feat(dots-tts): ship OpenAI-compatible dots.tts TTS stack on irv-ml1:8198

Thin FastAPI wrapper over DotsTtsRuntime (soar, optimize=True, RTF ~0.22),
serialized single-consumer; OpenAI /v1/audio/speech (stream + non-stream),
voices from the voices/ corpus derived set. Live + healthy alongside
chatterbox-fast on the 3090; nothing repointed. Dockerfile needs
build-essential (torch.compile/inductor JITs via gcc at runtime) + persisted
inductor cache. Remaining Phase-2: ratatoskr client cutover.

stacks/dots-tts/.env.example

@@ -0,0 +1,27 @@
+# dots-tts stack tunables. Copy to `.env` on irv-ml1 before deploying.
+
+# ── image ────────────────────────────────────────────────────────────
+DOTS_TAG=v1
+
+# ── network ──────────────────────────────────────────────────────────
+DOTS_BIND=0.0.0.0
+DOTS_PORT=8198
+
+# ── GPU ──────────────────────────────────────────────────────────────
+# 0 = 3090 in Docker (PCI order), co-resident with chatterbox-fast. soar needs
+# ~6GB; the 3090 has headroom with Zonos parked down.
+DOTS_GPU_DEVICES=0
+
+# ── model / inference ────────────────────────────────────────────────
+DOTS_MODEL=dots-studio/dots.tts-soar
+DOTS_DEFAULT_VOICE=donut
+DOTS_NUM_STEPS=10          # 10 = full quality @ RTF ~0.22; lower = faster/rougher
+DOTS_GUIDANCE_SCALE=1.2
+
+# ── host mounts ──────────────────────────────────────────────────────
+# HF cache holding the downloaded soar snapshot (~5GB). Reuse the burn-in cache.
+DOTS_HFCACHE_DIR=/home/lkraven/dots-tts/hf_cache
+# dots-derived voice references (derive.py dots -> derived/dots/<name>.{wav,txt}).
+# Burn-in points at the corpus output directly; for a durable deploy, copy the
+# derived set to /opt/docker/conf/dots-tts/voices and point here.
+DOTS_VOICES_HOST_DIR=/home/lkraven/voice-corpus/derived/dots