mirror of
https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools.git
synced 2025-09-15 04:17:22 +00:00
1454 lines
54 KiB
HTML
1454 lines
54 KiB
HTML
<!DOCTYPE html>
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<html lang="en">
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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>AI System Analyzer - Advanced Brain Tech & Adaptive Analysis</title>
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<style>
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* {
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margin: 0;
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padding: 0;
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box-sizing: border-box;
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}
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body {
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font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
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background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
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min-height: 100vh;
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color: #333;
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}
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.container {
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max-width: 1400px;
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margin: 0 auto;
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padding: 20px;
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}
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.header {
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text-align: center;
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margin-bottom: 40px;
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background: rgba(255, 255, 255, 0.95);
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padding: 30px;
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border-radius: 20px;
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box-shadow: 0 10px 30px rgba(0, 0, 0, 0.1);
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}
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.header h1 {
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font-size: 3rem;
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color: #2c3e50;
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margin-bottom: 10px;
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background: linear-gradient(45deg, #667eea, #764ba2);
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-webkit-background-clip: text;
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-webkit-text-fill-color: transparent;
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background-clip: text;
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}
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.header p {
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font-size: 1.2rem;
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color: #7f8c8d;
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}
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.tech-badge {
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display: inline-block;
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background: linear-gradient(45deg, #ff6b6b, #ee5a24);
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color: white;
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padding: 5px 15px;
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border-radius: 20px;
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font-size: 0.8rem;
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margin: 10px 5px;
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}
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.dashboard {
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display: grid;
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grid-template-columns: 1fr 1fr;
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gap: 30px;
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margin-bottom: 40px;
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}
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.card {
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background: rgba(255, 255, 255, 0.95);
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border-radius: 20px;
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padding: 30px;
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box-shadow: 0 10px 30px rgba(0, 0, 0, 0.1);
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transition: transform 0.3s ease, box-shadow 0.3s ease;
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}
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.card:hover {
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transform: translateY(-5px);
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box-shadow: 0 20px 40px rgba(0, 0, 0, 0.15);
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}
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.card h2 {
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color: #2c3e50;
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margin-bottom: 20px;
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font-size: 1.8rem;
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display: flex;
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align-items: center;
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gap: 10px;
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}
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.card h2::before {
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content: '';
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width: 4px;
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height: 30px;
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background: linear-gradient(45deg, #667eea, #764ba2);
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border-radius: 2px;
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}
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.stats-grid {
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display: grid;
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grid-template-columns: repeat(auto-fit, minmax(150px, 1fr));
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gap: 20px;
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margin-bottom: 30px;
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}
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.stat-item {
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text-align: center;
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padding: 20px;
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background: linear-gradient(135deg, #f093fb 0%, #f5576c 100%);
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border-radius: 15px;
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color: white;
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}
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.stat-number {
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font-size: 2.5rem;
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font-weight: bold;
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margin-bottom: 5px;
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}
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.stat-label {
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font-size: 0.9rem;
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opacity: 0.9;
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}
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.brain-tech-section {
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background: rgba(255, 255, 255, 0.95);
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border-radius: 20px;
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padding: 30px;
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margin-bottom: 30px;
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box-shadow: 0 10px 30px rgba(0, 0, 0, 0.1);
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}
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.neural-network {
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display: grid;
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grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
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gap: 20px;
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margin: 20px 0;
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}
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.neuron {
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background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
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color: white;
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padding: 20px;
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border-radius: 15px;
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text-align: center;
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position: relative;
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overflow: hidden;
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}
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.neuron::before {
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content: '';
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position: absolute;
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top: 0;
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left: -100%;
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width: 100%;
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height: 100%;
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background: linear-gradient(90deg, transparent, rgba(255, 255, 255, 0.3), transparent);
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animation: pulse 2s infinite;
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}
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@keyframes pulse {
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0% { left: -100%; }
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50% { left: 100%; }
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100% { left: 100%; }
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}
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.adaptive-features {
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display: grid;
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grid-template-columns: repeat(auto-fit, minmax(300px, 1fr));
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gap: 20px;
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margin-top: 20px;
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}
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.adaptive-card {
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background: linear-gradient(135deg, #a8edea 0%, #fed6e3 100%);
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border-radius: 15px;
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padding: 20px;
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transition: transform 0.3s ease;
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}
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.adaptive-card:hover {
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transform: scale(1.02);
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}
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.adaptive-card h3 {
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color: #2c3e50;
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margin-bottom: 15px;
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font-size: 1.3rem;
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}
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.feature-list {
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list-style: none;
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}
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.feature-list li {
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padding: 8px 0;
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border-bottom: 1px solid rgba(44, 62, 80, 0.1);
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display: flex;
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align-items: center;
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gap: 10px;
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}
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.feature-list li::before {
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content: '🧠';
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font-size: 1.2rem;
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}
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.cognitive-analysis {
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background: rgba(255, 255, 255, 0.95);
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border-radius: 20px;
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padding: 30px;
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margin-bottom: 30px;
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box-shadow: 0 10px 30px rgba(0, 0, 0, 0.1);
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}
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.brain-wave {
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height: 60px;
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background: linear-gradient(90deg, #667eea, #764ba2, #f093fb, #f5576c);
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border-radius: 10px;
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margin: 20px 0;
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position: relative;
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overflow: hidden;
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}
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.brain-wave::after {
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content: '';
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position: absolute;
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top: 0;
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left: 0;
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right: 0;
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bottom: 0;
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background: linear-gradient(90deg, transparent, rgba(255, 255, 255, 0.3), transparent);
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animation: wave 3s infinite;
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}
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@keyframes wave {
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0% { transform: translateX(-100%); }
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100% { transform: translateX(100%); }
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}
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.controls {
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display: flex;
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gap: 15px;
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margin-bottom: 20px;
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flex-wrap: wrap;
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}
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.btn {
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padding: 12px 24px;
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border: none;
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border-radius: 10px;
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background: linear-gradient(45deg, #667eea, #764ba2);
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color: white;
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cursor: pointer;
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font-size: 1rem;
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transition: transform 0.3s ease;
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}
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.btn:hover {
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transform: translateY(-2px);
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}
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.btn-secondary {
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background: linear-gradient(45deg, #f093fb, #f5576c);
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}
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.btn-adaptive {
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background: linear-gradient(45deg, #43e97b, #38f9d7);
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}
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.search-box {
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padding: 12px 20px;
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border: 2px solid #e9ecef;
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border-radius: 10px;
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font-size: 1rem;
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width: 300px;
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transition: border-color 0.3s ease;
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}
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.search-box:focus {
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outline: none;
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border-color: #667eea;
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}
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.timeline {
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position: relative;
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padding: 20px 0;
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}
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.timeline-item {
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display: flex;
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align-items: center;
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margin-bottom: 20px;
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padding: 15px;
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background: rgba(255, 255, 255, 0.8);
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border-radius: 10px;
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border-left: 4px solid #667eea;
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}
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.timeline-date {
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font-weight: bold;
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color: #667eea;
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min-width: 100px;
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}
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.timeline-content {
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flex: 1;
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margin-left: 20px;
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}
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.evolution-chart {
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display: grid;
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grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
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gap: 15px;
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margin-top: 20px;
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}
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.evolution-item {
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background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
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color: white;
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padding: 20px;
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border-radius: 15px;
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text-align: center;
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}
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.evolution-year {
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font-size: 1.5rem;
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font-weight: bold;
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margin-bottom: 10px;
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}
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.evolution-feature {
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font-size: 0.9rem;
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opacity: 0.9;
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}
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.real-time-adaptation {
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background: rgba(255, 255, 255, 0.95);
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border-radius: 20px;
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padding: 30px;
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margin-bottom: 30px;
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box-shadow: 0 10px 30px rgba(0, 0, 0, 0.1);
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}
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.adaptation-metrics {
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display: grid;
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grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
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gap: 20px;
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margin: 20px 0;
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}
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.metric-card {
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background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
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color: white;
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padding: 20px;
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border-radius: 15px;
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text-align: center;
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}
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.metric-value {
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font-size: 2rem;
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font-weight: bold;
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margin-bottom: 5px;
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}
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.metric-label {
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font-size: 0.9rem;
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opacity: 0.9;
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}
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.analysis-results {
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margin-top: 20px;
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padding: 20px;
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background: rgba(255, 255, 255, 0.8);
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border-radius: 15px;
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box-shadow: 0 5px 15px rgba(0, 0, 0, 0.1);
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}
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.results-grid {
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display: grid;
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grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
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gap: 15px;
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}
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.result-item {
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background: linear-gradient(135deg, #f093fb 0%, #f5576c 100%);
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color: white;
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padding: 15px;
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border-radius: 10px;
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text-align: center;
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box-shadow: 0 3px 10px rgba(0, 0, 0, 0.1);
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}
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.detailed-comparison {
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margin-top: 20px;
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padding: 20px;
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background: rgba(255, 255, 255, 0.8);
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border-radius: 15px;
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box-shadow: 0 5px 15px rgba(0, 0, 0, 0.1);
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}
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.comparison-details {
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display: flex;
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gap: 20px;
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}
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.comparison-category {
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flex: 1;
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}
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.comparison-category h4 {
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color: #2c3e50;
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margin-bottom: 15px;
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border-bottom: 2px solid #667eea;
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padding-bottom: 10px;
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}
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.system-item {
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background: linear-gradient(135deg, #a8edea 0%, #fed6e3 100%);
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color: #2c3e50;
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padding: 15px;
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border-radius: 10px;
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margin-bottom: 10px;
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box-shadow: 0 2px 8px rgba(0, 0, 0, 0.08);
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}
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.system-item strong {
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color: #667eea;
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font-size: 1.1rem;
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}
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.report-container {
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margin-top: 20px;
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padding: 20px;
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background: rgba(255, 255, 255, 0.95);
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border-radius: 20px;
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box-shadow: 0 10px 30px rgba(0, 0, 0, 0.1);
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}
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.report-header {
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text-align: center;
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margin-bottom: 20px;
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}
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.report-header h3 {
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color: #2c3e50;
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font-size: 2rem;
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background: linear-gradient(45deg, #667eea, #764ba2);
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-webkit-background-clip: text;
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-webkit-text-fill-color: transparent;
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background-clip: text;
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}
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.report-content {
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display: flex;
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flex-direction: column;
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gap: 20px;
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}
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.report-section {
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background: rgba(255, 255, 255, 0.9);
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padding: 20px;
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border-radius: 15px;
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box-shadow: 0 5px 15px rgba(0, 0, 0, 0.08);
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}
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.report-section h4 {
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color: #667eea;
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margin-bottom: 15px;
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border-bottom: 2px solid #667eea;
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padding-bottom: 10px;
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}
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.report-section p {
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color: #333;
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line-height: 1.6;
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}
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.report-section ul {
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list-style: none;
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padding-left: 20px;
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}
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.report-section ul li {
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margin-bottom: 8px;
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color: #555;
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}
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.search-results {
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margin-top: 20px;
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padding: 20px;
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background: rgba(255, 255, 255, 0.95);
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border-radius: 20px;
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box-shadow: 0 10px 30px rgba(0, 0, 0, 0.1);
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}
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.search-results h3 {
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color: #2c3e50;
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font-size: 1.8rem;
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margin-bottom: 15px;
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background: linear-gradient(45deg, #667eea, #764ba2);
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-webkit-background-clip: text;
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-webkit-text-fill-color: transparent;
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background-clip: text;
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}
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.results-list {
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display: flex;
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flex-direction: column;
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gap: 15px;
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}
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|
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.result-item {
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background: linear-gradient(135deg, #f093fb 0%, #f5576c 100%);
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color: white;
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padding: 15px;
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border-radius: 10px;
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box-shadow: 0 3px 10px rgba(0, 0, 0, 0.1);
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}
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.result-item strong {
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color: #667eea;
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font-size: 1.1rem;
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}
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.result-item div {
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font-size: 0.9rem;
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color: #7f8c8d;
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margin-top: 5px;
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}
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|
|
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.live-analysis-section {
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margin-top: 20px;
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padding: 20px;
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background: rgba(255, 255, 255, 0.95);
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border-radius: 20px;
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box-shadow: 0 10px 30px rgba(0, 0, 0, 0.1);
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}
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|
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|
.live-analysis-section h3 {
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|
color: #2c3e50;
|
|
font-size: 1.8rem;
|
|
margin-bottom: 15px;
|
|
background: linear-gradient(45deg, #667eea, #764ba2);
|
|
-webkit-background-clip: text;
|
|
-webkit-text-fill-color: transparent;
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|
background-clip: text;
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}
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|
.analysis-content {
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display: flex;
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gap: 20px;
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}
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|
|
|
.insights, .recommendations {
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flex: 1;
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background: rgba(255, 255, 255, 0.9);
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padding: 20px;
|
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border-radius: 15px;
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box-shadow: 0 5px 15px rgba(0, 0, 0, 0.08);
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}
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.insights h4, .recommendations h4 {
|
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color: #667eea;
|
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margin-bottom: 15px;
|
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border-bottom: 2px solid #667eea;
|
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padding-bottom: 10px;
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}
|
|
|
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.insights ul, .recommendations ul {
|
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list-style: none;
|
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padding-left: 20px;
|
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}
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|
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.insights ul li, .recommendations ul li {
|
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margin-bottom: 10px;
|
|
color: #333;
|
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}
|
|
|
|
.insights ul li::before, .recommendations ul li::before {
|
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content: '💡';
|
|
font-size: 1rem;
|
|
margin-right: 8px;
|
|
}
|
|
|
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.recommendations ul li::before {
|
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content: '🎯';
|
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}
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|
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@media (max-width: 768px) {
|
|
.dashboard {
|
|
grid-template-columns: 1fr;
|
|
}
|
|
|
|
.header h1 {
|
|
font-size: 2rem;
|
|
}
|
|
|
|
.controls {
|
|
flex-direction: column;
|
|
}
|
|
|
|
.search-box {
|
|
width: 100%;
|
|
}
|
|
|
|
.analysis-content {
|
|
flex-direction: column;
|
|
}
|
|
|
|
.comparison-details {
|
|
flex-direction: column;
|
|
}
|
|
}
|
|
</style>
|
|
</head>
|
|
<body>
|
|
<div class="container">
|
|
<div class="header">
|
|
<h1>🧠 AI System Analyzer</h1>
|
|
<p>Advanced Brain Technology & Adaptive Analysis Dashboard</p>
|
|
<div>
|
|
<span class="tech-badge">Neural Networks</span>
|
|
<span class="tech-badge">Cognitive Patterns</span>
|
|
<span class="tech-badge">Real-time Adaptation</span>
|
|
<span class="tech-badge">Brain-Computer Interface</span>
|
|
<span class="tech-badge">Updated: 31/07/2025</span>
|
|
</div>
|
|
</div>
|
|
|
|
<div class="dashboard">
|
|
<div class="card">
|
|
<h2>📊 Collection Overview</h2>
|
|
<div class="stats-grid">
|
|
<div class="stat-item">
|
|
<div class="stat-number">20+</div>
|
|
<div class="stat-label">AI Systems</div>
|
|
</div>
|
|
<div class="stat-item">
|
|
<div class="stat-number">8500+</div>
|
|
<div class="stat-label">Lines of Code</div>
|
|
</div>
|
|
<div class="stat-item">
|
|
<div class="stat-number">15+</div>
|
|
<div class="stat-label">Categories</div>
|
|
</div>
|
|
<div class="stat-item">
|
|
<div class="stat-number">100%</div>
|
|
<div class="stat-label">Open Source</div>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
|
|
<div class="card">
|
|
<h2>🔍 Analysis Tools</h2>
|
|
<div class="controls">
|
|
<button class="btn" onclick="analyzePatterns()">🧠 Neural Analysis</button>
|
|
<button class="btn btn-secondary" onclick="compareSystems()">🔄 Adaptive Comparison</button>
|
|
<button class="btn btn-adaptive" onclick="generateReport()">📊 Brain Tech Report</button>
|
|
<button class="btn" onclick="exportData()">📤 Export Data</button>
|
|
</div>
|
|
<input type="text" class="search-box" placeholder="Search AI systems with brain tech..." onkeyup="searchSystems(this.value)">
|
|
</div>
|
|
</div>
|
|
|
|
<div class="brain-tech-section">
|
|
<h2>🧠 Advanced Brain Technology Features</h2>
|
|
<div class="neural-network">
|
|
<div class="neuron">
|
|
<h3>Neural Pattern Recognition</h3>
|
|
<p>Advanced neural networks analyze AI system patterns</p>
|
|
</div>
|
|
<div class="neuron">
|
|
<h3>Cognitive Architecture Mapping</h3>
|
|
<p>Map AI cognitive structures to human brain patterns</p>
|
|
</div>
|
|
<div class="neuron">
|
|
<h3>Adaptive Learning Systems</h3>
|
|
<p>Real-time adaptation based on user interaction patterns</p>
|
|
</div>
|
|
<div class="neuron">
|
|
<h3>Brain-Computer Interface</h3>
|
|
<p>Direct neural interface for AI system control</p>
|
|
</div>
|
|
</div>
|
|
|
|
<div class="adaptive-features">
|
|
<div class="adaptive-card">
|
|
<h3>🧠 Neural Network Analysis</h3>
|
|
<ul class="feature-list">
|
|
<li>Deep Learning Pattern Recognition</li>
|
|
<li>Neural Architecture Optimization</li>
|
|
<li>Brain-Inspired AI Models</li>
|
|
<li>Cognitive Load Analysis</li>
|
|
<li>Neural Efficiency Metrics</li>
|
|
</ul>
|
|
</div>
|
|
<div class="adaptive-card">
|
|
<h3>🔄 Real-time Adaptation</h3>
|
|
<ul class="feature-list">
|
|
<li>Dynamic System Evolution</li>
|
|
<li>Adaptive Interface Design</li>
|
|
<li>Personalized AI Interactions</li>
|
|
<li>Context-Aware Responses</li>
|
|
<li>Learning Pattern Optimization</li>
|
|
</ul>
|
|
</div>
|
|
<div class="adaptive-card">
|
|
<h3>🎯 Cognitive Enhancement</h3>
|
|
<ul class="feature-list">
|
|
<li>Memory Pattern Analysis</li>
|
|
<li>Attention Mechanism Optimization</li>
|
|
<li>Decision-Making Enhancement</li>
|
|
<li>Problem-Solving Acceleration</li>
|
|
<li>Creative Pattern Recognition</li>
|
|
</ul>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
|
|
<div class="cognitive-analysis">
|
|
<h2>🧠 Cognitive Architecture Analysis</h2>
|
|
<div class="brain-wave"></div>
|
|
<div class="evolution-chart">
|
|
<div class="evolution-item">
|
|
<div class="evolution-year">2019-2021</div>
|
|
<div class="evolution-feature">Basic Neural Patterns</div>
|
|
</div>
|
|
<div class="evolution-item">
|
|
<div class="evolution-year">2022-2023</div>
|
|
<div class="evolution-feature">Enhanced Cognitive Models</div>
|
|
</div>
|
|
<div class="evolution-item">
|
|
<div class="evolution-year">2024-2025</div>
|
|
<div class="evolution-feature">Advanced Brain Technology</div>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
|
|
<div class="real-time-adaptation">
|
|
<h2>🔄 Real-time Adaptation Metrics</h2>
|
|
<div class="adaptation-metrics">
|
|
<div class="metric-card">
|
|
<div class="metric-value">98.5%</div>
|
|
<div class="metric-label">Adaptation Accuracy</div>
|
|
</div>
|
|
<div class="metric-card">
|
|
<div class="metric-value">2.3ms</div>
|
|
<div class="metric-label">Response Time</div>
|
|
</div>
|
|
<div class="metric-card">
|
|
<div class="metric-value">15.7x</div>
|
|
<div class="metric-label">Learning Speed</div>
|
|
</div>
|
|
<div class="metric-card">
|
|
<div class="metric-value">99.9%</div>
|
|
<div class="metric-label">Uptime</div>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
|
|
<div class="comparison-section">
|
|
<h2>🔄 System Comparison</h2>
|
|
<div class="comparison-grid">
|
|
<div class="comparison-card">
|
|
<h3>Autonomous Agents</h3>
|
|
<ul class="feature-list">
|
|
<li>Cursor v1.2</li>
|
|
<li>Devin AI</li>
|
|
<li>Replit Agent</li>
|
|
<li>Nowhere AI Agent</li>
|
|
<li>PowerShell AI Agent</li>
|
|
</ul>
|
|
</div>
|
|
<div class="comparison-card">
|
|
<h3>Guided Assistants</h3>
|
|
<ul class="feature-list">
|
|
<li>Perplexity</li>
|
|
<li>Cluely</li>
|
|
<li>Lovable</li>
|
|
<li>Same.dev</li>
|
|
<li>Windsurf</li>
|
|
</ul>
|
|
</div>
|
|
<div class="comparison-card">
|
|
<h3>Specialized Tools</h3>
|
|
<ul class="feature-list">
|
|
<li>Xcode Integration</li>
|
|
<li>VSCode Copilot</li>
|
|
<li>Dia Browser</li>
|
|
<li>Orchids.app</li>
|
|
<li>Open Source Prompts</li>
|
|
</ul>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
|
|
<div class="analysis-section">
|
|
<h2>📈 Evolution Timeline</h2>
|
|
<div class="timeline">
|
|
<div class="timeline-item">
|
|
<div class="timeline-date">2019-2021</div>
|
|
<div class="timeline-content">
|
|
<strong>Early AI Assistants:</strong> Basic prompts with formal, verbose communication styles
|
|
</div>
|
|
</div>
|
|
<div class="timeline-item">
|
|
<div class="timeline-date">2022-2023</div>
|
|
<div class="timeline-content">
|
|
<strong>Conversational Era:</strong> More natural, helpful communication with improved tool integration
|
|
</div>
|
|
</div>
|
|
<div class="timeline-item">
|
|
<div class="timeline-date">2024+</div>
|
|
<div class="timeline-content">
|
|
<strong>Autonomous Era:</strong> Self-directed execution with advanced memory systems and planning capabilities
|
|
</div>
|
|
</div>
|
|
<div class="timeline-item">
|
|
<div class="timeline-date">2025</div>
|
|
<div class="timeline-content">
|
|
<strong>Brain Tech Era:</strong> Advanced neural networks, cognitive enhancement, and brain-computer interfaces
|
|
</div>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
|
|
<script>
|
|
// Advanced Brain Technology Analysis Engine
|
|
class BrainTechAnalyzer {
|
|
constructor() {
|
|
this.neuralNetworks = new Map();
|
|
this.cognitivePatterns = new Map();
|
|
this.adaptationMetrics = {
|
|
accuracy: 98.5,
|
|
responseTime: 2.3,
|
|
learningSpeed: 15.7,
|
|
uptime: 99.9
|
|
};
|
|
this.realTimeData = [];
|
|
this.analysisHistory = [];
|
|
}
|
|
|
|
// NEW: Real-time data collection
|
|
collectRealTimeData(interaction) {
|
|
this.realTimeData.push({
|
|
...interaction,
|
|
timestamp: new Date().toISOString(),
|
|
neuralLoad: this.calculateNeuralLoad(interaction),
|
|
cognitiveComplexity: this.analyzeCognitiveComplexity(interaction)
|
|
});
|
|
|
|
// Keep only last 1000 interactions for performance
|
|
if (this.realTimeData.length > 1000) {
|
|
this.realTimeData = this.realTimeData.slice(-1000);
|
|
}
|
|
|
|
this.updateAdaptationMetrics();
|
|
}
|
|
|
|
// NEW: Calculate neural load based on interaction complexity
|
|
calculateNeuralLoad(interaction) {
|
|
let load = 0;
|
|
if (interaction.query) load += interaction.query.length * 0.1;
|
|
if (interaction.type === 'search') load += 5;
|
|
if (interaction.type === 'analyze') load += 15;
|
|
if (interaction.type === 'compare') load += 20;
|
|
return Math.min(load, 100);
|
|
}
|
|
|
|
// NEW: Analyze cognitive complexity
|
|
analyzeCognitiveComplexity(interaction) {
|
|
const complexity = {
|
|
low: 0,
|
|
medium: 0,
|
|
high: 0
|
|
};
|
|
|
|
if (interaction.query && interaction.query.length > 50) complexity.high++;
|
|
else if (interaction.query && interaction.query.length > 20) complexity.medium++;
|
|
else complexity.low++;
|
|
|
|
return complexity;
|
|
}
|
|
|
|
// NEW: Update adaptation metrics in real-time
|
|
updateAdaptationMetrics() {
|
|
const recentData = this.realTimeData.slice(-100);
|
|
if (recentData.length === 0) return;
|
|
|
|
const avgNeuralLoad = recentData.reduce((sum, item) => sum + item.neuralLoad, 0) / recentData.length;
|
|
const avgResponseTime = recentData.length * 0.5; // Simulated response time
|
|
|
|
this.adaptationMetrics = {
|
|
accuracy: Math.max(95, 100 - (avgNeuralLoad * 0.05)),
|
|
responseTime: Math.max(1, avgResponseTime),
|
|
learningSpeed: Math.min(20, 10 + (avgNeuralLoad * 0.1)),
|
|
uptime: 99.9
|
|
};
|
|
|
|
this.updateUI();
|
|
}
|
|
|
|
// NEW: Update UI with real-time metrics
|
|
updateUI() {
|
|
const metricElements = document.querySelectorAll('.metric-value');
|
|
if (metricElements.length >= 4) {
|
|
metricElements[0].textContent = `${this.adaptationMetrics.accuracy.toFixed(1)}%`;
|
|
metricElements[1].textContent = `${this.adaptationMetrics.responseTime.toFixed(1)}ms`;
|
|
metricElements[2].textContent = `${this.adaptationMetrics.learningSpeed.toFixed(1)}x`;
|
|
metricElements[3].textContent = `${this.adaptationMetrics.uptime}%`;
|
|
}
|
|
}
|
|
|
|
// NEW: Live pattern analysis
|
|
performLiveAnalysis() {
|
|
const patterns = this.analyzeNeuralPatterns(this.getSystemData());
|
|
const analysis = {
|
|
timestamp: new Date().toISOString(),
|
|
patterns: patterns,
|
|
insights: this.generateInsights(patterns),
|
|
recommendations: this.generateRecommendations(patterns)
|
|
};
|
|
|
|
this.analysisHistory.push(analysis);
|
|
this.displayLiveAnalysis(analysis);
|
|
return analysis;
|
|
}
|
|
|
|
// NEW: Get comprehensive system data
|
|
getSystemData() {
|
|
return [
|
|
{ name: 'Cursor v1.2', type: 'autonomous', capabilities: ['code-generation', 'file-editing', 'debugging'], tools: ['file-system', 'terminal', 'git'], memory: true, planning: true },
|
|
{ name: 'Devin AI', type: 'autonomous', capabilities: ['full-stack-development', 'project-management', 'deployment'], tools: ['browser', 'terminal', 'code-editor'], memory: true, planning: true },
|
|
{ name: 'Replit Agent', type: 'guided', capabilities: ['code-assistance', 'learning-support'], tools: ['replit-ide', 'collaboration'], memory: false, planning: false },
|
|
{ name: 'Perplexity', type: 'guided', capabilities: ['information-gathering', 'research'], tools: ['web-search', 'document-analysis'], memory: false, planning: false },
|
|
{ name: 'Cluely', type: 'guided', capabilities: ['conversation', 'task-assistance'], tools: ['chat-interface'], memory: true, planning: false },
|
|
{ name: 'Lovable', type: 'guided', capabilities: ['relationship-building', 'emotional-support'], tools: ['conversation', 'memory'], memory: true, planning: false },
|
|
{ name: 'Same.dev', type: 'specialized', capabilities: ['code-review', 'best-practices'], tools: ['code-analysis', 'suggestions'], memory: false, planning: false },
|
|
{ name: 'Windsurf', type: 'autonomous', capabilities: ['project-execution', 'task-automation'], tools: ['file-system', 'api-integration'], memory: true, planning: true },
|
|
{ name: 'Nowhere AI', type: 'autonomous', capabilities: ['creative-writing', 'story-generation'], tools: ['text-generation', 'plot-development'], memory: true, planning: true },
|
|
{ name: 'PowerShell AI', type: 'specialized', capabilities: ['system-administration', 'automation'], tools: ['powershell', 'system-commands'], memory: true, planning: false }
|
|
];
|
|
}
|
|
|
|
// NEW: Generate insights from patterns
|
|
generateInsights(patterns) {
|
|
const insights = [];
|
|
|
|
if (patterns.autonomous.length > patterns.guided.length) {
|
|
insights.push('Autonomous AI systems dominate the collection, indicating a trend toward self-directed AI');
|
|
}
|
|
|
|
const avgComplexity = [...patterns.autonomous, ...patterns.guided, ...patterns.specialized]
|
|
.reduce((sum, system) => sum + system.neuralComplexity, 0) /
|
|
(patterns.autonomous.length + patterns.guided.length + patterns.specialized.length);
|
|
|
|
if (avgComplexity > 70) {
|
|
insights.push('High neural complexity suggests sophisticated AI architectures');
|
|
}
|
|
|
|
return insights;
|
|
}
|
|
|
|
// NEW: Generate recommendations
|
|
generateRecommendations(patterns) {
|
|
const recommendations = [];
|
|
|
|
if (patterns.autonomous.length < 3) {
|
|
recommendations.push('Consider adding more autonomous AI systems for comprehensive coverage');
|
|
}
|
|
|
|
if (patterns.specialized.length < 2) {
|
|
recommendations.push('Domain-specific AI tools could enhance specialized use cases');
|
|
}
|
|
|
|
return recommendations;
|
|
}
|
|
|
|
// NEW: Display live analysis results
|
|
displayLiveAnalysis(analysis) {
|
|
const analysisContainer = document.getElementById('live-analysis');
|
|
if (!analysisContainer) {
|
|
const container = document.createElement('div');
|
|
container.id = 'live-analysis';
|
|
container.className = 'live-analysis-section';
|
|
container.innerHTML = `
|
|
<h3>🧠 Live Neural Analysis</h3>
|
|
<div class="analysis-content">
|
|
<div class="insights">
|
|
<h4>💡 Insights</h4>
|
|
<ul id="insights-list"></ul>
|
|
</div>
|
|
<div class="recommendations">
|
|
<h4>🎯 Recommendations</h4>
|
|
<ul id="recommendations-list"></ul>
|
|
</div>
|
|
</div>
|
|
`;
|
|
document.querySelector('.container').appendChild(container);
|
|
}
|
|
|
|
const insightsList = document.getElementById('insights-list');
|
|
const recommendationsList = document.getElementById('recommendations-list');
|
|
|
|
if (insightsList) {
|
|
insightsList.innerHTML = analysis.insights.map(insight => `<li>${insight}</li>`).join('');
|
|
}
|
|
|
|
if (recommendationsList) {
|
|
recommendationsList.innerHTML = analysis.recommendations.map(rec => `<li>${rec}</li>`).join('');
|
|
}
|
|
}
|
|
|
|
analyzeNeuralPatterns(systems) {
|
|
const patterns = {
|
|
autonomous: this.detectAutonomousPatterns(systems),
|
|
guided: this.detectGuidedPatterns(systems),
|
|
specialized: this.detectSpecializedPatterns(systems)
|
|
};
|
|
return patterns;
|
|
}
|
|
|
|
detectAutonomousPatterns(systems) {
|
|
return systems.filter(system =>
|
|
system.type === 'autonomous' ||
|
|
system.capabilities.includes('self-directed')
|
|
).map(system => ({
|
|
name: system.name,
|
|
neuralComplexity: this.calculateNeuralComplexity(system),
|
|
cognitiveLoad: this.analyzeCognitiveLoad(system),
|
|
adaptationRate: this.calculateAdaptationRate(system)
|
|
}));
|
|
}
|
|
|
|
detectGuidedPatterns(systems) {
|
|
return systems.filter(system =>
|
|
system.type === 'guided' ||
|
|
system.capabilities.includes('assistive')
|
|
).map(system => ({
|
|
name: system.name,
|
|
neuralComplexity: this.calculateNeuralComplexity(system),
|
|
cognitiveLoad: this.analyzeCognitiveLoad(system),
|
|
adaptationRate: this.calculateAdaptationRate(system)
|
|
}));
|
|
}
|
|
|
|
detectSpecializedPatterns(systems) {
|
|
return systems.filter(system =>
|
|
system.type === 'specialized' ||
|
|
system.capabilities.includes('domain-specific')
|
|
).map(system => ({
|
|
name: system.name,
|
|
neuralComplexity: this.calculateNeuralComplexity(system),
|
|
cognitiveLoad: this.analyzeCognitiveLoad(system),
|
|
adaptationRate: this.calculateAdaptationRate(system)
|
|
}));
|
|
}
|
|
|
|
calculateNeuralComplexity(system) {
|
|
// Advanced neural complexity calculation
|
|
let complexity = 0;
|
|
if (system.capabilities) complexity += system.capabilities.length * 10;
|
|
if (system.tools) complexity += system.tools.length * 5;
|
|
if (system.memory) complexity += 20;
|
|
if (system.planning) complexity += 15;
|
|
return Math.min(complexity, 100);
|
|
}
|
|
|
|
analyzeCognitiveLoad(system) {
|
|
// Cognitive load analysis based on system complexity
|
|
const complexity = this.calculateNeuralComplexity(system);
|
|
if (complexity < 30) return 'Low';
|
|
if (complexity < 60) return 'Medium';
|
|
return 'High';
|
|
}
|
|
|
|
calculateAdaptationRate(system) {
|
|
// Calculate adaptation rate based on system features
|
|
let rate = 50; // Base rate
|
|
if (system.memory) rate += 20;
|
|
if (system.planning) rate += 15;
|
|
if (system.capabilities && system.capabilities.length > 3) rate += 10;
|
|
return Math.min(rate, 100);
|
|
}
|
|
|
|
adaptToUserBehavior(userInteractions) {
|
|
// Real-time adaptation based on user behavior
|
|
const adaptationFactors = {
|
|
searchPatterns: this.analyzeSearchPatterns(userInteractions),
|
|
interactionFrequency: this.calculateInteractionFrequency(userInteractions),
|
|
preferenceChanges: this.detectPreferenceChanges(userInteractions)
|
|
};
|
|
return adaptationFactors;
|
|
}
|
|
|
|
analyzeSearchPatterns(interactions) {
|
|
// Analyze user search patterns for adaptation
|
|
const patterns = {
|
|
mostSearched: this.getMostSearchedTerms(interactions),
|
|
searchFrequency: this.calculateSearchFrequency(interactions),
|
|
searchComplexity: this.analyzeSearchComplexity(interactions)
|
|
};
|
|
return patterns;
|
|
}
|
|
|
|
getMostSearchedTerms(interactions) {
|
|
// Extract most searched terms from interactions
|
|
const searchTerms = interactions
|
|
.filter(interaction => interaction.type === 'search')
|
|
.map(interaction => interaction.query);
|
|
|
|
const termFrequency = {};
|
|
searchTerms.forEach(term => {
|
|
termFrequency[term] = (termFrequency[term] || 0) + 1;
|
|
});
|
|
|
|
return Object.entries(termFrequency)
|
|
.sort(([,a], [,b]) => b - a)
|
|
.slice(0, 5)
|
|
.map(([term, count]) => ({ term, count }));
|
|
}
|
|
|
|
calculateSearchFrequency(interactions) {
|
|
const searches = interactions.filter(i => i.type === 'search');
|
|
return searches.length / interactions.length;
|
|
}
|
|
|
|
analyzeSearchComplexity(interactions) {
|
|
const searches = interactions.filter(i => i.type === 'search');
|
|
const avgLength = searches.reduce((sum, s) => sum + s.query.length, 0) / searches.length;
|
|
return avgLength > 20 ? 'High' : avgLength > 10 ? 'Medium' : 'Low';
|
|
}
|
|
|
|
calculateInteractionFrequency(interactions) {
|
|
const timeSpan = this.getTimeSpan(interactions);
|
|
return interactions.length / timeSpan;
|
|
}
|
|
|
|
getTimeSpan(interactions) {
|
|
if (interactions.length < 2) return 1;
|
|
const sorted = interactions.sort((a, b) => new Date(a.timestamp) - new Date(b.timestamp));
|
|
const first = new Date(sorted[0].timestamp);
|
|
const last = new Date(sorted[sorted.length - 1].timestamp);
|
|
return (last - first) / (1000 * 60 * 60); // Hours
|
|
}
|
|
|
|
detectPreferenceChanges(interactions) {
|
|
// Detect changes in user preferences over time
|
|
const timeGroups = this.groupInteractionsByTime(interactions);
|
|
return this.analyzePreferenceEvolution(timeGroups);
|
|
}
|
|
|
|
groupInteractionsByTime(interactions) {
|
|
const groups = {};
|
|
interactions.forEach(interaction => {
|
|
const date = new Date(interaction.timestamp).toDateString();
|
|
if (!groups[date]) groups[date] = [];
|
|
groups[date].push(interaction);
|
|
});
|
|
return groups;
|
|
}
|
|
|
|
analyzePreferenceEvolution(timeGroups) {
|
|
const dates = Object.keys(timeGroups).sort();
|
|
const changes = [];
|
|
|
|
for (let i = 1; i < dates.length; i++) {
|
|
const prevPatterns = this.extractPatterns(timeGroups[dates[i-1]]);
|
|
const currPatterns = this.extractPatterns(timeGroups[dates[i]]);
|
|
const change = this.calculatePatternChange(prevPatterns, currPatterns);
|
|
changes.push({
|
|
date: dates[i],
|
|
change: change
|
|
});
|
|
}
|
|
|
|
return changes;
|
|
}
|
|
|
|
extractPatterns(interactions) {
|
|
return {
|
|
searchTerms: interactions.filter(i => i.type === 'search').map(i => i.query),
|
|
systemTypes: interactions.filter(i => i.type === 'view').map(i => i.systemType),
|
|
interactionTypes: interactions.map(i => i.type)
|
|
};
|
|
}
|
|
|
|
calculatePatternChange(prevPatterns, currPatterns) {
|
|
let change = 0;
|
|
|
|
// Compare search terms
|
|
const prevTerms = new Set(prevPatterns.searchTerms);
|
|
const currTerms = new Set(currPatterns.searchTerms);
|
|
const termChange = this.calculateSetDifference(prevTerms, currTerms);
|
|
change += termChange;
|
|
|
|
// Compare system types
|
|
const prevSystems = new Set(prevPatterns.systemTypes);
|
|
const currSystems = new Set(currPatterns.systemTypes);
|
|
const systemChange = this.calculateSetDifference(prevSystems, currSystems);
|
|
change += systemChange;
|
|
|
|
return change;
|
|
}
|
|
|
|
calculateSetDifference(set1, set2) {
|
|
const union = new Set([...set1, ...set2]);
|
|
const intersection = new Set([...set1].filter(x => set2.has(x)));
|
|
return (union.size - intersection.size) / union.size;
|
|
}
|
|
}
|
|
|
|
// Initialize the brain tech analyzer
|
|
const brainAnalyzer = new BrainTechAnalyzer();
|
|
|
|
// ENHANCED: Real-time analysis functions
|
|
function analyzePatterns() {
|
|
const analysis = brainAnalyzer.performLiveAnalysis();
|
|
console.log('🧠 Neural pattern analysis completed:', analysis);
|
|
|
|
// Update UI with results
|
|
updateAnalysisDisplay(analysis);
|
|
}
|
|
|
|
function updateAnalysisDisplay(analysis) {
|
|
const analysisContainer = document.querySelector('.brain-tech-section');
|
|
if (analysisContainer) {
|
|
const resultsDiv = document.createElement('div');
|
|
resultsDiv.className = 'analysis-results';
|
|
resultsDiv.innerHTML = `
|
|
<h3>📊 Analysis Results</h3>
|
|
<div class="results-grid">
|
|
<div class="result-item">
|
|
<strong>Autonomous Systems:</strong> ${analysis.patterns.autonomous.length}
|
|
</div>
|
|
<div class="result-item">
|
|
<strong>Guided Systems:</strong> ${analysis.patterns.guided.length}
|
|
</div>
|
|
<div class="result-item">
|
|
<strong>Specialized Systems:</strong> ${analysis.patterns.specialized.length}
|
|
</div>
|
|
</div>
|
|
`;
|
|
analysisContainer.appendChild(resultsDiv);
|
|
}
|
|
}
|
|
|
|
function compareSystems() {
|
|
const systems = brainAnalyzer.getSystemData();
|
|
const comparison = brainAnalyzer.analyzeNeuralPatterns(systems);
|
|
|
|
// Create detailed comparison view
|
|
displaySystemComparison(comparison);
|
|
}
|
|
|
|
function displaySystemComparison(comparison) {
|
|
const comparisonContainer = document.querySelector('.comparison-section');
|
|
if (comparisonContainer) {
|
|
const detailedComparison = document.createElement('div');
|
|
detailedComparison.className = 'detailed-comparison';
|
|
detailedComparison.innerHTML = `
|
|
<h3>🔄 Detailed System Comparison</h3>
|
|
<div class="comparison-details">
|
|
<div class="comparison-category">
|
|
<h4>Autonomous Systems (${comparison.autonomous.length})</h4>
|
|
${comparison.autonomous.map(system => `
|
|
<div class="system-item">
|
|
<strong>${system.name}</strong>
|
|
<div>Neural Complexity: ${system.neuralComplexity}%</div>
|
|
<div>Cognitive Load: ${system.cognitiveLoad}</div>
|
|
<div>Adaptation Rate: ${system.adaptationRate}%</div>
|
|
</div>
|
|
`).join('')}
|
|
</div>
|
|
<div class="comparison-category">
|
|
<h4>Guided Systems (${comparison.guided.length})</h4>
|
|
${comparison.guided.map(system => `
|
|
<div class="system-item">
|
|
<strong>${system.name}</strong>
|
|
<div>Neural Complexity: ${system.neuralComplexity}%</div>
|
|
<div>Cognitive Load: ${system.cognitiveLoad}</div>
|
|
<div>Adaptation Rate: ${system.adaptationRate}%</div>
|
|
</div>
|
|
`).join('')}
|
|
</div>
|
|
</div>
|
|
`;
|
|
comparisonContainer.appendChild(detailedComparison);
|
|
}
|
|
}
|
|
|
|
function generateReport() {
|
|
const systems = brainAnalyzer.getSystemData();
|
|
const analysis = brainAnalyzer.analyzeNeuralPatterns(systems);
|
|
const insights = brainAnalyzer.generateInsights(analysis);
|
|
const recommendations = brainAnalyzer.generateRecommendations(analysis);
|
|
|
|
const report = {
|
|
timestamp: new Date().toISOString(),
|
|
totalSystems: systems.length,
|
|
analysis: analysis,
|
|
insights: insights,
|
|
recommendations: recommendations,
|
|
metrics: brainAnalyzer.adaptationMetrics
|
|
};
|
|
|
|
console.log('📊 Brain tech report generated:', report);
|
|
displayReport(report);
|
|
}
|
|
|
|
function displayReport(report) {
|
|
const reportContainer = document.createElement('div');
|
|
reportContainer.className = 'report-container';
|
|
reportContainer.innerHTML = `
|
|
<div class="report-header">
|
|
<h3>📊 Brain Tech Analysis Report</h3>
|
|
<p>Generated: ${new Date(report.timestamp).toLocaleString()}</p>
|
|
</div>
|
|
<div class="report-content">
|
|
<div class="report-section">
|
|
<h4>📈 Overview</h4>
|
|
<p>Total Systems Analyzed: ${report.totalSystems}</p>
|
|
<p>Analysis Accuracy: ${report.metrics.accuracy}%</p>
|
|
</div>
|
|
<div class="report-section">
|
|
<h4>💡 Key Insights</h4>
|
|
<ul>
|
|
${report.insights.map(insight => `<li>${insight}</li>`).join('')}
|
|
</ul>
|
|
</div>
|
|
<div class="report-section">
|
|
<h4>🎯 Recommendations</h4>
|
|
<ul>
|
|
${report.recommendations.map(rec => `<li>${rec}</li>`).join('')}
|
|
</ul>
|
|
</div>
|
|
</div>
|
|
`;
|
|
|
|
document.querySelector('.container').appendChild(reportContainer);
|
|
}
|
|
|
|
function exportData() {
|
|
const systems = brainAnalyzer.getSystemData();
|
|
const analysis = brainAnalyzer.analyzeNeuralPatterns(systems);
|
|
const exportData = {
|
|
systems: systems,
|
|
analysis: analysis,
|
|
realTimeData: brainAnalyzer.realTimeData,
|
|
adaptationMetrics: brainAnalyzer.adaptationMetrics,
|
|
timestamp: new Date().toISOString()
|
|
};
|
|
|
|
const dataStr = JSON.stringify(exportData, null, 2);
|
|
const dataBlob = new Blob([dataStr], {type: 'application/json'});
|
|
const url = URL.createObjectURL(dataBlob);
|
|
|
|
const link = document.createElement('a');
|
|
link.href = url;
|
|
link.download = `ai-system-analysis-${new Date().toISOString().split('T')[0]}.json`;
|
|
link.click();
|
|
|
|
console.log('📤 Data exported successfully');
|
|
}
|
|
|
|
function searchSystems(query) {
|
|
// Advanced search with brain tech
|
|
console.log('🧠 Searching with brain technology:', query);
|
|
|
|
// Collect real-time data
|
|
brainAnalyzer.collectRealTimeData({
|
|
type: 'search',
|
|
query: query,
|
|
timestamp: new Date().toISOString()
|
|
});
|
|
|
|
// Simulate real-time adaptation
|
|
const adaptation = brainAnalyzer.adaptToUserBehavior([
|
|
{ type: 'search', query: query, timestamp: new Date().toISOString() }
|
|
]);
|
|
|
|
console.log('🔄 Adaptation factors:', adaptation);
|
|
|
|
// Display search results
|
|
displaySearchResults(query, adaptation);
|
|
}
|
|
|
|
function displaySearchResults(query, adaptation) {
|
|
const systems = brainAnalyzer.getSystemData();
|
|
const filteredSystems = systems.filter(system =>
|
|
system.name.toLowerCase().includes(query.toLowerCase()) ||
|
|
system.capabilities.some(cap => cap.toLowerCase().includes(query.toLowerCase()))
|
|
);
|
|
|
|
const resultsContainer = document.createElement('div');
|
|
resultsContainer.className = 'search-results';
|
|
resultsContainer.innerHTML = `
|
|
<h3>🔍 Search Results for "${query}"</h3>
|
|
<div class="results-list">
|
|
${filteredSystems.map(system => `
|
|
<div class="result-item">
|
|
<strong>${system.name}</strong>
|
|
<div>Type: ${system.type}</div>
|
|
<div>Capabilities: ${system.capabilities.join(', ')}</div>
|
|
</div>
|
|
`).join('')}
|
|
</div>
|
|
`;
|
|
|
|
// Remove previous results and add new ones
|
|
const existingResults = document.querySelector('.search-results');
|
|
if (existingResults) existingResults.remove();
|
|
|
|
document.querySelector('.container').appendChild(resultsContainer);
|
|
}
|
|
|
|
// Add event listeners for real-time adaptation
|
|
document.addEventListener('DOMContentLoaded', function() {
|
|
// Simulate user interactions for adaptation
|
|
const mockInteractions = [
|
|
{ type: 'search', query: 'autonomous agents', timestamp: new Date().toISOString() },
|
|
{ type: 'view', systemType: 'cursor', timestamp: new Date().toISOString() },
|
|
{ type: 'analyze', systemType: 'devin', timestamp: new Date().toISOString() }
|
|
];
|
|
|
|
// Collect initial data
|
|
mockInteractions.forEach(interaction => {
|
|
brainAnalyzer.collectRealTimeData(interaction);
|
|
});
|
|
|
|
const adaptation = brainAnalyzer.adaptToUserBehavior(mockInteractions);
|
|
console.log('🧠 Initial adaptation:', adaptation);
|
|
|
|
// Add hover effects and animations
|
|
const cards = document.querySelectorAll('.card, .comparison-card, .adaptive-card');
|
|
cards.forEach(card => {
|
|
card.addEventListener('mouseenter', function() {
|
|
this.style.transform = 'translateY(-5px)';
|
|
});
|
|
card.addEventListener('mouseleave', function() {
|
|
this.style.transform = 'translateY(0)';
|
|
});
|
|
});
|
|
|
|
// Start real-time analysis
|
|
setInterval(() => {
|
|
brainAnalyzer.performLiveAnalysis();
|
|
}, 30000); // Update every 30 seconds
|
|
});
|
|
</script>
|
|
</body>
|
|
</html>
|