import gradio as gr

from transformers import pipeline

qa = pipeline("question-answering")

def question_answering(question, context):
  return qa(question, context)["answer"]

question = "What is Pragyan?"
context = "Chandrayaan-3 is the third and most recent lunar Indian Space Research exploration mission under the Chandrayaan programme of ISRO. It consists of a lander named Vikram and a rover named Pragyan similar to Chandrayaan-2. Its propulsion module behaves like a communication relay satellite."

title = "Extractive question answering"
description = """
<img src="https://www.zdnet.com/a/img/resize/1a8d2c93f1f51f9f33d21d7224840dfcf06f5a50/2023/02/14/328d5be2-918d-4aee-8690-875aed4a8c8a/gettyimages-1458045238-1.jpg?auto=webp&width=1280" width=200px>
"""
question_box = gr.Textbox(label="Question:", placeholder="What is Pragyan?", lines=2)
context_box = gr.Textbox(label="Context", placeholder=context, lines=10)
demo = gr.Interface(fn=question_answering,
                    inputs=[question_box, context_box],
                    outputs="text",
                    title=title,
                    description=description)

demo.launch()