Update app.py

app.py

@@ -1,3 +1,4 @@
+import logging
 from fastapi import FastAPI, Request
 from fastapi.responses import StreamingResponse
 import httpx
@@ -5,16 +6,24 @@ 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')
@@ -34,27 +43,45 @@ async def chat(request: Request):
             "system": ""
         }
     }
+    logger.debug(f"LLM payload: {llm_payload}")
 
     headers = {
         'Host': 'llm.zed.dev',
         'accept': '*/*',
         'content-type': 'application/json',
-        'authorization': f'Bearer {jwt_token}',  # Use the generated JWT token
+        '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:
-            async with client.stream('POST', url, headers=headers, json=llm_payload) as response:
-                async for chunk in response.aiter_bytes():
-                    yield chunk
+            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)