- Implemented API endpoints for exporting and importing voice profiles as ZIP archives.
- Enhanced the frontend with new hooks and components for profile export and import, including file handling and user dialogs.
- Integrated Tauri plugins for file system access and dialog interactions to facilitate seamless user experience.
- Updated ProfileCard and ProfileList components to support new export and import features, improving overall functionality.
- Added necessary error handling and validation for file operations to ensure robustness.
- Added a new API endpoint to serve profile sample audio files.
- Introduced a method in the apiClient to generate sample audio URLs.
- Refactored the SampleList component to utilize the new API for audio playback, enhancing the user experience.
- Cleaned up unused imports and optimized the handlePlay function for better performance.
- Added new Tauri plugins: @tauri-apps/plugin-process and @tauri-apps/plugin-updater to improve application capabilities.
- Introduced UpdateStatus component to display update information in the UI.
- Enhanced GenerationForm to include an optional instruct field for additional input.
- Refactored various components for improved styling and responsiveness, including Sidebar, AudioPlayer, and ProfileCard.
- Updated API models and schemas to accommodate new instruct parameter in generation requests and responses.
- Improved documentation for autoupdater setup and usage.
- Added exclusions for 'torch.utils.tensorboard', 'scipy', 'PIL', 'tkinter', 'unittest', and 'test' to reduce bundle size and improve build efficiency.
- Renamed backend development script from `dev:backend` to `dev:server` for clarity.
- Added new macOS icon assets and configuration files for the application.
- Enhanced App component to improve server management during production and development modes.
- Updated ConnectionForm to reset state after successful submission and conditionally render the update button.
- Implemented database initialization on application startup in the backend.
- Install llvm-dev on Ubuntu for llvmlite compilation
- Install LLVM via Homebrew on macOS and configure PATH
- Exclude matplotlib, IPython, notebook, pytest, tensorboard from bundle to reduce size
- Keep --onefile mode with module exclusions to avoid 4GB limit
Jamie Pine