app.py

import gradio as gr
from transformers import pipeline

# Initialize the question-answering pipeline
qa_pipeline = pipeline("question-answering")

def answer_question(context, question):
    """
    Function to run the QA pipeline and get the answer.
    
    :param context: The context in which the question is asked.
    :param question: The question that needs to be answered.
    :return: Answer from the QA model.
    """
    result = qa_pipeline({'context': context, 'question': question})
    return result['answer']

# Create the Gradio interface
interface = gr.Interface(
    fn=answer_question,
    inputs=[
        gr.Textbox(label="Context", placeholder="Enter context here...", lines=4),  # Left-side input
        gr.Textbox(label="Question", placeholder="Ask a question here...", lines=1)  # Right-side input
    ],
    outputs="text",  # Output as text
    live=True,  # Optional: Display results as the user types
    layout="horizontal"  # Align inputs side by side
)

# Launch the interface
if __name__ == "__main__":
    interface.launch()