stacks: add Kokoro, VibeVoice 1.5B, Chatterbox Turbo (TTS slate fill-in)

Three TTS additions to round out coverage on irv-ml1, each filling a
distinct niche the existing slate doesn't own.

Final coverage matrix (all on irv-ml1):
  Kokoro              — low-latency English, fixed voice library, ~300ms TTFA
  Chatterbox Turbo    — low-latency English w/ voice cloning + paralinguistic tags
  IndexTTS-2          — English voice cloning + emotion vector / text control
  Qwen3-TTS-1.7B-Base — high-quality English voice cloning
  CosyVoice 3         — multilingual (Chinese-leaning)
  VibeVoice 1.5B      — long-form / multi-speaker dialogue

stacks/kokoro:
  - port 8193, GPU device 0 (3090)
  - pulls ghcr.io/remsky/kokoro-fastapi-gpu:v0.2.4-master (no Dockerfile,
    no first-run model download — models baked in)
  - 60+ built-in voices, OpenAI-compat with stream=true over chunked HTTP
  - Apache-2.0 weights + code, ~1 GB VRAM

stacks/vibevoice:
  - port 8194, GPU device 1 (A6000 — for 7B headroom)
  - builds groxaxo/VibeVoice-FastAPI1 (more current fork of ncoder-ai)
    pinned to 7614c469a145
  - default model microsoft/VibeVoice-1.5B (~7 GB bf16 VRAM); env var
    swap to rsxdalv/VibeVoice-Large (7B) or FabioSarracino/VibeVoice-Large-Q8
  - multi-speaker dialogue via /v1/vibevoice/generate with Speaker N: format
  - long-form niche only — not low-latency

stacks/chatterbox:
  - port 8196, GPU device 0 (3090)
  - builds devnen/Chatterbox-TTS-Server (most active Turbo-supporting wrapper)
  - default model ResembleAI/chatterbox-turbo (~2.5 GB fp16, ~75ms latency)
  - paralinguistic tags inline ([laugh] [whisper] etc) — different shape
    from IndexTTS-2's emotion vector; fills the speed+cloning niche
    Kokoro/IndexTTS don't cover together
  - mandatory PerTh watermark on outputs (Resemble policy)

Three matching playbooks under playbooks/deploy-{kokoro,vibevoice,
chatterbox}.yaml. All idempotent, creates-/when-gated.

Cold-deploy disk on /worktank/: ~7 GB Kokoro + ~19 GB VibeVoice 1.5B
+ ~12 GB Chatterbox = ~38 GB total. VRAM concurrent: ~10-11 GB across
both GPUs.

Skipped from the original four-stack proposal: VibeVoice Realtime
(overlaps Kokoro's niche; Kokoro wins on latency, license, and not
needing a build).

stacks/vibevoice/.env.example

@@ -0,0 +1,76 @@
+# VibeVoice 1.5B (long-form) stack tunables.
+# Copy to `.env` on irv-ml1 before deploying.
+
+# ── build pin ────────────────────────────────────────────────────────
+# SHA of groxaxo/VibeVoice-FastAPI1 (a more current fork of
+# ncoder-ai/VibeVoice-FastAPI). Bump + rebuild when you want upstream
+# wrapper updates.
+VIBEVOICE_SHA=7614c469a145
+
+# Local image tag — bump when you change build context to force a
+# fresh layer build.
+VIBEVOICE_TAG=v1
+
+# ── network ──────────────────────────────────────────────────────────
+# Host port. Container listens on 8001 internally.
+# Reserved on irv-ml1: 8188 ComfyUI, 8190 CosyVoice, 8191 Qwen3-TTS,
+# 8192 IndexTTS-2, 8193 Kokoro, 8765 Parakeet. 8194 picked here.
+VIBEVOICE_PORT=8194
+
+# Bind address. 0.0.0.0 exposes on all interfaces (incl. WG tunnel
+# interface 10.100.79.3); 127.0.0.1 restricts to local-only.
+VIBEVOICE_BIND=0.0.0.0
+
+# ── runtime / GPU ────────────────────────────────────────────────────
+# Devices visible inside the container. "1" pins to the RTX A6000 —
+# 1.5B fits easily on the 3090 too, but pinning to the bigger card
+# leaves headroom if you later flip VIBEVOICE_MODEL to the 7B variant.
+VIBEVOICE_GPU_DEVICES=1
+
+# Model. Options (per groxaxo/ncoder-ai docs):
+#   microsoft/VibeVoice-1.5B        — flagship, ~7 GB bf16 VRAM
+#   rsxdalv/VibeVoice-Large         — 7B variant, ~18 GB bf16 VRAM
+#                                     (need device_ids="1" / A6000)
+#   FabioSarracino/VibeVoice-Large-Q8 — 7B int8 quantized, ~10 GB
+VIBEVOICE_MODEL=microsoft/VibeVoice-1.5B
+
+# Number of denoising inference steps. Default 10 is a good
+# quality/speed tradeoff. Lower = faster but lower quality.
+VIBEVOICE_INFERENCE_STEPS=10
+
+# Compute dtype. bfloat16 default (best speed/quality on Ampere+).
+# Use float16 for older GPUs without bf16 support.
+VIBEVOICE_DTYPE=bfloat16
+
+# Attention impl. flash_attention_2 is fastest if installed (bundled
+# in the upstream image build). Fall back to "sdpa" if it errors.
+VIBEVOICE_ATTN=flash_attention_2
+
+# Quantization. Empty = none. "int8_torchao" saves ~40% VRAM at a
+# small quality cost — useful if you want to run 7B on a smaller GPU.
+VIBEVOICE_QUANT=
+
+# torch.compile. Bumps cold-start by ~3-5 min the first time but
+# trims per-generation latency. Disable if you're iterating quickly.
+VIBEVOICE_TORCH_COMPILE=false
+VIBEVOICE_TORCH_COMPILE_MODE=default
+
+# CFG (classifier-free guidance) scale. Default 1.8 from upstream;
+# higher = stronger adherence to text/voice, lower = more free.
+VIBEVOICE_CFG_SCALE=1.8
+
+# Max generation length in audio frames. 5400 = ~6 minutes at the
+# native rate. Bump for longer podcasts (each frame takes work).
+VIBEVOICE_MAX_GEN_LEN=5400
+
+# ── persistent storage on the host ───────────────────────────────────
+# Voice library — flat dir of .wav/.mp3/.flac/.m4a files. Mounted
+# read-only into the container. Drop a file in, restart container,
+# voice is available. (Restart needed because the upstream wrapper
+# scans on init, not per-request.)
+VIBEVOICE_VOICES_DIR=/worktank/vibevoice/voices
+
+# HuggingFace cache. Holds VibeVoice weights + any aux models pulled.
+# Bind-mounted so model state survives container recreate. Excluded
+# from restic (regenerable from HF).
+VIBEVOICE_CACHE_DIR=/worktank/vibevoice/cache