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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)
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