pixelassistent

Nexus Visual - Adaptive Pixels

Behavior-driven adaptive visual system with machine learning

Nexus Visual implements an advanced adaptive pixel system that learns from user interactions and reflects them in real-time visuals. The system combines realistic behavior tracking, simple heuristic adaptation, and optional machine learning to create personalized visual experiences.

✨ Features

🧠 Adaptive Learning System

• Real-time Behavior Tracking: Click, hover, scroll, and keyboard interaction monitoring
• Grid-based Heatmap: Spatial analysis of user interaction patterns
• Pixel Adaptation: 10,000 pixels that adapt based on user behavior
• Confidence Scoring: Machine learning confidence metrics

🎨 Visual Adaptation

• Color Shifting: Dynamic color adaptation based on context and preferences
• Speed Modulation: Movement speed adaptation based on interaction patterns
• Glow Intensity: Visual feedback intensity based on user engagement
• Size Scaling: Pixel size adaptation for different interaction styles

🤖 Machine Learning Integration

• TensorFlow.js: Optional ML model training and prediction
• Behavior Prediction: Predicts user preferences from interaction patterns
• Model Persistence: Saves trained models to localStorage
• Feature Flag Control: ML features only load when enabled

📊 Analytics Dashboard

• Real-time Stats: Live adaptation metrics and confidence scores
• Heatmap Visualization: Interactive heatmap of user activity
• Preference Controls: Manual adaptation controls and theme switching
• ML Model Management: Train, predict, and manage ML models

🛠️ Technical Stack

• React 18 - Component framework
• TypeScript - Type safety
• Vite - Build tool and dev server
• Tailwind CSS - Styling framework
• Framer Motion - Animations
• Zustand - State management
• Canvas API - High-performance rendering
• TensorFlow.js - Machine learning (optional)

🚀 Quick Start

Prerequisites

• Node.js 18+
• npm or yarn

Installation

cd apps/nexus-visual
npm install

Environment Setup

cp .env.local.example .env.local

Configure environment variables:

# Feature Flags
VITE_ENABLE_PIXEL_LEARNING=true
VITE_ENABLE_PIXEL_ML=false

# Optional Supabase Integration
VITE_SUPABASE_URL=https://your-project.supabase.co
VITE_SUPABASE_ANON_KEY=your-anon-key

Development

npm run dev

Visit http://localhost:3004 to see the adaptive pixels in action.

🎮 Usage

Basic Interaction

• Click: Interact with pixels to trigger adaptation
• Hover: Influence nearby pixels with mouse movement
• Scroll: Affect global pixel behavior patterns
• Keyboard: Track keyboard interaction patterns

Keyboard Shortcuts

• P: Toggle pause/play animation
• R: Reset pixel learning
• D: Toggle dashboard visibility

Dashboard Controls

• Stats Tab: View adaptation metrics and confidence scores
• Heatmap Tab: See interaction patterns and activity zones
• Preferences Tab: Apply manual adaptations and themes
• ML Tab: Train and manage machine learning models

🔧 Configuration

Feature Flags

# Enable behavior learning system
VITE_ENABLE_PIXEL_LEARNING=true

# Enable machine learning features (requires TensorFlow.js)
VITE_ENABLE_PIXEL_ML=false

Pixel Configuration

// Adjust pixel count and density
const PIXEL_COUNT = 10000
const ADAPTATION_RADIUS = 100
const GRID_SIZE = 50

Context Modes

• ghost-studio: Purple theme (#B84DFF)
• nova-pilot: Cyan theme (#00FFE7)
• nexus: Accent theme (#9AF7EE)

📊 Data Model

User Behavior

interface UserBehavior {
  clickHeatmap: Map<string, number>
  hoverAreas: Map<string, number>
  scrollSpeed: number
  timeOnPage: Record<string, number>
  interactions: {
    buttons: string[]
    features: string[]
    timeOfDay: string
  }
}

Pixel Preferences

interface PixelPreferences {
  colorShift: number        // -1..1
  speedMultiplier: number   // 0.5..2
  size: number              // 0.5..1.5
  opacity: number           // 0.3..1
  glowIntensity: number     // 0.5..2
}

🧪 Testing

# Run tests
npm run test

# Run tests with UI
npm run test:ui

# Test specific modules
npm run test behaviorTracker
npm run test adaptivePixels
npm run test storage

Test Coverage

• Behavior Tracker: Heatmap bucketing, notification radius
• Adaptive Pixels: Preference changes on interactions
• Storage: Persistence get/set roundtrip
• ML Integration: Model training and prediction

🔌 Integration

Embedding in Other Apps

import { AdaptivePixels } from '@/components/AdaptivePixels'

function MyApp() {
  return (
    <div>
      <MyAppContent />
      <AdaptivePixels 
        mode="real"
        context="nova-pilot"
        density={0.5}
      />
    </div>
  )
}

Initialization Helper

import { initAdaptivePixels } from '@/lib/adaptivePixels'

// Initialize with specific configuration
initAdaptivePixels({
  mode: 'real',
  context: 'ghost-studio',
  enableLearning: true,
  enableML: false
})

📈 Performance

Optimization Features

• RequestAnimationFrame: Smooth 60fps animation
• Canvas Rendering: Hardware-accelerated graphics
• Throttled Events: Optimized interaction tracking
• Lazy Loading: ML features load only when needed
• Memory Management: Efficient pixel data structures

Performance Metrics

• Target: 60fps with 10,000 pixels
• Memory: < 50MB for full system
• Bundle Size: < 2MB (without ML features)
• ML Bundle: +3MB when enabled

🔒 Privacy & Security

Data Handling

• Local Storage: Primary data persistence
• Optional Supabase: Cloud backup for pro users
• No Tracking: No external analytics or tracking
• User Control: Full data export and deletion

Security Features

• Input Validation: All user inputs validated
• XSS Protection: Content sanitization
• CSRF Protection: Request token validation
• Environment Variables: Secure configuration

🚀 Deployment

Build

npm run build

Environment Variables

# Production
VITE_ENABLE_PIXEL_LEARNING=true
VITE_ENABLE_PIXEL_ML=false
VITE_SUPABASE_URL=https://your-project.supabase.co
VITE_SUPABASE_ANON_KEY=your-anon-key

Deployment Platforms

• Vercel: Automatic deployment with environment variables
• Netlify: Static site deployment
• Docker: Containerized deployment
• CDN: Static asset optimization

📚 API Reference

Hooks

• useBehaviorTracker(): Track user interactions
• useAdaptivePixels(): Manage pixel adaptation
• useSimpleAdaptation(): Apply heuristic adaptations
• usePixelML(): Machine learning integration

Components

• AdaptivePixelsCanvas: Main rendering canvas
• PixelLearningDashboard: Analytics and controls
• HeatmapCanvas: Interaction visualization

Utilities

• pixelStorage: Local storage management
• pixelSupabase: Cloud persistence
• utils: Color, math, and helper functions

🤝 Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Add tests for new functionality
5. Submit a pull request

Development Guidelines

• Use TypeScript strict mode
• Follow existing code patterns
• Add tests for new features
• Update documentation
• Ensure performance targets

📄 License

MIT License - see LICENSE file for details.

🆘 Support

• Issues: GitHub Issues
• Documentation: This README
• Examples: See /examples directory
• Community: Discord server

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