feat: Bump version to 1.4.1

Merge Dev

.env-cmdrc.json

@@ -0,0 +1,5 @@
+{
+  "test": {
+    "NODE_OPTIONS": "--experimental-vm-modules"
+  }
+}

README.md

@@ -19,7 +19,6 @@
     - Natural tag insertion that considers cursor position and existing text.
 - **:art:Design**: Supports both light and dark themes of ComfyUI.
 - **:pencil:User CSV**: Allows users to add their own CSV files for autocomplete suggestions.
-- **Zero Dependencies**: All input assistance processing works in the browser without external libraries.
 
 ## Installation
 
@@ -42,6 +41,7 @@ When you type in a text input area, tags that partially match the text are displ
 - Tags are color-coded by category. The color-coding rules are the same as Danbooru.
 - Tags that have already been entered are displayed grayed out.
 - You can display Danbooru and e621 tags at the same time. You can also change the priority from the settings.
+- Supports autocomplete for Lora and Embedding inputs. You can enable/disable this feature in the settings.
 
 ## Related Tags
 
@@ -133,6 +133,8 @@ When the browser is reloaded, you can check the list of loaded CSV files in the
 
 - **Enable Autocomplete**: Enable/disable the autocomplete feature.
 - **Max suggestions**: Maximum number of autocomplete suggestions to display.
+- **Enable Loras and Embeddings**: Display Lora and Embedding in the suggestions.
+- **Use Fast Search**: Switch autocomplete suggestions search to fast processing (see [About Fast Search for Autocomplete](#about-fast-search-for-autocomplete) for details).
 
 ### Related Tags
 
@@ -172,6 +174,31 @@ You can skip the check process during ComfyUI startup by following these steps:
 - The check process will not be performed until the value of `check_updates_on_startup` is changed back to `true` or the `version` is switched.
 - Even when `check_updates_on_startup` is `false`, manual checking is still possible by pressing the `Check CSV updates` button in the Autocomplete Plus settings.
 
+## More details on how it works
+
+### About Fast Search for Autocomplete
+
+In `v1.3.0`, Added a fast search feature functionality to autocomplete. By enabling this function in the settings screen, tag search processing during text input operates faster, improving responsiveness.  
+While fast operation can be expected in any scenario, I particularly recommend **enabling** it in the following use cases:
+
+- When the loaded CSV files contain a large number of tags or aliases. This is especially useful when the total number of tags exceeds **100,000**.
+- When using natural language instead of comma-separated tags in prompt input.
+
+**Browser startup behavior**
+
+Fast search requires tag index building and is not available immediately after browser startup. The conventional search process is used until building is complete.  
+As of `v1.3.0`, The notification when building is completed is displayed only in the browser's developer tools. This is planned to be improved in future versions.
+
+For example, when index building for approximately 220,000 tags is completed, the following log is recorded:
+
+```
+[Autocomplete-Plus] Building 221787 index for danbooru took 9398.70ms.
+```
+
+> [!NOTE]
+> - Index building occurs in the background even when fast search is disabled in settings
+> - Fast search uses the full-text search library [nextapps-de/flexsearch](https://github.com/nextapps-de/flexsearch)
+
 ## Known Issues
 
 ### Performance
@@ -186,7 +213,9 @@ You can skip the check process during ComfyUI startup by following these steps:
 
 ## Credits
 
-- [ComfyUI-Custom-Node](https://github.com/pythongosssss/ComfyUI-Custom-Scripts)
+- [pythongosssss/ComfyUI-Custom-Node](https://github.com/pythongosssss/ComfyUI-Custom-Scripts)
   - Referenced for implementing the autocomplete function.
 - [DominikDoom/a1111-sd-webui-tagcomplete](https://github.com/DominikDoom/a1111-sd-webui-tagcomplete)
-  - Referenced for autocomplete function and CSV specifications.
+  - Referenced for autocomplete function and CSV specifications.
+- [nextapps-de/flexsearch](https://github.com/nextapps-de/flexsearch)
+  - Used to implement fast tag search processing for autocomplete.

docs/README_jp.md

@@ -17,7 +17,6 @@
     - カーソル位置や既存のテキストを考慮した自然なタグ挿入
 - **:art:デザイン**: ComfyUIのライトテーマとダークテーマの両方に対応
 - **:pencil:ユーザーCSV**: ユーザーが用意した CSV をオートコンプリート候補に追加可能
-- **依存ライブラリゼロ**: 外部ライブラリを使用せず、すべての入力支援処理がブラウザで動作
 
 ## インストール
 
@@ -40,6 +39,7 @@
 - タグのカテゴリ毎に色分けされます。色分けのルールは Danbooru と同じです
 - 入力済みのタグはグレーアウトで表示されます
 - Danbooruとe621のタグを同時に表示出来ます。設定から優先順位を変更できます
+- LoraとEmbeddingの入力補完に対応しています。設定から有効・無効を切り替えられます
 
 ## 関連タグ
 
@@ -130,7 +130,9 @@ worst_quality,5,9999999,
 ### オートコンプリート
 
 - **Enable Autocomplete**: オートコンプリート機能の有効化/無効化
-- **Max suggestions**: オートコンプリート候補の最大表示件数
+- **Max Suggestions**: オートコンプリート候補の最大表示件数
+- **Enable Loras and Embeddings**: LoraとEmbeddingを候補に表示する
+- **Use Fast Search**: オートコンプリート候補の検索を高速な処理に切り替える（詳細は [オートコンプリートの高速検索について](#オートコンプリートの高速検索について) を確認してください)
 
 ### 関連タグ
 
@@ -170,6 +172,30 @@ worst_quality,5,9999999,
 - `check_updates_on_startup` の値を再び `true` にするか、 `version` が切り替わるまでチェック処理は行われなくなります
 - `check_updates_on_startup` が `false` でも、Autocompelte Plusの設定から `Check CSV updates` のボタンを押す事で手動チェックが可能です
 
+## 動作に関する詳細
+
+## オートコンプリートの高速検索について
+
+`v1.3.0` にて、オートコンプリートにタグの検索を高速化する機能を追加しました。設定画面から有効にする事でテキスト入力時のタグ検索処理が高速に動作し、応答性が改善されます。  
+どのような場面でも高速な動作が期待できますが、特に以下のユースケースで **有効** にすることをお勧めします。
+
+- 読み込む CSV ファイルに大量のタグやエイリアスが含まれている場合。タグの合計が **10万件** を超える場合は特に有用です
+- プロンプト入力でタグのカンマ区切りの代わりに自然言語を使う場合
+
+**ブラウザ起動時の動作**
+
+高速検索はタグのインデックス構築が必要なため、ブラウザ起動直後は利用できません。構築が完了するまでは従来の検索処理で動作します。  
+`v1.3.0` 時点では構築が完了したタイミングはブラウザーの開発ツールにのみが表示されます。これは将来のバージョンで改善予定です。
+
+例として、約22万件のタグのインデックス構築が完了した際は以下のようなログが記録されます。
+```
+[Autocomplete-Plus] Building 221787 index for danbooru took 9398.70ms.
+```
+
+> [!NOTE]
+> - インデックス構築は設定から高速検索を無効にしてもバックグラウンドで行われます
+> - 高速検索の実現に全文検索ライブラリの [nextapps-de/flexsearch](https://github.com/nextapps-de/flexsearch) を使用しています 
+
 ## 既知の問題
 
 ### パフォーマンス
@@ -184,7 +210,9 @@ worst_quality,5,9999999,
 
 ## クレジット
 
-- [ComfyUI-Custom-Node](https://github.com/pythongosssss/ComfyUI-Custom-Scripts)
+- [pythongosssss/ComfyUI-Custom-Node](https://github.com/pythongosssss/ComfyUI-Custom-Scripts)
   - オートコンプリート機能の実装にあたり参考にしました
 - [DominikDoom/a1111-sd-webui-tagcomplete](https://github.com/DominikDoom/a1111-sd-webui-tagcomplete)
   - オートコンプリートの主要な機能や CSV の仕様で参考にしました
+- [nextapps-de/flexsearch](https://github.com/nextapps-de/flexsearch)
+  - オートコンプリートの高速なタグ検索処理の実装に利用させてもらいました

modules/api.py

@@ -1,7 +1,10 @@
-import os
 import json
+import os
+
+import folder_paths
 import server
 from aiohttp import web
+
 from . import downloader as dl
 
 # Get the absolute path to the 'data' directory
@@ -227,3 +230,21 @@ async def get_last_check_time(_request):
     except (IOError, json.JSONDecodeError) as e:
         print(f"[Autocomplete-Plus] Error reading csv_meta.json: {e}")
         return web.json_response({"last_check_time": None, "error": str(e)}, status=500)
+
+
+@server.PromptServer.instance.routes.get("/autocomplete-plus/embeddings")
+async def get_embeddings(request):
+    """
+    Returns a list of embedding files.
+    """
+    embeddings = folder_paths.get_filename_list("embeddings")
+    return web.json_response(list(map(lambda a: os.path.splitext(a)[0], embeddings)))
+
+
+@server.PromptServer.instance.routes.get("/autocomplete-plus/loras")
+async def get_loras(request):
+    """
+    Returns a list of lora files.
+    """
+    loras = folder_paths.get_filename_list("loras")
+    return web.json_response(list(map(lambda a: os.path.splitext(a)[0], loras)))

modules/downloader.py

@@ -235,16 +235,7 @@ class Downloader:
 
     def _check_new_csv_from_hf_dataset(self, dataset_meta: dict, now_utc: datetime, force_check: bool = False):
         """Checks HuggingFace for file updates and updates metadata."""
-        perform_hf_check = True
+        perform_hf_check = force_check
-        if not force_check and dataset_meta.get("last_remote_check_timestamp"):
-            try:
-                last_check_dt = datetime.fromisoformat(dataset_meta["last_remote_check_timestamp"])
-                if now_utc - last_check_dt < timedelta(days=7):
-                    perform_hf_check = False
-            except (ValueError, KeyError, TypeError):
-                print(
-                    "[Autocomplete-Plus] Invalid or missing timestamp for last_remote_check_timestamp. Will perform remote check."
-                )
 
         if perform_hf_check:
             huggingface_dataset_id = dataset_meta["hf_dataset_id"]
@@ -303,15 +294,16 @@ class Downloader:
             return f"File {file_name} is missing or empty locally."
 
         # Check if the last modified date on HuggingFace is newer than the last download date
-        try:
+        # Temporarily comment out until changes to remote files can be detected
-            last_download_dt = datetime.fromisoformat(file_meta_entry["last_download"])
+        # try:
-            hf_modified_dt = datetime.fromisoformat(file_meta_entry["last_modified_on_hf"])
+        #     last_download_dt = datetime.fromisoformat(file_meta_entry["last_download"])
-            if hf_modified_dt > last_download_dt:
+        #     hf_modified_dt = datetime.fromisoformat(file_meta_entry["last_modified_on_hf"])
-                return f"Remote file {file_name} is newer (HF: {last_download_dt}, Local Download: {hf_modified_dt})."
+        #     if hf_modified_dt > last_download_dt:
-        except (ValueError, TypeError):
+        #         return f"Remote file {file_name} is newer (HF: {hf_modified_dt}, Local Download: {last_download_dt})."
-            file_meta_entry["last_download"] = None
+        # except (ValueError, TypeError):
-            file_meta_entry["last_modified_on_hf"] = None
+        #     file_meta_entry["last_download"] = None
-            return f"Invalid timestamp format for {file_name}. Forcing download to ensure integrity."
+        #     file_meta_entry["last_modified_on_hf"] = None
+        #     return f"Invalid timestamp format for {file_name}. Forcing download to ensure integrity."
 
         # If the file is missing or empty, but the last download timestamp exists, we need to retry.
         if not check_file_valid(local_file_path) and file_meta_entry.get("last_download") is not None:

package-lock.json

@@ -8,6 +8,7 @@
         "@babel/core": "^7.27.1",
         "@babel/preset-env": "^7.27.2",
         "babel-jest": "^29.7.0",
+        "env-cmd": "^10.1.0",
         "jest": "^29.7.0",
         "stylelint": "^16.19.1",
         "stylelint-config-idiomatic-order": "^10.0.0",
@@ -3018,6 +3019,16 @@
       "dev": true,
       "license": "MIT"
     },
+    "node_modules/commander": {
+      "version": "4.1.1",
+      "resolved": "https://registry.npmjs.org/commander/-/commander-4.1.1.tgz",
+      "integrity": "sha512-NOKm8xhkzAjzFx8B2v5OAHT+u5pRQc2UCa2Vq9jYL/31o2wi9mxBA7LIFs3sV5VSC49z6pEhfbMULvShKj26WA==",
+      "dev": true,
+      "license": "MIT",
+      "engines": {
+        "node": ">= 6"
+      }
+    },
     "node_modules/concat-map": {
       "version": "0.0.1",
       "resolved": "https://registry.npmjs.org/concat-map/-/concat-map-0.0.1.tgz",
@@ -3266,6 +3277,23 @@
       "dev": true,
       "license": "MIT"
     },
+    "node_modules/env-cmd": {
+      "version": "10.1.0",
+      "resolved": "https://registry.npmjs.org/env-cmd/-/env-cmd-10.1.0.tgz",
+      "integrity": "sha512-mMdWTT9XKN7yNth/6N6g2GuKuJTsKMDHlQFUDacb/heQRRWOTIZ42t1rMHnQu4jYxU1ajdTeJM+9eEETlqToMA==",
+      "dev": true,
+      "license": "MIT",
+      "dependencies": {
+        "commander": "^4.0.0",
+        "cross-spawn": "^7.0.0"
+      },
+      "bin": {
+        "env-cmd": "bin/env-cmd.js"
+      },
+      "engines": {
+        "node": ">=8.0.0"
+      }
+    },
     "node_modules/env-paths": {
       "version": "2.2.1",
       "resolved": "https://registry.npmjs.org/env-paths/-/env-paths-2.2.1.tgz",

package.json

@@ -1,12 +1,13 @@
 {
   "type": "module",
   "scripts": {
-    "test": "jest"
+    "test": "env-cmd -e test -- jest"
   },
   "devDependencies": {
     "@babel/core": "^7.27.1",
     "@babel/preset-env": "^7.27.2",
     "babel-jest": "^29.7.0",
+    "env-cmd": "^10.1.0",
     "jest": "^29.7.0",
     "stylelint": "^16.19.1",
     "stylelint-config-idiomatic-order": "^10.0.0",

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-autocomplete-plus"
 description = "Autocomplete and Related Tag display for ComfyUI"
-version = "1.2.1"
+version = "1.4.1"
 license = {file = "LICENSE"}
 dependencies = ["",]
 

tests/js/flexsearch.test.js

@@ -0,0 +1,387 @@
+
+import {
+    createFlexSearchDocument,
+    createFlexSearchDocumentForModel,
+    __test__
+} from "../../web/js/searchengine.js";
+
+const { createTagEncoder, createCJKEncoder, createModelEncoder } = __test__;
+
+function parseCSVLine(line) {
+    const result = [];
+    let current = '';
+    let inQuotes = false;
+
+    for (let i = 0; i < line.length; i++) {
+        const char = line[i];
+
+        if (char === '"') {
+            if (inQuotes && i + 1 < line.length && line[i + 1] === '"') {
+                current += '"';
+                i++;
+            } else {
+                inQuotes = !inQuotes;
+            }
+        } else if (char === ',' && !inQuotes) {
+            result.push(current);
+            current = '';
+        } else {
+            current += char;
+        }
+    }
+
+    result.push(current);
+
+    return result;
+}
+
+describe('FlexSearch Integration', () => {
+
+    const commonCSV = `
+1girl,0,6008644,"1girls,sole_female"
+highres,5,5256195,"high_res,high_resolution,hires"
+solo,0,5000954,"alone,female_solo,single,solo_female,solo_in_panel"
+long_hair,0,4350743,"/lh,longhair,very_long_hair"
+one_two_three,0,29389,
+`;
+
+    const cjkAliasCSV = `
+blue_hair,0,676176,"青髪,青い髪,水色髪"
+red_hair,0,413261,"赤髪,紅髪,红发,빨강머리,빨간머리"
+smile,0,2294308,"笑い,スマイル,笑顔,笑顏,守りたい、この笑顔,笑,笑容,微笑み,微笑,微笑む,미소,守りたいこの笑顔"
+gloves,0,1105296,"手袋,裸手袋,手袋コキ,てぶくろ,장갑,手套"
+dragon_girl,0,37930,"竜娘,ドラゴン娘,龍娘,龙娘,メスドラ,辰娘"
+double_bun,0,103538,"お団子頭,お団子"
+sanshoku_dango,0,2061,"三色団子,三色团子,花見団子,花见团子"
+`;
+
+    const specialCharCSV = `
+:d,0,436700,
+>:),0,11041,
+year:1999,0,1999,
+d.d.,0,1999,
+copyright_(series),2,1298,"copyright,コピーライト (シリーズ),コピーライト名,コピーライト,著作"
+__wildcard__,0,0,
+`;
+
+    const ModelCSV = `
+<lora:my_lora1>,0,0,
+<lora:日本語Lora_v1>,0,0,
+embedding: my_embedding,0,0,
+`;
+
+    const mockCSV = [
+        commonCSV, cjkAliasCSV, specialCharCSV
+    ].map(csv => csv.trim()).join('\n');
+
+    let mockTags, mockModelTags;
+
+    let tagEncoder, cjkEncoder, modelEncoder;
+    let document, modelDocument;
+
+    let performSearch = function (query, limit = 100) {
+        const ids1 = document.search(query, {
+            field: ["tag", "alias"],
+            limit: limit,
+            suggest: false,
+            merge: true,
+        }).map(r => r.id);
+
+        const result1 = mockTags.filter(tag => ids1.includes(tag.id)).map(tag => tag.tag);
+
+        const ids2 = modelDocument.search(query, {
+            field: ["tag", "alias"],
+            limit: limit,
+            suggest: false,
+            merge: true,
+        }).map(r => r.id);
+
+        const result2 = mockModelTags.filter(tag => ids2.includes(tag.id)).map(tag => tag.tag);
+
+        return [...result1, ...result2];
+    }
+
+    beforeEach(() => {
+        mockTags = mockCSV.split('\n').map((line, id) => {
+            const [tag, category, count, alias] = parseCSVLine(line);
+            return { id, tag, category: parseInt(category), count: parseInt(count), alias };
+        });
+
+        tagEncoder = createTagEncoder();
+        cjkEncoder = createCJKEncoder();
+
+        document = createFlexSearchDocument();
+
+        mockTags.forEach(data => document.add(data));
+
+        mockModelTags = ModelCSV.split('\n').map((line, id) => {
+            const [tag, category, count, alias] = parseCSVLine(line);
+            return { id, tag, category: parseInt(category), count: parseInt(count), alias };
+        });
+
+        modelEncoder = createModelEncoder();
+        modelDocument = createFlexSearchDocumentForModel();
+        mockModelTags.forEach(data => modelDocument.add(data));
+    });
+
+    describe('Encoder', () => {
+        test('should split underscore-separated tags', () => {
+            const encoded = tagEncoder.encode('sanshoku_dango');
+            expect(encoded).toEqual(['sanshoku', 'dango']);
+        });
+
+        test('should extract words from parentheses', () => {
+            const encoded = tagEncoder.encode('copyright_(series)');
+            expect(encoded).toEqual(['copyright', 'series']);
+        });
+        test('should preserve colon-separated special tags', () => {
+            const encoded = tagEncoder.encode('year:1234');
+            expect(encoded).toEqual(['year:1234']);
+        });
+        test('should preserve dot-separated tags', () => {
+            const encoded = tagEncoder.encode('d.d.');
+            expect(encoded).toEqual(['d.d.']);
+        });
+        test('should preserve double underscore wildcard tags', () => {
+            const encoded = tagEncoder.encode('__wildcard__');
+            expect(encoded).toEqual(['__wildcard__']);
+        });
+        test('should convert katakana to hiragana', () => {
+            const encoded = cjkEncoder.encode('ガーデン');
+            expect(encoded).toEqual(['がーでん']);
+        });
+        test('should remove trailing underscores when splitting', () => {
+            const encoded = tagEncoder.encode('one_two_');
+            expect(encoded).toEqual(['one', 'two']);
+        });
+        test('should properly encode embedding notation', () => {
+            let encoded = modelEncoder.encode('embedding:path/to/my_embed1');
+            expect(encoded).toEqual(['embedding:', 'path', 'to', 'my', 'embed1']);
+
+            expect(
+                modelEncoder.encode('embedding:path\\to\\my-embed1')
+            ).toEqual(['embedding:', 'path', 'to', 'my', 'embed1']);
+
+            expect(
+                modelEncoder.encode('embedding:path\\to\\this is my embed. my-negative01 (v1)__by me')
+            ).toEqual(['embedding:', 'path', 'to', 'this', 'is', 'my', 'embed', 'my', 'negative01', 'v1', 'by', 'me']);
+        });
+        test('should properly encode lora notation', () => {
+            expect(
+                modelEncoder.encode('<lora:path/to/my_lora1>')
+            ).toEqual(['lora:', 'path', 'to', 'my', 'lora1']);
+
+            expect(
+                modelEncoder.encode('<lora:path\\to\\my-lora1>')
+            ).toEqual(['lora:', 'path', 'to', 'my', 'lora1']);
+
+            expect(
+                modelEncoder.encode('<lora:path\\to\\this is my lora. my-style01 (v1)__by me>')
+            ).toEqual(['lora:', 'path', 'to', 'this', 'is', 'my', 'lora', 'my', 'style01', 'v1', 'by', 'me']);
+        });
+    });
+
+    describe('Basic Search', () => {
+        test('should find a tag by exact match', () => {
+            const results = performSearch('1girl');
+            expect(results.length).toBeGreaterThan(0);
+            expect(results).toContain('1girl');
+        });
+
+        test('should find a tag by partial match (substring)', () => {
+            const results = performSearch('blue');
+            expect(results.length).toBeGreaterThan(0);
+            expect(results).toContain('blue_hair');
+        });
+
+        test('should be case-insensitive', () => {
+            const results = performSearch('BLUE_HAIR');
+            expect(results.length).toBeGreaterThan(0);
+
+            expect(results).toContain('blue_hair');
+        });
+
+        test('should find a tag by backward', () => {
+            const results = performSearch('gon');
+            expect(results.length).toEqual(1);
+
+            expect(results).toContain('dragon_girl');
+        });
+
+        test('should find a tag for terms contain space', () => {
+            const results = performSearch('double ');
+            expect(results.length).toEqual(1);
+
+            expect(results).toContain('double_bun');
+        });
+
+        test('should find a tag for terms contain underscore', () => {
+            const results = performSearch('double_');
+            expect(results.length).toEqual(1);
+
+            expect(results).toContain('double_bun');
+        });
+    });
+
+    describe('Alias Search', () => {
+        test('should find a tag by its Japanese alias', () => {
+            const results = performSearch('髪');
+            expect(results.length).toBeGreaterThan(0);
+
+            expect(results).toContain('blue_hair');
+        });
+
+        test('should find a tag by one of its multiple aliases', () => {
+            const results = performSearch('笑顔');
+            expect(results.length).toBeGreaterThan(0);
+
+            expect(results).toContain('smile');
+        });
+
+        test('should find a tag by its partial Japanese alias', () => {
+            const results = performSearch('青い');
+            expect(results.length).toBeGreaterThan(0);
+
+            expect(results).toContain('blue_hair');
+        });
+
+        test('should find a tag by katakana', () => {
+            const results = performSearch('テブクロ');
+            expect(results.length).toEqual(1);
+
+            expect(results).toContain('gloves');
+        });
+
+        test('should find a tag by hiragana', () => {
+            const results = performSearch('すまいる');
+            expect(results.length).toEqual(1);
+
+            expect(results).toContain('smile');
+        });
+
+        test('should not find a tag by english alias substring', () => {
+            const results = performSearch('meg');
+            expect(results.length).toEqual(0);
+        });
+
+        test('should find a tag by japanese alias substring', () => {
+            const results = performSearch('団子');
+            expect(results.length).toEqual(2);
+
+            expect(results).toContain('sanshoku_dango');
+            expect(results).toContain('double_bun');
+        });
+    });
+
+    describe('Special Characters and Edge Cases', () => {
+        test('should find a tag with parentheses', () => {
+            const results = performSearch('copyright_(series)');
+            expect(results.length).toBeGreaterThan(0);
+
+            expect(results).toContain('copyright_(series)');
+        });
+
+        test('should find a tag by searching for content inside parentheses', () => {
+            const results = performSearch('series');
+            expect(results.length).toBeGreaterThan(0);
+
+            expect(results).toContain('copyright_(series)');
+        });
+
+        test('should find a tag by partial word', () => {
+            const results = performSearch('right');
+            expect(results.length).toBeGreaterThan(0);
+
+            expect(results).toContain('copyright_(series)');
+        });
+
+        test('should return an empty array for a non-existent tag', () => {
+            const results = performSearch('non_existent_tag_xyz');
+            expect(results).toEqual([]);
+        });
+
+        test('should match to special character only tag', () => {
+            const tag = '>:)';
+            const results = performSearch(tag);
+            expect(results.length).toEqual(1);
+
+            expect(results).toContain(tag);
+        });
+
+        test('should match to contain special character tag', () => {
+            const tag = ':d';
+            const results = performSearch(tag);
+            expect(results.length).toEqual(1);
+
+            expect(results).toContain(tag);
+        });
+
+        test('should match to contain special character tag2', () => {
+            const tag = 'year:1999';
+            const results = performSearch(tag);
+            expect(results.length).toEqual(1);
+
+            expect(results).toContain(tag);
+        });
+
+        test('should match to contain special character tag3', () => {
+            const tag = 'd.d.';
+            const results = performSearch(tag);
+            expect(results.length).toEqual(1);
+
+            expect(results).toContain(tag);
+        });
+
+        test('should match to wildcard tag', () => {
+            const tag = '__';
+            const results = performSearch(tag);
+            expect(results.length).toEqual(1);
+
+            expect(results).toContain('__wildcard__');
+        });
+
+        test('should match to lora tag', () => {
+            const tag = '<lora';
+            const results = performSearch(tag);
+            expect(results.length).toEqual(2);
+
+            expect(results).toContain("<lora:my_lora1>");
+            expect(results).toContain("<lora:日本語Lora_v1>");
+        });
+
+        test('should match to lora tag2', () => {
+            const tag = 'lora:';
+            const results = performSearch(tag);
+            expect(results.length).toEqual(2);
+
+            expect(results).toContain("<lora:my_lora1>");
+            expect(results).toContain("<lora:日本語Lora_v1>");
+        });
+
+        test('should match to lora that contain CJK characters', () => {
+            const word = 'lora: 日本語';
+            const results = performSearch(word);
+            expect(results.length).toEqual(1);
+
+            expect(results).toContain("<lora:日本語Lora_v1>");
+        });
+    });
+
+    describe('Search Options', () => {
+        test('should respect the limit option', () => {
+            const results = performSearch('hair', 1);
+
+            expect(results.length).toEqual(1);
+        });
+
+        test('should return all matches when limit is higher than results', () => {
+            const results = performSearch('hair', 5);
+            expect(results.length).toBeGreaterThan(0);
+
+            expect(results).toHaveLength(3);
+            expect(results).toContain('long_hair');
+            expect(results).toContain('blue_hair');
+            expect(results).toContain('red_hair');
+        });
+    });
+});

web/js/autocomplete.js

@@ -1,4 +1,5 @@
 import {
+    ModelTagSource,
     TagCategory,
     TagData,
     autoCompleteData,
@@ -9,6 +10,7 @@ import {
     hiraToKata,
     kataToHira,
     formatCountHumanReadable,
+    escapeHtml,
     isContainsLetterOrNumber,
     normalizeTagToInsert,
     normalizeTagToSearch,
@@ -79,22 +81,17 @@ function matchWord(target, queries) {
  * @returns {Array<TagData>} The list of matching candidates.
  */
 function searchCompletionCandidates(textareaElement) {
-    const startTime = performance.now(); // Record start time for performance measurement
 
     const ESCAPE_SEQUENCE = ["#", "/"]; // If the first string is that character, autocomplete will not be displayed.
     const partialTag = getCurrentPartialTag(textareaElement);
-    if (!partialTag || partialTag.length <= 0 || 
+    if (!partialTag || partialTag.length <= 0 ||
-        ESCAPE_SEQUENCE.some(seq => partialTag.startsWith(seq)) || 
+        ESCAPE_SEQUENCE.some(seq => partialTag.startsWith(seq)) ||
         isLongText(partialTag)) {
         return []; // No valid input for autocomplete
     }
 
-    const exactMatches = [];
-    const partialMatches = [];
-    const addedTags = new Set();
-
     // Generate Hiragana/Katakana variations if applicable
-    const queryVariations = new Set([partialTag, normalizeTagToSearch(partialTag)]);
+    const queryVariations = new Set([partialTag.toLowerCase(), normalizeTagToSearch(partialTag).toLowerCase()]);
     const kataQuery = hiraToKata(partialTag);
     if (kataQuery !== partialTag) {
         queryVariations.add(kataQuery);
@@ -104,6 +101,26 @@ function searchCompletionCandidates(textareaElement) {
         queryVariations.add(hiraQuery);
     }
 
+    if (settingValues.useFastSearch) {
+        return searchWithFlexSearch(partialTag, queryVariations);
+    } else {
+        return sequentialSearch(partialTag, queryVariations);
+    }
+}
+
+/**
+ * Search completion candidates using sequential search.
+ * @param {string} partialTag 
+ * @param {Set<string>} queryVariations 
+ * @returns 
+ */
+function sequentialSearch(partialTag, queryVariations) {
+    const startTime = performance.now();
+
+    const exactMatches = [];
+    const partialMatches = [];
+    const addedTags = new Set();
+
     const sources = getEnabledTagSourceInPriorityOrder();
     for (const source of sources) {
         // Search in sortedTags (already sorted by count)
@@ -113,15 +130,14 @@ function searchCompletionCandidates(textareaElement) {
             let matchedAlias = null;
 
             // Check primary tag against all variations for exact/partial match
-            const tagMatch = matchWord(tagData.tag, queryVariations);
+            const tagMatch = matchWord(tagData.tag.toLowerCase(), queryVariations);
             matched = tagMatch.matched;
             isExactMatch = tagMatch.isExactMatch;
 
             // If primary tag didn't match, check aliases against all variations
             if (!matched && tagData.alias && Array.isArray(tagData.alias) && tagData.alias.length > 0) {
                 for (const alias of tagData.alias) {
-                    const lowerAlias = alias.toLowerCase();
+                    const aliasMatch = matchWord(alias.toLowerCase(), queryVariations);
-                    const aliasMatch = matchWord(lowerAlias, queryVariations);
                     if (aliasMatch.matched) {
                         matched = true;
                         isExactMatch = aliasMatch.isExactMatch;
@@ -173,6 +189,69 @@ function searchCompletionCandidates(textareaElement) {
     return candidates;
 }
 
+/**
+ * Search completion candidates using FlexSearch for fast matching.
+ * @param {string} partialTag 
+ * @param {Set<string>} queryVariations 
+ * @returns 
+ */
+function searchWithFlexSearch(partialTag, queryVariations) {
+    const startTime = performance.now();
+
+    let mergedResult = [];
+    let totalSearchCount = 0;
+
+    const sources = getEnabledTagSourceInPriorityOrder();
+    for (const source of sources) {
+        if (!autoCompleteData[source].flexSearchDocument) continue;
+        if (mergedResult.length >= settingValues.maxSuggestions) break;
+
+        // Use the FlexSearch Document to search
+        // NOTE: The limit param is reflected separately for "tag" and "alias".
+        let searchResult = autoCompleteData[source].flexSearchDocument.search(partialTag, {
+            field: ["tag", "alias"],
+            limit: Math.min(settingValues.maxSuggestions * 10, 500),
+            merge: true,
+            suggest: false,
+            cache: true,
+        });
+
+        if (!searchResult || searchResult.length <= 0) continue;
+
+        // Sort results based on exact matches and counts
+        searchResult = searchResult
+            .map(r => autoCompleteData[source].sortedTags[r.id])
+            .sort((aTag, bTag) => {
+                if (matchWord(bTag.tag, queryVariations).isExactMatch) {
+                    return 999999999999;
+                }
+                if (matchWord(aTag.tag, queryVariations).isExactMatch) {
+                    return -999999999999;
+                }
+                if (bTag.alias && bTag.alias.some(alias => matchWord(alias, queryVariations).isExactMatch)) {
+                    return 999999999999;
+                }
+                if (aTag.alias && aTag.alias.some(alias => matchWord(alias, queryVariations).isExactMatch)) {
+                    return -999999999999;
+                }
+                return bTag.count - aTag.count;
+            });
+
+        // Merge results into the final array
+        mergedResult = mergedResult.concat(searchResult.slice(0, settingValues.maxSuggestions - mergedResult.length));
+
+        totalSearchCount += searchResult.length;
+    }
+
+    if (settingValues._logprocessingTime) {
+        const endTime = performance.now();
+        const duration = endTime - startTime;
+        console.debug(`[Autocomplete-Plus] Fast Search for "${partialTag}" took ${duration.toFixed(2)}ms.Found ${mergedResult.length} candidates within ${totalSearchCount} searches from flexsearch.`);
+    }
+
+    return mergedResult;
+}
+
 /**
  * Extracts the current tag being typed before the cursor.
  * @param {HTMLTextAreaElement} inputElement
@@ -221,9 +300,9 @@ function getCurrentPartialTag(inputElement) {
  * Inserts the selected tag into the textarea, replacing the partial tag,
  * making the change undoable.
  * @param {HTMLTextAreaElement} inputElement
- * @param {string} tagToInsert The raw tag string to insert.
+ * @param {TagData} tagDataToInsert The raw tag string to insert.
  */
-function insertTagToTextArea(inputElement, tagToInsert) {
+function insertTagToTextArea(inputElement, tagDataToInsert) {
     const text = inputElement.value;
     const cursorPos = inputElement.selectionStart;
 
@@ -231,7 +310,13 @@ function insertTagToTextArea(inputElement, tagToInsert) {
     const replaceStart = Math.min(cursorPos, tagStart);
     let replaceEnd = cursorPos;
 
-    const normalizedTag = normalizeTagToInsert(tagToInsert);
+    let normalizedTag;
+    if(Object.values(ModelTagSource).includes(tagDataToInsert.source)){
+        // If the tag is from a model tag source, don't want to normalize it
+        normalizedTag = tagDataToInsert.tag;
+    }else{
+        normalizedTag = normalizeTagToInsert(tagDataToInsert.tag);
+    }
 
     const currentTagAfterCursor = text.substring(cursorPos, tagEnd).trimEnd();
     if (normalizedTag.lastIndexOf(currentTagAfterCursor) !== -1) {
@@ -300,7 +385,7 @@ class AutocompleteUI {
         this.tagsList.addEventListener('mousedown', (e) => {
             const row = e.target.closest('.autocomplete-plus-item');
             if (row && row.dataset.tag) {
-                this.#insertTag(row.dataset.tag);
+                this.#insertTag(row.dataset);
                 e.preventDefault(); // Prevent focus loss from input
                 e.stopPropagation();
             }
@@ -365,10 +450,12 @@ class AutocompleteUI {
         this.#highlightItem();
     }
 
-    /** Selects the currently highlighted item */
+    /** Selects the currently highlighted item
+     * @returns {TagData|null} The selected tag data.
+     */
     getSelectedTag() {
         if (this.selectedIndex >= 0 && this.selectedIndex < this.candidates.length) {
-            return this.candidates[this.selectedIndex].tag;
+            return this.candidates[this.selectedIndex];
         }
 
         return null; // No valid selection
@@ -414,9 +501,10 @@ class AutocompleteUI {
         if (settingValues.tagSourceIconPosition == 'hidden') {
             tagName.textContent = tagData.tag;
         } else {
+            const escapedTag = escapeHtml(tagData.tag);
             tagName.innerHTML = settingValues.tagSourceIconPosition == 'left'
-                ? `${tagSourceIconHtml} ${tagData.tag}`
+                ? `${tagSourceIconHtml} ${escapedTag}`
-                : `${tagData.tag} ${tagSourceIconHtml}`;
+                : `${escapedTag} ${tagSourceIconHtml}`;
         }
 
         // grayout tag name if it already exists
@@ -557,10 +645,10 @@ class AutocompleteUI {
 
     /**
      * Handles the selection of an item
-     * @param {string} selectedTag The tag to insert.
+     * @param {TagData} selectedTag The tag to insert.
      */
     #insertTag(selectedTag) {
-        if (!this.target || !selectedTag || selectedTag.length <= 0) {
+        if (!this.target || !selectedTag) {
             this.hide();
             return;
         }
@@ -921,4 +1009,4 @@ export class AutocompleteEventHandler {
      */
     handleClick(event) {
     }
-}
+}

web/js/data.js

@@ -1,13 +1,20 @@
 import { settingValues, updateMaxTagLength } from "./settings.js";
+import { createFlexSearchDocument, createFlexSearchDocumentForModel } from "./searchengine.js";
 
 // --- Constants ---
 
-// Tag data sources
+// Tag sources for booru-like tag data.
 export const TagSource = {
     Danbooru: 'danbooru',
     E621: 'e621',
 }
 
+// Tag sources for model based tag data.
+export const ModelTagSource = {
+    Embeddings: 'embeddings',
+    Lora: 'lora'
+}
+
 export const TagCategory = {
     'danbooru': [
         'general',
@@ -27,6 +34,12 @@ export const TagCategory = {
         'invalid',
         'meta',
         'lore',
+    ],
+    'embeddings': [
+        'embeddings'
+    ],
+    'lora': [
+        'lora'
     ]
 }
 
@@ -39,19 +52,19 @@ export class TagData {
     /**
      * Create a tag data object
      * @param {string} tag - The tag name
-     * @param {string[]} [alias=[]] - Array of aliases for the tag
+     * @param {number} [category] - Category index of the tag
-     * @param {string} [category='general'] - Category of the tag
      * @param {number} [count=0] - Frequency count/popularity of the tag
-     * @param {string} [source=TagSources.Danbooru] - The source of the tag data
+     * @param {string[]} [alias=[]] - Array of aliases for the tag
+     * @param {string} [source=TagSource.Danbooru] - The source of the tag data
      */
-    constructor(tag, alias = [], category = 'general', count = 0, source = TagSource.Danbooru) {
+    constructor(tag, category, count = 0, alias = [], source = TagSource.Danbooru) {
         /** @type {string} */
         this.tag = tag;
 
         /** @type {string[]} */
         this.alias = alias;
 
-        /** @type {string} */
+        /** @type {number} */
         this.category = category;
 
         /** @type {number} */
@@ -63,6 +76,9 @@ export class TagData {
 
 class AutocompleteData {
     constructor() {
+        /** @type {Document} */
+        this.flexSearchDocument = null;
+
         /** @type {TagData[]} */
         this.sortedTags = [];
 
@@ -80,7 +96,6 @@ class AutocompleteData {
 
         // Progress of "base" csv loading
         this.baseLoadingProgress = {
-            // tags: 0,
             cooccurrence: 0
         };
     }
@@ -95,24 +110,32 @@ export const autoCompleteData = {};
 const TAGS_CSV_HEADER = 'tag,category,count,alias';
 const TAGS_CSV_HEADER_COLUMNS = TAGS_CSV_HEADER.split(',');
 const TAG_INDEX = TAGS_CSV_HEADER_COLUMNS.indexOf('tag');
-const ALIAS_INDEX = TAGS_CSV_HEADER_COLUMNS.indexOf('alias');
 const CATEGORY_INDEX = TAGS_CSV_HEADER_COLUMNS.indexOf('category');
 const COUNT_INDEX = TAGS_CSV_HEADER_COLUMNS.indexOf('count');
+const ALIAS_INDEX = TAGS_CSV_HEADER_COLUMNS.indexOf('alias');
 
 // --- Helder Functions ---
 
+
 /**
  * Get the available tag sources in priority order based on the current settings.
  * @returns {string[]} Array of available tag sources in priority order
  */
 export function getEnabledTagSourceInPriorityOrder() {
-    return Object.values(TagSource)
+    let enabledTagSources = Object.values(TagSource)
         .filter((s) => {
             return settingValues.tagSource === s || settingValues.tagSource === 'all';
         })
         .toSorted((a, b) => {
             return a === settingValues.primaryTagSource ? -1 : 1;
         });
+
+    // Append Loras and Embeddings if enabled
+    if (settingValues.enableModels) {
+        enabledTagSources = [...enabledTagSources, ...Object.values(ModelTagSource)];
+    }
+
+    return enabledTagSources;
 }
 
 // --- Data Loading Functions ---
@@ -156,7 +179,7 @@ async function loadTags(csvUrl, siteName) {
                 const aliases = aliasStr ? aliasStr.split(',').map(a => a.trim()).filter(a => a.length > 0) : [];
 
                 // Create a TagData instance instead of a plain object
-                const tagData = new TagData(tag, aliases, category, count, siteName);
+                const tagData = new TagData(tag, category, count, aliases, siteName);
 
                 updateMaxTagLength(tag.length);
 
@@ -189,6 +212,52 @@ async function loadTags(csvUrl, siteName) {
     }
 }
 
+/**
+ * Build FlexSearch index for the given site name.
+ * @param {string} siteName 
+ */
+async function buildFlexSearchIndex(siteName) {
+    try {
+        if (autoCompleteData[siteName].sortedTags.length === 0) {
+            return;
+        }
+
+        let document = null;
+        if (Object.values(TagSource).includes(siteName)) {
+            document = createFlexSearchDocument();
+        } else if (Object.values(ModelTagSource).includes(siteName)) {
+            document = createFlexSearchDocumentForModel();
+        } else {
+            throw new Error(`[Autocomplete-Plus] Invalid site name: ${siteName}`);
+        }
+
+        let startIdx = 0;
+        const startTime = performance.now();
+        function processChunkTasks() {
+            const chunkSize = 1000;
+            const end = Math.min(startIdx + chunkSize, autoCompleteData[siteName].sortedTags.length);
+            for (; startIdx < end; startIdx++) {
+                const tagData = autoCompleteData[siteName].sortedTags[startIdx];
+                document.add(startIdx, tagData);
+            }
+
+            if (startIdx < autoCompleteData[siteName].sortedTags.length) {
+                setTimeout(processChunkTasks, 0);
+                // console.log(`[Autocomplete-Plus] Current porcess: ${startIdx}`);
+            } else {
+                autoCompleteData[siteName].flexSearchDocument = document;
+
+                const endTime = performance.now();
+                const duration = endTime - startTime;
+                console.info(`[Autocomplete-Plus] Building ${autoCompleteData[siteName].sortedTags.length} index for ${siteName} took ${duration.toFixed(2)}ms.`);
+            }
+        }
+        processChunkTasks();
+    } catch (error) {
+        console.error(`[Autocomplete-Plus] Failed to building flexSearch index`, error);
+    }
+}
+
 /**
  * Loads co-occurrence data from a single CSV file.
  * @param {string} csvUrl - The URL of the CSV file to load.
@@ -299,7 +368,11 @@ function parseCSVLine(line) {
     return result;
 }
 
-export async function fetchCsvList() {
+/**
+ * Fetch the list of CSV files from the API endpoint
+ * @returns {Promise<void>}
+ */
+async function fetchCsvList() {
     try {
         const response = await fetch('/autocomplete-plus/csv');
         if (!response.ok) {
@@ -315,9 +388,8 @@ export async function fetchCsvList() {
 
 /**
  * Initializes the autocomplete data by fetching the list of CSV files and loading them.
- * This function is called when the extension is initialized.
  */
-export async function initializeData(csvListData, source) {
+async function initializeDataFromCSV(csvListData, source) {
     if (autoCompleteData.hasOwnProperty(source) === false) {
         autoCompleteData[source] = new AutocompleteData();
     }
@@ -376,12 +448,17 @@ export async function initializeData(csvListData, source) {
         // Now, execute all promise factories and wait for their completion.
         // The actual loading (fetch calls) will start when the factories are invoked here.
         await Promise.all([
-            Promise.all(tagsLoadPromiseFactories.map(factory => factory())).then(() => {
+            Promise.all(tagsLoadPromiseFactories.map(factory => factory()))
-                const endTime = performance.now();
+                .then(() => {
-                if (csvListData[source].base_tags) {
+                    // Build FlexSearch index after tags are loaded
-                    console.log(`[Autocomplete-Plus] "${source}" Tags loading complete in ${(endTime - startTime).toFixed(2)}ms`);
+                    return buildFlexSearchIndex(source);
-                }
+                })
-            }),
+                .then(() => {
+                    const endTime = performance.now();
+                    if (csvListData[source].base_tags) {
+                        console.log(`[Autocomplete-Plus] "${source}" Tags loading complete in ${(endTime - startTime).toFixed(2)}ms`);
+                    }
+                }),
             Promise.all(cooccurrenceLoadPromiseFactories.map(factory => factory())).then(() => {
                 const endTime = performance.now();
                 if (csvListData[source].base_cooccurrence) {
@@ -397,3 +474,88 @@ export async function initializeData(csvListData, source) {
         autoCompleteData[source].isInitializing = false;
     }
 }
+
+/**
+ * Load Embeddings data from the API endpoint
+ * @returns {Promise<void>}
+ */
+async function loadEmbeddings() {
+    try {
+        const response = await fetch('/autocomplete-plus/embeddings', { cache: "no-store" });
+        if (!response.ok) {
+            throw new Error(`HTTP error! status: ${response.status}`);
+        }
+        const embeddings = await response.json();
+        const source = ModelTagSource.Embeddings;
+
+        if (autoCompleteData.hasOwnProperty(source) === false) {
+            autoCompleteData[source] = new AutocompleteData();
+        }
+
+        embeddings.forEach(embedding => {
+            if (!autoCompleteData[source].tagMap.has(embedding)) {
+                const tagData = new TagData(`embedding:${embedding}`, 0, 0, [], source);
+                autoCompleteData[source].sortedTags.push(tagData);
+                autoCompleteData[source].tagMap.set(embedding, tagData);
+
+                updateMaxTagLength(embedding.length);
+            }
+        });
+
+        await buildFlexSearchIndex(ModelTagSource.Embeddings);
+
+        console.log(`[Autocomplete-Plus] Loaded ${embeddings.length} Embeddings`);
+    } catch (error) {
+        console.error(`[Autocomplete-Plus] Failed to fetch Embeddings data:`, error);
+    }
+}
+
+/**
+ * Load LoRA data from the API endpoint
+ * @returns {Promise<void>}
+ */
+async function loadLoras() {
+    try {
+        const response = await fetch('/autocomplete-plus/loras', { cache: "no-store" });
+        if (!response.ok) {
+            throw new Error(`HTTP error! status: ${response.status}`);
+        }
+        const loraNames = await response.json();
+        const source = ModelTagSource.Lora;
+
+        if (autoCompleteData.hasOwnProperty(source) === false) {
+            autoCompleteData[source] = new AutocompleteData();
+        }
+
+        loraNames.forEach(loraName => {
+            if (!autoCompleteData[source].tagMap.has(loraName)) {
+                const tagData = new TagData(`<lora:${loraName}>`, 0, 0, [], source);
+                autoCompleteData[source].sortedTags.push(tagData);
+                autoCompleteData[source].tagMap.set(loraName, tagData);
+
+                updateMaxTagLength(loraName.length);
+            }
+        });
+
+        await buildFlexSearchIndex(ModelTagSource.Lora);
+
+        console.log(`[Autocomplete-Plus] Loaded ${loraNames.length} LoRA models`);
+    } catch (error) {
+        console.error(`[Autocomplete-Plus] Failed to fetch LoRA data:`, error);
+    }
+}
+
+/**
+ * Load all data sources asynchronously.
+ */
+export async function loadDataAsync() {
+    return Promise.all([
+        fetchCsvList().then((csvList) => {
+            Object.values(TagSource).forEach((source) => {
+                initializeDataFromCSV(csvList, source);
+            });
+        }),
+        loadEmbeddings(),
+        loadLoras(),
+    ]);
+}

web/js/main.js

@@ -3,7 +3,7 @@ import { $el } from "/scripts/ui.js";
 import { ComfyWidgets } from "/scripts/widgets.js";
 import { settingValues } from "./settings.js";
 import { loadCSS } from "./utils.js";
-import { TagSource, fetchCsvList, initializeData } from "./data.js";
+import { TagSource, loadDataAsync } from "./data.js";
 import { AutocompleteEventHandler } from "./autocomplete.js";
 import { RelatedTagsEventHandler } from "./related-tags.js";
 
@@ -190,40 +190,41 @@ async function addExtraSettings() {
     }
 
     // Add extra setting for checking new CSV updates
-    app.ui.settings.addSetting({
+    // Note: Temporarily comment out until changes to remote files can be detected
-        id: id + ".check_new_csv",
+    // app.ui.settings.addSetting({
-        defaultValue: null,
+    //     id: id + ".check_new_csv",
-        name: "Check CSV updates",
+    //     defaultValue: null,
-        category: [name, "Misc", "Check new CSV"],
+    //     name: "Check CSV updates",
-        type: () => {
+    //     category: [name, "Misc", "Check new CSV"],
-            const lastCheckSpan = $el("span", {
+    //     type: () => {
-                textContent: lastCheckTimeText,
+    //         const lastCheckSpan = $el("span", {
-                className: "text-sm text-gray-500",
+    //             textContent: lastCheckTimeText,
-                style: {
+    //             className: "text-sm text-gray-500",
-                    marginRight: "16px"
+    //             style: {
-                }
+    //                 marginRight: "16px"
-            });
+    //             }
+    //         });
 
-            const checkButton = $el("button", {
+    //         const checkButton = $el("button", {
-                textContent: "Check now",
+    //             textContent: "Check now",
-                className: "p-button p-component p-button-primary",
+    //             className: "p-button p-component p-button-primary",
-                onclick: async () => {
+    //             onclick: async () => {
-                    await performUpdateCheck(checkButton, lastCheckSpan);
+    //                 await performUpdateCheck(checkButton, lastCheckSpan);
-                }
+    //             }
-            });
+    //         });
 
-            return $el("div", {
+    //         return $el("div", {
-                className: "flex-row items-center gap-2",
+    //             className: "flex-row items-center gap-2",
-            }, [
+    //         }, [
-                $el("div", {
+    //             $el("div", {
-                    className: "p-component",
+    //                 className: "p-component",
-                }, [
+    //             }, [
-                    lastCheckSpan,
+    //                 lastCheckSpan,
-                    checkButton,
+    //                 checkButton,
-                ]),
+    //             ]),
-            ]);
+    //         ]);
-        }
+    //     }
-    });
+    // });
 }
 
 /**
@@ -240,11 +241,7 @@ app.registerExtension({
         let rootPath = import.meta.url.replace("js/main.js", "");
         loadCSS(rootPath + "css/autocomplete-plus.css"); // Load CSS for autocomplete
 
-        fetchCsvList().then((csvList) => {
+        await loadDataAsync();
-            Object.values(TagSource).forEach((source) => {
-                initializeData(csvList, source);
-            });
-        });
     },
 
     // One the Settings Screen, displays reverse order in same category
@@ -286,6 +283,28 @@ app.registerExtension({
             }
         },
         // --- Autocomplete Settings ---
+        {
+            id: id + ".use_fast_search",
+            name: "Use Fast Search",
+            tooltip: "Tag search processing during text input operates faster, improving responsiveness",
+            type: "boolean",
+            defaultValue: false,
+            category: [name, "Autocompletion", "Use Fast Search"],
+            onChange: (newVal, oldVal) => {
+                settingValues.useFastSearch = newVal;
+            }
+        },
+        {
+            id: id + ".enable_models",
+            name: "Enable Loras and Embeddings",
+            tooltip: "Enable Lora and Embedding suggestions",
+            type: "boolean",
+            defaultValue: true,
+            category: [name, "Autocompletion", "Enable Loras and Embeddings"],
+            onChange: (newVal, oldVal) => {
+                settingValues.enableModels = newVal;
+            }
+        },
         {
             id: id + ".max_suggestions",
             name: "Max suggestions",

web/js/searchengine.js

@@ -0,0 +1,133 @@
+import { Charset, Encoder, Document } from './thirdparty/flexsearch.bundle.module.min.js'
+import { kataToHira } from './utils.js';
+
+/**
+ * Creates an encoder optimized for processing English tag names.
+ * Handles tag formatting like underscores and parentheses commonly used in Danbooru tags.
+ * @returns {Encoder} FlexSearch encoder for English tags
+ */
+function createTagEncoder() {
+    return new Encoder({
+        normalize: true,
+        dedupe: false,
+        numeric: false,
+        cache: true,
+        // filter: new Set(['and', 'to', 'be', 'on']),
+        replacer: [/(?<=[a-zA-Z\)])_$/, ''],  // Remove trailing underscores after letters/parentheses
+        split: /(?<=[a-zA-Z\)])_(?=[a-zA-Z\(])|\((?=[a-zA-Z])|(?<=[a-zA-Z\)])\)|[ \n]/  // Split on underscores between words, parentheses, spaces, and newlines
+    });
+}
+
+/**
+ * Creates an encoder optimized for processing CJK (Chinese, Japanese, Korean) characters.
+ * Uses exact character matching and converts katakana to hiragana for better Japanese search.
+ * @returns {Encoder} FlexSearch encoder for CJK text
+ */
+function createCJKEncoder() {
+    return new Encoder(Charset.Exact, {
+        dedupe: true,
+        numeric: true,
+        cache: true,
+        filter: new Set(['(', ')']),  // Filter out parentheses characters
+        finalize: (term) => {         // Convert katakana to hiragana for better Japanese matching
+            return term.map(str => kataToHira(str));
+        }
+    });
+}
+
+/**
+ * Creates an encoder optimized for processing Embedding or Lora notation.
+ * @returns {Encoder} FlexSearch encoder
+ */
+function createModelEncoder() {
+    return new Encoder({
+        normalize: true,
+        dedupe: false,
+        numeric: true,
+        cache: true,
+        prepare: function (str) {
+            return str.replace(/^<|>$/g, '').split(/(lora:|embedding:|[^\u0000-\u007f]+)/g).filter(Boolean).join(" ").trim();
+        },
+        split: /(?<=lora:.*|embedding:.*)[_./\(\)\-\s\\]+/
+    });
+}
+
+/**
+ * Creates a FlexSearch Document instance optimized for tag searching.
+ * Configures separate encoders for English tags and CJK aliases with appropriate tokenization.
+ * @returns {Document} Configured FlexSearch document for tag indexing
+ */
+export function createFlexSearchDocument() {
+    const tagEncoder = createTagEncoder();
+    const cjkEncoder = createCJKEncoder();
+
+    // Custom encoding function for alias field that handles mixed language content
+    const encodeAlias = function (word) {
+        return word.split(",")
+            .flatMap(str => {
+                if (/[^\u0000-\u007f]/.test(str)) {
+                    // Contains non-ASCII characters (CJK text)
+                    return cjkEncoder.encode(str);
+                } else {
+                    // ASCII characters only (English text)
+                    return tagEncoder.encode(str);
+                }
+            })
+            .filter(Boolean);
+    }
+
+    // Configure the FlexSearch document with optimized indexing settings
+    const document = new Document({
+        document: {
+            id: "id",
+            index: [
+                {
+                    field: "tag",
+                    tokenize: "bidirectional",  // Allow partial matching from both ends
+                    encoder: tagEncoder,        // Use tag-optimized encoder
+                },
+                {
+                    field: "alias",             // Index the alias field for multi-language support
+                    tokenize: "full",           // Full tokenization for complete alias matching
+                    encode: encodeAlias,        // Use custom multi-language encoding function
+                }
+            ]
+        }
+    });
+
+    return document;
+}
+
+/**
+ * Creates a FlexSearch Document instance optimized for lora or embedding searching.
+ * @returns {Document} Configured FlexSearch document
+ */
+export function createFlexSearchDocumentForModel() {
+    const modelEncoder = createModelEncoder();
+
+
+    // Configure the FlexSearch document with optimized indexing settings
+    // Note: alias field is not indexed for lora or embedding search
+    const document = new Document({
+        tokenize: "full",  // Allow partial matching from both ends
+        encoder: modelEncoder,
+        document: {
+            id: "id",
+            index: [
+                {
+                    field: "tag",
+
+                },
+                {
+                    field: "alias",
+                }
+            ]
+        }
+    });
+
+    return document;
+}
+
+// Export functions for testing when in test environment
+const isTestEnvironment = typeof process !== 'undefined' && process.env.NODE_ENV === 'test';
+export const __test__ = isTestEnvironment ? { createTagEncoder, createCJKEncoder, createModelEncoder } : undefined;

web/js/settings.js

@@ -7,6 +7,8 @@ export const settingValues = {
     // Autocomplete feature settings
     enabled: true,
     maxSuggestions: 10,
+    enableModels: true, // Enable Lora and Embedding suggestions
+    useFastSearch: false,
 
     // Related tags feature settings
     enableRelatedTags: true,

web/js/thirdparty/flexsearch.bundle.module.min.js

@@ -0,0 +1,106 @@
+/**!
+ * FlexSearch.js v0.8.200 (Bundle/Module)
+ * Author and Copyright: Thomas Wilkerling
+ * Licence: Apache-2.0
+ * Hosted by Nextapps GmbH
+ * https://github.com/nextapps-de/flexsearch
+ */
+var w;function H(a,c,b){const e=typeof b,d=typeof a;if("undefined"!==e){if("undefined"!==d){if(b){if("function"===d&&e===d)return function(h){return a(b(h))};c=a.constructor;if(c===b.constructor){if(c===Array)return b.concat(a);if(c===Map){var f=new Map(b);for(var g of a)f.set(g[0],g[1]);return f}if(c===Set){g=new Set(b);for(f of a.values())g.add(f);return g}}}return a}return b}return"undefined"===d?c:a}function aa(a,c){return"undefined"===typeof a?c:a}function I(){return Object.create(null)}
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+function kb(a,c){var b=a.split(".");"json"===b[b.length-1]&&b.pop();const e=2<b.length?b[0]:"";b=2<b.length?b[2]:b[1];if(this.worker&&e)return this.index.get(e).import(a);if(c){"string"===typeof c&&(c=JSON.parse(c));if(e)return this.index.get(e).import(b,c);switch(b){case "reg":this.fastupdate=!1;this.reg=qb(c,this.reg);for(let d=0,f;d<this.field.length;d++)f=this.index.get(this.field[d]),f.fastupdate=!1,f.reg=this.reg;if(this.worker){c=[];for(const d of this.index.values())c.push(d.import(a));return Promise.all(c)}break;
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+2>g?0:1),m,p,h-1,k-1),q=this.bidirectional&&t>f;xb(this,l,q?f:t,r,a,b,q?t:f)}}}}this.fastupdate||this.reg.add(a)}else c=""}this.db&&(c||this.commit_task.push({del:a}),this.S&&ub(this));return this};
+function xb(a,c,b,e,d,f,g){let h=g?a.ctx:a.map,k;if(!c[b]||g&&!(k=c[b])[g])if(g?(c=k||(c[b]=I()),c[g]=1,(k=h.get(g))?h=k:h.set(g,h=new Map)):c[b]=1,(k=h.get(b))?h=k:h.set(b,h=k=[]),h=h[e]||(h[e]=[]),!f||!h.includes(d)){if(h.length===2**31-1){c=new za(h);if(a.fastupdate)for(let m of a.reg.values())m.includes(h)&&(m[m.indexOf(h)]=c);k[e]=h=c}h.push(d);a.fastupdate&&((e=a.reg.get(d))?e.push(h):a.reg.set(d,[h]))}}
+function wb(a,c,b,e,d){return b&&1<a?c+(e||0)<=a?b+(d||0):(a-1)/(c+(e||0))*(b+(d||0))+1|0:0};V.prototype.search=function(a,c,b){b||(c||"object"!==typeof a?"object"===typeof c&&(b=c,c=0):(b=a,a=""));if(b&&b.cache)return b.cache=!1,a=this.searchCache(a,c,b),b.cache=!0,a;let e=[],d,f,g,h=0,k,m,l,n,u;b&&(a=b.query||a,c=b.limit||c,h=b.offset||0,f=b.context,g=b.suggest,u=(k=b.resolve)&&b.enrich,l=b.boost,n=b.resolution,m=this.db&&b.tag);"undefined"===typeof k&&(k=this.resolve);f=this.depth&&!1!==f;let p=this.encoder.encode(a,!f);d=p.length;c=c||(k?100:0);if(1===d)return yb.call(this,p[0],"",c,
+h,k,u,m);if(2===d&&f&&!g)return yb.call(this,p[1],p[0],c,h,k,u,m);let t=I(),r=0,q;f&&(q=p[0],r=1);n||0===n||(n=q?this.T:this.resolution);if(this.db){if(this.db.search&&(b=this.db.search(this,p,c,h,g,k,u,m),!1!==b))return b;const y=this;return async function(){for(let v,A;r<d;r++){if((A=p[r])&&!t[A]){t[A]=1;v=await zb(y,A,q,0,0,!1,!1);if(v=Ab(v,e,g,n)){e=v;break}q&&(g&&v&&e.length||(q=A))}g&&q&&r===d-1&&!e.length&&(n=y.resolution,q="",r=-1,t=I())}return Bb(e,n,c,h,g,l,k)}()}for(let y,v;r<d;r++){if((v=
+p[r])&&!t[v]){t[v]=1;y=zb(this,v,q,0,0,!1,!1);if(y=Ab(y,e,g,n)){e=y;break}q&&(g&&y&&e.length||(q=v))}g&&q&&r===d-1&&!e.length&&(n=this.resolution,q="",r=-1,t=I())}return Bb(e,n,c,h,g,l,k)};function Bb(a,c,b,e,d,f,g){let h=a.length,k=a;if(1<h)k=$a(a,c,b,e,d,f,g);else if(1===h)return g?Sa.call(null,a[0],b,e):new Y(a[0],this);return g?k:new Y(k,this)}
+function yb(a,c,b,e,d,f,g){a=zb(this,a,c,b,e,d,f,g);return this.db?a.then(function(h){return d?h||[]:new Y(h,this)}):a&&a.length?d?Sa.call(this,a,b,e):new Y(a,this):d?[]:new Y([],this)}function Ab(a,c,b,e){let d=[];if(a&&a.length){if(a.length<=e){c.push(a);return}for(let f=0,g;f<e;f++)if(g=a[f])d[f]=g;if(d.length){c.push(d);return}}if(!b)return d}
+function zb(a,c,b,e,d,f,g,h){let k;b&&(k=a.bidirectional&&c>b)&&(k=b,b=c,c=k);if(a.db)return a.db.get(c,b,e,d,f,g,h);a=b?(a=a.ctx.get(b))&&a.get(c):a.map.get(c);return a};function V(a,c){if(!this||this.constructor!==V)return new V(a);if(a){var b=M(a)?a:a.preset;b&&(a=Object.assign({},vb[b],a))}else a={};b=a.context;const e=!0===b?{depth:1}:b||{},d=M(a.encoder)?va[a.encoder]:a.encode||a.encoder||{};this.encoder=d.encode?d:"object"===typeof d?new la(d):{encode:d};this.resolution=a.resolution||9;this.tokenize=b=(b=a.tokenize)&&"default"!==b&&"exact"!==b&&b||"strict";this.depth="strict"===b&&e.depth||0;this.bidirectional=!1!==e.bidirectional;this.fastupdate=!!a.fastupdate;
+this.score=a.score||null;(b=a.keystore||0)&&(this.keystore=b);this.map=b?new S(b):new Map;this.ctx=b?new S(b):new Map;this.reg=c||(this.fastupdate?b?new S(b):new Map:b?new T(b):new Set);this.T=e.resolution||3;this.rtl=d.rtl||a.rtl||!1;this.cache=(b=a.cache||null)&&new R(b);this.resolve=!1!==a.resolve;if(b=a.db)this.db=this.mount(b);this.S=!1!==a.commit;this.commit_task=[];this.commit_timer=null;this.priority=a.priority||4}w=V.prototype;
+w.mount=function(a){this.commit_timer&&(clearTimeout(this.commit_timer),this.commit_timer=null);return a.mount(this)};w.commit=function(a,c){this.commit_timer&&(clearTimeout(this.commit_timer),this.commit_timer=null);return this.db.commit(this,a,c)};w.destroy=function(){this.commit_timer&&(clearTimeout(this.commit_timer),this.commit_timer=null);return this.db.destroy()};function ub(a){a.commit_timer||(a.commit_timer=setTimeout(function(){a.commit_timer=null;a.db.commit(a,void 0,void 0)},1))}
+w.clear=function(){this.map.clear();this.ctx.clear();this.reg.clear();this.cache&&this.cache.clear();this.db&&(this.commit_timer&&clearTimeout(this.commit_timer),this.commit_timer=null,this.commit_task=[{clear:!0}]);return this};w.append=function(a,c){return this.add(a,c,!0)};w.contain=function(a){return this.db?this.db.has(a):this.reg.has(a)};w.update=function(a,c){const b=this,e=this.remove(a);return e&&e.then?e.then(()=>b.add(a,c)):this.add(a,c)};
+w.cleanup=function(){if(!this.fastupdate)return this;tb(this.map);this.depth&&tb(this.ctx);return this};w.searchCache=ma;w.export=function(a,c,b=0,e=0){let d,f;switch(e){case 0:d="reg";f=pb(this.reg);break;case 1:d="cfg";f=null;break;case 2:d="map";f=lb(this.map,this.reg.size);break;case 3:d="ctx";f=nb(this.ctx,this.reg.size);break;default:return}return rb.call(this,a,c,d,f,b,e)};
+w.import=function(a,c){if(c)switch("string"===typeof c&&(c=JSON.parse(c)),a=a.split("."),"json"===a[a.length-1]&&a.pop(),3===a.length&&a.shift(),a=1<a.length?a[1]:a[0],a){case "reg":this.fastupdate=!1;this.reg=qb(c,this.reg);break;case "map":this.map=mb(c,this.map);break;case "ctx":this.ctx=ob(c,this.ctx)}};
+w.serialize=function(a=!0){let c="",b="",e="";if(this.reg.size){let f;for(var d of this.reg.keys())f||(f=typeof d),c+=(c?",":"")+("string"===f?'"'+d+'"':d);c="index.reg=new Set(["+c+"]);";b=sb(this.map,f);b="index.map=new Map(["+b+"]);";for(const g of this.ctx.entries()){d=g[0];let h=sb(g[1],f);h="new Map(["+h+"])";h='["'+d+'",'+h+"]";e+=(e?",":"")+h}e="index.ctx=new Map(["+e+"]);"}return a?"function inject(index){"+c+b+e+"}":c+b+e};Fa(V.prototype);const Cb="undefined"!==typeof window&&(window.indexedDB||window.mozIndexedDB||window.webkitIndexedDB||window.msIndexedDB),Db=["map","ctx","tag","reg","cfg"],Eb=I();
+function Fb(a,c={}){if(!this||this.constructor!==Fb)return new Fb(a,c);"object"===typeof a&&(c=a,a=a.name);a||console.info("Default storage space was used, because a name was not passed.");this.id="flexsearch"+(a?":"+a.toLowerCase().replace(/[^a-z0-9_\-]/g,""):"");this.field=c.field?c.field.toLowerCase().replace(/[^a-z0-9_\-]/g,""):"";this.type=c.type;this.fastupdate=this.support_tag_search=!1;this.db=null;this.h={}}w=Fb.prototype;w.mount=function(a){if(a.index)return a.mount(this);a.db=this;return this.open()};
+w.open=function(){if(this.db)return this.db;let a=this;navigator.storage&&navigator.storage.persist();Eb[a.id]||(Eb[a.id]=[]);Eb[a.id].push(a.field);const c=Cb.open(a.id,1);c.onupgradeneeded=function(){const b=a.db=this.result;for(let e=0,d;e<Db.length;e++){d=Db[e];for(let f=0,g;f<Eb[a.id].length;f++)g=Eb[a.id][f],b.objectStoreNames.contains(d+("reg"!==d?g?":"+g:"":""))||b.createObjectStore(d+("reg"!==d?g?":"+g:"":""))}};return a.db=Z(c,function(b){a.db=b;a.db.onversionchange=function(){a.close()}})};
+w.close=function(){this.db&&this.db.close();this.db=null};w.destroy=function(){const a=Cb.deleteDatabase(this.id);return Z(a)};w.clear=function(){const a=[];for(let b=0,e;b<Db.length;b++){e=Db[b];for(let d=0,f;d<Eb[this.id].length;d++)f=Eb[this.id][d],a.push(e+("reg"!==e?f?":"+f:"":""))}const c=this.db.transaction(a,"readwrite");for(let b=0;b<a.length;b++)c.objectStore(a[b]).clear();return Z(c)};
+w.get=function(a,c,b=0,e=0,d=!0,f=!1){a=this.db.transaction((c?"ctx":"map")+(this.field?":"+this.field:""),"readonly").objectStore((c?"ctx":"map")+(this.field?":"+this.field:"")).get(c?c+":"+a:a);const g=this;return Z(a).then(function(h){let k=[];if(!h||!h.length)return k;if(d){if(!b&&!e&&1===h.length)return h[0];for(let m=0,l;m<h.length;m++)if((l=h[m])&&l.length){if(e>=l.length){e-=l.length;continue}const n=b?e+Math.min(l.length-e,b):l.length;for(let u=e;u<n;u++)k.push(l[u]);e=0;if(k.length===b)break}return f?
+g.enrich(k):k}return h})};w.tag=function(a,c=0,b=0,e=!1){a=this.db.transaction("tag"+(this.field?":"+this.field:""),"readonly").objectStore("tag"+(this.field?":"+this.field:"")).get(a);const d=this;return Z(a).then(function(f){if(!f||!f.length||b>=f.length)return[];if(!c&&!b)return f;f=f.slice(b,b+c);return e?d.enrich(f):f})};
+w.enrich=function(a){"object"!==typeof a&&(a=[a]);const c=this.db.transaction("reg","readonly").objectStore("reg"),b=[];for(let e=0;e<a.length;e++)b[e]=Z(c.get(a[e]));return Promise.all(b).then(function(e){for(let d=0;d<e.length;d++)e[d]={id:a[d],doc:e[d]?JSON.parse(e[d]):null};return e})};w.has=function(a){a=this.db.transaction("reg","readonly").objectStore("reg").getKey(a);return Z(a).then(function(c){return!!c})};w.search=null;w.info=function(){};
+w.transaction=function(a,c,b){a+="reg"!==a?this.field?":"+this.field:"":"";let e=this.h[a+":"+c];if(e)return b.call(this,e);let d=this.db.transaction(a,c);this.h[a+":"+c]=e=d.objectStore(a);const f=b.call(this,e);this.h[a+":"+c]=null;return Z(d).finally(function(){d=e=null;return f})};
+w.commit=async function(a,c,b){if(c)await this.clear(),a.commit_task=[];else{let e=a.commit_task;a.commit_task=[];for(let d=0,f;d<e.length;d++)if(f=e[d],f.clear){await this.clear();c=!0;break}else e[d]=f.del;c||(b||(e=e.concat(ca(a.reg))),e.length&&await this.remove(e))}a.reg.size&&(await this.transaction("map","readwrite",function(e){for(const d of a.map){const f=d[0],g=d[1];g.length&&(c?e.put(g,f):e.get(f).onsuccess=function(){let h=this.result;var k;if(h&&h.length){const m=Math.max(h.length,g.length);
+for(let l=0,n,u;l<m;l++)if((u=g[l])&&u.length){if((n=h[l])&&n.length)for(k=0;k<u.length;k++)n.push(u[k]);else h[l]=u;k=1}}else h=g,k=1;k&&e.put(h,f)})}}),await this.transaction("ctx","readwrite",function(e){for(const d of a.ctx){const f=d[0],g=d[1];for(const h of g){const k=h[0],m=h[1];m.length&&(c?e.put(m,f+":"+k):e.get(f+":"+k).onsuccess=function(){let l=this.result;var n;if(l&&l.length){const u=Math.max(l.length,m.length);for(let p=0,t,r;p<u;p++)if((r=m[p])&&r.length){if((t=l[p])&&t.length)for(n=
+0;n<r.length;n++)t.push(r[n]);else l[p]=r;n=1}}else l=m,n=1;n&&e.put(l,f+":"+k)})}}}),a.store?await this.transaction("reg","readwrite",function(e){for(const d of a.store){const f=d[0],g=d[1];e.put("object"===typeof g?JSON.stringify(g):1,f)}}):a.bypass||await this.transaction("reg","readwrite",function(e){for(const d of a.reg.keys())e.put(1,d)}),a.tag&&await this.transaction("tag","readwrite",function(e){for(const d of a.tag){const f=d[0],g=d[1];g.length&&(e.get(f).onsuccess=function(){let h=this.result;
+h=h&&h.length?h.concat(g):g;e.put(h,f)})}}),a.map.clear(),a.ctx.clear(),a.tag&&a.tag.clear(),a.store&&a.store.clear(),a.document||a.reg.clear())};function Gb(a,c,b){const e=a.value;let d,f=0;for(let g=0,h;g<e.length;g++){if(h=b?e:e[g]){for(let k=0,m,l;k<c.length;k++)if(l=c[k],m=h.indexOf(l),0<=m)if(d=1,1<h.length)h.splice(m,1);else{e[g]=[];break}f+=h.length}if(b)break}f?d&&a.update(e):a.delete();a.continue()}
+w.remove=function(a){"object"!==typeof a&&(a=[a]);return Promise.all([this.transaction("map","readwrite",function(c){c.openCursor().onsuccess=function(){const b=this.result;b&&Gb(b,a)}}),this.transaction("ctx","readwrite",function(c){c.openCursor().onsuccess=function(){const b=this.result;b&&Gb(b,a)}}),this.transaction("tag","readwrite",function(c){c.openCursor().onsuccess=function(){const b=this.result;b&&Gb(b,a,!0)}}),this.transaction("reg","readwrite",function(c){for(let b=0;b<a.length;b++)c.delete(a[b])})])};
+function Z(a,c){return new Promise((b,e)=>{a.onsuccess=a.oncomplete=function(){c&&c(this.result);c=null;b(this.result)};a.onerror=a.onblocked=e;a=null})};export default {Index:V,Charset:va,Encoder:la,Document:Na,Worker:La,Resolver:Y,IndexedDB:Fb,Language:{}};
+export const Index=V;export const Charset=va;export const Encoder=la;export const Document=Na;export const Worker=La;export const Resolver=Y;export const IndexedDB=Fb;export const Language={};

web/js/utils.js

@@ -109,6 +109,30 @@ export function formatCountHumanReadable(num) {
     return (num / si[i].value).toFixed(1).replace(rx, "$1") + si[i].symbol;
 }
 
+/**
+ * Escapes HTML special characters in a string.
+ * @param {string} str The input string.
+ * @returns {string} The escaped string.
+ */
+export function escapeHtml(str) {
+    if (typeof str !== 'string') {
+        return str;
+    }
+
+    const escapeMap = {
+        '&': '&',
+        '<': '&lt;',
+        '>': '&gt;',
+        '"': '&quot;',
+        "'": '&#x27;',
+        '`': '&#x60;',
+        '/': '&#x2F;'
+    };
+
+    return str.replace(/[&<>"'`/]/g, match =>
+        escapeMap[match]);
+}
+
 /**
  * Escapes parentheses in a string for use in prompts.
  * Replaces '(' with '\(' and ')' with '\)'.