Release Content:
This release marks a significant upgrade to AudioMuse-AI, introducing robust asynchronous processing for also for playlist clustering, alongside smarter playlist generation and a refined user interface.
Key Features & Improvements:
- Asynchronous Processing (Backend):
- Celery Integration: Playlist clustering are now handled asynchronously using Celery, preventing UI freezes and allowing long-running tasks to execute in the background (previously only music analysis was async)
- Real-time Task Tracking: A unified system provides real-time status updates and detailed logs for both analysis and clustering tasks, including progress bars and current album information during analysis.
- Task Cancellation: Users can now cancel ongoing analysis or clustering tasks directly from the UI.
- Smarter Playlist Generation:
- Weighted Diversity Score: The playlist clustering algorithm now incorporates a "Weighted Diversity Score." This new metric considers not only the variety of predominant moods across generated playlists but also the confidence of those mood predictions, resulting in more musically distinct and meaningful clusters. This empower the result that can be obtain by the multiple cluster run.
- User Interface (UI/UX) Enhancements:
- Improved Playlist Display: Fixed the "Show Tracks" button for discovered clusters, allowing seamless expansion and viewing of tracks within each generated playlist.
- Automated Playlist Loading: Playlists are now automatically fetched and displayed in the UI upon successful completion of the clustering process.
- Dynamic Button States: Action buttons (Start Analysis, Generate Playlists, Fetch Saved Playlists, Cancel) now correctly enable and disable based on the current task status, providing clearer user feedback.
- Application Renaming: The main application title has been updated to "AudioMuse-AI - Music Analyzer & Playlist Generator".