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):
    result = qa_pipeline(question=question, context=context)
    return result['answer']


def process(context_file, question):
    # Read the context from the uploaded file
    with open(context_file.name, 'r') as file:
        context = file.read()

    answer = answer_question(context, question)
    return answer


# Gradio interface
demo = gr.Interface(
    fn=process,
    inputs=[gr.File(label="Upload Context File"), gr.Textbox(label="Question")],
    outputs=[gr.Textbox(label="Answer")],
    title="Question Answering",
    description="Upload a file with context and ask a question. The answer will be displayed."
)

if __name__ == "__main__":
    demo.launch()