coder-music-cli 0.7.1

A command-line music application for coders with daemon support, radio streaming, and AI-generated music

music-cli

Code. Listen. Iterate.

A command-line music player for coders. Background daemon with radio streaming, local MP3s, and AI-generated music.

music-cli play --mood focus    # Start focus music
music-cli pause                # Pause for meeting
music-cli resume               # Back to coding
music-cli status               # Check what's playing + inspirational quote

Installation

# Install from PyPI
pip install coder-music-cli

# Or with uv (faster)
uv pip install coder-music-cli

# Install FFmpeg (required)
brew install ffmpeg       # macOS
sudo apt install ffmpeg   # Ubuntu/Debian
choco install ffmpeg      # Windows (or: winget install ffmpeg)

Optional: AI Music Generation

pip install 'coder-music-cli[ai]'  # ~5GB (PyTorch + Transformers + Diffusers)

Supports multiple AI models via HuggingFace: MusicGen, AudioLDM, and Bark.

Optional: YouTube Audio Streaming

pip install 'coder-music-cli[youtube]'  # ~10MB (yt-dlp)

Stream audio directly from YouTube URLs with automatic offline caching:

music-cli play -m youtube -s "https://youtube.com/watch?v=..."
music-cli play -m yt -s "https://youtu.be/..."  # Short alias
music-cli youtube                               # List cached tracks
music-cli youtube play 1                        # Play cached track offline

Features

• Daemon-based - Persistent background playback
• Multiple sources - Local files, radio streams, AI generation, YouTube audio streaming
• Context-aware - Selects music based on time of day and mood
• 35+ Radio Stations - Curated stations in English, French, Spanish, and Italian
• AI Music Generation - Generate music with MusicGen, AudioLDM, or Bark models
• YouTube Streaming - Extract and stream audio directly from YouTube URLs
• YouTube Offline Cache - Automatically cache YouTube audio for offline playback
• Version-aware Updates - Automatic notification when new stations are available
• Inspirational Quotes - Random music quotes with every status check
• Simple config - Human-readable text files

Quick Start

# Play
music-cli play                    # Context-aware radio
music-cli play --mood focus       # Focus music
music-cli play -m local --auto    # Shuffle local library
music-cli play -m youtube -s "https://youtube.com/watch?v=..."  # YouTube audio
music-cli play -m yt -s "https://youtu.be/..."  # YouTube (short alias)

Commands

Command	Description
play	Start playing (radio/local/ai/history/youtube)
stop / pause / resume	Playback control
status	Current track, state, and inspirational quote
next	Skip track (auto-play mode)
volume [0-100]	Get/set volume
radios	Manage radio stations (list/play/add/remove)
youtube	Manage cached YouTube tracks (list/play/remove/clear)
ai	Manage AI-generated tracks (list/play/replay/remove)
history	Playback log
moods	Available mood tags
config	Show configuration file locations
update-radios	Update stations after version upgrade
daemon start|stop|status	Daemon control

Radio Station Management

# List all stations with numbers
music-cli radios
music-cli radios list

# Play by station number
music-cli radios play 5

# Add a new station interactively
music-cli radios add

# Remove a station
music-cli radios remove 10

Pre-configured Stations

35 stations across 4 languages:

• English: ChillHop, SomaFM (Groove Salad, Drone Zone, DEF CON, etc.), BBC Radio 3
• French: FIP Radio, France Inter, France Musique, Mouv
• Spanish: Salsa Radio, Tropical 100, Los 40 Principales, Cadena SER
• Italian: Radio Italia, RTL 102.5, Radio 105, Virgin Radio Italy

Play Modes

# Radio (default)
music-cli play                     # Time-based selection
music-cli play -s "deep house"     # By station name
music-cli play --mood focus        # By mood

# Local
music-cli play -m local -s song.mp3
music-cli play -m local --auto     # Shuffle

# AI (requires [ai] extras)
music-cli play -m ai --mood happy -d 60

# History
music-cli play -m history -i 3     # Replay item #3

AI Music Generation

Generate unique audio with multiple AI models via HuggingFace:

# Install AI dependencies (~5GB: PyTorch + Transformers + Diffusers)
pip install 'coder-music-cli[ai]'

# Generate and manage AI music
music-cli ai play                              # Context-aware (default: musicgen-small)
music-cli ai play -p "jazz piano"              # Custom prompt
music-cli ai play -m audioldm-s-full-v2        # Use AudioLDM model
music-cli ai play -m bark-small -p "Hello!"    # Use Bark for speech
music-cli ai play --mood focus -d 30           # 30-second focus track
music-cli ai models                            # List available models
music-cli ai list                              # List all generated tracks
music-cli ai replay 1                          # Replay track #1
music-cli ai remove 2                          # Delete track #2

Available AI Models

Model ID	Type	Best For	Size
musicgen-small	MusicGen	Music generation (default)	~1.5GB
musicgen-medium	MusicGen	Higher quality music	~3GB
musicgen-large	MusicGen	Best quality music	~6GB
musicgen-melody	MusicGen	Melody-conditioned music	~3GB
audioldm-s-full-v2	AudioLDM	Sound effects, ambient audio	~1GB
audioldm-l-full	AudioLDM	High-quality audio generation	~2GB
bark	Bark	Speech synthesis, audio with voice	~5GB
bark-small	Bark	Faster speech synthesis	~1.5GB

AI Command Suite

Command	Description
ai models	List all available AI models
ai list	Show all AI-generated tracks with prompts
ai play	Generate music from current context
ai play -m <model>	Generate with specific model
ai play -p "prompt"	Generate with custom prompt
ai play --mood focus	Generate with specific mood
ai play -d 30	Generate 30-second track (default: 5s)
ai replay <num>	Replay track by number (regenerates if file missing)
ai remove <num>	Delete track and audio file

Features

• Multiple models - MusicGen, AudioLDM, and Bark model families
• Smart caching - LRU cache keeps up to 2 models in memory (configurable)
• Download progress - Progress bar shown during model downloads
• GPU memory management - Automatic cleanup when switching models
• Context-aware - Uses time of day, day of week, and session mood
• Custom prompts - Generate exactly what you want with -p
• Seamless looping - All tracks engineered for infinite playback
• Track management - List, replay, and remove generated tracks
• Regeneration - Missing files can be regenerated with original prompt
• Animated feedback - "composing..." animation while generating
• Persistent storage - Tracks saved to config directory

Requirements

• ~5GB disk space minimum (PyTorch + Transformers + Diffusers)
• ~8GB RAM minimum for generation (16GB recommended for larger models)
• Models are downloaded on first use

Configuration

Configure AI settings in ~/.config/music-cli/config.toml:

[ai]
default_model = "musicgen-small"  # Default model for generation

[ai.cache]
max_models = 2  # Max models to keep in memory (LRU eviction)

[ai.models.audioldm-s-full-v2.extra_params]
num_inference_steps = 10  # More = better quality, slower
guidance_scale = 2.5      # How closely to follow prompt

YouTube Offline Cache

YouTube audio is automatically cached for offline playback. When you play a YouTube URL, the audio is downloaded in the background and stored locally.

# Play YouTube audio (automatically cached)
music-cli play -m youtube -s "https://youtube.com/watch?v=..."

# Manage cached tracks
music-cli youtube                    # List all cached tracks
music-cli youtube cached             # Same as above
music-cli youtube play 3             # Play cached track #3 (works offline)
music-cli youtube remove 1           # Remove cached track #1
music-cli youtube clear              # Clear entire cache

YouTube Command Suite

Command	Description
youtube	List all cached tracks (default)
youtube cached	List cached tracks with cache statistics
youtube play <num>	Play cached track by number (offline)
youtube remove <num>	Remove a cached track
youtube clear	Clear all cached tracks

Features

• Automatic caching - Audio cached in background while streaming
• Offline playback - Play cached tracks without internet
• LRU eviction - 2GB cache limit with automatic cleanup of oldest tracks
• M4A format - 192kbps quality for good balance of size and quality
• Instant replay - Cached tracks play immediately

Configuration

Configure YouTube cache in ~/.config/music-cli/config.toml:

[youtube.cache]
enabled = true          # Enable/disable automatic caching
max_size_gb = 2.0       # Maximum cache size in GB

Cache Location

Cached files are stored in:

• Linux/macOS: ~/.config/music-cli/youtube_cache/
• Windows: %LOCALAPPDATA%\music-cli\youtube_cache\

Moods

focus happy sad excited relaxed energetic melancholic peaceful

Configuration

Configuration files location:

• Linux/macOS: ~/.config/music-cli/
• Windows: %LOCALAPPDATA%\music-cli\

File	Purpose
config.toml	Settings (volume, mood mappings, version)
radios.txt	Station URLs (name|url format)
history.jsonl	Play history
ai_tracks.json	AI track metadata (prompts, durations)
ai_music/	AI-generated audio files
youtube_cache.json	YouTube cache metadata
youtube_cache/	Cached YouTube audio files

Version Updates

When you update music-cli, you'll be notified if new radio stations are available:

# Check and update stations
music-cli update-radios

# Options:
# [M] Merge   - Add new stations to your list (recommended)
# [O] Overwrite - Replace with new defaults (backs up old file)
# [K] Keep    - Keep your current stations unchanged

Add Custom Stations

# Interactive
music-cli radios add

# Or edit directly: ~/.config/music-cli/radios.txt
ChillHop|https://streams.example.com/chillhop.mp3
Jazz FM|https://streams.example.com/jazz.mp3

Status & Quotes

The status command shows playback info plus a random inspirational quote:

$ music-cli status
Status: ▶ playing
Track: Groove Salad [radio]
Volume: 80%
Context: morning / weekday

"Music gives a soul to the universe, wings to the mind, flight to the imagination." - Plato

Version: 0.3.0
GitHub: https://github.com/luongnv89/music-cli

Documentation

Document	Description
User Guide	Complete usage instructions
AI Playbook	AI music generation guide with examples
Architecture	System design and diagrams
Development	Contributing guide

Requirements

• Python 3.9+
• FFmpeg
• Supported Platforms: Linux, macOS, Windows 10+

Changelog

v0.8.1

• Fix cached YouTube tracks not playing: reconnect options were incorrectly applied to local cached files instead of only remote streams

v0.8.0

• Add YouTube offline cache for automatic offline playback:
  • Automatically cache YouTube audio when played
  • Play cached tracks offline with music-cli youtube play <num>
  • Manage cache with music-cli youtube commands (list/play/remove/clear)
  • 2GB LRU cache with automatic eviction of oldest tracks
  • M4A format at 192kbps quality
  • Thread-safe cache operations
• Add youtube command group for cache management

v0.7.1

• Fix missing mood radio mappings: all 8 moods now have working radio streams
  • Added streams for: relaxed (Groove Salad), energetic (DEF CON Radio), melancholic (Indie Pop Rocks), peaceful (Drone Zone)
  • Fixed fallback to default config when user config lacks mood mappings

v0.7.0

• Add YouTube audio streaming support:
  • Stream audio directly from YouTube URLs without downloading
  • Support for youtube.com, youtu.be, YouTube Shorts, and YouTube Music URLs
  • Install with: pip install 'coder-music-cli[youtube]'
  • Play with: music-cli play -m youtube -s "https://youtube.com/watch?v=..."
  • Short alias: music-cli play -m yt -s "https://youtu.be/..."
• Fix version sync between pyproject.toml and init.py

v0.6.0

• Add AI model management commands:
  • music-cli ai models download <model> - Download models before use
  • music-cli ai models delete <model> - Delete cached models to free space
  • music-cli ai models set-default <model> - Set default generation model
• Add model descriptions and expected sizes to ai models output
• Add download status tracking via HuggingFace cache inspection
• Add comprehensive AI Playbook documentation with examples
• Improve config fallback to DEFAULT_CONFIG when user config is missing AI settings

v0.5.0

• Add multiple AI model support:
  • AudioLDM models: audioldm-s-full-v2, audioldm-l-full for sound effects and ambient audio
  • Bark models: bark, bark-small for speech synthesis
  • MusicGen models: All existing models continue to work
• Add ai models command to list all available AI models
• Add LRU cache for AI models with configurable size (default: 2 models)
• Add download progress bar during model downloads
• Add GPU memory management with automatic cleanup on model eviction
• Default model: musicgen-small

v0.4.1

• Add Windows 10+ support
  • Platform abstraction layer for cross-platform compatibility
  • TCP localhost IPC on Windows (Unix sockets on Linux/macOS)
  • stdin-based pause/resume on Windows (signals on Linux/macOS)
  • Windows-specific config directory (%LOCALAPPDATA%\music-cli\)
• Add Windows to CI test matrix

v0.4.0

• Add music-cli ai command suite for AI track management
  • ai list - Display all AI tracks with prompts
  • ai play [-p "prompt"] - Generate with context or custom prompt
  • ai replay <num> - Replay track (regenerates if missing)
  • ai remove <num> - Delete track and audio file
• Add seamless looping via prompt engineering
• Add context-aware AI generation (time of day, day of week, mood)
• Default AI duration reduced to 5s for faster generation

v0.3.0

• Add radio station management (list/play/add/remove by number)
• Add 35 curated radio stations (English, French, Spanish, Italian)
• Add version-aware config with update-radios command
• Add inspirational quotes to status command
• Add "composing..." animation for AI generation
• Save AI-generated music to persistent directory for replay
• Show GitHub link in status output
• Remove audiocraft dependency (use transformers only)

v0.2.0

• Switch to HuggingFace Transformers for AI music generation
• Auto-loop AI-generated tracks
• Pin transformers<4.51 for MusicGen compatibility
• CI/CD improvements

v0.1.0

• Initial release
• Daemon-based playback
• Radio streaming, local files, AI generation
• Context-aware music selection
• Mood support

License

MIT