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Release Date: August 21, 2026
AudioMuse-AI v3.4.0 introduce fixes to the calculation of Energy, Tempo, Key and Scale, making these values more accurate and consistent. While AudioMuse-AI itself mainly uses this information only for the Instant Playlist (chat) functionality, external applications integrating with AudioMuse-AI may rely on these values more extensively.
Important
If these values are important to your use case, a partial re-analysis is recommended. Clear the existing tempo, energy, key and scale values from the database to trigger their recalculation during the next analysis. Other AudioMuse-AI functionality does not require this data.
Before change the database remember to do a backup.
This release also fixes the native build to avoid forked processes, improving consistency across platforms and addressing issues affecting macOS analysis. Additionally, it includes minor improvements to idle RAM reclamation on the container version.
Database Reset Procedure
Below different way to clean tempo, energy, key and scale from the database to trigger a new analysis. Remember to put your actual access value of your database.
Docker Compose
docker compose exec -T -e PGPASSWORD=audiomusepassword postgres psql -U audiomuse -d audiomusedb -c "UPDATE score SET tempo = NULL, energy = NULL, key = NULL, scale = NULL;"Kubernetes
kubectl -n playlist exec deploy/postgres-deployment -- env PGPASSWORD=audiomusepassword psql -U audiomuse -d audiomusedb -c "UPDATE score SET tempo = NULL, energy = NULL, key = NULL, scale = NULL;"Direct psql (standalone PostgreSQL)
PGPASSWORD=audiomusepassword psql -h 127.0.0.1 -p 5432 -U audiomuse -d audiomusedb -c "UPDATE score SET tempo = NULL, energy = NULL, key = NULL, scale = NULL;"What's Changed
- Ram cleaning improvement by @NeptuneHub in #865
- Code refactoring by @NeptuneHub in #866
- fix build noavx2 by @NeptuneHub in #867
- Scale-Tempo-Energy fix + Native build fix by @NeptuneHub in #870
Full Changelog: v3.3.1...v3.4.0