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Use our own pydantic models for OpenAI Server APIs

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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.
This commit is contained in:
Ben Browning 2025-04-08 09:01:35 -04:00
parent a193c9fc3f
commit 92fdf6d0c9
8 changed files with 1826 additions and 15 deletions
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4
llama_stack/distribution/routers/routers.py
View file

@ -8,7 +8,6 @@ import time
from typing import Any, AsyncGenerator, AsyncIterator, Dict, List, Optional, Union
from openai.types.chat import ChatCompletion as OpenAIChatCompletion
from openai.types.chat import ChatCompletionMessageParam as OpenAIChatCompletionMessageParam
from openai.types.completion import Completion as OpenAICompletion
from llama_stack.apis.common.content_types import (
@ -39,6 +38,7 @@ from llama_stack.apis.inference import (
ToolDefinition,
ToolPromptFormat,
)
from llama_stack.apis.inference.inference import OpenAIMessageParam
from llama_stack.apis.models import Model, ModelType
from llama_stack.apis.safety import RunShieldResponse, Safety
from llama_stack.apis.scoring import (
@ -478,7 +478,7 @@ class InferenceRouter(Inference):
async def openai_chat_completion(
self,
model: str,
messages: List[OpenAIChatCompletionMessageParam],
messages: List[OpenAIMessageParam],
frequency_penalty: Optional[float] = None,
function_call: Optional[Union[str, Dict[str, Any]]] = None,
functions: Optional[List[Dict[str, Any]]] = None,

3
llama_stack/distribution/routers/routing_tables.py
View file

@ -9,7 +9,6 @@ import time
import uuid
from typing import Any, Dict, List, Optional
from openai.types.model import Model as OpenAIModel
from pydantic import TypeAdapter
from llama_stack.apis.benchmarks import Benchmark, Benchmarks, ListBenchmarksResponse
@ -25,7 +24,7 @@ from llama_stack.apis.datasets import (
RowsDataSource,
URIDataSource,
)
from llama_stack.apis.models import ListModelsResponse, Model, Models, ModelType, OpenAIListModelsResponse
from llama_stack.apis.models import ListModelsResponse, Model, Models, ModelType, OpenAIListModelsResponse, OpenAIModel
from llama_stack.apis.resource import ResourceType
from llama_stack.apis.scoring_functions import (
ListScoringFunctionsResponse,