👺 Remap Float List Auto Input

This is the lazier sibling of 👺 Remap Float List, and "lazier" is a compliment. The plain version makes you declare the input range - which means guessing what your generator actually emits, and the guess is usually the part that bites you. Auto Input removes that step: it measures the minimum and maximum of the list itself and rescales everything to whatever output range you specify. You hand it a list, you say "I want it in 0–1", and out comes a properly normalized version. No range hand-typing, no off-by-one-fudge, no "wait, was my noise actually 0.3–0.8?"

That makes it the node you reach for when you don't care about absolute values - only about relative shape. Classic use: you've got some generated curve or strength list and you want to stretch it to fill a full strength range for animation. Since it normalizes to min/max, the smallest value in the list always lands on min_output and the largest on max_output, and everything else slots in proportionally between. If your list already spans the full range, it behaves like the plain remap with correct inputs anyway.

Inputs and output

• list_of_floats - the values to normalize. It's a FLOAT list input, so feed it from a list generator (Kijai's KJNodes or this pack's own generators).
• min_output / max_output - the range you want the result in. Defaults 0 and 1, which is the classic normalize-to-0-1 setup.
• remapped_list (FLOAT output) - the rescaled list, same length and order as the input.

Two outputs, one output. If the output list isn't doing what you expect, check min_output/max_output first - those are the only things you can actually get wrong.

Installing it

Part of Nilor Nodes (nilor-corp/nilor-nodes):

cd ComfyUI/custom_nodes
git clone https://github.com/nilor-corp/nilor-nodes

or ComfyUI Manager → search "Nilor Nodes" → install → restart. No model files. The README lists Kijai's comfyui-kjnodes as a prerequisite, and the pack's requirements.txt drags in a lot of infrastructure (boto3, fastapi, huggingface_hub, openexr) regardless of whether you use any of it - normal for this pack, mildly annoying if you only wanted the one node.

Troubleshooting

Two edges worth knowing. First, if all your input values are identical, min equals max and the scale factor blows up - the source computes the range from the list rather than rejecting it, so feed it a flat list at your own risk. Second, and this is the one that trips people: because the range is auto-measured, a single outlier will crush everything else toward the middle of your output range. A list of 0.5, 0.6, 0.7, 1.0 normalizes the 0.5–0.7 values into a tight band just to fit that 1.0. If your data has spikes, the plain Remap Float List with hand-set bounds is the safer tool. And as always with this pack: no community threads to lean on, so the README and source are the docs.