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from fastapi import FastAPI, HTTPException, Header, Request
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from fastapi.middleware.cors import CORSMiddleware
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from fastapi.responses import StreamingResponse
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from pydantic import BaseModel
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import openai
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from typing import List, Optional
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import logging
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from itertools import cycle
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import asyncio
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import uvicorn
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from app import config
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logging.basicConfig(
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level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s"
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)
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logger = logging.getLogger(__name__)
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app = FastAPI()
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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API_KEYS = config.settings.API_KEYS
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key_cycle = cycle(API_KEYS)
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key_lock = asyncio.Lock()
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class ChatRequest(BaseModel):
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messages: List[dict]
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model: str = "llama-3.2-90b-text-preview"
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temperature: Optional[float] = 0.7
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max_tokens: Optional[int] = 8000
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stream: Optional[bool] = False
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async def verify_authorization(authorization: str = Header(None)):
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if not authorization:
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logger.error("Missing Authorization header")
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raise HTTPException(status_code=401, detail="Missing Authorization header")
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if not authorization.startswith("Bearer "):
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logger.error("Invalid Authorization header format")
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raise HTTPException(
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status_code=401, detail="Invalid Authorization header format"
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)
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token = authorization.replace("Bearer ", "")
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if token not in config.settings.ALLOWED_TOKENS:
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logger.error("Invalid token")
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raise HTTPException(status_code=401, detail="Invalid token")
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return token
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@app.get("/v1/models")
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async def list_models(authorization: str = Header(None)):
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await verify_authorization(authorization)
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async with key_lock:
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api_key = next(key_cycle)
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logger.info(f"Using API key: {api_key[:8]}...")
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try:
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client = openai.OpenAI(api_key=api_key, base_url=config.settings.BASE_URL)
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response = client.models.list()
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logger.info("Successfully retrieved models list")
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return response
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except Exception as e:
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logger.error(f"Error listing models: {str(e)}")
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raise HTTPException(status_code=500, detail=str(e))
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@app.post("/v1/chat/completions")
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async def chat_completion(request: ChatRequest, authorization: str = Header(None)):
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await verify_authorization(authorization)
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async with key_lock:
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api_key = next(key_cycle)
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logger.info(f"Using API key: {api_key[:8]}...")
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try:
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logger.info(f"Chat completion request - Model: {request.model}")
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client = openai.OpenAI(api_key=api_key, base_url=config.settings.BASE_URL)
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response = client.chat.completions.create(
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model=request.model,
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messages=request.messages,
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temperature=request.temperature,
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max_tokens=request.max_tokens,
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stream=request.stream if hasattr(request, "stream") else False,
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)
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if hasattr(request, "stream") and request.stream:
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logger.info("Streaming response enabled")
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async def generate():
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for chunk in response:
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yield f"data: {chunk.model_dump_json()}\n\n"
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return StreamingResponse(content=generate(), media_type="text/event-stream")
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logger.info("Chat completion successful")
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return response
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except Exception as e:
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logger.error(f"Error in chat completion: {str(e)}")
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raise HTTPException(status_code=500, detail=str(e))
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@app.get("/health")
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async def health_check(authorization: str = Header(None)):
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await verify_authorization(authorization)
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logger.info("Health check endpoint called")
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return {"status": "healthy"}
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if __name__ == "__main__":
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uvicorn.run(app, host="0.0.0.0", port=8000) |
