vh
7346e4623c
HunyuanVideo-Foley, MMAudio and ControlFoley load their Hugging Face dependencies from pinned snapshots staged on the model store. Without this they look in the container's ephemeral cache and download again on every recreate. Requested by comfy-dev; HF_HUB_OFFLINE deliberately not set.
108 lines
5.6 KiB
YAML
108 lines
5.6 KiB
YAML
# ComfyUI — node-based Stable Diffusion / Flux inference UI.
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#
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# Runs on irv-ml1 (dual GPU: RTX 3090 + RTX A6000). PINNED to the A6000
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# (device 1) via NVIDIA_VISIBLE_DEVICES=1 — the 3090 hosts the audio/TTS
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# zoo (chatterbox, parakeet, vibevoice, ytvc, kokoro) so ComfyUI gets the
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# full 48 GB A6000 to itself (operator consolidation 2026-06-18).
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#
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# All user state — models, workflows, custom_nodes, input, output —
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# lives under a single BASE_DIRECTORY tree on /worktank (462 GB
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# dedicated), owned by lkraven:lkraven (1000:1000) so external
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# tooling can read and write workflow files directly on the host.
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#
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# Runtime state (ComfyUI source, venv, pip cache) lives in a bind
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# mount at ${COMFYUI_RUNDIR} — disposable (can be wiped on version
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# bumps to force re-bootstrap), but owned by the host user so no
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# sudo dance is needed. (Named volumes would be created root-owned
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# and the image refuses to chown a mounted path.)
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#
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# First-run prerequisite: both ${COMFYUI_BASEDIR} and ${COMFYUI_RUNDIR}
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# must exist on the host with ownership matching COMFYUI_UID:COMFYUI_GID
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# before `up`. See README for the bootstrap command.
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#
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# All tunables live in .env — edit that, not this file.
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services:
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comfyui:
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image: mmartial/comfyui-nvidia-docker:${COMFYUI_VERSION}
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container_name: comfyui
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restart: unless-stopped
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runtime: nvidia
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ports:
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- "${COMFYUI_BIND:-0.0.0.0}:${COMFYUI_PORT}:8188"
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environment:
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- NVIDIA_VISIBLE_DEVICES=1
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# Pin torch at the current 2.12.1+cu129 so the boot script stops
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# auto-upgrading it — compiled SageAttention kernels must not drift
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# (comfy-dev torch-pin, operator-approved 2026-06-18).
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- DISABLE_UPGRADES=true
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- WANTED_UID=${COMFYUI_UID}
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- WANTED_GID=${COMFYUI_GID}
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- BASE_DIRECTORY=/basedir
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- SECURITY_LEVEL=${COMFYUI_SECURITY_LEVEL:-normal}
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- USE_UV=true
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# Extra ComfyUI launch flags (image appends these to main.py, then adds
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# --base-directory + --enable-manager itself):
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# --fp8_e4m3fn-text-enc — load the FLUX.2 Qwen3-8B text encoder as fp8
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# (~8.7 GB) instead of upcasting the fp8 file to fp16 (~16 GB). Matches
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# the box's Ampere-fp8 posture; the encoder runs once per gen so the
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# upcast-on-compute cost is negligible.
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# --use-sage-attention — 0.24.1's NATIVE attention selection (the node-based
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# BlehGlobalSageAttention is dead on 0.24.1: "does not support the new
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# ComfyUI attention changes"). Binds the in-image sageattention v2.2.0
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# sm_86 build (rebuilt against the pinned torch 2.12.1). Global speedup
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# across Flux/SDXL/Wan (comfy-dev benchmarking, 2026-06-18).
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#
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# ALLOCATOR (2026-07-19 — comfy-dev A/B, operator-run — cudaMallocAsync WON).
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# We deliberately DO NOT pass --disable-cuda-malloc, so ComfyUI keeps CUDA's
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# default async allocator (cudaMallocAsync). History: --disable-cuda-malloc +
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# PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True were added when the A6000 was
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# SHARED with the TTS zoo (the native allocator dodged a cudaMallocAsync
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# phantom-OOM). TTS moved to the 3090 (2026-06-18), removing that trigger; the
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# LTX-2.3 v1.5.0 LoRA stack (DMD+OmniNFT+act LoRAs patching the DiT + the 12B
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# Gemma text-encoder) then began hitting the 48 GB ceiling under the native
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# allocator, which fragments/over-reserves (~45 GB allocated+reserved-but-
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# unallocated) and OOMs at TE load. cudaMallocAsync packs tighter + promptly
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# returns freed blocks, so the same job now FITS: the operator's previously-
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# OOMing stress test peaks ~82% VRAM (~40/48 GB) with headroom, 0 OOM/errors.
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# COUPLING: PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True is native-allocator-
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# only, so it is REMOVED here (inert/invalid under cudaMallocAsync) — revert BOTH
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# together. If the TTS zoo ever moves back onto the A6000, re-evaluate the pair.
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- COMFY_CMDLINE_EXTRA=--fp8_e4m3fn-text-enc --use-sage-attention
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# Foley nodes (comfy-dev, 2026-10-05): HunyuanVideo-Foley, MMAudio and ControlFoley load their
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# Hugging Face dependencies (SigLIP2, CLAP, BigVGAN, roberta, t5-base, ...) from pinned snapshots
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# staged on the model store. Without this they look in the container's ephemeral ~/.cache and
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# download again on every recreate. Deliberately NOT HF_HUB_OFFLINE: other nodes fetch on first use.
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- HF_HUB_CACHE=/basedir/models/foley-hf-cache
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volumes:
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- ${COMFYUI_BASEDIR}:/basedir
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# models/ overlaid from storetank. The ~325 GB model tree was migrated
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# off the near-full worktank NVMe (2026-06-13) to /storetank/arbo (roomy
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# SATA SSD). This nested mount shadows the models subdir of /basedir;
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# everything else (custom_nodes, output, input, user, workflows) stays on
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# worktank. Inventory: docs/arbo-comfyui-model-catalog.md.
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- ${COMFYUI_MODELS_DIR:-/storetank/arbo/models}:/basedir/models
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- ${COMFYUI_RUNDIR}:/comfy/mnt
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healthcheck:
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test: ["CMD-SHELL", "curl -fsS http://localhost:8188/ >/dev/null || exit 1"]
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interval: 30s
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timeout: 10s
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retries: 3
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# First boot installs ~5 GB of Python packages; allow generous
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# start_period so the container isn't marked unhealthy during
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# bootstrap. Subsequent starts are fast.
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start_period: 600s
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networks:
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- tnet
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labels:
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- homepage.group=AI - Studios
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- homepage.name=ComfyUI
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- homepage.icon=mdi-image-auto-adjust
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- homepage.description=Node-based SD/Flux inference (irv-ml1)
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- homepage.href=http://irv-ml1.nh3.internal:${COMFYUI_PORT}
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networks:
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tnet:
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name: traefik-net
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external: true
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