app.py

import gradio as gr
from transformers import pipeline

# ✅ Correct pipeline
qa_pipeline = pipeline(
    "question-answering",
    model="deepset/bert-base-cased-squad2"
)

def answer_question(context, question):
    try:
        result = qa_pipeline(
            question=question,
            context=context
        )

        answer = result["answer"]
        score = result["score"]

        return f"Answer: {answer}\nConfidence: {round(score, 4)}"

    except Exception as e:
        return str(e)

with gr.Blocks() as demo:
    gr.Markdown("# 🤖 BERT Extractive Question Answering")

    context_input = gr.Textbox(lines=8, label="Context")
    question_input = gr.Textbox(label="Question")
    output = gr.Textbox(label="Answer")

    btn = gr.Button("Get Answer")
    btn.click(answer_question, inputs=[context_input, question_input], outputs=output)

demo.launch()