app.py

import gradio as gr
from transformers import pipeline

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

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

# Create a Gradio interface with custom labels
interface = gr.Interface(fn=generate_summary, 
                         inputs=gr.Textbox(lines=10, 
                                                  placeholder="Enter Text Here...", 
                                                  label="Input Text for Summarization"), 
                         outputs=gr.Textbox(label="Summarized Text"),
                         title="Text Summarization",
                         description="Enter a block of text to generate a concise summary using a Transformers model")

# Launch the interface
interface.launch()