app.py

import streamlit as st
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM

# Load the tokenizer and model
tokenizer = AutoTokenizer.from_pretrained("suriya7/bart-finetuned-text-summarization")
model = AutoModelForSeq2SeqLM.from_pretrained("suriya7/bart-finetuned-text-summarization")

def generate_summary(text, prompt):
    # Combine text and prompt into one input
    combined_input = f"{prompt}: {text}"
    inputs = tokenizer([combined_input], max_length=1024, return_tensors='pt', truncation=True)
    summary_ids = model.generate(inputs['input_ids'], max_new_tokens=100, do_sample=False)
    summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
    
    return summary

# Initialize session state for input history if it doesn't exist
if 'input_history' not in st.session_state:
    st.session_state['input_history'] = []

# Streamlit interface
st.title("Text Summarization App")

# User text inputs
bulk_text = st.text_area("Enter the bulk text you want to summarize", height=200)
prompt = st.text_input("Enter the prompt for the summary", "What are the key points?")

if st.button("Generate Summary"):
    if bulk_text and prompt:
        with st.spinner("Generating summary..."):
            summary = generate_summary(bulk_text, prompt)
            
        # Save the input and summary to the session state history
        st.session_state['input_history'].append({"text": bulk_text, "prompt": prompt, "summary": summary})
        
        st.subheader("Generated Summary:")
        st.write(summary)
    else:
        st.warning("Please enter both the bulk text and the prompt.")

# Display the history of inputs and summaries
if st.session_state['input_history']:
    st.subheader("History")
    for i, entry in enumerate(st.session_state['input_history']):
        st.write(f"**Input {i+1} (Text):** {entry['text']}")
        st.write(f"**Prompt {i+1}:** {entry['prompt']}")
        st.write(f"**Summary {i+1}:** {entry['summary']}")
        st.write("---")

# Instructions for using the app
st.write("Enter your bulk text and a prompt for summarization, then click 'Generate Summary' to get a summarized version based on your prompt.")