app.py

import gradio as gr
from transformers import pipeline

# Load the Question Answering pipeline
qa_model = pipeline("question-answering", model="distilbert-base-uncased-distilled-squad")

def answer_question(context, question):
    result = qa_model(question=question, context=context)
    answer = result['answer']
    score = result['score']
    return answer, f"{score:.2f}"

# Define the Gradio interface
with gr.Interface(
        fn=answer_question,
        inputs=[gr.inputs.Textbox(lines=10, placeholder="Enter the context here..."), gr.inputs.Textbox(lines=2, placeholder="Enter your question here...")],
        outputs=[gr.outputs.Textbox(label="Answer"), gr.outputs.Textbox(label="Confidence Score")],
        title="Question Answering System",
        description="Upload a document and ask questions to get answers based on the context."
) as qa_app:
    qa_app.launch()