app.py

import gradio as gr
from transformers import pipeline
import torch
# Load the summarization model
summarizer = pipeline("summarization", model="facebook/bart-large-cnn")

def summarize_text(input_text, min_length, max_length):
    # Summarize the input text
    summary = summarizer(input_text, min_length=min_length, max_length=max_length, do_sample=False)
    return summary[0]['summary_text']

# Create the Gradio interface
interface = gr.Interface(
    fn=summarize_text,
    inputs=[
        gr.Textbox(label="Enter Text", placeholder="Type or paste your long text here...", lines=10),
        gr.Slider(label="Minimum Length", minimum=10, maximum=50, step=1, value=10),
        gr.Slider(label="Maximum Length", minimum=50, maximum=150, step=1, value=100),
    ],
    outputs=gr.Textbox(label="Summary"),
    title="Text Summarization App",
    description="Enter a long piece of text, set the summary length, and click the button to get a summarized version."
)

# Launch the app
if __name__ == "__main__":
    interface.launch()