app.py

import logging
from fastapi import FastAPI, Request
from fastapi.responses import StreamingResponse
import httpx
import json
import os
from helper import create_jwt, generate_random_tuple

# 设置日志
logging.basicConfig(level=logging.DEBUG)
logger = logging.getLogger(__name__)

app = FastAPI()

@app.post('/ai/v1/chat/completions')
async def chat(request: Request):
    logger.debug("Received request")
    
    # Generate JWT token
    github_username, user_id = generate_random_tuple()
    jwt_token = create_jwt(github_username, user_id)
    logger.debug(f"Generated JWT token: {jwt_token}")

    # Get the payload from the request
    payload = await request.json()
    logger.debug(f"Received payload: {payload}")

    # Get the model from the payload, defaulting to "claude-3-5-sonnet-20240620"
    model = payload.get('model', 'claude-3-5-sonnet-20240620')

    # Prepare the request for the LLM API
    url = "https://llm.zed.dev/completion?"
    
    llm_payload = {
        "provider": "anthropic",
        "model": model,
        "provider_request": {
            "model": model,
            "max_tokens": payload.get('max_tokens', 8192),
            "temperature": payload.get('temperature', 0),
            "top_p": payload.get('top_p', 0.7),
            "messages": payload['messages'],
            "system": ""
        }
    }
    logger.debug(f"LLM payload: {llm_payload}")

    headers = {
        'Host': 'llm.zed.dev',
        'accept': '*/*',
        'content-type': 'application/json',
        'authorization': f'Bearer {jwt_token}',
        'user-agent': 'Zed/0.149.3 (macos; aarch64)'
    }
    logger.debug(f"Request headers: {headers}")

    # Get proxy from environment variable
    proxy = os.environ.get('HTTP_PROXY', None)
    proxies = {'http': proxy, 'https': proxy} if proxy else None
    logger.debug(f"Using proxies: {proxies}")

    async def generate():
        async with httpx.AsyncClient(proxies=proxies) as client:
            try:
                async with client.stream('POST', url, headers=headers, json=llm_payload) as response:
                    logger.debug(f"LLM API response status: {response.status_code}")
                    logger.debug(f"LLM API response headers: {response.headers}")
                    if response.status_code != 200:
                        error_content = await response.read()
                        logger.error(f"LLM API error response: {error_content}")
                        yield f"Error: {response.status_code} - {error_content}"
                    else:
                        async for chunk in response.aiter_bytes():
                            yield chunk
            except Exception as e:
                logger.error(f"Error during LLM API request: {str(e)}")
                yield f"Error: {str(e)}"

    return StreamingResponse(generate(), media_type='application/octet-stream')

@app.get("/")
async def root():
    return {"message": "Welcome to the AI Chat Completions API"}

if __name__ == '__main__':
    import uvicorn
    uvicorn.run(app, host="0.0.0.0", port=8000)