text-summarizer

import streamlit as st
from transformers import pipeline

# Title
st.title("📝 Text Summarizer")
st.write("Paste your text below and get a short summary!")

# Text input
user_input = st.text_area("Enter text here:", height=200)

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

summarizer = load_model()

# Summarize button
if st.button("Summarize"):
    if user_input.strip() == "":
        st.warning("Please enter some text first!")
    else:
        summary = summarizer(user_input, max_length=100, min_length=25, do_sample=False)
        st.success(summary[0]['summary_text'])