app.py

import gradio as gr
from transformers import pipeline

# Load the summarization pipeline
summarizer = pipeline("summarization", model="sshleifer/distilbart-cnn-12-6")

def summarize_text(text):
    summary = summarizer(text, max_length=130, min_length=30, do_sample=False)
    return summary[0]['summary_text']

# Create Gradio Interface
demo = gr.Interface(fn=summarize_text,
                    inputs=gr.Textbox(lines=10, placeholder="Enter article text here..."),
                    outputs="text",
                    title="Text Summarization",
                    description="Enter any long text and get a concise summary using DistilBART.")

if __name__ == "__main__":
    demo.launch()