NeptuneHub/AudioMuse-AI
AudioMuse-AI uses sonic analysis to rediscover forgotten songs, uncover hidden connections in your music library, and generate intelligent playlists for Navidrome, Jellyfin, LMS, Lyrion, Emby and Plex: no metadata or external services required. observed · 2026-08-28
Health v2 · maintenance only
81/100
- Activity 99
- Release rhythm 86
- Longevity 33
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: 2.0
- age_days: 466
- days_rel: 12
- days_push: 7
- n_releases_24m: 83
Adoption not part of the score
2496 stars · 145 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
AudioMuse-AI is a self-hosted application that performs sonic analysis on your music library to generate intelligent, AI-driven playlists without relying on metadata or external services. It integrates with self-hosted music servers like Navidrome, Jellyfin, LMS, Lyrion, Emby, and Plex, offering features like clustering, instant playlists, and a visual music map.
Use cases
- generate smart playlists from my local music library
- find sonically similar songs in my collection
- create playlists for Navidrome or Jellyfin automatically
- visualize my music library as a 2D map
- rediscover forgotten songs in my music collection
- generate playlists from natural language prompts like 'high-tempo low-energy'
- analyze music across multiple media servers with duplicate detection
When to choose
- you self-host music on Navidrome, Jellyfin, Plex, Emby, LMS, or Lyrion and want AI-generated playlists
- you want playlist generation based on actual audio characteristics rather than metadata or external APIs
- you want to explore and visualize your music library's sonic landscape
- you want a self-hosted, privacy-friendly alternative to streaming service recommendation engines
When to avoid
- you use a cloud streaming service like Spotify or Apple Music instead of self-hosted music servers
- you only need simple metadata-based playlists without audio analysis
- you cannot run Docker, Kubernetes, or native desktop applications
- your library is very small and manual playlist curation is sufficient
Facets
application · maturity active
machine-learning audio-processing nlp data-visualization self-hosted audio media machine-learning self-hosted windows self-hosted cross-platform sonic-analysis playlist-generation music-library navidrome jellyfin plex emby lyrion lms clap librosa onnx llm smart-playlists music-map audio docker kubernetes linux macos
2 sources
- readme: https://github.com/NeptuneHub/AudioMuse-AI · fetched 2026-08-28 · cebd692b8d02
- homepage: https://neptunehub.github.io/AudioMuse-AI/ · fetched 2026-08-29 · 168595c4b884
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| NeptuneHub/AudioMuse-AI | main | 81 |
For agents
markdown · JSON · MCP: product_card(name="NeptuneHub/AudioMuse-AI")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem