import warnings
warnings.filterwarnings("ignore")
import streamlit as st
from PyPDF2 import PdfReader
from concurrent.futures import ThreadPoolExecutor
from base64 import b64encode
from fpdf import FPDF
import io, string, re, math
from io import StringIO
from pathlib import Path
from streamlit_pdf_viewer import pdf_viewer

_here = Path(__file__).parent

# Importing the Fastify Class
from fast_reader import Fastify_Reader

def pdf_extract_text(pdf_docs):
    '''
    Basic function for extracting text from the PDFs
    '''
    text = ""
    for pdf in pdf_docs:
        pdf_reader = PdfReader(pdf)
        for page in pdf_reader.pages:
            text += page.extract_text()
    return text

def text_to_pdf_fastify(txt):    
    '''
    Basic function to apply fastification on the input text and convert it to bytes for PDF rendering
    '''
    text = (txt + '.')[:-1]
    # Applying the Fastify Logic
    bold_text = Fastify_Reader(text).fastify()
    bold_text = bold_text.encode('latin-1', 'ignore').decode('latin-1') #since fpdf works with latin-1 encoding
    
    # Creating the PDF
    pdf = FPDF()
    pdf.add_page()
    pdf.set_font("Arial", size = 12)
    pdf.multi_cell(0, 10, txt = bold_text, markdown=True)
    return bytes(pdf.output())

def text_to_pdf(txt):
    '''
    Basic function on the input text and convert it to bytes for PDF rendering
    '''
    text = (txt + '.')[:-1]
    text = text.encode('latin-1', 'ignore').decode('latin-1') #since fpdf works with latin-1 encoding
    # Creating the PDF
    pdf = FPDF()
    pdf.add_page()
    pdf.set_font("Arial", size = 12)
    pdf.multi_cell(0, 10, txt = text, markdown=True)
    return bytes(pdf.output())

#Setting the page config
st.set_page_config(page_title="Fastify Reader",
                   page_icon=":books:",
                   layout="wide")

# Sidebar
with st.sidebar:
    st.image("Logo.jpg")
    st.markdown("<div style='text-align: center;'>How fast can you read?</div>", unsafe_allow_html=True)

# Example inputs
example_text = '''
Did you know that your brain is capable of reading this text faster than you might think? It's true! Our brains have an incredible capacity for processing information rapidly, and with the right techniques, you can harness this power to become a speed reading master.

Speed reading isn't just about skimming through text; it's about training your brain to absorb and comprehend information at a much quicker pace. By utilizing strategies like chunking, minimizing subvocalization, and expanding your peripheral vision, you can significantly increase your reading speed without sacrificing understanding.

Imagine being able to plow through emails, reports, and articles in half the time it takes you now. With speed reading, that dream can become a reality. Not only will you save time, but you'll also improve your productivity and unlock new opportunities for learning and growth.

So why wait? Dive into the world of speed reading today and unlock your brain's full potential. With practice and dedication, you'll be amazed at how quickly you can conquer even the most daunting reading tasks. Get started now and watch your reading speed soar!
'''


# Main Page
tab1, tab2= st.tabs(["Input Text", "PDF file"])

# First tab where Text is input
with tab1:
    user_input = st.text_input("Enter some text", example_text)

    # Compare Check Box
    compare = st.checkbox('Compare with Fastified Text', value=False, key='compare')
    
    # Submit Button
    if st.button("Submit", key="input-text"):
        #Progess Bar for the processing
        with st.spinner("Processing"):
            text = user_input

            # Compare Logic implementation
            if compare:
                col1, col2, col3 = st.columns(3)
                with col3:
                    st.download_button(label="Download Fastified PDF", data=text_to_pdf_fastify(text), file_name='output.pdf', mime='application/pdf')
                
                # Side by Side comparison
                col1, col2 = st.columns([1, 1], gap="small")

                with col1:
                    with st.container(border = True):
                        st.markdown("<div style='text-align: center;'><strong>Original Text</strong></div>", unsafe_allow_html=True)
                        pdf_viewer(input = text_to_pdf(text), width = 600)
                with col2:
                    with st.container(border = True):
                        st.markdown("<div style='text-align: center;'><strong>Fastified Text</strong></div>", unsafe_allow_html=True)
                        pdf_viewer(text_to_pdf_fastify(text), width = 600)
                
            else:
                # # No Comparisons
                col1, col2, col3 = st.columns(3)
                with col1:
                    st.download_button(label="Download Fastified PDF", data=text_to_pdf_fastify(text), file_name='output.pdf', mime='application/pdf')
                
                with st.container():
                    st.markdown("<div><strong>Fastified PDF viewer</strong></div>", unsafe_allow_html=True)
                    pdf_viewer(text_to_pdf_fastify(text), width = 600)
                
    
# Added support for PDFs having text
with tab2:
        uploaded_file = st.file_uploader("Upload a PDF file", type="pdf", accept_multiple_files=True)

        # Compare Check Box
        compare = st.checkbox('Compare with Fastified Text', value=False, key='compare_pdf')

        # Submit Button
        if st.button("Submit", key="pdf"):
            #Progess Bar for the processing
            with st.spinner("Processing"):
                text = pdf_extract_text(uploaded_file)

                # Compare Logic implementation
                if compare:
                    col1, col2, col3 = st.columns(3)
                    with col3:
                        st.download_button(label="Download Fastified PDF", data=text_to_pdf_fastify(text), file_name='output.pdf', mime='application/pdf')
                    
                    # Side by Side comparison
                    col1, col2 = st.columns([1, 1], gap="small")
                    
                    with col1:
                        with st.container(border = True):
                            st.markdown("<div style='text-align: center;'><strong>Original Text</strong></div>", unsafe_allow_html=True)
                            pdf_viewer(text_to_pdf(text), width = 600)
                    with col2:
                        with st.container(border = True):
                            st.markdown("<div style='text-align: center;'><strong>Fastified Text</strong></div>", unsafe_allow_html=True)
                            pdf_viewer(text_to_pdf_fastify(text), width = 600)

                else:
                    # No Comparison
                    col1, col2, col3 = st.columns(3)
                    with col1:
                        st.download_button(label="Download Fastified PDF", data=text_to_pdf_fastify(text), file_name='output.pdf', mime='application/pdf')
                    
                    with st.container():
                        st.markdown("<div><strong>Fastified PDF viewer</strong></div>", unsafe_allow_html=True)
                        pdf_viewer(text_to_pdf_fastify(text), width = 500)