config:
  network:

    # Specify the IP address to listen on (default: 127.0.0.1). If --listen is provided without an argument, it defaults to 0.0.0.0. (listens on all)
    # Type: str
    listen: 127.0.0.1

    # Set the listen port.
    # Type: int
    port: 8188

    # Enable CORS (Cross-Origin Resource Sharing) with optional origin or allow all with default '*'.
    # Type: str
    enable_cors_header:
  files:

    # Extra paths to scan for model files.
    extra_model_paths:
      a1111:
        hypernetworks: models/hypernetworks
        base_path: path/to/stable-diffusion-webui/
        embeddings: embeddings
        controlnet: models/ControlNet
        configs: models/Stable-diffusion
        loras: models/Lora
        vae: models/VAE
        checkpoints: models/Stable-diffusion
        upscale_models: |
          models/ESRGAN
          models/SwinIR

    # Set the ComfyUI output directory. Leave empty to use the default.
    # Type: str
    output_directory:
  behavior:

    # Automatically launch ComfyUI in the default browser.
    # Type: bool
    auto_launch: false

    # Don't print server output.
    # Type: bool
    dont_print_server: false

    # Quick test for CI.
    # Type: bool
    quick_test_for_ci: false

    # Windows standalone build: Enable convenient things that most people using the standalone windows build will probably enjoy (like auto opening the page on startup).
    # Type: bool
    windows_standalone_build: false
  pytorch:

    # Set the id of the cuda device this instance will use, or leave empty to autodetect.
    # Type: int
    cuda_device:

    # Disable upcasting of attention. Can boost speed but increase the chances of black images.
    # Type: bool
    dont_upcast_attention: false

    # Force fp32 (If this makes your GPU work better please report it).
    # Type: bool
    force_fp32: false

    # Use torch-directml.
    # Type: int
    directml:

    # Type of cross attention to use
    # Choices:
    #  - (empty): Don't use cross-attention.
    #  - split: Use the split cross attention optimization instead of the sub-quadratic one. Ignored when xformers is used.
    #  - pytorch: Use the new pytorch 2.0 cross attention function.
    cross_attention:

    # Disable xformers.
    # Type: bool
    disable_xformers: false

    # Determines how VRAM is used.
    # Choices:
    #  - (empty): Autodetect the optional VRAM settings based on hardware.
    #  - highvram: By default models will be unloaded to CPU memory after being used. This option keeps them in GPU memory.
    #  - normalvram: Used to force normal vram use if lowvram gets automatically enabled.
    #  - lowvram: Split the unet in parts to use less vram.
    #  - novram: When lowvram isn't enough.
    #  - cpu: To use the CPU for everything (slow).
    vram: