Update app.py

app.py

@@ -98,12 +98,11 @@ async def websocket_endpoint(ws: WebSocket):
             del sessions[stream_sid]
         print(f"Session cleaned up for stream {stream_sid}")
 
-# THIS IS THE CORRECTED FUNCTION FROM THE PREVIOUS STEP, NOW IN THE FULL FILE
+
 async def process_user_audio(ws: WebSocket, stream_sid: str, audio_chunk: np.ndarray):
     """The main logic loop: STT -> LLM -> (Tool/TTS)"""
     print(f"[{stream_sid}] Processing audio chunk of size {len(audio_chunk)}...")
     
-    # 1. Speech-to-Text
     user_text = await transcribe_audio_chunk(audio_chunk)
     if not user_text:
         print(f"[{stream_sid}] No text transcribed.")
@@ -122,7 +121,6 @@ async def process_user_audio(ws: WebSocket, stream_sid: str, audio_chunk: np.nda
             if chunk is None: break
             yield chunk
 
-    # 2. Start LLM and TTS tasks concurrently
     llm_task = asyncio.create_task(get_llm_response(sessions[stream_sid]["messages"], llm_chunk_handler))
     tts_task = asyncio.create_task(stream_and_send_audio(ws, stream_sid, tts_text_iterator()))
 
@@ -133,13 +131,10 @@ async def process_user_audio(ws: WebSocket, stream_sid: str, audio_chunk: np.nda
     if assistant_message and assistant_message.get("content"):
        sessions[stream_sid]["messages"].append(assistant_message)
 
-    # 3. Handle Tool Calls if any
     if tool_calls:
-        # Before executing, add the assistant's tool request to history
         sessions[stream_sid]["messages"].append(assistant_message)
         
         for tool_call_data in tool_calls:
-            # Recreate a simple object that mimics the structure tool_handler expects
             tool_call = type('ToolCall', (), {
                 'id': tool_call_data.get('id'), 
                 'function': type('Function', (), tool_call_data.get('function'))
@@ -149,7 +144,6 @@ async def process_user_audio(ws: WebSocket, stream_sid: str, audio_chunk: np.nda
             tool_result_message = execute_tool_call(tool_call)
             sessions[stream_sid]["messages"].append(tool_result_message)
 
-        # 4. Get a final response from the LLM after executing the tool
         final_tts_queue = asyncio.Queue()
         async def final_llm_chunk_handler(chunk): await final_tts_queue.put(chunk)
         async def final_tts_iterator():
@@ -186,5 +180,7 @@ async def stream_and_send_audio(ws: WebSocket, stream_sid: str, text_iterator):
 
 if __name__ == "__main__":
     import uvicorn
-    print("Starting RentBot server...")
-    uvicorn.run(app, host="0.0.0.0", port=8000)
+    # Hugging Face Spaces expects the app to run on port 7860
+    port = int(os.environ.get("PORT", 7860))
+    print(f"Starting RentBot server on port {port}...")
+    uvicorn.run(app, host="0.0.0.0", port=port)