app.py

import gradio as gr
from transformers import pipeline

# Load your uploaded model from the hub
summarizer = pipeline("summarization", model="Aarush09/bart-conversation-summarizer")

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

# Gradio Interface
with gr.Blocks() as demo:
    gr.Markdown("## 📝 Text Summarizer\nEnter text below and get a summary using your Hugging Face model.")
    
    with gr.Row():
        input_text = gr.Textbox(label="Input Text", lines=10, placeholder="Paste text here...")
    
    with gr.Row():
        min_len = gr.Slider(10, 100, value=30, step=5, label="Min Summary Length")
        max_len = gr.Slider(50, 300, value=120, step=10, label="Max Summary Length")
    
    output_text = gr.Textbox(label="Summary", lines=8)

    summarize_btn = gr.Button("Summarize")
    summarize_btn.click(summarize_text, inputs=[input_text, max_len, min_len], outputs=output_text)

demo.launch()