app.py

import streamlit as st
from transformers import pipeline
from concurrent.futures import ThreadPoolExecutor
import time

# Function to load a single model
def load_model(model_name):
    if model_name == 'BART':
        return pipeline("summarization", model="facebook/bart-large-cnn")
    elif model_name == 'T5':
        return pipeline("summarization", model="t5-large")
    elif model_name == 'Pegasus':
        return pipeline("summarization", model="google/pegasus-cnn_dailymail")

# Function to load all models concurrently
@st.cache_resource
def load_all_models():
    model_names = ['BART', 'T5', 'Pegasus']
    models = {}
    with ThreadPoolExecutor() as executor:
        futures = {executor.submit(load_model, name): name for name in model_names}
        for future in futures:
            model_name = futures[future]
            models[model_name] = future.result()
    return models

# Streamlit app layout
st.title("Text Summarization with Pre-trained Models (BART, T5, Pegasus)")

text_input = st.text_area("Enter text to summarize:")

if text_input:
    # Display word count of input text
    word_count = len(text_input.split())
    st.write(f"**Word Count:** {word_count}")

    if st.button("Generate Summaries"):
        with st.spinner("Loading models and generating summaries..."):
            start_time = time.time()
            models = load_all_models()
            summaries = {}
            for model_name, model in models.items():
                summary = model(text_input, max_length=150, min_length=50, length_penalty=2.0, num_beams=4, early_stopping=True)[0]['summary_text']
                summaries[model_name] = summary
            end_time = time.time()

        st.subheader("Summaries")
        for model_name, summary in summaries.items():
            summary_word_count = len(summary.split())
            st.write(f"**{model_name}**")
            st.write(summary.replace('<n>', ''))
            st.write(f"**Summary Word Count:** {summary_word_count}")
            st.write("---")
        st.write(f"**Total Time Taken:** {end_time - start_time:.2f} seconds")
else:
    st.error("Please enter text to summarize.")