import os from folder_paths import get_filename_list, get_full_path import comfy.sd import comfy.utils class LoopLoraSelector: @classmethod def INPUT_TYPES(cls): lora_list = get_filename_list("loras") optional_inputs = {} # Add a default value if lora_list is empty if not lora_list: lora_list = ["none"] for i in range(1, 21): optional_inputs[f"lora_{i}"] = (lora_list, {"default": lora_list[0]}) optional_inputs[f"strength_model_{i}"] = ("FLOAT", {"default": 1.0, "min": -100.0, "max": 100.0, "step": 0.01}) optional_inputs[f"strength_clip_{i}"] = ("FLOAT", {"default": 1.0, "min": -100.0, "max": 100.0, "step": 0.01}) return { "required": { "number_of_loras": ("INT", {"default": 3, "min": 1, "max": 20, "step": 1}), "model": ("MODEL",), "clip": ("CLIP",), }, "optional": optional_inputs } RETURN_TYPES = ("MODEL", "CLIP", "STRING", "STRING", "STRING") RETURN_NAMES = ("model", "clip", "lora_path", "lora_name", "lora_folder") FUNCTION = "loop_select_lora" CATEGORY = "Bjornulf" OUTPUT_IS_LIST = (True, True, True, True, True) def loop_select_lora(self, number_of_loras, model, clip, **kwargs): available_loras = [] strengths_model = [] strengths_clip = [] for i in range(1, number_of_loras + 1): lora_key = f"lora_{i}" strength_model_key = f"strength_model_{i}" strength_clip_key = f"strength_clip_{i}" if lora_key in kwargs and kwargs[lora_key] and kwargs[lora_key] != "none": available_loras.append(kwargs[lora_key]) strengths_model.append(kwargs.get(strength_model_key, 1.0)) strengths_clip.append(kwargs.get(strength_clip_key, 1.0)) if not available_loras: # Return original model and clip if no valid LoRAs are selected return ([model], [clip], [""], [""], [""]) models = [] clips = [] lora_paths = [] lora_names = [] lora_folders = [] for selected_lora, strength_model, strength_clip in zip(available_loras, strengths_model, strengths_clip): lora_name = os.path.splitext(os.path.basename(selected_lora))[0] lora_path = get_full_path("loras", selected_lora) lora_folder = os.path.basename(os.path.dirname(lora_path)) lora = comfy.utils.load_torch_file(lora_path, safe_load=True) model_lora, clip_lora = comfy.sd.load_lora_for_models(model, clip, lora, strength_model, strength_clip) models.append(model_lora) clips.append(clip_lora) lora_paths.append(lora_path) lora_names.append(lora_name) lora_folders.append(lora_folder) return (models, clips, lora_paths, lora_names, lora_folders)