import io import re import os import glob import asyncio import hashlib import unicodedata import streamlit as st from PIL import Image import fitz import edge_tts from reportlab.lib.pagesizes import A4 from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer, Table, TableStyle from reportlab.lib.styles import getSampleStyleSheet, ParagraphStyle from reportlab.lib import colors from reportlab.pdfbase import pdfmetrics from reportlab.pdfbase.ttfonts import TTFont from datetime import datetime import pytz st.set_page_config(layout="wide", initial_sidebar_state="collapsed") def get_timestamp_prefix(): central = pytz.timezone("US/Central") now = datetime.now(central) return now.strftime("%a %m%d %I%M%p").upper() def clean_for_speech(text): text = text.replace("#", "") emoji_pattern = re.compile( r"[\U0001F300-\U0001F5FF" r"\U0001F600-\U0001F64F" r"\U0001F680-\U0001F6FF" r"\U0001F700-\U0001F77F" r"\U0001F780-\U0001F7FF" r"\U0001F800-\U0001F8FF" r"\U0001F900-\U0001F9FF" r"\U0001FA00-\U0001FA6F" r"\U0001FA70-\U0001FAFF" r"\u2600-\u26FF" r"\u2700-\u27BF]+", flags=re.UNICODE) text = emoji_pattern.sub('', text) return text def trim_emojis_except_numbered(markdown_text): emoji_pattern = re.compile( r"[\U0001F300-\U0001F5FF" r"\U0001F600-\U0001F64F" r"\U0001F680-\U0001F6FF" r"\U0001F700-\U0001F77F" r"\U0001F780-\U0001F7FF" r"\U0001F800-\U0001F8FF" r"\U0001F900-\U0001F9FF" r"\U0001FAD0-\U0001FAD9" r"\U0001FA00-\U0001FA6F" r"\U0001FA70-\U0001FAFF" r"\u2600-\u26FF" r"\u2700-\u27BF]+" ) number_pattern = re.compile(r'^\d+\.\s') lines = markdown_text.strip().split('\n') processed_lines = [] for line in lines: if number_pattern.match(line): # Keep emojis in numbered lines processed_lines.append(line) else: # Remove emojis from other lines processed_lines.append(emoji_pattern.sub('', line)) return '\n'.join(processed_lines) async def generate_audio(text, voice, filename): communicate = edge_tts.Communicate(text, voice) await communicate.save(filename) return filename def detect_and_convert_links(text): url_pattern = re.compile( r'(https?://|www\.)[^\s\[\]()<>{}]+(\.[^\s\[\]()<>{}]+)+(/[^\s\[\]()<>{}]*)?', re.IGNORECASE ) md_link_pattern = re.compile(r'\[(.*?)\]\((https?://[^\s\[\]()<>{}]+)\)') text = md_link_pattern.sub(r'\1', text) start_idx = 0 result = [] while start_idx < len(text): match = url_pattern.search(text, start_idx) if not match: result.append(text[start_idx:]) break prev_text = text[start_idx:match.start()] tag_balance = prev_text.count(' 0: result.append(text[start_idx:match.end()]) else: result.append(text[start_idx:match.start()]) url = match.group(0) if url.startswith('www.'): url_with_prefix = 'http://' + url else: url_with_prefix = url result.append(f'{url}') start_idx = match.end() return ''.join(result) def apply_emoji_font(text, emoji_font): link_pattern = re.compile(r'(.*?)') links = [] def save_link(match): link_idx = len(links) links.append((match.group(1), match.group(2))) return f"###LINK_{link_idx}###" text = link_pattern.sub(save_link, text) text = re.sub(r'(.*?)', lambda m: f'###BOLD_START###{m.group(1)}###BOLD_END###', text) emoji_pattern = re.compile( r"([\U0001F300-\U0001F5FF" r"\U0001F600-\U0001F64F" r"\U0001F680-\U0001F6FF" r"\U0001F700-\U0001F77F" r"\U0001F780-\U0001F7FF" r"\U0001F800-\U0001F8FF" r"\U0001F900-\U0001F9FF" r"\U0001FAD0-\U0001FAD9" r"\U0001FA00-\U0001FA6F" r"\U0001FA70-\U0001FAFF" r"\u2600-\u26FF" r"\u2700-\u27BF]+)" ) def replace_emoji(match): emoji = match.group(1) emoji = unicodedata.normalize('NFC', emoji) return f'{emoji}' segments = [] last_pos = 0 for match in emoji_pattern.finditer(text): start, end = match.span() if last_pos < start: segments.append(f'{text[last_pos:start]}') segments.append(replace_emoji(match)) last_pos = end if last_pos < len(text): segments.append(f'{text[last_pos:]}') combined_text = ''.join(segments) combined_text = combined_text.replace('###BOLD_START###', '') combined_text = combined_text.replace('###BOLD_END###', '') for i, (url, label) in enumerate(links): placeholder = f"###LINK_{i}###" if placeholder in combined_text: parts = combined_text.split(placeholder) if len(parts) == 2: before, after = parts if before.rfind(' before.rfind(''): link_html = f'{label}' combined_text = before + link_html + after else: combined_text = before + f'{label}' + after return combined_text def markdown_to_pdf_content(markdown_text, render_with_bold, auto_bold_numbers, add_space_before_numbered): lines = markdown_text.strip().split('\n') pdf_content = [] number_pattern = re.compile(r'^\d+\.\s') # Track if we've seen the first numbered line already first_numbered_seen = False for line in lines: line = line.strip() if not line or line.startswith('# '): continue # Check if this is a numbered line is_numbered_line = number_pattern.match(line) is not None # Add a blank line before numbered lines (except the first one with "1.") if add_space_before_numbered and is_numbered_line: # Only add space if this isn't the first numbered line if first_numbered_seen and not line.startswith("1."): pdf_content.append("") # Add an empty line # Mark that we've seen a numbered line if not first_numbered_seen: first_numbered_seen = True line = detect_and_convert_links(line) if render_with_bold: line = re.sub(r'\*\*(.*?)\*\*', r'\1', line) if auto_bold_numbers and is_numbered_line: if not (line.startswith("") and line.endswith("")): if "" in line and "" in line: line = re.sub(r'', '', line) line = f"{line}" else: line = f"{line}" pdf_content.append(line) total_lines = len(pdf_content) return pdf_content, total_lines def create_pdf(markdown_text, base_font_size, render_with_bold, auto_bold_numbers, enlarge_numbered, num_columns, add_space_before_numbered): buffer = io.BytesIO() page_width = A4[0] * 2 page_height = A4[1] doc = SimpleDocTemplate(buffer, pagesize=(page_width, page_height), leftMargin=36, rightMargin=36, topMargin=36, bottomMargin=36) styles = getSampleStyleSheet() spacer_height = 10 pdf_content, total_lines = markdown_to_pdf_content(markdown_text, render_with_bold, auto_bold_numbers, add_space_before_numbered) try: available_font_files = glob.glob("*.ttf") if not available_font_files: st.error("No .ttf font files found.") return selected_font_path = next((f for f in available_font_files if "NotoEmoji-Bold" in f), None) if selected_font_path: pdfmetrics.registerFont(TTFont("NotoEmoji-Bold", selected_font_path)) pdfmetrics.registerFont(TTFont("DejaVuSans", "DejaVuSans.ttf")) except Exception as e: st.error(f"Font registration error: {e}") return total_chars = sum(len(line) for line in pdf_content) hierarchy_weight = sum(1.5 if line.startswith("") else 1 for line in pdf_content) content_density = total_lines * hierarchy_weight + total_chars / 50 usable_height = page_height - 72 - spacer_height usable_width = page_width - 72 avg_line_chars = total_chars / total_lines if total_lines > 0 else 50 ideal_lines_per_col = 20 suggested_columns = max(1, min(6, int(total_lines / ideal_lines_per_col) + 1)) num_columns = num_columns if num_columns != 0 else suggested_columns col_width = usable_width / num_columns min_font_size = 6 max_font_size = 16 lines_per_col = total_lines / num_columns if num_columns > 0 else total_lines target_height_per_line = usable_height / lines_per_col if lines_per_col > 0 else usable_height estimated_font_size = int(target_height_per_line / 1.5) adjusted_font_size = max(min_font_size, min(max_font_size, estimated_font_size)) if avg_line_chars > col_width / adjusted_font_size * 10: adjusted_font_size = int(col_width / (avg_line_chars / 10)) adjusted_font_size = max(min_font_size, adjusted_font_size) item_style = ParagraphStyle( 'ItemStyle', parent=styles['Normal'], fontName="DejaVuSans", fontSize=adjusted_font_size, leading=adjusted_font_size * 1.15, spaceAfter=1, linkUnderline=True ) numbered_bold_style = ParagraphStyle( 'NumberedBoldStyle', parent=styles['Normal'], fontName="NotoEmoji-Bold", fontSize=adjusted_font_size + 1 if enlarge_numbered else adjusted_font_size, leading=(adjusted_font_size + 1) * 1.15 if enlarge_numbered else adjusted_font_size * 1.15, spaceAfter=1, linkUnderline=True ) section_style = ParagraphStyle( 'SectionStyle', parent=styles['Heading2'], fontName="DejaVuSans", textColor=colors.darkblue, fontSize=adjusted_font_size * 1.1, leading=adjusted_font_size * 1.32, spaceAfter=2, linkUnderline=True ) columns = [[] for _ in range(num_columns)] lines_per_column = total_lines / num_columns if num_columns > 0 else total_lines current_line_count = 0 current_column = 0 number_pattern = re.compile(r'^\d+\.\s') for item in pdf_content: if current_line_count >= lines_per_column and current_column < num_columns - 1: current_column += 1 current_line_count = 0 columns[current_column].append(item) current_line_count += 1 column_cells = [[] for _ in range(num_columns)] for col_idx, column in enumerate(columns): for item in column: if isinstance(item, str) and item.startswith("") and item.endswith(""): content = item[3:-4].strip() if number_pattern.match(content): column_cells[col_idx].append(Paragraph(apply_emoji_font(content, "NotoEmoji-Bold"), numbered_bold_style)) else: column_cells[col_idx].append(Paragraph(apply_emoji_font(content, "NotoEmoji-Bold"), section_style)) else: column_cells[col_idx].append(Paragraph(apply_emoji_font(item, "DejaVuSans"), item_style)) max_cells = max(len(cells) for cells in column_cells) if column_cells else 0 for cells in column_cells: cells.extend([Paragraph("", item_style)] * (max_cells - len(cells))) table_data = list(zip(*column_cells)) if column_cells else [[]] table = Table(table_data, colWidths=[col_width] * num_columns, hAlign='CENTER') table.setStyle(TableStyle([ ('VALIGN', (0, 0), (-1, -1), 'TOP'), ('ALIGN', (0, 0), (-1, -1), 'LEFT'), ('BACKGROUND', (0, 0), (-1, -1), colors.white), ('GRID', (0, 0), (-1, -1), 0, colors.white), ('LINEAFTER', (0, 0), (num_columns-1, -1), 0.5, colors.grey), ('LEFTPADDING', (0, 0), (-1, -1), 2), ('RIGHTPADDING', (0, 0), (-1, -1), 2), ('TOPPADDING', (0, 0), (-1, -1), 1), ('BOTTOMPADDING', (0, 0), (-1, -1), 1), ])) story = [Spacer(1, spacer_height), table] doc.build(story) buffer.seek(0) return buffer.getvalue() def pdf_to_image(pdf_bytes): try: doc = fitz.open(stream=pdf_bytes, filetype="pdf") images = [] for page in doc: pix = page.get_pixmap(matrix=fitz.Matrix(2.0, 2.0)) img = Image.frombytes("RGB", [pix.width, pix.height], pix.samples) images.append(img) doc.close() return images except Exception as e: st.error(f"Failed to render PDF preview: {e}") return None md_files = [f for f in glob.glob("*.md") if os.path.basename(f) != "README.md"] md_options = [os.path.splitext(os.path.basename(f))[0] for f in md_files] with st.sidebar: st.markdown("### PDF Options") if md_options: selected_md = st.selectbox("Select Markdown File", options=md_options, index=0) with open(f"{selected_md}.md", "r", encoding="utf-8") as f: st.session_state.markdown_content = f.read() else: st.warning("No markdown file found. Please add one to your folder.") selected_md = None st.session_state.markdown_content = "" available_font_files = {os.path.splitext(os.path.basename(f))[0]: f for f in glob.glob("*.ttf")} selected_font_name = st.selectbox("Select Emoji Font", options=list(available_font_files.keys()), index=list(available_font_files.keys()).index("NotoEmoji-Bold") if "NotoEmoji-Bold" in available_font_files else 0) base_font_size = st.slider("Font Size (points)", min_value=6, max_value=16, value=8, step=1) render_with_bold = st.checkbox("Render with Bold Formatting (remove ** markers)", value=True, key="render_with_bold") auto_bold_numbers = st.checkbox("Auto Bold Numbered Lines", value=True, key="auto_bold_numbers") enlarge_numbered = st.checkbox("Enlarge Font Size for Numbered Lines", value=True, key="enlarge_numbered") add_space_before_numbered = st.checkbox("Add Space Ahead of Numbered Lines", value=False, key="add_space_before_numbered") # Add AutoColumns option to automatically determine column count based on line length auto_columns = st.checkbox("AutoColumns", value=False, key="auto_columns") # Auto-determine column count based on longest line if AutoColumns is checked if auto_columns and 'markdown_content' in st.session_state: current_markdown = st.session_state.markdown_content lines = current_markdown.strip().split('\n') longest_line_words = 0 for line in lines: if line.strip(): # Skip empty lines word_count = len(line.split()) longest_line_words = max(longest_line_words, word_count) # Set recommended columns based on word count if longest_line_words > 25: recommended_columns = 1 # Very long lines need a single column elif longest_line_words >= 18: recommended_columns = 2 # Long lines need 2 columns elif longest_line_words >= 11: recommended_columns = 3 # Medium lines can use 3 columns else: recommended_columns = "Auto" # Default to auto for shorter lines st.info(f"Longest line has {longest_line_words} words. Recommending {recommended_columns} columns.") else: recommended_columns = "Auto" column_options = ["Auto"] + list(range(1, 7)) num_columns = st.selectbox("Number of Columns", options=column_options, index=0 if recommended_columns == "Auto" else column_options.index(recommended_columns)) num_columns = 0 if num_columns == "Auto" else int(num_columns) st.info("Font size and columns adjust to fit one page.") # Changed label from "Modify the markdown content below:" to "Input Markdown" edited_markdown = st.text_area("Input Markdown", value=st.session_state.markdown_content, height=300, key=f"markdown_{selected_md}_{selected_font_name}_{num_columns}") # Added emoji to "Update PDF" button and created a two-column layout for buttons col1, col2 = st.columns(2) with col1: if st.button("πŸ”„πŸ“„ Update PDF"): st.session_state.markdown_content = edited_markdown if selected_md: with open(f"{selected_md}.md", "w", encoding="utf-8") as f: f.write(edited_markdown) st.rerun() # Added "Trim Emojis" button in second column with col2: if st.button("βœ‚οΈ Trim Emojis"): trimmed_content = trim_emojis_except_numbered(edited_markdown) st.session_state.markdown_content = trimmed_content if selected_md: with open(f"{selected_md}.md", "w", encoding="utf-8") as f: f.write(trimmed_content) st.rerun() prefix = get_timestamp_prefix() st.download_button( label="πŸ’ΎπŸ“ Save Markdown", data=st.session_state.markdown_content, file_name=f"{prefix} {selected_md}.md" if selected_md else f"{prefix} default.md", mime="text/markdown" ) st.markdown("### Text-to-Speech") VOICES = ["en-US-AriaNeural", "en-US-JennyNeural", "en-GB-SoniaNeural", "en-US-GuyNeural", "en-US-AnaNeural"] selected_voice = st.selectbox("Select Voice for TTS", options=VOICES, index=0) if st.button("Generate Audio"): cleaned_text = clean_for_speech(st.session_state.markdown_content) audio_filename = f"{prefix} {selected_md} {selected_voice}.mp3" if selected_md else f"{prefix} default {selected_voice}.mp3" audio_file = asyncio.run(generate_audio(cleaned_text, selected_voice, audio_filename)) st.audio(audio_file) with open(audio_file, "rb") as f: audio_bytes = f.read() st.download_button( label="πŸ’ΎπŸ”Š Save Audio", data=audio_bytes, file_name=audio_filename, mime="audio/mpeg" ) with st.spinner("Generating PDF..."): pdf_bytes = create_pdf(st.session_state.markdown_content, base_font_size, render_with_bold, auto_bold_numbers, enlarge_numbered, num_columns, add_space_before_numbered) with st.container(): pdf_images = pdf_to_image(pdf_bytes) if pdf_images: for img in pdf_images: st.image(img, use_container_width=True) else: st.info("Download the PDF to view it locally.") with st.sidebar: st.download_button( label="πŸ’ΎπŸ“„ Save PDF", data=pdf_bytes, file_name=f"{prefix} {selected_md}.pdf" if selected_md else f"{prefix} output.pdf", mime="application/pdf" )