|  | 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): | 
					
						
						|  |  | 
					
						
						|  | processed_lines.append(line) | 
					
						
						|  | else: | 
					
						
						|  |  | 
					
						
						|  | 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'<a href="\2">\1</a>', 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('<a') - prev_text.count('</a') | 
					
						
						|  | if tag_balance > 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'<a href="{url_with_prefix}">{url}</a>') | 
					
						
						|  | start_idx = match.end() | 
					
						
						|  | return ''.join(result) | 
					
						
						|  |  | 
					
						
						|  | def apply_emoji_font(text, emoji_font): | 
					
						
						|  | link_pattern = re.compile(r'<a\s+href="([^"]+)">(.*?)</a>') | 
					
						
						|  | 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'<b>(.*?)</b>', 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'<font face="{emoji_font}">{emoji}</font>' | 
					
						
						|  | segments = [] | 
					
						
						|  | last_pos = 0 | 
					
						
						|  | for match in emoji_pattern.finditer(text): | 
					
						
						|  | start, end = match.span() | 
					
						
						|  | if last_pos < start: | 
					
						
						|  | segments.append(f'<font face="DejaVuSans">{text[last_pos:start]}</font>') | 
					
						
						|  | segments.append(replace_emoji(match)) | 
					
						
						|  | last_pos = end | 
					
						
						|  | if last_pos < len(text): | 
					
						
						|  | segments.append(f'<font face="DejaVuSans">{text[last_pos:]}</font>') | 
					
						
						|  | combined_text = ''.join(segments) | 
					
						
						|  | combined_text = combined_text.replace('###BOLD_START###', '</font><b><font face="DejaVuSans">') | 
					
						
						|  | combined_text = combined_text.replace('###BOLD_END###', '</font></b><font face="DejaVuSans">') | 
					
						
						|  | 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('<font') > before.rfind('</font>'): | 
					
						
						|  | link_html = f'</font><a href="{url}">{label}</a><font face="DejaVuSans">' | 
					
						
						|  | combined_text = before + link_html + after | 
					
						
						|  | else: | 
					
						
						|  | combined_text = before + f'<a href="{url}">{label}</a>' + 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') | 
					
						
						|  |  | 
					
						
						|  |  | 
					
						
						|  | first_numbered_seen = False | 
					
						
						|  |  | 
					
						
						|  | for line in lines: | 
					
						
						|  | line = line.strip() | 
					
						
						|  | if not line or line.startswith('# '): | 
					
						
						|  | continue | 
					
						
						|  |  | 
					
						
						|  |  | 
					
						
						|  | is_numbered_line = number_pattern.match(line) is not None | 
					
						
						|  |  | 
					
						
						|  |  | 
					
						
						|  | if add_space_before_numbered and is_numbered_line: | 
					
						
						|  |  | 
					
						
						|  | if first_numbered_seen and not line.startswith("1."): | 
					
						
						|  | pdf_content.append("") | 
					
						
						|  |  | 
					
						
						|  | if not first_numbered_seen: | 
					
						
						|  | first_numbered_seen = True | 
					
						
						|  |  | 
					
						
						|  | line = detect_and_convert_links(line) | 
					
						
						|  | if render_with_bold: | 
					
						
						|  | line = re.sub(r'\*\*(.*?)\*\*', r'<b>\1</b>', line) | 
					
						
						|  | if auto_bold_numbers and is_numbered_line: | 
					
						
						|  | if not (line.startswith("<b>") and line.endswith("</b>")): | 
					
						
						|  | if "<b>" in line and "</b>" in line: | 
					
						
						|  | line = re.sub(r'</?b>', '', line) | 
					
						
						|  | line = f"<b>{line}</b>" | 
					
						
						|  | else: | 
					
						
						|  | line = f"<b>{line}</b>" | 
					
						
						|  | 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("<b>") 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("<b>") and item.endswith("</b>"): | 
					
						
						|  | 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") | 
					
						
						|  |  | 
					
						
						|  |  | 
					
						
						|  | auto_columns = st.checkbox("AutoColumns", value=False, key="auto_columns") | 
					
						
						|  |  | 
					
						
						|  |  | 
					
						
						|  | 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(): | 
					
						
						|  | word_count = len(line.split()) | 
					
						
						|  | longest_line_words = max(longest_line_words, word_count) | 
					
						
						|  |  | 
					
						
						|  |  | 
					
						
						|  | if longest_line_words > 25: | 
					
						
						|  | recommended_columns = 1 | 
					
						
						|  | elif longest_line_words >= 18: | 
					
						
						|  | recommended_columns = 2 | 
					
						
						|  | elif longest_line_words >= 11: | 
					
						
						|  | recommended_columns = 3 | 
					
						
						|  | else: | 
					
						
						|  | recommended_columns = "Auto" | 
					
						
						|  |  | 
					
						
						|  | 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.") | 
					
						
						|  |  | 
					
						
						|  |  | 
					
						
						|  | 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}") | 
					
						
						|  |  | 
					
						
						|  |  | 
					
						
						|  | col1, col2 = st.columns(2) | 
					
						
						|  | with col1: | 
					
						
						|  | if st.button("ππ 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() | 
					
						
						|  |  | 
					
						
						|  |  | 
					
						
						|  | with col2: | 
					
						
						|  | if st.button("βοΈ 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="πΎπ 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="πΎπ 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="πΎπ Save PDF", | 
					
						
						|  | data=pdf_bytes, | 
					
						
						|  | file_name=f"{prefix} {selected_md}.pdf" if selected_md else f"{prefix} output.pdf", | 
					
						
						|  | mime="application/pdf" | 
					
						
						|  | ) |