🎵 Music bot for my private Discord server, powered by discord-player

• Music playback from YouTube
  • On-disk Opus file cache for subsequent streams
• Cached search powered by Spotify or YouTube
• Relies heavily on slash commands and message components
• Playlists stored in a dedicated channel
• Spotify-like volume normalization
• Recovery mechanism to continue listening after an error
• Redis-backed playback statistics
• AI-powered queue control with the /prompt command
• Maintenance mode that uses Kubernetes' API
• Lockdown mode for restricting command access temporarily
• Tic-tac-toe
• Friendly /help command
• Integration with Sentry
• Extensive logging powered by Pino
• Easy deployment with a Helm chart

You have two options:

1. Use the Helm chart (recommended)
2. Use the Docker image from either Docker Hub or GitHub Container Registry

First, install the Node.js version defined in the .nvmrc file and pnpm (ideally through Corepack).

# Install dependencies
$ pnpm install

# Start the bot in development mode
$ pnpm start

# Build the bot for production
$ pnpm build

# Lint, type check, and test
$ pnpm lint && pnpm tsc && pnpm test

# Test with coverage report
$ pnpm test:coverage

If you are using VS Code or a compatible editor, you can start the bot with a debugger attached using the debug task.

The bot was designed to be used on a single Discord server, on a small scale – typically on one voice channel at once. Therefore, it doesn't scale well horizontally.

• the Docker images are tagged with commit SHAs
• the Helm chart uses a MAJOR.MINOR.PATCH format where:
  • the PATCH increases with each Docker image update
  • the MINOR increases when other changes are made to the chart itself, e.g., when a Redis version is updated

The project should be consider to be in a pre-alpha stage:

• frequent nightly builds are released
• breaking changes occur often
• existing features may evolve or be removed without notice

No timeline for an alpha/beta release is planned.

Please read the Legal Disclaimer before using this software.

This project contains code generated by Large Language Models (LLMs), under human supervision and proofreading.

MIT