Update app.py

app.py

@@ -1,26 +1,78 @@
+import logging
 import gradio as gr
 from transformers import pipeline
+import os
 import torch
-import logging
+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')
 
-logging.basicConfig(level=logging.INFO)
+# 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
 
-qa_pipeline = pipeline(
-    "question-answering",
-    model="nguyenvulebinh/vi-mrc-base",
-    device=0 if torch.cuda.is_available() else -1
-)
+# 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
 
-def answer_fn(question, context):
+# Hàm xử lý cho Gradio và API
+def gradio_answer(question, context):
     result = qa_pipeline(question=question, context=context)
     return result["answer"]
 
-iface = gr.Interface(
-    fn=answer_fn,
-    inputs=["text", "text"],
-    outputs="text",
-    title="AgriBot: Hỏi đáp nông nghiệp"
-)
+# 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)
 
+# Chạy ứng dụng
 if __name__ == "__main__":
-    iface.launch()
+    logging.info("Starting Gradio on port 7860...")
+    demo.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        inline=False,
+    )