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):
    inputs = tokenizer([text], 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)
    
    # Post-process the summary to include only specific points
    important_points = extract_important_points(summary)
    
    return important_points

def extract_important_points(summary):
    # Filter the summary for sentences containing keywords related to change requests or important points
    keywords = ["change", "request", "important", "needs", "must", "critical", "required", "suggested"]
    filtered_lines = [line for line in summary.split('. ') if any(keyword in line.lower() for keyword in keywords)]
    return '. '.join(filtered_lines)

# 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 input
user_input = st.text_area("Enter the text you want to summarize", height=200)

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

# 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}:** {entry['input']}")
        st.write(f"**Summary {i+1}:** {entry['summary']}")
        st.write("---")

# Instructions for using the app
st.write("Enter your text in the box above and click 'Generate Summary' to get a summarized version of your text.")