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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'<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):
    lines = markdown_text.strip().split('\n')
    pdf_content = []
    number_pattern = re.compile(r'^\d+\.\s')
    for line in lines:
        line = line.strip()
        if not line or line.startswith('# '):
            continue
        line = detect_and_convert_links(line)
        if render_with_bold:
            line = re.sub(r'\*\*(.*?)\*\*', r'<b>\1</b>', line)
        if auto_bold_numbers and number_pattern.match(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):
    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)
    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 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)

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"
    )