AudioMuse-AI
Where Music Takes Shape
Loading…
Click any underlined number to open the full list.
Queue Workers Each worker container spins up two RQ workers: one serving the high priority queue and one serving the default queue. So a single physical node usually shows up as two rows here.
Loading…
| Hostname | State | Queues | OK | Fail | Current Job |
|---|---|---|---|---|---|
| Loading… | |||||
Recent tasks The last 10 completed top-level tasks. This is the full history AudioMuse-AI keeps: only the newest 10 rows are retained.
Loading…
| Type | Status | Duration | When | Note |
|---|---|---|---|---|
| Loading… | ||||
Library The catalogue is every analyzed song across all your music servers, deduplicated: a song present on two servers is counted once.
Loading…
Genres Every analyzed song is counted once, under the mood that scored highest in its vector (the closest proxy for "genre" in this library). All detected genres are shown.
Moods Coverage Emotional mood breakdown (danceable, aggressive, happy, party, relaxed, sad) summed across every song’s mood vector.
Tempo Profile Distribution of songs across tempo buckets: Slow (<85 BPM), Medium (85–110), Fast (110–140), Very Fast (≥140).
Scheduled Tasks Every schedule is catalogue-wide: a batch task always runs against all configured music servers, one server at a time. "Last triggered" is when the schedule last fired, not when the job last succeeded: a run skipped because another main task was already active still counts as triggered.
Loading…
| Name | Type | Cron | Enabled | Last Triggered |
|---|---|---|---|---|
| Loading… | ||||