feat: implement SFW classify mode and NSFW tag management

Add support for SFW classify mode, which restricts tag selection to SFW categories while parking NSFW tags. Update settings schema and API to handle new selected_tags_nsfw field. Adjust frontend logic to manage tag behavior based on SFW mode status, ensuring a seamless user experience.

backend/app/api.py

@@ -920,6 +920,9 @@ def _infer_batch_with_fallback(
         return [row], elapsed_ms, "single_fallback"
 
 
+SFW_CLASSIFY_FOLDERS: tuple[str, ...] = ("SFW", "scenery")
+
+
 def _settings_from_db() -> AppSettings:
     row = fetch_one("SELECT * FROM settings WHERE id = 1")
     if not row:
@@ -929,12 +932,20 @@ def _settings_from_db() -> AppSettings:
     if not isinstance(selected_tags, list):
         selected_tags = []
     selected_tags = [str(t).strip() for t in selected_tags if str(t).strip()]
+    nsfw_raw = row.get("selected_tags_nsfw_json") or "[]"
+    selected_tags_nsfw = from_json(nsfw_raw, default=[])
+    if not isinstance(selected_tags_nsfw, list):
+        selected_tags_nsfw = []
+    selected_tags_nsfw = [str(t).strip() for t in selected_tags_nsfw if str(t).strip()]
     tagger_model = str(row.get("tagger_model") or "wd_swinv2_v3").strip()
     if tagger_model not in {"ml_danbooru", "wd_swinv2_v3", "wd_eva02_large"}:
         tagger_model = "wd_swinv2_v3"
     tagging_domain = str(row.get("tagging_domain") or "drawn").strip().lower()
     if tagging_domain not in {"drawn", "real_life"}:
         tagging_domain = "drawn"
+    sfw_classify_mode = bool(row.get("sfw_classify_mode", 0))
+    if tagging_domain == "real_life":
+        sfw_classify_mode = False
     return AppSettings(
         root_repo=row["root_repo"],
         categories_root=row["categories_root"],
@@ -947,7 +958,9 @@ def _settings_from_db() -> AppSettings:
         ),
         hybrid_ml_on_review=bool(row.get("hybrid_ml_on_review", 1)),
         tagging_domain=tagging_domain,  # type: ignore[arg-type]
+        sfw_classify_mode=sfw_classify_mode,
         selected_tags=selected_tags,
+        selected_tags_nsfw=selected_tags_nsfw,
         max_inference_workers=int(row.get("max_inference_workers") or 2),
         inference_batch_size=int(row.get("inference_batch_size") or 4),
         force_cpu_inference=bool(row.get("force_cpu_inference", 0)),
@@ -2187,28 +2200,50 @@ def save_settings(payload: SaveSettingsRequest) -> AppSettings:
     if tagging_domain not in {"drawn", "real_life"}:
         tagging_domain = "drawn"
     payload.tagging_domain = tagging_domain  # type: ignore[assignment]
+    sfw_classify_mode = bool(payload.sfw_classify_mode)
+    if tagging_domain == "real_life":
+        sfw_classify_mode = False
+    payload.sfw_classify_mode = sfw_classify_mode
 
     known = load_known_tags(TAGS_CSV)
     known_by_norm = {normalize_tag_name(t): t for t in known}
+
+    def _resolve_drawn_tags(raw_tags: list[str]) -> list[str]:
+        cleaned: list[str] = []
+        for tag in raw_tags:
+            value = str(tag).strip()
+            if not value:
+                continue
+            tax = resolve_taxonomy_folder(value)
+            if tax is not None:
+                if tax.folder not in cleaned:
+                    cleaned.append(tax.folder)
+                continue
+            matched = value if value in known else known_by_norm.get(normalize_tag_name(value))
+            if matched and matched not in cleaned:
+                cleaned.append(matched)
+        return cleaned
+
+    cleaned_nsfw = _resolve_drawn_tags(list(payload.selected_tags_nsfw or []))
+    # Never park the SFW-mode destinations inside the NSFW stash.
+    cleaned_nsfw = [t for t in cleaned_nsfw if t not in SFW_CLASSIFY_FOLDERS]
+
     cleaned_tags: list[str] = []
-    for tag in payload.selected_tags:
-        value = tag.strip()
-        if not value:
-            continue
-        if tagging_domain == "real_life":
+    if tagging_domain == "real_life":
+        for tag in payload.selected_tags:
+            value = tag.strip()
+            if not value:
+                continue
             rl = resolve_real_life_folder(value)
             if rl is not None and rl.folder not in cleaned_tags:
                 cleaned_tags.append(rl.folder)
-            continue
-        tax = resolve_taxonomy_folder(value)
-        if tax is not None:
-            if tax.folder not in cleaned_tags:
-                cleaned_tags.append(tax.folder)
-            continue
-        matched = value if value in known else known_by_norm.get(normalize_tag_name(value))
-        if matched and matched not in cleaned_tags:
-            cleaned_tags.append(matched)
+    elif sfw_classify_mode:
+        cleaned_tags = list(SFW_CLASSIFY_FOLDERS)
+    else:
+        cleaned_tags = _resolve_drawn_tags(list(payload.selected_tags or []))
+
     payload.selected_tags = cleaned_tags
+    payload.selected_tags_nsfw = cleaned_nsfw
     try:
         execute(
             """
@@ -2216,8 +2251,9 @@ def save_settings(payload: SaveSettingsRequest) -> AppSettings:
             SET root_repo = ?, categories_root = ?, confidence_threshold = ?,
                 default_migrate_mode = ?, scan_recursive = ?, experimental_media_enabled = ?,
                 experimental_style_detector_enabled = ?, hybrid_ml_on_review = ?,
-                tagging_domain = ?,
-                selected_tags_json = ?, max_inference_workers = ?, inference_batch_size = ?,
+                tagging_domain = ?, sfw_classify_mode = ?,
+                selected_tags_json = ?, selected_tags_nsfw_json = ?,
+                max_inference_workers = ?, inference_batch_size = ?,
                 force_cpu_inference = ?, tagger_model = ?, wd_general_threshold = ?
             WHERE id = 1
             """,
@@ -2231,7 +2267,9 @@ def save_settings(payload: SaveSettingsRequest) -> AppSettings:
                 1 if payload.experimental_style_detector_enabled else 0,
                 1 if payload.hybrid_ml_on_review else 0,
                 tagging_domain,
+                1 if sfw_classify_mode else 0,
                 to_json(cleaned_tags),
+                to_json(cleaned_nsfw),
                 int(payload.max_inference_workers),
                 int(payload.inference_batch_size),
                 1 if payload.force_cpu_inference else 0,

backend/app/schemas.py

@@ -26,8 +26,13 @@ class AppSettings(BaseModel):
     hybrid_ml_on_review: bool = True
     # Drawn/anime WD+ML taxonomy vs isolated real-life adult tagger taxonomy.
     tagging_domain: TaggingDomain = "drawn"
+    # When true, classify uses only SFW/scenery; NSFW tags are parked.
+    # comic is omitted: WD SwinV2 is weak on B&W / lineart comic cues.
+    sfw_classify_mode: bool = False
     # Shuck3r-style persisted preferences (survive reload / restart).
     selected_tags: list[str] = Field(default_factory=list)
+    # Parked NSFW/specialty destinations while sfw_classify_mode is on.
+    selected_tags_nsfw: list[str] = Field(default_factory=list)
     # Shared ORT run lock; preprocess overlaps across workers. Prefer 2 on GPU.
     max_inference_workers: int = Field(default=2, ge=1, le=16)
     inference_batch_size: int = Field(default=4, ge=1, le=64)

backend/app/storage.py

@@ -95,6 +95,8 @@ def _ensure_settings_columns(conn: sqlite3.Connection) -> None:
         "hybrid_ml_on_review": "INTEGER NOT NULL DEFAULT 1",
         "tagging_domain": "TEXT NOT NULL DEFAULT 'drawn'",
         "selected_tags_json": "TEXT NOT NULL DEFAULT '[]'",
+        "selected_tags_nsfw_json": "TEXT NOT NULL DEFAULT '[]'",
+        "sfw_classify_mode": "INTEGER NOT NULL DEFAULT 0",
         "max_inference_workers": "INTEGER NOT NULL DEFAULT 2",
         "inference_batch_size": "INTEGER NOT NULL DEFAULT 4",
         "force_cpu_inference": "INTEGER NOT NULL DEFAULT 0",

backend/tests/test_api_sfw_classify_mode.py

@@ -0,0 +1,90 @@
+"""SFW classify mode parks NSFW tags and forces safe destinations."""
+
+from __future__ import annotations
+
+from pathlib import Path
+
+from fastapi.testclient import TestClient
+
+from app.main import app
+
+
+def _base_settings(tmp_path: Path, **overrides):
+    root = tmp_path / "root"
+    cats = tmp_path / "cats"
+    root.mkdir(exist_ok=True)
+    cats.mkdir(exist_ok=True)
+    payload = {
+        "root_repo": str(root),
+        "categories_root": str(cats),
+        "confidence_threshold": 0.45,
+        "default_migrate_mode": "copy",
+        "scan_recursive": True,
+        "experimental_media_enabled": False,
+        "experimental_style_detector_enabled": False,
+        "hybrid_ml_on_review": True,
+        "tagging_domain": "drawn",
+        "selected_tags": ["loli", "sex", "group_sex"],
+        "selected_tags_nsfw": [],
+        "sfw_classify_mode": False,
+        "max_inference_workers": 2,
+        "inference_batch_size": 4,
+        "force_cpu_inference": False,
+        "tagger_model": "wd_swinv2_v3",
+        "wd_general_threshold": 0.35,
+    }
+    payload.update(overrides)
+    return payload
+
+
+def test_sfw_classify_mode_parks_nsfw_and_forces_safe_folders(tmp_path: Path):
+    with TestClient(app) as client:
+        resp = client.put("/api/settings", json=_base_settings(tmp_path))
+        assert resp.status_code == 200
+        assert "loli" in resp.json()["selected_tags"]
+
+        resp = client.put(
+            "/api/settings",
+            json=_base_settings(
+                tmp_path,
+                sfw_classify_mode=True,
+                selected_tags=["SFW", "scenery"],
+                selected_tags_nsfw=["loli", "sex", "group_sex", "milf"],
+            ),
+        )
+        assert resp.status_code == 200
+        body = resp.json()
+        assert body["sfw_classify_mode"] is True
+        assert body["selected_tags"] == ["SFW", "scenery"]
+        assert "comic" not in body["selected_tags"]
+        assert body["selected_tags_nsfw"] == ["loli", "sex", "group_sex", "milf"]
+
+        resp = client.put(
+            "/api/settings",
+            json=_base_settings(
+                tmp_path,
+                sfw_classify_mode=True,
+                selected_tags=["loli", "fellatio", "SFW", "comic"],
+                selected_tags_nsfw=["loli", "sex"],
+            ),
+        )
+        assert resp.status_code == 200
+        body = resp.json()
+        assert body["selected_tags"] == ["SFW", "scenery"]
+        assert "comic" not in body["selected_tags"]
+        assert "loli" not in body["selected_tags"]
+
+        resp = client.put(
+            "/api/settings",
+            json=_base_settings(
+                tmp_path,
+                sfw_classify_mode=False,
+                selected_tags=["loli", "sex", "group_sex", "milf"],
+                selected_tags_nsfw=["loli", "sex", "group_sex", "milf"],
+            ),
+        )
+        assert resp.status_code == 200
+        body = resp.json()
+        assert body["sfw_classify_mode"] is False
+        assert "loli" in body["selected_tags"]
+        assert "milf" in body["selected_tags"]

frontend/src/App.jsx

@@ -12,7 +12,9 @@ const DEFAULT_SETTINGS = {
   experimental_style_detector_enabled: false,
   hybrid_ml_on_review: true,
   tagging_domain: "drawn",
+  sfw_classify_mode: false,
   selected_tags: [],
+  selected_tags_nsfw: [],
   max_inference_workers: 2,
   inference_batch_size: 8,
   force_cpu_inference: false,
@@ -61,6 +63,7 @@ const TAGGER_MODELS = [
   },
 ];
 
+const SFW_CLASSIFY_FOLDERS = ["SFW", "scenery"];
 const ACTIVE_RUN_STORAGE_KEY = "imageClassifierActiveRunId";
 const VIDEO_PREVIEW_EXTS = new Set([
   ".mp4",
@@ -685,8 +688,78 @@ function App() {
     }
   }
 
+  const sfwClassifyMode =
+    Boolean(settings.sfw_classify_mode) && settings.tagging_domain !== "real_life";
+  const parkedNsfwTags = Array.isArray(settings.selected_tags_nsfw)
+    ? settings.selected_tags_nsfw
+    : [];
+
+  async function setSfwClassifyMode(enabled) {
+    if (settings.tagging_domain === "real_life") return;
+    setError("");
+    skipNextTagPersistRef.current = true;
+    if (enabled) {
+      const parked = selectedTags.filter((t) => !SFW_CLASSIFY_FOLDERS.includes(t));
+      const nextTags = [...SFW_CLASSIFY_FOLDERS];
+      const next = {
+        ...settings,
+        sfw_classify_mode: true,
+        selected_tags: nextTags,
+        selected_tags_nsfw: parked.length ? parked : parkedNsfwTags,
+      };
+      setSelectedTags(nextTags);
+      setSettings(next);
+      try {
+        const saved = await api.saveSettings(next);
+        const merged = { ...DEFAULT_SETTINGS, ...saved };
+        setSettings(merged);
+        setSelectedTags(
+          Array.isArray(saved.selected_tags) ? saved.selected_tags : nextTags
+        );
+        setSavedSnapshot(
+          settingsSnapshot(
+            merged,
+            Array.isArray(saved.selected_tags) ? saved.selected_tags : nextTags
+          )
+        );
+      } catch (err) {
+        setError(`Failed to enable SFW mode: ${err.message}`);
+      }
+      return;
+    }
+
+    const restored =
+      parkedNsfwTags.length > 0
+        ? parkedNsfwTags
+        : selectedTags.filter((t) => !SFW_CLASSIFY_FOLDERS.includes(t));
+    const next = {
+      ...settings,
+      sfw_classify_mode: false,
+      selected_tags: restored,
+      selected_tags_nsfw: restored,
+    };
+    setSelectedTags(restored);
+    setSettings(next);
+    try {
+      const saved = await api.saveSettings(next);
+      const merged = { ...DEFAULT_SETTINGS, ...saved };
+      setSettings(merged);
+      setSelectedTags(
+        Array.isArray(saved.selected_tags) ? saved.selected_tags : restored
+      );
+      setSavedSnapshot(
+        settingsSnapshot(
+          merged,
+          Array.isArray(saved.selected_tags) ? saved.selected_tags : restored
+        )
+      );
+    } catch (err) {
+      setError(`Failed to disable SFW mode: ${err.message}`);
+    }
+  }
+
   function addSelectedTag(value) {
-    if (!value) return;
+    if (!value || sfwClassifyMode) return;
     setSelectedTags((prev) => (prev.includes(value) ? prev : [...prev, value]));
   }
 
@@ -732,6 +805,7 @@ function App() {
   }
 
   function removeSelectedTag(value) {
+    if (sfwClassifyMode) return;
     setSelectedTags((prev) => prev.filter((t) => t !== value));
   }
 
@@ -1029,6 +1103,7 @@ function App() {
                         ...settings,
                         tagging_domain: "real_life",
                         experimental_media_enabled: true,
+                        sfw_classify_mode: false,
                       })
                     }
                   />
@@ -1097,8 +1172,21 @@ function App() {
         <span className="kicker">
           {settings.tagging_domain === "real_life"
             ? "Real-life categories only (isolated from anime tags.csv). Changes auto-save after settings save."
-            : "Only these tags compete for folder assignment. Changes auto-save."}
+            : sfwClassifyMode
+              ? "SFW mode: only SFW / scenery compete. Your NSFW tags stay parked."
+              : "Only these tags compete for folder assignment. Changes auto-save."}
         </span>
+        {settings.tagging_domain !== "real_life" ? (
+          <label className="inline-check sfw-mode-toggle">
+            <input
+              type="checkbox"
+              checked={sfwClassifyMode}
+              disabled={runActive || opsLoading.startingRun}
+              onChange={(e) => setSfwClassifyMode(e.target.checked)}
+            />
+            SFW classify mode (parks NSFW tags; restore when off)
+          </label>
+        ) : null}
         <label>
           {settings.tagging_domain === "real_life"
             ? "Real-life category search"
@@ -1108,9 +1196,11 @@ function App() {
             onChange={(e) => setTagQuery(e.target.value)}
             list="tag-match-suggestions"
             autoComplete="off"
+            disabled={sfwClassifyMode}
             onKeyDown={async (e) => {
               if (e.key === "Enter") {
                 e.preventDefault();
+                if (sfwClassifyMode) return;
                 setError("");
                 try {
                   await addTagsFromInput(tagQuery);
@@ -1121,9 +1211,11 @@ function App() {
               }
             }}
             placeholder={
-              settings.tagging_domain === "real_life"
-                ? "Type creampie, BBC, hotwife…"
-                : "Type Voyeur, loli, Pokemon…"
+              sfwClassifyMode
+                ? "Tag editing disabled in SFW mode"
+                : settings.tagging_domain === "real_life"
+                  ? "Type creampie, BBC, hotwife…"
+                  : "Type Voyeur, loli, Pokemon…"
             }
           />
           <datalist id="tag-match-suggestions">
@@ -1132,7 +1224,7 @@ function App() {
             ))}
           </datalist>
         </label>
-        {tagQuery.trim() && (
+        {tagQuery.trim() && !sfwClassifyMode && (
           <div className="tag-suggestions">
             {tagOptions.length === 0 ? (
               <span className="muted">No matching tags</span>
@@ -1158,6 +1250,7 @@ function App() {
           <button
             type="button"
             className="secondary"
+            disabled={sfwClassifyMode}
             onClick={async () => {
               setError("");
               try {
@@ -1227,20 +1320,37 @@ function App() {
             </>
           )}
         </p>
-        <div className="stats">
+        <div className={`stats${sfwClassifyMode ? " tags-locked" : ""}`}>
           {selectedTags.length === 0 ? (
             <span className="muted">No tags selected</span>
           ) : (
             selectedTags.map((tag) => (
               <span key={tag} className="chip">
                 {tag}
-                <button type="button" onClick={() => removeSelectedTag(tag)} aria-label={`Remove ${tag}`}>
+                <button
+                  type="button"
+                  onClick={() => removeSelectedTag(tag)}
+                  aria-label={`Remove ${tag}`}
+                  disabled={sfwClassifyMode}
+                >
                   ×
                 </button>
               </span>
             ))
           )}
         </div>
+        {sfwClassifyMode && parkedNsfwTags.length > 0 ? (
+          <div className="parked-tags">
+            <span className="help">Parked NSFW tags (inactive until SFW mode is off):</span>
+            <div className="stats tags-locked">
+              {parkedNsfwTags.map((tag) => (
+                <span key={`parked-${tag}`} className="chip chip-parked">
+                  {tag}
+                </span>
+              ))}
+            </div>
+          </div>
+        ) : null}
       </section>
 
       {runId && runStatus && (

frontend/src/api.js

@@ -11,7 +11,9 @@ const defaultSettings = {
   experimental_style_detector_enabled: false,
   hybrid_ml_on_review: true,
   tagging_domain: "drawn",
+  sfw_classify_mode: false,
   selected_tags: [],
+  selected_tags_nsfw: [],
   max_inference_workers: 2,
   inference_batch_size: 8,
   force_cpu_inference: false,
@@ -320,7 +322,17 @@ function mockRequest(path, options = {}) {
     return Promise.resolve({ items, count: items.length });
   }
   if (path === "/settings" && method === "PUT") {
-    mockState.settings = { ...defaultSettings, ...body };
+    const next = { ...defaultSettings, ...mockState.settings, ...body };
+    if (next.tagging_domain === "real_life") {
+      next.sfw_classify_mode = false;
+    }
+    if (next.sfw_classify_mode) {
+      next.selected_tags = ["SFW", "scenery"];
+    }
+    if (!Array.isArray(next.selected_tags_nsfw)) {
+      next.selected_tags_nsfw = [];
+    }
+    mockState.settings = next;
     persistMockState();
     return Promise.resolve(mockState.settings);
   }

frontend/src/styles.css

@@ -453,6 +453,31 @@ button.danger {
   font-weight: 700;
 }
 
+.chip button:disabled {
+  opacity: 0.35;
+  cursor: not-allowed;
+}
+
+.sfw-mode-toggle {
+  margin: 8px 0 12px;
+  font-weight: 600;
+}
+
+.tags-locked .chip {
+  opacity: 0.72;
+  filter: grayscale(0.35);
+}
+
+.chip-parked {
+  background: #f1f5f9;
+  border-color: #cbd5e1;
+  color: #64748b;
+}
+
+.parked-tags {
+  margin-top: 10px;
+}
+
 .muted {
   color: var(--muted);
   font-size: 13px;