import streamlit as st
import pandas as pd
import numpy as np
import os
import pickle
import torch
import markdown
from weasyprint import HTML, CSS
import io
from io import BytesIO
from grobidmonkey import reader
from transformers import pipeline
from transformers import BartTokenizer, BartModel, BartForConditionalGeneration
from transformers import T5Tokenizer, T5ForConditionalGeneration
from document import Document
from BartSE import BARTAutoEncoder
st.title('Paper2Slides')
st.markdown("""
This space is a live demo of the [Zehao Lu](https://www.linkedin.com/in/zehao-lu/)’s thesis at Utrecht University (and internship project at ML6),
supervised by [Guanyi Chen](https://a-quei.github.io/) (During his time in Utrecht University) and
[Konstantin Buschmer](https://www.linkedin.com/in/konstantin-buschmeier/?locale=de_DE) (ML6).
To use this space:
1. Have a paper that you want to turn into slides.
2. Process your paper using GROBID. If you have GROBID installed, run it and use the output. If not, you can use GROBID’s live demo to generate the
processed TEI.xml file. To use the live demo, click on `TEI`, select `Process Fulltext Document` under Service to call, choose the paper file, and then
click `submit`.
""")
st.subheader('Set slide numbers')
range_values = st.slider(
'Select a range',
min_value=0,
max_value=100,
value=(0, 25)
)
def save_uploaded_file(uploaded_file):
file_path = os.path.join("./uploads", uploaded_file.name)
os.makedirs("./uploads", exist_ok=True) # Create 'uploads' directory if it doesn't exist
with open(file_path, "wb") as f:
f.write(uploaded_file.getbuffer())
return file_path # Return the file path as a string
st.subheader('Upload paper in TEI.xml format')
col1, col2 = st.columns([3, 1])
with col1:
uploaded_file = st.file_uploader("Choose a file")
with col2:
option = st.selectbox(
'Select parsing method.',
('monkey', 'x2d', 'lxml'))
summ_text = None
if (uploaded_file is not None) and (not 'generation_done' in st.session_state):
st.write(uploaded_file.name)
bytes_data = uploaded_file.getvalue()
st.write(len(bytes_data), "bytes")
saved_file_path = save_uploaded_file(uploaded_file)
monkeyReader = reader.MonkeyReader(option)
# read paper content
essay = monkeyReader.readEssay(saved_file_path)
with st.status("Understanding paper..."):
Barttokenizer = BartTokenizer.from_pretrained('facebook/bart-large-cnn')
summ_model_path = 'com3dian/Bart-large-paper2slides-summarizer'
summarizor = BartForConditionalGeneration.from_pretrained(summ_model_path)
exp_model_path = 'com3dian/Bart-large-paper2slides-expander'
expandor = BartForConditionalGeneration.from_pretrained(exp_model_path)
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
BartSE = BARTAutoEncoder(summarizor, summarizor, device)
del summarizor, expandor
document = Document(essay, Barttokenizer)
del Barttokenizer
length = document.merge(range_values[0],range_values[1], BartSE, device)
with st.status("Generating slides..."):
summarizor = pipeline("summarization", model=summ_model_path, device = device)
title_list = document.segmentation['key']
summ_text = summarizor(document.segmentation['text'], max_length=100, min_length=10, do_sample=False)
summ_text = [text['summary_text'] for text in summ_text]
st.session_state.generation_done = True
if (summ_text is not None) or ('summ_text' in st.session_state):
# Function to render HTML content
def format(title_list, text_list):
format_list = []
for index, text in enumerate(text_list):
title = "## " + title_list[index] + "\n"
# Split text by periods
sentences = text.split('.')
# Create HTML list items
list_items = "".join([f"- {sentence.strip()}.\n" for sentence in sentences if sentence.strip()])
format_list.append(title + list_items)
return format_list
# Initialize session state for page index and text
if 'page_index' not in st.session_state:
st.session_state.page_index = 0
if 'summ_text' not in st.session_state:
st.session_state.summ_text = format(title_list, summ_text)
if 'current_text' not in st.session_state:
st.session_state.current_text = st.session_state.summ_text[st.session_state.page_index]
# Function to handle page turn
def turn_page(direction):
if direction == "next" and st.session_state.page_index < len(st.session_state.summ_text) - 1:
st.session_state.page_index += 1
elif direction == "prev" and st.session_state.page_index > 0:
st.session_state.page_index -= 1
st.session_state.current_text = st.session_state.summ_text[st.session_state.page_index]
# Function to update the current text based on text_area changes
def update_text():
st.session_state.summ_text[st.session_state.page_index] = st.session_state.text_area_value
st.session_state.current_text = st.session_state.text_area_value
st.subheader('Generated slides content')
# Display editable text box
text = st.text_area("Edit Text", st.session_state.current_text, height=200, key="text_area_value", on_change=update_text)
# Display page turner controls
col1, col2, col3 = st.columns([2.25, 12, 1.7])
# Previous button in col1
with col1:
st.button("Previous", on_click=turn_page, args=("prev",))
# Center aligned text in col2
with col2:
st.markdown(
f'<div style="display: flex; justify-content: center; align-items: center; height: 100%;">'
f'Page {st.session_state.page_index + 1} of {len(st.session_state.summ_text)}'
f'</div>',
unsafe_allow_html=True
)
# Next button in col3, right aligned
with col3:
st.button("Next", on_click=turn_page, args=("next",))
# Display HTML box
st.markdown(st.session_state.current_text)
def render_markdown_to_html(markdown_str):
return markdown.markdown(markdown_str)
def generate_pdf(html_string):
css = """
@page {
size: 1920px 1080px; /* Set page size to Full HD resolution */
margin: 0; /* Remove all margins */
}
body {
font-family: sans-serif;
background-color: #45474B; /* Set background color to grey */
margin: 0; /* Remove body margin */
padding: 0; /* Remove body padding */
}
.content {
background-color: #45474B; /* Ensure the background color spans the full page */
color: #F5F7F8; /* Set font color to white */
padding: 20mm; /* Set padding to create text margins */
box-sizing: border-box; /* Include padding in the element's total width and height */
}
.page {
font-size: 32pt; /* Adjust the font size as needed */
margin: 0; /* Remove margin from page content */
padding: 0; /* Remove padding from page content */
}
"""
pdf = BytesIO()
HTML(string=html_string).write_pdf(pdf, stylesheets=[CSS(string=css)])
pdf.seek(0)
return pdf
def create_pdf_from_markdown_strings(markdown_strings):
html_pages = [render_markdown_to_html(md) for md in markdown_strings]
# Combine HTML content with page breaks and add a style section for font size, margins, background color, and font color
combined_html = '''
<html>
<head>
<style>
.page {
font-size: 32pt; /* Adjust the font size as needed */
margin: 0; /* Remove margin from page content */
padding: 0; /* Remove padding from page content */
}
</style>
</head>
<body>
'''
for i, page in enumerate(html_pages):
combined_html += f'<div class="content"><div class="page">{page}</div></div>'
if i < len(html_pages) - 1: # Only add page break if it's not the last page
combined_html += '<div style="page-break-after: always;"></div>'
combined_html += '</body></html>'
return combined_html
html_content = create_pdf_from_markdown_strings(st.session_state.summ_text)
pdf_file = generate_pdf(html_content)
# Provide download link
st.download_button(
label="Download PDF",
data=pdf_file,
file_name="slides.pdf",
mime="application/pdf"
)