handler.py

from fastapi import FastAPI, HTTPException
from pydantic import BaseModel
import logging
from QwenChat import EnterpriseQwenChat  # Import the chat system from QwenChat

# Initialize FastAPI app
app = FastAPI()

# Logging setup
logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(message)s")

# Initialize QwenChat system
model_directory = "./qwen"  # Path to the model directory
chat_system = EnterpriseQwenChat(model_directory=model_directory)


# Define input schema for the API
class ChatRequest(BaseModel):
    user_input: str


@app.get("/")
def health_check():
    """Health check endpoint."""
    return {"status": "Healthy", "message": "Model API is live!"}


@app.post("/chat")
def chat(request: ChatRequest):
    """
    Chat endpoint: Handles user input and returns the model's response.
    """
    try:
        user_input = request.user_input.strip()
        if not user_input:
            raise HTTPException(status_code=400, detail="User input cannot be empty.")

        # Add user input to the conversation
        chat_system.conversation_manager.add_turn("user", user_input)

        # Generate AI response
        prompt = chat_system.conversation_manager.get_prompt()
        response = chat_system.response_generator.generate_response(
            prompt, len(chat_system.conversation_manager.turns)
        )

        # Add response to conversation history
        chat_system.conversation_manager.add_turn("assistant", response)

        return {
            "response": response,
            "conversation": [
                {"role": turn.role, "content": turn.content}
                for turn in chat_system.conversation_manager.turns
            ],
        }
    except Exception as e:
        logging.error(f"Error in chat endpoint: {str(e)}")
        raise HTTPException(status_code=500, detail=str(e))


@app.post("/clear")
def clear_conversation():
    """
    Clear conversation history.
    """
    try:
        chat_system.conversation_manager.turns.clear()
        return {"message": "Conversation history cleared."}
    except Exception as e:
        logging.error(f"Error in clear endpoint: {str(e)}")
        raise HTTPException(status_code=500, detail=str(e))


@app.get("/save")
def save_conversation():
    """
    Save the current conversation to a file.
    """
    try:
        filename = chat_system.save_conversation()
        return {"message": f"Conversation saved to {filename}"}
    except Exception as e:
        logging.error(f"Error in save endpoint: {str(e)}")
        raise HTTPException(status_code=500, detail=str(e))


if __name__ == "__main__":
    import uvicorn

    # Run the FastAPI application
    uvicorn.run(app, host="0.0.0.0", port=8080)