import logging
from transformers import pipeline
import os
from huggingface_hub import login
from fastapi import FastAPI, Request
from fastapi.responses import JSONResponse
import uvicorn
import torch

# Cấu hình logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')

# Đăng nhập Hugging Face
try:
    login(token=os.getenv("HF_TOKEN"))
    logging.info("Logged in to Hugging Face Hub successfully")
except Exception as e:
    logging.error(f"Failed to login to Hugging Face Hub: {e}")
    raise

# Load mô hình
logging.info("Loading nguyenvulebinh/vi-mrc-base...")
try:
    qa_pipeline = pipeline(
        "question-answering",
        model="nguyenvulebinh/vi-mrc-base",
        device=0 if torch.cuda.is_available() else -1
    )
    logging.info("Model loaded successfully")
except Exception as e:
    logging.error(f"Failed to load model: {e}")
    raise

# Tạo FastAPI app
app = FastAPI()

@app.post("/api/answer")
async def api_answer(request: Request):
    try:
        data = await request.json()
        question = data.get("question")
        context = data.get("context", "Cây lúa là một loại cây trồng phổ biến ở Việt Nam, cần điều kiện đất và nước phù hợp.")
        logging.info(f"Received request - Question: {question}, Context: {context[:200]}...")
        if not question:
            logging.error("Missing question")
            return JSONResponse({"error": "Missing question"}, status_code=400)
        result = qa_pipeline(question=question, context=context)
        logging.info(f"Response - Answer: {result['answer']}")
        return JSONResponse({"answer": result["answer"]})
    except Exception as e:
        logging.error(f"API error: {e}")
        return JSONResponse({"error": str(e)}, status_code=500)

if __name__ == "__main__":
    logging.info("Starting FastAPI...")
    uvicorn.run(app, host="0.0.0.0")  # Bỏ tham số port để Spaces tự xử lý