app.py

import gradio as gr
from transformers import pipeline

# Load summarizer pipeline (T5 model, lightweight)
summarizer = pipeline("summarization", model="t5-small")

def summarize_text(text):
    summary = summarizer(text, max_length=150, min_length=30, do_sample=False)
    return summary[0]['summary_text']

# Gradio interface
iface = gr.Interface(
    fn=summarize_text,
    inputs=gr.Textbox(lines=8, placeholder="Paste any article or text here..."),
    outputs=gr.Textbox(lines=8),  # show full text without scrolling
    title="AI Text Summarizer 📖✨",
    description="Paste long text and get concise, clear summaries instantly!"
)

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