# 📝 Text Summarization Demo | CPU-only HF Space

from transformers import pipeline
import gradio as gr

# Load a distilled BART summarization model on CPU
summarizer = pipeline(
    "summarization",
    model="sshleifer/distilbart-cnn-12-6",
    device=-1    # force CPU
)

def summarize(text: str, max_length: int, min_length: int):
    if not text.strip():
        return ""
    # run the summarization pipeline
    summary = summarizer(
        text,
        max_length=max_length,
        min_length=min_length,
        do_sample=False
    )[0]["summary_text"]
    return summary

with gr.Blocks(title="📝 Text Summarization") as demo:
    gr.Markdown(
        "# 📝 Text Summarizer\n"
        "Paste in any article, report, or long-form text and get a concise summary—**100% CPU**."
    )

    with gr.Row():
        text_in    = gr.Textbox(lines=10, placeholder="Enter your text here…", label="Input Text")
        max_slider = gr.Slider(20, 200, value=100, step=10, label="Max Summary Length")
        min_slider = gr.Slider(10, 100, value=30, step=5, label="Min Summary Length")

    run_btn    = gr.Button("Summarize 🔍", variant="primary")
    summary_out = gr.Textbox(lines=5, label="Summary", interactive=False)

    run_btn.click(
        summarize,
        inputs=[text_in, max_slider, min_slider],
        outputs=summary_out
    )

if __name__ == "__main__":
    demo.launch(server_name="0.0.0.0")