The 2026-09-06 headscale cutover retired irv-ml1's wg0 tunnel IP 10.100.79.3
(now 10.6.110.50). Repointed all LIVE canonical refs to the DNS NAME so the next
move can't re-break them: homepage.href/siteMonitor labels across 25 stack
composes, load-bearing env defaults (asset-engine INFERENCE_HOST, open-webui
AUDIO_TTS_OPENAI_API_BASE_URL, skaldsong SKALDSONG_TTS_BASE_URL, zonos-gateway
ZONOS_URL, dia), homepage services.yaml manual cards (Voice Design Studio,
IRV-ML1), and servers/irv-ml1/ssh-target. Updated the stale 'WG tunnel' comment
to the mesh reality.
Left as-is: README curl-examples and .env.example comments (docs), and historical
mentions in CLAUDE.md/persistent-memory. NOTE: applying the label repoints to the
RUNNING irv-ml1 containers needs a recreate per service (labels read at creation);
deployed .env values are separate from these canonical defaults.
Move the ~22-service flat "AI Systems" group off the Main tab into a new
four-tab layout (Main / AI / Infrastructure / Toolchain). The AI tab sorts
the inference fleet by function into seven groups:
AI - Inference gen, char-rp, char-rp-reasoning, Granite summarizer
AI - Eval & Retrieval Selene, Skywork Reward, Qwen3 rerank/embed, image-bench
AI - Gateways & Chat LiteLLM, Asset Engine, Gateway Chat, Open WebUI, ...
AI - Speech (TTS) Chatterbox Fast, Kokoro, mOrpheus
AI - Audio Tools Parakeet ASR, YT Voice Clipper
AI - Image & Media ComfyUI, Arbo
AI - Dormant stopped rollback seats + retired auditions
Relabel each stack's homepage.group so canonical stacks/ matches the live
containers on ana-ml2, ana-docker, and irv-ml1. Dormant stacks were refreshed
with `docker compose up --no-start` so they carry the new label while staying
stopped (compose-start rollback preserved). settings.yaml drives tab/order/
columns; services.yaml and README updated to the new scheme.
Empirical follow-up to the streaming /tts smoke test on the 3090. OmniVoice
is diffusion: a ~fixed per-call overhead (~1.5s at 32 steps, ~0.7s at 16)
dominates regardless of chunk length, so the upstream-claimed 40x RTF does
NOT hold here (measured ~2.8x/32-step, ~5.6x/16-step) and the chatterbox-
tuned scheduler over-chunks and starves.
- Streaming /tts defaults to num_step=16 (TTFA ~1.5s -> ~0.7s); batch
/v1/audio/speech stays num_step=32 for quality. Per-request override intact.
- Scheduler prior raised to rtf_prior=20 (env OMNIVOICE_STREAM_RTF_PRIOR,
wired through compose + .env.example) so it packs whole-text-minus-first-
sentence into a few chunks: validated ~3 chunks, no starvation, total wall
~= one-shot, less per-chunk silence padding.
- Docs corrected: the "sub-second / 40x" claims were wrong; streaming has a
diffusion TTFA floor (~0.7s) and wins mainly on long replies. chatterbox-
fast (autoregressive, ~0.5s TTFA) stays the lowest-latency front-end;
OmniVoice is the multilingual / voice-design complement.
Add a live-consumer streaming path and text sanitation to the OmniVoice
wrapper, so it can front speech-to-speech chat engines (not just the
asset-engine's batch WAV use).
- POST /tts: chunked 24 kHz mono s16le PCM (or open-ended WAV), driven by
the adaptive buffer-ratchet scheduler. Emits the first sentence
immediately, then ratchets chunk size up on OmniVoice's ~40x realtime
headroom -> sub-second time-to-first-audio. Wire-compatible with
chatterbox-fast /tts (both 24 kHz mono PCM). Batch /v1/audio/speech is
unchanged for asset/file callers.
- scheduler.py: VENDORED byte-faithful copy of chatterbox-fast's pure-
Python (torch-free) scheduler, pinned to commit 7631462 (v0.1.0/v0.1.1).
Vendor-copy over a shared package (operator call 2026-06-19): the module
has no GPU deps, so reuse it without dragging chatterbox-fast's torch
tree into this image. Promote to a shared package only on a 3rd consumer
or real drift.
- sanitize.py: language-safe TTS sanitizer run on both endpoints. Strips
markdown, <think> blocks, HTML, and model control tokens; deliberately
SKIPS the fork's English-only number/phone normalization that would
corrupt OmniVoice's 600-language input. Preserves [laughter]-style tags.
- Refactor: shared GenParams base for SpeechRequest + TTSStreamRequest;
single GEN_LOCK serializes generation (single-stream interactive).
- Dockerfile/playbook: copy + upload the two new modules; build-time
`import app` smoke; correct stale "Gradio demo / no FastAPI" comments.
Wrapper /v1/audio/speech now accepts OmniVoice's whole surface:
- voice (clone, now OPTIONAL) and/or instruct (voice DESIGN). instruct is a CONTROLLED
vocabulary (gender/age/pitch/accent/whisper tags, comma-separated), not free prose —
discoverable at the new /v1/audio/instruct-items endpoint (23 items).
- language (Auto + 647, new /v1/audio/languages endpoint), speed, duration.
- diffusion controls: num_step, guidance_scale, denoise, preprocess_prompt,
postprocess_output; plus a generation_overrides JSON passthrough for expert
GenerationConfig knobs (t_shift, layer_penalty_factor, position/class temperature,
audio_chunk_*).
- at least one of voice/instruct required (else 400).
Catalog (services.yaml): omnivoice v1 -> v2, 13 schema-valid fields; instruct as a
controlled-vocab text field sourced from the items endpoint.
Verified live on irv-ml1: clone, voice-design (instruct-only), and tuned-param synths
all -> 24 kHz PCM_16 WAV; 647 languages; 23 instruct items.
- app.py: thin FastAPI wrapper exposing OpenAI /v1/audio/speech (+ /v1/audio/voices,
/healthz) around OmniVoice's Python API; precomputes a voice-clone prompt per voice
at startup (loaded Whisper auto-transcribes each reference). Replaces the Gradio demo.
- Dockerfile/compose: run the uvicorn wrapper, /healthz healthcheck, project name pinned
to "omnivoice" so the asset-engine liveness probe matches.
- deploy-omnivoice.yaml: stage chatterbox /refs/*.wav as clone voices (skip _* artifacts)
+ verify the API surface.
- services.yaml: catalog entry (id omnivoice, :8199/v1/audio/speech, voice list sourced
live from /v1/audio/voices) + reproducibility_audit row.
Verified live on irv-ml1: /healthz ok, 33 voices loaded, test synth -> 24kHz PCM_16 WAV.
Zero-shot, massively-multilingual (600+ language) voice-cloning + voice-design
TTS (diffusion-LM, Apache-2.0). No official image, so a thin CUDA container
around the pip package running upstream's own Gradio demo (no FastAPI wrapper).
Pinned to GPU 0 (3090) — the A6000 is ComfyUI-exclusive — port 8199. Built +
verified live on irv-ml1 (Gradio 200, container healthy). Surface is the Gradio
UI + Gradio API, NOT OpenAI-compat /v1/audio/speech (wrap later if asset-engine
should consume it). deploy-omnivoice.yaml builds local + verifies.
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