app.py

import gradio as gr
from transformers import pipeline
import torch

# Initialize the summarization pipeline with model caching
summarizer = pipeline(
    "summarization",
    model="facebook/bart-large-cnn",
    device=-1  # Use CPU for free-tier compatibility
)

def summarize_text(text, max_length=130, min_length=30):
    """
    Summarize the input text using BART model.
    
    Args:
        text (str): Input text to summarize
        max_length (int): Maximum length of the summary
        min_length (int): Minimum length of the summary
    
    Returns:
        str: Generated summary
    """
    try:
        # Input validation
        if not text or len(text.strip()) < 50:
            return "Please provide a longer text (at least 50 characters) for summarization."
        
        # Generate summary
        summary = summarizer(
            text,
            max_length=max_length,
            min_length=min_length,
            do_sample=False
        )
        
        return summary[0]['summary_text']
    except Exception as e:
        return f"Error during summarization: {str(e)}"

# Create Gradio interface
iface = gr.Interface(
    fn=summarize_text,
    inputs=[
        gr.Textbox(
            lines=10,
            placeholder="Enter text to summarize (minimum 50 characters)",
            label="Input Text"
        ),
        gr.Slider(
            minimum=30,
            maximum=250,
            value=130,
            step=10,
            label="Maximum Summary Length"
        ),
        gr.Slider(
            minimum=20,
            maximum=100,
            value=30,
            step=5,
            label="Minimum Summary Length"
        )
    ],
    outputs=gr.Textbox(label="Summary"),
    title="Text Summarizer (BART-large-CNN)",
    description="""
    This Space uses the BART-large-CNN model to generate concise summaries of your text.
    The model works best with news articles and formal content.
    For optimal results:
    - Provide clear, well-structured text
    - Aim for at least 100 words of input
    - Adjust the length parameters based on your needs
    """,
    examples=[
        [
            """The city council met on Tuesday to discuss the new recycling initiative. 
            The proposed program would require all residents to separate their waste into 
            three categories: organic, recyclable, and general waste. The council members 
            debated the costs and benefits of implementing such a system, with some arguing 
            that it would significantly reduce landfill usage while others expressed concerns 
            about the financial burden on residents. After three hours of discussion, 
            the council voted 7-3 in favor of implementing the program, which will begin 
            next spring.""",
            130,
            30
        ]
    ],
    allow_flagging="never"
)

# Launch with specific configurations for Spaces
iface.queue()  # Enable queuing
iface.launch(
    server_name="0.0.0.0",
    server_port=7860,
    share=False
)