ConditioningBatch8

The bigger sibling of ConditioningBatch4 - same job, more slots. Instead of chaining ComfyUI's stock ConditioningCombine seven times to merge eight conditionings, this is one node with eight input slots. It's mostly useful for regional-conditioning setups with a lot of zones, or prompt-batch generation across several distinct conditionings, where the alternative is a wall of combiner nodes cluttering the graph for no real benefit.

Eight slots isn't an arbitrary number for this pack. RES4LYF's regional conditioning feature is explicitly built for a lot of zones at once - the README says "unlimited zones" and points to examples using more than ten in a single image. If you're building one of those masked-region workflows by hand, you'll hit the point where you have five, six, seven separate conditionings that all need to land in one input before the sampler sees them, and a chain of two-input combiners just gets in the way of reading the graph.

How it works

It combines (batches) whatever conditionings you wire in - it doesn't blend or average them into each other. The output is a batch containing all of them, not a weighted mix. If a blend is what you actually want, this pack's ConditioningAdd or ConditioningAverageScheduler do that job instead.

The inputs and outputs that matter

• conditioning_0 (CONDITIONING) - the only required input.
• conditioning_1 through conditioning_7 (CONDITIONING, all optional) - seven more optional slots. Wire in as many as you have and leave the rest disconnected.

Output: conditioning (CONDITIONING), the combined batch.

How to install it

Via ComfyUI Manager, search "RES4LYF". Or:

cd ComfyUI/custom_nodes
git clone https://github.com/ClownsharkBatwing/RES4LYF/
cd RES4LYF
pip install -r requirements.txt

then restart.

Common issues & troubleshooting

Only conditioning_0 is required - the other seven are genuinely optional. If you've got three or four conditionings to combine, just leave the unused slots empty; there's no need to pad them with duplicates or dummy values.

Batching isn't blending. This produces a batch of conditionings, not an interpolated average - if your intent was a weighted mix rather than "all of these, together," you want a different node (ConditioningAdd or ConditioningAverageScheduler, both in this same pack).

If you only ever need two to four conditionings, ConditioningBatch4 is the same node with fewer unused slots on screen - purely a matter of graph tidiness, not a functional difference.

Keep your wiring order consistent with your mask order if this feeds a regional-conditioning setup. Some approaches to regional conditioning tie each entry in a batch to a specific zone by position rather than by name - if a region ends up with the wrong prompt after combining, check that conditioning_0 through conditioning_7 line up with your masks in the order you intended.