import streamlit as st
import PyPDF2
from extractive_model import summarize_with_textrank
from nltk.tokenize import sent_tokenize


# Set page to wide mode
st.set_page_config(layout="wide")

# Function to handle file upload and return its content
def load_pdf(file):
    pdf_reader = PyPDF2.PdfReader(file)
    pdf_text = ""
    for page_num in range(len(pdf_reader.pages)):
        pdf_text += pdf_reader.pages[page_num].extract_text() or ""
    return pdf_text

# Function to calculate overlap
def calculate_overlap(original_text, summary_text):
    original_sentences = set(sent_tokenize(original_text))
    summary_sentences = set(sent_tokenize(summary_text))
    overlap_count = sum(1 for sentence in summary_sentences if sentence in original_sentences)
    overlap_percentage = (overlap_count / len(original_sentences)) * 100 if original_sentences else 0
    return overlap_percentage

# Main app
def main():
    st.title("Terms of Service Summarizer")

    # Layout: 3 columns
    col1, col2, col3 = st.columns([1, 3, 2], gap="large")

    # Left column: Radio buttons for summarizer choice
    with col1:
        radio_options = ['Abstractive', 'Extractive']
        radio_selection = st.radio("Choose type of summarizer:", radio_options)

    # Middle column: Text input and File uploader
    with col2:
        user_input = st.text_area("Enter your text here:")
        uploaded_file = st.file_uploader("Upload a PDF", type="pdf")
        if st.button("Summarize"):
            if uploaded_file and user_input:
                st.warning("Please provide either text input or a PDF file, not both.")
                return
            
            # Perform overlap calculation
            if 'summary' in st.session_state:
                overlap = calculate_overlap(file_content, st.session_state.summary)
                st.session_state.overlap = overlap

            elif uploaded_file:
                # Extract text from PDF
                file_content = load_pdf(uploaded_file)
                st.write("PDF uploaded successfully.")
            elif user_input:
                file_content = user_input
            else:
                st.warning("Please upload a PDF or enter some text to summarize.")
                return

            # Perform extractive summarization
            if radio_selection == "Extractive":
                summary = summarize_with_textrank(file_content)
                st.session_state.summary = summary

            # Perform extractive summarization
            if radio_selection == "Abstractive":
                None
                #summary = summarize_with_textrank(file_content)
                #st.session_state.summary = summary

    # Right column: Displaying text after pressing 'Summarize'
    with col3:
        st.write("Summary:")
        if 'summary' in st.session_state:
            st.write(st.session_state.summary)

             # Display overlap percentage
            if 'overlap' in st.session_state:
                st.write(f"Overlap with Original Text: {st.session_state.overlap:.2f}%")

if __name__ == "__main__":
    main()