Spaces:
Running
Running
File size: 10,791 Bytes
f32d4c7 |
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 |
"""
UI Components
=============
HTML generation functions for the Gradio interface
"""
from typing import List
from config import TokenizerInfo, TokenizationMetrics
from utils import is_arabic_char
def generate_token_visualization(tokens: List[str], token_ids: List[int]) -> str:
"""Generate beautiful HTML visualization of tokens"""
colors = [
('#1a1a2e', '#eaeaea'),
('#16213e', '#f0f0f0'),
('#0f3460', '#ffffff'),
('#533483', '#f5f5f5'),
('#e94560', '#ffffff'),
('#0f4c75', '#f0f0f0'),
('#3282b8', '#ffffff'),
('#bbe1fa', '#1a1a2e'),
]
html_parts = []
for i, (token, tid) in enumerate(zip(tokens, token_ids)):
bg, fg = colors[i % len(colors)]
display_token = token.replace('<', '<').replace('>', '>')
is_arabic = any(is_arabic_char(c) for c in token)
direction = 'rtl' if is_arabic else 'ltr'
html_parts.append(f'''
<span class="token" style="
background: {bg};
color: {fg};
direction: {direction};
" title="ID: {tid}">
{display_token}
<span class="token-id">{tid}</span>
</span>
''')
return f'''
<div class="token-container">
{''.join(html_parts)}
</div>
'''
def generate_metrics_card(metrics: TokenizationMetrics, info: TokenizerInfo) -> str:
"""Generate metrics visualization card"""
fertility_quality = "excellent" if metrics.fertility < 1.5 else "good" if metrics.fertility < 2.5 else "poor"
strr_quality = "excellent" if metrics.single_token_retention_rate > 0.5 else "good" if metrics.single_token_retention_rate > 0.3 else "poor"
compression_quality = "excellent" if metrics.compression_ratio > 4 else "good" if metrics.compression_ratio > 2.5 else "poor"
return f'''
<div class="metrics-grid">
<div class="metric-card primary">
<div class="metric-icon">π</div>
<div class="metric-value">{metrics.total_tokens}</div>
<div class="metric-label">Total Tokens</div>
</div>
<div class="metric-card {fertility_quality}">
<div class="metric-icon">π―</div>
<div class="metric-value">{metrics.fertility:.3f}</div>
<div class="metric-label">Fertility (tokens/word)</div>
<div class="metric-hint">Lower is better (1.0 ideal)</div>
</div>
<div class="metric-card {compression_quality}">
<div class="metric-icon">π¦</div>
<div class="metric-value">{metrics.compression_ratio:.2f}</div>
<div class="metric-label">Compression (bytes/token)</div>
<div class="metric-hint">Higher is better</div>
</div>
<div class="metric-card {strr_quality}">
<div class="metric-icon">β¨</div>
<div class="metric-value">{metrics.single_token_retention_rate:.1%}</div>
<div class="metric-label">STRR (Single Token Retention)</div>
<div class="metric-hint">Higher is better</div>
</div>
<div class="metric-card">
<div class="metric-icon">π€</div>
<div class="metric-value">{metrics.char_per_token:.2f}</div>
<div class="metric-label">Characters/Token</div>
</div>
<div class="metric-card {'excellent' if metrics.oov_percentage == 0 else 'poor' if metrics.oov_percentage > 5 else 'good'}">
<div class="metric-icon">β</div>
<div class="metric-value">{metrics.oov_percentage:.1f}%</div>
<div class="metric-label">OOV Rate</div>
<div class="metric-hint">Lower is better (0% ideal)</div>
</div>
<div class="metric-card">
<div class="metric-icon">π</div>
<div class="metric-value">{metrics.arabic_fertility:.3f}</div>
<div class="metric-label">Arabic Fertility</div>
</div>
<div class="metric-card">
<div class="metric-icon">β‘</div>
<div class="metric-value">{metrics.tokenization_time_ms:.2f}ms</div>
<div class="metric-label">Processing Time</div>
</div>
</div>
'''
def generate_tokenizer_info_card(info: TokenizerInfo) -> str:
"""Generate tokenizer information card"""
dialect_badges = ''.join([f'<span class="badge dialect">{d}</span>' for d in info.dialect_support])
feature_badges = ''.join([f'<span class="badge feature">{f}</span>' for f in info.special_features])
support_class = "native" if info.arabic_support == "Native" else "supported" if info.arabic_support == "Supported" else "limited"
return f'''
<div class="info-card">
<div class="info-header">
<h3>{info.name}</h3>
<span class="org-badge">{info.organization}</span>
</div>
<p class="description">{info.description}</p>
<div class="info-grid">
<div class="info-item">
<span class="info-label">Type:</span>
<span class="info-value">{info.type.value}</span>
</div>
<div class="info-item">
<span class="info-label">Algorithm:</span>
<span class="info-value">{info.algorithm.value}</span>
</div>
<div class="info-item">
<span class="info-label">Vocab Size:</span>
<span class="info-value">{info.vocab_size:,}</span>
</div>
<div class="info-item">
<span class="info-label">Arabic Support:</span>
<span class="info-value support-{support_class}">{info.arabic_support}</span>
</div>
</div>
<div class="badge-container">
<div class="badge-group">
<span class="badge-label">Dialects:</span>
{dialect_badges}
</div>
<div class="badge-group">
<span class="badge-label">Features:</span>
{feature_badges}
</div>
</div>
</div>
'''
def generate_decoded_section(metrics: TokenizationMetrics) -> str:
"""Generate decoded output section"""
return f'''
<div class="decoded-section">
<h4>Decoded Output</h4>
<div class="decoded-text" dir="auto">{metrics.decoded_text}</div>
<div class="decoded-meta">
Diacritics preserved: {'β
Yes' if metrics.diacritic_preservation else 'β No'}
</div>
</div>
'''
def generate_about_html(tokenizers_by_type: dict, total_count: int) -> str:
"""Generate About page HTML"""
# Build tokenizer lists
sections = []
for category, tokenizers in tokenizers_by_type.items():
if tokenizers:
items = ''.join([f'<li>{t}</li>' for t in tokenizers[:12]])
if len(tokenizers) > 12:
items += f'<li><em>...and {len(tokenizers) - 12} more</em></li>'
sections.append(f'''
<div class="about-category">
<h4>{category}</h4>
<ul>{items}</ul>
</div>
''')
return f'''
<div class="about-container">
<div class="about-header">
<h2>ποΈ Arabic Tokenizer Arena Pro</h2>
<p class="about-subtitle">A comprehensive platform for evaluating Arabic tokenizers across multiple dimensions</p>
</div>
<div class="about-stats">
<div class="stat-card">
<div class="stat-value">{total_count}</div>
<div class="stat-label">Available Tokenizers</div>
</div>
<div class="stat-card">
<div class="stat-value">8</div>
<div class="stat-label">Evaluation Datasets</div>
</div>
<div class="stat-card">
<div class="stat-value">8+</div>
<div class="stat-label">Metrics</div>
</div>
</div>
<div class="about-tokenizers">
<h3>π Available Tokenizers</h3>
<div class="tokenizer-grid">
{''.join(sections)}
</div>
</div>
<div class="about-features">
<h3>β¨ Features</h3>
<div class="feature-grid">
<div class="feature-item">
<span class="feature-icon">π</span>
<span>Comprehensive efficiency metrics (fertility, compression, STRR)</span>
</div>
<div class="feature-item">
<span class="feature-icon">π</span>
<span>Arabic-specific analysis (dialect support, diacritic preservation)</span>
</div>
<div class="feature-item">
<span class="feature-icon">βοΈ</span>
<span>Side-by-side tokenizer comparison</span>
</div>
<div class="feature-item">
<span class="feature-icon">π¨</span>
<span>Beautiful token visualization</span>
</div>
<div class="feature-item">
<span class="feature-icon">π</span>
<span>Leaderboard with real HuggingFace datasets</span>
</div>
<div class="feature-item">
<span class="feature-icon">π</span>
<span>Support for MSA, dialectal, and Classical Arabic</span>
</div>
</div>
</div>
<div class="about-usecases">
<h3>π― Use Cases</h3>
<div class="usecase-grid">
<div class="usecase-card">
<h4>π¬ Research</h4>
<p>Compare tokenizers for Arabic NLP experiments</p>
</div>
<div class="usecase-card">
<h4>π Production</h4>
<p>Select optimal tokenizer for deployment</p>
</div>
<div class="usecase-card">
<h4>π Education</h4>
<p>Understand how different algorithms handle Arabic</p>
</div>
<div class="usecase-card">
<h4>π° Optimization</h4>
<p>Identify cost-efficient tokenizers for API usage</p>
</div>
</div>
</div>
<div class="about-footer">
<p>Built with β€οΈ for the Arabic NLP community</p>
</div>
</div>
'''
|