import streamlit as st
from transformers import pipeline

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

def summarize_text(text):
    summary = summarizer(text, max_length=150, min_length=50, do_sample=False)
    return summary[0]['summary_text']

# Streamlit app layout
st.title("Text Summarizer")
st.write("This app uses Hugging Face's transformers to summarize any text you provide.")

# User input
input_text = st.text_area("Enter Text to Summarize", height=200)

if st.button("Summarize"):
    if input_text:
        with st.spinner("Summarizing..."):
            summary = summarize_text(input_text)
            st.subheader("Summary:")
            st.write(summary)
    else:
        st.warning("Please enter some text to summarize.")