Merge remote-tracking branch 'origin/main' into stores

.dockerignore

@@ -0,0 +1,19 @@
+.venv
+__pycache__
+*.pyc
+*.pyo
+*.pyd
+*.so
+.git
+.gitignore
+htmlcov*
+.coverage
+coverage*
+.cache
+.mypy_cache
+.pytest_cache
+.ruff_cache
+uv.lock
+node_modules
+build
+/tmp

.github/actions/setup-test-environment/action.yml

@@ -57,7 +57,7 @@ runs:
         echo "Building Llama Stack"
 
         LLAMA_STACK_DIR=. \
-          uv run --no-sync llama stack build --template ci-tests --image-type venv
+          uv run --no-sync llama stack list-deps ci-tests | xargs -L1 uv pip install
 
     - name: Configure git for commits
       shell: bash

.github/workflows/README.md

@@ -14,6 +14,7 @@ Llama Stack uses GitHub Actions for Continuous Integration (CI). Below is a tabl
 | Pre-commit | [pre-commit.yml](pre-commit.yml) | Run pre-commit checks |
 | Pre-commit Bot | [precommit-trigger.yml](precommit-trigger.yml) | Pre-commit bot for PR |
 | Test Llama Stack Build | [providers-build.yml](providers-build.yml) | Test llama stack build |
+| Test llama stack list-deps | [providers-list-deps.yml](providers-list-deps.yml) | Test llama stack list-deps |
 | Python Package Build Test | [python-build-test.yml](python-build-test.yml) | Test building the llama-stack PyPI project |
 | Integration Tests (Record) | [record-integration-tests.yml](record-integration-tests.yml) | Run the integration test suite from tests/integration |
 | Check semantic PR titles | [semantic-pr.yml](semantic-pr.yml) | Ensure that PR titles follow the conventional commit spec |

.github/workflows/install-script-ci.yml

@@ -30,8 +30,11 @@ jobs:
 
       - name: Build a single provider
         run: |
-          USE_COPY_NOT_MOUNT=true LLAMA_STACK_DIR=. uv run --no-sync \
-            llama stack build --template starter --image-type container --image-name test
+          docker build . \
+            -f containers/Containerfile \
+            --build-arg INSTALL_MODE=editable \
+            --build-arg DISTRO_NAME=starter \
+            --tag llama-stack:starter-ci
 
       - name: Run installer end-to-end
         run: |

.github/workflows/integration-tests.yml

@@ -47,7 +47,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        client-type: [library, server]
+        client-type: [library, server, docker]
         # Use Python 3.13 only on nightly schedule (daily latest client test), otherwise use 3.12
         python-version: ${{ github.event.schedule == '0 0 * * *' && fromJSON('["3.12", "3.13"]') || fromJSON('["3.12"]') }}
         client-version: ${{ (github.event.schedule == '0 0 * * *' || github.event.inputs.test-all-client-versions == 'true') && fromJSON('["published", "latest"]') || fromJSON('["latest"]') }}
@@ -82,7 +82,7 @@ jobs:
         env:
           OPENAI_API_KEY: dummy
         with:
-          stack-config: ${{ matrix.client-type == 'library' && 'ci-tests' || 'server:ci-tests' }}
+          stack-config: ${{ matrix.client-type == 'library' && 'ci-tests' || matrix.client-type == 'server' && 'server:ci-tests' || 'docker:ci-tests' }}
           setup: ${{ matrix.config.setup }}
           inference-mode: 'replay'
           suite: ${{ matrix.config.suite }}

.github/workflows/integration-vector-io-tests.yml

@@ -144,7 +144,7 @@ jobs:
 
       - name: Build Llama Stack
         run: |
-          uv run --no-sync llama stack build --template ci-tests --image-type venv
+          uv run --no-sync llama stack list-deps ci-tests | xargs -L1 uv pip install
 
       - name: Check Storage and Memory Available Before Tests
         if: ${{ always() }}

.github/workflows/providers-build.yml

@@ -14,6 +14,8 @@ on:
       - '.github/workflows/providers-build.yml'
       - 'llama_stack/distributions/**'
       - 'pyproject.toml'
+      - 'containers/Containerfile'
+      - '.dockerignore'
 
   pull_request:
     paths:
@@ -24,6 +26,8 @@ on:
       - '.github/workflows/providers-build.yml'
       - 'llama_stack/distributions/**'
       - 'pyproject.toml'
+      - 'containers/Containerfile'
+      - '.dockerignore'
 
 concurrency:
   group: ${{ github.workflow }}-${{ github.ref == 'refs/heads/main' && github.run_id || github.ref }}
@@ -60,15 +64,19 @@ jobs:
       - name: Install dependencies
         uses: ./.github/actions/setup-runner
 
-      - name: Print build dependencies
+      - name: Install distribution into venv
+        if: matrix.image-type == 'venv'
         run: |
-          uv run llama stack build --distro ${{ matrix.distro }} --image-type ${{ matrix.image-type }} --image-name test --print-deps-only
+          uv run llama stack list-deps ${{ matrix.distro }} | xargs -L1 uv pip install
 
-      - name: Run Llama Stack Build
+      - name: Build container image
+        if: matrix.image-type == 'container'
         run: |
-          # USE_COPY_NOT_MOUNT is set to true since mounting is not supported by docker buildx, we use COPY instead
-          # LLAMA_STACK_DIR is set to the current directory so we are building from the source
-          USE_COPY_NOT_MOUNT=true LLAMA_STACK_DIR=. uv run llama stack build --distro ${{ matrix.distro }} --image-type ${{ matrix.image-type }} --image-name test
+          docker build . \
+            -f containers/Containerfile \
+            --build-arg INSTALL_MODE=editable \
+            --build-arg DISTRO_NAME=${{ matrix.distro }} \
+            --tag llama-stack:${{ matrix.distro }}-ci
 
       - name: Print dependencies in the image
         if: matrix.image-type == 'venv'
@@ -86,8 +94,8 @@ jobs:
 
       - name: Build a single provider
         run: |
-          USE_COPY_NOT_MOUNT=true LLAMA_STACK_DIR=. uv run llama stack build --image-type venv --image-name test --providers inference=remote::ollama
-
+          uv pip install -e .
+          uv run --no-sync llama stack list-deps --providers inference=remote::ollama | xargs -L1 uv pip install
   build-custom-container-distribution:
     runs-on: ubuntu-latest
     steps:
@@ -97,11 +105,16 @@ jobs:
       - name: Install dependencies
         uses: ./.github/actions/setup-runner
 
-      - name: Build a single provider
+      - name: Build container image
         run: |
-          yq -i '.image_type = "container"' llama_stack/distributions/ci-tests/build.yaml
-          yq -i '.image_name = "test"' llama_stack/distributions/ci-tests/build.yaml
-          USE_COPY_NOT_MOUNT=true LLAMA_STACK_DIR=. uv run llama stack build --config llama_stack/distributions/ci-tests/build.yaml
+          BASE_IMAGE=$(yq -r '.distribution_spec.container_image // "python:3.12-slim"' llama_stack/distributions/ci-tests/build.yaml)
+          docker build . \
+            -f containers/Containerfile \
+            --build-arg INSTALL_MODE=editable \
+            --build-arg DISTRO_NAME=ci-tests \
+            --build-arg BASE_IMAGE="$BASE_IMAGE" \
+            --build-arg RUN_CONFIG_PATH=/workspace/llama_stack/distributions/ci-tests/run.yaml \
+            -t llama-stack:ci-tests
 
       - name: Inspect the container image entrypoint
         run: |
@@ -112,7 +125,7 @@ jobs:
           fi
           entrypoint=$(docker inspect --format '{{ .Config.Entrypoint }}' $IMAGE_ID)
           echo "Entrypoint: $entrypoint"
-          if [ "$entrypoint" != "[llama stack run /app/run.yaml]" ]; then
+          if [ "$entrypoint" != "[/usr/local/bin/llama-stack-entrypoint.sh]" ]; then
             echo "Entrypoint is not correct"
             exit 1
           fi
@@ -129,17 +142,19 @@ jobs:
       - name: Pin distribution to UBI9 base
         run: |
           yq -i '
-            .image_type    = "container" |
-            .image_name    = "ubi9-test" |
             .distribution_spec.container_image = "registry.access.redhat.com/ubi9:latest"
           ' llama_stack/distributions/ci-tests/build.yaml
 
-      - name: Build dev container (UBI9)
-        env:
-          USE_COPY_NOT_MOUNT: "true"
-          LLAMA_STACK_DIR: "."
+      - name: Build UBI9 container image
         run: |
-          uv run llama stack build --config llama_stack/distributions/ci-tests/build.yaml
+          BASE_IMAGE=$(yq -r '.distribution_spec.container_image // "registry.access.redhat.com/ubi9:latest"' llama_stack/distributions/ci-tests/build.yaml)
+          docker build . \
+            -f containers/Containerfile \
+            --build-arg INSTALL_MODE=editable \
+            --build-arg DISTRO_NAME=ci-tests \
+            --build-arg BASE_IMAGE="$BASE_IMAGE" \
+            --build-arg RUN_CONFIG_PATH=/workspace/llama_stack/distributions/ci-tests/run.yaml \
+            -t llama-stack:ci-tests-ubi9
 
       - name: Inspect UBI9 image
         run: |
@@ -150,7 +165,7 @@ jobs:
           fi
           entrypoint=$(docker inspect --format '{{ .Config.Entrypoint }}' $IMAGE_ID)
           echo "Entrypoint: $entrypoint"
-          if [ "$entrypoint" != "[llama stack run /app/run.yaml]" ]; then
+          if [ "$entrypoint" != "[/usr/local/bin/llama-stack-entrypoint.sh]" ]; then
             echo "Entrypoint is not correct"
             exit 1
           fi

.github/workflows/providers-list-deps.yml

@@ -0,0 +1,105 @@
+name: Test llama stack list-deps
+
+run-name: Test llama stack list-deps
+
+on:
+  push:
+    branches:
+      - main
+    paths:
+      - 'llama_stack/cli/stack/list_deps.py'
+      - 'llama_stack/cli/stack/_list_deps.py'
+      - 'llama_stack/core/build.*'
+      - 'llama_stack/core/*.sh'
+      - '.github/workflows/providers-list-deps.yml'
+      - 'llama_stack/templates/**'
+      - 'pyproject.toml'
+
+  pull_request:
+    paths:
+      - 'llama_stack/cli/stack/list_deps.py'
+      - 'llama_stack/cli/stack/_list_deps.py'
+      - 'llama_stack/core/build.*'
+      - 'llama_stack/core/*.sh'
+      - '.github/workflows/providers-list-deps.yml'
+      - 'llama_stack/templates/**'
+      - 'pyproject.toml'
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  generate-matrix:
+    runs-on: ubuntu-latest
+    outputs:
+      distros: ${{ steps.set-matrix.outputs.distros }}
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+
+      - name: Generate Distribution List
+        id: set-matrix
+        run: |
+          distros=$(ls llama_stack/distributions/*/*build.yaml | awk -F'/' '{print $(NF-1)}' | jq -R -s -c 'split("\n")[:-1]')
+          echo "distros=$distros" >> "$GITHUB_OUTPUT"
+
+  list-deps:
+    needs: generate-matrix
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        distro: ${{ fromJson(needs.generate-matrix.outputs.distros) }}
+        image-type: [venv, container]
+      fail-fast: false # We want to run all jobs even if some fail
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+
+      - name: Install dependencies
+        uses: ./.github/actions/setup-runner
+
+      - name: Print dependencies
+        run: |
+          uv run llama stack list-deps ${{ matrix.distro }}
+
+      - name: Install Distro using llama stack list-deps
+        run: |
+          # USE_COPY_NOT_MOUNT is set to true since mounting is not supported by docker buildx, we use COPY instead
+          # LLAMA_STACK_DIR is set to the current directory so we are building from the source
+          USE_COPY_NOT_MOUNT=true LLAMA_STACK_DIR=. uv run llama stack list-deps ${{ matrix.distro }} | xargs -L1 uv pip install
+
+      - name: Print dependencies in the image
+        if: matrix.image-type == 'venv'
+        run: |
+          uv pip list
+
+  show-single-provider:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+
+      - name: Install dependencies
+        uses: ./.github/actions/setup-runner
+
+      - name: Show a single provider
+        run: |
+          USE_COPY_NOT_MOUNT=true LLAMA_STACK_DIR=. uv run llama stack list-deps --providers inference=remote::ollama
+
+  list-deps-from-config:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
+
+      - name: Install dependencies
+        uses: ./.github/actions/setup-runner
+
+      - name: list-des from Config
+        env:
+          USE_COPY_NOT_MOUNT: "true"
+          LLAMA_STACK_DIR: "."
+        run: |
+          uv run llama stack list-deps llama_stack/distributions/ci-tests/build.yaml

.github/workflows/test-external-provider-module.yml

@@ -46,9 +46,9 @@ jobs:
           yq -i '.image_type = "${{ matrix.image-type }}"' tests/external/ramalama-stack/run.yaml
           cat tests/external/ramalama-stack/run.yaml
 
-      - name: Build distro from config file
+      - name: Install distribution dependencies
         run: |
-          USE_COPY_NOT_MOUNT=true LLAMA_STACK_DIR=. uv run llama stack build --config tests/external/ramalama-stack/build.yaml
+          uv run llama stack list-deps tests/external/ramalama-stack/build.yaml | xargs -L1 uv pip install
 
       - name: Start Llama Stack server in background
         if: ${{ matrix.image-type }} == 'venv'

.github/workflows/test-external.yml

@@ -44,11 +44,14 @@ jobs:
 
       - name: Print distro dependencies
         run: |
-          USE_COPY_NOT_MOUNT=true LLAMA_STACK_DIR=. uv run --no-sync llama stack build --config tests/external/build.yaml --print-deps-only
+          uv run --no-sync llama stack list-deps tests/external/build.yaml
 
       - name: Build distro from config file
         run: |
-          USE_COPY_NOT_MOUNT=true LLAMA_STACK_DIR=. uv run --no-sync llama stack build --config tests/external/build.yaml
+          uv venv ci-test
+          source ci-test/bin/activate
+          uv pip install -e .
+          LLAMA_STACK_LOGGING=all=CRITICAL llama stack list-deps tests/external/build.yaml | xargs -L1 uv pip install
 
       - name: Start Llama Stack server in background
         if: ${{ matrix.image-type }} == 'venv'

CONTRIBUTING.md

@@ -167,9 +167,9 @@ under the LICENSE file in the root directory of this source tree.
 
 Some tips about common tasks you work on while contributing to Llama Stack:
 
-### Using `llama stack build`
+### Installing dependencies of distributions
 
-Building a stack image will use the production version of the `llama-stack` 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_STACK_CLIENT_DIR` to the appropriate checked out directories when running any of the `llama` CLI commands.
+When installing dependencies for a distribution, you can use `llama stack list-deps` to view and install the required packages.
 
 Example:
 ```bash
@@ -177,7 +177,12 @@ cd work/
 git clone https://github.com/llamastack/llama-stack.git
 git clone https://github.com/llamastack/llama-stack-client-python.git
 cd llama-stack
-LLAMA_STACK_DIR=$(pwd) LLAMA_STACK_CLIENT_DIR=../llama-stack-client-python llama stack build --distro <...>
+
+# Show dependencies for a distribution
+llama stack list-deps <distro-name>
+
+# Install dependencies
+llama stack list-deps <distro-name> | xargs -L1 uv pip install
 ```
 
 ### Updating distribution configurations

README.md

@@ -27,8 +27,11 @@ MODEL="Llama-4-Scout-17B-16E-Instruct"
 # get meta url from llama.com
 huggingface-cli download meta-llama/$MODEL --local-dir ~/.llama/$MODEL
 
+# install dependencies for the distribution
+llama stack list-deps meta-reference-gpu | xargs -L1 uv pip install
+
 # start a llama stack server
-INFERENCE_MODEL=meta-llama/$MODEL llama stack build --run --template meta-reference-gpu
+INFERENCE_MODEL=meta-llama/$MODEL llama stack run meta-reference-gpu
 
 # install client to interact with the server
 pip install llama-stack-client
@@ -89,7 +92,7 @@ As more providers start supporting Llama 4, you can use them in Llama Stack as w
 To try Llama Stack locally, run:
 
 ```bash
-curl -LsSf https://github.com/meta-llama/llama-stack/raw/main/scripts/install.sh | bash
+curl -LsSf https://github.com/llamastack/llama-stack/raw/main/scripts/install.sh | bash
 ```
 
 ### Overview

containers/Containerfile

@@ -0,0 +1,136 @@
+# syntax=docker/dockerfile:1.6
+#
+# This Dockerfile is used to build the Llama Stack container image.
+# Example:
+# docker build \
+#   -f containers/Containerfile \
+#   --build-arg DISTRO_NAME=starter \
+#   --tag llama-stack:starter .
+
+ARG BASE_IMAGE=python:3.12-slim
+FROM ${BASE_IMAGE}
+
+ARG INSTALL_MODE="pypi"
+ARG LLAMA_STACK_DIR="/workspace"
+ARG LLAMA_STACK_CLIENT_DIR=""
+ARG PYPI_VERSION=""
+ARG TEST_PYPI_VERSION=""
+ARG KEEP_WORKSPACE=""
+ARG DISTRO_NAME="starter"
+ARG RUN_CONFIG_PATH=""
+ARG UV_HTTP_TIMEOUT=500
+ENV UV_HTTP_TIMEOUT=${UV_HTTP_TIMEOUT}
+ENV PYTHONDONTWRITEBYTECODE=1
+ENV PIP_DISABLE_PIP_VERSION_CHECK=1
+WORKDIR /app
+
+RUN set -eux; \
+    if command -v dnf >/dev/null 2>&1; then \
+        dnf -y update && \
+        dnf install -y iputils git net-tools wget \
+            vim-minimal python3.12 python3.12-pip python3.12-wheel \
+            python3.12-setuptools python3.12-devel gcc gcc-c++ make && \
+        ln -sf /usr/bin/pip3.12 /usr/local/bin/pip && \
+        ln -sf /usr/bin/python3.12 /usr/local/bin/python && \
+        dnf clean all; \
+    elif command -v apt-get >/dev/null 2>&1; then \
+        apt-get update && \
+        apt-get install -y --no-install-recommends \
+            iputils-ping net-tools iproute2 dnsutils telnet \
+            curl wget git procps psmisc lsof traceroute bubblewrap \
+            gcc g++ && \
+        rm -rf /var/lib/apt/lists/*; \
+    else \
+        echo "Unsupported base image: expected dnf or apt-get" >&2; \
+        exit 1; \
+    fi
+
+RUN pip install --no-cache-dir uv
+ENV UV_SYSTEM_PYTHON=1
+
+ENV INSTALL_MODE=${INSTALL_MODE}
+ENV LLAMA_STACK_DIR=${LLAMA_STACK_DIR}
+ENV LLAMA_STACK_CLIENT_DIR=${LLAMA_STACK_CLIENT_DIR}
+ENV PYPI_VERSION=${PYPI_VERSION}
+ENV TEST_PYPI_VERSION=${TEST_PYPI_VERSION}
+ENV KEEP_WORKSPACE=${KEEP_WORKSPACE}
+ENV DISTRO_NAME=${DISTRO_NAME}
+ENV RUN_CONFIG_PATH=${RUN_CONFIG_PATH}
+
+# Copy the repository so editable installs and run configurations are available.
+COPY . /workspace
+
+# Install llama-stack
+RUN set -eux; \
+    if [ "$INSTALL_MODE" = "editable" ]; then \
+        if [ ! -d "$LLAMA_STACK_DIR" ]; then \
+            echo "INSTALL_MODE=editable requires LLAMA_STACK_DIR to point to a directory inside the build context" >&2; \
+            exit 1; \
+        fi; \
+        uv pip install --no-cache-dir -e "$LLAMA_STACK_DIR"; \
+    elif [ "$INSTALL_MODE" = "test-pypi" ]; then \
+        uv pip install --no-cache-dir fastapi libcst; \
+        if [ -n "$TEST_PYPI_VERSION" ]; then \
+            uv pip install --no-cache-dir --extra-index-url https://test.pypi.org/simple/ --index-strategy unsafe-best-match "llama-stack==$TEST_PYPI_VERSION"; \
+        else \
+            uv pip install --no-cache-dir --extra-index-url https://test.pypi.org/simple/ --index-strategy unsafe-best-match llama-stack; \
+        fi; \
+    else \
+        if [ -n "$PYPI_VERSION" ]; then \
+            uv pip install --no-cache-dir "llama-stack==$PYPI_VERSION"; \
+        else \
+            uv pip install --no-cache-dir llama-stack; \
+        fi; \
+    fi;
+
+# Install the client package if it is provided
+RUN set -eux; \
+    if [ -n "$LLAMA_STACK_CLIENT_DIR" ]; then \
+        if [ ! -d "$LLAMA_STACK_CLIENT_DIR" ]; then \
+            echo "LLAMA_STACK_CLIENT_DIR is set but $LLAMA_STACK_CLIENT_DIR does not exist" >&2; \
+            exit 1; \
+        fi; \
+        uv pip install --no-cache-dir -e "$LLAMA_STACK_CLIENT_DIR"; \
+    fi;
+
+# Install the dependencies for the distribution
+RUN set -eux; \
+    if [ -z "$DISTRO_NAME" ]; then \
+        echo "DISTRO_NAME must be provided" >&2; \
+        exit 1; \
+    fi; \
+    deps="$(llama stack list-deps "$DISTRO_NAME")"; \
+    if [ -n "$deps" ]; then \
+        printf '%s\n' "$deps" | xargs -L1 uv pip install --no-cache-dir; \
+    fi
+
+# Cleanup
+RUN set -eux; \
+    pip uninstall -y uv; \
+    should_remove=1; \
+    if [ -n "$KEEP_WORKSPACE" ]; then should_remove=0; fi; \
+    if [ "$INSTALL_MODE" = "editable" ]; then should_remove=0; fi; \
+    case "$RUN_CONFIG_PATH" in \
+        /workspace*) should_remove=0 ;; \
+    esac; \
+    if [ "$should_remove" -eq 1 ] && [ -d /workspace ]; then rm -rf /workspace; fi
+
+RUN cat <<'EOF' >/usr/local/bin/llama-stack-entrypoint.sh
+#!/bin/sh
+set -e
+
+if [ -n "$RUN_CONFIG_PATH" ] && [ -f "$RUN_CONFIG_PATH" ]; then
+  exec llama stack run "$RUN_CONFIG_PATH" "$@"
+fi
+
+if [ -n "$DISTRO_NAME" ]; then
+  exec llama stack run "$DISTRO_NAME" "$@"
+fi
+
+exec llama stack run "$@"
+EOF
+RUN chmod +x /usr/local/bin/llama-stack-entrypoint.sh
+
+RUN mkdir -p /.llama /.cache && chmod -R g+rw /app /.llama /.cache
+
+ENTRYPOINT ["/usr/local/bin/llama-stack-entrypoint.sh"]

docs/docs/advanced_apis/post_training.mdx

@@ -51,8 +51,8 @@ device: cpu
 You can access the HuggingFace trainer via the `starter` distribution:
 
 ```bash
-llama stack build --distro starter --image-type venv
-llama stack run ~/.llama/distributions/starter/starter-run.yaml
+llama stack list-deps starter | xargs -L1 uv pip install
+llama stack run starter
 ```
 
 ### Usage Example

docs/docs/building_applications/playground.mdx

@@ -175,8 +175,7 @@ llama-stack-client benchmarks register \
 **1. Start the Llama Stack API Server**
 
 ```bash
-# Build and run a distribution (example: together)
-llama stack build --distro together --image-type venv
+llama stack list-deps together | xargs -L1 uv pip install
 llama stack run together
 ```
 
@@ -209,7 +208,7 @@ The playground works with any Llama Stack distribution. Popular options include:
 <TabItem value="together" label="Together AI">
 
 ```bash
-llama stack build --distro together --image-type venv
+llama stack list-deps together | xargs -L1 uv pip install
 llama stack run together
 ```
 
@@ -222,7 +221,7 @@ llama stack run together
 <TabItem value="ollama" label="Ollama (Local)">
 
 ```bash
-llama stack build --distro ollama --image-type venv
+llama stack list-deps ollama | xargs -L1 uv pip install
 llama stack run ollama
 ```
 
@@ -235,7 +234,7 @@ llama stack run ollama
 <TabItem value="meta-reference" label="Meta Reference">
 
 ```bash
-llama stack build --distro meta-reference --image-type venv
+llama stack list-deps meta-reference | xargs -L1 uv pip install
 llama stack run meta-reference
 ```
 

docs/docs/building_applications/rag.mdx

@@ -20,7 +20,8 @@ RAG enables your applications to reference and recall information from external
 In one terminal, start the Llama Stack server:
 
 ```bash
-uv run llama stack build --distro starter --image-type venv --run
+llama stack list-deps starter | xargs -L1 uv pip install
+llama stack run starter
 ```
 
 ### 2. Connect with OpenAI Client

docs/docs/concepts/apis/api_leveling.mdx

@@ -62,6 +62,10 @@ The new `/v2` API must be introduced alongside the existing `/v1` API and run in
 
 When a `/v2` API is introduced, a clear and generous deprecation policy for the `/v1` API must be published simultaneously. This policy must outline the timeline for the eventual removal of the `/v1` API, giving users ample time to migrate.
 
+### Deprecated APIs
+
+Deprecated APIs are those that are no longer actively maintained or supported. Depreated APIs are marked with the flag `deprecated = True` in the OpenAPI spec. These APIs will be removed in a future release.
+
 ### API Stability vs. Provider Stability
 
 The leveling introduced in this document relates to the stability of the API and not specifically the providers within the API.

docs/docs/contributing/index.mdx

@@ -158,17 +158,16 @@ under the LICENSE file in the root directory of this source tree.
 
 Some tips about common tasks you work on while contributing to Llama Stack:
 
-### Using `llama stack build`
+### Setup for development
 
-Building a stack image will use the production version of the `llama-stack` 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_STACK_CLIENT_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-stack-client-python.git
 cd llama-stack
-LLAMA_STACK_DIR=$(pwd) LLAMA_STACK_CLIENT_DIR=../llama-stack-client-python llama stack build --distro <...>
+uv run llama stack list-deps <distro-name> | xargs -L1 uv pip install
+
+# (Optional) If you are developing the llama-stack-client-python package, you can add it as an editable package.
+git clone https://github.com/meta-llama/llama-stack-client-python.git
+uv add --editable ../llama-stack-client-python
 ```
 
 ### Updating distribution configurations

docs/docs/contributing/new_api_provider.mdx

@@ -67,7 +67,7 @@ def get_base_url(self) -> str:
 
 ## Testing the Provider
 
-Before running tests, you must have required dependencies installed. This depends on the providers or distributions you are testing. For example, if you are testing the `together` distribution, you should install dependencies via `llama stack build --distro together`.
+Before running tests, you must have required dependencies installed. This depends on the providers or distributions you are testing. For example, if you are testing the `together` distribution, install its dependencies with `llama stack list-deps together | xargs -L1 uv pip install`.
 
 ### 1. Integration Testing
 

docs/docs/distributions/building_distro.mdx

@@ -5,225 +5,79 @@ sidebar_label: Build your own Distribution
 sidebar_position: 3
 ---
 
-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.
+This guide walks you through inspecting existing distributions, customising their configuration, and building runnable artefacts for your own deployment.
 
+### Explore existing distributions
 
-### Setting your log level
+All first-party distributions live under `llama_stack/distributions/`. Each directory contains:
 
-In order to specify the proper logging level users can apply the following environment variable `LLAMA_STACK_LOGGING` with the following format:
+- `build.yaml` – the distribution specification (providers, additional dependencies, optional external provider directories).
+- `run.yaml` – sample run configuration (when provided).
+- Documentation fragments that power this site.
 
-`LLAMA_STACK_LOGGING=server=debug;core=info`
-
-Where each category in the following list:
-
-- all
-- core
-- server
-- router
-- inference
-- agents
-- safety
-- eval
-- tools
-- client
-
-Can be set to any of the following log levels:
-
-- debug
-- info
-- warning
-- error
-- critical
-
-The default global log level is `info`. `all` sets the log level for all components.
-
-A user can also set `LLAMA_STACK_LOG_FILE` which will pipe the logs to the specified path as well as to the terminal. An example would be: `export LLAMA_STACK_LOG_FILE=server.log`
-
-### Llama Stack Build
-
-In order to build your own distribution, we recommend you clone the `llama-stack` repository.
-
-
-```
-git clone git@github.com:meta-llama/llama-stack.git
-cd llama-stack
-pip install -e .
-```
-Use the CLI to build your distribution.
-The main points to consider are:
-1. **Image Type** - Do you want a 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?
-
-```
-llama stack build -h
-usage: llama stack build [-h] [--config CONFIG] [--template TEMPLATE] [--distro DISTRIBUTION] [--list-distros] [--image-type {container,venv}] [--image-name IMAGE_NAME] [--print-deps-only]
-                         [--run] [--providers PROVIDERS]
-
-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.cores/**/build.yaml. If this argument is not provided, you will be prompted to
-                        enter information interactively (default: None)
-  --template TEMPLATE   (deprecated) Name of the example template config to use for build. You may use `llama stack build --list-distros` to check out the available distributions (default:
-                        None)
-  --distro DISTRIBUTION, --distribution DISTRIBUTION
-                        Name of the distribution to use for build. You may use `llama stack build --list-distros` to check out the available distributions (default: None)
-  --list-distros, --list-distributions
-                        Show the available distributions for building a Llama Stack distribution (default: False)
-  --image-type {container,venv}
-                        Image Type to use for the build. If not specified, will use the image type from the template config. (default: None)
-  --image-name IMAGE_NAME
-                        [for image-type=container|venv] Name of the virtual environment to use for the build. If not specified, currently active environment will be used if found. (default:
-                        None)
-  --print-deps-only     Print the dependencies for the stack only, without building the stack (default: False)
-  --run                 Run the stack after building using the same image type, name, and other applicable arguments (default: False)
-  --providers PROVIDERS
-                        Build a config for a list of providers and only those providers. This list is formatted like: api1=provider1,api2=provider2. Where there can be multiple providers per
-                        API. (default: None)
-```
-
-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.
+Browse that folder to understand available providers and copy a distribution to use as a starting point. When creating a new stack, duplicate an existing directory, rename it, and adjust the `build.yaml` file to match your requirements.
 
 import Tabs from '@theme/Tabs';
 import TabItem from '@theme/TabItem';
-
 <Tabs>
-<TabItem value="template" label="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.
+<TabItem value="container" label="Building a container">
 
-The following command will allow you to see the available templates and their corresponding providers.
-```
-llama stack build --list-templates
+Use the Containerfile at `containers/Containerfile`, which installs `llama-stack`, resolves distribution dependencies via `llama stack list-deps`, and sets the entrypoint to `llama stack run`.
+
+```bash
+docker build . \
+  -f containers/Containerfile \
+  --build-arg DISTRO_NAME=starter \
+  --tag llama-stack:starter
 ```
 
-```
-------------------------------+-----------------------------------------------------------------------------+
-| Template Name                | Description                                                                 |
-+------------------------------+-----------------------------------------------------------------------------+
-| watsonx                      | Use watsonx for running LLM inference                                       |
-+------------------------------+-----------------------------------------------------------------------------+
-| vllm-gpu                     | Use a built-in vLLM engine for running LLM inference                        |
-+------------------------------+-----------------------------------------------------------------------------+
-| together                     | Use Together.AI for running LLM inference                                   |
-+------------------------------+-----------------------------------------------------------------------------+
-| tgi                          | Use (an external) TGI server for running LLM inference                      |
-+------------------------------+-----------------------------------------------------------------------------+
-| starter                      | Quick start template for running Llama Stack with several popular providers |
-+------------------------------+-----------------------------------------------------------------------------+
-| sambanova                    | Use SambaNova for running LLM inference and safety                          |
-+------------------------------+-----------------------------------------------------------------------------+
-| remote-vllm                  | Use (an external) vLLM server for running LLM inference                     |
-+------------------------------+-----------------------------------------------------------------------------+
-| postgres-demo                | Quick start template for running Llama Stack with several popular providers |
-+------------------------------+-----------------------------------------------------------------------------+
-| passthrough                  | Use Passthrough hosted llama-stack endpoint for LLM inference               |
-+------------------------------+-----------------------------------------------------------------------------+
-| open-benchmark               | Distribution for running open benchmarks                                    |
-+------------------------------+-----------------------------------------------------------------------------+
-| ollama                       | Use (an external) Ollama server for running LLM inference                   |
-+------------------------------+-----------------------------------------------------------------------------+
-| nvidia                       | Use NVIDIA NIM for running LLM inference, evaluation and safety             |
-+------------------------------+-----------------------------------------------------------------------------+
-| meta-reference-gpu           | Use Meta Reference for running LLM inference                                |
-+------------------------------+-----------------------------------------------------------------------------+
-| llama_api                    | Distribution for running e2e tests in CI                                    |
-+------------------------------+-----------------------------------------------------------------------------+
-| hf-serverless                | Use (an external) Hugging Face Inference Endpoint for running LLM inference |
-+------------------------------+-----------------------------------------------------------------------------+
-| hf-endpoint                  | Use (an external) Hugging Face Inference Endpoint for running LLM inference |
-+------------------------------+-----------------------------------------------------------------------------+
-| groq                         | Use Groq for running LLM inference                                          |
-+------------------------------+-----------------------------------------------------------------------------+
-| fireworks                    | Use Fireworks.AI for running LLM inference                                  |
-+------------------------------+-----------------------------------------------------------------------------+
-| experimental-post-training   | Experimental template for post training                                     |
-+------------------------------+-----------------------------------------------------------------------------+
-| dell                         | Dell's distribution of Llama Stack. TGI inference via Dell's custom         |
-|                              | container                                                                   |
-+------------------------------+-----------------------------------------------------------------------------+
-| ci-tests                     | Distribution for running e2e tests in CI                                    |
-+------------------------------+-----------------------------------------------------------------------------+
-| cerebras                     | Use Cerebras for running LLM inference                                      |
-+------------------------------+-----------------------------------------------------------------------------+
-| bedrock                      | Use AWS Bedrock for running LLM inference and safety                        |
-+------------------------------+-----------------------------------------------------------------------------+
-```
+Handy build arguments:
 
-You may then pick a template to build your distribution with providers fitted to your liking.
+- `DISTRO_NAME` – distribution directory name (defaults to `starter`).
+- `RUN_CONFIG_PATH` – absolute path inside the build context for a run config that should be baked into the image (e.g. `/workspace/run.yaml`).
+- `INSTALL_MODE=editable` – install the repository copied into `/workspace` with `uv pip install -e`. Pair it with `--build-arg LLAMA_STACK_DIR=/workspace`.
+- `LLAMA_STACK_CLIENT_DIR` – optional editable install of the Python client.
+- `PYPI_VERSION` / `TEST_PYPI_VERSION` – pin specific releases when not using editable installs.
+- `KEEP_WORKSPACE=1` – retain `/workspace` in the final image if you need to access additional files (such as sample configs or provider bundles).
 
-For example, to build a distribution with TGI as the inference provider, you can run:
-```
-$ llama stack build --distro starter
-...
-You can now edit ~/.llama/distributions/llamastack-starter/starter-run.yaml and run `llama stack run ~/.llama/distributions/llamastack-starter/starter-run.yaml`
-```
+Make sure any custom `build.yaml`, run configs, or provider directories you reference are included in the Docker build context so the Containerfile can read them.
 
-```{tip}
-The generated `run.yaml` file is a starting point for your configuration. For comprehensive guidance on customizing it for your specific needs, infrastructure, and deployment scenarios, see [Customizing Your run.yaml Configuration](customizing_run_yaml.md).
-```
 </TabItem>
-<TabItem value="scratch" label="Building from Scratch">
+<TabItem value="external" label="Building with external providers">
 
-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.
+External providers live outside the main repository but can be bundled by pointing `external_providers_dir` to a directory that contains your provider packages.
 
-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
+1. Copy providers into the build context, for example `cp -R path/to/providers providers.d`.
+2. Update `build.yaml` with the directory and provider entries.
+3. Adjust run configs to use the in-container path (usually `/.llama/providers.d`). Pass `--build-arg RUN_CONFIG_PATH=/workspace/run.yaml` if you want to bake the config.
 
-> 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 (container or venv): venv
-
-Llama Stack is composed of several APIs working together. Let's select
-the provider types (implementations) you want to use for these APIs.
-
-Tip: use <TAB> to see options for the providers.
-
-> Enter provider for API inference: inline::meta-reference
-> Enter provider for API safety: inline::llama-guard
-> Enter provider for API agents: inline::meta-reference
-> Enter provider for API memory: inline::faiss
-> Enter provider for API datasetio: inline::meta-reference
-> Enter provider for API scoring: inline::meta-reference
-> Enter provider for API eval: inline::meta-reference
-> Enter provider for API telemetry: inline::meta-reference
-
- > (Optional) Enter a short description for your Llama Stack:
-
-You can now edit ~/.llama/distributions/llamastack-my-local-stack/my-local-stack-run.yaml and run `llama stack run ~/.llama/distributions/llamastack-my-local-stack/my-local-stack-run.yaml`
-```
-</TabItem>
-<TabItem value="config" label="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.
-
-- The config file will be of contents like the ones in `llama_stack/distributions/*build.yaml`.
-
-```
-llama stack build --config llama_stack/distributions/starter/build.yaml
-```
-</TabItem>
-<TabItem value="external" label="Building with External Providers">
-
-Llama Stack supports external providers that live outside of the main codebase. This allows you to create and maintain your own providers independently or use community-provided providers.
-
-To build a distribution with external providers, you need to:
-
-1. Configure the `external_providers_dir` in your build configuration file:
+Example `build.yaml` excerpt for a custom Ollama provider:
 
 ```yaml
-# Example my-external-stack.yaml with external providers
-version: '2'
 distribution_spec:
-  description: Custom distro for CI tests
   providers:
     inference:
-    - remote::custom_ollama
-# Add more providers as needed
-image_type: container
-image_name: ci-test
-# Path to external provider implementations
-external_providers_dir: ~/.llama/providers.d
+      - remote::custom_ollama
+external_providers_dir: /workspace/providers.d
+```
+
+Inside `providers.d/custom_ollama/provider.py`, define `get_provider_spec()` so the CLI can discover dependencies:
+
+```python
+from llama_stack.providers.datatypes import ProviderSpec
+
+
+def get_provider_spec() -> ProviderSpec:
+    return ProviderSpec(
+        provider_type="remote::custom_ollama",
+        module="llama_stack_ollama_provider",
+        config_class="llama_stack_ollama_provider.config.OllamaImplConfig",
+        pip_packages=[
+            "ollama",
+            "aiohttp",
+            "llama-stack-provider-ollama",
+        ],
+    )
 ```
 
 Here's an example for a custom Ollama provider:
@@ -232,9 +86,9 @@ Here's an example for a custom Ollama provider:
 adapter:
   adapter_type: custom_ollama
   pip_packages:
-  - ollama
-  - aiohttp
-  - llama-stack-provider-ollama # This is the provider package
+    - ollama
+    - aiohttp
+    - llama-stack-provider-ollama  # This is the provider package
   config_class: llama_stack_ollama_provider.config.OllamaImplConfig
   module: llama_stack_ollama_provider
 api_dependencies: []
@@ -245,53 +99,22 @@ The `pip_packages` section lists the Python packages required by the provider, a
 provider package itself. The package must be available on PyPI or can be provided from a local
 directory or a git repository (git must be installed on the build environment).
 
-2. Build your distribution using the config file:
+For deeper guidance, see the [External Providers documentation](../providers/external/).
 
-```
-llama stack build --config my-external-stack.yaml
-```
-
-For more information on external providers, including directory structure, provider types, and implementation requirements, see the [External Providers documentation](../providers/external/).
 </TabItem>
-<TabItem value="container" label="Building Container">
+</Tabs>
 
-:::tip Podman Alternative
-Podman is supported as an alternative to Docker. Set `CONTAINER_BINARY` to `podman` in your environment to use Podman.
-:::
+### Run your stack server
 
-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 --distro starter --image-type container
-```
-
-```
-$ llama stack build --distro starter --image-type container
-...
-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`
-```
-
-Now set some environment variables for the inference model ID and Llama Stack Port and create a local directory to mount into the container's file system.
+After building the image, launch it directly with Docker or Podman—the entrypoint calls `llama stack run` using the baked distribution or the bundled run config:
 
 ```bash
-export INFERENCE_MODEL="llama3.2:3b"
-export LLAMA_STACK_PORT=8321
-mkdir -p ~/.llama
-```
-
-After this step is successful, you should be able to find the built container image and test it with the below Docker command:
-
-```
 docker run -d \
   -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
   -v ~/.llama:/root/.llama \
   -e INFERENCE_MODEL=$INFERENCE_MODEL \
   -e OLLAMA_URL=http://host.docker.internal:11434 \
-  localhost/distribution-ollama:dev \
+  llama-stack:starter \
   --port $LLAMA_STACK_PORT
 ```
 
@@ -311,131 +134,14 @@ Here are the docker flags and their uses:
 
 * `--port $LLAMA_STACK_PORT`: Port number for the server to listen on
 
-</TabItem>
-</Tabs>
 
 
-### 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.
+If you prepared a custom run config, mount it into the container and reference it explicitly:
 
+```bash
+docker run \
+  -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
+  -v $(pwd)/run.yaml:/app/run.yaml \
+  llama-stack:starter \
+  /app/run.yaml
 ```
-llama stack run -h
-usage: llama stack run [-h] [--port PORT] [--image-name IMAGE_NAME]
-                       [--image-type {venv}] [--enable-ui]
-                       [config | distro]
-
-Start the server for a Llama Stack Distribution. You should have already built (or downloaded) and configured the distribution.
-
-positional arguments:
-  config | distro       Path to config file to use for the run or name of known distro (`llama stack list` for a list). (default: None)
-
-options:
-  -h, --help            show this help message and exit
-  --port PORT           Port to run the server on. It can also be passed via the env var LLAMA_STACK_PORT. (default: 8321)
-  --image-name IMAGE_NAME
-                        [DEPRECATED] This flag is no longer supported. Please activate your virtual environment before running. (default: None)
-  --image-type {venv}
-                        [DEPRECATED] This flag is no longer supported. Please activate your virtual environment before running. (default: None)
-  --enable-ui           Start the UI server (default: False)
-```
-
-**Note:** Container images built with `llama stack build --image-type container` cannot be run using `llama stack run`. Instead, they must be run directly using Docker or Podman commands as shown in the container building section above.
-
-```
-# Start using template name
-llama stack run tgi
-
-# Start using config file
-llama stack run ~/.llama/distributions/llamastack-my-local-stack/my-local-stack-run.yaml
-```
-
-```
-$ llama stack run ~/.llama/distributions/llamastack-my-local-stack/my-local-stack-run.yaml
-
-Serving API inspect
- GET /health
- GET /providers/list
- GET /routes/list
-Serving API inference
- POST /inference/chat_completion
- POST /inference/completion
- POST /inference/embeddings
-...
-Serving API agents
- POST /agents/create
- POST /agents/session/create
- POST /agents/turn/create
- POST /agents/delete
- POST /agents/session/delete
- POST /agents/session/get
- POST /agents/step/get
- POST /agents/turn/get
-
-Listening on ['::', '0.0.0.0']:8321
-INFO:     Started server process [2935911]
-INFO:     Waiting for application startup.
-INFO:     Application startup complete.
-INFO:     Uvicorn running on http://['::', '0.0.0.0']:8321 (Press CTRL+C to quit)
-INFO:     2401:db00:35c:2d2b:face:0:c9:0:54678 - "GET /models/list HTTP/1.1" 200 OK
-```
-
-### Listing Distributions
-Using the list command, you can view all existing Llama Stack distributions, including stacks built from templates, from scratch, or using custom configuration files.
-
-```
-llama stack list -h
-usage: llama stack list [-h]
-
-list the build stacks
-
-options:
-  -h, --help  show this help message and exit
-```
-
-Example Usage
-
-```
-llama stack list
-```
-
-```
-------------------------------+-----------------------------------------------------------------+--------------+------------+
-| Stack Name                  | Path                                                            | Build Config | Run Config |
-+------------------------------+-----------------------------------------------------------------------------+--------------+
-| together                    | ~/.llama/distributions/together                                 | Yes          | No         |
-+------------------------------+-----------------------------------------------------------------------------+--------------+
-| bedrock                     | ~/.llama/distributions/bedrock                                  | Yes          | No         |
-+------------------------------+-----------------------------------------------------------------------------+--------------+
-| starter                     | ~/.llama/distributions/starter                                  | Yes          | Yes        |
-+------------------------------+-----------------------------------------------------------------------------+--------------+
-| remote-vllm                 | ~/.llama/distributions/remote-vllm                              | Yes          | Yes        |
-+------------------------------+-----------------------------------------------------------------------------+--------------+
-```
-
-### Removing a Distribution
-Use the remove command to delete a distribution you've previously built.
-
-```
-llama stack rm -h
-usage: llama stack rm [-h] [--all] [name]
-
-Remove the build stack
-
-positional arguments:
-  name        Name of the stack to delete (default: None)
-
-options:
-  -h, --help  show this help message and exit
-  --all, -a   Delete all stacks (use with caution) (default: False)
-```
-
-Example
-```
-llama stack rm llamastack-test
-```
-
-To keep your environment organized and avoid clutter, consider using `llama stack list` to review old or unused distributions and `llama stack rm <name>` to delete them when they're no longer needed.
-
-### Troubleshooting
-
-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.

docs/docs/distributions/importing_as_library.mdx

@@ -12,7 +12,7 @@ This avoids the overhead of setting up a server.
 ```bash
 # setup
 uv pip install llama-stack
-llama stack build --distro starter --image-type venv
+llama stack list-deps starter | xargs -L1 uv pip install
 ```
 
 ```python

docs/docs/distributions/ondevice_distro/android_sdk.md

@@ -59,7 +59,7 @@ Start a Llama Stack server on localhost. Here is an example of how you can do th
 uv venv starter --python 3.12
 source starter/bin/activate  # On Windows: starter\Scripts\activate
 pip install --no-cache llama-stack==0.2.2
-llama stack build --distro starter --image-type venv
+llama stack list-deps starter | xargs -L1 uv pip install
 export FIREWORKS_API_KEY=<SOME_KEY>
 llama stack run starter --port 5050
 ```

docs/docs/distributions/self_hosted_distro/dell.md

@@ -166,10 +166,10 @@ docker run \
 
 ### Via venv
 
-Make sure you have done `pip install llama-stack` and have the Llama Stack CLI available.
+Install the distribution dependencies before launching:
 
 ```bash
-llama stack build --distro dell --image-type venv
+llama stack list-deps dell | xargs -L1 uv pip install
 INFERENCE_MODEL=$INFERENCE_MODEL \
 DEH_URL=$DEH_URL \
 CHROMA_URL=$CHROMA_URL \

docs/docs/distributions/self_hosted_distro/meta-reference-gpu.md

@@ -81,10 +81,10 @@ docker run \
 
 ### Via venv
 
-Make sure you have done `uv pip install llama-stack` and have the Llama Stack CLI available.
+Make sure you have the Llama Stack CLI available.
 
 ```bash
-llama stack build --distro meta-reference-gpu --image-type venv
+llama stack list-deps meta-reference-gpu | xargs -L1 uv pip install
 INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct \
 llama stack run distributions/meta-reference-gpu/run.yaml \
   --port 8321

docs/docs/distributions/self_hosted_distro/nvidia.md

@@ -136,11 +136,11 @@ docker run \
 
 ### Via venv
 
-If you've set up your local development environment, you can also build the image using your local virtual environment.
+If you've set up your local development environment, you can also install the distribution dependencies using your local virtual environment.
 
 ```bash
 INFERENCE_MODEL=meta-llama/Llama-3.1-8B-Instruct
-llama stack build --distro nvidia --image-type venv
+llama stack list-deps nvidia | xargs -L1 uv pip install
 NVIDIA_API_KEY=$NVIDIA_API_KEY \
 INFERENCE_MODEL=$INFERENCE_MODEL \
 llama stack run ./run.yaml \

docs/docs/distributions/self_hosted_distro/starter.md

@@ -169,7 +169,11 @@ docker run \
 Ensure you have configured the starter distribution using the environment variables explained above.
 
 ```bash
-uv run --with llama-stack llama stack build --distro starter --image-type venv --run
+# Install dependencies for the starter distribution
+uv run --with llama-stack llama stack list-deps starter | xargs -L1 uv pip install
+
+# Run the server
+uv run --with llama-stack llama stack run starter
 ```
 
 ## Example Usage

docs/docs/distributions/starting_llama_stack_server.mdx

@@ -23,6 +23,17 @@ Another simple way to start interacting with Llama Stack is to just spin up a co
 If you have built a container image and want to deploy it in a Kubernetes cluster instead of starting the Llama Stack server locally. See [Kubernetes Deployment Guide](../deploying/kubernetes_deployment) for more details.
 
 
+## Configure logging
+
+Control log output via environment variables before starting the server.
+
+- `LLAMA_STACK_LOGGING` sets per-component levels, e.g. `LLAMA_STACK_LOGGING=server=debug;core=info`.
+- Supported categories: `all`, `core`, `server`, `router`, `inference`, `agents`, `safety`, `eval`, `tools`, `client`.
+- Levels: `debug`, `info`, `warning`, `error`, `critical` (default is `info`). Use `all=<level>` to apply globally.
+- `LLAMA_STACK_LOG_FILE=/path/to/log` mirrors logs to a file while still printing to stdout.
+
+Export these variables prior to running `llama stack run`, launching a container, or starting the server through any other pathway.
+
 ```{toctree}
 :maxdepth: 1
 :hidden:

docs/docs/getting_started/detailed_tutorial.mdx

@@ -58,15 +58,19 @@ Llama Stack is a server that exposes multiple APIs, you connect with it using th
 
 <Tabs>
 <TabItem value="venv" label="Using venv">
-You can use Python to build and run the Llama Stack server, which is useful for testing and development.
+You can use Python to install dependencies and run the Llama Stack server, which is useful for testing and development.
 
 Llama Stack uses a [YAML configuration file](../distributions/configuration) to specify the stack setup,
 which defines the providers and their settings. The generated configuration serves as a starting point that you can [customize for your specific needs](../distributions/customizing_run_yaml).
-Now let's build and run the Llama Stack config for Ollama.
+Now let's install dependencies and run the Llama Stack config for Ollama.
 We use `starter` as template. By default all providers are disabled, this requires enable ollama by passing environment variables.
 
 ```bash
-llama stack build --distro starter --image-type venv --run
+# Install dependencies for the starter distribution
+uv run --with llama-stack llama stack list-deps starter | xargs -L1 uv pip install
+
+# Run the server
+llama stack run starter
 ```
 </TabItem>
 <TabItem value="container" label="Using a Container">
@@ -304,7 +308,7 @@ stream = agent.create_turn(
 for event in AgentEventLogger().log(stream):
     event.print()
 ```
-### ii. Run the Script
+#### ii. Run the Script
 Let's run the script using `uv`
 ```bash
 uv run python agent.py

docs/docs/getting_started/quickstart.mdx

@@ -24,10 +24,13 @@ ollama run llama3.2:3b --keepalive 60m
 
 #### Step 2: Run the Llama Stack server
 
-We will use `uv` to run the Llama Stack server.
+We will use `uv` to install dependencies and run the Llama Stack server.
 ```bash
-OLLAMA_URL=http://localhost:11434 \
-  uv run --with llama-stack llama stack build --distro starter --image-type venv --run
+# Install dependencies for the starter distribution
+uv run --with llama-stack llama stack list-deps starter | xargs -L1 uv pip install
+
+# Run the server
+OLLAMA_URL=http://localhost:11434 uv run --with llama-stack llama stack run starter
 ```
 #### Step 3: Run the demo
 Now open up a new terminal and copy the following script into a file named `demo_script.py`.

docs/docs/providers/eval/index.mdx

@@ -1,5 +1,7 @@
 ---
-description: "Llama Stack Evaluation API for running evaluations on model and agent candidates."
+description: "Evaluations
+
+    Llama Stack Evaluation API for running evaluations on model and agent candidates."
 sidebar_label: Eval
 title: Eval
 ---
@@ -8,6 +10,8 @@ title: Eval
 
 ## Overview
 
-Llama Stack Evaluation API for running evaluations on model and agent candidates.
+Evaluations
+
+    Llama Stack Evaluation API for running evaluations on model and agent candidates.
 
 This section contains documentation for all available providers for the **eval** API.

docs/docs/providers/external/external-providers-guide.mdx

@@ -240,6 +240,6 @@ additional_pip_packages:
 - sqlalchemy[asyncio]
 ```
 
-No other steps are required other than `llama stack build` and `llama stack run`. The build process will use `module` to install all of the provider dependencies, retrieve the spec, etc.
+No other steps are required beyond installing dependencies with `llama stack list-deps <distro> | xargs -L1 uv pip install` and then running `llama stack run`. The CLI will use `module` to install the provider dependencies, retrieve the spec, etc.
 
 The provider will now be available in Llama Stack with the type `remote::ramalama`.

docs/notebooks/Alpha_Llama_Stack_Post_Training.ipynb

@@ -2864,7 +2864,7 @@
     }
    ],
    "source": [
-    "!llama stack build --distro experimental-post-training --image-type venv --image-name __system__"
+    "!llama stack list-deps experimental-post-training | xargs -L1 uv pip install"
    ]
   },
   {

docs/notebooks/Llama_Stack_Agent_Workflows.ipynb

@@ -38,7 +38,7 @@
    "source": [
     "# NBVAL_SKIP\n",
     "!pip install -U llama-stack\n",
-    "!UV_SYSTEM_PYTHON=1 llama stack build --distro fireworks --image-type venv"
+    "llama stack list-deps fireworks | xargs -L1 uv pip install\n"
    ]
   },
   {

docs/notebooks/crewai/Llama_Stack_CrewAI.ipynb

@@ -136,7 +136,8 @@
     "    \"\"\"Build and run LlamaStack server in one step using --run flag\"\"\"\n",
     "    log_file = open(\"llama_stack_server.log\", \"w\")\n",
     "    process = subprocess.Popen(\n",
-    "        \"uv run --with llama-stack llama stack build --distro starter --image-type venv --run\",\n",
+    "        \"uv run --with llama-stack llama stack list-deps starter | xargs -L1 uv pip install\",\n",
+    "        \"uv run --with llama-stack llama stack run starter\",\n",
     "        shell=True,\n",
     "        stdout=log_file,\n",
     "        stderr=log_file,\n",
@@ -172,7 +173,7 @@
     "\n",
     "def kill_llama_stack_server():\n",
     "    # Kill any existing llama stack server processes using pkill command\n",
-    "    os.system(\"pkill -f llama_stack.core.server.server\")"
+    "    os.system(\"pkill -f llama_stack.core.server.server\")\n"
    ]
   },
   {

docs/notebooks/langchain/Llama_Stack_LangChain.ipynb

@@ -105,7 +105,8 @@
     "    \"\"\"Build and run LlamaStack server in one step using --run flag\"\"\"\n",
     "    log_file = open(\"llama_stack_server.log\", \"w\")\n",
     "    process = subprocess.Popen(\n",
-    "        \"uv run --with llama-stack llama stack build --distro starter --image-type venv --run\",\n",
+    "        \"uv run --with llama-stack llama stack list-deps starter | xargs -L1 uv pip install\",\n",
+    "        \"uv run --with llama-stack llama stack run starter\",\n",
     "        shell=True,\n",
     "        stdout=log_file,\n",
     "        stderr=log_file,\n",

docs/notebooks/nvidia/beginner_e2e/Llama_Stack_NVIDIA_E2E_Flow.ipynb

@@ -92,7 +92,7 @@
    "metadata": {},
    "source": [
     "```bash\n",
-    "LLAMA_STACK_DIR=$(pwd) llama stack build --distro nvidia --image-type venv\n",
+    "uv run --with llama-stack llama stack list-deps nvidia | xargs -L1 uv pip install\n",
     "```"
    ]
   },

docs/notebooks/nvidia/tool_calling/1_data_preparation.ipynb

@@ -81,7 +81,7 @@
    "metadata": {},
    "source": [
     "```bash\n",
-    "LLAMA_STACK_DIR=$(pwd) llama stack build --distro nvidia --image-type venv\n",
+    "uv run --with llama-stack llama stack list-deps nvidia | xargs -L1 uv pip install\n",
     "```"
    ]
   },

docs/quick_start.ipynb

@@ -1,366 +1,366 @@
 {
-  "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/github/meta-llama/llama-stack/blob/main/docs/getting_started.ipynb)\n",
-        "\n",
-        "# Llama Stack - Building AI Applications\n",
-        "\n",
-        "<img src=\"https://llamastack.github.io/latest/_images/llama-stack.png\" alt=\"drawing\" width=\"500\"/>\n",
-        "\n",
-        "Get started with Llama Stack in minutes!\n",
-        "\n",
-        "[Llama Stack](https://github.com/meta-llama/llama-stack) is a stateful service with REST APIs to support the seamless transition of AI applications across different environments. You can build and test using a local server first and deploy to a hosted endpoint for production.\n",
-        "\n",
-        "In this guide, we'll walk through how to build a RAG application locally using Llama Stack with [Ollama](https://ollama.com/)\n",
-        "as the inference [provider](docs/source/providers/index.md#inference) for a Llama Model.\n"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "4CV1Q19BDMVw",
-      "metadata": {
-        "id": "4CV1Q19BDMVw"
-      },
-      "source": [
-        "## Step 1: Install and setup"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "K4AvfUAJZOeS",
-      "metadata": {
-        "id": "K4AvfUAJZOeS"
-      },
-      "source": [
-        "### 1.1. Install uv and test inference with Ollama\n",
-        "\n",
-        "We'll install [uv](https://docs.astral.sh/uv/) to setup the Python virtual environment, along with [colab-xterm](https://github.com/InfuseAI/colab-xterm) for running command-line tools, and [Ollama](https://ollama.com/download) as the inference provider."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "id": "7a2d7b85",
-      "metadata": {},
-      "outputs": [],
-      "source": [
-        "%pip install uv llama_stack llama-stack-client\n",
-        "\n",
-        "## If running on Collab:\n",
-        "# !pip install colab-xterm\n",
-        "# %load_ext colabxterm\n",
-        "\n",
-        "!curl https://ollama.ai/install.sh | sh"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "39fa584b",
-      "metadata": {},
-      "source": [
-        "### 1.2. Test inference with Ollama"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "3bf81522",
-      "metadata": {},
-      "source": [
-        "We’ll now launch a terminal and run inference on a Llama model with Ollama to verify that the model is working correctly."
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "id": "a7e8e0f1",
-      "metadata": {},
-      "outputs": [],
-      "source": [
-        "## If running on Colab:\n",
-        "# %xterm\n",
-        "\n",
-        "## To be ran in the terminal:\n",
-        "# ollama serve &\n",
-        "# ollama run llama3.2:3b --keepalive 60m"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "f3c5f243",
-      "metadata": {},
-      "source": [
-        "If successful, you should see the model respond to a prompt.\n",
-        "\n",
-        "...\n",
-        "```\n",
-        ">>> hi\n",
-        "Hello! How can I assist you today?\n",
-        "```"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "oDUB7M_qe-Gs",
-      "metadata": {
-        "id": "oDUB7M_qe-Gs"
-      },
-      "source": [
-        "## Step 2: Run the Llama Stack server\n",
-        "\n",
-        "In this showcase, we will start a Llama Stack server that is running locally."
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "732eadc6",
-      "metadata": {},
-      "source": [
-        "### 2.1. Setup the Llama Stack Server"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "id": "J2kGed0R5PSf",
-      "metadata": {
-        "colab": {
-          "base_uri": "https://localhost:8080/"
-        },
-        "collapsed": true,
-        "id": "J2kGed0R5PSf",
-        "outputId": "2478ea60-8d35-48a1-b011-f233831740c5"
-      },
-      "outputs": [],
-      "source": [
-        "import os\n",
-        "import subprocess\n",
-        "\n",
-        "if \"UV_SYSTEM_PYTHON\" in os.environ:\n",
-        "  del os.environ[\"UV_SYSTEM_PYTHON\"]\n",
-        "\n",
-        "# this command installs all the dependencies needed for the llama stack server with the ollama inference provider\n",
-        "!uv run --with llama-stack llama stack build --distro starter\n",
-        "\n",
-        "def run_llama_stack_server_background():\n",
-        "    log_file = open(\"llama_stack_server.log\", \"w\")\n",
-        "    process = subprocess.Popen(\n",
-        "        f\"OLLAMA_URL=http://localhost:11434 uv run --with llama-stack llama stack run starter\n",
-        "        shell=True,\n",
-        "        stdout=log_file,\n",
-        "        stderr=log_file,\n",
-        "        text=True\n",
-        "    )\n",
-        "\n",
-        "    print(f\"Starting Llama Stack server with PID: {process.pid}\")\n",
-        "    return process\n",
-        "\n",
-        "def wait_for_server_to_start():\n",
-        "    import requests\n",
-        "    from requests.exceptions import ConnectionError\n",
-        "    import time\n",
-        "\n",
-        "    url = \"http://0.0.0.0:8321/v1/health\"\n",
-        "    max_retries = 30\n",
-        "    retry_interval = 1\n",
-        "\n",
-        "    print(\"Waiting for server to start\", end=\"\")\n",
-        "    for _ in range(max_retries):\n",
-        "        try:\n",
-        "            response = requests.get(url)\n",
-        "            if response.status_code == 200:\n",
-        "                print(\"\\nServer is ready!\")\n",
-        "                return True\n",
-        "        except ConnectionError:\n",
-        "            print(\".\", end=\"\", flush=True)\n",
-        "            time.sleep(retry_interval)\n",
-        "\n",
-        "    print(\"\\nServer failed to start after\", max_retries * retry_interval, \"seconds\")\n",
-        "    return False\n",
-        "\n",
-        "\n",
-        "# use this helper if needed to kill the server\n",
-        "def kill_llama_stack_server():\n",
-        "    # Kill any existing llama stack server processes\n",
-        "    os.system(\"ps aux | grep -v grep | grep llama_stack.core.server.server | awk '{print $2}' | xargs kill -9\")\n"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "c40e9efd",
-      "metadata": {},
-      "source": [
-        "### 2.2. Start the Llama Stack Server"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 7,
-      "id": "f779283d",
-      "metadata": {},
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "Starting Llama Stack server with PID: 787100\n",
-            "Waiting for server to start\n",
-            "Server is ready!\n"
-          ]
-        }
-      ],
-      "source": [
-        "server_process = run_llama_stack_server_background()\n",
-        "assert wait_for_server_to_start()"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "28477c03",
-      "metadata": {},
-      "source": [
-        "## Step 3: Run the demo"
-      ]
-    },
-    {
-      "cell_type": "code",
-      "execution_count": 8,
-      "id": "7da71011",
-      "metadata": {},
-      "outputs": [
-        {
-          "name": "stdout",
-          "output_type": "stream",
-          "text": [
-            "rag_tool> Ingesting document: https://www.paulgraham.com/greatwork.html\n",
-            "prompt> How do you do great work?\n",
-            "\u001b[33minference> \u001b[0m\u001b[33m[k\u001b[0m\u001b[33mnowledge\u001b[0m\u001b[33m_search\u001b[0m\u001b[33m(query\u001b[0m\u001b[33m=\"\u001b[0m\u001b[33mWhat\u001b[0m\u001b[33m is\u001b[0m\u001b[33m the\u001b[0m\u001b[33m key\u001b[0m\u001b[33m to\u001b[0m\u001b[33m doing\u001b[0m\u001b[33m great\u001b[0m\u001b[33m work\u001b[0m\u001b[33m\")]\u001b[0m\u001b[97m\u001b[0m\n",
-            "\u001b[32mtool_execution> Tool:knowledge_search Args:{'query': 'What is the key to doing great work'}\u001b[0m\n",
-            "\u001b[32mtool_execution> Tool:knowledge_search Response:[TextContentItem(text='knowledge_search tool found 5 chunks:\\nBEGIN of knowledge_search tool results.\\n', type='text'), TextContentItem(text=\"Result 1:\\nDocument_id:docum\\nContent:  work. Doing great work means doing something important\\nso well that you expand people's ideas of what's possible. But\\nthere's no threshold for importance. It's a matter of degree, and\\noften hard to judge at the time anyway.\\n\", type='text'), TextContentItem(text=\"Result 2:\\nDocument_id:docum\\nContent:  work. Doing great work means doing something important\\nso well that you expand people's ideas of what's possible. But\\nthere's no threshold for importance. It's a matter of degree, and\\noften hard to judge at the time anyway.\\n\", type='text'), TextContentItem(text=\"Result 3:\\nDocument_id:docum\\nContent:  work. Doing great work means doing something important\\nso well that you expand people's ideas of what's possible. But\\nthere's no threshold for importance. It's a matter of degree, and\\noften hard to judge at the time anyway.\\n\", type='text'), TextContentItem(text=\"Result 4:\\nDocument_id:docum\\nContent:  work. Doing great work means doing something important\\nso well that you expand people's ideas of what's possible. But\\nthere's no threshold for importance. It's a matter of degree, and\\noften hard to judge at the time anyway.\\n\", type='text'), TextContentItem(text=\"Result 5:\\nDocument_id:docum\\nContent:  work. Doing great work means doing something important\\nso well that you expand people's ideas of what's possible. But\\nthere's no threshold for importance. It's a matter of degree, and\\noften hard to judge at the time anyway.\\n\", type='text'), TextContentItem(text='END of knowledge_search tool results.\\n', type='text'), TextContentItem(text='The above results were retrieved to help answer the user\\'s query: \"What is the key to doing great work\". Use them as supporting information only in answering this query.\\n', type='text')]\u001b[0m\n",
-            "\u001b[33minference> \u001b[0m\u001b[33mDoing\u001b[0m\u001b[33m great\u001b[0m\u001b[33m work\u001b[0m\u001b[33m means\u001b[0m\u001b[33m doing\u001b[0m\u001b[33m something\u001b[0m\u001b[33m important\u001b[0m\u001b[33m so\u001b[0m\u001b[33m well\u001b[0m\u001b[33m that\u001b[0m\u001b[33m you\u001b[0m\u001b[33m expand\u001b[0m\u001b[33m people\u001b[0m\u001b[33m's\u001b[0m\u001b[33m ideas\u001b[0m\u001b[33m of\u001b[0m\u001b[33m what\u001b[0m\u001b[33m's\u001b[0m\u001b[33m possible\u001b[0m\u001b[33m.\u001b[0m\u001b[33m However\u001b[0m\u001b[33m,\u001b[0m\u001b[33m there\u001b[0m\u001b[33m's\u001b[0m\u001b[33m no\u001b[0m\u001b[33m threshold\u001b[0m\u001b[33m for\u001b[0m\u001b[33m importance\u001b[0m\u001b[33m,\u001b[0m\u001b[33m and\u001b[0m\u001b[33m it\u001b[0m\u001b[33m's\u001b[0m\u001b[33m often\u001b[0m\u001b[33m hard\u001b[0m\u001b[33m to\u001b[0m\u001b[33m judge\u001b[0m\u001b[33m at\u001b[0m\u001b[33m the\u001b[0m\u001b[33m time\u001b[0m\u001b[33m anyway\u001b[0m\u001b[33m.\u001b[0m\u001b[33m Great\u001b[0m\u001b[33m work\u001b[0m\u001b[33m is\u001b[0m\u001b[33m a\u001b[0m\u001b[33m matter\u001b[0m\u001b[33m of\u001b[0m\u001b[33m degree\u001b[0m\u001b[33m,\u001b[0m\u001b[33m and\u001b[0m\u001b[33m it\u001b[0m\u001b[33m can\u001b[0m\u001b[33m be\u001b[0m\u001b[33m difficult\u001b[0m\u001b[33m to\u001b[0m\u001b[33m determine\u001b[0m\u001b[33m whether\u001b[0m\u001b[33m someone\u001b[0m\u001b[33m has\u001b[0m\u001b[33m done\u001b[0m\u001b[33m great\u001b[0m\u001b[33m work\u001b[0m\u001b[33m until\u001b[0m\u001b[33m after\u001b[0m\u001b[33m the\u001b[0m\u001b[33m fact\u001b[0m\u001b[33m.\u001b[0m\u001b[97m\u001b[0m\n",
-            "\u001b[30m\u001b[0m"
-          ]
-        }
-      ],
-      "source": [
-        "from llama_stack_client import Agent, AgentEventLogger, RAGDocument, LlamaStackClient\n",
-        "\n",
-        "vector_db_id = \"my_demo_vector_db\"\n",
-        "client = LlamaStackClient(base_url=\"http://0.0.0.0:8321\")\n",
-        "\n",
-        "models = client.models.list()\n",
-        "\n",
-        "# Select the first ollama and first ollama's embedding model\n",
-        "model_id = next(m for m in models if m.model_type == \"llm\" and m.provider_id == \"ollama\").identifier\n",
-        "embedding_model = next(m for m in models if m.model_type == \"embedding\" and m.provider_id == \"ollama\")\n",
-        "embedding_model_id = embedding_model.identifier\n",
-        "embedding_dimension = embedding_model.metadata[\"embedding_dimension\"]\n",
-        "\n",
-        "_ = client.vector_dbs.register(\n",
-        "    vector_db_id=vector_db_id,\n",
-        "    embedding_model=embedding_model_id,\n",
-        "    embedding_dimension=embedding_dimension,\n",
-        "    provider_id=\"faiss\",\n",
-        ")\n",
-        "source = \"https://www.paulgraham.com/greatwork.html\"\n",
-        "print(\"rag_tool> Ingesting document:\", source)\n",
-        "document = RAGDocument(\n",
-        "    document_id=\"document_1\",\n",
-        "    content=source,\n",
-        "    mime_type=\"text/html\",\n",
-        "    metadata={},\n",
-        ")\n",
-        "client.tool_runtime.rag_tool.insert(\n",
-        "    documents=[document],\n",
-        "    vector_db_id=vector_db_id,\n",
-        "    chunk_size_in_tokens=50,\n",
-        ")\n",
-        "agent = Agent(\n",
-        "    client,\n",
-        "    model=model_id,\n",
-        "    instructions=\"You are a helpful assistant\",\n",
-        "    tools=[\n",
-        "        {\n",
-        "            \"name\": \"builtin::rag/knowledge_search\",\n",
-        "            \"args\": {\"vector_db_ids\": [vector_db_id]},\n",
-        "        }\n",
-        "    ],\n",
-        ")\n",
-        "\n",
-        "prompt = \"How do you do great work?\"\n",
-        "print(\"prompt>\", prompt)\n",
-        "\n",
-        "response = agent.create_turn(\n",
-        "    messages=[{\"role\": \"user\", \"content\": prompt}],\n",
-        "    session_id=agent.create_session(\"rag_session\"),\n",
-        "    stream=True,\n",
-        ")\n",
-        "\n",
-        "for log in AgentEventLogger().log(response):\n",
-        "    log.print()"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "341aaadf",
-      "metadata": {},
-      "source": [
-        "Congratulations! You've successfully built your first RAG application using Llama Stack! 🎉🥳"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "e88e1185",
-      "metadata": {},
-      "source": [
-        "## Next Steps"
-      ]
-    },
-    {
-      "cell_type": "markdown",
-      "id": "bcb73600",
-      "metadata": {},
-      "source": [
-        "Now you're ready to dive deeper into Llama Stack!\n",
-        "- Explore the [Detailed Tutorial](./detailed_tutorial.md).\n",
-        "- Try the [Getting Started Notebook](https://github.com/meta-llama/llama-stack/blob/main/docs/getting_started.ipynb).\n",
-        "- Browse more [Notebooks on GitHub](https://github.com/meta-llama/llama-stack/tree/main/docs/notebooks).\n",
-        "- Learn about Llama Stack [Concepts](../concepts/index.md).\n",
-        "- Discover how to [Build Llama Stacks](../distributions/index.md).\n",
-        "- Refer to our [References](../references/index.md) for details on the Llama CLI and Python SDK.\n",
-        "- Check out the [llama-stack-apps](https://github.com/meta-llama/llama-stack-apps/tree/main/examples) repository for example applications and tutorials."
-      ]
-    }
-  ],
-  "metadata": {
-    "accelerator": "GPU",
-    "colab": {
-      "gpuType": "T4",
-      "provenance": []
-    },
-    "kernelspec": {
-      "display_name": "Python 3",
-      "language": "python",
-      "name": "python3"
-    },
-    "language_info": {
-      "codemirror_mode": {
-        "name": "ipython",
-        "version": 3
-      },
-      "file_extension": ".py",
-      "mimetype": "text/x-python",
-      "name": "python",
-      "nbconvert_exporter": "python",
-      "pygments_lexer": "ipython3",
-      "version": "3.10.6"
-    }
+ "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/github/meta-llama/llama-stack/blob/main/docs/getting_started.ipynb)\n",
+    "\n",
+    "# Llama Stack - Building AI Applications\n",
+    "\n",
+    "<img src=\"https://llamastack.github.io/latest/_images/llama-stack.png\" alt=\"drawing\" width=\"500\"/>\n",
+    "\n",
+    "Get started with Llama Stack in minutes!\n",
+    "\n",
+    "[Llama Stack](https://github.com/meta-llama/llama-stack) is a stateful service with REST APIs to support the seamless transition of AI applications across different environments. You can build and test using a local server first and deploy to a hosted endpoint for production.\n",
+    "\n",
+    "In this guide, we'll walk through how to build a RAG application locally using Llama Stack with [Ollama](https://ollama.com/)\n",
+    "as the inference [provider](docs/source/providers/index.md#inference) for a Llama Model.\n"
+   ]
   },
-  "nbformat": 4,
-  "nbformat_minor": 5
+  {
+   "cell_type": "markdown",
+   "id": "4CV1Q19BDMVw",
+   "metadata": {
+    "id": "4CV1Q19BDMVw"
+   },
+   "source": [
+    "## Step 1: Install and setup"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "K4AvfUAJZOeS",
+   "metadata": {
+    "id": "K4AvfUAJZOeS"
+   },
+   "source": [
+    "### 1.1. Install uv and test inference with Ollama\n",
+    "\n",
+    "We'll install [uv](https://docs.astral.sh/uv/) to setup the Python virtual environment, along with [colab-xterm](https://github.com/InfuseAI/colab-xterm) for running command-line tools, and [Ollama](https://ollama.com/download) as the inference provider."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7a2d7b85",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%pip install uv llama_stack llama-stack-client\n",
+    "\n",
+    "## If running on Collab:\n",
+    "# !pip install colab-xterm\n",
+    "# %load_ext colabxterm\n",
+    "\n",
+    "!curl https://ollama.ai/install.sh | sh"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "39fa584b",
+   "metadata": {},
+   "source": [
+    "### 1.2. Test inference with Ollama"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3bf81522",
+   "metadata": {},
+   "source": [
+    "We’ll now launch a terminal and run inference on a Llama model with Ollama to verify that the model is working correctly."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a7e8e0f1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "## If running on Colab:\n",
+    "# %xterm\n",
+    "\n",
+    "## To be ran in the terminal:\n",
+    "# ollama serve &\n",
+    "# ollama run llama3.2:3b --keepalive 60m"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f3c5f243",
+   "metadata": {},
+   "source": [
+    "If successful, you should see the model respond to a prompt.\n",
+    "\n",
+    "...\n",
+    "```\n",
+    ">>> hi\n",
+    "Hello! How can I assist you today?\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "oDUB7M_qe-Gs",
+   "metadata": {
+    "id": "oDUB7M_qe-Gs"
+   },
+   "source": [
+    "## Step 2: Run the Llama Stack server\n",
+    "\n",
+    "In this showcase, we will start a Llama Stack server that is running locally."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "732eadc6",
+   "metadata": {},
+   "source": [
+    "### 2.1. Setup the Llama Stack Server"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "J2kGed0R5PSf",
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "collapsed": true,
+    "id": "J2kGed0R5PSf",
+    "outputId": "2478ea60-8d35-48a1-b011-f233831740c5"
+   },
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import subprocess\n",
+    "\n",
+    "if \"UV_SYSTEM_PYTHON\" in os.environ:\n",
+    "  del os.environ[\"UV_SYSTEM_PYTHON\"]\n",
+    "\n",
+    "# this command installs all the dependencies needed for the llama stack server with the ollama inference provider\n",
+    "!uv run --with llama-stack llama stack list-deps starter | xargs -L1 uv pip install\n",
+    "\n",
+    "def run_llama_stack_server_background():\n",
+    "    log_file = open(\"llama_stack_server.log\", \"w\")\n",
+    "    process = subprocess.Popen(\n",
+    "        f\"OLLAMA_URL=http://localhost:11434 uv run --with llama-stack llama stack run starter\n",
+    "        shell=True,\n",
+    "        stdout=log_file,\n",
+    "        stderr=log_file,\n",
+    "        text=True\n",
+    "    )\n",
+    "\n",
+    "    print(f\"Starting Llama Stack server with PID: {process.pid}\")\n",
+    "    return process\n",
+    "\n",
+    "def wait_for_server_to_start():\n",
+    "    import requests\n",
+    "    from requests.exceptions import ConnectionError\n",
+    "    import time\n",
+    "\n",
+    "    url = \"http://0.0.0.0:8321/v1/health\"\n",
+    "    max_retries = 30\n",
+    "    retry_interval = 1\n",
+    "\n",
+    "    print(\"Waiting for server to start\", end=\"\")\n",
+    "    for _ in range(max_retries):\n",
+    "        try:\n",
+    "            response = requests.get(url)\n",
+    "            if response.status_code == 200:\n",
+    "                print(\"\\nServer is ready!\")\n",
+    "                return True\n",
+    "        except ConnectionError:\n",
+    "            print(\".\", end=\"\", flush=True)\n",
+    "            time.sleep(retry_interval)\n",
+    "\n",
+    "    print(\"\\nServer failed to start after\", max_retries * retry_interval, \"seconds\")\n",
+    "    return False\n",
+    "\n",
+    "\n",
+    "# use this helper if needed to kill the server\n",
+    "def kill_llama_stack_server():\n",
+    "    # Kill any existing llama stack server processes\n",
+    "    os.system(\"ps aux | grep -v grep | grep llama_stack.core.server.server | awk '{print $2}' | xargs kill -9\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c40e9efd",
+   "metadata": {},
+   "source": [
+    "### 2.2. Start the Llama Stack Server"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "f779283d",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Starting Llama Stack server with PID: 787100\n",
+      "Waiting for server to start\n",
+      "Server is ready!\n"
+     ]
+    }
+   ],
+   "source": [
+    "server_process = run_llama_stack_server_background()\n",
+    "assert wait_for_server_to_start()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "28477c03",
+   "metadata": {},
+   "source": [
+    "## Step 3: Run the demo"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "7da71011",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "rag_tool> Ingesting document: https://www.paulgraham.com/greatwork.html\n",
+      "prompt> How do you do great work?\n",
+      "\u001b[33minference> \u001b[0m\u001b[33m[k\u001b[0m\u001b[33mnowledge\u001b[0m\u001b[33m_search\u001b[0m\u001b[33m(query\u001b[0m\u001b[33m=\"\u001b[0m\u001b[33mWhat\u001b[0m\u001b[33m is\u001b[0m\u001b[33m the\u001b[0m\u001b[33m key\u001b[0m\u001b[33m to\u001b[0m\u001b[33m doing\u001b[0m\u001b[33m great\u001b[0m\u001b[33m work\u001b[0m\u001b[33m\")]\u001b[0m\u001b[97m\u001b[0m\n",
+      "\u001b[32mtool_execution> Tool:knowledge_search Args:{'query': 'What is the key to doing great work'}\u001b[0m\n",
+      "\u001b[32mtool_execution> Tool:knowledge_search Response:[TextContentItem(text='knowledge_search tool found 5 chunks:\\nBEGIN of knowledge_search tool results.\\n', type='text'), TextContentItem(text=\"Result 1:\\nDocument_id:docum\\nContent:  work. Doing great work means doing something important\\nso well that you expand people's ideas of what's possible. But\\nthere's no threshold for importance. It's a matter of degree, and\\noften hard to judge at the time anyway.\\n\", type='text'), TextContentItem(text=\"Result 2:\\nDocument_id:docum\\nContent:  work. Doing great work means doing something important\\nso well that you expand people's ideas of what's possible. But\\nthere's no threshold for importance. It's a matter of degree, and\\noften hard to judge at the time anyway.\\n\", type='text'), TextContentItem(text=\"Result 3:\\nDocument_id:docum\\nContent:  work. Doing great work means doing something important\\nso well that you expand people's ideas of what's possible. But\\nthere's no threshold for importance. It's a matter of degree, and\\noften hard to judge at the time anyway.\\n\", type='text'), TextContentItem(text=\"Result 4:\\nDocument_id:docum\\nContent:  work. Doing great work means doing something important\\nso well that you expand people's ideas of what's possible. But\\nthere's no threshold for importance. It's a matter of degree, and\\noften hard to judge at the time anyway.\\n\", type='text'), TextContentItem(text=\"Result 5:\\nDocument_id:docum\\nContent:  work. Doing great work means doing something important\\nso well that you expand people's ideas of what's possible. But\\nthere's no threshold for importance. It's a matter of degree, and\\noften hard to judge at the time anyway.\\n\", type='text'), TextContentItem(text='END of knowledge_search tool results.\\n', type='text'), TextContentItem(text='The above results were retrieved to help answer the user\\'s query: \"What is the key to doing great work\". Use them as supporting information only in answering this query.\\n', type='text')]\u001b[0m\n",
+      "\u001b[33minference> \u001b[0m\u001b[33mDoing\u001b[0m\u001b[33m great\u001b[0m\u001b[33m work\u001b[0m\u001b[33m means\u001b[0m\u001b[33m doing\u001b[0m\u001b[33m something\u001b[0m\u001b[33m important\u001b[0m\u001b[33m so\u001b[0m\u001b[33m well\u001b[0m\u001b[33m that\u001b[0m\u001b[33m you\u001b[0m\u001b[33m expand\u001b[0m\u001b[33m people\u001b[0m\u001b[33m's\u001b[0m\u001b[33m ideas\u001b[0m\u001b[33m of\u001b[0m\u001b[33m what\u001b[0m\u001b[33m's\u001b[0m\u001b[33m possible\u001b[0m\u001b[33m.\u001b[0m\u001b[33m However\u001b[0m\u001b[33m,\u001b[0m\u001b[33m there\u001b[0m\u001b[33m's\u001b[0m\u001b[33m no\u001b[0m\u001b[33m threshold\u001b[0m\u001b[33m for\u001b[0m\u001b[33m importance\u001b[0m\u001b[33m,\u001b[0m\u001b[33m and\u001b[0m\u001b[33m it\u001b[0m\u001b[33m's\u001b[0m\u001b[33m often\u001b[0m\u001b[33m hard\u001b[0m\u001b[33m to\u001b[0m\u001b[33m judge\u001b[0m\u001b[33m at\u001b[0m\u001b[33m the\u001b[0m\u001b[33m time\u001b[0m\u001b[33m anyway\u001b[0m\u001b[33m.\u001b[0m\u001b[33m Great\u001b[0m\u001b[33m work\u001b[0m\u001b[33m is\u001b[0m\u001b[33m a\u001b[0m\u001b[33m matter\u001b[0m\u001b[33m of\u001b[0m\u001b[33m degree\u001b[0m\u001b[33m,\u001b[0m\u001b[33m and\u001b[0m\u001b[33m it\u001b[0m\u001b[33m can\u001b[0m\u001b[33m be\u001b[0m\u001b[33m difficult\u001b[0m\u001b[33m to\u001b[0m\u001b[33m determine\u001b[0m\u001b[33m whether\u001b[0m\u001b[33m someone\u001b[0m\u001b[33m has\u001b[0m\u001b[33m done\u001b[0m\u001b[33m great\u001b[0m\u001b[33m work\u001b[0m\u001b[33m until\u001b[0m\u001b[33m after\u001b[0m\u001b[33m the\u001b[0m\u001b[33m fact\u001b[0m\u001b[33m.\u001b[0m\u001b[97m\u001b[0m\n",
+      "\u001b[30m\u001b[0m"
+     ]
+    }
+   ],
+   "source": [
+    "from llama_stack_client import Agent, AgentEventLogger, RAGDocument, LlamaStackClient\n",
+    "\n",
+    "vector_db_id = \"my_demo_vector_db\"\n",
+    "client = LlamaStackClient(base_url=\"http://0.0.0.0:8321\")\n",
+    "\n",
+    "models = client.models.list()\n",
+    "\n",
+    "# Select the first ollama and first ollama's embedding model\n",
+    "model_id = next(m for m in models if m.model_type == \"llm\" and m.provider_id == \"ollama\").identifier\n",
+    "embedding_model = next(m for m in models if m.model_type == \"embedding\" and m.provider_id == \"ollama\")\n",
+    "embedding_model_id = embedding_model.identifier\n",
+    "embedding_dimension = embedding_model.metadata[\"embedding_dimension\"]\n",
+    "\n",
+    "_ = client.vector_dbs.register(\n",
+    "    vector_db_id=vector_db_id,\n",
+    "    embedding_model=embedding_model_id,\n",
+    "    embedding_dimension=embedding_dimension,\n",
+    "    provider_id=\"faiss\",\n",
+    ")\n",
+    "source = \"https://www.paulgraham.com/greatwork.html\"\n",
+    "print(\"rag_tool> Ingesting document:\", source)\n",
+    "document = RAGDocument(\n",
+    "    document_id=\"document_1\",\n",
+    "    content=source,\n",
+    "    mime_type=\"text/html\",\n",
+    "    metadata={},\n",
+    ")\n",
+    "client.tool_runtime.rag_tool.insert(\n",
+    "    documents=[document],\n",
+    "    vector_db_id=vector_db_id,\n",
+    "    chunk_size_in_tokens=50,\n",
+    ")\n",
+    "agent = Agent(\n",
+    "    client,\n",
+    "    model=model_id,\n",
+    "    instructions=\"You are a helpful assistant\",\n",
+    "    tools=[\n",
+    "        {\n",
+    "            \"name\": \"builtin::rag/knowledge_search\",\n",
+    "            \"args\": {\"vector_db_ids\": [vector_db_id]},\n",
+    "        }\n",
+    "    ],\n",
+    ")\n",
+    "\n",
+    "prompt = \"How do you do great work?\"\n",
+    "print(\"prompt>\", prompt)\n",
+    "\n",
+    "response = agent.create_turn(\n",
+    "    messages=[{\"role\": \"user\", \"content\": prompt}],\n",
+    "    session_id=agent.create_session(\"rag_session\"),\n",
+    "    stream=True,\n",
+    ")\n",
+    "\n",
+    "for log in AgentEventLogger().log(response):\n",
+    "    log.print()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "341aaadf",
+   "metadata": {},
+   "source": [
+    "Congratulations! You've successfully built your first RAG application using Llama Stack! 🎉🥳"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e88e1185",
+   "metadata": {},
+   "source": [
+    "## Next Steps"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bcb73600",
+   "metadata": {},
+   "source": [
+    "Now you're ready to dive deeper into Llama Stack!\n",
+    "- Explore the [Detailed Tutorial](./detailed_tutorial.md).\n",
+    "- Try the [Getting Started Notebook](https://github.com/meta-llama/llama-stack/blob/main/docs/getting_started.ipynb).\n",
+    "- Browse more [Notebooks on GitHub](https://github.com/meta-llama/llama-stack/tree/main/docs/notebooks).\n",
+    "- Learn about Llama Stack [Concepts](../concepts/index.md).\n",
+    "- Discover how to [Build Llama Stacks](../distributions/index.md).\n",
+    "- Refer to our [References](../references/index.md) for details on the Llama CLI and Python SDK.\n",
+    "- Check out the [llama-stack-apps](https://github.com/meta-llama/llama-stack-apps/tree/main/examples) repository for example applications and tutorials."
+   ]
+  }
+ ],
+ "metadata": {
+  "accelerator": "GPU",
+  "colab": {
+   "gpuType": "T4",
+   "provenance": []
+  },
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
 }

docs/src/pages/index.js

@@ -47,11 +47,11 @@ function QuickStart() {
               <pre><code>{`# Install uv and start Ollama
 ollama run llama3.2:3b --keepalive 60m
 
+# Install server dependencies
+uv run --with llama-stack llama stack list-deps starter | xargs -L1 uv pip install
+
 # Run Llama Stack server
-OLLAMA_URL=http://localhost:11434 \\
-  uv run --with llama-stack \\
-  llama stack build --distro starter \\
-  --image-type venv --run
+OLLAMA_URL=http://localhost:11434 uv run --with llama-stack llama stack run starter
 
 # Try the Python SDK
 from llama_stack_client import LlamaStackClient

docs/static/deprecated-llama-stack-spec.html

@@ -13449,8 +13449,8 @@
         },
         {
             "name": "Eval",
-            "description": "",
-            "x-displayName": "Llama Stack Evaluation API for running evaluations on model and agent candidates."
+            "description": "Llama Stack Evaluation API for running evaluations on model and agent candidates.",
+            "x-displayName": "Evaluations"
         },
         {
             "name": "Files",

docs/static/deprecated-llama-stack-spec.yaml

@@ -10196,9 +10196,9 @@ tags:
   - name: Datasets
     description: ''
   - name: Eval
-    description: ''
-    x-displayName: >-
+    description: >-
       Llama Stack Evaluation API for running evaluations on model and agent candidates.
+    x-displayName: Evaluations
   - name: Files
     description: >-
       This API is used to upload documents that can be used with other Llama Stack

docs/static/experimental-llama-stack-spec.html

@@ -5518,8 +5518,8 @@
         },
         {
             "name": "Eval",
-            "description": "",
-            "x-displayName": "Llama Stack Evaluation API for running evaluations on model and agent candidates."
+            "description": "Llama Stack Evaluation API for running evaluations on model and agent candidates.",
+            "x-displayName": "Evaluations"
         },
         {
             "name": "PostTraining (Coming Soon)",

docs/static/experimental-llama-stack-spec.yaml

@@ -4119,9 +4119,9 @@ tags:
   - name: Datasets
     description: ''
   - name: Eval
-    description: ''
-    x-displayName: >-
+    description: >-
       Llama Stack Evaluation API for running evaluations on model and agent candidates.
+    x-displayName: Evaluations
   - name: PostTraining (Coming Soon)
     description: ''
 x-tagGroups:

docs/static/llama-stack-spec.html

@@ -282,7 +282,7 @@
                     "Conversations"
                 ],
                 "summary": "Create a conversation.",
-                "description": "Create a conversation.",
+                "description": "Create a conversation.\nCreate a conversation.",
                 "parameters": [],
                 "requestBody": {
                     "content": {
@@ -326,8 +326,8 @@
                 "tags": [
                     "Conversations"
                 ],
-                "summary": "Get a conversation with the given ID.",
-                "description": "Get a conversation with the given ID.",
+                "summary": "Retrieve a conversation.",
+                "description": "Retrieve a conversation.\nGet a conversation with the given ID.",
                 "parameters": [
                     {
                         "name": "conversation_id",
@@ -369,8 +369,8 @@
                 "tags": [
                     "Conversations"
                 ],
-                "summary": "Update a conversation's metadata with the given ID.",
-                "description": "Update a conversation's metadata with the given ID.",
+                "summary": "Update a conversation.",
+                "description": "Update a conversation.\nUpdate a conversation's metadata with the given ID.",
                 "parameters": [
                     {
                         "name": "conversation_id",
@@ -422,8 +422,8 @@
                 "tags": [
                     "Conversations"
                 ],
-                "summary": "Delete a conversation with the given ID.",
-                "description": "Delete a conversation with the given ID.",
+                "summary": "Delete a conversation.",
+                "description": "Delete a conversation.\nDelete a conversation with the given ID.",
                 "parameters": [
                     {
                         "name": "conversation_id",
@@ -467,8 +467,8 @@
                 "tags": [
                     "Conversations"
                 ],
-                "summary": "List items in the conversation.",
-                "description": "List items in the conversation.",
+                "summary": "List items.",
+                "description": "List items.\nList items in the conversation.",
                 "parameters": [
                     {
                         "name": "conversation_id",
@@ -597,8 +597,8 @@
                 "tags": [
                     "Conversations"
                 ],
-                "summary": "Create items in the conversation.",
-                "description": "Create items in the conversation.",
+                "summary": "Create items.",
+                "description": "Create items.\nCreate items in the conversation.",
                 "parameters": [
                     {
                         "name": "conversation_id",
@@ -652,8 +652,8 @@
                 "tags": [
                     "Conversations"
                 ],
-                "summary": "Retrieve a conversation item.",
-                "description": "Retrieve a conversation item.",
+                "summary": "Retrieve an item.",
+                "description": "Retrieve an item.\nRetrieve a conversation item.",
                 "parameters": [
                     {
                         "name": "conversation_id",
@@ -704,8 +704,8 @@
                 "tags": [
                     "Conversations"
                 ],
-                "summary": "Delete a conversation item.",
-                "description": "Delete a conversation item.",
+                "summary": "Delete an item.",
+                "description": "Delete an item.\nDelete a conversation item.",
                 "parameters": [
                     {
                         "name": "conversation_id",
@@ -13251,8 +13251,8 @@
         },
         {
             "name": "Conversations",
-            "description": "",
-            "x-displayName": "Protocol for conversation management operations."
+            "description": "Protocol for conversation management operations.",
+            "x-displayName": "Conversations"
         },
         {
             "name": "Files",

docs/static/llama-stack-spec.yaml

@@ -192,7 +192,10 @@ paths:
       tags:
         - Conversations
       summary: Create a conversation.
-      description: Create a conversation.
+      description: >-
+        Create a conversation.
+
+        Create a conversation.
       parameters: []
       requestBody:
         content:
@@ -222,8 +225,11 @@ paths:
           $ref: '#/components/responses/DefaultError'
       tags:
         - Conversations
-      summary: Get a conversation with the given ID.
-      description: Get a conversation with the given ID.
+      summary: Retrieve a conversation.
+      description: >-
+        Retrieve a conversation.
+
+        Get a conversation with the given ID.
       parameters:
         - name: conversation_id
           in: path
@@ -252,9 +258,10 @@ paths:
           $ref: '#/components/responses/DefaultError'
       tags:
         - Conversations
-      summary: >-
-        Update a conversation's metadata with the given ID.
+      summary: Update a conversation.
       description: >-
+        Update a conversation.
+
         Update a conversation's metadata with the given ID.
       parameters:
         - name: conversation_id
@@ -290,8 +297,11 @@ paths:
           $ref: '#/components/responses/DefaultError'
       tags:
         - Conversations
-      summary: Delete a conversation with the given ID.
-      description: Delete a conversation with the given ID.
+      summary: Delete a conversation.
+      description: >-
+        Delete a conversation.
+
+        Delete a conversation with the given ID.
       parameters:
         - name: conversation_id
           in: path
@@ -321,8 +331,11 @@ paths:
           $ref: '#/components/responses/DefaultError'
       tags:
         - Conversations
-      summary: List items in the conversation.
-      description: List items in the conversation.
+      summary: List items.
+      description: >-
+        List items.
+
+        List items in the conversation.
       parameters:
         - name: conversation_id
           in: path
@@ -495,8 +508,11 @@ paths:
           $ref: '#/components/responses/DefaultError'
       tags:
         - Conversations
-      summary: Create items in the conversation.
-      description: Create items in the conversation.
+      summary: Create items.
+      description: >-
+        Create items.
+
+        Create items in the conversation.
       parameters:
         - name: conversation_id
           in: path
@@ -532,8 +548,11 @@ paths:
           $ref: '#/components/responses/DefaultError'
       tags:
         - Conversations
-      summary: Retrieve a conversation item.
-      description: Retrieve a conversation item.
+      summary: Retrieve an item.
+      description: >-
+        Retrieve an item.
+
+        Retrieve a conversation item.
       parameters:
         - name: conversation_id
           in: path
@@ -568,8 +587,11 @@ paths:
           $ref: '#/components/responses/DefaultError'
       tags:
         - Conversations
-      summary: Delete a conversation item.
-      description: Delete a conversation item.
+      summary: Delete an item.
+      description: >-
+        Delete an item.
+
+        Delete a conversation item.
       parameters:
         - name: conversation_id
           in: path
@@ -10146,9 +10168,9 @@ tags:
       - `background`
     x-displayName: Agents
   - name: Conversations
-    description: ''
-    x-displayName: >-
+    description: >-
       Protocol for conversation management operations.
+    x-displayName: Conversations
   - name: Files
     description: >-
       This API is used to upload documents that can be used with other Llama Stack

docs/static/stainless-llama-stack-spec.html

@@ -282,7 +282,7 @@
                     "Conversations"
                 ],
                 "summary": "Create a conversation.",
-                "description": "Create a conversation.",
+                "description": "Create a conversation.\nCreate a conversation.",
                 "parameters": [],
                 "requestBody": {
                     "content": {
@@ -326,8 +326,8 @@
                 "tags": [
                     "Conversations"
                 ],
-                "summary": "Get a conversation with the given ID.",
-                "description": "Get a conversation with the given ID.",
+                "summary": "Retrieve a conversation.",
+                "description": "Retrieve a conversation.\nGet a conversation with the given ID.",
                 "parameters": [
                     {
                         "name": "conversation_id",
@@ -369,8 +369,8 @@
                 "tags": [
                     "Conversations"
                 ],
-                "summary": "Update a conversation's metadata with the given ID.",
-                "description": "Update a conversation's metadata with the given ID.",
+                "summary": "Update a conversation.",
+                "description": "Update a conversation.\nUpdate a conversation's metadata with the given ID.",
                 "parameters": [
                     {
                         "name": "conversation_id",
@@ -422,8 +422,8 @@
                 "tags": [
                     "Conversations"
                 ],
-                "summary": "Delete a conversation with the given ID.",
-                "description": "Delete a conversation with the given ID.",
+                "summary": "Delete a conversation.",
+                "description": "Delete a conversation.\nDelete a conversation with the given ID.",
                 "parameters": [
                     {
                         "name": "conversation_id",
@@ -467,8 +467,8 @@
                 "tags": [
                     "Conversations"
                 ],
-                "summary": "List items in the conversation.",
-                "description": "List items in the conversation.",
+                "summary": "List items.",
+                "description": "List items.\nList items in the conversation.",
                 "parameters": [
                     {
                         "name": "conversation_id",
@@ -597,8 +597,8 @@
                 "tags": [
                     "Conversations"
                 ],
-                "summary": "Create items in the conversation.",
-                "description": "Create items in the conversation.",
+                "summary": "Create items.",
+                "description": "Create items.\nCreate items in the conversation.",
                 "parameters": [
                     {
                         "name": "conversation_id",
@@ -652,8 +652,8 @@
                 "tags": [
                     "Conversations"
                 ],
-                "summary": "Retrieve a conversation item.",
-                "description": "Retrieve a conversation item.",
+                "summary": "Retrieve an item.",
+                "description": "Retrieve an item.\nRetrieve a conversation item.",
                 "parameters": [
                     {
                         "name": "conversation_id",
@@ -704,8 +704,8 @@
                 "tags": [
                     "Conversations"
                 ],
-                "summary": "Delete a conversation item.",
-                "description": "Delete a conversation item.",
+                "summary": "Delete an item.",
+                "description": "Delete an item.\nDelete a conversation item.",
                 "parameters": [
                     {
                         "name": "conversation_id",
@@ -17928,8 +17928,8 @@
         },
         {
             "name": "Conversations",
-            "description": "",
-            "x-displayName": "Protocol for conversation management operations."
+            "description": "Protocol for conversation management operations.",
+            "x-displayName": "Conversations"
         },
         {
             "name": "DatasetIO",
@@ -17941,8 +17941,8 @@
         },
         {
             "name": "Eval",
-            "description": "",
-            "x-displayName": "Llama Stack Evaluation API for running evaluations on model and agent candidates."
+            "description": "Llama Stack Evaluation API for running evaluations on model and agent candidates.",
+            "x-displayName": "Evaluations"
         },
         {
             "name": "Files",

docs/static/stainless-llama-stack-spec.yaml

@@ -195,7 +195,10 @@ paths:
       tags:
         - Conversations
       summary: Create a conversation.
-      description: Create a conversation.
+      description: >-
+        Create a conversation.
+
+        Create a conversation.
       parameters: []
       requestBody:
         content:
@@ -225,8 +228,11 @@ paths:
           $ref: '#/components/responses/DefaultError'
       tags:
         - Conversations
-      summary: Get a conversation with the given ID.
-      description: Get a conversation with the given ID.
+      summary: Retrieve a conversation.
+      description: >-
+        Retrieve a conversation.
+
+        Get a conversation with the given ID.
       parameters:
         - name: conversation_id
           in: path
@@ -255,9 +261,10 @@ paths:
           $ref: '#/components/responses/DefaultError'
       tags:
         - Conversations
-      summary: >-
-        Update a conversation's metadata with the given ID.
+      summary: Update a conversation.
       description: >-
+        Update a conversation.
+
         Update a conversation's metadata with the given ID.
       parameters:
         - name: conversation_id
@@ -293,8 +300,11 @@ paths:
           $ref: '#/components/responses/DefaultError'
       tags:
         - Conversations
-      summary: Delete a conversation with the given ID.
-      description: Delete a conversation with the given ID.
+      summary: Delete a conversation.
+      description: >-
+        Delete a conversation.
+
+        Delete a conversation with the given ID.
       parameters:
         - name: conversation_id
           in: path
@@ -324,8 +334,11 @@ paths:
           $ref: '#/components/responses/DefaultError'
       tags:
         - Conversations
-      summary: List items in the conversation.
-      description: List items in the conversation.
+      summary: List items.
+      description: >-
+        List items.
+
+        List items in the conversation.
       parameters:
         - name: conversation_id
           in: path
@@ -498,8 +511,11 @@ paths:
           $ref: '#/components/responses/DefaultError'
       tags:
         - Conversations
-      summary: Create items in the conversation.
-      description: Create items in the conversation.
+      summary: Create items.
+      description: >-
+        Create items.
+
+        Create items in the conversation.
       parameters:
         - name: conversation_id
           in: path
@@ -535,8 +551,11 @@ paths:
           $ref: '#/components/responses/DefaultError'
       tags:
         - Conversations
-      summary: Retrieve a conversation item.
-      description: Retrieve a conversation item.
+      summary: Retrieve an item.
+      description: >-
+        Retrieve an item.
+
+        Retrieve a conversation item.
       parameters:
         - name: conversation_id
           in: path
@@ -571,8 +590,11 @@ paths:
           $ref: '#/components/responses/DefaultError'
       tags:
         - Conversations
-      summary: Delete a conversation item.
-      description: Delete a conversation item.
+      summary: Delete an item.
+      description: >-
+        Delete an item.
+
+        Delete a conversation item.
       parameters:
         - name: conversation_id
           in: path
@@ -13533,17 +13555,17 @@ tags:
   - name: Benchmarks
     description: ''
   - name: Conversations
-    description: ''
-    x-displayName: >-
+    description: >-
       Protocol for conversation management operations.
+    x-displayName: Conversations
   - name: DatasetIO
     description: ''
   - name: Datasets
     description: ''
   - name: Eval
-    description: ''
-    x-displayName: >-
+    description: >-
       Llama Stack Evaluation API for running evaluations on model and agent candidates.
+    x-displayName: Evaluations
   - name: Files
     description: >-
       This API is used to upload documents that can be used with other Llama Stack

docs/zero_to_hero_guide/README.md

@@ -78,17 +78,14 @@ If you're looking for more specific topics, we have a [Zero to Hero Guide](#next
 
 ## Build, Configure, and Run Llama Stack
 
-1. **Build the Llama Stack**:
-   Build the Llama Stack using the `starter` template:
+1. **Install dependencies**:
    ```bash
-   uv run --with llama-stack llama stack build --distro starter --image-type venv
+   llama stack list-deps starter | xargs -L1 uv pip install
    ```
-   **Expected Output:**
+
+2. **Start the distribution**:
    ```bash
-   ...
-   Build Successful!
-   You can find the newly-built template here: ~/.llama/distributions/starter/starter-run.yaml
-   You can run the new Llama Stack Distro via: uv run --with llama-stack llama stack run starter
+   llama stack run starter
    ```
 
 3. **Set the ENV variables by exporting them to the terminal**:

llama_stack/apis/conversations/conversations.py

@@ -173,7 +173,9 @@ class ConversationItemDeletedResource(BaseModel):
 @runtime_checkable
 @trace_protocol
 class Conversations(Protocol):
-    """Protocol for conversation management operations."""
+    """Conversations
+
+    Protocol for conversation management operations."""
 
     @webmethod(route="/conversations", method="POST", level=LLAMA_STACK_API_V1)
     async def create_conversation(
@@ -181,6 +183,8 @@ class Conversations(Protocol):
     ) -> Conversation:
         """Create a conversation.
 
+        Create a conversation.
+
         :param items: Initial items to include in the conversation context.
         :param metadata: Set of key-value pairs that can be attached to an object.
         :returns: The created conversation object.
@@ -189,7 +193,9 @@ class Conversations(Protocol):
 
     @webmethod(route="/conversations/{conversation_id}", method="GET", level=LLAMA_STACK_API_V1)
     async def get_conversation(self, conversation_id: str) -> Conversation:
-        """Get a conversation with the given ID.
+        """Retrieve a conversation.
+
+        Get a conversation with the given ID.
 
         :param conversation_id: The conversation identifier.
         :returns: The conversation object.
@@ -198,7 +204,9 @@ class Conversations(Protocol):
 
     @webmethod(route="/conversations/{conversation_id}", method="POST", level=LLAMA_STACK_API_V1)
     async def update_conversation(self, conversation_id: str, metadata: Metadata) -> Conversation:
-        """Update a conversation's metadata with the given ID.
+        """Update a conversation.
+
+        Update a conversation's metadata with the given ID.
 
         :param conversation_id: The conversation identifier.
         :param metadata: Set of key-value pairs that can be attached to an object.
@@ -208,7 +216,9 @@ class Conversations(Protocol):
 
     @webmethod(route="/conversations/{conversation_id}", method="DELETE", level=LLAMA_STACK_API_V1)
     async def openai_delete_conversation(self, conversation_id: str) -> ConversationDeletedResource:
-        """Delete a conversation with the given ID.
+        """Delete a conversation.
+
+        Delete a conversation with the given ID.
 
         :param conversation_id: The conversation identifier.
         :returns: The deleted conversation resource.
@@ -217,7 +227,9 @@ class Conversations(Protocol):
 
     @webmethod(route="/conversations/{conversation_id}/items", method="POST", level=LLAMA_STACK_API_V1)
     async def add_items(self, conversation_id: str, items: list[ConversationItem]) -> ConversationItemList:
-        """Create items in the conversation.
+        """Create items.
+
+        Create items in the conversation.
 
         :param conversation_id: The conversation identifier.
         :param items: Items to include in the conversation context.
@@ -227,7 +239,9 @@ class Conversations(Protocol):
 
     @webmethod(route="/conversations/{conversation_id}/items/{item_id}", method="GET", level=LLAMA_STACK_API_V1)
     async def retrieve(self, conversation_id: str, item_id: str) -> ConversationItem:
-        """Retrieve a conversation item.
+        """Retrieve an item.
+
+        Retrieve a conversation item.
 
         :param conversation_id: The conversation identifier.
         :param item_id: The item identifier.
@@ -244,7 +258,9 @@ class Conversations(Protocol):
         limit: int | NotGiven = NOT_GIVEN,
         order: Literal["asc", "desc"] | NotGiven = NOT_GIVEN,
     ) -> ConversationItemList:
-        """List items in the conversation.
+        """List items.
+
+        List items in the conversation.
 
         :param conversation_id: The conversation identifier.
         :param after: An item ID to list items after, used in pagination.
@@ -259,7 +275,9 @@ class Conversations(Protocol):
     async def openai_delete_conversation_item(
         self, conversation_id: str, item_id: str
     ) -> ConversationItemDeletedResource:
-        """Delete a conversation item.
+        """Delete an item.
+
+        Delete a conversation item.
 
         :param conversation_id: The conversation identifier.
         :param item_id: The item identifier.

llama_stack/apis/eval/eval.py

@@ -82,7 +82,9 @@ class EvaluateResponse(BaseModel):
 
 
 class Eval(Protocol):
-    """Llama Stack Evaluation API for running evaluations on model and agent candidates."""
+    """Evaluations
+
+    Llama Stack Evaluation API for running evaluations on model and agent candidates."""
 
     @webmethod(route="/eval/benchmarks/{benchmark_id}/jobs", method="POST", level=LLAMA_STACK_API_V1, deprecated=True)
     @webmethod(route="/eval/benchmarks/{benchmark_id}/jobs", method="POST", level=LLAMA_STACK_API_V1ALPHA)

llama_stack/cli/stack/_list_deps.py

@@ -0,0 +1,182 @@
+# 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 argparse
+import sys
+from pathlib import Path
+
+import yaml
+from termcolor import cprint
+
+from llama_stack.cli.stack.utils import ImageType
+from llama_stack.core.build import get_provider_dependencies
+from llama_stack.core.datatypes import (
+    BuildConfig,
+    BuildProvider,
+    DistributionSpec,
+)
+from llama_stack.core.distribution import get_provider_registry
+from llama_stack.core.stack import replace_env_vars
+from llama_stack.log import get_logger
+from llama_stack.providers.datatypes import Api
+
+TEMPLATES_PATH = Path(__file__).parent.parent.parent / "templates"
+
+logger = get_logger(name=__name__, category="cli")
+
+
+# These are the dependencies needed by the distribution server.
+# `llama-stack` is automatically installed by the installation script.
+SERVER_DEPENDENCIES = [
+    "aiosqlite",
+    "fastapi",
+    "fire",
+    "httpx",
+    "uvicorn",
+    "opentelemetry-sdk",
+    "opentelemetry-exporter-otlp-proto-http",
+]
+
+
+def format_output_deps_only(
+    normal_deps: list[str],
+    special_deps: list[str],
+    external_deps: list[str],
+    uv: bool = False,
+) -> str:
+    """Format dependencies as a list."""
+    lines = []
+
+    uv_str = ""
+    if uv:
+        uv_str = "uv pip install "
+
+    # Quote deps with commas
+    quoted_normal_deps = [quote_if_needed(dep) for dep in normal_deps]
+    lines.append(f"{uv_str}{' '.join(quoted_normal_deps)}")
+
+    for special_dep in special_deps:
+        lines.append(f"{uv_str}{quote_special_dep(special_dep)}")
+
+    for external_dep in external_deps:
+        lines.append(f"{uv_str}{quote_special_dep(external_dep)}")
+
+    return "\n".join(lines)
+
+
+def run_stack_list_deps_command(args: argparse.Namespace) -> None:
+    if args.config:
+        try:
+            from llama_stack.core.utils.config_resolution import Mode, resolve_config_or_distro
+
+            config_file = resolve_config_or_distro(args.config, Mode.BUILD)
+        except ValueError as e:
+            cprint(
+                f"Could not parse config file {args.config}: {e}",
+                color="red",
+                file=sys.stderr,
+            )
+            sys.exit(1)
+        if config_file:
+            with open(config_file) as f:
+                try:
+                    contents = yaml.safe_load(f)
+                    contents = replace_env_vars(contents)
+                    build_config = BuildConfig(**contents)
+                    build_config.image_type = "venv"
+                except Exception as e:
+                    cprint(
+                        f"Could not parse config file {config_file}: {e}",
+                        color="red",
+                        file=sys.stderr,
+                    )
+                    sys.exit(1)
+    elif args.providers:
+        provider_list: dict[str, list[BuildProvider]] = dict()
+        for api_provider in args.providers.split(","):
+            if "=" not in api_provider:
+                cprint(
+                    "Could not parse `--providers`. Please ensure the list is in the format api1=provider1,api2=provider2",
+                    color="red",
+                    file=sys.stderr,
+                )
+                sys.exit(1)
+            api, provider_type = api_provider.split("=")
+            providers_for_api = get_provider_registry().get(Api(api), None)
+            if providers_for_api is None:
+                cprint(
+                    f"{api} is not a valid API.",
+                    color="red",
+                    file=sys.stderr,
+                )
+                sys.exit(1)
+            if provider_type in providers_for_api:
+                provider = BuildProvider(
+                    provider_type=provider_type,
+                    module=None,
+                )
+                provider_list.setdefault(api, []).append(provider)
+            else:
+                cprint(
+                    f"{provider_type} is not a valid provider for the {api} API.",
+                    color="red",
+                    file=sys.stderr,
+                )
+                sys.exit(1)
+        distribution_spec = DistributionSpec(
+            providers=provider_list,
+            description=",".join(args.providers),
+        )
+        build_config = BuildConfig(image_type=ImageType.VENV.value, distribution_spec=distribution_spec)
+
+    normal_deps, special_deps, external_provider_dependencies = get_provider_dependencies(build_config)
+    normal_deps += SERVER_DEPENDENCIES
+
+    # Add external API dependencies
+    if build_config.external_apis_dir:
+        from llama_stack.core.external import load_external_apis
+
+        external_apis = load_external_apis(build_config)
+        if external_apis:
+            for _, api_spec in external_apis.items():
+                normal_deps.extend(api_spec.pip_packages)
+
+    # Format and output based on requested format
+    output = format_output_deps_only(
+        normal_deps=normal_deps,
+        special_deps=special_deps,
+        external_deps=external_provider_dependencies,
+        uv=args.format == "uv",
+    )
+
+    print(output)
+
+
+def quote_if_needed(dep):
+    # Add quotes if the dependency contains special characters that need escaping in shell
+    # This includes: commas, comparison operators (<, >, <=, >=, ==, !=)
+    needs_quoting = any(char in dep for char in [",", "<", ">", "="])
+    return f"'{dep}'" if needs_quoting else dep
+
+
+def quote_special_dep(dep_string):
+    """
+    Quote individual packages in a special dependency string.
+    Special deps may contain multiple packages and flags like --extra-index-url.
+    We need to quote only the package specs that contain special characters.
+    """
+    parts = dep_string.split()
+    quoted_parts = []
+
+    for part in parts:
+        # Don't quote flags (they start with -)
+        if part.startswith("-"):
+            quoted_parts.append(part)
+        else:
+            # Quote package specs that need it
+            quoted_parts.append(quote_if_needed(part))
+
+    return " ".join(quoted_parts)

llama_stack/cli/stack/build.py

@@ -8,6 +8,9 @@ import textwrap
 
 from llama_stack.cli.stack.utils import ImageType
 from llama_stack.cli.subcommand import Subcommand
+from llama_stack.log import get_logger
+
+logger = get_logger(__name__, category="cli")
 
 
 class StackBuild(Subcommand):
@@ -16,7 +19,7 @@ class StackBuild(Subcommand):
         self.parser = subparsers.add_parser(
             "build",
             prog="llama stack build",
-            description="Build a Llama stack container",
+            description="[DEPRECATED] Build a Llama stack container. This command is deprecated and will be removed in a future release. Use `llama stack list-deps <distro>' instead.",
             formatter_class=argparse.ArgumentDefaultsHelpFormatter,
         )
         self._add_arguments()
@@ -93,6 +96,9 @@ the build. If not specified, currently active environment will be used if found.
         )
 
     def _run_stack_build_command(self, args: argparse.Namespace) -> None:
+        logger.warning(
+            "The 'llama stack build' command is deprecated and will be removed in a future release. Please use 'llama stack list-deps'"
+        )
         # always keep implementation completely silo-ed away from CLI so CLI
         # can be fast to load and reduces dependencies
         from ._build import run_stack_build_command

llama_stack/cli/stack/list_deps.py

@@ -0,0 +1,51 @@
+# 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 argparse
+
+from llama_stack.cli.subcommand import Subcommand
+
+
+class StackListDeps(Subcommand):
+    def __init__(self, subparsers: argparse._SubParsersAction):
+        super().__init__()
+        self.parser = subparsers.add_parser(
+            "list-deps",
+            prog="llama stack list-deps",
+            description="list the dependencies for a llama stack distribution",
+            formatter_class=argparse.ArgumentDefaultsHelpFormatter,
+        )
+        self._add_arguments()
+        self.parser.set_defaults(func=self._run_stack_list_deps_command)
+
+    def _add_arguments(self):
+        self.parser.add_argument(
+            "config",
+            type=str,
+            nargs="?",  # Make it optional
+            metavar="config | distro",
+            help="Path to config file to use or name of known distro (llama stack list for a list).",
+        )
+
+        self.parser.add_argument(
+            "--providers",
+            type=str,
+            default=None,
+            help="sync dependencies for a list of providers and only those providers. This list is formatted like: api1=provider1,api2=provider2. Where there can be multiple providers per API.",
+        )
+        self.parser.add_argument(
+            "--format",
+            type=str,
+            choices=["uv", "deps-only"],
+            default="deps-only",
+            help="Output format: 'uv' shows shell commands, 'deps-only' shows just the list of dependencies without `uv` (default)",
+        )
+
+    def _run_stack_list_deps_command(self, args: argparse.Namespace) -> None:
+        # always keep implementation completely silo-ed away from CLI so CLI
+        # can be fast to load and reduces dependencies
+        from ._list_deps import run_stack_list_deps_command
+
+        return run_stack_list_deps_command(args)

llama_stack/cli/stack/stack.py

@@ -13,6 +13,7 @@ from llama_stack.cli.subcommand import Subcommand
 
 from .build import StackBuild
 from .list_apis import StackListApis
+from .list_deps import StackListDeps
 from .list_providers import StackListProviders
 from .remove import StackRemove
 from .run import StackRun
@@ -39,6 +40,7 @@ class StackParser(Subcommand):
         subparsers = self.parser.add_subparsers(title="stack_subcommands")
 
         # Add sub-commands
+        StackListDeps.create(subparsers)
         StackBuild.create(subparsers)
         StackListApis.create(subparsers)
         StackListProviders.create(subparsers)

llama_stack/cli/stack/utils.py

@@ -4,7 +4,28 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
+import json
+import sys
 from enum import Enum
+from functools import lru_cache
+from pathlib import Path
+
+import yaml
+from termcolor import cprint
+
+from llama_stack.core.datatypes import (
+    BuildConfig,
+    Provider,
+    StackRunConfig,
+)
+from llama_stack.core.distribution import get_provider_registry
+from llama_stack.core.resolver import InvalidProviderError
+from llama_stack.core.utils.config_dirs import EXTERNAL_PROVIDERS_DIR
+from llama_stack.core.utils.dynamic import instantiate_class_type
+from llama_stack.core.utils.image_types import LlamaStackImageType
+from llama_stack.providers.datatypes import Api
+
+TEMPLATES_PATH = Path(__file__).parent.parent.parent / "distributions"
 
 
 class ImageType(Enum):
@@ -19,3 +40,91 @@ def print_subcommand_description(parser, subparsers):
         description = subcommand.description
         description_text += f"  {name:<21} {description}\n"
     parser.epilog = description_text
+
+
+def generate_run_config(
+    build_config: BuildConfig,
+    build_dir: Path,
+    image_name: str,
+) -> Path:
+    """
+    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(
+        container_image=(image_name if build_config.image_type == LlamaStackImageType.CONTAINER.value else None),
+        image_name=image_name,
+        apis=apis,
+        providers={},
+        external_providers_dir=build_config.external_providers_dir
+        if build_config.external_providers_dir
+        else EXTERNAL_PROVIDERS_DIR,
+    )
+    # build providers dict
+    provider_registry = get_provider_registry(build_config)
+    for api in apis:
+        run_config.providers[api] = []
+        providers = build_config.distribution_spec.providers[api]
+
+        for provider in providers:
+            pid = provider.provider_type.split("::")[-1]
+
+            p = provider_registry[Api(api)][provider.provider_type]
+            if p.deprecation_error:
+                raise InvalidProviderError(p.deprecation_error)
+
+            try:
+                config_type = instantiate_class_type(provider_registry[Api(api)][provider.provider_type].config_class)
+            except (ModuleNotFoundError, ValueError) as exc:
+                # HACK ALERT:
+                # This code executes after building is done, the import cannot work since the
+                # package is either available in the venv or container - not available on the host.
+                # TODO: use a "is_external" flag in ProviderSpec to check if the provider is
+                # external
+                cprint(
+                    f"Failed to import provider {provider.provider_type} for API {api} - assuming it's external, skipping: {exc}",
+                    color="yellow",
+                    file=sys.stderr,
+                )
+                # Set config_type to None to avoid UnboundLocalError
+                config_type = None
+
+            if config_type is not None and hasattr(config_type, "sample_run_config"):
+                config = config_type.sample_run_config(__distro_dir__=f"~/.llama/distributions/{image_name}")
+            else:
+                config = {}
+
+            p_spec = Provider(
+                provider_id=pid,
+                provider_type=provider.provider_type,
+                config=config,
+                module=provider.module,
+            )
+            run_config.providers[api].append(p_spec)
+
+    run_config_file = build_dir / f"{image_name}-run.yaml"
+
+    with open(run_config_file, "w") as f:
+        to_write = json.loads(run_config.model_dump_json())
+        f.write(yaml.dump(to_write, sort_keys=False))
+
+    # Only print this message for non-container builds since it will be displayed before the
+    # container is built
+    # For non-container builds, the run.yaml is generated at the very end of the build process so it
+    # makes sense to display this message
+    if build_config.image_type != LlamaStackImageType.CONTAINER.value:
+        cprint(f"You can now run your stack with `llama stack run {run_config_file}`", color="green", file=sys.stderr)
+    return run_config_file
+
+
+@lru_cache
+def available_templates_specs() -> dict[str, BuildConfig]:
+    import yaml
+
+    template_specs = {}
+    for p in TEMPLATES_PATH.rglob("*build.yaml"):
+        template_name = p.parent.name
+        with open(p) as f:
+            build_config = BuildConfig(**yaml.safe_load(f))
+            template_specs[template_name] = build_config
+    return template_specs

llama_stack/core/build_container.sh

@@ -338,7 +338,7 @@ fi
 # Add other require item commands genearic to all containers
 add_to_container << EOF
 
-RUN mkdir -p /.llama /.cache && chmod -R g+rw /app /.llama /.cache
+RUN mkdir -p /.llama /.cache && chmod -R g+rw /.llama /.cache && (chmod -R g+rw /app 2>/dev/null || true)
 EOF
 
 printf "Containerfile created successfully in %s/Containerfile\n\n" "$TEMP_DIR"

llama_stack/core/resolver.py

@@ -4,6 +4,7 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 import importlib
+import importlib.metadata
 import inspect
 from typing import Any
 

llama_stack/core/testing_context.py

@@ -42,3 +42,8 @@ def sync_test_context_from_provider_data():
         return TEST_CONTEXT.set(provider_data["__test_id"])
 
     return None
+
+
+def is_debug_mode() -> bool:
+    """Check if test recording debug mode is enabled via LLAMA_STACK_TEST_DEBUG env var."""
+    return os.environ.get("LLAMA_STACK_TEST_DEBUG", "").lower() in ("1", "true", "yes")

llama_stack/core/utils/config_resolution.py

@@ -42,25 +42,25 @@ def resolve_config_or_distro(
     # Strategy 1: Try as file path first
     config_path = Path(config_or_distro)
     if config_path.exists() and config_path.is_file():
-        logger.info(f"Using file path: {config_path}")
+        logger.debug(f"Using file path: {config_path}")
         return config_path.resolve()
 
     # Strategy 2: Try as distribution name (if no .yaml extension)
     if not config_or_distro.endswith(".yaml"):
         distro_config = _get_distro_config_path(config_or_distro, mode)
         if distro_config.exists():
-            logger.info(f"Using distribution: {distro_config}")
+            logger.debug(f"Using distribution: {distro_config}")
             return distro_config
 
     # Strategy 3: Try as built distribution name
     distrib_config = DISTRIBS_BASE_DIR / f"llamastack-{config_or_distro}" / f"{config_or_distro}-{mode}.yaml"
     if distrib_config.exists():
-        logger.info(f"Using built distribution: {distrib_config}")
+        logger.debug(f"Using built distribution: {distrib_config}")
         return distrib_config
 
     distrib_config = DISTRIBS_BASE_DIR / f"{config_or_distro}" / f"{config_or_distro}-{mode}.yaml"
     if distrib_config.exists():
-        logger.info(f"Using built distribution: {distrib_config}")
+        logger.debug(f"Using built distribution: {distrib_config}")
         return distrib_config
 
     # Strategy 4: Failed - provide helpful error

llama_stack/distributions/meta-reference-gpu/doc_template.md

@@ -70,10 +70,10 @@ docker run \
 
 ### Via venv
 
-Make sure you have done `uv pip install llama-stack` and have the Llama Stack CLI available.
+Make sure you have the Llama Stack CLI available.
 
 ```bash
-llama stack build --distro {{ name }} --image-type venv
+llama stack list-deps meta-reference-gpu | xargs -L1 uv pip install
 INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct \
 llama stack run distributions/{{ name }}/run.yaml \
   --port 8321

llama_stack/distributions/nvidia/doc_template.md

@@ -126,11 +126,11 @@ docker run \
 
 ### Via venv
 
-If you've set up your local development environment, you can also build the image using your local virtual environment.
+If you've set up your local development environment, you can also install the distribution dependencies using your local virtual environment.
 
 ```bash
 INFERENCE_MODEL=meta-llama/Llama-3.1-8B-Instruct
-llama stack build --distro nvidia --image-type venv
+llama stack list-deps nvidia | xargs -L1 uv pip install
 NVIDIA_API_KEY=$NVIDIA_API_KEY \
 INFERENCE_MODEL=$INFERENCE_MODEL \
 llama stack run ./run.yaml \

llama_stack/providers/inline/telemetry/meta_reference/telemetry.py

@@ -79,7 +79,6 @@ class TelemetryAdapter(Telemetry):
             metrics.set_meter_provider(metric_provider)
 
         self.meter = metrics.get_meter(__name__)
-
         self._lock = _global_lock
 
     async def initialize(self) -> None:

llama_stack/providers/remote/inference/nvidia/NVIDIA.md

@@ -45,7 +45,7 @@ The following example shows how to create a chat completion for an NVIDIA NIM.
 
 ```python
 response = client.chat.completions.create(
-    model="meta-llama/Llama-3.1-8B-Instruct",
+    model="nvidia/meta/llama-3.1-8b-instruct",
     messages=[
         {
             "role": "system",
@@ -67,37 +67,40 @@ print(f"Response: {response.choices[0].message.content}")
 The following example shows how to do tool calling for an NVIDIA NIM.
 
 ```python
-from llama_stack.models.llama.datatypes import ToolDefinition, ToolParamDefinition
-
-tool_definition = ToolDefinition(
-    tool_name="get_weather",
-    description="Get current weather information for a location",
-    parameters={
-        "location": ToolParamDefinition(
-            param_type="string",
-            description="The city and state, e.g. San Francisco, CA",
-            required=True,
-        ),
-        "unit": ToolParamDefinition(
-            param_type="string",
-            description="Temperature unit (celsius or fahrenheit)",
-            required=False,
-            default="celsius",
-        ),
+tool_definition = {
+    "type": "function",
+    "function": {
+        "name": "get_weather",
+        "description": "Get current weather information for a location",
+        "parameters": {
+            "type": "object",
+            "properties": {
+                "location": {
+                    "type": "string",
+                    "description": "The city and state, e.g. San Francisco, CA",
+                },
+                "unit": {
+                    "type": "string",
+                    "description": "Temperature unit (celsius or fahrenheit)",
+                    "default": "celsius",
+                },
+            },
+            "required": ["location"],
+        },
     },
-)
+}
 
 tool_response = client.chat.completions.create(
-    model="meta-llama/Llama-3.1-8B-Instruct",
+    model="nvidia/meta/llama-3.1-8b-instruct",
     messages=[{"role": "user", "content": "What's the weather like in San Francisco?"}],
     tools=[tool_definition],
 )
 
-print(f"Tool Response: {tool_response.choices[0].message.content}")
+print(f"Response content: {tool_response.choices[0].message.content}")
 if tool_response.choices[0].message.tool_calls:
     for tool_call in tool_response.choices[0].message.tool_calls:
-        print(f"Tool Called: {tool_call.tool_name}")
-        print(f"Arguments: {tool_call.arguments}")
+        print(f"Tool Called: {tool_call.function.name}")
+        print(f"Arguments: {tool_call.function.arguments}")
 ```
 
 ### Structured Output Example
@@ -105,33 +108,26 @@ if tool_response.choices[0].message.tool_calls:
 The following example shows how to do structured output for an NVIDIA NIM.
 
 ```python
-from llama_stack.apis.inference import JsonSchemaResponseFormat, ResponseFormatType
-
 person_schema = {
     "type": "object",
     "properties": {
         "name": {"type": "string"},
-        "age": {"type": "integer"},
+        "age": {"type": "number"},
         "occupation": {"type": "string"},
     },
     "required": ["name", "age", "occupation"],
 }
 
-response_format = JsonSchemaResponseFormat(
-    type=ResponseFormatType.json_schema, json_schema=person_schema
-)
-
 structured_response = client.chat.completions.create(
-    model="meta-llama/Llama-3.1-8B-Instruct",
+    model="nvidia/meta/llama-3.1-8b-instruct",
     messages=[
         {
             "role": "user",
             "content": "Create a profile for a fictional person named Alice who is 30 years old and is a software engineer. ",
         }
     ],
-    response_format=response_format,
+    extra_body={"nvext": {"guided_json": person_schema}},
 )
-
 print(f"Structured Response: {structured_response.choices[0].message.content}")
 ```
 
@@ -141,7 +137,7 @@ The following example shows how to create embeddings for an NVIDIA NIM.
 
 ```python
 response = client.embeddings.create(
-    model="nvidia/llama-3.2-nv-embedqa-1b-v2",
+    model="nvidia/nvidia/llama-3.2-nv-embedqa-1b-v2",
     input=["What is the capital of France?"],
     extra_body={"input_type": "query"},
 )
@@ -163,15 +159,15 @@ image_path = {path_to_the_image}
 demo_image_b64 = load_image_as_base64(image_path)
 
 vlm_response = client.chat.completions.create(
-    model="nvidia/vila",
+    model="nvidia/meta/llama-3.2-11b-vision-instruct",
     messages=[
         {
             "role": "user",
             "content": [
                 {
-                    "type": "image",
-                    "image": {
-                        "data": demo_image_b64,
+                    "type": "image_url",
+                    "image_url": {
+                        "url": f"data:image/png;base64,{demo_image_b64}",
                     },
                 },
                 {

llama_stack/providers/remote/inference/nvidia/nvidia.py

@@ -19,15 +19,6 @@ class NVIDIAInferenceAdapter(OpenAIMixin):
 
     """
     NVIDIA Inference Adapter for Llama Stack.
-
-    Note: The inheritance order is important here. OpenAIMixin must come before
-    ModelRegistryHelper to ensure that OpenAIMixin.check_model_availability()
-    is used instead of ModelRegistryHelper.check_model_availability(). It also
-    must come before Inference to ensure that OpenAIMixin methods are available
-    in the Inference interface.
-
-    - OpenAIMixin.check_model_availability() queries the NVIDIA API to check if a model exists
-    - ModelRegistryHelper.check_model_availability() just returns False and shows a warning
     """
 
     # source: https://docs.nvidia.com/nim/nemo-retriever/text-embedding/latest/support-matrix.html

llama_stack/providers/utils/telemetry/trace_protocol.py

@@ -70,7 +70,7 @@ def trace_protocol[T](cls: type[T]) -> type[T]:
                 "__class__": class_name,
                 "__method__": method_name,
                 "__type__": span_type,
-                "__args__": str(combined_args),
+                "__args__": json.dumps(combined_args),
             }
 
             return class_name, method_name, span_attributes
@@ -82,8 +82,8 @@ def trace_protocol[T](cls: type[T]) -> type[T]:
             class_name, method_name, span_attributes = create_span_context(self, *args, **kwargs)
 
             with tracing.span(f"{class_name}.{method_name}", span_attributes) as span:
+                count = 0
                 try:
-                    count = 0
                     async for item in method(self, *args, **kwargs):
                         yield item
                         count += 1

llama_stack/testing/api_recorder.py

@@ -37,7 +37,7 @@ _id_counters: dict[str, dict[str, int]] = {}
 # Test context uses ContextVar since it changes per-test and needs async isolation
 from openai.types.completion_choice import CompletionChoice
 
-from llama_stack.core.testing_context import get_test_context
+from llama_stack.core.testing_context import get_test_context, is_debug_mode
 
 # update the "finish_reason" field, since its type definition is wrong (no None is accepted)
 CompletionChoice.model_fields["finish_reason"].annotation = Literal["stop", "length", "content_filter"] | None
@@ -146,6 +146,7 @@ def normalize_inference_request(method: str, url: str, headers: dict[str, Any],
 
     body_for_hash = _normalize_body_for_hash(body)
 
+    test_id = get_test_context()
     normalized: dict[str, Any] = {
         "method": method.upper(),
         "endpoint": parsed.path,
@@ -154,10 +155,20 @@ def normalize_inference_request(method: str, url: str, headers: dict[str, Any],
 
     # Include test_id for isolation, except for shared infrastructure endpoints
     if parsed.path not in ("/api/tags", "/v1/models"):
-        normalized["test_id"] = get_test_context()
+        normalized["test_id"] = test_id
 
     normalized_json = json.dumps(normalized, sort_keys=True)
-    return hashlib.sha256(normalized_json.encode()).hexdigest()
+    request_hash = hashlib.sha256(normalized_json.encode()).hexdigest()
+
+    if is_debug_mode():
+        logger.info("[RECORDING DEBUG] Hash computation:")
+        logger.info(f"  Test ID: {test_id}")
+        logger.info(f"  Method: {method.upper()}")
+        logger.info(f"  Endpoint: {parsed.path}")
+        logger.info(f"  Model: {body.get('model', 'N/A')}")
+        logger.info(f"  Computed hash: {request_hash}")
+
+    return request_hash
 
 
 def normalize_tool_request(provider_name: str, tool_name: str, kwargs: dict[str, Any]) -> str:
@@ -212,6 +223,11 @@ def patch_httpx_for_test_id():
             provider_data["__test_id"] = test_id
             request.headers["X-LlamaStack-Provider-Data"] = json.dumps(provider_data)
 
+            if is_debug_mode():
+                logger.info("[RECORDING DEBUG] Injected test ID into request header:")
+                logger.info(f"  Test ID: {test_id}")
+                logger.info(f"  URL: {request.url}")
+
         return None
 
     LlamaStackClient._prepare_request = patched_prepare_request
@@ -355,12 +371,35 @@ class ResponseStorage:
             test_file = test_id.split("::")[0]  # Remove test function part
             test_dir = Path(test_file).parent  # Get parent directory
 
-            # Put recordings in a "recordings" subdirectory of the test's parent dir
-            # e.g., "tests/integration/inference" -> "tests/integration/inference/recordings"
-            return test_dir / "recordings"
+            if self.base_dir.is_absolute():
+                repo_root = self.base_dir.parent.parent.parent
+                result = repo_root / test_dir / "recordings"
+                if is_debug_mode():
+                    logger.info("[RECORDING DEBUG] Path resolution (absolute base_dir):")
+                    logger.info(f"  Test ID: {test_id}")
+                    logger.info(f"  Base dir: {self.base_dir}")
+                    logger.info(f"  Repo root: {repo_root}")
+                    logger.info(f"  Test file: {test_file}")
+                    logger.info(f"  Test dir: {test_dir}")
+                    logger.info(f"  Recordings dir: {result}")
+                return result
+            else:
+                result = test_dir / "recordings"
+                if is_debug_mode():
+                    logger.info("[RECORDING DEBUG] Path resolution (relative base_dir):")
+                    logger.info(f"  Test ID: {test_id}")
+                    logger.info(f"  Base dir: {self.base_dir}")
+                    logger.info(f"  Test dir: {test_dir}")
+                    logger.info(f"  Recordings dir: {result}")
+                return result
         else:
             # Fallback for non-test contexts
-            return self.base_dir / "recordings"
+            result = self.base_dir / "recordings"
+            if is_debug_mode():
+                logger.info("[RECORDING DEBUG] Path resolution (no test context):")
+                logger.info(f"  Base dir: {self.base_dir}")
+                logger.info(f"  Recordings dir: {result}")
+            return result
 
     def _ensure_directory(self):
         """Ensure test-specific directories exist."""
@@ -395,6 +434,13 @@ class ResponseStorage:
 
         response_path = responses_dir / response_file
 
+        if is_debug_mode():
+            logger.info("[RECORDING DEBUG] Storing recording:")
+            logger.info(f"  Request hash: {request_hash}")
+            logger.info(f"  File: {response_path}")
+            logger.info(f"  Test ID: {get_test_context()}")
+            logger.info(f"  Endpoint: {endpoint}")
+
         # Save response to JSON file with metadata
         with open(response_path, "w") as f:
             json.dump(
@@ -423,16 +469,33 @@ class ResponseStorage:
         test_dir = self._get_test_dir()
         response_path = test_dir / response_file
 
+        if is_debug_mode():
+            logger.info("[RECORDING DEBUG] Looking up recording:")
+            logger.info(f"  Request hash: {request_hash}")
+            logger.info(f"  Primary path: {response_path}")
+            logger.info(f"  Primary exists: {response_path.exists()}")
+
         if response_path.exists():
+            if is_debug_mode():
+                logger.info("  Found in primary location")
             return _recording_from_file(response_path)
 
         # Fallback to base recordings directory (for session-level recordings)
         fallback_dir = self.base_dir / "recordings"
         fallback_path = fallback_dir / response_file
 
+        if is_debug_mode():
+            logger.info(f"  Fallback path: {fallback_path}")
+            logger.info(f"  Fallback exists: {fallback_path.exists()}")
+
         if fallback_path.exists():
+            if is_debug_mode():
+                logger.info("  Found in fallback location")
             return _recording_from_file(fallback_path)
 
+        if is_debug_mode():
+            logger.info("  Recording not found in either location")
+
         return None
 
     def _model_list_responses(self, request_hash: str) -> list[dict[str, Any]]:
@@ -588,6 +651,13 @@ async def _patched_inference_method(original_method, self, client_type, endpoint
     mode = _current_mode
     storage = _current_storage
 
+    if is_debug_mode():
+        logger.info("[RECORDING DEBUG] Entering inference method:")
+        logger.info(f"  Mode: {mode}")
+        logger.info(f"  Client type: {client_type}")
+        logger.info(f"  Endpoint: {endpoint}")
+        logger.info(f"  Test context: {get_test_context()}")
+
     if mode == APIRecordingMode.LIVE or storage is None:
         if endpoint == "/v1/models":
             return original_method(self, *args, **kwargs)
@@ -643,6 +713,18 @@ async def _patched_inference_method(original_method, self, client_type, endpoint
                 return response_body
         elif mode == APIRecordingMode.REPLAY:
             # REPLAY mode requires recording to exist
+            if is_debug_mode():
+                logger.error("[RECORDING DEBUG] Recording not found!")
+                logger.error(f"  Mode: {mode}")
+                logger.error(f"  Request hash: {request_hash}")
+                logger.error(f"  Method: {method}")
+                logger.error(f"  URL: {url}")
+                logger.error(f"  Endpoint: {endpoint}")
+                logger.error(f"  Model: {body.get('model', 'unknown')}")
+                logger.error(f"  Test context: {get_test_context()}")
+                logger.error(
+                    f"  Stack config type: {os.environ.get('LLAMA_STACK_TEST_STACK_CONFIG_TYPE', 'library_client')}"
+                )
             raise RuntimeError(
                 f"Recording not found for request hash: {request_hash}\n"
                 f"Model: {body.get('model', 'unknown')} | Request: {method} {url}\n"

llama_stack/ui/package.json

@@ -43,16 +43,16 @@
     "@testing-library/dom": "^10.4.1",
     "@testing-library/jest-dom": "^6.8.0",
     "@testing-library/react": "^16.3.0",
-    "@types/jest": "^29.5.14",
+    "@types/jest": "^30.0.0",
     "@types/node": "^24",
     "@types/react": "^19",
     "@types/react-dom": "^19",
     "eslint": "^9",
-    "eslint-config-next": "15.5.2",
+    "eslint-config-next": "15.5.6",
     "eslint-config-prettier": "^10.1.8",
     "eslint-plugin-prettier": "^5.5.4",
-    "jest": "^29.7.0",
-    "jest-environment-jsdom": "^30.1.2",
+    "jest": "^30.2.0",
+    "jest-environment-jsdom": "^30.2.0",
     "prettier": "3.6.2",
     "tailwindcss": "^4",
     "ts-node": "^10.9.2",

scripts/diagnose_recordings.py

@@ -0,0 +1,370 @@
+#!/usr/bin/env python3
+# 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.
+
+"""
+Diagnostic tool for debugging test recording issues.
+
+Usage:
+    # Find where a hash would be looked up
+    ./scripts/diagnose_recordings.py find-hash 7526c930eab04ce337496a26cd15f2591d7943035f2527182861643da9b837a7
+
+    # Show what's in a recording file
+    ./scripts/diagnose_recordings.py show tests/integration/agents/recordings/7526c930....json
+
+    # List all recordings for a test
+    ./scripts/diagnose_recordings.py list-test "tests/integration/agents/test_agents.py::test_custom_tool"
+
+    # Explain lookup paths for a test
+    ./scripts/diagnose_recordings.py explain-paths --test-id "tests/integration/agents/test_agents.py::test_foo"
+
+    # Compare request hash computation
+    ./scripts/diagnose_recordings.py compute-hash --endpoint /v1/chat/completions --method POST --body '{"model":"llama3.2:3b"}' --test-id "..."
+"""
+
+import argparse
+import json
+import sys
+from pathlib import Path
+
+# Add parent directory to path to import from llama_stack
+REPO_ROOT = Path(__file__).parent.parent
+sys.path.insert(0, str(REPO_ROOT))
+
+try:
+    from llama_stack.testing.api_recorder import normalize_inference_request
+except ImportError:
+    normalize_inference_request = None
+
+
+def find_hash(hash_value: str, base_dir: Path | None = None, test_id: str | None = None):
+    """Find where a hash would be looked up and what exists"""
+    if base_dir is None:
+        base_dir = REPO_ROOT / "tests/integration/common"
+
+    print(f"Searching for hash: {hash_value}\n")
+    print(f"Base dir: {base_dir} (absolute={base_dir.is_absolute()})")
+
+    # Compute test directory
+    if test_id:
+        test_file = test_id.split("::")[0]
+        test_dir = Path(test_file).parent
+
+        if base_dir.is_absolute():
+            repo_root = base_dir.parent.parent.parent
+            test_recordings_dir = repo_root / test_dir / "recordings"
+        else:
+            test_recordings_dir = test_dir / "recordings"
+        print(f"Test ID: {test_id}")
+        print(f"Test dir: {test_recordings_dir}\n")
+    else:
+        test_recordings_dir = base_dir / "recordings"
+        print("No test ID provided, using base dir\n")
+
+    # Check primary location
+    response_file = f"{hash_value}.json"
+    response_path = test_recordings_dir / response_file
+
+    print("Checking primary location:")
+    print(f"  {response_path}")
+    if response_path.exists():
+        print("  EXISTS")
+        print("\nFound! Contents:")
+        show_recording(response_path)
+        return True
+    else:
+        print("  Does not exist")
+
+    # Check fallback location
+    fallback_dir = base_dir / "recordings"
+    fallback_path = fallback_dir / response_file
+
+    print("\nChecking fallback location:")
+    print(f"  {fallback_path}")
+    if fallback_path.exists():
+        print("  EXISTS")
+        print("\nFound in fallback! Contents:")
+        show_recording(fallback_path)
+        return True
+    else:
+        print("  Does not exist")
+
+    # Show what files DO exist
+    print(f"\nFiles in test directory ({test_recordings_dir}):")
+    if test_recordings_dir.exists():
+        json_files = list(test_recordings_dir.glob("*.json"))
+        if json_files:
+            for f in json_files[:20]:
+                print(f"  - {f.name}")
+            if len(json_files) > 20:
+                print(f"  ... and {len(json_files) - 20} more")
+        else:
+            print("  (empty)")
+    else:
+        print("  Directory does not exist")
+
+    print(f"\nFiles in fallback directory ({fallback_dir}):")
+    if fallback_dir.exists():
+        json_files = list(fallback_dir.glob("*.json"))
+        if json_files:
+            for f in json_files[:20]:
+                print(f"  - {f.name}")
+            if len(json_files) > 20:
+                print(f"  ... and {len(json_files) - 20} more")
+        else:
+            print("  (empty)")
+    else:
+        print("  Directory does not exist")
+
+    # Try partial hash match
+    print("\nLooking for partial matches (first 16 chars)...")
+    partial = hash_value[:16]
+    matches = []
+
+    for dir_to_search in [test_recordings_dir, fallback_dir]:
+        if dir_to_search.exists():
+            for f in dir_to_search.glob("*.json"):
+                if f.stem.startswith(partial):
+                    matches.append(f)
+
+    if matches:
+        print(f"Found {len(matches)} partial match(es):")
+        for m in matches:
+            print(f"  {m}")
+    else:
+        print("No partial matches found")
+
+    return False
+
+
+def show_recording(file_path: Path):
+    """Show contents of a recording file"""
+    if not file_path.exists():
+        print(f"File does not exist: {file_path}")
+        return
+
+    with open(file_path) as f:
+        data = json.load(f)
+
+    print(f"\nRecording: {file_path.name}\n")
+    print(f"Test ID: {data.get('test_id', 'N/A')}")
+    print("\nRequest:")
+    req = data.get("request", {})
+    print(f"  Method: {req.get('method', 'N/A')}")
+    print(f"  URL: {req.get('url', 'N/A')}")
+    print(f"  Endpoint: {req.get('endpoint', 'N/A')}")
+    print(f"  Model: {req.get('model', 'N/A')}")
+
+    body = req.get("body", {})
+    if body:
+        print("\nRequest Body:")
+        print(f"  Model: {body.get('model', 'N/A')}")
+        print(f"  Stream: {body.get('stream', 'N/A')}")
+        if "messages" in body:
+            print(f"  Messages: {len(body['messages'])} message(s)")
+            for i, msg in enumerate(body["messages"][:3]):
+                role = msg.get("role", "unknown")
+                content = msg.get("content", "")
+                if isinstance(content, str):
+                    preview = content[:80] + "..." if len(content) > 80 else content
+                else:
+                    preview = f"[{type(content).__name__}]"
+                print(f"    [{i}] {role}: {preview}")
+        if "tools" in body:
+            print(f"  Tools: {len(body['tools'])} tool(s)")
+
+    response = data.get("response", {})
+    if response:
+        print("\nResponse:")
+        print(f"  Is streaming: {response.get('is_streaming', False)}")
+        response_body = response.get("body", {})
+        if isinstance(response_body, dict):
+            if "__type__" in response_body:
+                print(f"  Type: {response_body['__type__']}")
+            if "__data__" in response_body:
+                response_data = response_body["__data__"]
+                if "choices" in response_data:
+                    print(f"  Choices: {len(response_data['choices'])}")
+                if "usage" in response_data:
+                    usage = response_data["usage"]
+                    print(f"  Usage: in={usage.get('input_tokens')}, out={usage.get('output_tokens')}")
+
+
+def list_test_recordings(test_id: str, base_dir: Path | None = None):
+    """List all recordings for a specific test"""
+    if base_dir is None:
+        base_dir = REPO_ROOT / "tests/integration/common"
+
+    test_file = test_id.split("::")[0]
+    test_dir = Path(test_file).parent
+
+    if base_dir.is_absolute():
+        repo_root = base_dir.parent.parent.parent
+        test_recordings_dir = repo_root / test_dir / "recordings"
+    else:
+        test_recordings_dir = test_dir / "recordings"
+
+    print(f"Recordings for test: {test_id}\n")
+    print(f"Directory: {test_recordings_dir}\n")
+
+    if not test_recordings_dir.exists():
+        print("Directory does not exist")
+        return
+
+    # Find all recordings for this specific test
+    recordings = []
+    for f in test_recordings_dir.glob("*.json"):
+        try:
+            with open(f) as fp:
+                data = json.load(fp)
+                if data.get("test_id") == test_id:
+                    recordings.append((f, data))
+        except Exception as e:
+            print(f"Could not read {f.name}: {e}")
+
+    if not recordings:
+        print("No recordings found for this exact test ID")
+        print("\nAll files in directory:")
+        for f in test_recordings_dir.glob("*.json"):
+            print(f"  - {f.name}")
+        return
+
+    print(f"Found {len(recordings)} recording(s):\n")
+    for f, data in recordings:
+        req = data.get("request", {})
+        print(f"  {f.name}")
+        print(f"     Endpoint: {req.get('endpoint', 'N/A')}")
+        print(f"     Model: {req.get('model', 'N/A')}")
+        print("")
+
+
+def explain_paths(test_id: str | None = None, base_dir: Path | None = None):
+    """Explain where recordings would be searched"""
+    if base_dir is None:
+        base_dir = REPO_ROOT / "tests/integration/common"
+
+    print("Recording Lookup Path Explanation\n")
+    print(f"Base directory: {base_dir}")
+    print(f"  Absolute: {base_dir.is_absolute()}")
+    print("")
+
+    if test_id:
+        print(f"Test ID: {test_id}")
+        test_file = test_id.split("::")[0]
+        print(f"  Test file: {test_file}")
+
+        test_dir = Path(test_file).parent
+        print(f"  Test dir (relative): {test_dir}")
+
+        if base_dir.is_absolute():
+            repo_root = base_dir.parent.parent.parent
+            print(f"  Repo root: {repo_root}")
+            test_recordings_dir = repo_root / test_dir / "recordings"
+            print(f"  Test recordings dir (absolute): {test_recordings_dir}")
+        else:
+            test_recordings_dir = test_dir / "recordings"
+            print(f"  Test recordings dir (relative): {test_recordings_dir}")
+
+        print("\nLookup order for recordings:")
+        print(f"  1. Test-specific: {test_recordings_dir}/<hash>.json")
+        print(f"  2. Fallback: {base_dir}/recordings/<hash>.json")
+
+    else:
+        print("No test ID provided")
+        print("\nLookup location:")
+        print(f"  {base_dir}/recordings/<hash>.json")
+
+
+def compute_hash(endpoint: str, method: str, body_json: str, test_id: str | None = None):
+    """Compute hash for a request"""
+    if normalize_inference_request is None:
+        print("Could not import normalize_inference_request from llama_stack.testing.api_recorder")
+        print("Make sure you're running from the repo root with proper PYTHONPATH")
+        return
+
+    try:
+        body = json.loads(body_json)
+    except json.JSONDecodeError as e:
+        print(f"Invalid JSON in body: {e}")
+        return
+
+    # Create a fake URL with the endpoint
+    url = f"http://example.com{endpoint}"
+
+    # Set test context if provided
+    if test_id:
+        from llama_stack.core.testing_context import set_test_context
+
+        set_test_context(test_id)
+
+    hash_result = normalize_inference_request(method, url, {}, body)
+
+    print("Hash Computation\n")
+    print(f"Method: {method}")
+    print(f"Endpoint: {endpoint}")
+    print(f"Test ID: {test_id or 'None (excluded from hash for model-list endpoints)'}")
+    print("\nBody:")
+    print(json.dumps(body, indent=2))
+    print(f"\nComputed Hash: {hash_result}")
+    print(f"\nLooking for file: {hash_result}.json")
+
+
+def main():
+    parser = argparse.ArgumentParser(
+        description="Diagnostic tool for test recording issues",
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        epilog=__doc__,
+    )
+
+    subparsers = parser.add_subparsers(dest="command", help="Command to run")
+
+    # find-hash command
+    find_parser = subparsers.add_parser("find-hash", help="Find where a hash would be looked up")
+    find_parser.add_argument("hash", help="Hash value to search for (full or partial)")
+    find_parser.add_argument("--test-id", help="Test ID to determine search paths")
+    find_parser.add_argument("--base-dir", type=Path, help="Base directory (default: tests/integration/common)")
+
+    # show command
+    show_parser = subparsers.add_parser("show", help="Show contents of a recording file")
+    show_parser.add_argument("file", type=Path, help="Path to recording JSON file")
+
+    # list-test command
+    list_parser = subparsers.add_parser("list-test", help="List all recordings for a test")
+    list_parser.add_argument("test_id", help="Full test ID (e.g., tests/integration/agents/test_agents.py::test_foo)")
+    list_parser.add_argument("--base-dir", type=Path, help="Base directory (default: tests/integration/common)")
+
+    # explain-paths command
+    explain_parser = subparsers.add_parser("explain-paths", help="Explain where recordings are searched")
+    explain_parser.add_argument("--test-id", help="Test ID to show paths for")
+    explain_parser.add_argument("--base-dir", type=Path, help="Base directory (default: tests/integration/common)")
+
+    # compute-hash command
+    hash_parser = subparsers.add_parser("compute-hash", help="Compute hash for a request")
+    hash_parser.add_argument("--endpoint", required=True, help="Endpoint path (e.g., /v1/chat/completions)")
+    hash_parser.add_argument("--method", default="POST", help="HTTP method (default: POST)")
+    hash_parser.add_argument("--body", required=True, help="Request body as JSON string")
+    hash_parser.add_argument("--test-id", help="Test ID (affects hash for non-model-list endpoints)")
+
+    args = parser.parse_args()
+
+    if not args.command:
+        parser.print_help()
+        return
+
+    if args.command == "find-hash":
+        find_hash(args.hash, args.base_dir, args.test_id)
+    elif args.command == "show":
+        show_recording(args.file)
+    elif args.command == "list-test":
+        list_test_recordings(args.test_id, args.base_dir)
+    elif args.command == "explain-paths":
+        explain_paths(args.test_id, args.base_dir)
+    elif args.command == "compute-hash":
+        compute_hash(args.endpoint, args.method, args.body, args.test_id)
+
+
+if __name__ == "__main__":
+    main()

scripts/docker.sh

@@ -0,0 +1,358 @@
+#!/bin/bash
+# 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.
+
+set -euo pipefail
+
+# Docker container management script for Llama Stack
+# Allows starting/stopping/restarting a Llama Stack docker container for testing
+
+# Default values
+DISTRO=""
+PORT=8321
+INFERENCE_MODE="replay"
+COMMAND=""
+USE_COPY_NOT_MOUNT=false
+NO_REBUILD=false
+
+# Function to display usage
+usage() {
+    cat <<EOF
+Usage: $0 COMMAND [OPTIONS]
+
+Commands:
+    start       Build and start the docker container
+    stop        Stop and remove the docker container
+    restart     Restart the docker container
+    status      Check if the container is running
+    logs        Show container logs (add -f to follow)
+
+Options:
+    --distro STRING          Distribution name (e.g., 'ci-tests', 'starter') (required for start/restart)
+    --port NUMBER            Port to run on (default: 8321)
+    --inference-mode STRING  Inference mode: replay, record-if-missing or record (default: replay)
+    --copy-source            Copy source into image instead of mounting (default: auto-detect CI, otherwise mount)
+    --no-rebuild             Skip building the image, just start the container (default: false)
+    --help                   Show this help message
+
+Examples:
+    # Start a docker container (local dev mode - mounts source, builds image)
+    $0 start --distro ci-tests
+
+    # Start without rebuilding (uses existing image)
+    $0 start --distro ci-tests --no-rebuild
+
+    # Start with source copied into image (like CI)
+    $0 start --distro ci-tests --copy-source
+
+    # Start with custom port
+    $0 start --distro starter --port 8080
+
+    # Check status
+    $0 status --distro ci-tests
+
+    # View logs
+    $0 logs --distro ci-tests
+
+    # Stop container
+    $0 stop --distro ci-tests
+
+    # Restart container
+    $0 restart --distro ci-tests
+
+Note: In CI environments (detected via CI or GITHUB_ACTIONS env vars), source is
+      automatically copied into the image. Locally, source is mounted for live development
+      unless --copy-source is specified.
+EOF
+}
+
+# Parse command (first positional arg)
+if [[ $# -eq 0 ]]; then
+    echo "Error: Command required"
+    usage
+    exit 1
+fi
+
+COMMAND="$1"
+shift
+
+# Validate command
+case "$COMMAND" in
+start | stop | restart | status | logs) ;;
+--help)
+    usage
+    exit 0
+    ;;
+*)
+    echo "Error: Unknown command: $COMMAND"
+    usage
+    exit 1
+    ;;
+esac
+
+# Parse options
+while [[ $# -gt 0 ]]; do
+    case $1 in
+    --distro)
+        DISTRO="$2"
+        shift 2
+        ;;
+    --port)
+        PORT="$2"
+        shift 2
+        ;;
+    --inference-mode)
+        INFERENCE_MODE="$2"
+        shift 2
+        ;;
+    --copy-source)
+        USE_COPY_NOT_MOUNT=true
+        shift
+        ;;
+    --no-rebuild)
+        NO_REBUILD=true
+        shift
+        ;;
+    --help)
+        usage
+        exit 0
+        ;;
+    *)
+        echo "Unknown option: $1"
+        usage
+        exit 1
+        ;;
+    esac
+done
+
+# Validate required parameters for commands that need them
+if [[ "$COMMAND" != "stop" && "$COMMAND" != "status" && "$COMMAND" != "logs" ]]; then
+    if [[ -z "$DISTRO" ]]; then
+        echo "Error: --distro is required for '$COMMAND' command"
+        usage
+        exit 1
+    fi
+fi
+
+# If distro not provided for stop/status/logs, try to infer from running containers
+if [[ -z "$DISTRO" && ("$COMMAND" == "stop" || "$COMMAND" == "status" || "$COMMAND" == "logs") ]]; then
+    # Look for any llama-stack-test-* container
+    RUNNING_CONTAINERS=$(docker ps -a --filter "name=llama-stack-test-" --format "{{.Names}}" | head -1)
+    if [[ -n "$RUNNING_CONTAINERS" ]]; then
+        DISTRO=$(echo "$RUNNING_CONTAINERS" | sed 's/llama-stack-test-//')
+        echo "Found running container for distro: $DISTRO"
+    else
+        echo "Error: --distro is required (no running containers found)"
+        usage
+        exit 1
+    fi
+fi
+
+# Remove docker: prefix if present
+DISTRO=$(echo "$DISTRO" | sed 's/^docker://')
+
+CONTAINER_NAME="llama-stack-test-$DISTRO"
+
+# Function to check if container is running
+is_container_running() {
+    docker ps --filter "name=^${CONTAINER_NAME}$" --format '{{.Names}}' | grep -q "^${CONTAINER_NAME}$"
+}
+
+# Function to check if container exists (running or stopped)
+container_exists() {
+    docker ps -a --filter "name=^${CONTAINER_NAME}$" --format '{{.Names}}' | grep -q "^${CONTAINER_NAME}$"
+}
+
+# Function to stop and remove container
+stop_container() {
+    if container_exists; then
+        echo "Stopping container: $CONTAINER_NAME"
+        docker stop "$CONTAINER_NAME" 2>/dev/null || true
+        echo "Removing container: $CONTAINER_NAME"
+        docker rm "$CONTAINER_NAME" 2>/dev/null || true
+        echo "✅ Container stopped and removed"
+    else
+        echo "⚠️  Container $CONTAINER_NAME does not exist"
+    fi
+}
+
+# Function to build docker image
+build_image() {
+    echo "=== Building Docker Image for distribution: $DISTRO ==="
+    # Get the repo root (parent of scripts directory)
+    SCRIPT_DIR=$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)
+    REPO_ROOT=$(cd "$SCRIPT_DIR/.." && pwd)
+
+    # Determine whether to copy or mount source
+    # Copy in CI or if explicitly requested, otherwise mount for live development
+    BUILD_ENV="LLAMA_STACK_DIR=$REPO_ROOT"
+    if [[ "$USE_COPY_NOT_MOUNT" == "true" ]] || [[ "${CI:-false}" == "true" ]] || [[ "${GITHUB_ACTIONS:-false}" == "true" ]]; then
+        echo "Copying source into image (USE_COPY_NOT_MOUNT=true, CI=${CI:-false}, GITHUB_ACTIONS=${GITHUB_ACTIONS:-false})"
+        BUILD_ENV="USE_COPY_NOT_MOUNT=true $BUILD_ENV"
+    else
+        echo "Will mount source for live development"
+    fi
+
+    if ! eval "$BUILD_ENV llama stack build --distro '$DISTRO' --image-type container"; then
+        echo "❌ Failed to build Docker image"
+        exit 1
+    fi
+    echo "✅ Docker image built successfully"
+}
+
+# Function to start container
+start_container() {
+    # Check if already running
+    if is_container_running; then
+        echo "⚠️  Container $CONTAINER_NAME is already running"
+        echo "URL: http://localhost:$PORT"
+        exit 0
+    fi
+
+    # Stop and remove if exists but not running
+    if container_exists; then
+        echo "Removing existing stopped container..."
+        docker rm "$CONTAINER_NAME" 2>/dev/null || true
+    fi
+
+    # Build the image unless --no-rebuild was specified
+    if [[ "$NO_REBUILD" == "true" ]]; then
+        echo "Skipping build (--no-rebuild specified)"
+        # Check if image exists (with or without localhost/ prefix)
+        if ! docker images --format "{{.Repository}}:{{.Tag}}" | grep -q "distribution-$DISTRO:dev$"; then
+            echo "❌ Error: Image distribution-$DISTRO:dev does not exist"
+            echo "Either build it first without --no-rebuild, or run: llama stack build --distro $DISTRO --image-type container"
+            exit 1
+        fi
+        echo "✅ Found existing image for distribution-$DISTRO:dev"
+    else
+        build_image
+    fi
+
+    echo ""
+    echo "=== Starting Docker Container ==="
+
+    # Get the repo root for volume mount
+    SCRIPT_DIR=$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)
+    REPO_ROOT=$(cd "$SCRIPT_DIR/.." && pwd)
+
+    # Determine the actual image name (may have localhost/ prefix)
+    IMAGE_NAME=$(docker images --format "{{.Repository}}:{{.Tag}}" | grep "distribution-$DISTRO:dev$" | head -1)
+    if [[ -z "$IMAGE_NAME" ]]; then
+        echo "❌ Error: Could not find image for distribution-$DISTRO:dev"
+        exit 1
+    fi
+    echo "Using image: $IMAGE_NAME"
+
+    # Build environment variables for docker run
+    DOCKER_ENV_VARS=""
+    DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e LLAMA_STACK_TEST_INFERENCE_MODE=$INFERENCE_MODE"
+    DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e LLAMA_STACK_TEST_STACK_CONFIG_TYPE=server"
+
+    # Set default OLLAMA_URL if not provided
+    # On macOS/Windows, use host.docker.internal to reach host from container
+    # On Linux with --network host, use localhost
+    if [[ "$(uname)" == "Darwin" ]] || [[ "$(uname)" == *"MINGW"* ]]; then
+        OLLAMA_URL="${OLLAMA_URL:-http://host.docker.internal:11434}"
+    else
+        OLLAMA_URL="${OLLAMA_URL:-http://localhost:11434}"
+    fi
+    DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e OLLAMA_URL=$OLLAMA_URL"
+
+    # Pass through API keys if they exist
+    [ -n "${TOGETHER_API_KEY:-}" ] && DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e TOGETHER_API_KEY=$TOGETHER_API_KEY"
+    [ -n "${FIREWORKS_API_KEY:-}" ] && DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e FIREWORKS_API_KEY=$FIREWORKS_API_KEY"
+    [ -n "${TAVILY_SEARCH_API_KEY:-}" ] && DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e TAVILY_SEARCH_API_KEY=$TAVILY_SEARCH_API_KEY"
+    [ -n "${OPENAI_API_KEY:-}" ] && DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e OPENAI_API_KEY=$OPENAI_API_KEY"
+    [ -n "${ANTHROPIC_API_KEY:-}" ] && DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e ANTHROPIC_API_KEY=$ANTHROPIC_API_KEY"
+    [ -n "${GROQ_API_KEY:-}" ] && DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e GROQ_API_KEY=$GROQ_API_KEY"
+    [ -n "${GEMINI_API_KEY:-}" ] && DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e GEMINI_API_KEY=$GEMINI_API_KEY"
+    [ -n "${SAFETY_MODEL:-}" ] && DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e SAFETY_MODEL=$SAFETY_MODEL"
+    [ -n "${SQLITE_STORE_DIR:-}" ] && DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e SQLITE_STORE_DIR=$SQLITE_STORE_DIR"
+
+    # Use --network host on Linux only (macOS doesn't support it properly)
+    NETWORK_MODE=""
+    if [[ "$(uname)" != "Darwin" ]] && [[ "$(uname)" != *"MINGW"* ]]; then
+        NETWORK_MODE="--network host"
+    fi
+
+    docker run -d $NETWORK_MODE --name "$CONTAINER_NAME" \
+        -p $PORT:$PORT \
+        $DOCKER_ENV_VARS \
+        -v "$REPO_ROOT":/app/llama-stack-source \
+        "$IMAGE_NAME" \
+        --port $PORT
+
+    echo "Waiting for container to start..."
+    for i in {1..30}; do
+        if curl -s http://localhost:$PORT/v1/health 2>/dev/null | grep -q "OK"; then
+            echo "✅ Container started successfully"
+            echo ""
+            echo "=== Container Information ==="
+            echo "Container name: $CONTAINER_NAME"
+            echo "URL: http://localhost:$PORT"
+            echo "Health check: http://localhost:$PORT/v1/health"
+            echo ""
+            echo "To view logs: $0 logs --distro $DISTRO"
+            echo "To stop: $0 stop --distro $DISTRO"
+            return 0
+        fi
+        if [[ $i -eq 30 ]]; then
+            echo "❌ Container failed to start within timeout"
+            echo "Showing container logs:"
+            docker logs "$CONTAINER_NAME"
+            exit 1
+        fi
+        sleep 1
+    done
+}
+
+# Execute command
+case "$COMMAND" in
+start)
+    start_container
+    ;;
+stop)
+    stop_container
+    ;;
+restart)
+    echo "Restarting container: $CONTAINER_NAME"
+    stop_container
+    echo ""
+    start_container
+    ;;
+status)
+    if is_container_running; then
+        echo "✅ Container $CONTAINER_NAME is running"
+        echo "URL: http://localhost:$PORT"
+        # Try to get the actual port from the container
+        ACTUAL_PORT=$(docker port "$CONTAINER_NAME" 2>/dev/null | grep "8321/tcp" | cut -d':' -f2 | head -1)
+        if [[ -n "$ACTUAL_PORT" ]]; then
+            echo "Port: $ACTUAL_PORT"
+        fi
+    elif container_exists; then
+        echo "⚠️  Container $CONTAINER_NAME exists but is not running"
+        echo "Start it with: $0 start --distro $DISTRO"
+    else
+        echo "❌ Container $CONTAINER_NAME does not exist"
+        echo "Start it with: $0 start --distro $DISTRO"
+    fi
+    ;;
+logs)
+    if container_exists; then
+        echo "=== Logs for $CONTAINER_NAME ==="
+        # Check if -f flag was passed after 'logs' command
+        if [[ "${1:-}" == "-f" || "${1:-}" == "--follow" ]]; then
+            docker logs --tail 100 --follow "$CONTAINER_NAME"
+        else
+            docker logs --tail 100 "$CONTAINER_NAME"
+        fi
+    else
+        echo "❌ Container $CONTAINER_NAME does not exist"
+        exit 1
+    fi
+    ;;
+esac

scripts/install.sh

@@ -5,10 +5,10 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-[ -z "$BASH_VERSION" ] && {
-  echo "This script must be run with bash" >&2
-  exit 1
-}
+[ -z "${BASH_VERSION:-}" ] && exec /usr/bin/env bash "$0" "$@"
+if set -o | grep -Eq 'posix[[:space:]]+on'; then
+  exec /usr/bin/env bash "$0" "$@"
+fi
 
 set -Eeuo pipefail
 
@@ -18,12 +18,110 @@ MODEL_ALIAS="llama3.2:3b"
 SERVER_IMAGE="docker.io/llamastack/distribution-starter:latest"
 WAIT_TIMEOUT=30
 TEMP_LOG=""
+WITH_TELEMETRY=true
+TELEMETRY_SERVICE_NAME="llama-stack"
+TELEMETRY_SINKS="otel_trace,otel_metric"
+OTEL_EXPORTER_OTLP_ENDPOINT="http://otel-collector:4318"
+TEMP_TELEMETRY_DIR=""
+
+materialize_telemetry_configs() {
+  local dest="$1"
+  mkdir -p "$dest"
+  local otel_cfg="${dest}/otel-collector-config.yaml"
+  local prom_cfg="${dest}/prometheus.yml"
+  local graf_cfg="${dest}/grafana-datasources.yaml"
+
+  for asset in "$otel_cfg" "$prom_cfg" "$graf_cfg"; do
+    if [ -e "$asset" ]; then
+      die "Telemetry asset ${asset} already exists; refusing to overwrite"
+    fi
+  done
+
+  cat <<'EOF' > "$otel_cfg"
+receivers:
+  otlp:
+    protocols:
+      grpc:
+        endpoint: 0.0.0.0:4317
+      http:
+        endpoint: 0.0.0.0:4318
+
+processors:
+  batch:
+    timeout: 1s
+    send_batch_size: 1024
+
+exporters:
+  # Export traces to Jaeger
+  otlp/jaeger:
+    endpoint: jaeger:4317
+    tls:
+      insecure: true
+
+  # Export metrics to Prometheus
+  prometheus:
+    endpoint: 0.0.0.0:9464
+    namespace: llama_stack
+
+  # Debug exporter for troubleshooting
+  debug:
+    verbosity: detailed
+
+service:
+  pipelines:
+    traces:
+      receivers: [otlp]
+      processors: [batch]
+      exporters: [otlp/jaeger, debug]
+
+    metrics:
+      receivers: [otlp]
+      processors: [batch]
+      exporters: [prometheus, debug]
+EOF
+
+  cat <<'EOF' > "$prom_cfg"
+global:
+  scrape_interval: 15s
+  evaluation_interval: 15s
+
+scrape_configs:
+  - job_name: 'prometheus'
+    static_configs:
+      - targets: ['localhost:9090']
+
+  - job_name: 'otel-collector'
+    static_configs:
+      - targets: ['otel-collector:9464']
+EOF
+
+  cat <<'EOF' > "$graf_cfg"
+apiVersion: 1
+
+datasources:
+  - name: Prometheus
+    type: prometheus
+    access: proxy
+    url: http://prometheus:9090
+    isDefault: true
+    editable: true
+
+  - name: Jaeger
+    type: jaeger
+    access: proxy
+    url: http://jaeger:16686
+    editable: true
+EOF
+}
 
 # Cleanup function to remove temporary files
 cleanup() {
   if [ -n "$TEMP_LOG" ] && [ -f "$TEMP_LOG" ]; then
     rm -f "$TEMP_LOG"
   fi
+  if [ -n "$TEMP_TELEMETRY_DIR" ] && [ -d "$TEMP_TELEMETRY_DIR" ]; then
+    rm -rf "$TEMP_TELEMETRY_DIR"
+  fi
 }
 
 # Set up trap to clean up on exit, error, or interrupt
@@ -32,7 +130,7 @@ trap cleanup EXIT ERR INT TERM
 log(){ printf "\e[1;32m%s\e[0m\n" "$*"; }
 die(){
   printf "\e[1;31m❌ %s\e[0m\n" "$*" >&2
-  printf "\e[1;31m🐛 Report an issue @ https://github.com/meta-llama/llama-stack/issues if you think it's a bug\e[0m\n" >&2
+  printf "\e[1;31m🐛 Report an issue @ https://github.com/llamastack/llama-stack/issues if you think it's a bug\e[0m\n" >&2
   exit 1
 }
 
@@ -89,6 +187,12 @@ Options:
     -m, --model MODEL          Model alias to use (default: ${MODEL_ALIAS})
     -i, --image IMAGE          Server image (default: ${SERVER_IMAGE})
     -t, --timeout SECONDS      Service wait timeout in seconds (default: ${WAIT_TIMEOUT})
+    --with-telemetry           Provision Jaeger, OTEL Collector, Prometheus, and Grafana (default: enabled)
+    --no-telemetry, --without-telemetry
+                              Skip provisioning the telemetry stack
+    --telemetry-service NAME   Service name reported to telemetry (default: ${TELEMETRY_SERVICE_NAME})
+    --telemetry-sinks SINKS    Comma-separated telemetry sinks (default: ${TELEMETRY_SINKS})
+    --otel-endpoint URL        OTLP endpoint provided to Llama Stack (default: ${OTEL_EXPORTER_OTLP_ENDPOINT})
     -h, --help                 Show this help message
 
 For more information:
@@ -127,6 +231,26 @@ while [[ $# -gt 0 ]]; do
             WAIT_TIMEOUT="$2"
             shift 2
             ;;
+        --with-telemetry)
+            WITH_TELEMETRY=true
+            shift
+            ;;
+        --no-telemetry|--without-telemetry)
+            WITH_TELEMETRY=false
+            shift
+            ;;
+        --telemetry-service)
+            TELEMETRY_SERVICE_NAME="$2"
+            shift 2
+            ;;
+        --telemetry-sinks)
+            TELEMETRY_SINKS="$2"
+            shift 2
+            ;;
+        --otel-endpoint)
+            OTEL_EXPORTER_OTLP_ENDPOINT="$2"
+            shift 2
+            ;;
         *)
             die "Unknown option: $1"
             ;;
@@ -171,7 +295,11 @@ if [ "$ENGINE" = "podman" ] && [ "$(uname -s)" = "Darwin" ]; then
 fi
 
 # Clean up any leftovers from earlier runs
-for name in ollama-server llama-stack; do
+containers=(ollama-server llama-stack)
+if [ "$WITH_TELEMETRY" = true ]; then
+  containers+=(jaeger otel-collector prometheus grafana)
+fi
+for name in "${containers[@]}"; do
   ids=$($ENGINE ps -aq --filter "name=^${name}$")
   if [ -n "$ids" ]; then
     log "⚠️  Found existing container(s) for '${name}', removing..."
@@ -191,6 +319,64 @@ if ! $ENGINE network inspect llama-net >/dev/null 2>&1; then
   fi
 fi
 
+###############################################################################
+# Telemetry Stack
+###############################################################################
+if [ "$WITH_TELEMETRY" = true ]; then
+  TEMP_TELEMETRY_DIR="$(mktemp -d)"
+  TELEMETRY_ASSETS_DIR="$TEMP_TELEMETRY_DIR"
+  log "🧰 Materializing telemetry configs..."
+  materialize_telemetry_configs "$TELEMETRY_ASSETS_DIR"
+
+  log "📡 Starting telemetry stack..."
+
+  if ! execute_with_log $ENGINE run -d "${PLATFORM_OPTS[@]}" --name jaeger \
+    --network llama-net \
+    -e COLLECTOR_ZIPKIN_HOST_PORT=:9411 \
+    -p 16686:16686 \
+    -p 14250:14250 \
+    -p 9411:9411 \
+    docker.io/jaegertracing/all-in-one:latest > /dev/null 2>&1; then
+    die "Jaeger startup failed"
+  fi
+
+  if ! execute_with_log $ENGINE run -d "${PLATFORM_OPTS[@]}" --name otel-collector \
+    --network llama-net \
+    -p 4318:4318 \
+    -p 4317:4317 \
+    -p 9464:9464 \
+    -p 13133:13133 \
+    -v "${TELEMETRY_ASSETS_DIR}/otel-collector-config.yaml:/etc/otel-collector-config.yaml:Z" \
+    docker.io/otel/opentelemetry-collector-contrib:latest \
+    --config /etc/otel-collector-config.yaml > /dev/null 2>&1; then
+    die "OpenTelemetry Collector startup failed"
+  fi
+
+  if ! execute_with_log $ENGINE run -d "${PLATFORM_OPTS[@]}" --name prometheus \
+    --network llama-net \
+    -p 9090:9090 \
+    -v "${TELEMETRY_ASSETS_DIR}/prometheus.yml:/etc/prometheus/prometheus.yml:Z" \
+    docker.io/prom/prometheus:latest \
+    --config.file=/etc/prometheus/prometheus.yml \
+    --storage.tsdb.path=/prometheus \
+    --web.console.libraries=/etc/prometheus/console_libraries \
+    --web.console.templates=/etc/prometheus/consoles \
+    --storage.tsdb.retention.time=200h \
+    --web.enable-lifecycle > /dev/null 2>&1; then
+    die "Prometheus startup failed"
+  fi
+
+  if ! execute_with_log $ENGINE run -d "${PLATFORM_OPTS[@]}" --name grafana \
+    --network llama-net \
+    -p 3000:3000 \
+    -e GF_SECURITY_ADMIN_PASSWORD=admin \
+    -e GF_USERS_ALLOW_SIGN_UP=false \
+    -v "${TELEMETRY_ASSETS_DIR}/grafana-datasources.yaml:/etc/grafana/provisioning/datasources/datasources.yaml:Z" \
+    docker.io/grafana/grafana:11.0.0 > /dev/null 2>&1; then
+    die "Grafana startup failed"
+  fi
+fi
+
 ###############################################################################
 # 1. Ollama
 ###############################################################################
@@ -218,9 +404,19 @@ fi
 ###############################################################################
 # 2. Llama‑Stack
 ###############################################################################
+server_env_opts=()
+if [ "$WITH_TELEMETRY" = true ]; then
+  server_env_opts+=(
+    -e TELEMETRY_SINKS="${TELEMETRY_SINKS}"
+    -e OTEL_EXPORTER_OTLP_ENDPOINT="${OTEL_EXPORTER_OTLP_ENDPOINT}"
+    -e OTEL_SERVICE_NAME="${TELEMETRY_SERVICE_NAME}"
+  )
+fi
+
 cmd=( run -d "${PLATFORM_OPTS[@]}" --name llama-stack \
       --network llama-net \
       -p "${PORT}:${PORT}" \
+      "${server_env_opts[@]}" \
       -e OLLAMA_URL="http://ollama-server:${OLLAMA_PORT}" \
       "${SERVER_IMAGE}" --port "${PORT}")
 
@@ -244,5 +440,12 @@ log "👉  API endpoint: http://localhost:${PORT}"
 log "📖 Documentation: https://llamastack.github.io/latest/references/api_reference/index.html"
 log "💻 To access the llama stack CLI, exec into the container:"
 log "   $ENGINE exec -ti llama-stack bash"
+if [ "$WITH_TELEMETRY" = true ]; then
+  log "📡 Telemetry dashboards:"
+  log "   Jaeger UI:      http://localhost:16686"
+  log "   Prometheus UI:  http://localhost:9090"
+  log "   Grafana UI:     http://localhost:3000 (admin/admin)"
+  log "   OTEL Collector: http://localhost:4318"
+fi
 log "🐛 Report an issue @ https://github.com/llamastack/llama-stack/issues if you think it's a bug"
 log ""

scripts/integration-tests.sh

@@ -42,9 +42,12 @@ Setups are defined in tests/integration/setups.py and provide global configurati
 You can also specify subdirectories (of tests/integration) to select tests from, which will override the suite.
 
 Examples:
-    # Basic inference tests with ollama
+    # Basic inference tests with ollama (server mode)
     $0 --stack-config server:ci-tests --suite base --setup ollama
 
+    # Basic inference tests with docker
+    $0 --stack-config docker:ci-tests --suite base --setup ollama
+
     # Multiple test directories with vllm
     $0 --stack-config server:ci-tests --subdirs 'inference,agents' --setup vllm
 
@@ -153,7 +156,7 @@ echo "Setting SQLITE_STORE_DIR: $SQLITE_STORE_DIR"
 
 # Determine stack config type for api_recorder test isolation
 if [[ "$COLLECT_ONLY" == false ]]; then
-    if [[ "$STACK_CONFIG" == server:* ]]; then
+    if [[ "$STACK_CONFIG" == server:* ]] || [[ "$STACK_CONFIG" == docker:* ]]; then
         export LLAMA_STACK_TEST_STACK_CONFIG_TYPE="server"
         echo "Setting stack config type: server"
     else
@@ -229,6 +232,104 @@ if [[ "$STACK_CONFIG" == *"server:"* && "$COLLECT_ONLY" == false ]]; then
     trap stop_server EXIT ERR INT TERM
 fi
 
+# Start Docker Container if needed
+if [[ "$STACK_CONFIG" == *"docker:"* && "$COLLECT_ONLY" == false ]]; then
+    stop_container() {
+        echo "Stopping Docker container..."
+        container_name="llama-stack-test-$DISTRO"
+        if docker ps -a --format '{{.Names}}' | grep -q "^${container_name}$"; then
+            echo "Stopping and removing container: $container_name"
+            docker stop "$container_name" 2>/dev/null || true
+            docker rm "$container_name" 2>/dev/null || true
+        else
+            echo "No container named $container_name found"
+        fi
+        echo "Docker container stopped"
+    }
+
+    # Extract distribution name from docker:distro format
+    DISTRO=$(echo "$STACK_CONFIG" | sed 's/^docker://')
+    export LLAMA_STACK_PORT=8321
+
+    echo "=== Building Docker Image for distribution: $DISTRO ==="
+    # Set LLAMA_STACK_DIR to repo root
+    # USE_COPY_NOT_MOUNT copies files into image (for CI), otherwise mounts for live development
+    BUILD_ENV="LLAMA_STACK_DIR=$ROOT_DIR"
+    if [[ "${CI:-false}" == "true" ]] || [[ "${GITHUB_ACTIONS:-false}" == "true" ]]; then
+        echo "CI detected (CI=$CI, GITHUB_ACTIONS=$GITHUB_ACTIONS): copying source into image"
+        BUILD_ENV="USE_COPY_NOT_MOUNT=true $BUILD_ENV"
+    else
+        echo "Local mode: will mount source for live development"
+    fi
+
+    eval "$BUILD_ENV llama stack build --distro '$DISTRO' --image-type container"
+
+    if [ $? -ne 0 ]; then
+        echo "❌ Failed to build Docker image"
+        exit 1
+    fi
+
+    echo ""
+    echo "=== Starting Docker Container ==="
+    container_name="llama-stack-test-$DISTRO"
+
+    # Stop and remove existing container if it exists
+    docker stop "$container_name" 2>/dev/null || true
+    docker rm "$container_name" 2>/dev/null || true
+
+    # Build environment variables for docker run
+    DOCKER_ENV_VARS=""
+    DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e LLAMA_STACK_TEST_INFERENCE_MODE=$INFERENCE_MODE"
+    DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e LLAMA_STACK_TEST_STACK_CONFIG_TYPE=server"
+
+    # Pass through API keys if they exist
+    [ -n "${TOGETHER_API_KEY:-}" ] && DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e TOGETHER_API_KEY=$TOGETHER_API_KEY"
+    [ -n "${FIREWORKS_API_KEY:-}" ] && DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e FIREWORKS_API_KEY=$FIREWORKS_API_KEY"
+    [ -n "${TAVILY_SEARCH_API_KEY:-}" ] && DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e TAVILY_SEARCH_API_KEY=$TAVILY_SEARCH_API_KEY"
+    [ -n "${OPENAI_API_KEY:-}" ] && DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e OPENAI_API_KEY=$OPENAI_API_KEY"
+    [ -n "${ANTHROPIC_API_KEY:-}" ] && DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e ANTHROPIC_API_KEY=$ANTHROPIC_API_KEY"
+    [ -n "${GROQ_API_KEY:-}" ] && DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e GROQ_API_KEY=$GROQ_API_KEY"
+    [ -n "${GEMINI_API_KEY:-}" ] && DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e GEMINI_API_KEY=$GEMINI_API_KEY"
+    [ -n "${OLLAMA_URL:-}" ] && DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e OLLAMA_URL=$OLLAMA_URL"
+    [ -n "${SAFETY_MODEL:-}" ] && DOCKER_ENV_VARS="$DOCKER_ENV_VARS -e SAFETY_MODEL=$SAFETY_MODEL"
+
+    # Determine the actual image name (may have localhost/ prefix)
+    IMAGE_NAME=$(docker images --format "{{.Repository}}:{{.Tag}}" | grep "distribution-$DISTRO:dev$" | head -1)
+    if [[ -z "$IMAGE_NAME" ]]; then
+        echo "❌ Error: Could not find image for distribution-$DISTRO:dev"
+        exit 1
+    fi
+    echo "Using image: $IMAGE_NAME"
+
+    docker run -d --network host --name "$container_name" \
+        -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
+        $DOCKER_ENV_VARS \
+        -v $ROOT_DIR:/app/llama-stack-source \
+        "$IMAGE_NAME" \
+        --port $LLAMA_STACK_PORT
+
+    echo "Waiting for Docker container to start..."
+    for i in {1..30}; do
+        if curl -s http://localhost:$LLAMA_STACK_PORT/v1/health 2>/dev/null | grep -q "OK"; then
+            echo "✅ Docker container started successfully"
+            break
+        fi
+        if [[ $i -eq 30 ]]; then
+            echo "❌ Docker container failed to start"
+            echo "Container logs:"
+            docker logs "$container_name"
+            exit 1
+        fi
+        sleep 1
+    done
+    echo ""
+
+    # Update STACK_CONFIG to point to the running container
+    STACK_CONFIG="http://localhost:$LLAMA_STACK_PORT"
+
+    trap stop_container EXIT ERR INT TERM
+fi
+
 # Run tests
 echo "=== Running Integration Tests ==="
 EXCLUDE_TESTS="builtin_tool or safety_with_image or code_interpreter or test_rag"

tests/integration/batches/conftest.py

@@ -70,10 +70,15 @@ class BatchHelper:
     ):
         """Wait for a batch to reach a terminal status.
 
+        Uses exponential backoff polling strategy for efficient waiting:
+        - Starts with short intervals (0.1s) for fast batches (e.g., replay mode)
+        - Doubles interval each iteration up to a maximum
+        - Adapts automatically to both fast and slow batch processing
+
         Args:
             batch_id: The batch ID to monitor
             max_wait_time: Maximum time to wait in seconds (default: 60 seconds)
-            sleep_interval: Time to sleep between checks in seconds (default: 1/10th of max_wait_time, min 1s, max 15s)
+            sleep_interval: If provided, uses fixed interval instead of exponential backoff
             expected_statuses: Set of expected terminal statuses (default: {"completed"})
             timeout_action: Action on timeout - "fail" (pytest.fail) or "skip" (pytest.skip)
 
@@ -84,10 +89,6 @@ class BatchHelper:
             pytest.Failed: If batch reaches an unexpected status or timeout_action is "fail"
             pytest.Skipped: If timeout_action is "skip" on timeout or unexpected status
         """
-        if sleep_interval is None:
-            # Default to 1/10th of max_wait_time, with min 1s and max 15s
-            sleep_interval = max(1, min(15, max_wait_time // 10))
-
         if expected_statuses is None:
             expected_statuses = {"completed"}
 
@@ -95,6 +96,15 @@ class BatchHelper:
         unexpected_statuses = terminal_statuses - expected_statuses
 
         start_time = time.time()
+
+        # Use exponential backoff if no explicit sleep_interval provided
+        if sleep_interval is None:
+            current_interval = 0.1  # Start with 100ms
+            max_interval = 10.0  # Cap at 10 seconds
+        else:
+            current_interval = sleep_interval
+            max_interval = sleep_interval
+
         while time.time() - start_time < max_wait_time:
             current_batch = self.client.batches.retrieve(batch_id)
 
@@ -107,7 +117,11 @@ class BatchHelper:
                 else:
                     pytest.fail(error_msg)
 
-            time.sleep(sleep_interval)
+            time.sleep(current_interval)
+
+            # Exponential backoff: double the interval each time, up to max
+            if sleep_interval is None:
+                current_interval = min(current_interval * 2, max_interval)
 
         timeout_msg = f"Batch did not reach expected status {expected_statuses} within {max_wait_time} seconds"
         if timeout_action == "skip":

tests/integration/common/recordings/ab1a32474062bbad640ce43d02d6b61ed9f174c225597f0241cf120c47c7d2fa.json

@@ -0,0 +1,506 @@
+{
+  "test_id": null,
+  "request": {
+    "method": "POST",
+    "url": "http://0.0.0.0:11434/v1/v1/chat/completions",
+    "headers": {},
+    "body": {
+      "model": "llama3.2:3b-instruct-fp16",
+      "messages": [
+        {
+          "role": "system",
+          "content": "You are a helpful assistant"
+        },
+        {
+          "role": "user",
+          "content": "What is 2 + 2?"
+        },
+        {
+          "role": "assistant",
+          "content": "The answer to the equation 2 + 2 is 4."
+        },
+        {
+          "role": "user",
+          "content": "Tell me a short joke"
+        }
+      ],
+      "max_tokens": 0,
+      "stream": true
+    },
+    "endpoint": "/v1/chat/completions",
+    "model": "llama3.2:3b-instruct-fp16"
+  },
+  "response": {
+    "body": [
+      {
+        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
+        "__data__": {
+          "id": "rec-ab1a32474062",
+          "choices": [
+            {
+              "delta": {
+                "content": "Why",
+                "function_call": null,
+                "refusal": null,
+                "role": "assistant",
+                "tool_calls": null
+              },
+              "finish_reason": null,
+              "index": 0,
+              "logprobs": null
+            }
+          ],
+          "created": 0,
+          "model": "llama3.2:3b-instruct-fp16",
+          "object": "chat.completion.chunk",
+          "service_tier": null,
+          "system_fingerprint": "fp_ollama",
+          "usage": null
+        }
+      },
+      {
+        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
+        "__data__": {
+          "id": "rec-ab1a32474062",
+          "choices": [
+            {
+              "delta": {
+                "content": " did",
+                "function_call": null,
+                "refusal": null,
+                "role": "assistant",
+                "tool_calls": null
+              },
+              "finish_reason": null,
+              "index": 0,
+              "logprobs": null
+            }
+          ],
+          "created": 0,
+          "model": "llama3.2:3b-instruct-fp16",
+          "object": "chat.completion.chunk",
+          "service_tier": null,
+          "system_fingerprint": "fp_ollama",
+          "usage": null
+        }
+      },
+      {
+        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
+        "__data__": {
+          "id": "rec-ab1a32474062",
+          "choices": [
+            {
+              "delta": {
+                "content": " the",
+                "function_call": null,
+                "refusal": null,
+                "role": "assistant",
+                "tool_calls": null
+              },
+              "finish_reason": null,
+              "index": 0,
+              "logprobs": null
+            }
+          ],
+          "created": 0,
+          "model": "llama3.2:3b-instruct-fp16",
+          "object": "chat.completion.chunk",
+          "service_tier": null,
+          "system_fingerprint": "fp_ollama",
+          "usage": null
+        }
+      },
+      {
+        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
+        "__data__": {
+          "id": "rec-ab1a32474062",
+          "choices": [
+            {
+              "delta": {
+                "content": " scare",
+                "function_call": null,
+                "refusal": null,
+                "role": "assistant",
+                "tool_calls": null
+              },
+              "finish_reason": null,
+              "index": 0,
+              "logprobs": null
+            }
+          ],
+          "created": 0,
+          "model": "llama3.2:3b-instruct-fp16",
+          "object": "chat.completion.chunk",
+          "service_tier": null,
+          "system_fingerprint": "fp_ollama",
+          "usage": null
+        }
+      },
+      {
+        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
+        "__data__": {
+          "id": "rec-ab1a32474062",
+          "choices": [
+            {
+              "delta": {
+                "content": "crow",
+                "function_call": null,
+                "refusal": null,
+                "role": "assistant",
+                "tool_calls": null
+              },
+              "finish_reason": null,
+              "index": 0,
+              "logprobs": null
+            }
+          ],
+          "created": 0,
+          "model": "llama3.2:3b-instruct-fp16",
+          "object": "chat.completion.chunk",
+          "service_tier": null,
+          "system_fingerprint": "fp_ollama",
+          "usage": null
+        }
+      },
+      {
+        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
+        "__data__": {
+          "id": "rec-ab1a32474062",
+          "choices": [
+            {
+              "delta": {
+                "content": " win",
+                "function_call": null,
+                "refusal": null,
+                "role": "assistant",
+                "tool_calls": null
+              },
+              "finish_reason": null,
+              "index": 0,
+              "logprobs": null
+            }
+          ],
+          "created": 0,
+          "model": "llama3.2:3b-instruct-fp16",
+          "object": "chat.completion.chunk",
+          "service_tier": null,
+          "system_fingerprint": "fp_ollama",
+          "usage": null
+        }
+      },
+      {
+        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
+        "__data__": {
+          "id": "rec-ab1a32474062",
+          "choices": [
+            {
+              "delta": {
+                "content": " an",
+                "function_call": null,
+                "refusal": null,
+                "role": "assistant",
+                "tool_calls": null
+              },
+              "finish_reason": null,
+              "index": 0,
+              "logprobs": null
+            }
+          ],
+          "created": 0,
+          "model": "llama3.2:3b-instruct-fp16",
+          "object": "chat.completion.chunk",
+          "service_tier": null,
+          "system_fingerprint": "fp_ollama",
+          "usage": null
+        }
+      },
+      {
+        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
+        "__data__": {
+          "id": "rec-ab1a32474062",
+          "choices": [
+            {
+              "delta": {
+                "content": " award",
+                "function_call": null,
+                "refusal": null,
+                "role": "assistant",
+                "tool_calls": null
+              },
+              "finish_reason": null,
+              "index": 0,
+              "logprobs": null
+            }
+          ],
+          "created": 0,
+          "model": "llama3.2:3b-instruct-fp16",
+          "object": "chat.completion.chunk",
+          "service_tier": null,
+          "system_fingerprint": "fp_ollama",
+          "usage": null
+        }
+      },
+      {
+        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
+        "__data__": {
+          "id": "rec-ab1a32474062",
+          "choices": [
+            {
+              "delta": {
+                "content": "?\n\n",
+                "function_call": null,
+                "refusal": null,
+                "role": "assistant",
+                "tool_calls": null
+              },
+              "finish_reason": null,
+              "index": 0,
+              "logprobs": null
+            }
+          ],
+          "created": 0,
+          "model": "llama3.2:3b-instruct-fp16",
+          "object": "chat.completion.chunk",
+          "service_tier": null,
+          "system_fingerprint": "fp_ollama",
+          "usage": null
+        }
+      },
+      {
+        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
+        "__data__": {
+          "id": "rec-ab1a32474062",
+          "choices": [
+            {
+              "delta": {
+                "content": "Because",
+                "function_call": null,
+                "refusal": null,
+                "role": "assistant",
+                "tool_calls": null
+              },
+              "finish_reason": null,
+              "index": 0,
+              "logprobs": null
+            }
+          ],
+          "created": 0,
+          "model": "llama3.2:3b-instruct-fp16",
+          "object": "chat.completion.chunk",
+          "service_tier": null,
+          "system_fingerprint": "fp_ollama",
+          "usage": null
+        }
+      },
+      {
+        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
+        "__data__": {
+          "id": "rec-ab1a32474062",
+          "choices": [
+            {
+              "delta": {
+                "content": " he",
+                "function_call": null,
+                "refusal": null,
+                "role": "assistant",
+                "tool_calls": null
+              },
+              "finish_reason": null,
+              "index": 0,
+              "logprobs": null
+            }
+          ],
+          "created": 0,
+          "model": "llama3.2:3b-instruct-fp16",
+          "object": "chat.completion.chunk",
+          "service_tier": null,
+          "system_fingerprint": "fp_ollama",
+          "usage": null
+        }
+      },
+      {
+        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
+        "__data__": {
+          "id": "rec-ab1a32474062",
+          "choices": [
+            {
+              "delta": {
+                "content": " was",
+                "function_call": null,
+                "refusal": null,
+                "role": "assistant",
+                "tool_calls": null
+              },
+              "finish_reason": null,
+              "index": 0,
+              "logprobs": null
+            }
+          ],
+          "created": 0,
+          "model": "llama3.2:3b-instruct-fp16",
+          "object": "chat.completion.chunk",
+          "service_tier": null,
+          "system_fingerprint": "fp_ollama",
+          "usage": null
+        }
+      },
+      {
+        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
+        "__data__": {
+          "id": "rec-ab1a32474062",
+          "choices": [
+            {
+              "delta": {
+                "content": " outstanding",
+                "function_call": null,
+                "refusal": null,
+                "role": "assistant",
+                "tool_calls": null
+              },
+              "finish_reason": null,
+              "index": 0,
+              "logprobs": null
+            }
+          ],
+          "created": 0,
+          "model": "llama3.2:3b-instruct-fp16",
+          "object": "chat.completion.chunk",
+          "service_tier": null,
+          "system_fingerprint": "fp_ollama",
+          "usage": null
+        }
+      },
+      {
+        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
+        "__data__": {
+          "id": "rec-ab1a32474062",
+          "choices": [
+            {
+              "delta": {
+                "content": " in",
+                "function_call": null,
+                "refusal": null,
+                "role": "assistant",
+                "tool_calls": null
+              },
+              "finish_reason": null,
+              "index": 0,
+              "logprobs": null
+            }
+          ],
+          "created": 0,
+          "model": "llama3.2:3b-instruct-fp16",
+          "object": "chat.completion.chunk",
+          "service_tier": null,
+          "system_fingerprint": "fp_ollama",
+          "usage": null
+        }
+      },
+      {
+        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
+        "__data__": {
+          "id": "rec-ab1a32474062",
+          "choices": [
+            {
+              "delta": {
+                "content": " his",
+                "function_call": null,
+                "refusal": null,
+                "role": "assistant",
+                "tool_calls": null
+              },
+              "finish_reason": null,
+              "index": 0,
+              "logprobs": null
+            }
+          ],
+          "created": 0,
+          "model": "llama3.2:3b-instruct-fp16",
+          "object": "chat.completion.chunk",
+          "service_tier": null,
+          "system_fingerprint": "fp_ollama",
+          "usage": null
+        }
+      },
+      {
+        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
+        "__data__": {
+          "id": "rec-ab1a32474062",
+          "choices": [
+            {
+              "delta": {
+                "content": " field",
+                "function_call": null,
+                "refusal": null,
+                "role": "assistant",
+                "tool_calls": null
+              },
+              "finish_reason": null,
+              "index": 0,
+              "logprobs": null
+            }
+          ],
+          "created": 0,
+          "model": "llama3.2:3b-instruct-fp16",
+          "object": "chat.completion.chunk",
+          "service_tier": null,
+          "system_fingerprint": "fp_ollama",
+          "usage": null
+        }
+      },
+      {
+        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
+        "__data__": {
+          "id": "rec-ab1a32474062",
+          "choices": [
+            {
+              "delta": {
+                "content": "!",
+                "function_call": null,
+                "refusal": null,
+                "role": "assistant",
+                "tool_calls": null
+              },
+              "finish_reason": null,
+              "index": 0,
+              "logprobs": null
+            }
+          ],
+          "created": 0,
+          "model": "llama3.2:3b-instruct-fp16",
+          "object": "chat.completion.chunk",
+          "service_tier": null,
+          "system_fingerprint": "fp_ollama",
+          "usage": null
+        }
+      },
+      {
+        "__type__": "openai.types.chat.chat_completion_chunk.ChatCompletionChunk",
+        "__data__": {
+          "id": "rec-ab1a32474062",
+          "choices": [
+            {
+              "delta": {
+                "content": "",
+                "function_call": null,
+                "refusal": null,
+                "role": "assistant",
+                "tool_calls": null
+              },
+              "finish_reason": "stop",
+              "index": 0,
+              "logprobs": null
+            }
+          ],
+          "created": 0,
+          "model": "llama3.2:3b-instruct-fp16",
+          "object": "chat.completion.chunk",
+          "service_tier": null,
+          "system_fingerprint": "fp_ollama",
+          "usage": null
+        }
+      }
+    ],
+    "is_streaming": true
+  }
+}

tests/integration/common/recordings/models-64a2277c90f0f42576f60c1030e3a020403d34a95f56931b792d5939f4cebc57-826d44c3.json

@@ -0,0 +1,88 @@
+{
+  "test_id": null,
+  "request": {
+    "method": "POST",
+    "url": "http://0.0.0.0:11434/v1/v1/models",
+    "headers": {},
+    "body": {},
+    "endpoint": "/v1/models",
+    "model": ""
+  },
+  "response": {
+    "body": [
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "llama3.2:3b-instruct-fp16",
+          "created": 1760453641,
+          "object": "model",
+          "owned_by": "library"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "qwen3:4b",
+          "created": 1757615302,
+          "object": "model",
+          "owned_by": "library"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "gpt-oss:latest",
+          "created": 1756395223,
+          "object": "model",
+          "owned_by": "library"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "nomic-embed-text:latest",
+          "created": 1756318548,
+          "object": "model",
+          "owned_by": "library"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "llama3.2:3b",
+          "created": 1755191039,
+          "object": "model",
+          "owned_by": "library"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "all-minilm:l6-v2",
+          "created": 1753968177,
+          "object": "model",
+          "owned_by": "library"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "llama3.2:1b",
+          "created": 1746124735,
+          "object": "model",
+          "owned_by": "library"
+        }
+      },
+      {
+        "__type__": "openai.types.model.Model",
+        "__data__": {
+          "id": "llama3.2:latest",
+          "created": 1746044170,
+          "object": "model",
+          "owned_by": "library"
+        }
+      }
+    ],
+    "is_streaming": false
+  }
+}

tests/integration/conftest.py

@@ -42,7 +42,9 @@ def pytest_sessionstart(session):
 
     # Set test stack config type for api_recorder test isolation
     stack_config = session.config.getoption("--stack-config", default=None)
-    if stack_config and (stack_config.startswith("server:") or stack_config.startswith("http")):
+    if stack_config and (
+        stack_config.startswith("server:") or stack_config.startswith("docker:") or stack_config.startswith("http")
+    ):
         os.environ["LLAMA_STACK_TEST_STACK_CONFIG_TYPE"] = "server"
         logger.info(f"Test stack config type: server (stack_config={stack_config})")
     else:
@@ -139,7 +141,9 @@ def pytest_addoption(parser):
             a 'pointer' to the stack. this can be either be:
             (a) a template name like `starter`, or
             (b) a path to a run.yaml file, or
-            (c) an adhoc config spec, e.g. `inference=fireworks,safety=llama-guard,agents=meta-reference`
+            (c) an adhoc config spec, e.g. `inference=fireworks,safety=llama-guard,agents=meta-reference`, or
+            (d) a server config like `server:ci-tests`, or
+            (e) a docker config like `docker:ci-tests` (builds and runs container)
             """
         ),
     )

tests/integration/telemetry/conftest.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.
+
+"""Telemetry test configuration using OpenTelemetry SDK exporters.
+
+This conftest provides in-memory telemetry collection for library_client mode only.
+Tests using these fixtures should skip in server mode since the in-memory collector
+cannot access spans from a separate server process.
+"""
+
+from typing import Any
+
+import opentelemetry.metrics as otel_metrics
+import opentelemetry.trace as otel_trace
+import pytest
+from opentelemetry import metrics, trace
+from opentelemetry.sdk.metrics import MeterProvider
+from opentelemetry.sdk.metrics.export import InMemoryMetricReader
+from opentelemetry.sdk.trace import ReadableSpan, TracerProvider
+from opentelemetry.sdk.trace.export import SimpleSpanProcessor
+from opentelemetry.sdk.trace.export.in_memory_span_exporter import InMemorySpanExporter
+
+import llama_stack.providers.inline.telemetry.meta_reference.telemetry as telemetry_module
+from llama_stack.testing.api_recorder import patch_httpx_for_test_id
+from tests.integration.fixtures.common import instantiate_llama_stack_client
+
+
+class TestCollector:
+    def __init__(self, span_exp, metric_read):
+        assert span_exp and metric_read
+        self.span_exporter = span_exp
+        self.metric_reader = metric_read
+
+    def get_spans(self) -> tuple[ReadableSpan, ...]:
+        return self.span_exporter.get_finished_spans()
+
+    def get_metrics(self) -> Any | None:
+        metrics = self.metric_reader.get_metrics_data()
+        if metrics and metrics.resource_metrics:
+            return metrics.resource_metrics[0].scope_metrics[0].metrics
+        return None
+
+    def clear(self) -> None:
+        self.span_exporter.clear()
+        self.metric_reader.get_metrics_data()
+
+
+@pytest.fixture(scope="session")
+def _telemetry_providers():
+    """Set up in-memory OTEL providers before llama_stack_client initializes."""
+    # Reset set-once flags to allow re-initialization
+    if hasattr(otel_trace, "_TRACER_PROVIDER_SET_ONCE"):
+        otel_trace._TRACER_PROVIDER_SET_ONCE._done = False  # type: ignore
+    if hasattr(otel_metrics, "_METER_PROVIDER_SET_ONCE"):
+        otel_metrics._METER_PROVIDER_SET_ONCE._done = False  # type: ignore
+
+    # Create in-memory exporters/readers
+    span_exporter = InMemorySpanExporter()
+    tracer_provider = TracerProvider()
+    tracer_provider.add_span_processor(SimpleSpanProcessor(span_exporter))
+    trace.set_tracer_provider(tracer_provider)
+
+    metric_reader = InMemoryMetricReader()
+    meter_provider = MeterProvider(metric_readers=[metric_reader])
+    metrics.set_meter_provider(meter_provider)
+
+    # Set module-level provider so TelemetryAdapter uses our in-memory providers
+    telemetry_module._TRACER_PROVIDER = tracer_provider
+
+    yield (span_exporter, metric_reader, tracer_provider, meter_provider)
+
+    telemetry_module._TRACER_PROVIDER = None
+    tracer_provider.shutdown()
+    meter_provider.shutdown()
+
+
+@pytest.fixture(scope="session")
+def llama_stack_client(_telemetry_providers, request):
+    """Override llama_stack_client to ensure in-memory telemetry providers are used."""
+    patch_httpx_for_test_id()
+    client = instantiate_llama_stack_client(request.session)
+
+    return client
+
+
+@pytest.fixture
+def mock_otlp_collector(_telemetry_providers):
+    """Provides access to telemetry data and clears between tests."""
+    span_exporter, metric_reader, _, _ = _telemetry_providers
+    collector = TestCollector(span_exporter, metric_reader)
+    yield collector
+    collector.clear()

tests/integration/telemetry/recordings/0de60cd6a6ec3dbfc4a7601e77be8083caf34f49147ad1c25efae1de3f0b25e5.json

@@ -0,0 +1,57 @@
+{
+  "test_id": "tests/integration/telemetry/test_openai_telemetry.py::test_openai_completion_creates_telemetry[txt=ollama/llama3.2:3b-instruct-fp16]",
+  "request": {
+    "method": "POST",
+    "url": "http://0.0.0.0:11434/v1/v1/chat/completions",
+    "headers": {},
+    "body": {
+      "model": "llama3.2:3b-instruct-fp16",
+      "messages": [
+        {
+          "role": "user",
+          "content": "Test OpenAI telemetry creation"
+        }
+      ],
+      "stream": false
+    },
+    "endpoint": "/v1/chat/completions",
+    "model": "llama3.2:3b-instruct-fp16"
+  },
+  "response": {
+    "body": {
+      "__type__": "openai.types.chat.chat_completion.ChatCompletion",
+      "__data__": {
+        "id": "rec-0de60cd6a6ec",
+        "choices": [
+          {
+            "finish_reason": "stop",
+            "index": 0,
+            "logprobs": null,
+            "message": {
+              "content": "I'm happy to help you with setting up and testing OpenAI's telemetry creation.\n\nOpenAI provides a feature called \"Telemetry\" which allows developers to collect data about their users' interactions with the model. To test this feature, we need to create a simple application that uses the OpenAI API and sends telemetry data to their servers.\n\nHere's an example code in Python that demonstrates how to create a simple telemetry creator:\n\n```python\nimport os\nfrom openai.api import API\n\n# Initialize the OpenAI API client\napi = API(os.environ['OPENAI_API_KEY'])\n\ndef create_user():\n    # Create a new user entity\n    user_entity = {\n        'id': 'user-123',\n        'name': 'John Doe',\n        'email': 'john.doe@example.com'\n    }\n    \n    # Send the user creation request to OpenAI\n    response = api.users.create(user_entity)\n    print(f\"User created: {response}\")\n\ndef create_transaction():\n    # Create a new transaction entity\n    transaction_entity = {\n        'id': 'tran-123',\n        'user_id': 'user-123',\n        'transaction_type': 'query'\n    }\n    \n    # Send the transaction creation request to OpenAI\n    response = api.transactions.create(transaction_entity)\n    print(f\"Transaction created: {response}\")\n\ndef send_telemetry_data():\n    # Create a new telemetry event entity\n    telemetry_event_entity = {\n        'id': 'telem-123',\n        'transaction_id': 'tran-123',\n        'data': '{ \"event\": \"test\", \"user_id\": 1 }'\n    }\n    \n    # Send the telemetry data to OpenAI\n    response = api.telemetry.create(telemetry_event_entity)\n    print(f\"Telemetry event sent: {response}\")\n\n# Test the telemetry creation\ncreate_user()\ncreate_transaction()\nsend_telemetry_data()\n```\n\nMake sure you replace `OPENAI_API_KEY` with your actual API key. Also, ensure that you have the OpenAI API client library installed by running `pip install openai`.\n\nOnce you've created the test code, run it and observe the behavior of the telemetry creation process.\n\nPlease let me know if you need further modifications or assistance!",
+              "refusal": null,
+              "role": "assistant",
+              "annotations": null,
+              "audio": null,
+              "function_call": null,
+              "tool_calls": null
+            }
+          }
+        ],
+        "created": 0,
+        "model": "llama3.2:3b-instruct-fp16",
+        "object": "chat.completion",
+        "service_tier": null,
+        "system_fingerprint": "fp_ollama",
+        "usage": {
+          "completion_tokens": 460,
+          "prompt_tokens": 30,
+          "total_tokens": 490,
+          "completion_tokens_details": null,
+          "prompt_tokens_details": null
+        }
+      }
+    },
+    "is_streaming": false
+  }
+}

tests/integration/telemetry/recordings/1fcfd86d8111374dc852cfdea6bfdb6a511f92cee84a6325b04ae84878512c30.json

@@ -0,0 +1,59 @@
+{
+  "test_id": "tests/integration/telemetry/test_completions.py::test_telemetry_format_completeness[txt=ollama/llama3.2:3b-instruct-fp16]",
+  "request": {
+    "method": "POST",
+    "url": "http://0.0.0.0:11434/v1/v1/chat/completions",
+    "headers": {},
+    "body": {
+      "model": "llama3.2:3b-instruct-fp16",
+      "messages": [
+        {
+          "role": "user",
+          "content": "Test trace openai with temperature 0.7"
+        }
+      ],
+      "max_tokens": 100,
+      "stream": false,
+      "temperature": 0.7
+    },
+    "endpoint": "/v1/chat/completions",
+    "model": "llama3.2:3b-instruct-fp16"
+  },
+  "response": {
+    "body": {
+      "__type__": "openai.types.chat.chat_completion.ChatCompletion",
+      "__data__": {
+        "id": "rec-1fcfd86d8111",
+        "choices": [
+          {
+            "finish_reason": "length",
+            "index": 0,
+            "logprobs": null,
+            "message": {
+              "content": "import torch\nfrom transformers import AutoModelForCausalLM, AutoTokenizer\n\n# Load the pre-trained model and tokenizer\nmodel_name = \"CompVis/transformers-base-uncased\"\nmodel = AutoModelForCausalLM.from_pretrained(model_name)\ntokenizer = AutoTokenizer.from_pretrained(model_name)\n\n# Set the temperature to 0.7\ntemperature = 0.7\n\n# Define a function to generate text\ndef generate_text(prompt, max_length=100):\n    input",
+              "refusal": null,
+              "role": "assistant",
+              "annotations": null,
+              "audio": null,
+              "function_call": null,
+              "tool_calls": null
+            }
+          }
+        ],
+        "created": 0,
+        "model": "llama3.2:3b-instruct-fp16",
+        "object": "chat.completion",
+        "service_tier": null,
+        "system_fingerprint": "fp_ollama",
+        "usage": {
+          "completion_tokens": 100,
+          "prompt_tokens": 35,
+          "total_tokens": 135,
+          "completion_tokens_details": null,
+          "prompt_tokens_details": null
+        }
+      }
+    },
+    "is_streaming": false
+  }
+}

tests/integration/telemetry/recordings/dba5042d6691c2fbc29f2172c0f175e235f2829cb1c3e49781dd2b1850e28775.json

@@ -0,0 +1,59 @@
+{
+  "test_id": "tests/integration/telemetry/test_completions.py::test_telemetry_format_completeness[txt=llama3.2:3b-instruct-fp16]",
+  "request": {
+    "method": "POST",
+    "url": "http://localhost:11434/v1/v1/chat/completions",
+    "headers": {},
+    "body": {
+      "model": "llama3.2:3b-instruct-fp16",
+      "messages": [
+        {
+          "role": "user",
+          "content": "Test trace openai with temperature 0.7"
+        }
+      ],
+      "max_tokens": 100,
+      "stream": false,
+      "temperature": 0.7
+    },
+    "endpoint": "/v1/chat/completions",
+    "model": "llama3.2:3b-instruct-fp16"
+  },
+  "response": {
+    "body": {
+      "__type__": "openai.types.chat.chat_completion.ChatCompletion",
+      "__data__": {
+        "id": "rec-dba5042d6691",
+        "choices": [
+          {
+            "finish_reason": "length",
+            "index": 0,
+            "logprobs": null,
+            "message": {
+              "content": "To test the \"trace\" functionality of OpenAI's GPT-4 model at a temperature of 0.7, you can follow these steps:\n\n1. First, make sure you have an account with OpenAI and have been granted access to their API.\n\n2. You will need to install the `transformers` library, which is the official library for working with Transformers models like GPT-4:\n\n   ```bash\npip install transformers\n```\n\n3. Next, import the necessary",
+              "refusal": null,
+              "role": "assistant",
+              "annotations": null,
+              "audio": null,
+              "function_call": null,
+              "tool_calls": null
+            }
+          }
+        ],
+        "created": 0,
+        "model": "llama3.2:3b-instruct-fp16",
+        "object": "chat.completion",
+        "service_tier": null,
+        "system_fingerprint": "fp_ollama",
+        "usage": {
+          "completion_tokens": 100,
+          "prompt_tokens": 35,
+          "total_tokens": 135,
+          "completion_tokens_details": null,
+          "prompt_tokens_details": null
+        }
+      }
+    },
+    "is_streaming": false
+  }
+}

tests/integration/telemetry/test_completions.py

@@ -0,0 +1,112 @@
+# 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.
+
+"""Telemetry tests verifying @trace_protocol decorator format using in-memory exporter."""
+
+import json
+import os
+
+import pytest
+
+pytestmark = pytest.mark.skipif(
+    os.environ.get("LLAMA_STACK_TEST_STACK_CONFIG_TYPE") == "server",
+    reason="In-memory telemetry tests only work in library_client mode (server mode runs in separate process)",
+)
+
+
+def test_streaming_chunk_count(mock_otlp_collector, llama_stack_client, text_model_id):
+    """Verify streaming adds chunk_count and __type__=async_generator."""
+
+    stream = llama_stack_client.chat.completions.create(
+        model=text_model_id,
+        messages=[{"role": "user", "content": "Test trace openai 1"}],
+        stream=True,
+    )
+
+    chunks = list(stream)
+    assert len(chunks) > 0
+
+    spans = mock_otlp_collector.get_spans()
+    assert len(spans) > 0
+
+    chunk_count = None
+    for span in spans:
+        if span.attributes.get("__type__") == "async_generator":
+            chunk_count = span.attributes.get("chunk_count")
+            if chunk_count:
+                chunk_count = int(chunk_count)
+                break
+
+    assert chunk_count is not None
+    assert chunk_count == len(chunks)
+
+
+def test_telemetry_format_completeness(mock_otlp_collector, llama_stack_client, text_model_id):
+    """Comprehensive validation of telemetry data format including spans and metrics."""
+    response = llama_stack_client.chat.completions.create(
+        model=text_model_id,
+        messages=[{"role": "user", "content": "Test trace openai with temperature 0.7"}],
+        temperature=0.7,
+        max_tokens=100,
+        stream=False,
+    )
+
+    # Handle both dict and Pydantic model for usage
+    # This occurs due to the replay system returning a dict for usage, but the client returning a Pydantic model
+    # TODO: Fix this by making the replay system return a Pydantic model for usage
+    usage = response.usage if isinstance(response.usage, dict) else response.usage.model_dump()
+    assert usage.get("prompt_tokens") and usage["prompt_tokens"] > 0
+    assert usage.get("completion_tokens") and usage["completion_tokens"] > 0
+    assert usage.get("total_tokens") and usage["total_tokens"] > 0
+
+    # Verify spans
+    spans = mock_otlp_collector.get_spans()
+    assert len(spans) == 5
+
+    # we only need this captured one time
+    logged_model_id = None
+
+    for span in spans:
+        attrs = span.attributes
+        assert attrs is not None
+
+        # Root span is created manually by tracing middleware, not by @trace_protocol decorator
+        is_root_span = attrs.get("__root__") is True
+
+        if is_root_span:
+            # Root spans have different attributes
+            assert attrs.get("__location__") in ["library_client", "server"]
+        else:
+            # Non-root spans are created by @trace_protocol decorator
+            assert attrs.get("__autotraced__")
+            assert attrs.get("__class__") and attrs.get("__method__")
+            assert attrs.get("__type__") in ["async", "sync", "async_generator"]
+
+            args = json.loads(attrs["__args__"])
+            if "model_id" in args:
+                logged_model_id = args["model_id"]
+
+    assert logged_model_id is not None
+    assert logged_model_id == text_model_id
+
+    # TODO: re-enable this once metrics get fixed
+    """
+    # Verify token usage metrics in response
+    metrics = mock_otlp_collector.get_metrics()
+
+    assert metrics
+    for metric in metrics:
+        assert metric.name in ["completion_tokens", "total_tokens", "prompt_tokens"]
+        assert metric.unit == "tokens"
+        assert metric.data.data_points and len(metric.data.data_points) == 1
+        match metric.name:
+            case "completion_tokens":
+                assert metric.data.data_points[0].value == usage["completion_tokens"]
+            case "total_tokens":
+                assert metric.data.data_points[0].value == usage["total_tokens"]
+            case "prompt_tokens":
+                assert metric.data.data_points[0].value == usage["prompt_tokens"
+    """

tests/unit/distribution/test_stack_list_deps.py

@@ -0,0 +1,50 @@
+# 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 argparse
+from io import StringIO
+from unittest.mock import patch
+
+from llama_stack.cli.stack._list_deps import (
+    run_stack_list_deps_command,
+)
+
+
+def test_stack_list_deps_basic():
+    args = argparse.Namespace(
+        config=None,
+        env_name="test-env",
+        providers="inference=remote::ollama",
+        format="deps-only",
+    )
+
+    with patch("sys.stdout", new_callable=StringIO) as mock_stdout:
+        run_stack_list_deps_command(args)
+        output = mock_stdout.getvalue()
+
+        # deps-only format should NOT include "uv pip install" or "Dependencies for"
+        assert "uv pip install" not in output
+        assert "Dependencies for" not in output
+
+        # Check that expected dependencies are present
+        assert "ollama" in output
+        assert "aiohttp" in output
+        assert "fastapi" in output
+
+
+def test_stack_list_deps_with_distro_uv():
+    args = argparse.Namespace(
+        config="starter",
+        env_name=None,
+        providers=None,
+        format="uv",
+    )
+
+    with patch("sys.stdout", new_callable=StringIO) as mock_stdout:
+        run_stack_list_deps_command(args)
+        output = mock_stdout.getvalue()
+
+        assert "uv pip install" in output

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+sdist = { url = "https://files.pythonhosted.org/packages/20/8e/fafaa6f15c332e73425d9c44ada85360501045d5ab0b81400076aff27cf6/ruff-0.9.10.tar.gz", hash = "sha256:9bacb735d7bada9cfb0f2c227d3658fc443d90a727b47f206fb33f52f3c0eac7", size = 3759776, upload-time = "2025-03-07T15:27:44.363Z" }
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