app.py

import streamlit as st
from transformers import pipeline

def main():
    st.title("Text Summarization")

    # Initialize the summarizer pipeline
    summarizer = pipeline(
        task="summarization",
        model="facebook/bart-large-cnn",  # Using a different model for better summarization
        min_length=50,  # Increased minimum length to capture more details
        max_length=150,  # Adjusted max length to allow for more detailed summaries
        truncation=True,
    )

    # User input
    input_text = st.text_area("Enter the text you want to summarize:", height=200)

    # Summarize button
    if st.button("Summarize"):
        if input_text:
            # Generate the summary
            output = summarizer(input_text, max_length=150, min_length=50, do_sample=False)
            summary = output[0]['summary_text']

            # Display the summary as bullet points
            st.subheader("Summary:")
            bullet_points = summary.split(". ")
            for point in bullet_points:
                st.write(f"- {point.strip()}")
        else:
            st.warning("Please enter text to summarize.")

if __name__ == "__main__":
    main()