vh
4a4c09177f
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.
48 lines
2.4 KiB
Bash
48 lines
2.4 KiB
Bash
# ACE-Step 1.5 stack tunables. Copy to `.env` on irv-ml1 before
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# deploying.
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# ── build pin ────────────────────────────────────────────────────────
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# SHA of ace-step/ACE-Step to build from. Use the FULL 40-char SHA —
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# docker buildx git source resolver rejects short hashes. `main` works
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# at first deploy; pin to a real SHA before any production cutover so
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# upstream commits don't surprise you on next rebuild.
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ACE_STEP_SHA=main
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# Local image tag — bump when you change build context to force a
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# fresh layer build.
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ACE_STEP_TAG=v1
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# ── network ──────────────────────────────────────────────────────────
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# Host port (container listens on 8000 internally — infer-api.py
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# hardcodes uvicorn.run(host=0.0.0.0, port=8000)).
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# Reservations on irv-ml1: 8188 ComfyUI, 8190 CosyVoice, 8191 Qwen3-TTS,
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# 8192 IndexTTS-2, 8193 Kokoro, 8194 VibeVoice, 8195 Fish, 8196
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# Chatterbox, 8197 Voxtral, 8765 Parakeet ASR. 8210 starts the
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# audio-generation block (music + SFX) so future TTS adds can keep
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# going from 8198+.
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ACE_STEP_PORT=8210
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ACE_STEP_BIND=0.0.0.0
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# ── runtime / GPU ────────────────────────────────────────────────────
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# GPU pinning. "0" = RTX 3090 (24 GB), "1" = RTX A6000 (48 GB).
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# A6000 (1) recommended — Fish s2-pro lives there at ~17 GB, and
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# ACE-Step adds ~10-12 GB during inference, leaving comfortable
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# headroom on the 48 GB card. The 3090 is full with the TTS slate.
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ACE_STEP_GPU_DEVICES=1
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# ── persistent storage on the host ───────────────────────────────────
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# Model checkpoints — primary spot for any manually-staged checkpoints.
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# ACE-Step's auto-download lands in HF_HOME (cache dir below).
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ACE_STEP_CHECKPOINTS_DIR=/worktank/ace-step/checkpoints
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# Generated audio output — clients can pull from here via the
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# returned file path in the /generate response.
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ACE_STEP_OUTPUTS_DIR=/worktank/ace-step/outputs
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# Application logs.
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ACE_STEP_LOGS_DIR=/worktank/ace-step/logs
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# HF cache — first start pulls the ACE-Step checkpoint (~5-10 GB)
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# into this dir. Persistent across container recreates.
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ACE_STEP_CACHE_DIR=/worktank/ace-step/hf_cache
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