File size: 11,399 Bytes
91db81f
 
 
 
fba4d1f
9f3cf94
 
 
 
91db81f
 
 
fba4d1f
 
 
 
91db81f
 
 
173ec9f
 
 
 
 
 
 
 
 
 
 
fba4d1f
173ec9f
91db81f
173ec9f
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
91db81f
173ec9f
 
91db81f
9f3cf94
9d7c221
fba4d1f
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
173ec9f
fba4d1f
 
 
 
 
 
 
 
 
 
 
 
 
9f3cf94
fba4d1f
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
91db81f
9d7c221
3febaf2
 
 
a11d82f
15f6774
c283503
 
 
3febaf2
 
 
 
 
15f6774
c283503
 
15f6774
 
 
 
fba4d1f
15f6774
 
 
 
9d7c221
a11d82f
9d7c221
c283503
 
 
9d7c221
c283503
91db81f
 
 
173ec9f
91db81f
 
 
 
3febaf2
 
 
 
173ec9f
3febaf2
c283503
 
 
3febaf2
 
 
 
 
173ec9f
c283503
 
 
3febaf2
 
 
 
 
173ec9f
c283503
 
 
 
3febaf2
 
 
c283503
3febaf2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
15f6774
3febaf2
c283503
3febaf2
 
c283503
3febaf2
15f6774
 
c283503
 
 
 
3febaf2
 
 
 
 
fba4d1f
 
91db81f
90a9144
 
 
 
173ec9f
90a9144
 
 
 
 
 
 
173ec9f
9d7c221
 
 
 
 
a11d82f
9d7c221
 
91db81f
9d7c221
 
 
91db81f
9d7c221
 
 
91db81f
d6b502d
 
 
d2cd664
d6b502d
 
9d7c221
91db81f
9d7c221
 
 
 
 
 
 
91db81f
9d7c221
 
 
 
 
 
91db81f
9d7c221
 
91db81f
9d7c221
91db81f
9d7c221
 
 
 
 
91db81f
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
import os
import urllib.request
import io
import re
import streamlit as st

# Set the page configuration as the very first Streamlit command.
st.set_page_config(layout="wide", initial_sidebar_state="collapsed")

from PIL import Image
import fitz  # PyMuPDF

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

# --- Step 1: Define and Download Available Emoji Fonts ---
font_files = [
    "Noto-COLRv1-emojicompat.ttf",
    "Noto-COLRv1-noflags.ttf",
    "Noto-COLRv1.ttf",
    "NotoColorEmoji-emojicompat.ttf",
    "NotoColorEmoji-flagsonly.ttf",
    "NotoColorEmoji-noflags.ttf",
    "NotoColorEmoji.ttf",
    "NotoColorEmoji_WindowsCompatible.ttf"
]

base_font_url = "https://github.com/googlefonts/noto-emoji/raw/main/fonts/"

for font_file in font_files:
    if not os.path.exists(font_file):
        st.info(f"Downloading {font_file}...")
        try:
            urllib.request.urlretrieve(base_font_url + font_file, font_file)
            st.success(f"Downloaded {font_file}")
        except Exception as e:
            st.error(f"Failed to download {font_file}: {e}")

# --- Step 2: Allow User to Select the Emoji Font ---
font_display_names = {f: f.replace(".ttf", "") for f in font_files}
selected_font_file = st.sidebar.selectbox(
    "Select Emoji Font",
    options=font_files,
    format_func=lambda f: font_display_names[f]
)

registered_font_name = font_display_names[selected_font_file]
pdfmetrics.registerFont(TTFont(registered_font_name, selected_font_file))

# --- Default Markdown Content with Emojis ---
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. πŸ”₯ **Supervised Fine-Tuning (SFT) using PyTorch**
   - Loss function customization
   - Gradient accumulation strategies
   - Learning rate schedulers

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

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

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

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

## Optimization & Deployment
7. πŸ“ **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. πŸ“‘ **Knowledge Extraction using Markdown Knowledge Graphs**
    - Entity recognition
    - Relationship mapping
    - Hierarchical structuring

11. πŸ—ΊοΈ **Knowledge Mapping with Mermaid Diagrams**
    - Flowchart generation
    - Sequence diagram creation
    - State diagrams

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

# --- Markdown to PDF Content Processing ---
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('# '):
            # Optionally skip main title
            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 ---
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 = []
    
    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
    
    if auto_size:
        base_font_size = max(6, min(12, 200 / total_items))
    
    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 = ParagraphStyle(
        'Heading1',
        parent=styles['Heading1'],
        fontName=registered_font_name,
        textColor=colors.darkblue,
        alignment=1,
        fontSize=title_font_size
    )
    
    section_style = ParagraphStyle(
        'SectionStyle',
        parent=styles['Heading2'],
        fontName=registered_font_name,
        textColor=colors.darkblue,
        fontSize=section_font_size,
        leading=section_font_size * 1.2,
        spaceAfter=2
    )
    
    item_style = ParagraphStyle(
        'ItemStyle',
        parent=styles['Normal'],
        fontName=registered_font_name,
        fontSize=item_font_size,
        leading=item_font_size * 1.2,
        spaceAfter=1
    )
    
    subitem_style = ParagraphStyle(
        'SubItemStyle',
        parent=styles['Normal'],
        fontName=registered_font_name,
        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 (for Preview) ---
def pdf_to_image(pdf_bytes):
    try:
        doc = fitz.open(stream=pdf_bytes, filetype="pdf")
        page = doc[0]
        pix = page.get_pixmap(matrix=fitz.Matrix(2.0, 2.0))
        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

# --- Sidebar UI for Additional Settings ---
with st.sidebar:
    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.")

# --- Persist Markdown Content in Session State ---
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 in UI ---
with st.container():
    pdf_image = pdf_to_image(pdf_bytes)
    if pdf_image:
        st.image(pdf_image, use_container_width=True)
    else:
        st.info("Download the PDF to view it locally.")

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

# --- Markdown Editor ---
edited_markdown = st.text_area(
    "Modify the markdown content below:",
    value=st.session_state.markdown_content,
    height=300
)

# --- Update PDF on Button Click ---
if st.button("Update PDF"):
    st.session_state.markdown_content = edited_markdown
    st.experimental_rerun()

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