app.py

import torch 
import gradio as gr

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("question-answering", model="deepset/roberta-base-squad2")


def read_file_content(file_obj):
    try:
        with open(file_obj.name, "r", encoding="utf-8") as f:
            content = f.read()
        return content
    except Exception as e:
        return f"An error occurred: {e}"


def get_answer(file, question):
    context= read_file_content(file)
    answer = pipe(question=question, context = context)
    return (answer['answer'])

demo = gr.Interface(fn=get_answer,
                    inputs= [gr.File(label="Upload the file for context"), gr.Textbox(label='Ask the question')],
                    outputs=[gr.Textbox(label='Here is the answer to your question')],
                    title='Get the Answers to your question',
                    description='This application gives the answers to your questions'
                    
        
)
demo.launch(share=True)