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Author SHA1 Message Date
3c1e8512b9 fix(build): install mlx-audio/mlx-lm with --no-deps to bypass transformers 5.x conflict (#482)
The previous fix (#481) capped transformers at 4.57.6 in requirements-mlx.txt,
but pip's clean resolver in CI can't satisfy that alongside mlx-audio>=0.3.1
(declares `transformers==5.0.0rc3` or `>=5.0.0`) — it backtracks through every
transformers and tokenizers version and exits with `ResolutionImpossible`.

The dev install worked only because mlx-audio 0.4.1 was already present, so
pip never tried to re-resolve.

mlx-audio 0.4.1 + mlx-lm 0.31.1 both declare transformers>=5.x but the API
surface we actually use works fine on 4.57.x in practice (verified across all
engines in dev). Install both --no-deps to bypass the resolver; transitive
runtime deps (huggingface_hub, librosa, numpy, numba, pyloudnorm, etc.) are
already pulled in by requirements.txt.

Co-authored-by: Claude Opus 4.7 (1M context) <[email protected]>
2026-04-18 17:43:31 -07:00
bf58750447 fix(build): pin transformers in MLX requirements to prevent 5.x upgrade (#481)
mlx-audio depends on `transformers` with no upper bound. Installing
requirements-mlx.txt after requirements.txt lets pip upgrade transformers
past the 4.57.x cap to 5.x, which breaks three engines in the frozen MLX
bundle:

- qwen-custom-voice: `check_model_inputs` was rewritten to take `func` as
  positional, so `@check_model_inputs()` factory calls fail with
  `TypeError: missing 1 required positional argument: 'func'`
- tada-1b: `PretrainedConfig.__init_subclass__` now applies `@dataclass`,
  which rejects tada's `strides: list = []` mutable default
- luxtts: Whisper init hits `AssertionError` in `torch._refs.normal_`

Restating the same constraint here keeps mlx-audio's transformers
dependency from quietly winning the resolver.

Co-authored-by: Claude Opus 4.7 (1M context) <[email protected]>
2026-04-18 17:05:36 -07:00
Jamie PineandGitHub 2d56309bdd Change 'About' link text to 'Models' 2026-04-18 16:46:23 -07:00
James Pine 0445be295c tests and better website 2026-04-18 16:19:12 -07:00
James Pine 8d550a5f7c Bump version: 0.4.0 → 0.4.1 2026-04-18 15:15:58 -07:00
Esteban FraccasciaandGitHub 795bd54381 fix(linux): use pactl to detect PipeWire/PulseAudio monitor for system audio capture (#457)
cpal 0.15 uses ALSA as its Linux backend, which does not expose
PulseAudio/PipeWire monitor sources. The previous approach searched
for 'monitor' in cpal device names, which never matched on most
Linux systems, silently falling back to the microphone input.

This fix:
- Detects the correct monitor source via 'pactl get-default-sink'
  and 'pactl list short sources'
- Sets PULSE_SOURCE env var before cpal initialization so PulseAudio's
  ALSA plugin routes the default input through the monitor
- Preserves the original name-based search as fallback when pactl is
  unavailable
- No new dependencies added

Tested on PipeWire 1.0.5 with Realtek ALC897 (HD-Audio Generic).
2026-04-18 03:15:05 -07:00
a6ab5f3858 Add initial frontend quality gates and TS hardening (#418)
Co-authored-by: Erion De Andrade <[email protected]>
2026-04-18 03:14:43 -07:00
9d7e4a417e fix(api-client): declare moved + errors on migrateModels response type (#470)
ModelManagement.tsx reads migrationResult.moved (added in #433) but
apiClient.migrateModels() was typed as returning only { source, destination }.
The backend actually returns { moved: int, errors: list[str], source, destination }
(backend/routes/models.py:140, 168). Widen the TS return type so the check
typechecks under the new CI gate from #418.

Co-authored-by: Claude Opus 4.7 (1M context) <[email protected]>
2026-04-18 03:14:08 -07:00
882cabc7d2 fix: warn user when no models to migrate during storage change (#433)
When user attempts to change model storage location with no models
downloaded, the migration API returns moved=0 early. Previously the UI
would still call setCustomModelsDir() and restart the server, causing
unexpected behavior (hang/connection lost).

This change checks migrationResult.moved === 0 and shows a helpful
toast message instead of proceeding with the storage change.

Fixes: #426

Co-authored-by: fuleinist <[email protected]>
2026-04-18 03:13:06 -07:00
9c76b5de2c docs: clarify paralinguistic tag support in quick start (#450)
Co-authored-by: txhno <[email protected]>
2026-04-18 03:12:46 -07:00
Cocoon-BreakandGitHub 4560b7378a fix: delete version rows and files in delete_generations_by_profile (Closes #446) (#447)
Signed-off-by: Cocoon-Break <[email protected]>
2026-04-18 03:12:39 -07:00
高巨龙andGitHub abd9943430 Fix migration dialog hanging when no models are present (#439)
When migrating model path with an empty cache, backend returned early without emitting migration completion SSE, causing frontend overlay to hang. This patch emits complete status for empty migrations.
2026-04-18 03:12:32 -07:00
c8cb12f1bc fix(build): repair frozen-binary imports for kokoro, chatterbox-multilingual, scipy, transformers (#438)
* fix(build): bundle kokoro source files for transformers runtime introspection

transformers opens .py source files at runtime to check attention/MoE
implementation via regex (e.g. _can_set_attn_implementation). PyInstaller's
--hidden-import only bundles .pyc bytecode, so kokoro/modules.py was missing
from the bundle causing a FileNotFoundError on Kokoro model load.

Switch from individual --hidden-import entries to --collect-all kokoro in both
build_binary.py and voicebox-server.spec. The kokoro package is 172K so no
meaningful bundle size impact.

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

* fix(build): use SPECPATH for runtime hook instead of hardcoded absolute path

The linter expanded runtime_hooks=[] to an absolute /Users/... path which
would break CI and other dev machines. Use os.path.join(SPECPATH, ...) to
mirror the relative approach in build_binary.py.

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

* fix(build): runtime hook to work around PyInstaller + Python 3.12 import breakages

Four distinct bundling-specific crashes blocked Kokoro and Qwen CustomVoice
from loading in the frozen binary:

1. torch._dynamo import triggered via class-body decorators
   (@torch._dynamo.allow_in_graph on PreTrainedModel,
   @torch.compiler.disable in flex_attention) pulls in torch._numpy._ufuncs
   which crashes on module load with NameError: name 'name' is not defined.

2. AlbertModel (Kokoro) triggers @auto_docstring -> modeling_auto ->
   GenerationMixin -> candidate_generator -> sklearn -> scipy, which hits
   the same class of bug in scipy.stats._distn_infrastructure (NameError:
   name 'obj' is not defined).

3. AutoModel (Qwen) pulls the same sklearn -> scipy chain directly.

4. librosa (required by most TTS engines) -> scipy.signal -> scipy.stats
   hits the _distn_infrastructure crash regardless of the transformers
   stubs above.

The root cause of (1) and (4) is that PyInstaller's frozen importer runs
module-level `for X in [<list-comp using dir()>]:` loops with an empty
iterable, leaving the loop variable unbound. Trailing `del obj` / unrelated
references then crash.

Fix: a single runtime hook (pyi_rth_torch_compiler_disable.py) installs:

- sys.modules stubs for torch._dynamo and torch._dynamo.config, plus a
  meta-path finder for torch._dynamo.* submodules — voicebox never uses
  torch.compile/dynamo for inference, so a permissive no-op stub (callable
  as decorator, falsey as predicate, context-manager-safe for
  TransformGetItemToIndex) is drop-in safe.
- meta-path finder stubs for transformers.utils.auto_docstring and
  transformers.generation.candidate_generator — both import-chain
  short-circuits; docstrings and speculative decoding aren't used for TTS.
- meta-path finder for scipy.stats._distn_infrastructure that reads the
  real .py source via the wrapped loader's get_source(), replaces the
  bundling-broken `del obj` with `globals().pop('obj', None)`, and
  compile+exec's the patched source. This keeps the real scipy module
  intact so librosa and everything downstream works normally.

Supporting changes:

- backend/pyi_hooks/hook-scipy.stats._distn_infrastructure.py sets
  module_collection_mode = "pyz+py" so the .py source is actually in the
  bundle for the runtime patcher to read.
- build_binary.py and voicebox-server.spec register the runtime hook and
  the new hooks dir.

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>

* fix(build): force transformers torch<2.6 mask path and bundle spacy_pkuseg

- patch transformers.masking_utils to set _is_torch_greater_or_equal_than_2_6
  = False, forcing sdpa_mask_older_torch and avoiding the vmap .item() crash
  that breaks Qwen CustomVoice generation (our torch._dynamo stub can't
  reproduce TransformGetItemToIndex's graph transform).
- add PyInstaller hook to bundle transformers.masking_utils .py source so the
  runtime finder can source-patch it.
- --collect-all spacy_pkuseg so Chatterbox Multilingual can load its Chinese
  segmenter (dicts/default.pkl + native .so extensions).
- add per-finder install diagnostics + _HOOK_VERSION marker to make future
  bundle-only regressions easier to triage.

Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]>

* fix(build): pass PyInstaller hook paths relative so .spec is portable

Absolute paths ended up in the auto-regenerated voicebox-server.spec
because build_binary.py prefixed every --runtime-hook and
--additional-hooks-dir with str(backend_dir / ...). That broke builds
on any machine whose checkout wasn't at /Users/jamie/... and anyone
invoking pyinstaller voicebox-server.spec directly.

os.chdir(backend_dir) already runs before PyInstaller (same reason
server.py works as a bare filename), so the backend_dir prefix is
unnecessary. Drop it so the generated spec references pyi_hooks/,
pyi_rth_numpy_compat.py, pyi_rth_torch_compiler_disable.py as repo-
relative paths.

Co-Authored-By: Claude Opus 4.7 (1M context) <[email protected]>

---------

Co-authored-by: Claude Opus 4.6 (1M context) <[email protected]>
2026-04-18 03:12:13 -07:00
Andrew BarnesandGitHub 54a3bf322e fix: add generation cancellation flow (#444) 2026-04-18 02:51:39 -07:00
476abe07fc fix(paths): strip legacy "data/" prefix when resolving stored paths (#440)
0.3.0 sometimes stored relative media paths with the data-dir name baked in
(e.g. "data/profiles/<uuid>/sample.wav"). resolve_storage_path joined those
directly with _data_dir, producing "<data_dir>/data/profiles/..." — a
spurious double nest that breaks file reads after upgrading to 0.4.0.

The 0.4.0 startup migration didn't catch it because resolve_storage_path
produced the buggy double-nested path, to_storage_path saw "data" at the
first (legitimate) index, and the normalized value matched the stored value
so the row was skipped.

Strip any leading "data/" component before joining. This unblocks runtime
reads and lets _normalize_storage_paths rewrite the affected rows on next
startup — no manual migration needed.

Fixes "No such file or directory: '<data_dir>/data/profiles/...'" and
associated 404s on GET /audio/<id> after upgrading from 0.3.0 to 0.4.0.

Co-authored-by: Claude Opus 4.6 (1M context) <[email protected]>
2026-04-17 17:53:11 -07:00
James PineandClaude Opus 4.6 67bf8e906a docs/landing: update for 0.4.0 — new engines, GPU docs, donate button, voice docs restructure
Docs:
- Add gpu-acceleration.mdx (all 9 platform/GPU combos, CUDA backend swap, Blackwell, XPU, troubleshooting)
- Add preset-voices.mdx (Kokoro 50 voices, Qwen CustomVoice 9 voices, instruct mode docs)
- Restructure voice-cloning.mdx to cover all 5 cloning engines with comparison table
- Restructure creating-voice-profiles.mdx around cloned vs preset workflows
- Update voice-profiles.mdx schema with voice_type discriminator, preset/design columns

Landing:
- Add 3 new engine cards (Qwen CustomVoice, HumeAI TADA, Kokoro) to Multi-Engine section
- Add Donate button (Buy Me a Coffee) to navbar and footer
- Add DONATE_URL constant

Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
2026-04-16 19:51:43 -07:00
55 changed files with 2884 additions and 678 deletions
+1 -1
View File
@@ -1,5 +1,5 @@
[bumpversion]
current_version = 0.4.0
current_version = 0.4.1
commit = True
tag = True
tag_name = v{new_version}
+26
View File
@@ -0,0 +1,26 @@
name: CI
on:
pull_request:
push:
branches:
- main
jobs:
frontend-quality:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Setup Bun
uses: oven-sh/setup-bun@v2
- name: Install dependencies
run: bun install --frozen-lockfile
- name: Typecheck app + web
run: bun run typecheck
- name: Build web smoke test
run: bun run build:web
+9
View File
@@ -68,6 +68,15 @@ jobs:
if: matrix.backend == 'mlx'
run: |
pip install -r backend/requirements-mlx.txt
# mlx-audio>=0.3.1 and mlx-lm>=0.31.1 both declare transformers>=5.x,
# which conflicts with our 4.57.x cap. The runtime APIs we use work
# fine on transformers 4.57.x in practice (verified in dev), so install
# them --no-deps. mlx-audio's other runtime deps (huggingface_hub,
# librosa, numpy, numba, pyloudnorm) are already in requirements.txt;
# the rest (sounddevice, miniaudio, protobuf, sentencepiece, pyyaml,
# jinja2) are pulled in by other engines.
pip install --no-deps mlx-lm==0.31.1
pip install --no-deps mlx-audio==0.4.1
- name: Build Python server (Linux/macOS)
if: matrix.platform != 'windows-latest'
+5
View File
@@ -63,3 +63,8 @@ nul
tmp/
temp/
*.tmp
# E2E test artifacts
backend/tests/results/
backend/tests/fixtures/reference_voice.wav
backend/tests/fixtures/reference_voice.txt
+42 -1
View File
@@ -7,6 +7,46 @@
## [Unreleased]
## [0.4.1] - 2026-04-18
A fast follow-up to 0.4.0 focused on making the new engines actually load in the production binary — plus generation cancellation, Linux system-audio capture, and the repo's first PR-time type check. Five first-time contributors shipped in this release.
0.4.0 introduced three new TTS engines, but the frozen PyInstaller binary tripped over several Python-ecosystem quirks that don't show up in the dev venv: `transformers` opening `.py` sources at runtime, `scipy.stats._distn_infrastructure` hitting a frozen-importer `NameError`, and `chatterbox-multilingual` failing to find its Chinese segmenter dictionary. This release patches all of those in one sweep.
### Frozen-Binary Reliability ([#438](https://github.com/jamiepine/voicebox/pull/438))
- **Kokoro** now bundles `.py` sources alongside `.pyc` via `--collect-all kokoro` so `transformers`' `_can_set_attn_implementation` regex scan can read them — previously `FileNotFoundError: kokoro/modules.py` killed Kokoro loading in production builds
- **Chatterbox Multilingual** now bundles `spacy_pkuseg/dicts/default.pkl` and the package's native `.so` extensions via `--collect-all spacy_pkuseg` — previously the Chinese word segmenter crashed with `FileNotFoundError` on first load
- **scipy.stats._distn_infrastructure** — new runtime hook source-patches the trailing `del obj` (which raises `NameError` under PyInstaller's frozen importer because the preceding list comprehension evaluates empty) to `globals().pop('obj', None)`, unblocking `librosa` → `scipy.signal` → `scipy.stats` for every TTS engine that depends on librosa
- **transformers.masking_utils** — same runtime hook forces `_is_torch_greater_or_equal_than_2_6 = False` so the older `sdpa_mask_older_torch` path is selected; the 2.6+ path uses `TransformGetItemToIndex()`, a real `torch._dynamo` graph transform our permissive stub can't reproduce
- **torch._dynamo** — no-op stub replaces the real module before `transformers` imports it, preventing the `torch._numpy._ufuncs` import crash (`NameError: name 'name' is not defined`) that blocked Kokoro and every engine pulling in `flex_attention`
- `.spec` paths are now repo-relative instead of absolute, so the generated spec is portable across machines and CI
### Generation
- **Cancel queued or running generations** ([#444](https://github.com/jamiepine/voicebox/pull/444)) — new `/generate/{id}/cancel` endpoint and a Stop button on the history row while generating. The serial queue now tracks per-ID state (queued / running / cancelled) so queued jobs are skipped before the worker picks them up and running jobs are `.cancel()`-ed mid-flight; `run_generation` catches `CancelledError` and marks the row `failed` with a "cancelled" error.
- **Legacy `data/` path prefix resolution** ([#440](https://github.com/jamiepine/voicebox/pull/440)) — generations stored with the old `data/` prefix under pre-0.4 installs now resolve correctly after the storage root moved, fixing 404s for historical audio.
### Model Migration
- Migration dialog no longer hangs when the cache is empty ([#439](https://github.com/jamiepine/voicebox/pull/439)) — the backend now emits a completion SSE event even when zero models are moved.
- Storage-change flow surfaces a toast when there's nothing to migrate ([#433](https://github.com/jamiepine/voicebox/pull/433)) instead of proceeding with a no-op move and restarting the server.
- Deleting all generations from a voice profile now deletes the associated version files and DB rows too ([#447](https://github.com/jamiepine/voicebox/pull/447)) — previously orphaned versions accumulated in storage.
### Platform
- **Linux system audio capture** ([#457](https://github.com/jamiepine/voicebox/pull/457)) — `cpal`'s ALSA backend doesn't expose PulseAudio/PipeWire monitor sources by name, so the previous device-name search never matched and silently fell back to the microphone. Detection now uses `pactl get-default-sink` + `pactl list short sources` and routes via `PULSE_SOURCE`, with the name-based search retained as a fallback when `pactl` is absent.
### Frontend CI
- First PR-time quality gate ([#418](https://github.com/jamiepine/voicebox/pull/418)) — new `.github/workflows/ci.yml` runs `bun run typecheck` + `bun run build:web` on every PR. Fixed pre-existing type issues that were being suppressed with `@ts-expect-error`, cleaned up a dep-array typo (`[platform.metadata.isTauricheckOnMountcheckForUpdates]`) in `useAutoUpdater`, and removed 100+ lines of dead `ModelItem` code from `ModelManagement.tsx`.
- Follow-up: widened `apiClient.migrateModels()` return type to include `moved` and `errors` so the storage-change handler typechecks against the real backend response ([#470](https://github.com/jamiepine/voicebox/pull/470)).
### Docs
- Clarified in the Quick Start + README that paralinguistic tags (`[laugh]`, `[sigh]`) only work with Chatterbox Turbo; other engines read them as literal text ([#450](https://github.com/jamiepine/voicebox/pull/450)).
### New Contributors
- [@Bortlesboat](https://github.com/Bortlesboat) — generation cancellation (#444)
- [@gaojulong](https://github.com/gaojulong) — migration dialog hang fix (#439)
- [@fuleinist](https://github.com/fuleinist) — migration no-op toast (#433)
- [@erionjuniordeandrade-a11y](https://github.com/erionjuniordeandrade-a11y) — frontend CI + type hardening (#418)
- [@estefrac](https://github.com/estefrac) — Linux pactl system-audio capture (#457)
## [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.
@@ -555,7 +595,8 @@ 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/v0.4.0...HEAD
[Unreleased]: https://github.com/jamiepine/voicebox/compare/v0.4.1...HEAD
[0.4.1]: https://github.com/jamiepine/voicebox/compare/v0.4.0...v0.4.1
[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
+6 -1
View File
@@ -105,7 +105,12 @@ Five TTS engines with different strengths, switchable per-generation:
### Emotions & Paralinguistic Tags
Type `/` in the text input to insert expressive tags that the model synthesizes inline with speech (Chatterbox Turbo):
Only **Chatterbox Turbo** interprets paralinguistic tags like `[laugh]` and
`[sigh]`. Qwen3-TTS, LuxTTS, Chatterbox Multilingual, and HumeAI TADA read them
literally as text.
With **Chatterbox Turbo** selected, type `/` in the text input to open the tag
inserter and add expressive tags inline with speech:
`[laugh]` `[chuckle]` `[gasp]` `[cough]` `[sigh]` `[groan]` `[sniff]` `[shush]` `[clear throat]`
+3 -3
View File
@@ -6,8 +6,8 @@ We release patches for security vulnerabilities. Which versions are eligible for
| Version | Supported |
| ------- | ------------------ |
| 0.1.x | :white_check_mark: |
| < 0.1 | :x: |
| 0.3.x | :white_check_mark: |
| < 0.3 | :x: |
## Reporting a Vulnerability
@@ -82,7 +82,7 @@ Timeline may vary based on severity and complexity.
## Security Updates
Security updates will be:
- Released as patch versions (e.g., 0.1.1)
- Released as patch versions (e.g., 0.3.2)
- Documented in CHANGELOG.md
- Announced via GitHub releases
- Automatically delivered via auto-updater
+2 -1
View File
@@ -1,11 +1,12 @@
{
"name": "@voicebox/app",
"version": "0.4.0",
"version": "0.4.1",
"private": true,
"type": "module",
"scripts": {
"dev": "vite",
"build": "vite build",
"typecheck": "tsc -p tsconfig.json --noEmit",
"preview": "vite preview",
"lint": "biome lint src",
"lint:fix": "biome lint --write src",
-3
View File
@@ -121,7 +121,6 @@ function App() {
console.log('Dev mode: Skipping auto-start of server (run it separately)');
setServerReady(true); // Mark as ready so UI doesn't show loading screen
// Mark that server was not started by app (so we don't try to stop it on close)
// @ts-expect-error - adding property to window
window.__voiceboxServerStartedByApp = false;
return;
}
@@ -144,13 +143,11 @@ function App() {
useServerStore.getState().setServerUrl(serverUrl);
setServerReady(true);
// Mark that we started the server (so we know to stop it on close)
// @ts-expect-error - adding property to window
window.__voiceboxServerStartedByApp = true;
})
.catch((error) => {
console.error('Failed to auto-start server:', error);
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
+1 -1
View File
@@ -124,7 +124,7 @@ export function AudioTab() {
);
}
const handleChannelDelete = async (e, channelId) => {
const handleChannelDelete = async (e: React.MouseEvent, channelId: string) => {
e.stopPropagation();
if (await confirm('Delete this channel?')) {
deleteChannel.mutate(channelId);
+85 -56
View File
@@ -1,15 +1,14 @@
import { useQueryClient } from '@tanstack/react-query';
import { useMutation, useQueryClient } from '@tanstack/react-query';
import { AnimatePresence, motion } from 'framer-motion';
import {
AlignCenter,
AudioLines,
AudioWaveform,
Download,
FileArchive,
Loader2,
MoreHorizontal,
Play,
RotateCcw,
Square,
Star,
Trash2,
Wand2,
@@ -130,6 +129,23 @@ export function HistoryTable() {
const exportGeneration = useExportGeneration();
const exportGenerationAudio = useExportGenerationAudio();
const importGeneration = useImportGeneration();
const cancelGeneration = useMutation({
mutationFn: (generationId: string) => apiClient.cancelGeneration(generationId),
onSuccess: async (data) => {
await queryClient.invalidateQueries({ queryKey: ['history'] });
toast({
title: 'Cancelling generation',
description: data.message,
});
},
onError: (error) => {
toast({
title: 'Cancel failed',
description: error instanceof Error ? error.message : 'Could not cancel generation',
variant: 'destructive',
});
},
});
const addPendingGeneration = useGenerationStore((state) => state.addPendingGeneration);
const setAudioWithAutoPlay = usePlayerStore((state) => state.setAudioWithAutoPlay);
const restartCurrentAudio = usePlayerStore((state) => state.restartCurrentAudio);
@@ -483,6 +499,8 @@ export function HistoryTable() {
const isPlayable = !isGenerating && !isFailed;
const hasVersions = gen.versions && gen.versions.length > 1;
const isVersionsExpanded = expandedVersionsId === gen.id;
const isCancelling =
cancelGeneration.isPending && cancelGeneration.variables === gen.id;
return (
<div
key={gen.id}
@@ -631,60 +649,71 @@ export function HistoryTable() {
<Trash2 className="h-2 w-2" />
</Button>
</>
) : isGenerating ? (
<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="Cancel generation"
disabled={isCancelling}
onClick={() => cancelGeneration.mutate(gen.id)}
>
{isCancelling ? (
<Loader2 className="h-2 w-2 animate-spin" />
) : (
<Square className="h-2 w-2" />
)}
</Button>
) : (
<>
<DropdownMenu>
<DropdownMenuTrigger asChild>
<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="Actions"
disabled={isGenerating}
>
<MoreHorizontal className="h-2 w-2" />
</Button>
</DropdownMenuTrigger>
<DropdownMenuContent align="end">
<DropdownMenuItem
onClick={() => handlePlay(gen.id, gen.text, gen.profile_id)}
>
<Play className="mr-2 h-4 w-4" />
Play
</DropdownMenuItem>
<DropdownMenuItem
onClick={() => handleDownloadAudio(gen.id, gen.text)}
disabled={exportGenerationAudio.isPending}
>
<Download className="mr-2 h-4 w-4" />
Export Audio
</DropdownMenuItem>
<DropdownMenuItem
onClick={() => handleExportPackage(gen.id, gen.text)}
disabled={exportGeneration.isPending}
>
<FileArchive className="mr-2 h-4 w-4" />
Export Package
</DropdownMenuItem>
<DropdownMenuItem onClick={() => handleApplyEffects(gen.id)}>
<Wand2 className="mr-2 h-4 w-4" />
Apply Effects
</DropdownMenuItem>
<DropdownMenuItem onClick={() => handleRegenerate(gen.id)}>
<RotateCcw className="mr-2 h-4 w-4" />
Regenerate
</DropdownMenuItem>
<DropdownMenuItem
onClick={() => handleDeleteClick(gen.id, gen.profile_name)}
disabled={deleteGeneration.isPending}
// className="text-destructive focus:text-destructive"
>
<Trash2 className="mr-2 h-4 w-4" />
Delete
</DropdownMenuItem>
</DropdownMenuContent>
</DropdownMenu>
</>
<DropdownMenu>
<DropdownMenuTrigger asChild>
<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="Actions"
disabled={isGenerating}
>
<MoreHorizontal className="h-2 w-2" />
</Button>
</DropdownMenuTrigger>
<DropdownMenuContent align="end">
<DropdownMenuItem onClick={() => handlePlay(gen.id, gen.text, gen.profile_id)}>
<Play className="mr-2 h-4 w-4" />
Play
</DropdownMenuItem>
<DropdownMenuItem
onClick={() => handleDownloadAudio(gen.id, gen.text)}
disabled={exportGenerationAudio.isPending}
>
<Download className="mr-2 h-4 w-4" />
Export Audio
</DropdownMenuItem>
<DropdownMenuItem
onClick={() => handleExportPackage(gen.id, gen.text)}
disabled={exportGeneration.isPending}
>
<FileArchive className="mr-2 h-4 w-4" />
Export Package
</DropdownMenuItem>
<DropdownMenuItem onClick={() => handleApplyEffects(gen.id)}>
<Wand2 className="mr-2 h-4 w-4" />
Apply Effects
</DropdownMenuItem>
<DropdownMenuItem onClick={() => handleRegenerate(gen.id)}>
<RotateCcw className="mr-2 h-4 w-4" />
Regenerate
</DropdownMenuItem>
<DropdownMenuItem
onClick={() => handleDeleteClick(gen.id, gen.profile_name)}
disabled={deleteGeneration.isPending}
// className="text-destructive focus:text-destructive"
>
<Trash2 className="mr-2 h-4 w-4" />
Delete
</DropdownMenuItem>
</DropdownMenuContent>
</DropdownMenu>
)}
</div>
</div>
@@ -977,7 +977,19 @@ export function ModelManagement() {
});
try {
// Start the migration (background task)
await apiClient.migrateModels(newDir);
const migrationResult = await apiClient.migrateModels(newDir);
// If no models to migrate, warn user and skip the change
if (migrationResult.moved === 0) {
setMigrating(false);
setMigrationProgress(null);
toast({
title: 'No models to migrate',
description: 'Download at least one model before changing the storage location.',
});
setPendingMigrateDir(null);
return;
}
// Connect to SSE for progress
await new Promise<void>((resolve, reject) => {
@@ -1064,105 +1076,3 @@ export function ModelManagement() {
);
}
interface ModelItemProps {
model: {
model_name: string;
display_name: string;
downloaded: boolean;
downloading?: boolean; // From server - true if download in progress
size_mb?: number;
loaded: boolean;
};
onDownload: () => void;
onDelete: () => void;
isDownloading: boolean; // Local state - true if user just clicked download
formatSize: (sizeMb?: number) => string;
}
function ModelItem({ model, onDownload, onDelete, isDownloading, formatSize }: ModelItemProps) {
// Use server's downloading state OR local state (for immediate feedback before server updates)
const showDownloading = model.downloading || isDownloading;
const statusText = model.loaded
? 'Loaded'
: showDownloading
? 'Downloading'
: model.downloaded
? 'Downloaded'
: 'Not downloaded';
const sizeText =
model.downloaded && model.size_mb && !showDownloading ? `, ${formatSize(model.size_mb)}` : '';
const rowLabel = `${model.display_name}, ${statusText}${sizeText}. Use Tab to reach Download or Delete.`;
return (
<div
className="flex items-center justify-between p-3 border rounded-lg"
role="group"
tabIndex={0}
aria-label={rowLabel}
>
<div className="flex-1">
<div className="flex items-center gap-2">
<span className="font-medium text-sm">{model.display_name}</span>
{model.loaded && (
<Badge variant="default" className="text-xs">
Loaded
</Badge>
)}
{/* Only show Downloaded if actually downloaded AND not downloading */}
{model.downloaded && !model.loaded && !showDownloading && (
<Badge variant="secondary" className="text-xs">
Downloaded
</Badge>
)}
</div>
{model.downloaded && model.size_mb && !showDownloading && (
<div className="text-xs text-muted-foreground mt-1">
Size: {formatSize(model.size_mb)}
</div>
)}
</div>
<div className="flex items-center gap-2">
{model.downloaded && !showDownloading ? (
<div className="flex items-center gap-2">
<div className="flex items-center gap-1 text-sm text-muted-foreground">
<span>Ready</span>
</div>
<Button
size="sm"
onClick={onDelete}
variant="outline"
disabled={model.loaded}
title={model.loaded ? 'Unload model before deleting' : 'Delete model'}
aria-label={
model.loaded ? 'Unload model before deleting' : `Delete ${model.display_name}`
}
>
<Trash2 className="h-4 w-4" />
</Button>
</div>
) : showDownloading ? (
<Button
size="sm"
variant="outline"
disabled
aria-label={`${model.display_name} downloading`}
>
<Loader2 className="h-4 w-4 mr-2 animate-spin" />
Downloading...
</Button>
) : (
<Button
size="sm"
onClick={onDownload}
variant="outline"
aria-label={`Download ${model.display_name}`}
>
<Download className="h-4 w-4 mr-2" />
Download
</Button>
)}
</div>
</div>
);
}
@@ -371,7 +371,7 @@ export function StoryTrackEditor({ storyId, items }: StoryTrackEditorProps) {
}
}, [isResizing, handleResizeMove, handleResizeEnd]);
const handleTimelineClick = (e: React.MouseEvent<HTMLDivElement>) => {
const handleTimelineClick = (e: React.MouseEvent<HTMLElement>) => {
if (!tracksRef.current || draggingItem || trimmingItem) return;
const rect = tracksRef.current.getBoundingClientRect();
const x = e.clientX - rect.left + tracksRef.current.scrollLeft;
+13 -4
View File
@@ -5,7 +5,15 @@ import type { UpdateStatus } from '@/platform/types';
// Re-export UpdateStatus for backwards compatibility
export type { UpdateStatus };
export function useAutoUpdater(checkOnMount = false) {
interface UseAutoUpdaterOptions {
checkOnMount?: boolean;
showToast?: boolean;
}
export function useAutoUpdater(options: boolean | UseAutoUpdaterOptions = false) {
const { checkOnMount } =
typeof options === 'boolean' ? { checkOnMount: options } : { checkOnMount: options.checkOnMount ?? false };
const platform = usePlatform();
const [status, setStatus] = useState<UpdateStatus>(platform.updater.getStatus());
const hasCheckedRef = useRef(false);
@@ -38,10 +46,11 @@ export function useAutoUpdater(checkOnMount = false) {
useEffect(() => {
if (checkOnMount && platform.metadata.isTauri && !hasCheckedRef.current) {
hasCheckedRef.current = true;
checkForUpdates();
checkForUpdates().catch((error) => {
console.error('Auto update check failed:', error);
});
}
// eslint-disable-next-line react-hooks/exhaustive-deps
}, [platform.metadata.isTauricheckOnMountcheckForUpdates]);
}, [checkOnMount, checkForUpdates, platform.metadata.isTauri]);
return {
status,
+1 -1
View File
@@ -73,7 +73,7 @@ export function useAutoUpdater(options: boolean | UseAutoUpdaterOptions = false)
}
// Empty dependency array - only run once on mount
// eslint-disable-next-line react-hooks/exhaustive-deps
}, [platform.metadata.isTauricheckOnMountcheckForUpdates]);
}, [checkOnMount, checkForUpdates, platform.metadata.isTauri]);
// Show toast when update is available
useEffect(() => {
+9 -1
View File
@@ -234,6 +234,12 @@ class ApiClient {
});
}
async cancelGeneration(generationId: string): Promise<{ message: string }> {
return this.request<{ message: string }>(`/generate/${generationId}/cancel`, {
method: 'POST',
});
}
async regenerateGeneration(generationId: string): Promise<GenerationResponse> {
return this.request<GenerationResponse>(`/generate/${generationId}/regenerate`, {
method: 'POST',
@@ -384,7 +390,9 @@ class ApiClient {
return this.request<{ path: string }>('/models/cache-dir');
}
async migrateModels(destination: string): Promise<{ source: string; destination: string }> {
async migrateModels(
destination: string,
): Promise<{ source: string; destination: string; moved: number; errors: string[] }> {
return this.request('/models/migrate', {
method: 'POST',
body: JSON.stringify({ destination }),
+1 -1
View File
@@ -1,3 +1,3 @@
# Backend package
__version__ = "0.4.0"
__version__ = "0.4.1"
+8
View File
@@ -89,6 +89,14 @@ def resolve_storage_path(path: str | Path | None) -> Path | None:
return stored_path
# 0.3.0 records sometimes stored relative paths with the data-dir name
# baked in (e.g. "data/profiles/..."). Joining those directly with
# _data_dir produces a spurious "<data_dir>/data/profiles/..." nest.
if stored_path.parts and stored_path.parts[0] == "data":
stored_path = (
Path(*stored_path.parts[1:]) if len(stored_path.parts) > 1 else Path()
)
return (_data_dir / stored_path).resolve()
+11 -1
View File
@@ -2,4 +2,14 @@
# These should only be installed on aarch64-apple-darwin platforms
mlx>=0.30.0
mlx-audio>=0.3.1
# NOTE: mlx-audio is intentionally not listed here. From 0.3.1 onward it
# declares `transformers==5.0.0rc3` / `>=5.0.0`, which conflicts with the
# `transformers<=4.57.6` cap in requirements.txt and breaks CI's clean
# resolver. The mlx-audio API surface we use (mlx_audio.tts.load,
# mlx_audio.stt.load) works fine on transformers 4.57.x in practice.
#
# Install it via `pip install --no-deps mlx-audio==0.4.1` after this file
# (see .github/workflows/release.yml). All other mlx-audio runtime deps
# (huggingface_hub, librosa, miniaudio, mlx-lm, numba, numpy, protobuf,
# pyloudnorm, sounddevice, tqdm) are already in requirements.txt.
+32 -1
View File
@@ -14,7 +14,7 @@ from .. import models
from ..services import history, profiles, tts
from ..database import Generation as DBGeneration, VoiceProfile as DBVoiceProfile, get_db
from ..services.generation import run_generation
from ..services.task_queue import enqueue_generation
from ..services.task_queue import cancel_generation as cancel_generation_job, enqueue_generation
from ..utils.tasks import get_task_manager
router = APIRouter()
@@ -82,6 +82,7 @@ async def generate_speech(
pass
enqueue_generation(
generation_id,
run_generation(
generation_id=generation_id,
profile_id=data.profile_id,
@@ -127,6 +128,7 @@ async def retry_generation(generation_id: str, db: Session = Depends(get_db)):
)
enqueue_generation(
generation_id,
run_generation(
generation_id=generation_id,
profile_id=gen.profile_id,
@@ -170,6 +172,7 @@ async def regenerate_generation(generation_id: str, db: Session = Depends(get_db
version_id = str(uuid.uuid4())
enqueue_generation(
generation_id,
run_generation(
generation_id=generation_id,
profile_id=gen.profile_id,
@@ -187,6 +190,34 @@ async def regenerate_generation(generation_id: str, db: Session = Depends(get_db
return models.GenerationResponse.model_validate(gen)
@router.post("/generate/{generation_id}/cancel")
async def cancel_generation(generation_id: str, db: Session = Depends(get_db)):
"""Cancel a queued or running generation."""
gen = db.query(DBGeneration).filter_by(id=generation_id).first()
if not gen:
raise HTTPException(status_code=404, detail="Generation not found")
if (gen.status or "completed") not in ("loading_model", "generating"):
raise HTTPException(status_code=400, detail="Only active generations can be cancelled")
cancellation_state = cancel_generation_job(generation_id)
if cancellation_state is None:
raise HTTPException(status_code=409, detail="Generation is no longer cancellable")
if cancellation_state == "queued":
task_manager = get_task_manager()
task_manager.complete_generation(generation_id)
await history.update_generation_status(
generation_id=generation_id,
status="failed",
db=db,
error="Generation cancelled",
)
return {"message": "Queued generation cancelled"}
return {"message": "Generation cancellation requested"}
@router.get("/generate/{generation_id}/status")
async def get_generation_status(generation_id: str, db: Session = Depends(get_db)):
"""SSE endpoint that streams generation status updates."""
+3 -2
View File
@@ -135,14 +135,15 @@ async def migrate_models(request: models.ModelMigrateRequest):
if destination.resolve().is_relative_to(source.resolve()):
raise HTTPException(status_code=400, detail="Destination cannot be inside the current cache directory")
progress_manager = get_progress_manager()
model_dirs = [d for d in source.iterdir() if d.name.startswith("models--") and d.is_dir()]
if not model_dirs:
progress_manager.update_progress("migration", 1, 1, status="complete")
progress_manager.mark_complete("migration")
return {"moved": 0, "errors": [], "source": str(source), "destination": str(destination)}
destination.mkdir(parents=True, exist_ok=True)
progress_manager = get_progress_manager()
same_fs = False
try:
same_fs = source.stat().st_dev == destination.stat().st_dev
+8
View File
@@ -16,6 +16,7 @@ Mode differences:
from __future__ import annotations
import asyncio
import traceback
from typing import Literal, Optional
@@ -126,6 +127,13 @@ async def run_generation(
duration=duration,
)
except asyncio.CancelledError:
await history.update_generation_status(
generation_id=generation_id,
status="failed",
db=bg_db,
error="Generation cancelled",
)
except Exception as e:
traceback.print_exc()
await history.update_generation_status(
+4
View File
@@ -319,6 +319,10 @@ async def delete_generations_by_profile(
count = 0
for generation in generations:
# Delete associated version files and rows first
from . import versions as versions_mod
versions_mod.delete_versions_for_generation(generation.id, db)
# Delete audio file
audio_path = config.resolve_storage_path(generation.audio_path)
if audio_path is not None and audio_path.exists():
+67 -7
View File
@@ -5,12 +5,27 @@ to avoid GPU contention.
import asyncio
import traceback
from dataclasses import dataclass
from typing import Coroutine, Literal
# Keep references to fire-and-forget background tasks to prevent GC
_background_tasks: set = set()
@dataclass
class GenerationJob:
"""Queued generation work plus the generation ID it belongs to."""
generation_id: str
coro: Coroutine
# Generation queue — serializes TTS inference to avoid GPU contention
_generation_queue: asyncio.Queue = None # type: ignore # initialized at startup
_generation_worker_task: asyncio.Task | None = None
_queued_generation_ids: set[str] = set()
_running_generation_tasks: dict[str, asyncio.Task] = {}
_cancelled_generation_ids: set[str] = set()
def create_background_task(coro) -> asyncio.Task:
@@ -24,25 +39,70 @@ def create_background_task(coro) -> asyncio.Task:
async def _generation_worker():
"""Worker that processes generation tasks one at a time."""
while True:
coro = await _generation_queue.get()
job = await _generation_queue.get()
try:
await coro
if job.generation_id in _cancelled_generation_ids:
_cancelled_generation_ids.discard(job.generation_id)
job.coro.close()
continue
task = asyncio.create_task(job.coro)
_running_generation_tasks[job.generation_id] = task
_queued_generation_ids.discard(job.generation_id)
try:
await task
except asyncio.CancelledError:
if not task.cancelled():
raise
except Exception:
traceback.print_exc()
finally:
_running_generation_tasks.pop(job.generation_id, None)
_queued_generation_ids.discard(job.generation_id)
_generation_queue.task_done()
def enqueue_generation(coro):
def enqueue_generation(generation_id: str, coro):
"""Add a generation coroutine to the serial queue."""
_generation_queue.put_nowait(coro)
if _generation_queue is None:
raise RuntimeError("Generation queue has not been initialized")
_queued_generation_ids.add(generation_id)
_generation_queue.put_nowait(GenerationJob(generation_id=generation_id, coro=coro))
def init_queue():
def cancel_generation(generation_id: str) -> Literal["queued", "running"] | None:
"""Cancel a queued or running generation if it is still active."""
running_task = _running_generation_tasks.get(generation_id)
if running_task is not None:
running_task.cancel()
return "running"
if generation_id in _queued_generation_ids:
_queued_generation_ids.discard(generation_id)
_cancelled_generation_ids.add(generation_id)
return "queued"
return None
def init_queue(force: bool = False):
"""Initialize the generation queue and start the worker.
Must be called once during application startup (inside a running event loop).
"""
global _generation_queue
global _generation_queue, _generation_worker_task
global _queued_generation_ids, _running_generation_tasks, _cancelled_generation_ids
if _generation_worker_task is not None and not _generation_worker_task.done():
if not force:
return
_generation_worker_task.cancel()
for task in list(_running_generation_tasks.values()):
task.cancel()
_generation_queue = asyncio.Queue()
create_background_task(_generation_worker())
_queued_generation_ids = set()
_running_generation_tasks = {}
_cancelled_generation_ids = set()
_generation_worker_task = create_background_task(_generation_worker())
+220
View File
@@ -0,0 +1,220 @@
# End-to-End Model Generation Test — Design
## Goal
A single script, runnable on macOS and Windows, that exercises every TTS model against the **frozen PyInstaller binary** (not the dev server), captures per-model pass/fail and error messages, and exits non-zero if any model fails. Generation is strictly sequential — one model loaded at a time.
## Test matrix (10 runs)
Derived from `backend/backends/__init__.py:185-316`. Each row maps to one `POST /generate` call.
| # | engine | model_size | profile kind | notes |
|---|-----------------------|------------|--------------|-------|
| 1 | `qwen` | `1.7B` | cloned | reference audio required |
| 2 | `qwen` | `0.6B` | cloned | |
| 3 | `qwen_custom_voice` | `1.7B` | preset | `preset_voice_id="Ryan"` |
| 4 | `qwen_custom_voice` | `0.6B` | preset | `preset_voice_id="Ryan"` |
| 5 | `luxtts` | — | cloned | English only |
| 6 | `chatterbox` | — | cloned | |
| 7 | `chatterbox_turbo` | — | cloned | English only |
| 8 | `tada` | `1B` | cloned | tada-1b, English only |
| 9 | `tada` | `3B` | cloned | tada-3b-ml, multilingual |
| 10| `kokoro` | — | preset | `preset_voice_id="af_heart"` |
Cloned engines (1, 2, 5, 6, 7, 8, 9) share **one** profile created once with the reference WAV. Preset profiles are created separately, one for kokoro and one for qwen_custom_voice.
Language for every run: `en` (covers every engine's supported set).
## End-to-end flow
```
1. Resolve paths → find binary, build if missing
2. Launch binary → spawn with --port --data-dir --parent-pid
3. Wait for /health → poll until status=="healthy" or 120s timeout
4. Create profiles → 1 cloned + 2 preset, via /profiles (+ /samples)
5. For each (engine, model_size) in matrix:
a. Check cache → GET /models/status → cached? short timeout : long
b. POST /generate → get generation_id
c. Stream /status → consume SSE until completed/failed/timeout
d. Record result → {engine, model_size, status, duration, error, elapsed}
6. Write results → JSON + Markdown table to ./results/
7. Shutdown binary → SIGTERM, fall back to kill, verify port freed
8. Exit code → 0 if all passed, 1 otherwise
```
## Binary resolution
Search order — **first hit wins**:
| Platform | Path | Build type |
|----------|------|------------|
| macOS | `backend/dist/voicebox-server-cuda/voicebox-server-cuda` | onedir (CUDA, rarely on Mac) |
| macOS | `backend/dist/voicebox-server` | onefile (CPU) |
| Windows | `backend\dist\voicebox-server-cuda\voicebox-server-cuda.exe` | onedir (CUDA) |
| Windows | `backend\dist\voicebox-server.exe` | onefile (CPU) |
If none exist, run `python backend/build_binary.py` and wait for it to finish (can take 5-20 min). Fail with a clear error if the build itself fails. `--skip-build` flag forces "error out if no binary" instead of building.
## Spawn command
Mirrors Tauri's launch in `tauri/src-tauri/src/main.rs:369-388`:
```
<binary> --host 127.0.0.1 --port <free-port> --data-dir <tempdir> --parent-pid <test-pid>
```
- **Port**: bind to `0` first in Python to grab a free port, then pass that number.
- **Data dir**: `tempfile.mkdtemp(prefix="voicebox-e2e-")`. Deleted after the run unless `--keep-data-dir`. Profiles and generated WAVs land here.
- **Parent PID**: current Python PID — ensures the backend dies if the test crashes (watchdog in `server.py:102-224`).
- **stdout/stderr**: tee to both a log file in `./results/server-<timestamp>.log` and a rolling in-memory buffer. On model failure, last 100 lines of the buffer are attached to that model's error record.
## Profile setup
One cloned profile shared across all cloning engines:
```http
POST /profiles
{
"name": "e2e-cloned",
"voice_type": "cloned",
"language": "en"
}
```
Then:
```http
POST /profiles/{id}/samples (multipart)
file: <reference WAV>
reference_text: <exact transcription>
```
Two preset profiles:
```http
POST /profiles
{ "name": "e2e-kokoro", "voice_type": "preset", "language": "en",
"preset_engine": "kokoro", "preset_voice_id": "af_heart" }
POST /profiles
{ "name": "e2e-qwen-cv", "voice_type": "preset", "language": "en",
"preset_engine": "qwen_custom_voice", "preset_voice_id": "Ryan" }
```
## Generation request (per matrix row)
```http
POST /generate
{
"profile_id": "<appropriate profile>",
"text": "The quick brown fox jumps over the lazy dog.",
"language": "en",
"engine": "<engine>",
"model_size": "<size or omitted>",
"seed": 42,
"normalize": true
}
```
Response `id` feeds into the SSE status loop (`GET /generate/{id}/status`, `routes/generations.py:190-227`). Loop reads lines until a payload with `status in ("completed", "failed")` arrives, then breaks.
## Timeout strategy (split)
Check `GET /models/status` for the target model **before** generation:
| Cached? | Per-model timeout | Rationale |
|---------|-------------------|-----------|
| Yes | **3 minutes** | Inference only; generous for CPU builds |
| No | **20 minutes** | First-run HF download up to 8 GB (tada-3b-ml) |
On timeout: cancel the SSE stream, mark the row `timeout`, and continue to the next row. Don't abort the whole run on one timeout.
## Result format
`./results/e2e-<platform>-<arch>-<timestamp>.json`:
```json
{
"platform": "darwin-arm64",
"binary": "/abs/path/voicebox-server",
"binary_size_mb": 612,
"started_at": "2026-04-16T12:34:56Z",
"finished_at": "...",
"results": [
{
"engine": "qwen",
"model_size": "1.7B",
"status": "passed|failed|timeout",
"generation_id": "...",
"was_cached": true,
"elapsed_seconds": 12.4,
"audio_duration": 3.1,
"audio_path": "/tmp/.../gen.wav",
"error": null,
"server_log_tail": null
}
]
}
```
Companion `./results/e2e-<...>.md`:
```
# Voicebox E2E — darwin-arm64 — 2026-04-16 12:34
| Engine | Size | Status | Elapsed | Error |
|---------------------|------|--------|---------|-------|
| qwen | 1.7B | PASS | 12.4s | |
| qwen | 0.6B | FAIL | 4.1s | CUDA OOM: ... |
...
```
## CLI flags
```
python -m backend.tests.test_all_models_e2e [flags]
--binary PATH Use this binary instead of auto-detecting
--skip-build Error if no binary found (no auto-build)
--reference-wav PATH Reference audio (default: backend/tests/fixtures/reference_voice.wav)
--reference-text STR Transcription (default: read from fixtures/reference_voice.txt)
--only ENGINE[,...] Run only these engines (e.g. kokoro,qwen)
--skip ENGINE[,...] Skip these engines
--keep-data-dir Don't delete tempdir after run
--timeout-cached SEC Override 180
--timeout-download SEC Override 1200
--port N Override auto-picked port
--output-dir PATH Default: backend/tests/results/
```
## File layout
```
backend/tests/
├── E2E_MODEL_TEST_DESIGN.md (this file)
├── test_all_models_e2e.py (main script, ~400-500 LoC)
├── fixtures/
│ ├── reference_voice.wav (user-provided, ~5-15s clean speech)
│ └── reference_voice.txt (exact transcription)
└── results/ (gitignored)
├── e2e-darwin-arm64-<ts>.json
├── e2e-darwin-arm64-<ts>.md
└── server-<ts>.log
```
The script uses only stdlib + `httpx` (or `requests`) + `sseclient-py` — all already in `backend/requirements.txt`. No pytest to keep it invocable as a single command on fresh checkouts.
## Safety & cleanup
- Always kill the spawned binary in a `try/finally`. On Windows, `taskkill /F /T` the whole tree (Tauri does the same).
- Verify the port is free on shutdown (Tauri port-reuse check in `main.rs:114-186` could otherwise pick up a ghost).
- Don't touch the user's HF cache by default — let the server use `HF_HUB_CACHE` / `VOICEBOX_MODELS_DIR`. Passing `--isolated-cache` would point both env vars at the tempdir for a true cold-start run (opt-in only; would re-download every time).
## Non-goals
- Not validating audio quality (no WER, no waveform comparison). Pass = "endpoint returned `completed` and produced a non-empty WAV".
- Not testing STT (Whisper), effects chains, channels, or streaming endpoints.
- Not running on CI today — human-invoked on dev machines. CI integration is a follow-up once the script is stable.
- No model unload between runs — models stay loaded; server manages its own eviction.
- No version-drift check on the binary.
- No `instruct` parameter exercised on qwen_custom_voice runs.
+16
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@@ -0,0 +1,16 @@
# E2E Test Fixtures
Place two files here before running `test_all_models_e2e.py`:
- `reference_voice.wav` — a clean speech sample, mono, 16–24 kHz, ~5–15 seconds.
- `reference_voice.txt` — the **exact** transcription of the WAV (single line, no trailing newline required).
These are used to create a cloned voice profile for every cloning-capable engine (qwen, luxtts, chatterbox, chatterbox_turbo, tada). Keep them out of version control if they contain personal audio — this directory is not gitignored by default, so add them to `.gitignore` locally if needed.
You can point the test at different files with:
```
python backend/tests/test_all_models_e2e.py \
--reference-wav /path/to/your.wav \
--reference-text "exact transcription here"
```
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@@ -0,0 +1,630 @@
"""
End-to-end model generation test.
Exercises every TTS model against the frozen PyInstaller binary, captures
per-model pass/fail, and writes a JSON + Markdown report.
Usage:
python backend/tests/test_all_models_e2e.py [flags]
See E2E_MODEL_TEST_DESIGN.md for the full design.
"""
from __future__ import annotations
import argparse
import json
import os
import platform
import shutil
import signal
import socket
import subprocess
import sys
import tempfile
import threading
import time
from collections import deque
from dataclasses import asdict, dataclass, field
from datetime import datetime, timezone
from pathlib import Path
from typing import Optional
import httpx
REPO_ROOT = Path(__file__).resolve().parents[2]
BACKEND_DIR = REPO_ROOT / "backend"
DIST_DIR = BACKEND_DIR / "dist"
FIXTURES_DIR = Path(__file__).resolve().parent / "fixtures"
RESULTS_DIR = Path(__file__).resolve().parent / "results"
# ── Test matrix ──────────────────────────────────────────────────────
@dataclass(frozen=True)
class MatrixRow:
label: str # human-readable (appears in report)
engine: str # /generate engine
model_size: Optional[str] # /generate model_size (None = omit)
profile_kind: str # "cloned" | "preset_kokoro" | "preset_qwen_cv"
model_name: str # /models/status key for cache lookup
MATRIX: list[MatrixRow] = [
MatrixRow("qwen 1.7B", "qwen", "1.7B", "cloned", "qwen-tts-1.7B"),
MatrixRow("qwen 0.6B", "qwen", "0.6B", "cloned", "qwen-tts-0.6B"),
MatrixRow("qwen_custom_voice 1.7B", "qwen_custom_voice", "1.7B", "preset_qwen_cv", "qwen-custom-voice-1.7B"),
MatrixRow("qwen_custom_voice 0.6B", "qwen_custom_voice", "0.6B", "preset_qwen_cv", "qwen-custom-voice-0.6B"),
MatrixRow("luxtts", "luxtts", None, "cloned", "luxtts"),
MatrixRow("chatterbox", "chatterbox", None, "cloned", "chatterbox-tts"),
MatrixRow("chatterbox_turbo", "chatterbox_turbo", None, "cloned", "chatterbox-turbo"),
MatrixRow("tada 1B", "tada", "1B", "cloned", "tada-1b"),
MatrixRow("tada 3B", "tada", "3B", "cloned", "tada-3b-ml"),
MatrixRow("kokoro", "kokoro", None, "preset_kokoro", "kokoro"),
]
TEXT = "The quick brown fox jumps over the lazy dog."
DEFAULT_TIMEOUT_CACHED = 180
DEFAULT_TIMEOUT_DOWNLOAD = 1200
HEALTH_TIMEOUT = 120
# ── Result record ────────────────────────────────────────────────────
@dataclass
class ModelResult:
label: str
engine: str
model_size: Optional[str]
status: str # "passed" | "failed" | "timeout"
was_cached: Optional[bool] = None
generation_id: Optional[str] = None
elapsed_seconds: float = 0.0
audio_duration: Optional[float] = None
audio_path: Optional[str] = None
audio_bytes: Optional[int] = None
error: Optional[str] = None
http_status: Optional[int] = None
server_log_tail: Optional[list[str]] = None
# ── Binary resolution ────────────────────────────────────────────────
def find_binary() -> Optional[Path]:
"""Return the first existing binary in priority order, or None."""
is_win = platform.system() == "Windows"
exe = ".exe" if is_win else ""
candidates = [
DIST_DIR / "voicebox-server-cuda" / f"voicebox-server-cuda{exe}",
DIST_DIR / f"voicebox-server{exe}",
]
for c in candidates:
if c.exists() and c.is_file():
return c
return None
def build_binary() -> Path:
"""Invoke build_binary.py and return the resulting binary path."""
print("[build] No frozen binary found — invoking build_binary.py (this may take 5-20 minutes)...", flush=True)
script = BACKEND_DIR / "build_binary.py"
result = subprocess.run(
[sys.executable, str(script)],
cwd=str(BACKEND_DIR),
)
if result.returncode != 0:
raise RuntimeError(f"build_binary.py exited with code {result.returncode}")
found = find_binary()
if found is None:
raise RuntimeError("build_binary.py finished but no binary was found in backend/dist/")
return found
# ── Server spawn + log capture ───────────────────────────────────────
class ServerProcess:
def __init__(self, binary: Path, port: int, data_dir: Path, log_path: Path):
self.binary = binary
self.port = port
self.data_dir = data_dir
self.log_path = log_path
self.proc: Optional[subprocess.Popen] = None
self._log_buffer: deque[str] = deque(maxlen=500)
self._reader_thread: Optional[threading.Thread] = None
def start(self) -> None:
args = [
str(self.binary),
"--host", "127.0.0.1",
"--port", str(self.port),
"--data-dir", str(self.data_dir),
"--parent-pid", str(os.getpid()),
]
print(f"[spawn] {' '.join(args)}", flush=True)
self._log_fh = open(self.log_path, "w", encoding="utf-8", errors="replace")
# Combine stderr into stdout so we get a single ordered stream.
self.proc = subprocess.Popen(
args,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
bufsize=1,
text=True,
errors="replace",
)
self._reader_thread = threading.Thread(target=self._pump_logs, daemon=True)
self._reader_thread.start()
def _pump_logs(self) -> None:
assert self.proc is not None and self.proc.stdout is not None
for line in self.proc.stdout:
self._log_buffer.append(line.rstrip("\n"))
self._log_fh.write(line)
self._log_fh.flush()
def log_tail(self, n: int = 100) -> list[str]:
tail = list(self._log_buffer)[-n:]
return tail
def is_alive(self) -> bool:
return self.proc is not None and self.proc.poll() is None
def stop(self) -> None:
if self.proc is None:
return
if self.proc.poll() is not None:
return
try:
if platform.system() == "Windows":
subprocess.run(
["taskkill", "/F", "/T", "/PID", str(self.proc.pid)],
capture_output=True,
)
else:
self.proc.send_signal(signal.SIGTERM)
except Exception as e:
print(f"[shutdown] signal failed: {e}", flush=True)
try:
self.proc.wait(timeout=10)
except subprocess.TimeoutExpired:
print("[shutdown] server didn't exit cleanly, killing", flush=True)
self.proc.kill()
try:
self.proc.wait(timeout=5)
except subprocess.TimeoutExpired:
pass
if self._reader_thread is not None:
self._reader_thread.join(timeout=2)
try:
self._log_fh.close()
except Exception:
pass
def pick_free_port() -> int:
s = socket.socket()
s.bind(("127.0.0.1", 0))
port = s.getsockname()[1]
s.close()
return port
# ── HTTP helpers ─────────────────────────────────────────────────────
def wait_for_health(base_url: str, server: ServerProcess, timeout: int) -> None:
deadline = time.time() + timeout
with httpx.Client(timeout=5.0) as client:
while time.time() < deadline:
if not server.is_alive():
raise RuntimeError("Server process exited before becoming healthy")
try:
r = client.get(f"{base_url}/health")
if r.status_code == 200 and r.json().get("status") == "healthy":
return
except httpx.HTTPError:
pass
time.sleep(1.0)
raise TimeoutError(f"Server did not become healthy within {timeout}s")
def get_model_cached(client: httpx.Client, base_url: str, model_name: str) -> Optional[bool]:
try:
r = client.get(f"{base_url}/models/status", timeout=30.0)
r.raise_for_status()
for m in r.json().get("models", []):
if m.get("model_name") == model_name:
return bool(m.get("downloaded"))
except httpx.HTTPError:
return None
return None
def create_cloned_profile(client: httpx.Client, base_url: str, wav_path: Path, reference_text: str) -> str:
r = client.post(f"{base_url}/profiles", json={
"name": "e2e-cloned",
"voice_type": "cloned",
"language": "en",
})
r.raise_for_status()
profile_id = r.json()["id"]
with open(wav_path, "rb") as f:
r = client.post(
f"{base_url}/profiles/{profile_id}/samples",
files={"file": (wav_path.name, f, "audio/wav")},
data={"reference_text": reference_text},
timeout=120.0,
)
r.raise_for_status()
return profile_id
def create_preset_profile(client: httpx.Client, base_url: str, name: str, engine: str, voice_id: str) -> str:
r = client.post(f"{base_url}/profiles", json={
"name": name,
"voice_type": "preset",
"language": "en",
"preset_engine": engine,
"preset_voice_id": voice_id,
})
r.raise_for_status()
return r.json()["id"]
def run_one_generation(
client: httpx.Client,
base_url: str,
row: MatrixRow,
profile_id: str,
timeout_s: int,
) -> tuple[str, dict]:
"""Start a generation and stream its status until done/failed/timeout.
Returns (status, payload) where status is "completed" | "failed" | "timeout".
"""
body = {
"profile_id": profile_id,
"text": TEXT,
"language": "en",
"engine": row.engine,
"seed": 42,
"normalize": True,
}
if row.model_size is not None:
body["model_size"] = row.model_size
r = client.post(f"{base_url}/generate", json=body, timeout=30.0)
r.raise_for_status()
gen = r.json()
gen_id = gen["id"]
deadline = time.time() + timeout_s
last_payload: dict = gen
status_url = f"{base_url}/generate/{gen_id}/status"
while time.time() < deadline:
remaining = max(1.0, deadline - time.time())
try:
with client.stream("GET", status_url, timeout=httpx.Timeout(remaining + 5, read=remaining + 5)) as resp:
resp.raise_for_status()
for line in resp.iter_lines():
if not line or not line.startswith("data: "):
continue
try:
payload = json.loads(line[6:])
except json.JSONDecodeError:
continue
last_payload = payload
status = payload.get("status")
if status == "not_found":
return "failed", {"error": "generation not found", **payload}
if status in ("completed", "failed"):
return status, payload
if time.time() >= deadline:
break
except httpx.HTTPError:
time.sleep(1.0)
continue
return "timeout", last_payload
def fetch_audio_info(
client: httpx.Client, base_url: str, generation_id: str, data_dir: Path
) -> tuple[Optional[str], Optional[int]]:
"""Return (audio_path, audio_bytes) for a completed generation.
Server stores audio_path relative to data_dir; resolve it to get a size.
"""
try:
r = client.get(f"{base_url}/history/{generation_id}", timeout=10.0)
if r.status_code != 200:
return None, None
data = r.json()
audio_path = data.get("audio_path")
if not audio_path:
return None, None
p = Path(audio_path)
if not p.is_absolute():
p = data_dir / p
if p.exists():
return str(p), p.stat().st_size
return audio_path, None
except httpx.HTTPError:
return None, None
# ── Report writers ───────────────────────────────────────────────────
def write_reports(
output_dir: Path,
binary: Path,
started_at: datetime,
finished_at: datetime,
results: list[ModelResult],
) -> tuple[Path, Path]:
output_dir.mkdir(parents=True, exist_ok=True)
plat = f"{platform.system().lower()}-{platform.machine().lower()}"
ts = started_at.strftime("%Y%m%d-%H%M%S")
json_path = output_dir / f"e2e-{plat}-{ts}.json"
md_path = output_dir / f"e2e-{plat}-{ts}.md"
doc = {
"platform": plat,
"binary": str(binary),
"binary_size_mb": round(binary.stat().st_size / (1024 * 1024), 1) if binary.exists() else None,
"started_at": started_at.isoformat(),
"finished_at": finished_at.isoformat(),
"elapsed_seconds": (finished_at - started_at).total_seconds(),
"results": [asdict(r) for r in results],
}
json_path.write_text(json.dumps(doc, indent=2))
lines = [
f"# Voicebox E2E — {plat} — {started_at.strftime('%Y-%m-%d %H:%M UTC')}",
"",
f"Binary: `{binary}` ",
f"Elapsed: {doc['elapsed_seconds']:.1f}s",
"",
"| Model | Status | Cached | Elapsed | Audio | Error |",
"|-------|--------|--------|---------|-------|-------|",
]
for r in results:
status_icon = {"passed": "PASS", "failed": "FAIL", "timeout": "TIMEOUT"}.get(r.status, r.status.upper())
cached = "yes" if r.was_cached else ("no" if r.was_cached is False else "?")
audio_col = f"{r.audio_duration:.2f}s" if r.audio_duration else ("—" if r.status != "passed" else "?")
error_col = (r.error or "").replace("\n", " ")[:120]
lines.append(f"| {r.label} | {status_icon} | {cached} | {r.elapsed_seconds:.1f}s | {audio_col} | {error_col} |")
failed_rows = [r for r in results if r.status != "passed"]
if failed_rows:
lines.append("")
lines.append("## Failures")
for r in failed_rows:
lines.append("")
lines.append(f"### {r.label} — {r.status}")
if r.error:
lines.append("")
lines.append("```")
lines.append(r.error)
lines.append("```")
if r.server_log_tail:
lines.append("")
lines.append("<details><summary>server log (last lines)</summary>")
lines.append("")
lines.append("```")
lines.extend(r.server_log_tail)
lines.append("```")
lines.append("</details>")
md_path.write_text("\n".join(lines) + "\n")
return json_path, md_path
# ── Main ─────────────────────────────────────────────────────────────
def parse_args() -> argparse.Namespace:
p = argparse.ArgumentParser(description="Voicebox E2E model generation test")
p.add_argument("--binary", type=Path, help="Path to voicebox-server binary (overrides auto-detect)")
p.add_argument("--skip-build", action="store_true", help="Error if binary missing instead of building")
p.add_argument(
"--reference-wav",
type=Path,
default=FIXTURES_DIR / "reference_voice.wav",
help="Reference audio for cloning engines",
)
p.add_argument(
"--reference-text",
help="Transcription of reference-wav (default: read from fixtures/reference_voice.txt)",
)
p.add_argument("--only", help="Comma-separated engines to run (e.g. kokoro,qwen)")
p.add_argument("--skip", help="Comma-separated engines to skip")
p.add_argument("--keep-data-dir", action="store_true", help="Don't delete tempdir after run")
p.add_argument("--timeout-cached", type=int, default=DEFAULT_TIMEOUT_CACHED)
p.add_argument("--timeout-download", type=int, default=DEFAULT_TIMEOUT_DOWNLOAD)
p.add_argument("--port", type=int, help="Override auto-picked port")
p.add_argument("--output-dir", type=Path, default=RESULTS_DIR)
return p.parse_args()
def filter_matrix(args: argparse.Namespace) -> list[MatrixRow]:
only = set(x.strip() for x in args.only.split(",")) if args.only else None
skip = set(x.strip() for x in args.skip.split(",")) if args.skip else set()
rows = []
for r in MATRIX:
if only is not None and r.engine not in only:
continue
if r.engine in skip:
continue
rows.append(r)
return rows
def resolve_reference(args: argparse.Namespace) -> tuple[Path, str]:
wav = args.reference_wav
if not wav.exists():
raise FileNotFoundError(
f"Reference WAV not found: {wav}\n"
f"Place a sample at {FIXTURES_DIR / 'reference_voice.wav'} or pass --reference-wav.\n"
f"See backend/tests/fixtures/README.md."
)
if args.reference_text:
text = args.reference_text
else:
txt_path = wav.with_suffix(".txt")
if not txt_path.exists():
raise FileNotFoundError(
f"Reference transcription not found: {txt_path}\n"
f"Create it next to the WAV, or pass --reference-text."
)
text = txt_path.read_text().strip()
if not text:
raise ValueError("Reference transcription is empty")
return wav, text
def main() -> int:
args = parse_args()
rows = filter_matrix(args)
if not rows:
print("No rows selected after --only/--skip filtering", file=sys.stderr)
return 2
# Binary
binary = args.binary or find_binary()
if binary is None:
if args.skip_build:
print("No frozen binary found and --skip-build set. Run: python backend/build_binary.py", file=sys.stderr)
return 2
binary = build_binary()
if not binary.exists():
print(f"Binary path does not exist: {binary}", file=sys.stderr)
return 2
print(f"[binary] {binary}", flush=True)
# Reference audio (only required if any cloning row is in the matrix)
needs_reference = any(r.profile_kind == "cloned" for r in rows)
ref_wav: Optional[Path] = None
ref_text: Optional[str] = None
if needs_reference:
try:
ref_wav, ref_text = resolve_reference(args)
except (FileNotFoundError, ValueError) as e:
print(f"[fixture] {e}", file=sys.stderr)
return 2
print(f"[fixture] reference WAV: {ref_wav}", flush=True)
print(f"[fixture] reference text: {ref_text!r}", flush=True)
# Tempdir + log path
data_dir = Path(tempfile.mkdtemp(prefix="voicebox-e2e-"))
args.output_dir.mkdir(parents=True, exist_ok=True)
ts = datetime.now(timezone.utc).strftime("%Y%m%d-%H%M%S")
log_path = args.output_dir / f"server-{ts}.log"
port = args.port or pick_free_port()
base_url = f"http://127.0.0.1:{port}"
server = ServerProcess(binary=binary, port=port, data_dir=data_dir, log_path=log_path)
started_at = datetime.now(timezone.utc)
results: list[ModelResult] = []
try:
server.start()
print(f"[health] waiting for {base_url}/health ...", flush=True)
wait_for_health(base_url, server, HEALTH_TIMEOUT)
print("[health] ready", flush=True)
with httpx.Client(timeout=30.0) as client:
# Profile setup (only create what's needed)
cloned_profile_id: Optional[str] = None
kokoro_profile_id: Optional[str] = None
qwen_cv_profile_id: Optional[str] = None
needed_kinds = {r.profile_kind for r in rows}
if "cloned" in needed_kinds:
assert ref_wav is not None and ref_text is not None
print("[profile] creating cloned profile...", flush=True)
cloned_profile_id = create_cloned_profile(client, base_url, ref_wav, ref_text)
if "preset_kokoro" in needed_kinds:
print("[profile] creating kokoro preset...", flush=True)
kokoro_profile_id = create_preset_profile(client, base_url, "e2e-kokoro", "kokoro", "af_heart")
if "preset_qwen_cv" in needed_kinds:
print("[profile] creating qwen_custom_voice preset...", flush=True)
qwen_cv_profile_id = create_preset_profile(client, base_url, "e2e-qwen-cv", "qwen_custom_voice", "Ryan")
profile_lookup = {
"cloned": cloned_profile_id,
"preset_kokoro": kokoro_profile_id,
"preset_qwen_cv": qwen_cv_profile_id,
}
# Matrix loop
for row in rows:
print(f"\n[run] {row.label} (engine={row.engine}, size={row.model_size})", flush=True)
profile_id = profile_lookup[row.profile_kind]
assert profile_id is not None
was_cached = get_model_cached(client, base_url, row.model_name)
timeout_s = args.timeout_cached if was_cached else args.timeout_download
print(f"[run] cached={was_cached} timeout={timeout_s}s", flush=True)
t0 = time.time()
result = ModelResult(
label=row.label,
engine=row.engine,
model_size=row.model_size,
status="failed",
was_cached=was_cached,
)
try:
status, payload = run_one_generation(client, base_url, row, profile_id, timeout_s)
result.status = "passed" if status == "completed" else status
result.generation_id = payload.get("id")
result.audio_duration = payload.get("duration")
result.error = payload.get("error")
if status == "completed" and result.generation_id:
audio_path, audio_bytes = fetch_audio_info(
client, base_url, result.generation_id, data_dir
)
result.audio_path = audio_path
result.audio_bytes = audio_bytes
if audio_bytes is not None and audio_bytes == 0:
result.status = "failed"
result.error = (result.error or "") + " (audio file is empty)"
except httpx.HTTPStatusError as e:
result.status = "failed"
result.http_status = e.response.status_code
try:
detail = e.response.json().get("detail")
except Exception:
detail = e.response.text
result.error = f"HTTP {e.response.status_code}: {detail}"
except Exception as e:
result.status = "failed"
result.error = f"{type(e).__name__}: {e}"
result.elapsed_seconds = round(time.time() - t0, 2)
if result.status != "passed":
result.server_log_tail = server.log_tail(100)
print(f"[run] {row.label} → {result.status} in {result.elapsed_seconds}s"
+ (f" ({result.error})" if result.error else ""), flush=True)
results.append(result)
finally:
finished_at = datetime.now(timezone.utc)
server.stop()
if not args.keep_data_dir:
shutil.rmtree(data_dir, ignore_errors=True)
else:
print(f"[cleanup] keeping data dir: {data_dir}", flush=True)
json_path, md_path = write_reports(args.output_dir, binary, started_at, finished_at, results)
print(f"\n[report] {json_path}")
print(f"[report] {md_path}")
print(f"[report] server log: {log_path}")
passed = sum(1 for r in results if r.status == "passed")
failed = len(results) - passed
print(f"\n== {passed} passed, {failed} failed ==")
return 0 if failed == 0 else 1
if __name__ == "__main__":
sys.exit(main())
@@ -0,0 +1,54 @@
import asyncio
import pytest
from backend.services import task_queue
@pytest.mark.asyncio
async def test_cancel_queued_generation_skips_execution():
task_queue.init_queue(force=True)
running_started = asyncio.Event()
release_running = asyncio.Event()
queued_ran = asyncio.Event()
async def running_job():
running_started.set()
await release_running.wait()
async def queued_job():
queued_ran.set()
task_queue.enqueue_generation("gen-running", running_job())
await asyncio.wait_for(running_started.wait(), timeout=1)
task_queue.enqueue_generation("gen-queued", queued_job())
assert task_queue.cancel_generation("gen-queued") == "queued"
release_running.set()
await asyncio.sleep(0.1)
assert not queued_ran.is_set()
@pytest.mark.asyncio
async def test_cancel_running_generation_cancels_task():
task_queue.init_queue(force=True)
running_started = asyncio.Event()
running_cancelled = asyncio.Event()
async def running_job():
running_started.set()
try:
await asyncio.Event().wait()
except asyncio.CancelledError:
running_cancelled.set()
raise
task_queue.enqueue_generation("gen-running", running_job())
await asyncio.wait_for(running_started.wait(), timeout=1)
assert task_queue.cancel_generation("gen-running") == "running"
await asyncio.wait_for(running_cancelled.wait(), timeout=1)
+37 -10
View File
@@ -5,17 +5,22 @@ description: "How voice profile management works in Voicebox"
## Overview
Voice profiles are the foundation of Voicebox's voice cloning capability. Each profile stores reference audio samples and metadata that the TTS model uses to clone a voice.
Voice profiles are the unit of "a saved voice" in Voicebox. As of 0.4 they support two flavors backed by the same `profiles` table:
- **Cloned profiles** — store one or more reference audio samples; the cloning engine generates a voice embedding at use time
- **Preset profiles** — store no audio; just a pointer to an engine-specific pre-built voice (e.g. Kokoro's `am_adam`, Qwen CustomVoice's `Ryan`)
The schema also reserves a third type, `designed`, for future text-described voices. Not currently used by any shipped engine.
## Architecture
The voice profile system consists of three main components:
**Database Layer:** SQLite tables store profile metadata and sample references.
**Database Layer:** SQLite tables store profile metadata, sample references (cloned), and engine + voice ID (preset).
**File Storage:** Audio samples are stored on disk in a structured directory format.
**File Storage:** Audio samples are stored on disk in a structured directory format. Preset profiles have no on-disk audio.
**Profile Module:** The `profiles.py` module provides the business logic for CRUD operations.
**Profile Module:** `backend/services/profiles.py` provides the business logic for CRUD operations and dispatches to the appropriate engine based on `voice_type`.
## Data Model
@@ -24,27 +29,49 @@ The voice profile system consists of three main components:
```python
class VoiceProfile(Base):
__tablename__ = "profiles"
id = Column(String, primary_key=True)
id = Column(String, primary_key=True, default=lambda: str(uuid.uuid4()))
name = Column(String, unique=True, nullable=False)
description = Column(Text)
language = Column(String, default="en")
created_at = Column(DateTime)
updated_at = Column(DateTime)
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 (reserved)
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)
```
The `voice_type` column discriminates the three flavors:
| `voice_type` | `preset_engine` | `preset_voice_id` | Samples in `profile_samples` |
| ------------ | --------------- | ----------------- | ---------------------------- |
| `cloned` | NULL | NULL | Required (≥1 row) |
| `preset` | engine name | voice ID string | None |
| `designed` | NULL | NULL | None (uses `design_prompt`) |
The `default_engine` column is set automatically when the profile is created. For preset profiles it's locked to the source engine — switching engines at generation time will skip the profile (and the UI auto-switches back when the user clicks a greyed-out card; see the floating generate box and profile grid).
### ProfileSample Table
```python
class ProfileSample(Base):
__tablename__ = "profile_samples"
id = Column(String, primary_key=True)
id = Column(String, primary_key=True, default=lambda: str(uuid.uuid4()))
profile_id = Column(String, ForeignKey("profiles.id"))
audio_path = Column(String, nullable=False)
reference_text = Column(Text, nullable=False)
```
Only populated for cloned profiles. Preset and designed profiles have zero rows in this table.
## File Structure
Profiles are stored in the data directory:
@@ -1,32 +1,43 @@
---
title: "Creating Voice Profiles"
description: "Advanced guide to creating high-quality voice profiles"
description: "How to create voice profiles, both cloning-based and preset-based"
---
## Overview
Voice profiles are the foundation of voice cloning in Voicebox. This guide covers best practices for creating professional-quality voice profiles.
A **voice profile** is a saved voice you can reuse across generations, stories, and the API. As of 0.4, Voicebox profiles come in two flavors that map to two different ways of getting a voice:
## Quick Start
| Profile type | What it stores | Use when… |
| -------------- | ---------------------------------------------------- | -------------------------------------------------------- |
| **Cloned** | One or more reference audio samples + a voice embedding | You want to replicate a specific person's voice |
| **Preset** | A reference to a pre-built voice in a specific engine | You want a curated, production-ready voice with no audio prep |
Both types live in the same Profiles tab and behave the same way at generation time — pick the type that matches your goal and follow the workflow below.
<Callout type="info">
Not sure which to use? Cloning gives you a *specific* voice but needs clean audio. Preset gives you *good* voices instantly but you don't get to choose who they sound like.
</Callout>
## Workflow A — Cloned Profiles
Use this when you want to replicate a specific person's voice from a recording.
<Steps>
<Step title="Prepare Audio">
10-30 seconds of clear speech
10-30 seconds of clear speech, minimal background noise. See [Voice Cloning](/overview/voice-cloning) for the engine catalog.
</Step>
<Step title="Create Profile">
**Profiles** → **+ New Profile**
**Profiles** → **+ New Profile** → choose a cloning engine (Qwen3-TTS, Chatterbox, LuxTTS, or TADA)
</Step>
<Step title="Upload Sample">
Add your audio file
<Step title="Upload or Record Sample">
Drag in an audio file, or record directly with the in-app recorder
</Step>
<Step title="Generate">
Use the profile to generate speech
<Step title="Generate to Test">
Use the profile to generate a test phrase. If quality is poor, add more samples
</Step>
</Steps>
## Audio Requirements
### Ideal Sample Characteristics
### Audio Requirements (Cloning Only)
<Cards>
<Card title="Duration">
@@ -44,7 +55,7 @@ Voice profiles are the foundation of voice cloning in Voicebox. This guide cover
<Card title="Quality">
**High fidelity**
44.1kHz or 48kHz sample rate
44.1 kHz or 48 kHz sample rate
Minimal compression
</Card>
<Card title="Content">
@@ -58,18 +69,16 @@ Voice profiles are the foundation of voice cloning in Voicebox. This guide cover
### File Formats
Supported formats:
- **WAV** (recommended) - Lossless quality
- **MP3** - Acceptable, minimal compression
- **M4A** - Acceptable
- **FLAC** - Lossless alternative
- **WAV** (recommended) — Lossless quality
- **MP3** — Acceptable, minimal compression
- **M4A** — Acceptable
- **FLAC** — Lossless alternative
<Callout type="info">
Use WAV for best results. Avoid heavily compressed formats.
</Callout>
## Recording Tips
### Environment
### Recording Tips
<AccordionGroup>
<Accordion title="Quiet Space">
@@ -87,27 +96,25 @@ Supported formats:
</Accordion>
<Accordion title="Recording Settings">
- 44.1kHz or 48kHz sample rate
- 44.1 kHz or 48 kHz sample rate
- 16-bit or 24-bit depth
- Mono is fine (stereo will be converted)
- Avoid automatic gain control
</Accordion>
</AccordionGroup>
### Speaking
### Speaking Style
- **Natural pace** - Don't rush or speak too slowly
- **Clear articulation** - Pronounce words clearly
- **Consistent volume** - Maintain steady loudness
- **Normal tone** - Speak as you normally would
- **Complete sentences** - Avoid fragments or "ums"
- **Natural pace** — Don't rush or speak too slowly
- **Clear articulation** — Pronounce words clearly
- **Consistent volume** — Maintain steady loudness
- **Normal tone** — Speak as you normally would
- **Complete sentences** — Avoid fragments or "ums"
## Multiple Samples
### Multiple Samples
Adding multiple samples can significantly improve quality:
### Why Multiple Samples?
<Cards>
<Card title="Robustness">
Model learns a more complete representation
@@ -123,110 +130,57 @@ Adding multiple samples can significantly improve quality:
</Card>
</Cards>
### Sample Variety
Consider adding samples with:
1. **Different tones**
- Casual conversation
- Professional/formal
- Excited/enthusiastic
- Calm/serious
2. **Different content**
- Narratives
- Questions
- Statements
- Emotions (happy, sad, neutral)
3. **Different recording conditions**
- Studio quality
- Phone call quality (if needed)
- Room acoustics
1. **Different tones** — casual, formal, excited, calm
2. **Different content** — narratives, questions, statements
3. **Different recording conditions** — studio quality, room acoustics
<Callout type="warn">
All samples should be from the **same speaker**. Mixing voices will produce poor results.
</Callout>
## Processing Existing Audio
### Processing Existing Audio
If you have existing audio (podcasts, videos, etc.):
### Extracting Clean Segments
<Steps>
<Step title="Find Clean Speech">
Look for segments with:
- Just the target speaker
- No background music
- Minimal noise
Look for segments with just the target speaker, no background music, minimal noise
</Step>
<Step title="Use Audio Editor">
Tools like Audacity or Adobe Audition:
- Cut out clean 10-30s segments
- Remove silence at start/end
- Normalize volume if needed
Tools like Audacity or Adobe Audition: cut clean 10-30s segments, remove silence at start/end, normalize volume
</Step>
<Step title="Export as WAV">
Save as high-quality WAV file
</Step>
</Steps>
### Noise Reduction
For light background noise, use Audacity's noise reduction (gentle settings — over-processing introduces artifacts).
If you have light background noise:
### Testing & Iteration
```
1. Use noise reduction in Audacity:
- Select noise-only section
- Get Noise Profile
- Select full audio
- Apply noise reduction (gentle settings)
2. Avoid over-processing:
- Can introduce artifacts
- May reduce voice quality
```
## Testing & Iteration
### Test Your Profile
After creating a profile:
After creating a cloned profile:
<Steps>
<Step title="Generate Test">
Generate a simple phrase:
```
"Hello, this is a test of my voice profile."
```
Try a simple phrase: `"Hello, this is a test of my voice profile."`
</Step>
<Step title="Evaluate Quality">
Listen for:
- Natural tone
- Clear pronunciation
- Proper prosody
- Lack of artifacts
Listen for natural tone, clear pronunciation, proper prosody, lack of artifacts
</Step>
<Step title="Iterate">
If quality is poor:
- Add more samples
- Try different source audio
- Check sample quality
If quality is poor: add more samples, try different source audio, check sample quality
</Step>
</Steps>
### Common Issues
#### Common Issues
<AccordionGroup>
<Accordion title="Robotic Voice">
**Cause**: Poor quality samples or too short
**Fix**: Use longer, higher quality samples
**Fix**: Use longer, higher-quality samples
</Accordion>
<Accordion title="Wrong Tone">
@@ -242,51 +196,89 @@ After creating a profile:
</Accordion>
</AccordionGroup>
## Workflow B — Preset Profiles
Use this when you want a ready-made voice without recording anything. Available engines: **Kokoro 82M** (50 voices) and **Qwen CustomVoice** (9 voices). See [Preset Voices](/overview/preset-voices) for the full catalog.
<Steps>
<Step title="Create Profile">
**Profiles** → **+ New Profile** → choose **Kokoro** or **Qwen CustomVoice** as the engine
</Step>
<Step title="Pick a Voice">
The engine's voice catalog appears. Click any voice to preview it
</Step>
<Step title="Name and Save">
Give the profile a name. No audio sample required
</Step>
<Step title="Generate">
The profile is ready immediately — use it in the floating generate box or Generate page
</Step>
</Steps>
<Callout type="info">
Preset profiles are **locked to their source engine**. Switching to a different engine in the floating generate box greys out the profile, since the voice only exists in that engine. Clicking a greyed profile auto-switches the engine back.
</Callout>
### Qwen CustomVoice + Instruct
Preset voices in Qwen CustomVoice support **delivery instructions** — natural-language style control over tone, pace, and emotion. The floating generate box shows a slider icon next to the generate button when a Qwen CustomVoice profile is selected; click it to reveal the instruct textarea.
See [Preset Voices → Using Instruct Mode](/overview/preset-voices#using-instruct-mode) for examples.
## Advanced Tips
### Celebrity/Character Voices
### Celebrity / Character Voices (Cloning)
For cloning public figures or characters:
1. **Legal considerations** - Ensure you have rights or it's fair use
2. **Source quality** - Find high-quality interview audio or clean clips
3. **Consistency** - Use clips where they speak similarly
4. **Multiple samples** - Very important for recognizable voices
1. **Legal considerations** — Ensure you have rights or it's clearly fair use
2. **Source quality** — Find high-quality interview audio or clean clips
3. **Consistency** — Use clips where they speak similarly
4. **Multiple samples** — Very important for recognizable voices
### Accent & Dialect
### Accent & Dialect (Cloning)
The model will preserve accent and dialect:
Cloning models preserve accent and dialect:
- British English will generate British English
- Southern accent will produce Southern accent
- Regional pronunciations will be maintained
- British English samples generate British English output
- Southern accent samples produce Southern accent output
- Regional pronunciations are maintained
### Emotion Transfer
### Emotion Transfer (Cloning)
The emotional tone of samples affects generation:
- Energetic samples → Energetic output
- Calm samples → Calm output
- Mix samples for versatile profile
- Energetic samples → energetic output
- Calm samples → calm output
- Mix samples for a more versatile profile
For Qwen CustomVoice presets, use the **instruct** field instead of relying on sample emotion — that's exactly what it controls.
## Managing Profiles
### Organization
- **Descriptive names** - "John Smith - Professional Narrator"
- **Add descriptions** - Note recording conditions, use cases
- **Language tags** - Mark the primary language
- **Archive unused** - Keep profile list manageable
- **Descriptive names** — "John Smith - Professional Narrator"
- **Add descriptions** — Note recording conditions, use cases, or which preset voice
- **Language tags** — Mark the primary language
- **Archive unused** — Keep profile list manageable
### Export/Import
### Export / Import
- **Export** profiles to share or backup
- **Import** from colleagues or teammates
- Profiles include voice embeddings, not original audio
- **Cloned profiles** export with their voice embeddings (not the original audio)
- **Preset profiles** export as engine + voice ID metadata only — the importer must have that engine's model installed
## Next Steps
<Cards>
<Card title="Voice Cloning" href="/overview/voice-cloning">
Engine catalog and best practices for cloning
</Card>
<Card title="Preset Voices" href="/overview/preset-voices">
Full catalog of Kokoro and Qwen CustomVoice voices
</Card>
<Card title="Generate Speech" href="/overview/generating-speech">
Use your profile to generate speech
</Card>
@@ -0,0 +1,236 @@
---
title: "GPU Acceleration"
description: "How Voicebox uses your GPU — auto-detection, manual setup, troubleshooting"
---
## Overview
Voicebox auto-detects available accelerators on first launch and picks the fastest backend it can use. For most people this just works — open the app and you're already on the right backend.
This page is for the cases where it doesn't:
- You have a GPU but Voicebox is running on CPU
- You upgraded GPUs (especially to RTX 50-series / Blackwell) and generation broke
- You want to switch backends manually (e.g. force MLX over PyTorch on Apple Silicon)
- You see `[UNSUPPORTED - see logs]` next to your GPU in Settings
## Backend Matrix
| Platform | Auto-selected backend | Notes |
| --------------------------- | ------------------------- | ---------------------------------------------------- |
| **macOS Apple Silicon** | MLX (Metal) | 4-5x faster than PyTorch via Apple Neural Engine |
| **macOS Intel** | PyTorch CPU | No GPU acceleration available; PyTorch ≥ 2.2 only |
| **Windows + NVIDIA** | PyTorch CUDA (cu128) | Auto-downloads the CUDA backend binary on first use |
| **Windows + Intel Arc** | PyTorch XPU (IPEX) | New in 0.4 — works with Arc A-series and B-series |
| **Windows generic GPU** | DirectML | Universal Windows GPU support; slower than CUDA |
| **Linux + NVIDIA** | PyTorch CUDA (cu128) | Same auto-download flow as Windows |
| **Linux + AMD** | PyTorch ROCm | Auto-configures `HSA_OVERRIDE_GFX_VERSION` |
| **Linux + Intel Arc** | PyTorch XPU (IPEX) | |
| **Any (no GPU)** | PyTorch CPU | Works everywhere; expect 5-50x slower than GPU |
The detected backend is shown in Settings → GPU. Logs at startup also print the chosen backend and the device name.
## Apple Silicon — MLX vs PyTorch
On M-series Macs, Voicebox ships an MLX-optimized backend that uses the Apple Neural Engine. It's **4-5x faster** than the PyTorch (CPU/Metal) path for supported engines.
| Engine | MLX support | Notes |
| -------------------- | ----------- | ------------------------------------------- |
| Qwen3-TTS | ✅ Native | Uses MLX exclusively when available |
| Chatterbox / Turbo | PyTorch MPS | Falls back to Metal via PyTorch |
| LuxTTS | PyTorch MPS | |
| TADA | PyTorch MPS | |
| Kokoro | PyTorch MPS | Requires `PYTORCH_ENABLE_MPS_FALLBACK=1` |
| Qwen CustomVoice | PyTorch MPS | |
| Whisper (transcribe) | ✅ Native | MLX-Whisper is the default on Apple Silicon |
The Whisper Turbo + MLX combo dropped transcription latency from ~20s to ~2-3s on M-series chips (see CHANGELOG entry for v0.1.10).
## Windows / Linux + NVIDIA — The CUDA Backend Swap
Voicebox doesn't bundle CUDA into the main installer (it would balloon downloads to multi-gigabyte territory for users who don't have an NVIDIA GPU). Instead, when you first need it, the app downloads a separate **CUDA backend binary** that contains the PyTorch + CUDA runtime.
<Steps>
<Step title="Open Settings → GPU">
If an NVIDIA GPU is detected, you'll see "Install CUDA backend" in the GPU panel
</Step>
<Step title="Click Install">
The app downloads two archives separately:
- **Server core** (~200-400 MB) — versioned with each Voicebox release
- **CUDA libs** (~4 GB) — the heavy PyTorch + CUDA DLLs, versioned independently
</Step>
<Step title="Restart">
Voicebox restarts to swap in the CUDA backend
</Step>
</Steps>
<Callout type="info">
The split-archive design (added in v0.4) means most Voicebox upgrades only redownload the small server-core archive. The 4 GB libs archive is only refreshed when the underlying CUDA toolkit or torch major version changes.
</Callout>
### Auto-update
When a new Voicebox release ships, the GPU panel checks if the bundled server-core matches the installed CUDA version. If only the core changed (typical), it pulls the new core in the background. If the libs version changed (rare — only happens on cu126 → cu128 type bumps), you'll be prompted to confirm the larger download.
## RTX 50-series / Blackwell
Voicebox 0.4 added explicit RTX 50-series support:
- CUDA toolkit upgraded to **cu128** (previous releases used cu126 which lacks Blackwell kernels)
- Build pinned with `TORCH_CUDA_ARCH_LIST=...12.0+PTX` for forward-compatibility
If you're on an RTX 5070 / 5080 / 5090 and you see "no kernel image is available" errors:
1. Make sure you're on Voicebox **≥ 0.4.0** (Settings → About)
2. Reinstall the CUDA backend (Settings → GPU → Reinstall CUDA backend) — older installs may have stale cu126 libs
3. If errors persist, see the GPU compatibility warnings section below
## Intel Arc (XPU)
New in 0.4. Works with both Arc A-series (Alchemist: A380, A580, A750, A770) and B-series (Battlemage).
### Setup
Voicebox auto-detects Arc GPUs and routes through Intel's PyTorch XPU backend (powered by IPEX — Intel Extension for PyTorch). No extra installation step beyond the standard Voicebox install.
Verify it's working:
- Settings → GPU should show **XPU** followed by your Arc model name (e.g. `XPU (Intel Arc A770)`)
- Startup logs print `Backend: PYTORCH` and `GPU: XPU (Intel Arc ...)`
### Engines on XPU
All PyTorch-based engines work on XPU. Performance is generally between CPU and CUDA — expect ~2-3x speedup over CPU for the larger models.
## DirectML
The fallback for Windows users with non-NVIDIA, non-Intel-Arc GPUs (older AMD discrete, integrated GPUs, etc.). Slower than CUDA and XPU but provides some acceleration over CPU.
Auto-selected when no other GPU backend is available.
## AMD ROCm (Linux)
ROCm provides PyTorch GPU acceleration on AMD discrete GPUs. Voicebox auto-configures `HSA_OVERRIDE_GFX_VERSION` for common cards that need the override.
### Verifying
```bash
# In a terminal
echo $HSA_OVERRIDE_GFX_VERSION
# Should show e.g. 10.3.0 for RX 6000 series
```
If detection fails, set the variable manually before launching Voicebox:
```bash
export HSA_OVERRIDE_GFX_VERSION=10.3.0
voicebox
```
Common values:
- `10.3.0` — RX 6000 series (RDNA 2)
- `11.0.0` — RX 7000 series (RDNA 3)
- `9.0.0` — Older Vega cards
## GPU Compatibility Warnings
Voicebox 0.4 added a runtime check that compares your GPU's compute capability against the architectures the bundled PyTorch was compiled for. If they don't match, you'll see:
- A startup log line: `WARNING: GPU COMPATIBILITY: <your GPU> is not supported by this PyTorch build...`
- The GPU label in Settings shows `[UNSUPPORTED - see logs]`
- The `/health` API returns a populated `gpu_compatibility_warning` field
### What to do
The most common trigger is a brand-new GPU architecture that pre-built PyTorch wheels don't yet cover natively. In order of preference:
1. **Update Voicebox** — newer releases ship newer PyTorch with broader arch support
2. **Reinstall the CUDA backend** — Settings → GPU → Reinstall CUDA backend
3. **For bleeding-edge GPUs (newer than current Blackwell):** install PyTorch nightly manually:
```bash
pip install torch --index-url https://download.pytorch.org/whl/nightly/cu128 --force-reinstall
```
Then point Voicebox at that environment via [Remote Mode](/overview/remote-mode) until stable PyTorch catches up.
4. **Fall back to CPU** temporarily — set `VOICEBOX_FORCE_CPU=1` before launching
## CPU-Only Fallback
When no GPU is available (or you've forced it off), Voicebox runs the PyTorch CPU backend. Expect:
- 5-50x slower generation depending on engine and text length
- Heavy CPU usage during generation
- Some engines work better than others on CPU:
- **Kokoro 82M** — runs at realtime on modern CPUs
- **LuxTTS** — exceeds 150x realtime on CPU
- **Chatterbox Turbo (350M)** — usable but slow
- Larger models (Qwen 1.7B, Chatterbox Multilingual, TADA 3B) — painful
For CPU-bound use cases, prefer the smaller, lighter engines.
## Verifying Your Setup
Three places to check that the right backend is being used:
<Steps>
<Step title="Settings → GPU">
Shows the detected backend, GPU model, and VRAM (when applicable). Look for the `[UNSUPPORTED - see logs]` suffix
</Step>
<Step title="Settings → Logs">
The "Server logs" tab shows the startup banner with `Backend: <type>` and `GPU: <name>`
</Step>
<Step title="Health endpoint">
`curl http://localhost:17493/health` returns a JSON payload with `backend_type`, `backend_variant`, and `gpu_compatibility_warning` (when applicable)
</Step>
</Steps>
## Troubleshooting
<AccordionGroup>
<Accordion title="Settings shows CPU instead of my GPU">
- On NVIDIA: install the CUDA backend (Settings → GPU)
- On Intel Arc: confirm IPEX detection in startup logs; restart the app after a driver update
- On AMD Linux: check `HSA_OVERRIDE_GFX_VERSION` is set
</Accordion>
<Accordion title="'no kernel image is available' / 'CUDA error'">
Almost always means the bundled PyTorch doesn't have kernels for your GPU's compute capability.
1. Update to Voicebox ≥ 0.4.0 (Blackwell support added there)
2. Reinstall the CUDA backend
3. If still broken, install PyTorch nightly via Remote Mode
</Accordion>
<Accordion title="Out of memory (CUDA)">
- Switch to a smaller model size (e.g. Qwen3 0.6B instead of 1.7B)
- Use Settings → Models to unload other engines you're not using
- Enable `low_cpu_mem_usage` is already on for CPU; for CUDA, the engine's `device_map` handles offload automatically
- Close other GPU applications
</Accordion>
<Accordion title="MPS fallback errors on macOS">
Some operations don't have a Metal implementation. Voicebox sets `PYTORCH_ENABLE_MPS_FALLBACK=1` for engines that need it (notably Kokoro), but if you launch from a custom env, set it manually:
```bash
export PYTORCH_ENABLE_MPS_FALLBACK=1
```
</Accordion>
<Accordion title="Generation works but is slow on my GPU">
- Check Settings → GPU shows your GPU (not CPU)
- Check VRAM usage — you may be paging to system memory
- Try a smaller model
- For NVIDIA: confirm cu128 is installed (Settings → GPU → version)
</Accordion>
</AccordionGroup>
## Next Steps
<Cards>
<Card title="Remote Mode" href="/overview/remote-mode">
Run the backend on a different machine with a stronger GPU
</Card>
<Card title="Model Management" href="/developer/model-management">
Unload models to free GPU memory
</Card>
<Card title="Troubleshooting" href="/overview/troubleshooting">
General troubleshooting beyond GPU
</Card>
</Cards>
+2
View File
@@ -6,7 +6,9 @@
"installation",
"docker",
"quick-start",
"gpu-acceleration",
"voice-cloning",
"preset-voices",
"stories-editor",
"recording-transcription",
"generation-history",
@@ -0,0 +1,202 @@
---
title: "Preset Voices"
description: "Use built-in, ready-made voices without recording audio samples"
---
## Overview
Some Voicebox engines ship with a curated set of pre-built voices. Instead of cloning from your own audio sample, you pick a voice from a fixed catalog and the model speaks in that voice. No recording, no upload, no per-voice training required.
Two engines in 0.4 ship preset voices:
| Engine | Voices | Languages | Strengths |
| --------------------- | ----------------------- | --------- | ------------------------------------------------------- |
| **Kokoro 82M** | 50 | 9 | Tiny model, CPU-friendly, lowest VRAM of any engine |
| **Qwen CustomVoice** | 9 (premium curated) | 4 | Natural-language style control over tone, emotion, pace |
<Callout type="info">
Looking for cloning a specific person's voice instead? See [Voice Cloning](/overview/voice-cloning).
</Callout>
## When to Use Preset Voices
<Cards>
<Card title="No reference audio">
You don't have (or don't want to provide) a recording of the target voice
</Card>
<Card title="Production reliability">
Curated voices have predictable quality across any text input
</Card>
<Card title="Speed">
Skip the audio cleanup, sample preparation, and quality iteration loop
</Card>
<Card title="Lightweight setup">
Kokoro runs at CPU realtime with ~150 MB on disk — no GPU needed
</Card>
</Cards>
## Creating a Preset-Voice Profile
<Steps>
<Step title="Open Profiles → New Profile">
Same entry point as cloning profiles
</Step>
<Step title="Choose the engine">
Select **Kokoro** or **Qwen CustomVoice** from the engine dropdown
</Step>
<Step title="Pick a preset voice">
The voice catalog for the chosen engine appears — preview each by clicking it
</Step>
<Step title="Name and save">
Give the profile a name. No audio sample needed — just save
</Step>
<Step title="Generate">
Use the profile like any other in the floating generate box or the Generate page
</Step>
</Steps>
<Callout type="info">
Preset profiles are locked to their source engine — switching engines won't work since the voice exists only for that model. The profile grid greys out preset profiles when you switch to a different engine, and clicking one auto-switches the engine back to the right one.
</Callout>
## Kokoro 82M — 50 Voices Across 9 Languages
Kokoro is the smallest engine in Voicebox at 82M parameters. It runs at CPU realtime with negligible VRAM, making it the best option for lightweight local inference. Voices are pre-built style vectors trained into the model — there's no concept of cloning here.
**Repository:** [`hexgrad/Kokoro-82M`](https://huggingface.co/hexgrad/Kokoro-82M) · Apache 2.0 licensed
### American English
| Female | Male |
| ------- | ------- |
| Alloy | Adam |
| Aoede | Echo |
| Bella | Eric |
| Heart | Fenrir |
| Jessica | Liam |
| Kore | Michael |
| Nicole | Onyx |
| Nova | Puck |
| River | Santa |
| Sarah | |
| Sky | |
### British English
| Female | Male |
| -------- | ------ |
| Alice | Daniel |
| Emma | Fable |
| Isabella | George |
| Lily | Lewis |
### Other Languages
| Language | Voices |
| ----------------- | ------------------------------------------- |
| Spanish (`es`) | Dora (f), Alex (m), Santa (m) |
| French (`fr`) | Siwis (f) |
| Hindi (`hi`) | Alpha (f), Beta (f), Omega (m), Psi (m) |
| Italian (`it`) | Sara (f), Nicola (m) |
| Japanese (`ja`) | Alpha (f), Gongitsune (f), Nezumi (f), Tebukuro (f), Kumo (m) |
| Portuguese (`pt`) | Dora (f), Alex (m), Santa (m) |
| Chinese (`zh`) | Xiaobei (f), Xiaoni (f), Xiaoxiao (f), Xiaoyi (f) |
### Kokoro at a Glance
| Property | Value |
| --------------- | -------------------------------------------- |
| Parameters | 82M |
| Sample rate | 24 kHz |
| VRAM | ~150 MB (negligible on CPU) |
| Speed | Realtime on CPU, faster on GPU |
| Instruct | Not supported (preset voice carries the style) |
| License | Apache 2.0 |
## Qwen CustomVoice — 9 Premium Voices with Instruct Control
Qwen CustomVoice ships with 9 curated speakers and supports **natural-language style control** — you tell the model how to deliver the line ("speak slowly with warmth", "authoritative and clear") and it adapts tone, emotion, and pace.
Two model sizes:
- **1.7B** — full quality, recommended default
- **0.6B** — lighter, faster, lower-end hardware
**Repository:** [`Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice`](https://huggingface.co/Qwen/Qwen3-TTS-12Hz-1.7B-CustomVoice) (and 0.6B variant) · by Alibaba
### Voice Catalog
| Speaker | Gender | Language | Description |
| --------- | ------ | -------- | ------------------------------------------------------------ |
| Vivian | female | Chinese | Bright, slightly edgy young female voice |
| Serena | female | Chinese | Warm, gentle young female voice |
| Uncle Fu | male | Chinese | Seasoned male voice with a low, mellow timbre |
| Dylan | male | Chinese | Youthful Beijing male voice with a clear, natural timbre |
| Eric | male | Chinese | Lively Chengdu male voice with a slightly husky brightness |
| Ryan | male | English | Dynamic male voice with strong rhythmic drive (default) |
| Aiden | male | English | Sunny American male voice with a clear midrange |
| Ono Anna | female | Japanese | Playful Japanese female voice with a light, nimble timbre |
| Sohee | female | Korean | Warm Korean female voice with rich emotion |
### Using Instruct Mode
In the floating generate box, switch to a Qwen CustomVoice profile and click the **delivery instructions** toggle (slider icon, left of the generate button). A second textarea appears below the main text:
- Main text → what you want the voice to say
- Instruct text → how you want it delivered
Examples of effective instruct prompts:
```
Speak slowly with emphasis, like reading bedtime stories
Warm and friendly, conversational tone
Professional and authoritative, broadcast quality
Whisper, intimate and close
Excited and energetic, like sports commentary
```
The full Generate page also surfaces the instruct field as a separate input.
### Qwen CustomVoice at a Glance
| Property | Value |
| --------------- | -------------------------------------------------- |
| Parameters | 1.7B / 0.6B |
| Languages | Chinese, English, Japanese, Korean (10 supported) |
| Voices | 9 curated preset speakers |
| VRAM | ~3.5 GB (1.7B), ~1.2 GB (0.6B) |
| Instruct | Yes — natural-language style control |
| Cloning | No — paired Base Qwen3-TTS engine handles cloning |
## Cloning vs Preset — Quick Decision
| You want… | Use |
| -------------------------------------------------- | ----------------------------------------- |
| To replicate a specific person's voice | [Voice Cloning](/overview/voice-cloning) |
| Production-ready voices with no audio prep | Kokoro or Qwen CustomVoice |
| The smallest possible footprint (CPU-only) | Kokoro |
| Fine control over delivery (tone, pace, emotion) | Qwen CustomVoice |
| The broadest language coverage | [Voice Cloning](/overview/voice-cloning) via Chatterbox Multilingual (23 langs) |
## Limitations
<Callout type="warn">
Preset voices are fixed — you can't fine-tune or modify the underlying voice. If you want a specific voice that isn't in the catalog, use a cloning engine and provide a reference sample.
</Callout>
- Preset voices can't be exported to use in other Voicebox installations as audio (only as profile metadata pointing to the same engine + voice ID)
- The Kokoro voice catalog is set by the upstream model — new voices appear only when hexgrad publishes new model releases
- Qwen CustomVoice's 9 speakers are part of the model checkpoint — same constraint
## Next Steps
<Cards>
<Card title="Voice Cloning" href="/overview/voice-cloning">
Clone a specific voice from your own audio
</Card>
<Card title="Generate Speech" href="/overview/generating-speech">
Use a profile to generate audio
</Card>
<Card title="Build Stories" href="/overview/building-stories">
Compose multi-voice narratives
</Card>
</Cards>
@@ -69,6 +69,16 @@ Now let's use your new voice profile to generate speech.
```
Hello! This is my first voice generation with Voicebox.
```
<Callout type="info">
Paralinguistic tags like `[laugh]`, `[sigh]`, and `[gasp]` only work with
**Chatterbox Turbo**. Qwen3-TTS, LuxTTS, Chatterbox Multilingual, and
HumeAI TADA will read those tags literally instead of turning them into
expressive sounds.
</Callout>
To insert supported tags, select **Chatterbox Turbo** and type `/` in the
text input to open the tag inserter.
</Step>
<Step title="Generate">
+58 -15
View File
@@ -1,11 +1,25 @@
---
title: "Voice Cloning"
description: "Clone any voice from just a few seconds of audio"
description: "Clone any voice from a few seconds of reference audio"
---
## Overview
Voicebox uses **Qwen3-TTS** from Alibaba to achieve near-perfect voice cloning from just a few seconds of audio. The model captures prosody, emotion, and natural cadence.
Voicebox can replicate a specific person's voice from a short audio sample — known as **zero-shot voice cloning**. You provide 10-30 seconds of clear speech, the model extracts a voice embedding, and from then on you can generate any text in that voice.
Five engines in 0.4 support cloning:
| Engine | Languages | Strengths |
| --------------------------- | --------- | -------------------------------------------------------------------------- |
| **Qwen3-TTS** (0.6B / 1.7B) | 10 | High-quality multilingual, supports delivery instructions on the same kwarg |
| **Chatterbox Multilingual** | 23 | Broadest language coverage — Arabic, Hindi, Swahili, Hebrew, more |
| **Chatterbox Turbo** | English | Fast 350M model with paralinguistic emotion tags (`[laugh]`, `[sigh]`) |
| **LuxTTS** | English | Lightweight (~1 GB VRAM), 48 kHz output, 150x realtime on CPU |
| **TADA** (1B / 3B) | 10 | Speech-language model with 700s+ coherent long-form generation |
<Callout type="info">
Don't want to record audio? Use a curated voice from Kokoro or Qwen CustomVoice instead — see [Preset Voices](/overview/preset-voices).
</Callout>
## How It Works
@@ -13,17 +27,30 @@ Voicebox uses **Qwen3-TTS** from Alibaba to achieve near-perfect voice cloning f
<Step title="Upload or Record Sample">
Provide 10-30 seconds of clear speech from the target voice
</Step>
<Step title="Model Analysis">
Qwen3-TTS analyzes vocal characteristics, tone, and speaking patterns
<Step title="Engine Analysis">
The selected engine analyzes vocal characteristics, tone, and speaking patterns
</Step>
<Step title="Voice Profile Created">
The model generates a voice embedding for synthesis
A voice embedding is generated and stored with your profile
</Step>
<Step title="Generate Speech">
Use the profile to generate any text in the cloned voice
</Step>
</Steps>
## Choosing an Engine for Cloning
Different engines suit different use cases. The profile grid greys out unsupported engines so you can switch easily.
| If you want… | Pick |
| -------------------------------------------------- | --------------------- |
| Best overall quality on a few common languages | **Qwen3-TTS 1.7B** |
| Faster generation, slightly lower quality | **Qwen3-TTS 0.6B** |
| Languages outside Qwen's 10 (Arabic, Hindi, etc.) | **Chatterbox Multilingual** |
| Expressive English with `[laugh]` `[sigh]` tags | **Chatterbox Turbo** |
| CPU-only or GPU-light setup, English | **LuxTTS** |
| Long-form generation (audiobooks, full chapters) | **TADA 3B** |
## Best Practices
### Sample Quality
@@ -52,24 +79,40 @@ Adding multiple samples from the same speaker can improve quality:
- Different recording conditions
<Callout type="info">
The model will learn a more robust representation from diverse samples.
The model will learn a more robust representation from diverse samples. Especially helpful for distinctive voices the model might otherwise smooth over.
</Callout>
## Supported Languages
## Supported Languages by Engine
Currently supported:
- English
- Chinese (Mandarin)
- **Qwen3-TTS** — English, Chinese, Japanese, Korean, German, French, Russian, Portuguese, Spanish, Italian (10)
- **Chatterbox Multilingual** — Arabic, Chinese, Danish, Dutch, English, Finnish, French, German, Greek, Hebrew, Hindi, Italian, Japanese, Korean, Malay, Norwegian, Polish, Portuguese, Russian, Spanish, Swahili, Swedish, Turkish (23)
- **Chatterbox Turbo** — English
- **LuxTTS** — English
- **TADA 3B** — 10 multilingual; **TADA 1B** — English
More languages coming soon.
For complete language tables and engine-specific notes, see the [TTS Engines developer guide](/developer/tts-engines).
## Limitations
<Callout type="warn">
Voice cloning should only be used with consent. Ensure you have permission to clone someone's voice.
Voice cloning should only be used with consent. Ensure you have permission to clone someone's voice. See the project's [SECURITY.md](https://github.com/jamiepine/voicebox/blob/main/SECURITY.md) and your local laws on synthetic voice content.
</Callout>
- Quality depends on sample clarity
- Works best with consistent speaking tone
- Quality depends on sample clarity — noisy samples produce noisy clones
- Works best with consistent speaking tone within a sample
- May struggle with extreme accents or speech impediments
- Background noise reduces quality
- Background noise reduces quality and can introduce artifacts
## Next Steps
<Cards>
<Card title="Creating Voice Profiles" href="/overview/creating-voice-profiles">
Step-by-step guide to creating profiles
</Card>
<Card title="Preset Voices" href="/overview/preset-voices">
Use built-in voices instead of cloning
</Card>
<Card title="Generating Speech" href="/overview/generating-speech">
Use a profile to generate audio
</Card>
</Cards>
+9
View File
@@ -295,6 +295,15 @@ fix-python: _ensure-venv
test: _ensure-venv
{{ venv_bin }}/python -m pytest {{ backend_dir }}/tests -v
# E2E: generate with every TTS model against the frozen binary (pass extra flags like --only kokoro)
[unix]
test-models *ARGS: _ensure-venv
{{ venv_bin }}/python {{ backend_dir }}/tests/test_all_models_e2e.py {{ ARGS }}
[windows]
test-models *ARGS: _ensure-venv
& "{{ python }}" {{ backend_dir }}/tests/test_all_models_e2e.py {{ ARGS }}
# ─── Database ─────────────────────────────────────────────────────────
# Initialize SQLite database
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "@voicebox/landing",
"version": "0.4.0",
"version": "0.4.1",
"description": "Landing page for voicebox.sh",
"scripts": {
"dev": "bun --bun next dev --turbo",
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+454 -300
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@@ -1,327 +1,481 @@
'use client';
"use client";
import { Github, Globe, Languages, MessageSquare, Zap } from 'lucide-react';
import { useEffect, useState } from 'react';
import { ControlUI } from '@/components/ControlUI';
import { Features } from '@/components/Features';
import { Footer } from '@/components/Footer';
import { Navbar } from '@/components/Navbar';
import { AppleIcon, LinuxIcon, WindowsIcon } from '@/components/PlatformIcons';
import { VoiceCreator } from '@/components/VoiceCreator';
import { DOWNLOAD_LINKS, GITHUB_REPO } from '@/lib/constants';
import type { DownloadLinks } from '@/lib/releases';
import {
Github,
Globe,
Languages,
MessageSquare,
SlidersHorizontal,
Zap,
} from "lucide-react";
import {useEffect, useState} from "react";
import {ApiSection} from "@/components/ApiSection";
import {ControlUI} from "@/components/ControlUI";
import {Features} from "@/components/Features";
import {Footer} from "@/components/Footer";
import {Navbar} from "@/components/Navbar";
import {AppleIcon, LinuxIcon, WindowsIcon} from "@/components/PlatformIcons";
import {TutorialsSection} from "@/components/TutorialsSection";
import {VoiceCreator} from "@/components/VoiceCreator";
import {DOWNLOAD_LINKS, GITHUB_REPO} from "@/lib/constants";
import type {DownloadLinks} from "@/lib/releases";
export default function Home() {
const [downloadLinks, setDownloadLinks] = useState<DownloadLinks>(DOWNLOAD_LINKS);
const [version, setVersion] = useState<string | null>(null);
const [totalDownloads, setTotalDownloads] = useState<number | null>(null);
const [downloadLinks, setDownloadLinks] =
useState<DownloadLinks>(DOWNLOAD_LINKS);
const [version, setVersion] = useState<string | null>(null);
const [totalDownloads, setTotalDownloads] = useState<number | null>(null);
useEffect(() => {
fetch('/api/releases')
.then((res) => {
if (!res.ok) throw new Error('Failed to fetch releases');
return res.json();
})
.then((data) => {
if (data.downloadLinks) setDownloadLinks(data.downloadLinks);
if (data.version) setVersion(data.version);
if (data.totalDownloads != null) setTotalDownloads(data.totalDownloads);
})
.catch((error) => {
console.error('Failed to fetch release info:', error);
});
}, []);
useEffect(() => {
fetch("/api/releases")
.then((res) => {
if (!res.ok) throw new Error("Failed to fetch releases");
return res.json();
})
.then((data) => {
if (data.downloadLinks) setDownloadLinks(data.downloadLinks);
if (data.version) setVersion(data.version);
if (data.totalDownloads != null) setTotalDownloads(data.totalDownloads);
})
.catch((error) => {
console.error("Failed to fetch release info:", error);
});
}, []);
return (
<>
<Navbar />
return (
<>
<Navbar />
{/* ── Hero Section ─────────────────────────────────────────────── */}
<section className="relative pt-32 pb-16">
{/* Background glow */}
<div className="hero-glow hero-glow-fade pointer-events-none absolute inset-0 -top-32">
<div className="absolute left-1/2 top-0 -translate-x-1/2 w-[800px] h-[600px] rounded-full bg-accent/15 blur-[150px]" />
<div className="absolute left-1/2 top-12 -translate-x-1/2 w-[500px] h-[400px] rounded-full bg-accent/10 blur-[80px]" />
</div>
{/* ── Hero Section ─────────────────────────────────────────────── */}
<section className="relative pt-32 pb-16">
{/* Background glow */}
<div className="hero-glow hero-glow-fade pointer-events-none absolute inset-0 -top-32">
<div className="absolute left-1/2 top-0 -translate-x-1/2 w-[800px] h-[600px] rounded-full bg-accent/15 blur-[150px]" />
<div className="absolute left-1/2 top-12 -translate-x-1/2 w-[500px] h-[400px] rounded-full bg-accent/10 blur-[80px]" />
</div>
<div className="relative mx-auto max-w-7xl px-6 text-center">
{/* Logo */}
<div
className="fade-in mx-auto mb-8 h-[120px] w-[120px] md:h-[160px] md:w-[160px]"
style={{ animationDelay: '0ms' }}
>
{/* eslint-disable-next-line @next/next/no-img-element */}
<img
src="/voicebox-logo-app.webp"
alt="Voicebox"
className="h-full w-full object-contain"
/>
</div>
<div className="relative mx-auto max-w-7xl px-6 text-center">
{/* Logo */}
<div
className="fade-in mx-auto mb-8 h-[120px] w-[120px] md:h-[160px] md:w-[160px]"
style={{animationDelay: "0ms"}}
>
{/* eslint-disable-next-line @next/next/no-img-element */}
<img
src="/voicebox-logo-app.webp"
alt="Voicebox"
className="h-full w-full object-contain"
/>
</div>
{/* Headline */}
<div className="fade-in relative" style={{ animationDelay: '100ms' }}>
<h1 className="text-5xl font-bold tracking-tighter leading-[0.9] text-foreground md:text-7xl lg:text-8xl">
Your voice, your machine.
</h1>
</div>
{/* Headline */}
<div className="fade-in relative" style={{animationDelay: "100ms"}}>
<h1 className="text-5xl font-bold tracking-tighter leading-[0.9] text-foreground md:text-7xl lg:text-8xl">
Clone any voice, in seconds.
</h1>
</div>
{/* Subtitle */}
<p
className="fade-in mx-auto mt-6 max-w-2xl text-lg text-muted-foreground md:text-xl"
style={{ animationDelay: '200ms' }}
>
Open source voice cloning studio with support for multiple TTS engines. Clone any voice,
generate natural speech, and compose multi-voice projects — all running locally.
</p>
{/* Subtitle */}
<p
className="fade-in mx-auto mt-6 max-w-2xl text-lg text-muted-foreground md:text-xl"
style={{animationDelay: "200ms"}}
>
Open source voice cloning studio with support for multiple TTS
engines. Clone any voice, generate natural speech, and compose
multi-voice projects. All running{" "}
<b className="text-white">locally on your machine.</b>
</p>
{/* CTAs */}
<div
className="fade-in mt-10 flex flex-col sm:flex-row items-center justify-center gap-4"
style={{ animationDelay: '300ms' }}
>
<a
href="#download"
className="rounded-full bg-accent px-8 py-3.5 text-sm font-semibold uppercase tracking-wider text-white shadow-[0_4px_20px_hsl(43_60%_50%/0.3),inset_0_2px_0_rgba(255,255,255,0.2),inset_0_-2px_0_rgba(0,0,0,0.1)] transition-all hover:bg-accent-faint active:shadow-[0_2px_10px_hsl(43_60%_50%/0.3),inset_0_4px_8px_rgba(0,0,0,0.3)]"
>
Download
</a>
<a
href={GITHUB_REPO}
target="_blank"
rel="noopener noreferrer"
className="flex items-center gap-2 rounded-full border border-border/60 bg-card/40 backdrop-blur-sm px-6 py-3 text-sm font-medium text-muted-foreground transition-colors hover:text-foreground hover:border-border"
>
<Github className="h-4 w-4" />
View on GitHub
</a>
</div>
{/* CTAs */}
<div
className="fade-in mt-10 flex flex-col sm:flex-row items-center justify-center gap-4"
style={{animationDelay: "300ms"}}
>
<a
href="#download"
className="rounded-full bg-accent px-8 py-3.5 text-sm font-semibold uppercase tracking-wider text-white shadow-[0_4px_20px_hsl(43_60%_50%/0.3),inset_0_2px_0_rgba(255,255,255,0.2),inset_0_-2px_0_rgba(0,0,0,0.1)] transition-all hover:bg-accent-faint active:shadow-[0_2px_10px_hsl(43_60%_50%/0.3),inset_0_4px_8px_rgba(0,0,0,0.3)]"
>
Download
</a>
<a
href={GITHUB_REPO}
target="_blank"
rel="noopener noreferrer"
className="flex items-center gap-2 rounded-full border border-border/60 bg-card/40 backdrop-blur-sm px-6 py-3 text-sm font-medium text-muted-foreground transition-colors hover:text-foreground hover:border-border"
>
<Github className="h-4 w-4" />
View on GitHub
</a>
</div>
{/* Version + downloads */}
<p
className="fade-in mt-4 text-xs text-muted-foreground/50"
style={{ animationDelay: '400ms' }}
>
{version ?? ''}
{version && totalDownloads != null ? ' \u00b7 ' : ''}
{totalDownloads != null ? `${totalDownloads.toLocaleString()} downloads` : ''}
{version || totalDownloads != null ? ' \u00b7 ' : ''}
macOS, Windows, Linux
</p>
</div>
{/* Version + downloads */}
<p
className="fade-in mt-4 text-xs text-muted-foreground/50"
style={{animationDelay: "400ms"}}
>
{version ?? ""}
{version && totalDownloads != null ? " \u00b7 " : ""}
{totalDownloads != null
? `${totalDownloads.toLocaleString()} downloads`
: ""}
{version || totalDownloads != null ? " \u00b7 " : ""}
macOS, Windows, Linux
</p>
</div>
{/* ── ControlUI mockup ─────────────────────────────────────── */}
<div className="mt-16">
<ControlUI />
</div>
</section>
{/* ── ControlUI mockup ─────────────────────────────────────── */}
<div className="mt-16">
<ControlUI />
</div>
</section>
{/* ── Features ─────────────────────────────────────────────── */}
<Features />
{/* ── Features ─────────────────────────────────────────────── */}
<Features />
{/* ── Voice Creator ────────────────────────────────────────── */}
<VoiceCreator />
{/* ── Voice Creator ────────────────────────────────────────── */}
<VoiceCreator />
{/* ── Models ─────────────────────────────────────────────────── */}
<section id="about" className="border-t border-border py-24">
<div className="mx-auto max-w-5xl px-6">
<div className="text-center mb-14">
<h2 className="text-3xl font-semibold tracking-tight text-foreground md:text-4xl mb-4">
Multi-Engine Architecture
</h2>
<p className="text-muted-foreground max-w-2xl mx-auto">
Choose the right model for every job. All models run locally on your hardware —
download once, use forever.
</p>
</div>
{/* ── Tutorials ────────────────────────────────────────────── */}
<TutorialsSection />
<div className="grid grid-cols-1 md:grid-cols-2 gap-4">
{/* Qwen3-TTS */}
<div className="rounded-xl border border-border bg-card/60 backdrop-blur-sm p-6 transition-colors hover:border-accent/30">
<div className="flex items-start justify-between mb-3">
<div>
<h3 className="text-base font-semibold text-foreground">Qwen3-TTS</h3>
<span className="text-xs text-muted-foreground/60">by Alibaba</span>
</div>
<div className="flex gap-1.5">
<span className="text-[10px] px-2 py-0.5 rounded-full border border-border bg-background text-muted-foreground">
1.7B
</span>
<span className="text-[10px] px-2 py-0.5 rounded-full border border-border bg-background text-muted-foreground">
0.6B
</span>
</div>
</div>
<p className="text-sm text-muted-foreground leading-relaxed mb-4">
High-quality multilingual voice cloning with natural prosody. The only engine with
delivery instructions — control tone, pace, and emotion with natural language.
</p>
<div className="flex flex-wrap gap-2">
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
<Globe className="h-3 w-3" />
10 languages
</span>
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
<MessageSquare className="h-3 w-3" />
Delivery instructions
</span>
</div>
</div>
{/* ── API Section ──────────────────────────────────────────── */}
<ApiSection />
{/* Chatterbox */}
<div className="rounded-xl border border-border bg-card/60 backdrop-blur-sm p-6 transition-colors hover:border-accent/30">
<div className="flex items-start justify-between mb-3">
<div>
<h3 className="text-base font-semibold text-foreground">Chatterbox</h3>
<span className="text-xs text-muted-foreground/60">by Resemble AI</span>
</div>
</div>
<p className="text-sm text-muted-foreground leading-relaxed mb-4">
Production-grade voice cloning with the broadest language support. 23 languages with
zero-shot cloning and emotion exaggeration control.
</p>
<div className="flex flex-wrap gap-2">
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
<Languages className="h-3 w-3" />
23 languages
</span>
</div>
</div>
{/* ── Models ─────────────────────────────────────────────────── */}
<section id="about" className="border-t border-border py-24">
<div className="mx-auto max-w-5xl px-6">
<div className="text-center mb-14">
<h2 className="text-3xl font-semibold tracking-tight text-foreground md:text-4xl mb-4">
Multi-Engine Architecture
</h2>
<p className="text-muted-foreground max-w-2xl mx-auto">
Choose the right model for every job. All models run locally on
your hardware — download once, use forever.
</p>
</div>
{/* Chatterbox Turbo */}
<div className="rounded-xl border border-border bg-card/60 backdrop-blur-sm p-6 transition-colors hover:border-accent/30">
<div className="flex items-start justify-between mb-3">
<div>
<h3 className="text-base font-semibold text-foreground">Chatterbox Turbo</h3>
<span className="text-xs text-muted-foreground/60">by Resemble AI</span>
</div>
<span className="text-[10px] px-2 py-0.5 rounded-full border border-border bg-background text-muted-foreground">
350M
</span>
</div>
<p className="text-sm text-muted-foreground leading-relaxed mb-4">
Lightweight and fast. Supports paralinguistic tags — embed [laugh], [sigh], [gasp]
and more directly in your text for expressive, natural speech.
</p>
<div className="flex flex-wrap gap-2">
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
<Zap className="h-3 w-3" />
350M params
</span>
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
<MessageSquare className="h-3 w-3" />
[laugh] [sigh] tags
</span>
</div>
</div>
<div className="grid grid-cols-1 md:grid-cols-2 gap-4">
{/* Qwen3-TTS */}
<div className="rounded-xl border border-border bg-card/60 backdrop-blur-sm p-6 transition-colors hover:border-accent/30">
<div className="flex items-start justify-between mb-3">
<div>
<h3 className="text-base font-semibold text-foreground">
Qwen3-TTS
</h3>
<span className="text-xs text-muted-foreground/60">
by Alibaba
</span>
</div>
<div className="flex gap-1.5">
<span className="text-[10px] px-2 py-0.5 rounded-full border border-border bg-background text-muted-foreground">
1.7B
</span>
<span className="text-[10px] px-2 py-0.5 rounded-full border border-border bg-background text-muted-foreground">
0.6B
</span>
</div>
</div>
<p className="text-sm text-muted-foreground leading-relaxed mb-4">
High-quality multilingual voice cloning with natural prosody.
The only engine with delivery instructions — control tone, pace,
and emotion with natural language.
</p>
<div className="flex flex-wrap gap-2">
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
<Globe className="h-3 w-3" />
10 languages
</span>
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
<MessageSquare className="h-3 w-3" />
Delivery instructions
</span>
</div>
</div>
{/* LuxTTS */}
<div className="rounded-xl border border-border bg-card/60 backdrop-blur-sm p-6 transition-colors hover:border-accent/30">
<div className="flex items-start justify-between mb-3">
<div>
<h3 className="text-base font-semibold text-foreground">LuxTTS</h3>
<span className="text-xs text-muted-foreground/60">by ZipVoice</span>
</div>
</div>
<p className="text-sm text-muted-foreground leading-relaxed mb-4">
Ultra-fast, CPU-friendly voice cloning at 48kHz. Exceeds 150x realtime on CPU with
~1GB VRAM. The fastest engine for quick iterations.
</p>
<div className="flex flex-wrap gap-2">
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
<Zap className="h-3 w-3" />
150x realtime
</span>
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
48kHz output
</span>
</div>
</div>
</div>
</div>
</section>
{/* Chatterbox */}
<div className="rounded-xl border border-border bg-card/60 backdrop-blur-sm p-6 transition-colors hover:border-accent/30">
<div className="flex items-start justify-between mb-3">
<div>
<h3 className="text-base font-semibold text-foreground">
Chatterbox
</h3>
<span className="text-xs text-muted-foreground/60">
by Resemble AI
</span>
</div>
</div>
<p className="text-sm text-muted-foreground leading-relaxed mb-4">
Production-grade voice cloning with the broadest language
support. 23 languages with zero-shot cloning and emotion
exaggeration control.
</p>
<div className="flex flex-wrap gap-2">
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
<Languages className="h-3 w-3" />
23 languages
</span>
</div>
</div>
{/* ── Download Section ─────────────────────────────────────── */}
<section id="download" className="border-t border-border py-24">
<div className="mx-auto max-w-4xl px-6">
<div className="text-center mb-12">
<h2 className="text-3xl font-semibold tracking-tight text-foreground md:text-4xl mb-4">
Download Voicebox
</h2>
<p className="text-muted-foreground">
Available for macOS, Windows, and Linux. No dependencies required.
</p>
</div>
{/* Chatterbox Turbo */}
<div className="rounded-xl border border-border bg-card/60 backdrop-blur-sm p-6 transition-colors hover:border-accent/30">
<div className="flex items-start justify-between mb-3">
<div>
<h3 className="text-base font-semibold text-foreground">
Chatterbox Turbo
</h3>
<span className="text-xs text-muted-foreground/60">
by Resemble AI
</span>
</div>
<span className="text-[10px] px-2 py-0.5 rounded-full border border-border bg-background text-muted-foreground">
350M
</span>
</div>
<p className="text-sm text-muted-foreground leading-relaxed mb-4">
Lightweight and fast. Supports paralinguistic tags — embed
[laugh], [sigh], [gasp] and more directly in your text for
expressive, natural speech.
</p>
<div className="flex flex-wrap gap-2">
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
<Zap className="h-3 w-3" />
350M params
</span>
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
<MessageSquare className="h-3 w-3" />
[laugh] [sigh] tags
</span>
</div>
</div>
<div className="grid grid-cols-1 sm:grid-cols-2 gap-3 max-w-2xl mx-auto">
{/* macOS ARM */}
<a
href={downloadLinks.macArm}
download
className="flex items-center rounded-xl border border-border bg-card/60 backdrop-blur-sm px-5 py-4 transition-all hover:border-accent/30 hover:bg-card group"
>
<AppleIcon className="h-6 w-6 shrink-0 text-muted-foreground group-hover:text-foreground transition-colors" />
<div className="ml-4">
<div className="text-sm font-medium">macOS</div>
<div className="text-xs text-muted-foreground">Apple Silicon (ARM)</div>
</div>
</a>
{/* LuxTTS */}
<div className="rounded-xl border border-border bg-card/60 backdrop-blur-sm p-6 transition-colors hover:border-accent/30">
<div className="flex items-start justify-between mb-3">
<div>
<h3 className="text-base font-semibold text-foreground">
LuxTTS
</h3>
<span className="text-xs text-muted-foreground/60">
by ZipVoice
</span>
</div>
</div>
<p className="text-sm text-muted-foreground leading-relaxed mb-4">
Ultra-fast, CPU-friendly voice cloning at 48kHz. Exceeds 150x
realtime on CPU with ~1GB VRAM. The fastest engine for quick
iterations.
</p>
<div className="flex flex-wrap gap-2">
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
<Zap className="h-3 w-3" />
150x realtime
</span>
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
48kHz output
</span>
</div>
</div>
{/* macOS Intel */}
<a
href={downloadLinks.macIntel}
download
className="flex items-center rounded-xl border border-border bg-card/60 backdrop-blur-sm px-5 py-4 transition-all hover:border-accent/30 hover:bg-card group"
>
<AppleIcon className="h-6 w-6 shrink-0 text-muted-foreground group-hover:text-foreground transition-colors" />
<div className="ml-4">
<div className="text-sm font-medium">macOS</div>
<div className="text-xs text-muted-foreground">Intel (x64)</div>
</div>
</a>
{/* Qwen CustomVoice */}
<div className="rounded-xl border border-border bg-card/60 backdrop-blur-sm p-6 transition-colors hover:border-accent/30">
<div className="flex items-start justify-between mb-3">
<div>
<h3 className="text-base font-semibold text-foreground">
Qwen CustomVoice
</h3>
<span className="text-xs text-muted-foreground/60">
by Alibaba
</span>
</div>
<div className="flex gap-1.5">
<span className="text-[10px] px-2 py-0.5 rounded-full border border-border bg-background text-muted-foreground">
1.7B
</span>
<span className="text-[10px] px-2 py-0.5 rounded-full border border-border bg-background text-muted-foreground">
0.6B
</span>
</div>
</div>
<p className="text-sm text-muted-foreground leading-relaxed mb-4">
Nine premium preset speakers with natural-language style
control. Tell the model how to deliver — "speak slowly with
warmth", "authoritative and clear" — and it adapts tone,
emotion, and pace.
</p>
<div className="flex flex-wrap gap-2">
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
<SlidersHorizontal className="h-3 w-3" />
Instruct control
</span>
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
<Globe className="h-3 w-3" />
10 languages
</span>
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
9 preset voices
</span>
</div>
</div>
{/* Windows */}
<a
href={downloadLinks.windows}
download
className="flex items-center rounded-xl border border-border bg-card/60 backdrop-blur-sm px-5 py-4 transition-all hover:border-accent/30 hover:bg-card group"
>
<WindowsIcon className="h-6 w-6 shrink-0 text-muted-foreground group-hover:text-foreground transition-colors" />
<div className="ml-4">
<div className="text-sm font-medium">Windows</div>
<div className="text-xs text-muted-foreground">64-bit (MSI)</div>
</div>
</a>
{/* HumeAI TADA */}
<div className="rounded-xl border border-border bg-card/60 backdrop-blur-sm p-6 transition-colors hover:border-accent/30">
<div className="flex items-start justify-between mb-3">
<div>
<h3 className="text-base font-semibold text-foreground">
TADA
</h3>
<span className="text-xs text-muted-foreground/60">
by Hume AI
</span>
</div>
<div className="flex gap-1.5">
<span className="text-[10px] px-2 py-0.5 rounded-full border border-border bg-background text-muted-foreground">
3B
</span>
<span className="text-[10px] px-2 py-0.5 rounded-full border border-border bg-background text-muted-foreground">
1B
</span>
</div>
</div>
<p className="text-sm text-muted-foreground leading-relaxed mb-4">
Speech-language model with text-acoustic dual alignment. Built
for long-form generation — produces 700s+ of coherent audio
without drift. Multilingual at 3B, English-focused at 1B.
</p>
<div className="flex flex-wrap gap-2">
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
<Globe className="h-3 w-3" />
10 languages
</span>
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
Long-form coherent
</span>
</div>
</div>
{/* Linux */}
<a
href="/linux-install"
className="flex items-center rounded-xl border border-border bg-card/60 backdrop-blur-sm px-5 py-4 transition-all hover:border-accent/30 hover:bg-card group"
>
<LinuxIcon className="h-6 w-6 shrink-0 text-muted-foreground group-hover:text-foreground transition-colors" />
<div className="ml-4">
<div className="text-sm font-medium">Linux</div>
<div className="text-xs text-muted-foreground">Build from source</div>
</div>
</a>
</div>
{/* Kokoro 82M */}
<div className="rounded-xl border border-border bg-card/60 backdrop-blur-sm p-6 transition-colors hover:border-accent/30">
<div className="flex items-start justify-between mb-3">
<div>
<h3 className="text-base font-semibold text-foreground">
Kokoro
</h3>
<span className="text-xs text-muted-foreground/60">
by hexgrad · Apache 2.0
</span>
</div>
<span className="text-[10px] px-2 py-0.5 rounded-full border border-border bg-background text-muted-foreground">
82M
</span>
</div>
<p className="text-sm text-muted-foreground leading-relaxed mb-4">
Tiny 82M-parameter TTS that runs at CPU realtime with negligible
VRAM. Pre-built voice styles instead of cloning — pick a voice,
type, generate. Smallest footprint of any engine.
</p>
<div className="flex flex-wrap gap-2">
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
<Zap className="h-3 w-3" />
CPU realtime
</span>
<span className="flex items-center gap-1 text-[11px] text-muted-foreground/70">
Preset voices
</span>
</div>
</div>
</div>
</div>
</section>
{/* GitHub link */}
<div className="mt-6 text-center">
<a
href={`${GITHUB_REPO}/releases`}
target="_blank"
rel="noopener noreferrer"
className="inline-flex items-center gap-2 text-sm text-muted-foreground hover:text-foreground transition-colors"
>
<Github className="h-4 w-4" />
View all releases on GitHub
</a>
</div>
</div>
</section>
{/* ── Download Section ─────────────────────────────────────── */}
<section id="download" className="border-t border-border py-24">
<div className="mx-auto max-w-4xl px-6">
<div className="text-center mb-12">
<h2 className="text-3xl font-semibold tracking-tight text-foreground md:text-4xl mb-4">
Download Voicebox
</h2>
<p className="text-muted-foreground">
Available for macOS, Windows, and Linux. No dependencies required.
</p>
</div>
{/* ── Footer ───────────────────────────────────────────────── */}
<Footer />
</>
);
<div className="grid grid-cols-1 sm:grid-cols-2 gap-3 max-w-2xl mx-auto">
{/* macOS ARM */}
<a
href={downloadLinks.macArm}
download
className="flex items-center rounded-xl border border-border bg-card/60 backdrop-blur-sm px-5 py-4 transition-all hover:border-accent/30 hover:bg-card group"
>
<AppleIcon className="h-6 w-6 shrink-0 text-muted-foreground group-hover:text-foreground transition-colors" />
<div className="ml-4">
<div className="text-sm font-medium">macOS</div>
<div className="text-xs text-muted-foreground">
Apple Silicon (ARM)
</div>
</div>
</a>
{/* macOS Intel */}
<a
href={downloadLinks.macIntel}
download
className="flex items-center rounded-xl border border-border bg-card/60 backdrop-blur-sm px-5 py-4 transition-all hover:border-accent/30 hover:bg-card group"
>
<AppleIcon className="h-6 w-6 shrink-0 text-muted-foreground group-hover:text-foreground transition-colors" />
<div className="ml-4">
<div className="text-sm font-medium">macOS</div>
<div className="text-xs text-muted-foreground">Intel (x64)</div>
</div>
</a>
{/* Windows */}
<a
href={downloadLinks.windows}
download
className="flex items-center rounded-xl border border-border bg-card/60 backdrop-blur-sm px-5 py-4 transition-all hover:border-accent/30 hover:bg-card group"
>
<WindowsIcon className="h-6 w-6 shrink-0 text-muted-foreground group-hover:text-foreground transition-colors" />
<div className="ml-4">
<div className="text-sm font-medium">Windows</div>
<div className="text-xs text-muted-foreground">
64-bit (MSI)
</div>
</div>
</a>
{/* Linux */}
<a
href="/linux-install"
className="flex items-center rounded-xl border border-border bg-card/60 backdrop-blur-sm px-5 py-4 transition-all hover:border-accent/30 hover:bg-card group"
>
<LinuxIcon className="h-6 w-6 shrink-0 text-muted-foreground group-hover:text-foreground transition-colors" />
<div className="ml-4">
<div className="text-sm font-medium">Linux</div>
<div className="text-xs text-muted-foreground">
Build from source
</div>
</div>
</a>
</div>
{/* GitHub link */}
<div className="mt-6 text-center">
<a
href={`${GITHUB_REPO}/releases`}
target="_blank"
rel="noopener noreferrer"
className="inline-flex items-center gap-2 text-sm text-muted-foreground hover:text-foreground transition-colors"
>
<Github className="h-4 w-4" />
View all releases on GitHub
</a>
</div>
</div>
</section>
{/* ── Footer ───────────────────────────────────────────────── */}
<Footer />
</>
);
}
+200
View File
@@ -0,0 +1,200 @@
"use client";
import {AppWindow, Code2, Gamepad2, Terminal, Wrench} from "lucide-react";
type Endpoint = {
method: "POST" | "GET" | "DELETE" | "PATCH";
path: string;
label: string;
};
const ENDPOINTS: Endpoint[] = [
{method: "POST", path: "/generate", label: "Generate speech"},
{method: "POST", path: "/generate/{id}/cancel", label: "Cancel a generation"},
{method: "GET", path: "/profiles", label: "List voice profiles"},
{method: "POST", path: "/profiles", label: "Create a new profile"},
{method: "GET", path: "/models/status", label: "Model catalog & state"},
{method: "GET", path: "/history", label: "Past generations"},
{method: "GET", path: "/health", label: "Server health"},
];
const METHOD_STYLES: Record<Endpoint["method"], string> = {
POST: "bg-accent/10 text-accent border-accent/20",
GET: "bg-muted text-muted-foreground border-border",
DELETE: "bg-red-500/10 text-red-400 border-red-500/20",
PATCH: "bg-blue-500/10 text-blue-400 border-blue-500/20",
};
const CURL_SNIPPET = `curl -X POST http://127.0.0.1:17493/generate \\
-H "Content-Type: application/json" \\
-d '{
"text": "Welcome to the game, player one.",
"profile_id": "morgan-freeman",
"engine": "qwen",
"instruct": "warm, slow, cinematic"
}' \\
--output line.wav`;
const USE_CASES = [
{
icon: Gamepad2,
title: "Games",
description:
"Generate NPC dialogue on the fly, localize characters into new languages, or ship expressive voice lines without a studio.",
},
{
icon: AppWindow,
title: "Apps & agents",
description:
"Give your app or AI agent a voice. Real-time narration, accessibility readouts, voice replies — all running on the user's machine.",
},
{
icon: Wrench,
title: "Scripts & tools",
description:
"Batch-generate audiobook chapters, automate podcast intros, or wire Voicebox into your Stream Deck. It's just a localhost URL.",
},
];
export function ApiSection() {
return (
<section id="api" className="border-t border-border py-24">
<div className="mx-auto max-w-6xl px-6">
{/* Header */}
<div className="text-center mb-14">
<div className="inline-flex items-center gap-2 rounded-full border border-border/60 bg-card/40 backdrop-blur-sm px-3 py-1 mb-4">
<Code2 className="h-3 w-3 text-accent" />
<span className="text-[11px] font-medium uppercase tracking-wider text-muted-foreground">
Built-in REST API
</span>
</div>
<h2 className="text-3xl font-semibold tracking-tight text-foreground md:text-4xl mb-4">
Your local voice API
</h2>
<p className="text-muted-foreground max-w-2xl mx-auto">
Every engine you download becomes a REST endpoint on your machine.
Build apps, games, and voice tools with full programmatic control —
no API keys, no rate limits, no per-character fees.
</p>
</div>
{/* Main panel: endpoints + code snippet */}
<div className="grid grid-cols-1 lg:grid-cols-5 gap-5 mb-14">
{/* Endpoint reference */}
<div className="lg:col-span-3 rounded-xl border border-border bg-card/60 backdrop-blur-sm overflow-hidden">
<div className="flex items-center justify-between px-5 py-3 border-b border-border/60 bg-card/40">
<div className="flex items-center gap-2">
<div className="flex gap-1">
<div className="h-2 w-2 rounded-full bg-muted-foreground/30" />
<div className="h-2 w-2 rounded-full bg-muted-foreground/30" />
<div className="h-2 w-2 rounded-full bg-muted-foreground/30" />
</div>
<span className="text-xs font-medium text-foreground ml-2">
API Reference
</span>
</div>
<code className="text-[10px] bg-background border border-border px-1.5 py-0.5 rounded font-mono text-muted-foreground">
http://127.0.0.1:17493
</code>
</div>
<div className="px-5 py-4 space-y-1">
{ENDPOINTS.map((ep) => (
<div
key={`${ep.method}-${ep.path}`}
className="flex items-center gap-3 py-1.5 group"
>
<span
className={`text-[10px] font-mono font-semibold w-12 text-center rounded px-1 py-0.5 border ${METHOD_STYLES[ep.method]}`}
>
{ep.method}
</span>
<code className="text-xs font-mono text-foreground/90">
{ep.path}
</code>
<span className="text-xs text-muted-foreground/60 ml-auto">
{ep.label}
</span>
</div>
))}
</div>
<div className="border-t border-border/60 px-5 py-3 bg-card/40">
<a
href="http://127.0.0.1:17493/docs"
target="_blank"
rel="noopener noreferrer"
className="text-xs text-accent hover:underline"
>
See the full OpenAPI reference at{" "}
<code className="font-mono">/docs</code> when Voicebox is running
→
</a>
</div>
</div>
{/* Code snippet */}
<div className="lg:col-span-2 rounded-xl border border-border bg-card/60 backdrop-blur-sm overflow-hidden flex flex-col">
<div className="flex items-center gap-2 px-4 py-3 border-b border-border/60 bg-card/40">
<Terminal className="h-3.5 w-3.5 text-muted-foreground" />
<span className="text-xs font-medium text-foreground">
Generate a line
</span>
<span className="ml-auto text-[10px] text-muted-foreground/50 font-mono">
curl
</span>
</div>
<pre className="flex-1 p-4 text-[11px] font-mono text-muted-foreground/90 leading-relaxed overflow-x-auto whitespace-pre">
<code>{CURL_SNIPPET}</code>
</pre>
</div>
</div>
{/* Use cases */}
<div className="grid grid-cols-1 md:grid-cols-3 gap-4">
{USE_CASES.map((uc) => {
const Icon = uc.icon;
return (
<div
key={uc.title}
className="rounded-xl border border-border bg-card/60 backdrop-blur-sm p-5 transition-colors hover:border-accent/30"
>
<div className="flex items-center gap-2 mb-2">
<Icon className="h-4 w-4 text-accent" />
<h3 className="text-[15px] font-medium text-foreground">
{uc.title}
</h3>
</div>
<p className="text-sm leading-relaxed text-muted-foreground">
{uc.description}
</p>
</div>
);
})}
</div>
{/* Bottom bar: key selling points */}
<div className="mt-10 flex flex-wrap items-center justify-center gap-x-8 gap-y-2 text-xs text-muted-foreground">
<span className="flex items-center gap-1.5">
<span className="h-1.5 w-1.5 rounded-full bg-accent" />
No API keys
</span>
<span className="flex items-center gap-1.5">
<span className="h-1.5 w-1.5 rounded-full bg-accent" />
No rate limits
</span>
<span className="flex items-center gap-1.5">
<span className="h-1.5 w-1.5 rounded-full bg-accent" />
No per-character fees
</span>
<span className="flex items-center gap-1.5">
<span className="h-1.5 w-1.5 rounded-full bg-accent" />
Works offline
</span>
<span className="flex items-center gap-1.5">
<span className="h-1.5 w-1.5 rounded-full bg-accent" />
Your audio, your machine
</span>
</div>
</div>
</section>
);
}
+13 -2
View File
@@ -1,6 +1,7 @@
import { Coffee } from 'lucide-react';
import Image from 'next/image';
import Link from 'next/link';
import { GITHUB_REPO } from '@/lib/constants';
import { DONATE_URL, GITHUB_REPO } from '@/lib/constants';
export function Footer() {
return (
@@ -19,9 +20,19 @@ export function Footer() {
/>
<span className="text-sm font-semibold">Voicebox</span>
</div>
<p className="text-sm text-muted-foreground leading-relaxed">
<p className="text-sm text-muted-foreground leading-relaxed mb-4">
Open source voice cloning studio. Local-first, free forever.
</p>
<a
href={DONATE_URL}
target="_blank"
rel="noopener noreferrer"
className="inline-flex items-center gap-2 rounded-lg border border-border/60 bg-card/60 px-3 py-2 text-sm text-muted-foreground transition-colors hover:text-foreground hover:border-[#FFDD00]/40"
aria-label="Donate via Buy Me a Coffee"
>
<Coffee className="h-4 w-4 text-[#FFDD00]" />
<span className="text-[13px] font-medium">Donate</span>
</a>
</div>
{/* Product */}
+36 -18
View File
@@ -1,9 +1,9 @@
'use client';
import { Github } from 'lucide-react';
import { Coffee, Github } from 'lucide-react';
import Image from 'next/image';
import { useEffect, useState } from 'react';
import { GITHUB_REPO } from '@/lib/constants';
import { DONATE_URL, GITHUB_REPO } from '@/lib/constants';
function formatStarCount(count: number): string {
if (count >= 1000) {
@@ -57,7 +57,13 @@ export function Navbar() {
href="#about"
className="rounded-md px-3 py-1.5 text-sm font-medium text-muted-foreground transition-colors hover:text-foreground"
>
About
Models
</a>
<a
href="#api"
className="rounded-md px-3 py-1.5 text-sm font-medium text-muted-foreground transition-colors hover:text-foreground"
>
API
</a>
<a
href="#download"
@@ -75,21 +81,33 @@ export function Navbar() {
</a>
</div>
{/* GitHub star button */}
<a
href={GITHUB_REPO}
target="_blank"
rel="noopener noreferrer"
className="flex items-center gap-2 justify-self-end rounded-lg border border-border/60 bg-card/60 px-3 py-1.5 text-sm text-muted-foreground transition-colors hover:text-foreground hover:border-border"
>
<Github className="h-4 w-4" />
<span className="text-[13px] font-medium">Star</span>
{starCount !== null && (
<span className="border-l border-border/60 pl-2 text-[13px] font-semibold text-foreground">
{formatStarCount(starCount)}
</span>
)}
</a>
{/* Donate + GitHub star buttons */}
<div className="flex items-center gap-2 justify-self-end">
<a
href={DONATE_URL}
target="_blank"
rel="noopener noreferrer"
className="hidden sm:flex items-center gap-2 rounded-lg border border-border/60 bg-card/60 px-3 py-1.5 text-sm text-muted-foreground transition-colors hover:text-foreground hover:border-[#FFDD00]/40"
aria-label="Donate via Buy Me a Coffee"
>
<Coffee className="h-4 w-4 text-[#FFDD00]" />
<span className="text-[13px] font-medium">Donate</span>
</a>
<a
href={GITHUB_REPO}
target="_blank"
rel="noopener noreferrer"
className="flex items-center gap-2 rounded-lg border border-border/60 bg-card/60 px-3 py-1.5 text-sm text-muted-foreground transition-colors hover:text-foreground hover:border-border"
>
<Github className="h-4 w-4" />
<span className="text-[13px] font-medium">Star</span>
{starCount !== null && (
<span className="border-l border-border/60 pl-2 text-[13px] font-semibold text-foreground">
{formatStarCount(starCount)}
</span>
)}
</a>
</div>
</div>
</nav>
);
+127
View File
@@ -0,0 +1,127 @@
"use client";
import {Play, Youtube} from "lucide-react";
type Tutorial = {
id: string;
title: string;
author: string;
thumbnail: string;
};
const TUTORIALS: (Tutorial | null)[] = [
{
id: "sisnzgc73zc",
title: "Free AI Voice Generator on Your PC (Clones Any Voice)",
author: "Kevin Stratvert",
thumbnail: "/tutorials/sisnzgc73zc.jpg",
},
{
id: "woQe90k7g3c",
title: "NEW Voicebox DESTROYS ElevenLabs?",
author: "Julian Goldie SEO",
thumbnail: "/tutorials/woQe90k7g3c.jpg",
},
{
id: "kqxqjRsdD5E",
title: "This Open-Source TTS App Sounds Scary Good (And It's Free)",
author: "Dave Swift",
thumbnail: "/tutorials/kqxqjRsdD5E.jpg",
},
];
function TutorialCard({tutorial}: {tutorial: Tutorial}) {
return (
<a
href={`https://www.youtube.com/watch?v=${tutorial.id}`}
target="_blank"
rel="noopener noreferrer"
className="group rounded-xl border border-border bg-card/60 backdrop-blur-sm overflow-hidden transition-all hover:border-accent/30 hover:bg-card"
>
<div className="relative aspect-video overflow-hidden bg-muted">
{/* eslint-disable-next-line @next/next/no-img-element */}
<img
src={tutorial.thumbnail}
alt={tutorial.title}
className="h-full w-full object-cover transition-transform duration-500 group-hover:scale-105"
/>
{/* Gradient overlay */}
<div className="absolute inset-0 bg-gradient-to-t from-black/60 via-black/0 to-black/0" />
{/* Play button overlay */}
<div className="absolute inset-0 flex items-center justify-center">
<div className="flex h-14 w-14 items-center justify-center rounded-full bg-black/50 backdrop-blur-md border border-white/20 transition-all group-hover:scale-110 group-hover:bg-accent/90 group-hover:border-accent">
<Play className="h-5 w-5 text-white fill-white ml-0.5" />
</div>
</div>
{/* YouTube badge */}
<div className="absolute top-3 right-3 flex items-center gap-1 rounded bg-black/60 backdrop-blur-sm px-2 py-1">
<Youtube className="h-3 w-3 text-white" />
<span className="text-[10px] font-medium text-white uppercase tracking-wider">
YouTube
</span>
</div>
</div>
<div className="p-4">
<h3 className="text-sm font-medium text-foreground line-clamp-2 leading-snug mb-1.5 group-hover:text-accent transition-colors">
{tutorial.title}
</h3>
<p className="text-xs text-muted-foreground">{tutorial.author}</p>
</div>
</a>
);
}
function TutorialPlaceholder() {
return (
<div className="rounded-xl border border-dashed border-border/60 bg-card/30 backdrop-blur-sm overflow-hidden">
<div className="relative aspect-video overflow-hidden bg-gradient-to-br from-card via-muted/20 to-card">
<div className="absolute inset-0 flex items-center justify-center">
<div className="flex h-14 w-14 items-center justify-center rounded-full border border-border/40 bg-card/40">
<Play className="h-5 w-5 text-muted-foreground/40 fill-muted-foreground/40 ml-0.5" />
</div>
</div>
</div>
<div className="p-4">
<div className="h-3 w-3/4 rounded bg-muted-foreground/10 mb-2" />
<div className="h-2.5 w-1/3 rounded bg-muted-foreground/10" />
<p className="text-[11px] text-muted-foreground/50 mt-3 uppercase tracking-wider">
Coming soon
</p>
</div>
</div>
);
}
export function TutorialsSection() {
return (
<section id="tutorials" className="border-t border-border py-24">
<div className="mx-auto max-w-6xl px-6">
<div className="text-center mb-14">
<div className="inline-flex items-center gap-2 rounded-full border border-border/60 bg-card/40 backdrop-blur-sm px-3 py-1 mb-4">
<Youtube className="h-3 w-3 text-accent" />
<span className="text-[11px] font-medium uppercase tracking-wider text-muted-foreground">
Video tutorials
</span>
</div>
<h2 className="text-3xl font-semibold tracking-tight text-foreground md:text-4xl mb-4">
Learn by watching
</h2>
<p className="text-muted-foreground max-w-2xl mx-auto">
Walkthroughs from the community covering setup, voice cloning, and
production workflows.
</p>
</div>
<div className="grid grid-cols-1 md:grid-cols-3 gap-5">
{TUTORIALS.map((tutorial, i) =>
tutorial ? (
<TutorialCard key={tutorial.id} tutorial={tutorial} />
) : (
<TutorialPlaceholder key={`placeholder-${i}`} />
),
)}
</div>
</div>
</section>
);
}
+1
View File
@@ -4,6 +4,7 @@ export const LATEST_VERSION = 'v0.1.0';
export const GITHUB_REPO = 'https://github.com/jamiepine/voicebox';
export const GITHUB_RELEASES_PAGE = `${GITHUB_REPO}/releases`;
export const DONATE_URL = 'https://buymeacoffee.com/jamiepine';
export const DOWNLOAD_LINKS = {
macArm: GITHUB_RELEASES_PAGE,
+3 -2
View File
@@ -1,6 +1,6 @@
{
"name": "voicebox",
"version": "0.4.0",
"version": "0.4.1",
"private": true,
"workspaces": [
"app",
@@ -24,12 +24,13 @@
"update:icons": "./scripts/update-icons.sh",
"convert:assets": "./scripts/convert-assets.sh",
"lint": "biome lint .",
"typecheck": "bunx tsc -p app/tsconfig.json --noEmit && cd web && bunx tsc --noEmit",
"lint:fix": "biome lint --write .",
"format": "biome format --write .",
"format:check": "biome format .",
"check": "biome check .",
"check:fix": "biome check --write .",
"ci": "biome ci ."
"ci": "bun run typecheck && bun run build:web"
},
"devDependencies": {
"@biomejs/biome": "2.3.12",
+1 -1
View File
@@ -1,7 +1,7 @@
{
"name": "@voicebox/tauri",
"private": true,
"version": "0.4.0",
"version": "0.4.1",
"type": "module",
"scripts": {
"dev": "vite",
+1 -1
View File
@@ -5041,7 +5041,7 @@ checksum = "0b928f33d975fc6ad9f86c8f283853ad26bdd5b10b7f1542aa2fa15e2289105a"
[[package]]
name = "voicebox"
version = "0.3.1"
version = "0.4.0"
dependencies = [
"base64 0.22.1",
"core-foundation-sys",
+1 -1
View File
@@ -1,6 +1,6 @@
[package]
name = "voicebox"
version = "0.4.0"
version = "0.4.1"
description = "A production-quality desktop app for Qwen3-TTS voice cloning and generation"
authors = ["you"]
license = ""
+107 -13
View File
@@ -8,12 +8,71 @@ use std::sync::atomic::{AtomicBool, Ordering};
use std::sync::Arc;
use std::thread;
/// Try to find a PulseAudio/PipeWire monitor source using `pactl`.
/// Returns the source name (e.g. "alsa_output.pci-0000_0d_00.6.analog-stereo.monitor") if found.
fn find_monitor_source_via_pactl() -> Option<String> {
let output = std::process::Command::new("pactl")
.args(["list", "short", "sources"])
.output()
.ok()?;
if !output.status.success() {
return None;
}
let stdout = String::from_utf8_lossy(&output.stdout);
// First, try to find the monitor of the default sink
let default_sink = std::process::Command::new("pactl")
.args(["get-default-sink"])
.output()
.ok()
.and_then(|o| {
if o.status.success() {
Some(String::from_utf8_lossy(&o.stdout).trim().to_string())
} else {
None
}
});
// If we know the default sink, look for its .monitor specifically
if let Some(sink_name) = &default_sink {
let monitor_name = format!("{}.monitor", sink_name);
for line in stdout.lines() {
let parts: Vec<&str> = line.split('\t').collect();
if parts.len() >= 2 && parts[1] == monitor_name {
eprintln!(
"Linux audio capture: Found default sink monitor via pactl: {}",
monitor_name
);
return Some(monitor_name);
}
}
}
// Fallback: find any .monitor source
for line in stdout.lines() {
let parts: Vec<&str> = line.split('\t').collect();
if parts.len() >= 2 && parts[1].ends_with(".monitor") {
let name = parts[1].to_string();
eprintln!(
"Linux audio capture: Found monitor source via pactl: {}",
name
);
return Some(name);
}
}
None
}
/// Start capturing system audio on Linux using PulseAudio monitor sources.
///
/// PulseAudio exposes "monitor" devices that mirror the output of each sink,
/// allowing us to capture whatever audio is currently playing on the system.
/// We use `cpal` with the default host (which will be PulseAudio or PipeWire
/// on modern Linux) and look for monitor input devices.
/// On modern Linux with PulseAudio or PipeWire, we first try to detect the
/// monitor source via `pactl` and set the `PULSE_SOURCE` environment variable.
/// This tells PulseAudio's ALSA plugin to use the monitor as the default input
/// source for this process. If `pactl` is unavailable, we fall back to searching
/// cpal device names for "monitor".
pub async fn start_capture(
state: &AudioCaptureState,
max_duration_secs: u32,
@@ -42,30 +101,62 @@ pub async fn start_capture(
// Spawn capture on a dedicated thread
thread::spawn(move || {
// Try to set PULSE_SOURCE to a monitor before initializing cpal.
// This tells PulseAudio/PipeWire's ALSA plugin to use the monitor
// as the default input source for this process.
let monitor_source = find_monitor_source_via_pactl();
if let Some(ref source_name) = monitor_source {
eprintln!(
"Linux audio capture: Setting PULSE_SOURCE={}",
source_name
);
std::env::set_var("PULSE_SOURCE", source_name);
}
let host = cpal::default_host();
// Try to find a monitor device for system audio capture.
// On PulseAudio/PipeWire, monitor sources have "monitor" in their name.
let device = {
// Select the capture device.
// If PULSE_SOURCE was set, the default input device IS the monitor.
// Otherwise, fall back to searching device names for "monitor".
let device = if monitor_source.is_some() {
// PULSE_SOURCE was set — default input IS the monitor now
match host.default_input_device() {
Some(d) => {
let name = d.name().unwrap_or_default();
eprintln!(
"Linux audio capture: Using PULSE_SOURCE monitor device: {}",
name
);
d
}
None => {
let error_msg = "No audio input device available".to_string();
eprintln!("{}", error_msg);
*error_arc.lock().unwrap() = Some(error_msg);
return;
}
}
} else {
// pactl not available — try to find monitor by name (original approach)
let mut monitor_device = None;
if let Ok(devices) = host.input_devices() {
for d in devices {
if let Ok(name) = d.name() {
let name_lower = name.to_lowercase();
if name_lower.contains("monitor") {
eprintln!("Linux audio capture: Found monitor device: {}", name);
eprintln!(
"Linux audio capture: Found monitor device by name: {}",
name
);
monitor_device = Some(d);
break;
}
}
}
}
match monitor_device {
Some(d) => d,
None => {
// Fallback to default input device (microphone)
eprintln!("Linux audio capture: No monitor device found, falling back to default input");
match host.default_input_device() {
Some(d) => d,
@@ -266,7 +357,11 @@ pub async fn stop_capture(state: &AudioCaptureState) -> Result<String, String> {
}
pub fn is_supported() -> bool {
// Check if we can find a monitor device for system audio capture
// Check via pactl first (most reliable on modern Linux)
if find_monitor_source_via_pactl().is_some() {
return true;
}
// Fallback: check cpal devices
let host = cpal::default_host();
if let Ok(devices) = host.input_devices() {
for d in devices {
@@ -277,7 +372,6 @@ pub fn is_supported() -> bool {
}
}
}
// Even without a monitor, basic input capture is available
host.default_input_device().is_some()
}
+1 -1
View File
@@ -1,7 +1,7 @@
{
"$schema": "https://schema.tauri.app/config/2",
"productName": "Voicebox",
"version": "0.4.0",
"version": "0.4.1",
"identifier": "sh.voicebox.app",
"build": {
"beforeDevCommand": "bun run dev",
+1 -1
View File
@@ -1,7 +1,7 @@
{
"name": "@voicebox/web",
"private": true,
"version": "0.4.0",
"version": "0.4.1",
"type": "module",
"scripts": {
"dev": "vite",
-4
View File
@@ -11,10 +11,6 @@ class WebUpdater implements PlatformUpdater {
private subscribers: Set<(status: UpdateStatus) => void> = new Set();
private notifySubscribers() {
this.subscribers.forEach((callback) => callback(this.status));
}
subscribe(callback: (status: UpdateStatus) => void): () => void {
this.subscribers.add(callback);
callback(this.status);
+3 -2
View File
@@ -18,8 +18,9 @@
"baseUrl": ".",
"paths": {
"@/*": ["../app/src/*"]
}
},
"types": ["vite/client"]
},
"include": ["src"],
"include": ["src", "../app/src/global.d.ts"],
"references": [{ "path": "./tsconfig.node.json" }]
}