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Add OpenAI-Compatible models, completions, chat/completions endpoints

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This stubs in some OpenAI server-side compatibility with three new
endpoints:

/v1/openai/v1/models
/v1/openai/v1/completions
/v1/openai/v1/chat/completions

This gives common inference apps using OpenAI clients the ability to
talk to Llama Stack using an endpoint like
http://localhost:8321/v1/openai/v1 .

The two "v1" instances in there isn't awesome, but the thinking is
that Llama Stack's API is v1 and then our OpenAI compatibility layer
is compatible with OpenAI V1. And, some OpenAI clients implicitly
assume the URL ends with "v1", so this gives maximum compatibility.

The openai models endpoint is implemented in the routing layer, and
just returns all the models Llama Stack knows about.

The chat endpoints are only actually implemented for the remote-vllm
provider right now, and it just proxies the completion and chat
completion requests to the backend vLLM.

The goal to support this for every inference provider - proxying
directly to the provider's OpenAI endpoint for OpenAI-compatible
providers. For providers that don't have an OpenAI-compatible API,
we'll add a mixin to translate incoming OpenAI requests to Llama Stack
inference requests and translate the Llama Stack inference responses
to OpenAI responses.
This commit is contained in:
Ben Browning 2025-04-07 21:27:06 -04:00
parent e2299291c4
commit a193c9fc3f
12 changed files with 443 additions and 8 deletions
Download patch file Download diff file Expand all files Collapse all files

58
llama_stack/providers/utils/inference/openai_compat.py
View file

@ -6,9 +6,10 @@
import json
import logging
import warnings
from typing import AsyncGenerator, Dict, Iterable, List, Optional, Union
from typing import Any, AsyncGenerator, Dict, Iterable, List, Optional, Union
from openai import AsyncStream
from openai.types.chat import ChatCompletion as OpenAIChatCompletion
from openai.types.chat import (
ChatCompletionAssistantMessageParam as OpenAIChatCompletionAssistantMessage,
)
@ -54,6 +55,7 @@ from openai.types.chat.chat_completion_content_part_image_param import (
from openai.types.chat.chat_completion_message_tool_call_param import (
Function as OpenAIFunction,
)
from openai.types.completion import Completion as OpenAICompletion
from pydantic import BaseModel
from llama_stack.apis.common.content_types import (
@ -1049,3 +1051,57 @@ async def convert_openai_chat_completion_stream(
stop_reason=stop_reason,
)
)
class OpenAICompletionUnsupportedMixin:
async def openai_completion(
self,
model: str,
prompt: str,
best_of: Optional[int] = None,
echo: Optional[bool] = None,
frequency_penalty: Optional[float] = None,
logit_bias: Optional[Dict[str, float]] = None,
logprobs: Optional[bool] = None,
max_tokens: Optional[int] = None,
n: Optional[int] = None,
presence_penalty: Optional[float] = None,
seed: Optional[int] = None,
stop: Optional[Union[str, List[str]]] = None,
stream: Optional[bool] = None,
stream_options: Optional[Dict[str, Any]] = None,
temperature: Optional[float] = None,
top_p: Optional[float] = None,
user: Optional[str] = None,
) -> OpenAICompletion:
raise ValueError(f"{self.__class__.__name__} doesn't support openai completion")
class OpenAIChatCompletionUnsupportedMixin:
async def openai_chat_completion(
self,
model: str,
messages: List[OpenAIChatCompletionMessage],
frequency_penalty: Optional[float] = None,
function_call: Optional[Union[str, Dict[str, Any]]] = None,
functions: Optional[List[Dict[str, Any]]] = None,
logit_bias: Optional[Dict[str, float]] = None,
logprobs: Optional[bool] = None,
max_completion_tokens: Optional[int] = None,
max_tokens: Optional[int] = None,
n: Optional[int] = None,
parallel_tool_calls: Optional[bool] = None,
presence_penalty: Optional[float] = None,
response_format: Optional[Dict[str, str]] = None,
seed: Optional[int] = None,
stop: Optional[Union[str, List[str]]] = None,
stream: Optional[bool] = None,
stream_options: Optional[Dict[str, Any]] = None,
temperature: Optional[float] = None,
tool_choice: Optional[Union[str, Dict[str, Any]]] = None,
tools: Optional[List[Dict[str, Any]]] = None,
top_logprobs: Optional[int] = None,
top_p: Optional[float] = None,
user: Optional[str] = None,
) -> OpenAIChatCompletion:
raise ValueError(f"{self.__class__.__name__} doesn't support openai chat completion")