diff --git a/docs/source/advanced_apis/evaluation_concepts.md b/docs/source/advanced_apis/evaluation_concepts.md index c26ec8f5e..52ad53ece 100644 --- a/docs/source/advanced_apis/evaluation_concepts.md +++ b/docs/source/advanced_apis/evaluation_concepts.md @@ -33,7 +33,7 @@ The list of open-benchmarks we currently support: - [MMMU](https://arxiv.org/abs/2311.16502) (A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI)]: Benchmark designed to evaluate multimodal models. -You can follow this [contributing guide](https://llama-stack.readthedocs.io/en/latest/references/evals_reference/index.html#open-benchmark-contributing-guide) to add more open-benchmarks to Llama Stack +You can follow this [contributing guide](../references/evals_reference/index.md#open-benchmark-contributing-guide) to add more open-benchmarks to Llama Stack #### Run evaluation on open-benchmarks via CLI diff --git a/docs/source/advanced_apis/post_training/inline_huggingface.md b/docs/source/advanced_apis/post_training/inline_huggingface.md index 4d2201c99..6536b4f8c 100644 --- a/docs/source/advanced_apis/post_training/inline_huggingface.md +++ b/docs/source/advanced_apis/post_training/inline_huggingface.md @@ -35,3 +35,6 @@ device: cpu ``` +[Find more detailed information here!](huggingface.md) + + diff --git a/docs/source/advanced_apis/post_training/inline_torchtune.md b/docs/source/advanced_apis/post_training/inline_torchtune.md index 6684c99ac..617975b0d 100644 --- a/docs/source/advanced_apis/post_training/inline_torchtune.md +++ b/docs/source/advanced_apis/post_training/inline_torchtune.md @@ -22,3 +22,4 @@ checkpoint_format: meta ``` +[Find more detailed information here!](torchtune.md) diff --git a/docs/source/building_applications/playground/index.md b/docs/source/building_applications/playground/index.md index fd2b92434..2390c422f 100644 --- a/docs/source/building_applications/playground/index.md +++ b/docs/source/building_applications/playground/index.md @@ -88,7 +88,7 @@ Interactive pages for users to play with and explore Llama Stack API capabilitie - **API Resources**: Inspect Llama Stack API resources - This page allows you to inspect Llama Stack API resources (`models`, `datasets`, `memory_banks`, `benchmarks`, `shields`). - Under the hood, it uses Llama Stack's `//list` API to get information about each resources. - - Please visit [Core Concepts](https://llama-stack.readthedocs.io/en/latest/concepts/index.html) for more details about the resources. + - Please visit [Core Concepts](../../concepts/index.md) for more details about the resources. ### Starting the Llama Stack Playground diff --git a/docs/source/building_applications/responses_vs_agents.md b/docs/source/building_applications/responses_vs_agents.md index 5abe951d6..63ff69e4f 100644 --- a/docs/source/building_applications/responses_vs_agents.md +++ b/docs/source/building_applications/responses_vs_agents.md @@ -3,7 +3,7 @@ Llama Stack (LLS) provides two different APIs for building AI applications with tool calling capabilities: the **Agents API** and the **OpenAI Responses API**. While both enable AI systems to use tools, and maintain full conversation history, they serve different use cases and have distinct characteristics. ```{note} -For simple and basic inferencing, you may want to use the [Chat Completions API](https://llama-stack.readthedocs.io/en/latest/providers/index.html#chat-completions) directly, before progressing to Agents or Responses API. + **Note:** For simple and basic inferencing, you may want to use the [Chat Completions API](../providers/openai.md#chat-completions) directly, before progressing to Agents or Responses API. ``` ## Overview @@ -173,7 +173,7 @@ Both APIs demonstrate distinct strengths that make them valuable on their own fo ## For More Information -- **LLS Agents API**: For detailed information on creating and managing agents, see the [Agents documentation](https://llama-stack.readthedocs.io/en/latest/building_applications/agent.html) +- **LLS Agents API**: For detailed information on creating and managing agents, see the [Agents documentation](agent.md) - **OpenAI Responses API**: For information on using the OpenAI-compatible responses API, see the [OpenAI API documentation](https://platform.openai.com/docs/api-reference/responses) -- **Chat Completions API**: For the default backend API used by Agents, see the [Chat Completions providers documentation](https://llama-stack.readthedocs.io/en/latest/providers/index.html#chat-completions) -- **Agent Execution Loop**: For understanding how agents process turns and steps in their execution, see the [Agent Execution Loop documentation](https://llama-stack.readthedocs.io/en/latest/building_applications/agent_execution_loop.html) +- **Chat Completions API**: For the default backend API used by Agents, see the [Chat Completions providers documentation](../providers/openai.md#chat-completions) +- **Agent Execution Loop**: For understanding how agents process turns and steps in their execution, see the [Agent Execution Loop documentation](agent_execution_loop.md) diff --git a/docs/source/concepts/distributions.md b/docs/source/concepts/distributions.md index c3be12d93..8c63914d1 100644 --- a/docs/source/concepts/distributions.md +++ b/docs/source/concepts/distributions.md @@ -6,4 +6,4 @@ While there is a lot of flexibility to mix-and-match providers, often users will **Locally Hosted Distro**: You may want to run Llama Stack on your own hardware. Typically though, you still need to use Inference via an external service. You can use providers like HuggingFace TGI, Fireworks, Together, etc. for this purpose. Or you may have access to GPUs and can run a [vLLM](https://github.com/vllm-project/vllm) or [NVIDIA NIM](https://build.nvidia.com/nim?filters=nimType%3Anim_type_run_anywhere&q=llama) instance. If you "just" have a regular desktop machine, you can use [Ollama](https://ollama.com/) for inference. To provide convenient quick access to these options, we provide a number of such pre-configured locally-hosted Distros. -**On-device Distro**: To run Llama Stack directly on an edge device (mobile phone or a tablet), we provide Distros for [iOS](https://llama-stack.readthedocs.io/en/latest/distributions/ondevice_distro/ios_sdk.html) and [Android](https://llama-stack.readthedocs.io/en/latest/distributions/ondevice_distro/android_sdk.html) +**On-device Distro**: To run Llama Stack directly on an edge device (mobile phone or a tablet), we provide Distros for [iOS](../distributions/ondevice_distro/ios_sdk.md) and [Android](../distributions/ondevice_distro/android_sdk.md) diff --git a/docs/source/distributions/importing_as_library.md b/docs/source/distributions/importing_as_library.md index b9b4b065a..9993be227 100644 --- a/docs/source/distributions/importing_as_library.md +++ b/docs/source/distributions/importing_as_library.md @@ -27,7 +27,7 @@ Then, you can access the APIs like `models` and `inference` on the client and ca response = client.models.list() ``` -If you've created a [custom distribution](https://llama-stack.readthedocs.io/en/latest/distributions/building_distro.html), you can also use the run.yaml configuration file directly: +If you've created a [custom distribution](building_distro.md), you can also use the run.yaml configuration file directly: ```python client = LlamaStackAsLibraryClient(config_path) diff --git a/docs/source/distributions/k8s/apply.sh b/docs/source/distributions/k8s/apply.sh index 3356da53e..1b5b26863 100755 --- a/docs/source/distributions/k8s/apply.sh +++ b/docs/source/distributions/k8s/apply.sh @@ -22,17 +22,17 @@ else fi if [ -z "${GITHUB_CLIENT_ID:-}" ]; then - echo "ERROR: GITHUB_CLIENT_ID not set. You need it for Github login to work. Refer to https://llama-stack.readthedocs.io/en/latest/deploying/index.html#kubernetes-deployment-guide" + echo "ERROR: GITHUB_CLIENT_ID not set. You need it for Github login to work. See the Kubernetes Deployment Guide in the Llama Stack documentation." exit 1 fi if [ -z "${GITHUB_CLIENT_SECRET:-}" ]; then - echo "ERROR: GITHUB_CLIENT_SECRET not set. You need it for Github login to work. Refer to https://llama-stack.readthedocs.io/en/latest/deploying/index.html#kubernetes-deployment-guide" + echo "ERROR: GITHUB_CLIENT_SECRET not set. You need it for Github login to work. See the Kubernetes Deployment Guide in the Llama Stack documentation." exit 1 fi if [ -z "${LLAMA_STACK_UI_URL:-}" ]; then - echo "ERROR: LLAMA_STACK_UI_URL not set. Should be set to the external URL of the UI (excluding port). You need it for Github login to work. Refer to https://llama-stack.readthedocs.io/en/latest/deploying/index.html#kubernetes-deployment-guide" + echo "ERROR: LLAMA_STACK_UI_URL not set. Should be set to the external URL of the UI (excluding port). You need it for Github login to work. See the Kubernetes Deployment Guide in the Llama Stack documentation." exit 1 fi diff --git a/docs/source/distributions/ondevice_distro/android_sdk.md b/docs/source/distributions/ondevice_distro/android_sdk.md index 9d16d07d7..ad86fa5f3 100644 --- a/docs/source/distributions/ondevice_distro/android_sdk.md +++ b/docs/source/distributions/ondevice_distro/android_sdk.md @@ -66,7 +66,7 @@ llama stack run starter --port 5050 Ensure the Llama Stack server version is the same as the Kotlin SDK Library for maximum compatibility. -Other inference providers: [Table](https://llama-stack.readthedocs.io/en/latest/index.html#supported-llama-stack-implementations) +Other inference providers: [Table](../../index.md#supported-llama-stack-implementations) How to set remote localhost in Demo App: [Settings](https://github.com/meta-llama/llama-stack-client-kotlin/tree/latest-release/examples/android_app#settings) diff --git a/docs/source/distributions/self_hosted_distro/meta-reference-gpu.md b/docs/source/distributions/self_hosted_distro/meta-reference-gpu.md index 7e50a4161..84b85b91c 100644 --- a/docs/source/distributions/self_hosted_distro/meta-reference-gpu.md +++ b/docs/source/distributions/self_hosted_distro/meta-reference-gpu.md @@ -2,7 +2,7 @@ orphan: true --- -# Meta Reference Distribution +# Meta Reference GPU Distribution ```{toctree} :maxdepth: 2 @@ -41,7 +41,7 @@ The following environment variables can be configured: ## Prerequisite: Downloading Models -Please use `llama model list --downloaded` to check that you have llama model checkpoints downloaded in `~/.llama` before proceeding. See [installation guide](https://llama-stack.readthedocs.io/en/latest/references/llama_cli_reference/download_models.html) here to download the models. Run `llama model list` to see the available models to download, and `llama model download` to download the checkpoints. +Please use `llama model list --downloaded` to check that you have llama model checkpoints downloaded in `~/.llama` before proceeding. See [installation guide](../../references/llama_cli_reference/download_models.md) here to download the models. Run `llama model list` to see the available models to download, and `llama model download` to download the checkpoints. ``` $ llama model list --downloaded diff --git a/docs/source/providers/post_training/index.md b/docs/source/providers/post_training/index.md index 5ada6f9aa..e69f2a45a 100644 --- a/docs/source/providers/post_training/index.md +++ b/docs/source/providers/post_training/index.md @@ -9,7 +9,6 @@ This section contains documentation for all available providers for the **post_t ```{toctree} :maxdepth: 1 -inline_huggingface-cpu inline_huggingface-gpu inline_torchtune-cpu inline_torchtune-gpu diff --git a/docs/source/references/evals_reference/index.md b/docs/source/references/evals_reference/index.md index 054a0b809..9a5ed2f1b 100644 --- a/docs/source/references/evals_reference/index.md +++ b/docs/source/references/evals_reference/index.md @@ -202,7 +202,7 @@ pprint(response) Llama Stack offers a library of scoring functions and the `/scoring` API, allowing you to run evaluations on your pre-annotated AI application datasets. -In this example, we will work with an example RAG dataset you have built previously, label with an annotation, and use LLM-As-Judge with custom judge prompt for scoring. Please checkout our [Llama Stack Playground](https://llama-stack.readthedocs.io/en/latest/playground/index.html) for an interactive interface to upload datasets and run scorings. +In this example, we will work with an example RAG dataset you have built previously, label with an annotation, and use LLM-As-Judge with custom judge prompt for scoring. Please checkout our [Llama Stack Playground](../../building_applications/playground/index.md) for an interactive interface to upload datasets and run scorings. ```python judge_model_id = "meta-llama/Llama-3.1-405B-Instruct-FP8" diff --git a/llama_stack/core/build.py b/llama_stack/core/build.py index fa1fe632b..2ceb9e9be 100644 --- a/llama_stack/core/build.py +++ b/llama_stack/core/build.py @@ -80,7 +80,7 @@ def get_provider_dependencies( normal_deps = [] special_deps = [] for package in deps: - if "--no-deps" in package or "--index-url" in package: + if any(f in package for f in ["--no-deps", "--index-url", "--extra-index-url"]): special_deps.append(package) else: normal_deps.append(package) diff --git a/llama_stack/distributions/ci-tests/build.yaml b/llama_stack/distributions/ci-tests/build.yaml index b4701cb81..8e6c0bf67 100644 --- a/llama_stack/distributions/ci-tests/build.yaml +++ b/llama_stack/distributions/ci-tests/build.yaml @@ -34,7 +34,7 @@ distribution_spec: telemetry: - provider_type: inline::meta-reference post_training: - - provider_type: inline::huggingface-cpu + - provider_type: inline::torchtune-cpu eval: - provider_type: inline::meta-reference datasetio: diff --git a/llama_stack/distributions/ci-tests/run.yaml b/llama_stack/distributions/ci-tests/run.yaml index 3acdd20f9..7523df581 100644 --- a/llama_stack/distributions/ci-tests/run.yaml +++ b/llama_stack/distributions/ci-tests/run.yaml @@ -156,13 +156,10 @@ providers: sqlite_db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/ci-tests}/trace_store.db otel_exporter_otlp_endpoint: ${env.OTEL_EXPORTER_OTLP_ENDPOINT:=} post_training: - - provider_id: huggingface-cpu - provider_type: inline::huggingface-cpu + - provider_id: torchtune-cpu + provider_type: inline::torchtune-cpu config: - checkpoint_format: huggingface - distributed_backend: null - device: cpu - dpo_output_dir: ~/.llama/distributions/ci-tests/dpo_output + checkpoint_format: meta eval: - provider_id: meta-reference provider_type: inline::meta-reference diff --git a/llama_stack/distributions/meta-reference-gpu/doc_template.md b/llama_stack/distributions/meta-reference-gpu/doc_template.md index ff45c3826..602d053c4 100644 --- a/llama_stack/distributions/meta-reference-gpu/doc_template.md +++ b/llama_stack/distributions/meta-reference-gpu/doc_template.md @@ -1,7 +1,7 @@ --- orphan: true --- -# Meta Reference Distribution +# Meta Reference GPU Distribution ```{toctree} :maxdepth: 2 @@ -29,7 +29,7 @@ The following environment variables can be configured: ## Prerequisite: Downloading Models -Please use `llama model list --downloaded` to check that you have llama model checkpoints downloaded in `~/.llama` before proceeding. See [installation guide](https://llama-stack.readthedocs.io/en/latest/references/llama_cli_reference/download_models.html) here to download the models. Run `llama model list` to see the available models to download, and `llama model download` to download the checkpoints. +Please use `llama model list --downloaded` to check that you have llama model checkpoints downloaded in `~/.llama` before proceeding. See [installation guide](../../references/llama_cli_reference/download_models.md) here to download the models. Run `llama model list` to see the available models to download, and `llama model download` to download the checkpoints. ``` $ llama model list --downloaded diff --git a/llama_stack/distributions/starter-gpu/build.yaml b/llama_stack/distributions/starter-gpu/build.yaml index ae0680cdc..ff7c58e6f 100644 --- a/llama_stack/distributions/starter-gpu/build.yaml +++ b/llama_stack/distributions/starter-gpu/build.yaml @@ -35,7 +35,7 @@ distribution_spec: telemetry: - provider_type: inline::meta-reference post_training: - - provider_type: inline::torchtune-gpu + - provider_type: inline::huggingface-gpu eval: - provider_type: inline::meta-reference datasetio: diff --git a/llama_stack/distributions/starter-gpu/run.yaml b/llama_stack/distributions/starter-gpu/run.yaml index 81c802317..8aed61519 100644 --- a/llama_stack/distributions/starter-gpu/run.yaml +++ b/llama_stack/distributions/starter-gpu/run.yaml @@ -156,10 +156,13 @@ providers: sqlite_db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter-gpu}/trace_store.db otel_exporter_otlp_endpoint: ${env.OTEL_EXPORTER_OTLP_ENDPOINT:=} post_training: - - provider_id: torchtune-gpu - provider_type: inline::torchtune-gpu + - provider_id: huggingface-gpu + provider_type: inline::huggingface-gpu config: - checkpoint_format: meta + checkpoint_format: huggingface + distributed_backend: null + device: cpu + dpo_output_dir: ~/.llama/distributions/starter-gpu/dpo_output eval: - provider_id: meta-reference provider_type: inline::meta-reference diff --git a/llama_stack/distributions/starter-gpu/starter_gpu.py b/llama_stack/distributions/starter-gpu/starter_gpu.py index 893df6c17..245334749 100644 --- a/llama_stack/distributions/starter-gpu/starter_gpu.py +++ b/llama_stack/distributions/starter-gpu/starter_gpu.py @@ -17,6 +17,6 @@ def get_distribution_template() -> DistributionTemplate: template.description = "Quick start template for running Llama Stack with several popular providers. This distribution is intended for GPU-enabled environments." template.providers["post_training"] = [ - BuildProvider(provider_type="inline::torchtune-gpu"), + BuildProvider(provider_type="inline::huggingface-gpu"), ] return template diff --git a/llama_stack/distributions/starter/build.yaml b/llama_stack/distributions/starter/build.yaml index 3df0eb129..e84e528da 100644 --- a/llama_stack/distributions/starter/build.yaml +++ b/llama_stack/distributions/starter/build.yaml @@ -35,7 +35,7 @@ distribution_spec: telemetry: - provider_type: inline::meta-reference post_training: - - provider_type: inline::huggingface-cpu + - provider_type: inline::torchtune-cpu eval: - provider_type: inline::meta-reference datasetio: diff --git a/llama_stack/distributions/starter/run.yaml b/llama_stack/distributions/starter/run.yaml index 7e1d46a61..a3962b8aa 100644 --- a/llama_stack/distributions/starter/run.yaml +++ b/llama_stack/distributions/starter/run.yaml @@ -156,13 +156,10 @@ providers: sqlite_db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter}/trace_store.db otel_exporter_otlp_endpoint: ${env.OTEL_EXPORTER_OTLP_ENDPOINT:=} post_training: - - provider_id: huggingface-cpu - provider_type: inline::huggingface-cpu + - provider_id: torchtune-cpu + provider_type: inline::torchtune-cpu config: - checkpoint_format: huggingface - distributed_backend: null - device: cpu - dpo_output_dir: ~/.llama/distributions/starter/dpo_output + checkpoint_format: meta eval: - provider_id: meta-reference provider_type: inline::meta-reference diff --git a/llama_stack/distributions/starter/starter.py b/llama_stack/distributions/starter/starter.py index f49da0bb7..a4bbc6371 100644 --- a/llama_stack/distributions/starter/starter.py +++ b/llama_stack/distributions/starter/starter.py @@ -120,7 +120,7 @@ def get_distribution_template() -> DistributionTemplate: ], "agents": [BuildProvider(provider_type="inline::meta-reference")], "telemetry": [BuildProvider(provider_type="inline::meta-reference")], - "post_training": [BuildProvider(provider_type="inline::huggingface-cpu")], + "post_training": [BuildProvider(provider_type="inline::torchtune-cpu")], "eval": [BuildProvider(provider_type="inline::meta-reference")], "datasetio": [ BuildProvider(provider_type="remote::huggingface"), diff --git a/llama_stack/providers/registry/inference.py b/llama_stack/providers/registry/inference.py index 1801cdcad..82b771a28 100644 --- a/llama_stack/providers/registry/inference.py +++ b/llama_stack/providers/registry/inference.py @@ -40,8 +40,9 @@ def available_providers() -> list[ProviderSpec]: InlineProviderSpec( api=Api.inference, provider_type="inline::sentence-transformers", + # CrossEncoder depends on torchao.quantization pip_packages=[ - "torch torchvision --index-url https://download.pytorch.org/whl/cpu", + "torch torchvision torchao>=0.12.0 --extra-index-url https://download.pytorch.org/whl/cpu", "sentence-transformers --no-deps", ], module="llama_stack.providers.inline.inference.sentence_transformers", diff --git a/llama_stack/providers/registry/post_training.py b/llama_stack/providers/registry/post_training.py index 4443f4df1..67238e3fc 100644 --- a/llama_stack/providers/registry/post_training.py +++ b/llama_stack/providers/registry/post_training.py @@ -13,7 +13,7 @@ from llama_stack.providers.datatypes import AdapterSpec, Api, InlineProviderSpec # The CPU version is used for distributions that don't have GPU support -- they result in smaller container images. torchtune_def = dict( api=Api.post_training, - pip_packages=["torchtune==0.5.0", "torchao==0.8.0", "numpy"], + pip_packages=["numpy"], module="llama_stack.providers.inline.post_training.torchtune", config_class="llama_stack.providers.inline.post_training.torchtune.TorchtunePostTrainingConfig", api_dependencies=[ @@ -23,56 +23,39 @@ torchtune_def = dict( description="TorchTune-based post-training provider for fine-tuning and optimizing models using Meta's TorchTune framework.", ) -huggingface_def = dict( - api=Api.post_training, - pip_packages=["trl", "transformers", "peft", "datasets"], - module="llama_stack.providers.inline.post_training.huggingface", - config_class="llama_stack.providers.inline.post_training.huggingface.HuggingFacePostTrainingConfig", - api_dependencies=[ - Api.datasetio, - Api.datasets, - ], - description="HuggingFace-based post-training provider for fine-tuning models using the HuggingFace ecosystem.", -) - def available_providers() -> list[ProviderSpec]: return [ InlineProviderSpec( - **{ + **{ # type: ignore **torchtune_def, "provider_type": "inline::torchtune-cpu", "pip_packages": ( cast(list[str], torchtune_def["pip_packages"]) - + ["torch torchtune==0.5.0 torchao==0.8.0 --index-url https://download.pytorch.org/whl/cpu"] + + ["torch torchtune>=0.5.0 torchao>=0.12.0 --extra-index-url https://download.pytorch.org/whl/cpu"] ), }, ), InlineProviderSpec( - **{ - **huggingface_def, - "provider_type": "inline::huggingface-cpu", - "pip_packages": ( - cast(list[str], huggingface_def["pip_packages"]) - + ["torch --index-url https://download.pytorch.org/whl/cpu"] - ), - }, - ), - InlineProviderSpec( - **{ + **{ # type: ignore **torchtune_def, "provider_type": "inline::torchtune-gpu", "pip_packages": ( - cast(list[str], torchtune_def["pip_packages"]) + ["torch torchtune==0.5.0 torchao==0.8.0"] + cast(list[str], torchtune_def["pip_packages"]) + ["torch torchtune>=0.5.0 torchao>=0.12.0"] ), }, ), InlineProviderSpec( - **{ - **huggingface_def, - "provider_type": "inline::huggingface-gpu", - "pip_packages": (cast(list[str], huggingface_def["pip_packages"]) + ["torch"]), - }, + api=Api.post_training, + provider_type="inline::huggingface-gpu", + pip_packages=["trl", "transformers", "peft", "datasets", "torch"], + module="llama_stack.providers.inline.post_training.huggingface", + config_class="llama_stack.providers.inline.post_training.huggingface.HuggingFacePostTrainingConfig", + api_dependencies=[ + Api.datasetio, + Api.datasets, + ], + description="HuggingFace-based post-training provider for fine-tuning models using the HuggingFace ecosystem.", ), remote_provider_spec( api=Api.post_training, diff --git a/llama_stack/testing/inference_recorder.py b/llama_stack/testing/inference_recorder.py index 4a6958399..8fa5f5f2e 100644 --- a/llama_stack/testing/inference_recorder.py +++ b/llama_stack/testing/inference_recorder.py @@ -9,7 +9,6 @@ from __future__ import annotations # for forward references import hashlib import json import os -import sqlite3 from collections.abc import Generator from contextlib import contextmanager from enum import StrEnum @@ -125,28 +124,13 @@ class ResponseStorage: def __init__(self, test_dir: Path): self.test_dir = test_dir self.responses_dir = self.test_dir / "responses" - self.db_path = self.test_dir / "index.sqlite" self._ensure_directories() - self._init_database() def _ensure_directories(self): self.test_dir.mkdir(parents=True, exist_ok=True) self.responses_dir.mkdir(exist_ok=True) - def _init_database(self): - with sqlite3.connect(self.db_path) as conn: - conn.execute(""" - CREATE TABLE IF NOT EXISTS recordings ( - request_hash TEXT PRIMARY KEY, - response_file TEXT, - endpoint TEXT, - model TEXT, - timestamp TEXT, - is_streaming BOOLEAN - ) - """) - def store_recording(self, request_hash: str, request: dict[str, Any], response: dict[str, Any]): """Store a request/response pair.""" # Generate unique response filename @@ -169,34 +153,9 @@ class ResponseStorage: f.write("\n") f.flush() - # Update SQLite index - with sqlite3.connect(self.db_path) as conn: - conn.execute( - """ - INSERT OR REPLACE INTO recordings - (request_hash, response_file, endpoint, model, timestamp, is_streaming) - VALUES (?, ?, ?, ?, datetime('now'), ?) - """, - ( - request_hash, - response_file, - request.get("endpoint", ""), - request.get("model", ""), - response.get("is_streaming", False), - ), - ) - def find_recording(self, request_hash: str) -> dict[str, Any] | None: """Find a recorded response by request hash.""" - with sqlite3.connect(self.db_path) as conn: - result = conn.execute( - "SELECT response_file FROM recordings WHERE request_hash = ?", (request_hash,) - ).fetchone() - - if not result: - return None - - response_file = result[0] + response_file = f"{request_hash[:12]}.json" response_path = self.responses_dir / response_file if not response_path.exists(): diff --git a/llama_stack/ui/package-lock.json b/llama_stack/ui/package-lock.json index 58888e586..2da25615c 100644 --- a/llama_stack/ui/package-lock.json +++ b/llama_stack/ui/package-lock.json @@ -18,7 +18,7 @@ "class-variance-authority": "^0.7.1", "clsx": "^2.1.1", "framer-motion": "^11.18.2", - "llama-stack-client": "^0.2.18", + "llama-stack-client": "^0.2.19", "lucide-react": "^0.510.0", "next": "15.3.3", "next-auth": "^4.24.11", @@ -36,7 +36,7 @@ "@eslint/eslintrc": "^3", "@tailwindcss/postcss": "^4", "@testing-library/dom": "^10.4.1", - 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}, - "node_modules/@testing-library/jest-dom/node_modules/chalk": { - "version": "3.0.0", - "resolved": "https://registry.npmjs.org/chalk/-/chalk-3.0.0.tgz", - "integrity": "sha512-4D3B6Wf41KOYRFdszmDqMCGq5VV/uMAB273JILmO+3jAlh8X4qDtdtgCR3fxtbLEMzSx22QdhnDcJvu2u1fVwg==", - "dev": true, - "license": "MIT", - "dependencies": { - "ansi-styles": "^4.1.0", - "supports-color": "^7.1.0" - }, - "engines": { - "node": ">=8" - } - }, "node_modules/@testing-library/jest-dom/node_modules/dom-accessibility-api": { "version": "0.6.3", "resolved": "https://registry.npmjs.org/dom-accessibility-api/-/dom-accessibility-api-0.6.3.tgz", @@ -10021,9 +10006,9 @@ "license": "MIT" }, "node_modules/llama-stack-client": { - "version": "0.2.18", - "resolved": "https://registry.npmjs.org/llama-stack-client/-/llama-stack-client-0.2.18.tgz", - "integrity": "sha512-k+xQOz/TIU0cINP4Aih8q6xs7f/6qs0fLDMXTTKQr5C0F1jtCjRiwsas7bTsDfpKfYhg/7Xy/wPw/uZgi6aIVg==", + "version": "0.2.19", + "resolved": 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"framer-motion": "^11.18.2", - "llama-stack-client": "^0.2.18", + "llama-stack-client": "^0.2.19", "lucide-react": "^0.510.0", "next": "15.3.3", "next-auth": "^4.24.11", @@ -41,7 +41,7 @@ "@eslint/eslintrc": "^3", "@tailwindcss/postcss": "^4", "@testing-library/dom": "^10.4.1", - "@testing-library/jest-dom": "^6.6.3", + "@testing-library/jest-dom": "^6.8.0", "@testing-library/react": "^16.3.0", "@types/jest": "^29.5.14", "@types/node": "^20", diff --git a/pyproject.toml b/pyproject.toml index 6c76da895..dd8529546 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -7,7 +7,7 @@ required-version = ">=0.7.0" [project] name = "llama_stack" -version = "0.2.18" +version = "0.2.19" authors = [{ name = "Meta Llama", email = "llama-oss@meta.com" }] description = "Llama Stack" readme = "README.md" @@ -31,7 +31,7 @@ dependencies = [ "huggingface-hub>=0.34.0,<1.0", "jinja2>=3.1.6", "jsonschema", - "llama-stack-client>=0.2.18", + "llama-stack-client>=0.2.19", "llama-api-client>=0.1.2", 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