import streamlit as st
from transformers import pipeline

# Load summarization pipeline
@st.cache_resource
def load_summarizer():
    return pipeline("summarization", model="facebook/bart-large-cnn")

summarizer = load_summarizer()

# Streamlit UI
st.set_page_config(page_title="Text Summarizer", page_icon="📝", layout="centered")
st.title("📝 Text Summarizer")

# Input text
text = st.text_area("Enter the text you want to summarize:", height=250)

# Summary button
if st.button("Summarize"):
    if text.strip():
        with st.spinner("Generating summary..."):
            summary = summarizer(text, max_length=150, min_length=40, do_sample=False)
            st.subheader("Summary")
            st.success(summary[0]['summary_text'])
    else:
        st.warning("Please enter some text to summarize.")

import os
port = int(os.environ.get("PORT", 7860))
app.launch(server_name="0.0.0.0", server_port=port)