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feat: split API and provider specs into separate llama-stack-api pkg (#3895)
# What does this PR do? Extract API definitions and provider specifications into a standalone llama-stack-api package that can be published to PyPI independently of the main llama-stack server. see: https://github.com/llamastack/llama-stack/pull/2978 and https://github.com/llamastack/llama-stack/pull/2978#issuecomment-3145115942 Motivation External providers currently import from llama-stack, which overrides the installed version and causes dependency conflicts. This separation allows external providers to: - Install only the type definitions they need without server dependencies - Avoid version conflicts with the installed llama-stack package - Be versioned and released independently This enables us to re-enable external provider module tests that were previously blocked by these import conflicts. Changes - Created llama-stack-api package with minimal dependencies (pydantic, jsonschema) - Moved APIs, providers datatypes, strong_typing, and schema_utils - Updated all imports from llama_stack.* to llama_stack_api.* - Configured local editable install for development workflow - Updated linting and type-checking configuration for both packages Next Steps - Publish llama-stack-api to PyPI - Update external provider dependencies - Re-enable external provider module tests Pre-cursor PRs to this one: - #4093 - #3954 - #4064 These PRs moved key pieces _out_ of the Api pkg, limiting the scope of change here. relates to #3237 ## Test Plan Package builds successfully and can be imported independently. All pre-commit hooks pass with expected exclusions maintained. --------- Signed-off-by: Charlie Doern <cdoern@redhat.com>
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Charlie Doern
GitHub
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from enum import StrEnum
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from typing import Any, Literal, Protocol, runtime_checkable
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from pydantic import BaseModel, ConfigDict, Field, field_validator
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from llama_stack.apis.common.tracing import telemetry_traceable
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from llama_stack.apis.resource import Resource, ResourceType
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from llama_stack.apis.version import LLAMA_STACK_API_V1
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from llama_stack.schema_utils import json_schema_type, webmethod
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class CommonModelFields(BaseModel):
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metadata: dict[str, Any] = Field(
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default_factory=dict,
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description="Any additional metadata for this model",
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)
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@json_schema_type
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class ModelType(StrEnum):
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"""Enumeration of supported model types in Llama Stack.
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:cvar llm: Large language model for text generation and completion
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:cvar embedding: Embedding model for converting text to vector representations
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:cvar rerank: Reranking model for reordering documents based on their relevance to a query
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"""
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llm = "llm"
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embedding = "embedding"
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rerank = "rerank"
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@json_schema_type
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class Model(CommonModelFields, Resource):
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"""A model resource representing an AI model registered in Llama Stack.
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:param type: The resource type, always 'model' for model resources
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:param model_type: The type of model (LLM or embedding model)
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:param metadata: Any additional metadata for this model
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:param identifier: Unique identifier for this resource in llama stack
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:param provider_resource_id: Unique identifier for this resource in the provider
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:param provider_id: ID of the provider that owns this resource
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"""
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type: Literal[ResourceType.model] = ResourceType.model
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@property
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def model_id(self) -> str:
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return self.identifier
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@property
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def provider_model_id(self) -> str:
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assert self.provider_resource_id is not None, "Provider resource ID must be set"
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return self.provider_resource_id
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model_config = ConfigDict(protected_namespaces=())
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model_type: ModelType = Field(default=ModelType.llm)
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@field_validator("provider_resource_id")
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@classmethod
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def validate_provider_resource_id(cls, v):
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if v is None:
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raise ValueError("provider_resource_id cannot be None")
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return v
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class ModelInput(CommonModelFields):
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model_id: str
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provider_id: str | None = None
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provider_model_id: str | None = None
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model_type: ModelType | None = ModelType.llm
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model_config = ConfigDict(protected_namespaces=())
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class ListModelsResponse(BaseModel):
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data: list[Model]
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@json_schema_type
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class OpenAIModel(BaseModel):
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"""A model from OpenAI.
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:id: The ID of the model
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:object: The object type, which will be "model"
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:created: The Unix timestamp in seconds when the model was created
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:owned_by: The owner of the model
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:custom_metadata: Llama Stack-specific metadata including model_type, provider info, and additional metadata
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"""
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id: str
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object: Literal["model"] = "model"
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created: int
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owned_by: str
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custom_metadata: dict[str, Any] | None = None
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class OpenAIListModelsResponse(BaseModel):
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data: list[OpenAIModel]
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@runtime_checkable
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@telemetry_traceable
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class Models(Protocol):
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async def list_models(self) -> ListModelsResponse:
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"""List all models.
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:returns: A ListModelsResponse.
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"""
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...
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@webmethod(route="/models", method="GET", level=LLAMA_STACK_API_V1)
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async def openai_list_models(self) -> OpenAIListModelsResponse:
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"""List models using the OpenAI API.
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:returns: A OpenAIListModelsResponse.
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"""
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...
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@webmethod(route="/models/{model_id:path}", method="GET", level=LLAMA_STACK_API_V1)
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async def get_model(
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self,
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model_id: str,
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) -> Model:
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"""Get model.
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Get a model by its identifier.
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:param model_id: The identifier of the model to get.
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:returns: A Model.
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"""
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...
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@webmethod(route="/models", method="POST", level=LLAMA_STACK_API_V1, deprecated=True)
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async def register_model(
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self,
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model_id: str,
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provider_model_id: str | None = None,
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provider_id: str | None = None,
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metadata: dict[str, Any] | None = None,
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model_type: ModelType | None = None,
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) -> Model:
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"""Register model.
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Register a model.
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:param model_id: The identifier of the model to register.
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:param provider_model_id: The identifier of the model in the provider.
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:param provider_id: The identifier of the provider.
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:param metadata: Any additional metadata for this model.
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:param model_type: The type of model to register.
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:returns: A Model.
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"""
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...
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@webmethod(route="/models/{model_id:path}", method="DELETE", level=LLAMA_STACK_API_V1, deprecated=True)
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async def unregister_model(
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self,
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model_id: str,
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) -> None:
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"""Unregister model.
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Unregister a model.
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:param model_id: The identifier of the model to unregister.
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"""
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...
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