Update main.py

main.py

@@ -232,53 +232,6 @@ async def chat(request: ChatRequest, background_tasks: BackgroundTasks, api_key:
 
 
 
-@app.post("/digiyatra-chat/", response_class=StreamingResponse, tags=["Chat"])
-async def chat(request: ChatRequest, background_tasks: BackgroundTasks, api_key: str = Depends(get_api_key)):
-    try:
-        document_list = load_embeddings(request.index_id)
-        search_results = embeddings.search(request.query, 6)
-        context = "\n".join([document_list[idx[0]] for idx in search_results])
-
-        rag_prompt = f"Based on the following context, please answer the user's question:\n\nContext:\n{context}\n\nUser's question: {request.query}\n\nAnswer:"
-        system_prompt = "You are a helpful assistant tasked with providing answers using the context provided"
-        
-        conversation_id = request.conversation_id or str(uuid.uuid4())
-
-        if request.enable_followup:
-            llm_request = {
-                "query": rag_prompt,
-                "model_id": 'openai/gpt-4o-mini',
-                "conversation_id": conversation_id,
-                "user_id": request.user_id
-            }
-            endpoint_url = "https://pvanand-general-chat.hf.space/digiyatra-followup"
-        else:
-            llm_request = {
-                "prompt": rag_prompt,
-                "system_message": system_prompt,
-                "model_id": request.model_id,
-                "conversation_id": conversation_id,
-                "user_id": request.user_id
-            }
-            endpoint_url = "https://pvanand-audio-chat.hf.space/llm-agent"
-        
-        logger.info(f"Starting chat response generation for user: {request.user_id} Full request: {llm_request}")
-        
-        def response_generator():
-            full_response = ""
-            for chunk in stream_llm_request(api_key, llm_request, endpoint_url):
-                full_response += chunk
-                yield chunk
-            logger.info(f"Finished chat response generation for user: {request.user_id} Full response: {full_response}")
-        
-        return StreamingResponse(response_generator(), media_type="text/event-stream")
-
-    except Exception as e:
-        logger.error(f"Error in chat endpoint: {str(e)}")
-        raise HTTPException(status_code=500, detail=f"Error in chat endpoint: {str(e)}")
-
-
-
 @app.on_event("startup")
 async def startup_event():
     check_and_index_csv_files()