chore(release): v0.7.4 - Video EditにBGM合成・テキストオーバーレイ・クロップ・Undo/Redoを追加

Video Editサブタブの残りフェーズ(Phase 2〜5)を実装。 - BGM/音声トラック合成: Core音声ノード+ConcatenateVideoのcomplete_audioでグラフ内完結。複数クリップ結合時も各クリップの音声を保持。BGMはボタン/ドロップ/AssetのBGMに設定で指定 - テキストオーバーレイ: クリップ単位の字幕(位置・区間・色・縁取り・背景)、PyAVストリーム処理で焼き込み - クロップ: Sourceプレビュー上の矩形エディタ(アスペクト固定・キャンセル)、VideoCropで書き出し - Undo/Redo: 編集状態のスナップショット履歴(ボタン+Ctrl+Z/Y) - クリアでオーディオ欄も初期化、BGM/Loadのファイル選択が開かない不具合を修正 Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
docs: document Video Edit BGM, text overlays, crop and undo/redo
2026-09-29 15:43:32 +09:00 · 2026-09-29 15:41:51 +09:00 · 2026-09-29 12:57:13 +09:00 · 2026-09-29 12:45:04 +09:00 · 2026-09-29 12:28:42 +09:00 · 2026-09-29 12:20:46 +09:00
110 changed files with 32665 additions and 6572 deletions
@@ -0,0 +1,60 @@
+"""PostToolUse hook: regenerate README.index.md / DEVLOG.index.md right after
+Claude Code edits README.md or DEVLOG.md, so graphify's excluded-doc index
+stand-ins (see .graphifyignore) never drift from the source files within a
+session. A git pre-commit hook covers edits made outside Claude Code.
+"""
+
+from __future__ import annotations
+
+import json
+import os
+import subprocess
+import sys
+from pathlib import Path
+
+TARGETS = {"readme.md": "readme", "devlog.md": "devlog"}
+
+
+def main() -> None:
+    try:
+        payload = json.load(sys.stdin)
+    except (json.JSONDecodeError, ValueError):
+        return
+
+    if payload.get("tool_name") not in ("Edit", "Write"):
+        return
+
+    file_path = payload.get("tool_input", {}).get("file_path", "")
+    if not file_path:
+        return
+
+    name = Path(file_path).name.lower()
+    target = TARGETS.get(name)
+    if target is None:
+        return
+
+    project_dir = os.environ.get("CLAUDE_PROJECT_DIR") or str(Path(file_path).resolve().parent)
+    script = Path(project_dir) / "tools" / "generate_doc_index.py"
+    if not script.exists():
+        return
+
+    result = subprocess.run(
+        [sys.executable, str(script), target],
+        cwd=project_dir,
+        capture_output=True,
+        text=True,
+        timeout=30,
+    )
+    if result.returncode == 0:
+        print(json.dumps({"systemMessage": f"[doc-index] {result.stdout.strip()}"}))
+    else:
+        print(
+            json.dumps(
+                {"systemMessage": f"[doc-index] generate_doc_index.py {target} failed: {result.stderr.strip()}"}
+            ),
+            file=sys.stderr,
+        )
+
+
+if __name__ == "__main__":
+    main()
@@ -0,0 +1,36 @@
+{
+  "hooks": {
+    "PreToolUse": [
+      {
+        "matcher": "Bash|Grep",
+        "hooks": [
+          {
+            "type": "command",
+            "command": "C:/Users/statsu-11/.local/bin/graphify.EXE hook-guard search"
+          }
+        ]
+      },
+      {
+        "matcher": "Read|Glob",
+        "hooks": [
+          {
+            "type": "command",
+            "command": "C:/Users/statsu-11/.local/bin/graphify.EXE hook-guard read"
+          }
+        ]
+      }
+    ],
+    "PostToolUse": [
+      {
+        "matcher": "Edit|Write",
+        "hooks": [
+          {
+            "type": "command",
+            "command": "python \"$CLAUDE_PROJECT_DIR/.claude/hooks/on_doc_edit.py\"",
+            "timeout": 30
+          }
+        ]
+      }
+    ]
+  }
+}
@@ -0,0 +1,5 @@
+# graphify: keep graph.json/graphify-out/ out of Claude Code's automatic
+# context so re-running `graphify extract` doesn't churn the prompt cache
+# on every rebuild. These are still tracked by git (see .gitignore).
+graph.json
+graphify-out/
@@ -0,0 +1,11 @@
+# ComfyUI-Workflow-Studio - Unsloth backend (AI TOOL tab / sidebar A tab)
+#
+# Unsloth Desktop requires an API key even for local access
+# (Settings -> API in the Unsloth app, shown only once when issued).
+#
+# 1. Copy this file to ".env" (same directory as this example file)
+# 2. Paste your key after the "=" below (do NOT add a leading #, or the
+#    line becomes a comment and the key will not be loaded)
+# 3. Restart ComfyUI
+
+UNSLOTH_API_KEY=
@@ -17,6 +17,6 @@ jobs:
        uses: actions/checkout@v4

      - name: Publish Custom Node
-        uses: Comfy-Org/publish-node-action@main
+        uses: Comfy-Org/publish-node-action@d2366e7abb6ab16f3bb03e3520ae25c8cf749bc9 # 1.0.1
        with:
          personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }}
@@ -5,3 +5,10 @@ __pycache__/
 .venv
 *.egg-info/
 data/
+
+# graphify: local-only knowledge graph output, not shared with other clones
+graphify-out/
+
+# Working-notes plan docs — local scratch, not meant to ship with the repo
+VIDEO_EDIT_TAB_PLAN.md
+QWEN_CHAT_INTEGRATION_PLAN.md
@@ -0,0 +1,10 @@
+# Private/unpublished planning notes — never committed to git, must not leak
+# into the published graphify-out/ knowledge graph either.
+QWEN_CHAT_INTEGRATION_PLAN.md
+
+# Too large for reliable local-Ollama semantic extraction (large chunks make the
+# model summarize in prose instead of emitting JSON, and time out on slower
+# models/hardware). README.index.md / DEVLOG.index.md are condensed stand-ins
+# that graphify extracts instead — regenerate them after editing the originals.
+README.md
+DEVLOG.md
@@ -194,9 +194,34 @@ os.environ["HF_HOME"] = "D:\\hf_cache"

 1. `pyproject.toml` の `version` を新バージョン番号に更新してステージングに含める
 2. `README.md` のバージョンバッジを更新（`![Version](https://img.shields.io/badge/version-X.Y.Z-green)`）
-3. `README.md` の Changelog に新バージョンのエントリを追加
-4. `DEVLOG.md` の先頭に変更詳細エントリを追加
-5. 上記すべてを同一コミットにまとめてプッシュ
-6. `gh release create vX.Y.Z` でリリースを作成
+3. `DEVLOG.md` の先頭に変更詳細エントリを追加
+4. 上記すべてを同一コミットにまとめてプッシュ
+5. `gh release create vX.Y.Z` でリリースを作成（リリースノート本文に変更点を記載する — v0.3.90でREADME.mdのChangelogセクションは廃止したため、以後のバージョン履歴はGitHub Releaseのリリースノートのみで管理する）

 `pyproject.toml` のバージョン変更が GitHub Actions のトリガー（`paths: pyproject.toml`）になっており、ComfyUI Registry への自動公開もここで行われる。バージョン更新を忘れると Registry に反映されない。
+
+<!-- graphify運用は一時停止中（2026-08-23〜、ユーザー指示により凍結）。再開時はこのコメントブロックを解除すること。graphify-out/ 自体は削除しておらずそのまま残っている。
+
+## graphify
+
+This project has a knowledge graph at graphify-out/ with god nodes, community structure, and cross-file relationships.
+
+Rules:
+- For codebase questions, first run `graphify query "<question>"` when graphify-out/graph.json exists. Use `graphify path "<A>" "<B>"` for relationships and `graphify explain "<concept>"` for focused concepts. These return a scoped subgraph, usually much smaller than GRAPH_REPORT.md or raw grep output.
+- If graphify-out/wiki/index.md exists, use it for broad navigation instead of raw source browsing.
+- Read graphify-out/GRAPH_REPORT.md only for broad architecture review or when query/path/explain do not surface enough context.
+- After modifying code, run `graphify update .` to keep the graph current (AST-only, no API cost).
+
+### README.md / DEVLOG.md の索引ファイル
+
+`README.md`/`DEVLOG.md`はサイズが大きすぎてローカルOllamaでの意味抽出が不安定になる（大きな塊を渡すとJSONではなく散文の要約を返す、または処理がタイムアウトする）ため、`.graphifyignore`でgraphifyの抽出対象から除外している。代わりに縮小版の`README.index.md`/`DEVLOG.index.md`を抽出対象にしている。
+
+- 生成スクリプト: `python tools/generate_doc_index.py [readme|devlog|all]`
+- 自動化: `README.md`/`DEVLOG.md`を編集すると以下の2つのフックが自動でindexを再生成する
+  - Claude Code PostToolUseフック（`.claude/hooks/on_doc_edit.py`）— Edit/Write直後に即時実行
+  - git pre-commitフック（`.git/hooks/pre-commit`）— コミット時にstagedファイルを検知して再生成し、同じコミットに含める（他エディタでの編集にも対応）
+- 索引ファイルを手動で編集しない（次の生成で上書きされる）
+- 索引ファイル再生成後は`graphify update .`を実行してグラフに反映する
+
+-->
+
@@ -0,0 +1,184 @@
+# DEVLOG Index — ComfyUI-Workflow-Studio
+
+Condensed version-by-version index of DEVLOG.md (each line: version + one-line summary of what changed and why). Full rationale, code details, and "How to apply" lessons live in the excluded DEVLOG.md itself; this index exists so graphify can extract a queryable semantic node per release without feeding the full log to the local Ollama model. Regenerate with `python tools/generate_doc_index.py devlog` whenever DEVLOG.md changes.
+
+- **v0.7.4（2026-09-29）** — Video Edit: BGM/音声トラック合成（Phase 4）— 複数クリップ結合時の音声消失も解消
+- **v0.7.3（2026-09-24）** — GenerateUIタブにQwen Image 2.1（TextEncodeQwenImage21）対応を追加
+- **v0.7.2（2026-09-18）** — Workflowタブにソート機能追加（Date/Name 昇順降順）
+- **v0.7.1（2026-09-17）** — セキュリティ修正: Tagger VLM の Unsloth 経路でAPIキーがSSRFにより外部送信され得る不備を修正
+- **v0.7.0（2026-09-17）** — プレビュー枠の高さ固定・AssetサブタブをPlan/Editと並ぶ中央下部へ移設・トリムパネルにClipchamp風スクラバー追加・Frame保存のVideo Assets登録とAsset→Plan画像連携
+- **v0.6.3** — Send CCボタンでMP4動画をComic Creatorの新設「動画ツール」へ送れるように対応
+- **v0.6.2** — Image Editタブにペンタブレット筆圧対応とFillツール（バケツ塗りつぶし）を追加
+- **v0.6.1** — Galleryタブの検索が「読み込み中」のまま止まりクリアでも中断できない不具合、および50枚程度のフォルダでも数秒〜十数秒かかる不具合を修正
+- **v0.6.0** — Gallery/Image Edit両タブにPSD(Photoshop)対応を追加 — 複数画像の一括PSD書き出し、レイヤー保存/読み込み、Gallery表示、Image Editのレイヤーパネル改善
+- **v0.5.8** — Tagger DBタブに一括削除機能を追加（外部コントリビューターPRのレビュー・検証・修正・マージ）
+- **v0.5.7** — 設定エクスポート/フルバックアップのドキュメント修正: v0.5.5のVideo Plan機能追加分の言及漏れ
+- **v0.5.6** — バグ修正: WD Taggerで不正確なタグが生成される問題を修正(GitHub Issue #1)
+- **v0.5.5** — Videoタブ全面刷新: Plan/Asset/Editバッチ生成 + Projectサブタブ + プレビュー2ペイン化 + Video Assets/Video Temp運用整理 + Galleryメタデータ消失バグ根本修正
+- **v0.5.4** — 機能追加: Video/GenerateUIタブのLTX-2.5・Wan2.2対応拡大 + AI Assistant設定のUnsloth対応・独立モーダル化・モデルアンロード機能
+- **v0.5.3** — バグ修正: Labタブのワークフロー切替時に前の内容が残留 + Galleryタブの読み込み高速化・root自動展開 + READMEスクリーンショット刷新
+- **v0.5.2** — 機能追加: GenerateUI/Labタブの動画ワークフロー対応 + VideoタブにFrame抽出/GIF変換機能 + データ管理監査とZIPフルバックアップ + Send to LI node統一
+- **v0.5.1** — 機能追加: mp4動画の埋め込みメタデータ対応（Gallery Prompt/JSON・Metadataサブタブ・サイドパネルIタブ）+ Gallery Infoタブに寸法/再生時間表示 + MiniMax H3等オールインワン動画ノードのプロンプト抽出バグ修正
+- **v0.5.0** — 機能追加: mp4動画Gallery対応 + Videoタブ新設(MiniMax H3専用) + バグ修正: Galleryのタグ/メモが再起動後に消える
+- **v0.4.8** — 機能追加: LabタブにPromptグループ一括適用＋キーフレーム並べ替え + バグ修正: デフォルトワークフローの上書き保存が反映されない + Styleテーブルの「このファイルへ追加」対応
+- **v0.4.7** — 機能追加: Prompt Tab内部リファクタ + Gallery Promptタブ新設 + Send to Canvas改善 + Presetsソート
+- **v0.4.6** — 機能追加: MetadataタブをGalleryタブへ統合 + Promptタブに一覧編集可能なTable表示を新設
+- **v0.4.5** — 調査: トップバー保存ワークフローのRMBG不具合報告（原因なし） + バグ修正: LabタブModel列の無意味な空キーフレーム表示を解消
+- **v0.4.4** — 機能追加: Lab/GenerateUI ModelタブへLoRAバイパス機能 + AI TOOL Chatの画像生成パラメータ拡張
+- **v0.4.3** — バグ修正: 共有モーダルのお気に入り☆/リネームがLabモーダルへ残留 + Lab Model列の＋／－をCheckpoint/LoRA/VAEで完全独立化
+- **v0.4.2** — 機能追加: Lab「Model」列統合（Checkpoint / LoRA Single / VAE）+ フィールド単位継承 + C/L/V表示切替
+- **v0.4.1** — UX改善: Mask Editor One連携ボタンを「選択中ノード優先」方式に再設計
+- **v0.4.0** — リファクタリング: image-edit-tab.js / models-tab.js の低凝集度モジュール分割
+- **v0.3.99** — 機能追加: AI TOOLタブ + サイドパネルAタブにUnslothバックエンド追加（APIキーは.env管理、SSRF脆弱性修正、reasoning_content対応）
+- **v0.3.98** — 機能追加・バグ修正: AI TOOL翻訳の信頼性向上 + GenerateUI Modelタブ再構成（ハイライト色・折りたたみ・並び替え）+ Thinking mode/Max tokens設定
+- **v0.3.97** — 機能追加・バグ修正: KREA-2ワークフロー対応 + Labタブ拡張（Clear/Get from Previous/Bypass/ライブ反映）+ Input Imageプレースホルダ機能
+- **v0.3.96** — バグ修正: カタログ作成バッチが特定件数で無言停止する問題の修正 + Style Catalog/Promptタブ機能拡張
+- **v0.3.95** — 機能追加: Style/Prompt→ImagePrompt改名 + Style_Catalogギャラリー新設 + GenerateUI「カタログ作成」機能
+- **v0.3.94** — 機能追加: Gallery タブのサブタブ化 + Style/Prompt ギャラリー新設（視覚的プロンプトビルダー）
+- **v0.3.93** — バグ修正・機能改善: Labタブ VAEキーフレーム不発バグの修正＋Style適用UI刷新＋Plan JSONスクロール同期修正＋キーフレーム個別削除＋Batch数超過警告＋ワイルドカード対応＋Save index image デフォルトON
+- **v0.3.92** — バグ修正: CLIPTextEncodeEditPlus使用ワークフローがGenerateUI経由だと直接実行と異なる画像になる問題（根本原因はconvertUiToApiのForceInput 未考慮バグ）＋LoRA Stack機能の改善一式
+- **v0.3.91** — 機能拡張: Labインデックス画像にPlanメタデータをPNG埋め込み＋README構成整理（Changelogセクション廃止）
+- **v0.3.90** — 機能拡張: Labタブの進化（ワークフロー呼び出し・T2I対応・Run時インデックス画像Output保存＋Eagle連携・プラン接頭辞）＋Galleryタブのルート表示簡略化
+- **v0.3.89** — バグ修正: v0.3.88で追加したLab機能への実動作確認フィードバック3件を反映
+- **v0.3.88** — 機能拡張: Labタブ Promptセルにスタイル適用・画像/GenerateUIからのプロンプト取得、Checkpoint/VAEフィルター、Plan JSONサブタブを追加
+- **v0.3.87** — 追加機能: GenerateUIタブに実験的な「Lab」サブタブを追加（I2Iバッチ生成・キーフレーム方式）
+- **v0.3.86** — バグ修正: 画像を一括生成（I2I）等の連続実行で "GalleryMetadataStore: save error: dictionary changed size during iteration" が発生
+- **v0.3.85** — 機能拡張: Generate UI連携ブリッジ（T2I）にデフォルトワークフロー・Negativeプロンプト対応を追加
+- **v0.3.84** — バグ修正: ernie_t2i.jsonをGenerateUIタブで実行すると "Prompt outputs failed validation" エラー
+- **v0.3.83** — 追加機能: Ernie Image（ernie-image / ernie-image-turbo）ワークフロー対応 + プロンプトがリンク経由のノードから供給されるパターンの修正
+- **v0.3.82** — バグ修正: MetadataタブとサイドパネルIタブでLongCat/Boogu/HiDream E1/FireRed等のプロンプトが表示されない不具合
+- **v0.3.81** — 追加機能: GenerateUIタブでFlux.2 Klein / LongCat / Boogu / HiDream E1 / FireRedのImage Editワークフローに対応
+- **v0.3.80** — 追加機能: Comic Creator「半自動マンガ作成」向けブリッジ（LLMプロンプト下書き・バッチ画像生成）
+- **v0.3.79** — 追加機能: サイドパネル（Workflow Studio Library）IタブのMage-Flow等サブグラフワークフロー対応
+- **v0.3.78** — 追加機能: Eagle自動保存のSVG対応
+- **v0.3.76** — 追加機能: Comic Creator向けI2I実行ブリッジ`_wfmReceiveI2IRunRequest`
+- **v0.3.77** — 追加機能: GalleryタブでSVGファイルの表示・管理に対応
+- **v0.3.75** — Lemonadeバックエンド追加(3つ目のAIバックエンド)
+- **v0.3.74** — AI TOOL Chatペインの画像添付対応 + I2I連携
+- **v0.3.73** — AI TOOL Chatペインからの対話式画像生成（Tool Calling）＋ Checkpoint関連の安全策
+- **v0.3.72** — Comic Creator連携用の外部Inpaintエントリポイントを追加
+- **v0.3.71** — Inpaint機能の追加（GenerateUI Imageタブ + Image Edit「Inpaint」タブ）
+- **v0.3.70** — Workflow AI要約: Ollama 404エラー修正
+- **v0.3.69** — Gallery → ComfyUI Comic Creator 連携（Send CC ボタン）
+- **v0.3.68** — MASK EDITOR ONE セクション常時表示化
+- **v0.3.67** — Alt+Click Apply & Generate
+- **計画: Image Edit 拡張 — ABRブラシ連携 + Mask Editor One 統合** — フェーズ1: Draw ツール — ABRブラシ対応
+- **2026-06-29: v0.3.66 — Mask ツール 5サブツール追加（Color / Alpha / Text / Vector / Shape）・Support リンク追加** — 概要
+- **2026-06-29: v0.3.65 — Mask Editor One 連携修正・トップバーアイコン修正・Mask ABRブラシ対応** — 概要
+- **2026-06-28: v0.3.64 — Image Edit マスク Add/Subtract・BiRefNet BG Remove・SAM3 セグメンテーション・ブラシカーソルバグ修正** — 概要
+- **2026-06-28: v0.3.63 — ノードタブ複数選択・全タブフィルタークリア・検索Xボタン** — 概要
+- **2026-06-27: WFS_PromptText の GenerateUI 対応・ドロップ時 title 固定** — 概要
+- **2026-06-27: v0.3.62 — Send GenUI Image ボタン追加・tagger_settings.json バグ修正・README 更新** — 概要
+- **2026-06-27: データ管理バグ修正 — tagger_settings.json をエクスポート対象に追加** — 概要
+- **2026-06-27: v0.3.61 — G'MIC バグ修正・セキュリティ・Draw/Mask ブラシ操作性改善** — 概要
+- **2026-06-27: v0.3.60 — Image Edit Filter Tool (G'MIC-Qt 連携) 実装** — 概要
+- **2026-06-27: v0.3.59 — Image Edit Mask Tool 実装・Draw/Mask 描画バグ修正・クリッピング保存対応** — 概要
+- **2026-06-27: v0.3.58 — GenerateUI Model タブ GGUF対応拡張（Diffusion Model / Text Encoder）** — 概要
+- **2026-06-26: v0.3.57 — Image Edit Blur Tool / BG Remove Tool 追加** — 概要
+- **2026-06-26: v0.3.56 — Style機能追加（GenerateUI ツールバー & Batchタブ）** — 概要
+- **2026-06-25: v0.3.55 — グループ機能バグ修正（全タブ）** — 根本原因（データ消失）: パス区切り文字の不一致
+- **2026-06-25: v0.3.54 — Image Edit Shape ツール追加・Models タブ overlay バグ修正** — Image Edit Tab — Shape ツール（□ / S キー）
+- **2026-06-25: v0.3.53 — Image Edit Tab 実装・レイヤーロック・ギャラリー保存** — Image Edit Tab（新規タブ）
+- **2026-06-25: GenUI設定タブ LATENT IMAGE にプリセット機能を追加** — 変更内容
+- **2026-06-24: GenUI ModelでLoRA適用後、Modelサブタブ再表示時に値がリセットされるバグ修正** — 問題
+- **2026-06-24: v0.3.51 — Embedding GenUI PP/NP対応 + GenerateUIプロンプトタブEmbeddingセレクタ追加** — 変更内容
+- **2026-06-24: v0.3.51 — GenerateUIタブ Hypernetwork対応 + ModelsタブGenUI Modelボタン追加** — 変更内容
+- **2026-06-24: v0.3.51 — Hypernetwork/Embeddingモデル未表示バグ修正** — 原因
+- **2026-06-24: v0.3.51 — ModelsタブサイドパネルにGenUI Modelボタン追加** — 変更内容
+- **2026-06-22: v0.3.50 — ギャラリータブ プロンプト検索負荷改善（バックグラウンドインデックス）** — 問題
+- **2026-06-22: v0.3.49 — 生成UIタブ A1111風ワイルドカード展開・ギャラリータブ バグ修正2件** — 生成UIタブ — A1111風SPAサイドワイルドカード展開
+- **2026-06-22: v0.3.48 — ギャラリータブ 画像ダウンロード・一括エクスポート機能追加** — 詳細パネルの画像プレビューにダウンロード機能を追加
+- **2026-06-22: v0.3.47 — モデルタブ ファイル移動後グループ状態修正** — モデル移動後のグループ状態不整合を修正
+- **2026-06-21: v0.3.46 — プロンプトタブ AI Assistant LM Studio対応・設定タブ AI Assistant設定に変更** — 設定タブ「AI Assistant設定（プロンプトタブ）」
+- **2026-06-21: v0.3.45 — グループ孤立エントリ自動クリーンアップ・Galleryタブ Shift+クリック範囲選択** — グループ孤立エントリ自動クリーンアップ
+- **2026-06-21: v0.3.44 — Galleryタブ高速化・比較モード・バルク強化・バルクバーUI整理** — フェーズ2-A: サーバーサイドサムネイル生成
+- **2026-06-21: ヘルプタブ改善 — Gallery mode 多言語対応・フォント拡大・検索機能追加** — Gallery mode の多言語対応
+- **2026-06-21: Send to Canvas — window.opener経由のキャンバス直接ロード対応**
+- **2026-06-20: API形式ワークフローのキャンバス読み込み修正・画像メタデータ埋め込み修正** — API形式ワークフローをキャンバスへドラッグすると空になる問題を修正
+- **2026-06-20: セキュリティ修正（XSS・パスバリデーション）** — 修正内容
+- **2026-06-20: WFS_GalleryFeeder — ComfyUI キャンバス上コントロール追加** — 新規ファイル（`web/comfyui/gallery_feeder_extension.js`）
+- **2026-06-20: __Feeder__ グループ保護 + サムネイル F ボタン + seed バグ修正** — `__Feeder__` グループの予約済み保護
+- **2026-06-20: Gallery Feeder 機能追加（WFS_GalleryFeeder ノード）** — 概要
+- **2026-06-19: Generate UI — ImpactWildcardEncode/Processor プロンプト検出バグ修正（v0.3.41）** — 修正内容（`static/js/comfyui-workflow.js`）
+- **2026-06-19: AI TOOL タブ Chat ペイン・ワイルドカード生成追加（v0.3.40）** — Chat ペイン（`templates/index.html`, `static/css/main.css`, `static/js/ai-tab.js`, `web/comfyui/node_sets_menu.js`）
+- **2026-06-18: Send to Canvas機能追加（ワークフロータブ・ギャラリータブ→LibraryタイトルDnD）** — ワークフロータブ — Send to Canvas（`static/js/workflow-tab.js`, `static/js/app.js`, `templates/index.html`）
+- **2026-06-15: TaggerシングルGenUI:Pボタン追加＋生成UIのZITワークフロープロンプト解析修正** — TaggerシングルGenUI:Pボタン（`templates/index.html`, `static/js/tagger-tab.js`, `static/js/i18n.js`）
+- **2026-06-15: Taggerバッチ.txt出力追加＋Galleryタグ保存バグ修正** — Taggerバッチ.txt出力（`templates/index.html`, `static/js/tagger-tab.js`, `static/js/i18n.js`, `py/routes/tagger_routes.py`, `py/services/tagger_service.py`）
+- **2026-06-15: Taggerタブ新規実装＋ギャラリー詳細パネルUI改善＋パストラバーサル修正** — Taggerタブ新規実装
+- **2026-06-15: 全選択ボタン追加＋ギャラリーバルクバーi18n対応** — 変更内容
+- **2026-06-10: v0.3.36 — コードレビュー修正＋リファクタリング＋README刷新** — コードレビュー修正（v0.3.35の不具合10件）
+- **2026-06-10: v0.3.35 — テーブルソート・Load GenUI・ワークフロー保存** — 変更内容
+- **2026-06-09: v0.3.34 — Modelsタブ テーブルビュー強化・バルク操作改善** — 変更内容
+- **2026-06-09: v0.3.33 — LoRAペイン・ワークフロー解析バグ修正** — 変更内容
+- **2026-06-08: v0.3.32 — Lora Loader (LoraManager) LoRA検出対応・ライブラリ機能拡張** — 変更内容
+- **2026-06-08: v0.3.31 — LoRAペイン Single/Stack タブ分割・GenUI Model LoRA対応強化** — 変更内容
+- **2026-06-08: v0.3.30 — LoRAスタック トリガーワードバグ修正・ヘルプ更新** — 変更内容
+- **2026-06-08: v0.3.29 — LoRAセクション統合・ヘルプタブサイドバー・UI細部改善** — 変更内容
+- **2026-06-08: 生成UIタブ 複数改善 — LoRA Stackトリガーワード連携・Reset Workflowボタン・Inputタブタブ化** — 変更内容
+- **2026-06-08: Feederタブ UI改善 — (root)自動選択・PREVIEWペイン右移動・RUN中プレビュー反映** — 変更内容
+- **2026-06-07: v0.3.28 — Batchタブ Sampler/Scheduler対応 + Modelsサムネイルバグ修正** — 概要
+- **2026-06-07: v0.3.27 — model-and-prompt-from-metadata カスタムノード対応 + README修正** — 概要
+- **2026-06-07: v0.3.26 — Stack LORA SYNTAX 表示修正 + 全体強度調整 UI** — 概要
+- **2026-06-07: v0.3.25 — Lora Loader (LoraManager) 対応 + Stack 有効無効切り替え** — 概要
+- **2026-06-06: v0.3.24 — Lora Stack 登録機能 + 生成UI Model タブ 3ペイン化** — 概要
+- **2026-06-05: v0.3.23 — バグ修正2件** — バグ修正
+- **2026-06-05: v0.3.22 — カードビュー廃止 + Batch タイプ切り替え UI + 4タイプバッチ生成** — 概要
+- **2026-06-05: (未リリース) — 生成UIタブ Batch 4タイプ対応（Lora/Prompt/Workflow グループ選択 + BATCH QUEUE 4列化）** — 概要
+- **2026-06-05: (未リリース) — Prompt・Workflow Batchグループ登録UI** — 概要
+- **2026-06-04: (未リリース) — モデルBatchグループ登録UI（サムネイル/カード/テーブル・フィルター・一括解除）** — 概要
+- **2026-06-04: (未リリース) — Batch予約グループ・Presets Save後リセット・グループフィルター種別絞り込み** — 概要
+- **2026-05-31: v0.3.21 — CivitAI ホスト設定・Sample サブタブ・URL 修正・ヘルプ i18n 整備** — 概要
+- **2026-05-31: v0.3.20 — CivitAI 詳細パネル強化（Type / Hash 表示・URL 修正・画像別タブ）** — 概要
+- **2026-05-31: v0.3.19 — CivitAI 連携強化（バッチ高速化・リトライ・APIキー・フィールド拡充）** — 概要
+- **2026-05-31: v0.3.18 — Batch タブ追加・Models 複数選択強化** — 概要
+- **2026-05-31: v0.3.17 patch — SSLコンテキスト セキュリティ強化** — 概要
+- **2026-05-30: v0.3.17 — SSL証明書エラー修正・Lora Manager対応** — 概要
+- **2026-05-20: v0.3.16 — CivitAIプレビューフォールバック表示** — 概要
+- **2026-05-20: v0.3.15 — サンプルワークフロー同梱・CivitAI自動プレビュー・Create Tagsオプション** — 概要
+- **2026-05-20: AI TOOL タブ 英語化（SPA・Libraryパネル）** — 概要
+- **2026-05-19: v0.3.14 — AI TOOL タブ 3ペイン化・RAW JSON 文字色カスタマイズ** — 概要
+- **2026-05-19: v0.3.13 — AI タブ（A）追加** — 概要
+- **2026-05-18: v0.3.12 リリース — README スクリーンショット刷新 / workflow_analyzer 拡張** — 概要
+- **2026-05-17: RAW JSON パネルに検索機能を追加** — 概要
+- **2026-05-17: v0.3.11 Metadata タブ対応ノードタイプ拡張 / Settings テキストサイズ UI 追加** — 概要
+- **2026-05-17: v0.3.10 Information タブ キャンバスドラッグ対応 / ノードタイプ拡張 / バグ修正** — 概要
+- **2026-05-16: v0.3.9 サイドパネル I タブ追加 / トップバーアイコン修正** — 概要
+- **2026-05-16: v0.3.8 Metadata タブ: data9 対応 / プロンプト判別不能テキスト** — 概要
+- **2026-05-15: v0.3.7 Metadata タブ: Flux2 / Qwen / Z-Image 対応** — 概要
+- **2026-05-15: v0.3.6 Metadata タブ追加** — 概要
+- **2026-05-09: v0.3.5 GenerateUI — Feeder サブタブ・ワークフロー解析精度向上** — 概要
+- **2026-04-29: v0.3.4 GenerateUI — Checkpoint Batch 刷新・Settings 横並びレイアウト・ヘルプ i18n 修正** — 概要
+- **2026-04-28: v0.3.3 Promptタブ — ワイルドカード支援パネル・Impact Packシンボリックリンク連携・サブディレクトリ対応・GenerateUI修正** — 概要
+- **2026-04-28: v0.3.2 生成UIタブ — Checkpoint Batch・Seed UIレイアウト修正** — 概要
+- **2026-04-27: v0.3.1 ギャラリー拡張（フォルダ/ファイル操作・ワークフロー保存）** — 概要
+- **2026-04-18: v0.3.0 モデルグループ表示改善（全タイプ横断・サイドパネル修正）** — 概要
+- **2026-04-18: v0.2.9 モデル有効/無効・複数選択・一括削除** — 概要
+- **2026-04-14: v0.2.8 データ保存先変更・エクスポート/インポート機能追加** — 概要
+- **2026-04-06: v0.2.6 UI改善・バッジ保存修正・フォルダフィルター追加** — 概要
+- **2026-04-04: v0.2.5 追加修正** — 概要
+- **2026-04-03: v0.2.5 サイドパネル Category/Package サブタブ・テーマ設定・Workflow修正** — 概要
+- **2026-03-29: v0.2.4 GenerateUIタブ レイアウト再設計** — 概要
+- **2026-03-29: v0.2.3 バッジ統一・GenUI Model・サイドパネルModels拡充** — 概要
+- **2026-03-28: v0.2.2 Modelsタブ・CivitAI連携** — 概要
+- **2026-03-27: テーマカスタマイズ機能・設定タブ改善** — 概要
+- **2026-03-26: トップバーボタンアイコン修正・Appモードバッジ調査** — 概要
+- **2026-03-25: v0.2.0 プロンプトプリセット機能・Workflow Studio Library** — 概要
+- **2026-03-24: v0.1.9 サイドパネルUI改善・保存ダイアログ・バグ修正** — 概要
+- **2026-03-24: v0.1.8 WF & Node Library サイドパネル拡張** — 概要
+- **2026-03-23: v0.1.7 Nodes タブ追加** — 概要
+- **2026-03-23: v0.1.6 パストラバーサル脆弱性修正** — 概要
+- **2026-03-22: v0.1.5 テーマシステム追加** — 概要
+- **2026-03-22: v0.1.4 App形式対応・プリセットコピー・分析バグ修正** — 概要
+- **2026-03-21: v0.1.3 ヘルプ＆サポートタブ追加** — 概要
+- **2026-03-19: v0.1.2 リリース** — 概要
+- **2026-03-19: v0.1.1 リリース** — 概要
+- **2026-03-18: プロジェクトリネーム & アイコン適用** — 概要
+- **2026-03-18: デフォルトビュー設定追加** — 概要
+- **2026-03-18: MarkdownNote表示専用ノード除外** — 概要
+- **2026-03-18: サブグラフワークフロー対応 & 変換精度修正** — 概要
+- **2026-03-18: Raw JSON同期修正** — 概要
+- **プロジェクト構成 (現在)**
+- **2026-03-18: JSONシンタックスハイライト** — 概要
+- **2026-03-18: プロンプトタブ 中国語↔英語翻訳追加** — 概要
+- **2026-03-18: v0.1.0 リリース** — 概要
+- **2026-04-13: Gallery タブ追加 & 全タブ Group UI 統一** — 概要
@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2026 ketle-man
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
@@ -0,0 +1,262 @@
+# README Index — ComfyUI-Workflow-Studio
+
+Condensed index of README.md: intro summary, feature names per tab (full descriptions live in the excluded README.md), and the installation/usage/requirements/project-structure sections verbatim. Exists so graphify can extract this without feeding the full README (with its screenshot table) to the local Ollama model. Regenerate with `python tools/generate_doc_index.py readme` whenever README.md changes.
+
+# ComfyUI-Workflow-Studio
+
+A comprehensive workflow, asset management, and generation UI plugin for [ComfyUI](https://github.com/comfyanonymous/ComfyUI).
+
+**📁 Management** — organize all your assets in one studio
+
+- Workflow, model, image, and prompt management
+- AI-powered prompt writing assistance, translation, and tag generation
+- File drop & Gallery-linked metadata viewing — inspect and reuse generation settings instantly
+
+**⚡ GenerateUI** — a productivity-focused generation tab connected to every other tab
+
+- Batch generation across models, samplers, prompts, and workflows
+- Image Feeder for continuous folder-based generation
+- Lab: experimental I2I batch generation with independent per-iteration keyframes for Model (Checkpoint/LoRA Single/VAE)/Prompt/KSampler
+
+**📚 Workflow Studio Library** — a multi-function side panel for smooth ComfyUI integration
+
+- Drag & drop models, nodes, prompts, and workflows straight onto the canvas
+- **Send to Canvas**: click "Send to Canvas" (Workflow tab) or "Copy & Send Canvas" (Gallery tab) to send the workflow directly to the ComfyUI canvas — UI and API formats both supported
+- View metadata from images / JSON, then drop the detected models and prompts onto the canvas
+- Built-in AI tools (translation and more)
+
+![Workflow Studio](https://img.shields.io/badge/ComfyUI-Custom_Node-blue)
+![Version](https://img.shields.io/badge/version-0.7.2-green)
+
+## Features (tab -> feature names)
+
+### Workflow Tab
+Thumbnail / Table views, Thumbnail side panel, Badge filtering, Search, Side panel tabs, Badge management, AI summary, Import / Export, Side panel toolbar buttons, Default view setting, Search clear (✕), Clear all filters (✕ Clear), Sort
+
+### Canvas Snapshot (v0.1.2)
+One-click capture, Auto-save as thumbnail, Embedded workflow metadata, Auto-import
+
+### GenerateUI Tab (v0.3.5)
+6-tab layout, Save button, Input tab, Model tab, Settings tab, Always-visible Raw JSON, Bypass/Mute node handling, One-click generation, Seed control, Style selector, Create Catalog / Catalog buttons, Batch type selector, Batch tab, UI-to-API conversion, Video workflow support, Eagle integration, Qwen Image 2.1 support
+
+### Feeder subtab (v0.3.5 / v0.3.42)
+ImageFeeder node control, Image library, Selection management, Presets, Continuous Run loop, Index sync, Seed, WFS_GalleryFeeder node, Node & group selector, Image grid, After Gen modes, Run / Stop controls
+
+### Lab subtab (v0.3.87 – v0.5.2)
+Setting / Results / Plan JSON sub-panels, Per-column keyframes, Model column — Checkpoint / LoRA Single / VAE, Empty state when no matching node exists, Wildcards, Prompt cell extras, Keyframe #1 live-reflect, Bypass checkbox, LoRA node bypass & prompt injection, T2I workflow support, Use generated image for next, Workflow recall, Plan files, Plan Load, Plan JSON tab, Save index image to Output on Run, Index images are self-contained plan files, Eagle integration, Select vs. edit, and keyframe reordering, PG — apply a Prompt tab preset group, Video workflow support, Use generated image for next, now video-aware
+
+### Prompt Tab
+3-column layout, AI chat assistant, Image attachment, Translation, Prompt presets, Preset Manager, Group management, Clipboard copy, GenUI Set, Wildcard/Style tab bar, Wildcard input toolbar, Wildcard file manager, Style manager, Form / Table toggle, Table view — Presets / Presets Group / Wildcards / Style
+
+### Settings Tab
+2-column layout, Collapsible sections, Theme selection, Theme customization, Workflows directory, Gallery output directory, Eagle connection, CivitAI Host, CivitAI API Key, Default workflow, Default Checkpoint, Video Playback Volume, Data Management, Text Size, RAW JSON Colors, GenerateUI Model Tab Highlight, Wildcard Integration, G'MIC-Qt Integration, Language
+
+### Gallery Tab (v0.3.44)
+Output / ImagePrompt / Style_Catalog / Metadata sub-tabs, Image browser, Folder tree root label, Thumbnail / Table views, Folder management, File operations, Download, MP4 video support, MP4 embedded metadata, Info tab: dimensions & duration, Multi-select, Image Compare, Prompt search, Server-side filtering, Group management, Thumbnail F button, Favorites, Detail panel, Prompt tab, Workflow viewer, GenUI button, Image Edit button, Send GenUI Image button, Send to LI node button, Send CC button, Search clear (✕), Clear all filters (✕ Clear), Workflow auto-save, Output folder configurable, SVG file support, PSD file support, Performance
+
+### ImagePrompt Gallery subtab (v0.3.94, renamed from Style/Prompt in v0.3.95)
+Visual prompt library, 3-column layout, Prompt builder (right pane), Plain-text prompt storage, ponyxlWildcardsVault format support, Seed data importer
+
+### Style_Catalog Gallery subtab (v0.3.95)
+Visual Style picker, 3-column layout, Positive/Negative panel, Select as Style button, Load in GenerateUI / Open in Metadata Tab buttons, Double-click to enlarge
+
+### Metadata Gallery subtab (v0.3.8, moved from a top-level tab in v0.4.6)
+Now inside Gallery, 3-column layout, File drop, MP4 embedded metadata, Model extraction, LoRA extraction, Prompt extraction, Prompt actions, Format support, Format note
+
+### Nodes Tab (v0.1.7)
+Node Browser, Search & Filter, Package badges, Node detail panel, Node Sets, Right-click context menu, Multi-select, Search clear (✕), Clear all filters (✕ Clear)
+
+### Models Tab (v0.2.3)
+Model Browser, Thumbnail / Table views, Table column sort, Search & Filter, User-defined badges, Side panel tabs, CivitAI integration, CivitAI panel — Info / Sample sub-tabs, CivitAI panel states, Batch CivitAI fetch, Detail modal, GenUI Model button, Group management, Table view memo, Preview images, Enable / Disable models, Multi-select & bulk operations, Search clear (✕), Clear all filters (✕ Clear)
+
+### Tagger Tab (v0.3.38)
+3 sub-tabs, Model support, Threshold sliders, VLM tagging, Single tab, Single output options, Batch tab, DB tab, Dependencies
+
+### Image Edit Tab (v0.3.65)
+Layer-based image editor, Loading images, Open PSD button, Close button, New button, Tools, Layer panel, Duplicate layer (⧉), Layer lock, Text quality, Export, Canvas navigation, Undo / Redo
+
+### Video Tab (v0.5.0 – v0.7.4)
+Dedicated video generation UI, independent of GenerateUI, Plan subtab, Base settings row, Edit subtab, Edit: Audio / BGM, Edit: Text overlays, Edit: Crop, Edit: Undo / Redo, Edit project persistence, Asset subtab, Project subtab, Two center previews, First Frame / Last Frame are both optional, Semantic node lookup, not hardcoded IDs, Field highlight color, Load in Video, Frame tab, GIF tab, Playback volume
+
+### AI TOOL Tab (v0.3.14)
+4-pane layout, Translation pane, Chat pane, Chat pane — image generation via Tool Calling, Chat pane — generate_image extra parameters, TOOLS pane (VLM), TOOLS pane — shared Chat attachment, TOOLS pane (Wildcards), Chat pane — image-to-image (I2I), Chat pane — SVG generation, no ComfyUI workflow involved, Chat pane — Skills, Settings pane, Unsloth backend, Settings pane — Chat Image Generation, Settings pane — Chat I2I Generation, Settings pane — Generation, Model unload, Settings shared, Backend support, URL security, Lemonade's other endpoints (not integrated)
+
+### Workflow Studio Library (ComfyUI Side Panel) (v0.3.9)
+Tab layout (W / N / P / M / I / A), W — Workflows tab, N — Nodes tab, M — Models tab, P — Prompts tab, I — Information tab, A — AI TOOL tab, Drag & drop workflows, Drag & drop nodes, Drag & drop prompts, Send to Canvas, Copy prompts, Double-click, Search, ⚙ Theme settings
+
+### Help &amp; Support Tab (v0.1.3)
+Sidebar navigation, Support, Feature list, Keyboard Shortcuts
+
+## Installation
+
+### Via ComfyUI Manager (Recommended)
+
+Search for **Workflow Studio** in ComfyUI Manager and install.
+
+### Manual Installation
+
+```bash
+cd ComfyUI/custom_nodes
+git clone https://github.com/ketle-man/ComfyUI-Workflow-Studio.git
+```
+
+Restart ComfyUI after installation.
+
+---
+
+## Sample Workflows
+
+Sample workflows are included in the `workflows/` folder. You can open them directly in ComfyUI via drag & drop, or load them from the Workflow tab.
+
+> **Note:** Some sample workflows require additional custom nodes.
+> If a node is shown as missing (red/unknown) after loading, install the required custom nodes via **ComfyUI Manager** or by cloning the repository from GitHub into your `ComfyUI/custom_nodes/` directory.
+>
+> ```bash
+> cd ComfyUI/custom_nodes
+> git clone <repository-url>
+> ```
+>
+> After installation, restart ComfyUI to activate the new nodes.
+
+---
+
+## Usage
+
+### Launch
+
+Click the **W** button in the ComfyUI top menu bar, or navigate to:
+
+```
+http://127.0.0.1:8188/wfm
+```
+
+> **Tip:** Shift+Click the W button to open in a new window.
+
+### Canvas Snapshot
+
+Click the **camera icon** (next to the W button) in ComfyUI's top bar to capture the current workflow canvas as a thumbnail. The image is automatically saved to the workflow data folder and appears in Workflow Studio's workflow list.
+
+### Quick Start
+
+1. **Workflow Tab** — Your workflows from `ComfyUI/user/default/workflows/` are automatically listed
+2. **Click a workflow** — View thumbnail, JSON details, and metadata in the side panel
+3. **Load in GenerateUI** — Click the button to load a workflow into the generation interface
+4. **Adjust parameters** — Modify prompts, models, seeds, and settings via the auto-generated UI
+5. **Generate** — Hit the Generate button to queue the prompt
+
+---
+
+## Requirements
+
+- **ComfyUI** — any recent version (v1.33.9+ recommended for action bar integration)
+- **Python 3.10+**
+- **Jinja2** — `pip install jinja2` (usually included with ComfyUI)
+
+### Optional
+
+- **[Ollama](https://ollama.com/)** — for AI chat assistant, translation, and VLM features
+- **[LM Studio](https://lmstudio.ai/)** — alternative backend for translation and VLM (OpenAI-compatible API)
+- **[Lemonade Server](https://lemonade-server.ai/)** — alternative backend for translation, chat, and VLM (OpenAI-compatible API)
+- **[Unsloth](https://unsloth.ai/)** — alternative backend for translation, chat, and VLM (OpenAI-compatible API); always requires an API key, set via `UNSLOTH_API_KEY` in a `.env` file — `pip install -r requirements.txt` for `python-dotenv`
+- **[Eagle](https://eagle.cool/)** — for auto-saving generated images with metadata
+- **[comfyui-mask-editor-one](https://github.com/ketle-man/comfyui-mask-editor-one) (v0.1.9+)** — enables BiRefNet background removal, SAM3 text-prompt segmentation, and ABR stamp-brush library in the Image Edit Mask tool; `birefnet.safetensors` must be placed in `ComfyUI/models/background_removal/` for BiRefNet
+- **[psd-tools](https://pypi.org/project/psd-tools/)** (v0.6.0) — enables all PSD (Photoshop) features: Gallery bulk "Create PSD" export, Gallery browsing/thumbnails for `.psd` files, and Image Edit's Save PSD / Open PSD buttons; `pip install -r requirements.txt` (ships prebuilt wheels, no C compiler required); without it, PSD-related actions show an error toast with the install command instead of failing silently
+
+---
+
+## Supported Languages
+
+| Language | Status |
+| -------- | ------ |
+| English  | Full   |
+| Japanese | Full   |
+| Chinese  | Full   |
+
+---
+
+## Project Structure
+
+```
+ComfyUI-Workflow-Studio/
+├── __init__.py                  # ComfyUI entry point
+├── py/
+│   ├── wfm.py                   # Main class & route registration
+│   ├── config.py                # Path configuration
+│   ├── nodes/
+│   │   ├── prompt_text.py       # WFS_PromptText custom node (positive/negative prompt)
+│   │   └── gallery_feeder_node.py  # WFS_GalleryFeeder custom node (gallery group → IMAGE)
+│   ├── routes/
+│   │   ├── workflow_routes.py   # Workflow CRUD & analysis API
+│   │   ├── nodes_routes.py      # Nodes metadata & node sets API
+│   │   ├── models_routes.py     # Model metadata, preview, CivitAI API
+│   │   ├── prompts_routes.py    # Prompt presets CRUD API
+│   │   ├── settings_routes.py   # Settings API
+│   │   ├── ollama_routes.py     # Ollama proxy API
+│   │   ├── eagle_routes.py      # Eagle integration API
+│   │   └── gallery_routes.py    # Gallery tab API (Output + ImagePrompt + Style_Catalog sub-tabs)
+│   └── services/
+│       ├── workflow_service.py  # Workflow file operations
+│       ├── nodes_service.py     # Node metadata & node sets
+│       ├── models_service.py    # Model metadata & preview images
+│       ├── civitai_service.py   # CivitAI API integration & cache
+│       ├── prompts_service.py   # Prompt presets persistence
+│       ├── workflow_analyzer.py # Model/node detection
+│       ├── settings_service.py  # Settings persistence
+│       ├── png_extractor.py     # PNG metadata extraction
+│       ├── gallery_service.py   # Gallery image scanning, .txt sidecar & ponyxlWildcardsVault prompt resolution
+│       └── gallery_metadata.py  # Gallery per-image metadata store (favorites/tags/memo/groups)
+├── templates/
+│   └── index.html               # SPA template (Workflow/GenerateUI/Prompt/Metadata/Gallery/Nodes/Models/Settings/Help/AI)
+├── static/
+│   ├── favicon.svg              # Browser tab icon (W+S Wave)
+│   ├── css/main.css             # Styles
+│   └── js/
+│       ├── app.js               # App initialization & routing
+│       ├── workflow-tab.js      # Workflow browser
+│       ├── generate-tab.js      # Generation UI
+│       ├── feeder-tab.js        # Feeder subtab (Image Loop + Gallery modes)
+│       ├── gallery-tab.js       # Gallery tab: Output sub-tab (image browser, groups, metadata) + sub-tab switching
+│       ├── image-prompt-tab.js  # Gallery tab: ImagePrompt sub-tab (visual prompt builder)
+│       ├── style-catalog-tab.js # Gallery tab: Style_Catalog sub-tab (visual Style picker)
+│       ├── tagger-tab.js        # Tagger tab (WD Tagger, DeepDanbooru, Ollama VLM)
+│       ├── prompt-tab.js        # AI assistant & presets
+│       ├── metadata-tab.js      # Metadata extraction & display (PNG/WebP/JSON)
+│       ├── settings-tab.js      # Settings panel
+│       ├── comfyui-client.js    # ComfyUI WebSocket/API client
+│       ├── nodes-tab.js          # Node browser & node sets
+│       ├── models-tab.js         # Model browser & CivitAI integration
+│       ├── ai-tab.js             # AI TOOL tab (Translation | Chat | TOOLS/VLM | Settings)
+│       ├── comfyui-workflow.js  # UI-to-API format conversion
+│       ├── comfyui-editor.js    # Dynamic parameter editor
+│       ├── json-highlight.js    # JSON syntax highlighting
+│       ├── util.js              # Shared utilities (escapeHtml, readJsonStorage, getSettings)
+│       └── i18n.js              # Internationalization
+├── web/comfyui/
+│   ├── top_menu_extension.js    # ComfyUI menu bar integration
+│   ├── node_sets_menu.js        # Workflow Studio Library side panel
+│   └── gallery_feeder_extension.js  # WFS_GalleryFeeder canvas widgets (After Gen / Run / Stop)
+├── tools/
+│   └── import_style_prompt_seed.py  # Dev tool: pre-process a wildcards-vault source into ws_image_prompt (not run by the plugin itself)
+└── data/                        # Fallback data dir (used when ComfyUI user/default/ is not found)
+```
+
+---
+
+## License
+
+MIT License
+
+---
+
+## Acknowledgements
+
+- [ComfyUI](https://github.com/comfyanonymous/ComfyUI) by comfyanonymous
+- [ComfyUI-Custom-Scripts](https://github.com/pythongosssss/ComfyUI-Custom-Scripts) by pythongosssss — Canvas snapshot and PNG workflow embedding implementation reference
+- [ComfyUI-Lora-Manager](https://github.com/willmiao/ComfyUI-Lora-Manager) — Plugin architecture and UI pattern reference
+- [Ollama](https://ollama.com/) for local LLM inference
+- [Eagle](https://eagle.cool/) for image management
+- [Pillow (PIL Fork)](https://python-pillow.org/) — server-side thumbnail generation (`data/thumb_cache/`)
+- [ComfyUI-Gallery](https://github.com/PanicTitan/ComfyUI-Gallery) by PanicTitan — thumbnail grid UX reference
+- [infinite-image-browsing](https://github.com/zanllp/sd-webui-infinite-image-browsing) by zanllp — thumbnail caching and index strategy reference
+- [Fooocus](https://github.com/lllyasviel/Fooocus) by lllyasviel — style preset JSON format reference
+
@@ -0,0 +1,24 @@
+"""Runs before ComfyUI imports any custom node — the only place early enough
+to populate os.environ for code that reads env vars at import/request time.
+
+Loads a .env file (if present) from this plugin's root directory so the
+Unsloth backend's API key (UNSLOTH_API_KEY) can be set without editing
+settings.json or exposing it to the frontend.
+"""
+
+from pathlib import Path
+
+PLUGIN_DIR = Path(__file__).resolve().parent
+ENV_FILE = PLUGIN_DIR / ".env"
+
+if ENV_FILE.exists():
+    try:
+        from dotenv import load_dotenv
+        load_dotenv(ENV_FILE)
+    except ImportError:
+        print(
+            "[WARNING] Workflow Studio: .env file found but python-dotenv is not installed "
+            "(pip install -r requirements.txt). UNSLOTH_API_KEY will not be loaded from .env."
+        )
+    except Exception as e:
+        print(f"[WARNING] Workflow Studio: failed to load .env file: {e}")
@@ -69,6 +69,10 @@ NODE_SETS_FILE = DATA_DIR / "node_sets.json"
 PROMPTS_FILE = DATA_DIR / "prompts.json"
 MODEL_METADATA_FILE = DATA_DIR / "model_metadata.json"
 WILDCARD_DIR = DATA_DIR / "wildcard"
+AI_SKILLS_DIR = DATA_DIR / "ai_skills"
+LAB_PLAN_DIR = DATA_DIR / "lab_plan"
+VIDEO_PLAN_DIR = DATA_DIR / "video_plan"
+VIDEO_EDIT_PROJECT_DIR = DATA_DIR / "video_edit_project"

 # Tagger
 TAGGER_DB_FILE = DATA_DIR / "tagger.db"
@@ -3,6 +3,7 @@
 import asyncio
 import json
 import logging
+import os
 import urllib.request
 import urllib.error

@@ -17,6 +18,84 @@ def setup_routes(app: web.Application):
    app.router.add_post("/api/wfm/eagle/test", handle_test)


+def _resolve_local_path(filename, subfolder, type_name):
+    """filename/subfolder/type を ComfyUI 出力ディレクトリ上の実パスに解決する。
+    ComfyUI と Eagle が同一マシン上で動作している場合のみ有効なパスが返る
+    (別マシンの場合は None を返し、呼び出し側は addFromURL にフォールバックする)。"""
+    try:
+        import folder_paths  # type: ignore
+    except Exception:
+        return None
+
+    base_dir = folder_paths.get_directory_by_type(type_name or "output")
+    if not base_dir:
+        return None
+    base_dir = os.path.abspath(base_dir)
+
+    filename = os.path.basename(filename or "")
+    if not filename:
+        return None
+
+    full_dir = os.path.abspath(os.path.join(base_dir, subfolder or ""))
+    # Windowsはパス比較で大文字小文字を区別しないため normcase で正規化してから比較する
+    if os.path.commonpath((os.path.normcase(full_dir), os.path.normcase(base_dir))) != os.path.normcase(base_dir):
+        # ディレクトリトラバーサル対策: base_dir 配下以外は拒否
+        return None
+
+    full_path = os.path.join(full_dir, filename)
+    if not os.path.isfile(full_path):
+        return None
+    return full_path
+
+
+def _resolve_absolute_svg_path(abs_path):
+    """comfyui-tosvg の Save SVG String ノードなどが返す絶対パスを検証する。
+    ComfyUI管理下(output/input/temp)ディレクトリ配下の実在する .svg ファイルのみ許可する
+    (任意の絶対パスをそのまま信頼すると、外部からこのAPIを叩かれた際に
+    ローカルの任意ファイルを送信させられてしまうため)。"""
+    if not abs_path or not abs_path.lower().endswith(".svg"):
+        return None
+    try:
+        import folder_paths  # type: ignore
+    except Exception:
+        return None
+
+    abs_path = os.path.abspath(abs_path)
+    if not os.path.isfile(abs_path):
+        return None
+
+    for type_name in ("output", "temp", "input"):
+        base_dir = folder_paths.get_directory_by_type(type_name)
+        if not base_dir:
+            continue
+        base_dir = os.path.abspath(base_dir)
+        try:
+            # Windowsはパス比較で大文字小文字を区別しないため normcase で正規化してから比較する
+            if os.path.commonpath((os.path.normcase(abs_path), os.path.normcase(base_dir))) == os.path.normcase(base_dir):
+                return abs_path
+        except ValueError:
+            # Windowsで異なるドライブレターの場合 commonpath が例外を投げる
+            continue
+    return None
+
+
+def _eagle_add_from_path(eagle_url, file_path, name, tags):
+    """Proxy request to Eagle's addFromPath API (runs in thread).
+    SVG は ComfyUI の /view がセキュリティ上 application/octet-stream +
+    attachment で返すため、addFromURL 経由だと正しい種別で保存されないことがある。
+    ComfyUI と Eagle が同一マシン上にある場合はローカルパスを直接渡す方が確実。"""
+    eagle_url = eagle_url.rstrip("/")
+    payload = json.dumps({"path": file_path, "name": name, "tags": tags}).encode("utf-8")
+    req = urllib.request.Request(
+        f"{eagle_url}/api/item/addFromPath",
+        data=payload,
+        headers={"Content-Type": "application/json"},
+        method="POST",
+    )
+    with urllib.request.urlopen(req, timeout=10) as resp:
+        return json.loads(resp.read().decode("utf-8"))
+
+
 def _eagle_add(eagle_url, image_url, name, tags):
    """Proxy request to Eagle API (runs in thread)."""
    eagle_url = eagle_url.rstrip("/")
@@ -71,11 +150,33 @@ async def handle_add(request: web.Request) -> web.Response:
        image_url = body.get("url", "")
        name = body.get("name", "image.png")
        tags = body.get("tags", [])
+        filename = body.get("filename", "")
+        subfolder = body.get("subfolder", "")
+        file_type = body.get("type", "output")
+        local_path_hint = body.get("localPath", "")

-        if not image_url:
+        if not image_url and not local_path_hint:
            return web.json_response({"status": "error", "message": "No URL provided"}, status=400)

-        result = await asyncio.to_thread(_eagle_add, eagle_url, image_url, name, tags)
+        # SVG は /view が application/octet-stream + attachment で返すため、
+        # ローカルファイルが解決できる場合は addFromPath で直接渡す
+        local_path = None
+        if local_path_hint:
+            # comfyui-tosvg の Save SVG String ノードなど、絶対パスが既知の場合
+            local_path = _resolve_absolute_svg_path(local_path_hint)
+        elif (filename or name or "").lower().endswith(".svg"):
+            local_path = _resolve_local_path(filename or name, subfolder, file_type)
+
+        if not local_path and not image_url:
+            return web.json_response(
+                {"status": "error", "message": f"Could not resolve local SVG path: {local_path_hint}"},
+                status=400,
+            )
+
+        if local_path:
+            result = await asyncio.to_thread(_eagle_add_from_path, eagle_url, local_path, name, tags)
+        else:
+            result = await asyncio.to_thread(_eagle_add, eagle_url, image_url, name, tags)
        return web.json_response(result)
    except urllib.error.URLError as e:
        logger.error("Eagle URL error: %s", e)
@@ -2,11 +2,9 @@
 Gallery Routes - ギャラリータブ用APIエンドポイント
 """
 import asyncio
-import base64
 import json
 import mimetypes
 import logging
-import re
 from pathlib import Path
 from aiohttp import web

@@ -43,6 +41,16 @@ def _init_allowed_root() -> None:
    except Exception as e:
        logger.warning("GalleryRoutes: failed to get ComfyUI output dir: %s", e)

+    # ImagePrompt/Style Catalogギャラリー用に実outputフォルダを常に別途保持する
+    # (Settingsで_allowed_rootが別フォルダに変更されていても影響しないようにするため)
+    try:
+        import folder_paths  # type: ignore
+        output_dir = folder_paths.get_output_directory()
+        if output_dir and Path(output_dir).is_dir():
+            _service.set_comfy_output_root(output_dir)
+    except Exception as e:
+        logger.warning("GalleryRoutes: failed to get ComfyUI output dir for image-prompt root: %s", e)
+

 _init_allowed_root()

@@ -55,7 +63,12 @@ def setup_routes(app: web.Application):
    app.router.add_get("/wfm/gallery/image/serve", serve_image)
    app.router.add_get("/wfm/gallery/image/thumb", serve_thumb)
    app.router.add_post("/wfm/gallery/image/meta", save_image_meta)
+    app.router.add_get("/wfm/gallery/image-prompt/root", get_image_prompt_root)
+    app.router.add_post("/wfm/gallery/image/image-prompt", save_image_prompt)
+    app.router.add_get("/wfm/gallery/style-catalog/root", get_style_catalog_root)
    app.router.add_post("/wfm/gallery/image/save", save_image_to_gallery)
+    app.router.add_post("/wfm/gallery/image/save-to-folder", save_image_to_folder_route)
+    app.router.add_post("/wfm/gallery/output-image/delete", delete_output_image)
    app.router.add_post("/wfm/gallery/image/favorite", toggle_favorite)
    app.router.add_get("/wfm/gallery/groups", list_groups)
    app.router.add_post("/wfm/gallery/groups", create_group)
@@ -75,6 +88,10 @@ def setup_routes(app: web.Application):
    app.router.add_post("/wfm/gallery/images/delete", delete_images_route)
    app.router.add_post("/wfm/gallery/images/move", move_images_route)
    app.router.add_post("/wfm/gallery/images/export-zip", export_images_zip)
+    app.router.add_post("/wfm/gallery/images/export-psd", export_images_psd)
+    app.router.add_post("/wfm/gallery/image/export-psd-layers", export_psd_from_layers)
+    app.router.add_post("/wfm/gallery/image/import-psd-layers", import_psd_layers)
+    app.router.add_get("/wfm/gallery/image/psd-layers", get_psd_layers)


 # ──────────────────────────────────────────────────────────────
@@ -104,6 +121,7 @@ async def list_images(request: web.Request) -> web.Response:
    favorite_only = request.rel_url.query.get("favorite", "false") == "true"
    tag_filter = request.rel_url.query.get("tag", "")
    group_filter = request.rel_url.query.get("group", "")
+    recursive = request.rel_url.query.get("recursive", "false") == "true"

    if not folder:
        return web.json_response({"error": "folder parameter required"}, status=400)
@@ -117,6 +135,7 @@ async def list_images(request: web.Request) -> web.Response:
            favorite_only=favorite_only,
            tag_filter=tag_filter,
            group_filter=group_filter,
+            recursive=recursive,
        )
        # 検索なしのフォルダロード時にバックグラウンドインデックスを起動
        if not search:
@@ -148,9 +167,15 @@ async def get_image_workflow(request: web.Request) -> web.Response:
        return web.json_response({"error": "path required"}, status=400)
    try:
        wf = _service.extract_workflow_from_metadata(path)
-        if wf is None:
-            return web.json_response({"workflow": None, "has_workflow": False})
-        return web.json_response({"workflow": wf, "has_workflow": True})
+        # prompt_workflow: プロンプト抽出専用（PNG[prompt]優先）。トップレベルとサブグラフに
+        # 独立した複数系統を持つワークフローではUI形式(workflow)からの抽出がトップレベル
+        # 系統しか拾えないことがあるため、Promptタブはこちらを使う(Metadataタブと揃える)。
+        prompt_wf = _service.extract_prompt_workflow_from_metadata(path)
+        return web.json_response({
+            "workflow": wf,
+            "has_workflow": wf is not None,
+            "prompt_workflow": prompt_wf,
+        })
    except Exception as e:
        return web.json_response({"error": str(e)}, status=500)

@@ -160,7 +185,10 @@ async def serve_image(request: web.Request) -> web.Response:
    if not path:
        return web.Response(status=400)

-    img_path = _service.serve_image(path)
+    # PSDの合成処理はCPU負荷が高く同期実行するとイベントループ全体をブロックする
+    # (他の並行リクエスト、例えば別画像のサムネイル配信も止まってしまう)ためexecutorで実行する
+    loop = asyncio.get_event_loop()
+    img_path = await loop.run_in_executor(None, _service.serve_image, path)
    if img_path is None:
        return web.Response(status=404)

@@ -182,7 +210,10 @@ async def serve_thumb(request: web.Request) -> web.Response:
    except ValueError:
        width = 256

-    thumb_path = _service.serve_thumbnail(path, width)
+    # PSD/MP4のサムネイル生成はCPU負荷が高く同期実行するとイベントループ全体をブロックするため
+    # executorで実行する（他画像のサムネイル配信が巻き添えで遅延・停止するのを防ぐ）
+    loop = asyncio.get_event_loop()
+    thumb_path = await loop.run_in_executor(None, _service.serve_thumbnail, path, width)
    if thumb_path is None:
        return web.Response(status=404)

@@ -248,6 +279,36 @@ async def save_image_meta(request: web.Request) -> web.Response:
        return web.json_response({"error": str(e)}, status=500)


+async def get_image_prompt_root(request: web.Request) -> web.Response:
+    """GET /wfm/gallery/image-prompt/root — ImagePromptギャラリーのルートフォルダを返す"""
+    root = _service.get_image_prompt_root()
+    if root is None:
+        return web.json_response({"error": "ComfyUI output directory not resolved"}, status=500)
+    return web.json_response({"root": root})
+
+
+async def save_image_prompt(request: web.Request) -> web.Response:
+    """POST /wfm/gallery/image/image-prompt — 画像の.txtサイドカーにプロンプトを保存"""
+    try:
+        body = await request.json()
+        img_path = body.get("path", "")
+        prompt = body.get("prompt", "")
+        if not img_path:
+            return web.json_response({"error": "path required"}, status=400)
+        ok = _service.save_image_prompt(img_path, prompt)
+        return web.json_response({"ok": ok})
+    except Exception as e:
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def get_style_catalog_root(request: web.Request) -> web.Response:
+    """GET /wfm/gallery/style-catalog/root — Style Catalogギャラリーのルートフォルダを返す"""
+    root = _service.get_style_catalog_root()
+    if root is None:
+        return web.json_response({"error": "ComfyUI output directory not resolved"}, status=500)
+    return web.json_response({"root": root})
+
+
 async def toggle_favorite(request: web.Request) -> web.Response:
    try:
        body = await request.json()
@@ -261,7 +322,8 @@ async def toggle_favorite(request: web.Request) -> web.Response:


 async def save_image_to_gallery(request: web.Request) -> web.Response:
-    """Image Edit Tab からの PNG をギャラリーのルートフォルダに保存する。"""
+    """Image Edit Tab / AI Chat からの画像(PNG等)やSVGをギャラリーのルートフォルダに保存する。
+    imageData は data URL (data:<mime>;base64,<data>) を想定。ヘッダがなければPNG扱い（旧互換）。"""
    try:
        body = await request.json()
        filename   = body.get("filename", "").strip()
@@ -273,27 +335,64 @@ async def save_image_to_gallery(request: web.Request) -> web.Response:
        if _service._allowed_root is None:
            return web.json_response({"error": "Gallery root not configured. Open Gallery tab and set output folder first."}, status=500)

-        # ファイル名サニタイズ（OSで使えない文字を除去）
-        safe = re.sub(r'[<>:"/\\|?*\x00-\x1f]', "_", filename)
-        if not safe.lower().endswith(".png"):
-            safe += ".png"
+        result = _service.save_image_to_folder(str(_service._allowed_root), filename, image_data)
+        if not result["ok"]:
+            return web.json_response({"error": result["error"]}, status=400)

-        # base64 data URL をデコード
-        raw = image_data
-        if "," in raw:
-            raw = raw.split(",", 1)[1]
-        image_bytes = base64.b64decode(raw)
-
-        save_path = _service._allowed_root / safe
-        save_path.write_bytes(image_bytes)
-
-        logger.info("save_image_to_gallery: saved %s (%d bytes)", save_path, len(image_bytes))
-        return web.json_response({"ok": True, "path": str(save_path)})
+        logger.info("save_image_to_gallery: saved %s", result["path"])
+        return web.json_response({"ok": True, "path": result["path"]})
    except Exception as e:
        logger.error("save_image_to_gallery error: %s", e)
        return web.json_response({"error": str(e)}, status=500)


+async def save_image_to_folder_route(request: web.Request) -> web.Response:
+    """POST /wfm/gallery/image/save-to-folder — 任意フォルダへ画像を保存（同名なら上書き）。
+    Style Catalogのカタログ作成で、スタイル名をファイル名として使う際に利用する。"""
+    try:
+        body = await request.json()
+        folder     = body.get("folder", "").strip()
+        filename   = body.get("filename", "").strip()
+        image_data = body.get("imageData", "")
+
+        if not folder or not filename or not image_data:
+            return web.json_response({"error": "folder, filename and imageData required"}, status=400)
+
+        result = _service.save_image_to_folder(folder, filename, image_data)
+        if not result["ok"]:
+            return web.json_response({"error": result["error"]}, status=400)
+        return web.json_response({"ok": True, "path": result["path"]})
+    except Exception as e:
+        logger.error("save_image_to_folder_route error: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def delete_output_image(request: web.Request) -> web.Response:
+    """POST /wfm/gallery/output-image/delete — ComfyUI標準の画像参照(filename/subfolder/type)から
+    実ファイルを削除する。Style Catalogのカタログ作成で「Outputフォルダに画像を残さない」
+    オプションが有効な時、カタログへコピー保存した直後の元画像を消すために使う。
+    type="output" 以外は拒否する（temp/inputの誤削除を防止）。"""
+    try:
+        body = await request.json()
+        filename = (body.get("filename") or "").strip()
+        subfolder = body.get("subfolder") or ""
+        img_type = body.get("type") or ""
+        if not filename or img_type != "output":
+            return web.json_response({"error": "filename required and type must be 'output'"}, status=400)
+
+        import folder_paths  # type: ignore
+        output_dir = Path(folder_paths.get_output_directory())
+        target = output_dir / subfolder / filename
+
+        result = await asyncio.to_thread(_service.delete_images, [str(target)])
+        if result["deleted"]:
+            return web.json_response({"ok": True})
+        return web.json_response({"error": "; ".join(result["errors"]) or "File not found"}, status=404)
+    except Exception as e:
+        logger.error("delete_output_image error: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
 # ──────────────────────────────────────────────────────────────
 # グループ管理
 # ──────────────────────────────────────────────────────────────
@@ -316,7 +415,7 @@ async def create_group(request: web.Request) -> web.Response:
        return web.json_response({"error": str(e)}, status=500)


-_RESERVED_GROUPS = {"__Feeder__"}
+_RESERVED_GROUPS = {"__Feeder__", "__Video Assets__", "__Video Temp__"}


 async def rename_group(request: web.Request) -> web.Response:
@@ -485,3 +584,97 @@ async def export_images_zip(request: web.Request) -> web.Response:
    except Exception as e:
        logger.error("Error exporting images to ZIP: %s", e)
        return web.json_response({"error": str(e)}, status=500)
+
+
+async def export_images_psd(request: web.Request) -> web.Response:
+    """POST /wfm/gallery/images/export-psd - 複数画像を1つのPSD(レイヤー分割)にしてダウンロード"""
+    try:
+        body = await request.json()
+        paths = body.get("paths", [])
+        if not paths:
+            return web.json_response({"error": "paths required"}, status=400)
+
+        psd_bytes = _service.build_psd_from_images(paths)
+
+        return web.Response(
+            body=psd_bytes,
+            content_type="image/vnd.adobe.photoshop",
+            headers={"Content-Disposition": "attachment; filename=gallery_export.psd"}
+        )
+    except RuntimeError as e:
+        logger.error("PSD export dependency missing: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+    except ValueError as e:
+        return web.json_response({"error": str(e)}, status=400)
+    except Exception as e:
+        logger.error("Error exporting images to PSD: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def export_psd_from_layers(request: web.Request) -> web.Response:
+    """POST /wfm/gallery/image/export-psd-layers - Image Editタブのレイヤー配列を1つのPSDにしてダウンロード"""
+    try:
+        body = await request.json()
+        width = int(body.get("width", 0))
+        height = int(body.get("height", 0))
+        layers = body.get("layers", [])
+        if not layers:
+            return web.json_response({"error": "layers required"}, status=400)
+
+        psd_bytes = _service.build_psd_from_layers(width, height, layers)
+
+        return web.Response(
+            body=psd_bytes,
+            content_type="image/vnd.adobe.photoshop",
+            headers={"Content-Disposition": "attachment; filename=image_edit_export.psd"}
+        )
+    except RuntimeError as e:
+        logger.error("PSD export dependency missing: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+    except ValueError as e:
+        return web.json_response({"error": str(e)}, status=400)
+    except Exception as e:
+        logger.error("Error exporting Image Edit layers to PSD: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def import_psd_layers(request: web.Request) -> web.Response:
+    """POST /wfm/gallery/image/import-psd-layers - アップロードされたPSDをレイヤー配列(JSON)に分解して返す"""
+    try:
+        reader = await request.multipart()
+        field = await reader.next()
+        if field is None:
+            return web.json_response({"error": "file required"}, status=400)
+        psd_bytes = await field.read(decode=False)
+
+        loop = asyncio.get_event_loop()
+        result = await loop.run_in_executor(None, _service.import_psd_layers, psd_bytes)
+        return web.json_response(result)
+    except RuntimeError as e:
+        logger.error("PSD import dependency missing: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+    except ValueError as e:
+        return web.json_response({"error": str(e)}, status=400)
+    except Exception as e:
+        logger.error("Error importing PSD layers: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def get_psd_layers(request: web.Request) -> web.Response:
+    """GET /wfm/gallery/image/psd-layers - サーバー上のPSDファイルをレイヤー配列(JSON)に分解して返す
+    (Galleryから直接Image Editへ送る際、アップロードの往復を挟まずに済ませるため)"""
+    path = request.rel_url.query.get("path", "")
+    if not path:
+        return web.json_response({"error": "path required"}, status=400)
+    try:
+        loop = asyncio.get_event_loop()
+        result = await loop.run_in_executor(None, _service.get_psd_layers_from_path, path)
+        return web.json_response(result)
+    except RuntimeError as e:
+        logger.error("PSD import dependency missing: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+    except ValueError as e:
+        return web.json_response({"error": str(e)}, status=400)
+    except Exception as e:
+        logger.error("Error reading PSD layers: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
@@ -82,9 +82,9 @@ async def handle_open(request: web.Request) -> web.Response:
        # Retrieve setting for gmic path
        data = _settings.load()
        gmic_exe = data.get("gmic_qt_path", "")
-        if not os.path.exists(gmic_exe):
+        if not os.path.isabs(gmic_exe) or os.path.splitext(gmic_exe)[1].lower() != ".exe" or not os.path.isfile(gmic_exe):
            return web.json_response({
-                "error": f"G'MIC executable not found at: {gmic_exe}. Please configure the path in settings."
+                "error": f"G'MIC executable not found at: {gmic_exe}. Please configure an absolute .exe path in settings."
            }, status=400)

        ext = ".png"
@@ -0,0 +1,85 @@
+"""Lab tab plan file management API routes."""
+
+import asyncio
+import logging
+
+from aiohttp import web
+
+from ..config import LAB_PLAN_DIR
+from ..services.lab_plan_service import LabPlanService
+
+logger = logging.getLogger(__name__)
+
+_service = LabPlanService(LAB_PLAN_DIR)
+
+
+def setup_routes(app: web.Application):
+    app.router.add_get("/api/wfm/lab/plans", handle_list)
+    app.router.add_get("/api/wfm/lab/plans/content", handle_get_content)
+    app.router.add_post("/api/wfm/lab/plans/save", handle_save)
+    app.router.add_post("/api/wfm/lab/plans/delete", handle_delete)
+    app.router.add_post("/api/wfm/lab/index-image/save-to-output", handle_save_index_to_output)
+
+
+async def handle_list(request: web.Request) -> web.Response:
+    try:
+        result = await asyncio.to_thread(_service.list_plans)
+        return web.json_response(result)
+    except Exception as e:
+        logger.error("Error listing lab plans: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def handle_get_content(request: web.Request) -> web.Response:
+    filename = request.rel_url.query.get("filename", "")
+    try:
+        data = await asyncio.to_thread(_service.get_plan, filename)
+        return web.json_response({"data": data})
+    except FileNotFoundError:
+        return web.json_response({"error": "not found"}, status=404)
+    except ValueError as e:
+        return web.json_response({"error": str(e)}, status=400)
+    except Exception as e:
+        logger.error("Error getting lab plan content: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def handle_save(request: web.Request) -> web.Response:
+    try:
+        body = await request.json()
+        filename = body.get("filename", "")
+        data = body.get("data", {})
+        index_image_base64 = body.get("index_image_base64")
+        result = await asyncio.to_thread(_service.save_plan, filename, data, index_image_base64)
+        return web.json_response({"status": "ok", **result})
+    except ValueError as e:
+        return web.json_response({"error": str(e)}, status=400)
+    except Exception as e:
+        logger.error("Error saving lab plan: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def handle_delete(request: web.Request) -> web.Response:
+    try:
+        body = await request.json()
+        filename = body.get("filename", "")
+        await asyncio.to_thread(_service.delete_plan, filename)
+        return web.json_response({"status": "ok"})
+    except ValueError as e:
+        return web.json_response({"error": str(e)}, status=400)
+    except Exception as e:
+        logger.error("Error deleting lab plan: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def handle_save_index_to_output(request: web.Request) -> web.Response:
+    try:
+        body = await request.json()
+        image_base64 = body.get("image_base64", "")
+        if not image_base64:
+            return web.json_response({"error": "image_base64 required"}, status=400)
+        result = await asyncio.to_thread(_service.save_index_image_to_output, image_base64)
+        return web.json_response({"status": "ok", **result})
+    except Exception as e:
+        logger.error("Error saving lab index image to output: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
@@ -1,8 +1,11 @@
 """Settings API routes."""

 import asyncio
+import io
 import json
 import logging
+import shutil
+import zipfile
 from pathlib import Path

 from aiohttp import web
@@ -24,6 +27,7 @@ _DATA_FILES = [
    "model_metadata.json",
    "gallery_metadata.json",
    "tagger_settings.json",
+    "civitai_cache.json",
 ]


@@ -37,7 +41,12 @@ def setup_routes(app: web.Application):
    app.router.add_post("/api/wfm/settings/output-dir", handle_set_output_dir)
    app.router.add_get("/api/wfm/settings/export", handle_export)
    app.router.add_post("/api/wfm/settings/import", handle_import)
+    app.router.add_get("/api/wfm/settings/export-full", handle_export_full)
+    app.router.add_post("/api/wfm/settings/import-full", handle_import_full)
    app.router.add_get("/api/wfm/styles", handle_get_styles)
+    app.router.add_post("/api/wfm/styles", handle_create_style)
+    app.router.add_put("/api/wfm/styles/{name}", handle_update_style)
+    app.router.add_delete("/api/wfm/styles/{name}", handle_delete_style)


 async def handle_get(request: web.Request) -> web.Response:
@@ -245,18 +254,174 @@ async def handle_import(request: web.Request) -> web.Response:
        return web.json_response({"error": str(e)}, status=500)


-def _load_styles() -> list:
-    """Load all style JSON files from DATA_DIR/style/ directory."""
+# Full-backup (ZIP) export/import: unlike the flat _DATA_FILES JSON bundle above, this
+# covers the whole DATA_DIR — directory-shaped data (ai_skills/, lab_plan/, video_plan/,
+# style/) and the SQLite tagger.db that the JSON bundle can't represent. Excludes transient/cache
+# dirs, and wildcard/ specifically because it's typically a symlink into a *different*
+# custom_node's folder (comfyui-impact-pack) rather than this plugin's own data.
+_FULL_BACKUP_EXCLUDE_NAMES = {"gmic_temp", "thumb_cache", "wildcard"}
+
+
+def _add_file_to_zip(zf: zipfile.ZipFile, path: Path, base: Path):
+    rel = str(path.relative_to(base)).replace("\\", "/")
+    if path.name == "settings.json":
+        # Same API-key scrubbing as the JSON-bundle export — fall through to a raw
+        # copy if the file turns out to be unreadable/corrupt rather than skipping it.
+        try:
+            with open(path, "r", encoding="utf-8") as f:
+                data = json.load(f)
+            data = {k: v for k, v in data.items() if k not in _SETTINGS_EXPORT_EXCLUDE}
+            zf.writestr(rel, json.dumps(data, ensure_ascii=False, indent=2))
+            return
+        except Exception:
+            pass
+    zf.write(path, rel)
+
+
+# Two folders this plugin doesn't own but users often want backed up alongside their
+# own data: ComfyUI's own default workflows dir, and the Impact Pack's wildcard
+# library (a separate custom_node — the plugin's own wildcard/ is usually just a
+# symlink into this same folder, see _FULL_BACKUP_EXCLUDE_NAMES above). Opt-in only
+# (see handle_export_full's include_workflows/include_wildcard query params), and
+# stored under an "_external/" prefix so _apply_full_backup_zip can recognize and
+# skip them on restore — see that function's docstring for why.
+def _default_workflows_dir() -> Path:
+    from ..config import COMFYUI_ROOT
+    return COMFYUI_ROOT / "user" / "default" / "workflows"
+
+
+def _impact_pack_wildcard_dir() -> Path:
+    from ..config import COMFYUI_ROOT
+    return COMFYUI_ROOT / "custom_nodes" / "comfyui-impact-pack" / "wildcards"
+
+
+def _add_external_dir_to_zip(zf: zipfile.ZipFile, src_dir: Path, zip_prefix: str):
+    if not src_dir.is_dir() or src_dir.is_symlink():
+        return
+    for path in src_dir.rglob("*"):
+        if path.is_dir() or path.is_symlink():
+            continue
+        rel = f"{zip_prefix}/{path.relative_to(src_dir)}".replace("\\", "/")
+        zf.write(path, rel)
+
+
+def _build_full_backup_zip(include_workflows: bool = False, include_wildcard: bool = False) -> bytes:
+    """Zips everything under DATA_DIR except the excluded names above. Walks
+    top-level entries first so an excluded symlinked directory (wildcard/) is never
+    even opened, rather than filtering after a recursive walk has already followed it.
+    Optionally also includes the two external folders above under "_external/"."""
+    buf = io.BytesIO()
+    with zipfile.ZipFile(buf, "w", zipfile.ZIP_DEFLATED) as zf:
+        for top in sorted(DATA_DIR.iterdir()):
+            if top.name in _FULL_BACKUP_EXCLUDE_NAMES or top.is_symlink():
+                continue
+            if top.is_file():
+                _add_file_to_zip(zf, top, DATA_DIR)
+            elif top.is_dir():
+                for path in top.rglob("*"):
+                    if path.is_dir() or path.is_symlink():
+                        continue
+                    _add_file_to_zip(zf, path, DATA_DIR)
+
+        if include_workflows:
+            _add_external_dir_to_zip(zf, _default_workflows_dir(), "_external/default_workflows")
+        if include_wildcard:
+            _add_external_dir_to_zip(zf, _impact_pack_wildcard_dir(), "_external/wildcard")
+    return buf.getvalue()
+
+
+def _apply_full_backup_zip(zip_bytes: bytes) -> dict:
+    """Extracts a full-backup ZIP into DATA_DIR, overwriting existing files. Guards
+    against Zip Slip (entries whose path resolves outside DATA_DIR via '..' or an
+    absolute path) by checking each entry before writing it.
+
+    Entries under "_external/" (default workflows dir, Impact Pack wildcards — see
+    _build_full_backup_zip) are always skipped here rather than restored: they live
+    outside DATA_DIR and are managed by ComfyUI core / a different custom_node, so
+    auto-restoring them could silently overwrite files this plugin doesn't own. They
+    stay in the ZIP for the user to copy back manually if they want them."""
+    summary = {"extracted": [], "skipped": []}
+    DATA_DIR.mkdir(parents=True, exist_ok=True)
+    base = DATA_DIR.resolve()
+    with zipfile.ZipFile(io.BytesIO(zip_bytes)) as zf:
+        for info in zf.infolist():
+            if info.is_dir():
+                continue
+            if info.filename.startswith("_external/"):
+                summary["skipped"].append(info.filename)
+                continue
+            target = (base / info.filename).resolve()
+            try:
+                target.relative_to(base)
+            except ValueError:
+                summary["skipped"].append(info.filename)
+                continue
+            target.parent.mkdir(parents=True, exist_ok=True)
+            with zf.open(info) as src, open(target, "wb") as dst:
+                shutil.copyfileobj(src, dst)
+            summary["extracted"].append(info.filename)
+    return summary
+
+
+async def handle_export_full(request: web.Request) -> web.Response:
+    """GET /api/wfm/settings/export-full - Download a ZIP of the entire data
+    directory, including data the flat JSON bundle (handle_export) can't represent.
+    Optional query params include_workflows=1 / include_wildcard=1 additionally bundle
+    ComfyUI's default workflows dir / the Impact Pack's wildcard dir (see
+    _build_full_backup_zip) — both restore-excluded, export-only, manual-copy-back."""
+    try:
+        include_workflows = request.rel_url.query.get("include_workflows") == "1"
+        include_wildcard = request.rel_url.query.get("include_wildcard") == "1"
+        zip_bytes = await asyncio.to_thread(_build_full_backup_zip, include_workflows, include_wildcard)
+        return web.Response(
+            body=zip_bytes,
+            content_type="application/zip",
+            headers={"Content-Disposition": 'attachment; filename="wfm-full-backup.zip"'},
+        )
+    except Exception as e:
+        logger.error("Error building full backup: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def handle_import_full(request: web.Request) -> web.Response:
+    """POST /api/wfm/settings/import-full - Upload and restore a full-backup ZIP."""
+    try:
+        reader = await request.multipart()
+        field = await reader.next()
+        if field is None or field.name != "file":
+            return web.json_response({"error": "file field required"}, status=400)
+        zip_bytes = await field.read(decode=False)
+        summary = await asyncio.to_thread(_apply_full_backup_zip, zip_bytes)
+        return web.json_response({"status": "ok", **summary})
+    except zipfile.BadZipFile:
+        return web.json_response({"error": "Not a valid ZIP file"}, status=400)
+    except Exception as e:
+        logger.error("Error importing full backup: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+def _style_files() -> list:
    style_dir = DATA_DIR / "style"
-    styles = []
    if not style_dir.is_dir():
-        return styles
-    for json_file in sorted(style_dir.glob("*.json")):
+        return []
+    return sorted(style_dir.glob("*.json"))
+
+
+def _load_styles() -> list:
+    """Load all style JSON files from DATA_DIR/style/ directory.
+    各エントリに定義元ファイル名を "file" として付与する（Promptタブの一覧表示・
+    「このファイルへ追加」機能で使用）。"""
+    styles = []
+    for json_file in _style_files():
        try:
            with open(json_file, "r", encoding="utf-8") as f:
                data = json.load(f)
            if isinstance(data, list):
-                styles.extend(data)
+                for entry in data:
+                    if isinstance(entry, dict):
+                        entry = dict(entry)
+                        entry["file"] = json_file.name
+                        styles.append(entry)
        except Exception as e:
            logger.warning("Failed to load style file %s: %s", json_file.name, e)
    return styles
@@ -270,3 +435,139 @@ async def handle_get_styles(request: web.Request) -> web.Response:
    except Exception as e:
        logger.error("Error loading styles: %s", e)
        return web.json_response({"error": str(e)}, status=500)
+
+
+# Promptタブ「Style」サブタブでの新規作成分の保存先。既存スタイルの編集は
+# 元々そのスタイルが記載されているファイルをそのまま書き換える（他ファイルへは移動しない）。
+_CUSTOM_STYLE_FILENAME = "custom.json"
+
+
+def _find_style(name: str):
+    """名前が一致する最初のスタイルを探し、(ファイルパス, そのファイルの全データ, インデックス) を返す。
+    見つからなければ None。"""
+    for json_file in _style_files():
+        try:
+            with open(json_file, "r", encoding="utf-8") as f:
+                data = json.load(f)
+        except Exception as e:
+            logger.warning("Failed to load style file %s: %s", json_file.name, e)
+            continue
+        if not isinstance(data, list):
+            continue
+        for i, entry in enumerate(data):
+            if isinstance(entry, dict) and entry.get("name") == name:
+                return json_file, data, i
+    return None
+
+
+def _write_style_file(path: Path, data: list) -> None:
+    with open(path, "w", encoding="utf-8") as f:
+        json.dump(data, f, ensure_ascii=False, indent=2)
+        f.write("\n")
+
+
+async def handle_create_style(request: web.Request) -> web.Response:
+    """POST /api/wfm/styles - 新規スタイルを作成する。
+    body.file を指定すると既存のそのファイルへ追記する（Promptタブの「このファイルへ追加」用、
+    ファイル名はstyleディレクトリに実在するもののみ許可しパストラバーサルを防ぐ）。
+    未指定ならデフォルトのcustom.jsonへ追記する。"""
+    try:
+        body = await request.json()
+        name = (body.get("name") or "").strip()
+        prompt = body.get("prompt", "") or ""
+        negative_prompt = body.get("negative_prompt", "") or ""
+        target_file = (body.get("file") or "").strip()
+        if not name:
+            return web.json_response({"error": "name is required"}, status=400)
+
+        def _create():
+            if _find_style(name) is not None:
+                return "duplicate"
+            style_dir = DATA_DIR / "style"
+            style_dir.mkdir(parents=True, exist_ok=True)
+
+            if target_file:
+                path = next((f for f in _style_files() if f.name == target_file), None)
+                if path is None:
+                    return "file_not_found"
+            else:
+                path = style_dir / _CUSTOM_STYLE_FILENAME
+
+            data = []
+            if path.is_file():
+                try:
+                    with open(path, "r", encoding="utf-8") as f:
+                        loaded = json.load(f)
+                    if isinstance(loaded, list):
+                        data = loaded
+                except Exception as e:
+                    logger.warning("Failed to load %s, recreating: %s", path.name, e)
+            data.append({"name": name, "prompt": prompt, "negative_prompt": negative_prompt})
+            _write_style_file(path, data)
+            return "ok"
+
+        result = await asyncio.to_thread(_create)
+        if result == "duplicate":
+            return web.json_response({"error": f'Style "{name}" already exists'}, status=400)
+        if result == "file_not_found":
+            return web.json_response({"error": f'File "{target_file}" not found'}, status=400)
+        return web.json_response({"ok": True})
+    except Exception as e:
+        logger.error("Error creating style: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def handle_update_style(request: web.Request) -> web.Response:
+    """PUT /api/wfm/styles/{name} - 既存スタイルを更新する（記載元のファイルをそのまま書き換え、リネームも可）。"""
+    try:
+        original_name = request.match_info.get("name", "")
+        body = await request.json()
+        new_name = (body.get("name") or "").strip()
+        prompt = body.get("prompt", "") or ""
+        negative_prompt = body.get("negative_prompt", "") or ""
+        if not new_name:
+            return web.json_response({"error": "name is required"}, status=400)
+
+        def _update():
+            found = _find_style(original_name)
+            if found is None:
+                return "not_found"
+            path, data, idx = found
+            if new_name != original_name and _find_style(new_name) is not None:
+                return "duplicate"
+            data[idx] = {"name": new_name, "prompt": prompt, "negative_prompt": negative_prompt}
+            _write_style_file(path, data)
+            return "ok"
+
+        result = await asyncio.to_thread(_update)
+        if result == "not_found":
+            return web.json_response({"error": "Style not found"}, status=404)
+        if result == "duplicate":
+            return web.json_response({"error": f'Style "{new_name}" already exists'}, status=400)
+        return web.json_response({"ok": True})
+    except Exception as e:
+        logger.error("Error updating style: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def handle_delete_style(request: web.Request) -> web.Response:
+    """DELETE /api/wfm/styles/{name} - スタイルを削除する（記載元のファイルから該当エントリのみ除去）。"""
+    try:
+        name = request.match_info.get("name", "")
+
+        def _delete():
+            found = _find_style(name)
+            if found is None:
+                return False
+            path, data, idx = found
+            del data[idx]
+            _write_style_file(path, data)
+            return True
+
+        ok = await asyncio.to_thread(_delete)
+        if not ok:
+            return web.json_response({"error": "Style not found"}, status=404)
+        return web.json_response({"ok": True})
+    except Exception as e:
+        logger.error("Error deleting style: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
@@ -0,0 +1,64 @@
+"""AI skill (.md system prompt) file management API routes."""
+
+import asyncio
+import logging
+
+from aiohttp import web
+
+from ..config import AI_SKILLS_DIR
+from ..services.skill_service import SkillService
+
+logger = logging.getLogger(__name__)
+
+_service = SkillService(AI_SKILLS_DIR)
+
+
+def setup_routes(app: web.Application):
+    app.router.add_get("/api/wfm/skills", handle_list)
+    app.router.add_get("/api/wfm/skills/content", handle_get_content)
+    app.router.add_post("/api/wfm/skills/save", handle_save)
+    app.router.add_post("/api/wfm/skills/delete", handle_delete)
+
+
+async def handle_list(request: web.Request) -> web.Response:
+    try:
+        result = await asyncio.to_thread(_service.list_skills)
+        return web.json_response(result)
+    except Exception as e:
+        logger.error("Error listing skills: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def handle_get_content(request: web.Request) -> web.Response:
+    filename = request.rel_url.query.get("filename", "")
+    try:
+        content = await asyncio.to_thread(_service.get_content, filename)
+        return web.json_response({"content": content})
+    except FileNotFoundError:
+        return web.json_response({"error": "not found"}, status=404)
+    except Exception as e:
+        logger.error("Error getting skill content: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def handle_save(request: web.Request) -> web.Response:
+    try:
+        body = await request.json()
+        filename = body.get("filename", "")
+        content = body.get("content", "")
+        result = await asyncio.to_thread(_service.save_file, filename, content)
+        return web.json_response({"status": "ok", "file": result})
+    except Exception as e:
+        logger.error("Error saving skill: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def handle_delete(request: web.Request) -> web.Response:
+    try:
+        body = await request.json()
+        filename = body.get("filename", "")
+        await asyncio.to_thread(_service.delete_file, filename)
+        return web.json_response({"status": "ok"})
+    except Exception as e:
+        logger.error("Error deleting skill: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
@@ -18,8 +18,8 @@ _db = TaggerDbService(TAGGER_DB_FILE)
 def setup_routes(app: web.Application):
    app.router.add_get("/wfm/tagger/models", handle_models)
    app.router.add_post("/wfm/tagger/predict", handle_predict)
-    app.router.add_get("/wfm/tagger/ollama/models", handle_ollama_models)
-    app.router.add_post("/wfm/tagger/ollama/predict", handle_ollama_predict)
+    app.router.add_get("/wfm/tagger/vlm/models", handle_vlm_models)
+    app.router.add_post("/wfm/tagger/vlm/predict", handle_vlm_predict)
    app.router.add_post("/wfm/tagger/batch/start", handle_batch_start)
    app.router.add_get("/wfm/tagger/batch/status", handle_batch_status)
    app.router.add_post("/wfm/tagger/batch/stop", handle_batch_stop)
@@ -27,6 +27,7 @@ def setup_routes(app: web.Application):
    app.router.add_get("/wfm/tagger/db/search", handle_db_search)
    app.router.add_put("/wfm/tagger/db/{id}", handle_db_update)
    app.router.add_delete("/wfm/tagger/db/{id}", handle_db_delete)
+    app.router.add_delete("/wfm/tagger/db", handle_db_delete_bulk)
    app.router.add_get("/wfm/tagger/db/export", handle_db_export)
    app.router.add_post("/wfm/tagger/db/save", handle_db_save)
    app.router.add_post("/wfm/tagger/write_meta", handle_write_meta)
@@ -61,25 +62,29 @@ async def handle_predict(request: web.Request) -> web.Response:
        return web.json_response({"error": str(e)}, status=500)


-async def handle_ollama_models(request: web.Request) -> web.Response:
+async def handle_vlm_models(request: web.Request) -> web.Response:
+    backend = request.rel_url.query.get("backend", "ollama")
    api_url = request.rel_url.query.get("api_url", "http://127.0.0.1:11434")
    try:
-        models = await asyncio.to_thread(_svc.ollama_models, api_url)
+        models = await asyncio.to_thread(_svc.vlm_models, backend, api_url)
        return web.json_response({"models": models})
    except Exception as e:
        return web.json_response({"error": str(e)}, status=500)


-async def handle_ollama_predict(request: web.Request) -> web.Response:
+async def handle_vlm_predict(request: web.Request) -> web.Response:
    try:
        body = await request.json()
        result = await asyncio.to_thread(
-            _svc.ollama_predict,
+            _svc.vlm_predict,
            body.get("image_b64", ""),
+            body.get("backend", "ollama"),
            body.get("api_url", "http://127.0.0.1:11434"),
            body.get("model", ""),
            body.get("prompt", ""),
            int(body.get("max_tags", 40)),
+            bool(body.get("thinking_mode", False)),
+            int(body.get("max_tokens", 0)),
        )
        return web.json_response(result)
    except Exception as e:
@@ -96,7 +101,8 @@ async def handle_batch_start(request: web.Request) -> web.Response:
            float(body.get("threshold", 0.35)),
            float(body.get("char_threshold", 0.85)),
            bool(body.get("use_ollama", False)),
-            body.get("ollama_api", "http://127.0.0.1:11434"),
+            body.get("vlm_backend", "ollama"),
+            body.get("vlm_api_url", "http://127.0.0.1:11434"),
            body.get("ollama_model", ""),
            body.get("ollama_prompt", ""),
            int(body.get("ollama_max_tags", 40)),
@@ -104,6 +110,8 @@ async def handle_batch_start(request: web.Request) -> web.Response:
            bool(body.get("write_file", False)),
            bool(body.get("write_txt", False)),
            _db,
+            bool(body.get("thinking_mode", False)),
+            int(body.get("max_tokens", 0)),
        )
        return web.json_response(result)
    except Exception as e:
@@ -161,6 +169,27 @@ async def handle_db_delete(request: web.Request) -> web.Response:
    except Exception as e:
        return web.json_response({"error": str(e)}, status=500)

+async def handle_db_delete_bulk(request: web.Request) -> web.Response:
+    try:
+        data = await request.json()
+        ids = data.get("ids", [])
+
+        if not ids:
+            return web.json_response(
+                {"error": "No IDs specified"},
+                status=400,
+            )
+
+        ids = [int(row_id) for row_id in ids]
+
+        deleted_count = await asyncio.to_thread(_db.delete_bulk, ids)
+
+        return web.json_response({
+            "ok": True,
+            "count": deleted_count,
+        })
+    except Exception as e:
+        return web.json_response({"error": str(e)}, status=500)

 async def handle_db_export(request: web.Request) -> web.Response:
    try:
@@ -0,0 +1,99 @@
+"""Unsloth API proxy routes.
+
+Unlike Ollama/LM Studio/Lemonade, Unsloth Desktop requires an API key even
+for local access (Authorization: Bearer sk-unsloth-...). The key lives in
+UNSLOTH_API_KEY (loaded from a .env file by prestartup_script.py) and is
+never sent to the frontend — the frontend calls this proxy with the target
+path/method/payload, and the server attaches the Authorization header before
+relaying to Unsloth's OpenAI-compatible API.
+"""
+
+import json
+import logging
+import os
+import urllib.request
+from urllib.error import HTTPError, URLError
+from urllib.parse import urlparse
+
+from aiohttp import web
+
+logger = logging.getLogger(__name__)
+
+UNSLOTH_DEFAULT_URL = "http://localhost:8888"
+_ALLOWED_PATHS = {"/v1/models", "/v1/chat/completions"}
+# baseUrl is client-supplied (so a custom Unsloth port works), but the
+# Authorization header carries a real secret — restrict the host to loopback
+# so this proxy can't be used to exfiltrate UNSLOTH_API_KEY to an arbitrary
+# server (SSRF). Port is unrestricted.
+_ALLOWED_HOSTS = {"localhost", "127.0.0.1", "::1"}
+
+
+def _get_api_key():
+    """Return the Unsloth API key from the environment (.env), or None."""
+    return os.environ.get("UNSLOTH_API_KEY", "").strip() or None
+
+
+def _is_allowed_base_url(base_url):
+    """Only relay (and attach the API key) to a loopback host."""
+    try:
+        parsed = urlparse(base_url)
+        return parsed.scheme in ("http", "https") and parsed.hostname in _ALLOWED_HOSTS
+    except Exception:
+        return False
+
+
+def setup_routes(app: web.Application):
+    """Register Unsloth API routes."""
+    app.router.add_post("/api/wfm/unsloth/proxy", handle_proxy)
+
+
+async def handle_proxy(request: web.Request) -> web.Response:
+    """POST /api/wfm/unsloth/proxy - Relay a request to Unsloth's OpenAI-compatible API.
+
+    Body: { baseUrl, path: "/v1/models" | "/v1/chat/completions", method: "GET" | "POST", payload }
+    """
+    import asyncio
+    try:
+        body = await request.json()
+        base_url = (body.get("baseUrl") or UNSLOTH_DEFAULT_URL).rstrip("/")
+        path = body.get("path") or "/v1/models"
+        method = (body.get("method") or "GET").upper()
+        payload = body.get("payload")
+
+        if path not in _ALLOWED_PATHS or method not in ("GET", "POST"):
+            return web.json_response({"message": "Unsupported proxy target"}, status=400)
+
+        if not _is_allowed_base_url(base_url):
+            return web.json_response({
+                "message": "Unsloth backend URL must point to localhost/127.0.0.1/::1",
+            }, status=400)
+
+        api_key = _get_api_key()
+        if not api_key:
+            return web.json_response({
+                "message": "UNSLOTH_API_KEY is not set. Copy .env.example to .env in the "
+                            "plugin folder, fill in the key, and restart ComfyUI.",
+            }, status=401)
+
+        def _fetch():
+            data = json.dumps(payload).encode("utf-8") if payload is not None else None
+            headers = {"Authorization": f"Bearer {api_key}"}
+            if data is not None:
+                headers["Content-Type"] = "application/json"
+            req = urllib.request.Request(f"{base_url}{path}", data=data, headers=headers, method=method)
+            with urllib.request.urlopen(req, timeout=120) as resp:
+                return json.loads(resp.read().decode("utf-8"))
+
+        data = await asyncio.to_thread(_fetch)
+        return web.json_response(data)
+
+    except HTTPError as e:
+        detail = e.read().decode("utf-8", errors="replace") if e.fp else str(e)
+        logger.warning("Unsloth proxy HTTP error: %s %s", e.code, detail)
+        return web.json_response({"message": f"Unsloth API error: HTTP {e.code}"}, status=e.code)
+    except URLError as e:
+        logger.warning("Unsloth proxy connection error: %s", e)
+        return web.json_response({"message": f"Could not reach Unsloth: {e.reason}"}, status=502)
+    except Exception as e:
+        logger.error("Unsloth proxy error: %s", e)
+        return web.json_response({"message": str(e)}, status=500)
@@ -0,0 +1,238 @@
+"""Video tab API routes: last-frame capture, animated GIF conversion, Edit
+tab probe/text-overlay burn-in, and Plan/Edit project file management."""
+
+import asyncio
+import logging
+
+from aiohttp import web
+
+from ..config import VIDEO_PLAN_DIR, VIDEO_EDIT_PROJECT_DIR
+from ..services.video_service import VideoService
+from ..services.video_plan_service import VideoPlanService
+from ..services.video_edit_project_service import VideoEditProjectService
+
+logger = logging.getLogger(__name__)
+
+_service = VideoService()
+_plan_service = VideoPlanService(VIDEO_PLAN_DIR)
+_edit_project_service = VideoEditProjectService(VIDEO_EDIT_PROJECT_DIR)
+
+
+def setup_routes(app: web.Application):
+    app.router.add_post("/api/wfm/video/frame/save-to-output", handle_save_frame)
+    app.router.add_post("/api/wfm/video/to-gif", handle_to_gif)
+    app.router.add_get("/api/wfm/video/edit/probe", handle_probe_video)
+    app.router.add_post("/api/wfm/video/edit/overlay-text", handle_overlay_text)
+
+    app.router.add_get("/api/wfm/video/plans", handle_list_plans)
+    app.router.add_get("/api/wfm/video/plans/content", handle_get_plan_content)
+    app.router.add_post("/api/wfm/video/plans/save", handle_save_plan)
+    app.router.add_post("/api/wfm/video/plans/delete", handle_delete_plan)
+    app.router.add_post("/api/wfm/video/index-image/save-to-output", handle_save_index_to_output)
+
+    app.router.add_get("/api/wfm/video/edit/projects", handle_list_edit_projects)
+    app.router.add_get("/api/wfm/video/edit/projects/content", handle_get_edit_project_content)
+    app.router.add_post("/api/wfm/video/edit/projects/save", handle_save_edit_project)
+    app.router.add_post("/api/wfm/video/edit/projects/delete", handle_delete_edit_project)
+
+
+async def handle_save_frame(request: web.Request) -> web.Response:
+    try:
+        body = await request.json()
+        image_base64 = body.get("image_base64", "")
+        if not image_base64:
+            return web.json_response({"error": "image_base64 required"}, status=400)
+        result = await asyncio.to_thread(_service.save_frame_to_output, image_base64)
+        return web.json_response({"status": "ok", **result})
+    except Exception as e:
+        logger.error("Error saving video frame to output: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def handle_to_gif(request: web.Request) -> web.Response:
+    try:
+        body = await request.json()
+        filename = body.get("filename", "")
+        subfolder = body.get("subfolder", "")
+        type_ = body.get("type", "output")
+        start_time = float(body.get("start_time") or 0)
+        end_time_raw = body.get("end_time")
+        end_time = float(end_time_raw) if end_time_raw not in (None, "") else None
+        fps = float(body.get("fps") or 10)
+        max_width_raw = body.get("max_width")
+        max_width = int(max_width_raw) if max_width_raw not in (None, "") else None
+
+        if not filename:
+            return web.json_response({"error": "filename required"}, status=400)
+
+        result = await asyncio.to_thread(
+            _service.convert_to_gif, filename, subfolder, type_, start_time, end_time, fps, max_width
+        )
+        return web.json_response({"status": "ok", **result})
+    except FileNotFoundError as e:
+        return web.json_response({"error": str(e)}, status=404)
+    except ValueError as e:
+        return web.json_response({"error": str(e)}, status=400)
+    except Exception as e:
+        logger.error("Error converting video to GIF: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def handle_probe_video(request: web.Request) -> web.Response:
+    filename = request.rel_url.query.get("filename", "")
+    subfolder = request.rel_url.query.get("subfolder", "")
+    type_ = request.rel_url.query.get("type", "input")
+    if not filename:
+        return web.json_response({"error": "filename required"}, status=400)
+    try:
+        result = await asyncio.to_thread(_service.probe_video, filename, subfolder, type_)
+        return web.json_response(result)
+    except FileNotFoundError as e:
+        return web.json_response({"error": str(e)}, status=404)
+    except ValueError as e:
+        return web.json_response({"error": str(e)}, status=400)
+    except Exception as e:
+        logger.error("Error probing video: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def handle_overlay_text(request: web.Request) -> web.Response:
+    try:
+        body = await request.json()
+        filename = body.get("filename", "")
+        subfolder = body.get("subfolder", "")
+        type_ = body.get("type", "output")
+        overlays = body.get("overlays") or []
+        delete_source = bool(body.get("delete_source"))
+        if not filename:
+            return web.json_response({"error": "filename required"}, status=400)
+        if not isinstance(overlays, list):
+            return web.json_response({"error": "overlays must be a list"}, status=400)
+
+        # Decode+re-encode of every frame — run off the event loop so other
+        # requests aren't stalled for the duration of the burn-in.
+        result = await asyncio.to_thread(
+            _service.overlay_text_on_video, filename, subfolder, type_, overlays, "video/wfm_edit", delete_source
+        )
+        return web.json_response({"status": "ok", **result})
+    except FileNotFoundError as e:
+        return web.json_response({"error": str(e)}, status=404)
+    except ValueError as e:
+        return web.json_response({"error": str(e)}, status=400)
+    except Exception as e:
+        logger.error("Error burning text overlay into video: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def handle_list_plans(request: web.Request) -> web.Response:
+    try:
+        result = await asyncio.to_thread(_plan_service.list_plans)
+        return web.json_response(result)
+    except Exception as e:
+        logger.error("Error listing video plans: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def handle_get_plan_content(request: web.Request) -> web.Response:
+    filename = request.rel_url.query.get("filename", "")
+    try:
+        data = await asyncio.to_thread(_plan_service.get_plan, filename)
+        return web.json_response({"data": data})
+    except FileNotFoundError:
+        return web.json_response({"error": "not found"}, status=404)
+    except ValueError as e:
+        return web.json_response({"error": str(e)}, status=400)
+    except Exception as e:
+        logger.error("Error getting video plan content: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def handle_save_plan(request: web.Request) -> web.Response:
+    try:
+        body = await request.json()
+        filename = body.get("filename", "")
+        data = body.get("data", {})
+        index_image_base64 = body.get("index_image_base64")
+        result = await asyncio.to_thread(_plan_service.save_plan, filename, data, index_image_base64)
+        return web.json_response({"status": "ok", **result})
+    except ValueError as e:
+        return web.json_response({"error": str(e)}, status=400)
+    except Exception as e:
+        logger.error("Error saving video plan: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def handle_delete_plan(request: web.Request) -> web.Response:
+    try:
+        body = await request.json()
+        filename = body.get("filename", "")
+        await asyncio.to_thread(_plan_service.delete_plan, filename)
+        return web.json_response({"status": "ok"})
+    except ValueError as e:
+        return web.json_response({"error": str(e)}, status=400)
+    except Exception as e:
+        logger.error("Error deleting video plan: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def handle_list_edit_projects(request: web.Request) -> web.Response:
+    try:
+        result = await asyncio.to_thread(_edit_project_service.list_projects)
+        return web.json_response(result)
+    except Exception as e:
+        logger.error("Error listing video edit projects: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def handle_get_edit_project_content(request: web.Request) -> web.Response:
+    filename = request.rel_url.query.get("filename", "")
+    try:
+        data = await asyncio.to_thread(_edit_project_service.get_project, filename)
+        return web.json_response({"data": data})
+    except FileNotFoundError:
+        return web.json_response({"error": "not found"}, status=404)
+    except ValueError as e:
+        return web.json_response({"error": str(e)}, status=400)
+    except Exception as e:
+        logger.error("Error getting video edit project content: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def handle_save_edit_project(request: web.Request) -> web.Response:
+    try:
+        body = await request.json()
+        filename = body.get("filename", "")
+        data = body.get("data", {})
+        result = await asyncio.to_thread(_edit_project_service.save_project, filename, data)
+        return web.json_response({"status": "ok", **result})
+    except ValueError as e:
+        return web.json_response({"error": str(e)}, status=400)
+    except Exception as e:
+        logger.error("Error saving video edit project: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def handle_delete_edit_project(request: web.Request) -> web.Response:
+    try:
+        body = await request.json()
+        filename = body.get("filename", "")
+        await asyncio.to_thread(_edit_project_service.delete_project, filename)
+        return web.json_response({"status": "ok"})
+    except ValueError as e:
+        return web.json_response({"error": str(e)}, status=400)
+    except Exception as e:
+        logger.error("Error deleting video edit project: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
+
+
+async def handle_save_index_to_output(request: web.Request) -> web.Response:
+    try:
+        body = await request.json()
+        image_base64 = body.get("image_base64", "")
+        if not image_base64:
+            return web.json_response({"error": "image_base64 required"}, status=400)
+        result = await asyncio.to_thread(_plan_service.save_index_image_to_output, image_base64)
+        return web.json_response({"status": "ok", **result})
+    except Exception as e:
+        logger.error("Error saving video index image to output: %s", e)
+        return web.json_response({"error": str(e)}, status=500)
@@ -1,8 +1,10 @@
 """
 Gallery Metadata Store - ギャラリー画像のメタデータ永続化
 """
+import copy
 import json
 import logging
+import threading
 from pathlib import Path

 logger = logging.getLogger(__name__)
@@ -24,14 +26,27 @@ class GalleryMetadataStore:
            {"name": str}
        ]
    }
+
+    self._data（特に "images" 辞書）は、バックグラウンドのフォルダインデックススレッド
+    （gallery_service.pyの_bg_index_folder）と、リクエストハンドラを処理するメインスレッドの
+    双方から並行に読み書きされる。ロックなしで辞書を反復（.items()/.values()/for key in ...や
+    json.dumpによるシリアライズ）している最中に別スレッドがキーを追加/削除すると
+    "dictionary changed size during iteration" が発生するため、_data へアクセスする
+    全メソッドを self._lock で保護する（re-entrant: ensure_group()がcreate_group()を
+    内部呼び出しするため、通常のLockではなくRLockを使う）。
    """

    def __init__(self, file_path: Path):
        self.file_path = file_path
+        self._lock = threading.RLock()
+        # ディスクへの実書き込み（JSONシリアライズ+ファイルI/O）を直列化するための
+        # 別ロック。_save_to_disk() を参照。
+        self._write_lock = threading.Lock()
        self._data: dict = {"images": {}, "groups": []}
        self._load()

    def _load(self):
+        # コンストラクタからのみ呼ばれ、この時点ではまだ他スレッドと共有されていないためロック不要
        if self.file_path.exists():
            try:
                with open(self.file_path, "r", encoding="utf-8") as f:
@@ -42,145 +57,233 @@ class GalleryMetadataStore:
                }
            except Exception as e:
                logger.warning("GalleryMetadataStore: load error: %s", e)
+                # 破損ファイルをリネームしてバックアップしておく。ここでリネームせずに
+                # 空の self._data のまま次の save() が走ると、破損直前までの全メタデータ
+                # (タグ/メモ/グループ登録)が跡形もなく上書きされ、二度と復元できなくなる
+                # (実際に発生した不具合: _save_to_disk が非アトミック書き込みだったため、
+                # 大量画像フォルダのBGインデックス処理中の頻繁な保存とComfyUIの終了タイミング
+                # が重なるとファイルが不完全な状態のまま残ることがあった — _save_to_disk側は
+                # os.replace()によるアトミック書き込みに修正済みだが、過去に壊れたファイルや
+                # 他要因による破損に備えてここでも保護しておく)。
+                try:
+                    backup_path = self.file_path.with_name(self.file_path.name + ".corrupt")
+                    self.file_path.replace(backup_path)
+                    logger.warning("GalleryMetadataStore: corrupt file backed up to %s", backup_path)
+                except Exception as backup_err:
+                    logger.warning("GalleryMetadataStore: failed to back up corrupt file: %s", backup_err)

    def _save_to_disk(self):
-        try:
-            self.file_path.parent.mkdir(parents=True, exist_ok=True)
-            with open(self.file_path, "w", encoding="utf-8") as f:
-                json.dump(self._data, f, ensure_ascii=False, indent=2)
-            return True
-        except Exception as e:
-            logger.error("GalleryMetadataStore: save error: %s", e)
-            return False
+        # 呼び出し元（save/create_group等）が既にself._lockを保持している前提の内部メソッド。
+        # ここではself._lock配下でスナップショット(deepcopy)を取るだけに留め、実際のJSON
+        # シリアライズ+ファイルI/Oはロックの外、別途self._write_lockで直列化して行う。
+        # 理由: gallery_metadata.jsonは画像数が多い環境では1MBを超えることがあり、
+        # self._lockを保持したままjson.dump+ファイル書き込みまで行うと、その間
+        # 他スレッドのget()（検索リクエストなど）が丸ごとブロックされてしまう
+        # （実際に発生した不具合: バックグラウンドインデックス処理が10枚ごとに保存する際、
+        # 検索リクエストのget()呼び出しがロック待ちになり、50枚程度のフォルダに対する
+        # 検索でも数秒〜十数秒かかっていた）。deepcopy自体はメモリ内操作でファイルI/Oより
+        # 大幅に軽いため、ロック内に残しても実用上のブロック時間は無視できるレベルになる。
+        snapshot = copy.deepcopy(self._data)
+        return self._write_snapshot(snapshot)
+
+    def _write_snapshot(self, snapshot: dict) -> bool:
+        """self._lockの外から呼ばれる。一時ファイルに書き出してから置き換える
+        (os.replace相当のPath.replace)ことで書き込みをアトミックにする。素朴な
+        open(path, "w") での直接上書きだと、書き込み完了前に他プロセスが読むと
+        不完全なJSONを掴む(torn read)うえ、書き込み中にComfyUIプロセスが終了すると
+        ファイルが壊れたまま残る — 大量画像フォルダのBGインデックス処理で書き込み
+        頻度が高い環境ほど発生しやすく、次回起動時のロード失敗→空データでの全上書き
+        という形でユーザーの登録済みグループ/タグ/メモが消失する原因になっていた。
+        self._write_lockで直列化し、複数スレッドの書き込みが競合して古いスナップショット
+        が新しいものを上書きしないようにする。"""
+        with self._write_lock:
+            try:
+                self.file_path.parent.mkdir(parents=True, exist_ok=True)
+                tmp_path = self.file_path.with_name(self.file_path.name + ".tmp")
+                with open(tmp_path, "w", encoding="utf-8") as f:
+                    json.dump(snapshot, f, ensure_ascii=False, indent=2)
+                tmp_path.replace(self.file_path)
+                return True
+            except Exception as e:
+                logger.error("GalleryMetadataStore: save error: %s", e)
+                return False

    def _normalize_path(self, image_path: str) -> str:
        return str(Path(image_path)).replace("\\", "/")

    def get(self, image_path: str) -> dict:
        key = self._normalize_path(image_path)
-        return dict(self._data["images"].get(key, {}))
+        with self._lock:
+            return dict(self._data["images"].get(key, {}))

    def save(self, image_path: str, data: dict) -> bool:
        key = self._normalize_path(image_path)
-        existing = self._data["images"].get(key, {})
-        existing.update(data)
+        with self._lock:
+            existing = self._data["images"].get(key, {})
+            existing.update(data)
+            allowed = {"favorite", "tags", "memo", "groups", "workflow"}
+            existing = {k: v for k, v in existing.items() if k in allowed}
+            self._data["images"][key] = existing
+            return self._save_to_disk()
+
+    def save_batch(self, entries: dict[str, dict]) -> bool:
+        """複数画像のメタデータを1回のディスク書き込みでまとめて保存する。
+        バックグラウンドインデックス処理のように多数の画像を連続して保存する場合、
+        1件ずつsave()を呼ぶと画像の数だけJSONシリアライズ+ファイルI/Oが発生してしまう
+        （実際に発生した不具合: gallery_metadata.jsonが1MBを超える環境で10枚ごとに
+        個別save()していたため、検索リクエストが完了するまで数秒〜十数秒かかっていた）。"""
+        if not entries:
+            return True
        allowed = {"favorite", "tags", "memo", "groups", "workflow"}
-        existing = {k: v for k, v in existing.items() if k in allowed}
-        self._data["images"][key] = existing
-        return self._save_to_disk()
+        with self._lock:
+            for image_path, data in entries.items():
+                key = self._normalize_path(image_path)
+                existing = self._data["images"].get(key, {})
+                existing.update(data)
+                existing = {k: v for k, v in existing.items() if k in allowed}
+                self._data["images"][key] = existing
+            return self._save_to_disk()

    # ── グループ管理 ──────────────────────────────────────────────

    def list_groups(self) -> list[dict]:
-        return list(self._data.get("groups", []))
+        with self._lock:
+            return list(self._data.get("groups", []))

    def create_group(self, name: str) -> bool:
-        groups = self._data.get("groups", [])
-        if any(g["name"] == name for g in groups):
-            return False
-        groups.append({"name": name})
-        self._data["groups"] = groups
-        return self._save_to_disk()
+        with self._lock:
+            groups = self._data.get("groups", [])
+            if any(g["name"] == name for g in groups):
+                return False
+            groups.append({"name": name})
+            self._data["groups"] = groups
+            return self._save_to_disk()

    def rename_group(self, old_name: str, new_name: str) -> bool:
        """グループ名を変更し、全画像のgroupsフィールドも更新する"""
-        groups = self._data.get("groups", [])
-        if not any(g["name"] == old_name for g in groups):
-            return False
-        if any(g["name"] == new_name for g in groups):
-            return False  # 新名前が既に存在
-        # グループリスト更新
-        for g in groups:
-            if g["name"] == old_name:
-                g["name"] = new_name
-                break
-        # 全画像のgroupsフィールドを更新
-        for meta in self._data["images"].values():
-            img_groups = meta.get("groups", [])
-            if old_name in img_groups:
-                meta["groups"] = [new_name if g == old_name else g for g in img_groups]
-        return self._save_to_disk()
+        with self._lock:
+            groups = self._data.get("groups", [])
+            if not any(g["name"] == old_name for g in groups):
+                return False
+            if any(g["name"] == new_name for g in groups):
+                return False  # 新名前が既に存在
+            # グループリスト更新
+            for g in groups:
+                if g["name"] == old_name:
+                    g["name"] = new_name
+                    break
+            # 全画像のgroupsフィールドを更新
+            for meta in self._data["images"].values():
+                img_groups = meta.get("groups", [])
+                if old_name in img_groups:
+                    meta["groups"] = [new_name if g == old_name else g for g in img_groups]
+            return self._save_to_disk()

    def delete_group(self, name: str) -> bool:
-        groups = [g for g in self._data.get("groups", []) if g["name"] != name]
-        self._data["groups"] = groups
-        # 画像のgroupsからも削除
-        for meta in self._data["images"].values():
-            if name in meta.get("groups", []):
-                meta["groups"] = [g for g in meta["groups"] if g != name]
-        return self._save_to_disk()
+        with self._lock:
+            groups = [g for g in self._data.get("groups", []) if g["name"] != name]
+            self._data["groups"] = groups
+            # 画像のgroupsからも削除
+            for meta in self._data["images"].values():
+                if name in meta.get("groups", []):
+                    meta["groups"] = [g for g in meta["groups"] if g != name]
+            return self._save_to_disk()

    def list_images_in_group(self, group_name: str) -> list[str]:
-        result = []
-        for key, meta in self._data["images"].items():
-            if group_name in meta.get("groups", []):
-                result.append(key)
-        return result
+        with self._lock:
+            result = []
+            for key, meta in self._data["images"].items():
+                if group_name in meta.get("groups", []):
+                    result.append(key)
+            return result

    def remove_stale_paths_from_group(self, group_name: str, stale_paths: list) -> int:
        """存在しないパスをグループから一括削除する（1回の保存で完結）"""
-        stale_set = {self._normalize_path(p) for p in stale_paths}
-        count = 0
-        for key, meta in self._data["images"].items():
-            if key in stale_set and group_name in meta.get("groups", []):
-                meta["groups"] = [g for g in meta["groups"] if g != group_name]
-                count += 1
-        if count:
-            self._save_to_disk()
-        return count
+        with self._lock:
+            stale_set = {self._normalize_path(p) for p in stale_paths}
+            count = 0
+            for key, meta in self._data["images"].items():
+                if key in stale_set and group_name in meta.get("groups", []):
+                    meta["groups"] = [g for g in meta["groups"] if g != group_name]
+                    count += 1
+            if count:
+                self._save_to_disk()
+            return count

    def get_group_member_set(self, group_name: str) -> set:
        """グループメンバーのパスをsetで返す（高速フィルタ用）"""
-        return {
-            key for key, meta in self._data["images"].items()
-            if group_name in meta.get("groups", [])
-        }
+        with self._lock:
+            return {
+                key for key, meta in self._data["images"].items()
+                if group_name in meta.get("groups", [])
+            }

    def clear_group(self, group_name: str) -> bool:
        """グループ内の全画像を除外する（グループ自体は残す）"""
-        for meta in self._data["images"].values():
-            if group_name in meta.get("groups", []):
-                meta["groups"] = [g for g in meta["groups"] if g != group_name]
-        return self._save_to_disk()
+        with self._lock:
+            for meta in self._data["images"].values():
+                if group_name in meta.get("groups", []):
+                    meta["groups"] = [g for g in meta["groups"] if g != group_name]
+            return self._save_to_disk()

    def ensure_group(self, name: str) -> bool:
        """グループが存在しない場合のみ作成する"""
-        if any(g["name"] == name for g in self._data.get("groups", [])):
-            return True
-        return self.create_group(name)
+        with self._lock:
+            if any(g["name"] == name for g in self._data.get("groups", [])):
+                return True
+            return self.create_group(name)

    def delete(self, image_path: str) -> bool:
        """画像のメタデータエントリを削除する"""
        key = self._normalize_path(image_path)
-        if key in self._data["images"]:
-            del self._data["images"][key]
-            return self._save_to_disk()
-        return True
+        with self._lock:
+            if key in self._data["images"]:
+                del self._data["images"][key]
+                return self._save_to_disk()
+            return True

    def rename_path(self, old_path: str, new_path: str) -> bool:
        """画像のパスキーを変更する（ファイル移動後のメタデータ引継ぎ）"""
        old_key = self._normalize_path(old_path)
        new_key = self._normalize_path(new_path)
-        if old_key in self._data["images"]:
-            self._data["images"][new_key] = self._data["images"].pop(old_key)
-            return self._save_to_disk()
-        return True
+        with self._lock:
+            if old_key in self._data["images"]:
+                self._data["images"][new_key] = self._data["images"].pop(old_key)
+                return self._save_to_disk()
+            return True

-    def cleanup_stale_images(self, folder_path: str, existing_paths: set) -> int:
+    def cleanup_stale_images(self, folder_path: str, existing_paths: set, recursive: bool = True) -> int:
        """folder_path 配下の存在しないファイルのメタデータを削除する。
        existing_paths: そのフォルダの現在のファイルパス集合（_normalize_path 済み）
+        recursive: False の場合、folder_path 直下のファイルのみを対象にする。
+            呼び出し元(list_images)が非recursiveスキャン(フォルダ直下のみ列挙)の
+            結果を existing_paths として渡してくる場合、サブフォルダ内のファイルは
+            existing_paths に含まれない。それにもかかわらず対象範囲を「folder_path配下
+            全階層」のままにすると、サブフォルダ内画像のメタデータ(tags/memo等)を
+            "存在しない"と誤判定して全削除してしまう(実際に発生した不具合: サブフォルダ
+            に動画を保存する運用で、ルートフォルダを非recursiveで開くたびに
+            サブフォルダ内の全メタデータが失われていた)。
        """
        folder_key = self._normalize_path(folder_path)
        if not folder_key.endswith("/"):
            folder_key += "/"
-        stale = [
-            key for key in self._data["images"]
-            if key.startswith(folder_key) and key not in existing_paths
-        ]
-        if not stale:
-            return 0
-        for key in stale:
-            del self._data["images"][key]
-        self._save_to_disk()
-        logger.info("Cleaned up %d stale metadata entries from %s", len(stale), folder_path)
-        return len(stale)
+
+        def _in_scope(key: str) -> bool:
+            if not key.startswith(folder_key):
+                return False
+            if recursive:
+                return True
+            return "/" not in key[len(folder_key):]
+
+        with self._lock:
+            stale = [
+                key for key in self._data["images"]
+                if _in_scope(key) and key not in existing_paths
+            ]
+            if not stale:
+                return 0
+            for key in stale:
+                del self._data["images"][key]
+            self._save_to_disk()
+            logger.info("Cleaned up %d stale metadata entries from %s", len(stale), folder_path)
+            return len(stale)
@@ -0,0 +1,138 @@
+"""Lab tab plan file management service (JSON plan + optional PNG index thumbnail)."""
+
+import base64
+import json
+import logging
+from datetime import datetime, timezone
+from pathlib import Path
+
+logger = logging.getLogger(__name__)
+
+
+class LabPlanService:
+    def __init__(self, plan_dir: Path):
+        self.plan_dir = plan_dir
+        self.plan_dir.mkdir(parents=True, exist_ok=True)
+
+    # ------------------------------------------------------------------
+    # Path safety
+    # ------------------------------------------------------------------
+
+    def _safe_path(self, filename: str, ext: str = ".json") -> Path | None:
+        if not filename or not filename.strip():
+            return None
+        name = filename.strip()
+        if not name.endswith(ext):
+            name = name + ext
+        if "/" in name or "\\" in name or name in (".", "..") or "\x00" in name:
+            return None
+        resolved = (self.plan_dir / name).resolve()
+        plan_dir_resolved = self.plan_dir.resolve()
+        if resolved != plan_dir_resolved and not str(resolved).startswith(str(plan_dir_resolved) + "\\") and not str(resolved).startswith(str(plan_dir_resolved) + "/"):
+            return None
+        return resolved
+
+    def _now_iso(self) -> str:
+        return datetime.now(timezone.utc).isoformat().replace("+00:00", "Z")
+
+    # ------------------------------------------------------------------
+    # CRUD
+    # ------------------------------------------------------------------
+
+    def list_plans(self) -> list[dict]:
+        if not self.plan_dir.is_dir():
+            return []
+        result = []
+        for path in sorted(self.plan_dir.glob("*.json")):
+            try:
+                with open(path, "r", encoding="utf-8") as f:
+                    data = json.load(f)
+            except Exception as e:
+                logger.warning("Skipping unreadable lab plan %s: %s", path.name, e)
+                continue
+
+            stem = path.stem
+            thumbnail = None
+            thumb_path = self.plan_dir / f"{stem}.png"
+            if thumb_path.is_file():
+                thumbnail = f"/wfm_data/lab_plan/{stem}.png"
+
+            result.append({
+                "filename": path.name,
+                "name": data.get("name", stem),
+                "note": data.get("note", ""),
+                "batch_count": data.get("batch_count", 1),
+                "updated_at": data.get("updated_at", ""),
+                "thumbnail": thumbnail,
+            })
+        result.sort(key=lambda p: p.get("updated_at", ""), reverse=True)
+        return result
+
+    def get_plan(self, filename: str) -> dict:
+        path = self._safe_path(filename)
+        if path is None:
+            raise ValueError(f"Invalid filename: {filename}")
+        if not path.is_file():
+            raise FileNotFoundError(f"Plan not found: {filename}")
+        with open(path, "r", encoding="utf-8") as f:
+            return json.load(f)
+
+    def save_plan(self, filename: str, data: dict, index_image_base64: str | None = None) -> dict:
+        path = self._safe_path(filename)
+        if path is None:
+            raise ValueError(f"Invalid filename: {filename}")
+
+        data = dict(data)
+        data["updated_at"] = self._now_iso()
+
+        path.parent.mkdir(parents=True, exist_ok=True)
+        with open(path, "w", encoding="utf-8") as f:
+            json.dump(data, f, ensure_ascii=False, indent=2)
+
+        if index_image_base64:
+            self.save_index_image(filename, index_image_base64)
+
+        return {"filename": path.name, "updated_at": data["updated_at"]}
+
+    def save_index_image(self, filename: str, image_base64: str) -> None:
+        path = self._safe_path(filename)
+        if path is None:
+            raise ValueError(f"Invalid filename: {filename}")
+        stem = path.stem
+        thumb_path = self.plan_dir / f"{stem}.png"
+
+        # Accept both raw base64 and data: URL forms
+        b64 = image_base64
+        if "," in b64 and b64.strip().lower().startswith("data:"):
+            b64 = b64.split(",", 1)[1]
+
+        image_bytes = base64.b64decode(b64)
+        with open(thumb_path, "wb") as f:
+            f.write(image_bytes)
+
+    def save_index_image_to_output(self, image_base64: str, filename_prefix: str = "Lab_index") -> dict:
+        """Saves the contact-sheet index image into ComfyUI's own output folder,
+        alongside the images generated during the run (unlike save_index_image,
+        which saves it next to the plan file in plan_dir)."""
+        b64 = image_base64
+        if "," in b64 and b64.strip().lower().startswith("data:"):
+            b64 = b64.split(",", 1)[1]
+        image_bytes = base64.b64decode(b64)
+
+        import folder_paths  # type: ignore
+        output_dir = folder_paths.get_output_directory()
+        full_output_folder, filename, counter, subfolder, _ = folder_paths.get_save_image_path(filename_prefix, output_dir)
+        save_name = f"{filename}_{counter:05}_.png"
+        save_path = Path(full_output_folder) / save_name
+        save_path.write_bytes(image_bytes)
+        return {"filename": save_name, "subfolder": subfolder}
+
+    def delete_plan(self, filename: str) -> None:
+        path = self._safe_path(filename)
+        if path is None:
+            raise ValueError(f"Invalid filename: {filename}")
+        if path.is_file():
+            path.unlink()
+        thumb_path = self.plan_dir / f"{path.stem}.png"
+        if thumb_path.is_file():
+            thumb_path.unlink()
@@ -0,0 +1,228 @@
+"""AI skill (.md system prompt) file management service."""
+
+import logging
+import re
+from pathlib import Path
+
+logger = logging.getLogger(__name__)
+
+ALLOWED_EXTS = {"md"}
+
+DEFAULT_SKILL_FILENAME = "svg-icon.md"
+
+DEFAULT_SKILL_CONTENT = """---
+name: SVG Icon Generator
+description: Produces clean, minimal, valid SVG icons and simple illustrations.
+---
+
+You are an expert SVG icon and illustration designer. When the user asks for an icon, logo, pictogram, diagram, character, animal, or any vector graphic, respond with valid, clean SVG markup.
+
+## Composition process (do this before writing markup - skipping this step is the main cause of unrecognizable output)
+- Break the subject down into 3-8 distinct parts that make it recognizable (e.g. a bird: body, head, beak, eye, wing, tail; a house: wall, roof, door, window). Drop parts that are not essential.
+- Decide each part's approximate position, size, and draw order within the viewBox (elements listed later in the markup are drawn on top).
+- Pick the simplest shape that captures each part's silhouette: `<circle>`/`<ellipse>` for round parts, `<rect>` for rectangular parts, `<polygon>` for angular parts (beaks, ears, leaves, roofs). For a rounded organic outline that no primitive can approximate well (a body silhouette, a wing, a leaf edge), use a short `<path>` with 2-4 smooth curve commands (`Q` or `C`) instead of a plain circle - a few deliberate curve points beat a distorted primitive.
+- Never fall back to drawing an unrelated blob plus a few disconnected decorative lines when a subject is hard to render - always decompose it into the named parts above instead, even if each part is crude.
+
+## Output rules
+- Always wrap the SVG markup in a fenced code block labeled `svg`, e.g. ```svg ... ```.
+- Keep any explanation brief and place it OUTSIDE the code block, never mixed inside the SVG.
+- Output exactly one `<svg>...</svg>` element per code block.
+
+## Structure rules
+- Always include a `viewBox` attribute (e.g. `viewBox="0 0 24 24"`). Do not hardcode large pixel `width`/`height`; if you set them, make them match the viewBox aspect ratio.
+- Use a small, round coordinate system (0-24 or 0-100).
+- Round coordinate values to at most 2 decimal places.
+- Keep every `<path>` short (at most about 6 commands) - long, intricate paths are where quality breaks down most often.
+- Group related elements with `<g>` when it clarifies structure, but do not over-nest.
+
+## Color rules
+- For single-color icons, use `fill="currentColor"` (or `stroke="currentColor"` for line icons) so the icon inherits the surrounding text color.
+- For multi-color illustrations, use explicit hex colors (e.g. `#4A90D9`) - never named CSS colors like `"blue"`.
+- Avoid gradients, filters, and blend modes unless the user explicitly asks for a glossy/gradient style - they rarely render correctly from generated coordinates.
+
+## Accessibility
+- Include a `<title>` element as the first child of `<svg>` describing what the icon depicts.
+
+## Security (mandatory - do not violate)
+- Never include `<script>`, `<foreignObject>`, event handler attributes (`onload`, `onclick`, etc.), or `<a>`/`href` links to external URLs.
+- Never reference external resources (no `xlink:href` to remote URLs, no `<image>` with external `src`).
+
+## Example 1 - simple geometric icon (single color, primitives only)
+
+Request: "Sun icon"
+
+Parts: disc (circle), 8 rays (lines).
+
+```svg
+<svg viewBox="0 0 24 24" xmlns="http://www.w3.org/2000/svg">
+  <title>Sun</title>
+  <circle cx="12" cy="12" r="5" fill="currentColor"/>
+  <g stroke="currentColor" stroke-width="2" stroke-linecap="round">
+    <line x1="12" y1="1" x2="12" y2="4"/>
+    <line x1="12" y1="20" x2="12" y2="23"/>
+    <line x1="4.22" y1="4.22" x2="6.34" y2="6.34"/>
+    <line x1="17.66" y1="17.66" x2="19.78" y2="19.78"/>
+    <line x1="1" y1="12" x2="4" y2="12"/>
+    <line x1="20" y1="12" x2="23" y2="12"/>
+    <line x1="4.22" y1="19.78" x2="6.34" y2="17.66"/>
+    <line x1="17.66" y1="6.34" x2="19.78" y2="4.22"/>
+  </g>
+</svg>
+```
+
+## Example 2 - organic subject (multi-color, decomposed into parts)
+
+Request: "Bird icon"
+
+Parts: body (rounded outline via a short curved path), head (circle), beak (small triangle), eye (dot), wing (small curved path) - each drawn as its own element, layered head/beak/eye on top of the body.
+
+```svg
+<svg viewBox="0 0 24 24" xmlns="http://www.w3.org/2000/svg">
+  <title>Bird</title>
+  <path d="M4 16 Q4 10 11 9 Q18 8 20 13 Q20 17 14 18 Q7 19 4 16 Z" fill="#4A90D9"/>
+  <path d="M8 14 Q5 12 3 14 Q6 16 9 16 Z" fill="#3576B8"/>
+  <circle cx="17" cy="10" r="3.2" fill="#4A90D9"/>
+  <polygon points="20,10 23,9.3 20,11.4" fill="#F2B807"/>
+  <circle cx="18" cy="9" r="0.6" fill="#1A1A1A"/>
+</svg>
+```
+
+Follow this pattern for every request: list the parts first, represent each with the simplest adequate shape, then assemble - never skip straight to unstructured shapes.
+"""
+
+SKILL_CREATOR_FILENAME = "skill-creator.md"
+
+SKILL_CREATOR_CONTENT = """---
+name: Skill Creator
+description: Interactively interviews you and drafts a new WFS chat skill (.md system prompt) ready to save.
+---
+
+You are a skill-design assistant embedded in ComfyUI Workflow Studio's AI TOOL Chat pane. Your job is to interactively help the user design a NEW "skill" - a markdown file with frontmatter (`name`, `description`) followed by system-prompt instructions. Once saved, a skill can be selected from a dropdown and is silently prepended to future chat messages as a system prompt.
+
+## How to conduct the interview
+- Ask ONE focused question at a time, never a bulleted list of questions. Wait for the user's answer before asking the next one.
+- Cover, in this order, only what is not already clear from context:
+  1. What task or domain should the skill specialize in (what should the model do differently once this skill is active)?
+  2. What output format is expected - plain prose, a specific fenced code block language, a fixed structure, a length limit?
+  3. Any hard constraints or things to avoid (tone, forbidden content, security concerns, things past attempts got wrong)?
+  4. Would a short worked example help smaller/local models follow the pattern more reliably? If yes, ask what a good example input/output looks like, or offer to draft one.
+- Keep it short - 3 to 5 questions is usually enough. If the user says "just generate it", "that's enough", or similar at any point, stop asking and produce the best skill you can from what you already have.
+
+## Output format for the finished skill
+- Once you have enough information, output the complete skill file in a single fenced code block labeled `skill` (```skill ... ```). Never mix prose inside that block - explanation goes outside it.
+- The block must start with frontmatter exactly in this shape:
+  ---
+  name: <short display name, shown in the skill dropdown>
+  description: <one sentence, shown as a tooltip in the dropdown>
+  ---
+- After the frontmatter, write clear, imperative system-prompt instructions for the target skill: what role the model should take, concrete output-format rules, hard constraints, and - if useful - one short worked example following a "request -> ideal output" shape.
+- After the code block, tell the user in one line that they can click the "Save as new skill" button below the message to add it, or copy the block manually into a new skill.
+"""
+
+_FRONTMATTER_RE = re.compile(r"^---\r?\n(.*?)\r?\n---\r?\n?", re.DOTALL)
+
+
+def _parse_frontmatter(content: str) -> dict:
+    """Extract a shallow `key: value` frontmatter block, if present."""
+    m = _FRONTMATTER_RE.match(content)
+    if not m:
+        return {}
+    fields: dict = {}
+    for line in m.group(1).splitlines():
+        if ":" not in line:
+            continue
+        key, _, value = line.partition(":")
+        key = key.strip()
+        value = value.strip()
+        if key:
+            fields[key] = value
+    return fields
+
+
+class SkillService:
+    def __init__(self, skills_dir: Path):
+        self.skills_dir = skills_dir
+        self.skills_dir.mkdir(parents=True, exist_ok=True)
+        self._seed_default_skill()
+
+    def _seed_default_skill(self) -> None:
+        """Seed a starter skill file the first time the directory is empty."""
+        try:
+            has_any = any(
+                p.is_file() and p.suffix.lstrip(".").lower() in ALLOWED_EXTS
+                for p in self.skills_dir.iterdir()
+            )
+        except FileNotFoundError:
+            has_any = False
+        if not has_any:
+            (self.skills_dir / DEFAULT_SKILL_FILENAME).write_text(
+                DEFAULT_SKILL_CONTENT, encoding="utf-8"
+            )
+            (self.skills_dir / SKILL_CREATOR_FILENAME).write_text(
+                SKILL_CREATOR_CONTENT, encoding="utf-8"
+            )
+
+    # ------------------------------------------------------------------
+    # File CRUD
+    # ------------------------------------------------------------------
+
+    def list_skills(self) -> list[dict]:
+        """Return sorted list of skill files with parsed frontmatter metadata."""
+        if not self.skills_dir.exists():
+            return []
+        files = []
+        for path in sorted(self.skills_dir.glob("*")):
+            if not (path.is_file() and path.suffix.lstrip(".").lower() in ALLOWED_EXTS):
+                continue
+            try:
+                content = path.read_text(encoding="utf-8")
+            except Exception:
+                content = ""
+            meta = _parse_frontmatter(content)
+            files.append({
+                "filename": path.name,
+                "name": meta.get("name") or path.stem,
+                "description": meta.get("description", ""),
+                "size": path.stat().st_size,
+            })
+        return files
+
+    def get_content(self, filename: str) -> str:
+        path = self._safe_path(filename)
+        if path is None:
+            raise ValueError(f"Invalid filename: {filename}")
+        if not path.is_file():
+            raise FileNotFoundError(f"File not found: {filename}")
+        return path.read_text(encoding="utf-8")
+
+    def save_file(self, filename: str, content: str) -> dict:
+        path = self._safe_path(filename)
+        if path is None:
+            raise ValueError(f"Invalid filename: {filename}")
+        path.write_text(content, encoding="utf-8")
+        meta = _parse_frontmatter(content)
+        return {
+            "filename": path.name,
+            "name": meta.get("name") or path.stem,
+            "description": meta.get("description", ""),
+            "size": path.stat().st_size,
+        }
+
+    def delete_file(self, filename: str) -> None:
+        path = self._safe_path(filename)
+        if path is None:
+            raise ValueError(f"Invalid filename: {filename}")
+        if path.is_file():
+            path.unlink()
+
+    def _safe_path(self, filename: str) -> Path | None:
+        if not filename or not filename.strip():
+            return None
+        # Skills are a flat directory - reject any path separator (no subfolders).
+        name = filename.strip()
+        if "/" in name or "\\" in name or name in (".", ".."):
+            return None
+        ext = Path(name).suffix.lstrip(".").lower()
+        if ext not in ALLOWED_EXTS:
+            return None
+        return self.skills_dir / name
@@ -5,6 +5,7 @@ import io
 import logging
 import sqlite3
 from pathlib import Path
+from typing import List

 logger = logging.getLogger(__name__)

@@ -85,6 +86,20 @@ class TaggerDbService:
            conn.execute("DELETE FROM images WHERE id=?", (row_id,))
            conn.commit()

+    def delete_bulk(self, row_ids: List[int]) -> int:
+        if not row_ids:
+            return 0
+
+        placeholders = ",".join("?" for _ in row_ids)
+
+        with self._conn() as conn:
+            cur = conn.execute(
+                f"DELETE FROM images WHERE id IN ({placeholders})",
+                row_ids,
+            )
+            conn.commit()
+            return cur.rowcount
+
    def export_csv(self) -> str:
        with self._conn() as conn:
            rows = conn.execute(
@@ -5,11 +5,14 @@ import csv
 import io
 import json
 import logging
+import os
+import re
 import tempfile
 import threading
 import urllib.request
 from pathlib import Path
 from typing import Optional
+from urllib.parse import urlparse

 import numpy as np
 from PIL import Image, ImageOps, PngImagePlugin
@@ -18,6 +21,20 @@ logger = logging.getLogger(__name__)

 _model_lock = threading.Lock()

+# Unsloth requires an Authorization: Bearer <UNSLOTH_API_KEY> header even for
+# local access. api_url is client-supplied per request, so without a host
+# check a client could point it at an arbitrary server and exfiltrate the key
+# (SSRF). Mirrors unsloth_routes.py's _is_allowed_base_url/_ALLOWED_HOSTS.
+_UNSLOTH_ALLOWED_HOSTS = {"localhost", "127.0.0.1", "::1"}
+
+
+def _is_allowed_unsloth_url(api_url: str) -> bool:
+    try:
+        parsed = urlparse(api_url)
+        return parsed.scheme in ("http", "https") and parsed.hostname in _UNSLOTH_ALLOWED_HOSTS
+    except Exception:
+        return False
+

 class TaggerService:
    def __init__(self, models_dir: Path, settings_file: Path):
@@ -185,19 +202,33 @@ class TaggerService:
    def _predict_onnx(self, img: Image.Image, data: dict, thr: float, char_thr: float) -> list:
        shape = data["input_shape"]
        fmt = "NHWC"
-        size = (224, 224)
+        size = 224
        if len(shape) == 4:
            if shape[1] == 3 and isinstance(shape[2], int) and shape[2] > 0:
                fmt = "NCHW"
-                size = (int(shape[3]), int(shape[2]))
+                size = int(shape[2])
            elif shape[3] == 3 and isinstance(shape[1], int) and shape[1] > 0:
                fmt = "NHWC"
-                size = (int(shape[2]), int(shape[1]))
+                size = int(shape[1])

        img = ImageOps.exif_transpose(img)
-        if img.mode != "RGB":
-            img = img.convert("RGB")
-        arr = np.array(img.resize(size, Image.Resampling.LANCZOS), dtype=np.float32) / 255.0
+        # WD Tagger系標準の前処理: 透過は白背景で合成 → アスペクト比を維持したまま
+        # 白背景で正方形にパディング → リサイズ → RGB→BGR → 0-255のfloat32のまま(NHWC)
+        if img.mode != "RGBA":
+            img = img.convert("RGBA")
+        canvas = Image.new("RGBA", img.size, (255, 255, 255))
+        canvas.paste(img, mask=img)
+        img = canvas.convert("RGB")
+
+        w, h = img.size
+        max_dim = max(w, h)
+        padded = Image.new("RGB", (max_dim, max_dim), (255, 255, 255))
+        padded.paste(img, ((max_dim - w) // 2, (max_dim - h) // 2))
+        if max_dim != size:
+            padded = padded.resize((size, size), Image.Resampling.BICUBIC)
+
+        arr = np.array(padded, dtype=np.float32)
+        arr = np.ascontiguousarray(arr[:, :, ::-1])  # RGB -> BGR
        if fmt == "NCHW":
            arr = arr.transpose((2, 0, 1))
        arr = np.expand_dims(arr, 0)
@@ -223,39 +254,112 @@ class TaggerService:
                tags.append(label.replace("character:", ""))
        return tags

-    # ── Ollama VLM ────────────────────────────────────────────
+    # ── VLM Tagging (Ollama / LM Studio / Lemonade / Unsloth) ──

-    def ollama_models(self, api_url: str) -> list:
+    @staticmethod
+    def _unsloth_api_key() -> Optional[str]:
+        """UNSLOTH_API_KEY を環境変数(.env)から取得。Unslothはローカルでも常に必須。"""
+        return os.environ.get("UNSLOTH_API_KEY", "").strip() or None
+
+    @staticmethod
+    def _strip_thinking_tags(text: str) -> str:
+        text = re.sub(r"<think>[\s\S]*?</think>", "", text, flags=re.IGNORECASE)
+        text = re.sub(r"<thinking>[\s\S]*?</thinking>", "", text, flags=re.IGNORECASE)
+        return text.strip()
+
+    def vlm_models(self, backend: str, api_url: str) -> list:
+        backend = (backend or "ollama").lower()
        try:
-            req = urllib.request.Request(api_url.rstrip("/") + "/api/tags")
+            if backend == "ollama":
+                req = urllib.request.Request(api_url.rstrip("/") + "/api/tags")
+                with urllib.request.urlopen(req, timeout=5) as resp:
+                    data = json.loads(resp.read().decode("utf-8"))
+                return sorted(m["name"] for m in data.get("models", []))
+
+            headers = {}
+            if backend == "unsloth":
+                if not _is_allowed_unsloth_url(api_url):
+                    logger.error("vlm_models: Unsloth backend URL must point to localhost/127.0.0.1/::1")
+                    return []
+                key = self._unsloth_api_key()
+                if not key:
+                    logger.error("vlm_models: UNSLOTH_API_KEY is not set")
+                    return []
+                headers["Authorization"] = f"Bearer {key}"
+            req = urllib.request.Request(api_url.rstrip("/") + "/v1/models", headers=headers)
            with urllib.request.urlopen(req, timeout=5) as resp:
                data = json.loads(resp.read().decode("utf-8"))
-            return sorted(m["name"] for m in data.get("models", []))
+            return sorted(m["id"] for m in data.get("data", []))
        except Exception as e:
-            logger.error("ollama_models: %s", e)
+            logger.error("vlm_models: %s", e)
            return []

-    def ollama_predict(self, image_b64: str, api_url: str, model: str, prompt: str, max_tags: int = 40) -> dict:
-        payload = json.dumps({
-            "model": model,
-            "messages": [{"role": "user", "content": prompt, "images": [image_b64]}],
-            "stream": False,
-            "options": {"temperature": 0.7, "num_ctx": 4096},
-        }).encode("utf-8")
+    def vlm_predict(self, image_b64: str, backend: str, api_url: str, model: str, prompt: str, max_tags: int = 40,
+                     thinking_mode: bool = False, max_tokens: int = 0) -> dict:
+        backend = (backend or "ollama").lower()
        try:
-            req = urllib.request.Request(
-                api_url.rstrip("/") + "/api/chat",
-                data=payload,
-                headers={"Content-Type": "application/json"},
-                method="POST",
-            )
-            with urllib.request.urlopen(req, timeout=180) as resp:
-                data = json.loads(resp.read().decode("utf-8"))
-            content = data.get("message", {}).get("content", "")
+            if backend == "ollama":
+                body = {
+                    "model": model,
+                    "messages": [{"role": "user", "content": prompt, "images": [image_b64]}],
+                    "stream": False,
+                    "think": bool(thinking_mode),
+                    "options": {"temperature": 0.7, "num_ctx": 4096},
+                }
+                if max_tokens > 0:
+                    body["options"]["num_predict"] = max_tokens
+                payload = json.dumps(body).encode("utf-8")
+                req = urllib.request.Request(
+                    api_url.rstrip("/") + "/api/chat",
+                    data=payload,
+                    headers={"Content-Type": "application/json"},
+                    method="POST",
+                )
+                with urllib.request.urlopen(req, timeout=180) as resp:
+                    data = json.loads(resp.read().decode("utf-8"))
+                content = data.get("message", {}).get("content", "")
+            else:
+                headers = {"Content-Type": "application/json"}
+                if backend == "unsloth":
+                    if not _is_allowed_unsloth_url(api_url):
+                        return {"error": "Unsloth backend URL must point to localhost/127.0.0.1/::1"}
+                    key = self._unsloth_api_key()
+                    if not key:
+                        return {"error": "UNSLOTH_API_KEY is not set. Copy .env.example to .env in the "
+                                          "plugin folder, fill in the key, and restart ComfyUI."}
+                    headers["Authorization"] = f"Bearer {key}"
+                body = {
+                    "model": model,
+                    "messages": [{"role": "user", "content": [
+                        {"type": "text", "text": prompt},
+                        {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{image_b64}"}},
+                    ]}],
+                    "stream": False,
+                }
+                if max_tokens > 0:
+                    body["max_tokens"] = max_tokens
+                payload = json.dumps(body).encode("utf-8")
+                req = urllib.request.Request(
+                    api_url.rstrip("/") + "/v1/chat/completions",
+                    data=payload,
+                    headers=headers,
+                    method="POST",
+                )
+                with urllib.request.urlopen(req, timeout=180) as resp:
+                    data = json.loads(resp.read().decode("utf-8"))
+                message = data.get("choices", [{}])[0].get("message", {})
+                content = message.get("content", "")
+                # Unslothはreasoningを別フィールドで返すため<think>タグに畳んで統一的に扱う
+                reasoning = message.get("reasoning_content")
+                if reasoning:
+                    content = f"<think>{reasoning}</think>{content}"
+
+            if not thinking_mode:
+                content = self._strip_thinking_tags(content)
            tags = [t.strip() for t in content.split(",") if t.strip()][:max_tags]
            return {"tags": ", ".join(tags), "count": len(tags)}
        except Exception as e:
-            logger.error("ollama_predict: %s", e)
+            logger.error("vlm_predict: %s", e)
            return {"error": str(e)}

    # ── ファイルメタデータ書込 ────────────────────────────────
@@ -334,8 +438,9 @@ class TaggerService:
        self._batch_state["stop"] = True

    def batch_start(self, folder: str, model_name: str, threshold: float, char_threshold: float,
-                    use_ollama: bool, ollama_api: str, ollama_model: str, ollama_prompt: str,
-                    ollama_max_tags: int, save_db: bool, write_file: bool, write_txt: bool, db_service) -> dict:
+                    use_ollama: bool, vlm_backend: str, vlm_api_url: str, ollama_model: str, ollama_prompt: str,
+                    ollama_max_tags: int, save_db: bool, write_file: bool, write_txt: bool, db_service,
+                    thinking_mode: bool = False, max_tokens: int = 0) -> dict:
        if self._batch_state["running"]:
            return {"error": "Batch already running"}
        folder_path = Path(folder)
@@ -370,7 +475,8 @@ class TaggerService:

                    vlm_tags = ""
                    if use_ollama and ollama_model:
-                        res2 = self.ollama_predict(b64, ollama_api, ollama_model, ollama_prompt, ollama_max_tags)
+                        res2 = self.vlm_predict(b64, vlm_backend, vlm_api_url, ollama_model, ollama_prompt, ollama_max_tags,
+                                                 thinking_mode, max_tokens)
                        vlm_tags = res2.get("tags", "")

                    all_tags = ", ".join(filter(None, [interrogator_tags, vlm_tags]))
@@ -0,0 +1,98 @@
+"""Video tab Edit subtab project file management (JSON timeline persistence).
+
+Same CRUD shape as VideoPlanService (list/get/save/delete with a safe-path
+helper), kept as its own class rather than sharing a base because the two
+JSON schemas are unrelated (batch keyframe blocks vs. an ordered clip
+timeline) — see VideoPlanService's own docstring for the same reasoning.
+No index-image thumbnail support (unlike VideoPlanService) since the Edit
+project list is plain text/JSON only for now.
+"""
+
+import json
+import logging
+from datetime import datetime, timezone
+from pathlib import Path
+
+logger = logging.getLogger(__name__)
+
+
+class VideoEditProjectService:
+    def __init__(self, project_dir: Path):
+        self.project_dir = project_dir
+        self.project_dir.mkdir(parents=True, exist_ok=True)
+
+    # ------------------------------------------------------------------
+    # Path safety
+    # ------------------------------------------------------------------
+
+    def _safe_path(self, filename: str, ext: str = ".json") -> Path | None:
+        if not filename or not filename.strip():
+            return None
+        name = filename.strip()
+        if not name.endswith(ext):
+            name = name + ext
+        if "/" in name or "\\" in name or name in (".", "..") or "\x00" in name:
+            return None
+        resolved = (self.project_dir / name).resolve()
+        project_dir_resolved = self.project_dir.resolve()
+        if resolved != project_dir_resolved and not str(resolved).startswith(str(project_dir_resolved) + "\\") and not str(resolved).startswith(str(project_dir_resolved) + "/"):
+            return None
+        return resolved
+
+    def _now_iso(self) -> str:
+        return datetime.now(timezone.utc).isoformat().replace("+00:00", "Z")
+
+    # ------------------------------------------------------------------
+    # CRUD
+    # ------------------------------------------------------------------
+
+    def list_projects(self) -> list[dict]:
+        if not self.project_dir.is_dir():
+            return []
+        result = []
+        for path in sorted(self.project_dir.glob("*.json")):
+            try:
+                with open(path, "r", encoding="utf-8") as f:
+                    data = json.load(f)
+            except Exception as e:
+                logger.warning("Skipping unreadable video edit project %s: %s", path.name, e)
+                continue
+
+            result.append({
+                "filename": path.name,
+                "name": data.get("name", path.stem),
+                "clip_count": len(data.get("clips", [])),
+                "updated_at": data.get("updated_at", ""),
+            })
+        result.sort(key=lambda p: p.get("updated_at", ""), reverse=True)
+        return result
+
+    def get_project(self, filename: str) -> dict:
+        path = self._safe_path(filename)
+        if path is None:
+            raise ValueError(f"Invalid filename: {filename}")
+        if not path.is_file():
+            raise FileNotFoundError(f"Project not found: {filename}")
+        with open(path, "r", encoding="utf-8") as f:
+            return json.load(f)
+
+    def save_project(self, filename: str, data: dict) -> dict:
+        path = self._safe_path(filename)
+        if path is None:
+            raise ValueError(f"Invalid filename: {filename}")
+
+        data = dict(data)
+        data["updated_at"] = self._now_iso()
+
+        path.parent.mkdir(parents=True, exist_ok=True)
+        with open(path, "w", encoding="utf-8") as f:
+            json.dump(data, f, ensure_ascii=False, indent=2)
+
+        return {"filename": path.name, "updated_at": data["updated_at"]}
+
+    def delete_project(self, filename: str) -> None:
+        path = self._safe_path(filename)
+        if path is None:
+            raise ValueError(f"Invalid filename: {filename}")
+        if path.is_file():
+            path.unlink()
@@ -0,0 +1,143 @@
+"""Video tab plan file management service (JSON plan + optional PNG index thumbnail).
+
+Duplicated from LabPlanService rather than shared — the two plan formats are
+unrelated (batch keyframe columns vs. sequential timeline blocks) and would
+gain nothing from a forced common base beyond coincidental line-count savings.
+"""
+
+import base64
+import json
+import logging
+from datetime import datetime, timezone
+from pathlib import Path
+
+logger = logging.getLogger(__name__)
+
+
+class VideoPlanService:
+    def __init__(self, plan_dir: Path):
+        self.plan_dir = plan_dir
+        self.plan_dir.mkdir(parents=True, exist_ok=True)
+
+    # ------------------------------------------------------------------
+    # Path safety
+    # ------------------------------------------------------------------
+
+    def _safe_path(self, filename: str, ext: str = ".json") -> Path | None:
+        if not filename or not filename.strip():
+            return None
+        name = filename.strip()
+        if not name.endswith(ext):
+            name = name + ext
+        if "/" in name or "\\" in name or name in (".", "..") or "\x00" in name:
+            return None
+        resolved = (self.plan_dir / name).resolve()
+        plan_dir_resolved = self.plan_dir.resolve()
+        if resolved != plan_dir_resolved and not str(resolved).startswith(str(plan_dir_resolved) + "\\") and not str(resolved).startswith(str(plan_dir_resolved) + "/"):
+            return None
+        return resolved
+
+    def _now_iso(self) -> str:
+        return datetime.now(timezone.utc).isoformat().replace("+00:00", "Z")
+
+    # ------------------------------------------------------------------
+    # CRUD
+    # ------------------------------------------------------------------
+
+    def list_plans(self) -> list[dict]:
+        if not self.plan_dir.is_dir():
+            return []
+        result = []
+        for path in sorted(self.plan_dir.glob("*.json")):
+            try:
+                with open(path, "r", encoding="utf-8") as f:
+                    data = json.load(f)
+            except Exception as e:
+                logger.warning("Skipping unreadable video plan %s: %s", path.name, e)
+                continue
+
+            stem = path.stem
+            thumbnail = None
+            thumb_path = self.plan_dir / f"{stem}.png"
+            if thumb_path.is_file():
+                thumbnail = f"/wfm_data/video_plan/{stem}.png"
+
+            result.append({
+                "filename": path.name,
+                "name": data.get("name", stem),
+                "note": data.get("note", ""),
+                "block_count": len(data.get("blocks", [])),
+                "updated_at": data.get("updated_at", ""),
+                "thumbnail": thumbnail,
+            })
+        result.sort(key=lambda p: p.get("updated_at", ""), reverse=True)
+        return result
+
+    def get_plan(self, filename: str) -> dict:
+        path = self._safe_path(filename)
+        if path is None:
+            raise ValueError(f"Invalid filename: {filename}")
+        if not path.is_file():
+            raise FileNotFoundError(f"Plan not found: {filename}")
+        with open(path, "r", encoding="utf-8") as f:
+            return json.load(f)
+
+    def save_plan(self, filename: str, data: dict, index_image_base64: str | None = None) -> dict:
+        path = self._safe_path(filename)
+        if path is None:
+            raise ValueError(f"Invalid filename: {filename}")
+
+        data = dict(data)
+        data["updated_at"] = self._now_iso()
+
+        path.parent.mkdir(parents=True, exist_ok=True)
+        with open(path, "w", encoding="utf-8") as f:
+            json.dump(data, f, ensure_ascii=False, indent=2)
+
+        if index_image_base64:
+            self.save_index_image(filename, index_image_base64)
+
+        return {"filename": path.name, "updated_at": data["updated_at"]}
+
+    def save_index_image(self, filename: str, image_base64: str) -> None:
+        path = self._safe_path(filename)
+        if path is None:
+            raise ValueError(f"Invalid filename: {filename}")
+        stem = path.stem
+        thumb_path = self.plan_dir / f"{stem}.png"
+
+        # Accept both raw base64 and data: URL forms
+        b64 = image_base64
+        if "," in b64 and b64.strip().lower().startswith("data:"):
+            b64 = b64.split(",", 1)[1]
+
+        image_bytes = base64.b64decode(b64)
+        with open(thumb_path, "wb") as f:
+            f.write(image_bytes)
+
+    def save_index_image_to_output(self, image_base64: str, filename_prefix: str = "Video_index") -> dict:
+        """Saves the contact-sheet index image into ComfyUI's own output folder,
+        alongside the videos generated during the run (unlike save_index_image,
+        which saves it next to the plan file in plan_dir)."""
+        b64 = image_base64
+        if "," in b64 and b64.strip().lower().startswith("data:"):
+            b64 = b64.split(",", 1)[1]
+        image_bytes = base64.b64decode(b64)
+
+        import folder_paths  # type: ignore
+        output_dir = folder_paths.get_output_directory()
+        full_output_folder, filename, counter, subfolder, _ = folder_paths.get_save_image_path(filename_prefix, output_dir)
+        save_name = f"{filename}_{counter:05}_.png"
+        save_path = Path(full_output_folder) / save_name
+        save_path.write_bytes(image_bytes)
+        return {"filename": save_name, "subfolder": subfolder}
+
+    def delete_plan(self, filename: str) -> None:
+        path = self._safe_path(filename)
+        if path is None:
+            raise ValueError(f"Invalid filename: {filename}")
+        if path.is_file():
+            path.unlink()
+        thumb_path = self.plan_dir / f"{path.stem}.png"
+        if thumb_path.is_file():
+            thumb_path.unlink()
@@ -0,0 +1,354 @@
+"""Video tab utilities: last-frame capture and animated GIF conversion.
+
+Runs entirely on dependencies ComfyUI itself already requires — PyAV for
+decoding (ComfyUI core already needs av>=17.0.0) and Pillow for GIF encoding
+— so no ffmpeg binary and no new pip installs, unlike a typical ffmpeg-based
+implementation (e.g. Eagle's video2gif/video-to-frame plugins).
+"""
+
+import base64
+import logging
+import os
+import sys
+from pathlib import Path
+
+logger = logging.getLogger(__name__)
+
+try:
+    from PIL import Image
+    _RESAMPLE = getattr(getattr(Image, "Resampling", Image), "LANCZOS")
+except Exception:  # pragma: no cover - Pillow is a hard ComfyUI dependency
+    _RESAMPLE = None
+
+# Text overlay anchors: 9-grid "<vertical>-<horizontal>" (e.g. "bottom-center").
+_ANCHOR_V = ("top", "middle", "bottom")
+_ANCHOR_H = ("left", "center", "right")
+
+# Fonts tried in order for text overlays. Pillow's built-in default font has no
+# CJK glyphs (Japanese/Chinese text would render as boxes), so a system font
+# with CJK coverage is preferred; load_default() is only the last resort.
+_FONT_CANDIDATES = {
+    "win32": ["meiryo.ttc", "YuGothM.ttc", "NotoSansJP-Regular.ttf", "msgothic.ttc", "arial.ttf"],
+    "darwin": [
+        "/System/Library/Fonts/ヒラギノ角ゴシック W4.ttc",
+        "/System/Library/Fonts/Hiragino Sans GB.ttc",
+        "/Library/Fonts/Arial Unicode.ttf",
+    ],
+    "linux": [
+        "/usr/share/fonts/opentype/noto/NotoSansCJK-Regular.ttc",
+        "/usr/share/fonts/noto-cjk/NotoSansCJK-Regular.ttc",
+        "/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf",
+    ],
+}
+
+
+def _load_overlay_font(size: int):
+    from PIL import ImageFont
+
+    platform = "win32" if sys.platform.startswith("win") else ("darwin" if sys.platform == "darwin" else "linux")
+    for name in _FONT_CANDIDATES[platform]:
+        path = name
+        if platform == "win32" and not os.path.isabs(name):
+            path = os.path.join(os.environ.get("WINDIR", r"C:\Windows"), "Fonts", name)
+        if os.path.isfile(path):
+            try:
+                return ImageFont.truetype(path, size)
+            except Exception:
+                continue
+    return ImageFont.load_default(size=size)
+
+
+def _render_text_layer(width: int, height: int, ov: dict):
+    """Renders one overlay's text onto a transparent full-frame RGBA layer, so
+    it can be alpha-composited over every frame in its time range without
+    re-rendering the text per frame (same idea as ComfyUI core's TextOverlay)."""
+    from PIL import ImageColor, ImageDraw
+
+    text = str(ov.get("text") or "").replace("\\n", "\n")
+    layer = Image.new("RGBA", (width, height), (0, 0, 0, 0))
+    if not text.strip():
+        return layer
+
+    size = max(8, round(float(ov.get("font_size") or 6.0) / 100.0 * height))
+    font = _load_overlay_font(size)
+    stroke = max(1, round(size * 0.06)) if ov.get("outline", True) else 0
+    spacing = round(size * 0.2)
+    try:
+        color = ImageColor.getrgb(str(ov.get("color") or "#ffffff"))
+    except ValueError:
+        color = (255, 255, 255)
+    fill = (*color[:3], 255)
+
+    anchor = str(ov.get("anchor") or "bottom-center").split("-")
+    v = anchor[0] if anchor and anchor[0] in _ANCHOR_V else "bottom"
+    h = anchor[1] if len(anchor) > 1 and anchor[1] in _ANCHOR_H else "center"
+
+    draw = ImageDraw.Draw(layer)
+    box = draw.multiline_textbbox((0, 0), text, font=font, spacing=spacing, stroke_width=stroke, align=h)
+    tw, th = box[2] - box[0], box[3] - box[1]
+    margin = round(0.04 * min(width, height))
+    x = {"left": margin, "center": (width - tw) / 2, "right": width - margin - tw}[h] - box[0]
+    y = {"top": margin, "middle": (height - th) / 2, "bottom": height - margin - th}[v] - box[1]
+
+    if ov.get("background"):
+        pad = round(size * 0.3)
+        draw.rounded_rectangle(
+            (x + box[0] - pad, y + box[1] - pad, x + box[2] + pad, y + box[3] + pad),
+            radius=pad, fill=(0, 0, 0, 140),
+        )
+    draw.multiline_text((x, y), text, font=font, fill=fill, spacing=spacing, align=h,
+                        stroke_width=stroke, stroke_fill=(0, 0, 0, 255))
+    return layer
+
+
+class VideoService:
+    def _resolve_media_path(self, filename: str, subfolder: str, type_: str) -> Path:
+        """Resolves a ComfyUI-style {filename, subfolder, type} reference to an
+        absolute path, guarding against path traversal outside the matching
+        input/output/temp directory."""
+        import folder_paths  # type: ignore
+
+        base_dir = folder_paths.get_directory_by_type(type_)
+        if not base_dir:
+            raise ValueError(f"Invalid type: {type_}")
+        base = Path(base_dir).resolve()
+        target = (base / (subfolder or "") / filename).resolve()
+        try:
+            target.relative_to(base)
+        except ValueError:
+            raise ValueError("Access denied: path outside allowed directory")
+        if not target.is_file():
+            raise FileNotFoundError(f"File not found: {filename}")
+        return target
+
+    def save_frame_to_output(self, image_base64: str, filename_prefix: str = "video/Frame") -> dict:
+        """Saves a client-captured video frame (PNG data URL) into ComfyUI's own
+        output folder — same auto-numbered pattern as Lab's index-image save
+        (see LabPlanService.save_index_image_to_output)."""
+        import folder_paths  # type: ignore
+
+        b64 = image_base64
+        if "," in b64 and b64.strip().lower().startswith("data:"):
+            b64 = b64.split(",", 1)[1]
+        image_bytes = base64.b64decode(b64)
+
+        output_dir = folder_paths.get_output_directory()
+        full_output_folder, filename, counter, subfolder, _ = folder_paths.get_save_image_path(filename_prefix, output_dir)
+        save_name = f"{filename}_{counter:05}_.png"
+        save_path = Path(full_output_folder) / save_name
+        save_path.write_bytes(image_bytes)
+        return {"filename": save_name, "subfolder": subfolder}
+
+    def probe_video(self, filename: str, subfolder: str, type_: str) -> dict:
+        """Reads duration/dimensions/fps/audio presence via PyAV only (no ffmpeg
+        subprocess) — used by the Video Edit tab right after a clip is added, so
+        the timeline UI can show its length and the export-time resolution-match
+        check has real numbers to compare against."""
+        import av  # type: ignore
+
+        src_path = self._resolve_media_path(filename, subfolder, type_)
+        container = av.open(str(src_path))
+        try:
+            stream = container.streams.video[0]
+            fps = float(stream.average_rate) if stream.average_rate else 0.0
+            if stream.duration is not None and stream.time_base is not None:
+                duration = float(stream.duration * stream.time_base)
+            elif container.duration is not None:
+                duration = float(container.duration) / 1_000_000
+            else:
+                duration = 0.0
+            width = stream.codec_context.width
+            height = stream.codec_context.height
+            has_audio = len(container.streams.audio) > 0
+        finally:
+            container.close()
+
+        return {
+            "duration": duration,
+            "width": width,
+            "height": height,
+            "fps": fps,
+            "has_audio": has_audio,
+        }
+
+    def convert_to_gif(
+        self,
+        filename: str,
+        subfolder: str,
+        type_: str,
+        start_time: float = 0.0,
+        end_time=None,
+        fps: float = 10.0,
+        max_width=None,
+        filename_prefix: str = "video/GIF",
+    ) -> dict:
+        """Decodes the given video (PyAV), samples it down to `fps`, optionally
+        downscales to `max_width`, and encodes the result as an animated GIF
+        (Pillow) into ComfyUI's own output folder."""
+        import av  # type: ignore
+        import folder_paths  # type: ignore
+
+        if _RESAMPLE is None:
+            raise RuntimeError("Pillow is not available")
+
+        src_path = self._resolve_media_path(filename, subfolder, type_)
+        fps = max(0.1, float(fps))
+
+        container = av.open(str(src_path))
+        try:
+            stream = container.streams.video[0]
+            source_fps = float(stream.average_rate) if stream.average_rate else 24.0
+            step = max(1, round(source_fps / fps))
+
+            pil_frames = []
+            idx = 0
+            for frame in container.decode(stream):
+                t = float(frame.pts * stream.time_base) if frame.pts is not None else None
+                if t is not None:
+                    if t < start_time:
+                        idx += 1
+                        continue
+                    if end_time is not None and t > end_time:
+                        break
+                if idx % step == 0:
+                    im = frame.to_image()
+                    if max_width and im.width > max_width:
+                        ratio = max_width / im.width
+                        im = im.resize((max_width, max(1, round(im.height * ratio))), _RESAMPLE)
+                    pil_frames.append(im.convert("RGB"))
+                idx += 1
+        finally:
+            container.close()
+
+        if not pil_frames:
+            raise ValueError("No frames found in the specified range")
+
+        output_dir = folder_paths.get_output_directory()
+        full_output_folder, out_filename, counter, out_subfolder, _ = folder_paths.get_save_image_path(filename_prefix, output_dir)
+        save_name = f"{out_filename}_{counter:05}_.gif"
+        save_path = Path(full_output_folder) / save_name
+
+        duration_ms = max(20, round(1000 / fps))
+        pil_frames[0].save(
+            save_path,
+            format="GIF",
+            save_all=True,
+            append_images=pil_frames[1:],
+            duration=duration_ms,
+            loop=0,
+            optimize=True,
+        )
+        return {"filename": save_name, "subfolder": out_subfolder, "frame_count": len(pil_frames)}
+
+    def overlay_text_on_video(
+        self,
+        filename: str,
+        subfolder: str,
+        type_: str,
+        overlays: list,
+        filename_prefix: str = "video/wfm_edit",
+        delete_source: bool = False,
+    ) -> dict:
+        """Burns timed text overlays into a video (Video Edit tab, Phase 3).
+
+        ComfyUI core has no time-ranged video text node (core TextOverlay draws
+        on every frame of an IMAGE batch, top/bottom only), and routing the
+        whole timeline through IMAGE tensors would hold every decoded frame in
+        memory at once — so this streams instead: decode one frame, composite
+        any overlay whose [start, end) covers it, encode, repeat. Audio packets
+        are remuxed untouched (no audio re-encode), so the soundtrack built by
+        the export graph (original audio / BGM) survives this pass as-is.
+
+        overlays: [{text, start, end, font_size (% of frame height), color,
+        anchor ("<top|middle|bottom>-<left|center|right>"), outline, background}]
+        with start/end in seconds from the start of the video.
+        """
+        import av  # type: ignore
+        import folder_paths  # type: ignore
+
+        src_path = self._resolve_media_path(filename, subfolder, type_)
+        items = []
+        for ov in overlays or []:
+            try:
+                start = max(0.0, float(ov.get("start") or 0.0))
+                end = float(ov.get("end") or 0.0)
+            except (TypeError, ValueError):
+                continue
+            if end > start and str(ov.get("text") or "").strip():
+                items.append((start, end, ov))
+        if not items:
+            raise ValueError("No valid text overlays")
+
+        output_dir = folder_paths.get_output_directory()
+        full_output_folder, out_filename, counter, out_subfolder, _ = folder_paths.get_save_image_path(filename_prefix, output_dir)
+        save_name = f"{out_filename}_{counter:05}_.mp4"
+        save_path = Path(full_output_folder) / save_name
+
+        in_c = av.open(str(src_path))
+        out_c = None
+        try:
+            in_v = in_c.streams.video[0]
+            in_a = in_c.streams.audio[0] if in_c.streams.audio else None
+            width, height = in_v.codec_context.width, in_v.codec_context.height
+            rate = in_v.average_rate or in_v.guessed_rate or 24
+
+            layers = [(s, e, _render_text_layer(width, height, ov)) for s, e, ov in items]
+
+            out_c = av.open(str(save_path), mode="w")
+            out_v = out_c.add_stream("libx264", rate=rate)
+            out_v.width = width
+            out_v.height = height
+            out_v.pix_fmt = "yuv420p"
+            out_v.options = {"crf": "18", "preset": "medium"}
+            out_a = out_c.add_stream_from_template(in_a) if in_a is not None else None
+
+            streams = [in_v] + ([in_a] if in_a is not None else [])
+            first_pts = None
+            index = 0
+            for packet in in_c.demux(*streams):
+                if packet.stream.type == "audio":
+                    if packet.dts is None:
+                        continue
+                    packet.stream = out_a
+                    out_c.mux(packet)
+                    continue
+                for frame in packet.decode():
+                    if frame.pts is not None and first_pts is None:
+                        first_pts = frame.pts
+                    t = float((frame.pts - first_pts) * in_v.time_base) if frame.pts is not None else index / float(rate)
+                    active = [layer for s, e, layer in layers if s <= t < e]
+                    if active:
+                        img = frame.to_image().convert("RGBA")
+                        for layer in active:
+                            img.alpha_composite(layer)
+                        out_frame = av.VideoFrame.from_image(img.convert("RGB"))
+                    else:
+                        out_frame = frame
+                    out_frame.pts = index
+                    out_frame.time_base = out_v.codec_context.time_base
+                    index += 1
+                    for out_packet in out_v.encode(out_frame):
+                        out_c.mux(out_packet)
+            for out_packet in out_v.encode(None):
+                out_c.mux(out_packet)
+        except BaseException:
+            if out_c is not None:
+                out_c.close()
+                out_c = None
+            save_path.unlink(missing_ok=True)
+            raise
+        finally:
+            if out_c is not None:
+                out_c.close()
+            in_c.close()
+
+        # The export graph's intermediate file is only deleted when the caller
+        # explicitly asks and it's one of this tab's own "_pre" intermediates in
+        # output — never an arbitrary user file.
+        if delete_source and type_ == "output" and Path(filename).name.startswith("wfm_edit_pre"):
+            try:
+                src_path.unlink()
+            except OSError as e:
+                logger.warning("Could not delete intermediate %s: %s", src_path, e)
+
+        return {"filename": save_name, "subfolder": out_subfolder, "frame_count": index}
@@ -3,6 +3,17 @@
 import os
 import re

+# プロンプトを直接持つノードタイプ（CLIPTextEncode以外の複合ノード含む）
+_PROMPT_NODE_TYPES = {
+    "CLIPTextEncode", "CLIPTextEncodeSDXL", "CLIPTextEncodeSDXLRefiner",
+    "CLIPTextEncodeEditPlus", "TextEncodeQwenImageEditPlus", "TextEncodeMageFlowEdit",
+    "SDXLPromptStyler", "SDXLPromptStylerAdvanced", "ImageMetadataPromptLoader",
+    "WFS_PromptText", "ImpactWildcardEncode", "ImpactWildcardProcessor",
+}
+
+# 画像を最終出力として保存するノードタイプ
+_OUTPUT_IMAGE_NODE_TYPES = {"SaveImage", "SaveImageAdvanced"}
+
 # CLIPLoader / DualCLIPLoader の type フィールド → モデル種別マッピング
 _CLIP_TYPE_TO_MODEL = {
    "flux": "Flux",
@@ -181,25 +192,27 @@ def analyze_workflow(workflow_data, filename=""):
        if "hidream" in title:
            model_types.add("HiDream")

-        if ntype == "CLIPTextEncode" or "prompt" in title:
+        if ntype in _PROMPT_NODE_TYPES or "prompt" in title:
            inputs["prompts"] += 1
        if ntype in ("LoadImage", "LoadImageMask"):
            inputs["images"] += 1
        if ntype == "LoadVideo" or "load video" in title:
            inputs["videos"] += 1
-        if ntype == "SaveImage":
+        if ntype in _OUTPUT_IMAGE_NODE_TYPES:
            outputs["images"] += 1
        if ntype in ("SaveVideo", "VH_VideoCombine"):
            outputs["videos"] += 1

    # Detect workflow format
    if raw_nodes is not None:
-        # App format: UI-based structure with definitions (subgraphs) or linearMode
+        # App format: simplified web-app-style UI (linearMode) or .app.json filename.
+        # A workflow that merely *contains* subgraphs (definitions.subgraphs) is still a
+        # normal node graph (comfyui-workflow.js's convertUiToApi flattens subgraphs before
+        # conversion), so it's treated as "ui" here too — must match detectFormat() in
+        # static/js/comfyui-workflow.js or the App/UI badge shown to the user disagrees
+        # with what GenerateUI actually does with the file.
        extra = workflow_data.get("extra", {})
-        if (
-            "definitions" in workflow_data
-            or extra.get("linearMode") is True
-        ):
+        if extra.get("linearMode") is True:
            wf_format = "app"
        elif filename and filename.lower().endswith(".app.json"):
            wf_format = "app"
@@ -4,7 +4,7 @@ import jinja2
 from aiohttp import web
 from pathlib import Path

-from .config import TEMPLATES_DIR, STATIC_DIR, DATA_DIR, WORKFLOWS_DIR
+from .config import TEMPLATES_DIR, STATIC_DIR, DATA_DIR, WORKFLOWS_DIR, LAB_PLAN_DIR, VIDEO_PLAN_DIR

 logger = logging.getLogger(__name__)

@@ -41,6 +41,38 @@ async def serve_workflow_file(request: web.Request) -> web.Response:
    })


+async def serve_lab_plan_file(request: web.Request) -> web.Response:
+    """Serve files (index thumbnails) from the Lab plan directory."""
+    filename = request.match_info.get("filename", "")
+    if not filename or ".." in filename or "/" in filename or "\\" in filename:
+        return web.Response(status=404)
+
+    file_path = LAB_PLAN_DIR / filename
+    if not file_path.is_file():
+        return web.Response(status=404)
+
+    content_type, _ = mimetypes.guess_type(str(file_path))
+    return web.FileResponse(file_path, headers={
+        "Content-Type": content_type or "application/octet-stream",
+    })
+
+
+async def serve_video_plan_file(request: web.Request) -> web.Response:
+    """Serve files (index thumbnails) from the Video plan directory."""
+    filename = request.match_info.get("filename", "")
+    if not filename or ".." in filename or "/" in filename or "\\" in filename:
+        return web.Response(status=404)
+
+    file_path = VIDEO_PLAN_DIR / filename
+    if not file_path.is_file():
+        return web.Response(status=404)
+
+    content_type, _ = mimetypes.guess_type(str(file_path))
+    return web.FileResponse(file_path, headers={
+        "Content-Type": content_type or "application/octet-stream",
+    })
+
+
 class WorkflowStudio:
    """Main entry point for Workflow Studio plugin."""

@@ -57,15 +89,22 @@ class WorkflowStudio:
        # Dynamic workflow file serving (thumbnails etc.)
        app.router.add_get("/wfm_data/workflows/{filename}", serve_workflow_file)

+        # Dynamic Lab plan file serving (index thumbnails)
+        app.router.add_get("/wfm_data/lab_plan/{filename}", serve_lab_plan_file)
+
+        # Dynamic Video plan file serving (index thumbnails)
+        app.router.add_get("/wfm_data/video_plan/{filename}", serve_video_plan_file)
+
        # Main page
        app.router.add_get("/wfm", serve_index_page)

        # API routes
-        from .routes import workflow_routes, settings_routes, ollama_routes, eagle_routes, nodes_routes, prompts_routes, models_routes, gallery_routes, wildcard_routes, tagger_routes, gmic_routes
+        from .routes import workflow_routes, settings_routes, ollama_routes, unsloth_routes, eagle_routes, nodes_routes, prompts_routes, models_routes, gallery_routes, wildcard_routes, tagger_routes, gmic_routes, skill_routes, lab_routes, video_routes

        workflow_routes.setup_routes(app)
        settings_routes.setup_routes(app)
        ollama_routes.setup_routes(app)
+        unsloth_routes.setup_routes(app)
        eagle_routes.setup_routes(app)
        nodes_routes.setup_routes(app)
        prompts_routes.setup_routes(app)
@@ -74,5 +113,8 @@ class WorkflowStudio:
        wildcard_routes.setup_routes(app)
        tagger_routes.setup_routes(app)
        gmic_routes.setup_routes(app)
+        skill_routes.setup_routes(app)
+        lab_routes.setup_routes(app)
+        video_routes.setup_routes(app)

        logger.info("Workflow Studio: Routes registered successfully")
@@ -1,8 +1,8 @@
 [project]
 name = "comfyui-workflow-studio"
 description = "A comprehensive workflow, asset management, and generation UI plugin for ComfyUI. Manage workflows, models, images, and prompts; batch generation and Image Feeder in the GenerateUI tab; library side panel with canvas drag & drop and AI tools."
-version = "0.3.74"
-license = "MIT"
+version = "0.7.4"
+license = { file = "LICENSE" }
 requires-python = ">= 3.10"
 dependencies = ["jinja2"]

@@ -19,3 +19,17 @@ piexif>=1.1.3
 # Omit if you do not use DeepDanbooru models.
 # TensorFlow is large (~600MB) and conflicts with some CUDA setups.
 # tensorflow>=2.10
+
+# -- Required to load UNSLOTH_API_KEY from a local .env file (Unsloth backend, AI TOOL tab) --
+python-dotenv>=1.0,<2.0
+
+# -- Multi-layer PSD export (Gallery tab bulk action) --
+# Pure-Python, ships prebuilt wheels (no C compiler required on Windows).
+psd-tools>=1.10
+
+# -- MP4 thumbnail generation (Gallery tab) --
+# Uses PyAV (av) to decode the first frame. ComfyUI core already requires av>=17.0.0,
+# so it is normally pre-installed in python_embeded and no action is needed here.
+# If missing, mp4 thumbnail generation simply fails and falls back to a placeholder
+# (Gallery itself keeps working). Not pinned here on purpose — see torch note above.
+# av>=17.0.0
@@ -2,11 +2,45 @@
   Gallery Tab Styles
   ============================================================ */

+/* ── サブタブ (Output / Style-Prompt) ──────────────────────── */
+
+.wfm-gallery-subtab-nav {
+    display: flex;
+    border-bottom: 1px solid var(--wfm-border);
+    flex-shrink: 0;
+}
+
+.wfm-gallery-subtab-btn {
+    padding: 6px 16px;
+    font-size: 12px;
+    background: transparent;
+    border: none;
+    color: var(--wfm-text-secondary);
+    cursor: pointer;
+    border-bottom: 2px solid transparent;
+    margin-bottom: -1px;
+    transition: color 0.15s;
+}
+
+.wfm-gallery-subtab-btn:hover { color: var(--wfm-text-primary); }
+.wfm-gallery-subtab-btn.active { color: var(--wfm-primary); border-bottom-color: var(--wfm-primary); }
+
+.wfm-gallery-panel {
+    display: none;
+    flex-direction: column;
+    flex: 1;
+    min-height: 0;
+    overflow: hidden;
+}
+
+.wfm-gallery-panel.active { display: flex; }
+
 /* ── 3カラムレイアウト ──────────────────────────────────────── */

 .wfm-gallery-layout {
    display: flex;
-    height: calc(100vh - var(--wfm-header-height, 96px));
+    flex: 1;
+    min-height: 0;
    overflow: hidden;
    gap: 0;
 }
@@ -256,6 +290,24 @@
    color: #38bdf8;
 }

+/* 動画ファイル（mp4）の再生アイコンバッジ（サムネイル中央） */
+.wfm-gallery-thumb-video-badge {
+    position: absolute;
+    top: 50%;
+    left: 50%;
+    transform: translate(-50%, -50%);
+    width: 36px;
+    height: 36px;
+    border-radius: 50%;
+    background: rgba(0,0,0,0.55);
+    color: #fff;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    font-size: 14px;
+    pointer-events: none;
+}
+
 /* テーブルビューのお気に入りボタン */
 .wfm-gallery-table-fav-btn {
    background: none;
@@ -431,43 +483,6 @@
    cursor: pointer;
 }

-.wfm-gallery-preview-overlay {
-    position: absolute;
-    top: 0;
-    left: 0;
-    right: 0;
-    bottom: 0;
-    background: rgba(0,0,0,0.5);
-    display: flex;
-    align-items: center;
-    justify-content: center;
-    opacity: 0;
-    transition: opacity 0.2s;
-}
-
-.wfm-gallery-preview-wrapper:hover .wfm-gallery-preview-overlay {
-    opacity: 1;
-}
-
-.wfm-gallery-download-btn {
-    background: var(--wfm-accent, #4f8ef7);
-    border: none;
-    border-radius: 50%;
-    width: 40px;
-    height: 40px;
-    font-size: 20px;
-    cursor: pointer;
-    display: flex;
-    align-items: center;
-    justify-content: center;
-    color: #fff;
-    transition: background 0.2s;
-}
-
-.wfm-gallery-download-btn:hover {
-    background: var(--wfm-accent-hover, #3f7fe7);
-}
-
 /* タブコンテンツ */
 .wfm-gallery-detail-tab-content {
    flex: 1;
@@ -499,6 +514,20 @@
    white-space: nowrap;
 }

+.wfm-gallery-image-prompt-text {
+    font-size: 12px;
+    color: var(--wfm-text-primary);
+    line-height: 1.5;
+    white-space: pre-wrap;
+    word-break: break-word;
+    background: var(--wfm-bg-primary, #16213e);
+    border: 1px solid var(--wfm-border);
+    border-radius: 4px;
+    padding: 6px 8px;
+    max-height: 160px;
+    overflow-y: auto;
+}
+
 .wfm-gallery-tags-display {
    display: flex;
    flex-wrap: wrap;
@@ -788,6 +817,16 @@
    border-color: #6a4de0;
 }

+.wfm-gallery-action-btn-orange {
+    background: #f59e0b;
+    border-color: #f59e0b;
+    color: #1a1a2e;
+}
+.wfm-gallery-action-btn-orange:hover {
+    background: #d97f06;
+    border-color: #d97f06;
+}
+
 /* ── ファイル操作ボタン (詳細パネル) ─────────────────────────── */

 .wfm-gallery-file-actions {
@@ -833,3 +872,114 @@
    gap: 8px;
    justify-content: flex-end;
 }
+
+/* ============================================================
+   ImagePrompt / Style_Catalog ギャラリー (右ペイン)
+   ============================================================ */
+
+.wfm-imageprompt-detail-panel {
+    width: 520px;
+    min-width: 520px;
+    max-width: 520px;
+    flex-direction: row;
+    overflow: hidden;
+}
+
+.wfm-imageprompt-detail-col {
+    display: flex;
+    flex-direction: column;
+    min-width: 0;
+}
+
+.wfm-imageprompt-detail-col-left {
+    width: 280px;
+    min-width: 280px;
+    max-width: 280px;
+    overflow-y: auto;
+    border-right: 1px solid var(--wfm-border);
+    padding-bottom: 8px;
+}
+
+.wfm-imageprompt-detail-col-right {
+    flex: 1;
+    min-width: 0;
+    padding: 8px 10px;
+}
+
+.wfm-imageprompt-section {
+    padding: 8px 10px;
+}
+
+.wfm-imageprompt-prompt-box {
+    width: 100%;
+    resize: vertical;
+    font-size: 12px;
+    padding: 6px 8px;
+    background: var(--wfm-bg-primary, #16213e);
+    border: 1px solid var(--wfm-border);
+    border-radius: 4px;
+    color: var(--wfm-text-primary);
+    box-sizing: border-box;
+}
+
+.wfm-imageprompt-btn-row {
+    display: flex;
+    gap: 6px;
+    margin-top: 6px;
+}
+
+.wfm-imageprompt-btn-row .wfm-btn {
+    flex: 1;
+}
+
+.wfm-imageprompt-chips {
+    display: flex;
+    flex-wrap: wrap;
+    gap: 4px;
+    margin-top: 6px;
+    min-height: 24px;
+}
+
+.wfm-imageprompt-chip {
+    display: inline-flex;
+    align-items: center;
+    gap: 4px;
+    max-width: 100%;
+    background: rgba(79,142,247,0.15);
+    color: var(--wfm-accent, #4f8ef7);
+    border: 1px solid rgba(79,142,247,0.3);
+    border-radius: 10px;
+    padding: 2px 4px 2px 8px;
+    font-size: 11px;
+}
+
+.wfm-imageprompt-chip-text {
+    overflow: hidden;
+    text-overflow: ellipsis;
+    white-space: nowrap;
+    max-width: 220px;
+}
+
+.wfm-imageprompt-chip-remove {
+    background: none;
+    border: none;
+    color: inherit;
+    cursor: pointer;
+    padding: 0 2px;
+    font-size: 13px;
+    line-height: 1;
+    opacity: 0.7;
+}
+
+.wfm-imageprompt-chip-remove:hover { opacity: 1; }
+
+.wfm-imageprompt-final-section {
+    height: 100%;
+}
+
+.wfm-imageprompt-final-textarea {
+    margin-top: 4px;
+    flex: 1;
+    min-height: 0;
+    resize: none;
+}
@@ -311,8 +311,8 @@

 .ie-layers-header {
    display: flex;
-    align-items: center;
-    gap: 2px;
+    flex-direction: column;
+    gap: 4px;
    padding: 5px 6px;
    border-bottom: 1px solid var(--wfm-border);
    font-size: 11px;
@@ -323,7 +323,13 @@
    flex-shrink: 0;
 }

-.ie-layers-header > span {
+.ie-layers-header-row {
+    display: flex;
+    align-items: center;
+    gap: 2px;
+}
+
+.ie-layers-header-row > span {
    flex: 1;
 }

@@ -0,0 +1,413 @@
+/* Lab tab — experimental I2I batch generation with per-column keyframes */
+
+/* .wfm-gen-subtab-content.active defaults to flex-direction:row (main.css);
+   Lab needs its Setting/Results nav stacked above the panel body. */
+#wfm-gen-subtab-lab.active {
+    flex-direction: column;
+}
+
+.wfm-lab-subtab-nav {
+    display: flex;
+    border-bottom: 1px solid var(--wfm-border);
+    flex-shrink: 0;
+}
+
+.wfm-lab-subtab-btn {
+    padding: 6px 16px;
+    font-size: 12px;
+    background: transparent;
+    border: none;
+    color: var(--wfm-text-secondary);
+    cursor: pointer;
+    border-bottom: 2px solid transparent;
+    margin-bottom: -1px;
+    transition: color 0.15s;
+}
+
+.wfm-lab-subtab-btn:hover { color: var(--wfm-text-primary); }
+.wfm-lab-subtab-btn.active { color: var(--wfm-primary); border-bottom-color: var(--wfm-primary); }
+
+.wfm-lab-panel {
+    display: none;
+    flex-direction: column;
+    flex: 1;
+    overflow: hidden;
+    height: calc(100% - 33px);
+}
+
+.wfm-lab-panel.active { display: flex; }
+
+.wfm-lab-planjson-toolbar {
+    display: flex;
+    gap: 8px;
+    padding: 8px 10px;
+    border-bottom: 1px solid var(--wfm-border);
+    flex-shrink: 0;
+}
+
+.wfm-lab-pane-header {
+    font-size: 11px;
+    font-weight: 600;
+    color: var(--wfm-text-secondary);
+    text-transform: uppercase;
+    letter-spacing: 0.05em;
+    padding: 4px 0 6px;
+    flex-shrink: 0;
+}
+
+/* ---------------- Setting layout: left | center (4 columns) | right ---------------- */
+
+.wfm-lab-setting-layout {
+    display: flex;
+    height: 100%;
+    overflow: hidden;
+    gap: 0;
+}
+
+.wfm-lab-pane {
+    display: flex;
+    flex-direction: column;
+    overflow: hidden;
+    min-width: 0;
+    border-right: 1px solid var(--wfm-border);
+    padding: 10px;
+}
+
+.wfm-lab-pane:last-child { border-right: none; }
+
+.wfm-lab-left { width: 220px; flex-shrink: 0; }
+.wfm-lab-center { flex: 1; padding: 0; }
+.wfm-lab-right { width: 260px; flex-shrink: 0; overflow-y: auto; }
+
+.wfm-lab-side-btns {
+    display: flex;
+    flex-direction: column;
+    gap: 6px;
+    margin-top: 12px;
+}
+
+.wfm-lab-plan-workflow-row {
+    display: flex;
+    align-items: center;
+    gap: 6px;
+    margin-top: 8px;
+    padding: 6px 8px;
+    background: var(--wfm-bg-secondary);
+    border: 1px solid var(--wfm-border);
+    border-radius: 4px;
+}
+
+.wfm-lab-plan-workflow-name {
+    flex: 1;
+    min-width: 0;
+    font-size: 11px;
+    color: var(--wfm-text-secondary);
+    overflow: hidden;
+    text-overflow: ellipsis;
+    white-space: nowrap;
+}
+
+.wfm-lab-field-row {
+    display: flex;
+    align-items: center;
+    gap: 8px;
+    margin-top: 10px;
+}
+
+.wfm-lab-field-row label {
+    font-size: 12px;
+    color: var(--wfm-text-secondary);
+    white-space: nowrap;
+}
+
+.wfm-lab-field-row input {
+    flex: 1;
+    min-width: 0;
+}
+
+.wfm-lab-note {
+    width: 100%;
+    resize: vertical;
+    font-size: 12px;
+}
+
+.wfm-lab-checkbox-label {
+    display: flex;
+    align-items: center;
+    gap: 6px;
+    margin-top: 8px;
+    font-size: 12px;
+    color: var(--wfm-text-secondary);
+    cursor: pointer;
+}
+
+/* ---------------- Keyframe columns ---------------- */
+
+.wfm-lab-columns {
+    display: flex;
+    height: 100%;
+    overflow: hidden;
+}
+
+.wfm-lab-column {
+    flex: 1;
+    min-width: 0;
+    display: flex;
+    flex-direction: column;
+    border-right: 1px solid var(--wfm-border);
+    overflow: hidden;
+}
+
+.wfm-lab-column:last-child { border-right: none; }
+
+.wfm-lab-col-header {
+    display: flex;
+    align-items: center;
+    flex-wrap: wrap;
+    justify-content: space-between;
+    gap: 4px;
+    row-gap: 4px;
+    padding: 6px 8px;
+    font-size: 11px;
+    font-weight: 600;
+    color: var(--wfm-text-secondary);
+    border-bottom: 1px solid var(--wfm-border);
+    flex-shrink: 0;
+}
+
+.wfm-lab-col-btns { display: flex; gap: 2px; }
+
+.wfm-lab-col-header-left {
+    display: flex;
+    align-items: center;
+    gap: 6px;
+}
+
+/* Model column header: C/L/V toggle that switches which single field its cells
+   summarize (see _modelViewMode in lab-tab.js) — not part of the Plan data. */
+.wfm-lab-model-view-toggle { display: flex; gap: 2px; }
+
+.wfm-lab-model-view-btn {
+    width: 20px;
+    height: 20px;
+    padding: 0;
+    font-size: 10px;
+    font-weight: 700;
+    line-height: 1;
+    background: var(--wfm-bg-tertiary);
+    border: 1px solid var(--wfm-border);
+    border-radius: var(--wfm-radius-sm);
+    color: var(--wfm-text-secondary);
+    cursor: pointer;
+    transition: color 0.15s, border-color 0.15s, background 0.15s;
+}
+
+.wfm-lab-model-view-btn:hover { color: var(--wfm-text-primary); border-color: var(--wfm-primary); }
+
+.wfm-lab-model-view-btn.active {
+    color: #fff;
+    background: var(--wfm-primary);
+    border-color: var(--wfm-primary);
+}
+
+.wfm-lab-col-cells {
+    flex: 1;
+    overflow-y: auto;
+    padding: 6px;
+    display: flex;
+    flex-direction: column;
+    gap: 6px;
+}
+
+.wfm-lab-cell {
+    border: 1px solid var(--wfm-border);
+    border-radius: var(--wfm-radius-sm);
+    padding: 6px 8px;
+    font-size: 11px;
+    cursor: pointer;
+    background: var(--wfm-bg-tertiary);
+    transition: border-color 0.15s;
+}
+
+.wfm-lab-cell:hover { border-color: var(--wfm-primary); }
+
+.wfm-lab-cell-index {
+    font-weight: 600;
+    color: var(--wfm-primary);
+    margin-right: 4px;
+}
+
+.wfm-lab-cell-value {
+    color: var(--wfm-text-primary);
+    word-break: break-all;
+}
+
+.wfm-lab-cell.wfm-lab-cell-revert .wfm-lab-cell-value {
+    color: var(--wfm-text-secondary);
+    font-style: italic;
+}
+
+/* Setting 1, not yet explicitly overridden: showing the live GenerateUI value instead of
+   its own stored one (see _isLiveDisplay in lab-tab.js). Dashed border distinguishes it
+   from a saved override (solid border) at a glance. */
+.wfm-lab-cell.wfm-lab-cell-live {
+    border-style: dashed;
+}
+
+.wfm-lab-cell.wfm-lab-cell-live .wfm-lab-cell-value {
+    color: var(--wfm-text-secondary);
+}
+
+/* This keyframe row is skipped entirely (see _resolveKeyframe's bypassed handling) —
+   amber to read as "temporarily disabled", distinct from the neutral gray used for
+   revert/live. Takes priority over both of those in _cellHtml. */
+.wfm-lab-cell.wfm-lab-cell-bypassed {
+    border-color: var(--wfm-warning);
+    opacity: 0.6;
+}
+
+.wfm-lab-cell.wfm-lab-cell-bypassed .wfm-lab-cell-value {
+    color: var(--wfm-warning);
+}
+
+/* LoRA node-bypass (strength forced to 0 at apply-time) — red to distinguish from the
+   amber row-level bypassed above; the row itself still applies, only the LoRA doesn't. */
+.wfm-lab-cell.wfm-lab-cell-node-bypassed {
+    border-color: var(--wfm-danger);
+}
+
+.wfm-lab-cell.wfm-lab-cell-node-bypassed .wfm-lab-cell-value {
+    color: var(--wfm-danger);
+}
+
+/* Single-click selection target for the column header's up/down reorder buttons —
+   layered as a box-shadow (not border-color) so it never conflicts with the
+   revert/live/bypassed/node-bypassed border-color signaling above. */
+.wfm-lab-cell.wfm-lab-cell-selected {
+    box-shadow: 0 0 0 2px var(--wfm-primary);
+}
+
+.wfm-lab-cell-applied {
+    margin-top: 3px;
+    padding-top: 3px;
+    border-top: 1px dashed var(--wfm-border);
+    font-size: 10px;
+    color: var(--wfm-text-secondary);
+}
+
+/* Shown instead of a keyframe list when the loaded workflow has no node this Model
+   sub-column (checkpoint/lora/vae) could override — see _hasNodeForColumn in lab-tab.js. */
+.wfm-lab-cell-empty {
+    padding: 6px 8px;
+    font-size: 11px;
+    font-style: italic;
+    color: var(--wfm-text-secondary);
+    cursor: default;
+}
+
+.wfm-lab-cell-prompt-line {
+    display: block;
+    overflow: hidden;
+    text-overflow: ellipsis;
+    white-space: nowrap;
+    max-width: 100%;
+}
+
+/* ---------------- Modal form (checkpoint/vae/prompt/ksampler edit) ---------------- */
+
+.wfm-lab-modal-row {
+    display: flex;
+    flex-direction: column;
+    gap: 4px;
+    margin-bottom: 10px;
+}
+
+.wfm-lab-modal-row label {
+    font-size: 12px;
+    color: var(--wfm-text-secondary);
+}
+
+.wfm-lab-modal-inline {
+    display: flex;
+    gap: 8px;
+}
+
+.wfm-lab-modal-btnrow {
+    display: flex;
+    flex-wrap: wrap;
+    gap: 6px;
+    margin-bottom: 10px;
+}
+
+.wfm-lab-modal-hint {
+    font-size: 11px;
+    color: var(--wfm-text-secondary);
+    font-style: italic;
+    margin: 0 0 10px;
+}
+
+.wfm-lab-modal-inline > div {
+    flex: 1;
+    min-width: 0;
+}
+
+.wfm-lab-modal-checkbox {
+    display: flex;
+    align-items: center;
+    gap: 6px;
+    font-size: 12px;
+    margin-top: 4px;
+}
+
+/* ---------------- Results layout ---------------- */
+
+.wfm-lab-results-layout {
+    display: flex;
+    height: 100%;
+    overflow: hidden;
+}
+
+.wfm-lab-results-left {
+    width: 260px;
+    flex-shrink: 0;
+    border-right: 1px solid var(--wfm-border);
+    padding: 10px;
+}
+
+.wfm-lab-results-center {
+    flex: 1;
+    min-width: 0;
+    padding: 10px;
+    overflow-y: auto;
+}
+
+.wfm-lab-results-grid {
+    display: grid;
+    grid-template-columns: repeat(auto-fill, minmax(140px, 1fr));
+    gap: 8px;
+}
+
+.wfm-lab-result-thumb {
+    width: 100%;
+    aspect-ratio: 1 / 1;
+    object-fit: cover;
+    border-radius: var(--wfm-radius-sm);
+    border: 1px solid var(--wfm-border);
+    cursor: pointer;
+    transition: border-color 0.15s;
+}
+
+.wfm-lab-result-thumb:hover { border-color: var(--wfm-primary); }
+
+.wfm-lab-result-item { position: relative; }
+
+.wfm-lab-result-index {
+    position: absolute;
+    top: 2px;
+    left: 2px;
+    background: rgba(0, 0, 0, 0.6);
+    color: #fff;
+    font-size: 10px;
+    padding: 1px 5px;
+    border-radius: var(--wfm-radius-sm);
+}
@@ -653,8 +653,8 @@ body {
    align-items: center;
 }

+.wfm-lora-bypass-btn,
 .wfm-lora-refresh-btn {
-    margin-left: auto;
    font-size: 13px;
    line-height: 1;
    padding: 2px 5px;
@@ -662,8 +662,21 @@ body {
    text-transform: none;
    letter-spacing: 0;
 }
+.wfm-lora-bypass-btn {
+    margin-left: auto;
+}
+.wfm-lora-bypass-btn:hover,
 .wfm-lora-refresh-btn:hover { opacity: 1; }

+/* Bypass is active for the current LoRA target node: strength forced to 0 (see
+   comfyui-editor.js renderLoraPane / _loraNodeBypass). */
+.wfm-lora-bypass-btn.active {
+    opacity: 1;
+    background: var(--wfm-danger);
+    border-color: var(--wfm-danger);
+    color: #fff;
+}
+
 .wfm-gen-lora-col-body {
    flex: 1;
    overflow-y: auto;
@@ -1056,6 +1069,17 @@ body {
    height: auto !important;
 }

+/* Bypass/Mute node indicator (shown above the Raw JSON search bar when present) */
+.wfm-gen-rawjson-bypass-note {
+    padding: 6px 10px;
+    background: rgba(255, 165, 2, 0.12);
+    border-bottom: 1px solid var(--wfm-border);
+    color: var(--wfm-warning);
+    font-size: 11px;
+    line-height: 1.5;
+    flex-shrink: 0;
+}
+
 /* RAW JSON search bar */
 .wfm-rawjson-search {
    display: flex;
@@ -2331,6 +2355,280 @@ body {
    flex-shrink: 0;
 }

+/* Col3 (Wildcard/Style) タブ切り替え */
+.wfm-prompt-col3-tabs {
+    display: flex;
+    background: var(--wfm-surface);
+    border-bottom: 1px solid var(--wfm-border);
+    flex-shrink: 0;
+}
+.wfm-prompt-col3-tab {
+    flex: 1;
+    padding: 8px 4px;
+    background: none;
+    border: none;
+    border-bottom: 2px solid transparent;
+    color: var(--wfm-text-secondary);
+    font-size: 13px;
+    font-weight: bold;
+    cursor: pointer;
+    transition: all 0.15s;
+}
+.wfm-prompt-col3-tab:hover { color: var(--wfm-text); }
+.wfm-prompt-col3-tab.active {
+    color: var(--wfm-text);
+    border-bottom-color: var(--wfm-primary);
+}
+.wfm-prompt-col3-tab-content {
+    display: flex;
+    flex-direction: column;
+    flex: 1;
+    min-height: 0;
+    overflow: hidden;
+}
+
+/* Prompt タブ: Form / Table 切り替え */
+.wfm-prompt-toplevel-nav {
+    display: flex;
+    border-bottom: 1px solid var(--wfm-border);
+    flex-shrink: 0;
+}
+.wfm-prompt-toplevel-tab {
+    padding: 6px 16px;
+    font-size: 12px;
+    background: transparent;
+    border: none;
+    color: var(--wfm-text-secondary);
+    cursor: pointer;
+    border-bottom: 2px solid transparent;
+    margin-bottom: -1px;
+    transition: color 0.15s;
+}
+.wfm-prompt-toplevel-tab:hover { color: var(--wfm-text-primary); }
+.wfm-prompt-toplevel-tab.active { color: var(--wfm-primary); border-bottom-color: var(--wfm-primary); }
+
+.wfm-prompt-panel {
+    display: none;
+    flex-direction: column;
+    flex: 1;
+    min-height: 0;
+    overflow: hidden;
+}
+.wfm-prompt-panel.active { display: flex; }
+
+/* Table パネル内サブタブ (Presets / Wildcards / Style) */
+.wfm-prompt-table-subnav {
+    display: flex;
+    background: var(--wfm-surface);
+    border-bottom: 1px solid var(--wfm-border);
+    flex-shrink: 0;
+}
+.wfm-prompt-table-subtab {
+    padding: 8px 16px;
+    background: none;
+    border: none;
+    border-bottom: 2px solid transparent;
+    color: var(--wfm-text-secondary);
+    font-size: 13px;
+    font-weight: bold;
+    cursor: pointer;
+    transition: all 0.15s;
+}
+.wfm-prompt-table-subtab:hover { color: var(--wfm-text); }
+.wfm-prompt-table-subtab.active { color: var(--wfm-text); border-bottom-color: var(--wfm-primary); }
+
+.wfm-prompt-table-pane {
+    display: none;
+    flex-direction: column;
+    flex: 1;
+    min-height: 0;
+    overflow: hidden;
+}
+.wfm-prompt-table-pane.active { display: flex; }
+
+.wfm-prompt-table-toolbar {
+    display: flex;
+    flex-wrap: wrap;
+    gap: 6px;
+    align-items: center;
+    padding: 8px;
+    flex-shrink: 0;
+    border-bottom: 1px solid var(--wfm-border);
+}
+
+.wfm-prompt-table-scroll {
+    flex: 1;
+    min-height: 0;
+    overflow: auto;
+}
+
+/* 編集可能テーブル (Presets / Wildcards / Style 共通) */
+.wfm-prompt-edit-table {
+    width: 100%;
+    border-collapse: collapse;
+}
+.wfm-prompt-edit-table th,
+.wfm-prompt-edit-table td {
+    border-bottom: 1px solid var(--wfm-border);
+    padding: 4px 6px;
+    vertical-align: top;
+}
+.wfm-prompt-edit-table th {
+    position: sticky;
+    top: 0;
+    background: var(--wfm-surface);
+    text-align: left;
+    font-size: 11px;
+    color: var(--wfm-text-secondary);
+    z-index: 1;
+}
+.wfm-prompt-edit-table tbody tr:hover td {
+    background: var(--wfm-surface);
+}
+.wfm-prompt-edit-input,
+.wfm-prompt-edit-textarea {
+    width: 100%;
+    box-sizing: border-box;
+    background: transparent;
+    border: 1px solid transparent;
+    border-radius: 3px;
+    color: var(--wfm-text);
+    font-size: 12px;
+    padding: 3px 5px;
+    font-family: inherit;
+}
+.wfm-prompt-edit-textarea {
+    min-height: 40px;
+    resize: vertical;
+}
+.wfm-prompt-edit-input:hover,
+.wfm-prompt-edit-textarea:hover {
+    border-color: var(--wfm-border);
+}
+.wfm-prompt-edit-input:focus,
+.wfm-prompt-edit-textarea:focus {
+    outline: none;
+    border-color: var(--wfm-primary);
+    background: var(--wfm-bg);
+}
+@keyframes wfm-prompt-cell-flash {
+    0% { background: rgba(74, 158, 255, 0.3); }
+    100% { background: transparent; }
+}
+.wfm-prompt-edit-cell-saved {
+    animation: wfm-prompt-cell-flash 0.7s ease;
+}
+.wfm-prompt-edit-fav-btn {
+    background: none;
+    border: none;
+    cursor: pointer;
+    font-size: 14px;
+    color: var(--wfm-text-secondary);
+    padding: 2px;
+    line-height: 1;
+}
+.wfm-prompt-edit-fav-btn.active { color: #ffd700; }
+.wfm-prompt-edit-batch-btn.active { color: #f0c040; }
+.wfm-prompt-edit-row-new td { background: rgba(74, 158, 255, 0.06); }
+.wfm-prompt-edit-file-badge {
+    font-size: 10px;
+    color: var(--wfm-text-secondary);
+    white-space: nowrap;
+    overflow: hidden;
+    text-overflow: ellipsis;
+    display: block;
+}
+.wfm-prompt-edit-empty {
+    padding: 24px;
+    text-align: center;
+    color: var(--wfm-text-secondary);
+    font-size: 12px;
+}
+
+/* ダブルクリックで開くプロンプト編集モーダル (Presets / Wildcards / Style 共通) */
+.wfm-prompt-modal-toggle {
+    display: flex;
+    gap: 6px;
+}
+.wfm-prompt-modal-textarea {
+    width: 100%;
+    box-sizing: border-box;
+    min-height: 320px;
+    resize: vertical;
+    margin-top: 8px;
+}
+.wfm-prompt-modal-actions {
+    display: flex;
+    gap: 6px;
+    justify-content: flex-end;
+    margin-top: 10px;
+}
+
+/* #(自動採番)列: クリックで行選択 → 上部の Delete ボタンで一括削除 */
+.wfm-prompt-edit-num-cell {
+    text-align: center;
+    cursor: pointer;
+    -webkit-user-select: none;
+    user-select: none;
+    color: var(--wfm-text-secondary);
+    font-size: 11px;
+    font-variant-numeric: tabular-nums;
+    white-space: nowrap;
+}
+.wfm-prompt-edit-num-cell:hover {
+    color: var(--wfm-text);
+    background: var(--wfm-surface-2, var(--wfm-surface));
+}
+.wfm-prompt-edit-table tbody tr.wfm-prompt-edit-row-selected td {
+    background: rgba(255, 69, 58, 0.14);
+}
+.wfm-prompt-edit-table tbody tr.wfm-prompt-edit-row-selected .wfm-prompt-edit-num-cell {
+    color: var(--wfm-danger);
+    font-weight: bold;
+}
+.wfm-prompt-edit-num-cell-new {
+    display: flex;
+    gap: 2px;
+    justify-content: center;
+}
+.wfm-prompt-edit-inline-add-btn,
+.wfm-prompt-edit-inline-cancel-btn {
+    background: none;
+    border: none;
+    cursor: pointer;
+    font-size: 12px;
+    padding: 2px 3px;
+    line-height: 1;
+    border-radius: 3px;
+}
+.wfm-prompt-edit-inline-add-btn { color: var(--wfm-primary); }
+.wfm-prompt-edit-inline-add-btn:hover { background: var(--wfm-primary); color: #fff; }
+.wfm-prompt-edit-inline-cancel-btn { color: var(--wfm-text-secondary); }
+.wfm-prompt-edit-inline-cancel-btn:hover { color: var(--wfm-danger); }
+
+/* Presets Group テーブル: プリセットバッジ */
+.wfm-prompt-edit-preset-badge {
+    display: inline-flex;
+    align-items: center;
+    gap: 3px;
+    background: var(--wfm-surface);
+    border: 1px solid var(--wfm-border);
+    border-radius: 10px;
+    padding: 2px 4px 2px 8px;
+    font-size: 11px;
+    margin: 2px 3px 2px 0;
+}
+.wfm-prompt-edit-badge-remove {
+    background: none;
+    border: none;
+    cursor: pointer;
+    color: var(--wfm-text-secondary);
+    font-size: 10px;
+    padding: 1px 3px;
+    line-height: 1;
+}
+.wfm-prompt-edit-badge-remove:hover { color: var(--wfm-danger); }
+
 /* Ollama Assistant */
 .wfm-ollama-assistant {
    display: flex;
@@ -2874,6 +3172,29 @@ body {
   Image Input (I2I) Slots
   ============================================ */

+/* Container/header styling comes from .wfm-settings-section / .wfm-settings-summary
+   (shared details/summary accordion used by the Settings tab) — collapsed by default
+   since this is a low-frequency feature. */
+
+.wfm-i2i-placeholder-mode {
+    display: flex;
+    gap: 16px;
+    font-size: 12px;
+    margin-bottom: 8px;
+}
+
+.wfm-i2i-placeholder-mode label {
+    display: flex;
+    align-items: center;
+    gap: 4px;
+    cursor: pointer;
+}
+
+.wfm-i2i-placeholder-fields input[type="color"] {
+    padding: 2px;
+    height: 30px;
+}
+
 .wfm-i2i-grid {
    display: grid;
    grid-template-columns: 1fr 1fr;
@@ -2937,6 +3258,12 @@ body {
    background: rgba(74, 158, 255, 0.08);
 }

+.wfm-i2i-drop-zone.wfm-disabled {
+    opacity: 0.4;
+    pointer-events: none;
+    cursor: default;
+}
+
 .wfm-i2i-drop-label {
    font-size: 12px;
    color: var(--wfm-text-secondary);
@@ -3171,6 +3498,21 @@ body {
    display: block;
 }

+.wfm-help-article-header {
+    display: flex;
+    align-items: center;
+    justify-content: space-between;
+    gap: 12px;
+    margin-bottom: 14px;
+}
+
+.wfm-help-article-header h2 {
+    font-size: 24px;
+    font-weight: 700;
+    color: var(--wfm-text);
+    margin: 0;
+}
+
 .wfm-help-card {
    background: var(--wfm-surface);
    border: 1px solid var(--wfm-border);
@@ -4931,15 +5273,12 @@ body {
   Metadata Tab
   ============================================ */

-#wfm-tab-metadata {
-    overflow: hidden;
-}
-
 .wfm-metadata-layout {
    display: grid;
    grid-template-columns: 220px 1fr 1fr;
    gap: 0;
-    height: 100%;
+    flex: 1;
+    min-height: 0;
    overflow: hidden;
 }

@@ -5613,6 +5952,23 @@ body {
    object-fit: cover;
 }

+.wfm-ai-chat-svg-wrapper {
+    margin-top: 6px;
+    display: flex;
+    flex-direction: column;
+    align-items: flex-start;
+    gap: 6px;
+}
+
+.wfm-ai-chat-svg-img {
+    max-width: 240px;
+    max-height: 240px;
+    border-radius: 6px;
+    border: 1px solid var(--wfm-border);
+    background: #fff;
+    padding: 6px;
+}
+
 .wfm-ai-chat-attachment {
    display: flex;
    align-items: center;
@@ -5686,3 +6042,42 @@ body {
    align-items: center;
    gap: 6px;
 }
+
+.wfm-ai-chat-skill-row {
+    display: flex;
+    align-items: center;
+    gap: 6px;
+    padding: 6px 8px 0;
+    flex-shrink: 0;
+}
+
+.wfm-ai-chat-skill-select {
+    flex: 1;
+    min-width: 0;
+}
+
+.wfm-ai-skill-panel {
+    margin: 6px 8px 0;
+    padding: 8px;
+    border: 1px solid var(--wfm-border);
+    border-radius: var(--wfm-radius);
+    background: var(--wfm-surface);
+    display: flex;
+    flex-direction: column;
+    gap: 6px;
+    flex-shrink: 0;
+}
+
+.wfm-ai-skill-panel-header {
+    display: flex;
+    align-items: center;
+    justify-content: space-between;
+}
+
+.wfm-ai-skill-panel-title {
+    font-size: 12px;
+    font-weight: 600;
+    color: var(--wfm-text-secondary);
+    text-transform: uppercase;
+    letter-spacing: 0.04em;
+}
@@ -250,6 +250,14 @@
    z-index: 1;
 }

+#wfm-tagger-db-th-select, td.wfm-tagger-db-select {
+    text-align: center;
+}
+
+#wfm-tagger-db-th-select input, .wfm-tagger-db-select input {
+    vertical-align: middle;
+}
+
 .wfm-tagger-db-table tbody tr {
    cursor: pointer;
    transition: background 0.1s;
@@ -0,0 +1,205 @@
+/**
+ * Shared AI backend settings modal (Backend / Connection / Model / Generation / Unload / Save).
+ * Used by the Prompt tab and Tagger tab, each with its own localStorage key so their
+ * settings stay independent — mirrors the AI TOOL tab's own settings pane (ai-tab.js).
+ */
+
+import { openModal, closeModal, showToast } from "./app.js";
+import { t } from "./i18n.js";
+import { readJsonStorage, getAiBackendDefaultUrl, unslothProxy, unloadAiModel } from "./util.js";
+
+function loadCfg(storageKey) {
+    return readJsonStorage(storageKey);
+}
+
+function saveCfg(storageKey, patch) {
+    const data = { ...loadCfg(storageKey), ...patch };
+    localStorage.setItem(storageKey, JSON.stringify(data));
+    return data;
+}
+
+// 保存済み設定を {backend, url, model, thinkingMode, maxTokens} の形で返す
+export function getAiBackendConfig(storageKey) {
+    const s = loadCfg(storageKey);
+    const backend = s.backend || "ollama";
+    const url = (s.backendUrl || getAiBackendDefaultUrl(backend)).replace(/\/$/, "");
+    return {
+        backend,
+        url,
+        model: s.model || "",
+        thinkingMode: !!s.thinkingMode,
+        maxTokens: Math.max(0, parseInt(s.maxTokens, 10) || 0),
+    };
+}
+
+function isValidBackendUrl(url) {
+    try {
+        const u = new URL(url);
+        return u.protocol === "http:" || u.protocol === "https:";
+    } catch {
+        return false;
+    }
+}
+
+async function fetchBackendModels(url, backend) {
+    if (backend === "ollama") {
+        const res = await fetch(`${url}/api/tags`);
+        if (!res.ok) throw new Error(`HTTP ${res.status}`);
+        return (await res.json()).models?.map(m => m.name) || [];
+    } else if (backend === "unsloth") {
+        const data = await unslothProxy(url, "/v1/models", "GET");
+        return (data.data || []).map(m => m.id);
+    } else {
+        const res = await fetch(`${url}/v1/models`);
+        if (!res.ok) throw new Error(`HTTP ${res.status}`);
+        return ((await res.json()).data || []).map(m => m.id);
+    }
+}
+
+/**
+ * @param {string} storageKey localStorage key holding {backend, backendUrl, model, thinkingMode, maxTokens}
+ * @param {string} title modal title
+ * @param {() => void} [onSaved] called after Save persists the config (e.g. to refresh a status label)
+ */
+export function openAiBackendSettingsModal(storageKey, title, onSaved) {
+    const saved = loadCfg(storageKey);
+    const backend = saved.backend || "ollama";
+
+    const html = `
+        <div class="wfm-ai-settings-container">
+            <div class="wfm-ai-settings-section">
+                <div class="wfm-ai-settings-title">${t("aiSettingsBackend")}</div>
+                <div class="wfm-ai-backend-row">
+                    ${[["ollama", "Ollama"], ["lmstudio", "LM Studio"], ["lemonade", "Lemonade"], ["unsloth", "Unsloth"]].map(([v, label]) => `
+                        <label class="wfm-ai-radio-label">
+                            <input type="radio" name="wfm-aism-backend" value="${v}" ${v === backend ? "checked" : ""}> ${label}
+                        </label>`).join("")}
+                </div>
+            </div>
+            <div class="wfm-ai-settings-section">
+                <div class="wfm-ai-settings-title">${t("aiSettingsConnection")}</div>
+                <div class="wfm-ai-settings-row">
+                    <label class="wfm-ai-label">URL</label>
+                    <input type="text" id="wfm-aism-url" class="wfm-input wfm-ai-url-input" value="${saved.backendUrl || getAiBackendDefaultUrl(backend)}">
+                </div>
+                <div class="wfm-ai-settings-row">
+                    <button id="wfm-aism-test-btn" class="wfm-btn">${t("aiSettingsTestBtn")}</button>
+                    <button id="wfm-aism-unload-btn" class="wfm-btn">${t("aiUnloadModel")}</button>
+                </div>
+                <div class="wfm-ai-settings-row">
+                    <span id="wfm-aism-test-result" class="wfm-ai-test-result"></span>
+                </div>
+            </div>
+            <div class="wfm-ai-settings-section">
+                <div class="wfm-ai-settings-title">${t("aiSettingsModelSection")}</div>
+                <div class="wfm-ai-settings-row">
+                    <select id="wfm-aism-model" class="wfm-select wfm-ai-model-select">
+                        <option value="">${t("selectModel")}</option>
+                    </select>
+                    <button id="wfm-aism-refresh-btn" class="wfm-btn">${t("aiSettingsRefreshBtn")}</button>
+                </div>
+            </div>
+            <div class="wfm-ai-settings-section">
+                <div class="wfm-ai-settings-title">${t("aiSettingsGenerationTitle")}</div>
+                <div class="wfm-ai-settings-row">
+                    <label class="wfm-ai-label" style="display:flex;align-items:center;gap:6px;cursor:pointer;">
+                        <input type="checkbox" id="wfm-aism-thinking"> ${t("aiSettingsThinkingMode")}
+                    </label>
+                </div>
+                <div class="wfm-ai-settings-row">
+                    <label class="wfm-ai-label">${t("aiSettingsMaxTokens")}</label>
+                    <input type="number" id="wfm-aism-max-tokens" class="wfm-input" min="0" step="1" placeholder="${t("aiSettingsMaxTokensPlaceholder")}">
+                </div>
+            </div>
+            <div class="wfm-ai-settings-section">
+                <button id="wfm-aism-save-btn" class="wfm-btn wfm-btn-primary">${t("aiSettingsSaveBtn")}</button>
+            </div>
+        </div>`;
+
+    openModal(title, html);
+
+    const urlInput = document.getElementById("wfm-aism-url");
+    const modelSelect = document.getElementById("wfm-aism-model");
+    const thinkingCheckbox = document.getElementById("wfm-aism-thinking");
+    const maxTokensInput = document.getElementById("wfm-aism-max-tokens");
+    const testResultEl = document.getElementById("wfm-aism-test-result");
+
+    thinkingCheckbox.checked = !!saved.thinkingMode;
+    if (saved.maxTokens) maxTokensInput.value = saved.maxTokens;
+
+    function currentBackend() {
+        return document.querySelector("input[name='wfm-aism-backend']:checked")?.value || "ollama";
+    }
+
+    async function populateModels(selectedModel) {
+        const url = urlInput.value.trim();
+        try {
+            const models = await fetchBackendModels(url, currentBackend());
+            modelSelect.innerHTML = models.length
+                ? models.map(name => `<option value="${name}" ${name === selectedModel ? "selected" : ""}>${name}</option>`).join("")
+                : `<option value="">${t("noModelsFound")}</option>`;
+        } catch {
+            modelSelect.innerHTML = `<option value="">${t("noModelsFound")}</option>`;
+        }
+    }
+    populateModels(saved.model || "");
+
+    document.querySelectorAll("input[name='wfm-aism-backend']").forEach(r => {
+        r.addEventListener("change", () => {
+            urlInput.value = getAiBackendDefaultUrl(r.value);
+            testResultEl.textContent = "";
+        });
+    });
+
+    document.getElementById("wfm-aism-refresh-btn")?.addEventListener("click", () => populateModels(modelSelect.value));
+
+    document.getElementById("wfm-aism-test-btn")?.addEventListener("click", async () => {
+        const url = urlInput.value.trim();
+        if (!isValidBackendUrl(url)) {
+            testResultEl.textContent = t("aiToastInvalidUrlInput");
+            testResultEl.className = "wfm-ai-test-result wfm-ai-status-error";
+            return;
+        }
+        testResultEl.textContent = t("aiStatusConnecting");
+        testResultEl.className = "wfm-ai-test-result wfm-ai-status-working";
+        try {
+            const models = await fetchBackendModels(url, currentBackend());
+            testResultEl.textContent = `${t("aiStatusConnectOk")} (${models.length} ${t("aiModels")})`;
+            testResultEl.className = "wfm-ai-test-result wfm-ai-status-ok";
+            await populateModels(modelSelect.value);
+        } catch (err) {
+            testResultEl.textContent = `${t("aiStatusConnectFail")}${err.message}`;
+            testResultEl.className = "wfm-ai-test-result wfm-ai-status-error";
+        }
+    });
+
+    document.getElementById("wfm-aism-unload-btn")?.addEventListener("click", async () => {
+        const url = urlInput.value.trim();
+        const model = modelSelect.value;
+        if (!model) { showToast(t("aiUnloadNoModel"), "error"); return; }
+        try {
+            await unloadAiModel(url, currentBackend(), model);
+            showToast(t("aiUnloadDone"), "success");
+        } catch (err) {
+            showToast(err.message === "UNSUPPORTED" ? t("aiUnloadUnsupported") : t("aiUnloadFailed") + err.message, "error");
+        }
+    });
+
+    document.getElementById("wfm-aism-save-btn")?.addEventListener("click", () => {
+        const url = urlInput.value.trim();
+        if (url && !isValidBackendUrl(url)) {
+            showToast(t("aiToastInvalidUrl"), "error");
+            return;
+        }
+        saveCfg(storageKey, {
+            backend: currentBackend(),
+            backendUrl: url,
+            model: modelSelect.value,
+            thinkingMode: !!thinkingCheckbox.checked,
+            maxTokens: Math.max(0, parseInt(maxTokensInput.value, 10) || 0),
+        });
+        showToast(t("aiToastSettingsSaved"), "success");
+        closeModal();
+        if (onSaved) onSaved();
+    });
+}
@@ -1,11 +1,11 @@
 /**
 * AI Tab - Translation, VLM, Settings
- * Supports Ollama and LM Studio as backends
+ * Supports Ollama, LM Studio, and Lemonade as backends
 */

 import { showToast } from "./app.js";
 import { t } from "./i18n.js";
-import { readJsonStorage } from "./util.js";
+import { readJsonStorage, getAiBackendDefaultUrl, escapeHtml, unloadAiModel } from "./util.js";
 import { comfyUI } from "./comfyui-client.js";
 import { comfyEditor } from "./comfyui-editor.js";
 import { comfyWorkflow } from "./comfyui-workflow.js";
@@ -50,33 +50,102 @@ function fileToBase64(file) {
    });
 }

-async function callVLM(url, backend, model, prompt, base64Image, mimeType) {
+// ============================================
+// Thinking mode / Max tokens (shared by callLLM / callChat / callVLM)
+// ============================================
+
+// Ollamaは `think` (bool) と `options.num_predict` で制御できるが、
+// LM Studio/LemonadeはOpenAI互換APIのため max_tokens のみ標準対応。
+// thinking mode切替は非対応バックエンド／モデル向けに、出力からの
+// <think>タグ除去でも担保する（stripThinkingTagsを参照）。
+function _applyGenOptions(body, backend, settings) {
+    const maxTokens = parseInt(settings?.maxTokens, 10);
+    if (backend === "ollama") {
+        body.think = !!settings?.thinkingMode;
+        if (maxTokens > 0) body.options = { ...(body.options || {}), num_predict: maxTokens };
+    } else if (maxTokens > 0) {
+        body.max_tokens = maxTokens;
+    }
+    return body;
+}
+
+function stripThinkingTags(text) {
+    return (text || "")
+        .replace(/<think>[\s\S]*?<\/think>/gi, "")
+        .replace(/<thinking>[\s\S]*?<\/thinking>/gi, "")
+        .trim();
+}
+
+async function callVLM(url, backend, model, prompt, base64Image, mimeType, settings = {}) {
    if (backend === "ollama") {
        const res = await fetch(`${url}/api/generate`, {
            method: "POST",
            headers: { "Content-Type": "application/json" },
-            body: JSON.stringify({ model, prompt, images: [base64Image], stream: false }),
+            body: JSON.stringify(_applyGenOptions({ model, prompt, images: [base64Image], stream: false }, backend, settings)),
        });
        if (!res.ok) throw new Error(`HTTP ${res.status}`);
-        return (await res.json()).response || "";
+        const text = (await res.json()).response || "";
+        return settings.thinkingMode ? text : stripThinkingTags(text);
+    } else if (backend === "unsloth") {
+        const body = _applyGenOptions({
+            model,
+            messages: [{ role: "user", content: [
+                { type: "text", text: prompt },
+                { type: "image_url", image_url: { url: `data:${mimeType};base64,${base64Image}` } },
+            ]}],
+            stream: false,
+        }, backend, settings);
+        const data = await unslothProxy(url, "/v1/chat/completions", "POST", body);
+        const text = _unslothContent(data.choices?.[0]?.message);
+        return settings.thinkingMode ? text : stripThinkingTags(text);
    } else {
        const res = await fetch(`${url}/v1/chat/completions`, {
            method: "POST",
            headers: { "Content-Type": "application/json" },
-            body: JSON.stringify({
+            body: JSON.stringify(_applyGenOptions({
                model,
                messages: [{ role: "user", content: [
                    { type: "text", text: prompt },
                    { type: "image_url", image_url: { url: `data:${mimeType};base64,${base64Image}` } },
                ]}],
                stream: false,
-            }),
+            }, backend, settings)),
        });
        if (!res.ok) throw new Error(`HTTP ${res.status}`);
-        return (await res.json()).choices?.[0]?.message?.content || "";
+        const text = (await res.json()).choices?.[0]?.message?.content || "";
+        return settings.thinkingMode ? text : stripThinkingTags(text);
    }
 }

+// ============================================
+// Unsloth proxy (server relays the request, attaching the API key from .env
+// so it never reaches the frontend — see py/routes/unsloth_routes.py)
+// ============================================
+
+async function unslothProxy(baseUrl, path, method, payload) {
+    const res = await fetch("/api/wfm/unsloth/proxy", {
+        method: "POST",
+        headers: { "Content-Type": "application/json" },
+        body: JSON.stringify({ baseUrl, path, method, payload }),
+    });
+    const data = await res.json().catch(() => ({}));
+    if (!res.ok) throw new Error(data.message || `HTTP ${res.status}`);
+    return data;
+}
+
+// Unlike Ollama/LM Studio/Lemonade (which inline reasoning as <think> tags
+// inside content), Unsloth's OpenAI-compatible API returns it in a separate
+// `reasoning_content` field. Fold it back into a <think> block so the
+// existing Thinking-mode show/strip logic (_applyGenOptions/stripThinkingTags)
+// still applies uniformly. Without this, a low max_tokens can make the model
+// spend its whole budget reasoning and return an empty `content` with no
+// visible explanation.
+function _unslothContent(message) {
+    const reasoning = message?.reasoning_content;
+    const content = message?.content || "";
+    return reasoning ? `<think>${reasoning}</think>${content}` : content;
+}
+
 // ============================================
 // URL validation
 // ============================================
@@ -100,6 +169,9 @@ async function fetchModels(url, backend) {
        if (!res.ok) throw new Error(`HTTP ${res.status}`);
        const data = await res.json();
        return (data.models || []).map((m) => m.name);
+    } else if (backend === "unsloth") {
+        const data = await unslothProxy(url, "/v1/models", "GET");
+        return (data.data || []).map((m) => m.id);
    } else {
        // LM Studio (OpenAI-compatible)
        const res = await fetch(`${url}/v1/models`);
@@ -114,30 +186,37 @@ async function testConnection(url, backend) {
    return models.length;
 }

-async function callLLM(url, backend, model, prompt) {
+async function callLLM(url, backend, model, prompt, settings = {}) {
    if (backend === "ollama") {
        const res = await fetch(`${url}/api/generate`, {
            method: "POST",
            headers: { "Content-Type": "application/json" },
-            body: JSON.stringify({ model, prompt, stream: false }),
+            body: JSON.stringify(_applyGenOptions({ model, prompt, stream: false }, backend, settings)),
        });
        if (!res.ok) throw new Error(`HTTP ${res.status}`);
        const data = await res.json();
-        return data.response || "";
+        const text = data.response || "";
+        return settings.thinkingMode ? text : stripThinkingTags(text);
+    } else if (backend === "unsloth") {
+        const body = _applyGenOptions({ model, messages: [{ role: "user", content: prompt }], stream: false }, backend, settings);
+        const data = await unslothProxy(url, "/v1/chat/completions", "POST", body);
+        const text = _unslothContent(data.choices?.[0]?.message);
+        return settings.thinkingMode ? text : stripThinkingTags(text);
    } else {
        // LM Studio (OpenAI-compatible)
        const res = await fetch(`${url}/v1/chat/completions`, {
            method: "POST",
            headers: { "Content-Type": "application/json" },
-            body: JSON.stringify({
+            body: JSON.stringify(_applyGenOptions({
                model,
                messages: [{ role: "user", content: prompt }],
                stream: false,
-            }),
+            }, backend, settings)),
        });
        if (!res.ok) throw new Error(`HTTP ${res.status}`);
        const data = await res.json();
-        return data.choices?.[0]?.message?.content || "";
+        const text = data.choices?.[0]?.message?.content || "";
+        return settings.thinkingMode ? text : stripThinkingTags(text);
    }
 }

@@ -145,11 +224,41 @@ async function callLLM(url, backend, model, prompt) {
 // Translation prompt builder
 // ============================================

-function buildTranslationPrompt(text, srcLang, dstLang, settings) {
-    const srcName = srcLang === "free" ? (settings.freeSrcLang || "Auto") : LANG_NAMES[srcLang];
-    const dstName = dstLang === "free" ? (settings.freeDstLang || "English") : LANG_NAMES[dstLang];
-    const fromPart = srcLang === "free" ? "" : `from ${srcName} `;
-    return `Translate the following text ${fromPart}to ${dstName}. Output only the translated text, nothing else.\n\n${text}`;
+// Uses a system role (via callChat) rather than a single raw prompt string —
+// local models follow "translate only, no commentary" far more reliably
+// when it's a system instruction instead of buried inside the user text.
+function buildTranslationMessages(text, srcLang, dstLang, settings) {
+    const srcName = srcLang === "free" ? (settings.freeSrcLang || "").trim() : LANG_NAMES[srcLang];
+    const dstName = dstLang === "free" ? (settings.freeDstLang || "English").trim() || "English" : LANG_NAMES[dstLang];
+    const fromPart = srcName ? ` from ${srcName}` : "";
+    const system = `You are a professional translator. Translate the text the user sends${fromPart} into ${dstName}. `
+        + `Reply with ONLY the translated text and nothing else: no explanations, no notes, no preamble like "Here is the translation:", `
+        + `no surrounding quotes, and do not repeat or echo the original text.`;
+    return [
+        { role: "system", content: system },
+        { role: "user", content: text },
+    ];
+}
+
+// Strips common LLM wrapping/preamble artifacts that survive despite the system prompt.
+function cleanTranslationOutput(raw) {
+    let s = (raw || "").trim();
+    s = s.replace(/^(sure[,.]?\s*)?(here('|)s|here is)?\s*(the\s+)?translation\s*:?\s*/i, "");
+    s = s.replace(/^(翻訳|译文|翻译)\s*[::]\s*/, "");
+    if (s.length >= 2) {
+        const first = s[0], last = s[s.length - 1];
+        const pairs = { '"': '"', "'": "'", "“": "”", "「": "」" };
+        if (pairs[first] === last) s = s.slice(1, -1).trim();
+    }
+    return s;
+}
+
+// Heuristic: if the cleaned output is (near-)identical to the input, the
+// model most likely echoed the source instead of translating it.
+function looksUntranslated(input, output) {
+    const normalize = (s) => s.trim().toLowerCase().replace(/[\s.,!?"'。、！？「」]/g, "");
+    const a = normalize(input), b = normalize(output);
+    return a.length > 0 && a === b;
 }

 // ============================================
@@ -199,7 +308,7 @@ function initTranslateTab() {

        const settings = loadAiSettings();
        const { backend = "ollama", backendUrl, model } = settings;
-        const url = backendUrl || (backend === "ollama" ? "http://localhost:11434" : "http://localhost:1234");
+        const url = backendUrl || getAiBackendDefaultUrl(backend);

        if (!isValidBackendUrl(url)) {
            showToast(t("aiToastInvalidUrl"), "error");
@@ -217,11 +326,19 @@ function initTranslateTab() {
        outputEl.value = "";

        try {
-            const prompt = buildTranslationPrompt(text, srcLangSel.value, dstLangSel.value, settings);
-            const result = await callLLM(url, backend, model, prompt);
-            outputEl.value = result.trim();
-            statusEl.textContent = t("aiStatusDone");
-            statusEl.className = "wfm-ai-trans-status wfm-ai-status-ok";
+            const messages = buildTranslationMessages(text, srcLangSel.value, dstLangSel.value, settings);
+            const { content } = await callChat(url, backend, model, messages, undefined, settings);
+            const cleaned = cleanTranslationOutput(content);
+            outputEl.value = cleaned;
+
+            if (srcLangSel.value !== dstLangSel.value && looksUntranslated(text, cleaned)) {
+                statusEl.textContent = t("aiStatusDone");
+                statusEl.className = "wfm-ai-trans-status wfm-ai-status-error";
+                showToast(t("aiToastMaybeNotTranslated"), "error");
+            } else {
+                statusEl.textContent = t("aiStatusDone");
+                statusEl.className = "wfm-ai-trans-status wfm-ai-status-ok";
+            }
        } catch (err) {
            statusEl.textContent = `${t("aiStatusConnectFail")}${err.message}`;
            statusEl.className = "wfm-ai-trans-status wfm-ai-status-error";
@@ -288,12 +405,16 @@ function initSettingsTab() {
    const urlInput = document.getElementById("wfm-ai-backend-url");
    if (urlInput && saved.backendUrl) urlInput.value = saved.backendUrl;

-    // Update URL placeholder when backend changes
+    const thinkingModeCheckbox = document.getElementById("wfm-ai-thinking-mode-checkbox");
+    if (thinkingModeCheckbox) thinkingModeCheckbox.checked = !!saved.thinkingMode;
+    const maxTokensInput = document.getElementById("wfm-ai-max-tokens");
+    if (maxTokensInput && saved.maxTokens) maxTokensInput.value = saved.maxTokens;
+
+    // Switch URL to the new backend's default when the user changes backend
    backendRadios.forEach((r) => {
        r.addEventListener("change", () => {
            if (!urlInput) return;
-            const defaultUrl = r.value === "ollama" ? "http://localhost:11434" : "http://localhost:1234";
-            if (!saved.backendUrl) urlInput.value = defaultUrl;
+            urlInput.value = getAiBackendDefaultUrl(r.value);
        });
    });

@@ -335,6 +456,20 @@ function initSettingsTab() {
        }
    });

+    // Unload model
+    document.getElementById("wfm-ai-unload-btn")?.addEventListener("click", async () => {
+        const backend = document.querySelector("input[name='wfm-ai-backend']:checked")?.value || "ollama";
+        const url = urlInput?.value?.trim() || "";
+        const model = document.getElementById("wfm-ai-model-select")?.value || "";
+        if (!model) { showToast(t("aiUnloadNoModel"), "error"); return; }
+        try {
+            await unloadAiModel(url, backend, model);
+            showToast(t("aiUnloadDone"), "success");
+        } catch (err) {
+            showToast(err.message === "UNSUPPORTED" ? t("aiUnloadUnsupported") : t("aiUnloadFailed") + err.message, "error");
+        }
+    });
+
    // Model refresh
    document.getElementById("wfm-ai-model-refresh-btn")?.addEventListener("click", () => refreshModels());

@@ -396,6 +531,8 @@ function initSettingsTab() {
        const chatGenDedicatedFilename = chatGenSelect?.value || "";
        const chatGenI2IDedicatedEnabled = !!chatGenI2ICheckbox?.checked;
        const chatGenI2IDedicatedFilename = chatGenI2ISelect?.value || "";
+        const thinkingMode = !!thinkingModeCheckbox?.checked;
+        const maxTokens = Math.max(0, parseInt(maxTokensInput?.value, 10) || 0);

        if (url && !isValidBackendUrl(url)) {
            showToast(t("aiToastInvalidUrl"), "error");
@@ -404,6 +541,7 @@ function initSettingsTab() {

        saveAiSettings({
            backend, backendUrl: url, model, freeSrcLang, freeDstLang,
+            thinkingMode, maxTokens,
            chatGenDedicatedEnabled, chatGenDedicatedFilename,
            chatGenI2IDedicatedEnabled, chatGenI2IDedicatedFilename,
        });
@@ -424,12 +562,22 @@ const IMAGE_GEN_TOOLS = [{
    type: "function",
    function: {
        name: "generate_image",
-        description: "Generate an image using the currently loaded ComfyUI workflow. If an image is currently attached to the conversation, this performs image-to-image generation using that image as the base; otherwise it performs text-to-image. Call this when the user asks to create, draw, paint, edit, or transform an image.",
+        description: "Generate an image using the currently loaded ComfyUI workflow. If an image is currently attached to the conversation, this performs image-to-image generation using that image as the base; otherwise it performs text-to-image. Call this when the user asks to create, draw, paint, edit, or transform an image. All parameters besides prompt are optional — omit any the user didn't specify and the workflow's own current setting is kept.",
        parameters: {
            type: "object",
            properties: {
                prompt: { type: "string", description: "Positive prompt describing the desired image." },
                negative_prompt: { type: "string", description: "What to avoid in the image. Optional." },
+                steps: { type: "integer", description: "Sampling steps. Optional." },
+                cfg: { type: "number", description: "Classifier-free guidance scale. Optional." },
+                sampler_name: { type: "string", description: "ComfyUI sampler name (e.g. euler, dpmpp_2m, ddim). Optional." },
+                scheduler: { type: "string", description: "ComfyUI scheduler name (e.g. normal, karras, simple). Optional." },
+                denoise: { type: "number", description: "Denoise strength 0-1 (mainly relevant for image-to-image). Optional." },
+                seed: { type: "integer", description: "Fixed seed. Omit for a random seed each time. Optional." },
+                width: { type: "integer", description: "Output image width in pixels. Ignored if the workflow has a Resolution Selector node — use aspect_ratio instead for those. Optional." },
+                height: { type: "integer", description: "Output image height in pixels. Ignored if the workflow has a Resolution Selector node — use aspect_ratio instead for those. Optional." },
+                aspect_ratio: { type: "string", enum: ["1:1", "2:3", "3:2", "3:4", "4:3", "9:16", "16:9", "21:9"], description: "Aspect ratio preset. Only applied if the workflow has a Resolution Selector node (feeding width/height from a ratio + megapixel target); ignored otherwise. Optional." },
+                batch_size: { type: "integer", description: "Number of images to generate in this single call. Optional." },
            },
            required: ["prompt"],
        },
@@ -454,10 +602,10 @@ function _formatMessagesForBackend(messages, backend) {
    });
 }

-async function callChat(url, backend, model, messages, tools) {
+async function callChat(url, backend, model, messages, tools, settings = {}) {
    const formattedMessages = _formatMessagesForBackend(messages, backend);
    if (backend === "ollama") {
-        const body = { model, messages: formattedMessages, stream: false };
+        const body = _applyGenOptions({ model, messages: formattedMessages, stream: false }, backend, settings);
        if (tools) body.tools = tools;
        const res = await fetch(`${url}/api/chat`, {
            method: "POST",
@@ -466,9 +614,17 @@ async function callChat(url, backend, model, messages, tools) {
        });
        if (!res.ok) throw new Error(`HTTP ${res.status}`);
        const message = (await res.json()).message || {};
-        return { content: message.content || "", toolCalls: message.tool_calls || null };
+        const content = message.content || "";
+        return { content: settings.thinkingMode ? content : stripThinkingTags(content), toolCalls: message.tool_calls || null };
+    } else if (backend === "unsloth") {
+        const body = _applyGenOptions({ model, messages: formattedMessages, stream: false }, backend, settings);
+        if (tools) { body.tools = tools; body.tool_choice = "auto"; }
+        const data = await unslothProxy(url, "/v1/chat/completions", "POST", body);
+        const message = data.choices?.[0]?.message || {};
+        const content = _unslothContent(message);
+        return { content: settings.thinkingMode ? content : stripThinkingTags(content), toolCalls: message.tool_calls || null };
    } else {
-        const body = { model, messages: formattedMessages, stream: false };
+        const body = _applyGenOptions({ model, messages: formattedMessages, stream: false }, backend, settings);
        if (tools) { body.tools = tools; body.tool_choice = "auto"; }
        const res = await fetch(`${url}/v1/chat/completions`, {
            method: "POST",
@@ -477,7 +633,8 @@ async function callChat(url, backend, model, messages, tools) {
        });
        if (!res.ok) throw new Error(`HTTP ${res.status}`);
        const message = (await res.json()).choices?.[0]?.message || {};
-        return { content: message.content || "", toolCalls: message.tool_calls || null };
+        const content = message.content || "";
+        return { content: settings.thinkingMode ? content : stripThinkingTags(content), toolCalls: message.tool_calls || null };
    }
 }

@@ -502,7 +659,7 @@ async function _loadDedicatedChatGenWorkflow(filename) {
    return { workflow, analysis: comfyWorkflow.analyzeWorkflow(workflow) };
 }

-async function generateImageFromChat(prompt, negativePrompt) {
+async function generateImageFromChat(prompt, negativePrompt, params = {}) {
    if (!window._wfmGenerateTab?.generate) throw new Error(t("aiChatGenerateNotReady"));

    const settings = loadAiSettings();
@@ -527,12 +684,312 @@ async function generateImageFromChat(prompt, negativePrompt) {
    comfyEditor.setPromptText("positive", prompt || "", { workflow, analysis });
    if (negativePrompt) comfyEditor.setPromptText("negative", negativePrompt, { workflow, analysis });

-    const result = await window._wfmGenerateTab.generate(workflow);
+    const { steps, cfg, sampler_name, scheduler, denoise, seed, width, height, batch_size, aspect_ratio } = params;
+    let resolvedAspectRatio = null;
+    const resSelector = analysis.resolution_selector_nodes?.[0];
+    if (aspect_ratio && resSelector) {
+        resolvedAspectRatio = await comfyEditor.resolveAspectRatioOption(resSelector.type, aspect_ratio);
+    }
+    comfyEditor.setGenerationParams({
+        steps, cfg, sampler_name, scheduler, denoise, seed, width, height, batch_size,
+        resolvedAspectRatio, workflow, analysis,
+    });
+
+    const result = await window._wfmGenerateTab.generate(workflow, seed != null ? { seedValue: seed } : {});
    const images = result?.images || [];
    if (images.length === 0) throw new Error(t("aiChatNoImageProduced"));

-    const img = images[0];
-    return `/view?filename=${encodeURIComponent(img.filename)}&subfolder=${encodeURIComponent(img.subfolder || "")}&type=${encodeURIComponent(img.type || "output")}`;
+    return images.map((img) =>
+        `/view?filename=${encodeURIComponent(img.filename)}&subfolder=${encodeURIComponent(img.subfolder || "")}&type=${encodeURIComponent(img.type || "output")}`
+    );
+}
+
+// アシスタント応答からSVGコードを抽出する（```svg フェンス or 生の <svg>...</svg>）
+function _extractSvgCode(text) {
+    if (!text) return null;
+    const fenced = text.match(/```(?:svg|xml)?\s*([\s\S]*?<svg[\s\S]*?<\/svg>)[\s\S]*?```/i);
+    if (fenced) return fenced[1].trim();
+    const bare = text.match(/<svg[\s\S]*?<\/svg>/i);
+    if (bare) return bare[0].trim();
+    return null;
+}
+
+// SVGコードをプレビュー表示し、Galleryへ保存するボタンを追加する。
+// <img src="data:..."> でのレンダリングはブラウザがスクリプト実行を無効化するため安全。
+function _appendSvgPreview(container, svgCode) {
+    const wrapper = document.createElement("div");
+    wrapper.className = "wfm-ai-chat-svg-wrapper";
+
+    const dataUrl = `data:image/svg+xml;base64,${btoa(unescape(encodeURIComponent(svgCode)))}`;
+
+    const img = document.createElement("img");
+    img.src = dataUrl;
+    img.className = "wfm-ai-chat-svg-img";
+    img.alt = "Generated SVG";
+    wrapper.appendChild(img);
+
+    const saveBtn = document.createElement("button");
+    saveBtn.className = "wfm-btn wfm-btn-sm";
+    saveBtn.textContent = t("aiChatSaveSvgToGallery");
+    saveBtn.addEventListener("click", async () => {
+        saveBtn.disabled = true;
+        try {
+            const res = await fetch("/wfm/gallery/image/save", {
+                method: "POST",
+                headers: { "Content-Type": "application/json" },
+                body: JSON.stringify({ filename: `chat_svg_${Date.now()}.svg`, imageData: dataUrl }),
+            });
+            const data = await res.json();
+            if (!res.ok || data.error) throw new Error(data.error || `HTTP ${res.status}`);
+            showToast(t("aiChatSvgSaved"), "success");
+        } catch (e) {
+            showToast(t("aiChatSvgSaveFailed") + e.message, "error");
+        } finally {
+            saveBtn.disabled = false;
+        }
+    });
+    wrapper.appendChild(saveBtn);
+
+    container.appendChild(wrapper);
+}
+
+// アシスタント応答から ```skill フェンスを抽出する（Skill Creator用スキルが出力する完成品ブロック）
+function _extractSkillBlock(text) {
+    if (!text) return null;
+    const m = text.match(/```skill\s*([\s\S]*?)```/i);
+    return m ? m[1].trim() : null;
+}
+
+// frontmatterの name から保存用ファイル名を推測する（未設定時は my-skill.md）
+function _slugifySkillName(content) {
+    const m = content.match(/^---\r?\n[\s\S]*?name:\s*(.+?)\r?\n/);
+    const name = (m ? m[1] : "").trim();
+    const slug = name.toLowerCase().replace(/[^a-z0-9]+/g, "-").replace(/^-+|-+$/g, "");
+    return `${slug || "my-skill"}.md`;
+}
+
+// 応答内にスキル定義ブロックがあれば「スキルとして保存」ボタンを追加する。
+// クリックすると管理パネルを開き、新規スキルとしてエディタに内容を流し込む（保存前にレビュー可能）。
+function _appendSkillSaveButton(container, skillContent) {
+    const btn = document.createElement("button");
+    btn.className = "wfm-btn wfm-btn-sm";
+    btn.textContent = t("aiChatSaveAsSkill");
+    btn.addEventListener("click", () => {
+        const panel = document.getElementById("wfm-ai-skill-panel");
+        if (panel) panel.style.display = "";
+        skillOpenEditor(null, skillContent);
+        const nameInput = document.getElementById("wfm-ai-skill-editor-filename");
+        if (nameInput) nameInput.value = _slugifySkillName(skillContent);
+    });
+    container.appendChild(btn);
+}
+
+// ============================================
+// AI skills (Chat system prompt library)
+// ============================================
+
+async function skillFetchFiles() {
+    try {
+        const res = await fetch("/api/wfm/skills");
+        return res.ok ? await res.json() : [];
+    } catch { return []; }
+}
+
+async function skillFetchContent(filename) {
+    try {
+        const res = await fetch(`/api/wfm/skills/content?filename=${encodeURIComponent(filename)}`);
+        const data = await res.json();
+        return data.content ?? null;
+    } catch { return null; }
+}
+
+async function skillSaveFile(filename, content) {
+    try {
+        const res = await fetch("/api/wfm/skills/save", {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify({ filename, content }),
+        });
+        const data = await res.json();
+        return data.status === "ok" ? data.file : null;
+    } catch { return null; }
+}
+
+async function skillDeleteFile(filename) {
+    try {
+        await fetch("/api/wfm/skills/delete", {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify({ filename }),
+        });
+    } catch { /* ignore */ }
+}
+
+// system prompt として送る前に frontmatter (---...---) を取り除く
+function _stripSkillFrontmatter(content) {
+    const m = content.match(/^---\r?\n[\s\S]*?\r?\n---\r?\n?/);
+    return (m ? content.slice(m[0].length) : content).trim();
+}
+
+let skillFiles = [];
+let skillEditingFilename = null; // null = new file
+let _activeSkillCache = null; // { filename, content } キャッシュ（送信毎の再フェッチを避ける）
+
+function skillRenderList() {
+    const list = document.getElementById("wfm-ai-skill-list");
+    if (!list) return;
+    list.innerHTML = "";
+
+    if (skillFiles.length === 0) {
+        list.innerHTML = `<div class="wfm-pm-empty" style="font-size:12px;">${t("aiSkillNoFiles")}</div>`;
+        return;
+    }
+
+    for (const f of skillFiles) {
+        const item = document.createElement("div");
+        item.className = "wfm-wc-file-item";
+        item.innerHTML = `
+            <div class="wfm-wc-file-item-info">
+                <span class="wfm-wc-file-name" title="${escapeHtml(f.description || "")}">${escapeHtml(f.name)}</span>
+                <span class="wfm-wc-file-ext">.md</span>
+            </div>
+            <div class="wfm-wc-file-item-actions">
+                <button class="wfm-pm-action-btn wfm-ai-skill-edit-btn" title="Edit">&#9998;</button>
+            </div>
+        `;
+        item.querySelector(".wfm-ai-skill-edit-btn").addEventListener("click", async (e) => {
+            e.stopPropagation();
+            const content = await skillFetchContent(f.filename);
+            skillOpenEditor(f.filename, content ?? "");
+        });
+        list.appendChild(item);
+    }
+}
+
+function skillOpenEditor(filename, content) {
+    skillEditingFilename = filename || null;
+
+    const editor = document.getElementById("wfm-ai-skill-editor");
+    const nameInput = document.getElementById("wfm-ai-skill-editor-filename");
+    const contentTA = document.getElementById("wfm-ai-skill-editor-content");
+    const deleteBtn = document.getElementById("wfm-ai-skill-editor-delete-btn");
+
+    if (!editor) return;
+    nameInput.value = filename || "";
+    contentTA.value = content || "";
+    deleteBtn.style.display = filename ? "" : "none";
+    editor.style.display = "";
+    nameInput.focus();
+}
+
+function skillCloseEditor() {
+    skillEditingFilename = null;
+    const editor = document.getElementById("wfm-ai-skill-editor");
+    if (editor) editor.style.display = "none";
+}
+
+function skillPopulateSelect() {
+    const sel = document.getElementById("wfm-ai-chat-skill-select");
+    if (!sel) return;
+    const settings = loadAiSettings();
+    const wanted = sel.value || settings.activeSkillFilename || "";
+
+    sel.innerHTML = `<option value="">-- ${t("aiSkillNone")} --</option>` +
+        skillFiles.map((f) => `<option value="${escapeHtml(f.filename)}" title="${escapeHtml(f.description || "")}">${escapeHtml(f.name)}</option>`).join("");
+
+    sel.value = skillFiles.some((f) => f.filename === wanted) ? wanted : "";
+    _activeSkillCache = null;
+}
+
+async function skillRefreshFiles() {
+    skillFiles = await skillFetchFiles();
+    skillRenderList();
+    skillPopulateSelect();
+}
+
+// 選択中スキルの本文を取得（system prompt注入用、選択が変わるまでキャッシュ）
+async function _getActiveSkillSystemPrompt() {
+    const sel = document.getElementById("wfm-ai-chat-skill-select");
+    const filename = sel?.value || "";
+    if (!filename) return null;
+    if (_activeSkillCache?.filename === filename) return _activeSkillCache.content;
+    const raw = await skillFetchContent(filename);
+    const content = _stripSkillFrontmatter(raw || "");
+    _activeSkillCache = { filename, content };
+    return content;
+}
+
+function initSkillManager() {
+    const selectEl = document.getElementById("wfm-ai-chat-skill-select");
+    const manageBtn = document.getElementById("wfm-ai-chat-skill-manage-btn");
+    const panel = document.getElementById("wfm-ai-skill-panel");
+    const closeBtn = document.getElementById("wfm-ai-skill-close-btn");
+    const newBtn = document.getElementById("wfm-ai-skill-new-btn");
+    const saveBtn = document.getElementById("wfm-ai-skill-editor-save-btn");
+    const deleteBtn = document.getElementById("wfm-ai-skill-editor-delete-btn");
+    const cancelBtn = document.getElementById("wfm-ai-skill-editor-cancel-btn");
+
+    if (!selectEl) return;
+
+    skillRefreshFiles();
+
+    selectEl.addEventListener("change", () => {
+        saveAiSettings({ activeSkillFilename: selectEl.value });
+        _activeSkillCache = null;
+    });
+
+    manageBtn?.addEventListener("click", () => {
+        if (!panel) return;
+        const show = panel.style.display === "none";
+        panel.style.display = show ? "" : "none";
+        if (show) skillRefreshFiles();
+    });
+
+    closeBtn?.addEventListener("click", () => {
+        if (panel) panel.style.display = "none";
+    });
+
+    newBtn?.addEventListener("click", () => {
+        skillOpenEditor(null, "---\nname: \ndescription: \n---\n\n");
+    });
+
+    saveBtn?.addEventListener("click", async () => {
+        const nameInput = document.getElementById("wfm-ai-skill-editor-filename");
+        const contentTA = document.getElementById("wfm-ai-skill-editor-content");
+        let filename = (nameInput?.value || "").trim();
+        const content = contentTA?.value || "";
+
+        if (!filename) { showToast(t("pleaseEnterFilename"), "error"); return; }
+        if (!/\.md$/i.test(filename)) filename += ".md";
+        if (!/^[\w\-. ]+\.md$/i.test(filename)) { showToast(t("invalidPathFormat"), "error"); return; }
+
+        const saved = await skillSaveFile(filename, content);
+        if (saved) {
+            showToast(t("savedAs", filename), "success");
+            skillCloseEditor();
+            await skillRefreshFiles();
+            selectEl.value = filename;
+            saveAiSettings({ activeSkillFilename: filename });
+            _activeSkillCache = null;
+        } else {
+            showToast(t("saveFailed"), "error");
+        }
+    });
+
+    deleteBtn?.addEventListener("click", async () => {
+        if (!skillEditingFilename) return;
+        if (!confirm(`Delete "${skillEditingFilename}"?`)) return;
+        await skillDeleteFile(skillEditingFilename);
+        showToast(t("deletedName", skillEditingFilename), "success");
+        if (selectEl.value === skillEditingFilename) {
+            saveAiSettings({ activeSkillFilename: "" });
+            _activeSkillCache = null;
+        }
+        skillCloseEditor();
+        await skillRefreshFiles();
+    });
+
+    cancelBtn?.addEventListener("click", () => skillCloseEditor());
 }

 function appendChatBubble(messagesEl, role, content, opts = {}) {
@@ -545,12 +1002,26 @@ function appendChatBubble(messagesEl, role, content, opts = {}) {
        img.className = "wfm-ai-chat-img";
        div.appendChild(img);
    }
+    if (opts.imageUrls?.length) {
+        opts.imageUrls.forEach((url) => {
+            const img = document.createElement("img");
+            img.src = url;
+            img.className = "wfm-ai-chat-img";
+            div.appendChild(img);
+        });
+    }
    if (opts.attachThumb) {
        const img = document.createElement("img");
        img.src = opts.attachThumb;
        img.className = "wfm-ai-chat-attach-thumb";
        div.appendChild(img);
    }
+    if (role === "assistant" && content) {
+        const svgCode = _extractSvgCode(content);
+        if (svgCode) _appendSvgPreview(div, svgCode);
+        const skillBlock = _extractSkillBlock(content);
+        if (skillBlock) _appendSkillSaveButton(div, skillBlock);
+    }
    messagesEl.appendChild(div);
    messagesEl.scrollTop = messagesEl.scrollHeight;
    return div;
@@ -578,6 +1049,8 @@ function initChatTab() {
        _clearToolsImage();
    });

+    initSkillManager();
+
    let chatHistory = [];

    async function sendMessage() {
@@ -586,7 +1059,7 @@ function initChatTab() {

        const settings = loadAiSettings();
        const { backend = "ollama", backendUrl, model } = settings;
-        const url = backendUrl || (backend === "ollama" ? "http://localhost:11434" : "http://localhost:1234");
+        const url = backendUrl || getAiBackendDefaultUrl(backend);

        if (!isValidBackendUrl(url)) {
            showToast(t("aiToastInvalidUrl"), "error");
@@ -610,7 +1083,11 @@ function initChatTab() {

        try {
            const tools = imgGenToggle?.checked !== false ? IMAGE_GEN_TOOLS : undefined;
-            const reply = await callChat(url, backend, model, chatHistory, tools);
+            const skillPrompt = await _getActiveSkillSystemPrompt();
+            const messagesToSend = skillPrompt
+                ? [{ role: "system", content: skillPrompt }, ...chatHistory]
+                : chatHistory;
+            const reply = await callChat(url, backend, model, messagesToSend, tools, settings);
            const toolCall = reply.toolCalls?.find(
                (tc) => (tc.function?.name || tc.name) === "generate_image"
            );
@@ -622,8 +1099,8 @@ function initChatTab() {
                statusEl.textContent = t("aiStatusGeneratingImage");
                const args = _parseToolArgs(toolCall);
                try {
-                    const imageUrl = await generateImageFromChat(args.prompt, args.negative_prompt);
-                    appendChatBubble(messagesEl, "assistant", "", { imageUrl });
+                    const imageUrls = await generateImageFromChat(args.prompt, args.negative_prompt, args);
+                    appendChatBubble(messagesEl, "assistant", "", { imageUrls });
                } catch (genErr) {
                    appendChatBubble(messagesEl, "assistant", `${t("aiToastImageGenFailed")}${genErr.message}`);
                    showToast(t("aiToastImageGenFailed") + genErr.message, "error");
@@ -752,7 +1229,7 @@ function initVlmTab() {
        const task = taskSel?.value || "describe";
        const settings = loadAiSettings();
        const { backend = "ollama", backendUrl, model } = settings;
-        const url = backendUrl || (backend === "ollama" ? "http://localhost:11434" : "http://localhost:1234");
+        const url = backendUrl || getAiBackendDefaultUrl(backend);

        if (!isValidBackendUrl(url)) { showToast(t("aiToastInvalidUrl"), "error"); return; }
        if (!model) { showToast(t("aiToastNoModel"), "error"); return; }
@@ -770,7 +1247,7 @@ function initVlmTab() {
            const prompt = `Generate ${count} wildcard entries for the category "${name}". Output only plain text in English, one entry per line, no numbers, no markdown, no asterisks, no bold, nothing else.`;

            try {
-                const result = await callLLM(url, backend, model, prompt);
+                const result = await callLLM(url, backend, model, prompt, settings);
                resultEl.value = result.trim()
                    .split("\n")
                    .map(l => l.replace(/\*\*/g, "").replace(/^\*\s*/, "").replace(/^\d+\.\s*/, "").trim())
@@ -796,7 +1273,7 @@ function initVlmTab() {
        resultEl.value = "";

        try {
-            const result = await callVLM(url, backend, model, VLM_PROMPTS[task], _toolsImage.base64, _toolsImage.mimeType);
+            const result = await callVLM(url, backend, model, VLM_PROMPTS[task], _toolsImage.base64, _toolsImage.mimeType, settings);
            resultEl.value = result.trim();
            statusEl.textContent = t("aiStatusDone");
            statusEl.className = "wfm-ai-trans-status wfm-ai-status-ok";
@@ -826,3 +1303,7 @@ export function initAiTab() {
    initVlmTab();
    initSettingsTab();
 }
+
+// gallery-tab.js の外部（Comic Creator）向けブリッジ（半自動マンガ作成の画像プロンプト
+// 下書き機能）が、設定タブと同じAI接続設定・LLM呼び出しロジックを再利用するためのexport。
+export { callLLM, loadAiSettings, isValidBackendUrl };
@@ -42,11 +42,32 @@ export function showToast(message, type = "info", duration = 3000) {

 export function openModal(title, contentHtml) {
    const overlay = document.getElementById("wfm-modal-overlay");
-    const titleEl = document.getElementById("wfm-modal-title");
+    let titleEl = document.getElementById("wfm-modal-title");
    const bodyEl = document.getElementById("wfm-modal-body");
+    const titleInput = document.getElementById("wfm-modal-title-input");

    if (!overlay || !titleEl || !bodyEl) return;

+    // This modal shell is shared by every caller (Workflow/Models/Nodes detail
+    // modals, Lab's keyframe editor, etc.). Some callers (e.g. workflow-tab.js's
+    // openDetailModal) inject extra header chrome after calling openModal() — a
+    // favorite star button, and a click-to-rename listener + tooltip/cursor on the
+    // title — but nothing ever tore that down again. The next caller to reuse this
+    // same DOM inherited it as stale leftovers: a Lab cell modal could show a
+    // favorite star wired to the PREVIOUS caller's workflow object, and clicking it
+    // silently toggled that unrelated workflow's favorite state. Clean slate every
+    // time, before any caller-specific chrome is added back on top.
+    titleEl.parentElement?.querySelectorAll(".wfm-fav-btn").forEach((el) => el.remove());
+    const freshTitleEl = titleEl.cloneNode(false); // drops any addEventListener from a prior caller
+    freshTitleEl.removeAttribute("title");
+    freshTitleEl.removeAttribute("style"); // also clears any leftover display:none from an interrupted rename
+    titleEl.replaceWith(freshTitleEl);
+    titleEl = freshTitleEl;
+    if (titleInput) {
+        titleInput.style.display = "none";
+        titleInput.value = "";
+    }
+
    titleEl.textContent = title;
    bodyEl.innerHTML = contentHtml;
    overlay.style.display = "flex";
@@ -91,7 +112,7 @@ function initTabs() {

 function applyI18nToHtml() {
    // Tab labels
-    const tabMap = { workflow: "tabWorkflow", nodes: "tabNodes", models: "tabModels", generate: "tabGenerate", prompt: "tabPrompt", metadata: "tabMetadata", gallery: "tabGallery", "image-edit": "tabImageEdit", settings: "tabSettings", help: "tabHelp", ai: "tabAi", tagger: "tabTagger" };
+    const tabMap = { workflow: "tabWorkflow", nodes: "tabNodes", models: "tabModels", generate: "tabGenerate", prompt: "tabPrompt", gallery: "tabGallery", "image-edit": "tabImageEdit", video: "tabVideo", settings: "tabSettings", help: "tabHelp", ai: "tabAi", tagger: "tabTagger" };
    document.querySelectorAll(".wfm-tab").forEach((tab) => {
        const key = tabMap[tab.dataset.tab];
        if (key) tab.textContent = t(key);
@@ -113,6 +134,12 @@ function applyI18nToHtml() {
        if (listLoadBtn.disabled) listLoadBtn.title = t("selectCardFirst");
    }

+    const listLoadVideoBtn = document.getElementById("wfm-list-load-video-btn");
+    if (listLoadVideoBtn) {
+        listLoadVideoBtn.textContent = t("loadInVideo");
+        if (listLoadVideoBtn.disabled) listLoadVideoBtn.title = t("selectCardFirst");
+    }
+
    const listOpenComfyBtn = document.getElementById("wfm-list-open-comfyui-btn");
    if (listOpenComfyBtn) {
        listOpenComfyBtn.textContent = t("sendToCanvas");
@@ -195,6 +222,7 @@ function applyI18nToHtml() {
        if (btn.dataset.detailTab === "info") btn.textContent = t("modelsSideInfo");
        if (btn.dataset.detailTab === "meta") btn.textContent = t("gallerySideMetadata");
        if (btn.dataset.detailTab === "group") btn.textContent = t("modelsSideGroup");
+        if (btn.dataset.detailTab === "prompt") btn.textContent = t("gallerySidePrompt");
    });
    const galleryBulkDeselect = document.getElementById("wfm-gallery-bulk-deselect");
    if (galleryBulkDeselect) galleryBulkDeselect.textContent = t("galleryBulkDeselectAll");
@@ -217,20 +245,86 @@ function applyI18nToHtml() {
    if (galleryBulkMove) galleryBulkMove.textContent = t("galleryBulkMoveTo");
    const galleryBulkExport = document.getElementById("wfm-gallery-bulk-export");
    if (galleryBulkExport) galleryBulkExport.textContent = t("galleryBulkExport");
+    const galleryBulkPsd = document.getElementById("wfm-gallery-bulk-psd");
+    if (galleryBulkPsd) galleryBulkPsd.textContent = t("galleryBulkPsd");
+    const galleryBulkEditLayers = document.getElementById("wfm-gallery-bulk-edit-layers");
+    if (galleryBulkEditLayers) galleryBulkEditLayers.textContent = t("galleryBulkEditLayers");
    const galleryBulkDelete = document.getElementById("wfm-gallery-bulk-delete");
    if (galleryBulkDelete) galleryBulkDelete.textContent = t("galleryBulkDelete");
    const galleryOpenTaggerBtn = document.getElementById("wfm-gallery-open-tagger-btn");
    if (galleryOpenTaggerBtn) galleryOpenTaggerBtn.textContent = t("tabTagger");

+    // Gallery サブタブ (Output / ImagePrompt / Style_Catalog)
+    const galleryOutputSubtab = document.getElementById("wfm-gallery-subtab-output");
+    if (galleryOutputSubtab) galleryOutputSubtab.textContent = t("galleryTabOutput");
+    const galleryImagePromptSubtab = document.getElementById("wfm-gallery-subtab-imageprompt");
+    if (galleryImagePromptSubtab) galleryImagePromptSubtab.textContent = t("galleryTabImagePrompt");
+    const galleryStyleCatalogSubtab = document.getElementById("wfm-gallery-subtab-styleCatalog");
+    if (galleryStyleCatalogSubtab) galleryStyleCatalogSubtab.textContent = t("galleryTabStyleCatalog");
+    const galleryMetadataSubtab = document.getElementById("wfm-gallery-subtab-metadata");
+    if (galleryMetadataSubtab) galleryMetadataSubtab.textContent = t("galleryTabMetadata");
+
+    // ImagePrompt ギャラリーパネル
+    const imagePromptSearch = document.getElementById("wfm-imageprompt-search");
+    if (imagePromptSearch) imagePromptSearch.placeholder = t("gallerySearchPlaceholder");
+    const imagePromptRefreshBtn = document.getElementById("wfm-imageprompt-refresh-btn");
+    if (imagePromptRefreshBtn) imagePromptRefreshBtn.textContent = t("refresh");
+    const imagePromptTreeTitle = document.getElementById("wfm-imageprompt-tree-title");
+    if (imagePromptTreeTitle) imagePromptTreeTitle.textContent = t("galleryFolders");
+    const imagePromptListPlaceholder = document.getElementById("wfm-imageprompt-list-placeholder");
+    if (imagePromptListPlaceholder) imagePromptListPlaceholder.textContent = t("gallerySelectFolder");
+    const imagePromptNoSelection = document.getElementById("wfm-imageprompt-no-selection");
+    if (imagePromptNoSelection) imagePromptNoSelection.textContent = t("galleryNoSelection");
+    const imagePromptSelectedPromptTitle = document.getElementById("wfm-imageprompt-selected-prompt-title");
+    if (imagePromptSelectedPromptTitle) imagePromptSelectedPromptTitle.textContent = t("imagePromptSelectedPrompt");
+    const imagePromptSelectedPrompt = document.getElementById("wfm-imageprompt-selected-prompt");
+    if (imagePromptSelectedPrompt) imagePromptSelectedPrompt.placeholder = t("imagePromptNoPrompt");
+    const imagePromptSavePromptBtn = document.getElementById("wfm-imageprompt-save-prompt-btn");
+    if (imagePromptSavePromptBtn) imagePromptSavePromptBtn.textContent = t("save");
+    const imagePromptAddBtn = document.getElementById("wfm-imageprompt-add-btn");
+    if (imagePromptAddBtn) imagePromptAddBtn.textContent = t("imagePromptAddBtn");
+    const imagePromptChipsTitle = document.getElementById("wfm-imageprompt-chips-title");
+    if (imagePromptChipsTitle) imagePromptChipsTitle.textContent = t("imagePromptChipsTitle");
+    const imagePromptClearBtn = document.getElementById("wfm-imageprompt-clear-btn");
+    if (imagePromptClearBtn) imagePromptClearBtn.textContent = t("imagePromptClearBtn");
+    const imagePromptFinalPromptTitle = document.getElementById("wfm-imageprompt-final-prompt-title");
+    if (imagePromptFinalPromptTitle) imagePromptFinalPromptTitle.textContent = t("imagePromptFinalPromptTitle");
+    const imagePromptCopyBtn = document.getElementById("wfm-imageprompt-copy-btn");
+    if (imagePromptCopyBtn) imagePromptCopyBtn.textContent = t("copy");
+
+    // Style_Catalog ギャラリーパネル
+    const scSearch = document.getElementById("wfm-stylecatalog-search");
+    if (scSearch) scSearch.placeholder = t("stylecatalogSearchPlaceholder");
+    const scRefreshBtn = document.getElementById("wfm-stylecatalog-refresh-btn");
+    if (scRefreshBtn) scRefreshBtn.textContent = t("refresh");
+    const scTreeTitle = document.getElementById("wfm-stylecatalog-tree-title");
+    if (scTreeTitle) scTreeTitle.textContent = t("galleryFolders");
+    const scListPlaceholder = document.getElementById("wfm-stylecatalog-list-placeholder");
+    if (scListPlaceholder) scListPlaceholder.textContent = t("gallerySelectFolder");
+    const scNoSelection = document.getElementById("wfm-stylecatalog-no-selection");
+    if (scNoSelection) scNoSelection.textContent = t("galleryNoSelection");
+    const scPositiveTitle = document.getElementById("wfm-stylecatalog-positive-title");
+    if (scPositiveTitle) scPositiveTitle.textContent = t("stylecatalogPositive");
+    const scCopyPositiveBtn = document.getElementById("wfm-stylecatalog-copy-positive-btn");
+    if (scCopyPositiveBtn) scCopyPositiveBtn.textContent = t("copy");
+    const scNegativeTitle = document.getElementById("wfm-stylecatalog-negative-title");
+    if (scNegativeTitle) scNegativeTitle.textContent = t("stylecatalogNegative");
+    const scCopyNegativeBtn = document.getElementById("wfm-stylecatalog-copy-negative-btn");
+    if (scCopyNegativeBtn) scCopyNegativeBtn.textContent = t("copy");
+    const scSelectStyleBtn = document.getElementById("wfm-stylecatalog-select-style-btn");
+    if (scSelectStyleBtn) scSelectStyleBtn.textContent = t("stylecatalogSelectStyleBtn");
+    const scLoadGenuiBtn = document.getElementById("wfm-stylecatalog-load-genui-btn");
+    if (scLoadGenuiBtn) scLoadGenuiBtn.textContent = t("stylecatalogLoadGenuiBtn");
+    const scOpenMetadataBtn = document.getElementById("wfm-stylecatalog-open-metadata-btn");
+    if (scOpenMetadataBtn) scOpenMetadataBtn.textContent = t("stylecatalogOpenMetadataBtn");
+
    // Prompt tab
    const assistantHeader = document.querySelector(".wfm-prompt-split-left .wfm-prompt-split-header");
    if (assistantHeader) assistantHeader.textContent = t("assistantSubtab");
    const presetsHeader = document.querySelector(".wfm-prompt-split-right .wfm-prompt-split-header");
    if (presetsHeader) presetsHeader.textContent = t("presetsSubtab");
-    const ollamaRefreshBtn = document.getElementById("wfm-ollama-refresh-btn");
-    if (ollamaRefreshBtn) ollamaRefreshBtn.textContent = t("refresh");
-    const ollamaTestBtn = document.getElementById("wfm-ollama-test-btn");
-    if (ollamaTestBtn) ollamaTestBtn.textContent = t("test");
+    const ollamaSettingsBtn = document.getElementById("wfm-ollama-settings-btn");
+    if (ollamaSettingsBtn) ollamaSettingsBtn.title = t("settings");
    const ollamaAttachBtn = document.getElementById("wfm-ollama-attach-btn");
    if (ollamaAttachBtn) ollamaAttachBtn.textContent = t("attachImage");
    const ollamaClearBtn = document.getElementById("wfm-ollama-clear-btn");
@@ -302,6 +396,14 @@ function applyI18nToHtml() {
    }
    const aiModelRefreshBtn = document.getElementById("wfm-ai-model-refresh-btn");
    if (aiModelRefreshBtn) aiModelRefreshBtn.textContent = t("aiSettingsRefreshBtn");
+    const aiGenerationTitle = document.getElementById("wfm-ai-settings-generation-title");
+    if (aiGenerationTitle) aiGenerationTitle.textContent = t("aiSettingsGenerationTitle");
+    const aiThinkingModeLabel = document.getElementById("wfm-ai-thinking-mode-label");
+    if (aiThinkingModeLabel) aiThinkingModeLabel.textContent = t("aiSettingsThinkingMode");
+    const aiMaxTokensLabel = document.getElementById("wfm-ai-max-tokens-label");
+    if (aiMaxTokensLabel) aiMaxTokensLabel.textContent = t("aiSettingsMaxTokens");
+    const aiMaxTokensInput = document.getElementById("wfm-ai-max-tokens");
+    if (aiMaxTokensInput) aiMaxTokensInput.placeholder = t("aiSettingsMaxTokensPlaceholder");
    const aiFreeLangTitle = document.getElementById("wfm-ai-settings-freelang-title");
    if (aiFreeLangTitle) aiFreeLangTitle.textContent = t("aiSettingsFreeLang");
    const aiFreeSrcLabel = document.getElementById("wfm-ai-free-src-label");
@@ -320,6 +422,19 @@ function applyI18nToHtml() {
    if (aiChatGenI2ITitle) aiChatGenI2ITitle.textContent = t("aiSettingsChatI2IGenTitle");
    const aiChatGenI2IDedicatedLabel = document.getElementById("wfm-ai-chatgen-i2i-dedicated-label");
    if (aiChatGenI2IDedicatedLabel) aiChatGenI2IDedicatedLabel.textContent = t("aiSettingsChatGenDedicated");
+    const aiSkillSel = document.getElementById("wfm-ai-chat-skill-select");
+    if (aiSkillSel) {
+        const firstOpt = aiSkillSel.querySelector("option[value='']");
+        if (firstOpt) firstOpt.textContent = `-- ${t("aiSkillNone")} --`;
+    }
+    const aiSkillManageBtn = document.getElementById("wfm-ai-chat-skill-manage-btn");
+    if (aiSkillManageBtn) aiSkillManageBtn.title = t("aiSkillManageBtnTitle");
+    const aiSkillPanelTitle = document.querySelector(".wfm-ai-skill-panel-title");
+    if (aiSkillPanelTitle) aiSkillPanelTitle.textContent = t("aiSkillPanelTitle");
+    const aiSkillNewBtn = document.getElementById("wfm-ai-skill-new-btn");
+    if (aiSkillNewBtn) aiSkillNewBtn.textContent = t("aiSkillNewBtn");
+    const aiSkillContentTA = document.getElementById("wfm-ai-skill-editor-content");
+    if (aiSkillContentTA) aiSkillContentTA.placeholder = t("aiSkillContentPlaceholder");

    // Group panel labels
    const propTitle = document.querySelector("#wfm-side-tab-group .wfm-group-section-title");
@@ -367,6 +482,14 @@ function applyI18nToHtml() {
        "wfm-help-gen-15": "helpGen15", "wfm-help-gen-16": "helpGen16",
        "wfm-help-gen-17": "helpGen17", "wfm-help-gen-18": "helpGen18",
        "wfm-help-gen-19": "helpGen19",
+        "wfm-help-gen-20": "helpGen20", "wfm-help-gen-21": "helpGen21",
+        "wfm-help-gen-22": "helpGen22", "wfm-help-gen-23": "helpGen23",
+        "wfm-help-gen-24": "helpGen24", "wfm-help-gen-25": "helpGen25",
+        "wfm-help-gen-26": "helpGen26", "wfm-help-gen-27": "helpGen27",
+        "wfm-help-gen-28": "helpGen28",
+        "wfm-help-gen-29": "helpGen29",
+        "wfm-help-gen-30": "helpGen30",
+        "wfm-help-gen-31": "helpGen31",
        "wfm-help-feeder-title": "helpFeederTitle",
        "wfm-help-feeder-desc": "helpFeederDesc",
        "wfm-help-feeder-imgloop-title": "helpFeederImgloopTitle",
@@ -381,18 +504,55 @@ function applyI18nToHtml() {
        "wfm-help-feeder-gal-1": "helpFeederGal1", "wfm-help-feeder-gal-2": "helpFeederGal2",
        "wfm-help-feeder-gal-3": "helpFeederGal3", "wfm-help-feeder-gal-4": "helpFeederGal4",
        "wfm-help-feeder-gal-5": "helpFeederGal5", "wfm-help-feeder-gal-6": "helpFeederGal6",
+        "wfm-help-lab-title": "helpLabTitle",
+        "wfm-help-lab-desc": "helpLabDesc",
+        "wfm-help-lab-card-columns-title": "helpLabCardColumnsTitle",
+        "wfm-help-lab-1": "helpLab1", "wfm-help-lab-2": "helpLab2",
+        "wfm-help-lab-3": "helpLab3", "wfm-help-lab-4": "helpLab4",
+        "wfm-help-lab-5": "helpLab5", "wfm-help-lab-6": "helpLab6",
+        "wfm-help-lab-7": "helpLab7", "wfm-help-lab-8": "helpLab8",
+        "wfm-help-lab-9": "helpLab9", "wfm-help-lab-10": "helpLab10",
+        "wfm-help-lab-11": "helpLab11", "wfm-help-lab-12": "helpLab12",
+        "wfm-help-lab-13": "helpLab13", "wfm-help-lab-14": "helpLab14",
+        "wfm-help-lab-15": "helpLab15",
+        "wfm-help-lab-16": "helpLab16", "wfm-help-lab-17": "helpLab17",
+        "wfm-help-lab-18": "helpLab18", "wfm-help-lab-19": "helpLab19",
+        "wfm-help-lab-card-plan-title": "helpLabCardPlanTitle",
+        "wfm-help-lab-plan-1": "helpLabPlan1", "wfm-help-lab-plan-2": "helpLabPlan2",
+        "wfm-help-lab-plan-3": "helpLabPlan3", "wfm-help-lab-plan-4": "helpLabPlan4",
+        "wfm-help-lab-plan-5": "helpLabPlan5", "wfm-help-lab-plan-6": "helpLabPlan6",
+        "wfm-help-lab-plan-7": "helpLabPlan7", "wfm-help-lab-plan-8": "helpLabPlan8",
+        "wfm-help-lab-plan-9": "helpLabPlan9", "wfm-help-lab-plan-10": "helpLabPlan10",
+        "wfm-help-lab-plan-11": "helpLabPlan11",
+        "wfm-help-lab-card-results-title": "helpLabCardResultsTitle",
+        "wfm-help-lab-results-1": "helpLabResults1", "wfm-help-lab-results-2": "helpLabResults2",
+        "wfm-help-lab-results-3": "helpLabResults3",
        "wfm-help-prompt-1": "helpPrompt1", "wfm-help-prompt-2": "helpPrompt2",
        "wfm-help-prompt-3": "helpPrompt3", "wfm-help-prompt-4": "helpPrompt4",
        "wfm-help-prompt-5": "helpPrompt5", "wfm-help-prompt-6": "helpPrompt6",
        "wfm-help-prompt-7": "helpPrompt7", "wfm-help-prompt-8": "helpPrompt8",
        "wfm-help-prompt-9": "helpPrompt9",
+        "wfm-help-prompt-card-style-title": "helpPromptCardStyleTitle",
+        "wfm-help-prompt-10": "helpPrompt10", "wfm-help-prompt-11": "helpPrompt11",
+        "wfm-help-prompt-12": "helpPrompt12", "wfm-help-prompt-13": "helpPrompt13",
+        "wfm-help-prompt-14": "helpPrompt14",
+        "wfm-help-prompt-card-toplevel-title": "helpPromptCardToplevel",
+        "wfm-help-prompt-15": "helpPrompt15",
+        "wfm-help-prompt-card-table-title": "helpPromptCardTable",
+        "wfm-help-prompt-16": "helpPrompt16", "wfm-help-prompt-17": "helpPrompt17",
+        "wfm-help-prompt-18": "helpPrompt18", "wfm-help-prompt-19": "helpPrompt19",
+        "wfm-help-prompt-20": "helpPrompt20", "wfm-help-prompt-21": "helpPrompt21",
+        "wfm-help-prompt-22": "helpPrompt22", "wfm-help-prompt-23": "helpPrompt23",
+        "wfm-help-prompt-24": "helpPrompt24", "wfm-help-prompt-25": "helpPrompt25",
+        "wfm-help-prompt-26": "helpPrompt26",
        "wfm-help-settings-1": "helpSettings1", "wfm-help-settings-2": "helpSettings2",
        "wfm-help-settings-3": "helpSettings3", "wfm-help-settings-4": "helpSettings4",
        "wfm-help-settings-5": "helpSettings5", "wfm-help-settings-6": "helpSettings6",
        "wfm-help-settings-7": "helpSettings7", "wfm-help-settings-8": "helpSettings8",
        "wfm-help-settings-9": "helpSettings9", "wfm-help-settings-10": "helpSettings10",
        "wfm-help-settings-11": "helpSettings11", "wfm-help-settings-12": "helpSettings12",
-        "wfm-help-settings-13": "helpSettings13",
+        "wfm-help-settings-13": "helpSettings13", "wfm-help-settings-14": "helpSettings14",
+        "wfm-help-settings-15": "helpSettings15", "wfm-help-settings-16": "helpSettings16",
        "wfm-help-nodes-1": "helpNodes1", "wfm-help-nodes-2": "helpNodes2",
        "wfm-help-nodes-3": "helpNodes3", "wfm-help-nodes-4": "helpNodes4",
        "wfm-help-nodes-5": "helpNodes5", "wfm-help-nodes-6": "helpNodes6",
@@ -412,7 +572,16 @@ function applyI18nToHtml() {
        "wfm-help-gallery-11": "helpGallery11", "wfm-help-gallery-12": "helpGallery12",
        "wfm-help-gallery-13": "helpGallery13", "wfm-help-gallery-14": "helpGallery14",
        "wfm-help-gallery-15": "helpGallery15", "wfm-help-gallery-16": "helpGallery16",
-        "wfm-help-gallery-17": "helpGallery17",
+        "wfm-help-gallery-17": "helpGallery17", "wfm-help-gallery-27": "helpGallery27",
+        "wfm-help-gallery-18": "helpGallery18", "wfm-help-gallery-19": "helpGallery19",
+        "wfm-help-gallery-20": "helpGallery20", "wfm-help-gallery-21": "helpGallery21",
+        "wfm-help-gallery-22": "helpGallery22", "wfm-help-gallery-23": "helpGallery23",
+        "wfm-help-gallery-24": "helpGallery24", "wfm-help-gallery-25": "helpGallery25",
+        "wfm-help-gallery-26": "helpGallery26",
+        "wfm-help-gallery-28": "helpGallery28", "wfm-help-gallery-29": "helpGallery29",
+        "wfm-help-gallery-30": "helpGallery30",
+        "wfm-help-gallery-card-styleprompt-title": "helpGalleryCardStyleprompt",
+        "wfm-help-gallery-card-stylecatalog-title": "helpGalleryCardStylecatalog",
        "wfm-help-tagger-title": "helpTaggerTitle",
        "wfm-help-tagger-1": "helpTagger1", "wfm-help-tagger-2": "helpTagger2",
        "wfm-help-tagger-3": "helpTagger3", "wfm-help-tagger-4": "helpTagger4",
@@ -432,7 +601,18 @@ function applyI18nToHtml() {
        "wfm-help-sidepanel-17": "helpSidepanel17",
        "wfm-help-ai-title": "helpAiTitle",
        "wfm-help-ai-1": "helpAi1", "wfm-help-ai-2": "helpAi2", "wfm-help-ai-3": "helpAi3",
-        "wfm-help-ai-4": "helpAi4", "wfm-help-ai-5": "helpAi5", "wfm-help-ai-6": "helpAi6",
+        "wfm-help-ai-4": "helpAi4", "wfm-help-ai-6": "helpAi6",
+        "wfm-help-ai-7": "helpAi7",
+        "wfm-help-ai-8": "helpAi8",
+        "wfm-help-ai-9": "helpAi9",
+        "wfm-help-ai-card-layout-title": "helpAiCardLayout",
+        "wfm-help-ai-card-translate-title": "helpAiCardTranslate",
+        "wfm-help-ai-card-chat-title": "helpAiCardChat",
+        "wfm-help-ai-card-svg-title": "helpAiCardSvg",
+        "wfm-help-ai-card-skills-title": "helpAiCardSkills",
+        "wfm-help-ai-card-skilltips-title": "helpAiCardSkillTips",
+        "wfm-help-ai-card-tools-title": "helpAiCardTools",
+        "wfm-help-ai-card-settings-title": "helpAiCardSettings",
        "wfm-help-imageedit-title": "helpImageEditTitle",
        "wfm-help-imageedit-tools-title": "helpImageEditToolsTitle",
        "wfm-help-imageedit-layer-title": "helpImageEditLayerTitle",
@@ -447,13 +627,16 @@ function applyI18nToHtml() {
        "wfm-help-imageedit-12": "helpImageEdit12", "wfm-help-imageedit-13": "helpImageEdit13",
        "wfm-help-imageedit-14": "helpImageEdit14", "wfm-help-imageedit-15": "helpImageEdit15",
        "wfm-help-imageedit-16": "helpImageEdit16", "wfm-help-imageedit-17": "helpImageEdit17",
-        "wfm-help-imageedit-18": "helpImageEdit18", "wfm-help-imageedit-19": "helpImageEdit19",
+        "wfm-help-imageedit-18": "helpImageEdit18",
+        "wfm-help-imageedit-19b": "helpImageEdit19b",
        "wfm-help-imageedit-20": "helpImageEdit20", "wfm-help-imageedit-21": "helpImageEdit21",
        "wfm-help-imageedit-22": "helpImageEdit22", "wfm-help-imageedit-23": "helpImageEdit23",
        "wfm-help-imageedit-24": "helpImageEdit24", "wfm-help-imageedit-25": "helpImageEdit25",
        "wfm-help-imageedit-26": "helpImageEdit26", "wfm-help-imageedit-27": "helpImageEdit27",
        "wfm-help-imageedit-28": "helpImageEdit28", "wfm-help-imageedit-29": "helpImageEdit29",
        "wfm-help-imageedit-30": "helpImageEdit30",
+        "wfm-help-imageedit-31": "helpImageEdit31", "wfm-help-imageedit-32": "helpImageEdit32",
+        "wfm-help-imageedit-33": "helpImageEdit33", "wfm-help-imageedit-34": "helpImageEdit34",
        "wfm-help-imageedit-7b": "helpImageEdit7b", "wfm-help-imageedit-7c": "helpImageEdit7c",
        "wfm-help-imageedit-7d": "helpImageEdit7d", "wfm-help-imageedit-7e": "helpImageEdit7e",
        "wfm-help-imageedit-8b": "helpImageEdit8b",
@@ -473,6 +656,7 @@ function applyI18nToHtml() {
        "wfm-help-imageedit-mask-9": "helpImageEditMask9", "wfm-help-imageedit-mask-10": "helpImageEditMask10",
        "wfm-help-imageedit-mask-11": "helpImageEditMask11", "wfm-help-imageedit-mask-12": "helpImageEditMask12",
        "wfm-help-imageedit-mask-13": "helpImageEditMask13",
+        "wfm-help-imageedit-mask-14": "helpImageEditMask14",
        "wfm-help-imageedit-gmic-title": "helpImageEditGmicTitle",
        "wfm-help-imageedit-gmic-1": "helpImageEditGmic1", "wfm-help-imageedit-gmic-2": "helpImageEditGmic2",
        "wfm-help-imageedit-gmic-3": "helpImageEditGmic3", "wfm-help-imageedit-gmic-4": "helpImageEditGmic4",
@@ -493,11 +677,75 @@ function applyI18nToHtml() {
        "wfm-help-trouble-3": "helpTrouble3", "wfm-help-trouble-4": "helpTrouble4",
        "wfm-help-trouble-5": "helpTrouble5", "wfm-help-trouble-6": "helpTrouble6",
        "wfm-help-trouble-7": "helpTrouble7", "wfm-help-trouble-8": "helpTrouble8",
+        "wfm-help-trouble-9": "helpTrouble9",
        "wfm-help-support-title": "helpSupportTitle",
        "wfm-help-support-desc": "helpSupportDesc",
        "wfm-help-github-desc": "helpGithubDesc",
        "wfm-help-kofi-desc": "helpKofiDesc",
        "wfm-help-thanks": "helpThanks",
+        // -- Help card headings (card-based redesign) --
+        "wfm-help-about-card-getting-started-title": "helpAboutCardGettingStarted",
+        "wfm-help-wf-title": "helpWfTitle",
+        "wfm-help-wf-card-browse-title": "helpWfCardBrowse",
+        "wfm-help-wf-card-groups-title": "helpWfCardGroups",
+        "wfm-help-wf-card-panel-title": "helpWfCardPanel",
+        "wfm-help-gen-title": "helpGenTitle",
+        "wfm-help-gen-card-connect-title": "helpGenCardConnect",
+        "wfm-help-gen-card-tabs-title": "helpGenCardTabs",
+        "wfm-help-gen-card-seed-title": "helpGenCardSeed",
+        "wfm-help-gen-card-batchsetup-title": "helpGenCardBatchSetup",
+        "wfm-help-gen-card-batchtypes-title": "helpGenCardBatchTypes",
+        "wfm-help-gen-card-lora-title": "helpGenCardLora",
+        "wfm-help-prompt-title": "helpPromptTitle",
+        "wfm-help-prompt-card-ai-title": "helpPromptCardAi",
+        "wfm-help-prompt-card-presets-title": "helpPromptCardPresets",
+        "wfm-help-prompt-card-wildcards-title": "helpPromptCardWildcards",
+        "wfm-help-metadata-card-overview-title": "helpMetadataCardOverview",
+        "wfm-help-metadata-card-extracted-title": "helpMetadataCardExtracted",
+        "wfm-help-metadata-card-formats-title": "helpMetadataCardFormats",
+        "wfm-help-settings-title": "helpSettingsTitle",
+        "wfm-help-settings-card-general-title": "helpSettingsCardGeneral",
+        "wfm-help-settings-card-connections-title": "helpSettingsCardConnections",
+        "wfm-help-settings-card-workflow-title": "helpSettingsCardWorkflow",
+        "wfm-help-settings-card-editor-title": "helpSettingsCardEditor",
+        "wfm-help-settings-card-misc-title": "helpSettingsCardMisc",
+        "wfm-help-nodes-title": "helpNodesTitle",
+        "wfm-help-nodes-card-browse-title": "helpNodesCardBrowse",
+        "wfm-help-nodes-card-groups-title": "helpNodesCardGroups",
+        "wfm-help-nodes-card-panel-title": "helpNodesCardPanel",
+        "wfm-help-gallery-card-browse-title": "helpGalleryCardBrowse",
+        "wfm-help-gallery-card-folder-title": "helpGalleryCardFolder",
+        "wfm-help-gallery-card-detail-title": "helpGalleryCardDetail",
+        "wfm-help-gallery-card-actions-title": "helpGalleryCardActions",
+        "wfm-help-gallery-card-formats-title": "helpGalleryCardFormats",
+        "wfm-help-models-title": "helpModelsTitle",
+        "wfm-help-models-card-browse-title": "helpModelsCardBrowse",
+        "wfm-help-models-card-civitai-title": "helpModelsCardCivitai",
+        "wfm-help-models-card-apply-title": "helpModelsCardApply",
+        "wfm-help-models-card-groups-title": "helpModelsCardGroups",
+        "wfm-help-models-card-bulk-title": "helpModelsCardBulk",
+        "wfm-help-sidepanel-card-tabs-title": "helpSidepanelCardTabs",
+        "wfm-help-sidepanel-card-dnd-title": "helpSidepanelCardDnd",
+        "wfm-help-sidepanel-card-info-title": "helpSidepanelCardInfo",
+        "wfm-help-sidepanel-card-ai-title": "helpSidepanelCardAi",
+        "wfm-help-sidepanel-card-nav-title": "helpSidepanelCardNav",
+        "wfm-help-tagger-card-overview-title": "helpTaggerCardOverview",
+        "wfm-help-tagger-card-single-title": "helpTaggerCardSingle",
+        "wfm-help-tagger-card-sending-title": "helpTaggerCardSending",
+        "wfm-help-tagger-card-batch-title": "helpTaggerCardBatch",
+        "wfm-help-imageedit-card-overview-title": "helpImageEditCardOverview",
+        "wfm-help-shortcuts-card-general-title": "helpShortcutsCardGeneral",
+        "wfm-help-trouble-card-connection-title": "helpTroubleCardConnection",
+        "wfm-help-trouble-card-workflow-title": "helpTroubleCardWorkflow",
+        "wfm-help-trouble-card-tagger-title": "helpTroubleCardTagger",
+        "wfm-help-video-title": "helpVideoTitle",
+        "wfm-help-video-desc": "helpVideoDesc",
+        "wfm-help-video-1": "helpVideo1", "wfm-help-video-2": "helpVideo2",
+        "wfm-help-video-3": "helpVideo3", "wfm-help-video-4": "helpVideo4",
+        "wfm-help-video-5": "helpVideo5", "wfm-help-video-6": "helpVideo6",
+        "wfm-help-video-7": "helpVideo7", "wfm-help-video-8": "helpVideo8",
+        "wfm-help-video-9": "helpVideo9", "wfm-help-video-10": "helpVideo10",
+        "wfm-help-video-11": "helpVideo11", "wfm-help-video-12": "helpVideo12",
    };
    for (const [id, key] of Object.entries(helpIdMap)) {
        const el = document.getElementById(id);
@@ -510,6 +758,11 @@ function applyI18nToHtml() {
        helpSearch.placeholder = t("helpSearchPlaceholder");
        helpSearch.addEventListener("input", _onHelpSearch);
    }
+
+    // Jump-to-tab buttons
+    document.querySelectorAll(".wfm-help-jump-btn").forEach((btn) => {
+        btn.textContent = t("helpJumpToTab");
+    });
 }

 function _onHelpSearch(e) {
@@ -575,13 +828,15 @@ import { initWorkflowTab } from "./workflow-tab.js";
 import { initNodesTab } from "./nodes-tab.js";
 import { initGenerateTab } from "./generate-tab.js";
 import { initPromptTab } from "./prompt-tab.js";
-import { initSettingsTab, applyTheme, getSavedTheme, applyTextareaFontSize, applyJsonColors } from "./settings-tab.js";
+import { initPromptTableTab } from "./prompt-table.js";
+import { initSettingsTab, applyTheme, getSavedTheme, applyTextareaFontSize, applyJsonColors, applyModelTabActiveColor } from "./settings-tab.js";
 import { initModelsTab } from "./models-tab.js";
 import { initGalleryTab } from "./gallery-tab.js";
 import { initMetadataTab } from "./metadata-tab.js";
 import { initAiTab } from "./ai-tab.js";
 import { initTaggerTab } from "./tagger-tab.js";
 import { imageEditTab } from "./image-edit-tab.js";
+import { initVideoTab } from "./video-tab.js";

 // Apply saved theme immediately to prevent flash of default theme
 applyTheme(getSavedTheme());
@@ -591,6 +846,7 @@ try {
    const _s = getSettings();
    if (_s.textareaFontSize) applyTextareaFontSize(_s.textareaFontSize);
    applyJsonColors(_s.jsonColors);
+    applyModelTabActiveColor(_s.modelTabActiveColor);
 } catch {}

 function initHelpTab() {
@@ -603,6 +859,16 @@ function initHelpTab() {
            document.getElementById(`wfm-help-page-${page}`)?.classList.add("active");
        });
    });
+
+    // Jump-to-tab buttons: switch to the real feature tab this help page documents
+    document.querySelectorAll(".wfm-help-jump-btn").forEach((btn) => {
+        btn.addEventListener("click", () => {
+            document.querySelector(`.wfm-tab[data-tab="${btn.dataset.jumpTab}"]`)?.click();
+            if (btn.dataset.jumpSubtab) {
+                document.querySelector(`.wfm-gallery-subtab-btn[data-gallery-subtab="${btn.dataset.jumpSubtab}"]`)?.click();
+            }
+        });
+    });
 }

 document.addEventListener("DOMContentLoaded", () => {
@@ -616,11 +882,13 @@ document.addEventListener("DOMContentLoaded", () => {
    initModelsTab();
    initGenerateTab();
    initPromptTab();
+    initPromptTableTab();
    initMetadataTab();
    initGalleryTab();
    initAiTab();
    initTaggerTab();
    imageEditTab.init();
+    initVideoTab();

    console.log("Workflow Studio: App initialized");
 });
@@ -18,8 +18,15 @@ export const comfyUI = {
    connected: false,
    generating: false,
    currentPromptId: null,
+    // trackProgress() 実行中の Promise を promptId -> reject関数 で保持。
+    // WebSocket切断時に、待機中のPromiseを解決させずに放置してバッチループが
+    // 無言のまま停止する（例: カタログ作成バッチが特定件数で止まる）のを防ぐ。
+    _pendingTrackers: new Map(),
    currentWorkflow: null,
    currentAnalysis: null,
+    // ワークフロー読み込み時点のLora Loader (LoraManager)ノードの loras/text 状態。
+    // Stackグループチェックボックスのトグル時に、OFF側の「読み込み時の状態へ戻す」用に使う。
+    loraManagerSnapshots: {},

    updateUrl(url) {
        if (!url) {
@@ -66,10 +73,18 @@ export const comfyUI = {
            this.socket = new WebSocket(url);
            this.socket.onopen = () => resolve(true);
            this.socket.onerror = () => resolve(false);
-            this.socket.onclose = () => { this.socket = null; };
+            this.socket.onclose = () => {
+                this.socket = null;
+                this._rejectPendingTrackers(new Error("WebSocket disconnected"));
+            };
        });
    },

+    _rejectPendingTrackers(err) {
+        for (const rejectFn of this._pendingTrackers.values()) rejectFn(err);
+        this._pendingTrackers.clear();
+    },
+
    // Node info fetching
    async fetchObjectInfo(nodeClass) {
        const res = await fetch(`${this.baseUrl}/object_info/${nodeClass}`);
@@ -196,12 +211,29 @@ export const comfyUI = {
        return await res.json();
    },

-    trackProgress(promptId, progressCallback) {
+    // timeoutMs: この時間内に完了/エラー/中断通知が来なければ強制的にreject。
+    // WebSocketの取りこぼしやexecution_interrupted未処理でPromiseが永久に
+    // ぶら下がり続け、バッチループが無言で停止するのを防ぐための安全弁。
+    trackProgress(promptId, progressCallback, timeoutMs = 10 * 60 * 1000) {
        return new Promise((resolve, reject) => {
            if (!this.socket || this.socket.readyState !== WebSocket.OPEN) {
                reject(new Error("WebSocket not connected"));
                return;
            }
+            let settled = false;
+            const finish = (isResolve, value) => {
+                if (settled) return;
+                settled = true;
+                this.socket?.removeEventListener("message", handler);
+                clearTimeout(timer);
+                this._pendingTrackers.delete(promptId);
+                if (isResolve) resolve(value); else reject(value);
+            };
+
+            const timer = setTimeout(() => {
+                finish(false, new Error(`Generation timed out after ${Math.round(timeoutMs / 1000)}s (prompt_id=${promptId})`));
+            }, timeoutMs);
+
            const handler = (event) => {
                try {
                    const msg = JSON.parse(event.data);
@@ -211,17 +243,19 @@ export const comfyUI = {
                    }
                    if (msg.type === "executing" && msg.data?.prompt_id === promptId) {
                        if (msg.data.node === null) {
-                            this.socket.removeEventListener("message", handler);
-                            resolve();
+                            finish(true);
                        }
                    }
                    if (msg.type === "execution_error" && msg.data?.prompt_id === promptId) {
-                        this.socket.removeEventListener("message", handler);
-                        reject(new Error(msg.data.exception_message || "Execution error"));
+                        finish(false, new Error(msg.data.exception_message || "Execution error"));
+                    }
+                    if (msg.type === "execution_interrupted" && msg.data?.prompt_id === promptId) {
+                        finish(false, new Error("Execution interrupted"));
                    }
                } catch {}
            };
            this.socket.addEventListener("message", handler);
+            this._pendingTrackers.set(promptId, (err) => finish(false, err));
        });
    },

@@ -240,7 +274,13 @@ export const comfyUI = {
        });
        const res = await fetch(`${this.baseUrl}/view?${params}`);
        if (!res.ok) throw new Error(`Failed to fetch image: HTTP ${res.status}`);
-        return await res.blob();
+        const blob = await res.blob();
+        // /view はSVGをセキュリティ上application/octet-streamで返すため、
+        // <img>で表示できるよう拡張子から正しいMIMEタイプへ付け替える
+        if (imageData.filename?.toLowerCase().endsWith(".svg") && blob.type !== "image/svg+xml") {
+            return blob.slice(0, blob.size, "image/svg+xml");
+        }
+        return blob;
    },

    async uploadImage(file, filename, overwrite = true) {
@@ -270,7 +310,7 @@ export const comfyUI = {

    // High-level generate
    async generate(workflow, options = {}) {
-        const { seedMode = "random", seedValue = -1, onProgress, onComplete, onError } = options;
+        const { seedMode = "random", seedValue = -1, onProgress, onComplete, onError, timeoutMs } = options;

        this.generating = true;
        try {
@@ -292,7 +332,7 @@ export const comfyUI = {
            this.currentPromptId = result.prompt_id;

            // Track progress
-            await this.trackProgress(result.prompt_id, onProgress);
+            await this.trackProgress(result.prompt_id, onProgress, timeoutMs);

            // Get history/results
            const history = await this.getHistory(result.prompt_id);
@@ -300,6 +340,9 @@ export const comfyUI = {

            // Extract images from SaveImage outputs only
            const images = [];
+            // comfyui-tosvg の "Save SVG String" ノードは images ではなく
+            // saved_svg(ファイル名) / path(絶対パス) という独自キーで返す
+            const svgOutputs = [];
            const outputs = history.outputs || {};
            for (const nodeOutput of Object.values(outputs)) {
                if (nodeOutput.images) {
@@ -307,10 +350,23 @@ export const comfyUI = {
                        images.push(img);
                    }
                }
+                if (nodeOutput.saved_svg) {
+                    // ComfyUI の実行エンジンは ui 出力の各値をイテラブルとして連結するため、
+                    // ノード側が単一文字列で返すと 1 文字ずつ分解された配列になってしまう。
+                    // (例: "a.svg" -> ["a",".","s","v","g"]) 文字配列を検出したら結合して復元する。
+                    const joinIfCharArray = (v) =>
+                        Array.isArray(v) && v.every((c) => typeof c === "string" && c.length === 1)
+                            ? v.join("")
+                            : v;
+                    svgOutputs.push({
+                        filename: joinIfCharArray(nodeOutput.saved_svg),
+                        path: joinIfCharArray(nodeOutput.path) || "",
+                    });
+                }
            }

            onComplete?.(images, seed);
-            return { images, seed };
+            return { images, seed, svgOutputs };
        } catch (err) {
            onError?.(err);
            throw err;
@@ -5,7 +5,8 @@
 import { comfyUI } from "./comfyui-client.js";
 import { syncJsonHighlight } from "./json-highlight.js";
 import { t } from "./i18n.js";
-import { escapeHtml } from "./util.js";
+import { escapeHtml, setupSearchClearBtn } from "./util.js";
+import { showToast } from "./app.js";

 // ── Latent Image preset state ─────────────────────────────
 const _LATENT_PRESET_KEY = "wfm_latent_presets";
@@ -27,6 +28,114 @@ function _saveLatentPresets(list) {
    localStorage.setItem(_LATENT_PRESET_KEY, JSON.stringify(list));
 }

+// ── I2I placeholder image (Input tab / Image sub-panel) ──────────────────
+// One shared default (color-generated or a fixed uploaded image), remembered across
+// sessions. Each LoadImage slot's own "Placeholder" button applies this same default
+// to just that slot — see renderImageTab.
+const _I2I_PLACEHOLDER_KEY = "wfm_i2i_placeholder";
+const _I2I_PLACEHOLDER_DEFAULT = { mode: "color", color: "#808080", width: 512, height: 512, imageFilename: "" };
+
+function _loadI2IPlaceholderConfig() {
+    try {
+        const raw = localStorage.getItem(_I2I_PLACEHOLDER_KEY);
+        return raw ? { ..._I2I_PLACEHOLDER_DEFAULT, ...JSON.parse(raw) } : { ..._I2I_PLACEHOLDER_DEFAULT };
+    } catch { return { ..._I2I_PLACEHOLDER_DEFAULT }; }
+}
+
+function _saveI2IPlaceholderConfig(cfg) {
+    localStorage.setItem(_I2I_PLACEHOLDER_KEY, JSON.stringify(cfg));
+}
+
+// Renders a solid-color PNG on an offscreen canvas and returns it as a File, ready to
+// upload through comfyUI.uploadImage() the same way a picked/dropped file would be.
+function _generateColorImageFile(width, height, color) {
+    return new Promise((resolve, reject) => {
+        const canvas = document.createElement("canvas");
+        canvas.width = Math.max(1, width || 512);
+        canvas.height = Math.max(1, height || 512);
+        const ctx = canvas.getContext("2d");
+        ctx.fillStyle = color || "#808080";
+        ctx.fillRect(0, 0, canvas.width, canvas.height);
+        canvas.toBlob((blob) => {
+            if (!blob) { reject(new Error("Failed to render placeholder image")); return; }
+            resolve(new File([blob], `placeholder_${canvas.width}x${canvas.height}.png`, { type: "image/png" }));
+        }, "image/png");
+    });
+}
+
+// Wires the placeholder config panel at the top of the Image sub-panel (mode switch,
+// color/size fields, default-image drop zone). Every change is persisted immediately via
+// _saveI2IPlaceholderConfig so it's remembered next time the panel is rendered — this
+// panel is display-only config, it doesn't touch any workflow node itself; only each
+// slot's own Placeholder button (see renderImageTab) does that.
+function _wireI2IPlaceholderConfig(scopeEl) {
+    const colorModeRadio = scopeEl.querySelector("#wfm-i2i-ph-mode-color");
+    const imageModeRadio = scopeEl.querySelector("#wfm-i2i-ph-mode-image");
+    const colorFields = scopeEl.querySelector("#wfm-i2i-ph-color-fields");
+    const imageFields = scopeEl.querySelector("#wfm-i2i-ph-image-fields");
+    const widthInput = scopeEl.querySelector("#wfm-i2i-ph-width");
+    const heightInput = scopeEl.querySelector("#wfm-i2i-ph-height");
+    const colorInput = scopeEl.querySelector("#wfm-i2i-ph-color");
+    const dropZone = scopeEl.querySelector("#wfm-i2i-ph-drop");
+    const fileInput = scopeEl.querySelector("#wfm-i2i-ph-file");
+    const previewWrap = scopeEl.querySelector("#wfm-i2i-ph-preview-wrap");
+    const previewImg = scopeEl.querySelector("#wfm-i2i-ph-preview-img");
+    const statusEl = scopeEl.querySelector("#wfm-i2i-ph-status");
+    if (!colorModeRadio) return; // no LoadImage slots rendered — panel doesn't exist
+
+    const setMode = (mode) => {
+        if (colorFields) colorFields.style.display = mode === "color" ? "" : "none";
+        if (imageFields) imageFields.style.display = mode === "image" ? "" : "none";
+        _saveI2IPlaceholderConfig({ ..._loadI2IPlaceholderConfig(), mode });
+    };
+    colorModeRadio.addEventListener("change", () => { if (colorModeRadio.checked) setMode("color"); });
+    imageModeRadio?.addEventListener("change", () => { if (imageModeRadio.checked) setMode("image"); });
+
+    widthInput?.addEventListener("change", () => {
+        const width = Math.max(1, parseInt(widthInput.value, 10) || 512);
+        widthInput.value = width;
+        _saveI2IPlaceholderConfig({ ..._loadI2IPlaceholderConfig(), width });
+    });
+    heightInput?.addEventListener("change", () => {
+        const height = Math.max(1, parseInt(heightInput.value, 10) || 512);
+        heightInput.value = height;
+        _saveI2IPlaceholderConfig({ ..._loadI2IPlaceholderConfig(), height });
+    });
+    colorInput?.addEventListener("change", () => {
+        _saveI2IPlaceholderConfig({ ..._loadI2IPlaceholderConfig(), color: colorInput.value });
+    });
+
+    // Default image: uploaded to ComfyUI immediately (its filename is what actually gets
+    // reused later, not the raw file) so every slot's Placeholder button can apply it
+    // without re-uploading.
+    const applyDefaultImageFile = async (file) => {
+        if (!file || !file.type.startsWith("image/")) return;
+        if (statusEl) statusEl.textContent = t("i2iPlaceholderUploading");
+        try {
+            const result = await comfyUI.uploadImage(file, file.name);
+            if (!result.name) throw new Error("Upload returned no filename");
+            _saveI2IPlaceholderConfig({ ..._loadI2IPlaceholderConfig(), imageFilename: result.name });
+            if (previewImg) previewImg.src = `/view?filename=${encodeURIComponent(result.name)}&type=input`;
+            if (previewWrap) previewWrap.style.display = "";
+            if (statusEl) { statusEl.textContent = `✓ ${result.name}`; statusEl.style.color = "var(--wfm-success)"; }
+        } catch (err) {
+            if (statusEl) { statusEl.textContent = `✗ ${err.message}`; statusEl.style.color = "var(--wfm-danger)"; }
+        }
+    };
+    fileInput?.addEventListener("change", () => {
+        if (fileInput.files.length > 0) applyDefaultImageFile(fileInput.files[0]);
+    });
+    if (dropZone) {
+        dropZone.addEventListener("dragover", (e) => { e.preventDefault(); dropZone.classList.add("drag-over"); });
+        dropZone.addEventListener("dragleave", () => dropZone.classList.remove("drag-over"));
+        dropZone.addEventListener("drop", (e) => {
+            e.preventDefault();
+            dropZone.classList.remove("drag-over");
+            if (e.dataTransfer.files.length > 0) applyDefaultImageFile(e.dataTransfer.files[0]);
+        });
+    }
+}
+
 function _buildPresetOptions(customPresets) {
    const customs = customPresets.map((p) =>
        `<option value="${p.w}x${p.h}">${p.w}x${p.h}</option>`
@@ -48,6 +157,16 @@ function _refreshPresetSelect(customPresets) {
 let _stackStrengths = {};
 // { modelFullPath: boolean } — true = active (default)
 let _stackActive = {};
+// ── LoRA node-bypass state (GenerateUI Model tab header toggle) ───────────
+// Force the LoRA node's strength to 0 without touching the actual ComfyUI node's mode —
+// currentWorkflow is already-converted API format (see comfyui-workflow.js
+// convertUiToApi), where mode has no effect at execution time, so a real Bypass(mode:4)
+// can't be reproduced here; zeroing strength is the behavioral equivalent.
+// { nodeId: boolean } — true = currently bypassed
+let _loraNodeBypass = {};
+// { nodeId: { loraName, strModel, strClip } | { loras, text } } — pre-bypass values to
+// restore when toggled back off. Shape depends on isLoraManager at bypass-time.
+let _loraBypassSnapshot = {};
 // { id: string|null, selStart: number, selEnd: number }
 let _lastPromptFocus = { id: null, selStart: 0, selEnd: 0 };

@@ -344,11 +463,11 @@ export const comfyEditor = {
        return found || name;
    },

-    renderAll(analysis, workflow) {
+    renderAll(analysis, workflow, opts = {}) {
        this.renderPromptTab(analysis, "wfm-gen-prompt-fields");
        this.renderImageTab(analysis, "wfm-gen-image-fields");
        this.renderModelTab(analysis, "wfm-gen-model-fields");
-        this.renderLoraPane(analysis, "wfm-gen-lora-fields"); // async, fires independently
+        this.renderLoraPane(analysis, "wfm-gen-lora-fields", opts); // async, fires independently
        this.renderSettingsTab(analysis, "wfm-gen-settings-fields");
        _syncRawJson();
    },
@@ -367,7 +486,7 @@ export const comfyEditor = {
                <label>Positive Prompt</label>
                <div style="display:flex;gap:8px;margin-bottom:6px;">
                    <select id="wfm-prompt-pos-target" class="wfm-select" style="width:auto;flex:1;min-width:0;">
-                        ${positiveNodes.map((n) => `<option value="${n.id}" data-text-key="${n.textKey || "text"}" selected>ID:${n.id} (${n.title})</option>`).join("")}
+                        ${positiveNodes.map((n, i) => `<option value="${n.id}" data-text-key="${n.textKey || "text"}" ${i === 0 ? "selected" : ""}>ID:${n.id} (${n.title})</option>`).join("")}
                        ${nodeOpts}
                    </select>
                    <button class="wfm-btn wfm-btn-sm" id="wfm-prompt-pos-revert" title="${t("revertPromptTitle")}">↺</button>
@@ -379,7 +498,7 @@ export const comfyEditor = {
                <label>Negative Prompt</label>
                <div style="display:flex;gap:8px;margin-bottom:6px;">
                    <select id="wfm-prompt-neg-target" class="wfm-select" style="width:auto;flex:1;min-width:0;">
-                        ${negativeNodes.map((n) => `<option value="${n.id}" data-text-key="${n.textKey || "text"}" selected>ID:${n.id} (${n.title})</option>`).join("")}
+                        ${negativeNodes.map((n, i) => `<option value="${n.id}" data-text-key="${n.textKey || "text"}" ${i === 0 ? "selected" : ""}>ID:${n.id} (${n.title})</option>`).join("")}
                        ${nodeOpts}
                    </select>
                    <button class="wfm-btn wfm-btn-sm" id="wfm-prompt-neg-revert" title="${t("revertPromptTitle")}">↺</button>
@@ -508,10 +627,14 @@ export const comfyEditor = {
        const el = document.getElementById(containerId);
        if (!el) return;

-        const sections = [
+        // 使用頻度の高い順: Checkpoint/VAE/Diffusion Model/Text Encoder は常時表示。
+        // ControlNet/Hypernetwork は意図的に使う場面が限られるため折りたたみにする。
+        const mainSections = [
            { label: "Checkpoint", key: "checkpoints", nodes: analysis.checkpoint_nodes, inputKey: "ckpt_name" },
            { label: "VAE", key: "vaes", nodes: analysis.vae_nodes, inputKey: "vae_name" },
            { label: "Diffusion Model", key: "diffusionModels", nodes: analysis.diffusion_model_nodes, inputKey: "unet_name" },
+        ];
+        const collapsibleSections = [
            { label: "ControlNet", key: "controlNets", nodes: analysis.controlnet_nodes, inputKey: "control_net_name" },
            {
                label: "Hypernetwork", key: "hypernetworks", nodes: analysis.hypernetwork_nodes, inputKey: "hypernetwork_name",
@@ -519,48 +642,70 @@ export const comfyEditor = {
            },
        ];

-        el.innerHTML = sections
-            .map((s) => {
-                const models = this.models[s.key] || [];
-                const currentVal = s.nodes?.[0]?.[s.inputKey] || "";
-                const isMissing = !!currentVal && !models.includes(currentVal);
-                const targetOpts = s.nodes
-                    .map((n) => `<option value="${n.id}">ID:${n.id} (${n.title})</option>`)
-                    .join("");
-                const extrasHtml = (s.extras || []).map((ex) => {
-                    const curVal = s.nodes?.[0]?.[ex.inputKey] ?? ex.defaultVal;
-                    return `<div style="display:flex;gap:6px;align-items:center;margin-top:4px;">
-                        <label style="font-size:12px;white-space:nowrap;color:var(--wfm-text-secondary);">${ex.label}</label>
-                        <input type="${ex.type}" class="wfm-input wfm-model-extra" id="wfm-model-${s.key}-${ex.inputKey}"
-                            data-key="${s.key}" data-input-key="${ex.inputKey}"
-                            value="${curVal}" step="${ex.step}" min="${ex.min}" max="${ex.max}"
-                            style="width:80px;">
-                    </div>`;
-                }).join("");
+        const renderSectionBody = (s) => {
+            const models = this.models[s.key] || [];
+            const currentVal = s.nodes?.[0]?.[s.inputKey] || "";
+            const isMissing = !!currentVal && !models.includes(currentVal);
+            const targetOpts = s.nodes
+                .map((n) => `<option value="${n.id}">ID:${n.id} (${n.title})</option>`)
+                .join("");
+            const extrasHtml = (s.extras || []).map((ex) => {
+                const curVal = s.nodes?.[0]?.[ex.inputKey] ?? ex.defaultVal;
+                return `<div style="display:flex;gap:6px;align-items:center;margin-top:4px;">
+                    <label style="font-size:12px;white-space:nowrap;color:var(--wfm-text-secondary);">${ex.label}</label>
+                    <input type="${ex.type}" class="wfm-input wfm-model-extra" id="wfm-model-${s.key}-${ex.inputKey}"
+                        data-key="${s.key}" data-input-key="${ex.inputKey}"
+                        value="${curVal}" step="${ex.step}" min="${ex.min}" max="${ex.max}"
+                        style="width:80px;">
+                </div>`;
+            }).join("");

-                return `
-                <div class="wfm-form-group" style="border-bottom:1px solid var(--wfm-border);padding-bottom:12px;">
-                    <label>${s.label}</label>
-                    <input type="text" class="wfm-input wfm-model-filter" placeholder="Filter..." data-target="wfm-model-${s.key}" style="margin-bottom:4px;">
-                    <select class="wfm-select ${isMissing ? "wfm-select-missing" : ""}" id="wfm-model-${s.key}" style="margin-bottom:4px;">
-                        ${isMissing ? `<option value="${escapeHtml(currentVal)}" selected>⚠ ${escapeHtml(currentVal)} (${t("modelNotFound")})</option>` : ""}
-                        ${models.map((m) => `<option value="${m}" ${m === currentVal ? "selected" : ""}>${m}</option>`).join("")}
-                    </select>
-                    ${isMissing ? `<div class="wfm-model-missing-hint">${t("modelNotFoundHint")}</div>` : ""}
-                    ${extrasHtml}
-                    <div style="display:flex;gap:8px;align-items:center;margin-top:4px;">
-                        <select class="wfm-select" id="wfm-model-${s.key}-target" style="flex:1;">${targetOpts}</select>
-                        <button class="wfm-btn wfm-btn-sm wfm-model-apply" data-key="${s.key}" data-input="${s.inputKey}" title="Apply (Alt+Click: Apply &amp; Generate)">Apply</button>
-                    </div>
+            return `
+                <div class="wfm-search-wrap" style="margin-bottom:4px;width:100%;">
+                    <input type="text" class="wfm-input wfm-search-input wfm-model-filter" id="wfm-model-${s.key}-filter" placeholder="Filter..." data-target="wfm-model-${s.key}">
+                    <button type="button" class="wfm-search-clear-btn" id="wfm-model-${s.key}-filter-clear" title="Clear search">✕</button>
+                </div>
+                <select class="wfm-select ${isMissing ? "wfm-select-missing" : ""}" id="wfm-model-${s.key}" style="margin-bottom:4px;">
+                    ${isMissing ? `<option value="${escapeHtml(currentVal)}" selected>⚠ ${escapeHtml(currentVal)} (${t("modelNotFound")})</option>` : ""}
+                    ${models.map((m) => `<option value="${m}" ${m === currentVal ? "selected" : ""}>${m}</option>`).join("")}
+                </select>
+                ${isMissing ? `<div class="wfm-model-missing-hint">${t("modelNotFoundHint")}</div>` : ""}
+                ${extrasHtml}
+                <div style="display:flex;gap:8px;align-items:center;margin-top:4px;">
+                    <select class="wfm-select" id="wfm-model-${s.key}-target" style="flex:1;">${targetOpts}</select>
+                    <button class="wfm-btn wfm-btn-sm wfm-model-apply" data-key="${s.key}" data-input="${s.inputKey}" title="Apply (Alt+Click: Apply &amp; Generate)">Apply</button>
                </div>
            `;
-            })
-            .join("") + '<div class="wfm-form-group" id="wfm-te-section" style="border-bottom:1px solid var(--wfm-border);padding-bottom:12px;"><label>Text Encoder</label></div>';
+        };
+
+        const mainHtml = mainSections.map((s) => {
+            const hasNodes = (s.nodes?.length || 0) > 0;
+            return `
+            <div class="wfm-form-group" style="border-bottom:1px solid var(--wfm-border);padding-bottom:12px;">
+                <label class="${hasNodes ? "wfm-model-label-active" : ""}">${s.label}</label>
+                ${renderSectionBody(s)}
+            </div>`;
+        }).join("");
+
+        const teHtml = '<div class="wfm-form-group" id="wfm-te-section" style="border-bottom:1px solid var(--wfm-border);padding-bottom:12px;"><label>Text Encoder</label></div>';
+
+        const collapsibleHtml = collapsibleSections.map((s) => {
+            const hasNodes = (s.nodes?.length || 0) > 0;
+            return `
+            <details class="wfm-settings-section">
+                <summary class="wfm-settings-summary ${hasNodes ? "wfm-model-label-active" : ""}">${s.label}</summary>
+                <div class="wfm-form-group" style="margin-bottom:0;">
+                    ${renderSectionBody(s)}
+                </div>
+            </details>`;
+        }).join("");
+
+        el.innerHTML = mainHtml + teHtml + collapsibleHtml;

        // Filter inputs
        el.querySelectorAll(".wfm-model-filter").forEach((input) => {
-            input.addEventListener("input", () => {
-                const targetId = input.dataset.target;
+            const targetId = input.dataset.target;
+            const rebuild = () => {
                const select = document.getElementById(targetId);
                if (!select) return;
                const filter = input.value.toLowerCase();
@@ -570,7 +715,9 @@ export const comfyEditor = {
                    .filter((m) => m.toLowerCase().includes(filter))
                    .map((m) => `<option value="${m}">${m}</option>`)
                    .join("");
-            });
+            };
+            input.addEventListener("input", rebuild);
+            setupSearchClearBtn(input.id, `${input.id}-clear`, rebuild);
        });

        // Apply buttons
@@ -606,13 +753,104 @@ export const comfyEditor = {
        _initTextEncoderSection(analysis, this.models.textEncoders || [], el).catch(() => {});
    },

-    async renderLoraPane(analysis, containerId) {
+    // Toggles the GenerateUI Model tab's LoRA column-header bypass button: forces the
+    // current target LoRA node's strength to 0 (both tabs' strength fields, whichever
+    // is currently in currentWorkflow), or restores whatever was there before. Targets
+    // the same node Single/Stack Apply default to (first LoraManager, else first LoRA
+    // node) so one button covers both tabs without needing its own node picker.
+    toggleLoraNodeBypass(analysis) {
+        const loraNodes = analysis?.lora_nodes || [];
+        let nodeId = (loraNodes.find((n) => n.is_lora_manager) || loraNodes[0])?.id;
+        let isLoraManager = !!loraNodes.find((n) => String(n.id) === String(nodeId))?.is_lora_manager;
+        if (nodeId == null) {
+            nodeId = Object.keys(comfyUI.currentWorkflow || {}).find((id) => comfyUI.currentWorkflow[id]?.inputs && "lora_name" in comfyUI.currentWorkflow[id].inputs);
+            isLoraManager = false;
+        }
+        const wfNode = nodeId != null ? comfyUI.currentWorkflow?.[nodeId] : null;
+        if (!wfNode) {
+            showToast(t("modelsGenUINoNode", "LoRA"), "warning");
+            return;
+        }
+
+        if (_loraNodeBypass[nodeId]) {
+            // Restore whatever was set before bypassing
+            const snap = _loraBypassSnapshot[nodeId];
+            if (snap) {
+                if (isLoraManager) {
+                    wfNode.inputs.loras = { __value__: JSON.parse(JSON.stringify(snap.loras || [])) };
+                    wfNode.inputs.text = snap.text ?? "";
+                } else {
+                    wfNode.inputs.lora_name = snap.lora_name;
+                    wfNode.inputs.strength_model = snap.strength_model;
+                    wfNode.inputs.strength_clip = snap.strength_clip;
+                }
+            }
+            delete _loraNodeBypass[nodeId];
+            delete _loraBypassSnapshot[nodeId];
+        } else {
+            // Snapshot current values, then zero the strength (LoraManager: every
+            // entry in its loras list, keeping the list itself intact so un-bypassing
+            // restores the exact same Stack — not just a single-LoRA fallback).
+            if (isLoraManager) {
+                const loras = Array.isArray(wfNode.inputs.loras?.__value__) ? wfNode.inputs.loras.__value__ : [];
+                _loraBypassSnapshot[nodeId] = { loras: JSON.parse(JSON.stringify(loras)), text: wfNode.inputs.text ?? "" };
+                wfNode.inputs.loras = { __value__: loras.map((l) => ({ ...l, strength: 0, clipStrength: 0 })) };
+                wfNode.inputs.text = "";
+            } else {
+                _loraBypassSnapshot[nodeId] = {
+                    lora_name: wfNode.inputs.lora_name,
+                    strength_model: wfNode.inputs.strength_model,
+                    strength_clip: wfNode.inputs.strength_clip,
+                };
+                wfNode.inputs.strength_model = 0;
+                wfNode.inputs.strength_clip = 0;
+            }
+            _loraNodeBypass[nodeId] = true;
+        }
+        _syncRawJson();
+    },
+
+    async renderLoraPane(analysis, containerId, opts = {}) {
        const el = document.getElementById(containerId);
        if (!el) return;

        const loraNodes = analysis.lora_nodes || [];
+        document.getElementById("wfm-gen-lora-col-title")?.classList.toggle("wfm-model-label-active", loraNodes.length > 0);
        const loras = this.models.loras || [];
        const defaultStackTarget = (loraNodes.find((n) => n.is_lora_manager) || loraNodes[0])?.id;
+        const hasLoraManager = loraNodes.some((n) => n.is_lora_manager);
+
+        // Sync the column-header bypass button (lives outside this container's
+        // innerHTML, in the static wfm-gen-lora-col-header) to whatever the target
+        // node's current bypass state is.
+        const bypassBtn = document.getElementById("wfm-lora-bypass-toggle");
+        if (bypassBtn) {
+            bypassBtn.classList.toggle("active", defaultStackTarget != null && !!_loraNodeBypass[defaultStackTarget]);
+            bypassBtn.disabled = loraNodes.length === 0;
+        }
+        // Use Stack Group チェックボックスの現在状態を先読み(Stack表示の取得元判定に使う)。
+        // resetStackMode(新規読み込み)時は常にOFF扱い。
+        const stackModeChecked = hasLoraManager && !opts.resetStackMode && (el.querySelector("#wfm-lora-stack-mode-toggle")?.checked ?? false);
+
+        // ワークフロー新規読み込み時のみ: LoraManagerノードのloras/text状態をスナップショットし、
+        // Stackグループ使用チェックボックスをOFFへリセットする(既存のGenUI状態への影響を避けるため
+        // タブ切替やStack再読込などの単なる再描画では行わない)。
+        if (opts.resetStackMode) {
+            // New workflow loaded — bypass state/snapshots belonged to the previous
+            // workflow's node IDs, so they can't be meaningfully carried forward.
+            _loraNodeBypass = {};
+            _loraBypassSnapshot = {};
+            comfyUI.loraManagerSnapshots = {};
+            for (const n of loraNodes) {
+                if (!n.is_lora_manager) continue;
+                const wfNode = comfyUI.currentWorkflow?.[n.id];
+                if (!wfNode?.inputs) continue;
+                comfyUI.loraManagerSnapshots[n.id] = {
+                    loras: Array.isArray(wfNode.inputs.loras?.__value__) ? JSON.parse(JSON.stringify(wfNode.inputs.loras.__value__)) : [],
+                    text: wfNode.inputs.text ?? "",
+                };
+            }
+        }
        const nodeOpts = loraNodes
            .map((n) => `<option value="${n.id}">ID:${n.id} (${n.title})</option>`)
            .join("");
@@ -637,26 +875,53 @@ export const comfyEditor = {
            }
        }

-        // Fetch Stack group, metadata, CivitAI cache in parallel
+        // Stack表示の取得元: ON(Use Stack Group)ならModelsタブの登録済みStackグループ、
+        // OFF(既定)ならLoraManagerノードに実際に設定されているLoRAをそのまま表示する。
        let stackModels = [];
        let metadata = {};
        let civitaiCache = {};
+        const useWorkflowLoraState = hasLoraManager && !stackModeChecked;
        try {
-            const [grpRes, metaRes, civRes] = await Promise.all([
-                fetch("/api/wfm/models/groups?type=lora"),
+            const [metaRes, civRes] = await Promise.all([
                fetch("/api/wfm/models/metadata"),
                fetch("/api/wfm/models/civitai/cache"),
            ]);
-            const groups = grpRes.ok ? await grpRes.json() : {};
-            stackModels = groups["Stack"] || [];
            metadata = metaRes.ok ? await metaRes.json() : {};
            civitaiCache = civRes.ok ? await civRes.json() : {};
        } catch { /* ignore */ }

-        stackModels.forEach((m) => {
-            if (!_stackStrengths[m]) _stackStrengths[m] = { m: 1.0, c: 1.0 };
-            if (_stackActive[m] === undefined) _stackActive[m] = true;
-        });
+        if (stackModeChecked) {
+            try {
+                const grpRes = await fetch("/api/wfm/models/groups?type=lora");
+                const groups = grpRes.ok ? await grpRes.json() : {};
+                stackModels = groups["Stack"] || [];
+            } catch { /* ignore */ }
+            stackModels.forEach((m) => {
+                if (!_stackStrengths[m]) _stackStrengths[m] = { m: 1.0, c: 1.0 };
+                if (_stackActive[m] === undefined) _stackActive[m] = true;
+            });
+        } else if (useWorkflowLoraState) {
+            const wfNode = comfyUI.currentWorkflow?.[defaultStackTarget];
+            const wfLoras = wfNode?.inputs?.loras?.__value__;
+            // resetStackMode(新規読み込み)/syncFromWorkflow(チェックボックスOFF切替直後)の時だけ
+            // ワークフローの実データで強制上書きする。タブ切替等の単なる再描画では、
+            // 既にメモリ上に値があればそれを維持し、Stackパネルでの一時的なON/OFF・強度編集を
+            // 再描画のたびに消してしまわないようにする。
+            const shouldSync = opts.resetStackMode || opts.syncFromWorkflow;
+            if (Array.isArray(wfLoras)) {
+                stackModels = wfLoras.map((l) => {
+                    const found = (this.models.loras || []).find((m) => _loraBasename(m) === l.name);
+                    const full = found || l.name;
+                    if (shouldSync || _stackStrengths[full] === undefined) {
+                        _stackStrengths[full] = { m: parseFloat(l.strength) || 1.0, c: parseFloat(l.clipStrength ?? l.strength) || 1.0 };
+                    }
+                    if (shouldSync || _stackActive[full] === undefined) {
+                        _stackActive[full] = l.active !== false;
+                    }
+                    return full;
+                });
+            }
+        }

        // Build Stack trigger words
        const activeTriggerWords = [];
@@ -673,7 +938,9 @@ export const comfyEditor = {
            ? activeTriggerWords.map((w) => `<span class="wfm-lora-trigger-word">${w}</span>`).join(" ")
            : `<span style="color:var(--wfm-text-secondary);font-size:12px;">—</span>`;
        const stackLoraSyntax = _buildLoraSyntax(stackModels);
-        const allActive = stackModels.every((m) => _stackActive[m] !== false);
+        // stackModelsが空だと every() が空配列に対し true を返す(空虚な真)ため、
+        // 何も無いのに「トグルオール」チェックボックスがON表示になるのを防ぐ
+        const allActive = stackModels.length > 0 && stackModels.every((m) => _stackActive[m] !== false);
        const anyActive = stackModels.some((m) => _stackActive[m] !== false);

        const stackModelRows = stackModels.map((m) => {
@@ -691,7 +958,10 @@ export const comfyEditor = {
            </div>`;
        }).join("");

-        const _prevActiveTab = el.querySelector(".wfm-lora-tab-btn.active")?.dataset?.tab || "single";
+        let _prevActiveTab = el.querySelector(".wfm-lora-tab-btn.active")?.dataset?.tab || "single";
+        // 新規読み込み時、LoraManagerノードに実際に複数LoRAが設定されている場合は
+        // Single(1件しか表示できない)ではなくStackタブを初期表示にする
+        if (opts.resetStackMode && useWorkflowLoraState && stackModels.length > 1) _prevActiveTab = "stack";
        // applyToGenUIで設定したSingle表示の状態を保存（再描画後に復元）
        const _prevSingleSyntax = document.getElementById("wfm-lora-single-syntax")?.textContent || "";
        const _prevSingleTriggers = document.getElementById("wfm-lora-single-triggers")?.innerHTML || "";
@@ -700,11 +970,19 @@ export const comfyEditor = {
            <div class="wfm-lora-tab-header">
                <button class="wfm-lora-tab-btn active" data-tab="single">Single</button>
                <button class="wfm-lora-tab-btn" data-tab="stack">Stack</button>
+                ${hasLoraManager ? `
+                <label class="wfm-lora-stack-mode-label" style="margin-left:auto;display:flex;align-items:center;gap:4px;font-size:12px;white-space:nowrap;" title="ON: 登録済みStackグループを読み込む / OFF: ワークフローに実際に設定されているLoRAを表示・編集する">
+                    <input type="checkbox" id="wfm-lora-stack-mode-toggle" ${stackModeChecked ? "checked" : ""}>
+                    Use Stack Group
+                </label>` : ""}
            </div>

            <!-- Single tab -->
            <div class="wfm-lora-tab-content" id="wfm-lora-panel-single">
-                <input type="text" class="wfm-input" id="wfm-lora-filter" placeholder="Filter...">
+                <div class="wfm-search-wrap" style="width:100%;">
+                    <input type="text" class="wfm-input wfm-search-input" id="wfm-lora-filter" placeholder="Filter...">
+                    <button type="button" class="wfm-search-clear-btn" id="wfm-lora-filter-clear" title="Clear search">✕</button>
+                </div>
                <select class="wfm-select" id="wfm-lora-select">
                    ${loras.map((m) => `<option value="${m}" ${m === currentVal ? "selected" : ""}>${m}</option>`).join("")}
                </select>
@@ -731,6 +1009,7 @@ export const comfyEditor = {

            <!-- Stack tab -->
            <div class="wfm-lora-tab-content" id="wfm-lora-panel-stack" style="display:none;">
+                ${hasLoraManager ? `<div style="font-size:11px;color:var(--wfm-text-secondary);margin-bottom:6px;">${useWorkflowLoraState ? "Showing: LoRAs currently in workflow" : "Showing: registered Stack group"}</div>` : ""}
                <div class="wfm-lora-stack-header">
                    <select class="wfm-select" id="wfm-lora-stack-target" style="flex:1;min-width:0;">${stackTargetOpts}</select>
                    <button class="wfm-btn wfm-btn-sm" id="wfm-lora-stack-apply" title="Apply Stack to node and sync to Positive prompt">Apply</button>
@@ -765,7 +1044,7 @@ export const comfyEditor = {
                    <div id="wfm-lora-stack-triggers" class="wfm-lora-stack-triggers">${stackTriggerHtml}</div>
                </div>
                <div class="wfm-lora-stack-models">
-                    ${stackModelRows || `<p class="wfm-placeholder">No models in Stack group</p>`}
+                    ${stackModelRows || `<p class="wfm-placeholder">${useWorkflowLoraState ? "No LoRAs set on this node" : "No models in Stack group"}</p>`}
                </div>
            </div>
        `;
@@ -803,9 +1082,63 @@ export const comfyEditor = {
            document.getElementById("wfm-lora-panel-stack").style.display = "";
        }

+        // ── Stackグループ使用チェックボックス ─────────────────
+        // ON: LoraManagerノードへStackグループを（クリアしてから）読み込む(既存のStack Applyを流用)
+        // OFF: ワークフロー読み込み時点のloras/text状態へ（クリアしてから）戻す
+        document.getElementById("wfm-lora-stack-mode-toggle")?.addEventListener("change", async (e) => {
+            const nodeId = document.getElementById("wfm-lora-stack-target")?.value || defaultStackTarget;
+            if (!nodeId || !comfyUI.currentWorkflow?.[nodeId]) return;
+
+            if (e.target.checked) {
+                // stackModelsはこの時点では「ワークフロー state」を指したままのため、
+                // 先に再描画してStackグループを取得させてからApplyする
+                await this.renderLoraPane(analysis, containerId);
+                document.getElementById("wfm-lora-stack-apply")?.click();
+                return;
+            }
+
+            const snap = comfyUI.loraManagerSnapshots?.[nodeId] || { loras: [], text: "" };
+            comfyUI.currentWorkflow[nodeId].inputs.loras = { __value__: JSON.parse(JSON.stringify(snap.loras)) };
+            comfyUI.currentWorkflow[nodeId].inputs.text = snap.text;
+            _syncRawJson();
+
+            // ON時にPositiveプロンプトへ挿入されたStack由来の<lora:...>構文とトリガーワードを除去する
+            // (新規に追加はしない。ワークフロー本来のプロンプトへ戻すだけ)
+            const posTextarea = document.getElementById("wfm-prompt-pos-text");
+            if (posTextarea && stackModels.length > 0) {
+                let cleaned = posTextarea.value;
+                for (const m of stackModels) {
+                    const stem = _loraBasename(m).replace(/[.*+?^${}()|[\]\\]/g, "\\$&");
+                    cleaned = cleaned.replace(new RegExp(`,?\\s*<lora:${stem}:[^>]*>`, "gi"), "");
+                }
+                const stackWords = new Set();
+                stackModels.forEach((m) => {
+                    const sha = (metadata[m] || {}).sha256;
+                    const civInfo = sha && civitaiCache[sha];
+                    civInfo?.trainedWords?.forEach((w) => stackWords.add(w.trim().toLowerCase()));
+                });
+                if (stackWords.size > 0) {
+                    cleaned = cleaned.split(",").map((p) => p.trim()).filter((p) => p && !stackWords.has(p.toLowerCase())).join(", ");
+                }
+                posTextarea.value = cleaned.replace(/,\s*$/, "").trim();
+
+                const posNodeId = document.getElementById("wfm-prompt-pos-target")?.value;
+                if (posNodeId && comfyUI.currentWorkflow?.[posNodeId]) {
+                    const promptNode = comfyUI.currentAnalysis?.prompt_nodes?.find((n) => String(n.id) === String(posNodeId));
+                    comfyUI.currentWorkflow[posNodeId].inputs[promptNode?.textKey || "text"] = posTextarea.value;
+                    _syncRawJson();
+                }
+            }
+
+            // syncFromWorkflow: OFFへ戻した直後は、たった今書き戻したloras/text状態と
+            // Stackパネルの強度/有効状態表示を一致させるため強制同期する
+            this.renderLoraPane(analysis, containerId, { syncFromWorkflow: true });
+        });
+
        // ── Single: filter ───────────────────────────────────
-        document.getElementById("wfm-lora-filter")?.addEventListener("input", (e) => {
-            const filter = e.target.value.toLowerCase();
+        const loraFilterInput = document.getElementById("wfm-lora-filter");
+        const rebuildLoraSingleList = () => {
+            const filter = loraFilterInput?.value.toLowerCase() || "";
            const select = document.getElementById("wfm-lora-select");
            if (!select) return;
            select.innerHTML = loras
@@ -813,7 +1146,9 @@ export const comfyEditor = {
                .map((m) => `<option value="${m}">${m}</option>`)
                .join("");
            _refreshLoraSingleDynamic(metadata, civitaiCache);
-        });
+        };
+        loraFilterInput?.addEventListener("input", rebuildLoraSingleList);
+        setupSearchClearBtn("wfm-lora-filter", "wfm-lora-filter-clear", rebuildLoraSingleList);

        // ── Single: update SYNTAX/TRIGGERS on model or strength change ──
        document.getElementById("wfm-lora-select")?.addEventListener("change", () => _refreshLoraSingleDynamic(metadata, civitaiCache));
@@ -830,6 +1165,11 @@ export const comfyEditor = {
            const strModel = parseFloat(document.getElementById("wfm-lora-str-model")?.value) || 1.0;
            const strClip = parseFloat(document.getElementById("wfm-lora-str-clip")?.value) || 1.0;
            _applyLoraToNode(nodeId, select.value, strModel, strClip, node?.is_lora_manager);
+            // An explicit Apply overwrites whatever bypass had zeroed — clear it so the
+            // header button (and a later un-bypass) don't stomp this new value.
+            delete _loraNodeBypass[nodeId];
+            delete _loraBypassSnapshot[nodeId];
+            document.getElementById("wfm-lora-bypass-toggle")?.classList.remove("active");
            _syncRawJson();

            // Sync to Positive prompt
@@ -962,6 +1302,11 @@ export const comfyEditor = {
                    comfyUI.currentWorkflow[nodeId].inputs.strength_clip = _stackStrengths[first]?.c ?? 1.0;
                }
            }
+            // An explicit Apply overwrites whatever bypass had zeroed — clear it so the
+            // header button (and a later un-bypass) don't stomp this new value.
+            delete _loraNodeBypass[nodeId];
+            delete _loraBypassSnapshot[nodeId];
+            document.getElementById("wfm-lora-bypass-toggle")?.classList.remove("active");
            _syncRawJson();

            // Sync Stack LORA SYNTAX + TRIGGER WORDS to Positive prompt
@@ -1030,23 +1375,39 @@ export const comfyEditor = {
        const sampler = analysis.sampler_nodes?.[0];
        const latent = analysis.latent_nodes?.[0];

+        // "Advanced Sampling" workflows (Flux.1/Flux.2, SD3.5, Chroma...) spread seed/steps/cfg/
+        // sampler/scheduler/denoise across RandomNoise + CFGGuider + KSamplerSelect + a *Scheduler
+        // node instead of one KSampler. sampler.*NodeId (set in analyzeWorkflow) says which real
+        // node each field writes back to; null/"" means that workflow has no such control at all
+        // (e.g. Flux2Scheduler has no named "scheduler" combo) so the field is disabled here.
+        const schedulerAvailable = !!sampler && sampler.schedulerNodeId != null;
+        const denoiseAvailable = !!sampler && sampler.denoiseNodeId != null;
+
        el.innerHTML = `
            <div style="display:flex;flex-direction:row;gap:0;align-items:flex-start;">
                <div style="flex:1;min-width:0;padding-right:14px;border-right:1px solid var(--wfm-border);">
-                    <h3 style="font-size:13px;font-weight:600;text-transform:uppercase;letter-spacing:0.5px;color:var(--wfm-text-secondary);margin:0 0 12px;">KSampler</h3>
+                    <h3 style="font-size:13px;font-weight:600;text-transform:uppercase;letter-spacing:0.5px;color:var(--wfm-text-secondary);margin:0 0 12px;">${sampler?.advanced ? "Sampler (Advanced)" : "KSampler"}</h3>
                    ${sampler ? `
-                    <input type="hidden" id="wfm-settings-sampler-id" value="${sampler.id}" data-seed-key="${sampler.seedKey || "seed"}">
+                    <input type="hidden" id="wfm-settings-sampler-id"
+                        data-seed-key="${sampler.seedKey || "seed"}"
+                        data-seed-node-id="${sampler.seedNodeId ?? sampler.id}"
+                        data-steps-node-id="${sampler.stepsNodeId ?? sampler.id}"
+                        data-cfg-key="${sampler.cfgKey || "cfg"}"
+                        data-cfg-node-id="${sampler.cfgNodeId ?? sampler.id}"
+                        data-sampler-node-id="${sampler.samplerNodeId ?? sampler.id}"
+                        data-scheduler-node-id="${sampler.schedulerNodeId ?? ""}"
+                        data-denoise-node-id="${sampler.denoiseNodeId ?? ""}">
                    <div class="wfm-form-group">
                        <label>Seed</label>
-                        <input type="number" class="wfm-input" id="wfm-settings-seed" value="${sampler.seed ?? -1}">
+                        <input type="number" class="wfm-input" id="wfm-settings-seed" value="${sampler.seed ?? ""}" placeholder="${sampler.seed === undefined ? "linked" : ""}">
                    </div>
                    <div class="wfm-form-group">
                        <label>Steps</label>
-                        <input type="number" class="wfm-input" id="wfm-settings-steps" value="${sampler.steps ?? 20}" min="1" max="200">
+                        <input type="number" class="wfm-input" id="wfm-settings-steps" value="${sampler.steps ?? ""}" placeholder="${sampler.steps === undefined ? "linked" : ""}" min="1" max="200">
                    </div>
                    <div class="wfm-form-group">
                        <label>CFG</label>
-                        <input type="number" class="wfm-input" id="wfm-settings-cfg" value="${sampler.cfg ?? 7}" step="0.5" min="0">
+                        <input type="number" class="wfm-input" id="wfm-settings-cfg" value="${sampler.cfg ?? ""}" placeholder="${sampler.cfg === undefined ? "linked" : ""}" step="0.5" min="0">
                    </div>
                    <div class="wfm-form-group">
                        <label>Sampler</label>
@@ -1056,13 +1417,15 @@ export const comfyEditor = {
                    </div>
                    <div class="wfm-form-group">
                        <label>Scheduler</label>
-                        <select class="wfm-select" id="wfm-settings-scheduler">
-                            ${this.models.schedulers.map((s) => `<option value="${s}" ${s === sampler.scheduler ? "selected" : ""}>${s}</option>`).join("")}
+                        <select class="wfm-select" id="wfm-settings-scheduler" ${schedulerAvailable ? "" : "disabled"}>
+                            ${schedulerAvailable
+                                ? this.models.schedulers.map((s) => `<option value="${s}" ${s === sampler.scheduler ? "selected" : ""}>${s}</option>`).join("")
+                                : `<option value="">N/A</option>`}
                        </select>
                    </div>
                    <div class="wfm-form-group">
                        <label>Denoise</label>
-                        <input type="number" class="wfm-input" id="wfm-settings-denoise" value="${sampler.denoise ?? 1.0}" step="0.05" min="0" max="1">
+                        <input type="number" class="wfm-input" id="wfm-settings-denoise" value="${sampler.denoise ?? ""}" placeholder="${denoiseAvailable && sampler.denoise === undefined ? "linked" : ""}" step="0.05" min="0" max="1" ${denoiseAvailable ? "" : "disabled"}>
                    </div>
                    <button class="wfm-btn wfm-btn-sm" id="wfm-settings-sampler-apply" title="Apply (Alt+Click: Apply &amp; Generate)">Apply</button>
                    ` : "<p class='wfm-placeholder'>No KSampler node found</p>"}
@@ -1073,17 +1436,24 @@ export const comfyEditor = {
                    <input type="hidden" id="wfm-settings-latent-id" value="${latent.id}">
                    <div class="wfm-form-group">
                        <label>Width</label>
-                        <input type="number" class="wfm-input" id="wfm-settings-width" value="${latent.width ?? 512}" step="8" min="64">
+                        <input type="number" class="wfm-input" id="wfm-settings-width" value="${latent.width ?? ""}" placeholder="${latent.width === undefined ? "linked" : ""}" step="8" min="64">
                    </div>
                    <div class="wfm-form-group">
                        <label>Height</label>
-                        <input type="number" class="wfm-input" id="wfm-settings-height" value="${latent.height ?? 512}" step="8" min="64">
+                        <input type="number" class="wfm-input" id="wfm-settings-height" value="${latent.height ?? ""}" placeholder="${latent.height === undefined ? "linked" : ""}" step="8" min="64">
                    </div>
                    <div class="wfm-form-group">
                        <label>Batch Size</label>
                        <input type="number" class="wfm-input" id="wfm-settings-batch" value="${latent.batch_size ?? 1}" min="1" max="64">
                    </div>
+                    ${latent.isVideoLatent ? `
+                    <div class="wfm-form-group">
+                        <label>Length (frames)</label>
+                        <input type="number" class="wfm-input" id="wfm-settings-latent-length" value="${latent.length ?? ""}" placeholder="${latent.length === undefined ? "linked" : ""}" step="1" min="1">
+                    </div>
+                    ` : ""}
                    <button class="wfm-btn wfm-btn-sm" id="wfm-settings-latent-apply">Apply</button>
+                    ${latent.width === undefined || latent.height === undefined ? `<p class="wfm-placeholder" style="margin-top:6px;">Width/Height is linked to another node (e.g. auto-follows the input image) — leave blank to keep it linked.</p>` : ""}
                    <div style="margin-top:10px;border-top:1px solid var(--wfm-border);padding-top:10px;">
                        <div style="display:flex;flex-wrap:wrap;gap:4px;margin-bottom:8px;">
                            ${[512, 768, 1024, 2048].map((s) => `<button class="wfm-btn wfm-btn-sm wfm-latent-sq-btn" data-size="${s}">${s}</button>`).join("")}
@@ -1109,17 +1479,21 @@ export const comfyEditor = {
        `;

        document.getElementById("wfm-settings-sampler-apply")?.addEventListener("click", (e) => {
-            const nodeId = document.getElementById("wfm-settings-sampler-id")?.value;
-            if (!nodeId || !comfyUI.currentWorkflow?.[nodeId]) return;
-            const inputs = comfyUI.currentWorkflow[nodeId].inputs;
-            // KSamplerAdvanced uses noise_seed; fall back to seed
-            const seedKey = document.getElementById("wfm-settings-sampler-id")?.dataset?.seedKey || "seed";
-            inputs[seedKey] = parseInt(document.getElementById("wfm-settings-seed")?.value) || -1;
-            inputs.steps = parseInt(document.getElementById("wfm-settings-steps")?.value) || 20;
-            inputs.cfg = parseFloat(document.getElementById("wfm-settings-cfg")?.value) || 7;
-            inputs.sampler_name = document.getElementById("wfm-settings-sampler-name")?.value;
-            inputs.scheduler = document.getElementById("wfm-settings-scheduler")?.value;
-            inputs.denoise = parseFloat(document.getElementById("wfm-settings-denoise")?.value) || 1.0;
+            const ds = document.getElementById("wfm-settings-sampler-id")?.dataset || {};
+            const write = (nodeId, key, value) => {
+                if (!nodeId || !comfyUI.currentWorkflow?.[nodeId]) return;
+                comfyUI.currentWorkflow[nodeId].inputs[key] = value;
+            };
+            const seedEl = document.getElementById("wfm-settings-seed");
+            if (seedEl?.value !== "") write(ds.seedNodeId, ds.seedKey || "seed", parseInt(seedEl.value) || -1);
+            const stepsEl = document.getElementById("wfm-settings-steps");
+            if (stepsEl?.value !== "") write(ds.stepsNodeId, "steps", parseInt(stepsEl.value) || 20);
+            const cfgEl = document.getElementById("wfm-settings-cfg");
+            if (cfgEl?.value !== "") write(ds.cfgNodeId, ds.cfgKey || "cfg", parseFloat(cfgEl.value) || 7);
+            write(ds.samplerNodeId, "sampler_name", document.getElementById("wfm-settings-sampler-name")?.value);
+            if (ds.schedulerNodeId) write(ds.schedulerNodeId, "scheduler", document.getElementById("wfm-settings-scheduler")?.value);
+            const denoiseEl = document.getElementById("wfm-settings-denoise");
+            if (ds.denoiseNodeId && denoiseEl?.value !== "") write(ds.denoiseNodeId, "denoise", parseFloat(denoiseEl.value) || 1.0);
            _syncRawJson();
            if (e.altKey) document.dispatchEvent(new CustomEvent("wfm:apply-and-generate"));
        });
@@ -1128,9 +1502,14 @@ export const comfyEditor = {
            const nodeId = document.getElementById("wfm-settings-latent-id")?.value;
            if (!nodeId || !comfyUI.currentWorkflow?.[nodeId]) return;
            const inputs = comfyUI.currentWorkflow[nodeId].inputs;
-            inputs.width = parseInt(document.getElementById("wfm-settings-width")?.value) || 512;
-            inputs.height = parseInt(document.getElementById("wfm-settings-height")?.value) || 512;
+            const wEl = document.getElementById("wfm-settings-width");
+            const hEl = document.getElementById("wfm-settings-height");
+            // Blank = leave the (linked) width/height alone instead of clobbering it with a default
+            if (wEl?.value !== "") inputs.width = parseInt(wEl.value) || 512;
+            if (hEl?.value !== "") inputs.height = parseInt(hEl.value) || 512;
            inputs.batch_size = parseInt(document.getElementById("wfm-settings-batch")?.value) || 1;
+            const lenEl = document.getElementById("wfm-settings-latent-length");
+            if (lenEl && lenEl.value !== "") inputs.length = parseInt(lenEl.value) || 1;
            _syncRawJson();
        });

@@ -1212,8 +1591,34 @@ export const comfyEditor = {
        const slots = loadNodes.slice(0, 4);
        // Mask Editor One ノード（画像+マスクを内包、常に両方必須）— 別枠で最大2件表示
        const meoSlots = meoNodes.slice(0, 2);
+        const phCfg = _loadI2IPlaceholderConfig();
+        const isColorMode = phCfg.mode !== "image";
        el.innerHTML = `
            ${slots.length === 0 ? "" : `
+            <details class="wfm-settings-section wfm-i2i-placeholder-config">
+                <summary class="wfm-settings-summary">${t("i2iPlaceholderTitle")}</summary>
+                <div class="wfm-i2i-placeholder-mode">
+                    <label><input type="radio" name="wfm-i2i-ph-mode" id="wfm-i2i-ph-mode-color" value="color" ${isColorMode ? "checked" : ""}> ${t("i2iPlaceholderColor")}</label>
+                    <label><input type="radio" name="wfm-i2i-ph-mode" id="wfm-i2i-ph-mode-image" value="image" ${isColorMode ? "" : "checked"}> ${t("i2iPlaceholderImage")}</label>
+                </div>
+                <div id="wfm-i2i-ph-color-fields" class="wfm-i2i-placeholder-fields wfm-lab-modal-inline" style="${isColorMode ? "" : "display:none;"}">
+                    <div><label>${t("i2iPlaceholderWidth")}</label><input type="number" min="1" id="wfm-i2i-ph-width" class="wfm-input" value="${Number(phCfg.width) || 512}"></div>
+                    <div><label>${t("i2iPlaceholderHeight")}</label><input type="number" min="1" id="wfm-i2i-ph-height" class="wfm-input" value="${Number(phCfg.height) || 512}"></div>
+                    <div><label>${t("i2iPlaceholderColorLabel")}</label><input type="color" id="wfm-i2i-ph-color" class="wfm-input" value="${escapeHtml(/^#[0-9a-fA-F]{6}$/.test(phCfg.color) ? phCfg.color : "#808080")}"></div>
+                </div>
+                <div id="wfm-i2i-ph-image-fields" class="wfm-i2i-placeholder-fields" style="${isColorMode ? "display:none;" : ""}">
+                    <div class="wfm-i2i-preview-wrap" id="wfm-i2i-ph-preview-wrap" style="${phCfg.imageFilename ? "" : "display:none;"}">
+                        <img class="wfm-i2i-preview-img" id="wfm-i2i-ph-preview-img" src="${phCfg.imageFilename ? `/view?filename=${encodeURIComponent(phCfg.imageFilename)}&type=input` : ""}">
+                    </div>
+                    <div class="wfm-i2i-drop-zone" id="wfm-i2i-ph-drop">
+                        <label class="wfm-i2i-drop-label">
+                            ${t("i2iPlaceholderDropImage")}
+                            <input type="file" accept="image/*" id="wfm-i2i-ph-file" style="display:none;">
+                        </label>
+                    </div>
+                    <span class="wfm-i2i-status" id="wfm-i2i-ph-status"></span>
+                </div>
+            </details>
            <div class="wfm-i2i-grid">
                ${slots.map((node, i) => `
                    <div class="wfm-i2i-slot" data-slot="${i}" data-node-id="${node.id}">
@@ -1247,8 +1652,10 @@ export const comfyEditor = {
                            </div>
                        </div>
                        ` : ""}
-                        <div style="display:flex;gap:6px;margin-top:6px;">
+                        <div style="display:flex;gap:6px;margin-top:6px;flex-wrap:wrap;">
                            <button class="wfm-btn wfm-btn-sm wfm-btn-primary wfm-i2i-apply" data-slot="${i}" disabled>Apply</button>
+                            <button type="button" class="wfm-btn wfm-btn-sm wfm-i2i-placeholder-btn" data-slot="${i}">${t("i2iPlaceholderApply")}</button>
+                            <button type="button" class="wfm-btn wfm-btn-sm wfm-i2i-clear" data-slot="${i}">${t("clear")}</button>
                            <span class="wfm-i2i-status" id="wfm-i2i-status-${i}"></span>
                        </div>
                    </div>
@@ -1409,8 +1816,64 @@ export const comfyEditor = {
                    applyBtn.disabled = false;
                }
            });
+
+            // Clear: reset this slot's staged/preview state back to empty. Doesn't touch
+            // the workflow node itself — LoadImage always needs *some* valid filename, so
+            // there's nothing meaningful to "unset" there; this just lets the user cancel
+            // a pending pick and start over.
+            const clearBtn = el.querySelector(`.wfm-i2i-clear[data-slot="${i}"]`);
+            clearBtn?.addEventListener("click", () => {
+                pendingFile = null;
+                previewImg.src = "";
+                previewWrap.style.display = "none";
+                filenameEl.textContent = "";
+                if (fileInput) fileInput.value = "";
+                applyBtn.disabled = !pendingMaskFile;
+                statusEl.textContent = "";
+            });
+
+            // Placeholder: generate (color mode) or reuse (image mode) the shared default
+            // configured at the top of the panel, and replace this slot's image
+            // immediately — no separate Apply click needed, matching the "one button,
+            // one slot" behavior described for this feature.
+            const placeholderBtn = el.querySelector(`.wfm-i2i-placeholder-btn[data-slot="${i}"]`);
+            placeholderBtn?.addEventListener("click", async () => {
+                const cfg = _loadI2IPlaceholderConfig();
+                placeholderBtn.disabled = true;
+                statusEl.textContent = t("i2iPlaceholderGenerating");
+                try {
+                    let filename;
+                    if (cfg.mode === "image") {
+                        if (!cfg.imageFilename) throw new Error(t("i2iPlaceholderNoDefaultImage"));
+                        filename = cfg.imageFilename;
+                    } else {
+                        const file = await _generateColorImageFile(cfg.width, cfg.height, cfg.color);
+                        const result = await comfyUI.uploadImage(file, file.name);
+                        if (!result.name) throw new Error("Upload returned no filename");
+                        filename = result.name;
+                    }
+                    if (comfyUI.currentWorkflow?.[node.id]) {
+                        comfyUI.currentWorkflow[node.id].inputs.image = filename;
+                    }
+                    pendingFile = null;
+                    previewImg.src = `/view?filename=${encodeURIComponent(filename)}&type=input`;
+                    previewWrap.style.display = "";
+                    filenameEl.textContent = filename;
+                    applyBtn.disabled = !pendingMaskFile;
+                    statusEl.textContent = `✓ ${filename}`;
+                    statusEl.style.color = "var(--wfm-success)";
+                    _syncRawJson();
+                } catch (err) {
+                    statusEl.textContent = `✗ ${err.message}`;
+                    statusEl.style.color = "var(--wfm-danger)";
+                } finally {
+                    placeholderBtn.disabled = false;
+                }
+            });
        });

+        _wireI2IPlaceholderConfig(el);
+
        // Initialize each Mask Editor One slot（画像+マスク両方が揃って初めてApply可能）
        meoSlots.forEach((node, i) => {
            const fileInput = document.getElementById(`wfm-meo-file-${i}`);
@@ -1626,6 +2089,75 @@ export const comfyEditor = {
        if (!workflow) _syncRawJson();
    },

+    // Resolves a user/LLM-supplied aspect ratio (e.g. "3:2" or the full COMBO label
+    // "3:2 (Photo)") against a ResolutionSelector-type node's actual options via
+    // /object_info — the workflow analysis only knows the node's CURRENT value, not its
+    // full option list, so a bare "3:2" needs matching against whatever labeled string
+    // that node's aspect_ratio COMBO actually accepts. Falls back to the raw input if
+    // the node type can't be queried or nothing matches, so ComfyUI's own validation
+    // surfaces a clear error instead of this silently doing nothing.
+    async resolveAspectRatioOption(nodeType, requested) {
+        if (!requested) return null;
+        const ratioMatch = String(requested).match(/(\d+)\s*:\s*(\d+)/);
+        const wantedRatio = ratioMatch ? `${ratioMatch[1]}:${ratioMatch[2]}` : String(requested).trim();
+        try {
+            const info = await comfyUI.fetchObjectInfo(nodeType);
+            const options = info?.[nodeType]?.input?.required?.aspect_ratio?.[1]?.options || [];
+            if (options.includes(requested)) return requested;
+            return options.find((o) => o.startsWith(wantedRatio)) || requested;
+        } catch {
+            return requested;
+        }
+    },
+
+    // AI TOOL Chat's generate_image tool call — writes whichever of KSampler
+    // (steps/cfg/sampler_name/scheduler/denoise/seed), Latent Image (width/height/
+    // batch_size), and Resolution Selector (resolvedAspectRatio) fields the LLM
+    // supplied onto the given workflow/analysis (or comfyUI.currentWorkflow/
+    // currentAnalysis by default). Mirrors lab-tab.js's _buildWorkflowForIteration
+    // KSampler branch — same per-field node-id indirection (stepsNodeId/cfgNodeId/...
+    // falling back to sampler.id) for Advanced-Sampling workflows (Flux.1/2, SD3.5,
+    // Chroma...) that spread these across several nodes.
+    // seed is returned rather than written directly — the caller passes it through to
+    // comfyUI.generate()'s seedMode/seedValue instead, same as every other seed source.
+    // resolvedAspectRatio must already be one of the node's actual option strings (see
+    // resolveAspectRatioOption above) — passed in rather than resolved here because
+    // that lookup is async and this stays a plain synchronous writer.
+    setGenerationParams({ steps, cfg, sampler_name, scheduler, denoise, seed, width, height, batch_size, resolvedAspectRatio, workflow, analysis } = {}) {
+        const wf = workflow || comfyUI.currentWorkflow;
+        const an = analysis || comfyUI.currentAnalysis;
+        if (!wf || !an) return { seed: null };
+
+        const sampler = an.sampler_nodes?.[0];
+        if (sampler) {
+            if (steps != null) { const id = sampler.stepsNodeId ?? sampler.id; if (wf[id]) wf[id].inputs.steps = steps; }
+            if (cfg != null) { const id = sampler.cfgNodeId ?? sampler.id; if (wf[id]) wf[id].inputs.cfg = cfg; }
+            if (sampler_name) { const id = sampler.samplerNodeId ?? sampler.id; if (wf[id]) wf[id].inputs.sampler_name = sampler_name; }
+            if (scheduler && sampler.schedulerNodeId != null && wf[sampler.schedulerNodeId]) {
+                wf[sampler.schedulerNodeId].inputs.scheduler = scheduler;
+            }
+            if (denoise != null && sampler.denoiseNodeId != null && wf[sampler.denoiseNodeId]) {
+                wf[sampler.denoiseNodeId].inputs.denoise = denoise;
+            }
+        }
+
+        // Resolution Selector takes priority over direct width/height — writing width/
+        // height straight onto the EmptyLatentImage would just clobber whatever the
+        // selector computed, silently ignoring the requested aspect ratio.
+        const resSelector = an.resolution_selector_nodes?.[0];
+        const latent = an.latent_nodes?.[0];
+        if (resolvedAspectRatio && resSelector && wf[resSelector.id]) {
+            wf[resSelector.id].inputs.aspect_ratio = resolvedAspectRatio;
+        } else if (latent && wf[latent.id]) {
+            if (width != null) wf[latent.id].inputs.width = width;
+            if (height != null) wf[latent.id].inputs.height = height;
+        }
+        if (latent && wf[latent.id] && batch_size != null) wf[latent.id].inputs.batch_size = batch_size;
+
+        if (!workflow) _syncRawJson();
+        return { seed: seed ?? null };
+    },
+
    syncToWorkflow() {
        // Sync prompt texts before generation
        const posSelect = document.getElementById("wfm-prompt-pos-target");
@@ -1752,7 +2284,7 @@ async function _initTextEncoderSection(analysis, textEncoders, containerEl) {
    const deviceOpts = ["default", "cpu"].map(d => `<option value="${d}" ${d === currentDevice ? "selected" : ""}>${d}</option>`).join("");

    section.innerHTML = `
-        <label>Text Encoder</label>
+        <label class="wfm-model-label-active">Text Encoder</label>
        <input type="text" class="wfm-input" id="wfm-te-filter" placeholder="Filter..." style="margin-bottom:4px;">
        <select class="wfm-select" id="wfm-te-clip1" style="margin-bottom:4px;">${clip1Opts}</select>
        ${isDual ? `<select class="wfm-select" id="wfm-te-clip2" style="margin-bottom:4px;">${clip2Opts}</select>` : ""}
@@ -5,12 +5,16 @@

 import { showToast } from "./app.js";
 import { t } from "./i18n.js";
-import { loadFileIntoMetadataTab } from "./metadata-tab.js";
+import { loadFileIntoMetadataTab, extractPrompts, buildPromptItem } from "./metadata-tab.js";
 import { loadWorkflowIntoEditor } from "./generate-tab.js";
-import { escapeHtml, setupSearchClearBtn } from "./util.js";
+import { escapeHtml, setupSearchClearBtn, getAiBackendDefaultUrl } from "./util.js";
 import { comfyWorkflow } from "./comfyui-workflow.js";
 import { comfyUI } from "./comfyui-client.js";
 import { comfyEditor } from "./comfyui-editor.js";
+import { callLLM, loadAiSettings, isValidBackendUrl } from "./ai-tab.js";
+import { initImagePromptTab, activateImagePromptTab } from "./image-prompt-tab.js";
+import { initStyleCatalogTab, activateStyleCatalogTab } from "./style-catalog-tab.js";
+import { applyStoredVideoVolume } from "./settings-tab.js";

 // ── 定数 ─────────────────────────────────────────────────────

@@ -39,9 +43,27 @@ const API = {
    imagesDelete:               `/wfm/gallery/images/delete`,
    imagesMove:                 `/wfm/gallery/images/move`,
    imagesExportZip:            `/wfm/gallery/images/export-zip`,
+    imagesExportPsd:            `/wfm/gallery/images/export-psd`,
 };

 export const FEEDER_GROUP = "__Feeder__";
+export const VIDEO_GROUP = "__Video Assets__";
+// Video Planを実行するたびに生成された動画が自動的に追加される作業用グループ
+// （Plan保存の有無に関わらず常にここへ入る）。__Video Assets__（ユーザーが手動で
+// キュレーションする素材グループ）への整理はユーザー任意のタイミングで行う。
+export const VTEMP_GROUP = "__Video Temp__";
+
+const _RESERVED_GROUPS = [FEEDER_GROUP, VIDEO_GROUP, VTEMP_GROUP];
+function _isReservedGroup(name) {
+    return _RESERVED_GROUPS.includes(name);
+}
+
+// 拡張子から動画ファイル（mp4）かどうかを判定する。
+// 一覧アイテムは path/filename、詳細メタ(get_image_metadata)は ext フィールドを持つため両対応。
+export function isVideoFile(img) {
+    const source = img?.ext || img?.filename || img?.path || "";
+    return source.toLowerCase().endsWith(".mp4");
+}

 // ComfyUI Comic Creater からiframe越しに画像を受け取り、Generate UIのImage入力スロットへ直接セットする（I2I連携）。
 // Comic Creater側の「I2Iへ送る」ボタンから
@@ -103,10 +125,117 @@ window._wfmReceiveInpaintRequest = async (imageBlob, maskBlob, params, workflowD
    }
 };

+// ComfyUI Comic Creater からiframe越しに画像を受け取り、Image Edit タブの
+// Select I2I機能をUIを開かずに直接実行して結果URLを返す（I2I連携、マスク不要）。
+// Comic Creater側の Image タブ「Select→I2I」から
+// iframe.contentWindow._wfmReceiveI2IRunRequest(imageBlob, params, workflowData?, workflowFilename?) として呼ばれる。
+// workflowData が渡された場合（Comic Creater側のI2I設定でデフォルトワークフローが有効な時）は、
+// 実行前にそのワークフローを読み込む。渡されない場合はGenerate UIに現在ロード中のワークフローをそのまま使う。
+window._wfmReceiveI2IRunRequest = async (imageBlob, params, workflowData, workflowFilename) => {
+    try {
+        if (workflowData) {
+            if (!comfyUI.connected) {
+                await comfyUI.checkConnection();
+            }
+            if (comfyUI.connected && (!comfyEditor.models.checkpoints || comfyEditor.models.checkpoints.length === 0)) {
+                await comfyEditor.loadModelLists();
+            }
+            await loadWorkflowIntoEditor(workflowData, workflowFilename || "workflow.json");
+        }
+        return await window._wfmImageEditTab.runI2IExternal(imageBlob, params);
+    } catch (e) {
+        return { ok: false, message: e.message };
+    }
+};
+
+// ComfyUI Comic Creater からiframe越しにコマの設定（シーン・要素・セリフ等）を受け取り、
+// AIタブの設定タブと同じLLM接続設定（Ollama/LM Studio）で画像生成プロンプトの下書きを
+// 生成して返す（半自動マンガ作成の「L」ボタン連携用）。
+// Comic Creater側のスクリプトタブ「L」ボタンから
+// iframe.contentWindow._wfmReceiveLLMPromptRequest(context) として呼ばれる。
+// context: { scene, elements, dialogues, existingPrompt }（いずれも文字列、空文字可）
+window._wfmReceiveLLMPromptRequest = async (context) => {
+    try {
+        const settings = loadAiSettings();
+        const { backend = "ollama", backendUrl, model } = settings;
+        const url = backendUrl || getAiBackendDefaultUrl(backend);
+        if (!isValidBackendUrl(url)) return { ok: false, message: "AI settings: invalid backend URL (configure it in the Settings tab)" };
+        if (!model) return { ok: false, message: "AI settings: no model selected (configure it in the Settings tab)" };
+
+        const { scene = "", elements = "", dialogues = "", existingPrompt = "" } = context || {};
+        const prompt = [
+            "Create a concise Stable Diffusion image generation prompt (English, comma-separated tags/phrases describing scene, composition, character appearance and action) for one manga panel, based on the following context.",
+            "Output only the prompt text, nothing else.",
+            scene ? `Scene: ${scene}` : null,
+            elements ? `Characters/elements: ${elements}` : null,
+            dialogues ? `Dialogue: ${dialogues}` : null,
+            existingPrompt ? `Current draft prompt (revise/improve it): ${existingPrompt}` : null,
+        ].filter(Boolean).join("\n");
+
+        const result = await callLLM(url, backend, model, prompt);
+        const text = (result || "").trim();
+        if (!text) return { ok: false, message: "LLM returned an empty response" };
+        return { ok: true, text };
+    } catch (e) {
+        return { ok: false, message: e.message };
+    }
+};
+
+// ComfyUI Comic Creater からiframe越しに画像プロンプト・サイズを受け取り、Generate UIで
+// テキストから画像を生成して結果URLを返す（半自動マンガ作成のコマ単位バッチ画像生成用）。
+// Comic Creater側のスクリプトタブ「画像を一括生成」から
+// iframe.contentWindow._wfmReceiveGenerateRequest(prompt, width, height, negative, workflowData?, workflowFilename?)
+// として呼ばれる。I2I/Inpaintと異なり画像アップロードは行わない（txt2img）。
+// workflowData が渡された場合（Comic Creater側のT2I設定でデフォルトワークフローが有効な時）は、
+// 実行前にそのワークフローを読み込む。渡されない場合はGenerate UIに現在ロード中のワークフローをそのまま使う。
+window._wfmReceiveGenerateRequest = async (prompt, width, height, negative, workflowData, workflowFilename) => {
+    try {
+        if (!window._wfmGenerateTab?.generate) return { ok: false, message: "Generate UI is not ready yet" };
+
+        if (workflowData) {
+            try {
+                if (!comfyUI.connected) {
+                    await comfyUI.checkConnection();
+                }
+                if (comfyUI.connected && (!comfyEditor.models.checkpoints || comfyEditor.models.checkpoints.length === 0)) {
+                    await comfyEditor.loadModelLists();
+                }
+                await loadWorkflowIntoEditor(workflowData, workflowFilename || "workflow.json");
+            } catch (e) {
+                console.warn("[T2I] failed to load default workflow:", e);
+            }
+        }
+
+        const analysis = comfyUI.currentAnalysis;
+        if (!comfyUI.currentWorkflow || !analysis) return { ok: false, message: "No workflow loaded in Generate UI" };
+
+        const workflow = JSON.parse(JSON.stringify(comfyUI.currentWorkflow));
+        const latent = analysis.latent_nodes?.[0];
+        if (latent && width && height && workflow[latent.id]) {
+            workflow[latent.id].inputs.width = width;
+            workflow[latent.id].inputs.height = height;
+        }
+
+        comfyEditor.setPromptText("positive", prompt || "", { workflow, analysis });
+        if (negative) comfyEditor.setPromptText("negative", negative, { workflow, analysis });
+
+        await window._wfmGenerateTab.generate(workflow);
+
+        const resultUrl = document.getElementById("wfm-gen-result-img")?.src;
+        if (!resultUrl) return { ok: false, message: "No result image produced" };
+        return { ok: true, url: resultUrl };
+    } catch (e) {
+        return { ok: false, message: e.message };
+    }
+};
+
 // ── ページング ────────────────────────────────────────────────
 const PAGE_SIZE = 50;
 let _renderedCount = 0;
 let _scrollObserver = null;
+let _loadImagesAbortController = null;
+let _searchDebounceTimer = null;
+const SEARCH_DEBOUNCE_MS = 300;

 // ── 状態 ─────────────────────────────────────────────────────

@@ -146,6 +275,13 @@ function formatDate(mtime) {
    return new Date(mtime * 1000).toLocaleString();
 }

+function formatDuration(seconds) {
+    const total = Math.round(seconds);
+    const m = Math.floor(total / 60);
+    const s = total % 60;
+    return `${m}:${String(s).padStart(2, "0")}`;
+}
+
 async function openImageInMetadataTab(img) {
    try {
        const res = await fetch(API.serveImage(img.path));
@@ -201,6 +337,30 @@ async function exportSelectedImagesToZip(paths) {
    }
 }

+async function exportSelectedImagesToPsd(paths) {
+    if (paths.length === 0) return;
+    try {
+        const res = await fetch(API.imagesExportPsd, {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify({ paths }),
+        });
+        if (!res.ok) throw new Error((await res.json()).error || `HTTP ${res.status}`);
+        const blob = await res.blob();
+        const url = URL.createObjectURL(blob);
+        const a = document.createElement("a");
+        a.href = url;
+        a.download = `gallery_export_${Date.now()}.psd`;
+        document.body.appendChild(a);
+        a.click();
+        document.body.removeChild(a);
+        URL.revokeObjectURL(url);
+        showToast(t("psdExportCompleted"), "success");
+    } catch (e) {
+        showToast(t("errorWithMsg", e.message), "error");
+    }
+}
+
 // ── フォルダツリー ────────────────────────────────────────────

 function _getExpandedPaths() {
@@ -296,7 +456,7 @@ function renderTreeNode(node, container, depth, isRoot) {
    // フォルダ名
    const label = document.createElement("span");
    label.className = "wfm-gallery-tree-label";
-    label.textContent = isRoot ? `[root] ${node.name}` : node.name;
+    label.textContent = isRoot ? "[root]" : node.name;
    if (node.image_count > 0) {
        const badge = document.createElement("span");
        badge.className = "wfm-gallery-tree-count";
@@ -346,6 +506,16 @@ function renderTreeNode(node, container, depth, isRoot) {

        container.appendChild(item);
        container.appendChild(childContainer);
+
+        // root フォルダはデフォルトで展開状態にする（フォルダスキャン高速化により
+        // サブフォルダの内容もすぐ確認できるようになったため、折りたたみ初期状態だと
+        // 気付きにくい）
+        if (isRoot) {
+            arrow.dataset.expanded = "true";
+            arrow.textContent = "▼";
+            childContainer.style.display = "";
+            node.children.forEach(child => renderTreeNode(child, childContainer, depth + 1, false));
+        }
    } else {
        container.appendChild(item);
    }
@@ -356,6 +526,16 @@ function renderTreeNode(node, container, depth, isRoot) {
 async function loadImages() {
    if (!state.currentFolder) return;

+    // 前回のリクエストがまだ処理中なら中断する。中断せず並行させると、後から
+    // 返ってきた古いレスポンス（例: クリア直前に打っていた検索文字列の結果）が
+    // 最新の表示を上書きしてしまい、「クリアしても検索結果のまま/読み込み中の
+    // まま」に見える不具合の原因になっていた。
+    if (_loadImagesAbortController) {
+        _loadImagesAbortController.abort();
+    }
+    const controller = new AbortController();
+    _loadImagesAbortController = controller;
+
    const grid = document.getElementById("wfm-gallery-grid");
    grid.innerHTML = `<p class="wfm-placeholder">${t("loading")}</p>`;

@@ -367,18 +547,29 @@ async function loadImages() {
    if (state.favoriteOnly) params.favorite = "true";
    if (state.tagFilter) params.tag = state.tagFilter;

-    // グループフィルタはサーバーサイドで処理
-    if (state.groupFilter) params.group = state.groupFilter;
+    // グループフィルタはサーバーサイドで処理。グループのメンバーは現在のフォルダの
+    // サブフォルダに散らばっている可能性がある(例: 動画は"video"サブフォルダ配下)ため、
+    // 通常のフォルダ単位ブラウズ(非再帰)とは異なり、フィルタ時はフォルダ配下を再帰的に
+    // 検索する。
+    if (state.groupFilter) {
+        params.group = state.groupFilter;
+        params.recursive = "true";
+    }

    try {
-        const images = (await apiFetch(API.images(params))).images || [];
+        const images = (await apiFetch(API.images(params), { signal: controller.signal })).images || [];
        state.images = images;
        state.lastSelectionIndex = -1;
        document.getElementById("wfm-gallery-count").textContent = `${state.images.length} images`;
        renderImages();
        updateTagFilter(state.images);
    } catch (e) {
+        if (e.name === "AbortError") return;
        grid.innerHTML = `<p class="wfm-placeholder">Error: ${escapeHtml(e.message)}</p>`;
+    } finally {
+        if (_loadImagesAbortController === controller) {
+            _loadImagesAbortController = null;
+        }
    }
 }

@@ -471,6 +662,14 @@ function createThumbCard(img) {
    };
    card.appendChild(imgEl);

+    // 動画ファイルは再生アイコンバッジを重ねて表示（サムネイル自体は先頭フレームのJPEG）
+    if (isVideoFile(img)) {
+        const playBadge = document.createElement("div");
+        playBadge.className = "wfm-gallery-thumb-video-badge";
+        playBadge.textContent = "▶";
+        card.appendChild(playBadge);
+    }
+
    // お気に入りトグルボタン（カード右上）
    const favBtn = document.createElement("button");
    favBtn.className = `wfm-gallery-thumb-fav-btn${img.favorite ? " active" : ""}`;
@@ -770,18 +969,20 @@ async function loadImageDetail(img) {
    if (moveBtn) moveBtn.disabled = false;
    if (delBtn) delBtn.disabled = false;

-    // プレビュー
+    // プレビュー（mp4は<video controls>、それ以外は<img>）
    const preview = document.getElementById("wfm-gallery-detail-preview");
+    const isVideo = isVideoFile(img);
+    const mediaHtml = isVideo
+        ? `<video src="${API.serveImage(img.path)}" class="wfm-gallery-detail-img" controls title="Double-click to enlarge"></video>`
+        : `<img src="${API.serveImage(img.path)}" class="wfm-gallery-detail-img" alt="${escapeHtml(img.filename)}" title="Double-click to enlarge">`;
    preview.innerHTML = `
        <div class="wfm-gallery-preview-wrapper">
-            <img src="${API.serveImage(img.path)}" class="wfm-gallery-detail-img" alt="${escapeHtml(img.filename)}" title="Double-click to enlarge">
-            <div class="wfm-gallery-preview-overlay">
-                <button class="wfm-gallery-download-btn" title="Download image">⬇</button>
-            </div>
+            ${mediaHtml}
        </div>
    `;
-    preview.querySelector("img").addEventListener("dblclick", () => openLightbox(img));
-    preview.querySelector(".wfm-gallery-download-btn").addEventListener("click", () => downloadImage(img));
+    const previewMediaEl = preview.querySelector(isVideo ? "video" : "img");
+    previewMediaEl.addEventListener("dblclick", () => openLightbox(img));
+    if (isVideo) applyStoredVideoVolume(previewMediaEl);

    // ファイル名
    document.getElementById("wfm-gallery-detail-filename").textContent = img.filename;
@@ -806,15 +1007,45 @@ async function loadImageDetail(img) {
        state.embeddedWorkflow = wfRes.has_workflow ? wfRes.workflow : null;
        renderWorkflowJson(state.embeddedWorkflow);
        _updateCopyCanvasBtn();
+        renderImagePromptSection(metaRes.image_prompt);
+        renderDimensionInfo(metaRes);
+        // Promptタブは prompt_workflow (API形式優先) を使う。トップレベルとサブグラフに
+        // 独立した複数系統を持つワークフローでは workflow (UI形式) からの抽出だと
+        // トップレベル系統しか拾えないことがあるため（Metadataタブと同じ優先順位に揃える）。
+        renderPromptTab(wfRes.prompt_workflow ?? state.embeddedWorkflow);
    } catch (e) {
        renderWorkflowJson(null);
        _updateCopyCanvasBtn();
+        renderImagePromptSection(null);
+        renderDimensionInfo(null);
+        renderPromptTab(null);
    }

    // グループタブ更新
    renderDetailGroup(img);
 }

+function renderDimensionInfo(metaRes) {
+    const el = document.getElementById("wfm-gallery-info-dim");
+    if (!el) return;
+    const parts = [];
+    if (metaRes?.width && metaRes?.height) parts.push(`${metaRes.width}×${metaRes.height}`);
+    if (metaRes?.duration) parts.push(formatDuration(metaRes.duration));
+    el.textContent = parts.length ? parts.join(" · ") : "";
+}
+
+function renderImagePromptSection(imagePrompt) {
+    const section = document.getElementById("wfm-gallery-image-prompt-section");
+    const text = document.getElementById("wfm-gallery-image-prompt-text");
+    if (!section || !text) return;
+    if (imagePrompt) {
+        text.textContent = imagePrompt;
+        section.style.display = "";
+    } else {
+        section.style.display = "none";
+    }
+}
+
 function renderTagsDisplay(tags) {
    const container = document.getElementById("wfm-gallery-tags-display");
    container.innerHTML = "";
@@ -843,6 +1074,44 @@ function renderWorkflowJson(workflow) {
    }
 }

+// 埋め込みワークフローからpositive/negativeプロンプトを抽出してPromptタブに表示する。
+// 複数候補があるケース(PromptStyler等で正負が複数生成される場合)に対応するため、
+// Metadataタブと同じ POS/NEGリスト → クリックで全文表示のUI(buildPromptItem)をそのまま
+// 再利用する。選択画像を切り替えるたびにマウス操作無しで読めるよう、先頭項目を自動選択する。
+function renderPromptTab(workflow) {
+    const listEl = document.getElementById("wfm-gallery-prompt-list");
+    const fullArea = document.getElementById("wfm-gallery-prompt-full");
+    const fullLabel = document.getElementById("wfm-gallery-prompt-full-label");
+    if (!listEl || !fullArea || !fullLabel) return;
+
+    listEl.innerHTML = "";
+    fullArea.value = "";
+    fullLabel.textContent = "";
+
+    if (!workflow) {
+        listEl.innerHTML = `<div class="wfm-meta-item" style="opacity:0.6;">No workflow embedded in this image.</div>`;
+        return;
+    }
+
+    const { positives, negatives, texts } = extractPrompts(workflow);
+    const allPrompts = [
+        ...positives.map(p => ({ type: "positive", text: p })),
+        ...negatives.map(p => ({ type: "negative", text: p })),
+        ...(texts ?? []).map(p => ({ type: "text", text: p })),
+    ];
+
+    if (allPrompts.length === 0) {
+        listEl.innerHTML = `<div class="wfm-meta-item" style="opacity:0.6;">No prompt found.</div>`;
+        return;
+    }
+
+    for (const { type, text } of allPrompts) {
+        listEl.appendChild(buildPromptItem(text, type, text, fullArea, fullLabel, listEl));
+    }
+    // Auto-select first item (positive prompts come first in allPrompts)
+    listEl.querySelector(".wfm-meta-item-clickable")?.click();
+}
+
 // ── タグ操作 ─────────────────────────────────────────────────

 async function addTag(tag) {
@@ -850,7 +1119,8 @@ async function addTag(tag) {
    const tags = [...(state.selectedImage.tags || [])];
    if (tags.includes(tag.trim())) return;
    tags.push(tag.trim());
-    await saveMetaField({ tags });
+    const ok = await saveMetaField({ tags });
+    if (!ok) return;
    state.selectedImage.tags = tags;
    renderTagsDisplay(tags);
    updateTagFilter(state.images);
@@ -859,24 +1129,38 @@ async function addTag(tag) {
 async function removeTag(tag) {
    if (!state.selectedImage) return;
    const tags = (state.selectedImage.tags || []).filter(t => t !== tag);
-    await saveMetaField({ tags });
+    const ok = await saveMetaField({ tags });
+    if (!ok) return;
    state.selectedImage.tags = tags;
    renderTagsDisplay(tags);
    updateTagFilter(state.images);
 }

+// 戻り値: 保存が実際にサーバーへ永続化されたか(true/false)。呼び出し元はこれを見て
+// ローカル状態(state.selectedImage等)の更新可否を判断すること — でないと、サーバーが
+// 保存を拒否した場合にもUI上は成功したように見えてしまう(リロードすると消える不具合の原因)。
 async function saveMetaField(fields) {
-    if (!state.selectedImage) return;
+    if (!state.selectedImage) return false;
    try {
-        await fetch(API.saveImageMeta, {
+        const res = await fetch(API.saveImageMeta, {
            method: "POST",
            headers: { "Content-Type": "application/json" },
            body: JSON.stringify({ path: state.selectedImage.path, ...fields }),
        });
+        if (!res.ok) throw new Error(`HTTP ${res.status}`);
+        const json = await res.json();
+        // サーバー側は常にHTTP 200を返し、成否は body.ok (bool) で表す設計
+        // (gallery_routes.py save_image_meta)。ここをチェックしないと、
+        // 許可パス外などでサーバーが保存を拒否してもUI上は成功したように見えてしまう。
+        if (json.error || json.ok === false) {
+            throw new Error(json.error || "Save rejected by server");
+        }
        const idx = state.images.findIndex(i => i.path === state.selectedImage.path);
        if (idx >= 0) Object.assign(state.images[idx], fields);
+        return true;
    } catch (e) {
        showToast(t("saveFailed", e.message), "error");
+        return false;
    }
 }

@@ -910,6 +1194,33 @@ export async function ensureFeederGroup() {
    }
 }

+/** __Video Assets__ と __Video Temp__ の両方が存在しない場合に作成する。add_to_groupは
+ * 対象グループがレジストリに登録されているかを確認せず画像側にグループ名を書き込むだけの
+ * ため、一度レジストリから消える(例: 予約保護が効く前の版で削除された)と、以後の手動追加は
+ * 画像には記録されてもグループ一覧・フィルタには一切出てこなくなる。VideoタブのAsset
+ * タブ初期化時に呼び、レジストリを確実に存在させる。
+ * （__Video Temp__側もここでensureする — 以前はensureVideoGroupがVIDEO_GROUPしか
+ * 保証しておらず、__Video Temp__のレジストリが何らかの理由で消えると誰も復活させられない
+ * バグがあった。バッチRun開始時のensure（video-plan-tab.jsの_ensureVideoAssetGroups）は
+ * Runするまで呼ばれないため、それだけでは不十分。） */
+export async function ensureVideoGroup() {
+    try {
+        await fetch(API.groupEnsure, {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify({ name: VIDEO_GROUP }),
+        });
+        await fetch(API.groupEnsure, {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify({ name: VTEMP_GROUP }),
+        });
+        await loadGroups();
+    } catch (e) {
+        console.warn("[Gallery] ensureVideoGroup error:", e);
+    }
+}
+
 /** Feederグループ内の全画像を除外する（FC ボタン） */
 async function clearFeederGroup() {
    try {
@@ -924,6 +1235,19 @@ async function clearFeederGroup() {
    }
 }

+/** __Video Temp__グループ内の全画像を除外する（詳細パネルの「Clear __Video Temp__」ボタン） */
+async function clearVtempGroup() {
+    try {
+        await fetch(API.groupClear(VTEMP_GROUP), { method: "POST" });
+        showToast(t("vtempGroupCleared"), "success");
+        if (state.groupFilter === VTEMP_GROUP) {
+            await loadImages();
+        }
+    } catch (e) {
+        showToast(t("errorWithMsg", e.message), "error");
+    }
+}
+
 /** ツールバーのグループフィルタと一括バーのセレクトを更新 */
 function _updateGroupSelects() {
    // ツールバー: グループフィルタ
@@ -1003,15 +1327,16 @@ function renderDetailGroup(img) {
                        ${allGroups.length === 0
                            ? `<option value="">${t("modelsNoGroupAvailable")}</option>`
                            : allGroups.map(g => {
-                                const label = g === FEEDER_GROUP ? `🔒 ${escapeHtml(g)}` : escapeHtml(g);
+                                const label = _isReservedGroup(g) ? `🔒 ${escapeHtml(g)}` : escapeHtml(g);
                                return `<option value="${escapeHtml(g)}">${label}</option>`;
                            }).join("")}
                    </select>
                    <button class="wfm-btn wfm-btn-sm" id="wfm-gallery-grp-rename-btn"
-                        ${allGroups.length === 0 || allGroups[0] === FEEDER_GROUP ? "disabled" : ""} title="${t("modelsRename")}">&#9998;</button>
+                        ${allGroups.length === 0 || _isReservedGroup(allGroups[0]) ? "disabled" : ""} title="${t("modelsRename")}">&#9998;</button>
                    <button class="wfm-btn wfm-btn-sm wfm-btn-danger" id="wfm-gallery-grp-delete-btn"
-                        ${allGroups.length === 0 || allGroups[0] === FEEDER_GROUP ? "disabled" : ""} title="${t("modelsDelete")}">&times;</button>
+                        ${allGroups.length === 0 || _isReservedGroup(allGroups[0]) ? "disabled" : ""} title="${t("modelsDelete")}">&times;</button>
                </div>
+                <button class="wfm-btn wfm-btn-sm" id="wfm-gallery-vtemp-clear-btn" style="width:100%;margin-top:6px;" title="${t("vtempClearBtnTitle")}">${t("vtempClearBtnLabel")}</button>
            </div>
        </div>
    `;
@@ -1090,15 +1415,18 @@ function renderDetailGroup(img) {
        }
    });

-    // 管理セレクト変更時: __Feeder__ は rename/delete を無効化
+    // 管理セレクト変更時: 予約グループ(__Feeder__/__Video Assets__/__Video Temp__)は rename/delete を無効化
    el.querySelector("#wfm-gallery-grp-manage-sel")?.addEventListener("change", (e) => {
-        const isReserved = e.target.value === FEEDER_GROUP;
+        const isReserved = _isReservedGroup(e.target.value);
        const renameBtn = el.querySelector("#wfm-gallery-grp-rename-btn");
        const deleteBtn = el.querySelector("#wfm-gallery-grp-delete-btn");
        if (renameBtn) renameBtn.disabled = isReserved;
        if (deleteBtn) deleteBtn.disabled = isReserved;
    });

+    // Clear __Video Temp__ ボタン: __Video Temp__ グループをクリア(Video Plan実行時に自動登録される生成物置き場)
+    el.querySelector("#wfm-gallery-vtemp-clear-btn")?.addEventListener("click", clearVtempGroup);
+
    // グループ名変更
    el.querySelector("#wfm-gallery-grp-rename-btn")?.addEventListener("click", async () => {
        const sel = el.querySelector("#wfm-gallery-grp-manage-sel");
@@ -1419,9 +1747,12 @@ async function bulkSetFavorite(favoriteValue) {
 function openLightbox(img) {
    const overlay = document.createElement("div");
    overlay.className = "wfm-gallery-lightbox";
+    const mediaHtml = isVideoFile(img)
+        ? `<video src="${API.serveImage(img.path)}" class="wfm-gallery-lightbox-img" controls autoplay></video>`
+        : `<img src="${API.serveImage(img.path)}" class="wfm-gallery-lightbox-img" alt="${escapeHtml(img.filename)}">`;
    overlay.innerHTML = `
        <div class="wfm-gallery-lightbox-inner">
-            <img src="${API.serveImage(img.path)}" class="wfm-gallery-lightbox-img" alt="${escapeHtml(img.filename)}">
+            ${mediaHtml}
            <div class="wfm-gallery-lightbox-footer">${escapeHtml(img.filename)}</div>
            <button class="wfm-gallery-lightbox-close">&times;</button>
        </div>
@@ -1432,6 +1763,7 @@ function openLightbox(img) {
        }
    });
    document.body.appendChild(overlay);
+    if (isVideoFile(img)) applyStoredVideoVolume(overlay.querySelector("video"));
 }

 // ── 画像比較ライトボックス ─────────────────────────────────────
@@ -1443,12 +1775,17 @@ function openCompare(paths) {
    const overlay = document.createElement("div");
    overlay.className = "wfm-gallery-lightbox wfm-lightbox-compare";

-    const itemsHtml = imgs.map(img => `
+    const itemsHtml = imgs.map(img => {
+        const mediaHtml = isVideoFile(img)
+            ? `<video src="${API.serveImage(img.path)}" class="wfm-lightbox-compare-img" controls></video>`
+            : `<img src="${API.serveImage(img.path)}" class="wfm-lightbox-compare-img" alt="${escapeHtml(img.filename)}" loading="lazy">`;
+        return `
        <div class="wfm-lightbox-compare-item">
-            <img src="${API.serveImage(img.path)}" class="wfm-lightbox-compare-img" alt="${escapeHtml(img.filename)}" loading="lazy">
+            ${mediaHtml}
            <div class="wfm-lightbox-compare-label">${escapeHtml(img.filename)}</div>
        </div>
-    `).join("");
+    `;
+    }).join("");

    overlay.innerHTML = `
        <div class="wfm-lightbox-compare-inner">
@@ -1462,6 +1799,7 @@ function openCompare(paths) {
        }
    });
    document.body.appendChild(overlay);
+    overlay.querySelectorAll("video").forEach(applyStoredVideoVolume);
 }

 // ── outputパス取得 ────────────────────────────────────────────
@@ -1501,6 +1839,9 @@ export function initGalleryTab() {
    }

    bindEvents();
+    _initGallerySubtabToggle();
+    initImagePromptTab();
+    initStyleCatalogTab();
 }

 let _initialized = false;
@@ -1512,6 +1853,24 @@ function onGalleryTabActivated() {
    loadGroups();
 }

+// ── サブタブ切替 (Output / ImagePrompt / Style_Catalog / Metadata) ────────────
+
+function _initGallerySubtabToggle() {
+    document.querySelectorAll(".wfm-gallery-subtab-btn").forEach((btn) => {
+        btn.addEventListener("click", () => {
+            const target = btn.dataset.gallerySubtab;
+            document.querySelectorAll(".wfm-gallery-subtab-btn").forEach((b) => b.classList.remove("active"));
+            btn.classList.add("active");
+            document.getElementById("wfm-gallery-panel-output")?.classList.toggle("active", target === "output");
+            document.getElementById("wfm-gallery-panel-imageprompt")?.classList.toggle("active", target === "imageprompt");
+            document.getElementById("wfm-gallery-panel-styleCatalog")?.classList.toggle("active", target === "styleCatalog");
+            document.getElementById("wfm-gallery-panel-metadata")?.classList.toggle("active", target === "metadata");
+            if (target === "imageprompt") activateImagePromptTab();
+            if (target === "styleCatalog") activateStyleCatalogTab();
+        });
+    });
+}
+
 function bindEvents() {
    // リフレッシュ
    document.getElementById("wfm-gallery-refresh-btn")?.addEventListener("click", () => {
@@ -1520,17 +1879,32 @@ function bindEvents() {
    });

    // 選択画像を Image Edit タブへ送信
-    document.getElementById("wfm-gallery-send-image-edit-btn")?.addEventListener("click", () => {
+    document.getElementById("wfm-gallery-send-image-edit-btn")?.addEventListener("click", async () => {
        if (!state.selectedImage) {
            showToast("Please select an image first", "info");
            return;
        }
-        const url  = API.serveImage(state.selectedImage.path);
+        if (!window._wfmImageEditTab) return;
+        const path = state.selectedImage.path;
        const name = (state.selectedImage.filename || "gallery-image").replace(/\.[^.]+$/, "");
-        if (window._wfmImageEditTab) {
-            document.querySelector('[data-tab="image-edit"]')?.click();
-            window._wfmImageEditTab.loadFromUrl(url, name);
+
+        // PSDはフラット画像1枚ではなくレイヤー分解して送る(Open PSDボタンと同じ経路)
+        if (/\.psd$/i.test(path)) {
+            try {
+                const r = await fetch(`/wfm/gallery/image/psd-layers?path=${encodeURIComponent(path)}`);
+                if (!r.ok) throw new Error((await r.json().catch(() => ({}))).error || r.statusText);
+                const data = await r.json();
+                document.querySelector('[data-tab="image-edit"]')?.click();
+                await window._wfmImageEditTab.loadPsdLayersData(data, name);
+            } catch (err) {
+                showToast(`PSD import failed: ${err.message}`, "error");
+            }
+            return;
        }
+
+        const url = API.serveImage(path);
+        document.querySelector('[data-tab="image-edit"]')?.click();
+        window._wfmImageEditTab.loadFromUrl(url, name);
    });

    // 選択画像を GenerateUI Image タブへ送信
@@ -1566,6 +1940,34 @@ function bindEvents() {
        }
    });

+    // 選択画像をComfyUIキャンバス上で選択中のノード（LoadImage系）のimageウィジェットへ送信。
+    // Image Editタブの「Send to LI node」と同じ橋渡し(window.opener.wfmSendImageToSelectedNode、
+    // node_sets_menu.js側で定義)を使う。Galleryの画像はGalleryルート配下の任意フォルダにあり得るため、
+    // GenUI送信と違いLoadImageノードの有無に依存しない — /upload/imageでinputフォルダへ
+    // アップロードしてから、そのファイル名を書き込む。
+    document.getElementById("wfm-gallery-send-li-node-btn")?.addEventListener("click", async () => {
+        if (!state.selectedImage) {
+            showToast(t("gallerySelectImageFirst"), "info");
+            return;
+        }
+        if (!window.opener || typeof window.opener.wfmSendImageToSelectedNode !== "function") {
+            showToast(t("sendToLiNodeNoOpener"), "error");
+            return;
+        }
+        try {
+            const res = await fetch(API.serveImage(state.selectedImage.path));
+            if (!res.ok) throw new Error(`HTTP ${res.status}`);
+            const blob = await res.blob();
+            const file = new File([blob], state.selectedImage.filename || "gallery-image.png", { type: blob.type || "image/png" });
+            const result = await comfyUI.uploadImage(file, file.name);
+            const filename = result.subfolder ? `${result.subfolder}/${result.name}` : result.name;
+            window.opener.wfmSendImageToSelectedNode(filename);
+            showToast(t("sendToLiNodeSuccess", filename), "success");
+        } catch (e) {
+            showToast(t("errorWithMsg", e.message), "error");
+        }
+    });
+
    // 選択画像を ComfyUI Comic Creator の選択コマ／オーバーレイへ送信
    // （ComfyUI Comic CreaterからこのGalleryタブがiframe埋め込みされている場合のみ表示・動作する）
    const sendCcBtn = document.getElementById("wfm-gallery-send-cc-btn");
@@ -1584,6 +1986,7 @@ function bindEvents() {
                return;
            }
            const url = API.serveImage(state.selectedImage.path);
+            const isVideo = isVideoFile(state.selectedImage);

            // I2I送信元がImageタブだった場合はそちらへ画像を読み込ませる（_ccI2ITargetModeはComic Creater側が
            // 「I2Iへ送る」ボタン押下時にセットするフラグ。undefined/'layout'なら従来通りコマ/オーバーレイへ挿入）
@@ -1594,6 +1997,11 @@ function bindEvents() {
                targetMode = null;
            }
            if (targetMode === "image") {
+                // Imageタブは動画未対応（Comic Creator側の動画ツールはレイアウトタブのみ対応）
+                if (isVideo) {
+                    showToast(t("galleryVideoNotSupportedInImageTab"), "info");
+                    return;
+                }
                let imageTab = null;
                try {
                    if (window.parent && window.parent !== window && typeof window.parent._ccImageTab?.loadFromUrl === "function") {
@@ -1611,6 +2019,26 @@ function bindEvents() {
                return;
            }

+            // レイアウトタブのコマ/オーバーレイへ（デフォルト経路）。動画（.mp4）はComic Creator側の
+            // 動画ツール専用の受け口（insertVideoFromUrl）へ、それ以外は従来通り画像として送る
+            if (isVideo) {
+                let insertVideoFn = null;
+                try {
+                    if (window.parent && window.parent !== window && typeof window.parent.insertVideoFromUrl === "function") {
+                        insertVideoFn = window.parent.insertVideoFromUrl;
+                    }
+                } catch (e) {
+                    insertVideoFn = null;
+                }
+                if (!insertVideoFn) {
+                    showToast(t("galleryCCNotAvailable"), "info");
+                    return;
+                }
+                insertVideoFn(url, state.selectedImage.filename || "video.mp4");
+                showToast(t("gallerySentCC"), "success");
+                return;
+            }
+
            let insertFn = null;
            try {
                if (window.parent && window.parent !== window && typeof window.parent.insertImageFromUrl === "function") {
@@ -1628,12 +2056,15 @@ function bindEvents() {
        });
    }

-    // 検索
+    // 検索（連続キー入力のたびにリクエストを飛ばすと、50枚程度のフォルダでも
+    // ファイルI/Oの重いサーバー処理が積み重なって読み込みが遅延するためdebounceする）
    document.getElementById("wfm-gallery-search")?.addEventListener("input", (e) => {
        state.search = e.target.value;
-        loadImages();
+        clearTimeout(_searchDebounceTimer);
+        _searchDebounceTimer = setTimeout(loadImages, SEARCH_DEBOUNCE_MS);
    });
    setupSearchClearBtn("wfm-gallery-search", "wfm-gallery-search-clear-btn", () => {
+        clearTimeout(_searchDebounceTimer);
        state.search = "";
        loadImages();
    });
@@ -1699,7 +2130,7 @@ function bindEvents() {
    // メモ保存
    document.getElementById("wfm-gallery-memo-save-btn")?.addEventListener("click", () => {
        const memo = document.getElementById("wfm-gallery-memo").value;
-        saveMetaField({ memo }).then(() => showToast(t("memoSaved"), "success"));
+        saveMetaField({ memo }).then((ok) => { if (ok) showToast(t("memoSaved"), "success"); });
    });

    // ワークフローコピー＆キャンバスへ送る
@@ -1713,7 +2144,7 @@ function bindEvents() {
            if (window.opener && typeof window.opener.wfmReceiveWorkflow === "function") {
                window.opener.wfmReceiveWorkflow(state.embeddedWorkflow);
                await navigator.clipboard.writeText(JSON.stringify(state.embeddedWorkflow, null, 2)).catch(() => {});
-                showToast(t("workflowSentToCanvas"), "success");
+                showToast(t("workflowSentToCanvasDirect"), "success");
                return;
            }
            // フォールバック: localStorage + タイトルドラッグ（UI形式のみ）
@@ -1787,6 +2218,36 @@ function bindEvents() {
        exportSelectedImagesToZip([...state.selectedImages]);
    });

+    document.getElementById("wfm-gallery-bulk-psd")?.addEventListener("click", () => {
+        if (state.selectedImages.size === 0) return;
+        exportSelectedImagesToPsd([...state.selectedImages]);
+    });
+
+    document.getElementById("wfm-gallery-bulk-edit-layers")?.addEventListener("click", () => {
+        if (state.selectedImages.size === 0) return;
+        if (!window._wfmImageEditTab) return;
+
+        const allPaths = [...state.selectedImages];
+        const paths    = allPaths.filter(p => !/\.mp4$/i.test(p));
+        if (paths.length === 0) {
+            showToast(t("editLayersNoImages"), "error");
+            return;
+        }
+
+        const items = paths.map(p => {
+            const img      = state.images.find(i => i.path === p);
+            const filename = img?.filename || p.split(/[\\/]/).pop() || "layer";
+            return { url: API.serveImage(p), name: filename.replace(/\.[^.]+$/, "") };
+        });
+
+        document.querySelector('[data-tab="image-edit"]')?.click();
+        window._wfmImageEditTab.loadLayersFromUrls(items);
+
+        if (paths.length < allPaths.length) {
+            showToast(t("editLayersSkippedVideo", allPaths.length - paths.length), "info");
+        }
+    });
+
    document.getElementById("wfm-gallery-bulk-delete")?.addEventListener("click", () => {
        if (state.selectedImages.size === 0) return;
        const count = state.selectedImages.size;
@@ -1832,6 +2293,16 @@ function bindEvents() {
        openImageInTaggerTab(state.selectedImage);
    });

+    // Downloadボタン: プレビューのオーバーレイだと動画の再生コントロール操作を妨げるため、
+    // アクションボタン行に常時表示のボタンとして配置している
+    document.getElementById("wfm-gallery-download-btn")?.addEventListener("click", () => {
+        if (!state.selectedImage) {
+            showToast(t("gallerySelectImageFirst"), "error");
+            return;
+        }
+        downloadImage(state.selectedImage);
+    });
+
    // Load in GenerateUI ボタン: 埋め込みワークフローをGenerateUIタブに読み込む
    document.getElementById("wfm-gallery-load-genui-btn")?.addEventListener("click", async () => {
        if (!state.selectedImage) {
@@ -1871,6 +2342,7 @@ function bindEvents() {
    if (galleryClearBtn) {
        galleryClearBtn.textContent = t("clearFilters");
        galleryClearBtn.addEventListener("click", () => {
+            clearTimeout(_searchDebounceTimer);
            state.search = "";
            state.favoriteOnly = false;
            state.tagFilter = "";
@@ -9,44 +9,9 @@ import { comfyEditor } from "./comfyui-editor.js";
 import { t } from "./i18n.js";
 import { syncJsonHighlight, syncScroll } from "./json-highlight.js";
 import { initFeederTab, refreshFeederNodeList } from "./feeder-tab.js";
-import { getSettings, readJsonStorage } from "./util.js";
-
-// ============================================
-// Eagle Auto-Save
-// ============================================
-
-function getEagleSettings() {
-    const s = getSettings();
-    return {
-        url: s.eagleUrl || "http://localhost:41595",
-        autoSave: !!s.eagleAutoSave,
-    };
-}
-
-async function saveToEagle(imageUrl, name, tags = []) {
-    const eagle = getEagleSettings();
-    if (!eagle.autoSave) return;
-    try {
-        const res = await fetch("/api/wfm/eagle/add", {
-            method: "POST",
-            headers: { "Content-Type": "application/json" },
-            body: JSON.stringify({
-                eagleUrl: eagle.url,
-                url: imageUrl,
-                name,
-                tags: ["wfm-comfyui", ...tags],
-            }),
-        });
-        const data = await res.json();
-        if (data.status === "success") {
-            console.log("[Eagle] Saved:", name);
-        } else {
-            console.warn("[Eagle] Save failed:", data.message);
-        }
-    } catch (err) {
-        console.warn("[Eagle] Save error:", err.message);
-    }
-}
+import { initLabTab, refreshLabLiveDefaults } from "./lab-tab.js";
+import { getSettings, readJsonStorage, escapeHtml, getEagleSettings, saveToEagle } from "./util.js";
+import { isVideoFilename } from "./video-utils.js";

 // ============================================
 // Gallery Metadata - ワークフロー保存
@@ -200,6 +165,17 @@ async function saveCurrentWorkflow() {
                    nameEl.dataset.filename = filename;
                }
            }
+
+            // このファイル名が「デフォルトワークフロー」(workflow-tab.jsの「デフォルトに設定」で
+            // localStorageにスナップショットされたAPI形式JSON、ページ起動時に自動読込される)に
+            // 一致する場合、保存内容と食い違ったまま残らないようスナップショットも更新する。
+            // 更新しないと、ここで上書き保存しても次回リロード時に古いモデル等が復活する。
+            const settings = getSettings();
+            if (settings.defaultWorkflow === filename) {
+                settings.defaultWorkflowData = workflow;
+                localStorage.setItem("wfm_settings", JSON.stringify(settings));
+            }
+
            showToast(t("savedAs", filename), "success");
        } catch (err) {
            showToast(t("saveFailed", err.message), "error");
@@ -267,7 +243,9 @@ export async function loadWorkflowIntoEditor(workflow, filename) {
    comfyUI.currentAnalysis = comfyWorkflow.analyzeWorkflow(apiWorkflow);

    // Render editor tabs
-    comfyEditor.renderAll(comfyUI.currentAnalysis, apiWorkflow);
+    // resetStackMode: 新規ワークフロー読み込み時のみ、LoraManagerノードのloras/text状態を
+    // スナップショットし、Stackグループ使用チェックボックスをOFFへリセットする
+    comfyEditor.renderAll(comfyUI.currentAnalysis, apiWorkflow, { resetStackMode: true });

    // Update raw JSON with highlight
    const rawTextarea = document.getElementById("wfm-gen-raw-json");
@@ -278,6 +256,30 @@ export async function loadWorkflowIntoEditor(workflow, filename) {
        syncJsonHighlight(rawHighlight, jsonStr);
    }

+    // Update Bypass/Mute node indicator (shared Raw JSON widget header, visible on
+    // Input/Model/Settings tabs). API-format JSON has no mode field, so this info is
+    // only available right after a UI→API conversion — captured via comfyWorkflow's
+    // getLastBypassedNodes()/getLastMutedNodes() before it's discarded.
+    const bypassNote = document.getElementById("wfm-gen-rawjson-bypass-note");
+    if (bypassNote) {
+        const bypassed = format === "ui" ? comfyWorkflow.getLastBypassedNodes() : [];
+        const muted = format === "ui" ? comfyWorkflow.getLastMutedNodes() : [];
+        const lines = [];
+        if (bypassed.length > 0) {
+            lines.push(t("rawJsonBypassNote", bypassed.map((n) => `${n.title} (${n.nodeId})`).join(", ")));
+        }
+        if (muted.length > 0) {
+            lines.push(t("rawJsonMutedNote", muted.map((n) => `${n.title} (${n.nodeId})`).join(", ")));
+        }
+        if (lines.length > 0) {
+            bypassNote.innerHTML = lines.map((l) => escapeHtml(l)).join("<br>");
+            bypassNote.style.display = "";
+        } else {
+            bypassNote.textContent = "";
+            bypassNote.style.display = "none";
+        }
+    }
+
    // Update workflow name display
    const nameEl = document.getElementById("wfm-gen-wf-name");
    if (nameEl) {
@@ -291,6 +293,13 @@ export async function loadWorkflowIntoEditor(workflow, filename) {

    refreshFeederNodeList();

+    // Lab subtab may already be the active one (e.g. it was active when this workflow
+    // was loaded) — the subtab-click handler that normally triggers this refresh never
+    // fires in that case, leaving Setting 1's live-reflected cells showing the previous
+    // workflow until the user clicks a cell or revisits the subtab.
+    const activeSubtab = document.querySelector(".wfm-gen-subtab-btn.active")?.dataset.subtab;
+    if (activeSubtab === "lab") refreshLabLiveDefaults();
+
    if (ckptWarning) {
        showToast(ckptWarning, "error");
    } else {
@@ -1275,6 +1284,12 @@ async function _loadStyles() {
    _rebuildStyleList();
 }

+// Promptタブ「Style」サブタブでスタイルを作成・編集・削除した後に呼ばれる。
+// GenerateUIのStyleドロップダウン・Batchタブのチェックリストを最新の状態へ再同期する。
+export async function refreshStylesList() {
+    await _loadStyles();
+}
+
 function _renderStyleDropdown() {
    const sel = document.getElementById("wfm-style-select");
    if (!sel) return;
@@ -1303,6 +1318,21 @@ function _rebuildStyleList() {
    );
 }

+// Style Catalogギャラリーの「Select as Style」から呼ばれる。名前が一致する登録済み
+// Styleを探し、GenerateUIのStyleドロップダウンをそれに切り替えてタブへ移動する。
+// 画像に埋め込まれたプロンプトを直接適用するのではなく、既存Styleシステムへの
+// 視覚的なショートカットとして機能する（元のStyle JSONが変更・削除されても影響を受けない）。
+export function selectStyleByName(name) {
+    const style = _stylesData.find((s) => s.name === name);
+    if (!style) return false;
+    const sel = document.getElementById("wfm-style-select");
+    if (sel) sel.value = name;
+    const enabled = document.getElementById("wfm-style-enabled");
+    if (enabled) enabled.checked = true;
+    document.querySelector('.wfm-tab[data-tab="generate"]')?.click();
+    return true;
+}
+
 function _applyNamedStyle(workflow, style) {
    if (!style) return workflow;
    const analysis = comfyUI.currentAnalysis;
@@ -1403,7 +1433,7 @@ async function _expandWildcardText(text) {

 const _IMPACT_WC_TYPES = new Set(["ImpactWildcardEncode", "ImpactWildcardProcessor"]);

-async function _expandWildcardsInWorkflow(workflow) {
+export async function _expandWildcardsInWorkflow(workflow) {
    let hasWildcard = false;
    outer: for (const node of Object.values(workflow)) {
        if (_IMPACT_WC_TYPES.has(node.class_type)) continue;
@@ -1432,26 +1462,38 @@ async function _expandWildcardsInWorkflow(workflow) {
 // Generation (core — throws on error)
 // ============================================

-async function _coreGenerate(silent = false, workflowOverride = null) {
+async function _coreGenerate(silent = false, workflowOverride = null, genOptions = {}) {
    const progressBar = document.getElementById("wfm-gen-progress-bar");
    const progressText = document.getElementById("wfm-gen-progress-text");
    const resultImg = document.getElementById("wfm-gen-result-img");
+    const resultVideo = document.getElementById("wfm-gen-result-video");
    const resultThumbs = document.getElementById("wfm-gen-result-thumbs");

-    const seedMode = document.getElementById("wfm-gen-seed-mode")?.value || "random";
-    const seedValue = parseInt(document.getElementById("wfm-gen-seed-value")?.value) || -1;
+    // genOptions.seedValue lets a caller (e.g. AI TOOL Chat's generate_image tool)
+    // force a specific seed on an override workflow without touching the GenerateUI
+    // seed fields — those still drive normal (non-override) generation as before.
+    const seedMode = genOptions.seedValue != null ? "fixed" : (document.getElementById("wfm-gen-seed-mode")?.value || "random");
+    const seedValue = genOptions.seedValue ?? (parseInt(document.getElementById("wfm-gen-seed-value")?.value) || -1);

    if (progressBar) progressBar.style.width = "0%";
    if (progressText) progressText.textContent = "Starting...";

+    // Style must be applied *before* wildcard expansion so a __name__ reference written
+    // inside a Style's prompt/negative_prompt also gets expanded, not just wildcards
+    // already present in the base workflow's prompt nodes.
    const baseWorkflow = workflowOverride || comfyUI.currentWorkflow;
-    const workflowExpanded = await _expandWildcardsInWorkflow({ ...baseWorkflow });
-    const workflowForGenerate = _applyStyleToWorkflow(workflowExpanded);
-    const { images, seed } = await comfyUI.generate(
+    const workflowStyled = _applyStyleToWorkflow({ ...baseWorkflow });
+    const workflowForGenerate = await _expandWildcardsInWorkflow(workflowStyled);
+    // Video workflows (e.g. MiniMax H3) run far longer than a still image — use a longer
+    // timeout so a multi-minute generation doesn't get force-rejected mid-run (see
+    // comfyWorkflow.isVideoWorkflow and video-tab.js's own 30-minute timeout).
+    const isVideo = comfyWorkflow.isVideoWorkflow(comfyUI.currentAnalysis);
+    const { images, seed, svgOutputs } = await comfyUI.generate(
        workflowForGenerate,
        {
            seedMode,
            seedValue,
+            timeoutMs: isVideo ? 30 * 60 * 1000 : undefined,
            onProgress: (pct) => {
                if (progressBar) progressBar.style.width = `${(pct * 100).toFixed(1)}%`;
                if (progressText) progressText.textContent = `${(pct * 100).toFixed(0)}%`;
@@ -1465,24 +1507,68 @@ async function _coreGenerate(silent = false, workflowOverride = null) {
    if (progressText) progressText.textContent = `Done (${images.length} image${images.length !== 1 ? "s" : ""})`;
    if (progressBar) progressBar.style.width = "100%";

-    if (images.length > 0) {
-        const blob = await comfyUI.getImageBlob(images[0]);
-        const url = URL.createObjectURL(blob);
-        if (resultImg) {
-            resultImg.src = url;
+    // type=temp はプレビュー用の一時画像 (PreviewImage, SVG String Preview など) のため
+    // 生成結果表示からは除外し、実際に保存された成果物のみを表示する
+    const outputImages = images.filter((img) => img.type !== "temp");
+
+    if (svgOutputs?.length > 0) {
+        // comfyui-tosvg の Save SVG String は images ではなく saved_svg/path で返すため、
+        // images配列には(あれば)プレビュー用の一時PNGしか入らず実際の保存物と食い違う。
+        // 実際に保存されたSVGファイルをそのままプレビューに表示する。
+        // /view はSVGをセキュリティ上application/octet-streamで返すため使えず、
+        // 代わりにGalleryタブの配信エンドポイント(絶対パス指定・正しいContent-Type)を使う。
+        const svgUrl = (svg) => `/wfm/gallery/image/serve?path=${encodeURIComponent(svg.path)}`;
+        if (resultImg && svgOutputs[0].path) {
+            resultImg.src = svgUrl(svgOutputs[0]);
            resultImg.style.display = "block";
        }

-        if (resultThumbs && images.length > 1) {
+        if (resultThumbs && svgOutputs.length > 1) {
            resultThumbs.innerHTML = "";
-            for (let i = 0; i < images.length; i++) {
-                const b = i === 0 ? blob : await comfyUI.getImageBlob(images[i]);
-                const u = i === 0 ? url : URL.createObjectURL(b);
+            svgOutputs.forEach((svg, i) => {
+                if (!svg.path) return;
                const thumb = document.createElement("img");
-                thumb.src = u;
+                thumb.src = svgUrl(svg);
                thumb.className = `wfm-gen-thumb ${i === 0 ? "active" : ""}`;
                thumb.addEventListener("click", () => {
-                    resultImg.src = u;
+                    resultImg.src = thumb.src;
+                    resultThumbs.querySelectorAll(".wfm-gen-thumb").forEach((t) => t.classList.remove("active"));
+                    thumb.classList.add("active");
+                });
+                resultThumbs.appendChild(thumb);
+            });
+        }
+    } else if (outputImages.length > 0) {
+        // Video outputs (SaveVideo/PreviewVideo, e.g. MiniMax H3) come back through the
+        // same {"images":[...]} shape as still images — dispatch to <video> vs <img>
+        // per-item by extension rather than assuming the whole batch is one media type.
+        const showMedia = (blob, filename) => {
+            const url = URL.createObjectURL(blob);
+            if (isVideoFilename(filename)) {
+                if (resultVideo) { resultVideo.src = url; resultVideo.style.display = "block"; }
+                if (resultImg) resultImg.style.display = "none";
+            } else {
+                if (resultImg) { resultImg.src = url; resultImg.style.display = "block"; }
+                if (resultVideo) { resultVideo.pause(); resultVideo.style.display = "none"; }
+            }
+        };
+
+        const blob = await comfyUI.getImageBlob(outputImages[0]);
+        showMedia(blob, outputImages[0].filename);
+
+        if (resultThumbs && outputImages.length > 1) {
+            resultThumbs.innerHTML = "";
+            for (let i = 0; i < outputImages.length; i++) {
+                const b = i === 0 ? blob : await comfyUI.getImageBlob(outputImages[i]);
+                const filename = outputImages[i].filename;
+                const u = URL.createObjectURL(b);
+                const isVid = isVideoFilename(filename);
+                const thumb = document.createElement(isVid ? "video" : "img");
+                thumb.src = u;
+                if (isVid) thumb.muted = true;
+                thumb.className = `wfm-gen-thumb ${i === 0 ? "active" : ""}`;
+                thumb.addEventListener("click", () => {
+                    showMedia(b, filename);
                    resultThumbs.querySelectorAll(".wfm-gen-thumb").forEach((t) => t.classList.remove("active"));
                    thumb.classList.add("active");
                });
@@ -1491,10 +1577,18 @@ async function _coreGenerate(silent = false, workflowOverride = null) {
        }
    }

-    if (getEagleSettings().autoSave && images.length > 0) {
-        for (const img of images) {
+    if (getEagleSettings().autoSave && outputImages.length > 0) {
+        for (const img of outputImages) {
            const viewUrl = `/view?filename=${encodeURIComponent(img.filename)}&subfolder=${encodeURIComponent(img.subfolder || "")}&type=${encodeURIComponent(img.type || "output")}`;
-            saveToEagle(viewUrl, img.filename);
+            saveToEagle(viewUrl, img.filename, [], img);
+        }
+    }
+
+    if (getEagleSettings().autoSave && svgOutputs?.length > 0) {
+        // comfyui-tosvg の "Save SVG String" は絶対パスを直接返すため、/view を介さず
+        // サーバー側でそのパスを検証した上で addFromPath させる
+        for (const svg of svgOutputs) {
+            saveToEagle("", svg.filename, [], { filename: svg.filename, localPath: svg.path });
        }
    }

@@ -1512,7 +1606,9 @@ async function _coreGenerate(silent = false, workflowOverride = null) {
 // ============================================

 // 汎用バッチループ: items を順に applyFn(item) → _coreGenerate() で処理する
-async function _runBatchLoop(items, applyFn, labelFn = (x) => String(x)) {
+// onResultFn(item, {images, seed}) が渡された場合、各アイテムの生成結果ごとに呼び出す
+// （Style Catalogのカタログ作成が、生成画像をスタイル名で保存するために使用）
+async function _runBatchLoop(items, applyFn, labelFn = (x) => String(x), onResultFn = null) {
    const batchProgress   = document.getElementById("wfm-ckpt-batch-progress");
    const batchCurrentName = document.getElementById("wfm-ckpt-batch-current-name");
    const batchCount      = document.getElementById("wfm-ckpt-batch-count");
@@ -1547,7 +1643,8 @@ async function _runBatchLoop(items, applyFn, labelFn = (x) => String(x)) {

            try {
                await applyFn(item);
-                await _coreGenerate(true);
+                const result = await _coreGenerate(true);
+                if (onResultFn) await onResultFn(item, result);
                completed++;
            } catch (err) {
                if (_ckptBatch.aborted) break;
@@ -1576,6 +1673,157 @@ async function _runBatchLoop(items, applyFn, labelFn = (x) => String(x)) {
    }
 }

+// ============================================
+// Style Catalog 作成
+// ============================================
+// Batchタブ「Style」サブタブで選択済みのスタイル(_batchStyleSelected)を対象に、
+// 現在ロード中のワークフローでそれぞれ生成し、結果をスタイル名でws_style_catalog
+// 配下の指定フォルダへ保存する（Style Catalogギャラリーからの視覚的スタイル選択に使う）。
+
+function _blobToDataUrl(blob) {
+    return new Promise((resolve, reject) => {
+        const reader = new FileReader();
+        reader.onload = () => resolve(reader.result);
+        reader.onerror = reject;
+        reader.readAsDataURL(blob);
+    });
+}
+
+function _flattenFolderTree(node, acc = [], isRoot = true) {
+    acc.push({ path: isRoot ? "[root]" : node.path, abs_path: node.abs_path });
+    (node.children || []).forEach((c) => _flattenFolderTree(c, acc, false));
+    return acc;
+}
+
+async function openCatalogCreateModal() {
+    const list = _stylesData.filter((s) => _batchStyleSelected.has(s.name));
+    if (list.length === 0) {
+        showToast(t("catalogCreateNoStyles"), "error");
+        return;
+    }
+
+    let catalogRoot = null;
+    let folderTree = null;
+    try {
+        const rootRes = await fetch("/wfm/gallery/style-catalog/root");
+        const rootData = await rootRes.json();
+        catalogRoot = rootData.root;
+        if (!catalogRoot) throw new Error(rootData.error || "Style Catalog root not resolved");
+        const treeRes = await fetch(`/wfm/gallery/folders?root=${encodeURIComponent(catalogRoot)}`);
+        folderTree = await treeRes.json();
+    } catch (e) {
+        showToast(t("errorWithMsg", e.message), "error");
+        return;
+    }
+
+    const folderOptions = folderTree && !folderTree.error ? _flattenFolderTree(folderTree) : [];
+
+    const html = `
+        <p style="margin:0 0 10px;font-size:13px;color:var(--wfm-text-secondary);">${t("catalogCreateSelectedCount", list.length)}</p>
+        <div style="display:flex;flex-direction:column;gap:8px;">
+            <label style="display:flex;align-items:center;gap:6px;">
+                <input type="radio" name="wfm-catalog-dest" value="new" checked>
+                ${t("catalogCreateNewFolder")}
+            </label>
+            <input type="text" id="wfm-catalog-new-folder-name" class="wfm-input" placeholder="folder name" style="margin-left:22px;">
+            <label style="display:flex;align-items:center;gap:6px;">
+                <input type="radio" name="wfm-catalog-dest" value="existing" ${folderOptions.length === 0 ? "disabled" : ""}>
+                ${t("catalogCreateExistingFolder")}
+            </label>
+            <select id="wfm-catalog-existing-folder" class="wfm-input" style="margin-left:22px;" ${folderOptions.length === 0 ? "disabled" : ""}>
+                ${folderOptions.map((f) => `<option value="${escapeHtml(f.abs_path)}">${escapeHtml(f.path)}</option>`).join("")}
+            </select>
+            <hr class="wfm-group-divider" style="margin:4px 0;">
+            <label style="display:flex;align-items:center;gap:6px;">
+                <input type="checkbox" id="wfm-catalog-skip-output">
+                ${t("catalogCreateSkipOutput")}
+            </label>
+        </div>
+        <button id="wfm-catalog-run-btn" class="wfm-btn wfm-btn-primary" style="width:100%;margin-top:14px;">${t("catalogCreateRun")}</button>
+    `;
+    openModal(t("catalogCreateTitle"), html);
+
+    document.getElementById("wfm-catalog-run-btn")?.addEventListener("click", async () => {
+        const destType = document.querySelector('input[name="wfm-catalog-dest"]:checked')?.value;
+        let destFolder = null;
+
+        if (destType === "new") {
+            const name = document.getElementById("wfm-catalog-new-folder-name")?.value.trim();
+            if (!name) {
+                showToast(t("catalogCreateFolderNameRequired"), "error");
+                return;
+            }
+            try {
+                const res = await fetch("/wfm/gallery/folder", {
+                    method: "POST",
+                    headers: { "Content-Type": "application/json" },
+                    body: JSON.stringify({ parent: catalogRoot, name }),
+                });
+                const data = await res.json();
+                if (!data.ok) throw new Error(data.error || "Failed to create folder");
+                destFolder = data.path;
+            } catch (e) {
+                showToast(t("errorWithMsg", e.message), "error");
+                return;
+            }
+        } else {
+            destFolder = document.getElementById("wfm-catalog-existing-folder")?.value || null;
+            if (!destFolder) {
+                showToast(t("catalogCreateFolderRequired"), "error");
+                return;
+            }
+        }
+
+        const skipOutput = document.getElementById("wfm-catalog-skip-output")?.checked || false;
+
+        closeModal();
+        await _runCatalogCreate(list, destFolder, skipOutput);
+    });
+}
+
+async function _runCatalogCreate(list, destFolder, skipOutput) {
+    try {
+        await _runBatchLoop(
+            list,
+            (style) => { _batchStyleOverride = style; },
+            (s) => s.name,
+            async (style, result) => {
+                const outputImages = (result?.images || []).filter((img) => img.type !== "temp");
+                if (outputImages.length === 0) return;
+                const srcImage = outputImages[0];
+                const blob = await comfyUI.getImageBlob(srcImage);
+                const dataUrl = await _blobToDataUrl(blob);
+                const res = await fetch("/wfm/gallery/image/save-to-folder", {
+                    method: "POST",
+                    headers: { "Content-Type": "application/json" },
+                    body: JSON.stringify({ folder: destFolder, filename: style.name, imageData: dataUrl }),
+                });
+                const data = await res.json();
+                if (!data.ok) throw new Error(data.error || "Failed to save catalog image");
+
+                // Outputフォルダに元画像を残さないオプション: カタログへのコピー保存が
+                // 成功した後にのみ、ComfyUIのOutputフォルダ側の元ファイルを削除する
+                // （コピー失敗時は削除せず、元画像を保持したままにする）
+                if (skipOutput) {
+                    try {
+                        await fetch("/wfm/gallery/output-image/delete", {
+                            method: "POST",
+                            headers: { "Content-Type": "application/json" },
+                            body: JSON.stringify({
+                                filename: srcImage.filename,
+                                subfolder: srcImage.subfolder || "",
+                                type: srcImage.type || "output",
+                            }),
+                        });
+                    } catch { /* 削除失敗はカタログ作成自体を止めない */ }
+                }
+            }
+        );
+    } finally {
+        _batchStyleOverride = null;
+    }
+}
+
 // アクティブなバッチタイプに応じてバッチを実行するディスパッチャ
 async function _runBatchGenerate() {
    switch (_activeBatchType) {
@@ -1768,9 +2016,11 @@ async function _runBatchGenerate() {
 // ============================================

 // workflowOverride: 明示的に渡された場合、comfyUI.currentWorkflow の代わりにこのワークフローで
-// 生成する（GenerateUIの表示状態には触れない。Image Edit「Inpaint」の専用ワークフロー実行から利用）。
+// 生成する（GenerateUIの表示状態には触れない。Image Edit「Inpaint」の専用ワークフロー実行や
+// AI TOOL Chatのgenerate_imageツールから利用）。
+// genOptions: 現状 seedValue のみ（指定時は_coreGenerateがseedMode "fixed"扱いにする）。
 // ボタンのclickハンドラから呼ばれる場合は第一引数がMouseEventになるため、その場合は無視する。
-async function handleGenerate(workflowOverride = null) {
+async function handleGenerate(workflowOverride = null, genOptions = {}) {
    if (workflowOverride instanceof Event) workflowOverride = null;

    if (!workflowOverride && !comfyUI.currentWorkflow) {
@@ -1799,7 +2049,7 @@ async function handleGenerate(workflowOverride = null) {
            await _runBatchGenerate();
        } else {
            try {
-                return await _coreGenerate(false, workflowOverride);
+                return await _coreGenerate(false, workflowOverride, genOptions);
            } catch (err) {
                const progressText = document.getElementById("wfm-gen-progress-text");
                if (progressText) progressText.textContent = "Error";
@@ -1864,6 +2114,25 @@ export async function initGenerateTab() {
        }
    });

+    // Style Catalog 作成ボタン
+    const catalogCreateBtn = document.getElementById("wfm-gen-catalog-create-btn");
+    if (catalogCreateBtn) {
+        catalogCreateBtn.textContent = t("catalogCreateBtn");
+        catalogCreateBtn.addEventListener("click", () => {
+            openCatalogCreateModal().catch((e) => showToast(t("errorWithMsg", e.message), "error"));
+        });
+    }
+
+    // Style Catalog を開くボタン（Gallery タブ → Style_Catalog サブタブへ遷移）
+    const catalogOpenBtn = document.getElementById("wfm-gen-catalog-open-btn");
+    if (catalogOpenBtn) {
+        catalogOpenBtn.textContent = t("catalogOpenBtn");
+        catalogOpenBtn.addEventListener("click", () => {
+            document.querySelector('.wfm-tab[data-tab="gallery"]')?.click();
+            document.querySelector('.wfm-gallery-subtab-btn[data-gallery-subtab="styleCatalog"]')?.click();
+        });
+    }
+
    // Generate button
    document.getElementById("wfm-gen-generate-btn")?.addEventListener("click", () => {
        handleGenerate().catch(() => {});
@@ -1892,7 +2161,7 @@ export async function initGenerateTab() {
    function moveRawJsonToTab(tabKey) {
        const widget = document.getElementById("wfm-gen-rawjson-widget");
        if (!widget) return;
-        if (tabKey === "feeder" || tabKey === "batch") {
+        if (tabKey === "feeder" || tabKey === "batch" || tabKey === "lab") {
            widget.style.display = "none";
            return;
        }
@@ -1916,6 +2185,17 @@ export async function initGenerateTab() {
            if (target === "model" && comfyUI.currentAnalysis) {
                comfyEditor.renderLoraPane(comfyUI.currentAnalysis, "wfm-gen-lora-fields");
            }
+            // Re-render Lab's column grid so Setting 1's live-reflected cells (checkpoint/
+            // VAE/prompt/KSampler) pick up whatever is currently loaded in GenerateUI, not
+            // whatever was loaded the last time Lab was rendered.
+            if (target === "lab") refreshLabLiveDefaults();
+            // Lab has its own Run/Results panel — hide the shared Generate/Seed/Batch column
+            const rightCol = document.querySelector(".wfm-gen-right");
+            if (rightCol) rightCol.style.display = (target === "lab") ? "none" : "";
+            // Save button writes the currently loaded workflow as-is — not meaningful while
+            // browsing Batch/Lab (which operate on workflow copies / their own Plan files)
+            const saveBtn = document.getElementById("wfm-gen-save-btn");
+            if (saveBtn) saveBtn.style.display = (target === "batch" || target === "lab") ? "none" : "";
        });
    });

@@ -1926,6 +2206,14 @@ export async function initGenerateTab() {
        }
    });

+    // Bypass button in LoRA column header — forces the target LoRA node's strength to
+    // 0 (or restores it), independent of the Single/Stack tabs' own Apply buttons.
+    document.getElementById("wfm-lora-bypass-toggle")?.addEventListener("click", () => {
+        if (!comfyUI.currentAnalysis) return;
+        comfyEditor.toggleLoraNodeBypass(comfyUI.currentAnalysis);
+        comfyEditor.renderLoraPane(comfyUI.currentAnalysis, "wfm-gen-lora-fields");
+    });
+
    // Input inner tab (Prompt / Image)
    document.querySelectorAll(".wfm-input-inner-tab").forEach((btn) => {
        btn.addEventListener("click", () => {
@@ -2003,10 +2291,11 @@ export async function initGenerateTab() {
            });
            searchOverlay.innerHTML = html + "\n";

-            // Scroll editor to current match
+            // Scroll editor to current match. フォーカス/selectionRangeは意図的に設定しない
+            // (テキストエリアにカーソルが当たった状態になり、検索直後のキー入力が選択範囲を
+            // 上書きして不意にJSONを編集してしまうため)。ハイライトはsearchOverlayの<mark>
+            // 表示のみで行い、編集はユーザーが明示的にエディタをクリックした場合に限る。
            const pos = matchPositions[currentMatchIndex];
-            editor.focus();
-            editor.setSelectionRange(pos, pos + term.length);
            const lineNum = (text.slice(0, pos).match(/\n/g) || []).length;
            const lineH = parseFloat(getComputedStyle(editor).lineHeight) || 18;
            editor.scrollTop = Math.max(0, lineH * lineNum - editor.clientHeight / 2);
@@ -2092,6 +2381,9 @@ export async function initGenerateTab() {
    // Feeder tab
    await initFeederTab();

+    // Lab tab (experimental I2I batch generation)
+    initLabTab();
+
    // Style dropdown
    await _loadStyles();

@@ -0,0 +1,208 @@
+/**
+ * Image Edit Tab - Background Removal
+ * Two backends: a lightweight in-browser model (@imgly/background-removal)
+ * and BiRefNet via the Mask Editor One server endpoints.
+ */
+
+import { showToast } from "../app.js";
+
+export class BgRemove {
+    /**
+     * @param {object} callbacks
+     * @param {() => object|null} callbacks.getLayerManager
+     * @param {() => void} callbacks.saveUndo
+     * @param {() => void} callbacks.updateCompositeView
+     * @param {() => void} callbacks.refreshLayerList
+     * @param {(newLayer: object) => void} callbacks.onLayerAdded
+     */
+    constructor(callbacks) {
+        this._cb = callbacks;
+        this.birefnetAvailable = false;
+    }
+
+    async checkAvailability() {
+        try {
+            const resp = await fetch("/mask_editor/birefnet/status");
+            if (!resp.ok) return;
+            const json = await resp.json();
+            this.birefnetAvailable = json.loaded === true || json.model_found === true;
+        } catch {
+            this.birefnetAvailable = false;
+        }
+    }
+
+    renderPanel(el) {
+        const birefnetDisabled = this.birefnetAvailable ? "" : "disabled";
+        const birefnetLabel    = this.birefnetAvailable
+            ? "BiRefNet (Mask Editor One)"
+            : "BiRefNet (Mask Editor One required)";
+        el.innerHTML = `
+            <div class="ie-opt-group">
+                <label>Model</label>
+                <select id="ie-bgremove-model" class="ie-opt-select">
+                    <option value="imgly">Lightweight (@imgly)</option>
+                    <option value="birefnet" ${birefnetDisabled}>${birefnetLabel}</option>
+                </select>
+            </div>
+            <div class="ie-opt-group">
+                <label style="font-size:11px;cursor:pointer;">
+                    <input type="checkbox" id="ie-bgremove-new-layer" checked> New Layer
+                </label>
+            </div>
+            <div class="ie-opt-group">
+                <button class="wfm-btn wfm-btn-sm" id="ie-bgremove-btn">Remove BG</button>
+            </div>
+            <span id="ie-bgremove-status" style="font-size:11px;color:var(--wfm-text-secondary);margin-left:4px;"></span>
+        `;
+        document.getElementById("ie-bgremove-btn")?.addEventListener("click", () => this.apply());
+    }
+
+    async apply() {
+        const layerMgr = this._cb.getLayerManager();
+        if (!layerMgr) { showToast("No image loaded", "error"); return; }
+        const layer = layerMgr.activeLayer;
+        if (!layer)  { showToast("No active layer", "error"); return; }
+
+        const model    = document.getElementById("ie-bgremove-model")?.value ?? "imgly";
+        const asNew    = document.getElementById("ie-bgremove-new-layer")?.checked ?? true;
+        const statusEl = document.getElementById("ie-bgremove-status");
+        const btn      = document.getElementById("ie-bgremove-btn");
+        const setStatus = msg => { if (statusEl) statusEl.textContent = msg; };
+
+        if (btn) btn.disabled = true;
+        setStatus("Starting...");
+
+        try {
+            const dataUrl = layer.canvas.toDataURL("image/png");
+
+            let resultDataUrl;
+            if (model === "imgly") {
+                resultDataUrl = await this._removeImgly(dataUrl, setStatus);
+            } else {
+                resultDataUrl = await this._removeBiRefNet(dataUrl, setStatus);
+            }
+
+            const img = await new Promise((resolve, reject) => {
+                const i = new Image();
+                i.onload  = () => resolve(i);
+                i.onerror = () => reject(new Error("Result image load failed"));
+                i.src = resultDataUrl;
+            });
+
+            this._cb.saveUndo();
+
+            if (asNew) {
+                const newL = layerMgr.addLayer("image", layer.name + " (no bg)", {
+                    contentW: img.width,    contentH: img.height,
+                    displayW: layer.displayW, displayH: layer.displayH,
+                    x: layer.x,            y: layer.y,
+                });
+                newL.ctx.drawImage(img, 0, 0);
+                layerMgr.setActive(newL.id);
+                this._cb.onLayerAdded(newL);
+            } else {
+                layer.canvas.width  = img.width;
+                layer.canvas.height = img.height;
+                layer.ctx = layer.canvas.getContext("2d");
+                layer.ctx.drawImage(img, 0, 0);
+            }
+
+            this._cb.updateCompositeView();
+            this._cb.refreshLayerList();
+            setStatus("Done!");
+            setTimeout(() => setStatus(""), 3000);
+            showToast("Background removed", "success");
+
+        } catch (err) {
+            setStatus("Error: " + err.message);
+            showToast("BG remove failed: " + err.message, "error");
+        } finally {
+            if (btn) btn.disabled = false;
+        }
+    }
+
+    async _removeImgly(dataUrl, onStatus) {
+        if (!window._wfmImglyRemoveBg) {
+            onStatus("Loading model...");
+            const mod = await import("https://esm.sh/@imgly/background-removal@1.5.7?bundle&target=es2022");
+            window._wfmImglyRemoveBg = mod.removeBackground;
+        }
+        onStatus("Processing...");
+        const res  = await fetch(dataUrl);
+        const blob = await res.blob();
+        const resultBlob = await window._wfmImglyRemoveBg(blob, {
+            publicPath: "https://staticimgly.com/@imgly/background-removal-data/1.5.7/dist/",
+        });
+        return await new Promise((resolve, reject) => {
+            const reader = new FileReader();
+            reader.onload  = () => resolve(reader.result);
+            reader.onerror = reject;
+            reader.readAsDataURL(resultBlob);
+        });
+    }
+
+    async _removeBiRefNet(dataUrl, onStatus) {
+        const NODE_ID = "wfs_bgremove";
+
+        // 1. アクティブレイヤー画像を Mask Editor One のキャッシュに登録
+        onStatus("Sending image...");
+        const storeResp = await fetch("/mask_editor/store_image", {
+            method:  "POST",
+            headers: { "Content-Type": "application/json" },
+            body:    JSON.stringify({ node_id: NODE_ID, image_b64: dataUrl }),
+        });
+        if (!storeResp.ok) throw new Error("Failed to cache image for BiRefNet");
+
+        // 2. BiRefNet 推論実行
+        onStatus("Running BiRefNet...");
+        const resp = await fetch("/mask_editor/birefnet/remove_bg", {
+            method:  "POST",
+            headers: { "Content-Type": "application/json" },
+            body:    JSON.stringify({ node_id: NODE_ID }),
+        });
+        const json = await resp.json();
+        if (json.error) throw new Error(json.error);
+
+        // 3. グレースケールマスク (白=前景) → RGBA PNG に変換して返す
+        onStatus("Compositing...");
+        return await this._applyMaskToImage(dataUrl, json.mask_b64);
+    }
+
+    async _applyMaskToImage(imageB64, maskB64) {
+        const loadImage = src => new Promise((resolve, reject) => {
+            const img = new Image();
+            img.onload  = () => resolve(img);
+            img.onerror = () => reject(new Error("Image load failed: " + src.slice(0, 40)));
+            img.src = src;
+        });
+        const [origImg, maskImg] = await Promise.all([loadImage(imageB64), loadImage(maskB64)]);
+
+        const w = origImg.naturalWidth;
+        const h = origImg.naturalHeight;
+
+        // マスク: グレースケール輝度値 → アルファチャンネル (RGBA 白マスク)
+        const maskCanvas = document.createElement("canvas");
+        maskCanvas.width  = w;
+        maskCanvas.height = h;
+        const mc = maskCanvas.getContext("2d");
+        mc.drawImage(maskImg, 0, 0, w, h);
+        const maskData = mc.getImageData(0, 0, w, h);
+        const md = maskData.data;
+        for (let i = 0; i < md.length; i += 4) {
+            md[i + 3] = md[i]; // 輝度 → アルファ
+            md[i] = md[i + 1] = md[i + 2] = 255;
+        }
+        mc.putImageData(maskData, 0, 0);
+
+        // 元画像にマスクを destination-in で適用
+        const out = document.createElement("canvas");
+        out.width  = w;
+        out.height = h;
+        const ctx = out.getContext("2d");
+        ctx.drawImage(origImg, 0, 0, w, h);
+        ctx.globalCompositeOperation = "destination-in";
+        ctx.drawImage(maskCanvas, 0, 0, w, h);
+
+        return out.toDataURL("image/png");
+    }
+}
@@ -0,0 +1,259 @@
+/**
+ * Image Edit Tab - Blur / Mosaic Tool
+ * Whole-layer blur/mosaic buttons plus a drag-to-select rectangle mode
+ * that applies blur or mosaic to just the dragged region.
+ */
+
+import { showToast } from "../app.js";
+
+function _applyMosaicToRegion(ctx, x, y, w, h, size) {
+    if (w <= 0 || h <= 0 || size < 1) return;
+    const imgData = ctx.getImageData(x, y, w, h);
+    const d = imgData.data;
+    for (let py = 0; py < h; py += size) {
+        for (let px = 0; px < w; px += size) {
+            const i = (py * w + px) * 4;
+            const r = d[i], g = d[i + 1], b = d[i + 2], a = d[i + 3];
+            for (let by = py; by < Math.min(py + size, h); by++) {
+                for (let bx = px; bx < Math.min(px + size, w); bx++) {
+                    const j = (by * w + bx) * 4;
+                    d[j] = r; d[j + 1] = g; d[j + 2] = b; d[j + 3] = a;
+                }
+            }
+        }
+    }
+    ctx.putImageData(imgData, x, y);
+}
+
+export class BlurTool {
+    /**
+     * @param {object} callbacks
+     * @param {() => object|null} callbacks.getLayerManager
+     * @param {() => number} callbacks.getZoom
+     * @param {() => void} callbacks.saveUndo
+     * @param {() => void} callbacks.updateCompositeView
+     * @param {() => void} callbacks.refreshLayerList
+     * @param {(toolId: string) => void} callbacks.renderToolOptions
+     */
+    constructor(callbacks) {
+        this._cb = callbacks;
+        this.rectMode  = null;   // null | 'blur' | 'mosaic'
+        this._dragging  = false;
+        this._dragStart = null;
+        this._dragCur   = null;
+    }
+
+    activate() {
+        const overlay = document.getElementById("ie-canvas-overlay");
+        if (overlay) overlay.style.cursor = this.rectMode ? "crosshair" : "default";
+    }
+
+    deactivate() {
+        this.rectMode  = null;
+        this._dragging = false;
+        const overlay = document.getElementById("ie-canvas-overlay");
+        if (overlay) {
+            overlay.style.cursor = "";
+            overlay.getContext("2d").clearRect(0, 0, overlay.width, overlay.height);
+        }
+    }
+
+    renderPanel(el) {
+        const blurOn   = this.rectMode === "blur";
+        const mosaicOn = this.rectMode === "mosaic";
+        el.innerHTML = `
+            <div class="ie-opt-group">
+                <span style="font-size:11px;color:var(--wfm-text-secondary);">Whole:</span>
+            </div>
+            <div class="ie-opt-group">
+                <label style="font-size:11px;">Blur</label>
+                <input type="range" id="ie-whole-blur" min="1" max="50" value="10" style="width:70px;">
+                <span id="ie-whole-blur-val" style="font-size:11px;min-width:22px;">10</span>px
+                <button class="wfm-btn wfm-btn-sm" id="ie-whole-blur-apply">Apply</button>
+            </div>
+            <div class="ie-opt-group">
+                <label style="font-size:11px;">Mosaic</label>
+                <input type="range" id="ie-whole-mosaic" min="5" max="100" value="20" style="width:70px;">
+                <span id="ie-whole-mosaic-val" style="font-size:11px;min-width:22px;">20</span>px
+                <button class="wfm-btn wfm-btn-sm" id="ie-whole-mosaic-apply">Apply</button>
+            </div>
+            <div style="width:1px;height:22px;background:var(--wfm-border);margin:0 6px;flex-shrink:0;"></div>
+            <div class="ie-opt-group">
+                <span style="font-size:11px;color:var(--wfm-text-secondary);">Rect:</span>
+            </div>
+            <div class="ie-opt-group">
+                <button class="wfm-btn wfm-btn-sm${blurOn ? " ie-opt-active" : ""}" id="ie-rect-blur-toggle"
+                    style="${blurOn ? "background:var(--wfm-accent,#4682e6);color:#fff;" : ""}">
+                    Rect Blur: ${blurOn ? "ON" : "OFF"}
+                </button>
+                <input type="range" id="ie-rect-blur" min="1" max="50" value="10" style="width:70px;">
+                <span id="ie-rect-blur-val" style="font-size:11px;min-width:22px;">10</span>px
+            </div>
+            <div class="ie-opt-group">
+                <button class="wfm-btn wfm-btn-sm${mosaicOn ? " ie-opt-active" : ""}" id="ie-rect-mosaic-toggle"
+                    style="${mosaicOn ? "background:var(--wfm-accent,#4682e6);color:#fff;" : ""}">
+                    Rect Mosaic: ${mosaicOn ? "ON" : "OFF"}
+                </button>
+                <input type="range" id="ie-rect-mosaic" min="5" max="50" value="15" style="width:70px;">
+                <span id="ie-rect-mosaic-val" style="font-size:11px;min-width:22px;">15</span>px
+            </div>
+        `;
+        document.getElementById("ie-whole-blur")?.addEventListener("input", e => {
+            document.getElementById("ie-whole-blur-val").textContent = e.target.value;
+        });
+        document.getElementById("ie-whole-mosaic")?.addEventListener("input", e => {
+            document.getElementById("ie-whole-mosaic-val").textContent = e.target.value;
+        });
+        document.getElementById("ie-whole-blur-apply")?.addEventListener("click", () => {
+            this.applyWholeBlur(parseInt(document.getElementById("ie-whole-blur").value));
+        });
+        document.getElementById("ie-whole-mosaic-apply")?.addEventListener("click", () => {
+            this.applyWholeMosaic(parseInt(document.getElementById("ie-whole-mosaic").value));
+        });
+        document.getElementById("ie-rect-blur-toggle")?.addEventListener("click", () => {
+            this.rectMode = this.rectMode === "blur" ? null : "blur";
+            this._cb.renderToolOptions("blur");
+            const ov = document.getElementById("ie-canvas-overlay");
+            if (ov) ov.style.cursor = this.rectMode ? "crosshair" : "default";
+        });
+        document.getElementById("ie-rect-mosaic-toggle")?.addEventListener("click", () => {
+            this.rectMode = this.rectMode === "mosaic" ? null : "mosaic";
+            this._cb.renderToolOptions("blur");
+            const ov = document.getElementById("ie-canvas-overlay");
+            if (ov) ov.style.cursor = this.rectMode ? "crosshair" : "default";
+        });
+        document.getElementById("ie-rect-blur")?.addEventListener("input", e => {
+            document.getElementById("ie-rect-blur-val").textContent = e.target.value;
+        });
+        document.getElementById("ie-rect-mosaic")?.addEventListener("input", e => {
+            document.getElementById("ie-rect-mosaic-val").textContent = e.target.value;
+        });
+    }
+
+    onMouseDown(pos) {
+        if (!this.rectMode) return;
+        this._dragging  = true;
+        this._dragStart = { x: pos.x, y: pos.y };
+        this._dragCur   = { x: pos.x, y: pos.y };
+    }
+
+    onMouseMove(pos) {
+        if (!this._dragging) return;
+        this._dragCur = pos;
+        this._drawPreview();
+    }
+
+    onMouseUp() {
+        if (!this._dragging) return;
+        this._dragging = false;
+        this._applyRectEffect();
+        const overlay = document.getElementById("ie-canvas-overlay");
+        if (overlay) overlay.getContext("2d").clearRect(0, 0, overlay.width, overlay.height);
+    }
+
+    onMouseLeave() {
+        if (!this._dragging) return;
+        this._dragging = false;
+        const overlay = document.getElementById("ie-canvas-overlay");
+        if (overlay) overlay.getContext("2d").clearRect(0, 0, overlay.width, overlay.height);
+    }
+
+    applyWholeBlur(amount) {
+        const layerMgr = this._cb.getLayerManager();
+        if (!layerMgr) return;
+        const layer = layerMgr.activeLayer;
+        if (!layer) { showToast("No active layer", "error"); return; }
+        this._cb.saveUndo();
+        const w = layer.canvas.width, h = layer.canvas.height;
+        const tmp = document.createElement("canvas");
+        tmp.width = w; tmp.height = h;
+        const tc = tmp.getContext("2d");
+        tc.filter = `blur(${amount}px)`;
+        tc.drawImage(layer.canvas, 0, 0);
+        layer.ctx.clearRect(0, 0, w, h);
+        layer.ctx.drawImage(tmp, 0, 0);
+        this._cb.updateCompositeView();
+        this._cb.refreshLayerList();
+    }
+
+    applyWholeMosaic(size) {
+        const layerMgr = this._cb.getLayerManager();
+        if (!layerMgr) return;
+        const layer = layerMgr.activeLayer;
+        if (!layer) { showToast("No active layer", "error"); return; }
+        this._cb.saveUndo();
+        _applyMosaicToRegion(layer.ctx, 0, 0, layer.canvas.width, layer.canvas.height, size);
+        this._cb.updateCompositeView();
+        this._cb.refreshLayerList();
+    }
+
+    // canvas座標 (cx,cy) → layer.canvas 座標への逆変換
+    _canvasToLayerCoords(layer, cx, cy) {
+        const centerX = layer.x + layer.displayW / 2;
+        const centerY = layer.y + layer.displayH / 2;
+        const dx = cx - centerX, dy = cy - centerY;
+        const angle = -(layer.rotation || 0) * Math.PI / 180;
+        const rdx = dx * Math.cos(angle) - dy * Math.sin(angle);
+        const rdy = dx * Math.sin(angle) + dy * Math.cos(angle);
+        const scaleX = layer.displayW / layer.canvas.width;
+        const scaleY = layer.displayH / layer.canvas.height;
+        let lx = rdx / scaleX + layer.canvas.width  / 2;
+        let ly = rdy / scaleY + layer.canvas.height / 2;
+        if (layer.flipX) lx = layer.canvas.width  - lx;
+        if (layer.flipY) ly = layer.canvas.height - ly;
+        return { x: lx, y: ly };
+    }
+
+    _drawPreview() {
+        const overlay = document.getElementById("ie-canvas-overlay");
+        if (!overlay) return;
+        const ctx = overlay.getContext("2d");
+        ctx.clearRect(0, 0, overlay.width, overlay.height);
+        const s = this._dragStart, c = this._dragCur;
+        if (!s || !c) return;
+        const x = Math.min(s.x, c.x), y = Math.min(s.y, c.y);
+        const w = Math.abs(c.x - s.x), h = Math.abs(c.y - s.y);
+        const zoom = this._cb.getZoom();
+        ctx.strokeStyle = this.rectMode === "blur" ? "#4af" : "#fa4";
+        ctx.lineWidth   = 1 / zoom;
+        ctx.setLineDash([4 / zoom, 2 / zoom]);
+        ctx.strokeRect(x, y, w, h);
+        ctx.setLineDash([]);
+    }
+
+    _applyRectEffect() {
+        const layer = this._cb.getLayerManager()?.activeLayer;
+        if (!layer || !this._dragStart || !this._dragCur) return;
+        const s = this._dragStart, c = this._dragCur;
+        if (Math.abs(c.x - s.x) < 3 || Math.abs(c.y - s.y) < 3) return;
+
+        const minX = Math.min(s.x, c.x), minY = Math.min(s.y, c.y);
+        const maxX = Math.max(s.x, c.x), maxY = Math.max(s.y, c.y);
+        const p1 = this._canvasToLayerCoords(layer, minX, minY);
+        const p2 = this._canvasToLayerCoords(layer, maxX, maxY);
+
+        const lx = Math.round(Math.max(0, Math.min(p1.x, p2.x)));
+        const ly = Math.round(Math.max(0, Math.min(p1.y, p2.y)));
+        const lw = Math.round(Math.min(layer.canvas.width  - lx, Math.abs(p2.x - p1.x)));
+        const lh = Math.round(Math.min(layer.canvas.height - ly, Math.abs(p2.y - p1.y)));
+        if (lw <= 0 || lh <= 0) return;
+
+        this._cb.saveUndo();
+
+        if (this.rectMode === "blur") {
+            const amount = parseInt(document.getElementById("ie-rect-blur")?.value ?? "10");
+            const tmp = document.createElement("canvas");
+            tmp.width = layer.canvas.width; tmp.height = layer.canvas.height;
+            const tc = tmp.getContext("2d");
+            tc.filter = `blur(${amount}px)`;
+            tc.drawImage(layer.canvas, 0, 0);
+            layer.ctx.drawImage(tmp, lx, ly, lw, lh, lx, ly, lw, lh);
+        } else {
+            const size = parseInt(document.getElementById("ie-rect-mosaic")?.value ?? "15");
+            _applyMosaicToRegion(layer.ctx, lx, ly, lw, lh, size);
+        }
+
+        this._cb.updateCompositeView();
+        this._cb.refreshLayerList();
+    }
+}
@@ -20,6 +20,11 @@ export class DrawTool {
        this.sizeJitterAmount = 0.5;
        this.rotationJitter   = false;

+        // Pen pressure (0–1, from PointerEvent.pressure; mouse reports 0.5).
+        // pressure=0.5 maps to a 1.0x multiplier so mouse behavior is unchanged.
+        this.pressureEnabled = true;
+        this._lastPressure   = 0.5;
+
        // Image brush from ABR library (null = default circle brush)
        this.brushImage  = null;
        this.brushName   = "Circle";
@@ -80,29 +85,31 @@ export class DrawTool {
        if (this.canvas) this.canvas.style.cursor = "";
    }

-    onMouseDown(x, y) {
-        this._drawing = true;
-        this._lastX   = x;
-        this._lastY   = y;
+    onMouseDown(x, y, pressure = 0.5) {
+        this._drawing      = true;
+        this._lastX         = x;
+        this._lastY         = y;
+        this._lastPressure  = pressure;
        if (this.brushImage) {
            this._initStrokeBuffer();
-            this._paintToStroke(x, y);
+            this._paintToStroke(x, y, pressure);
            this._mergeStroke();
        } else {
-            this._paint(x, y);
+            this._paint(x, y, pressure);
        }
    }

-    onMouseMove(x, y) {
+    onMouseMove(x, y, pressure = 0.5) {
        if (!this._drawing) return;
        if (this.brushImage) {
-            this._paintLineToStroke(this._lastX, this._lastY, x, y);
+            this._paintLineToStroke(this._lastX, this._lastY, x, y, this._lastPressure, pressure);
            this._mergeStroke();
        } else {
-            this._paintLine(this._lastX, this._lastY, x, y);
+            this._paintLine(this._lastX, this._lastY, x, y, this._lastPressure, pressure);
        }
-        this._lastX = x;
-        this._lastY = y;
+        this._lastX        = x;
+        this._lastY        = y;
+        this._lastPressure = pressure;
    }

    onMouseUp() {
@@ -117,6 +124,20 @@ export class DrawTool {
        if (this._drawing) this.onMouseUp();
    }

+    // ── Pressure response ──────────────────────────────────────────────
+
+    _effectiveSize(pressure) {
+        if (!this.pressureEnabled) return this.brushSize;
+        const p = Math.max(0, Math.min(1, pressure ?? 0.5));
+        return Math.max(1, this.brushSize * (0.3 + p * 1.4)); // p=0.5 -> 1.0x
+    }
+
+    _effectiveOpacity(pressure) {
+        if (!this.pressureEnabled) return this.opacity;
+        const p = Math.max(0, Math.min(1, pressure ?? 0.5));
+        return Math.max(0, Math.min(1, this.opacity * (0.4 + p * 1.2))); // p=0.5 -> 1.0x
+    }
+
    // ── Stroke buffer (image brush only) ─────────────────────────────

    _initStrokeBuffer() {
@@ -155,54 +176,48 @@ export class DrawTool {
        ctx.restore();
    }

-    _paintToStroke(x, y) {
+    _paintToStroke(x, y, pressure = 0.5) {
        const saved = this.ctx;
        this.ctx = this._strokeCtx;

-        if (this.sizeJitter || this.rotationJitter) {
-            const savedSize      = this.brushSize;
-            const savedAngle     = this.angle;
-            const savedStamp     = this._imgStamp;
-            const savedStampSize = this._imgStampSize;
-            if (this.sizeJitter) {
-                this.brushSize = Math.max(1, savedSize * (1 - Math.random() * this.sizeJitterAmount));
-            }
-            if (this.rotationJitter) {
-                this.angle = Math.random() * 360;
-            }
-            this._paintImageBrush(x, y);
-            this.brushSize     = savedSize;
-            this.angle         = savedAngle;
-            this._imgStamp     = savedStamp;
-            this._imgStampSize = savedStampSize;
+        let size = this._effectiveSize(pressure);
+        if (this.sizeJitter) {
+            size = Math.max(1, size * (1 - Math.random() * this.sizeJitterAmount));
+        }
+
+        if (this.rotationJitter) {
+            const savedAngle = this.angle;
+            this.angle = Math.random() * 360;
+            this._paintImageBrush(x, y, size);
+            this.angle = savedAngle;
        } else {
-            this._paintImageBrush(x, y);
+            this._paintImageBrush(x, y, size);
        }

        this.ctx = saved;
    }

-    _paintLineToStroke(x0, y0, x1, y1) {
+    _paintLineToStroke(x0, y0, x1, y1, p0 = 0.5, p1 = 0.5) {
        const dist  = Math.hypot(x1 - x0, y1 - y0);
        const step  = Math.max(1, this.brushSize * this.spacing);
        const steps = Math.ceil(dist / step);
        for (let i = 1; i <= steps; i++) {
            const t = i / steps;
-            this._paintToStroke(x0 + (x1 - x0) * t, y0 + (y1 - y0) * t);
+            this._paintToStroke(x0 + (x1 - x0) * t, y0 + (y1 - y0) * t, p0 + (p1 - p0) * t);
        }
    }

    // ── Circle brush ─────────────────────────────────────────────────

-    _getStamp() {
+    _getStamp(size) {
+        size = Math.max(1, Math.round(size));
        if (
            this._stamp &&
-            this._stampSize  === this.brushSize &&
+            this._stampSize  === size &&
            this._stampHard  === this.hardness &&
            this._stampColor === this.color
        ) return this._stamp;

-        const size = Math.max(1, Math.round(this.brushSize));
        const sc   = document.createElement("canvas");
        sc.width   = size;
        sc.height  = size;
@@ -225,11 +240,12 @@ export class DrawTool {
        return sc;
    }

-    _paint(x, y) {
-        const stamp = this._getStamp();
+    _paint(x, y, pressure = 0.5) {
+        const size  = this._effectiveSize(pressure);
+        const stamp = this._getStamp(size);
        const s     = stamp.width;
        this.ctx.save();
-        this.ctx.globalAlpha = this.opacity;
+        this.ctx.globalAlpha = this._effectiveOpacity(pressure);
        if (this.mode === "erase") {
            this.ctx.globalCompositeOperation = "destination-out";
        }
@@ -237,13 +253,13 @@ export class DrawTool {
        this.ctx.restore();
    }

-    _paintLine(x0, y0, x1, y1) {
+    _paintLine(x0, y0, x1, y1, p0 = 0.5, p1 = 0.5) {
        const dist    = Math.hypot(x1 - x0, y1 - y0);
        const spacing = Math.max(1, this.brushSize * 0.2);
        const steps   = Math.max(1, Math.ceil(dist / spacing));
        for (let i = 1; i <= steps; i++) {
            const t = i / steps;
-            this._paint(x0 + (x1 - x0) * t, y0 + (y1 - y0) * t);
+            this._paint(x0 + (x1 - x0) * t, y0 + (y1 - y0) * t, p0 + (p1 - p0) * t);
        }
    }

@@ -319,8 +335,8 @@ export class DrawTool {
        return sc;
    }

-    _paintImageBrush(x, y) {
-        const stamp = this._getImageStamp(Math.round(this.brushSize));
+    _paintImageBrush(x, y, size = this.brushSize) {
+        const stamp = this._getImageStamp(Math.round(size));
        this.ctx.globalCompositeOperation = "source-over";
        if (this.angle) {
            this.ctx.save();
@@ -0,0 +1,222 @@
+/**
+ * Image Edit Tab - File Export
+ * Composites the visible layers (respecting mask-apply clipping) into a
+ * flat canvas and offers three destinations: local PNG download, WFS
+ * Gallery, and the selected node's image widget on the ComfyUI canvas
+ * (Send to LI node).
+ */
+
+import { showToast } from "../app.js";
+import { Layer }     from "./LayerManager.js";
+
+export class FileExport {
+    /**
+     * @param {object} callbacks
+     * @param {() => object|null} callbacks.getLayerManager
+     * @param {() => {w: number, h: number}} callbacks.getCanvasSize
+     * @param {() => string} callbacks.getBaseName
+     * @param {(ctx: CanvasRenderingContext2D, drawCanvas: HTMLCanvasElement, maskLayer: object, targetLayer: object, showOverlay: boolean) => void} callbacks.renderMaskedLayer
+     */
+    constructor(callbacks) {
+        this._cb = callbacks;
+    }
+
+    _buildCompositeCanvas() {
+        const { w, h } = this._cb.getCanvasSize();
+        const canvas = document.createElement("canvas");
+        canvas.width  = w;
+        canvas.height = h;
+        const layerMgr = this._cb.getLayerManager();
+        if (!layerMgr) return canvas;
+        this._compositeForExport(canvas, layerMgr);
+        return canvas;
+    }
+
+    // 保存用合成: maskApply=true のクリッピングを適用、マスクオーバーレイは除外
+    _compositeForExport(target, layerMgr) {
+        const ctx = target.getContext("2d");
+        ctx.clearRect(0, 0, target.width, target.height);
+        const layers = layerMgr.layers;
+        const maskedIndices = new Set();
+        for (let i = 0; i < layers.length; i++) {
+            if (layers[i].type === "mask" && layers[i].maskApply && layers[i].visible && i + 1 < layers.length) {
+                maskedIndices.add(i + 1);
+            }
+        }
+        for (let i = layers.length - 1; i >= 0; i--) {
+            const layer = layers[i];
+            if (!layer.visible) continue;
+            if (maskedIndices.has(i)) continue;
+            if (layer.type === "mask") {
+                if (layer.maskApply && i + 1 < layers.length) {
+                    this._cb.renderMaskedLayer(ctx, target, layer, layers[i + 1], false);
+                }
+                // maskApply=false のマスクはエクスポートに含めない
+            } else {
+                ctx.save();
+                ctx.globalAlpha = layer.opacity;
+                ctx.globalCompositeOperation = layer.blendMode;
+                Layer.applyTransform(ctx, layer);
+                ctx.drawImage(layer.canvas, -layer.canvas.width / 2, -layer.canvas.height / 2);
+                ctx.restore();
+            }
+        }
+    }
+
+    // 保存用レイヤー配列を構築: 各レイヤーを個別のcanvas(ドキュメント全体サイズ)に
+    // 回転・反転・拡縮のみベイクして描画する。opacity/blendModeはピクセルに焼き込まず
+    // PSDレイヤー属性として渡すためメタデータのまま残す。
+    // maskApply=true のクリッピングマスクは対象レイヤーと合成して1枚にベイクする
+    // (PSDの本物のレイヤーマスクとしては書き出さない簡略化)。
+    _buildLayerExportList(layerMgr, w, h) {
+        const layers = layerMgr.layers;
+        const maskedIndices = new Set();
+        for (let i = 0; i < layers.length; i++) {
+            if (layers[i].type === "mask" && layers[i].maskApply && layers[i].visible && i + 1 < layers.length) {
+                maskedIndices.add(i + 1);
+            }
+        }
+
+        const exportLayers = [];
+        // 背面→前面の順(PSD側で後から追加したレイヤーほど上に重なるため、この順で送る)
+        for (let i = layers.length - 1; i >= 0; i--) {
+            const layer = layers[i];
+            if (maskedIndices.has(i)) continue; // マスク側の処理でまとめて扱う
+
+            if (layer.type === "mask") {
+                if (!(layer.maskApply && layer.visible && i + 1 < layers.length)) continue;
+                const target = layers[i + 1];
+                const canvas = document.createElement("canvas");
+                canvas.width = w;
+                canvas.height = h;
+                this._cb.renderMaskedLayer(canvas.getContext("2d"), canvas, layer, target, false);
+                exportLayers.push({
+                    name: target.name || "Layer",
+                    visible: target.visible,
+                    opacity: 1,
+                    blendMode: "source-over",
+                    imageData: canvas.toDataURL("image/png"),
+                });
+                continue;
+            }
+
+            const canvas = document.createElement("canvas");
+            canvas.width = w;
+            canvas.height = h;
+            const ctx = canvas.getContext("2d");
+            ctx.save();
+            Layer.applyTransform(ctx, layer);
+            ctx.drawImage(layer.canvas, -layer.canvas.width / 2, -layer.canvas.height / 2);
+            ctx.restore();
+            exportLayers.push({
+                name: layer.name || "Layer",
+                visible: layer.visible,
+                opacity: layer.opacity,
+                blendMode: layer.blendMode,
+                imageData: canvas.toDataURL("image/png"),
+            });
+        }
+        return exportLayers;
+    }
+
+    async saveAsPsd() {
+        if (!this._cb.getLayerManager()) { showToast("No image loaded", "error"); return; }
+        const layerMgr = this._cb.getLayerManager();
+        const { w, h } = this._cb.getCanvasSize();
+        const exportLayers = this._buildLayerExportList(layerMgr, w, h);
+        if (exportLayers.length === 0) { showToast("No layers to export", "error"); return; }
+
+        try {
+            const r = await fetch("/wfm/gallery/image/export-psd-layers", {
+                method: "POST",
+                headers: { "Content-Type": "application/json" },
+                body: JSON.stringify({ width: w, height: h, layers: exportLayers }),
+            });
+            if (!r.ok) {
+                const e = await r.json().catch(() => ({}));
+                throw new Error(e.error || r.statusText);
+            }
+            const blob = await r.blob();
+            const url  = URL.createObjectURL(blob);
+            const a = document.createElement("a");
+            a.href     = url;
+            a.download = (this._cb.getBaseName() || "wfs-edit") + ".psd";
+            a.click();
+            URL.revokeObjectURL(url);
+            showToast("PSD saved", "success");
+        } catch (err) {
+            showToast(`PSD save failed: ${err.message}`, "error");
+        }
+    }
+
+    savePng() {
+        if (!this._cb.getLayerManager()) { showToast("No image loaded", "error"); return; }
+        const canvas = this._buildCompositeCanvas();
+        const a = document.createElement("a");
+        a.href     = canvas.toDataURL("image/png");
+        a.download = (this._cb.getBaseName() || "wfs-edit") + "-output.png";
+        a.click();
+        showToast("PNG saved", "success");
+    }
+
+    async saveToGallery() {
+        if (!this._cb.getLayerManager()) { showToast("No image loaded", "error"); return; }
+
+        // デフォルトファイル名: wfs-image-YYYYMMDDHHmmss
+        const now = new Date();
+        const pad = n => String(n).padStart(2, "0");
+        const ts  = `${now.getFullYear()}${pad(now.getMonth()+1)}${pad(now.getDate())}${pad(now.getHours())}${pad(now.getMinutes())}${pad(now.getSeconds())}`;
+        const defaultName = `wfs-image-${ts}`;
+
+        const filename = window.prompt("Save to Gallery — file name (without extension):", defaultName);
+        if (filename === null) return; // キャンセル
+        const safeName = filename.trim() || defaultName;
+
+        const canvas   = this._buildCompositeCanvas();
+        const imageData = canvas.toDataURL("image/png");
+
+        try {
+            const r = await fetch("/wfm/gallery/image/save", {
+                method: "POST",
+                headers: { "Content-Type": "application/json" },
+                body: JSON.stringify({ filename: safeName, imageData }),
+            });
+            if (!r.ok) {
+                const e = await r.json().catch(() => ({}));
+                throw new Error(e.error || r.statusText);
+            }
+            showToast(`Saved to Gallery: ${safeName}.png`, "success");
+        } catch (err) {
+            showToast(`Gallery save failed: ${err.message}`, "error");
+        }
+    }
+
+    // Uploads the composite via /upload/image, then (via window.opener,
+    // since WFS runs in its own window — same cross-window pattern as
+    // wfmReceiveWorkflow/wfmOpenMaskEditorForNode) writes the resulting
+    // filename into the "image" widget of the currently selected ComfyUI
+    // node (falling back to the first node in the graph with one), mirroring
+    // the chat_TE custom node's "Send to workflow" button.
+    async sendToWorkflow() {
+        if (!this._cb.getLayerManager()) { showToast("No image loaded", "error"); return; }
+        if (!window.opener || typeof window.opener.wfmSendImageToSelectedNode !== "function") {
+            showToast("Open Workflow Studio from ComfyUI's top menu to use this feature", "error");
+            return;
+        }
+        const canvas = this._buildCompositeCanvas();
+        const blob   = await new Promise(resolve => canvas.toBlob(resolve, "image/png"));
+        const file   = new File([blob], (this._cb.getBaseName() || "wfs-edit") + "-output.png", { type: "image/png" });
+        const form   = new FormData();
+        form.append("image", file);
+        form.append("overwrite", "true");
+        try {
+            const r    = await fetch("/upload/image", { method: "POST", body: form });
+            const data = await r.json();
+            const filename = data.subfolder ? `${data.subfolder}/${data.name}` : data.name;
+            window.opener.wfmSendImageToSelectedNode(filename);
+            showToast(`Sent "${filename}" to LI node`, "success");
+        } catch (err) {
+            showToast(`Send to LI node failed: ${err.message}`, "error");
+        }
+    }
+}
@@ -0,0 +1,228 @@
+/**
+ * Image Edit Tab - Fill Tool (bucket fill)
+ * Flood-fills a contiguous same-color region on the active layer canvas,
+ * either with a solid color or a linear/radial gradient.
+ * Gradient ramp math (evalGradient / hex<->rgb) is ported from
+ * comfyUI-particle-pixijs's particle_engine.js.
+ */
+
+function _hexToRgb01(hex) {
+    const m = /^#?([0-9a-f]{2})([0-9a-f]{2})([0-9a-f]{2})$/i.exec(hex || "#000000");
+    if (!m) return { r: 0, g: 0, b: 0 };
+    return { r: parseInt(m[1], 16) / 255, g: parseInt(m[2], 16) / 255, b: parseInt(m[3], 16) / 255 };
+}
+
+function _rgb01ToHex({ r, g, b }) {
+    const h = v => Math.round(Math.max(0, Math.min(1, v)) * 255).toString(16).padStart(2, "0");
+    return `#${h(r)}${h(g)}${h(b)}`;
+}
+
+function _lerp(a, b, t) { return a + (b - a) * t; }
+
+export class FillTool {
+    constructor() {
+        // fill settings
+        this.tolerance    = 32;        // 0-255
+        this.fillMode     = "solid";   // "solid" | "gradient"
+        this.color        = "#ff0000"; // solid fill color
+        this.opacity      = 1.0;
+
+        // gradient settings
+        this.gradientShape    = "linear"; // "linear" | "radial"
+        this.gradientAngleDeg = 0;        // linear direction
+        this.gradientStrength = 1.0;      // 0.2-3.0, length/radius multiplier
+        this.gradientStops    = [
+            { pos: 0.0, color: "#ffffff" },
+            { pos: 1.0, color: "#888888" },
+        ];
+        this.selectedStopIdx  = 0;
+
+        // internal state
+        this._active = false;
+        this._canvas = null;
+        this._ctx    = null;
+
+        this._onChange = null;
+    }
+
+    setCanvas(canvas) {
+        this._canvas = canvas;
+        this._ctx    = canvas ? canvas.getContext("2d") : null;
+    }
+
+    onChange(cb) { this._onChange = cb; }
+
+    activate()   { this._active = true; }
+    deactivate() { this._active = false; }
+
+    // ── color ramp evaluation (ported from particle_engine.js evalGradient) ──
+
+    static evalGradient(stops, t) {
+        if (!stops || stops.length === 0) return { r: 0, g: 0, b: 0 };
+        const sorted = [...stops].sort((a, b) => a.pos - b.pos);
+        if (t <= sorted[0].pos) return _hexToRgb01(sorted[0].color);
+        const last = sorted[sorted.length - 1];
+        if (t >= last.pos) return _hexToRgb01(last.color);
+        for (let i = 0; i < sorted.length - 1; i++) {
+            const a = sorted[i], b = sorted[i + 1];
+            if (t >= a.pos && t <= b.pos) {
+                const span = b.pos - a.pos;
+                const localT = span > 0 ? (t - a.pos) / span : 0;
+                const ca = _hexToRgb01(a.color), cb = _hexToRgb01(b.color);
+                return {
+                    r: _lerp(ca.r, cb.r, localT),
+                    g: _lerp(ca.g, cb.g, localT),
+                    b: _lerp(ca.b, cb.b, localT),
+                };
+            }
+        }
+        return _hexToRgb01(last.color);
+    }
+
+    /** Preview swatch color (hex) of the ramp at position t. */
+    evalGradientHex(t) {
+        return _rgb01ToHex(FillTool.evalGradient(this.gradientStops, t));
+    }
+
+    // ── stop editing helpers (ported from particle_widget.js addStop/removeStop/selectStop) ──
+
+    addStop() {
+        const sorted = [...this.gradientStops].sort((a, b) => a.pos - b.pos);
+        let bestGapStart = 0, bestGapSize = 0;
+        for (let i = 0; i < sorted.length - 1; i++) {
+            const gap = sorted[i + 1].pos - sorted[i].pos;
+            if (gap > bestGapSize) { bestGapSize = gap; bestGapStart = sorted[i].pos; }
+        }
+        const pos = sorted.length < 2 ? 0.5 : bestGapStart + bestGapSize / 2;
+        const color = _rgb01ToHex(FillTool.evalGradient(this.gradientStops, pos));
+        this.gradientStops.push({ pos, color });
+        this.selectedStopIdx = this.gradientStops.length - 1;
+    }
+
+    removeStop(idx = this.selectedStopIdx) {
+        if (this.gradientStops.length <= 1) return;
+        this.gradientStops.splice(idx, 1);
+        this.selectedStopIdx = Math.max(0, Math.min(this.selectedStopIdx, this.gradientStops.length - 1));
+    }
+
+    selectStop(idx) {
+        this.selectedStopIdx = idx;
+    }
+
+    // ── flood fill ────────────────────────────────────────
+
+    /**
+     * Flood-fills the contiguous region matching the pixel at (x, y).
+     * (x, y) are canvas-pixel coordinates (already converted via DrawTool.getCanvasPos).
+     */
+    onMouseDown(x, y) {
+        if (!this._active || !this._ctx) return;
+        const w = this._canvas.width, h = this._canvas.height;
+        const px = Math.floor(x), py = Math.floor(y);
+        if (px < 0 || py < 0 || px >= w || py >= h) return;
+
+        const imgData = this._ctx.getImageData(0, 0, w, h);
+        const data = imgData.data;
+
+        const mask = this._buildFloodMask(data, w, h, px, py, this.tolerance);
+        if (!mask) return;
+
+        if (this.fillMode === "gradient") {
+            this._fillMaskWithGradient(data, w, h, mask.pixels, mask.bbox);
+        } else {
+            this._fillMaskWithSolid(data, mask.pixels, this.color, this.opacity);
+        }
+
+        this._ctx.putImageData(imgData, 0, 0);
+    }
+
+    /** Scanline stack-based flood fill. Returns { pixels: Uint8Array(w*h), bbox } or null. */
+    _buildFloodMask(data, w, h, startX, startY, tolerance) {
+        const idx0 = (startY * w + startX) * 4;
+        const tr = data[idx0], tg = data[idx0 + 1], tb = data[idx0 + 2], ta = data[idx0 + 3];
+        const tol2 = tolerance * tolerance;
+
+        const matches = (i) => {
+            const dr = data[i] - tr, dg = data[i + 1] - tg, db = data[i + 2] - tb, da = data[i + 3] - ta;
+            return (dr * dr + dg * dg + db * db + da * da) <= tol2 * 4;
+        };
+
+        const pixels = new Uint8Array(w * h);
+        const stack = [[startX, startY]];
+        let minX = startX, maxX = startX, minY = startY, maxY = startY;
+
+        while (stack.length) {
+            let [x, y] = stack.pop();
+            while (x >= 0 && matches((y * w + x) * 4)) x--;
+            x++;
+            let spanUp = false, spanDown = false;
+            while (x < w && matches((y * w + x) * 4) && !pixels[y * w + x]) {
+                pixels[y * w + x] = 1;
+                if (x < minX) minX = x; if (x > maxX) maxX = x;
+                if (y < minY) minY = y; if (y > maxY) maxY = y;
+
+                if (y > 0) {
+                    const above = matches((( y - 1) * w + x) * 4) && !pixels[(y - 1) * w + x];
+                    if (above && !spanUp) { stack.push([x, y - 1]); spanUp = true; }
+                    else if (!above) spanUp = false;
+                }
+                if (y < h - 1) {
+                    const below = matches(((y + 1) * w + x) * 4) && !pixels[(y + 1) * w + x];
+                    if (below && !spanDown) { stack.push([x, y + 1]); spanDown = true; }
+                    else if (!below) spanDown = false;
+                }
+                x++;
+            }
+        }
+        return { pixels, bbox: { minX, minY, maxX, maxY } };
+    }
+
+    _fillMaskWithSolid(data, pixels, colorHex, opacity) {
+        const { r, g, b } = _hexToRgb01(colorHex);
+        const cr = r * 255, cg = g * 255, cb = b * 255;
+        const alpha = Math.max(0, Math.min(1, opacity));
+        for (let i = 0; i < pixels.length; i++) {
+            if (!pixels[i]) continue;
+            const di = i * 4;
+            data[di]     = _lerp(data[di],     cr, alpha);
+            data[di + 1] = _lerp(data[di + 1], cg, alpha);
+            data[di + 2] = _lerp(data[di + 2], cb, alpha);
+            data[di + 3] = Math.max(data[di + 3], alpha * 255);
+        }
+    }
+
+    /** Reusable with any {pixels, bbox} mask (flood fill today; rect/ellipse selections in the future). */
+    _fillMaskWithGradient(data, w, h, pixels, bbox) {
+        const cx = (bbox.minX + bbox.maxX) / 2, cy = (bbox.minY + bbox.maxY) / 2;
+        const diagW = bbox.maxX - bbox.minX, diagH = bbox.maxY - bbox.minY;
+        const diag = Math.max(1, Math.hypot(diagW, diagH));
+        const strength = Math.max(0.2, Math.min(3.0, this.gradientStrength));
+        const alpha = Math.max(0, Math.min(1, this.opacity));
+
+        const angleRad = this.gradientAngleDeg * Math.PI / 180;
+        const dirX = Math.cos(angleRad), dirY = Math.sin(angleRad);
+        const halfLen = (diag / 2) * strength;
+        const radius = (diag / 2) * strength;
+
+        for (let y = bbox.minY; y <= bbox.maxY; y++) {
+            for (let x = bbox.minX; x <= bbox.maxX; x++) {
+                const i = y * w + x;
+                if (!pixels[i]) continue;
+                const dx = x - cx, dy = y - cy;
+                let t;
+                if (this.gradientShape === "radial") {
+                    t = Math.hypot(dx, dy) / radius;
+                } else {
+                    t = (dx * dirX + dy * dirY) / (halfLen * 2) + 0.5;
+                }
+                t = Math.max(0, Math.min(1, t));
+                const c = FillTool.evalGradient(this.gradientStops, t);
+                const di = i * 4;
+                data[di]     = _lerp(data[di],     c.r * 255, alpha);
+                data[di + 1] = _lerp(data[di + 1], c.g * 255, alpha);
+                data[di + 2] = _lerp(data[di + 2], c.b * 255, alpha);
+                data[di + 3] = Math.max(data[di + 3], alpha * 255);
+            }
+        }
+    }
+}
@@ -0,0 +1,197 @@
+/**
+ * Image Edit Tab - G'MIC Integration
+ * Launches the G'MIC GUI on the server for the active layer, polls job
+ * status, and applies the resulting image back onto the layer.
+ */
+
+import { showToast } from "../app.js";
+
+export class GmicIntegration {
+    /**
+     * @param {object} callbacks
+     * @param {() => object|null} callbacks.getLayerManager
+     * @param {() => void} callbacks.syncActiveLayerFromCanvas
+     * @param {() => void} callbacks.saveUndo
+     * @param {() => void} callbacks.updateCompositeView
+     * @param {() => void} callbacks.refreshLayerList
+     * @param {(toolId: string) => void} callbacks.renderToolOptions
+     */
+    constructor(callbacks) {
+        this._cb = callbacks;
+        this.state = {
+            lastResultJobId: null,
+            processing: false,
+            aborted: false
+        };
+    }
+
+    renderPanel(el) {
+        const openBtnDisabled  = this.state.processing ? "disabled" : "";
+        const applyBtnDisabled = (!this.state.lastResultJobId || this.state.processing) ? "disabled" : "";
+        const progressStyle    = this.state.processing ? "display:flex" : "display:none";
+
+        el.innerHTML = `
+            <div class="ie-opt-group">
+                <button class="wfm-btn wfm-btn-sm wfm-btn-primary" id="ie-gmic-open-btn" ${openBtnDisabled}>G'MIC GUIで編集</button>
+                <button class="wfm-btn wfm-btn-sm" id="ie-gmic-apply-btn" ${applyBtnDisabled}>結果を反映</button>
+            </div>
+            <div class="ie-opt-group" id="ie-gmic-progress-area" style="${progressStyle}; align-items:center; gap:6px;">
+                <span id="ie-gmic-progress-lbl" style="font-size:11px; color:var(--wfm-text-secondary);">G'MIC GUIを起動中...</span>
+                <button class="wfm-btn wfm-btn-sm" id="ie-gmic-abort-btn" style="background:#ea4335;color:#fff;">中断</button>
+            </div>
+        `;
+        document.getElementById("ie-gmic-open-btn")?.addEventListener("click", () => this.openGui());
+        document.getElementById("ie-gmic-apply-btn")?.addEventListener("click", () => this.applyResult());
+        document.getElementById("ie-gmic-abort-btn")?.addEventListener("click", () => this.abort());
+    }
+
+    async openGui() {
+        const layerMgr = this._cb.getLayerManager();
+        if (!layerMgr) { showToast("No image loaded", "error"); return; }
+        const layer = layerMgr.activeLayer;
+        if (!layer)  { showToast("No active layer", "error"); return; }
+        this._cb.syncActiveLayerFromCanvas();
+
+        if (this.state.processing) return;
+
+        const dataUrl = layer.canvas.toDataURL("image/png");
+
+        this.state.processing = true;
+        const openBtn      = document.getElementById("ie-gmic-open-btn");
+        const progressArea = document.getElementById("ie-gmic-progress-area");
+        const progressLbl  = document.getElementById("ie-gmic-progress-lbl");
+        const applyBtn     = document.getElementById("ie-gmic-apply-btn");
+
+        if (openBtn) openBtn.disabled = true;
+        if (applyBtn) applyBtn.disabled = true;
+        if (progressArea) progressArea.style.display = "flex";
+        if (progressLbl) progressLbl.textContent = "画像をサーバーへ送信中...";
+
+        try {
+            const res = await fetch("/api/wfm/gmic/open", {
+                method: "POST",
+                headers: { "Content-Type": "application/json" },
+                body: JSON.stringify({ image_b64: dataUrl })
+            });
+            if (!res.ok) {
+                const err = await res.json().catch(() => ({}));
+                throw new Error(err.error || `HTTP ${res.status}`);
+            }
+            const data = await res.json();
+            this.state.lastResultJobId = data.job_id;
+            if (progressLbl) progressLbl.textContent = "G'MIC GUIで編集中... フィルターを選択して「OK」を押すと適用可能になります";
+            await this._waitForJob(data.job_id);
+        } catch (e) {
+            if (e.message !== "__aborted__") {
+                showToast("G'MIC Error: " + e.message, "error");
+            }
+            this.state.processing = false;
+            this.state.aborted = false;
+            if (openBtn) openBtn.disabled = false;
+            if (progressArea) progressArea.style.display = "none";
+        }
+    }
+
+    abort() {
+        this.state.aborted = true;
+        this.state.processing = false;
+        const openBtn      = document.getElementById("ie-gmic-open-btn");
+        const progressArea = document.getElementById("ie-gmic-progress-area");
+        if (progressArea) progressArea.style.display = "none";
+        if (openBtn) openBtn.disabled = false;
+    }
+
+    async _waitForJob(jobId) {
+        const progressLbl = document.getElementById("ie-gmic-progress-lbl");
+        const applyBtn    = document.getElementById("ie-gmic-apply-btn");
+        const maxWait = 600, interval = 2000;
+        const start = Date.now();
+        this.state.aborted = false;
+
+        while (true) {
+            if (this.state.aborted) throw new Error("__aborted__");
+            if ((Date.now() - start) / 1000 > maxWait) throw new Error("Timeout");
+            await new Promise(r => setTimeout(r, interval));
+            if (this.state.aborted) throw new Error("__aborted__");
+            try {
+                const res = await fetch(`/api/wfm/gmic/status/${jobId}`);
+                if (res.status === 404) throw new Error("__aborted__");
+                if (!res.ok) continue;
+                const status = await res.json();
+                if (status.status === "completed") {
+                    this.state.lastResultJobId = jobId;
+                    if (applyBtn) applyBtn.disabled = false;
+                    if (progressLbl) progressLbl.textContent = "処理完了 → 「結果を反映」で画像に適用";
+                    this.state.processing = false;
+                    showToast("G'MIC filtering complete. Click Apply to insert result.", "success");
+                    return;
+                }
+                if (status.status === "failed") {
+                    if (progressLbl) progressLbl.textContent = status.error || "G'MIC GUIがキャンセルされました";
+                    throw new Error("__aborted__");
+                }
+                if (progressLbl) progressLbl.textContent = status.message || "G'MIC GUIで編集中...";
+            } catch (e) {
+                if (e.message === "__aborted__" || e.message.includes("Timeout")) throw e;
+            }
+        }
+    }
+
+    async applyResult() {
+        if (!this.state.lastResultJobId) {
+            showToast("No G'MIC result to apply", "error");
+            return;
+        }
+        const applyBtn = document.getElementById("ie-gmic-apply-btn");
+        const openBtn  = document.getElementById("ie-gmic-open-btn");
+        const progressArea = document.getElementById("ie-gmic-progress-area");
+        if (applyBtn) applyBtn.disabled = true;
+
+        try {
+            const statusRes = await fetch(`/api/wfm/gmic/status/${this.state.lastResultJobId}`);
+            if (!statusRes.ok) throw new Error(`HTTP ${statusRes.status}`);
+            const statusData = await statusRes.json();
+            if (!statusData.result_path) throw new Error("No result path found");
+
+            const b64res = await fetch("/api/wfm/gmic/result", {
+                method: "POST",
+                headers: { "Content-Type": "application/json" },
+                body: JSON.stringify({ result_path: statusData.result_path })
+            });
+            if (!b64res.ok) throw new Error(`HTTP ${b64res.status}`);
+            const { image_b64: dataUrl } = await b64res.json();
+
+            const img = await new Promise((resolve, reject) => {
+                const i = new Image();
+                i.onload  = () => resolve(i);
+                i.onerror = () => reject(new Error("Failed to load result image"));
+                i.src = dataUrl;
+            });
+
+            this._cb.saveUndo();
+
+            const layerMgr = this._cb.getLayerManager();
+            const layer = layerMgr?.activeLayer;
+            if (!layer) throw new Error("No active layer");
+
+            layer.canvas.width  = img.width;
+            layer.canvas.height = img.height;
+            layer.ctx = layer.canvas.getContext("2d");
+            layer.ctx.drawImage(img, 0, 0);
+
+            this._cb.updateCompositeView();
+            this._cb.refreshLayerList();
+            showToast("G'MIC filter applied successfully", "success");
+
+            // Reset G'MIC status
+            this.state.lastResultJobId = null;
+            this.state.processing = false;
+            if (openBtn) openBtn.disabled = false;
+            if (progressArea) progressArea.style.display = "none";
+            this._cb.renderToolOptions("filter");
+        } catch (err) {
+            showToast("Failed to apply G'MIC result: " + err.message, "error");
+            if (applyBtn) applyBtn.disabled = false;
+        }
+    }
+}
@@ -0,0 +1,303 @@
+/**
+ * Image Edit Tab - Inpaint / I2I Actions
+ * Composites the active mask layer against the background and runs it
+ * through GenerateUI's currently loaded workflow (or a dedicated one) for
+ * inpainting, plus a mask-less I2I variant. Also exposes the external
+ * entry points used by other same-origin panels (e.g. Comic Creator).
+ */
+
+import { showToast }     from "../app.js";
+import { comfyUI }       from "../comfyui-client.js";
+import { comfyEditor }   from "../comfyui-editor.js";
+import { comfyWorkflow } from "../comfyui-workflow.js";
+
+export class InpaintI2IActions {
+    /**
+     * @param {object} callbacks
+     * @param {() => object|null} callbacks.getLayerManager
+     * @param {() => HTMLCanvasElement} callbacks.buildBgCanvas
+     */
+    constructor(callbacks) {
+        this._cb = callbacks;
+
+        this.positive   = "";
+        this.negative   = "";
+        this.growMaskBy = null;  // null = 未初期化（ワークフローの現在値から初期化）
+        this.denoise    = null;  // null = 未初期化（ワークフローの現在値から初期化）
+        this.running    = false;
+        this.resultUrl  = null;
+        this.i2iExternalRunning = false;
+
+        // Inpaint 専用ワークフロー（OFF時は GenerateUI で読み込み中のワークフローを使用）
+        this.useDedicated     = false;
+        this.dedicatedFilename = null;
+        this.workflowList      = [];
+    }
+
+    async fetchWorkflowList(onLoaded) {
+        try {
+            const resp = await fetch(`${comfyUI.baseUrl}/api/wfm/workflows`);
+            if (!resp.ok) return;
+            const list = await resp.json();
+            this.workflowList = (list || []).map((w) => w.filename).filter(Boolean);
+            onLoaded?.();
+        } catch {
+            this.workflowList = [];
+        }
+    }
+
+    renderPanel() {
+        const pane  = document.getElementById("ie-props-pane");
+        const body  = document.getElementById("ie-props-body");
+        const title = document.getElementById("ie-props-title");
+        if (!pane || !body) return;
+        pane.style.display = "flex";
+        if (title) title.textContent = "Inpaint";
+
+        // 未初期化ならワークフローの現在値から初期化（VAEEncodeForInpaint.grow_mask_by / KSampler.denoise）
+        if (this.growMaskBy == null) {
+            this.growMaskBy = comfyUI.currentAnalysis?.inpaint_encode_nodes?.[0]?.grow_mask_by ?? 6;
+        }
+        if (this.denoise == null) {
+            const samplerNode = (comfyUI.currentAnalysis?.sampler_nodes || []).find((n) => n.denoise !== undefined);
+            this.denoise = samplerNode?.denoise ?? 1.0;
+        }
+
+        body.innerHTML = `
+            <div class="ie-props-row">
+                <label style="display:flex;align-items:center;gap:6px;cursor:pointer;">
+                    <input type="checkbox" id="ie-inpaint-use-dedicated" ${this.useDedicated ? "checked" : ""}>
+                    Use dedicated workflow
+                </label>
+            </div>
+            <div class="ie-props-row" id="ie-inpaint-dedicated-row" style="${this.useDedicated ? "" : "display:none;"}">
+                <select id="ie-inpaint-dedicated-select" style="flex:1;">
+                    <option value="">-- select workflow --</option>
+                    ${this.workflowList.map((f) => `<option value="${f}" ${f === this.dedicatedFilename ? "selected" : ""}>${f}</option>`).join("")}
+                </select>
+            </div>
+            <div class="ie-props-row" style="flex-direction:column;align-items:stretch;">
+                <label>Positive Prompt</label>
+                <textarea id="ie-inpaint-positive" rows="3" style="width:100%;resize:vertical;font-size:12px;">${this.positive}</textarea>
+            </div>
+            <div class="ie-props-row" style="flex-direction:column;align-items:stretch;">
+                <label>Negative Prompt</label>
+                <textarea id="ie-inpaint-negative" rows="3" style="width:100%;resize:vertical;font-size:12px;">${this.negative}</textarea>
+            </div>
+            <div class="ie-props-row">
+                <label>Grow Mask By</label>
+                <input type="number" id="ie-inpaint-grow-mask" min="0" max="200" step="1" value="${this.growMaskBy}" style="width:60px;">
+            </div>
+            <div class="ie-props-row">
+                <label>Denoise</label>
+                <input type="number" id="ie-inpaint-denoise" min="0" max="1" step="0.01" value="${this.denoise}" style="width:60px;">
+            </div>
+            <div class="ie-props-row">
+                <button class="wfm-btn wfm-btn-sm wfm-btn-primary" id="ie-inpaint-run-btn" style="flex:1;" ${this.running ? "disabled" : ""}>
+                    ${this.running ? "Running..." : "Run"}
+                </button>
+            </div>
+            <span id="ie-inpaint-status" style="font-size:11px;color:var(--wfm-text-secondary);"></span>
+            ${this.resultUrl ? `
+            <div class="ie-props-row" style="flex-direction:column;align-items:stretch;">
+                <label>Result</label>
+                <img src="${this.resultUrl}" style="max-width:100%;border-radius:var(--wfm-radius-sm);border:1px solid var(--wfm-border);">
+            </div>
+            ` : ""}
+        `;
+
+        document.getElementById("ie-inpaint-use-dedicated")?.addEventListener("change", e => {
+            this.useDedicated = e.target.checked;
+            this.renderPanel();
+        });
+        document.getElementById("ie-inpaint-dedicated-select")?.addEventListener("change", e => {
+            this.dedicatedFilename = e.target.value || null;
+        });
+        document.getElementById("ie-inpaint-positive")?.addEventListener("input", e => { this.positive = e.target.value; });
+        document.getElementById("ie-inpaint-negative")?.addEventListener("input", e => { this.negative = e.target.value; });
+        document.getElementById("ie-inpaint-grow-mask")?.addEventListener("input", e => {
+            this.growMaskBy = parseInt(e.target.value) || 0;
+        });
+        document.getElementById("ie-inpaint-denoise")?.addEventListener("input", e => {
+            this.denoise = Math.max(0, Math.min(1, parseFloat(e.target.value)));
+            if (Number.isNaN(this.denoise)) this.denoise = 1.0;
+        });
+        document.getElementById("ie-inpaint-run-btn")?.addEventListener("click", () => this.run());
+    }
+
+    _exportMaskCanvas(maskLayer) {
+        const w = maskLayer.canvas.width, h = maskLayer.canvas.height;
+        const canvas = document.createElement("canvas");
+        canvas.width = w; canvas.height = h;
+        const ctx = canvas.getContext("2d");
+        ctx.fillStyle = "#000";
+        ctx.fillRect(0, 0, w, h);
+        ctx.drawImage(maskLayer.canvas, 0, 0);
+        return canvas;
+    }
+
+    async run() {
+        if (this.running) return;
+        const layerMgr = this._cb.getLayerManager();
+        if (!layerMgr) { showToast("No image loaded", "error"); return; }
+
+        // 非表示のマスクレイヤーはInpaint対象から除外する（目玉アイコンOFF=対象外）
+        const maskLayer = (layerMgr.activeLayer?.type === "mask" && layerMgr.activeLayer.visible)
+            ? layerMgr.activeLayer
+            : layerMgr.layers.find(l => l.type === "mask" && l.visible);
+        if (!maskLayer) { showToast("Create or show a mask layer first (Mask tool)", "info"); return; }
+
+        if (this.useDedicated) {
+            if (!this.dedicatedFilename) { showToast("Select a dedicated workflow first", "info"); return; }
+        } else if (!comfyUI.currentAnalysis) {
+            showToast("Load a workflow in GenerateUI first", "info");
+            return;
+        }
+
+        const runBtn    = document.getElementById("ie-inpaint-run-btn");
+        const statusEl  = document.getElementById("ie-inpaint-status");
+        const setStatus = (msg) => { if (statusEl) statusEl.textContent = msg; };
+
+        this.running = true;
+        if (runBtn) { runBtn.disabled = true; runBtn.textContent = "Running..."; }
+        setStatus(this.useDedicated ? "Loading dedicated workflow..." : "Compositing...");
+
+        try {
+            // 専用ワークフロー使用時は GenerateUI の comfyUI.currentWorkflow/currentAnalysis には
+            // 一切触れず、ここでロード・解析したローカルなワークフロー/解析結果だけを使う。
+            let overrideOpts = {};
+
+            if (this.useDedicated) {
+                const resp = await fetch(`${comfyUI.baseUrl}/api/wfm/workflows/raw?filename=${encodeURIComponent(this.dedicatedFilename)}`);
+                if (!resp.ok) throw new Error(`Failed to load workflow (HTTP ${resp.status})`);
+                let dedicatedWorkflow = await resp.json();
+                const format = comfyWorkflow.detectFormat(dedicatedWorkflow, this.dedicatedFilename);
+                if (format === "ui") {
+                    dedicatedWorkflow = await comfyWorkflow.convertUiToApi(dedicatedWorkflow);
+                } else if (format !== "api") {
+                    throw new Error("Unsupported or unrecognized workflow format");
+                }
+                overrideOpts = { workflow: dedicatedWorkflow, analysis: comfyWorkflow.analyzeWorkflow(dedicatedWorkflow) };
+            }
+
+            setStatus("Compositing...");
+            const bgCanvas   = this._cb.buildBgCanvas();
+            const imageBlob  = await new Promise((resolve) => bgCanvas.toBlob(resolve, "image/png"));
+            const maskCanvas = this._exportMaskCanvas(maskLayer);
+            const maskBlob   = await new Promise((resolve) => maskCanvas.toBlob(resolve, "image/png"));
+
+            const resultUrl = await this._runWithImages(imageBlob, maskBlob, {
+                positive: this.positive,
+                negative: this.negative,
+                growMaskBy: this.growMaskBy,
+                denoise: this.denoise,
+                overrideOpts,
+                onStatus: setStatus,
+            });
+            if (resultUrl) this.resultUrl = resultUrl;
+
+            setStatus("Done");
+            showToast("Inpaint generation complete", "success");
+        } catch (err) {
+            setStatus("Error");
+            showToast(`Inpaint failed: ${err.message}`, "error");
+        } finally {
+            this.running = false;
+            this.renderPanel();
+        }
+    }
+
+    // 共通処理: 画像+マスクBlobを対象ノード（LoadImage/MaskEditorOne）へ反映し、
+    // プロンプト/grow_mask_by/denoiseを設定してGenerate UIで実行、結果URLを返す。
+    // UI駆動の run() と外部（Comic Creator等）向けの runExternal() の両方から使う。
+    async _runWithImages(imageBlob, maskBlob, { positive, negative, growMaskBy, denoise, overrideOpts = {}, onStatus } = {}) {
+        const setStatus = onStatus || (() => {});
+
+        // LoadImage(の MASK 出力が使われている)スロットを優先し、無ければ Mask Editor One
+        // ノード（LoadImage を介さず画像/マスクを内包する custom node）にフォールバックする
+        const analysisForLookup = overrideOpts.analysis || comfyUI.currentAnalysis;
+        if (!analysisForLookup) throw new Error("No workflow loaded in GenerateUI");
+        const slotIndex = (analysisForLookup.load_image_nodes || []).findIndex(n => n.mask_used);
+        const meoNode = (analysisForLookup.mask_editor_one_nodes || [])[0];
+        if (slotIndex === -1 && !meoNode) {
+            throw new Error("No inpaint-capable LoadImage or Mask Editor One node found in the workflow");
+        }
+
+        setStatus("Uploading...");
+        if (slotIndex !== -1) {
+            await comfyEditor.applyImageAndMaskToSlot(imageBlob, maskBlob, slotIndex, overrideOpts);
+        } else {
+            await comfyEditor.applyImageAndMaskToMaskEditorOneNode(imageBlob, maskBlob, meoNode.id, overrideOpts);
+        }
+
+        comfyEditor.setPromptText("positive", positive, overrideOpts);
+        comfyEditor.setPromptText("negative", negative, overrideOpts);
+        comfyEditor.setInpaintParams({ growMaskBy, denoise, ...overrideOpts });
+
+        if (!window._wfmGenerateTab?.generate) throw new Error("GenerateUI is not ready yet");
+
+        setStatus("Generating...");
+        await window._wfmGenerateTab.generate(overrideOpts.workflow || undefined);
+
+        const resultImg = document.getElementById("wfm-gen-result-img");
+        return resultImg?.src || null;
+    }
+
+    // Comic Creator等、同一オリジンiframe越しの外部呼び出し専用エントリポイント。
+    // 専用ワークフロー選択(useDedicated)は扱わず、常にGenerate UIに現在
+    // ロード中のワークフロー（comfyUI.currentWorkflow/currentAnalysis）を対象にする。
+    async runExternal(imageBlob, maskBlob, { positive = "", negative = "", growMaskBy = 6, denoise = 1.0 } = {}) {
+        if (this.running) throw new Error("Inpaint is already running");
+        this.running = true;
+        try {
+            const resultUrl = await this._runWithImages(imageBlob, maskBlob, { positive, negative, growMaskBy, denoise });
+            if (!resultUrl) throw new Error("No result image produced");
+            return { ok: true, url: resultUrl };
+        } finally {
+            this.running = false;
+        }
+    }
+
+    // 共通処理: 画像Blob（マスクなし）を対象LoadImageノード(slot 0)へ反映し、
+    // プロンプト/denoiseを設定してGenerate UIで実行、結果URLを返す。
+    // _runWithImages のマスクなし版（Comic CreatorのSelect I2I連携専用）。
+    async _runI2IWithImage(imageBlob, { positive, negative, denoise, overrideOpts = {}, onStatus } = {}) {
+        const setStatus = onStatus || (() => {});
+
+        const analysisForLookup = overrideOpts.analysis || comfyUI.currentAnalysis;
+        if (!analysisForLookup) throw new Error("No workflow loaded in GenerateUI");
+        if (!(analysisForLookup.load_image_nodes?.length > 0)) {
+            throw new Error("No LoadImage node found in the workflow");
+        }
+
+        setStatus("Uploading...");
+        const file = new File([imageBlob], `i2i_${Math.random().toString(36).slice(2, 10)}.png`, { type: "image/png" });
+        await comfyEditor.applyImageToSlot(file, 0, overrideOpts);
+
+        comfyEditor.setPromptText("positive", positive, overrideOpts);
+        comfyEditor.setPromptText("negative", negative, overrideOpts);
+        comfyEditor.setInpaintParams({ denoise, ...overrideOpts });
+
+        if (!window._wfmGenerateTab?.generate) throw new Error("GenerateUI is not ready yet");
+
+        setStatus("Generating...");
+        await window._wfmGenerateTab.generate(overrideOpts.workflow || undefined);
+
+        const resultImg = document.getElementById("wfm-gen-result-img");
+        return resultImg?.src || null;
+    }
+
+    // Comic Creator等、同一オリジンiframe越しの外部呼び出し専用エントリポイント（I2I版）。
+    // runExternal と対になる、マスク不要のシンプルなI2I実行。
+    async runI2IExternal(imageBlob, { positive = "", negative = "", denoise = 1.0 } = {}) {
+        if (this.i2iExternalRunning) throw new Error("I2I is already running");
+        this.i2iExternalRunning = true;
+        try {
+            const resultUrl = await this._runI2IWithImage(imageBlob, { positive, negative, denoise });
+            if (!resultUrl) throw new Error("No result image produced");
+            return { ok: true, url: resultUrl };
+        } finally {
+            this.i2iExternalRunning = false;
+        }
+    }
+}
@@ -0,0 +1,102 @@
+/**
+ * Image Edit Tab - Mask Editor One 連携ブリッジ
+ * WFS Image Edit タブの合成画像を、ComfyUIキャンバス上のMaskEditorOneノード（選択中のノードを
+ * 優先、無ければグラフ内で最初に見つかったもの）へ送り、window.opener（ComfyUIタブ）側で実際の
+ * モーダルを開いて編集させ、Apply後の結果マスクを新規マスクレイヤーとしてWFS側に取り込む。
+ * 「Send to Workflow」の image ウィジェット探索と同じ「選択中優先・フォールバック」方式のため、
+ * WFS側のワークフロー読み込み状況とは無関係に動作する。
+ * モーダル自体は ComfyUI ページの LiteGraph ノードに強く依存するため、WFS 側からは
+ * window.opener.wfmOpenMaskEditorForNode()（web/comfyui/node_sets_menu.js 側で定義）を介して操作する。
+ */
+
+import { showToast } from "../app.js";
+
+export class MaskEditorOneBridge {
+    /**
+     * @param {object} callbacks
+     * @param {() => object|null} callbacks.getLayerManager
+     * @param {() => void} callbacks.saveUndo
+     * @param {() => void} callbacks.updateCompositeView
+     * @param {() => void} callbacks.refreshLayerList
+     * @param {() => HTMLCanvasElement} callbacks.buildBgCanvas
+     */
+    constructor(callbacks) {
+        this._cb = callbacks;
+        this.running = false;
+    }
+
+    get bridgeReady() {
+        return !!(window.opener && typeof window.opener.wfmOpenMaskEditorForNode === "function");
+    }
+
+    async openEditor() {
+        if (this.running) return;
+        if (!this.bridgeReady) {
+            showToast("Open Workflow Studio from ComfyUI's top menu to use this feature", "error");
+            return;
+        }
+        const layerMgr = this._cb.getLayerManager();
+        if (!layerMgr) { showToast("No image loaded", "error"); return; }
+
+        this.running = true;
+        try {
+            const dataUrl = this._cb.buildBgCanvas().toDataURL("image/png");
+            // アクティブレイヤーが既存のマスクレイヤーなら、その内容もそのまま Mask Editor One の
+            // 初期マスクとして渡す（画像だけでなく、今描いているマスクも引き継ぐ）
+            const activeLayer = layerMgr.activeLayer;
+            const existingMaskDataUrl = activeLayer?.type === "mask" ? activeLayer.canvas.toDataURL("image/png") : null;
+            window.opener.focus();
+            showToast("Switch to the ComfyUI tab, edit the mask, then click Apply", "info");
+
+            const maskDataUrl = await window.opener.wfmOpenMaskEditorForNode(dataUrl, existingMaskDataUrl);
+            if (!maskDataUrl) {
+                showToast("Mask Editor One: cancelled (no changes)", "info");
+                return;
+            }
+
+            this._cb.saveUndo();
+            const maskLayer = layerMgr.addLayer("mask", "Mask Editor One", {
+                contentW: layerMgr.width, contentH: layerMgr.height,
+                displayW: layerMgr.width, displayH: layerMgr.height,
+                x: 0, y: 0,
+            });
+            layerMgr.setActive(maskLayer.id);
+            await this._applyMask(maskLayer, maskDataUrl);
+
+            this._cb.updateCompositeView();
+            this._cb.refreshLayerList();
+            showToast("Mask Editor One: mask imported", "success");
+        } catch (err) {
+            showToast("Mask Editor One error: " + err.message, "error");
+        } finally {
+            this.running = false;
+        }
+    }
+
+    // グレースケール輝度 → アルファ白マスクに変換して書き込む（Sam3Segmentation._applyMask と同じ変換）
+    _applyMask(maskLayer, maskDataUrl) {
+        return new Promise(resolve => {
+            const img = new Image();
+            img.onload = () => {
+                const W = maskLayer.canvas.width;
+                const H = maskLayer.canvas.height;
+                const off = document.createElement("canvas");
+                off.width = W; off.height = H;
+                const mc = off.getContext("2d");
+                mc.drawImage(img, 0, 0, W, H);
+                const imgData = mc.getImageData(0, 0, W, H);
+                const d = imgData.data;
+                for (let i = 0; i < d.length; i += 4) {
+                    const lum = d[i];
+                    d[i] = d[i + 1] = d[i + 2] = 255;
+                    d[i + 3] = lum;
+                }
+                mc.putImageData(imgData, 0, 0);
+                maskLayer.ctx.drawImage(off, 0, 0);
+                resolve();
+            };
+            img.onerror = resolve;
+            img.src = maskDataUrl;
+        });
+    }
+}
@@ -25,6 +25,11 @@ export class MaskTool {
        this.sizeJitterAmount = 0.5;    // 0–1: fraction of brushSize that can be removed
        this.rotationJitter   = false;

+        // Pen pressure (0–1, from PointerEvent.pressure; mouse reports 0.5).
+        // pressure=0.5 maps to a 1.0x multiplier so mouse behavior is unchanged.
+        this.pressureEnabled = true;
+        this._lastPressure   = 0.5;
+
        this._drawing    = false;
        this._lastX      = 0;
        this._lastY      = 0;
@@ -80,29 +85,31 @@ export class MaskTool {
        if (this.canvas) this.canvas.style.cursor = "";
    }

-    onMouseDown(x, y) {
-        this._drawing = true;
-        this._lastX   = x;
-        this._lastY   = y;
+    onMouseDown(x, y, pressure = 0.5) {
+        this._drawing      = true;
+        this._lastX         = x;
+        this._lastY         = y;
+        this._lastPressure  = pressure;
        if (this.brushImage) {
            this._initStrokeBuffer();
-            this._paintToStroke(x, y);
+            this._paintToStroke(x, y, pressure);
            this._mergeStroke();
        } else {
-            this._paint(x, y);
+            this._paint(x, y, pressure);
        }
    }

-    onMouseMove(x, y) {
+    onMouseMove(x, y, pressure = 0.5) {
        if (!this._drawing) return;
        if (this.brushImage) {
-            this._paintLineToStroke(this._lastX, this._lastY, x, y);
+            this._paintLineToStroke(this._lastX, this._lastY, x, y, this._lastPressure, pressure);
            this._mergeStroke();
        } else {
-            this._paintLine(this._lastX, this._lastY, x, y);
+            this._paintLine(this._lastX, this._lastY, x, y, this._lastPressure, pressure);
        }
-        this._lastX = x;
-        this._lastY = y;
+        this._lastX        = x;
+        this._lastY        = y;
+        this._lastPressure = pressure;
    }

    onMouseUp() {
@@ -117,6 +124,14 @@ export class MaskTool {
        if (this._drawing) this.onMouseUp();
    }

+    // ── Pressure response ──────────────────────────────────────────────
+
+    _effectiveSize(pressure) {
+        if (!this.pressureEnabled) return this.brushSize;
+        const p = Math.max(0, Math.min(1, pressure ?? 0.5));
+        return Math.max(1, this.brushSize * (0.3 + p * 1.4)); // p=0.5 -> 1.0x
+    }
+
    // ── Stroke buffer (image brush only) ─────────────────────────────

    _initStrokeBuffer() {
@@ -149,54 +164,48 @@ export class MaskTool {
        ctx.globalCompositeOperation = "source-over";
    }

-    _paintToStroke(x, y) {
+    _paintToStroke(x, y, pressure = 0.5) {
        const saved = this.ctx;
        this.ctx = this._strokeCtx;

-        if (this.sizeJitter || this.rotationJitter) {
-            const savedSize      = this.brushSize;
-            const savedAngle     = this.angle;
-            const savedStamp     = this._imgStamp;
-            const savedStampSize = this._imgStampSize;
-            if (this.sizeJitter) {
-                this.brushSize = Math.max(1, savedSize * (1 - Math.random() * this.sizeJitterAmount));
-            }
-            if (this.rotationJitter) {
-                this.angle = Math.random() * 360;
-            }
-            this._paintImageBrush(x, y);
-            this.brushSize     = savedSize;
-            this.angle         = savedAngle;
-            this._imgStamp     = savedStamp;
-            this._imgStampSize = savedStampSize;
+        let size = this._effectiveSize(pressure);
+        if (this.sizeJitter) {
+            size = Math.max(1, size * (1 - Math.random() * this.sizeJitterAmount));
+        }
+
+        if (this.rotationJitter) {
+            const savedAngle = this.angle;
+            this.angle = Math.random() * 360;
+            this._paintImageBrush(x, y, size);
+            this.angle = savedAngle;
        } else {
-            this._paintImageBrush(x, y);
+            this._paintImageBrush(x, y, size);
        }

        this.ctx = saved;
    }

-    _paintLineToStroke(x0, y0, x1, y1) {
+    _paintLineToStroke(x0, y0, x1, y1, p0 = 0.5, p1 = 0.5) {
        const dist  = Math.hypot(x1 - x0, y1 - y0);
        const step  = Math.max(1, this.brushSize * this.spacing);
        const steps = Math.ceil(dist / step);
        for (let i = 1; i <= steps; i++) {
            const t = i / steps;
-            this._paintToStroke(x0 + (x1 - x0) * t, y0 + (y1 - y0) * t);
+            this._paintToStroke(x0 + (x1 - x0) * t, y0 + (y1 - y0) * t, p0 + (p1 - p0) * t);
        }
    }

    // ── Circle brush ─────────────────────────────────────────────────

-    _getStamp() {
+    _getStamp(size) {
+        size = Math.max(1, Math.round(size));
        if (
            this._stamp &&
-            this._stampSize === this.brushSize &&
+            this._stampSize === size &&
            this._stampHard === this.hardness &&
            this._stampMode === this.mode
        ) return this._stamp;

-        const size  = Math.max(1, Math.round(this.brushSize));
        const sc    = document.createElement("canvas");
        sc.width    = size;
        sc.height   = size;
@@ -222,8 +231,9 @@ export class MaskTool {
        return sc;
    }

-    _paint(x, y) {
-        const stamp = this._getStamp();
+    _paint(x, y, pressure = 0.5) {
+        const size  = this._effectiveSize(pressure);
+        const stamp = this._getStamp(size);
        const s     = stamp.width;
        this.ctx.save();
        if (this.mode === "erase") {
@@ -233,13 +243,13 @@ export class MaskTool {
        this.ctx.restore();
    }

-    _paintLine(x0, y0, x1, y1) {
+    _paintLine(x0, y0, x1, y1, p0 = 0.5, p1 = 0.5) {
        const dist    = Math.hypot(x1 - x0, y1 - y0);
        const spacing = Math.max(1, this.brushSize * 0.2);
        const steps   = Math.max(1, Math.ceil(dist / spacing));
        for (let i = 1; i <= steps; i++) {
            const t = i / steps;
-            this._paint(x0 + (x1 - x0) * t, y0 + (y1 - y0) * t);
+            this._paint(x0 + (x1 - x0) * t, y0 + (y1 - y0) * t, p0 + (p1 - p0) * t);
        }
    }

@@ -307,8 +317,8 @@ export class MaskTool {
        return sc;
    }

-    _paintImageBrush(x, y) {
-        const stamp = this._getImageStamp(Math.round(this.brushSize));
+    _paintImageBrush(x, y, size = this.brushSize) {
+        const stamp = this._getImageStamp(Math.round(size));
        this.ctx.globalCompositeOperation = "source-over";
        if (this.angle) {
            this.ctx.save();
@@ -0,0 +1,248 @@
+/**
+ * Image Edit Tab - SAM3 Segmentation (Mask Editor One integration)
+ * Text-prompted segmentation via the Mask Editor One SAM3 server endpoints.
+ * Rendered as a subtool of the Mask tool; the toolbar shell itself stays in
+ * ImageEditTab (shared with the other mask subtools), but the prompt/run
+ * controls and the result thumbnail grid are owned here.
+ */
+
+import { showToast } from "../app.js";
+
+export class Sam3Segmentation {
+    /**
+     * @param {object} callbacks
+     * @param {() => object|null} callbacks.getLayerManager
+     * @param {() => void} callbacks.saveUndo
+     * @param {() => void} callbacks.updateCompositeView
+     * @param {() => void} callbacks.refreshLayerList
+     * @param {(toolId: string) => void} callbacks.renderToolOptions
+     * @param {(sub: string) => void} callbacks.renderMaskProps
+     */
+    constructor(callbacks) {
+        this._cb = callbacks;
+        this.available = false;
+        this.results   = [];   // [{mask_b64, score, area}, ...]
+        this.prompt    = "";
+        this.maxMasks  = 9;
+        this.loading   = false;
+        this.mode      = "add";        // "add" | "erase"
+        this.selected  = new Set();    // 選択中の結果インデックス
+    }
+
+    async checkAvailability() {
+        try {
+            const resp = await fetch("/mask_editor/sam3/status");
+            if (!resp.ok) return;
+            const json = await resp.json();
+            this.available = json.loaded === true || json.ckpt_found === true;
+        } catch {
+            this.available = false;
+        }
+    }
+
+    // マスクツールバー内、SAM3選択時にのみ表示するprompt/max/runコントロール
+    renderToolbarExtra(activeSub) {
+        if (!this.available || activeSub !== "sam3") return "";
+        return `
+            <div class="ie-opt-group">
+                <input type="text" id="ie-sam3-prompt" class="ie-opt-input"
+                    placeholder="e.g. cat, person..."
+                    value="${this.prompt}"
+                    style="width:160px;font-size:11px;padding:2px 6px;border:1px solid var(--wfm-border);border-radius:3px;background:var(--wfm-surface);color:var(--wfm-text);">
+            </div>
+            <div class="ie-opt-group">
+                <label style="font-size:11px;color:var(--wfm-text-secondary);">Max</label>
+                <select id="ie-sam3-max" class="ie-opt-select" style="width:44px;">
+                    ${[3,6,9,12].map(n => `<option value="${n}"${n === this.maxMasks ? " selected" : ""}>${n}</option>`).join("")}
+                </select>
+            </div>
+            <div class="ie-opt-group">
+                <button class="wfm-btn wfm-btn-sm wfm-btn-primary" id="ie-sam3-run-btn" ${this.loading ? "disabled" : ""}>
+                    ${this.loading ? "Running..." : "Segment"}
+                </button>
+            </div>
+            <span id="ie-sam3-status" style="font-size:11px;color:var(--wfm-text-secondary);margin-left:4px;">
+                ${this.results.length > 0 ? `${this.results.length} masks found` : ""}
+            </span>
+        `;
+    }
+
+    bindToolbarEvents() {
+        document.getElementById("ie-sam3-prompt")?.addEventListener("input", e => {
+            this.prompt = e.target.value;
+        });
+        document.getElementById("ie-sam3-max")?.addEventListener("change", e => {
+            this.maxMasks = parseInt(e.target.value);
+        });
+        document.getElementById("ie-sam3-run-btn")?.addEventListener("click", () => this.runSegment());
+    }
+
+    // props ペイン（"sam3" サブツール選択時）: モード切替 + 結果サムネイルグリッド
+    renderResultsPanel(body) {
+        const modeAdd   = this.mode === "add";
+        const selCount  = this.selected.size;
+        const hasResult = this.results.length > 0;
+        body.innerHTML = `
+            <div class="ie-props-row">
+                <label>Mode</label>
+                <div style="display:flex;gap:4px;">
+                    <button class="wfm-btn wfm-btn-sm${modeAdd   ? " ie-opt-active" : ""}" id="ie-sam3-mode-add"   style="flex:1;">Add</button>
+                    <button class="wfm-btn wfm-btn-sm${!modeAdd  ? " ie-opt-active" : ""}" id="ie-sam3-mode-erase" style="flex:1;">Erase</button>
+                </div>
+            </div>
+            ${hasResult ? `
+            <div class="ie-props-row" style="flex-direction:column;align-items:stretch;gap:4px;">
+                <div style="font-size:11px;color:var(--wfm-text-secondary);">Click to select / deselect:</div>
+                <div id="ie-sam3-results" style="display:grid;grid-template-columns:repeat(3,1fr);gap:4px;">
+                    ${this.results.map((r, i) => {
+                        const sel = this.selected.has(i);
+                        const borderColor = sel ? "var(--wfm-primary,#4682e6)" : "var(--wfm-border)";
+                        const bg          = sel ? "color-mix(in srgb,var(--wfm-primary,#4682e6) 15%,transparent)" : "transparent";
+                        return `<div class="ie-sam3-thumb" data-idx="${i}"
+                            style="cursor:pointer;border:2px solid ${borderColor};border-radius:4px;overflow:hidden;text-align:center;background:${bg};position:relative;">
+                            <img src="${r.mask_b64}" style="width:100%;display:block;background:#000;">
+                            <div style="font-size:10px;padding:2px 0;color:var(--wfm-text-secondary);">
+                                ${Math.round((r.score ?? 0) * 100)}%
+                            </div>
+                            ${sel ? '<div style="position:absolute;top:2px;right:3px;font-size:12px;line-height:1;color:var(--wfm-primary,#4682e6);">✓</div>' : ""}
+                        </div>`;
+                    }).join("")}
+                </div>
+                <button class="wfm-btn wfm-btn-sm wfm-btn-primary" id="ie-sam3-apply-btn"
+                    ${selCount === 0 ? "disabled" : ""} style="margin-top:4px;">
+                    Apply Selected${selCount > 0 ? ` (${selCount})` : ""}
+                </button>
+            </div>` : `
+            <div style="font-size:11px;color:var(--wfm-text-secondary);padding:4px 0;">
+                ${this.loading ? "Segmenting..." : "Enter a prompt and press Segment"}
+            </div>`}
+        `;
+        document.getElementById("ie-sam3-mode-add")?.addEventListener("click", () => {
+            this.mode = "add";
+            this._cb.renderMaskProps("sam3");
+        });
+        document.getElementById("ie-sam3-mode-erase")?.addEventListener("click", () => {
+            this.mode = "erase";
+            this._cb.renderMaskProps("sam3");
+        });
+        body.querySelectorAll(".ie-sam3-thumb").forEach(el => {
+            el.addEventListener("click", () => {
+                const idx = parseInt(el.dataset.idx);
+                if (this.selected.has(idx)) this.selected.delete(idx);
+                else                        this.selected.add(idx);
+                this._cb.renderMaskProps("sam3");
+            });
+        });
+        document.getElementById("ie-sam3-apply-btn")?.addEventListener("click", () => {
+            this.applySelectedMasks();
+        });
+    }
+
+    async runSegment() {
+        const layerMgr = this._cb.getLayerManager();
+        if (!layerMgr || this.loading) return;
+        const prompt = this.prompt.trim();
+        if (!prompt) { showToast("Please enter a prompt", "warning"); return; }
+
+        // 推論対象: アクティブレイヤー（マスクなら下のイメージレイヤーを探す）
+        let imageLayer = layerMgr.activeLayer;
+        if (!imageLayer || imageLayer.type === "mask") {
+            imageLayer = layerMgr.layers.find(l => l.type !== "mask" && l.visible);
+        }
+        if (!imageLayer) { showToast("No image layer found", "error"); return; }
+
+        const NODE_ID = "wfs_sam3";
+        this.loading  = true;
+        this.results  = [];
+        this.selected = new Set();
+        this._cb.renderToolOptions("mask");
+        this._cb.renderMaskProps("sam3");
+
+        try {
+            const dataUrl = imageLayer.canvas.toDataURL("image/png");
+            await fetch("/mask_editor/store_image", {
+                method:  "POST",
+                headers: { "Content-Type": "application/json" },
+                body:    JSON.stringify({ node_id: NODE_ID, image_b64: dataUrl }),
+            });
+
+            const resp = await fetch("/mask_editor/sam3/segment", {
+                method:  "POST",
+                headers: { "Content-Type": "application/json" },
+                body:    JSON.stringify({ node_id: NODE_ID, prompt, max_masks: this.maxMasks }),
+            });
+            const json = await resp.json();
+            if (json.error) throw new Error(json.error);
+            this.results = json.masks || [];
+            if (this.results.length === 0) showToast("No masks found", "warning");
+            else showToast(`${this.results.length} mask(s) found`, "success");
+        } catch (err) {
+            showToast("SAM3 error: " + err.message, "error");
+        } finally {
+            this.loading = false;
+            this._cb.renderToolOptions("mask");
+            this._cb.renderMaskProps("sam3");
+        }
+    }
+
+    async applySelectedMasks() {
+        const layerMgr = this._cb.getLayerManager();
+        if (!layerMgr || this.selected.size === 0) return;
+        const indices = [...this.selected].sort((a, b) => a - b);
+        const masks   = indices.map(i => this.results[i]).filter(Boolean);
+        if (masks.length === 0) return;
+
+        let maskLayer = layerMgr.activeLayer;
+        if (!maskLayer || maskLayer.type !== "mask") {
+            const ref = layerMgr.activeLayer;
+            maskLayer = layerMgr.addLayer("mask", "SAM3 Mask", {
+                contentW: ref?.canvas.width  ?? layerMgr.width,
+                contentH: ref?.canvas.height ?? layerMgr.height,
+                displayW: ref?.displayW      ?? layerMgr.width,
+                displayH: ref?.displayH      ?? layerMgr.height,
+                x: ref?.x ?? 0, y: ref?.y ?? 0,
+            });
+            layerMgr.setActive(maskLayer.id);
+        }
+
+        this._cb.saveUndo();
+        for (const r of masks) {
+            await this._applyMask(maskLayer, r.mask_b64, this.mode);
+        }
+
+        this._cb.updateCompositeView();
+        this._cb.refreshLayerList();
+        showToast(`SAM3: ${masks.length} mask(s) applied (${this.mode})`, "success");
+    }
+
+    _applyMask(maskLayer, maskB64, mode = "add") {
+        return new Promise(resolve => {
+            const img = new Image();
+            img.onload = () => {
+                const W = maskLayer.canvas.width;
+                const H = maskLayer.canvas.height;
+                // グレースケール輝度 → アルファ白マスクに変換
+                const off = document.createElement("canvas");
+                off.width = W; off.height = H;
+                const mc = off.getContext("2d");
+                mc.drawImage(img, 0, 0, W, H);
+                const imgData = mc.getImageData(0, 0, W, H);
+                const d = imgData.data;
+                for (let i = 0; i < d.length; i += 4) {
+                    const lum = d[i];
+                    d[i] = d[i+1] = d[i+2] = 255;
+                    d[i+3] = lum;
+                }
+                mc.putImageData(imgData, 0, 0);
+                // モードに合わせてマスクキャンバスに合成
+                maskLayer.ctx.save();
+                maskLayer.ctx.globalCompositeOperation = mode === "erase" ? "destination-out" : "source-over";
+                maskLayer.ctx.drawImage(off, 0, 0);
+                maskLayer.ctx.restore();
+                resolve();
+            };
+            img.onerror = resolve;
+            img.src = maskB64;
+        });
+    }
+}
@@ -0,0 +1,363 @@
+/**
+ * ImagePrompt Gallery — Gallery タブのサブタブ。
+ * ws_image_prompt フォルダ配下の画像+.txtサイドカーを閲覧し、
+ * クリックで選択→「追加」でプロンプトを組み立てて最終的にコピーする。
+ */
+
+import { showToast } from "./app.js";
+import { t } from "./i18n.js";
+import { escapeHtml, setupSearchClearBtn } from "./util.js";
+
+const API = {
+    root:        () => `/wfm/gallery/image-prompt/root`,
+    folders:     (root)   => `/wfm/gallery/folders?root=${encodeURIComponent(root)}`,
+    images:      (params) => `/wfm/gallery/images?${new URLSearchParams(params)}`,
+    imageMeta:   (path)   => `/wfm/gallery/image/meta?path=${encodeURIComponent(path)}`,
+    thumb:       (path, w = 200) => `/wfm/gallery/image/thumb?path=${encodeURIComponent(path)}&w=${w}`,
+    serveImage:  (path)   => `/wfm/gallery/image/serve?path=${encodeURIComponent(path)}`,
+    savePrompt:            `/wfm/gallery/image/image-prompt`,
+};
+
+const state = {
+    root: null,
+    currentFolder: null,
+    search: "",
+    images: [],
+    selectedImage: null,
+    chips: [], // [{ path, filename, prompt }]
+};
+
+let _initialized = false;
+
+async function apiFetch(url, opts = {}) {
+    const res = await fetch(url, opts);
+    if (!res.ok) throw new Error(`HTTP ${res.status}`);
+    return res.json();
+}
+
+function debounce(fn, wait) {
+    let timer;
+    return (...args) => {
+        clearTimeout(timer);
+        timer = setTimeout(() => fn(...args), wait);
+    };
+}
+
+// ── 初期化 ────────────────────────────────────────────────────
+
+export function initImagePromptTab() {
+    document.getElementById("wfm-imageprompt-refresh-btn")?.addEventListener("click", () => {
+        loadFolderTree();
+        loadImages();
+    });
+
+    setupSearchClearBtn("wfm-imageprompt-search", "wfm-imageprompt-search-clear-btn", () => {
+        state.search = "";
+        loadImages();
+    });
+
+    const searchInput = document.getElementById("wfm-imageprompt-search");
+    searchInput?.addEventListener("input", debounce(() => {
+        state.search = searchInput.value.trim();
+        loadImages();
+    }, 300));
+
+    document.getElementById("wfm-imageprompt-add-btn")?.addEventListener("click", addSelectedToChips);
+    document.getElementById("wfm-imageprompt-save-prompt-btn")?.addEventListener("click", saveSelectedPrompt);
+    document.getElementById("wfm-imageprompt-clear-btn")?.addEventListener("click", clearAllChips);
+    document.getElementById("wfm-imageprompt-copy-btn")?.addEventListener("click", copyFinalPrompt);
+}
+
+export async function activateImagePromptTab() {
+    if (_initialized) return;
+    _initialized = true;
+    try {
+        const data = await apiFetch(API.root());
+        state.root = data.root;
+        await loadFolderTree();
+    } catch (e) {
+        const tree = document.getElementById("wfm-imageprompt-tree");
+        if (tree) tree.innerHTML = `<p class="wfm-placeholder">Error: ${escapeHtml(e.message)}</p>`;
+    }
+}
+
+// ── フォルダツリー ────────────────────────────────────────────
+
+async function loadFolderTree() {
+    if (!state.root) return;
+    const tree = document.getElementById("wfm-imageprompt-tree");
+    tree.innerHTML = `<p class="wfm-placeholder">${t("loading")}</p>`;
+    try {
+        const data = await apiFetch(API.folders(state.root));
+        if (data.error) {
+            tree.innerHTML = `<p class="wfm-placeholder">${escapeHtml(data.error)}</p>`;
+            return;
+        }
+        tree.innerHTML = "";
+        renderTreeNode(data, tree, 0, true);
+        const firstLabel = tree.querySelector(".wfm-gallery-tree-label");
+        if (firstLabel) firstLabel.click();
+    } catch (e) {
+        tree.innerHTML = `<p class="wfm-placeholder">Error: ${escapeHtml(e.message)}</p>`;
+    }
+}
+
+function renderTreeNode(node, container, depth, isRoot) {
+    const item = document.createElement("div");
+    item.className = "wfm-gallery-tree-item";
+    item.style.paddingLeft = `${depth * 12}px`;
+    item.dataset.path = node.abs_path;
+
+    const hasChildren = node.children && node.children.length > 0;
+    const absPath = node.abs_path;
+
+    const arrow = document.createElement("span");
+    arrow.className = "wfm-gallery-tree-arrow";
+    if (hasChildren) {
+        arrow.textContent = "▶";
+        arrow.dataset.expanded = "false";
+    } else {
+        arrow.textContent = " ";
+        arrow.style.visibility = "hidden";
+    }
+    item.appendChild(arrow);
+
+    const label = document.createElement("span");
+    label.className = "wfm-gallery-tree-label";
+    label.textContent = isRoot ? "[root]" : node.name;
+    // サブフォルダ内も含めた合計件数（クリックで再帰的に全画像を表示するため）
+    const totalCount = node.image_count_total ?? node.image_count;
+    if (totalCount > 0) {
+        const badge = document.createElement("span");
+        badge.className = "wfm-gallery-tree-count";
+        badge.textContent = totalCount;
+        label.appendChild(badge);
+    }
+    item.appendChild(label);
+
+    label.addEventListener("click", () => {
+        document.querySelectorAll("#wfm-imageprompt-tree .wfm-gallery-tree-item.selected").forEach(el => el.classList.remove("selected"));
+        item.classList.add("selected");
+        state.currentFolder = absPath;
+        loadImages();
+    });
+
+    if (hasChildren) {
+        const childContainer = document.createElement("div");
+        childContainer.className = "wfm-gallery-tree-children";
+        childContainer.style.display = "none";
+
+        arrow.addEventListener("click", (e) => {
+            e.stopPropagation();
+            const expanded = arrow.dataset.expanded === "true";
+            if (!expanded) {
+                arrow.dataset.expanded = "true";
+                arrow.textContent = "▼";
+                childContainer.style.display = "";
+                if (childContainer.children.length === 0) {
+                    node.children.forEach(child => renderTreeNode(child, childContainer, depth + 1, false));
+                }
+            } else {
+                arrow.dataset.expanded = "false";
+                arrow.textContent = "▶";
+                childContainer.style.display = "none";
+            }
+        });
+
+        container.appendChild(item);
+        container.appendChild(childContainer);
+    } else {
+        container.appendChild(item);
+    }
+}
+
+// ── 画像一覧 ─────────────────────────────────────────────────
+
+async function loadImages() {
+    if (!state.currentFolder) return;
+    const grid = document.getElementById("wfm-imageprompt-grid");
+    grid.innerHTML = `<p class="wfm-placeholder">${t("loading")}</p>`;
+
+    // 上位フォルダを選択した場合もサブフォルダの画像をまとめて表示する
+    const params = { folder: state.currentFolder, sort: "name_asc", recursive: "true" };
+    if (state.search) params.search = state.search;
+
+    try {
+        const data = await apiFetch(API.images(params));
+        state.images = data.images || [];
+        document.getElementById("wfm-imageprompt-count").textContent = `${state.images.length} images`;
+        renderImages();
+    } catch (e) {
+        grid.innerHTML = `<p class="wfm-placeholder">Error: ${escapeHtml(e.message)}</p>`;
+    }
+}
+
+function renderImages() {
+    const grid = document.getElementById("wfm-imageprompt-grid");
+    if (state.images.length === 0) {
+        grid.innerHTML = `<p class="wfm-placeholder">${t("galleryNoImages")}</p>`;
+        return;
+    }
+    grid.innerHTML = "";
+    const fragment = document.createDocumentFragment();
+    state.images.forEach(img => fragment.appendChild(createThumbCard(img)));
+    grid.appendChild(fragment);
+}
+
+function createThumbCard(img) {
+    const card = document.createElement("div");
+    card.className = "wfm-gallery-thumb-card";
+    card.title = img.filename;
+    card.dataset.path = img.path;
+    if (state.selectedImage && state.selectedImage.path === img.path) {
+        card.classList.add("selected");
+    }
+
+    const imgEl = document.createElement("img");
+    imgEl.className = "wfm-gallery-thumb-img";
+    imgEl.loading = "lazy";
+    imgEl.src = API.thumb(img.path);
+    imgEl.alt = img.filename;
+    imgEl.onerror = () => {
+        imgEl.style.display = "none";
+        const placeholder = document.createElement("div");
+        placeholder.className = "wfm-gallery-thumb-placeholder";
+        placeholder.textContent = "?";
+        card.insertBefore(placeholder, imgEl.nextSibling);
+    };
+    card.appendChild(imgEl);
+
+    card.addEventListener("click", () => selectImage(img));
+
+    return card;
+}
+
+// ── 選択画像 / プロンプト表示 ─────────────────────────────────
+
+async function selectImage(img) {
+    state.selectedImage = img;
+    document.querySelectorAll("#wfm-imageprompt-grid .wfm-gallery-thumb-card").forEach(el => {
+        el.classList.toggle("selected", el.dataset.path === img.path);
+    });
+
+    document.getElementById("wfm-imageprompt-selected-name").textContent = img.filename;
+    const preview = document.getElementById("wfm-imageprompt-selected-preview");
+    preview.innerHTML = "";
+    const previewImg = document.createElement("img");
+    previewImg.src = API.serveImage(img.path);
+    previewImg.alt = img.filename;
+    previewImg.style.cssText = "max-width:100%;max-height:100%;object-fit:contain;";
+    preview.appendChild(previewImg);
+
+    const promptBox = document.getElementById("wfm-imageprompt-selected-prompt");
+    promptBox.value = "";
+    document.getElementById("wfm-imageprompt-save-prompt-btn").disabled = true;
+    document.getElementById("wfm-imageprompt-add-btn").disabled = true;
+
+    try {
+        const meta = await apiFetch(API.imageMeta(img.path));
+        promptBox.value = meta.image_prompt || "";
+        document.getElementById("wfm-imageprompt-save-prompt-btn").disabled = false;
+        document.getElementById("wfm-imageprompt-add-btn").disabled = !meta.image_prompt;
+    } catch (e) {
+        showToast(t("errorWithMsg", e.message), "error");
+    }
+}
+
+async function saveSelectedPrompt() {
+    if (!state.selectedImage) return;
+    const promptBox = document.getElementById("wfm-imageprompt-selected-prompt");
+    try {
+        const res = await apiFetch(API.savePrompt, {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify({ path: state.selectedImage.path, prompt: promptBox.value }),
+        });
+        if (res.ok) {
+            showToast(t("imagePromptSaved"), "success");
+            document.getElementById("wfm-imageprompt-add-btn").disabled = !promptBox.value.trim();
+        } else {
+            showToast(t("saveFailed"), "error");
+        }
+    } catch (e) {
+        showToast(t("errorWithMsg", e.message), "error");
+    }
+}
+
+// ── プロンプトビルダー (チップ / 最終プロンプト) ─────────────────
+
+function cleanPromptText(text) {
+    return String(text || "")
+        .replace(/^[,\s]+|[,\s]+$/g, "")
+        .replace(/\s*,\s*/g, ", ")
+        .trim();
+}
+
+function addSelectedToChips() {
+    const img = state.selectedImage;
+    if (!img) return;
+    const promptBox = document.getElementById("wfm-imageprompt-selected-prompt");
+    const prompt = cleanPromptText(promptBox.value);
+    if (!prompt) return;
+    if (state.chips.some(c => c.path === img.path)) {
+        showToast(t("imagePromptAlreadyAdded"), "info");
+        return;
+    }
+    state.chips.push({ path: img.path, filename: img.filename, prompt });
+    renderChips();
+    rebuildFinalPrompt();
+}
+
+function removeChip(path) {
+    state.chips = state.chips.filter(c => c.path !== path);
+    renderChips();
+    rebuildFinalPrompt();
+}
+
+function clearAllChips() {
+    state.chips = [];
+    renderChips();
+    document.getElementById("wfm-imageprompt-final-prompt").value = "";
+}
+
+function renderChips() {
+    const container = document.getElementById("wfm-imageprompt-chips");
+    container.innerHTML = "";
+    state.chips.forEach(chip => {
+        const el = document.createElement("span");
+        el.className = "wfm-imageprompt-chip";
+        el.title = chip.prompt;
+
+        const text = document.createElement("span");
+        text.className = "wfm-imageprompt-chip-text";
+        text.textContent = chip.filename.replace(/\.[^.]+$/, "");
+        el.appendChild(text);
+
+        const removeBtn = document.createElement("button");
+        removeBtn.className = "wfm-imageprompt-chip-remove";
+        removeBtn.textContent = "×";
+        removeBtn.addEventListener("click", () => removeChip(chip.path));
+        el.appendChild(removeBtn);
+
+        container.appendChild(el);
+    });
+}
+
+function rebuildFinalPrompt() {
+    const combined = state.chips.map(c => c.prompt).join(", ");
+    document.getElementById("wfm-imageprompt-final-prompt").value = cleanPromptText(combined);
+}
+
+async function copyFinalPrompt() {
+    const text = document.getElementById("wfm-imageprompt-final-prompt").value;
+    if (!text.trim()) {
+        showToast(t("imagePromptNothingToCopy"), "info");
+        return;
+    }
+    try {
+        await navigator.clipboard.writeText(text);
+        showToast(t("imagePromptCopiedToast"), "success");
+    } catch (e) {
+        showToast(t("errorWithMsg", e.message), "error");
+    }
+}
@@ -6,6 +6,7 @@

 import { t } from "./i18n.js";
 import { escapeHtml } from "./util.js";
+import { comfyWorkflow } from "./comfyui-workflow.js";

 // ── File size limit ───────────────────────────────────────────
 const MAX_FILE_SIZE = 50 * 1024 * 1024;
@@ -74,7 +75,7 @@ function parseITXtChunk(data, latin1, utf8) {
    pos = findNull(data, pos); if (pos === -1) return null; pos++;
    return { keyword, text: utf8.decode(data.slice(pos)) };
 }
-async function readAllPNGTextChunks(file) {
+export async function readAllPNGTextChunks(file) {
    const buffer = await file.arrayBuffer();
    const bytes = new Uint8Array(buffer);
    const PNG_SIG = [0x89, 0x50, 0x4e, 0x47, 0x0d, 0x0a, 0x1a, 0x0a];
@@ -96,6 +97,81 @@ async function readAllPNGTextChunks(file) {
    return chunks;
 }

+// ── MP4 container metadata (moov/udta/meta の mdta keys/ilst) ──
+// ComfyUIのSaveVideoはPNGのtEXtチャンクと同じキー名(workflow=UI形式, prompt=API形式)で
+// JSON文字列をisobmff(mp4)のudta/meta(mdta)にコンテナレベルタグとして書き込む(FFmpegの
+// movflags=+use_metadata_tags)。ここではPyAV等に頼らずブラウザ側でボックスを直接辿って読む。
+function findMP4Box(view, bytes, start, end, targetType) {
+    let offset = start;
+    while (offset + 8 <= end) {
+        const size = view.getUint32(offset);
+        const type = String.fromCharCode(bytes[offset + 4], bytes[offset + 5], bytes[offset + 6], bytes[offset + 7]);
+        let boxSize = size;
+        let bodyStart = offset + 8;
+        if (size === 1) {
+            if (offset + 16 > end) break;
+            const hi = view.getUint32(offset + 8);
+            const lo = view.getUint32(offset + 12);
+            boxSize = hi * 4294967296 + lo;
+            bodyStart = offset + 16;
+        } else if (size === 0) {
+            boxSize = end - offset;
+        }
+        if (boxSize < 8) break;
+        if (type === targetType) return { bodyStart, end: offset + boxSize };
+        offset += boxSize;
+    }
+    return null;
+}
+
+export async function readMP4MetaTags(file) {
+    const buffer = await file.arrayBuffer();
+    const bytes = new Uint8Array(buffer);
+    const view = new DataView(buffer);
+    if (bytes.length < 12) return null;
+    const ftyp = String.fromCharCode(bytes[4], bytes[5], bytes[6], bytes[7]);
+    if (ftyp !== "ftyp") return null;
+
+    const moov = findMP4Box(view, bytes, 0, bytes.length, "moov");
+    if (!moov) return null;
+    const udta = findMP4Box(view, bytes, moov.bodyStart, moov.end, "udta");
+    let meta = udta ? findMP4Box(view, bytes, udta.bodyStart, udta.end, "meta") : null;
+    if (!meta) meta = findMP4Box(view, bytes, moov.bodyStart, moov.end, "meta");
+    if (!meta) return null;
+    const metaBody = meta.bodyStart + 4; // meta は FullBox (version+flags 4バイト)
+    const keysBox = findMP4Box(view, bytes, metaBody, meta.end, "keys");
+    const ilstBox = findMP4Box(view, bytes, metaBody, meta.end, "ilst");
+    if (!keysBox || !ilstBox) return null;
+
+    const utf8 = new TextDecoder("utf-8", { fatal: false });
+    let off = keysBox.bodyStart + 4; // version+flags をスキップ
+    const count = view.getUint32(off); off += 4;
+    const keyNames = [];
+    for (let i = 0; i < count && off + 8 <= keysBox.end; i++) {
+        const ksize = view.getUint32(off);
+        if (ksize < 8) break;
+        keyNames.push(utf8.decode(bytes.slice(off + 8, off + ksize)));
+        off += ksize;
+    }
+
+    const result = {};
+    let ioff = ilstBox.bodyStart;
+    while (ioff + 8 <= ilstBox.end) {
+        const itemSize = view.getUint32(ioff);
+        const keyIndex = view.getUint32(ioff + 4);
+        if (itemSize < 8) break;
+        const itemEnd = Math.min(ioff + itemSize, ilstBox.end);
+        const data = findMP4Box(view, bytes, ioff + 8, itemEnd, "data");
+        if (data) {
+            const payload = bytes.slice(data.bodyStart + 8, data.end); // type(4)+locale(4)をスキップ
+            const name = keyNames[keyIndex - 1];
+            if (name) { try { result[name] = utf8.decode(payload); } catch { /* skip */ } }
+        }
+        ioff = itemEnd;
+    }
+    return result;
+}
+
 // ── Workflow extraction helpers ───────────────────────────────
 function collectUnique(arr) {
    const seen = new Set(), out = [];
@@ -187,11 +263,67 @@ function isTextEncoderNode(ct) { return ct === "CLIPTextEncode" || ct.includes("
 function isSamplerNode(ct) { return ct === "KSampler" || ct === "KSamplerAdvanced" || ct.includes("KSampler") || ct.includes("Sampler"); }
 function isPromptStylerNode(ct) { return ct.includes("PromptStyler"); }

-function extractPrompts(wf) {
+// CLIPTextEncodeEditPlus (model-and-prompt-from-metadata) の encode() と同じ結合ルール。
+// RAW: text1のみ。EDIT: text_editのみ。front/back: text2(未接続ならtext_edit)をtext1の前/後に結合。
+function resolveEditPlusText(mode, textEdit, text1, text2) {
+    const t1 = typeof text1 === "string" ? text1 : "";
+    const edit = typeof textEdit === "string" ? textEdit : "";
+    const insert = typeof text2 === "string" && text2 !== "" ? text2 : edit;
+    switch (mode) {
+        case "RAW": return t1;
+        case "EDIT": return edit;
+        case "front": return t1 ? `${insert}, ${t1}` : insert;
+        case "back": return t1 ? `${t1}, ${insert}` : insert;
+        default: return t1 || edit;
+    }
+}
+
+export function extractPrompts(wf) {
    if (!wf || typeof wf !== "object") return { positives: [], negatives: [] };
    return Array.isArray(wf.nodes) ? extractPromptsLiteGraph(wf) : extractPromptsAPI(wf);
 }

+// LiteGraph形式: リンクを辿ってテキストを解決（ComfySwitchNode等の中継ノードにも対応）
+function resolveLinkedTextInNodeSet(nodeMap, linkOrigin, linkSlot, srcId, slot, depth = 0) {
+    if (depth > 6) return null;
+    const srcNode = nodeMap.get(srcId);
+    if (!srcNode) return null;
+    const srcType = srcNode.type ?? "";
+    if (isPromptStylerNode(srcType)) {
+        const v = srcNode.widgets_values?.[slot];
+        return (v && typeof v === "string") ? v : null;
+    }
+    // ComfySwitchNode ("If/Else Switch") — 片方(TextGenerateなどLLMノード)は静的解決不能なため
+    // on_false/on_true の両方を試し、リテラルへ解決できた方を採用する。
+    if (srcType === "ComfySwitchNode" && Array.isArray(srcNode.inputs)) {
+        for (const name of ["on_false", "on_true"]) {
+            const inp = srcNode.inputs.find(i => i.name === name);
+            if (inp?.link == null) continue;
+            const originId = linkOrigin.get(inp.link);
+            const originSlot = linkSlot.get(inp.link) ?? 0;
+            if (originId == null) continue;
+            const text = resolveLinkedTextInNodeSet(nodeMap, linkOrigin, linkSlot, originId, originSlot, depth + 1);
+            if (text) return text;
+        }
+        return null;
+    }
+    // WFS_PromptText, PrimitiveStringMultiline 等、任意の STRING 出力ノード
+    const v = srcNode.widgets_values?.[slot] ?? srcNode.widgets_values?.[0];
+    if (v && typeof v === "string") return v;
+    // さらにリンクされている場合（StringReplace等の中継ノード）は追跡する
+    // "source" = PreviewAny（値タップ中継）, "string_a" = StringConcatenate（LoRAトリガーワード
+    // 連結等）— Krea-2のプロンプト強化配線で使われる中継ノード
+    if (Array.isArray(srcNode.inputs)) {
+        const nextInput = srcNode.inputs.find(i => ["text", "value", "prompt", "string", "source", "string_a"].includes(i.name));
+        if (nextInput?.link != null) {
+            const originId = linkOrigin.get(nextInput.link);
+            const originSlot = linkSlot.get(nextInput.link) ?? 0;
+            if (originId != null) return resolveLinkedTextInNodeSet(nodeMap, linkOrigin, linkSlot, originId, originSlot, depth + 1);
+        }
+    }
+    return null;
+}
+
 // CLIPTextEncode + KSampler でプロンプト抽出（トップレベル・サブグラフ共用）
 // サンプラーが見つかりテキストが取れた場合のみ非null を返す
 function extractPromptsFromNodeSet(nodes, links) {
@@ -211,7 +343,22 @@ function extractPromptsFromNodeSet(nodes, links) {
    }
    const textMap = new Map();
    for (const n of nodes) {
-        if (!isTextEncoderNode(n.type ?? "")) continue;
+        const type = n.type ?? "";
+        if (type === "CLIPTextEncodeEditPlus") {
+            const resolveNamedInput = (name) => {
+                if (!Array.isArray(n.inputs)) return null;
+                const inp = n.inputs.find(i => i.name === name);
+                if (inp?.link == null) return null;
+                const originId = linkOrigin.get(inp.link);
+                const originSlot = linkSlot.get(inp.link) ?? 0;
+                if (originId == null) return null;
+                return resolveLinkedTextInNodeSet(nodeMap, linkOrigin, linkSlot, originId, originSlot);
+            };
+            const combined = resolveEditPlusText(n.widgets_values?.[1], n.widgets_values?.[0], resolveNamedInput("text1"), resolveNamedInput("text2"));
+            if (combined) textMap.set(n.id, combined);
+            continue;
+        }
+        if (!isTextEncoderNode(type)) continue;
        const text = n.widgets_values?.[0];
        if (text && typeof text === "string") {
            textMap.set(n.id, text);
@@ -220,18 +367,8 @@ function extractPromptsFromNodeSet(nodes, links) {
            if (textInput?.link != null) {
                const originId = linkOrigin.get(textInput.link);
                const originSlot = linkSlot.get(textInput.link) ?? 0;
-                const srcNode = originId != null ? nodeMap.get(originId) : null;
-                if (srcNode) {
-                    const srcType = srcNode.type ?? "";
-                    if (isPromptStylerNode(srcType)) {
-                        const v = srcNode.widgets_values?.[originSlot];
-                        if (v && typeof v === "string") textMap.set(n.id, v);
-                    } else {
-                        // WFS_PromptText, PrimitiveStringMultiline, ComfySwitchNode 等、任意の STRING 出力ノード
-                        const v = srcNode.widgets_values?.[originSlot] ?? srcNode.widgets_values?.[0];
-                        if (v && typeof v === "string") textMap.set(n.id, v);
-                    }
-                }
+                const text2 = resolveLinkedTextInNodeSet(nodeMap, linkOrigin, linkSlot, originId, originSlot);
+                if (text2) textMap.set(n.id, text2);
            }
        }
    }
@@ -240,15 +377,48 @@ function extractPromptsFromNodeSet(nodes, links) {
    for (const n of nodes) {
        if (!isSamplerNode(n.type ?? "") || !Array.isArray(n.inputs)) continue;
        foundSampler = true;
-        for (const inp of n.inputs) {
+        // SamplerCustomAdvanced doesn't hold positive/negative directly — it drives a separate
+        // Guider node (CFGGuider/DualCFGGuider/BasicGuider) via its "guider" input. Scan that
+        // node's inputs instead so the loop below can find the positive/negative-role slots.
+        let inputsToScan = n.inputs;
+        const guiderInput = n.inputs.find(inp => inp.name === "guider");
+        if (guiderInput?.link != null) {
+            const guiderId = linkOrigin.get(guiderInput.link);
+            const guiderNode = guiderId != null ? nodeMap.get(guiderId) : null;
+            if (Array.isArray(guiderNode?.inputs)) inputsToScan = guiderNode.inputs;
+        }
+        for (const inp of inputsToScan) {
            if (!inp || inp.link == null) continue;
            const originId = linkOrigin.get(inp.link);
            if (originId == null) continue;
-            const text = textMap.get(originId);
-            if (!text) continue;
            const name = inp.name ?? "";
-            if (name === "positive" || name.startsWith("positive")) pos.add(text);
-            else if (name === "negative" || name.startsWith("negative")) neg.add(text);
+            // DualCFGGuider (HiDream E1): cond1 carries the positive-derived conditioning.
+            const isPos = name === "positive" || name === "cond1" || name.startsWith("positive");
+            const isNeg = name === "negative" || name.startsWith("negative");
+            if (!isPos && !isNeg) continue;
+            // TextEncodeMageFlowEdit / TextEncodeBooguEdit — one node carries both prompt &
+            // negative_prompt directly, so textMap (single text per node) can't represent both
+            // roles.
+            const srcNode = nodeMap.get(originId);
+            if (srcNode?.type === "TextEncodeMageFlowEdit" || srcNode?.type === "TextEncodeBooguEdit") {
+                const widgetIdx = isPos ? 0 : 1; // widgets_values: [prompt, negative_prompt, ...]
+                const text = srcNode.widgets_values?.[widgetIdx];
+                if (text && typeof text === "string") { if (isPos) pos.add(text); else neg.add(text); }
+                continue;
+            }
+            // InstructPixToPixConditioning (HiDream E1): forwards the actual text-encoder
+            // conditioning through its own positive/negative inputs — follow one more hop.
+            let resolvedOriginId = originId;
+            if (srcNode?.type === "InstructPixToPixConditioning" && Array.isArray(srcNode.inputs)) {
+                const innerInput = srcNode.inputs.find(i => i.name === (isPos ? "positive" : "negative"));
+                if (innerInput?.link != null) {
+                    const innerId = linkOrigin.get(innerInput.link);
+                    if (innerId != null) resolvedOriginId = innerId;
+                }
+            }
+            const text = textMap.get(resolvedOriginId);
+            if (!text) continue;
+            if (isPos) pos.add(text); else neg.add(text);
        }
    }
    if (!foundSampler) return null;
@@ -300,7 +470,8 @@ function extractMarkdownNoteModels(wf) {
 }

 // API形式: リンク参照 [srcNodeId, slot] からテキストを解決
-function resolveLinkedText(wf, srcId, slot) {
+function resolveLinkedText(wf, srcId, slot, depth = 0) {
+    if (depth > 6) return null;
    const src = wf[String(srcId)];
    if (!src || typeof src !== "object") return null;
    const ct = src.class_type ?? "";
@@ -309,13 +480,34 @@ function resolveLinkedText(wf, srcId, slot) {
        const v = slot === 0 ? src.inputs?.text_positive : src.inputs?.text_negative;
        return (v && typeof v === "string") ? v : null;
    }
-    // 汎用テキストキー
+    // ComfySwitchNode ("If/Else Switch", on_false/on_true/switch) — Ernie Imageのプロンプト強化
+    // トグルなどで使われる。片方(TextGenerateなどLLMノード)は静的解決不能なため両方試し、
+    // リテラルへ解決できた方を採用する。
+    if (ct === "ComfySwitchNode") {
+        for (const key of ["on_false", "on_true"]) {
+            const v = src.inputs?.[key];
+            if (Array.isArray(v)) {
+                const text = resolveLinkedText(wf, v[0], v[1] ?? 0, depth + 1);
+                if (text) return text;
+            } else if (typeof v === "string" && v) {
+                return v;
+            }
+        }
+        return null;
+    }
+    // 汎用テキストキー（"value" は PrimitiveString/PrimitiveStringMultiline、"source" は
+    // PreviewAny の値タップ中継、"string_a" は StringConcatenate の主オペランド — いずれも
+    // Krea-2のプロンプト強化配線で使われる中継ノード）
    const keys = slot === 0
-        ? ["text_positive", "text", "text_g", "prompt"]
-        : ["text_negative", "text_l"];
+        ? ["text_positive", "text", "text_g", "prompt", "value", "source", "string_a"]
+        : ["text_negative", "text_l", "source", "string_a"];
    for (const k of keys) {
        const v = src.inputs?.[k];
-        if (v && typeof v === "string") return v;
+        if (typeof v === "string" && v) return v;
+        if (Array.isArray(v)) {
+            const text = resolveLinkedText(wf, v[0], v[1] ?? 0, depth + 1);
+            if (text) return text;
+        }
    }
    return null;
 }
@@ -329,8 +521,30 @@ function extractPromptsAPI(wf) {
    }
    const textMap = new Map();
    for (const [id, n] of Object.entries(wf)) {
-        if (!n || !isTextEncoderNode(n.class_type ?? "")) continue;
-        const raw = n.inputs?.text ?? n.inputs?.text_g ?? null;
+        if (!n) continue;
+        const ct = n.class_type ?? "";
+        if (ct === "CLIPTextEncodeEditPlus") {
+            const resolveField = (key) => {
+                const v = n.inputs?.[key];
+                if (typeof v === "string") return v;
+                if (Array.isArray(v)) return resolveLinkedText(wf, v[0], v[1] ?? 0);
+                return null;
+            };
+            const combined = resolveEditPlusText(n.inputs?.mode, n.inputs?.text_edit, resolveField("text1"), resolveField("text2"));
+            if (combined) textMap.set(id, combined);
+            continue;
+        }
+        // MiniMaxH3ImageToVideo等の動画生成オールインワンノード。CLIPTextEncode等を経由せず
+        // 自ノードの"prompt"入力に直接テキストを持つ(positive/negativeの区別も無い)ため、
+        // isTextEncoderNode判定を通さずtextMapへ直接投入する(fallbackのtextsに載る)。
+        if (typeof n.inputs?.prompt === "string" && /ImageToVideo|TextToVideo/i.test(ct)) {
+            textMap.set(id, n.inputs.prompt);
+            continue;
+        }
+        if (!isTextEncoderNode(ct)) continue;
+        // "prompt" — TextEncodeQwenImageEdit(Plus)/TextEncodeBooguEdit and similar Image Edit
+        // model text encoders use this key instead of "text"/"text_g".
+        const raw = n.inputs?.text ?? n.inputs?.text_g ?? n.inputs?.prompt ?? null;
        if (raw && typeof raw === "string") {
            textMap.set(id, raw);
        } else if (Array.isArray(raw)) {
@@ -344,12 +558,37 @@ function extractPromptsAPI(wf) {
    for (const n of Object.values(wf)) {
        if (!n || !isSamplerNode(n.class_type ?? "")) continue;
        foundSampler = true;
-        for (const [key, val] of Object.entries(n.inputs ?? {})) {
+        // SamplerCustomAdvanced doesn't hold positive/negative directly — it drives a separate
+        // Guider node (CFGGuider/DualCFGGuider/BasicGuider) via its "guider" input. Scan that
+        // node's inputs instead so the loop below can find the positive/negative-role keys.
+        let inputsToScan = n.inputs ?? {};
+        if (Array.isArray(n.inputs?.guider)) {
+            const guiderNode = wf[String(n.inputs.guider[0])];
+            if (guiderNode?.inputs) inputsToScan = guiderNode.inputs;
+        }
+        for (const [key, val] of Object.entries(inputsToScan)) {
            if (!Array.isArray(val)) continue;
-            const text = textMap.get(String(val[0]));
+            // DualCFGGuider (HiDream E1): cond1 carries the positive-derived conditioning.
+            const isPos = key === "positive" || key === "cond1" || key.startsWith("positive");
+            const isNeg = key === "negative" || key.startsWith("negative");
+            if (!isPos && !isNeg) continue;
+            // TextEncodeMageFlowEdit / TextEncodeBooguEdit — one node carries both prompt &
+            // negative_prompt directly, so textMap (single text per node) can't represent both
+            // roles.
+            const srcNode = wf[String(val[0])];
+            if (srcNode?.class_type === "TextEncodeMageFlowEdit" || srcNode?.class_type === "TextEncodeBooguEdit") {
+                const text = isPos ? srcNode.inputs?.prompt : srcNode.inputs?.negative_prompt;
+                if (text && typeof text === "string") { if (isPos) pos.add(text); else neg.add(text); }
+                continue;
+            }
+            // InstructPixToPixConditioning (HiDream E1): forwards the actual text-encoder
+            // conditioning through its own positive/negative inputs — follow one more hop.
+            const resolvedId = srcNode?.class_type === "InstructPixToPixConditioning" && Array.isArray(srcNode.inputs?.[isPos ? "positive" : "negative"])
+                ? String(srcNode.inputs[isPos ? "positive" : "negative"][0])
+                : String(val[0]);
+            const text = textMap.get(resolvedId);
            if (!text) continue;
-            if (key === "positive" || key.startsWith("positive")) pos.add(text);
-            else if (key === "negative" || key.startsWith("negative")) neg.add(text);
+            if (isPos) pos.add(text); else neg.add(text);
        }
    }
    if (!foundSampler || (pos.size === 0 && neg.size === 0)) { const all = [...textMap.values()].filter(t => t && t.trim()); return { positives: [], negatives: [], texts: all }; }
@@ -446,15 +685,28 @@ function parseFooocusMetadata(raw) {
 }

 // ── Master extractAllMetadata ─────────────────────────────────
-async function extractAllMetadata(file) {
+export async function extractAllMetadata(file) {
    const name = file.name.toLowerCase();
    const isJSON = file.type === "application/json" || name.endsWith(".json");
    const isWebP = file.type === "image/webp" || name.endsWith(".webp");
+    const isMP4 = file.type === "video/mp4" || name.endsWith(".mp4");

-    function fromWorkflow(wf, source) {
+    async function fromWorkflow(originalWf, source) {
+        let wf = originalWf;
+        // サブグラフを持つワークフローは、外側のサブグラフノードに実際に設定された値
+        // (ユーザーが見ている値)が内部ノードのwidgets_valuesへ反映されていないことがある
+        // (テンプレートの古いデフォルト値のまま)。convertUiToApi() はこの注入も含めて
+        // 正しく解決するため、そちらを経由してから抽出する。通常のワークフローには影響しない。
+        if (Array.isArray(wf?.nodes) && wf.definitions?.subgraphs?.length > 0) {
+            try {
+                const apiWf = await comfyWorkflow.convertUiToApi(wf);
+                if (apiWf && Object.keys(apiWf).length > 0) wf = apiWf;
+            } catch { /* 変換失敗時は元のUI形式のまま抽出（既存ロジックにフォールバック） */ }
+        }
        const base = { source, checkpoints: extractCheckpoints(wf), vaes: extractVAEs(wf), diffusionModels: extractDiffusionModels(wf), textEncoders: extractTextEncoders(wf), loras: extractLoRAs(wf), ...extractPrompts(wf) };
-        // MarkdownNote からモデル情報を補完（subgraph形式の flux/qwen/z-image など）
-        const mdm = extractMarkdownNoteModels(wf);
+        // MarkdownNote からモデル情報を補完（subgraph形式の flux/qwen/z-image など）。
+        // API変換後は nodes 情報が失われるため、常に元のUI形式ワークフローから抽出する。
+        const mdm = extractMarkdownNoteModels(originalWf);
        if (mdm) {
            if (!base.checkpoints.length) base.checkpoints = mdm.checkpoints;
            if (!base.vaes.length) base.vaes = mdm.vaes;
@@ -467,20 +719,31 @@ async function extractAllMetadata(file) {

    if (isJSON) {
        let wf; try { wf = JSON.parse(sanitizeJSON(await file.text())); } catch { return null; }
-        return wf ? fromWorkflow(wf, "comfyui") : null;
+        return wf ? await fromWorkflow(wf, "comfyui") : null;
    }
    if (isWebP) {
        const exif = await readWebPEXIFChunk(file);
        if (!exif) return null;
        const wf = extractWorkflowFromEXIF(exif);
-        return wf ? fromWorkflow(wf, "comfyui") : null;
+        return wf ? await fromWorkflow(wf, "comfyui") : null;
+    }
+    if (isMP4) {
+        let tags; try { tags = await readMP4MetaTags(file); } catch { return null; }
+        if (!tags) return null;
+        for (const key of ["prompt", "workflow"]) {
+            const raw = tags[key];
+            if (!raw) continue;
+            let wf; try { wf = JSON.parse(sanitizeJSON(raw)); } catch { continue; }
+            if (wf) return await fromWorkflow(wf, "comfyui");
+        }
+        return null;
    }
    // PNG
    const chunks = await readAllPNGTextChunks(file);
    if (!chunks) return null;

-    if (chunks.prompt) { let wf; try { wf = JSON.parse(sanitizeJSON(chunks.prompt)); } catch { return null; } return wf ? fromWorkflow(wf, "comfyui") : null; }
-    if (chunks.workflow) { let wf; try { wf = JSON.parse(sanitizeJSON(chunks.workflow)); } catch { return null; } return wf ? fromWorkflow(wf, "comfyui") : null; }
+    if (chunks.prompt) { let wf; try { wf = JSON.parse(sanitizeJSON(chunks.prompt)); } catch { return null; } return wf ? await fromWorkflow(wf, "comfyui") : null; }
+    if (chunks.workflow) { let wf; try { wf = JSON.parse(sanitizeJSON(chunks.workflow)); } catch { return null; } return wf ? await fromWorkflow(wf, "comfyui") : null; }

    if (chunks.fooocus_scheme === "fooocus" && chunks.parameters) {
        const f = parseFooocusMetadata(chunks.parameters);
@@ -524,7 +787,7 @@ function buildLoRAItem(lora) {
    return el;
 }

-function buildPromptItem(label, type, full, fullArea, fullLabel, listEl) {
+export function buildPromptItem(label, type, full, fullArea, fullLabel, listEl) {
    const el = document.createElement("div");
    el.className = "wfm-meta-item wfm-meta-item-clickable";
    const snippet = label.length > 60 ? label.slice(0, 60) + "…" : label;
@@ -554,7 +817,8 @@ function renderSection(sectionEl, listEl, items, buildFn) {
 let _externalHandleFile = null;

 export async function loadFileIntoMetadataTab(file) {
-    document.querySelector('.wfm-tab[data-tab="metadata"]')?.click();
+    document.querySelector('.wfm-tab[data-tab="gallery"]')?.click();
+    document.querySelector('.wfm-gallery-subtab-btn[data-gallery-subtab="metadata"]')?.click();
    await new Promise(r => setTimeout(r, 0));
    if (_externalHandleFile) await _externalHandleFile(file);
 }
@@ -621,6 +885,7 @@ export function initMetadataTab() {
        "wfm-help-metadata-3": "helpMetadata3",
        "wfm-help-metadata-4": "helpMetadata4",
        "wfm-help-metadata-5": "helpMetadata5",
+        "wfm-help-metadata-6": "helpMetadata6",
    };
    for (const [id, key] of Object.entries(helpIds)) {
        const el = document.getElementById(id);
@@ -0,0 +1,159 @@
+/**
+ * Models Tab - Badge palette, badge rendering, badge edit modal, badge filter bar
+ */
+
+import { openModal } from "../app.js";
+import { t } from "../i18n.js";
+import { escapeHtml, readJsonStorage } from "../util.js";
+import { state } from "./state.js";
+
+// Grid re-render is owned by models-tab.js (grid rendering hasn't been split
+// out yet); registered once from initModelsTab() to avoid a circular import.
+let _onGridChange = () => {};
+export function setGridChangeCallback(fn) { _onGridChange = fn; }
+
+export function getBadgePalette() {
+    return readJsonStorage("wfm_models_badge_palette");
+}
+
+export function saveBadgePalette(palette) {
+    localStorage.setItem("wfm_models_badge_palette", JSON.stringify(palette));
+}
+
+export function badgeHtml(label) {
+    const palette = getBadgePalette();
+    const color = palette[label] || "";
+    const style = color ? ` style="background:${color};color:#fff;"` : "";
+    return `<span class="wfm-badge wfm-badge-model"${style}>${escapeHtml(label)}</span>`;
+}
+
+export function modelBadgesHtml(modelName, clickable = false) {
+    const meta = state.modelMetadata[modelName] || {};
+    const badges = meta.badges || [];
+    if (badges.length === 0) return "";
+    return badges.map((label) => {
+        const palette = getBadgePalette();
+        const color = palette[label] || "";
+        const style = color ? ` style="background:${color};color:#fff;"` : "";
+        const dataAttr = clickable ? ` data-badge-filter="${escapeHtml(label)}"` : "";
+        return `<span class="wfm-badge wfm-badge-model${clickable ? " wfm-badge-clickable" : ""}"${style}${dataAttr}>${escapeHtml(label)}</span>`;
+    }).join("");
+}
+
+export function openBadgeEditModal(onPaletteChange = null) {
+    const palette = getBadgePalette();
+    const labels = Object.keys(palette).sort();
+
+    const rowsHtml = labels.map((label) => {
+        const color = palette[label] || "#6366f1";
+        return `<div class="wfm-badge-color-row" data-badge-label="${escapeHtml(label)}">
+            ${badgeHtml(label)}
+            <input type="color" value="${color}" data-badge-label="${escapeHtml(label)}" class="wfm-badge-color-input" title="${t("badgeColorHint")}">
+            <button class="wfm-btn wfm-btn-sm wfm-btn-danger wfm-badge-delete-btn" data-badge-label="${escapeHtml(label)}" title="${t("badgeDelete")}">&times;</button>
+        </div>`;
+    }).join("");
+
+    const html = `
+        <div style="min-width:320px;">
+            <div id="wfm-badge-list">${rowsHtml || `<p style="color:var(--wfm-text-secondary);font-size:12px;">${t("badgeNone")}</p>`}</div>
+            <div style="border-top:1px solid var(--wfm-border);margin-top:12px;padding-top:12px;display:flex;gap:6px;align-items:center;">
+                <input type="text" id="wfm-badge-new-label" class="wfm-input" style="flex:1;" placeholder="${t("badgeNewLabel")}">
+                <input type="color" id="wfm-badge-new-color" value="#6366f1" style="width:36px;height:28px;padding:1px;border-radius:4px;cursor:pointer;">
+                <button class="wfm-btn wfm-btn-sm wfm-btn-primary" id="wfm-badge-add-btn">${t("badgeAdd")}</button>
+            </div>
+        </div>`;
+
+    openModal(t("badgeManage"), html);
+    bindBadgeModalEvents(onPaletteChange);
+}
+
+function bindBadgeModalEvents(onPaletteChange = null) {
+    const afterChange = () => {
+        renderBadgeFilter();
+        _onGridChange();
+        if (onPaletteChange) onPaletteChange();
+    };
+
+    const refreshList = () => {
+        const palette = getBadgePalette();
+        const labels = Object.keys(palette).sort();
+        const listEl = document.getElementById("wfm-badge-list");
+        if (!listEl) return;
+        listEl.innerHTML = labels.map((label) => {
+            const color = palette[label] || "#6366f1";
+            return `<div class="wfm-badge-color-row" data-badge-label="${escapeHtml(label)}">
+                ${badgeHtml(label)}
+                <input type="color" value="${color}" data-badge-label="${escapeHtml(label)}" class="wfm-badge-color-input" title="${t("badgeColorHint")}">
+                <button class="wfm-btn wfm-btn-sm wfm-btn-danger wfm-badge-delete-btn" data-badge-label="${escapeHtml(label)}" title="${t("badgeDelete")}">&times;</button>
+            </div>`;
+        }).join("") || `<p style="color:var(--wfm-text-secondary);font-size:12px;">${t("badgeNone")}</p>`;
+        bindBadgeRowEvents(refreshList, afterChange);
+        afterChange();
+    };
+
+    bindBadgeRowEvents(refreshList, afterChange);
+
+    document.getElementById("wfm-badge-add-btn")?.addEventListener("click", () => {
+        const labelInput = document.getElementById("wfm-badge-new-label");
+        const colorInput = document.getElementById("wfm-badge-new-color");
+        const label = labelInput?.value.trim();
+        if (!label) return;
+        const palette = getBadgePalette();
+        palette[label] = colorInput?.value || "#6366f1";
+        saveBadgePalette(palette);
+        if (labelInput) labelInput.value = "";
+        refreshList();
+    });
+}
+
+function bindBadgeRowEvents(refreshList, afterChange = null) {
+    document.querySelectorAll(".wfm-badge-color-input").forEach((input) => {
+        input.addEventListener("input", (e) => {
+            const label = e.target.dataset.badgeLabel;
+            const palette = getBadgePalette();
+            palette[label] = e.target.value;
+            saveBadgePalette(palette);
+            refreshList();
+        });
+    });
+    document.querySelectorAll(".wfm-badge-delete-btn").forEach((btn) => {
+        btn.addEventListener("click", () => {
+            const label = btn.dataset.badgeLabel;
+            const palette = getBadgePalette();
+            delete palette[label];
+            saveBadgePalette(palette);
+            refreshList();
+        });
+    });
+}
+
+// ── Badge Filter Bar ──────────────────────────────────────
+
+export function renderBadgeFilter() {
+    const container = document.getElementById("wfm-models-badge-filter-bar");
+    if (!container) return;
+    const palette = getBadgePalette();
+    const labels = Object.keys(palette).sort();
+
+    if (labels.length === 0) {
+        container.innerHTML = "";
+        return;
+    }
+
+    container.innerHTML = labels.map((label) => {
+        const color = palette[label] || "";
+        const isActive = state.badgeFilter === label;
+        const style = color ? `background:${color};color:#fff;` : "";
+        return `<button class="wfm-badge-filter-btn${isActive ? " active" : ""}" data-badge="${escapeHtml(label)}" style="${style}">${escapeHtml(label)}</button>`;
+    }).join("");
+
+    container.querySelectorAll(".wfm-badge-filter-btn").forEach((btn) => {
+        btn.addEventListener("click", () => {
+            const label = btn.dataset.badge;
+            state.badgeFilter = state.badgeFilter === label ? "" : label;
+            state.currentPage = 0;
+            renderBadgeFilter();
+            _onGridChange();
+        });
+    });
+}
@@ -0,0 +1,898 @@
+/**
+ * Models Tab - Detail modal (double-click) and the side panel's
+ * Info / Group / CivitAI tabs.
+ *
+ * Part of the grid-view.js / selection-bulk.js / detail-panel.js circular
+ * import triangle — see the note at the top of grid-view.js.
+ */
+
+import { showToast, openModal, closeModal } from "../app.js";
+import { t } from "../i18n.js";
+import { escapeHtml } from "../util.js";
+import { state, RESERVED_GROUPS, GENUI_TYPE_MAP } from "./state.js";
+import { getCurrentModels, renderTagFilter, renderDirFilter } from "./filters.js";
+import { getBadgePalette, modelBadgesHtml, openBadgeEditModal } from "./badges.js";
+import { parseModelPath, getExtension, getStem, loadPreviewImage, previewUrl } from "./helpers.js";
+import { renderModelGrid } from "./grid-view.js";
+import {
+    applyToGenUI, applyEmbeddingToPrompt, saveModelMetadata, toggleGroupEnable,
+    fetchModelMetadata, saveModelGroups,
+} from "../models-tab.js";
+
+// ── Detail Modal (double-click, with badges) ──────────────
+
+export function openDetailModal(modelName) {
+    const meta = state.modelMetadata[modelName] || {};
+    const { dir, name } = parseModelPath(modelName);
+    const ext = getExtension(name);
+    const isFav = !!meta.favorite;
+    const tagsStr = (meta.tags || []).join(", ");
+    const selectedBadges = meta.badges || [];
+    const palette = getBadgePalette();
+    const allBadgeLabels = Object.keys(palette).sort();
+
+    const badgeCheckboxes = allBadgeLabels.map((label) => {
+        const checked = selectedBadges.includes(label) ? " checked" : "";
+        const color = palette[label] || "";
+        const style = color ? `background:${color};color:#fff;` : "";
+        return `<label class="wfm-badge-check-label">
+            <input type="checkbox" class="wfm-badge-checkbox" value="${escapeHtml(label)}"${checked}>
+            <span class="wfm-badge wfm-badge-model" style="${style}">${escapeHtml(label)}</span>
+        </label>`;
+    }).join("");
+
+    const html = `
+        <div class="wfm-modal-thumb-section">
+            <img class="wfm-modal-thumb-img" style="display:none" />
+            <div class="wfm-modal-thumb-placeholder">${t("modelsNoPreview")}</div>
+        </div>
+        <div style="text-align:center;margin-bottom:8px;">
+            <button class="wfm-btn wfm-btn-sm" id="wfm-modal-change-thumb">${t("changeThumbnail")}</button>
+            <input type="file" id="wfm-modal-thumb-file" accept="image/*" style="display:none">
+        </div>
+        <div class="wfm-modal-two-col">
+            <div class="wfm-modal-left">
+                <section>
+                    <h4>${t("modelsInfo")}</h4>
+                    <div><span class="wfm-badge wfm-badge-sm">${escapeHtml(ext)}</span>${dir ? ` <span class="wfm-badge wfm-badge-sm wfm-badge-dir">${escapeHtml(dir)}</span>` : ""}</div>
+                </section>
+                <section>
+                    <h4>${t("modelsBadges")} <button class="wfm-btn wfm-btn-sm" id="wfm-modal-badge-manage" style="margin-left:6px;font-size:10px;">&#9881; ${t("badgeManage")}</button></h4>
+                    <div id="wfm-modal-badge-checkboxes" class="wfm-badge-checkboxes">
+                        ${allBadgeLabels.length === 0
+                            ? `<span style="color:var(--wfm-text-secondary);font-size:12px;">${t("badgeNoneHint")}</span>`
+                            : badgeCheckboxes}
+                    </div>
+                </section>
+                <section>
+                    <h4>${t("modelsTags")} <span style="font-weight:normal;font-size:11px;">${t("modelsTagsHint")}</span></h4>
+                    <input type="text" class="wfm-input" id="wfm-modal-model-tags" value="${escapeHtml(tagsStr)}" placeholder="${t("modelsTagsPlaceholder")}">
+                </section>
+                <section>
+                    <h4>${t("modelsMemo")}</h4>
+                    <textarea class="wfm-textarea" id="wfm-modal-model-memo" rows="4" placeholder="${t("modelsMemoPlaceholder")}">${escapeHtml(meta.memo || "")}</textarea>
+                </section>
+                <div class="wfm-modal-actions">
+                    <button class="wfm-btn wfm-btn-primary wfm-btn-sm" id="wfm-modal-model-save">${t("modelsSave")}</button>
+                    ${state.activeModelType === "embedding"
+                        ? `<button class="wfm-btn wfm-btn-sm" id="wfm-modal-genui-pp" title="Positive Promptにエンベッディング追加">GenUI PP</button>
+                           <button class="wfm-btn wfm-btn-sm" id="wfm-modal-genui-np" title="Negative Promptにエンベッディング追加">GenUI NP</button>`
+                        : (GENUI_TYPE_MAP[state.activeModelType]
+                            ? `<button class="wfm-btn wfm-btn-sm" id="wfm-modal-genui-model" title="${t("modelsGenUITitle")}">${t("modelsGenUIBtn")}</button>`
+                            : "")}
+                    <button class="wfm-btn wfm-btn-sm wfm-btn-danger" id="wfm-modal-model-delete" style="margin-left:auto;">${t("modelsDelete")}</button>
+                    <button class="wfm-btn wfm-btn-sm" id="wfm-modal-model-close">${t("close")}</button>
+                </div>
+            </div>
+        </div>`;
+
+    openModal(getStem(name), html);
+
+    // Load preview image
+    const modalImg = document.querySelector(".wfm-modal-thumb-img");
+    const modalPlaceholder = document.querySelector(".wfm-modal-thumb-placeholder");
+    if (modalImg) loadPreviewImage(modalImg, modalPlaceholder, modelName);
+
+    // Add favorite button in header
+    const titleEl = document.getElementById("wfm-modal-title");
+    if (titleEl) {
+        titleEl.parentNode.querySelectorAll(".wfm-fav-btn").forEach((el) => el.remove());
+        const favBtn = document.createElement("button");
+        favBtn.className = isFav ? "wfm-fav-btn active" : "wfm-fav-btn";
+        favBtn.style.cssText = "position:static;font-size:18px;margin-right:8px;";
+        favBtn.textContent = isFav ? "★" : "☆";
+        favBtn.addEventListener("click", async () => {
+            const newVal = !meta.favorite;
+            await saveModelMetadata(modelName, { favorite: newVal });
+            meta.favorite = newVal;
+            favBtn.textContent = newVal ? "★" : "☆";
+            favBtn.classList.toggle("active", newVal);
+            renderModelGrid();
+        });
+        titleEl.parentNode.insertBefore(favBtn, titleEl);
+    }
+
+    // Badge manage button → open badge edit modal
+    document.getElementById("wfm-modal-badge-manage")?.addEventListener("click", () => {
+        openBadgeEditModal();
+    });
+
+    // Save
+    document.getElementById("wfm-modal-model-save")?.addEventListener("click", async () => {
+        const tagsInput = document.getElementById("wfm-modal-model-tags");
+        const memoInput = document.getElementById("wfm-modal-model-memo");
+        const tags = tagsInput ? tagsInput.value.split(",").map((s) => s.trim()).filter(Boolean) : [];
+        const memo = memoInput ? memoInput.value : "";
+        const badges = [...document.querySelectorAll(".wfm-badge-checkbox:checked")].map((cb) => cb.value);
+        await saveModelMetadata(modelName, { tags, memo, badges });
+        showToast(t("modelsSaved"), "success");
+        renderTagFilter();
+        renderDirFilter();
+        renderModelGrid();
+    });
+
+    // GenUI Model / Embedding buttons
+    document.getElementById("wfm-modal-genui-model")?.addEventListener("click", () => {
+        applyToGenUI(modelName, state.activeModelType);
+    });
+    document.getElementById("wfm-modal-genui-pp")?.addEventListener("click", () => {
+        applyEmbeddingToPrompt(modelName, "positive");
+    });
+    document.getElementById("wfm-modal-genui-np")?.addEventListener("click", () => {
+        applyEmbeddingToPrompt(modelName, "negative");
+    });
+
+    // Close button (連続作業時にXボタンまでマウス移動しなくて済むように)
+    document.getElementById("wfm-modal-model-close")?.addEventListener("click", () => {
+        closeModal();
+    });
+
+    // Delete model button
+    document.getElementById("wfm-modal-model-delete")?.addEventListener("click", async () => {
+        const confirmMsg = t("modelBulkDeleteConfirm").replace("{count}", "1");
+        if (!confirm(confirmMsg)) return;
+        try {
+            const res = await fetch("/api/wfm/models/delete", {
+                method: "POST",
+                headers: { "Content-Type": "application/json" },
+                body: JSON.stringify({ model_type: state.activeModelType, model_names: [modelName] }),
+            });
+            const data = await res.json();
+            if (data.errors?.length > 0) {
+                showToast(`${t("modelBulkDeleteError")}: ${data.errors[0].error}`, "error");
+                return;
+            }
+            showToast(`${getStem(name)} ${t("modelBulkDeleteDone")}`, "success");
+            closeModal();
+            const list = state.modelsByType[state.activeModelType];
+            const idx = list.indexOf(modelName);
+            if (idx !== -1) list.splice(idx, 1);
+            delete state.modelMetadata[modelName];
+            const ds = state.disabledModels[state.activeModelType];
+            if (ds) ds.delete(modelName);
+            state.selectedModels.delete(modelName);
+            if (state.selectedModel === modelName) {
+                state.selectedModel = null;
+                const titleEl2 = document.getElementById("wfm-models-panel-title");
+                if (titleEl2) titleEl2.textContent = "";
+            }
+            renderModelGrid();
+        } catch (err) {
+            showToast(`${t("modelBulkDeleteError")}: ${err.message}`, "error");
+        }
+    });
+
+    // Change thumbnail
+    const changeBtn = document.getElementById("wfm-modal-change-thumb");
+    const thumbFile = document.getElementById("wfm-modal-thumb-file");
+    if (changeBtn && thumbFile) {
+        changeBtn.addEventListener("click", () => { thumbFile.value = ""; thumbFile.click(); });
+        thumbFile.addEventListener("change", async () => {
+            const file = thumbFile.files?.[0];
+            if (!file) return;
+            changeBtn.disabled = true;
+            changeBtn.textContent = t("uploading");
+            try {
+                const fd = new FormData();
+                fd.append("type", state.activeModelType);
+                fd.append("name", modelName);
+                fd.append("file", file);
+                const res = await fetch("/api/wfm/models/change-preview", { method: "POST", body: fd });
+                const data = await res.json();
+                if (data.error) throw new Error(data.error);
+                // Reload preview in modal
+                const newUrl = previewUrl(modelName) + "&t=" + Date.now();
+                const mImg = document.querySelector(".wfm-modal-thumb-img");
+                const mPlaceholder = document.querySelector(".wfm-modal-thumb-placeholder");
+                if (mImg) { mImg.src = newUrl; mImg.style.display = ""; }
+                if (mPlaceholder) mPlaceholder.style.display = "none";
+                renderModelGrid();
+                if (state.selectedModel === modelName) renderSideInfo(modelName);
+                showToast(t("thumbnailChanged"), "success");
+            } catch (err) {
+                showToast(t("thumbnailError") + ": " + err.message, "error");
+            } finally {
+                changeBtn.disabled = false;
+                changeBtn.textContent = t("changeThumbnail");
+                thumbFile.value = "";
+            }
+        });
+    }
+}
+
+// ── Side Panel ────────────────────────────────────────────
+
+export function showSidePanel(modelName) {
+    state.selectedModel = modelName;
+
+    // Highlight selected
+    document.querySelectorAll("#wfm-models-grid .wfm-card, #wfm-models-grid .wfm-models-table-row").forEach((el) => {
+        el.classList.toggle("wfm-card-selected", el.dataset.modelName === modelName);
+    });
+
+    const { name } = parseModelPath(modelName);
+    document.getElementById("wfm-models-panel-title").textContent = name;
+
+    // Reset to CivitAI tab
+    document.querySelectorAll(".wfm-models-side-tab-btn").forEach((b) => b.classList.remove("active"));
+    document.querySelector('.wfm-models-side-tab-btn[data-side-tab="civitai"]')?.classList.add("active");
+    document.querySelectorAll(".wfm-models-side-content").forEach((c) => (c.style.display = "none"));
+    const civitaiEl = document.getElementById("wfm-models-side-civitai");
+    if (civitaiEl) civitaiEl.style.display = "block";
+
+    const genuiNavBtn = document.getElementById("wfm-side-genui-nav-btn");
+    const genuiNpBtn = document.getElementById("wfm-side-genui-np-btn");
+    if (genuiNavBtn) {
+        if (state.activeModelType === "embedding") {
+            genuiNavBtn.textContent = "GenUI PP";
+            genuiNavBtn.title = "Positive Promptにエンベッディング追加";
+            genuiNavBtn.style.display = "";
+            if (genuiNpBtn) {
+                genuiNpBtn.textContent = "GenUI NP";
+                genuiNpBtn.title = "Negative Promptにエンベッディング追加";
+                genuiNpBtn.style.display = "";
+            }
+        } else if (GENUI_TYPE_MAP[state.activeModelType]) {
+            genuiNavBtn.textContent = t("modelsGenUIBtn");
+            genuiNavBtn.title = t("modelsGenUITitle");
+            genuiNavBtn.style.display = "";
+            if (genuiNpBtn) genuiNpBtn.style.display = "none";
+        } else {
+            genuiNavBtn.style.display = "none";
+            if (genuiNpBtn) genuiNpBtn.style.display = "none";
+        }
+    }
+
+    renderSideInfo(modelName);
+    renderSideGroup(modelName);
+    renderSideCivitai(modelName);
+}
+
+export function closeSidePanel() {
+    state.selectedModel = null;
+    const titleEl = document.getElementById("wfm-models-panel-title");
+    if (titleEl) titleEl.textContent = "";
+    document.querySelectorAll("#wfm-models-grid .wfm-card, #wfm-models-grid .wfm-models-table-row").forEach((el) => {
+        el.classList.remove("wfm-card-selected");
+    });
+    const npBtn = document.getElementById("wfm-side-genui-np-btn");
+    if (npBtn) npBtn.style.display = "none";
+    const ppBtn = document.getElementById("wfm-side-genui-nav-btn");
+    if (ppBtn) ppBtn.style.display = "none";
+}
+
+// ── Side Panel: Info Tab ──────────────────────────────────
+
+export function renderSideInfo(modelName) {
+    const el = document.getElementById("wfm-models-side-info");
+    if (!el) return;
+
+    const meta = state.modelMetadata[modelName] || {};
+    const { dir, name } = parseModelPath(modelName);
+    const ext = getExtension(name);
+    const tagsStr = (meta.tags || []).join(", ");
+    const userBadgesHtml = modelBadgesHtml(modelName, false);
+
+    el.innerHTML = `
+        <div class="wfm-side-thumb-container">
+            <div class="wfm-side-thumb-img-wrap">
+                <img style="display:none" />
+                <span class="wfm-side-thumb-placeholder">${t("modelsNoPreview")}</span>
+            </div>
+            <div class="wfm-side-thumb-info">
+                <div class="wfm-side-thumb-name wfm-model-name-copy" title="${t("modelsCopyName")}">${escapeHtml(name)}</div>
+                <div class="wfm-side-thumb-meta">
+                    <span class="wfm-badge wfm-badge-sm">${escapeHtml(ext)}</span>
+                    ${dir ? `<span class="wfm-badge wfm-badge-sm wfm-badge-dir">${escapeHtml(dir)}</span>` : ""}
+                    ${userBadgesHtml}
+                </div>
+            </div>
+        </div>
+        <div class="wfm-node-detail-section">
+            <div class="wfm-node-detail-label">${t("modelsFilePath")}</div>
+            <div class="wfm-node-detail-value">
+                <span id="wfm-models-side-filepath" class="wfm-model-filepath" title="${t("modelsCopyPath")}" style="cursor:pointer;word-break:break-all;font-size:0.85em;color:#aaa;">${t("modelsLoading")}...</span>
+            </div>
+        </div>
+        <div class="wfm-node-detail-section">
+            <div class="wfm-node-detail-label">${t("modelsTags")}</div>
+            <div class="wfm-node-detail-value">
+                <input type="text" id="wfm-models-side-tags" class="wfm-search-input" value="${escapeHtml(tagsStr)}" placeholder="${t("modelsTagsPlaceholder")}">
+            </div>
+        </div>
+        <div class="wfm-node-detail-section">
+            <div class="wfm-node-detail-label">${t("modelsMemo")}</div>
+            <div class="wfm-node-detail-value">
+                <textarea id="wfm-models-side-memo" class="wfm-textarea" rows="4" placeholder="${t("modelsMemoPlaceholder")}">${escapeHtml(meta.memo || "")}</textarea>
+            </div>
+        </div>
+        <div class="wfm-node-detail-section" style="display:flex;gap:6px;">
+            <button id="wfm-models-side-save-btn" class="wfm-btn wfm-btn-sm wfm-btn-primary">${t("modelsSave")}</button>
+            ${state.activeModelType === "embedding"
+                ? `<button id="wfm-models-side-genui-pp-btn" class="wfm-btn wfm-btn-sm" title="Positive Promptにエンベッディング追加">GenUI PP</button>
+                   <button id="wfm-models-side-genui-np-btn" class="wfm-btn wfm-btn-sm" title="Negative Promptにエンベッディング追加">GenUI NP</button>`
+                : (GENUI_TYPE_MAP[state.activeModelType]
+                    ? `<button id="wfm-models-side-genui-btn" class="wfm-btn wfm-btn-sm" title="${t("modelsGenUITitle")}">${t("modelsGenUIBtn")}</button>`
+                    : "")}
+        </div>`;
+
+    // Load preview image
+    const sideImg = el.querySelector(".wfm-side-thumb-img-wrap img");
+    const sidePlaceholder = el.querySelector(".wfm-side-thumb-placeholder");
+    if (sideImg) loadPreviewImage(sideImg, sidePlaceholder, modelName);
+
+    // Copy model name on click
+    el.querySelector(".wfm-model-name-copy")?.addEventListener("click", () => {
+        navigator.clipboard.writeText(modelName).then(() => {
+            showToast(t("modelsCopiedName"), "success");
+        });
+    });
+
+    // Fetch and display file path
+    fetch(`/api/wfm/models/filepath?type=${encodeURIComponent(state.activeModelType)}&name=${encodeURIComponent(modelName)}`)
+        .then((r) => r.json())
+        .then((data) => {
+            const fpEl = document.getElementById("wfm-models-side-filepath");
+            if (fpEl && data.path) {
+                fpEl.textContent = data.path;
+                fpEl.title = t("modelsCopyPath");
+            } else if (fpEl) {
+                fpEl.textContent = modelName;
+            }
+        })
+        .catch(() => {
+            const fpEl = document.getElementById("wfm-models-side-filepath");
+            if (fpEl) fpEl.textContent = modelName;
+        });
+
+    // Copy file path on click
+    el.querySelector("#wfm-models-side-filepath")?.addEventListener("click", () => {
+        const fpEl = document.getElementById("wfm-models-side-filepath");
+        if (fpEl) {
+            navigator.clipboard.writeText(fpEl.textContent).then(() => {
+                showToast(t("modelsCopiedPath"), "success");
+            });
+        }
+    });
+
+    // Save button
+    el.querySelector("#wfm-models-side-save-btn")?.addEventListener("click", () => {
+        const tagsInput = document.getElementById("wfm-models-side-tags");
+        const memoInput = document.getElementById("wfm-models-side-memo");
+        const tags = tagsInput ? tagsInput.value.split(",").map((s) => s.trim()).filter(Boolean) : [];
+        const memo = memoInput ? memoInput.value : "";
+        saveModelMetadata(modelName, { tags, memo }).then(() => {
+            showToast(t("modelsSaved"), "success");
+            renderTagFilter();
+            renderModelGrid();
+        });
+    });
+
+    // GenUI Model / Embedding buttons
+    el.querySelector("#wfm-models-side-genui-btn")?.addEventListener("click", () => {
+        applyToGenUI(modelName, state.activeModelType);
+    });
+    el.querySelector("#wfm-models-side-genui-pp-btn")?.addEventListener("click", () => {
+        applyEmbeddingToPrompt(modelName, "positive");
+    });
+    el.querySelector("#wfm-models-side-genui-np-btn")?.addEventListener("click", () => {
+        applyEmbeddingToPrompt(modelName, "negative");
+    });
+}
+
+// ── Side Panel: Group Tab ─────────────────────────────────
+
+export function renderSideGroup(modelName) {
+    const el = document.getElementById("wfm-models-side-group");
+    if (!el) return;
+
+    // Find groups this model belongs to
+    const memberOf = [];
+    for (const [gName, members] of Object.entries(state.modelGroups)) {
+        if (members.includes(modelName)) memberOf.push(gName);
+    }
+
+    // All group names for the assign dropdown
+    const allGroups = Object.keys(state.modelGroups).sort();
+    const availableGroups = allGroups.filter((g) => !memberOf.includes(g));
+
+    el.innerHTML = `
+        <div style="padding:0 4px;">
+            <div style="margin-bottom:12px;">
+                <div style="font-weight:600;font-size:13px;margin-bottom:6px;">${t("modelsCurrentGroups")}</div>
+                ${memberOf.length === 0
+                    ? `<p style="color:var(--wfm-text-secondary);font-size:12px;">${t("modelsNoGroup")}</p>`
+                    : memberOf.map((g) => `<div style="display:flex;align-items:center;justify-content:space-between;padding:3px 0;">
+                        <span style="font-size:13px;">${escapeHtml(g)}</span>
+                        <button class="wfm-btn wfm-btn-sm wfm-btn-danger wfm-group-remove" data-group="${escapeHtml(g)}" title="${t("modelsRemoveFromGroup")}">&times;</button>
+                      </div>`).join("")}
+            </div>
+            <div style="margin-bottom:12px;">
+                <div style="font-weight:600;font-size:13px;margin-bottom:6px;">${t("modelsAssignGroup")}</div>
+                <div style="display:flex;gap:4px;">
+                    <select id="wfm-models-group-assign" class="wfm-select" style="flex:1;font-size:12px;">
+                        ${availableGroups.length === 0
+                            ? `<option value="">${t("modelsNoGroupAvailable")}</option>`
+                            : availableGroups.map((g) => `<option value="${escapeHtml(g)}">${escapeHtml(g)}</option>`).join("")}
+                    </select>
+                    <button class="wfm-btn wfm-btn-sm wfm-btn-primary" id="wfm-models-group-assign-btn" ${availableGroups.length === 0 ? "disabled" : ""}>${t("modelsAdd")}</button>
+                </div>
+            </div>
+            <div>
+                <div style="font-weight:600;font-size:13px;margin-bottom:6px;">${t("modelsCreateGroup")}</div>
+                <div style="display:flex;gap:4px;">
+                    <input type="text" id="wfm-models-group-new" class="wfm-search-input" style="flex:1;font-size:12px;" placeholder="${t("modelsGroupName")}">
+                    <button class="wfm-btn wfm-btn-sm wfm-btn-primary" id="wfm-models-group-create-btn">${t("modelsCreate")}</button>
+                </div>
+            </div>
+            <div style="margin-top:16px;border-top:1px solid var(--wfm-border);padding-top:12px;">
+                <div style="font-weight:600;font-size:13px;margin-bottom:6px;">${t("modelsManageGroups")}</div>
+                <div style="display:flex;gap:4px;margin-bottom:6px;">
+                    <select id="wfm-models-group-manage-select" class="wfm-select" style="flex:1;font-size:12px;">
+                        ${allGroups.length === 0
+                            ? `<option value="">${t("modelsNoGroupAvailable")}</option>`
+                            : allGroups.map((g) => `<option value="${escapeHtml(g)}">${escapeHtml(g)}</option>`).join("")}
+                    </select>
+                    <button class="wfm-btn wfm-btn-sm" id="wfm-models-group-rename-btn" ${allGroups.length === 0 ? "disabled" : ""}>${t("modelsRename")}</button>
+                    <button class="wfm-btn wfm-btn-sm wfm-btn-danger" id="wfm-models-group-delete-btn" ${allGroups.length === 0 ? "disabled" : ""}>${t("modelsDelete")}</button>
+                </div>
+                <div style="display:flex;gap:4px;">
+                    <button class="wfm-btn wfm-btn-sm wfm-btn-primary" id="wfm-models-group-enable-btn" ${allGroups.length === 0 ? "disabled" : ""}>${t("modelGroupEnableAll")}</button>
+                    <button class="wfm-btn wfm-btn-sm" id="wfm-models-group-disable-btn" ${allGroups.length === 0 ? "disabled" : ""}>${t("modelGroupDisableAll")}</button>
+                </div>
+            </div>
+        </div>
+    `;
+
+    // Remove from group
+    el.querySelectorAll(".wfm-group-remove").forEach((btn) => {
+        btn.addEventListener("click", () => {
+            const g = btn.dataset.group;
+            const members = state.modelGroups[g] || [];
+            state.modelGroups[g] = members.filter((m) => m !== modelName);
+            if (state.modelGroups[g].length === 0) delete state.modelGroups[g];
+            saveModelGroups(state.modelGroups).then(() => {
+                renderSideGroup(modelName);
+                renderModelGrid();
+            });
+        });
+    });
+
+    // Assign to group
+    document.getElementById("wfm-models-group-assign-btn")?.addEventListener("click", () => {
+        const sel = document.getElementById("wfm-models-group-assign");
+        const g = sel?.value;
+        if (!g) return;
+        if (!state.modelGroups[g]) state.modelGroups[g] = [];
+        if (!state.modelGroups[g].includes(modelName)) state.modelGroups[g].push(modelName);
+        saveModelGroups(state.modelGroups).then(() => {
+            renderSideGroup(modelName);
+        });
+    });
+
+    // Create new group
+    document.getElementById("wfm-models-group-create-btn")?.addEventListener("click", () => {
+        const input = document.getElementById("wfm-models-group-new");
+        const name = input?.value.trim();
+        if (!name) return;
+        if (state.modelGroups[name]) {
+            showToast(t("modelsGroupExists"), "warning");
+            return;
+        }
+        state.modelGroups[name] = [modelName];
+        saveModelGroups(state.modelGroups).then(() => {
+            renderSideGroup(modelName);
+        });
+    });
+
+    // Rename group
+    document.getElementById("wfm-models-group-rename-btn")?.addEventListener("click", () => {
+        const sel = document.getElementById("wfm-models-group-manage-select");
+        const oldName = sel?.value;
+        if (!oldName) return;
+        if (RESERVED_GROUPS.includes(oldName)) {
+            showToast(t("modelsGroupReserved"), "warning");
+            return;
+        }
+        const newName = prompt(t("modelsRenamePrompt"), oldName);
+        if (!newName || newName === oldName) return;
+        if (state.modelGroups[newName]) {
+            showToast(t("modelsGroupExists"), "warning");
+            return;
+        }
+        state.modelGroups[newName] = state.modelGroups[oldName];
+        delete state.modelGroups[oldName];
+        saveModelGroups(state.modelGroups).then(() => {
+            renderSideGroup(modelName);
+            renderModelGrid();
+        });
+    });
+
+    // Delete group
+    document.getElementById("wfm-models-group-delete-btn")?.addEventListener("click", () => {
+        const sel = document.getElementById("wfm-models-group-manage-select");
+        const g = sel?.value;
+        if (!g) return;
+        if (RESERVED_GROUPS.includes(g)) {
+            showToast(t("modelsGroupReserved"), "warning");
+            return;
+        }
+        if (!confirm(t("modelsDeleteGroupConfirm").replace("{name}", g))) return;
+        delete state.modelGroups[g];
+        saveModelGroups(state.modelGroups).then(() => {
+            renderSideGroup(modelName);
+            renderModelGrid();
+        });
+    });
+
+    // Enable all models in selected group
+    document.getElementById("wfm-models-group-enable-btn")?.addEventListener("click", () => {
+        const sel = document.getElementById("wfm-models-group-manage-select");
+        const g = sel?.value;
+        if (!g) return;
+        toggleGroupEnable(g, true).then(() => renderSideGroup(modelName));
+    });
+
+    // Disable all models in selected group
+    document.getElementById("wfm-models-group-disable-btn")?.addEventListener("click", () => {
+        const sel = document.getElementById("wfm-models-group-manage-select");
+        const g = sel?.value;
+        if (!g) return;
+        toggleGroupEnable(g, false).then(() => renderSideGroup(modelName));
+    });
+}
+
+// ── Side Panel: CivitAI Tab ───────────────────────────────
+
+export function renderSideCivitai(modelName) {
+    const el = document.getElementById("wfm-models-side-civitai");
+    if (!el) return;
+
+    // Check if we have cached civitai data via sha256
+    const meta = state.modelMetadata[modelName] || {};
+    const sha256 = meta.sha256;
+    const cached = sha256 && state.civitaiCache[sha256];
+
+    if (cached) {
+        renderCivitaiInfo(el, cached, modelName);
+    } else if (sha256) {
+        // SHA256 is known but model was not found on CivitAI
+        el.innerHTML = `
+            <div style="padding:0 4px;text-align:center;">
+                <p style="color:var(--wfm-text-secondary);font-size:13px;margin-bottom:12px;">
+                    ${t("civitaiNotFoundDesc")}
+                </p>
+                <button class="wfm-btn wfm-btn-sm" id="wfm-civitai-fetch-btn">
+                    ${t("civitaiRefetchBtn")}
+                </button>
+                <div id="wfm-civitai-status" style="margin-top:8px;font-size:12px;color:var(--wfm-text-secondary);"></div>
+            </div>`;
+        document.getElementById("wfm-civitai-fetch-btn")?.addEventListener("click", () => {
+            fetchCivitaiForModel(modelName, el);
+        });
+    } else {
+        el.innerHTML = `
+            <div style="padding:0 4px;text-align:center;">
+                <p style="color:var(--wfm-text-secondary);font-size:13px;margin-bottom:12px;">
+                    ${t("civitaiFetchDesc")}
+                </p>
+                <button class="wfm-btn wfm-btn-sm wfm-btn-primary" id="wfm-civitai-fetch-btn">
+                    ${t("civitaiFetch")}
+                </button>
+                <div id="wfm-civitai-status" style="margin-top:8px;font-size:12px;color:var(--wfm-text-secondary);"></div>
+            </div>`;
+        document.getElementById("wfm-civitai-fetch-btn")?.addEventListener("click", () => {
+            fetchCivitaiForModel(modelName, el);
+        });
+    }
+}
+
+export async function fetchCivitaiForModel(modelName, el) {
+    const statusEl = document.getElementById("wfm-civitai-status");
+    const fetchBtn = document.getElementById("wfm-civitai-fetch-btn");
+    if (fetchBtn) fetchBtn.disabled = true;
+    if (statusEl) statusEl.textContent = t("civitaiHashing");
+
+    try {
+        const res = await fetch("/api/wfm/models/civitai/fetch", {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify({ type: state.activeModelType, name: modelName }),
+        });
+        const data = await res.json();
+
+        if (data.status === "ok" && data.civitai) {
+            // Update caches
+            if (data.sha256) {
+                state.civitaiCache[data.sha256] = data.civitai;
+                // Update metadata with sha256
+                if (!state.modelMetadata[modelName]) state.modelMetadata[modelName] = {};
+                state.modelMetadata[modelName].sha256 = data.sha256;
+            }
+            renderCivitaiInfo(el, data.civitai, modelName);
+            showToast(t("civitaiFound"), "success");
+            // Always refresh preview: local file if saved, otherwise civitai image as fallback
+            const sidePanel = document.getElementById("wfm-models-side-panel");
+            if (sidePanel) {
+                const sideImg = sidePanel.querySelector(".wfm-side-thumb-img-wrap img");
+                const sidePh = sidePanel.querySelector(".wfm-side-thumb-placeholder");
+                if (sideImg) {
+                    if (data.preview_saved) {
+                        sideImg.src = previewUrl(modelName) + "&t=" + Date.now();
+                    } else {
+                        const civitaiImg = data.civitai.images && data.civitai.images[0];
+                        if (civitaiImg) sideImg.src = civitaiImg;
+                    }
+                    sideImg.style.display = "";
+                    if (sidePh) sidePh.style.display = "none";
+                }
+            }
+            renderModelGrid();
+        } else if (data.status === "not_found") {
+            if (statusEl) statusEl.textContent = t("civitaiNotFound");
+            if (fetchBtn) fetchBtn.disabled = false;
+        } else {
+            if (statusEl) statusEl.textContent = data.error || t("civitaiError");
+            if (fetchBtn) fetchBtn.disabled = false;
+        }
+    } catch (err) {
+        console.error("CivitAI fetch error:", err);
+        if (statusEl) statusEl.textContent = t("civitaiError");
+        if (fetchBtn) fetchBtn.disabled = false;
+    }
+}
+
+export function renderCivitaiInfo(el, info, modelName) {
+    // URL: ユーザー設定ホスト（localStorage）を使用、modelId なし時は /model-versions/ にフォールバック
+    const civitaiHost = localStorage.getItem("wfm_civitai_host") || "civitai.com";
+    const modelUrl = info.modelId && info.versionId
+        ? `https://${civitaiHost}/models/${info.modelId}?modelVersionId=${info.versionId}`
+        : info.versionId
+            ? `https://${civitaiHost}/model-versions/${info.versionId}`
+            : (info.modelUrl || "#");
+
+    // Hash: BLAKE3 優先、なければ SHA256
+    const fileHashes = info.fileHashes || {};
+    const blake3 = fileHashes.BLAKE3 || fileHashes.Blake3 || "";
+    const sha256 = fileHashes.SHA256 || (state.modelMetadata[modelName] || {}).sha256 || "";
+    const hashType = blake3 ? "BLAKE3" : (sha256 ? "SHA256" : "");
+    const hashFull = blake3 || sha256;
+
+    // Detail rows
+    const ROW = "display:flex;align-items:center;font-size:12px;margin-bottom:5px;";
+    const LABEL = "color:var(--wfm-text-secondary);min-width:80px;flex-shrink:0;";
+
+    const typeRow = info.type ? `
+        <div style="${ROW}">
+            <span style="${LABEL}">${t("civitaiType")}</span>
+            <span style="font-size:10px;font-weight:700;background:var(--wfm-bg-tertiary,rgba(255,255,255,0.1));padding:2px 7px;border-radius:3px;letter-spacing:0.6px;">${escapeHtml(info.type.toUpperCase())}</span>
+        </div>` : "";
+
+    const baseModelRow = info.baseModel ? `
+        <div style="${ROW}">
+            <span style="${LABEL}">${t("civitaiBaseModel")}</span>
+            <span>${escapeHtml(info.baseModel)}</span>
+        </div>` : "";
+
+    const hashRow = hashFull ? `
+        <div style="${ROW}">
+            <span style="${LABEL}">${t("civitaiHashLabel")}</span>
+            <code class="wfm-hash-value" data-hash="${escapeHtml(hashFull)}"
+                style="background:var(--wfm-bg-secondary);padding:2px 6px;border-radius:3px;cursor:pointer;font-size:11px;overflow:hidden;text-overflow:ellipsis;white-space:nowrap;max-width:calc(100% - 84px);"
+                title="${t("civitaiCopyHash")}">${escapeHtml(hashType)}: ${escapeHtml(hashFull.substring(0, 16).toUpperCase())}…</code>
+        </div>` : "";
+
+    const detailSection = (typeRow || baseModelRow || hashRow)
+        ? `<div style="margin-bottom:10px;">${typeRow}${baseModelRow}${hashRow}</div>` : "";
+
+    const tagsHtml = (info.tags || []).map((tag) =>
+        `<span class="wfm-badge wfm-badge-sm">${escapeHtml(tag)}</span>`
+    ).join(" ");
+
+    const trainedWordsHtml = (info.trainedWords || []).map((w) =>
+        `<code style="font-size:11px;background:var(--wfm-bg-secondary);padding:1px 4px;border-radius:3px;cursor:pointer;" class="wfm-trained-word" title="${t("civitaiCopyWord")}">${escapeHtml(w)}</code>`
+    ).join(" ");
+
+    // Sample images — all go to Sample pane
+    const images = info.images || [];
+    const sampleImagesHtml = images.map((url) =>
+        `<a href="${escapeHtml(url)}" target="_blank" rel="noopener" title="${t("civitaiOpenImage")}"><img src="${escapeHtml(url)}" style="width:100%;border-radius:4px;margin-bottom:6px;cursor:pointer;display:block;" loading="lazy" /></a>`
+    ).join("");
+
+    el.innerHTML = `
+        <div style="padding:0 4px;">
+            <div style="display:flex;border-bottom:1px solid var(--wfm-border);margin-bottom:10px;">
+                <button class="wfm-civitai-subtab-btn" data-pane="info"
+                    style="padding:4px 10px;font-size:12px;border:none;background:none;cursor:pointer;border-bottom:2px solid var(--wfm-primary);color:var(--wfm-primary);font-weight:600;margin-bottom:-1px;">
+                    ${t("civitaiTabInfo")}
+                </button>
+                <button class="wfm-civitai-subtab-btn" data-pane="sample"
+                    style="padding:4px 10px;font-size:12px;border:none;background:none;cursor:pointer;border-bottom:2px solid transparent;color:var(--wfm-text-secondary);margin-bottom:-1px;">
+                    ${t("civitaiTabSample")}${images.length ? ` (${images.length})` : ""}
+                </button>
+            </div>
+
+            <div id="wfm-civitai-pane-info">
+                <div style="margin-bottom:10px;">
+                    <div style="font-weight:700;font-size:14px;margin-bottom:2px;">
+                        <a href="${escapeHtml(modelUrl)}" target="_blank" style="color:var(--wfm-primary);text-decoration:none;">${escapeHtml(info.modelName)}</a>
+                    </div>
+                    <div style="font-size:12px;color:var(--wfm-text-secondary);">
+                        ${escapeHtml(info.versionName)}${info.creator ? ` · by ${escapeHtml(info.creator)}` : ""}
+                    </div>
+                </div>
+                ${detailSection}
+                ${tagsHtml ? `<div style="margin-bottom:8px;">${tagsHtml}</div>` : ""}
+                ${trainedWordsHtml ? `<div style="margin-bottom:10px;"><div style="font-weight:600;font-size:12px;margin-bottom:4px;">${t("civitaiTriggerWords")}</div>${trainedWordsHtml}</div>` : ""}
+                ${info.description ? `<div style="font-size:12px;color:var(--wfm-text-secondary);line-height:1.5;max-height:120px;overflow-y:auto;">${info.description}</div>` : ""}
+                <div style="margin-top:10px;">
+                    <button class="wfm-btn wfm-btn-sm" id="wfm-civitai-refresh-btn">${t("civitaiRefresh")}</button>
+                </div>
+            </div>
+
+            <div id="wfm-civitai-pane-sample" style="display:none;">
+                ${sampleImagesHtml || `<p style="color:var(--wfm-text-secondary);font-size:13px;text-align:center;margin-top:20px;">${t("civitaiNoImages")}</p>`}
+            </div>
+        </div>`;
+
+    // Sub-tab switching
+    const subtabBtns = el.querySelectorAll(".wfm-civitai-subtab-btn");
+    subtabBtns.forEach((btn) => {
+        btn.addEventListener("click", () => {
+            const pane = btn.dataset.pane;
+            subtabBtns.forEach((b) => {
+                const isActive = b === btn;
+                b.style.borderBottom = isActive ? "2px solid var(--wfm-primary)" : "2px solid transparent";
+                b.style.color = isActive ? "var(--wfm-primary)" : "var(--wfm-text-secondary)";
+                b.style.fontWeight = isActive ? "600" : "400";
+            });
+            el.querySelector("#wfm-civitai-pane-info").style.display = pane === "info" ? "" : "none";
+            el.querySelector("#wfm-civitai-pane-sample").style.display = pane === "sample" ? "" : "none";
+        });
+    });
+
+    // Copy trigger word on click
+    el.querySelectorAll(".wfm-trained-word").forEach((wordEl) => {
+        wordEl.addEventListener("click", () => {
+            navigator.clipboard.writeText(wordEl.textContent).then(() => {
+                showToast(t("civitaiWordCopied"), "success");
+            });
+        });
+    });
+
+    // Copy hash on click
+    el.querySelectorAll(".wfm-hash-value").forEach((hashEl) => {
+        hashEl.addEventListener("click", () => {
+            navigator.clipboard.writeText(hashEl.dataset.hash).then(() => {
+                showToast(t("civitaiHashCopied"), "success");
+            });
+        });
+    });
+
+    // Refresh button
+    document.getElementById("wfm-civitai-refresh-btn")?.addEventListener("click", () => {
+        const meta = state.modelMetadata[modelName] || {};
+        if (meta.sha256) delete state.civitaiCache[meta.sha256];
+        delete meta.sha256;
+        fetchCivitaiForModel(modelName, el);
+    });
+}
+
+// ── CivitAI cache / batch fetch ───────────────────────────
+
+export async function fetchCivitaiCache() {
+    try {
+        const res = await fetch("/api/wfm/models/civitai/cache");
+        return res.ok ? await res.json() : {};
+    } catch { return {}; }
+}
+
+export async function batchFetchCivitai() {
+    const models = getCurrentModels();
+    if (models.length === 0) {
+        showToast(t("modelsNoModels"), "warning");
+        return;
+    }
+
+    // Filter out models that already have CivitAI data
+    const meta = state.modelMetadata;
+    const uncached = models.filter((m) => {
+        const sha = meta[m]?.sha256;
+        return !sha || !state.civitaiCache[sha];
+    });
+
+    if (uncached.length === 0) {
+        showToast(t("civitaiBatchAllCached"), "info");
+        return;
+    }
+
+    const btn = document.getElementById("wfm-models-civitai-batch-btn");
+    const progressEl = document.getElementById("wfm-models-civitai-progress");
+    if (btn) btn.disabled = true;
+
+    try {
+        const res = await fetch("/api/wfm/models/civitai/batch", {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify({ type: state.activeModelType, models: uncached }),
+        });
+
+        const reader = res.body.getReader();
+        const decoder = new TextDecoder();
+        let buffer = "";
+
+        while (true) {
+            const { done, value } = await reader.read();
+            if (done) break;
+            buffer += decoder.decode(value, { stream: true });
+
+            // Parse SSE events
+            const lines = buffer.split("\n");
+            buffer = lines.pop() || "";
+
+            let eventType = "";
+            for (const line of lines) {
+                if (line.startsWith("event: ")) {
+                    eventType = line.slice(7).trim();
+                } else if (line.startsWith("data: ")) {
+                    const data = JSON.parse(line.slice(6));
+                    if (eventType === "progress") {
+                        const pct = data.total > 0 ? Math.round((data.current / data.total) * 100) : 0;
+                        const statusText = data.status === "hashing" ? t("civitaiHashing2")
+                            : data.status === "fetching" ? t("civitaiFetching")
+                            : data.status === "cached" ? "✓"
+                            : data.status === "found" ? "✓"
+                            : data.status === "not_found" ? "—"
+                            : "";
+                        if (progressEl) progressEl.textContent = `${pct}% (${data.current}/${data.total}) ${statusText}`;
+                    } else if (eventType === "done") {
+                        if (progressEl) progressEl.textContent = "";
+                        const previewNote = data.preview_saved > 0 ? ` (+${data.preview_saved} preview)` : "";
+                        showToast(t("civitaiBatchDone", data.found, data.not_found) + previewNote, "success");
+                        // Reload caches
+                        const [newMeta, newCache] = await Promise.all([fetchModelMetadata(), fetchCivitaiCache()]);
+                        // Apply sha256 hashes from batch result directly in case fetchModelMetadata
+                        // returns before the server has flushed updated metadata to disk
+                        if (data.hashes) {
+                            for (const [modelName, sha256] of Object.entries(data.hashes)) {
+                                if (!newMeta[modelName]) newMeta[modelName] = {};
+                                if (!newMeta[modelName].sha256) newMeta[modelName].sha256 = sha256;
+                            }
+                        }
+                        state.modelMetadata = newMeta;
+                        state.civitaiCache = newCache;
+                        renderModelGrid();
+                        // Refresh side panel if open
+                        if (state.selectedModel) renderSideCivitai(state.selectedModel);
+                    }
+                }
+            }
+        }
+    } catch (err) {
+        console.error("Batch CivitAI error:", err);
+        showToast(t("civitaiError"), "error");
+    } finally {
+        if (btn) btn.disabled = false;
+        if (progressEl) progressEl.textContent = "";
+    }
+}
@@ -0,0 +1,179 @@
+/**
+ * Models Tab - Filtering, sorting, and the tag/group/directory filter dropdowns
+ */
+
+import { t } from "../i18n.js";
+import { escapeHtml } from "../util.js";
+import { state } from "./state.js";
+import { parseModelPath, getExtension } from "./helpers.js";
+
+export function getCurrentModels() {
+    return state.modelsByType[state.activeModelType] || [];
+}
+
+export function isModelDisabled(modelName) {
+    const s = state.disabledModels[state.activeModelType];
+    return s ? s.has(modelName) : false;
+}
+
+export function filterModels() {
+    let models = getCurrentModels();
+
+    if (state.statusFilter === "enabled") {
+        models = models.filter((m) => !isModelDisabled(m));
+    } else if (state.statusFilter === "disabled") {
+        models = models.filter((m) => isModelDisabled(m));
+    }
+
+    if (state.showFavoritesOnly) {
+        models = models.filter((m) => {
+            const meta = state.modelMetadata[m];
+            return meta && meta.favorite;
+        });
+    }
+
+    if (state.showBatchOnly) {
+        const batchMembers = state.modelGroups["Batch"] || [];
+        models = models.filter((m) => batchMembers.includes(m));
+    }
+
+    if (state.tagFilter) {
+        models = models.filter((m) => {
+            const meta = state.modelMetadata[m];
+            return meta && meta.tags && meta.tags.includes(state.tagFilter);
+        });
+    }
+
+    if (state.badgeFilter) {
+        models = models.filter((m) => {
+            const meta = state.modelMetadata[m];
+            return meta && meta.badges && meta.badges.includes(state.badgeFilter);
+        });
+    }
+
+    if (state.dirFilter) {
+        models = models.filter((m) => {
+            const { dir } = parseModelPath(m);
+            return dir === state.dirFilter;
+        });
+    }
+
+    if (state.groupFilter) {
+        const members = state.modelGroups[state.groupFilter] || [];
+        models = models.filter((m) => members.includes(m));
+    }
+
+    if (state.searchText) {
+        const q = state.searchText.toLowerCase();
+        models = models.filter((m) => {
+            const meta = state.modelMetadata[m];
+            const searchable = [m, ...(meta?.tags || []), meta?.memo || ""]
+                .join(" ")
+                .toLowerCase();
+            return searchable.includes(q);
+        });
+    }
+
+    return sortModels(models);
+}
+
+export function sortKeyOf(modelName) {
+    const meta = state.modelMetadata[modelName] || {};
+    switch (state.sortColumn) {
+        case "fav":
+            return meta.favorite ? 1 : 0;
+        case "filename":
+            return parseModelPath(modelName).name.toLowerCase();
+        case "subdir":
+            return parseModelPath(modelName).dir.toLowerCase();
+        case "civtype": {
+            const civ = meta.sha256 && state.civitaiCache[meta.sha256];
+            return (civ?.type || "").toLowerCase();
+        }
+        case "basemodel": {
+            const civ = meta.sha256 && state.civitaiCache[meta.sha256];
+            return (civ?.baseModel || "").toLowerCase();
+        }
+        case "ext":
+            return getExtension(parseModelPath(modelName).name).toLowerCase();
+        case "tags":
+            return (meta.tags || []).join(", ").toLowerCase();
+        case "memo":
+            return (meta.memo || "").toLowerCase();
+        case "enabled":
+            return isModelDisabled(modelName) ? 1 : 0;
+        default:
+            return 0;
+    }
+}
+
+export function sortModels(models) {
+    if (!state.sortColumn) return models;
+    // ソートキーを1モデル1回だけ計算（比較ごとのparseModelPath等の再計算を回避）
+    const dir = state.sortDir === "asc" ? 1 : -1;
+    return models
+        .map((m) => [sortKeyOf(m), m])
+        .sort((a, b) => (a[0] < b[0] ? -dir : a[0] > b[0] ? dir : 0))
+        .map((pair) => pair[1]);
+}
+
+export function getAllTags() {
+    const set = new Set();
+    const models = getCurrentModels();
+    models.forEach((m) => {
+        const meta = state.modelMetadata[m];
+        if (meta?.tags) meta.tags.forEach((tag) => set.add(tag));
+    });
+    return [...set].sort();
+}
+
+// ── Render: Tag Filter ────────────────────────────────────
+
+export function renderTagFilter() {
+    const select = document.getElementById("wfm-models-tag-filter");
+    if (!select) return;
+    const tags = getAllTags();
+    select.innerHTML =
+        `<option value="">${t("modelsAllTags")}</option>` +
+        tags.map((tag) => `<option value="${escapeHtml(tag)}">${escapeHtml(tag)}</option>`).join("");
+    select.value = state.tagFilter;
+}
+
+export function renderGroupFilter() {
+    const select = document.getElementById("wfm-models-group-filter");
+    if (!select) return;
+
+    const groups = state.allModelGroups[state.activeModelType] || {};
+    const names = Object.keys(groups).sort();
+
+    // 選択中のグループが削除された場合はフィルターをリセット
+    if (state.groupFilter && !groups[state.groupFilter]) {
+        state.groupFilter = "";
+    }
+
+    const currentValue = state.groupFilter
+        ? `${state.activeModelType}::${state.groupFilter}`
+        : "";
+
+    select.innerHTML =
+        `<option value="">${t("modelsAllGroups")}</option>` +
+        names.map((name) => {
+            const value = `${state.activeModelType}::${name}`;
+            const isActive = value === currentValue;
+            return `<option value="${escapeHtml(value)}"${isActive ? " selected" : ""}>${escapeHtml(name)}</option>`;
+        }).join("");
+}
+
+export function renderDirFilter() {
+    const select = document.getElementById("wfm-models-dir-filter");
+    if (!select) return;
+    const dirs = [...new Set(
+        getCurrentModels()
+            .map((m) => parseModelPath(m).dir)
+            .filter((d) => d !== "")
+    )].sort();
+    select.innerHTML =
+        `<option value="">${t("modelsAllDirs")}</option>` +
+        dirs.map((d) => `<option value="${escapeHtml(d)}">${escapeHtml(d)}</option>`).join("");
+    select.value = state.dirFilter;
+}
@@ -0,0 +1,329 @@
+/**
+ * Models Tab - Grid rendering (Thumbnail / Table views) and per-card
+ * Batch/Stack/Favorite toggles.
+ *
+ * This module and selection-bulk.js / detail-panel.js form a circular
+ * import triangle with each other and with models-tab.js: rendering a card
+ * needs to wire up selection, side-panel, and detail-modal click handlers,
+ * and those in turn re-render the grid after they change state. All the
+ * cross-module calls happen inside event handlers (never at module
+ * evaluation time), and every export here is a `function` declaration
+ * (hoisted), so the cycle resolves safely under ES Modules.
+ */
+
+import { showToast } from "../app.js";
+import { t } from "../i18n.js";
+import { escapeHtml } from "../util.js";
+import { state } from "./state.js";
+import { filterModels, getCurrentModels, isModelDisabled } from "./filters.js";
+import { modelBadgesHtml } from "./badges.js";
+import { parseModelPath, getExtension, getStem, loadPreviewImage } from "./helpers.js";
+import { toggleModelSelection } from "./selection-bulk.js";
+import { showSidePanel, openDetailModal, renderSideInfo } from "./detail-panel.js";
+import { saveModelGroups, saveModelMetadata, toggleModelEnable } from "../models-tab.js";
+
+export function renderModelGrid() {
+    const grid = document.getElementById("wfm-models-grid");
+    if (!grid) return;
+
+    grid.className = `wfm-grid wfm-view-${state.viewMode}`;
+    const filtered = filterModels();
+
+    // Update count
+    const countEl = document.getElementById("wfm-models-count");
+    if (countEl) {
+        const total = getCurrentModels().length;
+        countEl.textContent = `${filtered.length} / ${total}`;
+    }
+
+    if (filtered.length === 0) {
+        grid.innerHTML = `<p class="wfm-placeholder">${t("modelsNoModels")}</p>`;
+        return;
+    }
+
+    if (state.viewMode === "table") {
+        renderTableView(grid, filtered);
+    } else {
+        renderThumbView(grid, filtered);
+    }
+}
+
+// ── Thumbnail View (same as Workflow tab) ─────────────────
+
+export function renderThumbView(grid, models) {
+    grid.innerHTML = "";
+    models.forEach((modelName) => {
+        const meta = state.modelMetadata[modelName] || {};
+        const { name } = parseModelPath(modelName);
+        const disabled = isModelDisabled(modelName);
+        const userBadges = modelBadgesHtml(modelName);
+        const tagsHtml = (meta.tags || []).map((tag) => `<span class="wfm-badge wfm-badge-sm">${escapeHtml(tag)}</span>`).join("");
+        const favStar = meta.favorite ? "★" : "☆";
+        const favClass = meta.favorite ? "wfm-fav-btn active" : "wfm-fav-btn";
+        const showBatchBtn = ["checkpoint", "lora"].includes(state.activeModelType);
+        const showStackBtn = state.activeModelType === "lora";
+        const inBatch = showBatchBtn && isInBatch(modelName);
+        const inStack = showStackBtn && isInStack(modelName);
+        const batchClass = inBatch ? "wfm-batch-btn active" : "wfm-batch-btn";
+        const stackClass = inStack ? "wfm-stack-btn active" : "wfm-stack-btn";
+
+        const card = document.createElement("div");
+        card.className = "wfm-card";
+        if (disabled) card.classList.add("wfm-model-disabled");
+        if (state.selectedModel === modelName) card.classList.add("wfm-card-selected");
+        card.dataset.modelName = modelName;
+
+        card.innerHTML = `
+            <div class="wfm-card-thumb">
+                <img style="display:none" />
+                <span class="wfm-card-thumb-placeholder">${t("modelsNoPreview")}</span>
+                ${disabled ? `<span class="wfm-disabled-overlay">${t("modelDisabled")}</span>` : ""}
+            </div>
+            <div class="wfm-card-body">
+                <div class="wfm-card-title" title="${escapeHtml(modelName)}">${escapeHtml(getStem(name))}</div>
+                <div class="wfm-card-meta">${userBadges} ${tagsHtml}</div>
+            </div>
+            ${showBatchBtn ? `<button class="${batchClass}" title="${t("modelsBatch")}">B</button>` : ""}
+            ${showStackBtn ? `<button class="${stackClass}" title="Stack (Lora multi-apply)">S</button>` : ""}
+            <button class="${favClass}" title="${t("modelsFavorite")}">${favStar}</button>
+            <button class="wfm-toggle-btn${disabled ? " wfm-toggle-disabled" : ""}" title="${disabled ? t("modelEnable") : t("modelDisable")}">${disabled ? "▶" : "⏸"}</button>`;
+
+        // Load preview without 404 console spam
+        const img = card.querySelector(".wfm-card-thumb img");
+        const placeholder = card.querySelector(".wfm-card-thumb-placeholder");
+        loadPreviewImage(img, placeholder, modelName);
+
+        card.querySelector(".wfm-batch-btn")?.addEventListener("click", async (e) => {
+            e.stopPropagation();
+            const btn = e.currentTarget;
+            await toggleBatch(modelName);
+            if (state.showBatchOnly) {
+                renderModelGrid();
+            } else {
+                btn.classList.toggle("active", isInBatch(modelName));
+            }
+        });
+        card.querySelector(".wfm-stack-btn")?.addEventListener("click", async (e) => {
+            e.stopPropagation();
+            const btn = e.currentTarget;
+            await toggleStack(modelName);
+            btn.classList.toggle("active", isInStack(modelName));
+        });
+        card.querySelector(".wfm-fav-btn").addEventListener("click", (e) => {
+            e.stopPropagation();
+            toggleFavorite(modelName);
+        });
+        card.querySelector(".wfm-toggle-btn").addEventListener("click", (e) => {
+            e.stopPropagation();
+            toggleModelEnable(modelName);
+        });
+        if (state.selectMode) {
+            const isChecked = state.selectedModels.has(modelName);
+            card.classList.toggle("wfm-card-checked", isChecked);
+            const checkEl = document.createElement("div");
+            checkEl.className = "wfm-select-check" + (isChecked ? " checked" : "");
+            card.appendChild(checkEl);
+            card.addEventListener("click", (e) => {
+                if (e.target.closest(".wfm-batch-btn, .wfm-stack-btn, .wfm-fav-btn, .wfm-toggle-btn")) return;
+                toggleModelSelection(modelName);
+            });
+        } else {
+            card.addEventListener("click", () => showSidePanel(modelName));
+            card.addEventListener("dblclick", (e) => { e.stopPropagation(); openDetailModal(modelName); });
+        }
+        grid.appendChild(card);
+    });
+}
+
+
+// ── Table View ────────────────────────────────────────────
+
+export function thSortHtml(label, col, extraClass = "", extraStyle = "") {
+    const isActive = state.sortColumn === col;
+    const arrow = isActive ? (state.sortDir === "asc" ? " ▲" : " ▼") : "";
+    const activeStyle = isActive ? "color:var(--wfm-accent,#6366f1);" : "";
+    const cls = ["wfm-table-th-sortable", extraClass].filter(Boolean).join(" ");
+    return `<th class="${cls}" data-sort-col="${col}" style="${activeStyle}${extraStyle}">${label}${arrow}</th>`;
+}
+
+export function renderTableView(grid, models) {
+    const showBatchBtn = ["checkpoint", "lora"].includes(state.activeModelType);
+    const showStackBtn = state.activeModelType === "lora";
+    const rows = models
+        .map((modelName) => {
+            const meta = state.modelMetadata[modelName] || {};
+            const { dir, name } = parseModelPath(modelName);
+            const ext = getExtension(name);
+            const sha256 = meta.sha256;
+            const civitai = sha256 && state.civitaiCache[sha256];
+            const civitaiType = civitai ? (civitai.type || "") : "";
+            const civitaiBaseModel = civitai ? (civitai.baseModel || "") : "";
+            const disabled = isModelDisabled(modelName);
+            const isChecked = state.selectMode && state.selectedModels.has(modelName);
+            const favIcon = meta.favorite ? "&#9733;" : "&#9734;";
+            const batchIcon = !showBatchBtn ? "" : isInBatch(modelName) ? `<button class="wfm-batch-btn active" title="${t("modelsBatch")}">B</button>` : `<button class="wfm-batch-btn" title="${t("modelsBatch")}">B</button>`;
+            const stackIcon = isInStack(modelName) ? `<button class="wfm-stack-btn active" title="Stack (Lora multi-apply)">S</button>` : `<button class="wfm-stack-btn" title="Stack (Lora multi-apply)">S</button>`;
+            const tagsStr = (meta.tags || []).join(", ");
+            const memo = meta.memo || "";
+            const toggleLabel = disabled ? t("modelEnable") : t("modelDisable");
+            const toggleIcon = disabled ? "▶" : "⏸";
+            const checkCell = state.selectMode
+                ? `<td class="wfm-table-td-check"><div class="wfm-select-check${isChecked ? " checked" : ""}"></div></td>`
+                : "";
+            return `<tr class="wfm-models-table-row${state.selectedModel === modelName ? " wfm-card-selected" : ""}${disabled ? " wfm-model-disabled" : ""}${isChecked ? " wfm-card-checked" : ""}" data-model-name="${escapeHtml(modelName)}">
+                ${checkCell}
+                <td class="wfm-models-table-fav" title="Favorite">${favIcon}</td>
+                <td class="wfm-table-td-thumb"><img class="wfm-table-thumb" style="display:none" /></td>
+                <td class="wfm-table-td-filename" title="${escapeHtml(modelName)}">${escapeHtml(name)}</td>
+                <td class="wfm-table-td-subdir">${escapeHtml(dir)}</td>
+                <td class="wfm-table-td-civtype" title="${escapeHtml(civitaiType)}">${escapeHtml(civitaiType)}</td>
+                <td class="wfm-table-td-basemodel" title="${escapeHtml(civitaiBaseModel)}">${escapeHtml(civitaiBaseModel)}</td>
+                <td class="wfm-table-td-ext">${escapeHtml(ext)}</td>
+                <td>${escapeHtml(tagsStr)}</td>
+                <td class="wfm-table-td-memo" title="${escapeHtml(memo)}">${escapeHtml(memo)}</td>
+                <td class="wfm-table-td-toggle"><button class="wfm-toggle-btn${disabled ? " wfm-toggle-disabled" : ""}" title="${toggleLabel}">${toggleIcon}</button></td>
+                ${showBatchBtn ? `<td class="wfm-table-td-batch">${batchIcon}</td>` : ""}
+                ${showStackBtn ? `<td class="wfm-table-td-stack">${stackIcon}</td>` : ""}
+            </tr>`;
+        })
+        .join("");
+
+    const checkTh = state.selectMode ? `<th style="width:24px;"></th>` : "";
+    grid.innerHTML = `<table class="wfm-models-table"><thead><tr>
+        ${checkTh}
+        ${thSortHtml("&#9733;", "fav", "", "width:30px;text-align:center;")}
+        <th style="width:40px;"></th>
+        ${thSortHtml(t("modelsFileName"), "filename", "wfm-table-th-filename")}
+        ${thSortHtml(t("modelsSubdir"), "subdir", "wfm-table-th-subdir")}
+        ${thSortHtml(t("civitaiType"), "civtype", "wfm-table-th-civtype")}
+        ${thSortHtml(t("civitaiBaseModel"), "basemodel", "wfm-table-th-basemodel")}
+        ${thSortHtml(t("modelsExt"), "ext", "wfm-table-th-ext")}
+        ${thSortHtml(t("modelsTags"), "tags")}
+        ${thSortHtml(t("modelsMemo"), "memo")}
+        ${thSortHtml("E/D", "enabled", "", "width:50px;text-align:center;")}
+        ${showBatchBtn ? `<th style="width:30px;">B</th>` : ""}
+        ${showStackBtn ? `<th style="width:30px;">S</th>` : ""}
+    </tr></thead><tbody>${rows}</tbody></table>`;
+
+    grid.querySelectorAll(".wfm-models-table-row").forEach((row) => {
+        const mn = row.dataset.modelName;
+        const img = row.querySelector(".wfm-table-thumb");
+        if (img) loadPreviewImage(img, null, mn);
+
+        if (state.selectMode) {
+            row.addEventListener("click", (e) => {
+                if (e.target.closest(".wfm-models-table-fav, .wfm-toggle-btn, .wfm-batch-btn, .wfm-stack-btn")) return;
+                toggleModelSelection(mn);
+            });
+        } else {
+            row.addEventListener("click", () => showSidePanel(mn));
+            row.addEventListener("dblclick", (e) => { e.stopPropagation(); openDetailModal(mn); });
+        }
+        row.querySelector(".wfm-models-table-fav").addEventListener("click", (e) => {
+            e.stopPropagation();
+            toggleFavorite(mn);
+        });
+        row.querySelector(".wfm-toggle-btn").addEventListener("click", (e) => {
+            e.stopPropagation();
+            toggleModelEnable(mn);
+        });
+        row.querySelector(".wfm-batch-btn")?.addEventListener("click", async (e) => {
+            e.stopPropagation();
+            await toggleBatch(mn);
+            if (state.showBatchOnly) {
+                renderModelGrid();
+            } else {
+                e.currentTarget.classList.toggle("active", isInBatch(mn));
+            }
+        });
+        row.querySelector(".wfm-stack-btn")?.addEventListener("click", async (e) => {
+            e.stopPropagation();
+            await toggleStack(mn);
+            e.currentTarget.classList.toggle("active", isInStack(mn));
+        });
+    });
+
+    grid.querySelectorAll(".wfm-table-th-sortable").forEach((th) => {
+        th.addEventListener("click", () => {
+            const col = th.dataset.sortCol;
+            if (state.sortColumn === col) {
+                if (state.sortDir === "asc") {
+                    state.sortDir = "desc";
+                } else {
+                    state.sortColumn = null;
+                    state.sortDir = "asc";
+                }
+            } else {
+                state.sortColumn = col;
+                state.sortDir = "asc";
+            }
+            renderModelGrid();
+        });
+    });
+}
+
+// ── Batch group helpers ───────────────────────────────────
+
+export function isInBatch(modelName) {
+    return (state.modelGroups["Batch"] || []).includes(modelName);
+}
+
+export async function toggleBatch(modelName) {
+    const batch = state.modelGroups["Batch"] || [];
+    const idx = batch.indexOf(modelName);
+    if (idx >= 0) {
+        batch.splice(idx, 1);
+    } else {
+        batch.push(modelName);
+    }
+    state.modelGroups["Batch"] = batch;
+    state.allModelGroups[state.activeModelType] = state.modelGroups;
+    await saveModelGroups(state.modelGroups);
+}
+
+export async function clearBatchGroup() {
+    state.modelGroups["Batch"] = [];
+    state.allModelGroups[state.activeModelType] = state.modelGroups;
+    await saveModelGroups(state.modelGroups);
+    if (state.showBatchOnly) {
+        state.showBatchOnly = false;
+        document.getElementById("wfm-models-batch-filter-btn")?.classList.remove("active");
+    }
+    renderModelGrid();
+    showToast(t("modelsBatchClear"), "success");
+}
+
+export function isInStack(modelName) {
+    return (state.modelGroups["Stack"] || []).includes(modelName);
+}
+
+export async function toggleStack(modelName) {
+    const stack = state.modelGroups["Stack"] || [];
+    const idx = stack.indexOf(modelName);
+    if (idx >= 0) {
+        stack.splice(idx, 1);
+    } else {
+        stack.push(modelName);
+    }
+    state.modelGroups["Stack"] = stack;
+    state.allModelGroups[state.activeModelType] = state.modelGroups;
+    await saveModelGroups(state.modelGroups);
+}
+
+export async function clearStackGroup() {
+    state.modelGroups["Stack"] = [];
+    state.allModelGroups[state.activeModelType] = state.modelGroups;
+    await saveModelGroups(state.modelGroups);
+    renderModelGrid();
+    showToast(t("stackCleared"), "success");
+}
+
+// ── Favorite toggle ───────────────────────────────────────
+
+export async function toggleFavorite(modelName) {
+    const meta = state.modelMetadata[modelName] || {};
+    const newFav = !meta.favorite;
+    await saveModelMetadata(modelName, { favorite: newFav });
+    renderModelGrid();
+    if (state.selectedModel === modelName) renderSideInfo(modelName);
+}
@@ -0,0 +1,59 @@
+/**
+ * Models Tab - Small path/preview helpers shared across the models/* modules
+ */
+
+import { state } from "./state.js";
+
+export function parseModelPath(fullName) {
+    const lastSlash = Math.max(fullName.lastIndexOf("/"), fullName.lastIndexOf("\\"));
+    if (lastSlash === -1) return { dir: "", name: fullName };
+    return { dir: fullName.substring(0, lastSlash), name: fullName.substring(lastSlash + 1) };
+}
+
+export function getExtension(name) {
+    const dot = name.lastIndexOf(".");
+    return dot >= 0 ? name.substring(dot) : "";
+}
+
+export function getStem(name) {
+    const dot = name.lastIndexOf(".");
+    return dot >= 0 ? name.substring(0, dot) : name;
+}
+
+export function previewUrl(modelName, modelType) {
+    const type = modelType || state.activeModelType;
+    return `/api/wfm/models/preview?type=${encodeURIComponent(type)}&name=${encodeURIComponent(modelName)}`;
+}
+
+/**
+ * Load preview image. Uses img onload/onerror instead of HEAD request
+ * (aiohttp add_get does not auto-handle HEAD method).
+ * Falls back to CivitAI cached image if no local preview exists.
+ */
+export function loadPreviewImage(imgEl, placeholderEl, modelName, modelType) {
+    const url = previewUrl(modelName, modelType);
+    imgEl.onload = () => {
+        imgEl.style.display = "";
+        if (placeholderEl) placeholderEl.style.display = "none";
+    };
+    imgEl.onerror = () => {
+        // Fallback: use CivitAI cached image if available
+        const meta = state.modelMetadata[modelName] || {};
+        const sha256 = meta.sha256;
+        const civitai = sha256 && state.civitaiCache[sha256];
+        const civitaiImg = civitai && civitai.images && civitai.images[0];
+        if (civitaiImg) {
+            imgEl.onerror = () => {
+                imgEl.style.display = "none";
+                if (placeholderEl) placeholderEl.style.display = "";
+            };
+            imgEl.src = civitaiImg;
+            imgEl.style.display = "";
+            if (placeholderEl) placeholderEl.style.display = "none";
+        } else {
+            imgEl.style.display = "none";
+            if (placeholderEl) placeholderEl.style.display = "";
+        }
+    };
+    imgEl.src = url;
+}
@@ -0,0 +1,318 @@
+/**
+ * Models Tab - Multi-select mode and bulk group/badge/favorite/move/delete
+ * operations on the current selection.
+ *
+ * Part of the grid-view.js / selection-bulk.js / detail-panel.js circular
+ * import triangle — see the note at the top of grid-view.js.
+ */
+
+import { showToast } from "../app.js";
+import { t } from "../i18n.js";
+import { escapeHtml } from "../util.js";
+import { state, RESERVED_GROUPS } from "./state.js";
+import { filterModels, renderDirFilter } from "./filters.js";
+import { getBadgePalette } from "./badges.js";
+import { renderModelGrid } from "./grid-view.js";
+import { saveModelGroups, saveModelMetadata } from "../models-tab.js";
+
+export function toggleSelectMode() {
+    state.selectMode = !state.selectMode;
+    if (!state.selectMode) state.selectedModels.clear();
+    const btn = document.getElementById("wfm-models-select-btn");
+    if (btn) {
+        btn.classList.toggle("active", state.selectMode);
+        btn.textContent = state.selectMode ? t("modelSelectExit") : t("modelSelectMode");
+    }
+    renderModelGrid();
+    renderBulkActionBar();
+}
+
+export function toggleModelSelection(modelName) {
+    if (state.selectedModels.has(modelName)) {
+        state.selectedModels.delete(modelName);
+    } else {
+        state.selectedModels.add(modelName);
+    }
+    // Update DOM directly (avoid full re-render)
+    document.querySelectorAll("[data-model-name]").forEach((el) => {
+        if (el.dataset.modelName !== modelName) return;
+        const checked = state.selectedModels.has(modelName);
+        el.classList.toggle("wfm-card-checked", checked);
+        const c = el.querySelector(".wfm-select-check");
+        if (c) c.classList.toggle("checked", checked);
+    });
+    renderBulkActionBar();
+}
+
+export function clearSelection() {
+    state.selectedModels.clear();
+    renderModelGrid();
+    renderBulkActionBar();
+}
+
+export function selectAll() {
+    filterModels().forEach(m => state.selectedModels.add(m));
+    renderModelGrid();
+    renderBulkActionBar();
+}
+
+export function renderBulkActionBar() {
+    const bar = document.getElementById("wfm-models-bulk-bar");
+    if (!bar) return;
+    if (!state.selectMode || state.selectedModels.size === 0) {
+        bar.style.display = "none";
+        return;
+    }
+    const count = state.selectedModels.size;
+    const groupNames = Object.keys(state.modelGroups).sort();
+    const noGroups = groupNames.length === 0;
+    const groupOptions = noGroups
+        ? `<option value="">${t("modelsNoGroupAvailable")}</option>`
+        : groupNames.map((g) => `<option value="${escapeHtml(g)}">${escapeHtml(g)}</option>`).join("");
+
+    const palette = getBadgePalette();
+    const badgeLabels = Object.keys(palette).sort();
+    const noBadges = badgeLabels.length === 0;
+    const badgeOptions = noBadges
+        ? `<option value="">${t("modelBulkNoBadge")}</option>`
+        : badgeLabels.map((b) => `<option value="${escapeHtml(b)}">${escapeHtml(b)}</option>`).join("");
+
+    bar.style.display = "flex";
+    bar.innerHTML = `
+        <div class="wfm-bulk-header">
+            <span class="wfm-bulk-count">${count} ${t("modelSelected")}</span>
+            <button class="wfm-btn wfm-btn-sm" id="wfm-bulk-deselect-all-btn">${t("modelBulkDeselectAll")}</button>
+            <button class="wfm-btn wfm-btn-sm" id="wfm-bulk-select-all-btn">${t("modelBulkSelectAll")}</button>
+            <span class="wfm-bulk-sep"></span>
+            <button class="wfm-btn wfm-btn-sm" id="wfm-bulk-fav-add-btn">${t("modelBulkFavAdd")}</button>
+            <button class="wfm-btn wfm-btn-sm" id="wfm-bulk-fav-remove-btn">${t("modelBulkFavRemove")}</button>
+        </div>
+        <div class="wfm-bulk-rows">
+            <div class="wfm-bulk-row">
+                <span class="wfm-bulk-row-label">Group:</span>
+                <select id="wfm-bulk-group-select" class="wfm-select wfm-bulk-select">${groupOptions}</select>
+                <button class="wfm-btn wfm-btn-sm wfm-btn-primary" id="wfm-bulk-add-btn"${noGroups ? " disabled" : ""}>${t("modelBulkAddGroup")}</button>
+                <button class="wfm-btn wfm-btn-sm wfm-btn-danger" id="wfm-bulk-remove-btn"${noGroups ? " disabled" : ""}>${t("modelBulkRemoveGroup")}</button>
+                <span class="wfm-bulk-sep"></span>
+                <input type="text" id="wfm-bulk-new-group-input" class="wfm-search-input wfm-bulk-input" placeholder="${t("modelsGroupName")}">
+                <button class="wfm-btn wfm-btn-sm" id="wfm-bulk-create-add-btn">${t("modelBulkCreateAdd")}</button>
+            </div>
+            <div class="wfm-bulk-row">
+                <span class="wfm-bulk-row-label">Badge:</span>
+                <select id="wfm-bulk-badge-select" class="wfm-select wfm-bulk-select">${badgeOptions}</select>
+                <button class="wfm-btn wfm-btn-sm wfm-btn-primary" id="wfm-bulk-badge-apply-btn"${noBadges ? " disabled" : ""}>${t("modelBulkBadgeApply")}</button>
+                <button class="wfm-btn wfm-btn-sm wfm-btn-danger" id="wfm-bulk-badge-remove-btn"${noBadges ? " disabled" : ""}>${t("modelBulkBadgeRemove")}</button>
+            </div>
+            <div class="wfm-bulk-row">
+                <span class="wfm-bulk-row-label">File:</span>
+                <select id="wfm-bulk-move-select" class="wfm-select wfm-bulk-select">
+                    <option value="">${t("modelBulkMoveRoot")}</option>
+                    ${state.subdirs.map((d) => `<option value="${escapeHtml(d)}">${escapeHtml(d)}</option>`).join("")}
+                </select>
+                <button class="wfm-btn wfm-btn-sm" id="wfm-bulk-move-btn">${t("modelBulkMoveBtn")}</button>
+                <span class="wfm-bulk-sep"></span>
+                <input type="text" id="wfm-bulk-new-dir-input" class="wfm-search-input wfm-bulk-input" placeholder="${t("modelBulkMoveNewFolder")}">
+                <button class="wfm-btn wfm-btn-sm" id="wfm-bulk-mkdir-move-btn">${t("modelBulkMoveCreateMove")}</button>
+                <span style="flex:1"></span>
+                <button class="wfm-btn wfm-btn-sm wfm-btn-danger" id="wfm-bulk-delete-btn">${t("modelBulkDelete")}</button>
+            </div>
+        </div>
+    `;
+
+    document.getElementById("wfm-bulk-deselect-all-btn")?.addEventListener("click", clearSelection);
+    document.getElementById("wfm-bulk-select-all-btn")?.addEventListener("click", selectAll);
+    document.getElementById("wfm-bulk-fav-add-btn")?.addEventListener("click", () => bulkSetFavorite(true));
+    document.getElementById("wfm-bulk-fav-remove-btn")?.addEventListener("click", () => bulkSetFavorite(false));
+    document.getElementById("wfm-bulk-add-btn")?.addEventListener("click", () => {
+        const g = document.getElementById("wfm-bulk-group-select")?.value;
+        if (g) bulkAddToGroup(g);
+    });
+    document.getElementById("wfm-bulk-remove-btn")?.addEventListener("click", () => {
+        const g = document.getElementById("wfm-bulk-group-select")?.value;
+        if (g) bulkRemoveFromGroup(g);
+    });
+    document.getElementById("wfm-bulk-create-add-btn")?.addEventListener("click", () => {
+        const input = document.getElementById("wfm-bulk-new-group-input");
+        const name = input?.value.trim();
+        if (!name) return;
+        if (state.modelGroups[name]) { showToast(t("modelsGroupExists"), "warning"); return; }
+        bulkAddToGroup(name);
+    });
+    document.getElementById("wfm-bulk-badge-apply-btn")?.addEventListener("click", () => {
+        const label = document.getElementById("wfm-bulk-badge-select")?.value;
+        if (label) bulkApplyBadge(label, true);
+    });
+    document.getElementById("wfm-bulk-badge-remove-btn")?.addEventListener("click", () => {
+        const label = document.getElementById("wfm-bulk-badge-select")?.value;
+        if (label) bulkApplyBadge(label, false);
+    });
+    document.getElementById("wfm-bulk-move-btn")?.addEventListener("click", () => {
+        const dest = document.getElementById("wfm-bulk-move-select")?.value || "";
+        bulkMoveModels(dest);
+    });
+    document.getElementById("wfm-bulk-mkdir-move-btn")?.addEventListener("click", () => {
+        const input = document.getElementById("wfm-bulk-new-dir-input");
+        const name = input?.value.trim();
+        if (!name) return;
+        bulkMoveModels(name);
+    });
+    document.getElementById("wfm-bulk-delete-btn")?.addEventListener("click", bulkDeleteModels);
+}
+
+export async function bulkAddToGroup(groupName) {
+    const groups = { ...state.modelGroups };
+    if (!groups[groupName]) groups[groupName] = [];
+    const toAdd = [...state.selectedModels].filter((m) => !groups[groupName].includes(m));
+    groups[groupName] = [...groups[groupName], ...toAdd];
+    await saveModelGroups(groups);
+    showToast(`${toAdd.length} ${t("modelBulkAddDone")}`, "success");
+    renderBulkActionBar();
+}
+
+export async function bulkRemoveFromGroup(groupName) {
+    const groups = { ...state.modelGroups };
+    if (!groups[groupName]) return;
+    const before = groups[groupName].length;
+    groups[groupName] = groups[groupName].filter((m) => !state.selectedModels.has(m));
+    const removed = before - groups[groupName].length;
+    // RESERVED_GROUPS (Batch / Stack) は空になってもキーを保持する
+    if (groups[groupName].length === 0 && !RESERVED_GROUPS.includes(groupName)) delete groups[groupName];
+    await saveModelGroups(groups);
+    showToast(`${removed} ${t("modelBulkRemoveDone")}`, "success");
+    renderModelGrid();
+    renderBulkActionBar();
+}
+
+export async function bulkSetFavorite(isFav) {
+    const models = [...state.selectedModels];
+    let count = 0;
+    for (const mn of models) {
+        const meta = state.modelMetadata[mn] || {};
+        if (meta.favorite === isFav) continue;
+        await saveModelMetadata(mn, { favorite: isFav });
+        count++;
+    }
+    if (count > 0) {
+        showToast(`${count} ${isFav ? t("modelBulkFavDone") : t("modelBulkUnfavDone")}`, "success");
+        renderModelGrid();
+    }
+}
+
+export async function bulkApplyBadge(badgeLabel, add) {
+    const models = [...state.selectedModels];
+    let count = 0;
+    for (const mn of models) {
+        const meta = state.modelMetadata[mn] || {};
+        const badges = [...(meta.badges || [])];
+        if (add) {
+            if (badges.includes(badgeLabel)) continue;
+            badges.push(badgeLabel);
+        } else {
+            const idx = badges.indexOf(badgeLabel);
+            if (idx === -1) continue;
+            badges.splice(idx, 1);
+        }
+        await saveModelMetadata(mn, { badges });
+        count++;
+    }
+    if (count > 0) {
+        showToast(`${count} ${add ? t("modelBulkBadgeApplyDone") : t("modelBulkBadgeRemoveDone")}`, "success");
+        renderModelGrid();
+    }
+}
+
+export async function bulkDeleteModels() {
+    const count = state.selectedModels.size;
+    if (count === 0) return;
+    const msg = t("modelBulkDeleteConfirm").replace("{count}", count);
+    if (!window.confirm(msg)) return;
+
+    const model_names = [...state.selectedModels];
+    try {
+        const res = await fetch("/api/wfm/models/delete", {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify({ model_type: state.activeModelType, model_names }),
+        });
+        const data = await res.json();
+        const okCount = (data.ok || []).length;
+        const errCount = (data.errors || []).length;
+        if (errCount > 0) {
+            showToast(`${t("modelBulkDeleteError")}: ${errCount} errors`, "error");
+        }
+        if (okCount > 0) {
+            showToast(`${okCount} ${t("modelBulkDeleteDone")}`, "success");
+            // Remove deleted models from local state
+            model_names.forEach((mn) => {
+                const list = state.modelsByType[state.activeModelType];
+                const idx = list.indexOf(mn);
+                if (idx !== -1) list.splice(idx, 1);
+                delete state.modelMetadata[mn];
+                const ds = state.disabledModels[state.activeModelType];
+                if (ds) ds.delete(mn);
+                state.selectedModels.delete(mn);
+            });
+            state.loaded[state.activeModelType] = false;
+            renderModelGrid();
+            renderBulkActionBar();
+        }
+    } catch (err) {
+        showToast(`${t("modelBulkDeleteError")}: ${err.message}`, "error");
+    }
+}
+
+export async function fetchSubdirs() {
+    try {
+        const res = await fetch(`/api/wfm/models/subdirs?type=${encodeURIComponent(state.activeModelType)}`);
+        state.subdirs = res.ok ? await res.json() : [];
+    } catch { state.subdirs = []; }
+}
+
+export async function bulkMoveModels(destSubdir) {
+    const model_names = [...state.selectedModels];
+    if (model_names.length === 0) return;
+    try {
+        const res = await fetch("/api/wfm/models/move", {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify({ model_type: state.activeModelType, model_names, dest: destSubdir }),
+        });
+        const data = await res.json();
+        const okCount = data.moved?.length || 0;
+        const errCount = data.errors?.length || 0;
+
+        if (okCount > 0) {
+            data.moved.forEach(({ from, to }) => {
+                const list = state.modelsByType[state.activeModelType];
+                const idx = list.indexOf(from);
+                if (idx !== -1) list[idx] = to;
+                if (state.modelMetadata[from]) {
+                    state.modelMetadata[to] = state.modelMetadata[from];
+                    delete state.modelMetadata[from];
+                }
+                const ds = state.disabledModels[state.activeModelType];
+                if (ds && ds.has(from)) { ds.delete(from); ds.add(to); }
+                state.selectedModels.delete(from);
+                for (const members of Object.values(state.modelGroups)) {
+                    const gi = members.indexOf(from);
+                    if (gi !== -1) members[gi] = to;
+                }
+            });
+            if (state.selectedModel && data.moved.some((m) => m.from === state.selectedModel)) {
+                state.selectedModel = null;
+                const titleEl = document.getElementById("wfm-models-panel-title");
+                if (titleEl) titleEl.textContent = "";
+            }
+            showToast(`${okCount} ${t("modelBulkMoveDone")}`, "success");
+            await fetchSubdirs();
+            renderDirFilter();
+            renderModelGrid();
+            renderBulkActionBar();
+        }
+        if (errCount > 0) {
+            showToast(`${t("modelBulkMoveError")}: ${data.errors[0].error}`, "error");
+        }
+    } catch (err) {
+        showToast(`${t("modelBulkMoveError")}: ${err.message}`, "error");
+    }
+}
@@ -0,0 +1,82 @@
+/**
+ * Models Tab - Shared state and static lookup tables
+ * `state` is a `const` object never reassigned — modules read/write its
+ * properties directly, which stays within ESM's read-only binding rule
+ * (only the binding itself, not the object it points to, is immutable).
+ */
+
+import { comfyUI } from "../comfyui-client.js";
+
+export const RESERVED_GROUPS = ["Batch", "Stack"];
+export const BATCH_MODEL_TYPES = ["checkpoint", "lora"];
+export const STACK_MODEL_TYPES = ["lora"];
+
+export const state = {
+    modelsByType: {
+        checkpoint: [],
+        lora: [],
+        vae: [],
+        controlnet: [],
+        unet: [],
+        textencoder: [],
+        hypernetwork: [],
+        embedding: [],
+    },
+    modelMetadata: {},
+    modelGroups: {},
+    allModelGroups: {},  // { type: { groupName: [models] } } — all types
+    civitaiCache: {},
+    disabledModels: {},   // { type: Set<modelName> }
+    subdirs: [],
+    selectMode: false,
+    selectedModels: new Set(),
+    searchText: "",
+    tagFilter: "",
+    badgeFilter: "",
+    dirFilter: "",
+    groupFilter: "",
+    statusFilter: "all",  // "all" | "enabled" | "disabled"
+    showFavoritesOnly: false,
+    showBatchOnly: false,
+    viewMode: localStorage.getItem("wfm_models_view") === "table" ? "table" : "thumb",
+    activeModelType: "checkpoint",
+    selectedModel: null,
+    loaded: {},
+    currentPage: 0,
+    sortColumn: null,  // "fav" | "filename" | "subdir" | "civtype" | "basemodel" | "ext" | "tags" | "memo" | "enabled"
+    sortDir: "asc",    // "asc" | "desc"
+};
+
+
+export const FETCH_MAP = {
+    checkpoint: () => comfyUI.fetchCheckpoints(),
+    lora: () => comfyUI.fetchLoras(),
+    vae: () => comfyUI.fetchVaes(),
+    controlnet: () => comfyUI.fetchControlNets(),
+    unet: () => comfyUI.fetchDiffusionModels(),
+    textencoder: () => comfyUI.fetchTextEncoders(),
+    hypernetwork: () => comfyUI.fetchHypernetworks(),
+    embedding: () => comfyUI.fetchEmbeddings(),
+};
+
+export const TYPE_LABELS = {
+    checkpoint: "Checkpoint",
+    lora: "LoRA",
+    vae: "VAE",
+    controlnet: "ControlNet",
+    unet: "UNET",
+    textencoder: "TextEncoder",
+    hypernetwork: "Hypernetwork",
+    embedding: "Embedding",
+};
+
+// Mapping from models-tab type → comfyui-editor key + inputKey
+export const GENUI_TYPE_MAP = {
+    checkpoint:   { key: "checkpoints",    inputKey: "ckpt_name" },
+    lora:         { key: "loras",          inputKey: "lora_name" },
+    vae:          { key: "vaes",           inputKey: "vae_name" },
+    controlnet:   { key: "controlNets",    inputKey: "control_net_name" },
+    unet:         { key: "diffusionModels",inputKey: "unet_name" },
+    textencoder:  { key: "textEncoders",   inputKey: "clip_name1" },
+    hypernetwork: { key: "hypernetworks",  inputKey: "hypernetwork_name" },
+};
@@ -0,0 +1,359 @@
+/**
+ * Prompt Tab - AI Assistant (Ollama / LM Studio / Lemonade / Unsloth chat, translate, apply to GenerateUI)
+ */
+
+import { showToast } from "./app.js";
+import { t } from "./i18n.js";
+import { unslothProxy } from "./util.js";
+import { openAiBackendSettingsModal, getAiBackendConfig } from "./ai-settings-modal.js";
+
+// ============================================
+// State
+// ============================================
+
+const ollamaState = {
+    chatHistory: [],
+    attachedImage: null,
+};
+
+const PROMPT_AI_KEY = "wfm_prompt_ai_settings";
+
+export function getPromptAiConfig() {
+    return getAiBackendConfig(PROMPT_AI_KEY);
+}
+
+// Ollama-style messages (with .images) → OpenAI互換 content 配列に変換
+function _toOpenAiMessages(messages) {
+    return messages.map(msg => {
+        if (msg.images?.length) {
+            return {
+                role: msg.role,
+                content: [
+                    { type: "text", text: msg.content },
+                    ...msg.images.map(b64 => ({ type: "image_url", image_url: { url: `data:image/jpeg;base64,${b64}` } })),
+                ],
+            };
+        }
+        return { role: msg.role, content: msg.content };
+    });
+}
+
+function _stripThinkingTags(text) {
+    return (text || "")
+        .replace(/<think>[\s\S]*?<\/think>/gi, "")
+        .replace(/<thinking>[\s\S]*?<\/thinking>/gi, "")
+        .trim();
+}
+
+// Ollamaは `think` (bool) と `options.num_predict`、OpenAI互換は `max_tokens` で制御
+function _applyGenOptions(body, backend, cfg) {
+    if (backend === "ollama") {
+        body.think = !!cfg.thinkingMode;
+        if (cfg.maxTokens > 0) body.options = { ...(body.options || {}), num_predict: cfg.maxTokens };
+    } else if (cfg.maxTokens > 0) {
+        body.max_tokens = cfg.maxTokens;
+    }
+    return body;
+}
+
+async function chatWithAi(model, messages) {
+    const cfg = getPromptAiConfig();
+    const { backend, url } = cfg;
+    if (backend === "ollama") {
+        const res = await fetch(`${url}/api/chat`, {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify(_applyGenOptions({ model, messages, stream: false }, backend, cfg)),
+        });
+        if (!res.ok) throw new Error(`HTTP ${res.status}`);
+        const text = (await res.json()).message?.content || "";
+        return cfg.thinkingMode ? text : _stripThinkingTags(text);
+    } else if (backend === "unsloth") {
+        const body = _applyGenOptions({ model, messages: _toOpenAiMessages(messages), stream: false }, backend, cfg);
+        const data = await unslothProxy(url, "/v1/chat/completions", "POST", body);
+        const msg = data.choices?.[0]?.message;
+        // Unslothはreasoningを別フィールドで返すため<think>タグに畳んで表示に混ぜる
+        const text = (msg?.reasoning_content ? `<think>${msg.reasoning_content}</think>` : "") + (msg?.content || "");
+        return cfg.thinkingMode ? text : _stripThinkingTags(text);
+    } else {
+        // LM Studio / Lemonade (OpenAI-compatible)
+        const res = await fetch(`${url}/v1/chat/completions`, {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify(_applyGenOptions({ model, messages: _toOpenAiMessages(messages), stream: false }, backend, cfg)),
+        });
+        if (!res.ok) throw new Error(`HTTP ${res.status}`);
+        const text = (await res.json()).choices?.[0]?.message?.content || "";
+        return cfg.thinkingMode ? text : _stripThinkingTags(text);
+    }
+}
+
+// ============================================
+// Chat UI
+// ============================================
+
+function addChatMessage(role, content) {
+    const chat = document.getElementById("wfm-ollama-chat");
+    if (!chat) return;
+
+    const welcome = chat.querySelector(".wfm-ollama-welcome");
+    if (welcome) welcome.remove();
+
+    const msg = document.createElement("div");
+    msg.className = `wfm-ollama-msg ${role}`;
+
+    const roleLabel = document.createElement("div");
+    roleLabel.className = "wfm-ollama-msg-role";
+    roleLabel.textContent = role === "user" ? t("you") : "AI";
+    msg.appendChild(roleLabel);
+
+    const contentDiv = document.createElement("div");
+    contentDiv.className = "wfm-ollama-msg-content";
+    contentDiv.textContent = content;
+    msg.appendChild(contentDiv);
+
+    // Apply button for assistant messages
+    if (role === "assistant") {
+        const applyRow = document.createElement("div");
+        applyRow.className = "wfm-ollama-apply-row";
+
+        const applyBtn = document.createElement("button");
+        applyBtn.className = "wfm-btn wfm-btn-sm wfm-btn-primary";
+        applyBtn.textContent = t("applyToGenerateUI");
+        applyBtn.addEventListener("click", () => applyToGenerateUI(content));
+        applyRow.appendChild(applyBtn);
+
+        const copyBtn = document.createElement("button");
+        copyBtn.className = "wfm-btn wfm-btn-sm";
+        copyBtn.textContent = t("copy");
+        copyBtn.addEventListener("click", () => {
+            navigator.clipboard.writeText(content).then(() => {
+                copyBtn.textContent = t("copied");
+                setTimeout(() => { copyBtn.textContent = t("copy"); }, 1500);
+            });
+        });
+        applyRow.appendChild(copyBtn);
+
+        msg.appendChild(applyRow);
+    }
+
+    chat.appendChild(msg);
+    chat.scrollTop = chat.scrollHeight;
+}
+
+function clearChat() {
+    ollamaState.chatHistory = [];
+    ollamaState.attachedImage = null;
+    updateAttachmentDisplay();
+
+    const chat = document.getElementById("wfm-ollama-chat");
+    if (chat) {
+        chat.innerHTML = `
+            <div class="wfm-ollama-welcome">
+                <p>AI Assistant</p>
+                <p>${t("assistantWelcome")}</p>
+            </div>
+        `;
+    }
+}
+
+// ============================================
+// Image Attachment
+// ============================================
+
+function attachFile(file) {
+    if (!file) return;
+    const reader = new FileReader();
+    reader.onload = (e) => {
+        ollamaState.attachedImage = { name: file.name, dataUrl: e.target.result };
+        updateAttachmentDisplay();
+    };
+    reader.readAsDataURL(file);
+}
+
+function updateAttachmentDisplay() {
+    const container = document.getElementById("wfm-ollama-attachments");
+    if (!container) return;
+    container.innerHTML = "";
+
+    if (!ollamaState.attachedImage) return;
+
+    const item = document.createElement("div");
+    item.className = "wfm-ollama-attachment";
+
+    const img = document.createElement("img");
+    img.src = ollamaState.attachedImage.dataUrl;
+    item.appendChild(img);
+
+    const name = document.createElement("span");
+    name.className = "wfm-ollama-attachment-name";
+    name.textContent = ollamaState.attachedImage.name;
+    item.appendChild(name);
+
+    const removeBtn = document.createElement("button");
+    removeBtn.className = "wfm-ollama-attachment-remove";
+    removeBtn.textContent = "×";
+    removeBtn.addEventListener("click", () => {
+        ollamaState.attachedImage = null;
+        updateAttachmentDisplay();
+    });
+    item.appendChild(removeBtn);
+
+    container.appendChild(item);
+}
+
+// ============================================
+// Status label (設定モーダルで選択中のbackend/modelを表示)
+// ============================================
+
+function _updateStatusLabel() {
+    const status = document.getElementById("wfm-ollama-status");
+    if (!status) return;
+    const { backend, model } = getPromptAiConfig();
+    status.textContent = model ? `${backend}: ${model}` : `${backend}: ${t("selectModelFirst")}`;
+    status.className = model ? "wfm-ollama-status connected" : "wfm-ollama-status error";
+}
+
+// ============================================
+// Send Message
+// ============================================
+
+async function sendMessage() {
+    const input = document.getElementById("wfm-ollama-input");
+    if (!input) return;
+
+    const message = input.value.trim();
+    if (!message) return;
+
+    const { model } = getPromptAiConfig();
+    if (!model) {
+        showToast(t("selectModelFirst"), "error");
+        return;
+    }
+
+    addChatMessage("user", message);
+    input.value = "";
+
+    const userMsg = { role: "user", content: message };
+    if (ollamaState.attachedImage) {
+        userMsg.images = [ollamaState.attachedImage.dataUrl.split(",")[1]];
+    }
+    ollamaState.chatHistory.push(userMsg);
+
+    const sendBtn = document.getElementById("wfm-ollama-send-btn");
+    if (sendBtn) sendBtn.disabled = true;
+
+    try {
+        const reply = await chatWithAi(model, ollamaState.chatHistory);
+        addChatMessage("assistant", reply);
+        ollamaState.chatHistory.push({ role: "assistant", content: reply });
+        ollamaState.attachedImage = null;
+        updateAttachmentDisplay();
+    } catch (err) {
+        showToast(t("error") + ": " + err.message, "error");
+    } finally {
+        if (sendBtn) sendBtn.disabled = false;
+    }
+}
+
+// ============================================
+// Translation
+// ============================================
+
+async function sendTranslate(direction) {
+    const input = document.getElementById("wfm-ollama-input");
+    if (!input) return;
+
+    const text = input.value.trim();
+    if (!text) return;
+
+    const { model } = getPromptAiConfig();
+    if (!model) {
+        showToast(t("selectModelFirst"), "error");
+        return;
+    }
+
+    const labels = { ja2en: "JA→EN", en2ja: "EN→JA", zh2en: "ZH→EN", en2zh: "EN→ZH" };
+    addChatMessage("user", `[${labels[direction] || direction}]\n${text}`);
+    input.value = "";
+
+    const btns = ["wfm-ollama-send-btn", "wfm-ollama-ja2en-btn", "wfm-ollama-en2ja-btn", "wfm-ollama-zh2en-btn", "wfm-ollama-en2zh-btn"]
+        .map((id) => document.getElementById(id));
+    btns.forEach((b) => { if (b) b.disabled = true; });
+
+    try {
+        const prompts = {
+            ja2en: `Translate the following Japanese text into English. Output only the translated text, nothing else.\n\n${text}`,
+            en2ja: `以下の英語のテキストを日本語に翻訳してください。翻訳結果のみを出力し、他の説明は不要です。\n\n${text}`,
+            zh2en: `Translate the following Chinese text into English. Output only the translated text, nothing else.\n\n${text}`,
+            en2zh: `请将以下英文翻译成中文。只输出翻译结果，不需要其他说明。\n\n${text}`,
+        };
+        const prompt = prompts[direction];
+
+        const reply = await chatWithAi(model, [{ role: "user", content: prompt }]);
+        addChatMessage("assistant", reply);
+    } catch (err) {
+        showToast(t("error") + ": " + err.message, "error");
+    } finally {
+        btns.forEach((b) => { if (b) b.disabled = false; });
+    }
+}
+
+// ============================================
+// Apply to GenerateUI
+// ============================================
+
+function applyToGenerateUI(text) {
+    const textareas = document.querySelectorAll("#wfm-gen-prompt-fields textarea");
+    if (textareas.length === 0) {
+        showToast(t("noPromptFields"), "error");
+        return;
+    }
+    textareas[0].value = text;
+    textareas[0].dispatchEvent(new Event("input", { bubbles: true }));
+    textareas[0].dispatchEvent(new Event("change", { bubbles: true }));
+    showToast(t("appliedToGenerateUI"), "success");
+}
+
+// ============================================
+// UI wiring (called from prompt-tab.js's initPromptTab)
+// ============================================
+
+export function initAiChatUI() {
+    _updateStatusLabel();
+
+    // Settings modal
+    document.getElementById("wfm-ollama-settings-btn")?.addEventListener("click", () => {
+        openAiBackendSettingsModal(PROMPT_AI_KEY, t("settings"), _updateStatusLabel);
+    });
+
+    // Send message
+    document.getElementById("wfm-ollama-send-btn")?.addEventListener("click", sendMessage);
+
+    // Enter to send
+    document.getElementById("wfm-ollama-input")?.addEventListener("keydown", (e) => {
+        if (e.key === "Enter" && !e.shiftKey) {
+            e.preventDefault();
+            sendMessage();
+        }
+    });
+
+    // Clear chat
+    document.getElementById("wfm-ollama-clear-btn")?.addEventListener("click", clearChat);
+
+    // File attachment
+    const fileInput = document.getElementById("wfm-ollama-file-input");
+    document.getElementById("wfm-ollama-attach-btn")?.addEventListener("click", () => fileInput?.click());
+    fileInput?.addEventListener("change", () => {
+        if (fileInput.files.length > 0) {
+            attachFile(fileInput.files[0]);
+            fileInput.value = "";
+        }
+    });
+
+    // Translation
+    document.getElementById("wfm-ollama-ja2en-btn")?.addEventListener("click", () => sendTranslate("ja2en"));
+    document.getElementById("wfm-ollama-en2ja-btn")?.addEventListener("click", () => sendTranslate("en2ja"));
+    document.getElementById("wfm-ollama-zh2en-btn")?.addEventListener("click", () => sendTranslate("zh2en"));
+    document.getElementById("wfm-ollama-en2zh-btn")?.addEventListener("click", () => sendTranslate("en2zh"));
+}
@@ -0,0 +1,567 @@
+/**
+ * Prompt Tab - Presets (API CRUD, groups, Preset Manager panel)
+ */
+
+import { showToast } from "./app.js";
+import { t } from "./i18n.js";
+import { readJsonStorage } from "./util.js";
+
+// ============================================
+// State
+// ============================================
+
+// Preset data (loaded from API, with localStorage migration)
+let promptPresets = [];
+let pmActiveTab = "all";       // "all" | "favorites" | "groups"
+let pmSearchText = "";
+let pmSelectedId = null;       // currently selected preset id
+export let pmGroups = {};      // { groupName: [presetId, ...] }
+const PM_GROUPS_KEY = "wfm_prompt_preset_groups";
+export const PROMPT_RESERVED_GROUPS = ["Batch"];
+
+// ============================================
+// Preset API helpers
+// ============================================
+
+export async function fetchPresets() {
+    try {
+        const res = await fetch("/api/wfm/prompts");
+        return res.ok ? await res.json() : [];
+    } catch { return []; }
+}
+
+export async function apiCreatePreset(data) {
+    try {
+        const res = await fetch("/api/wfm/prompts", {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify(data),
+        });
+        const result = await res.json();
+        return result.status === "ok" ? result.prompt : null;
+    } catch { return null; }
+}
+
+export async function apiUpdatePreset(id, updates) {
+    try {
+        const res = await fetch("/api/wfm/prompts/update", {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify({ id, ...updates }),
+        });
+        const result = await res.json();
+        return result.status === "ok" ? result.prompt : null;
+    } catch { return null; }
+}
+
+export async function apiDeletePreset(id) {
+    try {
+        await fetch("/api/wfm/prompts/delete", {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify({ id }),
+        });
+    } catch { /* ignore */ }
+}
+
+// ============================================
+// Migrate localStorage presets to API
+// ============================================
+
+const PRESETS_KEY = "wfm_prompt_presets";
+
+async function migrateLocalStoragePresets() {
+    try {
+        const raw = localStorage.getItem(PRESETS_KEY);
+        if (!raw) return;
+        const local = JSON.parse(raw);
+        if (!Array.isArray(local) || local.length === 0) return;
+
+        // Only migrate if API has no presets yet
+        const existing = await fetchPresets();
+        if (existing.length > 0) {
+            localStorage.removeItem(PRESETS_KEY);
+            return;
+        }
+
+        for (const p of local) {
+            await apiCreatePreset({
+                name: p.name || "Untitled",
+                text: p.posText || p.text || "",
+                negText: p.negText || "",
+                category: "",
+                tags: [],
+                favorite: false,
+            });
+        }
+        localStorage.removeItem(PRESETS_KEY);
+    } catch { /* ignore migration errors */ }
+}
+
+// ============================================
+// Preset data management
+// ============================================
+
+export async function loadAllPresets() {
+    await migrateLocalStoragePresets();
+    promptPresets = await fetchPresets();
+
+    // Load groups from localStorage
+    pmGroups = readJsonStorage(PM_GROUPS_KEY);
+
+    // Clean stale entries from groups (preserve reserved groups even if empty)
+    const validIds = new Set(promptPresets.map(p => p.id));
+    for (const g of Object.keys(pmGroups)) {
+        pmGroups[g] = (pmGroups[g] || []).filter(id => validIds.has(id));
+        if (pmGroups[g].length === 0 && !PROMPT_RESERVED_GROUPS.includes(g)) delete pmGroups[g];
+    }
+    // Ensure reserved groups always exist
+    for (const g of PROMPT_RESERVED_GROUPS) {
+        if (!pmGroups[g]) pmGroups[g] = [];
+    }
+    saveGroups();
+
+    renderPresetSelect();
+    renderGroupSelect();
+    renderPresetManager();
+}
+
+export function saveGroups() {
+    localStorage.setItem(PM_GROUPS_KEY, JSON.stringify(pmGroups));
+    renderGroupSelect();
+}
+
+function renderGroupSelect() {
+    const select = document.getElementById("wfm-preset-group-select");
+    if (!select) return;
+    const prevVal = select.value;
+    select.innerHTML = `<option value="">Select group...</option>`;
+    for (const g of Object.keys(pmGroups).sort()) {
+        const opt = document.createElement("option");
+        opt.value = g;
+        opt.textContent = g;
+        select.appendChild(opt);
+    }
+    if (prevVal && pmGroups[prevVal]) select.value = prevVal;
+}
+
+function renderPresetSelect() {
+    const select = document.getElementById("wfm-preset-select");
+    if (!select) return;
+    const prevVal = select.value;
+    select.innerHTML = `<option value="">${t("newPreset")}</option>`;
+    promptPresets.forEach((p) => {
+        const opt = document.createElement("option");
+        opt.value = p.id;
+        opt.textContent = p.name;
+        select.appendChild(opt);
+    });
+    // Restore selection if still valid
+    if (prevVal && promptPresets.find(p => p.id === prevVal)) {
+        select.value = prevVal;
+    }
+}
+
+function selectPresetInEditor(preset) {
+    const presetSelect = document.getElementById("wfm-preset-select");
+    const presetName = document.getElementById("wfm-preset-name");
+    const presetCategory = document.getElementById("wfm-preset-category");
+    const presetPos = document.getElementById("wfm-preset-pos");
+    const presetNeg = document.getElementById("wfm-preset-neg");
+
+    if (presetSelect) presetSelect.value = preset ? preset.id : "";
+    if (presetName) presetName.value = preset ? preset.name : "";
+    if (presetCategory) presetCategory.value = preset ? (preset.category || "") : "";
+    if (presetPos) presetPos.value = preset ? (preset.text || preset.posText || "") : "";
+    if (presetNeg) presetNeg.value = preset ? (preset.negText || "") : "";
+
+    pmSelectedId = preset ? preset.id : null;
+    renderPresetManager();
+}
+
+// ============================================
+// Preset Manager rendering
+// ============================================
+
+export function esc(s) {
+    return s ? String(s).replace(/&/g, "&amp;").replace(/</g, "&lt;").replace(/>/g, "&gt;") : "";
+}
+
+export function renderPresetManager() {
+    const container = document.getElementById("wfm-pm-list");
+    if (!container) return;
+    container.innerHTML = "";
+
+    switch (pmActiveTab) {
+        case "all": renderPmAll(container); break;
+        case "favorites": renderPmFavorites(container); break;
+        case "groups": renderPmGroups(container); break;
+    }
+}
+
+function matchesSearch(p) {
+    if (!pmSearchText) return true;
+    const s = pmSearchText.toLowerCase();
+    return (p.name || "").toLowerCase().includes(s) ||
+           (p.text || "").toLowerCase().includes(s) ||
+           (p.category || "").toLowerCase().includes(s) ||
+           (p.tags || []).some(t => t.toLowerCase().includes(s));
+}
+
+// Ordered list of actual preset objects for a group (stale ids already filtered out by
+// loadAllPresets, but this is defensive for callers that read pmGroups directly too).
+export function getPresetsInGroup(groupName) {
+    const ids = pmGroups[groupName] || [];
+    return ids.map(id => promptPresets.find(p => p.id === id)).filter(Boolean);
+}
+
+export function isInBatchPreset(id) {
+    return (pmGroups["Batch"] || []).includes(id);
+}
+
+export function toggleBatchPreset(id) {
+    const batch = pmGroups["Batch"] || [];
+    const idx = batch.indexOf(id);
+    if (idx >= 0) { batch.splice(idx, 1); } else { batch.push(id); }
+    pmGroups["Batch"] = batch;
+    saveGroups();
+}
+
+export function clearBatchPresets() {
+    pmGroups["Batch"] = [];
+    saveGroups();
+    renderPresetManager();
+    showToast(t("promptBatchClear"), "success");
+}
+
+function createPmItem(preset) {
+    const el = document.createElement("div");
+    el.className = "wfm-pm-item" + (pmSelectedId === preset.id ? " active" : "");
+
+    const previewText = (preset.text || "").length > 50
+        ? preset.text.substring(0, 50) + "..."
+        : (preset.text || "");
+
+    const catBadge = preset.category
+        ? `<span style="font-size:9px;color:var(--wfm-primary);margin-left:4px;">[${esc(preset.category)}]</span>`
+        : "";
+
+    const inBatch = isInBatchPreset(preset.id);
+
+    el.innerHTML = `
+        <div class="wfm-pm-item-body">
+            <div class="wfm-pm-item-name">${preset.favorite ? '<span style="color:#ffd700;">&#9733;</span> ' : ""}${esc(preset.name)}${catBadge}</div>
+            <div class="wfm-pm-item-sub">${esc(previewText)}</div>
+        </div>
+        <div class="wfm-pm-item-actions">
+            <button class="wfm-pm-action-btn pm-batch-btn${inBatch ? " batch-active" : ""}" title="Batch">B</button>
+            <button class="wfm-pm-action-btn pm-fav-btn${preset.favorite ? " fav-active" : ""}" title="Favorite">&#9733;</button>
+            <button class="wfm-pm-action-btn pm-del-btn" title="Delete" style="color:var(--wfm-danger);">&#10005;</button>
+        </div>
+    `;
+
+    // Click to select in editor
+    el.addEventListener("click", (e) => {
+        if (e.target.closest(".wfm-pm-item-actions")) return;
+        selectPresetInEditor(preset);
+    });
+
+    // Batch toggle
+    el.querySelector(".pm-batch-btn").addEventListener("click", (e) => {
+        e.stopPropagation();
+        toggleBatchPreset(preset.id);
+        renderPresetManager();
+    });
+
+    // Favorite toggle
+    el.querySelector(".pm-fav-btn").addEventListener("click", async (e) => {
+        e.stopPropagation();
+        const updated = await apiUpdatePreset(preset.id, { favorite: !preset.favorite });
+        if (updated) {
+            const idx = promptPresets.findIndex(p => p.id === preset.id);
+            if (idx >= 0) promptPresets[idx] = updated;
+            renderPresetManager();
+        }
+    });
+
+    // Delete
+    el.querySelector(".pm-del-btn").addEventListener("click", async (e) => {
+        e.stopPropagation();
+        if (!confirm(`Delete "${preset.name}"?`)) return;
+        await apiDeletePreset(preset.id);
+        promptPresets = promptPresets.filter(p => p.id !== preset.id);
+        if (pmSelectedId === preset.id) {
+            pmSelectedId = null;
+            selectPresetInEditor(null);
+        }
+        renderPresetSelect();
+        renderPresetManager();
+        showToast(t("deleted"), "success");
+    });
+
+    return el;
+}
+
+function renderPmAll(container) {
+    const items = promptPresets.filter(matchesSearch);
+    if (items.length === 0) {
+        container.innerHTML = `<div class="wfm-pm-empty">${promptPresets.length === 0 ? "No presets yet.<br><small>Create one in the Presets panel</small>" : "No matches"}</div>`;
+        return;
+    }
+    for (const p of items) {
+        container.appendChild(createPmItem(p));
+    }
+}
+
+function renderPmFavorites(container) {
+    const favs = promptPresets.filter(p => p.favorite);
+    const items = favs.filter(matchesSearch);
+    if (items.length === 0) {
+        container.innerHTML = `<div class="wfm-pm-empty">${favs.length === 0 ? "No favorites yet.<br><small>Star presets to add them here</small>" : "No matches"}</div>`;
+        return;
+    }
+    for (const p of items) {
+        container.appendChild(createPmItem(p));
+    }
+}
+
+function renderPmGroups(container) {
+    const groupNames = Object.keys(pmGroups).sort();
+
+    if (groupNames.length === 0) {
+        container.innerHTML = `<div class="wfm-pm-empty">No groups yet.<br><small>Create groups from the Presets panel below</small></div>`;
+        return;
+    }
+
+    for (const groupName of groupNames) {
+        const ids = pmGroups[groupName] || [];
+        const presets = ids.map(id => promptPresets.find(p => p.id === id)).filter(Boolean);
+
+        const section = document.createElement("div");
+
+        const header = document.createElement("div");
+        header.className = "wfm-pm-group-header collapsed";
+        header.innerHTML = `<span>${esc(groupName)}</span> <span class="wfm-pm-badge">${presets.length}</span>`;
+
+        const list = document.createElement("div");
+        list.style.display = "none";
+
+        header.addEventListener("click", () => {
+            list.style.display = list.style.display === "none" ? "block" : "none";
+            header.classList.toggle("collapsed");
+        });
+
+        for (const p of presets) {
+            const item = createPmItem(p);
+            // Add remove-from-group button
+            const removeBtn = document.createElement("button");
+            removeBtn.className = "wfm-pm-action-btn";
+            removeBtn.title = "Remove from group";
+            removeBtn.textContent = "➖";
+            removeBtn.style.fontSize = "10px";
+            removeBtn.addEventListener("click", (e) => {
+                e.stopPropagation();
+                pmGroups[groupName] = pmGroups[groupName].filter(id => id !== p.id);
+                // 予約グループ (Batch) は空になってもキーを保持する
+                if (pmGroups[groupName].length === 0 && !PROMPT_RESERVED_GROUPS.includes(groupName)) delete pmGroups[groupName];
+                saveGroups();
+                renderPresetManager();
+            });
+            item.querySelector(".wfm-pm-item-actions").prepend(removeBtn);
+            list.appendChild(item);
+        }
+        section.appendChild(header);
+        section.appendChild(list);
+        container.appendChild(section);
+    }
+}
+
+// ============================================
+// UI wiring (called from prompt-tab.js's initPromptTab)
+// ============================================
+
+export function initPresetsUI() {
+    loadAllPresets();
+
+    const presetSelect = document.getElementById("wfm-preset-select");
+    const presetName = document.getElementById("wfm-preset-name");
+    const presetCategory = document.getElementById("wfm-preset-category");
+    const presetPos = document.getElementById("wfm-preset-pos");
+    const presetNeg = document.getElementById("wfm-preset-neg");
+
+    // Load preset on selection
+    presetSelect?.addEventListener("change", () => {
+        const id = presetSelect.value;
+        const p = promptPresets.find(pp => pp.id === id);
+        selectPresetInEditor(p || null);
+    });
+
+    // Copy positive prompt to clipboard
+    document.getElementById("wfm-preset-copy-pos-btn")?.addEventListener("click", () => {
+        const text = presetPos?.value || "";
+        if (!text.trim()) {
+            showToast(t("noTextToCopy"), "error");
+            return;
+        }
+        navigator.clipboard.writeText(text).then(() => {
+            showToast(t("copiedToClipboard"), "success");
+        });
+    });
+
+    // Copy negative prompt to clipboard
+    document.getElementById("wfm-preset-copy-neg-btn")?.addEventListener("click", () => {
+        const text = presetNeg?.value || "";
+        if (!text.trim()) {
+            showToast(t("noTextToCopy"), "error");
+            return;
+        }
+        navigator.clipboard.writeText(text).then(() => {
+            showToast(t("copiedToClipboard"), "success");
+        });
+    });
+
+    // Save preset (create or update via API)
+    document.getElementById("wfm-preset-save-btn")?.addEventListener("click", async () => {
+        const name = presetName?.value.trim();
+        const category = presetCategory?.value.trim() || "";
+        const pos = presetPos?.value || "";
+        const neg = presetNeg?.value || "";
+
+        if (!name) {
+            showToast(t("enterPresetName"), "error");
+            return;
+        }
+        if (!pos.trim() && !neg.trim()) {
+            showToast(t("noPromptToSave"), "error");
+            return;
+        }
+
+        const selectedId = presetSelect?.value;
+        const existing = selectedId ? promptPresets.find(p => p.id === selectedId) : null;
+
+        if (existing) {
+            // Update
+            const updated = await apiUpdatePreset(existing.id, {
+                name, text: pos, negText: neg, category,
+            });
+            if (updated) {
+                const idx = promptPresets.findIndex(p => p.id === existing.id);
+                if (idx >= 0) promptPresets[idx] = updated;
+                showToast(t("presetSaved"), "success");
+            }
+        } else {
+            // Create
+            const created = await apiCreatePreset({
+                name, text: pos, negText: neg, category,
+                tags: [], favorite: false,
+            });
+            if (created) {
+                promptPresets.push(created);
+                showToast(t("presetSaved"), "success");
+            }
+        }
+
+        pmSelectedId = null;
+        renderPresetSelect();
+        renderPresetManager();
+        if (presetSelect) presetSelect.value = "";
+    });
+
+    // Apply preset to GenerateUI
+    document.getElementById("wfm-preset-apply-btn")?.addEventListener("click", () => {
+        const pos = presetPos?.value || "";
+        const neg = presetNeg?.value || "";
+        const textareas = document.querySelectorAll("#wfm-gen-prompt-fields textarea");
+        if (textareas.length === 0) {
+            showToast(t("noPromptFields"), "error");
+            return;
+        }
+        let applied = false;
+        if (textareas.length > 0 && pos) {
+            textareas[0].value = pos;
+            textareas[0].dispatchEvent(new Event("input", { bubbles: true }));
+            applied = true;
+        }
+        if (textareas.length > 1 && neg) {
+            textareas[1].value = neg;
+            textareas[1].dispatchEvent(new Event("input", { bubbles: true }));
+            applied = true;
+        }
+        if (applied) showToast(t("appliedToGenerateUI"), "success");
+    });
+
+    // --- Group management (Presets side) ---
+    document.getElementById("wfm-preset-new-group-btn")?.addEventListener("click", () => {
+        const name = prompt("Group name:");
+        if (!name || !name.trim()) return;
+        const key = name.trim();
+        if (pmGroups[key]) {
+            showToast(t("groupExists"), "error");
+            return;
+        }
+        pmGroups[key] = [];
+        saveGroups();
+        renderPresetManager();
+        showToast(t("groupCreated", key), "success");
+    });
+
+    document.getElementById("wfm-preset-add-to-group-btn")?.addEventListener("click", () => {
+        const groupSelect = document.getElementById("wfm-preset-group-select");
+        const groupName = groupSelect?.value;
+        if (!groupName) {
+            showToast(t("selectGroupFirst"), "error");
+            return;
+        }
+        const id = presetSelect?.value;
+        if (!id) {
+            showToast(t("selectPresetFirst"), "error");
+            return;
+        }
+        if (!pmGroups[groupName]) pmGroups[groupName] = [];
+        if (pmGroups[groupName].includes(id)) {
+            showToast(t("alreadyInGroup"), "info");
+            return;
+        }
+        pmGroups[groupName].push(id);
+        saveGroups();
+        renderPresetManager();
+        showToast(t("addedToGroup"), "success");
+    });
+
+    document.getElementById("wfm-preset-del-group-btn")?.addEventListener("click", () => {
+        const groupSelect = document.getElementById("wfm-preset-group-select");
+        const groupName = groupSelect?.value;
+        if (!groupName) {
+            showToast(t("selectGroupFirst"), "error");
+            return;
+        }
+        if (PROMPT_RESERVED_GROUPS.includes(groupName)) {
+            showToast(t("modelsGroupReserved"), "warning");
+            return;
+        }
+        if (!confirm(`Delete group "${groupName}"?`)) return;
+        delete pmGroups[groupName];
+        saveGroups();
+        renderPresetManager();
+        showToast(t("groupDeleted", groupName), "success");
+    });
+
+    // --- Preset Manager ---
+    document.querySelectorAll(".wfm-pm-tab").forEach(btn => {
+        btn.addEventListener("click", () => {
+            pmActiveTab = btn.dataset.pmtab;
+            document.querySelectorAll(".wfm-pm-tab").forEach(b => b.classList.remove("active"));
+            btn.classList.add("active");
+            renderPresetManager();
+        });
+    });
+
+    document.getElementById("wfm-pm-search-input")?.addEventListener("input", (e) => {
+        pmSearchText = e.target.value.trim();
+        renderPresetManager();
+    });
+
+    document.getElementById("wfm-pm-batch-clear-btn")?.addEventListener("click", () => {
+        clearBatchPresets();
+    });
+}
@@ -0,0 +1,220 @@
+/**
+ * Prompt Tab - Style manager (Col3 "Style" タブ)
+ */
+// Wildcardファイルマネージャーと同じCRUDパターン（一覧→エディタ→保存/削除/キャンセル）。
+// 保存・削除後は generate-tab.js の refreshStylesList() を呼び、GenerateUIのStyleドロップダウンや
+// Batchタブのチェックリストを再読み込み無しで最新状態へ同期する。
+
+import { showToast } from "./app.js";
+import { t } from "./i18n.js";
+import { setupSearchClearBtn } from "./util.js";
+import { refreshStylesList } from "./generate-tab.js";
+import { esc } from "./prompt-presets.js";
+
+let styleListData = [];
+let styleSearchText = "";
+let styleEditingOriginalName = null; // null = 新規作成
+let styleEditingFile = null;         // 編集中/追加先スタイルの定義元ファイル名（style/配下、null = デフォルトのcustom.json）
+
+export async function styleFetchList() {
+    try {
+        const res = await fetch("/api/wfm/styles");
+        return res.ok ? await res.json() : [];
+    } catch { return []; }
+}
+
+export async function styleApiCreate(name, prompt, negativePrompt, targetFile) {
+    try {
+        const body = { name, prompt, negative_prompt: negativePrompt };
+        if (targetFile) body.file = targetFile;
+        const res = await fetch("/api/wfm/styles", {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify(body),
+        });
+        const data = await res.json().catch(() => ({}));
+        return res.ok ? { ok: true } : { ok: false, error: data.error || `HTTP ${res.status}` };
+    } catch (e) {
+        return { ok: false, error: e.message };
+    }
+}
+
+export async function styleApiUpdate(originalName, name, prompt, negativePrompt) {
+    try {
+        const res = await fetch(`/api/wfm/styles/${encodeURIComponent(originalName)}`, {
+            method: "PUT",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify({ name, prompt, negative_prompt: negativePrompt }),
+        });
+        const data = await res.json().catch(() => ({}));
+        return res.ok ? { ok: true } : { ok: false, error: data.error || `HTTP ${res.status}` };
+    } catch (e) {
+        return { ok: false, error: e.message };
+    }
+}
+
+export async function styleApiDelete(name) {
+    try {
+        const res = await fetch(`/api/wfm/styles/${encodeURIComponent(name)}`, { method: "DELETE" });
+        const data = await res.json().catch(() => ({}));
+        return res.ok ? { ok: true } : { ok: false, error: data.error || `HTTP ${res.status}` };
+    } catch (e) {
+        return { ok: false, error: e.message };
+    }
+}
+
+function styleRenderList() {
+    const list = document.getElementById("wfm-style-list");
+    if (!list) return;
+    list.innerHTML = "";
+
+    const q = styleSearchText.trim().toLowerCase();
+    const filtered = q ? styleListData.filter(s => s.name.toLowerCase().includes(q)) : styleListData;
+
+    if (filtered.length === 0) {
+        list.innerHTML = styleListData.length === 0
+            ? `<div class="wfm-pm-empty" style="font-size:12px;">No styles yet.<br><small>Click "+ New" to create one.</small></div>`
+            : `<div class="wfm-pm-empty" style="font-size:12px;">No matching styles.</div>`;
+        return;
+    }
+
+    for (const s of filtered) {
+        const item = document.createElement("div");
+        item.className = "wfm-wc-file-item";
+        item.innerHTML = `
+            <div class="wfm-wc-file-item-info">
+                <span style="flex:1;min-width:0;overflow:hidden;text-overflow:ellipsis;white-space:nowrap;">${esc(s.name)}</span>
+                ${s.file ? `<span class="wfm-wc-file-ext" title="${esc(s.file)}">${esc(s.file)}</span>` : ""}
+            </div>
+            <div class="wfm-wc-file-item-actions">
+                <button class="wfm-pm-action-btn wfm-style-edit-btn" title="Edit style">&#9998;</button>
+            </div>
+        `;
+        item.querySelector(".wfm-style-edit-btn").addEventListener("click", (e) => {
+            e.stopPropagation();
+            styleOpenEditor(s);
+        });
+        item.addEventListener("click", () => styleOpenEditor(s));
+        list.appendChild(item);
+    }
+}
+
+// forcedFile: 「+ Add to this file」から呼ばれた場合に、既存スタイルではなく
+// 特定ファイルを追加先として指定するために使う（styleは渡さずnullにする）
+function styleOpenEditor(style, forcedFile) {
+    styleEditingOriginalName = style ? style.name : null;
+    styleEditingFile = style ? (style.file || null) : (forcedFile || null);
+
+    const editor = document.getElementById("wfm-style-editor");
+    const nameInput = document.getElementById("wfm-style-editor-name");
+    const promptTA = document.getElementById("wfm-style-editor-prompt");
+    const negativeTA = document.getElementById("wfm-style-editor-negative");
+    const deleteBtn = document.getElementById("wfm-style-editor-delete-btn");
+    const addFileBtn = document.getElementById("wfm-style-editor-addfile-btn");
+    const fileLabel = document.getElementById("wfm-style-editor-file-label");
+
+    if (!editor) return;
+    nameInput.value = style?.name || "";
+    promptTA.value = style?.prompt || "";
+    negativeTA.value = style?.negative_prompt || "";
+    deleteBtn.style.display = style ? "" : "none";
+    // 「このファイルへ追加」は既存スタイルを編集中（=対象ファイルが分かっている）時だけ表示
+    addFileBtn.style.display = style ? "" : "none";
+    if (styleEditingFile) {
+        fileLabel.textContent = `File: ${styleEditingFile}`;
+        fileLabel.style.display = "";
+    } else {
+        fileLabel.style.display = "none";
+    }
+    editor.style.display = "";
+    nameInput.focus();
+}
+
+function styleCloseEditor() {
+    styleEditingOriginalName = null;
+    styleEditingFile = null;
+    const editor = document.getElementById("wfm-style-editor");
+    if (editor) editor.style.display = "none";
+}
+
+export async function styleRefreshList() {
+    styleListData = await styleFetchList();
+    styleRenderList();
+}
+
+// ============================================
+// UI wiring (called from prompt-tab.js's initPromptTab)
+// ============================================
+
+export function initStylesUI() {
+    document.getElementById("wfm-style-new-btn")?.addEventListener("click", () => {
+        styleOpenEditor(null);
+    });
+
+    document.getElementById("wfm-style-refresh-btn")?.addEventListener("click", () => {
+        styleRefreshList();
+    });
+
+    // 編集中の既存スタイルと同じファイルへ、新しい空のスタイルを追加する
+    document.getElementById("wfm-style-editor-addfile-btn")?.addEventListener("click", () => {
+        if (!styleEditingFile) return;
+        styleOpenEditor(null, styleEditingFile);
+    });
+
+    setupSearchClearBtn("wfm-style-search", "wfm-style-search-clear-btn", () => {
+        styleSearchText = "";
+        styleRenderList();
+    });
+    document.getElementById("wfm-style-search")?.addEventListener("input", (e) => {
+        styleSearchText = e.target.value;
+        styleRenderList();
+    });
+
+    document.getElementById("wfm-style-editor-save-btn")?.addEventListener("click", async () => {
+        const nameInput = document.getElementById("wfm-style-editor-name");
+        const promptTA = document.getElementById("wfm-style-editor-prompt");
+        const negativeTA = document.getElementById("wfm-style-editor-negative");
+
+        const name = (nameInput?.value || "").trim();
+        const prompt = promptTA?.value || "";
+        const negativePrompt = negativeTA?.value || "";
+
+        if (!name) { showToast(t("pleaseEnterStyleName"), "error"); return; }
+
+        const result = styleEditingOriginalName
+            ? await styleApiUpdate(styleEditingOriginalName, name, prompt, negativePrompt)
+            : await styleApiCreate(name, prompt, negativePrompt, styleEditingFile);
+
+        if (result.ok) {
+            showToast(t("savedAs", name), "success");
+            styleCloseEditor();
+            await styleRefreshList();
+            await refreshStylesList();
+        } else {
+            showToast(t("errorWithMsg", result.error), "error");
+        }
+    });
+
+    // Editor: delete
+    document.getElementById("wfm-style-editor-delete-btn")?.addEventListener("click", async () => {
+        if (!styleEditingOriginalName) return;
+        if (!confirm(`Delete "${styleEditingOriginalName}"?`)) return;
+        const result = await styleApiDelete(styleEditingOriginalName);
+        if (result.ok) {
+            showToast(t("deletedName", styleEditingOriginalName), "success");
+            styleCloseEditor();
+            await styleRefreshList();
+            await refreshStylesList();
+        } else {
+            showToast(t("errorWithMsg", result.error), "error");
+        }
+    });
+
+    // Editor: cancel
+    document.getElementById("wfm-style-editor-cancel-btn")?.addEventListener("click", () => {
+        styleCloseEditor();
+    });
+
+    // Initial style list load
+    styleRefreshList();
+}
@@ -0,0 +1,475 @@
+/**
+ * Prompt Tab - Wildcard file manager (list, editor, insert-at-cursor helpers)
+ */
+
+import { showToast } from "./app.js";
+import { t } from "./i18n.js";
+import { esc } from "./prompt-presets.js";
+
+// ============================================
+// Wildcard API helpers
+// ============================================
+
+export async function wcFetchFiles() {
+    try {
+        const res = await fetch("/api/wfm/wildcards");
+        return res.ok ? await res.json() : [];
+    } catch { return []; }
+}
+
+export async function wcFetchContent(filename) {
+    try {
+        const res = await fetch(`/api/wfm/wildcards/content?filename=${encodeURIComponent(filename)}`);
+        const data = await res.json();
+        return data.content ?? null;
+    } catch { return null; }
+}
+
+export async function wcSaveFile(filename, content) {
+    try {
+        const res = await fetch("/api/wfm/wildcards/save", {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify({ filename, content }),
+        });
+        const data = await res.json();
+        return data.status === "ok" ? data.file : null;
+    } catch { return null; }
+}
+
+export async function wcDeleteFile(filename) {
+    try {
+        await fetch("/api/wfm/wildcards/delete", {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify({ filename }),
+        });
+    } catch { /* ignore */ }
+}
+
+// ============================================
+// Wildcard state & helpers
+// ============================================
+
+let wcFiles = [];
+let wcEditingFilename = null; // null = new file
+
+// Insert text at cursor; if open+close provided wraps selection
+function wcInsertAtCursor(textarea, open, close = "") {
+    const start = textarea.selectionStart;
+    const end = textarea.selectionEnd;
+    const selected = textarea.value.substring(start, end);
+    let inserted, cursorStart, cursorEnd;
+
+    if (selected && close) {
+        inserted = open + selected + close;
+        cursorStart = start + open.length;
+        cursorEnd = cursorStart + selected.length;
+    } else if (close) {
+        inserted = open + close;
+        cursorStart = start + open.length;
+        cursorEnd = cursorStart;
+    } else {
+        inserted = open;
+        cursorStart = start + open.length;
+        cursorEnd = cursorStart;
+    }
+
+    textarea.value =
+        textarea.value.substring(0, start) +
+        inserted +
+        textarea.value.substring(end);
+    textarea.setSelectionRange(cursorStart, cursorEnd);
+    textarea.focus();
+    textarea.dispatchEvent(new Event("input"));
+}
+
+// ============================================
+// Wildcard file list rendering
+// ============================================
+
+function wcRenderFileList() {
+    const list = document.getElementById("wfm-wc-file-list");
+    if (!list) return;
+    list.innerHTML = "";
+
+    if (wcFiles.length === 0) {
+        list.innerHTML = `<div class="wfm-pm-empty" style="font-size:12px;">No wildcard files yet.<br><small>Click "+ New" to create one.</small></div>`;
+        return;
+    }
+
+    // Group by directory; root ("") first, then alphabetical
+    const grouped = {};
+    for (const f of wcFiles) {
+        const dir = f.dir || "";
+        if (!grouped[dir]) grouped[dir] = [];
+        grouped[dir].push(f);
+    }
+    const dirs = Object.keys(grouped).sort((a, b) => {
+        if (a === "") return -1;
+        if (b === "") return 1;
+        return a.localeCompare(b);
+    });
+
+    function addFileItem(f, indented) {
+        const item = document.createElement("div");
+        item.className = "wfm-wc-file-item" + (indented ? " wfm-wc-file-item--sub" : "");
+        item.innerHTML = `
+            <div class="wfm-wc-file-item-info">
+                <span class="wfm-wc-file-name">${esc(f.name)}</span>
+                <span class="wfm-wc-file-ext">.${esc(f.ext)}</span>
+            </div>
+            <div class="wfm-wc-file-item-actions">
+                <button class="wfm-pm-action-btn wfm-wc-use-btn" title="Insert __${esc(f.wc_name)}__ at cursor">Use</button>
+                <button class="wfm-pm-action-btn wfm-wc-edit-btn" title="Edit file">&#9998;</button>
+            </div>
+        `;
+        item.querySelector(".wfm-wc-use-btn").addEventListener("click", (e) => {
+            e.stopPropagation();
+            const ta = document.getElementById("wfm-wc-prompt");
+            if (ta) wcInsertAtCursor(ta, `__${f.wc_name}__`);
+        });
+        item.querySelector(".wfm-wc-edit-btn").addEventListener("click", async (e) => {
+            e.stopPropagation();
+            const content = await wcFetchContent(f.filename);
+            wcOpenEditor(f.wc_name, f.ext, content ?? "", f.filename);
+        });
+        item.addEventListener("click", () => {
+            const ta = document.getElementById("wfm-wc-prompt");
+            if (ta) wcInsertAtCursor(ta, `__${f.wc_name}__`);
+        });
+        list.appendChild(item);
+    }
+
+    for (const dir of dirs) {
+        if (dir) {
+            const header = document.createElement("div");
+            header.className = "wfm-wc-dir-header";
+            header.textContent = dir + "/";
+            list.appendChild(header);
+        }
+        for (const f of grouped[dir]) {
+            addFileItem(f, dir !== "");
+        }
+    }
+}
+
+// ============================================
+// Wildcard file editor
+// ============================================
+
+function wcOpenEditor(name, ext, content, existingFilename) {
+    wcEditingFilename = existingFilename || null;
+
+    const editor = document.getElementById("wfm-wc-editor");
+    const nameInput = document.getElementById("wfm-wc-editor-name");
+    const extSelect = document.getElementById("wfm-wc-editor-ext");
+    const contentTA = document.getElementById("wfm-wc-editor-content");
+    const deleteBtn = document.getElementById("wfm-wc-editor-delete-btn");
+
+    if (!editor) return;
+    nameInput.value = name || "";
+    extSelect.value = ext || "txt";
+    contentTA.value = content || "";
+    deleteBtn.style.display = existingFilename ? "" : "none";
+    editor.style.display = "";
+    nameInput.focus();
+}
+
+function wcCloseEditor() {
+    wcEditingFilename = null;
+    const editor = document.getElementById("wfm-wc-editor");
+    if (editor) editor.style.display = "none";
+}
+
+export async function wcRefreshFiles() {
+    wcFiles = await wcFetchFiles();
+    wcRenderFileList();
+    wcUpdateFilePicker();
+}
+
+// ============================================
+// Wildcard file picker popup
+// ============================================
+
+// Renders the wildcard-file-reference list into `picker`, inserting into `targetTa` on click.
+// Shared by the Form tab's fixed file-picker popup and any dynamically built toolbar
+// (see createWildcardToolbar) so both stay in sync with a single implementation.
+function renderFilePicker(picker, targetTa) {
+    picker.innerHTML = "";
+    if (wcFiles.length === 0) {
+        picker.innerHTML = `<div style="padding:8px;font-size:11px;color:var(--wfm-text-secondary);">No wildcard files</div>`;
+        return;
+    }
+    // Group by directory same as file list
+    const grouped = {};
+    for (const f of wcFiles) {
+        const dir = f.dir || "";
+        if (!grouped[dir]) grouped[dir] = [];
+        grouped[dir].push(f);
+    }
+    const dirs = Object.keys(grouped).sort((a, b) => {
+        if (a === "") return -1;
+        if (b === "") return 1;
+        return a.localeCompare(b);
+    });
+    for (const dir of dirs) {
+        if (dir) {
+            const sep = document.createElement("div");
+            sep.className = "wfm-wc-picker-dir";
+            sep.textContent = dir + "/";
+            picker.appendChild(sep);
+        }
+        for (const f of grouped[dir]) {
+            const btn = document.createElement("button");
+            btn.className = "wfm-wc-picker-item" + (dir ? " wfm-wc-picker-item--sub" : "");
+            btn.textContent = `__${f.wc_name}__`;
+            btn.addEventListener("click", () => {
+                wcInsertAtCursor(targetTa, `__${f.wc_name}__`);
+                picker.style.display = "none";
+            });
+            picker.appendChild(btn);
+        }
+    }
+}
+
+function wcUpdateFilePicker() {
+    const picker = document.getElementById("wfm-wc-file-picker");
+    const ta = document.getElementById("wfm-wc-prompt");
+    if (!picker || !ta) return;
+    renderFilePicker(picker, ta);
+}
+
+// ============================================
+// Reusable wildcard syntax toolbar (buttons + file-reference picker)
+// ============================================
+
+const WC_SYNTAX_BUTTONS = [
+    { open: "{", close: "}", label: "{ }", title: "Random pick set  e.g. {cat|dog}" },
+    { open: "|", close: "", label: "|", title: "Separator" },
+    { open: "__", close: "__", label: "__", title: "Wildcard file reference  e.g. __animals__" },
+    { open: ":", close: "", label: ":", title: "Colon" },
+    { open: ";", close: "", label: ";", title: "Semicolon" },
+    { open: "$$", close: "", label: "$$", title: "Multi-pick  e.g. {2$$cat|dog|bird}" },
+    { open: "[", close: "]", label: "[ ]", title: "Bracket set  e.g. [cat|dog]" },
+];
+
+// Builds a standalone wildcard-syntax toolbar (syntax buttons, LoRA/n$${} helpers, and the
+// file-reference picker) wired to insert into the given textarea. The Form tab's Col3 panel
+// uses the static toolbar markup in index.html instead (wired in initWildcardsUI below); this
+// is for callers that need the same toolbar attached to a textarea built at runtime, such as
+// the Table tab's wildcard edit modal (see prompt-table.js).
+export function createWildcardToolbar(textareaEl) {
+    const toolbar = document.createElement("div");
+    toolbar.className = "wfm-wc-toolbar";
+
+    for (const b of WC_SYNTAX_BUTTONS) {
+        const btn = document.createElement("button");
+        btn.className = "wfm-wc-btn";
+        btn.title = b.title;
+        btn.textContent = b.label;
+        btn.addEventListener("click", () => wcInsertAtCursor(textareaEl, b.open, b.close));
+        toolbar.appendChild(btn);
+    }
+
+    const loraBtn = document.createElement("button");
+    loraBtn.className = "wfm-wc-btn";
+    loraBtn.title = "LoRA with LBW  e.g. <lora:name:1:LBW=...;...>";
+    loraBtn.textContent = "<lora>";
+    loraBtn.addEventListener("click", () => {
+        wcInsertAtCursor(textareaEl, "<lora::1:LBW=;>");
+        // Move cursor to after "lora:" for the name
+        const pos = textareaEl.selectionStart - "<lora::1:LBW=;>".length + 6;
+        textareaEl.setSelectionRange(pos, pos);
+        textareaEl.focus();
+    });
+    toolbar.appendChild(loraBtn);
+
+    const nsetBtn = document.createElement("button");
+    nsetBtn.className = "wfm-wc-btn";
+    nsetBtn.title = "Multi-pick set  e.g. {2$$cat|dog|bird}";
+    nsetBtn.textContent = "n$${ }";
+    nsetBtn.addEventListener("click", () => {
+        const n = prompt("Number of items to pick (n):", "2");
+        if (n === null) return;
+        const num = parseInt(n, 10);
+        if (isNaN(num) || num < 1) { showToast(t("enterPositiveInt"), "error"); return; }
+        const template = "{" + num + "$$|}";
+        const start = textareaEl.selectionStart;
+        wcInsertAtCursor(textareaEl, template);
+        // Move cursor between $$ and |
+        const inner = start + ("{" + num + "$$").length;
+        textareaEl.setSelectionRange(inner, inner);
+        textareaEl.focus();
+    });
+    toolbar.appendChild(nsetBtn);
+
+    const pickerWrap = document.createElement("div");
+    pickerWrap.className = "wfm-wc-file-picker-wrap";
+    const pickBtn = document.createElement("button");
+    pickBtn.className = "wfm-wc-btn";
+    pickBtn.title = "Insert wildcard file reference";
+    pickBtn.innerHTML = "&#128194; File";
+    const picker = document.createElement("div");
+    picker.className = "wfm-wc-file-picker";
+    picker.style.display = "none";
+    pickBtn.addEventListener("click", (e) => {
+        e.stopPropagation();
+        const isOpen = picker.style.display !== "none";
+        picker.style.display = isOpen ? "none" : "";
+        if (!isOpen) renderFilePicker(picker, textareaEl);
+    });
+    document.addEventListener("click", () => { picker.style.display = "none"; });
+    pickerWrap.appendChild(pickBtn);
+    pickerWrap.appendChild(picker);
+    toolbar.appendChild(pickerWrap);
+
+    return toolbar;
+}
+
+// ============================================
+// UI wiring (called from prompt-tab.js's initPromptTab)
+// ============================================
+
+export function initWildcardsUI() {
+    // ── Wildcard syntax buttons ──────────────────────────────
+    document.querySelectorAll(".wfm-wc-btn[data-wc-open]").forEach(btn => {
+        btn.addEventListener("click", () => {
+            const ta = document.getElementById("wfm-wc-prompt");
+            if (!ta) return;
+            const open = btn.dataset.wcOpen || "";
+            const close = btn.dataset.wcClose || "";
+            wcInsertAtCursor(ta, open, close);
+        });
+    });
+
+    // LoRA LBW template button
+    document.getElementById("wfm-wc-lora-btn")?.addEventListener("click", () => {
+        const ta = document.getElementById("wfm-wc-prompt");
+        if (!ta) return;
+        wcInsertAtCursor(ta, "<lora::1:LBW=;>");
+        // Move cursor to after "lora:" for the name
+        const pos = ta.selectionStart - "<lora::1:LBW=;>".length + 6;
+        ta.setSelectionRange(pos, pos);
+        ta.focus();
+    });
+
+    // n$${ } button — asks for n then inserts multi-pick template
+    document.getElementById("wfm-wc-nset-btn")?.addEventListener("click", () => {
+        const ta = document.getElementById("wfm-wc-prompt");
+        if (!ta) return;
+        const n = prompt("Number of items to pick (n):", "2");
+        if (n === null) return;
+        const num = parseInt(n, 10);
+        if (isNaN(num) || num < 1) { showToast(t("enterPositiveInt"), "error"); return; }
+        const template = "{" + num + "$$|}";
+        const start = ta.selectionStart;
+        wcInsertAtCursor(ta, template);
+        // Move cursor between $$ and |
+        const inner = start + ("{" + num + "$$").length;
+        ta.setSelectionRange(inner, inner);
+        ta.focus();
+    });
+
+    // File picker toggle
+    const filePickBtn = document.getElementById("wfm-wc-filepick-btn");
+    const filePicker = document.getElementById("wfm-wc-file-picker");
+    filePickBtn?.addEventListener("click", (e) => {
+        e.stopPropagation();
+        if (!filePicker) return;
+        const isOpen = filePicker.style.display !== "none";
+        filePicker.style.display = isOpen ? "none" : "";
+        if (!isOpen) wcUpdateFilePicker();
+    });
+    document.addEventListener("click", () => {
+        if (filePicker) filePicker.style.display = "none";
+    });
+
+    // ── Wildcard prompt actions ──────────────────────────────
+    document.getElementById("wfm-wc-copy-btn")?.addEventListener("click", () => {
+        const ta = document.getElementById("wfm-wc-prompt");
+        const text = ta?.value || "";
+        if (!text.trim()) { showToast(t("noTextToCopy"), "error"); return; }
+        navigator.clipboard.writeText(text).then(() => showToast(t("copiedToClipboard"), "success"));
+    });
+
+    document.getElementById("wfm-wc-to-pos-btn")?.addEventListener("click", () => {
+        const src = document.getElementById("wfm-wc-prompt");
+        const dst = document.getElementById("wfm-preset-pos");
+        if (!src || !dst) return;
+        dst.value = src.value;
+        dst.dispatchEvent(new Event("input", { bubbles: true }));
+        showToast(t("sentToPositive"), "success");
+    });
+
+    document.getElementById("wfm-wc-to-neg-btn")?.addEventListener("click", () => {
+        const src = document.getElementById("wfm-wc-prompt");
+        const dst = document.getElementById("wfm-preset-neg");
+        if (!src || !dst) return;
+        dst.value = src.value;
+        dst.dispatchEvent(new Event("input", { bubbles: true }));
+        showToast(t("sentToNegative"), "success");
+    });
+
+    document.getElementById("wfm-wc-clear-btn")?.addEventListener("click", () => {
+        const ta = document.getElementById("wfm-wc-prompt");
+        if (ta) { ta.value = ""; ta.focus(); }
+    });
+
+    // ── Wildcard file manager ────────────────────────────────
+    document.getElementById("wfm-wc-new-file-btn")?.addEventListener("click", () => {
+        wcOpenEditor("", "txt", "", null);
+    });
+
+    document.getElementById("wfm-wc-files-refresh-btn")?.addEventListener("click", () => {
+        wcRefreshFiles();
+    });
+
+    // Editor: save
+    document.getElementById("wfm-wc-editor-save-btn")?.addEventListener("click", async () => {
+        const nameInput = document.getElementById("wfm-wc-editor-name");
+        const extSelect = document.getElementById("wfm-wc-editor-ext");
+        const contentTA = document.getElementById("wfm-wc-editor-content");
+
+        // Normalize separators and strip leading/trailing slashes
+        const rawName = (nameInput?.value || "").trim().replace(/\\/g, "/").replace(/\/+/g, "/").replace(/^\/|\/$/g, "");
+        const ext = extSelect?.value || "txt";
+        const content = contentTA?.value || "";
+
+        if (!rawName) { showToast(t("pleaseEnterFilename"), "error"); return; }
+        // Validate each path component (allow letters, numbers, -, _, ., space)
+        const nameParts = rawName.split("/");
+        if (nameParts.some(p => !p || !/^[\w\-. ]+$/.test(p))) {
+            showToast(t("invalidPathFormat"), "error");
+            return;
+        }
+        const name = rawName;
+        const filename = `${name}.${ext}`;
+        const saved = await wcSaveFile(filename, content);
+        if (saved) {
+            showToast(t("savedAs", filename), "success");
+            wcCloseEditor();
+            wcRefreshFiles();
+        } else {
+            showToast(t("saveFailed"), "error");
+        }
+    });
+
+    // Editor: delete
+    document.getElementById("wfm-wc-editor-delete-btn")?.addEventListener("click", async () => {
+        if (!wcEditingFilename) return;
+        if (!confirm(`Delete "${wcEditingFilename}"?`)) return;
+        await wcDeleteFile(wcEditingFilename);
+        showToast(t("deletedName", wcEditingFilename), "success");
+        wcCloseEditor();
+        wcRefreshFiles();
+    });
+
+    // Editor: cancel
+    document.getElementById("wfm-wc-editor-cancel-btn")?.addEventListener("click", () => {
+        wcCloseEditor();
+    });
+
+    // Initial wildcard file load
+    wcRefreshFiles();
+}
@@ -336,6 +336,34 @@ export function applyTextareaFontSize(size) {
    el.textContent = `${TEXTAREA_FONT_SIZE_TARGETS} { font-size: ${px}px !important; }`;
 }

+// Video playback volume — shared by every <video> player in the app (Video tab preview,
+// Gallery detail/lightbox/compare). The browser default for a freshly created <video> element
+// is always 100%, and Gallery's players are recreated from scratch each time a different video
+// is opened, so without this the volume silently jumps back to max on every video switch.
+const VIDEO_VOLUME_DEFAULT = 1;
+
+export function getVideoVolume() {
+    const v = loadLocalSettings().videoVolume;
+    return typeof v === "number" && v >= 0 && v <= 1 ? v : VIDEO_VOLUME_DEFAULT;
+}
+
+function setVideoVolume(volume) {
+    const clamped = Math.max(0, Math.min(1, volume));
+    saveLocalSettings({ videoVolume: clamped });
+    return clamped;
+}
+
+// Applies the saved volume to a <video> element, and keeps it in sync with any further change
+// the user makes via that element's own native controls — so adjusting the volume on any video
+// player anywhere in the app is remembered for the next video opened anywhere else.
+export function applyStoredVideoVolume(videoEl) {
+    if (!videoEl) return;
+    videoEl.volume = getVideoVolume();
+    if (videoEl.dataset.wfmVolumeWired) return;
+    videoEl.dataset.wfmVolumeWired = "1";
+    videoEl.addEventListener("volumechange", () => setVideoVolume(videoEl.volume));
+}
+
 // JSON highlight color settings
 const JSON_COLOR_STYLE_ID = "wfm-json-color-style";

@@ -366,6 +394,21 @@ export function applyJsonColors(colors) {
    ].join("\n");
 }

+// GenerateUI Model tab: highlight color for section labels that match the loaded workflow
+const MODEL_ACTIVE_COLOR_STYLE_ID = "wfm-model-active-color-style";
+const MODEL_ACTIVE_COLOR_DEFAULT = "#4ade80";
+
+export function applyModelTabActiveColor(color) {
+    const val = color || MODEL_ACTIVE_COLOR_DEFAULT;
+    let el = document.getElementById(MODEL_ACTIVE_COLOR_STYLE_ID);
+    if (!el) {
+        el = document.createElement("style");
+        el.id = MODEL_ACTIVE_COLOR_STYLE_ID;
+        document.head.appendChild(el);
+    }
+    el.textContent = `.wfm-form-group label.wfm-model-label-active,\n.wfm-settings-summary.wfm-model-label-active,\n#wfm-gen-lora-col-title.wfm-model-label-active,\n.wfm-lab-model-view-btn.wfm-model-label-active,\n.wfm-video-plan-content label.wfm-model-label-active { color: ${val}; }`;
+}
+
 export function applyTheme(themeId) {
    if (themeId) {
        document.documentElement.setAttribute("data-theme", themeId);
@@ -560,6 +603,24 @@ export async function initSettingsTab() {
            </div>
        </details>

+        <!-- Video Volume -->
+        <details class="wfm-settings-section" open>
+            <summary class="wfm-settings-summary">${t("videoVolumeLabel") || "Video Volume"}</summary>
+            <div class="wfm-form-group">
+                <label style="display:flex;align-items:center;justify-content:space-between;">
+                    <span>${t("videoVolumeLabel") || "Video Volume"}</span>
+                    <span id="wfm-video-volume-val" style="font-size:12px;color:var(--wfm-text-secondary);">${Math.round(getVideoVolume() * 100)}%</span>
+                </label>
+                <input type="range" class="wfm-range" id="wfm-video-volume"
+                    min="0" max="100" step="1"
+                    value="${Math.round(getVideoVolume() * 100)}"
+                    style="width:100%;margin-top:4px;">
+                <small style="color:var(--wfm-text-secondary);font-size:11px;display:block;margin-top:4px;">
+                    ${t("videoVolumeHint") || "Applies to: Video tab preview, Gallery detail/lightbox/compare video players"}
+                </small>
+            </div>
+        </details>
+
        <!-- RAW JSON Colors -->
        <details class="wfm-settings-section" open>
            <summary class="wfm-settings-summary">${t("jsonColorsSection") || "RAW JSON Colors"}</summary>
@@ -577,6 +638,21 @@ export async function initSettingsTab() {
            </div>
        </details>

+        <!-- GenerateUI Model Tab Highlight Color -->
+        <details class="wfm-settings-section" open>
+            <summary class="wfm-settings-summary">${t("modelTabColorSection") || "GenerateUI Modelタブ ハイライト色"}</summary>
+            <div class="wfm-form-group">
+                <label>${t("modelTabColorLabel") || "ワークフローに含まれる項目の色"}</label>
+                <div style="display:flex;align-items:center;gap:8px;">
+                    <input type="color" id="wfm-model-active-color" value="${settings.modelTabActiveColor || MODEL_ACTIVE_COLOR_DEFAULT}">
+                    <button class="wfm-btn wfm-btn-sm" id="wfm-model-active-color-reset">${t("jsonColorReset") || "デフォルトに戻す"}</button>
+                </div>
+                <small style="color:var(--wfm-text-secondary);font-size:11px;display:block;margin-top:4px;">
+                    ${t("modelTabColorHint") || "GenerateUIのModelタブで、読み込んだワークフローに実際に含まれる項目（Checkpoint / VAE など）のラベルをこの色で表示します"}
+                </small>
+            </div>
+        </details>
+
        <!-- Workflow Data Folder -->
        <details class="wfm-settings-section">
            <summary class="wfm-settings-summary">${t("workflowsDir")}</summary>
@@ -661,41 +737,6 @@ export async function initSettingsTab() {
            <button class="wfm-btn wfm-btn-primary wfm-btn-sm" id="wfm-settings-default-ckpt-save">${t("save")}</button>
        </details>

-        <!-- AI Assistant Settings (Prompt Tab) -->
-        <details class="wfm-settings-section">
-            <summary class="wfm-settings-summary">${t("ollamaSettings")}</summary>
-            <div class="wfm-form-group">
-                <label>${t("aiSettingsBackend")}</label>
-                <div class="wfm-ai-backend-row">
-                    <label class="wfm-ai-radio-label">
-                        <input type="radio" name="wfm-prompt-ai-backend" value="ollama"> Ollama
-                    </label>
-                    <label class="wfm-ai-radio-label">
-                        <input type="radio" name="wfm-prompt-ai-backend" value="lmstudio"> LM Studio
-                    </label>
-                </div>
-            </div>
-            <div class="wfm-form-group">
-                <label>${t("ollamaUrl")}</label>
-                <input type="text" class="wfm-input" id="wfm-settings-prompt-ai-url"
-                    placeholder="http://localhost:11434">
-            </div>
-            <div class="wfm-form-group">
-                <label>${t("ollamaDefaultModel")}</label>
-                <div style="display:flex;gap:8px;">
-                    <select class="wfm-select" id="wfm-settings-prompt-ai-model" style="flex:1;">
-                        <option value="">${t("selectModel")}</option>
-                    </select>
-                    <button class="wfm-btn wfm-btn-sm" id="wfm-settings-prompt-ai-refresh">${t("refresh")}</button>
-                </div>
-            </div>
-            <div style="display:flex;gap:8px;margin-top:8px;">
-                <button class="wfm-btn wfm-btn-primary wfm-btn-sm" id="wfm-settings-prompt-ai-save">${t("saveOllama")}</button>
-                <button class="wfm-btn wfm-btn-sm" id="wfm-settings-prompt-ai-test">${t("testConnection")}</button>
-                <span id="wfm-settings-prompt-ai-status" style="font-size:12px;line-height:28px;"></span>
-            </div>
-        </details>
-
        <!-- CivitAI Settings -->
        <details class="wfm-settings-section">
            <summary class="wfm-settings-summary">${t("civitaiApiKeySetting")}</summary>
@@ -791,6 +832,25 @@ export async function initSettingsTab() {
                    <input type="file" id="wfm-settings-import-file" accept=".json" style="display:none;">
                </label>
            </div>
+            <p style="font-size:12px;color:var(--wfm-text-secondary);margin:12px 0 8px 0;">${t("fullBackupHint")}</p>
+            <div style="display:flex;flex-direction:column;gap:4px;margin-bottom:8px;">
+                <label class="wfm-lab-checkbox-label" style="font-size:12px;">
+                    <input type="checkbox" id="wfm-settings-backup-include-workflows">
+                    ${t("fullBackupIncludeWorkflows")}
+                </label>
+                <label class="wfm-lab-checkbox-label" style="font-size:12px;">
+                    <input type="checkbox" id="wfm-settings-backup-include-wildcard">
+                    ${t("fullBackupIncludeWildcard")}
+                </label>
+                <span style="font-size:11px;color:var(--wfm-text-secondary);">${t("fullBackupExternalHint")}</span>
+            </div>
+            <div style="display:flex;gap:8px;flex-wrap:wrap;">
+                <button class="wfm-btn wfm-btn-sm" id="wfm-settings-export-full">${t("exportFullBackup")}</button>
+                <label class="wfm-btn wfm-btn-sm" style="cursor:pointer;margin:0;">
+                    ${t("importFullBackup")}
+                    <input type="file" id="wfm-settings-import-full-file" accept=".zip" style="display:none;">
+                </label>
+            </div>
            <div id="wfm-settings-data-status" style="font-size:12px;margin-top:8px;"></div>
        </details>

@@ -1106,92 +1166,6 @@ export async function initSettingsTab() {
        }
    });

-    // --- AI Assistant (Prompt Tab) settings ---
-    const PROMPT_AI_KEY = "wfm_prompt_ai_settings";
-    const loadPromptAiCfg = () => {
-        try { return JSON.parse(localStorage.getItem(PROMPT_AI_KEY) || "{}"); } catch { return {}; }
-    };
-    const savePromptAiCfg = (patch) => {
-        const data = { ...loadPromptAiCfg(), ...patch };
-        localStorage.setItem(PROMPT_AI_KEY, JSON.stringify(data));
-    };
-
-    // Restore saved values into UI
-    const promptAiSaved = loadPromptAiCfg();
-    const promptAiBackendSaved = promptAiSaved.backend || "ollama";
-    document.querySelectorAll('input[name="wfm-prompt-ai-backend"]').forEach(r => {
-        r.checked = r.value === promptAiBackendSaved;
-    });
-    const promptAiUrlEl = document.getElementById("wfm-settings-prompt-ai-url");
-    if (promptAiUrlEl) {
-        promptAiUrlEl.value = promptAiSaved.backendUrl || "";
-        promptAiUrlEl.placeholder = promptAiBackendSaved === "ollama" ? "http://localhost:11434" : "http://localhost:1234";
-    }
-
-    // Backend change → update URL placeholder
-    document.querySelectorAll('input[name="wfm-prompt-ai-backend"]').forEach(r => {
-        r.addEventListener("change", () => {
-            const backend = document.querySelector('input[name="wfm-prompt-ai-backend"]:checked')?.value || "ollama";
-            if (promptAiUrlEl) promptAiUrlEl.placeholder = backend === "ollama" ? "http://localhost:11434" : "http://localhost:1234";
-        });
-    });
-
-    // Load models directly from the selected backend
-    async function loadPromptAiModels() {
-        const select = document.getElementById("wfm-settings-prompt-ai-model");
-        if (!select) return;
-        const backend = document.querySelector('input[name="wfm-prompt-ai-backend"]:checked')?.value || "ollama";
-        const url = (promptAiUrlEl?.value.trim() || (backend === "ollama" ? "http://localhost:11434" : "http://localhost:1234")).replace(/\/$/, "");
-        try {
-            let models = [];
-            if (backend === "ollama") {
-                const res = await fetch(`${url}/api/tags`);
-                models = (await res.json()).models?.map(m => m.name) || [];
-            } else {
-                const res = await fetch(`${url}/v1/models`);
-                models = ((await res.json()).data || []).map(m => m.id);
-            }
-            const saved = loadPromptAiCfg().model || "";
-            select.innerHTML = models.length
-                ? models.map(name => `<option value="${name}" ${name === saved ? "selected" : ""}>${name}</option>`).join("")
-                : `<option value="">${t("noModelsFound")}</option>`;
-        } catch {
-            select.innerHTML = `<option value="">${t("failedLoadModels")}</option>`;
-        }
-    }
-    await loadPromptAiModels();
-
-    document.getElementById("wfm-settings-prompt-ai-refresh")?.addEventListener("click", loadPromptAiModels);
-
-    document.getElementById("wfm-settings-prompt-ai-test")?.addEventListener("click", async () => {
-        const statusEl = document.getElementById("wfm-settings-prompt-ai-status");
-        const backend = document.querySelector('input[name="wfm-prompt-ai-backend"]:checked')?.value || "ollama";
-        const url = (promptAiUrlEl?.value.trim() || (backend === "ollama" ? "http://localhost:11434" : "http://localhost:1234")).replace(/\/$/, "");
-        if (statusEl) { statusEl.textContent = t("aiStatusConnecting"); statusEl.style.color = "var(--wfm-text-secondary)"; }
-        try {
-            let count = 0;
-            if (backend === "ollama") {
-                const res = await fetch(`${url}/api/tags`);
-                count = ((await res.json()).models || []).length;
-            } else {
-                const res = await fetch(`${url}/v1/models`);
-                count = ((await res.json()).data || []).length;
-            }
-            if (statusEl) { statusEl.textContent = `${t("ollamaConnected")} (${count} models)`; statusEl.style.color = "var(--wfm-success)"; }
-            await loadPromptAiModels();
-        } catch (err) {
-            if (statusEl) { statusEl.textContent = `${t("ollamaFailed")}: ${err.message}`; statusEl.style.color = "var(--wfm-danger)"; }
-        }
-    });
-
-    document.getElementById("wfm-settings-prompt-ai-save")?.addEventListener("click", () => {
-        const backend = document.querySelector('input[name="wfm-prompt-ai-backend"]:checked')?.value || "ollama";
-        const url = promptAiUrlEl?.value.trim() || "";
-        const model = document.getElementById("wfm-settings-prompt-ai-model")?.value || "";
-        savePromptAiCfg({ backend, backendUrl: url, model });
-        showToast(t("ollamaSaved"), "success");
-    });
-
    // CivitAI host select
    document.getElementById("wfm-settings-civitai-host")?.addEventListener("change", async (e) => {
        const host = e.target.value;
@@ -1309,6 +1283,16 @@ export async function initSettingsTab() {
        applyTextareaFontSize(px);
    });

+    // --- Video volume slider (auto-saves immediately, no "Save" click needed — a dragged
+    // slider that silently didn't persist would defeat the whole point of this setting) ---
+    document.getElementById("wfm-video-volume")?.addEventListener("input", (e) => {
+        const pct = parseInt(e.target.value) || 0;
+        const valEl = document.getElementById("wfm-video-volume-val");
+        if (valEl) valEl.textContent = `${pct}%`;
+        const volume = setVideoVolume(pct / 100);
+        document.querySelectorAll("video").forEach((v) => { v.volume = volume; });
+    });
+
    // --- JSON highlight color pickers ---
    document.getElementById("wfm-json-color-grid")?.addEventListener("input", (e) => {
        if (e.target.type !== "color") return;
@@ -1330,6 +1314,22 @@ export async function initSettingsTab() {
        showToast(t("settingsSaved"), "success");
    });

+    // --- GenerateUI Model tab highlight color ---
+    document.getElementById("wfm-model-active-color")?.addEventListener("input", (e) => {
+        saveLocalSettings({ modelTabActiveColor: e.target.value });
+        applyModelTabActiveColor(e.target.value);
+    });
+
+    document.getElementById("wfm-model-active-color-reset")?.addEventListener("click", () => {
+        const cur = loadLocalSettings();
+        delete cur.modelTabActiveColor;
+        localStorage.setItem(SETTINGS_KEY, JSON.stringify(cur));
+        applyModelTabActiveColor(undefined);
+        const inp = document.getElementById("wfm-model-active-color");
+        if (inp) inp.value = MODEL_ACTIVE_COLOR_DEFAULT;
+        showToast(t("settingsSaved"), "success");
+    });
+
    // Save (local settings)
    document.getElementById("wfm-settings-save")?.addEventListener("click", () => {
        const taFontSize = parseInt(document.getElementById("wfm-ta-font-size")?.value) || TEXTAREA_FONT_SIZE_DEFAULT;
@@ -1483,8 +1483,53 @@ export async function initSettingsTab() {
            statusEl.textContent = t("importError") + ": " + e.message;
            statusEl.style.color = "var(--wfm-error, #f44336)";
        }
-        // Reset file input so same file can be re-selected
-        e.target.value = "";
+    });
+
+    // --- Full Backup Export (ZIP) ---
+    document.getElementById("wfm-settings-export-full")?.addEventListener("click", async () => {
+        const statusEl = document.getElementById("wfm-settings-data-status");
+        try {
+            const includeWorkflows = document.getElementById("wfm-settings-backup-include-workflows")?.checked ? "1" : "0";
+            const includeWildcard = document.getElementById("wfm-settings-backup-include-wildcard")?.checked ? "1" : "0";
+            const res = await fetch(`/api/wfm/settings/export-full?include_workflows=${includeWorkflows}&include_wildcard=${includeWildcard}`);
+            if (!res.ok) throw new Error(await res.text());
+            const blob = await res.blob();
+            const url = URL.createObjectURL(blob);
+            const a = document.createElement("a");
+            a.href = url;
+            a.download = "wfm-full-backup.zip";
+            a.click();
+            URL.revokeObjectURL(url);
+            statusEl.textContent = t("exportSuccess");
+            statusEl.style.color = "var(--wfm-success, #4caf50)";
+        } catch (e) {
+            statusEl.textContent = t("exportError") + ": " + e.message;
+            statusEl.style.color = "var(--wfm-error, #f44336)";
+        }
+    });
+
+    // --- Full Backup Import (ZIP) ---
+    document.getElementById("wfm-settings-import-full-file")?.addEventListener("change", async (e) => {
+        const statusEl = document.getElementById("wfm-settings-data-status");
+        const file = e.target.files?.[0];
+        if (!file) return;
+        try {
+            const fd = new FormData();
+            fd.append("file", file, file.name);
+            const res = await fetch("/api/wfm/settings/import-full", {
+                method: "POST",
+                body: fd,
+            });
+            const result = await res.json();
+            if (!res.ok) throw new Error(result.error || res.statusText);
+            statusEl.textContent = `${t("importSuccess")}: ${result.extracted?.length ?? 0} ${t("fullBackupFilesUnit")}`;
+            statusEl.style.color = "var(--wfm-success, #4caf50)";
+        } catch (e) {
+            statusEl.textContent = t("importError") + ": " + e.message;
+            statusEl.style.color = "var(--wfm-error, #f44336)";
+        } finally {
+            e.target.value = "";
+        }
    });

    // Save G'MIC path setting
@@ -0,0 +1,373 @@
+/**
+ * Style Catalog Gallery — Gallery タブのサブタブ。
+ * ws_style_catalog フォルダ配下の画像（GenerateUIの「カタログ作成」で生成した、
+ * ファイル名=スタイル名のプレビュー画像）を閲覧し、埋め込みPositive/Negative
+ * プロンプトを表示・コピーする。「Select as Style」でGenerateUIの登録済み
+ * Styleドロップダウンをファイル名と同名のStyleに切り替える。
+ */
+
+import { showToast } from "./app.js";
+import { t } from "./i18n.js";
+import { escapeHtml, setupSearchClearBtn } from "./util.js";
+import { extractAllMetadata, loadFileIntoMetadataTab } from "./metadata-tab.js";
+import { selectStyleByName, loadWorkflowIntoEditor } from "./generate-tab.js";
+
+const API = {
+    root:        () => `/wfm/gallery/style-catalog/root`,
+    folders:     (root)   => `/wfm/gallery/folders?root=${encodeURIComponent(root)}`,
+    images:      (params) => `/wfm/gallery/images?${new URLSearchParams(params)}`,
+    thumb:       (path, w = 200) => `/wfm/gallery/image/thumb?path=${encodeURIComponent(path)}&w=${w}`,
+    serveImage:  (path)   => `/wfm/gallery/image/serve?path=${encodeURIComponent(path)}`,
+    workflow:    (path)   => `/wfm/gallery/image/workflow?path=${encodeURIComponent(path)}`,
+};
+
+const state = {
+    root: null,
+    currentFolder: null,
+    search: "",
+    images: [],
+    selectedImage: null,
+};
+
+let _initialized = false;
+
+async function apiFetch(url, opts = {}) {
+    const res = await fetch(url, opts);
+    if (!res.ok) throw new Error(`HTTP ${res.status}`);
+    return res.json();
+}
+
+function debounce(fn, wait) {
+    let timer;
+    return (...args) => {
+        clearTimeout(timer);
+        timer = setTimeout(() => fn(...args), wait);
+    };
+}
+
+// ── 初期化 ────────────────────────────────────────────────────
+
+export function initStyleCatalogTab() {
+    document.getElementById("wfm-stylecatalog-refresh-btn")?.addEventListener("click", () => {
+        loadFolderTree();
+        loadImages();
+    });
+
+    setupSearchClearBtn("wfm-stylecatalog-search", "wfm-stylecatalog-search-clear-btn", () => {
+        state.search = "";
+        loadImages();
+    });
+
+    const searchInput = document.getElementById("wfm-stylecatalog-search");
+    searchInput?.addEventListener("input", debounce(() => {
+        state.search = searchInput.value.trim();
+        loadImages();
+    }, 300));
+
+    document.getElementById("wfm-stylecatalog-copy-positive-btn")?.addEventListener("click", () => copyText("wfm-stylecatalog-positive-text"));
+    document.getElementById("wfm-stylecatalog-copy-negative-btn")?.addEventListener("click", () => copyText("wfm-stylecatalog-negative-text"));
+    document.getElementById("wfm-stylecatalog-select-style-btn")?.addEventListener("click", onSelectStyleClick);
+    document.getElementById("wfm-stylecatalog-load-genui-btn")?.addEventListener("click", onLoadGenUIClick);
+    document.getElementById("wfm-stylecatalog-open-metadata-btn")?.addEventListener("click", onOpenMetadataClick);
+}
+
+export async function activateStyleCatalogTab() {
+    if (_initialized) return;
+    _initialized = true;
+    try {
+        const data = await apiFetch(API.root());
+        state.root = data.root;
+        await loadFolderTree();
+    } catch (e) {
+        const tree = document.getElementById("wfm-stylecatalog-tree");
+        if (tree) tree.innerHTML = `<p class="wfm-placeholder">Error: ${escapeHtml(e.message)}</p>`;
+    }
+}
+
+// ── フォルダツリー ────────────────────────────────────────────
+
+async function loadFolderTree() {
+    if (!state.root) return;
+    const tree = document.getElementById("wfm-stylecatalog-tree");
+    tree.innerHTML = `<p class="wfm-placeholder">${t("loading")}</p>`;
+    try {
+        const data = await apiFetch(API.folders(state.root));
+        if (data.error) {
+            tree.innerHTML = `<p class="wfm-placeholder">${escapeHtml(data.error)}</p>`;
+            return;
+        }
+        tree.innerHTML = "";
+        renderTreeNode(data, tree, 0, true);
+        const firstLabel = tree.querySelector(".wfm-gallery-tree-label");
+        if (firstLabel) firstLabel.click();
+    } catch (e) {
+        tree.innerHTML = `<p class="wfm-placeholder">Error: ${escapeHtml(e.message)}</p>`;
+    }
+}
+
+function renderTreeNode(node, container, depth, isRoot) {
+    const item = document.createElement("div");
+    item.className = "wfm-gallery-tree-item";
+    item.style.paddingLeft = `${depth * 12}px`;
+    item.dataset.path = node.abs_path;
+
+    const hasChildren = node.children && node.children.length > 0;
+    const absPath = node.abs_path;
+
+    const arrow = document.createElement("span");
+    arrow.className = "wfm-gallery-tree-arrow";
+    if (hasChildren) {
+        arrow.textContent = "▶";
+        arrow.dataset.expanded = "false";
+    } else {
+        arrow.textContent = " ";
+        arrow.style.visibility = "hidden";
+    }
+    item.appendChild(arrow);
+
+    const label = document.createElement("span");
+    label.className = "wfm-gallery-tree-label";
+    label.textContent = isRoot ? "[root]" : node.name;
+    const totalCount = node.image_count_total ?? node.image_count;
+    if (totalCount > 0) {
+        const badge = document.createElement("span");
+        badge.className = "wfm-gallery-tree-count";
+        badge.textContent = totalCount;
+        label.appendChild(badge);
+    }
+    item.appendChild(label);
+
+    label.addEventListener("click", () => {
+        document.querySelectorAll("#wfm-stylecatalog-tree .wfm-gallery-tree-item.selected").forEach(el => el.classList.remove("selected"));
+        item.classList.add("selected");
+        state.currentFolder = absPath;
+        loadImages();
+    });
+
+    if (hasChildren) {
+        const childContainer = document.createElement("div");
+        childContainer.className = "wfm-gallery-tree-children";
+        childContainer.style.display = "none";
+
+        arrow.addEventListener("click", (e) => {
+            e.stopPropagation();
+            const expanded = arrow.dataset.expanded === "true";
+            if (!expanded) {
+                arrow.dataset.expanded = "true";
+                arrow.textContent = "▼";
+                childContainer.style.display = "";
+                if (childContainer.children.length === 0) {
+                    node.children.forEach(child => renderTreeNode(child, childContainer, depth + 1, false));
+                }
+            } else {
+                arrow.dataset.expanded = "false";
+                arrow.textContent = "▶";
+                childContainer.style.display = "none";
+            }
+        });
+
+        container.appendChild(item);
+        container.appendChild(childContainer);
+    } else {
+        container.appendChild(item);
+    }
+}
+
+// ── 画像一覧 ─────────────────────────────────────────────────
+
+async function loadImages() {
+    if (!state.currentFolder) return;
+    const grid = document.getElementById("wfm-stylecatalog-grid");
+    grid.innerHTML = `<p class="wfm-placeholder">${t("loading")}</p>`;
+
+    // 上位フォルダを選択した場合もサブフォルダの画像をまとめて表示する
+    const params = { folder: state.currentFolder, sort: "name_asc", recursive: "true" };
+    if (state.search) params.search = state.search;
+
+    try {
+        const data = await apiFetch(API.images(params));
+        state.images = data.images || [];
+        document.getElementById("wfm-stylecatalog-count").textContent = `${state.images.length} images`;
+        renderImages();
+    } catch (e) {
+        grid.innerHTML = `<p class="wfm-placeholder">Error: ${escapeHtml(e.message)}</p>`;
+    }
+}
+
+function renderImages() {
+    const grid = document.getElementById("wfm-stylecatalog-grid");
+    if (state.images.length === 0) {
+        grid.innerHTML = `<p class="wfm-placeholder">${t("galleryNoImages")}</p>`;
+        return;
+    }
+    grid.innerHTML = "";
+    const fragment = document.createDocumentFragment();
+    state.images.forEach(img => fragment.appendChild(createThumbCard(img)));
+    grid.appendChild(fragment);
+}
+
+function createThumbCard(img) {
+    const card = document.createElement("div");
+    card.className = "wfm-gallery-thumb-card";
+    card.title = img.filename;
+    card.dataset.path = img.path;
+    if (state.selectedImage && state.selectedImage.path === img.path) {
+        card.classList.add("selected");
+    }
+
+    const imgEl = document.createElement("img");
+    imgEl.className = "wfm-gallery-thumb-img";
+    imgEl.loading = "lazy";
+    imgEl.src = API.thumb(img.path);
+    imgEl.alt = img.filename;
+    imgEl.onerror = () => {
+        imgEl.style.display = "none";
+        const placeholder = document.createElement("div");
+        placeholder.className = "wfm-gallery-thumb-placeholder";
+        placeholder.textContent = "?";
+        card.insertBefore(placeholder, imgEl.nextSibling);
+    };
+    card.appendChild(imgEl);
+
+    card.addEventListener("click", () => selectImage(img));
+    card.addEventListener("dblclick", () => openLightbox(img));
+
+    return card;
+}
+
+// ── 選択画像 / Positive・Negative表示 ─────────────────────────
+
+function styleNameFromFilename(filename) {
+    return filename.replace(/\.[^.]+$/, "");
+}
+
+async function selectImage(img) {
+    state.selectedImage = img;
+    document.querySelectorAll("#wfm-stylecatalog-grid .wfm-gallery-thumb-card").forEach(el => {
+        el.classList.toggle("selected", el.dataset.path === img.path);
+    });
+
+    document.getElementById("wfm-stylecatalog-selected-name").textContent = img.filename;
+    const preview = document.getElementById("wfm-stylecatalog-selected-preview");
+    preview.innerHTML = "";
+    const previewImg = document.createElement("img");
+    previewImg.src = API.serveImage(img.path);
+    previewImg.alt = img.filename;
+    previewImg.title = "Double-click to enlarge";
+    previewImg.style.cssText = "max-width:100%;max-height:100%;object-fit:contain;cursor:zoom-in;";
+    previewImg.addEventListener("dblclick", () => openLightbox(img));
+    preview.appendChild(previewImg);
+
+    const positiveText = document.getElementById("wfm-stylecatalog-positive-text");
+    const negativeText = document.getElementById("wfm-stylecatalog-negative-text");
+    const copyPositiveBtn = document.getElementById("wfm-stylecatalog-copy-positive-btn");
+    const copyNegativeBtn = document.getElementById("wfm-stylecatalog-copy-negative-btn");
+    const selectStyleBtn = document.getElementById("wfm-stylecatalog-select-style-btn");
+    const loadGenuiBtn = document.getElementById("wfm-stylecatalog-load-genui-btn");
+    const openMetadataBtn = document.getElementById("wfm-stylecatalog-open-metadata-btn");
+
+    positiveText.textContent = "";
+    negativeText.textContent = "";
+    copyPositiveBtn.disabled = true;
+    copyNegativeBtn.disabled = true;
+    selectStyleBtn.disabled = false; // ファイル名からのStyle選択はメタデータ抽出に依存しない
+    loadGenuiBtn.disabled = false;
+    openMetadataBtn.disabled = false;
+
+    try {
+        const res = await fetch(API.serveImage(img.path));
+        if (!res.ok) throw new Error(`HTTP ${res.status}`);
+        const blob = await res.blob();
+        const file = new File([blob], img.filename, { type: blob.type || "image/png" });
+        const meta = await extractAllMetadata(file);
+
+        const positive = meta?.positives?.[0] || "";
+        const negative = meta?.negatives?.[0] || "";
+
+        if (!positive && !negative) {
+            positiveText.textContent = t("stylecatalogNoPromptFound");
+        } else {
+            positiveText.textContent = positive;
+            negativeText.textContent = negative;
+            copyPositiveBtn.disabled = !positive;
+            copyNegativeBtn.disabled = !negative;
+        }
+    } catch (e) {
+        positiveText.textContent = t("stylecatalogNoPromptFound");
+    }
+}
+
+// gallery-tab.jsのライトボックスと同じCSSクラスを使う（ESCで閉じる処理もgallery-tab.js側の
+// グローバルkeydownリスナーが共通で担う）。
+function openLightbox(img) {
+    const overlay = document.createElement("div");
+    overlay.className = "wfm-gallery-lightbox";
+    overlay.innerHTML = `
+        <div class="wfm-gallery-lightbox-inner">
+            <img src="${API.serveImage(img.path)}" class="wfm-gallery-lightbox-img" alt="${escapeHtml(img.filename)}">
+            <div class="wfm-gallery-lightbox-footer">${escapeHtml(img.filename)}</div>
+            <button class="wfm-gallery-lightbox-close">&times;</button>
+        </div>
+    `;
+    overlay.addEventListener("click", (e) => {
+        if (e.target === overlay || e.target.classList.contains("wfm-gallery-lightbox-close")) {
+            overlay.remove();
+        }
+    });
+    document.body.appendChild(overlay);
+}
+
+function copyText(elementId) {
+    const el = document.getElementById(elementId);
+    const text = el?.textContent || "";
+    if (!text.trim()) return;
+    navigator.clipboard.writeText(text)
+        .then(() => showToast(t("imagePromptCopiedToast"), "success"))
+        .catch((e) => showToast(t("errorWithMsg", e.message), "error"));
+}
+
+function onSelectStyleClick() {
+    const img = state.selectedImage;
+    if (!img) return;
+    const name = styleNameFromFilename(img.filename);
+    const ok = selectStyleByName(name);
+    if (ok) {
+        showToast(t("stylecatalogStyleSelected", name), "success");
+    } else {
+        showToast(t("stylecatalogNoMatch"), "error");
+    }
+}
+
+// カタログ画像は生成元の出力画像と同一バイト列で保存されているため、埋め込みワークフローも
+// そのまま残っている。Outputフォルダ内の元画像を探す必要なく、この画像から直接読み込める。
+async function onLoadGenUIClick() {
+    const img = state.selectedImage;
+    if (!img) return;
+    try {
+        const data = await apiFetch(API.workflow(img.path));
+        if (!data.has_workflow) {
+            showToast(t("galleryNoEmbeddedWorkflow"), "warning");
+            return;
+        }
+        const loaded = await loadWorkflowIntoEditor(data.workflow, img.filename);
+        if (loaded !== false) {
+            document.querySelector('.wfm-tab[data-tab="generate"]')?.click();
+        }
+    } catch (e) {
+        showToast(t("errorWithMsg", e.message), "error");
+    }
+}
+
+async function onOpenMetadataClick() {
+    const img = state.selectedImage;
+    if (!img) return;
+    try {
+        const res = await fetch(API.serveImage(img.path));
+        if (!res.ok) throw new Error(`HTTP ${res.status}`);
+        const blob = await res.blob();
+        const file = new File([blob], img.filename, { type: blob.type || "image/png" });
+        await loadFileIntoMetadataTab(file);
+    } catch (e) {
+        showToast(t("errorWithMsg", e.message), "error");
+    }
+}
@@ -1,10 +1,16 @@
 /**
 * Tagger Tab
- * Handles WD Tagger / DeepDanbooru + Ollama VLM single/batch tagging.
+ * Handles WD Tagger / DeepDanbooru + VLM (Ollama/LM Studio/Lemonade/Unsloth) single/batch tagging.
 */

 import { t } from "./i18n.js";
 import { showToast } from "./app.js";
+import { openAiBackendSettingsModal, getAiBackendConfig } from "./ai-settings-modal.js";
+
+const TAGGER_AI_KEY = "wfm_tagger_ai_settings";
+function getTaggerAiConfig() {
+    return getAiBackendConfig(TAGGER_AI_KEY);
+}

 // ── 状態 ────────────────────────────────────────────────────────

@@ -32,7 +38,7 @@ export function initTaggerTab() {
    _setupBatchActions();
    _setupDbActions();
    _loadModels();
-    _loadSettings();
+    _updateVlmBackendIndicators();
 }

 /** GalleryタブからTaggerタブへ画像を渡す */
@@ -74,8 +80,6 @@ function _applyI18n() {
        "wfm-tagger-char-threshold-label": "taggerCharThreshold",
        "wfm-tagger-generate-btn": "taggerGenerateTags",
        "wfm-tagger-ollama-header-label": "taggerOllamaEnable",
-        "wfm-tagger-ollama-url-label": "taggerOllamaUrl",
-        "wfm-tagger-ollama-model-label": "taggerOllamaModel",
        "wfm-tagger-ollama-prompt-label": "taggerOllamaPrompt",
        "wfm-tagger-ollama-max-label": "taggerOllamaMaxTags",
        "wfm-tagger-result-header": "taggerResult",
@@ -87,8 +91,7 @@ function _applyI18n() {
        "wfm-tagger-batch-folder-header": "taggerBatchFolder",
        "wfm-tagger-batch-threshold-label": "taggerThreshold",
        "wfm-tagger-batch-char-threshold-label": "taggerCharThreshold",
-        "wfm-tagger-batch-url-label": "taggerOllamaUrl",
-        "wfm-tagger-batch-model-label": "taggerOllamaModel",
+        "wfm-tagger-batch-ollama-header-label": "taggerOllamaEnable",
        "wfm-tagger-batch-prompt-label": "taggerOllamaPrompt",
        "wfm-tagger-batch-output-header": "taggerBatchOutput",
        "wfm-tagger-batch-save-db-label": "taggerSaveToDB",
@@ -107,12 +110,18 @@ function _applyI18n() {
        "wfm-tagger-db-edit-vlm-label": "taggerDbVlm",
        "wfm-tagger-db-save-btn": "taggerDbSave",
        "wfm-tagger-db-delete-btn": "taggerDbDelete",
+        "wfm-tagger-db-delete-selected-btn": "taggerDbDelete"
    };
    for (const [id, key] of Object.entries(map)) {
        const el = document.getElementById(id);
        if (el) el.textContent = t(key);
    }

+    ["wfm-tagger-ollama-settings-btn", "wfm-tagger-batch-ollama-settings-btn"].forEach(id => {
+        const el = document.getElementById(id);
+        if (el) el.title = t("settings");
+    });
+
    // サブタブボタン
    const subtabKeys = ["taggerSingleTab", "taggerBatchTab", "taggerDbTab"];
    document.querySelectorAll(".wfm-tagger-subtab-btn").forEach((btn, i) => {
@@ -168,6 +177,24 @@ function _setupOllamaToggle() {
        });
        wrap.style.display = chk.checked ? "" : "none";
    }
+
+    document.getElementById("wfm-tagger-ollama-settings-btn")?.addEventListener("click", () => {
+        openAiBackendSettingsModal(TAGGER_AI_KEY, t("settings"), _updateVlmBackendIndicators);
+    });
+    document.getElementById("wfm-tagger-batch-ollama-settings-btn")?.addEventListener("click", () => {
+        openAiBackendSettingsModal(TAGGER_AI_KEY, t("settings"), _updateVlmBackendIndicators);
+    });
+}
+
+// ── VLMバックエンド表示 (Taggerタブ独自のAI設定を参照) ────────────
+
+function _updateVlmBackendIndicators() {
+    const { backend, model } = getTaggerAiConfig();
+    const label = `${backend}: ${model || t("taggerNoModel")}`;
+    const singleEl = document.getElementById("wfm-tagger-ollama-backend-value");
+    if (singleEl) singleEl.textContent = label;
+    const batchEl = document.getElementById("wfm-tagger-batch-backend-value");
+    if (batchEl) batchEl.textContent = label;
 }

 // ── モデル一覧ロード ─────────────────────────────────────────────
@@ -188,61 +215,6 @@ async function _loadModels() {
    }
 }

-// ── Ollamaモデル一覧ロード ───────────────────────────────────────
-
-async function _loadOllamaModels(urlId, selId) {
-    const urlEl = document.getElementById(urlId);
-    const selEl = document.getElementById(selId);
-    if (!urlEl || !selEl) return;
-    const api = urlEl.value || "http://127.0.0.1:11434";
-    try {
-        const res = await fetch(`/wfm/tagger/ollama/models?api_url=${encodeURIComponent(api)}`);
-        const data = await res.json();
-        const models = data.models || [];
-        if (models.length === 0) {
-            selEl.innerHTML = `<option value="">(${t("taggerNoModel")})</option>`;
-        } else {
-            selEl.innerHTML = models.map(m => `<option value="${m}">${m}</option>`).join("");
-        }
-    } catch {
-        selEl.innerHTML = `<option value="">(${t("taggerNoModel")})</option>`;
-    }
-}
-
-// ── 設定の読み込み/保存 ─────────────────────────────────────────
-
-async function _loadSettings() {
-    try {
-        const res = await fetch("/wfm/tagger/settings");
-        const data = await res.json();
-        if (data.ollama_url) {
-            const el = document.getElementById("wfm-tagger-ollama-url");
-            if (el) el.value = data.ollama_url;
-        }
-        if (data.batch_ollama_url) {
-            const el = document.getElementById("wfm-tagger-batch-ollama-url");
-            if (el) el.value = data.batch_ollama_url;
-        }
-    } catch {
-        // 初回は無視
-    }
-}
-
-async function _saveSettings() {
-    try {
-        await fetch("/wfm/tagger/settings", {
-            method: "POST",
-            headers: { "Content-Type": "application/json" },
-            body: JSON.stringify({
-                ollama_url: document.getElementById("wfm-tagger-ollama-url")?.value || "",
-                batch_ollama_url: document.getElementById("wfm-tagger-batch-ollama-url")?.value || "",
-            }),
-        });
-    } catch {
-        // サイレントに失敗
-    }
-}
-
 // ── Single サブタブ ─────────────────────────────────────────────

 function _setupSingleActions() {
@@ -279,11 +251,6 @@ function _setupSingleActions() {
    // タグ生成
    document.getElementById("wfm-tagger-generate-btn")?.addEventListener("click", _generateTags);

-    // Ollamaリフレッシュ
-    document.getElementById("wfm-tagger-ollama-refresh-btn")?.addEventListener("click", () => {
-        _loadOllamaModels("wfm-tagger-ollama-url", "wfm-tagger-ollama-model");
-    });
-
    // 結果アクション
    document.getElementById("wfm-tagger-send-genui-btn")?.addEventListener("click", _sendToGenUI);
    document.getElementById("wfm-tagger-send-prompt-btn")?.addEventListener("click", _sendToPrompt);
@@ -321,8 +288,7 @@ async function _generateTags() {
    const threshold = parseFloat(document.getElementById("wfm-tagger-threshold")?.value || "0.35");
    const charThreshold = parseFloat(document.getElementById("wfm-tagger-char-threshold")?.value || "0.85");
    const useOllama = document.getElementById("wfm-tagger-ollama-enable")?.checked || false;
-    const ollamaUrl = document.getElementById("wfm-tagger-ollama-url")?.value || "http://127.0.0.1:11434";
-    const ollamaModel = document.getElementById("wfm-tagger-ollama-model")?.value || "";
+    const { backend: vlmBackend, url: vlmUrl, model: ollamaModel, thinkingMode, maxTokens } = getTaggerAiConfig();
    const ollamaPrompt = document.getElementById("wfm-tagger-ollama-prompt")?.value || "";
    const maxTags = parseInt(document.getElementById("wfm-tagger-ollama-max-tags")?.value || "40");

@@ -344,12 +310,13 @@ async function _generateTags() {
        }

        if (useOllama && ollamaModel) {
-            const res2 = await fetch("/wfm/tagger/ollama/predict", {
+            const res2 = await fetch("/wfm/tagger/vlm/predict", {
                method: "POST",
                headers: { "Content-Type": "application/json" },
                body: JSON.stringify({
-                    image_b64: state.imageB64, api_url: ollamaUrl,
+                    image_b64: state.imageB64, backend: vlmBackend, api_url: vlmUrl,
                    model: ollamaModel, prompt: ollamaPrompt, max_tags: maxTags,
+                    thinking_mode: thinkingMode, max_tokens: maxTokens,
                }),
            });
            const data2 = await res2.json();
@@ -361,7 +328,6 @@ async function _generateTags() {
        if (!tags) { showToast(t("taggerNoTags"), "warning"); return; }
        document.getElementById("wfm-tagger-result").value = tags;
        showToast(t("taggerDone"), "success");
-        _saveSettings();
    } catch (e) {
        showToast(e.message, "error");
    } finally {
@@ -453,10 +419,6 @@ async function _saveToDb() {
 // ── Batch サブタブ ───────────────────────────────────────────────

 function _setupBatchActions() {
-    document.getElementById("wfm-tagger-batch-ollama-refresh-btn")?.addEventListener("click", () => {
-        _loadOllamaModels("wfm-tagger-batch-ollama-url", "wfm-tagger-batch-ollama-model");
-    });
-
    document.getElementById("wfm-tagger-batch-start-btn")?.addEventListener("click", _batchStart);
    document.getElementById("wfm-tagger-batch-stop-btn")?.addEventListener("click", _batchStop);
 }
@@ -465,15 +427,19 @@ async function _batchStart() {
    const folder = document.getElementById("wfm-tagger-batch-folder")?.value || "";
    if (!folder) { showToast(t("taggerBatchFolder"), "warning"); return; }

+    const { backend: vlmBackend, url: vlmUrl, model: vlmModel, thinkingMode, maxTokens } = getTaggerAiConfig();
    const body = {
        folder,
        model: document.getElementById("wfm-tagger-batch-model")?.value || "",
        threshold: parseFloat(document.getElementById("wfm-tagger-batch-threshold")?.value || "0.35"),
        char_threshold: parseFloat(document.getElementById("wfm-tagger-batch-char-threshold")?.value || "0.85"),
        use_ollama: document.getElementById("wfm-tagger-batch-ollama-enable")?.checked || false,
-        ollama_api: document.getElementById("wfm-tagger-batch-ollama-url")?.value || "http://127.0.0.1:11434",
-        ollama_model: document.getElementById("wfm-tagger-batch-ollama-model")?.value || "",
+        vlm_backend: vlmBackend,
+        vlm_api_url: vlmUrl,
+        ollama_model: vlmModel,
        ollama_prompt: document.getElementById("wfm-tagger-batch-ollama-prompt")?.value || "",
+        thinking_mode: thinkingMode,
+        max_tokens: maxTokens,
        save_db: document.getElementById("wfm-tagger-batch-save-db")?.checked ?? true,
        write_file: document.getElementById("wfm-tagger-batch-write-file")?.checked || false,
        write_txt: document.getElementById("wfm-tagger-batch-write-txt")?.checked || false,
@@ -549,6 +515,8 @@ function _setupDbActions() {
    });
    document.getElementById("wfm-tagger-db-save-btn")?.addEventListener("click", _dbSave);
    document.getElementById("wfm-tagger-db-delete-btn")?.addEventListener("click", _dbDelete);
+    document.getElementById("wfm-tagger-db-select").addEventListener("click", _dbToggleSelection);
+    document.getElementById("wfm-tagger-db-delete-selected-btn").addEventListener("click", _dbDeleteSelected);
 }

 async function _dbLoad() {
@@ -576,12 +544,20 @@ async function _dbSearch() {
 function _renderDbTable(rows) {
    const tbody = document.getElementById("wfm-tagger-db-tbody");
    if (!tbody) return;
+
    if (!rows.length) {
-        tbody.innerHTML = `<tr><td colspan="5" style="text-align:center;padding:20px;color:var(--wfm-text-secondary)">${t("taggerDbEmpty")}</td></tr>`;
+        tbody.innerHTML = `<tr><td colspan="6" style="text-align:center;padding:20px;color:var(--wfm-text-secondary)">${t("taggerDbEmpty")}</td></tr>`;
        return;
    }
+
    tbody.innerHTML = rows.map(row => `
        <tr data-id="${row.id}" title="${_esc(row.all_tags)}">
+            <td class="wfm-tagger-db-select">
+                <input
+                    type="checkbox"
+                    data-id="${row.id}"
+                >
+            </td>
            <td>${row.id}</td>
            <td>${_esc(row.filename)}</td>
            <td>${_esc(_truncate(row.interrogator_tags, 60))}</td>
@@ -591,9 +567,13 @@ function _renderDbTable(rows) {
    `).join("");

    tbody.querySelectorAll("tr").forEach(tr => {
-        tr.addEventListener("click", () => {
+        tr.addEventListener("click", e => {
+            // チェックボックスをクリックした場合は行選択を発生させない
+            if (e.target.closest(".wfm-tagger-db-select")) return;
+
            tbody.querySelectorAll("tr").forEach(r => r.classList.remove("selected"));
            tr.classList.add("selected");
+
            const row = rows.find(r => r.id === parseInt(tr.dataset.id));
            if (row) _openDbEdit(row);
        });
@@ -655,6 +635,55 @@ function _dbExport() {
    a.click();
 }

+async function _dbDeleteSelected() {
+    const ids = _getSelectedDbIds();
+
+    if (!ids.length) {
+        showToast(t("taggerDbNoSelection"), "warning");
+        return;
+    }
+
+    if (!confirm(t("taggerDbDeleteConfirm", ids.length))) {
+        return;
+    }
+
+    try {
+        const res = await fetch("/wfm/tagger/db", {
+            method: "DELETE",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify({ ids }),
+        });
+
+        const data = await res.json();
+
+        if (data.error) {
+            throw new Error(data.error);
+        }
+
+        showToast(t("taggerDbDeletedCount", data.count), "success");
+        _dbLoad();
+    } catch (e) {
+        showToast(e.message, "error");
+    }
+}
+
+function _getSelectedDbIds() {
+    return [...document.querySelectorAll(".wfm-tagger-db-select input:checked")]
+        .map(el => parseInt(el.dataset.id))
+        .filter(Number.isInteger);
+}
+
+function _dbToggleSelection(e) {
+    const checked = e.target.checked;
+    const checkboxes = document.querySelectorAll(
+        '#wfm-tagger-db-tbody input[type="checkbox"]'
+    );
+
+    checkboxes.forEach(checkbox => {
+        checkbox.checked = checked;
+    });
+}
+
 // ── ユーティリティ ───────────────────────────────────────────────

 function _esc(str) {
@@ -2,6 +2,76 @@
 * Shared utilities
 */

+// ============================================
+// PNG metadata embedding (iTXt chunk)
+// ============================================
+// Embeds an arbitrary key/UTF-8-text pair into a canvas-generated PNG data URL as
+// an iTXt chunk, inserted right after IHDR — same insertion point/CRC approach as
+// ComfyUI's own workflow-embedding (web/comfyui/top_menu_extension.js's
+// embedWorkflowInPng), but iTXt instead of tEXt so non-ASCII text (Japanese notes,
+// prompts, etc.) round-trips correctly through this codebase's PNG chunk reader
+// (metadata-tab.js's readAllPNGTextChunks already decodes iTXt text as UTF-8;
+// tEXt text there is decoded as Latin-1, which would mangle non-ASCII payloads).
+
+function _n2b(n) {
+    return new Uint8Array([(n >> 24) & 0xff, (n >> 16) & 0xff, (n >> 8) & 0xff, n & 0xff]);
+}
+
+function _joinBytes(...arrs) {
+    const result = new Uint8Array(arrs.reduce((total, a) => total + a.byteLength, 0));
+    arrs.reduce((offset, a) => { result.set(a, offset); return offset + a.byteLength; }, 0);
+    return result;
+}
+
+let _pngCrcTable = null;
+function _pngCrc32(data) {
+    if (!_pngCrcTable) {
+        _pngCrcTable = [];
+        for (let n = 0; n < 256; n++) {
+            let c = n;
+            for (let k = 0; k < 8; k++) c = c & 1 ? 0xedb88320 ^ (c >>> 1) : c >>> 1;
+            _pngCrcTable[n] = c;
+        }
+    }
+    let crc = 0 ^ -1;
+    for (let i = 0; i < data.byteLength; i++) crc = (crc >>> 8) ^ _pngCrcTable[(crc ^ data[i]) & 0xff];
+    return (crc ^ -1) >>> 0;
+}
+
+function _dataUrlToBytes(dataUrl) {
+    const binary = atob(dataUrl.slice(dataUrl.indexOf(",") + 1));
+    const bytes = new Uint8Array(binary.length);
+    for (let i = 0; i < binary.length; i++) bytes[i] = binary.charCodeAt(i);
+    return bytes;
+}
+
+function _bytesToDataUrl(bytes, mime) {
+    let binary = "";
+    const chunkSize = 0x8000;
+    for (let i = 0; i < bytes.length; i += chunkSize) {
+        binary += String.fromCharCode.apply(null, bytes.subarray(i, i + chunkSize));
+    }
+    return `data:${mime};base64,${btoa(binary)}`;
+}
+
+export function embedPngTextChunk(dataUrl, keyword, text) {
+    const bytes = _dataUrlToBytes(dataUrl);
+    const view = new DataView(bytes.buffer, bytes.byteOffset, bytes.byteLength);
+
+    const data = _joinBytes(
+        new TextEncoder().encode(`iTXt${keyword}`),
+        new Uint8Array([0, 0, 0, 0, 0]), // keyword-NUL, compression flag(0), compression method(0), empty lang tag+NUL, empty translated keyword+NUL
+        new TextEncoder().encode(text),
+    );
+    const chunk = _joinBytes(_n2b(data.byteLength - 4), data, _n2b(_pngCrc32(data)));
+
+    // Insert after IHDR (8-byte signature + 4-byte length + 4-byte type + IHDR data + 4-byte CRC)
+    const ihdrDataLen = view.getUint32(8);
+    const insertAt = ihdrDataLen + 20;
+    const result = _joinBytes(bytes.subarray(0, insertAt), chunk, bytes.subarray(insertAt));
+    return _bytesToDataUrl(result, "image/png");
+}
+
 // HTMLエスケープ（属性値・テキストコンテンツ両方で安全に使える）
 export function escapeHtml(s) {
    return String(s)
@@ -27,6 +97,107 @@ export function getSettings() {
    return readJsonStorage("wfm_settings");
 }

+// AIバックエンド(Ollama/LM Studio/Lemonade)ごとのデフォルトURL
+export const AI_BACKEND_DEFAULT_URLS = {
+    ollama: "http://localhost:11434",
+    lmstudio: "http://localhost:1234",
+    lemonade: "http://localhost:13305",
+    unsloth: "http://localhost:8888",
+};
+
+export function getAiBackendDefaultUrl(backend) {
+    return AI_BACKEND_DEFAULT_URLS[backend] || AI_BACKEND_DEFAULT_URLS.ollama;
+}
+
+// Unslothはローカルでも常にAPIキーが必要なため、フロントから直接叩かず
+// サーバー側プロキシ(/api/wfm/unsloth/proxy)経由でキーを付与して中継する
+// (see py/routes/unsloth_routes.py)
+export async function unslothProxy(baseUrl, path, method, payload) {
+    const res = await fetch("/api/wfm/unsloth/proxy", {
+        method: "POST",
+        headers: { "Content-Type": "application/json" },
+        body: JSON.stringify({ baseUrl, path, method, payload }),
+    });
+    const data = await res.json().catch(() => ({}));
+    if (!res.ok) throw new Error(data.message || `HTTP ${res.status}`);
+    return data;
+}
+
+// ローカルVLM/LLMバックエンドからモデルをVRAM/メモリからアンロードする。
+// 公式APIが存在しない場合(Unsloth)は "UNSUPPORTED" エラーを投げる。
+export async function unloadAiModel(url, backend, model) {
+    if (!model) throw new Error("No model selected");
+    if (backend === "ollama") {
+        // keep_alive:0 + 空プロンプトが公式に文書化されたアンロード方法
+        // (専用エンドポイントは存在しない) https://docs.ollama.com/api
+        const res = await fetch(`${url}/api/generate`, {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify({ model, prompt: "", keep_alive: 0 }),
+        });
+        if (!res.ok) throw new Error(`HTTP ${res.status}`);
+    } else if (backend === "lmstudio") {
+        const res = await fetch(`${url}/api/v1/models/unload`, {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify({ instance_id: model }),
+        });
+        if (!res.ok) throw new Error(`HTTP ${res.status}`);
+    } else if (backend === "lemonade") {
+        const res = await fetch(`${url}/api/v1/unload`, {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify({ model_name: model }),
+        });
+        if (!res.ok) throw new Error(`HTTP ${res.status}`);
+    } else {
+        throw new Error("UNSUPPORTED");
+    }
+}
+
+// ============================================
+// Eagle Auto-Save
+// ============================================
+
+export function getEagleSettings() {
+    const s = getSettings();
+    return {
+        url: s.eagleUrl || "http://localhost:41595",
+        autoSave: !!s.eagleAutoSave,
+    };
+}
+
+export async function saveToEagle(imageUrl, name, tags = [], fileInfo = null) {
+    const eagle = getEagleSettings();
+    if (!eagle.autoSave) return;
+    try {
+        const res = await fetch("/api/wfm/eagle/add", {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify({
+                eagleUrl: eagle.url,
+                url: imageUrl,
+                name,
+                tags: ["wfm-comfyui", ...tags],
+                // SVG はサーバー側でローカルパス解決(addFromPath)するために必要
+                filename: fileInfo?.filename || "",
+                subfolder: fileInfo?.subfolder || "",
+                type: fileInfo?.type || "output",
+                // comfyui-tosvg の Save SVG String など、絶対パスが既知の場合に渡す
+                localPath: fileInfo?.localPath || "",
+            }),
+        });
+        const data = await res.json();
+        if (data.status === "success") {
+            console.log("[Eagle] Saved:", name);
+        } else {
+            console.warn("[Eagle] Save failed:", data.message);
+        }
+    } catch (err) {
+        console.warn("[Eagle] Save error:", err.message);
+    }
+}
+
 /**
 * 検索inputにオーバーレイXボタンを設定する。
 * @param {string} inputId - 検索inputのID
@@ -0,0 +1,433 @@
+/**
+ * Video Tab - Asset subtab: browses the videos a Plan run has generated.
+ *
+ * Deliberately thin — it reuses Gallery's existing backend (groups, tags/memo
+ * sidecar, thumbnailing) exactly like feeder-tab.js's own Gallery mode does,
+ * rather than re-implementing folder browsing, bulk selection, etc. Anything
+ * beyond basic browsing/tagging (move, export, delete, multi-select) is left
+ * to the real Gallery tab via the "Open in Gallery" button.
+ */
+
+import { VIDEO_GROUP, VTEMP_GROUP, ensureVideoGroup, isVideoFile } from "./gallery-tab.js";
+import { setSourcePreview } from "./video-preview.js";
+import { showToast } from "./app.js";
+import { t } from "./i18n.js";
+import { addClipFromFile, setBgmFromFile } from "./video-edit-tab.js";
+import { setBlockImageFromFile } from "./video-plan-tab.js";
+
+// Sentinel for the "All Video Assets" option — not a real backend group, since
+// Gallery's group filter only ever matches one group at a time. Selecting it
+// fetches VIDEO_GROUP and VTEMP_GROUP separately and merges them (see _loadImages).
+const ALL_GROUPS_VALUE = "__video_asset_all__";
+
+// Display names are now identical to the underlying group names (minus the
+// "__...__" wrapping) — no more per-plan "VideoPlan:<name>" sub-groups, so the
+// dropdown is always exactly these three fixed entries.
+const _GROUPS = [ALL_GROUPS_VALUE, VIDEO_GROUP, VTEMP_GROUP];
+
+const _s = {
+    outputDir: "",
+    group: ALL_GROUPS_VALUE,
+    images: [],
+    selectedPath: null,
+    loaded: false, // becomes true once the Asset subtab has been shown at least once
+    searchQuery: "",
+    viewMode: "grid", // "grid" | "table"
+    kindFilter: "all", // "all" | "video" | "image"
+};
+
+function _formatDate(mtime) {
+    return new Date(mtime * 1000).toLocaleString();
+}
+
+function _filteredImages() {
+    const q = _s.searchQuery.trim().toLowerCase();
+    let list = _s.images;
+    if (_s.kindFilter === "video") list = list.filter((img) => isVideoFile(img));
+    else if (_s.kindFilter === "image") list = list.filter((img) => !isVideoFile(img));
+    if (q) list = list.filter((img) => img.filename.toLowerCase().includes(q));
+    return list;
+}
+
+async function _fetchOutputDir() {
+    if (_s.outputDir) return;
+    try {
+        const res = await fetch("/api/wfm/settings/output-dir");
+        if (res.ok) {
+            const data = await res.json();
+            _s.outputDir = (data.current || "").replace(/\\/g, "/").replace(/\/$/, "");
+        }
+    } catch { /* non-critical */ }
+}
+
+function _groupLabel(g) {
+    if (g === ALL_GROUPS_VALUE) return "All Video Assets";
+    if (g === VIDEO_GROUP) return "Video Assets";
+    if (g === VTEMP_GROUP) return "Video Temp";
+    return g;
+}
+
+function _renderGroupSelect() {
+    const sel = document.getElementById("wfm-video-asset-group");
+    if (!sel) return;
+    sel.innerHTML = _GROUPS
+        .map((g) => `<option value="${g}"${g === _s.group ? " selected" : ""}>${_groupLabel(g)}</option>`)
+        .join("");
+}
+
+async function _fetchGroupImages(group) {
+    const params = new URLSearchParams({ folder: _s.outputDir, group, recursive: "true", sort: "date_desc" });
+    const res = await fetch(`/wfm/gallery/images?${params}`);
+    if (!res.ok) throw new Error(String(res.status));
+    const data = await res.json();
+    return data.images || [];
+}
+
+async function _loadImages() {
+    const grid = document.getElementById("wfm-video-asset-grid");
+    const statusEl = document.getElementById("wfm-video-asset-status");
+    if (!grid) return;
+    await _fetchOutputDir();
+    if (!_s.outputDir) {
+        grid.innerHTML = `<div class="wfm-placeholder">No output folder configured</div>`;
+        return;
+    }
+    grid.innerHTML = `<div class="wfm-placeholder">Loading...</div>`;
+    try {
+        let images;
+        if (_s.group === ALL_GROUPS_VALUE) {
+            // "All Video Assets" = the union of the curated __Video Assets__
+            // group and __Video Temp__ (auto-populated by every plan run,
+            // organized into __Video Assets__ by the user on their own
+            // schedule) — not a single backend group filter, so fetch both
+            // and merge.
+            const [curated, temp] = await Promise.all([
+                _fetchGroupImages(VIDEO_GROUP),
+                _fetchGroupImages(VTEMP_GROUP),
+            ]);
+            const byPath = new Map();
+            for (const img of [...curated, ...temp]) byPath.set(img.path, img);
+            images = Array.from(byPath.values()).sort((a, b) => b.mtime - a.mtime);
+        } else {
+            images = await _fetchGroupImages(_s.group);
+        }
+        _s.images = images;
+        _renderList();
+        if (statusEl) statusEl.textContent = `${_s.images.length} video(s)`;
+    } catch (err) {
+        _s.images = [];
+        grid.innerHTML = `<div class="wfm-placeholder" style="color:var(--wfm-danger)">Load failed: ${err.message}</div>`;
+        if (statusEl) statusEl.textContent = "";
+    }
+}
+
+// Renders whichever of grid/table is active for the current viewMode — called
+// on load, on search input, and after switching view modes.
+function _renderList() {
+    if (_s.viewMode === "table") _renderTable();
+    else _renderGrid();
+}
+
+function _renderGrid() {
+    const grid = document.getElementById("wfm-video-asset-grid");
+    if (!grid) return;
+    const images = _filteredImages();
+    if (images.length === 0) {
+        grid.innerHTML = `<div class="wfm-placeholder">No videos yet</div>`;
+        return;
+    }
+    grid.innerHTML = "";
+    for (const img of images) grid.appendChild(_makeCard(img));
+}
+
+function _renderTable() {
+    const body = document.getElementById("wfm-video-asset-table-body");
+    if (!body) return;
+    const images = _filteredImages();
+    if (images.length === 0) {
+        body.innerHTML = `<tr><td colspan="3" class="wfm-placeholder">No videos yet</td></tr>`;
+        return;
+    }
+    body.innerHTML = "";
+    for (const img of images) body.appendChild(_makeRow(img));
+}
+
+function _makeRow(img) {
+    const row = document.createElement("tr");
+    row.className = "wfm-video-asset-row" + (img.path === _s.selectedPath ? " selected" : "");
+    row.dataset.path = img.path;
+
+    const nameCell = document.createElement("td");
+    nameCell.textContent = img.filename;
+    nameCell.title = img.filename;
+
+    const dateCell = document.createElement("td");
+    dateCell.textContent = _formatDate(img.mtime);
+
+    const tagsCell = document.createElement("td");
+    tagsCell.textContent = (img.tags || []).join(", ");
+
+    row.append(nameCell, dateCell, tagsCell);
+    row.addEventListener("click", () => _selectImage(img));
+    return row;
+}
+
+function _makeCard(img) {
+    const card = document.createElement("div");
+    card.className = "wfm-video-asset-card" + (img.path === _s.selectedPath ? " selected" : "");
+    card.dataset.path = img.path;
+
+    const thumb = document.createElement("img");
+    thumb.className = "wfm-video-asset-card-img";
+    thumb.loading = "lazy";
+    thumb.src = `/wfm/gallery/image/thumb?path=${encodeURIComponent(img.path)}&w=200`;
+    thumb.onerror = () => { thumb.style.display = "none"; };
+
+    const name = document.createElement("div");
+    name.className = "wfm-video-asset-card-name";
+    name.textContent = img.filename;
+    name.title = img.filename;
+
+    card.append(thumb, name);
+    card.addEventListener("click", () => _selectImage(img));
+    return card;
+}
+
+function _selectImage(img) {
+    _s.selectedPath = img.path;
+    document.querySelectorAll(".wfm-video-asset-card, .wfm-video-asset-row").forEach((c) => {
+        c.classList.toggle("selected", c.dataset.path === img.path);
+    });
+    _renderDetail(img);
+    _loadIntoSourcePreview(img);
+}
+
+// Feeds the selected asset's media into the center panel's Asset/Source preview
+// pane (see video-preview.js) so it's visible without switching tabs, and so the
+// Frame/GIF property tools can operate on it just like a Video Source drop.
+// Fetched as a Blob and wrapped as a "local" source rather than trying to map
+// Gallery's arbitrary absolute path onto ComfyUI's filename/subfolder/type
+// triple — that keeps the GIF tool's existing upload-on-first-use path working
+// unchanged for both cases. Still/animated images (this group isn't exclusively
+// videos — anything tagged into it shows up here) preview via the pane's <img>
+// companion element instead of trying to play them as a <video>.
+async function _loadIntoSourcePreview(img) {
+    try {
+        const res = await fetch(`/wfm/gallery/image/serve?path=${encodeURIComponent(img.path)}`);
+        if (!res.ok) throw new Error(String(res.status));
+        const blob = await res.blob();
+        const isVideo = isVideoFile(img);
+        const file = new File([blob], img.filename, { type: blob.type || (isVideo ? "video/mp4" : "image/png") });
+        setSourcePreview(URL.createObjectURL(file), { kind: "local", file }, isVideo ? "video" : "image");
+    } catch (err) {
+        console.warn("[VideoAsset] failed to load preview:", err);
+    }
+}
+
+function _renderDetail(img) {
+    const panel = document.getElementById("wfm-video-asset-detail");
+    if (!panel) return;
+    // Filename/memo are untrusted (filesystem names, user-entered text) — the
+    // markup skeleton is static, and those two values are assigned afterward
+    // via textContent/.value, never interpolated into the HTML string itself.
+    panel.innerHTML = `
+        <div class="wfm-video-asset-name" id="wfm-video-asset-name"></div>
+        <label>Tags</label>
+        <div class="wfm-video-asset-tags" id="wfm-video-asset-tags"></div>
+        <div style="display:flex;gap:6px;">
+            <input type="text" id="wfm-video-asset-tag-input" class="wfm-input" placeholder="Add tag" style="flex:1;">
+            <button type="button" class="wfm-btn wfm-btn-sm" id="wfm-video-asset-tag-add">Add</button>
+        </div>
+        <label style="margin-top:10px;">Memo</label>
+        <textarea id="wfm-video-asset-memo" class="wfm-textarea" rows="3"></textarea>
+        <button type="button" class="wfm-btn wfm-btn-sm" id="wfm-video-asset-memo-save" style="margin-top:6px;">Save Memo</button>
+        <button type="button" class="wfm-btn wfm-btn-sm" id="wfm-video-asset-send-to-edit" style="width:100%;margin-top:12px;">${t("videoEditSendToEdit")}</button>
+        <button type="button" class="wfm-btn wfm-btn-sm" id="wfm-video-asset-set-bgm" style="width:100%;margin-top:6px;display:${isVideoFile(img) ? "block" : "none"};">${t("videoAssetSetAsBgm")}</button>
+        <div id="wfm-video-asset-set-plan-image-row" style="display:${isVideoFile(img) ? "none" : "flex"};gap:6px;margin-top:6px;">
+            <button type="button" class="wfm-btn wfm-btn-sm" id="wfm-video-asset-set-first" style="flex:1;">${t("videoAssetSetAsFirst")}</button>
+            <button type="button" class="wfm-btn wfm-btn-sm" id="wfm-video-asset-set-last" style="flex:1;">${t("videoAssetSetAsLast")}</button>
+        </div>
+        <button type="button" class="wfm-btn wfm-btn-primary wfm-btn-sm" id="wfm-video-asset-open-gallery" style="width:100%;margin-top:6px;">Open in Gallery</button>
+    `;
+
+    const nameEl = document.getElementById("wfm-video-asset-name");
+    if (nameEl) { nameEl.textContent = img.filename; nameEl.title = img.filename; }
+    const memoEl = document.getElementById("wfm-video-asset-memo");
+    if (memoEl) memoEl.value = img.memo || "";
+
+    _renderTags(img);
+
+    panel.querySelector("#wfm-video-asset-tag-add")?.addEventListener("click", async () => {
+        const input = panel.querySelector("#wfm-video-asset-tag-input");
+        const tag = input?.value.trim();
+        if (!tag) return;
+        const tags = Array.from(new Set([...(img.tags || []), tag]));
+        await _saveMeta(img.path, { tags });
+        img.tags = tags;
+        input.value = "";
+        _renderTags(img);
+    });
+
+    panel.querySelector("#wfm-video-asset-memo-save")?.addEventListener("click", async () => {
+        const memo = panel.querySelector("#wfm-video-asset-memo")?.value || "";
+        await _saveMeta(img.path, { memo });
+        img.memo = memo;
+    });
+
+    panel.querySelector("#wfm-video-asset-send-to-edit")?.addEventListener("click", async () => {
+        try {
+            const res = await fetch(`/wfm/gallery/image/serve?path=${encodeURIComponent(img.path)}`);
+            if (!res.ok) throw new Error(String(res.status));
+            const blob = await res.blob();
+            const file = new File([blob], img.filename, { type: blob.type || (isVideoFile(img) ? "video/mp4" : "image/png") });
+            addClipFromFile(file, img.filename);
+            document.querySelector('.wfm-video-center-panel .wfm-video-subtab-btn[data-video-subtab="edit"]')?.click();
+            showToast(t("videoEditClipSent", img.filename), "success");
+        } catch (err) {
+            showToast(t("errorWithMsg", err.message), "error");
+        }
+    });
+
+    // Gallery lists no audio files, so a video asset's own audio track is the
+    // Asset-side way to pick a BGM (LoadAudio decodes audio from video files).
+    panel.querySelector("#wfm-video-asset-set-bgm")?.addEventListener("click", async () => {
+        try {
+            const res = await fetch(`/wfm/gallery/image/serve?path=${encodeURIComponent(img.path)}`);
+            if (!res.ok) throw new Error(String(res.status));
+            const blob = await res.blob();
+            const file = new File([blob], img.filename, { type: blob.type || "video/mp4" });
+            if (await setBgmFromFile(file, img.filename)) {
+                document.querySelector('.wfm-video-center-panel .wfm-video-subtab-btn[data-video-subtab="edit"]')?.click();
+                showToast(t("videoAssetSetAsBgmDone", img.filename), "success");
+            }
+        } catch (err) {
+            showToast(t("errorWithMsg", err.message), "error");
+        }
+    });
+
+    const setAsPlanImage = async (which) => {
+        try {
+            const res = await fetch(`/wfm/gallery/image/serve?path=${encodeURIComponent(img.path)}`);
+            if (!res.ok) throw new Error(String(res.status));
+            const blob = await res.blob();
+            const file = new File([blob], img.filename, { type: blob.type || "image/png" });
+            await setBlockImageFromFile(which, file);
+            document.querySelector('.wfm-video-center-panel .wfm-video-subtab-btn[data-video-subtab="plan"]')?.click();
+            showToast(t(which === "first" ? "videoAssetSetAsFirstDone" : "videoAssetSetAsLastDone", img.filename), "success");
+        } catch (err) {
+            showToast(t("errorWithMsg", err.message), "error");
+        }
+    };
+    panel.querySelector("#wfm-video-asset-set-first")?.addEventListener("click", () => setAsPlanImage("first"));
+    panel.querySelector("#wfm-video-asset-set-last")?.addEventListener("click", () => setAsPlanImage("last"));
+
+    panel.querySelector("#wfm-video-asset-open-gallery")?.addEventListener("click", () => {
+        document.querySelector('.wfm-tab[data-tab="gallery"]')?.click();
+        const filterSel = document.getElementById("wfm-gallery-group-filter");
+        if (filterSel) {
+            // ALL_GROUPS_VALUE is a virtual union with no Gallery-side equivalent
+            // (Gallery's own filter only ever matches one real group) — fall back
+            // to the curated group, the closer of the two to "everything worth keeping".
+            filterSel.value = _s.group === ALL_GROUPS_VALUE ? VIDEO_GROUP : _s.group;
+            filterSel.dispatchEvent(new Event("change"));
+        }
+    });
+}
+
+function _renderTags(img) {
+    const container = document.getElementById("wfm-video-asset-tags");
+    if (!container) return;
+    const tags = img.tags || [];
+    container.innerHTML = "";
+    if (tags.length === 0) {
+        const placeholder = document.createElement("span");
+        placeholder.className = "wfm-placeholder";
+        placeholder.textContent = "No tags";
+        container.appendChild(placeholder);
+        return;
+    }
+    // Built via DOM APIs (not innerHTML) since tag text is user-entered —
+    // textContent keeps it inert regardless of what characters it contains.
+    for (const tag of tags) {
+        const pill = document.createElement("span");
+        pill.className = "wfm-video-asset-tag";
+        pill.append(document.createTextNode(`${tag} `));
+
+        const removeBtn = document.createElement("button");
+        removeBtn.type = "button";
+        removeBtn.textContent = "×";
+        removeBtn.addEventListener("click", async () => {
+            const newTags = tags.filter((t2) => t2 !== tag);
+            await _saveMeta(img.path, { tags: newTags });
+            img.tags = newTags;
+            _renderTags(img);
+        });
+
+        pill.appendChild(removeBtn);
+        container.appendChild(pill);
+    }
+}
+
+async function _saveMeta(path, data) {
+    try {
+        await fetch("/wfm/gallery/image/meta", {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify({ path, ...data }),
+        });
+    } catch (err) {
+        console.warn("[VideoAsset] saveMeta failed:", err);
+    }
+}
+
+// Called whenever the Asset subtab becomes active (see video-tab.js's subtab
+// toggle) — always refetches rather than caching, so a Plan run's newly
+// generated videos show up as soon as the user switches over to look.
+export async function refreshVideoAssetTab() {
+    if (!_s.loaded) {
+        _renderGroupSelect();
+        _s.loaded = true;
+    }
+    await _loadImages();
+}
+
+function _setViewMode(mode) {
+    _s.viewMode = mode;
+    document.getElementById("wfm-video-asset-view-grid")?.classList.toggle("active", mode === "grid");
+    document.getElementById("wfm-video-asset-view-table")?.classList.toggle("active", mode === "table");
+    const grid = document.getElementById("wfm-video-asset-grid");
+    const tableWrap = document.getElementById("wfm-video-asset-table-wrap");
+    if (grid) grid.style.display = mode === "grid" ? "" : "none";
+    if (tableWrap) tableWrap.style.display = mode === "table" ? "" : "none";
+    _renderList();
+}
+
+export function initVideoAssetTab() {
+    document.getElementById("wfm-video-asset-group")?.addEventListener("change", (e) => {
+        _s.group = e.target.value;
+        _s.selectedPath = null;
+        const panel = document.getElementById("wfm-video-asset-detail");
+        if (panel) panel.innerHTML = `<span class="wfm-placeholder">Select a video</span>`;
+        _loadImages();
+    });
+    document.getElementById("wfm-video-asset-refresh")?.addEventListener("click", () => _loadImages());
+    document.getElementById("wfm-video-asset-kind")?.addEventListener("change", (e) => {
+        _s.kindFilter = e.target.value;
+        _renderList();
+    });
+    document.getElementById("wfm-video-asset-search")?.addEventListener("input", (e) => {
+        _s.searchQuery = e.target.value;
+        _renderList();
+    });
+    document.getElementById("wfm-video-asset-view-grid")?.addEventListener("click", () => _setViewMode("grid"));
+    document.getElementById("wfm-video-asset-view-table")?.addEventListener("click", () => _setViewMode("table"));
+
+    // Neither reserved group is ever auto-created by a batch run itself (see
+    // video-plan-tab.js's _ensureVideoAssetGroups, which only ensures
+    // __Video Temp__ right before a run starts), so a fresh install or a group
+    // deleted via Gallery's Manage Groups would otherwise never come back on
+    // its own — add_to_group() happily records membership on individual images
+    // without ever re-registering the group itself. ensureVideoGroup() ensures
+    // both __Video Assets__ and __Video Temp__ every time the Asset subtab inits.
+    ensureVideoGroup();
+}
@@ -0,0 +1,126 @@
+/**
+ * Video Tab - shared state for the two center-panel preview panes:
+ * "source" (#wfm-video-source-preview-video — an Asset selection or a
+ * locally-dropped file) and "result" (#wfm-video-preview-video — the latest
+ * generated clip). video-asset-tab.js (Asset selection), video-plan-tab.js
+ * (batch run results) and video-tab.js (the Video Source drop zone, Frame/GIF
+ * tools) all need to read or write these. Pulling this into its own module
+ * lets all three depend on it without needing to import each other —
+ * video-tab.js already imports both of the others for init/refresh, so a
+ * reverse import from either back into video-tab.js would create a cycle.
+ *
+ * Each pane also has a companion <img> element (wfm-video-*-preview-img) so a
+ * still/animated image (from Asset or a Video Source drop) can be previewed
+ * without forcing it through a <video> tag, which can't render image formats
+ * at all. mediaType controls which element is shown; Frame/GIF's
+ * getActivePreviewVideoElement() returns null while a pane is showing an
+ * image, since those tools only make sense against real video.
+ */
+
+const _PANES = {
+    source: { frame: "wfm-video-source-preview-frame", video: "wfm-video-source-preview-video", img: "wfm-video-source-preview-img", placeholder: "wfm-video-source-preview-placeholder" },
+    result: { frame: "wfm-video-preview-frame", video: "wfm-video-preview-video", img: "wfm-video-preview-img", placeholder: "wfm-video-preview-placeholder" },
+};
+
+const _objectUrls = { source: null, result: null };
+
+// Whichever pane most recently received media is what the Frame/GIF property
+// tabs act on (see getActivePreviewSource/getActivePreviewVideoElement below) —
+// an Asset selection or Video Source drop activates "source", a batch run
+// finishing a block (or the Edit tab's export/preview) activates "result".
+let _activePane = null; // "source" | "result" | null
+let _activeSource = null;
+let _activeMediaType = null; // "video" | "image" | null — mirrors _activePane's current content
+
+function _setPreview(pane, url, source, mediaType = "video") {
+    const ids = _PANES[pane];
+    const video = document.getElementById(ids.video);
+    const img = document.getElementById(ids.img);
+    const placeholder = document.getElementById(ids.placeholder);
+    if (!video || !placeholder) return;
+
+    if (_objectUrls[pane]) {
+        URL.revokeObjectURL(_objectUrls[pane]);
+        _objectUrls[pane] = null;
+    }
+    if (url && url.startsWith("blob:")) _objectUrls[pane] = url;
+
+    if (url) {
+        if (mediaType === "image") {
+            video.pause();
+            video.removeAttribute("src");
+            video.load();
+            video.style.display = "none";
+            if (img) { img.src = url; img.style.display = "block"; }
+        } else {
+            if (img) { img.removeAttribute("src"); img.style.display = "none"; }
+            video.src = url;
+            video.style.display = "block";
+        }
+        placeholder.style.display = "none";
+        _activePane = pane;
+        _activeSource = source;
+        _activeMediaType = mediaType;
+    } else {
+        video.pause();
+        video.removeAttribute("src");
+        video.load();
+        video.style.display = "none";
+        if (img) { img.removeAttribute("src"); img.style.display = "none"; }
+        placeholder.style.display = "";
+        if (_activePane === pane) { _activePane = null; _activeSource = null; _activeMediaType = null; }
+    }
+}
+
+// Sets (or clears, with url=null) the Asset-selection/Video-Source-drop pane.
+// mediaType: "video" (default) or "image".
+export function setSourcePreview(url, source, mediaType = "video") { _setPreview("source", url, source, mediaType); }
+
+// Sets (or clears) the generated-result pane — called once per block as a
+// batch run's video output comes in, and by the Edit tab's timeline preview
+// (which may show either a video clip or a held still image).
+export function setResultPreview(url, source, mediaType = "video") { _setPreview("result", url, source, mediaType); }
+
+// What the Frame/GIF property tabs operate on: { kind: "output"|"input", filename,
+// subfolder, type } for anything already on the server, or { kind: "local", file }
+// for a picked/dropped file not yet uploaded. null if neither pane has media.
+export function getActivePreviewSource() { return _activeSource; }
+
+// The GIF tab uploads a still-local source on first use and needs to remember
+// the resulting server-side reference so a repeat conversion doesn't re-upload —
+// this rewrites the active source in place without touching either <video> element.
+export function updateActivePreviewSourceRef(source) { _activeSource = source; }
+
+// The <video> element the Frame/GIF tools should read/capture from, or null if
+// neither pane currently has a video loaded (including when the active pane is
+// showing a still image instead).
+export function getActivePreviewVideoElement() {
+    if (!_activePane || _activeMediaType === "image") return null;
+    return document.getElementById(_PANES[_activePane].video);
+}
+
+// Both panes' <video> elements share the same persistent volume setting.
+export function getAllPreviewVideoElements() {
+    return Object.values(_PANES).map((ids) => document.getElementById(ids.video)).filter(Boolean);
+}
+
+// Direct access to the "result" pane's <video> element — used by
+// video-edit-tab.js's timeline preview, which needs to drive playback
+// (seek to a clip's trim-in, listen for the trim-out point, swap to the
+// next clip) rather than just set a src via setResultPreview().
+export function getResultPreviewVideoElement() {
+    return document.getElementById(_PANES.result.video);
+}
+
+// The frame/<video>/<img> elements of one pane ("source" | "result") — used by
+// video-edit-tab.js to position its text-overlay preview layer over whichever
+// media element is currently showing in that pane.
+export function getPreviewPaneElements(pane) {
+    const ids = _PANES[pane];
+    if (!ids) return null;
+    return {
+        frame: document.getElementById(ids.frame),
+        video: document.getElementById(ids.video),
+        img: document.getElementById(ids.img),
+    };
+}
@@ -0,0 +1,175 @@
+/**
+ * Video Tab - Sidebar "Project" subtab (next to Asset): browses saved Video
+ * Plan files (ws_videoplan_*.json in video_plan/) OR saved Video Edit
+ * projects (ws_videoeditproj_*.json in video_edit_project/), depending on
+ * which center subtab (Plan/Edit) is currently active — video-tab.js passes
+ * that mode in on every refresh (Asset stays on whichever of the two was
+ * last active, since it has no saved-list concept of its own).
+ *
+ * Deliberately thin, mirroring video-asset-tab.js's own scope — clicking an
+ * item hands off to video-plan-tab.js's openSavedVideoPlan() or
+ * video-edit-tab.js's openSavedVideoEditProject() rather than
+ * re-implementing plan/project loading here.
+ */
+
+import { showToast } from "./app.js";
+import { t } from "./i18n.js";
+import { escapeHtml } from "./util.js";
+import { openSavedVideoPlan } from "./video-plan-tab.js";
+import { openSavedVideoEditProject } from "./video-edit-tab.js";
+
+// Per-mode config: which endpoints to hit, which loader/toast strings to use,
+// and how to read each item's count field — keeps _renderList/_makeItem/etc.
+// mode-agnostic instead of branching throughout.
+const _MODES = {
+    plan: {
+        listUrl: "/api/wfm/video/plans",
+        deleteUrl: "/api/wfm/video/plans/delete",
+        open: (filename) => openSavedVideoPlan(filename),
+        countOf: (item) => item.block_count ?? 0,
+        countLabel: (n) => t("videoProjectBlockCount", n),
+        hintKey: "videoProjectHint",
+        emptyKey: "videoProjectEmpty",
+        deleteConfirmKey: "videoProjectDeleteConfirm",
+        deletedKey: "videoProjectDeleted",
+        deleteFailedKey: "videoProjectDeleteFailed",
+        loadListFailedKey: "videoProjectLoadListFailed",
+    },
+    edit: {
+        listUrl: "/api/wfm/video/edit/projects",
+        deleteUrl: "/api/wfm/video/edit/projects/delete",
+        open: (filename) => openSavedVideoEditProject(filename),
+        countOf: (item) => item.clip_count ?? 0,
+        countLabel: (n) => t("videoEditProjectClipCount", n),
+        hintKey: "videoEditProjectHint",
+        emptyKey: "videoEditProjectEmpty",
+        deleteConfirmKey: "videoEditProjectDeleteConfirm",
+        deletedKey: "videoEditProjectDeleted",
+        deleteFailedKey: "videoEditProjectDeleteFailed",
+        loadListFailedKey: "videoEditProjectLoadListFailed",
+    },
+};
+
+const _s = {
+    mode: "plan",
+    plans: [],
+    activeFilename: null,
+    loaded: false, // becomes true once the Project subtab has been shown at least once
+};
+
+function _formatUpdatedAt(iso) {
+    if (!iso) return "";
+    const d = new Date(iso);
+    if (isNaN(d.getTime())) return "";
+    return d.toLocaleString();
+}
+
+function _renderList() {
+    const list = document.getElementById("wfm-video-project-list");
+    if (!list) return;
+    const cfg = _MODES[_s.mode];
+    if (_s.plans.length === 0) {
+        list.innerHTML = `<span class="wfm-placeholder">${t(cfg.emptyKey)}</span>`;
+        return;
+    }
+    list.innerHTML = "";
+    for (const plan of _s.plans) list.appendChild(_makeItem(plan));
+}
+
+function _makeItem(plan) {
+    const cfg = _MODES[_s.mode];
+    const item = document.createElement("div");
+    item.className = "wfm-video-project-item" + (plan.filename === _s.activeFilename ? " active" : "");
+    item.dataset.filename = plan.filename;
+
+    const thumb = document.createElement("img");
+    thumb.className = "wfm-video-project-item-thumb";
+    thumb.loading = "lazy";
+    if (plan.thumbnail) thumb.src = plan.thumbnail;
+    thumb.onerror = () => { thumb.style.visibility = "hidden"; };
+
+    const info = document.createElement("div");
+    info.className = "wfm-video-project-item-info";
+
+    const name = document.createElement("div");
+    name.className = "wfm-video-project-item-name";
+    name.textContent = plan.name || plan.filename;
+    name.title = plan.filename;
+
+    const meta = document.createElement("div");
+    meta.className = "wfm-video-project-item-meta";
+    const countLabel = cfg.countLabel(cfg.countOf(plan));
+    const updated = _formatUpdatedAt(plan.updated_at);
+    meta.textContent = updated ? `${countLabel} · ${updated}` : countLabel;
+    meta.title = plan.note || "";
+
+    info.append(name, meta);
+
+    const deleteBtn = document.createElement("button");
+    deleteBtn.type = "button";
+    deleteBtn.className = "wfm-video-project-item-delete";
+    deleteBtn.textContent = "×";
+    deleteBtn.title = t("delete");
+    deleteBtn.addEventListener("click", (e) => {
+        e.stopPropagation();
+        _deletePlan(plan);
+    });
+
+    item.append(thumb, info, deleteBtn);
+    item.addEventListener("click", () => _openPlan(plan));
+    return item;
+}
+
+async function _openPlan(plan) {
+    _s.activeFilename = plan.filename;
+    _renderList();
+    await _MODES[_s.mode].open(plan.filename);
+}
+
+async function _deletePlan(plan) {
+    const cfg = _MODES[_s.mode];
+    if (!window.confirm(t(cfg.deleteConfirmKey, plan.name || plan.filename))) return;
+    try {
+        const res = await fetch(cfg.deleteUrl, {
+            method: "POST",
+            headers: { "Content-Type": "application/json" },
+            body: JSON.stringify({ filename: plan.filename }),
+        });
+        const json = await res.json();
+        if (!res.ok) throw new Error(json.error || `HTTP ${res.status}`);
+        if (_s.activeFilename === plan.filename) _s.activeFilename = null;
+        showToast(t(cfg.deletedKey), "success");
+        await refreshVideoProjectTab(_s.mode);
+    } catch (err) {
+        showToast(`${t(cfg.deleteFailedKey)}: ${err.message}`, "error");
+    }
+}
+
+// Called whenever the Project subtab becomes active (see video-tab.js's prop-tab
+// toggle) — always refetches rather than caching, so a plan/project saved
+// elsewhere (Plan pane's Save/Save As, Edit's Save/Save As) shows up as soon
+// as the user switches over to look. `mode` ("plan"|"edit") is video-tab.js's
+// record of which center subtab is currently active; defaults to "plan" so
+// direct calls (e.g. from initVideoProjectTab) keep the original behavior.
+export async function refreshVideoProjectTab(mode = "plan") {
+    const list = document.getElementById("wfm-video-project-list");
+    if (!list) return;
+    _s.mode = mode === "edit" ? "edit" : "plan";
+    _s.activeFilename = null;
+    const cfg = _MODES[_s.mode];
+    const hintEl = document.getElementById("wfm-video-project-hint");
+    if (hintEl) hintEl.textContent = t(cfg.hintKey);
+    try {
+        const res = await fetch(cfg.listUrl);
+        if (!res.ok) throw new Error(String(res.status));
+        _s.plans = await res.json();
+        _renderList();
+    } catch (err) {
+        list.innerHTML = `<span class="wfm-placeholder" style="color:var(--wfm-danger)">${escapeHtml(t(cfg.loadListFailedKey))}: ${escapeHtml(err.message)}</span>`;
+    }
+    _s.loaded = true;
+}
+
+export function initVideoProjectTab() {
+    document.getElementById("wfm-video-project-refresh")?.addEventListener("click", () => refreshVideoProjectTab());
+}
--- a/Show More
+++ b/Show More