Files
esh-pfi-infrastructure/stacks
vh 14f052461e stacks/fish-cpp: Phase 1 — s2.cpp + GGML CUDA backend image, FastAPI shim, deploy playbook
New stack scaffolding for the Fish quantized-realtime experiment. Not
deployed yet — this commit lands the canonical files; deploy follows.

Architecture decisions made in Phase 1:
* CUDA backend, NOT Vulkan. s2.cpp's CMakeLists exposes both
  -DS2_VULKAN and -DS2_CUDA; the most recent upstream commit
  (2026-04-12) was specifically about CUDA improvements, and CUDA
  on the A6000 will be substantially faster than Vulkan for ML
  matmul. -DS2_CUDA=ON in the Dockerfile build args.

* Pinned to s2.cpp commit e48ce8e02d8335bd9a0ba94679f605724b31d12
  (2026-04-12 HEAD of main). Repo is alpha software per README;
  pin tightly so future churn doesn't break our build. Bump
  deliberately when wanting upstream improvements.

* Multi-stage Dockerfile: nvidia/cuda:12.6.0-devel for build (needs
  CMake + ninja + git + the CUDA toolchain) → nvidia/cuda:12.6.0-runtime
  for serve (slimmer; just the s2 binary + GGML libs + a small Python
  shim). Cuts image size by ~50% vs single-stage devel.

* FastAPI shim (server.py) wraps s2.cpp CLI in Fish's `/v1/tts`
  contract so the same bench harness + clients work against fish-cpp
  with no changes. Per-request flow: decode optional reference WAV
  from base64 → write to temp → subprocess.run the s2 binary → stream
  resulting WAV back. Adds ~50-100ms per-request fork+exec overhead;
  negligible vs the multi-second generation cost.

* `streaming: true` accepted in request body but IGNORED — s2.cpp
  writes a complete WAV before returning, so chunked output isn't
  available. Unlike fish-s2 (HF wrapper) where streaming drops TTFB
  to 26ms, fish-cpp's TTFB ≈ total wall time. Speed depends entirely
  on raw generation throughput.

* q6_k as default quant — sweet spot per typical GGUF guidance:
  near-bf16 quality at ~5GB. Other variants (q4_k_m, q5_k_m, q8_0,
  f16) selectable via FISH_CPP_MODEL env.

* Pinned to GPU 1 (A6000) by default to share with fish-s2 for
  direct A/B benching. q6_k weights ~5GB + runtime ~3GB ≈ 8GB —
  comfortable on either GPU.

* Port 8199 (next free in the irv-ml1 TTS slate).

Phase 2 (next) is the actual deploy + first build. Reserved 30-45 min
for cold-cache build + weights pull.
2026-04-28 01:06:14 -07:00
..
2026-04-20 22:55:51 -07:00