ComfyUI-Lora-Sweeper

A single ComfyUI node, Lora Epoch Sweeper, that points at a folder of LoRA training epochs (e.g. an ai-toolkit / kohya output dir where files look like my_lora_000002000.safetensors), lets you pick a step range and a training-step interval, and applies each selected epoch to your model.

Because the node emits lists, ComfyUI runs everything downstream of it once per epoch — so a single click on Queue generates one image per LoRA epoch.

Install

Clone into ComfyUI/custom_nodes/ and restart ComfyUI:

git clone https://github.com/ethanfel/ComfyUI-Lora-Sweeper ComfyUI/custom_nodes/ComfyUI-Lora-Sweeper

No extra dependencies.

The node: Lora Epoch Sweeper

Category: loaders/LoraSweeper

Inputs

Name	Type	Notes
model	MODEL	Base model each epoch is applied to.
clip	CLIP (optional)	Patched too if connected; otherwise model-only.
folder_path	STRING	Absolute path to the epoch folder. ~ is expanded; a bare name is also looked up inside the loras dir.
lora_basename	STRING	Which LoRA in the folder to sweep, when the folder holds several (substring of its name). Leave empty to auto-pick the LoRA with the most epochs.
start_step	INT	Lowest training step to include (inclusive).
end_step	INT	Highest step to include. 0 = no upper limit.
step_interval	INT	Thin the range to ~one checkpoint per this many training steps (e.g. 500). 0 = keep every epoch.
strength_model / strength_clip	FLOAT	LoRA strengths (same as the stock LoRA loader).
include_base	BOOLEAN	Also include the final suffix-less name.safetensors.
max_count	INT	Hard cap on number of epochs. 0 = unlimited.

step_interval targets the multiples of the interval inside your range and snaps each to the nearest available checkpoint — so with epochs saved every 250 steps, step_interval = 500 gives the round 500, 1000, 1500, …. Odd intervals that don't divide your save schedule still return well-spaced checkpoints.

Folders with several LoRAs

One folder often contains epochs from more than one training run, e.g.:

styleA_000000250.safetensors ... styleA_000004000.safetensors   (16 epochs)
styleB_000006750.safetensors                                    (1)
styleC_000002500.safetensors                                    (1)

The node groups files by LoRA name (everything before the _<step> suffix) and only sweeps one group. Set lora_basename to pick it (e.g. styleA), or leave it empty to auto-select the group with the most epochs. An ambiguous substring raises an error listing the matches.

Outputs (all lists, one entry per epoch)

Name	Type	Use
model	MODEL	Wire to KSampler.
clip	CLIP	Wire to your text encoders (or ignore).
step_label	STRING	The step number, e.g. "2000" ("final" for the base file).
lora_name	STRING	Filename without extension.

Example

A LoRA with epochs saved every 250 steps from 250 to 4000:

• start_step = 1000, end_step = 3000, step_interval = 500 → sweeps 1000, 1500, 2000, 2500, 3000.

Wire it up:

Sweeper.model  -> KSampler.model
Sweeper.clip   -> CLIPTextEncode.clip   (if you use clip)
KSampler -> VAEDecode -> SaveImage

Press Queue once → you get one image per selected epoch.

Labeling each image with its step

On the SaveImage node, right-click → Convert filename_prefix to input, then connect step_label (or lora_name) to it. Each saved file is then named after the epoch it used. (Any text/label node that accepts a STRING input works the same way, since the output is list-aware.)

Notes

• Each epoch is a separate patched model held in memory for the run; sweeping a large number of epochs at once uses more RAM. Use step_interval / max_count to thin big sweeps.
• Step parsing expects the kohya/ai-toolkit _<digits>.safetensors suffix. Files without a numeric suffix are treated as the "final" checkpoint.

License

MIT