Add WanVideo Lora Select node and related functionality. Fixes #266

- Implemented the WanVideo Lora Select node in Python with input handling for low memory loading and LORA syntax processing.
- Updated the JavaScript side to register the new node and manage its widget interactions.
- Enhanced constants files to include the new node type and its corresponding ID.
- Modified existing Lora Loader and Stacker references to accommodate the new node in various workflows and UI components.
- Added example workflow JSON for the new node to demonstrate its usage.

__init__.py

@@ -4,6 +4,7 @@ from .py.nodes.trigger_word_toggle import TriggerWordToggle
 from .py.nodes.lora_stacker import LoraStacker
 from .py.nodes.save_image import SaveImage
 from .py.nodes.debug_metadata import DebugMetadata
+from .py.nodes.wanvideo_lora_select import WanVideoLoraSelect
 # Import metadata collector to install hooks on startup
 from .py.metadata_collector import init as init_metadata_collector
 
@@ -12,7 +13,8 @@ NODE_CLASS_MAPPINGS = {
     TriggerWordToggle.NAME: TriggerWordToggle,
     LoraStacker.NAME: LoraStacker,
     SaveImage.NAME: SaveImage,
-    DebugMetadata.NAME: DebugMetadata
+    DebugMetadata.NAME: DebugMetadata,
+    WanVideoLoraSelect.NAME: WanVideoLoraSelect
 }
 
 WEB_DIRECTORY = "./web/comfyui"

py/nodes/lora_stacker.py

@@ -1,6 +1,4 @@
 from comfy.comfy_types import IO # type: ignore
-from ..services.lora_scanner import LoraScanner
-from ..config import config
 import asyncio
 import os
 from .utils import FlexibleOptionalInputType, any_type, get_lora_info, extract_lora_name, get_loras_list

py/nodes/wanvideo_lora_select.py

@@ -0,0 +1,92 @@
+from comfy.comfy_types import IO # type: ignore
+import asyncio
+import folder_paths # type: ignore
+from .utils import FlexibleOptionalInputType, any_type, get_lora_info, extract_lora_name, get_loras_list
+import logging
+
+logger = logging.getLogger(__name__)
+
+class WanVideoLoraSelect:
+    NAME = "WanVideo Lora Select (LoraManager)"
+    CATEGORY = "Lora Manager/stackers"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "low_mem_load": ("BOOLEAN", {"default": False, "tooltip": "Load the LORA model with less VRAM usage, slower loading"}),
+                "text": (IO.STRING, {
+                    "multiline": True, 
+                    "dynamicPrompts": True, 
+                    "tooltip": "Format: <lora:lora_name:strength> separated by spaces or punctuation",
+                    "placeholder": "LoRA syntax input: <lora:name:strength>"
+                }),
+            },
+            "optional": FlexibleOptionalInputType(any_type),
+        }
+
+    RETURN_TYPES = ("WANVIDLORA", IO.STRING, IO.STRING)
+    RETURN_NAMES = ("lora", "trigger_words", "active_loras")
+    FUNCTION = "process_loras"
+    
+    def process_loras(self, text, low_mem_load=False, **kwargs):
+        loras_list = []
+        all_trigger_words = []
+        active_loras = []
+        
+        # Process existing prev_lora if available
+        prev_lora = kwargs.get('prev_lora', None)
+        if prev_lora is not None:
+            loras_list.extend(prev_lora)
+        
+        # Get blocks if available
+        blocks = kwargs.get('blocks', {})
+        selected_blocks = blocks.get("selected_blocks", {})
+        layer_filter = blocks.get("layer_filter", "")
+        
+        # Process loras from kwargs with support for both old and new formats
+        loras_from_widget = get_loras_list(kwargs)
+        for lora in loras_from_widget:
+            if not lora.get('active', False):
+                continue
+                
+            lora_name = lora['name']
+            model_strength = float(lora['strength'])
+            clip_strength = float(lora.get('clipStrength', model_strength))
+            
+            # Get lora path and trigger words
+            lora_path, trigger_words = asyncio.run(get_lora_info(lora_name))
+            
+            # Create lora item for WanVideo format
+            lora_item = {
+                "path": folder_paths.get_full_path("loras", lora_path),
+                "strength": model_strength,
+                "name": lora_path.split(".")[0],
+                "blocks": selected_blocks,
+                "layer_filter": layer_filter,
+                "low_mem_load": low_mem_load,
+            }
+            
+            # Add to list and collect active loras
+            loras_list.append(lora_item)
+            active_loras.append((lora_name, model_strength, clip_strength))
+            
+            # Add trigger words to collection
+            all_trigger_words.extend(trigger_words)
+        
+        # Format trigger_words for output
+        trigger_words_text = ",, ".join(all_trigger_words) if all_trigger_words else ""
+        
+        # Format active_loras for output
+        formatted_loras = []
+        for name, model_strength, clip_strength in active_loras:
+            if abs(model_strength - clip_strength) > 0.001:
+                # Different model and clip strengths
+                formatted_loras.append(f"<lora:{name}:{str(model_strength).strip()}:{str(clip_strength).strip()}>")
+            else:
+                # Same strength for both
+                formatted_loras.append(f"<lora:{name}:{str(model_strength).strip()}>")
+                
+        active_loras_text = " ".join(formatted_loras)
+
+        return (loras_list, trigger_words_text, active_loras_text)

py/utils/constants.py

@@ -10,7 +10,8 @@ NSFW_LEVELS = {
 # Node type constants
 NODE_TYPES = {
     "Lora Loader (LoraManager)": 1,
-    "Lora Stacker (LoraManager)": 2
+    "Lora Stacker (LoraManager)": 2,
+    "WanVideo Lora Select (LoraManager)": 3
 }
 
 # Default ComfyUI node color when bgcolor is null

static/js/utils/constants.js

@@ -108,19 +108,22 @@ export const NSFW_LEVELS = {
 // Node type constants
 export const NODE_TYPES = {
     LORA_LOADER: 1,
-    LORA_STACKER: 2
+    LORA_STACKER: 2,
+    WAN_VIDEO_LORA_SELECT: 3
 };
 
 // Node type names to IDs mapping
 export const NODE_TYPE_NAMES = {
     "Lora Loader (LoraManager)": NODE_TYPES.LORA_LOADER,
-    "Lora Stacker (LoraManager)": NODE_TYPES.LORA_STACKER
+    "Lora Stacker (LoraManager)": NODE_TYPES.LORA_STACKER,
+    "WanVideo Lora Select (LoraManager)": NODE_TYPES.WAN_VIDEO_LORA_SELECT
 };
 
 // Node type icons
 export const NODE_TYPE_ICONS = {
     [NODE_TYPES.LORA_LOADER]: "fas fa-l",
-    [NODE_TYPES.LORA_STACKER]: "fas fa-s"
+    [NODE_TYPES.LORA_STACKER]: "fas fa-s",
+    [NODE_TYPES.WAN_VIDEO_LORA_SELECT]: "fas fa-w"
 };
 
 // Default ComfyUI node color when bgcolor is null

static/js/utils/uiHelpers.js

@@ -337,7 +337,7 @@ export async function sendLoraToWorkflow(loraSyntax, replaceMode = false, syntax
     // Success case - check node count
     if (registryData.data.node_count === 0) {
       // No nodes found - show warning
-      showToast('No Lora Loader or Lora Stacker nodes found in workflow', 'warning');
+      showToast('No supported target nodes found in workflow', 'warning');
       return false;
     } else if (registryData.data.node_count > 1) {
       // Multiple nodes - show selector

web/comfyui/lora_loader.js

@@ -76,7 +76,9 @@ app.registerExtension({
         
         // Standard mode - update a specific node
         const node = app.graph.getNodeById(+id);
-        if (!node || (node.comfyClass !== "Lora Loader (LoraManager)" && node.comfyClass !== "Lora Stacker (LoraManager)")) {
+        if (!node || (node.comfyClass !== "Lora Loader (LoraManager)" && 
+                node.comfyClass !== "Lora Stacker (LoraManager)" && 
+                node.comfyClass !== "WanVideo Lora Select (LoraManager)")) {
             console.warn("Node not found or not a LoraLoader:", id);
             return;
         }
@@ -87,7 +89,7 @@ app.registerExtension({
     // Helper method to update a single node's lora code
     updateNodeLoraCode(node, loraCode, mode) {
         // Update the input widget with new lora code
-        const inputWidget = node.widgets[0];
+        const inputWidget = node.inputWidget;
         if (!inputWidget) return;
         
         // Get the current lora code
@@ -182,6 +184,7 @@ app.registerExtension({
 
             // Update input widget callback
             const inputWidget = this.widgets[0];
+            this.inputWidget = inputWidget;
             inputWidget.callback = (value) => {
               if (isUpdating) return;
               isUpdating = true;

web/comfyui/lora_stacker.js

@@ -105,6 +105,7 @@ app.registerExtension({
 
                 // Update input widget callback
                 const inputWidget = this.widgets[0];
+                this.inputWidget = inputWidget;
                 inputWidget.callback = (value) => {
                     if (isUpdating) return;
                     isUpdating = true;

web/comfyui/usage_stats.js

@@ -52,7 +52,9 @@ app.registerExtension({
             // Find all Lora nodes
             const loraNodes = [];
             for (const node of workflow.nodes.values()) {
-                if (node.type === "Lora Loader (LoraManager)" || node.type === "Lora Stacker (LoraManager)") {
+                if (node.type === "Lora Loader (LoraManager)" || 
+                    node.type === "Lora Stacker (LoraManager)" || 
+                    node.type === "WanVideo Lora Select (LoraManager)") {
                     loraNodes.push({
                         node_id: node.id,
                         bgcolor: node.bgcolor || null,

web/comfyui/wanvideo_lora_select.js

@@ -0,0 +1,131 @@
+import { app } from "../../scripts/app.js";
+import { 
+    LORA_PATTERN, 
+    getActiveLorasFromNode,
+    collectActiveLorasFromChain,
+    updateConnectedTriggerWords,
+    chainCallback
+} from "./utils.js";
+import { addLorasWidget } from "./loras_widget.js";
+
+function mergeLoras(lorasText, lorasArr) {
+    const result = [];
+    let match;
+
+    // Reset pattern index before using
+    LORA_PATTERN.lastIndex = 0;
+    
+    // Parse text input and create initial entries
+    while ((match = LORA_PATTERN.exec(lorasText)) !== null) {
+        const name = match[1];
+        const modelStrength = Number(match[2]);
+        // Extract clip strength if provided, otherwise use model strength
+        const clipStrength = match[3] ? Number(match[3]) : modelStrength;
+        
+        // Find if this lora exists in the array data
+        const existingLora = lorasArr.find(l => l.name === name);
+        
+        result.push({
+            name: name,
+            // Use existing strength if available, otherwise use input strength
+            strength: existingLora ? existingLora.strength : modelStrength,
+            active: existingLora ? existingLora.active : true,
+            clipStrength: existingLora ? existingLora.clipStrength : clipStrength,
+        });
+    }
+
+    return result;
+}
+
+app.registerExtension({
+    name: "LoraManager.WanVideoLoraSelect",
+    
+    async beforeRegisterNodeDef(nodeType, nodeData, app) {
+        if (nodeType.comfyClass === "WanVideo Lora Select (LoraManager)") {
+            chainCallback(nodeType.prototype, "onNodeCreated", async function() {
+                // Enable widget serialization
+                this.serialize_widgets = true;
+
+                // Add optional inputs
+                this.addInput("prev_lora", 'WANVIDLORA', {
+                    "shape": 7  // 7 is the shape of the optional input
+                });
+                
+                this.addInput("blocks", 'SELECTEDBLOCKS', {
+                    "shape": 7  // 7 is the shape of the optional input
+                });
+
+                // Restore saved value if exists
+                let existingLoras = [];
+                if (this.widgets_values && this.widgets_values.length > 0) {
+                    // 0 for low_mem_load, 1 for text widget, 2 for loras widget
+                    const savedValue = this.widgets_values[2];
+                    existingLoras = savedValue || [];
+                }
+                // Merge the loras data
+                const mergedLoras = mergeLoras(this.widgets[1].value, existingLoras);
+                
+                // Add flag to prevent callback loops
+                let isUpdating = false;
+                 
+                const result = addLorasWidget(this, "loras", {
+                    defaultVal: mergedLoras  // Pass object directly
+                }, (value) => {
+                    // Prevent recursive calls
+                    if (isUpdating) return;
+                    isUpdating = true;
+                    
+                    try {
+                        // Remove loras that are not in the value array
+                        const inputWidget = this.widgets[1];
+                        const currentLoras = value.map(l => l.name);
+                        
+                        // Use the constant pattern here as well
+                        let newText = inputWidget.value.replace(LORA_PATTERN, (match, name, strength) => {
+                            return currentLoras.includes(name) ? match : '';
+                        });
+                        
+                        // Clean up multiple spaces and trim
+                        newText = newText.replace(/\s+/g, ' ').trim();
+                        
+                        inputWidget.value = newText;
+                        
+                        // Update this node's direct trigger toggles with its own active loras
+                        const activeLoraNames = new Set();
+                        value.forEach(lora => {
+                            if (lora.active) {
+                                activeLoraNames.add(lora.name);
+                            }
+                        });
+                        updateConnectedTriggerWords(this, activeLoraNames);
+                    } finally {
+                        isUpdating = false;
+                    }
+                });
+                
+                this.lorasWidget = result.widget;
+
+                // Update input widget callback
+                const inputWidget = this.widgets[1];
+                this.inputWidget = inputWidget;
+                inputWidget.callback = (value) => {
+                    if (isUpdating) return;
+                    isUpdating = true;
+                    
+                    try {
+                        const currentLoras = this.lorasWidget.value || [];
+                        const mergedLoras = mergeLoras(value, currentLoras);
+                        
+                        this.lorasWidget.value = mergedLoras;
+                        
+                        // Update this node's direct trigger toggles with its own active loras
+                        const activeLoraNames = getActiveLorasFromNode(this);
+                        updateConnectedTriggerWords(this, activeLoraNames);
+                    } finally {
+                        isUpdating = false;
+                    }
+                };
+            });
+        }
+    },
+});