app.py

import gradio as gr
from transformers import pipeline

# Load the summarization pipeline
summarizer = pipeline("summarization", model="facebook/bart-large-cnn")

def summarize_text(text):
    if not text.strip():
        return "Please enter some text to summarize."
    
    summary = summarizer(text, min_length=10, max_length=100, do_sample=False)
    return summary[0]['summary_text']

# Define the Gradio interface
with gr.Blocks() as demo:
    gr.Markdown("# Text Summarization using BART Model")
    gr.Markdown("Enter a long piece of text below and click 'Summarize' to generate a concise summary.")
    
    text_input = gr.Textbox(label="Input Text", placeholder="Enter your text here...", lines=10)
    summarize_button = gr.Button("Summarize")
    output_text = gr.Textbox(label="Summarized Text", lines=5, interactive=False)
    
    summarize_button.click(summarize_text, inputs=text_input, outputs=output_text)
    
# Launch the Gradio app
demo.launch()