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92fdf6d0c9
Importing the models from the OpenAI client library required a top-level dependency on the openai python package, and also was incompatible with our API generation code due to some quirks in how the OpenAI pydantic models are defined. So, this creates our own stubs of those pydantic models so that we're in more direct control of our API surface for this OpenAI-compatible API, so that it works with our code generation, and so that the openai python client isn't a hard requirement of Llama Stack's API.
108 lines
2.8 KiB
Python
108 lines
2.8 KiB
Python
# 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 Enum
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from typing import Any, Dict, List, Literal, Optional, Protocol, runtime_checkable
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from pydantic import BaseModel, ConfigDict, Field
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from llama_stack.apis.resource import Resource, ResourceType
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from llama_stack.providers.utils.telemetry.trace_protocol import trace_protocol
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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(str, Enum):
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llm = "llm"
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embedding = "embedding"
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@json_schema_type
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class Model(CommonModelFields, Resource):
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type: Literal[ResourceType.model.value] = ResourceType.model.value
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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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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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class ModelInput(CommonModelFields):
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model_id: str
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provider_id: Optional[str] = None
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provider_model_id: Optional[str] = None
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model_type: Optional[ModelType] = 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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"""
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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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class OpenAIListModelsResponse(BaseModel):
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data: List[OpenAIModel]
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@runtime_checkable
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@trace_protocol
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class Models(Protocol):
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@webmethod(route="/models", method="GET")
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async def list_models(self) -> ListModelsResponse: ...
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@webmethod(route="/openai/v1/models", method="GET")
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async def openai_list_models(self) -> OpenAIListModelsResponse: ...
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@webmethod(route="/models/{model_id:path}", method="GET")
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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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@webmethod(route="/models", method="POST")
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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: Optional[str] = None,
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provider_id: Optional[str] = None,
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metadata: Optional[Dict[str, Any]] = None,
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model_type: Optional[ModelType] = None,
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) -> Model: ...
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@webmethod(route="/models/{model_id:path}", method="DELETE")
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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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