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README.md

@@ -20,18 +20,15 @@ Booru style tag autocompletion for the AUTOMATIC1111 Stable Diffusion WebUI
 </div>
 <br/>
 
-#### ⚠️ Notice:
-I am currently looking for feedback on a new feature I'm working on and want to release soon.<br/>
-Please check [the announcement post](https://github.com/DominikDoom/a1111-sd-webui-tagcomplete/discussions/270) for more info if you are interested to help.
-
 # 📄 Description
 
 Tag Autocomplete is an extension for the popular [AUTOMATIC1111 web UI](https://github.com/AUTOMATIC1111/stable-diffusion-webui) for Stable Diffusion.
+You can install it using the inbuilt available extensions list, clone the files manually as described [below](#-installation), or use a pre-packaged version from [Releases](https://github.com/DominikDoom/a1111-sd-webui-tagcomplete/releases).
 
 It displays autocompletion hints for recognized tags from "image booru" boards such as Danbooru, which are primarily used for browsing Anime-style illustrations.
-Since some Stable Diffusion models were trained using this information, for example [Waifu Diffusion](https://github.com/harubaru/waifu-diffusion) and many of the NAI-descendant models or merges, using exact tags in prompts can often improve composition and consistency.
+Since most custom Stable Diffusion models were trained using this information or merged with ones that did, using exact tags in prompts can often improve composition and consistency, even if the model itself has a photorealistic style.
 
-You can install it using the inbuilt available extensions list, clone the files manually as described [below](#-installation), or use a pre-packaged version from [Releases](https://github.com/DominikDoom/a1111-sd-webui-tagcomplete/releases).
+Disclaimer: The default tag lists contain NSFW terms, please use them responsibly.
 
 <br/>
 

javascript/_utils.js

@@ -61,7 +61,7 @@ async function loadCSV(path) {
 }
 
 // Fetch API
-async function fetchAPI(url, json = true, cache = false) {
+async function fetchTacAPI(url, json = true, cache = false) {
     if (!cache) {
         const appendChar = url.includes("?") ? "&" : "?";
         url += `${appendChar}${new Date().getTime()}`
@@ -80,7 +80,7 @@ async function fetchAPI(url, json = true, cache = false) {
         return await response.text();
 }
 
-async function postAPI(url, body = null) {
+async function postTacAPI(url, body = null) {
     let response = await fetch(url, {
         method: "POST",
         headers: {'Content-Type': 'application/json'},
@@ -95,7 +95,7 @@ async function postAPI(url, body = null) {
     return await response.json();
 }
 
-async function putAPI(url, body = null) {
+async function putTacAPI(url, body = null) {
     let response = await fetch(url, { method: "PUT", body: body });
     
     if (response.status != 200) {
@@ -107,8 +107,8 @@ async function putAPI(url, body = null) {
 }
 
 // Extra network preview thumbnails
-async function getExtraNetworkPreviewURL(filename, type) {
-    const previewJSON = await fetchAPI(`tacapi/v1/thumb-preview/${filename}?type=${type}`, true, true);
+async function getTacExtraNetworkPreviewURL(filename, type) {
+    const previewJSON = await fetchTacAPI(`tacapi/v1/thumb-preview/${filename}?type=${type}`, true, true);
     if (previewJSON?.url) {
         const properURL = `sd_extra_networks/thumb?filename=${previewJSON.url}`;
         if ((await fetch(properURL)).status == 200) {
@@ -237,24 +237,34 @@ function mapUseCountArray(useCounts, posAndNeg = false) {
 }
 // Call API endpoint to increase bias of tag in the database
 function increaseUseCount(tagName, type, negative = false) {
-    postAPI(`tacapi/v1/increase-use-count?tagname=${tagName}&ttype=${type}&neg=${negative}`);
+    postTacAPI(`tacapi/v1/increase-use-count?tagname=${tagName}&ttype=${type}&neg=${negative}`);
 }
 // Get use count of tag from the database
 async function getUseCount(tagName, type, negative = false) {
-    return (await fetchAPI(`tacapi/v1/get-use-count?tagname=${tagName}&ttype=${type}&neg=${negative}`, true, false))["result"];
+    const response = await fetchTacAPI(`tacapi/v1/get-use-count?tagname=${tagName}&ttype=${type}&neg=${negative}`, true, false);
+    // Guard for no db
+    if (response == null) return null;
+    // Result
+    return response["result"];
 }
 async function getUseCounts(tagNames, types, negative = false) {
     // While semantically weird, we have to use POST here for the body, as urls are limited in length
     const body = JSON.stringify({"tagNames": tagNames, "tagTypes": types, "neg": negative});
-    const rawArray = (await postAPI(`tacapi/v1/get-use-count-list`, body))["result"]
-    return mapUseCountArray(rawArray);
+    const response = await postTacAPI(`tacapi/v1/get-use-count-list`, body)
+    // Guard for no db
+    if (response == null) return null;
+    // Results
+    return mapUseCountArray(response["result"]);
 }
 async function getAllUseCounts() {
-    const rawArray = (await fetchAPI(`tacapi/v1/get-all-use-counts`))["result"];
-    return mapUseCountArray(rawArray, true);
+    const response = await fetchTacAPI(`tacapi/v1/get-all-use-counts`);
+    // Guard for no db
+    if (response == null) return null;
+    // Results
+    return mapUseCountArray(response["result"], true);
 }
 async function resetUseCount(tagName, type, resetPosCount, resetNegCount) {
-    await putAPI(`tacapi/v1/reset-use-count?tagname=${tagName}&ttype=${type}&pos=${resetPosCount}&neg=${resetNegCount}`);
+    await putTacAPI(`tacapi/v1/reset-use-count?tagname=${tagName}&ttype=${type}&pos=${resetPosCount}&neg=${resetNegCount}`);
 }
 
 function createTagUsageTable(tagCounts) {

javascript/ext_loras.js

@@ -50,7 +50,7 @@ async function load() {
 async function sanitize(tagType, text) {
     if (tagType === ResultType.lora) {
         let multiplier = TAC_CFG.extraNetworksDefaultMultiplier;
-        let info = await fetchAPI(`tacapi/v1/lora-info/${text}`)
+        let info = await fetchTacAPI(`tacapi/v1/lora-info/${text}`)
         if (info && info["preferred weight"]) {
             multiplier = info["preferred weight"];
         }

javascript/ext_lycos.js

@@ -50,7 +50,7 @@ async function load() {
 async function sanitize(tagType, text) {
     if (tagType === ResultType.lyco) {
         let multiplier = TAC_CFG.extraNetworksDefaultMultiplier;
-        let info = await fetchAPI(`tacapi/v1/lyco-info/${text}`)
+        let info = await fetchTacAPI(`tacapi/v1/lyco-info/${text}`)
         if (info && info["preferred weight"]) {
             multiplier = info["preferred weight"];
         }

javascript/ext_wildcards.js

@@ -1,14 +1,14 @@
 // Regex
-const WC_REGEX = /\b__([^,]+)__([^, ]*)\b/g;
+const WC_REGEX = new RegExp(/__([^,]+)__([^, ]*)/g);
 
 // Trigger conditions
-const WC_TRIGGER = () => TAC_CFG.useWildcards && [...tagword.matchAll(WC_REGEX)].length > 0;
-const WC_FILE_TRIGGER = () => TAC_CFG.useWildcards && (tagword.startsWith("__") && !tagword.endsWith("__") || tagword === "__");
+const WC_TRIGGER = () => TAC_CFG.useWildcards && [...tagword.matchAll(new RegExp(WC_REGEX.source.replaceAll("__", escapeRegExp(TAC_CFG.wcWrap)), "g"))].length > 0;
+const WC_FILE_TRIGGER = () => TAC_CFG.useWildcards && (tagword.startsWith(TAC_CFG.wcWrap) && !tagword.endsWith(TAC_CFG.wcWrap) || tagword === TAC_CFG.wcWrap);
 
 class WildcardParser extends BaseTagParser {
     async parse() {
         // Show wildcards from a file with that name
-        let wcMatch = [...tagword.matchAll(WC_REGEX)]
+        let wcMatch = [...tagword.matchAll(new RegExp(WC_REGEX.source.replaceAll("__", escapeRegExp(TAC_CFG.wcWrap)), "g"))];
         let wcFile = wcMatch[0][1];
         let wcWord = wcMatch[0][2];
 
@@ -38,7 +38,7 @@ class WildcardParser extends BaseTagParser {
                 }
                 wildcards = wildcards.concat(getDescendantProp(yamlWildcards[basePath], fileName));
             } else {
-                const fileContent = (await fetchAPI(`tacapi/v1/wildcard-contents?basepath=${basePath}&filename=${fileName}.txt`, false))
+                const fileContent = (await fetchTacAPI(`tacapi/v1/wildcard-contents?basepath=${basePath}&filename=${fileName}.txt`, false))
                     .split("\n")
                     .filter(x => x.trim().length > 0 && !x.startsWith('#'));  // Remove empty lines and comments
                 wildcards = wildcards.concat(fileContent);
@@ -64,8 +64,8 @@ class WildcardFileParser extends BaseTagParser {
     parse() {
         // Show available wildcard files
         let tempResults = [];
-        if (tagword !== "__") {
-            let lmb = (x) => x[1].toLowerCase().includes(tagword.replace("__", ""))
+        if (tagword !== TAC_CFG.wcWrap) {
+            let lmb = (x) => x[1].toLowerCase().includes(tagword.replace(TAC_CFG.wcWrap, ""))
             tempResults = wildcardFiles.filter(lmb).concat(wildcardExtFiles.filter(lmb)) // Filter by tagword
         } else {
             tempResults = wildcardFiles.concat(wildcardExtFiles);
@@ -151,7 +151,7 @@ async function load() {
 
 function sanitize(tagType, text) {
     if (tagType === ResultType.wildcardFile || tagType === ResultType.yamlWildcard) {
-        return `__${text}__`;
+        return `${TAC_CFG.wcWrap}${text}${TAC_CFG.wcWrap}`;
     } else if (tagType === ResultType.wildcardTag) {
         return text;
     }

javascript/tagAutocomplete.js

@@ -234,6 +234,7 @@ async function syncOptions() {
         useStyleVars: opts["tac_useStyleVars"],
         // Insertion related settings
         replaceUnderscores: opts["tac_replaceUnderscores"],
+        replaceUnderscoresExclusionList: opts["tac_undersocreReplacementExclusionList"],
         escapeParentheses: opts["tac_escapeParentheses"],
         appendComma: opts["tac_appendComma"],
         appendSpace: opts["tac_appendSpace"],
@@ -241,6 +242,7 @@ async function syncOptions() {
         wildcardCompletionMode: opts["tac_wildcardCompletionMode"],
         modelKeywordCompletion: opts["tac_modelKeywordCompletion"],
         modelKeywordLocation: opts["tac_modelKeywordLocation"],
+        wcWrap: opts["dp_parser_wildcard_wrap"] || "__", // to support custom wrapper chars set by dp_parser
         // Alias settings
         alias: {
             searchByAlias: opts["tac_alias.searchByAlias"],
@@ -413,7 +415,7 @@ const COMPLETED_WILDCARD_REGEX = /__[^\s,_][^\t\n\r,_]*[^\s,_]__[^\s,_]*/g;
 const STYLE_VAR_REGEX = /\$\(?[^$|\[\],\s]*\)?/g;
 const NORMAL_TAG_REGEX = /[^\s,|<>\[\]:]+_\([^\s,|<>\[\]:]*\)?|[^\s,|<>():\[\]]+|</g;
 const RUBY_TAG_REGEX = /[\w\d<][\w\d' \-?!/$%]{2,}>?/g;
-const TAG_REGEX = new RegExp(`${POINTY_REGEX.source}|${COMPLETED_WILDCARD_REGEX.source}|${STYLE_VAR_REGEX.source}|${NORMAL_TAG_REGEX.source}`, "g");
+const TAG_REGEX = () => { return new RegExp(`${POINTY_REGEX.source}|${COMPLETED_WILDCARD_REGEX.source.replaceAll("__", escapeRegExp(TAC_CFG.wcWrap))}|${STYLE_VAR_REGEX.source}|${NORMAL_TAG_REGEX.source}`, "g"); }
 
 // On click, insert the tag into the prompt textbox with respect to the cursor position
 async function insertTextAtCursor(textArea, result, tagword, tabCompletedWithoutChoice = false) {
@@ -429,8 +431,12 @@ async function insertTextAtCursor(textArea, result, tagword, tabCompletedWithout
     if (sanitizeResults && sanitizeResults.length > 0) {
         sanitizedText = sanitizeResults[0];
     } else {
-        sanitizedText = TAC_CFG.replaceUnderscores ? text.replaceAll("_", " ") : text;
-
+        const excluded_tags = TAC_CFG.replaceUnderscoresExclusionList?.split(',').map(s => s.trim()) || [];
+        if (TAC_CFG.replaceUnderscores && !excluded_tags.includes(sanitizedText)) {
+            sanitizedText = text.replaceAll("_", " ")
+        } else {
+            sanitizedText = text;
+        }
         if (TAC_CFG.escapeParentheses && tagType === ResultType.tag) {
             sanitizedText = sanitizedText
                 .replaceAll("(", "\\(")
@@ -469,7 +475,7 @@ async function insertTextAtCursor(textArea, result, tagword, tabCompletedWithout
             // Don't cut off the __ at the end if it is already the full path
             if (firstDifference > 0 && firstDifference < longestResult) {
                 // +2 because the sanitized text already has the __ at the start but the matched text doesn't
-                sanitizedText = sanitizedText.substring(0, firstDifference + 2);
+                sanitizedText = sanitizedText.substring(0, firstDifference + TAC_CFG.wcWrap.length);
             } else if (firstDifference === 0) {
                 sanitizedText = tagword;
             }
@@ -484,7 +490,7 @@ async function insertTextAtCursor(textArea, result, tagword, tabCompletedWithout
             case ResultType.wildcardFile:
             case ResultType.yamlWildcard:
                 // We only want to update the frequency for a full wildcard, not partial paths
-                if (sanitizedText.endsWith("__"))
+                if (sanitizedText.endsWith(TAC_CFG.wcWrap))
                     name = text
                 break;
             case ResultType.chant:
@@ -552,7 +558,7 @@ async function insertTextAtCursor(textArea, result, tagword, tabCompletedWithout
         let keywords = null;
         // Check built-in activation words first
         if (tagType === ResultType.lora || tagType === ResultType.lyco) {
-            let info = await fetchAPI(`tacapi/v1/lora-info/${result.text}`)
+            let info = await fetchTacAPI(`tacapi/v1/lora-info/${result.text}`)
             if (info && info["activation text"]) {
                 keywords = info["activation text"];
             }
@@ -564,7 +570,7 @@ async function insertTextAtCursor(textArea, result, tagword, tabCompletedWithout
 
             // No match, try to find a sha256 match from the cache file
             if (!nameDict) {
-                const sha256 = await fetchAPI(`/tacapi/v1/lora-cached-hash/${result.text}`)
+                const sha256 = await fetchTacAPI(`/tacapi/v1/lora-cached-hash/${result.text}`)
                 if (sha256) {
                     nameDict = modelKeywordDict.get(sha256);
                 }
@@ -622,7 +628,7 @@ async function insertTextAtCursor(textArea, result, tagword, tabCompletedWithout
     // Update previous tags with the edited prompt to prevent re-searching the same term
     let weightedTags = [...newPrompt.matchAll(WEIGHT_REGEX)]
             .map(match => match[1]);
-    let tags = newPrompt.match(TAG_REGEX)
+    let tags = newPrompt.match(TAG_REGEX())
     if (weightedTags !== null) {
         tags = tags.filter(tag => !weightedTags.some(weighted => tag.includes(weighted)))
             .concat(weightedTags);
@@ -725,29 +731,39 @@ function addResultsToList(textArea, results, tagword, resetList) {
         }
 
         // Add wiki link if the setting is enabled and a supported tag set loaded
-        if (TAC_CFG.showWikiLinks
-            && (result.type === ResultType.tag)
-            && (tagFileName.toLowerCase().startsWith("danbooru") || tagFileName.toLowerCase().startsWith("e621"))) {
+        if (
+            TAC_CFG.showWikiLinks &&
+            result.type === ResultType.tag &&
+            (tagFileName.toLowerCase().startsWith("danbooru") ||
+                tagFileName.toLowerCase().startsWith("e621"))
+        ) {
             let wikiLink = document.createElement("a");
             wikiLink.classList.add("acWikiLink");
             wikiLink.innerText = "?";
-            wikiLink.title = "Open external wiki page for this tag"
+            wikiLink.title = "Open external wiki page for this tag";
 
             let linkPart = displayText;
             // Only use alias result if it is one
-            if (displayText.includes("➝"))
-                linkPart = displayText.split(" ➝ ")[1];
+            if (displayText.includes("➝")) linkPart = displayText.split(" ➝ ")[1];
 
             // Remove any trailing translations
             if (linkPart.includes("[")) {
-                linkPart = linkPart.split("[")[0]
+                linkPart = linkPart.split("[")[0];
             }
 
             linkPart = encodeURIComponent(linkPart);
 
             // Set link based on selected file
             let tagFileNameLower = tagFileName.toLowerCase();
-            if (tagFileNameLower.startsWith("danbooru")) {
+            if (tagFileNameLower.startsWith("danbooru_e621_merged")) {
+                // Use danbooru for categories 0-5, e621 for 6+
+                // Based on the merged categories from https://github.com/DraconicDragon/dbr-e621-lists-archive/tree/main/tag-lists/danbooru_e621_merged
+                // Danbooru is also the fallback if result.category is not set
+                wikiLink.href =
+                    result.category && result.category >= 6
+                        ? `https://e621.net/wiki_pages/${linkPart}`
+                        : `https://danbooru.donmai.us/wiki_pages/${linkPart}`;
+            } else if (tagFileNameLower.startsWith("danbooru")) {
                 wikiLink.href = `https://danbooru.donmai.us/wiki_pages/${linkPart}`;
             } else if (tagFileNameLower.startsWith("e621")) {
                 wikiLink.href = `https://e621.net/wiki_pages/${linkPart}`;
@@ -818,7 +834,7 @@ function addResultsToList(textArea, results, tagword, resetList) {
         // Check if it's a negative prompt
         let isNegative = textAreaId.includes("n");
 
-        // Add listener
+        // Add click listener
         li.addEventListener("click", (e) => {
             if (e.ctrlKey || e.metaKey) {
                 resetUseCount(result.text, result.type, !isNegative, isNegative);
@@ -827,6 +843,38 @@ function addResultsToList(textArea, results, tagword, resetList) {
                 insertTextAtCursor(textArea, result, tagword);
             }
         });
+        // Add delayed hover listener for extra network previews
+        if (
+            TAC_CFG.showExtraNetworkPreviews &&
+            [
+                ResultType.embedding,
+                ResultType.hypernetwork,
+                ResultType.lora,
+                ResultType.lyco,
+            ].includes(result.type)
+        ) {
+            li.addEventListener("mouseover", async () => {
+                const me = this;
+                let hoverTimeout;
+
+                hoverTimeout = setTimeout(async () => {
+                    // If the tag we hover over is already selected, do nothing
+                    if (selectedTag && selectedTag === i) return;
+
+                    oldSelectedTag = selectedTag;
+                    selectedTag = i;
+
+                    // Update selection without scrolling to the item (since we would
+                    // immediately trigger the next scroll as the items move under the cursor)
+                    updateSelectionStyle(textArea, selectedTag, oldSelectedTag, false);
+                }, 400);
+                // Reset delay timer if we leave the item
+                me.addEventListener("mouseout", () => {
+                    clearTimeout(hoverTimeout);
+                });
+            });
+        }
+
         // Add element to list
         resultsList.appendChild(li);
     }
@@ -839,7 +887,7 @@ function addResultsToList(textArea, results, tagword, resetList) {
     }
 }
 
-async function updateSelectionStyle(textArea, newIndex, oldIndex) {
+async function updateSelectionStyle(textArea, newIndex, oldIndex, scroll = true) {
     let textAreaId = getTextAreaIdentifier(textArea);
     let resultDiv = gradioApp().querySelector('.autocompleteResults' + textAreaId);
     let resultsList = resultDiv.querySelector('ul');
@@ -854,40 +902,25 @@ async function updateSelectionStyle(textArea, newIndex, oldIndex) {
         let selected = items[newIndex];
         selected.classList.add('selected');
 
-         // Set scrolltop to selected item
-        resultDiv.scrollTop = selected.offsetTop - resultDiv.offsetTop;
+        // Set scrolltop to selected item
+        if (scroll) resultDiv.scrollTop = selected.offsetTop - resultDiv.offsetTop;
     }
 
     // Show preview if enabled and the selected type supports it
     if (newIndex !== null) {
-        let selected = items[newIndex];
-        let previewTypes = ["v1 Embedding", "v2 Embedding", "Hypernetwork", "Lora", "Lyco"];
-        let selectedType = selected.querySelector(".acMetaText").innerText;
-        let selectedFilename = selected.querySelector(".acListItem").innerText;
+        let selectedResult = results[newIndex];
+        let selectedType = selectedResult.type;
+        // These types support previews (others could technically too, but are not native to the webui gallery)
+        let previewTypes = [ResultType.embedding, ResultType.hypernetwork, ResultType.lora, ResultType.lyco];
 
         let previewDiv = gradioApp().querySelector(`.autocompleteParent${textAreaId} .sideInfo`);
 
         if (TAC_CFG.showExtraNetworkPreviews && previewTypes.includes(selectedType)) {
-            let shorthandType = "";
-            switch (selectedType) {
-                case "v1 Embedding":
-                case "v2 Embedding":
-                    shorthandType = "embed";
-                    break;
-                case "Hypernetwork":
-                    shorthandType = "hyper";
-                    break;
-                case "Lora":
-                    shorthandType = "lora";
-                    break;
-                case "Lyco":
-                    shorthandType = "lyco";
-                    break;
-            }
-
             let img = previewDiv.querySelector("img");
-
-            let url = await getExtraNetworkPreviewURL(selectedFilename, shorthandType);
+            // String representation of our type enum
+            const typeString = Object.keys(ResultType)[selectedType - 1].toLowerCase();
+            // Get image from API
+            let url = await getTacExtraNetworkPreviewURL(selectedResult.text, typeString);
             if (url) {
                 img.src = url;
                 previewDiv.style.display = "block";
@@ -1055,7 +1088,7 @@ async function autocomplete(textArea, prompt, fixedTag = null) {
         // We also match for the weighting format (e.g. "tag:1.0") here, and combine the two to get the full tag word set
         let weightedTags = [...prompt.matchAll(WEIGHT_REGEX)]
             .map(match => match[1]);
-        let tags = prompt.match(TAG_REGEX)
+        let tags = prompt.match(TAG_REGEX())
         if (weightedTags !== null && tags !== null) {
             tags = tags.filter(tag => !weightedTags.some(weighted => tag.includes(weighted) && !tag.startsWith("<[") && !tag.startsWith("$(")))
                 .concat(weightedTags);
@@ -1201,7 +1234,7 @@ async function autocomplete(textArea, prompt, fixedTag = null) {
 
         // Request use counts from the DB
         const names = TAC_CFG.frequencyIncludeAlias ? tagNames.concat(aliasNames) : tagNames;
-        const counts = await getUseCounts(names, types, isNegative);
+        const counts = await getUseCounts(names, types, isNegative) || [];
 
         // Pre-calculate weights to prevent duplicate work
         const resultBiasMap = new Map();
@@ -1361,7 +1394,7 @@ async function refreshTacTempFiles(api = false) {
     }
     
     if (api) {
-        await postAPI("tacapi/v1/refresh-temp-files");
+        await postTacAPI("tacapi/v1/refresh-temp-files");
         await reload();
     } else {
         setTimeout(async () => {
@@ -1371,7 +1404,7 @@ async function refreshTacTempFiles(api = false) {
 }
 
 async function refreshEmbeddings() {
-    await postAPI("tacapi/v1/refresh-embeddings", null);
+    await postTacAPI("tacapi/v1/refresh-embeddings", null);
     embeddings = [];
     await processQueue(QUEUE_FILE_LOAD, null);
     console.log("TAC: Refreshed embeddings");
@@ -1465,9 +1498,16 @@ async function setup() {
     gradioApp().querySelector("#refresh_tac_refreshTempFiles")?.addEventListener("click", refreshTacTempFiles);
 
     // Also add listener for external network refresh button (plus triggering python code)
-    ["#img2img_extra_refresh", "#txt2img_extra_refresh"].forEach(e => {
-        gradioApp().querySelector(e)?.addEventListener("click", ()=>{
-            refreshTacTempFiles(true);
+    let alreadyAdded = new Set();
+    ["#img2img_extra_refresh", "#txt2img_extra_refresh", ".extra-network-control--refresh"].forEach(e => {
+        const elems = gradioApp().querySelectorAll(e);
+        elems.forEach(elem => {
+            if (!elem || alreadyAdded.has(elem)) return;
+
+            alreadyAdded.add(elem);
+            elem.addEventListener("click", ()=>{
+                refreshTacTempFiles(true);
+            });
         });
     })
 

scripts/tag_autocomplete_helper.py

@@ -5,14 +5,16 @@ import glob
 import importlib
 import json
 import sqlite3
+import sys
 import urllib.parse
+from asyncio import sleep
 from pathlib import Path
 
 import gradio as gr
 import yaml
 from fastapi import FastAPI
-from fastapi.responses import Response, FileResponse, JSONResponse
-from modules import script_callbacks, sd_hijack, shared, hashes
+from fastapi.responses import FileResponse, JSONResponse, Response
+from modules import hashes, script_callbacks, sd_hijack, sd_models, shared
 from pydantic import BaseModel
 
 from scripts.model_keyword_support import (get_lora_simple_hash,
@@ -21,7 +23,14 @@ from scripts.model_keyword_support import (get_lora_simple_hash,
 from scripts.shared_paths import *
 
 try:
-    import scripts.tag_frequency_db as tdb
+    try:
+        from scripts import tag_frequency_db as tdb
+    except ModuleNotFoundError:
+        from inspect import currentframe, getframeinfo
+        filename = getframeinfo(currentframe()).filename
+        parent = Path(filename).resolve().parent
+        sys.path.append(str(parent))
+        import tag_frequency_db as tdb
 
     # Ensure the db dependency is reloaded on script reload
     importlib.reload(tdb)
@@ -33,9 +42,32 @@ except (ImportError, ValueError, sqlite3.Error) as e:
     print(f"Tag Autocomplete: Tag frequency database error - \"{e}\"")
     db = None
 
+def get_embed_db(sd_model=None):
+    """Returns the embedding database, if available."""
+    try:
+        return sd_hijack.model_hijack.embedding_db
+    except Exception:
+        try: # sd next with diffusers backend
+            sdnext_model = sd_model if sd_model is not None else shared.sd_model
+            return sdnext_model.embedding_db
+        except Exception:
+            try: # forge webui
+                forge_model = sd_model if sd_model is not None else sd_models.model_data.get_sd_model()
+                if type(forge_model).__name__ == "FakeInitialModel":
+                    return None
+                else:
+                    processer = getattr(forge_model, "text_processing_engine", getattr(forge_model, "text_processing_engine_l"))
+                    return processer.embeddings
+            except Exception:
+                return None
+
 # Attempt to get embedding load function, using the same call as api.
 try:
-    load_textual_inversion_embeddings = sd_hijack.model_hijack.embedding_db.load_textual_inversion_embeddings
+    embed_db = get_embed_db()
+    if embed_db is not None:
+        load_textual_inversion_embeddings = embed_db.load_textual_inversion_embeddings
+    else:
+        load_textual_inversion_embeddings = lambda *args, **kwargs: None
 except Exception as e: # Not supported.
     load_textual_inversion_embeddings = lambda *args, **kwargs: None
     print("Tag Autocomplete: Cannot reload embeddings instantly:", e)
@@ -43,8 +75,8 @@ except Exception as e: # Not supported.
 # Sorting functions for extra networks / embeddings stuff
 sort_criteria = {
     "Name": lambda path, name, subpath: name.lower() if subpath else path.stem.lower(),
-    "Date Modified (newest first)": lambda path, name, subpath: path.stat().st_mtime,
-    "Date Modified (oldest first)": lambda path, name, subpath: path.stat().st_mtime
+    "Date Modified (newest first)": lambda path, name, subpath: path.stat().st_mtime if path.exists() else name.lower(),
+    "Date Modified (oldest first)": lambda path, name, subpath: path.stat().st_mtime if path.exists() else name.lower()
 }
 
 def sort_models(model_list, sort_method = None, name_has_subpath = False):
@@ -102,7 +134,11 @@ def is_umi_format(data):
     """Returns True if the YAML file is in UMI format."""
     issue_found = False
     for item in data:
-        if not (data[item] and 'Tags' in data[item] and isinstance(data[item]['Tags'], list)):
+        try:
+            if not (data[item] and 'Tags' in data[item] and isinstance(data[item]['Tags'], list)):
+                issue_found = True
+                break
+        except:
             issue_found = True
             break
     return not issue_found
@@ -124,9 +160,12 @@ def parse_dynamic_prompt_format(yaml_wildcards, data, path):
             elif not (isinstance(value, list) and all(isinstance(v, str) for v in value)):
                 del d[key]
 
-    recurse_dict(data)
-    # Add to yaml_wildcards
-    yaml_wildcards[path.name] = data
+    try:
+        recurse_dict(data)
+        # Add to yaml_wildcards
+        yaml_wildcards[path.name] = data
+    except:
+        return
 
 
 def get_yaml_wildcards():
@@ -151,9 +190,13 @@ def get_yaml_wildcards():
                         parse_dynamic_prompt_format(yaml_wildcards, data, path)
                 else:
                     print('No data found in ' + path.name)
-        except (yaml.YAMLError, UnicodeDecodeError) as e:
+        except (yaml.YAMLError, UnicodeDecodeError, AttributeError, TypeError) as e:
+            # YAML file not in wildcard format or couldn't be read
             print(f'Issue in parsing YAML file {path.name}: {e}')
             continue
+        except Exception as e:
+            # Something else went wrong, just skip
+            continue
 
     # Sort by count
     umi_sorted = sorted(umi_tags.items(), key=lambda item: item[1], reverse=True)
@@ -182,35 +225,45 @@ def get_embeddings(sd_model):
     results = []
 
     try:
-        # The sd_model embedding_db reference only exists in sd.next with diffusers backend
-        try:
-            loaded_sdnext = sd_model.embedding_db.word_embeddings
-            skipped_sdnext = sd_model.embedding_db.skipped_embeddings
-        except (NameError, AttributeError):
-            loaded_sdnext = {}
-            skipped_sdnext = {}
+        embed_db = get_embed_db(sd_model)
+        # Re-register callback if needed
+        global load_textual_inversion_embeddings
+        if embed_db is not None and load_textual_inversion_embeddings != embed_db.load_textual_inversion_embeddings:
+            load_textual_inversion_embeddings = embed_db.load_textual_inversion_embeddings
         
-        # Get embedding dict from sd_hijack to separate v1/v2 embeddings
-        loaded = sd_hijack.model_hijack.embedding_db.word_embeddings
-        skipped = sd_hijack.model_hijack.embedding_db.skipped_embeddings
-        loaded = loaded | loaded_sdnext
-        skipped = skipped | skipped_sdnext
+        loaded = embed_db.word_embeddings
+        skipped = embed_db.skipped_embeddings
 
         # Add embeddings to the correct list
-        for key, emb in (loaded | skipped).items():
-            if emb.filename is None:
-                continue
-
-            if emb.shape is None:
-                emb_unknown.append((Path(emb.filename), Path(emb.filename).relative_to(EMB_PATH).as_posix(), ""))
-            elif emb.shape == V1_SHAPE:
-                emb_v1.append((Path(emb.filename), Path(emb.filename).relative_to(EMB_PATH).as_posix(), "v1"))
-            elif emb.shape == V2_SHAPE:
-                emb_v2.append((Path(emb.filename), Path(emb.filename).relative_to(EMB_PATH).as_posix(), "v2"))
-            elif emb.shape == VXL_SHAPE:
-                emb_vXL.append((Path(emb.filename), Path(emb.filename).relative_to(EMB_PATH).as_posix(), "vXL"))
+        for key, emb in (skipped | loaded).items():
+            filename = getattr(emb, "filename", None)
+            
+            if filename is None:
+                if emb.shape is None:
+                    emb_unknown.append((Path(key), key, ""))
+                elif emb.shape == V1_SHAPE:
+                    emb_v1.append((Path(key), key, "v1"))
+                elif emb.shape == V2_SHAPE:
+                    emb_v2.append((Path(key), key, "v2"))
+                elif emb.shape == VXL_SHAPE:
+                    emb_vXL.append((Path(key), key, "vXL"))
+                else:
+                    emb_unknown.append((Path(key), key, ""))
+            
             else:
-                emb_unknown.append((Path(emb.filename), Path(emb.filename).relative_to(EMB_PATH).as_posix(), ""))
+                if emb.filename is None:
+                    continue
+
+                if emb.shape is None:
+                    emb_unknown.append((Path(emb.filename), Path(emb.filename).relative_to(EMB_PATH).as_posix(), ""))
+                elif emb.shape == V1_SHAPE:
+                    emb_v1.append((Path(emb.filename), Path(emb.filename).relative_to(EMB_PATH).as_posix(), "v1"))
+                elif emb.shape == V2_SHAPE:
+                    emb_v2.append((Path(emb.filename), Path(emb.filename).relative_to(EMB_PATH).as_posix(), "v2"))
+                elif emb.shape == VXL_SHAPE:
+                    emb_vXL.append((Path(emb.filename), Path(emb.filename).relative_to(EMB_PATH).as_posix(), "vXL"))
+                else:
+                    emb_unknown.append((Path(emb.filename), Path(emb.filename).relative_to(EMB_PATH).as_posix(), ""))
 
         results = sort_models(emb_v1) + sort_models(emb_v2) + sort_models(emb_vXL) + sort_models(emb_unknown)
     except AttributeError:
@@ -281,7 +334,7 @@ try:
     import sys
     from modules import extensions
     sys.path.append(Path(extensions.extensions_builtin_dir).joinpath("Lora").as_posix())
-    import lora # pyright: ignore [reportMissingImports]
+    import lora  # pyright: ignore [reportMissingImports]
 
     def _get_lora():
         return [
@@ -422,8 +475,11 @@ def refresh_embeddings(force: bool, *args, **kwargs):
         # Fix for SD.Next infinite refresh loop due to gradio not updating after model load on demand.
         # This will just skip embedding loading if no model is loaded yet (or there really are no embeddings).
         # Try catch is just for safety incase sd_hijack access fails for some reason.
-        loaded = sd_hijack.model_hijack.embedding_db.word_embeddings
-        skipped = sd_hijack.model_hijack.embedding_db.skipped_embeddings
+        embed_db = get_embed_db()
+        if embed_db is None:
+            return
+        loaded = embed_db.word_embeddings
+        skipped = embed_db.skipped_embeddings
         if len((loaded | skipped)) > 0:
             load_textual_inversion_embeddings(force_reload=force)
             get_embeddings(None)
@@ -436,7 +492,8 @@ def refresh_temp_files(*args, **kwargs):
     if skip_wildcard_refresh:
         WILDCARD_EXT_PATHS = find_ext_wildcard_paths()
     write_temp_files(skip_wildcard_refresh)
-    refresh_embeddings(force=True)
+    force_embed_refresh = getattr(shared.opts, "tac_forceRefreshEmbeddings", False)
+    refresh_embeddings(force=force_embed_refresh)
 
 def write_style_names(*args, **kwargs):
     styles = get_style_names()
@@ -533,6 +590,7 @@ def on_ui_settings():
         "tac_wildcardExclusionList": shared.OptionInfo("", "Wildcard folder exclusion list").info("Add folder names that shouldn't be searched for wildcards, separated by comma.").needs_restart(),
         "tac_skipWildcardRefresh": shared.OptionInfo(False, "Don't re-scan for wildcard files when pressing the extra networks refresh button").info("Useful to prevent hanging if you use a very large wildcard collection."),
         "tac_useEmbeddings": shared.OptionInfo(True, "Search for embeddings"),
+        "tac_forceRefreshEmbeddings": shared.OptionInfo(False, "Force refresh embeddings when pressing the extra networks refresh button").info("Turn this on if you have issues with new embeddings not registering correctly in TAC. Warning: Seems to cause reloading issues in gradio for some users."),
         "tac_includeEmbeddingsInNormalResults": shared.OptionInfo(False, "Include embeddings in normal tag results").info("The 'JumpTo...' keybinds (End & Home key by default) will select the first non-embedding result of their direction on the first press for quick navigation in longer lists."),
         "tac_useHypernetworks": shared.OptionInfo(True, "Search for hypernetworks"),
         "tac_useLoras": shared.OptionInfo(True, "Search for Loras"),
@@ -551,6 +609,7 @@ def on_ui_settings():
         "tac_frequencyIncludeAlias": shared.OptionInfo(False, "Frequency sorting matches aliases for frequent tags").info("Tag frequency will be increased for the main tag even if an alias is used for completion. This option can be used to override the default behavior of alias results being ignored for frequency sorting."),
         # Insertion related settings
         "tac_replaceUnderscores": shared.OptionInfo(True, "Replace underscores with spaces on insertion"),
+        "tac_undersocreReplacementExclusionList": shared.OptionInfo("0_0,(o)_(o),+_+,+_-,._.,<o>_<o>,<|>_<|>,=_=,>_<,3_3,6_9,>_o,@_@,^_^,o_o,u_u,x_x,|_|,||_||", "Underscore replacement exclusion list").info("Add tags that shouldn't have underscores replaced with spaces, separated by comma."),
         "tac_escapeParentheses": shared.OptionInfo(True, "Escape parentheses on insertion"),
         "tac_appendComma": shared.OptionInfo(True, "Append comma on tag autocompletion"),
         "tac_appendSpace": shared.OptionInfo(True, "Append space on tag autocompletion").info("will append after comma if the above is enabled"),
@@ -627,6 +686,23 @@ def on_ui_settings():
         "9": ["#df3647", "#8e1c2b"],
         "10": ["#c98f2b", "#7b470e"],
         "11": ["#e87ebe", "#a83583"]
+    },
+    "danbooru_e621_merged": {
+        "-1": ["red", "maroon"],
+        "0": ["lightblue", "dodgerblue"],
+        "1": ["indianred", "firebrick"],
+        "3": ["violet", "darkorchid"],
+        "4": ["lightgreen", "darkgreen"],
+        "5": ["orange", "darkorange"],
+        "6": ["red", "maroon"],
+        "7": ["lightblue", "dodgerblue"],
+        "8": ["gold", "goldenrod"],
+        "9": ["gold", "goldenrod"],
+        "10": ["violet", "darkorchid"],
+        "11": ["lightgreen", "darkgreen"],
+        "12": ["tomato", "darksalmon"],
+        "14": ["whitesmoke", "black"],
+        "15": ["seagreen", "darkseagreen"]
     }
 }\
 """
@@ -688,6 +764,7 @@ def api_tac(_: gr.Blocks, app: FastAPI):
 
     @app.post("/tacapi/v1/refresh-temp-files")
     async def api_refresh_temp_files():
+        await sleep(0) # might help with refresh blocking gradio
         refresh_temp_files()
 
     @app.post("/tacapi/v1/refresh-embeddings")
@@ -719,9 +796,9 @@ def api_tac(_: gr.Blocks, app: FastAPI):
             return LORA_PATH
         elif type == "lyco":
             return LYCO_PATH
-        elif type == "hyper":
+        elif type == "hypernetwork":
             return HYP_PATH
-        elif type == "embed":
+        elif type == "embedding":
             return EMB_PATH
         else:
             return None
@@ -802,7 +879,10 @@ def api_tac(_: gr.Blocks, app: FastAPI):
         date_limit = getattr(shared.opts, "tac_frequencyMaxAge", 30)
         date_limit = date_limit if date_limit > 0 else None
 
-        count_list = list(db.get_tag_counts(body.tagNames, body.tagTypes, body.neg, date_limit))
+        if db:
+            count_list = list(db.get_tag_counts(body.tagNames, body.tagTypes, body.neg, date_limit))
+        else:
+            count_list = None
     
         # If a limit is set, return at max the top n results by count
         if count_list and len(count_list):
@@ -820,5 +900,5 @@ def api_tac(_: gr.Blocks, app: FastAPI):
     @app.get("/tacapi/v1/get-all-use-counts")
     async def get_all_tag_counts():
         return db_request(lambda: db.get_all_tags(), get=True)
-        
+
 script_callbacks.on_app_started(api_tac)

scripts/tag_frequency_db.py

@@ -78,6 +78,7 @@ class TagFrequencyDb:
         )
 
     def __get_version(self):
+        db_version = None
         with transaction() as cursor:
             cursor.execute(
                 """

tags/demo-chants.json

@@ -28,5 +28,17 @@
         "terms": "Water, Magic, Fancy",
         "content": "(extremely detailed CG unity 8k wallpaper), (masterpiece), (best quality), (ultra-detailed), (best illustration),(best shadow), (an extremely delicate and beautiful), classic, dynamic angle, floating, fine detail, Depth of field, classic, (painting), (sketch), (bloom), (shine), glinting stars,\n\na girl, solo, bare shoulders, flat chest, diamond and glaring eyes, beautiful detailed cold face, very long blue and sliver hair, floating black feathers, wavy hair, extremely delicate and beautiful girls, beautiful detailed eyes, glowing eyes,\n\nriver, (forest),palace, (fairyland,feather,flowers, nature),(sunlight),Hazy fog, mist",
         "color": 5
+    },
+    {
+        "name": "Pony-Positive",
+        "terms": "Pony,Score,Positive,Quality",
+        "content": "score_9, score_8_up, score_7_up, score_6_up, source_anime, source_furry, source_pony, source_cartoon",
+        "color": 1
+    },
+    {
+        "name": "Pony-Negative",
+        "terms": "Pony,Score,Negative,Quality",
+        "content": "score_1, score_2, score_3, score_4, score_5, source_anime, source_furry, source_pony, source_cartoon",
+        "color": 3
     }
 ]