comfyui-blackwell-docker/docker-compose.yml at main · ChiefNakor/comfyui-blackwell-docker · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
services:
  comfyui:
    build:
      context: .
      dockerfile: Dockerfile
      args:
        - CUDA_BASE_IMAGE=${CUDA_BASE_IMAGE:-nvidia/cuda:13.1.0-devel-ubuntu24.04}
        - TORCH_WHEEL_URL=${TORCH_WHEEL_URL:-https://download.pytorch.org/whl/cu130/torch-2.10.0%2Bcu130-cp312-cp312-manylinux_2_28_x86_64.whl}
        - TORCHVISION_WHEEL_URL=${TORCHVISION_WHEEL_URL:-https://download.pytorch.org/whl/cu130/torchvision-0.25.0%2Bcu130-cp312-cp312-manylinux_2_28_x86_64.whl}
        - TORCHAUDIO_WHEEL_URL=${TORCHAUDIO_WHEEL_URL:-https://download.pytorch.org/whl/cu130/torchaudio-2.10.0%2Bcu130-cp312-cp312-manylinux_2_28_x86_64.whl}
        - COMFYUI_BRANCH=${COMFYUI_BRANCH:-master}
        - SAGEATTENTION_VERSION=${SAGEATTENTION_VERSION:-v2}
        - SAGEATTENTION_USE=${SAGEATTENTION_USE:-1}
        - TORCH_CUDA_ARCH_LIST=${TORCH_CUDA_ARCH_LIST:-12.0}

    container_name: comfyui

    ports:
      - "${COMFYUI_PORT:-8188}:8188"

    volumes:
      # Models - This will get large! Keep it on a drive with plenty of space
      - ${MODELS_PATH:-./models}:/app/models

      # Generated outputs
      - ${OUTPUT_PATH:-./output}:/app/output

      # Input images for img2img workflows
      - ${INPUT_PATH:-./input}:/app/input

      # Custom nodes - IMPORTANT: Rebuild image after installing new nodes!
      - ${CUSTOM_NODES_PATH:-./custom_nodes}:/app/custom_nodes

      # User settings and saved workflows
      - ${USER_PATH:-./user}:/app/user

    environment:
      # Helps with VRAM fragmentation - improves stability
      - PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True

    # Command line arguments for ComfyUI
    # Customize in .env file via COMFYUI_ARGS and RESERVE_VRAM
    command: >
      python3 main.py --listen 0.0.0.0
      ${COMFYUI_ARGS}
      --reserve-vram ${RESERVE_VRAM:-1.5}

    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: all
              capabilities: [gpu]

    restart: unless-stopped