app.py

from transformers import pipeline
import gradio as gr

# Use the pipeline with optimized settings (no sampling, smaller batch)
summarizer = pipeline(
    "summarization",
    model="sshleifer/distilbart-cnn-6-6",
     # force CPU (if not using GPU)
)

# Function with higher max length and lower min length for longer summaries
def summarize_article(text):
    summary = summarizer(
        text,
        max_length=250,  # ✨ allow longer output
        min_length=100,  # 🚨 ensure decent length
        do_sample=False,  # ⚡ makes it deterministic and faster
    )
    return summary[0]['summary_text']

# Sample input
default_article = """New York (CNN)When Liana Barrientos was 23 years old, she got married..."""  # [TRIMMED for brevity]

# Generate summary once to display as default
default_summary = summarize_article(default_article)

# Gradio interface (read-only)
iface = gr.Interface(
    fn=summarize_article,
    inputs=gr.Textbox(lines=20, label="Article (Read Only)", value=default_article, interactive=False),
    outputs=gr.Textbox(label="Summary (Read Only)", value=default_summary, interactive=False),
    title="⚡ Fast Article Summarizer (CPU Optimized)",
    description="Fast summarization with longer output using CPU only. Inputs and outputs are read-only."
)

iface.launch()