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import logging
from flask import Flask, request, jsonify
from transformers import pipeline
import gradio as gr
import os
import torch
from huggingface_hub import login
from werkzeug.middleware.dispatcher import DispatcherMiddleware
from werkzeug.serving import run_simple
# 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 Flask app cho API
app = Flask(__name__)
@app.route("/api/answer", methods=["POST"])
def answer():
try:
data = 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 jsonify({"error": "Missing question or context"}), 400
result = qa_pipeline(question=question, context=context)
logging.info(f"Response - Answer: {result['answer']}")
return jsonify({"answer": result["answer"]})
except Exception as e:
logging.error(f"API error: {e}")
return jsonify({"error": str(e)}), 500
# Tạo Gradio Blocks
with gr.Blocks() 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.")
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)
# Tích hợp Flask và Gradio trên cùng port
application = DispatcherMiddleware(demo.app, {"/api": app})
if __name__ == "__main__":
logging.info("Starting Gradio and Flask on port 7860...")
run_simple("0.0.0.0", 7860, application) |