app.py

import os
from typing import Optional
from functools import partial
import asyncio
from typing_extensions import Annotated
from fastapi import Depends, FastAPI, HTTPException, status
from fastapi.middleware.cors import CORSMiddleware
from fastapi.security.http import HTTPAuthorizationCredentials, HTTPBearer
from contextlib import asynccontextmanager

from sse_starlette import EventSourceResponse
from chat import (create_stream_chat_completion_response,
                  create_chat_completion_response,
                  create_stream_image2text_completion_response
                  
                  )


from chat_engine.chat_model import ChatModel
from tools import torch_gc
import uvicorn

from protocol import (
    ChatCompletionRequest,
    ChatCompletionResponse,
    ModelList,
    ModelCard,
    ChatImage2TextCompletionRequest
    
)

async def sweeper() -> None:
    while True:
        torch_gc()
        await asyncio.sleep(300)


@asynccontextmanager
async def lifespan(app: "FastAPI", chat_model: "ChatModel"):  # collects GPU memory
    if chat_model.engine_type == "huggingface":
        asyncio.create_task(sweeper())

    yield
    torch_gc()
    
def create_app(chat_model: "ChatModel") -> "FastAPI":
    root_path = os.environ.get("FASTAPI_ROOT_PATH", "")
    app = FastAPI(lifespan=partial(lifespan, chat_model=chat_model), root_path=root_path)
    app.add_middleware(
        CORSMiddleware,
        allow_origins=["*"],
        allow_credentials=True,
        allow_methods=["*"],
        allow_headers=["*"],
    )
    api_key = os.environ.get("API_KEY")
    security = HTTPBearer(auto_error=False)

    async def verify_api_key(auth: Annotated[Optional[HTTPAuthorizationCredentials], Depends(security)]):
        if api_key and (auth is None or auth.credentials != api_key):
            raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="Invalid API key.")
        
    @app.get(
        "/v1/models",
        response_model=ModelList,
        status_code=status.HTTP_200_OK,
        dependencies=[Depends(verify_api_key)],
    )
    async def list_models():
        model_card = ModelCard(id="gpt-3.5-turbo")
        return ModelList(data=[model_card])

    @app.post(
        "/v1/chat/completions",
        response_model=ChatCompletionResponse,
        status_code=status.HTTP_200_OK,
        dependencies=[Depends(verify_api_key)],
    )
    async def create_image_2_text(request: ChatImage2TextCompletionRequest):
        # if not chat_model.engine.can_generate:
        #     raise HTTPException(status_code=status.HTTP_405_METHOD_NOT_ALLOWED, detail="Not allowed")

        if request.stream:
            generate = create_stream_image2text_completion_response(request, chat_model)
            return EventSourceResponse(generate, media_type="text/event-stream")
        else:
            return await create_chat_completion_response(request, chat_model)
    return app


def run_api() -> None:
    model = os.environ.get("MODEL","Qwen/Qwen2-VL-7B-Instruct")
    chat_model = ChatModel(model)
    app = create_app(chat_model)

    api_host = os.environ.get("API_HOST", "0.0.0.0")
    api_port = int(os.environ.get("API_PORT", "8000"))
    print("Visit http://localhost:{}/docs for API document.".format(api_port))
    uvicorn.run(app, host=api_host, port=api_port)
    
if __name__ == "__main__":
    run_api()