import gradio as gr
from transformers import pipeline

model_name = "sshleifer/distilbart-cnn-12-6"

def summarize_text(text, max_length, min_length):
    summarizer = pipeline('summarization', model=model_name, use_auth_token=None)
    result = summarizer(text, max_length=int(max_length), min_length=int(min_length), do_sample=False)
    return result[0]['summary_text']

with gr.Blocks() as demo:
    gr.Markdown("# Text Summarizer")
    gr.Markdown("Powered by sshleifer/distilbart-cnn-12-6")
    text_input = gr.Textbox(label="Text to Summarize", placeholder="Enter long text...", lines=5)
    max_len = gr.Slider(minimum=10, maximum=200, value=100, label="Max Summary Length")
    min_len = gr.Slider(minimum=5, maximum=50, value=10, label="Min Summary Length")
    output = gr.Textbox(label="Summary", lines=3)
    btn = gr.Button("Summarize")
    btn.click(fn=summarize_text, inputs=[text_input, max_len, min_len], outputs=output)

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