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import logging
import gradio as gr
from transformers import pipeline
import os
import torch
from huggingface_hub import login
from fastapi import FastAPI, Request
from fastapi.responses import JSONResponse
# 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
# Hàm xử lý cho Gradio và API
def gradio_answer(question, context):
result = qa_pipeline(question=question, context=context)
return result["answer"]
# Tạo FastAPI app để thêm endpoint API
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")
logging.info(f"Received request - Question: {question}, Context: {context[:200]}...")
if not question or not context:
logging.error("Missing question or context")
return JSONResponse({"error": "Missing question or context"}, 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)
# Tạo Gradio Blocks
with gr.Blocks(app=app) as demo:
gr.Markdown("# AgriBot: Hỏi đáp nông nghiệp")
gr.Markdown("Nhập câu hỏi và ngữ cảnh để nhận câu trả lời về nông nghiệp.")
with gr.Row():
question_input = gr.Textbox(label="Câu hỏi", placeholder="Nhập câu hỏi của bạn...")
context_input = gr.Textbox(label="Ngữ cảnh", placeholder="Nhập ngữ cảnh liên quan...")
output = gr.Textbox(label="Câu trả lời")
submit_btn = gr.Button("Gửi")
submit_btn.click(fn=gradio_answer, inputs=[question_input, context_input], outputs=output)
# Chạy ứng dụng
if __name__ == "__main__":
logging.info("Starting Gradio on port 7860...")
demo.launch(server_name="0.0.0.0", server_port=7860, inline=False) |