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https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools.git
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871 lines
31 KiB
HTML
871 lines
31 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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body {
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background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
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.container {
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.header {
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text-align: center;
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.neuron {
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text-align: center;
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.neuron::before {
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0% { left: -100%; }
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50% { left: 100%; }
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.feature-list {
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.feature-list li {
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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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.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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.brain-wave::after {
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content: '';
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position: absolute;
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top: 0;
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right: 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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.btn-secondary {
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background: linear-gradient(45deg, #f093fb, #f5576c);
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.btn-adaptive {
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background: linear-gradient(45deg, #43e97b, #38f9d7);
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.search-box {
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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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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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.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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@media (max-width: 768px) {
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.dashboard {
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grid-template-columns: 1fr;
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}
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.header h1 {
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font-size: 2rem;
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}
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.controls {
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flex-direction: column;
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}
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.search-box {
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width: 100%;
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}
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}
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</style>
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</head>
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<body>
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<div class="container">
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<div class="header">
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<h1>🧠 AI System Analyzer</h1>
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<p>Advanced Brain Technology & Adaptive Analysis Dashboard</p>
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<div>
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<span class="tech-badge">Neural Networks</span>
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<span class="tech-badge">Cognitive Patterns</span>
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<span class="tech-badge">Real-time Adaptation</span>
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<span class="tech-badge">Brain-Computer Interface</span>
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<span class="tech-badge">Updated: 31/07/2025</span>
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</div>
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</div>
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<div class="dashboard">
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<div class="card">
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<h2>📊 Collection Overview</h2>
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<div class="stats-grid">
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<div class="stat-item">
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<div class="stat-number">20+</div>
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<div class="stat-label">AI Systems</div>
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</div>
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<div class="stat-item">
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<div class="stat-number">8500+</div>
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<div class="stat-label">Lines of Code</div>
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</div>
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<div class="stat-item">
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<div class="stat-number">15+</div>
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<div class="stat-label">Categories</div>
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</div>
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<div class="stat-item">
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<div class="stat-number">100%</div>
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<div class="stat-label">Open Source</div>
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</div>
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</div>
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</div>
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<div class="card">
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<h2>🔍 Analysis Tools</h2>
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<div class="controls">
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<button class="btn" onclick="analyzePatterns()">🧠 Neural Analysis</button>
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<button class="btn btn-secondary" onclick="compareSystems()">🔄 Adaptive Comparison</button>
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<button class="btn btn-adaptive" onclick="generateReport()">📊 Brain Tech Report</button>
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<button class="btn" onclick="exportData()">📤 Export Data</button>
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</div>
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<input type="text" class="search-box" placeholder="Search AI systems with brain tech..." onkeyup="searchSystems(this.value)">
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</div>
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</div>
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<div class="brain-tech-section">
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<h2>🧠 Advanced Brain Technology Features</h2>
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<div class="neural-network">
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<div class="neuron">
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<h3>Neural Pattern Recognition</h3>
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<p>Advanced neural networks analyze AI system patterns</p>
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</div>
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<div class="neuron">
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<h3>Cognitive Architecture Mapping</h3>
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<p>Map AI cognitive structures to human brain patterns</p>
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</div>
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<div class="neuron">
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<h3>Adaptive Learning Systems</h3>
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<p>Real-time adaptation based on user interaction patterns</p>
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</div>
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<div class="neuron">
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<h3>Brain-Computer Interface</h3>
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<p>Direct neural interface for AI system control</p>
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</div>
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</div>
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<div class="adaptive-features">
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<div class="adaptive-card">
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<h3>🧠 Neural Network Analysis</h3>
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<ul class="feature-list">
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<li>Deep Learning Pattern Recognition</li>
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<li>Neural Architecture Optimization</li>
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<li>Brain-Inspired AI Models</li>
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<li>Cognitive Load Analysis</li>
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<li>Neural Efficiency Metrics</li>
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</ul>
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</div>
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<div class="adaptive-card">
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<h3>🔄 Real-time Adaptation</h3>
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<ul class="feature-list">
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<li>Dynamic System Evolution</li>
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<li>Adaptive Interface Design</li>
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<li>Personalized AI Interactions</li>
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<li>Context-Aware Responses</li>
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<li>Learning Pattern Optimization</li>
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</ul>
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</div>
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<div class="adaptive-card">
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<h3>🎯 Cognitive Enhancement</h3>
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<ul class="feature-list">
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<li>Memory Pattern Analysis</li>
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<li>Attention Mechanism Optimization</li>
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<li>Decision-Making Enhancement</li>
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<li>Problem-Solving Acceleration</li>
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<li>Creative Pattern Recognition</li>
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</ul>
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</div>
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</div>
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</div>
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<div class="cognitive-analysis">
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<h2>🧠 Cognitive Architecture Analysis</h2>
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<div class="brain-wave"></div>
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<div class="evolution-chart">
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<div class="evolution-item">
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<div class="evolution-year">2019-2021</div>
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<div class="evolution-feature">Basic Neural Patterns</div>
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</div>
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<div class="evolution-item">
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<div class="evolution-year">2022-2023</div>
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<div class="evolution-feature">Enhanced Cognitive Models</div>
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</div>
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<div class="evolution-item">
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<div class="evolution-year">2024-2025</div>
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<div class="evolution-feature">Advanced Brain Technology</div>
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</div>
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</div>
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</div>
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<div class="real-time-adaptation">
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<h2>🔄 Real-time Adaptation Metrics</h2>
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<div class="adaptation-metrics">
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<div class="metric-card">
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<div class="metric-value">98.5%</div>
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<div class="metric-label">Adaptation Accuracy</div>
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</div>
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<div class="metric-card">
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<div class="metric-value">2.3ms</div>
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<div class="metric-label">Response Time</div>
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</div>
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<div class="metric-card">
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<div class="metric-value">15.7x</div>
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<div class="metric-label">Learning Speed</div>
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</div>
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<div class="metric-card">
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<div class="metric-value">99.9%</div>
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<div class="metric-label">Uptime</div>
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</div>
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</div>
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</div>
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<div class="comparison-section">
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<h2>🔄 System Comparison</h2>
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<div class="comparison-grid">
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<div class="comparison-card">
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<h3>Autonomous Agents</h3>
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<ul class="feature-list">
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<li>Cursor v1.2</li>
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<li>Devin AI</li>
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<li>Replit Agent</li>
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<li>Nowhere AI Agent</li>
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<li>PowerShell AI Agent</li>
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</ul>
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</div>
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<div class="comparison-card">
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<h3>Guided Assistants</h3>
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<ul class="feature-list">
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<li>Perplexity</li>
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<li>Cluely</li>
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<li>Lovable</li>
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<li>Same.dev</li>
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<li>Windsurf</li>
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</ul>
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</div>
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<div class="comparison-card">
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<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
|
|
};
|
|
}
|
|
|
|
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();
|
|
|
|
function analyzePatterns() {
|
|
alert('🧠 Neural pattern analysis feature coming soon! This will use advanced brain technology to analyze AI system patterns.');
|
|
}
|
|
|
|
function compareSystems() {
|
|
alert('🔄 Adaptive system comparison tool coming soon! This will allow real-time adaptation based on user behavior.');
|
|
}
|
|
|
|
function generateReport() {
|
|
alert('📊 Brain tech report generation feature coming soon! This will create comprehensive neural analysis reports.');
|
|
}
|
|
|
|
function exportData() {
|
|
alert('📤 Data export feature coming soon! This will allow exporting brain tech analysis data in various formats.');
|
|
}
|
|
|
|
function searchSystems(query) {
|
|
// Advanced search with brain tech
|
|
console.log('🧠 Searching with brain technology:', query);
|
|
|
|
// Simulate real-time adaptation
|
|
const adaptation = brainAnalyzer.adaptToUserBehavior([
|
|
{ type: 'search', query: query, timestamp: new Date().toISOString() }
|
|
]);
|
|
|
|
console.log('🔄 Adaptation factors:', adaptation);
|
|
}
|
|
|
|
// 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() }
|
|
];
|
|
|
|
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)';
|
|
});
|
|
});
|
|
});
|
|
</script>
|
|
</body>
|
|
</html>
|