⚜️ SDXL All-In-One

The README doesn't hide its favorite: "I love this node so much." It's the node that handles everything that normally clutters the front of an SDXL graph - the empty latent, the wildcard resolution, the style injection, the CLIP encoding, and a resolution trick most SDXL workflows get wrong - collapsed into one box.

Why it exists

The author built this pack for a one-click portrait-generation workflow they posted to r/comfyui, and this node is the engine of it: feed it a wildcard-laden prompt and a style, and it produces a genuinely varied batch with almost no manual prompt editing between runs. That's the design center - a front-of-workflow node for a two-stage SDXL setup, not a general-purpose conditioning utility.

The mechanism worth understanding

SDXL's conditioning carries a target resolution separate from the actual latent size - a training-time input the model uses to compose the image for how big it's ultimately meant to be. Most hand-built SDXL graphs just leave that at the starting latent size, which means the model is composing for a smaller image than what you'll actually end up with after your hi-res pass. This node's upscale_factor input exists specifically to fix that: it multiplies your chosen resolution by that factor and injects the final expected size into the output conditioning, so SDXL composes correctly for the image you're actually going to end up with, not just the starting latent.

Inputs and outputs that matter

• resolution - 26 SDXL-native aspect ratio presets, default 832x1216 (0.68) - a portrait ratio, unsurprising given what this pack was built for.
• upscale_factor - 1 to 8, default 2. Feeds the target-resolution trick above; set it to whatever multiplier your downstream upscale pass will actually use.
• positive_in / negative_in - your prompt text, wildcards and all. Unlike the leaner SDXL Preprocess sibling node, __wildcard__ tokens here get resolved automatically.
• clip - from your checkpoint loader.
• style - a DICTIONARY, required, no default. Wire in a Style Selector or a Control Pipe's Style output - you can't leave this dangling, and if you want style off entirely, wire one in with Main Style set to Inactive rather than skipping the connection.
• freeze_wildcards and seed - same as the standalone Wildcard Processor: lock a combination you like, then explore further variation through your sampler's own seed.

Outputs: positive and negative CONDITIONING (straight into your KSampler), LATENT (empty, at your chosen resolution), and two STRING outputs - + prompt and - prompt - the fully resolved text after wildcards and style got applied. Wire those into a Text Display node if you ever want to see exactly what the model actually saw, which matters more than usual here since wildcards mean what you typed and what got encoded are two different strings.

Installing it

Via ComfyUI Manager: search Comfyui FOCUS nodes, install, restart. Manually:

cd ComfyUI/custom_nodes
git clone https://github.com/DJ-Tribefull/Comfyui_FOCUS_nodes

Restart ComfyUI. No extra downloads - it's orchestrating ComfyUI's own CLIP encode and latent machinery plus the pack's bundled wildcard/style files.

Common issues & troubleshooting

Errors about a missing required input on style. This socket has no default - you must wire something into it, even if it's just a Style Selector left on Inactive.

Wildcards aren't resolving. Same rule as the standalone processor: token names must exactly match a .txt filename in focus_wildcards, no spaces, case-sensitive.

Hands still come out wrong. This node handles composition and prompt/style plumbing, not detail refinement - even the creator's own showcase image has an off hand in it. That's what the pack's optional advanced workflow (a SAM/SEGS face detailer, not one of this pack's own 13 nodes) is for, not something All-In-One touches.

Batch size maxed at 4096 - plenty of headroom; you'll hit VRAM limits long before you hit the node's own ceiling.