app.py

import gradio as gr
from transformers import pipeline

# Load a pre-trained QA model
qa_pipeline = pipeline("question-answering", model="deepset/roberta-base-squad2")

# Define a function to get answers
def answer_question(context, question):
    result = qa_pipeline(question=question, context=context)
    return result['answer']

# Create Gradio Interface
interface = gr.Interface(
    fn=answer_question, 
    inputs=["text", "text"], 
    outputs="text",
    title="Question Answering Model",
    description="Ask a question based on the given context."
)

# Launch the app
interface.launch()