feat(other-models): announce the feature only when folders are available

Other Models management is opt-in and its folders come from
folder_paths.get_folder_paths(). In plugin mode ComfyUI registers vae,
upscale_models, text_encoders, clip_vision and controlnet out of the box, so
enabling the feature works immediately. Standalone only knows the keys present
in settings.json.folder_paths, and that file is edited by hand - there is no UI
for those keys - so a standalone user who followed the announcement banner
reached "Enable Other Models" and then an empty page.

Gate the announcement on the capability instead of on how the process was
started:

- Config.get_other_models_availability() probes every canonical other key
  (legacy clip collapses into text_encoders where the host exposes
  map_legacy) and reports which sub_types resolve to a folder that exists on
  disk. It deliberately ignores enable_other_models: the question is "could
  this work here at all?". An empty folder counts, because CivitAI downloads
  can target it.
- /api/lm/settings exposes it as the derived, non-persisted
  other_models_paths_available flag; a probe failure yields null and the
  banner fails open.
- BannerService only registers the announcement when the flag is not false.
  `=== false` (not falsy) keeps a cached/older payload working, and nothing is
  written to dismissed_banners, so the banner can return once folders exist.
- The Other page grows an "enabled but nothing to scan" empty state driven by
  config.other_roots, showing the settings.json snippet for standalone and a
  pointer to ComfyUI model paths otherwise, plus an Open Settings action. It
  also covers the corner where only a non-default sub_type has a folder.

Translate the six other.noPaths.* keys into all nine locales and record the
new "folder key" / "on disk" terminology in the i18n guidelines.

Backend tests and pytest tests/i18n could not run in this environment (no
pytest/platformdirs); the probe was exercised against a stubbed folder_paths.
Frontend: 120 files / 1101 JS tests passed.

AGENTS.md

@@ -166,7 +166,7 @@ The system runs in two modes:
 
 ### Model Types & Routes
 
-- API endpoints follow `/loras/*`, `/checkpoints/*`, `/embeddings/*` patterns
+- API endpoints follow `/loras/*`, `/checkpoints/*`, `/embeddings/*`, `/other/*` patterns
 - Route registrars organize endpoints by domain: `ModelRouteRegistrar`, `RecipeRouteRegistrar`, etc.
 - Request handlers in `py/routes/handlers/` implement route logic
 - All routes use aiohttp, return `web.json_response` or `web.Response`
@@ -190,6 +190,8 @@ The system runs in two modes:
 
 - `py/config.py` manages folder paths for models and handles symlink mappings
 - Auto-saves paths to `settings.json` in ComfyUI mode
+- `settings.json.example` is intentionally minimal (see Important Notes); all
+  other defaults live in `DEFAULT_SETTINGS` (`py/services/settings_manager.py`)
 
 ### Frontend UI Architecture
 
@@ -250,6 +252,12 @@ If a cross-layer issue ever needs a live server, the sandboxed helpers live in
 ## Important Notes
 
 - ALWAYS use English for comments (per copilot-instructions.md)
+- **`settings.json.example` must stay minimal**: only `use_portable_settings`,
+  `civitai_api_key`, and the four core `folder_paths` keys (`loras`,
+  `checkpoints`, `unet`, `embeddings`). Do NOT add optional/default keys
+  (model-category folders, `default_*_root`, `auto_organize_exclusions`, etc.)
+  to this file unless the user explicitly asks for it. Defaults belong in
+  `DEFAULT_SETTINGS` in `py/services/settings_manager.py`.
 - Run `python scripts/sync_translation_keys.py` after adding UI strings to `locales/en.json`
 - Symlinks require normalized paths.
   **Business paths vs real paths**: All stored paths and operation routing use the

docs/i18n-translation-guidelines.md

@@ -4,7 +4,7 @@ This document is the canonical set of conventions for translating LoRA Manager U
 It applies to **human translators and AI agents** alike. Read it before editing anything in
 `locales/`.
 
-Source of truth: `locales/en.json` (10 locales, 1810 leaf keys; all locales share the exact
+Source of truth: `locales/en.json` (10 locales, 1982 leaf keys; all locales share the exact
 same key structure).
 
 Locales: `en`, `zh-CN`, `zh-TW`, `ja`, `ko`, `fr`, `de`, `es`, `ru`, `he` (RTL).
@@ -13,6 +13,26 @@ Locales: `en`, `zh-CN`, `zh-TW`, `ja`, `ko`, `fr`, `de`, `es`, `ru`, `he` (RTL).
 > stale-text, and untranslated-block fixes described in §2–§6 were applied across all locales
 > (commits `3c3ac49f` … `fd1227d3`). The tables below are now the **normative target state**,
 > not a to-do list — future edits should preserve these renderings and only add what is new.
+>
+> **Status (2026-09, Other Models):** the `other` model type (VAE / Upscaler / Text Encoder /
+> CLIP Vision / ControlNet) and the Other Models opt-in toggles added 36 new keys; all of them
+> are now translated in all 9 locales (terminology in §2 "Other Models feature"). There are no
+> remaining `[TODO: Translate]` placeholders in any locale.
+>
+> **Status (2026-09, revision):** `other.disabled.description`, `banners.otherModels.content` and
+> `settings.folderSettings.enableOtherModelsHelp` were refreshed in `en.json` to name all five
+> sub_types (they had listed four, which read as "these are what enabling manages") and
+> re-translated in all 9 locales in the same pass. `clip_vision` and `controlnet` are now both
+> opt-in, so the first two describe **capability** and the third the **master switch**, not the
+> default set — keep all three enumerating the full five (`VAE / upscaler / text encoder /
+> CLIP vision / ControlNet` in `en`; locale slash-list casing follows each file's existing
+> `VAE / Upscaler / Text Encoder / …` style, de compounds as `CLIP-Vision- und ControlNet-Ordner`).
+>
+> **Status (2026-09, "no folders found" state):** the Other Models page gained an *enabled but
+> nothing to scan* empty state with 6 new keys (`other.noPaths.*`); translated in all 9 locales
+> in the same pass. The `folder_paths` JSON snippet shown in that state lives in
+> `templates/other.html`, **not** in the locale files, so it is never translated — only the
+> surrounding prose is. Terminology added in §2.
 
 ---
 
@@ -222,6 +242,56 @@ and must be normalized. `en` = keep the English word as-is.
 | hash | 哈希 (哈希值 variant OK) | 雜湊 ✓ |
 | register | 你 (fix 5×您 → 你) | 您 (fix 18×你 → 您) |
 
+### Other Models feature (VAE / Upscaler / Text Encoder / CLIP Vision / ControlNet)
+
+The `other` model type exposes five sub_types. They are **model-type names**, so they follow
+R3 and stay in Latin in every locale. The `settings.folderSettings.subType*` values are
+therefore **intentionally byte-identical to `en.json`** (same precedent as
+`settings.priorityTags.modelTypes` / `checkpoints.modelTypes.checkpoint`) — a §6 sweep must
+not "fix" them.
+
+| Term | Rendering | Note |
+|---|---|---|
+| VAE | `VAE` everywhere | acronym, always upper-case |
+| Upscaler | `Upscaler` everywhere | CivitAI `ModelType` name |
+| Text Encoder | `Text Encoder` everywhere | de compounds as `Text-Encoder-Stammordner` |
+| CLIP Vision | `CLIP Vision` everywhere | de compounds as `CLIP-Vision-Stammordner` |
+| ControlNet | `ControlNet` everywhere | brand casing, capital N |
+
+In prose these names sit next to localized nouns the same way `Diffusion Model` does
+(zh `VAE 根目录`, ja `VAEルート`, ko `VAE 루트`, ru `Корневая папка VAE`).
+
+**"Other Models" is the page/feature name, not a model type — translate it:**
+
+| Locale | `other.title` | `header.navigation.other` |
+|---|---|---|
+| fr | Autres modèles | Autres |
+| zh-CN | 其他模型 | 其他 |
+| zh-TW | 其他模型 | 其他 |
+| ja | その他のモデル | その他 |
+| ko | 기타 모델 | 기타 |
+| de | Weitere Modelle | Andere |
+| es | Otros modelos | Otros |
+| ru | Другие модели | Другое |
+| he | מודלים אחרים | אחרים |
+
+`settings.folderSettings.otherSubTypes` ("Managed Types") must name **model** types, matching
+each locale's `header.filter.modelTypes` rendering (zh `管理的模型类型`, ja `管理するモデルタイプ`,
+de `Verwaltete Modelltypen`, …).
+
+The "no folders found" empty state (`other.noPaths.*`) uses two phrases that must stay
+consistent whenever that copy is edited. `folder key` means the `folder_paths` key name
+(`vae`, `upscale_models`, … — Latin per the table above); `on disk` means the folder must
+physically exist:
+
+| Phrase | Rendering |
+|---|---|
+| folder key | zh-CN 文件夹键 · zh-TW 資料夾鍵 · ja フォルダーキー · ko 폴더 키 · fr clé de dossier · de Ordnerschlüssel · es clave de carpeta · ru ключ папки · he מפתח תיקייה |
+| on disk | zh-CN 在磁盘上 · zh-TW 在磁碟上 · ja ディスク上 · ko 디스크에 · fr sur le disque · de auf dem Datenträger · es en el disco · ru на диске · he בדיסק |
+
+`settings.json` and `ComfyUI` stay verbatim in every locale; "reload this page" / "restart
+LoRA Manager" reuse each locale's existing restart wording (`settings.extraFolderPaths.*`).
+
 ---
 
 ## 3. Cross-cutting confusion hot-spots (must-fix list)
@@ -312,8 +382,9 @@ blocks are translated** in every locale: `recipes.batchImport.*` + `toast.recipe
 The only values that remain intentionally identical to `en.json` are non-translatable:
 URL/path placeholders (`https://…`, `C:/…`), numeric presets (`5 (1080p), 6 (2K), 8 (4K)`),
 example token lists (`character, concept, style(toon|toon_style)`), service/provider names
-(`CivitAI → CivArchive → Archive DB`), and the external playlist title
-(`help.updateVlogs.playlistTitle`, de: translated to "LoRA Manager-Update-Playlist").
+(`CivitAI → CivArchive → Archive DB`), model-type names (`settings.priorityTags.modelTypes.*`,
+`settings.folderSettings.subTypeVae` … `subTypeControlnet` — see §2), and the external playlist
+title (`help.updateVlogs.playlistTitle`, de: translated to "LoRA Manager-Update-Playlist").
 
 Rule for `uiHelpers.workflow.noPromptTargets`: the second line (`Mark as → Send Prompt
 Target`) quotes literal ComfyUI context-menu items — keep those menu labels in English in

docs/plans/other-models-page.md

@@ -0,0 +1,363 @@
+# Plan: "Other Models" Page — Unified Management for VAE / Upscaler / Text Encoder / etc.
+
+**Status:** v2 — **Phase 1 implemented** (2026-09-12, commits `27da7b3c` backend + `fa7ce725` frontend; verified live against a running ComfyUI instance: scan/hash/sub_type-derivation/fetch/previews all green). **Phase 2 implemented** (2026-09-12, per §9 design; full pytest + vitest green). **Phase 3 implemented** (§11: opt-in management toggles; default off). **i18n done** (2026-09-13): all 36 new keys translated in the 9 non-English locales — the `[TODO: Translate]` placeholders left by the sync script during development are gone (see `docs/i18n-translation-guidelines.md` §2, "Other Models feature"). **Default set revised (pre-release):** only `vae` / `upscaler` / `text_encoder` are managed by default — `clip_vision` and `controlnet` are both opt-in (§2, §11.1.1).
+**Scope (Phase 1):** scan + manage (list, search, filter, tags, folders, preview, rename, move, delete/exclude, CivitAI metadata fetch) for a new model type `other`, exposed as a new web page. **Phase 2 (§9):** one-click download from CivitAI for these types.
+
+## 1. Goal
+
+Today the manager supports three model types:
+
+| page | model_type | sub_types |
+|---|---|---|
+| `/loras` | `lora` | `lora`, `locon`, `dora` |
+| `/checkpoints` | `checkpoint` | `checkpoint`, `diffusion_model` |
+| `/embeddings` | `embedding` | `embedding` |
+
+Add a fourth page that manages "everything else" — VAE, upscalers, text encoders / CLIP, CLIP vision, optionally ControlNet — with a folder→sub_type mapping table so new ComfyUI folder categories can be added later by configuration, not code.
+
+## 2. Locked Decisions
+
+1. **Architecture: one scanner + one service + one page, sub_type derived by location.**
+   Replicates the checkpoint pattern (`CheckpointScanner` aggregates `checkpoints` + `unet` roots and derives `checkpoint` vs `diffusion_model` from the root containing the file, `py/services/checkpoint_scanner.py:384-415`). One `OtherScanner` aggregates all enabled folder roots; `resolve_sub_type_for_path()` maps each root to a sub_type. No per-category scanners.
+
+2. **Naming: internal `model_type = "other"`, route prefix `/other`, page id `other`.**
+   - `misc` is rejected: `py/routes/misc_routes.py` already owns that name for system/settings routes (`/api/lm/settings`, `/api/lm/doctor/*`).
+   - `components` is rejected: `templates/components/` and `static/js/components/` directories would make `components.html` / `components.js` confusing neighbors.
+   - `other` matches CivitAI's `Other` fallback type semantics. The **display name** is an i18n string (`other.title`, e.g. "Other Models") and can be renamed later without touching code.
+
+3. **sub_type values:** snake_case, aligned with CivitAI `ModelType` semantics:
+
+   | sub_type | ComfyUI `folder_paths` key(s) | CivitAI ModelType | enabled by default |
+   |---|---|---|---|
+   | `vae` | `vae` | `VAE` | yes |
+   | `upscaler` | `upscale_models` | `Upscaler` | yes |
+   | `text_encoder` | `text_encoders`, `clip` (legacy) | `TextEncoder` (CLIP is retired upstream) | yes |
+   | `clip_vision` | `clip_vision` | `CLIPVision` | no (mapping present, opt-in) |
+   | `controlnet` | `controlnet` | `Controlnet` | no (mapping present, opt-in) |
+
+   New folder categories = one line in the mapping table (see §4.1).
+
+   **Why only three are on by default** (revised in Phase 3, before release):
+   VAE, upscalers and text encoders are dependency-style assets every pipeline
+   needs, and "which one am I actually using" is the recurring problem they
+   solve. `clip_vision` and `controlnet` are workflow-driven instead
+   (IPAdapter/SVD image conditioning; per-workflow ControlNet variants), and
+   ControlNet libraries routinely run to dozens of files, so both are treated
+   symmetrically as opt-in. Enumerating all five as "the default set" was not
+   defensible on demand breadth alone.
+
+4. **Phase 1 = scan/manage only.** Downloads from CivitAI (`download_manager.py` type mapping, default-root settings keys, download routing) are Phase 2 (§9). CivitAI **metadata fetch** for existing files IS in Phase 1 (hash-based lookup is type-agnostic; only the type-validation hook needs new values).
+
+5. **Out of scope (default off, revisit later):** usage statistics buckets, recipe matching (`recipe_scanner.py` only merges lora+checkpoint scanners), statistics page, embeddings re-classification (stays its own page — merging would be a breaking change).
+
+## 3. Why This Works With Minimal Churn
+
+- `ModelScanner` (`py/services/model_scanner.py:93`) is specialized entirely via constructor params (`model_type`, `model_class`, `file_extensions`) + optional hooks (`adjust_metadata`, `adjust_cached_entry`, `resolve_sub_type_for_path`, `model_scanner.py:1429-1443`).
+- `BaseModelService` subclasses can be one method (`EmbeddingService` implements only `format_response`, `py/services/embedding_service.py:12`).
+- Routes: `ModelServiceFactory.register_model_type()` (`py/services/model_service_factory.py:120-136`) + `COMMON_ROUTE_DEFINITIONS` (`py/routes/model_route_registrar.py:23-149`) generate the full `/api/lm/{prefix}/*` surface (~50 endpoints) plus the `GET /{prefix}` page route.
+- `PersistentModelCache` (`py/services/persistent_model_cache.py:526-606`) is a single `models` table keyed `(model_type, file_path)` with `model_type` as free text — **zero schema change**.
+- Frontend `apiConfig.js` (`static/js/api/apiConfig.js:51`) generates all endpoints from the model-type string; `ModelCard.js:670-675` renders the sub_type badge from data; the checkpoints page already demonstrates the "one page, multiple sub_types" filter (`header.html:298`).
+
+## 4. Backend Changes
+
+### 4.1 New constants — `py/utils/constants.py`
+
+```python
+# folder_paths key -> sub_type; single source of truth for extensibility
+OTHER_MODEL_FOLDER_SUBTYPES = {
+    "vae": "vae",
+    "upscale_models": "upscaler",
+    "text_encoders": "text_encoder",
+    "clip": "text_encoder",        # legacy ComfyUI key
+    "clip_vision": "clip_vision",
+    "controlnet": "controlnet",
+}
+DEFAULT_OTHER_MODEL_FOLDERS = ("vae", "upscale_models", "text_encoders", "clip", "clip_vision")
+VALID_OTHER_SUB_TYPES = ["vae", "upscaler", "text_encoder", "clip_vision", "controlnet"]
+# CivitAI model.type values accepted for this page (fetch-metadata validation)
+VALID_OTHER_CIVITAI_TYPES = {"vae", "upscaler", "textencoder", "clipvision", "controlnet", "other"}
+```
+
+Also extend `CIVITAI_USER_MODEL_TYPES` (`constants.py:90`) if user-model queries should include these types.
+
+### 4.2 New files (mirror the embedding/checkpoint implementations)
+
+1. **`py/utils/models.py`** — add `OtherModelMetadata(BaseModelMetadata)`: default `sub_type="vae"` placeholder overridden by scanner hook; `from_civitai_info` mapping CivitAI types → our sub_types (`TextEncoder`→`text_encoder`, `CLIPVision`→`clip_vision`, `Upscaler`→`upscaler`, `VAE`→`vae`, `Controlnet`→`controlnet`, else `other`-ish fallback to folder-derived sub_type).
+2. **`py/services/other_scanner.py`** — `OtherScanner(ModelScanner)`:
+   - `model_type="other"`, extensions: reuse the checkpoint set (`safetensors/pt/pt2/bin/pth/pkl/sft/gguf`).
+   - `get_model_roots()`: iterate `OTHER_MODEL_FOLDER_SUBTYPES` ∩ enabled keys, pull each from `config` (§4.3); dedupe; build `root → sub_type` map (normalized abspaths; multiple keys may share a sub_type).
+   - Implement all three hooks like `CheckpointScanner` (`checkpoint_scanner.py:384-415`): `resolve_sub_type_for_path` by longest-prefix root match, `adjust_metadata`, `adjust_cached_entry` (sub_type is re-derived on cache load, never persisted).
+   - **Lazy hashing, checkpoint-style**: text encoders (T5-XXL ≈ 10 GB) make eager sha256 painful. Copy the `hash_status="pending"` + singleflight `calculate_hash_for_model` pattern from `CheckpointScanner`.
+3. **`py/services/other_model_service.py`** — `OtherModelService(BaseModelService)`, `format_response` only (no usage_count, like `EmbeddingService`).
+4. **`py/routes/other_routes.py`** — `OtherRoutes(BaseModelRoutes)`, `template_name="other.html"`, hooks:
+   - `_validate_civitai_model_type` → `VALID_OTHER_CIVITAI_TYPES`
+   - `_get_expected_model_types`, `_parse_specific_params` (no type-specific download params in Phase 1)
+   - `initialize_services()` on `app.on_startup` pulling `ServiceRegistry.get_other_scanner()`.
+
+### 4.3 `py/config.py`
+
+- New `other_roots` property: for each enabled key in `OTHER_MODEL_FOLDER_SUBTYPES`, `folder_paths.get_folder_paths(key)` (plugin mode) — standalone mode needs nothing new: `MockFolderPaths` (`standalone.py:66-105`) already serves arbitrary keys from `settings.json.folder_paths`.
+- Follow the existing per-type recipe: an `_prepare_other_paths()` (dedupe + symlink registration; also **cross-scanner overlap detection** — warn if an `other` root is already covered by checkpoints/unet/embedding roots, mirroring the checkpoint/unet overlap check).
+- Wire into: `_apply_library_paths`, `_symlink_roots()`, `_rebuild_preview_roots()` (hard requirement — preview images are served per registered root), `save_folder_paths_to_settings()`.
+
+### 4.4 Existing-file edits (the "type string scatter" — each is a small branch/entry)
+
+| file | change |
+|---|---|
+| `py/services/model_service_factory.py:120` | register `("other", OtherModelService, OtherRoutes)` in `register_default_model_types()` |
+| `py/services/service_registry.py` | add `get_other_scanner()` (mirror `:297` `get_embedding_scanner`) |
+| `py/services/model_scanner.py:67` | `PAGE_TYPE_MAP['other'] = 'other'` (WebSocket progress) |
+| `py/services/base_model_service.py:896-906` | `get_model_types()` branch → `VALID_OTHER_SUB_TYPES` |
+| `py/lora_manager.py` | `_initialize_services` scanner task list (`:219-242`), `_cleanup` cancel list (`:463`), `_cleanup_backup_files` roots (`:327-330`) |
+| `py/routes/handlers/misc_handlers.py` | `scanner_getters` (`:657-661`) + `scanner_factories` (`:757-759`) so Doctor / init-status / refresh-all see the new scanner |
+| `py/services/pending_delete_service.py` | `_PAGE_TYPE` map (`:57-61`) + scanner getter list (`:983-985`) |
+| `py/metadata_ops/__init__.py:36-38` | `SCANNER_TYPE_MAP['other']` |
+| `settings.json.example` | document optional `folder_paths` keys: `vae`, `upscale_models`, `text_encoders`, `clip_vision` |
+
+**Explicitly NOT touched in Phase 1:** `py/services/download_manager.py`, `py/services/download_routing.py`, `py/services/settings_manager.py` default-root keys, `py/routes/stats_routes.py`, `py/utils/usage_stats.py`, `py/services/recipe_scanner.py`, `py/metadata_collector/`, `py/nodes/`.
+
+**Zero-change confirmations (verified):** `PersistentModelCache`, `ModelUpdateService`, `DownloadedVersionHistoryService`, `MetadataSyncService` + provider chain (type-agnostic hash lookups), `ModelFileService` / `ModelMoveService` / `ModelLifecycleService` (scanner + model_type injected), `ModelCache` / `ModelHashIndex`, `AutoV3BackfillService`.
+
+## 5. Frontend Changes
+
+1. **`static/js/api/apiConfig.js`** — `MODEL_TYPES.OTHER = 'other'`; `MODEL_CONFIG.other` entry (displayName, singularName, `supportsMove`, `supportsBulkOperations`; no letter filter); endpoints come free from `getApiEndpoints()` (`:51`).
+2. **`static/js/api/otherApi.js`** — thin `OtherApiClient extends BaseModelApiClient` (mirror `embeddingApi.js`); register in `modelApiFactory.js`.
+3. **`static/js/other.js`** — page entry (mirror `embeddings.js`): `appCore.initialize()` + `createPageControls('other')` + `initializePageFeatures()` + `ModelDuplicatesManager` + `initActiveFiltersSync('other')`.
+4. **Controls & context menu** — `OtherControls extends PageControls` and `OtherContextMenu` (start from the embedding variants — the smallest); add branches in the two factories (`components/controls/index.js:15`, `components/ContextMenu/index.js:15`). Context-menu template block lives in `templates/other.html` (`{% block additional_components %}`, the checkpoints/embeddings pattern — do NOT touch the shared `context_menu.html`).
+5. **`templates/other.html`** — copy `embeddings.html`: same content blocks (controls + breadcrumb + duplicates banner + folder sidebar + `#modelGrid`), `data-page="other"`, main script `/loras_static/js/other.js`.
+6. **`templates/components/header.html`** — nav entry (`:23-43`, active when `request.path.startswith('/other')`); enable the `modelTypes` sub_type filter panel for `other` (`:298-305` pattern from checkpoints); check search-options panel conditions (`:199-224`).
+7. **`static/js/utils/constants.js`** — `MODEL_SUBTYPE_ABBREVIATIONS` (`:115`): `vae→VAE`, `upscaler→UPS`, `text_encoder→TE`, `clip_vision→CV`, `controlnet→CN`; matching `MODEL_SUBTYPE_DISPLAY_NAMES` (`:99`). (Unknown fallback already uppercases 4 chars, but explicit mappings read better.)
+8. **`static/js/core.js:110` `getPageType()`** — verify `data-page="other"` flows through `state.pages` generically; add only if the page list is enumerated anywhere.
+9. No change to `web/comfyui/top_menu_extension.js` (it opens `/loras`; page-to-page nav is the header bar).
+
+## 6. i18n
+
+- `locales/en.json`: add `other.title` (e.g. "Other Models") + minimal `other.contextMenu.*` / `other.modelTypes.*` keys; reuse `modelCard.*`, `loras.contextMenu.*`, `common.*` wherever possible (the established pattern — checkpoints/embeddings already reuse lora keys).
+- Run `python scripts/sync_translation_keys.py`; leave `[TODO: Translate]` placeholders in other locales (per `docs/i18n-translation-guidelines.md` §7 — do not translate proactively).
+
+## 7. Testing
+
+Follow existing conventions (`pytest.ini`, `tests/frontend/` vitest):
+
+1. **Backend (pytest, async where needed):**
+   - `OtherScanner` root aggregation + `resolve_sub_type_for_path` (file under `vae/` root → `vae`; `text_encoders` and legacy `clip` both → `text_encoder`; disabled `controlnet` root not scanned).
+   - Cache round-trip: sub_type re-derived via `adjust_cached_entry` (not persisted).
+   - Lazy hash: `hash_status="pending"` default; `calculate_hash_for_model` singleflight.
+   - `OtherRoutes` registration smoke test: `/api/lm/other/...` endpoints exist; `_validate_civitai_model_type` accepts `vae`/`upscaler`/`textencoder`, rejects `lora`.
+   - Config: `other_roots` in both modes (mock `folder_paths`, and standalone `settings.json.folder_paths`).
+2. **Frontend (vitest + jsdom, `tests/frontend/`):**
+   - `apiConfig`: `getApiEndpoints('other')` URL shapes; `modelApiFactory` returns the Other client.
+   - `ModelCard` badge rendering for new sub_types.
+   - `createPageControls('other')` / `createPageContextMenu('other')` factories.
+3. **Manual UI verification by the user** (per AGENTS.md — no sandbox/browser automation): page loads, scans a real library, sub_type filter + badges, context menu actions.
+
+## 8. Execution Order
+
+1. `constants.py` + `OtherModelMetadata` + `config.py` roots
+2. `OtherScanner` (+ registry, factory, `PAGE_TYPE_MAP`) → scanner unit tests green
+3. `OtherModelService` + `OtherRoutes` + handler/registrar wiring + `lora_manager.py` lifecycle → route tests green
+4. Doctor/pending-delete/metadata-ops scatter entries
+5. Template + header nav + frontend API/controls/context-menu/card badges → vitest green
+6. i18n keys + sync script
+7. `pytest` + `npm test` full runs; hand to user for manual UI check
+
+## 9. Phase 2 Detailed Design — CivitAI Downloads for `other`
+
+Designed 2026-09-12 against the Phase-1 code on this branch; decisions marked **[locked]** follow the same recommendations the feature owner approved for Phase 1.
+
+### 9.1 Download pipeline touch points
+
+Flow: `POST /api/lm/download-model` (`py/routes/model_route_registrar.py:104`; GET variant `:105` for the browser extension) → `ModelDownloadHandler.download_model` (`model_handlers.py:1740`) → `DownloadModelUseCase.execute` → `DownloadCoordinator.schedule_download` → `DownloadManager.download_from_civitai` (`download_manager.py:386`) → `_execute_original_download` (`:1415`). Inside, seven scatter points need an `other` branch:
+
+1. **Type map** (`:1496-1507`): accept `model.type.lower() in VALID_OTHER_CIVITAI_TYPES` → `model_type = "other"` (reuses the Phase-1 set, incl. `"other"` itself).
+2. **Early version-exists gate** (`:1436-1463`): add `other_scanner.check_model_version_exists`.
+3. **File-level exists gate** (`:1640-1655` → `_find_local_file_entry` `:320-346` → `_get_scanner_for_model_type` `:230-236`): add explicit `other` branch. **Trap**: the function currently falls through to the lora scanner for unknown types — `"other"` would silently dedupe against loras. Also narrow the fall-through to `"lora"` only / raise on unknown.
+4. **Version-level fallback gate** (`:1656-1688`): add `elif model_type == "other"`.
+5. **Default-root selection** (`:1690-1727`): for `other`, first resolve sub_type (§9.2), then read `default_other_roots[sub_type]` (§9.3); if sub_type is undecidable or no default root configured → error guiding the user to pick a folder explicitly.
+6. **Metadata class selection** (`:1909-1928`) + `_build_metadata_for_resume` (`:969-981`): add `OtherModelMetadata.from_civitai_info` branches.
+7. **Post-download cache write** (`_execute_download_pipeline` `:2622-2679`): add `other` scanner branch; `adjust_metadata` re-derives sub_type from the on-disk root automatically. `_get_supported_extensions_for_type` (`:2720-2744`): `other` reuses the checkpoint extension set.
+
+Hooks: `_record_downloaded_version_history` (model_type is free text — zero change); `_sync_downloaded_version` (`:1984` → scanner dispatch `:2130-2135`) add `other`; `py/utils/example_images_download_manager.py` scanner dispatch at `:411-421`, `:591-601`, `:1089+` — add `other` at all three (silent no-scanner otherwise).
+
+Path templates: `get_download_path_template("other")` is unset, so `other` resolves to a **flat** layout (empty template) — downloads land directly under the resolved sub_type root. This is deliberate: other-model roots are already split per sub_type (`default_other_roots`), and `priority_tags` has no `other` entry, so `{first_tag}` would fall back to an arbitrary CivitAI tag and scatter files into unstable folders. Users who want nesting can still set `download_path_templates["other"]` in `settings.json`. See `DEFAULT_DOWNLOAD_PATH_TEMPLATES` (`py/utils/constants.py`) and `DEFAULT_PATH_TEMPLATES` (`static/js/utils/constants.js`).
+
+### 9.2 File-level routing (model.type / file.type → sub_type) **[locked]**
+
+Table-driven, mirroring Phase 1. New in `py/utils/constants.py`:
+
+```python
+CIVITAI_FILE_TYPE_TO_OTHER_SUB_TYPE = {
+    "VAE": "vae", "Upscaler": "upscaler", "Text Encoder": "text_encoder",
+    "Vision Encoder": "clip_vision", "CLIPVision": "clip_vision",
+    "ControlNet": "controlnet",
+}
+```
+
+`download_routing.py` gains `resolve_other_download_sub_type(civitai_model_type, file_types, selected_file_type=None)` with fixed priority:
+
+1. **Explicit user file pick** (`file_params` from #1058's `_resolve_target_file`) — if the picked file's type maps, it wins even when model.type is `Checkpoint`.
+2. **model.type** via the existing `CIVITAI_TYPE_TO_OTHER_SUB_TYPE` (`constants.py:120-127`).
+3. **file.type fallback** — only when model.type maps to nothing (e.g. model.type `Other` or retired `CLIP`). MUST NOT override a mapped model.type: checkpoint models routinely bundle VAE/Text Encoder component files, and unconditional file-type routing would misroute them.
+4. Still undecidable → `None`; `use_default_paths` errors and the UI offers all other roots for manual selection.
+
+HTTP: extend `DownloadRoutingHandler.get_download_routing` (`download_routing_handlers.py:23`) with an `other` branch returning `{root_kind: "other", sub_type: ...}`; add `GET /api/lm/other/roots_by_subtype` in `OtherRoutes.setup_specific_routes` (data from `config._prepare_other_paths`'s per-key roots, aggregating `text_encoders` + legacy `clip` under `text_encoder`).
+
+### 9.3 Settings: single dict key `default_other_roots` **[locked]**
+
+Rejected: four flat keys (`default_vae_root`…) — each flat key costs ~13 touch points in `settings_manager.py` (defaults `:82-85`, `_check_and_auto_set` `:890-895`, `set()` `:1621-1628`, `_update_active_library_entry` `:738-805`, upsert/create signatures `:1953-2132`, `_build_library_payload` `:552-612`, `_sync_active_library_to_root` `:519-547`, three library constructors, frontend `DEFAULT_SETTINGS_BASE`), repeated per future sub_type.
+
+Chosen: one mapping key `default_other_roots: {sub_type: path}`, copying the `extra_folder_paths` precedent (generic Mapping handling at `:533-535`, `:573-578`, `:763-767`). `_check_and_auto_set` generalizes to per-sub_type candidates (union over that sub_type's folder keys — `text_encoder` → `text_encoders` + `clip`). `set()` validates keys against `VALID_OTHER_SUB_TYPES`.
+
+Also fix the Phase-1 omission: add `"other_scanner"` to `_notify_library_change` (`:2150-2156`) and `_notify_model_name_display_change` (`:1795-1800`) — otherwise switching libraries leaves the other page stale.
+
+### 9.4 Settings UI
+
+- `templates/components/modals/settings/library.html:34-40`: sub_type selectors after the existing four `setting_select`s (Jinja loop; controlnet selector only when `enabled_other_folders` includes it). Dict-subkey save helper `saveOtherRootSetting(subType, value)` alongside the flat `saveSelectSetting`.
+- `static/js/managers/SettingsManager.js:1547-1697`: `loadOtherRoots()` mirroring `loadUnetRoots()`, fed by `/api/lm/other/roots_by_subtype`; current values from `state.global.settings.default_other_roots`. `state/index.js:24` `DEFAULT_SETTINGS_BASE` += `default_other_roots: {}`.
+- Optional: one `other` row in the download-path-template block (`library.html:153-211`).
+- i18n: `settings.folderSettings.*` keys into `locales/en.json` + sync script; other locales keep `[TODO: Translate]`.
+- Settings GET (`misc_handlers.py:1528-1536`) already returns all non-sensitive keys — new key reaches the frontend for free.
+
+### 9.5 Frontend download entry
+
+- `templates/components/controls.html:83`: drop the `page_id != 'other'` exclusion on the download button (keyboard shortcut D self-enables via `PageControls.js:196-198`).
+- `OtherControls.js:22-55`: add `showDownloadModal: () => downloadManager.showDownloadModal()` (mirror `EmbeddingsControls.js:43-45`).
+- `DownloadManager.js` `proceedToLocationContent` (`:955-1017`): add `_resolveOtherSubType()` (mirror `_resolveIsDiffusionModel` `:1026`): selected file type → `/api/lm/download/routing` → `otherApiClient.fetchModelRoots(subType)` (new); default-root preselect reads `default_other_roots[subType]` instead of `` `default_${singularType}_root` `` (`:974`). Undecidable → list all other roots (`/api/lm/other/roots`) for manual pick; an explicit save_dir skips backend default-root logic, so the two paths cannot disagree.
+- `ModelVersionsTab` download buttons are modelType-generic and already work via `getModelApiClient('other')`; context menu has no CivitAI download entry — no change.
+- Version-list type validation (`get_civitai_versions` → `_validate_civitai_model_type`) already accepts `VALID_OTHER_CIVITAI_TYPES` from Phase 1.
+
+### 9.6 CivitAI type mapping decisions **[locked]**
+
+- Download accepts exactly `VALID_OTHER_CIVITAI_TYPES` (`VAE, Upscaler, TextEncoder, CLIP, CLIPVision, Controlnet, Other`) — reuse the Phase-1 tables; do NOT create new ones.
+- Extend `CIVITAI_USER_MODEL_TYPES` (`constants.py:133-137`) with the 7 aliases, and point them at the other scanner / `"other"` history bucket in `misc_handlers.py` (`type_scanner_map` `:2793-2797`, `downloaded_version_map` `:2821-2827`) — otherwise creator pages silently filter these models while downloads claim support.
+- Fix (small Phase-1 bug): `OtherModelMetadata.from_civitai_info` (`py/utils/models.py:343`) reads `version_info.get("type")`, but the type lives at `version["model"]["type"]` — the mapping never fires and always degrades to the placeholder. Read `version_info.get("model", {}).get("type")` instead. (`CheckpointMetadata:290` has the same shape; leave it alone here.)
+
+### 9.7 Tests
+
+Existing base: `tests/services/test_download_manager_basic.py` (incl. `test_download_rejects_unsupported_model_type` `:1336`), `test_download_manager_error.py`, `test_download_manager_concurrent.py`, `tests/integration/test_download_flow.py`, `tests/services/test_settings_manager.py`; frontend `tests/frontend/managers/downloadManager.routing.test.js`, `settingsManager.library.test.js`.
+
+Add: (1) `resolve_other_download_sub_type` unit tests — every priority tier, bundled-component anti-misrouting, undecidable → None, civarchive-shaped payload; (2) download_manager — six model.types accepted → other scanner (mock), unknown still rejected, no lora-scanner fall-through, per-sub_type default roots + unconfigured error, resume metadata, extension set; (3) settings_manager — `default_other_roots` defaults/auto-set (incl. text_encoder dual-key union)/library sync/upsert passthrough/illegal sub_type rejection; (4) routes — `/api/lm/download/routing` other branch, `roots_by_subtype` shape; (5) example-images dispatch accepts `other` (3 sites); (6) vitest — `_resolveOtherSubType` + root select + default preselect, `loadOtherRoots`; (7) user-models existsLocally for VAE.
+
+### 9.8 Phase 2 file list
+
+Backend: `py/utils/constants.py`, `py/services/download_routing.py`, `py/routes/handlers/download_routing_handlers.py`, `py/services/download_manager.py`, `py/utils/example_images_download_manager.py`, `py/services/settings_manager.py`, `py/utils/models.py`, `py/routes/other_routes.py`, `py/routes/handlers/misc_handlers.py`, `settings.json.example`.
+Frontend/templates: `templates/components/controls.html`, `static/js/components/controls/OtherControls.js`, `static/js/managers/DownloadManager.js`, `static/js/api/otherApi.js`, `templates/components/modals/settings/library.html`, `static/js/managers/SettingsManager.js`, `static/js/state/index.js`, `locales/en.json` + sync.
+
+## 10. Risks / Open Questions
+
+- **Root overlap**: a user may point `text_encoders` at a directory already scanned as checkpoints/unet. Realpath dedup inside one scanner won't catch cross-scanner overlap → the `_prepare_other_paths` overlap warning (§4.3) is the mitigation; duplicate cards across pages are cosmetic, not corrupting (cache keyed by `(model_type, file_path)`).
+- **Huge text encoders + lazy hash**: CivitAI fetch for a pending-hash model must trigger on-demand hash like checkpoints do — verify that flow (`calculate_hash_for_model`) is reachable from the `other` routes' fetch-metadata handler.
+- **Retired CivitAI types**: `CLIP`/`CLIPVision` are retired upstream (grandfathered for existing models); metadata fetch must tolerate both retired and current types — `VALID_OTHER_CIVITAI_TYPES` includes them deliberately.
+- **Standalone users** must add the new `folder_paths` keys to `settings.json` themselves; document in `settings.json.example` and the feature doc.
+- **Page display name** is i18n-only; if "Other Models" tests poorly, rename `other.title` without code changes.
+
+### Phase 2 risks
+
+- **Bundled component files**: checkpoint models routinely ship VAE/Text Encoder component files — file.type routing must stay a fallback (or explicit user pick), never an override (§9.2 priority is load-bearing; test it).
+- **`_get_scanner_for_model_type` lora fall-through** (`download_manager.py:236`): without an explicit `other` branch, dedupe checks run against the lora scanner — the most insidious trap in Phase 2.
+- **text_encoder dual folder keys** (`text_encoders` + legacy `clip`): default-root candidates, `roots_by_subtype`, and auto-set must all merge both keys; miss one and the default-root dropdown comes up empty.
+- **Undecidable sub_type** (model.type `Other` + unknown file types): must error and ask, never silently default to the vae folder.
+- **Lazy hash after download**: downloads carry CivitAI SHA256 (no recompute needed) — ensure the post-download cache write doesn't leave `hash_status="pending"`, or the next metadata fetch re-hashes a 10 GB file.
+- **CivArchive source**: same `_execute_original_download` path, same payload shape — cover it once in tests.
+
+## 11. Phase 3 — Opt-in Management Toggles (implemented)
+
+Designed 2026-09-13 against the Phase-1/2 code. Other Models is **opt-in**: after
+Phase 3 the feature ships disabled, so no other-model folder is scanned and the
+page shows an "enable" empty state until the user turns it on.
+
+### 11.1 Settings (global, not per-library)
+
+| key | type | default | meaning |
+|---|---|---|---|
+| `enable_other_models` | bool | `false` | master switch |
+| `enabled_other_sub_types` | list[str] | `["vae","upscaler","text_encoder"]` | allow-list; `clip_vision` and `controlnet` are opt-in (see §2) |
+
+`enabled_other_folders` (the unreleased, additive, no-UI backend key) was removed
+and replaced by the sub_type-level allow-list; there is no migration because the
+feature never shipped. `text_encoder` expands to `text_encoders` + legacy `clip`
+via `OTHER_SUB_TYPE_FOLDER_KEYS`.
+
+The default allow-list lives on five surfaces that must stay in sync:
+`DEFAULT_ENABLED_OTHER_SUB_TYPES` (`py/utils/constants.py`), `DEFAULT_SETTINGS`
+(`py/services/settings_manager.py`), the two `DEFAULT_SETTINGS_BASE` /
+`createDefaultSettings` lists (`static/js/state/index.js`), the
+`updateOtherModelsControls()` fallback (`static/js/managers/SettingsManager.js`)
+and the server-rendered Jinja fallback
+(`templates/components/modals/settings/library.html`).
+
+### 11.1.1 Legacy key handling in `Config._init_other_paths`
+
+ComfyUI's `folder_paths` rewrites legacy names before every access (`clip` →
+`text_encoders`, `unet` → `diffusion_models`) and registers both legacy
+directories under the canonical key, so `get_folder_paths("clip")` returns
+exactly the same list as `get_folder_paths("text_encoders")`. Querying both keys
+made the overlap guard fire twice with `please fix your path configuration` for a
+configuration the user cannot fix. `Config._collapse_legacy_folder_keys()` now
+drops a key when the host exposes `map_legacy` and resolves it to another queried
+key, and `_prepare_other_paths()` downgrades a same-`sub_type` duplicate to
+`debug` (a cross-`sub_type` collision still warns). In standalone mode
+`MockFolderPaths` has no `map_legacy` and its keys are independent
+`settings.json` entries, so every key is still queried there.
+
+`settings.json.example` intentionally stays minimal (only `use_portable_settings`,
+`civitai_api_key`, and the four core `folder_paths` keys: `loras`, `checkpoints`,
+`unet`, `embeddings`). Optional keys — including the other-model folder paths and
+`enable_other_models` — are NOT documented there; they live in `DEFAULT_SETTINGS`
+and reach the user's `settings.json` on demand. This supersedes the Phase-1/Phase-2
+notes that proposed adding the other-model folder keys to the example.
+
+### 11.2 Behaviour matrix
+
+| state | scan | nav / `/other` | other downloads | `default_other_roots` | Doctor / refresh-all |
+|---|---|---|---|---|---|
+| master off | nothing (`other_roots == []`) | nav entry hidden (`nav-item--hidden`); `/other` still renders the disabled empty state + Enable button; one-time dismissible announcement banner on first visit | rejected | preserved, never auto-set | scanner skipped |
+| sub_type off | that sub_type's folder keys excluded | page keeps working, type disappears from data | auto-routing refused (manual folder still allowed) | preserved, not preselected | normal |
+| all on (after enabling) | Phase-1/2 behaviour | normal | normal | normal | normal |
+
+### 11.3 Backend touch points
+
+- `py/utils/constants.py` — `DEFAULT_ENABLED_OTHER_SUB_TYPES`, `OTHER_SUB_TYPE_FOLDER_KEYS`, `normalize_other_sub_types`.
+- `py/config.py` — `_get_enabled_other_folder_keys()` is the single scan gate (master switch + allow-list); new `refresh_other_roots()` rebuilds roots + preview roots on toggle.
+- `py/services/settings_manager.py` — new defaults, `set()` normalization, `is_other_models_enabled()` / `get_enabled_other_sub_types()` / `is_other_sub_type_enabled()`, and `_apply_other_model_settings_change()` which reapplies config and calls `other_scanner.on_library_changed(reconcile=True)`.
+- `py/services/model_scanner.py` — `_should_keep_cached_entry()` hydration hook (default keep) plus `on_library_changed(reconcile=...)` / `initialize_in_background(reconcile=...)`; the hook filters `raw_data` and the hash/autov3 index rows.
+- `py/services/other_scanner.py` — drops persisted entries whose folder is no longer a managed root (sub_type is location-derived, so config is the source of truth).
+- `py/routes/other_routes.py` — `_validate_civitai_model_type` rejects everything while off / mapped-but-disabled sub_types; `_get_page_context_provider()` injects `other_disabled` into the template.
+- `py/routes/handlers/model_handlers.py` + `base_model_routes.py` — optional `page_context_provider` hook on `ModelPageView`.
+- `py/routes/handlers/download_routing_handlers.py` — returns `{sub_type: None, disabled: true, reason}` instead of guessing.
+- `py/services/download_manager.py` — rejects other-type downloads while off; disabled sub_type refuses default-path routing with a "pick a folder" error.
+- `py/routes/handlers/misc_handlers.py` — Doctor / init-status / refresh-all skip the other scanner while off (`_active_scanner_factories` / `_active_scanner_getters`).
+- `py/services/pending_delete_service.py` — deliberately untouched: the scanner stays registered so staged deletes still merge.
+
+### 11.4 Frontend
+
+Discoverability: the nav entry is hidden while the feature is off, and three
+lightweight surfaces replace it — a one-time announcement banner, the download
+toast, and the settings toggle itself.
+
+- `templates/components/header.html` + `static/css/components/header.css` — `nav-item--hidden` class (server-rendered when off, client-toggled after enabling) and the `fa-shapes` icon.
+- `templates/other.html` — `other_disabled` branch in `content` + `main_script`; page-scoped CSS for the empty state.
+- `static/js/other_disabled.js` — boots `appCore` (shared header) and delegates to the shared enable helper.
+- `static/js/utils/otherModels.js` — shared `enableOtherModels()` (POST settings + reload) and `openOtherModelsSettings()` (settings modal on the Library section); used by the disabled page, the banner and the download modal.
+- `static/js/managers/BannerService.js` — `other-models-announcement` banner (only when off and not dismissed; `priority: 0`, dismissal persisted via `dismissed_banners`) with Enable / Open Settings actions; `removeOtherModelsAnnouncement()` drops it without persisting a dismissal.
+- `templates/components/modals/settings/library.html` + `SettingsManager.updateOtherModelsControls()` / `saveEnabledOtherSubTypes()` / `updateOtherModelsNavVisibility()` — master toggle + five sub_type checkboxes; unchecked/disabled sub_types have their default-root select disabled.
+- `static/js/managers/DownloadManager.js` — a disabled routing answer surfaces a `showActionToast` with an "Enable Other Models" action (opening settings) and falls back to manual selection.
+- i18n: `settings.folderSettings.*`, `other.disabled.*` and `banners.otherModels.*` keys in `locales/en.json` + `scripts/sync_translation_keys.py` (other locales keep `[TODO: Translate]`).
+
+### 11.5 Cache consistency
+
+- Disabling purges rows from the in-memory view at hydration time (the
+  `_should_keep_cached_entry` hook) and from SQLite on the reconcile triggered by
+  the toggle; the `.metadata.json` sidecars survive, so re-enabling rescans
+  without recomputing hashes (critical for multi-GB text encoders).
+- Enabling triggers a reconcile so newly managed roots are scanned immediately.
+- Editing `settings.json` while the server is stopped is still covered by the
+  hydration hook, so disabled types never appear after a restart.
+
+### 11.6 Tests
+
+Backend: opt-in fixtures added to the other-related suites; new coverage for
+"default off scans nothing", per-sub_type gating, routing/download rejection,
+`_should_keep_cached_entry`, settings normalization and `other_disabled` page
+context. Frontend: `updateOtherModelsControls` / `saveEnabledOtherSubTypes` and
+the disabled-page enable flow.

docs/technical/reconcile_windows_case_fallback_todo.md

@@ -0,0 +1,92 @@
+# Reconcile 的 Windows 大小写回退分支 - 待验证清单
+
+> **状态**: 待 Windows 环境验证 | **创建日期**: 2026-09-11
+> **相关文件**: `py/services/model_scanner.py` (`ModelScanner._reconcile_cache`)
+> **相关历史**: #871 (`76ee59cd`, 路径重叠去重)、#1108 (按文件夹扫描的需求)
+
+---
+
+## 背景
+
+Refresh 按钮走的是 `_reconcile_cache()`（快速增量对账）。2026-09-11 做了一轮性能优化，把两处"预防性"的
+realpath 全量遍历改成按需触发（详见下方"已完成"）。优化后，一次零变更 Refresh 在 5 万文件库上从
+~1400 ms 降到 ~120 ms。
+
+清理过程中发现**唯一一处遗留的可疑点**：Windows 专属的大小写不敏感回退分支。它无法在 Linux 上验证，
+因此单独记录，留待 Windows 机器上确认。
+
+---
+
+## 待验证分支（现状）
+
+`py/services/model_scanner.py` 中 `_reconcile_cache()` 的 walk 循环内：
+
+```python
+# Try case-insensitive match on Windows
+if os.name == 'nt':
+    lower_path = file_path.lower()
+    matched = False
+    for cached_path in cached_paths:          # 每个未命中文件都全量扫一遍缓存
+        if cached_path.lower() == lower_path:
+            found_paths.add(cached_path)
+            matched = True
+            break
+    if matched:
+        continue
+```
+
+它排在精确匹配（`file_path in cached_paths`）和 realpath 别名匹配之后，只有**未命中**的文件才会走到。
+
+### 为什么可疑
+
+1. **可能不可达**：Windows 上 `os.path.realpath()` 会返回磁盘上的真实大小写，因此"缓存路径大小写与磁盘
+   不一致"的情形，理论上已经被上一步的 realpath 别名匹配覆盖。若如此，这段就是纯冗余代码。
+2. **一旦可达就是 O(N×M)**：每个未命中文件都要遍历全部 `cached_paths` 做小写比较。若某种路径写法让
+   整个库都变成"未命中"（例如缓存里的盘符/大小写形式与 walk 结果系统性不一致），一次 Refresh 会退化
+   成 文件数 × 缓存条目数 次字符串比较，比真实 IO 还贵。
+3. **没有测试覆盖**：`tests/services/test_model_scanner.py` 没有任何针对该分支的用例（它在 Linux 上
+   被 `os.name == 'nt'` 短路，无法覆盖）。
+
+---
+
+## 待办
+
+- [ ] **验证可达性**：在 Windows 上构造"缓存路径与磁盘真实大小写不一致"的场景，确认 realpath 别名匹配
+      是否已经命中，即上面的 `if os.name == 'nt'` 分支是否还有进入的必要。
+- [ ] **若不可达 / 冗余**：删除该分支，并在删除处留注释说明 realpath 已覆盖大小写归一（附验证记录）。
+- [ ] **若可达**：保留语义但改成 O(1)——预先构建一次 `lower_path -> cached_path` 映射（与
+      `cached_real_paths` 同样按需、懒构建），把内层全量扫描换成一次字典查询。
+- [ ] **补一个 Windows-only 的回归测试**（`pytest.mark.skipif(os.name != "nt", ...)`），锁定最终结论。
+- [ ] 把验证结论回填到本文件，并同步更新状态行。
+
+---
+
+## 验证方法（Windows）
+
+1. **构造不一致的大小写**：让缓存里的 `file_path` 与磁盘实际路径大小写不同（例如改过盘符/目录大小写，
+   或从另一台机器迁移了 `settings.json` 与持久化缓存），然后在 UI 点 Refresh。
+2. **看后端日志判据**：
+   - 若 realpath 已覆盖 → 日志应显示 `Cache reconciliation completed in X seconds. Added 0, removed 0 models.`，
+     且**没有** `Found N new files to process` / `Processing <path>`。
+   - 若回退分支在起作用 → 同样应该是 `Added 0, removed 0`（因为 `found_paths` 被补上），这是"分支可达"
+     的证据；反之若出现大量 `Processing ...` 并重新 hash，说明连回退分支也没命中，问题更严重
+     （缓存路径被当成了新文件 + 旧条目被删）。
+3. **跑测试**：`python -m pytest tests/services/test_model_scanner.py -k reconcile`（该文件在 Windows 上会
+   真实执行 `os.name == 'nt'` 分支）。
+4. **量化**：如果需要，可在 `_reconcile_cache` 里临时插桩统计该分支的进入次数与内层迭代次数，确认是否为 0。
+
+---
+
+## 已完成（本轮优化，供对照）
+
+同一次清理里已经落地并验证的部分（Linux，5 万文件库）：
+
+- `cached_real_paths` 别名映射改为**首次未命中时**懒构建（原来每次 Refresh 都对全部缓存条目算一次 realpath）。
+- 每个文件的 `realpath` 移到精确命中检查**之后**（原来对每个文件都算，命中即丢弃）。
+- `get_model_roots()` 在新增文件处理阶段只快照一次（原来每个新文件重读一次）。
+- 全量去重 pass 加了 O(1) 前置判断（`cached_size_before != len(cached_paths) or total_added > 0`），
+  零变更且缓存干净时跳过；快照本身含重复路径时仍会自愈。
+
+结果：零变更 Refresh 5 万文件 **~1400 ms → ~120 ms**；根目录顺序/符号链接别名翻转场景仍是
+`re-processed=0`（不重新读 metadata、不重新 hash）。测试：`tests/services/test_model_scanner.py`
+47 项、全量后端 2567 项全部通过。

locales/de.json

@@ -149,6 +149,7 @@
             "copyCheckpointName": "Checkpoint-Name kopieren",
             "copyEmbeddingName": "Embedding-Name kopieren",
             "embeddingNameCopied": "Embedding-Syntax kopiert",
+            "modelNameCopied": "Modellname kopiert",
             "sendCheckpointToWorkflow": "An ComfyUI senden",
             "sendEmbeddingToWorkflow": "An ComfyUI senden"
         },
@@ -216,9 +217,6 @@
             "label": "Rezepte lokalen Modellen neu zuordnen",
             "loading": "Rezepte werden lokalen Modellen neu zugeordnet...",
             "success": "{entries} Einträge in {recipes} Rezepten zugeordnet",
-            "successErrors": "{entries} Einträge in {recipes} Rezepten zugeordnet, {failures} fehlgeschlagen",
-            "allFailed": "Zuordnung fehlgeschlagen für {failures} von {total} Rezepten",
-            "noMatch": "Keine lokale Übereinstimmung für {entries} Einträge in {recipes} Rezepten gefunden",
             "cancelled": "Zuordnung abgebrochen. {recipes} Rezepte aktualisiert ({entries} Einträge)",
             "error": "Zuordnung der Rezepte fehlgeschlagen: {message}"
         },
@@ -236,6 +234,7 @@
             "recipes": "Rezepte",
             "checkpoints": "Checkpoints",
             "embeddings": "Embeddings",
+            "other": "Andere",
             "statistics": "Statistiken"
         },
         "search": {
@@ -536,6 +535,25 @@
             "defaultUnetRootHelp": "Legen Sie den Standard-Diffusion-Modell-(UNET)-Stammordner für Downloads, Importe und Verschiebungen fest",
             "defaultEmbeddingRoot": "Embedding-Stammordner",
             "defaultEmbeddingRootHelp": "Legen Sie den Standard-Embedding-Stammordner für Downloads, Importe und Verschiebungen fest",
+            "defaultVaeRoot": "VAE-Stammordner",
+            "defaultVaeRootHelp": "Legen Sie den Standard-VAE-Stammordner für Downloads, Importe und Verschiebungen fest",
+            "defaultUpscalerRoot": "Upscaler-Stammordner",
+            "defaultUpscalerRootHelp": "Legen Sie den Standard-Upscaler-Stammordner für Downloads, Importe und Verschiebungen fest",
+            "defaultTextEncoderRoot": "Text-Encoder-Stammordner",
+            "defaultTextEncoderRootHelp": "Legen Sie den Standard-Text-Encoder-Stammordner für Downloads, Importe und Verschiebungen fest",
+            "defaultClipVisionRoot": "CLIP-Vision-Stammordner",
+            "defaultClipVisionRootHelp": "Legen Sie den Standard-CLIP-Vision-Stammordner für Downloads, Importe und Verschiebungen fest",
+            "defaultControlnetRoot": "ControlNet-Stammordner",
+            "defaultControlnetRootHelp": "Legen Sie den Standard-ControlNet-Stammordner für Downloads, Importe und Verschiebungen fest",
+            "enableOtherModels": "Verwaltung weiterer Modelle",
+            "enableOtherModelsHelp": "Wenn deaktiviert, werden VAE-, Upscaler-, Text-Encoder-, CLIP-Vision- und ControlNet-Ordner nicht gescannt, die Seite für weitere Modelle bleibt deaktiviert und diese Modelltypen können nicht heruntergeladen werden.",
+            "otherSubTypes": "Verwaltete Modelltypen",
+            "otherSubTypesHelp": "Wählen Sie, welche Kategorien weiterer Modelle gescannt und auf der Seite für weitere Modelle angezeigt werden.",
+            "subTypeVae": "VAE",
+            "subTypeUpscaler": "Upscaler",
+            "subTypeTextEncoder": "Text Encoder",
+            "subTypeClipVision": "CLIP Vision",
+            "subTypeControlnet": "ControlNet",
             "recipesPath": "Rezepte-Speicherpfad",
             "recipesPathHelp": "Optionales benutzerdefiniertes Verzeichnis für gespeicherte Rezepte. Leer lassen, um den recipes-Ordner im ersten LoRA-Stammverzeichnis zu verwenden.",
             "recipesPathPlaceholder": "/path/to/recipes",
@@ -1204,6 +1222,26 @@
     "embeddings": {
         "title": "Embedding-Modelle"
     },
+    "other": {
+        "title": "Weitere Modelle",
+        "disabled": {
+            "title": "Die Verwaltung weiterer Modelle ist deaktiviert",
+            "description": "Aktivieren Sie die Option, um VAE-, Upscaler-, Text-Encoder-, CLIP-Vision- und ControlNet-Dateien zu scannen und zu verwalten und sie von CivitAI herunterzuladen.",
+            "enableButton": "Weitere Modelle aktivieren",
+            "hint": "Sie können die verwalteten Modelltypen später unter Einstellungen > Bibliothek ändern.",
+            "enableFailed": "Aktivierung weiterer Modelle fehlgeschlagen",
+            "downloadBlocked": "Die Verwaltung weiterer Modelle ist für diesen Modelltyp deaktiviert. Aktivieren Sie sie unter Einstellungen > Bibliothek, um diese Datei herunterzuladen.",
+            "enableAction": "Weitere Modelle aktivieren"
+        },
+        "noPaths": {
+            "title": "Keine Ordner für weitere Modelle gefunden",
+            "descriptionStandalone": "Die Verwaltung weiterer Modelle ist aktiviert, aber keiner der konfigurierten Modellordner existiert auf dem Datenträger. Fügen Sie die unten stehenden Ordnerpfade zu settings.json hinzu und starten Sie LoRA Manager neu.",
+            "hintStandalone": "Nur die oben aufgeführten Ordnerschlüssel werden gescannt; nicht benötigte Schlüssel können weggelassen werden.",
+            "descriptionComfyUI": "Die Verwaltung weiterer Modelle ist aktiviert, aber keiner der konfigurierten Modellordner existiert auf dem Datenträger. Fügen Sie die entsprechenden Modellordner zu Ihren ComfyUI-Modellpfaden hinzu und laden Sie diese Seite neu.",
+            "hintComfyUI": "Weitere Modelle werden aus den Ordnern vae, upscale_models, text_encoders, clip_vision und controlnet von ComfyUI gelesen.",
+            "openSettings": "Einstellungen öffnen"
+        }
+    },
     "sidebar": {
         "modelRoot": "Stammverzeichnis",
         "collapseAll": "Alle Ordner einklappen",
@@ -1501,6 +1539,41 @@
             "note": "Dateien werden mit Standard-Pfad-Vorlagen heruntergeladen. Dies kann je nach Anzahl der LoRAs eine Weile dauern.",
             "downloadButton": "{count} LoRA(s) herunterladen"
         },
+        "rematchOptions": {
+            "title": "Rezepte neu zuordnen",
+            "messageGlobal": "Alle Rezepte werden mit Ihrer lokalen Modellbibliothek abgeglichen.",
+            "messageSingle": "Dieses Rezept wird mit Ihrer lokalen Modellbibliothek abgeglichen.",
+            "messageBulk": "{count} ausgewählte Rezepte werden mit Ihrer lokalen Modellbibliothek abgeglichen.",
+            "relaxedLabel": "Fehlende Modelle auch per Dateiname neu verbinden",
+            "relaxedDescription": "Diese Modelle könnten auch per Download behoben werden — der Download ist genauer. Übereinstimmungen verknüpfen möglicherweise eine andere Version; sie werden zur Überprüfung aufgelistet und können rückgängig gemacht werden.",
+            "confirmButton": "Neu zuordnen"
+        },
+        "rematchResults": {
+            "undo": "Rückgängig",
+            "undone": "Rückgängig gemacht",
+            "undoFailed": "Rückgängigmachen der Neuordnung fehlgeschlagen: {message}"
+        },
+        "rematchSummary": {
+            "title": "Zusammenfassung der Neuordnung",
+            "successMessage": "{entries} Einträge zugeordnet",
+            "failed": "Neuordnung fehlgeschlagen",
+            "completedWithWarnings": "Neuordnung abgeschlossen — Überprüfung empfohlen",
+            "cancelledNote": "Der Vorgang wurde vorzeitig abgebrochen — die Zahlen sind unvollständig.",
+            "statMatched": "Zugeordnete Einträge",
+            "statReview": "Zu überprüfen",
+            "statUnresolved": "Nicht zugeordnet",
+            "statErrors": "Fehler",
+            "reviewSection": "Dateinamen-Übereinstimmungen zur Überprüfung ({count})",
+            "columnRecipe": "Rezept",
+            "columnEntry": "Eintrag",
+            "columnFile": "Zugeordnete Datei",
+            "columnUndo": "Rückgängig",
+            "copyReport": "Bericht kopieren",
+            "close": "Schließen",
+            "scope_global": "Alle Rezepte",
+            "scope_bulk": "Ausgewählte Rezepte",
+            "scope_single": "Einzelnes Rezept"
+        },
         "exampleAccess": {
             "title": "Lokale Beispielbilder",
             "message": "Keine lokalen Beispielbilder für dieses Modell gefunden. Ansichtsoptionen:",
@@ -1846,6 +1919,10 @@
             "title": "Embedding Manager wird initialisiert",
             "message": "Embedding-Cache wird gescannt und aufgebaut. Dies kann einige Minuten dauern..."
         },
+        "other": {
+            "title": "Manager für weitere Modelle wird initialisiert",
+            "message": "Modell-Cache wird gescannt und aufgebaut. Dies kann einige Minuten dauern..."
+        },
         "recipes": {
             "title": "Rezept Manager wird initialisiert",
             "message": "Rezepte werden geladen und verarbeitet. Dies kann einige Minuten dauern..."
@@ -2168,6 +2245,7 @@
             "createMissingData": "Erforderliche Daten zum Erstellen des Rezepts fehlen",
             "created": "Rezept erfolgreich erstellt",
             "noMissingLoras": "Keine fehlenden LoRAs zum Herunterladen",
+            "unresolvableMarkedForReconnect": "{count} nicht auflösbare Einträge markiert — sie können jetzt mit einem lokalen LoRA neu verbunden werden.",
             "noPreviousRecipe": "Kein vorheriges Rezept verfügbar",
             "noNextRecipe": "Kein weiteres Rezept verfügbar",
             "missingLorasInfoFailed": "Fehler beim Abrufen der Informationen für fehlende LoRAs",
@@ -2222,10 +2300,6 @@
             "batchImportBrowseFailed": "Ordner konnte nicht durchsucht werden: {message}",
             "batchImportDirectorySelected": "Verzeichnis ausgewählt: {path}",
             "noRecipesSelected": "Keine Rezepte ausgewählt",
-            "rematchComplete": "{entries} Einträge in {recipes} Rezepten zugeordnet",
-            "rematchCompleteErrors": "{entries} Einträge in {recipes} Rezepten zugeordnet, {failures} fehlgeschlagen",
-            "rematchAllFailed": "Zuordnung fehlgeschlagen für {failures} von {total} ausgewählten Rezepten",
-            "rematchUnmatched": "Keine lokale Übereinstimmung für {entries} Einträge in {recipes} Rezepten gefunden",
             "rematchSkipped": "Keine Zuordnung für die {total} ausgewählten Rezepte erforderlich",
             "rematchFailed": "Zuordnung der ausgewählten Rezepte fehlgeschlagen: {message}",
             "reimporting": "Rezept wird aus Quelle neu importiert...",
@@ -2304,6 +2378,7 @@
             "checkpointRootsFailed": "Fehler beim Laden der Checkpoint-Stammverzeichnisse: {message}",
             "unetRootsFailed": "Fehler beim Laden der Diffusion-Modell-Stammverzeichnisse: {message}",
             "embeddingRootsFailed": "Fehler beim Laden der Embedding-Stammverzeichnisse: {message}",
+            "otherRootsFailed": "Fehler beim Laden der Stammverzeichnisse weiterer Modelle: {message}",
             "mappingsUpdated": "Basismodell-Pfad-Zuordnungen aktualisiert ({count})",
             "mappingsCleared": "Basismodell-Pfad-Zuordnungen gelöscht",
             "mappingSaveFailed": "Fehler beim Speichern der Basismodell-Zuordnungen: {message}",
@@ -2566,6 +2641,12 @@
             "rebuilding": "Cache wird neu aufgebaut...",
             "rebuildFailed": "Fehler beim Neuaufbau des Caches: {error}",
             "retry": "Wiederholen"
+        },
+        "otherModels": {
+            "title": "Die Verwaltung weiterer Modelle ist verfügbar",
+            "content": "Scannen und verwalten Sie VAE-, Upscaler-, Text-Encoder-, CLIP-Vision- und ControlNet-Dateien und laden Sie sie von CivitAI herunter, alles auf einer eigenen Seite.",
+            "enable": "Weitere Modelle aktivieren",
+            "openSettings": "Einstellungen öffnen"
         }
     }
 }

locales/en.json

@@ -149,6 +149,7 @@
       "copyCheckpointName": "Copy checkpoint name",
       "copyEmbeddingName": "Copy embedding name",
       "embeddingNameCopied": "Embedding syntax copied",
+      "modelNameCopied": "Model name copied",
       "sendCheckpointToWorkflow": "Send to ComfyUI",
       "sendEmbeddingToWorkflow": "Send to ComfyUI"
     },
@@ -216,9 +217,6 @@
       "label": "Rematch recipes to local models",
       "loading": "Rematching recipes to local models...",
       "success": "Matched {entries} entries across {recipes} recipes",
-      "successErrors": "Matched {entries} entries across {recipes} recipes, {failures} failed",
-      "allFailed": "Rematch failed for {failures} of {total} recipes",
-      "noMatch": "No local match found for {entries} entries in {recipes} recipes",
       "cancelled": "Rematch cancelled. {recipes} recipes updated ({entries} entries).",
       "error": "Recipe rematch failed: {message}"
     },
@@ -236,6 +234,7 @@
       "recipes": "Recipes",
       "checkpoints": "Checkpoints",
       "embeddings": "Embeddings",
+      "other": "Other",
       "statistics": "Stats"
     },
     "search": {
@@ -536,6 +535,25 @@
       "defaultUnetRootHelp": "Set default diffusion model (UNET) root directory for downloads, imports and moves",
       "defaultEmbeddingRoot": "Embedding Root",
       "defaultEmbeddingRootHelp": "Set default embedding root directory for downloads, imports and moves",
+      "defaultVaeRoot": "VAE Root",
+      "defaultVaeRootHelp": "Set default VAE root directory for downloads, imports and moves",
+      "defaultUpscalerRoot": "Upscaler Root",
+      "defaultUpscalerRootHelp": "Set default upscaler root directory for downloads, imports and moves",
+      "defaultTextEncoderRoot": "Text Encoder Root",
+      "defaultTextEncoderRootHelp": "Set default text encoder root directory for downloads, imports and moves",
+      "defaultClipVisionRoot": "CLIP Vision Root",
+      "defaultClipVisionRootHelp": "Set default CLIP vision root directory for downloads, imports and moves",
+      "defaultControlnetRoot": "ControlNet Root",
+      "defaultControlnetRootHelp": "Set default ControlNet root directory for downloads, imports and moves",
+      "enableOtherModels": "Other Models Management",
+      "enableOtherModelsHelp": "When off, VAE / upscaler / text encoder / CLIP vision / ControlNet folders are not scanned, the Other Models page stays disabled, and these model types cannot be downloaded.",
+      "otherSubTypes": "Managed Types",
+      "otherSubTypesHelp": "Choose which other-model categories are scanned and shown on the Other Models page.",
+      "subTypeVae": "VAE",
+      "subTypeUpscaler": "Upscaler",
+      "subTypeTextEncoder": "Text Encoder",
+      "subTypeClipVision": "CLIP Vision",
+      "subTypeControlnet": "ControlNet",
       "recipesPath": "Recipes Storage Path",
       "recipesPathHelp": "Optional custom directory for stored recipes. Leave empty to use the first LoRA root's recipes folder.",
       "recipesPathPlaceholder": "/path/to/recipes",
@@ -1204,6 +1222,26 @@
   "embeddings": {
     "title": "Embedding Models"
   },
+  "other": {
+    "title": "Other Models",
+    "disabled": {
+      "title": "Other Models management is off",
+      "description": "Enable it to scan and manage VAE, upscaler, text encoder, CLIP vision and ControlNet files, and to download them from CivitAI.",
+      "enableButton": "Enable Other Models",
+      "hint": "You can change the managed model types later in Settings > Library.",
+      "enableFailed": "Failed to enable Other Models",
+      "downloadBlocked": "Other Models management is disabled for this model type. Enable it in Settings > Library to download this file.",
+      "enableAction": "Enable Other Models"
+    },
+    "noPaths": {
+      "title": "No other-model folders found",
+      "descriptionStandalone": "Other Models management is on, but none of the configured model folders exist on disk. Add the folder paths below to settings.json and restart LoRA Manager.",
+      "hintStandalone": "Only the folder keys listed above are scanned; keys you do not need can be omitted.",
+      "descriptionComfyUI": "Other Models management is on, but none of the configured model folders exist on disk. Add the matching model folders to your ComfyUI model paths, then reload this page.",
+      "hintComfyUI": "Other models are read from ComfyUI's vae, upscale_models, text_encoders, clip_vision and controlnet folders.",
+      "openSettings": "Open Settings"
+    }
+  },
   "sidebar": {
     "modelRoot": "Root",
     "collapseAll": "Collapse All Folders",
@@ -1501,6 +1539,41 @@
       "note": "Files will be downloaded using default path templates. This may take a while depending on the number of LoRAs.",
       "downloadButton": "Download {count} LoRA(s)"
     },
+    "rematchOptions": {
+      "title": "Rematch Recipes",
+      "messageGlobal": "All recipes will be scanned against your local model library.",
+      "messageSingle": "This recipe will be scanned against your local model library.",
+      "messageBulk": "{count} selected recipe(s) will be scanned against your local model library.",
+      "relaxedLabel": "Also reconnect missing models by file name",
+      "relaxedDescription": "These models could also be fixed by downloading — download is more accurate. Matches may link a different version; they'll be listed for review and can be undone.",
+      "confirmButton": "Rematch"
+    },
+    "rematchResults": {
+      "undo": "Undo",
+      "undone": "Undone",
+      "undoFailed": "Failed to undo rematch: {message}"
+    },
+    "rematchSummary": {
+      "title": "Rematch Summary",
+      "successMessage": "Matched {entries} entries",
+      "failed": "Rematch failed",
+      "completedWithWarnings": "Rematch completed — review recommended",
+      "cancelledNote": "Run cancelled before completion — counts are partial.",
+      "statMatched": "Matched entries",
+      "statReview": "Needs review",
+      "statUnresolved": "Unresolved",
+      "statErrors": "Errors",
+      "reviewSection": "Filename matches to review ({count})",
+      "columnRecipe": "Recipe",
+      "columnEntry": "Entry",
+      "columnFile": "Matched file",
+      "columnUndo": "Undo",
+      "copyReport": "Copy Report",
+      "close": "Close",
+      "scope_global": "All recipes",
+      "scope_bulk": "Selected recipes",
+      "scope_single": "Single recipe"
+    },
     "exampleAccess": {
       "title": "Local Example Images",
       "message": "No local example images found for this model. View options:",
@@ -1846,6 +1919,10 @@
       "title": "Initializing Embedding Manager",
       "message": "Scanning and building embedding cache. This may take a few minutes..."
     },
+    "other": {
+      "title": "Initializing Other Models Manager",
+      "message": "Scanning and building model cache. This may take a few minutes..."
+    },
     "recipes": {
       "title": "Initializing Recipe Manager",
       "message": "Loading and processing recipes. This may take a few minutes..."
@@ -2168,6 +2245,7 @@
       "createMissingData": "Missing required data to create recipe",
       "created": "Recipe created successfully",
       "noMissingLoras": "No missing LoRAs to download",
+      "unresolvableMarkedForReconnect": "{count} unresolvable entr(ies) marked — they can now be reconnected to a local LoRA.",
       "noPreviousRecipe": "No previous recipe available",
       "noNextRecipe": "No next recipe available",
       "missingLorasInfoFailed": "Failed to get information for missing LoRAs",
@@ -2222,10 +2300,6 @@
       "batchImportBrowseFailed": "Failed to browse directory: {message}",
       "batchImportDirectorySelected": "Directory selected: {path}",
       "noRecipesSelected": "No recipes selected",
-      "rematchComplete": "Matched {entries} entries across {recipes} recipes",
-      "rematchCompleteErrors": "Matched {entries} entries across {recipes} recipes, {failures} failed",
-      "rematchAllFailed": "Rematch failed for {failures} of {total} selected recipes",
-      "rematchUnmatched": "No local match found for {entries} entries in {recipes} recipes",
       "rematchSkipped": "No rematch needed for any of the {total} selected recipes",
       "rematchFailed": "Failed to rematch selected recipes: {message}",
       "reimporting": "Re-importing recipe from source...",
@@ -2304,6 +2378,7 @@
       "checkpointRootsFailed": "Failed to load checkpoint roots: {message}",
       "unetRootsFailed": "Failed to load diffusion model roots: {message}",
       "embeddingRootsFailed": "Failed to load embedding roots: {message}",
+      "otherRootsFailed": "Failed to load other model roots: {message}",
       "mappingsUpdated": "Base model path mappings updated ({count} mapping{plural})",
       "mappingsCleared": "Base model path mappings cleared",
       "mappingSaveFailed": "Failed to save base model mappings: {message}",
@@ -2566,6 +2641,12 @@
       "rebuilding": "Rebuilding cache...",
       "rebuildFailed": "Failed to rebuild cache: {error}",
       "retry": "Retry"
+    },
+    "otherModels": {
+      "title": "Other Models Management is available",
+      "content": "Scan and manage VAE, upscaler, text encoder, CLIP vision and ControlNet files — and download them from CivitAI — from one dedicated page.",
+      "enable": "Enable Other Models",
+      "openSettings": "Open Settings"
     }
   }
 }

locales/es.json

@@ -149,6 +149,7 @@
             "copyCheckpointName": "Copiar nombre del checkpoint",
             "copyEmbeddingName": "Copiar nombre del embedding",
             "embeddingNameCopied": "Sintaxis de embedding copiada",
+            "modelNameCopied": "Nombre del modelo copiado",
             "sendCheckpointToWorkflow": "Enviar a ComfyUI",
             "sendEmbeddingToWorkflow": "Enviar a ComfyUI"
         },
@@ -216,9 +217,6 @@
             "label": "Reasociar recetas con modelos locales",
             "loading": "Reasociando recetas con modelos locales...",
             "success": "{entries} entradas asociadas en {recipes} recetas",
-            "successErrors": "{entries} entradas asociadas en {recipes} recetas, {failures} fallidas",
-            "allFailed": "Falló la reasociación de {failures} de {total} recetas",
-            "noMatch": "No se encontró coincidencia local para {entries} entradas en {recipes} recetas",
             "cancelled": "Reasociación cancelada. {recipes} recetas actualizadas ({entries} entradas)",
             "error": "Falló la reasociación de recetas: {message}"
         },
@@ -236,6 +234,7 @@
             "recipes": "Recetas",
             "checkpoints": "Checkpoints",
             "embeddings": "Embeddings",
+            "other": "Otros",
             "statistics": "Estadísticas"
         },
         "search": {
@@ -536,6 +535,25 @@
             "defaultUnetRootHelp": "Establecer el directorio raíz predeterminado de Diffusion Model (UNET) para descargas, importaciones y movimientos",
             "defaultEmbeddingRoot": "Raíz de embedding",
             "defaultEmbeddingRootHelp": "Establecer el directorio raíz predeterminado de embedding para descargas, importaciones y movimientos",
+            "defaultVaeRoot": "Raíz de VAE",
+            "defaultVaeRootHelp": "Establecer el directorio raíz predeterminado de VAE para descargas, importaciones y movimientos",
+            "defaultUpscalerRoot": "Raíz de Upscaler",
+            "defaultUpscalerRootHelp": "Establecer el directorio raíz predeterminado de Upscaler para descargas, importaciones y movimientos",
+            "defaultTextEncoderRoot": "Raíz de Text Encoder",
+            "defaultTextEncoderRootHelp": "Establecer el directorio raíz predeterminado de Text Encoder para descargas, importaciones y movimientos",
+            "defaultClipVisionRoot": "Raíz de CLIP Vision",
+            "defaultClipVisionRootHelp": "Establecer el directorio raíz predeterminado de CLIP Vision para descargas, importaciones y movimientos",
+            "defaultControlnetRoot": "Raíz de ControlNet",
+            "defaultControlnetRootHelp": "Establecer el directorio raíz predeterminado de ControlNet para descargas, importaciones y movimientos",
+            "enableOtherModels": "Gestión de otros modelos",
+            "enableOtherModelsHelp": "Cuando está desactivado, las carpetas VAE / Upscaler / Text Encoder / CLIP Vision / ControlNet no se escanean, la página Otros modelos permanece desactivada y estos tipos de modelos no se pueden descargar.",
+            "otherSubTypes": "Tipos de modelos gestionados",
+            "otherSubTypesHelp": "Elige qué categorías de otros modelos se escanean y se muestran en la página Otros modelos.",
+            "subTypeVae": "VAE",
+            "subTypeUpscaler": "Upscaler",
+            "subTypeTextEncoder": "Text Encoder",
+            "subTypeClipVision": "CLIP Vision",
+            "subTypeControlnet": "ControlNet",
             "recipesPath": "Ruta de almacenamiento de recetas",
             "recipesPathHelp": "Directorio personalizado opcional para las recetas guardadas. Déjalo vacío para usar la carpeta recipes del primer directorio raíz de LoRA.",
             "recipesPathPlaceholder": "/path/to/recipes",
@@ -1204,6 +1222,26 @@
     "embeddings": {
         "title": "Modelos embedding"
     },
+    "other": {
+        "title": "Otros modelos",
+        "disabled": {
+            "title": "La gestión de otros modelos está desactivada",
+            "description": "Actívala para escanear y gestionar archivos VAE, Upscaler, Text Encoder, CLIP Vision y ControlNet, y para descargarlos desde CivitAI.",
+            "enableButton": "Activar otros modelos",
+            "hint": "Puedes cambiar los tipos de modelos gestionados más adelante en Configuración > Biblioteca.",
+            "enableFailed": "No se pudieron activar los otros modelos",
+            "downloadBlocked": "La gestión de otros modelos está desactivada para este tipo de modelo. Actívala en Configuración > Biblioteca para descargar este archivo.",
+            "enableAction": "Activar otros modelos"
+        },
+        "noPaths": {
+            "title": "No se encontraron carpetas de otros modelos",
+            "descriptionStandalone": "La gestión de otros modelos está activada, pero ninguna de las carpetas de modelos configuradas existe en el disco. Añade las rutas de carpetas de abajo a settings.json y reinicia LoRA Manager.",
+            "hintStandalone": "Solo se escanean las claves de carpeta listadas arriba; las claves que no necesites puedes omitirlas.",
+            "descriptionComfyUI": "La gestión de otros modelos está activada, pero ninguna de las carpetas de modelos configuradas existe en el disco. Añade las carpetas de modelos correspondientes a tus rutas de modelos de ComfyUI y recarga esta página.",
+            "hintComfyUI": "Los otros modelos se leen de las carpetas vae, upscale_models, text_encoders, clip_vision y controlnet de ComfyUI.",
+            "openSettings": "Abrir configuración"
+        }
+    },
     "sidebar": {
         "modelRoot": "Raíz",
         "collapseAll": "Colapsar todas las carpetas",
@@ -1501,6 +1539,41 @@
             "note": "Los archivos se descargarán usando las plantillas de ruta predeterminadas. Esto puede tomar un tiempo dependiendo del número de LoRAs.",
             "downloadButton": "Descargar {count} LoRA(s)"
         },
+        "rematchOptions": {
+            "title": "Reasociar recetas",
+            "messageGlobal": "Se escanearán todas las recetas contra tu biblioteca local de modelos.",
+            "messageSingle": "Se escaneará esta receta contra tu biblioteca local de modelos.",
+            "messageBulk": "Se escanearán {count} receta(s) seleccionada(s) contra tu biblioteca local de modelos.",
+            "relaxedLabel": "Reconectar también los modelos faltantes por nombre de archivo",
+            "relaxedDescription": "Estos modelos también se pueden corregir descargándolos; la descarga es más precisa. Las coincidencias pueden enlazar una versión diferente; se listarán para su revisión y se pueden deshacer.",
+            "confirmButton": "Reasociar"
+        },
+        "rematchResults": {
+            "undo": "Deshacer",
+            "undone": "Deshecho",
+            "undoFailed": "No se pudo deshacer la reasociación: {message}"
+        },
+        "rematchSummary": {
+            "title": "Resumen de la reasociación",
+            "successMessage": "{entries} entradas asociadas",
+            "failed": "Falló la reasociación",
+            "completedWithWarnings": "Reasociación completada — se recomienda revisar",
+            "cancelledNote": "Ejecución cancelada antes de completarse — los recuentos son parciales.",
+            "statMatched": "Entradas asociadas",
+            "statReview": "Por revisar",
+            "statUnresolved": "Sin coincidencia",
+            "statErrors": "Errores",
+            "reviewSection": "Coincidencias por nombre de archivo para revisar ({count})",
+            "columnRecipe": "Receta",
+            "columnEntry": "Entrada",
+            "columnFile": "Archivo coincidente",
+            "columnUndo": "Deshacer",
+            "copyReport": "Copiar informe",
+            "close": "Cerrar",
+            "scope_global": "Todas las recetas",
+            "scope_bulk": "Recetas seleccionadas",
+            "scope_single": "Receta individual"
+        },
         "exampleAccess": {
             "title": "Imágenes de ejemplo locales",
             "message": "No se encontraron imágenes de ejemplo locales para este modelo. Opciones de visualización:",
@@ -1846,6 +1919,10 @@
             "title": "Inicializando gestor de embedding",
             "message": "Escaneando y construyendo caché de embedding. Esto puede tomar unos minutos..."
         },
+        "other": {
+            "title": "Inicializando el gestor de otros modelos",
+            "message": "Escaneando y construyendo la caché de modelos. Esto puede tomar unos minutos..."
+        },
         "recipes": {
             "title": "Inicializando gestor de recetas",
             "message": "Cargando y procesando recetas. Esto puede tomar unos minutos..."
@@ -2168,6 +2245,7 @@
             "createMissingData": "Faltan datos necesarios para crear la receta",
             "created": "Receta creada exitosamente",
             "noMissingLoras": "No hay LoRAs faltantes para descargar",
+            "unresolvableMarkedForReconnect": "Se marcaron {count} entrada(s) no resoluble(s) — ahora se pueden reconectar a un LoRA local.",
             "noPreviousRecipe": "No hay receta anterior disponible",
             "noNextRecipe": "No hay siguiente receta disponible",
             "missingLorasInfoFailed": "Error al obtener información de LoRAs faltantes",
@@ -2222,10 +2300,6 @@
             "batchImportBrowseFailed": "No se pudo examinar el directorio: {message}",
             "batchImportDirectorySelected": "Directorio seleccionado: {path}",
             "noRecipesSelected": "No se han seleccionado recetas",
-            "rematchComplete": "{entries} entradas asociadas en {recipes} recetas",
-            "rematchCompleteErrors": "{entries} entradas asociadas en {recipes} recetas, {failures} fallidas",
-            "rematchAllFailed": "Falló la reasociación de {failures} de {total} recetas seleccionadas",
-            "rematchUnmatched": "No se encontró coincidencia local para {entries} entradas en {recipes} recetas",
             "rematchSkipped": "Ninguna de las {total} recetas seleccionadas necesita reasociación",
             "rematchFailed": "Falló la reasociación de las recetas seleccionadas: {message}",
             "reimporting": "Reimportando receta desde origen...",
@@ -2304,6 +2378,7 @@
             "checkpointRootsFailed": "Error al cargar raíces de checkpoint: {message}",
             "unetRootsFailed": "Error al cargar raíces de Diffusion Model: {message}",
             "embeddingRootsFailed": "Error al cargar raíces de embedding: {message}",
+            "otherRootsFailed": "Error al cargar raíces de otros modelos: {message}",
             "mappingsUpdated": "Mapeos de rutas de modelo base actualizados ({count} mapeo{plural})",
             "mappingsCleared": "Mapeos de rutas de modelo base limpiados",
             "mappingSaveFailed": "Error al guardar mapeos de modelo base: {message}",
@@ -2566,6 +2641,12 @@
             "rebuilding": "Reconstruyendo caché...",
             "rebuildFailed": "Error al reconstruir la caché: {error}",
             "retry": "Reintentar"
+        },
+        "otherModels": {
+            "title": "La gestión de otros modelos ya está disponible",
+            "content": "Escanea y gestiona archivos VAE, Upscaler, Text Encoder, CLIP Vision y ControlNet, y descárgalos desde CivitAI, todo desde una página dedicada.",
+            "enable": "Activar otros modelos",
+            "openSettings": "Abrir configuración"
         }
     }
 }

locales/fr.json

@@ -149,6 +149,7 @@
             "copyCheckpointName": "Copier le nom du checkpoint",
             "copyEmbeddingName": "Copier le nom de l'embedding",
             "embeddingNameCopied": "Syntaxe dembedding copiée",
+            "modelNameCopied": "Nom du modèle copié",
             "sendCheckpointToWorkflow": "Envoyer vers ComfyUI",
             "sendEmbeddingToWorkflow": "Envoyer vers ComfyUI"
         },
@@ -216,9 +217,6 @@
             "label": "Réassocier les Recipes aux modèles locaux",
             "loading": "Réassociation des Recipes aux modèles locaux...",
             "success": "{entries} entrées associées dans {recipes} Recipes",
-            "successErrors": "{entries} entrées associées dans {recipes} Recipes, {failures} échecs",
-            "allFailed": "Échec de la réassociation de {failures} Recipes sur {total}",
-            "noMatch": "Aucune correspondance locale trouvée pour {entries} entrées dans {recipes} Recipes",
             "cancelled": "Réassociation annulée. {recipes} Recipes mises à jour ({entries} entrées)",
             "error": "Échec de la réassociation des Recipes : {message}"
         },
@@ -236,6 +234,7 @@
             "recipes": "Recipes",
             "checkpoints": "Checkpoints",
             "embeddings": "Embeddings",
+            "other": "Autres",
             "statistics": "Statistiques"
         },
         "search": {
@@ -536,6 +535,25 @@
             "defaultUnetRootHelp": "Définir le répertoire racine Diffusion Model (UNET) par défaut pour les téléchargements, imports et déplacements",
             "defaultEmbeddingRoot": "Racine Embedding",
             "defaultEmbeddingRootHelp": "Définir le répertoire racine embedding par défaut pour les téléchargements, imports et déplacements",
+            "defaultVaeRoot": "Racine VAE",
+            "defaultVaeRootHelp": "Définir le répertoire racine VAE par défaut pour les téléchargements, imports et déplacements",
+            "defaultUpscalerRoot": "Racine Upscaler",
+            "defaultUpscalerRootHelp": "Définir le répertoire racine Upscaler par défaut pour les téléchargements, imports et déplacements",
+            "defaultTextEncoderRoot": "Racine Text Encoder",
+            "defaultTextEncoderRootHelp": "Définir le répertoire racine Text Encoder par défaut pour les téléchargements, imports et déplacements",
+            "defaultClipVisionRoot": "Racine CLIP Vision",
+            "defaultClipVisionRootHelp": "Définir le répertoire racine CLIP Vision par défaut pour les téléchargements, imports et déplacements",
+            "defaultControlnetRoot": "Racine ControlNet",
+            "defaultControlnetRootHelp": "Définir le répertoire racine ControlNet par défaut pour les téléchargements, imports et déplacements",
+            "enableOtherModels": "Gestion des autres modèles",
+            "enableOtherModelsHelp": "Lorsque cette option est désactivée, les dossiers VAE / Upscaler / Text Encoder / CLIP Vision / ControlNet ne sont pas analysés, la page Autres modèles reste désactivée et ces types de modèles ne peuvent pas être téléchargés.",
+            "otherSubTypes": "Types de modèles gérés",
+            "otherSubTypesHelp": "Choisissez les catégories d’autres modèles analysées et affichées sur la page Autres modèles.",
+            "subTypeVae": "VAE",
+            "subTypeUpscaler": "Upscaler",
+            "subTypeTextEncoder": "Text Encoder",
+            "subTypeClipVision": "CLIP Vision",
+            "subTypeControlnet": "ControlNet",
             "recipesPath": "Chemin de stockage des Recipes",
             "recipesPathHelp": "Dossier personnalisé facultatif pour les Recipes enregistrées. Laissez vide pour utiliser le dossier recipes de la première racine LoRA.",
             "recipesPathPlaceholder": "/path/to/recipes",
@@ -1204,6 +1222,26 @@
     "embeddings": {
         "title": "Modèles Embedding"
     },
+    "other": {
+        "title": "Autres modèles",
+        "disabled": {
+            "title": "La gestion des autres modèles est désactivée",
+            "description": "Activez-la pour analyser et gérer les fichiers VAE, Upscaler, Text Encoder, CLIP Vision et ControlNet, et pour les télécharger depuis CivitAI.",
+            "enableButton": "Activer les autres modèles",
+            "hint": "Vous pourrez modifier les types de modèles gérés plus tard dans Paramètres > Bibliothèque.",
+            "enableFailed": "Échec de l’activation des autres modèles",
+            "downloadBlocked": "La gestion des autres modèles est désactivée pour ce type de modèle. Activez-la dans Paramètres > Bibliothèque pour télécharger ce fichier.",
+            "enableAction": "Activer les autres modèles"
+        },
+        "noPaths": {
+            "title": "Aucun dossier d’autres modèles trouvé",
+            "descriptionStandalone": "La gestion des autres modèles est activée, mais aucun des dossiers de modèles configurés n’existe sur le disque. Ajoutez les chemins de dossiers ci-dessous à settings.json, puis redémarrez LoRA Manager.",
+            "hintStandalone": "Seules les clés de dossiers listées ci-dessus sont analysées ; les clés inutiles peuvent être omises.",
+            "descriptionComfyUI": "La gestion des autres modèles est activée, mais aucun des dossiers de modèles configurés n’existe sur le disque. Ajoutez les dossiers de modèles correspondants à vos chemins de modèles ComfyUI, puis rechargez cette page.",
+            "hintComfyUI": "Les autres modèles sont lus depuis les dossiers vae, upscale_models, text_encoders, clip_vision et controlnet de ComfyUI.",
+            "openSettings": "Ouvrir les paramètres"
+        }
+    },
     "sidebar": {
         "modelRoot": "Racine",
         "collapseAll": "Réduire tous les dossiers",
@@ -1501,6 +1539,41 @@
             "note": "Les fichiers seront téléchargés en utilisant les modèles de chemins par défaut. Cela peut prendre un certain temps selon le nombre de LoRAs.",
             "downloadButton": "Télécharger {count} LoRA(s)"
         },
+        "rematchOptions": {
+            "title": "Réassocier les Recipes",
+            "messageGlobal": "Toutes les Recipes seront analysées par rapport à votre bibliothèque de modèles locale.",
+            "messageSingle": "Cette Recipe sera analysée par rapport à votre bibliothèque de modèles locale.",
+            "messageBulk": "{count} Recipes sélectionnées seront analysées par rapport à votre bibliothèque de modèles locale.",
+            "relaxedLabel": "Reconnecter aussi les modèles manquants par nom de fichier",
+            "relaxedDescription": "Ces modèles peuvent aussi être corrigés par téléchargement — le téléchargement est plus précis. Les correspondances peuvent associer une version différente ; elles seront listées pour vérification et peuvent être annulées.",
+            "confirmButton": "Réassocier"
+        },
+        "rematchResults": {
+            "undo": "Annuler",
+            "undone": "Annulé",
+            "undoFailed": "Échec de l'annulation de la réassociation : {message}"
+        },
+        "rematchSummary": {
+            "title": "Résumé de la réassociation",
+            "successMessage": "{entries} entrées associées",
+            "failed": "Échec de la réassociation",
+            "completedWithWarnings": "Réassociation terminée — vérification recommandée",
+            "cancelledNote": "Exécution annulée avant la fin — les décomptes sont partiels.",
+            "statMatched": "Entrées associées",
+            "statReview": "À vérifier",
+            "statUnresolved": "Sans correspondance",
+            "statErrors": "Erreurs",
+            "reviewSection": "Correspondances par nom de fichier à vérifier ({count})",
+            "columnRecipe": "Recipe",
+            "columnEntry": "Entrée",
+            "columnFile": "Fichier correspondant",
+            "columnUndo": "Annuler",
+            "copyReport": "Copier le rapport",
+            "close": "Fermer",
+            "scope_global": "Toutes les Recipes",
+            "scope_bulk": "Recipes sélectionnées",
+            "scope_single": "Une seule Recipe"
+        },
         "exampleAccess": {
             "title": "Images d'exemple locales",
             "message": "Aucune image d'exemple locale trouvée pour ce modèle. Options d'affichage :",
@@ -1846,6 +1919,10 @@
             "title": "Initialisation du gestionnaire Embedding",
             "message": "Scan et construction du cache embedding. Cela peut prendre quelques minutes..."
         },
+        "other": {
+            "title": "Initialisation du gestionnaire Autres modèles",
+            "message": "Analyse et construction du cache de modèles. Cela peut prendre quelques minutes..."
+        },
         "recipes": {
             "title": "Initialisation du gestionnaire de recipes",
             "message": "Chargement et traitement des recipes. Cela peut prendre quelques minutes..."
@@ -2168,6 +2245,7 @@
             "createMissingData": "Données requises manquantes pour créer le Recipe",
             "created": "Recipe créé avec succès",
             "noMissingLoras": "Aucun LoRA manquant à télécharger",
+            "unresolvableMarkedForReconnect": "{count} entrées irrésolubles marquées — elles peuvent maintenant être reconnectées à un LoRA local.",
             "noPreviousRecipe": "Aucune Recipe précédente",
             "noNextRecipe": "Aucune Recipe suivante",
             "missingLorasInfoFailed": "Échec de l'obtention des informations pour les LoRAs manquants",
@@ -2222,10 +2300,6 @@
             "batchImportBrowseFailed": "Échec de la navigation dans le dossier : {message}",
             "batchImportDirectorySelected": "Dossier sélectionné : {path}",
             "noRecipesSelected": "Aucune Recipe sélectionnée",
-            "rematchComplete": "{entries} entrées associées dans {recipes} Recipes",
-            "rematchCompleteErrors": "{entries} entrées associées dans {recipes} Recipes, {failures} échecs",
-            "rematchAllFailed": "Échec de la réassociation de {failures} Recipes sélectionnées sur {total}",
-            "rematchUnmatched": "Aucune correspondance locale trouvée pour {entries} entrées dans {recipes} Recipes",
             "rematchSkipped": "Aucune des {total} Recipes sélectionnées ne nécessite de réassociation",
             "rematchFailed": "Échec de la réassociation des Recipes sélectionnées : {message}",
             "reimporting": "Ré-import de la Recipe depuis la source...",
@@ -2304,6 +2378,7 @@
             "checkpointRootsFailed": "Échec du chargement des racines checkpoint : {message}",
             "unetRootsFailed": "Échec du chargement des racines Diffusion Model : {message}",
             "embeddingRootsFailed": "Échec du chargement des racines embedding : {message}",
+            "otherRootsFailed": "Échec du chargement des racines des autres modèles : {message}",
             "mappingsUpdated": "Mappages de chemin de modèle de base mis à jour ({count} mappage{plural})",
             "mappingsCleared": "Mappages de chemin de modèle de base effacés",
             "mappingSaveFailed": "Échec de la sauvegarde des mappages de modèle de base : {message}",
@@ -2566,6 +2641,12 @@
             "rebuilding": "Reconstruction du cache...",
             "rebuildFailed": "Échec de la reconstruction du cache : {error}",
             "retry": "Réessayer"
+        },
+        "otherModels": {
+            "title": "La gestion des autres modèles est disponible",
+            "content": "Analysez et gérez les fichiers VAE, Upscaler, Text Encoder, CLIP Vision et ControlNet, et téléchargez-les depuis CivitAI, le tout depuis une page dédiée.",
+            "enable": "Activer les autres modèles",
+            "openSettings": "Ouvrir les paramètres"
         }
     }
 }

locales/he.json

@@ -149,6 +149,7 @@
             "copyCheckpointName": "העתק שם Checkpoint",
             "copyEmbeddingName": "העתק שם Embedding",
             "embeddingNameCopied": "תחביר Embedding הועתק",
+            "modelNameCopied": "שם המודל הועתק",
             "sendCheckpointToWorkflow": "שלח ל-ComfyUI",
             "sendEmbeddingToWorkflow": "שלח ל-ComfyUI"
         },
@@ -216,9 +217,6 @@
             "label": "התאמה מחדש של מתכונים למודלים מקומיים",
             "loading": "מתבצעת התאמה מחדש של מתכונים למודלים מקומיים...",
             "success": "הותאמו {entries} פריטים ב־{recipes} מתכונים",
-            "successErrors": "הותאמו {entries} פריטים ב־{recipes} מתכונים, {failures} נכשלו",
-            "allFailed": "ההתאמה נכשלה עבור {failures} מתוך {total} מתכונים",
-            "noMatch": "לא נמצאה התאמה מקומית עבור {entries} פריטים ב־{recipes} מתכונים",
             "cancelled": "ההתאמה בוטלה. עודכנו {recipes} מתכונים ({entries} פריטים)",
             "error": "ההתאמה מחדש של המתכונים נכשלה: {message}"
         },
@@ -236,6 +234,7 @@
             "recipes": "מתכונים",
             "checkpoints": "Checkpoints",
             "embeddings": "Embeddings",
+            "other": "אחרים",
             "statistics": "סטטיסטיקה"
         },
         "search": {
@@ -536,6 +535,25 @@
             "defaultUnetRootHelp": "הגדר את ספריית השורש המוגדרת כברירת מחדל של Diffusion Model (UNET) להורדות, ייבוא והעברות",
             "defaultEmbeddingRoot": "תיקיית שורש Embedding",
             "defaultEmbeddingRootHelp": "הגדר את ספריית השורש המוגדרת כברירת מחדל של embedding להורדות, ייבוא והעברות",
+            "defaultVaeRoot": "תיקיית שורש VAE",
+            "defaultVaeRootHelp": "הגדר את ספריית השורש המוגדרת כברירת מחדל של VAE להורדות, ייבוא והעברות",
+            "defaultUpscalerRoot": "תיקיית שורש Upscaler",
+            "defaultUpscalerRootHelp": "הגדר את ספריית השורש המוגדרת כברירת מחדל של Upscaler להורדות, ייבוא והעברות",
+            "defaultTextEncoderRoot": "תיקיית שורש Text Encoder",
+            "defaultTextEncoderRootHelp": "הגדר את ספריית השורש המוגדרת כברירת מחדל של Text Encoder להורדות, ייבוא והעברות",
+            "defaultClipVisionRoot": "תיקיית שורש CLIP Vision",
+            "defaultClipVisionRootHelp": "הגדר את ספריית השורש המוגדרת כברירת מחדל של CLIP Vision להורדות, ייבוא והעברות",
+            "defaultControlnetRoot": "תיקיית שורש ControlNet",
+            "defaultControlnetRootHelp": "הגדר את ספריית השורש המוגדרת כברירת מחדל של ControlNet להורדות, ייבוא והעברות",
+            "enableOtherModels": "ניהול מודלים אחרים",
+            "enableOtherModelsHelp": "כשהאפשרות כבויה, תיקיות VAE / Upscaler / Text Encoder / CLIP Vision / ControlNet אינן נסרקות, עמוד המודלים האחרים נשאר מושבת ולא ניתן להוריד סוגי מודלים אלה.",
+            "otherSubTypes": "סוגי מודלים מנוהלים",
+            "otherSubTypesHelp": "בחר אילו קטגוריות של מודלים אחרים ייסרקו ויוצגו בעמוד המודלים האחרים.",
+            "subTypeVae": "VAE",
+            "subTypeUpscaler": "Upscaler",
+            "subTypeTextEncoder": "Text Encoder",
+            "subTypeClipVision": "CLIP Vision",
+            "subTypeControlnet": "ControlNet",
             "recipesPath": "נתיב אחסון מתכונים",
             "recipesPathHelp": "ספרייה מותאמת אישית אופציונלית למתכונים שנשמרו. השאר ריק כדי להשתמש בתיקיית recipes של שורש LoRA הראשון.",
             "recipesPathPlaceholder": "/path/to/recipes",
@@ -1204,6 +1222,26 @@
     "embeddings": {
         "title": "מודלי Embedding"
     },
+    "other": {
+        "title": "מודלים אחרים",
+        "disabled": {
+            "title": "ניהול המודלים האחרים כבוי",
+            "description": "הפעל כדי לסרוק ולנהל קבצי VAE, Upscaler, Text Encoder, CLIP Vision ו-ControlNet, ולהוריד אותם מ-CivitAI.",
+            "enableButton": "הפעל מודלים אחרים",
+            "hint": "ניתן לשנות את סוגי המודלים המנוהלים מאוחר יותר בהגדרות > ספרייה.",
+            "enableFailed": "הפעלת המודלים האחרים נכשלה",
+            "downloadBlocked": "ניהול המודלים האחרים מושבת עבור סוג מודל זה. הפעל אותו בהגדרות > ספרייה כדי להוריד קובץ זה.",
+            "enableAction": "הפעל מודלים אחרים"
+        },
+        "noPaths": {
+            "title": "לא נמצאו תיקיות של מודלים אחרים",
+            "descriptionStandalone": "ניהול המודלים האחרים פועל, אך אף אחת מתיקיות המודלים המוגדרות אינה קיימת בדיסק. הוסף את נתיבי התיקיות שלמטה ל-settings.json והפעל מחדש את LoRA Manager.",
+            "hintStandalone": "רק מפתחות התיקיות המפורטים למעלה נסרקים; ניתן להשמיט מפתחות שאינך צריך.",
+            "descriptionComfyUI": "ניהול המודלים האחרים פועל, אך אף אחת מתיקיות המודלים המוגדרות אינה קיימת בדיסק. הוסף את תיקיות המודלים המתאימות לנתיבי המודלים של ComfyUI וטען מחדש עמוד זה.",
+            "hintComfyUI": "מודלים אחרים נקראים מתיקיות vae, upscale_models, text_encoders, clip_vision ו-controlnet של ComfyUI.",
+            "openSettings": "פתח הגדרות"
+        }
+    },
     "sidebar": {
         "modelRoot": "שורש",
         "collapseAll": "כווץ את כל התיקיות",
@@ -1501,6 +1539,41 @@
             "note": "הקבצים יורדו באמצעות תבניות נתיב ברירת מחדל. זה עשוי לקחת זמן בהתאם למספר ה-LoRAs.",
             "downloadButton": "הורד {count} LoRA(s)"
         },
+        "rematchOptions": {
+            "title": "התאמה מחדש של מתכונים",
+            "messageGlobal": "כל המתכונים ייסרקו מול ספריית המודלים המקומית שלך.",
+            "messageSingle": "מתכון זה ייסרק מול ספריית המודלים המקומית שלך.",
+            "messageBulk": "{count} מתכונים שנבחרו ייסרקו מול ספריית המודלים המקומית שלך.",
+            "relaxedLabel": "חבר מחדש גם מודלים חסרים לפי שם קובץ",
+            "relaxedDescription": "אפשר לתקן את המודלים האלה גם על ידי הורדה — ההורדה מדויקת יותר. ההתאמות עשויות לקשר לגרסה אחרת; הן יוצגו לסקירה וניתן לבטל אותן.",
+            "confirmButton": "התאם מחדש"
+        },
+        "rematchResults": {
+            "undo": "בטל",
+            "undone": "בוטל",
+            "undoFailed": "ביטול ההתאמה מחדש נכשל: {message}"
+        },
+        "rematchSummary": {
+            "title": "סיכום התאמה מחדש",
+            "successMessage": "הותאמו {entries} פריטים",
+            "failed": "ההתאמה מחדש נכשלה",
+            "completedWithWarnings": "ההתאמה מחדש הושלמה — מומלץ לסקור",
+            "cancelledNote": "ההתאמה בוטלה לפני שהסתיימה — המספרים חלקיים.",
+            "statMatched": "פריטים שהותאמו",
+            "statReview": "טעוני סקירה",
+            "statUnresolved": "ללא התאמה",
+            "statErrors": "שגיאות",
+            "reviewSection": "התאמות לפי שם קובץ לסקירה ({count})",
+            "columnRecipe": "מתכון",
+            "columnEntry": "פריט",
+            "columnFile": "הקובץ שהותאם",
+            "columnUndo": "בטל",
+            "copyReport": "העתק דוח",
+            "close": "סגור",
+            "scope_global": "כל המתכונים",
+            "scope_bulk": "מתכונים שנבחרו",
+            "scope_single": "מתכון בודד"
+        },
         "exampleAccess": {
             "title": "תמונות דוגמה מקומיות",
             "message": "לא נמצאו תמונות דוגמה מקומיות למודל זה. אפשרויות צפייה:",
@@ -1846,6 +1919,10 @@
             "title": "מאתחל מנהל Embedding",
             "message": "סורק ובונה מטמון embedding. זה עשוי לקחת מספר דקות..."
         },
+        "other": {
+            "title": "מאתחל את מנהל המודלים האחרים",
+            "message": "סורק ובונה מטמון מודלים. זה עשוי לקחת מספר דקות..."
+        },
         "recipes": {
             "title": "מאתחל מנהל מתכונים",
             "message": "טוען ומעבד מתכונים. זה עשוי לקחת מספר דקות..."
@@ -2168,6 +2245,7 @@
             "createMissingData": "חסרים נתונים נדרשים ליצירת המתכון",
             "created": "המתכון נוצר בהצלחה",
             "noMissingLoras": "אין LoRAs חסרים להורדה",
+            "unresolvableMarkedForReconnect": "{count} פריטים שלא ניתן לפתור סומנו — עכשיו ניתן לחבר אותם מחדש ל-LoRA מקומי.",
             "noPreviousRecipe": "אין מתכון קודם זמין",
             "noNextRecipe": "אין מתכון נוסף זמין",
             "missingLorasInfoFailed": "קבלת מידע עבור LoRAs חסרים נכשלה",
@@ -2222,10 +2300,6 @@
             "batchImportBrowseFailed": "לא ניתן היה לעיין בתיקייה: {message}",
             "batchImportDirectorySelected": "נבחרה תיקייה: {path}",
             "noRecipesSelected": "לא נבחרו מתכונים",
-            "rematchComplete": "הותאמו {entries} פריטים ב־{recipes} מתכונים",
-            "rematchCompleteErrors": "הותאמו {entries} פריטים ב־{recipes} מתכונים, {failures} נכשלו",
-            "rematchAllFailed": "ההתאמה נכשלה עבור {failures} מתוך {total} מתכונים שנבחרו",
-            "rematchUnmatched": "לא נמצאה התאמה מקומית עבור {entries} פריטים ב־{recipes} מתכונים",
             "rematchSkipped": "אין צורך בהתאמה עבור {total} המתכונים שנבחרו",
             "rematchFailed": "ההתאמה מחדש של המתכונים שנבחרו נכשלה: {message}",
             "reimporting": "מייבא מתכון מחדש מהמקור...",
@@ -2304,6 +2378,7 @@
             "checkpointRootsFailed": "טעינת שורשי checkpoint נכשלה: {message}",
             "unetRootsFailed": "טעינת שורשי Diffusion Model נכשלה: {message}",
             "embeddingRootsFailed": "טעינת שורשי embedding נכשלה: {message}",
+            "otherRootsFailed": "טעינת שורשי המודלים האחרים נכשלה: {message}",
             "mappingsUpdated": "מיפויי נתיבי מודל בסיס עודכנו ({count})",
             "mappingsCleared": "מיפויי נתיבי מודל בסיס נוקו",
             "mappingSaveFailed": "שמירת מיפויי מודל בסיס נכשלה: {message}",
@@ -2566,6 +2641,12 @@
             "rebuilding": "בונה מחדש את המטמון...",
             "rebuildFailed": "נכשלה בניית המטמון מחדש: {error}",
             "retry": "נסה שוב"
+        },
+        "otherModels": {
+            "title": "ניהול המודלים האחרים זמין",
+            "content": "סרוק ונהל קבצי VAE, Upscaler, Text Encoder, CLIP Vision ו-ControlNet, והורד אותם מ-CivitAI — מהעמוד הייעודי.",
+            "enable": "הפעל מודלים אחרים",
+            "openSettings": "פתח הגדרות"
         }
     }
 }

locales/ja.json

@@ -149,6 +149,7 @@
             "copyCheckpointName": "Checkpoint名をコピー",
             "copyEmbeddingName": "embedding名をコピー",
             "embeddingNameCopied": "Embedding構文をコピーしました",
+            "modelNameCopied": "モデル名をコピーしました",
             "sendCheckpointToWorkflow": "ComfyUIに送信",
             "sendEmbeddingToWorkflow": "ComfyUIに送信"
         },
@@ -216,9 +217,6 @@
             "label": "レシピをローカルモデルに再マッチング",
             "loading": "レシピをローカルモデルに再マッチングしています...",
             "success": "{recipes} 件のレシピで {entries} エントリをマッチングしました",
-            "successErrors": "{recipes} 件のレシピで {entries} エントリをマッチングしました（{failures} 件失敗）",
-            "allFailed": "{total} 件中 {failures} 件のレシピの再マッチングに失敗しました",
-            "noMatch": "{recipes} 件のレシピで {entries} エントリのローカルマッチが見つかりませんでした",
             "cancelled": "再マッチングをキャンセルしました。{recipes} 件のレシピを更新（{entries} エントリ）",
             "error": "レシピの再マッチングに失敗しました：{message}"
         },
@@ -236,6 +234,7 @@
             "recipes": "レシピ",
             "checkpoints": "Checkpoint",
             "embeddings": "Embedding",
+            "other": "その他",
             "statistics": "統計"
         },
         "search": {
@@ -536,6 +535,25 @@
             "defaultUnetRootHelp": "ダウンロード、インポート、移動用のデフォルトDiffusion Model (UNET)ルートディレクトリを設定",
             "defaultEmbeddingRoot": "Embeddingルート",
             "defaultEmbeddingRootHelp": "ダウンロード、インポート、移動用のデフォルトembeddingルートディレクトリを設定",
+            "defaultVaeRoot": "VAEルート",
+            "defaultVaeRootHelp": "ダウンロード、インポート、移動用のデフォルトVAEルートディレクトリを設定",
+            "defaultUpscalerRoot": "Upscalerルート",
+            "defaultUpscalerRootHelp": "ダウンロード、インポート、移動用のデフォルトUpscalerルートディレクトリを設定",
+            "defaultTextEncoderRoot": "Text Encoderルート",
+            "defaultTextEncoderRootHelp": "ダウンロード、インポート、移動用のデフォルトText Encoderルートディレクトリを設定",
+            "defaultClipVisionRoot": "CLIP Visionルート",
+            "defaultClipVisionRootHelp": "ダウンロード、インポート、移動用のデフォルトCLIP Visionルートディレクトリを設定",
+            "defaultControlnetRoot": "ControlNetルート",
+            "defaultControlnetRootHelp": "ダウンロード、インポート、移動用のデフォルトControlNetルートディレクトリを設定",
+            "enableOtherModels": "その他のモデル管理",
+            "enableOtherModelsHelp": "オフにすると、VAE / Upscaler / Text Encoder / CLIP Vision / ControlNet フォルダーはスキャンされず、その他のモデルページは無効のままになり、これらのモデルタイプはダウンロードできません。",
+            "otherSubTypes": "管理するモデルタイプ",
+            "otherSubTypesHelp": "その他のモデルページでスキャンおよび表示するカテゴリを選択します。",
+            "subTypeVae": "VAE",
+            "subTypeUpscaler": "Upscaler",
+            "subTypeTextEncoder": "Text Encoder",
+            "subTypeClipVision": "CLIP Vision",
+            "subTypeControlnet": "ControlNet",
             "recipesPath": "レシピ保存先",
             "recipesPathHelp": "保存済みレシピ用の任意のカスタムディレクトリです。空欄にすると最初のLoRAルートのrecipesフォルダーを使用します。",
             "recipesPathPlaceholder": "/path/to/recipes",
@@ -1204,6 +1222,26 @@
     "embeddings": {
         "title": "Embeddingモデル"
     },
+    "other": {
+        "title": "その他のモデル",
+        "disabled": {
+            "title": "その他のモデル管理はオフです",
+            "description": "有効にすると VAE、Upscaler、Text Encoder、CLIP Vision、ControlNet の各ファイルをスキャン・管理し、CivitAI からダウンロードできます。",
+            "enableButton": "その他のモデルを有効にする",
+            "hint": "管理するモデルタイプは後で「設定 > ライブラリ」で変更できます。",
+            "enableFailed": "その他のモデルの有効化に失敗しました",
+            "downloadBlocked": "このモデルタイプではその他のモデル管理が無効です。このファイルをダウンロードするには「設定 > ライブラリ」で有効にしてください。",
+            "enableAction": "その他のモデルを有効にする"
+        },
+        "noPaths": {
+            "title": "その他のモデルのフォルダーが見つかりません",
+            "descriptionStandalone": "その他のモデル管理はオンですが、設定されたモデルフォルダーがディスク上に存在しません。以下のフォルダーパスをsettings.jsonに追加し、LoRA Managerを再起動してください。",
+            "hintStandalone": "スキャンされるのは上記のフォルダーキーのみです。不要なキーは省略できます。",
+            "descriptionComfyUI": "その他のモデル管理はオンですが、設定されたモデルフォルダーがディスク上に存在しません。該当するモデルフォルダーをComfyUIのモデルパスに追加し、このページを再読み込みしてください。",
+            "hintComfyUI": "その他のモデルは、ComfyUIのvae、upscale_models、text_encoders、clip_vision、controlnetフォルダーから読み込まれます。",
+            "openSettings": "設定を開く"
+        }
+    },
     "sidebar": {
         "modelRoot": "ルート",
         "collapseAll": "すべてのフォルダを折りたたむ",
@@ -1501,6 +1539,41 @@
             "note": "ファイルはデフォルトのパステンプレートを使用してダウンロードされます。LoRA の数によっては時間がかかる場合があります。",
             "downloadButton": "{count} 個の LoRA をダウンロード"
         },
+        "rematchOptions": {
+            "title": "レシピの再マッチング",
+            "messageGlobal": "すべてのレシピをローカルのモデルライブラリと照合します。",
+            "messageSingle": "このレシピをローカルのモデルライブラリと照合します。",
+            "messageBulk": "選択した {count} 件のレシピをローカルのモデルライブラリと照合します。",
+            "relaxedLabel": "見つからないモデルもファイル名で再接続する",
+            "relaxedDescription": "これらのモデルはダウンロードでも修正できます（ダウンロードの方が正確です）。マッチにより別バージョンが関連付けられる場合があります。マッチした項目は確認用に一覧表示され、元に戻すことができます。",
+            "confirmButton": "再マッチング"
+        },
+        "rematchResults": {
+            "undo": "元に戻す",
+            "undone": "元に戻しました",
+            "undoFailed": "再マッチングを元に戻せませんでした：{message}"
+        },
+        "rematchSummary": {
+            "title": "再マッチングの概要",
+            "successMessage": "{entries} エントリをマッチングしました",
+            "failed": "再マッチングに失敗しました",
+            "completedWithWarnings": "再マッチングは完了しましたが、要確認の項目があります",
+            "cancelledNote": "完了前に実行がキャンセルされたため、件数は一部のみです。",
+            "statMatched": "マッチしたエントリ",
+            "statReview": "要確認",
+            "statUnresolved": "マッチなし",
+            "statErrors": "エラー",
+            "reviewSection": "確認が必要なファイル名マッチ（{count}）",
+            "columnRecipe": "レシピ",
+            "columnEntry": "エントリ",
+            "columnFile": "マッチしたファイル",
+            "columnUndo": "元に戻す",
+            "copyReport": "レポートをコピー",
+            "close": "閉じる",
+            "scope_global": "すべてのレシピ",
+            "scope_bulk": "選択したレシピ",
+            "scope_single": "単一のレシピ"
+        },
         "exampleAccess": {
             "title": "ローカル例画像",
             "message": "このモデルのローカル例画像が見つかりませんでした。表示オプション：",
@@ -1846,6 +1919,10 @@
             "title": "Embedding Managerを初期化中",
             "message": "embeddingキャッシュをスキャンして構築中。数分かかる場合があります..."
         },
+        "other": {
+            "title": "その他のモデルマネージャーを初期化中",
+            "message": "モデルキャッシュをスキャンして構築中です。数分かかる場合があります..."
+        },
         "recipes": {
             "title": "レシピマネージャーを初期化中",
             "message": "レシピを読み込んで処理中。数分かかる場合があります..."
@@ -2168,6 +2245,7 @@
             "createMissingData": "レシピ作成に必要なデータが不足しています",
             "created": "レシピを作成しました",
             "noMissingLoras": "ダウンロードする不足LoRAがありません",
+            "unresolvableMarkedForReconnect": "解決できないエントリを {count} 件マークしました — ローカルの LoRA に再接続できるようになりました。",
             "noPreviousRecipe": "前のレシピがありません",
             "noNextRecipe": "次のレシピがありません",
             "missingLorasInfoFailed": "不足LoRAの情報取得に失敗しました",
@@ -2222,10 +2300,6 @@
             "batchImportBrowseFailed": "フォルダを参照できませんでした: {message}",
             "batchImportDirectorySelected": "選択されたフォルダ: {path}",
             "noRecipesSelected": "レシピが選択されていません",
-            "rematchComplete": "{recipes} 件のレシピで {entries} エントリをマッチングしました",
-            "rematchCompleteErrors": "{recipes} 件のレシピで {entries} エントリをマッチングしました（{failures} 件失敗）",
-            "rematchAllFailed": "選択した {total} 件中 {failures} 件のレシピの再マッチングに失敗しました",
-            "rematchUnmatched": "{recipes} 件のレシピで {entries} エントリのローカルマッチが見つかりませんでした",
             "rematchSkipped": "選択した {total} 件のレシピは再マッチングの必要がありませんでした",
             "rematchFailed": "選択したレシピの再マッチングに失敗しました：{message}",
             "reimporting": "ソースからレシピを再インポート中...",
@@ -2304,6 +2378,7 @@
             "checkpointRootsFailed": "Checkpointルートの読み込みに失敗しました：{message}",
             "unetRootsFailed": "Diffusion Modelルートの読み込みに失敗しました：{message}",
             "embeddingRootsFailed": "embeddingルートの読み込みに失敗しました：{message}",
+            "otherRootsFailed": "その他のモデルルートの読み込みに失敗しました：{message}",
             "mappingsUpdated": "ベースモデルパスマッピングが更新されました（{count} マッピング）",
             "mappingsCleared": "ベースモデルパスマッピングがクリアされました",
             "mappingSaveFailed": "ベースモデルマッピングの保存に失敗しました：{message}",
@@ -2566,6 +2641,12 @@
             "rebuilding": "キャッシュを再構築中...",
             "rebuildFailed": "キャッシュの再構築に失敗しました: {error}",
             "retry": "再試行"
+        },
+        "otherModels": {
+            "title": "その他のモデル管理が利用可能になりました",
+            "content": "専用ページで VAE、Upscaler、Text Encoder、CLIP Vision、ControlNet の各ファイルをスキャン・管理し、CivitAI からダウンロードできます。",
+            "enable": "その他のモデルを有効にする",
+            "openSettings": "設定を開く"
         }
     }
 }

locales/ko.json

@@ -149,6 +149,7 @@
             "copyCheckpointName": "Checkpoint 이름 복사",
             "copyEmbeddingName": "Embedding 이름 복사",
             "embeddingNameCopied": "Embedding 구문 복사됨",
+            "modelNameCopied": "모델 이름 복사됨",
             "sendCheckpointToWorkflow": "ComfyUI로 전송",
             "sendEmbeddingToWorkflow": "ComfyUI로 전송"
         },
@@ -216,9 +217,6 @@
             "label": "레시피를 로컬 모델에 다시 매칭",
             "loading": "레시피를 로컬 모델에 다시 매칭하는 중...",
             "success": "{recipes}개 레시피에서 {entries}개 항목이 매칭되었습니다",
-            "successErrors": "{recipes}개 레시피에서 {entries}개 항목이 매칭되었습니다. {failures}개 실패",
-            "allFailed": "{total}개 레시피 중 {failures}개 재매칭 실패",
-            "noMatch": "{recipes}개 레시피에서 {entries}개 항목의 로컬 매칭을 찾지 못했습니다",
             "cancelled": "재매칭이 취소되었습니다. {recipes}개 레시피 업데이트됨({entries}개 항목)",
             "error": "레시피 재매칭 실패: {message}"
         },
@@ -236,6 +234,7 @@
             "recipes": "레시피",
             "checkpoints": "Checkpoint",
             "embeddings": "Embedding",
+            "other": "기타",
             "statistics": "통계"
         },
         "search": {
@@ -536,6 +535,25 @@
             "defaultUnetRootHelp": "다운로드, 가져오기 및 이동을 위한 기본 Diffusion Model (UNET) 루트 디렉토리를 설정합니다",
             "defaultEmbeddingRoot": "Embedding 루트",
             "defaultEmbeddingRootHelp": "다운로드, 가져오기 및 이동을 위한 기본 Embedding 루트 디렉토리를 설정합니다",
+            "defaultVaeRoot": "VAE 루트",
+            "defaultVaeRootHelp": "다운로드, 가져오기 및 이동을 위한 기본 VAE 루트 디렉토리를 설정합니다",
+            "defaultUpscalerRoot": "Upscaler 루트",
+            "defaultUpscalerRootHelp": "다운로드, 가져오기 및 이동을 위한 기본 Upscaler 루트 디렉토리를 설정합니다",
+            "defaultTextEncoderRoot": "Text Encoder 루트",
+            "defaultTextEncoderRootHelp": "다운로드, 가져오기 및 이동을 위한 기본 Text Encoder 루트 디렉토리를 설정합니다",
+            "defaultClipVisionRoot": "CLIP Vision 루트",
+            "defaultClipVisionRootHelp": "다운로드, 가져오기 및 이동을 위한 기본 CLIP Vision 루트 디렉토리를 설정합니다",
+            "defaultControlnetRoot": "ControlNet 루트",
+            "defaultControlnetRootHelp": "다운로드, 가져오기 및 이동을 위한 기본 ControlNet 루트 디렉토리를 설정합니다",
+            "enableOtherModels": "기타 모델 관리",
+            "enableOtherModelsHelp": "끄면 VAE / Upscaler / Text Encoder / CLIP Vision / ControlNet 폴더를 스캔하지 않으며, 기타 모델 페이지가 비활성화된 상태로 유지되고 이러한 모델 유형은 다운로드할 수 없습니다.",
+            "otherSubTypes": "관리할 모델 유형",
+            "otherSubTypesHelp": "기타 모델 페이지에서 스캔하고 표시할 카테고리를 선택합니다.",
+            "subTypeVae": "VAE",
+            "subTypeUpscaler": "Upscaler",
+            "subTypeTextEncoder": "Text Encoder",
+            "subTypeClipVision": "CLIP Vision",
+            "subTypeControlnet": "ControlNet",
             "recipesPath": "레시피 저장 경로",
             "recipesPathHelp": "저장된 레시피를 위한 선택적 사용자 지정 디렉터리입니다. 비워 두면 첫 번째 LoRA 루트의 recipes 폴더를 사용합니다.",
             "recipesPathPlaceholder": "/path/to/recipes",
@@ -1204,6 +1222,26 @@
     "embeddings": {
         "title": "Embedding 모델"
     },
+    "other": {
+        "title": "기타 모델",
+        "disabled": {
+            "title": "기타 모델 관리가 꺼져 있습니다",
+            "description": "활성화하면 VAE, Upscaler, Text Encoder, CLIP Vision, ControlNet 파일을 스캔하고 관리하며 CivitAI에서 다운로드할 수 있습니다.",
+            "enableButton": "기타 모델 활성화",
+            "hint": "관리할 모델 유형은 나중에 설정 > 라이브러리에서 변경할 수 있습니다.",
+            "enableFailed": "기타 모델 활성화 실패",
+            "downloadBlocked": "이 모델 유형에 대해서는 기타 모델 관리가 비활성화되어 있습니다. 이 파일을 다운로드하려면 설정 > 라이브러리에서 활성화하세요.",
+            "enableAction": "기타 모델 활성화"
+        },
+        "noPaths": {
+            "title": "기타 모델 폴더를 찾을 수 없습니다",
+            "descriptionStandalone": "기타 모델 관리가 켜져 있지만, 설정된 모델 폴더가 디스크에 존재하지 않습니다. 아래 폴더 경로를 settings.json에 추가한 뒤 LoRA Manager를 재시작하세요.",
+            "hintStandalone": "위에 나열된 폴더 키만 스캔됩니다. 필요 없는 키는 생략할 수 있습니다.",
+            "descriptionComfyUI": "기타 모델 관리가 켜져 있지만, 설정된 모델 폴더가 디스크에 존재하지 않습니다. 해당 모델 폴더를 ComfyUI 모델 경로에 추가한 뒤 이 페이지를 새로 고침하세요.",
+            "hintComfyUI": "기타 모델은 ComfyUI의 vae, upscale_models, text_encoders, clip_vision, controlnet 폴더에서 읽어옵니다.",
+            "openSettings": "설정 열기"
+        }
+    },
     "sidebar": {
         "modelRoot": "루트",
         "collapseAll": "모든 폴더 접기",
@@ -1501,6 +1539,41 @@
             "note": "파일은 기본 경로 템플릿을 사용하여 다운로드됩니다. LoRA의 수에 따라 다소 시간이 걸릴 수 있습니다.",
             "downloadButton": "{count}개 LoRA 다운로드"
         },
+        "rematchOptions": {
+            "title": "레시피 재매칭",
+            "messageGlobal": "모든 레시피를 로컬 모델 라이브러리와 대조하여 검사합니다.",
+            "messageSingle": "이 레시피를 로컬 모델 라이브러리와 대조하여 검사합니다.",
+            "messageBulk": "선택한 레시피 {count}개를 로컬 모델 라이브러리와 대조하여 검사합니다.",
+            "relaxedLabel": "누락된 모델도 파일 이름으로 다시 연결",
+            "relaxedDescription": "이 모델들은 다운로드로도 해결할 수 있으며 다운로드가 더 정확합니다. 매칭 시 모델의 다른 버전이 연결될 수 있으며, 검토용으로 목록에 표시되고 실행 취소할 수 있습니다.",
+            "confirmButton": "재매칭"
+        },
+        "rematchResults": {
+            "undo": "실행 취소",
+            "undone": "실행 취소됨",
+            "undoFailed": "재매칭 실행 취소 실패: {message}"
+        },
+        "rematchSummary": {
+            "title": "재매칭 요약",
+            "successMessage": "{entries}개 항목이 매칭되었습니다",
+            "failed": "재매칭 실패",
+            "completedWithWarnings": "재매칭이 완료되었습니다 — 검토가 권장됩니다",
+            "cancelledNote": "완료 전에 실행이 취소되었습니다 — 집계는 부분적입니다.",
+            "statMatched": "매칭된 항목",
+            "statReview": "검토 필요",
+            "statUnresolved": "매칭 없음",
+            "statErrors": "오류",
+            "reviewSection": "검토할 파일 이름 매칭 ({count})",
+            "columnRecipe": "레시피",
+            "columnEntry": "항목",
+            "columnFile": "매칭된 파일",
+            "columnUndo": "실행 취소",
+            "copyReport": "보고서 복사",
+            "close": "닫기",
+            "scope_global": "모든 레시피",
+            "scope_bulk": "선택한 레시피",
+            "scope_single": "단일 레시피"
+        },
         "exampleAccess": {
             "title": "로컬 예시 이미지",
             "message": "이 모델의 로컬 예시 이미지를 찾을 수 없습니다. 보기 옵션:",
@@ -1846,6 +1919,10 @@
             "title": "Embedding Manager 초기화 중",
             "message": "Embedding 캐시를 스캔하고 구축하고 있습니다. 몇 분이 걸릴 수 있습니다..."
         },
+        "other": {
+            "title": "기타 모델 관리자 초기화 중",
+            "message": "모델 캐시를 스캔하고 구축하고 있습니다. 몇 분이 걸릴 수 있습니다..."
+        },
         "recipes": {
             "title": "레시피 매니저 초기화 중",
             "message": "레시피를 로딩하고 처리하고 있습니다. 몇 분이 걸릴 수 있습니다..."
@@ -2168,6 +2245,7 @@
             "createMissingData": "레시피 생성에 필요한 데이터가 없습니다",
             "created": "레시피가 생성되었습니다",
             "noMissingLoras": "다운로드할 누락된 LoRA가 없습니다",
+            "unresolvableMarkedForReconnect": "해석할 수 없는 항목 {count}개가 표시되었습니다 — 이제 로컬 LoRA에 다시 연결할 수 있습니다.",
             "noPreviousRecipe": "이전 레시피가 없습니다",
             "noNextRecipe": "다음 레시피가 없습니다",
             "missingLorasInfoFailed": "누락된 LoRA 정보를 가져오는데 실패했습니다",
@@ -2222,10 +2300,6 @@
             "batchImportBrowseFailed": "폴더를 찾아보지 못했습니다: {message}",
             "batchImportDirectorySelected": "선택한 폴더: {path}",
             "noRecipesSelected": "선택한 레시피가 없습니다",
-            "rematchComplete": "{recipes}개 레시피에서 {entries}개 항목이 매칭되었습니다",
-            "rematchCompleteErrors": "{recipes}개 레시피에서 {entries}개 항목이 매칭되었습니다. {failures}개 실패",
-            "rematchAllFailed": "선택한 {total}개 레시피 중 {failures}개 재매칭 실패",
-            "rematchUnmatched": "{recipes}개 레시피에서 {entries}개 항목의 로컬 매칭을 찾지 못했습니다",
             "rematchSkipped": "선택한 {total}개 레시피는 재매칭이 필요하지 않습니다",
             "rematchFailed": "선택한 레시피 재매칭 실패: {message}",
             "reimporting": "소스에서 레시피를 다시 가져오는 중...",
@@ -2304,6 +2378,7 @@
             "checkpointRootsFailed": "Checkpoint 루트 로딩 실패: {message}",
             "unetRootsFailed": "Diffusion Model 루트 로딩 실패: {message}",
             "embeddingRootsFailed": "Embedding 루트 로딩 실패: {message}",
+            "otherRootsFailed": "기타 모델 루트 로딩 실패: {message}",
             "mappingsUpdated": "베이스 모델 경로 매핑이 업데이트되었습니다 ({count}개 매핑)",
             "mappingsCleared": "베이스 모델 경로 매핑이 지워졌습니다",
             "mappingSaveFailed": "베이스 모델 매핑 저장 실패: {message}",
@@ -2566,6 +2641,12 @@
             "rebuilding": "캐시 재구축 중...",
             "rebuildFailed": "캐시 재구축 실패: {error}",
             "retry": "다시 시도"
+        },
+        "otherModels": {
+            "title": "기타 모델 관리를 사용할 수 있습니다",
+            "content": "전용 페이지에서 VAE, Upscaler, Text Encoder, CLIP Vision, ControlNet 파일을 스캔 및 관리하고 CivitAI에서 다운로드할 수 있습니다.",
+            "enable": "기타 모델 활성화",
+            "openSettings": "설정 열기"
         }
     }
 }

locales/ru.json

@@ -149,6 +149,7 @@
             "copyCheckpointName": "Копировать имя checkpoint",
             "copyEmbeddingName": "Копировать имя embedding",
             "embeddingNameCopied": "Синтаксис embedding скопирован",
+            "modelNameCopied": "Имя модели скопировано",
             "sendCheckpointToWorkflow": "Отправить в ComfyUI",
             "sendEmbeddingToWorkflow": "Отправить в ComfyUI"
         },
@@ -216,9 +217,6 @@
             "label": "Повторное сопоставление рецептов с локальными моделями",
             "loading": "Повторное сопоставление рецептов с локальными моделями...",
             "success": "Сопоставлено записей: {entries} в рецептах: {recipes}",
-            "successErrors": "Сопоставлено записей: {entries} в рецептах: {recipes}, ошибок: {failures}",
-            "allFailed": "Не удалось сопоставить: {failures} из {total} рецептов",
-            "noMatch": "Не найдено локального сопоставления для {entries} записей в {recipes} рецептах",
             "cancelled": "Сопоставление отменено. Обновлено рецептов: {recipes} (записей: {entries})",
             "error": "Не удалось выполнить сопоставление рецептов: {message}"
         },
@@ -236,6 +234,7 @@
             "recipes": "Рецепты",
             "checkpoints": "Checkpoints",
             "embeddings": "Embeddings",
+            "other": "Другое",
             "statistics": "Статистика"
         },
         "search": {
@@ -536,6 +535,25 @@
             "defaultUnetRootHelp": "Установить корневую папку Diffusion Model (UNET) по умолчанию для загрузок, импорта и перемещений",
             "defaultEmbeddingRoot": "Корневая папка Embedding",
             "defaultEmbeddingRootHelp": "Установить корневую папку embedding по умолчанию для загрузок, импорта и перемещений",
+            "defaultVaeRoot": "Корневая папка VAE",
+            "defaultVaeRootHelp": "Установить корневую папку VAE по умолчанию для загрузок, импорта и перемещений",
+            "defaultUpscalerRoot": "Корневая папка Upscaler",
+            "defaultUpscalerRootHelp": "Установить корневую папку Upscaler по умолчанию для загрузок, импорта и перемещений",
+            "defaultTextEncoderRoot": "Корневая папка Text Encoder",
+            "defaultTextEncoderRootHelp": "Установить корневую папку Text Encoder по умолчанию для загрузок, импорта и перемещений",
+            "defaultClipVisionRoot": "Корневая папка CLIP Vision",
+            "defaultClipVisionRootHelp": "Установить корневую папку CLIP Vision по умолчанию для загрузок, импорта и перемещений",
+            "defaultControlnetRoot": "Корневая папка ControlNet",
+            "defaultControlnetRootHelp": "Установить корневую папку ControlNet по умолчанию для загрузок, импорта и перемещений",
+            "enableOtherModels": "Управление другими моделями",
+            "enableOtherModelsHelp": "Если выключено, папки VAE / Upscaler / Text Encoder / CLIP Vision / ControlNet не сканируются, страница «Другие модели» остаётся отключённой, а эти типы моделей нельзя загрузить.",
+            "otherSubTypes": "Управляемые типы моделей",
+            "otherSubTypesHelp": "Выберите, какие категории других моделей сканируются и отображаются на странице «Другие модели».",
+            "subTypeVae": "VAE",
+            "subTypeUpscaler": "Upscaler",
+            "subTypeTextEncoder": "Text Encoder",
+            "subTypeClipVision": "CLIP Vision",
+            "subTypeControlnet": "ControlNet",
             "recipesPath": "Путь хранения рецептов",
             "recipesPathHelp": "Дополнительный пользовательский каталог для сохранённых рецептов. Оставьте пустым, чтобы использовать папку recipes в первом корне LoRA.",
             "recipesPathPlaceholder": "/path/to/recipes",
@@ -1204,6 +1222,26 @@
     "embeddings": {
         "title": "Модели Embedding"
     },
+    "other": {
+        "title": "Другие модели",
+        "disabled": {
+            "title": "Управление другими моделями отключено",
+            "description": "Включите, чтобы сканировать и управлять файлами VAE, Upscaler, Text Encoder, CLIP Vision и ControlNet, а также загружать их с CivitAI.",
+            "enableButton": "Включить другие модели",
+            "hint": "Вы сможете изменить управляемые типы моделей позже в разделе «Настройки > Библиотека».",
+            "enableFailed": "Не удалось включить другие модели",
+            "downloadBlocked": "Управление другими моделями отключено для этого типа моделей. Включите его в разделе «Настройки > Библиотека», чтобы загрузить этот файл.",
+            "enableAction": "Включить другие модели"
+        },
+        "noPaths": {
+            "title": "Папки других моделей не найдены",
+            "descriptionStandalone": "Управление другими моделями включено, но ни одна из настроенных папок моделей не существует на диске. Добавьте указанные ниже пути к папкам в settings.json и перезапустите LoRA Manager.",
+            "hintStandalone": "Сканируются только перечисленные выше ключи папок; ненужные ключи можно опустить.",
+            "descriptionComfyUI": "Управление другими моделями включено, но ни одна из настроенных папок моделей не существует на диске. Добавьте соответствующие папки моделей в пути к моделям ComfyUI и перезагрузите эту страницу.",
+            "hintComfyUI": "Другие модели читаются из папок vae, upscale_models, text_encoders, clip_vision и controlnet в ComfyUI.",
+            "openSettings": "Открыть настройки"
+        }
+    },
     "sidebar": {
         "modelRoot": "Корень",
         "collapseAll": "Свернуть все папки",
@@ -1501,6 +1539,41 @@
             "note": "Файлы будут скачаны с использованием шаблонов путей по умолчанию. Это может занять некоторое время в зависимости от количества LoRAs.",
             "downloadButton": "Скачать {count} LoRA(s)"
         },
+        "rematchOptions": {
+            "title": "Повторное сопоставление рецептов",
+            "messageGlobal": "Все рецепты будут проверены по вашей локальной библиотеке моделей.",
+            "messageSingle": "Этот рецепт будет проверен по вашей локальной библиотеке моделей.",
+            "messageBulk": "Выбранные рецепты ({count}) будут проверены по вашей локальной библиотеке моделей.",
+            "relaxedLabel": "Также переподключать отсутствующие модели по имени файла",
+            "relaxedDescription": "Эти модели также можно исправить загрузкой — загрузка точнее. Совпадения могут привязать другую версию; они будут перечислены для проверки, и их можно будет отменить.",
+            "confirmButton": "Сопоставить"
+        },
+        "rematchResults": {
+            "undo": "Отменить",
+            "undone": "Отменено",
+            "undoFailed": "Не удалось отменить сопоставление: {message}"
+        },
+        "rematchSummary": {
+            "title": "Сводка повторного сопоставления",
+            "successMessage": "Сопоставлено записей: {entries}",
+            "failed": "Не удалось выполнить сопоставление",
+            "completedWithWarnings": "Сопоставление завершено — рекомендуется проверка",
+            "cancelledNote": "Запуск отменён до завершения — подсчёты неполные.",
+            "statMatched": "Сопоставленные записи",
+            "statReview": "Требуют проверки",
+            "statUnresolved": "Не сопоставлено",
+            "statErrors": "Ошибки",
+            "reviewSection": "Совпадения по имени файла для проверки ({count})",
+            "columnRecipe": "Рецепт",
+            "columnEntry": "Запись",
+            "columnFile": "Совпавший файл",
+            "columnUndo": "Отменить",
+            "copyReport": "Скопировать отчёт",
+            "close": "Закрыть",
+            "scope_global": "Все рецепты",
+            "scope_bulk": "Выбранные рецепты",
+            "scope_single": "Один рецепт"
+        },
         "exampleAccess": {
             "title": "Локальные примеры изображений",
             "message": "Локальные примеры изображений для этой модели не найдены. Варианты просмотра:",
@@ -1846,6 +1919,10 @@
             "title": "Инициализация Embedding Manager",
             "message": "Сканирование и построение кэша embedding. Это может занять несколько минут..."
         },
+        "other": {
+            "title": "Инициализация менеджера других моделей",
+            "message": "Сканирование и построение кэша моделей. Это может занять несколько минут..."
+        },
         "recipes": {
             "title": "Инициализация менеджера рецептов",
             "message": "Загрузка и обработка рецептов. Это может занять несколько минут..."
@@ -2168,6 +2245,7 @@
             "createMissingData": "Отсутствуют необходимые данные для создания рецепта",
             "created": "Рецепт успешно создан",
             "noMissingLoras": "Нет отсутствующих LoRAs для загрузки",
+            "unresolvableMarkedForReconnect": "Помечено неразрешимых записей: {count} — теперь их можно переподключить к локальному LoRA.",
             "noPreviousRecipe": "Предыдущий рецепт отсутствует",
             "noNextRecipe": "Следующий рецепт отсутствует",
             "missingLorasInfoFailed": "Не удалось получить информацию для отсутствующих LoRAs",
@@ -2222,10 +2300,6 @@
             "batchImportBrowseFailed": "Не удалось открыть папку: {message}",
             "batchImportDirectorySelected": "Выбрана папка: {path}",
             "noRecipesSelected": "Рецепты не выбраны",
-            "rematchComplete": "Сопоставлено записей: {entries} в рецептах: {recipes}",
-            "rematchCompleteErrors": "Сопоставлено записей: {entries} в рецептах: {recipes}, ошибок: {failures}",
-            "rematchAllFailed": "Не удалось сопоставить: {failures} из {total} выбранных рецептов",
-            "rematchUnmatched": "Не найдено локального сопоставления для {entries} записей в {recipes} рецептах",
             "rematchSkipped": "Ни один из {total} выбранных рецептов не требует сопоставления",
             "rematchFailed": "Не удалось сопоставить выбранные рецепты: {message}",
             "reimporting": "Переимпорт рецепта из источника...",
@@ -2304,6 +2378,7 @@
             "checkpointRootsFailed": "Не удалось загрузить корни checkpoint: {message}",
             "unetRootsFailed": "Не удалось загрузить корни Diffusion Model: {message}",
             "embeddingRootsFailed": "Не удалось загрузить корни embedding: {message}",
+            "otherRootsFailed": "Не удалось загрузить корни других моделей: {message}",
             "mappingsUpdated": "Сопоставления путей базовых моделей обновлены ({count})",
             "mappingsCleared": "Сопоставления путей базовых моделей очищены",
             "mappingSaveFailed": "Не удалось сохранить сопоставления базовых моделей: {message}",
@@ -2566,6 +2641,12 @@
             "rebuilding": "Перестроение кэша...",
             "rebuildFailed": "Не удалось перестроить кэш: {error}",
             "retry": "Повторить"
+        },
+        "otherModels": {
+            "title": "Управление другими моделями доступно",
+            "content": "Сканирование и управление файлами VAE, Upscaler, Text Encoder, CLIP Vision и ControlNet, а также загрузка их с CivitAI — всё на одной отдельной странице.",
+            "enable": "Включить другие модели",
+            "openSettings": "Открыть настройки"
         }
     }
 }

locales/zh-CN.json

@@ -149,6 +149,7 @@
             "copyCheckpointName": "复制 Checkpoint 名称",
             "copyEmbeddingName": "复制 Embedding 名称",
             "embeddingNameCopied": "已复制 Embedding 语法",
+            "modelNameCopied": "模型名称已复制",
             "sendCheckpointToWorkflow": "发送到 ComfyUI",
             "sendEmbeddingToWorkflow": "发送到 ComfyUI"
         },
@@ -216,9 +217,6 @@
             "label": "将配方重新匹配到本地模型",
             "loading": "正在将配方重新匹配到本地模型...",
             "success": "已匹配 {entries} 个条目，涉及 {recipes} 个配方",
-            "successErrors": "已匹配 {entries} 个条目，涉及 {recipes} 个配方，{failures} 个失败",
-            "allFailed": "{failures}/{total} 个配方重新匹配失败",
-            "noMatch": "在 {recipes} 个配方中未找到 {entries} 个条目的本地匹配",
             "cancelled": "已取消重新匹配。{recipes} 个配方已更新（{entries} 个条目）。",
             "error": "配方重新匹配失败：{message}"
         },
@@ -236,6 +234,7 @@
             "recipes": "配方",
             "checkpoints": "Checkpoint",
             "embeddings": "Embedding",
+            "other": "其他",
             "statistics": "统计"
         },
         "search": {
@@ -536,6 +535,25 @@
             "defaultUnetRootHelp": "设置下载、导入和移动时的默认 Diffusion Model (UNET) 根目录",
             "defaultEmbeddingRoot": "Embedding 根目录",
             "defaultEmbeddingRootHelp": "设置下载、导入和移动时的默认 Embedding 根目录",
+            "defaultVaeRoot": "VAE 根目录",
+            "defaultVaeRootHelp": "设置下载、导入和移动时的默认 VAE 根目录",
+            "defaultUpscalerRoot": "Upscaler 根目录",
+            "defaultUpscalerRootHelp": "设置下载、导入和移动时的默认 Upscaler 根目录",
+            "defaultTextEncoderRoot": "Text Encoder 根目录",
+            "defaultTextEncoderRootHelp": "设置下载、导入和移动时的默认 Text Encoder 根目录",
+            "defaultClipVisionRoot": "CLIP Vision 根目录",
+            "defaultClipVisionRootHelp": "设置下载、导入和移动时的默认 CLIP Vision 根目录",
+            "defaultControlnetRoot": "ControlNet 根目录",
+            "defaultControlnetRootHelp": "设置下载、导入和移动时的默认 ControlNet 根目录",
+            "enableOtherModels": "其他模型管理",
+            "enableOtherModelsHelp": "关闭后，不会扫描 VAE / Upscaler / Text Encoder / CLIP Vision / ControlNet 文件夹，其他模型页面保持禁用，且无法下载这些模型类型。",
+            "otherSubTypes": "管理的模型类型",
+            "otherSubTypesHelp": "选择要在其他模型页面中扫描和显示的其他模型类别。",
+            "subTypeVae": "VAE",
+            "subTypeUpscaler": "Upscaler",
+            "subTypeTextEncoder": "Text Encoder",
+            "subTypeClipVision": "CLIP Vision",
+            "subTypeControlnet": "ControlNet",
             "recipesPath": "配方存储路径",
             "recipesPathHelp": "已保存配方的可选自定义目录。留空则使用第一个 LoRA 根目录下的 recipes 文件夹。",
             "recipesPathPlaceholder": "/path/to/recipes",
@@ -1204,6 +1222,26 @@
     "embeddings": {
         "title": "Embedding 模型"
     },
+    "other": {
+        "title": "其他模型",
+        "disabled": {
+            "title": "其他模型管理已关闭",
+            "description": "启用后可扫描和管理 VAE、Upscaler、Text Encoder、CLIP Vision 和 ControlNet 文件，并从 CivitAI 下载。",
+            "enableButton": "启用其他模型",
+            "hint": "你可以稍后在“设置 > 库”中更改管理的模型类型。",
+            "enableFailed": "启用其他模型失败",
+            "downloadBlocked": "其他模型管理已对此模型类型禁用。请在“设置 > 库”中启用以下载此文件。",
+            "enableAction": "启用其他模型"
+        },
+        "noPaths": {
+            "title": "未找到其他模型文件夹",
+            "descriptionStandalone": "其他模型管理已开启，但配置的模型文件夹在磁盘上都不存在。请将下面的文件夹路径添加到 settings.json，然后重启 LoRA Manager。",
+            "hintStandalone": "只会扫描上面列出的文件夹键；不需要的键可以省略。",
+            "descriptionComfyUI": "其他模型管理已开启，但配置的模型文件夹在磁盘上都不存在。请将对应的模型文件夹添加到 ComfyUI 的模型路径，然后重新加载此页面。",
+            "hintComfyUI": "其他模型从 ComfyUI 的 vae、upscale_models、text_encoders、clip_vision 和 controlnet 文件夹中读取。",
+            "openSettings": "打开设置"
+        }
+    },
     "sidebar": {
         "modelRoot": "根目录",
         "collapseAll": "折叠所有文件夹",
@@ -1501,6 +1539,41 @@
             "note": "文件将使用默认路径模板下载。根据 LoRAs 的数量，这可能需要一些时间。",
             "downloadButton": "下载 {count} 个 LoRA(s)"
         },
+        "rematchOptions": {
+            "title": "重新匹配配方",
+            "messageGlobal": "将对照你的本地模型库扫描所有配方。",
+            "messageSingle": "将对照你的本地模型库扫描此配方。",
+            "messageBulk": "将对照你的本地模型库扫描 {count} 个所选配方。",
+            "relaxedLabel": "同时按文件名重新关联缺失的模型",
+            "relaxedDescription": "这些模型也可以通过下载来修复——下载更为准确。匹配结果可能链接到模型的其他版本；它们会被列出供检查，且可以撤销。",
+            "confirmButton": "重新匹配"
+        },
+        "rematchResults": {
+            "undo": "撤销",
+            "undone": "已撤销",
+            "undoFailed": "撤销重新匹配失败：{message}"
+        },
+        "rematchSummary": {
+            "title": "重新匹配摘要",
+            "successMessage": "已匹配 {entries} 个条目",
+            "failed": "重新匹配失败",
+            "completedWithWarnings": "重新匹配已完成——建议检查",
+            "cancelledNote": "运行在完成前已取消——统计不完整。",
+            "statMatched": "已匹配条目",
+            "statReview": "需要检查",
+            "statUnresolved": "未匹配",
+            "statErrors": "错误",
+            "reviewSection": "需要检查的文件名匹配（{count}）",
+            "columnRecipe": "配方",
+            "columnEntry": "条目",
+            "columnFile": "匹配到的文件",
+            "columnUndo": "撤销",
+            "copyReport": "复制报告",
+            "close": "关闭",
+            "scope_global": "所有配方",
+            "scope_bulk": "所选配方",
+            "scope_single": "单个配方"
+        },
         "exampleAccess": {
             "title": "本地示例图片",
             "message": "未找到此模型的本地示例图片。可选操作：",
@@ -1846,6 +1919,10 @@
             "title": "初始化 Embedding 管理器",
             "message": "正在扫描并构建 Embedding 缓存。这可能需要几分钟..."
         },
+        "other": {
+            "title": "正在初始化其他模型管理器",
+            "message": "正在扫描并构建模型缓存。这可能需要几分钟..."
+        },
         "recipes": {
             "title": "初始化配方管理器",
             "message": "正在加载和处理配方。这可能需要几分钟..."
@@ -2168,6 +2245,7 @@
             "createMissingData": "缺少创建配方所需的数据",
             "created": "配方创建成功",
             "noMissingLoras": "没有缺失的 LoRA 可下载",
+            "unresolvableMarkedForReconnect": "已标记 {count} 个无法解析的条目——现在可以将它们重新关联到本地 LoRA。",
             "noPreviousRecipe": "没有上一个配方",
             "noNextRecipe": "没有下一个配方",
             "missingLorasInfoFailed": "获取缺失 LoRA 信息失败",
@@ -2222,10 +2300,6 @@
             "batchImportBrowseFailed": "浏览目录失败：{message}",
             "batchImportDirectorySelected": "已选择目录：{path}",
             "noRecipesSelected": "未选择任何配方",
-            "rematchComplete": "已匹配 {entries} 个条目，涉及 {recipes} 个配方",
-            "rematchCompleteErrors": "已匹配 {entries} 个条目，涉及 {recipes} 个配方，{failures} 个失败",
-            "rematchAllFailed": "{failures}/{total} 个所选配方重新匹配失败",
-            "rematchUnmatched": "在 {recipes} 个配方中未找到 {entries} 个条目的本地匹配",
             "rematchSkipped": "{total} 个所选配方均无需重新匹配",
             "rematchFailed": "重新匹配所选配方失败：{message}",
             "reimporting": "正在从源重新导入配方...",
@@ -2304,6 +2378,7 @@
             "checkpointRootsFailed": "加载 Checkpoint 根目录失败：{message}",
             "unetRootsFailed": "加载 Diffusion Model 根目录失败：{message}",
             "embeddingRootsFailed": "加载 Embedding 根目录失败：{message}",
+            "otherRootsFailed": "加载其他模型根目录失败：{message}",
             "mappingsUpdated": "基础模型路径映射已更新（{count} 条映射）",
             "mappingsCleared": "基础模型路径映射已清除",
             "mappingSaveFailed": "保存基础模型映射失败：{message}",
@@ -2566,6 +2641,12 @@
             "rebuilding": "正在重建缓存...",
             "rebuildFailed": "重建缓存失败：{error}",
             "retry": "重试"
+        },
+        "otherModels": {
+            "title": "其他模型管理现已可用",
+            "content": "在一个专属页面中扫描和管理 VAE、Upscaler、Text Encoder、CLIP Vision 和 ControlNet 文件，并从 CivitAI 下载。",
+            "enable": "启用其他模型",
+            "openSettings": "打开设置"
         }
     }
 }

locales/zh-TW.json

@@ -149,6 +149,7 @@
             "copyCheckpointName": "複製 Checkpoint 名稱",
             "copyEmbeddingName": "複製嵌入名稱",
             "embeddingNameCopied": "已複製 Embedding 語法",
+            "modelNameCopied": "模型名稱已複製",
             "sendCheckpointToWorkflow": "傳送到 ComfyUI",
             "sendEmbeddingToWorkflow": "傳送到 ComfyUI"
         },
@@ -216,9 +217,6 @@
             "label": "將配方重新匹配到本地模型",
             "loading": "正在將配方重新匹配到本地模型...",
             "success": "已匹配 {entries} 個條目，涉及 {recipes} 個配方",
-            "successErrors": "已匹配 {entries} 個條目，涉及 {recipes} 個配方，{failures} 個失敗",
-            "allFailed": "{failures}/{total} 個配方重新匹配失敗",
-            "noMatch": "在 {recipes} 個配方中找不到 {entries} 個條目的本地匹配",
             "cancelled": "已取消重新匹配。{recipes} 個配方已更新（{entries} 個條目）。",
             "error": "配方重新匹配失敗：{message}"
         },
@@ -236,6 +234,7 @@
             "recipes": "配方",
             "checkpoints": "Checkpoint",
             "embeddings": "Embedding",
+            "other": "其他",
             "statistics": "統計"
         },
         "search": {
@@ -536,6 +535,25 @@
             "defaultUnetRootHelp": "設定下載、匯入和移動時的預設 Diffusion Model (UNET) 根目錄",
             "defaultEmbeddingRoot": "Embedding 根目錄",
             "defaultEmbeddingRootHelp": "設定下載、匯入和移動時的預設 Embedding 根目錄",
+            "defaultVaeRoot": "VAE 根目錄",
+            "defaultVaeRootHelp": "設定下載、匯入和移動時的預設 VAE 根目錄",
+            "defaultUpscalerRoot": "Upscaler 根目錄",
+            "defaultUpscalerRootHelp": "設定下載、匯入和移動時的預設 Upscaler 根目錄",
+            "defaultTextEncoderRoot": "Text Encoder 根目錄",
+            "defaultTextEncoderRootHelp": "設定下載、匯入和移動時的預設 Text Encoder 根目錄",
+            "defaultClipVisionRoot": "CLIP Vision 根目錄",
+            "defaultClipVisionRootHelp": "設定下載、匯入和移動時的預設 CLIP Vision 根目錄",
+            "defaultControlnetRoot": "ControlNet 根目錄",
+            "defaultControlnetRootHelp": "設定下載、匯入和移動時的預設 ControlNet 根目錄",
+            "enableOtherModels": "其他模型管理",
+            "enableOtherModelsHelp": "關閉後，不會掃描 VAE / Upscaler / Text Encoder / CLIP Vision / ControlNet 資料夾，其他模型頁面會保持停用，且無法下載這些模型類型。",
+            "otherSubTypes": "管理的模型類型",
+            "otherSubTypesHelp": "選擇要在其他模型頁面中掃描和顯示的其他模型類別。",
+            "subTypeVae": "VAE",
+            "subTypeUpscaler": "Upscaler",
+            "subTypeTextEncoder": "Text Encoder",
+            "subTypeClipVision": "CLIP Vision",
+            "subTypeControlnet": "ControlNet",
             "recipesPath": "配方儲存路徑",
             "recipesPathHelp": "已儲存配方的可選自訂目錄。留空則使用第一個 LoRA 根目錄下的 recipes 資料夾。",
             "recipesPathPlaceholder": "/path/to/recipes",
@@ -1204,6 +1222,26 @@
     "embeddings": {
         "title": "Embedding 模型"
     },
+    "other": {
+        "title": "其他模型",
+        "disabled": {
+            "title": "其他模型管理已關閉",
+            "description": "啟用後可掃描和管理 VAE、Upscaler、Text Encoder、CLIP Vision 和 ControlNet 檔案，並從 CivitAI 下載。",
+            "enableButton": "啟用其他模型",
+            "hint": "您稍後可以在「設定 > 模型庫」中變更管理的模型類型。",
+            "enableFailed": "啟用其他模型失敗",
+            "downloadBlocked": "其他模型管理已對此模型類型停用。請在「設定 > 模型庫」中啟用以下載此檔案。",
+            "enableAction": "啟用其他模型"
+        },
+        "noPaths": {
+            "title": "找不到其他模型資料夾",
+            "descriptionStandalone": "其他模型管理已開啟，但設定的模型資料夾在磁碟上都不存在。請將下方的資料夾路徑加入 settings.json，然後重新啟動 LoRA Manager。",
+            "hintStandalone": "只會掃描上方列出的資料夾鍵；不需要的鍵可以省略。",
+            "descriptionComfyUI": "其他模型管理已開啟，但設定的模型資料夾在磁碟上都不存在。請將對應的模型資料夾加入 ComfyUI 的模型路徑，然後重新載入此頁面。",
+            "hintComfyUI": "其他模型會從 ComfyUI 的 vae、upscale_models、text_encoders、clip_vision 和 controlnet 資料夾讀取。",
+            "openSettings": "開啟設定"
+        }
+    },
     "sidebar": {
         "modelRoot": "根目錄",
         "collapseAll": "全部摺疊資料夾",
@@ -1501,6 +1539,41 @@
             "note": "檔案將使用預設路徑模板下載。根據 LoRAs 的數量，這可能需要一些時間。",
             "downloadButton": "下載 {count} 個 LoRA(s)"
         },
+        "rematchOptions": {
+            "title": "重新匹配配方",
+            "messageGlobal": "所有配方將對照您的本地模型庫進行掃描。",
+            "messageSingle": "此配方將對照您的本地模型庫進行掃描。",
+            "messageBulk": "將對照您的本地模型庫掃描 {count} 個所選配方。",
+            "relaxedLabel": "同時依檔案名稱重新關聯缺少的模型",
+            "relaxedDescription": "這些模型也可以透過下載修復——下載更為準確。比對可能會連結到模型的不同版本；比對結果將列出供您檢閱，且可以撤銷。",
+            "confirmButton": "重新匹配"
+        },
+        "rematchResults": {
+            "undo": "撤銷",
+            "undone": "已撤銷",
+            "undoFailed": "撤銷重新匹配失敗：{message}"
+        },
+        "rematchSummary": {
+            "title": "重新匹配摘要",
+            "successMessage": "已匹配 {entries} 個條目",
+            "failed": "重新匹配失敗",
+            "completedWithWarnings": "重新匹配已完成——建議檢查",
+            "cancelledNote": "執行在完成前已取消——統計不完整。",
+            "statMatched": "已匹配條目",
+            "statReview": "需要檢查",
+            "statUnresolved": "未匹配",
+            "statErrors": "錯誤",
+            "reviewSection": "需要檢查的檔案名稱匹配（{count}）",
+            "columnRecipe": "配方",
+            "columnEntry": "條目",
+            "columnFile": "匹配到的檔案",
+            "columnUndo": "撤銷",
+            "copyReport": "複製報告",
+            "close": "關閉",
+            "scope_global": "所有配方",
+            "scope_bulk": "所選配方",
+            "scope_single": "單個配方"
+        },
         "exampleAccess": {
             "title": "本機範例圖片",
             "message": "此模型未找到本機範例圖片。可選擇：",
@@ -1846,6 +1919,10 @@
             "title": "初始化 Embedding 管理器",
             "message": "正在掃描並建立 Embedding 快取，可能需要幾分鐘..."
         },
+        "other": {
+            "title": "正在初始化其他模型管理器",
+            "message": "正在掃描並建立模型快取。這可能需要幾分鐘..."
+        },
         "recipes": {
             "title": "初始化配方管理器",
             "message": "正在載入並處理配方，可能需要幾分鐘..."
@@ -2168,6 +2245,7 @@
             "createMissingData": "缺少建立配方所需的資料",
             "created": "配方建立成功",
             "noMissingLoras": "無缺少的 LoRA 可下載",
+            "unresolvableMarkedForReconnect": "已標記 {count} 個無法解析的條目——現在可以將它們重新關聯到本地 LoRA。",
             "noPreviousRecipe": "沒有上一個配方",
             "noNextRecipe": "沒有下一個配方",
             "missingLorasInfoFailed": "取得缺少 LoRA 資訊失敗",
@@ -2222,10 +2300,6 @@
             "batchImportBrowseFailed": "瀏覽目錄失敗：{message}",
             "batchImportDirectorySelected": "已選擇目錄：{path}",
             "noRecipesSelected": "未選取任何配方",
-            "rematchComplete": "已匹配 {entries} 個條目，涉及 {recipes} 個配方",
-            "rematchCompleteErrors": "已匹配 {entries} 個條目，涉及 {recipes} 個配方，{failures} 個失敗",
-            "rematchAllFailed": "{failures}/{total} 個所選配方重新匹配失敗",
-            "rematchUnmatched": "在 {recipes} 個配方中找不到 {entries} 個條目的本地匹配",
             "rematchSkipped": "{total} 個所選配方均無需重新匹配",
             "rematchFailed": "重新匹配所選配方失敗：{message}",
             "reimporting": "正在從來源重新匯入配方...",
@@ -2304,6 +2378,7 @@
             "checkpointRootsFailed": "載入 checkpoint 根目錄失敗：{message}",
             "unetRootsFailed": "載入 Diffusion Model 根目錄失敗：{message}",
             "embeddingRootsFailed": "載入 embedding 根目錄失敗：{message}",
+            "otherRootsFailed": "載入其他模型根目錄失敗：{message}",
             "mappingsUpdated": "基礎模型路徑對應已更新（{count} 個對應）",
             "mappingsCleared": "基礎模型路徑對應已清除",
             "mappingSaveFailed": "儲存基礎模型對應失敗：{message}",
@@ -2566,6 +2641,12 @@
             "rebuilding": "重建快取中...",
             "rebuildFailed": "重建快取失敗：{error}",
             "retry": "重試"
+        },
+        "otherModels": {
+            "title": "其他模型管理現已可用",
+            "content": "在專屬頁面中掃描和管理 VAE、Upscaler、Text Encoder、CLIP Vision 和 ControlNet 檔案，並從 CivitAI 下載。",
+            "enable": "啟用其他模型",
+            "openSettings": "開啟設定"
         }
     }
 }

py/config.py

@@ -17,6 +17,9 @@ import types as _types
 import time
 
 from .utils.cache_paths import CacheType, get_cache_file_path, get_legacy_cache_paths
+from .utils.constants import (
+    OTHER_MODEL_FOLDER_SUBTYPES,
+)
 from .utils.settings_paths import (
     ensure_settings_file,
     get_settings_dir,
@@ -172,6 +175,13 @@ class Config:
         self.embeddings_roots = None
         self.base_models_roots = self._init_checkpoint_paths()
         self.embeddings_roots = self._init_embedding_paths()
+        # Other-model roots (VAE, upscalers, text encoders, ...): flat deduped
+        # list plus a normalized root -> sub_type map and per-folder_paths-key
+        # roots for settings persistence.
+        self.other_roots: Optional[List[str]] = None
+        self.other_root_subtypes: Dict[str, str] = {}
+        self.other_folder_roots: Dict[str, List[str]] = {}
+        self.other_roots = self._init_other_paths()
         # Extra paths (only for LoRA Manager, not shared with ComfyUI)
         self.extra_loras_roots: List[str] = []
         self.extra_checkpoints_roots: List[str] = []
@@ -336,6 +346,10 @@ class Config:
                 "unet": list(self.unet_roots or []),
                 "embeddings": list(self.embeddings_roots or []),
             }
+            # Persist the other-model roots under their original folder_paths
+            # keys so library switching round-trips them.
+            for key, roots in (self.other_folder_roots or {}).items():
+                target_folder_paths[key] = list(roots)
 
             normalized_target_paths = _normalize_folder_paths_for_comparison(
                 target_folder_paths
@@ -522,6 +536,7 @@ class Config:
         roots.extend(self.loras_roots or [])
         roots.extend(self.base_models_roots or [])
         roots.extend(self.embeddings_roots or [])
+        roots.extend(self.other_roots or [])
         # Include extra paths for scanning symlinks
         roots.extend(self.extra_loras_roots or [])
         roots.extend(self.extra_checkpoints_roots or [])
@@ -862,6 +877,8 @@ class Config:
             preview_roots.update(self._expand_preview_root(root))
         for root in self.embeddings_roots or []:
             preview_roots.update(self._expand_preview_root(root))
+        for root in self.other_roots or []:
+            preview_roots.update(self._expand_preview_root(root))
         # Include extra paths for preview access
         for root in self.extra_loras_roots or []:
             preview_roots.update(self._expand_preview_root(root))
@@ -882,7 +899,7 @@ class Config:
             path for path in preview_roots if path.is_absolute()
         }
         logger.debug(
-            "Preview roots rebuilt: %d paths from %d lora roots (%d extra), %d checkpoint roots (%d extra), %d embedding roots (%d extra), %d symlink mappings",
+            "Preview roots rebuilt: %d paths from %d lora roots (%d extra), %d checkpoint roots (%d extra), %d embedding roots (%d extra), %d other roots, %d symlink mappings",
             len(self._preview_root_paths),
             len(self.loras_roots or []),
             len(self.extra_loras_roots or []),
@@ -890,6 +907,7 @@ class Config:
             len(self.extra_checkpoints_roots or []),
             len(self.embeddings_roots or []),
             len(self.extra_embeddings_roots or []),
+            len(self.other_roots or []),
             len(self._path_mappings),
         )
 
@@ -1128,6 +1146,155 @@ class Config:
 
         return unique_paths
 
+    def _get_enabled_other_folder_keys(self) -> List[str]:
+        """Return the OTHER_MODEL_FOLDER_SUBTYPES keys that are enabled.
+
+        Other Models management is opt-in: while ``enable_other_models`` is
+        off (the default) no other-model folder is scanned at all. When it is
+        on, only the folder keys of the enabled sub_types are scanned
+        (text_encoder merges ``text_encoders`` with the legacy ``clip`` key).
+        """
+        try:
+            from .services.settings_manager import get_settings_manager
+
+            enabled_sub_types = get_settings_manager().get_enabled_other_sub_types()
+        except Exception:
+            enabled_sub_types = []
+        if not enabled_sub_types:
+            return []
+        allowed = set(enabled_sub_types)
+        return [
+            key
+            for key, sub_type in OTHER_MODEL_FOLDER_SUBTYPES.items()
+            if sub_type in allowed
+        ]
+
+    @staticmethod
+    def _collapse_legacy_folder_keys(keys: List[str]) -> List[str]:
+        """Drop folder keys the host already normalizes onto another queried key.
+
+        ComfyUI's ``folder_paths`` rewrites legacy names before every access
+        (``clip`` -> ``text_encoders``, ``unet`` -> ``diffusion_models``), and
+        registers both legacy directories under the canonical key, so
+        ``get_folder_paths("clip")`` returns exactly the same list as
+        ``get_folder_paths("text_encoders")``. Querying both therefore reports
+        every text-encoder folder twice and trips the overlap guard with a
+        conflict the user cannot fix.
+
+        When the host exposes ``map_legacy`` the alias is provably redundant and
+        is skipped (an empty canonical list implies an empty alias list).
+        Without it - the standalone mock, whose keys are independent
+        ``settings.json`` entries - every key is kept, because a ``clip``-only
+        configuration is then genuinely distinct.
+        """
+        map_legacy = getattr(folder_paths, "map_legacy", None)
+        if not callable(map_legacy):
+            return list(keys)
+
+        queried = set(keys)
+        collapsed: List[str] = []
+        for key in keys:
+            try:
+                canonical = map_legacy(key)
+            except Exception:
+                canonical = key
+            if canonical != key and canonical in queried:
+                logger.debug(
+                    "Skipping legacy folder key '%s'; the host resolves it to "
+                    "'%s', which is queried as well.",
+                    key,
+                    canonical,
+                )
+                continue
+            collapsed.append(key)
+        return collapsed
+
+    def _prepare_other_paths(
+        self, folder_path_map: Mapping[str, Iterable[str]]
+    ) -> Tuple[List[str], Dict[str, str], Dict[str, List[str]]]:
+        """Prepare other-model paths from a folder_paths-key -> raw paths map.
+
+        Returns:
+            Tuple of (all_unique_roots, business_root -> sub_type map,
+            folder_paths key -> business roots). This method does NOT modify
+            instance variables - callers must set them.
+        """
+        unique_paths: List[str] = []
+        sub_type_map: Dict[str, str] = {}
+        per_key_roots: Dict[str, List[str]] = {}
+        # real path -> (business path, sub_type) of the category that claimed it
+        seen_real_paths: Dict[str, Tuple[str, str]] = {}
+
+        # Cross-scanner overlap detection: warn when an "other" root is
+        # already covered by the checkpoints/unet or embeddings scanners.
+        # Kept (not dropped) on purpose - duplicate cards across pages are
+        # cosmetic, while dropping would silently unmanage the files.
+        covered_real_paths = {
+            os.path.normpath(os.path.realpath(path)).replace(os.sep, "/"): path
+            for path in [
+                *(self.base_models_roots or []),
+                *(self.embeddings_roots or []),
+            ]
+            if isinstance(path, str) and path.strip() and os.path.exists(path)
+        }
+
+        for key, sub_type in OTHER_MODEL_FOLDER_SUBTYPES.items():
+            raw_paths = folder_path_map.get(key)
+            if not raw_paths:
+                continue
+            path_map = self._dedupe_existing_paths(raw_paths)
+            key_roots: List[str] = []
+            for real_path, business_path in sorted(
+                path_map.items(), key=lambda item: item[1].lower()
+            ):
+                seen = seen_real_paths.get(real_path)
+                if seen is not None:
+                    seen_business_path, seen_sub_type = seen
+                    if seen_sub_type == sub_type:
+                        # Same category reached through a second folder_paths
+                        # key (legacy alias, or a sub_type spanning two keys).
+                        # Expected, so never a "fix your configuration" warning.
+                        logger.debug(
+                            "Ignoring duplicate folder '%s' for category '%s' "
+                            "(already covered by '%s').",
+                            business_path,
+                            sub_type,
+                            seen_business_path,
+                        )
+                    else:
+                        logger.warning(
+                            "Detected the same folder '%s' under multiple other-model "
+                            "categories ('%s' is already mapped as '%s'). Keeping the "
+                            "first category; please fix your path configuration.",
+                            business_path,
+                            seen_business_path,
+                            seen_sub_type,
+                        )
+                    continue
+                seen_real_paths[real_path] = (business_path, sub_type)
+                unique_paths.append(business_path)
+                key_roots.append(business_path)
+                sub_type_map[business_path] = sub_type
+
+                if real_path != business_path:
+                    self.add_path_mapping(business_path, real_path)
+
+                covered_by = covered_real_paths.get(real_path)
+                if covered_by:
+                    logger.warning(
+                        "Detected an other-model root ('%s', category '%s') that "
+                        "overlaps an existing checkpoints/embeddings root ('%s'). "
+                        "The same files will appear on both pages; please review "
+                        "your path configuration.",
+                        business_path,
+                        key,
+                        covered_by,
+                    )
+            if key_roots:
+                per_key_roots[key] = key_roots
+
+        return unique_paths, sub_type_map, per_key_roots
+
     def _apply_library_paths(
         self,
         folder_paths: Mapping[str, Any],
@@ -1151,6 +1318,16 @@ class Config:
         ) = self._prepare_checkpoint_paths(checkpoint_paths, unet_paths)
         self.embeddings_roots = self._prepare_embedding_paths(embedding_paths)
 
+        other_path_map = {
+            key: folder_paths.get(key, []) or []
+            for key in self._get_enabled_other_folder_keys()
+        }
+        (
+            self.other_roots,
+            self.other_root_subtypes,
+            self.other_folder_roots,
+        ) = self._prepare_other_paths(other_path_map)
+
         # Process extra paths (only for LoRA Manager, not shared with ComfyUI)
         extra_paths = extra_folder_paths or {}
         extra_lora_paths = extra_paths.get("loras", []) or []
@@ -1267,6 +1444,104 @@ class Config:
             logger.warning(f"Error initializing embedding paths: {e}")
             return []
 
+    def _init_other_paths(self) -> List[str]:
+        """Initialize and validate other-model paths from ComfyUI settings.
+
+        Iterates the enabled OTHER_MODEL_FOLDER_SUBTYPES keys and pulls each
+        from ``folder_paths.get_folder_paths(key)`` (in standalone mode the
+        mock serves arbitrary keys from ``settings.json.folder_paths``).
+        Legacy aliases the host normalizes onto a canonical key (``clip`` ->
+        ``text_encoders``) are collapsed first so the same folders are not
+        reported twice.
+        """
+        try:
+            folder_path_map: Dict[str, List[str]] = {}
+            for key in self._collapse_legacy_folder_keys(
+                self._get_enabled_other_folder_keys()
+            ):
+                try:
+                    folder_path_map[key] = folder_paths.get_folder_paths(key)
+                except Exception as exc:
+                    logger.debug("Error reading folder paths for '%s': %s", key, exc)
+
+            (
+                unique_paths,
+                self.other_root_subtypes,
+                self.other_folder_roots,
+            ) = self._prepare_other_paths(folder_path_map)
+
+            logger.info(
+                "Found other model roots:"
+                + ("\n - " + "\n - ".join(unique_paths) if unique_paths else "[]")
+            )
+
+            if not unique_paths:
+                logger.info("No valid other-model folders found in configuration")
+                return []
+
+            return unique_paths
+        except Exception as e:
+            logger.warning(f"Error initializing other model paths: {e}")
+            return []
+
+    def refresh_other_roots(self) -> None:
+        """Rebuild other-model roots after the management toggles changed.
+
+        Called when ``enable_other_models`` / ``enabled_other_sub_types`` are
+        updated so the scanner immediately reflects the new folder set without
+        a full application restart.
+        """
+        self.other_roots = self._init_other_paths()
+        self._rebuild_preview_roots()
+
+    def get_other_models_availability(self) -> Dict[str, Any]:
+        """Report the other-model folders the host can actually expose.
+
+        Independent of the opt-in ``enable_other_models`` toggle: this answers
+        "could Other Models management work here at all?". ComfyUI mode almost
+        always has these folder keys registered, while standalone mode only
+        knows the keys present in ``settings.json.folder_paths`` - so the UI
+        uses this to decide whether announcing the feature would be actionable.
+
+        Returns:
+            ``{"available": bool, "sub_types": {sub_type: [existing roots]}}``.
+            A folder only counts when it exists on disk; an empty folder still
+            counts because CivitAI downloads can target it.
+        """
+        sub_types: Dict[str, List[str]] = {}
+        try:
+            keys = self._collapse_legacy_folder_keys(
+                list(OTHER_MODEL_FOLDER_SUBTYPES.keys())
+            )
+        except Exception:  # pragma: no cover - defensive
+            keys = list(OTHER_MODEL_FOLDER_SUBTYPES.keys())
+
+        for key in keys:
+            sub_type = OTHER_MODEL_FOLDER_SUBTYPES.get(key)
+            if not sub_type:
+                continue
+            try:
+                raw_paths = folder_paths.get_folder_paths(key)
+            except Exception as exc:
+                logger.debug("Error probing folder paths for '%s': %s", key, exc)
+                continue
+
+            bucket = sub_types.setdefault(sub_type, [])
+            for root in sorted(
+                self._dedupe_existing_paths(raw_paths or []).values(),
+                key=lambda path: path.lower(),
+            ):
+                if root not in bucket:
+                    bucket.append(root)
+
+        available_sub_types = {
+            sub_type: roots for sub_type, roots in sub_types.items() if roots
+        }
+        return {
+            "available": bool(available_sub_types),
+            "sub_types": available_sub_types,
+        }
+
     def get_preview_static_url(self, preview_path: str) -> str:
         if not preview_path:
             return ""

py/lora_manager.py

@@ -219,6 +219,7 @@ class LoraManager:
             lora_scanner = await ServiceRegistry.get_lora_scanner()
             checkpoint_scanner = await ServiceRegistry.get_checkpoint_scanner()
             embedding_scanner = await ServiceRegistry.get_embedding_scanner()
+            other_scanner = await ServiceRegistry.get_other_scanner()
 
             # Initialize recipe scanner if needed
             recipe_scanner = await ServiceRegistry.get_recipe_scanner()
@@ -236,6 +237,10 @@ class LoraManager:
                     embedding_scanner.initialize_in_background(),
                     name="embedding_cache_init",
                 ),
+                asyncio.create_task(
+                    other_scanner.initialize_in_background(),
+                    name="other_cache_init",
+                ),
                 asyncio.create_task(
                     recipe_scanner.initialize_in_background(), name="recipe_cache_init"
                 ),
@@ -328,6 +333,7 @@ class LoraManager:
             all_roots.update(config.loras_roots)
             all_roots.update(config.base_models_roots or [])
             all_roots.update(config.embeddings_roots or [])
+            all_roots.update(config.other_roots or [])
 
             total_deleted = 0
             total_size_freed = 0
@@ -460,7 +466,7 @@ class LoraManager:
             # Cancel any in-flight scanner initialization tasks so thread-pool
             # workers (e.g. _initialize_cache_sync) can break out of their loops
             # when the server shuts down (e.g. Ctrl+C on WSL).
-            for name in ("lora_scanner", "checkpoint_scanner", "embedding_scanner"):
+            for name in ("lora_scanner", "checkpoint_scanner", "embedding_scanner", "other_scanner"):
                 scanner = ServiceRegistry.get_service_sync(name)
                 if scanner is not None and hasattr(scanner, "cancel_task"):
                     scanner.cancel_task()

py/metadata_ops/__init__.py

@@ -36,6 +36,7 @@ SCANNER_TYPE_MAP: dict[str, str] = {
     "get_lora_scanner": "lora",
     "get_checkpoint_scanner": "checkpoint",
     "get_embedding_scanner": "embedding",
+    "get_other_scanner": "other",
 }
 
 SCANNER_GETTER_NAMES = tuple(SCANNER_TYPE_MAP.keys())
@@ -80,8 +81,8 @@ async def _find_scanner_for_model(
 
 
 async def identify_model_type(model_path: str) -> str:
-    """Determine the model type (``\"lora\"``, ``\"checkpoint\"``, or
-    ``\"embedding\"``) for *model_path*.
+    """Determine the model type (``\"lora\"``, ``\"checkpoint\"``,
+    ``\"embedding\"``, or ``\"other\"``) for *model_path*.
 
     Falls back to ``\"lora\"`` when unknown.
     """

py/routes/base_model_routes.py

@@ -149,6 +149,7 @@ class BaseModelRoutes(ABC):
             settings_service=self._settings,
             server_i18n=self._server_i18n,
             logger=logger,
+            page_context_provider=self._get_page_context_provider(),
         )
         listing = ModelListingHandler(
             service=service,
@@ -250,6 +251,10 @@ class BaseModelRoutes(ABC):
         """Get expected model types string for error messages - to be overridden by subclasses."""
         return "any model type"
 
+    def _get_page_context_provider(self):
+        """Optional hook returning extra template context for the page view."""
+        return None
+
     def _find_model_file(self, files):
         """Find the appropriate model file from the files list - can be overridden by subclasses."""
         return next((file for file in files if file.get("type") in MODEL_WEIGHT_FILE_TYPES and file.get("primary") is True), None)

py/routes/handlers/download_routing_handlers.py

@@ -0,0 +1,110 @@
+"""HTTP handler for download target routing decisions."""
+
+from __future__ import annotations
+
+import json
+import logging
+
+from aiohttp import web
+
+from ...services.download_routing import (
+    is_diffusion_model_download,
+    resolve_other_download_sub_type,
+)
+from ...utils.constants import VALID_OTHER_CIVITAI_TYPES
+
+logger = logging.getLogger(__name__)
+
+
+class DownloadRoutingHandler:
+    """Expose the download-time checkpoint/diffusion-model routing decision.
+
+    The web UI calls this when the user reaches the download location step
+    so the root dropdown offers the same root set (checkpoint vs unet) that
+    the download manager would pick for ``use_default_paths``.
+    """
+
+    async def get_download_routing(self, request: web.Request) -> web.Response:
+        try:
+            payload = await request.json()
+        except json.JSONDecodeError:
+            return web.json_response(
+                {"success": False, "error": "Invalid JSON payload"}, status=400
+            )
+
+        model_type = payload.get("model_type", "")
+        base_model = payload.get("base_model") or ""
+        file_types = payload.get("file_types") or []
+        selected_file_type = payload.get("selected_file_type")
+
+        if not isinstance(model_type, str) or not model_type:
+            return web.json_response(
+                {"success": False, "error": "model_type is required"}, status=400
+            )
+        if not isinstance(base_model, str) or not isinstance(file_types, list):
+            return web.json_response(
+                {
+                    "success": False,
+                    "error": "base_model must be a string and file_types a list",
+                },
+                status=400,
+            )
+        if selected_file_type is not None and not isinstance(selected_file_type, str):
+            return web.json_response(
+                {"success": False, "error": "selected_file_type must be a string"},
+                status=400,
+            )
+
+        if model_type.lower() in VALID_OTHER_CIVITAI_TYPES:
+            from ...services.settings_manager import get_settings_manager
+
+            settings = get_settings_manager()
+            if not settings.is_other_models_enabled():
+                # Opt-in feature is off: never auto-route, the UI falls back to
+                # manual folder selection and the download manager rejects it.
+                return web.json_response(
+                    {
+                        "success": True,
+                        "root_kind": "other",
+                        "sub_type": None,
+                        "disabled": True,
+                        "reason": "other_models_disabled",
+                    }
+                )
+
+            sub_type = resolve_other_download_sub_type(
+                model_type,
+                file_types=(str(t) for t in file_types),
+                selected_file_type=selected_file_type,
+            )
+            if sub_type and not settings.is_other_sub_type_enabled(sub_type):
+                return web.json_response(
+                    {
+                        "success": True,
+                        "root_kind": "other",
+                        "sub_type": None,
+                        "disabled": True,
+                        "reason": "other_sub_type_disabled",
+                        "requested_sub_type": sub_type,
+                    }
+                )
+            return web.json_response(
+                {
+                    "success": True,
+                    "root_kind": "other",
+                    "sub_type": sub_type,
+                }
+            )
+
+        is_diffusion = is_diffusion_model_download(
+            model_type,
+            file_types=(str(t) for t in file_types),
+            base_model=base_model,
+        )
+        return web.json_response(
+            {
+                "success": True,
+                "is_diffusion_model": is_diffusion,
+                "root_kind": "unet" if is_diffusion else model_type,
+            }
+        )

py/routes/handlers/hf_handlers.py

@@ -122,12 +122,8 @@ async def _save_hf_metadata(dest_path: str, repo: str, model_root: str) -> None:
         metadata._unknown_fields["hf_url"] = hf_url
         metadata.from_civitai = False  # HF models are not from CivitAI
 
-        metadata_dict = metadata.to_dict()
-        if "trainedWords" in metadata_dict and not metadata_dict["trainedWords"]:
-            del metadata_dict["trainedWords"]
-
         # 3. Save metadata atomically
-        await MetadataManager.save_metadata(dest_path, metadata_dict)
+        await MetadataManager.save_metadata(dest_path, metadata)
         logger.info("Saved HF metadata (with hf_url) for %s", dest_path)
 
         # 4. Determine relative folder path for cache
@@ -244,7 +240,10 @@ class HfHandler:
                 })
 
             existing["hf_url"] = hf_url
-            existing["from_civitai"] = False
+            # NOTE: deliberately do NOT touch `from_civitai` here. It records
+            # where the metadata came from, and the UI must show the CivitAI
+            # link whenever CivitAI data is present — linking HuggingFace must
+            # not hide it (#1094). HF provenance is tracked via `hf_url`.
             await MetadataManager.save_metadata(file_path, existing)
 
             await _add_to_scanner_cache(file_path, existing)

py/routes/handlers/misc_handlers.py

@@ -53,9 +53,11 @@ from ...utils.constants import (
     PREVIEW_EXTENSIONS,
     SUPPORTED_MEDIA_EXTENSIONS,
     VALID_LORA_TYPES,
+    VALID_OTHER_CIVITAI_TYPES,
 )
 from .hf_handlers import HfHandler
 from .agent_handlers import AgentHandler
+from .download_routing_handlers import DownloadRoutingHandler
 from .model_handlers import ModelCivitaiHandler
 from ...utils.civitai_utils import rewrite_preview_url
 from ...utils.example_images_paths import (
@@ -657,9 +659,21 @@ class HealthCheckHandler:
             "lora": ServiceRegistry.get_lora_scanner,
             "checkpoint": ServiceRegistry.get_checkpoint_scanner,
             "embedding": ServiceRegistry.get_embedding_scanner,
+            "other": ServiceRegistry.get_other_scanner,
             "recipe": ServiceRegistry.get_recipe_scanner,
         }
 
+    def _active_scanner_getters(
+        self,
+    ) -> Mapping[str, Callable[[], Awaitable[Any]]]:
+        """Drop the opt-in other scanner while Other Models is disabled."""
+        getters = self._scanner_getters
+        if "other" not in getters:
+            return getters
+        if get_settings_manager().is_other_models_enabled():
+            return getters
+        return {name: getter for name, getter in getters.items() if name != "other"}
+
     async def health_check(self, request: web.Request) -> web.Response:
         return web.json_response({"status": "ok"})
 
@@ -671,7 +685,7 @@ class HealthCheckHandler:
         page accepts the update and only reloads once all scanners are done.
         """
         pending: list[str] = []
-        for name, getter in self._scanner_getters.items():
+        for name, getter in self._active_scanner_getters().items():
             try:
                 scanner = await getter()
             except Exception:
@@ -756,10 +770,19 @@ class DoctorHandler:
                 ("lora", "LoRAs", ServiceRegistry.get_lora_scanner),
                 ("checkpoint", "Checkpoints", ServiceRegistry.get_checkpoint_scanner),
                 ("embedding", "Embeddings", ServiceRegistry.get_embedding_scanner),
+                ("other", "Other Models", ServiceRegistry.get_other_scanner),
             )
         )
         self._app_version_getter = app_version_getter
 
+    def _active_scanner_factories(
+        self,
+    ) -> Sequence[tuple[str, str, Callable[[], Awaitable[Any]]]]:
+        """Drop the opt-in other scanner while Other Models is disabled."""
+        if self._settings.is_other_models_enabled():
+            return self._scanner_factories
+        return tuple(entry for entry in self._scanner_factories if entry[0] != "other")
+
     async def get_doctor_diagnostics(self, request: web.Request) -> web.Response:
         try:
             client_version = (request.query.get("clientVersion") or "").strip()
@@ -807,7 +830,7 @@ class DoctorHandler:
         repaired: list[dict[str, Any]] = []
         failures: list[dict[str, str]] = []
 
-        for model_type, label, factory in self._scanner_factories:
+        for model_type, label, factory in self._active_scanner_factories():
             try:
                 scanner = await factory()
                 await scanner.get_cached_data(force_refresh=True, rebuild_cache=True)
@@ -839,7 +862,7 @@ class DoctorHandler:
         renamed: list[dict[str, Any]] = []
 
         try:
-            for model_type, label, factory in self._scanner_factories:
+            for model_type, label, factory in self._active_scanner_factories():
                 try:
                     scanner = await factory()
                     hash_index = getattr(scanner, "_hash_index", None)
@@ -1071,7 +1094,7 @@ class DoctorHandler:
         overall_status = "ok"
         summary = "All model caches look healthy."
 
-        for model_type, label, factory in self._scanner_factories:
+        for model_type, label, factory in self._active_scanner_factories():
             try:
                 scanner = await factory()
                 persisted = None
@@ -1156,7 +1179,7 @@ class DoctorHandler:
         total_conflict_groups = 0
         total_conflict_files = 0
 
-        for model_type, label, factory in self._scanner_factories:
+        for model_type, label, factory in self._active_scanner_factories():
             # Duplicate filename detection targets LoRAs which use basename-only
             # syntax (<lora:name:strength>). Checkpoints/embeddings reference
             # models via relative paths with extensions, so conflicts there would
@@ -1536,6 +1559,22 @@ class SettingsHandler:
             response_data["civitai_api_key_set"] = bool(raw_key)
             raw_llm_key = self._settings.get("llm_api_key")
             response_data["llm_api_key_set"] = bool(raw_llm_key)
+            # Derived capability flag (not persisted): whether the host exposes
+            # any other-model folder at all. Standalone installs only know the
+            # folder_paths keys present in settings.json, so the announcement
+            # banner uses this to avoid promising a page that cannot list
+            # anything.
+            try:
+                availability = config.get_other_models_availability()
+                response_data["other_models_paths_available"] = bool(
+                    availability.get("available")
+                )
+            except Exception as availability_error:  # pragma: no cover - defensive
+                logger.debug(
+                    "Could not resolve Other Models availability: %s",
+                    availability_error,
+                )
+                response_data["other_models_paths_available"] = None
             settings_file = getattr(self._settings, "settings_file", None)
             if settings_file:
                 response_data["settings_file"] = settings_file
@@ -2065,6 +2104,7 @@ class ServiceRegistryAdapter:
     get_embedding_scanner: Callable[[], Awaitable[Any]]
     get_downloaded_version_history_service: Callable[[], Awaitable[Any]]
     get_backup_service: Callable[[], Awaitable[Any]] = _noop_backup_service
+    get_other_scanner: Callable[[], Awaitable[Any]] = ServiceRegistry.get_other_scanner
 
 
 class ModelLibraryHandler:
@@ -2089,6 +2129,8 @@ class ModelLibraryHandler:
             return "checkpoint"
         if normalized in {"embedding", "textualinversion"}:
             return "embedding"
+        if normalized in VALID_OTHER_CIVITAI_TYPES:
+            return "other"
         return None
 
     async def _get_scanner_for_type(self, model_type: str | None):
@@ -2099,6 +2141,13 @@ class ModelLibraryHandler:
             return normalized_type, await self._service_registry.get_checkpoint_scanner()
         if normalized_type == "embedding":
             return normalized_type, await self._service_registry.get_embedding_scanner()
+        if normalized_type == "other":
+            # Opt-in feature: the other scanner only resolves while the master
+            # switch is on, so callers keep returning the legacy "required"
+            # error (400) when it is off.
+            if not get_settings_manager().is_other_models_enabled():
+                return None, None
+            return normalized_type, await self._service_registry.get_other_scanner()
         return None, None
 
     async def _get_download_history_service(self):
@@ -2190,6 +2239,11 @@ class ModelLibraryHandler:
             lora_scanner = await self._service_registry.get_lora_scanner()
             checkpoint_scanner = await self._service_registry.get_checkpoint_scanner()
             embedding_scanner = await self._service_registry.get_embedding_scanner()
+            # Opt-in: probe the other scanner only while Other Models is enabled,
+            # so the disabled behaviour stays byte-identical to the legacy one.
+            other_scanner = None
+            if get_settings_manager().is_other_models_enabled():
+                other_scanner = await self._service_registry.get_other_scanner()
 
             if model_version_id_str:
                 try:
@@ -2228,6 +2282,13 @@ class ModelLibraryHandler:
                     exists = True
                     model_type = "embedding"
                     matched_scanner = embedding_scanner
+                elif (
+                    other_scanner
+                    and await other_scanner.check_model_version_exists(model_version_id)
+                ):
+                    exists = True
+                    model_type = "other"
+                    matched_scanner = other_scanner
 
                 if exists:
                     return web.json_response(
@@ -2245,7 +2306,7 @@ class ModelLibraryHandler:
                 history_service = await self._get_download_history_service()
                 has_been_downloaded = False
                 history_type = None
-                for candidate_type in ("lora", "checkpoint", "embedding"):
+                for candidate_type in ("lora", "checkpoint", "embedding", "other"):
                     if await history_service.has_been_downloaded(
                         candidate_type,
                         model_version_id,
@@ -2267,6 +2328,7 @@ class ModelLibraryHandler:
             lora_versions = await lora_scanner.get_model_versions_by_id(model_id)
             checkpoint_versions = []
             embedding_versions = []
+            other_versions = []
             if not lora_versions and checkpoint_scanner:
                 checkpoint_versions = await checkpoint_scanner.get_model_versions_by_id(
                     model_id
@@ -2275,6 +2337,13 @@ class ModelLibraryHandler:
                 embedding_versions = await embedding_scanner.get_model_versions_by_id(
                     model_id
                 )
+            if (
+                not lora_versions
+                and not checkpoint_versions
+                and not embedding_versions
+                and other_scanner
+            ):
+                other_versions = await other_scanner.get_model_versions_by_id(model_id)
 
             model_type = None
             versions = []
@@ -2306,9 +2375,18 @@ class ModelLibraryHandler:
                         "downloadedVersionIds": [],
                     }
                 )
+            if other_versions:
+                return web.json_response(
+                    {
+                        "success": True,
+                        "modelType": "other",
+                        "versions": self._with_downloaded_flag(other_versions),
+                        "downloadedVersionIds": [],
+                    }
+                )
 
             history_service = await self._get_download_history_service()
-            for candidate_type in ("lora", "checkpoint", "embedding"):
+            for candidate_type in ("lora", "checkpoint", "embedding", "other"):
                 candidate_downloaded_version_ids = (
                     await history_service.get_downloaded_version_ids(
                         candidate_type,
@@ -2363,6 +2441,11 @@ class ModelLibraryHandler:
             lora_scanner = await self._service_registry.get_lora_scanner()
             checkpoint_scanner = await self._service_registry.get_checkpoint_scanner()
             embedding_scanner = await self._service_registry.get_embedding_scanner()
+            # Opt-in: keep the other probe last so model cards for lora /
+            # checkpoint / embedding ids are unaffected by the extra scanner.
+            other_scanner = None
+            if get_settings_manager().is_other_models_enabled():
+                other_scanner = await self._service_registry.get_other_scanner()
 
             results: list[dict[str, Any]] = []
             for model_id in model_ids:
@@ -2398,6 +2481,17 @@ class ModelLibraryHandler:
                         })
                         continue
 
+                if other_scanner:
+                    other_versions = await other_scanner.get_model_versions_by_id(model_id)
+                    if other_versions:
+                        results.append({
+                            "modelId": model_id,
+                            "modelType": "other",
+                            "versions": self._with_downloaded_flag(other_versions),
+                            "downloadedVersionIds": [],
+                        })
+                        continue
+
                 results.append({
                     "modelId": model_id,
                     "modelType": None,
@@ -2786,12 +2880,32 @@ class ModelLibraryHandler:
                 model_type.lower() for model_type in CIVITAI_USER_MODEL_TYPES
             }
             lora_type_aliases = {model_type.lower() for model_type in VALID_LORA_TYPES}
+            other_type_aliases = {
+                model_type.lower() for model_type in VALID_OTHER_CIVITAI_TYPES
+            }
+
+            # Acquire the other scanner lazily so adapters without it only
+            # fail when the payload actually contains other-type models.
+            # While the opt-in feature is off the scanner still exists (its
+            # cache is empty), so other types simply report inLibrary=False.
+            needs_other_scanner = any(
+                isinstance(model, dict)
+                and str(model.get("type", "")).lower() in other_type_aliases
+                for model in models
+            )
+            other_scanner = None
+            if needs_other_scanner:
+                other_scanner = await self._service_registry.get_other_scanner()
 
             type_scanner_map: Dict[str, Any] = {
                 **{alias: lora_scanner for alias in lora_type_aliases},
                 "checkpoint": checkpoint_scanner,
                 "textualinversion": embedding_scanner,
             }
+            if other_scanner is not None:
+                type_scanner_map.update(
+                    {alias: other_scanner for alias in other_type_aliases}
+                )
 
             versions: list[dict[str, Any]] = []
             history_service = await self._get_download_history_service()
@@ -2815,12 +2929,17 @@ class ModelLibraryHandler:
                 "embedding",
                 model_ids,
             )
+            other_downloaded = await history_service.get_downloaded_version_ids_bulk(
+                "other",
+                model_ids,
+            )
             downloaded_version_map: Dict[str, Dict[int, set[int]]] = {
                 "lora": lora_downloaded,
                 "locon": lora_downloaded,
                 "dora": lora_downloaded,
                 "checkpoint": checkpoint_downloaded,
                 "textualinversion": embedding_downloaded,
+                **{alias: other_downloaded for alias in VALID_OTHER_CIVITAI_TYPES},
             }
             for model in models:
                 if not isinstance(model, dict):
@@ -3884,6 +4003,7 @@ class MiscHandlerSet:
         base_model: BaseModelHandlerSet,
         hf_handler: Any = None,
         agent_handler: Any = None,
+        download_routing: Any = None,
     ) -> None:
         self.health = health
         self.settings = settings
@@ -3904,6 +4024,7 @@ class MiscHandlerSet:
         self.base_model = base_model
         self.hf_handler = hf_handler
         self.agent_handler = agent_handler
+        self.download_routing = download_routing
 
     def to_route_mapping(
         self,
@@ -3962,6 +4083,8 @@ class MiscHandlerSet:
             "get_agent_skills": self.agent_handler.get_agent_skills,
             "execute_agent_skill": self.agent_handler.execute_agent_skill,
             "cancel_agent_skill": self.agent_handler.cancel_agent_skill,
+            # Download routing handler
+            "get_download_routing": self.download_routing.get_download_routing,
             # Base model handlers
             "get_base_models": self.base_model.get_base_models,
             "refresh_base_models": self.base_model.refresh_base_models,
@@ -3975,6 +4098,7 @@ def build_service_registry_adapter() -> ServiceRegistryAdapter:
         get_lora_scanner=ServiceRegistry.get_lora_scanner,
         get_checkpoint_scanner=ServiceRegistry.get_checkpoint_scanner,
         get_embedding_scanner=ServiceRegistry.get_embedding_scanner,
+        get_other_scanner=ServiceRegistry.get_other_scanner,
         get_downloaded_version_history_service=ServiceRegistry.get_downloaded_version_history_service,
         get_backup_service=ServiceRegistry.get_backup_service,
     )

py/routes/handlers/model_handlers.py

@@ -90,6 +90,7 @@ class ModelPageView:
         settings_service: SettingsManager,
         server_i18n,
         logger: logging.Logger,
+        page_context_provider: Callable[[web.Request], Dict[str, Any]] | None = None,
     ) -> None:
         self._template_env = template_env
         self._template_name = template_name
@@ -97,6 +98,7 @@ class ModelPageView:
         self._settings = settings_service
         self._server_i18n = server_i18n
         self._logger = logger
+        self._page_context_provider = page_context_provider
 
     def _load_supporters(self) -> dict[str, Any]:
         """Load supporters data from JSON file."""
@@ -210,6 +212,16 @@ class ModelPageView:
                     self._logger.error("Error loading cache data: %s", cache_error)
                     template_context["is_initializing"] = True
 
+            if self._page_context_provider is not None:
+                try:
+                    extra_context = self._page_context_provider(request)
+                    if isinstance(extra_context, dict):
+                        template_context.update(extra_context)
+                except Exception as context_error:  # pragma: no cover - logging path
+                    self._logger.error(
+                        "Error building page context: %s", context_error
+                    )
+
             rendered = self._template_env.get_template(self._template_name).render(
                 **template_context
             )

py/routes/handlers/pending_delete_handler.py

@@ -35,6 +35,7 @@ _MODEL_TYPE_GETTER_NAMES: Dict[str, str] = {
     "loras": "get_lora_scanner",
     "checkpoints": "get_checkpoint_scanner",
     "embeddings": "get_embedding_scanner",
+    "other": "get_other_scanner",
 }
 
 # Staged batch ids are ``uuid.uuid4().hex`` (32 lowercase hex chars). The id is

py/routes/handlers/recipe_handlers.py

@@ -74,6 +74,26 @@ async def _read_preview_dims(path: str) -> Optional[Tuple[int, int]]:
         return await asyncio.to_thread(ExifUtils.get_image_dimensions, path)
 
 
+async def _parse_relaxed_flag(request: web.Request) -> bool:
+    """Read the relaxed-rematch flag from the JSON body or query string.
+
+    The flag defaults to False (strict candidacy). A JSON body value wins;
+    ``?relaxed=true`` is honored as a fallback so GET-only clients can opt
+    in. Body parse failures (empty/invalid JSON) are treated as "no flag".
+    """
+    relaxed = False
+    if request.can_read_body:
+        try:
+            data = await request.json()
+        except Exception:  # noqa: BLE001 - any parse failure means no flag
+            data = None
+        if isinstance(data, dict):
+            relaxed = bool(data.get("relaxed"))
+    if not relaxed:
+        relaxed = request.query.get("relaxed", "").lower() == "true"
+    return relaxed
+
+
 @dataclass(frozen=True)
 class RecipeHandlerSet:
     """Group of handlers providing recipe route implementations."""
@@ -812,6 +832,8 @@ class RecipeManagementHandler:
 
             recipe_scanner.reset_cancellation()
 
+            relaxed = await _parse_relaxed_flag(request)
+
             async def progress_callback(data):
                 await self._ws_manager.broadcast_recipe_rematch_progress(data)
 
@@ -819,7 +841,8 @@ class RecipeManagementHandler:
             async def run_rematch():
                 try:
                     await recipe_scanner.rematch_all_recipes(
-                        progress_callback=progress_callback
+                        progress_callback=progress_callback,
+                        relaxed=relaxed,
                     )
                 except Exception as e:
                     self._logger.error(
@@ -892,7 +915,13 @@ class RecipeManagementHandler:
                     status=400,
                 )
 
-            result = await recipe_scanner.rematch_recipes_bulk(recipe_ids)
+            relaxed = bool(data.get("relaxed")) or (
+                request.query.get("relaxed", "").lower() == "true"
+            )
+
+            result = await recipe_scanner.rematch_recipes_bulk(
+                recipe_ids, relaxed=relaxed
+            )
             return web.json_response(result)
         except Exception as exc:
             self._logger.error(
@@ -921,7 +950,10 @@ class RecipeManagementHandler:
                 )
 
             recipe_id = request.match_info["recipe_id"]
-            result = await recipe_scanner.rematch_recipe_by_id(recipe_id)
+            relaxed = await _parse_relaxed_flag(request)
+            result = await recipe_scanner.rematch_recipe_by_id(
+                recipe_id, relaxed=relaxed
+            )
             return web.json_response(result)
         except RecipeNotFoundError as exc:
             return web.json_response({"success": False, "error": str(exc)}, status=404)
@@ -3092,6 +3124,12 @@ class RecipeWorkflowHandler:
 class BatchImportHandler:
     """Handle batch import operations for recipes."""
 
+    # Virtual path token for the Windows drive list. Browsing up from a drive
+    # root (e.g. C:\) lands here so users can switch drives without typing a
+    # path. Only meaningful on Windows; elsewhere it falls through to normal
+    # path handling and fails the existence check.
+    WINDOWS_DRIVES_TOKEN = "__drives__"
+
     def __init__(
         self,
         *,
@@ -3265,31 +3303,27 @@ class BatchImportHandler:
             data = await request.json()
             directory_path = data.get("path", "")
 
+            if os.name == "nt" and directory_path == self.WINDOWS_DRIVES_TOKEN:
+                return self._windows_drives_response()
+
+            # Default to the user's home directory. The frontend previously
+            # sent "/" as the initial path, which is POSIX-only: on Windows it
+            # resolves to the current drive root and then fails the access
+            # check below.
             if not directory_path:
-                return web.json_response(
-                    {"success": False, "error": "Directory path is required"},
-                    status=400,
-                )
+                path = Path.home()
+            else:
+                path = Path(directory_path).expanduser().resolve()
 
-            # Normalize the path
-            path = Path(directory_path).expanduser().resolve()
-
-            # Security check: ensure path is within allowed directories
-            # Allow common image/model directories
-            allowed_roots = [
-                Path.home(),
-                Path("/"),  # Allow browsing from root for flexibility
-            ]
-
-            # Check if path is within any allowed root
-            is_allowed = False
-            for root in allowed_roots:
-                try:
-                    path.relative_to(root)
-                    is_allowed = True
-                    break
-                except ValueError:
-                    continue
+            # Access check: browsing intentionally covers the whole server
+            # filesystem (the server operator browses their own machine). On
+            # POSIX every absolute path is under "/", but Path("/") has no
+            # drive letter on Windows and can never anchor a drive-qualified
+            # path in relative_to(), so test for a drive there instead.
+            if os.name == "nt":
+                is_allowed = bool(path.drive)
+            else:
+                is_allowed = path.is_absolute()
 
             if not is_allowed:
                 return web.json_response(
@@ -3356,15 +3390,24 @@ class BatchImportHandler:
                 directories.sort(key=lambda x: x["name"].lower())
                 image_files.sort(key=lambda x: x["name"].lower())
 
-                # Add parent directory if not at root
-                parent_path = path.parent
-                show_parent = str(path) != str(path.root)
+                # Parent directory. A filesystem root is its own parent
+                # (parent == path): POSIX "/" gets no parent, while a Windows
+                # drive root (C:\) links up to the virtual drive list so users
+                # can switch drives. The previous str(path) != str(path.root)
+                # check misfired on Windows, where a drive root's parent is
+                # itself, producing an infinite self-loop.
+                if path.parent == path:
+                    parent_path = (
+                        self.WINDOWS_DRIVES_TOKEN if os.name == "nt" else None
+                    )
+                else:
+                    parent_path = str(path.parent)
 
                 return web.json_response(
                     {
                         "success": True,
                         "current_path": str(path),
-                        "parent_path": str(parent_path) if show_parent else None,
+                        "parent_path": parent_path,
                         "directories": directories,
                         "image_files": image_files,
                         "image_count": len(image_files),
@@ -3391,3 +3434,30 @@ class BatchImportHandler:
         except Exception as exc:
             self._logger.error("Error browsing directory: %s", exc, exc_info=True)
             return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    def _windows_drives_response(self) -> web.Response:
+        """List available drive letters as a virtual directory (Windows only)."""
+        try:
+            drives = os.listdrives()
+        except AttributeError:  # Python < 3.12
+            drives = [
+                f"{letter}:\\"
+                for letter in "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
+                if os.path.exists(f"{letter}:\\")
+            ]
+        directories = [
+            {"name": drive, "path": drive, "is_parent": False} for drive in drives
+        ]
+        return web.json_response(
+            {
+                "success": True,
+                # Empty current_path marks the virtual level; the frontend
+                # disables folder selection there.
+                "current_path": "",
+                "parent_path": None,
+                "directories": directories,
+                "image_files": [],
+                "image_count": 0,
+                "directory_count": len(directories),
+            }
+        )

py/routes/misc_route_registrar.py

@@ -103,6 +103,10 @@ MISC_ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
     RouteDefinition(
         "GET", "/api/lm/hf-repo-files", "get_hf_repo_files"
     ),
+    # Download target routing decision (checkpoint vs diffusion model roots)
+    RouteDefinition(
+        "POST", "/api/lm/download/routing", "get_download_routing"
+    ),
     RouteDefinition(
         "POST", "/api/lm/download-hf-model", "download_hf_model"
     ),

py/routes/misc_routes.py

@@ -41,6 +41,7 @@ from .handlers.misc_handlers import (
 from .handlers.base_model_handlers import BaseModelHandlerSet
 from .handlers.hf_handlers import HfHandler
 from .handlers.agent_handlers import AgentHandler
+from .handlers.download_routing_handlers import DownloadRoutingHandler
 from .misc_route_registrar import MiscRouteRegistrar
 
 logger = logging.getLogger(__name__)
@@ -140,6 +141,7 @@ class MiscRoutes:
         base_model = BaseModelHandlerSet()
         hf_handler = HfHandler()
         agent_handler = AgentHandler()
+        download_routing = DownloadRoutingHandler()
 
         return self._handler_set_factory(
             health=health,
@@ -161,6 +163,7 @@ class MiscRoutes:
             base_model=base_model,
             hf_handler=hf_handler,
             agent_handler=agent_handler,
+            download_routing=download_routing,
         )
 
 

py/routes/other_routes.py

@@ -0,0 +1,139 @@
+import logging
+import os
+from typing import Any, Dict, List
+from aiohttp import web
+
+from .base_model_routes import BaseModelRoutes
+from .model_route_registrar import ModelRouteRegistrar
+from ..config import config
+from ..services.other_model_service import OtherModelService
+from ..services.service_registry import ServiceRegistry
+from ..utils.constants import (
+    CIVITAI_TYPE_TO_OTHER_SUB_TYPE,
+    OTHER_MODEL_FOLDER_SUBTYPES,
+    VALID_OTHER_CIVITAI_TYPES,
+)
+
+logger = logging.getLogger(__name__)
+
+
+class OtherRoutes(BaseModelRoutes):
+    """Other-model-specific route controller (VAE, upscaler, text encoder, ...)"""
+
+    def __init__(self):
+        """Initialize Other-model routes with OtherModel service"""
+        super().__init__()
+        self.template_name = "other.html"
+
+    async def initialize_services(self):
+        """Initialize services from ServiceRegistry"""
+        other_scanner = await ServiceRegistry.get_other_scanner()
+        update_service = await ServiceRegistry.get_model_update_service()
+        self.service = OtherModelService(other_scanner, update_service=update_service)
+        self.set_model_update_service(update_service)
+
+        # Attach service dependencies
+        self.attach_service(self.service)
+
+    def setup_routes(self, app: web.Application, prefix: str = "other"):
+        """Setup Other-model routes"""
+        # Schedule service initialization on app startup
+        app.on_startup.append(lambda _: self.initialize_services())
+
+        # Setup common routes with 'other' prefix (includes page route)
+        super().setup_routes(app, prefix)
+
+    def setup_specific_routes(self, registrar: ModelRouteRegistrar, prefix: str):
+        """Setup Other-model-specific routes"""
+        # Other-model info by name
+        registrar.add_prefixed_route('GET', '/api/lm/{prefix}/info/{name}', prefix, self.get_other_model_info)
+        # Other-model roots grouped by sub_type (text_encoders + legacy clip
+        # are aggregated under text_encoder)
+        registrar.add_prefixed_route('GET', '/api/lm/{prefix}/roots_by_subtype', prefix, self.get_roots_by_subtype)
+
+    def _validate_civitai_model_type(self, model_type: str) -> bool:
+        """Validate CivitAI model type for other models.
+
+        Accepts retired CivitAI types (CLIP, CLIPVision) as well — grandfathered
+        models on CivitAI still carry them. Types whose sub_type is currently
+        disabled (or every type while the opt-in feature is off) are rejected.
+        """
+        normalized = (model_type or "").strip().lower()
+        if normalized not in VALID_OTHER_CIVITAI_TYPES:
+            return False
+        if not self._settings.is_other_models_enabled():
+            return False
+
+        sub_type = CIVITAI_TYPE_TO_OTHER_SUB_TYPE.get(normalized)
+        if sub_type is None:
+            # CivitAI "Other" has no sub_type of its own; it is only usable
+            # while at least one sub_type is enabled.
+            return bool(self._settings.get_enabled_other_sub_types())
+        return self._settings.is_other_sub_type_enabled(sub_type)
+
+    def _get_page_context_provider(self):
+        """Expose the opt-in feature state to the Other Models page template."""
+        return self._page_context_for_other
+
+    def _page_context_for_other(self, request: web.Request) -> Dict[str, Any]:
+        if not self._settings.is_other_models_enabled():
+            return {"other_disabled": True, "other_no_paths": False}
+
+        # Enabled but nothing to scan: folder paths for the managed sub_types
+        # resolved to no existing folder. Render an actionable empty state
+        # instead of an apparently broken empty grid.
+        standalone_mode = os.environ.get("LORA_MANAGER_STANDALONE", "0") == "1"
+        return {
+            "other_disabled": False,
+            "other_no_paths": not bool(config.other_roots),
+            "standalone_mode": standalone_mode,
+        }
+
+    def _get_expected_model_types(self) -> str:
+        """Get expected model types string for error messages"""
+        return "VAE, Upscaler, TextEncoder, CLIPVision, Controlnet, or Other"
+
+    def _parse_specific_params(self, request: web.Request) -> Dict[str, Any]:
+        """Parse other-model-specific parameters (none in Phase 1)."""
+        return {}
+
+    async def get_roots_by_subtype(self, request: web.Request) -> web.Response:
+        """Return other-model roots grouped by sub_type.
+
+        Aggregates the per-folder_paths-key roots from config
+        (``text_encoders`` and the legacy ``clip`` key both land under
+        ``text_encoder``).
+        """
+        try:
+            roots_by_subtype: Dict[str, List[str]] = {}
+            for key, roots in (config.other_folder_roots or {}).items():
+                sub_type = OTHER_MODEL_FOLDER_SUBTYPES.get(key)
+                if not sub_type:
+                    continue
+                bucket = roots_by_subtype.setdefault(sub_type, [])
+                for root in roots:
+                    if root and root not in bucket:
+                        bucket.append(root)
+            return web.json_response(
+                {"success": True, "roots_by_subtype": roots_by_subtype}
+            )
+        except Exception as e:
+            logger.error(f"Error getting other roots by sub_type: {e}", exc_info=True)
+            return web.json_response(
+                {"success": False, "error": str(e)}, status=500
+            )
+
+    async def get_other_model_info(self, request: web.Request) -> web.Response:
+        """Get detailed information for a specific other model by name"""
+        try:
+            name = request.match_info.get('name', '')
+            model_info = await self.service.get_model_info_by_name(name)  # pyright: ignore[reportAttributeAccessIssue]
+
+            if model_info:
+                return web.json_response(model_info)
+            else:
+                return web.json_response({"error": "Model not found"}, status=404)
+
+        except Exception as e:
+            logger.error(f"Error in get_other_model_info: {e}", exc_info=True)
+            return web.json_response({"error": str(e)}, status=500)

py/services/agent/agent_service.py

@@ -407,7 +407,6 @@ class AgentService:
             "base_model": metadata.get("base_model", ""),
             "tags": metadata.get("tags", []),
             "modelDescription": metadata.get("modelDescription", ""),
-            "trainedWords": metadata.get("trainedWords", []),
             "sha256": (metadata.get("sha256") or "")[:16] + "..." if metadata.get("sha256") else "",
             "size": metadata.get("size", 0),
         }

py/services/agent/post_processor.py

@@ -92,7 +92,10 @@ class PostProcessor:
         preview_downloaded = False
 
         # -- Determine whether this is an HF-sourced model -----------------
-        is_hf_model = not metadata.get("from_civitai", True)
+        # Key off `hf_url` directly: `from_civitai` records provenance and can
+        # be true for a model that is also linked to HuggingFace (both sources
+        # coexist, see #1094), so it must not gate HF enrichment.
+        is_hf_model = bool(metadata.get("hf_url", ""))
 
         # -- Collect updates -----------------------------------------------
         updates: Dict[str, Any] = {}

py/services/aria2_downloader.py

@@ -161,6 +161,11 @@ class Aria2Downloader:
         (typically an expired CivitAI signed URL): a fresh URL is resolved
         and the partial download continues.  Recovery is bounded by
         ``MAX_TRANSFER_RECOVERY_ATTEMPTS``.
+
+        Cancellation never leaks daemon transfers: the gid is tracked in
+        ``_transfers`` before any post-``addUri`` await, and a gid accepted
+        by the daemon while the caller is being cancelled is removed again
+        before the ``CancelledError`` propagates.
         """
 
         await self._ensure_process()
@@ -251,7 +256,11 @@ class Aria2Downloader:
                 await asyncio.sleep(self._poll_interval)
         finally:
             current = self._transfers.get(download_id)
-            if current is not None and current.gid == transfer.gid:
+            if (
+                transfer is not None
+                and current is not None
+                and current.gid == transfer.gid
+            ):
                 self._transfers.pop(download_id, None)
 
     async def _get_status_with_retry(
@@ -339,21 +348,43 @@ class Aria2Downloader:
             resolved_url != url,
         )
 
+        # Shield the addUri RPC from cancellation: the daemon may accept the
+        # download even when the caller is cancelled while the request is in
+        # flight.  On cancellation, wait for the RPC result so the freshly
+        # created gid can be removed instead of leaking an untracked
+        # download that keeps running in the daemon.
+        add_task = asyncio.ensure_future(
+            self._rpc_call("aria2.addUri", [[resolved_url], options])
+        )
         try:
-            gid = await self._rpc_call("aria2.addUri", [[resolved_url], options])
+            gid = await asyncio.shield(add_task)
+        except asyncio.CancelledError:
+            leaked_gid: Any = None
+            try:
+                leaked_gid = await add_task
+            except Exception:
+                leaked_gid = None
+            if isinstance(leaked_gid, str) and leaked_gid:
+                logger.info(
+                    "Removing aria2 gid %s accepted while download %s was "
+                    "being cancelled",
+                    leaked_gid,
+                    download_id,
+                )
+                try:
+                    await self._rpc_call("aria2.forceRemove", [leaked_gid])
+                except Exception as exc:
+                    logger.warning(
+                        "Failed to remove leaked aria2 gid %s for download %s: %s",
+                        leaked_gid,
+                        download_id,
+                        exc,
+                    )
+            raise
         except Exception as exc:
             raise Aria2Error(f"Failed to schedule aria2 download: {exc}") from exc
 
         logger.debug("aria2 accepted download %s with gid %s", download_id, gid)
-        await self._state_store.upsert(
-            download_id,
-            {
-                "gid": gid,
-                "save_path": save_path,
-                "status": "downloading",
-                "url": url,
-            },
-        )
         return gid
 
     async def _register_transfer(
@@ -372,7 +403,46 @@ class Aria2Downloader:
             headers=headers,
         )
         transfer = Aria2Transfer(gid=gid, save_path=os.path.abspath(save_path))
+        # Register the transfer before any further await: once the daemon
+        # holds the gid, cancel_download() must be able to find it.  An await
+        # in between would open a window where a concurrent cancel reports
+        # "Download task not found" and the daemon keeps downloading
+        # untracked.
         self._transfers[download_id] = transfer
+        try:
+            await self._state_store.upsert(
+                download_id,
+                {
+                    "gid": gid,
+                    "save_path": transfer.save_path,
+                    "status": "downloading",
+                    "url": url,
+                },
+            )
+        except asyncio.CancelledError:
+            # The task was cancelled while persisting state and the
+            # coordinator's cancel ran before the transfer was registered
+            # above.  Remove the daemon transfer unless it was deliberately
+            # paused (skip_download preserves paused transfers for resume).
+            status = None
+            try:
+                status = await self.get_status(download_id)
+            except Exception:
+                status = None
+            if status is not None and status.get("status") != "paused":
+                try:
+                    await self._rpc_call("aria2.forceRemove", [gid])
+                except Exception as exc:
+                    logger.warning(
+                        "Failed to remove aria2 gid %s for cancelled download %s: %s",
+                        gid,
+                        download_id,
+                        exc,
+                    )
+                current = self._transfers.get(download_id)
+                if current is not None and current.gid == gid:
+                    self._transfers.pop(download_id, None)
+            raise
         return transfer
 
     async def get_status(self, download_id: str) -> Optional[Dict[str, Any]]:

py/services/base_model_service.py

@@ -7,7 +7,7 @@ import logging
 import os
 import time
 
-from ..utils.constants import VALID_LORA_SUB_TYPES, VALID_CHECKPOINT_SUB_TYPES
+from ..utils.constants import VALID_LORA_SUB_TYPES, VALID_CHECKPOINT_SUB_TYPES, VALID_OTHER_SUB_TYPES
 from ..utils.models import BaseModelMetadata
 from ..utils.metadata_manager import MetadataManager
 from ..utils.usage_stats import UsageStats
@@ -904,6 +904,11 @@ class BaseModelService(ABC):
                 and normalized_type not in VALID_CHECKPOINT_SUB_TYPES
             ):
                 continue
+            if (
+                self.model_type == "other"
+                and normalized_type not in VALID_OTHER_SUB_TYPES
+            ):
+                continue
 
             type_counts[normalized_type] = type_counts.get(normalized_type, 0) + 1
 

py/services/checkpoint_scanner.py

@@ -410,6 +410,10 @@ class CheckpointScanner(ModelScanner):
 
         return None
 
+    def resolve_sub_type_for_path(self, file_path: Optional[str]) -> Optional[str]:
+        """Resolve sub_type from the configured root that contains the file."""
+        return self._resolve_sub_type(self._find_root_for_file(file_path))
+
     def adjust_metadata(self, metadata, file_path, root_path):
         """Adjust metadata during scanning to set sub_type."""
         sub_type = self._resolve_sub_type(root_path)
@@ -419,9 +423,7 @@ class CheckpointScanner(ModelScanner):
 
     def adjust_cached_entry(self, entry: Dict[str, Any]) -> Dict[str, Any]:
         """Adjust entries loaded from the persisted cache to ensure sub_type is set."""
-        sub_type = self._resolve_sub_type(
-            self._find_root_for_file(entry.get("file_path"))
-        )
+        sub_type = self.resolve_sub_type_for_path(entry.get("file_path"))
         if sub_type:
             entry["sub_type"] = sub_type
         return entry

py/services/download_manager.py

@@ -17,13 +17,18 @@ from dataclasses import dataclass, field
 import uuid
 from typing import Any, Dict, Iterable, List, Optional, Set, Tuple, cast
 from urllib.parse import urlparse
-from ..utils.models import LoraMetadata, CheckpointMetadata, EmbeddingMetadata
+from ..utils.models import (
+    LoraMetadata,
+    CheckpointMetadata,
+    EmbeddingMetadata,
+    OtherModelMetadata,
+)
 from ..utils.constants import (
     CARD_PREVIEW_WIDTH,
-    DIFFUSION_MODEL_BASE_MODELS,
     MODEL_WEIGHT_FILE_TYPES,
     SUPPORTED_DOWNLOAD_SKIP_BASE_MODELS,
     VALID_LORA_TYPES,
+    VALID_OTHER_CIVITAI_TYPES,
 )
 from ..utils.civitai_utils import normalize_civitai_download_url, rewrite_preview_url
 from ..utils.file_utils import calculate_sha256, calculate_autov3
@@ -32,6 +37,7 @@ from ..utils.utils import sanitize_folder_name
 from ..utils.exif_utils import ExifUtils
 from ..utils.metadata_manager import MetadataManager
 from .service_registry import ServiceRegistry
+from .download_routing import is_diffusion_model_download, resolve_other_download_sub_type
 from .settings_manager import get_settings_manager
 from .metadata_service import get_default_metadata_provider, get_metadata_provider
 from .downloader import get_downloader, DownloadProgress, DownloadStreamControl
@@ -228,12 +234,21 @@ class DownloadManager:
             return False
 
     async def _get_scanner_for_model_type(self, model_type: str):
-        """Return the scanner responsible for the given model type."""
+        """Return the scanner responsible for the given model type.
+
+        Every supported type resolves explicitly — an unknown type must never
+        fall through to the lora scanner (an "other" download would silently
+        dedupe against the lora library).
+        """
         if model_type == "checkpoint":
             return await self._get_checkpoint_scanner()
         if model_type == "embedding":
             return await ServiceRegistry.get_embedding_scanner()
-        return await self._get_lora_scanner()
+        if model_type == "other":
+            return await ServiceRegistry.get_other_scanner()
+        if model_type == "lora":
+            return await self._get_lora_scanner()
+        raise ValueError(f'Unknown model type "{model_type}"')
 
     @staticmethod
     def _resolve_target_file(
@@ -978,6 +993,8 @@ class DownloadManager:
             return CheckpointMetadata.from_civitai_info(version_info, file_info, save_path)
         if model_type == "embedding":
             return EmbeddingMetadata.from_civitai_info(version_info, file_info, save_path)
+        if model_type == "other":
+            return OtherModelMetadata.from_civitai_info(version_info, file_info, save_path)
         return LoraMetadata.from_civitai_info(version_info, file_info, save_path)
 
     def _resolve_save_path_from_persisted_record(self, record: Dict[str, Any]) -> Optional[str]:
@@ -1438,6 +1455,7 @@ class DownloadManager:
                 lora_scanner = await self._get_lora_scanner()
                 checkpoint_scanner = await self._get_checkpoint_scanner()
                 embedding_scanner = await ServiceRegistry.get_embedding_scanner()
+                other_scanner = await ServiceRegistry.get_other_scanner()
 
                 # Check lora scanner first
                 if await lora_scanner.check_model_version_exists(model_version_id):
@@ -1462,6 +1480,13 @@ class DownloadManager:
                         "error": "Model version already exists in embedding library",
                     }
 
+                # Check other scanner
+                if await other_scanner.check_model_version_exists(model_version_id):
+                    return {
+                        "success": False,
+                        "error": "Model version already exists in other library",
+                    }
+
             # Use CivArchive provider directly when source is 'civarchive'
             # This prioritizes CivArchive metadata (with mirror availability info) over Civitai
             if source == "civarchive":
@@ -1500,6 +1525,20 @@ class DownloadManager:
                 model_type = "lora"
             elif model_type_from_info == "textualinversion":
                 model_type = "embedding"
+            elif model_type_from_info in VALID_OTHER_CIVITAI_TYPES:
+                if not get_settings_manager().is_other_models_enabled():
+                    return {
+                        "success": False,
+                        "error": (
+                            "Other Models management is disabled. Enable it in "
+                            "Settings > Library before downloading VAE, upscaler, "
+                            "text encoder or CLIP files."
+                        ),
+                        # Machine-readable failure code consumed by the companion
+                        # browser extension (docs/other-models-support.md C4).
+                        "reason": "other_models_disabled",
+                    }
+                model_type = "other"
             else:
                 return {
                     "success": False,
@@ -1621,27 +1660,13 @@ class DownloadManager:
                 }
 
             # Check if this checkpoint should be treated as a diffusion model
-            # Priority: (1) any file has type "UNet" or "Diffusion Model",
-            #            (2) baseModel is in DIFFUSION_MODEL_BASE_MODELS
-            is_diffusion_model = False
-            if model_type == "checkpoint":
-                # Check file types first (more direct signal from CivitAI)
-                version_files = version_info.get("files", [])
-                for f in version_files:
-                    f_type = f.get("type", "")
-                    if f_type in ("UNet", "Diffusion Model"):
-                        is_diffusion_model = True
-                        logger.info(
-                            f"File type '{f_type}' detected, routing checkpoint to unet folder"
-                        )
-                        break
-
-                # Fallback to baseModel name check
-                if not is_diffusion_model and base_model_value in DIFFUSION_MODEL_BASE_MODELS:
-                    is_diffusion_model = True
-                    logger.info(
-                        f"baseModel '{base_model_value}' is a known diffusion model, routing to unet folder"
-                    )
+            # (shared with the download routing endpoint so the UI location
+            # step and the actual download agree on the target roots).
+            is_diffusion_model = is_diffusion_model_download(
+                model_type,
+                file_types=(f.get("type", "") for f in version_info.get("files", [])),
+                base_model=base_model_value,
+            )
 
             # Existence check after the metadata fetch (#1058):
             # - An explicit file selection only blocks when THIS file is
@@ -1700,6 +1725,13 @@ class DownloadManager:
                             "success": False,
                             "error": "Model version already exists in embedding library",
                         }
+                elif model_type == "other":
+                    other_scanner = await ServiceRegistry.get_other_scanner()
+                    if await other_scanner.check_model_version_exists(version_id):
+                        return {
+                            "success": False,
+                            "error": "Model version already exists in other library",
+                        }
 
             # Handle use_default_paths
             if use_default_paths:
@@ -1739,6 +1771,60 @@ class DownloadManager:
                                 "error": "Default embedding root path not set in settings",
                             }
                         save_dir = default_path
+                    elif model_type == "other":
+                        other_sub_type = resolve_other_download_sub_type(
+                            model_type_from_info,
+                            file_types=(
+                                f.get("type", "")
+                                for f in version_info.get("files", [])
+                                if isinstance(f, dict)
+                            ),
+                            selected_file_type=(
+                                target_file.get("type") if explicit_file else None
+                            ),
+                        )
+                        default_other_roots = (
+                            settings_manager.get("default_other_roots") or {}
+                        )
+                        if other_sub_type and not settings_manager.is_other_sub_type_enabled(
+                            other_sub_type
+                        ):
+                            return {
+                                "success": False,
+                                "error": (
+                                    f"Other-model sub-type '{other_sub_type}' is "
+                                    f"disabled in settings. Please pick a destination "
+                                    f"folder explicitly instead of using default paths."
+                                ),
+                                "reason": "other_sub_type_disabled",
+                            }
+                        default_path = (
+                            default_other_roots.get(other_sub_type)
+                            if other_sub_type
+                            else None
+                        )
+                        if not isinstance(default_path, str) or not default_path:
+                            if other_sub_type:
+                                detail = (
+                                    f"No default root configured for other-model "
+                                    f"sub-type '{other_sub_type}'"
+                                )
+                                reason = "other_no_default_root"
+                            else:
+                                detail = (
+                                    "Could not determine the other-model sub-type "
+                                    "from the model metadata"
+                                )
+                                reason = "other_sub_type_undecidable"
+                            return {
+                                "success": False,
+                                "error": (
+                                    f"{detail}. Please pick a destination folder "
+                                    f"explicitly instead of using default paths."
+                                ),
+                                "reason": reason,
+                            }
+                        save_dir = default_path
 
                 # Calculate relative path using template
                 relative_path = self._calculate_relative_path(version_info, model_type)
@@ -1935,6 +2021,11 @@ class DownloadManager:
                     version_info, file_info, save_path
                 )
                 logger.info(f"Creating EmbeddingMetadata for {file_name}")
+            elif model_type == "other":
+                metadata = OtherModelMetadata.from_civitai_info(
+                    version_info, file_info, save_path
+                )
+                logger.info(f"Creating OtherModelMetadata for {file_name}")
             else:
                 return {
                     "success": False,
@@ -2147,6 +2238,8 @@ class DownloadManager:
                 scanner = await self._get_checkpoint_scanner()
             elif model_type == "embedding":
                 scanner = await ServiceRegistry.get_embedding_scanner()
+            elif model_type == "other":
+                scanner = await ServiceRegistry.get_other_scanner()
         except Exception as exc:
             logger.debug("Failed to acquire scanner for %s models: %s", model_type, exc)
 
@@ -2643,6 +2736,9 @@ class DownloadManager:
             elif model_type == "embedding":
                 scanner = await ServiceRegistry.get_embedding_scanner()
                 logger.info(f"Updating embedding cache for {actual_file_paths[0]}")
+            elif model_type == "other":
+                scanner = await ServiceRegistry.get_other_scanner()
+                logger.info(f"Updating other-model cache for {actual_file_paths[0]}")
 
             adjust_cached_entry = (
                 getattr(scanner, "adjust_cached_entry", None)
@@ -2732,7 +2828,7 @@ class DownloadManager:
             return {"success": False, "error": str(e)}
 
     def _get_supported_extensions_for_type(self, model_type: str) -> Set[str]:
-        if model_type == "checkpoint":
+        if model_type in ("checkpoint", "other"):
             return {
                 ".ckpt",
                 ".pt",

py/services/download_routing.py

@@ -0,0 +1,103 @@
+"""Shared download routing logic.
+
+Decides whether a download initiated from the checkpoint library should be
+routed to the unet/diffusion-model roots instead of the checkpoint roots.
+Used by both the download manager (at download time) and the download
+routing HTTP endpoint (when the user picks a location in the UI), so the
+two can never disagree.
+"""
+
+from __future__ import annotations
+
+import logging
+from typing import Iterable, Optional
+
+from ..utils.constants import (
+    CIVITAI_FILE_TYPE_TO_OTHER_SUB_TYPE,
+    CIVITAI_TYPE_TO_OTHER_SUB_TYPE,
+    DIFFUSION_MODEL_BASE_MODELS,
+)
+
+logger = logging.getLogger(__name__)
+
+# File types reported by the CivitAI API that indicate a raw diffusion
+# model (loaded via UNETLoader in ComfyUI) rather than a full checkpoint.
+DIFFUSION_FILE_TYPES = frozenset({"UNet", "Diffusion Model"})
+
+
+def is_diffusion_model_download(
+    model_type: str,
+    file_types: Iterable[str] = (),
+    base_model: str = "",
+) -> bool:
+    """Return True when a download should be routed to the unet roots.
+
+    Only applies to downloads initiated from the checkpoint library.
+    Priority: (1) any file has type "UNet" or "Diffusion Model" (the more
+    direct signal from CivitAI), (2) baseModel is a known diffusion model.
+    """
+    if model_type != "checkpoint":
+        return False
+
+    for file_type in file_types:
+        if file_type in DIFFUSION_FILE_TYPES:
+            logger.info(
+                "File type '%s' detected, routing checkpoint to unet folder",
+                file_type,
+            )
+            return True
+
+    if base_model in DIFFUSION_MODEL_BASE_MODELS:
+        logger.info(
+            "baseModel '%s' is a known diffusion model, routing to unet folder",
+            base_model,
+        )
+        return True
+
+    return False
+
+
+def resolve_other_download_sub_type(
+    civitai_model_type: str,
+    file_types: Iterable[str] = (),
+    selected_file_type: Optional[str] = None,
+) -> Optional[str]:
+    """Resolve the "other"-page sub_type for a download.
+
+    Fixed priority (locked design, docs/plans/other-models-page.md §9.2):
+
+    1. Explicit user file pick — when the picked file's type maps, it wins
+       even when model.type maps to something else.
+    2. model.type via CIVITAI_TYPE_TO_OTHER_SUB_TYPE.
+    3. file.type fallback — only when model.type maps to nothing. Must NOT
+       override a mapped model.type: checkpoint models routinely bundle
+       VAE/Text Encoder component files.
+    4. Still undecidable -> None (caller must ask the user for a folder).
+    """
+    if selected_file_type:
+        mapped = CIVITAI_FILE_TYPE_TO_OTHER_SUB_TYPE.get(selected_file_type)
+        if mapped:
+            logger.info(
+                "Explicit file pick type '%s' routes other download to '%s'",
+                selected_file_type,
+                mapped,
+            )
+            return mapped
+
+    normalized_model_type = (civitai_model_type or "").strip().lower()
+    mapped = CIVITAI_TYPE_TO_OTHER_SUB_TYPE.get(normalized_model_type)
+    if mapped:
+        return mapped
+
+    for file_type in file_types:
+        mapped = CIVITAI_FILE_TYPE_TO_OTHER_SUB_TYPE.get(file_type)
+        if mapped:
+            logger.info(
+                "model.type '%s' unmapped; file type '%s' routes other download to '%s'",
+                civitai_model_type,
+                file_type,
+                mapped,
+            )
+            return mapped
+
+    return None

py/services/llm_service.py

@@ -11,6 +11,7 @@ from __future__ import annotations
 import asyncio
 import json
 import logging
+import time
 from typing import Any, Dict, List, Optional
 
 import aiohttp
@@ -32,8 +33,26 @@ _catalog_cache: Optional[Dict[str, List[str]]] = None
 # ``{provider_id: {model_id: max_output_tokens}}``.
 _model_output_limits: Dict[str, Dict[str, int]] = {}
 
+# Monotonic timestamp of the last failed catalog fetch (None = no failure
+# yet).  Failed fetches are negatively cached: further calls return the
+# empty fallback without hitting the network until the cooldown elapses,
+# so users on broken networks don't stall on every settings-modal open.
+_catalog_last_failure: Optional[float] = None
+_CATALOG_FAILURE_COOLDOWN = 600.0  # seconds
+
+# Serializes catalog fetches so concurrent callers don't duplicate requests.
+_catalog_lock = asyncio.Lock()
+
 _CATALOG_TIMEOUT = aiohttp.ClientTimeout(total=30)
 
+# Cloudflare serves brotli when the client advertises it, and brotli is a
+# required dependency here — a corrupted br stream can crash the native
+# decoder with a Windows access violation (issue #1099).  Request gzip
+# instead; zlib decompression is not affected and corrupt gzip data only
+# raises ContentEncodingError (an aiohttp.ClientError subclass), which the
+# exception handlers below already catch.
+_NO_BROTLI_HEADERS = {"Accept-Encoding": "gzip, deflate"}
+
 
 async def _load_model_catalog() -> Dict[str, List[str]]:
     """Fetch and parse the model catalog.
@@ -46,61 +65,85 @@ async def _load_model_catalog() -> Dict[str, List[str]]:
     value has a ``models`` sub-dict keyed by model ID.  The result is cached
     in memory after the first successful fetch.
     Subsequent calls return the cached data immediately.
+
+    Failed fetches are negatively cached: further calls return an empty
+    dict without hitting the network until ``_CATALOG_FAILURE_COOLDOWN``
+    has elapsed, so a broken network does not stall every settings-modal
+    open.  Concurrent callers are serialized behind :data:`_catalog_lock`
+    so only one request is ever in flight.
     """
-    global _catalog_cache, _model_output_limits
+    global _catalog_cache, _model_output_limits, _catalog_last_failure
     if _catalog_cache is not None:
         return _catalog_cache
 
-    try:
-        async with aiohttp.ClientSession(timeout=_CATALOG_TIMEOUT) as session:
-            async with session.get(_MODEL_CATALOG_URL) as resp:
-                if resp.status != 200:
-                    logger.warning("Model catalog returned HTTP %s", resp.status)
-                    return _catalog_cache or {}
-                data = await resp.json()
-    except (aiohttp.ClientError, asyncio.TimeoutError, json.JSONDecodeError, UnicodeDecodeError) as exc:
-        logger.warning("Failed to fetch model catalog: %s", exc)
-        return _catalog_cache or {}
+    async with _catalog_lock:
+        # Re-check under the lock: another caller may have fetched (or
+        # failed) while we were waiting.
+        if _catalog_cache is not None:
+            return _catalog_cache
+        if (
+            _catalog_last_failure is not None
+            and time.monotonic() - _catalog_last_failure < _CATALOG_FAILURE_COOLDOWN
+        ):
+            logger.debug(
+                "Skipping model catalog fetch: last attempt failed %.0fs ago",
+                time.monotonic() - _catalog_last_failure,
+            )
+            return {}
 
-    if not isinstance(data, dict):
-        logger.warning("Model catalog is not a dict, got %s", type(data).__name__)
-        return _catalog_cache or {}
+        try:
+            async with aiohttp.ClientSession(timeout=_CATALOG_TIMEOUT) as session:
+                async with session.get(_MODEL_CATALOG_URL, headers=_NO_BROTLI_HEADERS) as resp:
+                    if resp.status != 200:
+                        logger.warning("Model catalog returned HTTP %s", resp.status)
+                        _catalog_last_failure = time.monotonic()
+                        return {}
+                    data = await resp.json()
+        except (aiohttp.ClientError, asyncio.TimeoutError, json.JSONDecodeError, UnicodeDecodeError) as exc:
+            logger.warning("Failed to fetch model catalog: %s", exc)
+            _catalog_last_failure = time.monotonic()
+            return {}
 
-    result: Dict[str, List[str]] = {}
-    output_limits: Dict[str, Dict[str, int]] = {}
-    for provider_id, provider_info in data.items():
-        if not isinstance(provider_info, dict):
-            continue
-        models_dict = provider_info.get("models")
-        if not isinstance(models_dict, dict):
-            continue
-        model_ids: List[str] = []
-        provider_limits: Dict[str, int] = {}
-        for mid, model_info in models_dict.items():
-            if not isinstance(mid, str):
+        if not isinstance(data, dict):
+            logger.warning("Model catalog is not a dict, got %s", type(data).__name__)
+            _catalog_last_failure = time.monotonic()
+            return {}
+
+        result: Dict[str, List[str]] = {}
+        output_limits: Dict[str, Dict[str, int]] = {}
+        for provider_id, provider_info in data.items():
+            if not isinstance(provider_info, dict):
                 continue
-            model_ids.append(mid)
-            if isinstance(model_info, dict):
-                limit = model_info.get("limit")
-                if isinstance(limit, dict):
-                    output = limit.get("output")
-                    if isinstance(output, (int, float)) and output > 0:
-                        provider_limits[mid] = int(output)
-        if model_ids:
-            result[provider_id] = model_ids
-        if provider_limits:
-            output_limits[provider_id] = provider_limits
+            models_dict = provider_info.get("models")
+            if not isinstance(models_dict, dict):
+                continue
+            model_ids: List[str] = []
+            provider_limits: Dict[str, int] = {}
+            for mid, model_info in models_dict.items():
+                if not isinstance(mid, str):
+                    continue
+                model_ids.append(mid)
+                if isinstance(model_info, dict):
+                    limit = model_info.get("limit")
+                    if isinstance(limit, dict):
+                        output = limit.get("output")
+                        if isinstance(output, (int, float)) and output > 0:
+                            provider_limits[mid] = int(output)
+            if model_ids:
+                result[provider_id] = model_ids
+            if provider_limits:
+                output_limits[provider_id] = provider_limits
 
-    _catalog_cache = result
-    _model_output_limits = output_limits
-    logger.debug(
-        "Loaded model catalog: %d providers, %d total models "
-        "(%d providers have output limits)",
-        len(result),
-        sum(len(m) for m in result.values()),
-        len(output_limits),
-    )
-    return result
+        _catalog_cache = result
+        _model_output_limits = output_limits
+        logger.debug(
+            "Loaded model catalog: %d providers, %d total models "
+            "(%d providers have output limits)",
+            len(result),
+            sum(len(m) for m in result.values()),
+            len(output_limits),
+        )
+        return result
 
 
 def _get_model_max_output(provider: str, model: str) -> Optional[int]:
@@ -126,7 +169,7 @@ async def fetch_ollama_models(api_base: str) -> List[str]:
     url = f"{api_base.rstrip('/')}/models"
     try:
         async with aiohttp.ClientSession(timeout=_OLLAMA_API_TIMEOUT) as session:
-            async with session.get(url) as resp:
+            async with session.get(url, headers=_NO_BROTLI_HEADERS) as resp:
                 if resp.status != 200:
                     logger.debug("Ollama API returned HTTP %s from %s", resp.status, api_base)
                     return []

py/services/model_cache.py

@@ -33,6 +33,11 @@ class ModelCache:
 
     raw_data: List[Dict[str, Any]]
     folders: List[str]
+    # Every directory under the model roots (including empty ones), as
+    # recorded by the last scan/hydration. ``None`` means "never recorded"
+    # (e.g. a persisted snapshot predating this field) and triggers a
+    # background filesystem backfill in the scanner.
+    all_folders: Optional[List[str]] = None
     version_index: Dict[int, Dict[str, Any]] = field(default_factory=dict)
     model_id_index: Dict[int, List[Dict[str, Any]]] = field(default_factory=dict)
     # Multi-valued companion to version_index: every local file entry of a

py/services/model_scanner.py

@@ -62,16 +62,13 @@ def _is_hidden_relative_path(rel_path: str) -> bool:
     return any(part.startswith(".") for part in rel_path.replace(os.sep, "/").split("/"))
 
 
-# TTL (seconds) for the get_all_folders() live-walk cache, so rapid repeated
-# requests (modal open + autocomplete) do not re-walk the model roots.
-ALL_FOLDERS_CACHE_TTL_SECONDS = 5.0
-
 # Maps a scanner model type to the manager page type used in progress
 # broadcasts (e.g. 'lora' -> 'loras').
 PAGE_TYPE_MAP = {
     'lora': 'loras',
     'checkpoint': 'checkpoints',
     'embedding': 'embeddings',
+    'other': 'other',
 }
 
 
@@ -89,6 +86,10 @@ class CacheBuildResult:
     hash_index: ModelHashIndex
     tags_count: Dict[str, int]
     excluded_models: List[str]
+    # Every directory under the model roots (including empty ones) discovered
+    # during the scan, or None when the source has no folder information
+    # (e.g. a persisted snapshot predating folder recording).
+    all_folders: Optional[List[str]] = None
 
 class ModelScanner:
     """Base service for scanning and managing model files"""
@@ -144,8 +145,9 @@ class ModelScanner:
         self._name_display_mode = self._resolve_name_display_mode()
         self._cancel_requested = False  # Flag for cancellation
         self._autov3_backfill_scheduled = False  # One-time AutoV3 backfill trigger per process
-        # Short-lived cache for get_all_folders(): (timestamp, folders) or None
-        self._all_folders_ttl_cache: Optional[Tuple[float, List[str]]] = None
+        # Guard against concurrent all-folders backfill walks (cold fallback
+        # for persisted snapshots that predate folder recording).
+        self._all_folders_backfill_running = False
         try:
             loop = asyncio.get_running_loop()
         except RuntimeError:
@@ -208,8 +210,14 @@ class ModelScanner:
         """
         self._cache_version += 1
 
-    def on_library_changed(self) -> None:
-        """Reset caches when the active library changes."""
+    def on_library_changed(self, reconcile: bool = False) -> None:
+        """Reset caches when the active library changes.
+
+        When ``reconcile`` is True an incremental reconcile runs right after
+        the cache is re-hydrated, so newly configured roots are scanned and
+        entries for removed roots are purged. Used when scanner-affecting
+        settings (e.g. the Other Models toggles) change.
+        """
         self._persistent_cache = get_persistent_cache()
         self._cache = None
         self._hash_index = ModelHashIndex()
@@ -217,7 +225,6 @@ class ModelScanner:
         self._excluded_models = []
         self._is_initializing = False
         self._name_display_mode = self._resolve_name_display_mode()
-        self.invalidate_all_folders_cache()
         self.bump_cache_version()
 
         try:
@@ -228,7 +235,7 @@ class ModelScanner:
         if loop and not loop.is_closed():
             self._loop = loop
             self.loop = loop
-            loop.create_task(self.initialize_in_background())
+            loop.create_task(self.initialize_in_background(reconcile=reconcile))
 
     def _resolve_name_display_mode(self) -> str:
         """Return the configured display mode for name sorting."""
@@ -459,8 +466,14 @@ class ModelScanner:
         _, license_flags = resolve_license_info(license_source)
         entry['license_flags'] = license_flags
 
-    async def initialize_in_background(self) -> None:
-        """Initialize cache in background using thread pool"""
+    async def initialize_in_background(self, reconcile: bool = False) -> None:
+        """Initialize cache in background using thread pool
+
+        Args:
+            reconcile: When True and a persisted snapshot is hydrated, run an
+                incremental reconcile afterwards so the cache matches the
+                current root configuration.
+        """
         try:
             # Set initial empty cache to avoid None reference errors
             if self._cache is None:
@@ -500,6 +513,11 @@ class ModelScanner:
                 logger.info(
                     f"{self.model_type.capitalize()} cache hydrated from persisted snapshot with {len(self._cache.raw_data)} models"
                 )
+                if reconcile:
+                    # Root configuration changed (e.g. Other Models toggles):
+                    # pick up newly enabled folders and drop rows for folders
+                    # that are no longer managed.
+                    await self.get_cached_data(force_refresh=True)
                 return
 
             # Persistent load failed; fall back to a full scan
@@ -662,21 +680,33 @@ class ModelScanner:
         if not persisted or not persisted.raw_data:
             return None
 
+        # Drop entries the scanner no longer manages (e.g. an other-model
+        # sub_type the user just disabled) before rebuilding the indexes, so
+        # hash/autov3 lookups cannot resolve to unmanaged files either.
+        kept_items = [
+            item
+            for item in persisted.raw_data
+            if self._should_keep_cached_entry(item)
+        ]
+        kept_paths = {
+            item.get("file_path") for item in kept_items if item.get("file_path")
+        }
+
         hash_index = ModelHashIndex()
         for sha_value, path in persisted.hash_rows:
-            if sha_value and path:
+            if sha_value and path and path in kept_paths:
                 hash_index.add_entry(sha_value.lower(), path)
 
         # Rebuild the AutoV3 index from the persisted autov3_index rows. These
         # cover every known autov3 -> path mapping regardless of whether a
         # sha256 row also exists for the same file.
         for autov3_value, path in persisted.autov3_hash_rows:
-            if autov3_value and path:
+            if autov3_value and path and path in kept_paths:
                 hash_index.add_autov3(autov3_value.lower(), path)
 
         tags_count: Dict[str, int] = {}
         adjusted_raw_data: List[Dict[str, Any]] = []
-        for item in persisted.raw_data:
+        for item in kept_items:
             # load_cache builds a fresh dict per row, and validate_batch below
             # works on its own per-entry copy when auto_repair=True, so no
             # additional dict copy is needed here.
@@ -702,7 +732,8 @@ class ModelScanner:
             raw_data=valid_entries,
             hash_index=hash_index,
             tags_count=tags_count,
-            excluded_models=list(persisted.excluded_models)
+            excluded_models=list(persisted.excluded_models),
+            all_folders=list(persisted.all_folders) if persisted.all_folders is not None else None,
         )
         return scan_result, invalid_entries
 
@@ -737,6 +768,7 @@ class ModelScanner:
                 hash_snapshot,
                 list(scan_result.excluded_models),
                 autov3_snapshot,
+                scan_result.all_folders,
             )
         except Exception as exc:
             logger.warning("%s Scanner: Failed to persist cache: %s", self.model_type.capitalize(), exc)
@@ -784,7 +816,12 @@ class ModelScanner:
             raw_data=list(self._cache.raw_data),
             hash_index=self._hash_index,
             tags_count=dict(self._tags_count),
-            excluded_models=list(self._excluded_models)
+            excluded_models=list(self._excluded_models),
+            all_folders=(
+                list(self._cache.all_folders)
+                if self._cache.all_folders is not None
+                else None
+            ),
         )
         await self._save_persistent_cache(snapshot)
         await self._sync_download_history(snapshot.raw_data, source='scan')
@@ -1005,20 +1042,36 @@ class ModelScanner:
             await self._broadcast_scan_progress('started', 'reconcile_scan', 0, False)
             
             # Get current cached file paths
+            cached_size_before = len(self._cache.raw_data)
             cached_paths = {item['file_path'] for item in self._cache.raw_data}
             path_to_item = {item['file_path']: item for item in self._cache.raw_data}
-            cached_real_paths = {}
-            for cached_path in cached_paths:
-                try:
-                    cached_real_paths.setdefault(os.path.realpath(cached_path), cached_path)
-                except Exception:
-                    continue
+
+            # physical path -> cached business path, for the alias case where the
+            # same file is reachable under a different path than the cached one
+            # (overlapping roots / symlink layout changes): keep the existing
+            # entry instead of delete + re-add (which would re-read metadata and
+            # re-hash every file). Built lazily on the first miss, because a
+            # realpath per cached entry is ~half the cost of a no-change
+            # reconcile and the map is only ever consulted for misses.
+            cached_real_paths: Optional[Dict[str, str]] = None
+
+            def lookup_cached_real_path(real_path: str) -> Optional[str]:
+                nonlocal cached_real_paths
+                if cached_real_paths is None:
+                    cached_real_paths = {}
+                    for cached_path in cached_paths:
+                        try:
+                            cached_real_paths.setdefault(os.path.realpath(cached_path), cached_path)
+                        except Exception:
+                            continue
+                return cached_real_paths.get(real_path)
             
             # Track found files and new files
             found_paths = set()
             new_files = []
             visited_real_paths = set()
             discovered_real_files = set()
+            discovered_folders: Set[str] = set()
 
             # Scan all model roots
             for root_path in self.get_model_roots():
@@ -1033,19 +1086,31 @@ class ModelScanner:
                         continue
                     visited_real_paths.add(real_root)
 
+                    # Record every visited directory (including empty ones) so
+                    # the folder tree stays accurate without a live walk.
+                    rel_dir = os.path.relpath(
+                        os.path.abspath(root), os.path.abspath(root_path)
+                    ).replace(os.path.sep, "/")
+                    if rel_dir != "." and not _is_hidden_relative_path(rel_dir):
+                        discovered_folders.add(rel_dir)
+
                     for file in files:
                         ext = os.path.splitext(file)[1].lower()
                         if ext in self.file_extensions:
                             # Construct paths exactly as they would be in cache
                             file_path = os.path.join(root, file).replace(os.sep, '/')
-                            real_file_path = os.path.realpath(os.path.join(root, file))
-                            
+
                             # Check if this file is already in cache
                             if file_path in cached_paths:
                                 found_paths.add(file_path)
                                 continue
 
-                            cached_real_match = cached_real_paths.get(real_file_path)
+                            # Only a cache miss needs the physical path, so the
+                            # realpath syscalls are paid per changed file rather
+                            # than per file in the library.
+                            real_file_path = os.path.realpath(os.path.join(root, file))
+
+                            cached_real_match = lookup_cached_real_path(real_file_path)
                             if cached_real_match:
                                 found_paths.add(cached_real_match)
                                 continue
@@ -1090,6 +1155,9 @@ class ModelScanner:
                 total_new = len(new_files)
                 processed_new = 0
                 last_progress_time = time.time()
+                # Snapshot the roots once: this matches the walk above (which
+                # also snapshots them) and avoids a config read per new file.
+                model_roots = self.get_model_roots()
                 for i in range(0, total_new, batch_size):
                     batch = new_files[i:i+batch_size]
                     for path in batch:
@@ -1098,12 +1166,10 @@ class ModelScanner:
                         try:
                             # Find the appropriate root path for this file
                             root_path = None
-                            model_roots = self.get_model_roots()
+                            normalized_path = os.path.normpath(path)
                             for potential_root in model_roots:
                                 # Normalize both paths for comparison
-                                normalized_path = os.path.normpath(path)
-                                normalized_root = os.path.normpath(potential_root)
-                                if normalized_path.startswith(normalized_root):
+                                if normalized_path.startswith(os.path.normpath(potential_root)):
                                     root_path = potential_root
                                     break
                             
@@ -1200,25 +1266,41 @@ class ModelScanner:
                 # Update cache data
                 self._cache.raw_data = [item for item in self._cache.raw_data if item['file_path'] not in missing_files]
             
-            dedup_removed = 0
-            seen_paths: set[str] = set()
-            deduped: list[Dict[str, Any]] = []
-            for item in reversed(self._cache.raw_data):
-                path = item.get('file_path', '')
-                if path not in seen_paths:
-                    seen_paths.add(path)
-                    deduped.append(item)
-                else:
-                    for tag in item.get('tags', []):
-                        if tag in self._tags_count:
-                            self._tags_count[tag] = max(0, self._tags_count[tag] - 1)
-                            if self._tags_count[tag] == 0:
-                                del self._tags_count[tag]
-                    dedup_removed += 1
-            if dedup_removed > 0:
-                self._cache.raw_data = list(reversed(deduped))
-                total_removed += dedup_removed
+            # Defensive integrity pass: drop entries sharing a business path.
+            # Duplicates can only be introduced by external code rewriting
+            # raw_data directly or by this pass's own appends, so an unchanged
+            # filesystem walk over a clean cache has nothing to clean. The size
+            # mismatch is an O(1) tell that the snapshot already contained
+            # duplicates; skipping the O(N) pass when it is provably clean is
+            # what keeps a no-change Refresh cheap.
+            if cached_size_before != len(cached_paths) or total_added > 0:
+                dedup_removed = 0
+                seen_paths: set[str] = set()
+                deduped: list[Dict[str, Any]] = []
+                for item in reversed(self._cache.raw_data):
+                    path = item.get('file_path', '')
+                    if path not in seen_paths:
+                        seen_paths.add(path)
+                        deduped.append(item)
+                    else:
+                        for tag in item.get('tags', []):
+                            if tag in self._tags_count:
+                                self._tags_count[tag] = max(0, self._tags_count[tag] - 1)
+                                if self._tags_count[tag] == 0:
+                                    del self._tags_count[tag]
+                        dedup_removed += 1
+                if dedup_removed > 0:
+                    self._cache.raw_data = list(reversed(deduped))
+                    total_removed += dedup_removed
             
+            # The walk above visited every directory, so refresh the recorded
+            # folder list (including empty folders) even when no model files
+            # changed — e.g. an empty folder was created or removed externally.
+            sorted_discovered = sorted(discovered_folders, key=lambda x: x.lower())
+            folders_changed = self._cache.all_folders != sorted_discovered
+            if folders_changed:
+                self._cache.all_folders = sorted_discovered
+
             # Resort cache if changes were made
             if total_added > 0 or total_removed > 0:
                 # Update folders list
@@ -1231,6 +1313,8 @@ class ModelScanner:
                 await self._cache.resort()
 
                 await self._persist_current_cache()
+            elif folders_changed:
+                await self._persist_current_cache()
                 
             logger.info(f"{self.model_type.capitalize()} Scanner: Cache reconciliation completed in {time.time() - start_time:.2f} seconds. Added {total_added}, removed {total_removed} models.")
             await self._broadcast_scan_progress(
@@ -1270,22 +1354,73 @@ class ModelScanner:
         raise NotImplementedError("Subclasses must implement get_model_roots")
 
     async def get_all_folders(self) -> List[str]:
+        """Return every known directory under the model roots.
+
+        The directory list (including empty ones) is recorded during cache
+        scans and hydrated from the persisted snapshot, so this is a pure
+        in-memory read — no filesystem walk ever runs on the event loop
+        (walking network roots synchronously used to freeze the whole
+        server, see issue #1110). The result is unioned with the
+        model-derived folders so it is always a superset of
+        ``cache.folders``.
+
+        Cold fallback: when the cache was hydrated from a persisted snapshot
+        that predates folder recording (``all_folders is None``), a one-shot
+        background walk is scheduled off the event loop to backfill and
+        persist the list; until it lands, the models-only folders are
+        returned.
+        """
+        folders: Set[str] = set()
+        cache = self._cache
+        if cache is not None:
+            folders |= {item.get('folder', '') for item in cache.raw_data}
+            recorded = getattr(cache, 'all_folders', None)
+            if recorded is None:
+                self._schedule_all_folders_backfill()
+            else:
+                folders |= set(recorded)
+        else:
+            self._schedule_all_folders_backfill()
+
+        return sorted(folders, key=lambda x: x.lower())
+
+    def _schedule_all_folders_backfill(self) -> None:
+        """Kick off a one-shot background folder walk if none is running."""
+        if self._all_folders_backfill_running:
+            return
+        try:
+            loop = asyncio.get_running_loop()
+        except RuntimeError:
+            return
+        self._all_folders_backfill_running = True
+        loop.create_task(self._run_all_folders_backfill())
+
+    async def _run_all_folders_backfill(self) -> None:
+        """Walk the roots in a worker thread, then record and persist the result."""
+        try:
+            loop = asyncio.get_running_loop()
+            folders = await loop.run_in_executor(None, self._walk_all_folders_sync)
+            cache = self._cache
+            # A scan may have recorded the list while the walk was in flight;
+            # prefer the fresher scan data in that case.
+            if cache is not None and cache.all_folders is None:
+                cache.all_folders = folders
+                await self._persist_current_cache()
+        except Exception as exc:
+            logger.warning(
+                "%s Scanner: all-folders backfill failed: %s",
+                self.model_type.capitalize(),
+                exc,
+            )
+        finally:
+            self._all_folders_backfill_running = False
+
+    def _walk_all_folders_sync(self) -> List[str]:
         """Enumerate every directory under the model roots, live from disk.
 
-        Unlike the models-only ``cache.folders``, this includes empty
-        directories, so it stays accurate even when the in-memory cache was
-        hydrated from a persisted snapshot without a filesystem walk. Hidden
-        directories (any segment starting with '.') and the pending-delete
-        staging dir are excluded. The result is unioned with the model-derived
-        folders so it is always a superset of ``cache.folders``, and cached
-        for ``ALL_FOLDERS_CACHE_TTL_SECONDS`` to avoid repeated walks.
+        Runs in a worker thread. Hidden directories (any segment starting
+        with '.') and the pending-delete staging dir are excluded.
         """
-        now = time.monotonic()
-        if self._all_folders_ttl_cache is not None:
-            cached_at, cached_folders = self._all_folders_ttl_cache
-            if now - cached_at < ALL_FOLDERS_CACHE_TTL_SECONDS:
-                return cached_folders
-
         discovered: Set[str] = set()
         visited_real_paths: Set[str] = set()
 
@@ -1307,17 +1442,7 @@ class ModelScanner:
                 if rel_dir != "." and not _is_hidden_relative_path(rel_dir):
                     discovered.add(rel_dir)
 
-        folders = set(discovered)
-        if self._cache is not None:
-            folders |= {item.get('folder', '') for item in self._cache.raw_data}
-
-        result = sorted(folders, key=lambda x: x.lower())
-        self._all_folders_ttl_cache = (now, result)
-        return result
-
-    def invalidate_all_folders_cache(self) -> None:
-        """Drop the cached get_all_folders() result (e.g. after a move)."""
-        self._all_folders_ttl_cache = None
+        return sorted(discovered, key=lambda x: x.lower())
     
     async def _create_default_metadata(self, file_path: str) -> Optional[BaseModelMetadata]:
         """Get model file info and metadata (extensible for different model types)"""
@@ -1339,6 +1464,23 @@ class ModelScanner:
         """Hook for subclasses: adjust entries loaded from the persisted cache."""
         return entry
 
+    def _should_keep_cached_entry(self, entry: Dict[str, Any]) -> bool:
+        """Hook for subclasses: decide whether a persisted entry is still managed.
+
+        Entries rejected here are dropped (with their hash/autov3 index rows)
+        while hydrating the persisted cache, so a scanner whose configured
+        roots shrank does not surface stale models before the next reconcile.
+        """
+        return True
+
+    def resolve_sub_type_for_path(self, file_path: Optional[str]) -> Optional[str]:
+        """Hook for subclasses: resolve the location-derived sub_type for a file.
+
+        Returns ``None`` when the model type has no location-derived sub-types
+        (the default), in which case any stored value is left untouched.
+        """
+        return None
+
     @staticmethod
     def _normalize_path_value(path: Optional[str]) -> str:
         if not path:
@@ -1533,6 +1675,9 @@ class ModelScanner:
         else:
             self._cache.raw_data = list(scan_result.raw_data)
 
+        if scan_result.all_folders is not None:
+            self._cache.all_folders = list(scan_result.all_folders)
+
         # resort() rebuilds folders and the version index on every path, so a
         # separate rebuild_version_index() call here would be redundant.
         await self._cache.resort()
@@ -1630,6 +1775,7 @@ class ModelScanner:
         processed_files = 0
         processed_real_files: Set[str] = set()
         visited_real_dirs: Set[str] = set()
+        discovered_folders: Set[str] = set()
 
         async def handle_progress(current_name: str = '') -> None:
             if progress_callback is None:
@@ -1708,6 +1854,13 @@ class ModelScanner:
                         elif entry.is_dir(follow_symlinks=True):
                             if _is_excluded_dir(entry.name):
                                 continue
+                            # Record every directory (including empty ones) so
+                            # the folder tree can be served without a live walk.
+                            rel_dir = os.path.relpath(
+                                os.path.abspath(entry.path), os.path.abspath(root_path)
+                            ).replace(os.path.sep, "/")
+                            if not _is_hidden_relative_path(rel_dir):
+                                discovered_folders.add(rel_dir)
                             await scan_recursive(entry.path, root_path, visited_paths)
                     except Exception as entry_error:
                         logger.error(f"Error processing entry {entry.path}: {entry_error}")
@@ -1727,7 +1880,8 @@ class ModelScanner:
             raw_data=raw_data,
             hash_index=hash_index,
             tags_count=tags_count,
-            excluded_models=excluded_models
+            excluded_models=excluded_models,
+            all_folders=sorted(discovered_folders, key=lambda x: x.lower()),
         )
 
     async def add_model_to_cache(self, metadata_dict: Dict[str, Any], folder: str = '') -> bool:
@@ -1869,6 +2023,20 @@ class ModelScanner:
                 except Exception as e:
                     logger.error(f"Error moving metadata file: {e}")
             
+            if metadata is not None:
+                # sub_type is derived from the model's location (e.g. a file
+                # moved from a checkpoints root into a unet root becomes a
+                # diffusion_model). Persist the recalculated value into the
+                # moved metadata file so later metadata-driven cache syncs
+                # do not revert the cache entry to the stale sub_type.
+                new_sub_type = self.resolve_sub_type_for_path(target_file)
+                if new_sub_type and metadata.get('sub_type') != new_sub_type:
+                    metadata['sub_type'] = new_sub_type
+                    try:
+                        await MetadataManager.save_metadata(moved_metadata_path, metadata)
+                    except Exception as e:
+                        logger.error(f"Error persisting sub_type for moved model: {e}")
+
             update_result = await self.update_single_model_cache(source_path, target_file, metadata, recalculate_type=True)
             
             return {
@@ -1970,6 +2138,16 @@ class ModelScanner:
             all_folders = set(item['folder'] for item in cache.raw_data)
             cache.folders = sorted(list(all_folders), key=lambda x: x.lower())
 
+            # The move target may live in directories the last scan never saw;
+            # record the destination folder (and its parents) in the known
+            # folder list so the folder tree reflects it without a rescan.
+            if cache.all_folders is not None and folder_value:
+                parts = folder_value.split("/")
+                known = set(cache.all_folders)
+                for i in range(1, len(parts) + 1):
+                    known.add("/".join(parts[:i]))
+                cache.all_folders = sorted(known, key=lambda x: x.lower())
+
             for tag in cache_entry.get('tags', []):
                 self._tags_count[tag] = self._tags_count.get(tag, 0) + 1
 
@@ -1977,10 +2155,6 @@ class ModelScanner:
 
         await cache.resort()
 
-        # A move may have created new directories; drop the cached live-walk
-        # result so the next include_empty request sees them.
-        self.invalidate_all_folders_cache()
-
         if cache_modified:
             await self._persist_current_cache()
             self.bump_cache_version()
@@ -2064,6 +2238,11 @@ class ModelScanner:
             file_path_override=file_path,
         )
 
+        # Location-derived fields (e.g. the checkpoint sub_type) must be
+        # re-resolved from the file path rather than trusting the on-disk
+        # metadata snapshot, which may predate a cross-root move.
+        desired_entry = self.adjust_cached_entry(desired_entry)
+
         # Ensure sha256 is populated (defensive — metadata should have it)
         if (
             not desired_entry.get("sha256")

py/services/model_service_factory.py

@@ -118,19 +118,24 @@ class ModelServiceFactory:
 
 
 def register_default_model_types():
-    """Register the default model types (LoRA, Checkpoint, and Embedding)"""
+    """Register the default model types (LoRA, Checkpoint, Embedding, and Other)"""
     from ..services.lora_service import LoraService
     from ..services.checkpoint_service import CheckpointService
     from ..services.embedding_service import EmbeddingService
+    from ..services.other_model_service import OtherModelService
     from ..routes.lora_routes import LoraRoutes
     from ..routes.checkpoint_routes import CheckpointRoutes
     from ..routes.embedding_routes import EmbeddingRoutes
-    
+    from ..routes.other_routes import OtherRoutes
+
     # Register LoRA model type
     ModelServiceFactory.register_model_type('lora', LoraService, LoraRoutes)
-    
+
     # Register Checkpoint model type
     ModelServiceFactory.register_model_type('checkpoint', CheckpointService, CheckpointRoutes)
-    
+
     # Register Embedding model type
-    ModelServiceFactory.register_model_type('embedding', EmbeddingService, EmbeddingRoutes)
+    ModelServiceFactory.register_model_type('embedding', EmbeddingService, EmbeddingRoutes)
+
+    # Register Other model type (VAE, upscaler, text encoder, ...)
+    ModelServiceFactory.register_model_type('other', OtherModelService, OtherRoutes)

py/services/other_model_service.py

@@ -0,0 +1,79 @@
+import os
+import logging
+from typing import Any, Dict, Optional
+
+from .base_model_service import BaseModelService
+from .auto_tag_service import extract_auto_tags
+from ..utils.models import OtherModelMetadata
+from ..config import config
+
+logger = logging.getLogger(__name__)
+
+
+class OtherModelService(BaseModelService):
+    """Other-model-specific service implementation (VAE, upscaler, text encoder, ...)"""
+
+    def __init__(self, scanner, update_service=None):
+        """Initialize Other-model service
+
+        Args:
+            scanner: Other-model scanner instance
+            update_service: Optional service for remote update tracking.
+        """
+        super().__init__("other", scanner, OtherModelMetadata, update_service=update_service)
+
+    async def format_response(self, model_data: Dict[str, Any]) -> Optional[Dict[str, Any]]:
+        """Format other-model data for API response.
+
+        Returns None when the entry is missing critical fields (corrupted cache
+        row), so the handler layer can filter it out. See issue #730.
+        """
+        # Guard against corrupted cache entries missing critical fields
+        file_path = model_data.get("file_path")
+        if not file_path or not isinstance(file_path, str):
+            logger.warning(
+                "Skipping corrupted other-model entry (missing file_path): %s",
+                model_data.get("file_name", "<unknown>"),
+            )
+            return None
+
+        # Get sub_type from cache entry (new canonical field)
+        sub_type = model_data.get("sub_type", "vae")
+
+        file_name = model_data.get("file_name") or ""
+        model_name = model_data.get("model_name") or file_name
+        folder = model_data.get("folder") or ""
+
+        return {
+            "model_name": model_name,
+            "file_name": file_name,
+            "preview_url": config.get_preview_static_url(model_data.get("preview_url", "")),
+            "preview_nsfw_level": model_data.get("preview_nsfw_level", 0),
+            "base_model": model_data.get("base_model", ""),
+            "folder": folder,
+            "sha256": model_data.get("sha256", ""),
+            "autov3": model_data.get("autov3"),
+            "file_path": file_path.replace(os.sep, "/"),
+            "file_size": model_data.get("size", 0),
+            "modified": model_data.get("modified", ""),
+            "tags": model_data.get("tags", []),
+            "from_civitai": model_data.get("from_civitai", True),
+            "notes": model_data.get("notes", ""),
+            "sub_type": sub_type,
+            "favorite": model_data.get("favorite", False),
+            "exclude": bool(model_data.get("exclude", False)),
+            "update_available": bool(model_data.get("update_available", False)),
+            "skip_metadata_refresh": bool(model_data.get("skip_metadata_refresh", False)),
+            "civitai": self.filter_civitai_data(model_data.get("civitai", {}), minimal=True),
+            "auto_tags": model_data.get("auto_tags") or extract_auto_tags(model_data),
+            "version_count": model_data.get("version_count"),
+            "hf_url": model_data.get("hf_url", ""),
+        }
+
+    def find_duplicate_hashes(self) -> Dict[str, Any]:
+        """Find other models with duplicate SHA256 hashes"""
+        return self.scanner._hash_index.get_duplicate_hashes()
+
+    def find_duplicate_filenames(self) -> Dict[str, Any]:
+        """Find other models with conflicting filenames"""
+        return self.scanner._hash_index.get_duplicate_filenames()

py/services/other_scanner.py

@@ -0,0 +1,478 @@
+# pyright: reportImportCycles=false
+# Lazy (function-local) imports still count as static edges in basedpyright's
+# reportImportCycles, so the ServiceRegistry singleton pattern necessarily forms
+# import cycles. Breaking them would require an architectural refactor.
+import asyncio
+import json
+import logging
+import os
+from datetime import datetime
+from typing import Any, Dict, List, Optional
+
+from ..utils.models import OtherModelMetadata
+from ..utils.file_utils import find_preview_file, normalize_path, calculate_autov3
+from ..utils.metadata_manager import MetadataManager
+from ..config import config
+from .model_scanner import ModelScanner, _is_excluded_dir
+from .model_hash_index import ModelHashIndex
+
+logger = logging.getLogger(__name__)
+
+
+class OtherScanner(ModelScanner):
+    """Service for scanning and managing "other" model files.
+
+    Aggregates every enabled folder_paths category from
+    OTHER_MODEL_FOLDER_SUBTYPES (VAE, upscalers, text encoders, CLIP vision,
+    opt-in ControlNet) into one scanner; sub_type is derived from the root
+    containing the file (mirrors CheckpointScanner's checkpoints/unet split).
+
+    Hashing is lazy (checkpoint-style): text encoders can be ~10 GB, so the
+    initial scan records hash_status="pending" and the SHA256 is computed
+    on-demand via calculate_hash_for_model (e.g. when fetching CivitAI
+    metadata).
+    """
+
+    def __init__(self):
+        # Same extension set as CheckpointScanner (ComfyUI's
+        # supported_pt_extensions plus ".gguf").
+        file_extensions = {
+            ".ckpt",
+            ".pt",
+            ".pt2",
+            ".bin",
+            ".pth",
+            ".safetensors",
+            ".pkl",
+            ".sft",
+            ".gguf",
+        }
+        super().__init__(
+            model_type="other",
+            model_class=OtherModelMetadata,
+            file_extensions=file_extensions,
+            hash_index=ModelHashIndex(),
+        )
+        if not hasattr(self, "_hash_calculation_lock"):
+            self._hash_calculation_lock = asyncio.Lock()
+            self._hash_calculation_tasks: dict[str, asyncio.Task[Optional[str]]] = {}
+
+    async def _create_default_metadata(
+        self, file_path: str
+    ) -> Optional[OtherModelMetadata]:
+        """Create default metadata without calculating hash (lazy hash).
+
+        Other models include multi-GB text encoders, so hash calculation is
+        deferred until on-demand (e.g. CivitAI metadata fetch).
+        """
+        try:
+            real_path = os.path.realpath(file_path)
+            if not os.path.exists(real_path):
+                logger.error(f"File not found: {file_path}")
+                return None
+
+            base_name = os.path.splitext(os.path.basename(file_path))[0]
+            dir_path = os.path.dirname(file_path)
+
+            # Find preview image
+            preview_url = find_preview_file(base_name, dir_path)
+
+            # AutoV3 reads only the safetensors header, so it is cheap even for
+            # large files; record the checked state at creation time ("" =
+            # checked but unavailable).
+            autov3 = calculate_autov3(real_path)
+
+            # Create metadata WITHOUT calculating hash
+            metadata = OtherModelMetadata(
+                file_name=base_name,
+                model_name=base_name,
+                file_path=normalize_path(file_path),
+                size=os.path.getsize(real_path),
+                modified=datetime.now().timestamp(),
+                sha256="",  # Empty hash - will be calculated on-demand
+                base_model="Unknown",
+                preview_url=normalize_path(preview_url),
+                tags=[],
+                modelDescription="",
+                sub_type=self.resolve_sub_type_for_path(file_path) or "vae",
+                from_civitai=False,  # Mark as local model since no hash yet
+                hash_status="pending",  # Mark hash as pending
+                autov3=autov3 or "",
+            )
+
+            # Save the created metadata
+            logger.info(f"Creating other-model metadata (hash pending) for {file_path}")
+            await MetadataManager.save_metadata(file_path, metadata)
+
+            return metadata
+
+        except Exception as e:
+            logger.error(
+                f"Error creating default other-model metadata for {file_path}: {e}"
+            )
+            return None
+
+    async def calculate_hash_for_model(self, file_path: str) -> Optional[str]:
+        """Calculate hash for a model on-demand with per-file singleflight.
+
+        Args:
+            file_path: Path to the model file
+
+        Returns:
+            SHA256 hash string, or None if calculation failed
+        """
+        try:
+            real_path = os.path.realpath(file_path)
+            if not os.path.exists(real_path):
+                logger.error(f"File not found for hash calculation: {file_path}")
+                return None
+
+            metadata, _ = await MetadataManager.load_metadata(
+                file_path, self.model_class
+            )
+            if (
+                metadata is not None
+                and metadata.hash_status == "completed"
+                and metadata.sha256
+            ):
+                # Ensure the in-memory hash index is populated even when
+                # the hash was already computed and persisted to the metadata
+                # file.  Without this, usage tracking (and any other caller
+                # that queries get_hash_by_filename first) will miss on every
+                # lookup and keep calling back into this method, creating a
+                # tight loop that never populates the index.
+                self._hash_index.add_entry(
+                    metadata.sha256.lower(),
+                    file_path,
+                    getattr(metadata, "autov3", None) or None,
+                )
+                return metadata.sha256
+
+            async with self._hash_calculation_lock:
+                metadata, _ = await MetadataManager.load_metadata(
+                    file_path, self.model_class
+                )
+                if (
+                    metadata is not None
+                    and metadata.hash_status == "completed"
+                    and metadata.sha256
+                ):
+                    self._hash_index.add_entry(
+                        metadata.sha256.lower(),
+                        file_path,
+                        getattr(metadata, "autov3", None) or None,
+                    )
+                    return metadata.sha256
+
+                task = self._hash_calculation_tasks.get(real_path)
+                if task is None:
+                    task = asyncio.create_task(
+                        self._run_hash_calculation_task(file_path, real_path)
+                    )
+                    self._hash_calculation_tasks[real_path] = task
+
+            return await asyncio.shield(task)
+
+        except Exception as e:
+            logger.error(f"Error calculating hash for {file_path}: {e}")
+            return None
+
+    async def _run_hash_calculation_task(
+        self, file_path: str, real_path: str
+    ) -> Optional[str]:
+        """Run a hash calculation task and remove it from the in-flight map."""
+        try:
+            return await self._calculate_hash_for_model_uncached(file_path, real_path)
+        finally:
+            task = asyncio.current_task()
+            async with self._hash_calculation_lock:
+                if self._hash_calculation_tasks.get(real_path) is task:
+                    del self._hash_calculation_tasks[real_path]
+
+    async def _calculate_hash_for_model_uncached(
+        self, file_path: str, real_path: str
+    ) -> Optional[str]:
+        """Calculate hash for a model without checking in-flight tasks."""
+        from ..utils.file_utils import calculate_sha256
+
+        try:
+            # Load current metadata
+            metadata, should_skip = await MetadataManager.load_metadata(
+                file_path, self.model_class
+            )
+            if metadata is None:
+                if should_skip:
+                    logger.error(f"Invalid metadata found for {file_path}")
+                    return None
+                created_metadata = await self._create_default_metadata(file_path)
+                if created_metadata is None:
+                    logger.error(f"No metadata found for {file_path}")
+                    return None
+                metadata = created_metadata
+
+            # Check if hash is already calculated
+            if metadata.hash_status == "completed" and metadata.sha256:
+                # Populate the in-memory hash index even for pre-computed
+                # hashes, mirroring the fix in calculate_hash_for_model.
+                self._hash_index.add_entry(
+                    metadata.sha256.lower(),
+                    file_path,
+                    getattr(metadata, "autov3", None) or None,
+                )
+                return metadata.sha256
+
+            # Update status to calculating
+            metadata.hash_status = "calculating"
+            await MetadataManager.save_metadata(file_path, metadata)
+
+            # Calculate hash
+            logger.info(f"Calculating hash for other model: {file_path}")
+            sha256 = await calculate_sha256(real_path)
+
+            # Update metadata with hash
+            metadata.sha256 = sha256
+            metadata.hash_status = "completed"
+            await MetadataManager.save_metadata(file_path, metadata)
+
+            # Update hash index
+            self._hash_index.add_entry(
+                sha256.lower(),
+                file_path,
+                getattr(metadata, "autov3", None) or None,
+            )
+
+            # Update the in-memory cache entry so that subsequent
+            # _persist_current_cache / _save_persistent_cache calls
+            # write the hash back to the SQLite models table.  Without
+            # this the hash only lives in the metadata file and the
+            # in-memory hash index, both of which are lost across
+            # restarts, causing the same re-computation loop on the
+            # next session.
+            if self._cache is not None and self._cache.raw_data:
+                for entry in self._cache.raw_data:
+                    if entry.get("file_path") == file_path:
+                        entry["sha256"] = sha256.lower()
+                        entry["hash_status"] = "completed"
+                        self.bump_cache_version()
+                        break
+
+            logger.info(f"Hash calculated for other model: {file_path}")
+            return sha256
+
+        except Exception as e:
+            logger.error(f"Error calculating hash for {file_path}: {e}")
+            # Update status to failed
+            try:
+                metadata, _ = await MetadataManager.load_metadata(
+                    file_path, self.model_class
+                )
+                if metadata:
+                    metadata.hash_status = "failed"
+                    await MetadataManager.save_metadata(file_path, metadata)
+            except Exception:
+                pass
+            return None
+
+    async def calculate_all_pending_hashes(
+        self, progress_callback=None
+    ) -> Dict[str, int]:
+        """Calculate hashes for all other models with pending hash status.
+
+        If cache is not initialized, scans filesystem directly for metadata files
+        with hash_status != 'completed'.
+
+        Args:
+            progress_callback: Optional callback(progress, total, current_file)
+
+        Returns:
+            Dict with 'completed', 'failed', 'total' counts
+        """
+        # Try to get from cache first
+        cache = await self.get_cached_data()
+
+        if cache and cache.raw_data:
+            # Use cache if available
+            pending_models = [
+                item
+                for item in cache.raw_data
+                if item.get("hash_status") != "completed" or not item.get("sha256")
+            ]
+        else:
+            # Cache not initialized, scan filesystem directly
+            pending_models = await self._find_pending_models_from_filesystem()
+
+        if not pending_models:
+            return {"completed": 0, "failed": 0, "total": 0}
+
+        total = len(pending_models)
+        completed = 0
+        failed = 0
+
+        for i, model_data in enumerate(pending_models):
+            file_path = model_data.get("file_path")
+            if not file_path:
+                continue
+
+            try:
+                sha256 = await self.calculate_hash_for_model(file_path)
+                if sha256:
+                    completed += 1
+                else:
+                    failed += 1
+            except Exception as e:
+                logger.error(f"Error calculating hash for {file_path}: {e}")
+                failed += 1
+
+            if progress_callback:
+                try:
+                    await progress_callback(i + 1, total, file_path)
+                except Exception:
+                    pass
+
+        return {"completed": completed, "failed": failed, "total": total}
+
+    async def _find_pending_models_from_filesystem(self) -> List[Dict[str, Any]]:
+        """Scan filesystem for other-model metadata files with pending hash status."""
+        pending_models = []
+
+        for root_path in self.get_model_roots():
+            if not os.path.exists(root_path):
+                continue
+
+            for dirpath, dirnames, filenames in os.walk(root_path):
+                dirnames[:] = [d for d in dirnames if not _is_excluded_dir(d)]
+                for filename in filenames:
+                    if not filename.endswith(".metadata.json"):
+                        continue
+
+                    metadata_path = os.path.join(dirpath, filename)
+                    try:
+                        with open(metadata_path, "r", encoding="utf-8") as f:
+                            data = json.load(f)
+
+                        # Check if hash is pending
+                        hash_status = data.get("hash_status", "completed")
+                        sha256 = data.get("sha256", "")
+
+                        if hash_status != "completed" or not sha256:
+                            # Find corresponding model file
+                            model_name = filename.replace(".metadata.json", "")
+                            model_path = None
+
+                            # Look for model file with matching name
+                            for ext in self.file_extensions:
+                                potential_path = os.path.join(dirpath, model_name + ext)
+                                if os.path.exists(potential_path):
+                                    model_path = potential_path
+                                    break
+
+                            if model_path:
+                                pending_models.append(
+                                    {
+                                        "file_path": model_path.replace(os.sep, "/"),
+                                        "hash_status": hash_status,
+                                        "sha256": sha256,
+                                        **{
+                                            k: v
+                                            for k, v in data.items()
+                                            if k
+                                            not in [
+                                                "file_path",
+                                                "hash_status",
+                                                "sha256",
+                                            ]
+                                        },
+                                    }
+                                )
+                    except (json.JSONDecodeError, Exception) as e:
+                        logger.debug(
+                            f"Error reading metadata file {metadata_path}: {e}"
+                        )
+                        continue
+
+        return pending_models
+
+    def _root_sub_type_map(self) -> Dict[str, str]:
+        """Return the configured business root -> sub_type map."""
+        root_map = getattr(config, "other_root_subtypes", None)
+        return root_map if isinstance(root_map, dict) else {}
+
+    def _resolve_sub_type(self, root_path: Optional[str]) -> Optional[str]:
+        """Resolve the sub_type for a configured root path."""
+        if not root_path:
+            return None
+
+        normalized_root = self._normalize_path_value(root_path)
+        for root, sub_type in self._root_sub_type_map().items():
+            if self._normalize_path_value(root) == normalized_root:
+                return sub_type
+
+        return None
+
+    def resolve_sub_type_for_path(self, file_path: Optional[str]) -> Optional[str]:
+        """Resolve sub_type from the configured root that contains the file.
+
+        Uses the longest-prefix match so nested roots (e.g. a controlnet root
+        inside a vae root) resolve to the most specific category.
+        """
+        normalized_path = self._normalize_path_value(file_path)
+        if not normalized_path:
+            return None
+
+        best_length = 0
+        best_sub_type: Optional[str] = None
+        for root, sub_type in self._root_sub_type_map().items():
+            normalized_root = self._normalize_path_value(root)
+            if not normalized_root:
+                continue
+            if (
+                normalized_path == normalized_root
+                or normalized_path.startswith(f"{normalized_root}/")
+            ) and len(normalized_root) > best_length:
+                best_length = len(normalized_root)
+                best_sub_type = sub_type
+
+        return best_sub_type
+
+    def adjust_metadata(self, metadata, file_path, root_path):
+        """Adjust metadata during scanning to set sub_type."""
+        sub_type = self._resolve_sub_type(root_path) or self.resolve_sub_type_for_path(
+            file_path
+        )
+        if sub_type:
+            metadata.sub_type = sub_type
+        return metadata
+
+    def adjust_cached_entry(self, entry: Dict[str, Any]) -> Dict[str, Any]:
+        """Adjust entries loaded from the persisted cache to ensure sub_type is set.
+
+        sub_type is location-derived: it is re-derived on cache load, never
+        trusted from the persisted snapshot.
+        """
+        sub_type = self.resolve_sub_type_for_path(entry.get("file_path"))
+        if sub_type:
+            entry["sub_type"] = sub_type
+        return entry
+
+    def _should_keep_cached_entry(self, entry: Dict[str, Any]) -> bool:
+        """Drop persisted entries whose folder is no longer a managed root.
+
+        sub_type is location-derived and config only maps enabled roots, so a
+        file under a disabled sub_type - or under any other root while the
+        feature is off - resolves to None here and is filtered out while the
+        persisted cache is hydrated.
+        """
+        return self.resolve_sub_type_for_path(entry.get("file_path")) is not None
+
+    def get_model_roots(self) -> List[str]:
+        """Get other-model root directories"""
+        roots: List[str] = []
+        roots.extend(config.other_roots or [])
+        # Remove duplicates while preserving order
+        seen: set[str] = set()
+        unique_roots: List[str] = []
+        for root in roots:
+            if root and root not in seen:
+                seen.add(root)
+                unique_roots.append(root)
+        return unique_roots

py/services/pending_delete_service.py

@@ -59,6 +59,7 @@ _MODEL_TYPE_PAGE_MAP = {
     "lora": "loras",
     "checkpoint": "checkpoints",
     "embedding": "embeddings",
+    "other": "other",
 }
 
 # Module-level alias so tests can spy on timer task creation without patching
@@ -983,6 +984,7 @@ class PendingDeleteService:
             "get_lora_scanner",
             "get_checkpoint_scanner",
             "get_embedding_scanner",
+            "get_other_scanner",
         ):
             getter = getattr(ServiceRegistry, getter_name, None)
             if not callable(getter):

py/services/persistent_model_cache.py

@@ -19,6 +19,9 @@ class PersistedCacheData:
     hash_rows: List[Tuple[str, str]]
     excluded_models: List[str]
     autov3_hash_rows: List[Tuple[str, str]] = field(default_factory=list)
+    # Every directory under the model roots (including empty ones), or None
+    # when the snapshot predates folder recording.
+    all_folders: Optional[List[str]] = None
 
 
 DEFAULT_LICENSE_FLAGS = 127  # 127 (0b1111111) encodes default CivitAI permissions with all commercial modes enabled.
@@ -128,6 +131,14 @@ class PersistentModelCache:
                         "SELECT file_path FROM excluded_models WHERE model_type = ?",
                         (model_type,),
                     ).fetchall()
+                    folder_rows = conn.execute(
+                        "SELECT path FROM folders WHERE model_type = ?",
+                        (model_type,),
+                    ).fetchall()
+                    folders_recorded = conn.execute(
+                        "SELECT value FROM cache_meta WHERE key = ?",
+                        (f"folders_recorded:{model_type}",),
+                    ).fetchone()
                 finally:
                     conn.close()
         except Exception as exc:
@@ -216,14 +227,20 @@ class PersistentModelCache:
         ]
 
         excluded_paths = [row["file_path"] for row in excluded]
+        all_folders: Optional[List[str]] = None
+        if folders_recorded is not None:
+            all_folders = sorted(
+                (row["path"] for row in folder_rows), key=lambda x: x.lower()
+            )
         return PersistedCacheData(
             raw_data=raw_data,
             hash_rows=hash_pairs,
             excluded_models=excluded_paths,
             autov3_hash_rows=autov3_pairs,
+            all_folders=all_folders,
         )
 
-    def save_cache(self, model_type: str, raw_data: Sequence[Dict[str, Any]], hash_index: Dict[str, List[str]], excluded_models: Sequence[str], autov3_hash_index: Optional[Dict[str, List[str]]] = None) -> None:
+    def save_cache(self, model_type: str, raw_data: Sequence[Dict[str, Any]], hash_index: Dict[str, List[str]], excluded_models: Sequence[str], autov3_hash_index: Optional[Dict[str, List[str]]] = None, all_folders: Optional[Sequence[str]] = None) -> None:
         if not self.is_enabled():
             return
         if not self._schema_initialized:
@@ -469,6 +486,27 @@ class PersistentModelCache:
                             excluded_inserts,
                         )
 
+                    if all_folders is not None:
+                        conn.execute(
+                            "DELETE FROM folders WHERE model_type = ?",
+                            (model_type,),
+                        )
+                        folder_inserts = [
+                            (model_type, path) for path in all_folders if path
+                        ]
+                        if folder_inserts:
+                            conn.executemany(
+                                "INSERT OR IGNORE INTO folders (model_type, path) VALUES (?, ?)",
+                                folder_inserts,
+                            )
+                        # Mark the snapshot as having folder data even when the
+                        # library has no subfolders, so an empty list is not
+                        # mistaken for "never recorded" on load.
+                        conn.execute(
+                            "INSERT OR REPLACE INTO cache_meta (key, value) VALUES (?, ?)",
+                            (f"folders_recorded:{model_type}", "1"),
+                        )
+
                     conn.commit()
                 finally:
                     conn.close()
@@ -554,6 +592,17 @@ class PersistentModelCache:
                             file_path TEXT NOT NULL,
                             PRIMARY KEY (model_type, file_path)
                         );
+
+                        CREATE TABLE IF NOT EXISTS folders (
+                            model_type TEXT NOT NULL,
+                            path TEXT NOT NULL,
+                            PRIMARY KEY (model_type, path)
+                        );
+
+                        CREATE TABLE IF NOT EXISTS cache_meta (
+                            key TEXT PRIMARY KEY,
+                            value TEXT
+                        );
                         """
                     )
                     self._ensure_additional_model_columns(conn)

py/services/recipe_scanner.py

@@ -483,32 +483,43 @@ class RecipeScanner:
         suggestions.sort(key=lambda s: (-s["score"], s["file_name"].lower()))
         return suggestions[:limit]
 
-    def _is_rematch_candidate(self, entry: dict[str, Any]) -> bool:
+    def _is_rematch_candidate(
+        self, entry: dict[str, Any], relaxed: bool = False
+    ) -> bool:
         """Return True when a recipe entry is eligible for local re-matching.
 
         An entry counts as unresolved when its identity is known to be
         broken (``isDeleted`` or ``hashInvalid``) or when it is missing
         identity fields (``hash``/``file_name``). A healthy entry whose
-        hash is simply not present in the local library is NOT a candidate:
-        it may be a recipe imported without downloading the model yet, and
-        its CivitAI-valid hash must never be overwritten by the imprecise
-        filename fallback.
+        hash is simply not present in the local library is NOT a candidate
+        in the default strict mode: it may be a recipe imported without
+        downloading the model yet, and its CivitAI-valid hash must never be
+        overwritten by the imprecise filename fallback.
+
+        With ``relaxed=True`` any entry carrying an identifier is a
+        candidate, including healthy ones — the caller opted into trying to
+        reconnect "Not in Library" entries by file name. Entries without
+        any identifier are never candidates in either mode.
         """
         if not isinstance(entry, dict):
             return False
-        unresolved = (
-            entry.get("isDeleted")
-            or entry.get("hashInvalid")
-            or not entry.get("hash")
-            or not entry.get("file_name")
-        )
         has_identifier = (
             entry.get("hash")
             or entry.get("modelVersionId")
             or entry.get("id")
             or entry.get("file_name")
         )
-        return bool(unresolved and has_identifier)
+        if not has_identifier:
+            return False
+        if relaxed:
+            return True
+        unresolved = (
+            entry.get("isDeleted")
+            or entry.get("hashInvalid")
+            or not entry.get("hash")
+            or not entry.get("file_name")
+        )
+        return bool(unresolved)
 
     async def _build_rematch_autov3_cache(self) -> dict[str, dict[str, Any]]:
         """Build a version-cached map of computed AutoV3 hashes to local items.
@@ -809,7 +820,9 @@ class RecipeScanner:
         """Check if cancellation has been requested."""
         return self._cancel_requested
 
-    async def rematch_recipe_by_id(self, recipe_id: str) -> Dict[str, Any]:
+    async def rematch_recipe_by_id(
+        self, recipe_id: str, *, relaxed: bool = False
+    ) -> Dict[str, Any]:
         """Rematch a single recipe's deleted lora/checkpoint entries locally.
 
         Logs one INFO summary line for this run and delegates the per-recipe
@@ -817,12 +830,14 @@ class RecipeScanner:
 
         Args:
             recipe_id: ID of the recipe to rematch
+            relaxed: When True, healthy entries are rematch candidates too
+                (see ``_rematch_single_recipe``).
 
         Returns:
             Dict summary of the rematch result (see ``_rematch_recipe_by_id``).
             Raises RecipeNotFoundError when the recipe is missing.
         """
-        result = await self._rematch_recipe_by_id(recipe_id)
+        result = await self._rematch_recipe_by_id(recipe_id, relaxed=relaxed)
         recipe_name = (result.get("recipe") or {}).get("name") or recipe_id
         logger.info(
             "Recipe rematch %s (%s): success=%s, %d entries matched, %d unresolved, %d errors",
@@ -835,7 +850,9 @@ class RecipeScanner:
         )
         return result
 
-    async def _rematch_recipe_by_id(self, recipe_id: str) -> Dict[str, Any]:
+    async def _rematch_recipe_by_id(
+        self, recipe_id: str, *, relaxed: bool = False
+    ) -> Dict[str, Any]:
         """Rematch a single recipe's deleted lora/checkpoint entries locally.
 
         Match snapshots (local hash cache, computed autov3 cache, filename
@@ -846,12 +863,16 @@ class RecipeScanner:
 
         Args:
             recipe_id: ID of the recipe to rematch
+            relaxed: When True, healthy entries are rematch candidates too
+                (see ``_rematch_single_recipe``).
 
         Returns:
             Dict summary of the rematch result with unified counters
             (matched_recipes, matched_entries, unresolved_recipes,
             unresolved_entries plus the legacy rematched/skipped/errors
-            fields) and a per-entry ``details`` report. The legacy ``skipped``
+            fields) and a per-entry ``details`` report plus a flattened
+            ``l4_matches`` list (filename-level matches for review/undo,
+            consistent with the bulk/global paths). The legacy ``skipped``
             field means "recipe not updated" and overlaps
             ``unresolved_recipes`` (a recipe with unmatched candidates counts
             as both). Raises RecipeNotFoundError when the recipe is missing.
@@ -872,7 +893,8 @@ class RecipeScanner:
 
             try:
                 rematched, _errors, details = await self._rematch_single_recipe(
-                    recipe, local_cache, autov3_cache, filename_cache
+                    recipe, local_cache, autov3_cache, filename_cache,
+                    relaxed=relaxed,
                 )
             except RecipePersistenceError as exc:
                 logger.error(
@@ -891,12 +913,16 @@ class RecipeScanner:
                     "unresolved_recipes": 0,
                     "unresolved_entries": 0,
                     "details": {"matched": [], "unresolved": []},
+                    "l4_matches": [],
                     "recipe": recipe,
                     "error": str(exc),
                 }
 
             unresolved_entries = len(details["unresolved"])
             unresolved_recipes = 1 if unresolved_entries > 0 else 0
+            # Flattened L4 matches for the results modal, consistent with
+            # the bulk/global paths.
+            l4_matches = self._collect_l4_matches(recipe_id, details)
 
             if rematched == 0:
                 return {
@@ -908,6 +934,7 @@ class RecipeScanner:
                     "unresolved_recipes": unresolved_recipes,
                     "unresolved_entries": unresolved_entries,
                     "details": details,
+                    "l4_matches": l4_matches,
                     "recipe": recipe,
                 }
 
@@ -921,6 +948,7 @@ class RecipeScanner:
                 "unresolved_recipes": unresolved_recipes,
                 "unresolved_entries": unresolved_entries,
                 "details": details,
+                "l4_matches": l4_matches,
                 "recipe": await self.get_recipe_by_id(recipe_id),
             }
 
@@ -930,6 +958,8 @@ class RecipeScanner:
         local_cache: dict[str, dict[str, Any]],
         autov3_cache: dict[str, dict[str, Any]],
         filename_cache: Optional[dict[str, list[dict[str, Any]]]] = None,
+        *,
+        relaxed: bool = False,
     ) -> Tuple[int, int, Dict[str, Any]]:
         """Rematch a single recipe's lora/checkpoint entries against local models.
 
@@ -945,16 +975,24 @@ class RecipeScanner:
             autov3_cache: L3 computed-autov3 cache snapshot
             filename_cache: L4 filename cache snapshot, or None to disable
                 the filename fallback
+            relaxed: When True, healthy entries ("Not in Library") are also
+                rematch candidates. Anti-churn rule: an entry that is a
+                candidate ONLY because of relaxed mode is skipped when its
+                hash already resolves in the L1 ``local_cache`` — it is
+                already correctly linked and rematching would only add noise
+                and a pointless snapshot.
 
         Returns:
             Tuple of (rematched_entries, errors, details). The errors element
             is always 0 on a normal return — a persistence failure RAISES
             ``RecipePersistenceError`` so callers can count it. ``details``
             carries the per-entry outcome:
-            ``{"matched": [{type, entry, file_name, match_level}],
+            ``{"matched": [{type, entry, file_name, match_level, lora_index?}],
               "unresolved": [{type, entry}]}`` where an unresolved entry is a
             rematch candidate that found no local match — an expected outcome
             (the model may simply not exist locally), not an error.
+            ``lora_index`` is only present for lora entries (the checkpoint
+            restore endpoint needs no index).
 
         Raises:
             RecipePersistenceError: when the recipe changed but
@@ -963,11 +1001,23 @@ class RecipeScanner:
         rematched = 0
         details: Dict[str, Any] = {"matched": [], "unresolved": []}
 
+        def is_actionable_candidate(entry: Dict[str, Any]) -> bool:
+            """Apply candidacy plus the relaxed-mode anti-churn rule."""
+            if self._is_rematch_candidate(entry):
+                return True
+            if not relaxed or not self._is_rematch_candidate(entry, relaxed=True):
+                return False
+            # Relaxed-only candidate: skip when the stored hash already
+            # resolves in the L1 local cache — the entry is already correctly
+            # linked and rematching would just add noise and a snapshot.
+            entry_hash = (entry.get("hash") or "").lower()
+            return local_cache.get(entry_hash) is None
+
         # Lora entries
         loras = recipe.get("loras", [])
         if isinstance(loras, list):
-            for entry in loras:
-                if not self._is_rematch_candidate(entry):
+            for lora_index, entry in enumerate(loras):
+                if not is_actionable_candidate(entry):
                     continue
                 item, level = await self._match_rematch_entry_with_level(
                     entry,
@@ -991,6 +1041,7 @@ class RecipeScanner:
                         "entry": self._entry_identifier(entry),
                         "file_name": item.get("file_name") or "",
                         "match_level": level,
+                        "lora_index": lora_index,
                     }
                 )
                 self._write_rematch_lora_entry(entry, item)
@@ -1000,7 +1051,7 @@ class RecipeScanner:
         # silently since ``entry.get`` on a str would raise AttributeError).
         checkpoint = recipe.get("checkpoint")
         if isinstance(checkpoint, dict):
-            if self._is_rematch_candidate(checkpoint):
+            if is_actionable_candidate(checkpoint):
                 item, level = await self._match_rematch_entry_with_level(
                     checkpoint,
                     local_cache,
@@ -1065,8 +1116,36 @@ class RecipeScanner:
         self._update_fts_index_for_recipe(recipe, "update")
         return (rematched, 0, details)
 
+    @staticmethod
+    def _collect_l4_matches(
+        recipe_id: Any, details: Dict[str, Any]
+    ) -> List[Dict[str, Any]]:
+        """Flatten a recipe's L4 (filename-level) matches for review.
+
+        Returns ``[{recipe_id, type, entry, file_name, lora_index?}]`` rows —
+        one per matched detail at level L4. ``lora_index`` is only present
+        for lora entries (checkpoint restore needs no index).
+        """
+        rows: List[Dict[str, Any]] = []
+        for match in details.get("matched", []):
+            if match.get("match_level") != "L4":
+                continue
+            row: Dict[str, Any] = {
+                "recipe_id": recipe_id,
+                "type": match.get("type"),
+                "entry": match.get("entry"),
+                "file_name": match.get("file_name"),
+            }
+            if "lora_index" in match:
+                row["lora_index"] = match["lora_index"]
+            rows.append(row)
+        return rows
+
     async def rematch_all_recipes(
-        self, progress_callback: Optional[Callable[[Dict[str, Any]], Any]] = None
+        self,
+        progress_callback: Optional[Callable[[Dict[str, Any]], Any]] = None,
+        *,
+        relaxed: bool = False,
     ) -> Dict[str, Any]:
         """Rematch every recipe's deleted lora/checkpoint entries locally.
 
@@ -1080,14 +1159,19 @@ class RecipeScanner:
 
         Args:
             progress_callback: Optional callback for progress updates
-                (started/processing/cancelled/completed events).
+                (started/processing/cancelled/completed events). The
+                completed/cancelled payloads carry ``l4_matches``, a
+                flattened list of filename-level matches for review/undo.
+            relaxed: When True, healthy entries are rematch candidates too
+                (see ``_rematch_single_recipe``).
 
         Returns:
             Dict summary of the rematch run with unified counters
             (matched_recipes/matched_entries/unresolved_recipes/unresolved_
             entries plus the legacy success/status/rematched/skipped/errors/
-            total fields). ``rematched`` (legacy) counts updated recipes —
-            use ``matched_entries`` for the entry-level total.
+            total fields) and ``l4_matches``. ``rematched`` (legacy) counts
+            updated recipes — use ``matched_entries`` for the entry-level
+            total.
         """
         start_time = time.perf_counter()
 
@@ -1109,6 +1193,7 @@ class RecipeScanner:
             unresolved_entries = 0
             skipped_count = 0
             errors_count = 0
+            l4_matches: List[Dict[str, Any]] = []
 
             for i, recipe in enumerate(all_recipes):
                 if self.is_cancelled():
@@ -1137,6 +1222,7 @@ class RecipeScanner:
                                 "matched_entries": matched_entries,
                                 "unresolved_recipes": unresolved_recipes,
                                 "unresolved_entries": unresolved_entries,
+                                "l4_matches": l4_matches,
                             }
                         )
                     return {
@@ -1150,6 +1236,7 @@ class RecipeScanner:
                         "matched_entries": matched_entries,
                         "unresolved_recipes": unresolved_recipes,
                         "unresolved_entries": unresolved_entries,
+                        "l4_matches": l4_matches,
                     }
 
                 try:
@@ -1165,11 +1252,15 @@ class RecipeScanner:
                         )
 
                     rematched, _errors, details = await self._rematch_single_recipe(
-                        recipe, local_cache, autov3_cache, filename_cache
+                        recipe, local_cache, autov3_cache, filename_cache,
+                        relaxed=relaxed,
                     )
                     if rematched > 0:
                         matched_recipes += 1
                         matched_entries += rematched
+                        l4_matches.extend(
+                            self._collect_l4_matches(recipe.get("id"), details)
+                        )
                     else:
                         skipped_count += 1
 
@@ -1215,6 +1306,7 @@ class RecipeScanner:
                         "matched_entries": matched_entries,
                         "unresolved_recipes": unresolved_recipes,
                         "unresolved_entries": unresolved_entries,
+                        "l4_matches": l4_matches,
                     }
                 )
 
@@ -1228,9 +1320,12 @@ class RecipeScanner:
                 "matched_entries": matched_entries,
                 "unresolved_recipes": unresolved_recipes,
                 "unresolved_entries": unresolved_entries,
+                "l4_matches": l4_matches,
             }
 
-    async def rematch_recipes_bulk(self, recipe_ids: List[str]) -> Dict[str, Any]:
+    async def rematch_recipes_bulk(
+        self, recipe_ids: List[str], *, relaxed: bool = False
+    ) -> Dict[str, Any]:
         """Rematch a set of recipes by their IDs.
 
         Iterates ``_rematch_recipe_by_id`` over each id: not-found ids are
@@ -1241,14 +1336,18 @@ class RecipeScanner:
 
         Args:
             recipe_ids: List of recipe ids to rematch.
+            relaxed: When True, healthy entries are rematch candidates too
+                (see ``_rematch_single_recipe``).
 
         Returns:
             Dict summary of the bulk run with unified counters
             (matched_recipes, matched_entries, unresolved_recipes,
             unresolved_entries plus the legacy total/rematched/skipped/errors
-            fields) and a per-recipe ``details`` list. The legacy ``rematched``
-            field is the total entry count (same as ``matched_entries``) —
-            unlike ``rematch_all_recipes`` where it counts updated recipes.
+            fields), a per-recipe ``details`` list, and ``l4_matches`` — a
+            flattened list of filename-level matches for review/undo. The
+            legacy ``rematched`` field is the total entry count (same as
+            ``matched_entries``) — unlike ``rematch_all_recipes`` where it
+            counts updated recipes.
         """
         total = len(recipe_ids)
         matched_recipes = 0
@@ -1259,10 +1358,13 @@ class RecipeScanner:
         errors = 0
         recipes: List[Dict[str, Any]] = []
         details_list: List[Dict[str, Any]] = []
+        l4_matches: List[Dict[str, Any]] = []
 
         for recipe_id in recipe_ids:
             try:
-                result = await self._rematch_recipe_by_id(recipe_id)
+                result = await self._rematch_recipe_by_id(
+                    recipe_id, relaxed=relaxed
+                )
                 if result.get("success"):
                     matched_recipes += result.get("matched_recipes", 0)
                     matched_entries += result.get("matched_entries", 0)
@@ -1275,6 +1377,9 @@ class RecipeScanner:
                         details_list.append(
                             {"recipe_id": recipe_id, **result["details"]}
                         )
+                        l4_matches.extend(
+                            self._collect_l4_matches(recipe_id, result["details"])
+                        )
                 else:
                     errors += result.get("errors", 0)
             except RecipeNotFoundError:
@@ -1309,12 +1414,22 @@ class RecipeScanner:
             "unresolved_entries": unresolved_entries,
             "recipes": recipes,
             "details": details_list,
+            "l4_matches": l4_matches,
         }
 
     def _write_rematch_lora_entry(
         self, entry: Dict[str, Any], item: Dict[str, Any]
     ) -> None:
         """Write back a matched local model to a lora recipe entry."""
+        # Snapshot the pre-rematch state so the association can be restored
+        # later (undo), mirroring the manual reconnect flow in
+        # ``update_lora_entry``. Never nest snapshots.
+        snapshot = {
+            key: copy.deepcopy(value)
+            for key, value in entry.items()
+            if key != "reconnectSnapshot"
+        }
+
         entry["isDeleted"] = False
         entry["hashInvalid"] = False
 
@@ -1338,6 +1453,8 @@ class RecipeScanner:
             if civitai.get("name"):
                 entry["modelVersionName"] = civitai["name"]
 
+        entry["reconnectSnapshot"] = snapshot
+
     def _write_rematch_checkpoint_entry(
         self, entry: Dict[str, Any], item: Dict[str, Any]
     ) -> None:
@@ -1349,6 +1466,15 @@ class RecipeScanner:
         when they already exist on the entry (or written fresh for the
         identifier key when neither identifier form exists).
         """
+        # Snapshot the pre-rematch state so the association can be restored
+        # later (undo), mirroring the manual reconnect flow. Never nest
+        # snapshots.
+        snapshot = {
+            key: copy.deepcopy(value)
+            for key, value in entry.items()
+            if key != "reconnectSnapshot"
+        }
+
         entry["isDeleted"] = False
         entry["hashInvalid"] = False
 
@@ -1389,6 +1515,8 @@ class RecipeScanner:
             else:
                 entry["modelVersionId"] = civ_id
 
+        entry["reconnectSnapshot"] = snapshot
+
     async def _save_recipe_persistently(self, recipe: Dict[str, Any]) -> bool:
         """Helper to save a recipe to both JSON and EXIF metadata."""
         recipe_id = recipe.get("id")

py/services/service_registry.py

@@ -297,23 +297,44 @@ class ServiceRegistry:
     async def get_embedding_scanner(cls):
         """Get or create Embedding scanner instance"""
         service_name = "embedding_scanner"
-        
+
         if service_name in cls._services:
             return cls._services[service_name]
-        
+
         async with cls._get_lock(service_name):
             # Double-check after acquiring lock
             if service_name in cls._services:
                 return cls._services[service_name]
-            
+
             # Import here to avoid circular imports
             from .embedding_scanner import EmbeddingScanner
-            
+
             scanner = await EmbeddingScanner.get_instance()
             cls._services[service_name] = scanner
             logger.debug(f"Created and registered {service_name}")
             return scanner
-    
+
+    @classmethod
+    async def get_other_scanner(cls):
+        """Get or create Other-model scanner instance"""
+        service_name = "other_scanner"
+
+        if service_name in cls._services:
+            return cls._services[service_name]
+
+        async with cls._get_lock(service_name):
+            # Double-check after acquiring lock
+            if service_name in cls._services:
+                return cls._services[service_name]
+
+            # Import here to avoid circular imports
+            from .other_scanner import OtherScanner
+
+            scanner = await OtherScanner.get_instance()
+            cls._services[service_name] = scanner
+            logger.debug(f"Created and registered {service_name}")
+            return scanner
+
     @classmethod
     def clear_services(cls):
         """Clear all registered services - mainly for testing"""

py/services/settings_manager.py

@@ -25,9 +25,14 @@ from typing import (
 from platformdirs import user_config_dir
 
 from ..utils.constants import (
+    DEFAULT_DOWNLOAD_PATH_TEMPLATES,
+    DEFAULT_ENABLED_OTHER_SUB_TYPES,
     DEFAULT_HASH_CHUNK_SIZE_MB,
     DEFAULT_PRIORITY_TAG_CONFIG,
+    OTHER_SUB_TYPE_FOLDER_KEYS,
     SUPPORTED_DOWNLOAD_SKIP_BASE_MODELS,
+    VALID_OTHER_SUB_TYPES,
+    normalize_other_sub_types,
 )
 from ..utils.preview_selection import VALID_MATURE_BLUR_LEVELS
 from ..utils.settings_paths import (
@@ -83,6 +88,11 @@ DEFAULT_SETTINGS: Dict[str, Any] = {
     "default_checkpoint_root": "",
     "default_unet_root": "",
     "default_embedding_root": "",
+    "default_other_roots": {},
+    # Other Models management is opt-in: nothing is scanned, shown or offered
+    # for download until the user turns the feature on.
+    "enable_other_models": False,
+    "enabled_other_sub_types": list(DEFAULT_ENABLED_OTHER_SUB_TYPES),
     "recipes_path": "",
     "base_model_path_mappings": {},
     "download_path_templates": {},
@@ -309,6 +319,7 @@ class SettingsManager:
                 default_checkpoint_root=merged.get("default_checkpoint_root"),
                 default_unet_root=merged.get("default_unet_root"),
                 default_embedding_root=merged.get("default_embedding_root"),
+                default_other_roots=merged.get("default_other_roots"),
                 recipes_path=merged.get("recipes_path"),
             )
         }
@@ -443,6 +454,7 @@ class SettingsManager:
                 ),
                 default_unet_root=self.settings.get("default_unet_root", ""),
                 default_embedding_root=self.settings.get("default_embedding_root", ""),
+                default_other_roots=self.settings.get("default_other_roots"),
                 recipes_path=self.settings.get("recipes_path", ""),
             )
             libraries = {library_name: library_payload}
@@ -494,6 +506,7 @@ class SettingsManager:
                 default_checkpoint_root=data.get("default_checkpoint_root"),
                 default_unet_root=data.get("default_unet_root"),
                 default_embedding_root=data.get("default_embedding_root"),
+                default_other_roots=data.get("default_other_roots"),
                 recipes_path=data.get("recipes_path"),
                 metadata=data.get("metadata"),
                 base=data,
@@ -541,6 +554,9 @@ class SettingsManager:
         self.settings["default_embedding_root"] = active_library.get(
             "default_embedding_root", ""
         )
+        self.settings["default_other_roots"] = self._normalize_default_other_roots(
+            active_library.get("default_other_roots", {})
+        )
         self.settings["recipes_path"] = active_library.get("recipes_path", "")
 
         if save:
@@ -558,6 +574,7 @@ class SettingsManager:
         default_checkpoint_root: Optional[str] = None,
         default_unet_root: Optional[str] = None,
         default_embedding_root: Optional[str] = None,
+        default_other_roots: Optional[Mapping[str, str]] = None,
         recipes_path: Optional[str] = None,
         metadata: Optional[Mapping[str, Any]] = None,
         base: Optional[Mapping[str, Any]] = None,
@@ -597,6 +614,15 @@ class SettingsManager:
         else:
             payload.setdefault("default_embedding_root", "")
 
+        if default_other_roots is not None:
+            payload["default_other_roots"] = self._normalize_default_other_roots(
+                default_other_roots
+            )
+        else:
+            payload["default_other_roots"] = self._normalize_default_other_roots(
+                payload.get("default_other_roots", {})
+            )
+
         if recipes_path is not None:
             payload["recipes_path"] = recipes_path
         else:
@@ -632,6 +658,71 @@ class SettingsManager:
             normalized[key] = cleaned
         return normalized
 
+    def _normalize_default_other_roots(
+        self, value: Any, *, strict: bool = False
+    ) -> Dict[str, str]:
+        """Normalize a ``default_other_roots`` mapping ({sub_type: root path}).
+
+        Unknown sub_type keys and non-string/empty paths are dropped; with
+        ``strict=True`` unknown sub_type keys raise instead (used by ``set()``
+        so typos in API payloads surface as errors).
+        """
+        if not isinstance(value, Mapping):
+            if strict and value is not None:
+                raise ValueError("default_other_roots must be a mapping")
+            return {}
+        normalized: Dict[str, str] = {}
+        for sub_type, path in value.items():
+            if sub_type not in VALID_OTHER_SUB_TYPES:
+                if strict:
+                    raise ValueError(
+                        f"Unknown other-model sub-type '{sub_type}'; "
+                        f"expected one of {sorted(VALID_OTHER_SUB_TYPES)}"
+                    )
+                continue
+            if not isinstance(path, str):
+                continue
+            stripped = path.strip()
+            if stripped:
+                normalized[sub_type] = stripped
+        return normalized
+
+    def is_other_models_enabled(self) -> bool:
+        """Return True when the opt-in Other Models management is enabled."""
+        return bool(self.settings.get("enable_other_models", False))
+
+    def get_enabled_other_sub_types(self) -> List[str]:
+        """Return the enabled other-model sub_types (empty when the feature is off)."""
+        if not self.is_other_models_enabled():
+            return []
+        return normalize_other_sub_types(self.settings.get("enabled_other_sub_types"))
+
+    def is_other_sub_type_enabled(self, sub_type: Optional[str]) -> bool:
+        """Return True when ``sub_type`` is currently managed."""
+        if not sub_type:
+            return False
+        return sub_type in self.get_enabled_other_sub_types()
+
+    def _apply_other_model_settings_change(self) -> None:
+        """Rebuild other-model roots and refresh the other scanner after a toggle."""
+        try:
+            from ..config import config  # Local import to avoid circular dependency
+
+            config.refresh_other_roots()
+        except Exception as exc:  # pragma: no cover - defensive logging
+            logger.debug("Failed to refresh other-model roots: %s", exc)
+
+        try:
+            from .service_registry import ServiceRegistry  # pyright: ignore[reportImportCycles]
+
+            scanner = ServiceRegistry.get_service_sync("other_scanner")
+            if scanner is not None and hasattr(scanner, "on_library_changed"):
+                # reconcile=True lets the scanner pick up newly enabled roots and
+                # purge rows for folders that are no longer managed.
+                scanner.on_library_changed(reconcile=True)
+        except Exception as exc:  # pragma: no cover - defensive logging
+            logger.debug("Failed to refresh other scanner after settings change: %s", exc)
+
     def _has_configured_paths(self, folder_paths: Any) -> bool:
         if not isinstance(folder_paths, Mapping):
             return False
@@ -744,6 +835,7 @@ class SettingsManager:
         default_checkpoint_root: Optional[str] = None,
         default_unet_root: Optional[str] = None,
         default_embedding_root: Optional[str] = None,
+        default_other_roots: Optional[Mapping[str, str]] = None,
         recipes_path: Optional[str] = None,
     ) -> bool:
         libraries = self.settings.get("libraries", {})
@@ -794,6 +886,14 @@ class SettingsManager:
             library["default_embedding_root"] = default_embedding_root
             changed = True
 
+        if default_other_roots is not None:
+            normalized_other_roots = self._normalize_default_other_roots(
+                default_other_roots
+            )
+            if library.get("default_other_roots") != normalized_other_roots:
+                library["default_other_roots"] = normalized_other_roots
+                changed = True
+
         if recipes_path is not None and library.get("recipes_path") != recipes_path:
             library["recipes_path"] = recipes_path
             changed = True
@@ -894,12 +994,53 @@ class SettingsManager:
         updated = _check_and_auto_set("unet", "default_unet_root") or updated
         updated = _check_and_auto_set("embeddings", "default_embedding_root") or updated
 
+        # Other-model default roots: one entry per enabled sub_type; candidates
+        # are the union of that sub_type's folder_paths keys (text_encoder
+        # merges the legacy 'clip' key with 'text_encoders'). When the opt-in
+        # feature is off the existing mapping is left untouched.
+        other_roots = self._normalize_default_other_roots(
+            self.settings.get("default_other_roots")
+        )
+        if self.is_other_models_enabled():
+            for sub_type in self.get_enabled_other_sub_types():
+                candidates: List[str] = []
+                candidate_identities: set[str] = set()
+                for folder_key in OTHER_SUB_TYPE_FOLDER_KEYS.get(sub_type, []):
+                    for candidate in self._get_valid_root_candidates(folder_key):
+                        identity = _normalize_root_identity(candidate)
+                        if identity in candidate_identities:
+                            continue
+                        candidate_identities.add(identity)
+                        candidates.append(candidate)
+                if not candidates:
+                    continue
+                current = other_roots.get(sub_type, "")
+                if current and _normalize_root_identity(current) in candidate_identities:
+                    continue
+                other_roots[sub_type] = candidates[0]
+                if current:
+                    logger.info(
+                        "Repaired stale default_other_roots[%s] from '%s' to '%s' because it is not present in primary or extra roots",
+                        sub_type,
+                        current,
+                        candidates[0],
+                    )
+                else:
+                    logger.info(
+                        "Auto-set default_other_roots[%s] to '%s'",
+                        sub_type,
+                        candidates[0],
+                    )
+                updated = True
+
         if updated:
+            self.settings["default_other_roots"] = other_roots
             self._update_active_library_entry(
                 default_lora_root=self.settings.get("default_lora_root"),
                 default_checkpoint_root=self.settings.get("default_checkpoint_root"),
                 default_unet_root=self.settings.get("default_unet_root"),
                 default_embedding_root=self.settings.get("default_embedding_root"),
+                default_other_roots=other_roots,
             )
             if self._bootstrap_reason == "missing":
                 self._needs_initial_save = True
@@ -1599,6 +1740,12 @@ class SettingsManager:
             value = self.normalize_download_skip_base_models(value)
         elif key == "mature_blur_level":
             value = self.normalize_mature_blur_level(value)
+        elif key == "default_other_roots":
+            value = self._normalize_default_other_roots(value, strict=True)
+        elif key == "enabled_other_sub_types":
+            value = normalize_other_sub_types(value)
+        elif key == "enable_other_models":
+            value = bool(value)
         elif key == "recipes_path":
             current_recipes_dir = self._get_effective_recipes_dir()
             value = self._normalize_recipes_path_value(value)
@@ -1626,6 +1773,8 @@ class SettingsManager:
             self._update_active_library_entry(default_unet_root=str(value))
         elif key == "default_embedding_root":
             self._update_active_library_entry(default_embedding_root=str(value))
+        elif key == "default_other_roots":
+            self._update_active_library_entry(default_other_roots=value)
         elif key == "recipes_path":
             self._update_active_library_entry(recipes_path=str(value))
         elif key == "model_name_display":
@@ -1633,6 +1782,8 @@ class SettingsManager:
         self._save_settings()
         if key == "recipes_path":
             self._notify_library_change(self.get_active_library_name())
+        if key in ("enable_other_models", "enabled_other_sub_types"):
+            self._apply_other_model_settings_change()
         if portable_switch_pending:
             self._finalize_portable_switch()
 
@@ -1796,6 +1947,7 @@ class SettingsManager:
             "lora_scanner",
             "checkpoint_scanner",
             "embedding_scanner",
+            "other_scanner",
             "recipe_scanner",
         ):
             service = ServiceRegistry.get_service_sync(service_name)
@@ -1960,6 +2112,7 @@ class SettingsManager:
         default_checkpoint_root: Optional[str] = None,
         default_unet_root: Optional[str] = None,
         default_embedding_root: Optional[str] = None,
+        default_other_roots: Optional[Mapping[str, str]] = None,
         recipes_path: Optional[str] = None,
         metadata: Optional[Mapping[str, Any]] = None,
         activate: bool = False,
@@ -2004,6 +2157,11 @@ class SettingsManager:
                 if default_embedding_root is not None
                 else existing.get("default_embedding_root")
             ),
+            default_other_roots=(
+                default_other_roots
+                if default_other_roots is not None
+                else existing.get("default_other_roots")
+            ),
             recipes_path=(
                 recipes_path
                 if recipes_path is not None
@@ -2036,6 +2194,7 @@ class SettingsManager:
         default_checkpoint_root: str = "",
         default_unet_root: str = "",
         default_embedding_root: str = "",
+        default_other_roots: Optional[Mapping[str, str]] = None,
         recipes_path: str = "",
         metadata: Optional[Mapping[str, Any]] = None,
         activate: bool = False,
@@ -2054,6 +2213,7 @@ class SettingsManager:
             default_checkpoint_root=default_checkpoint_root,
             default_unet_root=default_unet_root,
             default_embedding_root=default_embedding_root,
+            default_other_roots=default_other_roots,
             recipes_path=recipes_path,
             metadata=metadata,
             activate=activate,
@@ -2114,6 +2274,7 @@ class SettingsManager:
         default_checkpoint_root: Optional[str] = None,
         default_unet_root: Optional[str] = None,
         default_embedding_root: Optional[str] = None,
+        default_other_roots: Optional[Mapping[str, str]] = None,
         recipes_path: Optional[str] = None,
     ) -> None:
         """Update folder paths for the active library."""
@@ -2127,6 +2288,7 @@ class SettingsManager:
             default_checkpoint_root=default_checkpoint_root,
             default_unet_root=default_unet_root,
             default_embedding_root=default_embedding_root,
+            default_other_roots=default_other_roots,
             recipes_path=recipes_path,
             activate=True,
         )
@@ -2151,6 +2313,7 @@ class SettingsManager:
                 "lora_scanner",
                 "checkpoint_scanner",
                 "embedding_scanner",
+                "other_scanner",
                 "recipe_scanner",
                 "model_update_service",
             ):
@@ -2173,10 +2336,14 @@ class SettingsManager:
         """Get download path template for specific model type
 
         Args:
-            model_type: The type of model ('lora', 'checkpoint', 'embedding')
+            model_type: The type of model ('lora', 'checkpoint', 'embedding',
+                'other')
 
         Returns:
-            Template string for the model type, defaults to '{base_model}/{first_tag}'
+            Template string for the model type. Falls back to the per-type
+            default in ``DEFAULT_DOWNLOAD_PATH_TEMPLATES``; unknown model types
+            resolve to an empty string (flat layout) rather than silently
+            nesting downloads under an unconfigured subfolder.
         """
         templates = self.settings.get("download_path_templates", {})
 
@@ -2200,27 +2367,19 @@ class SettingsManager:
                 logger.warning(
                     f"Failed to parse download_path_templates JSON string: {e}. Setting default values."
                 )
-                default_template = "{base_model}/{first_tag}"
-                templates = {
-                    "lora": default_template,
-                    "checkpoint": default_template,
-                    "embedding": default_template,
-                }
+                templates = dict(DEFAULT_DOWNLOAD_PATH_TEMPLATES)
                 self.settings["download_path_templates"] = templates
                 self._save_settings()
 
         # Ensure templates is a dictionary
         if not isinstance(templates, dict):
-            default_template = "{base_model}/{first_tag}"
-            templates = {
-                "lora": default_template,
-                "checkpoint": default_template,
-                "embedding": default_template,
-            }
+            templates = dict(DEFAULT_DOWNLOAD_PATH_TEMPLATES)
             self.settings["download_path_templates"] = templates
             self._save_settings()
 
-        return templates.get(model_type, "{base_model}/{first_tag}")
+        return templates.get(
+            model_type, DEFAULT_DOWNLOAD_PATH_TEMPLATES.get(model_type, "")
+        )
 
 
 _SETTINGS_MANAGER: Optional["SettingsManager"] = None

py/utils/constants.py

@@ -1,4 +1,4 @@
-from typing import Any
+from typing import Any, Dict, List
 
 NSFW_LEVELS = {
     "PG": 1,
@@ -83,6 +83,103 @@ VALID_LORA_SUB_TYPES = ["lora", "locon", "dora"]
 VALID_CHECKPOINT_SUB_TYPES = ["checkpoint", "diffusion_model"]
 VALID_EMBEDDING_SUB_TYPES = ["embedding"]
 
+# folder_paths key -> sub_type; single source of truth for extensibility.
+# Adding support for a new ComfyUI folder category is a one-line change here.
+OTHER_MODEL_FOLDER_SUBTYPES = {
+    "vae": "vae",
+    "upscale_models": "upscaler",
+    "text_encoders": "text_encoder",
+    "clip": "text_encoder",  # legacy ComfyUI key
+    "clip_vision": "clip_vision",
+    "controlnet": "controlnet",
+}
+VALID_OTHER_SUB_TYPES = ["vae", "upscaler", "text_encoder", "clip_vision", "controlnet"]
+# Sub-types managed when the (opt-in) Other Models feature is switched on.
+# The feature itself defaults to off (``enable_other_models`` = False), so
+# nothing here is scanned until the user enables it.
+#
+# The default set is deliberately limited to the dependency-style assets every
+# pipeline needs and where "which one am I actually using" is the real problem:
+# VAE, upscalers and text encoders. ``clip_vision`` and ``controlnet`` are
+# workflow-driven instead (IPAdapter/SVD, per-workflow ControlNet variants) and
+# ControlNet libraries routinely run to dozens of files, so both stay opt-in
+# and are treated symmetrically.
+DEFAULT_ENABLED_OTHER_SUB_TYPES: List[str] = [
+    "vae",
+    "upscaler",
+    "text_encoder",
+]
+
+
+def other_sub_type_folder_keys() -> Dict[str, List[str]]:
+    """Invert OTHER_MODEL_FOLDER_SUBTYPES into sub_type -> folder_paths keys.
+
+    ``text_encoder`` maps to two folder keys (``text_encoders`` and the legacy
+    ``clip``), so every consumer that resolves a sub_type back to folders must
+    merge both.
+    """
+    mapping: Dict[str, List[str]] = {}
+    for folder_key, sub_type in OTHER_MODEL_FOLDER_SUBTYPES.items():
+        mapping.setdefault(sub_type, []).append(folder_key)
+    return mapping
+
+
+# Precomputed inverse of OTHER_MODEL_FOLDER_SUBTYPES, keeping the table order.
+OTHER_SUB_TYPE_FOLDER_KEYS: Dict[str, List[str]] = other_sub_type_folder_keys()
+
+
+def normalize_other_sub_types(value: Any) -> List[str]:
+    """Normalize a stored/requested enabled-sub_type list.
+
+    Unknown values and duplicates are dropped; the result follows the
+    canonical VALID_OTHER_SUB_TYPES order so the stored setting and the UI
+    stay stable. Non-list input falls back to the defaults.
+    """
+    if isinstance(value, str):
+        candidates: Any = [value]
+    elif isinstance(value, (list, tuple, set)):
+        candidates = value
+    else:
+        return list(DEFAULT_ENABLED_OTHER_SUB_TYPES)
+
+    allowed = {item for item in candidates if isinstance(item, str)}
+    return [sub_type for sub_type in VALID_OTHER_SUB_TYPES if sub_type in allowed]
+# CivitAI model.type values accepted by the "other" page's fetch-metadata
+# validation (lowercased). CLIP/CLIPVision are retired upstream but still
+# appear on grandfathered models.
+VALID_OTHER_CIVITAI_TYPES = {
+    "vae",
+    "upscaler",
+    "textencoder",
+    "clip",
+    "clipvision",
+    "controlnet",
+    "other",
+}
+# CivitAI model.type -> internal sub_type for the "other" model page.
+CIVITAI_TYPE_TO_OTHER_SUB_TYPE = {
+    "vae": "vae",
+    "upscaler": "upscaler",
+    "textencoder": "text_encoder",
+    "clip": "text_encoder",
+    "clipvision": "clip_vision",
+    "controlnet": "controlnet",
+}
+
+# CivitAI ModelFile.type values -> internal sub_type for the "other" model
+# page. Used for download routing only, and strictly as an explicit user file
+# pick or a fallback when model.type maps to nothing — checkpoint models
+# routinely bundle VAE/Text Encoder component files, so file types must never
+# override a mapped model.type.
+CIVITAI_FILE_TYPE_TO_OTHER_SUB_TYPE = {
+    "VAE": "vae",
+    "Upscaler": "upscaler",
+    "Text Encoder": "text_encoder",
+    "Vision Encoder": "clip_vision",
+    "CLIPVision": "clip_vision",
+    "ControlNet": "controlnet",
+}
+
 # Backward compatibility alias
 VALID_LORA_TYPES = VALID_LORA_SUB_TYPES
 
@@ -91,6 +188,7 @@ CIVITAI_USER_MODEL_TYPES = [
     *VALID_LORA_TYPES,
     "textualinversion",
     "checkpoint",
+    *sorted(VALID_OTHER_CIVITAI_TYPES),
 ]
 
 # Default chunk size in megabytes used for hashing large files.
@@ -159,6 +257,19 @@ DEFAULT_PRIORITY_TAG_CONFIG = {
     "embedding": ", ".join(CIVITAI_MODEL_TAGS),
 }
 
+# Default download path template for each model type. "other" defaults to a
+# flat layout (empty template) on purpose: other-model downloads are already
+# separated by sub_type roots (default_other_roots), and priority_tags has no
+# "other" entry, so {first_tag} would resolve to an arbitrary CivitAI tag and
+# scatter files into unstable folders. Users can still opt in to a template by
+# writing "other" into download_path_templates in settings.json.
+DEFAULT_DOWNLOAD_PATH_TEMPLATES: Dict[str, str] = {
+    "lora": "{base_model}/{first_tag}",
+    "checkpoint": "{base_model}/{first_tag}",
+    "embedding": "{base_model}/{first_tag}",
+    "other": "",
+}
+
 # baseModel values from CivitAI that should be treated as diffusion models (unet)
 # These model types are incorrectly labeled as "checkpoint" by CivitAI but are actually diffusion models
 DIFFUSION_MODEL_BASE_MODELS = frozenset(

py/utils/example_images_download_manager.py

@@ -420,6 +420,10 @@ class DownloadManager:
                 embedding_scanner = await ServiceRegistry.get_embedding_scanner()
                 scanners.append(("embedding", embedding_scanner))
 
+            if "other" in model_types:
+                other_scanner = await ServiceRegistry.get_other_scanner()
+                scanners.append(("other", other_scanner))
+
             # Load progress file to check processed models (async to avoid blocking)
             settings_manager = get_settings_manager()
             active_library = settings_manager.get_active_library_name()
@@ -600,6 +604,10 @@ class DownloadManager:
                 embedding_scanner = await ServiceRegistry.get_embedding_scanner()
                 scanners.append(("embedding", embedding_scanner))
 
+            if "other" in model_types:
+                other_scanner = await ServiceRegistry.get_other_scanner()
+                scanners.append(("other", other_scanner))
+
             # Get all models
             all_models = []
             for scanner_type, scanner in scanners:
@@ -1098,6 +1106,10 @@ class DownloadManager:
                 embedding_scanner = await ServiceRegistry.get_embedding_scanner()
                 scanners.append(("embedding", embedding_scanner))
 
+            if "other" in model_types:
+                other_scanner = await ServiceRegistry.get_other_scanner()
+                scanners.append(("other", other_scanner))
+
             # Find the specified models
             models_to_process = []
             for scanner_type, scanner in scanners:

py/utils/models.py

@@ -2,7 +2,7 @@ from dataclasses import dataclass, asdict, field
 from typing import Callable, Dict, Optional, List, Any
 from datetime import datetime
 import os
-from .constants import INVALID_AUTOV3_EMPTY_HASH
+from .constants import CIVITAI_TYPE_TO_OTHER_SUB_TYPE, INVALID_AUTOV3_EMPTY_HASH
 from .model_utils import determine_base_model
 
 
@@ -77,9 +77,6 @@ class BaseModelMetadata:
     last_checked_at: float = 0  # Last checked timestamp
     hash_status: str = "completed"  # Hash calculation status: pending | calculating | completed | failed
     autov3: Optional[str] = None  # CivitAI AutoV3 hash (12-char lowercase hex); "" = checked but unavailable, None = not checked
-    trainedWords: List[str] = field(
-        default_factory=list
-    )  # Trigger words / activation prompts (source-agnostic)
     _unknown_fields: Dict[str, Any] = field(
         default_factory=dict, repr=False, compare=False
     )  # Store unknown fields
@@ -92,9 +89,6 @@ class BaseModelMetadata:
         if self.tags is None:
             self.tags = []
 
-        if self.trainedWords is None:
-            self.trainedWords = []
-
     @classmethod
     def from_dict(cls, data: Dict[str, Any]) -> "BaseModelMetadata":
         """Create instance from dictionary"""
@@ -324,6 +318,61 @@ class CheckpointMetadata(BaseModelMetadata):
         )
 
 
+@dataclass
+class OtherModelMetadata(BaseModelMetadata):
+    """Represents the metadata structure for an "other" model (VAE, upscaler,
+    text encoder, CLIP vision, ControlNet, ...).
+
+    The sub_type is location-derived: the OtherScanner sets it from the
+    folder_paths category whose root contains the file. The dataclass default
+    is only a placeholder.
+    """
+
+    sub_type: str = "vae"  # Placeholder; overridden by the scanner hooks
+
+    @classmethod
+    def from_civitai_info(
+        cls, version_info: Dict[str, Any], file_info: Dict[str, Any], save_path: str
+    ) -> "OtherModelMetadata":
+        """Create OtherModelMetadata instance from Civitai version info"""
+        file_name = file_info.get("name", "")
+        base_model = determine_base_model(version_info.get("baseModel", ""))
+        sha256_value = (file_info.get("hashes") or {}).get("SHA256", "").lower()
+        # Map the CivitAI model type onto our sub_types; unknown types keep the
+        # placeholder until the scanner re-derives sub_type from the location.
+        # The type lives at version["model"]["type"], not version["type"].
+        civitai_type = str((version_info.get("model") or {}).get("type", "") or "").lower()
+        sub_type = CIVITAI_TYPE_TO_OTHER_SUB_TYPE.get(civitai_type, "vae")
+
+        # Extract tags and description if available
+        tags = []
+        description = ""
+        model_data = version_info.get("model") or {}
+        if "tags" in model_data:
+            tags = model_data["tags"]
+        if "description" in model_data:
+            description = model_data["description"]
+
+        return cls(
+            file_name=os.path.splitext(file_name)[0],
+            model_name=model_data.get("name", os.path.splitext(file_name)[0]),
+            file_path=save_path.replace(os.sep, "/"),
+            size=file_info.get("sizeKB", 0) * 1024,
+            modified=datetime.now().timestamp(),
+            sha256=sha256_value,
+            base_model=base_model,
+            preview_url="",  # Will be updated after preview download
+            preview_nsfw_level=0,
+            from_civitai=True,
+            civitai=version_info,
+            sub_type=sub_type,
+            tags=tags,
+            modelDescription=description,
+            # Direct read: the downloaded file IS file_info, no SHA256 matching.
+            autov3=normalize_autov3((file_info.get("hashes") or {}).get("AutoV3")),
+        )
+
+
 @dataclass
 class EmbeddingMetadata(BaseModelMetadata):
     """Represents the metadata structure for an Embedding model"""

settings.json.example

@@ -18,6 +18,5 @@
       "C:/path/to/your/embeddings_folder",
       "C:/path/to/another/embeddings_folder"
     ]
-  },
-  "auto_organize_exclusions": []
+  }
 }

static/css/components/header.css

@@ -12,7 +12,7 @@
 }
 
 .header-container {
-  max-width: 1400px;
+  max-width: none;
   margin: 0 auto;
   padding: 0 15px;
   display: flex;
@@ -38,19 +38,6 @@
   flex-shrink: 0;
 }
 
-/* Responsive header container for larger screens */
-@media (min-width: 2150px) {
-  .header-container {
-    max-width: 1800px;
-  }
-}
-
-@media (min-width: 3000px) {
-  .header-container {
-    max-width: 2400px;
-  }
-}
-
 /* Logo and title styling */
 .header-branding {
   display: flex;
@@ -96,6 +83,12 @@
   white-space: nowrap;
 }
 
+/* Opt-in pages (e.g. Other Models) hide their nav entry until enabled.
+   A class is used instead of [hidden] because .nav-item sets display: flex. */
+.nav-item--hidden {
+  display: none;
+}
+
 .nav-item:hover,
 .nav-item:focus-visible {
   background-color: var(--lora-surface-hover, oklch(95% 0.02 256));
@@ -120,6 +113,9 @@
   display: flex;
   justify-content: center;
   max-width: 600px;
+  /* No hard floor: the field shrinks with the available space instead of parking
+     at a fixed width and crowding its own placeholder (see the 1366px query). */
+  min-width: 0;
   margin: 0 auto;
   transition: opacity 0.2s ease;
 }
@@ -128,6 +124,7 @@
 .header-search .search-container {
   width: 100%;
   max-width: 600px;
+  min-width: 0;
   position: relative;
   display: flex;
   align-items: center;
@@ -149,7 +146,12 @@
   width: 100%;
   padding: 0.5rem 0.75rem;
   padding-left: 2.25rem !important;
-  padding-right: 6.75rem !important; /* clear room for options + filter + clear/cue toggles */
+  /* Reserve exactly the inline chrome so typed text never runs under it:
+     cue(58) + clear(28) + toggles(28 + 28 + 4 gap) + edges(8 + 8) = 126px.
+     Below 1366px the cue is hidden and the reservation drops to 68px.
+     !important is required: search-filter.css loads later and sets its own
+     right padding at equal specificity (.search-container input). */
+  padding-right: 7.875rem !important;
   border: none;
   background: transparent;
   color: var(--text-color);
@@ -697,6 +699,20 @@
   margin: 0.25rem 0;
 }
 
+/* Responsive: the Ctrl+F cue is pure decoration and, above 950px, the widest
+   thing inside the field. Below 1366px the header (branding + full nav) leaves
+   too little room for it, so it steps aside and the field reclaims its 58px.
+   The shortcut itself keeps working - only the visual hint is dropped. */
+@media (max-width: 1366px) {
+  .header-search .search-shortcut-cue {
+    display: none;
+  }
+
+  .header-search input {
+    padding-right: 4.25rem !important;
+  }
+}
+
 /* Responsive: Early optimization at 1200px - reduce gaps and padding */
 @media (max-width: 1200px) {
   .header-container {
@@ -716,11 +732,6 @@
   .header-controls {
     gap: 6px;
   }
-
-  .header-controls > div {
-    width: 30px;
-    height: 30px;
-  }
 }
 
 /* Responsive: Hide nav icons at 1100px to save space */
@@ -797,13 +808,12 @@
   }
 }
 
-/* For very small screens - switch nav to icons only */
-@media (max-width: 600px) {
-  .header-container {
-    padding: 0 8px;
-    gap: 0.4rem;
-  }
-
+/* For narrower screens - switch nav to icons only.
+   A labelled nav needs ~383px and a readable search field needs ~300px, so the
+   two cannot coexist below ~700px: at 601-700px the search input was previously
+   squeezed to 200px, leaving only ~96px of text room and overlapping the
+   placeholder with the inline toggles. Labels therefore collapse here. */
+@media (max-width: 700px) {
   .main-nav {
     display: flex;
     gap: 0.15rem;
@@ -811,8 +821,7 @@
   }
 
   .nav-item {
-    padding: 0.25rem;
-    font-size: 0.75rem;
+    padding: 0.25rem 0.4rem;
   }
 
   .nav-item span {
@@ -821,6 +830,22 @@
 
   .nav-item i {
     display: block;
+  }
+}
+
+/* For very small screens - tighten container spacing */
+@media (max-width: 600px) {
+  .header-container {
+    padding: 0 8px;
+    gap: 0.4rem;
+  }
+
+  .nav-item {
+    padding: 0.25rem;
+    font-size: 0.75rem;
+  }
+
+  .nav-item i {
     font-size: 1rem;
   }
 }

static/css/components/modal/_base.css

@@ -592,3 +592,145 @@ button:disabled,
     margin-top: 2px;
     flex-shrink: 0;
 }
+
+/* Recipe Rematch Options Modal */
+#rematchOptionsModal .modal-body {
+    padding: var(--space-3);
+}
+
+#rematchOptionsModal .confirmation-message {
+    color: var(--text-color);
+    margin-bottom: var(--space-3);
+    font-size: 1em;
+    line-height: 1.5;
+}
+
+/* Selectable option card — click anywhere toggles the checkbox (label wrap).
+   Checkmark follows the batch-import modal's custom checkbox pattern. */
+#rematchOptionsModal .rematch-option-card {
+    position: relative;
+    display: flex;
+    align-items: flex-start;
+    gap: var(--space-2);
+    padding: var(--space-3);
+    background: var(--surface-subtle);
+    border: 1px solid var(--border-color);
+    border-radius: var(--border-radius-sm);
+    cursor: pointer;
+    user-select: none;
+    transition: var(--transition-base);
+}
+
+#rematchOptionsModal .rematch-option-card:hover {
+    border-color: var(--lora-accent);
+}
+
+#rematchOptionsModal .rematch-option-card:has(input[type="checkbox"]:checked) {
+    border-color: var(--lora-accent);
+    background: oklch(from var(--lora-accent) l c h / 0.08);
+}
+
+/* Visually hidden but keyboard-focusable (focus ring lands on the card). */
+#rematchOptionsModal .rematch-option-card input[type="checkbox"] {
+    position: absolute;
+    opacity: 0;
+    width: 0;
+    height: 0;
+}
+
+#rematchOptionsModal .rematch-option-card:has(input[type="checkbox"]:focus-visible) {
+    box-shadow: 0 0 0 2px oklch(from var(--lora-accent) l c h / 0.2);
+}
+
+#rematchOptionsModal .rematch-option-checkmark {
+    width: 18px;
+    height: 18px;
+    margin-top: 1px;
+    flex-shrink: 0;
+    border: 2px solid var(--border-color);
+    border-radius: 4px;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    transition: var(--transition-base);
+    background: var(--bg-color);
+}
+
+#rematchOptionsModal .rematch-option-card input[type="checkbox"]:checked + .rematch-option-checkmark {
+    background: var(--lora-accent);
+    border-color: var(--lora-accent);
+}
+
+#rematchOptionsModal .rematch-option-card input[type="checkbox"]:checked + .rematch-option-checkmark::after {
+    content: '\f00c';
+    font-family: 'Font Awesome 6 Free', sans-serif;
+    font-weight: 900;
+    color: var(--lora-text);
+    font-size: 12px;
+}
+
+#rematchOptionsModal .rematch-option-text {
+    display: flex;
+    flex-direction: column;
+    gap: var(--space-1);
+    color: var(--text-color);
+    min-width: 0;
+}
+
+#rematchOptionsModal .rematch-option-title {
+    font-weight: 600;
+    font-size: 0.95em;
+}
+
+#rematchOptionsModal .rematch-option-caveat {
+    display: flex;
+    align-items: flex-start;
+    gap: var(--space-2);
+    font-size: 0.85em;
+    line-height: 1.4;
+    color: var(--text-muted);
+}
+
+#rematchOptionsModal .rematch-option-caveat i {
+    color: var(--lora-accent);
+    margin-top: 2px;
+    flex-shrink: 0;
+}
+
+/* Recipe Rematch Summary Modal (dynamically built by RematchSummaryModal.js;
+   stat cards / failure table / summary header come from
+   metadata-refresh-result.css and download-batch-summary.css). */
+.rematch-summary-modal {
+    max-width: 700px;
+}
+
+.rematch-cancelled-note {
+    display: flex;
+    align-items: flex-start;
+    gap: var(--space-2);
+    margin: 0 0 var(--space-2) 0;
+    font-size: var(--text-sm);
+    color: var(--color-warning);
+}
+
+.rematch-cancelled-note i {
+    margin-top: 2px;
+    flex-shrink: 0;
+}
+
+/* Review section heading uses the accent (review, not failure) instead of
+   the failure-section error color. */
+.rematch-review-section h4 {
+    color: var(--lora-accent);
+}
+
+#rematchSummaryModal .rematch-undo-btn {
+    padding: var(--space-1) var(--space-2);
+    font-size: var(--text-xs);
+    white-space: nowrap;
+}
+
+#rematchSummaryModal tr.undone td:not(.rematch-undo-cell) {
+    text-decoration: line-through;
+    opacity: 0.6;
+}

static/css/components/modal/settings-modal.css

@@ -1744,3 +1744,39 @@ input:checked + .toggle-slider:before {
     font-style: italic;
     user-select: none;
 }
+
+/* Other Models opt-in: sub_type checkbox row */
+.other-subtype-checkboxes {
+    display: flex;
+    flex-wrap: wrap;
+    justify-content: flex-end;
+    gap: 6px 14px;
+}
+
+.other-subtype-checkbox {
+    display: inline-flex;
+    align-items: center;
+    gap: 6px;
+    font-size: 0.9em;
+    color: var(--text-color);
+    cursor: pointer;
+    white-space: nowrap;
+}
+
+.other-subtype-checkbox input[type="checkbox"] {
+    cursor: pointer;
+}
+
+.other-subtype-toggles.is-disabled {
+    opacity: 0.5;
+}
+
+.other-subtype-toggles.is-disabled .other-subtype-checkbox {
+    cursor: default;
+}
+
+/* Disabled default-root selects for switched-off sub_types / feature */
+.select-control select:disabled {
+    opacity: 0.5;
+    cursor: not-allowed;
+}

static/css/layout.css

@@ -59,7 +59,10 @@ body.sticky-controls .sticky-topbar {
     display: flex;
     align-items: center;
     gap: 8px;
-    margin-left: auto; /* Push to the right */
+    /* Push to the right of the row. Because it is also the flex item that is
+       allowed to drop to a second row, an auto margin keeps it right-aligned on
+       either row — no width: 100% / viewport breakpoint needed. */
+    margin-left: auto;
 }
 
 .actions {
@@ -67,7 +70,11 @@ body.sticky-controls .sticky-topbar {
     align-items: center;
     justify-content: space-between;
     gap: var(--space-2);
-    flex-wrap: nowrap;
+    /* Wrap only when the controls genuinely cannot fit, instead of at a fixed
+       viewport width. Viewport-based wrapping wasted space on high-DPI displays
+       (e.g. a 2560px monitor at 200% scaling reports a ~1280px CSS viewport even
+       when the window is maximized). */
+    flex-wrap: wrap;
     width: 100%;
 }
 
@@ -75,7 +82,11 @@ body.sticky-controls .sticky-topbar {
     display: flex;
     align-items: center;
     gap: var(--space-2);
-    flex-wrap: nowrap;
+    /* Let the group shrink rather than overflow so .controls-right only wraps
+       when it really has to. */
+    flex-wrap: wrap;
+    flex-shrink: 1;
+    min-width: 0;
 }
 
 /* Action button styling */
@@ -84,7 +95,9 @@ body.sticky-controls .sticky-topbar {
 }
 
 .control-group button {
-    min-width: 100px;
+    /* Keeps the toolbar visually even without forcing the row to overflow (the
+       old 100px floor pushed the total past the container on wide screens). */
+    min-width: 90px;
     display: flex;
     align-items: center;
     justify-content: center;
@@ -627,49 +640,42 @@ body.sticky-controls .sticky-topbar {
     text-align: center;
 }
 
-/* Intermediate breakpoint: wrap controls-right to prevent overflow */
+/* Intermediate breakpoint: tighten the controls so the whole bar still fits on
+   one row at common laptop/high-DPI widths. The buttons are allowed to shrink to
+   their content (min-width: 0) here, which is what reclaims the space the old
+   100px floor plus a forced wrap used to waste. .controls-right is deliberately
+   NOT forced onto its own row: it stays inline while it fits and only drops to a
+   second row (staying right-aligned through its auto margin) when it does not. */
 @media (max-width: 1500px) {
-    .actions {
-        flex-wrap: wrap;
-        gap: var(--space-2);
-    }
-
     .action-buttons {
-        flex-wrap: wrap;
         gap: var(--space-1);
     }
 
-    .controls-right {
-        width: 100%;
-        justify-content: flex-end;
-        margin-top: 8px;
-        padding-left: 0;
+    .control-group button {
+        min-width: 0;
+        padding: 4px 8px;
     }
 
-    /* Reduce button sizes to fit better */
-    .control-group button {
-        min-width: 80px;
-        padding: 4px 8px;
-        font-size: 0.8em;
+    .control-group select {
+        min-width: 0;
     }
 }
 
 @media (max-width: 768px) {
     .actions {
-        flex-wrap: wrap;
-        gap: var(--space-1);
+        gap: var(--space-2);
     }
-    
+
     .action-buttons {
-        flex-wrap: wrap;
-        gap: var(--space-1);
         width: 100%;
     }
-    
+
+    /* Narrow screens: let the right-hand group wrap below the buttons, still
+       right-aligned. */
     .controls-right {
-        width: 100%;
+        flex-wrap: wrap;
         justify-content: flex-end;
-        margin-top: 8px;
+        gap: var(--space-1);
     }
 
     .control-group button:hover {

static/css/onboarding.css

@@ -44,6 +44,13 @@
     pointer-events: auto !important;
 }
 
+/* Keep the fixed-position sidebar anchored when highlighted, otherwise
+   .onboarding-target-highlight's position: relative would pull it into
+   normal flow and it would move away from the spotlight cutout */
+.folder-sidebar.onboarding-target-highlight {
+    position: fixed;
+}
+
 .onboarding-popup {
     position: absolute;
     background: var(--lora-surface);

static/js/api/apiConfig.js

@@ -9,7 +9,8 @@ import { state } from '../state/index.js';
 export const MODEL_TYPES = {
     LORA: 'loras',
     CHECKPOINT: 'checkpoints',
-    EMBEDDING: 'embeddings' // Future model type
+    EMBEDDING: 'embeddings',
+    OTHER: 'other'
 };
 
 // Base API configuration for each model type
@@ -40,6 +41,15 @@ export const MODEL_CONFIG = {
         supportsBulkOperations: true,
         supportsMove: true,
         templateName: 'embeddings.html'
+    },
+    [MODEL_TYPES.OTHER]: {
+        displayName: 'Other Model',
+        singularName: 'other',
+        defaultPageSize: 100,
+        supportsLetterFilter: false,
+        supportsBulkOperations: true,
+        supportsMove: true,
+        templateName: 'other.html'
     }
 };
 
@@ -133,6 +143,10 @@ export const MODEL_SPECIFIC_ENDPOINTS = {
     },
     [MODEL_TYPES.EMBEDDING]: {
         metadata: `/api/lm/${MODEL_TYPES.EMBEDDING}/metadata`,
+    },
+    [MODEL_TYPES.OTHER]: {
+        metadata: `/api/lm/${MODEL_TYPES.OTHER}/metadata`,
+        roots_by_subtype: `/api/lm/${MODEL_TYPES.OTHER}/roots_by_subtype`,
     }
 };
 
@@ -184,6 +198,7 @@ export const DOWNLOAD_ENDPOINTS = {
     downloadGet: '/api/lm/download-model-get',
     cancelGet: '/api/lm/cancel-download-get',
     progress: '/api/lm/download-progress',
+    routing: '/api/lm/download/routing',
     exampleImages: '/api/lm/force-download-example-images', // Re-process example images ignoring previous status
     exampleImagesMissing: '/api/lm/download-example-images' // Download only missing example images
 };

static/js/api/modelApiFactory.js

@@ -1,6 +1,7 @@
 import { LoraApiClient } from './loraApi.js';
 import { CheckpointApiClient } from './checkpointApi.js';
 import { EmbeddingApiClient } from './embeddingApi.js';
+import { OtherApiClient } from './otherApi.js';
 import { MODEL_TYPES, isValidModelType } from './apiConfig.js';
 import { state } from '../state/index.js';
 
@@ -12,6 +13,8 @@ export function createModelApiClient(modelType) {
             return new CheckpointApiClient(MODEL_TYPES.CHECKPOINT);
         case MODEL_TYPES.EMBEDDING:
             return new EmbeddingApiClient(MODEL_TYPES.EMBEDDING);
+        case MODEL_TYPES.OTHER:
+            return new OtherApiClient(MODEL_TYPES.OTHER);
         default:
             throw new Error(`Unsupported model type: ${modelType}`);
     }

static/js/api/otherApi.js

@@ -0,0 +1,45 @@
+import { BaseModelApiClient } from './baseModelApi.js';
+
+/**
+ * Other-models-specific API client (VAE, upscalers, text encoders, etc.)
+ */
+export class OtherApiClient extends BaseModelApiClient {
+    /**
+     * Get other-model roots, optionally narrowed to one sub_type
+     * (vae/upscaler/text_encoder/clip_vision/controlnet).
+     *
+     * Without a sub_type this falls back to the merged roots list
+     * (GET /api/lm/other/roots); with one it reads the grouped
+     * roots_by_subtype map and extracts the matching list.
+     */
+    async fetchModelRoots(subType = null) {
+        if (!subType) {
+            return super.fetchModelRoots();
+        }
+
+        const data = await this.fetchRootsBySubType();
+        const groupedRoots = data.roots_by_subtype || {};
+        return {
+            success: data.success !== false,
+            roots: groupedRoots[subType] || [],
+        };
+    }
+
+    /**
+     * Get other-model roots grouped by sub_type.
+     * GET /api/lm/other/roots_by_subtype
+     *   -> { success, roots_by_subtype: {sub_type: [...]} }
+     */
+    async fetchRootsBySubType() {
+        try {
+            const response = await fetch(this.apiConfig.endpoints.specific.roots_by_subtype);
+            if (!response.ok) {
+                throw new Error('Failed to fetch other-model roots by sub_type');
+            }
+            return await response.json();
+        } catch (error) {
+            console.error('Error fetching other-model roots by sub_type:', error);
+            throw error;
+        }
+    }
+}

static/js/api/recipeApi.js

@@ -677,7 +677,7 @@ export class RecipeSidebarApiClient {
         };
     }
 
-    async rematchBulkModels(filePaths) {
+    async rematchBulkModels(filePaths, options = {}) {
         if (!filePaths || filePaths.length === 0) {
             throw new Error('No file paths provided');
         }
@@ -690,14 +690,19 @@ export class RecipeSidebarApiClient {
             throw new Error('No recipe IDs could be derived from file paths');
         }
 
+        const body = { recipe_ids: recipeIds };
+        // Only sent when opted in — the strict body stays exactly
+        // {recipe_ids} for backward compatibility.
+        if (options.relaxed === true) {
+            body.relaxed = true;
+        }
+
         const response = await fetch(this.apiConfig.endpoints.rematchBulk, {
             method: 'POST',
             headers: {
                 'Content-Type': 'application/json',
             },
-            body: JSON.stringify({
-                recipe_ids: recipeIds,
-            }),
+            body: JSON.stringify(body),
         });
 
         const result = await response.json();

static/js/components/ContextMenu/BulkContextMenu.js

@@ -139,8 +139,8 @@ export class BulkContextMenu extends BaseContextMenu {
 
         const downloadExampleImagesSubmenu = this.menu.querySelector('[data-has-submenu="download-example-images"]');
         if (downloadExampleImagesSubmenu) {
-            // Show on model pages (loras, checkpoints, embeddings), hide on recipes
-            downloadExampleImagesSubmenu.style.display = ['loras', 'checkpoints', 'embeddings'].includes(currentModelType) ? 'flex' : 'none';
+            // Show on model pages (loras, checkpoints, embeddings, other), hide on recipes
+            downloadExampleImagesSubmenu.style.display = ['loras', 'checkpoints', 'embeddings', 'other'].includes(currentModelType) ? 'flex' : 'none';
         }
 
         const skipMetadataRefreshItem = this.menu.querySelector('[data-action="skip-metadata-refresh"]');

static/js/components/ContextMenu/CheckpointContextMenu.js

@@ -25,6 +25,7 @@ export class CheckpointContextMenu extends BaseContextMenu {
     showMenu(x, y, card) {
         super.showMenu(x, y, card);
         this.updateExcludeMenuItem();
+        this.updateEnrichMenuItem(card);
 
         // Update the "Move to other root" label based on current model type
         const moveOtherItem = this.menu.querySelector('[data-action="move-other"]');

static/js/components/ContextMenu/GlobalContextMenu.js

@@ -4,6 +4,8 @@ import { translate } from '../../utils/i18nHelpers.js';
 import { state } from '../../state/index.js';
 import { getCompleteApiConfig, getCurrentModelType } from '../../api/apiConfig.js';
 import { performModelUpdateCheck } from '../../utils/updateCheckHelpers.js';
+import { rematchModalManager } from '../../managers/RematchModalManager.js';
+import { showRematchSummary } from '../RematchSummaryModal.js';
 
 export class GlobalContextMenu extends BaseContextMenu {
     constructor() {
@@ -368,6 +370,18 @@ export class GlobalContextMenu extends BaseContextMenu {
             return;
         }
 
+        // Collect options (relaxed matching) before starting anything; the
+        // run only begins when the user confirms the dialog.
+        rematchModalManager.showOptionsModal({
+            onConfirm: ({ relaxed }) => this._startRematch(menuItem, relaxed),
+        });
+    }
+
+    async _startRematch(menuItem, relaxed = false) {
+        if (this._rematchInProgress) {
+            return;
+        }
+
         this._rematchInProgress = true;
         menuItem?.classList.add('disabled');
 
@@ -384,6 +398,7 @@ export class GlobalContextMenu extends BaseContextMenu {
             const response = await fetch('/api/lm/recipes/rematch', {
                 method: 'POST',
                 headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({ relaxed: !!relaxed }),
             });
 
             const result = await response.json();
@@ -411,48 +426,32 @@ export class GlobalContextMenu extends BaseContextMenu {
                             const recipes = p.matched_recipes ?? p.rematched ?? 0;
                             const failures = p.errors || 0;
                             const unresolved = p.unresolved_entries ?? 0;
-                            if (entries > 0) {
-                                const successKey = failures > 0
-                                    ? 'globalContextMenu.rematchRecipes.successErrors'
-                                    : 'globalContextMenu.rematchRecipes.success';
-                                const successText = failures > 0
-                                    ? `Matched ${entries} entries across ${recipes} recipes, ${failures} failed.`
-                                    : `Matched ${entries} entries across ${recipes} recipes.`;
-                                progressUI?.complete(translate(
-                                    successKey,
-                                    { count: recipes, recipes, entries, failures },
-                                    successText
-                                ));
-                                showToast(successKey, { count: recipes, recipes, entries, failures }, failures > 0 ? 'warning' : 'success');
-                            } else if (failures > 0) {
-                                // Nothing matched and at least one recipe
-                                // errored — "no rematch needed" would be
-                                // actively misleading here.
-                                progressUI?.complete(translate(
-                                    'globalContextMenu.rematchRecipes.allFailed',
-                                    { total: p.total, recipes, entries, failures },
-                                    `Rematch failed for ${failures} of ${p.total} recipes.`
-                                ));
-                                showToast('globalContextMenu.rematchRecipes.allFailed', { total: p.total, recipes, entries, failures }, 'error');
-                            } else if (unresolved > 0) {
-                                // Entries existed but have no local model —
-                                // expected for models deleted from Civitai;
-                                // informational, not an error.
-                                const unresolvedRecipes = p.unresolved_recipes ?? 0;
-                                progressUI?.complete(translate(
-                                    'globalContextMenu.rematchRecipes.noMatch',
-                                    { entries: unresolved, recipes: unresolvedRecipes, total: p.total, failures },
-                                    `No local match found for ${unresolved} entries in ${unresolvedRecipes} recipes.`
-                                ));
-                                showToast('globalContextMenu.rematchRecipes.noMatch', { entries: unresolved, recipes: unresolvedRecipes, total: p.total, failures }, 'info');
-                            } else {
-                                // Everything was skipped (nothing to do).
+                            const l4Matches = Array.isArray(p.l4_matches) ? p.l4_matches : [];
+                            // Complete no-op (nothing matched, nothing
+                            // unresolved, no errors) keeps the lightweight
+                            // toast; anything else opens the post-run summary
+                            // modal.
+                            const isNoop = entries === 0 && unresolved === 0 && failures === 0;
+                            if (isNoop) {
                                 progressUI?.complete(translate(
                                     'globalContextMenu.rematchRecipes.success',
                                     { count: recipes, recipes, entries, failures },
                                     `Matched ${entries} entries across ${recipes} recipes.`
                                 ));
                                 showToast('globalContextMenu.rematchRecipes.success', { count: recipes, recipes, entries, failures }, 'success');
+                            } else {
+                                progressUI?.complete();
+                                showRematchSummary({
+                                    scope: 'global',
+                                    total: p.total || 0,
+                                    matchedRecipes: recipes,
+                                    matchedEntries: entries,
+                                    unresolvedRecipes: p.unresolved_recipes ?? 0,
+                                    unresolvedEntries: unresolved,
+                                    skipped: p.skipped || 0,
+                                    errors: failures,
+                                    l4Matches,
+                                });
                             }
                             // Refresh recipes page if active
                             if (window.recipesPage) {
@@ -469,7 +468,23 @@ export class GlobalContextMenu extends BaseContextMenu {
                                 { count: cancelledRecipes, recipes: cancelledRecipes, entries: cancelledEntries },
                                 `Rematch cancelled. ${cancelledRecipes} recipes updated (${cancelledEntries} entries).`
                             ));
-                            showToast('globalContextMenu.rematchRecipes.cancelled', { count: cancelledRecipes, recipes: cancelledRecipes, entries: cancelledEntries }, 'info');
+                            // A cancelled run still reports partial results
+                            // via the summary modal (marked as cancelled).
+                            showRematchSummary({
+                                scope: 'global',
+                                cancelled: true,
+                                total: p.total || 0,
+                                matchedRecipes: cancelledRecipes,
+                                matchedEntries: cancelledEntries,
+                                unresolvedRecipes: p.unresolved_recipes ?? 0,
+                                unresolvedEntries: p.unresolved_entries ?? 0,
+                                skipped: p.skipped || 0,
+                                errors: p.errors || 0,
+                                l4Matches: Array.isArray(p.l4_matches) ? p.l4_matches : [],
+                            });
+                            if (window.recipesPage) {
+                                window.recipesPage.refresh();
+                            }
                         }
                     } else if (progressResponse.status === 404) {
                         // Progress might have finished quickly and been cleaned up

static/js/components/ContextMenu/LoraContextMenu.js

@@ -1,8 +1,7 @@
 import { BaseContextMenu } from './BaseContextMenu.js';
 import { ModelContextMenuMixin } from './ModelContextMenuMixin.js';
-import { state } from '../../state/index.js';
 import { getModelApiClient, resetAndReload } from '../../api/modelApiFactory.js';
-import { copyLoraSyntax, sendLoraToWorkflow, buildLoraSyntax, showToast } from '../../utils/uiHelpers.js';
+import { copyLoraSyntax, sendLoraToWorkflow, buildLoraSyntax } from '../../utils/uiHelpers.js';
 import { showExcludeModal, showDeleteModal } from '../../utils/modalUtils.js';
 import { moveManager } from '../../managers/MoveManager.js';
 
@@ -27,16 +26,6 @@ export class LoraContextMenu extends BaseContextMenu {
         this.updateEnrichMenuItem(card);
     }
 
-    updateEnrichMenuItem(card) {
-        const enrichItem = this.menu?.querySelector('[data-action="enrich-hf-llm"]');
-        if (!enrichItem) return;
-        const hasHfUrl = !!card.dataset.hf_url;
-        enrichItem.classList.toggle('disabled', !hasHfUrl);
-        enrichItem.title = hasHfUrl
-            ? ''
-            : 'Link this model to a HuggingFace repo first (Link Model \u2192 Link to HuggingFace)';
-    }
-
     handleMenuAction(action, menuItem) {
         // First try to handle with common actions
         if (ModelContextMenuMixin.handleCommonMenuActions.call(this, action)) {
@@ -75,9 +64,6 @@ export class LoraContextMenu extends BaseContextMenu {
             case 'refresh-metadata':
                 getModelApiClient().refreshSingleModelMetadata(this.currentCard.dataset.filepath);
                 break;
-            case 'enrich-hf-llm':
-                this.enrichWithAgent(this.currentCard.dataset.filepath);
-                break;
             case 'exclude':
                 showExcludeModal(this.currentCard.dataset.filepath);
                 break;
@@ -87,68 +73,6 @@ export class LoraContextMenu extends BaseContextMenu {
         }
     }
 
-    async enrichWithAgent(filePath) {
-        const { agentManager } = await import('../../managers/AgentManager.js');
-
-        const configured = await agentManager.isLlmConfigured();
-        if (!configured) {
-            showToast('toast.agent.llmNotConfigured', {}, 'warning');
-            return;
-        }
-
-        agentManager.connect();
-
-        const progressUI = state.loadingManager.showEnhancedProgress(
-            'Enriching metadata with AI...'
-        );
-
-        function cleanupCallbacks() {
-            const pIdx = agentManager.progressCallbacks.indexOf(onProgress);
-            if (pIdx >= 0) agentManager.progressCallbacks.splice(pIdx, 1);
-            const cIdx = agentManager.completeCallbacks.indexOf(onComplete);
-            if (cIdx >= 0) agentManager.completeCallbacks.splice(cIdx, 1);
-            const eIdx = agentManager.errorCallbacks.indexOf(onError);
-            if (eIdx >= 0) agentManager.errorCallbacks.splice(eIdx, 1);
-        }
-
-        const onProgress = (data) => {
-            if (data.status === 'processing' && data.current_path && data.updated_data && Object.keys(data.updated_data).length > 0) {
-                if (state.virtualScroller?.updateSingleItem) {
-                    state.virtualScroller.updateSingleItem(data.current_path, data.updated_data);
-                }
-                const pct = data.total > 0 ? Math.floor((data.processed / data.total) * 100) : 0;
-                const name = data.current_path.split('/').pop();
-                progressUI.updateProgress(pct, name, `Processing ${name}`);
-            }
-        };
-        agentManager.onProgress(onProgress);
-
-        const onComplete = (data) => {
-            cleanupCallbacks();
-
-            if (data.status === 'completed') {
-                progressUI.complete(data.summary || 'Enrich complete');
-                showToast('toast.agent.enrichComplete', { summary: data.summary || 'Done' }, 'success');
-            }
-        };
-        agentManager.onComplete(onComplete);
-
-        const onError = (data) => {
-            cleanupCallbacks();
-            state.loadingManager.hide();
-            showToast('toast.agent.enrichFailed', { error: data.error || 'Unknown error' }, 'error');
-        };
-        agentManager.onError(onError);
-
-        try {
-            await agentManager.executeSkill('enrich_hf_metadata', [filePath]);
-        } catch (error) {
-            cleanupCallbacks();
-            state.loadingManager.hide();
-            showToast('toast.agent.enrichFailed', { error: error.message }, 'error');
-        }
-    }
-
     sendLoraToWorkflow(replaceMode) {
         const card = this.currentCard;
         const usageTips = JSON.parse(card.dataset.usage_tips || '{}');

static/js/components/ContextMenu/ModelContextMenuMixin.js

@@ -112,7 +112,8 @@ export const ModelContextMenuMixin = {
         const prefixMap = {
             lora: 'loras',
             checkpoint: 'checkpoints',
-            embedding: 'embeddings'
+            embedding: 'embeddings',
+            other: 'other'
         };
         return prefixMap[this.modelType] || 'loras';
     },
@@ -278,6 +279,79 @@ export const ModelContextMenuMixin = {
         setTimeout(() => urlInput.focus(), 50);
     },
 
+    // HF metadata enrichment (AI agent) methods
+    updateEnrichMenuItem(card) {
+        const enrichItem = this.menu?.querySelector('[data-action="enrich-hf-llm"]');
+        if (!enrichItem) return;
+        const hasHfUrl = !!card.dataset.hf_url;
+        enrichItem.classList.toggle('disabled', !hasHfUrl);
+        enrichItem.title = hasHfUrl
+            ? ''
+            : 'Link this model to a HuggingFace repo first (Link Model → Link to HuggingFace)';
+    },
+
+    async enrichWithAgent(filePath) {
+        const { agentManager } = await import('../../managers/AgentManager.js');
+
+        const configured = await agentManager.isLlmConfigured();
+        if (!configured) {
+            showToast('toast.agent.llmNotConfigured', {}, 'warning');
+            return;
+        }
+
+        agentManager.connect();
+
+        const progressUI = state.loadingManager.showEnhancedProgress(
+            'Enriching metadata with AI...'
+        );
+
+        function cleanupCallbacks() {
+            const pIdx = agentManager.progressCallbacks.indexOf(onProgress);
+            if (pIdx >= 0) agentManager.progressCallbacks.splice(pIdx, 1);
+            const cIdx = agentManager.completeCallbacks.indexOf(onComplete);
+            if (cIdx >= 0) agentManager.completeCallbacks.splice(cIdx, 1);
+            const eIdx = agentManager.errorCallbacks.indexOf(onError);
+            if (eIdx >= 0) agentManager.errorCallbacks.splice(eIdx, 1);
+        }
+
+        const onProgress = (data) => {
+            if (data.status === 'processing' && data.current_path && data.updated_data && Object.keys(data.updated_data).length > 0) {
+                if (state.virtualScroller?.updateSingleItem) {
+                    state.virtualScroller.updateSingleItem(data.current_path, data.updated_data);
+                }
+                const pct = data.total > 0 ? Math.floor((data.processed / data.total) * 100) : 0;
+                const name = data.current_path.split('/').pop();
+                progressUI.updateProgress(pct, name, `Processing ${name}`);
+            }
+        };
+        agentManager.onProgress(onProgress);
+
+        const onComplete = (data) => {
+            cleanupCallbacks();
+
+            if (data.status === 'completed') {
+                progressUI.complete(data.summary || 'Enrich complete');
+                showToast('toast.agent.enrichComplete', { summary: data.summary || 'Done' }, 'success');
+            }
+        };
+        agentManager.onComplete(onComplete);
+
+        const onError = (data) => {
+            cleanupCallbacks();
+            state.loadingManager.hide();
+            showToast('toast.agent.enrichFailed', { error: data.error || 'Unknown error' }, 'error');
+        };
+        agentManager.onError(onError);
+
+        try {
+            await agentManager.executeSkill('enrich_hf_metadata', [filePath]);
+        } catch (error) {
+            cleanupCallbacks();
+            state.loadingManager.hide();
+            showToast('toast.agent.enrichFailed', { error: error.message }, 'error');
+        }
+    },
+
     parseModelId(value) {
         if (value === undefined || value === null || value === '') {
             return null;
@@ -372,7 +446,10 @@ export const ModelContextMenuMixin = {
                 this.downloadExampleImages(true);
                 return true;
             case 'civitai':
-                if (this.currentCard.dataset.from_civitai === 'true') {
+                // Gate on actual CivitAI data (not the `from_civitai` flag) so
+                // that linking HuggingFace does not make the model look like it
+                // has no CivitAI info (#1094).
+                if (this.currentCard.dataset.has_civitai === 'true') {
                     if (this.currentCard.querySelector('.fa-globe')) {
                         this.currentCard.querySelector('.fa-globe').click();
                     } else {
@@ -388,6 +465,9 @@ export const ModelContextMenuMixin = {
             case 'link-hf':
                 this.showLinkHfModal();
                 return true;
+            case 'enrich-hf-llm':
+                this.enrichWithAgent(this.currentCard.dataset.filepath);
+                return true;
             case 'set-nsfw':
                 this.showNSFWLevelSelector(null, null, this.currentCard);
                 return true;

static/js/components/ContextMenu/OtherContextMenu.js

@@ -0,0 +1,72 @@
+import { BaseContextMenu } from './BaseContextMenu.js';
+import { ModelContextMenuMixin } from './ModelContextMenuMixin.js';
+import { getModelApiClient, resetAndReload } from '../../api/modelApiFactory.js';
+import { moveManager } from '../../managers/MoveManager.js';
+import { showDeleteModal, showExcludeModal } from '../../utils/modalUtils.js';
+
+export class OtherContextMenu extends BaseContextMenu {
+    constructor() {
+        super('otherContextMenu', '.model-card');
+        this.nsfwSelector = document.getElementById('nsfwLevelSelector');
+        this.modelType = 'other';
+        this.resetAndReload = resetAndReload;
+
+        this.initNSFWSelector();
+    }
+
+    // Implementation needed by the mixin
+    async saveModelMetadata(filePath, data) {
+        return getModelApiClient().saveModelMetadata(filePath, data);
+    }
+
+    showMenu(x, y, card) {
+        super.showMenu(x, y, card);
+        this.updateExcludeMenuItem();
+    }
+
+    handleMenuAction(action) {
+        // First try to handle with common actions
+        if (ModelContextMenuMixin.handleCommonMenuActions.call(this, action)) {
+            return;
+        }
+
+        const apiClient = getModelApiClient();
+
+        // Otherwise handle other-models-specific actions
+        switch(action) {
+            case 'details':
+                // Show model details
+                this.currentCard.click();
+                break;
+            case 'replace-preview':
+                // Add new action for replacing preview images
+                apiClient.replaceModelPreview(this.currentCard.dataset.filepath);
+                break;
+            case 'delete':
+                showDeleteModal(this.currentCard.dataset.filepath);
+                break;
+            case 'copyname':
+                // Copy model name
+                if (this.currentCard.querySelector('.fa-copy')) {
+                    this.currentCard.querySelector('.fa-copy').click();
+                }
+                break;
+            case 'refresh-metadata':
+                // Refresh metadata from CivitAI
+                apiClient.refreshSingleModelMetadata(this.currentCard.dataset.filepath);
+                break;
+            case 'move':
+                moveManager.showMoveModal(this.currentCard.dataset.filepath);
+                break;
+            case 'exclude':
+                showExcludeModal(this.currentCard.dataset.filepath);
+                break;
+            case 'restore':
+                this.restoreExcludedModel(this.currentCard.dataset.filepath);
+                break;
+        }
+    }
+}
+
+// Mix in shared methods
+Object.assign(OtherContextMenu.prototype, ModelContextMenuMixin);

static/js/components/ContextMenu/RecipeContextMenu.js

@@ -6,6 +6,8 @@ import { setSessionItem, removeSessionItem } from '../../utils/storageHelpers.js
 import { updateRecipeMetadata } from '../../api/recipeApi.js';
 import { state } from '../../state/index.js';
 import { moveManager } from '../../managers/MoveManager.js';
+import { rematchModalManager } from '../../managers/RematchModalManager.js';
+import { showRematchSummary } from '../RematchSummaryModal.js';
 import { probeExtension, delegateReimport, getCivitaiImageInfo } from '../../utils/extensionReimportBridge.js';
 
 export class RecipeContextMenu extends BaseContextMenu {
@@ -303,26 +305,36 @@ export class RecipeContextMenu extends BaseContextMenu {
         // Capture before any await: the menu's click handler nulls currentCard
         const filePath = this.currentCard?.dataset?.filepath;
 
+        // Collect options (relaxed matching) before starting anything; the
+        // run only begins when the user confirms the dialog.
+        rematchModalManager.showOptionsModal({
+            scope: 'single',
+            onConfirm: ({ relaxed }) => this._startRematchRecipe(recipeId, filePath, relaxed),
+        });
+    }
+
+    async _startRematchRecipe(recipeId, filePath, relaxed = false) {
         try {
             showToast('Rematching recipe to local models...', {}, 'info');
 
             const response = await fetch(`/api/lm/recipe/${recipeId}/rematch`, {
-                method: 'POST'
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({ relaxed: !!relaxed }),
             });
             const result = await response.json();
 
             if (result.success) {
                 const matchedEntries = result.matched_entries || result.rematched || 0;
                 const failures = result.errors || 0;
+                const unresolvedEntries = result.unresolved_entries || 0;
+                const l4Matches = Array.isArray(result.l4_matches) ? result.l4_matches : [];
+                // Complete no-op (nothing matched, nothing unresolved, no
+                // errors) keeps the lightweight toast; anything else opens
+                // the post-run summary modal.
+                const isNoop = matchedEntries === 0 && unresolvedEntries === 0 && failures === 0;
+
                 if (matchedEntries > 0) {
-                    const toastKey = failures > 0
-                        ? 'toast.recipes.rematchCompleteErrors'
-                        : 'toast.recipes.rematchComplete';
-                    showToast(
-                        toastKey,
-                        { rematched: matchedEntries, skipped: result.skipped || 0, total: 1, entries: matchedEntries, recipes: 1, failures },
-                        failures > 0 ? 'warning' : 'success'
-                    );
                     const detailResponse = await fetch(`/api/lm/recipe/${recipeId}`);
                     if (detailResponse.ok) {
                         const updatedRecipe = await detailResponse.json();
@@ -330,16 +342,22 @@ export class RecipeContextMenu extends BaseContextMenu {
                             state.virtualScroller.updateSingleItem(filePath, updatedRecipe);
                         }
                     }
-                } else if (result.unresolved_entries > 0) {
-                    // Entries existed but have no local model — expected for
-                    // models deleted from Civitai; informational, not an error.
-                    showToast(
-                        'toast.recipes.rematchUnmatched',
-                        { entries: result.unresolved_entries, recipes: 1, total: 1 },
-                        'info'
-                    );
-                } else {
+                }
+
+                if (isNoop) {
                     showToast('toast.recipes.rematchSkipped', { total: 1 }, 'info');
+                } else {
+                    showRematchSummary({
+                        scope: 'single',
+                        total: 1,
+                        matchedRecipes: result.matched_recipes || (matchedEntries > 0 ? 1 : 0),
+                        matchedEntries,
+                        unresolvedRecipes: result.unresolved_recipes || 0,
+                        unresolvedEntries,
+                        skipped: result.skipped || 0,
+                        errors: failures,
+                        l4Matches,
+                    });
                 }
             } else {
                 throw new Error(result.error || 'Rematch failed');

static/js/components/ContextMenu/index.js

@@ -2,6 +2,7 @@ export { LoraContextMenu } from './LoraContextMenu.js';
 export { RecipeContextMenu } from './RecipeContextMenu.js';
 export { CheckpointContextMenu } from './CheckpointContextMenu.js';
 export { EmbeddingContextMenu } from './EmbeddingContextMenu.js';
+export { OtherContextMenu } from './OtherContextMenu.js';
 export { GlobalContextMenu } from './GlobalContextMenu.js';
 export { ModelContextMenuMixin } from './ModelContextMenuMixin.js';
 
@@ -9,6 +10,7 @@ import { LoraContextMenu } from './LoraContextMenu.js';
 import { RecipeContextMenu } from './RecipeContextMenu.js';
 import { CheckpointContextMenu } from './CheckpointContextMenu.js';
 import { EmbeddingContextMenu } from './EmbeddingContextMenu.js';
+import { OtherContextMenu } from './OtherContextMenu.js';
 import { GlobalContextMenu } from './GlobalContextMenu.js';
 
 // Factory method to create page-specific context menu instances
@@ -22,6 +24,8 @@ export function createPageContextMenu(pageType) {
             return new CheckpointContextMenu();
         case 'embeddings':
             return new EmbeddingContextMenu();
+        case 'other':
+            return new OtherContextMenu();
         default:
             return null;
     }

static/js/components/Header.js

@@ -32,6 +32,7 @@ export class HeaderManager {
       if (path.includes('/loras/recipes')) return 'recipes';
       if (path.includes('/checkpoints')) return 'checkpoints';
       if (path.includes('/embeddings')) return 'embeddings';
+      if (path.includes('/other')) return 'other';
       if (path.includes('/statistics')) return 'statistics';
       if (path.includes('/loras')) return 'loras';
       return 'unknown';
@@ -49,6 +50,18 @@ export class HeaderManager {
     initializeCommonElements() {
       this.initializeThemePopover();
 
+      // Header icon buttons are divs with role="button"; make Enter/Space activate them
+      const headerControls = document.getElementById('headerControls');
+      if (headerControls) {
+        headerControls.addEventListener('keydown', (e) => {
+          if (e.key !== 'Enter' && e.key !== ' ') return;
+          const target = e.target.closest('[role="button"]');
+          if (!target || !headerControls.contains(target)) return;
+          e.preventDefault();
+          target.click();
+        });
+      }
+
       const settingsToggle = document.querySelector('.settings-toggle');
       if (settingsToggle) {
         settingsToggle.addEventListener('click', () => {

static/js/components/RecipeModal.js

@@ -1,5 +1,5 @@
 // Recipe Modal Component
-import { showToast, copyToClipboard, sendLoraToWorkflow, sendModelPathToWorkflow, stripLoraTags, sendPromptToWorkflow, sendGenParamsToWorkflow } from '../utils/uiHelpers.js';
+import { showToast, copyToClipboard, sendLoraToWorkflow, sendModelPathToWorkflow, stripLoraTags, sendPromptToWorkflow, sendGenParamsToWorkflow, isUnresolvableDownloadError } from '../utils/uiHelpers.js';
 import { isModelWeightFile } from '../utils/modelFileTypes.js';
 import { buildCivitaiUrl } from '../utils/civitaiUtils.js';
 import { translate } from '../utils/i18nHelpers.js';
@@ -1078,8 +1078,9 @@ class RecipeModal {
 
                 // Mirror the checkpoint "broken" rule: deleted, an
                 // unresolvable hash, or a name-only remnant with no CivitAI
-                // identifiers at all cannot be fixed by downloading —
-                // reconnecting a local LoRA is the only remediation.
+                // identifiers at all cannot be fixed by downloading, so no
+                // download button is offered. Reconnect is always available
+                // for missing entries (see renderLoraItemActions).
                 const needsReconnect = !existsLocally
                     && (isDeleted || lora.hashInvalid || !this.canDownloadLora(lora));
 
@@ -1180,7 +1181,7 @@ class RecipeModal {
                             </div>
                             ${actionsRow}
                         </div>
-                        ${needsReconnect ? `
+                        ${!existsLocally ? `
                         <div class="lora-reconnect-container" data-lora-index="${loraIndex}">
                             <div class="reconnect-instructions">
                                 <p>${escapeHtml(translate('recipes.resources.reconnectInstructions', {}, 'Enter LoRA syntax or name to reconnect:'))}</p>
@@ -2853,11 +2854,7 @@ class RecipeModal {
      * the model cannot be resolved — never for transient transport errors.
      */
     _isUnresolvableDownloadError(message) {
-        if (!message) {
-            return false;
-        }
-        const text = String(message).toLowerCase();
-        return /(not found|no longer available|deleted|removed|404|410|gone)/.test(text);
+        return isUnresolvableDownloadError(message);
     }
 
     getResourceCivitaiUrl(resource) {
@@ -2915,19 +2912,9 @@ class RecipeModal {
         }
 
         const controls = [];
-        if (needsReconnect) {
-            const reconnectLabel = translate('recipes.resources.reconnect', {}, 'Reconnect');
-            const reconnectTooltip = translate('recipes.resources.reconnectTooltip', {}, 'Reconnect with a local LoRA');
-            controls.push(`
-                <button type="button" class="resource-action ghost compact lora-reconnect" data-lora-index="${loraIndex}"
-                    title="${escapeHtml(reconnectTooltip)}" aria-label="${escapeHtml(reconnectTooltip)}">
-                    <i class="fas fa-link" aria-hidden="true"></i>
-                    <span>${escapeHtml(reconnectLabel)}</span>
-                </button>
-            `);
-        } else {
+        if (!needsReconnect) {
             // needsReconnect already implies canDownloadLora() here, so the
-            // download action is unconditional.
+            // download action is unconditional in this branch.
             const downloadLabel = translate('recipes.resources.download', {}, 'Download');
             const downloadTooltip = translate('recipes.resources.downloadLoraTooltip', {}, 'Download this LoRA');
             controls.push(`
@@ -2938,6 +2925,18 @@ class RecipeModal {
                 </button>
             `);
         }
+        // Reconnect is always offered for missing entries — when the LoRA
+        // already exists locally under a different hash, downloading first
+        // just to flip the button would be a waste.
+        const reconnectLabel = translate('recipes.resources.reconnect', {}, 'Reconnect');
+        const reconnectTooltip = translate('recipes.resources.reconnectTooltip', {}, 'Reconnect with a local LoRA');
+        controls.push(`
+            <button type="button" class="resource-action ghost compact lora-reconnect" data-lora-index="${loraIndex}"
+                title="${escapeHtml(reconnectTooltip)}" aria-label="${escapeHtml(reconnectTooltip)}">
+                <i class="fas fa-link" aria-hidden="true"></i>
+                <span>${escapeHtml(reconnectLabel)}</span>
+            </button>
+        `);
 
         return `<div class="recipe-lora-actions">${controls.join('')}</div>`;
     }

static/js/components/RematchSummaryModal.js

@@ -0,0 +1,338 @@
+import { translate } from '../utils/i18nHelpers.js';
+import { showToast } from '../utils/uiHelpers.js';
+
+/**
+ * Escape HTML entities in a string to prevent injection when interpolating
+ * into innerHTML (same approach as DownloadBatchSummaryModal).
+ * @param {string} str - The string to escape
+ * @returns {string} - The escaped string
+ */
+function _escapeHtml(str) {
+    if (str === null || str === undefined) return '';
+    const div = document.createElement('div');
+    div.textContent = String(str);
+    return div.innerHTML.replace(/"/g, '"').replace(/'/g, ''');
+}
+
+/**
+ * Resolve the 3-state summary header (mirrors the batch download/import
+ * summary semantics).
+ *
+ * - error: nothing matched and at least one recipe errored
+ * - warning: errors, unresolved entries, filename-level (L4) matches to
+ *   review, or a cancelled run
+ * - success: otherwise
+ */
+function _resolveHeader({ matchedEntries, errors, unresolvedEntries, l4Count, cancelled }) {
+    if (matchedEntries === 0 && errors > 0) {
+        return {
+            state: 'error',
+            icon: 'fa-times-circle',
+            text: translate('modals.rematchSummary.failed', {}, 'Rematch failed'),
+        };
+    }
+    if (errors > 0 || unresolvedEntries > 0 || l4Count > 0 || cancelled) {
+        return {
+            state: 'warning',
+            icon: 'fa-exclamation-circle',
+            text: translate('modals.rematchSummary.completedWithWarnings', {}, 'Rematch completed — review recommended'),
+        };
+    }
+    return {
+        state: 'success',
+        icon: 'fa-check-circle',
+        text: translate('modals.rematchSummary.successMessage', { entries: matchedEntries }, `Matched ${matchedEntries} entries`),
+    };
+}
+
+/**
+ * Build a plain-text report of the rematch run. `undoneIndexes` carries the
+ * L4 rows undone so far, so the report reflects the undo status at copy time.
+ */
+function _buildReportText({ scope, cancelled, total, matchedRecipes, matchedEntries, unresolvedRecipes, unresolvedEntries, skipped, errors, l4Matches, undoneIndexes }) {
+    const scopeFallbacks = {
+        global: 'All recipes',
+        bulk: 'Selected recipes',
+        single: 'Single recipe',
+    };
+    const scopeLabel = translate(
+        `modals.rematchSummary.scope_${scope}`,
+        {},
+        scopeFallbacks[scope] || scope
+    );
+    const lines = [
+        '=== Recipe Rematch Report ===',
+        `Date: ${new Date().toLocaleString()}`,
+        `Scope: ${scopeLabel}`,
+        `Cancelled: ${cancelled ? 'yes' : 'no'}`,
+        `Total recipes: ${total}`,
+        `Matched recipes: ${matchedRecipes}`,
+        `Matched entries: ${matchedEntries}`,
+        `Needs review (filename matches): ${l4Matches.length}`,
+        `Unresolved entries: ${unresolvedEntries} (in ${unresolvedRecipes} recipes)`,
+        `Skipped: ${skipped}`,
+        `Errors: ${errors}`,
+        '',
+    ];
+    if (l4Matches.length > 0) {
+        lines.push('--- Filename matches (L4) ---');
+        l4Matches.forEach((match, i) => {
+            const undone = undoneIndexes.has(i) ? ' [undone]' : '';
+            lines.push(`${i + 1}. [${match.recipe_id}] ${match.entry} -> ${match.file_name}${undone}`);
+        });
+        lines.push('');
+    }
+    lines.push('====================');
+    return lines.join('\n');
+}
+
+/**
+ * Handle a successful clipboard write: confirm via toast and briefly swap the
+ * trigger button to a "Copied!" state (mirrors the batch summary modal).
+ */
+function _onCopyReportSuccess(btn) {
+    showToast('toast.api.copiedToClipboard', {}, 'success');
+    if (btn) {
+        const origHTML = btn.innerHTML;
+        btn.innerHTML = '<i class="fas fa-check"></i> Copied!';
+        setTimeout(() => { btn.innerHTML = origHTML; }, 2000);
+    }
+}
+
+/**
+ * Fallback for environments without the async Clipboard API (e.g. insecure
+ * contexts over LAN http): copy via a hidden textarea and execCommand.
+ */
+function _copyReportWithExecCommand(text) {
+    const textarea = document.createElement('textarea');
+    textarea.value = text;
+    document.body.appendChild(textarea);
+    textarea.select();
+    document.execCommand('copy');
+    document.body.removeChild(textarea);
+    showToast('toast.api.copiedToClipboard', {}, 'success');
+}
+
+function _copyReport(btn, reportArgs) {
+    const text = _buildReportText(reportArgs);
+    if (navigator.clipboard && typeof navigator.clipboard.writeText === 'function') {
+        navigator.clipboard.writeText(text)
+            .then(() => _onCopyReportSuccess(btn))
+            .catch(() => _copyReportWithExecCommand(text));
+    } else {
+        _copyReportWithExecCommand(text);
+    }
+}
+
+/**
+ * Undo a single L4 match via the existing restore endpoints (moved from
+ * RematchModalManager). Checkpoint restore needs only recipe_id; lora
+ * restore additionally takes lora_index.
+ */
+async function _undoMatch(match) {
+    const isCheckpoint = match.type === 'checkpoint';
+    const body = isCheckpoint
+        ? { recipe_id: match.recipe_id }
+        : { recipe_id: match.recipe_id, lora_index: match.lora_index };
+    const response = await fetch(
+        isCheckpoint
+            ? '/api/lm/recipe/checkpoint/restore'
+            : '/api/lm/recipe/lora/restore',
+        {
+            method: 'POST',
+            headers: { 'Content-Type': 'application/json' },
+            body: JSON.stringify(body),
+        }
+    );
+    const result = await response.json();
+    if (!response.ok || !result.success) {
+        throw new Error(result.error || 'Restore failed');
+    }
+}
+
+/**
+ * Show the post-run rematch summary modal. Mirrors the batch download
+ * summary lifecycle: the modal element is appended directly to
+ * document.body and removed on close; it is not registered with
+ * ModalManager.
+ *
+ * @param {Object} options
+ * @param {'global'|'bulk'|'single'} options.scope - Which entry point ran
+ * @param {boolean} options.cancelled - Whether the run was cancelled
+ * @param {number} options.total - Recipes scanned
+ * @param {number} options.matchedRecipes - Recipes updated
+ * @param {number} options.matchedEntries - Entries reconnected
+ * @param {number} options.unresolvedRecipes - Recipes with unresolved entries
+ * @param {number} options.unresolvedEntries - Candidate entries with no local match
+ * @param {number} options.skipped - Recipes left untouched
+ * @param {number} options.errors - Per-recipe errors
+ * @param {Array} options.l4Matches - Filename-level matches for review/undo
+ *   ({ recipe_id, type, entry, file_name, lora_index? })
+ */
+export function showRematchSummary({
+    scope = 'global',
+    cancelled = false,
+    total = 0,
+    matchedRecipes = 0,
+    matchedEntries = 0,
+    unresolvedRecipes = 0,
+    unresolvedEntries = 0,
+    skipped = 0,
+    errors = 0,
+    l4Matches = [],
+} = {}) {
+    const matches = Array.isArray(l4Matches) ? l4Matches : [];
+    const undoneIndexes = new Set();
+    const header = _resolveHeader({
+        matchedEntries,
+        errors,
+        unresolvedEntries,
+        l4Count: matches.length,
+        cancelled,
+    });
+
+    const matchRows = matches.map((match, i) => `
+            <tr data-l4-index="${i}">
+                <td class="failure-index">${i + 1}</td>
+                <td class="failure-name" title="${_escapeHtml(match.recipe_id)}">${_escapeHtml(match.recipe_id)}</td>
+                <td class="failure-name" title="${_escapeHtml(match.entry)}">${_escapeHtml(match.entry)}</td>
+                <td class="failure-name" title="${_escapeHtml(match.file_name)}">${_escapeHtml(match.file_name)}</td>
+                <td class="rematch-undo-cell">
+                    <button class="secondary-btn rematch-undo-btn" data-action="undo-match" data-index="${i}">
+                        ${translate('modals.rematchResults.undo', {}, 'Undo')}
+                    </button>
+                </td>
+            </tr>`).join('');
+
+    const modalHtml = `
+        <div id="rematchSummaryModal" class="modal" style="display: block;">
+            <div class="modal-content rematch-summary-modal">
+                <button class="close" data-action="close-modal">&times;</button>
+
+                <h2>${translate('modals.rematchSummary.title', {}, 'Rematch Summary')}</h2>
+
+                <div class="summary-header ${header.state}">
+                    <i class="fas ${header.icon}"></i>
+                    <span class="summary-title">${header.text}</span>
+                    <span class="summary-hint">${matchedRecipes}/${total}</span>
+                </div>
+                ${cancelled ? `
+                <p class="rematch-cancelled-note">
+                    <i class="fas fa-info-circle"></i>
+                    ${translate('modals.rematchSummary.cancelledNote', {}, 'Run cancelled before completion — counts are partial.')}
+                </p>` : ''}
+
+                <div class="refresh-summary-stats">
+                    <div class="stat-card stat-card-success">
+                        <div class="stat-card-body">
+                            <span class="stat-card-label">${translate('modals.rematchSummary.statMatched', {}, 'Matched entries')}</span>
+                            <span class="stat-card-value">${matchedEntries}</span>
+                        </div>
+                    </div>
+                    <div class="stat-card stat-card-skipped">
+                        <div class="stat-card-body">
+                            <span class="stat-card-label">${translate('modals.rematchSummary.statReview', {}, 'Needs review')}</span>
+                            <span class="stat-card-value">${matches.length}</span>
+                        </div>
+                    </div>
+                    <div class="stat-card stat-card-total">
+                        <div class="stat-card-body">
+                            <span class="stat-card-label">${translate('modals.rematchSummary.statUnresolved', {}, 'Unresolved')}</span>
+                            <span class="stat-card-value">${unresolvedEntries}</span>
+                        </div>
+                    </div>
+                    <div class="stat-card stat-card-failure">
+                        <div class="stat-card-body">
+                            <span class="stat-card-label">${translate('modals.rematchSummary.statErrors', {}, 'Errors')}</span>
+                            <span class="stat-card-value">${errors}</span>
+                        </div>
+                    </div>
+                </div>
+
+                ${matches.length > 0 ? `
+                <div class="refresh-failures-section rematch-review-section">
+                    <h4><i class="fas fa-exclamation-triangle"></i> ${translate('modals.rematchSummary.reviewSection', { count: matches.length }, `Filename matches to review (${matches.length})`)}</h4>
+                    <div class="failure-table-wrapper">
+                        <table class="failure-table">
+                            <thead>
+                                <tr>
+                                    <th>#</th>
+                                    <th>${translate('modals.rematchSummary.columnRecipe', {}, 'Recipe')}</th>
+                                    <th>${translate('modals.rematchSummary.columnEntry', {}, 'Entry')}</th>
+                                    <th>${translate('modals.rematchSummary.columnFile', {}, 'Matched file')}</th>
+                                    <th>${translate('modals.rematchSummary.columnUndo', {}, 'Undo')}</th>
+                                </tr>
+                            </thead>
+                            <tbody>${matchRows}</tbody>
+                        </table>
+                    </div>
+                </div>
+                ` : ''}
+
+                <div class="modal-actions">
+                    <button class="secondary-btn" data-action="copy-report"><i class="fas fa-copy"></i> ${translate('modals.rematchSummary.copyReport', {}, 'Copy Report')}</button>
+                    <button class="cancel-btn" data-action="close-modal">${translate('modals.rematchSummary.close', {}, 'Close')}</button>
+                </div>
+            </div>
+        </div>
+    `;
+
+    const existing = document.getElementById('rematchSummaryModal');
+    if (existing) existing.remove();
+
+    const container = document.createElement('div');
+    container.innerHTML = modalHtml;
+    const modal = container.firstElementChild;
+    document.body.appendChild(modal);
+
+    const reportArgs = {
+        scope,
+        cancelled,
+        total,
+        matchedRecipes,
+        matchedEntries,
+        unresolvedRecipes,
+        unresolvedEntries,
+        skipped,
+        errors,
+        l4Matches: matches,
+        undoneIndexes,
+    };
+
+    modal.addEventListener('click', async (e) => {
+        const actionEl = e.target.closest('[data-action]');
+        const action = actionEl?.dataset.action;
+        if (!action) return;
+        e.preventDefault();
+
+        switch (action) {
+            case 'close-modal':
+                modal.remove();
+                break;
+            case 'copy-report':
+                _copyReport(actionEl, reportArgs);
+                break;
+            case 'undo-match': {
+                const index = Number(actionEl.dataset.index);
+                const match = matches[index];
+                if (!match || actionEl.disabled) break;
+                const row = modal.querySelector(`tr[data-l4-index="${index}"]`);
+                try {
+                    await _undoMatch(match);
+                    undoneIndexes.add(index);
+                    row?.classList.add('undone');
+                    actionEl.disabled = true;
+                    actionEl.textContent = translate('modals.rematchResults.undone', {}, 'Undone');
+                } catch (error) {
+                    console.error('Failed to undo rematch match:', error);
+                    showToast(
+                        'modals.rematchResults.undoFailed',
+                        { message: error.message },
+                        'error'
+                    );
+                }
+                break;
+            }
+        }
+    });
+}

static/js/components/SidebarManager.js

@@ -11,6 +11,13 @@ import { performFolderUpdateCheck } from '../utils/updateCheckHelpers.js';
 import { escapeHtml, escapeAttribute } from './shared/utils.js';
 import { MODEL_CARD_DRAG_MIME_TYPE } from '../utils/constants.js';
 
+// Pages whose folder sidebar starts hidden. "other" downloads default to a flat
+// layout (no subfolders are created), so on a fresh library the tree is empty
+// there and the sidebar would only consume horizontal space. The preference is
+// still persisted per page once the user toggles it, and the edge indicator
+// makes the hidden sidebar discoverable/recoverable.
+const SIDEBAR_DEFAULT_HIDDEN_PAGES = new Set(['other']);
+
 export class SidebarManager {
     constructor() {
         this.pageControls = null;
@@ -1126,6 +1133,7 @@ export class SidebarManager {
             recipes: 'Recipes',
             checkpoints: 'Checkpoints',
             embeddings: 'Embeddings',
+            other: 'Other Models',
         };
         return names[this.pageType] || this.pageType;
     }
@@ -1784,7 +1792,10 @@ export class SidebarManager {
         const expandedPaths = getStorageItem(`${this.pageType}_expandedNodes`, []);
         const displayMode = getStorageItem(`${this.pageType}_displayMode`, 'tree'); // 'tree' or 'list', default to 'tree'
         const recursiveSearchEnabled = getStorageItem(`${this.pageType}_recursiveSearch`, true);
-        this.isDisabledByPage = getStorageItem(`${this.pageType}_sidebarDisabled`, false);
+        this.isDisabledByPage = getStorageItem(
+            `${this.pageType}_sidebarDisabled`,
+            SIDEBAR_DEFAULT_HIDDEN_PAGES.has(this.pageType)
+        );
 
         this.expandedNodes = new Set(expandedPaths);
         this.displayMode = displayMode;
@@ -1804,7 +1815,7 @@ export class SidebarManager {
     _migrateOldSettings() {
         if (getStorageItem('_sidebar_migration_done')) return;
 
-        const PAGES = ['loras', 'recipes', 'checkpoints', 'embeddings'];
+        const PAGES = ['loras', 'recipes', 'checkpoints', 'embeddings', 'other'];
 
         // 1. Migrate global hide setting to per-page
         if (state?.global?.settings?.show_folder_sidebar === false) {

static/js/components/controls/OtherControls.js

@@ -0,0 +1,66 @@
+// OtherControls.js - Specific implementation for the Other Models page
+import { PageControls } from './PageControls.js';
+import { getModelApiClient, resetAndReload } from '../../api/modelApiFactory.js';
+import { showToast } from '../../utils/uiHelpers.js';
+import { downloadManager } from '../../managers/DownloadManager.js';
+
+/**
+ * OtherControls class - Extends PageControls for the Other Models page
+ * (VAE, upscalers, text encoders, CLIP vision, ControlNet, ...)
+ */
+export class OtherControls extends PageControls {
+    constructor() {
+        // Initialize with 'other' page type
+        super('other');
+
+        // Register API methods specific to the Other Models page
+        this.registerOtherAPI();
+    }
+
+    /**
+     * Register Other-models-specific API methods
+     */
+    registerOtherAPI() {
+        const otherAPI = {
+            // Core API functions
+            loadMoreModels: async (resetPage = false, updateFolders = false) => {
+                return await getModelApiClient().loadMoreWithVirtualScroll(resetPage, updateFolders);
+            },
+
+            resetAndReload: async (updateFolders = false) => {
+                return await resetAndReload(updateFolders);
+            },
+
+            refreshModels: async (fullRebuild = false) => {
+                return await getModelApiClient().refreshModels(fullRebuild);
+            },
+
+            // Add fetch from Civitai functionality for other models
+            fetchFromCivitai: async () => {
+                return await getModelApiClient().fetchCivitaiMetadata();
+            },
+
+            // Add show download modal functionality
+            showDownloadModal: () => {
+                downloadManager.showDownloadModal();
+            },
+
+            toggleBulkMode: () => {
+                if (window.bulkManager) {
+                    window.bulkManager.toggleBulkMode();
+                } else {
+                    console.error('Bulk manager not available');
+                }
+            },
+
+            // No clearCustomFilter implementation is needed for other models
+            // as custom filters are currently only used for LoRAs
+            clearCustomFilter: async () => {
+                showToast('toast.filters.noCustomFilterToClear', {}, 'info');
+            }
+        };
+
+        // Register the API
+        this.registerAPI(otherAPI);
+    }
+}

static/js/components/controls/index.js

@@ -3,13 +3,14 @@ import { PageControls } from './PageControls.js';
 import { LorasControls } from './LorasControls.js';
 import { CheckpointsControls } from './CheckpointsControls.js';
 import { EmbeddingsControls } from './EmbeddingsControls.js';
+import { OtherControls } from './OtherControls.js';
 
 // Export the classes
-export { PageControls, LorasControls, CheckpointsControls, EmbeddingsControls };
+export { PageControls, LorasControls, CheckpointsControls, EmbeddingsControls, OtherControls };
 
 /**
  * Factory function to create the appropriate controls based on page type
- * @param {string} pageType - The type of page ('loras', 'checkpoints', or 'embeddings')
+ * @param {string} pageType - The type of page ('loras', 'checkpoints', 'embeddings', or 'other')
  * @returns {PageControls} - The appropriate controls instance
  */
 export function createPageControls(pageType) {
@@ -19,8 +20,10 @@ export function createPageControls(pageType) {
         return new CheckpointsControls();
     } else if (pageType === 'embeddings') {
         return new EmbeddingsControls();
+    } else if (pageType === 'other') {
+        return new OtherControls();
     } else {
         console.error(`Unknown page type: ${pageType}`);
         return null;
     }
-}
+}

static/js/components/initialization.js

@@ -58,6 +58,8 @@ class InitializationManager {
             this.pageType = 'recipes';
         } else if (path.includes('/checkpoints')) {
             this.pageType = 'checkpoints';
+        } else if (path.includes('/other')) {
+            this.pageType = 'other';
         } else if (path.includes('/loras')) {
             this.pageType = 'loras';
         } else if (path.includes('/embeddings')) {
@@ -221,6 +223,7 @@ class InitializationManager {
                 'lora': 'loras',
                 'checkpoint': 'checkpoints',
                 'embedding': 'embeddings',
+                'other': 'other',
                 'recipe': 'recipes'
             };
             

static/js/components/shared/ModelCard.js

@@ -1,6 +1,7 @@
 import { showToast, openCivitai, openHuggingFace, copyToClipboard, copyLoraSyntax, sendLoraToWorkflow, sendEmbeddingToWorkflow, openExampleImagesFolder, buildLoraSyntax, sendModelPathToWorkflow } from '../../utils/uiHelpers.js';
 import { state, getCurrentPageState } from '../../state/index.js';
 import { showModelModal } from './ModelModal.js';
+import { hasCivitaiSource } from './utils.js';
 import { bulkManager } from '../../managers/BulkManager.js';
 import { modalManager } from '../../managers/ModalManager.js';
 import { NSFW_LEVELS, getBaseModelAbbreviation, getSubTypeAbbreviation, getMatureBlurThreshold, MODEL_SUBTYPE_DISPLAY_NAMES, MODEL_CARD_DRAG_MIME_TYPE } from '../../utils/constants.js';
@@ -63,7 +64,10 @@ function handleModelCardEvent_internal(event, modelType) {
 
     if (event.target.closest('.fa-globe')) {
         event.stopPropagation();
-        if (card.dataset.from_civitai === 'true') {
+        // CivitAI wins when the model actually has CivitAI data; otherwise fall
+        // back to HuggingFace. Relying on `from_civitai` here made the two
+        // sources mutually exclusive whenever one of them was (re)linked (#1094).
+        if (card.dataset.has_civitai === 'true') {
             openCivitai(card.dataset.filepath);
         } else if (card.dataset.hf_url) {
             openHuggingFace(card.dataset.hf_url);
@@ -250,6 +254,11 @@ function handleCopyAction(card, modelType) {
         const embeddingCode = folder ? `embedding:${folder}/${name}` : `embedding:${name}`;
         const message = translate('modelCard.actions.embeddingNameCopied', {}, 'Embedding syntax copied');
         copyToClipboard(embeddingCode, message);
+    } else {
+        // Other model types (VAE, upscalers, ...) - copy the file name
+        const fileName = card.dataset.file_name;
+        const message = translate('modelCard.actions.modelNameCopied', {}, 'Model name copied');
+        copyToClipboard(fileName, message);
     }
 }
 
@@ -473,6 +482,9 @@ export function createModelCard(model, modelType) {
     card.dataset.modified = model.modified;
     card.dataset.file_size = model.file_size;
     card.dataset.from_civitai = model.from_civitai;
+    // Independent of `from_civitai`: a model can have both CivitAI data and an
+    // HF link, and the card globe must keep pointing at CivitAI when it does.
+    card.dataset.has_civitai = hasCivitaiSource(model.civitai) ? 'true' : 'false';
     card.dataset.usage_count = String(model.usage_count);
     card.dataset.notes = model.notes || '';
     card.dataset.base_model = model.base_model || 'Unknown';
@@ -595,12 +607,13 @@ export function createModelCard(model, modelType) {
     const favoriteTitle = isFavorite ?
         translate('modelCard.actions.removeFromFavorites', {}, 'Remove from favorites') :
         translate('modelCard.actions.addToFavorites', {}, 'Add to favorites');
-    const globeTitle = model.from_civitai ?
+    const hasCivitai = hasCivitaiSource(model.civitai);
+    const globeTitle = hasCivitai ?
         translate('modelCard.actions.viewOnCivitai', {}, 'View on Civitai') :
         model.hf_url ?
             translate('modelCard.actions.viewOnHuggingFace', {}, 'View on Hugging Face') :
             translate('modelCard.actions.notAvailableFromCivitai', {}, 'Not available from Civitai');
-    const globeEnabled = model.from_civitai || !!model.hf_url;
+    const globeEnabled = hasCivitai || !!model.hf_url;
     let sendTitle;
     let copyTitle;
     if (modelType === MODEL_TYPES.LORA) {

static/js/components/shared/ModelModal.js

@@ -14,7 +14,7 @@ import {
 } from './ModelMetadata.js';
 import { setupTagEditMode } from './ModelTags.js';
 import { getModelApiClient } from '../../api/modelApiFactory.js';
-import { renderCompactTags, setupTagTooltip, formatFileSize, escapeAttribute, escapeHtml } from './utils.js';
+import { renderCompactTags, setupTagTooltip, formatFileSize, escapeAttribute, escapeHtml, hasCivitaiSource } from './utils.js';
 import { renderTriggerWords, setupTriggerWordsEditMode } from './TriggerWords.js';
 import { parsePresets, renderPresetTags } from './PresetTags.js';
 import { initVersionsTab } from './ModelVersionsTab.js';
@@ -389,7 +389,11 @@ export async function showModelModal(model, modelType) {
     const licenseIcons = useNewIcons
         ? renderNewLicenseIcons(modelWithFullData)
         : renderLicenseIcons(modelWithFullData);
-    const viewOnCivitaiAction = modelWithFullData.from_civitai ? `
+    // Gate the CivitAI link on actual CivitAI data, not the `from_civitai`
+    // provenance flag: a model can be linked to HuggingFace and to CivitAI at
+    // the same time, and both links must coexist (#1094).
+    const hasCivitai = hasCivitaiSource(modelWithFullData.civitai);
+    const viewOnCivitaiAction = hasCivitai ? `
 <div class="civitai-view" title="${translate('modals.model.actions.viewOnCivitai', {}, 'View on Civitai')}" data-action="view-civitai" data-filepath="${escapedFilePathAttr}">
     <i class="fas fa-globe"></i> ${translate('modals.model.actions.viewOnCivitaiText', {}, 'View on Civitai')}
 </div>`.trim() : '';

static/js/components/shared/ModelVersionsTab.js

@@ -1390,8 +1390,22 @@ export function initVersionsTab({
 
         try {
             const client = ensureClient();
-            const rootsData = await client.fetchModelRoots();
-            const roots = rootsData?.roots;
+            // On the checkpoints page a diffusion model lives under the unet
+            // roots, so both root sets are needed to locate the current file.
+            let roots;
+            if (modelType === 'checkpoints') {
+                const [checkpointRoots, unetRoots] = await Promise.all([
+                    client.fetchModelRoots(),
+                    client.fetchModelRoots('diffusion_model'),
+                ]);
+                roots = [
+                    ...(checkpointRoots?.roots || []),
+                    ...(unetRoots?.roots || []),
+                ];
+            } else {
+                const rootsData = await client.fetchModelRoots();
+                roots = rootsData?.roots;
+            }
             if (!Array.isArray(roots) || roots.length === 0) {
                 return null;
             }

static/js/components/shared/utils.js

@@ -36,6 +36,24 @@ export function formatFileSize(bytes) {
     return `${size.toFixed(1)} ${units[unitIndex]}`;
 }
 
+/**
+ * Whether a model has usable CivitAI metadata to link to.
+ *
+ * CivitAI links must be gated on the presence of actual CivitAI data rather
+ * than the `from_civitai` provenance flag: linking a model to HuggingFace used
+ * to flip `from_civitai` to false, which hid the CivitAI link even though the
+ * model still had CivitAI metadata. See issue #1094.
+ *
+ * @param {Object} [civitaiData] - The model's `civitai` payload
+ * @returns {boolean} True when a CivitAI model/version id is available
+ */
+export function hasCivitaiSource(civitaiData) {
+    if (!civitaiData || typeof civitaiData !== 'object') return false;
+    return Boolean(
+        civitaiData.modelId ?? civitaiData.model_id ?? civitaiData.id
+    );
+}
+
 /**
  * Render compact tags
  * @param {Array} tags - Array of tags

static/js/core.js

@@ -7,6 +7,7 @@ import { HeaderManager } from './components/Header.js';
 import { settingsManager } from './managers/SettingsManager.js';
 import { moveManager } from './managers/MoveManager.js';
 import { bulkManager } from './managers/BulkManager.js';
+import { rematchModalManager } from './managers/RematchModalManager.js';
 import { ExampleImagesManager } from './managers/ExampleImagesManager.js';
 import { helpManager } from './managers/HelpManager.js';
 import { doctorManager } from './managers/DoctorManager.js';
@@ -68,6 +69,7 @@ export class AppCore {
         window.doctorManager = doctorManager;
         window.moveManager = moveManager;
         window.bulkManager = bulkManager;
+        window.rematchModalManager = rematchModalManager;
         
         // Initialize UI components
         window.headerManager = new HeaderManager();
@@ -114,7 +116,7 @@ export class AppCore {
     initializePageFeatures() {
         const pageType = this.getPageType();
         
-        if (['loras', 'recipes', 'checkpoints', 'embeddings'].includes(pageType)) {
+        if (['loras', 'recipes', 'checkpoints', 'embeddings', 'other'].includes(pageType)) {
             this.initializeContextMenus(pageType);
             initializeInfiniteScroll(pageType);
         }

static/js/managers/BannerService.js

@@ -6,9 +6,11 @@ import {
 import { translate } from '../utils/i18nHelpers.js';
 import { state } from '../state/index.js';
 import { getModelApiClient } from '../api/modelApiFactory.js';
+import { enableOtherModels, openOtherModelsSettings } from '../utils/otherModels.js';
 
 const COMMUNITY_SUPPORT_BANNER_ID = 'community-support';
 const CACHE_HEALTH_BANNER_ID = 'cache-health-warning';
+const OTHER_MODELS_BANNER_ID = 'other-models-announcement';
 const COMMUNITY_SUPPORT_BANNER_DELAY_MS = 5 * 24 * 60 * 60 * 1000; // 5 days
 const COMMUNITY_SUPPORT_FIRST_SEEN_AT_KEY = 'community_support_banner_first_seen_at';
 const COMMUNITY_SUPPORT_VERSION_KEY = 'community_support_banner_state_version';
@@ -80,6 +82,7 @@ class BannerService {
         });
 
         this.prepareCommunitySupportBanner();
+        this.prepareOtherModelsBanner();
 
         await this.showActiveBanners();
         this.initialized = true;
@@ -424,12 +427,13 @@ class BannerService {
 
     /**
      * Get the current page type from the URL
-     * @returns {string} Page type (loras, checkpoints, embeddings, recipes)
+     * @returns {string} Page type (loras, checkpoints, embeddings, other, recipes)
      */
     getCurrentPageType() {
         const path = window.location.pathname;
         if (path.includes('/checkpoints')) return 'checkpoints';
         if (path.includes('/embeddings')) return 'embeddings';
+        if (path.includes('/other')) return 'other';
         if (path.includes('/recipes')) return 'recipes';
         return 'loras';
     }
@@ -443,7 +447,8 @@ class BannerService {
         const endpoints = {
             'loras': '/api/lm/loras/reload?rebuild=true',
             'checkpoints': '/api/lm/checkpoints/reload?rebuild=true',
-            'embeddings': '/api/lm/embeddings/reload?rebuild=true'
+            'embeddings': '/api/lm/embeddings/reload?rebuild=true',
+            'other': '/api/lm/other/reload?rebuild=true'
         };
         return endpoints[pageType] || endpoints['loras'];
     }
@@ -539,6 +544,99 @@ class BannerService {
         this.updateContainerVisibility();
     }
 
+    /**
+     * Announce the opt-in Other Models management to users who have not turned
+     * it on yet. Dismissal is persisted through the shared dismissed_banners
+     * setting, so users who are not interested are not nagged again.
+     */
+    prepareOtherModelsBanner() {
+        if (state.global.settings.enable_other_models) {
+            return;
+        }
+        // Only announce when the host can actually resolve other-model folders.
+        // Standalone installs only know the folder_paths keys present in
+        // settings.json, so announcing there would land the user on an empty
+        // page. `=== false` (not falsy) keeps older payloads working.
+        if (state.global.settings.other_models_paths_available === false) {
+            return;
+        }
+        if (this.isBannerDismissed(OTHER_MODELS_BANNER_ID)) {
+            return;
+        }
+
+        this.registerBanner(OTHER_MODELS_BANNER_ID, {
+            id: OTHER_MODELS_BANNER_ID,
+            title: translate(
+                'banners.otherModels.title',
+                {},
+                'Other Models Management is available'
+            ),
+            content: translate(
+                'banners.otherModels.content',
+                {},
+                'Scan and manage VAE, upscaler, text encoder and CLIP vision files — and download them from CivitAI — from one dedicated page.'
+            ),
+            actions: [
+                {
+                    text: translate(
+                        'banners.otherModels.enable',
+                        {},
+                        'Enable Other Models'
+                    ),
+                    icon: 'fas fa-shapes',
+                    type: 'primary',
+                    action: 'enable-other-models'
+                },
+                {
+                    text: translate(
+                        'banners.otherModels.openSettings',
+                        {},
+                        'Open Settings'
+                    ),
+                    icon: 'fas fa-cog',
+                    type: 'secondary',
+                    action: 'open-other-models-settings'
+                }
+            ],
+            dismissible: true,
+            priority: 0,
+            onRegister: (bannerElement) => {
+                const enableButton = bannerElement.querySelector(
+                    '.banner-action[data-action="enable-other-models"]'
+                );
+                if (enableButton) {
+                    enableButton.addEventListener('click', (event) => {
+                        event.preventDefault();
+                        enableOtherModels().catch((error) => {
+                            console.error('Failed to enable Other Models:', error);
+                        });
+                    });
+                }
+
+                const settingsButton = bannerElement.querySelector(
+                    '.banner-action[data-action="open-other-models-settings"]'
+                );
+                if (settingsButton) {
+                    settingsButton.addEventListener('click', (event) => {
+                        event.preventDefault();
+                        openOtherModelsSettings();
+                    });
+                }
+            }
+        });
+
+        this.updateContainerVisibility();
+    }
+
+    /**
+     * Drop the Other Models announcement once the feature is enabled.
+     * Dismissal is deliberately NOT persisted, so the announcement can come
+     * back if the user switches the feature off again.
+     */
+    removeOtherModelsAnnouncement() {
+        this.removeBannerElement(OTHER_MODELS_BANNER_ID);
+    }
+
     initializeCommunitySupportState() {
         const storedVersion = getStorageItem(COMMUNITY_SUPPORT_VERSION_KEY, null);
 

static/js/managers/BatchImportManager.js

@@ -18,6 +18,7 @@ export class BatchImportManager {
         this.results = null;
         this.isCancelled = false;
         this.isImporting = false;
+        this.currentParentPath = null;
     }
 
     /**
@@ -718,9 +719,10 @@ export class BatchImportManager {
             browser.style.display = isVisible ? 'none' : 'block';
             
             if (!isVisible) {
-                // Load initial directory when opening
+                // Load initial directory when opening. An empty path lets the
+                // server pick its default (user home); "/" would be POSIX-only.
                 const currentPath = document.getElementById('batchDirectoryInput').value;
-                this.loadDirectory(currentPath || '/');
+                this.loadDirectory(currentPath || '');
             }
         }
     }
@@ -761,6 +763,10 @@ export class BatchImportManager {
         const directoryCount = document.getElementById('batchDirectoryCount');
         const imageCount = document.getElementById('batchImageCount');
 
+        // Remember the server-computed parent path so the "up" navigation
+        // works with Windows paths too (they cannot be split on "/").
+        this.currentParentPath = data.parent_path || null;
+
         if (currentPathEl) {
             currentPathEl.textContent = data.current_path;
         }
@@ -811,11 +817,9 @@ export class BatchImportManager {
         `;
         
         item.addEventListener('click', () => {
-            if (isParent) {
-                this.navigateToParentDirectory();
-            } else {
-                this.loadDirectory(path);
-            }
+            // The parent entry uses the server-provided parent_path (or the
+            // Windows drive-list token) directly — both are plain load targets.
+            this.loadDirectory(path);
         });
         
         return item;
@@ -839,15 +843,12 @@ export class BatchImportManager {
     }
 
     /**
-     * Navigate to parent directory
+     * Navigate to parent directory using the path reported by the server.
+     * Deriving it client-side by splitting on "/" breaks Windows paths.
      */
     navigateToParentDirectory() {
-        const currentPath = document.getElementById('batchCurrentPath')?.textContent;
-        if (currentPath) {
-            // Get parent path using path manipulation
-            const lastSeparator = currentPath.lastIndexOf('/');
-            const parentPath = lastSeparator > 0 ? currentPath.substring(0, lastSeparator) : currentPath;
-            this.loadDirectory(parentPath);
+        if (this.currentParentPath) {
+            this.loadDirectory(this.currentParentPath);
         }
     }
 
@@ -857,8 +858,14 @@ export class BatchImportManager {
     selectCurrentDirectory() {
         const currentPath = document.getElementById('batchCurrentPath')?.textContent;
         const directoryInput = document.getElementById('batchDirectoryInput');
-        
-        if (currentPath && directoryInput) {
+
+        if (!currentPath) {
+            // Virtual levels (e.g. the Windows drive list) have no path.
+            showToast('toast.recipes.batchImportNoDirectory', {}, 'error');
+            return;
+        }
+
+        if (directoryInput) {
             directoryInput.value = currentPath;
             this.toggleDirectoryBrowser(); // Close browser
             showToast('toast.recipes.batchImportDirectorySelected', { path: currentPath }, 'success');

static/js/managers/BulkManager.js

@@ -3,6 +3,8 @@ import { showToast, showActionToast, copyToClipboard, sendLoraToWorkflow, sendEm
 import { handleUndoDelete } from '../utils/undoHelpers.js';
 import { updateCardsForBulkMode } from '../components/shared/ModelCard.js';
 import { modalManager } from './ModalManager.js';
+import { rematchModalManager } from './RematchModalManager.js';
+import { showRematchSummary } from '../components/RematchSummaryModal.js';
 import { getModelApiClient, resetAndReload } from '../api/modelApiFactory.js';
 import { RecipeSidebarApiClient, updateRecipeMetadata, extractRecipeId } from '../api/recipeApi.js';
 import { MODEL_TYPES, MODEL_CONFIG } from '../api/apiConfig.js';
@@ -91,6 +93,20 @@ export class BulkManager {
                 setFavorite: true,
                 unfavorite: true
             },
+            [MODEL_TYPES.OTHER]: {
+                addTags: true,
+                sendToWorkflow: false,
+                copyAll: false,
+                refreshAll: true,
+                checkUpdates: true,
+                moveAll: true,
+                autoOrganize: true,
+                deleteAll: true,
+                setContentRating: true,
+                skipMetadataRefresh: true,
+                setFavorite: true,
+                unfavorite: true
+            },
             recipes: {
                 addTags: true,
                 sendToWorkflow: false,
@@ -978,6 +994,15 @@ export class BulkManager {
             return;
         }
 
+        // Collect options (relaxed matching) before starting anything; the
+        // run only begins when the user confirms the dialog.
+        rematchModalManager.showOptionsModal({
+            recipeCount: state.selectedModels.size,
+            onConfirm: ({ relaxed }) => this._startRematchSelectedRecipes(relaxed),
+        });
+    }
+
+    async _startRematchSelectedRecipes(relaxed = false) {
         try {
             const apiClient = this.getActiveApiClient();
             const filePaths = Array.from(state.selectedModels);
@@ -989,7 +1014,7 @@ export class BulkManager {
 
             state.loadingManager.showSimpleLoading('Rematching recipes to local models...');
 
-            const result = await apiClient.rematchBulkModels(filePaths);
+            const result = await apiClient.rematchBulkModels(filePaths, { relaxed: !!relaxed });
 
             if (result.success) {
                 const total = result.total || filePaths.length;
@@ -1015,38 +1040,29 @@ export class BulkManager {
                     }
                 }
 
-                if (matchedEntries > 0) {
-                    const hasFailures = failures > 0;
-                    const toastKey = hasFailures
-                        ? 'toast.recipes.rematchCompleteErrors'
-                        : 'toast.recipes.rematchComplete';
-                    showToast(
-                        toastKey,
-                        { rematched, skipped, total, entries: matchedEntries, recipes: matchedRecipes, failures },
-                        hasFailures ? 'warning' : 'success'
-                    );
-                } else if (failures > 0) {
-                    // Nothing matched and at least one recipe errored —
-                    // "no rematch needed" would be actively misleading here.
-                    showToast(
-                        'toast.recipes.rematchAllFailed',
-                        { total, failures },
-                        'error'
-                    );
-                } else if (unresolvedEntries > 0) {
-                    // Entries existed but have no local model — expected for
-                    // models deleted from Civitai; informational, not an error.
-                    showToast(
-                        'toast.recipes.rematchUnmatched',
-                        { entries: unresolvedEntries, recipes: unresolvedRecipes, total },
-                        'info'
-                    );
-                } else {
+                // Complete no-op (nothing matched, nothing unresolved, no
+                // errors) keeps the lightweight toast; anything else opens
+                // the post-run summary modal.
+                const l4Matches = Array.isArray(result.l4_matches) ? result.l4_matches : [];
+                const isNoop = matchedEntries === 0 && unresolvedEntries === 0 && failures === 0;
+                if (isNoop) {
                     showToast(
                         'toast.recipes.rematchSkipped',
                         { total },
                         'info'
                     );
+                } else {
+                    showRematchSummary({
+                        scope: 'bulk',
+                        total,
+                        matchedRecipes,
+                        matchedEntries,
+                        unresolvedRecipes,
+                        unresolvedEntries,
+                        skipped,
+                        errors: failures,
+                        l4Matches,
+                    });
                 }
 
                 if (state.bulkMode) this.toggleBulkMode();

static/js/managers/BulkMissingLoraDownloadManager.js

@@ -1,7 +1,9 @@
 import { showToast } from '../utils/uiHelpers.js';
+import { isUnresolvableDownloadError } from '../utils/uiHelpers.js';
 import { translate } from '../utils/i18nHelpers.js';
 import { getModelApiClient } from '../api/modelApiFactory.js';
 import { MODEL_TYPES } from '../api/apiConfig.js';
+import { extractRecipeId } from '../api/recipeApi.js';
 import { state } from '../state/index.js';
 import { modalManager } from './ModalManager.js';
 
@@ -13,6 +15,7 @@ export class BulkMissingLoraDownloadManager {
         this.loraApiClient = getModelApiClient(MODEL_TYPES.LORA);
         this.pendingLoras = [];
         this.pendingRecipes = [];
+        this.pendingMissingByRecipe = null;
     }
 
     /**
@@ -136,6 +139,7 @@ export class BulkMissingLoraDownloadManager {
         // Execute download
         await this.executeDownload(this.pendingLoras);
         this.pendingLoras = [];
+        this.pendingMissingByRecipe = null;
     }
 
     /**
@@ -153,6 +157,9 @@ export class BulkMissingLoraDownloadManager {
 
         // Collect missing LoRAs with deduplication
         const stats = this.collectMissingLoras(selectedRecipes);
+        // Kept so executeDownload can mark unresolvable failures back onto
+        // every recipe occurrence (hashInvalid → reconnect candidacy).
+        this.pendingMissingByRecipe = stats.missingLorasByRecipe;
         
         if (stats.uniqueCount === 0) {
             showToast('toast.recipes.noMissingLorasInSelection', {}, 'info');
@@ -196,6 +203,7 @@ export class BulkMissingLoraDownloadManager {
 
         let completedDownloads = 0;
         let failedDownloads = 0;
+        let markedInvalidCount = 0;
         let currentLoraProgress = 0;
         let cancelled = false;
 
@@ -304,6 +312,12 @@ export class BulkMissingLoraDownloadManager {
                 if (!response.success) {
                     console.error(`Failed to download LoRA ${lora.name || lora.file_name}: ${response.error}`);
                     failedDownloads++;
+                    // An unresolvable failure (model gone on CivitAI) flips
+                    // every recipe occurrence to reconnect candidacy — same
+                    // rule as the single-LoRA download in RecipeModal.
+                    if (isUnresolvableDownloadError(response.error)) {
+                        markedInvalidCount += await this.markLoraHashInvalidInRecipes(lora);
+                    }
                 } else {
                     completedDownloads++;
                     updateProgress(100, completedDownloads, '');
@@ -312,6 +326,9 @@ export class BulkMissingLoraDownloadManager {
                 if (!cancelled) {
                     console.error(`Error downloading LoRA ${lora.name || lora.file_name}:`, error);
                     failedDownloads++;
+                    if (isUnresolvableDownloadError(error?.message)) {
+                        markedInvalidCount += await this.markLoraHashInvalidInRecipes(lora);
+                    }
                 }
             }
         }
@@ -335,9 +352,16 @@ export class BulkMissingLoraDownloadManager {
             }, 'warning');
         }
 
+        // Unresolvable failures were marked hash-invalid during the loop;
+        // tell the user those entries now offer reconnect instead of download.
+        if (markedInvalidCount > 0) {
+            showToast('toast.recipes.unresolvableMarkedForReconnect', {
+                count: markedInvalidCount
+            }, 'info', `${markedInvalidCount} unresolvable entr(ies) marked — they can now be reconnected to a local LoRA.`);
+        }
+
         // Update each affected recipe card with fresh data (LoRA inLibrary flags changed)
         if (state.virtualScroller) {
-            const { extractRecipeId } = await import('../api/recipeApi.js');
             for (const recipe of this.pendingRecipes) {
                 const recipeId = extractRecipeId(recipe.file_path);
                 if (!recipeId) continue;
@@ -354,6 +378,59 @@ export class BulkMissingLoraDownloadManager {
         }
     }
 
+    /**
+     * Mark every recipe occurrence of a failed LoRA as hash-invalid.
+     *
+     * Mirrors RecipeModal.markLoraHashInvalid for the bulk flow: the flag
+     * makes each occurrence an unresolved rematch candidate and swaps its
+     * action from download to reconnect. Only called for unresolvable
+     * failures — transient errors leave entries untouched.
+     *
+     * @param {Object} failedLora - The deduplicated LoRA that failed
+     * @returns {Promise<number>} - How many recipe entries were marked
+     */
+    async markLoraHashInvalidInRecipes(failedLora) {
+        const failedKey = failedLora.hash || failedLora.id || failedLora.modelVersionId;
+        if (!failedKey || !this.pendingMissingByRecipe) {
+            return 0;
+        }
+
+        let marked = 0;
+        for (const { recipe, missingLoras } of this.pendingMissingByRecipe.values()) {
+            const recipeId = extractRecipeId(recipe.file_path) || recipe.id;
+            if (!recipeId || !Array.isArray(recipe.loras)) {
+                continue;
+            }
+            for (const entry of missingLoras) {
+                const entryKey = entry.hash || entry.id || entry.modelVersionId;
+                if (entryKey !== failedKey) {
+                    continue;
+                }
+                const loraIndex = recipe.loras.indexOf(entry);
+                if (loraIndex < 0) {
+                    continue;
+                }
+                try {
+                    const response = await fetch('/api/lm/recipe/lora/mark-hash-invalid', {
+                        method: 'POST',
+                        headers: { 'Content-Type': 'application/json' },
+                        body: JSON.stringify({
+                            recipe_id: recipeId,
+                            lora_index: loraIndex,
+                        }),
+                    });
+                    if (response.ok) {
+                        entry.hashInvalid = true;
+                        marked++;
+                    }
+                } catch (error) {
+                    console.warn('Failed to mark LoRA hash invalid:', error);
+                }
+            }
+        }
+        return marked;
+    }
+
     /**
      * Get LoRA root directory from API
      * @returns {Promise<string|null>} - LoRA root directory or null

static/js/managers/DownloadManager.js

@@ -1,15 +1,18 @@
 import { modalManager } from './ModalManager.js';
-import { showToast, setupAutoNewlineOnPaste } from '../utils/uiHelpers.js';
+import { showToast, showActionToast, setupAutoNewlineOnPaste } from '../utils/uiHelpers.js';
 import { state } from '../state/index.js';
 import { LoadingManager } from './LoadingManager.js';
 import { getModelApiClient, resetAndReload } from '../api/modelApiFactory.js';
+import { DOWNLOAD_ENDPOINTS } from '../api/apiConfig.js';
 import { isModelWeightFile } from '../utils/modelFileTypes.js';
 import { getStorageItem, setStorageItem } from '../utils/storageHelpers.js';
 import { FolderTreeManager } from '../components/FolderTreeManager.js';
 import { translate } from '../utils/i18nHelpers.js';
+import { MODEL_SUBTYPE_DISPLAY_NAMES } from '../utils/constants.js';
 import { buildCivitaiUrl, extractCivitaiModelUrlParts, normalizeCivitaiPageHost } from '../utils/civitaiUtils.js';
 import { formatFileSize } from '../utils/formatters.js';
 import { showDownloadBatchSummary } from '../components/DownloadBatchSummaryModal.js';
+import { openOtherModelsSettings } from '../utils/otherModels.js';
 
 export class DownloadManager {
     constructor() {
@@ -489,8 +492,9 @@ export class DownloadManager {
             return { type: 'civitai' };
         }
 
-        // Hugging Face resolve URL → direct file
-        const hfResolveMatch = trimmed.match(/huggingface\.co\/([^/\s]+\/[^/\s]+)\/resolve\/([^/\s]+)\/(.+)/i);
+        // Hugging Face resolve/blob URL → direct file
+        // "blob" is the web preview page; it maps 1:1 to the "resolve" download URL
+        const hfResolveMatch = trimmed.match(/huggingface\.co\/([^/\s]+\/[^/\s]+)\/(?:resolve|blob)\/([^/\s]+)\/(.+)/i);
         if (hfResolveMatch) {
             return {
                 type: 'hf-resolve',
@@ -953,17 +957,18 @@ export class DownloadManager {
     async proceedToLocationContent() {
 
         try {
-            const _isDiffusionModel = this.selectedFile
-                ? (this.selectedFile.type === 'UNet' || this.selectedFile.type === 'Diffusion Model')
-                : (this.currentVersion?.files || []).some(
-                    f => f.type === 'UNet' || f.type === 'Diffusion Model'
-                );
-            this._isDiffusionModel = _isDiffusionModel;
+            this._isDiffusionModel = await this._resolveIsDiffusionModel();
+            this._otherSubType = await this._resolveOtherSubType();
 
             let rootsData;
             if (this._isDiffusionModel && this.apiClient.modelType === 'checkpoints') {
                 rootsData = await this.apiClient.fetchModelRoots('diffusion_model');
+            } else if (this.apiClient.modelType === 'other' && this._otherSubType) {
+                rootsData = await this.apiClient.fetchModelRoots(this._otherSubType);
             } else {
+                // An undecidable other sub_type (null) intentionally lands
+                // here: fetchModelRoots() lists all other roots so the user
+                // can pick manually.
                 rootsData = await this.apiClient.fetchModelRoots();
             }
             const modelRoot = document.getElementById('modelRoot');
@@ -971,19 +976,29 @@ export class DownloadManager {
                 `<option value="${root}">${root}</option>`
             ).join('');
 
-            const singularType = this._isDiffusionModel
-                ? 'unet'
-                : this.apiClient.modelType.replace(/s$/, '');
-            const defaultRootKey = `default_${singularType}_root`;
-            const defaultRoot = state.global.settings[defaultRootKey];
-            console.log(`Default root for ${singularType}:`, defaultRoot);
+            let defaultRoot;
+            let subtypeDisplay;
+            if (this.apiClient.modelType === 'other') {
+                const otherDefaultRoots = state.global.settings.default_other_roots || {};
+                defaultRoot = this._otherSubType ? (otherDefaultRoots[this._otherSubType] || '') : '';
+                subtypeDisplay = this._otherSubType
+                    ? (MODEL_SUBTYPE_DISPLAY_NAMES[this._otherSubType] || this._otherSubType)
+                    : this.apiClient.apiConfig.config.displayName;
+            } else {
+                const singularType = this._isDiffusionModel
+                    ? 'unet'
+                    : this.apiClient.modelType.replace(/s$/, '');
+                const defaultRootKey = `default_${singularType}_root`;
+                defaultRoot = state.global.settings[defaultRootKey];
+                subtypeDisplay = this._isDiffusionModel ? 'Diffusion Model' : this.apiClient.apiConfig.config.displayName;
+            }
+            console.log('Default root:', defaultRoot);
             console.log('Available roots:', rootsData.roots);
             if (defaultRoot && rootsData.roots.includes(defaultRoot)) {
                 console.log(`Setting default root: ${defaultRoot}`);
                 modelRoot.value = defaultRoot;
             }
 
-            const subtypeDisplay = this._isDiffusionModel ? 'Diffusion Model' : this.apiClient.apiConfig.config.displayName;
             document.getElementById('modelRootLabel').textContent =
                 translate('modals.download.selectTypeRoot', { type: subtypeDisplay });
 
@@ -1019,6 +1034,109 @@ export class DownloadManager {
         }
     }
 
+    /**
+     * Decide whether this download routes to the diffusion model (unet)
+     * roots rather than the checkpoint roots. The backend owns the routing
+     * rule (file type first, baseModel fallback), so the location step asks
+     * it; if the endpoint is unavailable we degrade to the local file-type
+     * signal, which matches the backend for well-annotated models.
+     */
+    async _resolveIsDiffusionModel() {
+        const localFileTypeCheck = this.selectedFile
+            ? (this.selectedFile.type === 'UNet' || this.selectedFile.type === 'Diffusion Model')
+            : (this.currentVersion?.files || []).some(
+                f => f.type === 'UNet' || f.type === 'Diffusion Model'
+            );
+
+        // Only checkpoint downloads can route to the diffusion model roots;
+        // without version metadata (e.g. Hugging Face downloads) the local
+        // signal is all we have.
+        if (this.apiClient.modelType !== 'checkpoints'
+            || (!this.selectedFile && !this.currentVersion)) {
+            return localFileTypeCheck;
+        }
+
+        try {
+            const fileTypes = this.selectedFile
+                ? [this.selectedFile.type]
+                : (this.currentVersion?.files || []).map(f => f.type);
+            const response = await fetch(DOWNLOAD_ENDPOINTS.routing, {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({
+                    model_type: 'checkpoint',
+                    base_model: this.currentVersion?.baseModel || '',
+                    file_types: fileTypes,
+                }),
+            });
+            if (!response.ok) {
+                throw new Error(`routing endpoint returned ${response.status}`);
+            }
+            const data = await response.json();
+            if (typeof data.is_diffusion_model === 'boolean') {
+                return data.is_diffusion_model;
+            }
+        } catch (error) {
+            console.warn('[download] routing endpoint unavailable, '
+                + 'falling back to local file-type check:', error);
+        }
+        return localFileTypeCheck;
+    }
+
+    /**
+     * Resolve which other-page sub_type (vae/upscaler/text_encoder/
+     * clip_vision/controlnet) this download routes to. The backend owns the
+     * routing rule (explicit file pick first, model.type next, file.type
+     * fallback), so the location step sends both the picked file's type
+     * (selected_file_type) and the version's full file-type list and lets
+     * the backend apply its priority chain. Returns null when the sub_type
+     * cannot be decided; the location step then lists all other roots for
+     * manual selection instead of guessing a folder.
+     */
+    async _resolveOtherSubType() {
+        // Only other-page downloads route by sub_type; without version
+        // metadata (e.g. Hugging Face downloads) there is nothing to route on.
+        if (this.apiClient.modelType !== 'other'
+            || (!this.selectedFile && !this.currentVersion)) {
+            return null;
+        }
+
+        try {
+            const fileTypes = (this.currentVersion?.files || []).map(f => f.type);
+            const response = await fetch(DOWNLOAD_ENDPOINTS.routing, {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({
+                    model_type: 'other',
+                    base_model: this.currentVersion?.baseModel || '',
+                    file_types: fileTypes,
+                    ...(this.selectedFile
+                        ? { selected_file_type: this.selectedFile.type }
+                        : {}),
+                }),
+            });
+            if (!response.ok) {
+                throw new Error(`routing endpoint returned ${response.status}`);
+            }
+            const data = await response.json();
+            if (data.disabled) {
+                // The matching sub_type (or the whole Other Models feature) is
+                // switched off: auto-routing is refused, so offer the settings
+                // shortcut while the user's intent is clear.
+                showActionToast('other.disabled.downloadBlocked', {}, 'warning', {
+                    actionText: translate('other.disabled.enableAction', {}, 'Enable Other Models'),
+                    onAction: () => openOtherModelsSettings(),
+                });
+                return null;
+            }
+            return data.sub_type || null;
+        } catch (error) {
+            console.warn('[download] other routing endpoint unavailable, '
+                + 'falling back to manual root selection:', error);
+            return null;
+        }
+    }
+
     loadDefaultPathSetting() {
         const modelType = this.apiClient.modelType;
         const storageKey = `use_default_path_${modelType}`;
@@ -2402,9 +2520,14 @@ export class DownloadManager {
                     const singularType = this._isDiffusionModel
                         ? 'unet'
                         : this.apiClient.modelType.replace(/s$/, '');
-                    const templates = state.global.settings.download_path_templates;
-                    const template = templates[singularType];
-                    fullPath += `/${template}`;
+                    const templates = state.global?.settings?.download_path_templates;
+                    const template = templates?.[singularType];
+                    // An empty or absent template means a flat layout: keep the
+                    // root as-is instead of appending "/undefined" or a
+                    // dangling slash.
+                    if (template) {
+                        fullPath += `/${template}`;
+                    }
                 } catch (error) {
                     console.error('Failed to fetch template:', error);
                     fullPath += '/' + translate('modals.download.autoOrganizedPath');

static/js/managers/FilterManager.js

@@ -805,7 +805,7 @@ export class FilterManager {
         // Call the appropriate manager's load method based on page type
         if (this.currentPage === 'recipes' && window.recipeManager) {
             await window.recipeManager.loadRecipes(true);
-        } else if (this.currentPage === 'loras' || this.currentPage === 'embeddings' || this.currentPage === 'checkpoints') {
+        } else if (this.currentPage === 'loras' || this.currentPage === 'embeddings' || this.currentPage === 'checkpoints' || this.currentPage === 'other') {
             // For models page, reset the page and reload
             await getModelApiClient().loadMoreWithVirtualScroll(true, false);
         }
@@ -904,7 +904,7 @@ export class FilterManager {
         // Reload data using the appropriate method for the current page
         if (this.currentPage === 'recipes' && window.recipeManager) {
             await window.recipeManager.loadRecipes(true);
-        } else if (this.currentPage === 'loras' || this.currentPage === 'checkpoints' || this.currentPage === 'embeddings') {
+        } else if (this.currentPage === 'loras' || this.currentPage === 'checkpoints' || this.currentPage === 'embeddings' || this.currentPage === 'other') {
             await getModelApiClient().loadMoreWithVirtualScroll(true, true);
         }
 

static/js/managers/ModalManager.js

@@ -347,6 +347,19 @@ export class ModalManager {
             });
         }
 
+        // Register rematchOptionsModal
+        const rematchOptionsModal = document.getElementById('rematchOptionsModal');
+        if (rematchOptionsModal) {
+            this.registerModal('rematchOptionsModal', {
+                element: rematchOptionsModal,
+                onClose: () => {
+                    this.getModal('rematchOptionsModal').element.style.display = 'none';
+                    document.body.classList.remove('modal-open');
+                },
+                closeOnOutsideClick: true
+            });
+        }
+
         document.addEventListener('keydown', this.boundHandleEscape);
         this.initialized = true;
     }

static/js/managers/MoveManager.js

@@ -60,7 +60,6 @@ class MoveManager {
         this.bulkFilePaths = null;
 
         const apiClient = this._getApiClient(modelType);
-        const currentPageType = state.currentPageType;
         const modelConfig = apiClient.apiConfig.config;
 
         // Handle bulk mode
@@ -113,7 +112,7 @@ class MoveManager {
             ).join('');
 
             // Set default root if available
-            const settingsKey = `default_${currentPageType.slice(0, -1)}_root`;
+            const settingsKey = `default_${modelConfig.singularName}_root`;
             const defaultRoot = state.global.settings[settingsKey];
             if (defaultRoot && rootsData.roots.includes(defaultRoot)) {
                 modelRootSelect.value = defaultRoot;
@@ -227,15 +226,13 @@ class MoveManager {
 
         if (modelRoot) {
             if (this.useDefaultPath) {
-                // Show actual template path
-                try {
-                    const singularType = apiClient.modelType.replace(/s$/, '');
-                    const templates = state.global.settings.download_path_templates;
-                    const template = templates[singularType];
+                // Show actual template path; an empty/absent template means a
+                // flat layout, so keep the root as-is.
+                const singularType = config.singularName || apiClient.modelType.replace(/s$/, '');
+                const templates = state.global?.settings?.download_path_templates;
+                const template = templates?.[singularType];
+                if (template) {
                     fullPath += `/${template}`;
-                } catch (error) {
-                    console.error('Failed to fetch template:', error);
-                    fullPath += '/' + translate('modals.download.autoOrganizedPath');
                 }
             } else {
                 // Show manual path selection
@@ -329,7 +326,11 @@ class MoveManager {
                 const results = await apiClient.moveBulkModels(this.bulkFilePaths, targetPath, this.useDefaultPath);
                 movedFiles = (results || [])
                     .filter(r => r.success)
-                    .map(r => ({ original_file_path: r.original_file_path, new_file_path: r.new_file_path }));
+                    .map(r => ({
+                        original_file_path: r.original_file_path,
+                        new_file_path: r.new_file_path,
+                        sub_type: r.cache_entry?.sub_type
+                    }));
 
                 // Deselect moving items and exit bulk mode
                 this.bulkFilePaths.forEach(path => bulkManager.deselectItem(path));
@@ -340,7 +341,11 @@ class MoveManager {
                 if (result) {
                     movedFiles.push({
                         original_file_path: result.original_file_path || this.currentFilePath,
-                        new_file_path: result.new_file_path
+                        new_file_path: result.new_file_path,
+                        // The backend recalculates location-derived fields
+                        // (e.g. checkpoint -> diffusion_model) during the move;
+                        // carry them so the card re-renders with the new type.
+                        sub_type: result.cache_entry?.sub_type
                     });
                 }
 
@@ -379,24 +384,28 @@ class MoveManager {
                         }
 
                         if (stillVisible) {
+                            const newData = {
+                                file_path: moved.new_file_path,
+                                folder: newRelativeFolder
+                            };
+                            if (moved.sub_type) newData.sub_type = moved.sub_type;
                             pathsToUpdate.push({
                                 originalPath: moved.original_file_path,
-                                newData: {
-                                    file_path: moved.new_file_path,
-                                    folder: newRelativeFolder
-                                }
+                                newData
                             });
                         } else {
                             pathsToRemove.push(moved.original_file_path);
                         }
                     } else {
                         // No folder filter active — items remain visible, just update path
+                        const newData = {
+                            file_path: moved.new_file_path,
+                            folder: this._getRelativeFolder(moved.new_file_path)
+                        };
+                        if (moved.sub_type) newData.sub_type = moved.sub_type;
                         pathsToUpdate.push({
                             originalPath: moved.original_file_path,
-                            newData: {
-                                file_path: moved.new_file_path,
-                                folder: this._getRelativeFolder(moved.new_file_path)
-                            }
+                            newData
                         });
                     }
                 }

static/js/managers/RematchModalManager.js

@@ -0,0 +1,72 @@
+import { modalManager } from './ModalManager.js';
+import { translate } from '../utils/i18nHelpers.js';
+
+/**
+ * Owns the recipe-rematch options modal (rematchOptionsModal), shown BEFORE
+ * a global/bulk/single rematch run; collects the "relaxed matching" opt-in
+ * and only then invokes the run callback. Post-run reporting lives in
+ * static/js/components/RematchSummaryModal.js.
+ */
+export class RematchModalManager {
+    constructor() {
+        this._optionsConfirmCallback = null;
+    }
+
+    /**
+     * Open the options modal. `onConfirm({ relaxed })` fires only when the
+     * user clicks Rematch — Cancel/X runs nothing.
+     *
+     * @param {{ scope?: 'global'|'bulk'|'single', recipeCount?: number|null, onConfirm?: function }} options
+     */
+    showOptionsModal({ scope = null, recipeCount = null, onConfirm } = {}) {
+        const resolvedScope = scope || (recipeCount != null ? 'bulk' : 'global');
+        const message = document.getElementById('rematchOptionsMessage');
+        if (message) {
+            if (resolvedScope === 'bulk') {
+                message.textContent = translate(
+                    'modals.rematchOptions.messageBulk',
+                    { count: recipeCount },
+                    `${recipeCount} selected recipe(s) will be scanned against your local model library.`
+                );
+            } else if (resolvedScope === 'single') {
+                message.textContent = translate(
+                    'modals.rematchOptions.messageSingle',
+                    {},
+                    'This recipe will be scanned against your local model library.'
+                );
+            } else {
+                message.textContent = translate(
+                    'modals.rematchOptions.messageGlobal',
+                    {},
+                    'All recipes will be scanned against your local model library.'
+                );
+            }
+        }
+        const checkbox = document.getElementById('rematchOptionsRelaxed');
+        if (checkbox) {
+            checkbox.checked = false;
+        }
+        this._optionsConfirmCallback = typeof onConfirm === 'function' ? onConfirm : null;
+        modalManager.showModal('rematchOptionsModal');
+    }
+
+    confirmOptions() {
+        const checkbox = document.getElementById('rematchOptionsRelaxed');
+        const relaxed = checkbox ? !!checkbox.checked : false;
+        const callback = this._optionsConfirmCallback;
+        this._optionsConfirmCallback = null;
+        modalManager.closeModal('rematchOptionsModal');
+        if (callback) {
+            // Returned so callers (and tests) can await the started run.
+            return callback({ relaxed });
+        }
+        return undefined;
+    }
+
+    cancelOptions() {
+        this._optionsConfirmCallback = null;
+        modalManager.closeModal('rematchOptionsModal');
+    }
+}
+
+export const rematchModalManager = new RematchModalManager();

static/js/managers/SearchManager.js

@@ -298,7 +298,7 @@ export class SearchManager {
             pageState.searchOptions.loraName = options.loraName || false;
             pageState.searchOptions.loraModel = options.loraModel || false;
             pageState.searchOptions.prompt = options.prompt || false;
-        } else if (this.currentPage === 'loras' || this.currentPage === 'checkpoints' || this.currentPage === 'embeddings') {
+        } else if (this.currentPage === 'loras' || this.currentPage === 'checkpoints' || this.currentPage === 'embeddings' || this.currentPage === 'other') {
             // Update only the relevant fields in searchOptions instead of replacing the whole object
             pageState.searchOptions.filename = options.filename || false;
             pageState.searchOptions.modelname = options.modelname || false;
@@ -311,7 +311,7 @@ export class SearchManager {
       // Call the appropriate manager's load method based on page type
       if (this.currentPage === 'recipes' && window.recipeManager) {
         window.recipeManager.loadRecipes(true);
-      } else if (this.currentPage === 'loras' || this.currentPage === 'embeddings' || this.currentPage === 'checkpoints') {
+      } else if (this.currentPage === 'loras' || this.currentPage === 'embeddings' || this.currentPage === 'checkpoints' || this.currentPage === 'other') {
         // For models page, reset the page and reload
         getModelApiClient().loadMoreWithVirtualScroll(true, false);
       }

static/js/managers/SettingsManager.js

@@ -1153,6 +1153,10 @@ export class SettingsManager {
         // Load default unet root
         await this.loadUnetRoots();
 
+        // Load default other-model roots (per sub_type)
+        await this.loadOtherRoots();
+        this.updateOtherModelsControls();
+
         // Load extra folder paths
         this.loadExtraFolderPaths();
 
@@ -1658,6 +1662,51 @@ export class SettingsManager {
         }
     }
 
+    async loadOtherRoots() {
+        const selects = document.querySelectorAll('select[data-other-root-subtype]');
+        if (!selects.length) return;
+
+        try {
+            // Fetch other-model roots grouped by sub_type
+            const response = await fetch('/api/lm/other/roots_by_subtype');
+            if (!response.ok) {
+                throw new Error('Failed to fetch other model roots');
+            }
+
+            const data = await response.json();
+            const groupedRoots = data.roots_by_subtype || {};
+            const defaultRoots = state.global.settings.default_other_roots || {};
+
+            selects.forEach((select) => {
+                const subType = select.dataset.otherRootSubtype;
+                const roots = groupedRoots[subType] || [];
+                if (!roots.length) {
+                    this.showNoRootsPlaceholder(select);
+                    return;
+                }
+
+                select.innerHTML = '';
+                select.disabled = false;
+
+                // Add options for each root
+                roots.forEach(root => {
+                    const option = document.createElement('option');
+                    option.value = root;
+                    option.textContent = root;
+                    select.appendChild(option);
+                });
+
+                const defaultRoot = defaultRoots[subType] || '';
+                select.value = roots.includes(defaultRoot) ? defaultRoot : roots[0];
+            });
+
+        } catch (error) {
+            console.error('Error loading other model roots:', error);
+            selects.forEach((select) => this.showNoRootsPlaceholder(select));
+            showToast('toast.settings.otherRootsFailed', { message: error.message }, 'error');
+        }
+    }
+
     async loadEmbeddingRoots() {
         const defaultEmbeddingRootSelect = document.getElementById('defaultEmbeddingRoot');
         if (!defaultEmbeddingRootSelect) return;
@@ -2256,6 +2305,16 @@ export class SettingsManager {
                 await this.updateBackupStatus();
             }
 
+            if (settingKey === 'enable_other_models') {
+                // Roots only exist while the feature is on, so re-fetch them
+                // after the backend rebuilt the other-model root set.
+                this.updateOtherModelsControls();
+                await this.loadOtherRoots();
+                this.updateOtherModelsControls();
+                this.updateOtherModelsNavVisibility(value);
+                this.removeOtherModelsAnnouncement(value);
+            }
+
             showToast('toast.settings.settingsUpdated', { setting: settingKey.replace(/_/g, ' ') }, 'success');
 
             // Apply frontend settings immediately
@@ -2339,6 +2398,103 @@ export class SettingsManager {
         }
     }
 
+    /**
+     * Save one sub_type entry of the default_other_roots dict setting
+     * (read-modify-write: the backend stores the whole mapping).
+     */
+    async saveOtherRootSetting(subType, value) {
+        try {
+            const defaultRoots = { ...(state.global.settings.default_other_roots || {}) };
+            if (value) {
+                defaultRoots[subType] = value;
+            } else {
+                delete defaultRoots[subType];
+            }
+
+            await this.saveSetting('default_other_roots', defaultRoots);
+
+            showToast('toast.settings.settingsUpdated', { setting: `default ${subType} root` }, 'success');
+        } catch (error) {
+            showToast('toast.settings.settingSaveFailed', { message: error.message }, 'error');
+        }
+    }
+
+    /**
+     * Reflect the opt-in Other Models state in the settings UI: the master
+     * toggle gates every sub_type checkbox, and a switched-off sub_type has
+     * its default-root select disabled. Never force-enables a select (the
+     * no-roots placeholder owns that state).
+     */
+    updateOtherModelsControls() {
+        const enableOtherModels = !!state.global.settings.enable_other_models;
+        const enabledSubTypes = new Set(
+            state.global.settings.enabled_other_sub_types
+            || ['vae', 'upscaler', 'text_encoder']
+        );
+
+        document.querySelectorAll('[data-other-subtype-toggle]').forEach((input) => {
+            input.checked = enabledSubTypes.has(input.value);
+            input.disabled = !enableOtherModels;
+        });
+
+        const container = document.getElementById('otherSubTypeToggles');
+        if (container) {
+            container.classList.toggle('is-disabled', !enableOtherModels);
+        }
+
+        document.querySelectorAll('select[data-other-root-subtype]').forEach((select) => {
+            const subType = select.dataset.otherRootSubtype;
+            if (!enableOtherModels || !enabledSubTypes.has(subType)) {
+                select.disabled = true;
+            }
+        });
+    }
+
+    /**
+     * Persist the whole enabled_other_sub_types list (the backend stores an
+     * allow-list) and refresh the per-sub_type default-root selects.
+     */
+    async saveEnabledOtherSubTypes() {
+        const values = Array.from(
+            document.querySelectorAll('[data-other-subtype-toggle]')
+        )
+            .filter((input) => input.checked)
+            .map((input) => input.value);
+
+        try {
+            await this.saveSetting('enabled_other_sub_types', values);
+            this.updateOtherModelsControls();
+            await this.loadOtherRoots();
+            this.updateOtherModelsControls();
+
+            showToast('toast.settings.settingsUpdated', { setting: 'other model types' }, 'success');
+        } catch (error) {
+            showToast('toast.settings.settingSaveFailed', { message: error.message }, 'error');
+        }
+    }
+
+    /**
+     * Show or hide the Other Models nav entry. The nav is server-rendered, so
+     * toggling the class here keeps it in sync when the switch is flipped from
+     * the settings modal (no reload needed).
+     */
+    updateOtherModelsNavVisibility(enabled) {
+        const navItem = document.getElementById('otherNavItem');
+        if (navItem) {
+            navItem.classList.toggle('nav-item--hidden', !enabled);
+        }
+    }
+
+    /**
+     * Drop the Other Models announcement banner once the feature is on.
+     */
+    removeOtherModelsAnnouncement(enabled) {
+        if (!enabled) {
+            return;
+        }
+        bannerService.removeOtherModelsAnnouncement();
+    }
+
     /**
      * Save the recipes page layout (grid | masonry) and rebuild the scroller.
      * Shared entry point for the settings modal segmented control and the
@@ -3360,6 +3516,9 @@ export class SettingsManager {
         } else if (this.currentPage === 'embeddings') {
             // Reload the embeddings without updating folders
             await resetAndReload(false);
+        } else if (this.currentPage === 'other') {
+            // Reload the other models without updating folders
+            await resetAndReload(false);
         }
     }
 

static/js/other.js

@@ -0,0 +1,57 @@
+import { appCore } from './core.js';
+import { confirmDelete, closeDeleteModal, confirmExclude, closeExcludeModal } from './utils/modalUtils.js';
+import { createPageControls } from './components/controls/index.js';
+import { ModelDuplicatesManager } from './components/ModelDuplicatesManager.js';
+import { MODEL_TYPES } from './api/apiConfig.js';
+import { initActiveFiltersSync } from './utils/activeFiltersSync.js';
+
+// Initialize the Other Models page
+class OtherPageManager {
+    constructor() {
+        // Initialize page controls
+        this.pageControls = createPageControls(MODEL_TYPES.OTHER);
+
+        // Initialize the ModelDuplicatesManager
+        this.duplicatesManager = new ModelDuplicatesManager(this, MODEL_TYPES.OTHER);
+
+        // Expose only necessary functions to global scope
+        this._exposeRequiredGlobalFunctions();
+    }
+
+    _exposeRequiredGlobalFunctions() {
+        // Minimal set of functions that need to remain global
+        window.confirmDelete = confirmDelete;
+        window.closeDeleteModal = closeDeleteModal;
+        window.confirmExclude = confirmExclude;
+        window.closeExcludeModal = closeExcludeModal;
+
+        // Expose duplicates manager
+        window.modelDuplicatesManager = this.duplicatesManager;
+    }
+
+    async initialize() {
+        // Initialize common page features (including context menus)
+        appCore.initializePageFeatures();
+
+        // Mirror active filters to the backend for the ComfyUI-side autocomplete
+        initActiveFiltersSync(MODEL_TYPES.OTHER);
+
+        console.log('Other Models Manager initialized');
+    }
+}
+
+async function initializeOtherPage() {
+    // Initialize core application
+    await appCore.initialize();
+
+    // Initialize other models page
+    const otherPage = new OtherPageManager();
+    await otherPage.initialize();
+
+    return otherPage;
+}
+
+// Initialize everything when DOM is ready
+document.addEventListener('DOMContentLoaded', initializeOtherPage);
+
+export { OtherPageManager, initializeOtherPage };

static/js/other_disabled.js

@@ -0,0 +1,53 @@
+import { appCore } from './core.js';
+import { showToast } from './utils/uiHelpers.js';
+import { enableOtherModels, openOtherModelsSettings } from './utils/otherModels.js';
+
+/**
+ * Other Models is an opt-in feature. While it is disabled this page renders an
+ * empty state whose button turns the feature on; the backend then rebuilds the
+ * other-model roots and starts scanning, so a reload lands on the real page.
+ *
+ * The same module backs the "enabled but no folders found" state, where the
+ * only useful action is jumping to Settings instead of enabling anything.
+ */
+async function handleEnableClick() {
+    const button = document.getElementById('enableOtherModelsBtn');
+    if (!button || button.disabled) return;
+
+    button.disabled = true;
+    try {
+        await enableOtherModels();
+    } catch (error) {
+        button.disabled = false;
+        showToast('other.disabled.enableFailed', { message: error.message }, 'error');
+    }
+}
+
+/**
+ * Open Settings on the Library section for the "no folders found" state, so a
+ * misconfigured install can be fixed without hand-editing unknown keys.
+ */
+function handleOpenSettingsClick(event) {
+    event.preventDefault();
+    openOtherModelsSettings();
+}
+
+async function initializeOtherDisabledPage() {
+    // appCore.initialize() wires the shared header (theme, settings modal,
+    // language) so this page is not a dead end.
+    await appCore.initialize();
+
+    const button = document.getElementById('enableOtherModelsBtn');
+    if (button) {
+        button.addEventListener('click', handleEnableClick);
+    }
+
+    const settingsButton = document.getElementById('openOtherModelsSettingsBtn');
+    if (settingsButton) {
+        settingsButton.addEventListener('click', handleOpenSettingsClick);
+    }
+}
+
+document.addEventListener('DOMContentLoaded', initializeOtherDisabledPage);
+
+export { handleEnableClick as enableOtherModels, initializeOtherDisabledPage };

static/js/state/index.js

@@ -24,6 +24,9 @@ const DEFAULT_SETTINGS_BASE = Object.freeze({
     default_lora_root: '',
     default_checkpoint_root: '',
     default_embedding_root: '',
+    default_other_roots: {},
+    enable_other_models: false,
+    enabled_other_sub_types: ['vae', 'upscaler', 'text_encoder'],
     recipes_path: '',
     base_model_path_mappings: {},
     download_path_templates: {},
@@ -72,6 +75,8 @@ export function createDefaultSettings() {
         base_model_path_mappings: {},
         download_path_templates: { ...DEFAULT_PATH_TEMPLATES },
         priority_tags: { ...DEFAULT_PRIORITY_TAG_CONFIG },
+        default_other_roots: {},
+        enabled_other_sub_types: ['vae', 'upscaler', 'text_encoder'],
     };
 }
 
@@ -79,6 +84,7 @@ export function createDefaultSettings() {
 const loraPreviewVersions = getMapFromStorage('loras_preview_versions');
 const checkpointPreviewVersions = getMapFromStorage('checkpoints_preview_versions');
 const embeddingPreviewVersions = getMapFromStorage('embeddings_preview_versions');
+const otherPreviewVersions = getMapFromStorage('other_preview_versions');
 
 export const state = {
     // Global state
@@ -234,6 +240,44 @@ export const state = {
                 search: '',
             },
             activeViewSnapshot: null,
+        },
+
+        [MODEL_TYPES.OTHER]: {
+            currentPage: 1,
+            isLoading: false,
+            hasMore: true,
+            sortBy: 'name',
+            activeFolder: getStorageItem(`${MODEL_TYPES.OTHER}_activeFolder`),
+            previewVersions: otherPreviewVersions,
+            searchManager: null,
+            searchOptions: {
+                filename: true,
+                modelname: true,
+                tags: false,
+                creator: false,
+                hash: false,
+                recursive: getStorageItem(`${MODEL_TYPES.OTHER}_recursiveSearch`, true),
+            },
+            filters: {
+                baseModel: [],
+                tags: {},
+                license: {},
+                modelTypes: [],
+                search: '',
+                tagLogic: 'any',
+            },
+            bulkMode: false,
+            selectedModels: new Set(),
+            metadataCache: new Map(),
+            showFavoritesOnly: false,
+            showUpdateAvailableOnly: false,
+            duplicatesMode: false,
+            viewMode: 'active',
+            excludedViewState: {
+                sortBy: 'name:asc',
+                search: '',
+            },
+            activeViewSnapshot: null,
         }
     },
 

static/js/utils/activeFiltersSync.js

@@ -53,7 +53,7 @@ export function syncActiveFilters(pageType) {
  * Register the storage listener and push the current (restored) state once.
  * The initial push covers server restarts, where the backend store is empty
  * until the manager page re-publishes its localStorage-restored filters.
- * @param {string} pageType - 'loras' | 'checkpoints' | 'embeddings'
+ * @param {string} pageType - 'loras' | 'checkpoints' | 'embeddings' | 'other'
  */
 export function initActiveFiltersSync(pageType) {
     setActiveFiltersListener((changedPageType) => syncActiveFilters(changedPageType));

static/js/utils/constants.js

@@ -106,6 +106,12 @@ export const MODEL_SUBTYPE_DISPLAY_NAMES = {
     diffusion_model: "Diffusion Model",
     // Embedding sub-types
     embedding: "Embedding",
+    // Other model sub-types
+    vae: "VAE",
+    upscaler: "Upscaler",
+    text_encoder: "Text Encoder",
+    clip_vision: "CLIP Vision",
+    controlnet: "ControlNet",
 };
 
 // Backward compatibility alias
@@ -119,6 +125,11 @@ export const MODEL_SUBTYPE_ABBREVIATIONS = {
     checkpoint: "CKPT",
     diffusion_model: "DM",
     embedding: "EMB",
+    vae: "VAE",
+    upscaler: "UPS",
+    text_encoder: "TE",
+    clip_vision: "CV",
+    controlnet: "CN",
 };
 
 export function getSubTypeAbbreviation(subType) {
@@ -342,7 +353,11 @@ export const DEFAULT_PATH_TEMPLATES = {
     lora: '{base_model}/{first_tag}',
     checkpoint: '{base_model}',
     unet: '{base_model}',
-    embedding: '{first_tag}'
+    embedding: '{first_tag}',
+    // Other models (VAE/upscaler/...) default to a flat layout: their root is
+    // already split per sub_type, and priority_tags has no "other" entry, so
+    // {first_tag} would resolve to an arbitrary CivitAI tag.
+    other: ''
 };
 
 // Model type labels for UI

static/js/utils/infiniteScroll.js

@@ -66,7 +66,7 @@ async function getCardCreator(pageType) {
 
 // Function to get the appropriate data fetcher based on page type
 async function getDataFetcher(pageType) {
-    if (pageType === 'loras' || pageType === 'embeddings' || pageType === 'checkpoints') {
+    if (pageType === 'loras' || pageType === 'embeddings' || pageType === 'checkpoints' || pageType === 'other') {
         return (page = 1, pageSize = 100) => getModelApiClient().fetchModelsPage(page, pageSize);
     } else if (pageType === 'recipes') {
         // Import the recipeApi module and use the fetchRecipesPage function

static/js/utils/otherModels.js

@@ -0,0 +1,52 @@
+/**
+ * Shared helpers for the opt-in Other Models feature.
+ *
+ * Used by the disabled page, the announcement banner and the download modal so
+ * that enabling the feature always goes through the same settings API call and
+ * lands on the same settings section.
+ */
+
+/**
+ * Turn on Other Models management and reload so the server-rendered nav and
+ * the scanner state pick up the change.
+ */
+export async function enableOtherModels() {
+    const response = await fetch('/api/lm/settings', {
+        method: 'POST',
+        headers: { 'Content-Type': 'application/json' },
+        body: JSON.stringify({ enable_other_models: true }),
+    });
+    const data = await response.json().catch(() => ({}));
+    if (!response.ok || data.success === false) {
+        throw new Error(data.error || `HTTP ${response.status}`);
+    }
+    window.location.reload();
+}
+
+/**
+ * Open the settings modal on the Library section and scroll the Other Models
+ * toggle into view. Mirrors DoctorManager's open-settings-syntax-format flow.
+ */
+export function openOtherModelsSettings() {
+    const modalManager = window.modalManager;
+    if (modalManager && typeof modalManager.showModal === 'function') {
+        modalManager.showModal('settingsModal');
+    }
+
+    window.setTimeout(() => {
+        document.querySelectorAll('.settings-section').forEach((section) => {
+            section.classList.remove('active');
+        });
+        document.getElementById('section-library')?.classList.add('active');
+
+        document.querySelectorAll('.settings-nav-item').forEach((item) => {
+            item.classList.remove('active');
+        });
+        document.querySelector('.settings-nav-item[data-section="library"]')?.classList.add('active');
+
+        document.getElementById('enableOtherModels')?.scrollIntoView({
+            behavior: 'smooth',
+            block: 'center',
+        });
+    }, 100);
+}

static/js/utils/storageHelpers.js

@@ -8,7 +8,7 @@ const STORAGE_PREFIX = 'lora_manager_';
 
 // Matches keys that carry the manager page's active filter state
 // (e.g. 'loras_activeFolder', 'checkpoints_filters').
-const ACTIVE_FILTER_KEY_PATTERN = /^(loras|checkpoints|embeddings)_(activeFolder|recursiveSearch|filters)$/;
+const ACTIVE_FILTER_KEY_PATTERN = /^(loras|checkpoints|embeddings|other)_(activeFolder|recursiveSearch|filters)$/;
 
 let activeFiltersListener = null;
 

static/js/utils/uiHelpers.js

@@ -325,6 +325,23 @@ export function isTypingContext(target) {
   return target.isContentEditable || tagName === 'input' || tagName === 'textarea' || tagName === 'select';
 }
 
+/**
+ * Decide whether a download failure means the model is unrecoverable.
+ *
+ * The hash-invalid flag (and the resulting rematch/reconnect candidacy) is
+ * only set when CivitAI explicitly says the model cannot be resolved — never
+ * for transient transport errors (network, 5xx).
+ * @param {*} message - The error message carried by the failed download
+ * @returns {boolean}
+ */
+export function isUnresolvableDownloadError(message) {
+  if (!message) {
+    return false;
+  }
+  const text = String(message).toLowerCase();
+  return /(not found|no longer available|deleted|removed|404|410|gone)/.test(text);
+}
+
 export function restoreFolderFilter() {
   const activeFolder = getStorageItem('activeFolder');
   const folderTag = activeFolder && document.querySelector(`.tag[data-folder="${activeFolder}"]`);

templates/checkpoints.html

@@ -25,6 +25,9 @@
             </div>
         </div>
     </div>
+    <div class="context-menu-item" data-action="enrich-hf-llm">
+        <i class="fas fa-wand-magic-sparkles"></i> <span>{{ t('loras.contextMenu.enrichHfAgent') }}</span>
+    </div>
     <div class="context-menu-separator menu-section-break"></div>
     <!-- Workflow -->
     <div class="context-menu-item" data-action="copyname"><i class="fas fa-copy"></i> {{ t('loras.contextMenu.copyFilename') }}</div>