app.py

import gradio as gr
from transformers import pipeline

nlp_qa = pipeline(
    'question-answering',
    model='mrm8488/bert-italian-finedtuned-squadv1-it-alfa',
    tokenizer='mrm8488/bert-italian-finedtuned-squadv1-it-alfa'
)

def start(question, context):
    response = nlp_qa({
        'question': question,
        'context': context
    })
    text_hilight_output = [
        (context[:response['start']], None),
        (context[response['start']:response['end']], 'Answer'),
        (context[response['end']:], None)

    ]
    return  text_hilight_output, response['answer'], {response['answer']: response['score']}

face = gr.Interface(
    fn=start, 
    inputs=[
        gr.inputs.Textbox(lines=1, placeholder="Question Here… "), 
        gr.inputs.Textbox(lines=10, placeholder="Context Here… ")
    ], 
    outputs=[
        gr.outputs.HighlightedText(label='Context'),
        gr.outputs.Textbox(label="Answer"), 
        gr.outputs.Label(num_top_classes=1, label='Score'), 
    ]
)
face.launch()