mirror of
https://github.com/willmiao/ComfyUI-Lora-Manager.git
synced 2026-08-06 14:10:13 -03:00
feat(nodes): add Create Hook LoRA (LoraManager) node for multi-LoRA hook pipelines
This commit is contained in:
@@ -17,6 +17,7 @@ try: # pragma: no cover - import fallback for pytest collection
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from .py.nodes.lora_cycler import LoraCyclerLM
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from .py.nodes.lora_info import LoraInfoLM
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from .py.nodes.lora_syntax_to_path import LoraSyntaxToPath
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from .py.nodes.create_hook_lora import CreateHookLoraLM
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from .py.metadata_collector import init as init_metadata_collector
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except (
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ImportError
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@@ -62,6 +63,9 @@ except (
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LoraSyntaxToPath = importlib.import_module(
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"py.nodes.lora_syntax_to_path"
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).LoraSyntaxToPath
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CreateHookLoraLM = importlib.import_module(
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"py.nodes.create_hook_lora"
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).CreateHookLoraLM
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init_metadata_collector = importlib.import_module("py.metadata_collector").init
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NODE_CLASS_MAPPINGS = {
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@@ -83,6 +87,7 @@ NODE_CLASS_MAPPINGS = {
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LoraCyclerLM.NAME: LoraCyclerLM,
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LoraInfoLM.NAME: LoraInfoLM,
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LoraSyntaxToPath.NAME: LoraSyntaxToPath,
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CreateHookLoraLM.NAME: CreateHookLoraLM,
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}
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WEB_DIRECTORY = "./web/comfyui"
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116
py/nodes/create_hook_lora.py
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116
py/nodes/create_hook_lora.py
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@@ -0,0 +1,116 @@
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"""Create Hook LoRA (LoraManager) — multi-LoRA hook node compatible with ComfyUI's built-in hook pipeline.
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Produces ``("HOOKS",)`` output that chains seamlessly with downstream hook consumers
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(ConditioningSetProperties, SetHookKeyframes, CombineHooks, SetClipHooks, etc.).
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"""
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from __future__ import annotations
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import logging
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import os
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import comfy.hooks # type: ignore
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import comfy.utils # type: ignore
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from ..utils.utils import get_lora_info_absolute
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from .utils import (
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FlexibleOptionalInputType,
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any_type,
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apply_lora_syntax_format,
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get_loras_list,
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)
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logger = logging.getLogger(__name__)
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class CreateHookLoraLM:
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NAME = "Create Hook LoRA (LoraManager)"
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CATEGORY = "Lora Manager/hooks"
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@classmethod
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def INPUT_TYPES(cls):
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return {
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"required": {
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"text": (
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"AUTOCOMPLETE_TEXT_LORAS",
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{
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"placeholder": "Search LoRAs to add...",
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"tooltip": (
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"Search and select LoRAs. Each LoRA gets its own "
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"model/clip strength. Hooks chain with prev_hooks."
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),
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},
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),
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},
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"optional": FlexibleOptionalInputType(any_type),
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}
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RETURN_TYPES = ("HOOKS", "STRING", "STRING")
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RETURN_NAMES = ("HOOKS", "trigger_words", "active_loras")
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FUNCTION = "create_hook"
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def create_hook(self, text: str, **kwargs):
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"""Create a HookGroup from the selected LoRAs, chained with prev_hooks.
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Each active LoRA from the widget is loaded and wrapped in a WeightHook
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via :func:`comfy.hooks.create_hook_lora`. All hooks are combined into a
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single group and returned alongside trigger words and a human-readable
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summary of the active LoRAs.
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"""
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del text # used by the frontend widget only
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prev_hooks: comfy.hooks.HookGroup | None = kwargs.get("prev_hooks")
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hook_group = prev_hooks.clone() if prev_hooks is not None else comfy.hooks.HookGroup()
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all_trigger_words: list[str] = []
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active_loras: list[tuple[str, float, float]] = []
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for lora in get_loras_list(kwargs):
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if not lora.get("active", False):
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continue
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lora_name = apply_lora_syntax_format(lora["name"])
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model_strength = float(lora["strength"])
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clip_strength = float(lora.get("clipStrength", model_strength))
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# Skip useless no-op entries (both strengths are zero)
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if model_strength == 0.0 and clip_strength == 0.0:
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continue
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lora_path, trigger_words = get_lora_info_absolute(lora_name)
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if not lora_path or not os.path.isfile(lora_path):
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logger.warning("LoRA '%s' not found — skipping", lora_name)
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continue
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try:
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lora_weights = comfy.utils.load_torch_file(lora_path, safe_load=True)
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lora_hooks = comfy.hooks.create_hook_lora(
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lora=lora_weights,
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strength_model=model_strength,
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strength_clip=clip_strength,
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)
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except Exception:
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logger.exception("Failed to load LoRA '%s' — skipping", lora_name)
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continue
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hook_group = hook_group.clone_and_combine(lora_hooks)
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active_loras.append((lora_name, model_strength, clip_strength))
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all_trigger_words.extend(trigger_words)
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# Format trigger words (group mode separator)
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trigger_words_text = ",, ".join(all_trigger_words) if all_trigger_words else ""
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# Format active LoRAs summary
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formatted_loras = []
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for name, model_s, clip_s in active_loras:
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if abs(model_s - clip_s) > 0.001:
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formatted_loras.append(
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f"<lora:{name}:{model_s}:{clip_s}>"
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)
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else:
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formatted_loras.append(f"<lora:{name}:{model_s}>")
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active_loras_text = " ".join(formatted_loras)
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return (hook_group, trigger_words_text, active_loras_text)
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143
web/comfyui/create_hook_lora.js
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143
web/comfyui/create_hook_lora.js
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@@ -0,0 +1,143 @@
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import { app } from "../../scripts/app.js";
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import {
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getActiveLorasFromNode,
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updateConnectedTriggerWords,
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chainCallback,
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mergeLoras,
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getWidgetByName,
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getWidgetSerializedValue,
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} from "./utils.js";
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import { addLorasWidget } from "./loras_widget.js";
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import { applyLoraValuesToText, debounce } from "./lora_syntax_utils.js";
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import { applySelectionHighlight } from "./trigger_word_highlight.js";
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import { updateConnectedLoraInfoNodes } from "./lora_info.js";
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app.registerExtension({
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name: "LoraManager.CreateHookLora",
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async beforeRegisterNodeDef(nodeType, nodeData, app) {
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if (nodeType.comfyClass === "Create Hook LoRA (LoraManager)") {
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chainCallback(nodeType.prototype, "onNodeCreated", function () {
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// Enable widget serialization so loras widget state is persisted
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this.serialize_widgets = true;
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this.addInput("prev_hooks", "HOOKS", {
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shape: 7,
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});
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// Flags to prevent callback loops between text widget ↔ loras widget
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let isUpdating = false;
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let isSyncingInput = false;
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// Get the text input widget (AUTOCOMPLETE_TEXT_LORAS type, created by Vue widgets)
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const inputWidget = getWidgetByName(this, "text");
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if (!inputWidget) {
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console.warn(
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"LoRA Manager: text widget not found for Create Hook LoRA"
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);
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return;
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}
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this.inputWidget = inputWidget;
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const scheduleInputSync = debounce((lorasValue) => {
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if (isSyncingInput) {
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return;
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}
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isSyncingInput = true;
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isUpdating = true;
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try {
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const nextText = applyLoraValuesToText(
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inputWidget.value,
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lorasValue
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);
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if (inputWidget.value !== nextText) {
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inputWidget.value = nextText;
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}
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} finally {
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isUpdating = false;
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isSyncingInput = false;
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}
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});
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// Create the LoRA list widget
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const result = addLorasWidget(
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this,
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"loras",
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{
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onSelectionChange: (selection) => {
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applySelectionHighlight(this, selection);
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updateConnectedLoraInfoNodes(this, selection);
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},
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},
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(value) => {
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// Prevent recursive calls
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if (isUpdating) return;
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isUpdating = true;
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try {
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// Update connected trigger word toggles with active LoRA names
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const activeLoraNames = new Set();
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value.forEach((lora) => {
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if (lora.active) {
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activeLoraNames.add(lora.name);
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}
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});
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updateConnectedTriggerWords(this, activeLoraNames);
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} finally {
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isUpdating = false;
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}
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scheduleInputSync(value);
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}
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);
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this.lorasWidget = result.widget;
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// Set up callback for the text input widget to trigger merge logic
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inputWidget.callback = (value) => {
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if (isUpdating) return;
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isUpdating = true;
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try {
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const currentLoras = this.lorasWidget?.value || [];
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const mergedLoras = mergeLoras(value, currentLoras);
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if (this.lorasWidget) {
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this.lorasWidget.value = mergedLoras;
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}
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// Update connected trigger word toggles
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const activeLoraNames = getActiveLorasFromNode(this);
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updateConnectedTriggerWords(this, activeLoraNames);
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} finally {
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isUpdating = false;
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}
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};
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});
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}
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},
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async loadedGraphNode(node) {
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if (node.comfyClass === "Create Hook LoRA (LoraManager)") {
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// Restore saved loras widget values on workflow load
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let existingLoras = [];
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if (node.widgets_values && node.widgets_values.length > 0) {
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const savedValue = getWidgetSerializedValue(node, "loras");
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existingLoras = savedValue || [];
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}
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// Merge the loras data from text widget with saved values
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const inputWidget =
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node.inputWidget || getWidgetByName(node, "text");
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if (!inputWidget) {
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console.warn(
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"LoRA Manager: text widget not found while restoring Create Hook LoRA"
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);
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return;
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}
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const mergedLoras = mergeLoras(inputWidget.value, existingLoras);
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node.lorasWidget.value = mergedLoras;
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}
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},
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});
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