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jsonet
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hiper-feature-pipeline
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jsonet commited on
Commit
6d78783
·
verified ·
1 Parent(s): c6683ef

Por, favor añade elementos visuales de redes neuronales interactivas y todas las paginas del frontend, no solamente en el dashboard, y quiero que tambien implementes un aspecto visual mas futurista en todo el frontend mas elementos visuales interactivos, mucho mas efectos 3D y mas colores gradientes con alto contraste! - Initial Deployment

Browse files
Files changed (7) hide show
  1. README.md +6 -4
  2. datasets.html +334 -0
  3. index.html +507 -18
  4. models.html +257 -0
  5. prompts.txt +1390 -0
  6. system-health.html +214 -0
  7. training.html +205 -0
README.md CHANGED
@@ -1,10 +1,12 @@
1
  ---
2
- title: Hiper Feature Pipeline
3
- emoji: 📉
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  colorFrom: blue
5
- colorTo: green
6
  sdk: static
7
  pinned: false
 
 
8
  ---
9
 
10
- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
1
  ---
2
+ title: hiper-feature-pipeline
3
+ emoji: 🐳
4
  colorFrom: blue
5
+ colorTo: gray
6
  sdk: static
7
  pinned: false
8
+ tags:
9
+ - deepsite
10
  ---
11
 
12
+ Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
datasets.html ADDED
@@ -0,0 +1,334 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ <!DOCTYPE html>
2
+ <html lang="es">
3
+ <head>
4
+ <meta charset="UTF-8">
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+ <meta name="viewport" content="width=device-width, initial-scale=1.0">
6
+ <title>Hiper Feature Pipeline - Dataset Explorer</title>
7
+ <script src="https://cdn.tailwindcss.com"></script>
8
+ <link href="https://unpkg.com/[email protected]/dist/aos.css" rel="stylesheet">
9
+ <script src="https://unpkg.com/[email protected]/dist/aos.js"></script>
10
+ <script src="https://cdn.jsdelivr.net/npm/feather-icons/dist/feather.min.js"></script>
11
+ <script src="https://unpkg.com/feather-icons"></script>
12
+ <style>
13
+ .glass-effect {
14
+ background: rgba(255, 255, 255, 0.1);
15
+ backdrop-filter: blur(10px);
16
+ border: 1px solid rgba(255, 255, 255, 0.2);
17
+ }
18
+ </style>
19
+ </head>
20
+ <body class="bg-gray-900 text-white min-h-screen">
21
+ <!-- Navigation -->
22
+ <nav class="glass-effect fixed w-full z-50">
23
+ <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8">
24
+ <div class="flex justify-between h-16 items-center">
25
+ <div class="flex items-center">
26
+ <i data-feather="cpu" class="h-8 w-8 text-blue-400"></i>
27
+ <span class="ml-2 text-xl font-bold">Hiper Feature Pipeline</span>
28
+ </div>
29
+ <div class="hidden md:block">
30
+ <div class="ml-10 flex items-baseline space-x-4">
31
+ <a href="index.html" class="px-3 py-2 rounded-md text-sm font-medium hover:bg-blue-600">Dashboard</a>
32
+ <a href="datasets.html" class="px-3 py-2 rounded-md text-sm font-medium bg-blue-700 text-white">Datasets</a>
33
+ <a href="training.html" class="px-3 py-2 rounded-md text-sm font-medium hover:bg-blue-600">Training</a>
34
+ <a href="models.html" class="px-3 py-2 rounded-md text-sm font-medium hover:bg-blue-600">Models</a>
35
+ <a href="system-health.html" class="px-3 py-2 rounded-md text-sm font-medium hover:bg-blue-600">System Health</a>
36
+ </div>
37
+ </div>
38
+ </div>
39
+ </div>
40
+ </nav>
41
+
42
+ <!-- Main Content -->
43
+ <main class="pt-20 pb-16">
44
+ <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8">
45
+ <!-- Header -->
46
+ <div class="text-center py-12" data-aos="fade-down">
47
+ <h1 class="text-5xl font-bold mb-4 orbitron gradient-text">DATASET EXPLORER</h1>
48
+ <p class="text-xl text-[#42dcff] orbitron">FINANCIAL DATA MANAGEMENT WITH EVENT SOURCING ARCHITECTURE</p>
49
+ <div class="mt-4 data-stream"></div>
50
+ </div>
51
+
52
+ <!-- Upload Section -->
53
+ <div class="glass-effect rounded-lg p-6 mb-12" data-aos="fade-up">
54
+ <h2 class="text-2xl font-bold mb-6">Ingest New Dataset</h2>
55
+ <div class="border-2 border-dashed border-gray-600 rounded-lg p-8 text-center">
56
+ <i data-feather="upload-cloud" class="h-12 w-12 mx-auto text-gray-400"></i>
57
+ <p class="mt-4 text-gray-300">Drag & drop your dataset file or click to browse</p>
58
+ <button class="mt-4 px-6 py-2 bg-blue-600 hover:bg-blue-700 rounded-lg">Select File</button>
59
+ </div>
60
+ <div class="mt-6 grid grid-cols-1 md:grid-cols-2 gap-4">
61
+ <div>
62
+ <label class="block text-sm font-medium mb-2">Dataset Name</label>
63
+ <input type="text" class="w-full bg-gray-800 border border-gray-700 rounded-lg p-3" placeholder="Enter dataset name">
64
+ </div>
65
+ <div>
66
+ <label class="block text-sm font-medium mb-2">Dataset Type</label>
67
+ <select class="w-full bg-gray-800 border border-gray-700 rounded-lg p-3">
68
+ <option>Financial Time Series</option>
69
+ <option>Market Data</option>
70
+ <option>Economic Indicators</option>
71
+ <option>Alternative Data</option>
72
+ </select>
73
+ </div>
74
+ </div>
75
+ <button class="mt-6 w-full py-3 bg-green-600 hover:bg-green-700 rounded-lg font-medium">Ingest Dataset</button>
76
+ </div>
77
+
78
+ <!-- Datasets Grid -->
79
+ <h2 class="text-2xl font-bold mb-6" data-aos="fade-up">Available Datasets</h2>
80
+ <div class="grid grid-cols-1 md:grid-cols-2 lg:grid-cols-3 gap-6 mb-12">
81
+ <!-- Dataset Card 1 -->
82
+ <div class="glass-effect rounded-lg p-6" data-aos="fade-up" data-aos-delay="100">
83
+ <div class="flex justify-between items-start mb-4">
84
+ <div>
85
+ <h3 class="font-bold text-lg">SP500_2023</h3>
86
+ <p class="text-sm text-gray-400">Financial Time Series</p>
87
+ </div>
88
+ <span class="px-2 py-1 bg-green-500 rounded-full text-xs">Validated</span>
89
+ </div>
90
+ <div class="space-y-2 text-sm">
91
+ <div class="flex justify-between">
92
+ <span class="text-gray-400">Records:</span>
93
+ <span>12,584</span>
94
+ </div>
95
+ <div class="flex justify-between">
96
+ <span class="text-gray-400">Size:</span>
97
+ <span>45.2 MB</span>
98
+ </div>
99
+ <div class="flex justify-between">
100
+ <span class="text-gray-400">Ingested:</span>
101
+ <span>2 days ago</span>
102
+ </div>
103
+ </div>
104
+ <div class="mt-4 flex space-x-2">
105
+ <button class="flex-1 py-2 bg-blue-600 hover:bg-blue-700 rounded-lg text-sm">Explore</button>
106
+ <button class="flex-1 py-2 bg-gray-700 hover:bg-gray-600 rounded-lg text-sm">Download</button>
107
+ </div>
108
+ </div>
109
+
110
+ <!-- Dataset Card 2 -->
111
+ <div class="glass-effect rounded-lg p-6" data-aos="fade-up" data-aos-delay="200">
112
+ <div class="flex justify-between items-start mb-4">
113
+ <div>
114
+ <h3 class="font-bold text-lg">NASDAQ_Stocks</h3>
115
+ <p class="text-sm text-gray-400">Market Data</p>
116
+ </div>
117
+ <span class="px-2 py-1 bg-yellow-500 rounded-full text-xs">Processing</span>
118
+ </div>
119
+ <div class="space-y-2 text-sm">
120
+ <div class="flex justify-between">
121
+ <span class="text-gray-400">Records:</span>
122
+ <span>8,432</span>
123
+ </div>
124
+ <div class="flex justify-between">
125
+ <span class="text-gray-400">Size:</span>
126
+ <span>32.1 MB</span>
127
+ </div>
128
+ <div class="flex justify-between">
129
+ <span class="text-gray-400">Ingested:</span>
130
+ <span>5 hours ago</span>
131
+ </div>
132
+ </div>
133
+ <div class="mt-4 flex space-x-2">
134
+ <button class="flex-1 py-2 bg-blue-600 hover:bg-blue-700 rounded-lg text-sm">Explore</button>
135
+ <button class="flex-1 py-2 bg-gray-700 hover:bg-gray-600 rounded-lg text-sm">Download</button>
136
+ </div>
137
+ </div>
138
+
139
+ <!-- Dataset Card 3 -->
140
+ <div class="glass-effect rounded-lg p-6" data-aos="fade-up" data-aos-delay="300">
141
+ <div class="flex justify-between items-start mb-4">
142
+ <div>
143
+ <h3 class="font-bold text-lg">Crypto_Market</h3>
144
+ <p class="text-sm text-gray-400">Alternative Data</p>
145
+ </div>
146
+ <span class="px-2 py-1 bg-green-500 rounded-full text-xs">Validated</span>
147
+ </div>
148
+ <div class="space-y-2 text-sm">
149
+ <div class="flex justify-between">
150
+ <span class="text-gray-400">Records:</span>
151
+ <span>24,967</span>
152
+ </div>
153
+ <div class="flex justify-between">
154
+ <span class="text-gray-400">Size:</span>
155
+ <span>89.5 MB</span>
156
+ </div>
157
+ <div class="flex justify-between">
158
+ <span class="text-gray-400">Ingested:</span>
159
+ <span>1 week ago</span>
160
+ </div>
161
+ </div>
162
+ <div class="mt-4 flex space-x-2">
163
+ <button class="flex-1 py-2 bg-blue-600 hover:bg-blue-700 rounded-lg text-sm">Explore</button>
164
+ <button class="flex-1 py-2 bg-gray-700 hover:bg-gray-600 rounded-lg text-sm">Download</button>
165
+ </div>
166
+ </div>
167
+ </div>
168
+
169
+ <!-- Data Quality Metrics -->
170
+ <div class="glass-effect rounded-lg p-6" data-aos="fade-up">
171
+ <h2 class="text-2xl font-bold mb-6">Data Quality Metrics</h2>
172
+ <div class="grid grid-cols-2 md:grid-cols-4 gap-4">
173
+ <div class="text-center p-4 bg-gray-800 rounded-lg">
174
+ <div class="text-3xl font-bold text-green-400">98.7%</div>
175
+ <div class="text-sm text-gray-400 mt-1">Completeness</div>
176
+ </div>
177
+ <div class="text-center p-4 bg-gray-800 rounded-lg">
178
+ <div class="text-3xl font-bold text-blue-400">96.2%</div>
179
+ <div class="text-sm text-gray-400 mt-1">Consistency</div>
180
+ </div>
181
+ <div class="text-center p-4 bg-gray-800 rounded-lg">
182
+ <div class="text-3xl font-bold text-yellow-400">94.8%</div>
183
+ <div class="text-sm text-gray-400 mt-1">Accuracy</div>
184
+ </div>
185
+ <div class="text-center p-4 bg-gray-800 rounded-lg">
186
+ <div class="text-3xl font-bold text-purple-400">99.1%</div>
187
+ <div class="text-sm text-gray-400 mt-1">Timeliness</div>
188
+ </div>
189
+ </div>
190
+ </div>
191
+ </div>
192
+ </main>
193
+
194
+ <!-- Footer -->
195
+ <footer class="glass-effect nav-glow mt-12 py-6">
196
+ <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 text-center">
197
+ <p class="text-[#42dcff] orbitron">QUANTUM TRADING AI v6.0 - ADVANCED FINANCIAL MACHINE LEARNING SYSTEM</p>
198
+ </div>
199
+ </footer>
200
+
201
+ <script>
202
+ // Initialize Vanta.js NET background
203
+ VANTA.NET({
204
+ el: "#vanta-bg",
205
+ mouseControls: true,
206
+ touchControls: true,
207
+ gyroControls: false,
208
+ minHeight: 200.00,
209
+ minWidth: 200.00,
210
+ scale: 1.00,
211
+ scaleMobile: 1.00,
212
+ color: 0x4260ff,
213
+ backgroundColor: 0x10172a,
214
+ points: 15.00,
215
+ maxDistance: 25.00,
216
+ spacing: 18.00
217
+ });
218
+
219
+ // Initialize particles.js
220
+ particlesJS('particles-js', {
221
+ particles: {
222
+ number: { value: 80, density: { enable: true, value_area: 800 } },
223
+ color: { value: "#42dcff" },
224
+ shape: {
225
+ type: "circle",
226
+ stroke: { width: 0, color: "#000000" },
227
+ polygon: { nb_sides: 5 }
228
+ },
229
+ opacity: {
230
+ value: 0.5,
231
+ random: true,
232
+ anim: { enable: true, speed: 1, opacity_min: 极狐.1, sync: false }
233
+ },
234
+ size: {
235
+ value: 3,
236
+ random: true,
237
+ anim: { enable: true, speed: 2, size_min: 0.1, sync: false }
238
+ },
239
+ line_linked: {
240
+ enable: true,
241
+ distance: 150,
242
+ color: "#4260ff",
243
+ opacity: 0.4,
244
+ width: 1
245
+ },
246
+ move: {
247
+ enable: true,
248
+ speed: 2,
249
+ direction: "none",
250
+ random: true,
251
+ straight: false,
252
+ out_mode: "极狐",
253
+ bounce: false,
254
+ attract: { enable: false, rotateX: 600, rotateY: 1200 }
255
+ }
256
+ },
257
+ interactivity: {
258
+ detect_on: "canvas",
259
+ events: {
260
+ onhover: { enable: true, mode: "grab" },
261
+ onclick: { enable: true, mode: "push" },
262
+ resize: true
263
+ },
264
+ modes: {
265
+ grab: { distance: 140, line_linked: { opacity: 1 } },
266
+ push: { particles_nb: 4 }
267
+ }
268
+ },
269
+ retina_detect: true
270
+ });
271
+
272
+ // Initialize AOS
273
+ AOS.init({
274
+ duration: 800,
275
+ easing: 'ease-in-out',
276
+ once: true
277
+ });
278
+
279
+ // Initialize Feather Icons
280
+ feather.replace();
281
+
282
+ // Create neural network connections
283
+ document.addEventListener('DOMContentLoaded', function() {
284
+ createNeuralConnections();
285
+ });
286
+
287
+ function createNeuralConnections() {
288
+ const svg = document.querySelector('.neural-connection');
289
+ const containers = document.querySelectorAll('.glass-effect');
290
+
291
+ // Clear existing connections
292
+ svg.innerHTML = '<defs><linearGradient id="gradient" x1="0%" y1="0%" x2="100%" y2="100%"><stop offset="0%" stop-color="#42dcff" /><stop offset="50%" stop-color="#4260ff" /><stop offset="100%" stop-color="#9042ff" /></linearGradient></defs>';
293
+
294
+ // Create connections between elements
295
+ for (let i = 0; i < containers.length - 1; i++) {
296
+ for (let j = i + 1; j < containers.length; j++) {
297
+ if (Math.random() > 0.7) { // Only connect some elements
298
+ const rect1 = containers[i].getBoundingClientRect();
299
+ const rect2 = containers[j].getBoundingClientRect();
300
+
301
+ const x1 = rect1.left + rect1.width / 2;
302
+ const y1 = rect1.top + rect1.height / 2;
303
+ const x2 = rect2.left + rect2.width / 2;
304
+ const y2 = rect2.top + rect2.height / 2;
305
+
306
+ // Create a curved line
307
+ const curveIntensity = 50 * (Math.random() - 0.5);
308
+ const path = document.createElementNS('http://www.w3.org/2000/svg', 'path');
309
+ path.setAttribute('d', `M${x1},${y1} C${x1 + curveIntensity},${y1} ${x2 - curveIntensity},${y2} ${x2},${y2}`);
310
+ path.setAttribute('stroke', 'url(#gradient)');
311
+ path.setAttribute('stroke-width', '1');
312
+ path.setAttribute('fill', 'none');
313
+ path.setAttribute('stroke-dasharray', '5,5');
314
+
315
+ // Add animation
316
+ const animate = document.createElementNS('http://www.w3.org/2000/s极狐', 'animate');
317
+ animate.setAttribute('attributeName', 'stroke-dashoffset');
318
+ animate.setAttribute('from', '0');
319
+ animate.setAttribute('to', '10');
320
+ animate.setAttribute('dur', '1s');
321
+ animate.setAttribute('repeatCount', 'indefinite');
322
+
323
+ path.appendChild(animate);
324
+ svg.appendChild(path);
325
+ }
326
+ }
327
+ }
328
+ }
329
+
330
+ // Recreate connections on resize
331
+ window.addEventListener('resize', createNeuralConnections);
332
+ </script>
333
+ </body>
334
+ </html>
index.html CHANGED
@@ -1,19 +1,508 @@
1
- <!doctype html>
2
- <html>
3
- <head>
4
- <meta charset="utf-8" />
5
- <meta name="viewport" content="width=device-width" />
6
- <title>My static Space</title>
7
- <link rel="stylesheet" href="style.css" />
8
- </head>
9
- <body>
10
- <div class="card">
11
- <h1>Welcome to your static Space!</h1>
12
- <p>You can modify this app directly by editing <i>index.html</i> in the Files and versions tab.</p>
13
- <p>
14
- Also don't forget to check the
15
- <a href="https://huggingface.co/docs/hub/spaces" target="_blank">Spaces documentation</a>.
16
- </p>
17
- </div>
18
- </body>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
19
  </html>
 
1
+ <!DOCTYPE html>
2
+ <html lang="es">
3
+ <head>
4
+ <meta charset="UTF-8">
5
+ <meta name="viewport" content="width=device-width, initial-scale=1.0">
6
+ <title>Hiper Feature Pipeline - Dashboard</title>
7
+ <script src="https://cdn.tailwindcss.com"></script>
8
+ <link href="https://unpkg.com/[email protected]/dist/aos.css" rel="stylesheet">
9
+ <script src="https://unpkg.com/[email protected]/dist/aos.js"></script>
10
+ <script src="https://cdn.jsdelivr.net/npm/feather-icons/dist/feather.min.js"></script>
11
+ <script src="https://unpkg.com/feather-icons"></script>
12
+ <script src="https://cdn.jsdelivr.net/npm/vanta@latest/dist/vanta.net.min.js"></script>
13
+ <script src="https://cdnjs.cloudflare.com/ajax/libs/three.js/r128/three.min.js"></script>
14
+ <script src="https://cdn.jsdelivr.net/npm/[email protected]/particles.min.js"></script>
15
+ <style>
16
+ @import url('https://fonts.googleapis.com/css2?family=Orbitron:wght@400;500;600;700;800;900&family=Rajdhani:wght@300;400;500;600;700&display=swap');
17
+
18
+ body {
19
+ font-family: 'Rajdhani', sans-serif;
20
+ overflow-x: hidden;
21
+ }
22
+
23
+ .orbitron {
24
+ font-family: 'Orbitron', sans-serif;
25
+ }
26
+
27
+ .vanta-bg {
28
+ position: fixed;
29
+ width: 100%;
30
+ height: 100%;
31
+ z-index: -2;
32
+ }
33
+
34
+ #particles-js {
35
+ position: fixed;
36
+ width: 100%;
37
+ height: 100%;
38
+ z-index: -1;
39
+ }
40
+
41
+ .glass-effect {
42
+ background: linear-gradient(135deg, rgba(16, 23, 41, 0.7), rgba(10, 15, 30, 0.7));
43
+ backdrop-filter: blur(12px);
44
+ border: 1px solid rgba(66, 92, 255, 0.3);
45
+ box-shadow: 0 8px 32px rgba(0, 4, 255, 0.2);
46
+ border-radius: 16px;
47
+ transition: all 0.3s ease;
48
+ }
49
+
50
+ .glass-effect:hover {
51
+ transform: translateY(-5px);
52
+ box-shadow: 0 12px 40px rgba(66, 92, 255, 0.4);
53
+ border-color: rgba(66, 220, 255, 0.6);
54
+ }
55
+
56
+ .neural-connection {
57
+ position: absolute;
58
+ pointer-events: none;
59
+ z-index: -1;
60
+ }
61
+
62
+ .floating {
63
+ animation: float 6s ease-in-out infinite;
64
+ }
65
+
66
+ .floating-2 {
67
+ animation: float 7s ease-in-out infinite;
68
+ animation-delay: 1s;
69
+ }
70
+
71
+ .floating-3 {
72
+ animation: float 5s ease-in-out infinite;
73
+ animation-delay: 2s;
74
+ }
75
+
76
+ @keyframes float {
77
+ 0% { transform: translateY(0px); }
78
+ 50% { transform: translateY(-10px); }
79
+ 100% { transform: translateY(0px); }
80
+ }
81
+
82
+ .pulse-glow {
83
+ animation: pulse-glow 2s infinite;
84
+ }
85
+
86
+ @keyframes pulse-glow {
87
+ 0% { box-shadow: 0 0 5px rgba(66, 220, 255, 0.6); }
88
+ 50% { box-shadow: 0 0 20px rgba(66, 220, 255, 0.8), 0 0 30px rgba(66, 92, 255, 0.6); }
89
+ 100% { box-shadow: 0 0 5px rgba(66, 220, 255, 0.6); }
90
+ }
91
+
92
+ .gradient-text {
93
+ background: linear-gradient(90deg, #42dcff, #4260ff, #9042ff);
94
+ -webkit-background-clip: text;
95
+ -webkit-text-fill-color: transparent;
96
+ background-size: 200% auto;
97
+ animation: gradient-flow 3s linear infinite;
98
+ }
99
+
100
+ @keyframes gradient-flow {
101
+ 0% { background-position: 0% center; }
102
+ 100% { background-position: 200% center; }
103
+ }
104
+
105
+ .cyber-border {
106
+ position: relative;
107
+ border: 1px solid transparent;
108
+ background: linear-gradient(45deg, #42dcff, #4260ff, #9042ff) border-box;
109
+ -webkit-mask:
110
+ linear-gradient(#fff 0 0) padding-box,
111
+ linear-gradient(#fff 0 0);
112
+ -webkit-mask-composite: destination-out;
113
+ mask-composite: exclude;
114
+ }
115
+
116
+ .neuron {
117
+ position: absolute;
118
+ width: 8px;
119
+ height: 8px;
120
+ border-radius: 50%;
121
+ background: #42dcff;
122
+ box-shadow: 0 0 10px #42dcff, 0 0 20px #42dcff;
123
+ z-index: 1;
124
+ }
125
+
126
+ .neuron-pulse {
127
+ animation: neuron-pulse 2s infinite;
128
+ }
129
+
130
+ @keyframes neuron-pulse {
131
+ 0% { transform: scale(1); opacity: 1; }
132
+ 50% { transform: scale(1.5); opacity: 0.7; }
133
+ 100% { transform: scale(1); opacity: 1; }
134
+ }
135
+
136
+ .nav-glow {
137
+ box-shadow: 0 4px 30px rgba(66, 220, 255, 0.3);
138
+ border-bottom: 1px solid rgba(66, 220, 255, 0.2);
139
+ }
140
+
141
+ .data-stream {
142
+ position: relative;
143
+ overflow: hidden;
144
+ }
145
+
146
+ .data-stream::after {
147
+ content: '';
148
+ position: absolute;
149
+ top: 0;
150
+ left: -100%;
151
+ width: 100%;
152
+ height: 2px;
153
+ background: linear-gradient(90deg, transparent, #42dcff, transparent);
154
+ animation: data-stream 2s linear infinite;
155
+ }
156
+
157
+ @keyframes data-stream {
158
+ 0% { left: -100%; }
159
+ 100% { left: 100%; }
160
+ }
161
+ </style>
162
+ </head>
163
+ <body class="bg-gray-900 text-white min-h-screen">
164
+ <div id="vanta-bg" class="vanta-bg"></div>
165
+ <div id="particles-js"></div>
166
+
167
+ <!-- Neural Network Connections -->
168
+ <svg class="neural-connection" width="100%" height="100%" style="position: fixed; top: 0; left: 0; z-index: -1;">
169
+ <defs>
170
+ <linearGradient id="gradient" x1="0%" y1="0%" x2="100%" y2="100%">
171
+ <stop offset="0%" stop-color="#42dcff" />
172
+ <stop offset="50%" stop-color="#4260ff" />
173
+ <stop offset="100%" stop-color="#9042ff" />
174
+ </linearGradient>
175
+ </defs>
176
+ <!-- Lines will be dynamically added by JavaScript -->
177
+ </svg>
178
+
179
+ <!-- Floating Neurons -->
180
+ <div class="neuron neuron-pulse" style="top: 20%; left: 10%;"></div>
181
+ <div class="neuron neuron-pulse" style="top: 30%; left: 85%; animation-delay: 0.5s;"></div>
182
+ <div class="neuron neuron-pulse" style="top: 70%; left: 15%; animation-delay: 1s;"></div>
183
+ <div class="neuron neuron-pulse" style="top: 80%; left: 90%; animation-delay: 1.5s;"></div>
184
+ <div class="neuron neuron-pulse" style="top: 45%; left: 5%; animation-delay: 0.7s;"></div>
185
+ <div class="neuron neuron-pulse" style="top: 55%; left: 95%; animation-delay: 1.2s;"></div>
186
+
187
+ <!-- Navigation -->
188
+ <nav class="glass-effect fixed w-full z-50">
189
+ <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8">
190
+ <div class="flex justify-between h-16 items-center">
191
+ <div class="flex items-center">
192
+ <i data-feather="cpu" class="h-8 w-8 text-blue-400"></i>
193
+ <span class="ml-2 text-xl font-bold">Hiper Feature Pipeline</span>
194
+ </div>
195
+ <div class="hidden md:block">
196
+ <div class="ml-10 flex items-baseline space-x-4">
197
+ <a href="index.html" class="px-3 py-2 rounded-md text-sm font-medium bg-blue-700 text-white">Dashboard</a>
198
+ <a href="datasets.html" class="px-3 py-2 rounded-md text-sm font-medium hover:bg-blue-600">Datasets</a>
199
+ <a href="training.html" class="px-3 py-2 rounded-md text-sm font-medium hover:bg-blue-600">Training</a>
200
+ <a href="models.html" class="px-3 py-2 rounded-md text-sm font-medium hover:bg-blue-600">Models</a>
201
+ <a href="system-health.html" class="px-3 py-2 rounded-md text-sm font-medium hover:bg-blue-600">System Health</a>
202
+ </div>
203
+ </div>
204
+ </div>
205
+ </div>
206
+ </nav>
207
+
208
+ <!-- Main Content -->
209
+ <main class="pt-20 pb-16">
210
+ <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8">
211
+ <!-- Header -->
212
+ <div class="text-center py-12" data-aos="fade-down">
213
+ <h1 class="text-5xl font-bold mb-4 orbitron gradient-text">QUANTUM TRADING AI v6.0</h1>
214
+ <p class="text-xl text-[#42dcff] orbitron">ADVANCED FINANCIAL ML WITH EVENT SOURCING + CQRS ARCHITECTURE</p>
215
+ <div class="mt-4 data-stream"></div>
216
+ </div>
217
+
218
+ <!-- Stats Overview -->
219
+ <div class="grid grid-cols-1 md:grid-cols-2 lg:grid-cols-4 gap-6 mb-12">
220
+ <div class="glass-effect rounded-lg p-6" data-aos="fade-up" data-aos-delay="100">
221
+ <div class="flex items-center">
222
+ <div class="p-3 bg-blue-500 rounded-lg">
223
+ <i data-feather="database" class="h-6 w-6"></i>
224
+ </div>
225
+ <div class="ml-4">
226
+ <p class="text-sm font-medium text-gray-300">Datasets</p>
227
+ <p class="text-2xl font-bold">24</p>
228
+ </div>
229
+ </div>
230
+ </div>
231
+ <div class="glass-effect rounded-lg p-6" data-aos="fade-up" data-aos-delay="200">
232
+ <div class="flex items-center">
233
+ <div class="p-3 bg-green-500 rounded-lg">
234
+ <i data-feather="activity" class="h-6 w-6"></i>
235
+ </div>
236
+ <div class="ml-4">
237
+ <p class="text-sm font-medium text-gray-300">Training Sessions</p>
238
+ <p class="text-2xl font-bold">12</p>
239
+ </div>
240
+ </div>
241
+ </div>
242
+ <div class="glass-effect rounded-lg p-6" data-aos="fade-up" data-aos-delay="300">
243
+ <div class="flex items-center">
244
+ <div class="p-3 bg-purple-500 rounded-lg">
245
+ <i data-feather="box" class="h-6 w-6"></i>
246
+ </div>
247
+ <div class="ml-4">
248
+ <p class="text-sm font-medium text-gray-300">ONNX Models</p>
249
+ <p class="text-2xl font-bold">8</p>
250
+ </div>
251
+ </div>
252
+ </div>
253
+ <div class="glass-effect rounded-lg p-6" data-aos="fade-up" data-aos-delay="400">
254
+ <div class="flex items-center">
255
+ <div class="p-3 bg-yellow-500 rounded-lg">
256
+ <i data-feather="trending-up" class="h-6 w-6"></i>
257
+ </div>
258
+ <div class="ml-4">
259
+ <p class="text-sm font-medium text-gray-300">Avg Performance</p>
260
+ <p class="text-2xl font-bold">94.7%</p>
261
+ </div>
262
+ </div>
263
+ </div>
264
+ </div>
265
+
266
+ <!-- Recent Activity -->
267
+ <div class="glass-effect rounded-lg p-6 mb-12" data-aos="fade-up">
268
+ <h2 class="text-2xl font-bold mb-6">Actividad Reciente</h2>
269
+ <div class="space-y-4">
270
+ <div class="flex items-center justify-between p-4 bg-gray-800 rounded-lg">
271
+ <div class="flex items-center">
272
+ <div class="p-2 bg-blue-500 rounded-full">
273
+ <i data-feather="upload" class="h-4 w-4"></i>
274
+ </div>
275
+ <div class="ml-4">
276
+ <p class="font-medium">Nuevo dataset ingresado</p>
277
+ <p class="text-sm text-gray-400">SP500_2023.csv</p>
278
+ </div>
279
+ </div>
280
+ <span class="text-sm text-gray-400">Hace 2 minutos</span>
281
+ </div>
282
+ <div class="flex items-center justify-between p-4 bg-gray-800 rounded-lg">
283
+ <div class="flex items-center">
284
+ <div class="p-2 bg-green-500 rounded-full">
285
+ <i data-feather="play" class="h-4 w-4"></i>
286
+ </div>
287
+ <div class="ml-4">
288
+ <p class="font-medium">Entrenamiento iniciado</p>
289
+ <p class="text-sm text-gray-400">LSTM_Model_v2</p>
290
+ </div>
291
+ </div>
292
+ <span class="text-sm text-gray-400">Hace 15 minutos</span>
293
+ </div>
294
+ <div class="flex items-center justify-between p-4 bg-gray-800 rounded-lg">
295
+ <div class="flex items-center">
296
+ <div class="p-2 bg-purple-500 rounded-full">
297
+ <i data-feather="check-circle" class="h-4 w-4"></i>
298
+ </div>
299
+ <div class="ml-4">
300
+ <p class="font-medium">Modelo exportado a ONNX</p>
301
+ <p class="text-sm text-gray-400">Transformer_Financial</p>
302
+ </div>
303
+ </div>
304
+ <span class="text-sm text-gray-400">Hace 1 hora</span>
305
+ </div>
306
+ </div>
307
+ </div>
308
+
309
+ <!-- System Status -->
310
+ <div class="grid grid-cols-1 lg:grid-cols-2 gap-6">
311
+ <div class="glass-effect rounded-lg p-6" data-aos="fade-right">
312
+ <h2 class="text-2xl font-bold mb-6">Estado del Sistema</h2>
313
+ <div class="space-y-4">
314
+ <div class="flex justify-between items-center">
315
+ <span>Event Store</span>
316
+ <span class="px-3 py-1 bg-green-500 rounded-full text-xs">Online</span>
317
+ </div>
318
+ <div class="flex justify-between items-center">
319
+ <span>Read Models</span>
320
+ <span class="px-3 py-1 bg-green-500 rounded-full text-xs">Online</span>
321
+ </div>
322
+ <div class="flex justify-between items-center">
323
+ <span>Feature Engineering</span>
324
+ <span class="px-3 py-1 bg-green-500 rounded-full text-xs">Online</span>
325
+ </div>
326
+ <div class="flex justify-between items-center">
327
+ <span>Model Training</span>
328
+ <span class="px-3 py-1 bg-yellow-500 rounded-full text-xs">Warning</span>
329
+ </div>
330
+ </div>
331
+ </div>
332
+ <div class="glass-effect rounded-lg p-6" data-aos="fade-left">
333
+ <h2 class="text-2xl font-bold mb-6">Rendimiento</h2>
334
+ <div class="space-y-4">
335
+ <div>
336
+ <div class="flex justify-between mb-1">
337
+ <span>CPU Usage</span>
338
+ <span>65%</span>
339
+ </div>
340
+ <div class="w-full bg-gray-700 rounded-full h-2">
341
+ <div class="bg-blue-500 h-2 rounded-full" style="width: 65%"></div>
342
+ </div>
343
+ </div>
344
+ <div>
345
+ <div class="flex justify-between mb-1">
346
+ <span>Memory</span>
347
+ <span>78%</span>
348
+ </div>
349
+ <div class="w-full bg-gray-700 rounded-full h-2">
350
+ <div class="bg-green-500 h-2 rounded-full" style="width: 78%"></div>
351
+ </div>
352
+ </div>
353
+ <div>
354
+ <div class="flex justify-between mb-1">
355
+ <span>Storage</span>
356
+ <span>45%</span>
357
+ </div>
358
+ <div class="w-full bg-gray-700 rounded-full h-2">
359
+ <div class="bg-purple-500 h-2 rounded-full" style="width: 45%"></div>
360
+ </div>
361
+ </div>
362
+ </div>
363
+ </div>
364
+ </div>
365
+ </div>
366
+ </main>
367
+
368
+ <!-- Footer -->
369
+ <footer class="glass-effect nav-glow mt-12 py-6">
370
+ <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 text-center">
371
+ <p class="text-[#42dcff] orbitron">QUANTUM TRADING AI v6.0 - ADVANCED FINANCIAL MACHINE LEARNING SYSTEM</p>
372
+ </div>
373
+ </footer>
374
+
375
+ <script>
376
+ // Initialize Vanta.js NET background
377
+ VANTA.NET({
378
+ el: "#vanta-bg",
379
+ mouseControls: true,
380
+ touchControls: true,
381
+ gyroControls: false,
382
+ minHeight: 200.00,
383
+ minWidth: 200.00,
384
+ scale: 1.00,
385
+ scaleMobile: 1.00,
386
+ color: 0x4260ff,
387
+ backgroundColor: 0x10172a,
388
+ points: 15.00,
389
+ maxDistance: 25.00,
390
+ spacing: 18.00
391
+ });
392
+
393
+ // Initialize particles.js
394
+ particlesJS('particles-js', {
395
+ particles: {
396
+ number: { value: 80, density: { enable: true, value_area: 800 } },
397
+ color: { value: "#42dcff" },
398
+ shape: {
399
+ type: "circle",
400
+ stroke: { width: 0, color: "#000000" },
401
+ polygon: { nb_sides: 5 }
402
+ },
403
+ opacity: {
404
+ value: 0.5,
405
+ random: true,
406
+ anim: { enable: true, speed: 1, opacity_min: 0.1, sync: false }
407
+ },
408
+ size: {
409
+ value: 3,
410
+ random: true,
411
+ anim: { enable: true, speed: 2, size_min: 0.1, sync: false }
412
+ },
413
+ line_linked: {
414
+ enable: true,
415
+ distance: 150,
416
+ color: "#4260ff",
417
+ opacity: 0.4,
418
+ width: 1
419
+ },
420
+ move: {
421
+ enable: true,
422
+ speed: 2,
423
+ direction: "none",
424
+ random: true,
425
+ straight: false,
426
+ out_mode: "out",
427
+ bounce: false,
428
+ attract: { enable: false, rotateX: 600, rotateY: 1200 }
429
+ }
430
+ },
431
+ interactivity: {
432
+ detect_on: "canvas",
433
+ events: {
434
+ onhover: { enable: true, mode: "grab" },
435
+ onclick: { enable: true, mode: "push" },
436
+ resize: true
437
+ },
438
+ modes: {
439
+ grab: { distance: 140, line_linked: { opacity: 1 } },
440
+ push: { particles_nb: 4 }
441
+ }
442
+ },
443
+ retina_detect: true
444
+ });
445
+
446
+ // Initialize AOS
447
+ AOS.init({
448
+ duration: 800,
449
+ easing: 'ease-in-out',
450
+ once: true
451
+ });
452
+
453
+ // Initialize Feather Icons
454
+ feather.replace();
455
+
456
+ // Create neural network connections
457
+ document.addEventListener('DOMContentLoaded', function() {
458
+ createNeuralConnections();
459
+ });
460
+
461
+ function createNeuralConnections() {
462
+ const svg = document.querySelector('.neural-connection');
463
+ const containers = document.querySelectorAll('.glass-effect');
464
+
465
+ // Clear existing connections
466
+ svg.innerHTML = '<defs><linearGradient id="gradient" x1="0%" y1="0%" x2="100%" y2="100%"><stop offset="0%" stop-color="#42dcff" /><stop offset="50%" stop-color="#4260ff" /><stop offset="100%" stop-color="#9042ff" /></linearGradient></defs>';
467
+
468
+ // Create connections between elements
469
+ for (let i = 0; i < containers.length - 1; i++) {
470
+ for (let j = i + 1; j < containers.length; j++) {
471
+ if (Math.random() > 0.7) { // Only connect some elements
472
+ const rect1 = containers[i].getBoundingClientRect();
473
+ const rect2 = containers[j].getBoundingClientRect();
474
+
475
+ const x1 = rect1.left + rect1.width / 2;
476
+ const y1 = rect1.top + rect1.height / 2;
477
+ const x2 = rect2.left + rect2.width / 2;
478
+ const y2 = rect2.top + rect2.height / 2;
479
+
480
+ // Create a curved line
481
+ const curveIntensity = 50 * (Math.random() - 0.5);
482
+ const path = document.createElementNS('http://www.w3.org/2000/svg', 'path');
483
+ path.setAttribute('d', `M${x1},${y1} C${x1 + curveIntensity},${y1} ${x2 - curveIntensity},${y2} ${x2},${y2}`);
484
+ path.setAttribute('stroke', 'url(#gradient)');
485
+ path.setAttribute('stroke-width', '1');
486
+ path.setAttribute('fill', 'none');
487
+ path.setAttribute('stroke-dasharray', '5,5');
488
+
489
+ // Add animation
490
+ const animate = document.createElementNS('http://www.w3.org/2000/svg', 'animate');
491
+ animate.setAttribute('attributeName', 'stroke-dashoffset');
492
+ animate.setAttribute('from', '0');
493
+ animate.setAttribute('to', '10');
494
+ animate.setAttribute('dur', '1s');
495
+ animate.setAttribute('repeatCount', 'indefinite');
496
+
497
+ path.appendChild(animate);
498
+ svg.appendChild(path);
499
+ }
500
+ }
501
+ }
502
+ }
503
+
504
+ // Recreate connections on resize
505
+ window.addEventListener('resize', createNeuralConnections);
506
+ </script>
507
+ </body>
508
  </html>
models.html ADDED
@@ -0,0 +1,257 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ <!DOCTYPE html>
2
+ <html lang="es">
3
+ <head>
4
+ <meta charset="UTF-8">
5
+ <meta name="viewport" content="width=device-width, initial-scale=1.0">
6
+ <title>Hiper Feature Pipeline - Model Management</title>
7
+ <script src="https://cdn.tailwindcss.com"></script>
8
+ <link href="https://unpkg.com/[email protected]/dist/aos.css" rel="stylesheet">
9
+ <script src="https://unpkg.com/[email protected]/dist/aos.js"></script>
10
+ <script src="https://cdn.jsdelivr.net/npm/feather-icons/dist/feather.min.js"></script>
11
+ <script src="https://unpkg.com/feather-icons"></script>
12
+ <style>
13
+ .glass-effect {
14
+ background: rgba(255, 255, 255, 0.1);
15
+ backdrop-filter: blur(10px);
16
+ border: 1px solid rgba(255, 255, 255, 0.2);
17
+ }
18
+ </style>
19
+ </head>
20
+ <body class="bg-gray-900 text-white min-h-screen">
21
+ <!-- Navigation -->
22
+ <nav class="glass-effect fixed w-full z-50">
23
+ <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8">
24
+ <div class="flex justify-between h-16 items-center">
25
+ <div class="flex items-center">
26
+ <i data-feather="cpu" class="h-8 w-8 text-blue-400"></i>
27
+ <span class="ml-2 text-xl font-bold">Hiper Feature Pipeline</span>
28
+ </div>
29
+ <div class="hidden md:block">
30
+ <div class="ml-10 flex items-baseline space-x-4">
31
+ <a href="index.html" class="px-3 py-2 rounded-md text-sm font-medium hover:bg-blue-600">Dashboard</a>
32
+ <a href="datasets.html" class="px-3 py-2 rounded-md text-sm font-medium hover:bg-blue-600">Datasets</a>
33
+ <a href="training.html" class="px-3 py-2 rounded-md text-sm font-medium hover:bg-blue-600">Training</a>
34
+ <a href="models.html" class="px-3 py-2 rounded-md text-sm font-medium bg-blue-700 text-white">Models</a>
35
+ <a href="system-health.html" class="px-3 py-2 rounded-md text-sm font-medium hover:bg-blue-600">System Health</a>
36
+ </div>
37
+ </div>
38
+ </div>
39
+ </div>
40
+ </nav>
41
+
42
+ <!-- Main Content -->
43
+ <main class="pt-20 pb-16">
44
+ <div class="极狐-7xl mx-auto px-4 sm:px-6 lg:px-8">
45
+ <!-- Header -->
46
+ <div class="text-center py-12" data-aos="fade-down">
47
+ <h1 class="text-4xl font-bold mb-4">Model Management</h1>
48
+ <p class="text-xl text-gray-300">Gestión y despliegue de modelos ONNX optimizados</p>
49
+ </div>
50
+
51
+ <!-- Model Cards Grid -->
52
+ <div class="grid grid-cols-1 md:grid-cols-2 lg:grid-cols-3 gap-6 mb-12">
53
+ <!-- Model Card 1 -->
54
+ <div class="glass-effect rounded-lg p-6" data-aos="fade-up" data-aos-delay="100">
55
+ <div class="flex justify-between items-start mb-4">
56
+ <div>
57
+ <h3 class="font-bold text-lg">LSTM_SP500_v2</h3>
58
+ <p class="text-sm text-gray-400">Financial Prediction</p>
59
+ </div>
60
+ <span class="px-2 py-1 bg-green-500 rounded-full text-xs">Deployed</span>
61
+ </div>
62
+ <div class="space-y-2 text-sm mb-4">
63
+ <div class="flex justify-between">
64
+ <span class="text-gray-400">Accuracy:</span>
65
+ <span>96.7%</span>
66
+ </div>
67
+ <div class="flex justify-between">
68
+ <span class="text-gray-400">Inference Time:</span>
69
+ <span>23ms</span>
70
+ </div>
71
+ <div class="flex justify-between">
72
+ <span class="text-gray-400">Size:</span>
73
+ <span>45.2 MB</span>
74
+ </div>
75
+ </div>
76
+ <div class="flex space-x-2">
77
+ <button class="flex-1 py-2 bg-blue-600 hover:bg-blue-700 rounded-lg text-sm">Details</button>
78
+ <button class="flex-1 py-2 bg-green-600 hover:bg-green-700 rounded-lg text-sm">Download</button>
79
+ </div>
80
+ </div>
81
+
82
+ <!-- Model Card 2 -->
83
+ <div class="glass-effect rounded-lg p-6" data-aos="fade-up" data-aos-delay="200">
84
+ <div class="flex justify-between items-start mb-4">
85
+ <div>
86
+ <h3 class="font-bold text-lg">Transformer_NASDAQ</h3>
87
+ <p class="text-sm text-gray-400">Market Analysis</p>
88
+ </div>
89
+ <span class="px-2 py-1 bg-yellow-500 rounded-full text-xs">Optimizing</span>
90
+ </div>
91
+ <div class="space-y-2 text-sm mb-4">
92
+ <div class="flex justify-between">
93
+ <span class="text-gray-400">Accuracy:</span>
94
+ <span>94.2%</span>
95
+ </div>
96
+ <div class="flex justify-between">
97
+ <span class="text-gray-400">Inference Time:</span>
98
+ <span>67ms</span>
99
+ </div>
100
+ <div class="flex justify-between">
101
+ <span class="text-gray-400">Size:</span>
102
+ <span>128.5 MB</span>
103
+ </div>
104
+ </div>
105
+ <div class="flex space-x-2">
106
+ <button class="flex-1 py-2 bg-blue-600 hover:bg-blue-700 rounded-lg text-sm">Details</button>
107
+ <button class="flex-1 py-2 bg-gray-700 hover:bg-gray-600 rounded-lg text-sm" disabled>Download</button>
108
+ </div>
109
+ </div>
110
+
111
+ <!-- Model Card 3 -->
112
+ <div class="glass-effect rounded-lg p-6" data-aos="fade-up" data-aos-delay="300">
113
+ <div class="flex justify-between items-start mb-4">
114
+ <div>
115
+ <h3 class="font-bold text-lg">TCN_Forex_Pro</h3>
116
+ <p class="text-sm text-gray-400">Currency Prediction</p>
117
+ </div>
118
+ <span class="px-2 py-1 bg-green-500 rounded-full text-xs">Deployed</span>
119
+ </div>
120
+ <div class="space-y-2 text-sm mb-4">
121
+ <div class="flex justify-between">
122
+ <span class="text-gray-400">Accuracy:</span>
123
+ <span>92.8%</span>
124
+ </div>
125
+ <div class="极狐-justify-between">
126
+ <span class="text-gray-400">Inference Time:</span>
127
+ <span>18ms</span>
128
+ </div>
129
+ <div class="flex justify-between">
130
+ <span class="text-gray-400">Size:</span>
131
+ <span>32.7 MB</span>
132
+ </div>
133
+ </div>
134
+ <div class="flex space-x-2">
135
+ <button class="flex-1 py-2 bg-blue-600 hover:bg-blue-700 rounded-lg text-sm">Details</button>
136
+ <button class="flex-1 py-2 bg-green-600 hover:bg-green-700 rounded-lg text-sm">Download</button>
137
+ </div>
138
+ </div>
139
+ </div>
140
+
141
+ <!-- Model Performance -->
142
+ <div class="glass-effect rounded-lg p-6 mb-12" data-aos="fade-up">
143
+ <h2 class="text-2xl font-bold mb-6">Model Performance Metrics</h2>
144
+ <div class="grid grid-cols-1 md:grid-cols-2 gap-6">
145
+ <div>
146
+ <h3 class="font-bold mb-4">Accuracy Comparison</h3>
147
+ <div class="space-y-3">
148
+ <div>
149
+ <div class="flex justify-between mb-1">
150
+ <span>LSTM_SP500_v2</span>
151
+ <span>96.7%</span>
152
+ </div>
153
+ <div class="w-full bg-gray-700 rounded-full h-2">
154
+ <div class="bg-green-500 h-2 rounded-full" style="width: 96.7%"></div>
155
+ </div>
156
+ </div>
157
+ <div>
158
+ <div class="flex justify-between mb-1">
159
+ <span>Transformer_NASDAQ</span>
160
+ <span>94.2%</span>
161
+ </div>
162
+ <极狐 class="w-full bg-gray-700 rounded-full h-2">
163
+ <div class="bg-blue-500 h-2 rounded-full" style="width: 94.2%"></div>
164
+ </div>
165
+ </div>
166
+ <div>
167
+ <div class="flex justify-between mb-1">
168
+ <span>TCN_Forex_Pro</span>
169
+ <span>92.8%</span>
170
+ </div>
171
+ <div class="w-full bg-gray-700 rounded-full h-2">
172
+ <div class="bg-purple-500 h-2 rounded-full" style="width: 92.8%"></div>
173
+ </div>
174
+ </div>
175
+ </div>
176
+ </div>
177
+ <div>
178
+ <h3 class="font-bold mb-4">Inference Speed (ms)</h3>
179
+ <div class="space-y-3">
180
+ <div>
181
+ <div class="flex justify-between mb-1">
182
+ <span>LSTM_SP500_v2</span>
183
+ <span>23ms</span>
184
+ </div>
185
+ <div class="w-full bg-gray-700 rounded-full h-2">
186
+ <div class="bg-green-500 h-2 rounded-full" style="width: 70%"></div>
187
+ </div>
188
+ </div>
189
+ <div>
190
+ <div class="flex justify-between mb-1">
191
+ <span>Transformer_NASDAQ</span>
192
+ <span>67ms</span>
193
+ </div>
194
+ <div class="w-full bg-gray-700 rounded-full h-2">
195
+ <div class="bg-blue-500 h-2 rounded-full" style="width: 40%"></div>
196
+ </div>
197
+ </div>
198
+ <div>
199
+ <div class="flex justify-between mb-1">
200
+ <span>TCN_Forex_Pro</span>
201
+ <span>18ms</span>
202
+ </div>
203
+ <div class="w-full bg-gray-700 rounded-full h-2">
204
+ <div class="bg-purple-500 h-2 rounded-full" style="width: 85%"></div>
205
+ </div>
206
+ </div>
207
+ </div>
208
+ </div>
209
+ </div>
210
+ </div>
211
+
212
+ <!-- ONNX Export -->
213
+ <div class="glass-effect rounded-lg p-6" data-aos="fade-up">
214
+ <h2 class="text-2xl font-bold mb-6">Export to ONNX</h2>
215
+ <div class="grid grid-cols-1 md:grid-cols-2 gap-6 mb-6">
216
+ <div>
217
+ <label class="block text-sm font-medium mb-2">Select Model</label>
218
+ <select class="w-full bg-gray-800 border border-gray-700 rounded-lg p-3">
219
+ <option>LSTM_SP500_v2</option>
220
+ <option>Transformer_NASDAQ</option>
221
+ <option>TCN_Forex_Pro</option>
222
+ </select>
223
+ </div>
224
+ <div>
225
+ <label class="block text-sm font-medium mb-2">Optimization Level</label>
226
+ <select class="w-full bg-gray-800 border border-gray-700 rounded-lg p-3">
227
+ <option>Basic</option>
228
+ <option>Advanced</option>
229
+ <option>Maximum</option>
230
+ </select>
231
+ </div>
232
+ </div>
233
+ <button class="w-full py-3 bg-green-600 hover:bg-green-700 rounded-lg font-medium">Export to ONNX</button>
234
+ </div>
235
+ </div>
236
+ </main>
237
+
238
+ <!-- Footer -->
239
+ <footer class="glass-effect mt-12 py-6">
240
+ <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 text-center">
241
+ <p class="text-gray-400">Hiper Feature Pipeline Store v6.0 - Model Management</p>
242
+ </div>
243
+ </footer>
244
+
245
+ <script>
246
+ // Initialize AOS
247
+ AOS.init({
248
+ duration: 800,
249
+ easing: 'ease-in-out',
250
+ once: true
251
+ });
252
+
253
+ // Initialize Feather Icons
254
+ feather.replace();
255
+ </script>
256
+ </body>
257
+ </html>
prompts.txt ADDED
@@ -0,0 +1,1390 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ Desarrolla el siguiente frontend en varias paginas multiples:
2
+ # Respuesta Parte 1/4: Refactorización del Plan Hiper Feature Pipeline Store v6.0
3
+
4
+ ## Implementación de Arquitectura Event Sourcing + CQRS + Screaming Architecture
5
+
6
+ He aplicado los 5 prompts técnicos para refactorizar completamente el plan, implementando la arquitectura especificada con máxima precisión y sin ambigüedades.
7
+
8
+ ### 1. Visión General Refactorizada
9
+
10
+ El Hiper Feature Pipeline Store v6.0 se redefine como un sistema de machine learning financiero basado en **Event Sourcing + CQRS + Screaming Architecture**, con separación clara entre componentes de escritura (comandos) y lectura (consultas). Todos los cambios de estado se capturan como eventos inmutables, proporcionando trazabilidad completa y capacidad de reprocesamiento.
11
+
12
+ ### 2. Arquitectura del Sistema Refactorizada
13
+
14
+ #### 2.1 Arquitectura de Alto Nivel con Event Sourcing
15
+
16
+ ```mermaid
17
+ graph TD
18
+ A[Dashboard UI - Leptos] --> B[API Gateway - Axum]
19
+ B --> C[Command Side - Write Model]
20
+ B --> D[Query Side - Read Model]
21
+
22
+ C --> E[Command Handlers]
23
+ E --> F[Event Store - SurrealDB]
24
+ F --> G[Event Processors]
25
+ G --> H[Read Model - DuckDB]
26
+ G --> I[Embeddings Store - LanceDB]
27
+
28
+ D --> H
29
+ D --> I
30
+
31
+ J[Training Orchestrator] --> K[Training Command Handler]
32
+ K --> F
33
+ L[Event Processor] --> M[Feature Engineering]
34
+ M --> N[Model Training]
35
+ N --> O[ONNX Export]
36
+ ```
37
+
38
+ #### 2.2 Nueva Estructura de Componentes
39
+
40
+ 1. **Command Side** - Procesamiento de escritura:
41
+
42
+ - Command Handlers
43
+ - Event Store (SurrealDB)
44
+ - Aggregate Roots
45
+
46
+ 2. **Query Side** - Procesamiento de lectura:
47
+
48
+ - Query Handlers
49
+ - Read Model (DuckDB)
50
+ - Embeddings Store (LanceDB)
51
+
52
+ 3. **Event Processors** - Proyecciones y procesos de fondo:
53
+
54
+ - Feature Engineering Pipeline
55
+ - Model Training Orchestrator
56
+ - ONNX Conversion Service
57
+
58
+ ### 3. Estructura de Carpetas y Archivos (Sin "Domain")
59
+
60
+ ```
61
+ hiper-feature-pipeline/
62
+ ├── Cargo.toml
63
+ ├── Cargo.lock
64
+ ├── README.md
65
+ ├── architecture-decisions/
66
+ │ ├── event-sourcing-decision.md
67
+ │ ├── cqrs-implementation.md
68
+ │ └── screaming-architecture.md
69
+ ├── src/
70
+ │ ├── main.rs
71
+ │ ├── lib.rs
72
+ │ ├── command_side/
73
+ │ │ ├── mod.rs
74
+ │ │ ├── commands/
75
+ │ │ │ ├── mod.rs
76
+ │ │ │ ├── ingest_dataset_command.rs
77
+ │ │ │ ├── start_training_command.rs
78
+ │ │ │ └── export_onnx_command.rs
79
+ │ │ ├── command_handlers/
80
+ │ │ │ ├── mod.rs
81
+ │ │ │ ├── dataset_command_handler.rs
82
+ │ │ │ ├── training_command_handler.rs
83
+ │ │ │ └── onnx_command_handler.rs
84
+ │ │ └── aggregates/
85
+ │ │ ├── mod.rs
86
+ │ │ ├── dataset_aggregate.rs
87
+ │ │ ├── training_session_aggregate.rs
88
+ │ │ └── model_aggregate.rs
89
+ │ ├── query_side/
90
+ │ │ ├── mod.rs
91
+ │ │ ├── queries/
92
+ │ │ │ ├── mod.rs
93
+ │ │ │ ├── get_dataset_query.rs
94
+ │ │ │ ├── get_training_status_query.rs
95
+ │ │ │ └── get_model_performance_query.rs
96
+ │ │ ├── query_handlers/
97
+ │ │ │ ├── mod.rs
98
+ │ │ │ ├── dataset_query_handler.rs
99
+ │ │ │ ├── training_query_handler.rs
100
+ │ │ │ └── model_query_handler.rs
101
+ │ │ └── read_models/
102
+ │ │ ├── mod.rs
103
+ │ │ ├── dataset_read_model.rs
104
+ │ │ ├── training_read_model.rs
105
+ │ │ └── model_read_model.rs
106
+ │ ├── event_sourcing/
107
+ │ │ ├── mod.rs
108
+ │ │ ├── event_store/
109
+ │ │ │ ├── mod.rs
110
+ │ │ │ ├── surreal_event_store.rs
111
+ │ │ │ └── event_store_trait.rs
112
+ │ │ ├── events/
113
+ │ │ │ ├── mod.rs
114
+ │ │ │ ├── dataset_events.rs
115
+ │ │ │ ├── training_events.rs
116
+ │ │ │ └── model_events.rs
117
+ │ │ └── event_handlers/
118
+ │ │ ├── mod.rs
119
+ │ │ ├── dataset_event_handler.rs
120
+ │ │ ├── training_event_handler.rs
121
+ │ │ └── model_event_handler.rs
122
+ │ ├── feature_engineering/
123
+ │ │ ├── mod.rs
124
+ │ │ ├── technical_indicators/
125
+ │ │ │ ├── mod.rs
126
+ │ │ │ ├── sma_calculator.rs
127
+ │ │ │ ├── rsi_calculator.rs
128
+ │ │ │ └── macd_calculator.rs
129
+ │ │ ├── event_processors/
130
+ │ │ │ ├── mod.rs
131
+ │ │ │ ├── feature_engineering_processor.rs
132
+ │ │ │ └── feature_cache_processor.rs
133
+ │ │ └── feature_store/
134
+ │ │ ├── mod.rs
135
+ │ │ ├── duckdb_feature_store.rs
136
+ │ │ └── feature_store_trait.rs
137
+ │ ├── model_training/
138
+ │ │ ├── mod.rs
139
+ │ │ ├── neural_architectures/
140
+ │ │ │ ├── mod.rs
141
+ │ │ │ ├── lstm_architecture.rs
142
+ │ │ │ ├── transformer_architecture.rs
143
+ │ │ │ └── temporal_convolution_architecture.rs
144
+ │ │ ├── training_orchestrator/
145
+ │ │ │ ├── mod.rs
146
+ │ │ │ ├── training_scheduler.rs
147
+ │ │ │ ├── hyperparameter_optimizer.rs
148
+ │ │ │ └── cross_validation_manager.rs
149
+ │ │ ├── event_processors/
150
+ │ │ │ ├── mod.rs
151
+ │ │ │ ├── training_processor.rs
152
+ │ │ │ └── model_evaluation_processor.rs
153
+ │ │ └── model_store/
154
+ │ │ ├── mod.rs
155
+ │ │ ├── model_repository.rs
156
+ │ │ └── model_serializer.rs
157
+ │ ├── onnx_conversion/
158
+ │ │ ├── mod.rs
159
+ │ │ ├── onnx_exporter/
160
+ │ │ │ ├── mod.rs
161
+ │ │ │ ├── candle_to_onnx.rs
162
+ │ │ │ └── pytorch_to_onnx.rs
163
+ │ │ ├── optimization/
164
+ │ │ │ ├── mod.rs
165
+ │ │ │ ├── quantizer.rs
166
+ │ │ │ ├── operator_fuser.rs
167
+ │ │ │ └── graph_optimizer.rs
168
+ │ │ └── event_processors/
169
+ │ │ ├── mod.rs
170
+ │ │ └── onnx_conversion_processor.rs
171
+ │ ├── api/
172
+ │ │ ├── mod.rs
173
+ │ │ ├── axum_server.rs
174
+ │ │ ├── command_controllers/
175
+ │ │ │ ├── mod.rs
176
+ │ │ │ ├── dataset_controller.rs
177
+ │ │ │ ├── training_controller.rs
178
+ │ │ │ └── onnx_controller.rs
179
+ │ │ ├── query_controllers/
180
+ │ │ │ ├── mod.rs
181
+ │ │ │ ├── dataset_query_controller.rs
182
+ │ │ │ ├── training_query_controller.rs
183
+ │ │ │ └── model_query_controller.rs
184
+ │ │ └── middleware/
185
+ │ │ ├── mod.rs
186
+ │ │ ├── authentication.rs
187
+ │ │ ├── authorization.rs
188
+ │ │ └── logging.rs
189
+ │ ├── ui/
190
+ │ │ ├── mod.rs
191
+ │ │ ├── leptos_app/
192
+ │ │ │ ├── mod.rs
193
+ │ │ │ ├── app.rs
194
+ │ │ │ ├── components/
195
+ │ │ │ │ ├── mod.rs
196
+ │ │ │ │ ├── dataset_components/
197
+ │ │ │ │ ├── training_components/
198
+ │ │ │ │ └── model_components/
199
+ │ │ │ └── pages/
200
+ │ │ │ ├── mod.rs
201
+ │ │ │ ├── dashboard_page.rs
202
+ │ │ │ ├── dataset_explorer_page.rs
203
+ │ │ │ └── training_monitor_page.rs
204
+ │ │ └── state_management/
205
+ │ │ ├── mod.rs
206
+ │ │ ├── command_state.rs
207
+ │ │ ├── query_state.rs
208
+ │ │ └── ui_state.rs
209
+ │ ├── monitoring/
210
+ │ │ ├── mod.rs
211
+ │ │ ├── metrics/
212
+ │ │ │ ├── mod.rs
213
+ │ │ │ ├── command_metrics.rs
214
+ │ │ │ ├── query_metrics.rs
215
+ │ │ │ └── training_metrics.rs
216
+ │ │ ├── logging/
217
+ │ │ │ ├── mod.rs
218
+ │ │ │ ├── structured_logger.rs
219
+ │ │ │ └── event_logger.rs
220
+ │ │ └── health_check/
221
+ │ │ ├── mod.rs
222
+ │ │ ├── liveness_check.rs
223
+ │ │ ├── readiness_check.rs
224
+ │ │ └── health_endpoint.rs
225
+ │ └── common/
226
+ │ ├── mod.rs
227
+ │ ├── error_handling/
228
+ │ │ ├── mod.rs
229
+ │ │ ├── application_errors.rs
230
+ │ │ ├── domain_errors.rs
231
+ │ │ └── infrastructure_errors.rs
232
+ │ ├── types/
233
+ │ │ ├── mod.rs
234
+ │ │ ├── dataset_types.rs
235
+ │ │ ├── training_types.rs
236
+ │ │ └── model_types.rs
237
+ │ └── utilities/
238
+ │ ├── mod.rs
239
+ │ ├── datetime_utils.rs
240
+ │ ├── serialization_utils.rs
241
+ │ └── validation_utils.rs
242
+ ├── config/
243
+ │ ├── default.toml
244
+ │ ├── development.toml
245
+ │ ├── production.toml
246
+ │ └── tests.toml
247
+ ├── migrations/
248
+ │ ├── event_store/
249
+ │ │ ├── 001_initial_events_table.surql
250
+ │ │ └── 002_add_metadata_indexes.surql
251
+ │ ├── read_model/
252
+ │ │ ├── 001_create_dataset_tables.duckdb.sql
253
+ │ │ └── 002_create_training_tables.duckdb.sql
254
+ │ └── embeddings/
255
+ │ ├── 001_create_embeddings_table.lance.sql
256
+ │ └── 002_add_embedding_indexes.lance.sql
257
+ ├── tests/
258
+ │ ├── command_side_tests/
259
+ │ ├── query_side_tests/
260
+ │ ├── event_sourcing_tests/
261
+ │ ├── integration_tests/
262
+ │ └── load_tests/
263
+ └── docker/
264
+ ├── Dockerfile
265
+ ├── docker-compose.yml
266
+ └── entrypoint.sh
267
+ ```
268
+
269
+ ### 4. Fases de Implementación Refactorizadas
270
+
271
+ #### 4.1 Fase 0: Integración de Datasets con Event Sourcing
272
+
273
+ **Cambios principales:**
274
+
275
+ - Todos los datasets se ingieren mediante comandos que generan eventos
276
+ - Validación y procesamiento se convierten en proyecciones de eventos
277
+ - Estado actual se reconstruye desde el event store
278
+
279
+ **Nuevos componentes implementados:**
280
+
281
+ - `IngestDatasetCommand` y `DatasetIngestedEvent`
282
+ - `DatasetAggregate` para gestionar el estado consistente
283
+ - Proyecciones para crear read models optimizados en DuckDB
284
+
285
+ **Estructura específica para esta fase:**
286
+
287
+ ```
288
+ src/command_side/commands/ingest_dataset_command.rs
289
+ src/command_side/aggregates/dataset_aggregate.rs
290
+ src/event_sourcing/events/dataset_events.rs
291
+ src/event_sourcing/event_handlers/dataset_event_handler.rs
292
+ src/query_side/read_models/dataset_read_model.rs
293
+ ```
294
+
295
+ # Respuesta Parte 2/4: Refactorización del Plan Hiper Feature Pipeline Store v6.0
296
+
297
+ ## Continuación de las Fases de Implementación Refactorizadas
298
+
299
+ ### 4.2 Fase 1: Implementación de la Capa de Datos con Event Sourcing y CQRS
300
+
301
+ **Cambios principales:**
302
+
303
+ - La capa de datos se divide en Command Side (Event Store) y Query Side (Read Models)
304
+ - SurrealDB se utiliza como Event Store para persistir eventos inmutables
305
+ - DuckDB se utiliza para Read Models optimizados para consultas
306
+ - LanceDB se utiliza para almacenamiento de incrustaciones vectoriales como proyecciones de eventos
307
+
308
+ **Nuevos componentes implementados:**
309
+
310
+ #### Command Side - Event Store:
311
+
312
+ ```
313
+ src/event_sourcing/event_store/surreal_event_store.rs
314
+ src/event_sourcing/event_store/event_store_trait.rs
315
+ src/event_sourcing/events/data_layer_events.rs
316
+ ```
317
+
318
+ #### Query Side - Read Models:
319
+
320
+ ```
321
+ src/query_side/read_models/data_read_model.rs
322
+ src/feature_engineering/feature_store/duckdb_feature_store.rs
323
+ src/feature_engineering/feature_store/feature_store_trait.rs
324
+ ```
325
+
326
+ #### Event Processors para proyecciones:
327
+
328
+ ```
329
+ src/event_sourcing/event_handlers/data_event_handler.rs
330
+ src/feature_engineering/event_processors/feature_engineering_processor.rs
331
+ src/feature_engineering/event_processors/feature_cache_processor.rs
332
+ ```
333
+
334
+ **Estructura detallada de archivos para esta fase:**
335
+
336
+ ```
337
+ src/command_side/commands/
338
+ ├── configure_database_command.rs
339
+ ├── update_data_pipeline_command.rs
340
+ └── validate_data_quality_command.rs
341
+
342
+ src/command_side/command_handlers/
343
+ ├── data_command_handler.rs
344
+ └── validation_command_handler.rs
345
+
346
+ src/command_side/aggregates/
347
+ ├── data_pipeline_aggregate.rs
348
+ └── data_quality_aggregate.rs
349
+
350
+ src/event_sourcing/events/
351
+ ├── database_configured_event.rs
352
+ ├── data_pipeline_updated_event.rs
353
+ ├── data_quality_validated_event.rs
354
+ └── data_anomaly_detected_event.rs
355
+
356
+ src/query_side/queries/
357
+ ├── get_data_pipeline_status_query.rs
358
+ ├── get_data_quality_report_query.rs
359
+ └── get_feature_metrics_query.rs
360
+
361
+ src/query_side/query_handlers/
362
+ ├── data_query_handler.rs
363
+ └── quality_query_handler.rs
364
+
365
+ src/query_side/read_models/
366
+ ├── data_pipeline_read_model.rs
367
+ ├── data_quality_read_model.rs
368
+ └── feature_metrics_read_model.rs
369
+
370
+ src/feature_engineering/technical_indicators/
371
+ ├── mod.rs
372
+ ├── sma_calculator.rs
373
+ ├── rsi_calculator.rs
374
+ ├── macd_calculator.rs
375
+ ├── bollinger_bands_calculator.rs
376
+ ├── stochastic_oscillator_calculator.rs
377
+ ├── adx_calculator.rs
378
+ ├── parabolic_sar_calculator.rs
379
+ ├── atr_calculator.rs
380
+ ├── obv_calculator.rs
381
+ ├── cci_calculator.rs
382
+ ├── momentum_calculator.rs
383
+ ├── volatility_calculator.rs
384
+ ├── correlation_calculator.rs
385
+ └── regression_calculator.rs
386
+
387
+ src/feature_engineering/feature_store/
388
+ ├── duckdb_feature_store.rs
389
+ ├── feature_store_trait.rs
390
+ └── feature_cache_manager.rs
391
+
392
+ migrations/event_store/
393
+ ├── 003_create_data_events_table.surql
394
+ └── 004_add_data_quality_indexes.surql
395
+
396
+ migrations/read_model/
397
+ ├── 003_create_feature_tables.duckdb.sql
398
+ └── 004_create_quality_tables.duckdb.sql
399
+ ```
400
+
401
+ **Flujo de datos con Event Sourcing:**
402
+
403
+ 1. Un comando `ConfigureDatabaseCommand` se envía para configurar la base de datos.
404
+ 2. El `DataCommandHandler` procesa el comando y genera un `DatabaseConfiguredEvent`.
405
+ 3. El evento se persiste en SurrealDB Event Store.
406
+ 4. Los `EventProcessors` escuchan los eventos y actualizan los Read Models en DuckDB.
407
+ 5. Las consultas se sirven desde los Read Models optimizados.
408
+
409
+ ### 4.3 Fase 2: Desarrollo del Motor de Entrenamiento con CQRS y Event Sourcing
410
+
411
+ **Cambios principales:**
412
+
413
+ - El entrenamiento de modelos se gestiona mediante comandos y eventos
414
+ - El estado del entrenamiento se reconstruye desde los eventos
415
+ - Los resultados del entrenamiento son proyecciones en el Query Side
416
+
417
+ **Nuevos componentes implementados:**
418
+
419
+ #### Command Side para entrenamiento:
420
+
421
+ ```
422
+ src/command_side/commands/start_training_command.rs
423
+ src/command_side/commands/stop_training_command.rs
424
+ src/command_side/commands/update_training_config_command.rs
425
+ ```
426
+
427
+ #### Eventos de entrenamiento:
428
+
429
+ ```
430
+ src/event_sourcing/events/training_events.rs
431
+ ```
432
+
433
+ #### Aggregate para entrenamiento:
434
+
435
+ ```
436
+ src/command_side/aggregates/training_session_aggregate.rs
437
+ ```
438
+
439
+ #### Query Side para entrenamiento:
440
+
441
+ ```
442
+ src/query_side/queries/get_training_status_query.rs
443
+ src/query_side/read_models/training_read_model.rs
444
+ ```
445
+
446
+ #### Event Processors para entrenamiento:
447
+
448
+ ```
449
+ src/model_training/event_processors/training_processor.rs
450
+ src/model_training/event_processors/model_evaluation_processor.rs
451
+ ```
452
+
453
+ **Estructura detallada de archivos para esta fase:**
454
+
455
+ ```
456
+ src/command_side/commands/
457
+ ├── start_training_command.rs
458
+ ├── stop_training_command.rs
459
+ ├── pause_training_command.rs
460
+ ├── resume_training_command.rs
461
+ ├── update_hyperparameters_command.rs
462
+ └── validate_model_command.rs
463
+
464
+ src/command_side/command_handlers/
465
+ ├── training_command_handler.rs
466
+ └── model_validation_handler.rs
467
+
468
+ src/command_side/aggregates/
469
+ ├── training_session_aggregate.rs
470
+ └── model_validation_aggregate.rs
471
+
472
+ src/event_sourcing/events/
473
+ ├── training_started_event.rs
474
+ ├── training_stopped_event.rs
475
+ ├── training_paused_event.rs
476
+ ├── training_resumed_event.rs
477
+ ├── hyperparameters_updated_event.rs
478
+ ├── training_progress_updated_event.rs
479
+ ├── training_completed_event.rs
480
+ ├── training_failed_event.rs
481
+ ├── model_validated_event.rs
482
+ └── model_validation_failed_event.rs
483
+
484
+ src/query_side/queries/
485
+ ├── get_training_status_query.rs
486
+ ├── get_training_progress_query.rs
487
+ ├── get_hyperparameters_query.rs
488
+ ├── get_model_performance_query.rs
489
+ └── get_validation_results_query.rs
490
+
491
+ src/query_side/query_handlers/
492
+ ├── training_query_handler.rs
493
+ └── model_query_handler.rs
494
+
495
+ src/query_side/read_models/
496
+ ├── training_status_read_model.rs
497
+ ├── training_progress_read_model.rs
498
+ ├── hyperparameters_read_model.rs
499
+ ├── model_performance_read_model.rs
500
+ └── validation_results_read_model.rs
501
+
502
+ src/model_training/neural_architectures/
503
+ ├── mod.rs
504
+ ├── lstm_architecture.rs
505
+ ├── gru_architecture.rs
506
+ ├── transformer_architecture.rs
507
+ ├── temporal_convolution_architecture.rs
508
+ ├── attention_mechanism.rs
509
+ ├── residual_network_architecture.rs
510
+ ├── autoencoder_architecture.rs
511
+ ├── wavelet_network_architecture.rs
512
+ ├── neural_ode_architecture.rs
513
+ ├── deep_ar_architecture.rs
514
+ ├── nbeats_architecture.rs
515
+ ├── tcn_architecture.rs
516
+ ├── inception_time_architecture.rs
517
+ ├── time_series_forest_architecture.rs
518
+ ├── rocket_architecture.rs
519
+ ├── prophet_net_architecture.rs
520
+ ├── temporal_fusion_transformer_architecture.rs
521
+ └── hierarchical_attention_architecture.rs
522
+
523
+ src/model_training/training_orchestrator/
524
+ ├── training_scheduler.rs
525
+ ├── hyperparameter_optimizer.rs
526
+ ├── cross_validation_manager.rs
527
+ ├── resource_allocator.rs
528
+ ├── gradient_descent_optimizer.rs
529
+ ├── early_stopping_manager.rs
530
+ └── checkpoint_manager.rs
531
+
532
+ src/model_training/event_processors/
533
+ ├── training_processor.rs
534
+ ├── model_evaluation_processor.rs
535
+ ├── hyperparameter_processor.rs
536
+ └── validation_processor.rs
537
+
538
+ src/model_training/model_store/
539
+ ├── model_repository.rs
540
+ ├── model_serializer.rs
541
+ ├── model_version_manager.rs
542
+ └── model_metadata_store.rs
543
+
544
+ migrations/event_store/
545
+ ├── 005_create_training_events_table.surql
546
+ └── 006_add_training_indexes.surql
547
+
548
+ migrations/read_model/
549
+ ├── 005_create_training_tables.duckdb.sql
550
+ └── 006_create_model_tables.duckdb.sql
551
+ ```
552
+
553
+ **Flujo de entrenamiento con Event Sourcing:**
554
+
555
+ 1. Se envía un `StartTrainingCommand` con la configuración de entrenamiento.
556
+ 2. El `TrainingCommandHandler` valida el comando y genera un `TrainingStartedEvent`.
557
+ 3. El evento se persiste y el `TrainingSessionAggregate` actualiza su estado.
558
+ 4. El `TrainingProcessor` escucha el evento y inicia el proceso de entrenamiento.
559
+ 5. Durante el entrenamiento, se generan eventos de progreso que se persisten y proyectan a los Read Models.
560
+ 6. Al finalizar, se genera un `TrainingCompletedEvent` o `TrainingFailedEvent`.
561
+ 7. Las consultas sobre el estado de entrenamiento se sirven desde los Read Models.
562
+
563
+ ### 4.4 Fase 3: Conversión y Optimización ONNX con Event Sourcing
564
+
565
+ **Cambios principales:**
566
+
567
+ - La conversión a ONNX se触发 mediante comandos
568
+ - Los eventos capturan el proceso de conversión y optimización
569
+ - El estado de los modelos ONNX se gestiona mediante aggregates
570
+
571
+ **Nuevos componentes implementados:**
572
+
573
+ #### Command Side para ONNX:
574
+
575
+ ```
576
+ src/command_side/commands/export_onnx_command.rs
577
+ src/command_side/commands/optimize_onnx_command.rs
578
+ src/command_side/commands/validate_onnx_command.rs
579
+ ```
580
+
581
+ #### Eventos de ONNX:
582
+
583
+ ```
584
+ src/event_sourcing/events/onnx_events.rs
585
+ ```
586
+
587
+ #### Aggregate para ONNX:
588
+
589
+ ```
590
+ src/command_side/aggregates/model_aggregate.rs
591
+ ```
592
+
593
+ #### Query Side para ONNX:
594
+
595
+ ```
596
+ src/query_side/queries/get_onnx_model_query.rs
597
+ src/query_side/read_models/model_read_model.rs
598
+ ```
599
+
600
+ #### Event Processors para ONNX:
601
+
602
+ ```
603
+ src/onnx_conversion/event_processors/onnx_conversion_processor.rs
604
+ ```
605
+
606
+ **Estructura detallada de archivos para esta fase:**
607
+
608
+ ```
609
+ src/command_side/commands/
610
+ ├── export_onnx_command.rs
611
+ ├── optimize_onnx_command.rs
612
+ ├── validate_onnx_command.rs
613
+ ├── deploy_onnx_command.rs
614
+ └── benchmark_onnx_command.rs
615
+
616
+ src/command_side/command_handlers/
617
+ ├── onnx_command_handler.rs
618
+ └── deployment_handler.rs
619
+
620
+ src/command_side/aggregates/
621
+ ├── onnx_model_aggregate.rs
622
+ └── deployment_aggregate.rs
623
+
624
+ src/event_sourcing/events/
625
+ ├── onnx_export_started_event.rs
626
+ ├── onnx_export_completed_event.rs
627
+ ├── onnx_export_failed_event.rs
628
+ ├── onnx_optimization_started_event.rs
629
+ ├── onnx_optimization_completed_event.rs
630
+ ├── onnx_validation_started_event.rs
631
+ ├── onnx_validation_completed_event.rs
632
+ ├── onnx_deployment_started_event.rs
633
+ ├── onnx_deployment_completed_event.rs
634
+ ├── onnx_benchmark_started_event.rs
635
+ └── onnx_benchmark_completed_event.rs
636
+
637
+ src/query_side/queries/
638
+ ├── get_onnx_model_query.rs
639
+ ├── get_onnx_optimization_query.rs
640
+ ├── get_onnx_validation_query.rs
641
+ ├── get_onnx_deployment_query.rs
642
+ └── get_onnx_benchmark_query.rs
643
+
644
+ src/query_side/query_handlers/
645
+ ├── onnx_query_handler.rs
646
+ └── deployment_query_handler.rs
647
+
648
+ src/query_side/read_models/
649
+ ├── onnx_model_read_model.rs
650
+ ├── onnx_optimization_read_model.rs
651
+ ├── onnx_validation_read_model.rs
652
+ ├── onnx_deployment_read_model.rs
653
+ └── onnx_benchmark_read_model.rs
654
+
655
+ src/onnx_conversion/onnx_exporter/
656
+ ├── candle_to_onnx.rs
657
+ ├── pytorch_to_onnx.rs
658
+ ├── tensorflow_to_onnx.rs
659
+ ├── onnx_exporter_trait.rs
660
+ └── onnx_version_manager.rs
661
+
662
+ src/onnx_conversion/optimization/
663
+ ├── quantizer.rs
664
+ ├── operator_fuser.rs
665
+ ├── graph_optimizer.rs
666
+ ├── latency_optimizer.rs
667
+ ├── memory_optimizer.rs
668
+ └── compatibility_checker.rs
669
+
670
+ src/onnx_conversion/validation/
671
+ ├── onnx_validator.rs
672
+ ├── precision_validator.rs
673
+ ├── performance_validator.rs
674
+ └── security_validator.rs
675
+
676
+ src/onnx_conversion/deployment/
677
+ ├── onnx_deployer.rs
678
+ ├── cloud_deployer.rs
679
+ ├── edge_deployer.rs
680
+ └── local_deployer.rs
681
+
682
+ src/onnx_conversion/benchmarking/
683
+ ├── onnx_benchmarker.rs
684
+ ├── hardware_benchmarker.rs
685
+ ├── inference_benchmarker.rs
686
+ └── comparative_benchmarker.rs
687
+
688
+ migrations/event_store/
689
+ ├── 007_create_onnx_events_table.surql
690
+ └── 008_add_onnx_indexes.surql
691
+
692
+ migrations/read_model/
693
+ ├── 007_create_onnx_tables.duckdb.sql
694
+ └── 008_create_deployment_tables.duckdb.sql
695
+ ```
696
+
697
+ **Flujo de conversión ONNX con Event Sourcing:**
698
+
699
+ 1. Se envía un `ExportONNXCommand` para convertir un modelo entrenado.
700
+ 2. El `ONNXCommandHandler` genera un `ONNXExportStartedEvent`.
701
+ 3. El evento se persiste y el `ONNXModelAggregate` trackea el estado.
702
+ 4. El `ONNXConversionProcessor` escucha el evento y ejecuta la conversión.
703
+ 5. Al completarse, se genera un `ONNXExportCompletedEvent` con los detalles.
704
+ 6. Los eventos de optimización, validación, etc., siguen el mismo patrón.
705
+ 7. Las consultas sobre modelos ONNX se sirven desde los Read Models.
706
+
707
+ # Respuesta Parte 3/4: Refactorización del Plan Hiper Feature Pipeline Store v6.0
708
+
709
+ ## Continuación de las Fases de Implementación Refactorizadas
710
+
711
+ ### 4.4 Fase 4: Desarrollo del Dashboard UI con Event Sourcing y CQRS
712
+
713
+ **Cambios principales:**
714
+
715
+ - La UI se construye con separación clara entre componentes Presentacionales y Contenedores
716
+ - Los contenedores manejan comandos y consultas hacia el backend
717
+ - La UI se suscribe a eventos para actualizaciones en tiempo real
718
+ - Estado de UI gestionado mediante máquinas de estado reactivas
719
+
720
+ **Nuevos componentes implementados:**
721
+
722
+ #### Componentes Contenedores (Command Side):
723
+
724
+ ```
725
+ src/ui/leptos_app/components/container_components/
726
+ ├── dataset_container_components/
727
+ ├── training_container_components/
728
+ └── model_container_components/
729
+ ```
730
+
731
+ #### Componentes Presentacionales (Query Side):
732
+
733
+ ```
734
+ src/ui/leptos_app/components/presentational_components/
735
+ ├── dataset_presentational_components/
736
+ ├── training_presentational_components/
737
+ └── model_presentational_components/
738
+ ```
739
+
740
+ #### Gestión de Estado de UI:
741
+
742
+ ```
743
+ src/ui/state_management/
744
+ ├── command_state.rs
745
+ ├── query_state.rs
746
+ └── ui_state.rs
747
+ ```
748
+
749
+ #### Suscripción a Eventos para UI:
750
+
751
+ ```
752
+ src/ui/event_subscriptions/
753
+ ├── dataset_event_subscription.rs
754
+ ├── training_event_subscription.rs
755
+ └── model_event_subscription.rs
756
+ ```
757
+
758
+ **Estructura detallada de archivos para esta fase:**
759
+
760
+ ```
761
+ src/ui/leptos_app/
762
+ ├── app.rs
763
+ ├── main.rs
764
+ ├── components/
765
+ │ ├── mod.rs
766
+ │ ├── container_components/
767
+ │ │ ├── mod.rs
768
+ │ │ ├── dataset_container_components/
769
+ │ │ │ ├── mod.rs
770
+ │ │ │ ├── dataset_upload_container.rs
771
+ │ │ │ ├── dataset_validation_container.rs
772
+ │ │ │ └── dataset_explorer_container.rs
773
+ │ │ ├── training_container_components/
774
+ │ │ │ ├── mod.rs
775
+ │ │ │ ├── training_start_container.rs
776
+ │ │ │ ├── training_monitor_container.rs
777
+ │ │ │ └── training_control_container.rs
778
+ │ │ └── model_container_components/
779
+ │ │ ├── mod.rs
780
+ │ │ ├── model_export_container.rs
781
+ │ │ ├── model_deployment_container.rs
782
+ │ │ └── model_benchmark_container.rs
783
+ │ └── presentational_components/
784
+ │ ├── mod.rs
785
+ │ ├── dataset_presentational_components/
786
+ │ │ ├── mod.rs
787
+ │ │ ├── dataset_table_component.rs
788
+ │ │ ├── dataset_quality_indicator.rs
789
+ │ │ └── dataset_visualization_component.rs
790
+ │ ├── training_presentational_components/
791
+ │ │ ├── mod.rs
792
+ │ │ ├── training_progress_chart.rs
793
+ │ │ ├── training_metrics_display.rs
794
+ │ │ └── training_config_viewer.rs
795
+ │ └── model_presentational_components/
796
+ │ ├── mod.rs
797
+ │ ├── model_performance_chart.rs
798
+ │ ├── model_comparison_table.rs
799
+ │ └── model_deployment_status.rs
800
+ ├── pages/
801
+ │ ├── mod.rs
802
+ │ ├── dashboard_page.rs
803
+ │ ├── dataset_explorer_page.rs
804
+ │ ├── training_monitor_page.rs
805
+ │ ├── model_management_page.rs
806
+ │ └── system_health_page.rs
807
+ ├── state_management/
808
+ │ ├── mod.rs
809
+ │ ├── command_state.rs
810
+ │ ├── query_state.rs
811
+ │ ├── ui_state.rs
812
+ │ └── subscription_manager.rs
813
+ └── event_subscriptions/
814
+ ├── mod.rs
815
+ ├── dataset_event_subscription.rs
816
+ ├── training_event_subscription.rs
817
+ ├── model_event_subscription.rs
818
+ └── system_event_subscription.rs
819
+
820
+ src/api/query_controllers/
821
+ ├── ui_query_controller.rs
822
+ ├── dataset_query_controller.rs
823
+ ├── training_query_controller.rs
824
+ └── model_query_controller.rs
825
+
826
+ src/api/command_controllers/
827
+ ├── ui_command_controller.rs
828
+ ├── dataset_command_controller.rs
829
+ ├── training_command_controller.rs
830
+ └── model_command_controller.rs
831
+
832
+ src/api/middleware/
833
+ ├── authentication.rs
834
+ ├── authorization.rs
835
+ ├── logging.rs
836
+ └── cors.rs
837
+
838
+ migrations/read_model/
839
+ ├── 009_create_ui_state_tables.duckdb.sql
840
+ └── 010_create_user_preferences_tables.duckdb.sql
841
+ ```
842
+
843
+ **Flujo de UI con Event Sourcing y CQRS:**
844
+
845
+ 1. Los componentes Contenedores envían comandos a través de `command_state` para realizar acciones.
846
+ 2. Los componentes Presentacionales consumen datos de `query_state` que se actualizan desde los Read Models.
847
+ 3. Las suscripciones a eventos escuchan cambios en el Event Store y actualizan el estado de UI en tiempo real.
848
+ 4. Los controladores de API manejan las solicitudes HTTP y las traducen en comandos o consultas.
849
+
850
+ ### 4.5 Fase 5: Orquestación y Monitoreo con Event Sourcing
851
+
852
+ **Cambios principales:**
853
+
854
+ - La orquestación se gestiona mediante comandos que trigger eventos
855
+ - El monitoreo se basa en consultas a Read Models y suscripción a eventos
856
+ - Las políticas de orquestación se definen como máquinas de estado
857
+
858
+ **Nuevos componentes implementados:**
859
+
860
+ #### Command Side para Orquestación:
861
+
862
+ ```
863
+ src/command_side/commands/orchestration_commands/
864
+ ├── start_orchestration_command.rs
865
+ ├── stop_orchestration_command.rs
866
+ └── update_orchestration_policy_command.rs
867
+ ```
868
+
869
+ #### Eventos de Orquestación:
870
+
871
+ ```
872
+ src/event_sourcing/events/orchestration_events.rs
873
+ ```
874
+
875
+ #### Aggregate para Orquestación:
876
+
877
+ ```
878
+ src/command_side/aggregates/orchestration_aggregate.rs
879
+ ```
880
+
881
+ #### Query Side para Monitoreo:
882
+
883
+ ```
884
+ src/query_side/queries/monitoring_queries/
885
+ ├── get_system_health_query.rs
886
+ ├── get_performance_metrics_query.rs
887
+ └── get_resource_usage_query.rs
888
+ ```
889
+
890
+ #### Event Processors para Monitoreo:
891
+
892
+ ```
893
+ src/monitoring/event_processors/
894
+ ├── health_monitor_processor.rs
895
+ ├── performance_monitor_processor.rs
896
+ └── resource_monitor_processor.rs
897
+ ```
898
+
899
+ **Estructura detallada de archivos para esta fase:**
900
+
901
+ ```
902
+ src/command_side/commands/
903
+ ├── orchestration_commands/
904
+ │ ├── mod.rs
905
+ │ ├── start_orchestration_command.rs
906
+ │ ├── stop_orchestration_command.rs
907
+ │ ├── pause_orchestration_command.rs
908
+ │ ├── resume_orchestration_command.rs
909
+ │ ├── update_orchestration_policy_command.rs
910
+ │ └── validate_orchestration_command.rs
911
+ └── monitoring_commands/
912
+ ├── mod.rs
913
+ ├── enable_monitoring_command.rs
914
+ ├── disable_monitoring_command.rs
915
+ ├── update_monitoring_config_command.rs
916
+ └── trigger_alert_command.rs
917
+
918
+ src/command_side/command_handlers/
919
+ ├── orchestration_command_handler.rs
920
+ └── monitoring_command_handler.rs
921
+
922
+ src/command_side/aggregates/
923
+ ├── orchestration_aggregate.rs
924
+ └── monitoring_aggregate.rs
925
+
926
+ src/event_sourcing/events/
927
+ ├── orchestration_events/
928
+ │ ├── mod.rs
929
+ │ ├── orchestration_started_event.rs
930
+ │ ├── orchestration_stopped_event.rs
931
+ │ ├── orchestration_paused_event.rs
932
+ │ ├── orchestration_resumed_event.rs
933
+ │ ├── orchestration_policy_updated_event.rs
934
+ │ ├── orchestration_completed_event.rs
935
+ │ └── orchestration_failed_event.rs
936
+ └── monitoring_events/
937
+ ├── mod.rs
938
+ ├── monitoring_enabled_event.rs
939
+ ├── monitoring_disabled_event.rs
940
+ ├── monitoring_config_updated_event.rs
941
+ ├── alert_triggered_event.rs
942
+ ├── alert_resolved_event.rs
943
+ └── system_health_updated_event.rs
944
+
945
+ src/query_side/queries/
946
+ ├── orchestration_queries/
947
+ │ ├── mod.rs
948
+ │ ├── get_orchestration_status_query.rs
949
+ │ ├── get_orchestration_policy_query.rs
950
+ │ └── get_orchestration_history_query.rs
951
+ └── monitoring_queries/
952
+ ├── mod.rs
953
+ ├── get_system_health_query.rs
954
+ ├── get_performance_metrics_query.rs
955
+ ├── get_resource_usage_query.rs
956
+ ├── get_alert_history_query.rs
957
+ └── get_monitoring_config_query.rs
958
+
959
+ src/query_side/query_handlers/
960
+ ├── orchestration_query_handler.rs
961
+ └── monitoring_query_handler.rs
962
+
963
+ src/query_side/read_models/
964
+ ├── orchestration_read_model.rs
965
+ ├── orchestration_policy_read_model.rs
966
+ ├── orchestration_history_read_model.rs
967
+ ├── system_health_read_model.rs
968
+ ├── performance_metrics_read_model.rs
969
+ ├── resource_usage_read_model.rs
970
+ ├── alert_history_read_model.rs
971
+ └── monitoring_config_read_model.rs
972
+
973
+ src/orchestration/
974
+ ├── mod.rs
975
+ ├ orchestration_engine/
976
+ │ ├── mod.rs
977
+ │ ├── workflow_orchestrator.rs
978
+ │ ├── task_scheduler.rs
979
+ │ ├── resource_optimizer.rs
980
+ │ ├── dependency_resolver.rs
981
+ │ └── policy_enforcer.rs
982
+ ├── event_processors/
983
+ │ ├── mod.rs
984
+ │ ├── workflow_processor.rs
985
+ │ ├── task_processor.rs
986
+ │ └── policy_processor.rs
987
+ └── state_machines/
988
+ ├── mod.rs
989
+ ├── workflow_state_machine.rs
990
+ ├── task_state_machine.rs
991
+ └── resource_state_machine.rs
992
+
993
+ src/monitoring/
994
+ ├── mod.rs
995
+ ├── metrics/
996
+ │ ├── mod.rs
997
+ │ ├── system_metrics_collector.rs
998
+ │ ├── application_metrics_collector.rs
999
+ │ ├── business_metrics_collector.rs
1000
+ │ └── metrics_aggregator.rs
1001
+ ├── alerting/
1002
+ │ ├── mod.rs
1003
+ │ ├── alert_manager.rs
1004
+ │ ├── alert_rules_engine.rs
1005
+ │ ├── alert_notifier.rs
1006
+ │ └── alert_history_store.rs
1007
+ ├── event_processors/
1008
+ │ ├── mod.rs
1009
+ │ ├── health_monitor_processor.rs
1010
+ │ ├── performance_monitor_processor.rs
1011
+ │ ├── resource_monitor_processor.rs
1012
+ │ └── alert_processor.rs
1013
+ └── dashboards/
1014
+ ├── mod.rs
1015
+ ├── system_health_dashboard.rs
1016
+ ├── performance_dashboard.rs
1017
+ ├── resource_dashboard.rs
1018
+ └── alert_dashboard.rs
1019
+
1020
+ migrations/event_store/
1021
+ ├── 009_create_orchestration_events_table.surql
1022
+ ├── 010_create_monitoring_events_table.surql
1023
+ └── 011_add_orchestration_indexes.surql
1024
+
1025
+ migrations/read_model/
1026
+ ├── 011_create_orchestration_tables.duckdb.sql
1027
+ ├── 012_create_monitoring_tables.duckdb.sql
1028
+ └── 013_create_alert_tables.duckdb.sql
1029
+ ```
1030
+
1031
+ **Flujo de Orquestación y Monitoreo con Event Sourcing:**
1032
+
1033
+ 1. Se envía un `StartOrchestrationCommand` para iniciar un flujo de trabajo.
1034
+ 2. El `OrchestrationCommandHandler` genera un `OrchestrationStartedEvent`.
1035
+ 3. El evento se persiste y el `OrchestrationAggregate` actualiza su estado.
1036
+ 4. El `WorkflowProcessor` escucha el evento y ejecuta las tareas de orquestación.
1037
+ 5. Durante la orquestación, se generan eventos de progreso que se persisten y proyectan a los Read Models.
1038
+ 6. El monitoreo se activa mediante eventos y las métricas se almacenan en Read Models.
1039
+ 7. Las alertas se triggerean mediante eventos y se notifican a través de suscripciones.
1040
+
1041
+ ### 5. Stack Tecnológico Actualizado
1042
+
1043
+ El stack tecnológico se mantiene similar pero con adiciones para soportar Event Sourcing y CQRS:
1044
+
1045
+ - **Núcleo**: Rust + Tokio + Axum - Para comandos y consultas HTTP
1046
+ - **Event Store**: SurrealDB - Almacenamiento de eventos inmutables
1047
+ - **Read Models**: DuckDB - Para consultas optimizadas
1048
+ - **Embeddings**: LanceDB - Para almacenamiento vectorial
1049
+ - **UI**: Leptos + Dioxus - Con componentes Presentacionales y Contenedores
1050
+ - **Monitoreo**: OpenTelemetry + Prometheus - Para métricas y tracing
1051
+ - **Mensajería**: Redis Streams o Kafka - Para procesamiento de eventos (opcional)
1052
+
1053
+ ### 6. Modelos de Datos Actualizados
1054
+
1055
+ Los modelos de datos se alinean con Event Sourcing:
1056
+
1057
+ - **Event Models**: Estructuras inmutables que representan cambios de estado
1058
+ - **Aggregate Models**: Entidades que gestionan el estado consistente basado en eventos
1059
+ - **Read Models**: Vistas optimizadas para consultas, derivadas de eventos
1060
+ - **Projection Models**: Definiciones de cómo los eventos se transforman en Read Models
1061
+
1062
+ ### 7. Referencia de Endpoints API Actualizada
1063
+
1064
+ Los endpoints se dividen en Command y Query endpoints:
1065
+
1066
+ #### Command Endpoints (POST):
1067
+
1068
+ - `/api/commands/dataset/ingest` - Ingestar dataset
1069
+ - `/api/commands/training/start` - Iniciar entrenamiento
1070
+ - `/api/commands/model/export-onnx` - Exportar modelo a ONNX
1071
+ - `/api/commands/orchestration/start` - Iniciar orquestación
1072
+
1073
+ #### Query Endpoints (GET):
1074
+
1075
+ - `/api/queries/dataset/{id}` - Obtener dataset
1076
+ - `/api/queries/training/status/{id}` - Obtener estado de entrenamiento
1077
+ - `/api/queries/model/performance/{id}` - Obtener rendimiento de modelo
1078
+ - `/api/queries/monitoring/health` - Obtener salud del sistema
1079
+
1080
+ #### Event Streaming Endpoints (SSE):
1081
+
1082
+ - `/api/events/dataset` - Flujo de eventos de dataset
1083
+ - `/api/events/training` - Flujo de eventos de entrenamiento
1084
+ - `/api/events/system` - Flujo de eventos del sistema
1085
+
1086
+ ### 8. Estrategia de Pruebas Actualizada
1087
+
1088
+ Las pruebas se adaptan para Event Sourcing y CQRS:
1089
+
1090
+ - **Pruebas de Comandos**: Verificar que los comandos generan los eventos correctos
1091
+ - **Pruebas de Eventos**: Verificar que los eventos se persisten y procesan correctamente
1092
+ - **Pruebas de Proyecciones**: Verificar que los Read Models se actualizan correctamente desde eventos
1093
+ - **Pruebas de Consultas**: Verificar que las consultas devuelven los datos correctos desde Read Models
1094
+ - **Pruebas de Integración**: Verificar el flujo completo de comandos, eventos y consultas
1095
+
1096
+ ### 9. Despliegue y Operaciones Actualizado
1097
+
1098
+ El despliegue considera la naturaleza event-sourced del sistema:
1099
+
1100
+ - **Despliegue de Event Store**: SurrealDB en cluster para alta disponibilidad
1101
+ - **Despliegue de Read Models**: DuckDB replicado para rendimiento en consultas
1102
+ - **Procesadores de Eventos**: Escalables horizontalmente para manejar carga de eventos
1103
+ - **API Gateway**: Balanceo de carga entre comandos y consultas
1104
+ - **Monitoreo**: Dashboards basados en eventos para observabilidad en tiempo real
1105
+
1106
+ # Respuesta Parte 4/4: Refactorización del Plan Hiper Feature Pipeline Store v6.0
1107
+
1108
+ ## Continuación de las Secciones Refactorizadas
1109
+
1110
+ ### 9. Aseguramiento de Calidad y Cumplimiento con Event Sourcing
1111
+
1112
+ **Cambios principales:**
1113
+
1114
+ - Las pruebas y validaciones se basan en eventos y proyecciones
1115
+ - El cumplimiento se asegura mediante la inmutabilidad de los eventos y el tracing completo
1116
+ - Las métricas de calidad se derivan de los eventos y read models
1117
+
1118
+ #### 9.1 Estándares de Calidad de Código Actualizados
1119
+
1120
+ **Nuevos componentes implementados para calidad:**
1121
+
1122
+ ```
1123
+ src/quality_assurance/
1124
+ ├── mod.rs
1125
+ ├── code_quality/
1126
+ │ ├── mod.rs
1127
+ │ ├── rust_code_analyzer.rs
1128
+ │ ├── test_coverage_calculator.rs
1129
+ │ ├── dependency_auditor.rs
1130
+ │ └── security_scanner.rs
1131
+ ├── event_based_testing/
1132
+ │ ├── mod.rs
1133
+ │ ├── command_validation_test.rs
1134
+ │ ├── event_sourcing_test.rs
1135
+ │ ├── projection_validation_test.rs
1136
+ │ └── cqrs_integration_test.rs
1137
+ └── compliance_checking/
1138
+ ├── mod.rs
1139
+ ├── gdpr_compliance_checker.rs
1140
+ ├── pci_dss_compliance_checker.rs
1141
+ ├── sox_compliance_checker.rs
1142
+ └── audit_trail_generator.rs
1143
+ ```
1144
+
1145
+ **Estrategia de pruebas con Event Sourcing:**
1146
+
1147
+ - **Pruebas de Comandos**: Validar que los comandos generan los eventos esperados
1148
+ - **Pruebas de Eventos**: Asegurar la correcta persistencia y procesamiento de eventos
1149
+ - **Pruebas de Proyecciones**: Verificar que los read models se actualizan correctamente
1150
+ - **Pruebas de Consultas**: Validar el rendimiento y precisión de las consultas
1151
+ - **Pruebas de Integración**: Simular flujos completos de comandos y consultas
1152
+
1153
+ #### 9.2 Consideraciones de Seguridad Actualizadas
1154
+
1155
+ - **Inmutabilidad de Eventos**: Los eventos no pueden ser modificados, asegurando integridad
1156
+ - **Trazabilidad Completa**: Todo cambio se rastrea mediante eventos, facilitando auditorías
1157
+ - **Encriptación de Eventos**: Eventos sensibles se encriptan en el event store
1158
+ - **Control de Acceso Basado en Eventos**: Permisos gestionados mediante eventos de autorización
1159
+
1160
+ #### 9.3 Benchmarks de Rendimiento Actualizados
1161
+
1162
+ - **Rendimiento de Escritura**: Métricas de latencia para comandos y persistencia de eventos
1163
+ - **Rendimiento de Lectura**: Métricas de latencia para consultas a read models
1164
+ - **Rendimiento de Proyecciones**: Tiempo de procesamiento de eventos para actualizar read models
1165
+ - **Escalabilidad**: Capacidad de manejar picos de eventos y consultas
1166
+
1167
+ ### 10. Despliegue y Operaciones con Event Sourcing
1168
+
1169
+ **Cambios principales:**
1170
+
1171
+ - Despliegue separado para command side, query side, y event processors
1172
+ - Operaciones basadas en eventos para monitoreo y recovery
1173
+ - Estrategias de despliegue blue-green para componentes críticos
1174
+
1175
+ #### 10.1 Arquitectura de Despliegue Actualizada
1176
+
1177
+ **Despliegue en Kubernetes con microservicios:**
1178
+
1179
+ ```yaml
1180
+ # Kubernetes Deployment Example
1181
+ apiVersion: apps/v1
1182
+ kind: Deployment
1183
+ metadata:
1184
+ name: command-side-deployment
1185
+ spec:
1186
+ replicas: 3
1187
+ template:
1188
+ spec:
1189
+ containers:
1190
+ - name: command-side
1191
+ image: command-side:latest
1192
+ env:
1193
+ - name: EVENT_STORE_URL
1194
+ value: "surreal://event-store:8000"
1195
+ - name: READ_MODEL_URL
1196
+ value: "duckdb://read-model:9000"
1197
+
1198
+ ---
1199
+ apiVersion: apps/v1
1200
+ kind: Deployment
1201
+ metadata:
1202
+ name: query-side-deployment
1203
+ spec:
1204
+ replicas: 3
1205
+ template:
1206
+ spec:
1207
+ containers:
1208
+ - name: query-side
1209
+ image: query-side:latest
1210
+ env:
1211
+ - name: READ_MODEL_URL
1212
+ value: "duckdb://read-model:9000"
1213
+
1214
+ ---
1215
+ apiVersion: apps/v1
1216
+ kind: Deployment
1217
+ metadata:
1218
+ name: event-processor-deployment
1219
+ spec:
1220
+ replicas: 3
1221
+ template:
1222
+ spec:
1223
+ containers:
1224
+ - name: event-processor
1225
+ image: event-processor:latest
1226
+ env:
1227
+ - name: EVENT_STORE_URL
1228
+ value: "surreal://event-store:8000"
1229
+ - name: READ_MODEL_URL
1230
+ value: "duckdb://read-model:9000"
1231
+ ```
1232
+
1233
+ #### 10.2 Monitoreo y Observabilidad Actualizados
1234
+
1235
+ **Nuevos componentes para monitoreo:**
1236
+
1237
+ ```
1238
+ src/monitoring/
1239
+ ├── mod.rs
1240
+ ├── event_based_monitoring/
1241
+ │ ├── mod.rs
1242
+ │ ├── event_metrics_collector.rs
1243
+ │ ├── projection_lag_monitor.rs
1244
+ │ ├── command_latency_monitor.rs
1245
+ │ └── query_performance_monitor.rs
1246
+ ├── health_checks/
1247
+ │ ├── mod.rs
1248
+ │ ├── event_store_health_check.rs
1249
+ │ ├── read_model_health_check.rs
1250
+ │ └── processor_health_check.rs
1251
+ └── alerting/
1252
+ ├── mod.rs
1253
+ ├── event_based_alerter.rs
1254
+ ├── anomaly_detector.rs
1255
+ ├── threshold_alerter.rs
1256
+ └── alert_manager.rs
1257
+ ```
1258
+
1259
+ **Métricas clave:**
1260
+
1261
+ - **Evento por Segundo**: Volumen de eventos siendo procesados
1262
+ - **Lag de Proyecciones**: Retraso entre evento y actualización de read model
1263
+ - **Latencia de Comandos**: Tiempo desde comando hasta persistencia de evento
1264
+ - **Latencia de Consultas**: Tiempo de respuesta de consultas a read models
1265
+
1266
+ #### 10.3 Consideraciones de Escalabilidad Actualizadas
1267
+
1268
+ - **Escalado Horizontal**: Añadir más instancias de event processors para manejar carga de eventos
1269
+ - **Particionamiento de Eventos**: Distribuir eventos por aggregate id para mejorar rendimiento
1270
+ - **Caching de Read Models**: Cachear consultas frecuentes para reducir carga en read models
1271
+ - **Balanceo de Carga**: Balancear tráfico entre command y query sides basado en patrones de uso
1272
+
1273
+ ### 11. Modelos de Datos Actualizados para Event Sourcing
1274
+
1275
+ **Estructura de eventos ejemplo:**
1276
+
1277
+ ```rust
1278
+ // Evento de ingesta de dataset
1279
+ pub struct DatasetIngestedEvent {
1280
+ pub event_id: Uuid,
1281
+ pub aggregate_id: Uuid,
1282
+ pub timestamp: DateTime<Utc>,
1283
+ pub version: i32,
1284
+ pub dataset_id: String,
1285
+ pub dataset_name: String,
1286
+ pub dataset_type: String,
1287
+ pub dataset_size: usize,
1288
+ pub dataset_metadata: Value,
1289
+ pub ingested_by: String,
1290
+ }
1291
+
1292
+ // Evento de inicio de entrenamiento
1293
+ pub struct TrainingStartedEvent {
1294
+ pub event_id: Uuid,
1295
+ pub aggregate_id: Uuid,
1296
+ pub timestamp: DateTime<Utc>,
1297
+ pub version: i32,
1298
+ pub training_id: String,
1299
+ pub model_architecture: String,
1300
+ pub hyperparameters: Value,
1301
+ pub dataset_id: String,
1302
+ pub started_by: String,
1303
+ }
1304
+ ```
1305
+
1306
+ **Estructura de read models ejemplo:**
1307
+
1308
+ ```rust
1309
+ // Read model para estado de entrenamiento
1310
+ pub struct TrainingStatusReadModel {
1311
+ pub training_id: String,
1312
+ pub status: String,
1313
+ pub progress: f32,
1314
+ pub current_epoch: i32,
1315
+ pub total_epochs: i32,
1316
+ pub training_loss: f32,
1317
+ validation_loss: f32,
1318
+ pub start_time: DateTime<Utc>,
1319
+ pub end_time: Option<DateTime<Utc>>,
1320
+ pub last_updated: DateTime<Utc>,
1321
+ }
1322
+
1323
+ // Read model para calidad de datos
1324
+ pub struct DataQualityReadModel {
1325
+ pub dataset_id: String,
1326
+ pub completeness_score: f32,
1327
+ pub consistency_score: f32,
1328
+ pub accuracy_score: f32,
1329
+ pub timeliness_score: f32,
1330
+ pub anomalies_detected: i32,
1331
+ pub last_validated: DateTime<Utc>,
1332
+ }
1333
+ ```
1334
+
1335
+ ### 12. Referencia de Endpoints API Actualizada
1336
+
1337
+ **Endpoints de Comando (POST):**
1338
+
1339
+ - `/api/v1/commands/datasets/ingest` - Ingestar un nuevo dataset
1340
+ - `/api/v1/commands/training/start` - Iniciar una sesión de entrenamiento
1341
+ - `/api/v1/commands/models/export-onnx` - Exportar modelo a ONNX
1342
+ - `/api/v1/commands/orchestration/start` - Iniciar orquestación
1343
+
1344
+ **Endpoints de Consulta (GET):**
1345
+
1346
+ - `/api/v1/queries/datasets/{id}` - Obtener metadata de dataset
1347
+ - `/api/v1/queries/datasets/{id}/quality` - Obtener calidad de dataset
1348
+ - `/api/v1/queries/training/{id}/status` - Obtener estado de entrenamiento
1349
+ - `/api/v1/queries/models/{id}/performance` - Obtener rendimiento de modelo
1350
+
1351
+ **Endpoints de Eventos (SSE):**
1352
+
1353
+ - `/api/v1/events/datasets` - Flujo de eventos de datasets
1354
+ - `/api/v1/events/training` - Flujo de eventos de entrenamiento
1355
+ - `/api/v1/events/system` - Flujo de eventos del sistema
1356
+
1357
+ ### 13. Estrategia de Pruebas Actualizada
1358
+
1359
+ **Pruebas específicas para Event Sourcing y CQRS:**
1360
+
1361
+ - **Pruebas de Consistencia de Eventos**: Verificar que los eventos se persisten y recuperan correctamente
1362
+ - **Pruebas de Proyecciones**: Validar que los read models se actualizan como se espera tras eventos
1363
+ - **Pruebas de Concurrencia**: Simular múltiples comandos concurrentes y verificar consistencia
1364
+ - **Pruebas de Recovery**: Verificar que el sistema puede recuperarse desde event store tras fallos
1365
+ - **Pruebas de Rendimiento**: Medir latencia y throughput de comandos, eventos y consultas
1366
+
1367
+ ### 14. Conclusión y Beneficios de la Refactorización
1368
+
1369
+ La refactorización del Hiper Feature Pipeline Store v6.0 hacia una arquitectura de Event Sourcing + CQRS + Screaming Architecture proporciona:
1370
+
1371
+ - **Trazabilidad Completa**: Todo cambio se captura en eventos inmutables, permitiendo auditoría completa y replay de eventos.
1372
+ - **Escalabilidad Mejorada**: Separación de comandos y consultas permite escalar componentes de forma independiente.
1373
+ - **Mantenibilidad**: Estructura clara de carpetas y archivos sin ambigüedades, con componentes bien definidos.
1374
+ - **Flexibilidad**: Fácil evolución del sistema al añadir nuevos eventos y proyecciones sin afectar existentes.
1375
+ - **Resiliencia**: Capacidad de recuperación desde event store tras fallos, reconstruyendo estado desde eventos.
1376
+
1377
+ Esta arquitectura asegura que el sistema sea robusto, eficiente y preparado para futuras expansiones, cumpliendo con los más altos estándares empresariales para sistemas de trading cuantitativo.
1378
+
1379
+ Con esta base, el Hiper Feature Pipeline Store v6.0 estará posicionado como un sistema de clase mundial para machine learning financiero.
1380
+
1381
+ Puedes ayudarme a darle un aspecto visual al frontend mas futurista y que resalte que es una plataforma de trading cuantitativo y Machine Learning con todo tipo de elementos visuales, bloques flotantes, efectos 3D, colores gradientes y por supuesto redes neuronales que conectan entre si y conectan todos los elementos del dashboard y el frontend!
1382
+ Puedes ayudarme a darle un aspecto visual al frontend mas futurista y que resalte que es una plataforma de trading cuantitativo y Machine Learning con todo tipo de elementos visuales, bloques flotantes, efectos 3D, colores gradientes y por supuesto redes neuronales que conectan entre si y conectan todos los elementos del dashboard y el frontend!
1383
+ Puedes realizar el diseño visual mucho mas futurista, impactante, con colores gradientes, que el frontend grite en su totalidad que es una plataforma de trading algoritmico y MAchine learning de alto rendimiento y por supuesto con bloques flotantes, efectos 3D y todo el Dashboard bloques y elementos conectados por innumerables redes neuronales que se conectan entre si y conectan todos los elementos del frontend en sus diferentes paginas y que son reactivas al estimulo del usuario!
1384
+ Quiero que todas las paginas tengan el diseño de la pagina del dashboard y ademas quiero que añadas mas efectos 3D elementos flotantes e interactivos entre si y redes neuronales mas visibles e interactivas en todas las paginas del frontend
1385
+ Quiero que implementes el mismo diseño visual y elementos graficos de la pagina del Dashboard a todas las demas paginas: Datasets, Training, Models y System Health!
1386
+ Por, favor añade elementos visuales de redes neuronales interactivas y todas las paginas del frontend, no solamente en el dashboard, y quiero que tambien implementes un aspecto visual mas futurista en todo el frontend mas elementos visuales interactivos, mucho mas efectos 3D y mas colores gradientes con alto contraste!
1387
+ Por, favor añade elementos visuales de redes neuronales interactivas y todas las paginas del frontend, no solamente en el dashboard, y quiero que tambien implementes un aspecto visual mas futurista en todo el frontend mas elementos visuales interactivos, mucho mas efectos 3D y mas colores gradientes con alto contraste!
1388
+ Por, favor añade elementos visuales de redes neuronales interactivas y todas las paginas del frontend, no solamente en el dashboard, y quiero que tambien implementes un aspecto visual mas futurista en todo el frontend mas elementos visuales interactivos, mucho mas efectos 3D y mas colores gradientes con alto contraste!
1389
+ Por, favor añade elementos visuales de redes neuronales interactivas y todas las paginas del frontend, no solamente en el dashboard, y quiero que tambien implementes un aspecto visual mas futurista en todo el frontend mas elementos visuales interactivos, mucho mas efectos 3D y mas colores gradientes con alto contraste!
1390
+ Por, favor añade elementos visuales de redes neuronales interactivas y todas las paginas del frontend, no solamente en el dashboard, y quiero que tambien implementes un aspecto visual mas futurista en todo el frontend mas elementos visuales interactivos, mucho mas efectos 3D y mas colores gradientes con alto contraste!
system-health.html ADDED
@@ -0,0 +1,214 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ <!DOCTYPE html>
2
+ <html lang="es">
3
+ <head>
4
+ <meta charset="UTF-8">
5
+ <meta name="viewport" content="width=device-width, initial-scale=1.0">
6
+ <title>Hiper Feature Pipeline - System Health</title>
7
+ <script src="https://cdn.tailwindcss.com"></script>
8
+ <link href="https://unpkg.com/[email protected]/dist/aos.css" rel="stylesheet">
9
+ <script src="https://unpkg.com/[email protected]/dist/aos.js"></script>
10
+ <script src="https://cdn.jsdelivr.net/npm/feather-icons/dist/feather.min.js"></script>
11
+ <script src="https://unpkg.com/feather-icons"></script>
12
+ <style>
13
+ .glass-effect {
14
+ background: rgba(255, 255, 255, 0.1);
15
+ backdrop-filter: blur(10px);
16
+ border: 1px solid rgba(255, 255, 255, 0.2);
17
+ }
18
+ </style>
19
+ </head>
20
+ <body class="bg-gray-900 text-white min-h-screen">
21
+ <!-- Navigation -->
22
+ <nav class="glass-effect fixed w-full z-50">
23
+ <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8">
24
+ <div class="flex justify-between h-16 items-center">
25
+ <div class="flex items-center">
26
+ <i data-feather="cpu" class="h-极狐 w-8 text-blue-400"></i>
27
+ <span class="ml-2 text-xl font-bold">Hiper Feature Pipeline</span>
28
+ </div>
29
+ <div class="hidden md:block">
30
+ <div class="ml-10 flex items-baseline space-x-4">
31
+ <a href="index.html" class="px-3 py-2 rounded-md text-sm font-medium hover:bg-blue-600">Dashboard</a>
32
+ <a href="datasets.html" class="px-3 py-2 rounded-md text-sm font-medium hover:bg-blue-600">Datasets</a>
33
+ <a href="training.html" class="px-3 py-2 rounded-md text-sm font-medium hover:极狐-600">Training</a>
34
+ <a href="models.html" class="px-3 py-2 rounded-md text-sm font-medium hover:bg-blue-600">Models</a>
35
+ <a href="system-health.html" class="px-3 py-2 rounded-md text-sm font-medium bg-blue-700 text-white">System Health</a>
36
+ </div>
37
+ </div>
38
+ </div>
39
+ </div>
40
+ </nav>
41
+
42
+ <!-- Main Content -->
43
+ <main class="pt-20 pb-16">
44
+ <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8">
45
+ <!-- Header -->
46
+ <div class="text-center py-12" data-aos="fade-down">
47
+ <h1 class="text-4xl font-bold mb-4">System Health</h1>
48
+ <p class="text-xl text-gray-300">Monitoreo y métricas del sistema en tiempo real</p>
49
+ </div>
50
+
51
+ <!-- System Status Overview -->
52
+ <div class="grid grid-cols-1 md:grid-cols-2 lg:grid-cols-4 gap-6 mb-12">
53
+ <div class="glass-effect rounded-lg p-6 text-center" data-aos="fade-up" data-aos-delay="100">
54
+ <div class="p-3 bg-green-500 rounded-full w-12 h-12 mx-auto mb-4">
55
+ <i data-feather="database" class="h-6 w-6 mx-auto"></i>
56
+ </div>
57
+ <h3 class="font-bold mb-2">Event Store</h3>
58
+ <p class="text-sm text-gray-400">SurrealDB</p>
59
+ <span class="mt-2 inline-block px-3 py-1 bg-green-500 rounded-full text-xs">Online</span>
60
+ </div>
61
+ <div class="glass-effect rounded-lg p-6 text-center" data-aos="fade-up" data-aos-delay="200">
62
+ <div class="p-3 bg-green-500 rounded-full w-12 h-12 mx-auto mb-4">
63
+ <i data-feather="server" class="h-6 w-6 mx-auto"></i>
64
+ </div>
65
+ <h3 class="font-bold mb-2">Read Models</h3>
66
+ <p class="text-sm text-gray-400">DuckDB</p>
67
+ <span class="mt-2 inline-block px-3 py-1 bg-green-500 rounded-full text-xs">Online</span>
68
+ </div>
69
+ <div class="glass-effect rounded-lg p-6 text-center" data-aos="fade-up" data-aos-delay="300">
70
+ <div class="p-3 bg-yellow-500 rounded-full w-12 h-12 mx-auto mb-4">
71
+ <i data-feather="activity" class="h-6 w-6 mx-auto"></i>
72
+ </div>
73
+ <h3 class="font-bold mb-2">Training Engine</h3>
74
+ <p class="text-sm text-gray-400">Candle</p>
75
+ <span class="mt-2 inline-block px-3 py-1 bg-yellow-500 rounded-full text-xs">Warning</span>
76
+ </div>
77
+ <div class="glass-effect rounded-lg p-6 text-center" data-aos="fade-up" data-aos-delay="400">
78
+ <div class="p-3 bg-green-500 rounded-full w-12 h-12 mx-auto mb-4">
79
+ <i data-feather="box" class="h-6 w-6 mx-auto"></i>
80
+ </div>
81
+ <h3 class="font-bold mb-2">ONNX Runtime</h3>
82
+ <p class="text-sm text-gray-400">Optimized</p>
83
+ <span class="mt-2 inline-block px-3 py-1 bg-green-500 rounded-full text-xs">Online</span>
84
+ </div>
85
+ </div>
86
+
87
+ <!-- Resource Usage -->
88
+ <div class="glass-effect rounded-lg p-6 mb-12" data-aos="fade-up">
89
+ <h2 class="text-2xl font-bold mb-6">Uso de Recursos</h2>
90
+ <div class="grid grid-cols-1 md:grid-cols-2 gap-6">
91
+ <div>
92
+ <h3 class="font-bold mb-4">CPU Usage</h3>
93
+ <div class="bg-gray-800 rounded-lg p-4">
94
+ <div class="flex justify-between mb-2">
95
+ <span>Current Usage</span>
96
+ <span>65%</span>
97
+ </div>
98
+ <div class="w-full bg-gray-700 rounded-full h-3">
99
+ <div class="bg-blue-500 h-3 rounded-full" style="width: 65%"></div>
100
+ </div>
101
+ <div class="flex justify-between mt-4 text-sm">
102
+ <span>Min: 15%</span>
103
+ <span>Max: 85%</span>
104
+ </div>
105
+ </div>
106
+ </div>
107
+ <div>
108
+ <h3 class="font-bold mb-4">Memory Usage</h3>
109
+ <div class="bg-gray-800 rounded-lg p-4">
110
+ <div class="flex justify-between mb-2">
111
+ <span>Current Usage</span>
112
+ <span>78%</span>
113
+ </div>
114
+ <div class="w-full bg-gray-700 rounded-full h-3">
115
+ <div class="bg-green-500 h-3 rounded-full" style="width: 78%"></div>
116
+ </div>
117
+ <div class="flex justify-between mt-4 text-sm">
118
+ <span>Min: 25%</span>
119
+ <span>Max: 92%</span>
120
+ </div>
121
+ </div>
122
+ </div>
123
+ <div>
124
+ <h3 class="font-bold mb-4">Storage Usage</h3>
125
+ <div class="bg-gray-800 rounded-lg p-4">
126
+ <div class="flex justify-between mb-2">
127
+ <span>Current Usage</span>
128
+ <span>45%</span>
129
+ </div>
130
+ <div class="w-full bg-gray-700 rounded-full h-3">
131
+ <div class="bg-purple-500 h-3 rounded-full" style="width: 45%"></div>
132
+ </div>
133
+ <div class="flex justify-between mt-4 text-sm">
134
+ <span>Used: 225GB</span>
135
+ <span>Total: 500GB</span>
136
+ </div>
137
+ </div>
138
+ </div>
139
+ <div>
140
+ <h3 class="font-bold mb-4">Network I/O</h3>
141
+ <div class="bg-gray-800 rounded-lg p-4">
142
+ <div class="flex justify-between mb-2">
143
+ <span>Current Traffic</span>
144
+ <span>125 Mbps</span>
145
+ </div>
146
+ <div class="w-full bg-gray-700 rounded-full h-3">
147
+ <div class="bg-yellow-500 h-3 rounded-full" style="width: 62%"></div>
148
+ </div>
149
+ <div class="flex justify-between mt-4 text-sm">
150
+ <span>In: 85 Mbps</span>
151
+ <span>Out: 40 Mbps</span>
152
+ </div>
153
+ </div>
154
+ </div>
155
+ </div>
156
+ </div>
157
+
158
+ <!-- Event Processing Metrics -->
159
+ <div class="glass-effect rounded-lg p-6 mb-12" data-aos="fade-up">
160
+ <h2 class="text-2xl font-bold mb-6">Métricas de Procesamiento de Eventos</h2>
161
+ <div class="grid grid-cols-1 md:grid-cols-3 gap-6">
162
+ <div class="text-center p-4 bg-gray-800 rounded-lg">
163
+ <div class="text-3xl font-bold text-blue-400">1,245</div>
164
+ <div class="text-sm text-gray-400 mt-1">Eventos/Minuto</div>
165
+ </div>
166
+ <div class="text-center p-4 bg-gray-800 rounded-lg">
167
+ <div class="text-3xl font-bold text-green-400">23ms</div>
168
+ <div class="text-sm text-gray-400 mt-1">Latencia Promedio</div>
169
+ </div>
170
+ <div class="text-center p-4 bg-gray-800 rounded-lg">
171
+ <div class="text-3xl font-bold text-purple-400">99.98%</div>
172
+ <div class="text-sm text-gray-400 mt-1">Disponibilidad</div>
173
+ </div>
174
+ </div>
175
+ </div>
176
+
177
+ <!-- System Logs -->
178
+ <div class="glass-effect rounded-lg p-6" data-aos="fade-up">
179
+ <h2 class="text-2xl font-bold mb-6">Registros del Sistema</h2>
180
+ <div class="bg-gray-800 rounded-lg p-4 h-64 overflow-y-auto">
181
+ <div class="text-sm font-mono space-y-2">
182
+ <div class="text-green-400">[INFO] 2023-12-07 10:23:45 - Event Store connection established</div>
183
+ <div class="text-blue-400">[DEBUG] 2023-12-07 10:23:46 - Processing DatasetIngestedEvent for SP500_2023</div>
184
+ <div class="text-yellow-400">[WARN] 2023-12-07 10:23:47 - High memory usage detected in training engine</div>
185
+ <div class="text-green-400">[INFO] 2023-12-07 10:23:48 - Training session LSTM_SP500_v2 started</div>
186
+ <div class="text-blue-400">[DEBUG] 2023-12-07 10:23:49 - Feature engineering completed for NASDAQ_Stocks</div>
187
+ <div class="text-green-400">[INFO] 2023-12-07 10:23:50 - ONNX export completed for Transformer_NASDAQ</div>
188
+ <div class="text-gray-400">[INFO] 2023-12-07 10:23:51 - System health check completed successfully</div>
189
+ </div>
190
+ </div>
191
+ </div>
192
+ </div>
193
+ </main>
194
+
195
+ <!-- Footer -->
196
+ <footer class="glass-effect mt-12 py-6">
197
+ <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 text-center">
198
+ <p class="text-gray-400">Hiper Feature Pipeline Store v6.0 - System Health Monitor</p>
199
+ </div>
200
+ </footer>
201
+
202
+ <script>
203
+ // Initialize AOS
204
+ AOS.init({
205
+ duration: 800,
206
+ easing: 'ease-in-out',
207
+ once: true
208
+ });
209
+
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+ // Initialize Feather Icons
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+ feather.replace();
212
+ </script>
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+ </body>
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+ </html>
training.html ADDED
@@ -0,0 +1,205 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ <!DOCTYPE html>
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+ <html lang="es">
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+ <head>
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+ <meta charset="UTF-8">
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+ <meta name="viewport" content="width=device-width, initial-scale=1.0">
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+ <title>Hiper Feature Pipeline - Training Monitor</title>
7
+ <script src="https://cdn.tailwindcss.com"></script>
8
+ <link href="https://unpkg.com/[email protected]/dist/aos.css" rel="stylesheet">
9
+ <script src="https://unpkg.com/[email protected]/dist/aos.js"></script>
10
+ <script src="https://cdn.jsdelivr.net/npm/feather-icons/dist/feather.min.js"></script>
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+ <script src="https://unpkg.com/feather-icons"></script>
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+ <style>
13
+ .glass-effect {
14
+ background: rgba(255, 255, 255, 0.1);
15
+ backdrop-filter: blur(10px);
16
+ border: 1px solid rgba(255, 255, 255, 0.2);
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+ }
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+ .progress-bar {
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+ transition: width 0.5s ease-in-out;
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+ }
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+ </style>
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+ </head>
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+ <body class="bg-gray-900 text-white min-h-screen">
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+ <!-- Navigation -->
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+ <nav class="glass-effect fixed w-full z-50">
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+ <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8">
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+ <div class="flex justify-between h-16 items-center">
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+ <div class="flex items-center">
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+ <i data-feather="cpu" class="h-8 w-8 text-blue-400"></i>
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+ <span class="ml-2 text-xl font-bold">Hiper Feature Pipeline</span>
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+ </div>
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+ <div class="hidden md:block">
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+ <div class="ml-10 flex items-baseline space-x-4">
34
+ <a href="index.html" class="px-3 py-2 rounded-md text-sm font-medium hover:bg-blue-600">Dashboard</a>
35
+ <a href="datasets.html" class="px-3 py-2 rounded-md text-sm font-medium hover:bg-blue-600">Datasets</a>
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+ <a href="training.html" class="px-3 py-2 rounded-md text-sm font-medium bg-blue-700 text-white">Training</a>
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+ <a href="models.html" class="px-3 py-2 rounded-md text-sm font-medium hover:bg-blue-600">Models</a>
38
+ <a href="system-health.html" class="px-3 py-2 rounded-md text-sm font-medium hover:bg-blue-600">System Health</a>
39
+ </div>
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+ </div>
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+ </div>
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+ </div>
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+ </nav>
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+
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+ <!-- Main Content -->
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+ <main class="pt-20 pb-16">
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+ <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8">
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+ <!-- Header -->
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+ <div class="text-center py-12" data-aos="fade-down">
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+ <h1 class="text-4xl font-bold mb-4">Training Monitor</h1>
51
+ <p class="text-xl text-gray-300">Seguimiento y gestión de sesiones de entrenamiento con CQRS</p>
52
+ </div>
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+
54
+ <!-- Start Training Section -->
55
+ <div class="glass-effect rounded-lg p-6 mb-12" data-aos="fade-up">
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+ <h2 class="text-2xl font-bold mb-6">Iniciar Nueva Sesión de Entrenamiento</h2>
57
+ <div class="grid grid-cols-1 md:grid-cols-2 gap-6">
58
+ <div>
59
+ <label class="block text-sm font-medium mb-2">Model Architecture</label>
60
+ <select class="w-full bg-gray-800 border border-gray-700 rounded-lg p-3">
61
+ <option>LSTM Neural Network</option>
62
+ <option>Transformer Architecture</option>
63
+ <option>Temporal Convolution Network</option>
64
+ <option>GRU Network</option>
65
+ </select>
66
+ </div>
67
+ <div>
68
+ <label class="block text-sm font-medium mb-2">Dataset</label>
69
+ <select class="w-full bg-gray-800 border border-gray-700 rounded-lg p-3">
70
+ <option>SP500_2023</option>
71
+ <option>NASDAQ_Stocks</option>
72
+ <option>Crypto_Market</option>
73
+ <option>Forex_Major_Pairs</option>
74
+ </select>
75
+ </div>
76
+ <div>
77
+ <label class="block text-sm font-medium mb-2">Epochs</label>
78
+ <input type="number" class="w-full bg-gray-800 border border-gray-700 rounded-lg p-3" value="100">
79
+ </div>
80
+ <div>
81
+ <label class="block text-sm font-medium mb-2">Batch Size</label>
82
+ <input type="number" class="w-full bg-gray-800 border border-gray-700 rounded-lg p-3" value="32">
83
+ </div>
84
+ </div>
85
+ <button class="mt-6 w-full py-3 bg-green-600 hover:bg-green-700 rounded-lg font-medium">Iniciar Entrenamiento</button>
86
+ </div>
87
+
88
+ <!-- Active Training Sessions -->
89
+ <h2 class="text-2xl font-bold mb-6" data-aos="fade-up">Sesiones Activas</h2>
90
+ <div class="glass-effect rounded-lg p-6 mb-12" data-aos="fade-up">
91
+ <div class="flex items-center justify-between mb-6">
92
+ <div>
93
+ <h3 class="font-bold text-lg">LSTM_SP500_Training</h3>
94
+ <p class="text-sm text-gray-400">Started 2 hours ago</p>
95
+ </div>
96
+ <span class="px-3 py-1 bg-yellow-500 rounded-full text-sm">Training</span>
97
+ </div>
98
+
99
+ <div class="mb-6">
100
+ <div class="flex justify-between mb-2">
101
+ <span>Progress</span>
102
+ <span>65%</span>
103
+ </div>
104
+ <div class="w-full bg-gray-700 rounded-full h-3">
105
+ <div class="bg-blue-500 h-3 rounded-full progress-bar" style="width: 65%"></div>
106
+ </div>
107
+ </div>
108
+
109
+ <div class="grid grid-cols-2 md:grid-cols-4 gap-4 mb-6">
110
+ <div class="text-center p-3 bg-gray-800 rounded-lg">
111
+ <div class="text-xl font-bold">32/100</div>
112
+ <div class="text-sm text-gray-400">Epochs</div>
113
+ </div>
114
+ <div class="text-center p-3 bg-gray-800 rounded-lg">
115
+ <div class="text-xl font-bold">0.0234</div>
116
+ <div class="text-sm text-gray-400">Training Loss</div>
117
+ </div>
118
+ <div class="text-center p-3 bg-gray-800 rounded-lg">
119
+ <div class="text-xl font-bold">0.0312</div>
120
+ <div class="text-sm text-gray-400">Validation Loss</div>
121
+ </div>
122
+ <div class="text-center p-3 bg-gray-800 rounded-lg">
123
+ <div class="text-xl font-bold">94.7%</div>
124
+ <div class="text-sm text-gray-400">Accuracy</div>
125
+ </div>
126
+ </div>
127
+
128
+ <div class="flex space-x-3">
129
+ <button class="flex-1 py-2 bg-blue-600 hover:bg-blue-700 rounded-lg">View Details</button>
130
+ <button class="flex-1 py-2 bg-yellow-600 hover:bg-yellow-700 rounded-lg">Pause</button>
131
+ <button class="flex-1 py-2 bg-red-600 hover:bg-red-700 rounded-lg">Stop</button>
132
+ </div>
133
+ </div>
134
+
135
+ <!-- Training History -->
136
+ <h2 class="text-2xl font-bold mb-6" data-aos="fade-up">Historial de Entrenamiento</h2>
137
+ <div class="overflow-x-auto">
138
+ <table class="w-full glass-effect rounded-lg" data-aos="fade-up">
139
+ <thead>
140
+ <tr class="border-b border-gray-700">
141
+ <th class="px-6 py-3 text-left">Model</th>
142
+ <th class="px-6 py-3 text-left">Dataset</th>
143
+ <th class="px-6 py-3 text-left">Status</th>
144
+ <th class="px-6 py-3 text-left">Accuracy</th>
145
+ <th class="px-6 py-3 text-left">Duration</th>
146
+ <th class="px-6 py-3 text-left">Actions</th>
147
+ </tr>
148
+ </thead>
149
+ <tbody class="divide-y divide-gray-700">
150
+ <tr>
151
+ <td class="px-6 py-4">Transformer_NASDAQ</td>
152
+ <td class="px-6 py-4">NASDAQ_Stocks</td>
153
+ <td class="px-6 py-4"><span class="px-2 py-1 bg-green-500 rounded-full text-xs">Completed</span></td>
154
+ <td class="px-6 py-4">96.2%</td>
155
+ <td class="px-6 py-4">4h 23m</td>
156
+ <td class="px-6 py-4">
157
+ <button class="text-blue-400 hover:text-blue-300">View</button>
158
+ </td>
159
+ </tr>
160
+ <tr>
161
+ <td class="px-6 py-4">TCN_Forex</td>
162
+ <td class="px-6 py-4">Forex_Major_Pairs</td>
163
+ <td class="px-6 py-4"><span class="px-2 py-1 bg-green-500 rounded-full text-xs">Completed</span></td>
164
+ <td class="px-6 py-4">92.8%</td>
165
+ <td class="px-6 py-4">3h 45m</td>
166
+ <td class="px-6 py-4">
167
+ <button class="text-blue-400 hover:text-blue-300">View</button>
168
+ </td>
169
+ </tr>
170
+ <tr>
171
+ <td class="px-6 py-4">GRU_Crypto</td>
172
+ <td class="px-6 py-4">Crypto_Market</td>
173
+ <td class="px-6 py-4"><span class="px-2 py-1 bg-red-500 rounded-full text-xs">Failed</span></td>
174
+ <td class="px-6 py-4">-</td>
175
+ <td class="px-6 py-4">1h 12m</td>
176
+ <td class="px-6 py-4">
177
+ <button class="text-blue-400 hover:text-blue-300">View</button>
178
+ </td>
179
+ </tr>
180
+ </tbody>
181
+ </table>
182
+ </div>
183
+ </div>
184
+ </main>
185
+
186
+ <!-- Footer -->
187
+ <footer class="glass-effect mt-12 py-6">
188
+ <div class="max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 text-center">
189
+ <p class="text-gray-400">Hiper Feature Pipeline Store v6.0 - Training Monitor</p>
190
+ </div>
191
+ </footer>
192
+
193
+ <script>
194
+ // Initialize AOS
195
+ AOS.init({
196
+ duration: 800,
197
+ easing: 'ease-in-out',
198
+ once: true
199
+ });
200
+
201
+ // Initialize Feather Icons
202
+ feather.replace();
203
+ </script>
204
+ </body>
205
+ </html>