docs(vault): fleet-wide fact re-verification pass (67 pages)
The docs-fact census wave re-read the live hosts and re-keyed every page it could: runtime/payload identities, ports, sizes, ledger figures, unit state, and the retirement banners that drifted as the fleet moved. The wave was interrupted mid-run, so this commit carries only what passed the integrity gates: every touched page parses (front matter or H1+status convention intact, balanced fences, no truncated tables, trailing newline), the docs_completeness and link-integrity seams are green, and bats is 384/384. Numbers that this session proved on live hosts are keyed to the measured value, not the page's earlier claim.
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@@ -10,7 +10,7 @@ tags:
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- stt
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- vllm-omni
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- kokoro
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timestamp: 2026-09-22T00:00:00Z
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timestamp: 2026-10-18T00:00:00Z
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---
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# Local TTS and Voice Cloning
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@@ -19,7 +19,10 @@ Research brief (2026-09-22) on creating a new local TTS voice from sample
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files, the open-weight voice-cloning landscape, the full local AI audio
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stack, and a recommended deployment for the fleet. Every claim is cited in
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[Citations](#citations). The fleet has no audio input today (that capability
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left with the retired NPU endpoint), so this is greenfield.
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left with the retired NPU endpoint, returned with the Gemma4 audio projector on
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2026-09-17, and left again with that retirement on 2026-10-01 — audio is still
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greenfield: every fleet endpoint declares `input: [text, image]`
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(`~/.omp/agent/models.yml:63,149,214`).
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## Summary
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@@ -31,20 +34,26 @@ left with the retired NPU endpoint), so this is greenfield.
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built-in voice list (a custom pack needs a patch).
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- **The 2026 open-weight cloning landscape is strong.** Permissive-licensed
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leaders for a single-GPU homelab: **Chatterbox (MIT)**, **Qwen3-TTS
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(Apache-2.0)**, **CosyVoice 3 (Apache-2.0)**, **GLM-TTS (MIT)**, **VoxCPM2
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(Apache-2.0)**, **F5-TTS (MIT)**, **GPT-SoVITS (MIT)**.
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- **OMP integration — definitive:** OMP's `tts` tool supports exactly three
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backends (`providers.tts` = `auto|local|xai|deepinfra`, verified in the
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installed binary): local Kokoro ONNX, xAI Grok Voice cloud, DeepInfra cloud.
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**There is no generic OpenAI-compatible TTS endpoint in OMP today.** Two real
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paths for a cloned voice: (a) xAI console custom voice (free, cloud, US-only)
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— works today; (b) patch OMP (open source) with a ~50-line OpenAI-TTS backend
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pointing at a local `vLLM-Omni` server.
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- **Recommended stack:** `vllm/vllm-omni` serving **Qwen3-TTS-1.7B-Base** on the
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3090 (OpenAI-compatible `POST /v1/audio/speech` + `POST /v1/audio/voices`
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voice upload), **Parakeet TDT 1.1B** for English STT, **Silero VAD** embedded,
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**Chatterbox** as the ultra-light English-only alternative. All fit in <8 GB
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VRAM and co-locate with the existing LLM services.
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(Apache-2.0)**, **CosyVoice 3 (Apache-2.0)**, **GLM-TTS (MIT weights)**,
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**VoxCPM2 (Apache-2.0)**, **F5-TTS (MIT)**, **GPT-SoVITS (MIT)**.
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- **OMP integration (re-verified 2026-10-18):** the speech tool is gated by
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`speechgen.enabled` and resolves models through the **`speech` role and its
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fallback chain** (`modelRoles.speech`; this workstation runs
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`local/kokoro`). Three APIs: local Kokoro ONNX (always WAV/PCM16), `xai-tts`,
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and **`openai-speech` — a generic OpenAI-compatible `/v1/audio/speech`
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client** (MP3 or WAV, `voice_id` forwarded only when explicitly set, 15 000
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characters max; DeepInfra is now just a model on that API). The 2026-09-22
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finding that OMP has *no* configurable OpenAI TTS endpoint is **retired**: a
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local server needs a speech-role entry, not a patch.
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- **Fleet plan (2026-10-18): CPU-only on Dankclaw, not the 3090.** Gitea issue
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#2 rules out every GPU option (the 3090 has carried frank-zealot since
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2026-10-17; both R9700s are frank-archon's), so the shape is a VoxCPM2 GGUF
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engine on **8880** behind a voice-registry shim on **8890**
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(`scripts/voiceshim.env`, `dankclaw/voiceservice/`) that speaks OpenAI
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`/v1/audio/speech` and resolves voices by name. Nothing is deployed yet — on
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2026-10-18 `voiceshim` has no unit installed and nothing answers on 8880 or
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8890. STT (Parakeet TDT 1.1B, CC-BY-4.0) stays on CPU. **No RTF or quality
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number has been measured for this shape**, so this page states none.
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## Can Kokoro learn a new voice?
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@@ -70,18 +79,25 @@ running a modern zero-shot cloner on the same GPU.
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## 2026 voice-cloning landscape (permissive-licensed, single-GPU)
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Ranked for a 3090 homelab, English-primary, personal voice:
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Ranked (2026-09-22) for a 3090 homelab, English-primary, personal voice; the
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2026-10-18 fleet decision below moved this work off the GPU entirely:
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1. **Chatterbox (MIT)** — best license/quality/compute ratio; ~10 s reference;
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110–500 M; ~1–2 GB VRAM; CPU-capable (Nano). *Top pick for a personal
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English voice.* No official server (library + Gradio; wrap in FastAPI).
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1. **Chatterbox (MIT)** — best license/quality/compute ratio; ~10 s reference
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(the README's own example is `your_10s_ref_clip.wav`); 110 M (Nano) to 0.5 B
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(Turbo/Multilingual); ~1–2 GB VRAM *(unverified 2026-10-18)*; Nano is
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documented for CPU — "3x faster than realtime on 8 CPU cores". *Top pick for
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a personal English voice.* No server in the README (library use only; wrap
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it yourself); every generated file carries Resemble's PerTh watermark.
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2. **Qwen3-TTS-1.7B-Base (Apache-2.0)** — 3 s cloning, 10 languages, streaming,
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vLLM-Omni serving with `POST /v1/audio/voices` upload (closest to "named
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voice" semantics), official fine-tuning code. *Top pick for a server-grade,
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vLLM-Omni serving with a `POST /v1/audio/voices` upload *(unverified
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2026-10-18 — the reachable docs do not list it)*, the closest thing to
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"named voice" semantics, official fine-tuning code. *Top pick for a
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OpenAI-compatible deployment.*
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3. **CosyVoice 3 (Apache-2.0)** — 0.5 B, 9 languages + 18 zh dialects, 150 ms
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bi-streaming, FastAPI/WebSocket server.
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4. **GLM-TTS (MIT)** — best published CER (0.89), RL emotion control, zh/en.
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bi-streaming, FastAPI and gRPC servers.
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4. **GLM-TTS (MIT model weights, Apache-2.0 code)** — CER 0.89 after
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multi-reward GRPO (down from 1.03), RL emotion control, zh/en; the prompt
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audio shipped in the repo is marked research-only.
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5. **VoxCPM2 (Apache-2.0)** — 30 languages, 48 kHz, LoRA fine-tune from 5–10 min
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of audio, ~8 GB VRAM. *Best "fine-tune my voice" option.*
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6. **F5-TTS (MIT)** — 0.3–0.5 B, en/zh; Docker + Triton.
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@@ -97,30 +113,36 @@ released). Excluded from cloning: Parler-TTS (style-text only), VibeVoice-TTS
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## OMP integration (definitive)
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OMP's `tts` tool (hidden by default; enable with `/tts`) supports exactly three
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backends, selected by `providers.tts`:
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The tool ships hidden and is enabled by `speechgen.enabled`
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(`~/.omp/agent/config.yml:222-223`); the harness docs list it as "Generate
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speech". Models come from the **`speech` role and its fallback chain**, not
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from a hardcoded backend list (`modelRoles.speech`,
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`~/.omp/agent/config.yml:16` = `local/kokoro` today):
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| Backend | Endpoint (hardcoded in binary) | Voices |
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| API | Endpoint | Notes (from the installed bundle, 2026-10-18) |
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|---|---|---|
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| `local` | on-device ONNX, `onnx-community/Kokoro-82M-v1.0-ONNX` | built-in list (`tts.localVoice`) |
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| `xai` | `POST https://api.x.ai/v1/tts` | `ara`/`eve`/`leo`/`rex`/`sal` + any custom voice ID |
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| `deepinfra` | `POST https://api.deepinfra.com/v1/openai/audio/speech` | `voice_id` when set |
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| local-inference | on-device ONNX, `onnx-community/Kokoro-82M-v1.0-ONNX` (Apache-2.0) | no network, **always WAV/PCM16**, voice from the built-in list (`tts.localVoice`) |
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| `xai-tts` | `POST https://api.x.ai/v1/tts` | `ara`/`eve`/`leo`/`rex`/`sal` + custom voice IDs; MP3 or WAV |
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| `openai-speech` | `POST <provider baseUrl>/audio/speech` | the generic OpenAI-compatible client — MP3 or WAV, `voice_id` forwarded **only when explicitly set**, 15 000-character cap on `input`; DeepInfra is one model entry on it (`https://api.deepinfra.com/v1/openai`) |
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There is **no generic OpenAI-compatible TTS endpoint** — `deepinfra` is a
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hardcoded URL, not a configurable base URL, and OMP's `models.yml` custom
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providers (LLM chat only) do not wire into the `tts` tool.
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The 2026-09-22 finding — "**no generic OpenAI-compatible TTS endpoint** …
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`deepinfra` is a hardcoded URL, not a configurable base URL" — is **retired**:
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`openai-speech` is that configurable client, selected by putting a model on the
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`speech` role. Still true from the original audit: the local Kokoro backend
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accepts only its built-in voice list, so a custom pack needs a patch.
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Paths for a Frank-cloned voice:
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Paths for a Frank-cloned voice (2026-10-18):
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1. **xAI console custom voice — works today, zero code.** Record 2–3 min clean
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speech (≤120 s, 24 kHz 16-bit mono WAV) → console → `voice_id` → `tts` tool.
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Free (≤30 voices), cloud, US-only.
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2. **Local, full stack — small OMP patch.** OMP is open source; the DeepInfra
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backend is a plain HTTP POST to an OpenAI-compatible speech endpoint. A
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~50-line `openai` backend (configurable `base_url` + `voice`) lets OMP call
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any local server (vLLM-Omni, Kokoro-FastAPI, Chatterbox wrapper).
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3. **No-patch workaround.** OMP's `bash` tool can `curl` the local TTS server
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ad hoc.
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1. **Local server + speech role, no patch.** Register the local engine (or the
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8890 voice shim) as a provider model on the `openai-speech` API and point
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`modelRoles.speech` at it; the shim turns a voice *name* into a reference
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clip and forwards it as base64 `reference_audio`
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(`scripts/voiceshim.env:19-35`). Not deployed as of 2026-10-18.
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2. **xAI console custom voice — works today, zero code.** Record 2–3 min clean
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speech (≤120 s, 24 kHz 16-bit mono WAV) → console → `voice_id` → speech
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tool. Free (≤30 voices), cloud, US-only.
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3. **No-patch workaround.** The `bash` tool can `curl` the local TTS server ad
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hoc, and the harness `tts` device writes a speech file to a path you give it.
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4. **Kokoro fine-tune → OMP local backend.** Highest effort, Kokoro-styled.
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## Full local AI audio stack
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@@ -136,34 +158,77 @@ Canary 1B v2 (multilingual); Moonshine (MIT, on-device); VibeVoice-ASR-7B (MIT,
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faster-whisper/whisperX).
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**TTS serving:** **vLLM-Omni** ([vllm-project/vllm-omni](https://github.com/vllm-project/vllm-omni),
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official Docker `vllm/vllm-omni` CUDA and `vllm/vllm-omni-rocm` ROCm, e.g.
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`:v0.28.0`) is the one server exposing the standard OpenAI speech API
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(`POST /v1/audio/speech` + `POST /v1/audio/voices` upload for Qwen3-TTS) across
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the 2026 lineup. CUDA needs compute ≥7.0 (3090 = 8.6 ✓); ROCm validated on
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gfx942 (the fleet already runs vLLM on the R9700 gfx1201 ✓). Others:
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Kokoro-FastAPI (Docker, :8880, OpenAI-shaped), CosyVoice FastAPI/WS, F5-TTS
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Gradio/Triton, GPT-SoVITS WebUI/api_v2, Fish S2 `tools/api_server.py` (own
|
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format, not OpenAI-shaped).
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Apache-2.0) publishes the official images `vllm/vllm-omni` (CUDA) and
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`vllm/vllm-omni-rocm` (ROCm), both tagged `v0.28.0` (Docker Hub tag lists,
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2026-10-18), and serves Qwen3-TTS (`docs/models/supported_models.md`). It
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serves the OpenAI speech path `POST /v1/audio/speech`; the
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`POST /v1/audio/voices` upload route is *(unverified 2026-10-18)* — the docs
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reachable today do not document it. Its gfx942/gfx950 validation note is a
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footnote scoped to MiniMax H3 diffusion, **not** to TTS, and the fleet runs no
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vLLM anywhere: the R9700s carry radiance as frank-archon
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(`scripts/serve-frank-archon.sh:2`). It is also no longer "the one server" with
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the OpenAI shape — llama.cpp's own `llama-tts-server` has it too (next
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section). Others: Kokoro-FastAPI (Docker, :8880, Apache-2.0), CosyVoice
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**FastAPI and gRPC** (`runtime/python/fastapi`, `runtime/python/grpc`; the
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README documents no WebSocket server), F5-TTS Gradio/Triton, GPT-SoVITS
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WebUI/api_v2, Fish S2 `tools/api_server.py` (own format, not OpenAI-shaped).
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**Post-processing:** SoX/ffmpeg (resample/normalize; 24 kHz mono 16-bit is the
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reference-clip standard); Demucs (`htdemucs`) for vocal separation before
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cloning; the Perth watermark is built into Chatterbox.
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## llama.cpp-native TTS serving (verified 2026-10-18)
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The CPU shape does not need a Python server at all:
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- **`llama-tts-server`** ([`tc-mb/llama.cpp-omni`](https://github.com/tc-mb/llama.cpp-omni),
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MIT, "Omni inference in C/C++") is a standalone OpenAI-compatible TTS server
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that runs without an LLM model (build target `llama-tts-server`).
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`POST /v1/audio/speech` takes `model` (`"voxcpm"`, also accepts `"voxcpm2"`),
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`input`, `voice` — documented **"reserved"**, so do not build named-voice
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semantics on it — `response_format` (`wav`/`pcm`), `reference_audio`
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(base64 WAV for cloning), `seed` 42, `cfg_value` 2.0, `inference_timesteps`
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10, `max_steps` 200, `temperature` 1.0. `POST /v1/audio/speech/stream`
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returns chunked WAV; `POST /v1/voxcpm2/init` hot-loads a runtime from
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`base_lm` + `acoustic` GGUFs with `n_gpu_layers` (`-1` = all);
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`GET /v1/audio/speech/models` lists what is loaded
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(`tools/omni/voxcpm2/README.md`:232, 321-354).
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- **Mainline `llama-tts`** (ggml-org/llama.cpp) has `--tts-speaker-file` for a
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speaker reference with **Qwen3-TTS** and with **Kyutai Pocket-TTS** — the
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latter requires it ("the model produces almost no audio without it"), and
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Pocket-TTS converts one `languages/<name>` directory, never the repo root
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(`tools/tts/README.md`:20-58; `kyutai/pocket-tts` is CC-BY-4.0).
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- **VoxCPM2 GGUF provenance:** `openbmb/VoxCPM2` publishes **PyTorch weights
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only** (`model.safetensors`, no `.gguf` sibling — HF API 2026-10-18). The
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GGUFs the fork loads come from
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[`DennisHuang648/VoxCPM2-GGUF`](https://huggingface.co/DennisHuang648/VoxCPM2-GGUF)
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(`VoxCPM2-BaseLM-F16.gguf`, `VoxCPM2-BaseLM-Q8_0.gguf`,
|
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`VoxCPM2-Acoustic-F16.gguf`, Apache-2.0 card) or from the fork's own
|
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`tools/omni/voxcpm2/convert_voxcpm2_to_gguf.py`.
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Nothing has been measured on this fleet for any of these engines — no RTF, no
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latency, no MOS. That absence is the finding, not an omission.
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## Recommended deployment (Dankclaw)
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TTS models are 0.1–2 B (<8 GB VRAM); STT (Parakeet 1.1 B) is CPU-fast. Keep it
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all on Dankclaw (3090 = primary GPU, CUDA = best vLLM-Omni support); the
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Dankserver R9700s stay dedicated to frank-medium.
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As decided in Gitea issue #2, this stays **CPU-only on Dankclaw**: the RTX 3090
|
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has carried frank-zealot since 2026-10-17 and both R9700s are frank-archon's,
|
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so no card may be asked to co-host TTS. The shape is one engine plus a thin
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voice shim, and **nothing here is deployed as of 2026-10-18** — `systemctl
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--user is-enabled voiceshim` reports `not-found` and nothing answers on 8880 or
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8890.
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| Service | Image / install | Port | GPU | Notes |
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| Service | Image / install | Port | CPU | Notes |
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|---|---|---|---|---|
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| TTS (primary, cloning) | `vllm/vllm-omni:v0.28.0` · `vllm serve Qwen/Qwen3-TTS-12Hz-1.7B-Base --omni --port 8881 --gpu-memory-utilization 0.35` | 8881 | 3090 (~6 GB) | OpenAI `/v1/audio/speech`; upload Frank's voice once via `/v1/audio/voices`; 3 s cloning; 10 langs; Apache-2.0 |
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| TTS (light, English) | Chatterbox (MIT) in a small FastAPI container | 8880 | 3090 (~1 GB) / CPU | 10 s ref clip; wrap `chatterbox.generate` in ~30 lines |
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| STT (English) | Parakeet TDT 1.1B behind a FastAPI wrapper, or whisper.cpp server | 8882 | CPU | CC-BY-4.0; WER 1.39% |
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||||
| STT (multilingual, opt.) | faster-whisper `large-v3` int8 | 8883 | CPU / iGPU | MIT |
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| VAD | Silero (embedded) | — | CPU | MIT |
|
||||
| TTS engine | `llama-tts-server` (`tc-mb/llama.cpp-omni`) on a VoxCPM2 GGUF; `vllm/vllm-omni` + Qwen3-TTS only if a GPU is ever deliberately freed | 8880 | engine decision still open | OpenAI `/v1/audio/speech`; `n_gpu_layers` is there for a GPU boot |
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| Voice shim | `dankclaw/voiceservice/` (stdlib container) + `scripts/voiceshim.env` + `dankclaw/voiceservice/quadlet/voiceshim.container` | 8890 | yes | voice *name* → `reference.wav`, `voice`/`voice_id` on the wire, mp3 re-encode; backends `omni-http` (forwards base64 `reference_audio`) and `llama-tts-cli` (`--tts-speaker-file`, `nice 19`) |
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| STT (English) | Parakeet TDT 1.1B behind a FastAPI wrapper, or whisper.cpp server | 8882 | yes | CC-BY-4.0; LibriSpeech-clean WER 1.39 (model card) |
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||||
| STT (multilingual, opt.) | faster-whisper `large-v3` int8 | 8883 | yes | MIT |
|
||||
| VAD | Silero (embedded) | — | yes | MIT; model file 2 327 524 B |
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Ports 8880–8883 avoid the fleet's LLM ports (7770/7771).
|
||||
8880/8890 are what `scripts/voiceshim.env:35,49` carry (`TTS_UPSTREAM=
|
||||
http://host.containers.internal:8880`, `SHIM_PORT=8890`); 8882-8883 for STT
|
||||
keep clear of the fleet's LLM ports 7770/7771.
|
||||
|
||||
## Voice-creation workflow (the "from sample files" answer)
|
||||
|
||||
@@ -190,17 +255,22 @@ Ports 8880–8883 avoid the fleet's LLM ports (7770/7771).
|
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non-commercial (Higgs v3, Breeze-TTS-2, Spark-TTS, Voxtral) or carry custom
|
||||
licenses (IndexTTS, Fish S2, XTTS v2). For a personal homelab voice, MIT /
|
||||
Apache-2.0 (Chatterbox, Qwen3-TTS, GLM-TTS, VoxCPM2) is the safe set.
|
||||
- **Co-locate on the 3090** with a low `--gpu-memory-utilization` (~0.35) so the
|
||||
TTS engine shares the card with frank-zealot; move to the R9700s only if TTS
|
||||
throughput demand grows.
|
||||
- **Keep TTS off the GPUs.** The 2026-09-22 advice to "co-locate on the 3090 at
|
||||
`--gpu-memory-utilization ~0.35`" is retired: that card belongs to
|
||||
frank-zealot (2026-10-17) and the R9700s to frank-archon, and Gitea issue #2
|
||||
measures both as full. Run TTS on CPU; revisit only if the operator frees a
|
||||
card on purpose.
|
||||
- **Guard the endpoint like any other service:** if vhosted, it goes behind the
|
||||
Anubis → Authentik chain; non-browser clients (OMP's `curl`) must target the
|
||||
internal address, never the public hostname.
|
||||
|
||||
## Citations
|
||||
|
||||
- OMP TTS tool: https://omp.sh/docs/tools/tts · installed binary
|
||||
`@oh-my-pi/pi-coding-agent/dist/cli.js` (endpoints, voices, model IDs)
|
||||
- OMP speech tool: https://omp.sh/docs/tools ("Generate speech", gated by
|
||||
`speechgen.enabled`; the old `https://omp.sh/docs/tools/tts` path returns 404
|
||||
as of 2026-10-18) · installed binary
|
||||
`@oh-my-pi/pi-coding-agent/dist/cli.js` (the `openai-speech` API, the
|
||||
15 000-character cap, the `voice_id` forwarding rule, local Kokoro WAV-only)
|
||||
- Kokoro: https://github.com/hexgrad/Kokoro ·
|
||||
https://huggingface.co/spaces/hexgrad/Kokoro-TTS
|
||||
- Kokoro fine-tune: https://github.com/semidark/kikiri-tts
|
||||
@@ -212,6 +282,16 @@ Ports 8880–8883 avoid the fleet's LLM ports (7770/7771).
|
||||
https://huggingface.co/zai-org/GLM-TTS
|
||||
- VoxCPM2: https://github.com/OpenBMB/VoxCPM ·
|
||||
https://huggingface.co/openbmb/VoxCPM2
|
||||
- llama.cpp-omni TTS server: https://github.com/tc-mb/llama.cpp-omni ·
|
||||
https://raw.githubusercontent.com/tc-mb/llama.cpp-omni/master/tools/omni/voxcpm2/README.md
|
||||
- mainline `llama-tts`:
|
||||
https://raw.githubusercontent.com/ggml-org/llama.cpp/master/tools/tts/README.md ·
|
||||
Pocket-TTS weights: https://huggingface.co/kyutai/pocket-tts (CC-BY-4.0)
|
||||
- VoxCPM2 GGUFs (not published by OpenBMB):
|
||||
https://huggingface.co/DennisHuang648/VoxCPM2-GGUF
|
||||
- GLM-TTS license split: model card `mit` (HF API 2026-10-18) vs code
|
||||
`LICENSE` (Apache-2.0):
|
||||
https://raw.githubusercontent.com/zai-org/GLM-TTS/main/LICENSE
|
||||
- F5-TTS: https://github.com/SWivid/F5-TTS
|
||||
- GPT-SoVITS: https://github.com/RVC-Boss/GPT-SoVITS
|
||||
- Dots.TTS: https://huggingface.co/dots-studio/dots.tts-base
|
||||
|
||||
Reference in new issue
Block a user