_db_2",
         provider_id="baz",
     )
-    await cached_registry.register(original_bank)
+    await cached_registry.register(original_vector_db)
 
-    duplicate_bank = VectorMemoryBank(
-        identifier="test_bank_2",
+    duplicate_vector_db = VectorDB(
+        identifier="test_vector_db_2",
         embedding_model="different-model",
-        chunk_size_in_tokens=128,
-        overlap_size_in_tokens=16,
-        provider_resource_id="test_bank_2",
+        embedding_dimension=384,
+        provider_resource_id="test_vector_db_2",
         provider_id="baz",  # Same provider_id
     )
-    await cached_registry.register(duplicate_bank)
+    await cached_registry.register(duplicate_vector_db)
 
-    result = await cached_registry.get("memory_bank", "test_bank_2")
+    result = await cached_registry.get("vector_db", "test_vector_db_2")
     assert result is not None
     assert (
-        result.embedding_model == original_bank.embedding_model
+        result.embedding_model == original_vector_db.embedding_model
     )  # Original values preserved
 
 
@@ -179,36 +172,35 @@ async def test_get_all_objects(config):
     await cached_registry.initialize()
 
     # Create multiple test banks
-    test_banks = [
-        VectorMemoryBank(
-            identifier=f"test_bank_{i}",
+    test_vector_dbs = [
+        VectorDB(
+            identifier=f"test_vector_db_{i}",
             embedding_model="all-MiniLM-L6-v2",
-            chunk_size_in_tokens=256,
-            overlap_size_in_tokens=32,
-            provider_resource_id=f"test_bank_{i}",
+            embedding_dimension=384,
+            provider_resource_id=f"test_vector_db_{i}",
             provider_id=f"provider_{i}",
         )
         for i in range(3)
     ]
 
-    # Register all banks
-    for bank in test_banks:
-        await cached_registry.register(bank)
+    # Register all vector_dbs
+    for vector_db in test_vector_dbs:
+        await cached_registry.register(vector_db)
 
     # Test get_all retrieval
     all_results = await cached_registry.get_all()
     assert len(all_results) == 3
 
-    # Verify each bank was stored correctly
-    for original_bank in test_banks:
-        matching_banks = [
-            b for b in all_results if b.identifier == original_bank.identifier
+    # Verify each vector_db was stored correctly
+    for original_vector_db in test_vector_dbs:
+        matching_vector_dbs = [
+            v for v in all_results if v.identifier == original_vector_db.identifier
         ]
-        assert len(matching_banks) == 1
-        stored_bank = matching_banks[0]
-        assert stored_bank.embedding_model == original_bank.embedding_model
-        assert stored_bank.provider_id == original_bank.provider_id
-        assert stored_bank.chunk_size_in_tokens == original_bank.chunk_size_in_tokens
+        assert len(matching_vector_dbs) == 1
+        stored_vector_db = matching_vector_dbs[0]
+        assert stored_vector_db.embedding_model == original_vector_db.embedding_model
+        assert stored_vector_db.provider_id == original_vector_db.provider_id
         assert (
-            stored_bank.overlap_size_in_tokens == original_bank.overlap_size_in_tokens
+            stored_vector_db.embedding_dimension
+            == original_vector_db.embedding_dimension
         )
diff --git a/llama_stack/distribution/ui/modules/api.py b/llama_stack/distribution/ui/modules/api.py
index 70c7a0898..7d3367ba5 100644
--- a/llama_stack/distribution/ui/modules/api.py
+++ b/llama_stack/distribution/ui/modules/api.py
@@ -18,6 +18,7 @@ class LlamaStackApi:
             provider_data={
                 "fireworks_api_key": os.environ.get("FIREWORKS_API_KEY", ""),
                 "together_api_key": os.environ.get("TOGETHER_API_KEY", ""),
+                "sambanova_api_key": os.environ.get("SAMBANOVA_API_KEY", ""),
                 "openai_api_key": os.environ.get("OPENAI_API_KEY", ""),
             },
         )
diff --git a/llama_stack/distribution/ui/page/distribution/memory_banks.py b/llama_stack/distribution/ui/page/distribution/memory_banks.py
deleted file mode 100644
index f28010bf2..000000000
--- a/llama_stack/distribution/ui/page/distribution/memory_banks.py
+++ /dev/null
@@ -1,23 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the terms described in the LICENSE file in
-# the root directory of this source tree.
-
-import streamlit as st
-from modules.api import llama_stack_api
-
-
-def memory_banks():
-    st.header("Memory Banks")
-    memory_banks_info = {
-        m.identifier: m.to_dict() for m in llama_stack_api.client.memory_banks.list()
-    }
-
-    if len(memory_banks_info) > 0:
-        selected_memory_bank = st.selectbox(
-            "Select a memory bank", list(memory_banks_info.keys())
-        )
-        st.json(memory_banks_info[selected_memory_bank])
-    else:
-        st.info("No memory banks found")
diff --git a/llama_stack/distribution/ui/page/distribution/resources.py b/llama_stack/distribution/ui/page/distribution/resources.py
index 6b3ea0e3a..38d494570 100644
--- a/llama_stack/distribution/ui/page/distribution/resources.py
+++ b/llama_stack/distribution/ui/page/distribution/resources.py
@@ -6,10 +6,10 @@
 
 from page.distribution.datasets import datasets
 from page.distribution.eval_tasks import eval_tasks
-from page.distribution.memory_banks import memory_banks
 from page.distribution.models import models
 from page.distribution.scoring_functions import scoring_functions
 from page.distribution.shields import shields
+from page.distribution.vector_dbs import vector_dbs
 
 from streamlit_option_menu import option_menu
 
@@ -17,7 +17,7 @@ from streamlit_option_menu import option_menu
 def resources_page():
     options = [
         "Models",
-        "Memory Banks",
+        "Vector Databases",
         "Shields",
         "Scoring Functions",
         "Datasets",
@@ -37,8 +37,8 @@ def resources_page():
     )
     if selected_resource == "Eval Tasks":
         eval_tasks()
-    elif selected_resource == "Memory Banks":
-        memory_banks()
+    elif selected_resource == "Vector Databases":
+        vector_dbs()
     elif selected_resource == "Datasets":
         datasets()
     elif selected_resource == "Models":
diff --git a/llama_stack/distribution/ui/page/distribution/vector_dbs.py b/llama_stack/distribution/ui/page/distribution/vector_dbs.py
new file mode 100644
index 000000000..9afa6de1f
--- /dev/null
+++ b/llama_stack/distribution/ui/page/distribution/vector_dbs.py
@@ -0,0 +1,23 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+import streamlit as st
+from modules.api import llama_stack_api
+
+
+def vector_dbs():
+    st.header("Vector Databases")
+    vector_dbs_info = {
+        v.identifier: v.to_dict() for v in llama_stack_api.client.vector_dbs.list()
+    }
+
+    if len(vector_dbs_info) > 0:
+        selected_vector_db = st.selectbox(
+            "Select a vector database", list(vector_dbs_info.keys())
+        )
+        st.json(vector_dbs_info[selected_vector_db])
+    else:
+        st.info("No vector databases found")
diff --git a/llama_stack/distribution/ui/page/playground/rag.py b/llama_stack/distribution/ui/page/playground/rag.py
index 11b05718d..49991dc54 100644
--- a/llama_stack/distribution/ui/page/playground/rag.py
+++ b/llama_stack/distribution/ui/page/playground/rag.py
@@ -29,12 +29,12 @@ def rag_chat_page():
         if uploaded_files:
             st.success(f"Successfully uploaded {len(uploaded_files)} files")
             # Add memory bank name input field
-            memory_bank_name = st.text_input(
-                "Memory Bank Name",
-                value="rag_bank",
-                help="Enter a unique identifier for this memory bank",
+            vector_db_name = st.text_input(
+                "Vector Database Name",
+                value="rag_vector_db",
+                help="Enter a unique identifier for this vector database",
             )
-            if st.button("Create Memory Bank"):
+            if st.button("Create Vector Database"):
                 documents = [
                     Document(
                         document_id=uploaded_file.name,
@@ -44,37 +44,33 @@ def rag_chat_page():
                 ]
 
                 providers = llama_stack_api.client.providers.list()
-                memory_provider = None
+                vector_io_provider = None
 
                 for x in providers:
-                    if x.api == "memory":
-                        memory_provider = x.provider_id
+                    if x.api == "vector_io":
+                        vector_io_provider = x.provider_id
 
-                llama_stack_api.client.memory_banks.register(
-                    memory_bank_id=memory_bank_name,  # Use the user-provided name
-                    params={
-                        "memory_bank_type": "vector",
-                        "embedding_model": "all-MiniLM-L6-v2",
-                        "chunk_size_in_tokens": 512,
-                        "overlap_size_in_tokens": 64,
-                    },
-                    provider_id=memory_provider,
+                llama_stack_api.client.vector_dbs.register(
+                    vector_db_id=vector_db_name,  # Use the user-provided name
+                    embedding_dimension=384,
+                    embedding_model="all-MiniLM-L6-v2",
+                    provider_id=vector_io_provider,
                 )
 
-                # insert documents using the custom bank name
-                llama_stack_api.client.memory.insert(
-                    bank_id=memory_bank_name,  # Use the user-provided name
+                # insert documents using the custom vector db name
+                llama_stack_api.client.tool_runtime.rag_tool.insert(
+                    vector_db_id=vector_db_name,  # Use the user-provided name
                     documents=documents,
                 )
-                st.success("Memory bank created successfully!")
+                st.success("Vector database created successfully!")
 
         st.subheader("Configure Agent")
         # select memory banks
-        memory_banks = llama_stack_api.client.memory_banks.list()
-        memory_banks = [bank.identifier for bank in memory_banks]
-        selected_memory_banks = st.multiselect(
-            "Select Memory Banks",
-            memory_banks,
+        vector_dbs = llama_stack_api.client.vector_dbs.list()
+        vector_dbs = [vector_db.identifier for vector_db in vector_dbs]
+        selected_vector_dbs = st.multiselect(
+            "Select Vector Databases",
+            vector_dbs,
         )
 
         available_models = llama_stack_api.client.models.list()
@@ -139,16 +135,16 @@ def rag_chat_page():
         },
         toolgroups=[
             dict(
-                name="builtin::memory",
+                name="builtin::rag",
                 args={
-                    "memory_bank_ids": [bank_id for bank_id in selected_memory_banks],
+                    "vector_db_ids": [
+                        vector_db_id for vector_db_id in selected_vector_dbs
+                    ],
                 },
             )
         ],
         tool_choice="auto",
         tool_prompt_format="json",
-        input_shields=[],
-        output_shields=[],
         enable_session_persistence=False,
     )
 
diff --git a/llama_stack/providers/datatypes.py b/llama_stack/providers/datatypes.py
index ce0c9f52e..d0c448f8c 100644
--- a/llama_stack/providers/datatypes.py
+++ b/llama_stack/providers/datatypes.py
@@ -4,7 +4,6 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-from enum import Enum
 from typing import Any, List, Optional, Protocol
 from urllib.parse import urlparse
 
@@ -12,38 +11,14 @@ from llama_models.schema_utils import json_schema_type
 from pydantic import BaseModel, Field
 
 from llama_stack.apis.datasets import Dataset
+
+from llama_stack.apis.datatypes import Api
 from llama_stack.apis.eval_tasks import EvalTask
-from llama_stack.apis.memory_banks.memory_banks import MemoryBank
 from llama_stack.apis.models import Model
 from llama_stack.apis.scoring_functions import ScoringFn
 from llama_stack.apis.shields import Shield
 from llama_stack.apis.tools import Tool
-
-
-@json_schema_type
-class Api(Enum):
-    inference = "inference"
-    safety = "safety"
-    agents = "agents"
-    memory = "memory"
-    datasetio = "datasetio"
-    scoring = "scoring"
-    eval = "eval"
-    post_training = "post_training"
-    tool_runtime = "tool_runtime"
-
-    telemetry = "telemetry"
-
-    models = "models"
-    shields = "shields"
-    memory_banks = "memory_banks"
-    datasets = "datasets"
-    scoring_functions = "scoring_functions"
-    eval_tasks = "eval_tasks"
-    tool_groups = "tool_groups"
-
-    # built-in API
-    inspect = "inspect"
+from llama_stack.apis.vector_dbs import VectorDB
 
 
 class ModelsProtocolPrivate(Protocol):
@@ -56,10 +31,10 @@ class ShieldsProtocolPrivate(Protocol):
     async def register_shield(self, shield: Shield) -> None: ...
 
 
-class MemoryBanksProtocolPrivate(Protocol):
-    async def register_memory_bank(self, memory_bank: MemoryBank) -> None: ...
+class VectorDBsProtocolPrivate(Protocol):
+    async def register_vector_db(self, vector_db: VectorDB) -> None: ...
 
-    async def unregister_memory_bank(self, memory_bank_id: str) -> None: ...
+    async def unregister_vector_db(self, vector_db_id: str) -> None: ...
 
 
 class DatasetsProtocolPrivate(Protocol):
@@ -96,6 +71,9 @@ class ProviderSpec(BaseModel):
         default_factory=list,
         description="Higher-level API surfaces may depend on other providers to provide their functionality",
     )
+    optional_api_dependencies: List[Api] = Field(
+        default_factory=list,
+    )
     deprecation_warning: Optional[str] = Field(
         default=None,
         description="If this provider is deprecated, specify the warning message here",
@@ -147,11 +125,11 @@ class InlineProviderSpec(ProviderSpec):
         default_factory=list,
         description="The pip dependencies needed for this implementation",
     )
-    docker_image: Optional[str] = Field(
+    container_image: Optional[str] = Field(
         default=None,
         description="""
-The docker image to use for this implementation. If one is provided, pip_packages will be ignored.
-If a provider depends on other providers, the dependencies MUST NOT specify a docker image.
+The container image to use for this implementation. If one is provided, pip_packages will be ignored.
+If a provider depends on other providers, the dependencies MUST NOT specify a container image.
 """,
     )
     module: str = Field(
@@ -194,7 +172,7 @@ API responses, specify the adapter here.
     )
 
     @property
-    def docker_image(self) -> Optional[str]:
+    def container_image(self) -> Optional[str]:
         return None
 
     @property
diff --git a/llama_stack/providers/inline/agents/meta_reference/__init__.py b/llama_stack/providers/inline/agents/meta_reference/__init__.py
index 50f61fb42..de34b8d2c 100644
--- a/llama_stack/providers/inline/agents/meta_reference/__init__.py
+++ b/llama_stack/providers/inline/agents/meta_reference/__init__.py
@@ -19,9 +19,8 @@ async def get_provider_impl(
     impl = MetaReferenceAgentsImpl(
         config,
         deps[Api.inference],
-        deps[Api.memory],
+        deps[Api.vector_io],
         deps[Api.safety],
-        deps[Api.memory_banks],
         deps[Api.tool_runtime],
         deps[Api.tool_groups],
     )
diff --git a/llama_stack/providers/inline/agents/meta_reference/agent_instance.py b/llama_stack/providers/inline/agents/meta_reference/agent_instance.py
index 2ebc7ded1..32801e514 100644
--- a/llama_stack/providers/inline/agents/meta_reference/agent_instance.py
+++ b/llama_stack/providers/inline/agents/meta_reference/agent_instance.py
@@ -18,6 +18,7 @@ from urllib.parse import urlparse
 
 import httpx
 from llama_models.llama3.api.datatypes import BuiltinTool, ToolCall, ToolParamDefinition
+from pydantic import TypeAdapter
 
 from llama_stack.apis.agents import (
     AgentConfig,
@@ -59,13 +60,12 @@ from llama_stack.apis.inference import (
     ToolResponseMessage,
     UserMessage,
 )
-from llama_stack.apis.memory import Memory, MemoryBankDocument
-from llama_stack.apis.memory_banks import MemoryBanks, VectorMemoryBankParams
 from llama_stack.apis.safety import Safety
-from llama_stack.apis.tools import ToolGroups, ToolRuntime
+from llama_stack.apis.tools import RAGDocument, RAGQueryConfig, ToolGroups, ToolRuntime
+from llama_stack.apis.vector_io import VectorIO
 from llama_stack.providers.utils.kvstore import KVStore
+from llama_stack.providers.utils.memory.vector_store import concat_interleaved_content
 from llama_stack.providers.utils.telemetry import tracing
-
 from .persistence import AgentPersistence
 from .safety import SafetyException, ShieldRunnerMixin
 
@@ -79,9 +79,9 @@ def make_random_string(length: int = 8):
 
 
 TOOLS_ATTACHMENT_KEY_REGEX = re.compile(r"__tools_attachment__=(\{.*?\})")
-MEMORY_QUERY_TOOL = "query_memory"
+MEMORY_QUERY_TOOL = "query_from_memory"
 WEB_SEARCH_TOOL = "web_search"
-MEMORY_GROUP = "builtin::memory"
+RAG_TOOL_GROUP = "builtin::rag"
 
 
 class ChatAgent(ShieldRunnerMixin):
@@ -91,20 +91,18 @@ class ChatAgent(ShieldRunnerMixin):
         agent_config: AgentConfig,
         tempdir: str,
         inference_api: Inference,
-        memory_api: Memory,
-        memory_banks_api: MemoryBanks,
         safety_api: Safety,
         tool_runtime_api: ToolRuntime,
         tool_groups_api: ToolGroups,
+        vector_io_api: VectorIO,
         persistence_store: KVStore,
     ):
         self.agent_id = agent_id
         self.agent_config = agent_config
         self.tempdir = tempdir
         self.inference_api = inference_api
-        self.memory_api = memory_api
-        self.memory_banks_api = memory_banks_api
         self.safety_api = safety_api
+        self.vector_io_api = vector_io_api
         self.storage = AgentPersistence(agent_id, persistence_store)
         self.tool_runtime_api = tool_runtime_api
         self.tool_groups_api = tool_groups_api
@@ -370,24 +368,30 @@ class ChatAgent(ShieldRunnerMixin):
         documents: Optional[List[Document]] = None,
         toolgroups_for_turn: Optional[List[AgentToolGroup]] = None,
     ) -> AsyncGenerator:
+        # TODO: simplify all of this code, it can be simpler
         toolgroup_args = {}
+        toolgroups = set()
         for toolgroup in self.agent_config.toolgroups:
             if isinstance(toolgroup, AgentToolGroupWithArgs):
+                toolgroups.add(toolgroup.name)
                 toolgroup_args[toolgroup.name] = toolgroup.args
+            else:
+                toolgroups.add(toolgroup)
         if toolgroups_for_turn:
             for toolgroup in toolgroups_for_turn:
                 if isinstance(toolgroup, AgentToolGroupWithArgs):
+                    toolgroups.add(toolgroup.name)
                     toolgroup_args[toolgroup.name] = toolgroup.args
+                else:
+                    toolgroups.add(toolgroup)
 
         tool_defs, tool_to_group = await self._get_tool_defs(toolgroups_for_turn)
         if documents:
             await self.handle_documents(
                 session_id, documents, input_messages, tool_defs
             )
-        if MEMORY_QUERY_TOOL in tool_defs and len(input_messages) > 0:
-            memory_tool_group = tool_to_group.get(MEMORY_QUERY_TOOL, None)
-            if memory_tool_group is None:
-                raise ValueError(f"Memory tool group not found for {MEMORY_QUERY_TOOL}")
+
+        if RAG_TOOL_GROUP in toolgroups and len(input_messages) > 0:
             with tracing.span(MEMORY_QUERY_TOOL) as span:
                 step_id = str(uuid.uuid4())
                 yield AgentTurnResponseStreamChunk(
@@ -398,17 +402,24 @@ class ChatAgent(ShieldRunnerMixin):
                         )
                     )
                 )
-                query_args = {
-                    "messages": [msg.content for msg in input_messages],
-                    **toolgroup_args.get(memory_tool_group, {}),
-                }
+
+                args = toolgroup_args.get(RAG_TOOL_GROUP, {})
+                vector_db_ids = args.get("vector_db_ids", [])
+                query_config = args.get("query_config")
+                if query_config:
+                    query_config = TypeAdapter(RAGQueryConfig).validate_python(
+                        query_config
+                    )
+                else:
+                    # handle someone passing an empty dict
+                    query_config = RAGQueryConfig()
 
                 session_info = await self.storage.get_session_info(session_id)
+
                 # if the session has a memory bank id, let the memory tool use it
-                if session_info.memory_bank_id:
-                    if "memory_bank_ids" not in query_args:
-                        query_args["memory_bank_ids"] = []
-                    query_args["memory_bank_ids"].append(session_info.memory_bank_id)
+                if session_info.vector_db_id:
+                    vector_db_ids.append(session_info.vector_db_id)
+
                 yield AgentTurnResponseStreamChunk(
                     event=AgentTurnResponseEvent(
                         payload=AgentTurnResponseStepProgressPayload(
@@ -416,7 +427,7 @@ class ChatAgent(ShieldRunnerMixin):
                             step_id=step_id,
                             delta=ToolCallDelta(
                                 parse_status=ToolCallParseStatus.succeeded,
-                                content=ToolCall(
+                                tool_call=ToolCall(
                                     call_id="",
                                     tool_name=MEMORY_QUERY_TOOL,
                                     arguments={},
@@ -425,10 +436,14 @@ class ChatAgent(ShieldRunnerMixin):
                         )
                     )
                 )
-                result = await self.tool_runtime_api.invoke_tool(
-                    tool_name=MEMORY_QUERY_TOOL,
-                    args=query_args,
+                result = await self.tool_runtime_api.rag_tool.query(
+                    content=concat_interleaved_content(
+                        [msg.content for msg in input_messages]
+                    ),
+                    vector_db_ids=vector_db_ids,
+                    query_config=query_config,
                 )
+                retrieved_context = result.content
 
                 yield AgentTurnResponseStreamChunk(
                     event=AgentTurnResponseEvent(
@@ -449,7 +464,7 @@ class ChatAgent(ShieldRunnerMixin):
                                     ToolResponse(
                                         call_id="",
                                         tool_name=MEMORY_QUERY_TOOL,
-                                        content=result.content,
+                                        content=retrieved_context or [],
                                     )
                                 ],
                             ),
@@ -459,13 +474,11 @@ class ChatAgent(ShieldRunnerMixin):
                 span.set_attribute(
                     "input", [m.model_dump_json() for m in input_messages]
                 )
-                span.set_attribute("output", result.content)
-                span.set_attribute("error_code", result.error_code)
-                span.set_attribute("error_message", result.error_message)
+                span.set_attribute("output", retrieved_context)
                 span.set_attribute("tool_name", MEMORY_QUERY_TOOL)
-                if result.error_code == 0:
+                if retrieved_context:
                     last_message = input_messages[-1]
-                    last_message.context = result.content
+                    last_message.context = retrieved_context
 
         output_attachments = []
 
@@ -496,7 +509,7 @@ class ChatAgent(ShieldRunnerMixin):
                     tools=[
                         tool
                         for tool in tool_defs.values()
-                        if tool_to_group.get(tool.tool_name, None) != MEMORY_GROUP
+                        if tool_to_group.get(tool.tool_name, None) != RAG_TOOL_GROUP
                     ],
                     tool_prompt_format=self.agent_config.tool_prompt_format,
                     stream=True,
@@ -512,7 +525,7 @@ class ChatAgent(ShieldRunnerMixin):
                     delta = event.delta
                     if delta.type == "tool_call":
                         if delta.parse_status == ToolCallParseStatus.succeeded:
-                            tool_calls.append(delta.content)
+                            tool_calls.append(delta.tool_call)
                         if stream:
                             yield AgentTurnResponseStreamChunk(
                                 event=AgentTurnResponseEvent(
@@ -626,7 +639,7 @@ class ChatAgent(ShieldRunnerMixin):
                             tool_call=tool_call,
                             delta=ToolCallDelta(
                                 parse_status=ToolCallParseStatus.in_progress,
-                                content=tool_call,
+                                tool_call=tool_call,
                             ),
                         )
                     )
@@ -743,7 +756,7 @@ class ChatAgent(ShieldRunnerMixin):
             for tool_def in tools.data:
                 if (
                     toolgroup_name.startswith("builtin")
-                    and toolgroup_name != MEMORY_GROUP
+                    and toolgroup_name != RAG_TOOL_GROUP
                 ):
                     tool_name = tool_def.identifier
                     built_in_type = BuiltinTool.brave_search
@@ -816,7 +829,7 @@ class ChatAgent(ShieldRunnerMixin):
             msg = await attachment_message(self.tempdir, url_items)
             input_messages.append(msg)
             # Since memory is present, add all the data to the memory bank
-            await self.add_to_session_memory_bank(session_id, documents)
+            await self.add_to_session_vector_db(session_id, documents)
         elif code_interpreter_tool:
             # if only code_interpreter is available, we download the URLs to a tempdir
             # and attach the path to them as a message to inference with the
@@ -825,7 +838,7 @@ class ChatAgent(ShieldRunnerMixin):
             input_messages.append(msg)
         elif memory_tool:
             # if only memory is available, we load the data from the URLs and content items to the memory bank
-            await self.add_to_session_memory_bank(session_id, documents)
+            await self.add_to_session_vector_db(session_id, documents)
         else:
             # if no memory or code_interpreter tool is available,
             # we try to load the data from the URLs and content items as a message to inference
@@ -835,32 +848,33 @@ class ChatAgent(ShieldRunnerMixin):
                 + await load_data_from_urls(url_items)
             )
 
-    async def _ensure_memory_bank(self, session_id: str) -> str:
+    async def _ensure_vector_db(self, session_id: str) -> str:
         session_info = await self.storage.get_session_info(session_id)
         if session_info is None:
             raise ValueError(f"Session {session_id} not found")
 
-        if session_info.memory_bank_id is None:
-            bank_id = f"memory_bank_{session_id}"
-            await self.memory_banks_api.register_memory_bank(
-                memory_bank_id=bank_id,
-                params=VectorMemoryBankParams(
-                    embedding_model="all-MiniLM-L6-v2",
-                    chunk_size_in_tokens=512,
-                ),
+        if session_info.vector_db_id is None:
+            vector_db_id = f"vector_db_{session_id}"
+
+            # TODO: the semantic for registration is definitely not "creation"
+            # so we need to fix it if we expect the agent to create a new vector db
+            # for each session
+            await self.vector_io_api.register_vector_db(
+                vector_db_id=vector_db_id,
+                embedding_model="all-MiniLM-L6-v2",
             )
-            await self.storage.add_memory_bank_to_session(session_id, bank_id)
+            await self.storage.add_vector_db_to_session(session_id, vector_db_id)
         else:
-            bank_id = session_info.memory_bank_id
+            vector_db_id = session_info.vector_db_id
 
-        return bank_id
+        return vector_db_id
 
-    async def add_to_session_memory_bank(
+    async def add_to_session_vector_db(
         self, session_id: str, data: List[Document]
     ) -> None:
-        bank_id = await self._ensure_memory_bank(session_id)
+        vector_db_id = await self._ensure_vector_db(session_id)
         documents = [
-            MemoryBankDocument(
+            RAGDocument(
                 document_id=str(uuid.uuid4()),
                 content=a.content,
                 mime_type=a.mime_type,
@@ -868,9 +882,10 @@ class ChatAgent(ShieldRunnerMixin):
             )
             for a in data
         ]
-        await self.memory_api.insert_documents(
-            bank_id=bank_id,
+        await self.tool_runtime_api.rag_tool.insert(
             documents=documents,
+            vector_db_id=vector_db_id,
+            chunk_size_in_tokens=512,
         )
 
 
@@ -955,7 +970,7 @@ async def execute_tool_call_maybe(
 
     result = await tool_runtime_api.invoke_tool(
         tool_name=name,
-        args=dict(
+        kwargs=dict(
             session_id=session_id,
             **tool_call_args,
         ),
diff --git a/llama_stack/providers/inline/agents/meta_reference/agents.py b/llama_stack/providers/inline/agents/meta_reference/agents.py
index d22ef82ab..b1844f4d0 100644
--- a/llama_stack/providers/inline/agents/meta_reference/agents.py
+++ b/llama_stack/providers/inline/agents/meta_reference/agents.py
@@ -26,10 +26,9 @@ from llama_stack.apis.agents import (
     Turn,
 )
 from llama_stack.apis.inference import Inference, ToolResponseMessage, UserMessage
-from llama_stack.apis.memory import Memory
-from llama_stack.apis.memory_banks import MemoryBanks
 from llama_stack.apis.safety import Safety
 from llama_stack.apis.tools import ToolGroups, ToolRuntime
+from llama_stack.apis.vector_io import VectorIO
 from llama_stack.providers.utils.kvstore import InmemoryKVStoreImpl, kvstore_impl
 
 from .agent_instance import ChatAgent
@@ -44,17 +43,15 @@ class MetaReferenceAgentsImpl(Agents):
         self,
         config: MetaReferenceAgentsImplConfig,
         inference_api: Inference,
-        memory_api: Memory,
+        vector_io_api: VectorIO,
         safety_api: Safety,
-        memory_banks_api: MemoryBanks,
         tool_runtime_api: ToolRuntime,
         tool_groups_api: ToolGroups,
     ):
         self.config = config
         self.inference_api = inference_api
-        self.memory_api = memory_api
+        self.vector_io_api = vector_io_api
         self.safety_api = safety_api
-        self.memory_banks_api = memory_banks_api
         self.tool_runtime_api = tool_runtime_api
         self.tool_groups_api = tool_groups_api
 
@@ -114,8 +111,7 @@ class MetaReferenceAgentsImpl(Agents):
             tempdir=self.tempdir,
             inference_api=self.inference_api,
             safety_api=self.safety_api,
-            memory_api=self.memory_api,
-            memory_banks_api=self.memory_banks_api,
+            vector_io_api=self.vector_io_api,
             tool_runtime_api=self.tool_runtime_api,
             tool_groups_api=self.tool_groups_api,
             persistence_store=(
diff --git a/llama_stack/providers/inline/agents/meta_reference/persistence.py b/llama_stack/providers/inline/agents/meta_reference/persistence.py
index 58b69858b..4b8ad6d4a 100644
--- a/llama_stack/providers/inline/agents/meta_reference/persistence.py
+++ b/llama_stack/providers/inline/agents/meta_reference/persistence.py
@@ -21,7 +21,7 @@ log = logging.getLogger(__name__)
 class AgentSessionInfo(BaseModel):
     session_id: str
     session_name: str
-    memory_bank_id: Optional[str] = None
+    vector_db_id: Optional[str] = None
     started_at: datetime
 
 
@@ -52,12 +52,12 @@ class AgentPersistence:
 
         return AgentSessionInfo(**json.loads(value))
 
-    async def add_memory_bank_to_session(self, session_id: str, bank_id: str):
+    async def add_vector_db_to_session(self, session_id: str, vector_db_id: str):
         session_info = await self.get_session_info(session_id)
         if session_info is None:
             raise ValueError(f"Session {session_id} not found")
 
-        session_info.memory_bank_id = bank_id
+        session_info.vector_db_id = vector_db_id
         await self.kvstore.set(
             key=f"session:{self.agent_id}:{session_id}",
             value=session_info.model_dump_json(),
diff --git a/llama_stack/providers/inline/agents/meta_reference/tests/test_chat_agent.py b/llama_stack/providers/inline/agents/meta_reference/tests/test_chat_agent.py
index a7e6efc8c..09fccd3c6 100644
--- a/llama_stack/providers/inline/agents/meta_reference/tests/test_chat_agent.py
+++ b/llama_stack/providers/inline/agents/meta_reference/tests/test_chat_agent.py
@@ -29,10 +29,9 @@ from llama_stack.apis.inference import (
     SamplingParams,
     ToolChoice,
     ToolDefinition,
+    ToolPromptFormat,
     UserMessage,
 )
-from llama_stack.apis.memory import MemoryBank
-from llama_stack.apis.memory_banks import BankParams, VectorMemoryBank
 from llama_stack.apis.safety import RunShieldResponse
 from llama_stack.apis.tools import (
     Tool,
@@ -40,8 +39,9 @@ from llama_stack.apis.tools import (
     ToolGroup,
     ToolHost,
     ToolInvocationResult,
-    ToolPromptFormat,
 )
+from llama_stack.apis.vector_io import QueryChunksResponse
+
 from llama_stack.providers.inline.agents.meta_reference.agent_instance import (
     MEMORY_QUERY_TOOL,
 )
@@ -110,68 +110,22 @@ class MockSafetyAPI:
         return RunShieldResponse(violation=None)
 
 
-class MockMemoryAPI:
+class MockVectorIOAPI:
     def __init__(self):
-        self.memory_banks = {}
-        self.documents = {}
+        self.chunks = {}
 
-    async def create_memory_bank(self, name, config, url=None):
-        bank_id = f"bank_{len(self.memory_banks)}"
-        bank = MemoryBank(bank_id, name, config, url)
-        self.memory_banks[bank_id] = bank
-        self.documents[bank_id] = {}
-        return bank
+    async def insert_chunks(self, vector_db_id, chunks, ttl_seconds=None):
+        for chunk in chunks:
+            metadata = chunk.metadata
+            self.chunks[vector_db_id][metadata["document_id"]] = chunk
 
-    async def list_memory_banks(self):
-        return list(self.memory_banks.values())
+    async def query_chunks(self, vector_db_id, query, params=None):
+        if vector_db_id not in self.chunks:
+            raise ValueError(f"Bank {vector_db_id} not found")
 
-    async def get_memory_bank(self, bank_id):
-        return self.memory_banks.get(bank_id)
-
-    async def drop_memory_bank(self, bank_id):
-        if bank_id in self.memory_banks:
-            del self.memory_banks[bank_id]
-            del self.documents[bank_id]
-        return bank_id
-
-    async def insert_documents(self, bank_id, documents, ttl_seconds=None):
-        if bank_id not in self.documents:
-            raise ValueError(f"Bank {bank_id} not found")
-        for doc in documents:
-            self.documents[bank_id][doc.document_id] = doc
-
-    async def update_documents(self, bank_id, documents):
-        if bank_id not in self.documents:
-            raise ValueError(f"Bank {bank_id} not found")
-        for doc in documents:
-            if doc.document_id in self.documents[bank_id]:
-                self.documents[bank_id][doc.document_id] = doc
-
-    async def query_documents(self, bank_id, query, params=None):
-        if bank_id not in self.documents:
-            raise ValueError(f"Bank {bank_id} not found")
-        # Simple mock implementation: return all documents
-        chunks = [
-            {"content": doc.content, "token_count": 10, "document_id": doc.document_id}
-            for doc in self.documents[bank_id].values()
-        ]
+        chunks = list(self.chunks[vector_db_id].values())
         scores = [1.0] * len(chunks)
-        return {"chunks": chunks, "scores": scores}
-
-    async def get_documents(self, bank_id, document_ids):
-        if bank_id not in self.documents:
-            raise ValueError(f"Bank {bank_id} not found")
-        return [
-            self.documents[bank_id][doc_id]
-            for doc_id in document_ids
-            if doc_id in self.documents[bank_id]
-        ]
-
-    async def delete_documents(self, bank_id, document_ids):
-        if bank_id not in self.documents:
-            raise ValueError(f"Bank {bank_id} not found")
-        for doc_id in document_ids:
-            self.documents[bank_id].pop(doc_id, None)
+        return QueryChunksResponse(chunks=chunks, scores=scores)
 
 
 class MockToolGroupsAPI:
@@ -198,7 +152,7 @@ class MockToolGroupsAPI:
                     toolgroup_id=MEMORY_TOOLGROUP,
                     tool_host=ToolHost.client,
                     description="Mock tool",
-                    provider_id="builtin::memory",
+                    provider_id="builtin::rag",
                     parameters=[],
                 )
             ]
@@ -241,31 +195,6 @@ class MockToolRuntimeAPI:
         return ToolInvocationResult(content={"result": "Mock tool result"})
 
 
-class MockMemoryBanksAPI:
-    async def list_memory_banks(self) -> List[MemoryBank]:
-        return []
-
-    async def get_memory_bank(self, memory_bank_id: str) -> Optional[MemoryBank]:
-        return None
-
-    async def register_memory_bank(
-        self,
-        memory_bank_id: str,
-        params: BankParams,
-        provider_id: Optional[str] = None,
-        provider_memory_bank_id: Optional[str] = None,
-    ) -> MemoryBank:
-        return VectorMemoryBank(
-            identifier=memory_bank_id,
-            provider_resource_id=provider_memory_bank_id or memory_bank_id,
-            embedding_model="mock_model",
-            chunk_size_in_tokens=512,
-        )
-
-    async def unregister_memory_bank(self, memory_bank_id: str) -> None:
-        pass
-
-
 @pytest.fixture
 def mock_inference_api():
     return MockInferenceAPI()
@@ -277,8 +206,8 @@ def mock_safety_api():
 
 
 @pytest.fixture
-def mock_memory_api():
-    return MockMemoryAPI()
+def mock_vector_io_api():
+    return MockVectorIOAPI()
 
 
 @pytest.fixture
@@ -291,17 +220,11 @@ def mock_tool_runtime_api():
     return MockToolRuntimeAPI()
 
 
-@pytest.fixture
-def mock_memory_banks_api():
-    return MockMemoryBanksAPI()
-
-
 @pytest.fixture
 async def get_agents_impl(
     mock_inference_api,
     mock_safety_api,
-    mock_memory_api,
-    mock_memory_banks_api,
+    mock_vector_io_api,
     mock_tool_runtime_api,
     mock_tool_groups_api,
 ):
@@ -314,8 +237,7 @@ async def get_agents_impl(
         ),
         inference_api=mock_inference_api,
         safety_api=mock_safety_api,
-        memory_api=mock_memory_api,
-        memory_banks_api=mock_memory_banks_api,
+        vector_io_api=mock_vector_io_api,
         tool_runtime_api=mock_tool_runtime_api,
         tool_groups_api=mock_tool_groups_api,
     )
@@ -338,7 +260,7 @@ async def get_chat_agent(get_agents_impl):
     return await impl.get_agent(response.agent_id)
 
 
-MEMORY_TOOLGROUP = "builtin::memory"
+MEMORY_TOOLGROUP = "builtin::rag"
 CODE_INTERPRETER_TOOLGROUP = "builtin::code_interpreter"
 
 
@@ -484,7 +406,7 @@ async def test_chat_agent_tools(
             toolgroups_for_turn=[
                 AgentToolGroupWithArgs(
                     name=MEMORY_TOOLGROUP,
-                    args={"memory_banks": ["test_memory_bank"]},
+                    args={"vector_dbs": ["test_vector_db"]},
                 )
             ]
         )
diff --git a/llama_stack/providers/inline/inference/meta_reference/inference.py b/llama_stack/providers/inline/inference/meta_reference/inference.py
index 31ad6fa28..73962ca7f 100644
--- a/llama_stack/providers/inline/inference/meta_reference/inference.py
+++ b/llama_stack/providers/inline/inference/meta_reference/inference.py
@@ -377,7 +377,7 @@ class MetaReferenceInferenceImpl(
                         event=ChatCompletionResponseEvent(
                             event_type=ChatCompletionResponseEventType.progress,
                             delta=ToolCallDelta(
-                                content="",
+                                tool_call="",
                                 parse_status=ToolCallParseStatus.started,
                             ),
                         )
@@ -395,7 +395,7 @@ class MetaReferenceInferenceImpl(
 
                 if ipython:
                     delta = ToolCallDelta(
-                        content=text,
+                        tool_call=text,
                         parse_status=ToolCallParseStatus.in_progress,
                     )
                 else:
@@ -434,7 +434,7 @@ class MetaReferenceInferenceImpl(
                     event=ChatCompletionResponseEvent(
                         event_type=ChatCompletionResponseEventType.progress,
                         delta=ToolCallDelta(
-                            content="",
+                            tool_call="",
                             parse_status=ToolCallParseStatus.failed,
                         ),
                         stop_reason=stop_reason,
@@ -446,7 +446,7 @@ class MetaReferenceInferenceImpl(
                     event=ChatCompletionResponseEvent(
                         event_type=ChatCompletionResponseEventType.progress,
                         delta=ToolCallDelta(
-                            content=tool_call,
+                            tool_call=tool_call,
                             parse_status=ToolCallParseStatus.succeeded,
                         ),
                         stop_reason=stop_reason,
diff --git a/llama_stack/providers/inline/inference/meta_reference/parallel_utils.py b/llama_stack/providers/inline/inference/meta_reference/parallel_utils.py
index 36720612c..ced712257 100644
--- a/llama_stack/providers/inline/inference/meta_reference/parallel_utils.py
+++ b/llama_stack/providers/inline/inference/meta_reference/parallel_utils.py
@@ -357,8 +357,8 @@ class ModelParallelProcessGroup:
         assert not self.running, "inference already running"
 
         self.running = True
-        self.request_socket.send(encode_msg(TaskRequest(task=req)))
         try:
+            self.request_socket.send(encode_msg(TaskRequest(task=req)))
             while True:
                 obj_json = self.request_socket.recv()
                 obj = parse_message(obj_json)
diff --git a/llama_stack/providers/inline/telemetry/meta_reference/telemetry.py b/llama_stack/providers/inline/telemetry/meta_reference/telemetry.py
index 4875f8cf0..569d02f50 100644
--- a/llama_stack/providers/inline/telemetry/meta_reference/telemetry.py
+++ b/llama_stack/providers/inline/telemetry/meta_reference/telemetry.py
@@ -72,7 +72,7 @@ def is_tracing_enabled(tracer):
 class TelemetryAdapter(TelemetryDatasetMixin, Telemetry):
     def __init__(self, config: TelemetryConfig, deps: Dict[str, Any]) -> None:
         self.config = config
-        self.datasetio_api = deps[Api.datasetio]
+        self.datasetio_api = deps.get(Api.datasetio)
 
         resource = Resource.create(
             {
@@ -81,6 +81,11 @@ class TelemetryAdapter(TelemetryDatasetMixin, Telemetry):
         )
 
         global _TRACER_PROVIDER
+        # Initialize the correct span processor based on the provider state.
+        # This is needed since once the span processor is set, it cannot be unset.
+        # Recreating the telemetry adapter multiple times will result in duplicate span processors.
+        # Since the library client can be recreated multiple times in a notebook,
+        # the kernel will hold on to the span processor and cause duplicate spans to be written.
         if _TRACER_PROVIDER is None:
             provider = TracerProvider(resource=resource)
             trace.set_tracer_provider(provider)
@@ -100,14 +105,18 @@ class TelemetryAdapter(TelemetryDatasetMixin, Telemetry):
                     resource=resource, metric_readers=[metric_reader]
                 )
                 metrics.set_meter_provider(metric_provider)
-                self.meter = metrics.get_meter(__name__)
             if TelemetrySink.SQLITE in self.config.sinks:
                 trace.get_tracer_provider().add_span_processor(
                     SQLiteSpanProcessor(self.config.sqlite_db_path)
                 )
-                self.trace_store = SQLiteTraceStore(self.config.sqlite_db_path)
             if TelemetrySink.CONSOLE in self.config.sinks:
                 trace.get_tracer_provider().add_span_processor(ConsoleSpanProcessor())
+
+        if TelemetrySink.OTEL in self.config.sinks:
+            self.meter = metrics.get_meter(__name__)
+        if TelemetrySink.SQLITE in self.config.sinks:
+            self.trace_store = SQLiteTraceStore(self.config.sqlite_db_path)
+
         self._lock = _global_lock
 
     async def initialize(self) -> None:
diff --git a/llama_stack/providers/inline/tool_runtime/code_interpreter/code_interpreter.py b/llama_stack/providers/inline/tool_runtime/code_interpreter/code_interpreter.py
index 361c91a92..04434768d 100644
--- a/llama_stack/providers/inline/tool_runtime/code_interpreter/code_interpreter.py
+++ b/llama_stack/providers/inline/tool_runtime/code_interpreter/code_interpreter.py
@@ -60,9 +60,9 @@ class CodeInterpreterToolRuntimeImpl(ToolsProtocolPrivate, ToolRuntime):
         ]
 
     async def invoke_tool(
-        self, tool_name: str, args: Dict[str, Any]
+        self, tool_name: str, kwargs: Dict[str, Any]
     ) -> ToolInvocationResult:
-        script = args["code"]
+        script = kwargs["code"]
         req = CodeExecutionRequest(scripts=[script])
         res = self.code_executor.execute(req)
         pieces = [res["process_status"]]
diff --git a/llama_stack/providers/inline/tool_runtime/memory/config.py b/llama_stack/providers/inline/tool_runtime/memory/config.py
deleted file mode 100644
index 6ff242c6b..000000000
--- a/llama_stack/providers/inline/tool_runtime/memory/config.py
+++ /dev/null
@@ -1,90 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the terms described in the LICENSE file in
-# the root directory of this source tree.
-
-from enum import Enum
-from typing import Annotated, List, Literal, Union
-
-from pydantic import BaseModel, Field
-
-
-class _MemoryBankConfigCommon(BaseModel):
-    bank_id: str
-
-
-class VectorMemoryBankConfig(_MemoryBankConfigCommon):
-    type: Literal["vector"] = "vector"
-
-
-class KeyValueMemoryBankConfig(_MemoryBankConfigCommon):
-    type: Literal["keyvalue"] = "keyvalue"
-    keys: List[str]  # what keys to focus on
-
-
-class KeywordMemoryBankConfig(_MemoryBankConfigCommon):
-    type: Literal["keyword"] = "keyword"
-
-
-class GraphMemoryBankConfig(_MemoryBankConfigCommon):
-    type: Literal["graph"] = "graph"
-    entities: List[str]  # what entities to focus on
-
-
-MemoryBankConfig = Annotated[
-    Union[
-        VectorMemoryBankConfig,
-        KeyValueMemoryBankConfig,
-        KeywordMemoryBankConfig,
-        GraphMemoryBankConfig,
-    ],
-    Field(discriminator="type"),
-]
-
-
-class MemoryQueryGenerator(Enum):
-    default = "default"
-    llm = "llm"
-    custom = "custom"
-
-
-class DefaultMemoryQueryGeneratorConfig(BaseModel):
-    type: Literal[MemoryQueryGenerator.default.value] = (
-        MemoryQueryGenerator.default.value
-    )
-    sep: str = " "
-
-
-class LLMMemoryQueryGeneratorConfig(BaseModel):
-    type: Literal[MemoryQueryGenerator.llm.value] = MemoryQueryGenerator.llm.value
-    model: str
-    template: str
-
-
-class CustomMemoryQueryGeneratorConfig(BaseModel):
-    type: Literal[MemoryQueryGenerator.custom.value] = MemoryQueryGenerator.custom.value
-
-
-MemoryQueryGeneratorConfig = Annotated[
-    Union[
-        DefaultMemoryQueryGeneratorConfig,
-        LLMMemoryQueryGeneratorConfig,
-        CustomMemoryQueryGeneratorConfig,
-    ],
-    Field(discriminator="type"),
-]
-
-
-class MemoryToolConfig(BaseModel):
-    memory_bank_configs: List[MemoryBankConfig] = Field(default_factory=list)
-
-
-class MemoryToolRuntimeConfig(BaseModel):
-    # This config defines how a query is generated using the messages
-    # for memory bank retrieval.
-    query_generator_config: MemoryQueryGeneratorConfig = Field(
-        default=DefaultMemoryQueryGeneratorConfig()
-    )
-    max_tokens_in_context: int = 4096
-    max_chunks: int = 5
diff --git a/llama_stack/providers/inline/tool_runtime/memory/memory.py b/llama_stack/providers/inline/tool_runtime/memory/memory.py
deleted file mode 100644
index fe6325abb..000000000
--- a/llama_stack/providers/inline/tool_runtime/memory/memory.py
+++ /dev/null
@@ -1,146 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the terms described in the LICENSE file in
-# the root directory of this source tree.
-
-import asyncio
-import logging
-import secrets
-import string
-from typing import Any, Dict, List, Optional
-
-from llama_stack.apis.common.content_types import URL
-from llama_stack.apis.inference import Inference, InterleavedContent
-from llama_stack.apis.memory import Memory, QueryDocumentsResponse
-from llama_stack.apis.memory_banks import MemoryBanks
-from llama_stack.apis.tools import (
-    ToolDef,
-    ToolInvocationResult,
-    ToolParameter,
-    ToolRuntime,
-)
-from llama_stack.providers.datatypes import ToolsProtocolPrivate
-from llama_stack.providers.utils.memory.vector_store import concat_interleaved_content
-
-from .config import MemoryToolConfig, MemoryToolRuntimeConfig
-from .context_retriever import generate_rag_query
-
-log = logging.getLogger(__name__)
-
-
-def make_random_string(length: int = 8):
-    return "".join(
-        secrets.choice(string.ascii_letters + string.digits) for _ in range(length)
-    )
-
-
-class MemoryToolRuntimeImpl(ToolsProtocolPrivate, ToolRuntime):
-    def __init__(
-        self,
-        config: MemoryToolRuntimeConfig,
-        memory_api: Memory,
-        memory_banks_api: MemoryBanks,
-        inference_api: Inference,
-    ):
-        self.config = config
-        self.memory_api = memory_api
-        self.memory_banks_api = memory_banks_api
-        self.inference_api = inference_api
-
-    async def initialize(self):
-        pass
-
-    async def list_runtime_tools(
-        self, tool_group_id: Optional[str] = None, mcp_endpoint: Optional[URL] = None
-    ) -> List[ToolDef]:
-        return [
-            ToolDef(
-                name="query_memory",
-                description="Retrieve context from memory",
-                parameters=[
-                    ToolParameter(
-                        name="messages",
-                        description="The input messages to search for",
-                        parameter_type="array",
-                    ),
-                ],
-            )
-        ]
-
-    async def _retrieve_context(
-        self, input_messages: List[InterleavedContent], bank_ids: List[str]
-    ) -> Optional[List[InterleavedContent]]:
-        if not bank_ids:
-            return None
-        query = await generate_rag_query(
-            self.config.query_generator_config,
-            input_messages,
-            inference_api=self.inference_api,
-        )
-        tasks = [
-            self.memory_api.query_documents(
-                bank_id=bank_id,
-                query=query,
-                params={
-                    "max_chunks": self.config.max_chunks,
-                },
-            )
-            for bank_id in bank_ids
-        ]
-        results: List[QueryDocumentsResponse] = await asyncio.gather(*tasks)
-        chunks = [c for r in results for c in r.chunks]
-        scores = [s for r in results for s in r.scores]
-
-        if not chunks:
-            return None
-
-        # sort by score
-        chunks, scores = zip(
-            *sorted(zip(chunks, scores), key=lambda x: x[1], reverse=True)
-        )
-
-        tokens = 0
-        picked = []
-        for c in chunks[: self.config.max_chunks]:
-            tokens += c.token_count
-            if tokens > self.config.max_tokens_in_context:
-                log.error(
-                    f"Using {len(picked)} chunks; reached max tokens in context: {tokens}",
-                )
-                break
-            picked.append(f"id:{c.document_id}; content:{c.content}")
-
-        return [
-            "Here are the retrieved documents for relevant context:\n=== START-RETRIEVED-CONTEXT ===\n",
-            *picked,
-            "\n=== END-RETRIEVED-CONTEXT ===\n",
-        ]
-
-    async def invoke_tool(
-        self, tool_name: str, args: Dict[str, Any]
-    ) -> ToolInvocationResult:
-        tool = await self.tool_store.get_tool(tool_name)
-        tool_group = await self.tool_store.get_tool_group(tool.toolgroup_id)
-        final_args = tool_group.args or {}
-        final_args.update(args)
-        config = MemoryToolConfig()
-        if tool.metadata and tool.metadata.get("config") is not None:
-            config = MemoryToolConfig(**tool.metadata["config"])
-        if "memory_bank_ids" in final_args:
-            bank_ids = final_args["memory_bank_ids"]
-        else:
-            bank_ids = [
-                bank_config.bank_id for bank_config in config.memory_bank_configs
-            ]
-        if "messages" not in final_args:
-            raise ValueError("messages are required")
-        context = await self._retrieve_context(
-            final_args["messages"],
-            bank_ids,
-        )
-        if context is None:
-            context = []
-        return ToolInvocationResult(
-            content=concat_interleaved_content(context), error_code=0
-        )
diff --git a/llama_stack/providers/inline/tool_runtime/memory/__init__.py b/llama_stack/providers/inline/tool_runtime/rag/__init__.py
similarity index 59%
rename from llama_stack/providers/inline/tool_runtime/memory/__init__.py
rename to llama_stack/providers/inline/tool_runtime/rag/__init__.py
index 928afa484..542872091 100644
--- a/llama_stack/providers/inline/tool_runtime/memory/__init__.py
+++ b/llama_stack/providers/inline/tool_runtime/rag/__init__.py
@@ -8,13 +8,11 @@ from typing import Any, Dict
 
 from llama_stack.providers.datatypes import Api
 
-from .config import MemoryToolRuntimeConfig
+from .config import RagToolRuntimeConfig
 from .memory import MemoryToolRuntimeImpl
 
 
-async def get_provider_impl(config: MemoryToolRuntimeConfig, deps: Dict[str, Any]):
-    impl = MemoryToolRuntimeImpl(
-        config, deps[Api.memory], deps[Api.memory_banks], deps[Api.inference]
-    )
+async def get_provider_impl(config: RagToolRuntimeConfig, deps: Dict[str, Any]):
+    impl = MemoryToolRuntimeImpl(config, deps[Api.vector_io], deps[Api.inference])
     await impl.initialize()
     return impl
diff --git a/llama_stack/providers/inline/tool_runtime/rag/config.py b/llama_stack/providers/inline/tool_runtime/rag/config.py
new file mode 100644
index 000000000..2d0d2f595
--- /dev/null
+++ b/llama_stack/providers/inline/tool_runtime/rag/config.py
@@ -0,0 +1,11 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from pydantic import BaseModel
+
+
+class RagToolRuntimeConfig(BaseModel):
+    pass
diff --git a/llama_stack/providers/inline/tool_runtime/memory/context_retriever.py b/llama_stack/providers/inline/tool_runtime/rag/context_retriever.py
similarity index 55%
rename from llama_stack/providers/inline/tool_runtime/memory/context_retriever.py
rename to llama_stack/providers/inline/tool_runtime/rag/context_retriever.py
index 803981f07..e77ec76af 100644
--- a/llama_stack/providers/inline/tool_runtime/memory/context_retriever.py
+++ b/llama_stack/providers/inline/tool_runtime/rag/context_retriever.py
@@ -5,68 +5,64 @@
 # the root directory of this source tree.
 
 
-from typing import List
-
 from jinja2 import Template
-from pydantic import BaseModel
 
 from llama_stack.apis.common.content_types import InterleavedContent
 from llama_stack.apis.inference import UserMessage
+
+from llama_stack.apis.tools.rag_tool import (
+    DefaultRAGQueryGeneratorConfig,
+    LLMRAGQueryGeneratorConfig,
+    RAGQueryGenerator,
+    RAGQueryGeneratorConfig,
+)
 from llama_stack.providers.utils.inference.prompt_adapter import (
     interleaved_content_as_str,
 )
 
-from .config import (
-    DefaultMemoryQueryGeneratorConfig,
-    LLMMemoryQueryGeneratorConfig,
-    MemoryQueryGenerator,
-    MemoryQueryGeneratorConfig,
-)
-
 
 async def generate_rag_query(
-    config: MemoryQueryGeneratorConfig,
-    messages: List[InterleavedContent],
+    config: RAGQueryGeneratorConfig,
+    content: InterleavedContent,
     **kwargs,
 ):
     """
     Generates a query that will be used for
     retrieving relevant information from the memory bank.
     """
-    if config.type == MemoryQueryGenerator.default.value:
-        query = await default_rag_query_generator(config, messages, **kwargs)
-    elif config.type == MemoryQueryGenerator.llm.value:
-        query = await llm_rag_query_generator(config, messages, **kwargs)
+    if config.type == RAGQueryGenerator.default.value:
+        query = await default_rag_query_generator(config, content, **kwargs)
+    elif config.type == RAGQueryGenerator.llm.value:
+        query = await llm_rag_query_generator(config, content, **kwargs)
     else:
         raise NotImplementedError(f"Unsupported memory query generator {config.type}")
     return query
 
 
 async def default_rag_query_generator(
-    config: DefaultMemoryQueryGeneratorConfig,
-    messages: List[InterleavedContent],
+    config: DefaultRAGQueryGeneratorConfig,
+    content: InterleavedContent,
     **kwargs,
 ):
-    return config.sep.join(interleaved_content_as_str(m) for m in messages)
+    return interleaved_content_as_str(content, sep=config.separator)
 
 
 async def llm_rag_query_generator(
-    config: LLMMemoryQueryGeneratorConfig,
-    messages: List[InterleavedContent],
+    config: LLMRAGQueryGeneratorConfig,
+    content: InterleavedContent,
     **kwargs,
 ):
     assert "inference_api" in kwargs, "LLMRAGQueryGenerator needs inference_api"
     inference_api = kwargs["inference_api"]
 
-    m_dict = {
-        "messages": [
-            message.model_dump() if isinstance(message, BaseModel) else message
-            for message in messages
-        ]
-    }
+    messages = []
+    if isinstance(content, list):
+        messages = [interleaved_content_as_str(m) for m in content]
+    else:
+        messages = [interleaved_content_as_str(content)]
 
     template = Template(config.template)
-    content = template.render(m_dict)
+    content = template.render({"messages": messages})
 
     model = config.model
     message = UserMessage(content=content)
diff --git a/llama_stack/providers/inline/tool_runtime/rag/memory.py b/llama_stack/providers/inline/tool_runtime/rag/memory.py
new file mode 100644
index 000000000..9a2687925
--- /dev/null
+++ b/llama_stack/providers/inline/tool_runtime/rag/memory.py
@@ -0,0 +1,177 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+import asyncio
+import logging
+import secrets
+import string
+from typing import Any, Dict, List, Optional
+
+from llama_stack.apis.common.content_types import (
+    InterleavedContent,
+    TextContentItem,
+    URL,
+)
+from llama_stack.apis.inference import Inference
+from llama_stack.apis.tools import (
+    RAGDocument,
+    RAGQueryConfig,
+    RAGQueryResult,
+    RAGToolRuntime,
+    ToolDef,
+    ToolInvocationResult,
+    ToolRuntime,
+)
+from llama_stack.apis.vector_io import QueryChunksResponse, VectorIO
+from llama_stack.providers.datatypes import ToolsProtocolPrivate
+from llama_stack.providers.utils.memory.vector_store import (
+    content_from_doc,
+    make_overlapped_chunks,
+)
+
+from .config import RagToolRuntimeConfig
+from .context_retriever import generate_rag_query
+
+log = logging.getLogger(__name__)
+
+
+def make_random_string(length: int = 8):
+    return "".join(
+        secrets.choice(string.ascii_letters + string.digits) for _ in range(length)
+    )
+
+
+class MemoryToolRuntimeImpl(ToolsProtocolPrivate, ToolRuntime, RAGToolRuntime):
+    def __init__(
+        self,
+        config: RagToolRuntimeConfig,
+        vector_io_api: VectorIO,
+        inference_api: Inference,
+    ):
+        self.config = config
+        self.vector_io_api = vector_io_api
+        self.inference_api = inference_api
+
+    async def initialize(self):
+        pass
+
+    async def shutdown(self):
+        pass
+
+    async def insert(
+        self,
+        documents: List[RAGDocument],
+        vector_db_id: str,
+        chunk_size_in_tokens: int = 512,
+    ) -> None:
+        chunks = []
+        for doc in documents:
+            content = await content_from_doc(doc)
+            chunks.extend(
+                make_overlapped_chunks(
+                    doc.document_id,
+                    content,
+                    chunk_size_in_tokens,
+                    chunk_size_in_tokens // 4,
+                )
+            )
+
+        if not chunks:
+            return
+
+        await self.vector_io_api.insert_chunks(
+            chunks=chunks,
+            vector_db_id=vector_db_id,
+        )
+
+    async def query(
+        self,
+        content: InterleavedContent,
+        vector_db_ids: List[str],
+        query_config: Optional[RAGQueryConfig] = None,
+    ) -> RAGQueryResult:
+        if not vector_db_ids:
+            return RAGQueryResult(content=None)
+
+        query_config = query_config or RAGQueryConfig()
+        query = await generate_rag_query(
+            query_config.query_generator_config,
+            content,
+            inference_api=self.inference_api,
+        )
+        tasks = [
+            self.vector_io_api.query_chunks(
+                vector_db_id=vector_db_id,
+                query=query,
+                params={
+                    "max_chunks": query_config.max_chunks,
+                },
+            )
+            for vector_db_id in vector_db_ids
+        ]
+        results: List[QueryChunksResponse] = await asyncio.gather(*tasks)
+        chunks = [c for r in results for c in r.chunks]
+        scores = [s for r in results for s in r.scores]
+
+        if not chunks:
+            return RAGQueryResult(content=None)
+
+        # sort by score
+        chunks, scores = zip(
+            *sorted(zip(chunks, scores), key=lambda x: x[1], reverse=True)
+        )
+
+        tokens = 0
+        picked = []
+        for c in chunks[: query_config.max_chunks]:
+            metadata = c.metadata
+            tokens += metadata["token_count"]
+            if tokens > query_config.max_tokens_in_context:
+                log.error(
+                    f"Using {len(picked)} chunks; reached max tokens in context: {tokens}",
+                )
+                break
+            picked.append(
+                TextContentItem(
+                    text=f"id:{metadata['document_id']}; content:{c.content}",
+                )
+            )
+
+        return RAGQueryResult(
+            content=[
+                TextContentItem(
+                    text="Here are the retrieved documents for relevant context:\n=== START-RETRIEVED-CONTEXT ===\n",
+                ),
+                *picked,
+                TextContentItem(
+                    text="\n=== END-RETRIEVED-CONTEXT ===\n",
+                ),
+            ],
+        )
+
+    async def list_runtime_tools(
+        self, tool_group_id: Optional[str] = None, mcp_endpoint: Optional[URL] = None
+    ) -> List[ToolDef]:
+        # Parameters are not listed since these methods are not yet invoked automatically
+        # by the LLM. The method is only implemented so things like /tools can list without
+        # encountering fatals.
+        return [
+            ToolDef(
+                name="query_from_memory",
+                description="Retrieve context from memory",
+            ),
+            ToolDef(
+                name="insert_into_memory",
+                description="Insert documents into memory",
+            ),
+        ]
+
+    async def invoke_tool(
+        self, tool_name: str, kwargs: Dict[str, Any]
+    ) -> ToolInvocationResult:
+        raise RuntimeError(
+            "This toolgroup should not be called generically but only through specific methods of the RAGToolRuntime protocol"
+        )
diff --git a/llama_stack/providers/inline/memory/__init__.py b/llama_stack/providers/inline/vector_io/__init__.py
similarity index 100%
rename from llama_stack/providers/inline/memory/__init__.py
rename to llama_stack/providers/inline/vector_io/__init__.py
diff --git a/llama_stack/providers/inline/memory/chroma/__init__.py b/llama_stack/providers/inline/vector_io/chroma/__init__.py
similarity index 73%
rename from llama_stack/providers/inline/memory/chroma/__init__.py
rename to llama_stack/providers/inline/vector_io/chroma/__init__.py
index 80620c780..68e28da63 100644
--- a/llama_stack/providers/inline/memory/chroma/__init__.py
+++ b/llama_stack/providers/inline/vector_io/chroma/__init__.py
@@ -14,8 +14,10 @@ from .config import ChromaInlineImplConfig
 async def get_provider_impl(
     config: ChromaInlineImplConfig, deps: Dict[Api, ProviderSpec]
 ):
-    from llama_stack.providers.remote.memory.chroma.chroma import ChromaMemoryAdapter
+    from llama_stack.providers.remote.vector_io.chroma.chroma import (
+        ChromaVectorIOAdapter,
+    )
 
-    impl = ChromaMemoryAdapter(config, deps[Api.inference])
+    impl = ChromaVectorIOAdapter(config, deps[Api.inference])
     await impl.initialize()
     return impl
diff --git a/llama_stack/providers/inline/memory/chroma/config.py b/llama_stack/providers/inline/vector_io/chroma/config.py
similarity index 100%
rename from llama_stack/providers/inline/memory/chroma/config.py
rename to llama_stack/providers/inline/vector_io/chroma/config.py
diff --git a/llama_stack/providers/inline/memory/faiss/__init__.py b/llama_stack/providers/inline/vector_io/faiss/__init__.py
similarity index 85%
rename from llama_stack/providers/inline/memory/faiss/__init__.py
rename to llama_stack/providers/inline/vector_io/faiss/__init__.py
index 2d7ede3b1..32cf262fd 100644
--- a/llama_stack/providers/inline/memory/faiss/__init__.py
+++ b/llama_stack/providers/inline/vector_io/faiss/__init__.py
@@ -11,12 +11,12 @@ from .config import FaissImplConfig
 
 
 async def get_provider_impl(config: FaissImplConfig, deps: Dict[Api, ProviderSpec]):
-    from .faiss import FaissMemoryImpl
+    from .faiss import FaissVectorIOImpl
 
     assert isinstance(
         config, FaissImplConfig
     ), f"Unexpected config type: {type(config)}"
 
-    impl = FaissMemoryImpl(config, deps[Api.inference])
+    impl = FaissVectorIOImpl(config, deps[Api.inference])
     await impl.initialize()
     return impl
diff --git a/llama_stack/providers/inline/memory/faiss/config.py b/llama_stack/providers/inline/vector_io/faiss/config.py
similarity index 100%
rename from llama_stack/providers/inline/memory/faiss/config.py
rename to llama_stack/providers/inline/vector_io/faiss/config.py
diff --git a/llama_stack/providers/inline/memory/faiss/faiss.py b/llama_stack/providers/inline/vector_io/faiss/faiss.py
similarity index 62%
rename from llama_stack/providers/inline/memory/faiss/faiss.py
rename to llama_stack/providers/inline/vector_io/faiss/faiss.py
index af398801a..69a7eef7c 100644
--- a/llama_stack/providers/inline/memory/faiss/faiss.py
+++ b/llama_stack/providers/inline/vector_io/faiss/faiss.py
@@ -17,35 +17,29 @@ import numpy as np
 from numpy.typing import NDArray
 
 from llama_stack.apis.inference import InterleavedContent
-from llama_stack.apis.memory import (
-    Chunk,
-    Memory,
-    MemoryBankDocument,
-    QueryDocumentsResponse,
-)
-from llama_stack.apis.memory_banks import MemoryBank, MemoryBankType, VectorMemoryBank
-from llama_stack.providers.datatypes import Api, MemoryBanksProtocolPrivate
+from llama_stack.apis.vector_dbs import VectorDB
+from llama_stack.apis.vector_io import Chunk, QueryChunksResponse, VectorIO
+from llama_stack.providers.datatypes import Api, VectorDBsProtocolPrivate
 from llama_stack.providers.utils.kvstore import kvstore_impl
 from llama_stack.providers.utils.memory.vector_store import (
-    BankWithIndex,
     EmbeddingIndex,
+    VectorDBWithIndex,
 )
 
 from .config import FaissImplConfig
 
 logger = logging.getLogger(__name__)
 
-MEMORY_BANKS_PREFIX = "memory_banks:v2::"
-FAISS_INDEX_PREFIX = "faiss_index:v2::"
+VERSION = "v3"
+VECTOR_DBS_PREFIX = f"vector_dbs:{VERSION}::"
+FAISS_INDEX_PREFIX = f"faiss_index:{VERSION}::"
 
 
 class FaissIndex(EmbeddingIndex):
-    id_by_index: Dict[int, str]
     chunk_by_index: Dict[int, str]
 
     def __init__(self, dimension: int, kvstore=None, bank_id: str = None):
         self.index = faiss.IndexFlatL2(dimension)
-        self.id_by_index = {}
         self.chunk_by_index = {}
         self.kvstore = kvstore
         self.bank_id = bank_id
@@ -65,7 +59,6 @@ class FaissIndex(EmbeddingIndex):
 
         if stored_data:
             data = json.loads(stored_data)
-            self.id_by_index = {int(k): v for k, v in data["id_by_index"].items()}
             self.chunk_by_index = {
                 int(k): Chunk.model_validate_json(v)
                 for k, v in data["chunk_by_index"].items()
@@ -82,7 +75,6 @@ class FaissIndex(EmbeddingIndex):
         buffer = io.BytesIO()
         np.savetxt(buffer, np_index)
         data = {
-            "id_by_index": self.id_by_index,
             "chunk_by_index": {
                 k: v.model_dump_json() for k, v in self.chunk_by_index.items()
             },
@@ -108,10 +100,9 @@ class FaissIndex(EmbeddingIndex):
                 f"Embedding dimension mismatch. Expected {self.index.d}, got {embedding_dim}"
             )
 
-        indexlen = len(self.id_by_index)
+        indexlen = len(self.chunk_by_index)
         for i, chunk in enumerate(chunks):
             self.chunk_by_index[indexlen + i] = chunk
-            self.id_by_index[indexlen + i] = chunk.document_id
 
         self.index.add(np.array(embeddings).astype(np.float32))
 
@@ -120,7 +111,7 @@ class FaissIndex(EmbeddingIndex):
 
     async def query(
         self, embedding: NDArray, k: int, score_threshold: float
-    ) -> QueryDocumentsResponse:
+    ) -> QueryChunksResponse:
         distances, indices = self.index.search(
             embedding.reshape(1, -1).astype(np.float32), k
         )
@@ -133,10 +124,10 @@ class FaissIndex(EmbeddingIndex):
             chunks.append(self.chunk_by_index[int(i)])
             scores.append(1.0 / float(d))
 
-        return QueryDocumentsResponse(chunks=chunks, scores=scores)
+        return QueryChunksResponse(chunks=chunks, scores=scores)
 
 
-class FaissMemoryImpl(Memory, MemoryBanksProtocolPrivate):
+class FaissVectorIOImpl(VectorIO, VectorDBsProtocolPrivate):
     def __init__(self, config: FaissImplConfig, inference_api: Api.inference) -> None:
         self.config = config
         self.inference_api = inference_api
@@ -146,77 +137,74 @@ class FaissMemoryImpl(Memory, MemoryBanksProtocolPrivate):
     async def initialize(self) -> None:
         self.kvstore = await kvstore_impl(self.config.kvstore)
         # Load existing banks from kvstore
-        start_key = MEMORY_BANKS_PREFIX
-        end_key = f"{MEMORY_BANKS_PREFIX}\xff"
-        stored_banks = await self.kvstore.range(start_key, end_key)
+        start_key = VECTOR_DBS_PREFIX
+        end_key = f"{VECTOR_DBS_PREFIX}\xff"
+        stored_vector_dbs = await self.kvstore.range(start_key, end_key)
 
-        for bank_data in stored_banks:
-            bank = VectorMemoryBank.model_validate_json(bank_data)
-            index = BankWithIndex(
-                bank,
+        for vector_db_data in stored_vector_dbs:
+            vector_db = VectorDB.model_validate_json(vector_db_data)
+            index = VectorDBWithIndex(
+                vector_db,
                 await FaissIndex.create(
-                    bank.embedding_dimension, self.kvstore, bank.identifier
+                    vector_db.embedding_dimension, self.kvstore, vector_db.identifier
                 ),
                 self.inference_api,
             )
-            self.cache[bank.identifier] = index
+            self.cache[vector_db.identifier] = index
 
     async def shutdown(self) -> None:
         # Cleanup if needed
         pass
 
-    async def register_memory_bank(
+    async def register_vector_db(
         self,
-        memory_bank: MemoryBank,
+        vector_db: VectorDB,
     ) -> None:
-        assert (
-            memory_bank.memory_bank_type == MemoryBankType.vector.value
-        ), f"Only vector banks are supported {memory_bank.type}"
-
-        # Store in kvstore
-        key = f"{MEMORY_BANKS_PREFIX}{memory_bank.identifier}"
+        key = f"{VECTOR_DBS_PREFIX}{vector_db.identifier}"
         await self.kvstore.set(
             key=key,
-            value=memory_bank.model_dump_json(),
+            value=vector_db.model_dump_json(),
         )
 
         # Store in cache
-        self.cache[memory_bank.identifier] = BankWithIndex(
-            memory_bank,
-            await FaissIndex.create(
-                memory_bank.embedding_dimension, self.kvstore, memory_bank.identifier
+        self.cache[vector_db.identifier] = VectorDBWithIndex(
+            vector_db=vector_db,
+            index=await FaissIndex.create(
+                vector_db.embedding_dimension, self.kvstore, vector_db.identifier
             ),
-            self.inference_api,
+            inference_api=self.inference_api,
         )
 
-    async def list_memory_banks(self) -> List[MemoryBank]:
-        return [i.bank for i in self.cache.values()]
+    async def list_vector_dbs(self) -> List[VectorDB]:
+        return [i.vector_db for i in self.cache.values()]
 
-    async def unregister_memory_bank(self, memory_bank_id: str) -> None:
-        await self.cache[memory_bank_id].index.delete()
-        del self.cache[memory_bank_id]
-        await self.kvstore.delete(f"{MEMORY_BANKS_PREFIX}{memory_bank_id}")
+    async def unregister_vector_db(self, vector_db_id: str) -> None:
+        await self.cache[vector_db_id].index.delete()
+        del self.cache[vector_db_id]
+        await self.kvstore.delete(f"{VECTOR_DBS_PREFIX}{vector_db_id}")
 
-    async def insert_documents(
+    async def insert_chunks(
         self,
-        bank_id: str,
-        documents: List[MemoryBankDocument],
+        vector_db_id: str,
+        chunks: List[Chunk],
         ttl_seconds: Optional[int] = None,
     ) -> None:
-        index = self.cache.get(bank_id)
+        index = self.cache.get(vector_db_id)
         if index is None:
-            raise ValueError(f"Bank {bank_id} not found. found: {self.cache.keys()}")
+            raise ValueError(
+                f"Vector DB {vector_db_id} not found. found: {self.cache.keys()}"
+            )
 
-        await index.insert_documents(documents)
+        await index.insert_chunks(chunks)
 
-    async def query_documents(
+    async def query_chunks(
         self,
-        bank_id: str,
+        vector_db_id: str,
         query: InterleavedContent,
         params: Optional[Dict[str, Any]] = None,
-    ) -> QueryDocumentsResponse:
-        index = self.cache.get(bank_id)
+    ) -> QueryChunksResponse:
+        index = self.cache.get(vector_db_id)
         if index is None:
-            raise ValueError(f"Bank {bank_id} not found")
+            raise ValueError(f"Vector DB {vector_db_id} not found")
 
-        return await index.query_documents(query, params)
+        return await index.query_chunks(query, params)
diff --git a/llama_stack/providers/registry/agents.py b/llama_stack/providers/registry/agents.py
index 3e38b1adc..655303f98 100644
--- a/llama_stack/providers/registry/agents.py
+++ b/llama_stack/providers/registry/agents.py
@@ -33,8 +33,8 @@ def available_providers() -> List[ProviderSpec]:
             api_dependencies=[
                 Api.inference,
                 Api.safety,
-                Api.memory,
-                Api.memory_banks,
+                Api.vector_io,
+                Api.vector_dbs,
                 Api.tool_runtime,
                 Api.tool_groups,
             ],
diff --git a/llama_stack/providers/registry/inference.py b/llama_stack/providers/registry/inference.py
index 55924a1e9..e72140ccf 100644
--- a/llama_stack/providers/registry/inference.py
+++ b/llama_stack/providers/registry/inference.py
@@ -195,4 +195,24 @@ def available_providers() -> List[ProviderSpec]:
                 config_class="llama_stack.providers.remote.inference.nvidia.NVIDIAConfig",
             ),
         ),
+        remote_provider_spec(
+            api=Api.inference,
+            adapter=AdapterSpec(
+                adapter_type="runpod",
+                pip_packages=["openai"],
+                module="llama_stack.providers.remote.inference.runpod",
+                config_class="llama_stack.providers.remote.inference.runpod.RunpodImplConfig",
+            ),
+        ),
+        remote_provider_spec(
+            api=Api.inference,
+            adapter=AdapterSpec(
+                adapter_type="sambanova",
+                pip_packages=[
+                    "openai",
+                ],
+                module="llama_stack.providers.remote.inference.sambanova",
+                config_class="llama_stack.providers.remote.inference.sambanova.SambaNovaImplConfig",
+            ),
+        ),
     ]
diff --git a/llama_stack/providers/registry/telemetry.py b/llama_stack/providers/registry/telemetry.py
index ba7e2f806..f3b41374c 100644
--- a/llama_stack/providers/registry/telemetry.py
+++ b/llama_stack/providers/registry/telemetry.py
@@ -24,7 +24,7 @@ def available_providers() -> List[ProviderSpec]:
                 "opentelemetry-sdk",
                 "opentelemetry-exporter-otlp-proto-http",
             ],
-            api_dependencies=[Api.datasetio],
+            optional_api_dependencies=[Api.datasetio],
             module="llama_stack.providers.inline.telemetry.meta_reference",
             config_class="llama_stack.providers.inline.telemetry.meta_reference.config.TelemetryConfig",
         ),
diff --git a/llama_stack/providers/registry/tool_runtime.py b/llama_stack/providers/registry/tool_runtime.py
index 40299edad..33d880f30 100644
--- a/llama_stack/providers/registry/tool_runtime.py
+++ b/llama_stack/providers/registry/tool_runtime.py
@@ -19,11 +19,11 @@ def available_providers() -> List[ProviderSpec]:
     return [
         InlineProviderSpec(
             api=Api.tool_runtime,
-            provider_type="inline::memory-runtime",
+            provider_type="inline::rag-runtime",
             pip_packages=[],
-            module="llama_stack.providers.inline.tool_runtime.memory",
-            config_class="llama_stack.providers.inline.tool_runtime.memory.config.MemoryToolRuntimeConfig",
-            api_dependencies=[Api.memory, Api.memory_banks, Api.inference],
+            module="llama_stack.providers.inline.tool_runtime.rag",
+            config_class="llama_stack.providers.inline.tool_runtime.rag.config.RagToolRuntimeConfig",
+            api_dependencies=[Api.vector_io, Api.inference],
         ),
         InlineProviderSpec(
             api=Api.tool_runtime,
diff --git a/llama_stack/providers/registry/memory.py b/llama_stack/providers/registry/vector_io.py
similarity index 64%
rename from llama_stack/providers/registry/memory.py
rename to llama_stack/providers/registry/vector_io.py
index 6867a9186..df7b7f4b3 100644
--- a/llama_stack/providers/registry/memory.py
+++ b/llama_stack/providers/registry/vector_io.py
@@ -38,78 +38,78 @@ EMBEDDING_DEPS = [
 def available_providers() -> List[ProviderSpec]:
     return [
         InlineProviderSpec(
-            api=Api.memory,
+            api=Api.vector_io,
             provider_type="inline::meta-reference",
             pip_packages=EMBEDDING_DEPS + ["faiss-cpu"],
-            module="llama_stack.providers.inline.memory.faiss",
-            config_class="llama_stack.providers.inline.memory.faiss.FaissImplConfig",
+            module="llama_stack.providers.inline.vector_io.faiss",
+            config_class="llama_stack.providers.inline.vector_io.faiss.FaissImplConfig",
             deprecation_warning="Please use the `inline::faiss` provider instead.",
             api_dependencies=[Api.inference],
         ),
         InlineProviderSpec(
-            api=Api.memory,
+            api=Api.vector_io,
             provider_type="inline::faiss",
             pip_packages=EMBEDDING_DEPS + ["faiss-cpu"],
-            module="llama_stack.providers.inline.memory.faiss",
-            config_class="llama_stack.providers.inline.memory.faiss.FaissImplConfig",
+            module="llama_stack.providers.inline.vector_io.faiss",
+            config_class="llama_stack.providers.inline.vector_io.faiss.FaissImplConfig",
             api_dependencies=[Api.inference],
         ),
         remote_provider_spec(
-            Api.memory,
+            Api.vector_io,
             AdapterSpec(
                 adapter_type="chromadb",
                 pip_packages=EMBEDDING_DEPS + ["chromadb-client"],
-                module="llama_stack.providers.remote.memory.chroma",
-                config_class="llama_stack.providers.remote.memory.chroma.ChromaRemoteImplConfig",
+                module="llama_stack.providers.remote.vector_io.chroma",
+                config_class="llama_stack.providers.remote.vector_io.chroma.ChromaRemoteImplConfig",
             ),
             api_dependencies=[Api.inference],
         ),
         InlineProviderSpec(
-            api=Api.memory,
+            api=Api.vector_io,
             provider_type="inline::chromadb",
             pip_packages=EMBEDDING_DEPS + ["chromadb"],
-            module="llama_stack.providers.inline.memory.chroma",
-            config_class="llama_stack.providers.inline.memory.chroma.ChromaInlineImplConfig",
+            module="llama_stack.providers.inline.vector_io.chroma",
+            config_class="llama_stack.providers.inline.vector_io.chroma.ChromaInlineImplConfig",
             api_dependencies=[Api.inference],
         ),
         remote_provider_spec(
-            Api.memory,
+            Api.vector_io,
             AdapterSpec(
                 adapter_type="pgvector",
                 pip_packages=EMBEDDING_DEPS + ["psycopg2-binary"],
-                module="llama_stack.providers.remote.memory.pgvector",
-                config_class="llama_stack.providers.remote.memory.pgvector.PGVectorConfig",
+                module="llama_stack.providers.remote.vector_io.pgvector",
+                config_class="llama_stack.providers.remote.vector_io.pgvector.PGVectorConfig",
             ),
             api_dependencies=[Api.inference],
         ),
         remote_provider_spec(
-            Api.memory,
+            Api.vector_io,
             AdapterSpec(
                 adapter_type="weaviate",
                 pip_packages=EMBEDDING_DEPS + ["weaviate-client"],
-                module="llama_stack.providers.remote.memory.weaviate",
-                config_class="llama_stack.providers.remote.memory.weaviate.WeaviateConfig",
-                provider_data_validator="llama_stack.providers.remote.memory.weaviate.WeaviateRequestProviderData",
+                module="llama_stack.providers.remote.vector_io.weaviate",
+                config_class="llama_stack.providers.remote.vector_io.weaviate.WeaviateConfig",
+                provider_data_validator="llama_stack.providers.remote.vector_io.weaviate.WeaviateRequestProviderData",
             ),
             api_dependencies=[Api.inference],
         ),
         remote_provider_spec(
-            api=Api.memory,
+            api=Api.vector_io,
             adapter=AdapterSpec(
                 adapter_type="sample",
                 pip_packages=[],
-                module="llama_stack.providers.remote.memory.sample",
-                config_class="llama_stack.providers.remote.memory.sample.SampleConfig",
+                module="llama_stack.providers.remote.vector_io.sample",
+                config_class="llama_stack.providers.remote.vector_io.sample.SampleConfig",
             ),
             api_dependencies=[],
         ),
         remote_provider_spec(
-            Api.memory,
+            Api.vector_io,
             AdapterSpec(
                 adapter_type="qdrant",
                 pip_packages=EMBEDDING_DEPS + ["qdrant-client"],
-                module="llama_stack.providers.remote.memory.qdrant",
-                config_class="llama_stack.providers.remote.memory.qdrant.QdrantConfig",
+                module="llama_stack.providers.remote.vector_io.qdrant",
+                config_class="llama_stack.providers.remote.vector_io.qdrant.QdrantConfig",
             ),
             api_dependencies=[Api.inference],
         ),
diff --git a/llama_stack/providers/remote/inference/fireworks/fireworks.py b/llama_stack/providers/remote/inference/fireworks/fireworks.py
index e22144326..5c98d2054 100644
--- a/llama_stack/providers/remote/inference/fireworks/fireworks.py
+++ b/llama_stack/providers/remote/inference/fireworks/fireworks.py
@@ -265,7 +265,8 @@ class FireworksInferenceAdapter(
         if isinstance(request, ChatCompletionRequest):
             if media_present:
                 input_dict["messages"] = [
-                    await convert_message_to_openai_dict(m) for m in request.messages
+                    await convert_message_to_openai_dict(m, download=True)
+                    for m in request.messages
                 ]
             else:
                 input_dict["prompt"] = await chat_completion_request_to_prompt(
diff --git a/llama_stack/providers/remote/inference/groq/groq_utils.py b/llama_stack/providers/remote/inference/groq/groq_utils.py
index 964395a14..99fa8219c 100644
--- a/llama_stack/providers/remote/inference/groq/groq_utils.py
+++ b/llama_stack/providers/remote/inference/groq/groq_utils.py
@@ -232,7 +232,7 @@ async def convert_chat_completion_response_stream(
                     event=ChatCompletionResponseEvent(
                         event_type=event_type,
                         delta=ToolCallDelta(
-                            content=tool_call,
+                            tool_call=tool_call,
                             parse_status=ToolCallParseStatus.succeeded,
                         ),
                     )
@@ -243,7 +243,7 @@ async def convert_chat_completion_response_stream(
                     event=ChatCompletionResponseEvent(
                         event_type=event_type,
                         delta=ToolCallDelta(
-                            content=tool_call.model_dump_json(),
+                            tool_call=tool_call.model_dump_json(),
                             parse_status=ToolCallParseStatus.failed,
                         ),
                     )
diff --git a/llama_stack/providers/remote/inference/nvidia/openai_utils.py b/llama_stack/providers/remote/inference/nvidia/openai_utils.py
index e85c8dd21..0f753f80d 100644
--- a/llama_stack/providers/remote/inference/nvidia/openai_utils.py
+++ b/llama_stack/providers/remote/inference/nvidia/openai_utils.py
@@ -505,7 +505,9 @@ async def convert_openai_chat_completion_stream(
                 event=ChatCompletionResponseEvent(
                     event_type=next(event_type),
                     delta=ToolCallDelta(
-                        content=_convert_openai_tool_calls(choice.delta.tool_calls)[0],
+                        tool_call=_convert_openai_tool_calls(choice.delta.tool_calls)[
+                            0
+                        ],
                         parse_status=ToolCallParseStatus.succeeded,
                     ),
                     logprobs=_convert_openai_logprobs(choice.logprobs),
diff --git a/llama_stack/providers/remote/inference/ollama/ollama.py b/llama_stack/providers/remote/inference/ollama/ollama.py
index 38721ea22..6811d435b 100644
--- a/llama_stack/providers/remote/inference/ollama/ollama.py
+++ b/llama_stack/providers/remote/inference/ollama/ollama.py
@@ -172,6 +172,7 @@ class OllamaInferenceAdapter(Inference, ModelsProtocolPrivate):
             model=model.provider_resource_id,
             content=content,
             sampling_params=sampling_params,
+            response_format=response_format,
             stream=stream,
             logprobs=logprobs,
         )
diff --git a/llama_stack/providers/remote/inference/runpod/__init__.py b/llama_stack/providers/remote/inference/runpod/__init__.py
new file mode 100644
index 000000000..37432dbb4
--- /dev/null
+++ b/llama_stack/providers/remote/inference/runpod/__init__.py
@@ -0,0 +1,17 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from .config import RunpodImplConfig
+from .runpod import RunpodInferenceAdapter
+
+
+async def get_adapter_impl(config: RunpodImplConfig, _deps):
+    assert isinstance(
+        config, RunpodImplConfig
+    ), f"Unexpected config type: {type(config)}"
+    impl = RunpodInferenceAdapter(config)
+    await impl.initialize()
+    return impl
diff --git a/llama_stack/providers/remote/inference/runpod/config.py b/llama_stack/providers/remote/inference/runpod/config.py
new file mode 100644
index 000000000..1a9582052
--- /dev/null
+++ b/llama_stack/providers/remote/inference/runpod/config.py
@@ -0,0 +1,22 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from typing import Optional
+
+from llama_models.schema_utils import json_schema_type
+from pydantic import BaseModel, Field
+
+
+@json_schema_type
+class RunpodImplConfig(BaseModel):
+    url: Optional[str] = Field(
+        default=None,
+        description="The URL for the Runpod model serving endpoint",
+    )
+    api_token: Optional[str] = Field(
+        default=None,
+        description="The API token",
+    )
diff --git a/llama_stack/providers/remote/inference/runpod/runpod.py b/llama_stack/providers/remote/inference/runpod/runpod.py
new file mode 100644
index 000000000..e5b19426f
--- /dev/null
+++ b/llama_stack/providers/remote/inference/runpod/runpod.py
@@ -0,0 +1,136 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+from typing import AsyncGenerator
+
+from llama_models.llama3.api.chat_format import ChatFormat
+from llama_models.llama3.api.datatypes import Message
+from llama_models.llama3.api.tokenizer import Tokenizer
+
+from openai import OpenAI
+
+from llama_stack.apis.inference import *  # noqa: F403
+
+# from llama_stack.providers.datatypes import ModelsProtocolPrivate
+from llama_stack.providers.utils.inference.model_registry import ModelRegistryHelper
+
+from llama_stack.providers.utils.inference.openai_compat import (
+    get_sampling_options,
+    process_chat_completion_response,
+    process_chat_completion_stream_response,
+)
+from llama_stack.providers.utils.inference.prompt_adapter import (
+    chat_completion_request_to_prompt,
+)
+
+from .config import RunpodImplConfig
+
+RUNPOD_SUPPORTED_MODELS = {
+    "Llama3.1-8B": "meta-llama/Llama-3.1-8B",
+    "Llama3.1-70B": "meta-llama/Llama-3.1-70B",
+    "Llama3.1-405B:bf16-mp8": "meta-llama/Llama-3.1-405B",
+    "Llama3.1-405B": "meta-llama/Llama-3.1-405B-FP8",
+    "Llama3.1-405B:bf16-mp16": "meta-llama/Llama-3.1-405B",
+    "Llama3.1-8B-Instruct": "meta-llama/Llama-3.1-8B-Instruct",
+    "Llama3.1-70B-Instruct": "meta-llama/Llama-3.1-70B-Instruct",
+    "Llama3.1-405B-Instruct:bf16-mp8": "meta-llama/Llama-3.1-405B-Instruct",
+    "Llama3.1-405B-Instruct": "meta-llama/Llama-3.1-405B-Instruct-FP8",
+    "Llama3.1-405B-Instruct:bf16-mp16": "meta-llama/Llama-3.1-405B-Instruct",
+    "Llama3.2-1B": "meta-llama/Llama-3.2-1B",
+    "Llama3.2-3B": "meta-llama/Llama-3.2-3B",
+}
+
+
+class RunpodInferenceAdapter(ModelRegistryHelper, Inference):
+    def __init__(self, config: RunpodImplConfig) -> None:
+        ModelRegistryHelper.__init__(
+            self, stack_to_provider_models_map=RUNPOD_SUPPORTED_MODELS
+        )
+        self.config = config
+        self.formatter = ChatFormat(Tokenizer.get_instance())
+
+    async def initialize(self) -> None:
+        return
+
+    async def shutdown(self) -> None:
+        pass
+
+    async def completion(
+        self,
+        model: str,
+        content: InterleavedTextMedia,
+        sampling_params: Optional[SamplingParams] = SamplingParams(),
+        response_format: Optional[ResponseFormat] = None,
+        stream: Optional[bool] = False,
+        logprobs: Optional[LogProbConfig] = None,
+    ) -> AsyncGenerator:
+        raise NotImplementedError()
+
+    async def chat_completion(
+        self,
+        model: str,
+        messages: List[Message],
+        sampling_params: Optional[SamplingParams] = SamplingParams(),
+        response_format: Optional[ResponseFormat] = None,
+        tools: Optional[List[ToolDefinition]] = None,
+        tool_choice: Optional[ToolChoice] = ToolChoice.auto,
+        tool_prompt_format: Optional[ToolPromptFormat] = ToolPromptFormat.json,
+        stream: Optional[bool] = False,
+        logprobs: Optional[LogProbConfig] = None,
+    ) -> AsyncGenerator:
+        request = ChatCompletionRequest(
+            model=model,
+            messages=messages,
+            sampling_params=sampling_params,
+            tools=tools or [],
+            tool_choice=tool_choice,
+            tool_prompt_format=tool_prompt_format,
+            stream=stream,
+            logprobs=logprobs,
+        )
+
+        client = OpenAI(base_url=self.config.url, api_key=self.config.api_token)
+        if stream:
+            return self._stream_chat_completion(request, client)
+        else:
+            return await self._nonstream_chat_completion(request, client)
+
+    async def _nonstream_chat_completion(
+        self, request: ChatCompletionRequest, client: OpenAI
+    ) -> ChatCompletionResponse:
+        params = self._get_params(request)
+        r = client.completions.create(**params)
+        return process_chat_completion_response(r, self.formatter)
+
+    async def _stream_chat_completion(
+        self, request: ChatCompletionRequest, client: OpenAI
+    ) -> AsyncGenerator:
+        params = self._get_params(request)
+
+        async def _to_async_generator():
+            s = client.completions.create(**params)
+            for chunk in s:
+                yield chunk
+
+        stream = _to_async_generator()
+        async for chunk in process_chat_completion_stream_response(
+            stream, self.formatter
+        ):
+            yield chunk
+
+    def _get_params(self, request: ChatCompletionRequest) -> dict:
+        return {
+            "model": self.map_to_provider_model(request.model),
+            "prompt": chat_completion_request_to_prompt(request, self.formatter),
+            "stream": request.stream,
+            **get_sampling_options(request.sampling_params),
+        }
+
+    async def embeddings(
+        self,
+        model: str,
+        contents: List[InterleavedTextMedia],
+    ) -> EmbeddingsResponse:
+        raise NotImplementedError()
diff --git a/llama_stack/providers/remote/inference/sambanova/__init__.py b/llama_stack/providers/remote/inference/sambanova/__init__.py
new file mode 100644
index 000000000..ab442066a
--- /dev/null
+++ b/llama_stack/providers/remote/inference/sambanova/__init__.py
@@ -0,0 +1,23 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from pydantic import BaseModel
+
+from .config import SambaNovaImplConfig
+from .sambanova import SambaNovaInferenceAdapter
+
+
+class SambaNovaProviderDataValidator(BaseModel):
+    sambanova_api_key: str
+
+
+async def get_adapter_impl(config: SambaNovaImplConfig, _deps):
+    assert isinstance(
+        config, SambaNovaImplConfig
+    ), f"Unexpected config type: {type(config)}"
+    impl = SambaNovaInferenceAdapter(config)
+    await impl.initialize()
+    return impl
diff --git a/llama_stack/providers/remote/inference/sambanova/config.py b/llama_stack/providers/remote/inference/sambanova/config.py
new file mode 100644
index 000000000..1798841df
--- /dev/null
+++ b/llama_stack/providers/remote/inference/sambanova/config.py
@@ -0,0 +1,29 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from typing import Any, Dict, Optional
+
+from llama_models.schema_utils import json_schema_type
+from pydantic import BaseModel, Field
+
+
+@json_schema_type
+class SambaNovaImplConfig(BaseModel):
+    url: str = Field(
+        default="https://api.sambanova.ai/v1",
+        description="The URL for the SambaNova AI server",
+    )
+    api_key: Optional[str] = Field(
+        default=None,
+        description="The SambaNova.ai API Key",
+    )
+
+    @classmethod
+    def sample_run_config(cls, **kwargs) -> Dict[str, Any]:
+        return {
+            "url": "https://api.sambanova.ai/v1",
+            "api_key": "${env.SAMBANOVA_API_KEY}",
+        }
diff --git a/llama_stack/providers/remote/inference/sambanova/sambanova.py b/llama_stack/providers/remote/inference/sambanova/sambanova.py
new file mode 100644
index 000000000..da446567a
--- /dev/null
+++ b/llama_stack/providers/remote/inference/sambanova/sambanova.py
@@ -0,0 +1,342 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+import json
+from typing import AsyncGenerator
+
+from llama_models.datatypes import (
+    CoreModelId,
+    GreedySamplingStrategy,
+    TopKSamplingStrategy,
+    TopPSamplingStrategy,
+)
+from llama_models.llama3.api.chat_format import ChatFormat
+from llama_models.llama3.api.tokenizer import Tokenizer
+from openai import OpenAI
+
+from llama_stack.apis.common.content_types import (
+    ImageContentItem,
+    InterleavedContent,
+    TextContentItem,
+)
+from llama_stack.apis.inference import *  # noqa: F403
+from llama_stack.providers.utils.inference.model_registry import (
+    build_model_alias,
+    ModelRegistryHelper,
+)
+from llama_stack.providers.utils.inference.openai_compat import (
+    process_chat_completion_stream_response,
+)
+from llama_stack.providers.utils.inference.prompt_adapter import (
+    convert_image_content_to_url,
+)
+
+from .config import SambaNovaImplConfig
+
+MODEL_ALIASES = [
+    build_model_alias(
+        "Meta-Llama-3.1-8B-Instruct",
+        CoreModelId.llama3_1_8b_instruct.value,
+    ),
+    build_model_alias(
+        "Meta-Llama-3.1-70B-Instruct",
+        CoreModelId.llama3_1_70b_instruct.value,
+    ),
+    build_model_alias(
+        "Meta-Llama-3.1-405B-Instruct",
+        CoreModelId.llama3_1_405b_instruct.value,
+    ),
+    build_model_alias(
+        "Meta-Llama-3.2-1B-Instruct",
+        CoreModelId.llama3_2_1b_instruct.value,
+    ),
+    build_model_alias(
+        "Meta-Llama-3.2-3B-Instruct",
+        CoreModelId.llama3_2_3b_instruct.value,
+    ),
+    build_model_alias(
+        "Llama-3.2-11B-Vision-Instruct",
+        CoreModelId.llama3_2_11b_vision_instruct.value,
+    ),
+    build_model_alias(
+        "Llama-3.2-90B-Vision-Instruct",
+        CoreModelId.llama3_2_90b_vision_instruct.value,
+    ),
+    build_model_alias(
+        "Meta-Llama-Guard-3-8B",
+        CoreModelId.llama_guard_3_8b.value,
+    ),
+]
+
+
+class SambaNovaInferenceAdapter(ModelRegistryHelper, Inference):
+    def __init__(self, config: SambaNovaImplConfig) -> None:
+        ModelRegistryHelper.__init__(
+            self,
+            model_aliases=MODEL_ALIASES,
+        )
+
+        self.config = config
+        self.formatter = ChatFormat(Tokenizer.get_instance())
+
+    async def initialize(self) -> None:
+        return
+
+    async def shutdown(self) -> None:
+        pass
+
+    def _get_client(self) -> OpenAI:
+        return OpenAI(base_url=self.config.url, api_key=self.config.api_key)
+
+    async def completion(
+        self,
+        model_id: str,
+        content: InterleavedContent,
+        sampling_params: Optional[SamplingParams] = SamplingParams(),
+        response_format: Optional[ResponseFormat] = None,
+        stream: Optional[bool] = False,
+        logprobs: Optional[LogProbConfig] = None,
+    ) -> AsyncGenerator:
+        raise NotImplementedError()
+
+    async def chat_completion(
+        self,
+        model_id: str,
+        messages: List[Message],
+        sampling_params: Optional[SamplingParams] = SamplingParams(),
+        response_format: Optional[ResponseFormat] = None,
+        tools: Optional[List[ToolDefinition]] = None,
+        tool_choice: Optional[ToolChoice] = ToolChoice.auto,
+        tool_prompt_format: Optional[ToolPromptFormat] = ToolPromptFormat.json,
+        stream: Optional[bool] = False,
+        logprobs: Optional[LogProbConfig] = None,
+    ) -> AsyncGenerator:
+        model = await self.model_store.get_model(model_id)
+
+        request = ChatCompletionRequest(
+            model=model.provider_resource_id,
+            messages=messages,
+            sampling_params=sampling_params,
+            tools=tools or [],
+            tool_choice=tool_choice,
+            tool_prompt_format=tool_prompt_format,
+            stream=stream,
+            logprobs=logprobs,
+        )
+        request_sambanova = await self.convert_chat_completion_request(request)
+
+        if stream:
+            return self._stream_chat_completion(request_sambanova)
+        else:
+            return await self._nonstream_chat_completion(request_sambanova)
+
+    async def _nonstream_chat_completion(
+        self, request: ChatCompletionRequest
+    ) -> ChatCompletionResponse:
+        response = self._get_client().chat.completions.create(**request)
+
+        choice = response.choices[0]
+
+        result = ChatCompletionResponse(
+            completion_message=CompletionMessage(
+                content=choice.message.content or "",
+                stop_reason=self.convert_to_sambanova_finish_reason(
+                    choice.finish_reason
+                ),
+                tool_calls=self.convert_to_sambanova_tool_calls(
+                    choice.message.tool_calls
+                ),
+            ),
+            logprobs=None,
+        )
+
+        return result
+
+    async def _stream_chat_completion(
+        self, request: ChatCompletionRequest
+    ) -> AsyncGenerator:
+        async def _to_async_generator():
+            streaming = self._get_client().chat.completions.create(**request)
+            for chunk in streaming:
+                yield chunk
+
+        stream = _to_async_generator()
+        async for chunk in process_chat_completion_stream_response(
+            stream, self.formatter
+        ):
+            yield chunk
+
+    async def embeddings(
+        self,
+        model_id: str,
+        contents: List[InterleavedContent],
+    ) -> EmbeddingsResponse:
+        raise NotImplementedError()
+
+    async def convert_chat_completion_request(
+        self, request: ChatCompletionRequest
+    ) -> dict:
+        compatible_request = self.convert_sampling_params(request.sampling_params)
+        compatible_request["model"] = request.model
+        compatible_request["messages"] = await self.convert_to_sambanova_messages(
+            request.messages
+        )
+        compatible_request["stream"] = request.stream
+        compatible_request["logprobs"] = False
+        compatible_request["extra_headers"] = {
+            b"User-Agent": b"llama-stack: sambanova-inference-adapter",
+        }
+        compatible_request["tools"] = self.convert_to_sambanova_tool(request.tools)
+        return compatible_request
+
+    def convert_sampling_params(
+        self, sampling_params: SamplingParams, legacy: bool = False
+    ) -> dict:
+        params = {}
+
+        if sampling_params:
+            params["frequency_penalty"] = sampling_params.repetition_penalty
+
+            if sampling_params.max_tokens:
+                if legacy:
+                    params["max_tokens"] = sampling_params.max_tokens
+                else:
+                    params["max_completion_tokens"] = sampling_params.max_tokens
+
+            if isinstance(sampling_params.strategy, TopPSamplingStrategy):
+                params["top_p"] = sampling_params.strategy.top_p
+            if isinstance(sampling_params.strategy, TopKSamplingStrategy):
+                params["extra_body"]["top_k"] = sampling_params.strategy.top_k
+            if isinstance(sampling_params.strategy, GreedySamplingStrategy):
+                params["temperature"] = 0.0
+
+        return params
+
+    async def convert_to_sambanova_messages(
+        self, messages: List[Message]
+    ) -> List[dict]:
+        conversation = []
+        for message in messages:
+            content = {}
+
+            content["content"] = await self.convert_to_sambanova_content(message)
+
+            if isinstance(message, UserMessage):
+                content["role"] = "user"
+            elif isinstance(message, CompletionMessage):
+                content["role"] = "assistant"
+                tools = []
+                for tool_call in message.tool_calls:
+                    tools.append(
+                        {
+                            "id": tool_call.call_id,
+                            "function": {
+                                "name": tool_call.name,
+                                "arguments": json.dumps(tool_call.arguments),
+                            },
+                            "type": "function",
+                        }
+                    )
+                content["tool_calls"] = tools
+            elif isinstance(message, ToolResponseMessage):
+                content["role"] = "tool"
+                content["tool_call_id"] = message.call_id
+            elif isinstance(message, SystemMessage):
+                content["role"] = "system"
+
+            conversation.append(content)
+
+        return conversation
+
+    async def convert_to_sambanova_content(self, message: Message) -> dict:
+        async def _convert_content(content) -> dict:
+            if isinstance(content, ImageContentItem):
+                url = await convert_image_content_to_url(content, download=True)
+                # A fix to make sure the call sucess.
+                components = url.split(";base64")
+                url = f"{components[0].lower()};base64{components[1]}"
+                return {
+                    "type": "image_url",
+                    "image_url": {"url": url},
+                }
+            else:
+                text = content.text if isinstance(content, TextContentItem) else content
+                assert isinstance(text, str)
+                return {"type": "text", "text": text}
+
+        if isinstance(message.content, list):
+            # If it is a list, the text content should be wrapped in dict
+            content = [await _convert_content(c) for c in message.content]
+        else:
+            content = message.content
+
+        return content
+
+    def convert_to_sambanova_tool(self, tools: List[ToolDefinition]) -> List[dict]:
+        if tools is None:
+            return tools
+
+        compatiable_tools = []
+
+        for tool in tools:
+            properties = {}
+            compatiable_required = []
+            if tool.parameters:
+                for tool_key, tool_param in tool.parameters.items():
+                    properties[tool_key] = {"type": tool_param.param_type}
+                    if tool_param.description:
+                        properties[tool_key]["description"] = tool_param.description
+                    if tool_param.default:
+                        properties[tool_key]["default"] = tool_param.default
+                    if tool_param.required:
+                        compatiable_required.append(tool_key)
+
+            compatiable_tool = {
+                "type": "function",
+                "function": {
+                    "name": tool.tool_name,
+                    "description": tool.description,
+                    "parameters": {
+                        "type": "object",
+                        "properties": properties,
+                        "required": compatiable_required,
+                    },
+                },
+            }
+
+            compatiable_tools.append(compatiable_tool)
+
+        if len(compatiable_tools) > 0:
+            return compatiable_tools
+        return None
+
+    def convert_to_sambanova_finish_reason(self, finish_reason: str) -> StopReason:
+        return {
+            "stop": StopReason.end_of_turn,
+            "length": StopReason.out_of_tokens,
+            "tool_calls": StopReason.end_of_message,
+        }.get(finish_reason, StopReason.end_of_turn)
+
+    def convert_to_sambanova_tool_calls(
+        self,
+        tool_calls,
+    ) -> List[ToolCall]:
+        if not tool_calls:
+            return []
+
+        for call in tool_calls:
+            call_function_arguments = json.loads(call.function.arguments)
+
+        compitable_tool_calls = [
+            ToolCall(
+                call_id=call.id,
+                tool_name=call.function.name,
+                arguments=call_function_arguments,
+            )
+            for call in tool_calls
+        ]
+
+        return compitable_tool_calls
diff --git a/llama_stack/providers/remote/inference/vllm/vllm.py b/llama_stack/providers/remote/inference/vllm/vllm.py
index 317d05207..0cf16f013 100644
--- a/llama_stack/providers/remote/inference/vllm/vllm.py
+++ b/llama_stack/providers/remote/inference/vllm/vllm.py
@@ -41,6 +41,8 @@ from llama_stack.providers.utils.inference.openai_compat import (
     get_sampling_options,
     process_chat_completion_response,
     process_chat_completion_stream_response,
+    process_completion_response,
+    process_completion_stream_response,
 )
 from llama_stack.providers.utils.inference.prompt_adapter import (
     chat_completion_request_to_prompt,
@@ -92,7 +94,19 @@ class VLLMInferenceAdapter(Inference, ModelsProtocolPrivate):
         stream: Optional[bool] = False,
         logprobs: Optional[LogProbConfig] = None,
     ) -> Union[CompletionResponse, CompletionResponseStreamChunk]:
-        raise NotImplementedError("Completion not implemented for vLLM")
+        model = await self.model_store.get_model(model_id)
+        request = CompletionRequest(
+            model=model.provider_resource_id,
+            content=content,
+            sampling_params=sampling_params,
+            response_format=response_format,
+            stream=stream,
+            logprobs=logprobs,
+        )
+        if stream:
+            return self._stream_completion(request)
+        else:
+            return await self._nonstream_completion(request)
 
     async def chat_completion(
         self,
@@ -154,6 +168,26 @@ class VLLMInferenceAdapter(Inference, ModelsProtocolPrivate):
         ):
             yield chunk
 
+    async def _nonstream_completion(
+        self, request: CompletionRequest
+    ) -> CompletionResponse:
+        params = await self._get_params(request)
+        r = self.client.completions.create(**params)
+        return process_completion_response(r, self.formatter)
+
+    async def _stream_completion(self, request: CompletionRequest) -> AsyncGenerator:
+        params = await self._get_params(request)
+
+        # Wrapper for async generator similar
+        async def _to_async_generator():
+            stream = self.client.completions.create(**params)
+            for chunk in stream:
+                yield chunk
+
+        stream = _to_async_generator()
+        async for chunk in process_completion_stream_response(stream, self.formatter):
+            yield chunk
+
     async def register_model(self, model: Model) -> Model:
         model = await self.register_helper.register_model(model)
         res = self.client.models.list()
@@ -176,7 +210,6 @@ class VLLMInferenceAdapter(Inference, ModelsProtocolPrivate):
         media_present = request_has_media(request)
         if isinstance(request, ChatCompletionRequest):
             if media_present:
-                # vllm does not seem to work well with image urls, so we download the images
                 input_dict["messages"] = [
                     await convert_message_to_openai_dict(m, download=True)
                     for m in request.messages
diff --git a/llama_stack/providers/remote/tool_runtime/bing_search/bing_search.py b/llama_stack/providers/remote/tool_runtime/bing_search/bing_search.py
index 5114e06aa..677e29c12 100644
--- a/llama_stack/providers/remote/tool_runtime/bing_search/bing_search.py
+++ b/llama_stack/providers/remote/tool_runtime/bing_search/bing_search.py
@@ -68,7 +68,7 @@ class BingSearchToolRuntimeImpl(
         ]
 
     async def invoke_tool(
-        self, tool_name: str, args: Dict[str, Any]
+        self, tool_name: str, kwargs: Dict[str, Any]
     ) -> ToolInvocationResult:
         api_key = self._get_api_key()
         headers = {
@@ -78,7 +78,7 @@ class BingSearchToolRuntimeImpl(
             "count": self.config.top_k,
             "textDecorations": True,
             "textFormat": "HTML",
-            "q": args["query"],
+            "q": kwargs["query"],
         }
 
         response = requests.get(
diff --git a/llama_stack/providers/remote/tool_runtime/brave_search/brave_search.py b/llama_stack/providers/remote/tool_runtime/brave_search/brave_search.py
index 016f746ea..1162cc900 100644
--- a/llama_stack/providers/remote/tool_runtime/brave_search/brave_search.py
+++ b/llama_stack/providers/remote/tool_runtime/brave_search/brave_search.py
@@ -68,7 +68,7 @@ class BraveSearchToolRuntimeImpl(
         ]
 
     async def invoke_tool(
-        self, tool_name: str, args: Dict[str, Any]
+        self, tool_name: str, kwargs: Dict[str, Any]
     ) -> ToolInvocationResult:
         api_key = self._get_api_key()
         url = "https://api.search.brave.com/res/v1/web/search"
@@ -77,7 +77,7 @@ class BraveSearchToolRuntimeImpl(
             "Accept-Encoding": "gzip",
             "Accept": "application/json",
         }
-        payload = {"q": args["query"]}
+        payload = {"q": kwargs["query"]}
         response = requests.get(url=url, params=payload, headers=headers)
         response.raise_for_status()
         results = self._clean_brave_response(response.json())
diff --git a/llama_stack/providers/remote/tool_runtime/model_context_protocol/model_context_protocol.py b/llama_stack/providers/remote/tool_runtime/model_context_protocol/model_context_protocol.py
index a304167e9..e0caec1d0 100644
--- a/llama_stack/providers/remote/tool_runtime/model_context_protocol/model_context_protocol.py
+++ b/llama_stack/providers/remote/tool_runtime/model_context_protocol/model_context_protocol.py
@@ -65,7 +65,7 @@ class ModelContextProtocolToolRuntimeImpl(ToolsProtocolPrivate, ToolRuntime):
         return tools
 
     async def invoke_tool(
-        self, tool_name: str, args: Dict[str, Any]
+        self, tool_name: str, kwargs: Dict[str, Any]
     ) -> ToolInvocationResult:
         tool = await self.tool_store.get_tool(tool_name)
         if tool.metadata is None or tool.metadata.get("endpoint") is None:
@@ -77,7 +77,7 @@ class ModelContextProtocolToolRuntimeImpl(ToolsProtocolPrivate, ToolRuntime):
         async with sse_client(endpoint) as streams:
             async with ClientSession(*streams) as session:
                 await session.initialize()
-                result = await session.call_tool(tool.identifier, args)
+                result = await session.call_tool(tool.identifier, kwargs)
 
         return ToolInvocationResult(
             content="\n".join([result.model_dump_json() for result in result.content]),
diff --git a/llama_stack/providers/remote/tool_runtime/tavily_search/tavily_search.py b/llama_stack/providers/remote/tool_runtime/tavily_search/tavily_search.py
index 82077193e..f5826c0ff 100644
--- a/llama_stack/providers/remote/tool_runtime/tavily_search/tavily_search.py
+++ b/llama_stack/providers/remote/tool_runtime/tavily_search/tavily_search.py
@@ -67,12 +67,12 @@ class TavilySearchToolRuntimeImpl(
         ]
 
     async def invoke_tool(
-        self, tool_name: str, args: Dict[str, Any]
+        self, tool_name: str, kwargs: Dict[str, Any]
     ) -> ToolInvocationResult:
         api_key = self._get_api_key()
         response = requests.post(
             "https://api.tavily.com/search",
-            json={"api_key": api_key, "query": args["query"]},
+            json={"api_key": api_key, "query": kwargs["query"]},
         )
 
         return ToolInvocationResult(
diff --git a/llama_stack/providers/remote/tool_runtime/wolfram_alpha/wolfram_alpha.py b/llama_stack/providers/remote/tool_runtime/wolfram_alpha/wolfram_alpha.py
index 04ecfcc15..bf298c13e 100644
--- a/llama_stack/providers/remote/tool_runtime/wolfram_alpha/wolfram_alpha.py
+++ b/llama_stack/providers/remote/tool_runtime/wolfram_alpha/wolfram_alpha.py
@@ -68,11 +68,11 @@ class WolframAlphaToolRuntimeImpl(
         ]
 
     async def invoke_tool(
-        self, tool_name: str, args: Dict[str, Any]
+        self, tool_name: str, kwargs: Dict[str, Any]
     ) -> ToolInvocationResult:
         api_key = self._get_api_key()
         params = {
-            "input": args["query"],
+            "input": kwargs["query"],
             "appid": api_key,
             "format": "plaintext",
             "output": "json",
diff --git a/llama_stack/providers/remote/memory/__init__.py b/llama_stack/providers/remote/vector_io/__init__.py
similarity index 100%
rename from llama_stack/providers/remote/memory/__init__.py
rename to llama_stack/providers/remote/vector_io/__init__.py
diff --git a/llama_stack/providers/remote/memory/chroma/__init__.py b/llama_stack/providers/remote/vector_io/chroma/__init__.py
similarity index 81%
rename from llama_stack/providers/remote/memory/chroma/__init__.py
rename to llama_stack/providers/remote/vector_io/chroma/__init__.py
index 581d60e75..d66a93ac7 100644
--- a/llama_stack/providers/remote/memory/chroma/__init__.py
+++ b/llama_stack/providers/remote/vector_io/chroma/__init__.py
@@ -14,8 +14,8 @@ from .config import ChromaRemoteImplConfig
 async def get_adapter_impl(
     config: ChromaRemoteImplConfig, deps: Dict[Api, ProviderSpec]
 ):
-    from .chroma import ChromaMemoryAdapter
+    from .chroma import ChromaVectorIOAdapter
 
-    impl = ChromaMemoryAdapter(config, deps[Api.inference])
+    impl = ChromaVectorIOAdapter(config, deps[Api.inference])
     await impl.initialize()
     return impl
diff --git a/llama_stack/providers/remote/memory/chroma/chroma.py b/llama_stack/providers/remote/vector_io/chroma/chroma.py
similarity index 62%
rename from llama_stack/providers/remote/memory/chroma/chroma.py
rename to llama_stack/providers/remote/vector_io/chroma/chroma.py
index c04d775ca..724dc3f51 100644
--- a/llama_stack/providers/remote/memory/chroma/chroma.py
+++ b/llama_stack/providers/remote/vector_io/chroma/chroma.py
@@ -6,25 +6,20 @@
 import asyncio
 import json
 import logging
-from typing import List, Optional, Union
+from typing import Any, Dict, List, Optional, Union
 from urllib.parse import urlparse
 
 import chromadb
 from numpy.typing import NDArray
 
 from llama_stack.apis.inference import InterleavedContent
-from llama_stack.apis.memory import (
-    Chunk,
-    Memory,
-    MemoryBankDocument,
-    QueryDocumentsResponse,
-)
-from llama_stack.apis.memory_banks import MemoryBank, MemoryBankType
-from llama_stack.providers.datatypes import Api, MemoryBanksProtocolPrivate
-from llama_stack.providers.inline.memory.chroma import ChromaInlineImplConfig
+from llama_stack.apis.vector_dbs import VectorDB
+from llama_stack.apis.vector_io import Chunk, QueryChunksResponse, VectorIO
+from llama_stack.providers.datatypes import Api, VectorDBsProtocolPrivate
+from llama_stack.providers.inline.vector_io.chroma import ChromaInlineImplConfig
 from llama_stack.providers.utils.memory.vector_store import (
-    BankWithIndex,
     EmbeddingIndex,
+    VectorDBWithIndex,
 )
 from .config import ChromaRemoteImplConfig
 
@@ -61,7 +56,7 @@ class ChromaIndex(EmbeddingIndex):
 
     async def query(
         self, embedding: NDArray, k: int, score_threshold: float
-    ) -> QueryDocumentsResponse:
+    ) -> QueryChunksResponse:
         results = await maybe_await(
             self.collection.query(
                 query_embeddings=[embedding.tolist()],
@@ -85,19 +80,19 @@ class ChromaIndex(EmbeddingIndex):
             chunks.append(chunk)
             scores.append(1.0 / float(dist))
 
-        return QueryDocumentsResponse(chunks=chunks, scores=scores)
+        return QueryChunksResponse(chunks=chunks, scores=scores)
 
     async def delete(self):
         await maybe_await(self.client.delete_collection(self.collection.name))
 
 
-class ChromaMemoryAdapter(Memory, MemoryBanksProtocolPrivate):
+class ChromaVectorIOAdapter(VectorIO, VectorDBsProtocolPrivate):
     def __init__(
         self,
         config: Union[ChromaRemoteImplConfig, ChromaInlineImplConfig],
         inference_api: Api.inference,
     ) -> None:
-        log.info(f"Initializing ChromaMemoryAdapter with url: {config}")
+        log.info(f"Initializing ChromaVectorIOAdapter with url: {config}")
         self.config = config
         self.inference_api = inference_api
 
@@ -123,60 +118,58 @@ class ChromaMemoryAdapter(Memory, MemoryBanksProtocolPrivate):
     async def shutdown(self) -> None:
         pass
 
-    async def register_memory_bank(
+    async def register_vector_db(
         self,
-        memory_bank: MemoryBank,
+        vector_db: VectorDB,
     ) -> None:
-        assert (
-            memory_bank.memory_bank_type == MemoryBankType.vector.value
-        ), f"Only vector banks are supported {memory_bank.memory_bank_type}"
-
         collection = await maybe_await(
             self.client.get_or_create_collection(
-                name=memory_bank.identifier,
-                metadata={"bank": memory_bank.model_dump_json()},
+                name=vector_db.identifier,
+                metadata={"vector_db": vector_db.model_dump_json()},
             )
         )
-        self.cache[memory_bank.identifier] = BankWithIndex(
-            memory_bank, ChromaIndex(self.client, collection), self.inference_api
+        self.cache[vector_db.identifier] = VectorDBWithIndex(
+            vector_db, ChromaIndex(self.client, collection), self.inference_api
         )
 
-    async def unregister_memory_bank(self, memory_bank_id: str) -> None:
-        await self.cache[memory_bank_id].index.delete()
-        del self.cache[memory_bank_id]
+    async def unregister_vector_db(self, vector_db_id: str) -> None:
+        await self.cache[vector_db_id].index.delete()
+        del self.cache[vector_db_id]
 
-    async def insert_documents(
+    async def insert_chunks(
         self,
-        bank_id: str,
-        documents: List[MemoryBankDocument],
-        ttl_seconds: Optional[int] = None,
+        vector_db_id: str,
+        chunks: List[Chunk],
+        embeddings: NDArray,
     ) -> None:
-        index = await self._get_and_cache_bank_index(bank_id)
+        index = await self._get_and_cache_vector_db_index(vector_db_id)
 
-        await index.insert_documents(documents)
+        await index.insert_chunks(chunks, embeddings)
 
-    async def query_documents(
+    async def query_chunks(
         self,
-        bank_id: str,
+        vector_db_id: str,
         query: InterleavedContent,
         params: Optional[Dict[str, Any]] = None,
-    ) -> QueryDocumentsResponse:
-        index = await self._get_and_cache_bank_index(bank_id)
+    ) -> QueryChunksResponse:
+        index = await self._get_and_cache_vector_db_index(vector_db_id)
 
-        return await index.query_documents(query, params)
+        return await index.query_chunks(query, params)
 
-    async def _get_and_cache_bank_index(self, bank_id: str) -> BankWithIndex:
-        if bank_id in self.cache:
-            return self.cache[bank_id]
+    async def _get_and_cache_vector_db_index(
+        self, vector_db_id: str
+    ) -> VectorDBWithIndex:
+        if vector_db_id in self.cache:
+            return self.cache[vector_db_id]
 
-        bank = await self.memory_bank_store.get_memory_bank(bank_id)
-        if not bank:
-            raise ValueError(f"Bank {bank_id} not found in Llama Stack")
-        collection = await maybe_await(self.client.get_collection(bank_id))
+        vector_db = await self.vector_db_store.get_vector_db(vector_db_id)
+        if not vector_db:
+            raise ValueError(f"Vector DB {vector_db_id} not found in Llama Stack")
+        collection = await maybe_await(self.client.get_collection(vector_db_id))
         if not collection:
-            raise ValueError(f"Bank {bank_id} not found in Chroma")
-        index = BankWithIndex(
-            bank, ChromaIndex(self.client, collection), self.inference_api
+            raise ValueError(f"Vector DB {vector_db_id} not found in Chroma")
+        index = VectorDBWithIndex(
+            vector_db, ChromaIndex(self.client, collection), self.inference_api
         )
-        self.cache[bank_id] = index
+        self.cache[vector_db_id] = index
         return index
diff --git a/llama_stack/providers/remote/memory/chroma/config.py b/llama_stack/providers/remote/vector_io/chroma/config.py
similarity index 100%
rename from llama_stack/providers/remote/memory/chroma/config.py
rename to llama_stack/providers/remote/vector_io/chroma/config.py
diff --git a/llama_stack/providers/remote/memory/pgvector/__init__.py b/llama_stack/providers/remote/vector_io/pgvector/__init__.py
similarity index 100%
rename from llama_stack/providers/remote/memory/pgvector/__init__.py
rename to llama_stack/providers/remote/vector_io/pgvector/__init__.py
diff --git a/llama_stack/providers/remote/memory/pgvector/config.py b/llama_stack/providers/remote/vector_io/pgvector/config.py
similarity index 100%
rename from llama_stack/providers/remote/memory/pgvector/config.py
rename to llama_stack/providers/remote/vector_io/pgvector/config.py
diff --git a/llama_stack/providers/remote/memory/pgvector/pgvector.py b/llama_stack/providers/remote/vector_io/pgvector/pgvector.py
similarity index 66%
rename from llama_stack/providers/remote/memory/pgvector/pgvector.py
rename to llama_stack/providers/remote/vector_io/pgvector/pgvector.py
index b2c720b2c..3605f038c 100644
--- a/llama_stack/providers/remote/memory/pgvector/pgvector.py
+++ b/llama_stack/providers/remote/vector_io/pgvector/pgvector.py
@@ -12,21 +12,16 @@ from numpy.typing import NDArray
 from psycopg2 import sql
 from psycopg2.extras import execute_values, Json
 
-from pydantic import BaseModel, parse_obj_as
+from pydantic import BaseModel, TypeAdapter
 
 from llama_stack.apis.inference import InterleavedContent
-from llama_stack.apis.memory import (
-    Chunk,
-    Memory,
-    MemoryBankDocument,
-    QueryDocumentsResponse,
-)
-from llama_stack.apis.memory_banks import MemoryBank, MemoryBankType, VectorMemoryBank
-from llama_stack.providers.datatypes import Api, MemoryBanksProtocolPrivate
+from llama_stack.apis.vector_dbs import VectorDB
+from llama_stack.apis.vector_io import Chunk, QueryChunksResponse, VectorIO
+from llama_stack.providers.datatypes import Api, VectorDBsProtocolPrivate
 
 from llama_stack.providers.utils.memory.vector_store import (
-    BankWithIndex,
     EmbeddingIndex,
+    VectorDBWithIndex,
 )
 
 from .config import PGVectorConfig
@@ -50,20 +45,20 @@ def upsert_models(cur, keys_models: List[Tuple[str, BaseModel]]):
     """
     )
 
-    values = [(key, Json(model.dict())) for key, model in keys_models]
+    values = [(key, Json(model.model_dump())) for key, model in keys_models]
     execute_values(cur, query, values, template="(%s, %s)")
 
 
 def load_models(cur, cls):
     cur.execute("SELECT key, data FROM metadata_store")
     rows = cur.fetchall()
-    return [parse_obj_as(cls, row["data"]) for row in rows]
+    return [TypeAdapter(cls).validate_python(row["data"]) for row in rows]
 
 
 class PGVectorIndex(EmbeddingIndex):
-    def __init__(self, bank: VectorMemoryBank, dimension: int, cursor):
+    def __init__(self, vector_db: VectorDB, dimension: int, cursor):
         self.cursor = cursor
-        self.table_name = f"vector_store_{bank.identifier}"
+        self.table_name = f"vector_store_{vector_db.identifier}"
 
         self.cursor.execute(
             f"""
@@ -85,7 +80,7 @@ class PGVectorIndex(EmbeddingIndex):
             values.append(
                 (
                     f"{chunk.document_id}:chunk-{i}",
-                    Json(chunk.dict()),
+                    Json(chunk.model_dump()),
                     embeddings[i].tolist(),
                 )
             )
@@ -101,7 +96,7 @@ class PGVectorIndex(EmbeddingIndex):
 
     async def query(
         self, embedding: NDArray, k: int, score_threshold: float
-    ) -> QueryDocumentsResponse:
+    ) -> QueryChunksResponse:
         self.cursor.execute(
             f"""
         SELECT document, embedding <-> %s::vector AS distance
@@ -119,13 +114,13 @@ class PGVectorIndex(EmbeddingIndex):
             chunks.append(Chunk(**doc))
             scores.append(1.0 / float(dist))
 
-        return QueryDocumentsResponse(chunks=chunks, scores=scores)
+        return QueryChunksResponse(chunks=chunks, scores=scores)
 
     async def delete(self):
         self.cursor.execute(f"DROP TABLE IF EXISTS {self.table_name}")
 
 
-class PGVectorMemoryAdapter(Memory, MemoryBanksProtocolPrivate):
+class PGVectorVectorDBAdapter(VectorIO, VectorDBsProtocolPrivate):
     def __init__(self, config: PGVectorConfig, inference_api: Api.inference) -> None:
         self.config = config
         self.inference_api = inference_api
@@ -167,46 +162,45 @@ class PGVectorMemoryAdapter(Memory, MemoryBanksProtocolPrivate):
     async def shutdown(self) -> None:
         pass
 
-    async def register_memory_bank(self, memory_bank: MemoryBank) -> None:
-        assert (
-            memory_bank.memory_bank_type == MemoryBankType.vector.value
-        ), f"Only vector banks are supported {memory_bank.memory_bank_type}"
+    async def register_vector_db(self, vector_db: VectorDB) -> None:
+        upsert_models(self.cursor, [(vector_db.identifier, vector_db)])
 
-        upsert_models(self.cursor, [(memory_bank.identifier, memory_bank)])
-        index = PGVectorIndex(memory_bank, memory_bank.embedding_dimension, self.cursor)
-        self.cache[memory_bank.identifier] = BankWithIndex(
-            memory_bank, index, self.inference_api
+        index = PGVectorIndex(vector_db, vector_db.embedding_dimension, self.cursor)
+        self.cache[vector_db.identifier] = VectorDBWithIndex(
+            vector_db, index, self.inference_api
         )
 
-    async def unregister_memory_bank(self, memory_bank_id: str) -> None:
-        await self.cache[memory_bank_id].index.delete()
-        del self.cache[memory_bank_id]
+    async def unregister_vector_db(self, vector_db_id: str) -> None:
+        await self.cache[vector_db_id].index.delete()
+        del self.cache[vector_db_id]
 
-    async def insert_documents(
+    async def insert_chunks(
         self,
-        bank_id: str,
-        documents: List[MemoryBankDocument],
+        vector_db_id: str,
+        chunks: List[Chunk],
         ttl_seconds: Optional[int] = None,
     ) -> None:
-        index = await self._get_and_cache_bank_index(bank_id)
-        await index.insert_documents(documents)
+        index = await self._get_and_cache_vector_db_index(vector_db_id)
+        await index.insert_chunks(chunks)
 
-    async def query_documents(
+    async def query_chunks(
         self,
-        bank_id: str,
+        vector_db_id: str,
         query: InterleavedContent,
         params: Optional[Dict[str, Any]] = None,
-    ) -> QueryDocumentsResponse:
-        index = await self._get_and_cache_bank_index(bank_id)
-        return await index.query_documents(query, params)
+    ) -> QueryChunksResponse:
+        index = await self._get_and_cache_vector_db_index(vector_db_id)
+        return await index.query_chunks(query, params)
 
-        self.inference_api = inference_api
+    async def _get_and_cache_vector_db_index(
+        self, vector_db_id: str
+    ) -> VectorDBWithIndex:
+        if vector_db_id in self.cache:
+            return self.cache[vector_db_id]
 
-    async def _get_and_cache_bank_index(self, bank_id: str) -> BankWithIndex:
-        if bank_id in self.cache:
-            return self.cache[bank_id]
-
-        bank = await self.memory_bank_store.get_memory_bank(bank_id)
-        index = PGVectorIndex(bank, bank.embedding_dimension, self.cursor)
-        self.cache[bank_id] = BankWithIndex(bank, index, self.inference_api)
-        return self.cache[bank_id]
+        vector_db = await self.vector_db_store.get_vector_db(vector_db_id)
+        index = PGVectorIndex(vector_db, vector_db.embedding_dimension, self.cursor)
+        self.cache[vector_db_id] = VectorDBWithIndex(
+            vector_db, index, self.inference_api
+        )
+        return self.cache[vector_db_id]
diff --git a/llama_stack/providers/remote/memory/qdrant/__init__.py b/llama_stack/providers/remote/vector_io/qdrant/__init__.py
similarity index 100%
rename from llama_stack/providers/remote/memory/qdrant/__init__.py
rename to llama_stack/providers/remote/vector_io/qdrant/__init__.py
diff --git a/llama_stack/providers/remote/memory/qdrant/config.py b/llama_stack/providers/remote/vector_io/qdrant/config.py
similarity index 100%
rename from llama_stack/providers/remote/memory/qdrant/config.py
rename to llama_stack/providers/remote/vector_io/qdrant/config.py
diff --git a/llama_stack/providers/remote/memory/qdrant/qdrant.py b/llama_stack/providers/remote/vector_io/qdrant/qdrant.py
similarity index 67%
rename from llama_stack/providers/remote/memory/qdrant/qdrant.py
rename to llama_stack/providers/remote/vector_io/qdrant/qdrant.py
index b1d5bd7fa..d3257b4c9 100644
--- a/llama_stack/providers/remote/memory/qdrant/qdrant.py
+++ b/llama_stack/providers/remote/vector_io/qdrant/qdrant.py
@@ -13,19 +13,14 @@ from qdrant_client import AsyncQdrantClient, models
 from qdrant_client.models import PointStruct
 
 from llama_stack.apis.inference import InterleavedContent
-from llama_stack.apis.memory import (
-    Chunk,
-    Memory,
-    MemoryBankDocument,
-    QueryDocumentsResponse,
-)
-from llama_stack.apis.memory_banks import MemoryBank, MemoryBankType
-from llama_stack.providers.datatypes import Api, MemoryBanksProtocolPrivate
-from llama_stack.providers.remote.memory.qdrant.config import QdrantConfig
+from llama_stack.apis.vector_dbs import VectorDB
+from llama_stack.apis.vector_io import Chunk, QueryChunksResponse, VectorIO
+from llama_stack.providers.datatypes import Api, VectorDBsProtocolPrivate
 from llama_stack.providers.utils.memory.vector_store import (
-    BankWithIndex,
     EmbeddingIndex,
+    VectorDBWithIndex,
 )
+from .config import QdrantConfig
 
 log = logging.getLogger(__name__)
 CHUNK_ID_KEY = "_chunk_id"
@@ -76,7 +71,7 @@ class QdrantIndex(EmbeddingIndex):
 
     async def query(
         self, embedding: NDArray, k: int, score_threshold: float
-    ) -> QueryDocumentsResponse:
+    ) -> QueryChunksResponse:
         results = (
             await self.client.query_points(
                 collection_name=self.collection_name,
@@ -101,10 +96,10 @@ class QdrantIndex(EmbeddingIndex):
             chunks.append(chunk)
             scores.append(point.score)
 
-        return QueryDocumentsResponse(chunks=chunks, scores=scores)
+        return QueryChunksResponse(chunks=chunks, scores=scores)
 
 
-class QdrantVectorMemoryAdapter(Memory, MemoryBanksProtocolPrivate):
+class QdrantVectorDBAdapter(VectorIO, VectorDBsProtocolPrivate):
     def __init__(self, config: QdrantConfig, inference_api: Api.inference) -> None:
         self.config = config
         self.client = AsyncQdrantClient(**self.config.model_dump(exclude_none=True))
@@ -117,58 +112,56 @@ class QdrantVectorMemoryAdapter(Memory, MemoryBanksProtocolPrivate):
     async def shutdown(self) -> None:
         self.client.close()
 
-    async def register_memory_bank(
+    async def register_vector_db(
         self,
-        memory_bank: MemoryBank,
+        vector_db: VectorDB,
     ) -> None:
-        assert (
-            memory_bank.memory_bank_type == MemoryBankType.vector
-        ), f"Only vector banks are supported {memory_bank.memory_bank_type}"
-
-        index = BankWithIndex(
-            bank=memory_bank,
-            index=QdrantIndex(self.client, memory_bank.identifier),
+        index = VectorDBWithIndex(
+            vector_db=vector_db,
+            index=QdrantIndex(self.client, vector_db.identifier),
             inference_api=self.inference_api,
         )
 
-        self.cache[memory_bank.identifier] = index
+        self.cache[vector_db.identifier] = index
 
-    async def _get_and_cache_bank_index(self, bank_id: str) -> Optional[BankWithIndex]:
-        if bank_id in self.cache:
-            return self.cache[bank_id]
+    async def _get_and_cache_vector_db_index(
+        self, vector_db_id: str
+    ) -> Optional[VectorDBWithIndex]:
+        if vector_db_id in self.cache:
+            return self.cache[vector_db_id]
 
-        bank = await self.memory_bank_store.get_memory_bank(bank_id)
-        if not bank:
-            raise ValueError(f"Bank {bank_id} not found")
+        vector_db = await self.vector_db_store.get_vector_db(vector_db_id)
+        if not vector_db:
+            raise ValueError(f"Vector DB {vector_db_id} not found")
 
-        index = BankWithIndex(
-            bank=bank,
-            index=QdrantIndex(client=self.client, collection_name=bank_id),
+        index = VectorDBWithIndex(
+            vector_db=vector_db,
+            index=QdrantIndex(client=self.client, collection_name=vector_db.identifier),
             inference_api=self.inference_api,
         )
-        self.cache[bank_id] = index
+        self.cache[vector_db_id] = index
         return index
 
-    async def insert_documents(
+    async def insert_chunks(
         self,
-        bank_id: str,
-        documents: List[MemoryBankDocument],
+        vector_db_id: str,
+        chunks: List[Chunk],
         ttl_seconds: Optional[int] = None,
     ) -> None:
-        index = await self._get_and_cache_bank_index(bank_id)
+        index = await self._get_and_cache_vector_db_index(vector_db_id)
         if not index:
-            raise ValueError(f"Bank {bank_id} not found")
+            raise ValueError(f"Vector DB {vector_db_id} not found")
 
-        await index.insert_documents(documents)
+        await index.insert_chunks(chunks)
 
-    async def query_documents(
+    async def query_chunks(
         self,
-        bank_id: str,
+        vector_db_id: str,
         query: InterleavedContent,
         params: Optional[Dict[str, Any]] = None,
-    ) -> QueryDocumentsResponse:
-        index = await self._get_and_cache_bank_index(bank_id)
+    ) -> QueryChunksResponse:
+        index = await self._get_and_cache_vector_db_index(vector_db_id)
         if not index:
-            raise ValueError(f"Bank {bank_id} not found")
+            raise ValueError(f"Vector DB {vector_db_id} not found")
 
-        return await index.query_documents(query, params)
+        return await index.query_chunks(query, params)
diff --git a/llama_stack/providers/remote/memory/sample/__init__.py b/llama_stack/providers/remote/vector_io/sample/__init__.py
similarity index 100%
rename from llama_stack/providers/remote/memory/sample/__init__.py
rename to llama_stack/providers/remote/vector_io/sample/__init__.py
diff --git a/llama_stack/providers/remote/memory/sample/config.py b/llama_stack/providers/remote/vector_io/sample/config.py
similarity index 100%
rename from llama_stack/providers/remote/memory/sample/config.py
rename to llama_stack/providers/remote/vector_io/sample/config.py
diff --git a/llama_stack/providers/remote/memory/sample/sample.py b/llama_stack/providers/remote/vector_io/sample/sample.py
similarity index 55%
rename from llama_stack/providers/remote/memory/sample/sample.py
rename to llama_stack/providers/remote/vector_io/sample/sample.py
index b051eb544..e311be39d 100644
--- a/llama_stack/providers/remote/memory/sample/sample.py
+++ b/llama_stack/providers/remote/vector_io/sample/sample.py
@@ -4,19 +4,22 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-from llama_stack.apis.memory import Memory
-from llama_stack.apis.memory_banks import MemoryBank
+from llama_stack.apis.vector_dbs import VectorDB
+from llama_stack.apis.vector_io import VectorIO
 from .config import SampleConfig
 
 
-class SampleMemoryImpl(Memory):
+class SampleMemoryImpl(VectorIO):
     def __init__(self, config: SampleConfig):
         self.config = config
 
-    async def register_memory_bank(self, memory_bank: MemoryBank) -> None:
-        # these are the memory banks the Llama Stack will use to route requests to this provider
+    async def register_vector_db(self, vector_db: VectorDB) -> None:
+        # these are the vector dbs the Llama Stack will use to route requests to this provider
         # perform validation here if necessary
         pass
 
     async def initialize(self):
         pass
+
+    async def shutdown(self):
+        pass
diff --git a/llama_stack/providers/remote/memory/weaviate/__init__.py b/llama_stack/providers/remote/vector_io/weaviate/__init__.py
similarity index 100%
rename from llama_stack/providers/remote/memory/weaviate/__init__.py
rename to llama_stack/providers/remote/vector_io/weaviate/__init__.py
diff --git a/llama_stack/providers/remote/memory/weaviate/config.py b/llama_stack/providers/remote/vector_io/weaviate/config.py
similarity index 100%
rename from llama_stack/providers/remote/memory/weaviate/config.py
rename to llama_stack/providers/remote/vector_io/weaviate/config.py
diff --git a/llama_stack/providers/remote/memory/weaviate/weaviate.py b/llama_stack/providers/remote/vector_io/weaviate/weaviate.py
similarity index 68%
rename from llama_stack/providers/remote/memory/weaviate/weaviate.py
rename to llama_stack/providers/remote/vector_io/weaviate/weaviate.py
index f1433090d..ea9ce5185 100644
--- a/llama_stack/providers/remote/memory/weaviate/weaviate.py
+++ b/llama_stack/providers/remote/vector_io/weaviate/weaviate.py
@@ -15,18 +15,13 @@ from weaviate.classes.init import Auth
 from weaviate.classes.query import Filter
 
 from llama_stack.apis.common.content_types import InterleavedContent
-from llama_stack.apis.memory import (
-    Chunk,
-    Memory,
-    MemoryBankDocument,
-    QueryDocumentsResponse,
-)
-from llama_stack.apis.memory_banks import MemoryBank, MemoryBankType
+from llama_stack.apis.vector_dbs import VectorDB
+from llama_stack.apis.vector_io import Chunk, QueryChunksResponse, VectorIO
 from llama_stack.distribution.request_headers import NeedsRequestProviderData
-from llama_stack.providers.datatypes import Api, MemoryBanksProtocolPrivate
+from llama_stack.providers.datatypes import Api, VectorDBsProtocolPrivate
 from llama_stack.providers.utils.memory.vector_store import (
-    BankWithIndex,
     EmbeddingIndex,
+    VectorDBWithIndex,
 )
 
 from .config import WeaviateConfig, WeaviateRequestProviderData
@@ -49,7 +44,7 @@ class WeaviateIndex(EmbeddingIndex):
             data_objects.append(
                 wvc.data.DataObject(
                     properties={
-                        "chunk_content": chunk.json(),
+                        "chunk_content": chunk.model_dump_json(),
                     },
                     vector=embeddings[i].tolist(),
                 )
@@ -63,7 +58,7 @@ class WeaviateIndex(EmbeddingIndex):
 
     async def query(
         self, embedding: NDArray, k: int, score_threshold: float
-    ) -> QueryDocumentsResponse:
+    ) -> QueryChunksResponse:
         collection = self.client.collections.get(self.collection_name)
 
         results = collection.query.near_vector(
@@ -86,7 +81,7 @@ class WeaviateIndex(EmbeddingIndex):
             chunks.append(chunk)
             scores.append(1.0 / doc.metadata.distance)
 
-        return QueryDocumentsResponse(chunks=chunks, scores=scores)
+        return QueryChunksResponse(chunks=chunks, scores=scores)
 
     async def delete(self, chunk_ids: List[str]) -> None:
         collection = self.client.collections.get(self.collection_name)
@@ -96,9 +91,9 @@ class WeaviateIndex(EmbeddingIndex):
 
 
 class WeaviateMemoryAdapter(
-    Memory,
+    VectorIO,
     NeedsRequestProviderData,
-    MemoryBanksProtocolPrivate,
+    VectorDBsProtocolPrivate,
 ):
     def __init__(self, config: WeaviateConfig, inference_api: Api.inference) -> None:
         self.config = config
@@ -129,20 +124,16 @@ class WeaviateMemoryAdapter(
         for client in self.client_cache.values():
             client.close()
 
-    async def register_memory_bank(
+    async def register_vector_db(
         self,
-        memory_bank: MemoryBank,
+        vector_db: VectorDB,
     ) -> None:
-        assert (
-            memory_bank.memory_bank_type == MemoryBankType.vector.value
-        ), f"Only vector banks are supported {memory_bank.memory_bank_type}"
-
         client = self._get_client()
 
         # Create collection if it doesn't exist
-        if not client.collections.exists(memory_bank.identifier):
+        if not client.collections.exists(vector_db.identifier):
             client.collections.create(
-                name=memory_bank.identifier,
+                name=vector_db.identifier,
                 vectorizer_config=wvc.config.Configure.Vectorizer.none(),
                 properties=[
                     wvc.config.Property(
@@ -152,52 +143,54 @@ class WeaviateMemoryAdapter(
                 ],
             )
 
-        self.cache[memory_bank.identifier] = BankWithIndex(
-            memory_bank,
-            WeaviateIndex(client=client, collection_name=memory_bank.identifier),
+        self.cache[vector_db.identifier] = VectorDBWithIndex(
+            vector_db,
+            WeaviateIndex(client=client, collection_name=vector_db.identifier),
             self.inference_api,
         )
 
-    async def _get_and_cache_bank_index(self, bank_id: str) -> Optional[BankWithIndex]:
-        if bank_id in self.cache:
-            return self.cache[bank_id]
+    async def _get_and_cache_vector_db_index(
+        self, vector_db_id: str
+    ) -> Optional[VectorDBWithIndex]:
+        if vector_db_id in self.cache:
+            return self.cache[vector_db_id]
 
-        bank = await self.memory_bank_store.get_memory_bank(bank_id)
-        if not bank:
-            raise ValueError(f"Bank {bank_id} not found")
+        vector_db = await self.vector_db_store.get_vector_db(vector_db_id)
+        if not vector_db:
+            raise ValueError(f"Vector DB {vector_db_id} not found")
 
         client = self._get_client()
-        if not client.collections.exists(bank.identifier):
-            raise ValueError(f"Collection with name `{bank.identifier}` not found")
+        if not client.collections.exists(vector_db.identifier):
+            raise ValueError(f"Collection with name `{vector_db.identifier}` not found")
 
-        index = BankWithIndex(
-            bank=bank,
-            index=WeaviateIndex(client=client, collection_name=bank_id),
+        index = VectorDBWithIndex(
+            vector_db=vector_db,
+            index=WeaviateIndex(client=client, collection_name=vector_db.identifier),
             inference_api=self.inference_api,
         )
-        self.cache[bank_id] = index
+        self.cache[vector_db_id] = index
         return index
 
-    async def insert_documents(
+    async def insert_chunks(
         self,
-        bank_id: str,
-        documents: List[MemoryBankDocument],
+        vector_db_id: str,
+        chunks: List[Chunk],
         ttl_seconds: Optional[int] = None,
     ) -> None:
-        index = await self._get_and_cache_bank_index(bank_id)
+        index = await self._get_and_cache_vector_db_index(vector_db_id)
         if not index:
-            raise ValueError(f"Bank {bank_id} not found")
+            raise ValueError(f"Vector DB {vector_db_id} not found")
 
-        await index.insert_documents(documents)
+        await index.insert_chunks(chunks)
 
-    async def query_documents(
+    async def query_chunks(
         self,
-        bank_id: str,
+        vector_db_id: str,
         query: InterleavedContent,
         params: Optional[Dict[str, Any]] = None,
-    ) -> QueryDocumentsResponse:
-        index = await self._get_and_cache_bank_index(bank_id)
+    ) -> QueryChunksResponse:
+        index = await self._get_and_cache_vector_db_index(vector_db_id)
         if not index:
-            raise ValueError(f"Bank {bank_id} not found")
+            raise ValueError(f"Vector DB {vector_db_id} not found")
 
-        return await index.query_documents(query, params)
+        return await index.query_chunks(query, params)
diff --git a/llama_stack/providers/tests/agents/conftest.py b/llama_stack/providers/tests/agents/conftest.py
index 4efdfe8b7..9c115e3a1 100644
--- a/llama_stack/providers/tests/agents/conftest.py
+++ b/llama_stack/providers/tests/agents/conftest.py
@@ -12,10 +12,10 @@ from ..conftest import (
     get_test_config_for_api,
 )
 from ..inference.fixtures import INFERENCE_FIXTURES
-from ..memory.fixtures import MEMORY_FIXTURES
 from ..safety.fixtures import SAFETY_FIXTURES, safety_model_from_shield
 
 from ..tools.fixtures import TOOL_RUNTIME_FIXTURES
+from ..vector_io.fixtures import VECTOR_IO_FIXTURES
 from .fixtures import AGENTS_FIXTURES
 
 DEFAULT_PROVIDER_COMBINATIONS = [
@@ -23,7 +23,7 @@ DEFAULT_PROVIDER_COMBINATIONS = [
         {
             "inference": "meta_reference",
             "safety": "llama_guard",
-            "memory": "faiss",
+            "vector_io": "faiss",
             "agents": "meta_reference",
             "tool_runtime": "memory_and_search",
         },
@@ -34,7 +34,7 @@ DEFAULT_PROVIDER_COMBINATIONS = [
         {
             "inference": "ollama",
             "safety": "llama_guard",
-            "memory": "faiss",
+            "vector_io": "faiss",
             "agents": "meta_reference",
             "tool_runtime": "memory_and_search",
         },
@@ -46,7 +46,7 @@ DEFAULT_PROVIDER_COMBINATIONS = [
             "inference": "together",
             "safety": "llama_guard",
             # make this work with Weaviate which is what the together distro supports
-            "memory": "faiss",
+            "vector_io": "faiss",
             "agents": "meta_reference",
             "tool_runtime": "memory_and_search",
         },
@@ -57,7 +57,7 @@ DEFAULT_PROVIDER_COMBINATIONS = [
         {
             "inference": "fireworks",
             "safety": "llama_guard",
-            "memory": "faiss",
+            "vector_io": "faiss",
             "agents": "meta_reference",
             "tool_runtime": "memory_and_search",
         },
@@ -68,7 +68,7 @@ DEFAULT_PROVIDER_COMBINATIONS = [
         {
             "inference": "remote",
             "safety": "remote",
-            "memory": "remote",
+            "vector_io": "remote",
             "agents": "remote",
             "tool_runtime": "memory_and_search",
         },
@@ -115,7 +115,7 @@ def pytest_generate_tests(metafunc):
         available_fixtures = {
             "inference": INFERENCE_FIXTURES,
             "safety": SAFETY_FIXTURES,
-            "memory": MEMORY_FIXTURES,
+            "vector_io": VECTOR_IO_FIXTURES,
             "agents": AGENTS_FIXTURES,
             "tool_runtime": TOOL_RUNTIME_FIXTURES,
         }
diff --git a/llama_stack/providers/tests/agents/fixtures.py b/llama_stack/providers/tests/agents/fixtures.py
index 1b1781f36..bb4a6e6a3 100644
--- a/llama_stack/providers/tests/agents/fixtures.py
+++ b/llama_stack/providers/tests/agents/fixtures.py
@@ -69,7 +69,7 @@ async def agents_stack(
 
     providers = {}
     provider_data = {}
-    for key in ["inference", "safety", "memory", "agents", "tool_runtime"]:
+    for key in ["inference", "safety", "vector_io", "agents", "tool_runtime"]:
         fixture = request.getfixturevalue(f"{key}_{fixture_dict[key]}")
         providers[key] = fixture.providers
         if key == "inference":
@@ -118,7 +118,7 @@ async def agents_stack(
     )
 
     test_stack = await construct_stack_for_test(
-        [Api.agents, Api.inference, Api.safety, Api.memory, Api.tool_runtime],
+        [Api.agents, Api.inference, Api.safety, Api.vector_io, Api.tool_runtime],
         providers,
         provider_data,
         models=models,
diff --git a/llama_stack/providers/tests/agents/test_agents.py b/llama_stack/providers/tests/agents/test_agents.py
index 320096826..68ee9133c 100644
--- a/llama_stack/providers/tests/agents/test_agents.py
+++ b/llama_stack/providers/tests/agents/test_agents.py
@@ -184,7 +184,7 @@ class TestAgents:
         agent_config = AgentConfig(
             **{
                 **common_params,
-                "toolgroups": ["builtin::memory"],
+                "toolgroups": ["builtin::rag"],
                 "tool_choice": ToolChoice.auto,
             }
         )
@@ -214,9 +214,11 @@ class TestAgents:
         turn_response = [
             chunk async for chunk in await agents_impl.create_agent_turn(**turn_request)
         ]
-
         assert len(turn_response) > 0
 
+        # FIXME: we need to check the content of the turn response and ensure
+        # RAG actually worked
+
     @pytest.mark.asyncio
     async def test_create_agent_turn_with_tavily_search(
         self, agents_stack, search_query_messages, common_params
diff --git a/llama_stack/providers/tests/conftest.py b/llama_stack/providers/tests/conftest.py
index 4aa53a687..7d0d2ae74 100644
--- a/llama_stack/providers/tests/conftest.py
+++ b/llama_stack/providers/tests/conftest.py
@@ -302,7 +302,7 @@ def pytest_collection_modifyitems(session, config, items):
 pytest_plugins = [
     "llama_stack.providers.tests.inference.fixtures",
     "llama_stack.providers.tests.safety.fixtures",
-    "llama_stack.providers.tests.memory.fixtures",
+    "llama_stack.providers.tests.vector_io.fixtures",
     "llama_stack.providers.tests.agents.fixtures",
     "llama_stack.providers.tests.datasetio.fixtures",
     "llama_stack.providers.tests.scoring.fixtures",
diff --git a/llama_stack/providers/tests/eval/fixtures.py b/llama_stack/providers/tests/eval/fixtures.py
index 37bb0527a..009e65fb3 100644
--- a/llama_stack/providers/tests/eval/fixtures.py
+++ b/llama_stack/providers/tests/eval/fixtures.py
@@ -53,7 +53,7 @@ async def eval_stack(
         "inference",
         "agents",
         "safety",
-        "memory",
+        "vector_io",
         "tool_runtime",
     ]:
         fixture = request.getfixturevalue(f"{key}_{fixture_dict[key]}")
@@ -69,7 +69,7 @@ async def eval_stack(
             Api.scoring,
             Api.agents,
             Api.safety,
-            Api.memory,
+            Api.vector_io,
             Api.tool_runtime,
         ],
         providers,
diff --git a/llama_stack/providers/tests/inference/fixtures.py b/llama_stack/providers/tests/inference/fixtures.py
index 0767e940f..331898a7f 100644
--- a/llama_stack/providers/tests/inference/fixtures.py
+++ b/llama_stack/providers/tests/inference/fixtures.py
@@ -23,6 +23,7 @@ from llama_stack.providers.remote.inference.fireworks import FireworksImplConfig
 from llama_stack.providers.remote.inference.groq import GroqConfig
 from llama_stack.providers.remote.inference.nvidia import NVIDIAConfig
 from llama_stack.providers.remote.inference.ollama import OllamaImplConfig
+from llama_stack.providers.remote.inference.sambanova import SambaNovaImplConfig
 from llama_stack.providers.remote.inference.tgi import TGIImplConfig
 from llama_stack.providers.remote.inference.together import TogetherImplConfig
 from llama_stack.providers.remote.inference.vllm import VLLMInferenceAdapterConfig
@@ -232,6 +233,23 @@ def inference_tgi() -> ProviderFixture:
 
 
 @pytest.fixture(scope="session")
+def inference_sambanova() -> ProviderFixture:
+    return ProviderFixture(
+        providers=[
+            Provider(
+                provider_id="sambanova",
+                provider_type="remote::sambanova",
+                config=SambaNovaImplConfig(
+                    api_key=get_env_or_fail("SAMBANOVA_API_KEY"),
+                ).model_dump(),
+            )
+        ],
+        provider_data=dict(
+            sambanova_api_key=get_env_or_fail("SAMBANOVA_API_KEY"),
+        ),
+    )
+
+
 def inference_sentence_transformers() -> ProviderFixture:
     return ProviderFixture(
         providers=[
@@ -282,6 +300,7 @@ INFERENCE_FIXTURES = [
     "cerebras",
     "nvidia",
     "tgi",
+    "sambanova",
 ]
 
 
diff --git a/llama_stack/providers/tests/inference/groq/test_groq_utils.py b/llama_stack/providers/tests/inference/groq/test_groq_utils.py
index 177a5a1b7..5e0797871 100644
--- a/llama_stack/providers/tests/inference/groq/test_groq_utils.py
+++ b/llama_stack/providers/tests/inference/groq/test_groq_utils.py
@@ -493,7 +493,7 @@ class TestConvertStreamChatCompletionResponse:
         iter = converted.__aiter__()
         chunk = await iter.__anext__()
         assert chunk.event.event_type == ChatCompletionResponseEventType.start
-        assert chunk.event.delta.content == ToolCall(
+        assert chunk.event.delta.tool_call == ToolCall(
             call_id="tool_call_id",
             tool_name="get_flight_info",
             arguments={"origin": "AU", "destination": "LAX"},
diff --git a/llama_stack/providers/tests/inference/test_model_registration.py b/llama_stack/providers/tests/inference/test_model_registration.py
index 3cd7b2496..96a34ec0e 100644
--- a/llama_stack/providers/tests/inference/test_model_registration.py
+++ b/llama_stack/providers/tests/inference/test_model_registration.py
@@ -59,7 +59,7 @@ class TestModelRegistration:
             },
         )
 
-        with pytest.raises(AssertionError) as exc_info:
+        with pytest.raises(ValueError) as exc_info:
             await models_impl.register_model(
                 model_id="custom-model-2",
                 metadata={
diff --git a/llama_stack/providers/tests/inference/test_text_inference.py b/llama_stack/providers/tests/inference/test_text_inference.py
index c2a5b38ac..5f1a429a1 100644
--- a/llama_stack/providers/tests/inference/test_text_inference.py
+++ b/llama_stack/providers/tests/inference/test_text_inference.py
@@ -109,18 +109,6 @@ class TestInference:
     async def test_completion(self, inference_model, inference_stack):
         inference_impl, _ = inference_stack
 
-        provider = inference_impl.routing_table.get_provider_impl(inference_model)
-        if provider.__provider_spec__.provider_type not in (
-            "inline::meta-reference",
-            "remote::ollama",
-            "remote::tgi",
-            "remote::together",
-            "remote::fireworks",
-            "remote::nvidia",
-            "remote::cerebras",
-        ):
-            pytest.skip("Other inference providers don't support completion() yet")
-
         response = await inference_impl.completion(
             content="Micheael Jordan is born in ",
             stream=False,
@@ -154,12 +142,6 @@ class TestInference:
     async def test_completion_logprobs(self, inference_model, inference_stack):
         inference_impl, _ = inference_stack
 
-        provider = inference_impl.routing_table.get_provider_impl(inference_model)
-        if provider.__provider_spec__.provider_type not in (
-            # "remote::nvidia", -- provider doesn't provide all logprobs
-        ):
-            pytest.skip("Other inference providers don't support completion() yet")
-
         response = await inference_impl.completion(
             content="Micheael Jordan is born in ",
             stream=False,
@@ -208,25 +190,9 @@ class TestInference:
                 assert not chunk.logprobs, "Logprobs should be empty"
 
     @pytest.mark.asyncio(loop_scope="session")
-    @pytest.mark.skip("This test is not quite robust")
     async def test_completion_structured_output(self, inference_model, inference_stack):
         inference_impl, _ = inference_stack
 
-        provider = inference_impl.routing_table.get_provider_impl(inference_model)
-        if provider.__provider_spec__.provider_type not in (
-            "inline::meta-reference",
-            "remote::ollama",
-            "remote::tgi",
-            "remote::together",
-            "remote::fireworks",
-            "remote::nvidia",
-            "remote::vllm",
-            "remote::cerebras",
-        ):
-            pytest.skip(
-                "Other inference providers don't support structured output in completions yet"
-            )
-
         class Output(BaseModel):
             name: str
             year_born: str
@@ -275,18 +241,6 @@ class TestInference:
     ):
         inference_impl, _ = inference_stack
 
-        provider = inference_impl.routing_table.get_provider_impl(inference_model)
-        if provider.__provider_spec__.provider_type not in (
-            "inline::meta-reference",
-            "remote::ollama",
-            "remote::fireworks",
-            "remote::tgi",
-            "remote::together",
-            "remote::vllm",
-            "remote::nvidia",
-        ):
-            pytest.skip("Other inference providers don't support structured output yet")
-
         class AnswerFormat(BaseModel):
             first_name: str
             last_name: str
@@ -377,7 +331,6 @@ class TestInference:
         sample_tool_definition,
     ):
         inference_impl, _ = inference_stack
-
         messages = sample_messages + [
             UserMessage(
                 content="What's the weather like in San Francisco?",
@@ -417,14 +370,6 @@ class TestInference:
         sample_tool_definition,
     ):
         inference_impl, _ = inference_stack
-        provider = inference_impl.routing_table.get_provider_impl(inference_model)
-        if (
-            provider.__provider_spec__.provider_type == "remote::groq"
-            and "Llama-3.2" in inference_model
-        ):
-            # TODO(aidand): Remove this skip once Groq's tool calling for Llama3.2 works better
-            pytest.skip("Groq's tool calling for Llama3.2 doesn't work very well")
-
         messages = sample_messages + [
             UserMessage(
                 content="What's the weather like in San Francisco?",
@@ -464,16 +409,16 @@ class TestInference:
             )
             first = grouped[ChatCompletionResponseEventType.progress][0]
             if not isinstance(
-                first.event.delta.content, ToolCall
+                first.event.delta.tool_call, ToolCall
             ):  # first chunk may contain entire call
                 assert first.event.delta.parse_status == ToolCallParseStatus.started
 
         last = grouped[ChatCompletionResponseEventType.progress][-1]
         # assert last.event.stop_reason == expected_stop_reason
         assert last.event.delta.parse_status == ToolCallParseStatus.succeeded
-        assert isinstance(last.event.delta.content, ToolCall)
+        assert isinstance(last.event.delta.tool_call, ToolCall)
 
-        call = last.event.delta.content
+        call = last.event.delta.tool_call
         assert call.tool_name == "get_weather"
         assert "location" in call.arguments
         assert "San Francisco" in call.arguments["location"]
diff --git a/llama_stack/providers/tests/inference/test_vision_inference.py b/llama_stack/providers/tests/inference/test_vision_inference.py
index df2f3cfb9..a06c4a7d5 100644
--- a/llama_stack/providers/tests/inference/test_vision_inference.py
+++ b/llama_stack/providers/tests/inference/test_vision_inference.py
@@ -32,13 +32,15 @@ class TestVisionModelInference:
         "image, expected_strings",
         [
             (
-                ImageContentItem(data=PASTA_IMAGE),
+                ImageContentItem(image=dict(data=PASTA_IMAGE)),
                 ["spaghetti"],
             ),
             (
                 ImageContentItem(
-                    url=URL(
-                        uri="https://www.healthypawspetinsurance.com/Images/V3/DogAndPuppyInsurance/Dog_CTA_Desktop_HeroImage.jpg"
+                    image=dict(
+                        url=URL(
+                            uri="https://www.healthypawspetinsurance.com/Images/V3/DogAndPuppyInsurance/Dog_CTA_Desktop_HeroImage.jpg"
+                        )
                     )
                 ),
                 ["puppy"],
@@ -49,19 +51,6 @@ class TestVisionModelInference:
         self, inference_model, inference_stack, image, expected_strings
     ):
         inference_impl, _ = inference_stack
-
-        provider = inference_impl.routing_table.get_provider_impl(inference_model)
-        if provider.__provider_spec__.provider_type not in (
-            "inline::meta-reference",
-            "remote::together",
-            "remote::fireworks",
-            "remote::ollama",
-            "remote::vllm",
-        ):
-            pytest.skip(
-                "Other inference providers don't support vision chat completion() yet"
-            )
-
         response = await inference_impl.chat_completion(
             model_id=inference_model,
             messages=[
@@ -89,22 +78,12 @@ class TestVisionModelInference:
     ):
         inference_impl, _ = inference_stack
 
-        provider = inference_impl.routing_table.get_provider_impl(inference_model)
-        if provider.__provider_spec__.provider_type not in (
-            "inline::meta-reference",
-            "remote::together",
-            "remote::fireworks",
-            "remote::ollama",
-            "remote::vllm",
-        ):
-            pytest.skip(
-                "Other inference providers don't support vision chat completion() yet"
-            )
-
         images = [
             ImageContentItem(
-                url=URL(
-                    uri="https://www.healthypawspetinsurance.com/Images/V3/DogAndPuppyInsurance/Dog_CTA_Desktop_HeroImage.jpg"
+                image=dict(
+                    url=URL(
+                        uri="https://www.healthypawspetinsurance.com/Images/V3/DogAndPuppyInsurance/Dog_CTA_Desktop_HeroImage.jpg"
+                    )
                 )
             ),
         ]
diff --git a/llama_stack/providers/tests/memory/test_memory.py b/llama_stack/providers/tests/memory/test_memory.py
deleted file mode 100644
index 801b04dfc..000000000
--- a/llama_stack/providers/tests/memory/test_memory.py
+++ /dev/null
@@ -1,192 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the terms described in the LICENSE file in
-# the root directory of this source tree.
-
-import uuid
-
-import pytest
-
-from llama_stack.apis.memory import MemoryBankDocument, QueryDocumentsResponse
-
-from llama_stack.apis.memory_banks import (
-    MemoryBank,
-    MemoryBanks,
-    VectorMemoryBankParams,
-)
-
-# How to run this test:
-#
-# pytest llama_stack/providers/tests/memory/test_memory.py
-#   -m "sentence_transformers" --env EMBEDDING_DIMENSION=384
-#   -v -s --tb=short --disable-warnings
-
-
-@pytest.fixture
-def sample_documents():
-    return [
-        MemoryBankDocument(
-            document_id="doc1",
-            content="Python is a high-level programming language.",
-            metadata={"category": "programming", "difficulty": "beginner"},
-        ),
-        MemoryBankDocument(
-            document_id="doc2",
-            content="Machine learning is a subset of artificial intelligence.",
-            metadata={"category": "AI", "difficulty": "advanced"},
-        ),
-        MemoryBankDocument(
-            document_id="doc3",
-            content="Data structures are fundamental to computer science.",
-            metadata={"category": "computer science", "difficulty": "intermediate"},
-        ),
-        MemoryBankDocument(
-            document_id="doc4",
-            content="Neural networks are inspired by biological neural networks.",
-            metadata={"category": "AI", "difficulty": "advanced"},
-        ),
-    ]
-
-
-async def register_memory_bank(
-    banks_impl: MemoryBanks, embedding_model: str
-) -> MemoryBank:
-    bank_id = f"test_bank_{uuid.uuid4().hex}"
-    return await banks_impl.register_memory_bank(
-        memory_bank_id=bank_id,
-        params=VectorMemoryBankParams(
-            embedding_model=embedding_model,
-            chunk_size_in_tokens=512,
-            overlap_size_in_tokens=64,
-        ),
-    )
-
-
-class TestMemory:
-    @pytest.mark.asyncio
-    async def test_banks_list(self, memory_stack, embedding_model):
-        _, banks_impl = memory_stack
-
-        # Register a test bank
-        registered_bank = await register_memory_bank(banks_impl, embedding_model)
-
-        try:
-            # Verify our bank shows up in list
-            response = await banks_impl.list_memory_banks()
-            assert isinstance(response, list)
-            assert any(
-                bank.memory_bank_id == registered_bank.memory_bank_id
-                for bank in response
-            )
-        finally:
-            # Clean up
-            await banks_impl.unregister_memory_bank(registered_bank.memory_bank_id)
-
-        # Verify our bank was removed
-        response = await banks_impl.list_memory_banks()
-        assert all(
-            bank.memory_bank_id != registered_bank.memory_bank_id for bank in response
-        )
-
-    @pytest.mark.asyncio
-    async def test_banks_register(self, memory_stack, embedding_model):
-        _, banks_impl = memory_stack
-
-        bank_id = f"test_bank_{uuid.uuid4().hex}"
-
-        try:
-            # Register initial bank
-            await banks_impl.register_memory_bank(
-                memory_bank_id=bank_id,
-                params=VectorMemoryBankParams(
-                    embedding_model=embedding_model,
-                    chunk_size_in_tokens=512,
-                    overlap_size_in_tokens=64,
-                ),
-            )
-
-            # Verify our bank exists
-            response = await banks_impl.list_memory_banks()
-            assert isinstance(response, list)
-            assert any(bank.memory_bank_id == bank_id for bank in response)
-
-            # Try registering same bank again
-            await banks_impl.register_memory_bank(
-                memory_bank_id=bank_id,
-                params=VectorMemoryBankParams(
-                    embedding_model=embedding_model,
-                    chunk_size_in_tokens=512,
-                    overlap_size_in_tokens=64,
-                ),
-            )
-
-            # Verify still only one instance of our bank
-            response = await banks_impl.list_memory_banks()
-            assert isinstance(response, list)
-            assert (
-                len([bank for bank in response if bank.memory_bank_id == bank_id]) == 1
-            )
-        finally:
-            # Clean up
-            await banks_impl.unregister_memory_bank(bank_id)
-
-    @pytest.mark.asyncio
-    async def test_query_documents(
-        self, memory_stack, embedding_model, sample_documents
-    ):
-        memory_impl, banks_impl = memory_stack
-
-        with pytest.raises(ValueError):
-            await memory_impl.insert_documents("test_bank", sample_documents)
-
-        registered_bank = await register_memory_bank(banks_impl, embedding_model)
-        await memory_impl.insert_documents(
-            registered_bank.memory_bank_id, sample_documents
-        )
-
-        query1 = "programming language"
-        response1 = await memory_impl.query_documents(
-            registered_bank.memory_bank_id, query1
-        )
-        assert_valid_response(response1)
-        assert any("Python" in chunk.content for chunk in response1.chunks)
-
-        # Test case 3: Query with semantic similarity
-        query3 = "AI and brain-inspired computing"
-        response3 = await memory_impl.query_documents(
-            registered_bank.memory_bank_id, query3
-        )
-        assert_valid_response(response3)
-        assert any(
-            "neural networks" in chunk.content.lower() for chunk in response3.chunks
-        )
-
-        # Test case 4: Query with limit on number of results
-        query4 = "computer"
-        params4 = {"max_chunks": 2}
-        response4 = await memory_impl.query_documents(
-            registered_bank.memory_bank_id, query4, params4
-        )
-        assert_valid_response(response4)
-        assert len(response4.chunks) <= 2
-
-        # Test case 5: Query with threshold on similarity score
-        query5 = "quantum computing"  # Not directly related to any document
-        params5 = {"score_threshold": 0.01}
-        response5 = await memory_impl.query_documents(
-            registered_bank.memory_bank_id, query5, params5
-        )
-        assert_valid_response(response5)
-        print("The scores are:", response5.scores)
-        assert all(score >= 0.01 for score in response5.scores)
-
-
-def assert_valid_response(response: QueryDocumentsResponse):
-    assert isinstance(response, QueryDocumentsResponse)
-    assert len(response.chunks) > 0
-    assert len(response.scores) > 0
-    assert len(response.chunks) == len(response.scores)
-    for chunk in response.chunks:
-        assert isinstance(chunk.content, str)
-        assert chunk.document_id is not None
diff --git a/llama_stack/providers/tests/resolver.py b/llama_stack/providers/tests/resolver.py
index 81816d51e..f0c4c530e 100644
--- a/llama_stack/providers/tests/resolver.py
+++ b/llama_stack/providers/tests/resolver.py
@@ -12,11 +12,11 @@ from pydantic import BaseModel
 
 from llama_stack.apis.datasets import DatasetInput
 from llama_stack.apis.eval_tasks import EvalTaskInput
-from llama_stack.apis.memory_banks import MemoryBankInput
 from llama_stack.apis.models import ModelInput
 from llama_stack.apis.scoring_functions import ScoringFnInput
 from llama_stack.apis.shields import ShieldInput
 from llama_stack.apis.tools import ToolGroupInput
+from llama_stack.apis.vector_dbs import VectorDBInput
 from llama_stack.distribution.build import print_pip_install_help
 from llama_stack.distribution.configure import parse_and_maybe_upgrade_config
 from llama_stack.distribution.datatypes import Provider, StackRunConfig
@@ -39,7 +39,7 @@ async def construct_stack_for_test(
     provider_data: Optional[Dict[str, Any]] = None,
     models: Optional[List[ModelInput]] = None,
     shields: Optional[List[ShieldInput]] = None,
-    memory_banks: Optional[List[MemoryBankInput]] = None,
+    vector_dbs: Optional[List[VectorDBInput]] = None,
     datasets: Optional[List[DatasetInput]] = None,
     scoring_fns: Optional[List[ScoringFnInput]] = None,
     eval_tasks: Optional[List[EvalTaskInput]] = None,
@@ -53,7 +53,7 @@ async def construct_stack_for_test(
         metadata_store=SqliteKVStoreConfig(db_path=sqlite_file.name),
         models=models or [],
         shields=shields or [],
-        memory_banks=memory_banks or [],
+        vector_dbs=vector_dbs or [],
         datasets=datasets or [],
         scoring_fns=scoring_fns or [],
         eval_tasks=eval_tasks or [],
diff --git a/llama_stack/providers/tests/tools/conftest.py b/llama_stack/providers/tests/tools/conftest.py
index 525abe8ab..0df547a9d 100644
--- a/llama_stack/providers/tests/tools/conftest.py
+++ b/llama_stack/providers/tests/tools/conftest.py
@@ -8,8 +8,8 @@ import pytest
 
 from ..conftest import get_provider_fixture_overrides
 from ..inference.fixtures import INFERENCE_FIXTURES
-from ..memory.fixtures import MEMORY_FIXTURES
 from ..safety.fixtures import SAFETY_FIXTURES
+from ..vector_io.fixtures import VECTOR_IO_FIXTURES
 from .fixtures import TOOL_RUNTIME_FIXTURES
 
 DEFAULT_PROVIDER_COMBINATIONS = [
@@ -17,7 +17,7 @@ DEFAULT_PROVIDER_COMBINATIONS = [
         {
             "inference": "together",
             "safety": "llama_guard",
-            "memory": "faiss",
+            "vector_io": "faiss",
             "tool_runtime": "memory_and_search",
         },
         id="together",
@@ -39,12 +39,11 @@ def pytest_generate_tests(metafunc):
         available_fixtures = {
             "inference": INFERENCE_FIXTURES,
             "safety": SAFETY_FIXTURES,
-            "memory": MEMORY_FIXTURES,
+            "vector_io": VECTOR_IO_FIXTURES,
             "tool_runtime": TOOL_RUNTIME_FIXTURES,
         }
         combinations = (
             get_provider_fixture_overrides(metafunc.config, available_fixtures)
             or DEFAULT_PROVIDER_COMBINATIONS
         )
-        print(combinations)
         metafunc.parametrize("tools_stack", combinations, indirect=True)
diff --git a/llama_stack/providers/tests/tools/fixtures.py b/llama_stack/providers/tests/tools/fixtures.py
index a559dbf8c..a2dd4239a 100644
--- a/llama_stack/providers/tests/tools/fixtures.py
+++ b/llama_stack/providers/tests/tools/fixtures.py
@@ -22,8 +22,8 @@ def tool_runtime_memory_and_search() -> ProviderFixture:
     return ProviderFixture(
         providers=[
             Provider(
-                provider_id="memory-runtime",
-                provider_type="inline::memory-runtime",
+                provider_id="rag-runtime",
+                provider_type="inline::rag-runtime",
                 config={},
             ),
             Provider(
@@ -47,8 +47,8 @@ def tool_runtime_memory_and_search() -> ProviderFixture:
 @pytest.fixture(scope="session")
 def tool_group_input_memory() -> ToolGroupInput:
     return ToolGroupInput(
-        toolgroup_id="builtin::memory",
-        provider_id="memory-runtime",
+        toolgroup_id="builtin::rag",
+        provider_id="rag-runtime",
     )
 
 
@@ -83,7 +83,7 @@ async def tools_stack(
 
     providers = {}
     provider_data = {}
-    for key in ["inference", "memory", "tool_runtime"]:
+    for key in ["inference", "vector_io", "tool_runtime"]:
         fixture = request.getfixturevalue(f"{key}_{fixture_dict[key]}")
         providers[key] = fixture.providers
         if key == "inference":
@@ -117,7 +117,12 @@ async def tools_stack(
     )
 
     test_stack = await construct_stack_for_test(
-        [Api.tool_groups, Api.inference, Api.memory, Api.tool_runtime],
+        [
+            Api.tool_groups,
+            Api.inference,
+            Api.vector_io,
+            Api.tool_runtime,
+        ],
         providers,
         provider_data,
         models=models,
diff --git a/llama_stack/providers/tests/tools/test_tools.py b/llama_stack/providers/tests/tools/test_tools.py
index 16081b939..281ea404d 100644
--- a/llama_stack/providers/tests/tools/test_tools.py
+++ b/llama_stack/providers/tests/tools/test_tools.py
@@ -8,10 +8,7 @@ import os
 
 import pytest
 
-from llama_stack.apis.inference import UserMessage
-from llama_stack.apis.memory import MemoryBankDocument
-from llama_stack.apis.memory_banks import VectorMemoryBankParams
-from llama_stack.apis.tools import ToolInvocationResult
+from llama_stack.apis.tools import RAGDocument, RAGQueryResult, ToolInvocationResult
 from llama_stack.providers.datatypes import Api
 
 
@@ -36,7 +33,7 @@ def sample_documents():
         "lora_finetune.rst",
     ]
     return [
-        MemoryBankDocument(
+        RAGDocument(
             document_id=f"num-{i}",
             content=f"https://raw.githubusercontent.com/pytorch/torchtune/main/docs/source/tutorials/{url}",
             mime_type="text/plain",
@@ -57,7 +54,7 @@ class TestTools:
 
         # Execute the tool
         response = await tools_impl.invoke_tool(
-            tool_name="web_search", args={"query": sample_search_query}
+            tool_name="web_search", kwargs={"query": sample_search_query}
         )
 
         # Verify the response
@@ -75,7 +72,7 @@ class TestTools:
         tools_impl = tools_stack.impls[Api.tool_runtime]
 
         response = await tools_impl.invoke_tool(
-            tool_name="wolfram_alpha", args={"query": sample_wolfram_alpha_query}
+            tool_name="wolfram_alpha", kwargs={"query": sample_wolfram_alpha_query}
         )
 
         # Verify the response
@@ -85,43 +82,33 @@ class TestTools:
         assert isinstance(response.content, str)
 
     @pytest.mark.asyncio
-    async def test_memory_tool(self, tools_stack, sample_documents):
+    async def test_rag_tool(self, tools_stack, sample_documents):
         """Test the memory tool functionality."""
-        memory_banks_impl = tools_stack.impls[Api.memory_banks]
-        memory_impl = tools_stack.impls[Api.memory]
+        vector_dbs_impl = tools_stack.impls[Api.vector_dbs]
         tools_impl = tools_stack.impls[Api.tool_runtime]
 
         # Register memory bank
-        await memory_banks_impl.register_memory_bank(
-            memory_bank_id="test_bank",
-            params=VectorMemoryBankParams(
-                embedding_model="all-MiniLM-L6-v2",
-                chunk_size_in_tokens=512,
-                overlap_size_in_tokens=64,
-            ),
+        await vector_dbs_impl.register_vector_db(
+            vector_db_id="test_bank",
+            embedding_model="all-MiniLM-L6-v2",
+            embedding_dimension=384,
             provider_id="faiss",
         )
 
         # Insert documents into memory
-        await memory_impl.insert_documents(
-            bank_id="test_bank",
+        await tools_impl.rag_tool.insert(
             documents=sample_documents,
+            vector_db_id="test_bank",
+            chunk_size_in_tokens=512,
         )
 
         # Execute the memory tool
-        response = await tools_impl.invoke_tool(
-            tool_name="memory",
-            args={
-                "messages": [
-                    UserMessage(
-                        content="What are the main topics covered in the documentation?",
-                    )
-                ],
-                "memory_bank_ids": ["test_bank"],
-            },
+        response = await tools_impl.rag_tool.query(
+            content="What are the main topics covered in the documentation?",
+            vector_db_ids=["test_bank"],
         )
 
         # Verify the response
-        assert isinstance(response, ToolInvocationResult)
+        assert isinstance(response, RAGQueryResult)
         assert response.content is not None
         assert len(response.content) > 0
diff --git a/llama_stack/providers/tests/memory/__init__.py b/llama_stack/providers/tests/vector_io/__init__.py
similarity index 100%
rename from llama_stack/providers/tests/memory/__init__.py
rename to llama_stack/providers/tests/vector_io/__init__.py
diff --git a/llama_stack/providers/tests/memory/conftest.py b/llama_stack/providers/tests/vector_io/conftest.py
similarity index 79%
rename from llama_stack/providers/tests/memory/conftest.py
rename to llama_stack/providers/tests/vector_io/conftest.py
index 87dec4beb..df5c8ea6a 100644
--- a/llama_stack/providers/tests/memory/conftest.py
+++ b/llama_stack/providers/tests/vector_io/conftest.py
@@ -13,14 +13,14 @@ from ..conftest import (
 )
 
 from ..inference.fixtures import INFERENCE_FIXTURES
-from .fixtures import MEMORY_FIXTURES
+from .fixtures import VECTOR_IO_FIXTURES
 
 
 DEFAULT_PROVIDER_COMBINATIONS = [
     pytest.param(
         {
             "inference": "sentence_transformers",
-            "memory": "faiss",
+            "vector_io": "faiss",
         },
         id="sentence_transformers",
         marks=pytest.mark.sentence_transformers,
@@ -28,7 +28,7 @@ DEFAULT_PROVIDER_COMBINATIONS = [
     pytest.param(
         {
             "inference": "ollama",
-            "memory": "faiss",
+            "vector_io": "faiss",
         },
         id="ollama",
         marks=pytest.mark.ollama,
@@ -36,7 +36,7 @@ DEFAULT_PROVIDER_COMBINATIONS = [
     pytest.param(
         {
             "inference": "sentence_transformers",
-            "memory": "chroma",
+            "vector_io": "chroma",
         },
         id="chroma",
         marks=pytest.mark.chroma,
@@ -44,7 +44,7 @@ DEFAULT_PROVIDER_COMBINATIONS = [
     pytest.param(
         {
             "inference": "bedrock",
-            "memory": "qdrant",
+            "vector_io": "qdrant",
         },
         id="qdrant",
         marks=pytest.mark.qdrant,
@@ -52,7 +52,7 @@ DEFAULT_PROVIDER_COMBINATIONS = [
     pytest.param(
         {
             "inference": "fireworks",
-            "memory": "weaviate",
+            "vector_io": "weaviate",
         },
         id="weaviate",
         marks=pytest.mark.weaviate,
@@ -61,7 +61,7 @@ DEFAULT_PROVIDER_COMBINATIONS = [
 
 
 def pytest_configure(config):
-    for fixture_name in MEMORY_FIXTURES:
+    for fixture_name in VECTOR_IO_FIXTURES:
         config.addinivalue_line(
             "markers",
             f"{fixture_name}: marks tests as {fixture_name} specific",
@@ -69,7 +69,7 @@ def pytest_configure(config):
 
 
 def pytest_generate_tests(metafunc):
-    test_config = get_test_config_for_api(metafunc.config, "memory")
+    test_config = get_test_config_for_api(metafunc.config, "vector_io")
     if "embedding_model" in metafunc.fixturenames:
         model = getattr(test_config, "embedding_model", None)
         # Fall back to the default if not specified by the config file
@@ -81,16 +81,16 @@ def pytest_generate_tests(metafunc):
 
         metafunc.parametrize("embedding_model", params, indirect=True)
 
-    if "memory_stack" in metafunc.fixturenames:
+    if "vector_io_stack" in metafunc.fixturenames:
         available_fixtures = {
             "inference": INFERENCE_FIXTURES,
-            "memory": MEMORY_FIXTURES,
+            "vector_io": VECTOR_IO_FIXTURES,
         }
         combinations = (
             get_provider_fixture_overrides_from_test_config(
-                metafunc.config, "memory", DEFAULT_PROVIDER_COMBINATIONS
+                metafunc.config, "vector_io", DEFAULT_PROVIDER_COMBINATIONS
             )
             or get_provider_fixture_overrides(metafunc.config, available_fixtures)
             or DEFAULT_PROVIDER_COMBINATIONS
         )
-        metafunc.parametrize("memory_stack", combinations, indirect=True)
+        metafunc.parametrize("vector_io_stack", combinations, indirect=True)
diff --git a/llama_stack/providers/tests/memory/fixtures.py b/llama_stack/providers/tests/vector_io/fixtures.py
similarity index 80%
rename from llama_stack/providers/tests/memory/fixtures.py
rename to llama_stack/providers/tests/vector_io/fixtures.py
index b9dbb84f7..c8d5fa8cf 100644
--- a/llama_stack/providers/tests/memory/fixtures.py
+++ b/llama_stack/providers/tests/vector_io/fixtures.py
@@ -12,11 +12,12 @@ import pytest_asyncio
 
 from llama_stack.apis.models import ModelInput, ModelType
 from llama_stack.distribution.datatypes import Api, Provider
-from llama_stack.providers.inline.memory.chroma import ChromaInlineImplConfig
-from llama_stack.providers.inline.memory.faiss import FaissImplConfig
-from llama_stack.providers.remote.memory.chroma import ChromaRemoteImplConfig
-from llama_stack.providers.remote.memory.pgvector import PGVectorConfig
-from llama_stack.providers.remote.memory.weaviate import WeaviateConfig
+
+from llama_stack.providers.inline.vector_io.chroma import ChromaInlineImplConfig
+from llama_stack.providers.inline.vector_io.faiss import FaissImplConfig
+from llama_stack.providers.remote.vector_io.chroma import ChromaRemoteImplConfig
+from llama_stack.providers.remote.vector_io.pgvector import PGVectorConfig
+from llama_stack.providers.remote.vector_io.weaviate import WeaviateConfig
 from llama_stack.providers.tests.resolver import construct_stack_for_test
 from llama_stack.providers.utils.kvstore.config import SqliteKVStoreConfig
 
@@ -32,12 +33,12 @@ def embedding_model(request):
 
 
 @pytest.fixture(scope="session")
-def memory_remote() -> ProviderFixture:
+def vector_io_remote() -> ProviderFixture:
     return remote_stack_fixture()
 
 
 @pytest.fixture(scope="session")
-def memory_faiss() -> ProviderFixture:
+def vector_io_faiss() -> ProviderFixture:
     temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".db")
     return ProviderFixture(
         providers=[
@@ -53,7 +54,7 @@ def memory_faiss() -> ProviderFixture:
 
 
 @pytest.fixture(scope="session")
-def memory_pgvector() -> ProviderFixture:
+def vector_io_pgvector() -> ProviderFixture:
     return ProviderFixture(
         providers=[
             Provider(
@@ -72,7 +73,7 @@ def memory_pgvector() -> ProviderFixture:
 
 
 @pytest.fixture(scope="session")
-def memory_weaviate() -> ProviderFixture:
+def vector_io_weaviate() -> ProviderFixture:
     return ProviderFixture(
         providers=[
             Provider(
@@ -89,7 +90,7 @@ def memory_weaviate() -> ProviderFixture:
 
 
 @pytest.fixture(scope="session")
-def memory_chroma() -> ProviderFixture:
+def vector_io_chroma() -> ProviderFixture:
     url = os.getenv("CHROMA_URL")
     if url:
         config = ChromaRemoteImplConfig(url=url)
@@ -110,23 +111,23 @@ def memory_chroma() -> ProviderFixture:
     )
 
 
-MEMORY_FIXTURES = ["faiss", "pgvector", "weaviate", "remote", "chroma"]
+VECTOR_IO_FIXTURES = ["faiss", "pgvector", "weaviate", "chroma"]
 
 
 @pytest_asyncio.fixture(scope="session")
-async def memory_stack(embedding_model, request):
+async def vector_io_stack(embedding_model, request):
     fixture_dict = request.param
 
     providers = {}
     provider_data = {}
-    for key in ["inference", "memory"]:
+    for key in ["inference", "vector_io"]:
         fixture = request.getfixturevalue(f"{key}_{fixture_dict[key]}")
         providers[key] = fixture.providers
         if fixture.provider_data:
             provider_data.update(fixture.provider_data)
 
     test_stack = await construct_stack_for_test(
-        [Api.memory, Api.inference],
+        [Api.vector_io, Api.inference],
         providers,
         provider_data,
         models=[
@@ -140,4 +141,4 @@ async def memory_stack(embedding_model, request):
         ],
     )
 
-    return test_stack.impls[Api.memory], test_stack.impls[Api.memory_banks]
+    return test_stack.impls[Api.vector_io], test_stack.impls[Api.vector_dbs]
diff --git a/llama_stack/providers/tests/memory/fixtures/dummy.pdf b/llama_stack/providers/tests/vector_io/fixtures/dummy.pdf
similarity index 100%
rename from llama_stack/providers/tests/memory/fixtures/dummy.pdf
rename to llama_stack/providers/tests/vector_io/fixtures/dummy.pdf
diff --git a/llama_stack/providers/tests/vector_io/test_vector_io.py b/llama_stack/providers/tests/vector_io/test_vector_io.py
new file mode 100644
index 000000000..521131f63
--- /dev/null
+++ b/llama_stack/providers/tests/vector_io/test_vector_io.py
@@ -0,0 +1,199 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+import uuid
+
+import pytest
+
+from llama_stack.apis.tools import RAGDocument
+
+from llama_stack.apis.vector_dbs import ListVectorDBsResponse, VectorDB
+from llama_stack.apis.vector_io import QueryChunksResponse
+
+from llama_stack.providers.utils.memory.vector_store import make_overlapped_chunks
+
+# How to run this test:
+#
+# pytest llama_stack/providers/tests/memory/test_memory.py
+#   -m "sentence_transformers" --env EMBEDDING_DIMENSION=384
+#   -v -s --tb=short --disable-warnings
+
+
+@pytest.fixture(scope="session")
+def sample_chunks():
+    docs = [
+        RAGDocument(
+            document_id="doc1",
+            content="Python is a high-level programming language.",
+            metadata={"category": "programming", "difficulty": "beginner"},
+        ),
+        RAGDocument(
+            document_id="doc2",
+            content="Machine learning is a subset of artificial intelligence.",
+            metadata={"category": "AI", "difficulty": "advanced"},
+        ),
+        RAGDocument(
+            document_id="doc3",
+            content="Data structures are fundamental to computer science.",
+            metadata={"category": "computer science", "difficulty": "intermediate"},
+        ),
+        RAGDocument(
+            document_id="doc4",
+            content="Neural networks are inspired by biological neural networks.",
+            metadata={"category": "AI", "difficulty": "advanced"},
+        ),
+    ]
+    chunks = []
+    for doc in docs:
+        chunks.extend(
+            make_overlapped_chunks(
+                doc.document_id, doc.content, window_len=512, overlap_len=64
+            )
+        )
+    return chunks
+
+
+async def register_vector_db(vector_dbs_impl: VectorDB, embedding_model: str):
+    vector_db_id = f"test_vector_db_{uuid.uuid4().hex}"
+    return await vector_dbs_impl.register_vector_db(
+        vector_db_id=vector_db_id,
+        embedding_model=embedding_model,
+        embedding_dimension=384,
+    )
+
+
+class TestVectorIO:
+    @pytest.mark.asyncio
+    async def test_banks_list(self, vector_io_stack, embedding_model):
+        _, vector_dbs_impl = vector_io_stack
+
+        # Register a test bank
+        registered_vector_db = await register_vector_db(
+            vector_dbs_impl, embedding_model
+        )
+
+        try:
+            # Verify our bank shows up in list
+            response = await vector_dbs_impl.list_vector_dbs()
+            assert isinstance(response, ListVectorDBsResponse)
+            assert any(
+                vector_db.vector_db_id == registered_vector_db.vector_db_id
+                for vector_db in response.data
+            )
+        finally:
+            # Clean up
+            await vector_dbs_impl.unregister_vector_db(
+                registered_vector_db.vector_db_id
+            )
+
+        # Verify our bank was removed
+        response = await vector_dbs_impl.list_vector_dbs()
+        assert isinstance(response, ListVectorDBsResponse)
+        assert all(
+            vector_db.vector_db_id != registered_vector_db.vector_db_id
+            for vector_db in response.data
+        )
+
+    @pytest.mark.asyncio
+    async def test_banks_register(self, vector_io_stack, embedding_model):
+        _, vector_dbs_impl = vector_io_stack
+
+        vector_db_id = f"test_vector_db_{uuid.uuid4().hex}"
+
+        try:
+            # Register initial bank
+            await vector_dbs_impl.register_vector_db(
+                vector_db_id=vector_db_id,
+                embedding_model=embedding_model,
+                embedding_dimension=384,
+            )
+
+            # Verify our bank exists
+            response = await vector_dbs_impl.list_vector_dbs()
+            assert isinstance(response, ListVectorDBsResponse)
+            assert any(
+                vector_db.vector_db_id == vector_db_id for vector_db in response.data
+            )
+
+            # Try registering same bank again
+            await vector_dbs_impl.register_vector_db(
+                vector_db_id=vector_db_id,
+                embedding_model=embedding_model,
+                embedding_dimension=384,
+            )
+
+            # Verify still only one instance of our bank
+            response = await vector_dbs_impl.list_vector_dbs()
+            assert isinstance(response, ListVectorDBsResponse)
+            assert (
+                len(
+                    [
+                        vector_db
+                        for vector_db in response.data
+                        if vector_db.vector_db_id == vector_db_id
+                    ]
+                )
+                == 1
+            )
+        finally:
+            # Clean up
+            await vector_dbs_impl.unregister_vector_db(vector_db_id)
+
+    @pytest.mark.asyncio
+    async def test_query_documents(
+        self, vector_io_stack, embedding_model, sample_chunks
+    ):
+        vector_io_impl, vector_dbs_impl = vector_io_stack
+
+        with pytest.raises(ValueError):
+            await vector_io_impl.insert_chunks("test_vector_db", sample_chunks)
+
+        registered_db = await register_vector_db(vector_dbs_impl, embedding_model)
+        await vector_io_impl.insert_chunks(registered_db.vector_db_id, sample_chunks)
+
+        query1 = "programming language"
+        response1 = await vector_io_impl.query_chunks(
+            registered_db.vector_db_id, query1
+        )
+        assert_valid_response(response1)
+        assert any("Python" in chunk.content for chunk in response1.chunks)
+
+        # Test case 3: Query with semantic similarity
+        query3 = "AI and brain-inspired computing"
+        response3 = await vector_io_impl.query_chunks(
+            registered_db.vector_db_id, query3
+        )
+        assert_valid_response(response3)
+        assert any(
+            "neural networks" in chunk.content.lower() for chunk in response3.chunks
+        )
+
+        # Test case 4: Query with limit on number of results
+        query4 = "computer"
+        params4 = {"max_chunks": 2}
+        response4 = await vector_io_impl.query_chunks(
+            registered_db.vector_db_id, query4, params4
+        )
+        assert_valid_response(response4)
+        assert len(response4.chunks) <= 2
+
+        # Test case 5: Query with threshold on similarity score
+        query5 = "quantum computing"  # Not directly related to any document
+        params5 = {"score_threshold": 0.01}
+        response5 = await vector_io_impl.query_chunks(
+            registered_db.vector_db_id, query5, params5
+        )
+        assert_valid_response(response5)
+        print("The scores are:", response5.scores)
+        assert all(score >= 0.01 for score in response5.scores)
+
+
+def assert_valid_response(response: QueryChunksResponse):
+    assert len(response.chunks) > 0
+    assert len(response.scores) > 0
+    assert len(response.chunks) == len(response.scores)
+    for chunk in response.chunks:
+        assert isinstance(chunk.content, str)
diff --git a/llama_stack/providers/tests/memory/test_vector_store.py b/llama_stack/providers/tests/vector_io/test_vector_store.py
similarity index 87%
rename from llama_stack/providers/tests/memory/test_vector_store.py
rename to llama_stack/providers/tests/vector_io/test_vector_store.py
index 1ad7abf0c..2a41a8982 100644
--- a/llama_stack/providers/tests/memory/test_vector_store.py
+++ b/llama_stack/providers/tests/vector_io/test_vector_store.py
@@ -11,8 +11,9 @@ from pathlib import Path
 
 import pytest
 
-from llama_stack.apis.memory.memory import MemoryBankDocument, URL
-from llama_stack.providers.utils.memory.vector_store import content_from_doc
+from llama_stack.apis.tools import RAGDocument
+
+from llama_stack.providers.utils.memory.vector_store import content_from_doc, URL
 
 DUMMY_PDF_PATH = Path(os.path.abspath(__file__)).parent / "fixtures" / "dummy.pdf"
 
@@ -38,33 +39,33 @@ class TestVectorStore:
     @pytest.mark.asyncio
     async def test_returns_content_from_pdf_data_uri(self):
         data_uri = data_url_from_file(DUMMY_PDF_PATH)
-        doc = MemoryBankDocument(
+        doc = RAGDocument(
             document_id="dummy",
             content=data_uri,
             mime_type="application/pdf",
             metadata={},
         )
         content = await content_from_doc(doc)
-        assert content == "Dummy PDF file"
+        assert content == "Dumm y PDF file"
 
     @pytest.mark.asyncio
     async def test_downloads_pdf_and_returns_content(self):
         # Using GitHub to host the PDF file
         url = "https://raw.githubusercontent.com/meta-llama/llama-stack/da035d69cfca915318eaf485770a467ca3c2a238/llama_stack/providers/tests/memory/fixtures/dummy.pdf"
-        doc = MemoryBankDocument(
+        doc = RAGDocument(
             document_id="dummy",
             content=url,
             mime_type="application/pdf",
             metadata={},
         )
         content = await content_from_doc(doc)
-        assert content == "Dummy PDF file"
+        assert content == "Dumm y PDF file"
 
     @pytest.mark.asyncio
     async def test_downloads_pdf_and_returns_content_with_url_object(self):
         # Using GitHub to host the PDF file
         url = "https://raw.githubusercontent.com/meta-llama/llama-stack/da035d69cfca915318eaf485770a467ca3c2a238/llama_stack/providers/tests/memory/fixtures/dummy.pdf"
-        doc = MemoryBankDocument(
+        doc = RAGDocument(
             document_id="dummy",
             content=URL(
                 uri=url,
@@ -73,4 +74,4 @@ class TestVectorStore:
             metadata={},
         )
         content = await content_from_doc(doc)
-        assert content == "Dummy PDF file"
+        assert content == "Dumm y PDF file"
diff --git a/llama_stack/providers/utils/inference/openai_compat.py b/llama_stack/providers/utils/inference/openai_compat.py
index 127fd19f3..6c93f49c0 100644
--- a/llama_stack/providers/utils/inference/openai_compat.py
+++ b/llama_stack/providers/utils/inference/openai_compat.py
@@ -240,7 +240,7 @@ async def process_chat_completion_stream_response(
                 event=ChatCompletionResponseEvent(
                     event_type=ChatCompletionResponseEventType.progress,
                     delta=ToolCallDelta(
-                        content="",
+                        tool_call="",
                         parse_status=ToolCallParseStatus.started,
                     ),
                 )
@@ -260,7 +260,7 @@ async def process_chat_completion_stream_response(
         if ipython:
             buffer += text
             delta = ToolCallDelta(
-                content=text,
+                tool_call=text,
                 parse_status=ToolCallParseStatus.in_progress,
             )
 
@@ -289,7 +289,7 @@ async def process_chat_completion_stream_response(
             event=ChatCompletionResponseEvent(
                 event_type=ChatCompletionResponseEventType.progress,
                 delta=ToolCallDelta(
-                    content="",
+                    tool_call="",
                     parse_status=ToolCallParseStatus.failed,
                 ),
                 stop_reason=stop_reason,
@@ -301,7 +301,7 @@ async def process_chat_completion_stream_response(
             event=ChatCompletionResponseEvent(
                 event_type=ChatCompletionResponseEventType.progress,
                 delta=ToolCallDelta(
-                    content=tool_call,
+                    tool_call=tool_call,
                     parse_status=ToolCallParseStatus.succeeded,
                 ),
                 stop_reason=stop_reason,
diff --git a/llama_stack/providers/utils/inference/prompt_adapter.py b/llama_stack/providers/utils/inference/prompt_adapter.py
index 7ee19fd7b..f5298d844 100644
--- a/llama_stack/providers/utils/inference/prompt_adapter.py
+++ b/llama_stack/providers/utils/inference/prompt_adapter.py
@@ -113,28 +113,29 @@ async def interleaved_content_convert_to_raw(
         elif isinstance(c, TextContentItem):
             return RawTextItem(text=c.text)
         elif isinstance(c, ImageContentItem):
-            if c.url:
+            image = c.image
+            if image.url:
                 # Load image bytes from URL
-                if c.url.uri.startswith("data"):
-                    match = re.match(r"data:image/(\w+);base64,(.+)", c.url.uri)
+                if image.url.uri.startswith("data"):
+                    match = re.match(r"data:image/(\w+);base64,(.+)", image.url.uri)
                     if not match:
                         raise ValueError(
-                            f"Invalid data URL format, {c.url.uri[:40]}..."
+                            f"Invalid data URL format, {image.url.uri[:40]}..."
                         )
                     _, image_data = match.groups()
                     data = base64.b64decode(image_data)
-                elif c.url.uri.startswith("file://"):
-                    path = c.url.uri[len("file://") :]
+                elif image.url.uri.startswith("file://"):
+                    path = image.url.uri[len("file://") :]
                     with open(path, "rb") as f:
                         data = f.read()  # type: ignore
-                elif c.url.uri.startswith("http"):
+                elif image.url.uri.startswith("http"):
                     async with httpx.AsyncClient() as client:
-                        response = await client.get(c.url.uri)
+                        response = await client.get(image.url.uri)
                         data = response.content
                 else:
                     raise ValueError("Unsupported URL type")
-            elif c.data:
-                data = c.data
+            elif image.data:
+                data = image.data
             else:
                 raise ValueError("No data or URL provided")
 
@@ -170,26 +171,29 @@ def request_has_media(request: Union[ChatCompletionRequest, CompletionRequest]):
 
 
 async def localize_image_content(media: ImageContentItem) -> Tuple[bytes, str]:
-    if media.url and media.url.uri.startswith("http"):
+    image = media.image
+    if image.url and image.url.uri.startswith("http"):
         async with httpx.AsyncClient() as client:
-            r = await client.get(media.url.uri)
+            r = await client.get(image.url.uri)
             content = r.content
             content_type = r.headers.get("content-type")
             if content_type:
                 format = content_type.split("/")[-1]
             else:
                 format = "png"
+
         return content, format
     else:
-        image = PIL_Image.open(io.BytesIO(media.data))
-        return media.data, image.format
+        pil_image = PIL_Image.open(io.BytesIO(image.data))
+        return image.data, pil_image.format
 
 
 async def convert_image_content_to_url(
     media: ImageContentItem, download: bool = False, include_format: bool = True
 ) -> str:
-    if media.url and not download:
-        return media.url.uri
+    image = media.image
+    if image.url and (not download or image.url.uri.startswith("data")):
+        return image.url.uri
 
     content, format = await localize_image_content(media)
     if include_format:
diff --git a/llama_stack/providers/utils/memory/vector_store.py b/llama_stack/providers/utils/memory/vector_store.py
index c97633558..82c0c9c07 100644
--- a/llama_stack/providers/utils/memory/vector_store.py
+++ b/llama_stack/providers/utils/memory/vector_store.py
@@ -18,6 +18,7 @@ import numpy as np
 
 from llama_models.llama3.api.tokenizer import Tokenizer
 from numpy.typing import NDArray
+
 from pypdf import PdfReader
 
 from llama_stack.apis.common.content_types import (
@@ -25,8 +26,9 @@ from llama_stack.apis.common.content_types import (
     TextContentItem,
     URL,
 )
-from llama_stack.apis.memory import Chunk, MemoryBankDocument, QueryDocumentsResponse
-from llama_stack.apis.memory_banks import VectorMemoryBank
+from llama_stack.apis.tools import RAGDocument
+from llama_stack.apis.vector_dbs import VectorDB
+from llama_stack.apis.vector_io import Chunk, QueryChunksResponse
 from llama_stack.providers.datatypes import Api
 from llama_stack.providers.utils.inference.prompt_adapter import (
     interleaved_content_as_str,
@@ -112,7 +114,7 @@ def concat_interleaved_content(content: List[InterleavedContent]) -> Interleaved
     return ret
 
 
-async def content_from_doc(doc: MemoryBankDocument) -> str:
+async def content_from_doc(doc: RAGDocument) -> str:
     if isinstance(doc.content, URL):
         if doc.content.uri.startswith("data:"):
             return content_from_data(doc.content.uri)
@@ -151,7 +153,13 @@ def make_overlapped_chunks(
         chunk = tokenizer.decode(toks)
         # chunk is a string
         chunks.append(
-            Chunk(content=chunk, token_count=len(toks), document_id=document_id)
+            Chunk(
+                content=chunk,
+                metadata={
+                    "token_count": len(toks),
+                    "document_id": document_id,
+                },
+            )
         )
 
     return chunks
@@ -165,7 +173,7 @@ class EmbeddingIndex(ABC):
     @abstractmethod
     async def query(
         self, embedding: NDArray, k: int, score_threshold: float
-    ) -> QueryDocumentsResponse:
+    ) -> QueryChunksResponse:
         raise NotImplementedError()
 
     @abstractmethod
@@ -174,56 +182,35 @@ class EmbeddingIndex(ABC):
 
 
 @dataclass
-class BankWithIndex:
-    bank: VectorMemoryBank
+class VectorDBWithIndex:
+    vector_db: VectorDB
     index: EmbeddingIndex
     inference_api: Api.inference
 
-    async def insert_documents(
+    async def insert_chunks(
         self,
-        documents: List[MemoryBankDocument],
+        chunks: List[Chunk],
     ) -> None:
-        for doc in documents:
-            content = await content_from_doc(doc)
-            chunks = make_overlapped_chunks(
-                doc.document_id,
-                content,
-                self.bank.chunk_size_in_tokens,
-                self.bank.overlap_size_in_tokens
-                or (self.bank.chunk_size_in_tokens // 4),
-            )
-            if not chunks:
-                continue
-            embeddings_response = await self.inference_api.embeddings(
-                self.bank.embedding_model, [x.content for x in chunks]
-            )
-            embeddings = np.array(embeddings_response.embeddings)
+        embeddings_response = await self.inference_api.embeddings(
+            self.vector_db.embedding_model, [x.content for x in chunks]
+        )
+        embeddings = np.array(embeddings_response.embeddings)
 
-            await self.index.add_chunks(chunks, embeddings)
+        await self.index.add_chunks(chunks, embeddings)
 
-    async def query_documents(
+    async def query_chunks(
         self,
         query: InterleavedContent,
         params: Optional[Dict[str, Any]] = None,
-    ) -> QueryDocumentsResponse:
+    ) -> QueryChunksResponse:
         if params is None:
             params = {}
         k = params.get("max_chunks", 3)
         score_threshold = params.get("score_threshold", 0.0)
 
-        def _process(c) -> str:
-            if isinstance(c, str):
-                return c
-            else:
-                return "<media>"
-
-        if isinstance(query, list):
-            query_str = " ".join([_process(c) for c in query])
-        else:
-            query_str = _process(query)
-
+        query_str = interleaved_content_as_str(query)
         embeddings_response = await self.inference_api.embeddings(
-            self.bank.embedding_model, [query_str]
+            self.vector_db.embedding_model, [query_str]
         )
         query_vector = np.array(embeddings_response.embeddings[0], dtype=np.float32)
         return await self.index.query(query_vector, k, score_threshold)
diff --git a/llama_stack/providers/utils/telemetry/dataset_mixin.py b/llama_stack/providers/utils/telemetry/dataset_mixin.py
index 6806f39aa..a2bfdcb87 100644
--- a/llama_stack/providers/utils/telemetry/dataset_mixin.py
+++ b/llama_stack/providers/utils/telemetry/dataset_mixin.py
@@ -22,6 +22,9 @@ class TelemetryDatasetMixin:
         dataset_id: str,
         max_depth: Optional[int] = None,
     ) -> None:
+        if self.datasetio_api is None:
+            raise RuntimeError("DatasetIO API not available")
+
         spans = await self.query_spans(
             attribute_filters=attribute_filters,
             attributes_to_return=attributes_to_save,
diff --git a/llama_stack/scripts/test_rag_via_curl.py b/llama_stack/scripts/test_rag_via_curl.py
new file mode 100644
index 000000000..28d6fb601
--- /dev/null
+++ b/llama_stack/scripts/test_rag_via_curl.py
@@ -0,0 +1,105 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+import json
+from typing import List
+
+import pytest
+import requests
+from pydantic import TypeAdapter
+
+from llama_stack.apis.tools import (
+    DefaultRAGQueryGeneratorConfig,
+    RAGDocument,
+    RAGQueryConfig,
+    RAGQueryResult,
+)
+from llama_stack.apis.vector_dbs import VectorDB
+from llama_stack.providers.utils.memory.vector_store import interleaved_content_as_str
+
+
+class TestRAGToolEndpoints:
+    @pytest.fixture
+    def base_url(self) -> str:
+        return "http://localhost:8321/v1"  # Adjust port if needed
+
+    @pytest.fixture
+    def sample_documents(self) -> List[RAGDocument]:
+        return [
+            RAGDocument(
+                document_id="doc1",
+                content="Python is a high-level programming language.",
+                metadata={"category": "programming", "difficulty": "beginner"},
+            ),
+            RAGDocument(
+                document_id="doc2",
+                content="Machine learning is a subset of artificial intelligence.",
+                metadata={"category": "AI", "difficulty": "advanced"},
+            ),
+            RAGDocument(
+                document_id="doc3",
+                content="Data structures are fundamental to computer science.",
+                metadata={"category": "computer science", "difficulty": "intermediate"},
+            ),
+        ]
+
+    @pytest.mark.asyncio
+    async def test_rag_workflow(
+        self, base_url: str, sample_documents: List[RAGDocument]
+    ):
+        vector_db_payload = {
+            "vector_db_id": "test_vector_db",
+            "embedding_model": "all-MiniLM-L6-v2",
+            "embedding_dimension": 384,
+        }
+
+        response = requests.post(f"{base_url}/vector-dbs", json=vector_db_payload)
+        assert response.status_code == 200
+        vector_db = VectorDB(**response.json())
+
+        insert_payload = {
+            "documents": [
+                json.loads(doc.model_dump_json()) for doc in sample_documents
+            ],
+            "vector_db_id": vector_db.identifier,
+            "chunk_size_in_tokens": 512,
+        }
+
+        response = requests.post(
+            f"{base_url}/tool-runtime/rag-tool/insert-documents",
+            json=insert_payload,
+        )
+        assert response.status_code == 200
+
+        query = "What is Python?"
+        query_config = RAGQueryConfig(
+            query_generator_config=DefaultRAGQueryGeneratorConfig(),
+            max_tokens_in_context=4096,
+            max_chunks=2,
+        )
+
+        query_payload = {
+            "content": query,
+            "query_config": json.loads(query_config.model_dump_json()),
+            "vector_db_ids": [vector_db.identifier],
+        }
+
+        response = requests.post(
+            f"{base_url}/tool-runtime/rag-tool/query-context",
+            json=query_payload,
+        )
+        assert response.status_code == 200
+        result = response.json()
+        result = TypeAdapter(RAGQueryResult).validate_python(result)
+
+        content_str = interleaved_content_as_str(result.content)
+        print(f"content: {content_str}")
+        assert len(content_str) > 0
+        assert "Python" in content_str
+
+        # Clean up: Delete the vector DB
+        response = requests.delete(f"{base_url}/vector-dbs/{vector_db.identifier}")
+        assert response.status_code == 200
diff --git a/llama_stack/templates/bedrock/bedrock.py b/llama_stack/templates/bedrock/bedrock.py
index c80625cf6..6b83e9536 100644
--- a/llama_stack/templates/bedrock/bedrock.py
+++ b/llama_stack/templates/bedrock/bedrock.py
@@ -10,7 +10,7 @@ from llama_models.sku_list import all_registered_models
 
 from llama_stack.apis.models import ModelInput
 from llama_stack.distribution.datatypes import Provider, ToolGroupInput
-from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
+from llama_stack.providers.inline.vector_io.faiss.config import FaissImplConfig
 from llama_stack.providers.remote.inference.bedrock.bedrock import MODEL_ALIASES
 from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
 
@@ -18,7 +18,7 @@ from llama_stack.templates.template import DistributionTemplate, RunConfigSettin
 def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["remote::bedrock"],
-        "memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
         "safety": ["remote::bedrock"],
         "agents": ["inline::meta-reference"],
         "telemetry": ["inline::meta-reference"],
@@ -29,11 +29,12 @@ def get_distribution_template() -> DistributionTemplate:
             "remote::brave-search",
             "remote::tavily-search",
             "inline::code-interpreter",
-            "inline::memory-runtime",
+            "inline::rag-runtime",
+            "remote::model-context-protocol",
         ],
     }
     name = "bedrock"
-    memory_provider = Provider(
+    vector_io_provider = Provider(
         provider_id="faiss",
         provider_type="inline::faiss",
         config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
@@ -57,8 +58,8 @@ def get_distribution_template() -> DistributionTemplate:
             provider_id="tavily-search",
         ),
         ToolGroupInput(
-            toolgroup_id="builtin::memory",
-            provider_id="memory-runtime",
+            toolgroup_id="builtin::rag",
+            provider_id="rag-runtime",
         ),
         ToolGroupInput(
             toolgroup_id="builtin::code_interpreter",
@@ -70,14 +71,14 @@ def get_distribution_template() -> DistributionTemplate:
         name=name,
         distro_type="self_hosted",
         description="Use AWS Bedrock for running LLM inference and safety",
-        docker_image=None,
+        container_image=None,
         template_path=Path(__file__).parent / "doc_template.md",
         providers=providers,
         default_models=default_models,
         run_configs={
             "run.yaml": RunConfigSettings(
                 provider_overrides={
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=default_models,
                 default_tool_groups=default_tool_groups,
diff --git a/llama_stack/templates/bedrock/build.yaml b/llama_stack/templates/bedrock/build.yaml
index 794e54306..6c07b0478 100644
--- a/llama_stack/templates/bedrock/build.yaml
+++ b/llama_stack/templates/bedrock/build.yaml
@@ -4,7 +4,7 @@ distribution_spec:
   providers:
     inference:
     - remote::bedrock
-    memory:
+    vector_io:
     - inline::faiss
     - remote::chromadb
     - remote::pgvector
@@ -27,5 +27,6 @@ distribution_spec:
     - remote::brave-search
     - remote::tavily-search
     - inline::code-interpreter
-    - inline::memory-runtime
+    - inline::rag-runtime
+    - remote::model-context-protocol
 image_type: conda
diff --git a/llama_stack/templates/bedrock/run.yaml b/llama_stack/templates/bedrock/run.yaml
index 3a6922ae7..39408c1bd 100644
--- a/llama_stack/templates/bedrock/run.yaml
+++ b/llama_stack/templates/bedrock/run.yaml
@@ -5,17 +5,17 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: bedrock
     provider_type: remote::bedrock
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -78,8 +78,11 @@ providers:
   - provider_id: code-interpreter
     provider_type: inline::code-interpreter
     config: {}
-  - provider_id: memory-runtime
-    provider_type: inline::memory-runtime
+  - provider_id: rag-runtime
+    provider_type: inline::rag-runtime
+    config: {}
+  - provider_id: model-context-protocol
+    provider_type: remote::model-context-protocol
     config: {}
 metadata_store:
   type: sqlite
@@ -101,14 +104,14 @@ models:
   provider_model_id: meta.llama3-1-405b-instruct-v1:0
   model_type: llm
 shields: []
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []
 tool_groups:
 - toolgroup_id: builtin::websearch
   provider_id: tavily-search
-- toolgroup_id: builtin::memory
-  provider_id: memory-runtime
+- toolgroup_id: builtin::rag
+  provider_id: rag-runtime
 - toolgroup_id: builtin::code_interpreter
   provider_id: code-interpreter
diff --git a/llama_stack/templates/cerebras/build.yaml b/llama_stack/templates/cerebras/build.yaml
index 9f187d3c7..9d5ab1a52 100644
--- a/llama_stack/templates/cerebras/build.yaml
+++ b/llama_stack/templates/cerebras/build.yaml
@@ -6,7 +6,7 @@ distribution_spec:
     - remote::cerebras
     safety:
     - inline::llama-guard
-    memory:
+    vector_io:
     - inline::faiss
     - remote::chromadb
     - remote::pgvector
@@ -27,5 +27,5 @@ distribution_spec:
     - remote::brave-search
     - remote::tavily-search
     - inline::code-interpreter
-    - inline::memory-runtime
+    - inline::rag-runtime
 image_type: conda
diff --git a/llama_stack/templates/cerebras/cerebras.py b/llama_stack/templates/cerebras/cerebras.py
index df3b55ddd..50a878645 100644
--- a/llama_stack/templates/cerebras/cerebras.py
+++ b/llama_stack/templates/cerebras/cerebras.py
@@ -13,7 +13,7 @@ from llama_stack.distribution.datatypes import ModelInput, Provider, ToolGroupIn
 from llama_stack.providers.inline.inference.sentence_transformers import (
     SentenceTransformersInferenceConfig,
 )
-from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
+from llama_stack.providers.inline.vector_io.faiss.config import FaissImplConfig
 from llama_stack.providers.remote.inference.cerebras import CerebrasImplConfig
 from llama_stack.providers.remote.inference.cerebras.cerebras import model_aliases
 from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
@@ -23,7 +23,7 @@ def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["remote::cerebras"],
         "safety": ["inline::llama-guard"],
-        "memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
         "agents": ["inline::meta-reference"],
         "eval": ["inline::meta-reference"],
         "datasetio": ["remote::huggingface", "inline::localfs"],
@@ -33,7 +33,7 @@ def get_distribution_template() -> DistributionTemplate:
             "remote::brave-search",
             "remote::tavily-search",
             "inline::code-interpreter",
-            "inline::memory-runtime",
+            "inline::rag-runtime",
         ],
     }
 
@@ -68,7 +68,7 @@ def get_distribution_template() -> DistributionTemplate:
             "embedding_dimension": 384,
         },
     )
-    memory_provider = Provider(
+    vector_io_provider = Provider(
         provider_id="faiss",
         provider_type="inline::faiss",
         config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
@@ -79,8 +79,8 @@ def get_distribution_template() -> DistributionTemplate:
             provider_id="tavily-search",
         ),
         ToolGroupInput(
-            toolgroup_id="builtin::memory",
-            provider_id="memory-runtime",
+            toolgroup_id="builtin::rag",
+            provider_id="rag-runtime",
         ),
         ToolGroupInput(
             toolgroup_id="builtin::code_interpreter",
@@ -92,7 +92,7 @@ def get_distribution_template() -> DistributionTemplate:
         name="cerebras",
         distro_type="self_hosted",
         description="Use Cerebras for running LLM inference",
-        docker_image=None,
+        container_image=None,
         template_path=Path(__file__).parent / "doc_template.md",
         providers=providers,
         default_models=default_models,
@@ -100,7 +100,7 @@ def get_distribution_template() -> DistributionTemplate:
             "run.yaml": RunConfigSettings(
                 provider_overrides={
                     "inference": [inference_provider, embedding_provider],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=default_models + [embedding_model],
                 default_shields=[],
diff --git a/llama_stack/templates/cerebras/report.md b/llama_stack/templates/cerebras/report.md
new file mode 100644
index 000000000..7c09474b1
--- /dev/null
+++ b/llama_stack/templates/cerebras/report.md
@@ -0,0 +1,44 @@
+# Report for cerebras distribution
+
+## Supported Models
+| Model Descriptor | cerebras |
+|:---|:---|
+| meta-llama/Llama-3-8B-Instruct | ❌ |
+| meta-llama/Llama-3-70B-Instruct | ❌ |
+| meta-llama/Llama-3.1-8B-Instruct | ✅ |
+| meta-llama/Llama-3.1-70B-Instruct | ❌ |
+| meta-llama/Llama-3.1-405B-Instruct-FP8 | ❌ |
+| meta-llama/Llama-3.2-1B-Instruct | ❌ |
+| meta-llama/Llama-3.2-3B-Instruct | ❌ |
+| meta-llama/Llama-3.2-11B-Vision-Instruct | ❌ |
+| meta-llama/Llama-3.2-90B-Vision-Instruct | ❌ |
+| meta-llama/Llama-3.3-70B-Instruct | ✅ |
+| meta-llama/Llama-Guard-3-11B-Vision | ❌ |
+| meta-llama/Llama-Guard-3-1B | ❌ |
+| meta-llama/Llama-Guard-3-8B | ❌ |
+| meta-llama/Llama-Guard-2-8B | ❌ |
+
+## Inference
+| Model | API | Capability | Test | Status |
+|:----- |:-----|:-----|:-----|:-----|
+| Llama-3.1-8B-Instruct | /chat_completion | streaming | test_text_chat_completion_streaming | ✅ |
+| Llama-3.2-11B-Vision-Instruct | /chat_completion | streaming | test_image_chat_completion_streaming | ❌ |
+| Llama-3.2-11B-Vision-Instruct | /chat_completion | non_streaming | test_image_chat_completion_non_streaming | ❌ |
+| Llama-3.1-8B-Instruct | /chat_completion | non_streaming | test_text_chat_completion_non_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /chat_completion | tool_calling | test_text_chat_completion_with_tool_calling_and_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /chat_completion | tool_calling | test_text_chat_completion_with_tool_calling_and_non_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /completion | streaming | test_text_completion_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /completion | non_streaming | test_text_completion_non_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /completion | structured_output | test_text_completion_structured_output | ❌ |
+
+## Vector IO
+| API | Capability | Test | Status |
+|:-----|:-----|:-----|:-----|
+| /retrieve |  | test_vector_db_retrieve | ✅ |
+
+## Agents
+| API | Capability | Test | Status |
+|:-----|:-----|:-----|:-----|
+| /create_agent_turn | rag | test_rag_agent | ✅ |
+| /create_agent_turn | custom_tool | test_custom_tool | ❌ |
+| /create_agent_turn | code_execution | test_code_interpreter_for_attachments | ✅ |
diff --git a/llama_stack/templates/cerebras/run.yaml b/llama_stack/templates/cerebras/run.yaml
index bfc492bda..5a70890a8 100644
--- a/llama_stack/templates/cerebras/run.yaml
+++ b/llama_stack/templates/cerebras/run.yaml
@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: cerebras
@@ -24,7 +24,7 @@ providers:
   - provider_id: llama-guard
     provider_type: inline::llama-guard
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -83,8 +83,8 @@ providers:
   - provider_id: code-interpreter
     provider_type: inline::code-interpreter
     config: {}
-  - provider_id: memory-runtime
-    provider_type: inline::memory-runtime
+  - provider_id: rag-runtime
+    provider_type: inline::rag-runtime
     config: {}
 metadata_store:
   type: sqlite
@@ -106,14 +106,14 @@ models:
   provider_id: sentence-transformers
   model_type: embedding
 shields: []
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []
 tool_groups:
 - toolgroup_id: builtin::websearch
   provider_id: tavily-search
-- toolgroup_id: builtin::memory
-  provider_id: memory-runtime
+- toolgroup_id: builtin::rag
+  provider_id: rag-runtime
 - toolgroup_id: builtin::code_interpreter
   provider_id: code-interpreter
diff --git a/llama_stack/templates/experimental-post-training/build.yaml b/llama_stack/templates/experimental-post-training/build.yaml
index 4997ab8a3..c146d1b37 100644
--- a/llama_stack/templates/experimental-post-training/build.yaml
+++ b/llama_stack/templates/experimental-post-training/build.yaml
@@ -2,7 +2,7 @@ version: '2'
 name: experimental-post-training
 distribution_spec:
   description: Experimental template for post training
-  docker_image: null
+  container_image: null
   providers:
     inference:
     - inline::meta-reference
@@ -22,7 +22,7 @@ distribution_spec:
     - inline::meta-reference
     safety:
     - inline::llama-guard
-    memory:
+    vector_io:
     - inline::faiss
     tool_runtime:
     - remote::brave-search
diff --git a/llama_stack/templates/experimental-post-training/run.yaml b/llama_stack/templates/experimental-post-training/run.yaml
index 2e0ee029b..75d103c9f 100644
--- a/llama_stack/templates/experimental-post-training/run.yaml
+++ b/llama_stack/templates/experimental-post-training/run.yaml
@@ -1,13 +1,13 @@
 version: '2'
 image_name: experimental-post-training
-docker_image: null
+container_image: null
 conda_env: experimental-post-training
 apis:
 - agents
 - datasetio
 - eval
 - inference
-- memory
+- vector_io
 - safety
 - scoring
 - telemetry
@@ -60,7 +60,7 @@ providers:
   - provider_id: llama-guard
     provider_type: inline::llama-guard
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -82,7 +82,7 @@ metadata_store:
   db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/meta-reference-gpu}/registry.db
 models: []
 shields: []
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []
diff --git a/llama_stack/templates/fireworks/build.yaml b/llama_stack/templates/fireworks/build.yaml
index 504c913bd..cdd60ec2a 100644
--- a/llama_stack/templates/fireworks/build.yaml
+++ b/llama_stack/templates/fireworks/build.yaml
@@ -4,7 +4,7 @@ distribution_spec:
   providers:
     inference:
     - remote::fireworks
-    memory:
+    vector_io:
     - inline::faiss
     - remote::chromadb
     - remote::pgvector
@@ -27,5 +27,6 @@ distribution_spec:
     - remote::brave-search
     - remote::tavily-search
     - inline::code-interpreter
-    - inline::memory-runtime
+    - inline::rag-runtime
+    - remote::model-context-protocol
 image_type: conda
diff --git a/llama_stack/templates/fireworks/fireworks.py b/llama_stack/templates/fireworks/fireworks.py
index 8add75f7d..546a8b82a 100644
--- a/llama_stack/templates/fireworks/fireworks.py
+++ b/llama_stack/templates/fireworks/fireworks.py
@@ -18,7 +18,7 @@ from llama_stack.distribution.datatypes import (
 from llama_stack.providers.inline.inference.sentence_transformers import (
     SentenceTransformersInferenceConfig,
 )
-from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
+from llama_stack.providers.inline.vector_io.faiss.config import FaissImplConfig
 from llama_stack.providers.remote.inference.fireworks import FireworksImplConfig
 from llama_stack.providers.remote.inference.fireworks.fireworks import MODEL_ALIASES
 from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
@@ -27,7 +27,7 @@ from llama_stack.templates.template import DistributionTemplate, RunConfigSettin
 def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["remote::fireworks"],
-        "memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
         "safety": ["inline::llama-guard"],
         "agents": ["inline::meta-reference"],
         "telemetry": ["inline::meta-reference"],
@@ -38,7 +38,8 @@ def get_distribution_template() -> DistributionTemplate:
             "remote::brave-search",
             "remote::tavily-search",
             "inline::code-interpreter",
-            "inline::memory-runtime",
+            "inline::rag-runtime",
+            "remote::model-context-protocol",
         ],
     }
 
@@ -54,7 +55,7 @@ def get_distribution_template() -> DistributionTemplate:
         provider_type="inline::sentence-transformers",
         config=SentenceTransformersInferenceConfig.sample_run_config(),
     )
-    memory_provider = Provider(
+    vector_io_provider = Provider(
         provider_id="faiss",
         provider_type="inline::faiss",
         config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
@@ -85,8 +86,8 @@ def get_distribution_template() -> DistributionTemplate:
             provider_id="tavily-search",
         ),
         ToolGroupInput(
-            toolgroup_id="builtin::memory",
-            provider_id="memory-runtime",
+            toolgroup_id="builtin::rag",
+            provider_id="rag-runtime",
         ),
         ToolGroupInput(
             toolgroup_id="builtin::code_interpreter",
@@ -98,7 +99,7 @@ def get_distribution_template() -> DistributionTemplate:
         name=name,
         distro_type="self_hosted",
         description="Use Fireworks.AI for running LLM inference",
-        docker_image=None,
+        container_image=None,
         template_path=Path(__file__).parent / "doc_template.md",
         providers=providers,
         default_models=default_models,
@@ -106,7 +107,7 @@ def get_distribution_template() -> DistributionTemplate:
             "run.yaml": RunConfigSettings(
                 provider_overrides={
                     "inference": [inference_provider, embedding_provider],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=default_models + [embedding_model],
                 default_shields=[ShieldInput(shield_id="meta-llama/Llama-Guard-3-8B")],
@@ -118,7 +119,7 @@ def get_distribution_template() -> DistributionTemplate:
                         inference_provider,
                         embedding_provider,
                     ],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                     "safety": [
                         Provider(
                             provider_id="llama-guard",
diff --git a/llama_stack/templates/fireworks/remote-hosted-report.md b/llama_stack/templates/fireworks/remote-hosted-report.md
new file mode 100644
index 000000000..2f3c882b7
--- /dev/null
+++ b/llama_stack/templates/fireworks/remote-hosted-report.md
@@ -0,0 +1,45 @@
+# Report for fireworks distribution
+
+## Supported Models
+| Model Descriptor | fireworks |
+|:---|:---|
+| meta-llama/Llama-3-8B-Instruct | ❌ |
+| meta-llama/Llama-3-70B-Instruct | ❌ |
+| meta-llama/Llama-3.1-8B-Instruct | ❌ |
+| meta-llama/Llama-3.1-70B-Instruct | ❌ |
+| meta-llama/Llama-3.1-405B-Instruct-FP8 | ❌ |
+| meta-llama/Llama-3.2-1B-Instruct | ❌ |
+| meta-llama/Llama-3.2-3B-Instruct | ❌ |
+| meta-llama/Llama-3.2-11B-Vision-Instruct | ❌ |
+| meta-llama/Llama-3.2-90B-Vision-Instruct | ❌ |
+| meta-llama/Llama-3.3-70B-Instruct | ❌ |
+| meta-llama/Llama-Guard-3-11B-Vision | ❌ |
+| meta-llama/Llama-Guard-3-1B | ❌ |
+| meta-llama/Llama-Guard-3-8B | ❌ |
+| meta-llama/Llama-Guard-2-8B | ❌ |
+
+## Inference
+| Model | API | Capability | Test | Status |
+|:----- |:-----|:-----|:-----|:-----|
+| Text | /chat_completion | streaming | test_text_chat_completion_streaming | ❌ |
+| Vision | /chat_completion | streaming | test_image_chat_completion_streaming | ❌ |
+| Vision | /chat_completion | non_streaming | test_image_chat_completion_non_streaming | ❌ |
+| Text | /chat_completion | non_streaming | test_text_chat_completion_non_streaming | ❌ |
+| Text | /chat_completion | tool_calling | test_text_chat_completion_with_tool_calling_and_streaming | ❌ |
+| Text | /chat_completion | tool_calling | test_text_chat_completion_with_tool_calling_and_non_streaming | ❌ |
+| Text | /completion | streaming | test_text_completion_streaming | ❌ |
+| Text | /completion | non_streaming | test_text_completion_non_streaming | ❌ |
+| Text | /completion | structured_output | test_text_completion_structured_output | ❌ |
+
+## Memory:
+| API | Capability | Test | Status |
+|:-----|:-----|:-----|:-----|
+| /insert, /query | inline | test_memory_bank_insert_inline_and_query | ❌ |
+| /insert, /query | url | test_memory_bank_insert_from_url_and_query | ❌ |
+
+## Agents
+| API | Capability | Test | Status |
+|:-----|:-----|:-----|:-----|
+| create_agent_turn | rag | test_rag_agent | ❌ |
+| create_agent_turn | custom_tool | test_custom_tool | ❌ |
+| create_agent_turn | code_execution | test_code_execution | ❌ |
diff --git a/llama_stack/templates/fireworks/report.md b/llama_stack/templates/fireworks/report.md
new file mode 100644
index 000000000..2c1ccc943
--- /dev/null
+++ b/llama_stack/templates/fireworks/report.md
@@ -0,0 +1,46 @@
+# Report for fireworks distribution
+
+## Supported Models
+| Model Descriptor | fireworks |
+|:---|:---|
+| Llama-3-8B-Instruct | ❌ |
+| Llama-3-70B-Instruct | ❌ |
+| Llama3.1-8B-Instruct | ✅ |
+| Llama3.1-70B-Instruct | ✅ |
+| Llama3.1-405B-Instruct | ✅ |
+| Llama3.2-1B-Instruct | ✅ |
+| Llama3.2-3B-Instruct | ✅ |
+| Llama3.2-11B-Vision-Instruct | ✅ |
+| Llama3.2-90B-Vision-Instruct | ✅ |
+| Llama3.3-70B-Instruct | ✅ |
+| Llama-Guard-3-11B-Vision | ✅ |
+| Llama-Guard-3-1B | ❌ |
+| Llama-Guard-3-8B | ✅ |
+| Llama-Guard-2-8B | ❌ |
+
+## Inference
+| Model | API | Capability | Test | Status |
+|:----- |:-----|:-----|:-----|:-----|
+| Llama-3.1-8B-Instruct | /chat_completion | streaming | test_text_chat_completion_streaming | ✅ |
+| Llama-3.2-11B-Vision-Instruct | /chat_completion | streaming | test_image_chat_completion_streaming | ✅ |
+| Llama-3.2-11B-Vision-Instruct | /chat_completion | non_streaming | test_image_chat_completion_non_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /chat_completion | non_streaming | test_text_chat_completion_non_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /chat_completion | tool_calling | test_text_chat_completion_with_tool_calling_and_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /chat_completion | tool_calling | test_text_chat_completion_with_tool_calling_and_non_streaming | ✅ |
+| Llama-3.2-11B-Vision-Instruct | /chat_completion | log_probs | test_completion_log_probs_non_streaming | ✅ |
+| Llama-3.2-11B-Vision-Instruct | /chat_completion | log_probs | test_completion_log_probs_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /completion | streaming | test_text_completion_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /completion | non_streaming | test_text_completion_non_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /completion | structured_output | test_text_completion_structured_output | ✅ |
+
+## Vector IO
+| Provider | API | Capability | Test | Status |
+|:-----|:-----|:-----|:-----|:-----|
+| inline::faiss | /retrieve |  | test_vector_db_retrieve | ✅ |
+
+## Agents
+| Provider | API | Capability | Test | Status |
+|:-----|:-----|:-----|:-----|:-----|
+| inline::meta-reference | /create_agent_turn | rag | test_rag_agent | ✅ |
+| inline::meta-reference | /create_agent_turn | custom_tool | test_custom_tool | ✅ |
+| inline::meta-reference | /create_agent_turn | code_execution | test_code_interpreter_for_attachments | ✅ |
diff --git a/llama_stack/templates/fireworks/run-with-safety.yaml b/llama_stack/templates/fireworks/run-with-safety.yaml
index 8fefbd98a..a4b425436 100644
--- a/llama_stack/templates/fireworks/run-with-safety.yaml
+++ b/llama_stack/templates/fireworks/run-with-safety.yaml
@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: fireworks
@@ -20,7 +20,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -89,8 +89,11 @@ providers:
   - provider_id: code-interpreter
     provider_type: inline::code-interpreter
     config: {}
-  - provider_id: memory-runtime
-    provider_type: inline::memory-runtime
+  - provider_id: rag-runtime
+    provider_type: inline::rag-runtime
+    config: {}
+  - provider_id: model-context-protocol
+    provider_type: remote::model-context-protocol
     config: {}
 metadata_store:
   type: sqlite
@@ -158,14 +161,14 @@ shields:
   provider_id: llama-guard-vision
 - shield_id: CodeScanner
   provider_id: code-scanner
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []
 tool_groups:
 - toolgroup_id: builtin::websearch
   provider_id: tavily-search
-- toolgroup_id: builtin::memory
-  provider_id: memory-runtime
+- toolgroup_id: builtin::rag
+  provider_id: rag-runtime
 - toolgroup_id: builtin::code_interpreter
   provider_id: code-interpreter
diff --git a/llama_stack/templates/fireworks/run.yaml b/llama_stack/templates/fireworks/run.yaml
index 53128f456..a497317bd 100644
--- a/llama_stack/templates/fireworks/run.yaml
+++ b/llama_stack/templates/fireworks/run.yaml
@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: fireworks
@@ -20,7 +20,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -83,8 +83,11 @@ providers:
   - provider_id: code-interpreter
     provider_type: inline::code-interpreter
     config: {}
-  - provider_id: memory-runtime
-    provider_type: inline::memory-runtime
+  - provider_id: rag-runtime
+    provider_type: inline::rag-runtime
+    config: {}
+  - provider_id: model-context-protocol
+    provider_type: remote::model-context-protocol
     config: {}
 metadata_store:
   type: sqlite
@@ -147,14 +150,14 @@ models:
   model_type: embedding
 shields:
 - shield_id: meta-llama/Llama-Guard-3-8B
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []
 tool_groups:
 - toolgroup_id: builtin::websearch
   provider_id: tavily-search
-- toolgroup_id: builtin::memory
-  provider_id: memory-runtime
+- toolgroup_id: builtin::rag
+  provider_id: rag-runtime
 - toolgroup_id: builtin::code_interpreter
   provider_id: code-interpreter
diff --git a/llama_stack/templates/hf-endpoint/build.yaml b/llama_stack/templates/hf-endpoint/build.yaml
index 43486030e..c2eaaa05b 100644
--- a/llama_stack/templates/hf-endpoint/build.yaml
+++ b/llama_stack/templates/hf-endpoint/build.yaml
@@ -4,7 +4,7 @@ distribution_spec:
   providers:
     inference:
     - remote::hf::endpoint
-    memory:
+    vector_io:
     - inline::faiss
     - remote::chromadb
     - remote::pgvector
@@ -27,5 +27,6 @@ distribution_spec:
     - remote::brave-search
     - remote::tavily-search
     - inline::code-interpreter
-    - inline::memory-runtime
+    - inline::rag-runtime
+    - remote::model-context-protocol
 image_type: conda
diff --git a/llama_stack/templates/hf-endpoint/hf_endpoint.py b/llama_stack/templates/hf-endpoint/hf_endpoint.py
index 54aaa56ac..4533fd95b 100644
--- a/llama_stack/templates/hf-endpoint/hf_endpoint.py
+++ b/llama_stack/templates/hf-endpoint/hf_endpoint.py
@@ -14,7 +14,7 @@ from llama_stack.distribution.datatypes import (
 from llama_stack.providers.inline.inference.sentence_transformers import (
     SentenceTransformersInferenceConfig,
 )
-from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
+from llama_stack.providers.inline.vector_io.faiss.config import FaissImplConfig
 from llama_stack.providers.remote.inference.tgi import InferenceEndpointImplConfig
 from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
 
@@ -22,7 +22,7 @@ from llama_stack.templates.template import DistributionTemplate, RunConfigSettin
 def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["remote::hf::endpoint"],
-        "memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
         "safety": ["inline::llama-guard"],
         "agents": ["inline::meta-reference"],
         "telemetry": ["inline::meta-reference"],
@@ -33,7 +33,8 @@ def get_distribution_template() -> DistributionTemplate:
             "remote::brave-search",
             "remote::tavily-search",
             "inline::code-interpreter",
-            "inline::memory-runtime",
+            "inline::rag-runtime",
+            "remote::model-context-protocol",
         ],
     }
     name = "hf-endpoint"
@@ -47,7 +48,7 @@ def get_distribution_template() -> DistributionTemplate:
         provider_type="inline::sentence-transformers",
         config=SentenceTransformersInferenceConfig.sample_run_config(),
     )
-    memory_provider = Provider(
+    vector_io_provider = Provider(
         provider_id="faiss",
         provider_type="inline::faiss",
         config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
@@ -75,8 +76,8 @@ def get_distribution_template() -> DistributionTemplate:
             provider_id="tavily-search",
         ),
         ToolGroupInput(
-            toolgroup_id="builtin::memory",
-            provider_id="memory-runtime",
+            toolgroup_id="builtin::rag",
+            provider_id="rag-runtime",
         ),
         ToolGroupInput(
             toolgroup_id="builtin::code_interpreter",
@@ -88,7 +89,7 @@ def get_distribution_template() -> DistributionTemplate:
         name=name,
         distro_type="self_hosted",
         description="Use (an external) Hugging Face Inference Endpoint for running LLM inference",
-        docker_image=None,
+        container_image=None,
         template_path=None,
         providers=providers,
         default_models=[inference_model, safety_model],
@@ -96,7 +97,7 @@ def get_distribution_template() -> DistributionTemplate:
             "run.yaml": RunConfigSettings(
                 provider_overrides={
                     "inference": [inference_provider, embedding_provider],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=[inference_model, embedding_model],
                 default_tool_groups=default_tool_groups,
@@ -114,7 +115,7 @@ def get_distribution_template() -> DistributionTemplate:
                             ),
                         ),
                     ],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=[
                     inference_model,
diff --git a/llama_stack/templates/hf-endpoint/run-with-safety.yaml b/llama_stack/templates/hf-endpoint/run-with-safety.yaml
index 6a52ca861..0329f580b 100644
--- a/llama_stack/templates/hf-endpoint/run-with-safety.yaml
+++ b/llama_stack/templates/hf-endpoint/run-with-safety.yaml
@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: hf-endpoint
@@ -25,7 +25,7 @@ providers:
     config:
       endpoint_name: ${env.SAFETY_INFERENCE_ENDPOINT_NAME}
       api_token: ${env.HF_API_TOKEN}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -88,8 +88,11 @@ providers:
   - provider_id: code-interpreter
     provider_type: inline::code-interpreter
     config: {}
-  - provider_id: memory-runtime
-    provider_type: inline::memory-runtime
+  - provider_id: rag-runtime
+    provider_type: inline::rag-runtime
+    config: {}
+  - provider_id: model-context-protocol
+    provider_type: remote::model-context-protocol
     config: {}
 metadata_store:
   type: sqlite
@@ -110,14 +113,14 @@ models:
   model_type: embedding
 shields:
 - shield_id: ${env.SAFETY_MODEL}
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []
 tool_groups:
 - toolgroup_id: builtin::websearch
   provider_id: tavily-search
-- toolgroup_id: builtin::memory
-  provider_id: memory-runtime
+- toolgroup_id: builtin::rag
+  provider_id: rag-runtime
 - toolgroup_id: builtin::code_interpreter
   provider_id: code-interpreter
diff --git a/llama_stack/templates/hf-endpoint/run.yaml b/llama_stack/templates/hf-endpoint/run.yaml
index c019c587a..8163fe28e 100644
--- a/llama_stack/templates/hf-endpoint/run.yaml
+++ b/llama_stack/templates/hf-endpoint/run.yaml
@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: hf-endpoint
@@ -20,7 +20,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -83,8 +83,11 @@ providers:
   - provider_id: code-interpreter
     provider_type: inline::code-interpreter
     config: {}
-  - provider_id: memory-runtime
-    provider_type: inline::memory-runtime
+  - provider_id: rag-runtime
+    provider_type: inline::rag-runtime
+    config: {}
+  - provider_id: model-context-protocol
+    provider_type: remote::model-context-protocol
     config: {}
 metadata_store:
   type: sqlite
@@ -100,14 +103,14 @@ models:
   provider_id: sentence-transformers
   model_type: embedding
 shields: []
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []
 tool_groups:
 - toolgroup_id: builtin::websearch
   provider_id: tavily-search
-- toolgroup_id: builtin::memory
-  provider_id: memory-runtime
+- toolgroup_id: builtin::rag
+  provider_id: rag-runtime
 - toolgroup_id: builtin::code_interpreter
   provider_id: code-interpreter
diff --git a/llama_stack/templates/hf-serverless/build.yaml b/llama_stack/templates/hf-serverless/build.yaml
index e1328bd58..f9303cfab 100644
--- a/llama_stack/templates/hf-serverless/build.yaml
+++ b/llama_stack/templates/hf-serverless/build.yaml
@@ -4,7 +4,7 @@ distribution_spec:
   providers:
     inference:
     - remote::hf::serverless
-    memory:
+    vector_io:
     - inline::faiss
     - remote::chromadb
     - remote::pgvector
@@ -27,5 +27,6 @@ distribution_spec:
     - remote::brave-search
     - remote::tavily-search
     - inline::code-interpreter
-    - inline::memory-runtime
+    - inline::rag-runtime
+    - remote::model-context-protocol
 image_type: conda
diff --git a/llama_stack/templates/hf-serverless/hf_serverless.py b/llama_stack/templates/hf-serverless/hf_serverless.py
index 788faa986..8438de7a5 100644
--- a/llama_stack/templates/hf-serverless/hf_serverless.py
+++ b/llama_stack/templates/hf-serverless/hf_serverless.py
@@ -14,7 +14,7 @@ from llama_stack.distribution.datatypes import (
 from llama_stack.providers.inline.inference.sentence_transformers import (
     SentenceTransformersInferenceConfig,
 )
-from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
+from llama_stack.providers.inline.vector_io.faiss.config import FaissImplConfig
 from llama_stack.providers.remote.inference.tgi import InferenceAPIImplConfig
 from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
 
@@ -22,7 +22,7 @@ from llama_stack.templates.template import DistributionTemplate, RunConfigSettin
 def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["remote::hf::serverless"],
-        "memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
         "safety": ["inline::llama-guard"],
         "agents": ["inline::meta-reference"],
         "telemetry": ["inline::meta-reference"],
@@ -33,7 +33,8 @@ def get_distribution_template() -> DistributionTemplate:
             "remote::brave-search",
             "remote::tavily-search",
             "inline::code-interpreter",
-            "inline::memory-runtime",
+            "inline::rag-runtime",
+            "remote::model-context-protocol",
         ],
     }
 
@@ -48,7 +49,7 @@ def get_distribution_template() -> DistributionTemplate:
         provider_type="inline::sentence-transformers",
         config=SentenceTransformersInferenceConfig.sample_run_config(),
     )
-    memory_provider = Provider(
+    vector_io_provider = Provider(
         provider_id="faiss",
         provider_type="inline::faiss",
         config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
@@ -76,8 +77,8 @@ def get_distribution_template() -> DistributionTemplate:
             provider_id="tavily-search",
         ),
         ToolGroupInput(
-            toolgroup_id="builtin::memory",
-            provider_id="memory-runtime",
+            toolgroup_id="builtin::rag",
+            provider_id="rag-runtime",
         ),
         ToolGroupInput(
             toolgroup_id="builtin::code_interpreter",
@@ -89,7 +90,7 @@ def get_distribution_template() -> DistributionTemplate:
         name=name,
         distro_type="self_hosted",
         description="Use (an external) Hugging Face Inference Endpoint for running LLM inference",
-        docker_image=None,
+        container_image=None,
         template_path=None,
         providers=providers,
         default_models=[inference_model, safety_model],
@@ -97,7 +98,7 @@ def get_distribution_template() -> DistributionTemplate:
             "run.yaml": RunConfigSettings(
                 provider_overrides={
                     "inference": [inference_provider, embedding_provider],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=[inference_model, embedding_model],
                 default_tool_groups=default_tool_groups,
@@ -115,7 +116,7 @@ def get_distribution_template() -> DistributionTemplate:
                             ),
                         ),
                     ],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=[
                     inference_model,
diff --git a/llama_stack/templates/hf-serverless/run-with-safety.yaml b/llama_stack/templates/hf-serverless/run-with-safety.yaml
index 0a64de358..9cee920a5 100644
--- a/llama_stack/templates/hf-serverless/run-with-safety.yaml
+++ b/llama_stack/templates/hf-serverless/run-with-safety.yaml
@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: hf-serverless
@@ -25,7 +25,7 @@ providers:
     config:
       huggingface_repo: ${env.SAFETY_MODEL}
       api_token: ${env.HF_API_TOKEN}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -88,8 +88,11 @@ providers:
   - provider_id: code-interpreter
     provider_type: inline::code-interpreter
     config: {}
-  - provider_id: memory-runtime
-    provider_type: inline::memory-runtime
+  - provider_id: rag-runtime
+    provider_type: inline::rag-runtime
+    config: {}
+  - provider_id: model-context-protocol
+    provider_type: remote::model-context-protocol
     config: {}
 metadata_store:
   type: sqlite
@@ -110,14 +113,14 @@ models:
   model_type: embedding
 shields:
 - shield_id: ${env.SAFETY_MODEL}
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []
 tool_groups:
 - toolgroup_id: builtin::websearch
   provider_id: tavily-search
-- toolgroup_id: builtin::memory
-  provider_id: memory-runtime
+- toolgroup_id: builtin::rag
+  provider_id: rag-runtime
 - toolgroup_id: builtin::code_interpreter
   provider_id: code-interpreter
diff --git a/llama_stack/templates/hf-serverless/run.yaml b/llama_stack/templates/hf-serverless/run.yaml
index f04213533..c8ad0d38d 100644
--- a/llama_stack/templates/hf-serverless/run.yaml
+++ b/llama_stack/templates/hf-serverless/run.yaml
@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: hf-serverless
@@ -20,7 +20,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -83,8 +83,11 @@ providers:
   - provider_id: code-interpreter
     provider_type: inline::code-interpreter
     config: {}
-  - provider_id: memory-runtime
-    provider_type: inline::memory-runtime
+  - provider_id: rag-runtime
+    provider_type: inline::rag-runtime
+    config: {}
+  - provider_id: model-context-protocol
+    provider_type: remote::model-context-protocol
     config: {}
 metadata_store:
   type: sqlite
@@ -100,14 +103,14 @@ models:
   provider_id: sentence-transformers
   model_type: embedding
 shields: []
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []
 tool_groups:
 - toolgroup_id: builtin::websearch
   provider_id: tavily-search
-- toolgroup_id: builtin::memory
-  provider_id: memory-runtime
+- toolgroup_id: builtin::rag
+  provider_id: rag-runtime
 - toolgroup_id: builtin::code_interpreter
   provider_id: code-interpreter
diff --git a/llama_stack/templates/meta-reference-gpu/build.yaml b/llama_stack/templates/meta-reference-gpu/build.yaml
index 9ad7b26bf..b9130fc7d 100644
--- a/llama_stack/templates/meta-reference-gpu/build.yaml
+++ b/llama_stack/templates/meta-reference-gpu/build.yaml
@@ -4,7 +4,7 @@ distribution_spec:
   providers:
     inference:
     - inline::meta-reference
-    memory:
+    vector_io:
     - inline::faiss
     - remote::chromadb
     - remote::pgvector
@@ -27,5 +27,6 @@ distribution_spec:
     - remote::brave-search
     - remote::tavily-search
     - inline::code-interpreter
-    - inline::memory-runtime
+    - inline::rag-runtime
+    - remote::model-context-protocol
 image_type: conda
diff --git a/llama_stack/templates/meta-reference-gpu/meta_reference.py b/llama_stack/templates/meta-reference-gpu/meta_reference.py
index 7364ee422..a3f82b0c8 100644
--- a/llama_stack/templates/meta-reference-gpu/meta_reference.py
+++ b/llama_stack/templates/meta-reference-gpu/meta_reference.py
@@ -19,14 +19,14 @@ from llama_stack.providers.inline.inference.meta_reference import (
 from llama_stack.providers.inline.inference.sentence_transformers import (
     SentenceTransformersInferenceConfig,
 )
-from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
+from llama_stack.providers.inline.vector_io.faiss.config import FaissImplConfig
 from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
 
 
 def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["inline::meta-reference"],
-        "memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
         "safety": ["inline::llama-guard"],
         "agents": ["inline::meta-reference"],
         "telemetry": ["inline::meta-reference"],
@@ -37,7 +37,8 @@ def get_distribution_template() -> DistributionTemplate:
             "remote::brave-search",
             "remote::tavily-search",
             "inline::code-interpreter",
-            "inline::memory-runtime",
+            "inline::rag-runtime",
+            "remote::model-context-protocol",
         ],
     }
     name = "meta-reference-gpu"
@@ -54,7 +55,7 @@ def get_distribution_template() -> DistributionTemplate:
         provider_type="inline::sentence-transformers",
         config=SentenceTransformersInferenceConfig.sample_run_config(),
     )
-    memory_provider = Provider(
+    vector_io_provider = Provider(
         provider_id="faiss",
         provider_type="inline::faiss",
         config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
@@ -82,8 +83,8 @@ def get_distribution_template() -> DistributionTemplate:
             provider_id="tavily-search",
         ),
         ToolGroupInput(
-            toolgroup_id="builtin::memory",
-            provider_id="memory-runtime",
+            toolgroup_id="builtin::rag",
+            provider_id="rag-runtime",
         ),
         ToolGroupInput(
             toolgroup_id="builtin::code_interpreter",
@@ -102,7 +103,7 @@ def get_distribution_template() -> DistributionTemplate:
             "run.yaml": RunConfigSettings(
                 provider_overrides={
                     "inference": [inference_provider, embedding_provider],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=[inference_model, embedding_model],
                 default_tool_groups=default_tool_groups,
@@ -121,7 +122,7 @@ def get_distribution_template() -> DistributionTemplate:
                             ),
                         ),
                     ],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=[
                     inference_model,
diff --git a/llama_stack/templates/meta-reference-gpu/run-with-safety.yaml b/llama_stack/templates/meta-reference-gpu/run-with-safety.yaml
index 591afa2be..0faaabb15 100644
--- a/llama_stack/templates/meta-reference-gpu/run-with-safety.yaml
+++ b/llama_stack/templates/meta-reference-gpu/run-with-safety.yaml
@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: meta-reference-inference
@@ -27,7 +27,7 @@ providers:
       model: ${env.SAFETY_MODEL}
       max_seq_len: 4096
       checkpoint_dir: ${env.SAFETY_CHECKPOINT_DIR:null}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -90,8 +90,11 @@ providers:
   - provider_id: code-interpreter
     provider_type: inline::code-interpreter
     config: {}
-  - provider_id: memory-runtime
-    provider_type: inline::memory-runtime
+  - provider_id: rag-runtime
+    provider_type: inline::rag-runtime
+    config: {}
+  - provider_id: model-context-protocol
+    provider_type: remote::model-context-protocol
     config: {}
 metadata_store:
   type: sqlite
@@ -112,14 +115,14 @@ models:
   model_type: embedding
 shields:
 - shield_id: ${env.SAFETY_MODEL}
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []
 tool_groups:
 - toolgroup_id: builtin::websearch
   provider_id: tavily-search
-- toolgroup_id: builtin::memory
-  provider_id: memory-runtime
+- toolgroup_id: builtin::rag
+  provider_id: rag-runtime
 - toolgroup_id: builtin::code_interpreter
   provider_id: code-interpreter
diff --git a/llama_stack/templates/meta-reference-gpu/run.yaml b/llama_stack/templates/meta-reference-gpu/run.yaml
index ecde69fdf..6ffe1fa36 100644
--- a/llama_stack/templates/meta-reference-gpu/run.yaml
+++ b/llama_stack/templates/meta-reference-gpu/run.yaml
@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: meta-reference-inference
@@ -21,7 +21,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -84,8 +84,11 @@ providers:
   - provider_id: code-interpreter
     provider_type: inline::code-interpreter
     config: {}
-  - provider_id: memory-runtime
-    provider_type: inline::memory-runtime
+  - provider_id: rag-runtime
+    provider_type: inline::rag-runtime
+    config: {}
+  - provider_id: model-context-protocol
+    provider_type: remote::model-context-protocol
     config: {}
 metadata_store:
   type: sqlite
@@ -101,14 +104,14 @@ models:
   provider_id: sentence-transformers
   model_type: embedding
 shields: []
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []
 tool_groups:
 - toolgroup_id: builtin::websearch
   provider_id: tavily-search
-- toolgroup_id: builtin::memory
-  provider_id: memory-runtime
+- toolgroup_id: builtin::rag
+  provider_id: rag-runtime
 - toolgroup_id: builtin::code_interpreter
   provider_id: code-interpreter
diff --git a/llama_stack/templates/meta-reference-quantized-gpu/build.yaml b/llama_stack/templates/meta-reference-quantized-gpu/build.yaml
index e6b64ea1e..7bbcfe5f2 100644
--- a/llama_stack/templates/meta-reference-quantized-gpu/build.yaml
+++ b/llama_stack/templates/meta-reference-quantized-gpu/build.yaml
@@ -4,7 +4,7 @@ distribution_spec:
   providers:
     inference:
     - inline::meta-reference-quantized
-    memory:
+    vector_io:
     - inline::faiss
     - remote::chromadb
     - remote::pgvector
@@ -27,5 +27,6 @@ distribution_spec:
     - remote::brave-search
     - remote::tavily-search
     - inline::code-interpreter
-    - inline::memory-runtime
+    - inline::rag-runtime
+    - remote::model-context-protocol
 image_type: conda
diff --git a/llama_stack/templates/meta-reference-quantized-gpu/meta_reference.py b/llama_stack/templates/meta-reference-quantized-gpu/meta_reference.py
index 5c40134af..8c2a6ec9f 100644
--- a/llama_stack/templates/meta-reference-quantized-gpu/meta_reference.py
+++ b/llama_stack/templates/meta-reference-quantized-gpu/meta_reference.py
@@ -14,14 +14,14 @@ from llama_stack.providers.inline.inference.meta_reference import (
 from llama_stack.providers.inline.inference.sentence_transformers import (
     SentenceTransformersInferenceConfig,
 )
-from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
+from llama_stack.providers.inline.vector_io.faiss.config import FaissImplConfig
 from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
 
 
 def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["inline::meta-reference-quantized"],
-        "memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
         "safety": ["inline::llama-guard"],
         "agents": ["inline::meta-reference"],
         "telemetry": ["inline::meta-reference"],
@@ -32,7 +32,8 @@ def get_distribution_template() -> DistributionTemplate:
             "remote::brave-search",
             "remote::tavily-search",
             "inline::code-interpreter",
-            "inline::memory-runtime",
+            "inline::rag-runtime",
+            "remote::model-context-protocol",
         ],
     }
     default_tool_groups = [
@@ -41,8 +42,8 @@ def get_distribution_template() -> DistributionTemplate:
             provider_id="tavily-search",
         ),
         ToolGroupInput(
-            toolgroup_id="builtin::memory",
-            provider_id="memory-runtime",
+            toolgroup_id="builtin::rag",
+            provider_id="rag-runtime",
         ),
         ToolGroupInput(
             toolgroup_id="builtin::code_interpreter",
@@ -63,7 +64,7 @@ def get_distribution_template() -> DistributionTemplate:
         provider_type="inline::sentence-transformers",
         config=SentenceTransformersInferenceConfig.sample_run_config(),
     )
-    memory_provider = Provider(
+    vector_io_provider = Provider(
         provider_id="faiss",
         provider_type="inline::faiss",
         config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
@@ -92,7 +93,7 @@ def get_distribution_template() -> DistributionTemplate:
             "run.yaml": RunConfigSettings(
                 provider_overrides={
                     "inference": [inference_provider, embedding_provider],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=[inference_model, embedding_model],
                 default_tool_groups=default_tool_groups,
diff --git a/llama_stack/templates/meta-reference-quantized-gpu/run.yaml b/llama_stack/templates/meta-reference-quantized-gpu/run.yaml
index ff0affafb..5ff87a901 100644
--- a/llama_stack/templates/meta-reference-quantized-gpu/run.yaml
+++ b/llama_stack/templates/meta-reference-quantized-gpu/run.yaml
@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: meta-reference-inference
@@ -23,7 +23,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -86,8 +86,11 @@ providers:
   - provider_id: code-interpreter
     provider_type: inline::code-interpreter
     config: {}
-  - provider_id: memory-runtime
-    provider_type: inline::memory-runtime
+  - provider_id: rag-runtime
+    provider_type: inline::rag-runtime
+    config: {}
+  - provider_id: model-context-protocol
+    provider_type: remote::model-context-protocol
     config: {}
 metadata_store:
   type: sqlite
@@ -103,14 +106,14 @@ models:
   provider_id: sentence-transformers
   model_type: embedding
 shields: []
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []
 tool_groups:
 - toolgroup_id: builtin::websearch
   provider_id: tavily-search
-- toolgroup_id: builtin::memory
-  provider_id: memory-runtime
+- toolgroup_id: builtin::rag
+  provider_id: rag-runtime
 - toolgroup_id: builtin::code_interpreter
   provider_id: code-interpreter
diff --git a/llama_stack/templates/nvidia/build.yaml b/llama_stack/templates/nvidia/build.yaml
index 56124552b..e9748721a 100644
--- a/llama_stack/templates/nvidia/build.yaml
+++ b/llama_stack/templates/nvidia/build.yaml
@@ -4,7 +4,7 @@ distribution_spec:
   providers:
     inference:
     - remote::nvidia
-    memory:
+    vector_io:
     - inline::faiss
     safety:
     - inline::llama-guard
@@ -25,5 +25,6 @@ distribution_spec:
     - remote::brave-search
     - remote::tavily-search
     - inline::code-interpreter
-    - inline::memory-runtime
+    - inline::rag-runtime
+    - remote::model-context-protocol
 image_type: conda
diff --git a/llama_stack/templates/nvidia/nvidia.py b/llama_stack/templates/nvidia/nvidia.py
index cfa86dbe7..19eb4bd5d 100644
--- a/llama_stack/templates/nvidia/nvidia.py
+++ b/llama_stack/templates/nvidia/nvidia.py
@@ -17,7 +17,7 @@ from llama_stack.templates.template import DistributionTemplate, RunConfigSettin
 def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["remote::nvidia"],
-        "memory": ["inline::faiss"],
+        "vector_io": ["inline::faiss"],
         "safety": ["inline::llama-guard"],
         "agents": ["inline::meta-reference"],
         "telemetry": ["inline::meta-reference"],
@@ -28,7 +28,8 @@ def get_distribution_template() -> DistributionTemplate:
             "remote::brave-search",
             "remote::tavily-search",
             "inline::code-interpreter",
-            "inline::memory-runtime",
+            "inline::rag-runtime",
+            "remote::model-context-protocol",
         ],
     }
 
@@ -55,8 +56,8 @@ def get_distribution_template() -> DistributionTemplate:
             provider_id="tavily-search",
         ),
         ToolGroupInput(
-            toolgroup_id="builtin::memory",
-            provider_id="memory-runtime",
+            toolgroup_id="builtin::rag",
+            provider_id="rag-runtime",
         ),
         ToolGroupInput(
             toolgroup_id="builtin::code_interpreter",
@@ -68,7 +69,7 @@ def get_distribution_template() -> DistributionTemplate:
         name="nvidia",
         distro_type="remote_hosted",
         description="Use NVIDIA NIM for running LLM inference",
-        docker_image=None,
+        container_image=None,
         template_path=Path(__file__).parent / "doc_template.md",
         providers=providers,
         default_models=default_models,
diff --git a/llama_stack/templates/nvidia/run.yaml b/llama_stack/templates/nvidia/run.yaml
index 578f70c9d..c57ca2b9a 100644
--- a/llama_stack/templates/nvidia/run.yaml
+++ b/llama_stack/templates/nvidia/run.yaml
@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: nvidia
@@ -17,7 +17,7 @@ providers:
     config:
       url: https://integrate.api.nvidia.com
       api_key: ${env.NVIDIA_API_KEY}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -80,8 +80,11 @@ providers:
   - provider_id: code-interpreter
     provider_type: inline::code-interpreter
     config: {}
-  - provider_id: memory-runtime
-    provider_type: inline::memory-runtime
+  - provider_id: rag-runtime
+    provider_type: inline::rag-runtime
+    config: {}
+  - provider_id: model-context-protocol
+    provider_type: remote::model-context-protocol
     config: {}
 metadata_store:
   type: sqlite
@@ -133,14 +136,14 @@ models:
   provider_model_id: meta/llama-3.2-90b-vision-instruct
   model_type: llm
 shields: []
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []
 tool_groups:
 - toolgroup_id: builtin::websearch
   provider_id: tavily-search
-- toolgroup_id: builtin::memory
-  provider_id: memory-runtime
+- toolgroup_id: builtin::rag
+  provider_id: rag-runtime
 - toolgroup_id: builtin::code_interpreter
   provider_id: code-interpreter
diff --git a/llama_stack/templates/ollama/build.yaml b/llama_stack/templates/ollama/build.yaml
index 5f2e010ee..0fee6808c 100644
--- a/llama_stack/templates/ollama/build.yaml
+++ b/llama_stack/templates/ollama/build.yaml
@@ -4,7 +4,7 @@ distribution_spec:
   providers:
     inference:
     - remote::ollama
-    memory:
+    vector_io:
     - inline::faiss
     - remote::chromadb
     - remote::pgvector
@@ -27,5 +27,5 @@ distribution_spec:
     - remote::brave-search
     - remote::tavily-search
     - inline::code-interpreter
-    - inline::memory-runtime
+    - inline::rag-runtime
 image_type: conda
diff --git a/llama_stack/templates/ollama/doc_template.md b/llama_stack/templates/ollama/doc_template.md
index a75583592..7c260e2c1 100644
--- a/llama_stack/templates/ollama/doc_template.md
+++ b/llama_stack/templates/ollama/doc_template.md
@@ -74,11 +74,15 @@ docker run \
 If you are using Llama Stack Safety / Shield APIs, use:
 
 ```bash
+# You need a local checkout of llama-stack to run this, get it using
+# git clone https://github.com/meta-llama/llama-stack.git
+cd /path/to/llama-stack
+
 docker run \
   -it \
   -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
   -v ~/.llama:/root/.llama \
-  -v ./run-with-safety.yaml:/root/my-run.yaml \
+  -v ./llama_stack/templates/ollama/run-with-safety.yaml:/root/my-run.yaml \
   llamastack/distribution-{{ name }} \
   --yaml-config /root/my-run.yaml \
   --port $LLAMA_STACK_PORT \
diff --git a/llama_stack/templates/ollama/ollama.py b/llama_stack/templates/ollama/ollama.py
index 0473f8692..d14cb3aad 100644
--- a/llama_stack/templates/ollama/ollama.py
+++ b/llama_stack/templates/ollama/ollama.py
@@ -16,7 +16,7 @@ from llama_stack.distribution.datatypes import (
 from llama_stack.providers.inline.inference.sentence_transformers import (
     SentenceTransformersInferenceConfig,
 )
-from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
+from llama_stack.providers.inline.vector_io.faiss.config import FaissImplConfig
 from llama_stack.providers.remote.inference.ollama import OllamaImplConfig
 from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
 
@@ -24,7 +24,7 @@ from llama_stack.templates.template import DistributionTemplate, RunConfigSettin
 def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["remote::ollama"],
-        "memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
         "safety": ["inline::llama-guard"],
         "agents": ["inline::meta-reference"],
         "telemetry": ["inline::meta-reference"],
@@ -35,7 +35,7 @@ def get_distribution_template() -> DistributionTemplate:
             "remote::brave-search",
             "remote::tavily-search",
             "inline::code-interpreter",
-            "inline::memory-runtime",
+            "inline::rag-runtime",
         ],
     }
     name = "ollama"
@@ -49,7 +49,7 @@ def get_distribution_template() -> DistributionTemplate:
         provider_type="inline::sentence-transformers",
         config=SentenceTransformersInferenceConfig.sample_run_config(),
     )
-    memory_provider = Provider(
+    vector_io_provider = Provider(
         provider_id="faiss",
         provider_type="inline::faiss",
         config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
@@ -77,8 +77,8 @@ def get_distribution_template() -> DistributionTemplate:
             provider_id="tavily-search",
         ),
         ToolGroupInput(
-            toolgroup_id="builtin::memory",
-            provider_id="memory-runtime",
+            toolgroup_id="builtin::rag",
+            provider_id="rag-runtime",
         ),
         ToolGroupInput(
             toolgroup_id="builtin::code_interpreter",
@@ -90,7 +90,7 @@ def get_distribution_template() -> DistributionTemplate:
         name=name,
         distro_type="self_hosted",
         description="Use (an external) Ollama server for running LLM inference",
-        docker_image=None,
+        container_image=None,
         template_path=Path(__file__).parent / "doc_template.md",
         providers=providers,
         default_models=[inference_model, safety_model],
@@ -98,7 +98,7 @@ def get_distribution_template() -> DistributionTemplate:
             "run.yaml": RunConfigSettings(
                 provider_overrides={
                     "inference": [inference_provider, embedding_provider],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=[inference_model, embedding_model],
                 default_tool_groups=default_tool_groups,
@@ -109,7 +109,7 @@ def get_distribution_template() -> DistributionTemplate:
                         inference_provider,
                         embedding_provider,
                     ],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                     "safety": [
                         Provider(
                             provider_id="llama-guard",
diff --git a/llama_stack/templates/ollama/report.md b/llama_stack/templates/ollama/report.md
new file mode 100644
index 000000000..724809a59
--- /dev/null
+++ b/llama_stack/templates/ollama/report.md
@@ -0,0 +1,44 @@
+# Report for ollama distribution
+
+## Supported Models
+| Model Descriptor | ollama |
+|:---|:---|
+| Llama-3-8B-Instruct | ❌ |
+| Llama-3-70B-Instruct | ❌ |
+| Llama3.1-8B-Instruct | ✅ |
+| Llama3.1-70B-Instruct | ✅ |
+| Llama3.1-405B-Instruct | ✅ |
+| Llama3.2-1B-Instruct | ✅ |
+| Llama3.2-3B-Instruct | ✅ |
+| Llama3.2-11B-Vision-Instruct | ✅ |
+| Llama3.2-90B-Vision-Instruct | ✅ |
+| Llama3.3-70B-Instruct | ✅ |
+| Llama-Guard-3-11B-Vision | ❌ |
+| Llama-Guard-3-1B | ✅ |
+| Llama-Guard-3-8B | ✅ |
+| Llama-Guard-2-8B | ❌ |
+
+## Inference
+| Model | API | Capability | Test | Status |
+|:----- |:-----|:-----|:-----|:-----|
+| Llama-3.1-8B-Instruct | /chat_completion | streaming | test_text_chat_completion_streaming | ✅ |
+| Llama-3.2-11B-Vision-Instruct | /chat_completion | streaming | test_image_chat_completion_streaming | ❌ |
+| Llama-3.2-11B-Vision-Instruct | /chat_completion | non_streaming | test_image_chat_completion_non_streaming | ❌ |
+| Llama-3.1-8B-Instruct | /chat_completion | non_streaming | test_text_chat_completion_non_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /chat_completion | tool_calling | test_text_chat_completion_with_tool_calling_and_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /chat_completion | tool_calling | test_text_chat_completion_with_tool_calling_and_non_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /completion | streaming | test_text_completion_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /completion | non_streaming | test_text_completion_non_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /completion | structured_output | test_text_completion_structured_output | ✅ |
+
+## Vector IO
+| API | Capability | Test | Status |
+|:-----|:-----|:-----|:-----|
+| /retrieve |  | test_vector_db_retrieve | ✅ |
+
+## Agents
+| API | Capability | Test | Status |
+|:-----|:-----|:-----|:-----|
+| /create_agent_turn | rag | test_rag_agent | ✅ |
+| /create_agent_turn | custom_tool | test_custom_tool | ✅ |
+| /create_agent_turn | code_execution | test_code_interpreter_for_attachments | ✅ |
diff --git a/llama_stack/templates/ollama/run-with-safety.yaml b/llama_stack/templates/ollama/run-with-safety.yaml
index a808590c3..5b5c9c253 100644
--- a/llama_stack/templates/ollama/run-with-safety.yaml
+++ b/llama_stack/templates/ollama/run-with-safety.yaml
@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: ollama
@@ -19,7 +19,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -85,8 +85,8 @@ providers:
   - provider_id: code-interpreter
     provider_type: inline::code-interpreter
     config: {}
-  - provider_id: memory-runtime
-    provider_type: inline::memory-runtime
+  - provider_id: rag-runtime
+    provider_type: inline::rag-runtime
     config: {}
 metadata_store:
   type: sqlite
@@ -110,14 +110,14 @@ shields:
   provider_id: llama-guard
 - shield_id: CodeScanner
   provider_id: code-scanner
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []
 tool_groups:
 - toolgroup_id: builtin::websearch
   provider_id: tavily-search
-- toolgroup_id: builtin::memory
-  provider_id: memory-runtime
+- toolgroup_id: builtin::rag
+  provider_id: rag-runtime
 - toolgroup_id: builtin::code_interpreter
   provider_id: code-interpreter
diff --git a/llama_stack/templates/ollama/run.yaml b/llama_stack/templates/ollama/run.yaml
index 2c69296fc..3cc1cb2ac 100644
--- a/llama_stack/templates/ollama/run.yaml
+++ b/llama_stack/templates/ollama/run.yaml
@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: ollama
@@ -19,7 +19,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -82,8 +82,8 @@ providers:
   - provider_id: code-interpreter
     provider_type: inline::code-interpreter
     config: {}
-  - provider_id: memory-runtime
-    provider_type: inline::memory-runtime
+  - provider_id: rag-runtime
+    provider_type: inline::rag-runtime
     config: {}
 metadata_store:
   type: sqlite
@@ -99,14 +99,14 @@ models:
   provider_id: sentence-transformers
   model_type: embedding
 shields: []
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []
 tool_groups:
 - toolgroup_id: builtin::websearch
   provider_id: tavily-search
-- toolgroup_id: builtin::memory
-  provider_id: memory-runtime
+- toolgroup_id: builtin::rag
+  provider_id: rag-runtime
 - toolgroup_id: builtin::code_interpreter
   provider_id: code-interpreter
diff --git a/llama_stack/templates/remote-vllm/build.yaml b/llama_stack/templates/remote-vllm/build.yaml
index 2659c8190..74d9f32d9 100644
--- a/llama_stack/templates/remote-vllm/build.yaml
+++ b/llama_stack/templates/remote-vllm/build.yaml
@@ -4,7 +4,7 @@ distribution_spec:
   providers:
     inference:
     - remote::vllm
-    memory:
+    vector_io:
     - inline::faiss
     - remote::chromadb
     - remote::pgvector
@@ -12,11 +12,21 @@ distribution_spec:
     - inline::llama-guard
     agents:
     - inline::meta-reference
+    eval:
+    - inline::meta-reference
+    datasetio:
+    - remote::huggingface
+    - inline::localfs
+    scoring:
+    - inline::basic
+    - inline::llm-as-judge
+    - inline::braintrust
     telemetry:
     - inline::meta-reference
     tool_runtime:
     - remote::brave-search
     - remote::tavily-search
     - inline::code-interpreter
-    - inline::memory-runtime
+    - inline::rag-runtime
+    - remote::model-context-protocol
 image_type: conda
diff --git a/llama_stack/templates/remote-vllm/doc_template.md b/llama_stack/templates/remote-vllm/doc_template.md
index 7f48f961e..c855f6e62 100644
--- a/llama_stack/templates/remote-vllm/doc_template.md
+++ b/llama_stack/templates/remote-vllm/doc_template.md
@@ -98,10 +98,15 @@ If you are using Llama Stack Safety / Shield APIs, use:
 export SAFETY_PORT=8081
 export SAFETY_MODEL=meta-llama/Llama-Guard-3-1B
 
+# You need a local checkout of llama-stack to run this, get it using
+# git clone https://github.com/meta-llama/llama-stack.git
+cd /path/to/llama-stack
+
 docker run \
   -it \
   -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-  -v ./run-with-safety.yaml:/root/my-run.yaml \
+  -v ~/.llama:/root/.llama \
+  -v ./llama_stack/templates/remote-vllm/run-with-safety.yaml:/root/my-run.yaml \
   llamastack/distribution-{{ name }} \
   --yaml-config /root/my-run.yaml \
   --port $LLAMA_STACK_PORT \
diff --git a/llama_stack/templates/remote-vllm/run-with-safety.yaml b/llama_stack/templates/remote-vllm/run-with-safety.yaml
index 4bf73bbda..4a0fa9a85 100644
--- a/llama_stack/templates/remote-vllm/run-with-safety.yaml
+++ b/llama_stack/templates/remote-vllm/run-with-safety.yaml
@@ -2,11 +2,14 @@ version: '2'
 image_name: remote-vllm
 apis:
 - agents
+- datasetio
+- eval
 - inference
-- memory
 - safety
+- scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: vllm-inference
@@ -24,7 +27,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -44,6 +47,28 @@ providers:
         type: sqlite
         namespace: null
         db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/remote-vllm}/agents_store.db
+  eval:
+  - provider_id: meta-reference
+    provider_type: inline::meta-reference
+    config: {}
+  datasetio:
+  - provider_id: huggingface
+    provider_type: remote::huggingface
+    config: {}
+  - provider_id: localfs
+    provider_type: inline::localfs
+    config: {}
+  scoring:
+  - provider_id: basic
+    provider_type: inline::basic
+    config: {}
+  - provider_id: llm-as-judge
+    provider_type: inline::llm-as-judge
+    config: {}
+  - provider_id: braintrust
+    provider_type: inline::braintrust
+    config:
+      openai_api_key: ${env.OPENAI_API_KEY:}
   telemetry:
   - provider_id: meta-reference
     provider_type: inline::meta-reference
@@ -65,8 +90,11 @@ providers:
   - provider_id: code-interpreter
     provider_type: inline::code-interpreter
     config: {}
-  - provider_id: memory-runtime
-    provider_type: inline::memory-runtime
+  - provider_id: rag-runtime
+    provider_type: inline::rag-runtime
+    config: {}
+  - provider_id: model-context-protocol
+    provider_type: remote::model-context-protocol
     config: {}
 metadata_store:
   type: sqlite
@@ -87,14 +115,14 @@ models:
   model_type: embedding
 shields:
 - shield_id: ${env.SAFETY_MODEL}
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []
 tool_groups:
 - toolgroup_id: builtin::websearch
   provider_id: tavily-search
-- toolgroup_id: builtin::memory
-  provider_id: memory-runtime
+- toolgroup_id: builtin::rag
+  provider_id: rag-runtime
 - toolgroup_id: builtin::code_interpreter
   provider_id: code-interpreter
diff --git a/llama_stack/templates/remote-vllm/run.yaml b/llama_stack/templates/remote-vllm/run.yaml
index c35694d73..9631f94a2 100644
--- a/llama_stack/templates/remote-vllm/run.yaml
+++ b/llama_stack/templates/remote-vllm/run.yaml
@@ -2,11 +2,14 @@ version: '2'
 image_name: remote-vllm
 apis:
 - agents
+- datasetio
+- eval
 - inference
-- memory
 - safety
+- scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: vllm-inference
@@ -18,7 +21,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -38,6 +41,28 @@ providers:
         type: sqlite
         namespace: null
         db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/remote-vllm}/agents_store.db
+  eval:
+  - provider_id: meta-reference
+    provider_type: inline::meta-reference
+    config: {}
+  datasetio:
+  - provider_id: huggingface
+    provider_type: remote::huggingface
+    config: {}
+  - provider_id: localfs
+    provider_type: inline::localfs
+    config: {}
+  scoring:
+  - provider_id: basic
+    provider_type: inline::basic
+    config: {}
+  - provider_id: llm-as-judge
+    provider_type: inline::llm-as-judge
+    config: {}
+  - provider_id: braintrust
+    provider_type: inline::braintrust
+    config:
+      openai_api_key: ${env.OPENAI_API_KEY:}
   telemetry:
   - provider_id: meta-reference
     provider_type: inline::meta-reference
@@ -59,8 +84,11 @@ providers:
   - provider_id: code-interpreter
     provider_type: inline::code-interpreter
     config: {}
-  - provider_id: memory-runtime
-    provider_type: inline::memory-runtime
+  - provider_id: rag-runtime
+    provider_type: inline::rag-runtime
+    config: {}
+  - provider_id: model-context-protocol
+    provider_type: remote::model-context-protocol
     config: {}
 metadata_store:
   type: sqlite
@@ -76,14 +104,14 @@ models:
   provider_id: sentence-transformers
   model_type: embedding
 shields: []
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []
 tool_groups:
 - toolgroup_id: builtin::websearch
   provider_id: tavily-search
-- toolgroup_id: builtin::memory
-  provider_id: memory-runtime
+- toolgroup_id: builtin::rag
+  provider_id: rag-runtime
 - toolgroup_id: builtin::code_interpreter
   provider_id: code-interpreter
diff --git a/llama_stack/templates/remote-vllm/vllm.py b/llama_stack/templates/remote-vllm/vllm.py
index 9dcaf2414..6c835ef86 100644
--- a/llama_stack/templates/remote-vllm/vllm.py
+++ b/llama_stack/templates/remote-vllm/vllm.py
@@ -16,7 +16,7 @@ from llama_stack.distribution.datatypes import (
 from llama_stack.providers.inline.inference.sentence_transformers import (
     SentenceTransformersInferenceConfig,
 )
-from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
+from llama_stack.providers.inline.vector_io.faiss.config import FaissImplConfig
 from llama_stack.providers.remote.inference.vllm import VLLMInferenceAdapterConfig
 from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
 
@@ -24,15 +24,19 @@ from llama_stack.templates.template import DistributionTemplate, RunConfigSettin
 def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["remote::vllm"],
-        "memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
         "safety": ["inline::llama-guard"],
         "agents": ["inline::meta-reference"],
+        "eval": ["inline::meta-reference"],
+        "datasetio": ["remote::huggingface", "inline::localfs"],
+        "scoring": ["inline::basic", "inline::llm-as-judge", "inline::braintrust"],
         "telemetry": ["inline::meta-reference"],
         "tool_runtime": [
             "remote::brave-search",
             "remote::tavily-search",
             "inline::code-interpreter",
-            "inline::memory-runtime",
+            "inline::rag-runtime",
+            "remote::model-context-protocol",
         ],
     }
     name = "remote-vllm"
@@ -48,7 +52,7 @@ def get_distribution_template() -> DistributionTemplate:
         provider_type="inline::sentence-transformers",
         config=SentenceTransformersInferenceConfig.sample_run_config(),
     )
-    memory_provider = Provider(
+    vector_io_provider = Provider(
         provider_id="faiss",
         provider_type="inline::faiss",
         config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
@@ -76,8 +80,8 @@ def get_distribution_template() -> DistributionTemplate:
             provider_id="tavily-search",
         ),
         ToolGroupInput(
-            toolgroup_id="builtin::memory",
-            provider_id="memory-runtime",
+            toolgroup_id="builtin::rag",
+            provider_id="rag-runtime",
         ),
         ToolGroupInput(
             toolgroup_id="builtin::code_interpreter",
@@ -96,7 +100,7 @@ def get_distribution_template() -> DistributionTemplate:
             "run.yaml": RunConfigSettings(
                 provider_overrides={
                     "inference": [inference_provider, embedding_provider],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=[inference_model, embedding_model],
                 default_tool_groups=default_tool_groups,
@@ -114,7 +118,7 @@ def get_distribution_template() -> DistributionTemplate:
                         ),
                         embedding_provider,
                     ],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=[
                     inference_model,
diff --git a/llama_stack/templates/sambanova/__init__.py b/llama_stack/templates/sambanova/__init__.py
new file mode 100644
index 000000000..30209fb7f
--- /dev/null
+++ b/llama_stack/templates/sambanova/__init__.py
@@ -0,0 +1,7 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from .sambanova import get_distribution_template  # noqa: F401
diff --git a/llama_stack/templates/sambanova/build.yaml b/llama_stack/templates/sambanova/build.yaml
new file mode 100644
index 000000000..0966bfdd9
--- /dev/null
+++ b/llama_stack/templates/sambanova/build.yaml
@@ -0,0 +1,32 @@
+version: '2'
+distribution_spec:
+  description: Use SambaNova.AI for running LLM inference
+  providers:
+    inference:
+    - remote::sambanova
+    vector_io:
+    - inline::faiss
+    - remote::chromadb
+    - remote::pgvector
+    safety:
+    - inline::llama-guard
+    agents:
+    - inline::meta-reference
+    telemetry:
+    - inline::meta-reference
+    eval:
+    - inline::meta-reference
+    datasetio:
+    - remote::huggingface
+    - inline::localfs
+    scoring:
+    - inline::basic
+    - inline::llm-as-judge
+    - inline::braintrust
+    tool_runtime:
+    - remote::brave-search
+    - remote::tavily-search
+    - inline::code-interpreter
+    - inline::rag-runtime
+    - remote::model-context-protocol
+image_type: conda
diff --git a/llama_stack/templates/sambanova/doc_template.md b/llama_stack/templates/sambanova/doc_template.md
new file mode 100644
index 000000000..4af4718e5
--- /dev/null
+++ b/llama_stack/templates/sambanova/doc_template.md
@@ -0,0 +1,68 @@
+---
+orphan: true
+---
+# SambaNova Distribution
+
+```{toctree}
+:maxdepth: 2
+:hidden:
+
+self
+```
+
+The `llamastack/distribution-{{ name }}` distribution consists of the following provider configurations.
+
+{{ providers_table }}
+
+{% if run_config_env_vars %}
+### Environment Variables
+
+The following environment variables can be configured:
+
+{% for var, (default_value, description) in run_config_env_vars.items() %}
+- `{{ var }}`: {{ description }} (default: `{{ default_value }}`)
+{% endfor %}
+{% endif %}
+
+{% if default_models %}
+### Models
+
+The following models are available by default:
+
+{% for model in default_models %}
+- `{{ model.model_id }} ({{ model.provider_model_id }})`
+{% endfor %}
+{% endif %}
+
+
+### Prerequisite: API Keys
+
+Make sure you have access to a SambaNova API Key. You can get one by visiting [SambaBova.ai](https://sambanova.ai/).
+
+
+## Running Llama Stack with SambaNova
+
+You can do this via Conda (build code) or Docker which has a pre-built image.
+
+### Via Docker
+
+This method allows you to get started quickly without having to build the distribution code.
+
+```bash
+LLAMA_STACK_PORT=5001
+docker run \
+  -it \
+  -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
+  llamastack/distribution-{{ name }} \
+  --port $LLAMA_STACK_PORT \
+  --env SAMBANOVA_API_KEY=$SAMBANOVA_API_KEY
+```
+
+### Via Conda
+
+```bash
+llama stack build --template sambanova --image-type conda
+llama stack run ./run.yaml \
+  --port $LLAMA_STACK_PORT \
+  --env SAMBANOVA_API_KEY=$SAMBANOVA_API_KEY
+```
diff --git a/llama_stack/templates/sambanova/run.yaml b/llama_stack/templates/sambanova/run.yaml
new file mode 100644
index 000000000..c63b5d217
--- /dev/null
+++ b/llama_stack/templates/sambanova/run.yaml
@@ -0,0 +1,151 @@
+version: '2'
+image_name: sambanova
+apis:
+- agents
+- datasetio
+- eval
+- inference
+- safety
+- scoring
+- telemetry
+- tool_runtime
+- vector_io
+providers:
+  inference:
+  - provider_id: sambanova
+    provider_type: remote::sambanova
+    config:
+      url: https://api.sambanova.ai/v1
+      api_key: ${env.SAMBANOVA_API_KEY}
+  vector_io:
+  - provider_id: faiss
+    provider_type: inline::faiss
+    config:
+      kvstore:
+        type: sqlite
+        namespace: null
+        db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/sambanova}/faiss_store.db
+  safety:
+  - provider_id: llama-guard
+    provider_type: inline::llama-guard
+    config: {}
+  agents:
+  - provider_id: meta-reference
+    provider_type: inline::meta-reference
+    config:
+      persistence_store:
+        type: sqlite
+        namespace: null
+        db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/sambanova}/agents_store.db
+  telemetry:
+  - provider_id: meta-reference
+    provider_type: inline::meta-reference
+    config:
+      service_name: ${env.OTEL_SERVICE_NAME:llama-stack}
+      sinks: ${env.TELEMETRY_SINKS:console,sqlite}
+      sqlite_db_path: ${env.SQLITE_DB_PATH:~/.llama/distributions/sambanova/trace_store.db}
+  eval:
+  - provider_id: meta-reference
+    provider_type: inline::meta-reference
+    config: {}
+  datasetio:
+  - provider_id: huggingface
+    provider_type: remote::huggingface
+    config: {}
+  - provider_id: localfs
+    provider_type: inline::localfs
+    config: {}
+  scoring:
+  - provider_id: basic
+    provider_type: inline::basic
+    config: {}
+  - provider_id: llm-as-judge
+    provider_type: inline::llm-as-judge
+    config: {}
+  - provider_id: braintrust
+    provider_type: inline::braintrust
+    config:
+      openai_api_key: ${env.OPENAI_API_KEY:}
+  tool_runtime:
+  - provider_id: brave-search
+    provider_type: remote::brave-search
+    config:
+      api_key: ${env.BRAVE_SEARCH_API_KEY:}
+      max_results: 3
+  - provider_id: tavily-search
+    provider_type: remote::tavily-search
+    config:
+      api_key: ${env.TAVILY_SEARCH_API_KEY:}
+      max_results: 3
+  - provider_id: code-interpreter
+    provider_type: inline::code-interpreter
+    config: {}
+  - provider_id: rag-runtime
+    provider_type: inline::rag-runtime
+    config: {}
+  - provider_id: model-context-protocol
+    provider_type: remote::model-context-protocol
+    config: {}
+metadata_store:
+  type: sqlite
+  db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/sambanova}/registry.db
+models:
+- metadata: {}
+  model_id: meta-llama/Llama-3.1-8B-Instruct
+  provider_id: sambanova
+  provider_model_id: Meta-Llama-3.1-8B-Instruct
+  model_type: llm
+- metadata: {}
+  model_id: meta-llama/Llama-3.1-70B-Instruct
+  model_type: llm
+  provider_id: sambanova
+  provider_model_id: Meta-Llama-3.1-70B-Instruct
+  model_type: llm
+- metadata: {}
+  model_id: meta-llama/Llama-3.1-405B-Instruct-FP8
+  provider_id: sambanova
+  provider_model_id: Meta-Llama-3.1-405B-Instruct
+  model_type: llm
+- metadata: {}
+  model_id: meta-llama/Llama-3.2-1B-Instruct
+  provider_id: sambanova
+  provider_model_id: Meta-Llama-3.2-1B-Instruct
+  model_type: llm
+- metadata: {}
+  model_id: meta-llama/Llama-3.2-3B-Instruct
+  provider_id: sambanova
+  provider_model_id: Meta-Llama-3.2-3B-Instruct
+  model_type: llm
+- metadata: {}
+  model_id: meta-llama/Llama-3.2-11B-Vision-Instruct
+  provider_id: sambanova
+  provider_model_id: Llama-3.2-11B-Vision-Instruct
+  model_type: llm
+- metadata: {}
+  model_id: meta-llama/Llama-3.2-90B-Vision-Instruct
+  provider_id: sambanova
+  provider_model_id: Llama-3.2-90B-Vision-Instruct
+  model_type: llm
+- metadata: {}
+  model_id: meta-llama/Llama-3.2-90B-Vision-Instruct
+  provider_id: sambanova
+  provider_model_id: Llama-3.2-90B-Vision-Instruct
+  model_type: llm
+- metadata: {}
+  model_id: meta-llama/Llama-Guard-3-8B
+  provider_id: sambanova
+  provider_model_id: Llama-Guard-3-8B
+  model_type: llm
+shields:
+- shield_id: meta-llama/Llama-Guard-3-8B
+vector_dbs: []
+datasets: []
+scoring_fns: []
+eval_tasks: []
+tool_groups:
+- toolgroup_id: builtin::websearch
+  provider_id: tavily-search
+- toolgroup_id: builtin::rag
+  provider_id: rag-runtime
+- toolgroup_id: builtin::code_interpreter
+  provider_id: code-interpreter
diff --git a/llama_stack/templates/sambanova/sambanova.py b/llama_stack/templates/sambanova/sambanova.py
new file mode 100644
index 000000000..389e2a6c5
--- /dev/null
+++ b/llama_stack/templates/sambanova/sambanova.py
@@ -0,0 +1,77 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from pathlib import Path
+
+from llama_models.sku_list import all_registered_models
+
+from llama_stack.distribution.datatypes import ModelInput, Provider, ShieldInput
+from llama_stack.providers.remote.inference.sambanova import SambaNovaImplConfig
+from llama_stack.providers.remote.inference.sambanova.sambanova import MODEL_ALIASES
+
+from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
+
+
+def get_distribution_template() -> DistributionTemplate:
+    providers = {
+        "inference": ["remote::sambanova"],
+        "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "safety": ["inline::llama-guard"],
+        "agents": ["inline::meta-reference"],
+        "telemetry": ["inline::meta-reference"],
+        "tool_runtime": [
+            "remote::brave-search",
+            "remote::tavily-search",
+            "inline::code-interpreter",
+            "inline::rag-runtime",
+        ],
+    }
+
+    inference_provider = Provider(
+        provider_id="sambanova",
+        provider_type="remote::sambanova",
+        config=SambaNovaImplConfig.sample_run_config(),
+    )
+
+    core_model_to_hf_repo = {
+        m.descriptor(): m.huggingface_repo for m in all_registered_models()
+    }
+    default_models = [
+        ModelInput(
+            model_id=core_model_to_hf_repo[m.llama_model],
+            provider_model_id=m.provider_model_id,
+        )
+        for m in MODEL_ALIASES
+    ]
+
+    return DistributionTemplate(
+        name="sambanova",
+        distro_type="self_hosted",
+        description="Use SambaNova.AI for running LLM inference",
+        docker_image=None,
+        template_path=Path(__file__).parent / "doc_template.md",
+        providers=providers,
+        default_models=default_models,
+        run_configs={
+            "run.yaml": RunConfigSettings(
+                provider_overrides={
+                    "inference": [inference_provider],
+                },
+                default_models=default_models,
+                default_shields=[ShieldInput(shield_id="meta-llama/Llama-Guard-3-8B")],
+            ),
+        },
+        run_config_env_vars={
+            "LLAMASTACK_PORT": (
+                "5001",
+                "Port for the Llama Stack distribution server",
+            ),
+            "SAMBANOVA_API_KEY": (
+                "",
+                "SambaNova.AI API Key",
+            ),
+        },
+    )
diff --git a/llama_stack/templates/template.py b/llama_stack/templates/template.py
index 5bb88c821..78f57b795 100644
--- a/llama_stack/templates/template.py
+++ b/llama_stack/templates/template.py
@@ -37,7 +37,7 @@ class RunConfigSettings(BaseModel):
         self,
         name: str,
         providers: Dict[str, List[str]],
-        docker_image: Optional[str] = None,
+        container_image: Optional[str] = None,
     ) -> StackRunConfig:
         provider_registry = get_provider_registry()
 
@@ -83,8 +83,7 @@ class RunConfigSettings(BaseModel):
 
         return StackRunConfig(
             image_name=name,
-            docker_image=docker_image,
-            conda_env=name,
+            container_image=container_image,
             apis=apis,
             providers=provider_configs,
             metadata_store=SqliteKVStoreConfig.sample_run_config(
@@ -113,7 +112,7 @@ class DistributionTemplate(BaseModel):
 
     # Optional configuration
     run_config_env_vars: Optional[Dict[str, Tuple[str, str]]] = None
-    docker_image: Optional[str] = None
+    container_image: Optional[str] = None
 
     default_models: Optional[List[ModelInput]] = None
 
@@ -122,7 +121,7 @@ class DistributionTemplate(BaseModel):
             name=self.name,
             distribution_spec=DistributionSpec(
                 description=self.description,
-                docker_image=self.docker_image,
+                container_image=self.container_image,
                 providers=self.providers,
             ),
             image_type="conda",  # default to conda, can be overridden
@@ -170,7 +169,7 @@ class DistributionTemplate(BaseModel):
 
         for yaml_pth, settings in self.run_configs.items():
             run_config = settings.run_config(
-                self.name, self.providers, self.docker_image
+                self.name, self.providers, self.container_image
             )
             with open(yaml_output_dir / yaml_pth, "w") as f:
                 yaml.safe_dump(
diff --git a/llama_stack/templates/tgi/build.yaml b/llama_stack/templates/tgi/build.yaml
index 3bcacffb0..8bc628158 100644
--- a/llama_stack/templates/tgi/build.yaml
+++ b/llama_stack/templates/tgi/build.yaml
@@ -4,7 +4,7 @@ distribution_spec:
   providers:
     inference:
     - remote::tgi
-    memory:
+    vector_io:
     - inline::faiss
     - remote::chromadb
     - remote::pgvector
@@ -27,5 +27,6 @@ distribution_spec:
     - remote::brave-search
     - remote::tavily-search
     - inline::code-interpreter
-    - inline::memory-runtime
+    - inline::rag-runtime
+    - remote::model-context-protocol
 image_type: conda
diff --git a/llama_stack/templates/tgi/doc_template.md b/llama_stack/templates/tgi/doc_template.md
index 067f69d1f..18b7d6b86 100644
--- a/llama_stack/templates/tgi/doc_template.md
+++ b/llama_stack/templates/tgi/doc_template.md
@@ -91,10 +91,15 @@ docker run \
 If you are using Llama Stack Safety / Shield APIs, use:
 
 ```bash
+# You need a local checkout of llama-stack to run this, get it using
+# git clone https://github.com/meta-llama/llama-stack.git
+cd /path/to/llama-stack
+
 docker run \
   -it \
   -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
-  -v ./run-with-safety.yaml:/root/my-run.yaml \
+  -v ~/.llama:/root/.llama \
+  -v ./llama_stack/templates/tgi/run-with-safety.yaml:/root/my-run.yaml \
   llamastack/distribution-{{ name }} \
   --yaml-config /root/my-run.yaml \
   --port $LLAMA_STACK_PORT \
diff --git a/llama_stack/templates/tgi/report.md b/llama_stack/templates/tgi/report.md
new file mode 100644
index 000000000..b0f5d88a2
--- /dev/null
+++ b/llama_stack/templates/tgi/report.md
@@ -0,0 +1,44 @@
+# Report for tgi distribution
+
+## Supported Models
+| Model Descriptor | tgi |
+|:---|:---|
+| Llama-3-8B-Instruct | ✅ |
+| Llama-3-70B-Instruct | ✅ |
+| Llama3.1-8B-Instruct | ✅ |
+| Llama3.1-70B-Instruct | ✅ |
+| Llama3.1-405B-Instruct | ✅ |
+| Llama3.2-1B-Instruct | ✅ |
+| Llama3.2-3B-Instruct | ✅ |
+| Llama3.2-11B-Vision-Instruct | ✅ |
+| Llama3.2-90B-Vision-Instruct | ✅ |
+| Llama3.3-70B-Instruct | ✅ |
+| Llama-Guard-3-11B-Vision | ✅ |
+| Llama-Guard-3-1B | ✅ |
+| Llama-Guard-3-8B | ✅ |
+| Llama-Guard-2-8B | ✅ |
+
+## Inference
+| Model | API | Capability | Test | Status |
+|:----- |:-----|:-----|:-----|:-----|
+| Llama-3.1-8B-Instruct | /chat_completion | streaming | test_text_chat_completion_streaming | ✅ |
+| Llama-3.2-11B-Vision-Instruct | /chat_completion | streaming | test_image_chat_completion_streaming | ❌ |
+| Llama-3.2-11B-Vision-Instruct | /chat_completion | non_streaming | test_image_chat_completion_non_streaming | ❌ |
+| Llama-3.1-8B-Instruct | /chat_completion | non_streaming | test_text_chat_completion_non_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /chat_completion | tool_calling | test_text_chat_completion_with_tool_calling_and_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /chat_completion | tool_calling | test_text_chat_completion_with_tool_calling_and_non_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /completion | streaming | test_text_completion_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /completion | non_streaming | test_text_completion_non_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /completion | structured_output | test_text_completion_structured_output | ✅ |
+
+## Vector IO
+| API | Capability | Test | Status |
+|:-----|:-----|:-----|:-----|
+| /retrieve |  | test_vector_db_retrieve | ✅ |
+
+## Agents
+| API | Capability | Test | Status |
+|:-----|:-----|:-----|:-----|
+| /create_agent_turn | rag | test_rag_agent | ✅ |
+| /create_agent_turn | custom_tool | test_custom_tool | ✅ |
+| /create_agent_turn | code_execution | test_code_interpreter_for_attachments | ✅ |
diff --git a/llama_stack/templates/tgi/run-with-safety.yaml b/llama_stack/templates/tgi/run-with-safety.yaml
index 070daedc1..503505c32 100644
--- a/llama_stack/templates/tgi/run-with-safety.yaml
+++ b/llama_stack/templates/tgi/run-with-safety.yaml
@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: tgi-inference
@@ -20,7 +20,7 @@ providers:
     provider_type: remote::tgi
     config:
       url: ${env.TGI_SAFETY_URL}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -83,8 +83,11 @@ providers:
   - provider_id: code-interpreter
     provider_type: inline::code-interpreter
     config: {}
-  - provider_id: memory-runtime
-    provider_type: inline::memory-runtime
+  - provider_id: rag-runtime
+    provider_type: inline::rag-runtime
+    config: {}
+  - provider_id: model-context-protocol
+    provider_type: remote::model-context-protocol
     config: {}
 metadata_store:
   type: sqlite
@@ -100,14 +103,14 @@ models:
   model_type: llm
 shields:
 - shield_id: ${env.SAFETY_MODEL}
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []
 tool_groups:
 - toolgroup_id: builtin::websearch
   provider_id: tavily-search
-- toolgroup_id: builtin::memory
-  provider_id: memory-runtime
+- toolgroup_id: builtin::rag
+  provider_id: rag-runtime
 - toolgroup_id: builtin::code_interpreter
   provider_id: code-interpreter
diff --git a/llama_stack/templates/tgi/run.yaml b/llama_stack/templates/tgi/run.yaml
index e9696c584..f1953c513 100644
--- a/llama_stack/templates/tgi/run.yaml
+++ b/llama_stack/templates/tgi/run.yaml
@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: tgi-inference
@@ -19,7 +19,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -82,8 +82,11 @@ providers:
   - provider_id: code-interpreter
     provider_type: inline::code-interpreter
     config: {}
-  - provider_id: memory-runtime
-    provider_type: inline::memory-runtime
+  - provider_id: rag-runtime
+    provider_type: inline::rag-runtime
+    config: {}
+  - provider_id: model-context-protocol
+    provider_type: remote::model-context-protocol
     config: {}
 metadata_store:
   type: sqlite
@@ -99,14 +102,14 @@ models:
   provider_id: sentence-transformers
   model_type: embedding
 shields: []
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []
 tool_groups:
 - toolgroup_id: builtin::websearch
   provider_id: tavily-search
-- toolgroup_id: builtin::memory
-  provider_id: memory-runtime
+- toolgroup_id: builtin::rag
+  provider_id: rag-runtime
 - toolgroup_id: builtin::code_interpreter
   provider_id: code-interpreter
diff --git a/llama_stack/templates/tgi/tgi.py b/llama_stack/templates/tgi/tgi.py
index b62e7719e..e49c98d72 100644
--- a/llama_stack/templates/tgi/tgi.py
+++ b/llama_stack/templates/tgi/tgi.py
@@ -16,7 +16,7 @@ from llama_stack.distribution.datatypes import (
 from llama_stack.providers.inline.inference.sentence_transformers import (
     SentenceTransformersInferenceConfig,
 )
-from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
+from llama_stack.providers.inline.vector_io.faiss.config import FaissImplConfig
 from llama_stack.providers.remote.inference.tgi import TGIImplConfig
 from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
 
@@ -24,7 +24,7 @@ from llama_stack.templates.template import DistributionTemplate, RunConfigSettin
 def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["remote::tgi"],
-        "memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
         "safety": ["inline::llama-guard"],
         "agents": ["inline::meta-reference"],
         "telemetry": ["inline::meta-reference"],
@@ -35,7 +35,8 @@ def get_distribution_template() -> DistributionTemplate:
             "remote::brave-search",
             "remote::tavily-search",
             "inline::code-interpreter",
-            "inline::memory-runtime",
+            "inline::rag-runtime",
+            "remote::model-context-protocol",
         ],
     }
     name = "tgi"
@@ -51,7 +52,7 @@ def get_distribution_template() -> DistributionTemplate:
         provider_type="inline::sentence-transformers",
         config=SentenceTransformersInferenceConfig.sample_run_config(),
     )
-    memory_provider = Provider(
+    vector_io_provider = Provider(
         provider_id="faiss",
         provider_type="inline::faiss",
         config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
@@ -79,8 +80,8 @@ def get_distribution_template() -> DistributionTemplate:
             provider_id="tavily-search",
         ),
         ToolGroupInput(
-            toolgroup_id="builtin::memory",
-            provider_id="memory-runtime",
+            toolgroup_id="builtin::rag",
+            provider_id="rag-runtime",
         ),
         ToolGroupInput(
             toolgroup_id="builtin::code_interpreter",
@@ -92,7 +93,7 @@ def get_distribution_template() -> DistributionTemplate:
         name=name,
         distro_type="self_hosted",
         description="Use (an external) TGI server for running LLM inference",
-        docker_image=None,
+        container_image=None,
         template_path=Path(__file__).parent / "doc_template.md",
         providers=providers,
         default_models=[inference_model, safety_model],
@@ -100,7 +101,7 @@ def get_distribution_template() -> DistributionTemplate:
             "run.yaml": RunConfigSettings(
                 provider_overrides={
                     "inference": [inference_provider, embedding_provider],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=[inference_model, embedding_model],
                 default_tool_groups=default_tool_groups,
@@ -117,7 +118,7 @@ def get_distribution_template() -> DistributionTemplate:
                             ),
                         ),
                     ],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=[
                     inference_model,
diff --git a/llama_stack/templates/together/build.yaml b/llama_stack/templates/together/build.yaml
index ad970f405..90ee5bcee 100644
--- a/llama_stack/templates/together/build.yaml
+++ b/llama_stack/templates/together/build.yaml
@@ -4,7 +4,7 @@ distribution_spec:
   providers:
     inference:
     - remote::together
-    memory:
+    vector_io:
     - inline::faiss
     - remote::chromadb
     - remote::pgvector
@@ -27,5 +27,6 @@ distribution_spec:
     - remote::brave-search
     - remote::tavily-search
     - inline::code-interpreter
-    - inline::memory-runtime
+    - inline::rag-runtime
+    - remote::model-context-protocol
 image_type: conda
diff --git a/llama_stack/templates/together/report.md b/llama_stack/templates/together/report.md
new file mode 100644
index 000000000..e125d5665
--- /dev/null
+++ b/llama_stack/templates/together/report.md
@@ -0,0 +1,46 @@
+# Report for together distribution
+
+## Supported Models
+| Model Descriptor | together |
+|:---|:---|
+| Llama-3-8B-Instruct | ❌ |
+| Llama-3-70B-Instruct | ❌ |
+| Llama3.1-8B-Instruct | ✅ |
+| Llama3.1-70B-Instruct | ✅ |
+| Llama3.1-405B-Instruct | ✅ |
+| Llama3.2-1B-Instruct | ❌ |
+| Llama3.2-3B-Instruct | ✅ |
+| Llama3.2-11B-Vision-Instruct | ✅ |
+| Llama3.2-90B-Vision-Instruct | ✅ |
+| Llama3.3-70B-Instruct | ✅ |
+| Llama-Guard-3-11B-Vision | ✅ |
+| Llama-Guard-3-1B | ❌ |
+| Llama-Guard-3-8B | ✅ |
+| Llama-Guard-2-8B | ❌ |
+
+## Inference
+| Model | API | Capability | Test | Status |
+|:----- |:-----|:-----|:-----|:-----|
+| Llama-3.1-8B-Instruct | /chat_completion | streaming | test_text_chat_completion_streaming | ✅ |
+| Llama-3.2-11B-Vision-Instruct | /chat_completion | streaming | test_image_chat_completion_streaming | ✅ |
+| Llama-3.2-11B-Vision-Instruct | /chat_completion | non_streaming | test_image_chat_completion_non_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /chat_completion | non_streaming | test_text_chat_completion_non_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /chat_completion | tool_calling | test_text_chat_completion_with_tool_calling_and_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /chat_completion | tool_calling | test_text_chat_completion_with_tool_calling_and_non_streaming | ✅ |
+| Llama-3.2-11B-Vision-Instruct | /chat_completion | log_probs | test_completion_log_probs_non_streaming | ✅ |
+| Llama-3.2-11B-Vision-Instruct | /chat_completion | log_probs | test_completion_log_probs_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /completion | streaming | test_text_completion_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /completion | non_streaming | test_text_completion_non_streaming | ✅ |
+| Llama-3.1-8B-Instruct | /completion | structured_output | test_text_completion_structured_output | ✅ |
+
+## Vector IO
+| Provider | API | Capability | Test | Status |
+|:-----|:-----|:-----|:-----|:-----|
+| inline::faiss | /retrieve |  | test_vector_db_retrieve | ✅ |
+
+## Agents
+| Provider | API | Capability | Test | Status |
+|:-----|:-----|:-----|:-----|:-----|
+| inline::meta-reference | /create_agent_turn | rag | test_rag_agent | ✅ |
+| inline::meta-reference | /create_agent_turn | custom_tool | test_custom_tool | ✅ |
+| inline::meta-reference | /create_agent_turn | code_execution | test_code_interpreter_for_attachments | ✅ |
diff --git a/llama_stack/templates/together/run-with-safety.yaml b/llama_stack/templates/together/run-with-safety.yaml
index 4e162aab3..ec351108e 100644
--- a/llama_stack/templates/together/run-with-safety.yaml
+++ b/llama_stack/templates/together/run-with-safety.yaml
@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: together
@@ -20,7 +20,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -89,8 +89,11 @@ providers:
   - provider_id: code-interpreter
     provider_type: inline::code-interpreter
     config: {}
-  - provider_id: memory-runtime
-    provider_type: inline::memory-runtime
+  - provider_id: rag-runtime
+    provider_type: inline::rag-runtime
+    config: {}
+  - provider_id: model-context-protocol
+    provider_type: remote::model-context-protocol
     config: {}
 metadata_store:
   type: sqlite
@@ -153,14 +156,14 @@ shields:
   provider_id: llama-guard-vision
 - shield_id: CodeScanner
   provider_id: code-scanner
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []
 tool_groups:
 - toolgroup_id: builtin::websearch
   provider_id: tavily-search
-- toolgroup_id: builtin::memory
-  provider_id: memory-runtime
+- toolgroup_id: builtin::rag
+  provider_id: rag-runtime
 - toolgroup_id: builtin::code_interpreter
   provider_id: code-interpreter
diff --git a/llama_stack/templates/together/run.yaml b/llama_stack/templates/together/run.yaml
index 3c4844447..c2afd98e9 100644
--- a/llama_stack/templates/together/run.yaml
+++ b/llama_stack/templates/together/run.yaml
@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: together
@@ -20,7 +20,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -83,8 +83,11 @@ providers:
   - provider_id: code-interpreter
     provider_type: inline::code-interpreter
     config: {}
-  - provider_id: memory-runtime
-    provider_type: inline::memory-runtime
+  - provider_id: rag-runtime
+    provider_type: inline::rag-runtime
+    config: {}
+  - provider_id: model-context-protocol
+    provider_type: remote::model-context-protocol
     config: {}
 metadata_store:
   type: sqlite
@@ -142,14 +145,14 @@ models:
   model_type: embedding
 shields:
 - shield_id: meta-llama/Llama-Guard-3-8B
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []
 tool_groups:
 - toolgroup_id: builtin::websearch
   provider_id: tavily-search
-- toolgroup_id: builtin::memory
-  provider_id: memory-runtime
+- toolgroup_id: builtin::rag
+  provider_id: rag-runtime
 - toolgroup_id: builtin::code_interpreter
   provider_id: code-interpreter
diff --git a/llama_stack/templates/together/together.py b/llama_stack/templates/together/together.py
index b51918a6c..5e9520433 100644
--- a/llama_stack/templates/together/together.py
+++ b/llama_stack/templates/together/together.py
@@ -18,7 +18,7 @@ from llama_stack.distribution.datatypes import (
 from llama_stack.providers.inline.inference.sentence_transformers import (
     SentenceTransformersInferenceConfig,
 )
-from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
+from llama_stack.providers.inline.vector_io.faiss.config import FaissImplConfig
 from llama_stack.providers.remote.inference.together import TogetherImplConfig
 from llama_stack.providers.remote.inference.together.together import MODEL_ALIASES
 from llama_stack.templates.template import DistributionTemplate, RunConfigSettings
@@ -27,7 +27,7 @@ from llama_stack.templates.template import DistributionTemplate, RunConfigSettin
 def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["remote::together"],
-        "memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
         "safety": ["inline::llama-guard"],
         "agents": ["inline::meta-reference"],
         "telemetry": ["inline::meta-reference"],
@@ -38,7 +38,8 @@ def get_distribution_template() -> DistributionTemplate:
             "remote::brave-search",
             "remote::tavily-search",
             "inline::code-interpreter",
-            "inline::memory-runtime",
+            "inline::rag-runtime",
+            "remote::model-context-protocol",
         ],
     }
     name = "together"
@@ -47,7 +48,7 @@ def get_distribution_template() -> DistributionTemplate:
         provider_type="remote::together",
         config=TogetherImplConfig.sample_run_config(),
     )
-    memory_provider = Provider(
+    vector_io_provider = Provider(
         provider_id="faiss",
         provider_type="inline::faiss",
         config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
@@ -75,8 +76,8 @@ def get_distribution_template() -> DistributionTemplate:
             provider_id="tavily-search",
         ),
         ToolGroupInput(
-            toolgroup_id="builtin::memory",
-            provider_id="memory-runtime",
+            toolgroup_id="builtin::rag",
+            provider_id="rag-runtime",
         ),
         ToolGroupInput(
             toolgroup_id="builtin::code_interpreter",
@@ -96,7 +97,7 @@ def get_distribution_template() -> DistributionTemplate:
         name=name,
         distro_type="self_hosted",
         description="Use Together.AI for running LLM inference",
-        docker_image=None,
+        container_image=None,
         template_path=Path(__file__).parent / "doc_template.md",
         providers=providers,
         default_models=default_models,
@@ -104,7 +105,7 @@ def get_distribution_template() -> DistributionTemplate:
             "run.yaml": RunConfigSettings(
                 provider_overrides={
                     "inference": [inference_provider, embedding_provider],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=default_models + [embedding_model],
                 default_tool_groups=default_tool_groups,
@@ -116,7 +117,7 @@ def get_distribution_template() -> DistributionTemplate:
                         inference_provider,
                         embedding_provider,
                     ],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                     "safety": [
                         Provider(
                             provider_id="llama-guard",
diff --git a/llama_stack/templates/vllm-gpu/build.yaml b/llama_stack/templates/vllm-gpu/build.yaml
index e068fa97e..d24046613 100644
--- a/llama_stack/templates/vllm-gpu/build.yaml
+++ b/llama_stack/templates/vllm-gpu/build.yaml
@@ -4,7 +4,7 @@ distribution_spec:
   providers:
     inference:
     - inline::vllm
-    memory:
+    vector_io:
     - inline::faiss
     - remote::chromadb
     - remote::pgvector
@@ -27,5 +27,6 @@ distribution_spec:
     - remote::brave-search
     - remote::tavily-search
     - inline::code-interpreter
-    - inline::memory-runtime
+    - inline::rag-runtime
+    - remote::model-context-protocol
 image_type: conda
diff --git a/llama_stack/templates/vllm-gpu/run.yaml b/llama_stack/templates/vllm-gpu/run.yaml
index 1cb44b052..165e4d51d 100644
--- a/llama_stack/templates/vllm-gpu/run.yaml
+++ b/llama_stack/templates/vllm-gpu/run.yaml
@@ -5,11 +5,11 @@ apis:
 - datasetio
 - eval
 - inference
-- memory
 - safety
 - scoring
 - telemetry
 - tool_runtime
+- vector_io
 providers:
   inference:
   - provider_id: vllm
@@ -23,7 +23,7 @@ providers:
   - provider_id: sentence-transformers
     provider_type: inline::sentence-transformers
     config: {}
-  memory:
+  vector_io:
   - provider_id: faiss
     provider_type: inline::faiss
     config:
@@ -86,8 +86,11 @@ providers:
   - provider_id: code-interpreter
     provider_type: inline::code-interpreter
     config: {}
-  - provider_id: memory-runtime
-    provider_type: inline::memory-runtime
+  - provider_id: rag-runtime
+    provider_type: inline::rag-runtime
+    config: {}
+  - provider_id: model-context-protocol
+    provider_type: remote::model-context-protocol
     config: {}
 metadata_store:
   type: sqlite
@@ -103,14 +106,14 @@ models:
   provider_id: sentence-transformers
   model_type: embedding
 shields: []
-memory_banks: []
+vector_dbs: []
 datasets: []
 scoring_fns: []
 eval_tasks: []
 tool_groups:
 - toolgroup_id: builtin::websearch
   provider_id: tavily-search
-- toolgroup_id: builtin::memory
-  provider_id: memory-runtime
+- toolgroup_id: builtin::rag
+  provider_id: rag-runtime
 - toolgroup_id: builtin::code_interpreter
   provider_id: code-interpreter
diff --git a/llama_stack/templates/vllm-gpu/vllm.py b/llama_stack/templates/vllm-gpu/vllm.py
index dd80c15dc..54ebd2d41 100644
--- a/llama_stack/templates/vllm-gpu/vllm.py
+++ b/llama_stack/templates/vllm-gpu/vllm.py
@@ -10,7 +10,7 @@ from llama_stack.providers.inline.inference.sentence_transformers import (
     SentenceTransformersInferenceConfig,
 )
 from llama_stack.providers.inline.inference.vllm import VLLMConfig
-from llama_stack.providers.inline.memory.faiss.config import FaissImplConfig
+from llama_stack.providers.inline.vector_io.faiss.config import FaissImplConfig
 from llama_stack.templates.template import (
     DistributionTemplate,
     RunConfigSettings,
@@ -21,7 +21,7 @@ from llama_stack.templates.template import (
 def get_distribution_template() -> DistributionTemplate:
     providers = {
         "inference": ["inline::vllm"],
-        "memory": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
+        "vector_io": ["inline::faiss", "remote::chromadb", "remote::pgvector"],
         "safety": ["inline::llama-guard"],
         "agents": ["inline::meta-reference"],
         "telemetry": ["inline::meta-reference"],
@@ -32,7 +32,8 @@ def get_distribution_template() -> DistributionTemplate:
             "remote::brave-search",
             "remote::tavily-search",
             "inline::code-interpreter",
-            "inline::memory-runtime",
+            "inline::rag-runtime",
+            "remote::model-context-protocol",
         ],
     }
 
@@ -42,7 +43,7 @@ def get_distribution_template() -> DistributionTemplate:
         provider_type="inline::vllm",
         config=VLLMConfig.sample_run_config(),
     )
-    memory_provider = Provider(
+    vector_io_provider = Provider(
         provider_id="faiss",
         provider_type="inline::faiss",
         config=FaissImplConfig.sample_run_config(f"distributions/{name}"),
@@ -71,8 +72,8 @@ def get_distribution_template() -> DistributionTemplate:
             provider_id="tavily-search",
         ),
         ToolGroupInput(
-            toolgroup_id="builtin::memory",
-            provider_id="memory-runtime",
+            toolgroup_id="builtin::rag",
+            provider_id="rag-runtime",
         ),
         ToolGroupInput(
             toolgroup_id="builtin::code_interpreter",
@@ -84,7 +85,7 @@ def get_distribution_template() -> DistributionTemplate:
         name=name,
         distro_type="self_hosted",
         description="Use a built-in vLLM engine for running LLM inference",
-        docker_image=None,
+        container_image=None,
         template_path=None,
         providers=providers,
         default_models=[inference_model],
@@ -92,7 +93,7 @@ def get_distribution_template() -> DistributionTemplate:
             "run.yaml": RunConfigSettings(
                 provider_overrides={
                     "inference": [inference_provider, embedding_provider],
-                    "memory": [memory_provider],
+                    "vector_io": [vector_io_provider],
                 },
                 default_models=[inference_model, embedding_model],
                 default_tool_groups=default_tool_groups,
diff --git a/requirements.txt b/requirements.txt
index 304467ddc..e38b23043 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -2,8 +2,8 @@ blobfile
 fire
 httpx
 huggingface-hub
-llama-models>=0.0.63
-llama-stack-client>=0.0.63
+llama-models>=0.1.0
+llama-stack-client>=0.1.0
 prompt-toolkit
 python-dotenv
 pydantic>=2
diff --git a/setup.py b/setup.py
index c0f8cf575..2af0fdee3 100644
--- a/setup.py
+++ b/setup.py
@@ -16,7 +16,7 @@ def read_requirements():
 
 setup(
     name="llama_stack",
-    version="0.0.63",
+    version="0.1.0",
     author="Meta Llama",
     author_email="llama-oss@meta.com",
     description="Llama Stack",
diff --git a/tests/client-sdk/README.md b/tests/client-sdk/README.md
new file mode 100644
index 000000000..13142d46f
--- /dev/null
+++ b/tests/client-sdk/README.md
@@ -0,0 +1,34 @@
+# Llama Stack Integration Tests
+You can run llama stack integration tests on either a Llama Stack Library or a Llama Stack endpoint.
+
+To test on a Llama Stack library with certain configuration, run
+```bash
+LLAMA_STACK_CONFIG=./llama_stack/templates/cerebras/run.yaml
+pytest -s -v tests/client-sdk/inference/test_inference.py
+```
+or just the template name
+```bash
+LLAMA_STACK_CONFIG=together
+pytest -s -v tests/client-sdk/inference/test_inference.py
+```
+
+To test on a Llama Stack endpoint, run
+```bash
+LLAMA_STACK_BASE_URL=http//localhost:8089
+pytest -s -v tests/client-sdk/inference/test_inference.py
+```
+
+## Report Generation
+
+To generate a report, run with `--report` option
+```bash
+LLAMA_STACK_CONFIG=together pytest -s -v report.md tests/client-sdk/ --report
+```
+
+## Common options
+Depending on the API, there are custom options enabled
+- For tests in `inference/` and `agents/, we support `--inference-model` (to be used in text inference tests) and `--vision-inference-model` (only used in image inference tests) overrides
+- For tests in `vector_io/`, we support `--embedding-model` override
+- For tests in `safety/`, we support `--safety-shield` override
+- The param can be `--report` or `--report <path>`
+If path is not provided, we do a best effort to infer based on the config / template name. For url endpoints, path is required.
diff --git a/tests/client-sdk/agents/test_agents.py b/tests/client-sdk/agents/test_agents.py
index d6d88a34f..4a8fdd36a 100644
--- a/tests/client-sdk/agents/test_agents.py
+++ b/tests/client-sdk/agents/test_agents.py
@@ -80,26 +80,14 @@ class TestClientTool(ClientTool):
 
 
 @pytest.fixture(scope="session")
-def model_id(llama_stack_client):
-    available_models = [
-        model.identifier
-        for model in llama_stack_client.models.list()
-        if model.identifier.startswith("meta-llama") and "405" not in model.identifier
-    ]
-    model_id = available_models[0]
-    print(f"Using model: {model_id}")
-    return model_id
-
-
-@pytest.fixture(scope="session")
-def agent_config(llama_stack_client, model_id):
+def agent_config(llama_stack_client, text_model_id):
     available_shields = [
         shield.identifier for shield in llama_stack_client.shields.list()
     ]
     available_shields = available_shields[:1]
     print(f"Using shield: {available_shields}")
     agent_config = AgentConfig(
-        model=model_id,
+        model=text_model_id,
         instructions="You are a helpful assistant",
         sampling_params={
             "strategy": {
@@ -110,7 +98,6 @@ def agent_config(llama_stack_client, model_id):
         },
         toolgroups=[],
         tool_choice="auto",
-        tool_prompt_format="json",
         input_shields=available_shields,
         output_shields=available_shields,
         enable_session_persistence=False,
@@ -182,7 +169,8 @@ def test_builtin_tool_web_search(llama_stack_client, agent_config):
     assert "tool_execution>" in logs_str
     assert "Tool:brave_search Response:" in logs_str
     assert "mark zuckerberg" in logs_str.lower()
-    assert "No Violation" in logs_str
+    if len(agent_config["output_shields"]) > 0:
+        assert "No Violation" in logs_str
 
 
 def test_builtin_tool_code_execution(llama_stack_client, agent_config):
@@ -211,7 +199,10 @@ def test_builtin_tool_code_execution(llama_stack_client, agent_config):
     assert "Tool:code_interpreter Response" in logs_str
 
 
-def test_code_execution(llama_stack_client, agent_config):
+# This test must be run in an environment where `bwrap` is available. If you are running against a
+# server, this means the _server_ must have `bwrap` available. If you are using library client, then
+# you must have `bwrap` available in test's environment.
+def test_code_interpreter_for_attachments(llama_stack_client, agent_config):
     agent_config = {
         **agent_config,
         "toolgroups": [
@@ -285,27 +276,24 @@ def test_rag_agent(llama_stack_client, agent_config):
         )
         for i, url in enumerate(urls)
     ]
-    memory_bank_id = "test-memory-bank"
-    llama_stack_client.memory_banks.register(
-        memory_bank_id=memory_bank_id,
-        params={
-            "memory_bank_type": "vector",
-            "embedding_model": "all-MiniLM-L6-v2",
-            "chunk_size_in_tokens": 512,
-            "overlap_size_in_tokens": 64,
-        },
+    vector_db_id = "test-vector-db"
+    llama_stack_client.vector_dbs.register(
+        vector_db_id=vector_db_id,
+        embedding_model="all-MiniLM-L6-v2",
+        embedding_dimension=384,
     )
-    llama_stack_client.memory.insert(
-        bank_id=memory_bank_id,
+    llama_stack_client.tool_runtime.rag_tool.insert(
         documents=documents,
+        vector_db_id=vector_db_id,
+        chunk_size_in_tokens=512,
     )
     agent_config = {
         **agent_config,
         "toolgroups": [
             dict(
-                name="builtin::memory",
+                name="builtin::rag",
                 args={
-                    "memory_bank_ids": [memory_bank_id],
+                    "vector_db_ids": [vector_db_id],
                 },
             )
         ],
@@ -323,4 +311,4 @@ def test_rag_agent(llama_stack_client, agent_config):
         )
         logs = [str(log) for log in EventLogger().log(response) if log is not None]
         logs_str = "".join(logs)
-        assert "Tool:query_memory" in logs_str
+        assert "Tool:query_from_memory" in logs_str
diff --git a/tests/client-sdk/conftest.py b/tests/client-sdk/conftest.py
index b40d54ee5..2a366e985 100644
--- a/tests/client-sdk/conftest.py
+++ b/tests/client-sdk/conftest.py
@@ -10,11 +10,48 @@ import pytest
 from llama_stack import LlamaStackAsLibraryClient
 from llama_stack.providers.tests.env import get_env_or_fail
 from llama_stack_client import LlamaStackClient
+from report import Report
 
 
 def pytest_configure(config):
     config.option.tbstyle = "short"
     config.option.disable_warnings = True
+    # Note:
+    # if report_path is not provided (aka no option --report in the pytest command),
+    # it will be set to False
+    # if --report will give None ( in this case we infer report_path)
+    # if --report /a/b is provided, it will be set to the path provided
+    # We want to handle all these cases and hence explicitly check for False
+    report_path = config.getoption("--report")
+    if report_path is not False:
+        config.pluginmanager.register(Report(report_path))
+
+
+TEXT_MODEL = "meta-llama/Llama-3.1-8B-Instruct"
+VISION_MODEL = "meta-llama/Llama-3.2-11B-Vision-Instruct"
+
+
+def pytest_addoption(parser):
+    parser.addoption(
+        "--report",
+        action="store",
+        default=False,
+        nargs="?",
+        type=str,
+        help="Path where the test report should be written, e.g. --report=/path/to/report.md",
+    )
+    parser.addoption(
+        "--inference-model",
+        action="store",
+        default=TEXT_MODEL,
+        help="Specify the inference model to use for testing",
+    )
+    parser.addoption(
+        "--vision-inference-model",
+        action="store",
+        default=VISION_MODEL,
+        help="Specify the vision inference model to use for testing",
+    )
 
 
 @pytest.fixture(scope="session")
@@ -36,7 +73,9 @@ def llama_stack_client(provider_data):
             provider_data=provider_data,
             skip_logger_removal=True,
         )
-        client.initialize()
+        if not client.initialize():
+            raise RuntimeError("Initialization failed")
+
     elif os.environ.get("LLAMA_STACK_BASE_URL"):
         client = LlamaStackClient(
             base_url=get_env_or_fail("LLAMA_STACK_BASE_URL"),
@@ -45,3 +84,18 @@ def llama_stack_client(provider_data):
     else:
         raise ValueError("LLAMA_STACK_CONFIG or LLAMA_STACK_BASE_URL must be set")
     return client
+
+
+def pytest_generate_tests(metafunc):
+    if "text_model_id" in metafunc.fixturenames:
+        metafunc.parametrize(
+            "text_model_id",
+            [metafunc.config.getoption("--inference-model")],
+            scope="session",
+        )
+    if "vision_model_id" in metafunc.fixturenames:
+        metafunc.parametrize(
+            "vision_model_id",
+            [metafunc.config.getoption("--vision-inference-model")],
+            scope="session",
+        )
diff --git a/tests/client-sdk/inference/dog.png b/tests/client-sdk/inference/dog.png
new file mode 100644
index 000000000..2d502e606
Binary files /dev/null and b/tests/client-sdk/inference/dog.png differ
diff --git a/tests/client-sdk/inference/test_inference.py b/tests/client-sdk/inference/test_inference.py
index 19314e4ab..8ca11521c 100644
--- a/tests/client-sdk/inference/test_inference.py
+++ b/tests/client-sdk/inference/test_inference.py
@@ -4,11 +4,14 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
+import base64
+import os
+
 import pytest
 from pydantic import BaseModel
 
 PROVIDER_TOOL_PROMPT_FORMAT = {
-    "remote::ollama": "python_list",
+    "remote::ollama": "json",
     "remote::together": "json",
     "remote::fireworks": "json",
 }
@@ -31,30 +34,6 @@ def inference_provider_type(llama_stack_client):
     return inference_providers[0].provider_type
 
 
-@pytest.fixture(scope="session")
-def text_model_id(llama_stack_client):
-    available_models = [
-        model.identifier
-        for model in llama_stack_client.models.list()
-        if model.identifier.startswith("meta-llama") and "405" not in model.identifier
-    ]
-    assert len(available_models) > 0
-    return available_models[0]
-
-
-@pytest.fixture(scope="session")
-def vision_model_id(llama_stack_client):
-    available_models = [
-        model.identifier
-        for model in llama_stack_client.models.list()
-        if "vision" in model.identifier.lower()
-    ]
-    if len(available_models) == 0:
-        pytest.skip("No vision models available")
-
-    return available_models[0]
-
-
 @pytest.fixture
 def get_weather_tool_definition():
     return {
@@ -69,7 +48,17 @@ def get_weather_tool_definition():
     }
 
 
-def test_completion_non_streaming(llama_stack_client, text_model_id):
+@pytest.fixture
+def base64_image_url():
+    image_path = os.path.join(os.path.dirname(__file__), "dog.png")
+    with open(image_path, "rb") as image_file:
+        # Convert the image to base64
+        base64_string = base64.b64encode(image_file.read()).decode("utf-8")
+        base64_url = f"data:image/png;base64,{base64_string}"
+        return base64_url
+
+
+def test_text_completion_non_streaming(llama_stack_client, text_model_id):
     response = llama_stack_client.inference.completion(
         content="Complete the sentence using one word: Roses are red, violets are ",
         stream=False,
@@ -81,7 +70,7 @@ def test_completion_non_streaming(llama_stack_client, text_model_id):
     assert "blue" in response.content.lower().strip()
 
 
-def test_completion_streaming(llama_stack_client, text_model_id):
+def test_text_completion_streaming(llama_stack_client, text_model_id):
     response = llama_stack_client.inference.completion(
         content="Complete the sentence using one word: Roses are red, violets are ",
         stream=True,
@@ -94,6 +83,7 @@ def test_completion_streaming(llama_stack_client, text_model_id):
     assert "blue" in "".join(streamed_content).lower().strip()
 
 
+@pytest.mark.skip("Most inference providers don't support log probs yet")
 def test_completion_log_probs_non_streaming(llama_stack_client, text_model_id):
     response = llama_stack_client.inference.completion(
         content="Complete the sentence: Micheael Jordan is born in ",
@@ -111,6 +101,7 @@ def test_completion_log_probs_non_streaming(llama_stack_client, text_model_id):
     assert all(len(logprob.logprobs_by_token) == 3 for logprob in response.logprobs)
 
 
+@pytest.mark.skip("Most inference providers don't support log probs yet")
 def test_completion_log_probs_streaming(llama_stack_client, text_model_id):
     response = llama_stack_client.inference.completion(
         content="Complete the sentence: Micheael Jordan is born in ",
@@ -134,7 +125,7 @@ def test_completion_log_probs_streaming(llama_stack_client, text_model_id):
             assert not chunk.logprobs, "Logprobs should be empty"
 
 
-def test_completion_structured_output(
+def test_text_completion_structured_output(
     llama_stack_client, text_model_id, inference_provider_type
 ):
     user_input = """
@@ -245,7 +236,7 @@ def extract_tool_invocation_content(response):
     for chunk in response:
         delta = chunk.event.delta
         if delta.type == "tool_call" and delta.parse_status == "succeeded":
-            call = delta.content
+            call = delta.tool_call
             tool_invocation_content += f"[{call.tool_name}, {call.arguments}]"
     return tool_invocation_content
 
@@ -308,9 +299,11 @@ def test_image_chat_completion_non_streaming(llama_stack_client, vision_model_id
         "content": [
             {
                 "type": "image",
-                "url": {
-                    # TODO: Replace with Github based URI to resources/sample1.jpg
-                    "uri": "https://www.healthypawspetinsurance.com/Images/V3/DogAndPuppyInsurance/Dog_CTA_Desktop_HeroImage.jpg"
+                "image": {
+                    "url": {
+                        # TODO: Replace with Github based URI to resources/sample1.jpg
+                        "uri": "https://www.healthypawspetinsurance.com/Images/V3/DogAndPuppyInsurance/Dog_CTA_Desktop_HeroImage.jpg"
+                    },
                 },
             },
             {
@@ -335,9 +328,11 @@ def test_image_chat_completion_streaming(llama_stack_client, vision_model_id):
         "content": [
             {
                 "type": "image",
-                "url": {
-                    # TODO: Replace with Github based URI to resources/sample1.jpg
-                    "uri": "https://www.healthypawspetinsurance.com/Images/V3/DogAndPuppyInsurance/Dog_CTA_Desktop_HeroImage.jpg"
+                "image": {
+                    "url": {
+                        # TODO: Replace with Github based URI to resources/sample1.jpg
+                        "uri": "https://www.healthypawspetinsurance.com/Images/V3/DogAndPuppyInsurance/Dog_CTA_Desktop_HeroImage.jpg"
+                    },
                 },
             },
             {
@@ -356,3 +351,32 @@ def test_image_chat_completion_streaming(llama_stack_client, vision_model_id):
         streamed_content += chunk.event.delta.text.lower()
     assert len(streamed_content) > 0
     assert any(expected in streamed_content for expected in {"dog", "puppy", "pup"})
+
+
+def test_image_chat_completion_base64_url(
+    llama_stack_client, vision_model_id, base64_image_url
+):
+    message = {
+        "role": "user",
+        "content": [
+            {
+                "type": "image",
+                "image": {
+                    "url": {
+                        "uri": base64_image_url,
+                    },
+                },
+            },
+            {
+                "type": "text",
+                "text": "Describe what is in this image.",
+            },
+        ],
+    }
+    response = llama_stack_client.inference.chat_completion(
+        model_id=vision_model_id,
+        messages=[message],
+        stream=False,
+    )
+    message_content = response.completion_message.content.lower().strip()
+    assert len(message_content) > 0
diff --git a/tests/client-sdk/memory/test_memory.py b/tests/client-sdk/memory/test_memory.py
deleted file mode 100644
index 1e9b34355..000000000
--- a/tests/client-sdk/memory/test_memory.py
+++ /dev/null
@@ -1,258 +0,0 @@
-# Copyright (c) Meta Platforms, Inc. and affiliates.
-# All rights reserved.
-#
-# This source code is licensed under the terms described in the LICENSE file in
-# the root directory of this source tree.
-
-import random
-
-import pytest
-
-from llama_stack.apis.memory import MemoryBankDocument
-from llama_stack_client.types.memory_insert_params import Document
-
-
-@pytest.fixture(scope="function")
-def empty_memory_bank_registry(llama_stack_client):
-    memory_banks = [
-        memory_bank.identifier for memory_bank in llama_stack_client.memory_banks.list()
-    ]
-    for memory_bank_id in memory_banks:
-        llama_stack_client.memory_banks.unregister(memory_bank_id=memory_bank_id)
-
-
-@pytest.fixture(scope="function")
-def single_entry_memory_bank_registry(llama_stack_client, empty_memory_bank_registry):
-    memory_bank_id = f"test_bank_{random.randint(1000, 9999)}"
-    llama_stack_client.memory_banks.register(
-        memory_bank_id=memory_bank_id,
-        params={
-            "memory_bank_type": "vector",
-            "embedding_model": "all-MiniLM-L6-v2",
-            "chunk_size_in_tokens": 512,
-            "overlap_size_in_tokens": 64,
-        },
-        provider_id="faiss",
-    )
-    memory_banks = [
-        memory_bank.identifier for memory_bank in llama_stack_client.memory_banks.list()
-    ]
-    return memory_banks
-
-
-@pytest.fixture(scope="session")
-def sample_documents():
-    return [
-        MemoryBankDocument(
-            document_id="test-doc-1",
-            content="Python is a high-level programming language.",
-            metadata={"category": "programming", "difficulty": "beginner"},
-        ),
-        MemoryBankDocument(
-            document_id="test-doc-2",
-            content="Machine learning is a subset of artificial intelligence.",
-            metadata={"category": "AI", "difficulty": "advanced"},
-        ),
-        MemoryBankDocument(
-            document_id="test-doc-3",
-            content="Data structures are fundamental to computer science.",
-            metadata={"category": "computer science", "difficulty": "intermediate"},
-        ),
-        MemoryBankDocument(
-            document_id="test-doc-4",
-            content="Neural networks are inspired by biological neural networks.",
-            metadata={"category": "AI", "difficulty": "advanced"},
-        ),
-    ]
-
-
-def assert_valid_response(response):
-    assert len(response.chunks) > 0
-    assert len(response.scores) > 0
-    assert len(response.chunks) == len(response.scores)
-    for chunk in response.chunks:
-        assert isinstance(chunk.content, str)
-        assert chunk.document_id is not None
-
-
-def test_memory_bank_retrieve(llama_stack_client, empty_memory_bank_registry):
-    # Register a memory bank first
-    memory_bank_id = f"test_bank_{random.randint(1000, 9999)}"
-    llama_stack_client.memory_banks.register(
-        memory_bank_id=memory_bank_id,
-        params={
-            "memory_bank_type": "vector",
-            "embedding_model": "all-MiniLM-L6-v2",
-            "chunk_size_in_tokens": 512,
-            "overlap_size_in_tokens": 64,
-        },
-        provider_id="faiss",
-    )
-
-    # Retrieve the memory bank and validate its properties
-    response = llama_stack_client.memory_banks.retrieve(memory_bank_id=memory_bank_id)
-    assert response is not None
-    assert response.identifier == memory_bank_id
-    assert response.type == "memory_bank"
-    assert response.memory_bank_type == "vector"
-    assert response.embedding_model == "all-MiniLM-L6-v2"
-    assert response.chunk_size_in_tokens == 512
-    assert response.overlap_size_in_tokens == 64
-    assert response.provider_id == "faiss"
-    assert response.provider_resource_id == memory_bank_id
-
-
-def test_memory_bank_list(llama_stack_client, empty_memory_bank_registry):
-    memory_banks_after_register = [
-        memory_bank.identifier for memory_bank in llama_stack_client.memory_banks.list()
-    ]
-    assert len(memory_banks_after_register) == 0
-
-
-def test_memory_bank_register(llama_stack_client, empty_memory_bank_registry):
-    memory_provider_id = "faiss"
-    memory_bank_id = f"test_bank_{random.randint(1000, 9999)}"
-    llama_stack_client.memory_banks.register(
-        memory_bank_id=memory_bank_id,
-        params={
-            "memory_bank_type": "vector",
-            "embedding_model": "all-MiniLM-L6-v2",
-            "chunk_size_in_tokens": 512,
-            "overlap_size_in_tokens": 64,
-        },
-        provider_id=memory_provider_id,
-    )
-
-    memory_banks_after_register = [
-        memory_bank.identifier for memory_bank in llama_stack_client.memory_banks.list()
-    ]
-    assert memory_banks_after_register == [memory_bank_id]
-
-
-def test_memory_bank_unregister(llama_stack_client, single_entry_memory_bank_registry):
-    memory_banks = [
-        memory_bank.identifier for memory_bank in llama_stack_client.memory_banks.list()
-    ]
-    assert len(memory_banks) == 1
-
-    memory_bank_id = memory_banks[0]
-    llama_stack_client.memory_banks.unregister(memory_bank_id=memory_bank_id)
-
-    memory_banks = [
-        memory_bank.identifier for memory_bank in llama_stack_client.memory_banks.list()
-    ]
-    assert len(memory_banks) == 0
-
-
-def test_memory_bank_insert_inline_and_query(
-    llama_stack_client, single_entry_memory_bank_registry, sample_documents
-):
-    memory_bank_id = single_entry_memory_bank_registry[0]
-    llama_stack_client.memory.insert(
-        bank_id=memory_bank_id,
-        documents=sample_documents,
-    )
-
-    # Query with a direct match
-    query1 = "programming language"
-    response1 = llama_stack_client.memory.query(
-        bank_id=memory_bank_id,
-        query=query1,
-    )
-    assert_valid_response(response1)
-    assert any("Python" in chunk.content for chunk in response1.chunks)
-
-    # Query with semantic similarity
-    query2 = "AI and brain-inspired computing"
-    response2 = llama_stack_client.memory.query(
-        bank_id=memory_bank_id,
-        query=query2,
-    )
-    assert_valid_response(response2)
-    assert any("neural networks" in chunk.content.lower() for chunk in response2.chunks)
-
-    # Query with limit on number of results (max_chunks=2)
-    query3 = "computer"
-    response3 = llama_stack_client.memory.query(
-        bank_id=memory_bank_id,
-        query=query3,
-        params={"max_chunks": 2},
-    )
-    assert_valid_response(response3)
-    assert len(response3.chunks) <= 2
-
-    # Query with threshold on similarity score
-    query4 = "computer"
-    response4 = llama_stack_client.memory.query(
-        bank_id=memory_bank_id,
-        query=query4,
-        params={"score_threshold": 0.01},
-    )
-    assert_valid_response(response4)
-    assert all(score >= 0.01 for score in response4.scores)
-
-
-def test_memory_bank_insert_from_url_and_query(
-    llama_stack_client, empty_memory_bank_registry
-):
-    providers = [p for p in llama_stack_client.providers.list() if p.api == "memory"]
-    assert len(providers) > 0
-
-    memory_provider_id = providers[0].provider_id
-    memory_bank_id = "test_bank"
-
-    llama_stack_client.memory_banks.register(
-        memory_bank_id=memory_bank_id,
-        params={
-            "memory_bank_type": "vector",
-            "embedding_model": "all-MiniLM-L6-v2",
-            "chunk_size_in_tokens": 512,
-            "overlap_size_in_tokens": 64,
-        },
-        provider_id=memory_provider_id,
-    )
-
-    # list to check memory bank is successfully registered
-    available_memory_banks = [
-        memory_bank.identifier for memory_bank in llama_stack_client.memory_banks.list()
-    ]
-    assert memory_bank_id in available_memory_banks
-
-    # URLs of documents to insert
-    # TODO: Move to test/memory/resources then update the url to
-    # https://raw.githubusercontent.com/meta-llama/llama-stack/main/tests/memory/resources/{url}
-    urls = [
-        "memory_optimizations.rst",
-        "chat.rst",
-        "llama3.rst",
-    ]
-    documents = [
-        Document(
-            document_id=f"num-{i}",
-            content=f"https://raw.githubusercontent.com/pytorch/torchtune/main/docs/source/tutorials/{url}",
-            mime_type="text/plain",
-            metadata={},
-        )
-        for i, url in enumerate(urls)
-    ]
-
-    llama_stack_client.memory.insert(
-        bank_id=memory_bank_id,
-        documents=documents,
-    )
-
-    # Query for the name of method
-    response1 = llama_stack_client.memory.query(
-        bank_id=memory_bank_id,
-        query="What's the name of the fine-tunning method used?",
-    )
-    assert_valid_response(response1)
-    assert any("lora" in chunk.content.lower() for chunk in response1.chunks)
-
-    # Query for the name of model
-    response2 = llama_stack_client.memory.query(
-        bank_id=memory_bank_id,
-        query="Which Llama model is mentioned?",
-    )
-    assert_valid_response(response1)
-    assert any("llama2" in chunk.content.lower() for chunk in response2.chunks)
diff --git a/tests/client-sdk/metadata.py b/tests/client-sdk/metadata.py
new file mode 100644
index 000000000..55663c046
--- /dev/null
+++ b/tests/client-sdk/metadata.py
@@ -0,0 +1,54 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from llama_stack.providers.datatypes import Api
+
+INFERENCE_API_CAPA_TEST_MAP = {
+    "chat_completion": {
+        "streaming": [
+            "test_text_chat_completion_streaming",
+            "test_image_chat_completion_streaming",
+        ],
+        "non_streaming": [
+            "test_image_chat_completion_non_streaming",
+            "test_text_chat_completion_non_streaming",
+        ],
+        "tool_calling": [
+            "test_text_chat_completion_with_tool_calling_and_streaming",
+            "test_text_chat_completion_with_tool_calling_and_non_streaming",
+        ],
+        "log_probs": [
+            "test_completion_log_probs_non_streaming",
+            "test_completion_log_probs_streaming",
+        ],
+    },
+    "completion": {
+        "streaming": ["test_text_completion_streaming"],
+        "non_streaming": ["test_text_completion_non_streaming"],
+        "structured_output": ["test_text_completion_structured_output"],
+    },
+}
+
+VECTORIO_API_TEST_MAP = {
+    "retrieve": {
+        "": ["test_vector_db_retrieve"],
+    }
+}
+
+AGENTS_API_TEST_MAP = {
+    "create_agent_turn": {
+        "rag": ["test_rag_agent"],
+        "custom_tool": ["test_custom_tool"],
+        "code_execution": ["test_code_interpreter_for_attachments"],
+    }
+}
+
+
+API_MAPS = {
+    Api.inference: INFERENCE_API_CAPA_TEST_MAP,
+    Api.vector_io: VECTORIO_API_TEST_MAP,
+    Api.agents: AGENTS_API_TEST_MAP,
+}
diff --git a/tests/client-sdk/report.py b/tests/client-sdk/report.py
new file mode 100644
index 000000000..f39ea02fa
--- /dev/null
+++ b/tests/client-sdk/report.py
@@ -0,0 +1,258 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+
+import importlib
+import os
+from collections import defaultdict
+from pathlib import Path
+from typing import Optional
+from urllib.parse import urlparse
+
+import pytest
+from llama_models.datatypes import CoreModelId
+from llama_models.sku_list import (
+    all_registered_models,
+    llama3_1_instruct_models,
+    llama3_2_instruct_models,
+    llama3_3_instruct_models,
+    llama3_instruct_models,
+    safety_models,
+)
+
+from llama_stack.providers.datatypes import Api
+from llama_stack.providers.tests.env import get_env_or_fail
+
+from metadata import API_MAPS
+
+from pytest import CollectReport
+from termcolor import cprint
+
+
+def featured_models():
+    models = [
+        *llama3_instruct_models(),
+        *llama3_1_instruct_models(),
+        *llama3_2_instruct_models(),
+        *llama3_3_instruct_models(),
+        *safety_models(),
+    ]
+    return {model.huggingface_repo: model for model in models if not model.variant}
+
+
+SUPPORTED_MODELS = {
+    "ollama": set(
+        [
+            CoreModelId.llama3_1_8b_instruct.value,
+            CoreModelId.llama3_1_8b_instruct.value,
+            CoreModelId.llama3_1_70b_instruct.value,
+            CoreModelId.llama3_1_70b_instruct.value,
+            CoreModelId.llama3_1_405b_instruct.value,
+            CoreModelId.llama3_1_405b_instruct.value,
+            CoreModelId.llama3_2_1b_instruct.value,
+            CoreModelId.llama3_2_1b_instruct.value,
+            CoreModelId.llama3_2_3b_instruct.value,
+            CoreModelId.llama3_2_3b_instruct.value,
+            CoreModelId.llama3_2_11b_vision_instruct.value,
+            CoreModelId.llama3_2_11b_vision_instruct.value,
+            CoreModelId.llama3_2_90b_vision_instruct.value,
+            CoreModelId.llama3_2_90b_vision_instruct.value,
+            CoreModelId.llama3_3_70b_instruct.value,
+            CoreModelId.llama_guard_3_8b.value,
+            CoreModelId.llama_guard_3_1b.value,
+        ]
+    ),
+    "tgi": set(
+        [
+            model.core_model_id.value
+            for model in all_registered_models()
+            if model.huggingface_repo
+        ]
+    ),
+    "vllm": set(
+        [
+            model.core_model_id.value
+            for model in all_registered_models()
+            if model.huggingface_repo
+        ]
+    ),
+}
+
+
+class Report:
+
+    def __init__(self, report_path: Optional[str] = None):
+        if os.environ.get("LLAMA_STACK_CONFIG"):
+            config_path_or_template_name = get_env_or_fail("LLAMA_STACK_CONFIG")
+            if config_path_or_template_name.endswith(".yaml"):
+                config_path = Path(config_path_or_template_name)
+            else:
+                config_path = Path(
+                    importlib.resources.files("llama_stack")
+                    / f"templates/{config_path_or_template_name}/run.yaml"
+                )
+            if not config_path.exists():
+                raise ValueError(f"Config file {config_path} does not exist")
+            self.output_path = Path(config_path.parent / "report.md")
+            self.distro_name = None
+        elif os.environ.get("LLAMA_STACK_BASE_URL"):
+            url = get_env_or_fail("LLAMA_STACK_BASE_URL")
+            self.distro_name = urlparse(url).netloc
+            if report_path is None:
+                raise ValueError(
+                    "Report path must be provided when LLAMA_STACK_BASE_URL is set"
+                )
+            self.output_path = Path(report_path)
+        else:
+            raise ValueError("LLAMA_STACK_CONFIG or LLAMA_STACK_BASE_URL must be set")
+
+        self.report_data = defaultdict(dict)
+        # test function -> test nodeid
+        self.test_data = dict()
+        self.test_name_to_nodeid = defaultdict(list)
+        self.vision_model_id = None
+        self.text_model_id = None
+        self.client = None
+
+    @pytest.hookimpl(tryfirst=True)
+    def pytest_runtest_logreport(self, report):
+        # This hook is called in several phases, including setup, call and teardown
+        # The test is considered failed / error if any of the outcomes is not "Passed"
+        outcome = self._process_outcome(report)
+        if report.nodeid not in self.test_data:
+            self.test_data[report.nodeid] = outcome
+        elif self.test_data[report.nodeid] != outcome and outcome != "Passed":
+            self.test_data[report.nodeid] = outcome
+
+    def pytest_sessionfinish(self, session):
+        report = []
+        report.append(f"# Report for {self.distro_name} distribution")
+        report.append("\n## Supported Models")
+
+        header = f"| Model Descriptor | {self.distro_name} |"
+        dividor = "|:---|:---|"
+
+        report.append(header)
+        report.append(dividor)
+
+        rows = []
+        if self.distro_name in SUPPORTED_MODELS:
+            for model in all_registered_models():
+                if (
+                    "Instruct" not in model.core_model_id.value
+                    and "Guard" not in model.core_model_id.value
+                ) or (model.variant):
+                    continue
+                row = f"| {model.core_model_id.value} |"
+                if model.core_model_id.value in SUPPORTED_MODELS[self.distro_name]:
+                    row += " ✅ |"
+                else:
+                    row += " ❌ |"
+                rows.append(row)
+        else:
+            supported_models = {m.identifier for m in self.client.models.list()}
+            for hf_name, model in featured_models().items():
+                row = f"| {model.core_model_id.value} |"
+                if hf_name in supported_models:
+                    row += " ✅ |"
+                else:
+                    row += " ❌ |"
+                rows.append(row)
+        report.extend(rows)
+
+        report.append("\n## Inference")
+        test_table = [
+            "| Model | API | Capability | Test | Status |",
+            "|:----- |:-----|:-----|:-----|:-----|",
+        ]
+        for api, capa_map in API_MAPS[Api.inference].items():
+            for capa, tests in capa_map.items():
+                for test_name in tests:
+                    model_id = (
+                        self.text_model_id
+                        if "text" in test_name
+                        else self.vision_model_id
+                    )
+                    test_nodeids = self.test_name_to_nodeid[test_name]
+                    assert len(test_nodeids) > 0
+
+                    # There might be more than one parametrizations for the same test function. We take
+                    # the result of the first one for now. Ideally we should mark the test as failed if
+                    # any of the parametrizations failed.
+                    test_table.append(
+                        f"| {model_id} | /{api} | {capa} | {test_name} | {self._print_result_icon(self.test_data[test_nodeids[0]])} |"
+                    )
+
+        report.extend(test_table)
+
+        name_map = {Api.vector_io: "Vector IO", Api.agents: "Agents"}
+        providers = self.client.providers.list()
+        for api_group in [Api.vector_io, Api.agents]:
+            api_capitalized = name_map[api_group]
+            report.append(f"\n## {api_capitalized}")
+            test_table = [
+                "| Provider | API | Capability | Test | Status |",
+                "|:-----|:-----|:-----|:-----|:-----|",
+            ]
+            provider = [p for p in providers if p.api == str(api_group.name)]
+            provider_str = provider[0].provider_type if provider else ""
+            for api, capa_map in API_MAPS[api_group].items():
+                for capa, tests in capa_map.items():
+                    for test_name in tests:
+                        test_nodeids = self.test_name_to_nodeid[test_name]
+                        assert len(test_nodeids) > 0
+                        test_table.append(
+                            f"| {provider_str} | /{api} | {capa} | {test_name} | {self._print_result_icon(self.test_data[test_nodeids[0]])} |"
+                        )
+            report.extend(test_table)
+
+        output_file = self.output_path
+        text = "\n".join(report) + "\n"
+        output_file.write_text(text)
+        cprint(f"\nReport generated: {output_file.absolute()}", "green")
+
+    def pytest_runtest_makereport(self, item, call):
+        func_name = getattr(item, "originalname", item.name)
+        self.test_name_to_nodeid[func_name].append(item.nodeid)
+
+        # Get values from fixtures for report output
+        if "text_model_id" in item.funcargs:
+            text_model = item.funcargs["text_model_id"].split("/")[1]
+            self.text_model_id = self.text_model_id or text_model
+        elif "vision_model_id" in item.funcargs:
+            vision_model = item.funcargs["vision_model_id"].split("/")[1]
+            self.vision_model_id = self.vision_model_id or vision_model
+
+        if self.client is None and "llama_stack_client" in item.funcargs:
+            self.client = item.funcargs["llama_stack_client"]
+            self.distro_name = (
+                self.distro_name or self.client.async_client.config.image_name
+            )
+
+    def _print_result_icon(self, result):
+        if result == "Passed":
+            return "✅"
+        elif result == "Failed" or result == "Error":
+            return "❌"
+        else:
+            #  result == "Skipped":
+            return "⏭️"
+
+    def _process_outcome(self, report: CollectReport):
+        if self._is_error(report):
+            return "Error"
+        if hasattr(report, "wasxfail"):
+            if report.outcome in ["passed", "failed"]:
+                return "XPassed"
+            if report.outcome == "skipped":
+                return "XFailed"
+        return report.outcome.capitalize()
+
+    def _is_error(self, report: CollectReport):
+        return (
+            report.when in ["setup", "teardown", "collect"]
+            and report.outcome == "failed"
+        )
diff --git a/tests/client-sdk/safety/conftest.py b/tests/client-sdk/safety/conftest.py
new file mode 100644
index 000000000..c4570801c
--- /dev/null
+++ b/tests/client-sdk/safety/conftest.py
@@ -0,0 +1,22 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+
+def pytest_addoption(parser):
+    parser.addoption(
+        "--safety-shield",
+        action="store",
+        default="meta-llama/Llama-Guard-3-1B",
+        help="Specify the safety shield model to use for testing",
+    )
+
+
+def pytest_generate_tests(metafunc):
+    if "llama_guard_text_shield_id" in metafunc.fixturenames:
+        metafunc.parametrize(
+            "llama_guard_text_shield_id",
+            [metafunc.config.getoption("--safety-shield")],
+        )
diff --git a/tests/client-sdk/safety/test_safety.py b/tests/client-sdk/safety/test_safety.py
index 6af417a09..7456fb88f 100644
--- a/tests/client-sdk/safety/test_safety.py
+++ b/tests/client-sdk/safety/test_safety.py
@@ -32,16 +32,6 @@ def available_shields(llama_stack_client):
     return [shield.identifier for shield in llama_stack_client.shields.list()]
 
 
-@pytest.fixture(scope="session")
-def llama_guard_text_shield_id(available_shields):
-    if "meta-llama/Llama-Guard-3-1B" in available_shields:
-        return "meta-llama/Llama-Guard-3-1B"
-    elif "meta-llama/Llama-Guard-3-8B" in available_shields:
-        return "meta-llama/Llama-Guard-3-8B"
-    else:
-        pytest.skip("Llama-Guard shield is not available. Skipping.")
-
-
 @pytest.fixture(scope="session")
 def code_scanner_shield_id(available_shields):
     if "CodeScanner" in available_shields:
@@ -141,7 +131,7 @@ def test_safety_with_image(llama_stack_client, model_providers):
                 },
                 {
                     "type": "image",
-                    "url": {"uri": data_url_from_image(file_path)},
+                    "image": {"url": {"uri": data_url_from_image(file_path)}},
                 },
             ],
         }
diff --git a/tests/client-sdk/tool_runtime/test_rag_tool.py b/tests/client-sdk/tool_runtime/test_rag_tool.py
new file mode 100644
index 000000000..6e158a1e3
--- /dev/null
+++ b/tests/client-sdk/tool_runtime/test_rag_tool.py
@@ -0,0 +1,180 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+import random
+
+import pytest
+
+from llama_stack_client.types import Document
+
+
+@pytest.fixture(scope="function")
+def empty_vector_db_registry(llama_stack_client):
+    vector_dbs = [
+        vector_db.identifier for vector_db in llama_stack_client.vector_dbs.list()
+    ]
+    for vector_db_id in vector_dbs:
+        llama_stack_client.vector_dbs.unregister(vector_db_id=vector_db_id)
+
+
+@pytest.fixture(scope="function")
+def single_entry_vector_db_registry(llama_stack_client, empty_vector_db_registry):
+    vector_db_id = f"test_vector_db_{random.randint(1000, 9999)}"
+    llama_stack_client.vector_dbs.register(
+        vector_db_id=vector_db_id,
+        embedding_model="all-MiniLM-L6-v2",
+        embedding_dimension=384,
+        provider_id="faiss",
+    )
+    vector_dbs = [
+        vector_db.identifier for vector_db in llama_stack_client.vector_dbs.list()
+    ]
+    return vector_dbs
+
+
+@pytest.fixture(scope="session")
+def sample_documents():
+    return [
+        Document(
+            document_id="test-doc-1",
+            content="Python is a high-level programming language.",
+            metadata={"category": "programming", "difficulty": "beginner"},
+        ),
+        Document(
+            document_id="test-doc-2",
+            content="Machine learning is a subset of artificial intelligence.",
+            metadata={"category": "AI", "difficulty": "advanced"},
+        ),
+        Document(
+            document_id="test-doc-3",
+            content="Data structures are fundamental to computer science.",
+            metadata={"category": "computer science", "difficulty": "intermediate"},
+        ),
+        Document(
+            document_id="test-doc-4",
+            content="Neural networks are inspired by biological neural networks.",
+            metadata={"category": "AI", "difficulty": "advanced"},
+        ),
+    ]
+
+
+def assert_valid_response(response):
+    assert len(response.chunks) > 0
+    assert len(response.scores) > 0
+    assert len(response.chunks) == len(response.scores)
+    for chunk in response.chunks:
+        assert isinstance(chunk.content, str)
+
+
+def test_vector_db_insert_inline_and_query(
+    llama_stack_client, single_entry_vector_db_registry, sample_documents
+):
+    vector_db_id = single_entry_vector_db_registry[0]
+    llama_stack_client.tool_runtime.rag_tool.insert(
+        documents=sample_documents,
+        chunk_size_in_tokens=512,
+        vector_db_id=vector_db_id,
+    )
+
+    # Query with a direct match
+    query1 = "programming language"
+    response1 = llama_stack_client.vector_io.query(
+        vector_db_id=vector_db_id,
+        query=query1,
+    )
+    assert_valid_response(response1)
+    assert any("Python" in chunk.content for chunk in response1.chunks)
+
+    # Query with semantic similarity
+    query2 = "AI and brain-inspired computing"
+    response2 = llama_stack_client.vector_io.query(
+        vector_db_id=vector_db_id,
+        query=query2,
+    )
+    assert_valid_response(response2)
+    assert any("neural networks" in chunk.content.lower() for chunk in response2.chunks)
+
+    # Query with limit on number of results (max_chunks=2)
+    query3 = "computer"
+    response3 = llama_stack_client.vector_io.query(
+        vector_db_id=vector_db_id,
+        query=query3,
+        params={"max_chunks": 2},
+    )
+    assert_valid_response(response3)
+    assert len(response3.chunks) <= 2
+
+    # Query with threshold on similarity score
+    query4 = "computer"
+    response4 = llama_stack_client.vector_io.query(
+        vector_db_id=vector_db_id,
+        query=query4,
+        params={"score_threshold": 0.01},
+    )
+    assert_valid_response(response4)
+    assert all(score >= 0.01 for score in response4.scores)
+
+
+def test_vector_db_insert_from_url_and_query(
+    llama_stack_client, empty_vector_db_registry
+):
+    providers = [p for p in llama_stack_client.providers.list() if p.api == "vector_io"]
+    assert len(providers) > 0
+
+    vector_db_id = "test_vector_db"
+
+    llama_stack_client.vector_dbs.register(
+        vector_db_id=vector_db_id,
+        embedding_model="all-MiniLM-L6-v2",
+        embedding_dimension=384,
+        provider_id="faiss",
+    )
+
+    # list to check memory bank is successfully registered
+    available_vector_dbs = [
+        vector_db.identifier for vector_db in llama_stack_client.vector_dbs.list()
+    ]
+    assert vector_db_id in available_vector_dbs
+
+    # URLs of documents to insert
+    # TODO: Move to test/memory/resources then update the url to
+    # https://raw.githubusercontent.com/meta-llama/llama-stack/main/tests/memory/resources/{url}
+    urls = [
+        "memory_optimizations.rst",
+        "chat.rst",
+        "llama3.rst",
+    ]
+    documents = [
+        Document(
+            document_id=f"num-{i}",
+            content=f"https://raw.githubusercontent.com/pytorch/torchtune/main/docs/source/tutorials/{url}",
+            mime_type="text/plain",
+            metadata={},
+        )
+        for i, url in enumerate(urls)
+    ]
+
+    llama_stack_client.tool_runtime.rag_tool.insert(
+        documents=documents,
+        vector_db_id=vector_db_id,
+        chunk_size_in_tokens=512,
+    )
+
+    # Query for the name of method
+    response1 = llama_stack_client.vector_io.query(
+        vector_db_id=vector_db_id,
+        query="What's the name of the fine-tunning method used?",
+    )
+    assert_valid_response(response1)
+    assert any("lora" in chunk.content.lower() for chunk in response1.chunks)
+
+    # Query for the name of model
+    response2 = llama_stack_client.vector_io.query(
+        vector_db_id=vector_db_id,
+        query="Which Llama model is mentioned?",
+    )
+    assert_valid_response(response2)
+    assert any("llama2" in chunk.content.lower() for chunk in response2.chunks)
diff --git a/tests/client-sdk/memory/__init__.py b/tests/client-sdk/vector_io/__init__.py
similarity index 100%
rename from tests/client-sdk/memory/__init__.py
rename to tests/client-sdk/vector_io/__init__.py
diff --git a/tests/client-sdk/vector_io/conftest.py b/tests/client-sdk/vector_io/conftest.py
new file mode 100644
index 000000000..64cac27d2
--- /dev/null
+++ b/tests/client-sdk/vector_io/conftest.py
@@ -0,0 +1,22 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+
+def pytest_addoption(parser):
+    parser.addoption(
+        "--embedding-model",
+        action="store",
+        default="all-MiniLM-L6-v2",
+        help="Specify the embedding model to use for testing",
+    )
+
+
+def pytest_generate_tests(metafunc):
+    if "embedding_model" in metafunc.fixturenames:
+        metafunc.parametrize(
+            "embedding_model",
+            [metafunc.config.getoption("--embedding-model")],
+        )
diff --git a/tests/client-sdk/vector_io/test_vector_io.py b/tests/client-sdk/vector_io/test_vector_io.py
new file mode 100644
index 000000000..2a110b73a
--- /dev/null
+++ b/tests/client-sdk/vector_io/test_vector_io.py
@@ -0,0 +1,93 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+import random
+
+import pytest
+
+
+@pytest.fixture(scope="function")
+def empty_vector_db_registry(llama_stack_client):
+    vector_dbs = [
+        vector_db.identifier for vector_db in llama_stack_client.vector_dbs.list()
+    ]
+    for vector_db_id in vector_dbs:
+        llama_stack_client.vector_dbs.unregister(vector_db_id=vector_db_id)
+
+
+@pytest.fixture(scope="function")
+def single_entry_vector_db_registry(llama_stack_client, empty_vector_db_registry):
+    vector_db_id = f"test_vector_db_{random.randint(1000, 9999)}"
+    llama_stack_client.vector_dbs.register(
+        vector_db_id=vector_db_id,
+        embedding_model="all-MiniLM-L6-v2",
+        embedding_dimension=384,
+        provider_id="faiss",
+    )
+    vector_dbs = [
+        vector_db.identifier for vector_db in llama_stack_client.vector_dbs.list()
+    ]
+    return vector_dbs
+
+
+def test_vector_db_retrieve(
+    llama_stack_client, embedding_model, empty_vector_db_registry
+):
+    # Register a memory bank first
+    vector_db_id = f"test_vector_db_{random.randint(1000, 9999)}"
+    llama_stack_client.vector_dbs.register(
+        vector_db_id=vector_db_id,
+        embedding_model=embedding_model,
+        embedding_dimension=384,
+        provider_id="faiss",
+    )
+
+    # Retrieve the memory bank and validate its properties
+    response = llama_stack_client.vector_dbs.retrieve(vector_db_id=vector_db_id)
+    assert response is not None
+    assert response.identifier == vector_db_id
+    assert response.embedding_model == embedding_model
+    assert response.provider_id == "faiss"
+    assert response.provider_resource_id == vector_db_id
+
+
+def test_vector_db_list(llama_stack_client, empty_vector_db_registry):
+    vector_dbs_after_register = [
+        vector_db.identifier for vector_db in llama_stack_client.vector_dbs.list()
+    ]
+    assert len(vector_dbs_after_register) == 0
+
+
+def test_vector_db_register(
+    llama_stack_client, embedding_model, empty_vector_db_registry
+):
+    vector_db_id = f"test_vector_db_{random.randint(1000, 9999)}"
+    llama_stack_client.vector_dbs.register(
+        vector_db_id=vector_db_id,
+        embedding_model=embedding_model,
+        embedding_dimension=384,
+        provider_id="faiss",
+    )
+
+    vector_dbs_after_register = [
+        vector_db.identifier for vector_db in llama_stack_client.vector_dbs.list()
+    ]
+    assert vector_dbs_after_register == [vector_db_id]
+
+
+def test_vector_db_unregister(llama_stack_client, single_entry_vector_db_registry):
+    vector_dbs = [
+        vector_db.identifier for vector_db in llama_stack_client.vector_dbs.list()
+    ]
+    assert len(vector_dbs) == 1
+
+    vector_db_id = vector_dbs[0]
+    llama_stack_client.vector_dbs.unregister(vector_db_id=vector_db_id)
+
+    vector_dbs = [
+        vector_db.identifier for vector_db in llama_stack_client.vector_dbs.list()
+    ]
+    assert len(vector_dbs) == 0