Sonobarr

Sonobarr is a web-based music discovery tool that integrates directly with a Lidarr music library and Last.fm similarity data to surface artists a user is likely to enjoy. It provides a modern, real-time UI, administrative controls, and optional AI-assisted seeding for discovery sessions.

Key Features

• Deep Lidarr integration: sync monitored artists, apply per-source monitor strategies, and add candidates back to Lidarr with chosen quality/metadata settings
• Last.fm and ListenBrainz-powered discovery: batch similarity lookups streamed to the client as candidate artist cards with stats and genres
• Real-time UI: Flask backend with Socket.IO keeps discovery progress, notifications, and actions in sync across connected clients
• AI assistant: optional OpenAI-compatible prompt interface to seed discovery sessions with vibe/genre-based suggestions
• Preview and enrichment: YouTube/iTunes previews, Last.fm biographies, and MusicBrainz matching for added context
• Role-based access and admin tooling: user management, request/approval workflow for non-admin requests, and audit trails
• Docker-first deployment and automatic migrations: official container image, config via .env, and SQLite-based persistent store

Use Cases

• Allow a home music server to recommend new artists based on an existing Lidarr collection
• Provide a shared discovery interface for friends or household members with admin-moderated requests
• Seed curated discovery sessions using natural-language prompts to explore new artists and tastes

Limitations and Considerations

• Discovery relies on external services (Lidarr, Last.fm, optional YouTube/ListenBrainz); those APIs and credentials are required for full functionality
• Default persistent store is SQLite, which is suitable for single-instance/home use but may be limiting for large multi-tenant deployments
• AI features require an OpenAI-compatible API endpoint and valid credentials; the assistant is disabled without them

Sonobarr is focused on bridging a managed Lidarr library with discovery sources to streamline artist discovery and additions. It is optimized for Docker-based home or small-group deployments and emphasizes a fast, real-time user experience.