Palash Debnath
3008f89919
The engine matrix (five columns, three-line rows, every chip on every row) becomes a shadcn table with three columns — Engine · Runs on · Status — and one primary action per row (Use / Install). Everything else lives in a detail panel for the selected row: GPU compatibility chips, isolation, hints and reasons, health and self-test probes, one-click install progress, setup snippet, disk usage, docs, license, the curated-model picker, and now the engine's downloadable WEIGHTS. Weights belong to their engine: every models.yaml entry names the backend ids that load it (`engines:`), the detail panel lists and installs them (EngineWeights, on the model store's install/cancel/remove flow via the extracted useModelDownloads hook), and the sherpa-onnx engine shows its dictation-model picker there. The page's "Downloaded weights" list and recommendation card are gone; only weights no engine owns (speaker diarisation) remain in a small "Other weights" list. A backend test pins the mapping: every entry has an `engines` list and every id is a real backend. - useEngineInventory: the matrix's state machines extracted verbatim (shared/local fetch, residency, health/self-test cooldowns, install poller with overlap guard + epoch, disk-usage generations, license). - Row status phrases: GPU active / CPU fallback / CPU / Available / Needs setup / Installing… / failed; routing "unavailable" never reads Ready. Group captions keep "Ready to use" / "Add more engines". - Engine titles read "Engines" (each locale's own word); backend "Model Catalogue → Engines/Models" messages and docs updated to the new structure. - Dead matrix CSS (phone-tier grid) removed; scopeReco and RecoBanner gone.
4.2 KiB
VoiceStudio — OmniVoice GGUF Engine
OmniVoice GGUF runs the same OmniVoice model as the default
engine, but through a bundled native binary
(bin/omnivoice-tts-<platform>) loading quantized GGUF weights. It is
hardware-adaptive: a probe picks the quantization that fits your machine, so
small GPUs and CPU-only hosts get a working OmniVoice instead of a paging,
timing-out one.
When to pick it
- Your GPU is below the default engine's 6 GB VRAM floor.
- CPU-only machines that still want OmniVoice's voice and language coverage.
- You want generation isolated in a separate process (a crash or leak never takes the app down — each generation spawns the binary fresh).
Quantization selection
Weights come from the Serveurperso/OmniVoice-GGUF HuggingFace repo, pinned
to an exact revision. The hardware probe selects:
| Hardware | Quant | Approx. VRAM use |
|---|---|---|
| 12 GB+ VRAM | BF16 | ~1.6 GB (quality-first) |
| 4–12 GB VRAM | Q8_0 | ~945 MB (recommended balance) |
| 1–4 GB VRAM | Q4_K_M | ~659 MB (minimal footprint) |
| CPU-only | Q4_K_M | RAM-bound, latency-tolerable |
You can override the selection from Settings; overrides are allow-listed against the same table (an F32 reference quant, ~3.2 GB, is override-only).
Setup
Nothing to install: installer and CI builds bundle the binary for your
platform. Select the engine via Model Catalogue (TTS tab → Use) or
OMNIVOICE_TTS_BACKEND=omnivoice-gguf. The quant weights download on first
use (see downloading-models.md) — install them
ahead of time from Model Catalogue (TTS tab → the engine's Weights) if you want the first
generation to be quick; a long first render is the download, not a hang.
Source checkouts: the repo ships zero-byte placeholders in bin/ — real
binaries come from CI or the installer. The engine detects a placeholder and
reports unavailable with instructions
(#1172) instead of
failing at spawn time; build one with
scripts/build-omnivoice-tts.sh --platform <slug> or use the default
in-process engine.
Linux ARM64 (Asahi Apple Silicon): the linux-aarch64 binary prefers
GGML's Vulkan backend when built on a host with glslc and the Khronos
SPIRV headers installed (Arch: pacman -S shaderc spirv-headers; Debian:
apt install glslc libvulkan-dev spirv-headers), so Apple GPUs accelerate
generation through the open-source Honeykrisp driver. Without those deps the
build falls back to CPU. Expect roughly 2–4x slower generation than macOS
Metal while upstream Mesa and llama.cpp Vulkan optimizations mature; still
well ahead of CPU-only.
Integrity and self-healing
Before reporting ready, the engine:
- verifies the binary against the SHA-256 manifest (
bin/checksums.sha256); - detects macOS Gatekeeper quarantine and prints the exact
xattr -cr '/Applications/VoiceStudio.app'fix; - restores a missing execute bit (a git clone or zip extract on POSIX can
drop
+x, which used to surface as a permission error mislabeled as out-of-memory — #437). The chmod runs only after the SHA check confirms it's the right file.
Behaviour notes
- Output is 24 kHz mono — same model, same rate as in-process OmniVoice.
- Cloning from a reference clip (with optional transcript) and style instructions are supported; no voice design.
- Same multilingual surface as OmniVoice (languages.md).
- Because generation runs in another process, the app's own GPU counters don't see its allocations — diagnostics label it accordingly.
| Variable | Default | Meaning |
|---|---|---|
OMNIVOICE_GGUF_GENERATE_TIMEOUT_S |
(generous built-in) | Per-generation timeout for the spawned binary |
Troubleshooting
- "GGUF binary missing": this build doesn't bundle the runtime for your platform — use the default engine.
- Checksum mismatch or quarantine messages: follow the printed fix, or reinstall.
- Other issues: install/troubleshooting.md.
See also: benchmarks.md, performance.md, disk usage.