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ComfyUI/custom_nodes/rgthree-comfy/py/lora_stack.py
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Add custom nodes, Civitai loras (LFS), and vast.ai setup script
Includes 30 custom nodes committed directly, 7 Civitai-exclusive
loras stored via Git LFS, and a setup script that installs all
dependencies and downloads HuggingFace-hosted models on vast.ai.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-09 00:56:42 +00:00

47 lines
2.0 KiB
Python

from .constants import get_category, get_name
from nodes import LoraLoader
import folder_paths
class RgthreeLoraLoaderStack:
NAME = get_name('Lora Loader Stack')
CATEGORY = get_category()
@classmethod
def INPUT_TYPES(cls): # pylint: disable = invalid-name, missing-function-docstring
return {
"required": {
"model": ("MODEL",),
"clip": ("CLIP", ),
"lora_01": (['None'] + folder_paths.get_filename_list("loras"), ),
"strength_01":("FLOAT", {"default": 1.0, "min": -10.0, "max": 10.0, "step": 0.01}),
"lora_02": (['None'] + folder_paths.get_filename_list("loras"), ),
"strength_02":("FLOAT", {"default": 1.0, "min": -10.0, "max": 10.0, "step": 0.01}),
"lora_03": (['None'] + folder_paths.get_filename_list("loras"), ),
"strength_03":("FLOAT", {"default": 1.0, "min": -10.0, "max": 10.0, "step": 0.01}),
"lora_04": (['None'] + folder_paths.get_filename_list("loras"), ),
"strength_04":("FLOAT", {"default": 1.0, "min": -10.0, "max": 10.0, "step": 0.01}),
}
}
RETURN_TYPES = ("MODEL", "CLIP")
FUNCTION = "load_lora"
def load_lora(self, model, clip, lora_01, strength_01, lora_02, strength_02, lora_03, strength_03, lora_04, strength_04):
if lora_01 != "None" and strength_01 != 0:
model, clip = LoraLoader().load_lora(model, clip, lora_01, strength_01, strength_01)
if lora_02 != "None" and strength_02 != 0:
model, clip = LoraLoader().load_lora(model, clip, lora_02, strength_02, strength_02)
if lora_03 != "None" and strength_03 != 0:
model, clip = LoraLoader().load_lora(model, clip, lora_03, strength_03, strength_03)
if lora_04 != "None" and strength_04 != 0:
model, clip = LoraLoader().load_lora(model, clip, lora_04, strength_04, strength_04)
return (model, clip)