stacks: add dia + zonos to the TTS bench
dia: Nari Labs dialogue TTS (Dia 1.6B / Dia2-1B / Dia2-2B) via devnen/Dia-TTS-Server — OpenAI-compat, fills the multi-speaker dialogue-scene slot for skaldsong. Port 8200 on irv-ml1. zonos: Zyphra Zonos-v0.1 (Apache-2.0, 44kHz, emotion sliders) via the official Gradio interface. Audition surface only — no OpenAI-compat endpoint yet (needs the FastAPI fork to become skaldsong-pluggable). Port 8199 on irv-ml1. Both follow the chatterbox/fish-s2 convention: local image built from a pinned wrapper SHA via buildx git-context, .env-driven port/GPU, python healthcheck, homepage labels.
This commit is contained in:
@@ -0,0 +1,56 @@
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# Dia / Dia2 stack tunables. Copy to `.env` on irv-ml1 before deploying.
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# ── build pin ────────────────────────────────────────────────────────
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# SHA of devnen/Dia-TTS-Server. Use the FULL 40-char SHA — docker
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# buildx's git source resolver doesn't accept short hashes. `main`
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# works but is NOT reproducible; pin a SHA before you rely on this in
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# anger (same churn lesson as chatterbox, whose `main` once broke on an
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# upstream path restructure). Latest commits:
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# https://github.com/devnen/Dia-TTS-Server/commits/main
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DIA_SHA=main
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# Local image tag — bump when you change build context to force a
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# fresh layer build.
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DIA_TAG=v1
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# ── network ──────────────────────────────────────────────────────────
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# Host port. Container listens on 8003 internally.
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# Reserved on irv-ml1: 8188 ComfyUI, 8190 CosyVoice, 8191 Qwen3-TTS,
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# 8192 IndexTTS-2, 8193 Kokoro, 8194 VibeVoice, 8195 Fish-S2,
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# 8196 Chatterbox, 8197 Voxtral, 8198 Kyutai, 8199 Zonos, 8765 Parakeet.
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# 8200 picked here.
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DIA_PORT=8200
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# Bind address. 0.0.0.0 exposes on all interfaces (incl. WG tunnel
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# interface 10.100.79.3); 127.0.0.1 restricts to local-only.
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DIA_BIND=0.0.0.0
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# ── runtime / GPU ────────────────────────────────────────────────────
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# Devices visible inside the container. "0" pins to the RTX 3090
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# (24 GB) — Dia at BF16 (~7 GB) fits comfortably. Use "1" for the
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# A6000 if you'd rather keep the 3090 free.
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DIA_GPU_DEVICES=0
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# Model selection is config.yaml-driven in the wrapper (model.repo_id),
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# not a plain env var. Default in-image model is Dia 1.6B. To pin a
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# different default, mount a host config.yaml (see commented volume in
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# compose.yaml) setting one of:
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# nari-labs/Dia-1.6B — original, single/dual-speaker dialogue
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# Dia2-1B — streaming, lower latency
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# Dia2-2B — highest quality
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# Or just switch live from the Web UI at http://<host>:8200/ .
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# ── persistent storage on the host ───────────────────────────────────
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# Reference audio dir for voice cloning / speaker prompts. Drop short
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# reference WAVs here; the wrapper picks them up by filename. Included
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# in restic (cloned voices need the original reference to recreate).
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DIA_REFERENCE_DIR=/worktank/dia/reference_audio
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# HuggingFace cache — Dia/Dia2 checkpoints land here on first start.
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# Bind-mounted so they survive container recreate. Excluded from restic
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# (regenerable from HF).
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DIA_CACHE_DIR=/worktank/dia/cache
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# Optional: host config.yaml to pin a default model + generation
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# defaults. Leave commented in compose.yaml unless you want it.
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# DIA_CONFIG=/worktank/dia/config.yaml
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@@ -0,0 +1,68 @@
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# Dia / Dia2
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Nari Labs' dialogue-focused TTS — generates ultra-realistic
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multi-speaker conversation in a single pass — served via
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[devnen/Dia-TTS-Server](https://github.com/devnen/Dia-TTS-Server), the
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same actively-maintained OpenAI-compat wrapper author as our
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[chatterbox](../chatterbox/) stack. The wrapper carries multi-model
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support for the whole Dia family:
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| Model | HF repo | Notes |
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|---|---|---|
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| Dia 1.6B | [nari-labs/Dia-1.6B](https://huggingface.co/nari-labs/Dia-1.6B) | original, dialogue in one pass (in-image default) |
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| Dia2-1B | Nari Labs Dia2 family | streaming, lower latency |
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| Dia2-2B | Nari Labs Dia2 family | highest quality |
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Dia2 was released 2025-11-19 ([nari-labs/dia2](https://github.com/nari-labs/dia2)).
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**Server:** irv-ml1 (Irvine, WireGuard-only)
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**Port:** 8200 (container listens on 8003)
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**GPUs:** pins to device 0 (RTX 3090) by default; ~7 GB VRAM at BF16
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**Image:** `local/dia:v1` — built locally from a pinned git SHA of the
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wrapper repo via docker buildx's git URL context
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**Upstream wrapper:** [devnen/Dia-TTS-Server](https://github.com/devnen/Dia-TTS-Server) (MIT)
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**Upstream model:** [nari-labs/dia](https://github.com/nari-labs/dia) / [nari-labs/dia2](https://github.com/nari-labs/dia2) (Apache-2.0 weights)
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## Why this stack exists
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Fills the **dialogue-scene** slot none of the other TTS own cleanly.
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Dia generates multi-speaker turn-taking in one pass with inline `[S1]`/
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`[S2]` speaker tags and nonverbal cues — `(laughs)`, `(coughs)`,
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`(sighs)`, `(clears throat)` — directly in the prompt. That's a
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different shape from the single-speaker engines:
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- **Fish S2-Pro / IndexTTS-2 / Chatterbox** are excellent single-voice
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readers (rich emotion, cloning) but you'd have to stitch turns
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yourself.
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- **VibeVoice** does long-form multi-speaker but is podcast/narration
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shaped, not fast turn-taking with nonverbals.
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- **Dia** is the one built for *scene dialogue* — the
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multi-character-storytelling case skaldsong is aimed at.
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OpenAI-compatible (`POST /v1/audio/speech`), so skaldsong can target it
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by base-URL once we add a `dia` engine option to its router.
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## Deploy
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```bash
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# from this workstation (irv-ml1 is WG-only — routes via ana-wg):
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scripts/deploy-stack.sh irv-ml1 dia
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# then on irv-ml1, first run builds the image from the pinned SHA:
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# docker compose up -d --build
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```
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First boot pulls the checkpoint (~6-10 GB) into `DIA_CACHE_DIR` and can
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take several minutes; the healthcheck's 600 s `start_period` covers it.
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## Notes
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- **Pin `DIA_SHA`** to a full 40-char commit before relying on this —
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`.env.example` ships `main` for convenience, but `main` is not
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reproducible (chatterbox learned this when an upstream restructure
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broke its `main` build).
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- **Model switching** is config.yaml-driven in the wrapper, or live from
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the Web UI at `http://10.100.79.3:8200/`. To pin a non-default model
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declaratively, mount a host `config.yaml` (see the commented volume in
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`compose.yaml`).
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- Endpoints: `/v1/audio/speech` (OpenAI-compat), `/health` (liveness),
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`/api/model-status` (download/load progress), `/api/model-info`.
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@@ -0,0 +1,67 @@
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# Dia / Dia2 (Nari Labs' dialogue-focused TTS) served via
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# devnen/Dia-TTS-Server — the same OpenAI-compat wrapper author as our
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# chatterbox stack, with multi-model support for the Dia 2 family
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# (Dia 1.6B / Dia2-1B / Dia2-2B), switchable from the Web UI.
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#
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# Why this stack exists alongside the other TTS:
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# * DIALOGUE scenes with nonverbal cues — Dia generates multi-speaker
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# turn-taking in a single pass with inline [S1]/[S2] speaker tags
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# and nonverbals like (laughs), (coughs), (sighs). Purpose-built for
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# the character-dialogue case skaldsong's storytelling hits, which
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# the single-speaker engines (Fish/Index/Chatterbox) don't own.
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# * Dia2 (released 2025-11-19) adds realtime streaming + a 2B
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# high-quality checkpoint.
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# * Apache-2.0 model weights; MIT wrapper; OpenAI-compat
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# /v1/audio/speech so skaldsong can target it by base-URL.
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# * ~7 GB VRAM at BF16 SafeTensors.
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#
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# Image is built locally from the upstream wrapper via docker buildx
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# git-context (no source vendored on the host) — same pattern as
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# chatterbox/fish-s2.
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#
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# All tunables live in .env — edit that, not this file.
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services:
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dia:
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image: local/dia:${DIA_TAG}
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build:
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# Single Dockerfile at repo root; GPU via NVIDIA Container Toolkit.
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context: https://github.com/devnen/Dia-TTS-Server.git#${DIA_SHA}
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dockerfile: Dockerfile
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container_name: dia
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restart: unless-stopped
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runtime: nvidia
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ports:
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- "${DIA_BIND:-0.0.0.0}:${DIA_PORT}:8003"
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environment:
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- NVIDIA_VISIBLE_DEVICES=${DIA_GPU_DEVICES:-0}
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- NVIDIA_DRIVER_CAPABILITIES=compute,utility
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# Speeds the first-boot HF download of the checkpoint.
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- HF_HUB_ENABLE_HF_TRANSFER=1
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- HF_HOME=/app/hf_cache
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volumes:
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- ${DIA_REFERENCE_DIR}:/app/reference_audio
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- ${DIA_CACHE_DIR}:/app/hf_cache
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# Model selection lives in the wrapper's config.yaml (model.repo_id):
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# mount a host config to pin a default of Dia2-1B / Dia2-2B instead
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# of the in-image default (Dia 1.6B). Otherwise switch live in the
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# Web UI (selection may not survive a container recreate).
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# - ${DIA_CONFIG}:/app/config.yaml
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healthcheck:
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# devnen's Dia server exposes GET /health (liveness) plus
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# /api/model-status (download/load progress) and /api/model-info.
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# /health is the simple liveness probe; start_period covers the
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# first-boot model pull. python urllib (image has no curl), bound
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# to 127.0.0.1 (uvicorn is IPv4-only).
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test: ["CMD-SHELL", "python3 -c \"import urllib.request,sys; urllib.request.urlopen('http://127.0.0.1:8003/health', timeout=5); sys.exit(0)\""]
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interval: 30s
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timeout: 10s
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retries: 3
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# First boot pulls the checkpoint (~6-10 GB) — generous deadline.
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start_period: 600s
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labels:
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- homepage.group=AI Systems
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- homepage.name=Dia / Dia2
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- homepage.icon=mdi-account-voice
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- homepage.description=Dialogue TTS — multi-speaker turn-taking + nonverbals (irv-ml1)
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- homepage.href=http://10.100.79.3:${DIA_PORT}
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@@ -0,0 +1,44 @@
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# Zonos-v0.1 stack tunables. Copy to `.env` on irv-ml1 before deploying.
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# ── build pin ────────────────────────────────────────────────────────
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# SHA of Zyphra/Zonos. Use the FULL 40-char SHA — docker buildx's git
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# source resolver doesn't accept short hashes. `main` works but is NOT
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# reproducible; pin a SHA before you rely on this. Latest commits:
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# https://github.com/Zyphra/Zonos/commits/main
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ZONOS_SHA=main
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# Local image tag — bump when you change build context to force a
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# fresh layer build.
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ZONOS_TAG=v1
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# ── network ──────────────────────────────────────────────────────────
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# Host port. Container's Gradio listens on 7860 internally.
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# Reserved on irv-ml1: 8188 ComfyUI, 8190 CosyVoice, 8191 Qwen3-TTS,
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# 8192 IndexTTS-2, 8193 Kokoro, 8194 VibeVoice, 8195 Fish-S2,
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# 8196 Chatterbox, 8197 Voxtral, 8198 Kyutai, 8200 Dia, 8765 Parakeet.
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# 8199 picked here.
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ZONOS_PORT=8199
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# Bind address. 0.0.0.0 exposes on all interfaces (incl. WG tunnel
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# interface 10.100.79.3); 127.0.0.1 restricts to local-only.
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ZONOS_BIND=0.0.0.0
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# ── runtime / GPU ────────────────────────────────────────────────────
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# Devices visible inside the container. "0" pins to the RTX 3090
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# (24 GB) — plenty for Zonos (~6 GB). Both the 3090 and the A6000 are
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# Ampere, so either satisfies the hybrid variant's "3000-series or
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# newer" requirement; "1" selects the A6000.
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ZONOS_GPU_DEVICES=0
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# Model variant is chosen in the Gradio UI / SDK, not via env:
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# Zyphra/Zonos-v0.1-transformer — default, ~3.6 GB, no special kernels
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# Zyphra/Zonos-v0.1-hybrid — Mamba-SSM hybrid; needs Ampere+ and
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# extra build deps (mamba-ssm,
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# causal-conv1d) baked by the image
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# Start with the transformer variant unless you specifically want hybrid.
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# ── persistent storage on the host ───────────────────────────────────
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# HuggingFace cache — Zonos weights land here on first start.
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# Bind-mounted so they survive container recreate. Excluded from restic
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# (regenerable from HF).
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ZONOS_CACHE_DIR=/worktank/zonos/cache
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@@ -0,0 +1,65 @@
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# Zonos
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Zyphra's expressive multilingual open-weight TTS
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([Zyphra/Zonos](https://github.com/Zyphra/Zonos)) — 44 kHz output,
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zero-shot voice cloning, and explicit emotion/conditioning controls —
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served via the **official repo's Gradio interface**.
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Models ([`Zonos.from_pretrained()`](https://github.com/Zyphra/Zonos)):
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| Variant | HF repo | Notes |
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|---|---|---|
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| transformer | [Zyphra/Zonos-v0.1-transformer](https://huggingface.co/Zyphra/Zonos-v0.1-transformer) | ~3.6 GB, no special kernels (default) |
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| hybrid | [Zyphra/Zonos-v0.1-hybrid](https://huggingface.co/Zyphra/Zonos-v0.1-hybrid) | Mamba-SSM; needs Ampere+ GPU + extra build deps |
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**Server:** irv-ml1 (Irvine, WireGuard-only)
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**Port:** 8199 (container Gradio listens on 7860)
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**GPUs:** pins to device 0 (RTX 3090) by default; ~6 GB VRAM
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**Image:** `local/zonos:v1` — built locally from a pinned git SHA of the
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upstream repo via docker buildx's git URL context
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**Upstream:** [Zyphra/Zonos](https://github.com/Zyphra/Zonos) (Apache-2.0),
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trained on 200k+ hours; multilingual EN/JA/ZH/FR/DE
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## Why this stack exists
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A different *control surface* from the rest of the bench: Zonos exposes
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**emotion/conditioning sliders** plus pitch/rate conditioning and 44 kHz
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output, where Chatterbox/Dia use inline tags and Fish uses
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natural-language paralinguistic tags. Worth A/B-ing by ear against
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Chatterbox-Turbo (the research that prompted this stack explicitly said
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"benchmark Zonos against Chatterbox before choosing").
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## ⚠️ Audition surface, not skaldsong-pluggable (yet)
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The official repo ships a **Gradio WebUI + Python SDK only** — there is
|
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**no OpenAI-compatible `/v1/audio/speech` endpoint**. So this stack is
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for *auditioning quality*, not for wiring into skaldsong's engine
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router as-is. To promote Zonos to a real engine slot we'd need either:
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- the community FastAPI fork ([Zyphra/Zonos PR #73](https://github.com/Zyphra/Zonos/pull/73), adds REST + basic streaming), or
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- a thin OpenAI-compat adapter in front of the Python SDK.
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Both are a follow-up if Zonos earns a slot in the ear test.
|
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|
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## Deploy
|
||||
|
||||
```bash
|
||||
# from this workstation (irv-ml1 is WG-only — routes via ana-wg):
|
||||
scripts/deploy-stack.sh irv-ml1 zonos
|
||||
# then on irv-ml1, first run builds the image from the pinned SHA:
|
||||
# docker compose up -d --build
|
||||
```
|
||||
|
||||
Open `http://10.100.79.3:8199/` for the Gradio UI. First boot pulls the
|
||||
model (~3.6 GB) into `ZONOS_CACHE_DIR`; the 600 s `start_period` covers
|
||||
it.
|
||||
|
||||
## Notes
|
||||
|
||||
- **Pin `ZONOS_SHA`** to a full 40-char commit before relying on this —
|
||||
`.env.example` ships `main`, which is not reproducible.
|
||||
- The upstream image bundles **espeak-ng** (required for Zonos's
|
||||
phonemization) via its Dockerfile.
|
||||
- `GRADIO_SERVER_NAME=0.0.0.0` is set so the in-container Gradio binds
|
||||
all interfaces and the host port-map reaches it. If a future upstream
|
||||
hardcodes `server_name`, the API fork above is the cleaner path.
|
||||
@@ -0,0 +1,56 @@
|
||||
# Zonos-v0.1 (Zyphra's expressive multilingual open-weight TTS) served
|
||||
# via the OFFICIAL Zyphra/Zonos repo's Gradio interface.
|
||||
#
|
||||
# Why this stack exists alongside the other TTS:
|
||||
# * Apache-2.0, 44 kHz output, zero-shot voice cloning from a
|
||||
# 10-30 s sample, and explicit emotion/conditioning sliders —
|
||||
# a different control surface from tag-based engines.
|
||||
# * Multilingual (EN/JA/ZH/FR/DE), trained on 200k+ hours.
|
||||
# * Cheap to run (~6 GB VRAM, transformer variant ~3.6 GB weights).
|
||||
#
|
||||
# CAVEAT — this is an AUDITION/EVAL surface, not a skaldsong-pluggable
|
||||
# engine yet: the official repo ships a Gradio WebUI + Python SDK, NOT
|
||||
# an OpenAI-compatible /v1/audio/speech endpoint. To wire Zonos into
|
||||
# skaldsong's router we'd need the community FastAPI fork (Zyphra/Zonos
|
||||
# PR #73) or a thin adapter. Bench it by ear first; promote later if it
|
||||
# earns a slot.
|
||||
#
|
||||
# Image is built locally from the upstream repo's Dockerfile via docker
|
||||
# buildx git-context. All tunables live in .env — edit that, not this.
|
||||
|
||||
services:
|
||||
zonos:
|
||||
image: local/zonos:${ZONOS_TAG}
|
||||
build:
|
||||
# Single Dockerfile at repo root; bundles espeak-ng (required for
|
||||
# Zonos's eSpeak phonemization).
|
||||
context: https://github.com/Zyphra/Zonos.git#${ZONOS_SHA}
|
||||
dockerfile: Dockerfile
|
||||
container_name: zonos
|
||||
restart: unless-stopped
|
||||
runtime: nvidia
|
||||
ports:
|
||||
- "${ZONOS_BIND:-0.0.0.0}:${ZONOS_PORT}:7860"
|
||||
environment:
|
||||
- NVIDIA_VISIBLE_DEVICES=${ZONOS_GPU_DEVICES:-0}
|
||||
- NVIDIA_DRIVER_CAPABILITIES=compute,utility
|
||||
# Make Gradio bind all interfaces inside the container so the host
|
||||
# port-map reaches it (Gradio otherwise may bind 127.0.0.1 only).
|
||||
- GRADIO_SERVER_NAME=0.0.0.0
|
||||
- HF_HOME=/app/hf_cache
|
||||
volumes:
|
||||
- ${ZONOS_CACHE_DIR}:/app/hf_cache
|
||||
healthcheck:
|
||||
# No JSON status route on the Gradio app — just probe the root
|
||||
# page for liveness. start_period covers the first-boot model pull.
|
||||
test: ["CMD-SHELL", "python3 -c \"import urllib.request,sys; urllib.request.urlopen('http://127.0.0.1:7860/', timeout=5); sys.exit(0)\""]
|
||||
interval: 30s
|
||||
timeout: 10s
|
||||
retries: 3
|
||||
start_period: 600s
|
||||
labels:
|
||||
- homepage.group=AI Systems
|
||||
- homepage.name=Zonos
|
||||
- homepage.icon=mdi-waveform
|
||||
- homepage.description=Expressive multilingual TTS + cloning, 44kHz (Gradio eval, irv-ml1)
|
||||
- homepage.href=http://10.100.79.3:${ZONOS_PORT}
|
||||
Reference in New Issue
Block a user