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.
Create personalized music playlists and rediscover forgotten songs from your library without needing any song details.
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Free · no card · unsubscribe anytimeAudioMuse-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.
AudioMuse-AI has 2.5k stars on GitHub. It has been forked 145 times. AudioMuse-AI is written mainly in Python. It has been in active development since 2025. AudioMuse-AI is available under the AGPL-3.0 license. Its main topics are clap, docker, emby, jellyfin.
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.
AudioMuse-AI is an open-source project. It is released under the AGPL-3.0 license.
Yes. AudioMuse-AI is free and open source — you can use, modify and self-host it. Its AGPL-3.0 license is a strong copyleft: if you distribute a modified version — including offering it as a network service — your changes must be released under the same license.
AudioMuse-AI is available under the AGPL-3.0 license.
AudioMuse-AI is written mainly in Python.
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