stacks/{fish-s2,voxtral,kyutai-tts}: three new TTS deploys for irv-ml1 quality A/B

Adds the three premier 2026 TTS releases we missed during the original
fleet build-out (early April), all licensed for self-host:

* Fish Audio S2-Pro (port 8195, GPU 1 / A6000) — released 2026-03-09.
  4B dual-AR (Slow + Fast) trained on 10M+ hours / 80+ languages.
  Headline: 15,000+ paralinguistic / emotion tags via natural language
  ([laugh] [whispers] [super happy] etc.) — a step-function over
  Chatterbox Turbo's 9 fixed tags. 91.61% paralinguistic win rate on
  EmergentTTS-Eval. ~150 ms streaming TTFB, voice cloning, MIT-style
  open. ~17 GB VRAM.

* Voxtral TTS (port 8197, GPU 1 / A6000) — Mistral, released 2026-03-28.
  4B open-weight, 70 ms model latency, 9.7× realtime. 68.4% blind A/B
  win rate vs ElevenLabs Flash v2.5 in cloning. 8 languages
  (EN/FR/DE/ES/IT/PT/NL/HI). Served via vLLM-Omni (Mistral's partner
  serving stack) — published Docker image, no local build. ~16 GB VRAM.
  CC BY-NC license — personal/research use only; flagged in README.

* Kyutai TTS (port 8198, GPU 0 / 3090) — kyutai/tts-1.6b-en_fr.
  Trained on 2.5M hours from the Moshi/Mimi team. Claimed 220 ms in
  solo setup, 32 simultaneous streams under 350 ms on L40. Kyutai's
  official deploy is Rust + websockets only; using NillPointer's
  community OpenAI-compat wrapper to bridge to /v1/audio/speech so
  it slots into the same bench harness. ~4-6 GB VRAM.

Each stack: compose.yaml (build context, env, volumes, healthcheck,
homepage label), .env.example (all tunables documented), README.md
(why it exists, headline numbers, API, deploy + hardware notes).
Playbooks at playbooks/deploy-{fish-s2,voxtral,kyutai-tts}.yaml are
idempotent in the same shape as the existing deploy-vibevoice /
deploy-chatterbox playbooks.

Port allocations on irv-ml1 after this lands: 8188 ComfyUI, 8190
CosyVoice, 8191 Qwen3-TTS, 8192 IndexTTS-2, 8193 Kokoro, 8194
VibeVoice, 8195 Fish, 8196 Chatterbox, 8197 Voxtral, 8198 Kyutai,
8765 Parakeet ASR.

stacks/voxtral/compose.yaml

@@ -0,0 +1,59 @@
+# Voxtral TTS — Mistral AI's 4B open-weight streaming TTS, served via
+# vLLM-Omni (the production serving stack Mistral co-developed for
+# Voxtral). Released March 28, 2026.
+#
+# Why this stack alongside the existing TTS:
+#   * 70 ms model latency, 9.7× realtime — fastest non-Kokoro option.
+#   * Multilingual-first (EN strong, plus FR, DE, ES, IT, PT, NL, HI).
+#     Different from CosyVoice's Chinese-leaning balance.
+#   * 68.4% blind A/B win rate vs ElevenLabs Flash v2.5 in cloning.
+#   * vLLM-Omni serving = continuous batching + paged attention — the
+#     same mechanism that gave qwen3.6 its speed on llama-swap.
+#
+# LICENSE: CC BY-NC. Personal / research use only. Don't ship Voxtral
+# output in any commercial product without re-licensing from Mistral.
+#
+# All tunables live in .env — edit that, not this file.
+
+services:
+  voxtral:
+    # vLLM-Omni image — Mistral's official partnership for Voxtral
+    # serving. Version-pinned via .env.
+    image: vllm/vllm-omni:${VOXTRAL_VLLM_TAG}
+    container_name: voxtral
+    restart: unless-stopped
+    runtime: nvidia
+    ports:
+      - "${VOXTRAL_BIND:-0.0.0.0}:${VOXTRAL_PORT}:8000"
+    environment:
+      - NVIDIA_VISIBLE_DEVICES=${VOXTRAL_GPU_DEVICES:-1}
+      - HF_HOME=/root/.cache/huggingface
+      # vLLM serving args — see https://docs.vllm.ai for full list.
+      # We override the default model via cmd args below.
+    volumes:
+      - ${VOXTRAL_CACHE_DIR}:/root/.cache/huggingface
+      - ${VOXTRAL_VOICES_DIR}:/voices:ro
+    # vLLM-Omni's serve command — model + dtype + port pinned.
+    command:
+      - --model=${VOXTRAL_MODEL:-mistralai/Voxtral-4B-TTS-2603}
+      - --port=8000
+      - --dtype=bfloat16
+      - --gpu-memory-utilization=${VOXTRAL_GPU_UTIL:-0.85}
+    healthcheck:
+      # vLLM-Omni exposes /health for liveness + /v1/models for readiness.
+      # /health 200 means the server's listening; /v1/models 200 means
+      # the model is loaded and request-ready. Use readiness as the
+      # healthy signal so we don't mark it "healthy" before it can
+      # accept synthesis requests.
+      test: ["CMD-SHELL", "python3 -c \"import urllib.request,sys; sys.exit(0 if urllib.request.urlopen('http://127.0.0.1:8000/v1/models', timeout=5).status==200 else 1)\""]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      # First boot pulls Voxtral-4B (~8 GB BF16) + warms vLLM. Generous.
+      start_period: 600s
+    labels:
+      - homepage.group=AI Systems
+      - homepage.name=Voxtral TTS
+      - homepage.icon=mdi-translate
+      - homepage.description=Mistral 4B multilingual streaming TTS — 70 ms latency, voice cloning (irv-ml1)
+      - homepage.href=http://10.100.79.3:${VOXTRAL_PORT}