app.py

import torch
import gradio as gr

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

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

text_summarize = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6")


def summary(input_text):
    output_text = text_summarize(input_text)
    return output_text[0]['summary_text']


gr.close_all()

# demo = gr.Interface(fn=summary, inputs="text", outputs="text")
demo = gr.Interface(fn=summary,
                    inputs=[gr.Textbox(label="Input text to summarize", lines=10)],
                    outputs=[gr.Textbox(label="Summarized text", lines=5)])

demo.launch()