- 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.
- Rearranged imports for consistency in useModelDownloadToast hook.
- Improved logging in useModelDownloadToast for better debugging during download events.
- Updated progress calculation to handle cases where progress exceeds 100%.
- Enhanced toast notifications to reflect download completion and error states.
- Introduced throttling in ProgressManager to optimize SSE updates and prevent overwhelming clients.
- Added new test scripts for monitoring SSE events during model downloads, ensuring accurate progress reporting.
- Rearranged imports for consistency across components.
- Enhanced the ModelManagement component to include detailed logging for download actions and errors.
- Updated the ModelProgress component to connect to SSE only when actively downloading, preventing connection exhaustion.
- Added a downloading state to the model status to indicate ongoing downloads.
- Improved toast notifications for model downloads with completion and error callbacks.
- Refactored the useModelDownloadToast hook to support new callbacks for download completion and error handling.
- Updated backend model status to reflect downloading state during active downloads.
- Added a step to install PyTorch with CUDA for Windows in the release workflow.
- Updated model references in backend/main.py to use openai/whisper models instead of mlx-community for the MLX backend.
- Bumped version numbers for @voicebox/app, @voicebox/landing, @voicebox/tauri, and @voicebox/web to 0.1.11.
- Added a new `useAutoUpdater` hook to check for app updates on startup and notify users with toast messages.
- Enhanced `UpdateStatus` component to handle version retrieval errors more gracefully.
- Updated dependencies in `package.json` for Tauri plugins to support new update functionalities.
- Added a default `type` prop set to 'button' in the CircleButton component to ensure proper button behavior.
- Enhanced the component's flexibility by allowing the type to be overridden through props.
- Implemented delete confirmation dialogs for both HistoryTable and SampleList components to enhance user experience and prevent accidental deletions.
- Added state management for handling the selected item to be deleted and the visibility of the delete dialog.
- Refactored delete handling functions to utilize the new dialog confirmation flow, improving code clarity and maintainability.
- Added `clear_profile_cache` function to manage cache files for specific profiles.
- Integrated cache clearing in `add_profile_sample`, `delete_profile`, and `delete_profile_sample` functions to ensure stale audio caches are invalidated after modifications.
- Enhanced `clear_voice_prompt_cache` to also delete combined audio files, improving overall cache management.
- Introduced a new directory for manual test scripts aimed at debugging and validating backend functionality.
- Added README.md detailing the purpose and usage of various test scripts, including tests for TTS generation, model downloads, and progress tracking.
- Included an __init__.py file to define the test suite structure and provide context for the tests.
- Introduced methods to check if models are cached locally in MLX and PyTorch backends.
- Enhanced progress tracking during model loading to filter out non-download progress when models are cached.
- Updated HFProgressTracker to conditionally report progress based on download status.
- Added test scripts for monitoring SSE events during model downloads and verifying progress tracking functionality.
- Improved overall error handling and logging for better debugging during model download processes.
- Updated HistoryTable to implement infinite scrolling for loading history items dynamically.
- Introduced state management for accumulated history and total item count.
- Added Intersection Observer for triggering additional data fetches when scrolling.
- Implemented cache clearing functionality in the backend to manage voice prompt caches effectively.
- Improved loading indicators and user feedback for data fetching states.
- Refactored code for better readability and maintainability.
- Replaced direct Tauri API calls with a unified platform context across multiple components, enhancing code maintainability and readability.
- Removed the deprecated tauri.ts file, consolidating platform-related logic into the new PlatformContext.
- Updated components such as App, AudioPlayer, and ServerSettings to utilize the new platform context for lifecycle management and server interactions.
- Improved platform detection and handling for audio playback and system audio capture functionalities.
- Ensured consistent error handling and user feedback across the application when interacting with platform-specific features.
- Modified the file extension filters in useHistory.ts and useProfiles.ts to only allow 'zip' files, removing 'voicebox.zip' for a more streamlined export process.
- Added user-selected read-write permission in Entitlements.plist to enhance file handling capabilities.
- Updated README.md to highlight MLX backend performance improvements on Mac with Metal acceleration.
- Refined ProfileCard and ProfileForm components by optimizing imports and improving error handling for avatar uploads.
- Adjusted landing page content to better describe features, including a new multi-voice narrative editor and performance optimizations for different platforms.
- Bumped version to 0.1.11 in Cargo.lock to reflect recent changes.
- Updated hidden imports in build_binary.py to replace 'mlx_audio.asr' with 'mlx_audio.stt'.
- Enhanced model loading logic in MLX and PyTorch backends to ensure proper progress tracking during model downloads.
- Improved error handling and context management for progress tracking in both backends.
- Bumped version to 0.1.10 in Cargo.lock to reflect recent changes.
Jamie Pine