app.py

import streamlit as st
import base64
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
import io
import re
import fitz  # PyMuPDF
from PIL import Image

# Initial markdown content
default_markdown = """# Cutting-Edge ML Outline

## Core ML Techniques
1. 🌟 **Mixture of Experts (MoE)**
   - Conditional computation techniques
   - Sparse gating mechanisms
   - Training specialized sub-models

2. 🔥 **Supervised Fine-Tuning (SFT) using PyTorch**
   - Loss function customization
   - Gradient accumulation strategies
   - Learning rate schedulers

3. 🤖 **Large Language Models (LLM) using Transformers**
   - Attention mechanisms
   - Tokenization strategies
   - Position encodings

## Training Methods
4. 📊 **Self-Rewarding Learning using NPS 0-10 and Verbatims**
   - Custom reward functions
   - Feedback categorization
   - Signal extraction from text

5. 👍 **Reinforcement Learning from Human Feedback (RLHF)**
   - Preference datasets
   - PPO implementation
   - KL divergence constraints

6. 🔗 **MergeKit: Merging Models to Same Embedding Space**
   - TIES merging
   - Task arithmetic
   - SLERP interpolation

## Optimization & Deployment
7. 📏 **DistillKit: Model Size Reduction with Spectrum Analysis**
   - Knowledge distillation
   - Quantization techniques
   - Model pruning strategies

8. 🧠 **Agentic RAG Agents using Document Inputs**
   - Vector database integration
   - Query planning
   - Self-reflection mechanisms

9. ⏳ **Longitudinal Data Summarization from Multiple Docs**
   - Multi-document compression
   - Timeline extraction
   - Entity tracking

## Knowledge Representation
10. 📑 **Knowledge Extraction using Markdown Knowledge Graphs**
    - Entity recognition
    - Relationship mapping
    - Hierarchical structuring

11. 🗺️ **Knowledge Mapping with Mermaid Diagrams**
    - Flowchart generation
    - Sequence diagram creation
    - State diagrams

12. 💻 **ML Code Generation with Streamlit/Gradio/HTML5+JS**
    - Code completion
    - Unit test generation
    - Documentation synthesis
"""

# Process multilevel markdown for PDF output
def markdown_to_pdf_content(markdown_text):
    lines = markdown_text.strip().split('\n')
    pdf_content = []
    in_list_item = False
    current_item = None
    sub_items = []
    
    for line in lines:
        line = line.strip()
        if not line:
            continue
            
        if line.startswith('# '):
            pass
        elif line.startswith('## '):
            if current_item and sub_items:
                pdf_content.append([current_item, sub_items])
                sub_items = []
                current_item = None
                
            section = line.replace('## ', '').strip()
            pdf_content.append(f"<b>{section}</b>")
            in_list_item = False
        elif re.match(r'^\d+\.', line):
            if current_item and sub_items:
                pdf_content.append([current_item, sub_items])
                sub_items = []
            
            current_item = line.strip()
            in_list_item = True
        elif line.startswith('- ') and in_list_item:
            sub_items.append(line.strip())
        else:
            if not in_list_item:
                pdf_content.append(line.strip())
    
    if current_item and sub_items:
        pdf_content.append([current_item, sub_items])
    
    mid_point = len(pdf_content) // 2
    left_column = pdf_content[:mid_point]
    right_column = pdf_content[mid_point:]
    
    return left_column, right_column

# Main PDF creation with parameterized text sizes
def create_main_pdf(markdown_text, base_font_size=10, auto_size=False):
    buffer = io.BytesIO()
    doc = SimpleDocTemplate(
        buffer, 
        pagesize=(A4[1], A4[0]),
        leftMargin=36,
        rightMargin=36,
        topMargin=36,
        bottomMargin=36
    )
    
    styles = getSampleStyleSheet()
    story = []
    
    page_height = A4[0] - 72
    title_height = 20
    spacer_height = 10
    
    left_column, right_column = markdown_to_pdf_content(markdown_text)
    
    total_items = 0
    for col in (left_column, right_column):
        for item in col:
            if isinstance(item, list):
                main_item, sub_items = item
                total_items += 1 + len(sub_items)
            else:
                total_items += 1
    
    # 🔧 Adjust this multiplier to control autosizing sensitivity
    if auto_size:
        base_font_size = max(6, min(12, 200 / total_items))
    
    # 🔧 Font size parameters - tweak these ratios as needed
    item_font_size = base_font_size
    subitem_font_size = base_font_size * 0.9
    section_font_size = base_font_size * 1.2
    title_font_size = min(16, base_font_size * 1.5)
    
    title_style = styles['Heading1']
    title_style.textColor = colors.darkblue
    title_style.alignment = 1
    title_style.fontSize = title_font_size
    
    section_style = ParagraphStyle(
        'SectionStyle',
        parent=styles['Heading2'],
        textColor=colors.darkblue,
        fontSize=section_font_size,
        leading=section_font_size * 1.2,
        spaceAfter=2
    )
    
    item_style = ParagraphStyle(
        'ItemStyle',
        parent=styles['Normal'],
        fontSize=item_font_size,
        leading=item_font_size * 1.2,
        fontName='Helvetica-Bold',
        spaceAfter=1
    )
    
    subitem_style = ParagraphStyle(
        'SubItemStyle',
        parent=styles['Normal'],
        fontSize=subitem_font_size,
        leading=subitem_font_size * 1.2,
        leftIndent=10,
        spaceAfter=1
    )
    
    story.append(Paragraph("Cutting-Edge ML Outline (ReportLab)", title_style))
    story.append(Spacer(1, spacer_height))
    
    left_cells = []
    for item in left_column:
        if isinstance(item, str) and item.startswith('<b>'):
            text = item.replace('<b>', '').replace('</b>', '')
            left_cells.append(Paragraph(text, section_style))
        elif isinstance(item, list):
            main_item, sub_items = item
            left_cells.append(Paragraph(main_item, item_style))
            for sub_item in sub_items:
                left_cells.append(Paragraph(sub_item, subitem_style))
        else:
            left_cells.append(Paragraph(item, item_style))
    
    right_cells = []
    for item in right_column:
        if isinstance(item, str) and item.startswith('<b>'):
            text = item.replace('<b>', '').replace('</b>', '')
            right_cells.append(Paragraph(text, section_style))
        elif isinstance(item, list):
            main_item, sub_items = item
            right_cells.append(Paragraph(main_item, item_style))
            for sub_item in sub_items:
                right_cells.append(Paragraph(sub_item, subitem_style))
        else:
            right_cells.append(Paragraph(item, item_style))
    
    max_cells = max(len(left_cells), len(right_cells))
    left_cells.extend([""] * (max_cells - len(left_cells)))
    right_cells.extend([""] * (max_cells - len(right_cells)))
    
    table_data = list(zip(left_cells, right_cells))
    col_width = (A4[1] - 72) / 2.0
    
    table = Table(table_data, colWidths=[col_width, col_width], 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), (0, -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.append(table)
    doc.build(story)
    buffer.seek(0)
    return buffer.getvalue()

# Function to convert PDF bytes to image using fitz (from backup.03302025-720pm.app.py)
def pdf_to_image(pdf_bytes):
    try:
        # Open PDF from bytes
        doc = fitz.open(stream=pdf_bytes, filetype="pdf")
        # Get the first page
        page = doc[0]
        # Render page to pixmap with a zoom factor for clarity
        pix = page.get_pixmap(matrix=fitz.Matrix(2.0, 2.0))  # 2x zoom
        # Convert to PIL Image
        img = Image.frombytes("RGB", [pix.width, pix.height], pix.samples)
        doc.close()
        return img
    except Exception as e:
        st.error(f"Failed to render PDF preview: {e}")
        return None

# Streamlit UI
st.title("🚀 Cutting-Edge ML Outline Generator")

# Sidebar for settings
with st.sidebar:
    st.header("PDF Settings")
    auto_size = st.checkbox("Auto-size text", value=True)
    if not auto_size:
        base_font_size = st.slider("Base Font Size (points)", min_value=6, max_value=16, value=10, step=1)
    else:
        base_font_size = 10
        st.info("Font size will auto-adjust between 6-12 points based on content length.")

# Use session state to persist markdown content
if 'markdown_content' not in st.session_state:
    st.session_state.markdown_content = default_markdown

# Generate PDF
with st.spinner("Generating PDF..."):
    pdf_bytes = create_main_pdf(st.session_state.markdown_content, base_font_size, auto_size)

# Display PDF preview using fitz
st.subheader("PDF Preview")
pdf_image = pdf_to_image(pdf_bytes)
if pdf_image:
    st.image(pdf_image, caption="PDF Page 1", use_column_width=True)
else:
    st.info("Download the PDF to view it locally.")

# Download button
st.download_button(
    label="Download PDF",
    data=pdf_bytes,
    file_name="ml_outline.pdf",
    mime="application/pdf"
)

# Markdown editor
st.subheader("Edit Markdown Outline")
edited_markdown = st.text_area(
    "Modify the markdown content below:",
    value=st.session_state.markdown_content,
    height=300
)

# Update markdown and regenerate PDF on change
if st.button("Update PDF"):
    st.session_state.markdown_content = edited_markdown
    st.rerun()

# Save markdown option
st.download_button(
    label="Save Markdown",
    data=st.session_state.markdown_content,
    file_name="ml_outline.md",
    mime="text/markdown"
)