Update app.py

app.py

@@ -1,79 +1,26 @@
-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')
+import logging
 
-# 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
+logging.basicConfig(level=logging.INFO)
 
-# 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
+qa_pipeline = pipeline(
+    "question-answering",
+    model="nguyenvulebinh/vi-mrc-base",
+    device=0 if torch.cuda.is_available() else -1
+)
 
-# Hàm xử lý cho Gradio và API
-def gradio_answer(question, context):
+def answer_fn(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() 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)
+iface = gr.Interface(
+    fn=answer_fn,
+    inputs=["text", "text"],
+    outputs="text",
+    title="AgriBot: Hỏi đáp nông nghiệp"
+)
 
-# 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,
-        app=app 
-    )
+    iface.launch()