Implement automatic pydantic model selection for 'request' parameter in FastAPI applications

[ajndkr]

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Example Code

from functools import lru_cache
from typing import Callable
from fastapi import Depends, FastAPI
from langchain import ConversationChain
from langchain.chat_models import ChatOpenAI
from pydantic import BaseModel
from lanarky.responses import StreamingResponse

app = FastAPI(title="ConversationChainDemo")

class QueryRequest(BaseModel):
    query: str

def conversation_chain_dependency() -> Callable[[], ConversationChain]:
    @lru_cache(maxsize=1)
    def dependency() -> ConversationChain:
        return ConversationChain(
            llm=ChatOpenAI(
                temperature=0,
                streaming=True,
            ),
            verbose=True,
        )

    return dependency

conversation_chain = conversation_chain_dependency()

@app.post("/chat")
async def chat(
    request: QueryRequest,
    chain: ConversationChain = Depends(conversation_chain),
) -> StreamingResponse:
    return StreamingResponse.from_chain(
        chain, request.query, media_type="text/event-stream"
    )

Description

Hello! I am building a library on top of FastAPI: https://github.com/ajndkr/lanarky. The objective is to simplify building FastAPI applications for LLM projects.

There is a new feature request for which I'm trying to understand how it can be implemented. I have shared an example code.

The feature request is to auto-select the pydantic model for request parameter based on chain instance. I have gone through the documentation and haven't been able to decide if this can be solved via dependency injection or creating a custom APIRouter class. I'm not a FastAPI expert, so I'm really eager to brainstorm a bit with the experts here. Any help is appreciated!

Operating System

macOS

Operating System Details

No response

FastAPI Version

0.95.2

Python Version

3.9.16

Additional Context

No response