app.py

import streamlit as st
from transformers import pipeline

# Load summarization pipeline
summarizer = pipeline(task="summarization", model="facebook/bart-large-cnn")


def summarize_text(text: str, min_len: int, max_len:int) -> str:
    summary = summarizer(text,
                     min_length=min_len,
                     max_length=max_len)
    return summary[0]['summary_text']


# Streamlit app
st.title("Text Summarizer")

# Input text
text_input = st.text_area("Enter the text you want to summarize:")

# Slider for minimum summary length
min_length = st.slider("Minimum summary length:", 10, 100, 30)

# Slider for maximum summary length
max_length = st.slider("Maximum summary length:", 50, 200, 100)

# Button to summarize text
summarize_btn = st.button("Summarize") 
if summarize_btn and text_input:
    summary = summarize_text(text_input, min_length, max_length)
    st.subheader("Summary:")
    st.write(summary)
    
if summarize_btn and not text_input:
    st.write("Please enter text to summarize.")