app.py

import streamlit as st
from transformers import pipeline


st.title("Text Summarization App |PEGASUS-Large|) ")

# Create a text input widget
text_input = st.text_area(label="Input Text", height=200)

# Define a function to generate the summary
def generate_summary(text):
    summarizer = pipeline("summarization", model="sabre-code/pegasus-large-cnn-dailymail")
    generated_summary = summarizer(text)
    
    
    # Return the generated summary
    return generated_summary

# Add a button to trigger the generation of the summary
generate_button = st.button(label="Generate Summary")
if generate_button:
    # Call the generate_summary function when the button is clicked
    generated_summary = generate_summary(text_input.value)
    st.success("Summary Generated!")
else:
    st.warning("Please enter some text in the input field above.")

# Display the generated summary
st.markdown("# Summary")
st.code(generated_summary)