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/kyutai-tts/compose.yaml

@@ -0,0 +1,56 @@
+# Kyutai TTS — 1.6B / 2B-class streaming TTS from Kyutai (the Moshi /
+# Mimi team), trained on 2.5M hours. 220 ms latency in solo setup; up
+# to 32 simultaneous streams under 350 ms on an L40-class GPU.
+#
+# Served via the NillPointer/Kyutai-TTS-Server community wrapper —
+# Kyutai's official deployment is Rust + websockets only, which doesn't
+# fit our OpenAI-compat fleet. The community wrapper bridges Kyutai's
+# native streaming to the OpenAI /v1/audio/speech contract.
+#
+# Why this stack alongside the existing TTS:
+#   * Kyutai's claim is the lowest streaming latency in this size
+#     class (220 ms on a single GPU). Worth bench-comparing against
+#     Chatterbox (~1.2 s) and Fish S2-Pro (~150 ms claimed).
+#   * Trained on 2.5M hours — a different scaling regime from the
+#     others (CosyVoice 5k hrs, Fish 10M hrs).
+#   * Designed for full-duplex dialogue (Moshi heritage) — may surface
+#     conversational quality the others lack.
+#
+# All tunables live in .env — edit that, not this file.
+
+services:
+  kyutai-tts:
+    image: local/kyutai-tts:${KYUTAI_TTS_TAG}
+    build:
+      context: https://github.com/NillPointer/Kyutai-TTS-Server.git#${KYUTAI_TTS_SHA}
+      dockerfile: Dockerfile
+    container_name: kyutai-tts
+    restart: unless-stopped
+    runtime: nvidia
+    ports:
+      - "${KYUTAI_TTS_BIND:-0.0.0.0}:${KYUTAI_TTS_PORT}:8000"
+    environment:
+      - NVIDIA_VISIBLE_DEVICES=${KYUTAI_TTS_GPU_DEVICES:-0}
+      # Kyutai's en/fr bilingual model on HF. Switch to a different
+      # checkpoint via .env without rebuilding.
+      - KYUTAI_MODEL=${KYUTAI_TTS_MODEL:-kyutai/tts-1.6b-en_fr}
+      - HF_HOME=/app/hf_cache
+    volumes:
+      - ${KYUTAI_TTS_CACHE_DIR}:/app/hf_cache
+      - ${KYUTAI_TTS_VOICES_DIR}:/app/voices:ro
+    healthcheck:
+      # The wrapper exposes /v1/models for OpenAI-compat — same shape
+      # as Voxtral / Qwen3-TTS. Use that as the readiness signal.
+      # 127.0.0.1 explicit to dodge IPv4/IPv6 localhost race.
+      test: ["CMD-SHELL", "python3 -c \"import urllib.request,sys; sys.exit(0 if urllib.request.urlopen('http://127.0.0.1:8000/v1/models', timeout=5).status==200 else 1)\""]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      # First boot pulls the Kyutai checkpoint (~3-6 GB) + warms.
+      start_period: 600s
+    labels:
+      - homepage.group=AI Systems
+      - homepage.name=Kyutai TTS
+      - homepage.icon=mdi-radio-tower
+      - homepage.description=Ultra-low-latency streaming TTS — 220 ms on solo GPU, EN/FR (irv-ml1)
+      - homepage.href=http://10.100.79.3:${KYUTAI_TTS_PORT}