Aioli Nodes — ComfyUI Custom Node Suite

Two utility nodes for outpainting and inpainting in ComfyUI.

Installation

Via ComfyUI Registry (recommended)

Search "Aioli Nodes" directly in the ComfyUI Manager → Install Nodes.

Via Git URL

https://github.com/aiolicollective/aioli-nodes

Manual installation

1. Copy the aioli-nodes folder into ComfyUI/custom_nodes/
2. Restart ComfyUI
3. The nodes appear under the Aioli Nodes category

No extra dependencies — only math (Python stdlib), torch and Pillow (already bundled with ComfyUI).

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🖼️ Ratio Outpaint Calc

Prepares an image for outpainting to a standard aspect ratio.
Automatically computes padding and generates the mask.

Inputs

Parameter	Type	Description
image	IMAGE	Source image
ratio	dropdown	none · 1:1 · 4:5 · 5:4 · 3:4 · 4:3 · 16:9 · 9:16

Outputs

Output	Type	Description
image_padded	IMAGE	Image padded with neutral grey (0.5)
mask	MASK	Binary mask (0 = keep, 1 = generate)

Workflow

Load Image → 🖼️ Ratio Outpaint Calc → VAE Encode (Inpaint) → KSampler

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📐 BBox Multiple Fix

Plugs in right after Mask Bounding Box (ComfyUI Essentials).
Rounds the crop to the chosen multiple and optionally upscales to a Flux-friendly resolution.

The node ensures the inpainted region stitches back pixel-perfectly onto the base image — no border artefacts, no alignment drift.

Example

The inpaint applied back onto the base image fits the original contours exactly — pixel-perfect edges, no alignment drift.

Inputs

Parameter	Type	Description
image	IMAGE	Full source image (before crop)
mask	MASK	Full source mask (before crop)
x	INT	x output from Mask Bounding Box
y	INT	y output from Mask Bounding Box
width	INT	width output from Mask Bounding Box
height	INT	height output from Mask Bounding Box
multiple	dropdown	8 (VAE) · 32 (SD1.5) · 64 (SDXL/Flux)
target	dropdown	none · 512 · 768 · 1024 · 1536 · 2048

Outputs

Output	Type	Description
image_cropped	IMAGE	Cropped image (scaled if target is set or if bbox > 2048px)
mask_cropped	MASK	Cropped mask (scaled if target is set or if bbox > 2048px)
x	INT	x position for ImageCompositeMasked
y	INT	y position for ImageCompositeMasked
orig_width	INT	Crop width BEFORE scale (use for resize-back after VAE Decode)
orig_height	INT	Crop height BEFORE scale (use for resize-back after VAE Decode)
width	INT	Final width (after scale)
height	INT	Final height (after scale)

Scaling behaviour

Situation	Behaviour
bbox ≤ 2048, target none	Round up to multiple only — no scale
bbox ≤ 2048, target set	Upscale crop to target — pixel-perfect ratio via GCD
bbox > 2048 (any target)	Downscale crop to fit 2048px — ratio preserved via GCD

Workflow without scale

BBox Fix → VAE Encode → KSampler → VAE Decode → ImageCompositeMasked ← x, y

Workflow with upscale / downscale

BBox Fix → VAE Encode → KSampler → VAE Decode
  ↓ orig_width, orig_height              ↓
  ↓ x, y        → ImageResize+ ←────────┘
                       ↓
               ImageCompositeMasked ← x, y

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🔁 Example Workflow — Flux2Klein Inpaint

⬇ Download workflow JSON

A complete, ready-to-use inpaint workflow for Flux2Klein (9B), packaged as a ComfyUI subgraph (FLUX2KLEIN_INPAINT).

Required models

Role	File
UNet	flux2/flux-2-klein-9b-fp8.safetensors
VAE	flux2/flux2-vae.safetensors
Text encoder	qwen_3_8b_fp8mixed.safetensors

Required custom nodes

• Aioli Nodes (this repo) — BBoxMultipleFix
• ComfyUI Essentials — MaskBoundingBox+, ImageResize+
• ComfyUI KJNodes — GrowMaskWithBlur
• rgthree-comfy — Image Comparer (optional, for before/after preview)

Subgraph inputs

Input	Description
IMAGE	Source image (with painted mask)
MASK	Inpaint mask
Resize_Megapixels	Working resolution in megapixels (default: 4)
PROMPT	Inpaint prompt
Resize_Inpaint_Target	BBox target size (none · 512 · 768 · 1024 · 1536 · 2048)

Internal pipeline

LoadImageOutput (with mask painter)
  └→ FLUX2KLEIN_INPAINT subgraph
        ├── ImageScaleToTotalPixels   (resize source to working MP)
        ├── MaskBoundingBox+          (detect mask region)
        ├── BBoxMultipleFix           (crop + scale for Flux, cap 2048px)
        ├── GrowMaskWithBlur          (soften mask edges)
        ├── VAEEncode × 2 + SetLatentNoiseMask
        ├── CLIPTextEncode → ReferenceLatent → FluxGuidance
        ├── Flux2Scheduler + KSamplerSelect + RandomNoise
        ├── SamplerCustomAdvanced
        ├── VAEDecode
        ├── ImageResize+              (resize back to orig_width × orig_height)
        └── ImageCompositeMasked     (stitch result onto source)
  └→ SaveImage + Image Comparer (before / after)

Usage

1. Download the JSON and drag it into ComfyUI
2. Point LoadImageOutput to your image and paint your mask
3. Set your prompt and target resolution in the subgraph inputs
4. Run — the result is composited pixel-perfectly back onto the source image