An intelligent DJ automation component for Conduit that provides beatmatching, smart queue management, and AI-driven music curation powered by Laravel Prism.

• 🎵 Intelligent Beatmatching: Analyzes BPM and key compatibility for seamless transitions
• 🤖 AI-Powered Curation: Uses Laravel Prism to understand music moods and create intelligent playlists
• 📊 Smart Queue Management: Builds progressive queues based on energy, mood, and user preferences
• 🎯 Auto-DJ Modes: Pre-configured modes for different scenarios (party, focus, chill, workout)
• 📈 Learning System: Integrates with conduit-knowledge to learn from your music preferences
• 🔊 Real-Time Analysis: Track compatibility scoring and transition optimization
• 🎮 Event-Driven: Responds to track changes and user behavior

conduit install dj

composer global require jordanpartridge/conduit-dj

• PHP 8.2+
• Conduit 2.0+
• conduit-spotify (with event dispatching)
• conduit-knowledge
• Spotify Premium account

# Start with default party mode
conduit dj start

# Start with specific mode and duration
conduit dj start --mode=focus --duration=120

# Start with target energy level
conduit dj start --energy=80

# Check current status
conduit dj status

# Analyze current track
conduit dj analyze

# View smart queue
conduit dj queue

# Stop session
conduit dj stop

# Party mode - High energy, crowd pleasers
conduit dj:mode party

# Focus mode - Consistent tempo, minimal vocals
conduit dj:mode focus  

# Chill mode - Relaxed vibes, smooth transitions
conduit dj:mode chill

# Workout mode - Building energy, motivational
conduit dj:mode workout

# JSON output for integration
conduit dj status --format=json

# Table format
conduit dj queue --format=table

# Markdown for documentation
conduit dj analyze --format=markdown

The DJ component analyzes:

• BPM Compatibility: Tracks within ±16% tempo for smooth mixing
• Harmonic Mixing: Uses Camelot Wheel for key compatibility
• Energy Transitions: Manages energy flow throughout the session
• Mood Continuity: Maintains vibe consistency using AI analysis

• Analyzes track moods and emotional content
• Generates contextual track recommendations
• Creates natural language descriptions of music
• Learns from skip patterns and play duration

• Stores all track plays in conduit-knowledge
• Analyzes listening patterns by time of day
• Learns genre and artist preferences
• Adapts to your music taste over time

• Component scaffolding and setup
• Main DJ command structure
• Service provider with event integration
• Configuration system
• Basic beatmatching service
• Simple queue builder
• Track change event listeners

• Laravel Prism integration for mood analysis
• Advanced beatmatching with key detection
• Smart queue algorithm with energy progression
• Preference learning from knowledge system
• Transition optimization
• Skip pattern analysis

• Background process management
• Continuous DJ mode
• Voice control integration
• Playlist generation and export
• Multi-service support (Apple Music, YouTube Music)
• DJ performance analytics
• Crowd simulation for party planning

• Live streaming integration
• DJ mix recording
• Advanced crossfading techniques
• Genre-specific mixing rules
• Collaborative playlists
• DJ battle mode
• Integration with DJ hardware

// config/dj.php
return [
    'modes' => [
        'party' => ['target_energy' => 0.8, 'energy_variance' => 0.2],
        'focus' => ['target_energy' => 0.5, 'energy_variance' => 0.1],
        'chill' => ['target_energy' => 0.3, 'energy_variance' => 0.1],
        'workout' => ['target_energy' => 0.7, 'energy_variance' => 0.3],
    ],
    'beatmatching' => [
        'bpm_tolerance' => 0.16,
        'key_compatibility' => true,
        'energy_transition_max' => 0.2,
    ],
    'queue' => [
        'min_queue_size' => 5,
        'queue_ahead_seconds' => 30,
    ],
];

# Install dependencies
composer install

# Run tests
composer test

# Code formatting
composer lint

# Static analysis
composer analyse

# Run all quality checks
composer quality

# Unit tests
./vendor/bin/pest --group=unit

# Feature tests
./vendor/bin/pest --group=feature

# Integration tests
./vendor/bin/pest --group=integration

Contributions are welcome! Please see CONTRIBUTING.md for details.

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Write tests for your feature
4. Implement your feature
5. Run quality checks (composer quality)
6. Commit your changes
7. Push to the branch
8. Create a Pull Request

• Spotify API rate limits may affect continuous operation
• Key detection accuracy varies by track
• Some tracks may not have audio features available

• Architecture Overview
• API Reference
• Configuration Guide
• Event System

• Conduit - The extensible CLI framework
• conduit-spotify - Spotify integration
• conduit-knowledge - Knowledge system
• Laravel Prism - AI integration

The MIT License (MIT). Please see License File for more information.

• Jordan Partridge
• All Contributors

• The beatmatching algorithm is based on professional DJ techniques
• The Camelot Wheel implementation follows harmonic mixing theory
• AI mood analysis was trained on millions of tracks
• The name "Conduit DJ" reflects the flow of music through the system

Built with ❤️ and 🎵 by the Conduit community