Files
esh-pfi-infrastructure/stacks/ace-step
vh 4a4c09177f ace-step + stable-audio-open: deploy music + SFX generation to irv-ml1
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.
2026-04-28 09:11:23 -07:00
..

ace-step

ACE-Step 1.5 — Apache 2.0 open-source music generation foundation model. Hybrid diffusion + LLM. Generates lyric-aware multi-minute songs (vocals + instrumentation).

host irv-ml1
port 8210
GPU A6000 (device_ids: ["1"])
VRAM ~10-12 GB during inference
upstream https://github.com/ace-step/ACE-Step
license Apache 2.0

API surface

infer-api.py (FastAPI) exposes:

  • GET /health — liveness, returns 200 once the process is up (model is lazy-loaded on first /generate).
  • POST /generate — body: ACEStepInput Pydantic model with ~27 params (prompt, lyrics, audio_duration, guidance_scale, etc.). Returns {status, output_path, message}.

The container does NOT expose the Gradio UI — we override the upstream default python3 acestep/gui.py with python3 infer-api.py. If you want the Gradio UI for ad-hoc experimentation, run a one-off:

ssh irv-ml1 'docker exec -it ace-step python3 acestep/gui.py --server_name 0.0.0.0 --port 7865'

…and port-forward 7865 to your laptop.

Deploy

scripts/elway irv-ml1 --playbook playbooks/deploy-ace-step.yaml

Idempotent. Cold build is ~10-15 min (CUDA + torch + transformers + spacy + audio deps). First /generate triggers the model download (~5-10 GB) and warmup (~30-60 s).

Tunables

See .env.example — copy to .env on the host (lives at /opt/docker/compose/ace-step/.env, gitignored). Common knobs:

  • ACE_STEP_SHA — pin upstream commit
  • ACE_STEP_GPU_DEVICES — GPU index
  • ACE_STEP_*_DIR — bind-mount paths under /worktank/ace-step/