- Documents entire problem from 3GB installer to GitHub 2GB limit
- Analyzes compression test failure (1% reduction)
- Compares 7 different hosting options
- Cost analysis for each approach
- Recommends Cloudflare R2 (free egress, ~/usr/bin/bash.04/month)
- Technical implementation details for all options
- Complete research document for decision making
GitHub has a 2GB limit on release assets, but the CUDA binary is ~2.5GB. Added compression test script to check if 7z can get it under the limit. If not, we'll need external hosting (S3/Azure).
Problem: The server binary with CUDA support was 2.9GB, causing:
- MSI installer failures in CI (WiX can't handle 3GB files)
- Massive downloads for all users (even those without GPUs)
- Poor user experience
Solution: Build two separate server binaries:
- voicebox-server.exe (CPU-only, ~295MB) - ships with installer
- voicebox-server-cuda.exe (CUDA, ~2.9GB) - optional download
Changes:
- backend/build_binary.py: Added 'variant' parameter for CPU/CUDA builds
- backend/build_cpu.bat: Script to build CPU-only binary
- backend/build_cuda.bat: Script to build CUDA binary
- backend/build_both.bat: Script to build both binaries
- backend/build_cpu.sh: Unix build script for CPU binary
- .github/workflows/release.yml: Build both variants, upload CUDA separately
- tauri/vite.config.ts: Externalize Tauri plugins to fix build
- docs/dual-server-binaries.md: Complete documentation
Results:
- Installer size reduced from 3GB to ~500MB (6x smaller)
- CI builds now succeed (WiX can handle 500MB)
- GPU users can opt-in to download CUDA support
- Better bandwidth usage for CPU-only users
Next steps:
- Frontend implementation to detect GPU and download CUDA binary
- Settings UI to toggle between CPU/CUDA modes
Co-Authored-By: Claude Sonnet 4.5 (1M context) <[email protected]>
- Added support for MLX backend on Apple Silicon, enabling optimized performance for TTS and STT tasks.
- Implemented platform detection to dynamically select between MLX and PyTorch based on the runtime environment.
- Updated build process to include MLX-specific dependencies and configurations for macOS.
- Refactored backend code to improve model loading and inference logic, accommodating backend-specific requirements.
- Enhanced documentation to clarify backend selection and performance benefits for different platforms.
- Streamlined installation instructions and troubleshooting guidance for MLX-related issues.
- Updated MLX_AUDIO.md to reflect validated status and included detailed validation results, model mapping, and API usage examples.
- Added a demo script (demo.py) for testing audio generation speed and functionality.
- Introduced a test script (test_tts.py) to validate MLX audio model loading and generation, ensuring robust testing for future developments.
- Created a .gitignore file in the mlx-test directory to exclude unnecessary files from version control.
- Introduced a new backend for MLX audio to enable GPU acceleration on macOS Apple Silicon, improving performance and user experience.
- Implemented platform detection to switch between MLX and PyTorch backends based on the runtime environment.
- Added new streaming capabilities for TTS and STT, enhancing real-time audio generation.
- Updated API endpoints and frontend components to support new features while maintaining backward compatibility.
- Created documentation for backend integration and performance comparisons.
- Removed unnecessary isDownloading variable and related logic.
- Consolidated model download state reset to the finally block for improved clarity and reliability.
- Enhanced error handling by ensuring model download state is reset in case of failure.
- Reorganized import statements for clarity and consistency.
- Adjusted formatting of state declarations for better readability.
- Streamlined JSX structure for improved visual hierarchy.
- Updated dialog descriptions for consistency in presentation.
- Made minor adjustments to spacing and layout for enhanced UI consistency.
- Created a new .npmrc file to enforce bun usage.
- Bumped version numbers for multiple packages to 0.1.9 in bun.lock.
- Added react-sound-visualizer dependency to enhance audio visualization features.
- Introduced convert:assets script in package.json for asset optimization.
- Updated CONTRIBUTING.md with instructions for converting assets to web formats.
- Added documentation files for API endpoints and developer guidelines in the docs directory.
- Updated CONTRIBUTING.md to include instructions for building with a local Qwen3-TTS development version, facilitating easier testing and development.
- Refactored FloatingGenerateBox component to streamline the rendering of text and instruct fields, improving code readability and maintainability.
- Added functionality to handle auto-resizing of text areas based on content changes, enhancing user experience.
- Improved event handling for keyboard interactions in StoryTrackEditor, allowing for play/pause functionality with the spacebar.
- Introduced a MiniSamplePlayer component in SampleList for better audio playback control, including play, pause, and seek features.
- Implemented sample update functionality in the backend, allowing users to edit reference text for audio samples, with appropriate error handling and user feedback.
- 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 a new UpdateNotification component to inform users about available updates and facilitate installation.
- Integrated useAutoUpdater hook for managing update checks and installations.
- Updated package.json with new build and generate scripts for release preparation and key generation.
- Enhanced tauri configuration to support autoupdater with signing keys and endpoints.
- Created scripts for preparing signed releases and updating icons, ensuring a streamlined workflow for asset management.
- Added detailed documentation for autoupdater setup and icon update workflow.
Jamie Pine