import json
from fastapi import APIRouter, HTTPException
from fastapi.responses import StreamingResponse
from core.llm import LLMClient
from core.memory import save_user_state, load_user_state
from core.session import session_manager
import logging

router = APIRouter()
logger = logging.getLogger(__name__)

llm_client = LLMClient(provider="ollama")  # Default to Ollama

@router.post("/chat")
async def chat(user_id: str, message: str):
    if not message:
        raise HTTPException(status_code=400, detail="Message is required")
    
    try:
        # Use session manager for better session handling
        session = session_manager.get_session(user_id)
        conversation_history = session.get("conversation", [])
        
        # Add user message to history
        conversation_history.append({"role": "user", "content": message})
        
        # Generate AI response
        full_response = ""
        response_stream = llm_client.generate(prompt=message, stream=True)
        
        # Collect streamed response
        for chunk in response_stream:
            full_response += chunk
        
        # Save updated conversation using session manager
        conversation_history.append({"role": "assistant", "content": full_response})
        session_manager.update_session(user_id, {"conversation": conversation_history})
        
        logger.info(f"Successfully processed chat for user {user_id}")
        return {"response": full_response}
        
    except Exception as e:
        logger.error(f"LLM generation failed for user {user_id}: {e}")
        raise HTTPException(status_code=500, detail=f"LLM generation failed: {e}")