- Removed unnecessary class from the FloatingGenerateBox button for cleaner styling.
- Updated HistoryTable to remove redundant class from the delete button.
- Reorganized imports in dropdown-menu for better readability.
- Enhanced useAutoUpdater hook with improved dependency management and updated icon usage.
- Deleted obsolete useAutoUpdater.ts file to streamline codebase.
- Added platform detection for macOS and Windows to improve user experience.
- Updated UI to conditionally disable options and provide clearer guidance based on installed providers.
- Refactored button states and labels for PyTorch CUDA and CPU to reflect availability and download status accurately.
- Enhanced text descriptions for TTS providers, clarifying the functionality of PyTorch CUDA and Apple MLX.
- Removed outdated references to availability and added notes regarding model version differences.
- Improved UI structure by ensuring consistent labeling and disabling options based on system compatibility.
- Replaced python3-pip with python3.12-venv in the installation process.
- Added commands to ensure pip is upgraded and installed after setting Python 3.12 as the default.
- Streamlined the installation of PyTorch by removing redundant pip upgrade command.
- Introduced a new DataFolders component to display and manage paths for application data, models, and providers.
- Implemented a FolderRow component for individual folder display, including loading states and open folder functionality.
- Added API client methods and hooks to fetch system folder paths from the backend.
- Updated ServerTab to include the new DataFolders component, enhancing server settings management.
- Removed unnecessary line breaks in the rendering of radio buttons and labels for a cleaner code structure.
- Added missing imports for numpy and scipy in build_binary.py to ensure proper functionality.
- Updated binary Assets.car file to reflect recent changes.
- Adds tooltips on hover for buttons of the generate box
- Replaces the message square icon with a sliders icon for the instruction mode toggle.
- Adds a tooltip to the instruction mode toggle button.
- Updates the placeholder text for the input field.
- Introduced a loading state to indicate when a provider is starting, enhancing user experience.
- Disabled radio buttons and action buttons during the loading state to prevent user interaction.
- Updated UI elements to reflect the loading state, including a spinner and appropriate cursor styles.
- Added environment variables to Dockerfiles to set non-interactive mode and configure the timezone to UTC.
- Included installation of `tzdata` in both Dockerfiles to support timezone configuration during the build process.
- Added support for packaging provider archives in the release workflow, creating platform-specific zip and tar.gz files for distribution.
- Updated the `.gitignore` to exclude `.spec` files.
- Introduced a new `CudaDownloadSection` component to manage CUDA downloads, including progress tracking and error handling.
- Refactored provider download logic to handle archive extraction and cleanup after download.
- Improved subprocess output handling in the provider manager for better logging and error reporting.
- Revised README to include links for downloading the latest releases for macOS, Windows, and Linux.
- Added detailed instructions for running Voicebox with Docker, including Docker Compose usage.
- Updated installation documentation to reflect Linux availability and provide specific download options for AppImage and Deb packages.
- Enhanced clarity in Docker documentation regarding accessing the web UI.
- Added functionality to create log files for provider output, improving debugging on Windows.
- Updated error handling to read from log files instead of using subprocess output directly.
- Enhanced logging messages to include log file locations for easier troubleshooting.
- Introduced Docker support with CPU-only and GPU-enabled configurations via Dockerfiles and docker-compose files.
- Added a .dockerignore file to exclude unnecessary files from Docker images.
- Updated bun.lock and package.json to include new dependencies for icon handling.
- Enhanced README with Docker usage instructions and deployment options.
- Refactored components to utilize new icon libraries for improved UI consistency.
- Removed `lucide-react` version 0.454.0 and downgraded to version 0.316.0 in `bun.lock`.
- Added `@tailwindcss/vite` and `tailwindcss` as development dependencies in `package.json`.
- Updated Vite configuration to include Tailwind CSS plugin.
- Set the HTML document to use a dark theme by adding the `class="dark"` attribute to the `<html>` tag.
- Included a conditional installation of CPU-only PyTorch packages for Ubuntu 22.04 to reduce unnecessary CUDA dependencies.
- Updated the release workflow to ensure compatibility with CPU-focused builds on Linux.
- Changed the backend setting for Windows from "none" to "pytorch" to ensure compatibility with bundled PyTorch CPU providers.
- Updated comments for clarity regarding the Windows setup.
- Clarified the bundling of PyTorch CPU providers for Windows and macOS Intel builds in documentation.
- Improved handling of platform-specific dependencies in the build process, including asyncio support for PyInstaller.
- Updated backend logic to gracefully handle missing dependencies and provide clearer error messages.
- Enhanced progress management to ensure compatibility with PyInstaller's async handling.
- Removed unnecessary exclusions from the build scripts for PyTorch providers to streamline the build process.
- Updated the `ProviderSettings` component to log the current active provider.
- Changed the provider health status to use specific names for MLX and PyTorch backends.
- Removed unnecessary exclusions from the build scripts for both PyTorch CPU and CUDA providers.
- Ensured consistency in the `.spec` files for PyTorch providers by aligning exclusion lists.
- Renamed `bundled-mlx` to `apple-mlx` for clarity in provider types.
- Updated the ProviderSettings component to reflect the new provider naming.
- Improved logging for provider startup and error handling in the backend.
- Added scripts for building and installing PyTorch CPU and CUDA providers locally.
- Enhanced the documentation to include details on TTS provider architecture and development setup.
- Added macOS support for PyTorch CPU providers in the release workflow.
- Updated the ProviderSettings component to handle macOS-specific conditions and improve UI interactions.
- Refactored the radio group component styles for better accessibility and visual consistency.
- Improved provider management logic to ensure proper handling of available providers across different platforms.
- Renamed `load_model` to `load_model_async` in TTS provider classes for clarity and consistency.
- Added compatibility alias for `load_model` to maintain existing functionality.
- Enhanced `get_model_status` to handle both synchronous and asynchronous check functions.
- Updated version numbers in `bun.lock` and `Cargo.lock` to 0.1.12, reflecting recent changes.
- Introduced a new `linux.rs` module for audio capture, indicating that audio capture is not supported on Linux at this time.
- Updated `mod.rs` to include the Linux module conditionally based on the target OS.
- Commented out the PyTorch CPU configuration in the release workflow for Ubuntu 22.04.
- Updated TTS provider documentation to clarify options for Windows and Linux users.
- Enhanced build scripts for both CPU and CUDA providers by excluding large unused modules to reduce binary size.
- Updated the release workflow to include a new configuration for the Ubuntu 22.04 platform without TTS bundled.
- Added the @radix-ui/react-radio-group dependency to package.json.
- Implemented a new RadioGroup component for better UI handling of radio inputs.
- Introduced a new attribute `_current_model_size` in `LocalProvider` to store the current model size, allowing for dynamic configuration during generation.
- Updated the `generate` method to use the current model size instead of a hardcoded value.
- Modified the `load_model` method to track the requested model size.
- Removed platform-specific extension handling from the build scripts for both CPU and CUDA providers to streamline the build process.
- Added support for TTS providers in the backend, including endpoints for listing, starting, stopping, and downloading providers.
- Enhanced the release workflow to build and upload TTS provider binaries for both Windows and Linux platforms.
- Updated the architecture documentation to reflect the new provider system and its benefits for modularity and user experience.
- Introduced a new `ProviderSettings` component in the frontend for managing provider configurations.
- Updated caching methods in MLX, PyTorch, and backend to ensure models are fully downloaded before being marked as cached.
- Improved progress tracking to filter out non-download progress and provide accurate feedback during model downloads.
- Enhanced HFProgressTracker to skip non-byte progress bars and ensure meaningful progress reporting.
- Refactored progress initialization to provide immediate feedback while fetching metadata from HuggingFace.
- Added error handling and logging for better debugging during cache checks and download processes.
Jamie Pine