From dafd9ed5c0cfc287a5a68df84c10c56349f5196d Mon Sep 17 00:00:00 2001 From: Jorge Date: Wed, 9 Jul 2025 15:41:57 +0200 Subject: [PATCH 01/34] docs: Update links to Android Demo App (#2687) # What does this PR do? Updates some broken or outdated links pointing to the Android Demo App Signed-off-by: Jorge Garcia Oncins --- docs/source/distributions/ondevice_distro/android_sdk.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/docs/source/distributions/ondevice_distro/android_sdk.md b/docs/source/distributions/ondevice_distro/android_sdk.md index a097a2adf..1cddf1d1f 100644 --- a/docs/source/distributions/ondevice_distro/android_sdk.md +++ b/docs/source/distributions/ondevice_distro/android_sdk.md @@ -13,7 +13,7 @@ Latest Release Notes: [link](https://github.com/meta-llama/llama-stack-client-ko *Tagged releases are stable versions of the project. While we strive to maintain a stable main branch, it's not guaranteed to be free of bugs or issues.* ## Android Demo App -Check out our demo app to see how to integrate Llama Stack into your Android app: [Android Demo App](https://github.com/meta-llama/llama-stack-client-kotlin/tree/examples/android_app) +Check out our demo app to see how to integrate Llama Stack into your Android app: [Android Demo App](https://github.com/meta-llama/llama-stack-client-kotlin/tree/latest-release/examples/android_app) The key files in the app are `ExampleLlamaStackLocalInference.kt`, `ExampleLlamaStackRemoteInference.kts`, and `MainActivity.java`. With encompassed business logic, the app shows how to use Llama Stack for both the environments. @@ -68,7 +68,7 @@ Ensure the Llama Stack server version is the same as the Kotlin SDK Library for Other inference providers: [Table](https://llama-stack.readthedocs.io/en/latest/index.html#supported-llama-stack-implementations) -How to set remote localhost in Demo App: [Settings](https://github.com/meta-llama/llama-stack-apps/tree/main/examples/android_app#settings) +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) ### Initialize the Client A client serves as the primary interface for interacting with a specific inference type and its associated parameters. Only after client is initialized then you can configure and start inferences. @@ -135,7 +135,7 @@ val result = client!!.inference().chatCompletionStreaming( ### Setup Custom Tool Calling -Android demo app for more details: [Custom Tool Calling](https://github.com/meta-llama/llama-stack-apps/tree/main/examples/android_app#tool-calling) +Android demo app for more details: [Custom Tool Calling](https://github.com/meta-llama/llama-stack-client-kotlin/tree/latest-release/examples/android_app#tool-calling) ## Advanced Users From de01eefdefad90d1f094ce9057c5212ced0f049b Mon Sep 17 00:00:00 2001 From: Mustafa Elbehery Date: Wed, 9 Jul 2025 15:44:39 +0200 Subject: [PATCH 02/34] chore: add `mypy` post training (#2675) # What does this PR do? This PR adds static type coverage to `llama-stack` Part of https://github.com/meta-llama/llama-stack/issues/2647 ## Test Plan Signed-off-by: Mustafa Elbehery --- .../providers/inline/post_training/torchtune/post_training.py | 3 ++- pyproject.toml | 1 - 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/llama_stack/providers/inline/post_training/torchtune/post_training.py b/llama_stack/providers/inline/post_training/torchtune/post_training.py index c7d8d6758..d20e11b11 100644 --- a/llama_stack/providers/inline/post_training/torchtune/post_training.py +++ b/llama_stack/providers/inline/post_training/torchtune/post_training.py @@ -123,7 +123,8 @@ class TorchtunePostTrainingImpl: training_config: TrainingConfig, hyperparam_search_config: dict[str, Any], logger_config: dict[str, Any], - ) -> PostTrainingJob: ... + ) -> PostTrainingJob: + raise NotImplementedError() async def get_training_jobs(self) -> ListPostTrainingJobsResponse: return ListPostTrainingJobsResponse( diff --git a/pyproject.toml b/pyproject.toml index b41e03615..04a6a685e 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -256,7 +256,6 @@ exclude = [ "^llama_stack/providers/inline/inference/sentence_transformers/sentence_transformers\\.py$", "^llama_stack/providers/inline/inference/vllm/", "^llama_stack/providers/inline/post_training/common/validator\\.py$", - "^llama_stack/providers/inline/post_training/torchtune/post_training\\.py$", "^llama_stack/providers/inline/safety/code_scanner/", "^llama_stack/providers/inline/safety/llama_guard/", "^llama_stack/providers/inline/safety/prompt_guard/", From 9b7eecebcf17acc01cf994761b4f91063c12cd52 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?S=C3=A9bastien=20Han?= Date: Wed, 9 Jul 2025 16:53:50 +0200 Subject: [PATCH 03/34] ci: test safety with starter (#2628) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit # What does this PR do? We are now testing the safety capability with the starter image. This includes a few changes: * Enable the safety integration test * Relax the shield model requirements from llama-guard to make it work with llama-guard3:8b coming from Ollama * Expose a shield for each inference provider in the starter distro. The shield will only be registered if the provider is enabled. Closes: https://github.com/meta-llama/llama-stack/issues/2528 Signed-off-by: Sébastien Han --- .github/actions/setup-ollama/action.yml | 2 + .github/workflows/integration-tests.yml | 19 +- llama_stack/distribution/stack.py | 6 + .../inline/safety/llama_guard/llama_guard.py | 34 +- .../remote/inference/anthropic/models.py | 39 +- .../remote/inference/bedrock/models.py | 6 +- .../remote/inference/cerebras/models.py | 9 +- .../remote/inference/databricks/databricks.py | 9 +- .../remote/inference/fireworks/models.py | 21 +- .../remote/inference/gemini/models.py | 19 +- .../providers/remote/inference/groq/models.py | 4 +- .../remote/inference/nvidia/models.py | 5 +- .../remote/inference/openai/models.py | 28 +- .../remote/inference/runpod/runpod.py | 12 +- .../remote/inference/sambanova/models.py | 14 +- .../remote/inference/together/models.py | 20 +- .../utils/inference/model_registry.py | 3 +- llama_stack/templates/starter/run.yaml | 373 ++++++++++++++++-- llama_stack/templates/starter/starter.py | 121 +++++- tests/Containerfile | 3 +- 20 files changed, 621 insertions(+), 126 deletions(-) diff --git a/.github/actions/setup-ollama/action.yml b/.github/actions/setup-ollama/action.yml index 1f6e9818b..da24839c2 100644 --- a/.github/actions/setup-ollama/action.yml +++ b/.github/actions/setup-ollama/action.yml @@ -7,3 +7,5 @@ runs: shell: bash run: | docker run -d --name ollama -p 11434:11434 docker.io/leseb/ollama-with-models + # TODO: rebuild an ollama image with llama-guard3:1b + docker exec ollama ollama pull llama-guard3:1b diff --git a/.github/workflows/integration-tests.yml b/.github/workflows/integration-tests.yml index a71b7c5b6..b102191f2 100644 --- a/.github/workflows/integration-tests.yml +++ b/.github/workflows/integration-tests.yml @@ -24,7 +24,7 @@ jobs: matrix: # Listing tests manually since some of them currently fail # TODO: generate matrix list from tests/integration when fixed - test-type: [agents, inference, datasets, inspect, scoring, post_training, providers, tool_runtime, vector_io] + test-type: [agents, inference, datasets, inspect, safety, scoring, post_training, providers, tool_runtime, vector_io] client-type: [library, server] python-version: ["3.12", "3.13"] fail-fast: false # we want to run all tests regardless of failure @@ -51,11 +51,23 @@ jobs: free -h df -h + - name: Verify Ollama status is OK + if: matrix.client-type == 'http' + run: | + echo "Verifying Ollama status..." + ollama_status=$(curl -s -L http://127.0.0.1:8321/v1/providers/ollama|jq --raw-output .health.status) + echo "Ollama status: $ollama_status" + if [ "$ollama_status" != "OK" ]; then + echo "Ollama health check failed" + exit 1 + fi + - name: Run Integration Tests env: - OLLAMA_INFERENCE_MODEL: "meta-llama/Llama-3.2-3B-Instruct" # for server tests + OLLAMA_INFERENCE_MODEL: "llama3.2:3b-instruct-fp16" # for server tests ENABLE_OLLAMA: "ollama" # for server tests OLLAMA_URL: "http://0.0.0.0:11434" + SAFETY_MODEL: "llama-guard3:1b" # Use 'shell' to get pipefail behavior # https://docs.github.com/en/actions/reference/workflow-syntax-for-github-actions#exit-codes-and-error-action-preference # TODO: write a precommit hook to detect if a test contains a pipe but does not use 'shell: bash' @@ -68,8 +80,9 @@ jobs: fi uv run pytest -s -v tests/integration/${{ matrix.test-type }} --stack-config=${stack_config} \ -k "not(builtin_tool or safety_with_image or code_interpreter or test_rag)" \ - --text-model="ollama/meta-llama/Llama-3.2-3B-Instruct" \ + --text-model="ollama/llama3.2:3b-instruct-fp16" \ --embedding-model=all-MiniLM-L6-v2 \ + --safety-shield=ollama \ --color=yes \ --capture=tee-sys | tee pytest-${{ matrix.test-type }}.log diff --git a/llama_stack/distribution/stack.py b/llama_stack/distribution/stack.py index 1a9237d6c..8d7307b03 100644 --- a/llama_stack/distribution/stack.py +++ b/llama_stack/distribution/stack.py @@ -98,6 +98,7 @@ async def register_resources(run_config: StackRunConfig, impls: dict[Api, Any]): method = getattr(impls[api], register_method) for obj in objects: + logger.debug(f"registering {rsrc.capitalize()} {obj} for provider {obj.provider_id}") # Do not register models on disabled providers if hasattr(obj, "provider_id") and obj.provider_id is not None and obj.provider_id == "__disabled__": logger.debug(f"Skipping {rsrc.capitalize()} registration for disabled provider.") @@ -112,6 +113,11 @@ async def register_resources(run_config: StackRunConfig, impls: dict[Api, Any]): ): logger.debug(f"Skipping {rsrc.capitalize()} registration for disabled model.") continue + + if hasattr(obj, "shield_id") and obj.shield_id is not None and obj.shield_id == "__disabled__": + logger.debug(f"Skipping {rsrc.capitalize()} registration for disabled shield.") + continue + # we want to maintain the type information in arguments to method. # instead of method(**obj.model_dump()), which may convert a typed attr to a dict, # we use model_dump() to find all the attrs and then getattr to get the still typed value. diff --git a/llama_stack/providers/inline/safety/llama_guard/llama_guard.py b/llama_stack/providers/inline/safety/llama_guard/llama_guard.py index 30d7f93cd..9d359e053 100644 --- a/llama_stack/providers/inline/safety/llama_guard/llama_guard.py +++ b/llama_stack/providers/inline/safety/llama_guard/llama_guard.py @@ -146,10 +146,9 @@ class LlamaGuardSafetyImpl(Safety, ShieldsProtocolPrivate): pass async def register_shield(self, shield: Shield) -> None: - if shield.provider_resource_id not in LLAMA_GUARD_MODEL_IDS: - raise ValueError( - f"Unsupported Llama Guard type: {shield.provider_resource_id}. Allowed types: {LLAMA_GUARD_MODEL_IDS}" - ) + # Allow any model to be registered as a shield + # The model will be validated during runtime when making inference calls + pass async def run_shield( self, @@ -167,11 +166,25 @@ class LlamaGuardSafetyImpl(Safety, ShieldsProtocolPrivate): if len(messages) > 0 and messages[0].role != Role.user.value: messages[0] = UserMessage(content=messages[0].content) - model = LLAMA_GUARD_MODEL_IDS[shield.provider_resource_id] + # Use the inference API's model resolution instead of hardcoded mappings + # This allows the shield to work with any registered model + model_id = shield.provider_resource_id + + # Determine safety categories based on the model type + # For known Llama Guard models, use specific categories + if model_id in LLAMA_GUARD_MODEL_IDS: + # Use the mapped model for categories but the original model_id for inference + mapped_model = LLAMA_GUARD_MODEL_IDS[model_id] + safety_categories = MODEL_TO_SAFETY_CATEGORIES_MAP.get(mapped_model, DEFAULT_LG_V3_SAFETY_CATEGORIES) + else: + # For unknown models, use default Llama Guard 3 8B categories + safety_categories = DEFAULT_LG_V3_SAFETY_CATEGORIES + [CAT_CODE_INTERPRETER_ABUSE] + impl = LlamaGuardShield( - model=model, + model=model_id, inference_api=self.inference_api, excluded_categories=self.config.excluded_categories, + safety_categories=safety_categories, ) return await impl.run(messages) @@ -183,20 +196,21 @@ class LlamaGuardShield: model: str, inference_api: Inference, excluded_categories: list[str] | None = None, + safety_categories: list[str] | None = None, ): if excluded_categories is None: excluded_categories = [] + if safety_categories is None: + safety_categories = [] assert len(excluded_categories) == 0 or all( x in SAFETY_CATEGORIES_TO_CODE_MAP.values() for x in excluded_categories ), "Invalid categories in excluded categories. Expected format is ['S1', 'S2', ..]" - if model not in MODEL_TO_SAFETY_CATEGORIES_MAP: - raise ValueError(f"Unsupported model: {model}") - self.model = model self.inference_api = inference_api self.excluded_categories = excluded_categories + self.safety_categories = safety_categories def check_unsafe_response(self, response: str) -> str | None: match = re.match(r"^unsafe\n(.*)$", response) @@ -214,7 +228,7 @@ class LlamaGuardShield: final_categories = [] - all_categories = MODEL_TO_SAFETY_CATEGORIES_MAP[self.model] + all_categories = self.safety_categories for cat in all_categories: cat_code = SAFETY_CATEGORIES_TO_CODE_MAP[cat] if cat_code in excluded_categories: diff --git a/llama_stack/providers/remote/inference/anthropic/models.py b/llama_stack/providers/remote/inference/anthropic/models.py index afaf3c4e4..172e06c70 100644 --- a/llama_stack/providers/remote/inference/anthropic/models.py +++ b/llama_stack/providers/remote/inference/anthropic/models.py @@ -15,21 +15,26 @@ LLM_MODEL_IDS = [ "anthropic/claude-3-5-haiku-latest", ] +SAFETY_MODELS_ENTRIES = [] -MODEL_ENTRIES = [ProviderModelEntry(provider_model_id=m) for m in LLM_MODEL_IDS] + [ - ProviderModelEntry( - provider_model_id="anthropic/voyage-3", - model_type=ModelType.embedding, - metadata={"embedding_dimension": 1024, "context_length": 32000}, - ), - ProviderModelEntry( - provider_model_id="anthropic/voyage-3-lite", - model_type=ModelType.embedding, - metadata={"embedding_dimension": 512, "context_length": 32000}, - ), - ProviderModelEntry( - provider_model_id="anthropic/voyage-code-3", - model_type=ModelType.embedding, - metadata={"embedding_dimension": 1024, "context_length": 32000}, - ), -] +MODEL_ENTRIES = ( + [ProviderModelEntry(provider_model_id=m) for m in LLM_MODEL_IDS] + + [ + ProviderModelEntry( + provider_model_id="anthropic/voyage-3", + model_type=ModelType.embedding, + metadata={"embedding_dimension": 1024, "context_length": 32000}, + ), + ProviderModelEntry( + provider_model_id="anthropic/voyage-3-lite", + model_type=ModelType.embedding, + metadata={"embedding_dimension": 512, "context_length": 32000}, + ), + ProviderModelEntry( + provider_model_id="anthropic/voyage-code-3", + model_type=ModelType.embedding, + metadata={"embedding_dimension": 1024, "context_length": 32000}, + ), + ] + + SAFETY_MODELS_ENTRIES +) diff --git a/llama_stack/providers/remote/inference/bedrock/models.py b/llama_stack/providers/remote/inference/bedrock/models.py index ec8120049..17273c122 100644 --- a/llama_stack/providers/remote/inference/bedrock/models.py +++ b/llama_stack/providers/remote/inference/bedrock/models.py @@ -9,6 +9,10 @@ from llama_stack.providers.utils.inference.model_registry import ( build_hf_repo_model_entry, ) +SAFETY_MODELS_ENTRIES = [] + + +# https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html MODEL_ENTRIES = [ build_hf_repo_model_entry( "meta.llama3-1-8b-instruct-v1:0", @@ -22,4 +26,4 @@ MODEL_ENTRIES = [ "meta.llama3-1-405b-instruct-v1:0", CoreModelId.llama3_1_405b_instruct.value, ), -] +] + SAFETY_MODELS_ENTRIES diff --git a/llama_stack/providers/remote/inference/cerebras/models.py b/llama_stack/providers/remote/inference/cerebras/models.py index 38301b32a..4de2e62c9 100644 --- a/llama_stack/providers/remote/inference/cerebras/models.py +++ b/llama_stack/providers/remote/inference/cerebras/models.py @@ -9,6 +9,9 @@ from llama_stack.providers.utils.inference.model_registry import ( build_hf_repo_model_entry, ) +SAFETY_MODELS_ENTRIES = [] + +# https://inference-docs.cerebras.ai/models MODEL_ENTRIES = [ build_hf_repo_model_entry( "llama3.1-8b", @@ -18,4 +21,8 @@ MODEL_ENTRIES = [ "llama-3.3-70b", CoreModelId.llama3_3_70b_instruct.value, ), -] + build_hf_repo_model_entry( + "llama-4-scout-17b-16e-instruct", + CoreModelId.llama4_scout_17b_16e_instruct.value, + ), +] + SAFETY_MODELS_ENTRIES diff --git a/llama_stack/providers/remote/inference/databricks/databricks.py b/llama_stack/providers/remote/inference/databricks/databricks.py index 1dc18b97f..34ee59212 100644 --- a/llama_stack/providers/remote/inference/databricks/databricks.py +++ b/llama_stack/providers/remote/inference/databricks/databricks.py @@ -47,7 +47,10 @@ from llama_stack.providers.utils.inference.prompt_adapter import ( from .config import DatabricksImplConfig -model_entries = [ +SAFETY_MODELS_ENTRIES = [] + +# https://docs.databricks.com/aws/en/machine-learning/model-serving/foundation-model-overview +MODEL_ENTRIES = [ build_hf_repo_model_entry( "databricks-meta-llama-3-1-70b-instruct", CoreModelId.llama3_1_70b_instruct.value, @@ -56,7 +59,7 @@ model_entries = [ "databricks-meta-llama-3-1-405b-instruct", CoreModelId.llama3_1_405b_instruct.value, ), -] +] + SAFETY_MODELS_ENTRIES class DatabricksInferenceAdapter( @@ -66,7 +69,7 @@ class DatabricksInferenceAdapter( OpenAICompletionToLlamaStackMixin, ): def __init__(self, config: DatabricksImplConfig) -> None: - ModelRegistryHelper.__init__(self, model_entries=model_entries) + ModelRegistryHelper.__init__(self, model_entries=MODEL_ENTRIES) self.config = config async def initialize(self) -> None: diff --git a/llama_stack/providers/remote/inference/fireworks/models.py b/llama_stack/providers/remote/inference/fireworks/models.py index 392aed72f..30807a0d4 100644 --- a/llama_stack/providers/remote/inference/fireworks/models.py +++ b/llama_stack/providers/remote/inference/fireworks/models.py @@ -11,6 +11,17 @@ from llama_stack.providers.utils.inference.model_registry import ( build_hf_repo_model_entry, ) +SAFETY_MODELS_ENTRIES = [ + build_hf_repo_model_entry( + "accounts/fireworks/models/llama-guard-3-8b", + CoreModelId.llama_guard_3_8b.value, + ), + build_hf_repo_model_entry( + "accounts/fireworks/models/llama-guard-3-11b-vision", + CoreModelId.llama_guard_3_11b_vision.value, + ), +] + MODEL_ENTRIES = [ build_hf_repo_model_entry( "accounts/fireworks/models/llama-v3p1-8b-instruct", @@ -40,14 +51,6 @@ MODEL_ENTRIES = [ "accounts/fireworks/models/llama-v3p3-70b-instruct", CoreModelId.llama3_3_70b_instruct.value, ), - build_hf_repo_model_entry( - "accounts/fireworks/models/llama-guard-3-8b", - CoreModelId.llama_guard_3_8b.value, - ), - build_hf_repo_model_entry( - "accounts/fireworks/models/llama-guard-3-11b-vision", - CoreModelId.llama_guard_3_11b_vision.value, - ), build_hf_repo_model_entry( "accounts/fireworks/models/llama4-scout-instruct-basic", CoreModelId.llama4_scout_17b_16e_instruct.value, @@ -64,4 +67,4 @@ MODEL_ENTRIES = [ "context_length": 8192, }, ), -] +] + SAFETY_MODELS_ENTRIES diff --git a/llama_stack/providers/remote/inference/gemini/models.py b/llama_stack/providers/remote/inference/gemini/models.py index c4bb4f08b..a7f4732ec 100644 --- a/llama_stack/providers/remote/inference/gemini/models.py +++ b/llama_stack/providers/remote/inference/gemini/models.py @@ -17,11 +17,16 @@ LLM_MODEL_IDS = [ "gemini/gemini-2.5-pro", ] +SAFETY_MODELS_ENTRIES = [] -MODEL_ENTRIES = [ProviderModelEntry(provider_model_id=m) for m in LLM_MODEL_IDS] + [ - ProviderModelEntry( - provider_model_id="gemini/text-embedding-004", - model_type=ModelType.embedding, - metadata={"embedding_dimension": 768, "context_length": 2048}, - ), -] +MODEL_ENTRIES = ( + [ProviderModelEntry(provider_model_id=m) for m in LLM_MODEL_IDS] + + [ + ProviderModelEntry( + provider_model_id="gemini/text-embedding-004", + model_type=ModelType.embedding, + metadata={"embedding_dimension": 768, "context_length": 2048}, + ), + ] + + SAFETY_MODELS_ENTRIES +) diff --git a/llama_stack/providers/remote/inference/groq/models.py b/llama_stack/providers/remote/inference/groq/models.py index 0b4b81cfe..70c089c4a 100644 --- a/llama_stack/providers/remote/inference/groq/models.py +++ b/llama_stack/providers/remote/inference/groq/models.py @@ -10,6 +10,8 @@ from llama_stack.providers.utils.inference.model_registry import ( build_model_entry, ) +SAFETY_MODELS_ENTRIES = [] + MODEL_ENTRIES = [ build_hf_repo_model_entry( "groq/llama3-8b-8192", @@ -51,4 +53,4 @@ MODEL_ENTRIES = [ "groq/meta-llama/llama-4-maverick-17b-128e-instruct", CoreModelId.llama4_maverick_17b_128e_instruct.value, ), -] +] + SAFETY_MODELS_ENTRIES diff --git a/llama_stack/providers/remote/inference/nvidia/models.py b/llama_stack/providers/remote/inference/nvidia/models.py index 127a6ca59..76e579da8 100644 --- a/llama_stack/providers/remote/inference/nvidia/models.py +++ b/llama_stack/providers/remote/inference/nvidia/models.py @@ -11,6 +11,9 @@ from llama_stack.providers.utils.inference.model_registry import ( build_hf_repo_model_entry, ) +SAFETY_MODELS_ENTRIES = [] + +# https://docs.nvidia.com/nim/large-language-models/latest/supported-llm-agnostic-architectures.html MODEL_ENTRIES = [ build_hf_repo_model_entry( "meta/llama3-8b-instruct", @@ -99,4 +102,4 @@ MODEL_ENTRIES = [ ), # TODO(mf): how do we handle Nemotron models? # "Llama3.1-Nemotron-51B-Instruct" -> "meta/llama-3.1-nemotron-51b-instruct", -] +] + SAFETY_MODELS_ENTRIES diff --git a/llama_stack/providers/remote/inference/openai/models.py b/llama_stack/providers/remote/inference/openai/models.py index 14a6955d5..37bee57de 100644 --- a/llama_stack/providers/remote/inference/openai/models.py +++ b/llama_stack/providers/remote/inference/openai/models.py @@ -48,16 +48,20 @@ EMBEDDING_MODEL_IDS: dict[str, EmbeddingModelInfo] = { "text-embedding-3-small": EmbeddingModelInfo(1536, 8192), "text-embedding-3-large": EmbeddingModelInfo(3072, 8192), } +SAFETY_MODELS_ENTRIES = [] - -MODEL_ENTRIES = [ProviderModelEntry(provider_model_id=m) for m in LLM_MODEL_IDS] + [ - ProviderModelEntry( - provider_model_id=model_id, - model_type=ModelType.embedding, - metadata={ - "embedding_dimension": model_info.embedding_dimension, - "context_length": model_info.context_length, - }, - ) - for model_id, model_info in EMBEDDING_MODEL_IDS.items() -] +MODEL_ENTRIES = ( + [ProviderModelEntry(provider_model_id=m) for m in LLM_MODEL_IDS] + + [ + ProviderModelEntry( + provider_model_id=model_id, + model_type=ModelType.embedding, + metadata={ + "embedding_dimension": model_info.embedding_dimension, + "context_length": model_info.context_length, + }, + ) + for model_id, model_info in EMBEDDING_MODEL_IDS.items() + ] + + SAFETY_MODELS_ENTRIES +) diff --git a/llama_stack/providers/remote/inference/runpod/runpod.py b/llama_stack/providers/remote/inference/runpod/runpod.py index afdb33b62..ff2fe6401 100644 --- a/llama_stack/providers/remote/inference/runpod/runpod.py +++ b/llama_stack/providers/remote/inference/runpod/runpod.py @@ -11,7 +11,7 @@ from llama_stack.apis.inference import * # noqa: F403 from llama_stack.apis.inference import OpenAIEmbeddingsResponse # from llama_stack.providers.datatypes import ModelsProtocolPrivate -from llama_stack.providers.utils.inference.model_registry import ModelRegistryHelper +from llama_stack.providers.utils.inference.model_registry import ModelRegistryHelper, build_hf_repo_model_entry from llama_stack.providers.utils.inference.openai_compat import ( OpenAIChatCompletionToLlamaStackMixin, OpenAICompletionToLlamaStackMixin, @@ -25,6 +25,8 @@ from llama_stack.providers.utils.inference.prompt_adapter import ( from .config import RunpodImplConfig +# https://docs.runpod.io/serverless/vllm/overview#compatible-models +# https://github.com/runpod-workers/worker-vllm/blob/main/README.md#compatible-model-architectures RUNPOD_SUPPORTED_MODELS = { "Llama3.1-8B": "meta-llama/Llama-3.1-8B", "Llama3.1-70B": "meta-llama/Llama-3.1-70B", @@ -40,6 +42,14 @@ RUNPOD_SUPPORTED_MODELS = { "Llama3.2-3B": "meta-llama/Llama-3.2-3B", } +SAFETY_MODELS_ENTRIES = [] + +# Create MODEL_ENTRIES from RUNPOD_SUPPORTED_MODELS for compatibility with starter template +MODEL_ENTRIES = [ + build_hf_repo_model_entry(provider_model_id, model_descriptor) + for provider_model_id, model_descriptor in RUNPOD_SUPPORTED_MODELS.items() +] + SAFETY_MODELS_ENTRIES + class RunpodInferenceAdapter( ModelRegistryHelper, diff --git a/llama_stack/providers/remote/inference/sambanova/models.py b/llama_stack/providers/remote/inference/sambanova/models.py index 9954fa7a0..0b8c2e042 100644 --- a/llama_stack/providers/remote/inference/sambanova/models.py +++ b/llama_stack/providers/remote/inference/sambanova/models.py @@ -9,6 +9,14 @@ from llama_stack.providers.utils.inference.model_registry import ( build_hf_repo_model_entry, ) +SAFETY_MODELS_ENTRIES = [ + build_hf_repo_model_entry( + "sambanova/Meta-Llama-Guard-3-8B", + CoreModelId.llama_guard_3_8b.value, + ), +] + + MODEL_ENTRIES = [ build_hf_repo_model_entry( "sambanova/Meta-Llama-3.1-8B-Instruct", @@ -46,8 +54,4 @@ MODEL_ENTRIES = [ "sambanova/Llama-4-Maverick-17B-128E-Instruct", CoreModelId.llama4_maverick_17b_128e_instruct.value, ), - build_hf_repo_model_entry( - "sambanova/Meta-Llama-Guard-3-8B", - CoreModelId.llama_guard_3_8b.value, - ), -] +] + SAFETY_MODELS_ENTRIES diff --git a/llama_stack/providers/remote/inference/together/models.py b/llama_stack/providers/remote/inference/together/models.py index 85e1b1848..3d19f8dec 100644 --- a/llama_stack/providers/remote/inference/together/models.py +++ b/llama_stack/providers/remote/inference/together/models.py @@ -11,6 +11,16 @@ from llama_stack.providers.utils.inference.model_registry import ( build_hf_repo_model_entry, ) +SAFETY_MODELS_ENTRIES = [ + build_hf_repo_model_entry( + "meta-llama/Llama-Guard-3-8B", + CoreModelId.llama_guard_3_8b.value, + ), + build_hf_repo_model_entry( + "meta-llama/Llama-Guard-3-11B-Vision-Turbo", + CoreModelId.llama_guard_3_11b_vision.value, + ), +] MODEL_ENTRIES = [ build_hf_repo_model_entry( "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo", @@ -40,14 +50,6 @@ MODEL_ENTRIES = [ "meta-llama/Llama-3.3-70B-Instruct-Turbo", CoreModelId.llama3_3_70b_instruct.value, ), - build_hf_repo_model_entry( - "meta-llama/Meta-Llama-Guard-3-8B", - CoreModelId.llama_guard_3_8b.value, - ), - build_hf_repo_model_entry( - "meta-llama/Llama-Guard-3-11B-Vision-Turbo", - CoreModelId.llama_guard_3_11b_vision.value, - ), ProviderModelEntry( provider_model_id="togethercomputer/m2-bert-80M-8k-retrieval", model_type=ModelType.embedding, @@ -78,4 +80,4 @@ MODEL_ENTRIES = [ "together/meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8", ], ), -] +] + SAFETY_MODELS_ENTRIES diff --git a/llama_stack/providers/utils/inference/model_registry.py b/llama_stack/providers/utils/inference/model_registry.py index 46c0ca7b5..c2fc13e07 100644 --- a/llama_stack/providers/utils/inference/model_registry.py +++ b/llama_stack/providers/utils/inference/model_registry.py @@ -44,6 +44,7 @@ def build_hf_repo_model_entry( ] if additional_aliases: aliases.extend(additional_aliases) + aliases = [alias for alias in aliases if alias is not None] return ProviderModelEntry( provider_model_id=provider_model_id, aliases=aliases, @@ -90,7 +91,7 @@ class ModelRegistryHelper(ModelsProtocolPrivate): # embedding models are always registered by their provider model id and does not need to be mapped to a llama model provider_resource_id = model.provider_resource_id if provider_resource_id: - if provider_resource_id != supported_model_id: # be idemopotent, only reject differences + if provider_resource_id != supported_model_id: # be idempotent, only reject differences raise ValueError( f"Model id '{model.model_id}' is already registered. Please use a different id or unregister it first." ) diff --git a/llama_stack/templates/starter/run.yaml b/llama_stack/templates/starter/run.yaml index 02288da44..b3dfe32d5 100644 --- a/llama_stack/templates/starter/run.yaml +++ b/llama_stack/templates/starter/run.yaml @@ -256,11 +256,46 @@ inference_store: type: sqlite db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter}/inference_store.db models: +- metadata: {} + model_id: ${env.ENABLE_CEREBRAS:=__disabled__}/llama3.1-8b + provider_id: ${env.ENABLE_CEREBRAS:=__disabled__} + provider_model_id: llama3.1-8b + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_CEREBRAS:=__disabled__}/meta-llama/Llama-3.1-8B-Instruct + provider_id: ${env.ENABLE_CEREBRAS:=__disabled__} + provider_model_id: llama3.1-8b + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_CEREBRAS:=__disabled__}/llama-3.3-70b + provider_id: ${env.ENABLE_CEREBRAS:=__disabled__} + provider_model_id: llama-3.3-70b + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_CEREBRAS:=__disabled__}/meta-llama/Llama-3.3-70B-Instruct + provider_id: ${env.ENABLE_CEREBRAS:=__disabled__} + provider_model_id: llama-3.3-70b + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_CEREBRAS:=__disabled__}/llama-4-scout-17b-16e-instruct + provider_id: ${env.ENABLE_CEREBRAS:=__disabled__} + provider_model_id: llama-4-scout-17b-16e-instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_CEREBRAS:=__disabled__}/meta-llama/Llama-4-Scout-17B-16E-Instruct + provider_id: ${env.ENABLE_CEREBRAS:=__disabled__} + provider_model_id: llama-4-scout-17b-16e-instruct + model_type: llm - metadata: {} model_id: ${env.ENABLE_OLLAMA:=__disabled__}/${env.OLLAMA_INFERENCE_MODEL:=__disabled__} provider_id: ${env.ENABLE_OLLAMA:=__disabled__} provider_model_id: ${env.OLLAMA_INFERENCE_MODEL:=__disabled__} model_type: llm +- metadata: {} + model_id: ${env.ENABLE_OLLAMA:=__disabled__}/${env.SAFETY_MODEL:=__disabled__} + provider_id: ${env.ENABLE_OLLAMA:=__disabled__} + provider_model_id: ${env.SAFETY_MODEL:=__disabled__} + model_type: llm - metadata: embedding_dimension: ${env.OLLAMA_EMBEDDING_DIMENSION:=384} model_id: ${env.ENABLE_OLLAMA:=__disabled__}/${env.OLLAMA_EMBEDDING_MODEL:=__disabled__} @@ -342,26 +377,6 @@ models: provider_id: ${env.ENABLE_FIREWORKS:=__disabled__} provider_model_id: accounts/fireworks/models/llama-v3p3-70b-instruct model_type: llm -- metadata: {} - model_id: ${env.ENABLE_FIREWORKS:=__disabled__}/accounts/fireworks/models/llama-guard-3-8b - provider_id: ${env.ENABLE_FIREWORKS:=__disabled__} - provider_model_id: accounts/fireworks/models/llama-guard-3-8b - model_type: llm -- metadata: {} - model_id: ${env.ENABLE_FIREWORKS:=__disabled__}/meta-llama/Llama-Guard-3-8B - provider_id: ${env.ENABLE_FIREWORKS:=__disabled__} - provider_model_id: accounts/fireworks/models/llama-guard-3-8b - model_type: llm -- metadata: {} - model_id: ${env.ENABLE_FIREWORKS:=__disabled__}/accounts/fireworks/models/llama-guard-3-11b-vision - provider_id: ${env.ENABLE_FIREWORKS:=__disabled__} - provider_model_id: accounts/fireworks/models/llama-guard-3-11b-vision - model_type: llm -- metadata: {} - model_id: ${env.ENABLE_FIREWORKS:=__disabled__}/meta-llama/Llama-Guard-3-11B-Vision - provider_id: ${env.ENABLE_FIREWORKS:=__disabled__} - provider_model_id: accounts/fireworks/models/llama-guard-3-11b-vision - model_type: llm - metadata: {} model_id: ${env.ENABLE_FIREWORKS:=__disabled__}/accounts/fireworks/models/llama4-scout-instruct-basic provider_id: ${env.ENABLE_FIREWORKS:=__disabled__} @@ -389,6 +404,26 @@ models: provider_id: ${env.ENABLE_FIREWORKS:=__disabled__} provider_model_id: nomic-ai/nomic-embed-text-v1.5 model_type: embedding +- metadata: {} + model_id: ${env.ENABLE_FIREWORKS:=__disabled__}/accounts/fireworks/models/llama-guard-3-8b + provider_id: ${env.ENABLE_FIREWORKS:=__disabled__} + provider_model_id: accounts/fireworks/models/llama-guard-3-8b + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_FIREWORKS:=__disabled__}/meta-llama/Llama-Guard-3-8B + provider_id: ${env.ENABLE_FIREWORKS:=__disabled__} + provider_model_id: accounts/fireworks/models/llama-guard-3-8b + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_FIREWORKS:=__disabled__}/accounts/fireworks/models/llama-guard-3-11b-vision + provider_id: ${env.ENABLE_FIREWORKS:=__disabled__} + provider_model_id: accounts/fireworks/models/llama-guard-3-11b-vision + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_FIREWORKS:=__disabled__}/meta-llama/Llama-Guard-3-11B-Vision + provider_id: ${env.ENABLE_FIREWORKS:=__disabled__} + provider_model_id: accounts/fireworks/models/llama-guard-3-11b-vision + model_type: llm - metadata: {} model_id: ${env.ENABLE_TOGETHER:=__disabled__}/meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo provider_id: ${env.ENABLE_TOGETHER:=__disabled__} @@ -459,26 +494,6 @@ models: provider_id: ${env.ENABLE_TOGETHER:=__disabled__} provider_model_id: meta-llama/Llama-3.3-70B-Instruct-Turbo model_type: llm -- metadata: {} - model_id: ${env.ENABLE_TOGETHER:=__disabled__}/meta-llama/Meta-Llama-Guard-3-8B - provider_id: ${env.ENABLE_TOGETHER:=__disabled__} - provider_model_id: meta-llama/Meta-Llama-Guard-3-8B - model_type: llm -- metadata: {} - model_id: ${env.ENABLE_TOGETHER:=__disabled__}/meta-llama/Llama-Guard-3-8B - provider_id: ${env.ENABLE_TOGETHER:=__disabled__} - provider_model_id: meta-llama/Meta-Llama-Guard-3-8B - model_type: llm -- metadata: {} - model_id: ${env.ENABLE_TOGETHER:=__disabled__}/meta-llama/Llama-Guard-3-11B-Vision-Turbo - provider_id: ${env.ENABLE_TOGETHER:=__disabled__} - provider_model_id: meta-llama/Llama-Guard-3-11B-Vision-Turbo - model_type: llm -- metadata: {} - model_id: ${env.ENABLE_TOGETHER:=__disabled__}/meta-llama/Llama-Guard-3-11B-Vision - provider_id: ${env.ENABLE_TOGETHER:=__disabled__} - provider_model_id: meta-llama/Llama-Guard-3-11B-Vision-Turbo - model_type: llm - metadata: embedding_dimension: 768 context_length: 8192 @@ -523,6 +538,264 @@ models: provider_id: ${env.ENABLE_TOGETHER:=__disabled__} provider_model_id: meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8 model_type: llm +- metadata: {} + model_id: ${env.ENABLE_TOGETHER:=__disabled__}/meta-llama/Llama-Guard-3-8B + provider_id: ${env.ENABLE_TOGETHER:=__disabled__} + provider_model_id: meta-llama/Llama-Guard-3-8B + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_TOGETHER:=__disabled__}/meta-llama/Llama-Guard-3-8B + provider_id: ${env.ENABLE_TOGETHER:=__disabled__} + provider_model_id: meta-llama/Llama-Guard-3-8B + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_TOGETHER:=__disabled__}/meta-llama/Llama-Guard-3-11B-Vision-Turbo + provider_id: ${env.ENABLE_TOGETHER:=__disabled__} + provider_model_id: meta-llama/Llama-Guard-3-11B-Vision-Turbo + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_TOGETHER:=__disabled__}/meta-llama/Llama-Guard-3-11B-Vision + provider_id: ${env.ENABLE_TOGETHER:=__disabled__} + provider_model_id: meta-llama/Llama-Guard-3-11B-Vision-Turbo + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_BEDROCK:=__disabled__}/meta.llama3-1-8b-instruct-v1:0 + provider_id: ${env.ENABLE_BEDROCK:=__disabled__} + provider_model_id: meta.llama3-1-8b-instruct-v1:0 + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_BEDROCK:=__disabled__}/meta-llama/Llama-3.1-8B-Instruct + provider_id: ${env.ENABLE_BEDROCK:=__disabled__} + provider_model_id: meta.llama3-1-8b-instruct-v1:0 + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_BEDROCK:=__disabled__}/meta.llama3-1-70b-instruct-v1:0 + provider_id: ${env.ENABLE_BEDROCK:=__disabled__} + provider_model_id: meta.llama3-1-70b-instruct-v1:0 + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_BEDROCK:=__disabled__}/meta-llama/Llama-3.1-70B-Instruct + provider_id: ${env.ENABLE_BEDROCK:=__disabled__} + provider_model_id: meta.llama3-1-70b-instruct-v1:0 + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_BEDROCK:=__disabled__}/meta.llama3-1-405b-instruct-v1:0 + provider_id: ${env.ENABLE_BEDROCK:=__disabled__} + provider_model_id: meta.llama3-1-405b-instruct-v1:0 + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_BEDROCK:=__disabled__}/meta-llama/Llama-3.1-405B-Instruct-FP8 + provider_id: ${env.ENABLE_BEDROCK:=__disabled__} + provider_model_id: meta.llama3-1-405b-instruct-v1:0 + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_DATABRICKS:=__disabled__}/databricks-meta-llama-3-1-70b-instruct + provider_id: ${env.ENABLE_DATABRICKS:=__disabled__} + provider_model_id: databricks-meta-llama-3-1-70b-instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_DATABRICKS:=__disabled__}/meta-llama/Llama-3.1-70B-Instruct + provider_id: ${env.ENABLE_DATABRICKS:=__disabled__} + provider_model_id: databricks-meta-llama-3-1-70b-instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_DATABRICKS:=__disabled__}/databricks-meta-llama-3-1-405b-instruct + provider_id: ${env.ENABLE_DATABRICKS:=__disabled__} + provider_model_id: databricks-meta-llama-3-1-405b-instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_DATABRICKS:=__disabled__}/meta-llama/Llama-3.1-405B-Instruct-FP8 + provider_id: ${env.ENABLE_DATABRICKS:=__disabled__} + provider_model_id: databricks-meta-llama-3-1-405b-instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_NVIDIA:=__disabled__}/meta/llama3-8b-instruct + provider_id: ${env.ENABLE_NVIDIA:=__disabled__} + provider_model_id: meta/llama3-8b-instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_NVIDIA:=__disabled__}/meta-llama/Llama-3-8B-Instruct + provider_id: ${env.ENABLE_NVIDIA:=__disabled__} + provider_model_id: meta/llama3-8b-instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_NVIDIA:=__disabled__}/meta/llama3-70b-instruct + provider_id: ${env.ENABLE_NVIDIA:=__disabled__} + provider_model_id: meta/llama3-70b-instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_NVIDIA:=__disabled__}/meta-llama/Llama-3-70B-Instruct + provider_id: ${env.ENABLE_NVIDIA:=__disabled__} + provider_model_id: meta/llama3-70b-instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_NVIDIA:=__disabled__}/meta/llama-3.1-8b-instruct + provider_id: ${env.ENABLE_NVIDIA:=__disabled__} + provider_model_id: meta/llama-3.1-8b-instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_NVIDIA:=__disabled__}/meta-llama/Llama-3.1-8B-Instruct + provider_id: ${env.ENABLE_NVIDIA:=__disabled__} + provider_model_id: meta/llama-3.1-8b-instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_NVIDIA:=__disabled__}/meta/llama-3.1-70b-instruct + provider_id: ${env.ENABLE_NVIDIA:=__disabled__} + provider_model_id: meta/llama-3.1-70b-instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_NVIDIA:=__disabled__}/meta-llama/Llama-3.1-70B-Instruct + provider_id: ${env.ENABLE_NVIDIA:=__disabled__} + provider_model_id: meta/llama-3.1-70b-instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_NVIDIA:=__disabled__}/meta/llama-3.1-405b-instruct + provider_id: ${env.ENABLE_NVIDIA:=__disabled__} + provider_model_id: meta/llama-3.1-405b-instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_NVIDIA:=__disabled__}/meta-llama/Llama-3.1-405B-Instruct-FP8 + provider_id: ${env.ENABLE_NVIDIA:=__disabled__} + provider_model_id: meta/llama-3.1-405b-instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_NVIDIA:=__disabled__}/meta/llama-3.2-1b-instruct + provider_id: ${env.ENABLE_NVIDIA:=__disabled__} + provider_model_id: meta/llama-3.2-1b-instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_NVIDIA:=__disabled__}/meta-llama/Llama-3.2-1B-Instruct + provider_id: ${env.ENABLE_NVIDIA:=__disabled__} + provider_model_id: meta/llama-3.2-1b-instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_NVIDIA:=__disabled__}/meta/llama-3.2-3b-instruct + provider_id: ${env.ENABLE_NVIDIA:=__disabled__} + provider_model_id: meta/llama-3.2-3b-instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_NVIDIA:=__disabled__}/meta-llama/Llama-3.2-3B-Instruct + provider_id: ${env.ENABLE_NVIDIA:=__disabled__} + provider_model_id: meta/llama-3.2-3b-instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_NVIDIA:=__disabled__}/meta/llama-3.2-11b-vision-instruct + provider_id: ${env.ENABLE_NVIDIA:=__disabled__} + provider_model_id: meta/llama-3.2-11b-vision-instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_NVIDIA:=__disabled__}/meta-llama/Llama-3.2-11B-Vision-Instruct + provider_id: ${env.ENABLE_NVIDIA:=__disabled__} + provider_model_id: meta/llama-3.2-11b-vision-instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_NVIDIA:=__disabled__}/meta/llama-3.2-90b-vision-instruct + provider_id: ${env.ENABLE_NVIDIA:=__disabled__} + provider_model_id: meta/llama-3.2-90b-vision-instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_NVIDIA:=__disabled__}/meta-llama/Llama-3.2-90B-Vision-Instruct + provider_id: ${env.ENABLE_NVIDIA:=__disabled__} + provider_model_id: meta/llama-3.2-90b-vision-instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_NVIDIA:=__disabled__}/meta/llama-3.3-70b-instruct + provider_id: ${env.ENABLE_NVIDIA:=__disabled__} + provider_model_id: meta/llama-3.3-70b-instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_NVIDIA:=__disabled__}/meta-llama/Llama-3.3-70B-Instruct + provider_id: ${env.ENABLE_NVIDIA:=__disabled__} + provider_model_id: meta/llama-3.3-70b-instruct + model_type: llm +- metadata: + embedding_dimension: 2048 + context_length: 8192 + model_id: ${env.ENABLE_NVIDIA:=__disabled__}/nvidia/llama-3.2-nv-embedqa-1b-v2 + provider_id: ${env.ENABLE_NVIDIA:=__disabled__} + provider_model_id: nvidia/llama-3.2-nv-embedqa-1b-v2 + model_type: embedding +- metadata: + embedding_dimension: 1024 + context_length: 512 + model_id: ${env.ENABLE_NVIDIA:=__disabled__}/nvidia/nv-embedqa-e5-v5 + provider_id: ${env.ENABLE_NVIDIA:=__disabled__} + provider_model_id: nvidia/nv-embedqa-e5-v5 + model_type: embedding +- metadata: + embedding_dimension: 4096 + context_length: 512 + model_id: ${env.ENABLE_NVIDIA:=__disabled__}/nvidia/nv-embedqa-mistral-7b-v2 + provider_id: ${env.ENABLE_NVIDIA:=__disabled__} + provider_model_id: nvidia/nv-embedqa-mistral-7b-v2 + model_type: embedding +- metadata: + embedding_dimension: 1024 + context_length: 512 + model_id: ${env.ENABLE_NVIDIA:=__disabled__}/snowflake/arctic-embed-l + provider_id: ${env.ENABLE_NVIDIA:=__disabled__} + provider_model_id: snowflake/arctic-embed-l + model_type: embedding +- metadata: {} + model_id: ${env.ENABLE_RUNPOD:=__disabled__}/Llama3.1-8B + provider_id: ${env.ENABLE_RUNPOD:=__disabled__} + provider_model_id: Llama3.1-8B + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_RUNPOD:=__disabled__}/Llama3.1-70B + provider_id: ${env.ENABLE_RUNPOD:=__disabled__} + provider_model_id: Llama3.1-70B + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_RUNPOD:=__disabled__}/Llama3.1-405B:bf16-mp8 + provider_id: ${env.ENABLE_RUNPOD:=__disabled__} + provider_model_id: Llama3.1-405B:bf16-mp8 + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_RUNPOD:=__disabled__}/Llama3.1-405B + provider_id: ${env.ENABLE_RUNPOD:=__disabled__} + provider_model_id: Llama3.1-405B + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_RUNPOD:=__disabled__}/Llama3.1-405B:bf16-mp16 + provider_id: ${env.ENABLE_RUNPOD:=__disabled__} + provider_model_id: Llama3.1-405B:bf16-mp16 + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_RUNPOD:=__disabled__}/Llama3.1-8B-Instruct + provider_id: ${env.ENABLE_RUNPOD:=__disabled__} + provider_model_id: Llama3.1-8B-Instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_RUNPOD:=__disabled__}/Llama3.1-70B-Instruct + provider_id: ${env.ENABLE_RUNPOD:=__disabled__} + provider_model_id: Llama3.1-70B-Instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_RUNPOD:=__disabled__}/Llama3.1-405B-Instruct:bf16-mp8 + provider_id: ${env.ENABLE_RUNPOD:=__disabled__} + provider_model_id: Llama3.1-405B-Instruct:bf16-mp8 + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_RUNPOD:=__disabled__}/Llama3.1-405B-Instruct + provider_id: ${env.ENABLE_RUNPOD:=__disabled__} + provider_model_id: Llama3.1-405B-Instruct + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_RUNPOD:=__disabled__}/Llama3.1-405B-Instruct:bf16-mp16 + provider_id: ${env.ENABLE_RUNPOD:=__disabled__} + provider_model_id: Llama3.1-405B-Instruct:bf16-mp16 + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_RUNPOD:=__disabled__}/Llama3.2-1B + provider_id: ${env.ENABLE_RUNPOD:=__disabled__} + provider_model_id: Llama3.2-1B + model_type: llm +- metadata: {} + model_id: ${env.ENABLE_RUNPOD:=__disabled__}/Llama3.2-3B + provider_id: ${env.ENABLE_RUNPOD:=__disabled__} + provider_model_id: Llama3.2-3B + model_type: llm - metadata: {} model_id: ${env.ENABLE_OPENAI:=__disabled__}/openai/gpt-4o provider_id: ${env.ENABLE_OPENAI:=__disabled__} @@ -894,7 +1167,25 @@ models: model_id: all-MiniLM-L6-v2 provider_id: ${env.ENABLE_SENTENCE_TRANSFORMERS:=sentence-transformers} model_type: embedding -shields: [] +shields: +- shield_id: ${env.ENABLE_OLLAMA:=__disabled__} + provider_id: llama-guard + provider_shield_id: ${env.ENABLE_OLLAMA:=__disabled__}/${env.SAFETY_MODEL:=llama-guard3:1b} +- shield_id: ${env.ENABLE_FIREWORKS:=__disabled__} + provider_id: llama-guard + provider_shield_id: ${env.ENABLE_FIREWORKS:=__disabled__}/${env.SAFETY_MODEL:=accounts/fireworks/models/llama-guard-3-8b} +- shield_id: ${env.ENABLE_FIREWORKS:=__disabled__} + provider_id: llama-guard + provider_shield_id: ${env.ENABLE_FIREWORKS:=__disabled__}/${env.SAFETY_MODEL:=accounts/fireworks/models/llama-guard-3-11b-vision} +- shield_id: ${env.ENABLE_TOGETHER:=__disabled__} + provider_id: llama-guard + provider_shield_id: ${env.ENABLE_TOGETHER:=__disabled__}/${env.SAFETY_MODEL:=meta-llama/Llama-Guard-3-8B} +- shield_id: ${env.ENABLE_TOGETHER:=__disabled__} + provider_id: llama-guard + provider_shield_id: ${env.ENABLE_TOGETHER:=__disabled__}/${env.SAFETY_MODEL:=meta-llama/Llama-Guard-3-11B-Vision-Turbo} +- shield_id: ${env.ENABLE_SAMBANOVA:=__disabled__} + provider_id: llama-guard + provider_shield_id: ${env.ENABLE_SAMBANOVA:=__disabled__}/${env.SAFETY_MODEL:=sambanova/Meta-Llama-Guard-3-8B} vector_dbs: [] datasets: [] scoring_fns: [] diff --git a/llama_stack/templates/starter/starter.py b/llama_stack/templates/starter/starter.py index 773693285..6b8aa8974 100644 --- a/llama_stack/templates/starter/starter.py +++ b/llama_stack/templates/starter/starter.py @@ -12,6 +12,7 @@ from llama_stack.distribution.datatypes import ( ModelInput, Provider, ProviderSpec, + ShieldInput, ToolGroupInput, ) from llama_stack.distribution.utils.dynamic import instantiate_class_type @@ -31,24 +32,75 @@ from llama_stack.providers.registry.inference import available_providers from llama_stack.providers.remote.inference.anthropic.models import ( MODEL_ENTRIES as ANTHROPIC_MODEL_ENTRIES, ) +from llama_stack.providers.remote.inference.anthropic.models import ( + SAFETY_MODELS_ENTRIES as ANTHROPIC_SAFETY_MODELS_ENTRIES, +) +from llama_stack.providers.remote.inference.bedrock.models import ( + MODEL_ENTRIES as BEDROCK_MODEL_ENTRIES, +) +from llama_stack.providers.remote.inference.bedrock.models import ( + SAFETY_MODELS_ENTRIES as BEDROCK_SAFETY_MODELS_ENTRIES, +) +from llama_stack.providers.remote.inference.cerebras.models import ( + MODEL_ENTRIES as CEREBRAS_MODEL_ENTRIES, +) +from llama_stack.providers.remote.inference.cerebras.models import ( + SAFETY_MODELS_ENTRIES as CEREBRAS_SAFETY_MODELS_ENTRIES, +) +from llama_stack.providers.remote.inference.databricks.databricks import ( + MODEL_ENTRIES as DATABRICKS_MODEL_ENTRIES, +) +from llama_stack.providers.remote.inference.databricks.databricks import ( + SAFETY_MODELS_ENTRIES as DATABRICKS_SAFETY_MODELS_ENTRIES, +) from llama_stack.providers.remote.inference.fireworks.models import ( MODEL_ENTRIES as FIREWORKS_MODEL_ENTRIES, ) +from llama_stack.providers.remote.inference.fireworks.models import ( + SAFETY_MODELS_ENTRIES as FIREWORKS_SAFETY_MODELS_ENTRIES, +) from llama_stack.providers.remote.inference.gemini.models import ( MODEL_ENTRIES as GEMINI_MODEL_ENTRIES, ) +from llama_stack.providers.remote.inference.gemini.models import ( + SAFETY_MODELS_ENTRIES as GEMINI_SAFETY_MODELS_ENTRIES, +) from llama_stack.providers.remote.inference.groq.models import ( MODEL_ENTRIES as GROQ_MODEL_ENTRIES, ) +from llama_stack.providers.remote.inference.groq.models import ( + SAFETY_MODELS_ENTRIES as GROQ_SAFETY_MODELS_ENTRIES, +) +from llama_stack.providers.remote.inference.nvidia.models import ( + MODEL_ENTRIES as NVIDIA_MODEL_ENTRIES, +) +from llama_stack.providers.remote.inference.nvidia.models import ( + SAFETY_MODELS_ENTRIES as NVIDIA_SAFETY_MODELS_ENTRIES, +) from llama_stack.providers.remote.inference.openai.models import ( MODEL_ENTRIES as OPENAI_MODEL_ENTRIES, ) +from llama_stack.providers.remote.inference.openai.models import ( + SAFETY_MODELS_ENTRIES as OPENAI_SAFETY_MODELS_ENTRIES, +) +from llama_stack.providers.remote.inference.runpod.runpod import ( + MODEL_ENTRIES as RUNPOD_MODEL_ENTRIES, +) +from llama_stack.providers.remote.inference.runpod.runpod import ( + SAFETY_MODELS_ENTRIES as RUNPOD_SAFETY_MODELS_ENTRIES, +) from llama_stack.providers.remote.inference.sambanova.models import ( MODEL_ENTRIES as SAMBANOVA_MODEL_ENTRIES, ) +from llama_stack.providers.remote.inference.sambanova.models import ( + SAFETY_MODELS_ENTRIES as SAMBANOVA_SAFETY_MODELS_ENTRIES, +) from llama_stack.providers.remote.inference.together.models import ( MODEL_ENTRIES as TOGETHER_MODEL_ENTRIES, ) +from llama_stack.providers.remote.inference.together.models import ( + SAFETY_MODELS_ENTRIES as TOGETHER_SAFETY_MODELS_ENTRIES, +) from llama_stack.providers.remote.vector_io.chroma.config import ChromaVectorIOConfig from llama_stack.providers.remote.vector_io.pgvector.config import ( PGVectorVectorIOConfig, @@ -72,6 +124,11 @@ def _get_model_entries_for_provider(provider_type: str) -> list[ProviderModelEnt "gemini": GEMINI_MODEL_ENTRIES, "groq": GROQ_MODEL_ENTRIES, "sambanova": SAMBANOVA_MODEL_ENTRIES, + "cerebras": CEREBRAS_MODEL_ENTRIES, + "bedrock": BEDROCK_MODEL_ENTRIES, + "databricks": DATABRICKS_MODEL_ENTRIES, + "nvidia": NVIDIA_MODEL_ENTRIES, + "runpod": RUNPOD_MODEL_ENTRIES, } # Special handling for providers with dynamic model entries @@ -81,6 +138,10 @@ def _get_model_entries_for_provider(provider_type: str) -> list[ProviderModelEnt provider_model_id="${env.OLLAMA_INFERENCE_MODEL:=__disabled__}", model_type=ModelType.llm, ), + ProviderModelEntry( + provider_model_id="${env.SAFETY_MODEL:=__disabled__}", + model_type=ModelType.llm, + ), ProviderModelEntry( provider_model_id="${env.OLLAMA_EMBEDDING_MODEL:=__disabled__}", model_type=ModelType.embedding, @@ -100,6 +161,35 @@ def _get_model_entries_for_provider(provider_type: str) -> list[ProviderModelEnt return model_entries_map.get(provider_type, []) +def _get_model_safety_entries_for_provider(provider_type: str) -> list[ProviderModelEntry]: + """Get model entries for a specific provider type.""" + safety_model_entries_map = { + "openai": OPENAI_SAFETY_MODELS_ENTRIES, + "fireworks": FIREWORKS_SAFETY_MODELS_ENTRIES, + "together": TOGETHER_SAFETY_MODELS_ENTRIES, + "anthropic": ANTHROPIC_SAFETY_MODELS_ENTRIES, + "gemini": GEMINI_SAFETY_MODELS_ENTRIES, + "groq": GROQ_SAFETY_MODELS_ENTRIES, + "sambanova": SAMBANOVA_SAFETY_MODELS_ENTRIES, + "cerebras": CEREBRAS_SAFETY_MODELS_ENTRIES, + "bedrock": BEDROCK_SAFETY_MODELS_ENTRIES, + "databricks": DATABRICKS_SAFETY_MODELS_ENTRIES, + "nvidia": NVIDIA_SAFETY_MODELS_ENTRIES, + "runpod": RUNPOD_SAFETY_MODELS_ENTRIES, + } + + # Special handling for providers with dynamic model entries + if provider_type == "ollama": + return [ + ProviderModelEntry( + provider_model_id="llama-guard3:1b", + model_type=ModelType.llm, + ), + ] + + return safety_model_entries_map.get(provider_type, []) + + def _get_config_for_provider(provider_spec: ProviderSpec) -> dict[str, Any]: """Get configuration for a provider using its adapter's config class.""" config_class = instantiate_class_type(provider_spec.config_class) @@ -155,6 +245,31 @@ def get_remote_inference_providers() -> tuple[list[Provider], dict[str, list[Pro return inference_providers, available_models +# build a list of shields for all possible providers +def get_shields_for_providers(providers: list[Provider]) -> list[ShieldInput]: + shields = [] + for provider in providers: + provider_type = provider.provider_type.split("::")[1] + safety_model_entries = _get_model_safety_entries_for_provider(provider_type) + if len(safety_model_entries) == 0: + continue + if provider.provider_id: + shield_id = provider.provider_id + else: + raise ValueError(f"Provider {provider.provider_type} has no provider_id") + for safety_model_entry in safety_model_entries: + print(f"provider.provider_id: {provider.provider_id}") + print(f"safety_model_entry.provider_model_id: {safety_model_entry.provider_model_id}") + shields.append( + ShieldInput( + provider_id="llama-guard", + shield_id=shield_id, + provider_shield_id=f"{provider.provider_id}/${{env.SAFETY_MODEL:={safety_model_entry.provider_model_id}}}", + ) + ) + return shields + + def get_distribution_template() -> DistributionTemplate: remote_inference_providers, available_models = get_remote_inference_providers() @@ -192,6 +307,8 @@ def get_distribution_template() -> DistributionTemplate: ), ] + shields = get_shields_for_providers(remote_inference_providers) + providers = { "inference": ([p.provider_type for p in remote_inference_providers] + ["inline::sentence-transformers"]), "vector_io": ([p.provider_type for p in vector_io_providers]), @@ -266,9 +383,7 @@ def get_distribution_template() -> DistributionTemplate: default_models=default_models + [embedding_model], default_tool_groups=default_tool_groups, # TODO: add a way to enable/disable shields on the fly - # default_shields=[ - # ShieldInput(provider_id="llama-guard", shield_id="${env.SAFETY_MODEL:=meta-llama/Llama-Guard-3-8B}") - # ], + default_shields=shields, ), }, run_config_env_vars={ diff --git a/tests/Containerfile b/tests/Containerfile index 441d276c2..d58216810 100644 --- a/tests/Containerfile +++ b/tests/Containerfile @@ -7,7 +7,8 @@ FROM --platform=linux/amd64 ollama/ollama:latest RUN ollama serve & \ sleep 5 && \ ollama pull llama3.2:3b-instruct-fp16 && \ - ollama pull all-minilm:l6-v2 + ollama pull all-minilm:l6-v2 && \ + ollama pull llama-guard3:1b # Set the entrypoint to start ollama serve ENTRYPOINT ["ollama", "serve"] From 1d8c00635c67ced185167f3c27e29433f738141a Mon Sep 17 00:00:00 2001 From: Matthew Farrellee Date: Wed, 9 Jul 2025 11:19:31 -0400 Subject: [PATCH 04/34] chore: Update CODEOWNERS (#2692) add @mattf --- .github/CODEOWNERS | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/CODEOWNERS b/.github/CODEOWNERS index b709c482f..a1eed9432 100644 --- a/.github/CODEOWNERS +++ b/.github/CODEOWNERS @@ -2,4 +2,4 @@ # These owners will be the default owners for everything in # the repo. Unless a later match takes precedence, -* @ashwinb @yanxi0830 @hardikjshah @raghotham @ehhuang @terrytangyuan @leseb @bbrowning @reluctantfuturist +* @ashwinb @yanxi0830 @hardikjshah @raghotham @ehhuang @terrytangyuan @leseb @bbrowning @reluctantfuturist @mattf From 7915551eeefb51ffaa284c2cadbed43641983c69 Mon Sep 17 00:00:00 2001 From: Nathan Weinberg <31703736+nathan-weinberg@users.noreply.github.com> Date: Wed, 9 Jul 2025 16:21:57 -0400 Subject: [PATCH 05/34] build: replace "python-jose" with "python-jose[cryptography]" (#2695) # What does this PR do? `python-jose` recommends using the `cryptography` backend in their installation docs: https://github.com/mpdavis/python-jose?tab=readme-ov-file#cryptographic-backends This PR modifies the LLS dependencies to use this instead of the current `native-python` Signed-off-by: Nathan Weinberg --- pyproject.toml | 2 +- requirements.txt | 6 + uv.lock | 3002 +++++++++++++++++++++++----------------------- 3 files changed, 1528 insertions(+), 1482 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 04a6a685e..30598e5e3 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -32,7 +32,7 @@ dependencies = [ "openai>=1.66", "prompt-toolkit", "python-dotenv", - "python-jose", + "python-jose[cryptography]", "pydantic>=2", "rich", "starlette", diff --git a/requirements.txt b/requirements.txt index 47f0d9660..8ec138a6f 100644 --- a/requirements.txt +++ b/requirements.txt @@ -28,6 +28,8 @@ certifi==2025.1.31 # httpcore # httpx # requests +cffi==1.17.1 ; platform_python_implementation != 'PyPy' + # via cryptography charset-normalizer==3.4.1 # via requests click==8.1.8 @@ -38,6 +40,8 @@ colorama==0.4.6 ; sys_platform == 'win32' # via # click # tqdm +cryptography==45.0.5 + # via python-jose deprecated==1.2.18 # via # opentelemetry-api @@ -156,6 +160,8 @@ pyasn1==0.4.8 # via # python-jose # rsa +pycparser==2.22 ; platform_python_implementation != 'PyPy' + # via cffi pydantic==2.10.6 # via # fastapi diff --git a/uv.lock b/uv.lock 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_resolve_config_and_template(self, args: argparse.Namespace) -> tuple[Path | None, str | None]: + """Resolve config file path and template name from args.config""" + from llama_stack.distribution.utils.config_dirs import DISTRIBS_BASE_DIR + + if not args.config: + return None, None + + config_file = Path(args.config) + has_yaml_suffix = args.config.endswith(".yaml") + template_name = None + + if not config_file.exists() and not has_yaml_suffix: + # check if this is a template + config_file = Path(REPO_ROOT) / "llama_stack" / "templates" / args.config / "run.yaml" + if config_file.exists(): + template_name = args.config + + if not config_file.exists() and not has_yaml_suffix: + # check if it's a build config saved to ~/.llama dir + config_file = Path(DISTRIBS_BASE_DIR / f"llamastack-{args.config}" / f"{args.config}-run.yaml") + + if not config_file.exists(): + self.parser.error( + f"File {str(config_file)} does not exist.\n\nPlease run `llama stack build` to generate (and optionally edit) a run.yaml file" + ) + + if not config_file.is_file(): + self.parser.error( + f"Config file must be a valid file path, '{config_file}' is not a file: type={type(config_file)}" + ) + + return config_file, template_name + def _run_stack_run_cmd(self, args: argparse.Namespace) -> None: import yaml from llama_stack.distribution.configure import parse_and_maybe_upgrade_config - from llama_stack.distribution.utils.config_dirs import DISTRIBS_BASE_DIR from llama_stack.distribution.utils.exec import formulate_run_args, run_command if args.enable_ui: self._start_ui_development_server(args.port) image_type, image_name = self._get_image_type_and_name(args) + # Resolve config file and template name first + config_file, template_name = self._resolve_config_and_template(args) + # Check if config is required based on image type - if (image_type in [ImageType.CONDA.value, ImageType.VENV.value]) and not args.config: + if (image_type in [ImageType.CONDA.value, ImageType.VENV.value]) and not config_file: self.parser.error("Config file is required for venv and conda environments") - if args.config: - config_file = Path(args.config) - has_yaml_suffix = args.config.endswith(".yaml") - template_name = None - - if not config_file.exists() and not has_yaml_suffix: - # check if this is a template - config_file = Path(REPO_ROOT) / "llama_stack" / "templates" / args.config / "run.yaml" - if config_file.exists(): - template_name = args.config - - if not config_file.exists() and not has_yaml_suffix: - # check if it's a build config saved to ~/.llama dir - config_file = Path(DISTRIBS_BASE_DIR / f"llamastack-{args.config}" / f"{args.config}-run.yaml") - - if not config_file.exists(): - self.parser.error( - f"File {str(config_file)} does not exist.\n\nPlease run `llama stack build` to generate (and optionally edit) a run.yaml file" - ) - - if not config_file.is_file(): - self.parser.error( - f"Config file must be a valid file path, '{config_file}' is not a file: type={type(config_file)}" - ) - + if config_file: logger.info(f"Using run configuration: {config_file}") try: @@ -138,8 +149,6 @@ class StackRun(Subcommand): self.parser.error(f"failed to parse config file '{config_file}':\n {e}") else: config = None - config_file = None - template_name = None # If neither image type nor image name is provided, assume the server should be run directly # using the current environment packages. @@ -172,10 +181,7 @@ class StackRun(Subcommand): run_args.extend([str(args.port)]) if config_file: - if template_name: - run_args.extend(["--template", str(template_name)]) - else: - run_args.extend(["--config", str(config_file)]) + run_args.extend(["--config", str(config_file)]) if args.env: for env_var in args.env: diff --git a/tests/integration/fixtures/common.py b/tests/integration/fixtures/common.py index 6d37d5341..27b2d6dc3 100644 --- a/tests/integration/fixtures/common.py +++ b/tests/integration/fixtures/common.py @@ -197,7 +197,7 @@ def llama_stack_client(request, provider_data): server_process = start_llama_stack_server(config_name) # Wait for server to be ready - if not wait_for_server_ready(base_url, timeout=30, process=server_process): + if not wait_for_server_ready(base_url, timeout=120, process=server_process): print("Server failed to start within timeout") server_process.terminate() raise RuntimeError( From 81109a0f72cdcef280ba11af29009b41f4c88edd Mon Sep 17 00:00:00 2001 From: ehhuang Date: Wed, 9 Jul 2025 20:59:37 -0700 Subject: [PATCH 07/34] test: terminate server process when finished (#2700) # What does this PR do? Terminate server process for real. ## Test Plan ```ENABLE_OPENAI=openai LLAMA_STACK_CONFIG=server:starter pytest -v tests/integration/agents/test_openai_responses.py --text-model "gpt-4o-mini" -vv -s -k 'test_list_response_input_items[' && lsof -ti:8321``` observe no process printed anymore --- tests/integration/fixtures/common.py | 14 ++++++++++---- 1 file changed, 10 insertions(+), 4 deletions(-) diff --git a/tests/integration/fixtures/common.py b/tests/integration/fixtures/common.py index 27b2d6dc3..28a047ea5 100644 --- a/tests/integration/fixtures/common.py +++ b/tests/integration/fixtures/common.py @@ -6,6 +6,7 @@ import inspect import os +import signal import socket import subprocess import tempfile @@ -45,6 +46,8 @@ def start_llama_stack_server(config_name: str) -> subprocess.Popen: stderr=subprocess.PIPE, # keep stderr to see errors text=True, env={**os.environ, "LLAMA_STACK_LOG_FILE": "server.log"}, + # Create new process group so we can kill all child processes + preexec_fn=os.setsid, ) return process @@ -267,14 +270,17 @@ def cleanup_server_process(request): print(f"Server process already terminated with return code: {server_process.returncode}") return try: - server_process.terminate() + print(f"Terminating process {server_process.pid} and its group...") + # Kill the entire process group + os.killpg(os.getpgid(server_process.pid), signal.SIGTERM) server_process.wait(timeout=10) - print("Server process terminated gracefully") + print("Server process and children terminated gracefully") except subprocess.TimeoutExpired: print("Server process did not terminate gracefully, killing it") - server_process.kill() + # Force kill the entire process group + os.killpg(os.getpgid(server_process.pid), signal.SIGKILL) server_process.wait() - print("Server process killed") + print("Server process and children killed") except Exception as e: print(f"Error during server cleanup: {e}") else: From 01c222e12f8b5e6c1cf8c2661bfe69e5680415c9 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?S=C3=A9bastien=20Han?= Date: Thu, 10 Jul 2025 15:16:08 +0200 Subject: [PATCH 08/34] ci: run all APIs integration tests (#2646) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit # What does this PR do? We are now automatically building the list of integration test to run. In that process, eval and files and being tested now. This is pending https://github.com/meta-llama/llama-stack/pull/2628 Signed-off-by: Sébastien Han --- .github/actions/setup-ollama/action.yml | 2 ++ .github/workflows/integration-tests.yml | 39 +++++++++++++++---------- tests/integration/fixtures/common.py | 1 + 3 files changed, 26 insertions(+), 16 deletions(-) diff --git a/.github/actions/setup-ollama/action.yml b/.github/actions/setup-ollama/action.yml index da24839c2..37a369a9a 100644 --- a/.github/actions/setup-ollama/action.yml +++ b/.github/actions/setup-ollama/action.yml @@ -8,4 +8,6 @@ runs: run: | docker run -d --name ollama -p 11434:11434 docker.io/leseb/ollama-with-models # TODO: rebuild an ollama image with llama-guard3:1b + echo "Verifying Ollama status..." + timeout 30 bash -c 'while ! curl -s -L http://127.0.0.1:11434; do sleep 1 && echo "."; done' docker exec ollama ollama pull llama-guard3:1b diff --git a/.github/workflows/integration-tests.yml b/.github/workflows/integration-tests.yml index b102191f2..c46100c38 100644 --- a/.github/workflows/integration-tests.yml +++ b/.github/workflows/integration-tests.yml @@ -18,16 +18,33 @@ concurrency: cancel-in-progress: true jobs: - test-matrix: + discover-tests: runs-on: ubuntu-latest + outputs: + test-type: ${{ steps.generate-matrix.outputs.test-type }} + steps: + - name: Checkout repository + uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2 + + - name: Generate test matrix + id: generate-matrix + run: | + # Get test directories dynamically, excluding non-test directories + TEST_TYPES=$(find tests/integration -maxdepth 1 -mindepth 1 -type d -printf "%f\n" | + grep -Ev "^(__pycache__|fixtures|test_cases)$" | + sort | jq -R -s -c 'split("\n")[:-1]') + echo "test-type=$TEST_TYPES" >> $GITHUB_OUTPUT + + test-matrix: + needs: discover-tests + runs-on: ubuntu-latest + strategy: + fail-fast: false matrix: - # Listing tests manually since some of them currently fail - # TODO: generate matrix list from tests/integration when fixed - test-type: [agents, inference, datasets, inspect, safety, scoring, post_training, providers, tool_runtime, vector_io] + test-type: ${{ fromJson(needs.discover-tests.outputs.test-type) }} client-type: [library, server] python-version: ["3.12", "3.13"] - fail-fast: false # we want to run all tests regardless of failure steps: - name: Checkout repository @@ -51,23 +68,13 @@ jobs: free -h df -h - - name: Verify Ollama status is OK - if: matrix.client-type == 'http' - run: | - echo "Verifying Ollama status..." - ollama_status=$(curl -s -L http://127.0.0.1:8321/v1/providers/ollama|jq --raw-output .health.status) - echo "Ollama status: $ollama_status" - if [ "$ollama_status" != "OK" ]; then - echo "Ollama health check failed" - exit 1 - fi - - name: Run Integration Tests env: OLLAMA_INFERENCE_MODEL: "llama3.2:3b-instruct-fp16" # for server tests ENABLE_OLLAMA: "ollama" # for server tests OLLAMA_URL: "http://0.0.0.0:11434" SAFETY_MODEL: "llama-guard3:1b" + LLAMA_STACK_CLIENT_TIMEOUT: "300" # Increased timeout for eval operations # Use 'shell' to get pipefail behavior # https://docs.github.com/en/actions/reference/workflow-syntax-for-github-actions#exit-codes-and-error-action-preference # TODO: write a precommit hook to detect if a test contains a pipe but does not use 'shell: bash' diff --git a/tests/integration/fixtures/common.py b/tests/integration/fixtures/common.py index 28a047ea5..749793b64 100644 --- a/tests/integration/fixtures/common.py +++ b/tests/integration/fixtures/common.py @@ -218,6 +218,7 @@ def llama_stack_client(request, provider_data): return LlamaStackClient( base_url=base_url, provider_data=provider_data, + timeout=int(os.environ.get("LLAMA_STACK_CLIENT_TIMEOUT", "30")), ) # check if this looks like a URL using proper URL parsing From 81ebaf6e9a1744c36941baba5295337a8a7eb2af Mon Sep 17 00:00:00 2001 From: Charlie Doern Date: Thu, 10 Jul 2025 10:19:12 -0400 Subject: [PATCH 09/34] fix: properly represent paths in server logs (#2698) # What does this PR do? currently when logging the run yaml, if there are path objects in the object they are represented as: ``` external_providers_dir: !!python/object/apply:pathlib.PosixPath - '~' - .llama - providers.d ``` now, with a config.model_dump(mode="json"), it works properly ``` external_providers_dir: ~/.llama/providers.d ``` Signed-off-by: Charlie Doern --- llama_stack/distribution/server/server.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/llama_stack/distribution/server/server.py b/llama_stack/distribution/server/server.py index a7e860a36..f2e29a6f9 100644 --- a/llama_stack/distribution/server/server.py +++ b/llama_stack/distribution/server/server.py @@ -445,7 +445,7 @@ def main(args: argparse.Namespace | None = None): logger.info(log_line) logger.info("Run configuration:") - safe_config = redact_sensitive_fields(config.model_dump()) + safe_config = redact_sensitive_fields(config.model_dump(mode="json")) logger.info(yaml.dump(safe_config, indent=2)) app = FastAPI( From bbe0199bb70d56c3ec86d7066b3db0712afdd3f7 Mon Sep 17 00:00:00 2001 From: Nathan Weinberg <31703736+nathan-weinberg@users.noreply.github.com> Date: Thu, 10 Jul 2025 10:47:59 -0400 Subject: [PATCH 10/34] chore: update pre-commit hook versions (#2708) While investigating the `uv.lock` changes made in https://github.com/meta-llama/llama-stack/pull/2695 I noticed several of the pre-commit hook versions were out of date This PR updates them and fixes some new `ruff` errors --------- Signed-off-by: Nathan Weinberg --- .pre-commit-config.yaml | 10 +++++----- llama_stack/distribution/utils/context.py | 5 +---- .../providers/utils/telemetry/trace_protocol.py | 6 ++---- 3 files changed, 8 insertions(+), 13 deletions(-) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index ebbadefa6..f3a5a718b 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -29,7 +29,7 @@ repos: - id: check-toml - repo: https://github.com/Lucas-C/pre-commit-hooks - rev: v1.5.4 + rev: v1.5.5 hooks: - id: insert-license files: \.py$|\.sh$ @@ -38,7 +38,7 @@ repos: - docs/license_header.txt - repo: https://github.com/astral-sh/ruff-pre-commit - rev: v0.9.4 + rev: v0.12.2 hooks: - id: ruff args: [ --fix ] @@ -46,14 +46,14 @@ repos: - id: ruff-format - repo: https://github.com/adamchainz/blacken-docs - rev: 1.19.0 + rev: 1.19.1 hooks: - id: blacken-docs additional_dependencies: - black==24.3.0 - repo: https://github.com/astral-sh/uv-pre-commit - rev: 0.7.8 + rev: 0.7.20 hooks: - id: uv-lock - id: uv-export @@ -66,7 +66,7 @@ repos: ] - repo: https://github.com/pre-commit/mirrors-mypy - rev: v1.15.0 + rev: v1.16.1 hooks: - id: mypy additional_dependencies: diff --git a/llama_stack/distribution/utils/context.py b/llama_stack/distribution/utils/context.py index 3fcd3315f..24b249890 100644 --- a/llama_stack/distribution/utils/context.py +++ b/llama_stack/distribution/utils/context.py @@ -6,12 +6,9 @@ from collections.abc import AsyncGenerator from contextvars import ContextVar -from typing import TypeVar - -T = TypeVar("T") -def preserve_contexts_async_generator( +def preserve_contexts_async_generator[T]( gen: AsyncGenerator[T, None], context_vars: list[ContextVar] ) -> AsyncGenerator[T, None]: """ diff --git a/llama_stack/providers/utils/telemetry/trace_protocol.py b/llama_stack/providers/utils/telemetry/trace_protocol.py index eb6d8b331..916f7622a 100644 --- a/llama_stack/providers/utils/telemetry/trace_protocol.py +++ b/llama_stack/providers/utils/telemetry/trace_protocol.py @@ -9,14 +9,12 @@ import inspect import json from collections.abc import AsyncGenerator, Callable from functools import wraps -from typing import Any, TypeVar +from typing import Any from pydantic import BaseModel from llama_stack.models.llama.datatypes import Primitive -T = TypeVar("T") - def serialize_value(value: Any) -> Primitive: return str(_prepare_for_json(value)) @@ -44,7 +42,7 @@ def _prepare_for_json(value: Any) -> str: return str(value) -def trace_protocol(cls: type[T]) -> type[T]: +def trace_protocol[T](cls: type[T]) -> type[T]: """ A class decorator that automatically traces all methods in a protocol/base class and its inheriting classes. From 83c6b200674b94d3e32a033398a79ba06380805e Mon Sep 17 00:00:00 2001 From: Mustafa Elbehery Date: Thu, 10 Jul 2025 16:53:38 +0200 Subject: [PATCH 11/34] chore(api): add `mypy` coverage to `cli/stack` (#2650) # What does this PR do? This PR adds static type coverage to `llama-stack` Part of https://github.com/meta-llama/llama-stack/issues/2647 ## Test Plan Signed-off-by: Mustafa Elbehery --- llama_stack/cli/stack/_build.py | 24 +++++++++++++++++++----- pyproject.toml | 1 - 2 files changed, 19 insertions(+), 6 deletions(-) diff --git a/llama_stack/cli/stack/_build.py b/llama_stack/cli/stack/_build.py index 5d88b1d82..b573b2edc 100644 --- a/llama_stack/cli/stack/_build.py +++ b/llama_stack/cli/stack/_build.py @@ -93,7 +93,7 @@ def run_stack_build_command(args: argparse.Namespace) -> None: ) sys.exit(1) elif args.providers: - providers = dict() + providers_list: dict[str, str | list[str]] = dict() for api_provider in args.providers.split(","): if "=" not in api_provider: cprint( @@ -112,7 +112,15 @@ def run_stack_build_command(args: argparse.Namespace) -> None: ) sys.exit(1) if provider in providers_for_api: - providers.setdefault(api, []).append(provider) + if api not in providers_list: + providers_list[api] = [] + # Use type guarding to ensure we have a list + provider_value = providers_list[api] + if isinstance(provider_value, list): + provider_value.append(provider) + else: + # Convert string to list and append + providers_list[api] = [provider_value, provider] else: cprint( f"{provider} is not a valid provider for the {api} API.", @@ -121,7 +129,7 @@ def run_stack_build_command(args: argparse.Namespace) -> None: ) sys.exit(1) distribution_spec = DistributionSpec( - providers=providers, + providers=providers_list, description=",".join(args.providers), ) if not args.image_type: @@ -182,7 +190,7 @@ def run_stack_build_command(args: argparse.Namespace) -> None: cprint("Tip: use to see options for the providers.\n", color="green", file=sys.stderr) - providers = dict() + providers: dict[str, str | list[str]] = dict() for api, providers_for_api in get_provider_registry().items(): available_providers = [x for x in providers_for_api.keys() if x not in ("remote", "remote::sample")] if not available_providers: @@ -371,10 +379,16 @@ def _run_stack_build_command_from_build_config( if not image_name: raise ValueError("Please specify an image name when building a venv image") + # At this point, image_name should be guaranteed to be a string + if image_name is None: + raise ValueError("image_name should not be None after validation") + if template_name: build_dir = DISTRIBS_BASE_DIR / template_name build_file_path = build_dir / f"{template_name}-build.yaml" else: + if image_name is None: + raise ValueError("image_name cannot be None") build_dir = DISTRIBS_BASE_DIR / image_name build_file_path = build_dir / f"{image_name}-build.yaml" @@ -395,7 +409,7 @@ def _run_stack_build_command_from_build_config( build_file_path, image_name, template_or_config=template_name or config_path or str(build_file_path), - run_config=run_config_file, + run_config=run_config_file.as_posix() if run_config_file else None, ) if return_code != 0: raise RuntimeError(f"Failed to build image {image_name}") diff --git a/pyproject.toml b/pyproject.toml index 30598e5e3..d84a823a3 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -226,7 +226,6 @@ follow_imports = "silent" exclude = [ # As we fix more and more of these, we should remove them from the list "^llama_stack/cli/download\\.py$", - "^llama_stack/cli/stack/_build\\.py$", "^llama_stack/distribution/build\\.py$", "^llama_stack/distribution/client\\.py$", "^llama_stack/distribution/request_headers\\.py$", From b18f4d1ccfeb3321285a2cefb03baf515e978d7f Mon Sep 17 00:00:00 2001 From: Nathan Weinberg <31703736+nathan-weinberg@users.noreply.github.com> Date: Thu, 10 Jul 2025 11:24:10 -0400 Subject: [PATCH 12/34] ci: add config for pre-commit.ci (#2712) # What does this PR do? the project already had some config setup for https://pre-commit.ci/ this commit adds additional explicit fields Closes #2711 **IMPORTANT:** A project maintainer must add `pre-commit.ci` to this repo for this to work - this can be done via https://pre-commit.ci/ Signed-off-by: Nathan Weinberg --- .pre-commit-config.yaml | 5 +++++ 1 file changed, 5 insertions(+) diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index f3a5a718b..3c744c6bc 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -133,3 +133,8 @@ repos: ci: autofix_commit_msg: 🎨 [pre-commit.ci] Auto format from pre-commit.com hooks autoupdate_commit_msg: ⬆ [pre-commit.ci] pre-commit autoupdate + autofix_prs: true + autoupdate_branch: '' + autoupdate_schedule: weekly + skip: [] + submodules: false From 6a6b66ae4f965de4cd3cd71a4320e868fa777b95 Mon Sep 17 00:00:00 2001 From: Francisco Arceo Date: Thu, 10 Jul 2025 14:22:13 -0400 Subject: [PATCH 13/34] chore: Adding unit tests for OpenAI vector stores and migrating SQLite-vec registry to kvstore (#2665) # What does this PR do? This PR refactors and the VectorIO backend logic for `sqlite-vec` and adds unit tests and fixtures to make it easy to test both `sqlite-vec` and `milvus`. Key changes: - `sqlite-vec` migrated to `kvstore` registry - added in-memory cache for sqlite-vec to be consistent with `milvus` - default fixtures moved to `conftest.py` - removed redundant tests from sqlite`-vec` - made `test_vector_io_openai_vector_stores.py` more easily extensible ## Test Plan Unit tests added testing inline providers. --------- Signed-off-by: Francisco Javier Arceo --- .../providers/vector_io/inline_milvus.md | 2 +- .../providers/vector_io/inline_sqlite-vec.md | 6 +- .../providers/vector_io/inline_sqlite_vec.md | 6 +- .../inline/vector_io/milvus/config.py | 2 +- .../inline/vector_io/sqlite_vec/config.py | 14 +- .../inline/vector_io/sqlite_vec/sqlite_vec.py | 313 +++++++----------- .../remote/vector_io/milvus/milvus.py | 8 + llama_stack/templates/open-benchmark/run.yaml | 3 + llama_stack/templates/starter/run.yaml | 3 + tests/unit/providers/vector_io/conftest.py | 157 +++++++++ .../providers/vector_io/test_sqlite_vec.py | 35 +- .../test_vector_io_openai_vector_stores.py | 297 ++++++----------- 12 files changed, 422 insertions(+), 424 deletions(-) diff --git a/docs/source/providers/vector_io/inline_milvus.md b/docs/source/providers/vector_io/inline_milvus.md index be7340c9d..3b3aad3fc 100644 --- a/docs/source/providers/vector_io/inline_milvus.md +++ b/docs/source/providers/vector_io/inline_milvus.md @@ -11,7 +11,7 @@ Please refer to the remote provider documentation. | Field | Type | Required | Default | Description | |-------|------|----------|---------|-------------| | `db_path` | `` | No | PydanticUndefined | | -| `kvstore` | `utils.kvstore.config.RedisKVStoreConfig \| utils.kvstore.config.SqliteKVStoreConfig \| utils.kvstore.config.PostgresKVStoreConfig \| utils.kvstore.config.MongoDBKVStoreConfig` | No | sqlite | | +| `kvstore` | `utils.kvstore.config.RedisKVStoreConfig \| utils.kvstore.config.SqliteKVStoreConfig \| utils.kvstore.config.PostgresKVStoreConfig \| utils.kvstore.config.MongoDBKVStoreConfig` | No | sqlite | Config for KV store backend (SQLite only for now) | | `consistency_level` | `` | No | Strong | The consistency level of the Milvus server | ## Sample Configuration diff --git a/docs/source/providers/vector_io/inline_sqlite-vec.md b/docs/source/providers/vector_io/inline_sqlite-vec.md index fd3ec1dc4..ae7c45b21 100644 --- a/docs/source/providers/vector_io/inline_sqlite-vec.md +++ b/docs/source/providers/vector_io/inline_sqlite-vec.md @@ -205,12 +205,16 @@ See [sqlite-vec's GitHub repo](https://github.com/asg017/sqlite-vec/tree/main) f | Field | Type | Required | Default | Description | |-------|------|----------|---------|-------------| -| `db_path` | `` | No | PydanticUndefined | | +| `db_path` | `` | No | PydanticUndefined | Path to the SQLite database file | +| `kvstore` | `utils.kvstore.config.RedisKVStoreConfig \| utils.kvstore.config.SqliteKVStoreConfig \| utils.kvstore.config.PostgresKVStoreConfig \| utils.kvstore.config.MongoDBKVStoreConfig` | No | sqlite | Config for KV store backend (SQLite only for now) | ## Sample Configuration ```yaml db_path: ${env.SQLITE_STORE_DIR:=~/.llama/dummy}/sqlite_vec.db +kvstore: + type: sqlite + db_path: ${env.SQLITE_STORE_DIR:=~/.llama/dummy}/sqlite_vec_registry.db ``` diff --git a/docs/source/providers/vector_io/inline_sqlite_vec.md b/docs/source/providers/vector_io/inline_sqlite_vec.md index e4b69c9ab..7e14bb8bd 100644 --- a/docs/source/providers/vector_io/inline_sqlite_vec.md +++ b/docs/source/providers/vector_io/inline_sqlite_vec.md @@ -10,12 +10,16 @@ Please refer to the sqlite-vec provider documentation. | Field | Type | Required | Default | Description | |-------|------|----------|---------|-------------| -| `db_path` | `` | No | PydanticUndefined | | +| `db_path` | `` | No | PydanticUndefined | Path to the SQLite database file | +| `kvstore` | `utils.kvstore.config.RedisKVStoreConfig \| utils.kvstore.config.SqliteKVStoreConfig \| utils.kvstore.config.PostgresKVStoreConfig \| utils.kvstore.config.MongoDBKVStoreConfig` | No | sqlite | Config for KV store backend (SQLite only for now) | ## Sample Configuration ```yaml db_path: ${env.SQLITE_STORE_DIR:=~/.llama/dummy}/sqlite_vec.db +kvstore: + type: sqlite + db_path: ${env.SQLITE_STORE_DIR:=~/.llama/dummy}/sqlite_vec_registry.db ``` diff --git a/llama_stack/providers/inline/vector_io/milvus/config.py b/llama_stack/providers/inline/vector_io/milvus/config.py index a05ca1670..8cbd056be 100644 --- a/llama_stack/providers/inline/vector_io/milvus/config.py +++ b/llama_stack/providers/inline/vector_io/milvus/config.py @@ -18,7 +18,7 @@ from llama_stack.schema_utils import json_schema_type @json_schema_type class MilvusVectorIOConfig(BaseModel): db_path: str - kvstore: KVStoreConfig + kvstore: KVStoreConfig = Field(description="Config for KV store backend (SQLite only for now)") consistency_level: str = Field(description="The consistency level of the Milvus server", default="Strong") @classmethod diff --git a/llama_stack/providers/inline/vector_io/sqlite_vec/config.py b/llama_stack/providers/inline/vector_io/sqlite_vec/config.py index 4c57f4aba..525ed4b1f 100644 --- a/llama_stack/providers/inline/vector_io/sqlite_vec/config.py +++ b/llama_stack/providers/inline/vector_io/sqlite_vec/config.py @@ -6,14 +6,24 @@ from typing import Any -from pydantic import BaseModel +from pydantic import BaseModel, Field + +from llama_stack.providers.utils.kvstore.config import ( + KVStoreConfig, + SqliteKVStoreConfig, +) class SQLiteVectorIOConfig(BaseModel): - db_path: str + db_path: str = Field(description="Path to the SQLite database file") + kvstore: KVStoreConfig = Field(description="Config for KV store backend (SQLite only for now)") @classmethod def sample_run_config(cls, __distro_dir__: str) -> dict[str, Any]: return { "db_path": "${env.SQLITE_STORE_DIR:=" + __distro_dir__ + "}/" + "sqlite_vec.db", + "kvstore": SqliteKVStoreConfig.sample_run_config( + __distro_dir__=__distro_dir__, + db_name="sqlite_vec_registry.db", + ), } diff --git a/llama_stack/providers/inline/vector_io/sqlite_vec/sqlite_vec.py b/llama_stack/providers/inline/vector_io/sqlite_vec/sqlite_vec.py index 7e977635a..6acd85c56 100644 --- a/llama_stack/providers/inline/vector_io/sqlite_vec/sqlite_vec.py +++ b/llama_stack/providers/inline/vector_io/sqlite_vec/sqlite_vec.py @@ -24,6 +24,8 @@ from llama_stack.apis.vector_io import ( VectorIO, ) from llama_stack.providers.datatypes import VectorDBsProtocolPrivate +from llama_stack.providers.utils.kvstore import kvstore_impl +from llama_stack.providers.utils.kvstore.api import KVStore from llama_stack.providers.utils.memory.openai_vector_store_mixin import OpenAIVectorStoreMixin from llama_stack.providers.utils.memory.vector_store import ( RERANKER_TYPE_RRF, @@ -40,6 +42,13 @@ KEYWORD_SEARCH = "keyword" HYBRID_SEARCH = "hybrid" SEARCH_MODES = {VECTOR_SEARCH, KEYWORD_SEARCH, HYBRID_SEARCH} +VERSION = "v3" +VECTOR_DBS_PREFIX = f"vector_dbs:sqlite_vec:{VERSION}::" +VECTOR_INDEX_PREFIX = f"vector_index:sqlite_vec:{VERSION}::" +OPENAI_VECTOR_STORES_PREFIX = f"openai_vector_stores:sqlite_vec:{VERSION}::" +OPENAI_VECTOR_STORES_FILES_PREFIX = f"openai_vector_stores_files:sqlite_vec:{VERSION}::" +OPENAI_VECTOR_STORES_FILES_CONTENTS_PREFIX = f"openai_vector_stores_files_contents:sqlite_vec:{VERSION}::" + def serialize_vector(vector: list[float]) -> bytes: """Serialize a list of floats into a compact binary representation.""" @@ -117,13 +126,14 @@ class SQLiteVecIndex(EmbeddingIndex): - An FTS5 table (fts_chunks_{bank_id}) for full-text keyword search. """ - def __init__(self, dimension: int, db_path: str, bank_id: str): + def __init__(self, dimension: int, db_path: str, bank_id: str, kvstore: KVStore | None = None): self.dimension = dimension self.db_path = db_path self.bank_id = bank_id self.metadata_table = f"chunks_{bank_id}".replace("-", "_") self.vector_table = f"vec_chunks_{bank_id}".replace("-", "_") self.fts_table = f"fts_chunks_{bank_id}".replace("-", "_") + self.kvstore = kvstore @classmethod async def create(cls, dimension: int, db_path: str, bank_id: str): @@ -425,27 +435,116 @@ class SQLiteVecVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtoc self.files_api = files_api self.cache: dict[str, VectorDBWithIndex] = {} self.openai_vector_stores: dict[str, dict[str, Any]] = {} + self.kvstore: KVStore | None = None async def initialize(self) -> None: - def _setup_connection(): - # Open a connection to the SQLite database (the file is specified in the config). + self.kvstore = await kvstore_impl(self.config.kvstore) + + start_key = VECTOR_DBS_PREFIX + end_key = f"{VECTOR_DBS_PREFIX}\xff" + stored_vector_dbs = await self.kvstore.values_in_range(start_key, end_key) + for db_json in stored_vector_dbs: + vector_db = VectorDB.model_validate_json(db_json) + index = await SQLiteVecIndex.create( + vector_db.embedding_dimension, + self.config.db_path, + vector_db.identifier, + ) + self.cache[vector_db.identifier] = VectorDBWithIndex(vector_db, index, self.inference_api) + + # load any existing OpenAI vector stores + self.openai_vector_stores = await self._load_openai_vector_stores() + + async def shutdown(self) -> None: + # nothing to do since we don't maintain a persistent connection + pass + + async def list_vector_dbs(self) -> list[VectorDB]: + return [v.vector_db for v in self.cache.values()] + + async def register_vector_db(self, vector_db: VectorDB) -> None: + index = await SQLiteVecIndex.create( + vector_db.embedding_dimension, + self.config.db_path, + vector_db.identifier, + ) + self.cache[vector_db.identifier] = VectorDBWithIndex(vector_db, index, self.inference_api) + + async def _get_and_cache_vector_db_index(self, vector_db_id: str) -> VectorDBWithIndex | None: + if vector_db_id in self.cache: + return self.cache[vector_db_id] + + if self.vector_db_store is None: + raise ValueError(f"Vector DB {vector_db_id} not found") + + vector_db = self.vector_db_store.get_vector_db(vector_db_id) + if not vector_db: + raise ValueError(f"Vector DB {vector_db_id} not found") + + index = VectorDBWithIndex( + vector_db=vector_db, + index=SQLiteVecIndex( + dimension=vector_db.embedding_dimension, + db_path=self.config.db_path, + bank_id=vector_db.identifier, + kvstore=self.kvstore, + ), + inference_api=self.inference_api, + ) + self.cache[vector_db_id] = index + return index + + async def unregister_vector_db(self, vector_db_id: str) -> None: + if vector_db_id not in self.cache: + logger.warning(f"Vector DB {vector_db_id} not found") + return + await self.cache[vector_db_id].index.delete() + del self.cache[vector_db_id] + + # OpenAI Vector Store Mixin abstract method implementations + async def _save_openai_vector_store(self, store_id: str, store_info: dict[str, Any]) -> None: + """Save vector store metadata to SQLite database.""" + assert self.kvstore is not None + key = f"{OPENAI_VECTOR_STORES_PREFIX}{store_id}" + await self.kvstore.set(key=key, value=json.dumps(store_info)) + self.openai_vector_stores[store_id] = store_info + + async def _load_openai_vector_stores(self) -> dict[str, dict[str, Any]]: + """Load all vector store metadata from SQLite database.""" + assert self.kvstore is not None + start_key = OPENAI_VECTOR_STORES_PREFIX + end_key = f"{OPENAI_VECTOR_STORES_PREFIX}\xff" + stored_openai_stores = await self.kvstore.values_in_range(start_key, end_key) + stores = {} + for store_data in stored_openai_stores: + store_info = json.loads(store_data) + stores[store_info["id"]] = store_info + return stores + + async def _update_openai_vector_store(self, store_id: str, store_info: dict[str, Any]) -> None: + """Update vector store metadata in SQLite database.""" + assert self.kvstore is not None + key = f"{OPENAI_VECTOR_STORES_PREFIX}{store_id}" + await self.kvstore.set(key=key, value=json.dumps(store_info)) + self.openai_vector_stores[store_id] = store_info + + async def _delete_openai_vector_store_from_storage(self, store_id: str) -> None: + """Delete vector store metadata from SQLite database.""" + assert self.kvstore is not None + key = f"{OPENAI_VECTOR_STORES_PREFIX}{store_id}" + await self.kvstore.delete(key) + if store_id in self.openai_vector_stores: + del self.openai_vector_stores[store_id] + + async def _save_openai_vector_store_file( + self, store_id: str, file_id: str, file_info: dict[str, Any], file_contents: list[dict[str, Any]] + ) -> None: + """Save vector store file metadata to SQLite database.""" + + def _create_or_store(): connection = _create_sqlite_connection(self.config.db_path) cur = connection.cursor() try: - # Create a table to persist vector DB registrations. - cur.execute(""" - CREATE TABLE IF NOT EXISTS vector_dbs ( - id TEXT PRIMARY KEY, - metadata TEXT - ); - """) - # Create a table to persist OpenAI vector stores. - cur.execute(""" - CREATE TABLE IF NOT EXISTS openai_vector_stores ( - id TEXT PRIMARY KEY, - metadata TEXT - ); - """) # Create a table to persist OpenAI vector store files. cur.execute(""" CREATE TABLE IF NOT EXISTS openai_vector_store_files ( @@ -464,168 +563,6 @@ class SQLiteVecVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtoc ); """) connection.commit() - # Load any existing vector DB registrations. - cur.execute("SELECT metadata FROM vector_dbs") - vector_db_rows = cur.fetchall() - return vector_db_rows - finally: - cur.close() - connection.close() - - vector_db_rows = await asyncio.to_thread(_setup_connection) - - # Load existing vector DBs - for row in vector_db_rows: - vector_db_data = row[0] - vector_db = VectorDB.model_validate_json(vector_db_data) - index = await SQLiteVecIndex.create( - vector_db.embedding_dimension, - self.config.db_path, - vector_db.identifier, - ) - self.cache[vector_db.identifier] = VectorDBWithIndex(vector_db, index, self.inference_api) - - # Load existing OpenAI vector stores using the mixin method - self.openai_vector_stores = await self._load_openai_vector_stores() - - async def shutdown(self) -> None: - # nothing to do since we don't maintain a persistent connection - pass - - async def register_vector_db(self, vector_db: VectorDB) -> None: - def _register_db(): - connection = _create_sqlite_connection(self.config.db_path) - cur = connection.cursor() - try: - cur.execute( - "INSERT OR REPLACE INTO vector_dbs (id, metadata) VALUES (?, ?)", - (vector_db.identifier, vector_db.model_dump_json()), - ) - connection.commit() - finally: - cur.close() - connection.close() - - await asyncio.to_thread(_register_db) - index = await SQLiteVecIndex.create( - vector_db.embedding_dimension, - self.config.db_path, - vector_db.identifier, - ) - self.cache[vector_db.identifier] = VectorDBWithIndex(vector_db, index, self.inference_api) - - async def list_vector_dbs(self) -> list[VectorDB]: - return [v.vector_db for v in self.cache.values()] - - async def unregister_vector_db(self, vector_db_id: str) -> None: - if vector_db_id not in self.cache: - logger.warning(f"Vector DB {vector_db_id} not found") - return - await self.cache[vector_db_id].index.delete() - del self.cache[vector_db_id] - - def _delete_vector_db_from_registry(): - connection = _create_sqlite_connection(self.config.db_path) - cur = connection.cursor() - try: - cur.execute("DELETE FROM vector_dbs WHERE id = ?", (vector_db_id,)) - connection.commit() - finally: - cur.close() - connection.close() - - await asyncio.to_thread(_delete_vector_db_from_registry) - - # OpenAI Vector Store Mixin abstract method implementations - async def _save_openai_vector_store(self, store_id: str, store_info: dict[str, Any]) -> None: - """Save vector store metadata to SQLite database.""" - - def _store(): - connection = _create_sqlite_connection(self.config.db_path) - cur = connection.cursor() - try: - cur.execute( - "INSERT OR REPLACE INTO openai_vector_stores (id, metadata) VALUES (?, ?)", - (store_id, json.dumps(store_info)), - ) - connection.commit() - except Exception as e: - logger.error(f"Error saving openai vector store {store_id}: {e}") - raise - finally: - cur.close() - connection.close() - - try: - await asyncio.to_thread(_store) - except Exception as e: - logger.error(f"Error saving openai vector store {store_id}: {e}") - raise - - async def _load_openai_vector_stores(self) -> dict[str, dict[str, Any]]: - """Load all vector store metadata from SQLite database.""" - - def _load(): - connection = _create_sqlite_connection(self.config.db_path) - cur = connection.cursor() - try: - cur.execute("SELECT metadata FROM openai_vector_stores") - rows = cur.fetchall() - return rows - finally: - cur.close() - connection.close() - - rows = await asyncio.to_thread(_load) - stores = {} - for row in rows: - store_data = row[0] - store_info = json.loads(store_data) - stores[store_info["id"]] = store_info - return stores - - async def _update_openai_vector_store(self, store_id: str, store_info: dict[str, Any]) -> None: - """Update vector store metadata in SQLite database.""" - - def _update(): - connection = _create_sqlite_connection(self.config.db_path) - cur = connection.cursor() - try: - cur.execute( - "UPDATE openai_vector_stores SET metadata = ? WHERE id = ?", - (json.dumps(store_info), store_id), - ) - connection.commit() - finally: - cur.close() - connection.close() - - await asyncio.to_thread(_update) - - async def _delete_openai_vector_store_from_storage(self, store_id: str) -> None: - """Delete vector store metadata from SQLite database.""" - - def _delete(): - connection = _create_sqlite_connection(self.config.db_path) - cur = connection.cursor() - try: - cur.execute("DELETE FROM openai_vector_stores WHERE id = ?", (store_id,)) - connection.commit() - finally: - cur.close() - connection.close() - - await asyncio.to_thread(_delete) - - async def _save_openai_vector_store_file( - self, store_id: str, file_id: str, file_info: dict[str, Any], file_contents: list[dict[str, Any]] - ) -> None: - """Save vector store file metadata to SQLite database.""" - - def _store(): - connection = _create_sqlite_connection(self.config.db_path) - cur = connection.cursor() - try: cur.execute( "INSERT OR REPLACE INTO openai_vector_store_files (store_id, file_id, metadata) VALUES (?, ?, ?)", (store_id, file_id, json.dumps(file_info)), @@ -643,7 +580,7 @@ class SQLiteVecVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtoc connection.close() try: - await asyncio.to_thread(_store) + await asyncio.to_thread(_create_or_store) except Exception as e: logger.error(f"Error saving openai vector store file {store_id} {file_id}: {e}") raise @@ -722,6 +659,10 @@ class SQLiteVecVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtoc cur.execute( "DELETE FROM openai_vector_store_files WHERE store_id = ? AND file_id = ?", (store_id, file_id) ) + cur.execute( + "DELETE FROM openai_vector_store_files_contents WHERE store_id = ? AND file_id = ?", + (store_id, file_id), + ) connection.commit() finally: cur.close() @@ -730,15 +671,17 @@ class SQLiteVecVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtoc await asyncio.to_thread(_delete) async def insert_chunks(self, vector_db_id: str, chunks: list[Chunk], ttl_seconds: int | None = None) -> None: - if vector_db_id not in self.cache: - raise ValueError(f"Vector DB {vector_db_id} not found. Found: {list(self.cache.keys())}") + index = await self._get_and_cache_vector_db_index(vector_db_id) + if not index: + raise ValueError(f"Vector DB {vector_db_id} not found") # The VectorDBWithIndex helper is expected to compute embeddings via the inference_api # and then call our index's add_chunks. - await self.cache[vector_db_id].insert_chunks(chunks) + await index.insert_chunks(chunks) async def query_chunks( self, vector_db_id: str, query: Any, params: dict[str, Any] | None = None ) -> QueryChunksResponse: - if vector_db_id not in self.cache: + index = await self._get_and_cache_vector_db_index(vector_db_id) + if not index: raise ValueError(f"Vector DB {vector_db_id} not found") - return await self.cache[vector_db_id].query_chunks(query, params) + return await index.query_chunks(query, params) diff --git a/llama_stack/providers/remote/vector_io/milvus/milvus.py b/llama_stack/providers/remote/vector_io/milvus/milvus.py index 1f65e580e..a06130fd0 100644 --- a/llama_stack/providers/remote/vector_io/milvus/milvus.py +++ b/llama_stack/providers/remote/vector_io/milvus/milvus.py @@ -61,6 +61,11 @@ class MilvusIndex(EmbeddingIndex): self.consistency_level = consistency_level self.kvstore = kvstore + async def initialize(self): + # MilvusIndex does not require explicit initialization + # TODO: could move collection creation into initialization but it is not really necessary + pass + async def delete(self): if await asyncio.to_thread(self.client.has_collection, self.collection_name): await asyncio.to_thread(self.client.drop_collection, collection_name=self.collection_name) @@ -199,6 +204,9 @@ class MilvusVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtocolP if vector_db_id in self.cache: return self.cache[vector_db_id] + if self.vector_db_store is None: + raise ValueError(f"Vector DB {vector_db_id} not found") + vector_db = await self.vector_db_store.get_vector_db(vector_db_id) if not vector_db: raise ValueError(f"Vector DB {vector_db_id} not found") diff --git a/llama_stack/templates/open-benchmark/run.yaml b/llama_stack/templates/open-benchmark/run.yaml index 76c029864..0b368ebc9 100644 --- a/llama_stack/templates/open-benchmark/run.yaml +++ b/llama_stack/templates/open-benchmark/run.yaml @@ -39,6 +39,9 @@ providers: provider_type: inline::sqlite-vec config: db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/sqlite_vec.db + kvstore: + type: sqlite + db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/sqlite_vec_registry.db - provider_id: ${env.ENABLE_CHROMADB:+chromadb} provider_type: remote::chromadb config: diff --git a/llama_stack/templates/starter/run.yaml b/llama_stack/templates/starter/run.yaml index b3dfe32d5..888a2c3bf 100644 --- a/llama_stack/templates/starter/run.yaml +++ b/llama_stack/templates/starter/run.yaml @@ -144,6 +144,9 @@ providers: provider_type: inline::sqlite-vec config: db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter}/sqlite_vec.db + kvstore: + type: sqlite + db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter}/sqlite_vec_registry.db - provider_id: ${env.ENABLE_MILVUS:=__disabled__} provider_type: inline::milvus config: diff --git a/tests/unit/providers/vector_io/conftest.py b/tests/unit/providers/vector_io/conftest.py index 5eaca8a25..4a9639326 100644 --- a/tests/unit/providers/vector_io/conftest.py +++ b/tests/unit/providers/vector_io/conftest.py @@ -8,10 +8,18 @@ import random import numpy as np import pytest +from pymilvus import MilvusClient, connections +from llama_stack.apis.vector_dbs import VectorDB from llama_stack.apis.vector_io import Chunk, ChunkMetadata +from llama_stack.providers.inline.vector_io.milvus.config import MilvusVectorIOConfig, SqliteKVStoreConfig +from llama_stack.providers.inline.vector_io.sqlite_vec import SQLiteVectorIOConfig +from llama_stack.providers.inline.vector_io.sqlite_vec.sqlite_vec import SQLiteVecIndex, SQLiteVecVectorIOAdapter +from llama_stack.providers.remote.vector_io.milvus.milvus import MilvusIndex, MilvusVectorIOAdapter EMBEDDING_DIMENSION = 384 +COLLECTION_PREFIX = "test_collection" +MILVUS_ALIAS = "test_milvus" @pytest.fixture @@ -50,7 +58,156 @@ def sample_chunks(): return sample +@pytest.fixture(scope="session") +def sample_chunks_with_metadata(): + """Generates chunks that force multiple batches for a single document to expose ID conflicts.""" + n, k = 10, 3 + sample = [ + Chunk( + content=f"Sentence {i} from document {j}", + metadata={"document_id": f"document-{j}"}, + chunk_metadata=ChunkMetadata( + document_id=f"document-{j}", + chunk_id=f"document-{j}-chunk-{i}", + source=f"example source-{j}-{i}", + ), + ) + for j in range(k) + for i in range(n) + ] + return sample + + @pytest.fixture(scope="session") def sample_embeddings(sample_chunks): np.random.seed(42) return np.array([np.random.rand(EMBEDDING_DIMENSION).astype(np.float32) for _ in sample_chunks]) + + +@pytest.fixture(scope="session") +def sample_embeddings_with_metadata(sample_chunks_with_metadata): + np.random.seed(42) + return np.array([np.random.rand(EMBEDDING_DIMENSION).astype(np.float32) for _ in sample_chunks_with_metadata]) + + +@pytest.fixture(params=["milvus", "sqlite_vec"]) +def vector_provider(request): + return request.param + + +@pytest.fixture(scope="session") +def mock_inference_api(embedding_dimension): + class MockInferenceAPI: + async def embed_batch(self, texts: list[str]) -> list[list[float]]: + return [np.random.rand(embedding_dimension).astype(np.float32).tolist() for _ in texts] + + return MockInferenceAPI() + + +@pytest.fixture +async def unique_kvstore_config(tmp_path_factory): + # Generate a unique filename for this test + unique_id = f"test_kv_{np.random.randint(1e6)}" + temp_dir = tmp_path_factory.getbasetemp() + db_path = str(temp_dir / f"{unique_id}.db") + + return SqliteKVStoreConfig(db_path=db_path) + + +@pytest.fixture(scope="session") +def sqlite_vec_db_path(tmp_path_factory): + db_path = str(tmp_path_factory.getbasetemp() / "test.db") + return db_path + + +@pytest.fixture +async def sqlite_vec_vec_index(embedding_dimension, tmp_path_factory): + temp_dir = tmp_path_factory.getbasetemp() + db_path = str(temp_dir / f"test_sqlite_vec_{np.random.randint(1e6)}.db") + bank_id = f"sqlite_vec_bank_{np.random.randint(1e6)}" + index = SQLiteVecIndex(embedding_dimension, db_path, bank_id) + await index.initialize() + index.db_path = db_path + yield index + index.delete() + + +@pytest.fixture +async def sqlite_vec_adapter(sqlite_vec_db_path, mock_inference_api, embedding_dimension): + config = SQLiteVectorIOConfig( + db_path=sqlite_vec_db_path, + kvstore=SqliteKVStoreConfig(), + ) + adapter = SQLiteVecVectorIOAdapter( + config=config, + inference_api=mock_inference_api, + files_api=None, + ) + collection_id = f"sqlite_test_collection_{np.random.randint(1e6)}" + await adapter.initialize() + await adapter.register_vector_db( + VectorDB( + identifier=collection_id, + provider_id="test_provider", + embedding_model="test_model", + embedding_dimension=embedding_dimension, + ) + ) + adapter.test_collection_id = collection_id + yield adapter + await adapter.shutdown() + + +@pytest.fixture(scope="session") +def milvus_vec_db_path(tmp_path_factory): + db_path = str(tmp_path_factory.getbasetemp() / "test_milvus.db") + return db_path + + +@pytest.fixture +async def milvus_vec_index(milvus_vec_db_path, embedding_dimension): + client = MilvusClient(milvus_vec_db_path) + name = f"{COLLECTION_PREFIX}_{np.random.randint(1e6)}" + connections.connect(alias=MILVUS_ALIAS, uri=milvus_vec_db_path) + index = MilvusIndex(client, name, consistency_level="Strong") + index.db_path = milvus_vec_db_path + yield index + + +@pytest.fixture +async def milvus_vec_adapter(milvus_vec_db_path, mock_inference_api): + config = MilvusVectorIOConfig( + db_path=milvus_vec_db_path, + kvstore=SqliteKVStoreConfig(), + ) + adapter = MilvusVectorIOAdapter( + config=config, + inference_api=mock_inference_api, + files_api=None, + ) + await adapter.initialize() + await adapter.register_vector_db( + VectorDB( + identifier=adapter.metadata_collection_name, + provider_id="test_provider", + embedding_model="test_model", + embedding_dimension=128, + ) + ) + yield adapter + await adapter.shutdown() + + +@pytest.fixture +def vector_io_adapter(vector_provider, request): + """Returns the appropriate vector IO adapter based on the provider parameter.""" + if vector_provider == "milvus": + return request.getfixturevalue("milvus_vec_adapter") + else: + return request.getfixturevalue("sqlite_vec_adapter") + + +@pytest.fixture +def vector_index(vector_provider, request): + """Returns appropriate vector index based on provider parameter""" + return request.getfixturevalue(f"{vector_provider}_vec_index") diff --git a/tests/unit/providers/vector_io/test_sqlite_vec.py b/tests/unit/providers/vector_io/test_sqlite_vec.py index 5d9d92cf3..8579c31bb 100644 --- a/tests/unit/providers/vector_io/test_sqlite_vec.py +++ b/tests/unit/providers/vector_io/test_sqlite_vec.py @@ -34,7 +34,7 @@ def loop(): return asyncio.new_event_loop() -@pytest_asyncio.fixture(scope="session", autouse=True) +@pytest_asyncio.fixture async def sqlite_vec_index(embedding_dimension, tmp_path_factory): temp_dir = tmp_path_factory.getbasetemp() db_path = str(temp_dir / "test_sqlite.db") @@ -44,38 +44,15 @@ async def sqlite_vec_index(embedding_dimension, tmp_path_factory): @pytest.mark.asyncio -async def test_add_chunks(sqlite_vec_index, sample_chunks, sample_embeddings): - await sqlite_vec_index.add_chunks(sample_chunks, sample_embeddings, batch_size=2) - connection = _create_sqlite_connection(sqlite_vec_index.db_path) - cur = connection.cursor() - cur.execute(f"SELECT COUNT(*) FROM {sqlite_vec_index.metadata_table}") - count = cur.fetchone()[0] - assert count == len(sample_chunks) - cur.close() - connection.close() - - -@pytest.mark.asyncio -async def test_query_chunks_vector(sqlite_vec_index, sample_chunks, sample_embeddings, embedding_dimension): - await sqlite_vec_index.add_chunks(sample_chunks, sample_embeddings) - query_embedding = np.random.rand(embedding_dimension).astype(np.float32) - response = await sqlite_vec_index.query_vector(query_embedding, k=2, score_threshold=0.0) - assert isinstance(response, QueryChunksResponse) - assert len(response.chunks) == 2 - - -@pytest.mark.xfail(reason="Chunk Metadata not yet supported for SQLite-vec", strict=True) -async def test_query_chunk_metadata(sqlite_vec_index, sample_chunks, sample_embeddings): - await sqlite_vec_index.add_chunks(sample_chunks, sample_embeddings) - query_embedding = sample_embeddings[0] - response = await sqlite_vec_index.query_vector(query_embedding, k=2, score_threshold=0.0) - assert response.chunks[-1].chunk_metadata == sample_chunks[-1].chunk_metadata +async def test_query_chunk_metadata(sqlite_vec_index, sample_chunks_with_metadata, sample_embeddings_with_metadata): + await sqlite_vec_index.add_chunks(sample_chunks_with_metadata, sample_embeddings_with_metadata) + response = await sqlite_vec_index.query_vector(sample_embeddings_with_metadata[-1], k=2, score_threshold=0.0) + assert response.chunks[0].chunk_metadata == sample_chunks_with_metadata[-1].chunk_metadata @pytest.mark.asyncio async def test_query_chunks_full_text_search(sqlite_vec_index, sample_chunks, sample_embeddings): await sqlite_vec_index.add_chunks(sample_chunks, sample_embeddings) - query_string = "Sentence 5" response = await sqlite_vec_index.query_keyword(k=3, score_threshold=0.0, query_string=query_string) @@ -148,7 +125,7 @@ async def test_chunk_id_conflict(sqlite_vec_index, sample_chunks, embedding_dime assert len(chunk_ids) == len(set(chunk_ids)), "Duplicate chunk IDs detected across batches!" -@pytest_asyncio.fixture(scope="session") +@pytest.fixture(scope="session") async def sqlite_vec_adapter(sqlite_connection): config = type("Config", (object,), {"db_path": ":memory:"}) # Mock config with in-memory database adapter = SQLiteVecVectorIOAdapter(config=config, inference_api=None) diff --git a/tests/unit/providers/vector_io/test_vector_io_openai_vector_stores.py b/tests/unit/providers/vector_io/test_vector_io_openai_vector_stores.py index 0a109e833..5f7926ce6 100644 --- a/tests/unit/providers/vector_io/test_vector_io_openai_vector_stores.py +++ b/tests/unit/providers/vector_io/test_vector_io_openai_vector_stores.py @@ -4,253 +4,142 @@ # This source code is licensed under the terms described in the LICENSE file in # the root directory of this source tree. -import asyncio +import json import time from unittest.mock import AsyncMock import numpy as np import pytest -import pytest_asyncio -from pymilvus import Collection, MilvusClient, connections from llama_stack.apis.vector_dbs import VectorDB from llama_stack.apis.vector_io import Chunk, QueryChunksResponse -from llama_stack.providers.inline.vector_io.milvus.config import MilvusVectorIOConfig, SqliteKVStoreConfig -from llama_stack.providers.remote.vector_io.milvus.milvus import VECTOR_DBS_PREFIX, MilvusIndex, MilvusVectorIOAdapter -from llama_stack.providers.utils.kvstore import kvstore_impl +from llama_stack.providers.remote.vector_io.milvus.milvus import VECTOR_DBS_PREFIX -# TODO: Refactor these to be for inline vector-io providers -MILVUS_ALIAS = "test_milvus" -COLLECTION_PREFIX = "test_collection" - - -@pytest.fixture(scope="session") -def loop(): - return asyncio.new_event_loop() - - -@pytest.fixture(scope="session") -def mock_inference_api(embedding_dimension): - class MockInferenceAPI: - async def embed_batch(self, texts: list[str]) -> list[list[float]]: - return [np.random.rand(embedding_dimension).astype(np.float32).tolist() for _ in texts] - - return MockInferenceAPI() - - -@pytest_asyncio.fixture -async def unique_kvstore_config(tmp_path_factory): - # Generate a unique filename for this test - unique_id = f"test_kv_{np.random.randint(1e6)}" - temp_dir = tmp_path_factory.getbasetemp() - db_path = str(temp_dir / f"{unique_id}.db") - - return SqliteKVStoreConfig(db_path=db_path) - - -@pytest_asyncio.fixture(scope="session", autouse=True) -async def milvus_vec_index(embedding_dimension, tmp_path_factory): - temp_dir = tmp_path_factory.getbasetemp() - db_path = str(temp_dir / "test_milvus.db") - client = MilvusClient(db_path) - name = f"{COLLECTION_PREFIX}_{np.random.randint(1e6)}" - connections.connect(alias=MILVUS_ALIAS, uri=db_path) - index = MilvusIndex(client, name, consistency_level="Strong") - index.db_path = db_path - yield index - - -@pytest_asyncio.fixture(scope="session") -async def milvus_vec_adapter(milvus_vec_index, mock_inference_api): - config = MilvusVectorIOConfig( - db_path=milvus_vec_index.db_path, - kvstore=SqliteKVStoreConfig(), - ) - adapter = MilvusVectorIOAdapter( - config=config, - inference_api=mock_inference_api, - files_api=None, - ) - await adapter.initialize() - await adapter.register_vector_db( - VectorDB( - identifier=adapter.metadata_collection_name, - provider_id="test_provider", - embedding_model="test_model", - embedding_dimension=128, - ) - ) - yield adapter - await adapter.shutdown() +# This test is a unit test for the inline VectoerIO providers. This should only contain +# tests which are specific to this class. More general (API-level) tests should be placed in +# tests/integration/vector_io/ +# +# How to run this test: +# +# pytest tests/unit/providers/vector_io/test_vector_io_openai_vector_stores.py \ +# -v -s --tb=short --disable-warnings --asyncio-mode=auto @pytest.mark.asyncio -async def test_cache_contains_initial_collection(milvus_vec_adapter): - coll_name = milvus_vec_adapter.metadata_collection_name - assert coll_name in milvus_vec_adapter.cache +async def test_initialize_index(vector_index): + await vector_index.initialize() @pytest.mark.asyncio -async def test_add_chunks(milvus_vec_index, sample_chunks, sample_embeddings): - await milvus_vec_index.add_chunks(sample_chunks, sample_embeddings) - resp = await milvus_vec_index.query_vector(sample_embeddings[0], k=1, score_threshold=-1) +async def test_add_chunks_query_vector(vector_index, sample_chunks, sample_embeddings): + vector_index.delete() + vector_index.initialize() + await vector_index.add_chunks(sample_chunks, sample_embeddings) + resp = await vector_index.query_vector(sample_embeddings[0], k=1, score_threshold=-1) assert resp.chunks[0].content == sample_chunks[0].content + vector_index.delete() @pytest.mark.asyncio -async def test_query_chunks_vector(milvus_vec_index, sample_chunks, sample_embeddings, embedding_dimension): - await milvus_vec_index.add_chunks(sample_chunks, sample_embeddings) - query_emb = np.random.rand(embedding_dimension).astype(np.float32) - resp = await milvus_vec_index.query_vector(query_emb, k=2, score_threshold=0.0) - assert isinstance(resp, QueryChunksResponse) - assert len(resp.chunks) == 2 - - -@pytest.mark.asyncio -async def test_chunk_id_conflict(milvus_vec_index, sample_chunks, embedding_dimension): +async def test_chunk_id_conflict(vector_index, sample_chunks, embedding_dimension): embeddings = np.random.rand(len(sample_chunks), embedding_dimension).astype(np.float32) - await milvus_vec_index.add_chunks(sample_chunks, embeddings) - coll = Collection(milvus_vec_index.collection_name, using=MILVUS_ALIAS) - ids = coll.query(expr="id >= 0", output_fields=["id"], timeout=30) - flat_ids = [i["id"] for i in ids] - assert len(flat_ids) == len(set(flat_ids)) + await vector_index.add_chunks(sample_chunks, embeddings) + resp = await vector_index.query_vector( + np.random.rand(embedding_dimension).astype(np.float32), + k=len(sample_chunks), + score_threshold=-1, + ) + + contents = [chunk.content for chunk in resp.chunks] + assert len(contents) == len(set(contents)) @pytest.mark.asyncio -async def test_initialize_with_milvus_client(milvus_vec_index, unique_kvstore_config): - kvstore = await kvstore_impl(unique_kvstore_config) - vector_db = VectorDB( - identifier="test_db", - provider_id="test_provider", - embedding_model="test_model", - embedding_dimension=128, - metadata={"test_key": "test_value"}, - ) - test_vector_db_data = vector_db.model_dump_json() - await kvstore.set(f"{VECTOR_DBS_PREFIX}test_db", test_vector_db_data) - tmp_milvus_vec_adapter = MilvusVectorIOAdapter( - config=MilvusVectorIOConfig( - db_path=milvus_vec_index.db_path, - kvstore=unique_kvstore_config, - ), - inference_api=None, - files_api=None, - ) - await tmp_milvus_vec_adapter.initialize() - - vector_db = VectorDB( - identifier="test_db", - provider_id="test_provider", - embedding_model="test_model", - embedding_dimension=128, - ) - test_vector_db_data = vector_db.model_dump_json() - await tmp_milvus_vec_adapter.kvstore.set(f"{VECTOR_DBS_PREFIX}/test_db", test_vector_db_data) - - assert milvus_vec_index.client is not None - assert isinstance(milvus_vec_index.client, MilvusClient) - assert tmp_milvus_vec_adapter.cache is not None - # registering a vector won't update the cache or openai_vector_store collection name - assert ( - tmp_milvus_vec_adapter.metadata_collection_name not in tmp_milvus_vec_adapter.cache - or tmp_milvus_vec_adapter.openai_vector_stores - ) - - -@pytest.mark.asyncio -async def test_persistence_across_adapter_restarts( - tmp_path, milvus_vec_index, mock_inference_api, unique_kvstore_config -): - adapter1 = MilvusVectorIOAdapter( - config=MilvusVectorIOConfig(db_path=milvus_vec_index.db_path, kvstore=unique_kvstore_config), - inference_api=mock_inference_api, - files_api=None, - ) - await adapter1.initialize() +async def test_initialize_adapter_with_existing_kvstore(vector_io_adapter): + key = f"{VECTOR_DBS_PREFIX}db1" dummy = VectorDB( identifier="foo_db", provider_id="test_provider", embedding_model="test_model", embedding_dimension=128 ) - await adapter1.register_vector_db(dummy) - await adapter1.shutdown() + await vector_io_adapter.kvstore.set(key=key, value=json.dumps(dummy.model_dump())) - await adapter1.initialize() - assert "foo_db" in adapter1.cache - await adapter1.shutdown() + await vector_io_adapter.initialize() @pytest.mark.asyncio -async def test_register_and_unregister_vector_db(milvus_vec_adapter): - try: - connections.disconnect(MILVUS_ALIAS) - except Exception as _: - pass +async def test_persistence_across_adapter_restarts(vector_io_adapter): + await vector_io_adapter.initialize() + dummy = VectorDB( + identifier="foo_db", provider_id="test_provider", embedding_model="test_model", embedding_dimension=128 + ) + await vector_io_adapter.register_vector_db(dummy) + await vector_io_adapter.shutdown() - connections.connect(alias=MILVUS_ALIAS, uri=milvus_vec_adapter.config.db_path) + await vector_io_adapter.initialize() + assert "foo_db" in vector_io_adapter.cache + await vector_io_adapter.shutdown() + + +@pytest.mark.asyncio +async def test_register_and_unregister_vector_db(vector_io_adapter): unique_id = f"foo_db_{np.random.randint(1e6)}" dummy = VectorDB( identifier=unique_id, provider_id="test_provider", embedding_model="test_model", embedding_dimension=128 ) - await milvus_vec_adapter.register_vector_db(dummy) - assert dummy.identifier in milvus_vec_adapter.cache - - if dummy.identifier in milvus_vec_adapter.cache: - index = milvus_vec_adapter.cache[dummy.identifier].index - if hasattr(index, "client") and hasattr(index.client, "_using"): - index.client._using = MILVUS_ALIAS - - await milvus_vec_adapter.unregister_vector_db(dummy.identifier) - assert dummy.identifier not in milvus_vec_adapter.cache + await vector_io_adapter.register_vector_db(dummy) + assert dummy.identifier in vector_io_adapter.cache + await vector_io_adapter.unregister_vector_db(dummy.identifier) + assert dummy.identifier not in vector_io_adapter.cache @pytest.mark.asyncio -async def test_query_unregistered_raises(milvus_vec_adapter): +async def test_query_unregistered_raises(vector_io_adapter): fake_emb = np.zeros(8, dtype=np.float32) - with pytest.raises(AttributeError): - await milvus_vec_adapter.query_chunks("no_such_db", fake_emb) + with pytest.raises(ValueError): + await vector_io_adapter.query_chunks("no_such_db", fake_emb) @pytest.mark.asyncio -async def test_insert_chunks_calls_underlying_index(milvus_vec_adapter): +async def test_insert_chunks_calls_underlying_index(vector_io_adapter): fake_index = AsyncMock() - milvus_vec_adapter._get_and_cache_vector_db_index = AsyncMock(return_value=fake_index) + vector_io_adapter._get_and_cache_vector_db_index = AsyncMock(return_value=fake_index) chunks = ["chunk1", "chunk2"] - await milvus_vec_adapter.insert_chunks("db1", chunks) + await vector_io_adapter.insert_chunks("db1", chunks) fake_index.insert_chunks.assert_awaited_once_with(chunks) @pytest.mark.asyncio -async def test_insert_chunks_missing_db_raises(milvus_vec_adapter): - milvus_vec_adapter._get_and_cache_vector_db_index = AsyncMock(return_value=None) +async def test_insert_chunks_missing_db_raises(vector_io_adapter): + vector_io_adapter._get_and_cache_vector_db_index = AsyncMock(return_value=None) with pytest.raises(ValueError): - await milvus_vec_adapter.insert_chunks("db_not_exist", []) + await vector_io_adapter.insert_chunks("db_not_exist", []) @pytest.mark.asyncio -async def test_query_chunks_calls_underlying_index_and_returns(milvus_vec_adapter): +async def test_query_chunks_calls_underlying_index_and_returns(vector_io_adapter): expected = QueryChunksResponse(chunks=[Chunk(content="c1")], scores=[0.1]) fake_index = AsyncMock(query_chunks=AsyncMock(return_value=expected)) - milvus_vec_adapter._get_and_cache_vector_db_index = AsyncMock(return_value=fake_index) + vector_io_adapter._get_and_cache_vector_db_index = AsyncMock(return_value=fake_index) - response = await milvus_vec_adapter.query_chunks("db1", "my_query", {"param": 1}) + response = await vector_io_adapter.query_chunks("db1", "my_query", {"param": 1}) fake_index.query_chunks.assert_awaited_once_with("my_query", {"param": 1}) assert response is expected @pytest.mark.asyncio -async def test_query_chunks_missing_db_raises(milvus_vec_adapter): - milvus_vec_adapter._get_and_cache_vector_db_index = AsyncMock(return_value=None) +async def test_query_chunks_missing_db_raises(vector_io_adapter): + vector_io_adapter._get_and_cache_vector_db_index = AsyncMock(return_value=None) with pytest.raises(ValueError): - await milvus_vec_adapter.query_chunks("db_missing", "q", None) + await vector_io_adapter.query_chunks("db_missing", "q", None) @pytest.mark.asyncio -async def test_save_openai_vector_store(milvus_vec_adapter): +async def test_save_openai_vector_store(vector_io_adapter): store_id = "vs_1234" openai_vector_store = { "id": store_id, @@ -260,14 +149,14 @@ async def test_save_openai_vector_store(milvus_vec_adapter): "embedding_model": "test_model", } - await milvus_vec_adapter._save_openai_vector_store(store_id, openai_vector_store) + await vector_io_adapter._save_openai_vector_store(store_id, openai_vector_store) - assert openai_vector_store["id"] in milvus_vec_adapter.openai_vector_stores - assert milvus_vec_adapter.openai_vector_stores[openai_vector_store["id"]] == openai_vector_store + assert openai_vector_store["id"] in vector_io_adapter.openai_vector_stores + assert vector_io_adapter.openai_vector_stores[openai_vector_store["id"]] == openai_vector_store @pytest.mark.asyncio -async def test_update_openai_vector_store(milvus_vec_adapter): +async def test_update_openai_vector_store(vector_io_adapter): store_id = "vs_1234" openai_vector_store = { "id": store_id, @@ -277,14 +166,14 @@ async def test_update_openai_vector_store(milvus_vec_adapter): "embedding_model": "test_model", } - await milvus_vec_adapter._save_openai_vector_store(store_id, openai_vector_store) + await vector_io_adapter._save_openai_vector_store(store_id, openai_vector_store) openai_vector_store["description"] = "Updated description" - await milvus_vec_adapter._update_openai_vector_store(store_id, openai_vector_store) - assert milvus_vec_adapter.openai_vector_stores[openai_vector_store["id"]] == openai_vector_store + await vector_io_adapter._update_openai_vector_store(store_id, openai_vector_store) + assert vector_io_adapter.openai_vector_stores[openai_vector_store["id"]] == openai_vector_store @pytest.mark.asyncio -async def test_delete_openai_vector_store(milvus_vec_adapter): +async def test_delete_openai_vector_store(vector_io_adapter): store_id = "vs_1234" openai_vector_store = { "id": store_id, @@ -294,13 +183,13 @@ async def test_delete_openai_vector_store(milvus_vec_adapter): "embedding_model": "test_model", } - await milvus_vec_adapter._save_openai_vector_store(store_id, openai_vector_store) - await milvus_vec_adapter._delete_openai_vector_store_from_storage(store_id) - assert openai_vector_store["id"] not in milvus_vec_adapter.openai_vector_stores + await vector_io_adapter._save_openai_vector_store(store_id, openai_vector_store) + await vector_io_adapter._delete_openai_vector_store_from_storage(store_id) + assert openai_vector_store["id"] not in vector_io_adapter.openai_vector_stores @pytest.mark.asyncio -async def test_load_openai_vector_stores(milvus_vec_adapter): +async def test_load_openai_vector_stores(vector_io_adapter): store_id = "vs_1234" openai_vector_store = { "id": store_id, @@ -310,13 +199,13 @@ async def test_load_openai_vector_stores(milvus_vec_adapter): "embedding_model": "test_model", } - await milvus_vec_adapter._save_openai_vector_store(store_id, openai_vector_store) - loaded_stores = await milvus_vec_adapter._load_openai_vector_stores() + await vector_io_adapter._save_openai_vector_store(store_id, openai_vector_store) + loaded_stores = await vector_io_adapter._load_openai_vector_stores() assert loaded_stores[store_id] == openai_vector_store @pytest.mark.asyncio -async def test_save_openai_vector_store_file(milvus_vec_adapter, tmp_path_factory): +async def test_save_openai_vector_store_file(vector_io_adapter, tmp_path_factory): store_id = "vs_1234" file_id = "file_1234" @@ -334,11 +223,11 @@ async def test_save_openai_vector_store_file(milvus_vec_adapter, tmp_path_factor ] # validating we don't raise an exception - await milvus_vec_adapter._save_openai_vector_store_file(store_id, file_id, file_info, file_contents) + await vector_io_adapter._save_openai_vector_store_file(store_id, file_id, file_info, file_contents) @pytest.mark.asyncio -async def test_update_openai_vector_store_file(milvus_vec_adapter, tmp_path_factory): +async def test_update_openai_vector_store_file(vector_io_adapter, tmp_path_factory): store_id = "vs_1234" file_id = "file_1234" @@ -355,24 +244,24 @@ async def test_update_openai_vector_store_file(milvus_vec_adapter, tmp_path_fact {"content": "Test content", "chunk_metadata": {"chunk_id": "chunk_001"}, "metadata": {"file_id": file_id}} ] - await milvus_vec_adapter._save_openai_vector_store_file(store_id, file_id, file_info, file_contents) + await vector_io_adapter._save_openai_vector_store_file(store_id, file_id, file_info, file_contents) updated_file_info = file_info.copy() updated_file_info["filename"] = "updated_test_file.txt" - await milvus_vec_adapter._update_openai_vector_store_file( + await vector_io_adapter._update_openai_vector_store_file( store_id, file_id, updated_file_info, ) - loaded_contents = await milvus_vec_adapter._load_openai_vector_store_file(store_id, file_id) + loaded_contents = await vector_io_adapter._load_openai_vector_store_file(store_id, file_id) assert loaded_contents == updated_file_info assert loaded_contents != file_info @pytest.mark.asyncio -async def test_load_openai_vector_store_file_contents(milvus_vec_adapter, tmp_path_factory): +async def test_load_openai_vector_store_file_contents(vector_io_adapter, tmp_path_factory): store_id = "vs_1234" file_id = "file_1234" @@ -389,14 +278,14 @@ async def test_load_openai_vector_store_file_contents(milvus_vec_adapter, tmp_pa {"content": "Test content", "chunk_metadata": {"chunk_id": "chunk_001"}, "metadata": {"file_id": file_id}} ] - await milvus_vec_adapter._save_openai_vector_store_file(store_id, file_id, file_info, file_contents) + await vector_io_adapter._save_openai_vector_store_file(store_id, file_id, file_info, file_contents) - loaded_contents = await milvus_vec_adapter._load_openai_vector_store_file_contents(store_id, file_id) + loaded_contents = await vector_io_adapter._load_openai_vector_store_file_contents(store_id, file_id) assert loaded_contents == file_contents @pytest.mark.asyncio -async def test_delete_openai_vector_store_file_from_storage(milvus_vec_adapter, tmp_path_factory): +async def test_delete_openai_vector_store_file_from_storage(vector_io_adapter, tmp_path_factory): store_id = "vs_1234" file_id = "file_1234" @@ -413,8 +302,8 @@ async def test_delete_openai_vector_store_file_from_storage(milvus_vec_adapter, {"content": "Test content", "chunk_metadata": {"chunk_id": "chunk_001"}, "metadata": {"file_id": file_id}} ] - await milvus_vec_adapter._save_openai_vector_store_file(store_id, file_id, file_info, file_contents) - await milvus_vec_adapter._delete_openai_vector_store_file_from_storage(store_id, file_id) + await vector_io_adapter._save_openai_vector_store_file(store_id, file_id, file_info, file_contents) + await vector_io_adapter._delete_openai_vector_store_file_from_storage(store_id, file_id) - loaded_contents = await milvus_vec_adapter._load_openai_vector_store_file_contents(store_id, file_id) + loaded_contents = await vector_io_adapter._load_openai_vector_store_file_contents(store_id, file_id) assert loaded_contents == [] From 0bbff91c7ef2614c98e1af3578fb10980c0cfd36 Mon Sep 17 00:00:00 2001 From: Nathan Weinberg <31703736+nathan-weinberg@users.noreply.github.com> Date: Thu, 10 Jul 2025 14:47:54 -0400 Subject: [PATCH 14/34] docs: fix a few broken things in the CONTRIBUTING.md (#2714) # What does this PR do? "dev" dependencies were moved in pyproject.toml typo with guidance around automatic doc generation Signed-off-by: Nathan Weinberg --- CONTRIBUTING.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index b9b25cedf..304c4dd26 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -66,7 +66,7 @@ You can install the dependencies by running: ```bash cd llama-stack -uv sync --extra dev +uv sync --group dev uv pip install -e . source .venv/bin/activate ``` @@ -168,7 +168,7 @@ manually as they are auto-generated. ### Updating the provider documentation -If you have made changes to a provider's configuration, you should run `./scripts/distro_codegen.py` +If you have made changes to a provider's configuration, you should run `./scripts/provider_codegen.py` to re-generate the documentation. You should not change `docs/source/.../providers/` files manually as they are auto-generated. Note that the provider "description" field will be used to generate the provider documentation. From 9f04bc6d1af4bb70512fc1f09c911c8c0a060401 Mon Sep 17 00:00:00 2001 From: Nathan Weinberg <31703736+nathan-weinberg@users.noreply.github.com> Date: Thu, 10 Jul 2025 16:14:10 -0400 Subject: [PATCH 15/34] chore: move "install.sh" script into "scripts" dir (#2719) # What does this PR do? "install.sh" is something that a general user might not use e.g. it is specific to using the "ollama" inference provider cleanup the top-level structure of the repo by moving it into the "scripts" dir and updating the relevant references accordingly Signed-off-by: Nathan Weinberg --- .github/workflows/install-script-ci.yml | 8 ++++---- README.md | 2 +- install.sh => scripts/install.sh | 0 3 files changed, 5 insertions(+), 5 deletions(-) rename install.sh => scripts/install.sh (100%) diff --git a/.github/workflows/install-script-ci.yml b/.github/workflows/install-script-ci.yml index 2eb234c77..d711444e8 100644 --- a/.github/workflows/install-script-ci.yml +++ b/.github/workflows/install-script-ci.yml @@ -3,10 +3,10 @@ name: Installer CI on: pull_request: paths: - - 'install.sh' + - 'scripts/install.sh' push: paths: - - 'install.sh' + - 'scripts/install.sh' schedule: - cron: '0 2 * * *' # every day at 02:00 UTC @@ -16,11 +16,11 @@ jobs: steps: - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # 4.2.2 - name: Run ShellCheck on install.sh - run: shellcheck install.sh + run: shellcheck scripts/install.sh smoke-test: needs: lint runs-on: ubuntu-latest steps: - uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # 4.2.2 - name: Run installer end-to-end - run: ./install.sh + run: ./scripts/install.sh diff --git a/README.md b/README.md index 1bebf6b19..9148ce05d 100644 --- a/README.md +++ b/README.md @@ -77,7 +77,7 @@ 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/install.sh | bash +curl -LsSf https://github.com/meta-llama/llama-stack/raw/main/scripts/install.sh | bash ``` ### Overview diff --git a/install.sh b/scripts/install.sh similarity index 100% rename from install.sh rename to scripts/install.sh From 5fe3027cbfd823f420b493bf07537be5d8d65436 Mon Sep 17 00:00:00 2001 From: Nathan Weinberg <31703736+nathan-weinberg@users.noreply.github.com> Date: Thu, 10 Jul 2025 17:06:10 -0400 Subject: [PATCH 16/34] chore: remove "rfc" directory and move original rfc to "docs" (#2718) # What does this PR do? the "rfc" directory has only a single document in it, and its the original RFC for creating Llama Stack simply the project directory structure by moving this into the "docs" directory and renaming it to "original_rfc" to preserve the context of the doc ## Why did you do this? A simplified top-level directory structure helps keep the project simpler and prevents misleading new contributors into thinking we use it (we really don't) --------- Signed-off-by: Nathan Weinberg Co-authored-by: raghotham --- rfcs/RFC-0001-llama-stack.md => docs/original_rfc.md | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) rename rfcs/RFC-0001-llama-stack.md => docs/original_rfc.md (96%) diff --git a/rfcs/RFC-0001-llama-stack.md b/docs/original_rfc.md similarity index 96% rename from rfcs/RFC-0001-llama-stack.md rename to docs/original_rfc.md index 222487bd6..dc95a04cb 100644 --- a/rfcs/RFC-0001-llama-stack.md +++ b/docs/original_rfc.md @@ -1,5 +1,7 @@ # The Llama Stack API +*Originally authored Jul 23, 2024* + **Authors:** * Meta: @raghotham, @ashwinb, @hjshah, @jspisak @@ -24,7 +26,7 @@ Meta releases weights of both the pretrained and instruction fine-tuned Llama mo ### Model Lifecycle -![Figure 1: Model Life Cycle](../docs/resources/model-lifecycle.png) +![Figure 1: Model Life Cycle](resources/model-lifecycle.png) For each of the operations that need to be performed (e.g. fine tuning, inference, evals etc) during the model life cycle, we identified the capabilities as toolchain APIs that are needed. Some of these capabilities are primitive operations like inference while other capabilities like synthetic data generation are composed of other capabilities. The list of APIs we have identified to support the lifecycle of Llama models is below: @@ -37,7 +39,7 @@ For each of the operations that need to be performed (e.g. fine tuning, inferenc ### Agentic System -![Figure 2: Agentic System](../docs/resources/agentic-system.png) +![Figure 2: Agentic System](resources/agentic-system.png) In addition to the model lifecycle, we considered the different components involved in an agentic system. Specifically around tool calling and shields. Since the model may decide to call tools, a single model inference call is not enough. What’s needed is an agentic loop consisting of tool calls and inference. The model provides separate tokens representing end-of-message and end-of-turn. A message represents a possible stopping point for execution where the model can inform the execution environment that a tool call needs to be made. The execution environment, upon execution, adds back the result to the context window and makes another inference call. This process can get repeated until an end-of-turn token is generated. Note that as of today, in the OSS world, such a “loop” is often coded explicitly via elaborate prompt engineering using a ReAct pattern (typically) or preconstructed execution graph. Llama 3.1 (and future Llamas) attempts to absorb this multi-step reasoning loop inside the main model itself. @@ -63,9 +65,9 @@ The sequence diagram that details the steps is [here](https://github.com/meta-ll We define the Llama Stack as a layer cake shown below. -![Figure 3: Llama Stack](../docs/resources/llama-stack.png) +![Figure 3: Llama Stack](resources/llama-stack.png) -The API is defined in the [YAML](../docs/_static/llama-stack-spec.yaml) and [HTML](../docs/_static/llama-stack-spec.html) files. +The API is defined in the [YAML](_static/llama-stack-spec.yaml) and [HTML](_static/llama-stack-spec.html) files. ## Sample implementations From 4cf1952c32b74be607fd1aefb026a65e70d8b7ef Mon Sep 17 00:00:00 2001 From: ehhuang Date: Thu, 10 Jul 2025 14:40:17 -0700 Subject: [PATCH 17/34] chore: update vllm k8s command to support tool calling (#2717) # What does this PR do? ## Test Plan --- docs/source/distributions/k8s/apply.sh | 10 +++++----- docs/source/distributions/k8s/vllm-k8s.yaml.template | 2 +- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/docs/source/distributions/k8s/apply.sh b/docs/source/distributions/k8s/apply.sh index 06b1ea10c..7b403d34e 100755 --- a/docs/source/distributions/k8s/apply.sh +++ b/docs/source/distributions/k8s/apply.sh @@ -6,12 +6,12 @@ # This source code is licensed under the terms described in the LICENSE file in # the root directory of this source tree. -export POSTGRES_USER=${POSTGRES_USER:-llamastack} -export POSTGRES_DB=${POSTGRES_DB:-llamastack} -export POSTGRES_PASSWORD=${POSTGRES_PASSWORD:-llamastack} +export POSTGRES_USER=llamastack +export POSTGRES_DB=llamastack +export POSTGRES_PASSWORD=llamastack -export INFERENCE_MODEL=${INFERENCE_MODEL:-meta-llama/Llama-3.2-3B-Instruct} -export SAFETY_MODEL=${SAFETY_MODEL:-meta-llama/Llama-Guard-3-1B} +export INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct +export SAFETY_MODEL=meta-llama/Llama-Guard-3-1B # HF_TOKEN should be set by the user; base64 encode it for the secret if [ -n "${HF_TOKEN:-}" ]; then diff --git a/docs/source/distributions/k8s/vllm-k8s.yaml.template b/docs/source/distributions/k8s/vllm-k8s.yaml.template index 03f3759c3..22bee4bbc 100644 --- a/docs/source/distributions/k8s/vllm-k8s.yaml.template +++ b/docs/source/distributions/k8s/vllm-k8s.yaml.template @@ -32,7 +32,7 @@ spec: image: vllm/vllm-openai:latest command: ["/bin/sh", "-c"] args: - - "vllm serve ${INFERENCE_MODEL} --dtype float16 --enforce-eager --max-model-len 4096 --gpu-memory-utilization 0.6" + - "vllm serve ${INFERENCE_MODEL} --dtype float16 --enforce-eager --max-model-len 4096 --gpu-memory-utilization 0.6 --enable-auto-tool-choice --tool-call-parser llama4_pythonic" env: - name: INFERENCE_MODEL value: "${INFERENCE_MODEL}" From d880c2df0ed0d1405a5458a25309ad3b66907219 Mon Sep 17 00:00:00 2001 From: ehhuang Date: Thu, 10 Jul 2025 14:40:32 -0700 Subject: [PATCH 18/34] fix: auth sql store: user is owner policy (#2674) # What does this PR do? The current authorized sql store implementation does not respect user.principal (only checks attributes). This PR addresses that. ## Test Plan Added test cases to integration tests. --- .../access_control/access_control.py | 2 +- .../utils/sqlstore/authorized_sqlstore.py | 54 ++-- .../utils/sqlstore/sqlalchemy_sqlstore.py | 58 ++-- .../sqlstore/test_authorized_sqlstore.py | 304 +++++++++++------- tests/unit/utils/test_authorized_sqlstore.py | 4 +- 5 files changed, 247 insertions(+), 175 deletions(-) diff --git a/llama_stack/distribution/access_control/access_control.py b/llama_stack/distribution/access_control/access_control.py index 075152ce4..64c0122c1 100644 --- a/llama_stack/distribution/access_control/access_control.py +++ b/llama_stack/distribution/access_control/access_control.py @@ -81,7 +81,7 @@ def is_action_allowed( if not len(policy): policy = default_policy() - qualified_resource_id = resource.type + "::" + resource.identifier + qualified_resource_id = f"{resource.type}::{resource.identifier}" for rule in policy: if rule.forbid and matches_scope(rule.forbid, action, qualified_resource_id, user.principal): if rule.when: diff --git a/llama_stack/providers/utils/sqlstore/authorized_sqlstore.py b/llama_stack/providers/utils/sqlstore/authorized_sqlstore.py index 5dff7f122..864a7dbb6 100644 --- a/llama_stack/providers/utils/sqlstore/authorized_sqlstore.py +++ b/llama_stack/providers/utils/sqlstore/authorized_sqlstore.py @@ -39,22 +39,10 @@ SQL_OPTIMIZED_POLICY = [ class SqlRecord(ProtectedResource): - """Simple ProtectedResource implementation for SQL records.""" - - def __init__(self, record_id: str, table_name: str, access_attributes: dict[str, list[str]] | None = None): + def __init__(self, record_id: str, table_name: str, owner: User): self.type = f"sql_record::{table_name}" self.identifier = record_id - - if access_attributes: - self.owner = User( - principal="system", - attributes=access_attributes, - ) - else: - self.owner = User( - principal="system_public", - attributes=None, - ) + self.owner = owner class AuthorizedSqlStore: @@ -101,22 +89,27 @@ class AuthorizedSqlStore: async def create_table(self, table: str, schema: Mapping[str, ColumnType | ColumnDefinition]) -> None: """Create a table with built-in access control support.""" - await self.sql_store.add_column_if_not_exists(table, "access_attributes", ColumnType.JSON) enhanced_schema = dict(schema) if "access_attributes" not in enhanced_schema: enhanced_schema["access_attributes"] = ColumnType.JSON + if "owner_principal" not in enhanced_schema: + enhanced_schema["owner_principal"] = ColumnType.STRING await self.sql_store.create_table(table, enhanced_schema) + await self.sql_store.add_column_if_not_exists(table, "access_attributes", ColumnType.JSON) + await self.sql_store.add_column_if_not_exists(table, "owner_principal", ColumnType.STRING) async def insert(self, table: str, data: Mapping[str, Any]) -> None: """Insert a row with automatic access control attribute capture.""" enhanced_data = dict(data) current_user = get_authenticated_user() - if current_user and current_user.attributes: + if current_user: + enhanced_data["owner_principal"] = current_user.principal enhanced_data["access_attributes"] = current_user.attributes else: + enhanced_data["owner_principal"] = None enhanced_data["access_attributes"] = None await self.sql_store.insert(table, enhanced_data) @@ -146,9 +139,12 @@ class AuthorizedSqlStore: for row in rows.data: stored_access_attrs = row.get("access_attributes") + stored_owner_principal = row.get("owner_principal") or "" record_id = row.get("id", "unknown") - sql_record = SqlRecord(str(record_id), table, stored_access_attrs) + sql_record = SqlRecord( + str(record_id), table, User(principal=stored_owner_principal, attributes=stored_access_attrs) + ) if is_action_allowed(policy, Action.READ, sql_record, current_user): filtered_rows.append(row) @@ -186,8 +182,10 @@ class AuthorizedSqlStore: Only applies SQL filtering for the default policy to ensure correctness. For custom policies, uses conservative filtering to avoid blocking legitimate access. """ + current_user = get_authenticated_user() + if not policy or policy == SQL_OPTIMIZED_POLICY: - return self._build_default_policy_where_clause() + return self._build_default_policy_where_clause(current_user) else: return self._build_conservative_where_clause() @@ -227,29 +225,27 @@ class AuthorizedSqlStore: def _get_public_access_conditions(self) -> list[str]: """Get the SQL conditions for public access.""" + # Public records are records that have no owner_principal or access_attributes + conditions = ["owner_principal = ''"] if self.database_type == SqlStoreType.postgres: # Postgres stores JSON null as 'null' - return ["access_attributes::text = 'null'"] + conditions.append("access_attributes::text = 'null'") elif self.database_type == SqlStoreType.sqlite: - return ["access_attributes = 'null'"] + conditions.append("access_attributes = 'null'") else: raise ValueError(f"Unsupported database type: {self.database_type}") + return conditions - def _build_default_policy_where_clause(self) -> str: + def _build_default_policy_where_clause(self, current_user: User | None) -> str: """Build SQL WHERE clause for the default policy. Default policy: permit all actions when user in owners [roles, teams, projects, namespaces] This means user must match ALL attribute categories that exist in the resource. """ - current_user = get_authenticated_user() - base_conditions = self._get_public_access_conditions() - if not current_user or not current_user.attributes: - # Only allow public records - return f"({' OR '.join(base_conditions)})" - else: - user_attr_conditions = [] + user_attr_conditions = [] + if current_user and current_user.attributes: for attr_key, user_values in current_user.attributes.items(): if user_values: value_conditions = [] @@ -269,7 +265,7 @@ class AuthorizedSqlStore: all_requirements_met = f"({' AND '.join(user_attr_conditions)})" base_conditions.append(all_requirements_met) - return f"({' OR '.join(base_conditions)})" + return f"({' OR '.join(base_conditions)})" def _build_conservative_where_clause(self) -> str: """Conservative SQL filtering for custom policies. diff --git a/llama_stack/providers/utils/sqlstore/sqlalchemy_sqlstore.py b/llama_stack/providers/utils/sqlstore/sqlalchemy_sqlstore.py index 3aecb0d59..6414929db 100644 --- a/llama_stack/providers/utils/sqlstore/sqlalchemy_sqlstore.py +++ b/llama_stack/providers/utils/sqlstore/sqlalchemy_sqlstore.py @@ -244,35 +244,41 @@ class SqlAlchemySqlStoreImpl(SqlStore): engine = create_async_engine(self.config.engine_str) try: - inspector = inspect(engine) - - table_names = inspector.get_table_names() - if table not in table_names: - return - - existing_columns = inspector.get_columns(table) - column_names = [col["name"] for col in existing_columns] - - if column_name in column_names: - return - - sqlalchemy_type = TYPE_MAPPING.get(column_type) - if not sqlalchemy_type: - raise ValueError(f"Unsupported column type '{column_type}' for column '{column_name}'.") - - # Create the ALTER TABLE statement - # Note: We need to get the dialect-specific type name - dialect = engine.dialect - type_impl = sqlalchemy_type() - compiled_type = type_impl.compile(dialect=dialect) - - nullable_clause = "" if nullable else " NOT NULL" - add_column_sql = text(f"ALTER TABLE {table} ADD COLUMN {column_name} {compiled_type}{nullable_clause}") - async with engine.begin() as conn: + + def check_column_exists(sync_conn): + inspector = inspect(sync_conn) + + table_names = inspector.get_table_names() + if table not in table_names: + return False, False # table doesn't exist, column doesn't exist + + existing_columns = inspector.get_columns(table) + column_names = [col["name"] for col in existing_columns] + + return True, column_name in column_names # table exists, column exists or not + + table_exists, column_exists = await conn.run_sync(check_column_exists) + if not table_exists or column_exists: + return + + sqlalchemy_type = TYPE_MAPPING.get(column_type) + if not sqlalchemy_type: + raise ValueError(f"Unsupported column type '{column_type}' for column '{column_name}'.") + + # Create the ALTER TABLE statement + # Note: We need to get the dialect-specific type name + dialect = engine.dialect + type_impl = sqlalchemy_type() + compiled_type = type_impl.compile(dialect=dialect) + + nullable_clause = "" if nullable else " NOT NULL" + add_column_sql = text(f"ALTER TABLE {table} ADD COLUMN {column_name} {compiled_type}{nullable_clause}") + await conn.execute(add_column_sql) - except Exception: + except Exception as e: # If any error occurs during migration, log it but don't fail # The table creation will handle adding the column + logger.error(f"Error adding column {column_name} to table {table}: {e}") pass diff --git a/tests/integration/providers/utils/sqlstore/test_authorized_sqlstore.py b/tests/integration/providers/utils/sqlstore/test_authorized_sqlstore.py index 93b4d8905..bf6077532 100644 --- a/tests/integration/providers/utils/sqlstore/test_authorized_sqlstore.py +++ b/tests/integration/providers/utils/sqlstore/test_authorized_sqlstore.py @@ -14,8 +14,7 @@ from llama_stack.distribution.access_control.access_control import default_polic from llama_stack.distribution.datatypes import User from llama_stack.providers.utils.sqlstore.api import ColumnType from llama_stack.providers.utils.sqlstore.authorized_sqlstore import AuthorizedSqlStore -from llama_stack.providers.utils.sqlstore.sqlalchemy_sqlstore import SqlAlchemySqlStoreImpl -from llama_stack.providers.utils.sqlstore.sqlstore import PostgresSqlStoreConfig, SqliteSqlStoreConfig +from llama_stack.providers.utils.sqlstore.sqlstore import PostgresSqlStoreConfig, SqliteSqlStoreConfig, sqlstore_impl def get_postgres_config(): @@ -30,144 +29,213 @@ def get_postgres_config(): def get_sqlite_config(): - """Get SQLite configuration with temporary database.""" - tmp_file = tempfile.NamedTemporaryFile(suffix=".db", delete=False) - tmp_file.close() - return SqliteSqlStoreConfig(db_path=tmp_file.name), tmp_file.name + """Get SQLite configuration with temporary file database.""" + temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".db") + temp_file.close() + return SqliteSqlStoreConfig(db_path=temp_file.name) + + +# Backend configurations for parametrized tests +BACKEND_CONFIGS = [ + pytest.param( + get_postgres_config, + marks=pytest.mark.skipif( + not os.environ.get("ENABLE_POSTGRES_TESTS"), + reason="PostgreSQL tests require ENABLE_POSTGRES_TESTS environment variable", + ), + id="postgres", + ), + pytest.param(get_sqlite_config, id="sqlite"), +] + + +@pytest.fixture +def authorized_store(backend_config): + """Set up authorized store with proper cleanup.""" + config_func = backend_config + + config = config_func() + + base_sqlstore = sqlstore_impl(config) + authorized_store = AuthorizedSqlStore(base_sqlstore) + + yield authorized_store + + if hasattr(config, "db_path"): + try: + os.unlink(config.db_path) + except (OSError, FileNotFoundError): + pass + + +async def create_test_table(authorized_store, table_name): + """Create a test table with standard schema.""" + await authorized_store.create_table( + table=table_name, + schema={ + "id": ColumnType.STRING, + "data": ColumnType.STRING, + }, + ) + + +async def cleanup_records(sql_store, table_name, record_ids): + """Clean up test records.""" + for record_id in record_ids: + try: + await sql_store.delete(table_name, {"id": record_id}) + except Exception: + pass @pytest.mark.asyncio -@pytest.mark.parametrize( - "backend_config", - [ - pytest.param( - ("postgres", get_postgres_config), - marks=pytest.mark.skipif( - not os.environ.get("ENABLE_POSTGRES_TESTS"), - reason="PostgreSQL tests require ENABLE_POSTGRES_TESTS environment variable", - ), - id="postgres", - ), - pytest.param(("sqlite", get_sqlite_config), id="sqlite"), - ], -) +@pytest.mark.parametrize("backend_config", BACKEND_CONFIGS) @patch("llama_stack.providers.utils.sqlstore.authorized_sqlstore.get_authenticated_user") -async def test_json_comparison(mock_get_authenticated_user, backend_config): +async def test_authorized_store_attributes(mock_get_authenticated_user, authorized_store, request): """Test that JSON column comparisons work correctly for both PostgreSQL and SQLite""" - backend_name, config_func = backend_config + backend_name = request.node.callspec.id - # Handle different config types - if backend_name == "postgres": - config = config_func() - cleanup_path = None - else: # sqlite - config, cleanup_path = config_func() + # Create test table + table_name = f"test_json_comparison_{backend_name}" + await create_test_table(authorized_store, table_name) try: - base_sqlstore = SqlAlchemySqlStoreImpl(config) - authorized_store = AuthorizedSqlStore(base_sqlstore) + # Test with no authenticated user (should handle JSON null comparison) + mock_get_authenticated_user.return_value = None - # Create test table - table_name = f"test_json_comparison_{backend_name}" - await authorized_store.create_table( - table=table_name, - schema={ - "id": ColumnType.STRING, - "data": ColumnType.STRING, - }, + # Insert some test data + await authorized_store.insert(table_name, {"id": "1", "data": "public_data"}) + + # Test fetching with no user - should not error on JSON comparison + result = await authorized_store.fetch_all(table_name, policy=default_policy()) + assert len(result.data) == 1 + assert result.data[0]["id"] == "1" + assert result.data[0]["access_attributes"] is None + + # Test with authenticated user + test_user = User("test-user", {"roles": ["admin"]}) + mock_get_authenticated_user.return_value = test_user + + # Insert data with user attributes + await authorized_store.insert(table_name, {"id": "2", "data": "admin_data"}) + + # Fetch all - admin should see both + result = await authorized_store.fetch_all(table_name, policy=default_policy()) + assert len(result.data) == 2 + + # Test with non-admin user + regular_user = User("regular-user", {"roles": ["user"]}) + mock_get_authenticated_user.return_value = regular_user + + # Should only see public record + result = await authorized_store.fetch_all(table_name, policy=default_policy()) + assert len(result.data) == 1 + assert result.data[0]["id"] == "1" + + # Test the category missing branch: user with multiple attributes + multi_user = User("multi-user", {"roles": ["admin"], "teams": ["dev"]}) + mock_get_authenticated_user.return_value = multi_user + + # Insert record with multi-user (has both roles and teams) + await authorized_store.insert(table_name, {"id": "3", "data": "multi_user_data"}) + + # Test different user types to create records with different attribute patterns + # Record with only roles (teams category will be missing) + roles_only_user = User("roles-user", {"roles": ["admin"]}) + mock_get_authenticated_user.return_value = roles_only_user + await authorized_store.insert(table_name, {"id": "4", "data": "roles_only_data"}) + + # Record with only teams (roles category will be missing) + teams_only_user = User("teams-user", {"teams": ["dev"]}) + mock_get_authenticated_user.return_value = teams_only_user + await authorized_store.insert(table_name, {"id": "5", "data": "teams_only_data"}) + + # Record with different roles/teams (shouldn't match our test user) + different_user = User("different-user", {"roles": ["user"], "teams": ["qa"]}) + mock_get_authenticated_user.return_value = different_user + await authorized_store.insert(table_name, {"id": "6", "data": "different_user_data"}) + + # Now test with the multi-user who has both roles=admin and teams=dev + mock_get_authenticated_user.return_value = multi_user + result = await authorized_store.fetch_all(table_name, policy=default_policy()) + + # Should see: + # - public record (1) - no access_attributes + # - admin record (2) - user matches roles=admin, teams missing (allowed) + # - multi_user record (3) - user matches both roles=admin and teams=dev + # - roles_only record (4) - user matches roles=admin, teams missing (allowed) + # - teams_only record (5) - user matches teams=dev, roles missing (allowed) + # Should NOT see: + # - different_user record (6) - user doesn't match roles=user or teams=qa + expected_ids = {"1", "2", "3", "4", "5"} + actual_ids = {record["id"] for record in result.data} + assert actual_ids == expected_ids, f"Expected to see records {expected_ids} but got {actual_ids}" + + # Verify the category missing logic specifically + # Records 4 and 5 test the "category missing" branch where one attribute category is missing + category_test_ids = {record["id"] for record in result.data if record["id"] in ["4", "5"]} + assert category_test_ids == {"4", "5"}, ( + f"Category missing logic failed: expected 4,5 but got {category_test_ids}" ) - try: - # Test with no authenticated user (should handle JSON null comparison) - mock_get_authenticated_user.return_value = None + finally: + # Clean up records + await cleanup_records(authorized_store.sql_store, table_name, ["1", "2", "3", "4", "5", "6"]) - # Insert some test data - await authorized_store.insert(table_name, {"id": "1", "data": "public_data"}) - # Test fetching with no user - should not error on JSON comparison - result = await authorized_store.fetch_all(table_name, policy=default_policy()) - assert len(result.data) == 1 - assert result.data[0]["id"] == "1" - assert result.data[0]["access_attributes"] is None +@pytest.mark.asyncio +@pytest.mark.parametrize("backend_config", BACKEND_CONFIGS) +@patch("llama_stack.providers.utils.sqlstore.authorized_sqlstore.get_authenticated_user") +async def test_user_ownership_policy(mock_get_authenticated_user, authorized_store, request): + """Test that 'user is owner' policies work correctly with record ownership""" + from llama_stack.distribution.access_control.datatypes import AccessRule, Action, Scope - # Test with authenticated user - test_user = User("test-user", {"roles": ["admin"]}) - mock_get_authenticated_user.return_value = test_user + backend_name = request.node.callspec.id - # Insert data with user attributes - await authorized_store.insert(table_name, {"id": "2", "data": "admin_data"}) + # Create test table + table_name = f"test_ownership_{backend_name}" + await create_test_table(authorized_store, table_name) - # Fetch all - admin should see both - result = await authorized_store.fetch_all(table_name, policy=default_policy()) - assert len(result.data) == 2 + try: + # Test with first user who creates records + user1 = User("user1", {"roles": ["admin"]}) + mock_get_authenticated_user.return_value = user1 - # Test with non-admin user - regular_user = User("regular-user", {"roles": ["user"]}) - mock_get_authenticated_user.return_value = regular_user + # Insert a record owned by user1 + await authorized_store.insert(table_name, {"id": "1", "data": "user1_data"}) - # Should only see public record - result = await authorized_store.fetch_all(table_name, policy=default_policy()) - assert len(result.data) == 1 - assert result.data[0]["id"] == "1" + # Test with second user + user2 = User("user2", {"roles": ["user"]}) + mock_get_authenticated_user.return_value = user2 - # Test the category missing branch: user with multiple attributes - multi_user = User("multi-user", {"roles": ["admin"], "teams": ["dev"]}) - mock_get_authenticated_user.return_value = multi_user + # Insert a record owned by user2 + await authorized_store.insert(table_name, {"id": "2", "data": "user2_data"}) - # Insert record with multi-user (has both roles and teams) - await authorized_store.insert(table_name, {"id": "3", "data": "multi_user_data"}) + # Create a policy that only allows access when user is the owner + owner_only_policy = [ + AccessRule( + permit=Scope(actions=[Action.READ]), + when=["user is owner"], + ), + ] - # Test different user types to create records with different attribute patterns - # Record with only roles (teams category will be missing) - roles_only_user = User("roles-user", {"roles": ["admin"]}) - mock_get_authenticated_user.return_value = roles_only_user - await authorized_store.insert(table_name, {"id": "4", "data": "roles_only_data"}) + # Test user1 access - should only see their own record + mock_get_authenticated_user.return_value = user1 + result = await authorized_store.fetch_all(table_name, policy=owner_only_policy) + assert len(result.data) == 1, f"Expected user1 to see 1 record, got {len(result.data)}" + assert result.data[0]["id"] == "1", f"Expected user1's record, got {result.data[0]['id']}" - # Record with only teams (roles category will be missing) - teams_only_user = User("teams-user", {"teams": ["dev"]}) - mock_get_authenticated_user.return_value = teams_only_user - await authorized_store.insert(table_name, {"id": "5", "data": "teams_only_data"}) + # Test user2 access - should only see their own record + mock_get_authenticated_user.return_value = user2 + result = await authorized_store.fetch_all(table_name, policy=owner_only_policy) + assert len(result.data) == 1, f"Expected user2 to see 1 record, got {len(result.data)}" + assert result.data[0]["id"] == "2", f"Expected user2's record, got {result.data[0]['id']}" - # Record with different roles/teams (shouldn't match our test user) - different_user = User("different-user", {"roles": ["user"], "teams": ["qa"]}) - mock_get_authenticated_user.return_value = different_user - await authorized_store.insert(table_name, {"id": "6", "data": "different_user_data"}) - - # Now test with the multi-user who has both roles=admin and teams=dev - mock_get_authenticated_user.return_value = multi_user - result = await authorized_store.fetch_all(table_name, policy=default_policy()) - - # Should see: - # - public record (1) - no access_attributes - # - admin record (2) - user matches roles=admin, teams missing (allowed) - # - multi_user record (3) - user matches both roles=admin and teams=dev - # - roles_only record (4) - user matches roles=admin, teams missing (allowed) - # - teams_only record (5) - user matches teams=dev, roles missing (allowed) - # Should NOT see: - # - different_user record (6) - user doesn't match roles=user or teams=qa - expected_ids = {"1", "2", "3", "4", "5"} - actual_ids = {record["id"] for record in result.data} - assert actual_ids == expected_ids, f"Expected to see records {expected_ids} but got {actual_ids}" - - # Verify the category missing logic specifically - # Records 4 and 5 test the "category missing" branch where one attribute category is missing - category_test_ids = {record["id"] for record in result.data if record["id"] in ["4", "5"]} - assert category_test_ids == {"4", "5"}, ( - f"Category missing logic failed: expected 4,5 but got {category_test_ids}" - ) - - finally: - # Clean up records - for record_id in ["1", "2", "3", "4", "5", "6"]: - try: - await base_sqlstore.delete(table_name, {"id": record_id}) - except Exception: - pass + # Test with anonymous user - should see no records + mock_get_authenticated_user.return_value = None + result = await authorized_store.fetch_all(table_name, policy=owner_only_policy) + assert len(result.data) == 0, f"Expected anonymous user to see 0 records, got {len(result.data)}" finally: - # Clean up temporary SQLite database file if needed - if cleanup_path: - try: - os.unlink(cleanup_path) - except OSError: - pass + # Clean up records + await cleanup_records(authorized_store.sql_store, table_name, ["1", "2"]) diff --git a/tests/unit/utils/test_authorized_sqlstore.py b/tests/unit/utils/test_authorized_sqlstore.py index 1624c0ba7..61763719a 100644 --- a/tests/unit/utils/test_authorized_sqlstore.py +++ b/tests/unit/utils/test_authorized_sqlstore.py @@ -153,7 +153,9 @@ async def test_sql_policy_consistency(mock_get_authenticated_user): policy_ids = set() for scenario in test_scenarios: sql_record = SqlRecord( - record_id=scenario["id"], table_name="resources", access_attributes=scenario["access_attributes"] + record_id=scenario["id"], + table_name="resources", + owner=User(principal="test-user", attributes=scenario["access_attributes"]), ) if is_action_allowed(policy, Action.READ, sql_record, user): From 2e4eedce14132e5ed125766404fa05f973ab84a5 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?S=C3=A9bastien=20Han?= Date: Fri, 11 Jul 2025 16:25:33 +0200 Subject: [PATCH 19/34] fix: container build on podman (#2723) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit # What does this PR do? COPY with chmod does not work, see https://github.com/containers/buildah/issues/4614. Also Docker arguably implements it. Anyway, this command is not even needed since later don't we do: ``` RUN mkdir -p /.llama /.cache && chmod -R g+rw /app /.llama /.cache ``` And providers.d will get the right modes. ## Test Plan Build with CONTAINER_BINARY=podman and success Signed-off-by: Sébastien Han --- llama_stack/distribution/build_container.sh | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/llama_stack/distribution/build_container.sh b/llama_stack/distribution/build_container.sh index d9a918fb5..6e794b36f 100755 --- a/llama_stack/distribution/build_container.sh +++ b/llama_stack/distribution/build_container.sh @@ -96,7 +96,7 @@ FROM $container_base WORKDIR /app # We install the Python 3.12 dev headers and build tools so that any -# C‑extension wheels (e.g. polyleven, faiss‑cpu) can compile successfully. +# C-extension wheels (e.g. polyleven, faiss-cpu) can compile successfully. RUN dnf -y update && dnf install -y iputils git net-tools wget \ vim-minimal python3.12 python3.12-pip python3.12-wheel \ @@ -169,7 +169,7 @@ if [ -n "$run_config" ]; then echo "Copying external providers directory: $external_providers_dir" cp -r "$external_providers_dir" "$BUILD_CONTEXT_DIR/providers.d" add_to_container << EOF -COPY --chmod=g+w providers.d /.llama/providers.d +COPY providers.d /.llama/providers.d EOF fi From 2ebc172f339916d450139325c30808f675f022fb Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?S=C3=A9bastien=20Han?= Date: Fri, 11 Jul 2025 16:25:51 +0200 Subject: [PATCH 20/34] fix: pin opentelemtry version (#2722) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit # What does this PR do? Otherwise we can get old versions like 1.11 and experience this error: ``` ModuleNotFoundError: No module named 'opentelemetry.exporter.otlp.proto.http.metric_exporter' ``` Signed-off-by: Sébastien Han --- pyproject.toml | 4 ++-- uv.lock | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index d84a823a3..89ae4bc23 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -42,8 +42,8 @@ dependencies = [ "h11>=0.16.0", "python-multipart>=0.0.20", # For fastapi Form "uvicorn>=0.34.0", # server - "opentelemetry-sdk", # server - "opentelemetry-exporter-otlp-proto-http", # server + "opentelemetry-sdk>=1.30.0", # server + "opentelemetry-exporter-otlp-proto-http>=1.30.0", # server "aiosqlite>=0.21.0", # server - for metadata store "asyncpg", # for metadata store ] diff --git a/uv.lock b/uv.lock index e77fb89f5..8374fe38a 100644 --- a/uv.lock +++ b/uv.lock @@ -1365,8 +1365,8 @@ requires-dist = [ { name = "llama-stack-client", specifier = ">=0.2.14" }, { name = "llama-stack-client", marker = "extra == 'ui'", specifier = ">=0.2.14" }, { name = "openai", specifier = ">=1.66" }, - { name = "opentelemetry-exporter-otlp-proto-http" }, - { name = "opentelemetry-sdk" }, + { name = "opentelemetry-exporter-otlp-proto-http", specifier = ">=1.30.0" }, + { name = "opentelemetry-sdk", specifier = ">=1.30.0" }, { name = "pandas", marker = "extra == 'ui'" }, { name = "pillow" }, { name = "prompt-toolkit" }, From 30b2e6a495361faa6e52e6255780a69e92254f58 Mon Sep 17 00:00:00 2001 From: Matthew Farrellee Date: Fri, 11 Jul 2025 16:00:24 -0400 Subject: [PATCH 21/34] chore: default to pytest asyncio-mode=auto (#2730) # What does this PR do? previously, developers who ran `./scripts/unit-tests.sh` would get `asyncio-mode=auto`, which meant `@pytest.mark.asyncio` and `@pytest_asyncio.fixture` were redundent. developers who ran `pytest` directly would get pytest's default (strict mode), would run into errors leading them to add `@pytest.mark.asyncio` / `@pytest_asyncio.fixture` to their code. with this change - - `asyncio_mode=auto` is included in `pyproject.toml` making behavior consistent for all invocations of pytest - removes all redundant `@pytest_asyncio.fixture` and `@pytest.mark.asyncio` - for good measure, requires `pytest>=8.4` and `pytest-asyncio>=1.0` ## Test Plan - `./scripts/unit-tests.sh` - `uv run pytest tests/unit` --- pyproject.toml | 7 ++++-- scripts/unit-tests.sh | 2 +- tests/integration/agents/test_persistence.py | 2 -- tests/integration/inspect/test_inspect.py | 3 --- tests/integration/providers/test_providers.py | 2 -- .../sqlstore/test_authorized_sqlstore.py | 2 -- .../routers/test_routing_tables.py | 8 ------- tests/unit/distribution/test_context.py | 3 --- tests/unit/files/test_files.py | 22 +------------------ tests/unit/fixtures.py | 8 +++---- .../agent/test_meta_reference_agent.py | 9 +------- .../meta_reference/test_openai_responses.py | 15 ------------- .../agents/test_persistence_access_control.py | 7 +----- .../providers/inference/test_remote_vllm.py | 16 +------------- .../utils/inference/test_openai_compat.py | 6 ----- .../utils/memory/test_vector_store.py | 7 ------ .../providers/utils/test_model_registry.py | 10 --------- tests/unit/providers/utils/test_scheduler.py | 3 --- tests/unit/providers/vector_io/test_faiss.py | 8 ++----- tests/unit/providers/vector_io/test_qdrant.py | 5 +---- .../providers/vector_io/test_sqlite_vec.py | 18 +-------------- .../test_vector_io_openai_vector_stores.py | 19 ---------------- tests/unit/rag/test_rag_query.py | 2 -- tests/unit/rag/test_vector_store.py | 7 ------ tests/unit/registry/test_registry.py | 8 ------- tests/unit/registry/test_registry_acl.py | 5 ----- tests/unit/server/test_access_control.py | 11 ++-------- tests/unit/server/test_auth.py | 1 - tests/unit/server/test_resolver.py | 2 -- tests/unit/server/test_sse.py | 7 ------ .../utils/inference/test_inference_store.py | 5 ----- .../utils/responses/test_responses_store.py | 8 ------- tests/unit/utils/sqlstore/test_sqlstore.py | 8 ------- tests/unit/utils/test_authorized_sqlstore.py | 5 ----- uv.lock | 17 +++++++------- 35 files changed, 29 insertions(+), 239 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 89ae4bc23..f4115d028 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -58,9 +58,9 @@ ui = [ [dependency-groups] dev = [ - "pytest", + "pytest>=8.4", "pytest-timeout", - "pytest-asyncio", + "pytest-asyncio>=1.0", "pytest-cov", "pytest-html", "pytest-json-report", @@ -339,3 +339,6 @@ warn_required_dynamic_aliases = true [tool.ruff.lint.pep8-naming] classmethod-decorators = ["classmethod", "pydantic.field_validator"] + +[tool.pytest.ini_options] +asyncio_mode = "auto" diff --git a/scripts/unit-tests.sh b/scripts/unit-tests.sh index 1fc3ff7fc..68d6458fc 100755 --- a/scripts/unit-tests.sh +++ b/scripts/unit-tests.sh @@ -16,4 +16,4 @@ if [ $FOUND_PYTHON -ne 0 ]; then uv python install "$PYTHON_VERSION" fi -uv run --python "$PYTHON_VERSION" --with-editable . --group unit pytest --asyncio-mode=auto -s -v tests/unit/ $@ +uv run --python "$PYTHON_VERSION" --with-editable . --group unit pytest -s -v tests/unit/ $@ diff --git a/tests/integration/agents/test_persistence.py b/tests/integration/agents/test_persistence.py index ef35c97a5..49d9d42d0 100644 --- a/tests/integration/agents/test_persistence.py +++ b/tests/integration/agents/test_persistence.py @@ -44,7 +44,6 @@ def common_params(inference_model): ) -@pytest.mark.asyncio @pytest.mark.skip(reason="This test needs to be migrated to api / client-sdk world") async def test_delete_agents_and_sessions(self, agents_stack, common_params): agents_impl = agents_stack.impls[Api.agents] @@ -73,7 +72,6 @@ async def test_delete_agents_and_sessions(self, agents_stack, common_params): assert agent_response is None -@pytest.mark.asyncio @pytest.mark.skip(reason="This test needs to be migrated to api / client-sdk world") async def test_get_agent_turns_and_steps(self, agents_stack, sample_messages, common_params): agents_impl = agents_stack.impls[Api.agents] diff --git a/tests/integration/inspect/test_inspect.py b/tests/integration/inspect/test_inspect.py index da704178d..1597a319b 100644 --- a/tests/integration/inspect/test_inspect.py +++ b/tests/integration/inspect/test_inspect.py @@ -4,20 +4,17 @@ # This source code is licensed under the terms described in the LICENSE file in # the root directory of this source tree. -import pytest from llama_stack_client import LlamaStackClient from llama_stack import LlamaStackAsLibraryClient class TestInspect: - @pytest.mark.asyncio def test_health(self, llama_stack_client: LlamaStackAsLibraryClient | LlamaStackClient): health = llama_stack_client.inspect.health() assert health is not None assert health.status == "OK" - @pytest.mark.asyncio def test_version(self, llama_stack_client: LlamaStackAsLibraryClient | LlamaStackClient): version = llama_stack_client.inspect.version() assert version is not None diff --git a/tests/integration/providers/test_providers.py b/tests/integration/providers/test_providers.py index 8b153411c..fc65e2a10 100644 --- a/tests/integration/providers/test_providers.py +++ b/tests/integration/providers/test_providers.py @@ -4,14 +4,12 @@ # This source code is licensed under the terms described in the LICENSE file in # the root directory of this source tree. -import pytest from llama_stack_client import LlamaStackClient from llama_stack import LlamaStackAsLibraryClient class TestProviders: - @pytest.mark.asyncio def test_providers(self, llama_stack_client: LlamaStackAsLibraryClient | LlamaStackClient): provider_list = llama_stack_client.providers.list() assert provider_list is not None diff --git a/tests/integration/providers/utils/sqlstore/test_authorized_sqlstore.py b/tests/integration/providers/utils/sqlstore/test_authorized_sqlstore.py index bf6077532..c32d6cd17 100644 --- a/tests/integration/providers/utils/sqlstore/test_authorized_sqlstore.py +++ b/tests/integration/providers/utils/sqlstore/test_authorized_sqlstore.py @@ -88,7 +88,6 @@ async def cleanup_records(sql_store, table_name, record_ids): pass -@pytest.mark.asyncio @pytest.mark.parametrize("backend_config", BACKEND_CONFIGS) @patch("llama_stack.providers.utils.sqlstore.authorized_sqlstore.get_authenticated_user") async def test_authorized_store_attributes(mock_get_authenticated_user, authorized_store, request): @@ -183,7 +182,6 @@ async def test_authorized_store_attributes(mock_get_authenticated_user, authoriz await cleanup_records(authorized_store.sql_store, table_name, ["1", "2", "3", "4", "5", "6"]) -@pytest.mark.asyncio @pytest.mark.parametrize("backend_config", BACKEND_CONFIGS) @patch("llama_stack.providers.utils.sqlstore.authorized_sqlstore.get_authenticated_user") async def test_user_ownership_policy(mock_get_authenticated_user, authorized_store, request): diff --git a/tests/unit/distribution/routers/test_routing_tables.py b/tests/unit/distribution/routers/test_routing_tables.py index 0eeb68167..3ba042bd9 100644 --- a/tests/unit/distribution/routers/test_routing_tables.py +++ b/tests/unit/distribution/routers/test_routing_tables.py @@ -8,8 +8,6 @@ from unittest.mock import AsyncMock -import pytest - from llama_stack.apis.common.type_system import NumberType from llama_stack.apis.datasets.datasets import Dataset, DatasetPurpose, URIDataSource from llama_stack.apis.datatypes import Api @@ -119,7 +117,6 @@ class ToolGroupsImpl(Impl): ) -@pytest.mark.asyncio async def test_models_routing_table(cached_disk_dist_registry): table = ModelsRoutingTable({"test_provider": InferenceImpl()}, cached_disk_dist_registry, {}) await table.initialize() @@ -161,7 +158,6 @@ async def test_models_routing_table(cached_disk_dist_registry): assert len(openai_models.data) == 0 -@pytest.mark.asyncio async def test_shields_routing_table(cached_disk_dist_registry): table = ShieldsRoutingTable({"test_provider": SafetyImpl()}, cached_disk_dist_registry, {}) await table.initialize() @@ -177,7 +173,6 @@ async def test_shields_routing_table(cached_disk_dist_registry): assert "test-shield-2" in shield_ids -@pytest.mark.asyncio async def test_vectordbs_routing_table(cached_disk_dist_registry): table = VectorDBsRoutingTable({"test_provider": VectorDBImpl()}, cached_disk_dist_registry, {}) await table.initialize() @@ -233,7 +228,6 @@ async def test_datasets_routing_table(cached_disk_dist_registry): assert len(datasets.data) == 0 -@pytest.mark.asyncio async def test_scoring_functions_routing_table(cached_disk_dist_registry): table = ScoringFunctionsRoutingTable({"test_provider": ScoringFunctionsImpl()}, cached_disk_dist_registry, {}) await table.initialize() @@ -259,7 +253,6 @@ async def test_scoring_functions_routing_table(cached_disk_dist_registry): assert "test-scoring-fn-2" in scoring_fn_ids -@pytest.mark.asyncio async def test_benchmarks_routing_table(cached_disk_dist_registry): table = BenchmarksRoutingTable({"test_provider": BenchmarksImpl()}, cached_disk_dist_registry, {}) await table.initialize() @@ -277,7 +270,6 @@ async def test_benchmarks_routing_table(cached_disk_dist_registry): assert "test-benchmark" in benchmark_ids -@pytest.mark.asyncio async def test_tool_groups_routing_table(cached_disk_dist_registry): table = ToolGroupsRoutingTable({"test_provider": ToolGroupsImpl()}, cached_disk_dist_registry, {}) await table.initialize() diff --git a/tests/unit/distribution/test_context.py b/tests/unit/distribution/test_context.py index 84944bfe8..7914be51d 100644 --- a/tests/unit/distribution/test_context.py +++ b/tests/unit/distribution/test_context.py @@ -13,7 +13,6 @@ import pytest from llama_stack.distribution.utils.context import preserve_contexts_async_generator -@pytest.mark.asyncio async def test_preserve_contexts_with_exception(): # Create context variable context_var = ContextVar("exception_var", default="initial") @@ -41,7 +40,6 @@ async def test_preserve_contexts_with_exception(): context_var.reset(token) -@pytest.mark.asyncio async def test_preserve_contexts_empty_generator(): # Create context variable context_var = ContextVar("empty_var", default="initial") @@ -66,7 +64,6 @@ async def test_preserve_contexts_empty_generator(): context_var.reset(token) -@pytest.mark.asyncio async def test_preserve_contexts_across_event_loops(): """ Test that context variables are preserved across event loop boundaries with nested generators. diff --git a/tests/unit/files/test_files.py b/tests/unit/files/test_files.py index ef1dc9743..785077e91 100644 --- a/tests/unit/files/test_files.py +++ b/tests/unit/files/test_files.py @@ -6,7 +6,6 @@ import pytest -import pytest_asyncio from llama_stack.apis.common.responses import Order from llama_stack.apis.files import OpenAIFilePurpose @@ -29,7 +28,7 @@ class MockUploadFile: return self.content -@pytest_asyncio.fixture +@pytest.fixture async def files_provider(tmp_path): """Create a files provider with temporary storage for testing.""" storage_dir = tmp_path / "files" @@ -68,7 +67,6 @@ def large_file(): class TestOpenAIFilesAPI: """Test suite for OpenAI Files API endpoints.""" - @pytest.mark.asyncio async def test_upload_file_success(self, files_provider, sample_text_file): """Test successful file upload.""" # Upload file @@ -82,7 +80,6 @@ class TestOpenAIFilesAPI: assert result.created_at > 0 assert result.expires_at > result.created_at - @pytest.mark.asyncio async def test_upload_different_purposes(self, files_provider, sample_text_file): """Test uploading files with different purposes.""" purposes = list(OpenAIFilePurpose) @@ -93,7 +90,6 @@ class TestOpenAIFilesAPI: uploaded_files.append(result) assert result.purpose == purpose - @pytest.mark.asyncio async def test_upload_different_file_types(self, files_provider, sample_text_file, sample_json_file, large_file): """Test uploading different types and sizes of files.""" files_to_test = [ @@ -107,7 +103,6 @@ class TestOpenAIFilesAPI: assert result.filename == expected_filename assert result.bytes == len(file_obj.content) - @pytest.mark.asyncio async def test_list_files_empty(self, files_provider): """Test listing files when no files exist.""" result = await files_provider.openai_list_files() @@ -117,7 +112,6 @@ class TestOpenAIFilesAPI: assert result.first_id == "" assert result.last_id == "" - @pytest.mark.asyncio async def test_list_files_with_content(self, files_provider, sample_text_file, sample_json_file): """Test listing files when files exist.""" # Upload multiple files @@ -132,7 +126,6 @@ class TestOpenAIFilesAPI: assert file1.id in file_ids assert file2.id in file_ids - @pytest.mark.asyncio async def test_list_files_with_purpose_filter(self, files_provider, sample_text_file): """Test listing files with purpose filtering.""" # Upload file with specific purpose @@ -146,7 +139,6 @@ class TestOpenAIFilesAPI: assert result.data[0].id == uploaded_file.id assert result.data[0].purpose == OpenAIFilePurpose.ASSISTANTS - @pytest.mark.asyncio async def test_list_files_with_limit(self, files_provider, sample_text_file): """Test listing files with limit parameter.""" # Upload multiple files @@ -157,7 +149,6 @@ class TestOpenAIFilesAPI: result = await files_provider.openai_list_files(limit=3) assert len(result.data) == 3 - @pytest.mark.asyncio async def test_list_files_with_order(self, files_provider, sample_text_file): """Test listing files with different order.""" # Upload multiple files @@ -178,7 +169,6 @@ class TestOpenAIFilesAPI: # Oldest should be first assert result_asc.data[0].created_at <= result_asc.data[1].created_at <= result_asc.data[2].created_at - @pytest.mark.asyncio async def test_retrieve_file_success(self, files_provider, sample_text_file): """Test successful file retrieval.""" # Upload file @@ -197,13 +187,11 @@ class TestOpenAIFilesAPI: assert retrieved_file.created_at == uploaded_file.created_at assert retrieved_file.expires_at == uploaded_file.expires_at - @pytest.mark.asyncio async def test_retrieve_file_not_found(self, files_provider): """Test retrieving a non-existent file.""" with pytest.raises(ValueError, match="File with id file-nonexistent not found"): await files_provider.openai_retrieve_file("file-nonexistent") - @pytest.mark.asyncio async def test_retrieve_file_content_success(self, files_provider, sample_text_file): """Test successful file content retrieval.""" # Upload file @@ -217,13 +205,11 @@ class TestOpenAIFilesAPI: # Verify content assert content.body == sample_text_file.content - @pytest.mark.asyncio async def test_retrieve_file_content_not_found(self, files_provider): """Test retrieving content of a non-existent file.""" with pytest.raises(ValueError, match="File with id file-nonexistent not found"): await files_provider.openai_retrieve_file_content("file-nonexistent") - @pytest.mark.asyncio async def test_delete_file_success(self, files_provider, sample_text_file): """Test successful file deletion.""" # Upload file @@ -245,13 +231,11 @@ class TestOpenAIFilesAPI: with pytest.raises(ValueError, match=f"File with id {uploaded_file.id} not found"): await files_provider.openai_retrieve_file(uploaded_file.id) - @pytest.mark.asyncio async def test_delete_file_not_found(self, files_provider): """Test deleting a non-existent file.""" with pytest.raises(ValueError, match="File with id file-nonexistent not found"): await files_provider.openai_delete_file("file-nonexistent") - @pytest.mark.asyncio async def test_file_persistence_across_operations(self, files_provider, sample_text_file): """Test that files persist correctly across multiple operations.""" # Upload file @@ -279,7 +263,6 @@ class TestOpenAIFilesAPI: files_list = await files_provider.openai_list_files() assert len(files_list.data) == 0 - @pytest.mark.asyncio async def test_multiple_files_operations(self, files_provider, sample_text_file, sample_json_file): """Test operations with multiple files.""" # Upload multiple files @@ -302,7 +285,6 @@ class TestOpenAIFilesAPI: content = await files_provider.openai_retrieve_file_content(file2.id) assert content.body == sample_json_file.content - @pytest.mark.asyncio async def test_file_id_uniqueness(self, files_provider, sample_text_file): """Test that each uploaded file gets a unique ID.""" file_ids = set() @@ -316,7 +298,6 @@ class TestOpenAIFilesAPI: file_ids.add(uploaded_file.id) assert uploaded_file.id.startswith("file-") - @pytest.mark.asyncio async def test_file_no_filename_handling(self, files_provider): """Test handling files with no filename.""" file_without_name = MockUploadFile(b"content", None) # No filename @@ -327,7 +308,6 @@ class TestOpenAIFilesAPI: assert uploaded_file.filename == "uploaded_file" # Default filename - @pytest.mark.asyncio async def test_after_pagination_works(self, files_provider, sample_text_file): """Test that 'after' pagination works correctly.""" # Upload multiple files to test pagination diff --git a/tests/unit/fixtures.py b/tests/unit/fixtures.py index 4e50c5e08..7174d2e78 100644 --- a/tests/unit/fixtures.py +++ b/tests/unit/fixtures.py @@ -4,14 +4,14 @@ # This source code is licensed under the terms described in the LICENSE file in # the root directory of this source tree. -import pytest_asyncio +import pytest from llama_stack.distribution.store.registry import CachedDiskDistributionRegistry, DiskDistributionRegistry from llama_stack.providers.utils.kvstore.config import SqliteKVStoreConfig from llama_stack.providers.utils.kvstore.sqlite import SqliteKVStoreImpl -@pytest_asyncio.fixture(scope="function") +@pytest.fixture(scope="function") async def sqlite_kvstore(tmp_path): db_path = tmp_path / "test_kv.db" kvstore_config = SqliteKVStoreConfig(db_path=db_path.as_posix()) @@ -20,14 +20,14 @@ async def sqlite_kvstore(tmp_path): yield kvstore -@pytest_asyncio.fixture(scope="function") +@pytest.fixture(scope="function") async def disk_dist_registry(sqlite_kvstore): registry = DiskDistributionRegistry(sqlite_kvstore) await registry.initialize() yield registry -@pytest_asyncio.fixture(scope="function") +@pytest.fixture(scope="function") async def cached_disk_dist_registry(sqlite_kvstore): registry = CachedDiskDistributionRegistry(sqlite_kvstore) await registry.initialize() diff --git a/tests/unit/providers/agent/test_meta_reference_agent.py b/tests/unit/providers/agent/test_meta_reference_agent.py index 7a7d52892..c06d9ab0e 100644 --- a/tests/unit/providers/agent/test_meta_reference_agent.py +++ b/tests/unit/providers/agent/test_meta_reference_agent.py @@ -8,7 +8,6 @@ from datetime import datetime from unittest.mock import AsyncMock import pytest -import pytest_asyncio from llama_stack.apis.agents import ( Agent, @@ -50,7 +49,7 @@ def config(tmp_path): ) -@pytest_asyncio.fixture +@pytest.fixture async def agents_impl(config, mock_apis): impl = MetaReferenceAgentsImpl( config, @@ -117,7 +116,6 @@ def sample_agent_config(): ) -@pytest.mark.asyncio async def test_create_agent(agents_impl, sample_agent_config): response = await agents_impl.create_agent(sample_agent_config) @@ -132,7 +130,6 @@ async def test_create_agent(agents_impl, sample_agent_config): assert isinstance(agent_info.created_at, datetime) -@pytest.mark.asyncio async def test_get_agent(agents_impl, sample_agent_config): create_response = await agents_impl.create_agent(sample_agent_config) agent_id = create_response.agent_id @@ -146,7 +143,6 @@ async def test_get_agent(agents_impl, sample_agent_config): assert isinstance(agent.created_at, datetime) -@pytest.mark.asyncio async def test_list_agents(agents_impl, sample_agent_config): agent1_response = await agents_impl.create_agent(sample_agent_config) agent2_response = await agents_impl.create_agent(sample_agent_config) @@ -160,7 +156,6 @@ async def test_list_agents(agents_impl, sample_agent_config): assert agent2_response.agent_id in agent_ids -@pytest.mark.asyncio @pytest.mark.parametrize("enable_session_persistence", [True, False]) async def test_create_agent_session_persistence(agents_impl, sample_agent_config, enable_session_persistence): # Create an agent with specified persistence setting @@ -188,7 +183,6 @@ async def test_create_agent_session_persistence(agents_impl, sample_agent_config await agents_impl.get_agents_session(agent_id, session_response.session_id) -@pytest.mark.asyncio @pytest.mark.parametrize("enable_session_persistence", [True, False]) async def test_list_agent_sessions_persistence(agents_impl, sample_agent_config, enable_session_persistence): # Create an agent with specified persistence setting @@ -221,7 +215,6 @@ async def test_list_agent_sessions_persistence(agents_impl, sample_agent_config, assert session2.session_id in {s["session_id"] for s in sessions.data} -@pytest.mark.asyncio async def test_delete_agent(agents_impl, sample_agent_config): # Create an agent response = await agents_impl.create_agent(sample_agent_config) diff --git a/tests/unit/providers/agents/meta_reference/test_openai_responses.py b/tests/unit/providers/agents/meta_reference/test_openai_responses.py index 0d1ef8eca..6485e3512 100644 --- a/tests/unit/providers/agents/meta_reference/test_openai_responses.py +++ b/tests/unit/providers/agents/meta_reference/test_openai_responses.py @@ -122,7 +122,6 @@ async def fake_stream(fixture: str = "simple_chat_completion.yaml"): ) -@pytest.mark.asyncio async def test_create_openai_response_with_string_input(openai_responses_impl, mock_inference_api): """Test creating an OpenAI response with a simple string input.""" # Setup @@ -155,7 +154,6 @@ async def test_create_openai_response_with_string_input(openai_responses_impl, m assert result.output[0].content[0].text == "Dublin" -@pytest.mark.asyncio async def test_create_openai_response_with_string_input_with_tools(openai_responses_impl, mock_inference_api): """Test creating an OpenAI response with a simple string input and tools.""" # Setup @@ -224,7 +222,6 @@ async def test_create_openai_response_with_string_input_with_tools(openai_respon assert result.output[1].content[0].annotations == [] -@pytest.mark.asyncio async def test_create_openai_response_with_tool_call_type_none(openai_responses_impl, mock_inference_api): """Test creating an OpenAI response with a tool call response that has a type of None.""" # Setup @@ -294,7 +291,6 @@ async def test_create_openai_response_with_tool_call_type_none(openai_responses_ assert chunks[1].response.output[0].name == "get_weather" -@pytest.mark.asyncio async def test_create_openai_response_with_multiple_messages(openai_responses_impl, mock_inference_api): """Test creating an OpenAI response with multiple messages.""" # Setup @@ -340,7 +336,6 @@ async def test_create_openai_response_with_multiple_messages(openai_responses_im assert isinstance(inference_messages[i], OpenAIDeveloperMessageParam) -@pytest.mark.asyncio async def test_prepend_previous_response_none(openai_responses_impl): """Test prepending no previous response to a new response.""" @@ -348,7 +343,6 @@ async def test_prepend_previous_response_none(openai_responses_impl): assert input == "fake_input" -@pytest.mark.asyncio async def test_prepend_previous_response_basic(openai_responses_impl, mock_responses_store): """Test prepending a basic previous response to a new response.""" @@ -388,7 +382,6 @@ async def test_prepend_previous_response_basic(openai_responses_impl, mock_respo assert input[2].content == "fake_input" -@pytest.mark.asyncio async def test_prepend_previous_response_web_search(openai_responses_impl, mock_responses_store): """Test prepending a web search previous response to a new response.""" input_item_message = OpenAIResponseMessage( @@ -434,7 +427,6 @@ async def test_prepend_previous_response_web_search(openai_responses_impl, mock_ assert input[3].content == "fake_input" -@pytest.mark.asyncio async def test_create_openai_response_with_instructions(openai_responses_impl, mock_inference_api): # Setup input_text = "What is the capital of Ireland?" @@ -463,7 +455,6 @@ async def test_create_openai_response_with_instructions(openai_responses_impl, m assert sent_messages[1].content == input_text -@pytest.mark.asyncio async def test_create_openai_response_with_instructions_and_multiple_messages( openai_responses_impl, mock_inference_api ): @@ -508,7 +499,6 @@ async def test_create_openai_response_with_instructions_and_multiple_messages( assert sent_messages[3].content == "Which is the largest?" -@pytest.mark.asyncio async def test_create_openai_response_with_instructions_and_previous_response( openai_responses_impl, mock_responses_store, mock_inference_api ): @@ -565,7 +555,6 @@ async def test_create_openai_response_with_instructions_and_previous_response( assert sent_messages[3].content == "Which is the largest?" -@pytest.mark.asyncio async def test_list_openai_response_input_items_delegation(openai_responses_impl, mock_responses_store): """Test that list_openai_response_input_items properly delegates to responses_store with correct parameters.""" # Setup @@ -601,7 +590,6 @@ async def test_list_openai_response_input_items_delegation(openai_responses_impl assert result.data[0].id == "msg_123" -@pytest.mark.asyncio async def test_responses_store_list_input_items_logic(): """Test ResponsesStore list_response_input_items logic - mocks get_response_object to test actual ordering/limiting.""" @@ -680,7 +668,6 @@ async def test_responses_store_list_input_items_logic(): assert len(result.data) == 0 # Should return no items -@pytest.mark.asyncio async def test_store_response_uses_rehydrated_input_with_previous_response( openai_responses_impl, mock_responses_store, mock_inference_api ): @@ -747,7 +734,6 @@ async def test_store_response_uses_rehydrated_input_with_previous_response( assert result.status == "completed" -@pytest.mark.asyncio @pytest.mark.parametrize( "text_format, response_format", [ @@ -787,7 +773,6 @@ async def test_create_openai_response_with_text_format( assert first_call.kwargs["response_format"] == response_format -@pytest.mark.asyncio async def test_create_openai_response_with_invalid_text_format(openai_responses_impl, mock_inference_api): """Test creating an OpenAI response with an invalid text format.""" # Setup diff --git a/tests/unit/providers/agents/test_persistence_access_control.py b/tests/unit/providers/agents/test_persistence_access_control.py index 656d1e53c..26001fcf1 100644 --- a/tests/unit/providers/agents/test_persistence_access_control.py +++ b/tests/unit/providers/agents/test_persistence_access_control.py @@ -9,7 +9,6 @@ from datetime import datetime from unittest.mock import patch import pytest -import pytest_asyncio from llama_stack.apis.agents import Turn from llama_stack.apis.inference import CompletionMessage, StopReason @@ -17,13 +16,12 @@ from llama_stack.distribution.datatypes import User from llama_stack.providers.inline.agents.meta_reference.persistence import AgentPersistence, AgentSessionInfo -@pytest_asyncio.fixture +@pytest.fixture async def test_setup(sqlite_kvstore): agent_persistence = AgentPersistence(agent_id="test_agent", kvstore=sqlite_kvstore, policy={}) yield agent_persistence -@pytest.mark.asyncio @patch("llama_stack.providers.inline.agents.meta_reference.persistence.get_authenticated_user") async def test_session_creation_with_access_attributes(mock_get_authenticated_user, test_setup): agent_persistence = test_setup @@ -44,7 +42,6 @@ async def test_session_creation_with_access_attributes(mock_get_authenticated_us assert session_info.owner.attributes["teams"] == ["ai-team"] -@pytest.mark.asyncio @patch("llama_stack.providers.inline.agents.meta_reference.persistence.get_authenticated_user") async def test_session_access_control(mock_get_authenticated_user, test_setup): agent_persistence = test_setup @@ -79,7 +76,6 @@ async def test_session_access_control(mock_get_authenticated_user, test_setup): assert retrieved_session is None -@pytest.mark.asyncio @patch("llama_stack.providers.inline.agents.meta_reference.persistence.get_authenticated_user") async def test_turn_access_control(mock_get_authenticated_user, test_setup): agent_persistence = test_setup @@ -133,7 +129,6 @@ async def test_turn_access_control(mock_get_authenticated_user, test_setup): await agent_persistence.get_session_turns(session_id) -@pytest.mark.asyncio @patch("llama_stack.providers.inline.agents.meta_reference.persistence.get_authenticated_user") async def test_tool_call_and_infer_iters_access_control(mock_get_authenticated_user, test_setup): agent_persistence = test_setup diff --git a/tests/unit/providers/inference/test_remote_vllm.py b/tests/unit/providers/inference/test_remote_vllm.py index eaa9b40da..ca44cc95d 100644 --- a/tests/unit/providers/inference/test_remote_vllm.py +++ b/tests/unit/providers/inference/test_remote_vllm.py @@ -14,7 +14,6 @@ from typing import Any from unittest.mock import AsyncMock, MagicMock, patch import pytest -import pytest_asyncio from openai.types.chat.chat_completion_chunk import ( ChatCompletionChunk as OpenAIChatCompletionChunk, ) @@ -103,7 +102,7 @@ def mock_openai_models_list(): yield mock_list -@pytest_asyncio.fixture(scope="module") +@pytest.fixture(scope="module") async def vllm_inference_adapter(): config = VLLMInferenceAdapterConfig(url="http://mocked.localhost:12345") inference_adapter = VLLMInferenceAdapter(config) @@ -112,7 +111,6 @@ async def vllm_inference_adapter(): return inference_adapter -@pytest.mark.asyncio async def test_register_model_checks_vllm(mock_openai_models_list, vllm_inference_adapter): async def mock_openai_models(): yield OpenAIModel(id="foo", created=1, object="model", owned_by="test") @@ -125,7 +123,6 @@ async def test_register_model_checks_vllm(mock_openai_models_list, vllm_inferenc mock_openai_models_list.assert_called() -@pytest.mark.asyncio async def test_old_vllm_tool_choice(vllm_inference_adapter): """ Test that we set tool_choice to none when no tools are in use @@ -149,7 +146,6 @@ async def test_old_vllm_tool_choice(vllm_inference_adapter): assert request.tool_config.tool_choice == ToolChoice.none -@pytest.mark.asyncio async def test_tool_call_response(vllm_inference_adapter): """Verify that tool call arguments from a CompletionMessage are correctly converted into the expected JSON format.""" @@ -192,7 +188,6 @@ async def test_tool_call_response(vllm_inference_adapter): ] -@pytest.mark.asyncio async def test_tool_call_delta_empty_tool_call_buf(): """ Test that we don't generate extra chunks when processing a @@ -222,7 +217,6 @@ async def test_tool_call_delta_empty_tool_call_buf(): assert chunks[1].event.stop_reason == StopReason.end_of_turn -@pytest.mark.asyncio async def test_tool_call_delta_streaming_arguments_dict(): async def mock_stream(): mock_chunk_1 = OpenAIChatCompletionChunk( @@ -297,7 +291,6 @@ async def test_tool_call_delta_streaming_arguments_dict(): assert chunks[2].event.event_type.value == "complete" -@pytest.mark.asyncio async def test_multiple_tool_calls(): async def mock_stream(): mock_chunk_1 = OpenAIChatCompletionChunk( @@ -376,7 +369,6 @@ async def test_multiple_tool_calls(): assert chunks[3].event.event_type.value == "complete" -@pytest.mark.asyncio async def test_process_vllm_chat_completion_stream_response_no_choices(): """ Test that we don't error out when vLLM returns no choices for a @@ -453,7 +445,6 @@ def test_chat_completion_doesnt_block_event_loop(caplog): assert not asyncio_warnings -@pytest.mark.asyncio async def test_get_params_empty_tools(vllm_inference_adapter): request = ChatCompletionRequest( tools=[], @@ -464,7 +455,6 @@ async def test_get_params_empty_tools(vllm_inference_adapter): assert "tools" not in params -@pytest.mark.asyncio async def test_process_vllm_chat_completion_stream_response_tool_call_args_last_chunk(): """ Tests the edge case where the model returns the arguments for the tool call in the same chunk that @@ -543,7 +533,6 @@ async def test_process_vllm_chat_completion_stream_response_tool_call_args_last_ assert chunks[-2].event.delta.tool_call.arguments == mock_tool_arguments -@pytest.mark.asyncio async def test_process_vllm_chat_completion_stream_response_no_finish_reason(): """ Tests the edge case where the model requests a tool call and stays idle without explicitly providing the @@ -596,7 +585,6 @@ async def test_process_vllm_chat_completion_stream_response_no_finish_reason(): assert chunks[-2].event.delta.tool_call.arguments == mock_tool_arguments -@pytest.mark.asyncio async def test_process_vllm_chat_completion_stream_response_tool_without_args(): """ Tests the edge case where no arguments are provided for the tool call. @@ -645,7 +633,6 @@ async def test_process_vllm_chat_completion_stream_response_tool_without_args(): assert chunks[-2].event.delta.tool_call.arguments == {} -@pytest.mark.asyncio async def test_health_status_success(vllm_inference_adapter): """ Test the health method of VLLM InferenceAdapter when the connection is successful. @@ -679,7 +666,6 @@ async def test_health_status_success(vllm_inference_adapter): mock_models.list.assert_called_once() -@pytest.mark.asyncio async def test_health_status_failure(vllm_inference_adapter): """ Test the health method of VLLM InferenceAdapter when the connection fails. diff --git a/tests/unit/providers/utils/inference/test_openai_compat.py b/tests/unit/providers/utils/inference/test_openai_compat.py index 3598e4810..f57f6c9b3 100644 --- a/tests/unit/providers/utils/inference/test_openai_compat.py +++ b/tests/unit/providers/utils/inference/test_openai_compat.py @@ -4,7 +4,6 @@ # This source code is licensed under the terms described in the LICENSE file in # the root directory of this source tree. -import pytest from llama_stack.apis.common.content_types import TextContentItem from llama_stack.apis.inference import ( @@ -23,7 +22,6 @@ from llama_stack.providers.utils.inference.openai_compat import ( ) -@pytest.mark.asyncio async def test_convert_message_to_openai_dict(): message = UserMessage(content=[TextContentItem(text="Hello, world!")], role="user") assert await convert_message_to_openai_dict(message) == { @@ -33,7 +31,6 @@ async def test_convert_message_to_openai_dict(): # Test convert_message_to_openai_dict with a tool call -@pytest.mark.asyncio async def test_convert_message_to_openai_dict_with_tool_call(): message = CompletionMessage( content="", @@ -54,7 +51,6 @@ async def test_convert_message_to_openai_dict_with_tool_call(): } -@pytest.mark.asyncio async def test_convert_message_to_openai_dict_with_builtin_tool_call(): message = CompletionMessage( content="", @@ -80,7 +76,6 @@ async def test_convert_message_to_openai_dict_with_builtin_tool_call(): } -@pytest.mark.asyncio async def test_openai_messages_to_messages_with_content_str(): openai_messages = [ OpenAISystemMessageParam(content="system message"), @@ -98,7 +93,6 @@ async def test_openai_messages_to_messages_with_content_str(): assert llama_messages[2].content == "assistant message" -@pytest.mark.asyncio async def test_openai_messages_to_messages_with_content_list(): openai_messages = [ OpenAISystemMessageParam(content=[OpenAIChatCompletionContentPartTextParam(text="system message")]), diff --git a/tests/unit/providers/utils/memory/test_vector_store.py b/tests/unit/providers/utils/memory/test_vector_store.py index 220c21994..90b229262 100644 --- a/tests/unit/providers/utils/memory/test_vector_store.py +++ b/tests/unit/providers/utils/memory/test_vector_store.py @@ -13,7 +13,6 @@ from llama_stack.apis.tools import RAGDocument from llama_stack.providers.utils.memory.vector_store import content_from_data_and_mime_type, content_from_doc -@pytest.mark.asyncio async def test_content_from_doc_with_url(): """Test extracting content from RAGDocument with URL content.""" mock_url = URL(uri="https://example.com") @@ -33,7 +32,6 @@ async def test_content_from_doc_with_url(): mock_instance.get.assert_called_once_with(mock_url.uri) -@pytest.mark.asyncio async def test_content_from_doc_with_pdf_url(): """Test extracting content from RAGDocument with URL pointing to a PDF.""" mock_url = URL(uri="https://example.com/document.pdf") @@ -58,7 +56,6 @@ async def test_content_from_doc_with_pdf_url(): mock_parse_pdf.assert_called_once_with(b"PDF binary data") -@pytest.mark.asyncio async def test_content_from_doc_with_data_url(): """Test extracting content from RAGDocument with data URL content.""" data_url = "data:text/plain;base64,SGVsbG8gV29ybGQ=" # "Hello World" base64 encoded @@ -74,7 +71,6 @@ async def test_content_from_doc_with_data_url(): mock_content_from_data.assert_called_once_with(data_url) -@pytest.mark.asyncio async def test_content_from_doc_with_string(): """Test extracting content from RAGDocument with string content.""" content_string = "This is plain text content" @@ -85,7 +81,6 @@ async def test_content_from_doc_with_string(): assert result == content_string -@pytest.mark.asyncio async def test_content_from_doc_with_string_url(): """Test extracting content from RAGDocument with string URL content.""" url_string = "https://example.com" @@ -105,7 +100,6 @@ async def test_content_from_doc_with_string_url(): mock_instance.get.assert_called_once_with(url_string) -@pytest.mark.asyncio async def test_content_from_doc_with_string_pdf_url(): """Test extracting content from RAGDocument with string URL pointing to a PDF.""" url_string = "https://example.com/document.pdf" @@ -130,7 +124,6 @@ async def test_content_from_doc_with_string_pdf_url(): mock_parse_pdf.assert_called_once_with(b"PDF binary data") -@pytest.mark.asyncio async def test_content_from_doc_with_interleaved_content(): """Test extracting content from RAGDocument with InterleavedContent (the new case added in the commit).""" interleaved_content = [TextContentItem(text="First item"), TextContentItem(text="Second item")] diff --git a/tests/unit/providers/utils/test_model_registry.py b/tests/unit/providers/utils/test_model_registry.py index 10fa1e075..e11f95d49 100644 --- a/tests/unit/providers/utils/test_model_registry.py +++ b/tests/unit/providers/utils/test_model_registry.py @@ -87,18 +87,15 @@ def helper(known_provider_model: ProviderModelEntry, known_provider_model2: Prov return ModelRegistryHelper([known_provider_model, known_provider_model2]) -@pytest.mark.asyncio async def test_lookup_unknown_model(helper: ModelRegistryHelper, unknown_model: Model) -> None: assert helper.get_provider_model_id(unknown_model.model_id) is None -@pytest.mark.asyncio async def test_register_unknown_provider_model(helper: ModelRegistryHelper, unknown_model: Model) -> None: with pytest.raises(ValueError): await helper.register_model(unknown_model) -@pytest.mark.asyncio async def test_register_model(helper: ModelRegistryHelper, known_model: Model) -> None: model = Model( provider_id=known_model.provider_id, @@ -110,7 +107,6 @@ async def test_register_model(helper: ModelRegistryHelper, known_model: Model) - assert helper.get_provider_model_id(model.model_id) == model.provider_resource_id -@pytest.mark.asyncio async def test_register_model_from_alias(helper: ModelRegistryHelper, known_model: Model) -> None: model = Model( provider_id=known_model.provider_id, @@ -122,13 +118,11 @@ async def test_register_model_from_alias(helper: ModelRegistryHelper, known_mode assert helper.get_provider_model_id(model.model_id) == known_model.provider_resource_id -@pytest.mark.asyncio async def test_register_model_existing(helper: ModelRegistryHelper, known_model: Model) -> None: await helper.register_model(known_model) assert helper.get_provider_model_id(known_model.model_id) == known_model.provider_resource_id -@pytest.mark.asyncio async def test_register_model_existing_different( helper: ModelRegistryHelper, known_model: Model, known_model2: Model ) -> None: @@ -137,7 +131,6 @@ async def test_register_model_existing_different( await helper.register_model(known_model) -@pytest.mark.asyncio async def test_unregister_model(helper: ModelRegistryHelper, known_model: Model) -> None: await helper.register_model(known_model) # duplicate entry assert helper.get_provider_model_id(known_model.model_id) == known_model.provider_model_id @@ -145,18 +138,15 @@ async def test_unregister_model(helper: ModelRegistryHelper, known_model: Model) assert helper.get_provider_model_id(known_model.model_id) is None -@pytest.mark.asyncio async def test_unregister_unknown_model(helper: ModelRegistryHelper, unknown_model: Model) -> None: with pytest.raises(ValueError): await helper.unregister_model(unknown_model.model_id) -@pytest.mark.asyncio async def test_register_model_during_init(helper: ModelRegistryHelper, known_model: Model) -> None: assert helper.get_provider_model_id(known_model.provider_resource_id) == known_model.provider_model_id -@pytest.mark.asyncio async def test_unregister_model_during_init(helper: ModelRegistryHelper, known_model: Model) -> None: assert helper.get_provider_model_id(known_model.provider_resource_id) == known_model.provider_model_id await helper.unregister_model(known_model.provider_resource_id) diff --git a/tests/unit/providers/utils/test_scheduler.py b/tests/unit/providers/utils/test_scheduler.py index 25b4935de..e5ee74bfa 100644 --- a/tests/unit/providers/utils/test_scheduler.py +++ b/tests/unit/providers/utils/test_scheduler.py @@ -11,7 +11,6 @@ import pytest from llama_stack.providers.utils.scheduler import JobStatus, Scheduler -@pytest.mark.asyncio async def test_scheduler_unknown_backend(): with pytest.raises(ValueError): Scheduler(backend="unknown") @@ -26,7 +25,6 @@ async def wait_for_job_completed(sched: Scheduler, job_id: str) -> None: raise TimeoutError(f"Job {job_id} did not complete in time.") -@pytest.mark.asyncio async def test_scheduler_naive(): sched = Scheduler() @@ -87,7 +85,6 @@ async def test_scheduler_naive(): assert job.logs[0][0] < job.logs[1][0] -@pytest.mark.asyncio async def test_scheduler_naive_handler_raises(): sched = Scheduler() diff --git a/tests/unit/providers/vector_io/test_faiss.py b/tests/unit/providers/vector_io/test_faiss.py index 8348b84e3..90108d7a0 100644 --- a/tests/unit/providers/vector_io/test_faiss.py +++ b/tests/unit/providers/vector_io/test_faiss.py @@ -9,7 +9,6 @@ from unittest.mock import AsyncMock, MagicMock, patch import numpy as np import pytest -import pytest_asyncio from llama_stack.apis.files import Files from llama_stack.apis.inference import EmbeddingsResponse, Inference @@ -91,13 +90,13 @@ def faiss_config(): return config -@pytest_asyncio.fixture +@pytest.fixture async def faiss_index(embedding_dimension): index = await FaissIndex.create(dimension=embedding_dimension) yield index -@pytest_asyncio.fixture +@pytest.fixture async def faiss_adapter(faiss_config, mock_inference_api, mock_files_api) -> FaissVectorIOAdapter: # Create the adapter adapter = FaissVectorIOAdapter(config=faiss_config, inference_api=mock_inference_api, files_api=mock_files_api) @@ -113,7 +112,6 @@ async def faiss_adapter(faiss_config, mock_inference_api, mock_files_api) -> Fai yield adapter -@pytest.mark.asyncio async def test_faiss_query_vector_returns_infinity_when_query_and_embedding_are_identical( faiss_index, sample_chunks, sample_embeddings, embedding_dimension ): @@ -136,7 +134,6 @@ async def test_faiss_query_vector_returns_infinity_when_query_and_embedding_are_ assert response.chunks[1] == sample_chunks[1] -@pytest.mark.asyncio async def test_health_success(): """Test that the health check returns OK status when faiss is working correctly.""" # Create a fresh instance of FaissVectorIOAdapter for testing @@ -160,7 +157,6 @@ async def test_health_success(): mock_index_flat.assert_called_once_with(128) # VECTOR_DIMENSION is 128 -@pytest.mark.asyncio async def test_health_failure(): """Test that the health check returns ERROR status when faiss encounters an error.""" # Create a fresh instance of FaissVectorIOAdapter for testing diff --git a/tests/unit/providers/vector_io/test_qdrant.py b/tests/unit/providers/vector_io/test_qdrant.py index 6902c8850..d3ffe711c 100644 --- a/tests/unit/providers/vector_io/test_qdrant.py +++ b/tests/unit/providers/vector_io/test_qdrant.py @@ -10,7 +10,6 @@ from typing import Any from unittest.mock import AsyncMock, MagicMock, patch import pytest -import pytest_asyncio from llama_stack.apis.inference import EmbeddingsResponse, Inference from llama_stack.apis.vector_io import ( @@ -68,7 +67,7 @@ def mock_api_service(sample_embeddings): return mock_api_service -@pytest_asyncio.fixture +@pytest.fixture async def qdrant_adapter(qdrant_config, mock_vector_db_store, mock_api_service, loop) -> QdrantVectorIOAdapter: adapter = QdrantVectorIOAdapter(config=qdrant_config, inference_api=mock_api_service) adapter.vector_db_store = mock_vector_db_store @@ -80,7 +79,6 @@ async def qdrant_adapter(qdrant_config, mock_vector_db_store, mock_api_service, __QUERY = "Sample query" -@pytest.mark.asyncio @pytest.mark.parametrize("max_query_chunks, expected_chunks", [(2, 2), (100, 60)]) async def test_qdrant_adapter_returns_expected_chunks( qdrant_adapter: QdrantVectorIOAdapter, @@ -111,7 +109,6 @@ def _prepare_for_json(value: Any) -> str: @patch("llama_stack.providers.utils.telemetry.trace_protocol._prepare_for_json", new=_prepare_for_json) -@pytest.mark.asyncio async def test_qdrant_register_and_unregister_vector_db( qdrant_adapter: QdrantVectorIOAdapter, mock_vector_db, diff --git a/tests/unit/providers/vector_io/test_sqlite_vec.py b/tests/unit/providers/vector_io/test_sqlite_vec.py index 8579c31bb..a61eeeeca 100644 --- a/tests/unit/providers/vector_io/test_sqlite_vec.py +++ b/tests/unit/providers/vector_io/test_sqlite_vec.py @@ -8,7 +8,6 @@ import asyncio import numpy as np import pytest -import pytest_asyncio from llama_stack.apis.vector_io import Chunk, QueryChunksResponse from llama_stack.providers.inline.vector_io.sqlite_vec.sqlite_vec import ( @@ -34,7 +33,7 @@ def loop(): return asyncio.new_event_loop() -@pytest_asyncio.fixture +@pytest.fixture async def sqlite_vec_index(embedding_dimension, tmp_path_factory): temp_dir = tmp_path_factory.getbasetemp() db_path = str(temp_dir / "test_sqlite.db") @@ -43,14 +42,12 @@ async def sqlite_vec_index(embedding_dimension, tmp_path_factory): await index.delete() -@pytest.mark.asyncio async def test_query_chunk_metadata(sqlite_vec_index, sample_chunks_with_metadata, sample_embeddings_with_metadata): await sqlite_vec_index.add_chunks(sample_chunks_with_metadata, sample_embeddings_with_metadata) response = await sqlite_vec_index.query_vector(sample_embeddings_with_metadata[-1], k=2, score_threshold=0.0) assert response.chunks[0].chunk_metadata == sample_chunks_with_metadata[-1].chunk_metadata -@pytest.mark.asyncio async def test_query_chunks_full_text_search(sqlite_vec_index, sample_chunks, sample_embeddings): await sqlite_vec_index.add_chunks(sample_chunks, sample_embeddings) query_string = "Sentence 5" @@ -68,7 +65,6 @@ async def test_query_chunks_full_text_search(sqlite_vec_index, sample_chunks, sa assert len(response_no_results.chunks) == 0, f"Expected 0 results, but got {len(response_no_results.chunks)}" -@pytest.mark.asyncio async def test_query_chunks_hybrid(sqlite_vec_index, sample_chunks, sample_embeddings): await sqlite_vec_index.add_chunks(sample_chunks, sample_embeddings) @@ -90,7 +86,6 @@ async def test_query_chunks_hybrid(sqlite_vec_index, sample_chunks, sample_embed assert all(response.scores[i] >= response.scores[i + 1] for i in range(len(response.scores) - 1)) -@pytest.mark.asyncio async def test_query_chunks_full_text_search_k_greater_than_results(sqlite_vec_index, sample_chunks, sample_embeddings): # Re-initialize with a clean index await sqlite_vec_index.add_chunks(sample_chunks, sample_embeddings) @@ -103,7 +98,6 @@ async def test_query_chunks_full_text_search_k_greater_than_results(sqlite_vec_i assert any("Sentence 1 from document 0" in chunk.content for chunk in response.chunks), "Expected chunk not found" -@pytest.mark.asyncio async def test_chunk_id_conflict(sqlite_vec_index, sample_chunks, embedding_dimension): """Test that chunk IDs do not conflict across batches when inserting chunks.""" # Reduce batch size to force multiple batches for same document @@ -134,7 +128,6 @@ async def sqlite_vec_adapter(sqlite_connection): await adapter.shutdown() -@pytest.mark.asyncio async def test_query_chunks_hybrid_no_keyword_matches(sqlite_vec_index, sample_chunks, sample_embeddings): """Test hybrid search when keyword search returns no matches - should still return vector results.""" await sqlite_vec_index.add_chunks(sample_chunks, sample_embeddings) @@ -163,7 +156,6 @@ async def test_query_chunks_hybrid_no_keyword_matches(sqlite_vec_index, sample_c assert all(response.scores[i] >= response.scores[i + 1] for i in range(len(response.scores) - 1)) -@pytest.mark.asyncio async def test_query_chunks_hybrid_score_threshold(sqlite_vec_index, sample_chunks, sample_embeddings): """Test hybrid search with a high score threshold.""" await sqlite_vec_index.add_chunks(sample_chunks, sample_embeddings) @@ -185,7 +177,6 @@ async def test_query_chunks_hybrid_score_threshold(sqlite_vec_index, sample_chun assert len(response.chunks) == 0 -@pytest.mark.asyncio async def test_query_chunks_hybrid_different_embedding( sqlite_vec_index, sample_chunks, sample_embeddings, embedding_dimension ): @@ -211,7 +202,6 @@ async def test_query_chunks_hybrid_different_embedding( assert all(response.scores[i] >= response.scores[i + 1] for i in range(len(response.scores) - 1)) -@pytest.mark.asyncio async def test_query_chunks_hybrid_rrf_ranking(sqlite_vec_index, sample_chunks, sample_embeddings): """Test that RRF properly combines rankings when documents appear in both search methods.""" await sqlite_vec_index.add_chunks(sample_chunks, sample_embeddings) @@ -236,7 +226,6 @@ async def test_query_chunks_hybrid_rrf_ranking(sqlite_vec_index, sample_chunks, assert all(response.scores[i] >= response.scores[i + 1] for i in range(len(response.scores) - 1)) -@pytest.mark.asyncio async def test_query_chunks_hybrid_score_selection(sqlite_vec_index, sample_chunks, sample_embeddings): await sqlite_vec_index.add_chunks(sample_chunks, sample_embeddings) @@ -284,7 +273,6 @@ async def test_query_chunks_hybrid_score_selection(sqlite_vec_index, sample_chun assert response.scores[0] == pytest.approx(2.0 / 61.0, rel=1e-6) # Should behave like RRF -@pytest.mark.asyncio async def test_query_chunks_hybrid_mixed_results(sqlite_vec_index, sample_chunks, sample_embeddings): """Test hybrid search with documents that appear in only one search method.""" await sqlite_vec_index.add_chunks(sample_chunks, sample_embeddings) @@ -313,7 +301,6 @@ async def test_query_chunks_hybrid_mixed_results(sqlite_vec_index, sample_chunks assert "document-2" in doc_ids # From keyword search -@pytest.mark.asyncio async def test_query_chunks_hybrid_weighted_reranker_parametrization( sqlite_vec_index, sample_chunks, sample_embeddings ): @@ -369,7 +356,6 @@ async def test_query_chunks_hybrid_weighted_reranker_parametrization( ) -@pytest.mark.asyncio async def test_query_chunks_hybrid_rrf_impact_factor(sqlite_vec_index, sample_chunks, sample_embeddings): """Test RRFReRanker with different impact factors.""" await sqlite_vec_index.add_chunks(sample_chunks, sample_embeddings) @@ -401,7 +387,6 @@ async def test_query_chunks_hybrid_rrf_impact_factor(sqlite_vec_index, sample_ch assert response.scores[0] == pytest.approx(2.0 / 101.0, rel=1e-6) -@pytest.mark.asyncio async def test_query_chunks_hybrid_edge_cases(sqlite_vec_index, sample_chunks, sample_embeddings): await sqlite_vec_index.add_chunks(sample_chunks, sample_embeddings) @@ -445,7 +430,6 @@ async def test_query_chunks_hybrid_edge_cases(sqlite_vec_index, sample_chunks, s assert len(response.chunks) <= 100 -@pytest.mark.asyncio async def test_query_chunks_hybrid_tie_breaking( sqlite_vec_index, sample_embeddings, embedding_dimension, tmp_path_factory ): diff --git a/tests/unit/providers/vector_io/test_vector_io_openai_vector_stores.py b/tests/unit/providers/vector_io/test_vector_io_openai_vector_stores.py index 5f7926ce6..97e2f085e 100644 --- a/tests/unit/providers/vector_io/test_vector_io_openai_vector_stores.py +++ b/tests/unit/providers/vector_io/test_vector_io_openai_vector_stores.py @@ -25,12 +25,10 @@ from llama_stack.providers.remote.vector_io.milvus.milvus import VECTOR_DBS_PREF # -v -s --tb=short --disable-warnings --asyncio-mode=auto -@pytest.mark.asyncio async def test_initialize_index(vector_index): await vector_index.initialize() -@pytest.mark.asyncio async def test_add_chunks_query_vector(vector_index, sample_chunks, sample_embeddings): vector_index.delete() vector_index.initialize() @@ -40,7 +38,6 @@ async def test_add_chunks_query_vector(vector_index, sample_chunks, sample_embed vector_index.delete() -@pytest.mark.asyncio async def test_chunk_id_conflict(vector_index, sample_chunks, embedding_dimension): embeddings = np.random.rand(len(sample_chunks), embedding_dimension).astype(np.float32) await vector_index.add_chunks(sample_chunks, embeddings) @@ -54,7 +51,6 @@ async def test_chunk_id_conflict(vector_index, sample_chunks, embedding_dimensio assert len(contents) == len(set(contents)) -@pytest.mark.asyncio async def test_initialize_adapter_with_existing_kvstore(vector_io_adapter): key = f"{VECTOR_DBS_PREFIX}db1" dummy = VectorDB( @@ -65,7 +61,6 @@ async def test_initialize_adapter_with_existing_kvstore(vector_io_adapter): await vector_io_adapter.initialize() -@pytest.mark.asyncio async def test_persistence_across_adapter_restarts(vector_io_adapter): await vector_io_adapter.initialize() dummy = VectorDB( @@ -79,7 +74,6 @@ async def test_persistence_across_adapter_restarts(vector_io_adapter): await vector_io_adapter.shutdown() -@pytest.mark.asyncio async def test_register_and_unregister_vector_db(vector_io_adapter): unique_id = f"foo_db_{np.random.randint(1e6)}" dummy = VectorDB( @@ -92,14 +86,12 @@ async def test_register_and_unregister_vector_db(vector_io_adapter): assert dummy.identifier not in vector_io_adapter.cache -@pytest.mark.asyncio async def test_query_unregistered_raises(vector_io_adapter): fake_emb = np.zeros(8, dtype=np.float32) with pytest.raises(ValueError): await vector_io_adapter.query_chunks("no_such_db", fake_emb) -@pytest.mark.asyncio async def test_insert_chunks_calls_underlying_index(vector_io_adapter): fake_index = AsyncMock() vector_io_adapter._get_and_cache_vector_db_index = AsyncMock(return_value=fake_index) @@ -110,7 +102,6 @@ async def test_insert_chunks_calls_underlying_index(vector_io_adapter): fake_index.insert_chunks.assert_awaited_once_with(chunks) -@pytest.mark.asyncio async def test_insert_chunks_missing_db_raises(vector_io_adapter): vector_io_adapter._get_and_cache_vector_db_index = AsyncMock(return_value=None) @@ -118,7 +109,6 @@ async def test_insert_chunks_missing_db_raises(vector_io_adapter): await vector_io_adapter.insert_chunks("db_not_exist", []) -@pytest.mark.asyncio async def test_query_chunks_calls_underlying_index_and_returns(vector_io_adapter): expected = QueryChunksResponse(chunks=[Chunk(content="c1")], scores=[0.1]) fake_index = AsyncMock(query_chunks=AsyncMock(return_value=expected)) @@ -130,7 +120,6 @@ async def test_query_chunks_calls_underlying_index_and_returns(vector_io_adapter assert response is expected -@pytest.mark.asyncio async def test_query_chunks_missing_db_raises(vector_io_adapter): vector_io_adapter._get_and_cache_vector_db_index = AsyncMock(return_value=None) @@ -138,7 +127,6 @@ async def test_query_chunks_missing_db_raises(vector_io_adapter): await vector_io_adapter.query_chunks("db_missing", "q", None) -@pytest.mark.asyncio async def test_save_openai_vector_store(vector_io_adapter): store_id = "vs_1234" openai_vector_store = { @@ -155,7 +143,6 @@ async def test_save_openai_vector_store(vector_io_adapter): assert vector_io_adapter.openai_vector_stores[openai_vector_store["id"]] == openai_vector_store -@pytest.mark.asyncio async def test_update_openai_vector_store(vector_io_adapter): store_id = "vs_1234" openai_vector_store = { @@ -172,7 +159,6 @@ async def test_update_openai_vector_store(vector_io_adapter): assert vector_io_adapter.openai_vector_stores[openai_vector_store["id"]] == openai_vector_store -@pytest.mark.asyncio async def test_delete_openai_vector_store(vector_io_adapter): store_id = "vs_1234" openai_vector_store = { @@ -188,7 +174,6 @@ async def test_delete_openai_vector_store(vector_io_adapter): assert openai_vector_store["id"] not in vector_io_adapter.openai_vector_stores -@pytest.mark.asyncio async def test_load_openai_vector_stores(vector_io_adapter): store_id = "vs_1234" openai_vector_store = { @@ -204,7 +189,6 @@ async def test_load_openai_vector_stores(vector_io_adapter): assert loaded_stores[store_id] == openai_vector_store -@pytest.mark.asyncio async def test_save_openai_vector_store_file(vector_io_adapter, tmp_path_factory): store_id = "vs_1234" file_id = "file_1234" @@ -226,7 +210,6 @@ async def test_save_openai_vector_store_file(vector_io_adapter, tmp_path_factory await vector_io_adapter._save_openai_vector_store_file(store_id, file_id, file_info, file_contents) -@pytest.mark.asyncio async def test_update_openai_vector_store_file(vector_io_adapter, tmp_path_factory): store_id = "vs_1234" file_id = "file_1234" @@ -260,7 +243,6 @@ async def test_update_openai_vector_store_file(vector_io_adapter, tmp_path_facto assert loaded_contents != file_info -@pytest.mark.asyncio async def test_load_openai_vector_store_file_contents(vector_io_adapter, tmp_path_factory): store_id = "vs_1234" file_id = "file_1234" @@ -284,7 +266,6 @@ async def test_load_openai_vector_store_file_contents(vector_io_adapter, tmp_pat assert loaded_contents == file_contents -@pytest.mark.asyncio async def test_delete_openai_vector_store_file_from_storage(vector_io_adapter, tmp_path_factory): store_id = "vs_1234" file_id = "file_1234" diff --git a/tests/unit/rag/test_rag_query.py b/tests/unit/rag/test_rag_query.py index d2dd1783b..b2baa744a 100644 --- a/tests/unit/rag/test_rag_query.py +++ b/tests/unit/rag/test_rag_query.py @@ -17,13 +17,11 @@ from llama_stack.providers.inline.tool_runtime.rag.memory import MemoryToolRunti class TestRagQuery: - @pytest.mark.asyncio async def test_query_raises_on_empty_vector_db_ids(self): rag_tool = MemoryToolRuntimeImpl(config=MagicMock(), vector_io_api=MagicMock(), inference_api=MagicMock()) with pytest.raises(ValueError): await rag_tool.query(content=MagicMock(), vector_db_ids=[]) - @pytest.mark.asyncio async def test_query_chunk_metadata_handling(self): rag_tool = MemoryToolRuntimeImpl(config=MagicMock(), vector_io_api=MagicMock(), inference_api=MagicMock()) content = "test query content" diff --git a/tests/unit/rag/test_vector_store.py b/tests/unit/rag/test_vector_store.py index 9d6b9ee67..dd36d3992 100644 --- a/tests/unit/rag/test_vector_store.py +++ b/tests/unit/rag/test_vector_store.py @@ -112,7 +112,6 @@ class TestValidateEmbedding: class TestVectorStore: - @pytest.mark.asyncio async def test_returns_content_from_pdf_data_uri(self): data_uri = data_url_from_file(DUMMY_PDF_PATH) doc = RAGDocument( @@ -124,7 +123,6 @@ class TestVectorStore: content = await content_from_doc(doc) assert content in DUMMY_PDF_TEXT_CHOICES - @pytest.mark.asyncio async def test_downloads_pdf_and_returns_content(self): # Using GitHub to host the PDF file url = "https://raw.githubusercontent.com/meta-llama/llama-stack/da035d69cfca915318eaf485770a467ca3c2a238/llama_stack/providers/tests/memory/fixtures/dummy.pdf" @@ -137,7 +135,6 @@ class TestVectorStore: content = await content_from_doc(doc) assert content in DUMMY_PDF_TEXT_CHOICES - @pytest.mark.asyncio async def test_downloads_pdf_and_returns_content_with_url_object(self): # Using GitHub to host the PDF file url = "https://raw.githubusercontent.com/meta-llama/llama-stack/da035d69cfca915318eaf485770a467ca3c2a238/llama_stack/providers/tests/memory/fixtures/dummy.pdf" @@ -204,7 +201,6 @@ class TestVectorStore: class TestVectorDBWithIndex: - @pytest.mark.asyncio async def test_insert_chunks_without_embeddings(self): mock_vector_db = MagicMock() mock_vector_db.embedding_model = "test-model without embeddings" @@ -230,7 +226,6 @@ class TestVectorDBWithIndex: assert args[0] == chunks assert np.array_equal(args[1], np.array([[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]], dtype=np.float32)) - @pytest.mark.asyncio async def test_insert_chunks_with_valid_embeddings(self): mock_vector_db = MagicMock() mock_vector_db.embedding_model = "test-model with embeddings" @@ -255,7 +250,6 @@ class TestVectorDBWithIndex: assert args[0] == chunks assert np.array_equal(args[1], np.array([[0.1, 0.2, 0.3], [0.4, 0.5, 0.6]], dtype=np.float32)) - @pytest.mark.asyncio async def test_insert_chunks_with_invalid_embeddings(self): mock_vector_db = MagicMock() mock_vector_db.embedding_dimension = 3 @@ -295,7 +289,6 @@ class TestVectorDBWithIndex: mock_inference_api.embeddings.assert_not_called() mock_index.add_chunks.assert_not_called() - @pytest.mark.asyncio async def test_insert_chunks_with_partially_precomputed_embeddings(self): mock_vector_db = MagicMock() mock_vector_db.embedding_model = "test-model with partial embeddings" diff --git a/tests/unit/registry/test_registry.py b/tests/unit/registry/test_registry.py index 909581bb7..87fe18d54 100644 --- a/tests/unit/registry/test_registry.py +++ b/tests/unit/registry/test_registry.py @@ -38,14 +38,12 @@ def sample_model(): ) -@pytest.mark.asyncio async def test_registry_initialization(disk_dist_registry): # Test empty registry result = await disk_dist_registry.get("nonexistent", "nonexistent") assert result is None -@pytest.mark.asyncio async def test_basic_registration(disk_dist_registry, sample_vector_db, sample_model): print(f"Registering {sample_vector_db}") await disk_dist_registry.register(sample_vector_db) @@ -64,7 +62,6 @@ async def test_basic_registration(disk_dist_registry, sample_vector_db, sample_m assert result_model.provider_id == sample_model.provider_id -@pytest.mark.asyncio async def test_cached_registry_initialization(sqlite_kvstore, sample_vector_db, sample_model): # First populate the disk registry disk_registry = DiskDistributionRegistry(sqlite_kvstore) @@ -85,7 +82,6 @@ async def test_cached_registry_initialization(sqlite_kvstore, sample_vector_db, assert result_vector_db.provider_id == sample_vector_db.provider_id -@pytest.mark.asyncio async def test_cached_registry_updates(cached_disk_dist_registry): new_vector_db = VectorDB( identifier="test_vector_db_2", @@ -112,7 +108,6 @@ async def test_cached_registry_updates(cached_disk_dist_registry): assert result_vector_db.provider_id == new_vector_db.provider_id -@pytest.mark.asyncio async def test_duplicate_provider_registration(cached_disk_dist_registry): original_vector_db = VectorDB( identifier="test_vector_db_2", @@ -137,7 +132,6 @@ async def test_duplicate_provider_registration(cached_disk_dist_registry): assert result.embedding_model == original_vector_db.embedding_model # Original values preserved -@pytest.mark.asyncio async def test_get_all_objects(cached_disk_dist_registry): # Create multiple test banks # Create multiple test banks @@ -170,7 +164,6 @@ async def test_get_all_objects(cached_disk_dist_registry): assert stored_vector_db.embedding_dimension == original_vector_db.embedding_dimension -@pytest.mark.asyncio async def test_parse_registry_values_error_handling(sqlite_kvstore): valid_db = VectorDB( identifier="valid_vector_db", @@ -209,7 +202,6 @@ async def test_parse_registry_values_error_handling(sqlite_kvstore): assert invalid_obj is None -@pytest.mark.asyncio async def test_cached_registry_error_handling(sqlite_kvstore): valid_db = VectorDB( identifier="valid_cached_db", diff --git a/tests/unit/registry/test_registry_acl.py b/tests/unit/registry/test_registry_acl.py index 48b3ac51b..6cfb20944 100644 --- a/tests/unit/registry/test_registry_acl.py +++ b/tests/unit/registry/test_registry_acl.py @@ -5,14 +5,11 @@ # the root directory of this source tree. -import pytest - from llama_stack.apis.models import ModelType from llama_stack.distribution.datatypes import ModelWithOwner, User from llama_stack.distribution.store.registry import CachedDiskDistributionRegistry -@pytest.mark.asyncio async def test_registry_cache_with_acl(cached_disk_dist_registry): model = ModelWithOwner( identifier="model-acl", @@ -48,7 +45,6 @@ async def test_registry_cache_with_acl(cached_disk_dist_registry): assert new_model.owner.attributes["teams"] == ["ai-team"] -@pytest.mark.asyncio async def test_registry_empty_acl(cached_disk_dist_registry): model = ModelWithOwner( identifier="model-empty-acl", @@ -85,7 +81,6 @@ async def test_registry_empty_acl(cached_disk_dist_registry): assert len(all_models) == 2 -@pytest.mark.asyncio async def test_registry_serialization(cached_disk_dist_registry): attributes = { "roles": ["admin", "researcher"], diff --git a/tests/unit/server/test_access_control.py b/tests/unit/server/test_access_control.py index af03ddacb..fb9c6f95e 100644 --- a/tests/unit/server/test_access_control.py +++ b/tests/unit/server/test_access_control.py @@ -7,7 +7,6 @@ from unittest.mock import MagicMock, Mock, patch import pytest -import pytest_asyncio import yaml from pydantic import TypeAdapter, ValidationError @@ -27,7 +26,7 @@ def _return_model(model): return model -@pytest_asyncio.fixture +@pytest.fixture async def test_setup(cached_disk_dist_registry): mock_inference = Mock() mock_inference.__provider_spec__ = MagicMock() @@ -41,7 +40,6 @@ async def test_setup(cached_disk_dist_registry): yield cached_disk_dist_registry, routing_table -@pytest.mark.asyncio @patch("llama_stack.distribution.routing_tables.common.get_authenticated_user") async def test_access_control_with_cache(mock_get_authenticated_user, test_setup): registry, routing_table = test_setup @@ -106,7 +104,6 @@ async def test_access_control_with_cache(mock_get_authenticated_user, test_setup await routing_table.get_model("model-admin") -@pytest.mark.asyncio @patch("llama_stack.distribution.routing_tables.common.get_authenticated_user") async def test_access_control_and_updates(mock_get_authenticated_user, test_setup): registry, routing_table = test_setup @@ -145,7 +142,6 @@ async def test_access_control_and_updates(mock_get_authenticated_user, test_setu assert model.identifier == "model-updates" -@pytest.mark.asyncio @patch("llama_stack.distribution.routing_tables.common.get_authenticated_user") async def test_access_control_empty_attributes(mock_get_authenticated_user, test_setup): registry, routing_table = test_setup @@ -170,7 +166,6 @@ async def test_access_control_empty_attributes(mock_get_authenticated_user, test assert "model-empty-attrs" in model_ids -@pytest.mark.asyncio @patch("llama_stack.distribution.routing_tables.common.get_authenticated_user") async def test_no_user_attributes(mock_get_authenticated_user, test_setup): registry, routing_table = test_setup @@ -201,7 +196,6 @@ async def test_no_user_attributes(mock_get_authenticated_user, test_setup): assert all_models.data[0].identifier == "model-public-2" -@pytest.mark.asyncio @patch("llama_stack.distribution.routing_tables.common.get_authenticated_user") async def test_automatic_access_attributes(mock_get_authenticated_user, test_setup): """Test that newly created resources inherit access attributes from their creator.""" @@ -246,7 +240,7 @@ async def test_automatic_access_attributes(mock_get_authenticated_user, test_set assert model.identifier == "auto-access-model" -@pytest_asyncio.fixture +@pytest.fixture async def test_setup_with_access_policy(cached_disk_dist_registry): mock_inference = Mock() mock_inference.__provider_spec__ = MagicMock() @@ -281,7 +275,6 @@ async def test_setup_with_access_policy(cached_disk_dist_registry): yield routing_table -@pytest.mark.asyncio @patch("llama_stack.distribution.routing_tables.common.get_authenticated_user") async def test_access_policy(mock_get_authenticated_user, test_setup_with_access_policy): routing_table = test_setup_with_access_policy diff --git a/tests/unit/server/test_auth.py b/tests/unit/server/test_auth.py index 39d6af1c8..7012a7f17 100644 --- a/tests/unit/server/test_auth.py +++ b/tests/unit/server/test_auth.py @@ -202,7 +202,6 @@ def test_http_auth_request_payload(http_client, valid_api_key, mock_auth_endpoin assert "param2" in payload["request"]["params"] -@pytest.mark.asyncio async def test_http_middleware_with_access_attributes(mock_http_middleware, mock_scope): """Test HTTP middleware behavior with access attributes""" middleware, mock_app = mock_http_middleware diff --git a/tests/unit/server/test_resolver.py b/tests/unit/server/test_resolver.py index acf4da0a3..a348590b1 100644 --- a/tests/unit/server/test_resolver.py +++ b/tests/unit/server/test_resolver.py @@ -9,7 +9,6 @@ import sys from typing import Any, Protocol from unittest.mock import AsyncMock, MagicMock -import pytest from pydantic import BaseModel, Field from llama_stack.apis.inference import Inference @@ -66,7 +65,6 @@ class SampleImpl: pass -@pytest.mark.asyncio async def test_resolve_impls_basic(): # Create a real provider spec provider_spec = InlineProviderSpec( diff --git a/tests/unit/server/test_sse.py b/tests/unit/server/test_sse.py index 60e9f4609..d42857186 100644 --- a/tests/unit/server/test_sse.py +++ b/tests/unit/server/test_sse.py @@ -7,13 +7,10 @@ import asyncio from unittest.mock import AsyncMock, MagicMock -import pytest - from llama_stack.apis.common.responses import PaginatedResponse from llama_stack.distribution.server.server import create_dynamic_typed_route, create_sse_event, sse_generator -@pytest.mark.asyncio async def test_sse_generator_basic(): # An AsyncIterator wrapped in an Awaitable, just like our web methods async def async_event_gen(): @@ -35,7 +32,6 @@ async def test_sse_generator_basic(): assert seen_events[1] == create_sse_event("Test event 2") -@pytest.mark.asyncio async def test_sse_generator_client_disconnected(): # An AsyncIterator wrapped in an Awaitable, just like our web methods async def async_event_gen(): @@ -58,7 +54,6 @@ async def test_sse_generator_client_disconnected(): assert seen_events[0] == create_sse_event("Test event 1") -@pytest.mark.asyncio async def test_sse_generator_client_disconnected_before_response_starts(): # Disconnect before the response starts async def async_event_gen(): @@ -75,7 +70,6 @@ async def test_sse_generator_client_disconnected_before_response_starts(): assert len(seen_events) == 0 -@pytest.mark.asyncio async def test_sse_generator_error_before_response_starts(): # Raise an error before the response starts async def async_event_gen(): @@ -93,7 +87,6 @@ async def test_sse_generator_error_before_response_starts(): assert 'data: {"error":' in seen_events[0] -@pytest.mark.asyncio async def test_paginated_response_url_setting(): """Test that PaginatedResponse gets url set to route path.""" diff --git a/tests/unit/utils/inference/test_inference_store.py b/tests/unit/utils/inference/test_inference_store.py index de619c760..730f54a05 100644 --- a/tests/unit/utils/inference/test_inference_store.py +++ b/tests/unit/utils/inference/test_inference_store.py @@ -42,7 +42,6 @@ def create_test_chat_completion( ) -@pytest.mark.asyncio async def test_inference_store_pagination_basic(): """Test basic pagination functionality.""" with TemporaryDirectory() as tmp_dir: @@ -88,7 +87,6 @@ async def test_inference_store_pagination_basic(): assert result3.has_more is False -@pytest.mark.asyncio async def test_inference_store_pagination_ascending(): """Test pagination with ascending order.""" with TemporaryDirectory() as tmp_dir: @@ -123,7 +121,6 @@ async def test_inference_store_pagination_ascending(): assert result2.has_more is True -@pytest.mark.asyncio async def test_inference_store_pagination_with_model_filter(): """Test pagination combined with model filtering.""" with TemporaryDirectory() as tmp_dir: @@ -161,7 +158,6 @@ async def test_inference_store_pagination_with_model_filter(): assert result2.has_more is False -@pytest.mark.asyncio async def test_inference_store_pagination_invalid_after(): """Test error handling for invalid 'after' parameter.""" with TemporaryDirectory() as tmp_dir: @@ -174,7 +170,6 @@ async def test_inference_store_pagination_invalid_after(): await store.list_chat_completions(after="non-existent", limit=2) -@pytest.mark.asyncio async def test_inference_store_pagination_no_limit(): """Test pagination behavior when no limit is specified.""" with TemporaryDirectory() as tmp_dir: diff --git a/tests/unit/utils/responses/test_responses_store.py b/tests/unit/utils/responses/test_responses_store.py index 3f25e2524..44d4b30da 100644 --- a/tests/unit/utils/responses/test_responses_store.py +++ b/tests/unit/utils/responses/test_responses_store.py @@ -44,7 +44,6 @@ def create_test_response_input(content: str, input_id: str) -> OpenAIResponseInp ) -@pytest.mark.asyncio async def test_responses_store_pagination_basic(): """Test basic pagination functionality for responses store.""" with TemporaryDirectory() as tmp_dir: @@ -90,7 +89,6 @@ async def test_responses_store_pagination_basic(): assert result3.has_more is False -@pytest.mark.asyncio async def test_responses_store_pagination_ascending(): """Test pagination with ascending order.""" with TemporaryDirectory() as tmp_dir: @@ -125,7 +123,6 @@ async def test_responses_store_pagination_ascending(): assert result2.has_more is True -@pytest.mark.asyncio async def test_responses_store_pagination_with_model_filter(): """Test pagination combined with model filtering.""" with TemporaryDirectory() as tmp_dir: @@ -163,7 +160,6 @@ async def test_responses_store_pagination_with_model_filter(): assert result2.has_more is False -@pytest.mark.asyncio async def test_responses_store_pagination_invalid_after(): """Test error handling for invalid 'after' parameter.""" with TemporaryDirectory() as tmp_dir: @@ -176,7 +172,6 @@ async def test_responses_store_pagination_invalid_after(): await store.list_responses(after="non-existent", limit=2) -@pytest.mark.asyncio async def test_responses_store_pagination_no_limit(): """Test pagination behavior when no limit is specified.""" with TemporaryDirectory() as tmp_dir: @@ -205,7 +200,6 @@ async def test_responses_store_pagination_no_limit(): assert result.has_more is False -@pytest.mark.asyncio async def test_responses_store_get_response_object(): """Test retrieving a single response object.""" with TemporaryDirectory() as tmp_dir: @@ -230,7 +224,6 @@ async def test_responses_store_get_response_object(): await store.get_response_object("non-existent") -@pytest.mark.asyncio async def test_responses_store_input_items_pagination(): """Test pagination functionality for input items.""" with TemporaryDirectory() as tmp_dir: @@ -308,7 +301,6 @@ async def test_responses_store_input_items_pagination(): await store.list_response_input_items("test-resp", before="some-id", after="other-id") -@pytest.mark.asyncio async def test_responses_store_input_items_before_pagination(): """Test before pagination functionality for input items.""" with TemporaryDirectory() as tmp_dir: diff --git a/tests/unit/utils/sqlstore/test_sqlstore.py b/tests/unit/utils/sqlstore/test_sqlstore.py index c4230a396..778f0b658 100644 --- a/tests/unit/utils/sqlstore/test_sqlstore.py +++ b/tests/unit/utils/sqlstore/test_sqlstore.py @@ -14,7 +14,6 @@ from llama_stack.providers.utils.sqlstore.sqlalchemy_sqlstore import SqlAlchemyS from llama_stack.providers.utils.sqlstore.sqlstore import SqliteSqlStoreConfig -@pytest.mark.asyncio async def test_sqlite_sqlstore(): with TemporaryDirectory() as tmp_dir: db_name = "test.db" @@ -66,7 +65,6 @@ async def test_sqlite_sqlstore(): assert result.has_more is False -@pytest.mark.asyncio async def test_sqlstore_pagination_basic(): """Test basic pagination functionality at the SQL store level.""" with TemporaryDirectory() as tmp_dir: @@ -131,7 +129,6 @@ async def test_sqlstore_pagination_basic(): assert result3.has_more is False -@pytest.mark.asyncio async def test_sqlstore_pagination_with_filter(): """Test pagination with WHERE conditions.""" with TemporaryDirectory() as tmp_dir: @@ -184,7 +181,6 @@ async def test_sqlstore_pagination_with_filter(): assert result2.has_more is False -@pytest.mark.asyncio async def test_sqlstore_pagination_ascending_order(): """Test pagination with ascending order.""" with TemporaryDirectory() as tmp_dir: @@ -233,7 +229,6 @@ async def test_sqlstore_pagination_ascending_order(): assert result2.has_more is True -@pytest.mark.asyncio async def test_sqlstore_pagination_multi_column_ordering_error(): """Test that multi-column ordering raises an error when using cursor pagination.""" with TemporaryDirectory() as tmp_dir: @@ -271,7 +266,6 @@ async def test_sqlstore_pagination_multi_column_ordering_error(): assert result.data[0]["id"] == "task1" -@pytest.mark.asyncio async def test_sqlstore_pagination_cursor_requires_order_by(): """Test that cursor pagination requires order_by parameter.""" with TemporaryDirectory() as tmp_dir: @@ -289,7 +283,6 @@ async def test_sqlstore_pagination_cursor_requires_order_by(): ) -@pytest.mark.asyncio async def test_sqlstore_pagination_error_handling(): """Test error handling for invalid columns and cursor IDs.""" with TemporaryDirectory() as tmp_dir: @@ -339,7 +332,6 @@ async def test_sqlstore_pagination_error_handling(): ) -@pytest.mark.asyncio async def test_sqlstore_pagination_custom_key_column(): """Test pagination with custom primary key column (not 'id').""" with TemporaryDirectory() as tmp_dir: diff --git a/tests/unit/utils/test_authorized_sqlstore.py b/tests/unit/utils/test_authorized_sqlstore.py index 61763719a..066f67a98 100644 --- a/tests/unit/utils/test_authorized_sqlstore.py +++ b/tests/unit/utils/test_authorized_sqlstore.py @@ -7,8 +7,6 @@ from tempfile import TemporaryDirectory from unittest.mock import patch -import pytest - from llama_stack.distribution.access_control.access_control import default_policy, is_action_allowed from llama_stack.distribution.access_control.datatypes import Action from llama_stack.distribution.datatypes import User @@ -18,7 +16,6 @@ from llama_stack.providers.utils.sqlstore.sqlalchemy_sqlstore import SqlAlchemyS from llama_stack.providers.utils.sqlstore.sqlstore import SqliteSqlStoreConfig -@pytest.mark.asyncio @patch("llama_stack.providers.utils.sqlstore.authorized_sqlstore.get_authenticated_user") async def test_authorized_fetch_with_where_sql_access_control(mock_get_authenticated_user): """Test that fetch_all works correctly with where_sql for access control""" @@ -81,7 +78,6 @@ async def test_authorized_fetch_with_where_sql_access_control(mock_get_authentic assert row["title"] == "User Document" -@pytest.mark.asyncio @patch("llama_stack.providers.utils.sqlstore.authorized_sqlstore.get_authenticated_user") async def test_sql_policy_consistency(mock_get_authenticated_user): """Test that SQL WHERE clause logic exactly matches is_action_allowed policy logic""" @@ -168,7 +164,6 @@ async def test_sql_policy_consistency(mock_get_authenticated_user): ) -@pytest.mark.asyncio @patch("llama_stack.providers.utils.sqlstore.authorized_sqlstore.get_authenticated_user") async def test_authorized_store_user_attribute_capture(mock_get_authenticated_user): """Test that user attributes are properly captured during insert""" diff --git a/uv.lock b/uv.lock index 8374fe38a..fe50f88aa 100644 --- a/uv.lock +++ b/uv.lock @@ -1394,8 +1394,8 @@ dev = [ { name = "black" }, { name = "nbval" }, { name = "pre-commit" }, - { name = "pytest" }, - { name = "pytest-asyncio" }, + { name = "pytest", specifier = ">=8.4" }, + { name = "pytest-asyncio", specifier = ">=1.0" }, { name = "pytest-cov" }, { name = "pytest-html" }, { name = "pytest-json-report" }, @@ -2432,29 +2432,30 @@ wheels = [ [[package]] name = "pytest" -version = "8.3.4" +version = "8.4.1" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "colorama", marker = "sys_platform == 'win32'" }, { name = "iniconfig" }, { name = "packaging" }, { name = "pluggy" }, + { name = "pygments" }, ] -sdist = { url = "https://files.pythonhosted.org/packages/05/35/30e0d83068951d90a01852cb1cef56e5d8a09d20c7f511634cc2f7e0372a/pytest-8.3.4.tar.gz", hash = "sha256:965370d062bce11e73868e0335abac31b4d3de0e82f4007408d242b4f8610761", size = 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url = "https://files.pythonhosted.org/packages/30/05/ce271016e351fddc8399e546f6e23761967ee09c8c568bbfbecb0c150171/pytest_asyncio-1.0.0-py3-none-any.whl", hash = "sha256:4f024da9f1ef945e680dc68610b52550e36590a67fd31bb3b4943979a1f90ef3", size = 15976, upload-time = "2025-05-26T04:54:39.035Z" }, ] [[package]] From aa2595c7c3a4145951acdf8c7bc5247c72ded353 Mon Sep 17 00:00:00 2001 From: Jorge Piedrahita Ortiz Date: Fri, 11 Jul 2025 15:29:15 -0500 Subject: [PATCH 22/34] fix: sambanova shields and model validation (#2693) # What does this PR do? Update the shield register validation of Sambanova not to raise, but only warn when a model is not available in the base url endpoint used, also added warnings when model is not available in the base url endpoint used ## Test Plan run starter distro with Sambanova enabled --- .../remote/inference/sambanova/sambanova.py | 21 ++++++++++++++++++- .../remote/safety/sambanova/sambanova.py | 21 ++++++++++--------- .../inference/test_openai_completion.py | 1 - 3 files changed, 31 insertions(+), 12 deletions(-) diff --git a/llama_stack/providers/remote/inference/sambanova/sambanova.py b/llama_stack/providers/remote/inference/sambanova/sambanova.py index 20f863665..9c2dda889 100644 --- a/llama_stack/providers/remote/inference/sambanova/sambanova.py +++ b/llama_stack/providers/remote/inference/sambanova/sambanova.py @@ -7,6 +7,7 @@ import json from collections.abc import Iterable +import requests from openai.types.chat import ( ChatCompletionAssistantMessageParam as OpenAIChatCompletionAssistantMessage, ) @@ -56,6 +57,7 @@ from llama_stack.apis.inference import ( ToolResponseMessage, UserMessage, ) +from llama_stack.apis.models import Model from llama_stack.log import get_logger from llama_stack.models.llama.datatypes import BuiltinTool from llama_stack.providers.utils.inference.litellm_openai_mixin import LiteLLMOpenAIMixin @@ -176,10 +178,11 @@ class SambaNovaInferenceAdapter(LiteLLMOpenAIMixin): def __init__(self, config: SambaNovaImplConfig): self.config = config + self.environment_available_models = [] LiteLLMOpenAIMixin.__init__( self, model_entries=MODEL_ENTRIES, - api_key_from_config=self.config.api_key, + api_key_from_config=self.config.api_key.get_secret_value() if self.config.api_key else None, provider_data_api_key_field="sambanova_api_key", ) @@ -246,6 +249,22 @@ class SambaNovaInferenceAdapter(LiteLLMOpenAIMixin): **get_sampling_options(request.sampling_params), } + async def register_model(self, model: Model) -> Model: + model_id = self.get_provider_model_id(model.provider_resource_id) + + list_models_url = self.config.url + "/models" + if len(self.environment_available_models) == 0: + try: + response = requests.get(list_models_url) + response.raise_for_status() + except requests.exceptions.RequestException as e: + raise RuntimeError(f"Request to {list_models_url} failed") from e + self.environment_available_models = [model.get("id") for model in response.json().get("data", {})] + + if model_id.split("sambanova/")[-1] not in self.environment_available_models: + logger.warning(f"Model {model_id} not available in {list_models_url}") + return model + async def initialize(self): await super().initialize() diff --git a/llama_stack/providers/remote/safety/sambanova/sambanova.py b/llama_stack/providers/remote/safety/sambanova/sambanova.py index 84c8267ae..1a65f6aa1 100644 --- a/llama_stack/providers/remote/safety/sambanova/sambanova.py +++ b/llama_stack/providers/remote/safety/sambanova/sambanova.py @@ -33,6 +33,7 @@ CANNED_RESPONSE_TEXT = "I can't answer that. Can I help with something else?" class SambaNovaSafetyAdapter(Safety, ShieldsProtocolPrivate, NeedsRequestProviderData): def __init__(self, config: SambaNovaSafetyConfig) -> None: self.config = config + self.environment_available_models = [] async def initialize(self) -> None: pass @@ -54,18 +55,18 @@ class SambaNovaSafetyAdapter(Safety, ShieldsProtocolPrivate, NeedsRequestProvide async def register_shield(self, shield: Shield) -> None: list_models_url = self.config.url + "/models" - try: - response = requests.get(list_models_url) - response.raise_for_status() - except requests.exceptions.RequestException as e: - raise RuntimeError(f"Request to {list_models_url} failed") from e - available_models = [model.get("id") for model in response.json().get("data", {})] + if len(self.environment_available_models) == 0: + try: + response = requests.get(list_models_url) + response.raise_for_status() + except requests.exceptions.RequestException as e: + raise RuntimeError(f"Request to {list_models_url} failed") from e + self.environment_available_models = [model.get("id") for model in response.json().get("data", {})] if ( - len(available_models) == 0 - or "guard" not in shield.provider_resource_id.lower() - or shield.provider_resource_id.split("sambanova/")[-1] not in available_models + "guard" not in shield.provider_resource_id.lower() + or shield.provider_resource_id.split("sambanova/")[-1] not in self.environment_available_models ): - raise ValueError(f"Shield {shield.provider_resource_id} not found in SambaNova") + logger.warning(f"Shield {shield.provider_resource_id} not available in {list_models_url}") async def run_shield( self, shield_id: str, messages: list[Message], params: dict[str, Any] | None = None diff --git a/tests/integration/inference/test_openai_completion.py b/tests/integration/inference/test_openai_completion.py index 05aee5096..e82714ffd 100644 --- a/tests/integration/inference/test_openai_completion.py +++ b/tests/integration/inference/test_openai_completion.py @@ -71,7 +71,6 @@ def skip_if_model_doesnt_support_openai_chat_completion(client_with_models, mode "remote::cerebras", "remote::databricks", "remote::runpod", - "remote::sambanova", "remote::tgi", ): pytest.skip(f"Model {model_id} hosted by {provider.provider_type} doesn't support OpenAI chat completions.") From 51d9fd48083de32e9796f00030b57be10a8ac7bd Mon Sep 17 00:00:00 2001 From: Ben Browning Date: Fri, 11 Jul 2025 16:38:27 -0400 Subject: [PATCH 23/34] fix: Don't cache clients for passthrough auth providers (#2728) # What does this PR do? Some of our inference providers support passthrough authentication via `x-llamastack-provider-data` header values. This fixes the providers that support passthrough auth to not cache their clients to the backend providers (mostly OpenAI client instances) so that the client connecting to Llama Stack has to provide those auth values on each and every request. ## Test Plan I added some unit tests to ensure we're not caching clients across requests for all the fixed providers in this PR. ``` uv run pytest -sv tests/unit/providers/inference/test_inference_client_caching.py ``` I also ran some of our OpenAI compatible API integration tests for each of the changed providers, just to ensure they still work. Note that these providers don't actually pass all these tests (for unrelated reasons due to quirks of the Groq and Together SaaS services), but enough of the tests passed to confirm the clients are still working as intended. ### Together ``` ENABLE_TOGETHER="together" \ uv run llama stack run llama_stack/templates/starter/run.yaml LLAMA_STACK_CONFIG=http://localhost:8321 \ uv run pytest -sv \ tests/integration/inference/test_openai_completion.py \ --text-model "together/meta-llama/Llama-3.1-8B-Instruct" ``` ### OpenAI ``` ENABLE_OPENAI="openai" \ uv run llama stack run llama_stack/templates/starter/run.yaml LLAMA_STACK_CONFIG=http://localhost:8321 \ uv run pytest -sv \ tests/integration/inference/test_openai_completion.py \ --text-model "openai/gpt-4o-mini" ``` ### Groq ``` ENABLE_GROQ="groq" \ uv run llama stack run llama_stack/templates/starter/run.yaml LLAMA_STACK_CONFIG=http://localhost:8321 \ uv run pytest -sv \ tests/integration/inference/test_openai_completion.py \ --text-model "groq/meta-llama/Llama-3.1-8B-Instruct" ``` --------- Signed-off-by: Ben Browning --- .../providers/remote/inference/groq/groq.py | 14 +-- .../remote/inference/openai/openai.py | 14 +-- .../remote/inference/together/together.py | 47 ++++------ pyproject.toml | 2 + .../test_inference_client_caching.py | 73 +++++++++++++++ uv.lock | 91 +++++++++++++++++++ 6 files changed, 196 insertions(+), 45 deletions(-) create mode 100644 tests/unit/providers/inference/test_inference_client_caching.py diff --git a/llama_stack/providers/remote/inference/groq/groq.py b/llama_stack/providers/remote/inference/groq/groq.py index 4b295e788..91c6b6c17 100644 --- a/llama_stack/providers/remote/inference/groq/groq.py +++ b/llama_stack/providers/remote/inference/groq/groq.py @@ -38,24 +38,18 @@ class GroqInferenceAdapter(LiteLLMOpenAIMixin): provider_data_api_key_field="groq_api_key", ) self.config = config - self._openai_client = None async def initialize(self): await super().initialize() async def shutdown(self): await super().shutdown() - if self._openai_client: - await self._openai_client.close() - self._openai_client = None def _get_openai_client(self) -> AsyncOpenAI: - if not self._openai_client: - self._openai_client = AsyncOpenAI( - base_url=f"{self.config.url}/openai/v1", - api_key=self.config.api_key, - ) - return self._openai_client + return AsyncOpenAI( + base_url=f"{self.config.url}/openai/v1", + api_key=self.get_api_key(), + ) async def openai_chat_completion( self, diff --git a/llama_stack/providers/remote/inference/openai/openai.py b/llama_stack/providers/remote/inference/openai/openai.py index 72428422f..818883919 100644 --- a/llama_stack/providers/remote/inference/openai/openai.py +++ b/llama_stack/providers/remote/inference/openai/openai.py @@ -59,9 +59,6 @@ class OpenAIInferenceAdapter(LiteLLMOpenAIMixin): # if we do not set this, users will be exposed to the # litellm specific model names, an abstraction leak. self.is_openai_compat = True - self._openai_client = AsyncOpenAI( - api_key=self.config.api_key, - ) async def initialize(self) -> None: await super().initialize() @@ -69,6 +66,11 @@ class OpenAIInferenceAdapter(LiteLLMOpenAIMixin): async def shutdown(self) -> None: await super().shutdown() + def _get_openai_client(self) -> AsyncOpenAI: + return AsyncOpenAI( + api_key=self.get_api_key(), + ) + async def openai_completion( self, model: str, @@ -120,7 +122,7 @@ class OpenAIInferenceAdapter(LiteLLMOpenAIMixin): user=user, suffix=suffix, ) - return await self._openai_client.completions.create(**params) + return await self._get_openai_client().completions.create(**params) async def openai_chat_completion( self, @@ -176,7 +178,7 @@ class OpenAIInferenceAdapter(LiteLLMOpenAIMixin): top_p=top_p, user=user, ) - return await self._openai_client.chat.completions.create(**params) + return await self._get_openai_client().chat.completions.create(**params) async def openai_embeddings( self, @@ -204,7 +206,7 @@ class OpenAIInferenceAdapter(LiteLLMOpenAIMixin): params["user"] = user # Call OpenAI embeddings API - response = await self._openai_client.embeddings.create(**params) + response = await self._get_openai_client().embeddings.create(**params) data = [] for i, embedding_data in enumerate(response.data): diff --git a/llama_stack/providers/remote/inference/together/together.py b/llama_stack/providers/remote/inference/together/together.py index 9e6877b7c..e1eb934c5 100644 --- a/llama_stack/providers/remote/inference/together/together.py +++ b/llama_stack/providers/remote/inference/together/together.py @@ -68,19 +68,12 @@ class TogetherInferenceAdapter(ModelRegistryHelper, Inference, NeedsRequestProvi def __init__(self, config: TogetherImplConfig) -> None: ModelRegistryHelper.__init__(self, MODEL_ENTRIES) self.config = config - self._client = None - self._openai_client = None async def initialize(self) -> None: pass async def shutdown(self) -> None: - if self._client: - # Together client has no close method, so just set to None - self._client = None - if self._openai_client: - await self._openai_client.close() - self._openai_client = None + pass async def completion( self, @@ -108,29 +101,25 @@ class TogetherInferenceAdapter(ModelRegistryHelper, Inference, NeedsRequestProvi return await self._nonstream_completion(request) def _get_client(self) -> AsyncTogether: - if not self._client: - together_api_key = None - config_api_key = self.config.api_key.get_secret_value() if self.config.api_key else None - if config_api_key: - together_api_key = config_api_key - else: - provider_data = self.get_request_provider_data() - if provider_data is None or not provider_data.together_api_key: - raise ValueError( - 'Pass Together API Key in the header X-LlamaStack-Provider-Data as { "together_api_key": }' - ) - together_api_key = provider_data.together_api_key - self._client = AsyncTogether(api_key=together_api_key) - return self._client + together_api_key = None + config_api_key = self.config.api_key.get_secret_value() if self.config.api_key else None + if config_api_key: + together_api_key = config_api_key + else: + provider_data = self.get_request_provider_data() + if provider_data is None or not provider_data.together_api_key: + raise ValueError( + 'Pass Together API Key in the header X-LlamaStack-Provider-Data as { "together_api_key": }' + ) + together_api_key = provider_data.together_api_key + return AsyncTogether(api_key=together_api_key) def _get_openai_client(self) -> AsyncOpenAI: - if not self._openai_client: - together_client = self._get_client().client - self._openai_client = AsyncOpenAI( - base_url=together_client.base_url, - api_key=together_client.api_key, - ) - return self._openai_client + together_client = self._get_client().client + return AsyncOpenAI( + base_url=together_client.base_url, + api_key=together_client.api_key, + ) async def _nonstream_completion(self, request: CompletionRequest) -> ChatCompletionResponse: params = await self._get_params(request) diff --git a/pyproject.toml b/pyproject.toml index f4115d028..9977d7372 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -87,6 +87,8 @@ unit = [ "blobfile", "faiss-cpu", "pymilvus>=2.5.12", + "litellm", + "together", ] # These are the core dependencies required for running integration tests. They are shared across all # providers. If a provider requires additional dependencies, please add them to your environment diff --git a/tests/unit/providers/inference/test_inference_client_caching.py b/tests/unit/providers/inference/test_inference_client_caching.py new file mode 100644 index 000000000..c9a931d47 --- /dev/null +++ b/tests/unit/providers/inference/test_inference_client_caching.py @@ -0,0 +1,73 @@ +# Copyright (c) Meta Platforms, Inc. and affiliates. +# All rights reserved. +# +# This source code is licensed under the terms described in the LICENSE file in +# the root directory of this source tree. + +import json +from unittest.mock import MagicMock + +from llama_stack.distribution.request_headers import request_provider_data_context +from llama_stack.providers.remote.inference.groq.config import GroqConfig +from llama_stack.providers.remote.inference.groq.groq import GroqInferenceAdapter +from llama_stack.providers.remote.inference.openai.config import OpenAIConfig +from llama_stack.providers.remote.inference.openai.openai import OpenAIInferenceAdapter +from llama_stack.providers.remote.inference.together.config import TogetherImplConfig +from llama_stack.providers.remote.inference.together.together import TogetherInferenceAdapter + + +def test_groq_provider_openai_client_caching(): + """Ensure the Groq provider does not cache api keys across client requests""" + + config = GroqConfig() + inference_adapter = GroqInferenceAdapter(config) + + inference_adapter.__provider_spec__ = MagicMock() + inference_adapter.__provider_spec__.provider_data_validator = ( + "llama_stack.providers.remote.inference.groq.config.GroqProviderDataValidator" + ) + + for api_key in ["test1", "test2"]: + with request_provider_data_context( + {"x-llamastack-provider-data": json.dumps({inference_adapter.provider_data_api_key_field: api_key})} + ): + openai_client = inference_adapter._get_openai_client() + assert openai_client.api_key == api_key + + +def test_openai_provider_openai_client_caching(): + """Ensure the OpenAI provider does not cache api keys across client requests""" + + config = OpenAIConfig() + inference_adapter = OpenAIInferenceAdapter(config) + + inference_adapter.__provider_spec__ = MagicMock() + inference_adapter.__provider_spec__.provider_data_validator = ( + "llama_stack.providers.remote.inference.openai.config.OpenAIProviderDataValidator" + ) + + for api_key in ["test1", "test2"]: + with request_provider_data_context( + {"x-llamastack-provider-data": json.dumps({inference_adapter.provider_data_api_key_field: api_key})} + ): + openai_client = inference_adapter._get_openai_client() + assert openai_client.api_key == api_key + + +def test_together_provider_openai_client_caching(): + """Ensure the Together provider does not cache api keys across client requests""" + + config = TogetherImplConfig() + inference_adapter = TogetherInferenceAdapter(config) + + inference_adapter.__provider_spec__ = MagicMock() + inference_adapter.__provider_spec__.provider_data_validator = ( + "llama_stack.providers.remote.inference.together.TogetherProviderDataValidator" + ) + + for api_key in ["test1", "test2"]: + with request_provider_data_context({"x-llamastack-provider-data": json.dumps({"together_api_key": api_key})}): + together_client = inference_adapter._get_client() + assert together_client.client.api_key == api_key + openai_client = inference_adapter._get_openai_client() + assert openai_client.api_key == api_key diff --git a/uv.lock b/uv.lock index fe50f88aa..bca12fc51 100644 --- a/uv.lock +++ b/uv.lock @@ -615,6 +615,15 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/cb/a3/460c57f094a4a165c84a1341c373b0a4f5ec6ac244b998d5021aade89b77/ecdsa-0.19.1-py2.py3-none-any.whl", hash = "sha256:30638e27cf77b7e15c4c4cc1973720149e1033827cfd00661ca5c8cc0cdb24c3", size = 150607, upload-time = "2025-03-13T11:52:41.757Z" }, ] +[[package]] +name = "eval-type-backport" +version = "0.2.2" +source = { 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+version = "0.15.4" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "click" }, + { name = "rich" }, + { name = "shellingham" }, + { name = "typing-extensions" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/6c/89/c527e6c848739be8ceb5c44eb8208c52ea3515c6cf6406aa61932887bf58/typer-0.15.4.tar.gz", hash = "sha256:89507b104f9b6a0730354f27c39fae5b63ccd0c95b1ce1f1a6ba0cfd329997c3", size = 101559, upload-time = "2025-05-14T16:34:57.704Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/c9/62/d4ba7afe2096d5659ec3db8b15d8665bdcb92a3c6ff0b95e99895b335a9c/typer-0.15.4-py3-none-any.whl", hash = "sha256:eb0651654dcdea706780c466cf06d8f174405a659ffff8f163cfbfee98c0e173", size = 45258, upload-time = "2025-05-14T16:34:55.583Z" }, +] + [[package]] name = "types-requests" version = "2.32.0.20241016" From 8374d4cefd3e59c4dad68ec2842622b5f4154fd5 Mon Sep 17 00:00:00 2001 From: "dependabot[bot]" <49699333+dependabot[bot]@users.noreply.github.com> Date: Sat, 12 Jul 2025 16:23:42 -0400 Subject: [PATCH 24/34] chore(github-deps): bump medyagh/setup-minikube from 0.0.19 to 0.0.20 (#2738) --- .github/workflows/integration-auth-tests.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/integration-auth-tests.yml b/.github/workflows/integration-auth-tests.yml index 7822e4216..cf10e005c 100644 --- a/.github/workflows/integration-auth-tests.yml +++ b/.github/workflows/integration-auth-tests.yml @@ -35,7 +35,7 @@ jobs: - name: Install minikube if: ${{ matrix.auth-provider == 'kubernetes' }} - uses: medyagh/setup-minikube@cea33675329b799adccc9526aa5daccc26cd5052 # v0.0.19 + uses: medyagh/setup-minikube@e3c7f79eb1e997eabccc536a6cf318a2b0fe19d9 # v0.0.20 - name: Start minikube if: ${{ matrix.auth-provider == 'oauth2_token' }} From 68e7978c8890fd0aec901e0871fb92061a0d8fa5 Mon Sep 17 00:00:00 2001 From: Matthew Farrellee Date: Sat, 12 Jul 2025 19:53:54 -0400 Subject: [PATCH 25/34] chore: block network access from unit tests (#2732) # What does this PR do? this blocks network access for all `tests/unit/` tests. `tests/integration/` are untouched. it also introduces an `allow_network` marker to explicitly allow network access. ## Test Plan `./scripts/unit-tests.sh` --- pyproject.toml | 4 ++++ tests/unit/conftest.py | 11 +++++++++++ tests/unit/providers/inference/test_remote_vllm.py | 1 + tests/unit/rag/test_vector_store.py | 2 ++ uv.lock | 14 ++++++++++++++ 5 files changed, 32 insertions(+) diff --git a/pyproject.toml b/pyproject.toml index 9977d7372..2974ff996 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -64,6 +64,7 @@ dev = [ "pytest-cov", "pytest-html", "pytest-json-report", + "pytest-socket", # For blocking network access in unit tests "nbval", # For notebook testing "black", "ruff", @@ -344,3 +345,6 @@ classmethod-decorators = ["classmethod", "pydantic.field_validator"] [tool.pytest.ini_options] asyncio_mode = "auto" +markers = [ + "allow_network: Allow network access for specific unit tests", +] diff --git a/tests/unit/conftest.py b/tests/unit/conftest.py index aedac0386..b5eb1217d 100644 --- a/tests/unit/conftest.py +++ b/tests/unit/conftest.py @@ -4,6 +4,17 @@ # This source code is licensed under the terms described in the LICENSE file in # the root directory of this source tree. +import pytest_socket + # We need to import the fixtures here so that pytest can find them # but ruff doesn't think they are used and removes the import. "noqa: F401" prevents them from being removed from .fixtures import cached_disk_dist_registry, disk_dist_registry, sqlite_kvstore # noqa: F401 + + +def pytest_runtest_setup(item): + """Setup for each test - check if network access should be allowed.""" + if "allow_network" in item.keywords: + pytest_socket.enable_socket() + else: + # Allowing Unix sockets is necessary for some tests that use local servers and mocks + pytest_socket.disable_socket(allow_unix_socket=True) diff --git a/tests/unit/providers/inference/test_remote_vllm.py b/tests/unit/providers/inference/test_remote_vllm.py index ca44cc95d..5c2ad03ab 100644 --- a/tests/unit/providers/inference/test_remote_vllm.py +++ b/tests/unit/providers/inference/test_remote_vllm.py @@ -393,6 +393,7 @@ async def test_process_vllm_chat_completion_stream_response_no_choices(): assert chunks[0].event.event_type.value == "start" +@pytest.mark.allow_network def test_chat_completion_doesnt_block_event_loop(caplog): loop = asyncio.new_event_loop() loop.set_debug(True) diff --git a/tests/unit/rag/test_vector_store.py b/tests/unit/rag/test_vector_store.py index dd36d3992..919f97ba7 100644 --- a/tests/unit/rag/test_vector_store.py +++ b/tests/unit/rag/test_vector_store.py @@ -123,6 +123,7 @@ class TestVectorStore: content = await content_from_doc(doc) assert content in DUMMY_PDF_TEXT_CHOICES + @pytest.mark.allow_network async def test_downloads_pdf_and_returns_content(self): # Using GitHub to host the PDF file url = "https://raw.githubusercontent.com/meta-llama/llama-stack/da035d69cfca915318eaf485770a467ca3c2a238/llama_stack/providers/tests/memory/fixtures/dummy.pdf" @@ -135,6 +136,7 @@ class TestVectorStore: content = await content_from_doc(doc) assert content in DUMMY_PDF_TEXT_CHOICES + @pytest.mark.allow_network async def test_downloads_pdf_and_returns_content_with_url_object(self): # Using GitHub to host the PDF file url = "https://raw.githubusercontent.com/meta-llama/llama-stack/da035d69cfca915318eaf485770a467ca3c2a238/llama_stack/providers/tests/memory/fixtures/dummy.pdf" diff --git a/uv.lock b/uv.lock index bca12fc51..83e502e7f 100644 --- a/uv.lock +++ b/uv.lock @@ -1324,6 +1324,7 @@ dev = [ { name = "pytest-cov" }, { name = "pytest-html" }, { name = "pytest-json-report" }, + { name = "pytest-socket" }, { name = "pytest-timeout" }, { name = "ruamel-yaml" }, { name = "ruff" }, @@ -1432,6 +1433,7 @@ dev = [ { name = "pytest-cov" }, { name = "pytest-html" }, { name = "pytest-json-report" }, + { name = "pytest-socket" }, { name = "pytest-timeout" }, { name = "ruamel-yaml" }, { name = "ruff" }, @@ -2545,6 +2547,18 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/3e/43/7e7b2ec865caa92f67b8f0e9231a798d102724ca4c0e1f414316be1c1ef2/pytest_metadata-3.1.1-py3-none-any.whl", hash = "sha256:c8e0844db684ee1c798cfa38908d20d67d0463ecb6137c72e91f418558dd5f4b", size = 11428, upload-time = "2024-02-12T19:38:42.531Z" }, ] +[[package]] +name = "pytest-socket" +version = "0.7.0" +source = { registry = "https://pypi.org/simple" } +dependencies = [ + { name = "pytest" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/05/ff/90c7e1e746baf3d62ce864c479fd53410b534818b9437413903596f81580/pytest_socket-0.7.0.tar.gz", hash = "sha256:71ab048cbbcb085c15a4423b73b619a8b35d6a307f46f78ea46be51b1b7e11b3", size = 12389, upload-time = "2024-01-28T20:17:23.177Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/19/58/5d14cb5cb59409e491ebe816c47bf81423cd03098ea92281336320ae5681/pytest_socket-0.7.0-py3-none-any.whl", hash = "sha256:7e0f4642177d55d317bbd58fc68c6bd9048d6eadb2d46a89307fa9221336ce45", size = 6754, upload-time = "2024-01-28T20:17:22.105Z" }, +] + [[package]] name = "pytest-timeout" version = "2.4.0" From 958fc92b1bc99ba8e57e0819696f74a7e09f45f0 Mon Sep 17 00:00:00 2001 From: Francisco Arceo Date: Sun, 13 Jul 2025 04:03:55 -0400 Subject: [PATCH 26/34] feat: Add Vector stores UI (#2737) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit # What does this PR do? - Adds two pages to UI - Vector stores - Vector store detail view - Fixed darkmode navbar highlighting - Updated darkmode font color - Updated llama-stack-client package Screenshot 2025-07-12 at 11 34 35 PM Screenshot 2025-07-12 at 11 57 09 PM ## Test Plan --------- Signed-off-by: Francisco Javier Arceo --- .../ui/app/logs/vector-stores/[id]/page.tsx | 82 +++ .../ui/app/logs/vector-stores/layout.tsx | 16 + .../ui/app/logs/vector-stores/page.tsx | 121 +++++ .../ui/components/layout/app-sidebar.tsx | 16 +- .../ui/components/layout/detail-layout.tsx | 8 +- .../ui/components/ui/message-components.tsx | 4 +- .../vector-stores/vector-store-detail.tsx | 128 +++++ llama_stack/ui/package-lock.json | 474 +----------------- llama_stack/ui/package.json | 2 +- 9 files changed, 378 insertions(+), 473 deletions(-) create mode 100644 llama_stack/ui/app/logs/vector-stores/[id]/page.tsx create mode 100644 llama_stack/ui/app/logs/vector-stores/layout.tsx create mode 100644 llama_stack/ui/app/logs/vector-stores/page.tsx create mode 100644 llama_stack/ui/components/vector-stores/vector-store-detail.tsx diff --git a/llama_stack/ui/app/logs/vector-stores/[id]/page.tsx b/llama_stack/ui/app/logs/vector-stores/[id]/page.tsx new file mode 100644 index 000000000..f27c9d802 --- /dev/null +++ b/llama_stack/ui/app/logs/vector-stores/[id]/page.tsx @@ -0,0 +1,82 @@ +"use client"; + +import { useEffect, useState } from "react"; +import { useParams, useRouter } from "next/navigation"; +import { useAuthClient } from "@/hooks/use-auth-client"; +import type { VectorStore } from "llama-stack-client/resources/vector-stores/vector-stores"; +import type { VectorStoreFile } from "llama-stack-client/resources/vector-stores/files"; +import { VectorStoreDetailView } from "@/components/vector-stores/vector-store-detail"; + +export default function VectorStoreDetailPage() { + const params = useParams(); + const id = params.id as string; + const client = useAuthClient(); + const router = useRouter(); + + const [store, setStore] = useState(null); + const [files, setFiles] = useState([]); + const [isLoadingStore, setIsLoadingStore] = useState(true); + const [isLoadingFiles, setIsLoadingFiles] = useState(true); + const [errorStore, setErrorStore] = useState(null); + const [errorFiles, setErrorFiles] = useState(null); + + useEffect(() => { + if (!id) { + setErrorStore(new Error("Vector Store ID is missing.")); + setIsLoadingStore(false); + return; + } + const fetchStore = async () => { + setIsLoadingStore(true); + setErrorStore(null); + try { + const response = await client.vectorStores.retrieve(id); + setStore(response as VectorStore); + } catch (err) { + setErrorStore( + err instanceof Error + ? err + : new Error("Failed to load vector store."), + ); + } finally { + setIsLoadingStore(false); + } + }; + fetchStore(); + }, [id, client]); + + useEffect(() => { + if (!id) { + setErrorFiles(new Error("Vector Store ID is missing.")); + setIsLoadingFiles(false); + return; + } + const fetchFiles = async () => { + setIsLoadingFiles(true); + setErrorFiles(null); + try { + const result = await client.vectorStores.files.list(id as any); + setFiles((result as any).data); + } catch (err) { + setErrorFiles( + err instanceof Error ? err : new Error("Failed to load files."), + ); + } finally { + setIsLoadingFiles(false); + } + }; + fetchFiles(); + }, [id]); + + return ( + + ); +} diff --git a/llama_stack/ui/app/logs/vector-stores/layout.tsx b/llama_stack/ui/app/logs/vector-stores/layout.tsx new file mode 100644 index 000000000..9245f5486 --- /dev/null +++ b/llama_stack/ui/app/logs/vector-stores/layout.tsx @@ -0,0 +1,16 @@ +"use client"; + +import React from "react"; +import LogsLayout from "@/components/layout/logs-layout"; + +export default function VectorStoresLayout({ + children, +}: { + children: React.ReactNode; +}) { + return ( + + {children} + + ); +} diff --git a/llama_stack/ui/app/logs/vector-stores/page.tsx b/llama_stack/ui/app/logs/vector-stores/page.tsx new file mode 100644 index 000000000..29e1fabd6 --- /dev/null +++ b/llama_stack/ui/app/logs/vector-stores/page.tsx @@ -0,0 +1,121 @@ +"use client"; + +import React from "react"; +import { useAuthClient } from "@/hooks/use-auth-client"; +import type { + ListVectorStoresResponse, + VectorStore, +} from "llama-stack-client/resources/vector-stores/vector-stores"; +import { useRouter } from "next/navigation"; +import { usePagination } from "@/hooks/use-pagination"; +import { + Table, + TableBody, + TableCaption, + TableCell, + TableHead, + TableHeader, + TableRow, +} from "@/components/ui/table"; +import { Skeleton } from "@/components/ui/skeleton"; + +export default function VectorStoresPage() { + const client = useAuthClient(); + const router = useRouter(); + const { + data: stores, + status, + hasMore, + error, + loadMore, + } = usePagination({ + limit: 20, + order: "desc", + fetchFunction: async (client, params) => { + const response = await client.vectorStores.list({ + after: params.after, + limit: params.limit, + order: params.order, + } as any); + return response as ListVectorStoresResponse; + }, + errorMessagePrefix: "vector stores", + }); + + // Auto-load all pages for infinite scroll behavior (like Responses) + React.useEffect(() => { + if (status === "idle" && hasMore) { + loadMore(); + } + }, [status, hasMore, loadMore]); + + if (status === "loading") { + return ( +
+ + + +
+ ); + } + + if (status === "error") { + return
Error: {error?.message}
; + } + + if (!stores || stores.length === 0) { + return

No vector stores found.

; + } + + return ( +
+ + + + ID + Name + Created + Completed + Cancelled + Failed + In Progress + Total + Usage Bytes + Provider ID + Provider Vector DB ID + + + + {stores.map((store) => { + const fileCounts = store.file_counts; + const metadata = store.metadata || {}; + const providerId = metadata.provider_id ?? ""; + const providerDbId = metadata.provider_vector_db_id ?? ""; + + return ( + router.push(`/logs/vector-stores/${store.id}`)} + className="cursor-pointer hover:bg-muted/50" + > + {store.id} + {store.name} + + {new Date(store.created_at * 1000).toLocaleString()} + + {fileCounts.completed} + {fileCounts.cancelled} + {fileCounts.failed} + {fileCounts.in_progress} + {fileCounts.total} + {store.usage_bytes} + {providerId} + {providerDbId} + + ); + })} + +
+
+ ); +} diff --git a/llama_stack/ui/components/layout/app-sidebar.tsx b/llama_stack/ui/components/layout/app-sidebar.tsx index 1c53d6cc5..532e43dbd 100644 --- a/llama_stack/ui/components/layout/app-sidebar.tsx +++ b/llama_stack/ui/components/layout/app-sidebar.tsx @@ -1,6 +1,11 @@ "use client"; -import { MessageSquareText, MessagesSquare, MoveUpRight } from "lucide-react"; +import { + MessageSquareText, + MessagesSquare, + MoveUpRight, + Database, +} from "lucide-react"; import Link from "next/link"; import { usePathname } from "next/navigation"; import { cn } from "@/lib/utils"; @@ -28,6 +33,11 @@ const logItems = [ url: "/logs/responses", icon: MessagesSquare, }, + { + title: "Vector Stores", + url: "/logs/vector-stores", + icon: Database, + }, { title: "Documentation", url: "https://llama-stack.readthedocs.io/en/latest/references/api_reference/index.html", @@ -57,13 +67,13 @@ export function AppSidebar() { className={cn( "justify-start", isActive && - "bg-gray-200 hover:bg-gray-200 text-primary hover:text-primary", + "bg-gray-200 dark:bg-gray-700 hover:bg-gray-200 dark:hover:bg-gray-700 text-gray-900 dark:text-gray-100", )} > diff --git a/llama_stack/ui/components/layout/detail-layout.tsx b/llama_stack/ui/components/layout/detail-layout.tsx index 58b912703..3013195a2 100644 --- a/llama_stack/ui/components/layout/detail-layout.tsx +++ b/llama_stack/ui/components/layout/detail-layout.tsx @@ -93,7 +93,9 @@ export function PropertyItem({ > {label}:{" "} {typeof value === "string" || typeof value === "number" ? ( - {value} + + {value} + ) : ( value )} @@ -112,7 +114,9 @@ export function PropertiesCard({ children }: PropertiesCardProps) { Properties -
    {children}
+
    + {children} +
); diff --git a/llama_stack/ui/components/ui/message-components.tsx b/llama_stack/ui/components/ui/message-components.tsx index 50ccd623e..39cb570b7 100644 --- a/llama_stack/ui/components/ui/message-components.tsx +++ b/llama_stack/ui/components/ui/message-components.tsx @@ -17,10 +17,10 @@ export const MessageBlock: React.FC = ({ }) => { return (
-

+

{label} {labelDetail && ( - + {labelDetail} )} diff --git a/llama_stack/ui/components/vector-stores/vector-store-detail.tsx b/llama_stack/ui/components/vector-stores/vector-store-detail.tsx new file mode 100644 index 000000000..7c5c91dd3 --- /dev/null +++ b/llama_stack/ui/components/vector-stores/vector-store-detail.tsx @@ -0,0 +1,128 @@ +"use client"; + +import type { VectorStore } from "llama-stack-client/resources/vector-stores/vector-stores"; +import type { VectorStoreFile } from "llama-stack-client/resources/vector-stores/files"; +import { Card, CardContent, CardHeader, CardTitle } from "@/components/ui/card"; +import { Skeleton } from "@/components/ui/skeleton"; +import { + DetailLoadingView, + DetailErrorView, + DetailNotFoundView, + DetailLayout, + PropertiesCard, + PropertyItem, +} from "@/components/layout/detail-layout"; +import { + Table, + TableBody, + TableCaption, + TableCell, + TableHead, + TableHeader, + TableRow, +} from "@/components/ui/table"; + +interface VectorStoreDetailViewProps { + store: VectorStore | null; + files: VectorStoreFile[]; + isLoadingStore: boolean; + isLoadingFiles: boolean; + errorStore: Error | null; + errorFiles: Error | null; + id: string; +} + +export function VectorStoreDetailView({ + store, + files, + isLoadingStore, + isLoadingFiles, + errorStore, + errorFiles, + id, +}: VectorStoreDetailViewProps) { + const title = "Vector Store Details"; + + if (errorStore) { + return ; + } + if (isLoadingStore) { + return ; + } + if (!store) { + return ; + } + + const mainContent = ( + <> + + + Files + + + {isLoadingFiles ? ( + + ) : errorFiles ? ( +

+ Error loading files: {errorFiles.message} +
+ ) : files.length > 0 ? ( + + Files in this vector store + + + ID + Status + Created + Usage Bytes + + + + {files.map((file) => ( + + {file.id} + {file.status} + + {new Date(file.created_at * 1000).toLocaleString()} + + {file.usage_bytes} + + ))} + +
+ ) : ( +

+ No files in this vector store. +

+ )} + + + + ); + + const sidebar = ( + + + + + + + + + + + ); + + return ( + + ); +} diff --git a/llama_stack/ui/package-lock.json b/llama_stack/ui/package-lock.json index 8fd5fb56c..158569241 100644 --- a/llama_stack/ui/package-lock.json +++ b/llama_stack/ui/package-lock.json @@ -15,7 +15,7 @@ "@radix-ui/react-tooltip": "^1.2.6", "class-variance-authority": "^0.7.1", "clsx": "^2.1.1", - "llama-stack-client": "0.2.13", + "llama-stack-client": "^0.2.14", "lucide-react": "^0.510.0", "next": "15.3.3", "next-auth": "^4.24.11", @@ -676,406 +676,6 @@ "tslib": "^2.4.0" } }, - "node_modules/@esbuild/aix-ppc64": { - "version": "0.25.5", - "resolved": "https://registry.npmjs.org/@esbuild/aix-ppc64/-/aix-ppc64-0.25.5.tgz", - "integrity": "sha512-9o3TMmpmftaCMepOdA5k/yDw8SfInyzWWTjYTFCX3kPSDJMROQTb8jg+h9Cnwnmm1vOzvxN7gIfB5V2ewpjtGA==", - "cpu": [ - "ppc64" - ], - "license": "MIT", - "optional": true, - "os": [ - "aix" - ], - "engines": { - "node": ">=18" - } - }, - "node_modules/@esbuild/android-arm": { - 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"version": "0.2.13", - "resolved": "https://registry.npmjs.org/llama-stack-client/-/llama-stack-client-0.2.13.tgz", - "integrity": "sha512-R1rTFLwgUimr+KjEUkzUvFL6vLASwS9qj3UDSVkJ5BmrKAs5GwVAMeL7yZaTBXGuPUVh124WSlC4d9H0FjWqLA==", + "version": "0.2.14", + "resolved": "https://registry.npmjs.org/llama-stack-client/-/llama-stack-client-0.2.14.tgz", + "integrity": "sha512-bVU3JHp+EPEKR0Vb9vcd9ZyQj/72jSDuptKLwOXET9WrkphIQ8xuW5ueecMTgq8UEls3lwB3HiZM2cDOR9eDsQ==", + "license": "Apache-2.0", "dependencies": { "@types/node": "^18.11.18", "@types/node-fetch": "^2.6.4", @@ -9547,8 +9110,7 @@ "agentkeepalive": "^4.2.1", "form-data-encoder": "1.7.2", "formdata-node": "^4.3.2", - "node-fetch": "^2.6.7", - "tsx": "^4.19.2" + "node-fetch": "^2.6.7" } }, "node_modules/llama-stack-client/node_modules/@types/node": { @@ -11148,6 +10710,7 @@ "version": "1.0.0", "resolved": "https://registry.npmjs.org/resolve-pkg-maps/-/resolve-pkg-maps-1.0.0.tgz", "integrity": "sha512-seS2Tj26TBVOC2NIc2rOe2y2ZO7efxITtLZcGSOnHHNOQ7CkiUBfw0Iw2ck6xkIhPwLhKNLS8BO+hEpngQlqzw==", + "dev": true, "license": "MIT", "funding": { "url": "https://github.com/privatenumber/resolve-pkg-maps?sponsor=1" @@ -12198,25 +11761,6 @@ "integrity": "sha512-oJFu94HQb+KVduSUQL7wnpmqnfmLsOA/nAh6b6EH0wCEoK0/mPeXU6c3wKDV83MkOuHPRHtSXKKU99IBazS/2w==", "license": "0BSD" }, - "node_modules/tsx": { - "version": "4.19.4", - "resolved": "https://registry.npmjs.org/tsx/-/tsx-4.19.4.tgz", - "integrity": "sha512-gK5GVzDkJK1SI1zwHf32Mqxf2tSJkNx+eYcNly5+nHvWqXUJYUkWBQtKauoESz3ymezAI++ZwT855x5p5eop+Q==", - "license": "MIT", - "dependencies": { - "esbuild": "~0.25.0", - "get-tsconfig": "^4.7.5" - }, - "bin": { - "tsx": "dist/cli.mjs" - }, - "engines": { - "node": ">=18.0.0" - }, - "optionalDependencies": { - "fsevents": "~2.3.3" - } - }, "node_modules/tw-animate-css": { "version": "1.2.9", "resolved": "https://registry.npmjs.org/tw-animate-css/-/tw-animate-css-1.2.9.tgz", diff --git a/llama_stack/ui/package.json b/llama_stack/ui/package.json index 9524ce0a5..b38efe309 100644 --- a/llama_stack/ui/package.json +++ b/llama_stack/ui/package.json @@ -20,7 +20,7 @@ "@radix-ui/react-tooltip": "^1.2.6", "class-variance-authority": "^0.7.1", "clsx": "^2.1.1", - "llama-stack-client": "0.2.13", + "llama-stack-client": "^0.2.14", "lucide-react": "^0.510.0", "next": "15.3.3", "next-auth": "^4.24.11", From 618ccea0908bc03914f71fdb6aca5062c8f01699 Mon Sep 17 00:00:00 2001 From: Mark Campbell Date: Mon, 14 Jul 2025 14:11:34 +0100 Subject: [PATCH 27/34] feat: add input validation for search mode of rag query config (#2275) # What does this PR do? Adds input validation for mode in RagQueryConfig This will prevent users from inputting search modes other than `vector` and `keyword` for the time being with `hybrid` to follow when that functionality is implemented. ## Test Plan [Describe the tests you ran to verify your changes with result summaries. *Provide clear instructions so the plan can be easily re-executed.*] ``` # Check out this PR and enter the LS directory uv sync --extra dev ``` Run the quickstart [example](https://llama-stack.readthedocs.io/en/latest/getting_started/#step-3-run-the-demo) Alter the Agent to include a query_config ``` agent = Agent( client, model=model_id, instructions="You are a helpful assistant", tools=[ { "name": "builtin::rag/knowledge_search", "args": { "vector_db_ids": [vector_db_id], "query_config": { "mode": "i-am-not-vector", # Test for non valid search mode "max_chunks": 6 } }, } ], ) ``` Ensure you get the following error: ``` 400: {'errors': [{'loc': ['mode'], 'msg': "Value error, mode must be either 'vector' or 'keyword' if supported by the vector_io provider", 'type': 'value_error'}]} ``` ## Running unit tests ``` uv sync --extra dev uv run pytest tests/unit/rag/test_rag_query.py -v ``` [//]: # (## Documentation) --- docs/_static/llama-stack-spec.html | 13 ++++++++++++- docs/_static/llama-stack-spec.yaml | 14 +++++++++++++- llama_stack/apis/tools/rag_tool.py | 16 +++++++++++++++- tests/unit/rag/test_rag_query.py | 12 ++++++++++++ 4 files changed, 52 insertions(+), 3 deletions(-) diff --git a/docs/_static/llama-stack-spec.html b/docs/_static/llama-stack-spec.html index 8021e0e55..6794d1fbb 100644 --- a/docs/_static/llama-stack-spec.html +++ b/docs/_static/llama-stack-spec.html @@ -14796,7 +14796,8 @@ "description": "Template for formatting each retrieved chunk in the context. Available placeholders: {index} (1-based chunk ordinal), {chunk.content} (chunk content string), {metadata} (chunk metadata dict). Default: \"Result {index}\\nContent: {chunk.content}\\nMetadata: {metadata}\\n\"" }, "mode": { - "type": "string", + "$ref": "#/components/schemas/RAGSearchMode", + "default": "vector", "description": "Search mode for retrieval—either \"vector\", \"keyword\", or \"hybrid\". Default \"vector\"." }, "ranker": { @@ -14831,6 +14832,16 @@ } } }, + "RAGSearchMode": { + "type": "string", + "enum": [ + "vector", + "keyword", + "hybrid" + ], + "title": "RAGSearchMode", + "description": "Search modes for RAG query retrieval: - VECTOR: Uses vector similarity search for semantic matching - KEYWORD: Uses keyword-based search for exact matching - HYBRID: Combines both vector and keyword search for better results" + }, "RRFRanker": { "type": "object", "properties": { diff --git a/docs/_static/llama-stack-spec.yaml b/docs/_static/llama-stack-spec.yaml index a18474646..548c5a988 100644 --- a/docs/_static/llama-stack-spec.yaml +++ b/docs/_static/llama-stack-spec.yaml @@ -10346,7 +10346,8 @@ components: content string), {metadata} (chunk metadata dict). Default: "Result {index}\nContent: {chunk.content}\nMetadata: {metadata}\n" mode: - type: string + $ref: '#/components/schemas/RAGSearchMode' + default: vector description: >- Search mode for retrieval—either "vector", "keyword", or "hybrid". Default "vector". @@ -10373,6 +10374,17 @@ components: mapping: default: '#/components/schemas/DefaultRAGQueryGeneratorConfig' llm: '#/components/schemas/LLMRAGQueryGeneratorConfig' + RAGSearchMode: + type: string + enum: + - vector + - keyword + - hybrid + title: RAGSearchMode + description: >- + Search modes for RAG query retrieval: - VECTOR: Uses vector similarity search + for semantic matching - KEYWORD: Uses keyword-based search for exact matching + - HYBRID: Combines both vector and keyword search for better results RRFRanker: type: object properties: diff --git a/llama_stack/apis/tools/rag_tool.py b/llama_stack/apis/tools/rag_tool.py index d497fe1a7..cfaa49488 100644 --- a/llama_stack/apis/tools/rag_tool.py +++ b/llama_stack/apis/tools/rag_tool.py @@ -87,6 +87,20 @@ class RAGQueryGenerator(Enum): custom = "custom" +@json_schema_type +class RAGSearchMode(Enum): + """ + Search modes for RAG query retrieval: + - VECTOR: Uses vector similarity search for semantic matching + - KEYWORD: Uses keyword-based search for exact matching + - HYBRID: Combines both vector and keyword search for better results + """ + + VECTOR = "vector" + KEYWORD = "keyword" + HYBRID = "hybrid" + + @json_schema_type class DefaultRAGQueryGeneratorConfig(BaseModel): type: Literal["default"] = "default" @@ -128,7 +142,7 @@ class RAGQueryConfig(BaseModel): max_tokens_in_context: int = 4096 max_chunks: int = 5 chunk_template: str = "Result {index}\nContent: {chunk.content}\nMetadata: {metadata}\n" - mode: str | None = None + mode: RAGSearchMode | None = RAGSearchMode.VECTOR ranker: Ranker | None = Field(default=None) # Only used for hybrid mode @field_validator("chunk_template") diff --git a/tests/unit/rag/test_rag_query.py b/tests/unit/rag/test_rag_query.py index b2baa744a..ad155c205 100644 --- a/tests/unit/rag/test_rag_query.py +++ b/tests/unit/rag/test_rag_query.py @@ -8,6 +8,7 @@ from unittest.mock import AsyncMock, MagicMock import pytest +from llama_stack.apis.tools.rag_tool import RAGQueryConfig from llama_stack.apis.vector_io import ( Chunk, ChunkMetadata, @@ -58,3 +59,14 @@ class TestRagQuery: ) assert expected_metadata_string in result.content[1].text assert result.content is not None + + async def test_query_raises_incorrect_mode(self): + with pytest.raises(ValueError): + RAGQueryConfig(mode="invalid_mode") + + @pytest.mark.asyncio + async def test_query_accepts_valid_modes(self): + RAGQueryConfig() # Test default (vector) + RAGQueryConfig(mode="vector") # Test vector + RAGQueryConfig(mode="keyword") # Test keyword + RAGQueryConfig(mode="hybrid") # Test hybrid From 77d2c8e95d95625e506d7ae06105e213b69351d9 Mon Sep 17 00:00:00 2001 From: Sumanth Kamenani Date: Mon, 14 Jul 2025 12:53:13 -0400 Subject: [PATCH 28/34] docs: clarify run.yaml files are starting points for customization (#2746) # What does this PR do? This PR improves documentation clarity around run.yaml file usage. It adds comprehensive guidance to help users understand that generated run.yaml files are templates meant to be customized for production use, not used as-is. ## Changes - Add new documentation section on customizing run.yaml files - Clarify that generated run.yaml files are templates, not production configs - Add guidance on customization best practices and common scenarios - Update existing documentation to reference customization guide - Improve clarity around run.yaml file usage for better user experience ## Test Plan - Verified new documentation file exists at correct location - Confirmed documentation is properly integrated into the toctree structure - Checked all internal links use correct paths and reference existing files - Validated references are added to relevant existing documentation files - Documentation build testing will be handled by CI environment --- docs/source/distributions/building_distro.md | 4 ++ docs/source/distributions/configuration.md | 4 ++ .../distributions/customizing_run_yaml.md | 40 +++++++++++++++++++ docs/source/distributions/index.md | 1 + .../getting_started/detailed_tutorial.md | 2 +- 5 files changed, 50 insertions(+), 1 deletion(-) create mode 100644 docs/source/distributions/customizing_run_yaml.md diff --git a/docs/source/distributions/building_distro.md b/docs/source/distributions/building_distro.md index f24974dd3..cd2c6b6a8 100644 --- a/docs/source/distributions/building_distro.md +++ b/docs/source/distributions/building_distro.md @@ -145,6 +145,10 @@ $ llama stack build --template starter ... You can now edit ~/.llama/distributions/llamastack-starter/starter-run.yaml and run `llama stack run ~/.llama/distributions/llamastack-starter/starter-run.yaml` ``` + +```{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). +``` ::: :::{tab-item} Building from Scratch diff --git a/docs/source/distributions/configuration.md b/docs/source/distributions/configuration.md index 4709cb8c6..9548780c6 100644 --- a/docs/source/distributions/configuration.md +++ b/docs/source/distributions/configuration.md @@ -2,6 +2,10 @@ The Llama Stack runtime configuration is specified as a YAML file. Here is a simplified version of an example configuration file for the Ollama distribution: +```{note} +The default `run.yaml` files generated by templates are starting points for your configuration. For guidance on customizing these files for your specific needs, see [Customizing Your run.yaml Configuration](customizing_run_yaml.md). +``` + ```{dropdown} 👋 Click here for a Sample Configuration File ```yaml diff --git a/docs/source/distributions/customizing_run_yaml.md b/docs/source/distributions/customizing_run_yaml.md new file mode 100644 index 000000000..10067bab7 --- /dev/null +++ b/docs/source/distributions/customizing_run_yaml.md @@ -0,0 +1,40 @@ +# Customizing run.yaml Files + +The `run.yaml` files generated by Llama Stack templates are **starting points** designed to be customized for your specific needs. They are not meant to be used as-is in production environments. + +## Key Points + +- **Templates are starting points**: Generated `run.yaml` files contain defaults for development/testing +- **Customization expected**: Update URLs, credentials, models, and settings for your environment +- **Version control separately**: Keep customized configs in your own repository +- **Environment-specific**: Create different configurations for dev, staging, production + +## What You Can Customize + +You can customize: +- **Provider endpoints**: Change `http://localhost:8000` to your actual servers +- **Swap providers**: Replace default providers (e.g., swap Tavily with Brave for search) +- **Storage paths**: Move from `/tmp/` to production directories +- **Authentication**: Add API keys, SSL, timeouts +- **Models**: Different model sizes for dev vs prod +- **Database settings**: Switch from SQLite to PostgreSQL +- **Tool configurations**: Add custom tools and integrations + +## Best Practices + +- Use environment variables for secrets and environment-specific values +- Create separate `run.yaml` files for different environments (dev, staging, prod) +- Document your changes with comments +- Test configurations before deployment +- Keep your customized configs in version control + +Example structure: +``` +your-project/ +├── configs/ +│ ├── dev-run.yaml +│ ├── prod-run.yaml +└── README.md +``` + +The goal is to take the generated template and adapt it to your specific infrastructure and operational needs. \ No newline at end of file diff --git a/docs/source/distributions/index.md b/docs/source/distributions/index.md index 103a6131f..600eec3a1 100644 --- a/docs/source/distributions/index.md +++ b/docs/source/distributions/index.md @@ -9,6 +9,7 @@ This section provides an overview of the distributions available in Llama Stack. importing_as_library configuration +customizing_run_yaml list_of_distributions kubernetes_deployment building_distro diff --git a/docs/source/getting_started/detailed_tutorial.md b/docs/source/getting_started/detailed_tutorial.md index 35cb7f02e..97e7df774 100644 --- a/docs/source/getting_started/detailed_tutorial.md +++ b/docs/source/getting_started/detailed_tutorial.md @@ -54,7 +54,7 @@ Llama Stack is a server that exposes multiple APIs, you connect with it using th You can use Python to build and run the Llama Stack server, which is useful for testing and development. Llama Stack uses a [YAML configuration file](../distributions/configuration.md) to specify the stack setup, -which defines the providers and their settings. +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.md). Now let's build 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. From a7ed86181c8b823ca13af0c911be694e49899be9 Mon Sep 17 00:00:00 2001 From: Derek Higgins Date: Mon, 14 Jul 2025 18:58:23 +0100 Subject: [PATCH 29/34] fix(faiss): Delete file contents from kvstore (#2686) Remove both the metadata and content from the kvstore when a file is being removed from the vector store. Closes: #2685 Also add faiss provider to openai_vector_stores test suite --------- Signed-off-by: Derek Higgins Co-authored-by: raghotham --- .../providers/inline/vector_io/faiss/faiss.py | 21 +++++++-- tests/unit/providers/vector_io/conftest.py | 44 ++++++++++++++++++- .../test_vector_io_openai_vector_stores.py | 6 ++- 3 files changed, 63 insertions(+), 8 deletions(-) diff --git a/llama_stack/providers/inline/vector_io/faiss/faiss.py b/llama_stack/providers/inline/vector_io/faiss/faiss.py index 62a98413d..0306d9156 100644 --- a/llama_stack/providers/inline/vector_io/faiss/faiss.py +++ b/llama_stack/providers/inline/vector_io/faiss/faiss.py @@ -267,6 +267,7 @@ class FaissVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtocolPr assert self.kvstore is not None key = f"{OPENAI_VECTOR_STORES_PREFIX}{store_id}" await self.kvstore.set(key=key, value=json.dumps(store_info)) + self.openai_vector_stores[store_id] = store_info async def _load_openai_vector_stores(self) -> dict[str, dict[str, Any]]: """Load all vector store metadata from kvstore.""" @@ -286,17 +287,20 @@ class FaissVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtocolPr assert self.kvstore is not None key = f"{OPENAI_VECTOR_STORES_PREFIX}{store_id}" await self.kvstore.set(key=key, value=json.dumps(store_info)) + self.openai_vector_stores[store_id] = store_info async def _delete_openai_vector_store_from_storage(self, store_id: str) -> None: """Delete vector store metadata from kvstore.""" assert self.kvstore is not None key = f"{OPENAI_VECTOR_STORES_PREFIX}{store_id}" await self.kvstore.delete(key) + if store_id in self.openai_vector_stores: + del self.openai_vector_stores[store_id] async def _save_openai_vector_store_file( self, store_id: str, file_id: str, file_info: dict[str, Any], file_contents: list[dict[str, Any]] ) -> None: - """Save vector store file metadata to kvstore.""" + """Save vector store file data to kvstore.""" assert self.kvstore is not None key = f"{OPENAI_VECTOR_STORES_FILES_PREFIX}{store_id}:{file_id}" await self.kvstore.set(key=key, value=json.dumps(file_info)) @@ -324,7 +328,16 @@ class FaissVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtocolPr await self.kvstore.set(key=key, value=json.dumps(file_info)) async def _delete_openai_vector_store_file_from_storage(self, store_id: str, file_id: str) -> None: - """Delete vector store file metadata from kvstore.""" + """Delete vector store data from kvstore.""" assert self.kvstore is not None - key = f"{OPENAI_VECTOR_STORES_FILES_PREFIX}{store_id}:{file_id}" - await self.kvstore.delete(key) + + keys_to_delete = [ + f"{OPENAI_VECTOR_STORES_FILES_PREFIX}{store_id}:{file_id}", + f"{OPENAI_VECTOR_STORES_FILES_CONTENTS_PREFIX}{store_id}:{file_id}", + ] + for key in keys_to_delete: + try: + await self.kvstore.delete(key) + except Exception as e: + logger.warning(f"Failed to delete key {key}: {e}") + continue diff --git a/tests/unit/providers/vector_io/conftest.py b/tests/unit/providers/vector_io/conftest.py index 4a9639326..9f86f877d 100644 --- a/tests/unit/providers/vector_io/conftest.py +++ b/tests/unit/providers/vector_io/conftest.py @@ -12,6 +12,8 @@ from pymilvus import MilvusClient, connections from llama_stack.apis.vector_dbs import VectorDB from llama_stack.apis.vector_io import Chunk, ChunkMetadata +from llama_stack.providers.inline.vector_io.faiss.config import FaissVectorIOConfig +from llama_stack.providers.inline.vector_io.faiss.faiss import FaissIndex, FaissVectorIOAdapter from llama_stack.providers.inline.vector_io.milvus.config import MilvusVectorIOConfig, SqliteKVStoreConfig from llama_stack.providers.inline.vector_io.sqlite_vec import SQLiteVectorIOConfig from llama_stack.providers.inline.vector_io.sqlite_vec.sqlite_vec import SQLiteVecIndex, SQLiteVecVectorIOAdapter @@ -90,7 +92,7 @@ def sample_embeddings_with_metadata(sample_chunks_with_metadata): return np.array([np.random.rand(EMBEDDING_DIMENSION).astype(np.float32) for _ in sample_chunks_with_metadata]) -@pytest.fixture(params=["milvus", "sqlite_vec"]) +@pytest.fixture(params=["milvus", "sqlite_vec", "faiss"]) def vector_provider(request): return request.param @@ -116,7 +118,7 @@ async def unique_kvstore_config(tmp_path_factory): @pytest.fixture(scope="session") def sqlite_vec_db_path(tmp_path_factory): - db_path = str(tmp_path_factory.getbasetemp() / "test.db") + db_path = str(tmp_path_factory.getbasetemp() / "test_sqlite_vec.db") return db_path @@ -198,11 +200,49 @@ async def milvus_vec_adapter(milvus_vec_db_path, mock_inference_api): await adapter.shutdown() +@pytest.fixture +def faiss_vec_db_path(tmp_path_factory): + db_path = str(tmp_path_factory.getbasetemp() / "test_faiss.db") + return db_path + + +@pytest.fixture +async def faiss_vec_index(embedding_dimension): + index = FaissIndex(embedding_dimension) + yield index + await index.delete() + + +@pytest.fixture +async def faiss_vec_adapter(unique_kvstore_config, mock_inference_api, embedding_dimension): + config = FaissVectorIOConfig( + kvstore=unique_kvstore_config, + ) + adapter = FaissVectorIOAdapter( + config=config, + inference_api=mock_inference_api, + files_api=None, + ) + await adapter.initialize() + await adapter.register_vector_db( + VectorDB( + identifier=f"faiss_test_collection_{np.random.randint(1e6)}", + provider_id="test_provider", + embedding_model="test_model", + embedding_dimension=embedding_dimension, + ) + ) + yield adapter + await adapter.shutdown() + + @pytest.fixture def vector_io_adapter(vector_provider, request): """Returns the appropriate vector IO adapter based on the provider parameter.""" if vector_provider == "milvus": return request.getfixturevalue("milvus_vec_adapter") + elif vector_provider == "faiss": + return request.getfixturevalue("faiss_vec_adapter") else: return request.getfixturevalue("sqlite_vec_adapter") diff --git a/tests/unit/providers/vector_io/test_vector_io_openai_vector_stores.py b/tests/unit/providers/vector_io/test_vector_io_openai_vector_stores.py index 97e2f085e..bf7663d2e 100644 --- a/tests/unit/providers/vector_io/test_vector_io_openai_vector_stores.py +++ b/tests/unit/providers/vector_io/test_vector_io_openai_vector_stores.py @@ -94,7 +94,7 @@ async def test_query_unregistered_raises(vector_io_adapter): async def test_insert_chunks_calls_underlying_index(vector_io_adapter): fake_index = AsyncMock() - vector_io_adapter._get_and_cache_vector_db_index = AsyncMock(return_value=fake_index) + vector_io_adapter.cache["db1"] = fake_index chunks = ["chunk1", "chunk2"] await vector_io_adapter.insert_chunks("db1", chunks) @@ -112,7 +112,7 @@ async def test_insert_chunks_missing_db_raises(vector_io_adapter): async def test_query_chunks_calls_underlying_index_and_returns(vector_io_adapter): expected = QueryChunksResponse(chunks=[Chunk(content="c1")], scores=[0.1]) fake_index = AsyncMock(query_chunks=AsyncMock(return_value=expected)) - vector_io_adapter._get_and_cache_vector_db_index = AsyncMock(return_value=fake_index) + vector_io_adapter.cache["db1"] = fake_index response = await vector_io_adapter.query_chunks("db1", "my_query", {"param": 1}) @@ -286,5 +286,7 @@ async def test_delete_openai_vector_store_file_from_storage(vector_io_adapter, t await vector_io_adapter._save_openai_vector_store_file(store_id, file_id, file_info, file_contents) await vector_io_adapter._delete_openai_vector_store_file_from_storage(store_id, file_id) + loaded_file_info = await vector_io_adapter._load_openai_vector_store_file(store_id, file_id) + assert loaded_file_info == {} loaded_contents = await vector_io_adapter._load_openai_vector_store_file_contents(store_id, file_id) assert loaded_contents == [] From f731f369a2be1ad1d28ff8b3e1b9f59ae261451e Mon Sep 17 00:00:00 2001 From: Matthew Farrellee Date: Mon, 14 Jul 2025 14:38:53 -0400 Subject: [PATCH 30/34] feat: add infrastructure to allow inference model discovery (#2710) # What does this PR do? inference providers each have a static list of supported / known models. some also have access to a dynamic list of currently available models. this change gives prodivers using the ModelRegistryHelper the ability to combine their static and dynamic lists. for instance, OpenAIInferenceAdapter can implement ``` def query_available_models(self) -> list[str]: return [entry.model for entry in self.openai_client.models.list()] ``` to augment its static list w/ a current list from openai. ## Test Plan scripts/unit-test.sh --- .../utils/inference/model_registry.py | 33 ++++++- .../providers/utils/test_model_registry.py | 91 +++++++++++++++++++ 2 files changed, 122 insertions(+), 2 deletions(-) diff --git a/llama_stack/providers/utils/inference/model_registry.py b/llama_stack/providers/utils/inference/model_registry.py index c2fc13e07..801b8ea06 100644 --- a/llama_stack/providers/utils/inference/model_registry.py +++ b/llama_stack/providers/utils/inference/model_registry.py @@ -83,9 +83,37 @@ class ModelRegistryHelper(ModelsProtocolPrivate): def get_llama_model(self, provider_model_id: str) -> str | None: return self.provider_id_to_llama_model_map.get(provider_model_id, None) + async def check_model_availability(self, model: str) -> bool: + """ + Check if a specific model is available from the provider (non-static check). + + This is for subclassing purposes, so providers can check if a specific + model is currently available for use through dynamic means (e.g., API calls). + + This method should NOT check statically configured model entries in + `self.alias_to_provider_id_map` - that is handled separately in register_model. + + Default implementation returns False (no dynamic models available). + + :param model: The model identifier to check. + :return: True if the model is available dynamically, False otherwise. + """ + return False + async def register_model(self, model: Model) -> Model: - if not (supported_model_id := self.get_provider_model_id(model.provider_resource_id)): - raise UnsupportedModelError(model.provider_resource_id, self.alias_to_provider_id_map.keys()) + # Check if model is supported in static configuration + supported_model_id = self.get_provider_model_id(model.provider_resource_id) + + # If not found in static config, check if it's available dynamically from provider + if not supported_model_id: + if await self.check_model_availability(model.provider_resource_id): + supported_model_id = model.provider_resource_id + else: + # note: we cannot provide a complete list of supported models without + # getting a complete list from the provider, so we return "..." + all_supported_models = [*self.alias_to_provider_id_map.keys(), "..."] + raise UnsupportedModelError(model.provider_resource_id, all_supported_models) + provider_resource_id = self.get_provider_model_id(model.model_id) if model.model_type == ModelType.embedding: # embedding models are always registered by their provider model id and does not need to be mapped to a llama model @@ -114,6 +142,7 @@ class ModelRegistryHelper(ModelsProtocolPrivate): ALL_HUGGINGFACE_REPOS_TO_MODEL_DESCRIPTOR[llama_model] ) + # Register the model alias, ensuring it maps to the correct provider model id self.alias_to_provider_id_map[model.model_id] = supported_model_id return model diff --git a/tests/unit/providers/utils/test_model_registry.py b/tests/unit/providers/utils/test_model_registry.py index e11f95d49..1a1705961 100644 --- a/tests/unit/providers/utils/test_model_registry.py +++ b/tests/unit/providers/utils/test_model_registry.py @@ -87,6 +87,37 @@ def helper(known_provider_model: ProviderModelEntry, known_provider_model2: Prov return ModelRegistryHelper([known_provider_model, known_provider_model2]) +class MockModelRegistryHelperWithDynamicModels(ModelRegistryHelper): + """Test helper that simulates a provider with dynamically available models.""" + + def __init__(self, model_entries: list[ProviderModelEntry], available_models: list[str]): + super().__init__(model_entries) + self._available_models = available_models + + async def check_model_availability(self, model: str) -> bool: + return model in self._available_models + + +@pytest.fixture +def dynamic_model() -> Model: + """A model that's not in static config but available dynamically.""" + return Model( + provider_id="provider", + identifier="dynamic-model", + provider_resource_id="dynamic-provider-id", + ) + + +@pytest.fixture +def helper_with_dynamic_models( + known_provider_model: ProviderModelEntry, known_provider_model2: ProviderModelEntry, dynamic_model: Model +) -> MockModelRegistryHelperWithDynamicModels: + """Helper that includes dynamically available models.""" + return MockModelRegistryHelperWithDynamicModels( + [known_provider_model, known_provider_model2], [dynamic_model.provider_resource_id] + ) + + async def test_lookup_unknown_model(helper: ModelRegistryHelper, unknown_model: Model) -> None: assert helper.get_provider_model_id(unknown_model.model_id) is None @@ -151,3 +182,63 @@ async def test_unregister_model_during_init(helper: ModelRegistryHelper, known_m assert helper.get_provider_model_id(known_model.provider_resource_id) == known_model.provider_model_id await helper.unregister_model(known_model.provider_resource_id) assert helper.get_provider_model_id(known_model.provider_resource_id) is None + + +async def test_register_model_from_check_model_availability( + helper_with_dynamic_models: MockModelRegistryHelperWithDynamicModels, dynamic_model: Model +) -> None: + """Test that models returned by check_model_availability can be registered.""" + # Verify the model is not in static config + assert helper_with_dynamic_models.get_provider_model_id(dynamic_model.provider_resource_id) is None + + # But it should be available via check_model_availability + is_available = await helper_with_dynamic_models.check_model_availability(dynamic_model.provider_resource_id) + assert is_available + + # Registration should succeed + registered_model = await helper_with_dynamic_models.register_model(dynamic_model) + assert registered_model == dynamic_model + + # Model should now be registered and accessible + assert ( + helper_with_dynamic_models.get_provider_model_id(dynamic_model.model_id) == dynamic_model.provider_resource_id + ) + + +async def test_register_model_not_in_static_or_dynamic( + helper_with_dynamic_models: MockModelRegistryHelperWithDynamicModels, unknown_model: Model +) -> None: + """Test that models not in static config or dynamic models are rejected.""" + # Verify the model is not in static config + assert helper_with_dynamic_models.get_provider_model_id(unknown_model.provider_resource_id) is None + + # And not available via check_model_availability + is_available = await helper_with_dynamic_models.check_model_availability(unknown_model.provider_resource_id) + assert not is_available + + # Registration should fail with comprehensive error message + with pytest.raises(Exception) as exc_info: # UnsupportedModelError + await helper_with_dynamic_models.register_model(unknown_model) + + # Error should include static models and "..." for dynamic models + error_str = str(exc_info.value) + assert "..." in error_str # "..." should be in error message + + +async def test_register_alias_for_dynamic_model( + helper_with_dynamic_models: MockModelRegistryHelperWithDynamicModels, dynamic_model: Model +) -> None: + """Test that we can register an alias that maps to a dynamically available model.""" + # Create a model with a different identifier but same provider_resource_id + alias_model = Model( + provider_id=dynamic_model.provider_id, + identifier="dynamic-model-alias", + provider_resource_id=dynamic_model.provider_resource_id, + ) + + # Registration should succeed since the provider_resource_id is available dynamically + registered_model = await helper_with_dynamic_models.register_model(alias_model) + assert registered_model == alias_model + + # Both the original provider_resource_id and the new alias should work + assert helper_with_dynamic_models.get_provider_model_id(alias_model.model_id) == dynamic_model.provider_resource_id From aa0840c2813c6140840dd91d5a40ee3850a6a889 Mon Sep 17 00:00:00 2001 From: ehhuang Date: Mon, 14 Jul 2025 12:06:56 -0700 Subject: [PATCH 31/34] docs: fix building distro link (#2750) # What does this PR do? ## Test Plan Co-authored-by: raghotham --- docs/source/getting_started/detailed_tutorial.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/source/getting_started/detailed_tutorial.md b/docs/source/getting_started/detailed_tutorial.md index 97e7df774..fc59022f9 100644 --- a/docs/source/getting_started/detailed_tutorial.md +++ b/docs/source/getting_started/detailed_tutorial.md @@ -77,7 +77,7 @@ ENABLE_OLLAMA=ollama INFERENCE_MODEL="llama3.2:3b" llama stack build --template You can use a container image to run the Llama Stack server. We provide several container images for the server component that works with different inference providers out of the box. For this guide, we will use `llamastack/distribution-starter` as the container image. If you'd like to build your own image or customize the -configurations, please check out [this guide](../references/index.md). +configurations, please check out [this guide](../distributions/building_distro.md). First lets setup some environment variables and create a local directory to mount into the container’s file system. ```bash export INFERENCE_MODEL="llama3.2:3b" From 6ad22c209ff53f996a30d94f9769c9e405f3bc71 Mon Sep 17 00:00:00 2001 From: Nathan Weinberg <31703736+nathan-weinberg@users.noreply.github.com> Date: Mon, 14 Jul 2025 17:41:44 -0400 Subject: [PATCH 32/34] chore: add issue template for technical debt (#2753) # What does this PR do? Adds a template for technical debt. Currently we don't support blank issues so everything filed has to a bug or a feature. This would allow maintainers as well as community members to track things we might want to merge to expose the functionality but should be addressed later. Such things can also be "good first issues" for new contributors. ## Example of what we constitute as technical debt Inelegant code solutions, tests we intend to temporarily disable but would like to restore, CI hacks around infrastructure or installation, etc. Signed-off-by: Nathan Weinberg --- .github/ISSUE_TEMPLATE/tech-debt.yml | 30 ++++++++++++++++++++++++++++ 1 file changed, 30 insertions(+) create mode 100644 .github/ISSUE_TEMPLATE/tech-debt.yml diff --git a/.github/ISSUE_TEMPLATE/tech-debt.yml b/.github/ISSUE_TEMPLATE/tech-debt.yml new file mode 100644 index 000000000..b281b3482 --- /dev/null +++ b/.github/ISSUE_TEMPLATE/tech-debt.yml @@ -0,0 +1,30 @@ +name: 🔧 Tech Debt +description: Something that is functional but should be improved or optimizied +labels: ["tech-debt"] +body: +- type: textarea + id: tech-debt-explanation + attributes: + label: 🤔 What is the technical debt you think should be addressed? + description: > + A clear and concise description of _what_ needs to be addressed - ensure you are describing + constitutes [technical debt](https://en.wikipedia.org/wiki/Technical_debt) and is not a bug + or feature request. + validations: + required: true + +- type: textarea + id: tech-debt-motivation + attributes: + label: 💡 What is the benefit of addressing this technical debt? + description: > + A clear and concise description of _why_ this work is needed. + validations: + required: true + +- type: textarea + id: other-thoughts + attributes: + label: Other thoughts + description: > + Any thoughts about how this may result in complexity in the codebase, or other trade-offs. From 6b8a8c1be9c61cf1135422f2105c4cc0040e19fc Mon Sep 17 00:00:00 2001 From: Hardik Shah Date: Mon, 14 Jul 2025 15:07:40 -0700 Subject: [PATCH 33/34] fix: Safety in starter (#2731) - fireworks, together do not support Llama-guard 3 8b model anymore - Need to default to ollama - current safety shields logic was not correct since the shield_id was the provider ( which had duplicates ) - Followed similar logic to models Note: Seems a bit over-engineered but this can now be extended to other providers and fits in the overall mechanism of how env_vars are used to manage starter. ### How to test ``` ENABLE_OLLAMA=ollama ENABLE_FIREWORKS=fireworks SAFETY_MODEL=llama-guard3:1b pytest -s -v tests/integration/ --stack-config starter -k 'not(supervised_fine_tune or builtin_tool_code or safety_with_image or code_interpreter_for or rag_and_code or truncation or register_and_unregister)' --text-model fireworks/meta-llama/Llama-3.3-70B-Instruct --vision-model fireworks/meta-llama/Llama-4-Scout-17B-16E-Instruct --safety-shield llama-guard3:1b --embedding-model all-MiniLM-L6-v2 ``` ### Related but not obvious in this PR In the llama-stack-ops repo, we run tests before publishing packages and docker containers. The actions in that repo were using the fireworks / together distros ( which are non-existent ) So need to update that to run with `starter` and use `ollama` specifically for safety. --- .github/workflows/integration-tests.yml | 2 +- .../remote/inference/ollama/models.py | 25 +++-- llama_stack/templates/nvidia/nvidia.py | 2 +- .../open-benchmark/open_benchmark.py | 3 +- llama_stack/templates/starter/run.yaml | 20 +--- llama_stack/templates/starter/starter.py | 94 +++------------- llama_stack/templates/template.py | 47 +++++++- llama_stack/templates/watsonx/watsonx.py | 2 +- tests/integration/agents/test_agents.py | 104 ++++-------------- 9 files changed, 104 insertions(+), 195 deletions(-) diff --git a/.github/workflows/integration-tests.yml b/.github/workflows/integration-tests.yml index c46100c38..1a8d6734f 100644 --- a/.github/workflows/integration-tests.yml +++ b/.github/workflows/integration-tests.yml @@ -89,7 +89,7 @@ jobs: -k "not(builtin_tool or safety_with_image or code_interpreter or test_rag)" \ --text-model="ollama/llama3.2:3b-instruct-fp16" \ --embedding-model=all-MiniLM-L6-v2 \ - --safety-shield=ollama \ + --safety-shield=$SAFETY_MODEL \ --color=yes \ --capture=tee-sys | tee pytest-${{ matrix.test-type }}.log diff --git a/llama_stack/providers/remote/inference/ollama/models.py b/llama_stack/providers/remote/inference/ollama/models.py index 64ddb23d9..7c0a19a1a 100644 --- a/llama_stack/providers/remote/inference/ollama/models.py +++ b/llama_stack/providers/remote/inference/ollama/models.py @@ -12,6 +12,19 @@ from llama_stack.providers.utils.inference.model_registry import ( build_model_entry, ) +SAFETY_MODELS_ENTRIES = [ + # The Llama Guard models don't have their full fp16 versions + # so we are going to alias their default version to the canonical SKU + build_hf_repo_model_entry( + "llama-guard3:8b", + CoreModelId.llama_guard_3_8b.value, + ), + build_hf_repo_model_entry( + "llama-guard3:1b", + CoreModelId.llama_guard_3_1b.value, + ), +] + MODEL_ENTRIES = [ build_hf_repo_model_entry( "llama3.1:8b-instruct-fp16", @@ -73,16 +86,6 @@ MODEL_ENTRIES = [ "llama3.3:70b", CoreModelId.llama3_3_70b_instruct.value, ), - # The Llama Guard models don't have their full fp16 versions - # so we are going to alias their default version to the canonical SKU - build_hf_repo_model_entry( - "llama-guard3:8b", - CoreModelId.llama_guard_3_8b.value, - ), - build_hf_repo_model_entry( - "llama-guard3:1b", - CoreModelId.llama_guard_3_1b.value, - ), ProviderModelEntry( provider_model_id="all-minilm:l6-v2", aliases=["all-minilm"], @@ -100,4 +103,4 @@ MODEL_ENTRIES = [ "context_length": 8192, }, ), -] +] + SAFETY_MODELS_ENTRIES diff --git a/llama_stack/templates/nvidia/nvidia.py b/llama_stack/templates/nvidia/nvidia.py index 4eccfb25c..e5c13aa74 100644 --- a/llama_stack/templates/nvidia/nvidia.py +++ b/llama_stack/templates/nvidia/nvidia.py @@ -68,7 +68,7 @@ def get_distribution_template() -> DistributionTemplate: ), ] - default_models = get_model_registry(available_models) + default_models, _ = get_model_registry(available_models) return DistributionTemplate( name="nvidia", distro_type="self_hosted", diff --git a/llama_stack/templates/open-benchmark/open_benchmark.py b/llama_stack/templates/open-benchmark/open_benchmark.py index 942905dae..56ee9c47d 100644 --- a/llama_stack/templates/open-benchmark/open_benchmark.py +++ b/llama_stack/templates/open-benchmark/open_benchmark.py @@ -146,7 +146,8 @@ def get_distribution_template() -> DistributionTemplate: ), ] - default_models = get_model_registry(available_models) + [ + models, _ = get_model_registry(available_models) + default_models = models + [ ModelInput( model_id="meta-llama/Llama-3.3-70B-Instruct", provider_id="groq", diff --git a/llama_stack/templates/starter/run.yaml b/llama_stack/templates/starter/run.yaml index 888a2c3bf..ad449cb1b 100644 --- a/llama_stack/templates/starter/run.yaml +++ b/llama_stack/templates/starter/run.yaml @@ -1171,24 +1171,8 @@ models: provider_id: ${env.ENABLE_SENTENCE_TRANSFORMERS:=sentence-transformers} model_type: embedding shields: -- shield_id: ${env.ENABLE_OLLAMA:=__disabled__} - provider_id: llama-guard - provider_shield_id: ${env.ENABLE_OLLAMA:=__disabled__}/${env.SAFETY_MODEL:=llama-guard3:1b} -- shield_id: ${env.ENABLE_FIREWORKS:=__disabled__} - provider_id: llama-guard - provider_shield_id: ${env.ENABLE_FIREWORKS:=__disabled__}/${env.SAFETY_MODEL:=accounts/fireworks/models/llama-guard-3-8b} -- shield_id: ${env.ENABLE_FIREWORKS:=__disabled__} - provider_id: llama-guard - provider_shield_id: ${env.ENABLE_FIREWORKS:=__disabled__}/${env.SAFETY_MODEL:=accounts/fireworks/models/llama-guard-3-11b-vision} -- shield_id: ${env.ENABLE_TOGETHER:=__disabled__} - provider_id: llama-guard - provider_shield_id: ${env.ENABLE_TOGETHER:=__disabled__}/${env.SAFETY_MODEL:=meta-llama/Llama-Guard-3-8B} -- shield_id: ${env.ENABLE_TOGETHER:=__disabled__} - provider_id: llama-guard - provider_shield_id: ${env.ENABLE_TOGETHER:=__disabled__}/${env.SAFETY_MODEL:=meta-llama/Llama-Guard-3-11B-Vision-Turbo} -- shield_id: ${env.ENABLE_SAMBANOVA:=__disabled__} - provider_id: llama-guard - provider_shield_id: ${env.ENABLE_SAMBANOVA:=__disabled__}/${env.SAFETY_MODEL:=sambanova/Meta-Llama-Guard-3-8B} +- shield_id: ${env.SAFETY_MODEL:=__disabled__} + provider_shield_id: ${env.ENABLE_OLLAMA:=__disabled__}/${env.SAFETY_MODEL:=__disabled__} vector_dbs: [] datasets: [] scoring_fns: [] diff --git a/llama_stack/templates/starter/starter.py b/llama_stack/templates/starter/starter.py index 6b8aa8974..c0ac44183 100644 --- a/llama_stack/templates/starter/starter.py +++ b/llama_stack/templates/starter/starter.py @@ -12,7 +12,6 @@ from llama_stack.distribution.datatypes import ( ModelInput, Provider, ProviderSpec, - ShieldInput, ToolGroupInput, ) from llama_stack.distribution.utils.dynamic import instantiate_class_type @@ -32,75 +31,39 @@ from llama_stack.providers.registry.inference import available_providers from llama_stack.providers.remote.inference.anthropic.models import ( MODEL_ENTRIES as ANTHROPIC_MODEL_ENTRIES, ) -from llama_stack.providers.remote.inference.anthropic.models import ( - SAFETY_MODELS_ENTRIES as ANTHROPIC_SAFETY_MODELS_ENTRIES, -) from llama_stack.providers.remote.inference.bedrock.models import ( MODEL_ENTRIES as BEDROCK_MODEL_ENTRIES, ) -from llama_stack.providers.remote.inference.bedrock.models import ( - SAFETY_MODELS_ENTRIES as BEDROCK_SAFETY_MODELS_ENTRIES, -) from llama_stack.providers.remote.inference.cerebras.models import ( MODEL_ENTRIES as CEREBRAS_MODEL_ENTRIES, ) -from llama_stack.providers.remote.inference.cerebras.models import ( - SAFETY_MODELS_ENTRIES as CEREBRAS_SAFETY_MODELS_ENTRIES, -) from llama_stack.providers.remote.inference.databricks.databricks import ( MODEL_ENTRIES as DATABRICKS_MODEL_ENTRIES, ) -from llama_stack.providers.remote.inference.databricks.databricks import ( - SAFETY_MODELS_ENTRIES as DATABRICKS_SAFETY_MODELS_ENTRIES, -) from llama_stack.providers.remote.inference.fireworks.models import ( MODEL_ENTRIES as FIREWORKS_MODEL_ENTRIES, ) -from llama_stack.providers.remote.inference.fireworks.models import ( - SAFETY_MODELS_ENTRIES as FIREWORKS_SAFETY_MODELS_ENTRIES, -) from llama_stack.providers.remote.inference.gemini.models import ( MODEL_ENTRIES as GEMINI_MODEL_ENTRIES, ) -from llama_stack.providers.remote.inference.gemini.models import ( - SAFETY_MODELS_ENTRIES as GEMINI_SAFETY_MODELS_ENTRIES, -) from llama_stack.providers.remote.inference.groq.models import ( MODEL_ENTRIES as GROQ_MODEL_ENTRIES, ) -from llama_stack.providers.remote.inference.groq.models import ( - SAFETY_MODELS_ENTRIES as GROQ_SAFETY_MODELS_ENTRIES, -) from llama_stack.providers.remote.inference.nvidia.models import ( MODEL_ENTRIES as NVIDIA_MODEL_ENTRIES, ) -from llama_stack.providers.remote.inference.nvidia.models import ( - SAFETY_MODELS_ENTRIES as NVIDIA_SAFETY_MODELS_ENTRIES, -) from llama_stack.providers.remote.inference.openai.models import ( MODEL_ENTRIES as OPENAI_MODEL_ENTRIES, ) -from llama_stack.providers.remote.inference.openai.models import ( - SAFETY_MODELS_ENTRIES as OPENAI_SAFETY_MODELS_ENTRIES, -) from llama_stack.providers.remote.inference.runpod.runpod import ( MODEL_ENTRIES as RUNPOD_MODEL_ENTRIES, ) -from llama_stack.providers.remote.inference.runpod.runpod import ( - SAFETY_MODELS_ENTRIES as RUNPOD_SAFETY_MODELS_ENTRIES, -) from llama_stack.providers.remote.inference.sambanova.models import ( MODEL_ENTRIES as SAMBANOVA_MODEL_ENTRIES, ) -from llama_stack.providers.remote.inference.sambanova.models import ( - SAFETY_MODELS_ENTRIES as SAMBANOVA_SAFETY_MODELS_ENTRIES, -) from llama_stack.providers.remote.inference.together.models import ( MODEL_ENTRIES as TOGETHER_MODEL_ENTRIES, ) -from llama_stack.providers.remote.inference.together.models import ( - SAFETY_MODELS_ENTRIES as TOGETHER_SAFETY_MODELS_ENTRIES, -) from llama_stack.providers.remote.vector_io.chroma.config import ChromaVectorIOConfig from llama_stack.providers.remote.vector_io.pgvector.config import ( PGVectorVectorIOConfig, @@ -111,6 +74,7 @@ from llama_stack.templates.template import ( DistributionTemplate, RunConfigSettings, get_model_registry, + get_shield_registry, ) @@ -164,28 +128,13 @@ def _get_model_entries_for_provider(provider_type: str) -> list[ProviderModelEnt def _get_model_safety_entries_for_provider(provider_type: str) -> list[ProviderModelEntry]: """Get model entries for a specific provider type.""" safety_model_entries_map = { - "openai": OPENAI_SAFETY_MODELS_ENTRIES, - "fireworks": FIREWORKS_SAFETY_MODELS_ENTRIES, - "together": TOGETHER_SAFETY_MODELS_ENTRIES, - "anthropic": ANTHROPIC_SAFETY_MODELS_ENTRIES, - "gemini": GEMINI_SAFETY_MODELS_ENTRIES, - "groq": GROQ_SAFETY_MODELS_ENTRIES, - "sambanova": SAMBANOVA_SAFETY_MODELS_ENTRIES, - "cerebras": CEREBRAS_SAFETY_MODELS_ENTRIES, - "bedrock": BEDROCK_SAFETY_MODELS_ENTRIES, - "databricks": DATABRICKS_SAFETY_MODELS_ENTRIES, - "nvidia": NVIDIA_SAFETY_MODELS_ENTRIES, - "runpod": RUNPOD_SAFETY_MODELS_ENTRIES, - } - - # Special handling for providers with dynamic model entries - if provider_type == "ollama": - return [ + "ollama": [ ProviderModelEntry( - provider_model_id="llama-guard3:1b", + provider_model_id="${env.SAFETY_MODEL:=__disabled__}", model_type=ModelType.llm, ), - ] + ], + } return safety_model_entries_map.get(provider_type, []) @@ -246,28 +195,20 @@ def get_remote_inference_providers() -> tuple[list[Provider], dict[str, list[Pro # build a list of shields for all possible providers -def get_shields_for_providers(providers: list[Provider]) -> list[ShieldInput]: - shields = [] +def get_safety_models_for_providers(providers: list[Provider]) -> dict[str, list[ProviderModelEntry]]: + available_models = {} for provider in providers: provider_type = provider.provider_type.split("::")[1] safety_model_entries = _get_model_safety_entries_for_provider(provider_type) if len(safety_model_entries) == 0: continue - if provider.provider_id: - shield_id = provider.provider_id - else: - raise ValueError(f"Provider {provider.provider_type} has no provider_id") - for safety_model_entry in safety_model_entries: - print(f"provider.provider_id: {provider.provider_id}") - print(f"safety_model_entry.provider_model_id: {safety_model_entry.provider_model_id}") - shields.append( - ShieldInput( - provider_id="llama-guard", - shield_id=shield_id, - provider_shield_id=f"{provider.provider_id}/${{env.SAFETY_MODEL:={safety_model_entry.provider_model_id}}}", - ) - ) - return shields + + env_var = f"ENABLE_{provider_type.upper().replace('-', '_').replace('::', '_')}" + provider_id = f"${{env.{env_var}:=__disabled__}}" + + available_models[provider_id] = safety_model_entries + + return available_models def get_distribution_template() -> DistributionTemplate: @@ -307,8 +248,6 @@ def get_distribution_template() -> DistributionTemplate: ), ] - shields = get_shields_for_providers(remote_inference_providers) - providers = { "inference": ([p.provider_type for p in remote_inference_providers] + ["inline::sentence-transformers"]), "vector_io": ([p.provider_type for p in vector_io_providers]), @@ -361,7 +300,10 @@ def get_distribution_template() -> DistributionTemplate: }, ) - default_models = get_model_registry(available_models) + default_models, ids_conflict_in_models = get_model_registry(available_models) + + available_safety_models = get_safety_models_for_providers(remote_inference_providers) + shields = get_shield_registry(available_safety_models, ids_conflict_in_models) return DistributionTemplate( name=name, diff --git a/llama_stack/templates/template.py b/llama_stack/templates/template.py index dceb13c8b..fb2528873 100644 --- a/llama_stack/templates/template.py +++ b/llama_stack/templates/template.py @@ -37,7 +37,7 @@ from llama_stack.providers.utils.sqlstore.sqlstore import get_pip_packages as ge def get_model_registry( available_models: dict[str, list[ProviderModelEntry]], -) -> list[ModelInput]: +) -> tuple[list[ModelInput], bool]: models = [] # check for conflicts in model ids @@ -74,7 +74,50 @@ def get_model_registry( metadata=entry.metadata, ) ) - return models + return models, ids_conflict + + +def get_shield_registry( + available_safety_models: dict[str, list[ProviderModelEntry]], + ids_conflict_in_models: bool, +) -> list[ShieldInput]: + shields = [] + + # check for conflicts in shield ids + all_ids = set() + ids_conflict = False + + for _, entries in available_safety_models.items(): + for entry in entries: + ids = [entry.provider_model_id] + entry.aliases + for model_id in ids: + if model_id in all_ids: + ids_conflict = True + rich.print( + f"[yellow]Shield id {model_id} conflicts; all shield ids will be prefixed with provider id[/yellow]" + ) + break + all_ids.update(ids) + if ids_conflict: + break + if ids_conflict: + break + + for provider_id, entries in available_safety_models.items(): + for entry in entries: + ids = [entry.provider_model_id] + entry.aliases + for model_id in ids: + identifier = f"{provider_id}/{model_id}" if ids_conflict and provider_id not in model_id else model_id + shields.append( + ShieldInput( + shield_id=identifier, + provider_shield_id=f"{provider_id}/{entry.provider_model_id}" + if ids_conflict_in_models + else entry.provider_model_id, + ) + ) + + return shields class DefaultModel(BaseModel): diff --git a/llama_stack/templates/watsonx/watsonx.py b/llama_stack/templates/watsonx/watsonx.py index 7fa3a55e5..ea185f05d 100644 --- a/llama_stack/templates/watsonx/watsonx.py +++ b/llama_stack/templates/watsonx/watsonx.py @@ -69,7 +69,7 @@ def get_distribution_template() -> DistributionTemplate: }, ) - default_models = get_model_registry(available_models) + default_models, _ = get_model_registry(available_models) return DistributionTemplate( name="watsonx", distro_type="remote_hosted", diff --git a/tests/integration/agents/test_agents.py b/tests/integration/agents/test_agents.py index 66c9ab829..05549cf18 100644 --- a/tests/integration/agents/test_agents.py +++ b/tests/integration/agents/test_agents.py @@ -77,6 +77,24 @@ def agent_config(llama_stack_client, text_model_id): return agent_config +@pytest.fixture(scope="session") +def agent_config_without_safety(text_model_id): + agent_config = dict( + model=text_model_id, + instructions="You are a helpful assistant", + sampling_params={ + "strategy": { + "type": "top_p", + "temperature": 0.0001, + "top_p": 0.9, + }, + }, + tools=[], + enable_session_persistence=False, + ) + return agent_config + + def test_agent_simple(llama_stack_client, agent_config): agent = Agent(llama_stack_client, **agent_config) session_id = agent.create_session(f"test-session-{uuid4()}") @@ -491,7 +509,7 @@ def test_rag_agent(llama_stack_client, agent_config, rag_tool_name): assert expected_kw in response.output_message.content.lower() -def test_rag_agent_with_attachments(llama_stack_client, agent_config): +def test_rag_agent_with_attachments(llama_stack_client, agent_config_without_safety): urls = ["llama3.rst", "lora_finetune.rst"] documents = [ # passign as url @@ -514,14 +532,8 @@ def test_rag_agent_with_attachments(llama_stack_client, agent_config): metadata={}, ), ] - rag_agent = Agent(llama_stack_client, **agent_config) + rag_agent = Agent(llama_stack_client, **agent_config_without_safety) session_id = rag_agent.create_session(f"test-session-{uuid4()}") - user_prompts = [ - ( - "Instead of the standard multi-head attention, what attention type does Llama3-8B use?", - "grouped", - ), - ] user_prompts = [ ( "I am attaching some documentation for Torchtune. Help me answer questions I will ask next.", @@ -549,82 +561,6 @@ def test_rag_agent_with_attachments(llama_stack_client, agent_config): assert "lora" in response.output_message.content.lower() -@pytest.mark.skip(reason="Code interpreter is currently disabled in the Stack") -def test_rag_and_code_agent(llama_stack_client, agent_config): - if "llama-4" in agent_config["model"].lower(): - pytest.xfail("Not working for llama4") - - documents = [] - documents.append( - Document( - document_id="nba_wiki", - content="The NBA was created on August 3, 1949, with the merger of the Basketball Association of America (BAA) and the National Basketball League (NBL).", - metadata={}, - ) - ) - documents.append( - Document( - document_id="perplexity_wiki", - content="""Perplexity the company was founded in 2022 by Aravind Srinivas, Andy Konwinski, Denis Yarats and Johnny Ho, engineers with backgrounds in back-end systems, artificial intelligence (AI) and machine learning: - - Srinivas, the CEO, worked at OpenAI as an AI researcher. - Konwinski was among the founding team at Databricks. - Yarats, the CTO, was an AI research scientist at Meta. - Ho, the CSO, worked as an engineer at Quora, then as a quantitative trader on Wall Street.[5]""", - metadata={}, - ) - ) - vector_db_id = f"test-vector-db-{uuid4()}" - llama_stack_client.vector_dbs.register( - vector_db_id=vector_db_id, - embedding_model="all-MiniLM-L6-v2", - embedding_dimension=384, - ) - llama_stack_client.tool_runtime.rag_tool.insert( - documents=documents, - vector_db_id=vector_db_id, - chunk_size_in_tokens=128, - ) - agent_config = { - **agent_config, - "tools": [ - dict( - name="builtin::rag/knowledge_search", - args={"vector_db_ids": [vector_db_id]}, - ), - "builtin::code_interpreter", - ], - } - agent = Agent(llama_stack_client, **agent_config) - user_prompts = [ - ( - "when was Perplexity the company founded?", - [], - "knowledge_search", - "2022", - ), - ( - "when was the nba created?", - [], - "knowledge_search", - "1949", - ), - ] - - for prompt, docs, tool_name, expected_kw in user_prompts: - session_id = agent.create_session(f"test-session-{uuid4()}") - response = agent.create_turn( - messages=[{"role": "user", "content": prompt}], - session_id=session_id, - documents=docs, - stream=False, - ) - tool_execution_step = next(step for step in response.steps if step.step_type == "tool_execution") - assert tool_execution_step.tool_calls[0].tool_name == tool_name, f"Failed on {prompt}" - if expected_kw: - assert expected_kw in response.output_message.content.lower() - - @pytest.mark.parametrize( "client_tools", [(get_boiling_point, False), (get_boiling_point_with_metadata, True)], From 33f0d83ad396bf647ee999105272829e86321d38 Mon Sep 17 00:00:00 2001 From: Francisco Arceo Date: Mon, 14 Jul 2025 18:10:35 -0400 Subject: [PATCH 34/34] chore: Move vector store `kvstore` implementation into `openai_vector_store_mixin.py` (#2748) --- .../providers/vector_io/remote_pgvector.md | 4 + .../providers/vector_io/remote_weaviate.md | 4 +- .../providers/inline/vector_io/faiss/faiss.py | 40 +---- .../inline/vector_io/sqlite_vec/sqlite_vec.py | 39 +--- .../remote/vector_io/milvus/milvus.py | 33 +--- .../remote/vector_io/pgvector/config.py | 18 +- .../remote/vector_io/pgvector/pgvector.py | 169 ++++++------------ .../remote/vector_io/weaviate/config.py | 17 +- .../remote/vector_io/weaviate/weaviate.py | 64 ++++++- .../utils/memory/openai_vector_store_mixin.py | 41 ++++- .../open-benchmark/open_benchmark.py | 1 + llama_stack/templates/open-benchmark/run.yaml | 3 + llama_stack/templates/starter/run.yaml | 3 + llama_stack/templates/starter/starter.py | 1 + 14 files changed, 203 insertions(+), 234 deletions(-) diff --git a/docs/source/providers/vector_io/remote_pgvector.md b/docs/source/providers/vector_io/remote_pgvector.md index 685b98f37..3e7d6e776 100644 --- a/docs/source/providers/vector_io/remote_pgvector.md +++ b/docs/source/providers/vector_io/remote_pgvector.md @@ -40,6 +40,7 @@ See [PGVector's documentation](https://github.com/pgvector/pgvector) for more de | `db` | `str \| None` | No | postgres | | | `user` | `str \| None` | No | postgres | | | `password` | `str \| None` | No | mysecretpassword | | +| `kvstore` | `utils.kvstore.config.RedisKVStoreConfig \| utils.kvstore.config.SqliteKVStoreConfig \| utils.kvstore.config.PostgresKVStoreConfig \| utils.kvstore.config.MongoDBKVStoreConfig, annotation=NoneType, required=False, default='sqlite', discriminator='type'` | No | | Config for KV store backend (SQLite only for now) | ## Sample Configuration @@ -49,6 +50,9 @@ port: ${env.PGVECTOR_PORT:=5432} db: ${env.PGVECTOR_DB} user: ${env.PGVECTOR_USER} password: ${env.PGVECTOR_PASSWORD} +kvstore: + type: sqlite + db_path: ${env.SQLITE_STORE_DIR:=~/.llama/dummy}/pgvector_registry.db ``` diff --git a/docs/source/providers/vector_io/remote_weaviate.md b/docs/source/providers/vector_io/remote_weaviate.md index b7f811c35..d930515d5 100644 --- a/docs/source/providers/vector_io/remote_weaviate.md +++ b/docs/source/providers/vector_io/remote_weaviate.md @@ -36,7 +36,9 @@ See [Weaviate's documentation](https://weaviate.io/developers/weaviate) for more ## Sample Configuration ```yaml -{} +kvstore: + type: sqlite + db_path: ${env.SQLITE_STORE_DIR:=~/.llama/dummy}/weaviate_registry.db ``` diff --git a/llama_stack/providers/inline/vector_io/faiss/faiss.py b/llama_stack/providers/inline/vector_io/faiss/faiss.py index 0306d9156..2a1370c56 100644 --- a/llama_stack/providers/inline/vector_io/faiss/faiss.py +++ b/llama_stack/providers/inline/vector_io/faiss/faiss.py @@ -181,8 +181,8 @@ class FaissVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtocolPr ) self.cache[vector_db.identifier] = index - # Load existing OpenAI vector stores using the mixin method - self.openai_vector_stores = await self._load_openai_vector_stores() + # Load existing OpenAI vector stores into the in-memory cache + await self.initialize_openai_vector_stores() async def shutdown(self) -> None: # Cleanup if needed @@ -261,42 +261,6 @@ class FaissVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtocolPr return await index.query_chunks(query, params) - # OpenAI Vector Store Mixin abstract method implementations - async def _save_openai_vector_store(self, store_id: str, store_info: dict[str, Any]) -> None: - """Save vector store metadata to kvstore.""" - assert self.kvstore is not None - key = f"{OPENAI_VECTOR_STORES_PREFIX}{store_id}" - await self.kvstore.set(key=key, value=json.dumps(store_info)) - self.openai_vector_stores[store_id] = store_info - - async def _load_openai_vector_stores(self) -> dict[str, dict[str, Any]]: - """Load all vector store metadata from kvstore.""" - assert self.kvstore is not None - start_key = OPENAI_VECTOR_STORES_PREFIX - end_key = f"{OPENAI_VECTOR_STORES_PREFIX}\xff" - stored_openai_stores = await self.kvstore.values_in_range(start_key, end_key) - - stores = {} - for store_data in stored_openai_stores: - store_info = json.loads(store_data) - stores[store_info["id"]] = store_info - return stores - - async def _update_openai_vector_store(self, store_id: str, store_info: dict[str, Any]) -> None: - """Update vector store metadata in kvstore.""" - assert self.kvstore is not None - key = f"{OPENAI_VECTOR_STORES_PREFIX}{store_id}" - await self.kvstore.set(key=key, value=json.dumps(store_info)) - self.openai_vector_stores[store_id] = store_info - - async def _delete_openai_vector_store_from_storage(self, store_id: str) -> None: - """Delete vector store metadata from kvstore.""" - assert self.kvstore is not None - key = f"{OPENAI_VECTOR_STORES_PREFIX}{store_id}" - await self.kvstore.delete(key) - if store_id in self.openai_vector_stores: - del self.openai_vector_stores[store_id] - async def _save_openai_vector_store_file( self, store_id: str, file_id: str, file_info: dict[str, Any], file_contents: list[dict[str, Any]] ) -> None: diff --git a/llama_stack/providers/inline/vector_io/sqlite_vec/sqlite_vec.py b/llama_stack/providers/inline/vector_io/sqlite_vec/sqlite_vec.py index 6acd85c56..771ffa607 100644 --- a/llama_stack/providers/inline/vector_io/sqlite_vec/sqlite_vec.py +++ b/llama_stack/providers/inline/vector_io/sqlite_vec/sqlite_vec.py @@ -452,8 +452,8 @@ class SQLiteVecVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtoc ) self.cache[vector_db.identifier] = VectorDBWithIndex(vector_db, index, self.inference_api) - # load any existing OpenAI vector stores - self.openai_vector_stores = await self._load_openai_vector_stores() + # Load existing OpenAI vector stores into the in-memory cache + await self.initialize_openai_vector_stores() async def shutdown(self) -> None: # nothing to do since we don't maintain a persistent connection @@ -501,41 +501,6 @@ class SQLiteVecVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtoc await self.cache[vector_db_id].index.delete() del self.cache[vector_db_id] - # OpenAI Vector Store Mixin abstract method implementations - async def _save_openai_vector_store(self, store_id: str, store_info: dict[str, Any]) -> None: - """Save vector store metadata to SQLite database.""" - assert self.kvstore is not None - key = f"{OPENAI_VECTOR_STORES_PREFIX}{store_id}" - await self.kvstore.set(key=key, value=json.dumps(store_info)) - self.openai_vector_stores[store_id] = store_info - - async def _load_openai_vector_stores(self) -> dict[str, dict[str, Any]]: - """Load all vector store metadata from SQLite database.""" - assert self.kvstore is not None - start_key = OPENAI_VECTOR_STORES_PREFIX - end_key = f"{OPENAI_VECTOR_STORES_PREFIX}\xff" - stored_openai_stores = await self.kvstore.values_in_range(start_key, end_key) - stores = {} - for store_data in stored_openai_stores: - store_info = json.loads(store_data) - stores[store_info["id"]] = store_info - return stores - - async def _update_openai_vector_store(self, store_id: str, store_info: dict[str, Any]) -> None: - """Update vector store metadata in SQLite database.""" - assert self.kvstore is not None - key = f"{OPENAI_VECTOR_STORES_PREFIX}{store_id}" - await self.kvstore.set(key=key, value=json.dumps(store_info)) - self.openai_vector_stores[store_id] = store_info - - async def _delete_openai_vector_store_from_storage(self, store_id: str) -> None: - """Delete vector store metadata from SQLite database.""" - assert self.kvstore is not None - key = f"{OPENAI_VECTOR_STORES_PREFIX}{store_id}" - await self.kvstore.delete(key) - if store_id in self.openai_vector_stores: - del self.openai_vector_stores[store_id] - async def _save_openai_vector_store_file( self, store_id: str, file_id: str, file_info: dict[str, Any], file_contents: list[dict[str, Any]] ) -> None: diff --git a/llama_stack/providers/remote/vector_io/milvus/milvus.py b/llama_stack/providers/remote/vector_io/milvus/milvus.py index a06130fd0..d88d954ef 100644 --- a/llama_stack/providers/remote/vector_io/milvus/milvus.py +++ b/llama_stack/providers/remote/vector_io/milvus/milvus.py @@ -179,7 +179,8 @@ class MilvusVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtocolP uri = os.path.expanduser(self.config.db_path) self.client = MilvusClient(uri=uri) - self.openai_vector_stores = await self._load_openai_vector_stores() + # Load existing OpenAI vector stores into the in-memory cache + await self.initialize_openai_vector_stores() async def shutdown(self) -> None: self.client.close() @@ -248,36 +249,6 @@ class MilvusVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtocolP return await index.query_chunks(query, params) - async def _save_openai_vector_store(self, store_id: str, store_info: dict[str, Any]) -> None: - """Save vector store metadata to persistent storage.""" - assert self.kvstore is not None - key = f"{OPENAI_VECTOR_STORES_PREFIX}{store_id}" - await self.kvstore.set(key=key, value=json.dumps(store_info)) - self.openai_vector_stores[store_id] = store_info - - async def _update_openai_vector_store(self, store_id: str, store_info: dict[str, Any]) -> None: - """Update vector store metadata in persistent storage.""" - assert self.kvstore is not None - key = f"{OPENAI_VECTOR_STORES_PREFIX}{store_id}" - await self.kvstore.set(key=key, value=json.dumps(store_info)) - self.openai_vector_stores[store_id] = store_info - - async def _delete_openai_vector_store_from_storage(self, store_id: str) -> None: - """Delete vector store metadata from persistent storage.""" - assert self.kvstore is not None - key = f"{OPENAI_VECTOR_STORES_PREFIX}{store_id}" - await self.kvstore.delete(key) - if store_id in self.openai_vector_stores: - del self.openai_vector_stores[store_id] - - async def _load_openai_vector_stores(self) -> dict[str, dict[str, Any]]: - """Load all vector store metadata from persistent storage.""" - assert self.kvstore is not None - start_key = OPENAI_VECTOR_STORES_PREFIX - end_key = f"{OPENAI_VECTOR_STORES_PREFIX}\xff" - stored = await self.kvstore.values_in_range(start_key, end_key) - return {json.loads(s)["id"]: json.loads(s) for s in stored} - async def _save_openai_vector_store_file( self, store_id: str, file_id: str, file_info: dict[str, Any], file_contents: list[dict[str, Any]] ) -> None: diff --git a/llama_stack/providers/remote/vector_io/pgvector/config.py b/llama_stack/providers/remote/vector_io/pgvector/config.py index 92908aa8a..334cbe5be 100644 --- a/llama_stack/providers/remote/vector_io/pgvector/config.py +++ b/llama_stack/providers/remote/vector_io/pgvector/config.py @@ -8,6 +8,10 @@ from typing import Any from pydantic import BaseModel, Field +from llama_stack.providers.utils.kvstore.config import ( + KVStoreConfig, + SqliteKVStoreConfig, +) from llama_stack.schema_utils import json_schema_type @@ -18,10 +22,12 @@ class PGVectorVectorIOConfig(BaseModel): db: str | None = Field(default="postgres") user: str | None = Field(default="postgres") password: str | None = Field(default="mysecretpassword") + kvstore: KVStoreConfig | None = Field(description="Config for KV store backend (SQLite only for now)", default=None) @classmethod def sample_run_config( cls, + __distro_dir__: str, host: str = "${env.PGVECTOR_HOST:=localhost}", port: int = "${env.PGVECTOR_PORT:=5432}", db: str = "${env.PGVECTOR_DB}", @@ -29,4 +35,14 @@ class PGVectorVectorIOConfig(BaseModel): password: str = "${env.PGVECTOR_PASSWORD}", **kwargs: Any, ) -> dict[str, Any]: - return {"host": host, "port": port, "db": db, "user": user, "password": password} + return { + "host": host, + "port": port, + "db": db, + "user": user, + "password": password, + "kvstore": SqliteKVStoreConfig.sample_run_config( + __distro_dir__=__distro_dir__, + db_name="pgvector_registry.db", + ), + } diff --git a/llama_stack/providers/remote/vector_io/pgvector/pgvector.py b/llama_stack/providers/remote/vector_io/pgvector/pgvector.py index c3cdef9b8..1bf3eedf8 100644 --- a/llama_stack/providers/remote/vector_io/pgvector/pgvector.py +++ b/llama_stack/providers/remote/vector_io/pgvector/pgvector.py @@ -13,24 +13,18 @@ from psycopg2 import sql from psycopg2.extras import Json, execute_values from pydantic import BaseModel, TypeAdapter +from llama_stack.apis.files.files import Files from llama_stack.apis.inference import InterleavedContent from llama_stack.apis.vector_dbs import VectorDB from llama_stack.apis.vector_io import ( Chunk, QueryChunksResponse, - SearchRankingOptions, VectorIO, - VectorStoreChunkingStrategy, - VectorStoreDeleteResponse, - VectorStoreFileContentsResponse, - VectorStoreFileObject, - VectorStoreFileStatus, - VectorStoreListFilesResponse, - VectorStoreListResponse, - VectorStoreObject, - VectorStoreSearchResponsePage, ) from llama_stack.providers.datatypes import Api, VectorDBsProtocolPrivate +from llama_stack.providers.utils.kvstore import kvstore_impl +from llama_stack.providers.utils.kvstore.api import KVStore +from llama_stack.providers.utils.memory.openai_vector_store_mixin import OpenAIVectorStoreMixin from llama_stack.providers.utils.memory.vector_store import ( EmbeddingIndex, VectorDBWithIndex, @@ -40,6 +34,13 @@ from .config import PGVectorVectorIOConfig log = logging.getLogger(__name__) +VERSION = "v3" +VECTOR_DBS_PREFIX = f"vector_dbs:pgvector:{VERSION}::" +VECTOR_INDEX_PREFIX = f"vector_index:pgvector:{VERSION}::" +OPENAI_VECTOR_STORES_PREFIX = f"openai_vector_stores:pgvector:{VERSION}::" +OPENAI_VECTOR_STORES_FILES_PREFIX = f"openai_vector_stores_files:pgvector:{VERSION}::" +OPENAI_VECTOR_STORES_FILES_CONTENTS_PREFIX = f"openai_vector_stores_files_contents:pgvector:{VERSION}::" + def check_extension_version(cur): cur.execute("SELECT extversion FROM pg_extension WHERE extname = 'vector'") @@ -69,7 +70,7 @@ def load_models(cur, cls): class PGVectorIndex(EmbeddingIndex): - def __init__(self, vector_db: VectorDB, dimension: int, conn): + def __init__(self, vector_db: VectorDB, dimension: int, conn, kvstore: KVStore | None = None): self.conn = conn with conn.cursor(cursor_factory=psycopg2.extras.DictCursor) as cur: # Sanitize the table name by replacing hyphens with underscores @@ -77,6 +78,7 @@ class PGVectorIndex(EmbeddingIndex): # when created with patterns like "test-vector-db-{uuid4()}" sanitized_identifier = vector_db.identifier.replace("-", "_") self.table_name = f"vector_store_{sanitized_identifier}" + self.kvstore = kvstore cur.execute( f""" @@ -158,15 +160,28 @@ class PGVectorIndex(EmbeddingIndex): cur.execute(f"DROP TABLE IF EXISTS {self.table_name}") -class PGVectorVectorIOAdapter(VectorIO, VectorDBsProtocolPrivate): - def __init__(self, config: PGVectorVectorIOConfig, inference_api: Api.inference) -> None: +class PGVectorVectorIOAdapter(OpenAIVectorStoreMixin, VectorIO, VectorDBsProtocolPrivate): + def __init__( + self, + config: PGVectorVectorIOConfig, + inference_api: Api.inference, + files_api: Files | None = None, + ) -> None: self.config = config self.inference_api = inference_api self.conn = None self.cache = {} + self.files_api = files_api + self.kvstore: KVStore | None = None + self.vector_db_store = None + self.openai_vector_store: dict[str, dict[str, Any]] = {} + self.metadatadata_collection_name = "openai_vector_stores_metadata" async def initialize(self) -> None: log.info(f"Initializing PGVector memory adapter with config: {self.config}") + self.kvstore = await kvstore_impl(self.config.kvstore) + await self.initialize_openai_vector_stores() + try: self.conn = psycopg2.connect( host=self.config.host, @@ -201,14 +216,31 @@ class PGVectorVectorIOAdapter(VectorIO, VectorDBsProtocolPrivate): log.info("Connection to PGVector database server closed") async def register_vector_db(self, vector_db: VectorDB) -> None: + # Persist vector DB metadata in the KV store + assert self.kvstore is not None + key = f"{VECTOR_DBS_PREFIX}{vector_db.identifier}" + await self.kvstore.set(key=key, value=vector_db.model_dump_json()) + + # Upsert model metadata in Postgres upsert_models(self.conn, [(vector_db.identifier, vector_db)]) - index = PGVectorIndex(vector_db, vector_db.embedding_dimension, self.conn) - self.cache[vector_db.identifier] = VectorDBWithIndex(vector_db, index, self.inference_api) + # Create and cache the PGVector index table for the vector DB + index = VectorDBWithIndex( + vector_db, + index=PGVectorIndex(vector_db, vector_db.embedding_dimension, self.conn, kvstore=self.kvstore), + inference_api=self.inference_api, + ) + self.cache[vector_db.identifier] = index async def unregister_vector_db(self, vector_db_id: str) -> None: - await self.cache[vector_db_id].index.delete() - del self.cache[vector_db_id] + # Remove provider index and cache + if vector_db_id in self.cache: + await self.cache[vector_db_id].index.delete() + del self.cache[vector_db_id] + + # Delete vector DB metadata from KV store + assert self.kvstore is not None + await self.kvstore.delete(key=f"{VECTOR_DBS_PREFIX}{vector_db_id}") async def insert_chunks( self, @@ -237,107 +269,20 @@ class PGVectorVectorIOAdapter(VectorIO, VectorDBsProtocolPrivate): self.cache[vector_db_id] = VectorDBWithIndex(vector_db, index, self.inference_api) return self.cache[vector_db_id] - async def openai_create_vector_store( - self, - name: str, - file_ids: list[str] | None = None, - expires_after: dict[str, Any] | None = None, - chunking_strategy: dict[str, Any] | None = None, - metadata: dict[str, Any] | None = None, - embedding_model: str | None = None, - embedding_dimension: int | None = 384, - provider_id: str | None = None, - provider_vector_db_id: str | None = None, - ) -> VectorStoreObject: + # OpenAI Vector Stores File operations are not supported in PGVector + async def _save_openai_vector_store_file( + self, store_id: str, file_id: str, file_info: dict[str, Any], file_contents: list[dict[str, Any]] + ) -> None: raise NotImplementedError("OpenAI Vector Stores API is not supported in PGVector") - async def openai_list_vector_stores( - self, - limit: int | None = 20, - order: str | None = "desc", - after: str | None = None, - before: str | None = None, - ) -> VectorStoreListResponse: + async def _load_openai_vector_store_file(self, store_id: str, file_id: str) -> dict[str, Any]: raise NotImplementedError("OpenAI Vector Stores API is not supported in PGVector") - async def openai_retrieve_vector_store( - self, - vector_store_id: str, - ) -> VectorStoreObject: + async def _load_openai_vector_store_file_contents(self, store_id: str, file_id: str) -> list[dict[str, Any]]: raise NotImplementedError("OpenAI Vector Stores API is not supported in PGVector") - async def openai_update_vector_store( - self, - vector_store_id: str, - name: str | None = None, - expires_after: dict[str, Any] | None = None, - metadata: dict[str, Any] | None = None, - ) -> VectorStoreObject: + async def _update_openai_vector_store_file(self, store_id: str, file_id: str, file_info: dict[str, Any]) -> None: raise NotImplementedError("OpenAI Vector Stores API is not supported in PGVector") - async def openai_delete_vector_store( - self, - vector_store_id: str, - ) -> VectorStoreDeleteResponse: - raise NotImplementedError("OpenAI Vector Stores API is not supported in PGVector") - - async def openai_search_vector_store( - self, - vector_store_id: str, - query: str | list[str], - filters: dict[str, Any] | None = None, - max_num_results: int | None = 10, - ranking_options: SearchRankingOptions | None = None, - rewrite_query: bool | None = False, - search_mode: str | None = "vector", - ) -> VectorStoreSearchResponsePage: - raise NotImplementedError("OpenAI Vector Stores API is not supported in PGVector") - - async def openai_attach_file_to_vector_store( - self, - vector_store_id: str, - file_id: str, - attributes: dict[str, Any] | None = None, - chunking_strategy: VectorStoreChunkingStrategy | None = None, - ) -> VectorStoreFileObject: - raise NotImplementedError("OpenAI Vector Stores API is not supported in PGVector") - - async def openai_list_files_in_vector_store( - self, - vector_store_id: str, - limit: int | None = 20, - order: str | None = "desc", - after: str | None = None, - before: str | None = None, - filter: VectorStoreFileStatus | None = None, - ) -> VectorStoreListFilesResponse: - raise NotImplementedError("OpenAI Vector Stores API is not supported in PGVector") - - async def openai_retrieve_vector_store_file( - self, - vector_store_id: str, - file_id: str, - ) -> VectorStoreFileObject: - raise NotImplementedError("OpenAI Vector Stores API is not supported in PGVector") - - async def openai_retrieve_vector_store_file_contents( - self, - vector_store_id: str, - file_id: str, - ) -> VectorStoreFileContentsResponse: - raise NotImplementedError("OpenAI Vector Stores API is not supported in PGVector") - - async def openai_update_vector_store_file( - self, - vector_store_id: str, - file_id: str, - attributes: dict[str, Any] | None = None, - ) -> VectorStoreFileObject: - raise NotImplementedError("OpenAI Vector Stores API is not supported in PGVector") - - async def openai_delete_vector_store_file( - self, - vector_store_id: str, - file_id: str, - ) -> VectorStoreFileObject: + async def _delete_openai_vector_store_file_from_storage(self, store_id: str, file_id: str) -> None: raise NotImplementedError("OpenAI Vector Stores API is not supported in PGVector") diff --git a/llama_stack/providers/remote/vector_io/weaviate/config.py b/llama_stack/providers/remote/vector_io/weaviate/config.py index a8c6e3e2c..4283b8d3b 100644 --- a/llama_stack/providers/remote/vector_io/weaviate/config.py +++ b/llama_stack/providers/remote/vector_io/weaviate/config.py @@ -6,15 +6,26 @@ from typing import Any -from pydantic import BaseModel +from pydantic import BaseModel, Field + +from llama_stack.providers.utils.kvstore.config import ( + KVStoreConfig, + SqliteKVStoreConfig, +) class WeaviateRequestProviderData(BaseModel): weaviate_api_key: str weaviate_cluster_url: str + kvstore: KVStoreConfig | None = Field(description="Config for KV store backend (SQLite only for now)", default=None) class WeaviateVectorIOConfig(BaseModel): @classmethod - def sample_run_config(cls, **kwargs: Any) -> dict[str, Any]: - return {} + def sample_run_config(cls, __distro_dir__: str, **kwargs: Any) -> dict[str, Any]: + return { + "kvstore": SqliteKVStoreConfig.sample_run_config( + __distro_dir__=__distro_dir__, + db_name="weaviate_registry.db", + ), + } diff --git a/llama_stack/providers/remote/vector_io/weaviate/weaviate.py b/llama_stack/providers/remote/vector_io/weaviate/weaviate.py index c63dd70c6..35bb40454 100644 --- a/llama_stack/providers/remote/vector_io/weaviate/weaviate.py +++ b/llama_stack/providers/remote/vector_io/weaviate/weaviate.py @@ -14,10 +14,13 @@ from weaviate.classes.init import Auth from weaviate.classes.query import Filter from llama_stack.apis.common.content_types import InterleavedContent +from llama_stack.apis.files.files import Files from llama_stack.apis.vector_dbs import VectorDB from llama_stack.apis.vector_io import Chunk, QueryChunksResponse, VectorIO from llama_stack.distribution.request_headers import NeedsRequestProviderData from llama_stack.providers.datatypes import Api, VectorDBsProtocolPrivate +from llama_stack.providers.utils.kvstore import kvstore_impl +from llama_stack.providers.utils.kvstore.api import KVStore from llama_stack.providers.utils.memory.vector_store import ( EmbeddingIndex, VectorDBWithIndex, @@ -27,11 +30,19 @@ from .config import WeaviateRequestProviderData, WeaviateVectorIOConfig log = logging.getLogger(__name__) +VERSION = "v3" +VECTOR_DBS_PREFIX = f"vector_dbs:weaviate:{VERSION}::" +VECTOR_INDEX_PREFIX = f"vector_index:weaviate:{VERSION}::" +OPENAI_VECTOR_STORES_PREFIX = f"openai_vector_stores:weaviate:{VERSION}::" +OPENAI_VECTOR_STORES_FILES_PREFIX = f"openai_vector_stores_files:weaviate:{VERSION}::" +OPENAI_VECTOR_STORES_FILES_CONTENTS_PREFIX = f"openai_vector_stores_files_contents:weaviate:{VERSION}::" + class WeaviateIndex(EmbeddingIndex): - def __init__(self, client: weaviate.Client, collection_name: str): + def __init__(self, client: weaviate.Client, collection_name: str, kvstore: KVStore | None = None): self.client = client self.collection_name = collection_name + self.kvstore = kvstore async def add_chunks(self, chunks: list[Chunk], embeddings: NDArray): assert len(chunks) == len(embeddings), ( @@ -109,11 +120,21 @@ class WeaviateVectorIOAdapter( NeedsRequestProviderData, VectorDBsProtocolPrivate, ): - def __init__(self, config: WeaviateVectorIOConfig, inference_api: Api.inference) -> None: + def __init__( + self, + config: WeaviateVectorIOConfig, + inference_api: Api.inference, + files_api: Files | None, + ) -> None: self.config = config self.inference_api = inference_api self.client_cache = {} self.cache = {} + self.files_api = files_api + self.kvstore: KVStore | None = None + self.vector_db_store = None + self.openai_vector_stores: dict[str, dict[str, Any]] = {} + self.metadata_collection_name = "openai_vector_stores_metadata" def _get_client(self) -> weaviate.Client: provider_data = self.get_request_provider_data() @@ -132,7 +153,26 @@ class WeaviateVectorIOAdapter( return client async def initialize(self) -> None: - pass + """Set up KV store and load existing vector DBs and OpenAI vector stores.""" + # Initialize KV store for metadata + self.kvstore = await kvstore_impl(self.config.kvstore) + + # Load existing vector DB definitions + start_key = VECTOR_DBS_PREFIX + end_key = f"{VECTOR_DBS_PREFIX}\xff" + stored = await self.kvstore.values_in_range(start_key, end_key) + for raw in stored: + vector_db = VectorDB.model_validate_json(raw) + client = self._get_client() + idx = WeaviateIndex(client=client, collection_name=vector_db.identifier, kvstore=self.kvstore) + self.cache[vector_db.identifier] = VectorDBWithIndex( + vector_db=vector_db, + index=idx, + inference_api=self.inference_api, + ) + + # Load OpenAI vector stores metadata into cache + await self.initialize_openai_vector_stores() async def shutdown(self) -> None: for client in self.client_cache.values(): @@ -206,3 +246,21 @@ class WeaviateVectorIOAdapter( raise ValueError(f"Vector DB {vector_db_id} not found") return await index.query_chunks(query, params) + + # OpenAI Vector Stores File operations are not supported in Weaviate + async def _save_openai_vector_store_file( + self, store_id: str, file_id: str, file_info: dict[str, Any], file_contents: list[dict[str, Any]] + ) -> None: + raise NotImplementedError("OpenAI Vector Stores API is not supported in Weaviate") + + async def _load_openai_vector_store_file(self, store_id: str, file_id: str) -> dict[str, Any]: + raise NotImplementedError("OpenAI Vector Stores API is not supported in Weaviate") + + async def _load_openai_vector_store_file_contents(self, store_id: str, file_id: str) -> list[dict[str, Any]]: + raise NotImplementedError("OpenAI Vector Stores API is not supported in Weaviate") + + async def _update_openai_vector_store_file(self, store_id: str, file_id: str, file_info: dict[str, Any]) -> None: + raise NotImplementedError("OpenAI Vector Stores API is not supported in Weaviate") + + async def _delete_openai_vector_store_file_from_storage(self, store_id: str, file_id: str) -> None: + raise NotImplementedError("OpenAI Vector Stores API is not supported in Weaviate") diff --git a/llama_stack/providers/utils/memory/openai_vector_store_mixin.py b/llama_stack/providers/utils/memory/openai_vector_store_mixin.py index 7c97ff7f6..27bb1c997 100644 --- a/llama_stack/providers/utils/memory/openai_vector_store_mixin.py +++ b/llama_stack/providers/utils/memory/openai_vector_store_mixin.py @@ -5,6 +5,7 @@ # the root directory of this source tree. import asyncio +import json import logging import mimetypes import time @@ -35,6 +36,7 @@ from llama_stack.apis.vector_io import ( VectorStoreSearchResponse, VectorStoreSearchResponsePage, ) +from llama_stack.providers.utils.kvstore.api import KVStore from llama_stack.providers.utils.memory.vector_store import content_from_data_and_mime_type, make_overlapped_chunks logger = logging.getLogger(__name__) @@ -59,26 +61,45 @@ class OpenAIVectorStoreMixin(ABC): # These should be provided by the implementing class openai_vector_stores: dict[str, dict[str, Any]] files_api: Files | None + # KV store for persisting OpenAI vector store metadata + kvstore: KVStore | None - @abstractmethod async def _save_openai_vector_store(self, store_id: str, store_info: dict[str, Any]) -> None: """Save vector store metadata to persistent storage.""" - pass + assert self.kvstore is not None + key = f"{OPENAI_VECTOR_STORES_PREFIX}{store_id}" + await self.kvstore.set(key=key, value=json.dumps(store_info)) + # update in-memory cache + self.openai_vector_stores[store_id] = store_info - @abstractmethod async def _load_openai_vector_stores(self) -> dict[str, dict[str, Any]]: """Load all vector store metadata from persistent storage.""" - pass + assert self.kvstore is not None + start_key = OPENAI_VECTOR_STORES_PREFIX + end_key = f"{OPENAI_VECTOR_STORES_PREFIX}\xff" + stored_data = await self.kvstore.values_in_range(start_key, end_key) + + stores: dict[str, dict[str, Any]] = {} + for item in stored_data: + info = json.loads(item) + stores[info["id"]] = info + return stores - @abstractmethod async def _update_openai_vector_store(self, store_id: str, store_info: dict[str, Any]) -> None: """Update vector store metadata in persistent storage.""" - pass + assert self.kvstore is not None + key = f"{OPENAI_VECTOR_STORES_PREFIX}{store_id}" + await self.kvstore.set(key=key, value=json.dumps(store_info)) + # update in-memory cache + self.openai_vector_stores[store_id] = store_info - @abstractmethod async def _delete_openai_vector_store_from_storage(self, store_id: str) -> None: """Delete vector store metadata from persistent storage.""" - pass + assert self.kvstore is not None + key = f"{OPENAI_VECTOR_STORES_PREFIX}{store_id}" + await self.kvstore.delete(key) + # remove from in-memory cache + self.openai_vector_stores.pop(store_id, None) @abstractmethod async def _save_openai_vector_store_file( @@ -117,6 +138,10 @@ class OpenAIVectorStoreMixin(ABC): """Unregister a vector database (provider-specific implementation).""" pass + async def initialize_openai_vector_stores(self) -> None: + """Load existing OpenAI vector stores into the in-memory cache.""" + self.openai_vector_stores = await self._load_openai_vector_stores() + @abstractmethod async def insert_chunks( self, diff --git a/llama_stack/templates/open-benchmark/open_benchmark.py b/llama_stack/templates/open-benchmark/open_benchmark.py index 56ee9c47d..63a27e07f 100644 --- a/llama_stack/templates/open-benchmark/open_benchmark.py +++ b/llama_stack/templates/open-benchmark/open_benchmark.py @@ -128,6 +128,7 @@ def get_distribution_template() -> DistributionTemplate: provider_id="${env.ENABLE_PGVECTOR:+pgvector}", provider_type="remote::pgvector", config=PGVectorVectorIOConfig.sample_run_config( + f"~/.llama/distributions/{name}", db="${env.PGVECTOR_DB:=}", user="${env.PGVECTOR_USER:=}", password="${env.PGVECTOR_PASSWORD:=}", diff --git a/llama_stack/templates/open-benchmark/run.yaml b/llama_stack/templates/open-benchmark/run.yaml index 0b368ebc9..7d07cc4bf 100644 --- a/llama_stack/templates/open-benchmark/run.yaml +++ b/llama_stack/templates/open-benchmark/run.yaml @@ -54,6 +54,9 @@ providers: db: ${env.PGVECTOR_DB:=} user: ${env.PGVECTOR_USER:=} password: ${env.PGVECTOR_PASSWORD:=} + kvstore: + type: sqlite + db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/open-benchmark}/pgvector_registry.db safety: - provider_id: llama-guard provider_type: inline::llama-guard diff --git a/llama_stack/templates/starter/run.yaml b/llama_stack/templates/starter/run.yaml index ad449cb1b..8e20f5224 100644 --- a/llama_stack/templates/starter/run.yaml +++ b/llama_stack/templates/starter/run.yaml @@ -166,6 +166,9 @@ providers: db: ${env.PGVECTOR_DB:=} user: ${env.PGVECTOR_USER:=} password: ${env.PGVECTOR_PASSWORD:=} + kvstore: + type: sqlite + db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter}/pgvector_registry.db files: - provider_id: meta-reference-files provider_type: inline::localfs diff --git a/llama_stack/templates/starter/starter.py b/llama_stack/templates/starter/starter.py index c0ac44183..f6ca73028 100644 --- a/llama_stack/templates/starter/starter.py +++ b/llama_stack/templates/starter/starter.py @@ -241,6 +241,7 @@ def get_distribution_template() -> DistributionTemplate: provider_id="${env.ENABLE_PGVECTOR:=__disabled__}", provider_type="remote::pgvector", config=PGVectorVectorIOConfig.sample_run_config( + f"~/.llama/distributions/{name}", db="${env.PGVECTOR_DB:=}", user="${env.PGVECTOR_USER:=}", password="${env.PGVECTOR_PASSWORD:=}",