mirror of
https://github.com/willmiao/ComfyUI-Lora-Manager.git
synced 2026-03-21 21:22:11 -03:00
Create unified settings.js extension to centralize all Lora Manager ComfyUI settings registration, eliminating code duplication across multiple files. Add new setting "Enable Custom Words Autocomplete in Prompt Nodes" (enabled by default) to control custom words autocomplete in prompt node text widgets. When disabled, only 'emb:' prefix triggers embeddings autocomplete. Changes: - Create web/comfyui/settings.js with all three settings: * Trigger Word Wheel Sensitivity (existing) * Auto path correction (existing) * Enable Custom Words Autocomplete in Prompt Nodes (new) - Refactor autocomplete.js to respect the new setting - Update trigger_word_toggle.js to import from settings.js - Update usage_stats.js to import from settings.js
163 lines
6.2 KiB
JavaScript
163 lines
6.2 KiB
JavaScript
// ComfyUI extension to track model usage statistics
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import { app } from "../../scripts/app.js";
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import { api } from "../../scripts/api.js";
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import { showToast } from "./utils.js";
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import { getAutoPathCorrectionPreference } from "./settings.js";
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// Define target nodes and their widget configurations
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const PATH_CORRECTION_TARGETS = [
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{ comfyClass: "CheckpointLoaderSimple", widgetName: "ckpt_name", modelType: "checkpoints" },
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{ comfyClass: "Checkpoint Loader with Name (Image Saver)", widgetName: "ckpt_name", modelType: "checkpoints" },
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{ comfyClass: "UNETLoader", widgetName: "unet_name", modelType: "checkpoints" },
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{ comfyClass: "easy comfyLoader", widgetName: "ckpt_name", modelType: "checkpoints" },
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{ comfyClass: "CheckpointLoader|pysssss", widgetName: "ckpt_name", modelType: "checkpoints" },
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{ comfyClass: "Efficient Loader", widgetName: "ckpt_name", modelType: "checkpoints" },
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{ comfyClass: "UnetLoaderGGUF", widgetName: "unet_name", modelType: "checkpoints" },
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{ comfyClass: "UnetLoaderGGUFAdvanced", widgetName: "unet_name", modelType: "checkpoints" },
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{ comfyClass: "LoraLoader", widgetName: "lora_name", modelType: "loras" },
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{ comfyClass: "easy loraStack", widgetNamePattern: "lora_\\d+_name", modelType: "loras" }
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];
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// Register the extension
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app.registerExtension({
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name: "LoraManager.UsageStats",
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setup() {
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// Listen for successful executions
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api.addEventListener("execution_success", ({ detail }) => {
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if (detail && detail.prompt_id) {
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this.updateUsageStats(detail.prompt_id);
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}
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});
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},
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async updateUsageStats(promptId) {
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try {
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// Call backend endpoint with the prompt_id
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const response = await fetch(`/api/lm/update-usage-stats`, {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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},
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body: JSON.stringify({ prompt_id: promptId }),
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});
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if (!response.ok) {
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console.warn("Failed to update usage statistics:", response.statusText);
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}
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} catch (error) {
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console.error("Error updating usage statistics:", error);
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}
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},
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async loadedGraphNode(node) {
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if (!getAutoPathCorrectionPreference()) {
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return;
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}
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// Check if this node type needs path correction
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const target = PATH_CORRECTION_TARGETS.find(t => t.comfyClass === node.comfyClass);
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if (!target) {
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return;
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}
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await this.correctNodePaths(node, target);
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},
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async correctNodePaths(node, target) {
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try {
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if (target.widgetNamePattern) {
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// Handle pattern-based widget names (like lora_1_name, lora_2_name, etc.)
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const pattern = new RegExp(target.widgetNamePattern);
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const widgetIndexes = [];
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if (node.widgets) {
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node.widgets.forEach((widget, index) => {
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if (pattern.test(widget.name)) {
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widgetIndexes.push(index);
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}
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});
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}
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// Process each matching widget
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for (const widgetIndex of widgetIndexes) {
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await this.correctWidgetPath(node, widgetIndex, target.modelType);
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}
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} else {
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// Handle single widget name
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if (node.widgets) {
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const widgetIndex = node.widgets.findIndex(w => w.name === target.widgetName);
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if (widgetIndex !== -1) {
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await this.correctWidgetPath(node, widgetIndex, target.modelType);
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}
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}
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}
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} catch (error) {
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console.error("Error correcting node paths:", error);
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}
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},
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async correctWidgetPath(node, widgetIndex, modelType) {
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if (!node.widgets_values || !node.widgets_values[widgetIndex]) {
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return;
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}
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const currentPath = node.widgets_values[widgetIndex];
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if (!currentPath || typeof currentPath !== 'string') {
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return;
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}
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// Extract filename from path (after last separator)
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const fileName = currentPath.split(/[/\\]/).pop();
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if (!fileName) {
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return;
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}
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try {
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// Search for current relative path
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const response = await api.fetchApi(`/lm/${modelType}/relative-paths?search=${encodeURIComponent(fileName)}&limit=2`);
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const data = await response.json();
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if (!data.success || !data.relative_paths || data.relative_paths.length === 0) {
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return;
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}
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const foundPaths = data.relative_paths;
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const firstPath = foundPaths[0];
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// Check if we need to update the path
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if (firstPath !== currentPath) {
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// Update the widget value
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// node.widgets_values[widgetIndex] = firstPath;
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node.widgets[widgetIndex].value = firstPath;
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if (foundPaths.length === 1) {
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// Single match found - success
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showToast({
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severity: 'info',
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summary: 'LoRA Manager Path Correction',
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detail: `Updated path for ${fileName}: ${firstPath}`,
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life: 5000
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});
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} else {
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// Multiple matches found - warning
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showToast({
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severity: 'warn',
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summary: 'LoRA Manager Path Correction',
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detail: `Multiple paths found for ${fileName}, using: ${firstPath}`,
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life: 5000
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});
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}
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// Mark node as modified
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if (node.setDirtyCanvas) {
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node.setDirtyCanvas(true);
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}
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}
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} catch (error) {
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console.error(`Error correcting path for ${fileName}:`, error);
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}
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}
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});
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