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

# Define the ML outline as a markdown string
ml_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):
    """Convert markdown text to a format suitable for PDF generation"""
    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 using ReportLab
def create_main_pdf(markdown_text):
    """Create a single-page landscape PDF with the outline in two columns"""
    buffer = io.BytesIO()
    doc = SimpleDocTemplate(
        buffer, 
        pagesize=(A4[1], A4[0]),  # Landscape
        leftMargin=50,
        rightMargin=50,
        topMargin=50,
        bottomMargin=50
    )
    
    styles = getSampleStyleSheet()
    story = []
    
    # Create custom styles
    title_style = styles['Heading1']
    title_style.textColor = colors.darkblue
    title_style.alignment = 1  # Center alignment
    
    section_style = ParagraphStyle(
        'SectionStyle',
        parent=styles['Heading2'],
        textColor=colors.darkblue,
        spaceAfter=6
    )
    
    item_style = ParagraphStyle(
        'ItemStyle',
        parent=styles['Normal'],
        fontSize=11,
        leading=14,
        fontName='Helvetica-Bold'
    )
    
    subitem_style = ParagraphStyle(
        'SubItemStyle',
        parent=styles['Normal'],
        fontSize=10,
        leading=12,
        leftIndent=20
    )
    
    # Add title
    story.append(Paragraph("Cutting-Edge ML Outline (ReportLab)", title_style))
    story.append(Spacer(1, 20))
    
    # Process markdown content
    left_column, right_column = markdown_to_pdf_content(markdown_text)
    
    # Prepare data for table
    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))
    
    # Make columns equal length
    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)))
    
    # Create table data
    table_data = list(zip(left_cells, right_cells))
    
    # Calculate column widths
    col_width = (A4[1] - 120) / 2.0
    
    # Create and style table
    table = Table(table_data, colWidths=[col_width, col_width])
    table.setStyle(TableStyle([
        ('VALIGN', (0, 0), (-1, -1), 'TOP'),
        ('ALIGN', (0, 0), (0, -1), 'LEFT'),
        ('ALIGN', (1, 0), (1, -1), 'LEFT'),
        ('BACKGROUND', (0, 0), (-1, -1), colors.white),
        ('GRID', (0, 0), (-1, -1), 0.5, colors.white),
        ('LINEAFTER', (0, 0), (0, -1), 1, colors.grey),
    ]))
    
    story.append(table)
    doc.build(story)
    buffer.seek(0)
    return buffer.getvalue()

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

if st.button("Generate Main PDF"):
    with st.spinner("Generating PDF..."):
        pdf_bytes = create_main_pdf(ml_markdown)
        st.download_button(
            label="Download Main PDF",
            data=pdf_bytes,
            file_name="ml_outline.pdf",
            mime="application/pdf"
        )
        base64_pdf = base64.b64encode(pdf_bytes).decode('utf-8')
        pdf_display = f'<embed src="data:application/pdf;base64,{base64_pdf}" width="100%" height="400px" type="application/pdf">'
        st.markdown(pdf_display, unsafe_allow_html=True)
        st.success("PDF generated successfully!")