Generations now return immediately with a 'generating' status and appear
in history right away. TTS runs in a serial background queue to avoid
GPU contention. Users can kick off multiple generations without blocking.
- Async POST /generate creates DB record immediately, queues TTS work
- Serial generation queue prevents concurrent GPU access (Metal/CUDA/CPU)
- SSE endpoint GET /generate/{id}/status for real-time completion tracking
- Retry endpoint POST /generate/{id}/retry for failed generations
- Store engine and model_size on generation records for retry support
- History cards show animated loader (react-loaders) for generating/playing
- Failed generations show retry button instead of actions menu
- Model downloads happen inline in the queue instead of rejecting with 202
- Stale 'generating' records marked as failed on server startup
- Autoplay on generate setting (default: on)
- Show engine name on generation cards
- Remove sidebar generation spinner
- Checkbox alignment fix in settings
- Add model folder migration with byte-level progress tracking (backend + UI)
- Custom models directory support via VOICEBOX_MODELS_DIR env var passed to sidecar
- Hardcoded model descriptions displayed in model detail cards
- Open model folder button in storage location row
- Remove 'not downloaded' badge from model cards
- Fix server settings scroll offset for audio player
- Fix shell open permission to allow file paths
- Add normalize toggle to generation settings
Text exceeding max_chunk_chars (default 800) is automatically split at
sentence boundaries, generated per-chunk, and concatenated with a 50ms
crossfade. Works with all engines (Qwen, LuxTTS, Chatterbox, Turbo).
- Abbreviation-aware sentence splitter (Dr., Mr., e.g., decimals)
- CJK sentence-ending punctuation support
- Paralinguistic tag preservation ([laugh], [cough], etc.)
- Per-chunk seed variation to avoid correlated RNG artefacts
- Per-chunk Chatterbox trim (catches hallucination at each boundary)
- max_chunk_chars exposed as per-request param on GenerationRequest
- Text max_length raised to 50,000 characters
Closes#99
- Initialize lastSerializedRef to empty string so first-mount hydration
always runs (fixes initial value not rendering)
- Guard arrow-key menu nav against empty filteredTags (avoids NaN index)
- Disable ARIA role/multiline and detach event handlers when disabled
- Add onBlur to close autocomplete dropdown when editor loses focus
- Chain exception with 'from e' in unload endpoint for better tracebacks
Apply local-var-then-assign pattern to chatterbox_backend.py (multilingual)
to match the turbo backend. Also use _current_model_size fallback in
unload, delete, and status endpoints for consistent Qwen model size checks.
- POST /models/{model_name}/unload — unloads a specific model from
memory without deleting from disk, supports all engine types
- Frontend: Unload button in model detail dialog when model is loaded
- Delete button remains disabled while loaded (unload first)
- save_audio() now writes to .tmp then os.replace() for atomic writes
- /generate endpoint catches OSError with specific messages for ENOENT, EACCES, ENOSPC, and BrokenPipeError
- New /health/filesystem endpoint checks directory existence, write permissions, and disk space
- New DirectoryCheck and FilesystemHealthResponse models
Cherry-picked and expanded from #178 (@Vaibhavee89)
Cherry-picked and adapted from PR #89 and #214:
- Linux audio capture via PulseAudio/PipeWire monitor sources (cpal)
- AMD ROCm GPU support: HSA_OVERRIDE_GFX_VERSION env var, ROCm detection
- Whisper Turbo model (openai/whisper-large-v3-turbo) in all endpoints
- Cleaner Whisper language handling via generate_kwargs
- tauri::async_runtime::spawn fix to prevent panic on app shutdown
- Enable Linux (ubuntu-22.04) in release CI matrix
- New ChatterboxTurboTTSBackend wrapping ChatterboxTurboTTS (ResembleAI/chatterbox-turbo)
- English-only 350M model with paralinguistic tag support ([laugh], [cough], [chuckle])
- Bypasses upstream token=True bug by calling snapshot_download(token=None) + from_local()
- Same CPU-on-macOS forcing and torch.load monkey-patching as multilingual backend
- Full engine integration: generate, stream, model status/download/delete endpoints
- Language dropdown now shows only languages supported by the selected engine
- Per-engine language maps: Qwen (10), LuxTTS (en), Chatterbox (23), Turbo (en)
- Auto-switches to English when selecting English-only engines
- Backend language regex expanded to accept all 23 Chatterbox languages
- Add HFProgressTracker to LuxTTS and Chatterbox backends so tqdm-based
file-level download progress reaches the frontend (previously only Qwen
had this, LuxTTS/Chatterbox showed a static spinner)
- Add progress/current/total/filename fields to ActiveDownloadTask so the
/tasks/active polling endpoint carries progress data
- Show inline progress bar + bytes in the model list and detail modal,
poll at 1s during active downloads (5s otherwise)
- Fix GpuAcceleration crash: cudaStatusLoading was referenced before
initialization in its own useQuery declaration
- New ChatterboxTTSBackend wrapping ChatterboxMultilingualTTS (ResembleAI/chatterbox)
- Supports 23 languages including Hebrew, forces CPU on macOS (MPS issue)
- Monkey-patches torch.load for CPU loading, forces eager attention for compatibility
- trim_tts_output utility cuts trailing silence/hallucination from Chatterbox output
- Full engine integration: /generate, /generate/stream, model status/download/delete
- Hebrew (he) added to supported languages in frontend and backend validation
- Single flat model dropdown extended with Chatterbox option in both generation UIs
- ModelManagement UI groups LuxTTS and Chatterbox under 'Other Voice Models' section
- Add threading lock to get_tts_backend_for_engine() to prevent race
condition where concurrent requests could create duplicate backend
instances (double-checked locking pattern)
- Fix LuxTTS generate: call .detach().cpu() before .numpy() so it
works on GPU/MPS devices, not just CPU
- Store background download tasks in a module-level set to prevent
garbage collection before completion (asyncio.create_task fire-and-
forget pattern)
- Deduplicate cache_key computation in LuxTTS create_voice_prompt
- Prefix unused sr variable with underscore
Introduce LuxTTS (ZipVoice) alongside Qwen TTS, enabling users to choose
between engines at generation time. LuxTTS offers fast, English-focused
voice cloning at 48kHz with ~1GB VRAM.
Backend:
- Add LuxTTSBackend with encode_prompt/generate_speech integration
- Multi-engine registry (get_tts_backend_for_engine) replacing singleton
- Engine-prefixed voice prompt cache keys to avoid collisions
- Engine field on GenerationRequest (default 'qwen' for backward compat)
- Engine dispatch in /generate and /generate/stream endpoints
- LuxTTS in model status, download, and delete maps
Frontend:
- TTS Engine selector dropdown in GenerationForm (Qwen TTS / LuxTTS)
- Conditionally hide Model Size and Delivery Instructions for LuxTTS
- Engine field added to TypeScript types and Zod schema
- LuxTTS section in Model Management page
Add the ability to download a CUDA-enabled backend binary (~2.4 GB) and
swap it in via a backend-only restart, solving the #1 user pain point
(19 open 'GPU not detected' issues caused by GitHub's 2 GB asset limit).
Backend:
- cuda_download.py: download from R2 (primary) or GitHub split-parts
(fallback), SHA-256 verification, atomic writes, progress via SSE
- 4 new endpoints: GET/POST/DELETE /backend/cuda-*, GET cuda-progress
- server.py: --version flag, auto-detect variant from binary name
- build_binary.py: --cuda flag for CUDA PyInstaller builds
- split_binary.py: split large binaries into <2GB GitHub Release assets
- CI workflow for building CUDA binary
Tauri:
- restart_server command (stop -> wait -> start)
- start_server prefers CUDA binary from {data_dir}/backends/ if present
- Version mismatch check: runs --version before launching CUDA binary
Frontend:
- GpuAcceleration component: download, progress, restart, switch, delete
- API client + types for CUDA status and management
- Platform lifecycle: restartServer() on Tauri/Web
- Aggressive 1s health polling during restart for fast reconnection
- Fix transcribe_audio to use whisper-large-v3 mapping (not openai/whisper-large)
- Propagate error field in progress-only fallback path for get_active_tasks
- Use removed return value in cancel endpoint to vary response message
- Add error rollback to handleCancel with toast on failure
- Make isCancelling per-model instead of global
- Fix inverted chevron icons in Problems panel
- Move all clears under lock in clear_all_tasks
- Simplify cancel_download to use dict.pop()
- Add cancel (X) button on downloading and errored model items
- Add collapsible Problems panel (VS Code-style) showing error details
- Add "Clear All" button to reset all stale download/error state
- Add POST /models/download/cancel endpoint to dismiss individual downloads
- Add POST /tasks/clear endpoint to reset all task and progress state
- Include error messages in /tasks/active response for visibility
- Capture SSE error messages client-side for immediate display
- Fix whisper-large using wrong HF repo (openai/whisper-large → openai/whisper-large-v3)
- Fix Whisper HF repo mapping in both PyTorch and MLX backends
- Shorten error toast to point users to Problems panel instead of wall of text
- Add validation in create_profile() to check for existing names before insert
- Add validation in update_profile() to prevent renaming to duplicate names
- Improve error handling in API endpoints with user-friendly messages
- Add comprehensive test suite for duplicate name validation
- Update CHANGELOG.md with fix details
This fix prevents database constraint violations and provides clear
error messages when users attempt to create or update profiles with
names that already exist in the database.
The /generate endpoint created the voice prompt before loading the
user's requested model size. Since create_voice_prompt() internally
calls load_model_async(None), it fell back to the hardcoded default
of "1.7B", causing the 1.7B model to be downloaded even when the
user explicitly selected 0.6B.
This reorders the operations so the requested model is loaded first,
ensuring create_voice_prompt() and generate() use the correct model.
Co-Authored-By: Claude Opus 4.6 <[email protected]>
The wildcard `allow_origins=["*"]` allows any website the user visits to
make requests to the local voicebox backend, potentially triggering TTS
generation or reading voice profiles without consent.
Restrict to the known Tauri webview and Vite dev server origins by
default. Users running in remote server mode can set
VOICEBOX_CORS_ORIGINS to allow additional origins.
The export endpoints (export-audio, export generation, export profile,
export story) crash with `'latin-1' codec can't encode characters` when
the generated text or profile/story name contains non-ASCII characters
(e.g. Cyrillic, Chinese, Arabic).
Root cause: Python's `str.isalnum()` passes Unicode letters through to
the filename, but HTTP headers are encoded as latin-1 by the ASGI server,
which cannot represent characters outside the 0-255 range.
Fix: introduce `_safe_content_disposition()` helper that builds a
standards-compliant header with an ASCII-only `filename` fallback and a
RFC 5987 `filename*=UTF-8''...` parameter for Unicode-capable clients.
Fixes#68
Co-authored-by: Cursor <[email protected]>
- 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 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.
- 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.
- 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.
- 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.
- Added support for MLX backend on Apple Silicon, enabling optimized performance for TTS and STT tasks.
- Updated release workflow to include MLX-specific dependencies and configurations for macOS platforms.
- Refactored backend code to dynamically select between MLX and PyTorch based on the runtime environment.
- Enhanced model loading and inference logic to accommodate backend-specific requirements, including updated model IDs and hidden imports.
- Improved health check and model status reporting to reflect the active backend type.
- Streamlined caching mechanisms to support both backend types, ensuring compatibility and performance.
- Added functionality to upload, delete, and retrieve avatar images for voice profiles.
- Introduced new API endpoints for avatar management, including upload and delete operations.
- Enhanced profile forms and components to support avatar image handling, including previews and error handling.
- Updated database schema to include avatar_path for profiles and added necessary migrations.
- Implemented image validation and processing utilities to ensure proper avatar uploads.
- 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.
- Added thread-safe mechanisms to the ProgressManager for handling model download progress updates.
- Introduced a main event loop setter to ensure safe operations from background threads.
- Improved listener notification to handle updates in a thread-safe manner.
- Updated methods to ensure thread safety when accessing progress data.
- 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.
- Updated the health check endpoint to include the type of GPU available (CUDA or MPS).
- Modified the HealthResponse model to accommodate the new gpu_type field, enhancing the response with detailed GPU information.
- This change improves the clarity of system capabilities for users and developers.
- Added a new `/shutdown` endpoint to allow graceful server shutdown via HTTP.
- Implemented process tree management functions to handle child processes during shutdown on Windows.
- Updated the `stop_server` function to attempt graceful shutdown before forcefully terminating processes.
- Enhanced error handling and logging for shutdown operations.
- Implemented background tasks for downloading TTS and Whisper models to prevent blocking HTTP responses.
- Enhanced error handling during model downloads, providing users with real-time feedback on download status.
- Updated HTTP responses to indicate when models are being downloaded, improving user experience during model initialization.
- Moved model download logic into a separate asynchronous function to allow non-blocking HTTP responses.
- Improved error handling by tracking download status and reporting errors without interrupting the main request flow.
- The frontend is now expected to poll the progress endpoint for download status updates.
- Added __version__ variable in backend/__init__.py to centralize versioning.
- Updated main.py to use __version__ for API versioning in the FastAPI app.
- Enhanced cache directory handling by utilizing HuggingFace's constants for improved compatibility across platforms.
- Updated StoryTrackEditor and StoryContent components to support trimming and splitting of story items.
- Introduced new API endpoints for trimming, splitting, and duplicating story items, enhancing item management capabilities.
- Refactored related hooks and state management to accommodate new functionalities.
- Improved data models to include trim start and end times for better audio playback control.
- Enhanced UI interactions for selecting and managing story items within the track editor.
Jamie Pine