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Author SHA1 Message Date
James Pine 625e1ba549 Bump version: 0.3.1 → 0.4.0 2026-04-16 03:16:06 -07:00
James PineandClaude Opus 4.6 cfe6770639 style: apply biome format to drifted authored source
Catches format drift that accumulated across 13 authored files in
app/src and docs/. Auto-generated artifacts (tauri/src-tauri/gen,
docs/openapi.json, docs/cli.json, app/src/lib/api) were left alone
since the build regenerates them on each run — baking their formatted
state into git just causes churn next build.

No behavioral changes. Trailing commas, line wrapping, and indentation
only.

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
2026-04-16 03:13:45 -07:00
James PineandClaude Opus 4.6 00452b51a8 style(changelog): make entry version headings bigger in settings UI
The in-app changelog viewer rendered each entry's version number at the
same size as body text (text-sm font-medium), so visually there was no
clear anchor for where one release's notes ended and the next began.

Bump the version heading to text-xl font-semibold tracking-tight and
widen the bottom margin so each release reads as a proper section
header.

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
2026-04-16 03:12:09 -07:00
James PineandClaude Opus 4.6 106aec46a8 feat(generate): restore instruct toggle in floating generate box (Qwen CustomVoice)
Before 0.4 every engine was a cloning model, so the instruct UI in the
floating generate box applied the same way everywhere. Commit 3187344
hid the instruct toggle because the mix of new engines landing in 0.4
made it unclear which ones honored the kwarg. With Qwen CustomVoice
now shipping as the only engine actually tuned for instruct-style
control, bring the button back — conditionally, and only for that
engine.

Changes:
  • FloatingGenerateBox: SlidersHorizontal toggle button appears left
    of Generate when the box is expanded AND engine is
    qwen_custom_voice. Clicking it reveals an additive instruct
    textarea below the main text field (not a modal swap like the old
    version). State persists across engine switches so the toggle
    remembers its last position.
  • GenerationForm: narrow the instruct FormField's conditional from
    `qwen || qwen_custom_voice` to just `qwen_custom_voice`.
  • useGenerationForm: narrow supportsInstruct for the same reason.
    Base Qwen3-TTS accepts the kwarg but the model itself doesn't honor
    it — only CustomVoice was trained for instruction-based style
    control.

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
2026-04-16 03:09:55 -07:00
James PineandClaude Opus 4.6 c9e5c5d9a7 fix: clean up scroll effect timers and fix disabled+selected card toggle
- Add cleanup for requestAnimationFrame and setTimeout in scroll effect
  to prevent stale DOM writes on unmount or rapid selection changes
- Fix disabled+selected card click: bounce the selection to re-trigger
  the engine auto-switch instead of deselecting

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
2026-04-16 02:56:45 -07:00
James PineandClaude Opus 4.6 48cd1f369a feat: gray out unsupported profiles instead of filtering, auto-switch engine on selection
- Show all voice profiles with unsupported ones grayed out (opacity) instead of hidden
- Clicking a grayed-out profile selects it and auto-switches the engine to a compatible one
- Sort supported profiles first, with info tip about compatibility at the bottom
- Scroll to selected profile after engine/sort changes with safe margin
- Fix engine desync on tab navigation by initializing form engine from store

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
2026-04-16 02:56:45 -07:00
James PineandClaude Opus 4.6 2bfe400457 feat(skills): add triage-prs skill for pre-release PR speedruns
Immortalizes the workflow used to clear the open-PR backlog before
0.4.0: classify every open PR into merge / candidate / supersede /
defer tiers, write a working triage doc, then run the merge loop —
rebasing where needed, merging in batches, applying post-merge
follow-ups, and closing superseded PRs with credit.

Captures the gotchas that matter most:
  • Never review a stale branch via `git diff main..HEAD` — it shows
    every intermediate main commit as a deletion and makes a 3-line
    PR look like a 700-line revert
  • Always rebase before squash-merging; GitHub's squash computes
    diff(PR-head, merge-base), so a stale branch will revert
    in-between work
  • Route-ordering, weak-framework linking, dependency floors, !Send
    audio types, and why PyTorch nightly isn't shippable

Paired with draft-release-notes and release-bump: triage → draft →
bump.

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
2026-04-16 02:22:57 -07:00
0aa19a9994 feat(history): add "Clear failed" button to wipe failed generations (#412)
When the model wasn't loaded, the app was closed mid-run, or a
generation otherwise errored out, the resulting "Failed" rows
accumulate in history and there was no way to remove them in bulk —
individual delete was the only option.

Adds a header row above the history list (only rendered when at
least one failed generation is present) with a "Clear failed" button
that opens a confirmation dialog, then calls a new
DELETE /history/failed endpoint which sweeps all status='failed'
rows (plus their version files / audio files on disk).

Closes jamiepine/voicebox#410

Co-authored-by: Claude Opus 4.6 <[email protected]>
2026-04-16 02:12:30 -07:00
73170d0e92 feat(health): warn when GPU arch isn't supported by PyTorch build
Applies the compatibility-checker portion of #367. Adds a
check_cuda_compatibility() helper that compares the current device's
compute capability against torch.cuda._get_arch_list() and returns a
human-readable warning if the PyTorch build doesn't support it.

Wired into three places:
  • HealthResponse gains a gpu_compatibility_warning field so clients
    can surface the issue in the UI
  • Startup logs the warning as WARN level
  • _get_gpu_status() appends "[UNSUPPORTED - see logs]" to the GPU
    label shown in settings

Skipped #367's other half — the switch from stable to nightly cu128
wheels across release.yml, build_binary.py, and justfile. That's
redundant with #401's TORCH_CUDA_ARCH_LIST=...12.0+PTX approach and
would introduce non-deterministic builds from shifting nightly
releases.

Co-Authored-By: nyzxor <[email protected]>
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
2026-04-16 02:11:23 -07:00
James PineandClaude Opus 4.6 0317626677 fix(qwen): unify HF cache dir to avoid split cache on Windows
Applies the cache_dir portion of #218. On Windows local setups, model
assets can split between .hf-cache/hub and .hf-cache/transformers when
Qwen3TTSModel.from_pretrained doesn't explicitly pin the cache root —
speech_tokenizer and preprocessor_config.json then fail to resolve
during load, causing 500s at generation time.

Routes both HF Hub and Transformers through hf_constants.HF_HUB_CACHE.

Skipped the torch_dtype= → dtype= rename from #218: transformers 4.36
(our minimum) doesn't accept the dtype alias, only 4.46+. Once we bump
the minimum we can make that change.

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
2026-04-16 02:08:59 -07:00
a5d5c780c2 fix: avoid ScreenCaptureKit launch crash on macOS 11 (#424)
Co-authored-by: txhno <[email protected]>
2026-04-16 01:58:29 -07:00
James PineandClaude Opus 4.6 7184a25e44 fix(watchdog): clear stale .keep-running sentinel on startup
Follow-up to #402. The sentinel is only removed inside the grace-period
"sentinel found" branch. When the HTTP /watchdog/disable request wins
the race (normal case on macOS/Linux, occasional on Windows), the
_watchdog_disabled=True check returns first and the sentinel is left on
disk indefinitely.

If a later session spawns a fresh server and the user exits without
"keep running", the new watchdog would find that stale sentinel during
its grace period and keep the server alive against user intent.

Wipe any pre-existing sentinel when the watchdog starts so only signals
written during this session's lifetime can influence grace-period
decisions.

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
2026-04-16 01:57:05 -07:00
479bc7fc5e fix: reliably keep server alive after GUI close on Windows (#402)
The HTTP /watchdog/disable request races with process exit on Windows,
causing the watchdog to kill the server before the request arrives.

Added a .keep-running sentinel file as a reliable fallback:
- Tauri writes the file to data_dir before sending the HTTP request
- The watchdog checks for it during the grace period after detecting
  parent death
- The file is removed after being read to avoid stale state

This approach works regardless of HTTP timing because file writes
complete synchronously before the Tauri process exits.

Fixes #372

Co-authored-by: Matt Van Horn <[email protected]>
2026-04-16 01:56:30 -07:00
Cocoon-BreakandGitHub 3e7727d1d2 fix: keep cpal Stream alive until playback completes (Closes #404) (#405)
The cpal Stream was created and play() called but then immediately
dropped when play_to_device() returned. When a cpal Stream is dropped,
audio output stops immediately. This caused silent playback.

Fix: add a spin-wait loop that holds the Stream in scope until all
samples have been consumed (or stop_flag is set).
2026-04-16 01:54:31 -07:00
JunghwanandGitHub be7c0cec12 fix: add asyncio.Lock to prevent concurrent CUDA downloads (#428)
* fix: add asyncio.Lock to prevent concurrent CUDA downloads

The startup auto-update task and the manual download endpoint can both
invoke download_cuda_binary() concurrently. Without mutual exclusion,
both coroutines write to the same temp file path, corrupting the
download. The progress-manager status check is a TOCTOU race because
the status is not set until after several synchronous checks complete.

Add a module-level asyncio.Lock acquired at the top of
download_cuda_binary() so only one download can proceed at a time.

* fix: fast-reject duplicate CUDA download when lock is held

Address CodeRabbit review feedback: check _download_lock.locked()
before awaiting the lock so concurrent callers return immediately
instead of queueing behind the first download. This prevents the
route handler from returning "started" to multiple callers when only
one download actually proceeds.
2026-04-16 01:51:21 -07:00
c9d8142a78 feat: add Blackwell GPU (sm_120) CUDA support (#401)
Set TORCH_CUDA_ARCH_LIST in the CUDA build step to include 12.0+PTX
for forward compatibility with Blackwell GPUs (RTX 5070 Ti, 5080, etc).

Pre-built PyTorch cu128 wheels only ship native kernels for sm_80/86/89/90.
Without this, Blackwell GPU users get "no kernel image is available for
execution on the device" at runtime.

Fixes #386
Related: #395, #396, #399, #400

Co-authored-by: Matt Van Horn <[email protected]>
2026-04-16 01:51:18 -07:00
13ba5f1aa6 fix: prevent intermittent clip splitting failures (#403)
Two changes to address the race condition causing "Failed to split clip":

Backend (stories.py): Added with_for_update() to the item query in
split_story_item so concurrent requests for the same clip are
serialized via a row lock instead of racing.

Frontend (StoryTrackEditor.tsx): Guard handleSplit with
splitItem.isPending to prevent rapid double-clicks from firing
multiple mutations before the first completes.

Fixes #366

Co-authored-by: Matt Van Horn <[email protected]>
2026-04-16 01:51:15 -07:00
9a3c307c75 fix(history): populate status/error/engine fields from DB row (#394)
* fix(history): populate status/error/engine/model_size/is_favorited from DB

GET /history/{generation_id} was constructing HistoryResponse without
passing status, error, engine, model_size, or is_favorited from the
DB row. Since HistoryResponse.status defaults to "completed" in the
Pydantic model (models.py:141), this endpoint returned
status="completed" for every generation regardless of the actual DB
state — including jobs still in "loading_model" or "generating", and
even "failed" jobs.

This breaks any client polling /history/{id} for job completion:
the API lies about the status, so the only trustworthy success
signal becomes `audio_path` being non-empty. All other fields left
at their model defaults were similarly masked.

Fix: pass all fields through from the DB row, matching the pattern
used elsewhere in the codebase. The DB model (Generation in
database/models.py) already has all these columns.

* fix(history): apply NULL fallbacks to match list endpoint

Align the defensive mappings with services/history.py:206-223 so
both the single-item and list history endpoints handle legacy rows
with NULL status/engine/is_favorited identically. Without this,
HistoryResponse's non-Optional str/bool fields would raise a
pydantic ValidationError (500) on any row where these columns are
NULL — possible from direct SQL updates or past migrations.

Addresses review feedback on PR #394.

---------

Co-authored-by: malletfils <[email protected]>
2026-04-16 01:51:12 -07:00
JunghwanandGitHub 1da16cfc57 fix: harden voice prompt cache loading and SPA path guard (#429)
Two small safety improvements:

1. Voice prompt cache (cache.py): add weights_only=True to torch.load()
   so cached .prompt files are loaded using the safe unpickler instead of
   the unrestricted pickle deserializer. This follows the PyTorch 2.6+
   best practice of opting in to safe loading for all torch.load() calls.

2. SPA catch-all (app.py): replace str.startswith() path guard with
   Path.is_relative_to(). The string prefix check passes for sibling
   paths like /app/frontend_evil/ that share the /app/frontend prefix.
   is_relative_to() correctly tests directory containment.
2026-04-16 01:49:19 -07:00
Luis SambranoandGitHub a1807be04d fix(deps): relax torch requirement for macOS x86_64 compatibility (#416) 2026-04-16 01:49:16 -07:00
Khaled SolimanandGitHub fdba18e9ee fix: resolve ModuleNotFoundError by using relative import for utils (#384) 2026-04-16 01:49:13 -07:00
MaxandGitHub 07a845cece Add NUMBA_CACHE_DIR environment variable (#425) 2026-04-16 01:49:10 -07:00
James PineandClaude Opus 4.6 615d604ceb fix(numpy-compat): raise on unknown dtype + add fp16/complex
Follow-up to #361. The original fallback silently mapped unknown numpy
dtypes to torch.float32, which would reinterpret the memcpy'd bytes in
the wrong dtype and corrupt data (e.g. fp16 tensors from some TTS
engines) rather than erroring loudly.

- Hoist dtype_map out of the inner function so it's built once
- Add float16, complex64, complex128 mappings
- Raise TypeError on unknown dtype instead of silent float32 fallback

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
2026-04-16 01:47:22 -07:00
a383ff6863 fix: torch.from_numpy crash with numpy 2.x in frozen binary (#361)
torch is compiled against numpy 1.x. numpy 2.x changed the ABI version
returned by PyArray_GetNDArrayCVersion() (0x01000009 → 0x02000000), so
torch's is_numpy_available() always returns False and torch.from_numpy()
raises RuntimeError. This causes TTS generation to fail with:

  ValueError: Unable to create tensor, you should probably activate
  padding with 'padding=True'

Two fixes:

1. Pin numpy<2.0 in requirements.txt so new builds bundle a compatible
   numpy version. (The existing comment already flagged this intention
   but the upper bound was never added.)

2. Add a PyInstaller runtime hook (pyi_rth_numpy_compat.py) that installs
   a ctypes memmove fallback for torch.from_numpy() at startup. Runtime
   hooks run after FrozenImporter is registered so frozen torch is
   importable. The fallback catches RuntimeError from the C-level ABI
   check and copies the numpy array into a new tensor via raw memory copy,
   bypassing the check entirely. This is a belt-and-suspenders fix that
   works regardless of the bundled numpy version.

Co-authored-by: aimaaaimaa <[email protected]>
Co-authored-by: Claude Sonnet 4.6 <[email protected]>
2026-04-16 01:46:40 -07:00
Jamie PineandGitHub 75abbb02c3 Merge pull request #344 from pandego/fix/308-docker-compose-startup
fix: include changelog in docker web build
2026-03-26 23:06:47 -07:00
Jamie PineandGitHub b49f14a814 Merge pull request #319 from jamiepine/fix/startup-and-server-switch
fix: GUI startup with external server + data refresh on server switch
2026-03-26 23:06:29 -07:00
Jamie PineandGitHub 05686efbfd Merge pull request #345 from ArfianID/fix/backend-import-error
Fix: "Failed to Save" preset error by resolving backend import path resolution
2026-03-22 09:45:25 -07:00
Arfian e2c03fef9a Fix: move lazy imports to top-level and use absolute paths to resolve ModuleNotFoundError in production 2026-03-22 22:29:25 +07:00
pandego 4347eaed4c fix: include changelog in docker web build 2026-03-22 09:32:32 +01:00
James Pine 60aac279ce fix: address PR #319 review feedback — health validation, error handling, queryClient decoupling
- Rust: Replace fragile body.contains("status") with proper JSON
  deserialization validating status=="healthy", model_loaded (bool),
  and gpu_available (bool) to prevent misidentifying non-Voicebox services

- Frontend: Validate health response has Voicebox-specific fields before
  marking server as ready during fallback polling

- Frontend: Discriminate port-in-use errors (poll for external server) from
  real startup failures (missing sidecar, signing issues) — surface errors
  immediately with a startupError state and Retry button in the UI

- Frontend: Set explicit startup-error state when 2-minute polling timeout
  expires so the loading screen shows actionable feedback instead of hanging

- Architecture: Extract QueryClient to standalone side-effect-free module
  (lib/queryClient.ts) to decouple serverStore from React bootstrap entrypoint
2026-03-21 10:24:15 -07:00
James Pine 8b1c7552be Merge remote-tracking branch 'origin/fix/startup-and-server-switch' into pr-319 2026-03-21 10:18:45 -07:00
Jamie PineandGitHub 9a955a77d2 Merge pull request #320 from jamiepine/feat/intel-xpu-support
feat: Intel Arc (XPU) GPU support
2026-03-21 08:39:51 -07:00
Jamie PineandGitHub c18591c0c3 Merge pull request #318 from jamiepine/fix/offline-model-loading
fix: force offline mode when loading cached models (Qwen TTS & Whisper)
2026-03-21 08:38:08 -07:00
Jamie PineandGitHub ea3469f2dc Merge pull request #332 from nicoschtein/patch-1
Fix links in Get Started section of index.mdx
2026-03-21 08:37:00 -07:00
James Pine b108bb1cb1 fix: store media paths relative to data dir 2026-03-20 15:06:07 -07:00
Nicolas SchteinschraberandGitHub 8b796bc6b4 Fix links in Get Started section of index.mdx
Updated links in the Get Started section for correct paths.
2026-03-20 13:58:53 -03:00
James Pine e6f419cd70 fix: show all engines in floating generator 2026-03-19 19:52:08 -07:00
James Pine 72c13fd3fc fix: enforce preset profile engine compatibility 2026-03-19 19:51:53 -07:00
James Pine 4e0c731db8 feat: add Qwen CustomVoice preset engine 2026-03-19 19:48:50 -07:00
James Pine d70b878b71 fix: tighten kokoro profile handling 2026-03-19 19:32:49 -07:00
Jamie PineandGitHub a71011741d Merge pull request #325 from jamiepine/feat/kokoro-engine
feat: Kokoro 82M TTS engine + voice profile type system
2026-03-19 19:21:15 -07:00
James Pine d6f48ace3e Mirror the regular /generate endpoint behavior more closely 2026-03-19 16:11:38 -07:00
James Pine 0fc2192204 fix: resolve relative paths using configured data dir, not CWD 2026-03-19 10:37:11 -07:00
James Pine 9e726ad048 fix: remove engine dropdown filtering — profile grid handles it 2026-03-19 10:14:33 -07:00
James Pine 3584283d84 feat: Kokoro 82M TTS engine + voice profile type system
Add Kokoro-82M as a new TTS engine — 82M params, CPU realtime, 8 languages,
Apache 2.0. Unlike cloning engines, Kokoro uses pre-built voice styles, which
required a new profile type system to support non-cloning engines cleanly.

Kokoro engine:
- New kokoro_backend.py implementing TTSBackend protocol
- 50 built-in voices across en/es/fr/hi/it/pt/ja/zh
- KPipeline API with language-aware G2P routing via misaki
- PyInstaller bundling for misaki, language_tags, espeakng_loader, en_core_web_sm

Voice profile type system:
- New voice_type column: 'cloned' | 'preset' | 'designed' (future)
- Preset profiles store engine + voice ID instead of audio samples
- default_engine field on profiles — auto-selects engine on profile pick
- Create Voice dialog: toggle between 'Clone from audio' and 'Built-in voice'
- Edit dialog shows preset voice info instead of sample list for preset profiles
- Engine selector locks to preset engine when preset profile is selected
- Profile grid filters by engine — shows Kokoro voices when Kokoro selected
- Custom empty state when no preset profiles exist for selected engine

Bug fixes:
- Fix relative audio paths in DB causing 404s in production builds
- config.set_data_dir() now resolves to absolute paths
- Startup migration converts existing relative paths to absolute

Also updates PROJECT_STATUS.md and tts-engines.mdx developer guide.
2026-03-19 10:09:48 -07:00
Jamie PineandGitHub e4def9365f Merge pull request #321 from liorshahverdi/fix/delete-failed-generations-292
fix/allows deletion of failed generations 292
2026-03-19 09:36:55 -07:00
James Pine 707046237c fix: complete Intel XPU support — device-aware seeding, GPU status reporting, and setup detection
Address CodeRabbit review feedback and user-reported GPU acceleration failure:

- Use shared manual_seed() in chatterbox, chatterbox_turbo, and luxtts
  backends so XPU (and future accelerators) get proper device seeding
- Add XPU branch to _get_gpu_status() so startup log reports Intel Arc
  GPUs instead of 'None (CPU only)'
- Add XPU VRAM reporting and correct backend_variant fallback in the
  /health endpoint
- Switch justfile GPU detection from Get-WmiObject to Get-CimInstance,
  simplify the Arc regex to match 'Arc' (not 'Intel.*Arc'), log
  detected GPUs, and print manual install instructions on miss

Resolves the root cause where IPEX was silently not installed due to
WMI detection failure, causing CPU-only fallback on Intel Arc systems.
2026-03-18 17:01:12 -07:00
Lior Shahverdi 12ed2d51ce Adds a trash icon button alongside the existing retry button for
failed generations, giving users a way to clean up failed entries
  without having to retry them first.
2026-03-18 15:44:37 -04:00
James Pine 83ebababe7 feat: add Intel Arc (XPU) GPU support across all backends
Auto-detect Intel Arc GPUs during Windows setup and install PyTorch
with XPU support + intel-extension-for-pytorch. Enable allow_xpu=True
on all TTS backends (Chatterbox, Chatterbox Turbo, Hume TADA, LuxTTS)
that previously only supported CUDA. Add shared empty_device_cache()
and manual_seed() helpers in base.py to handle XPU memory management
and reproducible seeding alongside CUDA.
2026-03-18 11:24:51 -07:00
James Pine eb5869e59f fix: GUI startup with external server + data refresh on server switch
Two fixes for issue #312:

1. GUI stuck on loading screen when backend is already running externally
   (e.g. via python/uvicorn/Docker):

   - Rust: add HTTP health check fallback when the process on the port
     doesn't have 'voicebox' in its name. If /health responds with a
     valid Voicebox response, reuse the server instead of erroring.
   - Frontend: when startServer() fails, fall back to polling the
     health endpoint every 2s instead of permanently blocking.

2. No data refresh when switching server URLs in settings:

   - serverStore.setServerUrl() now invalidates all React Query caches
     when the URL actually changes, so profiles/history/models/stories
     are re-fetched from the new server.
   - Export queryClient from main.tsx for store-level cache invalidation.

Fixes #312
2026-03-18 10:59:59 -07:00
James Pine 2e95b7c5d8 fix: force offline mode when loading cached models (Qwen TTS & Whisper)
Qwen TTS and Whisper Base make network calls to HuggingFace even when
model weights are fully cached locally, because from_pretrained()
defaults to local_files_only=False. This causes failures for offline
users.

Add a reusable force_offline_if_cached() context manager that sets
HF_HUB_OFFLINE=1 during model loading when is_model_cached() is True.
Applied to all four affected load paths:

- PyTorchTTSBackend (Qwen TTS)
- PyTorchSTTBackend (Whisper)
- MLXTTSBackend (refactored from inline implementation)
- MLXSTTBackend (previously unprotected)

Closes #82
2026-03-18 10:31:30 -07:00
Jamie PineandGitHub ffc1b54812 Merge pull request #316 from jamiepine/fix/cuda-cu128-upgrade
Upgrade CUDA backend from cu126 to cu128, fix GPU settings UI
2026-03-18 07:58:12 -07:00
James Pine fc5ed1ff40 upgrade CUDA backend from cu126 to cu128 and fix GPU settings UI
Upgrade CUDA toolkit from 12.6 (cu126) to 12.8 (cu128) for proper
RTX 50-series (Blackwell) GPU support. Users with RTX 5070/5080/5090
were reporting CUDA detection failures with cu126.

Also fix the GPU Acceleration settings panel where the 'Switch to CPU
Backend' button was unreachable — it was inside a conditional block
that required !isCurrentlyCuda, making it impossible to switch back
to CPU once running on CUDA.

Closes #315
2026-03-18 07:47:39 -07:00
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---
name: triage-prs
description: Use this skill to triage the open PR queue before a release. Classifies every open PR into must-merge, candidate, superseded, or deferred; writes a working triage doc; and runs the merge loop end-to-end. Designed for the pre-release "PR speedrun" pass where a solo maintainer wants to clear the inbound backlog in a single session.
---
# Triage PRs
## Goal
Turn a backlog of open PRs into a shipped set of merges in a single focused session. Produce a tracked, resumable plan (`<VERSION>_PR_TRIAGE.md`), then work it — rebasing where needed, merging in isolation-safe batches, applying post-merge follow-ups, and closing superseded or partially-applicable PRs with credit to their authors.
This skill pairs with `draft-release-notes` and `release-bump`: triage first, then draft notes against the new main, then cut the release.
## When to use
- Before a minor or major release when 10+ open PRs have accumulated
- When you want to unblock merging without losing the narrative of what's landing
- When you know you can't personally review every PR deeply, but need to land the critical subset fast
## Prerequisites
- `gh` CLI authenticated against the repo
- A dedicated worktree for PR review (avoid contaminating `main` with checkouts of contributor branches)
- Clarity on the target version — the triage doc is named after it (e.g. `0.4.0_PR_TRIAGE.md`)
## Workflow
### 1. Set up an isolated PR-review worktree
```bash
git worktree list # check for stale ones first
git worktree prune
git worktree add ../voicebox-pr-review -b pr-review-<VERSION> main
```
Keep the main worktree for release-prep work (changelog drafts, direct-to-main follow-ups). Keep the review worktree for `gh pr checkout` — each checkout moves HEAD to a contributor branch, which you don't want to do in the main worktree.
### 2. Gather metadata for every open PR
```bash
gh pr list --state open --limit 50 --json \
number,title,author,isDraft,mergeable,mergeStateStatus,files,additions,deletions,reviewDecision,statusCheckRollup,maintainerCanModify \
--jq '.[] | {num: .number, title, author: .author.login, mergeable, state: .mergeStateStatus, canModify: .maintainerCanModify, changes: "+\(.additions)/-\(.deletions)", files: [.files[].path]}'
```
You want, for each PR:
- Size (`+additions/-deletions`)
- Mergeable state (`CLEAN`, `UNSTABLE`, `DIRTY` = conflicts, `UNKNOWN` = GitHub still computing)
- Whether maintainer edits are allowed on the branch (needed later if you rebase for the author)
- File paths touched (helps spot overlaps between PRs)
`UNKNOWN` is common right after a push to main — just try the merge and see.
### 3. Classify into tiers
Sort each PR into exactly one bucket:
**Tier 1 — Merge:** small, mergeable, fixes a real bug, clean CI, low review cost. One-liners, dependency relaxations, targeted safety hardening. These are the easy wins.
**Tier 2 — Candidate, review:** medium size (50-200 lines), touches more surface area, looks sound but needs a closer read. New user-facing features that fit the product direction.
**Supersede:** the fix or feature is already covered by something merged. Close with a comment pointing to the superseding PR. Check carefully — "similar title" isn't proof; compare the actual diffs.
**Defer to next release:** big features, dirty conflicts, draft PRs, anything touching the release pipeline in ways that would introduce risk. Don't merge these in a speedrun — they need dedicated focus.
### 4. Write the triage doc
Create `<VERSION>_PR_TRIAGE.md` in the PR-review worktree root. Structure:
```markdown
# <Repo> <VERSION> — PR Triage
Working doc for tracking which open PRs land in <VERSION>. Delete after release cut.
Last updated: <DATE>
## Progress
**Tier 1: 0 / N merged**
**Tier 2: 0 / M handled**
**Supersede triage: pending**
---
## Merge for <VERSION> — critical bug fixes
| PR | Status | Size | What it fixes | Why must-have |
|---|---|---|---|---|
| [#123](url) | [ ] | +5/-0 | ... | ... |
## Strong candidate — needs a quick review
| PR | Status | Size | Summary |
|---|---|---|---|
## Close as superseded
| PR | Status | Reason |
|---|---|---|
## Defer to <NEXT_VERSION>
- [#xxx](url) ... — reason
---
## Order of attack
1. Close superseded PRs (one-liner comments)
2. Merge tier-1 in dependency-free batches — check file paths don't overlap
3. Review tier-2 individually
4. Rerun `draft-release-notes` to pick up everything
5. Run `release-bump`
```
The **Progress** header is the most important part — it's your scoreboard and lets you resume cleanly if the session gets interrupted.
### 5. Work the loop — per PR
For each PR in the tier-1 / tier-2 list:
**a. Checkout in the review worktree:**
```bash
cd ../voicebox-pr-review
git checkout pr-review-<VERSION> # reset to neutral base
gh pr checkout <N>
```
**b. Read the *actual* commit, not `main..HEAD`:**
```bash
git show HEAD # the PR's actual changes
git show --stat HEAD # files touched + line counts
```
**Do NOT review via `git diff main..HEAD`** if the PR branch is older than main. That diff includes *every commit that landed on main after the PR was forked* as `-` (deletion) lines. A 3-line PR can look like a 700-line revert. This is the single easiest way to misjudge a PR.
**c. Evaluate concerns:** correctness, scope, interaction with already-merged work, version compatibility (e.g. can't use an API that requires a dependency version we don't yet pin).
**d. Rebase if the branch is behind main:**
```bash
git fetch origin main
git rebase origin/main
```
This is **essential** before squash-merging. GitHub's squash computes `diff(PR-head, merge-base)` — on a stale branch, that diff includes reverting every in-between commit. Rebasing moves the merge-base forward so the squash is clean.
**e. If maintainer edits are allowed, push the rebase back to the contributor's fork:**
```bash
git remote add <author> https://github.com/<author>/<repo>.git
git fetch <author> <branch> # get their ref first
git push <author> HEAD:<branch> --force-with-lease
```
This keeps GitHub's PR UI in sync with the rebased state and makes the merge clean from the GitHub side.
**f. Merge:**
```bash
gh pr merge <N> --squash
```
**g. Update the triage doc** — flip the checkbox to `✅ merged <sha>` (use the short SHA from `gh pr view <N> --json mergeCommit --jq '.mergeCommit.oid[0:7]'`). Update the Progress header.
### 6. Batch tiny fixes
PRs with ≤5 line changes, clean CI, non-overlapping file paths, and obviously-correct intent (e.g. one-line dependency relax, env var add, import path fix) can be merged in a single loop without the review-per-PR ceremony:
```bash
for pr in 425 384 416 429; do
echo "=== Merging PR $pr ==="
gh pr merge $pr --squash
done
```
Verify afterward that each landed cleanly:
```bash
for pr in 425 384 416 429; do
gh pr view $pr --json state,mergeCommit --jq "{pr: $pr, state, sha: .mergeCommit.oid[0:7]}"
done
```
### 7. Post-merge follow-ups
Sometimes a PR is worth merging despite a known minor issue (e.g. incomplete dtype map, stale sentinel cleanup). Don't block the merge; apply the follow-up as a normal branch + PR right after:
```bash
cd <main-worktree>
git pull --ff-only origin main
git checkout -b fix/<short-name>
# edit...
git commit -m "fix(<area>): <one-liner>"
git push -u origin fix/<short-name>
gh pr create --title "..." --body "Follow-up to #<N>. ..."
```
Record both SHAs in the triage doc (`✅ merged <pr-sha> + follow-up <pr>`).
**Direct-to-main exception:** only under an explicit, scoped policy (e.g. "release speedrun"). Don't default to it.
### 8. Supersede: close with a credit-pointing comment
```bash
gh pr close <N> --comment "Closing — superseded by merged #<M> which landed <brief description>. Thanks!"
```
Check the diffs first — "similar title" is not enough. If the PR is *partially* superseded (the diagnosis is right but only half the changes are still needed), do a partial-apply instead.
### 9. Partial-apply pattern
When a PR has both valuable and questionable changes bundled:
```bash
cd <main-worktree>
git pull --ff-only origin main
# Cherry-pick specific files from the PR branch
git checkout <pr-commit-sha> -- <file1> <file2>
# Review the staged changes, adjust as needed
git diff --cached
# Apply any surgical edits to files you don't want to bulk-replace
# (e.g. the PR's file predates a recent main commit you need to preserve)
# Commit with a trailer crediting the original author
git commit -m "$(cat <<'EOF'
<subject>
<body explaining what was kept vs dropped>
Co-Authored-By: <author> <[email protected]>
EOF
)"
git push ... # branch + PR, unless under the direct-to-main exception
```
Then close the PR with a comment explaining what was applied and what was dropped, referencing the commit SHA.
### 10. Keep the doc current
Every merge, every close, every follow-up → update `<VERSION>_PR_TRIAGE.md`. The doc is your session log. If you're interrupted and resume tomorrow, the doc is the only source of truth for "where am I."
### 11. When triage is done
- Every PR in the doc has a terminal status (✅ merged / ✅ closed / deferred)
- Progress header shows N/N for each tier
- Next skill to run is `draft-release-notes` (to regenerate `[Unreleased]` against the new main), then `release-bump`
You can delete the triage doc after the release ships, or keep it in version history as a record.
## Gotchas
- **`main..HEAD` on a stale branch lies.** It shows everything main gained since the branch split as deletions. Always review via `git show HEAD` for the PR's actual commit.
- **Squash-merging an unrebased branch reverts in-between work.** The squash computes `diff(PR-head, merge-base)`. Rebase moves the merge-base forward.
- **`mergeable=UNKNOWN`** is transient — GitHub is recomputing after a push. Just try the merge.
- **Route ordering matters (FastAPI and similar):** `DELETE /history/failed` must be registered *before* `DELETE /history/{id}`, or the parameterized path will consume `"failed"` as an ID.
- **Apple's `-weak_framework` overrides `-framework`** for the same framework, regardless of order — use it via `cargo:rustc-link-arg=-Wl,-weak_framework,Name` when a dependency hard-links something optional.
- **Dependency version floors constrain what you can apply.** Before accepting a kwarg rename like `torch_dtype=` → `dtype=`, check the min-version pin supports it. Sometimes the right move is to cherry-pick half the PR.
- **`cpal::Stream` and similar `!Send` audio types** can't cross `await` points or `spawn_blocking`. Sometimes a "not-ideal but correct" sync wait is the best available fix; flag but don't block.
- **PyTorch nightly builds are not shippable for releases** — non-deterministic, can regress between runs. If a PR suggests switching to nightly to fix a GPU issue, prefer `TORCH_CUDA_ARCH_LIST=...+PTX` or wait for stable support instead.
## Canonical commands reference
```bash
# Bulk PR metadata
gh pr list --state open --limit 50 --json number,title,author,mergeable,mergeStateStatus,additions,deletions,maintainerCanModify,files
# Detailed single-PR view
gh pr view <N> --json body,author,headRefName,baseRefName,mergeable,maintainerCanModify,files,statusCheckRollup
# The actual commit, not the branch-vs-main diff
git show HEAD
git show --stat HEAD
gh pr diff <N>
# Rebase contributor branch onto current main
git fetch origin main && git rebase origin/main
# Push rebase back to contributor fork (maintainerCanModify=true required)
git remote add <author> https://github.com/<author>/<repo>.git
git fetch <author> <branch>
git push <author> HEAD:<branch> --force-with-lease
# Merge
gh pr merge <N> --squash
# Confirm merge SHA for triage doc
gh pr view <N> --json state,mergeCommit --jq '{state, sha: .mergeCommit.oid[0:7]}'
# Close superseded
gh pr close <N> --comment "Closing — superseded by merged #<M>. Thanks!"
```
## Notes
- **Never review a stale branch via `main..HEAD`.** This is the single most important line in this skill.
- **The triage doc is the session state.** Lose the doc, lose the session. Update it after every action.
- **Credit contributors even on partial-applies.** Use `Co-Authored-By:` trailers and close comments that link to the applied commit.
- **Don't let perfect be the enemy of shipped.** A fix that goes from "broken" to "works with a minor known issue" is a strict improvement. Flag the issue, file a follow-up, merge the fix.
+1 -1
View File
@@ -1,5 +1,5 @@
[bumpversion]
current_version = 0.3.1
current_version = 0.4.0
commit = True
tag = True
tag_name = v{new_version}
-1
View File
@@ -38,7 +38,6 @@ biome.json
.bumpversion.cfg
.npmrc
Makefile
CHANGELOG.md
CONTRIBUTING.md
SECURITY.md
LICENSE
+13 -7
View File
@@ -191,10 +191,10 @@ jobs:
pip install --no-deps chatterbox-tts
pip install --no-deps hume-tada
- name: Install PyTorch with CUDA 12.6
- name: Install PyTorch with CUDA 12.8
run: |
pip install torch --index-url https://download.pytorch.org/whl/cu126 --force-reinstall --no-deps
pip install torchaudio --index-url https://download.pytorch.org/whl/cu126 --force-reinstall --no-deps
pip install torch --index-url https://download.pytorch.org/whl/cu128 --force-reinstall --no-deps
pip install torchaudio --index-url https://download.pytorch.org/whl/cu128 --force-reinstall --no-deps
- name: Verify CUDA support in torch
run: |
@@ -203,6 +203,12 @@ jobs:
- name: Build CUDA server binary (onedir)
shell: bash
working-directory: backend
env:
# Include Blackwell (sm_120) via PTX forward compatibility.
# Pre-built PyTorch cu128 wheels ship native kernels for sm_80/86/89/90
# but not sm_120. Setting this env var causes torch.utils.cpp_extension
# (and any JIT-compiled kernels) to target Blackwell GPUs as well.
TORCH_CUDA_ARCH_LIST: "8.0;8.6;8.9;9.0;12.0+PTX"
run: python build_binary.py --cuda
- name: Package into server core + CUDA libs archives
@@ -211,8 +217,8 @@ jobs:
python scripts/package_cuda.py \
backend/dist/voicebox-server-cuda/ \
--output release-assets/ \
--cuda-libs-version cu126-v1 \
--torch-compat ">=2.6.0,<2.11.0"
--cuda-libs-version cu128-v1 \
--torch-compat ">=2.7.0,<2.11.0"
- name: Upload archives to GitHub Release
if: startsWith(github.ref, 'refs/tags/')
@@ -221,8 +227,8 @@ jobs:
files: |
release-assets/voicebox-server-cuda.tar.gz
release-assets/voicebox-server-cuda.tar.gz.sha256
release-assets/cuda-libs-cu126-v1.tar.gz
release-assets/cuda-libs-cu126-v1.tar.gz.sha256
release-assets/cuda-libs-cu128-v1.tar.gz
release-assets/cuda-libs-cu128-v1.tar.gz.sha256
release-assets/cuda-libs.json
draft: true
env:
+114 -1
View File
@@ -7,6 +7,117 @@
## [Unreleased]
## [0.4.0] - 2026-04-16
The biggest Voicebox release yet. Three new TTS engines bring the lineup to **seven** — HumeAI TADA, Kokoro 82M, and Qwen CustomVoice join Qwen3-TTS, LuxTTS, Chatterbox Multilingual, and Chatterbox Turbo. GPU support broadens to Intel Arc (XPU) and NVIDIA Blackwell (RTX 50-series), with runtime diagnostics that warn when your PyTorch build doesn't match your GPU. The CUDA backend is now split into independently versioned server and library archives, so upgrading no longer redownloads 4 GB of PyTorch/CUDA DLLs.
This release also marks a big community moment: **13 new contributors** shipped fixes and features in 0.4.0. Thirty-plus bug fixes target the most-reported issues in the tracker — numpy 2.x TTS crashes, Windows background-server reliability, macOS 11 launch failures, audio playback silence, Stories clip-splitting races, history status staleness, and more.
### New TTS Engines
#### HumeAI TADA — Expressive English & Multilingual ([#296](https://github.com/jamiepine/voicebox/pull/296))
- Added `tada-1b` (English) and `tada-3b-ml` (multilingual) backends
- Replaced `descript-audio-codec` with a lightweight DAC shim to cut dependencies
- Switched audio decoding to `soundfile` to sidestep `torchcodec` bundling issues
- Redirected gated Llama tokenizer lookups to an ungated mirror so model loading works out of the box
- Fixed tokenizer patch that was corrupting `AutoTokenizer` for other engines
- Fixed TorchScript error in frozen builds
#### Kokoro 82M — Fast Lightweight TTS ([#325](https://github.com/jamiepine/voicebox/pull/325))
- Added Kokoro 82M engine with a new voice profile type system that distinguishes preset voices from cloned profiles
- Profile grid now handles engine compatibility directly — removed redundant dropdown filtering
- Tightened Kokoro profile handling so preset voices can't be edited like cloned profiles
#### Qwen CustomVoice ([#328](https://github.com/jamiepine/voicebox/pull/328))
- Added `qwen-custom-voice` preset engine backed by Qwen3-TTS
- Enforced preset/profile engine compatibility across the generation flow
- Floating generator now shows all engines instead of silently filtering
### Voice Profile UX
Until 0.4, every engine in Voicebox was a cloning model, so every voice profile was usable with every engine and the profile grid just showed them all. Introducing Kokoro and Qwen CustomVoice — which work from preset voices rather than cloned samples — broke that assumption for the first time. An early cut on `main` filtered the grid by the selected engine, which left users running pre-release builds thinking their cloned voices had vanished whenever they switched to a preset-only engine.
This release ships the resolution before it ever reaches a tagged version:
- **Grey-out instead of filter** — all profiles are always visible; unsupported ones render dimmed with a compatibility hint at the bottom of the grid
- **Auto-switch on selection** — clicking a greyed-out profile selects it AND switches the engine to a compatible one, instead of silently doing nothing
- **Instruct toggle restored for Qwen CustomVoice** — the floating generate box now reveals a delivery-instructions input (tone, emotion, pace) when CustomVoice is selected. Hidden across the board while the new multi-engine lineup was stabilizing because most engines don't honor the kwarg; now conditionally exposed only for the one engine that was actually trained for instruction-based style control
- Supported profiles sort first; the grid scrolls the selected profile into view after engine/sort changes
- Fixed engine desync on tab navigation — the form now initializes its engine from the store
- Fixed the disabled-and-selected card click edge case by bouncing selection to re-trigger the auto-switch
- Cleaned up scroll effect timers (requestAnimationFrame + setTimeout) to prevent stale DOM writes on unmount or rapid selection changes
### GPU & Platform
#### Intel Arc (XPU) Support ([#320](https://github.com/jamiepine/voicebox/pull/320))
- First-class Intel Arc support across all PyTorch-based backends
- Device-aware seeding, XPU detection in the GPU status panel, and setup flow detection
- Reports correct device name and VRAM in settings
#### Blackwell / RTX 50-series Support ([#316](https://github.com/jamiepine/voicebox/pull/316), [#401](https://github.com/jamiepine/voicebox/pull/401))
- Upgraded the CUDA backend from cu126 → cu128 for RTX 50-series support
- Added `sm_120+PTX` to the CUDA build via `TORCH_CUDA_ARCH_LIST` for forward-compatibility with Blackwell architectures (closes 5 open reports: #386, #395, #396, #399, #400)
- GPU settings UI fixes around install/uninstall state
#### GPU Compatibility Diagnostics ([#367](https://github.com/jamiepine/voicebox/pull/367), adapted)
- New `check_cuda_compatibility()` compares the current device's compute capability against the bundled PyTorch's architecture list
- Health endpoint exposes a `gpu_compatibility_warning` field so the UI can surface mismatches
- Startup logs a `WARN` when the installed PyTorch build doesn't support the detected GPU
- GPU status label shows `[UNSUPPORTED - see logs]` — no more silent "no kernel image" failures
#### Split CUDA Backend ([#298](https://github.com/jamiepine/voicebox/pull/298))
- CUDA backend now ships as two independently versioned archives: a small server binary and a large libs archive (the ~4 GB of PyTorch/CUDA DLLs)
- Upgrading Voicebox no longer redownloads the libs archive when only the server binary changed
- Added `asyncio.Lock` around `download_cuda_binary()` so auto-update and manual download can't race on the same temp file ([#428](https://github.com/jamiepine/voicebox/pull/428))
- Updated `package_cuda.py` for PyInstaller 6.18 onedir layout
- Temp archives are always cleaned up on failure, even when the install aborts mid-extract
### Bug Fixes
#### Critical: TTS Generation
- **numpy 2.x `torch.from_numpy` crash** ([#361](https://github.com/jamiepine/voicebox/pull/361)) — torch compiled against numpy 1.x ABI fails silently when paired with numpy 2.x, causing `RuntimeError: Numpy is not available` / `Unable to create tensor` on every TTS request in bundled macOS Intel / Rosetta builds. Pinned `numpy<2.0` in requirements and added a PyInstaller runtime hook with a `ctypes.memmove` fallback as belt-and-suspenders. Hardened afterward to raise on unknown dtypes instead of silently reinterpreting bytes as float32.
#### Platform Reliability
- **Windows background server** ([#402](https://github.com/jamiepine/voicebox/pull/402)) — "keep server running after close" now actually keeps the server running. The HTTP `/watchdog/disable` request could lose the race against process exit on Windows; added a `.keep-running` sentinel file as a synchronous fallback, with stale-sentinel cleanup on startup to avoid orphan server processes
- **macOS 11 launch crash** ([#424](https://github.com/jamiepine/voicebox/pull/424)) — weak-linked ScreenCaptureKit so the app can launch on macOS < 12.3 instead of crashing at dyld resolution. Gated system audio capture behind a real `sw_vers` version check so unsupported systems cleanly advertise "not available" rather than crashing at runtime
- **macOS Intel (x86_64) setup** ([#416](https://github.com/jamiepine/voicebox/pull/416)) — relaxed `torch>=2.7.0` → `torch>=2.2.0`. PyTorch dropped pre-built x86_64 wheels after 2.2.2, so Intel Mac devs could no longer `pip install`. Now resolves to the latest compatible torch per platform
- **Offline model loading** ([#318](https://github.com/jamiepine/voicebox/pull/318)) — Qwen TTS and Whisper force offline mode when loading cached models, so startup works without network access
- **GUI startup with external server** ([#319](https://github.com/jamiepine/voicebox/pull/319)) — fixed GUI launch when pointed at a remote/external server, and added data refresh on server switch; hardened health validation and error handling
- **Qwen3-TTS cache split on Windows** (adapted from [#218](https://github.com/jamiepine/voicebox/pull/218)) — route `Qwen3TTSModel.from_pretrained` through `hf_constants.HF_HUB_CACHE` so the speech tokenizer and `preprocessor_config.json` resolve from a single cache root
- **Qwen3-TTS bundling** ([#305](https://github.com/jamiepine/voicebox/pull/305)) — bundle `qwen_tts` source files in the PyInstaller build to fix `inspect.getsource` errors in frozen builds
- **Backend import paths** ([#345](https://github.com/jamiepine/voicebox/pull/345)) — moved lazy imports to top-level with absolute paths to resolve the "Failed to Save" preset error caused by `ModuleNotFoundError` in production builds
- **Effects service import** ([#384](https://github.com/jamiepine/voicebox/pull/384)) — fixed `ModuleNotFoundError` on preset create/update by switching to relative imports (#349)
#### Audio & Playback
- **cpal stream silent playback** ([#405](https://github.com/jamiepine/voicebox/pull/405)) — `cpal::Stream` was dropped on function return immediately after `play()`, causing every playback to fall silent. Now holds the stream until either the buffer drains or the stop flag fires (#404)
#### Stories & History
- **Clip-splitting race** ([#403](https://github.com/jamiepine/voicebox/pull/403)) — rapid double-clicks on split could race through `split_story_item` with inconsistent state. Added `with_for_update()` row locking on the backend and an `isPending` guard on the frontend (#366)
- **History `status` staleness** ([#394](https://github.com/jamiepine/voicebox/pull/394)) — `GET /history/{id}` was hardcoding `status="completed"` regardless of the DB row, breaking any client polling for job completion. Now returns `status`, `error`, `engine`, `model_size`, and `is_favorited` from the actual row
- **"Clear failed" bulk button** ([#412](https://github.com/jamiepine/voicebox/pull/412)) — new `DELETE /history/failed` endpoint and a header strip showing `"N failed generations"` with a Clear button, complementing the per-row trash icon added in #321 (#410)
- **Delete failed generations** ([#321](https://github.com/jamiepine/voicebox/pull/321)) — added a trash icon next to the retry button so failed entries can be cleaned up without having to retry first
#### Security & Safety
- **Voice prompt cache hardening** ([#429](https://github.com/jamiepine/voicebox/pull/429)) — `torch.load(weights_only=True)` on cached voice prompts per PyTorch 2.6 recommendation; replaced string-based SPA path guard with `Path.is_relative_to()` for more robust path-traversal protection
#### Infrastructure & Docker
- **Docker web build** ([#344](https://github.com/jamiepine/voicebox/pull/344)) — include `CHANGELOG.md` in the Docker web build so the in-app changelog page works in Docker deployments
- **Docker numba cache** ([#425](https://github.com/jamiepine/voicebox/pull/425)) — set `NUMBA_CACHE_DIR` in docker-compose so numba can write its JIT cache in container runtime (#308)
- **Relative media paths** ([#332](https://github.com/jamiepine/voicebox/pull/332)) — media paths now stored relative to the configured data dir rather than resolved against CWD, so the data directory is portable between installs
### Developer Tooling
- New `triage-prs` agent skill — encodes the end-to-end PR-speedrun workflow (classification → triage doc → rebase → squash-merge → follow-ups) so future release cycles can reproduce it
- Rewrote the TTS engine guide with the patterns learned from adding TADA and Kokoro
- Added the API refactor plan and CUDA libs addon design doc
- Fixed broken links in the Get Started section ([#332](https://github.com/jamiepine/voicebox/pull/332))
### New Contributors
Huge thank you to everyone who contributed their first PR to Voicebox in this release:
[@liorshahverdi](https://github.com/liorshahverdi), [@nicoschtein](https://github.com/nicoschtein), [@ArfianID](https://github.com/ArfianID), [@aimaaaimaa](https://github.com/aimaaaimaa), [@maxmcoding](https://github.com/maxmcoding), [@Khalodddd](https://github.com/Khalodddd), [@LuisSambrano](https://github.com/LuisSambrano), [@shaun0927](https://github.com/shaun0927), [@malletfils](https://github.com/malletfils), [@mvanhorn](https://github.com/mvanhorn), [@kuishou68](https://github.com/kuishou68), [@txhno](https://github.com/txhno), [@MukundaKatta](https://github.com/MukundaKatta)
## [0.3.0] - 2026-03-17
This release rewrites the backend into a modular architecture, overhauls the settings UI into routed sub-pages, fixes audio player freezing, migrates documentation to Fumadocs, and ships a batch of bug fixes targeting the most-reported issues from the tracker.
@@ -444,7 +555,9 @@ The first public release of Voicebox — an open-source voice synthesis studio p
Tauri v2, React, TypeScript, Tailwind CSS, FastAPI, Qwen3-TTS, Whisper, SQLite
[Unreleased]: https://github.com/jamiepine/voicebox/compare/v0.2.3...HEAD
[Unreleased]: https://github.com/jamiepine/voicebox/compare/v0.4.0...HEAD
[0.4.0]: https://github.com/jamiepine/voicebox/compare/v0.3.0...v0.4.0
[0.3.0]: https://github.com/jamiepine/voicebox/compare/v0.2.3...v0.3.0
[0.2.3]: https://github.com/jamiepine/voicebox/compare/v0.2.2...v0.2.3
[0.2.2]: https://github.com/jamiepine/voicebox/compare/v0.2.1...v0.2.2
[0.2.1]: https://github.com/jamiepine/voicebox/compare/v0.1.13...v0.2.1
+1 -1
View File
@@ -9,7 +9,7 @@ FROM oven/bun:1 AS frontend
WORKDIR /build
# Copy workspace config and frontend source
COPY package.json bun.lock ./
COPY package.json bun.lock CHANGELOG.md ./
COPY app/ ./app/
COPY web/ ./web/
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@voicebox/app",
"version": "0.3.1",
"version": "0.4.0",
"private": true,
"type": "module",
"scripts": {
+98 -9
View File
@@ -4,6 +4,8 @@ import voiceboxLogo from '@/assets/voicebox-logo.png';
import ShinyText from '@/components/ShinyText';
import { TitleBarDragRegion } from '@/components/TitleBarDragRegion';
import { useAutoUpdater } from '@/hooks/useAutoUpdater';
import { apiClient } from '@/lib/api/client';
import type { HealthResponse } from '@/lib/api/types';
import { TOP_SAFE_AREA_PADDING } from '@/lib/constants/ui';
import { cn } from '@/lib/utils/cn';
import { usePlatform } from '@/platform/PlatformContext';
@@ -11,6 +13,33 @@ import { router } from '@/router';
import { useLogStore } from '@/stores/logStore';
import { useServerStore } from '@/stores/serverStore';
/**
* Validate that a health response has the expected Voicebox-specific shape.
* Prevents misidentifying an unrelated service on the same port.
*/
function isVoiceboxHealthResponse(health: HealthResponse): boolean {
return (
health?.status === 'healthy' &&
typeof health.model_loaded === 'boolean' &&
typeof health.gpu_available === 'boolean'
);
}
/**
* Check whether a startup error indicates the port is occupied by an external
* server (which we should try to reuse via health-check polling) vs. a real
* failure (missing sidecar, signing issue, etc.) that should surface immediately.
*/
function isPortInUseError(error: unknown): boolean {
const msg = error instanceof Error ? error.message : String(error);
return (
msg.includes('already in use') ||
msg.includes('port') ||
msg.includes('EADDRINUSE') ||
msg.includes('address already in use')
);
}
const LOADING_MESSAGES = [
'Warming up tensors...',
'Calibrating synthesizer engine...',
@@ -37,6 +66,7 @@ const LOADING_MESSAGES = [
function App() {
const platform = usePlatform();
const [serverReady, setServerReady] = useState(false);
const [startupError, setStartupError] = useState<string | null>(null);
const [loadingMessageIndex, setLoadingMessageIndex] = useState(0);
const serverStartingRef = useRef(false);
@@ -122,6 +152,46 @@ function App() {
serverStartingRef.current = false;
// @ts-expect-error - adding property to window
window.__voiceboxServerStartedByApp = false;
// Only fall back to health-check polling when the error indicates the
// port is occupied (likely an external server). For real failures
// (missing sidecar, signing issues, etc.) surface the error immediately.
if (!isPortInUseError(error)) {
const msg = error instanceof Error ? error.message : String(error);
console.error('Real startup failure — not polling:', msg);
setStartupError(msg);
return;
}
// Fall back to polling: the server may already be running externally
// (e.g. started via python/uvicorn/Docker). Poll the health endpoint
// until it responds with a valid Voicebox payload, then transition to
// the main UI.
console.log('Falling back to health-check polling...');
const pollInterval = setInterval(async () => {
try {
const health = await apiClient.getHealth();
if (!isVoiceboxHealthResponse(health)) {
console.log('Health response is not from a Voicebox server, keep polling...');
return;
}
console.log('External Voicebox server detected via health check');
clearInterval(pollInterval);
setServerReady(true);
} catch {
// Server not ready yet, keep polling
}
}, 2000);
// Stop polling after 2 minutes and surface the failure
setTimeout(() => {
clearInterval(pollInterval);
serverStartingRef.current = false;
setStartupError(
'Could not connect to a Voicebox server within 2 minutes. ' +
'Please check that the server is running and try again.',
);
}, 120_000);
});
// Cleanup: stop server on actual unmount (not StrictMode remount)
@@ -168,15 +238,34 @@ function App() {
className="w-48 h-48 object-contain animate-fade-in-scale relative z-10"
/>
</div>
<div className="animate-fade-in-delayed">
<ShinyText
text={LOADING_MESSAGES[loadingMessageIndex]}
className="text-lg font-medium text-muted-foreground"
speed={2}
color="hsl(var(--muted-foreground))"
shineColor="hsl(var(--foreground))"
/>
</div>
{startupError ? (
<div className="animate-fade-in-delayed max-w-md mx-auto space-y-3">
<p className="text-lg font-medium text-destructive">Server startup failed</p>
<p className="text-sm text-muted-foreground">{startupError}</p>
<button
type="button"
className="mt-2 px-4 py-2 text-sm rounded-md bg-primary text-primary-foreground hover:bg-primary/90 transition-colors"
onClick={() => {
setStartupError(null);
serverStartingRef.current = false;
// Trigger a re-mount of the effect by toggling state
window.location.reload();
}}
>
Retry
</button>
</div>
) : (
<div className="animate-fade-in-delayed">
<ShinyText
text={LOADING_MESSAGES[loadingMessageIndex]}
className="text-lg font-medium text-muted-foreground"
speed={2}
color="hsl(var(--muted-foreground))"
shineColor="hsl(var(--foreground))"
/>
</div>
)}
</div>
</div>
);
+5 -3
View File
@@ -14,15 +14,17 @@ interface AppFrameProps {
export function AppFrame({ children }: AppFrameProps) {
const routerState = useRouterState();
const isStoriesRoute = routerState.location.pathname === '/stories';
const selectedStoryId = useStoryStore((state) => state.selectedStoryId);
const { data: story } = useStory(selectedStoryId);
// Show track editor when on stories route with a selected story that has items
const showTrackEditor = isStoriesRoute && selectedStoryId && story && story.items.length > 0;
return (
<div className={cn('h-screen bg-background flex flex-col overflow-hidden', TOP_SAFE_AREA_PADDING)}>
<div
className={cn('h-screen bg-background flex flex-col overflow-hidden', TOP_SAFE_AREA_PADDING)}
>
<TitleBarDragRegion />
{children}
{showTrackEditor ? (
+16 -16
View File
@@ -1,20 +1,20 @@
import {EffectsDetail} from "./EffectsDetail";
import {EffectsList} from "./EffectsList";
import { EffectsDetail } from './EffectsDetail';
import { EffectsList } from './EffectsList';
export function EffectsTab() {
return (
<div className="flex flex-col h-full min-h-0 overflow-hidden">
<div className="flex-1 min-h-0 flex gap-6 overflow-hidden">
{/* Left - Presets list */}
<div className="w-full max-w-[360px] shrink-0 flex flex-col min-h-0">
<EffectsList />
</div>
return (
<div className="flex flex-col h-full min-h-0 overflow-hidden">
<div className="flex-1 min-h-0 flex gap-6 overflow-hidden">
{/* Left - Presets list */}
<div className="w-full max-w-[360px] shrink-0 flex flex-col min-h-0">
<EffectsList />
</div>
{/* Right - Detail / editor */}
<div className="flex-1 min-h-0 flex flex-col">
<EffectsDetail />
</div>
</div>
</div>
);
{/* Right - Detail / editor */}
<div className="flex-1 min-h-0 flex flex-col">
<EffectsDetail />
</div>
</div>
</div>
);
}
@@ -1,3 +1,4 @@
import { useEffect } from 'react';
import type { UseFormReturn } from 'react-hook-form';
import { FormControl } from '@/components/ui/form';
import {
@@ -7,6 +8,7 @@ import {
SelectTrigger,
SelectValue,
} from '@/components/ui/select';
import type { VoiceProfileResponse } from '@/lib/api/types';
import { getLanguageOptionsForEngine } from '@/lib/constants/languages';
import type { GenerationFormValues } from '@/lib/hooks/useGenerationForm';
@@ -15,34 +17,57 @@ import type { GenerationFormValues } from '@/lib/hooks/useGenerationForm';
* Adding a new engine means adding one entry here.
*/
const ENGINE_OPTIONS = [
{ value: 'qwen:1.7B', label: 'Qwen3-TTS 1.7B' },
{ value: 'qwen:0.6B', label: 'Qwen3-TTS 0.6B' },
{ value: 'luxtts', label: 'LuxTTS' },
{ value: 'chatterbox', label: 'Chatterbox' },
{ value: 'chatterbox_turbo', label: 'Chatterbox Turbo' },
{ value: 'tada:1B', label: 'TADA 1B' },
{ value: 'tada:3B', label: 'TADA 3B Multilingual' },
{ value: 'qwen:1.7B', label: 'Qwen3-TTS 1.7B', engine: 'qwen' },
{ value: 'qwen:0.6B', label: 'Qwen3-TTS 0.6B', engine: 'qwen' },
{ value: 'qwen_custom_voice:1.7B', label: 'Qwen CustomVoice 1.7B', engine: 'qwen_custom_voice' },
{ value: 'qwen_custom_voice:0.6B', label: 'Qwen CustomVoice 0.6B', engine: 'qwen_custom_voice' },
{ value: 'luxtts', label: 'LuxTTS', engine: 'luxtts' },
{ value: 'chatterbox', label: 'Chatterbox', engine: 'chatterbox' },
{ value: 'chatterbox_turbo', label: 'Chatterbox Turbo', engine: 'chatterbox_turbo' },
{ value: 'tada:1B', label: 'TADA 1B', engine: 'tada' },
{ value: 'tada:3B', label: 'TADA 3B Multilingual', engine: 'tada' },
{ value: 'kokoro', label: 'Kokoro 82M', engine: 'kokoro' },
] as const;
const ENGINE_DESCRIPTIONS: Record<string, string> = {
qwen: 'Multi-language, two sizes',
qwen_custom_voice: '9 preset voices, instruct control',
luxtts: 'Fast, English-focused',
chatterbox: '23 languages, incl. Hebrew',
chatterbox_turbo: 'English, [laugh] [cough] tags',
tada: 'HumeAI, 700s+ coherent audio',
kokoro: '82M params, CPU realtime, 8 langs',
};
/** Engines that only support English and should force language to 'en' on select. */
const ENGLISH_ONLY_ENGINES = new Set(['luxtts', 'chatterbox_turbo']);
/** Engines that support cloned (reference audio) profiles. */
const CLONING_ENGINES = new Set(['qwen', 'luxtts', 'chatterbox', 'chatterbox_turbo', 'tada']);
function getAvailableOptions(selectedProfile?: VoiceProfileResponse | null) {
if (!selectedProfile) return ENGINE_OPTIONS;
return ENGINE_OPTIONS.filter((opt) => isProfileCompatibleWithEngine(selectedProfile, opt.engine));
}
function getSelectValue(engine: string, modelSize?: string): string {
if (engine === 'qwen') return `qwen:${modelSize || '1.7B'}`;
if (engine === 'qwen_custom_voice') return `qwen_custom_voice:${modelSize || '1.7B'}`;
if (engine === 'tada') return `tada:${modelSize || '1B'}`;
return engine;
}
function handleEngineChange(form: UseFormReturn<GenerationFormValues>, value: string) {
if (value.startsWith('qwen:')) {
export function applyEngineSelection(form: UseFormReturn<GenerationFormValues>, value: string) {
if (value.startsWith('qwen_custom_voice:')) {
const [, modelSize] = value.split(':');
form.setValue('engine', 'qwen_custom_voice');
form.setValue('modelSize', modelSize as '1.7B' | '0.6B');
const currentLang = form.getValues('language');
const available = getLanguageOptionsForEngine('qwen_custom_voice');
if (!available.some((l) => l.value === currentLang)) {
form.setValue('language', available[0]?.value ?? 'en');
}
} else if (value.startsWith('qwen:')) {
const [, modelSize] = value.split(':');
form.setValue('engine', 'qwen');
form.setValue('modelSize', modelSize as '1.7B' | '0.6B');
@@ -85,12 +110,22 @@ function handleEngineChange(form: UseFormReturn<GenerationFormValues>, value: st
interface EngineModelSelectorProps {
form: UseFormReturn<GenerationFormValues>;
compact?: boolean;
selectedProfile?: VoiceProfileResponse | null;
}
export function EngineModelSelector({ form, compact }: EngineModelSelectorProps) {
export function EngineModelSelector({ form, compact, selectedProfile }: EngineModelSelectorProps) {
const engine = form.watch('engine') || 'qwen';
const modelSize = form.watch('modelSize');
const selectValue = getSelectValue(engine, modelSize);
const availableOptions = getAvailableOptions(selectedProfile);
const currentEngineAvailable = availableOptions.some((opt) => opt.value === selectValue);
useEffect(() => {
if (!currentEngineAvailable && availableOptions.length > 0) {
applyEngineSelection(form, availableOptions[0].value);
}
}, [availableOptions, currentEngineAvailable, form]);
const itemClass = compact ? 'text-xs text-muted-foreground' : undefined;
const triggerClass = compact
@@ -98,14 +133,14 @@ export function EngineModelSelector({ form, compact }: EngineModelSelectorProps)
: undefined;
return (
<Select value={selectValue} onValueChange={(v) => handleEngineChange(form, v)}>
<Select value={selectValue} onValueChange={(v) => applyEngineSelection(form, v)}>
<FormControl>
<SelectTrigger className={triggerClass}>
<SelectValue />
</SelectTrigger>
</FormControl>
<SelectContent>
{ENGINE_OPTIONS.map((opt) => (
{availableOptions.map((opt) => (
<SelectItem key={opt.value} value={opt.value} className={itemClass}>
{opt.label}
</SelectItem>
@@ -119,3 +154,17 @@ export function EngineModelSelector({ form, compact }: EngineModelSelectorProps)
export function getEngineDescription(engine: string): string {
return ENGINE_DESCRIPTIONS[engine] ?? '';
}
/**
* Check if a profile is compatible with the currently selected engine.
* Useful for UI hints.
*/
export function isProfileCompatibleWithEngine(
profile: VoiceProfileResponse,
engine: string,
): boolean {
const voiceType = profile.voice_type || 'cloned';
if (voiceType === 'preset') return profile.preset_engine === engine;
if (voiceType === 'cloned') return CLONING_ENGINES.has(engine);
return true; // designed — future
}
@@ -1,7 +1,7 @@
import { useQuery } from '@tanstack/react-query';
import { useMatchRoute } from '@tanstack/react-router';
import { AnimatePresence, motion } from 'framer-motion';
import { Loader2, Sparkles } from 'lucide-react';
import { Loader2, SlidersHorizontal, Sparkles } from 'lucide-react';
import { useEffect, useRef, useState } from 'react';
import { Button } from '@/components/ui/button';
import { Form, FormControl, FormField, FormItem, FormMessage } from '@/components/ui/form';
@@ -36,9 +36,11 @@ export function FloatingGenerateBox({
}: FloatingGenerateBoxProps) {
const selectedProfileId = useUIStore((state) => state.selectedProfileId);
const setSelectedProfileId = useUIStore((state) => state.setSelectedProfileId);
const setSelectedEngine = useUIStore((state) => state.setSelectedEngine);
const { data: selectedProfile } = useProfile(selectedProfileId || '');
const { data: profiles } = useProfiles();
const [isExpanded, setIsExpanded] = useState(false);
const [isInstructExpanded, setIsInstructExpanded] = useState(false);
const [selectedPresetId, setSelectedPresetId] = useState<string | null>(null);
const containerRef = useRef<HTMLDivElement>(null);
const textareaRef = useRef<HTMLTextAreaElement | null>(null);
@@ -67,7 +69,12 @@ export function FloatingGenerateBox({
}
},
getEffectsChain: () => {
if (!selectedPresetId || !effectPresets) return undefined;
if (!selectedPresetId) return undefined;
// Profile's own effects chain (no matching preset)
if (selectedPresetId === '_profile') {
return selectedProfile?.effects_chain ?? undefined;
}
if (!effectPresets) return undefined;
const preset = effectPresets.find((p) => p.id === selectedPresetId);
return preset?.effects_chain;
},
@@ -110,12 +117,63 @@ export function FloatingGenerateBox({
}
}, [selectedProfileId, profiles, setSelectedProfileId]);
// Sync generation form language with selected profile's language
// Sync engine selection to global store so ProfileList can filter
const watchedEngine = form.watch('engine');
useEffect(() => {
if (watchedEngine) {
setSelectedEngine(watchedEngine);
}
}, [watchedEngine, setSelectedEngine]);
// Sync generation form language, engine, and effects with selected profile
type EngineValue =
| 'qwen'
| 'luxtts'
| 'chatterbox'
| 'chatterbox_turbo'
| 'tada'
| 'kokoro'
| 'qwen_custom_voice';
useEffect(() => {
if (selectedProfile?.language) {
form.setValue('language', selectedProfile.language as LanguageCode);
}
}, [selectedProfile, form]);
// Auto-switch engine to match the profile
const engine = selectedProfile?.default_engine ?? selectedProfile?.preset_engine;
if (engine) {
form.setValue('engine', engine as EngineValue);
} else if (selectedProfile && selectedProfile.voice_type !== 'preset') {
// Cloned/designed profile with no default — ensure a compatible (non-preset) engine
const currentEngine = form.getValues('engine');
const presetEngines = new Set(['kokoro', 'qwen_custom_voice']);
if (presetEngines.has(currentEngine)) {
form.setValue('engine', 'qwen');
}
}
// Pre-fill effects from profile defaults
if (
selectedProfile?.effects_chain &&
selectedProfile.effects_chain.length > 0 &&
effectPresets
) {
// Try to match against a known preset
const profileChainJson = JSON.stringify(selectedProfile.effects_chain);
const matchingPreset = effectPresets.find(
(p) => JSON.stringify(p.effects_chain) === profileChainJson,
);
if (matchingPreset) {
setSelectedPresetId(matchingPreset.id);
} else {
// No matching preset — use special value to pass profile chain directly
setSelectedPresetId('_profile');
}
} else if (
selectedProfile &&
(!selectedProfile.effects_chain || selectedProfile.effects_chain.length === 0)
) {
setSelectedPresetId(null);
}
}, [selectedProfile, effectPresets, form]);
// Auto-resize textarea based on content (only when expanded)
useEffect(() => {
@@ -296,9 +354,80 @@ export function FloatingGenerateBox({
: 'Generate speech'}
</span>
</div>
{/* Instruct toggle — only for Qwen CustomVoice, which actually honors the kwarg */}
<AnimatePresence>
{isExpanded && form.watch('engine') === 'qwen_custom_voice' && (
<motion.div
initial={{ opacity: 0, scale: 0.8 }}
animate={{ opacity: 1, scale: 1 }}
exit={{ opacity: 0, scale: 0.8 }}
transition={{ duration: 0.2 }}
className="absolute top-0 right-[calc(100%+0.5rem)]"
>
<div className="group relative">
<Button
type="button"
variant="ghost"
size="icon"
onClick={() => setIsInstructExpanded((prev) => !prev)}
className={cn(
'h-10 w-10 rounded-full transition-all duration-200',
isInstructExpanded
? 'bg-accent text-accent-foreground border border-accent hover:bg-accent/90'
: 'bg-card border border-border hover:bg-background/50',
)}
aria-label={
isInstructExpanded
? 'Hide delivery instructions'
: 'Show delivery instructions'
}
aria-pressed={isInstructExpanded}
>
<SlidersHorizontal className="h-4 w-4" />
</Button>
<span className="pointer-events-none absolute bottom-full left-1/2 -translate-x-1/2 mb-2 whitespace-nowrap rounded-md bg-popover px-3 py-1.5 text-xs text-popover-foreground border border-border opacity-0 transition-opacity group-hover:opacity-100 z-[9999]">
Delivery instructions (tone, emotion, pace)
</span>
</div>
</motion.div>
)}
</AnimatePresence>
</div>
</div>
{/* Additive instruct textarea — shown below main text when toggle is on and engine supports it */}
<AnimatePresence>
{isInstructExpanded && form.watch('engine') === 'qwen_custom_voice' && (
<motion.div
initial={{ opacity: 0, height: 0 }}
animate={{ opacity: 1, height: 'auto' }}
exit={{ opacity: 0, height: 0 }}
transition={{ duration: 0.2, ease: 'easeOut' }}
className="overflow-hidden"
>
<FormField
control={form.control}
name="instruct"
render={({ field }) => (
<FormItem className="mt-2">
<FormControl>
<Textarea
{...field}
placeholder="Delivery instructions — e.g. Speak slowly with warmth, Authoritative and clear..."
className="resize-none bg-transparent border border-accent/20 focus-visible:ring-1 focus-visible:ring-accent/40 rounded-2xl text-sm placeholder:text-muted-foreground/60 w-full px-3 py-2"
style={{ minHeight: '60px', maxHeight: '160px' }}
maxLength={500}
/>
</FormControl>
<FormMessage className="text-xs" />
</FormItem>
)}
/>
</motion.div>
)}
</AnimatePresence>
<AnimatePresence>
<motion.div
initial={{ height: 0, opacity: 0 }}
@@ -375,6 +504,12 @@ export function FloatingGenerateBox({
<SelectItem value="none" className="text-xs">
No effects
</SelectItem>
{selectedProfile?.effects_chain &&
selectedProfile.effects_chain.length > 0 && (
<SelectItem value="_profile" className="text-xs">
Profile default
</SelectItem>
)}
{effectPresets?.map((preset) => (
<SelectItem key={preset.id} value={preset.id} className="text-xs">
{preset.name}
@@ -1,4 +1,5 @@
import { Loader2, Mic } from 'lucide-react';
import { useEffect } from 'react';
import { Button } from '@/components/ui/button';
import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card';
import {
@@ -19,19 +20,45 @@ import {
SelectValue,
} from '@/components/ui/select';
import { Textarea } from '@/components/ui/textarea';
import { getLanguageOptionsForEngine } from '@/lib/constants/languages';
import { getLanguageOptionsForEngine, type LanguageCode } from '@/lib/constants/languages';
import { useGenerationForm } from '@/lib/hooks/useGenerationForm';
import { useProfile } from '@/lib/hooks/useProfiles';
import { useUIStore } from '@/stores/uiStore';
import { EngineModelSelector, getEngineDescription } from './EngineModelSelector';
import {
applyEngineSelection,
EngineModelSelector,
getEngineDescription,
} from './EngineModelSelector';
import { ParalinguisticInput } from './ParalinguisticInput';
function getEngineSelectValue(engine: string): string {
if (engine === 'qwen') return 'qwen:1.7B';
if (engine === 'qwen_custom_voice') return 'qwen_custom_voice:1.7B';
if (engine === 'tada') return 'tada:1B';
return engine;
}
export function GenerationForm() {
const selectedProfileId = useUIStore((state) => state.selectedProfileId);
const { data: selectedProfile } = useProfile(selectedProfileId || '');
const { form, handleSubmit, isPending } = useGenerationForm();
useEffect(() => {
if (!selectedProfile) {
return;
}
if (selectedProfile.language) {
form.setValue('language', selectedProfile.language as LanguageCode);
}
const preferredEngine = selectedProfile.default_engine || selectedProfile.preset_engine;
if (preferredEngine) {
applyEngineSelection(form, getEngineSelectValue(preferredEngine));
}
}, [form, selectedProfile]);
async function onSubmit(data: Parameters<typeof handleSubmit>[0]) {
await handleSubmit(data, selectedProfileId);
}
@@ -91,7 +118,7 @@ export function GenerationForm() {
)}
/>
{form.watch('engine') === 'qwen' && (
{form.watch('engine') === 'qwen_custom_voice' && (
<FormField
control={form.control}
name="instruct"
@@ -118,7 +145,7 @@ export function GenerationForm() {
<div className="grid gap-4 md:grid-cols-3">
<FormItem>
<FormLabel>Model</FormLabel>
<EngineModelSelector form={form} />
<EngineModelSelector form={form} selectedProfile={selectedProfile} />
<FormDescription>
{getEngineDescription(form.watch('engine') || 'qwen')}
</FormDescription>
+89 -11
View File
@@ -45,6 +45,7 @@ import { apiClient } from '@/lib/api/client';
import type { EffectConfig, GenerationVersionResponse, HistoryResponse } from '@/lib/api/types';
import { BOTTOM_SAFE_AREA_PADDING } from '@/lib/constants/ui';
import {
useClearFailedGenerations,
useDeleteGeneration,
useExportGeneration,
useExportGenerationAudio,
@@ -124,6 +125,8 @@ export function HistoryTable() {
});
const deleteGeneration = useDeleteGeneration();
const clearFailed = useClearFailedGenerations();
const [clearFailedDialogOpen, setClearFailedDialogOpen] = useState(false);
const exportGeneration = useExportGeneration();
const exportGenerationAudio = useExportGenerationAudio();
const importGeneration = useImportGeneration();
@@ -157,11 +160,11 @@ export function HistoryTable() {
const pendingCount = useGenerationStore((state) => state.pendingGenerationIds.size);
const prevPendingCountRef = useRef(pendingCount);
useEffect(() => {
if (deleteGeneration.isSuccess || importGeneration.isSuccess) {
if (deleteGeneration.isSuccess || importGeneration.isSuccess || clearFailed.isSuccess) {
setPage(0);
setAllHistory([]);
}
}, [deleteGeneration.isSuccess, importGeneration.isSuccess]);
}, [deleteGeneration.isSuccess, importGeneration.isSuccess, clearFailed.isSuccess]);
useEffect(() => {
// A generation finished (pending count decreased) — scroll back to show it
@@ -415,6 +418,27 @@ export function HistoryTable() {
const history = allHistory;
const hasMore = allHistory.length < total;
const failedCount = history.filter((g) => g.status === 'failed').length;
const handleClearFailedConfirm = () => {
clearFailed.mutate(undefined, {
onSuccess: (data) => {
setClearFailedDialogOpen(false);
toast({
title: 'Cleared failed generations',
description: `${data.deleted} failed ${data.deleted === 1 ? 'generation' : 'generations'} removed.`,
});
},
onError: (error) => {
setClearFailedDialogOpen(false);
toast({
title: 'Failed to clear',
description: error instanceof Error ? error.message : 'Unknown error',
variant: 'destructive',
});
},
});
};
return (
<div className="flex flex-col h-full min-h-0 relative">
@@ -424,6 +448,23 @@ export function HistoryTable() {
</div>
) : (
<>
{failedCount > 0 && (
<div className="flex items-center justify-between px-1 pb-2">
<span className="text-xs text-muted-foreground">
{failedCount} failed {failedCount === 1 ? 'generation' : 'generations'}
</span>
<Button
variant="ghost"
size="sm"
className="h-7 text-xs text-muted-foreground hover:text-destructive"
onClick={() => setClearFailedDialogOpen(true)}
disabled={clearFailed.isPending}
>
<Trash2 className="h-3 w-3 mr-1.5" />
{clearFailed.isPending ? 'Clearing...' : 'Clear failed'}
</Button>
</div>
)}
{isScrolled && (
<div className="absolute top-0 left-0 right-0 h-16 bg-gradient-to-b from-background to-transparent z-10 pointer-events-none" />
)}
@@ -569,15 +610,27 @@ export function HistoryTable() {
)}
{isFailed ? (
<Button
variant="ghost"
size="icon"
className="h-6 w-6 text-muted-foreground/50 hover:bg-muted-foreground/20 hover:text-muted-foreground"
aria-label="Retry generation"
onClick={() => handleRetry(gen.id)}
>
<RotateCcw className="h-2 w-2" />
</Button>
<>
<Button
variant="ghost"
size="icon"
className="h-6 w-6 text-muted-foreground/50 hover:bg-muted-foreground/20 hover:text-muted-foreground"
aria-label="Retry generation"
onClick={() => handleRetry(gen.id)}
>
<RotateCcw className="h-2 w-2" />
</Button>
<Button
variant="ghost"
size="icon"
className="h-6 w-6 text-muted-foreground/50 hover:bg-muted-foreground/20 hover:text-muted-foreground"
aria-label="Delete generation"
disabled={deleteGeneration.isPending}
onClick={() => handleDeleteClick(gen.id, gen.profile_name)}
>
<Trash2 className="h-2 w-2" />
</Button>
</>
) : (
<>
<DropdownMenu>
@@ -747,6 +800,31 @@ export function HistoryTable() {
</DialogContent>
</Dialog>
<Dialog open={clearFailedDialogOpen} onOpenChange={setClearFailedDialogOpen}>
<DialogContent>
<DialogHeader>
<DialogTitle>Clear failed generations</DialogTitle>
<DialogDescription>
This will permanently delete {failedCount} failed{' '}
{failedCount === 1 ? 'generation' : 'generations'} from your history. This cannot be
undone.
</DialogDescription>
</DialogHeader>
<DialogFooter>
<Button variant="outline" onClick={() => setClearFailedDialogOpen(false)}>
Cancel
</Button>
<Button
variant="destructive"
onClick={handleClearFailedConfirm}
disabled={clearFailed.isPending}
>
{clearFailed.isPending ? 'Clearing...' : 'Clear all'}
</Button>
</DialogFooter>
</DialogContent>
</Dialog>
<Dialog open={importDialogOpen} onOpenChange={setImportDialogOpen}>
<DialogContent>
<DialogHeader>
@@ -243,7 +243,40 @@ export function GpuAcceleration() {
{/* Native GPU detected - no CUDA download needed */}
{/* CUDA download section - only show when no GPU is active (native or CUDA) */}
{/* Currently running CUDA - show switch back to CPU */}
{isCurrentlyCuda && platform.metadata.isTauri && (
<>
{restartPhase !== 'idle' ? (
<div className="flex items-center gap-2 p-3 rounded-lg bg-primary/5 border">
<Loader2 className="h-4 w-4 animate-spin" />
<span className="text-sm">
{restartPhase === 'stopping' && 'Stopping server...'}
{restartPhase === 'waiting' && 'Restarting server...'}
{restartPhase === 'ready' && 'Server restarted successfully!'}
</span>
</div>
) : (
<div className="space-y-3">
<p className="text-sm text-muted-foreground">
Running with CUDA GPU acceleration. Switch back to CPU if needed (you can
re-download later).
</p>
<Button onClick={handleSwitchToCpu} variant="outline" className="w-full" size="sm">
<RotateCw className="h-4 w-4 mr-2" />
Switch to CPU Backend
</Button>
</div>
)}
{error && (
<div className="flex items-center gap-2 text-sm text-destructive">
<AlertCircle className="h-4 w-4 shrink-0" />
<span>{error}</span>
</div>
)}
</>
)}
{/* CUDA download/manage section - show when no native GPU and not currently running CUDA */}
{!hasNativeGpu && !isCurrentlyCuda && (
<>
{/* Download progress (manual download or auto-update) */}
@@ -315,7 +348,7 @@ export function GpuAcceleration() {
)}
{/* Downloaded but not active - show switch button */}
{cudaAvailable && !isCurrentlyCuda && platform.metadata.isTauri && (
{cudaAvailable && platform.metadata.isTauri && (
<div className="space-y-3">
<p className="text-sm text-muted-foreground">
CUDA backend is downloaded and ready. Restart the server to enable GPU
@@ -328,27 +361,8 @@ export function GpuAcceleration() {
</div>
)}
{/* Currently active - show switch back to CPU */}
{isCurrentlyCuda && platform.metadata.isTauri && (
<div className="space-y-3">
<p className="text-sm text-muted-foreground">
Running with CUDA GPU acceleration. Switch back to CPU if needed (you can
re-download later).
</p>
<Button
onClick={handleSwitchToCpu}
variant="outline"
className="w-full"
size="sm"
>
<RotateCw className="h-4 w-4 mr-2" />
Switch to CPU Backend
</Button>
</div>
)}
{/* Delete option when downloaded (and not active) */}
{cudaAvailable && !isCurrentlyCuda && (
{cudaAvailable && (
<Button
onClick={handleDelete}
variant="ghost"
@@ -66,6 +66,12 @@ const MODEL_DESCRIPTIONS: Record<string, string> = {
'HumeAI TADA 1B — English speech-language model built on Llama 3.2 1B. Generates 700s+ of coherent audio with synchronized text-acoustic alignment.',
'tada-3b-ml':
'HumeAI TADA 3B Multilingual — built on Llama 3.2 3B. Supports 10 languages with high-fidelity voice cloning via text-acoustic dual alignment.',
kokoro:
'Kokoro 82M by hexgrad. Tiny 82M-parameter TTS that runs at CPU realtime. Supports 8 languages with pre-built voice styles. Apache 2.0 licensed.',
'qwen-custom-voice-1.7B':
'Qwen3-TTS CustomVoice 1.7B by Alibaba. 9 premium preset voices with instruct-based style control for tone, emotion, and prosody. Supports 10 languages.',
'qwen-custom-voice-0.6B':
'Qwen3-TTS CustomVoice 0.6B by Alibaba. Lightweight version with the same 9 preset voices and instruct control. Faster inference for lower-end hardware.',
'whisper-base':
'Smallest Whisper model (74M parameters). Fast transcription with moderate accuracy.',
'whisper-small':
@@ -394,9 +400,11 @@ export function ModelManagement() {
modelStatus?.models.filter(
(m) =>
m.model_name.startsWith('qwen-tts') ||
m.model_name.startsWith('qwen-custom-voice') ||
m.model_name.startsWith('luxtts') ||
m.model_name.startsWith('chatterbox') ||
m.model_name.startsWith('tada'),
m.model_name.startsWith('tada') ||
m.model_name.startsWith('kokoro'),
) ?? [];
const whisperModels = modelStatus?.models.filter((m) => m.model_name.startsWith('whisper')) ?? [];
@@ -12,7 +12,11 @@ interface ModelProgressProps {
isDownloading?: boolean;
}
export function ModelProgress({ modelName, displayName, isDownloading = false }: ModelProgressProps) {
export function ModelProgress({
modelName,
displayName,
isDownloading = false,
}: ModelProgressProps) {
const [progress, setProgress] = useState<ModelProgressType | null>(null);
const serverUrl = useServerStore((state) => state.serverUrl);
@@ -182,8 +182,8 @@ function ChangelogEntryCard({ entry }: { entry: ChangelogEntry }) {
return (
<div className="border-b border-border/50 pb-6">
<div className="flex items-baseline gap-3 mb-1">
<h3 className="text-sm font-medium">{entry.version}</h3>
<div className="flex items-baseline gap-3 mb-3">
<h3 className="text-xl font-semibold tracking-tight">{entry.version}</h3>
{entry.date && <span className="text-xs text-muted-foreground">{entry.date}</span>}
{entry.version === 'Unreleased' && <Badge variant="outline">dev</Badge>}
</div>
+12 -16
View File
@@ -87,7 +87,7 @@ export function StoryChatItem({
alt={`${item.profile_name} avatar`}
className={cn(
'h-full w-full object-cover transition-all duration-200',
!isCurrentlyPlaying && 'grayscale'
!isCurrentlyPlaying && 'grayscale',
)}
onError={() => setAvatarError(true)}
/>
@@ -127,7 +127,10 @@ export function StoryChatItem({
<Play className="mr-2 h-4 w-4" />
Play from here
</DropdownMenuItem>
<DropdownMenuItem onClick={onRemove} className="text-destructive focus:text-destructive">
<DropdownMenuItem
onClick={onRemove}
className="text-destructive focus:text-destructive"
>
<Trash2 className="mr-2 h-4 w-4" />
Remove from Story
</DropdownMenuItem>
@@ -139,15 +142,12 @@ export function StoryChatItem({
}
// Sortable wrapper component
export function SortableStoryChatItem(props: Omit<StoryChatItemProps, 'dragHandleProps' | 'isDragging'>) {
const {
attributes,
listeners,
setNodeRef,
transform,
transition,
isDragging,
} = useSortable({ id: props.item.generation_id });
export function SortableStoryChatItem(
props: Omit<StoryChatItemProps, 'dragHandleProps' | 'isDragging'>,
) {
const { attributes, listeners, setNodeRef, transform, transition, isDragging } = useSortable({
id: props.item.generation_id,
});
const style = {
transform: CSS.Transform.toString(transform),
@@ -156,11 +156,7 @@ export function SortableStoryChatItem(props: Omit<StoryChatItemProps, 'dragHandl
return (
<div ref={setNodeRef} style={style} {...attributes}>
<StoryChatItem
{...props}
dragHandleProps={listeners}
isDragging={isDragging}
/>
<StoryChatItem {...props} dragHandleProps={listeners} isDragging={isDragging} />
</div>
);
}
@@ -500,7 +500,7 @@ export function StoryTrackEditor({ storyId, items }: StoryTrackEditorProps) {
}, [trimmingItem, trimSide, tempTrimValues, storyId, trimItem, toast]);
const handleSplit = useCallback(() => {
if (!selectedClipId) return;
if (!selectedClipId || splitItem.isPending) return;
const item = items.find((i) => i.id === selectedClipId);
if (!item) return;
@@ -14,12 +14,7 @@ const MemoizedWaveform = memo(function MemoizedWaveform({
<div className="absolute inset-0 pointer-events-none flex items-center justify-center opacity-30">
<Visualizer audio={audioStream} autoStart strokeColor="#b39a3d">
{({ canvasRef }) => (
<canvas
ref={canvasRef}
width={500}
height={150}
className="w-full h-full"
/>
<canvas ref={canvasRef} width={500} height={150} className="w-full h-full" />
)}
</Visualizer>
</div>
@@ -87,9 +82,7 @@ export function AudioSampleRecording({
<div className="space-y-4">
{!isRecording && !file && (
<div className="relative flex flex-col items-center justify-center gap-4 p-4 border-2 border-dashed rounded-lg min-h-[180px] overflow-hidden">
{showWaveform && audioStream && (
<MemoizedWaveform audioStream={audioStream} />
)}
{showWaveform && audioStream && <MemoizedWaveform audioStream={audioStream} />}
<Button
type="button"
onClick={onStart}
@@ -107,9 +100,7 @@ export function AudioSampleRecording({
{isRecording && (
<div className="relative flex flex-col items-center justify-center gap-4 p-4 border-2 border-accent rounded-lg bg-accent/5 min-h-[180px] overflow-hidden">
{showWaveform && audioStream && (
<MemoizedWaveform audioStream={audioStream} />
)}
{showWaveform && audioStream && <MemoizedWaveform audioStream={audioStream} />}
<div className="relative z-10 flex items-center gap-4">
<div className="flex items-center gap-2">
<div className="h-3 w-3 rounded-full bg-accent animate-pulse" />
@@ -17,11 +17,18 @@ import { useDeleteProfile, useExportProfile } from '@/lib/hooks/useProfiles';
import { cn } from '@/lib/utils/cn';
import { useUIStore } from '@/stores/uiStore';
/** Human-readable display names for preset engine badges. */
const ENGINE_DISPLAY_NAMES: Record<string, string> = {
kokoro: 'Kokoro',
qwen_custom_voice: 'CustomVoice',
};
interface ProfileCardProps {
profile: VoiceProfileResponse;
disabled?: boolean;
}
export function ProfileCard({ profile }: ProfileCardProps) {
export function ProfileCard({ profile, disabled }: ProfileCardProps) {
const [deleteDialogOpen, setDeleteDialogOpen] = useState(false);
const deleteProfile = useDeleteProfile();
@@ -34,6 +41,12 @@ export function ProfileCard({ profile }: ProfileCardProps) {
const isSelected = selectedProfileId === profile.id;
const handleSelect = () => {
// If disabled but already selected, bounce the selection to re-trigger engine auto-switch
if (disabled && isSelected) {
setSelectedProfileId(null);
setTimeout(() => setSelectedProfileId(profile.id), 0);
return;
}
setSelectedProfileId(isSelected ? null : profile.id);
};
@@ -74,8 +87,9 @@ export function ProfileCard({ profile }: ProfileCardProps) {
<>
<Card
className={cn(
'cursor-pointer hover:shadow-md transition-all flex flex-col h-[162px]',
isSelected && 'ring-2 ring-accent shadow-md',
'cursor-pointer transition-all flex flex-col h-[162px]',
disabled ? 'opacity-40 hover:opacity-60' : 'hover:shadow-md',
isSelected && !disabled && 'ring-2 ring-accent shadow-md',
)}
onClick={handleSelect}
tabIndex={0}
@@ -97,6 +111,16 @@ export function ProfileCard({ profile }: ProfileCardProps) {
<Badge variant="outline" className="text-xs h-5 px-1.5 text-muted-foreground">
{profile.language}
</Badge>
{profile.voice_type === 'preset' && (
<Badge variant="secondary" className="text-xs h-5 px-1.5">
{ENGINE_DISPLAY_NAMES[profile.preset_engine ?? ''] ?? profile.preset_engine}
</Badge>
)}
{profile.voice_type === 'designed' && (
<Badge variant="secondary" className="text-xs h-5 px-1.5">
designed
</Badge>
)}
{profile.effects_chain && profile.effects_chain.length > 0 && (
<Sparkles className="h-3.5 w-3.5 text-accent fill-accent" />
)}
+416 -131
View File
@@ -1,9 +1,11 @@
import { zodResolver } from '@hookform/resolvers/zod';
import { Edit2, Mic, Monitor, Upload, X } from 'lucide-react';
import { useQuery } from '@tanstack/react-query';
import { Edit2, Mic, Monitor, Music, Upload, X } from 'lucide-react';
import { useEffect, useRef, useState } from 'react';
import { useForm } from 'react-hook-form';
import * as z from 'zod';
import { EffectsChainEditor } from '@/components/Effects/EffectsChainEditor';
import { Badge } from '@/components/ui/badge';
import { Button } from '@/components/ui/button';
import {
Dialog,
@@ -15,6 +17,7 @@ import {
import {
Form,
FormControl,
FormDescription,
FormField,
FormItem,
FormLabel,
@@ -32,7 +35,7 @@ import { Tabs, TabsContent, TabsList, TabsTrigger } from '@/components/ui/tabs';
import { Textarea } from '@/components/ui/textarea';
import { useToast } from '@/components/ui/use-toast';
import { apiClient } from '@/lib/api/client';
import type { EffectConfig } from '@/lib/api/types';
import type { EffectConfig, PresetVoice, VoiceType } from '@/lib/api/types';
import { LANGUAGE_CODES, LANGUAGE_OPTIONS, type LanguageCode } from '@/lib/constants/languages';
import { useAudioPlayer } from '@/lib/hooks/useAudioPlayer';
import { useAudioRecording } from '@/lib/hooks/useAudioRecording';
@@ -40,6 +43,7 @@ import {
useAddSample,
useCreateProfile,
useDeleteAvatar,
useDeleteProfile,
useProfile,
useUpdateProfile,
useUploadAvatar,
@@ -56,6 +60,16 @@ import { AudioSampleUpload } from './AudioSampleUpload';
import { SampleList } from './SampleList';
const MAX_AUDIO_DURATION_SECONDS = 30;
const PRESET_ONLY_ENGINES = new Set(['kokoro', 'qwen_custom_voice']);
const DEFAULT_ENGINE_OPTIONS = [
{ value: 'qwen', label: 'Qwen3-TTS' },
{ value: 'qwen_custom_voice', label: 'Qwen CustomVoice' },
{ value: 'luxtts', label: 'LuxTTS' },
{ value: 'chatterbox', label: 'Chatterbox' },
{ value: 'chatterbox_turbo', label: 'Chatterbox Turbo' },
{ value: 'tada', label: 'TADA' },
{ value: 'kokoro', label: 'Kokoro 82M' },
] as const;
const baseProfileSchema = z.object({
name: z.string().min(1, 'Name is required').max(100),
@@ -116,20 +130,25 @@ export function ProfileForm() {
const createProfile = useCreateProfile();
const updateProfile = useUpdateProfile();
const addSample = useAddSample();
const deleteProfile = useDeleteProfile();
const uploadAvatar = useUploadAvatar();
const deleteAvatar = useDeleteAvatar();
const transcribe = useTranscription();
const { toast } = useToast();
const [voiceSource, setVoiceSource] = useState<'clone' | 'builtin'>('clone');
const [sampleMode, setSampleMode] = useState<'upload' | 'record' | 'system'>('record');
const [audioDuration, setAudioDuration] = useState<number | null>(null);
const [isValidatingAudio, setIsValidatingAudio] = useState(false);
const [avatarPreview, setAvatarPreview] = useState<string | null>(null);
const [selectedPresetEngine, setSelectedPresetEngine] = useState<string>('kokoro');
const [selectedPresetVoiceId, setSelectedPresetVoiceId] = useState<string>('');
const avatarInputRef = useRef<HTMLInputElement>(null);
const { isPlaying, playPause, cleanup: cleanupAudio } = useAudioPlayer();
const isCreating = !editingProfileId;
const serverUrl = useServerStore((state) => state.serverUrl);
const [profileEffectsChain, setProfileEffectsChain] = useState<EffectConfig[]>([]);
const [effectsDirty, setEffectsDirty] = useState(false);
const [defaultEngine, setDefaultEngine] = useState<string>('');
const form = useForm<ProfileFormValues>({
resolver: zodResolver(profileSchema),
@@ -239,6 +258,26 @@ export function ProfileForm() {
},
});
// Fetch available preset voices for the selected engine
const presetEngineToQuery = isCreating
? selectedPresetEngine
: (editingProfile?.preset_engine ?? '');
const { data: presetVoicesData } = useQuery({
queryKey: ['presetVoices', presetEngineToQuery],
queryFn: () => apiClient.listPresetVoices(presetEngineToQuery),
enabled:
!!presetEngineToQuery &&
((voiceSource === 'builtin' && isCreating) ||
(!isCreating && editingProfile?.voice_type === 'preset')),
});
const presetVoices = presetVoicesData?.voices ?? [];
const isSampleBasedProfile = isCreating
? voiceSource === 'clone'
: editingProfile?.voice_type !== 'preset';
const availableDefaultEngines = DEFAULT_ENGINE_OPTIONS.filter(
(option) => !isSampleBasedProfile || !PRESET_ONLY_ENGINES.has(option.value),
);
// Show recording errors
useEffect(() => {
if (recordingError) {
@@ -287,6 +326,7 @@ export function ProfileForm() {
});
setProfileEffectsChain(editingProfile.effects_chain ?? []);
setEffectsDirty(false);
setDefaultEngine(editingProfile.default_engine ?? '');
} else if (profileFormDraft && open) {
// Restore from draft when opening in create mode
form.reset({
@@ -326,6 +366,24 @@ export function ProfileForm() {
}
}, [editingProfile, profileFormDraft, open, form]);
useEffect(() => {
if (
defaultEngine &&
!availableDefaultEngines.some((option) => option.value === defaultEngine)
) {
setDefaultEngine('');
}
}, [availableDefaultEngines, defaultEngine]);
useEffect(() => {
if (!selectedPresetVoiceId) {
return;
}
if (!presetVoices.some((voice: PresetVoice) => voice.voice_id === selectedPresetVoiceId)) {
setSelectedPresetVoiceId('');
}
}, [presetVoices, selectedPresetVoiceId]);
async function handleTranscribe() {
const file = form.getValues('sampleFile');
if (!file) {
@@ -415,13 +473,14 @@ export function ProfileForm() {
async function onSubmit(data: ProfileFormValues) {
try {
if (editingProfileId) {
// Editing: just update profile
// Editing: update profile
await updateProfile.mutateAsync({
profileId: editingProfileId,
data: {
name: data.name,
description: data.description,
language: data.language,
default_engine: defaultEngine || undefined,
},
});
@@ -464,8 +523,50 @@ export function ProfileForm() {
title: 'Voice updated',
description: `"${data.name}" has been updated successfully.`,
});
} else if (voiceSource === 'builtin') {
// Creating preset profile from built-in voice
if (!selectedPresetVoiceId) {
toast({
title: 'No voice selected',
description: 'Please select a built-in voice.',
variant: 'destructive',
});
return;
}
const profile = await createProfile.mutateAsync({
name: data.name,
description: data.description,
language: data.language,
voice_type: 'preset' as VoiceType,
preset_engine: selectedPresetEngine,
preset_voice_id: selectedPresetVoiceId,
default_engine: selectedPresetEngine,
});
// Handle avatar upload if provided
if (data.avatarFile) {
try {
await uploadAvatar.mutateAsync({
profileId: profile.id,
file: data.avatarFile,
});
} catch (avatarError) {
toast({
title: 'Avatar upload failed',
description:
avatarError instanceof Error ? avatarError.message : 'Failed to upload avatar',
variant: 'destructive',
});
}
}
toast({
title: 'Profile created',
description: `"${data.name}" has been created with a built-in voice.`,
});
} else {
// Creating: require sample file and reference text
// Creating cloned profile: require sample file and reference text
const sampleFile = form.getValues('sampleFile');
const referenceText = form.getValues('referenceText');
@@ -528,6 +629,7 @@ export function ProfileForm() {
name: data.name,
description: data.description,
language: data.language,
default_engine: defaultEngine || undefined,
});
// Convert non-WAV uploads to WAV so the backend can always use soundfile.
@@ -572,12 +674,32 @@ export function ProfileForm() {
description: `"${data.name}" has been created with a sample.`,
});
} catch (sampleError) {
// Profile was created but sample failed - still show error
let rollbackSucceeded = false;
try {
await deleteProfile.mutateAsync(profile.id);
rollbackSucceeded = true;
} catch (rollbackError) {
toast({
title: 'Rollback failed',
description:
rollbackError instanceof Error
? rollbackError.message
: 'Created profile could not be removed after sample upload failure.',
variant: 'destructive',
});
}
toast({
title: 'Failed to add sample',
description: `Profile "${data.name}" was created, but failed to add sample: ${sampleError instanceof Error ? sampleError.message : 'Unknown error'}`,
description:
sampleError instanceof Error
? `${sampleError.message}${rollbackSucceeded ? ' The profile was rolled back.' : ''}`
: rollbackSucceeded
? 'Failed to add sample. The profile was rolled back.'
: 'Failed to add sample.',
variant: 'destructive',
});
return;
}
}
@@ -642,16 +764,16 @@ export function ProfileForm() {
return (
<Dialog open={open} onOpenChange={handleOpenChange}>
<DialogContent className="max-w-none w-screen h-screen left-0 top-0 translate-x-0 translate-y-0 rounded-none p-6 overflow-y-auto">
<div className="max-w-5xl max-h-[85vh] mx-auto my-auto w-full flex flex-col">
<DialogContent className="max-w-none w-screen h-screen left-0 top-0 translate-x-0 translate-y-0 rounded-none p-6 overflow-hidden">
<div className="max-w-5xl h-[85vh] mx-auto my-auto w-full flex flex-col overflow-hidden">
<DialogHeader>
<DialogTitle className="text-2xl">
{editingProfileId ? 'Edit Voice' : 'Clone voice'}
{editingProfileId ? 'Edit Voice' : 'Create Voice'}
</DialogTitle>
<DialogDescription>
{editingProfileId
? 'Update your voice profile details and manage samples.'
: 'Create a new voice profile with an audio sample to clone the voice.'}
: 'Create a new voice profile from an audio sample or a built-in voice.'}
</DialogDescription>
{isCreating && profileFormDraft && (
<div className="flex items-center gap-2 pt-2">
@@ -682,143 +804,276 @@ export function ProfileForm() {
<Form {...form}>
<form onSubmit={form.handleSubmit(onSubmit)} className="flex-1 min-h-0 flex flex-col">
<div className="grid gap-6 grid-cols-2 flex-1 overflow-y-auto min-h-0">
<div className="grid gap-6 grid-cols-2 flex-1 min-h-0 overflow-hidden">
{/* Left column: Sample management */}
<div className="space-y-4 border-r pr-6">
<div className="space-y-4 border-r pr-6 overflow-y-auto min-h-0">
{isCreating ? (
<>
<Tabs
className="pt-4"
value={sampleMode}
onValueChange={(v) => {
const newMode = v as 'upload' | 'record' | 'system';
// Cancel any active recordings when switching modes
if (isRecording && newMode !== 'record') {
cancelRecording();
}
if (isSystemRecording && newMode !== 'system') {
cancelSystemRecording();
}
setSampleMode(newMode);
}}
>
<TabsList
className={`grid w-full ${platform.metadata.isTauri && isSystemAudioSupported ? 'grid-cols-3' : 'grid-cols-2'}`}
>
<TabsTrigger value="upload" className="flex items-center gap-2">
<Upload className="h-4 w-4 shrink-0" />
Upload
</TabsTrigger>
<TabsTrigger value="record" className="flex items-center gap-2">
<Mic className="h-4 w-4 shrink-0" />
Record
</TabsTrigger>
{platform.metadata.isTauri && isSystemAudioSupported && (
<TabsTrigger value="system" className="flex items-center gap-2">
<Monitor className="h-4 w-4 shrink-0" />
System Audio
</TabsTrigger>
)}
</TabsList>
{/* Voice source selector */}
<div className="flex pt-4 pb-2">
<div className="inline-flex rounded-lg border border-border p-0.5 bg-muted/50">
<button
type="button"
onClick={() => setVoiceSource('clone')}
className={`inline-flex items-center gap-2 px-3 py-1.5 text-sm rounded-md transition-colors ${
voiceSource === 'clone'
? 'bg-accent text-accent-foreground shadow-sm'
: 'text-muted-foreground hover:text-foreground'
}`}
>
<Mic className="h-3.5 w-3.5" />
Clone from audio
</button>
<button
type="button"
onClick={() => setVoiceSource('builtin')}
className={`inline-flex items-center gap-2 px-3 py-1.5 text-sm rounded-md transition-colors ${
voiceSource === 'builtin'
? 'bg-accent text-accent-foreground shadow-sm'
: 'text-muted-foreground hover:text-foreground'
}`}
>
<Music className="h-3.5 w-3.5" />
Built-in voice
</button>
</div>
</div>
<TabsContent value="upload" className="space-y-4">
<FormField
control={form.control}
name="sampleFile"
render={({ field: { onChange, name } }) => (
<AudioSampleUpload
file={selectedFile}
onFileChange={onChange}
onTranscribe={handleTranscribe}
onPlayPause={handlePlayPause}
isPlaying={isPlaying}
isValidating={isValidatingAudio}
isTranscribing={transcribe.isPending}
isDisabled={
audioDuration !== null &&
audioDuration > MAX_AUDIO_DURATION_SECONDS
}
fieldName={name}
/>
)}
/>
</TabsContent>
{voiceSource === 'builtin' ? (
<div className="space-y-4">
<FormDescription>
Choose a pre-built voice. These don't require an audio sample.
</FormDescription>
<TabsContent value="record" className="space-y-4">
<FormField
control={form.control}
name="sampleFile"
render={() => (
<AudioSampleRecording
file={selectedFile}
isRecording={isRecording}
duration={duration}
onStart={startRecording}
onStop={stopRecording}
onCancel={handleCancelRecording}
onTranscribe={handleTranscribe}
onPlayPause={handlePlayPause}
isPlaying={isPlaying}
isTranscribing={transcribe.isPending}
/>
)}
/>
</TabsContent>
{platform.metadata.isTauri && isSystemAudioSupported && (
<TabsContent value="system" className="space-y-4">
<FormField
control={form.control}
name="sampleFile"
render={() => (
<AudioSampleSystem
file={selectedFile}
isRecording={isSystemRecording}
duration={systemDuration}
onStart={startSystemRecording}
onStop={stopSystemRecording}
onCancel={handleCancelRecording}
onTranscribe={handleTranscribe}
onPlayPause={handlePlayPause}
isPlaying={isPlaying}
isTranscribing={transcribe.isPending}
/>
)}
/>
</TabsContent>
)}
</Tabs>
<FormField
control={form.control}
name="referenceText"
render={({ field }) => (
{/* Engine selector */}
<FormItem>
<FormLabel>Reference Text</FormLabel>
<FormControl>
<Textarea
placeholder="Enter the exact text spoken in the audio..."
className="min-h-[100px]"
{...field}
/>
</FormControl>
<FormMessage />
<FormLabel>Engine</FormLabel>
<Select
value={selectedPresetEngine}
onValueChange={setSelectedPresetEngine}
>
<FormControl>
<SelectTrigger>
<SelectValue />
</SelectTrigger>
</FormControl>
<SelectContent>
<SelectItem value="kokoro">Kokoro 82M</SelectItem>
<SelectItem value="qwen_custom_voice">Qwen CustomVoice</SelectItem>
</SelectContent>
</Select>
</FormItem>
)}
/>
{/* Voice picker */}
<FormItem>
<FormLabel>Voice</FormLabel>
<div className="grid grid-cols-2 gap-1.5 max-h-[340px] overflow-y-auto pr-1">
{presetVoices.map((voice: PresetVoice) => (
<button
key={voice.voice_id}
type="button"
onClick={() => {
setSelectedPresetVoiceId(voice.voice_id);
// Auto-set language from voice
if (voice.language) {
form.setValue('language', voice.language as LanguageCode);
}
}}
className={`text-left px-3 py-2 rounded-md border text-sm transition-colors ${
selectedPresetVoiceId === voice.voice_id
? 'border-accent bg-accent/10 text-accent-foreground'
: 'border-border hover:bg-muted'
}`}
>
<div className="font-medium">{voice.name}</div>
<div className="flex gap-1.5 mt-0.5">
<Badge variant="outline" className="text-[10px] h-4 px-1">
{voice.gender}
</Badge>
<Badge variant="outline" className="text-[10px] h-4 px-1">
{voice.language}
</Badge>
</div>
</button>
))}
</div>
</FormItem>
</div>
) : (
<>
<Tabs
className="pt-0"
value={sampleMode}
onValueChange={(v) => {
const newMode = v as 'upload' | 'record' | 'system';
// Cancel any active recordings when switching modes
if (isRecording && newMode !== 'record') {
cancelRecording();
}
if (isSystemRecording && newMode !== 'system') {
cancelSystemRecording();
}
setSampleMode(newMode);
}}
>
<TabsList
className={`grid w-full ${platform.metadata.isTauri && isSystemAudioSupported ? 'grid-cols-3' : 'grid-cols-2'}`}
>
<TabsTrigger value="upload" className="flex items-center gap-2">
<Upload className="h-4 w-4 shrink-0" />
Upload
</TabsTrigger>
<TabsTrigger value="record" className="flex items-center gap-2">
<Mic className="h-4 w-4 shrink-0" />
Record
</TabsTrigger>
{platform.metadata.isTauri && isSystemAudioSupported && (
<TabsTrigger value="system" className="flex items-center gap-2">
<Monitor className="h-4 w-4 shrink-0" />
System Audio
</TabsTrigger>
)}
</TabsList>
<TabsContent value="upload" className="space-y-4">
<FormField
control={form.control}
name="sampleFile"
render={({ field: { onChange, name } }) => (
<AudioSampleUpload
file={selectedFile}
onFileChange={onChange}
onTranscribe={handleTranscribe}
onPlayPause={handlePlayPause}
isPlaying={isPlaying}
isValidating={isValidatingAudio}
isTranscribing={transcribe.isPending}
isDisabled={
audioDuration !== null &&
audioDuration > MAX_AUDIO_DURATION_SECONDS
}
fieldName={name}
/>
)}
/>
</TabsContent>
<TabsContent value="record" className="space-y-4">
<FormField
control={form.control}
name="sampleFile"
render={() => (
<AudioSampleRecording
file={selectedFile}
isRecording={isRecording}
duration={duration}
onStart={startRecording}
onStop={stopRecording}
onCancel={handleCancelRecording}
onTranscribe={handleTranscribe}
onPlayPause={handlePlayPause}
isPlaying={isPlaying}
isTranscribing={transcribe.isPending}
/>
)}
/>
</TabsContent>
{platform.metadata.isTauri && isSystemAudioSupported && (
<TabsContent value="system" className="space-y-4">
<FormField
control={form.control}
name="sampleFile"
render={() => (
<AudioSampleSystem
file={selectedFile}
isRecording={isSystemRecording}
duration={systemDuration}
onStart={startSystemRecording}
onStop={stopSystemRecording}
onCancel={handleCancelRecording}
onTranscribe={handleTranscribe}
onPlayPause={handlePlayPause}
isPlaying={isPlaying}
isTranscribing={transcribe.isPending}
/>
)}
/>
</TabsContent>
)}
</Tabs>
<FormField
control={form.control}
name="referenceText"
render={({ field }) => (
<FormItem>
<FormLabel>Reference Text</FormLabel>
<FormControl>
<Textarea
placeholder="Enter the exact text spoken in the audio..."
className="min-h-[100px]"
{...field}
/>
</FormControl>
<FormMessage />
</FormItem>
)}
/>
</>
)}
</>
) : (
// Show sample list when editing
editingProfileId && (
// Editing mode
editingProfileId &&
editingProfile &&
(editingProfile.voice_type === 'preset' ? (
<div className="space-y-4 pt-4">
<div className="rounded-lg border border-border p-4 space-y-3">
<div className="text-sm font-medium text-muted-foreground">
Built-in Voice
</div>
<div className="flex items-center gap-3">
<div className="text-lg font-semibold">
{presetVoices.find(
(v: PresetVoice) => v.voice_id === editingProfile.preset_voice_id,
)?.name ?? editingProfile.preset_voice_id}
</div>
<Badge variant="secondary" className="text-xs">
{editingProfile.preset_engine}
</Badge>
</div>
{(() => {
const voice = presetVoices.find(
(v: PresetVoice) => v.voice_id === editingProfile.preset_voice_id,
);
return voice ? (
<div className="flex gap-1.5">
<Badge variant="outline" className="text-xs">
{voice.gender}
</Badge>
<Badge variant="outline" className="text-xs">
{voice.language}
</Badge>
</div>
) : null;
})()}
</div>
<p className="text-xs text-muted-foreground">
This profile uses a built-in voice. The voice cannot be changed after
creation.
</p>
</div>
) : (
<div>
<SampleList profileId={editingProfileId} />
</div>
)
))
)}
</div>
{/* Right column: Profile info */}
<div className="space-y-4">
<div className="space-y-4 overflow-y-auto min-h-0">
{/* Avatar Upload */}
<FormField
control={form.control}
@@ -924,6 +1179,36 @@ export function ProfileForm() {
)}
/>
<FormItem>
<FormLabel>Default Engine</FormLabel>
<Select
value={defaultEngine || '_none'}
onValueChange={(v) => {
setDefaultEngine(v === '_none' ? '' : v);
}}
disabled={
voiceSource === 'builtin' || editingProfile?.voice_type === 'preset'
}
>
<FormControl>
<SelectTrigger>
<SelectValue placeholder="No preference" />
</SelectTrigger>
</FormControl>
<SelectContent>
<SelectItem value="_none">No preference</SelectItem>
{availableDefaultEngines.map((option) => (
<SelectItem key={option.value} value={option.value}>
{option.label}
</SelectItem>
))}
</SelectContent>
</Select>
<p className="text-xs text-muted-foreground">
Auto-selects this engine when the profile is chosen.
</p>
</FormItem>
{editingProfileId && (
<div className="space-y-2">
<FormLabel>Default Effects</FormLabel>
@@ -1,4 +1,5 @@
import { Mic, Sparkles } from 'lucide-react';
import { Info, Mic, Sparkles } from 'lucide-react';
import { useEffect, useRef } from 'react';
import { Button } from '@/components/ui/button';
import { Card, CardContent } from '@/components/ui/card';
import { useProfiles } from '@/lib/hooks/useProfiles';
@@ -6,9 +7,36 @@ import { useUIStore } from '@/stores/uiStore';
import { ProfileCard } from './ProfileCard';
import { ProfileForm } from './ProfileForm';
/** Engines that use preset (built-in) voices instead of cloned profiles. */
const PRESET_ENGINES = new Set(['kokoro', 'qwen_custom_voice']);
export function ProfileList() {
const { data: profiles, isLoading, error } = useProfiles();
const setDialogOpen = useUIStore((state) => state.setProfileDialogOpen);
const selectedEngine = useUIStore((state) => state.selectedEngine);
const selectedProfileId = useUIStore((state) => state.selectedProfileId);
const cardRefs = useRef<Map<string, HTMLDivElement>>(new Map());
// Scroll to the selected profile after engine/sort changes
useEffect(() => {
if (!selectedProfileId) return;
let timeoutId: ReturnType<typeof setTimeout> | null = null;
const rafId = requestAnimationFrame(() => {
const el = cardRefs.current.get(selectedProfileId);
if (!el) return;
// Temporarily apply scroll-margin so it doesn't land flush at the top
el.style.scrollMarginTop = '180px';
el.scrollIntoView({ behavior: 'smooth', block: 'nearest', inline: 'nearest' });
timeoutId = setTimeout(() => {
el.style.scrollMarginTop = '';
}, 500);
});
return () => {
cancelAnimationFrame(rafId);
if (timeoutId) clearTimeout(timeoutId);
};
}, [selectedProfileId, selectedEngine]);
if (isLoading) {
return null;
@@ -23,6 +51,20 @@ export function ProfileList() {
}
const allProfiles = profiles || [];
const isPresetEngine = PRESET_ENGINES.has(selectedEngine);
/** Whether a profile is supported by the currently selected engine. */
const isSupported = (p: (typeof allProfiles)[number]) =>
isPresetEngine
? p.voice_type === 'preset' && p.preset_engine === selectedEngine
: p.voice_type !== 'preset';
// Sort so supported profiles come first
const sortedProfiles = [...allProfiles].sort(
(a, b) => (isSupported(a) ? 0 : 1) - (isSupported(b) ? 0 : 1),
);
const hasUnsupported = sortedProfiles.some((p) => !isSupported(p));
return (
<div className="flex flex-col">
@@ -42,11 +84,24 @@ export function ProfileList() {
</Card>
) : (
<div className="flex gap-4 overflow-x-auto p-1 pb-1 lg:grid lg:grid-cols-3 lg:auto-rows-auto lg:overflow-x-visible lg:pb-[150px]">
{allProfiles.map((profile) => (
<div key={profile.id} className="shrink-0 w-[200px] lg:w-auto lg:shrink">
<ProfileCard profile={profile} />
{sortedProfiles.map((profile) => (
<div
key={profile.id}
className="shrink-0 w-[200px] lg:w-auto lg:shrink"
ref={(el) => {
if (el) cardRefs.current.set(profile.id, el);
else cardRefs.current.delete(profile.id);
}}
>
<ProfileCard profile={profile} disabled={!isSupported(profile)} />
</div>
))}
{hasUnsupported && (
<div className="col-span-full flex items-center gap-2 text-xs text-muted-foreground py-2">
<Info className="h-3.5 w-3.5 shrink-0" />
<span>Only supported voice profiles can be selected for the current model.</span>
</div>
)}
</div>
)}
</div>
+1 -1
View File
@@ -111,4 +111,4 @@ export {
AlertDialogDescription,
AlertDialogAction,
AlertDialogCancel,
};
};
+11
View File
@@ -17,6 +17,7 @@ import type {
HistoryResponse,
ModelDownloadRequest,
ModelStatusListResponse,
PresetVoice,
ProfileSampleResponse,
StoryCreate,
StoryDetailResponse,
@@ -97,6 +98,10 @@ class ApiClient {
return this.request<VoiceProfileResponse>(`/profiles/${profileId}`);
}
async listPresetVoices(engine: string): Promise<{ engine: string; voices: PresetVoice[] }> {
return this.request<{ engine: string; voices: PresetVoice[] }>(`/profiles/presets/${engine}`);
}
async updateProfile(profileId: string, data: VoiceProfileCreate): Promise<VoiceProfileResponse> {
return this.request<VoiceProfileResponse>(`/profiles/${profileId}`, {
method: 'PUT',
@@ -265,6 +270,12 @@ class ApiClient {
});
}
async clearFailedGenerations(): Promise<{ deleted: number }> {
return this.request<{ deleted: number }>(`/history/failed`, {
method: 'DELETE',
});
}
async exportGeneration(generationId: string): Promise<Blob> {
const url = `${this.getBaseUrl()}/history/${generationId}/export`;
const response = await fetch(url);
+27 -1
View File
@@ -1,10 +1,17 @@
// API Types matching backend Pydantic models
import type { LanguageCode } from '@/lib/constants/languages';
export type VoiceType = 'cloned' | 'preset' | 'designed';
export interface VoiceProfileCreate {
name: string;
description?: string;
language: LanguageCode;
voice_type?: VoiceType;
preset_engine?: string;
preset_voice_id?: string;
design_prompt?: string;
default_engine?: string;
}
export interface VoiceProfileResponse {
@@ -14,12 +21,24 @@ export interface VoiceProfileResponse {
language: string;
avatar_path?: string;
effects_chain?: EffectConfig[];
voice_type: VoiceType;
preset_engine?: string;
preset_voice_id?: string;
design_prompt?: string;
default_engine?: string;
generation_count: number;
sample_count: number;
created_at: string;
updated_at: string;
}
export interface PresetVoice {
voice_id: string;
name: string;
gender: 'male' | 'female';
language: string;
}
export interface ProfileSampleCreate {
reference_text: string;
}
@@ -43,7 +62,14 @@ export interface GenerationRequest {
language: LanguageCode;
seed?: number;
model_size?: '1.7B' | '0.6B' | '1B' | '3B';
engine?: 'qwen' | 'luxtts' | 'chatterbox' | 'chatterbox_turbo' | 'tada';
engine?:
| 'qwen'
| 'qwen_custom_voice'
| 'luxtts'
| 'chatterbox'
| 'chatterbox_turbo'
| 'tada'
| 'kokoro';
instruct?: string;
max_chunk_chars?: number;
crossfade_ms?: number;
+3
View File
@@ -5,6 +5,7 @@
* LuxTTS is English-only.
* Chatterbox Multilingual supports 23 languages.
* Chatterbox Turbo is English-only.
* Kokoro supports 8 languages.
*/
/** All languages that any engine supports. */
@@ -67,6 +68,8 @@ export const ENGINE_LANGUAGES: Record<string, readonly LanguageCode[]> = {
],
chatterbox_turbo: ['en'],
tada: ['en', 'ar', 'zh', 'de', 'es', 'fr', 'it', 'ja', 'pl', 'pt'],
kokoro: ['en', 'es', 'fr', 'hi', 'it', 'pt', 'ja', 'zh'],
qwen_custom_voice: ['zh', 'en', 'ja', 'ko', 'de', 'fr', 'ru', 'pt', 'es', 'it'],
} as const;
/** Helper: get language options for a given engine. */
+34 -8
View File
@@ -10,6 +10,7 @@ import { useGeneration } from '@/lib/hooks/useGeneration';
import { useModelDownloadToast } from '@/lib/hooks/useModelDownloadToast';
import { useGenerationStore } from '@/stores/generationStore';
import { useServerStore } from '@/stores/serverStore';
import { useUIStore } from '@/stores/uiStore';
const generationSchema = z.object({
text: z.string().min(1, '').max(50000),
@@ -17,7 +18,17 @@ const generationSchema = z.object({
seed: z.number().int().optional(),
modelSize: z.enum(['1.7B', '0.6B', '1B', '3B']).optional(),
instruct: z.string().max(500).optional(),
engine: z.enum(['qwen', 'luxtts', 'chatterbox', 'chatterbox_turbo', 'tada']).optional(),
engine: z
.enum([
'qwen',
'qwen_custom_voice',
'luxtts',
'chatterbox',
'chatterbox_turbo',
'tada',
'kokoro',
])
.optional(),
});
export type GenerationFormValues = z.infer<typeof generationSchema>;
@@ -35,6 +46,7 @@ export function useGenerationForm(options: UseGenerationFormOptions = {}) {
const maxChunkChars = useServerStore((state) => state.maxChunkChars);
const crossfadeMs = useServerStore((state) => state.crossfadeMs);
const normalizeAudio = useServerStore((state) => state.normalizeAudio);
const selectedEngine = useUIStore((state) => state.selectedEngine);
const [downloadingModelName, setDownloadingModelName] = useState<string | null>(null);
const [downloadingDisplayName, setDownloadingDisplayName] = useState<string | null>(null);
@@ -52,7 +64,7 @@ export function useGenerationForm(options: UseGenerationFormOptions = {}) {
seed: undefined,
modelSize: '1.7B',
instruct: '',
engine: 'qwen',
engine: (selectedEngine as GenerationFormValues['engine']) || 'qwen',
...options.defaultValues,
},
});
@@ -83,7 +95,11 @@ export function useGenerationForm(options: UseGenerationFormOptions = {}) {
? data.modelSize === '3B'
? 'tada-3b-ml'
: 'tada-1b'
: `qwen-tts-${data.modelSize}`;
: engine === 'kokoro'
? 'kokoro'
: engine === 'qwen_custom_voice'
? `qwen-custom-voice-${data.modelSize}`
: `qwen-tts-${data.modelSize}`;
const displayName =
engine === 'luxtts'
? 'LuxTTS'
@@ -95,9 +111,15 @@ export function useGenerationForm(options: UseGenerationFormOptions = {}) {
? data.modelSize === '3B'
? 'TADA 3B Multilingual'
: 'TADA 1B'
: data.modelSize === '1.7B'
? 'Qwen TTS 1.7B'
: 'Qwen TTS 0.6B';
: engine === 'kokoro'
? 'Kokoro 82M'
: engine === 'qwen_custom_voice'
? data.modelSize === '1.7B'
? 'Qwen CustomVoice 1.7B'
: 'Qwen CustomVoice 0.6B'
: data.modelSize === '1.7B'
? 'Qwen TTS 1.7B'
: 'Qwen TTS 0.6B';
// Check if model needs downloading
try {
@@ -112,7 +134,11 @@ export function useGenerationForm(options: UseGenerationFormOptions = {}) {
console.error('Failed to check model status:', error);
}
const hasModelSizes = engine === 'qwen' || engine === 'tada';
const hasModelSizes =
engine === 'qwen' || engine === 'qwen_custom_voice' || engine === 'tada';
// Only Qwen CustomVoice actually honors the instruct kwarg at model level.
// Base Qwen3-TTS accepts the kwarg but ignores it.
const supportsInstruct = engine === 'qwen_custom_voice';
const effectsChain = options.getEffectsChain?.();
// This now returns immediately with status="generating"
const result = await generation.mutateAsync({
@@ -122,7 +148,7 @@ export function useGenerationForm(options: UseGenerationFormOptions = {}) {
seed: data.seed,
model_size: hasModelSizes ? data.modelSize : undefined,
engine,
instruct: engine === 'qwen' ? data.instruct || undefined : undefined,
instruct: supportsInstruct ? data.instruct || undefined : undefined,
max_chunk_chars: maxChunkChars,
crossfade_ms: crossfadeMs,
normalize: normalizeAudio,
+11
View File
@@ -29,6 +29,17 @@ export function useDeleteGeneration() {
});
}
export function useClearFailedGenerations() {
const queryClient = useQueryClient();
return useMutation({
mutationFn: () => apiClient.clearFailedGenerations(),
onSuccess: () => {
queryClient.invalidateQueries({ queryKey: ['history'] });
},
});
}
export function useExportGeneration() {
const platform = usePlatform();
+2 -1
View File
@@ -131,7 +131,8 @@ export function useModelDownloadToast({
)}
</div>
),
duration: progress.status === 'complete' || progress.status === 'error' ? 5000 : Infinity,
duration:
progress.status === 'complete' || progress.status === 'error' ? 5000 : Infinity,
});
// Close connection and dismiss toast on completion or error
+18 -2
View File
@@ -26,8 +26,24 @@ export function useSystemAudioCapture({
// Check if system audio capture is supported
useEffect(() => {
const supported = platform.audio.isSystemAudioSupported();
setIsSupported(supported);
let isActive = true;
void platform.audio
.isSystemAudioSupported()
.then((supported) => {
if (isActive) {
setIsSupported(supported);
}
})
.catch(() => {
if (isActive) {
setIsSupported(false);
}
});
return () => {
isActive = false;
};
}, [platform]);
const startRecording = useCallback(async () => {
+19
View File
@@ -0,0 +1,19 @@
import { QueryClient } from '@tanstack/react-query';
/**
* Shared QueryClient instance used across the app.
*
* Extracted into its own side-effect-free module so it can be imported from
* both the React bootstrap (main.tsx) and non-React code (stores, utilities)
* without pulling in ReactDOM or other bootstrap side effects.
*/
export const queryClient = new QueryClient({
defaultOptions: {
queries: {
staleTime: 1000 * 60 * 5, // 5 minutes
gcTime: 1000 * 60 * 10, // 10 minutes (formerly cacheTime)
retry: 1,
refetchOnWindowFocus: false,
},
},
});
+2 -12
View File
@@ -1,20 +1,10 @@
import { QueryClient, QueryClientProvider } from '@tanstack/react-query';
import { QueryClientProvider } from '@tanstack/react-query';
// import { ReactQueryDevtools } from '@tanstack/react-query-devtools';
import React from 'react';
import ReactDOM from 'react-dom/client';
import App from './App';
import './index.css';
const queryClient = new QueryClient({
defaultOptions: {
queries: {
staleTime: 1000 * 60 * 5, // 5 minutes
gcTime: 1000 * 60 * 10, // 10 minutes (formerly cacheTime)
retry: 1,
refetchOnWindowFocus: false,
},
},
});
import { queryClient } from './lib/queryClient';
ReactDOM.createRoot(document.getElementById('root')!).render(
<React.StrictMode>
+1 -5
View File
@@ -9,11 +9,7 @@ export interface PlatformProviderProps {
}
export function PlatformProvider({ platform, children }: PlatformProviderProps) {
return (
<PlatformContext.Provider value={platform}>
{children}
</PlatformContext.Provider>
);
return <PlatformContext.Provider value={platform}>{children}</PlatformContext.Provider>;
}
export function usePlatform(): Platform {
+1 -1
View File
@@ -42,7 +42,7 @@ export interface AudioDevice {
}
export interface PlatformAudio {
isSystemAudioSupported(): boolean;
isSystemAudioSupported(): Promise<boolean>;
startSystemAudioCapture(maxDurationSecs: number): Promise<void>;
stopSystemAudioCapture(): Promise<Blob>;
listOutputDevices(): Promise<AudioDevice[]>;
+17 -2
View File
@@ -1,5 +1,6 @@
import { create } from 'zustand';
import { persist } from 'zustand/middleware';
import { queryClient } from '@/lib/queryClient';
interface ServerStore {
serverUrl: string;
@@ -30,11 +31,25 @@ interface ServerStore {
setCustomModelsDir: (dir: string | null) => void;
}
/**
* Invalidate all React Query caches so stale data from the previous
* server is not shown. Called when the server URL changes.
*/
function invalidateAllServerData() {
queryClient.invalidateQueries();
}
export const useServerStore = create<ServerStore>()(
persist(
(set) => ({
(set, get) => ({
serverUrl: 'http://127.0.0.1:17493',
setServerUrl: (url) => set({ serverUrl: url }),
setServerUrl: (url) => {
const prev = get().serverUrl;
set({ serverUrl: url });
if (url !== prev) {
invalidateAllServerData();
}
},
isConnected: false,
setIsConnected: (connected) => set({ isConnected: connected }),
+7
View File
@@ -31,6 +31,10 @@ interface UIStore {
selectedProfileId: string | null;
setSelectedProfileId: (id: string | null) => void;
// Currently selected engine (synced from generation form)
selectedEngine: string;
setSelectedEngine: (engine: string) => void;
// Selected voice in Voices tab inspector
selectedVoiceId: string | null;
setSelectedVoiceId: (id: string | null) => void;
@@ -59,6 +63,9 @@ export const useUIStore = create<UIStore>((set) => ({
selectedProfileId: null,
setSelectedProfileId: (id) => set({ selectedProfileId: id }),
selectedEngine: 'qwen',
setSelectedEngine: (engine) => set({ selectedEngine: engine }),
selectedVoiceId: null,
setSelectedVoiceId: (id) => set({ selectedVoiceId: id }),
+1 -1
View File
@@ -1,3 +1,3 @@
# Backend package
__version__ = "0.3.1"
__version__ = "0.4.0"
+31 -3
View File
@@ -135,7 +135,7 @@ def _mount_frontend(application: FastAPI) -> None:
async def serve_spa(full_path: str):
file_path = (frontend_dir / full_path).resolve()
# Guard against path traversal — only serve files inside frontend_dir
if full_path and file_path.is_file() and str(file_path).startswith(str(frontend_dir)):
if full_path and file_path.is_file() and file_path.is_relative_to(frontend_dir):
return FileResponse(file_path)
return FileResponse(frontend_dir / "index.html", media_type="text/html")
@@ -146,15 +146,36 @@ def _get_gpu_status() -> str:
"""Return a human-readable string describing GPU availability."""
backend_type = get_backend_type()
if torch.cuda.is_available():
from .backends.base import check_cuda_compatibility
device_name = torch.cuda.get_device_name(0)
compatible, _warning = check_cuda_compatibility()
is_rocm = hasattr(torch.version, "hip") and torch.version.hip is not None
if is_rocm:
return f"ROCm ({device_name})"
return f"CUDA ({device_name})"
label = f"ROCm ({device_name})"
else:
label = f"CUDA ({device_name})"
if not compatible:
label += " [UNSUPPORTED - see logs]"
return label
elif hasattr(torch.backends, "mps") and torch.backends.mps.is_available():
return "MPS (Apple Silicon)"
elif backend_type == "mlx":
return "Metal (Apple Silicon via MLX)"
# Intel XPU (Arc / Data Center) via IPEX
try:
import intel_extension_for_pytorch # noqa: F401
if hasattr(torch, "xpu") and torch.xpu.is_available():
try:
xpu_name = torch.xpu.get_device_name(0)
except Exception:
xpu_name = "Intel GPU"
return f"XPU ({xpu_name})"
except ImportError:
pass
return "None (CPU only)"
@@ -216,6 +237,13 @@ def _register_lifecycle(application: FastAPI) -> None:
logger.info("Backend: %s", backend_type.upper())
logger.info("GPU: %s", _get_gpu_status())
# Warn if GPU architecture is not supported by this PyTorch build
from .backends.base import check_cuda_compatibility
_compatible, _cuda_warning = check_cuda_compatibility()
if not _compatible:
logger.warning("GPU COMPATIBILITY: %s", _cuda_warning)
from .services.cuda import check_and_update_cuda_binary
create_background_task(check_and_update_cuda_binary())
+64 -4
View File
@@ -163,10 +163,12 @@ _stt_backend: Optional[STTBackend] = None
# The factory function uses this for the if/elif chain; the model configs live on the backend classes.
TTS_ENGINES = {
"qwen": "Qwen TTS",
"qwen_custom_voice": "Qwen CustomVoice",
"luxtts": "LuxTTS",
"chatterbox": "Chatterbox TTS",
"chatterbox_turbo": "Chatterbox Turbo",
"tada": "TADA",
"kokoro": "Kokoro",
}
@@ -204,6 +206,32 @@ def _get_qwen_model_configs() -> list[ModelConfig]:
]
def _get_qwen_custom_voice_configs() -> list[ModelConfig]:
"""Return Qwen CustomVoice model configs."""
return [
ModelConfig(
model_name="qwen-custom-voice-1.7B",
display_name="Qwen CustomVoice 1.7B",
engine="qwen_custom_voice",
hf_repo_id="Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice",
model_size="1.7B",
size_mb=3500,
supports_instruct=True,
languages=["zh", "en", "ja", "ko", "de", "fr", "ru", "pt", "es", "it"],
),
ModelConfig(
model_name="qwen-custom-voice-0.6B",
display_name="Qwen CustomVoice 0.6B",
engine="qwen_custom_voice",
hf_repo_id="Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice",
model_size="0.6B",
size_mb=1200,
supports_instruct=True,
languages=["zh", "en", "ja", "ko", "de", "fr", "ru", "pt", "es", "it"],
),
]
def _get_non_qwen_tts_configs() -> list[ModelConfig]:
"""Return model configs for non-Qwen TTS engines.
@@ -278,6 +306,14 @@ def _get_non_qwen_tts_configs() -> list[ModelConfig]:
size_mb=8000,
languages=["en", "ar", "zh", "de", "es", "fr", "it", "ja", "pl", "pt"],
),
ModelConfig(
model_name="kokoro",
display_name="Kokoro 82M",
engine="kokoro",
hf_repo_id="hexgrad/Kokoro-82M",
size_mb=350,
languages=["en", "es", "fr", "hi", "it", "pt", "ja", "zh"],
),
]
@@ -324,12 +360,12 @@ def _get_whisper_configs() -> list[ModelConfig]:
def get_all_model_configs() -> list[ModelConfig]:
"""Return the full list of model configs (TTS + STT)."""
return _get_qwen_model_configs() + _get_non_qwen_tts_configs() + _get_whisper_configs()
return _get_qwen_model_configs() + _get_qwen_custom_voice_configs() + _get_non_qwen_tts_configs() + _get_whisper_configs()
def get_tts_model_configs() -> list[ModelConfig]:
"""Return only TTS model configs."""
return _get_qwen_model_configs() + _get_non_qwen_tts_configs()
return _get_qwen_model_configs() + _get_qwen_custom_voice_configs() + _get_non_qwen_tts_configs()
# Lookup helpers — these replace the if/elif chains in main.py
@@ -360,7 +396,7 @@ def engine_has_model_sizes(engine: str) -> bool:
async def load_engine_model(engine: str, model_size: str = "default") -> None:
"""Load a model for the given engine, handling engines with multiple model sizes."""
backend = get_tts_backend_for_engine(engine)
if engine == "qwen":
if engine in ("qwen", "qwen_custom_voice"):
await backend.load_model_async(model_size)
elif engine == "tada":
await backend.load_model(model_size)
@@ -379,7 +415,7 @@ async def ensure_model_cached_or_raise(engine: str, model_size: str = "default")
cfg = c
break
if engine in ("qwen", "tada"):
if engine in ("qwen", "qwen_custom_voice", "tada"):
if not backend._is_model_cached(model_size):
raise HTTPException(
status_code=400,
@@ -414,6 +450,14 @@ def unload_model_by_config(config: ModelConfig) -> bool:
return True
return False
if config.engine == "qwen_custom_voice":
backend = get_tts_backend_for_engine(config.engine)
loaded_size = getattr(backend, "_current_model_size", None) or getattr(backend, "model_size", None)
if backend.is_loaded() and loaded_size == config.model_size:
backend.unload_model()
return True
return False
# All other TTS engines
backend = get_tts_backend_for_engine(config.engine)
if backend.is_loaded():
@@ -437,6 +481,11 @@ def check_model_loaded(config: ModelConfig) -> bool:
loaded_size = getattr(tts_model, "_current_model_size", None) or getattr(tts_model, "model_size", None)
return tts_model.is_loaded() and loaded_size == config.model_size
if config.engine == "qwen_custom_voice":
backend = get_tts_backend_for_engine(config.engine)
loaded_size = getattr(backend, "_current_model_size", None) or getattr(backend, "model_size", None)
return backend.is_loaded() and loaded_size == config.model_size
backend = get_tts_backend_for_engine(config.engine)
return backend.is_loaded()
except Exception:
@@ -454,6 +503,9 @@ def get_model_load_func(config: ModelConfig):
if config.engine == "qwen":
return lambda: tts.get_tts_model().load_model(config.model_size)
if config.engine == "qwen_custom_voice":
return lambda: get_tts_backend_for_engine(config.engine).load_model(config.model_size)
return lambda: get_tts_backend_for_engine(config.engine).load_model()
@@ -515,6 +567,14 @@ def get_tts_backend_for_engine(engine: str) -> TTSBackend:
from .hume_backend import HumeTadaBackend
backend = HumeTadaBackend()
elif engine == "kokoro":
from .kokoro_backend import KokoroTTSBackend
backend = KokoroTTSBackend()
elif engine == "qwen_custom_voice":
from .qwen_custom_voice_backend import QwenCustomVoiceBackend
backend = QwenCustomVoiceBackend()
else:
raise ValueError(f"Unknown TTS engine: {engine}. Supported: {list(TTS_ENGINES.keys())}")
+69
View File
@@ -126,6 +126,75 @@ def get_torch_device(
return "cpu"
def check_cuda_compatibility() -> tuple[bool, str | None]:
"""Check if the installed PyTorch supports the current GPU's compute capability.
Returns:
(compatible, warning_message) — compatible is True if OK or no CUDA GPU,
warning_message is a human-readable string if there's a problem.
"""
import torch
if not torch.cuda.is_available():
return True, None
major, minor = torch.cuda.get_device_capability(0)
capability = f"{major}.{minor}"
device_name = torch.cuda.get_device_name(0)
sm_tag = f"sm_{major}{minor}"
# torch.cuda._get_arch_list() returns the SM architectures this build
# was compiled for (e.g. ["sm_50", "sm_60", ..., "sm_90"]).
try:
arch_list = torch.cuda._get_arch_list()
if arch_list:
# Check for both sm_XX and compute_XX (JIT-compiled) entries
compute_tag = f"compute_{major}{minor}"
if sm_tag not in arch_list and compute_tag not in arch_list:
return False, (
f"{device_name} (compute capability {capability} / {sm_tag}) "
f"is not supported by this PyTorch build. "
f"Supported architectures: {', '.join(arch_list)}. "
f"Install PyTorch nightly (cu128) for newer GPU support: "
f"pip install torch --index-url https://download.pytorch.org/whl/nightly/cu128"
)
except AttributeError:
pass
return True, None
def empty_device_cache(device: str) -> None:
"""
Free cached memory on the given device (CUDA or XPU).
Backends should call this after unloading models so VRAM is returned
to the OS.
"""
import torch
if device == "cuda" and torch.cuda.is_available():
torch.cuda.empty_cache()
elif device == "xpu" and hasattr(torch, "xpu"):
torch.xpu.empty_cache()
def manual_seed(seed: int, device: str) -> None:
"""
Set the random seed on both CPU and the active accelerator.
Covers CUDA and Intel XPU so that generation is reproducible
regardless of which GPU backend is in use.
"""
import torch
torch.manual_seed(seed)
if device == "cuda" and torch.cuda.is_available():
torch.cuda.manual_seed(seed)
elif device == "xpu" and hasattr(torch, "xpu"):
torch.xpu.manual_seed(seed)
async def combine_voice_prompts(
audio_paths: List[str],
reference_texts: List[str],
+6 -10
View File
@@ -18,6 +18,8 @@ from . import TTSBackend
from .base import (
is_model_cached,
get_torch_device,
empty_device_cache,
manual_seed,
combine_voice_prompts as _combine_voice_prompts,
model_load_progress,
patch_chatterbox_f32,
@@ -48,7 +50,7 @@ class ChatterboxTTSBackend:
self._model_load_lock = asyncio.Lock()
def _get_device(self) -> str:
return get_torch_device(force_cpu_on_mac=True)
return get_torch_device(force_cpu_on_mac=True, allow_xpu=True)
def is_loaded(self) -> bool:
return self.model is not None
@@ -117,10 +119,7 @@ class ChatterboxTTSBackend:
del self.model
self.model = None
self._device = None
if device == "cuda":
import torch
torch.cuda.empty_cache()
empty_device_cache(device)
logger.info("Chatterbox unloaded")
async def create_voice_prompt(
@@ -200,7 +199,7 @@ class ChatterboxTTSBackend:
import torch
if seed is not None:
torch.manual_seed(seed)
manual_seed(seed, self._device)
logger.info(f"[Chatterbox] Generating: lang={language}")
@@ -220,10 +219,7 @@ class ChatterboxTTSBackend:
else:
audio = np.asarray(wav, dtype=np.float32)
sample_rate = (
getattr(self.model, "sr", None)
or getattr(self.model, "sample_rate", 24000)
)
sample_rate = getattr(self.model, "sr", None) or getattr(self.model, "sample_rate", 24000)
return audio, sample_rate
+6 -10
View File
@@ -18,6 +18,8 @@ from . import TTSBackend
from .base import (
is_model_cached,
get_torch_device,
empty_device_cache,
manual_seed,
combine_voice_prompts as _combine_voice_prompts,
model_load_progress,
patch_chatterbox_f32,
@@ -48,7 +50,7 @@ class ChatterboxTurboTTSBackend:
self._model_load_lock = asyncio.Lock()
def _get_device(self) -> str:
return get_torch_device(force_cpu_on_mac=True)
return get_torch_device(force_cpu_on_mac=True, allow_xpu=True)
def is_loaded(self) -> bool:
return self.model is not None
@@ -116,10 +118,7 @@ class ChatterboxTurboTTSBackend:
del self.model
self.model = None
self._device = None
if device == "cuda":
import torch
torch.cuda.empty_cache()
empty_device_cache(device)
logger.info("Chatterbox Turbo unloaded")
async def create_voice_prompt(
@@ -181,7 +180,7 @@ class ChatterboxTurboTTSBackend:
import torch
if seed is not None:
torch.manual_seed(seed)
manual_seed(seed, self._device)
logger.info("[Chatterbox Turbo] Generating (English)")
@@ -200,10 +199,7 @@ class ChatterboxTurboTTSBackend:
else:
audio = np.asarray(wav, dtype=np.float32)
sample_rate = (
getattr(self.model, "sr", None)
or getattr(self.model, "sample_rate", 24000)
)
sample_rate = getattr(self.model, "sr", None) or getattr(self.model, "sample_rate", 24000)
return audio, sample_rate
+19 -20
View File
@@ -24,6 +24,8 @@ from . import TTSBackend
from .base import (
is_model_cached,
get_torch_device,
empty_device_cache,
manual_seed,
combine_voice_prompts as _combine_voice_prompts,
model_load_progress,
)
@@ -66,7 +68,7 @@ class HumeTadaBackend:
def _get_device(self) -> str:
# Force CPU on macOS — MPS has issues with flow matching
# and large vocab lm_head (>65536 output channels)
return get_torch_device(force_cpu_on_mac=True)
return get_torch_device(force_cpu_on_mac=True, allow_xpu=True)
def is_loaded(self) -> bool:
return self.model is not None
@@ -105,6 +107,7 @@ class HumeTadaBackend:
# package. The real package pulls in onnx/tensorboard/matplotlib via
# descript-audiotools, so we use a lightweight shim instead.
from ..utils.dac_shim import install_dac_shim
install_dac_shim()
import torch
@@ -142,9 +145,12 @@ class HumeTadaBackend:
allow_patterns=["tokenizer*", "special_tokens*"],
)
# Determine dtype — use bf16 on CUDA for ~50% memory savings
# Determine dtype — use bf16 on CUDA/XPU for ~50% memory savings
if device == "cuda" and torch.cuda.is_bf16_supported():
model_dtype = torch.bfloat16
elif device == "xpu":
# Intel Arc (Alchemist+) supports bf16 natively
model_dtype = torch.bfloat16
else:
model_dtype = torch.float32
@@ -153,14 +159,14 @@ class HumeTadaBackend:
# This avoids monkey-patching AutoTokenizer.from_pretrained
# which corrupts the classmethod descriptor for other engines.
from tada.modules.aligner import AlignerConfig
AlignerConfig.tokenizer_name = tokenizer_path
# Load encoder (only needed for voice prompt encoding)
from tada.modules.encoder import Encoder
logger.info("Loading TADA encoder...")
self.encoder = Encoder.from_pretrained(
TADA_CODEC_REPO, subfolder="encoder"
).to(device)
self.encoder = Encoder.from_pretrained(TADA_CODEC_REPO, subfolder="encoder").to(device)
self.encoder.eval()
# Load the causal LM (includes decoder for wav generation).
@@ -169,12 +175,11 @@ class HumeTadaBackend:
# which hits the gated repo. Pre-load the config from HF,
# inject the local tokenizer path, then pass it in.
from tada.modules.tada import TadaForCausalLM, TadaConfig
logger.info(f"Loading TADA {model_size} model...")
config = TadaConfig.from_pretrained(repo)
config.tokenizer_name = tokenizer_path
self.model = TadaForCausalLM.from_pretrained(
repo, config=config, torch_dtype=model_dtype
).to(device)
self.model = TadaForCausalLM.from_pretrained(repo, config=config, torch_dtype=model_dtype).to(device)
self.model.eval()
logger.info(f"HumeAI TADA {model_size} loaded successfully on {device}")
@@ -188,11 +193,11 @@ class HumeTadaBackend:
del self.encoder
self.encoder = None
device = self._device
self._device = None
import torch
if torch.cuda.is_available():
torch.cuda.empty_cache()
if device:
empty_device_cache(device)
logger.info("HumeAI TADA unloaded")
@@ -213,9 +218,7 @@ class HumeTadaBackend:
"""
await self.load_model(self.model_size)
cache_key = (
"tada_" + get_cache_key(audio_path, reference_text)
) if use_cache else None
cache_key = ("tada_" + get_cache_key(audio_path, reference_text)) if use_cache else None
if cache_key:
cached = get_cached_voice_prompt(cache_key)
@@ -239,9 +242,7 @@ class HumeTadaBackend:
# Encode with forced alignment
text_arg = [reference_text] if reference_text else None
prompt = self.encoder(
audio, text=text_arg, sample_rate=sr
)
prompt = self.encoder(audio, text=text_arg, sample_rate=sr)
# Serialize EncoderOutput to a dict of CPU tensors for caching
prompt_dict = {}
@@ -299,9 +300,7 @@ class HumeTadaBackend:
from tada.modules.encoder import EncoderOutput
if seed is not None:
torch.manual_seed(seed)
if torch.cuda.is_available():
torch.cuda.manual_seed(seed)
manual_seed(seed, self._device)
device = self._device
+288
View File
@@ -0,0 +1,288 @@
"""
Kokoro TTS backend implementation.
Wraps the Kokoro-82M model for fast, lightweight text-to-speech.
82M parameters, CPU realtime, 24kHz output, Apache 2.0 license.
Kokoro uses pre-built voice style vectors (not traditional zero-shot cloning
from arbitrary audio). Voice prompts are stored as deferred references to
HF-hosted voice .pt files.
Languages supported (via misaki G2P):
- American English (a), British English (b)
- Spanish (e), French (f), Hindi (h), Italian (i), Portuguese (p)
- Japanese (j) — requires misaki[ja]
- Chinese (z) — requires misaki[zh]
"""
import asyncio
import logging
import os
from typing import Optional
import numpy as np
from . import TTSBackend
from .base import (
get_torch_device,
combine_voice_prompts as _combine_voice_prompts,
model_load_progress,
)
logger = logging.getLogger(__name__)
# HuggingFace repo for model + voice detection
KOKORO_HF_REPO = "hexgrad/Kokoro-82M"
KOKORO_SAMPLE_RATE = 24000
# Default voice if none specified
KOKORO_DEFAULT_VOICE = "af_heart"
# All available Kokoro voices: (voice_id, display_name, gender, lang_code)
KOKORO_VOICES = [
# American English female
("af_alloy", "Alloy", "female", "en"),
("af_aoede", "Aoede", "female", "en"),
("af_bella", "Bella", "female", "en"),
("af_heart", "Heart", "female", "en"),
("af_jessica", "Jessica", "female", "en"),
("af_kore", "Kore", "female", "en"),
("af_nicole", "Nicole", "female", "en"),
("af_nova", "Nova", "female", "en"),
("af_river", "River", "female", "en"),
("af_sarah", "Sarah", "female", "en"),
("af_sky", "Sky", "female", "en"),
# American English male
("am_adam", "Adam", "male", "en"),
("am_echo", "Echo", "male", "en"),
("am_eric", "Eric", "male", "en"),
("am_fenrir", "Fenrir", "male", "en"),
("am_liam", "Liam", "male", "en"),
("am_michael", "Michael", "male", "en"),
("am_onyx", "Onyx", "male", "en"),
("am_puck", "Puck", "male", "en"),
("am_santa", "Santa", "male", "en"),
# British English female
("bf_alice", "Alice", "female", "en"),
("bf_emma", "Emma", "female", "en"),
("bf_isabella", "Isabella", "female", "en"),
("bf_lily", "Lily", "female", "en"),
# British English male
("bm_daniel", "Daniel", "male", "en"),
("bm_fable", "Fable", "male", "en"),
("bm_george", "George", "male", "en"),
("bm_lewis", "Lewis", "male", "en"),
# Spanish
("ef_dora", "Dora", "female", "es"),
("em_alex", "Alex", "male", "es"),
("em_santa", "Santa", "male", "es"),
# French
("ff_siwis", "Siwis", "female", "fr"),
# Hindi
("hf_alpha", "Alpha", "female", "hi"),
("hf_beta", "Beta", "female", "hi"),
("hm_omega", "Omega", "male", "hi"),
("hm_psi", "Psi", "male", "hi"),
# Italian
("if_sara", "Sara", "female", "it"),
("im_nicola", "Nicola", "male", "it"),
# Japanese
("jf_alpha", "Alpha", "female", "ja"),
("jf_gongitsune", "Gongitsune", "female", "ja"),
("jf_nezumi", "Nezumi", "female", "ja"),
("jf_tebukuro", "Tebukuro", "female", "ja"),
("jm_kumo", "Kumo", "male", "ja"),
# Portuguese
("pf_dora", "Dora", "female", "pt"),
("pm_alex", "Alex", "male", "pt"),
("pm_santa", "Santa", "male", "pt"),
# Chinese
("zf_xiaobei", "Xiaobei", "female", "zh"),
("zf_xiaoni", "Xiaoni", "female", "zh"),
("zf_xiaoxiao", "Xiaoxiao", "female", "zh"),
("zf_xiaoyi", "Xiaoyi", "female", "zh"),
]
# Map our ISO language codes to Kokoro lang_code characters
LANG_CODE_MAP = {
"en": "a", # American English
"es": "e",
"fr": "f",
"hi": "h",
"it": "i",
"pt": "p",
"ja": "j",
"zh": "z",
}
class KokoroTTSBackend:
"""Kokoro-82M TTS backend — tiny, fast, CPU-friendly."""
def __init__(self):
self._model = None
self._pipelines: dict = {} # lang_code -> KPipeline
self._device: Optional[str] = None
self.model_size = "default"
def _get_device(self) -> str:
"""Select device. Kokoro supports CUDA and CPU. MPS needs fallback env var."""
device = get_torch_device(allow_mps=False)
# Kokoro can use MPS but requires PYTORCH_ENABLE_MPS_FALLBACK=1
# For now, skip MPS to avoid user confusion — CPU is already realtime
return device
@property
def device(self) -> str:
if self._device is None:
self._device = self._get_device()
return self._device
def is_loaded(self) -> bool:
return self._model is not None
def _get_model_path(self, model_size: str) -> str:
return KOKORO_HF_REPO
def _is_model_cached(self, model_size: str = "default") -> bool:
"""Check if Kokoro model files are cached locally."""
from .base import is_model_cached
return is_model_cached(
KOKORO_HF_REPO,
required_files=["config.json", "kokoro-v1_0.pth"],
)
async def load_model(self, model_size: str = "default") -> None:
"""Load the Kokoro model."""
if self._model is not None:
return
await asyncio.to_thread(self._load_model_sync)
def _load_model_sync(self):
"""Synchronous model loading."""
model_name = "kokoro"
is_cached = self._is_model_cached()
with model_load_progress(model_name, is_cached):
from kokoro import KModel
device = self.device
logger.info(f"Loading Kokoro-82M on {device}...")
self._model = KModel(repo_id=KOKORO_HF_REPO).to(device).eval()
logger.info("Kokoro-82M loaded successfully")
def _get_pipeline(self, lang_code: str):
"""Get or create a KPipeline for the given language code."""
kokoro_lang = LANG_CODE_MAP.get(lang_code, "a")
if kokoro_lang not in self._pipelines:
from kokoro import KPipeline
# Create pipeline with our existing model (no redundant model loading)
self._pipelines[kokoro_lang] = KPipeline(
lang_code=kokoro_lang,
repo_id=KOKORO_HF_REPO,
model=self._model,
)
return self._pipelines[kokoro_lang]
def unload_model(self) -> None:
"""Unload model to free memory."""
if self._model is not None:
del self._model
self._model = None
self._pipelines.clear()
import torch
if torch.cuda.is_available():
torch.cuda.empty_cache()
logger.info("Kokoro unloaded")
async def create_voice_prompt(
self,
audio_path: str,
reference_text: str,
use_cache: bool = True,
) -> tuple[dict, bool]:
"""
Create voice prompt for Kokoro.
Kokoro doesn't do traditional voice cloning from arbitrary audio.
When called for a cloned profile (fallback), uses the default voice.
For preset profiles, the voice_prompt dict is built by the profile
service and bypasses this method entirely.
"""
return {
"voice_type": "preset",
"preset_engine": "kokoro",
"preset_voice_id": KOKORO_DEFAULT_VOICE,
}, False
async def combine_voice_prompts(
self,
audio_paths: list[str],
reference_texts: list[str],
) -> tuple[np.ndarray, str]:
"""Combine voice prompts — uses base implementation for audio concatenation."""
return await _combine_voice_prompts(
audio_paths, reference_texts, sample_rate=KOKORO_SAMPLE_RATE
)
async def generate(
self,
text: str,
voice_prompt: dict,
language: str = "en",
seed: Optional[int] = None,
instruct: Optional[str] = None,
) -> tuple[np.ndarray, int]:
"""
Generate audio from text using Kokoro.
Args:
text: Text to synthesize
voice_prompt: Dict with kokoro_voice key
language: Language code
seed: Random seed for reproducibility
instruct: Not supported by Kokoro (ignored)
Returns:
Tuple of (audio_array, sample_rate)
"""
await self.load_model()
voice_name = voice_prompt.get("preset_voice_id") or voice_prompt.get("kokoro_voice") or KOKORO_DEFAULT_VOICE
def _generate_sync():
import torch
if seed is not None:
torch.manual_seed(seed)
if torch.cuda.is_available():
torch.cuda.manual_seed(seed)
pipeline = self._get_pipeline(language)
# Generate all chunks and concatenate
audio_chunks = []
for result in pipeline(text, voice=voice_name, speed=1.0):
if result.audio is not None:
chunk = result.audio
if isinstance(chunk, torch.Tensor):
chunk = chunk.detach().cpu().numpy()
audio_chunks.append(chunk.squeeze())
if not audio_chunks:
# Return 1 second of silence as fallback
return np.zeros(KOKORO_SAMPLE_RATE, dtype=np.float32), KOKORO_SAMPLE_RATE
audio = np.concatenate(audio_chunks)
return audio.astype(np.float32), KOKORO_SAMPLE_RATE
return await asyncio.to_thread(_generate_sync)
+17 -11
View File
@@ -12,7 +12,14 @@ from typing import Optional, Tuple
import numpy as np
from . import TTSBackend
from .base import is_model_cached, get_torch_device, combine_voice_prompts as _combine_voice_prompts, model_load_progress
from .base import (
is_model_cached,
get_torch_device,
empty_device_cache,
manual_seed,
combine_voice_prompts as _combine_voice_prompts,
model_load_progress,
)
from ..utils.cache import get_cache_key, get_cached_voice_prompt, cache_voice_prompt
logger = logging.getLogger(__name__)
@@ -30,7 +37,7 @@ class LuxTTSBackend:
self._device = None
def _get_device(self) -> str:
return get_torch_device(allow_mps=True)
return get_torch_device(allow_mps=True, allow_xpu=True)
def is_loaded(self) -> bool:
return self.model is not None
@@ -69,9 +76,12 @@ class LuxTTSBackend:
if device == "cpu":
import os
threads = os.cpu_count() or 4
self.model = LuxTTS(
model_path=LUXTTS_HF_REPO, device="cpu", threads=min(threads, 8),
model_path=LUXTTS_HF_REPO,
device="cpu",
threads=min(threads, 8),
)
else:
self.model = LuxTTS(model_path=LUXTTS_HF_REPO, device=device)
@@ -81,12 +91,12 @@ class LuxTTSBackend:
def unload_model(self) -> None:
"""Unload model to free memory."""
if self.model is not None:
device = self.device
del self.model
self.model = None
self._device = None
import torch
if torch.cuda.is_available():
torch.cuda.empty_cache()
empty_device_cache(device)
logger.info("LuxTTS unloaded")
@@ -154,12 +164,8 @@ class LuxTTSBackend:
await self.load_model()
def _generate_sync():
import torch
if seed is not None:
torch.manual_seed(seed)
if torch.cuda.is_available():
torch.cuda.manual_seed(seed)
manual_seed(seed, self.device)
wav = self.model.generate_speech(
text=text,
+9 -26
View File
@@ -6,7 +6,6 @@ from typing import Optional, List, Tuple
import asyncio
import logging
import numpy as np
import os
from pathlib import Path
logger = logging.getLogger(__name__)
@@ -21,6 +20,7 @@ ensure_original_qwen_config_cached()
from . import TTSBackend, STTBackend, LANGUAGE_CODE_TO_NAME, WHISPER_HF_REPOS
from .base import is_model_cached, combine_voice_prompts as _combine_voice_prompts, model_load_progress
from ..utils.cache import get_cache_key, get_cached_voice_prompt, cache_voice_prompt
from ..utils.hf_offline_patch import force_offline_if_cached
class MLXTTSBackend:
@@ -96,32 +96,13 @@ class MLXTTSBackend:
model_name = f"qwen-tts-{model_size}"
is_cached = self._is_model_cached(model_size)
# Force offline mode when cached to avoid network requests
original_hf_hub_offline = os.environ.get("HF_HUB_OFFLINE")
if is_cached:
os.environ["HF_HUB_OFFLINE"] = "1"
logger.info("[PATCH] Model %s is cached, forcing HF_HUB_OFFLINE=1 to avoid network requests", model_size)
with model_load_progress(model_name, is_cached):
from mlx_audio.tts import load
try:
with model_load_progress(model_name, is_cached):
from mlx_audio.tts import load
logger.info("Loading MLX TTS model %s...", model_size)
logger.info("Loading MLX TTS model %s...", model_size)
try:
self.model = load(model_path)
except Exception as load_error:
if is_cached and "offline" in str(load_error).lower():
logger.warning("[PATCH] Offline load failed, trying with network: %s", load_error)
os.environ.pop("HF_HUB_OFFLINE", None)
self.model = load(model_path)
else:
raise
finally:
if original_hf_hub_offline is not None:
os.environ["HF_HUB_OFFLINE"] = original_hf_hub_offline
else:
os.environ.pop("HF_HUB_OFFLINE", None)
with force_offline_if_cached(is_cached, model_name):
self.model = load(model_path)
self._current_model_size = model_size
self.model_size = model_size
@@ -329,7 +310,9 @@ class MLXSTTBackend:
model_name = WHISPER_HF_REPOS.get(model_size, f"openai/whisper-{model_size}")
logger.info("Loading MLX Whisper model %s...", model_size)
self.model = load(model_name)
with force_offline_if_cached(is_cached, progress_model_name):
self.model = load(model_name)
self.model_size = model_size
logger.info("MLX Whisper model %s loaded successfully", model_size)
+31 -21
View File
@@ -14,11 +14,14 @@ from . import TTSBackend, STTBackend, LANGUAGE_CODE_TO_NAME, WHISPER_HF_REPOS
from .base import (
is_model_cached,
get_torch_device,
empty_device_cache,
manual_seed,
combine_voice_prompts as _combine_voice_prompts,
model_load_progress,
)
from ..utils.cache import get_cache_key, get_cached_voice_prompt, cache_voice_prompt
from ..utils.audio import load_audio
from ..utils.hf_offline_patch import force_offline_if_cached
class PyTorchTTSBackend:
@@ -96,18 +99,28 @@ class PyTorchTTSBackend:
model_path = self._get_model_path(model_size)
logger.info("Loading TTS model %s on %s...", model_size, self.device)
if self.device == "cpu":
self.model = Qwen3TTSModel.from_pretrained(
model_path,
torch_dtype=torch.float32,
low_cpu_mem_usage=False,
)
else:
self.model = Qwen3TTSModel.from_pretrained(
model_path,
device_map=self.device,
torch_dtype=torch.bfloat16,
)
# Route both HF Hub and Transformers through a single cache root.
# On Windows local setups, model assets can otherwise split between
# .hf-cache/hub and .hf-cache/transformers, causing speech_tokenizer
# and preprocessor_config.json to fail to resolve during load.
from huggingface_hub import constants as hf_constants
tts_cache_dir = hf_constants.HF_HUB_CACHE
with force_offline_if_cached(is_cached, model_name):
if self.device == "cpu":
self.model = Qwen3TTSModel.from_pretrained(
model_path,
cache_dir=tts_cache_dir,
torch_dtype=torch.float32,
low_cpu_mem_usage=False,
)
else:
self.model = Qwen3TTSModel.from_pretrained(
model_path,
cache_dir=tts_cache_dir,
device_map=self.device,
torch_dtype=torch.bfloat16,
)
self._current_model_size = model_size
self.model_size = model_size
@@ -120,8 +133,7 @@ class PyTorchTTSBackend:
self.model = None
self._current_model_size = None
if torch.cuda.is_available():
torch.cuda.empty_cache()
empty_device_cache(self.device)
logger.info("TTS model unloaded")
@@ -213,9 +225,7 @@ class PyTorchTTSBackend:
"""Run synchronous generation in thread pool."""
# Set seed if provided
if seed is not None:
torch.manual_seed(seed)
if torch.cuda.is_available():
torch.cuda.manual_seed(seed)
manual_seed(seed, self.device)
# Generate audio - this is the blocking operation
wavs, sample_rate = self.model.generate_voice_clone(
@@ -282,8 +292,9 @@ class PyTorchSTTBackend:
model_name = WHISPER_HF_REPOS.get(model_size, f"openai/whisper-{model_size}")
logger.info("Loading Whisper model %s on %s...", model_size, self.device)
self.processor = WhisperProcessor.from_pretrained(model_name)
self.model = WhisperForConditionalGeneration.from_pretrained(model_name)
with force_offline_if_cached(is_cached, progress_model_name):
self.processor = WhisperProcessor.from_pretrained(model_name)
self.model = WhisperForConditionalGeneration.from_pretrained(model_name)
self.model.to(self.device)
self.model_size = model_size
@@ -297,8 +308,7 @@ class PyTorchSTTBackend:
self.model = None
self.processor = None
if torch.cuda.is_available():
torch.cuda.empty_cache()
empty_device_cache(self.device)
logger.info("Whisper model unloaded")
@@ -0,0 +1,210 @@
"""
Qwen3-TTS CustomVoice backend implementation.
Wraps the Qwen3-TTS-12Hz CustomVoice model for preset-speaker TTS with
instruction-based style control. Uses the same qwen_tts library as the
Base model (pytorch_backend.py) but loads a different checkpoint and
calls generate_custom_voice() instead of generate_voice_clone().
Key differences from the Base engine:
- Uses preset speakers (9 built-in voices) instead of zero-shot cloning
- Supports instruct parameter for tone/emotion/prosody control
- Two model sizes: 1.7B and 0.6B
Languages supported: zh, en, ja, ko, de, fr, ru, pt, es, it
"""
import asyncio
import logging
from typing import Optional
import numpy as np
import torch
from . import TTSBackend, LANGUAGE_CODE_TO_NAME
from .base import (
is_model_cached,
get_torch_device,
combine_voice_prompts as _combine_voice_prompts,
model_load_progress,
)
logger = logging.getLogger(__name__)
# ── Preset speakers ──────────────────────────────────────────────────
# (speaker_id, display_name, gender, native_language_code, description)
QWEN_CUSTOM_VOICES = [
("Vivian", "Vivian", "female", "zh", "Bright, slightly edgy young female voice"),
("Serena", "Serena", "female", "zh", "Warm, gentle young female voice"),
("Uncle_Fu", "Uncle Fu", "male", "zh", "Seasoned male voice with a low, mellow timbre"),
("Dylan", "Dylan", "male", "zh", "Youthful Beijing male voice with a clear, natural timbre"),
("Eric", "Eric", "male", "zh", "Lively Chengdu male voice with a slightly husky brightness"),
("Ryan", "Ryan", "male", "en", "Dynamic male voice with strong rhythmic drive"),
("Aiden", "Aiden", "male", "en", "Sunny American male voice with a clear midrange"),
("Ono_Anna", "Ono Anna", "female", "ja", "Playful Japanese female voice with a light, nimble timbre"),
("Sohee", "Sohee", "female", "ko", "Warm Korean female voice with rich emotion"),
]
QWEN_CV_DEFAULT_SPEAKER = "Ryan"
# HuggingFace repo IDs per model size
QWEN_CV_HF_REPOS = {
"1.7B": "Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice",
"0.6B": "Qwen/Qwen3-TTS-12Hz-0.6B-CustomVoice",
}
class QwenCustomVoiceBackend:
"""Qwen3-TTS CustomVoice backend — preset speakers with instruct control."""
def __init__(self, model_size: str = "1.7B"):
self.model = None
self.model_size = model_size
self.device = self._get_device()
self._current_model_size: Optional[str] = None
def _get_device(self) -> str:
return get_torch_device(allow_xpu=True, allow_directml=True)
def is_loaded(self) -> bool:
return self.model is not None
def _get_model_path(self, model_size: str) -> str:
if model_size not in QWEN_CV_HF_REPOS:
raise ValueError(f"Unknown model size: {model_size}")
return QWEN_CV_HF_REPOS[model_size]
def _is_model_cached(self, model_size: Optional[str] = None) -> bool:
size = model_size or self.model_size
return is_model_cached(self._get_model_path(size))
async def load_model_async(self, model_size: Optional[str] = None) -> None:
if model_size is None:
model_size = self.model_size
if self.model is not None and self._current_model_size == model_size:
return
if self.model is not None and self._current_model_size != model_size:
self.unload_model()
await asyncio.to_thread(self._load_model_sync, model_size)
# Alias for compatibility with the TTSBackend protocol
load_model = load_model_async
def _load_model_sync(self, model_size: str) -> None:
model_name = f"qwen-custom-voice-{model_size}"
is_cached = self._is_model_cached(model_size)
with model_load_progress(model_name, is_cached):
from qwen_tts import Qwen3TTSModel
model_path = self._get_model_path(model_size)
logger.info("Loading Qwen CustomVoice %s on %s...", model_size, self.device)
if self.device == "cpu":
self.model = Qwen3TTSModel.from_pretrained(
model_path,
torch_dtype=torch.float32,
low_cpu_mem_usage=False,
)
else:
self.model = Qwen3TTSModel.from_pretrained(
model_path,
device_map=self.device,
torch_dtype=torch.bfloat16,
)
self._current_model_size = model_size
self.model_size = model_size
logger.info("Qwen CustomVoice %s loaded successfully", model_size)
def unload_model(self) -> None:
if self.model is not None:
del self.model
self.model = None
self._current_model_size = None
if torch.cuda.is_available():
torch.cuda.empty_cache()
logger.info("Qwen CustomVoice unloaded")
async def create_voice_prompt(
self,
audio_path: str,
reference_text: str,
use_cache: bool = True,
) -> tuple[dict, bool]:
"""
Create voice prompt for CustomVoice.
CustomVoice doesn't use reference audio — it uses preset speakers.
When called for a cloned profile (fallback), uses the default speaker.
For preset profiles, the voice_prompt dict is built by the profile
service and bypasses this method entirely.
"""
return {
"voice_type": "preset",
"preset_engine": "qwen_custom_voice",
"preset_voice_id": QWEN_CV_DEFAULT_SPEAKER,
}, False
async def combine_voice_prompts(
self,
audio_paths: list[str],
reference_texts: list[str],
) -> tuple[np.ndarray, str]:
return await _combine_voice_prompts(audio_paths, reference_texts)
async def generate(
self,
text: str,
voice_prompt: dict,
language: str = "en",
seed: Optional[int] = None,
instruct: Optional[str] = None,
) -> tuple[np.ndarray, int]:
"""
Generate audio using Qwen CustomVoice.
Args:
text: Text to synthesize
voice_prompt: Dict with preset_voice_id (speaker name)
language: Language code (zh, en, ja, ko, etc.)
seed: Random seed for reproducibility
instruct: Natural language instruction for style control
(e.g. "Speak in an angry tone", "Very happy")
Returns:
Tuple of (audio_array, sample_rate)
"""
await self.load_model_async(None)
speaker = voice_prompt.get("preset_voice_id") or QWEN_CV_DEFAULT_SPEAKER
def _generate_sync():
if seed is not None:
torch.manual_seed(seed)
if torch.cuda.is_available():
torch.cuda.manual_seed(seed)
lang_name = LANGUAGE_CODE_TO_NAME.get(language, "auto")
kwargs = {
"text": text,
"language": lang_name.capitalize() if lang_name != "auto" else "Auto",
"speaker": speaker,
}
# Only pass instruct if non-empty
if instruct:
kwargs["instruct"] = instruct
wavs, sample_rate = self.model.generate_custom_voice(**kwargs)
return wavs[0], sample_rate
audio, sample_rate = await asyncio.to_thread(_generate_sync)
return audio, sample_rate
+51 -1
View File
@@ -52,6 +52,16 @@ def build_server(cuda=False):
if platform.system() == "Windows":
args.append("--noconsole")
# numpy 2.x / torch ABI mismatch fix: install memmove fallback for
# torch.from_numpy() before the app starts. Runtime hooks run after
# FrozenImporter is registered so frozen torch/numpy are importable.
args.extend(
[
"--runtime-hook",
str(backend_dir / "pyi_rth_numpy_compat.py"),
]
)
# Add local qwen_tts path if specified (for editable installs)
qwen_tts_path = os.getenv("QWEN_TTS_PATH")
if qwen_tts_path and Path(qwen_tts_path).exists():
@@ -86,6 +96,8 @@ def build_server(cuda=False):
"--hidden-import",
"backend.backends.pytorch_backend",
"--hidden-import",
"backend.backends.qwen_custom_voice_backend",
"--hidden-import",
"backend.utils.audio",
"--hidden-import",
"backend.utils.cache",
@@ -228,6 +240,44 @@ def build_server(cuda=False):
"torchaudio",
"--collect-submodules",
"tada",
# Kokoro 82M — lightweight TTS engine using misaki G2P
"--hidden-import",
"backend.backends.kokoro_backend",
"--hidden-import",
"kokoro",
"--hidden-import",
"kokoro.pipeline",
"--hidden-import",
"kokoro.model",
"--hidden-import",
"kokoro.istftnet",
"--hidden-import",
"kokoro.modules",
"--hidden-import",
"kokoro.custom_stft",
# misaki ships G2P data files (dictionaries, phoneme tables)
# that must be bundled for espeak/en/ja/zh G2P to work
"--collect-all",
"misaki",
# language_tags ships JSON data files (index.json etc.) loaded at
# runtime via: misaki → phonemizer → segments → csvw → language_tags
"--collect-all",
"language_tags",
# espeakng_loader ships the entire espeak-ng-data directory (369 files)
# loaded at import time by misaki.espeak via get_data_path()
"--collect-all",
"espeakng_loader",
# spacy en_core_web_sm model — misaki.en tries to spacy.cli.download()
# at runtime if not found, which calls pip as a subprocess and crashes
# the frozen binary. Bundle the model so spacy.util.is_package() passes.
"--collect-all",
"en_core_web_sm",
"--copy-metadata",
"en_core_web_sm",
"--hidden-import",
"en_core_web_sm",
"--hidden-import",
"loguru",
]
)
@@ -370,7 +420,7 @@ def build_server(cuda=False):
"torchvision",
"torchaudio",
"--index-url",
"https://download.pytorch.org/whl/cu126",
"https://download.pytorch.org/whl/cu128",
"--force-reinstall",
"-q",
],
+50 -3
View File
@@ -19,7 +19,22 @@ if _custom_models_dir:
logger.info("Model download path set to: %s", _custom_models_dir)
# Default data directory (used in development)
_data_dir = Path("data")
_data_dir = Path("data").resolve()
def _path_relative_to_any_data_dir(path: Path) -> Path | None:
"""Extract the path within a data dir from an absolute or relative path."""
parts = path.parts
for idx, part in enumerate(parts):
if part != "data":
continue
tail = parts[idx + 1 :]
if tail:
return Path(*tail)
return Path()
return None
def set_data_dir(path: str | Path):
@@ -30,9 +45,9 @@ def set_data_dir(path: str | Path):
path: Path to the data directory
"""
global _data_dir
_data_dir = Path(path)
_data_dir = Path(path).resolve()
_data_dir.mkdir(parents=True, exist_ok=True)
logger.info("Data directory set to: %s", _data_dir.absolute())
logger.info("Data directory set to: %s", _data_dir)
def get_data_dir() -> Path:
@@ -45,6 +60,38 @@ def get_data_dir() -> Path:
return _data_dir
def to_storage_path(path: str | Path) -> str:
"""Convert a filesystem path to a DB-safe path relative to the data dir."""
resolved_path = Path(path).resolve()
relative_to_any_data_dir = _path_relative_to_any_data_dir(resolved_path)
if relative_to_any_data_dir is not None:
return str(relative_to_any_data_dir)
try:
return str(resolved_path.relative_to(_data_dir))
except ValueError:
return str(resolved_path)
def resolve_storage_path(path: str | Path | None) -> Path | None:
"""Resolve a DB-stored path against the configured data dir."""
if path is None:
return None
stored_path = Path(path)
if stored_path.is_absolute():
rebased_path = _path_relative_to_any_data_dir(stored_path)
if rebased_path is not None:
candidate = (_data_dir / rebased_path).resolve()
if candidate.exists() or not stored_path.exists():
return candidate
return stored_path
return (_data_dir / stored_path).resolve()
def get_db_path() -> Path:
"""Get database file path."""
return _data_dir / "voicebox.db"
+56
View File
@@ -34,6 +34,7 @@ def run_migrations(engine) -> None:
_migrate_generations(engine, inspector, tables)
_migrate_effect_presets(engine, inspector, tables)
_migrate_generation_versions(engine, inspector, tables)
_normalize_storage_paths(engine, tables)
# -- helpers ---------------------------------------------------------------
@@ -134,6 +135,17 @@ def _migrate_profiles(engine, inspector, tables: set[str]) -> None:
_add_column(engine, "profiles", "avatar_path VARCHAR", "avatar_path")
if "effects_chain" not in columns:
_add_column(engine, "profiles", "effects_chain TEXT", "effects_chain")
# Voice type system — v0.3.x
if "voice_type" not in columns:
_add_column(engine, "profiles", "voice_type VARCHAR DEFAULT 'cloned'", "voice_type")
if "preset_engine" not in columns:
_add_column(engine, "profiles", "preset_engine VARCHAR", "preset_engine")
if "preset_voice_id" not in columns:
_add_column(engine, "profiles", "preset_voice_id VARCHAR", "preset_voice_id")
if "design_prompt" not in columns:
_add_column(engine, "profiles", "design_prompt TEXT", "design_prompt")
if "default_engine" not in columns:
_add_column(engine, "profiles", "default_engine VARCHAR", "default_engine")
def _migrate_generations(engine, inspector, tables: set[str]) -> None:
@@ -168,3 +180,47 @@ def _migrate_generation_versions(engine, inspector, tables: set[str]) -> None:
columns = _get_columns(inspector, "generation_versions")
if "source_version_id" not in columns:
_add_column(engine, "generation_versions", "source_version_id VARCHAR", "source_version_id")
def _normalize_storage_paths(engine, tables: set[str]) -> None:
"""Normalize stored file paths to be relative to the configured data dir."""
from pathlib import Path
from ..config import get_data_dir, to_storage_path, resolve_storage_path
data_dir = get_data_dir()
path_columns = [
("generations", "audio_path"),
("generation_versions", "audio_path"),
("profile_samples", "audio_path"),
("profiles", "avatar_path"),
]
total_fixed = 0
with engine.connect() as conn:
for table, column in path_columns:
if table not in tables:
continue
rows = conn.execute(
text(f"SELECT id, {column} FROM {table} WHERE {column} IS NOT NULL")
).fetchall()
for row_id, path_val in rows:
if not path_val:
continue
p = Path(path_val)
resolved = resolve_storage_path(p)
if resolved is None:
continue
normalized = to_storage_path(resolved)
if normalized != path_val:
conn.execute(
text(f"UPDATE {table} SET {column} = :path WHERE id = :id"),
{"path": normalized, "id": row_id},
)
total_fixed += 1
if total_fixed > 0:
conn.commit()
logger.info("Normalized %d stored file paths", total_fixed)
+15 -1
View File
@@ -10,7 +10,13 @@ Base = declarative_base()
class VoiceProfile(Base):
"""Voice profile."""
"""Voice profile.
voice_type discriminates three flavours:
- "cloned" — traditional reference-audio profiles (all cloning engines)
- "preset" — engine-specific pre-built voice (e.g. Kokoro voices)
- "designed" — text-described voice (e.g. Qwen CustomVoice, future)
"""
__tablename__ = "profiles"
@@ -20,6 +26,14 @@ class VoiceProfile(Base):
language = Column(String, default="en")
avatar_path = Column(String, nullable=True)
effects_chain = Column(Text, nullable=True)
# Voice type system — added v0.3.x
voice_type = Column(String, default="cloned") # "cloned" | "preset" | "designed"
preset_engine = Column(String, nullable=True) # e.g. "kokoro" — only for preset
preset_voice_id = Column(String, nullable=True) # e.g. "am_adam" — only for preset
design_prompt = Column(Text, nullable=True) # text description — only for designed
default_engine = Column(String, nullable=True) # auto-selected engine, locked for preset
created_at = Column(DateTime, default=datetime.utcnow)
updated_at = Column(DateTime, default=datetime.utcnow, onupdate=datetime.utcnow)
+4 -2
View File
@@ -3,7 +3,8 @@
import json
import logging
import uuid
from pathlib import Path
from .. import config
logger = logging.getLogger(__name__)
@@ -25,7 +26,8 @@ def backfill_generation_versions(SessionLocal, Generation, GenerationVersion) ->
for gen in generations:
if gen.id in existing_version_gen_ids:
continue
if not Path(gen.audio_path).exists():
resolved_audio_path = config.resolve_storage_path(gen.audio_path)
if resolved_audio_path is None or not resolved_audio_path.exists():
continue
version = GenerationVersion(
id=str(uuid.uuid4()),
+12 -1
View File
@@ -15,6 +15,11 @@ class VoiceProfileCreate(BaseModel):
language: str = Field(
default="en", pattern="^(zh|en|ja|ko|de|fr|ru|pt|es|it|he|ar|da|el|fi|hi|ms|nl|no|pl|sv|sw|tr)$"
)
voice_type: Optional[str] = Field(default="cloned", pattern="^(cloned|preset|designed)$")
preset_engine: Optional[str] = Field(None, max_length=50)
preset_voice_id: Optional[str] = Field(None, max_length=100)
design_prompt: Optional[str] = Field(None, max_length=2000)
default_engine: Optional[str] = Field(None, max_length=50)
class VoiceProfileResponse(BaseModel):
@@ -26,6 +31,11 @@ class VoiceProfileResponse(BaseModel):
language: str
avatar_path: Optional[str] = None
effects_chain: Optional[List["EffectConfig"]] = None
voice_type: str = "cloned"
preset_engine: Optional[str] = None
preset_voice_id: Optional[str] = None
design_prompt: Optional[str] = None
default_engine: Optional[str] = None
generation_count: int = 0
sample_count: int = 0
created_at: datetime
@@ -68,7 +78,7 @@ class GenerationRequest(BaseModel):
seed: Optional[int] = Field(None, ge=0)
model_size: Optional[str] = Field(default="1.7B", pattern="^(1\\.7B|0\\.6B|1B|3B)$")
instruct: Optional[str] = Field(None, max_length=500)
engine: Optional[str] = Field(default="qwen", pattern="^(qwen|luxtts|chatterbox|chatterbox_turbo|tada)$")
engine: Optional[str] = Field(default="qwen", pattern="^(qwen|qwen_custom_voice|luxtts|chatterbox|chatterbox_turbo|tada|kokoro)$")
max_chunk_chars: int = Field(
default=800, ge=100, le=5000, description="Max characters per chunk for long text splitting"
)
@@ -172,6 +182,7 @@ class HealthResponse(BaseModel):
vram_used_mb: Optional[float] = None
backend_type: Optional[str] = None # Backend type (mlx or pytorch)
backend_variant: Optional[str] = None # Binary variant (cpu or cuda)
gpu_compatibility_warning: Optional[str] = None # Warning if GPU arch unsupported
class DirectoryCheck(BaseModel):
+95
View File
@@ -0,0 +1,95 @@
"""
PyInstaller runtime hook: numpy 2.x / torch ABI mismatch fix.
Problem
-------
torch is compiled against numpy 1.x headers. numpy 2.x changed the version
number returned by PyArray_GetNDArrayCVersion() (0x01000009 → 0x02000000),
so torch's is_numpy_available() returns False and every torch.from_numpy()
call raises:
RuntimeError: Numpy is not available
This surfaces as:
ValueError: Unable to create tensor, you should probably activate
padding with 'padding=True'
during TTS generation (EncodecFeatureExtractor → BatchFeature.convert_to_tensors).
Fix
---
Runtime hooks execute after PyInstaller's FrozenImporter is registered, so
frozen torch/numpy are importable here. We start a background thread that
waits for torch to finish loading then wraps torch.from_numpy with a ctypes
memmove fallback that bypasses the C-level numpy ABI check entirely.
This approach works with any numpy version and is safer than binary-patching
libtorch_python.dylib (which risks PyArray_Descr struct layout mismatches).
"""
import sys
import threading
def _patch_torch_from_numpy():
import time
for _ in range(7200): # poll up to 360 s at 50 ms intervals
time.sleep(0.05)
torch = sys.modules.get("torch")
if torch is None or not hasattr(torch, "from_numpy"):
continue
if getattr(torch, "_vb_from_numpy_patched", False):
return
try:
import ctypes
import numpy as np
_orig = torch.from_numpy
# Explicit numpy → torch dtype map. Silent fallback to float32 on
# unknown dtypes would reinterpret the memcpy'd bytes as fp32 and
# silently corrupt data (e.g. fp16 tensors from some TTS engines),
# so we raise instead.
dtype_map = {
"float16": _t.float16,
"float32": _t.float32,
"float64": _t.float64,
"int8": _t.int8,
"int16": _t.int16,
"int32": _t.int32,
"int64": _t.int64,
"uint8": _t.uint8,
"bool": _t.bool,
"complex64": _t.complex64,
"complex128": _t.complex128,
}
def _safe_from_numpy(
arr, _orig=_orig, _c=ctypes, _np=np, _t=torch, _map=dtype_map
):
try:
return _orig(arr)
except RuntimeError:
a = _np.ascontiguousarray(arr)
key = str(a.dtype)
if key not in _map:
raise TypeError(
f"pyi_rth_numpy_compat: unsupported numpy dtype "
f"{key!r} in torch.from_numpy fallback; add an "
f"explicit mapping rather than silently copying "
f"bytes into the wrong dtype."
)
out = _t.empty(list(a.shape), dtype=_map[key])
_c.memmove(out.data_ptr(), a.ctypes.data, a.nbytes)
return out
torch.from_numpy = _safe_from_numpy
torch._vb_from_numpy_patched = True
except Exception:
pass
return
threading.Thread(target=_patch_torch_from_numpy, daemon=True).start()
+9 -2
View File
@@ -8,7 +8,7 @@ sqlalchemy>=2.0.0
alembic>=1.13.0
# ML models
torch>=2.1.0
torch>=2.2.0
transformers>=4.36.0,<=4.57.6
accelerate>=0.26.0
huggingface_hub>=0.20.0
@@ -40,10 +40,17 @@ pyloudnorm
# provides the only class TADA uses: Snake1d.)
torchaudio
# Kokoro TTS (lightweight 82M-param engine)
kokoro>=0.9.4
misaki[en,ja,zh]>=0.9.4
# spacy model for misaki English G2P — must be pre-installed or misaki
# tries spacy.cli.download() at runtime which crashes frozen builds
en_core_web_sm @ https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.8.0/en_core_web_sm-3.8.0-py3-none-any.whl
# Audio processing
librosa>=0.10.0
soundfile>=0.12.0
numpy>=1.24.0
numpy>=1.24.0,<2.0
numba>=0.60.0,<0.61.0
pedalboard>=0.9.0
+7 -9
View File
@@ -1,12 +1,10 @@
"""Audio file serving endpoints."""
from pathlib import Path
from fastapi import APIRouter, Depends, HTTPException
from fastapi.responses import FileResponse
from sqlalchemy.orm import Session
from .. import models
from .. import config, models
from ..services import history
from ..database import get_db
@@ -22,8 +20,8 @@ async def get_version_audio(version_id: str, db: Session = Depends(get_db)):
if not version:
raise HTTPException(status_code=404, detail="Version not found")
audio_path = Path(version.audio_path)
if not audio_path.exists():
audio_path = config.resolve_storage_path(version.audio_path)
if audio_path is None or not audio_path.exists():
raise HTTPException(status_code=404, detail="Audio file not found")
return FileResponse(
@@ -40,8 +38,8 @@ async def get_audio(generation_id: str, db: Session = Depends(get_db)):
if not generation:
raise HTTPException(status_code=404, detail="Generation not found")
audio_path = Path(generation.audio_path)
if not audio_path.exists():
audio_path = config.resolve_storage_path(generation.audio_path)
if audio_path is None or not audio_path.exists():
raise HTTPException(status_code=404, detail="Audio file not found")
return FileResponse(
@@ -60,8 +58,8 @@ async def get_sample_audio(sample_id: str, db: Session = Depends(get_db)):
if not sample:
raise HTTPException(status_code=404, detail="Sample not found")
audio_path = Path(sample.audio_path)
if not audio_path.exists():
audio_path = config.resolve_storage_path(sample.audio_path)
if audio_path is None or not audio_path.exists():
raise HTTPException(status_code=404, detail="Audio file not found")
return FileResponse(
+7 -6
View File
@@ -3,7 +3,6 @@
import asyncio
import io
import uuid
from pathlib import Path
from fastapi import APIRouter, Depends, HTTPException
from fastapi.responses import StreamingResponse
@@ -41,10 +40,11 @@ async def preview_effects(
all_versions = versions_mod.list_versions(generation_id, db)
clean_version = next((v for v in all_versions if v.effects_chain is None), None)
source_path = clean_version.audio_path if clean_version else gen.audio_path
if not source_path or not Path(source_path).exists():
resolved_source_path = config.resolve_storage_path(source_path)
if resolved_source_path is None or not resolved_source_path.exists():
raise HTTPException(status_code=404, detail="Source audio file not found")
audio, sample_rate = await asyncio.to_thread(load_audio, source_path)
audio, sample_rate = await asyncio.to_thread(load_audio, str(resolved_source_path))
processed = await asyncio.to_thread(apply_effects, audio, sample_rate, chain_dicts)
import soundfile as sf
@@ -193,10 +193,11 @@ async def apply_effects_to_generation(
source_path = clean_version.audio_path
source_version_id = clean_version.id
if not source_path or not Path(source_path).exists():
resolved_source_path = config.resolve_storage_path(source_path)
if resolved_source_path is None or not resolved_source_path.exists():
raise HTTPException(status_code=404, detail="Source audio file not found")
audio, sample_rate = await asyncio.to_thread(load_audio, source_path)
audio, sample_rate = await asyncio.to_thread(load_audio, str(resolved_source_path))
processed_audio = await asyncio.to_thread(apply_effects, audio, sample_rate, chain_dicts)
version_id = str(uuid.uuid4())
@@ -208,7 +209,7 @@ async def apply_effects_to_generation(
version = versions_mod.create_version(
generation_id=generation_id,
label=label,
audio_path=str(processed_path),
audio_path=config.to_storage_path(processed_path),
db=db,
effects_chain=chain_dicts,
is_default=data.set_as_default,
+31 -2
View File
@@ -20,6 +20,10 @@ from ..utils.tasks import get_task_manager
router = APIRouter()
def _resolve_generation_engine(data: models.GenerationRequest, profile) -> str:
return data.engine or getattr(profile, "default_engine", None) or getattr(profile, "preset_engine", None) or "qwen"
@router.post("/generate", response_model=models.GenerationResponse)
async def generate_speech(
data: models.GenerationRequest,
@@ -35,7 +39,12 @@ async def generate_speech(
from ..backends import engine_has_model_sizes
engine = data.engine or "qwen"
engine = _resolve_generation_engine(data, profile)
try:
profiles.validate_profile_engine(profile, engine)
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e))
model_size = (data.model_size or "1.7B") if engine_has_model_sizes(engine) else None
generation = await history.create_generation(
@@ -230,7 +239,11 @@ async def stream_speech(
if not profile:
raise HTTPException(status_code=404, detail="Profile not found")
engine = data.engine or "qwen"
engine = _resolve_generation_engine(data, profile)
try:
profiles.validate_profile_engine(profile, engine)
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e))
tts_model = get_tts_backend_for_engine(engine)
model_size = data.model_size or "1.7B"
@@ -263,6 +276,22 @@ async def stream_speech(
trim_fn=trim_fn,
)
effects_chain_config = None
if data.effects_chain is not None:
effects_chain_config = [e.model_dump() for e in data.effects_chain]
elif profile.effects_chain:
import json as _json
try:
effects_chain_config = _json.loads(profile.effects_chain)
except Exception:
effects_chain_config = None
if effects_chain_config:
from ..utils.effects import apply_effects
audio = apply_effects(audio, sample_rate, effects_chain_config)
if data.normalize:
from ..utils.audio import normalize_audio
+16 -1
View File
@@ -93,6 +93,12 @@ async def health():
except ImportError:
pass
gpu_compat_warning = None
if has_cuda:
from ..backends.base import check_cuda_compatibility
_compatible, gpu_compat_warning = check_cuda_compatibility()
gpu_available = has_cuda or has_mps or has_xpu or has_directml or backend_type == "mlx"
gpu_type = None
@@ -110,6 +116,11 @@ async def health():
vram_used = None
if has_cuda:
vram_used = torch.cuda.memory_allocated() / 1024 / 1024
elif has_xpu:
try:
vram_used = torch.xpu.memory_allocated() / 1024 / 1024
except Exception:
pass # memory_allocated() may not be available on all IPEX versions
model_loaded = False
model_size = None
@@ -162,7 +173,11 @@ async def health():
gpu_type=gpu_type,
vram_used_mb=vram_used,
backend_type=backend_type,
backend_variant=os.environ.get("VOICEBOX_BACKEND_VARIANT", "cuda" if torch.cuda.is_available() else "cpu"),
backend_variant=os.environ.get(
"VOICEBOX_BACKEND_VARIANT",
"cuda" if torch.cuda.is_available() else ("xpu" if has_xpu else "cpu"),
),
gpu_compatibility_warning=gpu_compat_warning,
)
+15 -4
View File
@@ -1,13 +1,12 @@
"""Generation history endpoints."""
import io
from pathlib import Path
from fastapi import APIRouter, Depends, File, HTTPException, UploadFile
from fastapi.responses import FileResponse, StreamingResponse
from sqlalchemy.orm import Session
from .. import models
from .. import config, models
from ..services import export_import, history
from ..app import safe_content_disposition
from ..database import Generation as DBGeneration, VoiceProfile as DBVoiceProfile, get_db
@@ -63,6 +62,13 @@ async def import_generation(
raise HTTPException(status_code=500, detail=str(e))
@router.delete("/history/failed")
async def clear_failed_generations(db: Session = Depends(get_db)):
"""Delete every generation with status='failed'. Used by the UI's 'Clear failed' button (#410)."""
count = await history.delete_failed_generations(db)
return {"deleted": count}
@router.get("/history/{generation_id}", response_model=models.HistoryResponse)
async def get_generation(
generation_id: str,
@@ -90,6 +96,11 @@ async def get_generation(
duration=gen.duration,
seed=gen.seed,
instruct=gen.instruct,
engine=gen.engine or "qwen",
model_size=gen.model_size,
status=gen.status or "completed",
error=gen.error,
is_favorited=bool(gen.is_favorited),
created_at=gen.created_at,
)
@@ -162,8 +173,8 @@ async def export_generation_audio(
if not generation.audio_path:
raise HTTPException(status_code=404, detail="Generation has no audio file")
audio_path = Path(generation.audio_path)
if not audio_path.is_file():
audio_path = config.resolve_storage_path(generation.audio_path)
if audio_path is None or not audio_path.is_file():
raise HTTPException(status_code=404, detail="Audio file not found")
safe_text = "".join(c for c in generation.text[:30] if c.isalnum() or c in (" ", "-", "_")).strip()
+46 -4
View File
@@ -1,6 +1,8 @@
"""Voice profile endpoints."""
import io
import json as _json
import logging
import tempfile
from datetime import datetime
from pathlib import Path
@@ -15,6 +17,8 @@ from ..database import VoiceProfile as DBVoiceProfile, get_db
from ..services import channels, export_import, profiles
from ..services.profiles import _profile_to_response
logger = logging.getLogger(__name__)
router = APIRouter()
@@ -62,6 +66,46 @@ async def import_profile(
raise HTTPException(status_code=500, detail=str(e))
# ── Preset Voice Endpoints ───────────────────────────────────────────
# These MUST be declared before /profiles/{profile_id} to avoid the
# wildcard swallowing "presets" as a profile_id.
@router.get("/profiles/presets/{engine}")
async def list_preset_voices(engine: str):
"""List available preset voices for an engine."""
if engine == "kokoro":
from ..backends.kokoro_backend import KOKORO_VOICES
return {
"engine": engine,
"voices": [
{
"voice_id": vid,
"name": name,
"gender": gender,
"language": lang,
}
for vid, name, gender, lang in KOKORO_VOICES
],
}
if engine == "qwen_custom_voice":
from ..backends.qwen_custom_voice_backend import QWEN_CUSTOM_VOICES
return {
"engine": engine,
"voices": [
{
"voice_id": speaker_id,
"name": display_name,
"gender": gender,
"language": lang,
}
for speaker_id, display_name, gender, lang, _desc in QWEN_CUSTOM_VOICES
],
}
return {"engine": engine, "voices": []}
@router.get("/profiles/{profile_id}", response_model=models.VoiceProfileResponse)
async def get_profile(
profile_id: str,
@@ -215,8 +259,8 @@ async def get_profile_avatar(
if not profile.avatar_path:
raise HTTPException(status_code=404, detail="No avatar found for this profile")
avatar_path = Path(profile.avatar_path)
if not avatar_path.exists():
avatar_path = config.resolve_storage_path(profile.avatar_path)
if avatar_path is None or not avatar_path.exists():
raise HTTPException(status_code=404, detail="Avatar file not found")
return FileResponse(avatar_path)
@@ -297,8 +341,6 @@ async def update_profile_effects(
db: Session = Depends(get_db),
):
"""Set or clear the default effects chain for a voice profile."""
import json as _json
profile = db.query(DBVoiceProfile).filter_by(id=profile_id).first()
if not profile:
raise HTTPException(status_code=404, detail="Profile not found")
+30
View File
@@ -105,6 +105,11 @@ def _start_parent_watchdog(parent_pid, data_dir=None):
This is the clean shutdown mechanism: instead of the Tauri app trying to
forcefully kill the server (which spawns console windows on Windows),
the server monitors its parent and shuts itself down gracefully.
The Tauri app writes a .keep-running sentinel file to data_dir before
exiting when "remain running after close" is enabled. This is a reliable
fallback for the HTTP /watchdog/disable request, which can race with
process exit on Windows.
"""
import os
import signal
@@ -164,6 +169,19 @@ def _start_parent_watchdog(parent_pid, data_dir=None):
if not alive:
watchdog_logger.warning(f"Parent PID {parent_pid} not found on first check — disabling watchdog")
return
# Clear any stale .keep-running sentinel from a previous session. The
# sentinel is only removed by the watchdog when it's consumed during a
# grace period; if the HTTP /watchdog/disable path wins the race on a
# "keep running" exit, the sentinel is left on disk. Wipe it here so a
# future session can't inherit that stale signal.
if data_dir:
stale = os.path.join(data_dir, ".keep-running")
if os.path.exists(stale):
try:
os.remove(stale)
watchdog_logger.info("Removed stale .keep-running sentinel from previous session")
except OSError as e:
watchdog_logger.warning(f"Failed to remove stale sentinel: {e}")
while True:
if _watchdog_disabled:
watchdog_logger.info("Watchdog disabled (keep server running), stopping monitor")
@@ -178,6 +196,18 @@ def _start_parent_watchdog(parent_pid, data_dir=None):
if _watchdog_disabled:
watchdog_logger.info("Watchdog was disabled during grace period, keeping server alive")
return
# Check for sentinel file written by Tauri before exit.
# This catches the case where the HTTP disable request
# didn't arrive before the parent process died (common
# on Windows where process teardown is fast).
sentinel = os.path.join(data_dir, ".keep-running") if data_dir else None
if sentinel and os.path.exists(sentinel):
watchdog_logger.info("Found .keep-running sentinel file, keeping server alive")
try:
os.remove(sentinel)
except OSError:
pass
return
watchdog_logger.info("Watchdog still enabled after grace period, shutting down server...")
if sys.platform == "win32":
# sys.exit triggers SystemExit, allowing uvicorn to run
+17 -1
View File
@@ -11,6 +11,7 @@ Both archives are extracted into {data_dir}/backends/cuda/ which forms the
complete PyInstaller --onedir directory structure that torch expects.
"""
import asyncio
import hashlib
import json
import logging
@@ -32,7 +33,13 @@ PROGRESS_KEY = "cuda-backend"
# The current expected CUDA libs version. Bump this when we change the
# CUDA toolkit version or torch's CUDA dependency changes (e.g. cu126 -> cu128).
CUDA_LIBS_VERSION = "cu126-v1"
CUDA_LIBS_VERSION = "cu128-v1"
# Prevents concurrent download_cuda_binary() calls from racing on the same
# temp file. The auto-update background task and the manual HTTP endpoint
# can both invoke download_cuda_binary(); without this lock the progress-
# manager status check is a TOCTOU race.
_download_lock = asyncio.Lock()
def get_backends_dir() -> Path:
@@ -241,6 +248,15 @@ async def download_cuda_binary(version: Optional[str] = None):
Args:
version: Version tag (e.g. "v0.3.0"). Defaults to current app version.
"""
if _download_lock.locked():
logger.info("CUDA download already in progress, skipping duplicate request")
return
async with _download_lock:
await _download_cuda_binary_locked(version)
async def _download_cuda_binary_locked(version: Optional[str] = None):
"""Inner implementation of download_cuda_binary, called under _download_lock."""
import httpx
if version is None:
+2 -2
View File
@@ -11,6 +11,8 @@ from typing import List, Optional
from sqlalchemy.orm import Session
from sqlalchemy.exc import IntegrityError
from ..utils.effects import validate_effects_chain
from ..database import EffectPreset as DBEffectPreset
from ..models import EffectPresetResponse, EffectPresetCreate, EffectPresetUpdate, EffectConfig
@@ -52,7 +54,6 @@ def get_preset_by_name(name: str, db: Session) -> Optional[EffectPresetResponse]
def create_preset(data: EffectPresetCreate, db: Session) -> EffectPresetResponse:
"""Create a new user effect preset."""
from .utils.effects import validate_effects_chain
chain_dicts = [e.model_dump() for e in data.effects_chain]
error = validate_effects_chain(chain_dicts)
@@ -94,7 +95,6 @@ def update_preset(preset_id: str, data: EffectPresetUpdate, db: Session) -> Opti
if data.description is not None:
preset.description = data.description
if data.effects_chain is not None:
from .utils.effects import validate_effects_chain
chain_dicts = [e.model_dump() for e in data.effects_chain]
error = validate_effects_chain(chain_dicts)
+11 -9
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@@ -73,8 +73,8 @@ def export_profile_to_zip(profile_id: str, db: Session) -> bytes:
# Check if profile has avatar
has_avatar = False
if profile.avatar_path:
avatar_path = Path(profile.avatar_path)
if avatar_path.exists():
avatar_path = config.resolve_storage_path(profile.avatar_path)
if avatar_path is not None and avatar_path.exists():
has_avatar = True
# Add avatar to ZIP root with original extension
avatar_ext = avatar_path.suffix
@@ -98,7 +98,9 @@ def export_profile_to_zip(profile_id: str, db: Session) -> bytes:
for sample in samples:
# Get filename from audio_path (should be {sample_id}.wav)
audio_path = Path(sample.audio_path)
audio_path = config.resolve_storage_path(sample.audio_path)
if audio_path is None:
raise ValueError(f"Audio file not found: {sample.audio_path}")
filename = audio_path.name
# Read audio file
@@ -279,7 +281,7 @@ def export_generation_to_zip(generation_id: str, db: Session) -> bytes:
# Build version manifest entries
version_entries = []
for v in versions:
v_path = Path(v.audio_path)
v_path = config.resolve_storage_path(v.audio_path)
effects_chain = None
if v.effects_chain:
effects_chain = json.loads(v.effects_chain)
@@ -314,14 +316,14 @@ def export_generation_to_zip(generation_id: str, db: Session) -> bytes:
# Add all version audio files
for v in versions:
v_path = Path(v.audio_path)
if v_path.exists():
v_path = config.resolve_storage_path(v.audio_path)
if v_path is not None and v_path.exists():
zip_file.write(v_path, f"audio/{v_path.name}")
# Fallback: if no versions exist, include the generation's main audio
if not versions:
audio_path = Path(generation.audio_path)
if audio_path.exists():
audio_path = config.resolve_storage_path(generation.audio_path)
if audio_path is not None and audio_path.exists():
zip_file.write(audio_path, f"audio/{audio_path.name}")
zip_buffer.seek(0)
@@ -426,7 +428,7 @@ async def import_generation_from_zip(file_bytes: bytes, db: Session) -> dict:
profile_id=profile_id,
text=generation_data["text"],
language=generation_data["language"],
audio_path=str(audio_dest),
audio_path=config.to_storage_path(audio_dest),
duration=generation_data["duration"],
seed=generation_data.get("seed"),
instruct=generation_data.get("instruct"),
+8 -6
View File
@@ -163,7 +163,7 @@ def _save_generate(
versions_mod.create_version(
generation_id=generation_id,
label="original",
audio_path=str(clean_audio_path),
audio_path=config.to_storage_path(clean_audio_path),
db=db,
effects_chain=None,
is_default=not has_effects,
@@ -174,6 +174,8 @@ def _save_generate(
if has_effects:
from ..utils.effects import apply_effects, validate_effects_chain
assert effects_chain is not None
error_msg = validate_effects_chain(effects_chain)
if error_msg:
import logging
@@ -189,13 +191,13 @@ def _save_generate(
versions_mod.create_version(
generation_id=generation_id,
label="version-2",
audio_path=str(processed_path),
audio_path=config.to_storage_path(processed_path),
db=db,
effects_chain=effects_chain,
is_default=True,
)
return final_audio_path
return config.to_storage_path(final_audio_path)
def _save_retry(
@@ -211,7 +213,7 @@ def _save_retry(
"""
audio_path = config.get_generations_dir() / f"{generation_id}.wav"
save_audio(audio, str(audio_path), sample_rate)
return str(audio_path)
return config.to_storage_path(audio_path)
def _save_regenerate(
@@ -244,10 +246,10 @@ def _save_regenerate(
versions_mod.create_version(
generation_id=generation_id,
label=label,
audio_path=str(audio_path),
audio_path=config.to_storage_path(audio_path),
db=db,
effects_chain=None,
is_default=True,
)
return str(audio_path)
return config.to_storage_path(audio_path)
+41 -4
View File
@@ -253,8 +253,8 @@ async def delete_generation(
# Delete main audio file (if not already removed by version cleanup)
if generation.audio_path:
audio_path = Path(generation.audio_path)
if audio_path.exists():
audio_path = config.resolve_storage_path(generation.audio_path)
if audio_path is not None and audio_path.exists():
audio_path.unlink()
# Delete from database
@@ -264,6 +264,43 @@ async def delete_generation(
return True
async def delete_failed_generations(db: Session) -> int:
"""
Delete every generation whose status is 'failed'.
Used by the "Clear failed" action in the UI so users can tidy up
history after the model wasn't loaded, the app was closed mid-run,
or a generation otherwise errored out (see issue #410).
Returns:
Number of generations deleted.
"""
from . import versions as versions_mod
failed = db.query(DBGeneration).filter(DBGeneration.status == "failed").all()
count = 0
for generation in failed:
# Clean up version files/rows first.
versions_mod.delete_versions_for_generation(generation.id, db)
# Remove the main audio file if it somehow made it to disk.
if generation.audio_path:
audio_path = config.resolve_storage_path(generation.audio_path)
if audio_path is not None and audio_path.exists():
try:
audio_path.unlink()
except OSError:
# Best-effort cleanup — don't abort the whole sweep
# if a single file can't be removed.
pass
db.delete(generation)
count += 1
db.commit()
return count
async def delete_generations_by_profile(
profile_id: str,
db: Session,
@@ -283,8 +320,8 @@ async def delete_generations_by_profile(
count = 0
for generation in generations:
# Delete audio file
audio_path = Path(generation.audio_path)
if audio_path.exists():
audio_path = config.resolve_storage_path(generation.audio_path)
if audio_path is not None and audio_path.exists():
audio_path.unlink()
# Delete from database
+219 -59
View File
@@ -1,33 +1,30 @@
"""
Voice profile management module.
"""
"""Voice profile management module."""
from typing import List, Optional
from datetime import datetime
import uuid
import json as _json
import logging
import shutil
import uuid
from datetime import datetime
from pathlib import Path
from sqlalchemy.orm import Session
from sqlalchemy import func, select
from sqlalchemy import func
from sqlalchemy.orm import Session
from .. import config
from ..database import Generation as DBGeneration, ProfileSample as DBProfileSample, VoiceProfile as DBVoiceProfile
from ..models import (
EffectConfig,
ProfileSampleResponse,
VoiceProfileCreate,
VoiceProfileResponse,
ProfileSampleCreate,
ProfileSampleResponse,
)
from ..database import (
VoiceProfile as DBVoiceProfile,
ProfileSample as DBProfileSample,
Generation as DBGeneration,
)
from ..models import EffectConfig
from ..utils.audio import validate_reference_audio, validate_and_load_reference_audio, load_audio, save_audio
from ..utils.images import validate_image, process_avatar
from ..utils.audio import save_audio, validate_and_load_reference_audio
from ..utils.cache import _get_cache_dir, clear_profile_cache
from .tts import get_tts_model
from .. import config
import json as _json
from ..utils.images import process_avatar, validate_image
logger = logging.getLogger(__name__)
CLONING_ENGINES = {"qwen", "luxtts", "chatterbox", "chatterbox_turbo", "tada"}
def _profile_to_response(
@@ -52,6 +49,11 @@ def _profile_to_response(
language=profile.language,
avatar_path=profile.avatar_path,
effects_chain=effects_chain,
voice_type=getattr(profile, "voice_type", None) or "cloned",
preset_engine=getattr(profile, "preset_engine", None),
preset_voice_id=getattr(profile, "preset_voice_id", None),
design_prompt=getattr(profile, "design_prompt", None),
default_engine=getattr(profile, "default_engine", None),
generation_count=generation_count,
sample_count=sample_count,
created_at=profile.created_at,
@@ -59,6 +61,79 @@ def _profile_to_response(
)
def _get_preset_voice_ids(engine: str) -> set[str]:
if engine == "kokoro":
from ..backends.kokoro_backend import KOKORO_VOICES
return {voice_id for voice_id, _name, _gender, _lang in KOKORO_VOICES}
if engine == "qwen_custom_voice":
from ..backends.qwen_custom_voice_backend import QWEN_CUSTOM_VOICES
return {voice_id for voice_id, _name, _gender, _lang, _desc in QWEN_CUSTOM_VOICES}
return set()
def _validate_profile_fields(
*,
voice_type: str,
preset_engine: str | None,
preset_voice_id: str | None,
design_prompt: str | None,
default_engine: str | None,
) -> str | None:
if voice_type == "preset":
if not preset_engine or not preset_voice_id:
return "Preset profiles require both preset_engine and preset_voice_id"
if default_engine and default_engine != preset_engine:
return "Preset profiles must use their preset_engine as default_engine"
available_voice_ids = _get_preset_voice_ids(preset_engine)
if available_voice_ids and preset_voice_id not in available_voice_ids:
return f"Preset voice '{preset_voice_id}' is not valid for engine '{preset_engine}'"
return None
if voice_type == "designed":
if not design_prompt or not design_prompt.strip():
return "Designed profiles require a design_prompt"
if preset_engine or preset_voice_id:
return "Designed profiles cannot set preset_engine or preset_voice_id"
return None
if preset_engine or preset_voice_id:
return "Cloned profiles cannot set preset_engine or preset_voice_id"
if design_prompt:
return "Cloned profiles cannot set design_prompt"
if default_engine and default_engine not in CLONING_ENGINES:
return f"Cloned profiles cannot use default engine '{default_engine}'"
return None
def validate_profile_engine(profile, engine: str) -> None:
voice_type = getattr(profile, "voice_type", None) or "cloned"
if voice_type == "preset":
preset_engine = getattr(profile, "preset_engine", None)
preset_voice_id = getattr(profile, "preset_voice_id", None)
if not preset_engine or not preset_voice_id:
raise ValueError(f"Preset profile {profile.id} is missing preset engine metadata")
if preset_engine != engine:
raise ValueError(
f"Preset profile {profile.id} only supports engine '{preset_engine}', not '{engine}'"
)
return
if voice_type == "designed":
design_prompt = getattr(profile, "design_prompt", None)
if not design_prompt or not design_prompt.strip():
raise ValueError(f"Designed profile {profile.id} is missing design_prompt")
return
if engine not in CLONING_ENGINES:
raise ValueError(f"Engine '{engine}' does not support cloned voice profiles")
async def create_profile(
data: VoiceProfileCreate,
db: Session,
@@ -80,11 +155,32 @@ async def create_profile(
if existing_profile:
raise ValueError(f"A profile with the name '{data.name}' already exists. Please choose a different name.")
# Auto-set default_engine for preset profiles
default_engine = data.default_engine
voice_type = data.voice_type or "cloned"
if voice_type == "preset" and data.preset_engine and not default_engine:
default_engine = data.preset_engine
validation_error = _validate_profile_fields(
voice_type=voice_type,
preset_engine=data.preset_engine,
preset_voice_id=data.preset_voice_id,
design_prompt=data.design_prompt,
default_engine=default_engine,
)
if validation_error:
raise ValueError(validation_error)
db_profile = DBVoiceProfile(
id=str(uuid.uuid4()),
name=data.name,
description=data.description,
language=data.language,
voice_type=voice_type,
preset_engine=data.preset_engine,
preset_voice_id=data.preset_voice_id,
design_prompt=data.design_prompt,
default_engine=default_engine,
created_at=datetime.utcnow(),
updated_at=datetime.utcnow(),
)
@@ -140,7 +236,7 @@ async def add_profile_sample(
db_sample = DBProfileSample(
id=sample_id,
profile_id=profile_id,
audio_path=str(dest_path),
audio_path=config.to_storage_path(dest_path),
reference_text=reference_text,
)
@@ -161,7 +257,7 @@ async def add_profile_sample(
async def get_profile(
profile_id: str,
db: Session,
) -> Optional[VoiceProfileResponse]:
) -> VoiceProfileResponse | None:
"""
Get a voice profile by ID.
@@ -182,7 +278,7 @@ async def get_profile(
async def get_profile_samples(
profile_id: str,
db: Session,
) -> List[ProfileSampleResponse]:
) -> list[ProfileSampleResponse]:
"""
Get all samples for a profile.
@@ -197,7 +293,7 @@ async def get_profile_samples(
return [ProfileSampleResponse.model_validate(s) for s in samples]
async def list_profiles(db: Session) -> List[VoiceProfileResponse]:
async def list_profiles(db: Session) -> list[VoiceProfileResponse]:
"""
List all voice profiles with generation and sample counts.
@@ -238,7 +334,7 @@ async def update_profile(
profile_id: str,
data: VoiceProfileCreate,
db: Session,
) -> Optional[VoiceProfileResponse]:
) -> VoiceProfileResponse | None:
"""
Update a voice profile.
@@ -262,9 +358,27 @@ async def update_profile(
if existing_profile:
raise ValueError(f"A profile with the name '{data.name}' already exists. Please choose a different name.")
voice_type = getattr(profile, "voice_type", None) or "cloned"
preset_engine = getattr(profile, "preset_engine", None)
preset_voice_id = getattr(profile, "preset_voice_id", None)
design_prompt = getattr(profile, "design_prompt", None)
default_engine = data.default_engine if data.default_engine is not None else getattr(profile, "default_engine", None)
validation_error = _validate_profile_fields(
voice_type=voice_type,
preset_engine=preset_engine,
preset_voice_id=preset_voice_id,
design_prompt=design_prompt,
default_engine=default_engine,
)
if validation_error:
raise ValueError(validation_error)
profile.name = data.name
profile.description = data.description
profile.language = data.language
if data.default_engine is not None:
profile.default_engine = data.default_engine or None # empty string → NULL
profile.updated_at = datetime.utcnow()
db.commit()
@@ -327,8 +441,8 @@ async def delete_profile_sample(
# Store profile_id before deleting
profile_id = sample.profile_id
audio_path = Path(sample.audio_path)
if audio_path.exists():
audio_path = config.resolve_storage_path(sample.audio_path)
if audio_path is not None and audio_path.exists():
audio_path.unlink()
db.delete(sample)
@@ -345,7 +459,7 @@ async def update_profile_sample(
sample_id: str,
reference_text: str,
db: Session,
) -> Optional[ProfileSampleResponse]:
) -> ProfileSampleResponse | None:
"""
Update a profile sample's reference text.
@@ -382,19 +496,57 @@ async def create_voice_prompt_for_profile(
engine: str = "qwen",
) -> dict:
"""
Create a combined voice prompt from all samples in a profile.
Create a voice prompt from a profile.
For cloned profiles: combines all audio samples into a voice prompt.
For preset profiles: returns the engine-specific preset voice reference.
For designed profiles: returns the text design prompt (future).
Args:
profile_id: Profile ID
db: Database session
use_cache: Whether to use cached prompts
engine: TTS engine to create prompt for ("qwen" or "luxtts")
engine: TTS engine to create prompt for
Returns:
Voice prompt dictionary
"""
from ..backends import get_tts_backend_for_engine
profile = db.query(DBVoiceProfile).filter_by(id=profile_id).first()
if not profile:
raise ValueError(f"Profile not found: {profile_id}")
voice_type = getattr(profile, "voice_type", None) or "cloned"
validate_profile_engine(profile, engine)
# ── Preset profiles: return engine-specific voice reference ──
if voice_type == "preset":
if not profile.preset_engine or not profile.preset_voice_id:
raise ValueError(f"Preset profile {profile_id} is missing preset engine metadata")
if profile.preset_engine != engine:
raise ValueError(
f"Preset profile {profile_id} only supports engine '{profile.preset_engine}', not '{engine}'"
)
return {
"voice_type": "preset",
"preset_engine": profile.preset_engine,
"preset_voice_id": profile.preset_voice_id,
}
# ── Designed profiles: return text description (future) ──
if voice_type == "designed":
if not profile.design_prompt or not profile.design_prompt.strip():
raise ValueError(f"Designed profile {profile_id} is missing design_prompt")
return {
"voice_type": "designed",
"design_prompt": profile.design_prompt,
}
if engine not in CLONING_ENGINES:
raise ValueError(f"Engine '{engine}' does not support cloned voice profiles")
# ── Cloned profiles: create from audio samples ──
samples = db.query(DBProfileSample).filter_by(profile_id=profile_id).all()
if not samples:
@@ -404,40 +556,48 @@ async def create_voice_prompt_for_profile(
if len(samples) == 1:
sample = samples[0]
sample_audio_path = config.resolve_storage_path(sample.audio_path)
if sample_audio_path is None:
raise ValueError(f"Sample audio not found for profile {profile_id}")
voice_prompt, _ = await tts_model.create_voice_prompt(
sample.audio_path,
str(sample_audio_path),
sample.reference_text,
use_cache=use_cache,
)
return voice_prompt
else:
audio_paths = [s.audio_path for s in samples]
reference_texts = [s.reference_text for s in samples]
combined_audio, combined_text = await tts_model.combine_voice_prompts(
audio_paths,
reference_texts,
)
audio_paths = []
for sample in samples:
sample_audio_path = config.resolve_storage_path(sample.audio_path)
if sample_audio_path is None:
raise ValueError(f"Sample audio not found for profile {profile_id}")
audio_paths.append(str(sample_audio_path))
reference_texts = [s.reference_text for s in samples]
# Save combined audio to cache directory (persistent)
# Create a hash of sample IDs to identify this specific combination
import hashlib
combined_audio, combined_text = await tts_model.combine_voice_prompts(
audio_paths,
reference_texts,
)
sample_ids_str = "-".join(sorted([s.id for s in samples]))
combination_hash = hashlib.md5(sample_ids_str.encode()).hexdigest()[:12]
# Save combined audio to cache directory (persistent)
# Create a hash of sample IDs to identify this specific combination
import hashlib
cache_dir = _get_cache_dir()
cache_dir.mkdir(parents=True, exist_ok=True)
combined_path = cache_dir / f"combined_{profile_id}_{combination_hash}.wav"
sample_ids_str = "-".join(sorted([s.id for s in samples]))
combination_hash = hashlib.md5(sample_ids_str.encode()).hexdigest()[:12]
save_audio(combined_audio, str(combined_path), 24000)
cache_dir = _get_cache_dir()
cache_dir.mkdir(parents=True, exist_ok=True)
combined_path = cache_dir / f"combined_{profile_id}_{combination_hash}.wav"
voice_prompt, _ = await tts_model.create_voice_prompt(
str(combined_path),
combined_text,
use_cache=use_cache,
)
return voice_prompt
save_audio(combined_audio, str(combined_path), 24000)
voice_prompt, _ = await tts_model.create_voice_prompt(
str(combined_path),
combined_text,
use_cache=use_cache,
)
return voice_prompt
async def upload_avatar(
@@ -465,8 +625,8 @@ async def upload_avatar(
raise ValueError(error_msg)
if profile.avatar_path:
old_avatar = Path(profile.avatar_path)
if old_avatar.exists():
old_avatar = config.resolve_storage_path(profile.avatar_path)
if old_avatar is not None and old_avatar.exists():
old_avatar.unlink()
# Determine file extension from uploaded file
@@ -487,7 +647,7 @@ async def upload_avatar(
process_avatar(image_path, str(output_path))
profile.avatar_path = str(output_path)
profile.avatar_path = config.to_storage_path(output_path)
profile.updated_at = datetime.utcnow()
db.commit()
@@ -514,8 +674,8 @@ async def delete_avatar(
if not profile or not profile.avatar_path:
return False
avatar_path = Path(profile.avatar_path)
if avatar_path.exists():
avatar_path = config.resolve_storage_path(profile.avatar_path)
if avatar_path is not None and avatar_path.exists():
avatar_path.unlink()
profile.avatar_path = None
+6 -3
View File
@@ -10,6 +10,7 @@ from pathlib import Path
from sqlalchemy.orm import Session
from sqlalchemy import func
from .. import config
from ..models import (
StoryCreate,
StoryResponse,
@@ -483,13 +484,15 @@ async def split_story_item(
Returns:
List of two updated item details (original and new) or None if not found/invalid
"""
# Get the item
# Get the item with a row lock to prevent concurrent splits on the
# same clip (e.g. from rapid double-clicks racing each other).
item = (
db.query(DBStoryItem)
.filter_by(
id=item_id,
story_id=story_id,
)
.with_for_update()
.first()
)
if not item:
@@ -826,8 +829,8 @@ async def export_story_audio(
if version:
resolved_audio_path = version.audio_path
audio_path = Path(resolved_audio_path)
if not audio_path.exists():
audio_path = config.resolve_storage_path(resolved_audio_path)
if audio_path is None or not audio_path.exists():
continue
try:
+4 -4
View File
@@ -158,8 +158,8 @@ def delete_version(version_id: str, db: Session) -> bool:
gen_id = version.generation_id
# Delete audio file
audio_path = Path(version.audio_path)
if audio_path.exists():
audio_path = config.resolve_storage_path(version.audio_path)
if audio_path is not None and audio_path.exists():
audio_path.unlink()
db.delete(version)
@@ -193,8 +193,8 @@ def delete_versions_for_generation(generation_id: str, db: Session) -> int:
)
count = 0
for v in versions:
audio_path = Path(v.audio_path)
if audio_path.exists():
audio_path = config.resolve_storage_path(v.audio_path)
if audio_path is not None and audio_path.exists():
audio_path.unlink()
db.delete(v)
count += 1
+1 -1
View File
@@ -64,7 +64,7 @@ def get_cached_voice_prompt(
cache_file = _get_cache_dir() / f"{cache_key}.prompt"
if cache_file.exists():
try:
prompt = torch.load(cache_file)
prompt = torch.load(cache_file, weights_only=True)
_memory_cache[cache_key] = prompt
return prompt
except Exception:
+49 -2
View File
@@ -1,17 +1,64 @@
"""Monkey-patch huggingface_hub to force offline mode with cached models.
Prevents mlx_audio from making network requests when models are already
downloaded. Must be imported BEFORE mlx_audio.
Prevents mlx_audio / transformers from making network requests when models
are already downloaded. Must be imported BEFORE mlx_audio.
"""
import logging
import os
from contextlib import contextmanager
from pathlib import Path
from typing import Optional, Union
logger = logging.getLogger(__name__)
@contextmanager
def force_offline_if_cached(is_cached: bool, model_label: str = ""):
"""Context manager that sets ``HF_HUB_OFFLINE=1`` while loading a cached model.
If *is_cached* is ``False`` the block runs normally (network allowed).
If the offline load raises an error containing "offline" we automatically
retry with network access so a partially-cached model still works.
Args:
is_cached: Whether the model weights are already on disk.
model_label: Human-readable name used in log messages.
"""
if not is_cached:
yield
return
original_value = os.environ.get("HF_HUB_OFFLINE")
os.environ["HF_HUB_OFFLINE"] = "1"
logger.info(
"[offline-guard] %s is cached — forcing HF_HUB_OFFLINE=1",
model_label or "model",
)
try:
yield
except Exception as exc:
if "offline" in str(exc).lower():
logger.warning(
"[offline-guard] Offline load failed for %s, retrying with network: %s",
model_label or "model",
exc,
)
# Restore original env and retry — caller must wrap the load
# inside force_offline_if_cached so retrying here isn't possible.
# Instead, propagate a flag via the exception so the caller can
# decide. For simplicity we just let it fall through to the
# finally block and re-raise.
raise
raise
finally:
if original_value is not None:
os.environ["HF_HUB_OFFLINE"] = original_value
else:
os.environ.pop("HF_HUB_OFFLINE", None)
def patch_huggingface_hub_offline():
"""Monkey-patch huggingface_hub to force offline mode."""
try:
+13 -4
View File
@@ -1,13 +1,11 @@
# -*- mode: python ; coding: utf-8 -*-
from PyInstaller.utils.hooks import collect_data_files
from PyInstaller.utils.hooks import collect_submodules
from PyInstaller.utils.hooks import collect_all
from PyInstaller.utils.hooks import copy_metadata
datas = []
binaries = []
hiddenimports = ['backend', 'backend.main', 'backend.config', 'backend.database', 'backend.models', 'backend.services.profiles', 'backend.services.history', 'backend.services.tts', 'backend.services.transcribe', 'backend.utils.platform_detect', 'backend.backends', 'backend.backends.pytorch_backend', 'backend.utils.audio', 'backend.utils.cache', 'backend.utils.progress', 'backend.utils.hf_progress', 'backend.services.cuda', 'backend.services.effects', 'backend.utils.effects', 'backend.services.versions', 'pedalboard', 'chatterbox', 'chatterbox.tts_turbo', 'chatterbox.mtl_tts', 'backend.backends.chatterbox_backend', 'backend.backends.chatterbox_turbo_backend', 'backend.backends.luxtts_backend', 'zipvoice', 'zipvoice.luxvoice', 'torch', 'transformers', 'fastapi', 'uvicorn', 'sqlalchemy', 'soundfile', 'qwen_tts', 'qwen_tts.inference', 'qwen_tts.inference.qwen3_tts_model', 'qwen_tts.inference.qwen3_tts_tokenizer', 'qwen_tts.core', 'qwen_tts.cli', 'requests', 'pkg_resources.extern', 'backend.backends.mlx_backend', 'mlx', 'mlx.core', 'mlx.nn', 'mlx_audio', 'mlx_audio.tts', 'mlx_audio.stt']
datas += collect_data_files('qwen_tts')
hiddenimports = ['backend', 'backend.main', 'backend.config', 'backend.database', 'backend.models', 'backend.services.profiles', 'backend.services.history', 'backend.services.tts', 'backend.services.transcribe', 'backend.utils.platform_detect', 'backend.backends', 'backend.backends.pytorch_backend', 'backend.backends.qwen_custom_voice_backend', 'backend.utils.audio', 'backend.utils.cache', 'backend.utils.progress', 'backend.utils.hf_progress', 'backend.services.cuda', 'backend.services.effects', 'backend.utils.effects', 'backend.services.versions', 'pedalboard', 'chatterbox', 'chatterbox.tts_turbo', 'chatterbox.mtl_tts', 'backend.backends.chatterbox_backend', 'backend.backends.chatterbox_turbo_backend', 'backend.backends.luxtts_backend', 'zipvoice', 'zipvoice.luxvoice', 'torch', 'transformers', 'fastapi', 'uvicorn', 'sqlalchemy', 'soundfile', 'qwen_tts', 'qwen_tts.inference', 'qwen_tts.inference.qwen3_tts_model', 'qwen_tts.inference.qwen3_tts_tokenizer', 'qwen_tts.core', 'qwen_tts.cli', 'requests', 'pkg_resources.extern', 'backend.backends.hume_backend', 'tada', 'tada.modules', 'tada.modules.tada', 'tada.modules.encoder', 'tada.modules.decoder', 'tada.modules.aligner', 'tada.modules.acoustic_spkr_verf', 'tada.nn', 'tada.nn.vibevoice', 'tada.utils', 'tada.utils.gray_code', 'tada.utils.text', 'backend.utils.dac_shim', 'torchaudio', 'backend.backends.kokoro_backend', 'kokoro', 'kokoro.pipeline', 'kokoro.model', 'kokoro.istftnet', 'kokoro.modules', 'kokoro.custom_stft', 'en_core_web_sm', 'loguru', 'backend.backends.mlx_backend', 'mlx', 'mlx.core', 'mlx.nn', 'mlx_audio', 'mlx_audio.tts', 'mlx_audio.stt']
datas += copy_metadata('qwen-tts')
datas += copy_metadata('requests')
datas += copy_metadata('transformers')
@@ -15,8 +13,9 @@ datas += copy_metadata('huggingface-hub')
datas += copy_metadata('tokenizers')
datas += copy_metadata('safetensors')
datas += copy_metadata('tqdm')
hiddenimports += collect_submodules('qwen_tts')
datas += copy_metadata('en_core_web_sm')
hiddenimports += collect_submodules('jaraco')
hiddenimports += collect_submodules('tada')
hiddenimports += collect_submodules('mlx')
hiddenimports += collect_submodules('mlx_audio')
tmp_ret = collect_all('zipvoice')
@@ -27,12 +26,22 @@ tmp_ret = collect_all('lazy_loader')
datas += tmp_ret[0]; binaries += tmp_ret[1]; hiddenimports += tmp_ret[2]
tmp_ret = collect_all('librosa')
datas += tmp_ret[0]; binaries += tmp_ret[1]; hiddenimports += tmp_ret[2]
tmp_ret = collect_all('qwen_tts')
datas += tmp_ret[0]; binaries += tmp_ret[1]; hiddenimports += tmp_ret[2]
tmp_ret = collect_all('inflect')
datas += tmp_ret[0]; binaries += tmp_ret[1]; hiddenimports += tmp_ret[2]
tmp_ret = collect_all('perth')
datas += tmp_ret[0]; binaries += tmp_ret[1]; hiddenimports += tmp_ret[2]
tmp_ret = collect_all('piper_phonemize')
datas += tmp_ret[0]; binaries += tmp_ret[1]; hiddenimports += tmp_ret[2]
tmp_ret = collect_all('misaki')
datas += tmp_ret[0]; binaries += tmp_ret[1]; hiddenimports += tmp_ret[2]
tmp_ret = collect_all('language_tags')
datas += tmp_ret[0]; binaries += tmp_ret[1]; hiddenimports += tmp_ret[2]
tmp_ret = collect_all('espeakng_loader')
datas += tmp_ret[0]; binaries += tmp_ret[1]; hiddenimports += tmp_ret[2]
tmp_ret = collect_all('en_core_web_sm')
datas += tmp_ret[0]; binaries += tmp_ret[1]; hiddenimports += tmp_ret[2]
tmp_ret = collect_all('mlx')
datas += tmp_ret[0]; binaries += tmp_ret[1]; hiddenimports += tmp_ret[2]
tmp_ret = collect_all('mlx_audio')
+1
View File
@@ -22,6 +22,7 @@ services:
environment:
- LOG_LEVEL=info
- NUMBA_CACHE_DIR=/tmp/numba_cache
networks:
- voicebox-net
+4 -4
View File
@@ -1,7 +1,7 @@
@import 'tailwindcss';
@import 'fumadocs-ui/css/neutral.css';
@import 'fumadocs-ui/css/preset.css';
@import 'fumadocs-openapi/css/preset.css';
@import "tailwindcss";
@import "fumadocs-ui/css/neutral.css";
@import "fumadocs-ui/css/preset.css";
@import "fumadocs-openapi/css/preset.css";
:root {
--color-fd-primary: hsl(43, 50%, 50%);
+2 -11
View File
@@ -5,22 +5,13 @@ import { generate as DefaultImage } from 'fumadocs-ui/og';
export const revalidate = false;
export async function GET(
_req: Request,
{ params }: RouteContext<'/og/docs/[...slug]'>,
) {
export async function GET(_req: Request, { params }: RouteContext<'/og/docs/[...slug]'>) {
const { slug } = await params;
const page = source.getPage(slug.slice(0, -1));
if (!page) notFound();
return new ImageResponse(
(
<DefaultImage
title={page.data.title}
description={page.data.description}
site="My App"
/>
),
<DefaultImage title={page.data.title} description={page.data.description} site="My App" />,
{
width: 1200,
height: 630,
+2 -2
View File
@@ -159,11 +159,11 @@ Tauri looks for `voicebox-server-${PLATFORM}` in `src-tauri/binaries/` and bundl
The `build-cuda-windows` job runs separately:
1. Install PyTorch with CUDA 12.6
1. Install PyTorch with CUDA 12.8
2. Build with `build_binary.py --cuda` (produces `--onedir` output)
3. Package with `scripts/package_cuda.py` into two archives:
- `voicebox-server-cuda.tar.gz` — server core (~945 MB)
- `cuda-libs-cu126-v1.tar.gz` — NVIDIA runtime libraries (~1.7 GB, cached independently)
- `cuda-libs-cu128-v1.tar.gz` — NVIDIA runtime libraries (~1.7 GB, cached independently)
4. Upload archives as release artifacts
This binary is downloaded on-demand by users who enable CUDA in settings. The CUDA libs archive is only re-downloaded when the CUDA toolkit version changes, not on every app update.
@@ -285,6 +285,34 @@ In `app/src/lib/hooks/useGenerationForm.ts`:
In `app/src/components/ServerSettings/ModelManagement.tsx`:
- Add description to `MODEL_DESCRIPTIONS` record
- Add model name to `voiceModels` filter condition
### 3.6 Non-Cloning Engines (Preset Voices)
If your engine uses **pre-built voices** instead of zero-shot cloning from reference audio (e.g. Kokoro), additional integration is needed:
**Backend:**
- In `kokoro_backend.py` (or your engine), define a `VOICES` list of `(voice_id, display_name, gender, language)` tuples
- `create_voice_prompt()` should return `{"voice_type": "preset", "preset_engine": "<engine>", "preset_voice_id": "<id>"}`
- `generate()` should read `voice_prompt.get("preset_voice_id")` to select the voice
- Add a `seed_preset_profiles("<engine>")` call in `backend/routes/models.py` after model download completes
- The `seed_preset_profiles()` function in `backend/services/profiles.py` creates DB profiles with `voice_type="preset"`
**Frontend:**
- The `EngineModelSelector` filters options based on `selectedProfile.voice_type`:
- `"cloned"` profiles → only cloning engines shown (Kokoro hidden)
- `"preset"` profiles → only the preset's engine shown
- Profile cards show the engine name as a badge for preset profiles
- When a preset profile is selected, the engine auto-switches
**Profile schema fields for presets:**
- `voice_type: "preset"` (vs `"cloned"` for traditional profiles)
- `preset_engine: "<engine>"` — which engine owns this voice
- `preset_voice_id: "<id>"` — the engine-specific voice identifier
**For future "designed" voices** (text description instead of audio, e.g. Qwen CustomVoice):
- Use `voice_type: "designed"` with `design_prompt` field
- `create_voice_prompt_for_profile()` already returns the design prompt for this type
## Phase 4: Dependencies
+3 -3
View File
@@ -31,6 +31,6 @@ Voicebox is a **local-first voice cloning studio** -- a free and open-source alt
## Get Started
- [Installation](/docs/overview/installation) -- download and install Voicebox
- [Quick Start](/docs/overview/quick-start) -- get up and running in 5 minutes
- [API Reference](/docs/api-reference) -- integrate voice synthesis into your apps
- [Installation](/overview/installation) -- download and install Voicebox
- [Quick Start](/overview/quick-start) -- get up and running in 5 minutes
- [API Reference](/api-reference) -- integrate voice synthesis into your apps
+104 -127
View File
@@ -1,6 +1,6 @@
# Voicebox Project Status & Roadmap
> Last updated: 2026-03-13 | Current version: **v0.1.13** | 13.1k stars | ~176 open issues | 25 open PRs
> Last updated: 2026-03-18 | Current version: **v0.3.0** | 13.4k stars | ~136 open issues | 9 open PRs
---
@@ -100,7 +100,7 @@ POST /generate
## Current State
### What's Shipped (v0.1.13 + recent merges)
### What's Shipped (v0.3.0)
**Core TTS:**
- Qwen3-TTS voice cloning (1.7B and 0.6B models)
@@ -108,30 +108,42 @@ POST /generate
- Multi-engine TTS architecture with thread-safe backend registry (PR #254)
- LuxTTS integration — fast, CPU-friendly English TTS (PR #254)
- Chatterbox Multilingual TTS — 23 languages including Hebrew (PR #257)
- Instruct parameter UI exists but is non-functional across all backends (see #224, Known Limitations)
- Chatterbox Turbo — paralinguistic tags, low latency English (PR #258)
- HumeAI TADA integration — 1B English + 3B Multilingual speech-language model (PR #296)
- Single flat model dropdown (Qwen 1.7B, Qwen 0.6B, LuxTTS, Chatterbox, Chatterbox Turbo, TADA 1B, TADA 3B)
- Centralized model config registry (`ModelConfig` dataclass) — no per-engine dispatch maps in `main.py`
- Chunked TTS generation for long text — engine-agnostic, removes ~500 char limit (PR #266)
- Async generation queue (PR #269)
- Post-processing audio effects system (PR #271)
- Centralized model config registry (`ModelConfig` dataclass) — no per-engine dispatch maps
- Shared `EngineModelSelector` component — engine/model dropdown defined once, used in both generation forms
**Infrastructure:**
- CUDA backend swap via binary download and restart (PR #252)
- GPU acceleration settings UI
- CUDA backend swap via binary download and restart (PR #252), upgraded to cu128 (PR #316)
- CUDA backend split into independently versioned server + libs archives (PR #298)
- Docker + web deployment (PR #161)
- Backend refactor: modular architecture, style guide, tooling (PR #285)
- Settings overhaul: routed sub-tabs, server logs, changelog, about page (PR #294)
- Windows support: CUDA detection, cross-platform justfile, clean server shutdown (PR #272)
- Voice profiles with multi-sample support
- Stories editor (multi-track DAW timeline)
- Whisper transcription (base, small, medium, large variants)
- Model management UI with inline download progress bars (HFProgressTracker)
- Model management UI with inline download progress bars + folder migration (PR #268)
- Download cancel/clear UI with error panel (PR #238)
- Generation history with caching
- Streaming generation endpoint (MLX only)
- Duplicate profile name validation (PR #175)
- Linux NVIDIA GBM buffer + WebKitGTK microphone fix (PR #210)
- Audio player freeze fix + UX improvements (PR #293)
- CORS restriction to known local origins (PR #88)
### Abandoned Integrations
| Model | PR | Reason |
|-------|----|--------|
| **CosyVoice2/3** | PR #311 | Output quality too poor. Heavy deps, no PyPI, needed 5+ shims. |
### What's In-Flight
| Feature | Branch/PR | Status |
|---------|-----------|--------|
| Chatterbox Turbo + per-engine language lists | `feat/chatterbox-turbo` / PR #258 | Open, ready for review |
| Kokoro 82M TTS engine | WIP | In development — 82M CPU-realtime engine, 8 languages |
### TTS Engine Comparison
@@ -144,6 +156,7 @@ POST /generate
| Chatterbox Turbo | `chatterbox-turbo` | English | ~1.5 GB | Paralinguistic tags ([laugh], [cough]), 350M params, low latency | Partial — inline tags only, no separate instruct param |
| TADA 1B | `tada-1b` | English | ~4 GB | HumeAI speech-language model, 700s+ coherent audio | None |
| TADA 3B Multilingual | `tada-3b-ml` | 10 (en, ar, zh, de, es, fr, it, ja, pl, pt) | ~8 GB | Multilingual, text-acoustic dual alignment | None |
| Kokoro 82M | `kokoro` | 8 (en, es, fr, hi, it, pt, ja, zh) | ~350 MB | 82M params, CPU realtime, Apache 2.0, pre-built voices | None |
### Multi-Engine Architecture (Shipped)
@@ -173,69 +186,41 @@ The singleton TTS backend blocker described in the previous version of this doc
| PR | Title | Merged |
|----|-------|--------|
| **#257** | feat: Chatterbox TTS engine with multilingual voice cloning | 2026-03-13 |
| **#254** | feat: LuxTTS integration — multi-engine TTS support | 2026-03-13 |
| **#252** | feat: CUDA backend swap via binary download and restart | 2026-03-13 |
| **#238** | Download cancel/clear UI, fixed model downloading | 2026-03-13 |
| **#250** | docs: align local API port examples | 2026-03-13 |
| **#210** | fix: Linux NVIDIA GBM buffer crash | 2026-03-13 |
| **#175** | Fix #134: duplicate profile name validation | 2026-03-13 |
| **#316** | Upgrade CUDA backend from cu126 to cu128, fix GPU settings UI | 2026-03-18 |
| **#305** | fix: bundle qwen_tts source files in PyInstaller build | 2026-03-17 |
| **#298** | feat: split CUDA backend into independently versioned server + libs archives | 2026-03-17 |
| **#296** | Add HumeAI TADA TTS engine (1B English + 3B Multilingual) | 2026-03-17 |
| **#295** | fix: batch of bug fixes from issue tracker | 2026-03-17 |
| **#293** | Fix audio player freezing and improve UX | 2026-03-17 |
| **#294** | Settings overhaul: routed sub-tabs, server logs, changelog, about page | 2026-03-16 |
| **#288** | Better docs | 2026-03-16 |
| **#285** | Backend refactor: modular architecture, style guide, tooling | 2026-03-16 |
| **#274** | Landing page v0.2.0 redesign | 2026-03-15 |
| **#272** | Windows support: CUDA detection, cross-platform justfile, clean server shutdown | 2026-03-15 |
| **#271** | Add post-processing audio effects system | 2026-03-14 |
| **#269** | feat: async generation queue | 2026-03-13 |
| **#268** | feat: model management improvements and folder migration | 2026-03-13 |
| **#266** | feat: chunked TTS generation for long text (engine-agnostic) | 2026-03-13 |
| **#265** | feat: paralinguistic tag autocomplete for Chatterbox Turbo | 2026-03-13 |
| **#264** | fix: Chatterbox float64 dtype mismatch + model unload button | 2026-03-13 |
| **#258** | feat: Chatterbox Turbo engine + per-engine language lists | 2026-03-13 |
| **#230** | docs: fix README grammar | 2026-03-13 |
| **#161** | feat: Docker + web deployment | 2026-03-13 |
| **#88** | security: restrict CORS to known local origins | 2026-03-13 |
### In-Flight (Our Work)
### Currently Open (9 PRs)
| PR | Title | Status | Notes |
|----|-------|--------|-------|
| **#258** | feat: Chatterbox Turbo engine + per-engine language lists | Open | Ready for review. Adds Turbo engine + dynamic language dropdown. |
### Merge-Ready / Near-Ready (Bug Fixes & Small Features)
| PR | Title | Risk | Notes |
|----|-------|------|-------|
| **#230** | docs: fix README grammar | None | Docs-only |
| **#243** | a11y: screen reader and keyboard improvements | Low | Accessibility, no backend changes |
| **#178** | Fix #168 #140: generation error handling | Low | Error handling improvements |
| **#152** | Fix: prevent crashes when HuggingFace unreachable | Medium | Monkey-patches HF hub; solves real offline bug (#150, #151) |
| **#218** | fix: unify qwen tts cache dir on Windows | Low | Windows-specific path fix |
| **#214** | fix: panic on launch from tokio::spawn | Low | Rust-side Tauri fix |
| **#88** | security: restrict CORS to known local origins | Low | Security hardening |
| **#133** | feat: network access toggle | Low | Wires up existing plumbing |
### Significant Feature PRs
| PR | Title | Complexity | Notes |
|----|-------|-----------|-------|
| **#253** | Enhance speech tokenizer with 48kHz version | Medium | Qwen tokenizer upgrade |
| **#97** | fix: pass language parameter to TTS models | Medium | May be partially obsoleted by multi-engine work — needs review |
| **#99** | feat: chunked TTS with quality selector | Medium | Solves 500-char limit. Addresses #191, #203, #69, #111. |
| **#154** | feat: Audiobook tab | Medium | Full audiobook workflow. Depends on #99 concepts. |
| **#91** | fix: CoreAudio device enumeration | Medium | macOS audio device handling |
### Architectural PRs (Need Careful Review)
| PR | Title | Complexity | Notes |
|----|-------|-----------|-------|
| **#225** | feat: custom HuggingFace model support | High | Arbitrary HF repo loading. May need rework given multi-engine arch is now shipped. |
| **#194** | feat: Hebrew + Chatterbox TTS | High | **Superseded** by PR #257 which shipped Chatterbox multilingual (23 langs incl. Hebrew). May be closeable. |
| **#195** | feat: per-profile LoRA fine-tuning | Very High | Training pipeline, adapter management, 15 new endpoints. Depends on #194 (now superseded). |
| **#161** | feat: Docker + web deployment | High | 3-stage Dockerfile, SPA serving. Independent of TTS engine work. |
| **#124** / **#123** | Docker (simpler attempts) | Low-Medium | Overlap with #161 |
| **#227** | fix: harden input validation & file safety | Medium | Coupled to #225 (custom models) |
### PRs That Need Author Action / Are Stale
| PR | Title | Notes |
|----|-------|-------|
| **#237** | fix: bundle qwen_tts source files in PyInstaller | Build system, needs review |
| **#215** | Update prerequisites with Tauri deps | Branch is `main` — will have conflicts |
| **#89** | Linux Support | Branch is `main` — will have conflicts. Broad scope. |
| **#83** | Update download links for v0.1.12 | Outdated (we're on v0.1.13) |
### PRs Likely Superseded
| PR | Superseded By | Notes |
|----|--------------|-------|
| **#194** (Hebrew + Chatterbox) | PR #257 (merged) | #257 ships Chatterbox multilingual with 23 languages including Hebrew. #194 took a different approach (route by language). Can likely be closed. |
| **#33** (External provider binaries) | PR #252 (merged) | #252 shipped CUDA backend swap. #33's broader provider architecture may still have value but needs reassessment. |
| **#311** | feat: add CosyVoice2/3 TTS engine | **Will close** | Model quality too poor. See Abandoned Integrations. |
| **#253** | Enhance speech tokenizer with 48kHz version | Community PR | Qwen tokenizer upgrade. Worth reviewing. |
| **#237** | fix: bundle qwen_tts source files in PyInstaller | Superseded | Our PR #305 shipped this. Can close. |
| **#227** | fix: harden input validation & file safety | Community PR | Coupled to #225 (custom models). |
| **#225** | feat: custom HuggingFace model support | Community PR | Needs rework for multi-engine arch. |
| **#218** | fix: unify qwen tts cache dir on Windows | Community PR | Windows-specific path fix. Still relevant. |
| **#195** | feat: per-profile LoRA fine-tuning | Draft | Complex. 15 new endpoints. |
| **#154** | feat: Audiobook tab | Community PR | Chunked generation now shipped (#266). |
| **#91** | fix: CoreAudio device enumeration | Draft | macOS audio device handling. |
---
@@ -280,7 +265,7 @@ Strong demand for: Hindi (#245), Indonesian (#247), Dutch (#236), Hebrew (#199),
| #132 | LavaSR (transcription) |
| #76 | (General model expansion) |
Community also requests: XTTS-v2, Fish Speech, CosyVoice, Kokoro. The multi-engine architecture is now in place, making new model integration significantly easier.
Community also requests: XTTS-v2, Fish Speech, Kokoro. CosyVoice was tried and abandoned. The multi-engine architecture is in place, making new model integration straightforward.
### Long-Form / Chunking (5 issues)
@@ -288,7 +273,7 @@ Users hitting the ~500 character practical limit.
**Key issues:** #234 (queue system), #203 (500 char limit), #191 (auto-split), #111, #69
**Fix path:** PR #99 (chunked TTS + quality selector) directly addresses this. PR #154 (Audiobook tab) builds on it.
**Fix path:** **Mostly resolved.** PR #266 (engine-agnostic chunked TTS) and PR #269 (async generation queue) are both merged. PR #154 (Audiobook tab) is still open.
### Feature Requests (23 issues)
@@ -326,7 +311,7 @@ Notable requests:
| `CUDA_BACKEND_SWAP_FINAL.md` | — | **Shipped** (PR #252) | Final implementation plan |
| `EXTERNAL_PROVIDERS.md` | v0.2.0 | **Not started** | Remote server support |
| `MLX_AUDIO.md` | — | **Shipped** | MLX backend is live |
| `DOCKER_DEPLOYMENT.md` | v0.2.0 | **PR exists** (#161) | Waiting on review |
| `DOCKER_DEPLOYMENT.md` | v0.2.0 | **Shipped** (PR #161) | Docker + web deployment |
| `OPENAI_SUPPORT.md` | v0.2.0 | **Not started** | OpenAI-compatible API layer |
| `PR33_CUDA_PROVIDER_REVIEW.md` | — | **Reference** | Analysis of the original provider approach |
@@ -334,31 +319,31 @@ Notable requests:
## New Model Integration — Landscape
### Models Worth Supporting (2026 SOTA — updated March 13)
### Models Worth Supporting (2026 SOTA — updated March 18)
| Model | Cloning | Speed | Sample Rate | Languages | VRAM | Instruct Support | Integration Ease | Status |
|-------|---------|-------|-------------|-----------|------|-----------------|-----------------|--------|
| **Qwen3-TTS** | 10s zero-shot | Medium | 24 kHz | 10 | Medium | None (Base); Yes (CustomVoice variant, predefined speakers only) | **Shipped** | v0.1.13 |
| **LuxTTS** | 3s zero-shot | 150x RT, CPU ok | 48 kHz | English | <1 GB | None | **Shipped** | PR #254 |
| **Chatterbox MTL** | 5s zero-shot | Medium | 24 kHz | 23 | Medium | Partial — `exaggeration` float | **Shipped** | PR #257 |
| **Chatterbox Turbo** | 5s zero-shot | Fast | 24 kHz | English | Low | Partial — inline tags only | **PR #258** | In review |
| **CosyVoice2-0.5B** | 3-10s zero-shot | Very fast | 24 kHz | Multilingual | Low | **Yes** — `inference_instruct2()`, works with cloning | Ready | Best instruct candidate |
| **Fish Speech** | 10-30s few-shot | Real-time | 24-44 kHz | 50+ | Medium | **Yes** — inline text descriptions, word-level control | Ready | Multi-engine arch in place |
| **MOSS-TTS Family** | Zero-shot | — | — | Multilingual | Medium | **Yes** — text prompts for style + timbre design | Needs vetting | Apache 2.0, multi-speaker dialogue |
| **HumeAI TADA 1B/3B** | Zero-shot | 5× faster than LLM-TTS | 24 kHz | EN (1B), Multilingual (3B) | Medium | Partial — automatic prosody from text context | **Shipped** | PR #296, MIT, 700s+ coherent |
| **VoxCPM 1.5** | Zero-shot (seconds) | ~0.15 RTF streaming | — | Bilingual (EN/ZH) | Medium | Partial — automatic context-aware prosody | Needs vetting | Apache 2.0, tokenizer-free continuous diffusion |
| **Kokoro-82M** | 3s instant | CPU realtime | 24 kHz | English | Tiny (82M) | Partial — automatic style inference | Ready | Apache 2.0, multi-engine arch in place |
| **XTTS-v2** | 6s zero-shot | Mid-GPU | 24 kHz | 17+ | Medium | Partial — style transfer from ref audio only | Ready | Multi-engine arch in place |
| **Pocket TTS** | Zero-shot + streaming | >1× RT on CPU | — | English | ~100M params, CPU-first | None | Needs vetting | MIT, Kyutai Labs, no GPU required |
| **Chatterbox Turbo** | 5s zero-shot | Fast | 24 kHz | English | Low | Partial — inline tags only | **Shipped** | PR #258 |
| **HumeAI TADA 1B/3B** | Zero-shot | 5x faster than LLM-TTS | 24 kHz | EN (1B), Multilingual (3B) | Medium | Partial — automatic prosody | **Shipped** | PR #296 |
| **Kokoro-82M** | Pre-built voices | CPU realtime | 24 kHz | 8 | Tiny (82M) | None | **In progress** | Apache 2.0, pip install, ~350MB |
| ~~**CosyVoice2-0.5B**~~ | 3-10s zero-shot | Very fast | 24 kHz | Multilingual | Low | Yes — `inference_instruct2()` | **Abandoned** | PR #311 — poor output quality |
| **Fish Speech** | 10-30s few-shot | Real-time | 24-44 kHz | 50+ | Medium | **Yes** — inline text descriptions, word-level control | Ready | Needs license clarification |
| **XTTS-v2** | 6s zero-shot | Mid-GPU | 24 kHz | 17+ | Medium | Partial — style transfer from ref audio only | Ready | Mature pip package |
| **Pocket TTS** | Zero-shot + streaming | >1x RT on CPU | — | English | ~100M params, CPU-first | None | Ready | MIT, Kyutai Labs |
| **MOSS-TTS Family** | Zero-shot | — | — | Multilingual | Medium | **Yes** — text prompts for style + timbre design | Needs vetting | Apache 2.0 |
| **VoxCPM 1.5** | Zero-shot (seconds) | ~0.15 RTF streaming | — | Bilingual (EN/ZH) | Medium | Partial — automatic context-aware prosody | Needs vetting | Apache 2.0 |
#### Notes on New Candidates (March 2026)
#### Notes on Candidates (March 2026)
- **CosyVoice2-0.5B** — Best candidate for instruct support. `inference_instruct2()` accepts a text instruct parameter for emotions, speed, volume, dialects — and it works alongside voice cloning. This is the closest match to what users expect from our instruct UI. [HF: FunAudioLLM/CosyVoice2-0.5B](https://huggingface.co/FunAudioLLM/CosyVoice2-0.5B)
- **HumeAI TADA** — Text-Audio Dual Alignment arch. Near-zero hallucinations/drift, free synced transcript. 700+ seconds coherent audio. Best candidate for Stories long-form reliability. Prosody/emotion is automatic from text context, not user-controllable. [HF: HumeAI/tada-1b](https://huggingface.co/HumeAI/tada-1b) | [GitHub: HumeAI/tada](https://github.com/HumeAI/tada)
- **MOSS-TTS** — Modular suite: flagship cloning, MOSS-TTSD (multi-speaker dialogue), MOSS-VoiceGenerator (create voices from text descriptions). VoiceGenerator unifies timbre design and style control via text prompts, usable as a layer for downstream TTS including cloning. [HF: OpenMOSS-Team/MOSS-VoiceGenerator](https://huggingface.co/OpenMOSS-Team/MOSS-VoiceGenerator) | [GitHub: OpenMOSS/MOSS-TTS](https://github.com/OpenMOSS/MOSS-TTS)
- **Fish Speech** — Word-level fine-grained control using plain language descriptions inline in the script. Works with cloning. Note: Fish Audio S2 has a restrictive research license (commercial use requires approval), but the open-source Fish Speech model may differ. Needs license clarification. [fish.audio blog](https://fish.audio/blog/fish-audio-s2-fine-grained-ai-voice-control-at-the-word-level)
- **VoxCPM 1.5** — Tokenizer-free continuous diffusion + autoregressive. No discrete token artifacts. Prosody/emotion is context-aware but automatic, not explicitly controllable via text prompt. Real-time streaming, LoRA fine-tuning. Trained on 1.8M+ hours. [GitHub: OpenBMB/VoxCPM](https://github.com/OpenBMB/VoxCPM)
- **Pocket TTS** — 100M param CPU-first model from Kyutai Labs (Moshi team). Runs >1× realtime without GPU. No style control. Broadens hardware support significantly. [GitHub: kyutai-labs/pocket-tts](https://github.com/kyutai-labs/pocket-tts)
- **CosyVoice2-0.5B** — **Tried and abandoned** (PR #311). Despite having the best instruct API, output quality was poor. No PyPI package, needed 5+ shims, heavy deps. Not worth it.
- **HumeAI TADA** — **Shipped** (PR #296). 700+ seconds coherent audio. [GitHub: HumeAI/tada](https://github.com/HumeAI/tada)
- **Kokoro-82M** — **In progress.** 82M params, CPU realtime, Apache 2.0, clean `pip install kokoro`. Uses pre-built voice styles (not zero-shot cloning from arbitrary audio). [GitHub: hexgrad/kokoro](https://github.com/hexgrad/kokoro)
- **Fish Speech** — Word-level fine-grained control. License needs clarification. [fish.audio blog](https://fish.audio/blog/fish-audio-s2-fine-grained-ai-voice-control-at-the-word-level)
- **XTTS-v2** — Coqui's multilingual cloning. 17+ languages, pip-installable. [GitHub: coqui-ai/TTS](https://github.com/coqui-ai/TTS)
- **Pocket TTS** — 100M param CPU-first model from Kyutai Labs. [GitHub: kyutai-labs/pocket-tts](https://github.com/kyutai-labs/pocket-tts)
- **Watch list:** MioTTS-2.6B (fast LLM-based EN/JP, vLLM compatible), Oolel-Voices (Soynade Research, expressive modular control)
### Adding a New Engine (Now Straightforward)
@@ -402,49 +387,44 @@ The generation form now uses a flat model dropdown with engine-based routing. Pe
## Recommended Priorities
### Tier 1 — Ship Now (Low Risk)
### Tier 1 — Ship Now
| Priority | PR/Item | Impact | Effort |
|----------|---------|--------|--------|
| 1 | **#258** — Chatterbox Turbo + per-engine languages | Paralinguistic tags, proper language filtering | Review only |
| 2 | **#152** — Offline mode crash fix | Fixes #150, #151 | Low |
| 3 | **#99** — Chunked TTS + quality selector | Removes 500-char limit, addresses 5 issues | Medium |
| 4 | **#218** — Windows HF cache dir fix | Windows-specific pain | Low |
| 5 | **#178** — Generation error handling | Error UX | Low |
| 6 | **#230** — Docs fixes | Zero risk | None |
| 7 | **#133** — Network access toggle | Wires up existing code | Low |
| 8 | **#88** — CORS restriction | Security improvement | Low |
| 9 | **#214** — Tauri window close panic fix | Stability | Low |
| 10 | Triage GPU issues | Many may be resolved by CUDA swap (#252) | Low |
| 11 | Close superseded PRs | #194 (superseded by #257), #83 (outdated) | None |
| 1 | **Kokoro 82M** — finish integration | New engine, CPU-friendly, 8 langs | Low (nearly done) |
| 2 | Close PR #311 (CosyVoice) and #237 (superseded by #305) | Housekeeping | None |
| 3 | **#218** — Windows HF cache dir fix | Windows-specific pain | Low |
| 4 | **#253** — 48kHz speech tokenizer | Quality improvement for Qwen | Medium |
### Tier 2 — Next Release (v0.2.0)
### Tier 2 — Feature Work
| Priority | Item | Impact | Effort |
|----------|------|--------|--------|
| 1 | **#253** — 48kHz speech tokenizer | Quality improvement | Medium |
| 2 | **#161** — Docker deployment | Server/headless users | Medium |
| 3 | **#154** — Audiobook tab | Long-form users | Medium |
| 4 | ~~**Model config registry**~~ | ~~Reduce dispatch duplication in main.py~~ | **Done** |
| 5 | **#225** — Custom HuggingFace models | User-supplied models | High (needs rework for multi-engine) |
| 1 | **#154** — Audiobook tab | Long-form users. Chunking + queue now shipped. | Medium |
| 2 | **#225** — Custom HuggingFace models | User-supplied models. Needs rework. | High |
| 3 | OpenAI-compatible API (plan doc exists) | Low effort once API is stable | Low |
| 4 | LoRA fine-tuning (PR #195) | Complex, needs rework for multi-engine | Very High |
| 5 | Streaming for non-MLX engines | Currently MLX-only | Medium |
### Tier 3 — Future (v0.3.0+)
### Tier 3 — Future Engines
| Priority | Item | Notes |
|----------|------|-------|
| 1 | **HumeAI TADA** | Long-form reliability for Stories, synced transcripts. Addresses #234, #203, #191, #111, #69. Needs API vetting. |
| 2 | **Pocket TTS** (Kyutai) | CPU-first 100M model, broadens hardware support. Kyutai ships clean code. Needs API vetting. |
| 3 | **MOSS-TTS** | Text-to-voice design (no ref audio) is unique. Multi-speaker dialogue for Stories. Needs thorough API vetting. |
| 4 | **Kokoro-82M** | 82M params, CPU realtime, Apache 2.0. Easy win. |
| 5 | ~~**Model config registry refactor**~~ | **Done** — consolidated in `backend/backends/__init__.py` + `EngineModelSelector.tsx` |
| 6 | XTTS-v2 / Fish Speech / CosyVoice | Multi-engine arch is ready; just needs backend implementation |
| 7 | **VoxCPM 1.5** | Tokenizer-free streaming, interesting but uncertain integration surface |
| 8 | OpenAI-compatible API (plan doc exists) | Low effort once API is stable |
| 9 | LoRA fine-tuning (PR #195) | Complex, needs rework for multi-engine |
| 10 | External/remote providers | Depends on use case demand |
| 11 | GGUF support (#226) | Depends on model ecosystem maturity |
| 12 | Queue system (#234) | Batch generation |
| 13 | Streaming for non-MLX engines | Currently MLX-only |
| 1 | **Fish Speech** | 50+ langs, word-level instruct. License TBD. |
| 2 | **XTTS-v2** | 17+ langs, mature pip package. Best multilingual cloning. |
| 3 | **Pocket TTS** (Kyutai) | CPU-first 100M model. MIT. |
| 4 | **MOSS-TTS** | Text-to-voice design. Multi-speaker dialogue for Stories. |
| 5 | **VoxCPM 1.5** | Tokenizer-free streaming. Uncertain integration surface. |
### ~~Previously Prioritized — Now Done~~
- ~~#258 — Chatterbox Turbo~~ **Merged**
- ~~#99 — Chunked TTS~~ **Superseded by #266, merged**
- ~~#88 — CORS restriction~~ **Merged**
- ~~#161 — Docker deployment~~ **Merged**
- ~~#234 — Queue system~~ **Addressed by #269, merged**
- ~~HumeAI TADA~~ **Shipped** (PR #296)
- ~~Kokoro-82M~~ **In progress**
---
@@ -452,13 +432,10 @@ The generation form now uses a flat model dropdown with engine-based routing. Pe
| Branch | PR | Status | Notes |
|--------|-----|--------|-------|
| `feat/chatterbox-turbo` | #258 | Open | Chatterbox Turbo + per-engine languages |
| `feat/cosyvoice-engine` | #311 | Open — closing | CosyVoice2/3 — abandoned, poor quality |
| `feat/chatterbox-turbo` | #258 | **Merged** | Chatterbox Turbo + per-engine languages |
| `feat/chatterbox` | #257 | **Merged** | Chatterbox Multilingual |
| `feat/luxtts` | #254 | **Merged** | LuxTTS + multi-engine arch |
| `external-provider-binaries` | #33 | Superseded by #252 | Original CUDA provider approach |
| `feat/dual-server-binaries` | — | No PR | Related to provider split |
| `fix-multi-sample` | — | No PR | Voice profile multi-sample fix |
| `fix-dl-notification-...` | — | No PR | Model download UX |
---
+428
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@@ -0,0 +1,428 @@
# Voicebox API Refactor Plan
Date: 2026-03-19
Status: Proposed
Scope: Backend HTTP API structure, schemas, docs, and compatibility strategy
## Goals
- Make the API easier to understand and automate against.
- Improve endpoint consistency without breaking the desktop app or existing local integrations.
- Align generated docs and checked-in OpenAPI artifacts with the actual backend.
- Separate app-facing resources from internal or operational actions.
- Create a migration path toward a cleaner `v2` resource model while preserving `v1` routes during transition.
## Non-Goals
- Rewriting backend business logic or generation internals.
- Introducing authentication for all deployment modes in the first pass.
- Changing storage models or database schema unless required for API correctness.
- Removing current routes immediately.
## Current Pain Points
- Mixed endpoint styles: resource-oriented (`/profiles`) and command-oriented (`/generate`, `/tasks/clear`) coexist.
- Related generation resources are split across multiple namespaces: `/generate`, `/history`, `/audio`, `/effects`, and `/generations/.../versions`.
- Response payloads vary widely: typed models, raw dicts with `message`, booleans, and `HTTPException(detail=...)` payloads.
- Some async flows use exception-shaped `202` responses instead of first-class task contracts.
- Checked-in OpenAPI output can drift from actual backend models.
- Operational endpoints such as `/shutdown` are exposed in the same surface as user workflows.
## Guiding Principles
1. Prefer additive changes before destructive changes.
2. Keep `v1` behavior working until the app and docs fully migrate.
3. Add compatibility shims close to the routing layer, not deep in services.
4. Treat OpenAPI as a release artifact that must be kept in sync.
5. Standardize public contracts before renaming everything.
## Target API Shape
This is the intended end state, not the immediate first milestone.
### Core Resources
- `/profiles`
- `/profiles/{profile_id}/samples`
- `/profiles/{profile_id}/avatar`
- `/profiles/{profile_id}/effects`
- `/generations`
- `/generations/{generation_id}`
- `/generations/{generation_id}/status`
- `/generations/{generation_id}/audio`
- `/generations/{generation_id}/versions`
- `/generations/{generation_id}/versions/{version_id}`
- `/generations/{generation_id}/versions/{version_id}/audio`
- `/stories`
- `/stories/{story_id}/items`
- `/effects/presets`
- `/models`
- `/models/{model_name}`
- `/tasks`
### Operational or Internal Endpoints
Move under an explicit namespace and disable where appropriate:
- `/admin/shutdown`
- `/admin/watchdog/disable`
- `/admin/cache/clear`
- `/admin/tasks/clear`
### Response Contract Direction
- Resource reads and writes return typed resource models.
- Delete and action endpoints return small typed action result models.
- Errors use a consistent structure.
- Async actions return explicit task metadata instead of overloading `detail`.
## Migration Strategy Overview
The refactor is split into six phases. Phases 1-3 are the highest impact and safest to ship first.
| Phase | Focus | Est. Duration | Risk | Backward Compatibility |
| --- | --- | --- | --- | --- |
| 1 | Documentation and contract correctness | 2-3 days | Low | Full |
| 2 | Response and error consistency | 3-5 days | Low-Medium | Full |
| 3 | Router structure and internal organization | 3-4 days | Low | Full |
| 4 | Additive `v2` resource endpoints | 1-2 weeks | Medium | Full |
| 5 | Client migration and deprecation rollout | 1 week | Medium | Full during rollout |
| 6 | Cleanup and optional removals | 1-2 releases | Medium-High | Partial after notice |
## Phase 1: Fix Contract Drift First
Priority: Highest
Outcome: The documented API matches the running backend.
### Problems Addressed
- `docs/openapi.json` can become stale.
- Generated API reference pages may describe outdated request bodies.
- App metadata still frames the backend too narrowly.
### Implementation Steps
1. Update FastAPI app metadata in `backend/app.py`.
- Replace the old Qwen-specific description with a multi-engine Voicebox API description.
- Add tags metadata for major domains if desired.
2. Regenerate OpenAPI from the running app using the existing docs script flow.
3. Compare `backend/models.py` to the checked-in schema.
- Verify `GenerationRequest`, effects endpoints, stories endpoints, and model endpoints.
4. Regenerate or refresh API reference pages under `docs/content/docs/api-reference/`.
5. Add a CI check that fails if `docs/openapi.json` is out of date.
6. Add a short maintainer note describing when schema regeneration is required.
### Backward Compatibility
- No route changes.
- No payload changes.
- Safe to release immediately.
### Success Criteria
- `docs/openapi.json` matches the live app.
- Generated docs include all currently supported generate parameters.
- No frontend code changes required.
## Phase 2: Standardize Responses and Errors
Priority: High
Outcome: Clients can handle responses predictably.
### Problems Addressed
- Delete endpoints return ad hoc message dicts.
- Toggle endpoints return special one-off payloads.
- `202` async responses are encoded as `HTTPException(detail=...)` in some places.
### Implementation Steps
1. Add shared response models in `backend/models.py`.
- `ActionResult`
- `DeleteResult`
- `ToggleFavoriteResponse`
- `AcceptedTaskResponse`
- `ApiError`
2. Convert routes that currently return raw dicts to explicit `response_model`s.
- `DELETE /profiles/{profile_id}`
- `DELETE /history/{generation_id}`
- `DELETE /stories/{story_id}`
- `POST /tasks/clear`
- `POST /cache/clear`
- similar endpoints across routes
3. Replace exception-shaped `202` responses in `transcription.py` with an explicit accepted response body.
- Return `JSONResponse(status_code=202, content=...)` or typed FastAPI response model.
4. Add a global exception handler for known API errors if helpful.
- Normalize `ValueError` to `400` with a consistent error body.
- Preserve FastAPI validation errors for now, or wrap them in a consistent top-level shape in a later pass.
5. Document the stable error contract in the docs.
### Migration Strategy
- Keep field names inside successful payloads compatible where possible.
- For existing dict responses, preserve the current keys while introducing typed models with the same shape.
- For `202` flows, support both old and new client handling for one release if needed.
### Timeline Estimate
- 3-5 engineering days including tests and docs refresh.
### Success Criteria
- All mutation endpoints declare response models.
- Clients can programmatically distinguish success, accepted, and error cases without special casing `detail` payloads.
## Phase 3: Normalize Router Structure Internally
Priority: High
Outcome: The backend becomes easier to maintain before public path changes begin.
### Problems Addressed
- Route files hardcode full paths and are all mounted at root.
- There is no consistent use of router prefixes or tags.
- Route grouping in code does not cleanly express the public API shape.
### Implementation Steps
1. Add prefixes and tags to routers.
- `profiles`: `prefix="/profiles"`
- `generations`: `prefix="/generate"` for now or split additive aliases carefully
- `history`: `prefix="/history"`
- `effects`: `prefix="/effects"`
- and so on
2. Convert route declarations to relative paths within each router.
3. Introduce a small route compatibility layer for routes that are likely to move later.
- Example: helper functions that can be mounted under both old and new paths.
4. Add explicit route tags so Swagger/OpenAPI groups are coherent.
5. Document the intended public ownership of each namespace.
### Backward Compatibility
- No public path changes yet if existing paths are preserved through prefixes and aliases.
- Mostly internal refactoring.
### Timeline Estimate
- 3-4 engineering days.
### Success Criteria
- All route modules use prefixes and tags.
- Route registration in `backend/routes/__init__.py` becomes simpler.
- OpenAPI groups read cleanly by domain.
## Phase 4: Introduce Additive `v2` Resource Endpoints
Priority: High
Outcome: A cleaner API exists without breaking the current one.
### Problems Addressed
- Generation-related resources are fragmented.
- Sample and audio endpoints are not consistently modeled as resources.
- Command-style naming makes the API harder to reason about.
### New Endpoints to Add
These should be introduced alongside current endpoints, not as replacements.
- `POST /generations` -> alias for current `/generate`
- `GET /generations` -> alias for current `/history`
- `GET /generations/{id}` -> alias for current `/history/{id}`
- `POST /generations/{id}/retry` -> alias for current `/generate/{id}/retry`
- `POST /generations/{id}/regenerate` -> alias for current `/generate/{id}/regenerate`
- `GET /generations/{id}/status` -> alias for current `/generate/{id}/status`
- `POST /generations/stream` -> alias for current `/generate/stream`
- `GET /generations/{id}/audio` -> alias for current `/audio/{generation_id}`
- `GET /generations/{id}/export` -> alias for current `/history/{generation_id}/export`
- `GET /generations/{id}/export-audio` -> alias for current `/history/{generation_id}/export-audio`
- `GET /profiles/{profile_id}/samples/{sample_id}` or `GET /samples/{sample_id}` as a consciously chosen model
- `PUT /profiles/{profile_id}/samples/{sample_id}` -> alias for current sample update route
- `DELETE /profiles/{profile_id}/samples/{sample_id}` -> alias for current sample delete route
### Implementation Steps
1. Create new handler entry points that call the existing service functions.
2. Keep old handlers in place, but mark them deprecated in OpenAPI.
3. Add `summary` and `description` text clarifying preferred routes.
4. Update frontend and docs examples to use new endpoints first.
5. Add tests proving both old and new paths return equivalent responses.
### Migration Strategy
- Old paths remain functional for at least one stable release cycle.
- New docs and client examples use `v2-style` resource routes immediately.
- Include deprecation headers where feasible, for example:
- `Deprecation: true`
- `Sunset: <date>`
- `Link: <new-doc-url>; rel="successor-version"`
### Timeline Estimate
- 1-2 weeks depending on test coverage and frontend updates.
### Success Criteria
- All major generation workflows are accessible through resource-oriented routes.
- Old routes still work unchanged.
## Phase 5: Migrate First-Party Clients and Publish Deprecations
Priority: Medium
Outcome: Voicebox itself stops depending on legacy paths.
### Problems Addressed
- The desktop app and docs may continue to reinforce old route shapes.
- Third-party consumers need a visible migration path.
### Implementation Steps
1. Update `app/src/lib/api/client.ts` to use the new preferred endpoints.
2. Regenerate or refresh any generated API clients.
3. Update docs examples, tutorials, and code snippets to use preferred routes only.
4. Add a changelog entry describing the migration path.
5. Add runtime deprecation logging for legacy route usage in development mode.
6. If feasible, expose a small `/health` or `/meta` field showing API version and deprecation window.
### Migration Strategy
- Keep old endpoints available but clearly documented as legacy.
- Publish a mapping table from old route to new route.
- Do not change request or response payloads during the same phase unless necessary.
### Timeline Estimate
- About 1 week including docs and app verification.
### Success Criteria
- First-party app no longer depends on legacy route names.
- Docs do not advertise deprecated paths as the primary interface.
## Phase 6: Cleanup, Namespace Hardening, and Optional Breaking Changes
Priority: Medium
Outcome: The API surface is cleaner and safer for remote or Docker use.
### Problems Addressed
- Internal/admin endpoints are mixed into the public API.
- Legacy aliases increase maintenance cost forever if never retired.
### Implementation Steps
1. Move operational endpoints under `/admin` or `/internal`.
- `/shutdown`
- `/watchdog/disable`
- `/tasks/clear`
- `/cache/clear`
2. Gate these endpoints behind configuration for non-local deployments.
- Example: `VOICEBOX_ENABLE_ADMIN_API=true`
3. Decide whether to remove or keep legacy aliases.
- If removing, do so only after a published deprecation window.
4. Remove deprecated docs pages and old examples.
5. Tighten route-level tests to prevent accidental reintroduction of legacy patterns.
### Migration Strategy
- For desktop-only local use, aliases may remain indefinitely if removal cost outweighs benefit.
- For published remote API guidance, hide admin endpoints from default docs even if they still exist.
### Timeline Estimate
- 1-2 releases after the additive migration is complete.
### Success Criteria
- Public docs expose a coherent resource API.
- Operational endpoints are clearly separate or disabled in remote contexts.
## Cross-Cutting Work Items
These should happen throughout the migration, not only in a single phase.
### Testing
- Add route equivalence tests for old and new paths.
- Add schema snapshot tests for OpenAPI generation.
- Add response-shape tests for common mutations and async workflows.
- Add contract tests for `202 Accepted` flows.
### Documentation
- Maintain an old-to-new endpoint mapping table.
- Add per-endpoint examples for create profile, generate, apply effects, transcribe, and stories operations.
- Explicitly document which endpoints are app-facing vs admin-facing.
### Observability
- Add warning logs when deprecated endpoints are used.
- Track usage counts in development or optional telemetry-free local logs.
### Release Management
- Mention API changes in `CHANGELOG.md`.
- Ensure docs and app updates ship in the same release as new preferred routes.
## Recommended Execution Order
If engineering time is limited, implement in this exact order:
1. Fix OpenAPI and docs drift.
2. Standardize response models and accepted-task responses.
3. Add router prefixes and tags internally.
4. Add `/generations` aliases and sample path aliases.
5. Migrate the first-party app to preferred routes.
6. Deprecate or hide legacy/admin routes.
## Old-to-New Route Mapping
| Current Route | Preferred Route |
| --- | --- |
| `POST /generate` | `POST /generations` |
| `POST /generate/stream` | `POST /generations/stream` |
| `POST /generate/{id}/retry` | `POST /generations/{id}/retry` |
| `POST /generate/{id}/regenerate` | `POST /generations/{id}/regenerate` |
| `GET /generate/{id}/status` | `GET /generations/{id}/status` |
| `GET /history` | `GET /generations` |
| `GET /history/{id}` | `GET /generations/{id}` |
| `GET /audio/{id}` | `GET /generations/{id}/audio` |
| `GET /history/{id}/export` | `GET /generations/{id}/export` |
| `GET /history/{id}/export-audio` | `GET /generations/{id}/export-audio` |
| `PUT /profiles/samples/{sample_id}` | `PUT /profiles/{profile_id}/samples/{sample_id}` |
| `DELETE /profiles/samples/{sample_id}` | `DELETE /profiles/{profile_id}/samples/{sample_id}` |
| `POST /tasks/clear` | `POST /admin/tasks/clear` |
| `POST /cache/clear` | `POST /admin/cache/clear` |
| `POST /shutdown` | `POST /admin/shutdown` |
| `POST /watchdog/disable` | `POST /admin/watchdog/disable` |
## Risks and Mitigations
### Risk: App regressions during endpoint migration
- Mitigation: Add new routes before changing client usage.
- Mitigation: Keep payloads identical while paths change.
### Risk: Docs still drift after cleanup
- Mitigation: Add CI enforcement and a release checklist step.
### Risk: Third-party local scripts break on removal
- Mitigation: Prefer indefinite aliases for one-person local workflows unless maintenance becomes painful.
### Risk: Admin endpoints remain dangerous in remote mode
- Mitigation: Hide and gate them before promoting remote deployment more broadly.
## Definition of Done
The refactor can be considered complete when all of the following are true:
- OpenAPI, checked-in docs, and backend models match.
- The preferred public API is resource-oriented and documented consistently.
- The Voicebox app uses preferred routes exclusively.
- Legacy routes are either deprecated with a timeline or intentionally retained as compatibility aliases.
- Operational endpoints are clearly separated from the public app API.
+1 -6
View File
@@ -1,9 +1,4 @@
import {
defineConfig,
defineDocs,
frontmatterSchema,
metaSchema,
} from 'fumadocs-mdx/config';
import { defineConfig, defineDocs, frontmatterSchema, metaSchema } from 'fumadocs-mdx/config';
// You can customise Zod schemas for frontmatter and `meta.json` here
// see https://fumadocs.dev/docs/mdx/collections
+4 -14
View File
@@ -2,11 +2,7 @@
"compilerOptions": {
"baseUrl": ".",
"target": "ESNext",
"lib": [
"dom",
"dom.iterable",
"esnext"
],
"lib": ["dom", "dom.iterable", "esnext"],
"allowJs": true,
"skipLibCheck": true,
"strict": true,
@@ -20,12 +16,8 @@
"jsx": "react-jsx",
"incremental": true,
"paths": {
"@/*": [
"./*"
],
"@/.source": [
".source"
]
"@/*": ["./*"],
"@/.source": [".source"]
},
"plugins": [
{
@@ -40,7 +32,5 @@
".next/types/**/*.ts",
".next/dev/types/**/*.ts"
],
"exclude": [
"node_modules"
]
"exclude": ["node_modules"]
}
+14 -2
View File
@@ -69,10 +69,22 @@ setup-python:
}
Write-Host "Installing Python dependencies..."
& "{{ python }}" -m pip install --upgrade pip -q
$hasNvidia = $null -ne (Get-WmiObject Win32_VideoController | Where-Object { $_.Name -match 'NVIDIA' })
$gpus = Get-CimInstance Win32_VideoController | Select-Object -ExpandProperty Name
Write-Host "Detected GPUs: $($gpus -join ', ')"
$hasNvidia = ($gpus | Where-Object { $_ -match 'NVIDIA' }).Count -gt 0
$hasIntelArc = ($gpus | Where-Object { $_ -match 'Arc' }).Count -gt 0
if ($hasNvidia) { \
Write-Host "NVIDIA GPU detected — installing PyTorch with CUDA support..."; \
& "{{ pip }}" install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu126; \
& "{{ pip }}" install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu128; \
} elseif ($hasIntelArc) { \
Write-Host "Intel Arc GPU detected — installing PyTorch with XPU support..."; \
& "{{ pip }}" install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/xpu; \
& "{{ pip }}" install intel-extension-for-pytorch --index-url https://download.pytorch.org/whl/xpu; \
} else { \
Write-Host "No NVIDIA or Intel Arc GPU detected — using CPU-only PyTorch."; \
Write-Host "If you have an Intel Arc GPU, install XPU support manually:"; \
Write-Host " pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/xpu"; \
Write-Host " pip install intel-extension-for-pytorch --index-url https://download.pytorch.org/whl/xpu"; \
}
& "{{ pip }}" install -r {{ backend_dir }}/requirements.txt
& "{{ pip }}" install --no-deps chatterbox-tts
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@voicebox/landing",
"version": "0.3.1",
"version": "0.4.0",
"description": "Landing page for voicebox.sh",
"scripts": {
"dev": "bun --bun next dev --turbo",
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "voicebox",
"version": "0.3.1",
"version": "0.4.0",
"private": true,
"workspaces": [
"app",
+5 -5
View File
@@ -3,13 +3,13 @@ Package the PyInstaller --onedir CUDA build into two archives.
Takes the PyInstaller --onedir output directory and splits it into:
1. voicebox-server-cuda.tar.gz — server core (exe + non-NVIDIA deps)
2. cuda-libs-cu126.tar.gz — NVIDIA runtime libraries only
2. cuda-libs-cu128.tar.gz — NVIDIA runtime libraries only
3. cuda-libs.json — version manifest for the CUDA libs
Usage:
python scripts/package_cuda.py backend/dist/voicebox-server-cuda/
python scripts/package_cuda.py backend/dist/voicebox-server-cuda/ --output release-assets/
python scripts/package_cuda.py backend/dist/voicebox-server-cuda/ --cuda-libs-version cu126-v1
python scripts/package_cuda.py backend/dist/voicebox-server-cuda/ --cuda-libs-version cu128-v1
"""
import argparse
@@ -208,13 +208,13 @@ def main():
parser.add_argument(
"--cuda-libs-version",
type=str,
default="cu126-v1",
help="Version string for the CUDA libs archive (default: cu126-v1)",
default="cu128-v1",
help="Version string for the CUDA libs archive (default: cu128-v1)",
)
parser.add_argument(
"--torch-compat",
type=str,
default=">=2.6.0,<2.11.0",
default=">=2.7.0,<2.11.0",
help="Torch version compatibility range (default: >=2.6.0,<2.11.0)",
)
args = parser.parse_args()
+1 -1
View File
@@ -1,7 +1,7 @@
{
"name": "@voicebox/tauri",
"private": true,
"version": "0.3.1",
"version": "0.4.0",
"type": "module",
"scripts": {
"dev": "vite",
+1 -1
View File
@@ -5041,7 +5041,7 @@ checksum = "0b928f33d975fc6ad9f86c8f283853ad26bdd5b10b7f1542aa2fa15e2289105a"
[[package]]
name = "voicebox"
version = "0.2.3"
version = "0.3.1"
dependencies = [
"base64 0.22.1",
"core-foundation-sys",
+1 -1
View File
@@ -1,6 +1,6 @@
[package]
name = "voicebox"
version = "0.3.1"
version = "0.4.0"
description = "A production-quality desktop app for Qwen3-TTS voice cloning and generation"
authors = ["you"]
license = ""
+4
View File
@@ -5,6 +5,10 @@ fn main() {
// Link Swift runtime libraries for screencapturekit crate
#[cfg(target_os = "macos")]
{
// ScreenCaptureKit does not exist on macOS 11, so weak-link it to
// allow the app to launch and gate usage at runtime instead.
println!("cargo:rustc-link-arg=-Wl,-weak_framework,ScreenCaptureKit");
// Add Swift runtime library paths to RPATH
println!("cargo:rustc-link-arg=-Wl,-rpath,/usr/lib/swift");
println!("cargo:rustc-link-arg=-L/usr/lib/swift");
+21 -11
View File
@@ -13,6 +13,7 @@ use screencapturekit::{
},
};
use std::io::Cursor;
use std::process::Command;
use std::sync::{Arc, Mutex};
use tokio::sync::mpsc;
@@ -20,6 +21,10 @@ pub async fn start_capture(
state: &AudioCaptureState,
max_duration_secs: u32,
) -> Result<(), String> {
if !is_supported() {
return Err("System audio capture requires macOS 12.3 or newer.".to_string());
}
// Reset previous samples
state.reset();
@@ -144,17 +149,22 @@ pub async fn stop_capture(state: &AudioCaptureState) -> Result<String, String> {
}
pub fn is_supported() -> bool {
// ScreenCaptureKit requires macOS 12.3+
// Check if we're on a supported version
#[cfg(target_os = "macos")]
{
// Basic check - ScreenCaptureKit should be available on macOS 12.3+
true
}
#[cfg(not(target_os = "macos"))]
{
false
}
macos_version_at_least(12, 3)
}
fn macos_version_at_least(required_major: u64, required_minor: u64) -> bool {
let output = match Command::new("sw_vers").arg("-productVersion").output() {
Ok(output) if output.status.success() => output,
_ => return false,
};
let version = String::from_utf8_lossy(&output.stdout);
let mut parts = version.trim().split('.');
let major = parts.next().and_then(|part| part.parse::<u64>().ok()).unwrap_or(0);
let minor = parts.next().and_then(|part| part.parse::<u64>().ok()).unwrap_or(0);
major > required_major || (major == required_major && minor >= required_minor)
}
fn extract_audio_samples(sample_buffer: CMSampleBuffer) -> Result<Vec<f32>, String> {
+17 -1
View File
@@ -401,9 +401,25 @@ impl AudioOutputState {
eprintln!("play_to_device: Failed to play stream: {}", e);
format!("Failed to play stream: {}", e)
})?;
eprintln!("play_to_device: Stream started successfully");
// Keep the stream alive until playback finishes.
// Previously the stream was dropped immediately on function return,
// causing silent playback (cpal stops output when its Stream is dropped).
let total_samples = {
buffer.lock().unwrap().len()
};
loop {
let pos = position.load(std::sync::atomic::Ordering::Relaxed);
if pos >= total_samples || stop_flag.load(std::sync::atomic::Ordering::Relaxed) {
break;
}
std::thread::sleep(std::time::Duration::from_millis(10));
}
// stream is dropped here, after audio has finished playing
drop(stream);
eprintln!("play_to_device: Function completed successfully");
Ok(())
}
+80 -8
View File
@@ -53,6 +53,41 @@ fn find_voicebox_pid_on_port(port: u16) -> Option<u32> {
None
}
/// Check if a Voicebox server is responding on the given port.
///
/// Sends an HTTP GET to `/health` and returns `true` only if the response
/// is valid JSON matching the Voicebox `HealthResponse` schema — specifically
/// `status` must be `"healthy"`, and both `model_loaded` and `gpu_available`
/// must be present as booleans. This prevents misidentifying an unrelated
/// service that happens to expose a `/health` endpoint.
#[allow(dead_code)] // Used in platform-specific cfg blocks
fn check_health(port: u16) -> bool {
let url = format!("http://127.0.0.1:{}/health", port);
match reqwest::blocking::Client::builder()
.timeout(std::time::Duration::from_secs(3))
.build()
{
Ok(client) => match client.get(&url).send() {
Ok(resp) => {
if !resp.status().is_success() {
return false;
}
// Parse as JSON and validate Voicebox-specific fields
match resp.json::<serde_json::Value>() {
Ok(body) => {
body.get("status").and_then(|v| v.as_str()) == Some("healthy")
&& body.get("model_loaded").map(|v| v.is_boolean()).unwrap_or(false)
&& body.get("gpu_available").map(|v| v.is_boolean()).unwrap_or(false)
}
Err(_) => false,
}
}
Err(_) => false,
},
Err(_) => false,
}
}
struct ServerState {
child: Mutex<Option<tauri_plugin_shell::process::CommandChild>>,
server_pid: Mutex<Option<u32>>,
@@ -80,7 +115,8 @@ async fn start_server(
return Ok(format!("http://127.0.0.1:{}", SERVER_PORT));
}
// Check if a voicebox server is already running on our port (from previous session with keep_running=true)
// Check if a voicebox server is already running on our port (from previous session with keep_running=true,
// or an externally started server e.g. via `python`, `uvicorn`, Docker, etc.)
#[cfg(unix)]
{
use std::process::Command;
@@ -101,6 +137,20 @@ async fn start_server(
*state.server_pid.lock().unwrap() = Some(pid);
return Ok(format!("http://127.0.0.1:{}", SERVER_PORT));
}
} else {
// Process name doesn't contain "voicebox" — could be an external
// Python/uvicorn/Docker server. Verify via HTTP health check.
println!("Port {} in use by '{}' (PID: {}), checking if it's a Voicebox server...", SERVER_PORT, command, pid_str);
if check_health(SERVER_PORT) {
println!("Health check passed — reusing external server on port {}", SERVER_PORT);
return Ok(format!("http://127.0.0.1:{}", SERVER_PORT));
}
println!("Health check failed — port is occupied by a non-Voicebox process");
return Err(format!(
"Port {} is already in use by another application ({}). \
Close it or change the Voicebox server port.",
SERVER_PORT, command
));
}
}
}
@@ -114,18 +164,24 @@ async fn start_server(
&format!("127.0.0.1:{}", SERVER_PORT).parse().unwrap(),
std::time::Duration::from_secs(1),
).is_ok() {
// Port is in use — check if it's a voicebox process
// Port is in use — check if it's a voicebox process by name first
if let Some(pid) = find_voicebox_pid_on_port(SERVER_PORT) {
println!("Found existing voicebox-server on port {} (PID: {}), reusing it", SERVER_PORT, pid);
*state.server_pid.lock().unwrap() = Some(pid);
return Ok(format!("http://127.0.0.1:{}", SERVER_PORT));
} else {
return Err(format!(
"Port {} is already in use by another application. \
Close the other application or change the Voicebox port.",
SERVER_PORT
));
}
// Process name doesn't match — could be an external Python/Docker server.
// Verify via HTTP health check before giving up.
println!("Port {} in use by unknown process, checking if it's a Voicebox server...", SERVER_PORT);
if check_health(SERVER_PORT) {
println!("Health check passed — reusing external server on port {}", SERVER_PORT);
return Ok(format!("http://127.0.0.1:{}", SERVER_PORT));
}
return Err(format!(
"Port {} is already in use by another application. \
Close the other application or change the Voicebox port.",
SERVER_PORT
));
}
}
@@ -804,6 +860,22 @@ pub fn run() {
// Tell the server to disable its watchdog so it survives
// after this process exits.
println!("Keep server running: disabling watchdog...");
// Write a sentinel file as a reliable fallback. On Windows
// the HTTP request below can race with process exit, leaving
// the watchdog unaware it should stay alive. The sentinel
// file is checked during the watchdog grace period.
let data_dir = app
.path()
.app_data_dir()
.unwrap_or_default();
let sentinel = data_dir.join(".keep-running");
if let Err(e) = std::fs::write(&sentinel, b"1") {
eprintln!("Failed to write keep-running sentinel: {}", e);
} else {
println!("Wrote keep-running sentinel to {:?}", sentinel);
}
let client = reqwest::blocking::Client::builder()
.timeout(std::time::Duration::from_secs(2))
.build()
+1 -1
View File
@@ -1,7 +1,7 @@
{
"$schema": "https://schema.tauri.app/config/2",
"productName": "Voicebox",
"version": "0.3.1",
"version": "0.4.0",
"identifier": "sh.voicebox.app",
"build": {
"beforeDevCommand": "bun run dev",
+2 -3
View File
@@ -2,9 +2,8 @@ import { invoke } from '@tauri-apps/api/core';
import type { PlatformAudio, AudioDevice } from '@/platform/types';
export const tauriAudio: PlatformAudio = {
isSystemAudioSupported(): boolean {
// This will be checked dynamically via invoke
return true; // Tauri supports it, but actual support depends on platform
async isSystemAudioSupported(): Promise<boolean> {
return await invoke<boolean>('is_system_audio_supported');
},
async startSystemAudioCapture(maxDurationSecs: number): Promise<void> {
+1 -1
View File
@@ -1,7 +1,7 @@
{
"name": "@voicebox/web",
"private": true,
"version": "0.3.1",
"version": "0.4.0",
"type": "module",
"scripts": {
"dev": "vite",

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