Compare commits

..
Author SHA1 Message Date
Jamie Pine 3bdc18f278 Remove orphaned react-qr-code entries from lockfile
bun.lock was out of date with package.json (react-qr-code was removed
without reinstalling), failing the frozen-lockfile install in CI.
2026-07-05 03:17:33 -07:00
Jamie Pine 0b8fd31c89 Address review feedback on cloud login
- time out status polling after 2 min so an abandoned browser flow
  doesn't leave the button stuck on "Waiting for browser…"
- handle non-JSON / non-object payloads from the exchange and account
  endpoints instead of 500ing after the state is consumed
- make singleton row creation race-safe (IntegrityError -> re-query)
- clear device_name on disconnect along with the rest of the metadata
- serve the dashboard URL from /cloud/status so the Manage link follows
  VOICEBOX_CLOUD_URL instead of hardcoding production
- keep a "Disconnecting…" label on the disconnect button while pending
2026-07-04 21:07:59 -07:00
James Pine 376afad852 Add "Log in with browser" cloud device login
Connects the desktop app to Voicebox Cloud without the user ever handling an
API key. One button in Settings → General opens the system browser to
voicebox.sh, the user authorizes while signed in, and the credential lands
back in the app automatically.

Backend (FastAPI):
- /cloud/login/start opens the browser to the cloud authorize page with a
  state we mint; the existing loopback server catches the redirect at
  /cloud/callback and exchanges the one-time code (server-to-server, over TLS)
  for a voicebox_ API key, verifies it against the API, and stores it.
- /cloud/status and /cloud/disconnect back the settings UI.
- state round-trip guards against login-CSRF; the key never crosses a browser
  URL and is never exposed to the frontend (status returns a prefix only).
- CloudSettings singleton row; config gains VOICEBOX_CLOUD_URL /
  VOICEBOX_CLOUD_API_URL (default the prod hosts, overridable for dev).

Frontend (React):
- CloudSection in Settings → General: "Log in with browser", polls status,
  shows the connected device + a dashboard link. API keys are the advanced
  path only, surfaced in the web dashboard.

The key is stored in the local app DB for now; OS keychain is a marked
follow-up.
2026-06-28 16:51:18 -07:00
176 changed files with 9940 additions and 11182 deletions
+1 -2
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@@ -8,8 +8,7 @@ tauri/
landing/
docs/
mlx-test/
scripts/*
!scripts/rocm-entrypoint.sh
scripts/
# Dependencies & build artifacts (rebuilt in Docker)
node_modules/
-61
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@@ -340,64 +340,3 @@ jobs:
name: voicebox-server-cuda-windows
path: backend/dist/voicebox-server-cuda/
retention-days: 7
build-rocm-windows:
runs-on: windows-latest
permissions:
contents: write
steps:
- uses: actions/checkout@v4
- name: Setup Python
uses: actions/setup-python@v5
with:
# ROCm wheels are cp312-cp312-specific — build_binary.py --rocm enforces this.
python-version: "3.12"
cache: "pip"
- name: Install Python dependencies
run: |
python -m pip install --upgrade pip
pip install pyinstaller
pip install -r backend/requirements.txt
pip install --no-deps chatterbox-tts
pip install --no-deps hume-tada
- name: Build ROCm server binary (onedir)
shell: bash
working-directory: backend
# build_binary.py --rocm pulls the official AMD Radeon torch + rocm_sdk
# wheels (rocm-rel-7.2.1) itself when ROCm torch is not already present,
# then restores the dev torch afterwards.
run: python build_binary.py --rocm
- name: Package into server core + ROCm libs archives
shell: bash
run: |
python scripts/package_rocm.py \
backend/dist/voicebox-server-rocm/ \
--output release-assets/ \
--rocm-libs-version rocm7.2-v1 \
--torch-compat ">=2.9.0,<2.10.0"
- name: Upload archives to GitHub Release
if: startsWith(github.ref, 'refs/tags/')
uses: softprops/action-gh-release@v2
with:
files: |
release-assets/voicebox-server-rocm.tar.gz
release-assets/voicebox-server-rocm.tar.gz.sha256
release-assets/rocm-libs-rocm7.2-v1.tar.gz
release-assets/rocm-libs-rocm7.2-v1.tar.gz.sha256
release-assets/rocm-libs.json
draft: true
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
- name: Upload onedir as workflow artifact
uses: actions/upload-artifact@v4
with:
name: voicebox-server-rocm-windows
path: backend/dist/voicebox-server-rocm/
retention-days: 7
BIN
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-11
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@@ -5,17 +5,6 @@
# Changelog
## [Unreleased]
### Linux
- **ROCm setup works on Linux AMD systems.** Docker ROCm builds now keep PyTorch
on the ROCm wheel index during dependency installation, so later installs do
not replace it with CUDA wheels. The ROCm compose overlay no longer assumes
Ubuntu render/video group IDs; the container joins the groups that own the GPU
device nodes at startup. Native Linux setup now picks ROCm wheels for AMD GPUs
and CUDA wheels for NVIDIA GPUs before installing backend dependencies.
## [0.5.0] - 2026-04-22
**The Capture release.** Voicebox stops being just a voice-cloning studio and becomes a full AI voice studio. Hold a key anywhere on your machine, speak, release — the transcript lands in the focused text field. Flip the primitive around and any MCP-aware agent — Claude Code, Cursor, Spacebot — speaks back through an on-screen pill in one of your cloned voices. A local LLM sits between the two, so transcripts come out clean and voice profiles can carry a personality that reshapes what the agent says before it gets spoken.
+2 -2
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@@ -91,7 +91,7 @@ On Windows, to build with CUDA support for local testing:
just build-local # Build CPU + CUDA server binaries + Tauri installer
```
This builds the CPU sidecar (bundled with the app), the CUDA binary (placed in `%APPDATA%/sh.voicebox.app/backends/` for runtime GPU switching), and the installable Tauri app.
This builds the CPU sidecar (bundled with the app), the CUDA binary (placed in `%APPDATA%/com.voicebox.app/backends/` for runtime GPU switching), and the installable Tauri app.
Creates platform-specific installers (`.dmg`, `.msi`, `.AppImage`) in `tauri/src-tauri/target/release/bundle/`.
@@ -133,7 +133,7 @@ bun run convert:assets
This script:
- Converts PNG → WebP (better compression, same quality)
- Converts MOV → WebM (VP9 codec, smaller file size)
- Processes files in `docs/public/`
- Processes files in `landing/public/` and `docs/public/`
- **Deletes original files** after successful conversion
**Requirements:** Install `webp` and `ffmpeg`:
+8 -31
View File
@@ -1,15 +1,8 @@
# ============================================================
# Voicebox — Local TTS Server with Web UI
# Voicebox — Local TTS Server with Web UI (CPU)
# 3-stage build: Frontend → Python deps → Runtime
#
# Build variants:
# CPU (default): docker compose up --build
# ROCm (AMD GPU): docker compose -f docker-compose.yml -f docker-compose.rocm.yml up --build
# ============================================================
# Top-level ARG so it is visible to all stages.
ARG PYTORCH_VARIANT=cpu
# === Stage 1: Build frontend ===
FROM oven/bun:1 AS frontend
@@ -21,7 +14,7 @@ COPY app/ ./app/
COPY web/ ./web/
# Strip workspaces not needed for web build, and fix trailing comma
RUN sed -i '/"tauri"/d' package.json && \
RUN sed -i '/"tauri"/d; /"landing"/d' package.json && \
sed -i -z 's/,\n ]/\n ]/' package.json
RUN bun install --no-save
# Build frontend (skip tsc — upstream has pre-existing type errors)
@@ -31,9 +24,6 @@ RUN cd web && bunx --bun vite build
# === Stage 2: Build Python dependencies ===
FROM python:3.11-slim AS backend-builder
# Re-declare ARG inside the stage (Docker scoping requirement).
ARG PYTORCH_VARIANT=cpu
WORKDIR /build
RUN apt-get update && apt-get install -y --no-install-recommends \
@@ -44,19 +34,6 @@ RUN apt-get update && apt-get install -y --no-install-recommends \
RUN pip install --no-cache-dir --upgrade pip
COPY backend/requirements.txt .
# ROCm wheel index. Default 6.3 (RDNA1/2/3); set ROCM_VERSION=7.2 for RDNA4.
ARG ROCM_VERSION=6.3
# For ROCm, make the PyTorch ROCm index primary so every install below resolves
# torch to ROCm wheels instead of the default CUDA build.
RUN if [ "$PYTORCH_VARIANT" = "rocm" ]; then \
pip install --no-cache-dir --prefix=/install \
--index-url "https://download.pytorch.org/whl/rocm${ROCM_VERSION}" \
torch torchaudio && \
printf '[global]\nindex-url = https://download.pytorch.org/whl/rocm%s\nextra-index-url = https://pypi.org/simple\n' "$ROCM_VERSION" > /etc/pip.conf; \
fi
RUN pip install --no-cache-dir --prefix=/install -r requirements.txt
RUN pip install --no-cache-dir --prefix=/install --no-deps chatterbox-tts
RUN pip install --no-cache-dir --prefix=/install --no-deps hume-tada
@@ -67,17 +44,16 @@ RUN pip install --no-cache-dir --prefix=/install \
# === Stage 3: Runtime ===
FROM python:3.11-slim
# Create non-root user; the entrypoint joins GPU device groups at runtime.
# Create non-root user for security
RUN groupadd -r voicebox && \
useradd -r -g voicebox -m -s /bin/bash voicebox
WORKDIR /app
# Install only runtime system dependencies (gosu drops root in the entrypoint)
# Install only runtime system dependencies
RUN apt-get update && apt-get install -y --no-install-recommends \
ffmpeg \
curl \
gosu \
&& rm -rf /var/lib/apt/lists/*
# Copy installed Python packages from builder stage
@@ -93,6 +69,9 @@ COPY --from=frontend --chown=voicebox:voicebox /build/web/dist /app/frontend/
RUN mkdir -p /app/data/generations /app/data/profiles /app/data/cache \
&& chown -R voicebox:voicebox /app/data
# Switch to non-root user
USER voicebox
# Expose the API port
EXPOSE 17493
@@ -100,7 +79,5 @@ EXPOSE 17493
HEALTHCHECK --interval=30s --timeout=10s --retries=3 --start-period=60s \
CMD curl -f http://localhost:17493/health || exit 1
# Entrypoint joins GPU groups then drops to the voicebox user
COPY --chmod=755 scripts/rocm-entrypoint.sh /usr/local/bin/entrypoint.sh
ENTRYPOINT ["/usr/local/bin/entrypoint.sh"]
# Start the FastAPI server
CMD ["uvicorn", "backend.main:app", "--host", "0.0.0.0", "--port", "17493"]
+5 -5
View File
@@ -45,7 +45,7 @@
<p align="center">
<a href="https://voicebox.sh">
<img src="docs/public/images/readme/app-screenshot-1.webp" alt="Voicebox App Screenshot" width="800" />
<img src="landing/public/assets/app-screenshot-1.webp" alt="Voicebox App Screenshot" width="800" />
</a>
</p>
@@ -56,11 +56,11 @@
<br/>
<p align="center">
<img src="docs/public/images/readme/app-screenshot-2.webp" alt="Voicebox Screenshot 2" width="800" />
<img src="landing/public/assets/app-screenshot-2.webp" alt="Voicebox Screenshot 2" width="800" />
</p>
<p align="center">
<img src="docs/public/images/readme/app-screenshot-3.webp" alt="Voicebox Screenshot 3" width="800" />
<img src="landing/public/assets/app-screenshot-3.webp" alt="Voicebox Screenshot 3" width="800" />
</p>
<br/>
@@ -270,8 +270,7 @@ Use cases: agent dev loops (dictate a question, hear the answer in a cloned voic
| Platform | Backend | Notes |
| ------------------------ | -------------- | ---------------------------------------------- |
| macOS (Apple Silicon) | MLX (Metal) | 4-5x faster via Neural Engine |
| Windows (NVIDIA) | PyTorch (CUDA) | Auto-downloads CUDA binary from within the app |
| Linux (NVIDIA) | PyTorch (CUDA) | Use a local/remote Python backend with CUDA PyTorch |
| Windows / Linux (NVIDIA) | PyTorch (CUDA) | Auto-downloads CUDA binary from within the app |
| Linux (AMD) | PyTorch (ROCm) | Auto-configures HSA_OVERRIDE_GFX_VERSION |
| Windows (any GPU) | DirectML | Universal Windows GPU support |
| Intel Arc | IPEX/XPU | Intel discrete GPU acceleration |
@@ -442,6 +441,7 @@ voicebox/
├── tauri/ # Desktop app (Tauri + Rust)
├── web/ # Web deployment
├── backend/ # Python FastAPI server
├── landing/ # Marketing website
└── scripts/ # Build & release scripts
```
@@ -35,17 +35,19 @@ export function DictateWindow() {
};
}, []);
// Mirrored from the main window: true only when dictation is armed and the
// user opted into keeping the microphone ready.
const [micWarm, setMicWarm] = useState(false);
// Snapshot of the focused UI element at chord-start, shipped over from
// Rust on the ``dictate:start`` payload. Held in a ref so it survives
// the 1–2 s transcribe + refine window — the paste only fires once the
// final text comes back.
const focusRef = useRef<FocusSnapshot | null>(null);
const session = useCaptureRecordingSession({
keepMicWarm: micWarm,
onFinalText: async (text, _capture, allowAutoPaste, context) => {
// Focus is the snapshot taken at chord-start and threaded through as this
// take's context, so it survives the 1–2 s transcribe + refine window and
// overlapping dictations can't paste into each other's target.
const focus = context as FocusSnapshot | null;
onFinalText: async (text, _capture, allowAutoPaste) => {
const focus = focusRef.current;
// Consume-once: a second chord before this fires would overwrite
// focusRef, but nulling it here guards against the late-arriving
// refine-result firing a paste after the user has moved on.
focusRef.current = null;
if (!allowAutoPaste) return;
if (!focus || !text.trim()) return;
try {
@@ -70,41 +72,23 @@ export function DictateWindow() {
sessionRef.current = session;
useEffect(() => {
let disposed = false;
const unlistens: UnlistenFn[] = [];
const registrations = [
const unlistens: Promise<UnlistenFn>[] = [];
unlistens.push(
listen<{ focus: FocusSnapshot | null }>('dictate:start', (event) => {
sessionRef.current.startRecording(event.payload?.focus ?? null);
focusRef.current = event.payload?.focus ?? null;
sessionRef.current.startRecording();
}),
);
unlistens.push(
listen('dictate:stop', () => {
// Forward stops that arrive while getUserMedia is still resolving.
sessionRef.current.stopRecording();
if (sessionRef.current.isRecording) sessionRef.current.stopRecording();
}),
listen<boolean>('dictate:warm', (event) => {
setMicWarm(Boolean(event.payload));
}),
];
Promise.all(registrations)
.then((registered) => {
if (disposed) {
for (const unlisten of registered) unlisten();
return;
}
unlistens.push(...registered);
emit('dictate:warm-request').catch(() => {});
})
.catch((err) => console.warn('[dictate] event listener registration failed:', err));
);
return () => {
disposed = true;
for (const unlisten of unlistens) unlisten();
for (const p of unlistens) p.then((fn) => fn()).catch(() => {});
};
}, []);
useEffect(() => {
if (micWarm) void session.prewarm();
else session.releaseWarm();
}, [micWarm, session.prewarm, session.releaseWarm]);
// --- Agent-speak cycle ---------------------------------------------------
const [speaking, setSpeaking] = useState<{
@@ -5,7 +5,7 @@ import { Button } from '@/components/ui/button';
import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card';
import { Progress } from '@/components/ui/progress';
import { apiClient } from '@/lib/api/client';
import type { CudaDownloadProgress, RocmDownloadProgress } from '@/lib/api/types';
import type { CudaDownloadProgress } from '@/lib/api/types';
import { useServerHealth } from '@/lib/hooks/useServer';
import { usePlatform } from '@/platform/PlatformContext';
import { useServerStore } from '@/stores/serverStore';
@@ -21,9 +21,6 @@ export function GpuAcceleration() {
const [restartPhase, setRestartPhase] = useState<RestartPhase>('idle');
const [error, setError] = useState<string | null>(null);
const [downloadProgress, setDownloadProgress] = useState<CudaDownloadProgress | null>(null);
const [rocmDownloadProgress, setRocmDownloadProgress] = useState<RocmDownloadProgress | null>(
null,
);
const healthPollRef = useRef<ReturnType<typeof setInterval> | null>(null);
// Query CUDA backend status
@@ -39,26 +36,10 @@ export function GpuAcceleration() {
enabled: !!health, // Only fetch when backend is reachable
});
// Query ROCm backend status
const {
data: rocmStatus,
isLoading: _rocmStatusLoading,
refetch: refetchRocmStatus,
} = useQuery({
queryKey: ['rocm-status', serverUrl],
queryFn: () => apiClient.getRocmStatus(),
refetchInterval: (query) => (query.state.status === 'pending' ? false : 10000),
retry: 1,
enabled: !!health, // Only fetch when backend is reachable
});
// Derived state
const isCurrentlyCuda = health?.backend_variant === 'cuda';
const isCurrentlyRocm = health?.backend_variant === 'rocm';
const cudaAvailable = cudaStatus?.available ?? false;
const cudaDownloading = cudaStatus?.downloading ?? false;
const rocmAvailable = rocmStatus?.available ?? false;
const rocmDownloading = rocmStatus?.downloading ?? false;
// Clean up health poll on unmount
useEffect(() => {
@@ -70,7 +51,7 @@ export function GpuAcceleration() {
};
}, []);
// SSE progress tracking during CUDA download
// SSE progress tracking during download
useEffect(() => {
if (!cudaDownloading || !serverUrl) {
return;
@@ -107,43 +88,6 @@ export function GpuAcceleration() {
};
}, [cudaDownloading, serverUrl, refetchCudaStatus]);
// SSE progress tracking during ROCm download
useEffect(() => {
if (!rocmDownloading || !serverUrl) {
return;
}
const eventSource = new EventSource(`${serverUrl}/backend/rocm-progress`);
eventSource.onmessage = (event) => {
try {
const data = JSON.parse(event.data) as RocmDownloadProgress;
setRocmDownloadProgress(data);
if (data.status === 'complete') {
eventSource.close();
setRocmDownloadProgress(null);
refetchRocmStatus();
} else if (data.status === 'error') {
eventSource.close();
setError(data.error || 'Download failed');
setRocmDownloadProgress(null);
refetchRocmStatus();
}
} catch (e) {
console.error('Error parsing ROCm progress event:', e);
}
};
eventSource.onerror = () => {
eventSource.close();
};
return () => {
eventSource.close();
};
}, [rocmDownloading, serverUrl, refetchRocmStatus]);
// Start aggressive health polling during restart
const startHealthPolling = useCallback(() => {
if (healthPollRef.current) return;
@@ -169,7 +113,7 @@ export function GpuAcceleration() {
}, 1000);
}, [queryClient]);
const handleDownloadCuda = async () => {
const handleDownload = async () => {
setError(null);
try {
await apiClient.downloadCudaBackend();
@@ -184,21 +128,6 @@ export function GpuAcceleration() {
}
};
const handleDownloadRocm = async () => {
setError(null);
try {
await apiClient.downloadRocmBackend();
refetchRocmStatus();
} catch (e: unknown) {
const msg = e instanceof Error ? e.message : 'Failed to start download';
if (msg.includes('already downloaded')) {
refetchRocmStatus();
} else {
setError(msg);
}
}
};
const handleRestart = async () => {
setError(null);
setRestartPhase('stopping');
@@ -225,17 +154,18 @@ export function GpuAcceleration() {
}
};
const handleSwitchToCpuFromCuda = async () => {
const handleSwitchToCpu = async () => {
// To switch to CPU: delete the CUDA binary, then restart.
// start_server always prefers CUDA if present, so we must remove it first.
setError(null);
setRestartPhase('stopping');
try {
// Tell Rust launcher to skip GPU binary detection on next start.
// We cannot delete an active .exe on Windows, so we override instead.
await platform.lifecycle.setBackendOverride('cpu');
await apiClient.deleteCudaBackend();
setRestartPhase('waiting');
startHealthPolling();
await platform.lifecycle.restartServer();
// Invoke resolved — server is likely ready
if (healthPollRef.current) {
clearInterval(healthPollRef.current);
healthPollRef.current = null;
@@ -254,36 +184,7 @@ export function GpuAcceleration() {
}
};
const handleSwitchToCpuFromRocm = async () => {
setError(null);
setRestartPhase('stopping');
try {
// Tell Rust launcher to skip GPU binary detection on next start.
// We cannot delete an active .exe on Windows, so we override instead.
await platform.lifecycle.setBackendOverride('cpu');
setRestartPhase('waiting');
startHealthPolling();
await platform.lifecycle.restartServer();
if (healthPollRef.current) {
clearInterval(healthPollRef.current);
healthPollRef.current = null;
}
setRestartPhase('ready');
queryClient.invalidateQueries();
setTimeout(() => setRestartPhase('idle'), 2000);
} catch (e: unknown) {
setRestartPhase('idle');
if (healthPollRef.current) {
clearInterval(healthPollRef.current);
healthPollRef.current = null;
}
setError(e instanceof Error ? e.message : 'Failed to switch to CPU');
refetchRocmStatus();
}
};
const handleDeleteCuda = async () => {
const handleDelete = async () => {
setError(null);
try {
await apiClient.deleteCudaBackend();
@@ -293,16 +194,6 @@ export function GpuAcceleration() {
}
};
const handleDeleteRocm = async () => {
setError(null);
try {
await apiClient.deleteRocmBackend();
refetchRocmStatus();
} catch (e: unknown) {
setError(e instanceof Error ? e.message : 'Failed to delete ROCm backend');
}
};
const formatBytes = (bytes: number): string => {
if (bytes === 0) return '0 B';
const k = 1024;
@@ -314,7 +205,7 @@ export function GpuAcceleration() {
// Don't render until health data is available
if (!health) return null;
// If the system already has native GPU (MPS, ROCm active, etc.), only show info - no download needed
// If the system already has native GPU (MPS, etc.), only show info - no CUDA needed
const hasNativeGpu =
health.gpu_available &&
!isCurrentlyCuda &&
@@ -350,6 +241,8 @@ export function GpuAcceleration() {
)}
</div>
{/* Native GPU detected - no CUDA download needed */}
{/* Currently running CUDA - show switch back to CPU */}
{isCurrentlyCuda && platform.metadata.isTauri && (
<>
@@ -368,12 +261,7 @@ export function GpuAcceleration() {
Running with CUDA GPU acceleration. Switch back to CPU if needed (you can
re-download later).
</p>
<Button
onClick={handleSwitchToCpuFromCuda}
variant="outline"
className="w-full"
size="sm"
>
<Button onClick={handleSwitchToCpu} variant="outline" className="w-full" size="sm">
<RotateCw className="h-4 w-4 mr-2" />
Switch to CPU Backend
</Button>
@@ -388,207 +276,39 @@ export function GpuAcceleration() {
</>
)}
{/* Currently running ROCm - show switch back to CPU */}
{isCurrentlyRocm && platform.metadata.isTauri && (
{/* CUDA download/manage section - show when no native GPU and not currently running CUDA */}
{!hasNativeGpu && !isCurrentlyCuda && (
<>
{restartPhase !== 'idle' ? (
<div className="flex items-center gap-2 p-3 rounded-lg bg-primary/5 border">
<Loader2 className="h-4 w-4 animate-spin" />
<span className="text-sm">
{restartPhase === 'stopping' && 'Stopping server...'}
{restartPhase === 'waiting' && 'Restarting server...'}
{restartPhase === 'ready' && 'Server restarted successfully!'}
</span>
</div>
) : (
<div className="space-y-3">
<p className="text-sm text-muted-foreground">
Running with ROCm GPU acceleration for AMD. Switch back to CPU if needed (you can
re-download later).
</p>
<Button
onClick={handleSwitchToCpuFromRocm}
variant="outline"
className="w-full"
size="sm"
>
<RotateCw className="h-4 w-4 mr-2" />
Switch to CPU Backend
</Button>
</div>
)}
{error && (
<div className="flex items-center gap-2 text-sm text-destructive">
<AlertCircle className="h-4 w-4 shrink-0" />
<span>{error}</span>
</div>
)}
</>
)}
{/* Backend download/manage sections - show when no native GPU and not currently running GPU */}
{!hasNativeGpu && !isCurrentlyCuda && !isCurrentlyRocm && (
<>
{/* CUDA Section */}
<div className="space-y-4">
<div className="text-sm font-medium">NVIDIA (CUDA)</div>
{/* CUDA Download progress */}
{cudaDownloading && downloadProgress && (
<div className="space-y-2">
<div className="flex items-center justify-between text-sm">
<div className="flex items-center gap-2">
<Loader2 className="h-4 w-4 animate-spin" />
<span>
{downloadProgress.filename ||
(cudaAvailable
? 'Updating CUDA backend...'
: 'Downloading CUDA backend...')}
</span>
</div>
{downloadProgress.total > 0 && (
<span className="text-muted-foreground">
{downloadProgress.progress.toFixed(1)}%
</span>
)}
{/* Download progress (manual download or auto-update) */}
{cudaDownloading && downloadProgress && (
<div className="space-y-2">
<div className="flex items-center justify-between text-sm">
<div className="flex items-center gap-2">
<Loader2 className="h-4 w-4 animate-spin" />
<span>
{downloadProgress.filename ||
(cudaAvailable
? 'Updating CUDA backend...'
: 'Downloading CUDA backend...')}
</span>
</div>
{downloadProgress.total > 0 && (
<>
<Progress value={downloadProgress.progress} className="h-2" />
<div className="text-xs text-muted-foreground">
{formatBytes(downloadProgress.current)} /{' '}
{formatBytes(downloadProgress.total)}
</div>
</>
<span className="text-muted-foreground">
{downloadProgress.progress.toFixed(1)}%
</span>
)}
</div>
)}
{/* CUDA Actions */}
{restartPhase === 'idle' && !cudaDownloading && (
<div className="space-y-2">
{!cudaAvailable && (
<div className="space-y-3">
<p className="text-sm text-muted-foreground">
Download the CUDA backend (~2.4 GB) for NVIDIA GPU acceleration. Requires an
NVIDIA GPU with CUDA support.
</p>
<Button onClick={handleDownloadCuda} className="w-full" size="sm">
<Download className="h-4 w-4 mr-2" />
Download CUDA Backend
</Button>
{downloadProgress.total > 0 && (
<>
<Progress value={downloadProgress.progress} className="h-2" />
<div className="text-xs text-muted-foreground">
{formatBytes(downloadProgress.current)} /{' '}
{formatBytes(downloadProgress.total)}
</div>
)}
{cudaAvailable && platform.metadata.isTauri && (
<div className="space-y-3">
<p className="text-sm text-muted-foreground">
CUDA backend is downloaded and ready. Restart the server to enable GPU
acceleration.
</p>
<Button onClick={handleRestart} className="w-full" size="sm">
<RotateCw className="h-4 w-4 mr-2" />
Switch to CUDA Backend
</Button>
</div>
)}
{cudaAvailable && (
<Button
onClick={handleDeleteCuda}
variant="ghost"
className="w-full text-muted-foreground hover:text-destructive"
size="sm"
>
<Trash2 className="h-4 w-4 mr-2" />
Remove CUDA Backend
</Button>
)}
</div>
)}
</div>
{/* Divider */}
<div className="border-t" />
{/* ROCm Section */}
<div className="space-y-4">
<div className="text-sm font-medium">AMD (ROCm)</div>
{/* ROCm Download progress */}
{rocmDownloading && rocmDownloadProgress && (
<div className="space-y-2">
<div className="flex items-center justify-between text-sm">
<div className="flex items-center gap-2">
<Loader2 className="h-4 w-4 animate-spin" />
<span>
{rocmDownloadProgress.filename ||
(rocmAvailable
? 'Updating ROCm backend...'
: 'Downloading ROCm backend...')}
</span>
</div>
{rocmDownloadProgress.total > 0 && (
<span className="text-muted-foreground">
{rocmDownloadProgress.progress.toFixed(1)}%
</span>
)}
</div>
{rocmDownloadProgress.total > 0 && (
<>
<Progress value={rocmDownloadProgress.progress} className="h-2" />
<div className="text-xs text-muted-foreground">
{formatBytes(rocmDownloadProgress.current)} /{' '}
{formatBytes(rocmDownloadProgress.total)}
</div>
</>
)}
</div>
)}
{/* ROCm Actions */}
{restartPhase === 'idle' && !rocmDownloading && (
<div className="space-y-2">
{!rocmAvailable && (
<div className="space-y-3">
<p className="text-sm text-muted-foreground">
Download the ROCm backend (~2-3 GB) for AMD GPU acceleration. Requires an
AMD Radeon GPU with ROCm support.
</p>
<Button onClick={handleDownloadRocm} className="w-full" size="sm">
<Download className="h-4 w-4 mr-2" />
Download AMD ROCm Backend
</Button>
</div>
)}
{rocmAvailable && platform.metadata.isTauri && (
<div className="space-y-3">
<p className="text-sm text-muted-foreground">
ROCm backend is downloaded and ready. Restart the server to enable AMD GPU
acceleration.
</p>
<Button onClick={handleRestart} className="w-full" size="sm">
<RotateCw className="h-4 w-4 mr-2" />
Switch to ROCm Backend
</Button>
</div>
)}
{rocmAvailable && (
<Button
onClick={handleDeleteRocm}
variant="ghost"
className="w-full text-muted-foreground hover:text-destructive"
size="sm"
>
<Trash2 className="h-4 w-4 mr-2" />
Remove ROCm Backend
</Button>
)}
</div>
)}
</div>
</>
)}
</div>
)}
{/* Restart in progress */}
{restartPhase !== 'idle' && (
@@ -609,6 +329,52 @@ export function GpuAcceleration() {
<span>{error}</span>
</div>
)}
{/* Actions */}
{restartPhase === 'idle' && !cudaDownloading && (
<div className="space-y-2">
{/* Not downloaded yet - show download button */}
{!cudaAvailable && (
<div className="space-y-3">
<p className="text-sm text-muted-foreground">
Download the CUDA backend (~2.4 GB) for NVIDIA GPU acceleration. Requires an
NVIDIA GPU with CUDA support.
</p>
<Button onClick={handleDownload} className="w-full" size="sm">
<Download className="h-4 w-4 mr-2" />
Download CUDA Backend
</Button>
</div>
)}
{/* Downloaded but not active - show switch button */}
{cudaAvailable && platform.metadata.isTauri && (
<div className="space-y-3">
<p className="text-sm text-muted-foreground">
CUDA backend is downloaded and ready. Restart the server to enable GPU
acceleration.
</p>
<Button onClick={handleRestart} className="w-full" size="sm">
<RotateCw className="h-4 w-4 mr-2" />
Switch to CUDA Backend
</Button>
</div>
)}
{/* Delete option when downloaded (and not active) */}
{cudaAvailable && (
<Button
onClick={handleDelete}
variant="ghost"
className="w-full text-muted-foreground "
size="sm"
>
<Trash2 className="h-4 w-4 mr-2" />
Remove CUDA Backend
</Button>
)}
</div>
)}
</>
)}
</CardContent>
@@ -138,7 +138,6 @@ export function CapturesPage() {
const allowAutoPaste = settings?.allow_auto_paste ?? true;
const defaultVoiceId = settings?.default_playback_voice_id ?? null;
const hotkeyEnabled = settings?.hotkey_enabled ?? false;
const keepMicWarm = settings?.keep_mic_warm ?? false;
const pushToTalkKeys = settings?.chord_push_to_talk_keys ?? defaultChordKeys('push');
const toggleToTalkKeys = settings?.chord_toggle_to_talk_keys ?? defaultChordKeys('toggle');
@@ -222,22 +221,6 @@ export function CapturesPage() {
<InputMonitoringNotice enabled={hotkeyEnabled} />
</div>
<SettingRow
title={t('settings.captures.dictation.keepMicWarm.title')}
description={t('settings.captures.dictation.keepMicWarm.description')}
htmlFor="keepMicWarm"
action={
<Toggle
id="keepMicWarm"
checked={keepMicWarm}
disabled={!hotkeyEnabled}
onCheckedChange={(v) => {
update({ keep_mic_warm: v });
}}
/>
}
/>
<SettingRow
title={t('settings.captures.dictation.pushToTalk.title')}
description={t('settings.captures.dictation.pushToTalk.description')}
+99 -316
View File
@@ -5,7 +5,7 @@ import { useTranslation } from 'react-i18next';
import { Button } from '@/components/ui/button';
import { Progress } from '@/components/ui/progress';
import { apiClient } from '@/lib/api/client';
import type { CudaDownloadProgress, RocmDownloadProgress, HealthResponse } from '@/lib/api/types';
import type { CudaDownloadProgress, HealthResponse } from '@/lib/api/types';
import { useServerHealth } from '@/lib/hooks/useServer';
import { usePlatform } from '@/platform/PlatformContext';
import { useServerStore } from '@/stores/serverStore';
@@ -50,10 +50,7 @@ function GpuInfoCard({ health }: { health: HealthResponse }) {
: null;
const gpuBackend = hasGpu ? health.gpu_type!.replace(/\s*\(.+\)$/, '') : null;
const isApple = gpuBackend === 'MPS' || gpuBackend === 'Metal';
const showBackendVariant =
health.backend_variant &&
health.backend_variant !== 'cpu' &&
health.backend_variant.toLowerCase() !== gpuBackend?.toLowerCase();
const showBackendVariant = health.backend_variant && health.backend_variant !== 'cpu';
return (
<div className="rounded-lg border border-border/60 p-4">
@@ -118,14 +115,10 @@ export function GpuPage() {
const [restartPhase, setRestartPhase] = useState<RestartPhase>('idle');
const [error, setError] = useState<string | null>(null);
const [cudaStreaming, setCudaStreaming] = useState(false);
const [rocmStreaming, setRocmStreaming] = useState(false);
const [downloadProgress, setDownloadProgress] = useState<CudaDownloadProgress | null>(null);
const [rocmDownloadProgress, setRocmDownloadProgress] = useState<RocmDownloadProgress | null>(
null,
);
const healthPollRef = useRef<ReturnType<typeof setInterval> | null>(null);
// Hold the latest `t` in a ref so the CUDA progress SSE effect below doesn't
// tear down and reconnect the EventSource every time the language changes.
const tRef = useRef(t);
useEffect(() => {
tRef.current = t;
@@ -143,27 +136,9 @@ export function GpuPage() {
enabled: !!health,
});
const {
data: rocmStatus,
isLoading: _rocmStatusLoading,
refetch: refetchRocmStatus,
} = useQuery({
queryKey: ['rocm-status', serverUrl],
queryFn: () => apiClient.getRocmStatus(),
refetchInterval: (query) => (query.state.status === 'pending' ? false : 10000),
retry: 1,
enabled: !!health,
});
const isCurrentlyCuda = health?.backend_variant === 'cuda';
const isCurrentlyRocm = health?.backend_variant === 'rocm';
const cudaAvailable = cudaStatus?.available ?? false;
const cudaDownloading = cudaStatus?.downloading ?? false;
const rocmAvailable = rocmStatus?.available ?? false;
const rocmDownloading = rocmStatus?.downloading ?? false;
// The ROCm backend only applies to AMD GPUs on Windows. Show the section when
// the backend detects applicable hardware, or it is already downloaded/active.
const supportsRocm = (health?.supports_rocm ?? false) || rocmAvailable || isCurrentlyRocm;
useEffect(() => {
return () => {
@@ -175,7 +150,7 @@ export function GpuPage() {
}, []);
useEffect(() => {
if ((!cudaDownloading && !cudaStreaming) || !serverUrl) return;
if (!cudaDownloading || !serverUrl) return;
const eventSource = new EventSource(`${serverUrl}/backend/cuda-progress`);
@@ -187,13 +162,11 @@ export function GpuPage() {
if (data.status === 'complete') {
eventSource.close();
setDownloadProgress(null);
setCudaStreaming(false);
refetchCudaStatus();
} else if (data.status === 'error') {
eventSource.close();
setError(data.error || tRef.current('settings.gpu.errors.downloadFailed'));
setDownloadProgress(null);
setCudaStreaming(false);
refetchCudaStatus();
}
} catch (e) {
@@ -203,50 +176,12 @@ export function GpuPage() {
eventSource.onerror = () => {
eventSource.close();
setCudaStreaming(false);
};
return () => {
eventSource.close();
};
}, [cudaDownloading, cudaStreaming, serverUrl, refetchCudaStatus]);
useEffect(() => {
if ((!rocmDownloading && !rocmStreaming) || !serverUrl) return;
const eventSource = new EventSource(`${serverUrl}/backend/rocm-progress`);
eventSource.onmessage = (event) => {
try {
const data = JSON.parse(event.data) as RocmDownloadProgress;
setRocmDownloadProgress(data);
if (data.status === 'complete') {
eventSource.close();
setRocmDownloadProgress(null);
setRocmStreaming(false);
refetchRocmStatus();
} else if (data.status === 'error') {
eventSource.close();
setError(data.error || tRef.current('settings.gpu.errors.downloadFailed'));
setRocmDownloadProgress(null);
setRocmStreaming(false);
refetchRocmStatus();
}
} catch (e) {
console.error('Error parsing ROCm progress event:', e);
}
};
eventSource.onerror = () => {
eventSource.close();
setRocmStreaming(false);
};
return () => {
eventSource.close();
};
}, [rocmDownloading, rocmStreaming, serverUrl, refetchRocmStatus]);
}, [cudaDownloading, serverUrl, refetchCudaStatus]);
const clearHealthPolling = useCallback(() => {
if (healthPollRef.current) {
@@ -289,11 +224,10 @@ export function GpuPage() {
[platform, startHealthPolling, clearHealthPolling],
);
const handleDownloadCuda = async () => {
const handleDownload = async () => {
setError(null);
try {
await apiClient.downloadCudaBackend();
setCudaStreaming(true);
refetchCudaStatus();
} catch (e: unknown) {
const msg = e instanceof Error ? e.message : t('settings.gpu.errors.downloadStart');
@@ -305,64 +239,28 @@ export function GpuPage() {
}
};
const handleDownloadRocm = async () => {
const handleRestart = async () => {
setError(null);
try {
await apiClient.downloadRocmBackend();
setRocmStreaming(true);
refetchRocmStatus();
await restartServerWithPolling(t('settings.gpu.errors.restartFailed'));
} catch (e: unknown) {
const msg = e instanceof Error ? e.message : t('settings.gpu.errors.downloadStart');
if (msg.includes('already downloaded')) {
refetchRocmStatus();
} else {
setError(msg);
}
setError(e instanceof Error ? e.message : t('settings.gpu.errors.restartFailed'));
}
};
const handleSwitchToCpu = async () => {
setError(null);
setRestartPhase('stopping');
try {
await platform.lifecycle.setBackendOverride('cpu');
await apiClient.deleteCudaBackend();
await restartServerWithPolling(t('settings.gpu.errors.switchCpu'));
} catch (e: unknown) {
setRestartPhase('idle');
setError(e instanceof Error ? e.message : t('settings.gpu.errors.switchCpu'));
refetchCudaStatus();
refetchRocmStatus();
}
};
const handleSwitchToCuda = async () => {
setError(null);
setRestartPhase('stopping');
try {
await platform.lifecycle.setBackendOverride('cuda');
await restartServerWithPolling(t('settings.gpu.errors.restartFailed'));
} catch (e: unknown) {
setRestartPhase('idle');
setError(e instanceof Error ? e.message : t('settings.gpu.errors.restartFailed'));
refetchCudaStatus();
}
};
const handleSwitchToRocm = async () => {
setError(null);
setRestartPhase('stopping');
try {
await platform.lifecycle.setBackendOverride('rocm');
await restartServerWithPolling(t('settings.gpu.errors.restartFailed'));
} catch (e: unknown) {
setRestartPhase('idle');
setError(e instanceof Error ? e.message : t('settings.gpu.errors.restartFailed'));
refetchRocmStatus();
}
};
const handleDeleteCuda = async () => {
const handleDelete = async () => {
setError(null);
try {
await apiClient.deleteCudaBackend();
@@ -372,16 +270,6 @@ export function GpuPage() {
}
};
const handleDeleteRocm = async () => {
setError(null);
try {
await apiClient.deleteRocmBackend();
refetchRocmStatus();
} catch (e: unknown) {
setError(e instanceof Error ? e.message : t('settings.gpu.errors.deleteRocm'));
}
};
const formatBytes = (bytes: number): string => {
if (bytes === 0) return '0 B';
const k = 1024;
@@ -395,7 +283,6 @@ export function GpuPage() {
const hasNativeGpu =
health.gpu_available &&
!isCurrentlyCuda &&
!isCurrentlyRocm &&
health.gpu_type &&
!health.gpu_type.includes('CUDA');
@@ -403,188 +290,33 @@ export function GpuPage() {
<div className="space-y-8 max-w-2xl">
<GpuInfoCard health={health} />
{!hasNativeGpu && !isCurrentlyCuda && !isCurrentlyRocm && (
<>
<SettingSection
title={t('settings.gpu.cuda.title')}
description={t('settings.gpu.cuda.description')}
>
{cudaDownloading && downloadProgress && (
<SettingRow title={t('settings.gpu.cuda.downloading')}>
<div className="space-y-1.5">
<Progress value={downloadProgress.progress} className="h-2" />
<div className="flex items-center justify-between text-xs text-muted-foreground">
<span>
{downloadProgress.filename ||
(cudaAvailable
? t('settings.gpu.cuda.updating')
: t('settings.gpu.cuda.downloadingShort'))}
</span>
<span>
{downloadProgress.total > 0
? `${formatBytes(downloadProgress.current)} / ${formatBytes(downloadProgress.total)}`
: `${downloadProgress.progress.toFixed(1)}%`}
</span>
</div>
</div>
</SettingRow>
)}
{restartPhase !== 'idle' && (
<SettingRow
title={
restartPhase === 'ready'
? t('settings.gpu.restart.ready')
: restartPhase === 'waiting'
? t('settings.gpu.restart.waiting')
: t('settings.gpu.restart.stopping')
}
action={<Loader2 className="h-4 w-4 animate-spin text-muted-foreground" />}
/>
)}
{error && (
<SettingRow title={t('common.error')}>
<div className="flex items-center gap-2 text-sm text-destructive">
<AlertCircle className="h-4 w-4 shrink-0" />
<span>{error}</span>
</div>
</SettingRow>
)}
{restartPhase === 'idle' && !cudaDownloading && (
<>
{!cudaAvailable && !isCurrentlyCuda && (
<SettingRow
title={t('settings.gpu.download.title')}
description={t('settings.gpu.download.description')}
action={
<Button onClick={handleDownloadCuda} size="sm">
<Download className="h-3.5 w-3.5 mr-1.5" />
{t('settings.gpu.download.button')}
</Button>
}
/>
)}
{cudaAvailable && !isCurrentlyCuda && platform.metadata.isTauri && (
<SettingRow
title={t('settings.gpu.switchToCuda.title')}
description={t('settings.gpu.switchToCuda.description')}
action={
<Button onClick={handleSwitchToCuda} size="sm">
<RotateCw className="h-3.5 w-3.5 mr-1.5" />
{t('settings.gpu.switchToCuda.button')}
</Button>
}
/>
)}
{cudaAvailable && !isCurrentlyCuda && (
<SettingRow
title={t('settings.gpu.remove.title')}
description={t('settings.gpu.remove.description')}
action={
<Button
onClick={handleDeleteCuda}
variant="ghost"
size="sm"
className="text-muted-foreground hover:text-destructive"
>
<Trash2 className="h-3.5 w-3.5 mr-1.5" />
{t('settings.gpu.remove.button')}
</Button>
}
/>
)}
</>
)}
</SettingSection>
{supportsRocm && (
<SettingSection
title={t('settings.gpu.rocm.title')}
description={t('settings.gpu.rocm.description')}
>
{rocmDownloading && rocmDownloadProgress && (
<SettingRow title={t('settings.gpu.rocm.downloading')}>
<div className="space-y-1.5">
<Progress value={rocmDownloadProgress.progress} className="h-2" />
<div className="flex items-center justify-between text-xs text-muted-foreground">
<span>
{rocmDownloadProgress.filename ||
(rocmAvailable
? t('settings.gpu.rocm.updating')
: t('settings.gpu.rocm.downloadingShort'))}
</span>
<span>
{rocmDownloadProgress.total > 0
? `${formatBytes(rocmDownloadProgress.current)} / ${formatBytes(rocmDownloadProgress.total)}`
: `${rocmDownloadProgress.progress.toFixed(1)}%`}
</span>
</div>
</div>
</SettingRow>
)}
{restartPhase === 'idle' && !rocmDownloading && (
<>
{!rocmAvailable && !isCurrentlyRocm && (
<SettingRow
title={t('settings.gpu.downloadRocm.title')}
description={t('settings.gpu.downloadRocm.description')}
action={
<Button onClick={handleDownloadRocm} size="sm">
<Download className="h-3.5 w-3.5 mr-1.5" />
{t('settings.gpu.downloadRocm.button')}
</Button>
}
/>
)}
{rocmAvailable && !isCurrentlyRocm && platform.metadata.isTauri && (
<SettingRow
title={t('settings.gpu.switchToRocm.title')}
description={t('settings.gpu.switchToRocm.description')}
action={
<Button onClick={handleSwitchToRocm} size="sm">
<RotateCw className="h-3.5 w-3.5 mr-1.5" />
{t('settings.gpu.switchToRocm.button')}
</Button>
}
/>
)}
{rocmAvailable && !isCurrentlyRocm && (
<SettingRow
title={t('settings.gpu.removeRocm.title')}
description={t('settings.gpu.removeRocm.description')}
action={
<Button
onClick={handleDeleteRocm}
variant="ghost"
size="sm"
className="text-muted-foreground hover:text-destructive"
>
<Trash2 className="h-3.5 w-3.5 mr-1.5" />
{t('settings.gpu.removeRocm.button')}
</Button>
}
/>
)}
</>
)}
</SettingSection>
)}
</>
)}
{(isCurrentlyCuda || isCurrentlyRocm) && platform.metadata.isTauri && (
{!hasNativeGpu && !isCurrentlyCuda && (
<SettingSection
title={isCurrentlyCuda ? t('settings.gpu.cuda.activeTitle') : t('settings.gpu.rocm.activeTitle')}
description={t('settings.gpu.activeBackend.description')}
title={t('settings.gpu.cuda.title')}
description={t('settings.gpu.cuda.description')}
>
{restartPhase !== 'idle' ? (
{cudaDownloading && downloadProgress && (
<SettingRow title={t('settings.gpu.cuda.downloading')}>
<div className="space-y-1.5">
<Progress value={downloadProgress.progress} className="h-2" />
<div className="flex items-center justify-between text-xs text-muted-foreground">
<span>
{downloadProgress.filename ||
(cudaAvailable
? t('settings.gpu.cuda.updating')
: t('settings.gpu.cuda.downloadingShort'))}
</span>
<span>
{downloadProgress.total > 0
? `${formatBytes(downloadProgress.current)} / ${formatBytes(downloadProgress.total)}`
: `${downloadProgress.progress.toFixed(1)}%`}
</span>
</div>
</div>
</SettingRow>
)}
{restartPhase !== 'idle' && (
<SettingRow
title={
restartPhase === 'ready'
@@ -595,18 +327,8 @@ export function GpuPage() {
}
action={<Loader2 className="h-4 w-4 animate-spin text-muted-foreground" />}
/>
) : (
<SettingRow
title={t('settings.gpu.switchToCpu.title')}
description={t('settings.gpu.switchToCpu.description')}
action={
<Button onClick={handleSwitchToCpu} variant="outline" size="sm">
<RotateCw className="h-3.5 w-3.5 mr-1.5" />
{t('settings.gpu.switchToCpu.button')}
</Button>
}
/>
)}
{error && (
<SettingRow title={t('common.error')}>
<div className="flex items-center gap-2 text-sm text-destructive">
@@ -615,6 +337,67 @@ export function GpuPage() {
</div>
</SettingRow>
)}
{restartPhase === 'idle' && !cudaDownloading && (
<>
{!cudaAvailable && !isCurrentlyCuda && (
<SettingRow
title={t('settings.gpu.download.title')}
description={t('settings.gpu.download.description')}
action={
<Button onClick={handleDownload} size="sm">
<Download className="h-3.5 w-3.5 mr-1.5" />
{t('settings.gpu.download.button')}
</Button>
}
/>
)}
{cudaAvailable && !isCurrentlyCuda && platform.metadata.isTauri && (
<SettingRow
title={t('settings.gpu.switchToCuda.title')}
description={t('settings.gpu.switchToCuda.description')}
action={
<Button onClick={handleRestart} size="sm">
<RotateCw className="h-3.5 w-3.5 mr-1.5" />
{t('settings.gpu.switchToCuda.button')}
</Button>
}
/>
)}
{isCurrentlyCuda && platform.metadata.isTauri && (
<SettingRow
title={t('settings.gpu.switchToCpu.title')}
description={t('settings.gpu.switchToCpu.description')}
action={
<Button onClick={handleSwitchToCpu} variant="outline" size="sm">
<RotateCw className="h-3.5 w-3.5 mr-1.5" />
{t('settings.gpu.switchToCpu.button')}
</Button>
}
/>
)}
{cudaAvailable && !isCurrentlyCuda && (
<SettingRow
title={t('settings.gpu.remove.title')}
description={t('settings.gpu.remove.description')}
action={
<Button
onClick={handleDelete}
variant="ghost"
size="sm"
className="text-muted-foreground "
>
<Trash2 className="h-3.5 w-3.5 mr-1.5" />
{t('settings.gpu.remove.button')}
</Button>
}
/>
)}
</>
)}
</SettingSection>
)}
-15
View File
@@ -2,25 +2,15 @@ import i18n from 'i18next';
import LanguageDetector from 'i18next-browser-languagedetector';
import { initReactI18next } from 'react-i18next';
import en from './locales/en/translation.json';
import es from './locales/es/translation.json';
import fr from './locales/fr/translation.json';
import it from './locales/it/translation.json';
import ja from './locales/ja/translation.json';
import ko from './locales/ko/translation.json';
import ptBR from './locales/pt-BR/translation.json';
import zhCN from './locales/zh-CN/translation.json';
import zhTW from './locales/zh-TW/translation.json';
export const SUPPORTED_LANGUAGES = [
{ code: 'en', label: 'English' },
{ code: 'es', label: 'Español' },
{ code: 'pt-BR', label: 'Português (Brasil)' },
{ code: 'ja', label: '日本語' },
{ code: 'ko', label: '한국어' },
{ code: 'zh-CN', label: '简体中文' },
{ code: 'zh-TW', label: '繁體中文' },
{ code: 'fr', label: 'Français' },
{ code: 'it', label: 'Italiano' },
] as const;
export type LanguageCode = (typeof SUPPORTED_LANGUAGES)[number]['code'];
@@ -31,14 +21,9 @@ i18n
.init({
resources: {
en: { translation: en },
es: { translation: es },
'pt-BR': { translation: ptBR },
ja: { translation: ja },
ko: { translation: ko },
'zh-CN': { translation: zhCN },
'zh-TW': { translation: zhTW },
fr: { translation: fr },
it: { translation: it },
},
fallbackLng: 'en',
supportedLngs: SUPPORTED_LANGUAGES.map((l) => l.code),
+7 -43
View File
@@ -760,13 +760,8 @@
}
},
"general": {
"docs": {
"title": "Read the Docs"
},
"discord": {
"title": "Join the Discord",
"subtitle": "Get help & share voices"
},
"docs": { "title": "Read the Docs" },
"discord": { "title": "Join the Discord", "subtitle": "Get help & share voices" },
"serverUrl": {
"title": "Server URL",
"description": "The address of your voicebox backend server.",
@@ -887,10 +882,6 @@
"title": "Global shortcut",
"description": "Hold the shortcut to record from anywhere on your machine. Release to transcribe."
},
"keepMicWarm": {
"title": "Keep microphone ready",
"description": "Hold the microphone open while dictation is enabled so the first words are never clipped. The macOS microphone indicator stays lit while it's on."
},
"pushToTalk": {
"title": "Push-to-talk shortcut",
"description": "Hold these keys anywhere on your system to record. Release to stop and transcribe.",
@@ -1100,15 +1091,11 @@
"active": "Active",
"cuda": {
"title": "CUDA Backend",
"activeTitle": "CUDA Backend Active",
"description": "NVIDIA GPU acceleration via a downloadable CUDA backend.",
"downloading": "Downloading CUDA backend…",
"downloadingShort": "Downloading…",
"updating": "Updating…"
},
"activeBackend": {
"description": "GPU acceleration is currently enabled."
},
"restart": {
"ready": "Server restarted successfully",
"waiting": "Restarting server…",
@@ -1126,9 +1113,10 @@
},
"switchToCpu": {
"title": "Switch to CPU backend",
"description": "Disable GPU acceleration. You can re-download the GPU backend later.",
"description": "Disable GPU acceleration. You can re-download CUDA later.",
"button": "Switch"
}, "remove": {
},
"remove": {
"title": "Remove CUDA backend",
"description": "Delete the downloaded CUDA binary to free disk space.",
"button": "Remove"
@@ -1138,33 +1126,9 @@
"downloadStart": "Failed to start download",
"restartFailed": "Restart failed",
"switchCpu": "Failed to switch to CPU",
"deleteCuda": "Failed to delete CUDA backend",
"deleteRocm": "Failed to delete ROCm backend"
"deleteCuda": "Failed to delete CUDA backend"
},
"footer": "Voicebox automatically detects and uses the best available GPU on your system. On Apple Silicon Macs, the MLX backend runs natively on the Neural Engine and GPU via Metal Performance Shaders (MPS), with no additional setup required. On Windows, you can download optional CUDA (NVIDIA) or ROCm (AMD) backends for hardware-accelerated inference. Intel XPU and DirectML are also supported where available through PyTorch. When no GPU is detected, Voicebox falls back to CPU — all engines still work, just slower.",
"rocm": {
"title": "AMD ROCm Backend",
"activeTitle": "ROCm Backend Active",
"description": "AMD GPU acceleration via a downloadable ROCm backend.",
"downloading": "Downloading ROCm backend…",
"downloadingShort": "Downloading…",
"updating": "Updating…"
},
"downloadRocm": {
"title": "Download AMD ROCm backend",
"description": "~2-3 GB download. Requires an AMD Radeon GPU with ROCm support.",
"button": "Download"
},
"switchToRocm": {
"title": "Switch to ROCm backend",
"description": "ROCm backend is downloaded and ready. Restart to enable.",
"button": "Restart"
},
"removeRocm": {
"title": "Remove ROCm backend",
"description": "Delete the downloaded ROCm binary to free disk space.",
"button": "Remove"
}
"footer": "Voicebox automatically detects and uses the best available GPU on your system. On Apple Silicon Macs, the MLX backend runs natively on the Neural Engine and GPU via Metal Performance Shaders (MPS), with no additional setup required. On Windows and Linux with NVIDIA GPUs, you can download an optional CUDA backend for hardware-accelerated inference. AMD ROCm, Intel XPU, and DirectML are also supported where available through PyTorch. When no GPU is detected, Voicebox falls back to CPU — all engines still work, just slower."
},
"logs": {
"title": "Server Logs",
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-18
View File
@@ -20,7 +20,6 @@ import type {
PresetVoice,
PersonalityTextResponse,
ProfileSampleResponse,
RocmStatus,
StoryCreate,
StoryDetailResponse,
StoryItemBatchUpdate,
@@ -696,23 +695,6 @@ class ApiClient {
});
}
// ROCm Backend Management
async getRocmStatus(): Promise<RocmStatus> {
return this.request<RocmStatus>('/backend/rocm-status');
}
async downloadRocmBackend(): Promise<{ message: string; progress_key: string }> {
return this.request<{ message: string; progress_key: string }>('/backend/download-rocm', {
method: 'POST',
});
}
async deleteRocmBackend(): Promise<{ message: string }> {
return this.request<{ message: string }>('/backend/rocm', {
method: 'DELETE',
});
}
// Stories
async listStories(): Promise<StoryResponse[]> {
return this.request<StoryResponse[]>('/stories');
+1 -1
View File
@@ -9,7 +9,7 @@ export type ModelStatus = {
model_name: string;
display_name: string;
downloaded: boolean;
downloading?: boolean; // True if download is in progress
downloading?: boolean; // True if download is in progress
size_mb?: number | null;
loaded?: boolean;
};
+2 -30
View File
@@ -213,10 +213,6 @@ export interface CaptureSettings {
/** Whether the global keyboard hotkey is armed. Off by default — turning
* this on triggers the macOS Input Monitoring TCC prompt. */
hotkey_enabled: boolean;
/** Hold the mic open while dictation is enabled so push-to-talk doesn't clip
* the first words. Off by default — when on, the OS mic indicator stays lit
* the whole time dictation is enabled. */
keep_mic_warm: boolean;
/** keytap key names. Defaults are platform-specific right-hand modifiers. */
chord_push_to_talk_keys: string[];
/** keytap key names. Toggle adds Space to the platform-specific PTT chord. */
@@ -273,8 +269,7 @@ export interface HealthResponse {
gpu_type?: string;
vram_used_mb?: number;
backend_type?: string;
backend_variant?: string; // "cpu", "cuda", or "rocm"
supports_rocm?: boolean; // AMD GPU on Windows — the ROCm backend is applicable
backend_variant?: string; // "cpu" or "cuda"
}
export interface CudaDownloadProgress {
@@ -291,34 +286,11 @@ export interface CudaDownloadProgress {
export interface CudaStatus {
available: boolean; // CUDA binary exists on disk
active: boolean; // Currently running the CUDA binary
binary_path: string | null;
cuda_libs_version: string | null;
download_supported: boolean; // Platform has a matching release asset
unsupported_reason: string | null;
binary_path?: string;
downloading: boolean; // Download in progress
download_progress?: CudaDownloadProgress;
}
export interface RocmDownloadProgress {
model_name: string;
current: number;
total: number;
progress: number;
filename?: string;
status: 'downloading' | 'extracting' | 'complete' | 'error';
timestamp: string;
error?: string;
}
export interface RocmStatus {
available: boolean; // ROCm binary exists on disk
active: boolean; // Currently running the ROCm binary
binary_path?: string;
rocm_libs_version?: string;
downloading: boolean; // Download in progress
download_progress?: RocmDownloadProgress;
}
export interface ModelProgress {
model_name: string;
current: number;
+139 -371
View File
@@ -4,45 +4,12 @@ import { convertToWav } from '@/lib/utils/audio';
interface UseAudioRecordingOptions {
maxDurationSeconds?: number;
// ``context`` is whatever was handed to ``startRecording`` for this take,
// threaded back untouched so callers can correlate the result with the
// recording it came from (the dictate window pairs it with the focus
// snapshot captured at chord-start).
onRecordingComplete?: (blob: Blob, duration?: number, context?: unknown) => void;
/**
* Keep the microphone ``MediaStream`` open between recordings instead of
* tearing it down on every stop. This is what removes the "first words get
* clipped" problem on push-to-talk dictation: ``getUserMedia`` on macOS can
* take several hundred ms — up to a second cold — to hand back a stream, and
* ``MediaRecorder`` only starts capturing *after* it resolves, so everything
* spoken in that window is lost. With a warm stream already open, the next
* ``startRecording`` skips ``getUserMedia`` entirely.
*
* Off by default: the voice-clone sample recorders release the device
* immediately, and the dictation session only opts in when the user enables
* the "keep microphone ready" setting. While on, the warm stream stays open —
* and the OS mic-in-use indicator stays lit — until it's explicitly released
* (dictation disabled or the setting turned off), so the trade-off is visible
* and user-controlled rather than a background mic that's always warm.
*/
keepWarm?: boolean;
onRecordingComplete?: (blob: Blob, duration?: number) => void;
}
// Audio constraints for capture. Kept identical to the previous inline value so
// this change is purely about *when* the stream is opened, not *how*.
const AUDIO_CONSTRAINTS: MediaTrackConstraints = {
echoCancellation: true,
noiseSuppression: true,
autoGainControl: true,
};
const streamHasLiveAudio = (stream: MediaStream | null): stream is MediaStream =>
!!stream && stream.getAudioTracks().some((t) => t.readyState === 'live');
export function useAudioRecording({
maxDurationSeconds,
onRecordingComplete,
keepWarm = false,
}: UseAudioRecordingOptions = {}) {
const platform = usePlatform();
const [isRecording, setIsRecording] = useState(false);
@@ -50,392 +17,195 @@ export function useAudioRecording({
const [error, setError] = useState<string | null>(null);
const mediaRecorderRef = useRef<MediaRecorder | null>(null);
const chunksRef = useRef<Blob[]>([]);
// The stream currently backing the MediaRecorder. When ``keepWarm`` is set
// this is the same object as ``warmStreamRef`` and is *not* torn down on
// stop; otherwise it's stopped as soon as the recording completes.
const streamRef = useRef<MediaStream | null>(null);
// Persistent pre-opened stream reused across recordings when ``keepWarm``.
const warmStreamRef = useRef<MediaStream | null>(null);
const timerRef = useRef<number | null>(null);
const startTimeRef = useRef<number | null>(null);
const cancelledRef = useRef<boolean>(false);
// Mirror of ``isRecording`` for reads inside callbacks that would otherwise
// close over a stale render.
const isRecordingRef = useRef(false);
// A ``getUserMedia`` call in flight, shared so concurrent acquirers (prewarm
// plus an immediate chord) coalesce onto one stream instead of each opening —
// and orphaning — their own.
const acquiringRef = useRef<Promise<MediaStream> | null>(null);
// True from ``startRecording`` entry until the recorder is actually running
// (or has failed), so a stop that arrives mid-acquisition can be deferred.
const startingRef = useRef(false);
// True from MediaRecorder.stop() until onstop has snapshotted the take's
// shared refs. React state and MediaRecorder.state both flip before onstop,
// so without this gate a rapid next chord can clear chunks/duration/cancel
// state out from under the recorder that is still finalising.
const finishingRef = useRef(false);
const pendingStopRef = useRef(false);
// Bumped per recording so a stale recorder's ``onstop`` can tell it's no
// longer the active one before it touches the shared stream refs.
const recordingCounterRef = useRef(0);
// Bumped whenever the warm stream is released/aborted so a ``getUserMedia``
// still in flight can tell its result is stale and stop it instead of
// adopting a live mic after disable/unmount.
const acquireGenRef = useRef(0);
// Set when a release is requested mid-recording; the onstop path performs the
// deferred release once capture finishes rather than yanking the device now.
const releaseAfterStopRef = useRef(false);
// Keeps the ref in lockstep with the state so the synchronous stop path reads
// a fresh value without waiting for a rerender.
const setRecording = useCallback((next: boolean) => {
isRecordingRef.current = next;
setIsRecording(next);
}, []);
const startRecording = useCallback(async () => {
try {
setError(null);
chunksRef.current = [];
cancelledRef.current = false;
setDuration(0);
const releaseWarmStream = useCallback(() => {
// Invalidate any getUserMedia still in flight so its stream is stopped on
// resolve rather than adopted as the warm stream.
acquireGenRef.current += 1;
// Don't tear the device out from under an active/starting recording — the
// warm stream is the one backing it; defer to the onstop path instead.
if (isRecordingRef.current || startingRef.current) {
releaseAfterStopRef.current = true;
return;
}
warmStreamRef.current?.getTracks().forEach((track) => {
track.stop();
});
warmStreamRef.current = null;
}, []);
// Assert that getUserMedia is reachable, mirroring the previous inline guard
// (Tauri webviews occasionally expose ``navigator.mediaDevices`` a beat late).
const assertMediaDevices = useCallback(async () => {
if (typeof navigator === 'undefined') {
throw new Error('Navigator API is not available. This might be a Tauri configuration issue.');
}
if (!navigator.mediaDevices || !navigator.mediaDevices.getUserMedia) {
await new Promise((resolve) => setTimeout(resolve, 100));
if (!navigator.mediaDevices || !navigator.mediaDevices.getUserMedia) {
throw new Error(
platform.metadata.isTauri
? 'Microphone access is not available. Please ensure:\n1. The app has microphone permissions in System Settings (macOS: System Settings > Privacy & Security > Microphone)\n2. You restart the app after granting permissions\n3. You are using Tauri v2 with a webview that supports getUserMedia'
: 'Microphone access is not available. Please ensure you are using a secure context (HTTPS or localhost) and that your browser has microphone permissions enabled.',
);
// Check if getUserMedia is available
// In Tauri, navigator.mediaDevices might not be available immediately
if (typeof navigator === 'undefined') {
const errorMsg =
'Navigator API is not available. This might be a Tauri configuration issue.';
setError(errorMsg);
throw new Error(errorMsg);
}
}
}, [platform.metadata.isTauri]);
// Return a live capture stream, reusing the warm one when available so the
// hot path (chord-down → record) never waits on getUserMedia.
const acquireStream = useCallback(async (): Promise<MediaStream> => {
// Captured separately so it stays typed as the full stream after the live
// check narrows ``warmStreamRef.current`` itself.
const existing = warmStreamRef.current;
if (streamHasLiveAudio(warmStreamRef.current)) {
return warmStreamRef.current;
}
// Coalesce concurrent acquirers onto one getUserMedia call so prewarm and
// an immediate chord can't open two streams.
if (acquiringRef.current) return acquiringRef.current;
// A dead warm stream (device unplugged / tracks ended) — drop it and reopen.
if (existing) {
existing.getTracks().forEach((track) => {
track.stop();
});
warmStreamRef.current = null;
}
const gen = acquireGenRef.current;
const acquisition = (async () => {
await assertMediaDevices();
if (!navigator.mediaDevices || !navigator.mediaDevices.getUserMedia) {
// Try waiting a bit for Tauri webview to initialize
await new Promise((resolve) => setTimeout(resolve, 100));
if (!navigator.mediaDevices || !navigator.mediaDevices.getUserMedia) {
console.error('MediaDevices check:', {
hasNavigator: typeof navigator !== 'undefined',
hasMediaDevices: !!navigator?.mediaDevices,
hasGetUserMedia: !!navigator?.mediaDevices?.getUserMedia,
isTauri: platform.metadata.isTauri,
});
const errorMsg = platform.metadata.isTauri
? 'Microphone access is not available. Please ensure:\n1. The app has microphone permissions in System Settings (macOS: System Settings > Privacy & Security > Microphone)\n2. You restart the app after granting permissions\n3. You are using Tauri v2 with a webview that supports getUserMedia'
: 'Microphone access is not available. Please ensure you are using a secure context (HTTPS or localhost) and that your browser has microphone permissions enabled.';
setError(errorMsg);
throw new Error(errorMsg);
}
}
// Request microphone access
const stream = await navigator.mediaDevices.getUserMedia({
audio: AUDIO_CONSTRAINTS,
audio: {
echoCancellation: true,
noiseSuppression: true,
autoGainControl: true,
},
});
// Released / disabled / unmounted while acquiring — this stream is stale,
// so stop it instead of leaving a live mic open, and abort the caller.
if (gen !== acquireGenRef.current) {
stream.getTracks().forEach((track) => {
streamRef.current = stream;
// Create MediaRecorder with preferred MIME type
const options: MediaRecorderOptions = {
mimeType: 'audio/webm;codecs=opus',
};
// Fallback to default if webm not supported
if (!MediaRecorder.isTypeSupported(options.mimeType!)) {
delete options.mimeType;
}
const mediaRecorder = new MediaRecorder(stream, options);
mediaRecorderRef.current = mediaRecorder;
mediaRecorder.ondataavailable = (event) => {
if (event.data.size > 0) {
chunksRef.current.push(event.data);
}
};
mediaRecorder.onstop = async () => {
// Snapshot the cancellation flag and recorded duration immediately —
// cancelRecording() clears chunks and sets cancelledRef synchronously
// before this async handler runs, so we must check it first.
const wasCancelled = cancelledRef.current;
const recordedDuration = startTimeRef.current
? (Date.now() - startTimeRef.current) / 1000
: undefined;
const webmBlob = new Blob(chunksRef.current, { type: 'audio/webm' });
// Stop all tracks now that we have the data
streamRef.current?.getTracks().forEach((track) => {
track.stop();
});
throw new Error('microphone acquisition aborted');
}
if (keepWarm) warmStreamRef.current = stream;
return stream;
})();
acquiringRef.current = acquisition;
try {
return await acquisition;
} finally {
if (acquiringRef.current === acquisition) acquiringRef.current = null;
}
}, [assertMediaDevices, keepWarm]);
streamRef.current = null;
/**
* Open the microphone ahead of the first recording so the initial dictation
* doesn't clip. No-op unless ``keepWarm`` is set. Safe to call repeatedly and
* safe to fail (e.g. permission not yet granted) — ``startRecording`` still
* surfaces a real error if capture is genuinely unavailable.
*/
const prewarm = useCallback(async () => {
if (!keepWarm) return;
try {
await acquireStream();
} catch {
// Permission missing / device busy / aborted — recording will report a
// real error if capture is genuinely unavailable.
}
}, [keepWarm, acquireStream]);
// Don't fire completion callback if the recording was cancelled
if (wasCancelled) return;
const startRecording = useCallback(
async (context?: unknown) => {
// A second chord can arrive while the first one is still waiting on
// getUserMedia. Never create overlapping MediaRecorders on the same
// coalesced stream; the original take will honor any deferred stop.
if (
startingRef.current ||
finishingRef.current ||
mediaRecorderRef.current?.state === 'recording'
)
return;
startingRef.current = true;
pendingStopRef.current = false;
// A new recording supersedes any release deferred from a prior take.
releaseAfterStopRef.current = false;
const recordingId = ++recordingCounterRef.current;
try {
setError(null);
chunksRef.current = [];
cancelledRef.current = false;
setDuration(0);
// Reuse the warm stream when present (instant); otherwise open one now.
const stream = await acquireStream();
streamRef.current = stream;
// Create MediaRecorder with preferred MIME type
const options: MediaRecorderOptions = {
mimeType: 'audio/webm;codecs=opus',
};
// Fallback to default if webm not supported
if (!MediaRecorder.isTypeSupported(options.mimeType!)) {
delete options.mimeType;
// Convert to WAV format to avoid needing ffmpeg on backend
try {
const wavBlob = await convertToWav(webmBlob);
onRecordingComplete?.(wavBlob, recordedDuration);
} catch (err) {
console.error('Error converting audio to WAV:', err);
// Fallback to original blob if conversion fails
onRecordingComplete?.(webmBlob, recordedDuration);
}
};
const mediaRecorder = new MediaRecorder(stream, options);
mediaRecorderRef.current = mediaRecorder;
mediaRecorder.onerror = (event) => {
setError('Recording error occurred');
console.error('MediaRecorder error:', event);
};
mediaRecorder.ondataavailable = (event) => {
if (event.data.size > 0) {
chunksRef.current.push(event.data);
}
};
// WebKit's MediaRecorder drops the WebM EBML header from chunks when
// started with a timeslice, so concatenated blobs fail to parse in
// both AudioContext and ffmpeg. Starting with no timeslice produces
// exactly one dataavailable on stop() with a valid container.
mediaRecorder.start();
setIsRecording(true);
startTimeRef.current = Date.now();
mediaRecorder.onstop = async () => {
// Whether this recorder is still the active one. A stale onstop (an
// older recorder stopping after a newer startRecording) must not touch
// the shared stream refs.
const isCurrent = recordingCounterRef.current === recordingId;
// Snapshot the cancellation flag and recorded duration immediately —
// cancelRecording() clears chunks and sets cancelledRef synchronously
// before this async handler runs, so we must check it first.
const wasCancelled = cancelledRef.current;
const recordedDuration = startTimeRef.current
? (Date.now() - startTimeRef.current) / 1000
: undefined;
// Start timer
timerRef.current = window.setInterval(() => {
if (startTimeRef.current) {
const elapsed = (Date.now() - startTimeRef.current) / 1000;
setDuration(elapsed);
const webmBlob = new Blob(chunksRef.current, { type: 'audio/webm' });
// Release the device unless we're keeping it warm for the next capture.
// Act on this recorder's own stream; only touch the shared refs when
// this is still the current recording.
if (keepWarm) {
if (isCurrent) {
streamRef.current = null;
// A release requested mid-recording (dictation disabled) is
// honored now that capture has finished; otherwise the warm
// stream stays open for the next take.
if (releaseAfterStopRef.current) {
releaseAfterStopRef.current = false;
releaseWarmStream();
}
}
} else {
stream.getTracks().forEach((track) => {
track.stop();
});
if (isCurrent) streamRef.current = null;
}
// All shared per-take refs have now been snapshotted and stream
// cleanup is complete. A new take may begin while WAV conversion and
// upload continue using the local values above.
finishingRef.current = false;
// Don't fire completion callback if the recording was cancelled
if (wasCancelled) return;
// Convert to WAV format to avoid needing ffmpeg on backend
try {
const wavBlob = await convertToWav(webmBlob);
onRecordingComplete?.(wavBlob, recordedDuration, context);
} catch (err) {
console.error('Error converting audio to WAV:', err);
// Fallback to original blob if conversion fails
onRecordingComplete?.(webmBlob, recordedDuration, context);
}
};
mediaRecorder.onerror = (event) => {
setError('Recording error occurred');
console.error('MediaRecorder error:', event);
};
// WebKit's MediaRecorder drops the WebM EBML header from chunks when
// started with a timeslice, so concatenated blobs fail to parse in
// both AudioContext and ffmpeg. Starting with no timeslice produces
// exactly one dataavailable on stop() with a valid container.
mediaRecorder.start();
setRecording(true);
startTimeRef.current = Date.now();
startingRef.current = false;
// A stop (chord release) that landed while the mic was still opening —
// honor it now that capture has actually begun.
if (pendingStopRef.current) {
pendingStopRef.current = false;
finishingRef.current = true;
mediaRecorder.stop();
setRecording(false);
return;
}
// Start timer
timerRef.current = window.setInterval(() => {
if (startTimeRef.current) {
const elapsed = (Date.now() - startTimeRef.current) / 1000;
setDuration(elapsed);
// Auto-stop at max duration when the caller opts in — dictation
// sessions pass undefined and run until the user releases the
// chord or hits stop; voice-clone sample recorders pass 29s to
// keep reference clips short.
if (maxDurationSeconds !== undefined && elapsed >= maxDurationSeconds) {
if (mediaRecorderRef.current && mediaRecorderRef.current.state !== 'inactive') {
finishingRef.current = true;
mediaRecorderRef.current.stop();
setRecording(false);
if (timerRef.current !== null) {
clearInterval(timerRef.current);
timerRef.current = null;
}
// Auto-stop at max duration when the caller opts in — dictation
// sessions pass undefined and run until the user releases the
// chord or hits stop; voice-clone sample recorders pass 29s to
// keep reference clips short.
if (maxDurationSeconds !== undefined && elapsed >= maxDurationSeconds) {
if (mediaRecorderRef.current && mediaRecorderRef.current.state !== 'inactive') {
mediaRecorderRef.current.stop();
setIsRecording(false);
if (timerRef.current !== null) {
clearInterval(timerRef.current);
timerRef.current = null;
}
}
}
}, 100);
} catch (err) {
const errorMessage =
err instanceof Error
? err.message
: 'Failed to access microphone. Please check permissions.';
// A fresh (non-warm) stream opened before the failure must be released
// so the mic doesn't stay lit; a warm stream is reusable, so it's kept.
if (!keepWarm) {
streamRef.current?.getTracks().forEach((track) => {
track.stop();
});
streamRef.current = null;
}
startingRef.current = false;
finishingRef.current = false;
pendingStopRef.current = false;
setError(errorMessage);
setRecording(false);
}
},
[
maxDurationSeconds,
onRecordingComplete,
acquireStream,
keepWarm,
releaseWarmStream,
setRecording,
],
);
}, 100);
} catch (err) {
const errorMessage =
err instanceof Error
? err.message
: 'Failed to access microphone. Please check permissions.';
setError(errorMessage);
setIsRecording(false);
}
}, [maxDurationSeconds, onRecordingComplete]);
const stopRecording = useCallback(() => {
// The recorder's own state is the lifecycle authority — React ``isRecording``
// lags a render behind ``mediaRecorder.start()``, so a chord release in that
// window would otherwise be dropped.
const recorder = mediaRecorderRef.current;
if (recorder && recorder.state === 'recording') {
finishingRef.current = true;
recorder.stop();
setRecording(false);
if (mediaRecorderRef.current && isRecording) {
mediaRecorderRef.current.stop();
setIsRecording(false);
if (timerRef.current !== null) {
clearInterval(timerRef.current);
timerRef.current = null;
}
} else if (startingRef.current) {
// Stop arrived before capture began (mic still opening) — defer it so
// startRecording stops as soon as the recorder goes live.
pendingStopRef.current = true;
}
}, [setRecording]);
}, [isRecording]);
const cancelRecording = useCallback(() => {
cancelledRef.current = true; // Must be set before stop() triggers onstop
const recorder = mediaRecorderRef.current;
if (recorder && recorder.state !== 'inactive') {
if (mediaRecorderRef.current) {
cancelledRef.current = true; // Must be set before stop() triggers onstop
chunksRef.current = [];
finishingRef.current = true;
recorder.stop();
setRecording(false);
mediaRecorderRef.current.stop();
setIsRecording(false);
setDuration(0);
} else if (startingRef.current) {
// Cancel during mic acquisition — stop as soon as capture begins; the
// cancelled flag suppresses the completion callback.
pendingStopRef.current = true;
}
// Keep the device warm for the next capture when opted in; otherwise stop
// the tracks so the mic is released immediately.
if (keepWarm) {
streamRef.current = null;
if (releaseAfterStopRef.current) {
releaseAfterStopRef.current = false;
releaseWarmStream();
}
} else {
streamRef.current?.getTracks().forEach((track) => {
track.stop();
});
streamRef.current = null;
}
// Stop all tracks
streamRef.current?.getTracks().forEach((track) => {
track.stop();
});
streamRef.current = null;
if (timerRef.current !== null) {
clearInterval(timerRef.current);
timerRef.current = null;
}
}, [keepWarm, releaseWarmStream, setRecording]);
}, []);
// Cleanup on unmount — always fully release the device, warm or not.
// Cleanup on unmount
useEffect(() => {
return () => {
// Invalidate any in-flight acquisition so a stream resolving after unmount
// stops itself instead of leaking a live mic.
acquireGenRef.current += 1;
if (timerRef.current !== null) {
clearInterval(timerRef.current);
}
streamRef.current?.getTracks().forEach((track) => {
track.stop();
});
warmStreamRef.current?.getTracks().forEach((track) => {
track.stop();
});
};
}, []);
@@ -446,7 +216,5 @@ export function useAudioRecording({
startRecording,
stopRecording,
cancelRecording,
prewarm,
releaseWarm: releaseWarmStream,
};
}
+23 -60
View File
@@ -54,15 +54,11 @@ const SHORT_RECORDING_MESSAGE = 'Recording too short, canceled';
export type CapturePillState = PillState | 'hidden';
export interface UseCaptureRecordingSessionOptions {
/** Keep the microphone stream open between dictations when explicitly
* enabled. Off by default so normal recorders release the device. */
keepMicWarm?: boolean;
/**
* Fired after a capture row is created on the server. Callers can use this
* to select the new capture or emit a Tauri event to a sibling window.
* ``context`` is whatever was passed to ``startRecording`` for this take.
*/
onCaptureCreated?: (capture: CaptureResponse, context?: unknown) => void;
onCaptureCreated?: (capture: CaptureResponse) => void;
/**
* Fired with the final delivered text — refined if ``auto_refine`` was on
* for this capture, raw transcript otherwise. Used by the floating
@@ -70,14 +66,12 @@ export interface UseCaptureRecordingSessionOptions {
*
* ``allowAutoPaste`` snapshots the setting at chord-start so a refine that
* lands after the user flips the toggle still uses the value the capture
* was created under. ``context`` is the value passed to ``startRecording``
* for this take, so overlapping dictations can't cross their targets.
* was created under.
*/
onFinalText?: (
text: string,
capture: CaptureResponse,
allowAutoPaste: boolean,
context?: unknown,
) => void;
}
@@ -88,14 +82,12 @@ export interface UseCaptureRecordingSessionResult {
isRecording: boolean;
isUploading: boolean;
isRefining: boolean;
startRecording: (context?: unknown) => void;
startRecording: () => void;
stopRecording: () => void;
toggleRecording: () => void;
dismissError: () => void;
uploadFile: (file: File, source: CaptureSource) => void;
refine: (captureId: string) => void;
prewarm: () => Promise<void>;
releaseWarm: () => void;
}
/**
@@ -131,13 +123,10 @@ export function useCaptureRecordingSession(
const onFinalTextRef = useRef(options.onFinalText);
onFinalTextRef.current = options.onFinalText;
// Per-capture recording context and its ``allow_auto_paste`` snapshot, keyed
// by capture id so a refine that resolves after another dictation started
// still delivers to the right target with the setting the capture was created
// under. Populated on capture-create and consumed once the final text lands.
const captureDeliveryRef = useRef<Map<string, { context: unknown; allowAutoPaste: boolean }>>(
new Map(),
);
// Snapshot of ``allow_auto_paste`` from the capture-create response —
// held so the refine onSuccess (which only sees the plain CaptureResponse)
// can still pass the original setting through to onFinalText.
const allowAutoPasteRef = useRef<boolean>(true);
const clearRestTimer = useCallback(() => {
if (restTimerRef.current !== null) {
@@ -203,34 +192,20 @@ export function useCaptureRecordingSession(
queryClient.invalidateQueries({ queryKey: ['captures'] });
broadcastUpdated(captureId);
if (pillStateRef.current === 'refining') scheduleHidePill();
const delivery = captureDeliveryRef.current.get(captureId);
captureDeliveryRef.current.delete(captureId);
const finalText = data.transcript_refined ?? data.transcript_raw;
if (finalText) {
onFinalTextRef.current?.(
finalText,
data,
delivery?.allowAutoPaste ?? true,
delivery?.context,
);
onFinalTextRef.current?.(finalText, data, allowAutoPasteRef.current);
}
},
onError: (err: Error, captureId) => {
captureDeliveryRef.current.delete(captureId);
onError: (err: Error) => {
showError(err.message || 'Refinement failed');
},
});
const uploadMutation = useMutation({
mutationFn: async ({
file,
source,
}: {
file: File;
source: CaptureSource;
context?: unknown;
}) => apiClient.createCapture(file, { source }),
onSuccess: (capture, { context }) => {
mutationFn: async ({ file, source }: { file: File; source: CaptureSource }) =>
apiClient.createCapture(file, { source }),
onSuccess: (capture) => {
queryClient.setQueryData<CaptureListResponse>(['captures'], (prev) => {
if (!prev) return prev;
if (prev.items.some((c) => c.id === capture.id)) return prev;
@@ -238,12 +213,9 @@ export function useCaptureRecordingSession(
});
queryClient.invalidateQueries({ queryKey: ['captures'] });
broadcastCreated(capture);
onCaptureCreatedRef.current?.(capture, context);
onCaptureCreatedRef.current?.(capture);
allowAutoPasteRef.current = capture.allow_auto_paste;
if (capture.auto_refine) {
captureDeliveryRef.current.set(capture.id, {
context,
allowAutoPaste: capture.allow_auto_paste,
});
setPillState('refining');
refineMutation.mutate(capture.id);
} else {
@@ -253,7 +225,6 @@ export function useCaptureRecordingSession(
capture.transcript_raw,
capture,
capture.allow_auto_paste,
context,
);
}
}
@@ -278,11 +249,8 @@ export function useCaptureRecordingSession(
startRecording: beginAudioRecording,
stopRecording,
error: recordError,
prewarm,
releaseWarm,
} = useAudioRecording({
keepWarm: options.keepMicWarm ?? false,
onRecordingComplete: (blob, recordedDuration, context) => {
onRecordingComplete: (blob, recordedDuration) => {
// Trigger-happy tap — MediaRecorder hasn't emitted a usable chunk yet
// so the blob is empty or unparseable. Surface it as a transient pill
// so the user sees their recording was recognised and canceled.
@@ -300,7 +268,7 @@ export function useCaptureRecordingSession(
const file = new File([blob], `dictation-${Date.now()}.${extension}`, {
type: blob.type,
});
uploadMutation.mutate({ file, source: 'dictation', context });
uploadMutation.mutate({ file, source: 'dictation' });
},
});
@@ -310,16 +278,13 @@ export function useCaptureRecordingSession(
}
}, [recordError, showError]);
const startRecording = useCallback(
(context?: unknown) => {
if (isRecording) return;
clearRestTimer();
setFrozenElapsedMs(0);
setPillState('recording');
beginAudioRecording(context);
},
[isRecording, beginAudioRecording, clearRestTimer],
);
const startRecording = useCallback(() => {
if (isRecording) return;
clearRestTimer();
setFrozenElapsedMs(0);
setPillState('recording');
beginAudioRecording();
}, [isRecording, beginAudioRecording, clearRestTimer]);
const toggleRecording = useCallback(() => {
if (isRecording) {
@@ -359,7 +324,5 @@ export function useCaptureRecordingSession(
dismissError,
uploadFile,
refine,
prewarm,
releaseWarm,
};
}
+1 -26
View File
@@ -1,6 +1,5 @@
import { invoke } from '@tauri-apps/api/core';
import { emit, listen } from '@tauri-apps/api/event';
import { useEffect, useRef } from 'react';
import { useEffect } from 'react';
import { useDictationReadiness } from '@/lib/hooks/useDictationReadiness';
import { useCaptureSettings } from '@/lib/hooks/useSettings';
import { usePlatform } from '@/platform/PlatformContext';
@@ -31,45 +30,21 @@ export function useChordSync() {
const { settings } = useCaptureSettings();
const { canRecord } = useDictationReadiness();
const enabled = settings?.hotkey_enabled;
const keepMicWarm = settings?.keep_mic_warm;
const pushKeys = settings?.chord_push_to_talk_keys;
const toggleKeys = settings?.chord_toggle_to_talk_keys;
// Latest warm state, so the dictate window's mount-time request can be
// answered even between the dep-driven emits below.
const shouldWarmRef = useRef(false);
// The floating dictate window holds the mic warm ahead of the first chord to
// avoid clipping, but it's a separate webview with no view of settings. Mirror
// the decision to it: warm only when dictation is armed AND the user enabled
// "keep microphone ready". Gating here is what stops the always-mounted pill
// from opening the mic — or prompting for access — when the user hasn't asked.
useEffect(() => {
if (!platform.metadata.isTauri) return;
const unlisten = listen('dictate:warm-request', () => {
emit('dictate:warm', shouldWarmRef.current).catch(() => {});
});
return () => {
unlisten.then((fn) => fn()).catch(() => {});
};
}, [platform.metadata.isTauri]);
useEffect(() => {
if (!platform.metadata.isTauri) return;
if (enabled === undefined || !pushKeys || !toggleKeys) return;
const shouldArm = enabled && canRecord;
const shouldWarm = shouldArm && (keepMicWarm ?? false);
shouldWarmRef.current = shouldWarm;
const command = shouldArm ? 'enable_hotkey' : 'disable_hotkey';
const args = shouldArm ? { pushToTalk: pushKeys, toggleToTalk: toggleKeys } : {};
invoke(command, args).catch((err) => {
console.warn(`[chord-sync] ${command} failed:`, err);
});
emit('dictate:warm', shouldWarm).catch(() => {});
}, [
platform.metadata.isTauri,
enabled,
keepMicWarm,
canRecord,
// Stringify so a referentially-new array with the same content
// doesn't fire a redundant invoke on every settings refetch.
+1 -5
View File
@@ -1,5 +1,5 @@
import { formatDistance } from 'date-fns';
import { es, fr, ja, zhCN, zhTW } from 'date-fns/locale';
import { ja, zhCN, zhTW } from 'date-fns/locale';
import i18n from '@/i18n';
export function formatDuration(seconds: number): string {
@@ -10,16 +10,12 @@ export function formatDuration(seconds: number): string {
function getDateLocale() {
switch (i18n.language) {
case 'es':
return es;
case 'ja':
return ja;
case 'zh-CN':
return zhCN;
case 'zh-TW':
return zhTW;
case 'fr':
return fr;
default:
return undefined;
}
-1
View File
@@ -60,7 +60,6 @@ export interface PlatformLifecycle {
stopServer(): Promise<void>;
restartServer(modelsDir?: string | null): Promise<string>;
setKeepServerRunning(keep: boolean): Promise<void>;
setBackendOverride(backend?: string | null): Promise<void>;
setupWindowCloseHandler(): Promise<void>;
subscribeToServerLogs(callback: (entry: ServerLogEntry) => void): () => void;
onServerReady?: () => void;
+4 -66
View File
@@ -3,8 +3,6 @@
import asyncio
import logging
import os
import re
import subprocess
import sys
from contextlib import asynccontextmanager
from pathlib import Path
@@ -38,67 +36,9 @@ logging.basicConfig(
logger = logging.getLogger(__name__)
# An empty HSA_OVERRIDE_GFX_VERSION poisons the ROCm HSA runtime. It is
# treated as "force-empty" and no GPU is detected, even natively supported
# ones (e.g. gfx1201 / RX 9070 on ROCm 7.2). docker-compose can't
# conditionally omit an env var, so we clean it up here before torch loads.
if not os.environ.get("HSA_OVERRIDE_GFX_VERSION"):
os.environ.pop("HSA_OVERRIDE_GFX_VERSION", None)
# AMD GPU environment variables must be set before torch import
# Only set HSA_OVERRIDE_GFX_VERSION for older GPUs that need it.
# RDNA 3+ (gfx1100+) and RDNA 4 (gfx1200+) are natively supported by ROCm
# and the override can cause suboptimal performance or errors.
if not os.environ.get("HSA_OVERRIDE_GFX_VERSION"):
try:
result = subprocess.run(
["rocminfo"],
capture_output=True,
text=True,
timeout=5,
)
if result.returncode == 0:
# Collect all GPUs found in rocminfo output
gfx_versions = []
for line in result.stdout.splitlines():
line_lower = line.lower()
if "gfx" in line_lower:
match = re.search(r"(gfx\d+)", line_lower)
if match:
gfx_versions.append(match.group(1))
if gfx_versions:
# Check if any GPU needs the override (RDNA 2 and older)
# Use the oldest GPU (lowest gfx number) for the decision
try:
gfx_nums = []
for v in gfx_versions:
m = re.search(r"\d+", v)
if m:
gfx_nums.append(int(m.group()))
if gfx_nums:
oldest_num = min(gfx_nums)
oldest_gfx = gfx_versions[gfx_nums.index(oldest_num)]
if oldest_num < 1100:
os.environ["HSA_OVERRIDE_GFX_VERSION"] = "10.3.0"
logger.info(
"AMD GPU detected (%s), setting HSA_OVERRIDE_GFX_VERSION=10.3.0 for compatibility. All GPUs: %s",
oldest_gfx,
", ".join(gfx_versions),
)
else:
logger.info(
"AMD GPU detected (%s), native ROCm support available, skipping HSA_OVERRIDE_GFX_VERSION. All GPUs: %s",
oldest_gfx,
", ".join(gfx_versions),
)
except (ValueError, AttributeError) as e:
logger.info("Could not parse GPU version from rocminfo output: %s", e)
except (FileNotFoundError, subprocess.TimeoutExpired, Exception) as e:
logger.info(
"Could not detect AMD GPU via rocminfo, skipping automatic HSA_OVERRIDE_GFX_VERSION configuration: %s",
e,
)
os.environ["HSA_OVERRIDE_GFX_VERSION"] = "10.3.0"
if not os.environ.get("MIOPEN_LOG_LEVEL"):
os.environ["MIOPEN_LOG_LEVEL"] = "4"
@@ -333,10 +273,8 @@ async def _run_startup(application: FastAPI) -> None:
logger.warning("GPU COMPATIBILITY: %s", _cuda_warning)
from .services.cuda import check_and_update_cuda_binary
from .services.rocm import check_and_update_rocm_binary
create_background_task(check_and_update_cuda_binary())
create_background_task(check_and_update_rocm_binary())
try:
progress_manager = get_progress_manager()
@@ -360,15 +298,15 @@ async def _run_shutdown() -> None:
"""Unload models on lifespan exit."""
logger.info("Voicebox server shutting down...")
try:
await tts.unload_tts_model()
tts.unload_tts_model()
except Exception:
logger.exception("Failed to unload TTS model")
try:
await transcribe.unload_whisper_model()
transcribe.unload_whisper_model()
except Exception:
logger.exception("Failed to unload Whisper model")
try:
await llm.unload_llm_model()
llm.unload_llm_model()
except Exception:
logger.exception("Failed to unload LLM model")
+6 -20
View File
@@ -547,21 +547,7 @@ async def ensure_model_cached_or_raise(engine: str, model_size: str = "default")
)
async def unload_backend(backend) -> None:
"""Free a backend's model, serialized onto the MLX worker when it has one.
MLX backends expose an async ``unload`` that runs the free on the dedicated
MLX thread so it can't collide with an in-flight load/generate. Other
backends only carry the synchronous ``unload_model``.
"""
unload = getattr(backend, "unload", None)
if unload is not None:
await unload()
else:
backend.unload_model()
async def unload_model_by_config(config: ModelConfig) -> bool:
def unload_model_by_config(config: ModelConfig) -> bool:
"""Unload a model given its config. Returns True if it was loaded, False otherwise."""
from . import get_tts_backend_for_engine
from ..services import tts, transcribe, llm as llm_service
@@ -569,7 +555,7 @@ async def unload_model_by_config(config: ModelConfig) -> bool:
if config.engine == "whisper":
whisper_model = transcribe.get_whisper_model()
if whisper_model.is_loaded() and whisper_model.model_size == config.model_size:
await unload_backend(whisper_model)
transcribe.unload_whisper_model()
return True
return False
@@ -577,7 +563,7 @@ async def unload_model_by_config(config: ModelConfig) -> bool:
backend = llm_service.get_llm_model()
loaded_size = getattr(backend, "_current_model_size", None) or getattr(backend, "model_size", None)
if backend.is_loaded() and loaded_size == config.model_size:
await unload_backend(backend)
backend.unload_model()
return True
return False
@@ -585,7 +571,7 @@ async def unload_model_by_config(config: ModelConfig) -> bool:
tts_model = tts.get_tts_model()
loaded_size = getattr(tts_model, "_current_model_size", None) or getattr(tts_model, "model_size", None)
if tts_model.is_loaded() and loaded_size == config.model_size:
await unload_backend(tts_model)
tts.unload_tts_model()
return True
return False
@@ -593,14 +579,14 @@ async def unload_model_by_config(config: ModelConfig) -> bool:
backend = get_tts_backend_for_engine(config.engine)
loaded_size = getattr(backend, "_current_model_size", None) or getattr(backend, "model_size", None)
if backend.is_loaded() and loaded_size == config.model_size:
await unload_backend(backend)
backend.unload_model()
return True
return False
# All other TTS engines
backend = get_tts_backend_for_engine(config.engine)
if backend.is_loaded():
await unload_backend(backend)
backend.unload_model()
return True
return False
-5
View File
@@ -138,11 +138,6 @@ def check_cuda_compatibility() -> tuple[bool, str | None]:
if not torch.cuda.is_available():
return True, None
# ROCm/HIP uses the cuda frontend but has different architecture names (gfx*).
# Skip NVIDIA-specific compute capability checks on AMD hardware.
if hasattr(torch.version, "hip") and torch.version.hip:
return True, None
major, minor = torch.cuda.get_device_capability(0)
capability = f"{major}.{minor}"
device_name = torch.cuda.get_device_name(0)
+1 -9
View File
@@ -146,15 +146,7 @@ class HumeTadaBackend:
)
# Determine dtype — use bf16 on CUDA/XPU for ~50% memory savings
# On ROCm/AMD, torch.cuda.is_bf16_supported() works via the HIP abstraction,
# but we wrap it defensively in case an older build lacks the symbol.
_bf16_ok = False
if device == "cuda":
try:
_bf16_ok = torch.cuda.is_bf16_supported()
except Exception:
_bf16_ok = False
if _bf16_ok:
if device == "cuda" and torch.cuda.is_bf16_supported():
model_dtype = torch.bfloat16
elif device == "xpu":
# Intel Arc (Alchemist+) supports bf16 natively
+1 -6
View File
@@ -96,16 +96,11 @@ KOKORO_VOICES = [
("pf_dora", "Dora", "female", "pt"),
("pm_alex", "Alex", "male", "pt"),
("pm_santa", "Santa", "male", "pt"),
# Chinese female
# Chinese
("zf_xiaobei", "Xiaobei", "female", "zh"),
("zf_xiaoni", "Xiaoni", "female", "zh"),
("zf_xiaoxiao", "Xiaoxiao", "female", "zh"),
("zf_xiaoyi", "Xiaoyi", "female", "zh"),
# Chinese male
("zm_yunjian", "Yunjian", "male", "zh"),
("zm_yunxi", "Yunxi", "male", "zh"),
("zm_yunxia", "Yunxia", "male", "zh"),
("zm_yunyang", "Yunyang", "male", "zh"),
]
# Map our ISO language codes to Kokoro lang_code characters
+30 -56
View File
@@ -3,6 +3,7 @@ MLX backend implementation for TTS and STT using mlx-audio.
"""
from typing import Optional, List, Tuple
import asyncio
import logging
import numpy as np
from pathlib import Path
@@ -18,7 +19,6 @@ ensure_original_qwen_config_cached()
from . import TTSBackend, STTBackend, LANGUAGE_CODE_TO_NAME, WHISPER_HF_REPOS
from .base import is_model_cached, combine_voice_prompts as _combine_voice_prompts, model_load_progress
from ..services.mlx_thread import run_on_mlx_thread, clear_mlx_cache
from ..utils.cache import get_cache_key, get_cached_voice_prompt, cache_voice_prompt
@@ -63,22 +63,6 @@ class MLXTTSBackend:
weight_extensions=(".safetensors", ".bin", ".npz"),
)
def _ensure_loaded_sync(self, model_size: Optional[str]):
"""Load the model if the requested size isn't already resident.
Runs on the MLX worker thread so it stays serialized with generation.
"""
if model_size is None:
model_size = self.model_size
if self.model is not None and self._current_model_size == model_size:
return
if self.model is not None and self._current_model_size != model_size:
self.unload_model()
self._load_model_sync(model_size)
async def load_model_async(self, model_size: Optional[str] = None):
"""
Lazy load the MLX TTS model.
@@ -86,15 +70,23 @@ class MLXTTSBackend:
Args:
model_size: Model size to load (1.7B or 0.6B)
"""
await run_on_mlx_thread(self._ensure_loaded_sync, model_size)
if model_size is None:
model_size = self.model_size
# If already loaded with correct size, return
if self.model is not None and self._current_model_size == model_size:
return
# Unload existing model if different size requested
if self.model is not None and self._current_model_size != model_size:
self.unload_model()
# Run blocking load in thread pool
await asyncio.to_thread(self._load_model_sync, model_size)
# Alias for compatibility
load_model = load_model_async
async def unload(self):
"""Free the model, serialized onto the MLX worker thread."""
await run_on_mlx_thread(self.unload_model)
def _load_model_sync(self, model_size: str):
"""Synchronous model loading."""
model_path = self._get_model_path(model_size)
@@ -118,7 +110,6 @@ class MLXTTSBackend:
del self.model
self.model = None
self._current_model_size = None
clear_mlx_cache()
logger.info("MLX TTS model unloaded")
async def create_voice_prompt(
@@ -196,6 +187,8 @@ class MLXTTSBackend:
Returns:
Tuple of (audio_array, sample_rate)
"""
await self.load_model_async(None)
logger.info("Generating audio for text: %s", text)
def _generate_sync():
@@ -265,13 +258,8 @@ class MLXTTSBackend:
return audio, sample_rate
# Load-if-needed and inference run as one job on the MLX worker so a
# concurrent unload or different-size load can't land between them.
def _load_and_generate():
self._ensure_loaded_sync(None)
return _generate_sync()
audio, sample_rate = await run_on_mlx_thread(_load_and_generate)
# Run blocking inference in thread pool
audio, sample_rate = await asyncio.to_thread(_generate_sync)
return audio, sample_rate
@@ -291,19 +279,6 @@ class MLXSTTBackend:
hf_repo = WHISPER_HF_REPOS.get(model_size, f"openai/whisper-{model_size}")
return is_model_cached(hf_repo, weight_extensions=(".safetensors", ".bin", ".npz"))
def _ensure_loaded_sync(self, model_size: Optional[str]):
"""Load the model if the requested size isn't already resident.
Runs on the MLX worker thread so it stays serialized with transcription.
"""
if model_size is None:
model_size = self.model_size
if self.model is not None and self.model_size == model_size:
return
self._load_model_sync(model_size)
async def load_model_async(self, model_size: Optional[str] = None):
"""
Lazy load the MLX Whisper model.
@@ -311,15 +286,18 @@ class MLXSTTBackend:
Args:
model_size: Model size (tiny, base, small, medium, large)
"""
await run_on_mlx_thread(self._ensure_loaded_sync, model_size)
if model_size is None:
model_size = self.model_size
if self.model is not None and self.model_size == model_size:
return
# Run blocking load in thread pool
await asyncio.to_thread(self._load_model_sync, model_size)
# Alias for compatibility
load_model = load_model_async
async def unload(self):
"""Free the model, serialized onto the MLX worker thread."""
await run_on_mlx_thread(self.unload_model)
def _load_model_sync(self, model_size: str):
"""Synchronous model loading."""
progress_model_name = f"whisper-{model_size}"
@@ -341,7 +319,6 @@ class MLXSTTBackend:
if self.model is not None:
del self.model
self.model = None
clear_mlx_cache()
logger.info("MLX Whisper model unloaded")
async def transcribe(
@@ -361,6 +338,8 @@ class MLXSTTBackend:
Returns:
Transcribed text
"""
await self.load_model_async(model_size)
def _transcribe_sync():
"""Run synchronous transcription in thread pool."""
# MLX Whisper transcription using generate method
@@ -384,10 +363,5 @@ class MLXSTTBackend:
else:
return str(result).strip()
# Load-if-needed and transcription run as one job on the MLX worker so
# a concurrent unload or load can't land between them.
def _load_and_transcribe():
self._ensure_loaded_sync(model_size)
return _transcribe_sync()
return await run_on_mlx_thread(_load_and_transcribe)
# Run blocking transcription in thread pool
return await asyncio.to_thread(_transcribe_sync)
+18 -37
View File
@@ -19,7 +19,7 @@ from .base import (
manual_seed,
model_load_progress,
)
from ..services.mlx_thread import run_on_mlx_thread, clear_mlx_cache
from ..utils.hf_offline_patch import force_offline_if_cached
logger = logging.getLogger(__name__)
@@ -103,19 +103,15 @@ class PyTorchQwenLLMBackend:
with model_load_progress(progress_model_name, is_cached):
logger.info("Loading Qwen3 %s on %s...", model_size, self.device)
# Loads run with the process's default HF_HUB_OFFLINE state.
# Forcing offline for cached models flips process-global state
# and silently switches every concurrent download/load on other
# threads to offline mode (issue #841) — the same regression
# removed app-wide in #524/#530.
self.tokenizer = AutoTokenizer.from_pretrained(repo)
dtype = torch.float16 if self.device in ("cuda", "mps") else torch.float32
self.model = AutoModelForCausalLM.from_pretrained(
repo,
dtype=dtype,
)
self.model.to(self.device)
self.model.eval()
with force_offline_if_cached(is_cached, progress_model_name):
self.tokenizer = AutoTokenizer.from_pretrained(repo)
dtype = torch.float16 if self.device in ("cuda", "mps") else torch.float32
self.model = AutoModelForCausalLM.from_pretrained(
repo,
dtype=dtype,
)
self.model.to(self.device)
self.model.eval()
self._current_model_size = model_size
self.model_size = model_size
@@ -206,11 +202,7 @@ class MLXQwenLLMBackend:
weight_extensions=(".safetensors", ".bin", ".npz"),
)
def _ensure_loaded_sync(self, model_size: Optional[str]) -> None:
"""Load the model if the requested size isn't already resident.
Runs on the MLX worker thread so it stays serialized with generation.
"""
async def load_model(self, model_size: Optional[str] = None) -> None:
if model_size is None:
model_size = self.model_size
@@ -220,14 +212,7 @@ class MLXQwenLLMBackend:
if self.model is not None and self._current_model_size != model_size:
self.unload_model()
self._load_model_sync(model_size)
async def load_model(self, model_size: Optional[str] = None) -> None:
await run_on_mlx_thread(self._ensure_loaded_sync, model_size)
async def unload(self) -> None:
"""Free the model, serialized onto the MLX worker thread."""
await run_on_mlx_thread(self.unload_model)
await asyncio.to_thread(self._load_model_sync, model_size)
def _load_model_sync(self, model_size: str) -> None:
from mlx_lm import load as mlx_load
@@ -238,8 +223,8 @@ class MLXQwenLLMBackend:
with model_load_progress(progress_model_name, is_cached):
logger.info("Loading Qwen3 %s via MLX...", model_size)
# See the PyTorch loader comment — no offline forcing (issue #841).
loaded = mlx_load(repo)
with force_offline_if_cached(is_cached, progress_model_name):
loaded = mlx_load(repo)
# mlx_lm.load returns (model, tokenizer) by default and
# (model, tokenizer, config) when return_config=True.
@@ -258,7 +243,6 @@ class MLXQwenLLMBackend:
self.model = None
self.tokenizer = None
self._current_model_size = None
clear_mlx_cache()
logger.info("Qwen3 (MLX) unloaded")
async def generate(
@@ -270,13 +254,10 @@ class MLXQwenLLMBackend:
model_size: Optional[str] = None,
examples: Optional[list[tuple[str, str]]] = None,
) -> str:
# Load-if-needed and inference run as one job on the MLX worker so a
# concurrent unload or different-size load can't land between them.
def _load_and_generate() -> str:
self._ensure_loaded_sync(model_size)
return self._generate_sync(prompt, system, max_tokens, temperature, examples)
return await run_on_mlx_thread(_load_and_generate)
await self.load_model(model_size)
return await asyncio.to_thread(
self._generate_sync, prompt, system, max_tokens, temperature, examples
)
def _generate_sync(
self,
+54 -252
View File
@@ -22,34 +22,24 @@ def is_apple_silicon():
return platform.system() == "Darwin" and platform.machine() == "arm64"
def build_server(cuda=False, rocm=False):
def build_server(cuda=False):
"""Build Python server as standalone binary.
Args:
cuda: If True, build with CUDA support and name the binary
voicebox-server-cuda instead of voicebox-server.
rocm: If True, build with ROCm support and name the binary
voicebox-server-rocm instead of voicebox-server.
"""
if cuda and rocm:
raise ValueError("Cannot build with both CUDA and ROCm support")
backend_dir = Path(__file__).parent
if rocm:
binary_name = "voicebox-server-rocm"
elif cuda:
binary_name = "voicebox-server-cuda"
else:
binary_name = "voicebox-server"
binary_name = "voicebox-server-cuda" if cuda else "voicebox-server"
# PyInstaller arguments
# CUDA and ROCm builds use --onedir so we can split the output into two archives:
# CUDA builds use --onedir so we can split the output into two archives:
# 1. Server core (~200-400MB) — versioned with the app
# 2. GPU libs (~2GB) — versioned independently (only redownloaded on
# GPU toolkit / torch major version changes)
# 2. CUDA libs (~2GB) — versioned independently (only redownloaded on
# CUDA toolkit / torch major version changes)
# CPU builds remain --onefile for simplicity.
pack_mode = "--onedir" if (cuda or rocm) else "--onefile"
pack_mode = "--onedir" if cuda else "--onefile"
args = [
"server.py", # Use server.py as entry point instead of main.py
pack_mode,
@@ -330,77 +320,22 @@ def build_server(cuda=False, rocm=False):
]
)
if sys.version_info >= (3, 13):
args.extend(["--hidden-import", "audioop"])
# Add CUDA/ROCm-specific hidden imports
if cuda or rocm:
variant = "ROCm" if rocm else "CUDA"
logger.info("Building with %s support", variant)
gpu_hidden = [
"--hidden-import",
"torch.cuda",
]
# cudnn is NVIDIA-specific; ROCm uses MIOpen under the abstraction layer
if cuda:
gpu_hidden.extend(
[
"--hidden-import",
"torch.backends.cudnn",
]
)
args.extend(gpu_hidden)
if rocm:
# rocm_sdk imports its backend packages dynamically via
# importlib.import_module(py_package_name), which PyInstaller's
# static analyzer cannot see. We must collect them explicitly —
# otherwise only the pure-python rocm_sdk wrapper ships and
# rocm_sdk.find_libraries crashes with UnboundLocalError at boot.
#
# The backend packages also contain the HIP/MIOpen/hipBLAS DLLs
# under bin/ (plus ~750 MB of tensile kernel files under
# bin/rocblas/library and bin/hipblaslt/library) — collect-all
# walks the tree recursively so both DLLs and kernel data are
# bundled. See rocm_sdk/_dist_info.py for the package mapping.
# Add CUDA-specific hidden imports
if cuda:
logger.info("Building with CUDA support")
args.extend(
[
"--collect-all",
"rocm_sdk",
"--collect-all",
"_rocm_sdk_core",
"--collect-all",
"_rocm_sdk_libraries_custom",
"--collect-all",
"rocm_sdk_core",
"--collect-all",
"rocm_sdk_libraries_custom",
"--hidden-import",
"_rocm_sdk_core",
"torch.cuda",
"--hidden-import",
"_rocm_sdk_libraries_custom",
"--hidden-import",
"rocm_sdk_core",
"--hidden-import",
"rocm_sdk_libraries_custom",
"--copy-metadata",
"rocm",
"--copy-metadata",
"rocm-sdk-core",
"--copy-metadata",
"rocm-sdk-libraries-custom",
# Repair rocm_sdk.find_libraries (masks UnboundLocalError
# with a readable ModuleNotFoundError on missing backends).
"--runtime-hook",
"pyi_rth_rocm_sdk.py",
"torch.backends.cudnn",
]
)
# Exclude NVIDIA CUDA packages from non-CUDA builds to keep binary small.
# When building from a venv with CUDA torch installed, PyInstaller would
# bundle ~3GB of NVIDIA shared libraries. We exclude both the Python
# modules and the binary DLLs. This applies to CPU and ROCm builds.
if not cuda:
else:
# Exclude NVIDIA CUDA packages from CPU-only builds to keep binary small.
# When building from a venv with CUDA torch installed, PyInstaller would
# bundle ~3GB of NVIDIA shared libraries. We exclude both the Python
# modules and the binary DLLs.
nvidia_packages = [
"nvidia",
"nvidia.cublas",
@@ -419,8 +354,8 @@ def build_server(cuda=False, rocm=False):
for pkg in nvidia_packages:
args.extend(["--exclude-module", pkg])
# Add MLX-specific imports if building on Apple Silicon (never for GPU builds)
if is_apple_silicon() and not cuda and not rocm:
# Add MLX-specific imports if building on Apple Silicon (never for CUDA builds)
if is_apple_silicon() and not cuda:
logger.info("Building for Apple Silicon - including MLX dependencies")
args.extend(
[
@@ -464,7 +399,7 @@ def build_server(cuda=False, rocm=False):
"mlx_lm",
]
)
elif not cuda and not rocm:
elif not cuda:
logger.info("Building for non-Apple Silicon platform - PyTorch only")
dist_dir = str(backend_dir / "dist")
@@ -485,128 +420,43 @@ def build_server(cuda=False, rocm=False):
os.chdir(backend_dir)
# For CPU builds on Windows, ensure we're using CPU-only torch.
# If CUDA or ROCm torch is installed (local dev), swap to CPU torch before
# building, then restore afterwards. This prevents PyInstaller from bundling
# GPU libraries into the CPU binary.
restore_torch = None
# If CUDA torch is installed (local dev), swap to CPU torch before building,
# then restore CUDA torch after. This prevents PyInstaller from bundling
# ~3GB of CUDA DLLs into the CPU binary.
restore_cuda = False
if not cuda and platform.system() == "Windows":
import subprocess
result = subprocess.run(
[sys.executable, "-c", "import torch; print(torch.version.cuda or '')"], capture_output=True, text=True
)
has_cuda_torch = bool(result.stdout.strip())
if has_cuda_torch:
logger.info("CUDA torch detected — installing CPU torch for CPU build...")
subprocess.run(
[
sys.executable,
"-m",
"pip",
"install",
"torch",
"torchvision",
"torchaudio",
"--index-url",
"https://download.pytorch.org/whl/cpu",
"--force-reinstall",
"-q",
],
check=True,
)
restore_cuda = True
# Run PyInstaller
try:
if not cuda and not rocm and platform.system() == "Windows":
import subprocess
cuda_result = subprocess.run(
[sys.executable, "-c", "import torch; print(torch.version.cuda or '')"], capture_output=True, text=True
)
rocm_result = subprocess.run(
[sys.executable, "-c", "import torch; print(torch.version.hip or '')"], capture_output=True, text=True
)
if cuda_result.stdout.strip():
restore_torch = "cuda"
logger.info("CUDA torch detected — installing CPU torch for CPU build...")
subprocess.run(
[
sys.executable,
"-m",
"pip",
"install",
"torch",
"torchvision",
"torchaudio",
"--index-url",
"https://download.pytorch.org/whl/cpu",
"--force-reinstall",
"--no-deps",
"-q",
],
check=True,
)
elif rocm_result.stdout.strip():
restore_torch = "rocm"
logger.info("ROCm torch detected — installing CPU torch for CPU build...")
subprocess.run(
[
sys.executable,
"-m",
"pip",
"install",
"torch",
"torchvision",
"torchaudio",
"--index-url",
"https://download.pytorch.org/whl/cpu",
"--force-reinstall",
"--no-deps",
"-q",
],
check=True,
)
# For ROCm builds on Windows, ensure ROCm torch is installed.
if rocm and platform.system() == "Windows":
import subprocess
if sys.implementation.name != "cpython" or sys.version_info[:2] != (3, 12):
raise RuntimeError(
"ROCm wheels are cp312-cp312-specific; "
f"got {sys.implementation.name} {sys.version.split()[0]}. "
"Use CPython 3.12 to build the ROCm binary."
)
result = subprocess.run(
[sys.executable, "-c", "import torch; print(torch.version.hip or '')"], capture_output=True, text=True
)
has_rocm_torch = bool(result.stdout.strip())
if not has_rocm_torch:
logger.info("ROCm torch not detected — installing ROCm torch for ROCm build...")
# Determine what to restore BEFORE overwriting the environment
cuda_result = subprocess.run(
[sys.executable, "-c", "import torch; print(torch.version.cuda or '')"],
capture_output=True,
text=True,
)
if cuda_result.stdout.strip():
restore_torch = "cuda"
else:
restore_torch = "cpu"
# Now overwrite the environment safely
subprocess.run(
[
sys.executable,
"-m",
"pip",
"install",
"https://repo.radeon.com/rocm/windows/rocm-rel-7.2.1/rocm_sdk_core-7.2.1-py3-none-win_amd64.whl",
"https://repo.radeon.com/rocm/windows/rocm-rel-7.2.1/rocm_sdk_devel-7.2.1-py3-none-win_amd64.whl",
"https://repo.radeon.com/rocm/windows/rocm-rel-7.2.1/rocm_sdk_libraries_custom-7.2.1-py3-none-win_amd64.whl",
"https://repo.radeon.com/rocm/windows/rocm-rel-7.2.1/rocm-7.2.1.tar.gz",
"--no-deps",
"-q",
],
check=True,
)
subprocess.run(
[
sys.executable,
"-m",
"pip",
"install",
"https://repo.radeon.com/rocm/windows/rocm-rel-7.2.1/torch-2.9.1%2Brocm7.2.1-cp312-cp312-win_amd64.whl",
"https://repo.radeon.com/rocm/windows/rocm-rel-7.2.1/torchaudio-2.9.1%2Brocm7.2.1-cp312-cp312-win_amd64.whl",
"https://repo.radeon.com/rocm/windows/rocm-rel-7.2.1/torchvision-0.24.1%2Brocm7.2.1-cp312-cp312-win_amd64.whl",
"--force-reinstall",
"--no-deps",
"-q",
],
check=True,
)
# Run PyInstaller
PyInstaller.__main__.run(args)
finally:
# Restore torch if we swapped it out (even on build failure)
if restore_torch == "cuda":
# Restore CUDA torch if we swapped it out (even on build failure)
if restore_cuda:
logger.info("Restoring CUDA torch...")
import subprocess
@@ -622,52 +472,10 @@ def build_server(cuda=False, rocm=False):
"--index-url",
"https://download.pytorch.org/whl/cu128",
"--force-reinstall",
"--no-deps",
"-q",
],
check=True,
)
elif restore_torch == "rocm":
logger.info("Restoring ROCm torch...")
import subprocess
subprocess.run(
[
sys.executable,
"-m",
"pip",
"install",
"https://repo.radeon.com/rocm/windows/rocm-rel-7.2.1/torch-2.9.1%2Brocm7.2.1-cp312-cp312-win_amd64.whl",
"https://repo.radeon.com/rocm/windows/rocm-rel-7.2.1/torchaudio-2.9.1%2Brocm7.2.1-cp312-cp312-win_amd64.whl",
"https://repo.radeon.com/rocm/windows/rocm-rel-7.2.1/torchvision-0.24.1%2Brocm7.2.1-cp312-cp312-win_amd64.whl",
"--force-reinstall",
"--no-deps",
"-q",
],
check=True,
)
elif restore_torch == "cpu":
logger.info("Restoring CPU torch...")
import subprocess
subprocess.run(
[
sys.executable,
"-m",
"pip",
"install",
"torch",
"torchvision",
"torchaudio",
"--index-url",
"https://download.pytorch.org/whl/cpu",
"--force-reinstall",
"--no-deps",
"-q",
],
check=True,
)
logger.info("Binary built in %s", backend_dir / "dist" / binary_name)
@@ -769,11 +577,6 @@ if __name__ == "__main__":
action="store_true",
help="Build CUDA-enabled binary (voicebox-server-cuda)",
)
parser.add_argument(
"--rocm",
action="store_true",
help="Build ROCm-enabled binary (voicebox-server-rocm) for AMD GPUs",
)
parser.add_argument(
"--shim",
action="store_true",
@@ -783,5 +586,4 @@ if __name__ == "__main__":
if cli_args.shim:
build_shim()
else:
build_server(cuda=cli_args.cuda, rocm=cli_args.rocm)
build_server(cuda=cli_args.cuda)
-5
View File
@@ -80,11 +80,6 @@ def resolve_storage_path(path: str | Path | None) -> Path | None:
return None
stored_path = Path(path)
# Empty paths (e.g. failed generations) must not resolve to the data
# dir itself, which exists and would defeat the callers' 404 guards.
# Path("") is truthy, so check parts rather than the raw value.
if not stored_path.parts:
return None
if stored_path.is_absolute():
rebased_path = _path_relative_to_any_data_dir(stored_path)
if rebased_path is not None:
-7
View File
@@ -243,13 +243,6 @@ def _migrate_capture_settings(engine, inspector, tables: set[str]) -> None:
"hotkey_enabled BOOLEAN NOT NULL DEFAULT 0",
"hotkey_enabled",
)
if "keep_mic_warm" not in columns:
_add_column(
engine,
"capture_settings",
"keep_mic_warm BOOLEAN NOT NULL DEFAULT 0",
"keep_mic_warm",
)
def _migrate_mcp_bindings(engine, inspector, tables: set[str]) -> None:
-4
View File
@@ -210,10 +210,6 @@ class CaptureSettings(Base):
# "Voicebox would like to receive keystrokes from any application" dialog
# before they've even opened the Captures tab.
hotkey_enabled = Column(Boolean, nullable=False, default=False)
# Hold the microphone open while dictation is enabled so push-to-talk
# doesn't clip the first words. Off by default — when on, the OS mic-in-use
# indicator stays lit the whole time dictation is enabled.
keep_mic_warm = Column(Boolean, nullable=False, default=False)
# Lists of keytap key names (e.g. "MetaRight", "ControlRight"). Right-hand
# modifiers by default so they don't collide with left-hand shortcuts.
chord_push_to_talk_keys = Column(
+1 -4
View File
@@ -258,7 +258,6 @@ class CaptureSettingsResponse(BaseModel):
allow_auto_paste: bool = True
default_playback_voice_id: Optional[str] = None
hotkey_enabled: bool = False
keep_mic_warm: bool = False
chord_push_to_talk_keys: List[str] = Field(
default_factory=default_push_to_talk_chord
)
@@ -283,7 +282,6 @@ class CaptureSettingsUpdate(BaseModel):
allow_auto_paste: Optional[bool] = None
default_playback_voice_id: Optional[str] = None
hotkey_enabled: Optional[bool] = None
keep_mic_warm: Optional[bool] = None
chord_push_to_talk_keys: Optional[List[str]] = Field(default=None, min_length=1, max_length=6)
chord_toggle_to_talk_keys: Optional[List[str]] = Field(default=None, min_length=1, max_length=6)
@@ -444,8 +442,7 @@ class HealthResponse(BaseModel):
gpu_type: Optional[str] = None # GPU type (CUDA, MPS, or None)
vram_used_mb: Optional[float] = None
backend_type: Optional[str] = None # Backend type (mlx or pytorch)
backend_variant: Optional[str] = None # Binary variant (cpu, cuda, or rocm)
supports_rocm: bool = False # AMD GPU on Windows — the ROCm backend is applicable
backend_variant: Optional[str] = None # Binary variant (cpu or cuda)
gpu_compatibility_warning: Optional[str] = None # Warning if GPU arch unsupported
-85
View File
@@ -1,85 +0,0 @@
"""
Runtime hook: repair rocm_sdk.find_libraries under PyInstaller.
rocm_sdk 7.2.x ships a find_libraries() with a latent bug: when the
backend package (_rocm_sdk_core / _rocm_sdk_libraries_{target}) cannot
be imported, the except clause records the miss but falls through to
`py_root = Path(py_module.__file__).parent`, where py_module was never
assigned. This surfaces as UnboundLocalError instead of the intended
ModuleNotFoundError, masking the real cause.
Frozen apps trip this because rocm_sdk imports the backend packages
dynamically via importlib, which PyInstaller's static analyzer cannot
see. We re-collect those packages in build_binary.py; this hook is
defense-in-depth: it replaces find_libraries with a corrected version
so any future missing-package case surfaces a readable error.
"""
def _patch_rocm_sdk():
try:
import rocm_sdk
from rocm_sdk import _dist_info
except ModuleNotFoundError as e:
if e.name not in {"rocm_sdk", "rocm_sdk._dist_info"}:
raise
return
import importlib
import platform
from pathlib import Path
def find_libraries(*shortnames):
paths = []
missing_extras = set()
is_windows = platform.system() == "Windows"
for shortname in shortnames:
try:
lib_entry = _dist_info.ALL_LIBRARIES[shortname]
except KeyError:
raise ModuleNotFoundError(f"Unknown rocm library '{shortname}'") from None
if is_windows and not lib_entry.dll_pattern:
continue
package = lib_entry.package
target_family = None
if package.is_target_specific:
target_family = _dist_info.determine_target_family()
py_package_name = package.get_py_package_name(target_family)
try:
py_module = importlib.import_module(py_package_name)
except ModuleNotFoundError as e:
if e.name != py_package_name:
raise
missing_extras.add(package.logical_name)
continue
py_root = Path(py_module.__file__).parent
if is_windows:
relpath = py_root / lib_entry.windows_relpath
entry_pattern = lib_entry.dll_pattern
else:
relpath = py_root / lib_entry.posix_relpath
entry_pattern = lib_entry.so_pattern
matching_paths = sorted(relpath.glob(entry_pattern))
if len(matching_paths) == 0:
raise FileNotFoundError(
f"Could not find rocm library '{shortname}' at path "
f"'{relpath},' no match for pattern '{entry_pattern}'"
)
paths.append(matching_paths[0])
if missing_extras:
raise ModuleNotFoundError(
f"Missing required rocm backend packages: "
f"{', '.join(sorted(missing_extras))}. The frozen build did "
f"not bundle _rocm_sdk_core / _rocm_sdk_libraries_<target>. "
f"Check build_binary.py --collect-all flags."
)
return paths
rocm_sdk.find_libraries = find_libraries
_patch_rocm_sdk()
+1 -2
View File
@@ -16,8 +16,7 @@ miniaudio>=1.59
# 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 and the setup-python recipe in the
# justfile). Most other mlx-audio runtime deps
# (see .github/workflows/release.yml). Most other mlx-audio runtime deps
# (huggingface_hub, librosa, mlx-lm, numba, numpy, protobuf, pyloudnorm,
# sounddevice, tqdm) are already in requirements.txt or pulled in by
# other engines.
-4
View File
@@ -1,4 +0,0 @@
--extra-index-url https://repo.radeon.com/rocm/windows/rocm-rel-7.2.1/
torch==2.9.1+rocm7.2.1
torchaudio==2.9.1+rocm7.2.1
torchvision==0.24.1+rocm7.2.1
-1
View File
@@ -53,7 +53,6 @@ en_core_web_sm @ https://github.com/explosion/spacy-models/releases/download/en_
unidic-lite>=1.0.8
# Audio processing
audioop-lts>=0.2.1; python_version >= "3.13"
librosa>=0.10.0
soundfile>=0.12.0
numpy>=1.24.0,<2.0
-2
View File
@@ -20,7 +20,6 @@ def register_routers(app: FastAPI) -> None:
from .settings import router as settings_router
from .tasks import router as tasks_router
from .cuda import router as cuda_router
from .rocm import router as rocm_router
from .speak import router as speak_router
from .mcp_bindings import router as mcp_bindings_router
from .events import router as events_router
@@ -41,7 +40,6 @@ def register_routers(app: FastAPI) -> None:
app.include_router(settings_router)
app.include_router(tasks_router)
app.include_router(cuda_router)
app.include_router(rocm_router)
app.include_router(speak_router)
app.include_router(mcp_bindings_router)
app.include_router(events_router)
+4 -9
View File
@@ -34,7 +34,7 @@ async def get_version_audio(version_id: str, db: Session = Depends(get_db)):
raise HTTPException(status_code=404, detail="Version not found")
audio_path = config.resolve_storage_path(version.audio_path)
if audio_path is None or not audio_path.is_file():
if audio_path is None or not audio_path.exists():
raise HTTPException(status_code=404, detail="Audio file not found")
return FileResponse(
@@ -52,13 +52,8 @@ async def get_audio(generation_id: str, db: Session = Depends(get_db)):
raise HTTPException(status_code=404, detail="Generation not found")
audio_path = config.resolve_storage_path(generation.audio_path)
if audio_path is None or not audio_path.is_file():
detail = (
"Generation failed; no audio available"
if generation.status == "failed"
else "Audio file not found"
)
raise HTTPException(status_code=404, detail=detail)
if audio_path is None or not audio_path.exists():
raise HTTPException(status_code=404, detail="Audio file not found")
return FileResponse(
audio_path,
@@ -77,7 +72,7 @@ async def get_sample_audio(sample_id: str, db: Session = Depends(get_db)):
raise HTTPException(status_code=404, detail="Sample not found")
audio_path = config.resolve_storage_path(sample.audio_path)
if audio_path is None or not audio_path.is_file():
if audio_path is None or not audio_path.exists():
raise HTTPException(status_code=404, detail="Audio file not found")
return FileResponse(
-4
View File
@@ -26,10 +26,6 @@ async def download_cuda_backend():
"""Download the CUDA backend binary."""
from ..services import cuda
unsupported_reason = cuda.get_cuda_download_unsupported_reason()
if unsupported_reason:
raise HTTPException(status_code=409, detail=unsupported_reason)
if cuda.get_cuda_binary_path() is not None:
raise HTTPException(status_code=409, detail="CUDA backend already downloaded")
+6 -16
View File
@@ -13,7 +13,7 @@ from sqlalchemy.orm import Session
from .. import config, models
from ..services import tts
from ..database import get_db
from ..utils.platform_detect import get_backend_type, is_amd_gpu_windows
from ..utils.platform_detect import get_backend_type
router = APIRouter()
@@ -103,10 +103,7 @@ async def health():
gpu_type = None
if has_cuda:
if hasattr(torch.version, "hip") and torch.version.hip:
gpu_type = f"ROCm ({torch.cuda.get_device_name(0)})"
else:
gpu_type = f"CUDA ({torch.cuda.get_device_name(0)})"
gpu_type = f"CUDA ({torch.cuda.get_device_name(0)})"
elif has_mps:
gpu_type = "MPS (Apple Silicon)"
elif backend_type == "mlx":
@@ -167,15 +164,6 @@ async def health():
except Exception:
pass
default_variant = "cpu"
if has_cuda:
if hasattr(torch.version, "hip") and torch.version.hip:
default_variant = "rocm"
else:
default_variant = "cuda"
elif has_xpu:
default_variant = "xpu"
return models.HealthResponse(
status="healthy",
model_loaded=model_loaded,
@@ -185,8 +173,10 @@ async def health():
gpu_type=gpu_type,
vram_used_mb=vram_used,
backend_type=backend_type,
backend_variant=os.environ.get("VOICEBOX_BACKEND_VARIANT", default_variant),
supports_rocm=is_amd_gpu_windows(),
backend_variant=os.environ.get(
"VOICEBOX_BACKEND_VARIANT",
"cuda" if torch.cuda.is_available() else ("xpu" if has_xpu else "cpu"),
),
gpu_compatibility_warning=gpu_compat_warning,
)
+4 -7
View File
@@ -66,7 +66,7 @@ async def unload_model():
from ..services import tts
try:
await tts.unload_tts_model()
tts.unload_tts_model()
return {"message": "Model unloaded successfully"}
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
@@ -82,7 +82,7 @@ async def unload_model_by_name(model_name: str):
raise HTTPException(status_code=400, detail=f"Unknown model: {model_name}")
try:
was_loaded = await unload_model_by_config(config)
was_loaded = unload_model_by_config(config)
if not was_loaded:
return {"message": f"Model {model_name} is not loaded"}
return {"message": f"Model {model_name} unloaded successfully"}
@@ -231,10 +231,7 @@ async def get_model_status():
backend_type = get_backend_type()
task_manager = get_task_manager()
# Pending only — an errored task stays in the active list for the
# error/retry UI, but reporting it as "downloading" here would mask
# the model's real cache state until the app restarts (issue #925).
active_download_names = {task.model_name for task in task_manager.get_pending_downloads()}
active_download_names = {task.model_name for task in task_manager.get_active_downloads()}
try:
from huggingface_hub import scan_cache_dir
@@ -457,7 +454,7 @@ async def delete_model(model_name: str):
hf_repo_id = config.hf_repo_id
try:
await unload_model_by_config(config)
unload_model_by_config(config)
cache_dir = hf_constants.HF_HUB_CACHE
repo_cache_dir = Path(cache_dir) / ("models--" + hf_repo_id.replace("/", "--"))
-79
View File
@@ -1,79 +0,0 @@
"""ROCm backend management endpoints."""
import logging
from fastapi import APIRouter, HTTPException
from fastapi.responses import StreamingResponse
from ..services.task_queue import create_background_task
from ..utils.progress import get_progress_manager
router = APIRouter()
logger = logging.getLogger(__name__)
@router.get("/backend/rocm-status")
async def get_rocm_status():
"""Get ROCm backend download/availability status."""
from ..services import rocm
return rocm.get_rocm_status()
@router.post("/backend/download-rocm")
async def download_rocm_backend():
"""Download the ROCm backend binary."""
from ..services import rocm
progress_manager = get_progress_manager()
existing = progress_manager.get_progress(rocm.PROGRESS_KEY)
if existing and existing.get("status") in {"downloading", "extracting"}:
raise HTTPException(status_code=409, detail="ROCm backend download already in progress")
async def _download():
try:
await rocm.download_rocm_binary()
except Exception as e:
logger.error("ROCm download failed: %s", e)
create_background_task(_download())
return {"message": "ROCm backend download started", "progress_key": rocm.PROGRESS_KEY}
@router.delete("/backend/rocm")
async def delete_rocm_backend():
"""Delete the downloaded ROCm backend binary."""
from ..services import rocm
if rocm.is_rocm_active():
raise HTTPException(
status_code=409,
detail="Cannot delete ROCm backend while it is active. Switch to CPU first.",
)
deleted = await rocm.delete_rocm_binary()
if not deleted:
raise HTTPException(status_code=404, detail="No ROCm backend found to delete")
return {"message": "ROCm backend deleted"}
@router.get("/backend/rocm-progress")
async def get_rocm_download_progress():
"""Get ROCm backend download progress via Server-Sent Events."""
progress_manager = get_progress_manager()
async def event_generator():
async for event in progress_manager.subscribe("rocm-backend"):
yield event
return StreamingResponse(
event_generator(),
media_type="text/event-stream",
headers={
"Cache-Control": "no-cache",
"Connection": "keep-alive",
"X-Accel-Buffering": "no",
},
)
+1 -8
View File
@@ -15,10 +15,6 @@ router = APIRouter()
UPLOAD_CHUNK_SIZE = 1024 * 1024 # 1MB
# Same set profiles.py accepts for voice samples. librosa picks its decoder from the
# file extension, so the temp file has to keep the uploaded one.
ALLOWED_AUDIO_EXTS = {".wav", ".mp3", ".m4a", ".ogg", ".flac", ".aac", ".webm", ".opus"}
@router.post("/transcribe", response_model=models.TranscriptionResponse)
async def transcribe_audio(
@@ -27,10 +23,7 @@ async def transcribe_audio(
model: str | None = Form(None),
):
"""Transcribe audio file to text."""
uploaded_ext = Path(file.filename or "").suffix.lower()
file_suffix = uploaded_ext if uploaded_ext in ALLOWED_AUDIO_EXTS else ".wav"
with tempfile.NamedTemporaryFile(suffix=file_suffix, delete=False) as tmp:
with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as tmp:
while chunk := await file.read(UPLOAD_CHUNK_SIZE):
tmp.write(chunk)
tmp_path = tmp.name
+10 -13
View File
@@ -7,7 +7,6 @@ absolute imports instead of relative imports.
import sys
import os
import re
# On Windows with --noconsole (PyInstaller), sys.stdout/stderr are None.
# They can also be broken file objects in some edge cases.
@@ -48,17 +47,6 @@ if "--version" in sys.argv:
print(f"voicebox-server {__version__}")
sys.exit(0)
# Detect backend variant from binary name BEFORE importing backend modules
# so that env-var guards in app.py (e.g. HSA_OVERRIDE_GFX_VERSION) fire at import time.
_binary_name = os.path.basename(sys.executable).lower()
if re.search(r"voicebox-server-rocm(\.exe)?$", _binary_name):
os.environ["VOICEBOX_BACKEND_VARIANT"] = "rocm"
elif re.search(r"voicebox-server-cuda(\.exe)?$", _binary_name):
os.environ["VOICEBOX_BACKEND_VARIANT"] = "cuda"
else:
os.environ.setdefault("VOICEBOX_BACKEND_VARIANT", "cpu")
import logging
# Set up logging FIRST, before any imports that might fail
@@ -272,7 +260,16 @@ if __name__ == "__main__":
if args.parent_pid is not None and args.parent_pid <= 0:
parser.error("--parent-pid must be a positive integer")
logger.info(f"Backend variant: {os.environ.get('VOICEBOX_BACKEND_VARIANT', 'cpu').upper()}")
# Detect backend variant from binary name
# voicebox-server-cuda → sets VOICEBOX_BACKEND_VARIANT=cuda
import os
binary_name = os.path.basename(sys.executable).lower()
if "cuda" in binary_name:
os.environ["VOICEBOX_BACKEND_VARIANT"] = "cuda"
logger.info("Backend variant: CUDA")
else:
os.environ["VOICEBOX_BACKEND_VARIANT"] = "cpu"
logger.info("Backend variant: CPU")
# Register parent watchdog to start after server is fully ready
if args.parent_pid is not None:
+1 -32
View File
@@ -21,9 +21,9 @@ import tarfile
from pathlib import Path
from typing import Optional
from .. import __version__
from ..config import get_data_dir
from ..utils.progress import get_progress_manager
from .. import __version__
logger = logging.getLogger(__name__)
@@ -31,8 +31,6 @@ GITHUB_RELEASES_URL = "https://github.com/jamiepine/voicebox/releases/download"
PROGRESS_KEY = "cuda-backend"
CUDA_DOWNLOAD_UNSUPPORTED_REASON = "Downloadable CUDA backend releases are currently only published for Windows."
# The current expected CUDA libs version. Bump this when we change the
# CUDA toolkit version or torch's CUDA dependency changes (e.g. cu126 -> cu128).
CUDA_LIBS_VERSION = "cu128-v1"
@@ -65,25 +63,6 @@ def get_cuda_exe_name() -> str:
return "voicebox-server-cuda"
def is_cuda_download_supported() -> bool:
"""Return whether this platform has a matching CUDA release asset."""
return sys.platform == "win32"
def get_cuda_download_unsupported_reason() -> str | None:
"""Explain why this platform cannot use the release-download flow."""
if is_cuda_download_supported():
return None
return CUDA_DOWNLOAD_UNSUPPORTED_REASON
def ensure_cuda_download_supported() -> None:
"""Raise if downloading would fetch an asset built for another platform."""
reason = get_cuda_download_unsupported_reason()
if reason:
raise RuntimeError(reason)
def get_cuda_binary_path() -> Optional[Path]:
"""Return path to the CUDA executable if it exists inside the onedir."""
p = get_cuda_dir() / get_cuda_exe_name()
@@ -124,15 +103,12 @@ def get_cuda_status() -> dict:
cuda_path = get_cuda_binary_path()
progress = progress_manager.get_progress(PROGRESS_KEY)
cuda_libs_version = get_installed_cuda_libs_version()
unsupported_reason = get_cuda_download_unsupported_reason()
return {
"available": cuda_path is not None,
"active": is_cuda_active(),
"binary_path": str(cuda_path) if cuda_path else None,
"cuda_libs_version": cuda_libs_version,
"download_supported": unsupported_reason is None,
"unsupported_reason": unsupported_reason,
"downloading": progress is not None and progress.get("status") == "downloading",
"download_progress": progress,
}
@@ -281,8 +257,6 @@ async def download_cuda_binary(version: Optional[str] = None):
async def _download_cuda_binary_locked(version: Optional[str] = None):
"""Inner implementation of download_cuda_binary, called under _download_lock."""
ensure_cuda_download_supported()
import httpx
if version is None:
@@ -413,11 +387,6 @@ async def check_and_update_cuda_binary():
if not cuda_path:
return # No CUDA binary installed, nothing to update
unsupported_reason = get_cuda_download_unsupported_reason()
if unsupported_reason:
logger.info("Skipping CUDA backend auto-update: %s", unsupported_reason)
return
need_server = _needs_server_download()
need_libs = _needs_cuda_libs_download()
+4 -4
View File
@@ -2,7 +2,7 @@
LLM inference module - delegates to backend abstraction layer.
"""
from ..backends import LLMBackend, get_llm_backend, unload_backend
from ..backends import get_llm_backend, LLMBackend
def get_llm_model() -> LLMBackend:
@@ -10,6 +10,6 @@ def get_llm_model() -> LLMBackend:
return get_llm_backend()
async def unload_llm_model() -> None:
"""Unload LLM model to free memory, serialized onto the MLX worker."""
await unload_backend(get_llm_backend())
def unload_llm_model() -> None:
"""Unload LLM model to free memory."""
get_llm_backend().unload_model()
-39
View File
@@ -1,39 +0,0 @@
"""Single dedicated worker thread for all MLX GPU work.
MLX's Metal command encoder/stream is thread-local: it binds to whichever
thread first touches the GPU device. ``asyncio.to_thread()`` uses the event
loop's default executor, which hands successive calls to different worker
threads — a model loaded on one thread and generated on another raises
"There is no Stream(gpu, N) in current thread" (issue #699).
Routing every MLX load, generate, transcribe and unload through this one
worker keeps them on a single thread. Because the pool has a single worker,
submitted jobs also run to completion one at a time in submission order, so a
load-then-infer pair submitted as one job cannot be interleaved with an unload
or a different-size load from another request.
"""
import asyncio
from concurrent.futures import ThreadPoolExecutor
_mlx_executor = ThreadPoolExecutor(max_workers=1, thread_name_prefix="mlx-worker")
def run_on_mlx_thread(func, *args):
"""Run ``func(*args)`` on the single dedicated MLX worker thread."""
loop = asyncio.get_running_loop()
return loop.run_in_executor(_mlx_executor, func, *args)
def clear_mlx_cache() -> None:
"""Return MLX's cached unified memory to the OS after a model is freed.
Must run on the MLX worker thread (call it from an unload that is already
routed through ``run_on_mlx_thread``). ``clear_cache`` moved out of the
``mlx.core.metal`` namespace in newer MLX, so resolve it from either.
"""
import mlx.core as mx
clear = getattr(mx, "clear_cache", None) or getattr(getattr(mx, "metal", None), "clear_cache", None)
if clear is not None:
clear()
-467
View File
@@ -1,467 +0,0 @@
"""
ROCm backend download, assembly, and verification.
Downloads two archives from GitHub Releases:
1. Server core (voicebox-server-rocm.tar.gz) — the exe + non-AMD deps,
versioned with the app.
2. ROCm libs (rocm-libs-{version}.tar.gz) — AMD runtime libraries,
versioned independently (only redownloaded on ROCm toolkit bump).
Both archives are extracted into {data_dir}/backends/rocm/ which forms the
complete PyInstaller --onedir directory structure that torch expects.
"""
import asyncio
import hashlib
import json
import logging
import os
import shutil
import sys
import tarfile
from pathlib import Path
from typing import Optional
from ..config import get_data_dir
from ..utils.progress import get_progress_manager
from .. import __version__
logger = logging.getLogger(__name__)
GITHUB_RELEASES_URL = "https://github.com/jamiepine/voicebox/releases/download"
PROGRESS_KEY = "rocm-backend"
# The current expected ROCm libs version. Bump this when we change the
# ROCm toolkit version or torch's ROCm dependency changes (e.g. rocm7.2 -> rocm7.4).
ROCM_LIBS_VERSION = "rocm7.2-v1"
# Prevents concurrent download_rocm_binary() calls from racing on the same
# temp file. The auto-update background task and the manual HTTP endpoint
# can both invoke download_rocm_binary(); without this lock the progress-
# manager status check is a TOCTOU race.
_download_lock = asyncio.Lock()
def get_backends_dir() -> Path:
"""Directory where downloaded backend binaries are stored."""
d = get_data_dir() / "backends"
d.mkdir(parents=True, exist_ok=True)
return d
def get_rocm_dir() -> Path:
"""Directory where the ROCm backend (onedir) is extracted."""
d = get_backends_dir() / "rocm"
d.mkdir(parents=True, exist_ok=True)
return d
def get_rocm_exe_name() -> str:
"""Platform-specific ROCm executable filename."""
if sys.platform == "win32":
return "voicebox-server-rocm.exe"
return "voicebox-server-rocm"
def get_rocm_binary_path() -> Optional[Path]:
"""Return path to the ROCm executable if it exists inside the onedir."""
p = get_rocm_dir() / get_rocm_exe_name()
if p.exists():
return p
return None
def get_rocm_libs_manifest_path() -> Path:
"""Path to the rocm-libs.json manifest inside the ROCm dir."""
return get_rocm_dir() / "rocm-libs.json"
def get_installed_rocm_libs_version() -> Optional[str]:
"""Read the installed ROCm libs version from rocm-libs.json, or None."""
manifest_path = get_rocm_libs_manifest_path()
if not manifest_path.exists():
return None
try:
data = json.loads(manifest_path.read_text())
return data.get("version")
except Exception as e:
logger.warning(f"Could not read rocm-libs.json: {e}")
return None
def is_rocm_active() -> bool:
"""Check if the current process is the ROCm binary.
The ROCm binary sets this env var on startup (see server.py).
"""
return os.environ.get("VOICEBOX_BACKEND_VARIANT") == "rocm"
def get_rocm_status() -> dict:
"""Get current ROCm backend status for the API."""
progress_manager = get_progress_manager()
rocm_path = get_rocm_binary_path()
progress = progress_manager.get_progress(PROGRESS_KEY)
rocm_libs_version = get_installed_rocm_libs_version()
return {
"available": rocm_path is not None,
"active": is_rocm_active(),
"binary_path": str(rocm_path) if rocm_path else None,
"rocm_libs_version": rocm_libs_version,
"downloading": progress is not None and progress.get("status") == "downloading",
"download_progress": progress,
}
def _needs_server_download(version: Optional[str] = None) -> bool:
"""Check if the server core archive needs to be (re)downloaded."""
rocm_path = get_rocm_binary_path()
if not rocm_path:
return True
# Check if the binary version matches the expected app version
installed = get_rocm_binary_version()
expected = version or __version__
if expected.startswith("v"):
expected = expected[1:]
return installed != expected
def _needs_rocm_libs_download() -> bool:
"""Check if the ROCm libs archive needs to be (re)downloaded."""
installed = get_installed_rocm_libs_version()
if installed is None:
return True
return installed != ROCM_LIBS_VERSION
async def _download_and_extract_archive(
client,
url: str,
sha256_url: Optional[str],
dest_dir: Path,
label: str,
progress_offset: int,
total_size: int,
):
"""Download a .tar.gz archive and extract it into dest_dir.
Args:
client: httpx.AsyncClient
url: URL of the .tar.gz archive
sha256_url: URL of the .sha256 checksum file (optional)
dest_dir: Directory to extract into
label: Human-readable label for progress updates
progress_offset: Byte offset for progress reporting (when downloading
multiple archives sequentially)
total_size: Total bytes across all downloads (for progress bar)
"""
progress = get_progress_manager()
temp_path = dest_dir / f".download-{label.replace(' ', '-')}.tmp"
# Clean up leftover partial download
if temp_path.exists():
temp_path.unlink()
# Fetch expected checksum (fail-fast: never extract an unverified archive)
expected_sha = None
if sha256_url:
try:
sha_resp = await client.get(sha256_url)
sha_resp.raise_for_status()
expected_sha = sha_resp.text.strip().split()[0]
logger.info(f"{label}: expected SHA-256: {expected_sha[:16]}...")
except Exception as e:
raise RuntimeError(f"{label}: failed to fetch checksum from {sha256_url}") from e
# Stream download, verify, and extract — always clean up temp file
downloaded = 0
try:
async with client.stream("GET", url) as response:
response.raise_for_status()
with open(temp_path, "wb") as f:
async for chunk in response.aiter_bytes(chunk_size=1024 * 1024):
f.write(chunk)
downloaded += len(chunk)
progress.update_progress(
PROGRESS_KEY,
current=progress_offset + downloaded,
total=total_size,
filename=f"Downloading {label}",
status="downloading",
)
# Verify integrity
if expected_sha:
progress.update_progress(
PROGRESS_KEY,
current=progress_offset + downloaded,
total=total_size,
filename=f"Verifying {label}...",
status="downloading",
)
sha256 = hashlib.sha256()
with open(temp_path, "rb") as f:
while True:
data = f.read(1024 * 1024)
if not data:
break
sha256.update(data)
actual = sha256.hexdigest()
if actual != expected_sha:
raise ValueError(
f"{label} integrity check failed: expected {expected_sha[:16]}..., got {actual[:16]}..."
)
logger.info(f"{label}: integrity verified")
# Extract (use data filter for path traversal protection on Python 3.12+)
progress.update_progress(
PROGRESS_KEY,
current=progress_offset + downloaded,
total=total_size,
filename=f"Extracting {label}...",
status="downloading",
)
with tarfile.open(temp_path, "r:gz") as tar:
tar.extractall(path=dest_dir, filter="data")
logger.info(f"{label}: extracted to {dest_dir}")
finally:
if temp_path.exists():
temp_path.unlink()
return downloaded
async def download_rocm_binary(version: Optional[str] = None):
"""Download the ROCm backend (server core + ROCm libs if needed).
Downloads both archives from GitHub Releases, extracts them into
{data_dir}/backends/rocm/, and writes the rocm-libs.json manifest.
Only downloads what's needed:
- Server core: always redownloaded (versioned with app)
- ROCm libs: only if missing or version mismatch
Args:
version: Version tag (e.g. "v0.3.0"). Defaults to current app version.
"""
if _download_lock.locked():
logger.info("ROCm download already in progress, skipping duplicate request")
return
async with _download_lock:
await _download_rocm_binary_locked(version)
async def _download_rocm_binary_locked(version: Optional[str] = None):
"""Inner implementation of download_rocm_binary, called under _download_lock."""
import httpx
if version is None:
version = f"v{__version__}"
progress = get_progress_manager()
rocm_dir = get_rocm_dir()
need_server = _needs_server_download(version)
need_libs = _needs_rocm_libs_download()
if not need_server and not need_libs:
logger.info("ROCm backend is up to date, nothing to download")
return
logger.info(
f"Starting ROCm backend download for {version} "
f"(server={'yes' if need_server else 'cached'}, "
f"libs={'yes' if need_libs else 'cached'})"
)
progress.update_progress(
PROGRESS_KEY,
current=0,
total=0,
filename="Preparing download...",
status="downloading",
)
# Server core and libs archive are both published under the app-version
# release tag; the libs content version is encoded in the filename only.
server_base_url = f"{GITHUB_RELEASES_URL}/{version}"
libs_base_url = server_base_url
server_archive = "voicebox-server-rocm.tar.gz"
libs_archive = f"rocm-libs-{ROCM_LIBS_VERSION}.tar.gz"
# Always stage when any download is needed, then atomically rename over
# rocm_dir on success. This prevents a failed mid-extraction from leaving
# rocm_dir in a partially-installed state that still passes the
# get_rocm_binary_path() existence check. Existing files are pre-copied
# into staging so partial updates (e.g. libs-only or server-only) preserve
# whatever isn't being re-downloaded.
use_staging = need_server or need_libs
staging_dir = get_backends_dir() / "rocm-staging"
if use_staging:
if staging_dir.exists():
shutil.rmtree(staging_dir)
staging_dir.mkdir(parents=True, exist_ok=True)
# Preserve existing files (server or libs) that don't need re-downloading.
# Extracted archives will overwrite only what we actually download.
if rocm_dir.exists():
shutil.copytree(rocm_dir, staging_dir, dirs_exist_ok=True)
extract_dir = staging_dir
else:
extract_dir = rocm_dir
try:
async with httpx.AsyncClient(follow_redirects=True, timeout=30.0) as client:
# Estimate total download size
total_size = 0
if need_server:
try:
head = await client.head(f"{server_base_url}/{server_archive}")
total_size += int(head.headers.get("content-length", 0))
except Exception:
pass
if need_libs:
try:
head = await client.head(f"{libs_base_url}/{libs_archive}")
total_size += int(head.headers.get("content-length", 0))
except Exception:
pass
logger.info(f"Total download size: {total_size / 1024 / 1024:.1f} MB")
offset = 0
# Download server core
if need_server:
server_downloaded = await _download_and_extract_archive(
client,
url=f"{server_base_url}/{server_archive}",
sha256_url=f"{server_base_url}/{server_archive}.sha256",
dest_dir=extract_dir,
label="ROCm server",
progress_offset=offset,
total_size=total_size,
)
offset += server_downloaded
# Make executable on Unix
exe_path = extract_dir / get_rocm_exe_name()
if sys.platform != "win32" and exe_path.exists():
exe_path.chmod(0o755)
# Download ROCm libs
if need_libs:
await _download_and_extract_archive(
client,
url=f"{libs_base_url}/{libs_archive}",
sha256_url=f"{libs_base_url}/{libs_archive}.sha256",
dest_dir=extract_dir,
label="ROCm libraries",
progress_offset=offset,
total_size=total_size,
)
# Write local rocm-libs.json manifest
manifest = {"version": ROCM_LIBS_VERSION}
(extract_dir / "rocm-libs.json").write_text(json.dumps(manifest, indent=2) + "\n")
# Atomic swap: replace rocm_dir with the fully-extracted staging dir
if use_staging:
backup_dir = get_backends_dir() / "rocm-backup"
if backup_dir.exists():
shutil.rmtree(backup_dir)
if rocm_dir.exists():
rocm_dir.rename(backup_dir)
try:
staging_dir.rename(rocm_dir)
except Exception:
if backup_dir.exists() and not rocm_dir.exists():
backup_dir.rename(rocm_dir)
raise
else:
if backup_dir.exists():
shutil.rmtree(backup_dir)
logger.info(f"ROCm backend ready at {rocm_dir}")
progress.mark_complete(PROGRESS_KEY)
except Exception as e:
if use_staging and staging_dir.exists():
shutil.rmtree(staging_dir)
logger.error(f"ROCm backend download failed: {e}")
progress.mark_error(PROGRESS_KEY, str(e))
raise
def get_rocm_binary_version() -> Optional[str]:
"""Get the version of the installed ROCm binary, or None if not installed."""
import subprocess
rocm_path = get_rocm_binary_path()
if not rocm_path:
return None
try:
result = subprocess.run(
[str(rocm_path), "--version"],
capture_output=True,
text=True,
timeout=30,
cwd=str(rocm_path.parent), # Run from the onedir directory
)
# Output format: "voicebox-server 0.3.0"
for line in result.stdout.strip().splitlines():
if "voicebox-server" in line:
return line.split()[-1]
except Exception as e:
logger.warning(f"Could not get ROCm binary version: {e}")
return None
async def check_and_update_rocm_binary():
"""Check if the ROCm binary is outdated and auto-download if so.
Called on server startup. Checks both server version and ROCm libs
version. Downloads only what's needed.
"""
rocm_path = get_rocm_binary_path()
if not rocm_path:
return # No ROCm binary installed, nothing to update
if is_rocm_active():
logger.info("ROCm backend is active; skipping auto-update to avoid replacing the running backend")
return
need_server = _needs_server_download()
need_libs = _needs_rocm_libs_download()
if not need_server and not need_libs:
logger.info(f"ROCm binary is up to date (server=v{__version__}, libs={get_installed_rocm_libs_version()})")
return
reasons = []
if need_server:
rocm_version = get_rocm_binary_version()
reasons.append(f"server v{rocm_version} != v{__version__}")
if need_libs:
installed_libs = get_installed_rocm_libs_version()
reasons.append(f"libs {installed_libs} != {ROCM_LIBS_VERSION}")
logger.info(f"ROCm backend needs update ({', '.join(reasons)}). Auto-downloading...")
try:
await download_rocm_binary()
except Exception as e:
logger.error(f"Auto-update of ROCm binary failed: {e}")
async def delete_rocm_binary() -> bool:
"""Delete the downloaded ROCm backend directory. Returns True if deleted."""
import shutil
rocm_dir = get_rocm_dir()
if rocm_dir.exists() and any(rocm_dir.iterdir()):
shutil.rmtree(rocm_dir)
logger.info(f"Deleted ROCm backend directory: {rocm_dir}")
return True
return False
+3 -15
View File
@@ -125,24 +125,12 @@ async def list_stories(
"""
stories = db.query(DBStory).order_by(DBStory.updated_at.desc()).all()
if not stories:
return []
# Batch-fetch all story item counts in one query to avoid an N+1 pattern
# (previously there was one COUNT query per story in the loop below).
story_ids = [s.id for s in stories]
count_rows = (
db.query(DBStoryItem.story_id, func.count(DBStoryItem.id).label("cnt"))
.filter(DBStoryItem.story_id.in_(story_ids))
.group_by(DBStoryItem.story_id)
.all()
)
item_counts = {row.story_id: row.cnt for row in count_rows}
result = []
for story in stories:
item_count = db.query(func.count(DBStoryItem.id)).filter(DBStoryItem.story_id == story.id).scalar()
response = StoryResponse.model_validate(story)
response.item_count = item_counts.get(story.id, 0)
response.item_count = item_count
result.append(response)
return result
+7 -5
View File
@@ -2,19 +2,21 @@
STT (Speech-to-Text) module - delegates to backend abstraction layer.
"""
from ..backends import STTBackend, get_stt_backend, unload_backend
from typing import Optional
from ..backends import get_stt_backend, STTBackend
def get_whisper_model() -> STTBackend:
"""
Get STT backend instance (MLX or PyTorch based on platform).
Returns:
STT backend instance
"""
return get_stt_backend()
async def unload_whisper_model():
"""Unload Whisper model to free memory, serialized onto the MLX worker."""
await unload_backend(get_stt_backend())
def unload_whisper_model():
"""Unload Whisper model to free memory."""
backend = get_stt_backend()
backend.unload_model()
+8 -7
View File
@@ -2,27 +2,28 @@
TTS inference module - delegates to backend abstraction layer.
"""
import io
from typing import Optional
import numpy as np
import io
import soundfile as sf
from ..backends import TTSBackend, get_tts_backend, unload_backend
from ..backends import get_tts_backend, TTSBackend
def get_tts_model() -> TTSBackend:
"""
Get TTS backend instance (MLX or PyTorch based on platform).
Returns:
TTS backend instance
"""
return get_tts_backend()
async def unload_tts_model():
"""Unload TTS model to free memory, serialized onto the MLX worker."""
await unload_backend(get_tts_backend())
def unload_tts_model():
"""Unload TTS model to free memory."""
backend = get_tts_backend()
backend.unload_model()
def audio_to_wav_bytes(audio: np.ndarray, sample_rate: int) -> bytes:
-96
View File
@@ -1,96 +0,0 @@
"""
Phase 2.1 Test: AMD GPU detection on Windows.
Validates is_amd_gpu_windows() via mocked WMI and torch queries.
Usage:
python -m pytest backend/tests/test_amd_gpu_detect.py -v
"""
from unittest.mock import MagicMock, patch
import pytest
from backend.utils.platform_detect import is_amd_gpu_windows
class TestAmdGpuWindows:
"""Unit tests for is_amd_gpu_windows with mocks."""
@pytest.fixture(autouse=True)
def _clear_detection_cache(self):
# is_amd_gpu_windows is memoized; reset between cases so each mock takes effect.
is_amd_gpu_windows.cache_clear()
yield
is_amd_gpu_windows.cache_clear()
@patch("backend.utils.platform_detect.platform.system", return_value="Linux")
def test_returns_false_on_linux(self, _mock_system):
"""Non-Windows platforms should always return False."""
assert is_amd_gpu_windows() is False
@patch("backend.utils.platform_detect.platform.system", return_value="Windows")
@patch(
"backend.utils.platform_detect.subprocess.run",
return_value=MagicMock(stdout="1\n", returncode=0),
)
def test_detects_amd_via_wmi(self, _mock_run, _mock_system):
"""WMI reporting an AMD adapter should return True."""
assert is_amd_gpu_windows() is True
@patch("backend.utils.platform_detect.platform.system", return_value="Windows")
@patch(
"backend.utils.platform_detect.subprocess.run",
return_value=MagicMock(stdout="0\n", returncode=0),
)
def test_no_amd_via_wmi(self, _mock_run, _mock_system):
"""WMI reporting zero AMD adapters should return False."""
assert is_amd_gpu_windows() is False
@patch("backend.utils.platform_detect.platform.system", return_value="Windows")
@patch(
"backend.utils.platform_detect.subprocess.run",
side_effect=Exception("WMI not available"),
)
@patch("torch.cuda.is_available", return_value=True)
@patch(
"torch.cuda.get_device_name",
return_value="AMD Radeon RX 7800 XT",
)
def test_fallback_to_torch_radeon(self, _mock_name, _mock_avail, _mock_run, _mock_system):
"""When WMI fails, torch.cuda.get_device_name('Radeon') should return True."""
assert is_amd_gpu_windows() is True
@patch("backend.utils.platform_detect.platform.system", return_value="Windows")
@patch(
"backend.utils.platform_detect.subprocess.run",
side_effect=Exception("WMI not available"),
)
@patch("torch.cuda.is_available", return_value=True)
@patch(
"torch.cuda.get_device_name",
return_value="NVIDIA GeForce RTX 4090",
)
def test_fallback_to_torch_nvidia(self, _mock_name, _mock_avail, _mock_run, _mock_system):
"""When WMI fails, torch.cuda.get_device_name('NVIDIA') should return False."""
assert is_amd_gpu_windows() is False
@patch("backend.utils.platform_detect.platform.system", return_value="Windows")
@patch(
"backend.utils.platform_detect.subprocess.run",
side_effect=Exception("WMI not available"),
)
@patch("torch.cuda.is_available", return_value=False)
def test_no_torch_cuda(self, _mock_avail, _mock_run, _mock_system):
"""When WMI fails and torch.cuda is unavailable, should return False."""
assert is_amd_gpu_windows() is False
@patch("backend.utils.platform_detect.platform.system", return_value="Windows")
@patch(
"backend.utils.platform_detect.subprocess.run",
side_effect=Exception("WMI not available"),
)
def test_torch_not_installed(self, _mock_run, _mock_system):
"""When torch is not installed, should return False without crashing."""
with patch.dict("sys.modules", {"torch": None}):
assert is_amd_gpu_windows() is False
@@ -1,164 +0,0 @@
"""
Regression tests for GET /audio/{generation_id} on failed generations.
A failed generation stores an empty ``audio_path``. Previously,
``config.resolve_storage_path("")`` resolved to the data directory itself,
which exists, so the route's 404 guard passed and ``FileResponse`` raised
``RuntimeError: File at path .../data is not a file`` — a 500 instead of
a clean 404.
Usage:
python -m pytest backend/tests/test_audio_failed_generation.py -v
"""
import sys
from pathlib import Path
import pytest
from fastapi import FastAPI
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from starlette.testclient import TestClient
# Repo root on sys.path so ``backend`` imports as a package (the audio
# routes use package-relative imports).
sys.path.insert(0, str(Path(__file__).parent.parent.parent))
from backend import config
from backend.database import (
Base,
Generation,
GenerationVersion,
ProfileSample,
VoiceProfile,
get_db,
)
from backend.routes.audio import router as audio_router
def test_resolve_storage_path_empty_returns_none():
"""An empty stored path must not resolve to the data dir itself."""
assert config.resolve_storage_path("") is None
assert config.resolve_storage_path(None) is None
# Path("") is truthy, so it must be rejected via its (empty) parts.
assert config.resolve_storage_path(Path("")) is None
@pytest.fixture
def client(tmp_path, monkeypatch):
"""Minimal app with only the audio routes and a temp sqlite DB."""
monkeypatch.setattr(config, "_data_dir", tmp_path)
# An existing directory that a stored audio_path may wrongly point to.
(tmp_path / "somedir").mkdir()
engine = create_engine(
f"sqlite:///{tmp_path / 'test.db'}",
connect_args={"check_same_thread": False},
)
Base.metadata.create_all(bind=engine)
testing_session_local = sessionmaker(autocommit=False, autoflush=False, bind=engine)
session = testing_session_local()
profile = VoiceProfile(id="profile-1", name="Test Profile")
session.add(profile)
session.add_all(
[
Generation(
id="gen-failed-empty",
profile_id="profile-1",
text="failed generation",
audio_path="",
status="failed",
error="engine exploded",
),
Generation(
id="gen-failed-null",
profile_id="profile-1",
text="failed generation",
audio_path=None,
status="failed",
),
Generation(
id="gen-missing-file",
profile_id="profile-1",
text="completed but file deleted",
audio_path="generations/does-not-exist.wav",
status="completed",
),
Generation(
id="gen-with-version",
profile_id="profile-1",
text="generation with a broken version",
audio_path="somedir",
status="completed",
),
GenerationVersion(
id="version-dir",
generation_id="gen-with-version",
label="original",
audio_path="somedir",
),
ProfileSample(
id="sample-dir",
profile_id="profile-1",
audio_path="somedir",
reference_text="sample pointing at a directory",
),
]
)
session.commit()
session.close()
app = FastAPI()
app.include_router(audio_router)
def override_get_db():
db = testing_session_local()
try:
yield db
finally:
db.close()
app.dependency_overrides[get_db] = override_get_db
return TestClient(app)
@pytest.mark.parametrize("generation_id", ["gen-failed-empty", "gen-failed-null"])
def test_failed_generation_returns_404(client, generation_id):
"""Failed generations (empty/null audio_path) get a clean 404, not a 500."""
response = client.get(f"/audio/{generation_id}")
assert response.status_code == 404
assert response.json()["detail"] == "Generation failed; no audio available"
def test_missing_audio_file_returns_404(client):
"""A completed generation whose file vanished still 404s."""
response = client.get("/audio/gen-missing-file")
assert response.status_code == 404
assert response.json()["detail"] == "Audio file not found"
def test_unknown_generation_returns_404(client):
response = client.get("/audio/no-such-generation")
assert response.status_code == 404
assert response.json()["detail"] == "Generation not found"
@pytest.mark.parametrize(
"url",
[
"/audio/gen-with-version",
"/audio/version/version-dir",
"/samples/sample-dir",
],
)
def test_audio_path_pointing_at_directory_returns_404(client, url):
"""A stored path resolving to an existing directory must 404, not 500.
Guards the is_file() checks: a directory passes exists() and would
crash FileResponse.
"""
response = client.get(url)
assert response.status_code == 404
assert response.json()["detail"] == "Audio file not found"
-123
View File
@@ -1,123 +0,0 @@
"""
Regression tests for issue #852: audioop removed from Python 3.13 stdlib.
Voice sample validation imports audioop transitively (librosa → audioread).
The audioop-lts backport must be declared in requirements and bundled in
PyInstaller builds on 3.13+.
"""
import re
import sys
from pathlib import Path
from unittest.mock import patch
import pytest
sys.path.insert(0, str(Path(__file__).parent.parent))
from build_binary import build_server
@pytest.fixture
def backend_dir():
return Path(__file__).parent.parent
class TestAudioopRequirements:
def test_requirements_declare_audioop_lts_for_python_313(self, backend_dir):
content = (backend_dir / "requirements.txt").read_text()
assert re.search(
r"^audioop-lts.*python_version\s*>=\s*['\"]3\.13['\"]",
content,
re.MULTILINE,
), "requirements.txt must pin audioop-lts for Python 3.13+"
@pytest.mark.skipif(sys.version_info < (3, 13), reason="Python 3.13+ only")
class TestAudioopRuntime:
def test_audioop_importable(self):
import audioop # noqa: F401
def test_validate_reference_wav_does_not_fail_on_missing_audioop(self, tmp_path):
import numpy as np
import soundfile as sf
from utils.audio import validate_and_load_reference_audio
sr = 24000
t = np.arange(int(sr * 3), dtype=np.float32) / sr
audio = (0.3 * np.sin(2 * np.pi * 220 * t)).astype(np.float32)
path = tmp_path / "reference.wav"
sf.write(str(path), audio, sr)
ok, err, out_audio, out_sr = validate_and_load_reference_audio(str(path))
assert ok, err
assert out_audio is not None
assert out_sr == sr
assert "audioop" not in (err or "").lower()
class TestAudioopBuildArgs:
@staticmethod
def _hidden_imports(args):
imports = []
for i, arg in enumerate(args):
if arg == "--hidden-import" and i + 1 < len(args):
imports.append(args[i + 1])
return imports
def test_pyinstaller_includes_audioop_on_python_313(self):
class FakeVersionInfo(tuple):
@property
def major(self):
return self[0]
@property
def minor(self):
return self[1]
@property
def micro(self):
return self[2]
fake_313 = FakeVersionInfo((3, 13, 0, "final", 0))
with (
patch("build_binary.PyInstaller.__main__.run") as mock_run,
patch("build_binary.platform.system", return_value="Linux"),
patch("build_binary.is_apple_silicon", return_value=False),
patch("build_binary.os.chdir"),
patch("build_binary.sys.version_info", fake_313),
):
build_server()
args = mock_run.call_args[0][0]
assert "audioop" in self._hidden_imports(args)
def test_pyinstaller_omits_audioop_on_python_312(self):
class FakeVersionInfo(tuple):
@property
def major(self):
return self[0]
@property
def minor(self):
return self[1]
@property
def micro(self):
return self[2]
fake_312 = FakeVersionInfo((3, 12, 0, "final", 0))
with (
patch("build_binary.PyInstaller.__main__.run") as mock_run,
patch("build_binary.platform.system", return_value="Linux"),
patch("build_binary.is_apple_silicon", return_value=False),
patch("build_binary.os.chdir"),
patch("build_binary.sys.version_info", fake_312),
):
build_server()
args = mock_run.call_args[0][0]
assert "audioop" not in self._hidden_imports(args)
-32
View File
@@ -1,32 +0,0 @@
import sys as py_sys
import types
import pytest
from backend.services import cuda
def test_cuda_status_reports_unsupported_linux_download(monkeypatch, tmp_path):
monkeypatch.setattr(cuda.sys, "platform", "linux")
monkeypatch.setattr(cuda, "get_data_dir", lambda: tmp_path)
status = cuda.get_cuda_status()
assert status["available"] is False
assert status["download_supported"] is False
assert status["unsupported_reason"] == cuda.CUDA_DOWNLOAD_UNSUPPORTED_REASON
@pytest.mark.asyncio
async def test_cuda_download_rejects_linux_before_network(monkeypatch, tmp_path):
monkeypatch.setattr(cuda.sys, "platform", "linux")
monkeypatch.setattr(cuda, "get_data_dir", lambda: tmp_path)
class UnexpectedClient:
def __init__(self, *args, **kwargs):
raise AssertionError("unsupported platforms should not start a release download")
monkeypatch.setitem(py_sys.modules, "httpx", types.SimpleNamespace(AsyncClient=UnexpectedClient))
with pytest.raises(RuntimeError, match="currently only published for Windows"):
await cuda._download_cuda_binary_locked("v0.5.0")
-55
View File
@@ -1,55 +0,0 @@
"""
Smoke test for the MLX backend dependencies on Apple Silicon.
Guards the `--no-deps` install of mlx-audio/mlx-lm done by `just setup-python`
and release.yml: those packages skip their declared dependencies (transformers
>=5.x conflict), so a missing transitive dep only surfaces at import time.
This test fails fast if the MLX STT/TTS entry points the backend uses stop
importing (e.g. the `miniaudio` regression from issue #505).
Usage:
python -m pytest backend/tests/test_mlx_smoke.py -v
"""
import platform
import sys
import pytest
pytestmark = pytest.mark.skipif(
not (sys.platform == "darwin" and platform.machine() == "arm64"),
reason="MLX packages are only installed on Apple Silicon macOS",
)
def test_mlx_core_runs():
"""The MLX runtime itself works (Metal array op)."""
import mlx.core as mx
assert mx.array([1, 2]).sum().item() == 3
def test_mlx_audio_tts_entry_point():
"""`from mlx_audio.tts import load` — used by MLXBackend.load_model_async."""
from mlx_audio.tts import load
assert callable(load)
def test_mlx_audio_stt_entry_point():
"""`from mlx_audio.stt import load` — used by the Whisper MLX STT path.
Importing mlx_audio.stt also pulls in miniaudio, so this catches the
ModuleNotFoundError from issue #505 on fresh installs.
"""
from mlx_audio.stt import load
assert callable(load)
def test_mlx_lm_entry_points():
"""`mlx_lm.load` / `mlx_lm.generate` — used by qwen_llm_backend."""
from mlx_lm import generate, load
assert callable(load)
assert callable(generate)
-128
View File
@@ -1,128 +0,0 @@
"""Regression tests for MLX single-thread serialization.
MLX's Metal stream is thread-local, so every load/generate/unload must run on
one dedicated worker thread (issue #699), and a load+infer pair must run as one
atomic job so a concurrent unload or different-size load can't land between the
load and the inference that reads the model.
These drive the real async orchestration on ``MLXQwenLLMBackend`` with the
heavy mlx-lm calls faked, so they exercise the shipped code paths without
needing MLX installed.
"""
import asyncio
import threading
import time
import pytest
from backend.backends.qwen_llm_backend import MLXQwenLLMBackend
from backend.services import llm as llm_service
from backend.services.mlx_thread import run_on_mlx_thread
@pytest.mark.asyncio
async def test_run_on_mlx_thread_uses_a_single_worker():
idents = set()
def record():
idents.add(threading.get_ident())
await asyncio.gather(*(run_on_mlx_thread(record) for _ in range(12)))
assert len(idents) == 1, "MLX work must stay pinned to one worker thread"
assert idents.pop() != threading.get_ident(), "MLX work must not run on the event loop thread"
def _install_fakes(backend, worker_threads):
"""Replace the heavy sync internals with fakes that record their thread.
``_load_model_sync`` and ``_generate_sync`` sleep briefly so that, if the
load and inference of one request were ever split into separate jobs, a
second request could interleave and be observed.
"""
def fake_load(model_size):
worker_threads.add(threading.get_ident())
time.sleep(0.02)
backend.model = {"size": model_size}
backend._current_model_size = model_size
backend.model_size = model_size
def fake_unload():
worker_threads.add(threading.get_ident())
backend.model = None
backend._current_model_size = None
def fake_generate(prompt, system, max_tokens, temperature, examples=None):
worker_threads.add(threading.get_ident())
# Capture the resident model, do "work", then confirm it wasn't
# swapped or freed underneath us — that is exactly the interleave the
# atomic load+infer job is meant to prevent.
resident = backend.model
assert resident is not None, "model was freed mid-generation"
time.sleep(0.02)
assert backend.model is resident, "model was swapped mid-generation"
return resident["size"]
backend._load_model_sync = fake_load
backend.unload_model = fake_unload
backend._generate_sync = fake_generate
@pytest.mark.asyncio
async def test_concurrent_generate_does_not_cross_models():
backend = MLXQwenLLMBackend()
worker_threads = set()
_install_fakes(backend, worker_threads)
small, large = await asyncio.gather(
backend.generate("a", model_size="0.6B"),
backend.generate("b", model_size="4B"),
)
assert small == "0.6B"
assert large == "4B"
assert len(worker_threads) == 1, "load and generate must share the one MLX thread"
@pytest.mark.asyncio
async def test_unload_cannot_free_model_mid_generation():
backend = MLXQwenLLMBackend()
worker_threads = set()
_install_fakes(backend, worker_threads)
await backend.load_model("0.6B")
# An unload issued while a generation is in flight must serialize behind it
# on the worker rather than free the model out from under it.
size, _ = await asyncio.gather(
backend.generate("a", model_size="0.6B"),
backend.unload(),
)
assert size == "0.6B"
assert backend.model is None, "unload should still take effect once generation completes"
assert len(worker_threads) == 1
@pytest.mark.asyncio
async def test_service_path_unload_serializes_with_generation(monkeypatch):
# The service unload helpers (tts/stt/llm) all route through unload_backend,
# which must serialize on the MLX worker rather than free the model on the
# event-loop thread mid-generation.
backend = MLXQwenLLMBackend()
worker_threads = set()
_install_fakes(backend, worker_threads)
monkeypatch.setattr(llm_service, "get_llm_backend", lambda: backend)
await backend.load_model("0.6B")
size, _ = await asyncio.gather(
backend.generate("a", model_size="0.6B"),
llm_service.unload_llm_model(),
)
assert size == "0.6B"
assert backend.model is None
assert len(worker_threads) == 1
@@ -1,51 +0,0 @@
"""Errored downloads must not be reported as still downloading.
A failed download intentionally stays in the TaskManager with
``status="error"`` so ``/tasks/active`` can surface the error and retry
UI — but ``/models/status`` derives its ``downloading`` flag from the
same list. Without a status filter, one failed download shows the model
as "downloading" forever and masks its real cache state until the app
restarts (issue #925, symptom reports like #181).
"""
from backend.utils.tasks import TaskManager
def test_errored_download_is_not_pending():
tm = TaskManager()
tm.start_download("whisper-turbo")
assert [t.model_name for t in tm.get_pending_downloads()] == ["whisper-turbo"]
tm.error_download("whisper-turbo", "boom")
assert tm.get_pending_downloads() == []
# Still visible to /tasks/active for the error/retry UI.
active = tm.get_active_downloads()
assert [t.model_name for t in active] == ["whisper-turbo"]
assert active[0].status == "error"
assert active[0].error == "boom"
def test_retry_after_error_is_pending_again():
tm = TaskManager()
tm.start_download("qwen3-4b")
tm.error_download("qwen3-4b", "boom")
tm.start_download("qwen3-4b")
assert [t.model_name for t in tm.get_pending_downloads()] == ["qwen3-4b"]
def test_completed_download_is_removed_everywhere():
tm = TaskManager()
tm.start_download("whisper-turbo")
tm.complete_download("whisper-turbo")
assert tm.get_pending_downloads() == []
assert tm.get_active_downloads() == []
def test_cancel_dismisses_errored_download():
tm = TaskManager()
tm.start_download("whisper-turbo")
tm.error_download("whisper-turbo", "boom")
assert tm.cancel_download("whisper-turbo") is True
assert tm.get_active_downloads() == []
assert tm.get_pending_downloads() == []
-121
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@@ -1,121 +0,0 @@
"""
Tests for scripts/package_rocm.py — the ROCm onedir → server + libs splitter.
The classifier can't be validated against a real AMD build on CI hardware, so
these tests pin the file-classification rules against a synthetic onedir layout
that mirrors the PyInstaller --rocm output (torch/lib HIP DLLs + bundled
rocm_sdk runtime packages).
Usage:
python -m pytest backend/tests/test_package_rocm.py -v
"""
import importlib.util
import tarfile
from pathlib import Path
import pytest
_PACKAGE_ROCM = Path(__file__).resolve().parents[2] / "scripts" / "package_rocm.py"
_spec = importlib.util.spec_from_file_location("package_rocm", _PACKAGE_ROCM)
package_rocm = importlib.util.module_from_spec(_spec)
_spec.loader.exec_module(package_rocm)
class TestIsRocmFile:
"""Classification of individual files into core vs ROCm libs."""
@pytest.mark.parametrize(
"rel_path",
[
"_internal/torch/lib/amdhip64.dll",
"_internal/torch/lib/rocblas.dll",
"_internal/torch/lib/hipblaslt.dll",
"_internal/torch/lib/miopen.dll",
"_internal/_rocm_sdk_core/amd_comgr.dll",
"_internal/_rocm_sdk_libraries_custom/lib/rocblas/library/TensileLibrary.dat",
"_internal/_rocm_sdk_libraries_custom/lib/miopen/db/kernels.kdb",
# Windows path separators must be handled too.
"_internal\\torch\\lib\\rccl.dll",
],
)
def test_runtime_files_are_rocm(self, rel_path):
assert package_rocm.is_rocm_file(rel_path) is True
@pytest.mark.parametrize(
"rel_path",
[
"voicebox-server-rocm.exe",
"_internal/python312.dll",
"_internal/torch/lib/torch_cpu.dll",
"_internal/torch/lib/c10.dll",
# Pure-python rocm_sdk glue stays in the core, even under an SDK dir.
"_internal/rocm_sdk/__init__.py",
"_internal/_rocm_sdk_core/_dist_info.py",
"_internal/torch/_inductor/codegen/something.py",
],
)
def test_core_files_are_not_rocm(self, rel_path):
assert package_rocm.is_rocm_file(rel_path) is False
def _write(path: Path, content: bytes = b"x"):
path.parent.mkdir(parents=True, exist_ok=True)
path.write_bytes(content)
class TestPackage:
"""End-to-end split of a synthetic onedir into the two archives."""
def test_split_and_manifest(self, tmp_path):
onedir = tmp_path / "voicebox-server-rocm"
_write(onedir / "voicebox-server-rocm.exe")
_write(onedir / "_internal" / "python312.dll")
_write(onedir / "_internal" / "rocm_sdk" / "__init__.py")
_write(onedir / "_internal" / "torch" / "lib" / "torch_cpu.dll")
_write(onedir / "_internal" / "torch" / "lib" / "amdhip64.dll")
_write(onedir / "_internal" / "_rocm_sdk_core" / "miopen.dll")
_write(
onedir
/ "_internal"
/ "_rocm_sdk_libraries_custom"
/ "lib"
/ "rocblas"
/ "library"
/ "TensileLibrary.dat"
)
out = tmp_path / "release-assets"
package_rocm.package(onedir, out, "rocm7.2-v1", ">=2.9.0,<2.10.0")
server = out / "voicebox-server-rocm.tar.gz"
libs = out / "rocm-libs-rocm7.2-v1.tar.gz"
assert server.exists()
assert libs.exists()
assert (out / "voicebox-server-rocm.tar.gz.sha256").exists()
assert (out / "rocm-libs-rocm7.2-v1.tar.gz.sha256").exists()
with tarfile.open(libs) as tar:
lib_names = set(tar.getnames())
with tarfile.open(server) as tar:
core_names = set(tar.getnames())
assert "_internal/torch/lib/amdhip64.dll" in lib_names
assert "_internal/_rocm_sdk_core/miopen.dll" in lib_names
assert (
"_internal/_rocm_sdk_libraries_custom/lib/rocblas/library/TensileLibrary.dat"
in lib_names
)
assert "voicebox-server-rocm.exe" in core_names
assert "_internal/torch/lib/torch_cpu.dll" in core_names
assert "_internal/rocm_sdk/__init__.py" in core_names
# Archives must be disjoint.
assert lib_names.isdisjoint(core_names)
def test_empty_rocm_set_exits(self, tmp_path):
onedir = tmp_path / "voicebox-server-rocm"
_write(onedir / "voicebox-server-rocm.exe")
_write(onedir / "_internal" / "torch" / "lib" / "torch_cpu.dll")
with pytest.raises(SystemExit):
package_rocm.package(onedir, tmp_path / "out", "rocm7.2-v1", ">=2.9.0,<2.10.0")
-68
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@@ -1,68 +0,0 @@
"""
Phase 2.2 Test: Backend ROCm compatibility.
Validates that check_cuda_compatibility() and other backend utilities
behave correctly on ROCm/AMD hardware.
Usage:
python -m pytest backend/tests/test_rocm_backends.py -v
"""
from unittest.mock import patch
import pytest
class TestCheckCudaCompatibility:
"""Unit tests for check_cuda_compatibility with ROCm awareness."""
def test_no_gpu_returns_compatible(self):
from backend.backends.base import check_cuda_compatibility
with patch("torch.cuda.is_available", return_value=False):
compatible, warning = check_cuda_compatibility()
assert compatible is True
assert warning is None
def test_rocm_skips_compute_check(self):
"""On ROCm, the NVIDIA compute-capability check should be skipped."""
from backend.backends.base import check_cuda_compatibility
with patch("torch.cuda.is_available", return_value=True):
with patch("torch.version.hip", "6.2.41133"):
compatible, warning = check_cuda_compatibility()
assert compatible is True
assert warning is None
def test_cuda_compatible_arch(self):
from backend.backends.base import check_cuda_compatibility
with patch("torch.cuda.is_available", return_value=True):
with patch("torch.version.hip", None):
with patch("torch.cuda.get_device_capability", return_value=(8, 6)):
with patch("torch.cuda.get_device_name", return_value="NVIDIA GeForce RTX 3060"):
with patch.object(
__import__("torch").cuda, "_get_arch_list",
return_value=["sm_80", "sm_86", "sm_89"],
create=True,
):
compatible, warning = check_cuda_compatibility()
assert compatible is True
assert warning is None
def test_cuda_incompatible_arch(self):
from backend.backends.base import check_cuda_compatibility
with patch("torch.cuda.is_available", return_value=True):
with patch("torch.version.hip", None):
with patch("torch.cuda.get_device_capability", return_value=(9, 0)):
with patch("torch.cuda.get_device_name", return_value="NVIDIA GeForce RTX 4090"):
with patch.object(
__import__("torch").cuda, "_get_arch_list",
return_value=["sm_80", "sm_86"],
create=True,
):
compatible, warning = check_cuda_compatibility()
assert compatible is False
assert warning is not None
assert "not supported" in warning
-129
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@@ -1,129 +0,0 @@
"""
Phase 1.2 Test: ROCm build script configuration.
Validates that build_binary.py --rocm generates the correct PyInstaller
arguments and optionally performs a true E2E build.
Usage:
python -m pytest backend/tests/test_rocm_build.py -v
python -m pytest backend/tests/test_rocm_build.py -v -m "slow" # include E2E
"""
import subprocess
import sys
from pathlib import Path
from unittest.mock import patch
import pytest
from build_binary import build_server
class TestRocmBuildArgs:
"""Validate PyInstaller arguments for ROCm builds."""
@pytest.fixture
def captured_args(self):
"""Run build_server(rocm=True) with mocked PyInstaller and return args."""
with (
patch("build_binary.PyInstaller.__main__.run") as mock_run,
patch("build_binary.platform.system", return_value="Linux"),
patch("build_binary.os.chdir"),
):
build_server(rocm=True)
return mock_run.call_args[0][0]
def test_binary_name(self, captured_args):
idx = captured_args.index("--name")
assert captured_args[idx + 1] == "voicebox-server-rocm"
def test_pack_mode_is_onedir(self, captured_args):
assert "--onedir" in captured_args
assert "--onefile" not in captured_args
def test_hidden_imports_cuda(self, captured_args):
"""ROCm builds must include torch.cuda hidden imports."""
assert "torch.cuda" in captured_args
def test_no_cudnn_hidden_import_for_rocm(self, captured_args):
"""ROCm builds must NOT include NVIDIA-specific cudnn hidden imports."""
assert "torch.backends.cudnn" not in captured_args
def test_nvidia_excludes_present(self, captured_args):
"""ROCm builds must exclude nvidia packages to avoid bundling ~3GB of bloat."""
excludes = []
for i, arg in enumerate(captured_args):
if arg == "--exclude-module":
excludes.append(captured_args[i + 1])
assert "nvidia" in excludes
assert "nvidia.cudnn" in excludes
class TestRocmBuildCli:
"""Validate CLI argument parsing for --rocm."""
def test_rocm_flag_parses(self):
build_script = Path(__file__).parent.parent / "build_binary.py"
result = subprocess.run(
[sys.executable, str(build_script), "--rocm", "--help"],
capture_output=True,
text=True,
)
assert result.returncode == 0
assert "--rocm" in result.stdout
def test_cannot_combine_cuda_and_rocm(self):
"""Building with both CUDA and ROCm should raise ValueError."""
with pytest.raises(ValueError, match="Cannot build with both CUDA and ROCm"):
build_server(cuda=True, rocm=True)
@pytest.mark.slow()
@pytest.mark.skipif(sys.platform != "win32", reason="ROCm build E2E only runs on Windows")
class TestRocmBuildE2E:
"""
True end-to-end build test.
Executes build_binary.py --rocm, verifies the binary exists, and runs it
with --help to confirm it boots without import errors.
"""
def test_rocm_binary_compiles_and_runs(self, tmp_path):
backend_dir = Path(__file__).parent.parent
build_script = backend_dir / "build_binary.py"
dist_dir = backend_dir / "dist"
binary_dir = dist_dir / "voicebox-server-rocm"
binary_exe = binary_dir / "voicebox-server-rocm.exe"
# Clean previous dist if it exists to ensure a fresh build
if binary_dir.exists():
import shutil
shutil.rmtree(binary_dir)
# Run the full build (this can take several minutes)
result = subprocess.run(
[sys.executable, str(build_script), "--rocm"],
capture_output=True,
text=True,
cwd=str(backend_dir),
timeout=900,
)
assert result.returncode == 0, (
f"Build failed with stdout:\n{result.stdout}\nstderr:\n{result.stderr}"
)
assert binary_exe.exists(), (
f"Expected binary not found at {binary_exe}"
)
# Run the binary with --help to ensure it boots without import errors
run_result = subprocess.run(
[str(binary_exe), "--help"],
capture_output=True,
text=True,
timeout=60,
)
# A frozen binary may not have argparse help, but it should not crash
# with a ModuleNotFoundError or similar import error.
assert "ModuleNotFoundError" not in run_result.stderr
assert "ImportError" not in run_result.stderr
-203
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@@ -1,203 +0,0 @@
"""
Tests for the ROCm backend download service.
Mocks httpx to verify download, extraction, and progress reporting
without hitting the network.
"""
import json
import tarfile
import tempfile
from io import BytesIO
from pathlib import Path
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
from backend.services import rocm
from backend.utils.progress import get_progress_manager
@pytest.fixture(autouse=True)
def reset_progress_manager():
"""Reset the global progress manager before each test."""
import backend.utils.progress
backend.utils.progress._progress_manager = None
yield
backend.utils.progress._progress_manager = None
@pytest.fixture
def mock_backends_dir(tmp_path: Path, monkeypatch):
"""Patch get_data_dir so downloads land in a temp directory."""
monkeypatch.setattr(rocm, "get_backends_dir", lambda: tmp_path / "backends")
return tmp_path / "backends"
@pytest.fixture
def fake_tar_gz():
"""Create an in-memory .tar.gz archive containing a dummy file."""
buf = BytesIO()
with tarfile.open(fileobj=buf, mode="w:gz") as tar:
data = b"fake binary content"
info = tarfile.TarInfo(name="voicebox-server-rocm.exe")
info.size = len(data)
tar.addfile(info, BytesIO(data))
buf.seek(0)
return buf.read()
@pytest.fixture
def fake_sha256():
"""Return a dummy SHA-256 hex string."""
return "a" * 64
class FakeResponse:
"""Minimal fake for httpx.Response."""
def __init__(self, content: bytes = b"", status_code: int = 200, headers: dict | None = None):
self.content = content
self.status_code = status_code
self.headers = headers or {}
def raise_for_status(self):
if self.status_code >= 400:
raise Exception(f"HTTP {self.status_code}")
def iter_bytes(self, chunk_size: int = 1024):
for i in range(0, len(self.content), chunk_size):
yield self.content[i : i + chunk_size]
async def aiter_bytes(self, chunk_size: int = 1024):
for i in range(0, len(self.content), chunk_size):
yield self.content[i : i + chunk_size]
@property
def text(self):
return self.content.decode()
class FakeHttpxClient:
"""Minimal fake for httpx.AsyncClient."""
def __init__(self, responses: dict[str, FakeResponse]):
self._responses = responses
async def __aenter__(self):
return self
async def __aexit__(self, *args):
return False
async def head(self, url: str):
return self._responses.get(url, FakeResponse(status_code=404))
async def get(self, url: str):
return self._responses.get(url, FakeResponse(status_code=404))
def stream(self, method: str, url: str):
resp = self._responses.get(url, FakeResponse(status_code=404))
resp.raise_for_status()
class _Streamer:
async def __aenter__(self):
return resp
async def __aexit__(self, *args):
return False
async def aiter_bytes(self, chunk_size: int = 1024):
for i in range(0, len(resp.content), chunk_size):
yield resp.content[i : i + chunk_size]
return _Streamer()
@pytest.mark.asyncio
async def test_get_rocm_status_not_installed(mock_backends_dir):
status = rocm.get_rocm_status()
assert status["available"] is False
assert status["active"] is False
assert status["binary_path"] is None
assert status["downloading"] is False
@pytest.mark.asyncio
async def test_download_rocm_binary_progress_reporting(mock_backends_dir, fake_tar_gz, fake_sha256):
"""
Verify that download_rocm_binary():
1. Downloads the server archive and ROCm libs archive.
2. Extracts them into the backends/rocm directory.
3. Reports progress via the progress_manager.
"""
import hashlib
server_sha = hashlib.sha256(fake_tar_gz).hexdigest()
libs_sha = hashlib.sha256(fake_tar_gz).hexdigest()
responses = {
"https://github.com/jamiepine/voicebox/releases/download/v0.2.3/voicebox-server-rocm.tar.gz": FakeResponse(
content=fake_tar_gz,
headers={"content-length": str(len(fake_tar_gz))},
),
"https://github.com/jamiepine/voicebox/releases/download/v0.2.3/voicebox-server-rocm.tar.gz.sha256": FakeResponse(
content=f"{server_sha} voicebox-server-rocm.tar.gz\n".encode(),
),
f"https://github.com/jamiepine/voicebox/releases/download/v0.2.3/rocm-libs-{rocm.ROCM_LIBS_VERSION}.tar.gz": FakeResponse(
content=fake_tar_gz,
headers={"content-length": str(len(fake_tar_gz))},
),
f"https://github.com/jamiepine/voicebox/releases/download/v0.2.3/rocm-libs-{rocm.ROCM_LIBS_VERSION}.tar.gz.sha256": FakeResponse(
content=f"{libs_sha} rocm-libs.tar.gz\n".encode(),
),
}
fake_client = FakeHttpxClient(responses)
with patch("httpx.AsyncClient", return_value=fake_client):
await rocm.download_rocm_binary(version="v0.2.3")
# Verify extraction
rocm_dir = rocm.get_rocm_dir()
assert (rocm_dir / "voicebox-server-rocm.exe").exists()
# Verify manifest written
manifest_path = rocm.get_rocm_libs_manifest_path()
assert manifest_path.exists()
data = json.loads(manifest_path.read_text())
assert data["version"] == rocm.ROCM_LIBS_VERSION
# Verify progress was reported
progress = get_progress_manager().get_progress("rocm-backend")
assert progress is not None
assert progress["status"] == "complete"
assert progress["progress"] == 100.0
@pytest.mark.asyncio
async def test_is_rocm_active(mock_backends_dir, monkeypatch):
monkeypatch.setenv("VOICEBOX_BACKEND_VARIANT", "rocm")
assert rocm.is_rocm_active() is True
monkeypatch.setenv("VOICEBOX_BACKEND_VARIANT", "cpu")
assert rocm.is_rocm_active() is False
monkeypatch.delenv("VOICEBOX_BACKEND_VARIANT", raising=False)
assert rocm.is_rocm_active() is False
@pytest.mark.asyncio
async def test_delete_rocm_binary(mock_backends_dir, fake_tar_gz):
"""Test deleting the ROCm backend directory."""
rocm_dir = rocm.get_rocm_dir()
rocm_dir.mkdir(parents=True, exist_ok=True)
(rocm_dir / "dummy.txt").write_text("hello")
result = await rocm.delete_rocm_binary()
assert result is True
assert not rocm_dir.exists()
# Deleting again should return False
result = await rocm.delete_rocm_binary()
assert result is False
-130
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@@ -1,130 +0,0 @@
"""
Phase 1.1 Test: ROCm requirements installation.
Validates that requirements-rocm.txt correctly installs ROCm-enabled PyTorch
and that torch.cuda.is_available() returns True on AMD hardware.
Usage:
python -m pytest backend/tests/test_rocm_requirements.py -v
"""
import os
import platform
import subprocess
import sys
import tempfile
from pathlib import Path
import pytest
def _has_amd_hardware():
"""Check if AMD GPU hardware is present on Windows."""
if platform.system() != "Windows":
return False
try:
result = subprocess.run(
[
"powershell",
"-Command",
"Get-WmiObject Win32_VideoController | "
"Where-Object {$_.AdapterCompatibility -like '*AMD*'} | "
"Measure-Object | Select-Object -ExpandProperty Count",
],
capture_output=True,
text=True,
check=True,
)
return int(result.stdout.strip()) > 0
except Exception:
return False
@pytest.fixture()
def backend_dir():
return Path(__file__).parent.parent
class TestRocmRequirements:
"""Validate requirements-rocm.txt content and installation."""
def test_requirements_file_exists(self, backend_dir):
req_file = backend_dir / "requirements-rocm.txt"
assert req_file.exists(), "requirements-rocm.txt must exist"
def test_requirements_file_content(self, backend_dir):
import re
req_file = backend_dir / "requirements-rocm.txt"
content = req_file.read_text()
assert "rocm7.2" in content, "Must point to ROCm 7.2 extra index"
# Parse exact package names to avoid false positives from URL substrings
package_names = re.findall(r"^([A-Za-z][A-Za-z0-9_-]*)", content, re.MULTILINE)
assert "torch" in package_names, "Must include torch package"
assert "torchaudio" in package_names, "Must include torchaudio package"
assert "torchvision" in package_names, "Must include torchvision package"
@pytest.mark.timeout(900)
@pytest.mark.skipif(
not os.environ.get("VOICEBOX_TEST_ROCM_INSTALL"),
reason="Set VOICEBOX_TEST_ROCM_INSTALL=1 to run the heavy install test",
)
def test_rocm_torch_installs_and_detects_amd(self, backend_dir):
"""
Create a temporary venv, install requirements-rocm.txt, and verify
torch.cuda.is_available() returns True on AMD hardware.
"""
req_file = backend_dir / "requirements-rocm.txt"
has_amd = _has_amd_hardware()
with tempfile.TemporaryDirectory() as tmpdir:
venv_dir = Path(tmpdir) / "venv"
subprocess.run(
[sys.executable, "-m", "venv", str(venv_dir)],
check=True,
)
if sys.platform == "win32":
venv_python = venv_dir / "Scripts" / "python.exe"
else:
venv_python = venv_dir / "bin" / "python"
# Upgrade pip to avoid resolver issues
subprocess.run(
[str(venv_python), "-m", "pip", "install", "--upgrade", "pip"],
check=True,
)
# Install ROCm requirements
subprocess.run(
[str(venv_python), "-m", "pip", "install", "-r", str(req_file)],
check=True,
)
# Verify torch imports and cuda availability
result = subprocess.run(
[
str(venv_python),
"-c",
"import torch; print(torch.__version__); print(torch.cuda.is_available())",
],
capture_output=True,
text=True,
check=True,
)
lines = result.stdout.strip().splitlines()
assert len(lines) >= 2, f"Unexpected output: {result.stdout}"
torch_version = lines[0]
cuda_available = lines[1] == "True"
# The honest test: on AMD hardware ROCm torch should report cuda available
if has_amd:
assert cuda_available, (
f"AMD hardware detected but torch.cuda.is_available() returned False. "
f"torch version: {torch_version}, stderr: {result.stderr}"
)
else:
assert not cuda_available, (
f"No AMD hardware detected but torch.cuda.is_available() returned True. "
f"torch version: {torch_version}"
)
+1 -54
View File
@@ -3,72 +3,19 @@ Platform detection for backend selection.
"""
import platform
import subprocess
from functools import lru_cache
from typing import Literal
def is_apple_silicon() -> bool:
"""
Check if running on Apple Silicon (arm64 macOS).
Returns:
True if on Apple Silicon, False otherwise
"""
return platform.system() == "Darwin" and platform.machine() == "arm64"
@lru_cache(maxsize=1)
def is_amd_gpu_windows() -> bool:
"""
Check if the primary GPU on Windows is an AMD Radeon card.
Uses WMI to query Win32_VideoController, with a fallback to
torch.cuda.get_device_name(0) if WMI is unavailable. This is
useful for deciding whether the ROCm backend is appropriate.
Result is cached since it shells out to PowerShell and the GPU
does not change at runtime — safe to call from the health path.
Returns:
True if an AMD GPU is detected on Windows, False otherwise.
"""
if platform.system() != "Windows":
return False
# Primary method: WMI query for AMD adapters
try:
result = subprocess.run(
[
"powershell",
"-Command",
"Get-CimInstance Win32_VideoController | "
"Where-Object {$_.AdapterCompatibility -like '*AMD*'} | "
"Measure-Object | Select-Object -ExpandProperty Count",
],
capture_output=True,
text=True,
check=True,
)
if int(result.stdout.strip()) > 0:
return True
except Exception:
pass
# Fallback: torch.cuda.get_device_name(0) (works for ROCm/HIP too)
try:
import torch
if torch.cuda.is_available():
name = torch.cuda.get_device_name(0)
if "Radeon" in name or "AMD" in name:
return True
except Exception:
pass
return False
def get_backend_type() -> Literal["mlx", "pytorch"]:
"""
Detect the best backend for the current platform.
-13
View File
@@ -67,19 +67,6 @@ class TaskManager:
def get_active_downloads(self) -> List[DownloadTask]:
"""Get all active downloads."""
return list(self._active_downloads.values())
def get_pending_downloads(self) -> List[DownloadTask]:
"""Get downloads that are still in flight.
Excludes errored tasks, which stay in the active list so the
error/retry UI can show them but must not be reported as
"downloading" by /models/status.
"""
return [
task
for task in self._active_downloads.values()
if task.status in ("downloading", "extracting")
]
def get_active_generations(self) -> List[GenerationTask]:
"""Get all active generations."""
+246 -3
View File
@@ -73,6 +73,37 @@
"vite": "^5.4.0",
},
},
"landing": {
"name": "@voicebox/landing",
"version": "0.5.0",
"dependencies": {
"@fontsource/space-grotesk": "^5.2.10",
"@icons-pack/react-simple-icons": "^13.13.0",
"@radix-ui/react-separator": "^1.1.8",
"@radix-ui/react-slot": "^1.2.4",
"autoprefixer": "^10.4.17",
"class-variance-authority": "^0.7.1",
"clsx": "^2.1.1",
"framer-motion": "^12.36.0",
"gray-matter": "^4.0.3",
"lucide-react": "^0.316.0",
"marked": "^18.0.5",
"next": "^16.1.3",
"postcss": "^8.4.33",
"react": "^18.2.0",
"react-dom": "^18.2.0",
"tailwind-merge": "^3.4.0",
"tailwindcss": "^3.4.1",
"tailwindcss-animate": "^1.0.7",
"wavesurfer.js": "^7.12.2",
},
"devDependencies": {
"@types/node": "^20.11.5",
"@types/react": "^18.2.48",
"@types/react-dom": "^18.2.18",
"typescript": "^5.3.3",
},
},
"tauri": {
"name": "@voicebox/tauri",
"version": "0.5.0",
@@ -122,6 +153,8 @@
},
},
"packages": {
"@alloc/quick-lru": ["@alloc/[email protected]", "", {}, "sha512-UrcABB+4bUrFABwbluTIBErXwvbsU/V7TZWfmbgJfbkwiBuziS9gxdODUyuiecfdGQ85jglMW6juS3+z5TsKLw=="],
"@babel/code-frame": ["@babel/[email protected]", "", { "dependencies": { "@babel/helper-validator-identifier": "^7.28.5", "js-tokens": "^4.0.0", "picocolors": "^1.1.1" } }, "sha512-JYgintcMjRiCvS8mMECzaEn+m3PfoQiyqukOMCCVQtoJGYJw8j/8LBJEiqkHLkfwCcs74E3pbAUFNg7d9VNJ+Q=="],
"@babel/compat-data": ["@babel/[email protected]", "", {}, "sha512-2lfu57JtzctfIrcGMz992hyLlByuzgIk58+hhGCxjKZ3rWI82NnVLjXcaTqkI2NvlcvOskZaiZ5kjUALo3Lpxg=="],
@@ -188,6 +221,8 @@
"@dnd-kit/utilities": ["@dnd-kit/[email protected]", "", { "dependencies": { "tslib": "^2.0.0" }, "peerDependencies": { "react": ">=16.8.0" } }, "sha512-+MKAJEOfaBe5SmV6t34p80MMKhjvUz0vRrvVJbPT0WElzaOJ/1xs+D+KDv+tD/NE5ujfrChEcshd4fLn0wpiqg=="],
"@emnapi/runtime": ["@emnapi/[email protected]", "", { "dependencies": { "tslib": "^2.4.0" } }, "sha512-mehfKSMWjjNol8659Z8KxEMrdSJDDot5SXMq00dM8BN4o+CLNXQ0xH2V7EchNHV4RmbZLmmPdEaXZc5H2FXmDg=="],
"@esbuild/aix-ppc64": ["@esbuild/[email protected]", "", { "os": "aix", "cpu": "ppc64" }, "sha512-1SDgH6ZSPTlggy1yI6+Dbkiz8xzpHJEVAlF/AM1tHPLsf5STom9rwtjE4hKAF20FfXXNTFqEYXyJNWh1GiZedQ=="],
"@esbuild/android-arm": ["@esbuild/[email protected]", "", { "os": "android", "cpu": "arm" }, "sha512-vCPvzSjpPHEi1siZdlvAlsPxXl7WbOVUBBAowWug4rJHb68Ox8KualB+1ocNvT5fjv6wpkX6o/iEpbDrf68zcg=="],
@@ -250,6 +285,8 @@
"@floating-ui/utils": ["@floating-ui/[email protected]", "", {}, "sha512-aGTxbpbg8/b5JfU1HXSrbH3wXZuLPJcNEcZQFMxLs3oSzgtVu6nFPkbbGGUvBcUjKV2YyB9Wxxabo+HEH9tcRQ=="],
"@fontsource/space-grotesk": ["@fontsource/[email protected]", "", {}, "sha512-XNXEbT74OIITPqw2H6HXwPDp85fy43uxfBwFR5PU+9sLnjuLj12KlhVM9nZVN6q6dlKjkuN8JisW/OBxwxgUew=="],
"@hookform/resolvers": ["@hookform/[email protected]", "", { "peerDependencies": { "react-hook-form": "^7.0.0" } }, "sha512-79Dv+3mDF7i+2ajj7SkypSKHhl1cbln1OGavqrsF7p6mbUv11xpqpacPsGDCTRvCSjEEIez2ef1NveSVL3b0Ag=="],
"@humanwhocodes/config-array": ["@humanwhocodes/[email protected]", "", { "dependencies": { "@humanwhocodes/object-schema": "^2.0.3", "debug": "^4.3.1", "minimatch": "^3.0.5" } }, "sha512-DZLEEqFWQFiyK6h5YIeynKx7JlvCYWL0cImfSRXZ9l4Sg2efkFGTuFf6vzXjK1cq6IYkU+Eg/JizXw+TD2vRNw=="],
@@ -258,6 +295,58 @@
"@humanwhocodes/object-schema": ["@humanwhocodes/[email protected]", "", {}, "sha512-93zYdMES/c1D69yZiKDBj0V24vqNzB/koF26KPaagAfd3P/4gUlh3Dys5ogAK+Exi9QyzlD8x/08Zt7wIKcDcA=="],
"@icons-pack/react-simple-icons": ["@icons-pack/[email protected]", "", { "peerDependencies": { "react": "^16.13 || ^17 || ^18 || ^19" } }, "sha512-B5HhQMIpcSH4z8IZ8HFhD59CboHceKYMpPC9kAwGyKntvPdyJJv26DLu4Z1wAjcCLyrJhf11tMhiQGom9Rxb9g=="],
"@img/colour": ["@img/[email protected]", "", {}, "sha512-A5P/LfWGFSl6nsckYtjw9da+19jB8hkJ6ACTGcDfEJ0aE+l2n2El7dsVM7UVHZQ9s2lmYMWlrS21YLy2IR1LUw=="],
"@img/sharp-darwin-arm64": ["@img/[email protected]", "", { "optionalDependencies": { "@img/sharp-libvips-darwin-arm64": "1.2.4" }, "os": "darwin", "cpu": "arm64" }, "sha512-imtQ3WMJXbMY4fxb/Ndp6HBTNVtWCUI0WdobyheGf5+ad6xX8VIDO8u2xE4qc/fr08CKG/7dDseFtn6M6g/r3w=="],
"@img/sharp-darwin-x64": ["@img/[email protected]", "", { "optionalDependencies": { "@img/sharp-libvips-darwin-x64": "1.2.4" }, "os": "darwin", "cpu": "x64" }, "sha512-YNEFAF/4KQ/PeW0N+r+aVVsoIY0/qxxikF2SWdp+NRkmMB7y9LBZAVqQ4yhGCm/H3H270OSykqmQMKLBhBJDEw=="],
"@img/sharp-libvips-darwin-arm64": ["@img/[email protected]", "", { "os": "darwin", "cpu": "arm64" }, "sha512-zqjjo7RatFfFoP0MkQ51jfuFZBnVE2pRiaydKJ1G/rHZvnsrHAOcQALIi9sA5co5xenQdTugCvtb1cuf78Vf4g=="],
"@img/sharp-libvips-darwin-x64": ["@img/[email protected]", "", { "os": "darwin", "cpu": "x64" }, "sha512-1IOd5xfVhlGwX+zXv2N93k0yMONvUlANylbJw1eTah8K/Jtpi15KC+WSiaX/nBmbm2HxRM1gZ0nSdjSsrZbGKg=="],
"@img/sharp-libvips-linux-arm": ["@img/[email protected]", "", { "os": "linux", "cpu": "arm" }, "sha512-bFI7xcKFELdiNCVov8e44Ia4u2byA+l3XtsAj+Q8tfCwO6BQ8iDojYdvoPMqsKDkuoOo+X6HZA0s0q11ANMQ8A=="],
"@img/sharp-libvips-linux-arm64": ["@img/[email protected]", "", { "os": "linux", "cpu": "arm64" }, "sha512-excjX8DfsIcJ10x1Kzr4RcWe1edC9PquDRRPx3YVCvQv+U5p7Yin2s32ftzikXojb1PIFc/9Mt28/y+iRklkrw=="],
"@img/sharp-libvips-linux-ppc64": ["@img/[email protected]", "", { "os": "linux", "cpu": "ppc64" }, "sha512-FMuvGijLDYG6lW+b/UvyilUWu5Ayu+3r2d1S8notiGCIyYU/76eig1UfMmkZ7vwgOrzKzlQbFSuQfgm7GYUPpA=="],
"@img/sharp-libvips-linux-riscv64": ["@img/[email protected]", "", { "os": "linux", "cpu": "none" }, "sha512-oVDbcR4zUC0ce82teubSm+x6ETixtKZBh/qbREIOcI3cULzDyb18Sr/Wcyx7NRQeQzOiHTNbZFF1UwPS2scyGA=="],
"@img/sharp-libvips-linux-s390x": ["@img/[email protected]", "", { "os": "linux", "cpu": "s390x" }, "sha512-qmp9VrzgPgMoGZyPvrQHqk02uyjA0/QrTO26Tqk6l4ZV0MPWIW6LTkqOIov+J1yEu7MbFQaDpwdwJKhbJvuRxQ=="],
"@img/sharp-libvips-linux-x64": ["@img/[email protected]", "", { "os": "linux", "cpu": "x64" }, "sha512-tJxiiLsmHc9Ax1bz3oaOYBURTXGIRDODBqhveVHonrHJ9/+k89qbLl0bcJns+e4t4rvaNBxaEZsFtSfAdquPrw=="],
"@img/sharp-libvips-linuxmusl-arm64": ["@img/[email protected]", "", { "os": "linux", "cpu": "arm64" }, "sha512-FVQHuwx1IIuNow9QAbYUzJ+En8KcVm9Lk5+uGUQJHaZmMECZmOlix9HnH7n1TRkXMS0pGxIJokIVB9SuqZGGXw=="],
"@img/sharp-libvips-linuxmusl-x64": ["@img/[email protected]", "", { "os": "linux", "cpu": "x64" }, "sha512-+LpyBk7L44ZIXwz/VYfglaX/okxezESc6UxDSoyo2Ks6Jxc4Y7sGjpgU9s4PMgqgjj1gZCylTieNamqA1MF7Dg=="],
"@img/sharp-linux-arm": ["@img/[email protected]", "", { "optionalDependencies": { "@img/sharp-libvips-linux-arm": "1.2.4" }, "os": "linux", "cpu": "arm" }, "sha512-9dLqsvwtg1uuXBGZKsxem9595+ujv0sJ6Vi8wcTANSFpwV/GONat5eCkzQo/1O6zRIkh0m/8+5BjrRr7jDUSZw=="],
"@img/sharp-linux-arm64": ["@img/[email protected]", "", { "optionalDependencies": { "@img/sharp-libvips-linux-arm64": "1.2.4" }, "os": "linux", "cpu": "arm64" }, "sha512-bKQzaJRY/bkPOXyKx5EVup7qkaojECG6NLYswgktOZjaXecSAeCWiZwwiFf3/Y+O1HrauiE3FVsGxFg8c24rZg=="],
"@img/sharp-linux-ppc64": ["@img/[email protected]", "", { "optionalDependencies": { "@img/sharp-libvips-linux-ppc64": "1.2.4" }, "os": "linux", "cpu": "ppc64" }, "sha512-7zznwNaqW6YtsfrGGDA6BRkISKAAE1Jo0QdpNYXNMHu2+0dTrPflTLNkpc8l7MUP5M16ZJcUvysVWWrMefZquA=="],
"@img/sharp-linux-riscv64": ["@img/[email protected]", "", { "optionalDependencies": { "@img/sharp-libvips-linux-riscv64": "1.2.4" }, "os": "linux", "cpu": "none" }, "sha512-51gJuLPTKa7piYPaVs8GmByo7/U7/7TZOq+cnXJIHZKavIRHAP77e3N2HEl3dgiqdD/w0yUfiJnII77PuDDFdw=="],
"@img/sharp-linux-s390x": ["@img/[email protected]", "", { "optionalDependencies": { "@img/sharp-libvips-linux-s390x": "1.2.4" }, "os": "linux", "cpu": "s390x" }, "sha512-nQtCk0PdKfho3eC5MrbQoigJ2gd1CgddUMkabUj+rBevs8tZ2cULOx46E7oyX+04WGfABgIwmMC0VqieTiR4jg=="],
"@img/sharp-linux-x64": ["@img/[email protected]", "", { "optionalDependencies": { "@img/sharp-libvips-linux-x64": "1.2.4" }, "os": "linux", "cpu": "x64" }, "sha512-MEzd8HPKxVxVenwAa+JRPwEC7QFjoPWuS5NZnBt6B3pu7EG2Ge0id1oLHZpPJdn3OQK+BQDiw9zStiHBTJQQQQ=="],
"@img/sharp-linuxmusl-arm64": ["@img/[email protected]", "", { "optionalDependencies": { "@img/sharp-libvips-linuxmusl-arm64": "1.2.4" }, "os": "linux", "cpu": "arm64" }, "sha512-fprJR6GtRsMt6Kyfq44IsChVZeGN97gTD331weR1ex1c1rypDEABN6Tm2xa1wE6lYb5DdEnk03NZPqA7Id21yg=="],
"@img/sharp-linuxmusl-x64": ["@img/[email protected]", "", { "optionalDependencies": { "@img/sharp-libvips-linuxmusl-x64": "1.2.4" }, "os": "linux", "cpu": "x64" }, "sha512-Jg8wNT1MUzIvhBFxViqrEhWDGzqymo3sV7z7ZsaWbZNDLXRJZoRGrjulp60YYtV4wfY8VIKcWidjojlLcWrd8Q=="],
"@img/sharp-wasm32": ["@img/[email protected]", "", { "dependencies": { "@emnapi/runtime": "^1.7.0" }, "cpu": "none" }, "sha512-OdWTEiVkY2PHwqkbBI8frFxQQFekHaSSkUIJkwzclWZe64O1X4UlUjqqqLaPbUpMOQk6FBu/HtlGXNblIs0huw=="],
"@img/sharp-win32-arm64": ["@img/[email protected]", "", { "os": "win32", "cpu": "arm64" }, "sha512-WQ3AgWCWYSb2yt+IG8mnC6Jdk9Whs7O0gxphblsLvdhSpSTtmu69ZG1Gkb6NuvxsNACwiPV6cNSZNzt0KPsw7g=="],
"@img/sharp-win32-ia32": ["@img/[email protected]", "", { "os": "win32", "cpu": "ia32" }, "sha512-FV9m/7NmeCmSHDD5j4+4pNI8Cp3aW+JvLoXcTUo0IqyjSfAZJ8dIUmijx1qaJsIiU+Hosw6xM5KijAWRJCSgNg=="],
"@img/sharp-win32-x64": ["@img/[email protected]", "", { "os": "win32", "cpu": "x64" }, "sha512-+29YMsqY2/9eFEiW93eqWnuLcWcufowXewwSNIT6UwZdUUCrM3oFjMWH/Z6/TMmb4hlFenmfAVbpWeup2jryCw=="],
"@jridgewell/gen-mapping": ["@jridgewell/[email protected]", "", { "dependencies": { "@jridgewell/sourcemap-codec": "^1.5.0", "@jridgewell/trace-mapping": "^0.3.24" } }, "sha512-2kkt/7niJ6MgEPxF0bYdQ6etZaA+fQvDcLKckhy1yIQOzaoKjBBjSj63/aLVjYE3qhRt5dvM+uUyfCg6UKCBbA=="],
"@jridgewell/remapping": ["@jridgewell/[email protected]", "", { "dependencies": { "@jridgewell/gen-mapping": "^0.3.5", "@jridgewell/trace-mapping": "^0.3.24" } }, "sha512-LI9u/+laYG4Ds1TDKSJW2YPrIlcVYOwi2fUC6xB43lueCjgxV4lffOCZCtYFiH6TNOX+tQKXx97T4IKHbhyHEQ=="],
@@ -268,6 +357,24 @@
"@jridgewell/trace-mapping": ["@jridgewell/[email protected]", "", { "dependencies": { "@jridgewell/resolve-uri": "^3.1.0", "@jridgewell/sourcemap-codec": "^1.4.14" } }, "sha512-zzNR+SdQSDJzc8joaeP8QQoCQr8NuYx2dIIytl1QeBEZHJ9uW6hebsrYgbz8hJwUQao3TWCMtmfV8Nu1twOLAw=="],
"@next/env": ["@next/[email protected]", "", {}, "sha512-gkrXnZyxPUy0Gg6SrPQPccbNVLSP3vmW8LU5dwEttEEC1RwDivk8w4O+sZIjFvPrSICXyhQDCG+y3VmjlJf+9A=="],
"@next/swc-darwin-arm64": ["@next/[email protected]", "", { "os": "darwin", "cpu": "arm64" }, "sha512-T8atLKuvk13XQUdVLCv1ZzMPgLPW0+DWWbHSQXs0/3TjPrKNxTmUIhOEaoEyl3Z82k8h/gEtqyuoZGv6+Ugawg=="],
"@next/swc-darwin-x64": ["@next/[email protected]", "", { "os": "darwin", "cpu": "x64" }, "sha512-AKC/qVjUGUQDSPI6gESTx0xOnOPQ5gttogNS3o6bA83yiaSZJek0Am5yXy82F1KcZCx3DdOwdGPZpQCluonuxg=="],
"@next/swc-linux-arm64-gnu": ["@next/[email protected]", "", { "os": "linux", "cpu": "arm64" }, "sha512-POQ65+pnYOkZNdngWfMEt7r53bzWiKkVNbjpmCt1Zb3V6lxJNXSsjwRuTQ8P/kguxDC8LRkqaL3vvsFrce4dMQ=="],
"@next/swc-linux-arm64-musl": ["@next/[email protected]", "", { "os": "linux", "cpu": "arm64" }, "sha512-3Wm0zGYVCs6qDFAiSSDL+Z+r46EdtCv/2l+UlIdMbAq9hPJBvGu/rZOeuvCaIUjbArkmXac8HnTyQPJFzFWA0Q=="],
"@next/swc-linux-x64-gnu": ["@next/[email protected]", "", { "os": "linux", "cpu": "x64" }, "sha512-lWAYAezFinaJiD5Gv8HDidtsZdT3CDaCeqoPoJjeB57OqzvMajpIhlZFce5sCAH6VuX4mdkxCRqecCJFwfm2nQ=="],
"@next/swc-linux-x64-musl": ["@next/[email protected]", "", { "os": "linux", "cpu": "x64" }, "sha512-fHaIpT7x4gA6VQbdEpYUXRGyge/YbRrkG6DXM60XiBqDM2g2NcrsQaIuj375egnGFkJow4RHacgBOEsHfGbiUw=="],
"@next/swc-win32-arm64-msvc": ["@next/[email protected]", "", { "os": "win32", "cpu": "arm64" }, "sha512-MCrXxrTSE7jPN1NyXJr39E+aNFBrQZtO154LoCz7n99FuKqJDekgxipoodLNWdQP7/DZ5tKMc/efybx1l159hw=="],
"@next/swc-win32-x64-msvc": ["@next/[email protected]", "", { "os": "win32", "cpu": "x64" }, "sha512-JSVlm9MDhmTXw/sO2PE/MRj+G6XOSMZB+BcZ0a7d6KwVFZVpkHcb2okyoYFBaco6LeiL53BBklRlOrDDbOeE5w=="],
"@nodelib/fs.scandir": ["@nodelib/[email protected]", "", { "dependencies": { "@nodelib/fs.stat": "2.0.5", "run-parallel": "^1.1.9" } }, "sha512-vq24Bq3ym5HEQm2NKCr3yXDwjc7vTsEThRDnkp2DK9p1uqLR+DHurm/NOTo0KG7HYHU7eppKZj3MyqYuMBf62g=="],
"@nodelib/fs.stat": ["@nodelib/[email protected]", "", {}, "sha512-RkhPPp2zrqDAQA/2jNhnztcPAlv64XdhIp7a7454A5ovI7Bukxgt7MX7udwAu3zg1DcpPU0rz3VV1SeaqvY4+A=="],
@@ -410,6 +517,8 @@
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"@voicebox/landing": ["@voicebox/landing@workspace:landing"],
"@voicebox/tauri": ["@voicebox/tauri@workspace:tauri"],
"@voicebox/web": ["@voicebox/web@workspace:web"],
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@@ -912,6 +1129,8 @@
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@@ -932,6 +1151,8 @@
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@@ -958,6 +1179,8 @@
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-36
View File
@@ -1,36 +0,0 @@
---
# ROCm (AMD GPU) overlay for Voicebox
#
# docker compose -f docker-compose.yml -f docker-compose.rocm.yml up --build
#
# Requires ROCm drivers on the host:
# https://rocm.docs.amd.com/projects/install-on-linux
# RDNA4 (RX 9000): export ROCM_VERSION=7.2 (default 6.3 covers RDNA1-3).
services:
voicebox:
build:
context: .
args:
PYTORCH_VARIANT: rocm
ROCM_VERSION: ${ROCM_VERSION:-6.3}
devices:
- /dev/kfd
- /dev/dri
environment:
# HSA_OVERRIDE_GFX_VERSION forces the ROCm runtime to treat the GPU as a
# specific GFX version when auto-detection fails or the GPU is newer than
# the ROCm release. app.py sets 10.3.0 (RDNA2) by default; override here
# for your GPU family:
# RDNA4 / RX 9000 series: 12.0.0
# (requires ROCM_VERSION=7.2)
# RDNA3 / RX 7000 series / Strix Halo: 11.0.0
# RDNA2 / RX 6000 series: 10.3.0
# RDNA1 / RX 5000 series: 10.1.0
# Vega / GCN5: 9.0.0
- HSA_OVERRIDE_GFX_VERSION=${HSA_OVERRIDE_GFX_VERSION:-}
# Tune the ROCm memory allocator
- PYTORCH_HIP_ALLOC_CONF=garbage_collection_threshold:0.8,max_split_size_mb:512
-4
View File
@@ -1,7 +1,3 @@
# Voicebox — CPU build (default)
# For AMD ROCm GPU acceleration use the overlay:
# docker compose -f docker-compose.yml -f docker-compose.rocm.yml up --build
services:
voicebox:
build: .
+3 -74
View File
@@ -1,6 +1,6 @@
# Voicebox Project Status & Roadmap
> Last updated: 2026-07-02 | Current version: **v0.5.0** | 402 open issues | 88 open PRs | 1.3M downloads · 34.8k stars
> Last updated: 2026-06-27 | Current version: **v0.5.0** | 402 open issues | 88 open PRs | 1.3M downloads · 34.8k stars
---
@@ -218,19 +218,6 @@ Shipped 2026-04-25 (PR #544). Voicebox went from a voice-cloning studio to a ful
**Integration shape if we revive it:** Zero-shot cloning maps naturally to the Chatterbox-style backend (store `ref_audio` + `ref_text` paths in the voice prompt dict, process at generate time). Est. ~250 lines for `voxcpm_backend.py` + one `ModelConfig` entry + engine registration in `backends/__init__.py`. Frontend UI gating is the bigger lift.
### Funded Roadmap (2026-H2)
`$VOICEBOX` funded ~2–3 months of full-time work; cadence resumes the week of 2026-06-27. Direction committed publicly in #806:
| Item | Notes |
|------|-------|
| **Resume merge/release cadence** | Clear the 88-PR backlog, regular commits + releases — this is the immediate focus (see Tier 1) |
| **Mobile companion app** | New surface; already drawing issues (#773 iPhone logout) |
| **Encrypted cloud backup/sync** | For voice profiles + generations — first cloud feature; stays opt-in, local-first remains default |
| **More TTS models** | Engine candidates in the Landscape section below; community PRs #507/#766/#777 in queue |
| **Better GPU support** | Blackwell/sm_120, ROCm, DirectML, Intel — incl. paying testers for hardware the dev lacks |
| **Bug fixes** | 0.5.0 regression cluster first (macOS load crash, capture cutoffs, MCP, refinement) |
### What's In-Flight
| Feature | Branch/PR | Status |
@@ -239,7 +226,7 @@ Shipped 2026-04-25 (PR #544). Voicebox went from a voice-cloning studio to a ful
| Engine sprawl cleanup | issue #419 | First-class vs experimental TTS backends distinction |
| Frontend tech-debt burn-down | issue #421 | Biome + a11y debt before gating CI |
| Docker registry auto-publish | PR #463, issue #453 | ghcr.io image on tag push |
| New model research | `voicebox-new-models` branch | Evaluating Fish Speech, XTTS-v2, Pocket TTS, VibeVoice, Fish Audio S2, index-tts2. **2026-06-27 sweep** added dots.tts, LongCat-AudioDiT, SoproTTS, NeuTTS, Nemotron/Cohere STT — see Landscape → New Candidate Sweep |
| New model research | `voicebox-new-models` branch | Evaluating Fish Speech, XTTS-v2, Pocket TTS, VibeVoice, Fish Audio S2, index-tts2 |
### TTS Engine Comparison
@@ -605,43 +592,6 @@ Notable:
4. **Instruct support fills a real gap** (#173, #224, #303). Qwen CustomVoice partially addresses it with preset speakers; zero-shot clone-with-instruct is still unmet.
5. **Long-form + streaming are user-requested** (#363, #365, #464). Candidates with native streaming (Pocket TTS, Fish Speech) get extra weight.
### New Candidate Sweep (2026-06-27)
A follow-up deep-research pass, filtered against everything already tracked — the shipped engines plus MOSS-TTS-Nano, Pocket TTS, IndicF5, VibeVoice, Voxtral, Fish/Fish Audio, XTTS-v2, index-tts2, VoxCPM2, OmniVoice, MioTTS, Oolel, Faster-Qwen, Orpheus/Sesame, MiniMax, RVC, Parakeet, Qwen3-ASR, Moshi, GLM-4-Voice, Qwen2.5-Omni — kept only where a **newer sibling/variant** changes the evaluation. Same criteria as the 04-18 cycle: cross-platform, PyPI/clean packaging, permissive license, quality, instruct/style control, long-form, streaming.
**Top new TTS candidates**
| Candidate | Add as | Why it matters | Caveat |
|-----------|--------|----------------|--------|
| **[dots.tts](https://github.com/rednote-hilab/dots.tts)** (soar / mf) | **Top new TTS candidate** | 2B fully-continuous end-to-end autoregressive TTS, 48 kHz AudioVAE output, zero-shot cloning via prompt audio/text, Apache-2.0 code+checkpoints, MeanFlow-distilled variant for low latency. Freshest "serious clone engine" not yet on the roadmap. | Git-source install with constraints, not clean PyPI. Needs Windows/macOS packaging + VRAM/CPU smoke test; probably experimental until platform gating exists. |
| **[MOSS-TTS family](https://github.com/OpenMOSS/MOSS-TTS)** / v1.5 / Local-Transformer-v1.5 | **Upgrade the MOSS-Nano entry into a MOSS family epic** | We track only Nano, but MOSS now spans MOSS-TTS, TTSD (long multi-speaker dialogue), VoiceGenerator (text-prompt voice design), TTS-Realtime, SoundEffect. v1.5 adds broader languages, long-reference cloning, pause control, 48 kHz stereo, MLX/vLLM support, Apache-2.0. | Full 4B/8B variants aren't the lightweight Nano win. Treat as several engines/features, not one checkbox. |
| **[LongCat-AudioDiT](https://arxiv.org/html/2603.29339v1)** | **High-priority Apple Silicon candidate** | 3.5B non-autoregressive diffusion TTS in waveform latent space, zero-shot cloning, already has an MLX conversion usable via `mlx_audio` — unusually aligned with our Apple Silicon base. | zh/en only, not realtime. Quality play, not low-latency agent speech. |
| **[SoproTTS](https://github.com/samuel-vitorino/sopro)** | **Lightweight CPU/streaming cloned TTS** | 135M zero-shot cloning, `pip install -U sopro`, streaming + non-streaming APIs, 3–12s reference, claimed 250 ms TTFA / 0.05 RTF on M3 CPU. Strong local-first/low-maintenance fit. | English-focused, self-described as inconsistent — quality-test before promoting past experimental. |
| **[NeuTTS Air / Nano](https://github.com/neuphonic/neutts)** | **GGUF/on-device cloned TTS** | On-device instant cloning, GGUF-ready, ~3s reference, laptop/phone/Pi targets. Air is Apache-2.0. | Needs a GGUF/llama.cpp-style wrapper, not a normal PyTorch backend. Nano has a separate NeuTTS Open License — split needs review. |
| **[X-Voice](https://github.com/sunnyxrxrx/X-Voice)** | **Small multilingual clone** | 0.4B multilingual zero-shot cloning, 30 languages, IPA-style unified rep, claims no prompt-transcript requirement — targets a real cloning-UX pain point. | Verify license, packaging, production-readiness of weights/code. |
| **[FireRedTTS-2](https://huggingface.co/FireRedTeam/FireRedTTS2)** | **Stories / podcast / multi-speaker** | Apache-2.0 long-form streaming, 3-min / 4-speaker dialogue, cross-lingual code-switching cloning, low first-packet latency. | Stories-editor engine more than a general default. Needs platform/VRAM testing. |
| **[Maya1](https://huggingface.co/maya-research/maya1)** | **Expressive English voice-design** | 3B Apache-2.0, voice design, streaming, emotion/style tags, vLLM-compatible, 24 kHz, single-GPU. Good "voice personalities" / game-dialogue fit. | English-only, 16 GB+ VRAM — platform gating required. |
**MOSS is now a family, not one checkbox.** The single `MOSS-TTS-Nano` row above should become an epic: keep Nano as the CPU-friendly model, and track v1.5 / Local-Transformer-v1.5, Realtime, TTSD, VoiceGenerator, and SoundEffect as siblings under it.
**STT / capture candidates** (feed the planned streaming-transcription roadmap)
| Candidate | Add as | Why it matters | Caveat |
|-----------|--------|----------------|--------|
| **[Nemotron 3.5 ASR Streaming 0.6B](https://huggingface.co/mlx-community/nemotron-3.5-asr-streaming-0.6b)** | **Top new STT candidate** | Cache-aware streaming FastConformer-RNNT, 40 language-locales, punctuation/caps, language-ID conditioning, MLX conversion path — strongest fit for planned streaming transcription. | NVIDIA-origin; verify license + non-CUDA (MLX/CPU) performance. |
| **[Cohere Transcribe 03-2026](https://huggingface.co/blog/CohereLabs/cohere-transcribe-03-2026-release)** | **High-quality offline STT** | 2B Apache-2.0, 14 languages, ONNX/INT8 exports across CPU / Apple Silicon / GPU. Cleanest-looking offline `/transcribe` + captures candidate. | Less clearly a streaming dictation model than Nemotron. |
| **[ARK-ASR 3B / 0.6B](https://huggingface.co/AutoArk-AI/ARK-ASR-3B)** | **Multilingual STT watch** | New family, broad European/Asian coverage, strong leaderboard claims, INT8 ONNX for edge. | Very new; likely `trust_remote_code`. Validate stability first. |
| **[IBM Granite Speech 4.1 2B / NAR](https://huggingface.co/ibm-granite/granite-speech-4.1-2b)** | **ASR + speech translation** | Compact multilingual ASR + bidirectional speech translation (en/fr/de/es/pt/ja); NAR variant for latency-sensitive work. | More compelling if we expand into translation, not just dictation. |
**Watch-list / blocked** (license or platform work must land first): LEMAS-TTS, Supertonic 3, KugelAudio, GLM-TTS, KittenTTS, TinyTTS (preset/on-device, not cloning); Sarashina2.2, Higgs Audio v3, T5Gemma-TTS, Step-Audio-EditX, MisoTTS (non-commercial terms or CUDA-heavy); MegaTTS3 (incomplete WaveVAE encoder distribution); PFluxTTS, LongCat-Next (paper-only / too broad). **Low-hanging Qwen-family variants:** `Qwen3-TTS-VoiceDesign` (fills text-to-voice-design with minimal churn) and ZipVoice/ZipVoice-Dialog (only if it brings zh-en/dialogue behavior our shipped LuxTTS doesn't already expose).
**Roadmap patch from this sweep** (reflected in Tier 3 below):
1. Replace the `MOSS-TTS-Nano` checkbox with a **MOSS-TTS family** epic (Nano tracked separately as the CPU model).
2. New Tier-3 TTS candidates, in order: **dots.tts → LongCat-AudioDiT → SoproTTS → NeuTTS → X-Voice → FireRedTTS-2 → Maya1**.
3. New STT expansion candidates, in order: **Nemotron 3.5 → Cohere Transcribe → ARK-ASR → Granite Speech**.
4. Keep Sarashina2.2, Higgs v3, T5Gemma, Step-Audio-EditX, MisoTTS, MegaTTS3, PFluxTTS blocked/watch-only.
5. **Do platform gating (bottleneck #6 / `ModelConfig.requires`) before shipping GPU-only engines** — Maya1, Step-Audio-EditX, MisoTTS, and probably dots.tts stay experimental until it exists.
### Adding a New Engine (Now Straightforward)
With the model config registry and shared `EngineModelSelector` component, adding a new TTS engine requires:
@@ -725,11 +675,9 @@ The two-month gap means the highest-leverage work isn't new code — it's review
### Tier 3 — Future Engines (cross-platform preferred)
Committed ordering (04-18 cycle), then the 2026-06-27 sweep additions. See Landscape → New Candidate Sweep for full rationale.
| Priority | Item | Notes |
|----------|------|-------|
| 1 | **MOSS-TTS family** (was MOSS-TTS-Nano) | Nano first: 0.1B, Apache 2.0, 4-core CPU realtime, 48 kHz stereo, streaming, 20 langs. Best alignment with our criteria. Then track v1.5 / Realtime / TTSD / VoiceGenerator / SoundEffect as siblings under one epic. |
| 1 | **MOSS-TTS-Nano** | 0.1B, Apache 2.0, 4-core CPU realtime, 48 kHz stereo, streaming, 20 langs, released 2026-04-13. Best alignment with our criteria. Verify install ergonomics before committing. |
| 2 | **Pocket TTS** (Kyutai) | CPU-first 100M model. MIT. Fills streaming gap without CUDA dependency. Several European langs added by Feb 2026. |
| 3 | **IndicF5** | Fills Indian-language gap (#339). Closes many language-request issues. |
| 4 | **VibeVoice** (Microsoft, #172) | 1.5B, long-form multi-speaker (up to 90 min, 4 speakers). Strong Stories-editor fit. |
@@ -738,25 +686,6 @@ Committed ordering (04-18 cycle), then the 2026-06-27 sweep additions. See Lands
| 7 | **XTTS-v2** | 17+ langs, mature pip. CPML likely kills commercial use — verify. |
| 8 | **index-tts2** (#370) | Unvetted. |
| — | ~~**VoxCPM2**~~ | **Backlogged** — CUDA-only upstream. Revisit when tier system ships or MPS bugs are fixed upstream. |
| — | *New (06-27 sweep), in order* → | |
| 9 | **dots.tts** | 2B end-to-end AR, 48 kHz, Apache-2.0 + fast MeanFlow variant. Top new candidate. Git-source install — smoke-test packaging + VRAM; likely experimental until platform gating exists. |
| 10 | **LongCat-AudioDiT** | 3.5B diffusion, has an MLX/`mlx_audio` path — best Apple Silicon fit. zh/en only, not realtime. |
| 11 | **SoproTTS** | 135M, `pip install sopro`, streaming, ~250 ms TTFA / 0.05 RTF on M3 CPU. Quality-test first. |
| 12 | **NeuTTS Air/Nano** | On-device GGUF cloning, ~3s reference. Needs a GGUF wrapper; Air is Apache-2.0, Nano license split needs review. |
| 13 | **X-Voice** | 0.4B, 30 langs, no prompt-transcript required. Verify license/packaging. |
| 14 | **FireRedTTS-2** | Apache-2.0 long-form multi-speaker/podcast streaming. Stories-editor engine; needs VRAM testing. |
| 15 | **Maya1** | 3B Apache-2.0 expressive voice-design, emotion tags. English-only, 16 GB+ VRAM — gate behind platform tiers. |
### Tier 3b — STT / Capture Candidates (06-27 sweep)
Feeds the planned streaming-transcription roadmap; Whisper alternatives.
| Priority | Item | Notes |
|----------|------|-------|
| 1 | **Nemotron 3.5 ASR Streaming 0.6B** | Cache-aware streaming FastConformer-RNNT, 40 locales, MLX path. Strongest streaming-dictation fit. Verify license + non-CUDA perf. |
| 2 | **Cohere Transcribe 03-2026** | 2B Apache-2.0, 14 langs, ONNX/INT8 across CPU/Apple Silicon/GPU. Cleanest offline `/transcribe` candidate. |
| 3 | **ARK-ASR 3B / 0.6B** | Broad multilingual, INT8 ONNX for edge. Very new; likely `trust_remote_code` — validate stability. |
| 4 | **IBM Granite Speech 4.1 2B / NAR** | ASR + speech translation (en/fr/de/es/pt/ja). Compelling if we expand into translation. |
### ~~Previously Prioritized — Now Done~~
@@ -188,6 +188,7 @@ When creating a pull request:
<File name="src-tauri/" />
</Folder>
<File name="web/" />
<File name="landing/" />
<File name="scripts/" />
</Folder>
</Files>
@@ -23,7 +23,7 @@ This page is for the cases where it doesn't:
| **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) | Use a local/remote Python backend with CUDA PyTorch |
| **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 |
@@ -46,7 +46,7 @@ On M-series Macs, Voicebox ships an MLX-optimized backend that uses the Apple Ne
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 + NVIDIA — The CUDA Backend Swap
## 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.
+1 -2
View File
@@ -75,8 +75,7 @@ No cloud fallback, no bring-your-own-API-key. Local is the product.
| Platform | Backend | Notes |
|----------|---------|-------|
| macOS (Apple Silicon) | MLX (Metal) | 4-5x faster via Neural Engine |
| Windows (NVIDIA) | PyTorch (CUDA) | Auto-downloads CUDA binary from within the app |
| Linux (NVIDIA) | PyTorch (CUDA) | Use a local/remote Python backend with CUDA PyTorch |
| Windows / Linux (NVIDIA) | PyTorch (CUDA) | Auto-downloads CUDA binary from within the app |
| Linux (AMD) | PyTorch (ROCm) | Auto-configures HSA_OVERRIDE_GFX_VERSION |
| Windows (any GPU) | DirectML | Universal Windows GPU support |
| Intel Arc | IPEX/XPU | Intel discrete GPU acceleration |
+7 -37
View File
@@ -43,26 +43,6 @@ setup-python:
fi
echo "Installing Python dependencies..."
{{ pip }} install --upgrade pip -q
if [ "$(uname)" = "Linux" ]; then
torch_index=""
if [ -e /proc/driver/nvidia/version ] || [ -d /sys/module/nvidia ]; then
echo "Detected NVIDIA GPU — installing CUDA PyTorch..."
torch_index="https://download.pytorch.org/whl/cu128"
elif [ -e /dev/kfd ]; then
if [ -n "${VOICEBOX_ROCM_VERSION:-}" ]; then
rocm_ver="$VOICEBOX_ROCM_VERSION"
elif lspci 2>/dev/null | grep -qi "Navi 4"; then
rocm_ver=7.2
else
rocm_ver=6.3
fi
echo "Detected AMD GPU — installing ROCm PyTorch (rocm${rocm_ver})..."
torch_index="https://download.pytorch.org/whl/rocm${rocm_ver}"
fi
if [ -n "$torch_index" ]; then
{{ pip }} install torch torchaudio --index-url "$torch_index"
fi
fi
{{ pip }} install -r {{ backend_dir }}/requirements.txt
# Chatterbox pins numpy<1.26 / torch==2.6 which break on Python 3.12+
{{ pip }} install --no-deps chatterbox-tts
@@ -72,12 +52,6 @@ setup-python:
if [ "$(uname -m)" = "arm64" ] && [ "$(uname)" = "Darwin" ]; then
echo "Detected Apple Silicon — installing MLX dependencies..."
{{ pip }} install -r {{ backend_dir }}/requirements-mlx.txt
# mlx-lm and mlx-audio declare transformers>=5.x, which conflicts with
# our transformers<=4.57.x cap, so install them --no-deps (their other
# runtime deps are covered by requirements.txt / requirements-mlx.txt —
# see the note in requirements-mlx.txt and .github/workflows/release.yml)
{{ pip }} install --no-deps mlx-lm==0.31.1
{{ pip }} install --no-deps mlx-audio==0.4.1
fi
{{ pip }} install git+https://github.com/QwenLM/Qwen3-TTS.git
{{ pip }} install pyinstaller ruff pytest pytest-asyncio -q
@@ -95,10 +69,10 @@ setup-python:
}
Write-Host "Installing Python dependencies..."
& "{{ python }}" -m pip install --upgrade pip -q
$gpus = Get-CimInstance Win32_VideoController | Select-Object -ExpandProperty Name; \
Write-Host "Detected GPUs: $($gpus -join ', ')"; \
$hasNvidia = ($gpus | Where-Object { $_ -match 'NVIDIA' }).Count -gt 0; \
$hasIntelArc = ($gpus | Where-Object { $_ -match 'Arc' }).Count -gt 0; \
$gpus = Get-CimInstance Win32_VideoController | Select-Object -ExpandProperty Name
Write-Host "Detected GPUs: $($gpus -join ', ')"
$hasNvidia = ($gpus | Where-Object { $_ -match 'NVIDIA' }).Count -gt 0
$hasIntelArc = ($gpus | Where-Object { $_ -match 'Arc' }).Count -gt 0
if ($hasNvidia) { \
Write-Host "NVIDIA GPU detected — installing PyTorch with CUDA support..."; \
& "{{ pip }}" install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu128; \
@@ -232,16 +206,12 @@ build-server: _ensure-venv
build-server: _ensure-venv
$ErrorActionPreference = "Stop"; \
$env:PATH = "{{ venv_bin }};$env:PATH"; \
$triple = (rustc --print host-tuple); \
New-Item -ItemType Directory -Path "{{ tauri_dir }}/src-tauri/binaries" -Force | Out-Null; \
& "{{ python }}" backend/build_binary.py; \
if ($LASTEXITCODE -ne 0) { throw "build_binary.py failed with exit code $LASTEXITCODE" }; \
$triple = (rustc --print host-tuple); \
New-Item -ItemType Directory -Path "{{ tauri_dir }}/src-tauri/binaries" -Force | Out-Null; \
Copy-Item "backend/dist/voicebox-server.exe" "{{ tauri_dir }}/src-tauri/binaries/voicebox-server-$triple.exe" -Force; \
Write-Host "Copied sidecar: voicebox-server-$triple.exe"; \
& "{{ python }}" backend/build_binary.py --shim; \
if ($LASTEXITCODE -ne 0) { throw "build_binary.py --shim failed with exit code $LASTEXITCODE" }; \
Copy-Item "backend/dist/voicebox-mcp.exe" "{{ tauri_dir }}/src-tauri/binaries/voicebox-mcp-$triple.exe" -Force; \
Write-Host "Copied sidecar: voicebox-mcp-$triple.exe"
Write-Host "Copied sidecar: voicebox-server-$triple.exe"
# Build CUDA server binary and place in app data dir for local testing
[windows]
+35
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@@ -0,0 +1,35 @@
# See https://help.github.com/articles/ignoring-files/ for more about ignoring files.
# dependencies
/node_modules
/.pnp
.pnp.js
# testing
/coverage
# next.js
/.next/
/out/
# production
/build
# misc
.DS_Store
*.pem
# debug
npm-debug.log*
yarn-debug.log*
yarn-error.log*
# local env files
.env*.local
# vercel
.vercel
# typescript
*.tsbuildinfo
next-env.d.ts
+100
View File
@@ -0,0 +1,100 @@
# Voicebox Landing Page
Landing page for voicebox.sh - a modern Next.js 16 application.
## Tech Stack
- **Next.js 16** with App Router
- **Bun** for package management
- **Tailwind CSS** with shadcn/ui components
- **TypeScript** with strict mode
- **Railway** deployment ready
## Getting Started
### Prerequisites
- Bun installed ([bun.sh](https://bun.sh))
### Installation
```bash
cd landing
bun install
```
### Development
```bash
bun run dev
```
Open [http://localhost:3000](http://localhost:3000) to view the landing page.
### Build
```bash
bun run build
```
### Production
```bash
bun run start
```
## Configuration
### Update Download Links
Edit `src/lib/constants.ts` to update:
- `LATEST_VERSION` - Current release version
- `DOWNLOAD_LINKS` - GitHub release download URLs
- `GITHUB_REPO` - Repository URL
### Update GitHub Username
Replace `USERNAME` in `src/lib/constants.ts` with your actual GitHub username.
## Deployment to Railway
1. Connect your GitHub repository to Railway
2. Railway will auto-detect `nixpacks.toml`
3. Set root directory to `landing/`
4. Railway will automatically:
- Install dependencies with `bun install`
- Build with `bun run build`
- Start with `bun run start`
5. Configure custom domain `voicebox.sh` in Railway settings
## Project Structure
```
landing/
├── src/
│ ├── app/
│ │ ├── layout.tsx # Root layout with metadata
│ │ ├── page.tsx # Landing page
│ │ └── globals.css # Global styles
│ ├── components/
│ │ ├── Header.tsx # Top navigation
│ │ ├── Footer.tsx # Footer
│ │ ├── DownloadSection.tsx # Download buttons
│ │ └── ui/ # shadcn/ui components
│ └── lib/
│ ├── utils.ts # Utility functions
│ └── constants.ts # App constants
├── public/
│ └── voicebox-logo.png # Logo asset
└── nixpacks.toml # Railway deployment config
```
## Features
- Responsive design (mobile-first)
- Dark mode by default
- SEO optimized metadata
- Download links for Mac, Windows, Linux
- Feature showcase
- Platform highlights
- GitHub integration
+18
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@@ -0,0 +1,18 @@
{
"$schema": "https://ui.shadcn.com/schema.json",
"style": "default",
"rsc": true,
"tsx": true,
"tailwind": {
"config": "tailwind.config.js",
"css": "src/app/globals.css",
"baseColor": "slate",
"cssVariables": true,
"prefix": ""
},
"aliases": {
"components": "@/components",
"utils": "@/lib/utils",
"ui": "@/components/ui"
}
}
+12
View File
@@ -0,0 +1,12 @@
/** @type {import('next').NextConfig} */
const nextConfig = {
reactStrictMode: true,
output: 'standalone',
images: {
unoptimized: false,
formats: ['image/avif', 'image/webp'],
},
turbopack: {},
};
module.exports = nextConfig;
+11
View File
@@ -0,0 +1,11 @@
[phases.setup]
nixPkgs = ["nodejs_20", "bun"]
[phases.install]
cmds = ["bun install"]
[phases.build]
cmds = ["bun run build"]
[start]
cmd = "bun run start"
+38
View File
@@ -0,0 +1,38 @@
{
"name": "@voicebox/landing",
"version": "0.5.0",
"description": "Landing page for voicebox.sh",
"scripts": {
"dev": "next dev --turbo",
"build": "bun --bun next build",
"start": "bun --bun next start",
"lint": "next lint"
},
"dependencies": {
"@fontsource/space-grotesk": "^5.2.10",
"@icons-pack/react-simple-icons": "^13.13.0",
"@radix-ui/react-separator": "^1.1.8",
"@radix-ui/react-slot": "^1.2.4",
"autoprefixer": "^10.4.17",
"class-variance-authority": "^0.7.1",
"clsx": "^2.1.1",
"framer-motion": "^12.36.0",
"gray-matter": "^4.0.3",
"lucide-react": "^0.316.0",
"marked": "^18.0.5",
"next": "^16.1.3",
"postcss": "^8.4.33",
"react": "^18.2.0",
"react-dom": "^18.2.0",
"tailwind-merge": "^3.4.0",
"tailwindcss": "^3.4.1",
"tailwindcss-animate": "^1.0.7",
"wavesurfer.js": "^7.12.2"
},
"devDependencies": {
"@types/node": "^20.11.5",
"@types/react": "^18.2.48",
"@types/react-dom": "^18.2.18",
"typescript": "^5.3.3"
}
}
+6
View File
@@ -0,0 +1,6 @@
module.exports = {
plugins: {
tailwindcss: {},
autoprefixer: {},
},
};
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