The 2026-09-06 headscale cutover retired irv-ml1's wg0 tunnel IP 10.100.79.3
(now 10.6.110.50). Repointed all LIVE canonical refs to the DNS NAME so the next
move can't re-break them: homepage.href/siteMonitor labels across 25 stack
composes, load-bearing env defaults (asset-engine INFERENCE_HOST, open-webui
AUDIO_TTS_OPENAI_API_BASE_URL, skaldsong SKALDSONG_TTS_BASE_URL, zonos-gateway
ZONOS_URL, dia), homepage services.yaml manual cards (Voice Design Studio,
IRV-ML1), and servers/irv-ml1/ssh-target. Updated the stale 'WG tunnel' comment
to the mesh reality.
Left as-is: README curl-examples and .env.example comments (docs), and historical
mentions in CLAUDE.md/persistent-memory. NOTE: applying the label repoints to the
RUNNING irv-ml1 containers needs a recreate per service (labels read at creation);
deployed .env values are separate from these canonical defaults.
StableAudioPipeline isn't reentrant — concurrent requests share the
scheduler's step_index counter and corrupt each other mid-run
(observed: IndexError in cosine_dpmsolver_multistep when two requests
overlap). Wrap the pipeline call + audio decode in a single
asyncio.Lock created at startup, and run the (sync, GPU-bound)
pipeline call via asyncio.to_thread so the event loop stays
responsive. Concurrent requests now queue cleanly instead of racing.
Verified: 5 parallel POSTs at steps=50 all return 200, clear ~4s
serialization spacing (4, 8, 12, 16, 20s wall time), distinct
output hashes per seed.
server.py accepted cfg_scale in the request schema and the README
documented its 0–20 range, but the pipeline call never received it
— so changing cfg_scale between requests silently produced identical
output (the pipeline ran at its own default of 7.0 every time). Add
guidance_scale=req.cfg_scale to the pipe(...) call.
Verified: (prompt, seed, steps) held constant, cfg_scale=3.0 vs 15.0
now produce different SHA256s; same triple at cfg_scale=7.0 is
deterministic across repeated calls.
Two new audio-generation stacks alongside the TTS slate:
ace-step :8210 — Apache 2.0 music generation foundation model
(hybrid diffusion + LLM). Lyric-aware multi-minute songs. ~10-12 GB
VRAM during inference, A6000-pinned. Custom Dockerfile patches
upstream's torch/cu126 resolution bug (--extra-index-url cu126 was
falling back to pypi-default cu13 wheels, mismatching torchvision).
stable-audio-open :8211 — Stability AI 1.21B latent-diffusion SFX +
ambience. Up to 47s clips at 44.1 kHz. ~6 GB VRAM in fp16,
A6000-pinned. Custom FastAPI shim around diffusers' StableAudioPipeline
(no upstream HTTP server). Dockerfile pins torchsde explicitly —
diffusers doesn't pull it as a hard dep but
CosineDPMSolverMultistepScheduler needs it.
vh