app.py

from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
import gradio as grad
import ast

mdl_name = "deepset/roberta-base-squad2"
my_pipeline = pipeline('question-answering', model=mdl_name, tokenizer=mdl_name)

def answer_question(question,context):
    text = "{'question': '" + question + "', 'context': '" + context + "'}"
    di=ast.literal_eval(text)
    response = my_pipeline(di)
    return response

grad.Interface(answer_question, inputs=["text","text"], outputs="text").launch()
Listing 5-1Code for app.py