fix(preview): revert to FileResponse as default for all platforms (#975)

The previous commit (a19ddc14) restored Linux sendfile but kept the
manual streaming path for Windows via sys.platform guard. A Windows
user reports performance is still worse than v1.0.5.

Switch back to web.FileResponse for all files on all platforms as the
default. The IOCP crash is an edge case (fast scrolling through many
video previews) that affects few users, while the Python chunked I/O
performance penalty affects everyone.

_stream_file() is kept as an unused fallback for a future compat
setting toggle.

.agents/skills/lora-manager-runtime-context/SKILL.md

@@ -0,0 +1,69 @@
+---
+name: lora-manager-runtime-context
+description: Inspect ComfyUI LoRA Manager runtime configuration and local diagnostic state. Use when debugging LoRA Manager issues that require locating or reading settings.json, active library paths, model metadata JSON sidecars, recipe metadata JSON files, example image folders, SQLite caches, symlink maps, download history, aria2 state, or other cache files under the LoRA Manager user config directory.
+---
+
+# LoRA Manager Runtime Context
+
+## Core Rules
+
+- Treat runtime state as local user data. Prefer read-only inspection unless the user explicitly asks for mutation.
+- Never print secret-like settings values. Redact keys containing `key`, `token`, `secret`, `password`, `auth`, or `credential`, including `civitai_api_key`.
+- Resolve paths from the runtime configuration before guessing. In this environment the settings file is normally `/home/miao/.config/ComfyUI-LoRA-Manager/settings.json`, but portable settings can override this through the repository `settings.json`.
+- Use the active library when selecting per-library caches and paths. Read `active_library` from settings; fall back to `default` if missing.
+- Normalize and expand `~` before comparing paths. Symlinks are common in this repo.
+
+## Quick Start
+
+Use the bundled helper for a safe first pass:
+
+```bash
+python .agents/skills/lora-manager-runtime-context/scripts/inspect_runtime_context.py summary
+python .agents/skills/lora-manager-runtime-context/scripts/inspect_runtime_context.py caches
+```
+
+The script redacts sensitive settings, opens SQLite databases read-only, and reports inaccessible or locked databases as warnings.
+
+For focused checks:
+
+```bash
+python .agents/skills/lora-manager-runtime-context/scripts/inspect_runtime_context.py recipes
+python .agents/skills/lora-manager-runtime-context/scripts/inspect_runtime_context.py model --path /path/to/model.safetensors
+python .agents/skills/lora-manager-runtime-context/scripts/inspect_runtime_context.py sqlite --db /path/to/cache.sqlite --limit 3
+```
+
+## Runtime Path Rules
+
+- Settings directory: use `py/utils/settings_paths.py`. Default platform path is `platformdirs.user_config_dir("ComfyUI-LoRA-Manager", appauthor=False)`.
+- Settings file: `<settings_dir>/settings.json`.
+- Cache root: `<settings_dir>/cache`.
+- Canonical cache files:
+  - Model cache: `cache/model/<active_library>.sqlite`.
+  - Recipe cache: `cache/recipe/<active_library>.sqlite`.
+  - Model update cache: `cache/model_update/<active_library>.sqlite`.
+  - Recipe FTS: `cache/fts/recipe_fts.sqlite`.
+  - Tag FTS: `cache/fts/tag_fts.sqlite`.
+  - Symlink map: `cache/symlink/symlink_map.json`.
+  - Download history: `cache/download_history/downloaded_versions.sqlite`.
+  - aria2 state: `cache/aria2/downloads.json`.
+- Legacy cache locations may exist; prefer canonical paths unless diagnosing migrations.
+
+## Data Location Rules
+
+- Model roots come from `settings.folder_paths` and the active library payload under `settings.libraries[active_library]`.
+- Model metadata JSON sidecars live next to the model file as `<model basename>.metadata.json`.
+- Recipes root is `settings.recipes_path` when it is a non-empty string. If empty, use the first configured LoRA root plus `/recipes`.
+- Recipe JSON files are named `*.recipe.json` under the recipes root and may be nested in folders.
+- Example image root is `settings.example_images_path`.
+- If multiple libraries are configured, example images are stored under `<example_images_path>/<sanitized_library>/<sha256>/`; otherwise they are under `<example_images_path>/<sha256>/`.
+
+## Useful Cache Tables
+
+- Model cache: `models`, `model_tags`, `hash_index`, `excluded_models`.
+- Recipe cache: `recipes`, `cache_metadata`.
+- Model update cache: `model_update_status`, `model_update_versions`.
+- Tag FTS cache: `tags`, `fts_metadata`, plus FTS internal tables.
+- Recipe FTS cache: `recipe_rowid`, `fts_metadata`, plus FTS internal tables.
+- Download history: `downloaded_model_versions`.
+
+Prefer querying only counts, schema, and a few sample rows unless the user asks for full output.

.agents/skills/lora-manager-runtime-context/agents/openai.yaml

@@ -0,0 +1,4 @@
+interface:
+  display_name: "LoRA Manager Runtime Context"
+  short_description: "Inspect LoRA Manager runtime state"
+  default_prompt: "Use $lora-manager-runtime-context to inspect LoRA Manager settings, metadata paths, and caches for debugging."

.agents/skills/lora-manager-runtime-context/scripts/inspect_runtime_context.py

@@ -0,0 +1,381 @@
+#!/usr/bin/env python3
+from __future__ import annotations
+
+import argparse
+import json
+import os
+import re
+import shutil
+import sqlite3
+import sys
+import tempfile
+from pathlib import Path
+from typing import Any
+
+SECRET_PATTERN = re.compile(r"(key|token|secret|password|auth|credential)", re.IGNORECASE)
+APP_NAME = "ComfyUI-LoRA-Manager"
+CACHE_SQLITE = {
+    "model": ("model", "{library}.sqlite"),
+    "recipe": ("recipe", "{library}.sqlite"),
+    "model_update": ("model_update", "{library}.sqlite"),
+    "recipe_fts": ("fts", "recipe_fts.sqlite"),
+    "tag_fts": ("fts", "tag_fts.sqlite"),
+    "download_history": ("download_history", "downloaded_versions.sqlite"),
+}
+CACHE_JSON = {
+    "symlink": ("symlink", "symlink_map.json"),
+    "aria2": ("aria2", "downloads.json"),
+}
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(description="Inspect LoRA Manager runtime state read-only.")
+    subparsers = parser.add_subparsers(dest="command", required=True)
+
+    subparsers.add_parser("summary", help="Print redacted settings and resolved paths.")
+    subparsers.add_parser("caches", help="Print cache paths and SQLite table summaries.")
+    subparsers.add_parser("recipes", help="Print resolved recipes root and recipe JSON count.")
+
+    model_parser = subparsers.add_parser("model", help="Inspect a model metadata sidecar path.")
+    model_parser.add_argument("--path", required=True, help="Path to a model file or metadata JSON file.")
+
+    sqlite_parser = subparsers.add_parser("sqlite", help="Inspect a SQLite database read-only.")
+    sqlite_parser.add_argument("--db", required=True, help="Path to the SQLite database.")
+    sqlite_parser.add_argument("--limit", type=int, default=3, help="Rows to sample from each user table.")
+
+    args = parser.parse_args()
+    context = build_context()
+
+    if args.command == "summary":
+        print_json(summary_payload(context))
+    elif args.command == "caches":
+        print_json(caches_payload(context))
+    elif args.command == "recipes":
+        print_json(recipes_payload(context))
+    elif args.command == "model":
+        print_json(model_payload(args.path))
+    elif args.command == "sqlite":
+        print_json(sqlite_payload(Path(args.db).expanduser(), args.limit))
+    return 0
+
+
+def build_context() -> dict[str, Any]:
+    settings_path = resolve_settings_path()
+    settings = load_json(settings_path)
+    settings_dir = settings_path.parent
+    active_library = settings.get("active_library") or "default"
+    safe_library = sanitize_library_name(str(active_library))
+    cache_root = settings_dir / "cache"
+    return {
+        "settings_path": str(settings_path),
+        "settings_dir": str(settings_dir),
+        "settings": settings,
+        "active_library": active_library,
+        "safe_library": safe_library,
+        "cache_root": str(cache_root),
+        "cache_paths": resolve_cache_paths(cache_root, safe_library),
+    }
+
+
+def resolve_settings_path() -> Path:
+    repo_root = find_repo_root()
+    portable = repo_root / "settings.json"
+    if portable.exists():
+        payload = load_json(portable)
+        if isinstance(payload, dict) and payload.get("use_portable_settings") is True:
+            return portable
+
+    config_home = os.environ.get("XDG_CONFIG_HOME")
+    if config_home:
+        return Path(config_home).expanduser() / APP_NAME / "settings.json"
+    return Path.home() / ".config" / APP_NAME / "settings.json"
+
+
+def find_repo_root() -> Path:
+    current = Path(__file__).resolve()
+    for parent in current.parents:
+        if (parent / "py").is_dir() and (parent / "standalone.py").exists():
+            return parent
+    return Path.cwd()
+
+
+def load_json(path: Path) -> dict[str, Any]:
+    try:
+        with path.open("r", encoding="utf-8") as handle:
+            payload = json.load(handle)
+    except FileNotFoundError:
+        return {}
+    except json.JSONDecodeError as exc:
+        return {"_error": f"invalid JSON: {exc}"}
+    except OSError as exc:
+        return {"_error": f"unreadable: {exc}"}
+    return payload if isinstance(payload, dict) else {"_error": "JSON root is not an object"}
+
+
+def resolve_cache_paths(cache_root: Path, library: str) -> dict[str, str]:
+    paths: dict[str, str] = {}
+    for name, (subdir, filename) in CACHE_SQLITE.items():
+        paths[name] = str(cache_root / subdir / filename.format(library=library))
+    for name, (subdir, filename) in CACHE_JSON.items():
+        paths[name] = str(cache_root / subdir / filename)
+    return paths
+
+
+def summary_payload(context: dict[str, Any]) -> dict[str, Any]:
+    settings = context["settings"]
+    return {
+        "settings_path": context["settings_path"],
+        "settings_dir": context["settings_dir"],
+        "active_library": context["active_library"],
+        "settings": redact(settings),
+        "model_roots": model_roots(settings, context["active_library"]),
+        "recipes_root": str(resolve_recipes_root(settings, context["active_library"]) or ""),
+        "example_images": example_images_payload(settings, context["active_library"]),
+        "cache_root": context["cache_root"],
+        "cache_paths": context["cache_paths"],
+    }
+
+
+def caches_payload(context: dict[str, Any]) -> dict[str, Any]:
+    caches: dict[str, Any] = {}
+    for name, path_string in context["cache_paths"].items():
+        path = Path(path_string)
+        item: dict[str, Any] = {
+            "path": str(path),
+            "exists": path.exists(),
+            "size": path.stat().st_size if path.exists() else None,
+        }
+        if path.suffix == ".sqlite":
+            item["sqlite"] = sqlite_payload(path, limit=0)
+        elif path.suffix == ".json":
+            item["json"] = json_file_summary(path)
+        caches[name] = item
+    return {"active_library": context["active_library"], "caches": caches}
+
+
+def recipes_payload(context: dict[str, Any]) -> dict[str, Any]:
+    root = resolve_recipes_root(context["settings"], context["active_library"])
+    files: list[str] = []
+    if root and root.exists():
+        files = [str(path) for path in sorted(root.rglob("*.recipe.json"))[:20]]
+    return {
+        "recipes_root": str(root or ""),
+        "exists": bool(root and root.exists()),
+        "recipe_json_count": count_recipe_files(root),
+        "sample_recipe_json": files,
+        "recipe_cache": context["cache_paths"].get("recipe"),
+    }
+
+
+def model_payload(raw_path: str) -> dict[str, Any]:
+    path = Path(raw_path).expanduser()
+    metadata_path = path if path.name.endswith(".metadata.json") else path.with_suffix(".metadata.json")
+    payload = {
+        "input_path": str(path),
+        "metadata_path": str(metadata_path),
+        "model_exists": path.exists(),
+        "metadata_exists": metadata_path.exists(),
+    }
+    if metadata_path.exists():
+        data = load_json(metadata_path)
+        payload["metadata_summary"] = redact(summarize_value(data))
+    return payload
+
+
+def sqlite_payload(path: Path, limit: int = 3, allow_copy: bool = True) -> dict[str, Any]:
+    result: dict[str, Any] = {"path": str(path), "exists": path.exists(), "tables": {}}
+    if not path.exists():
+        return result
+    try:
+        conn = connect_sqlite_readonly(path)
+    except sqlite3.Error as exc:
+        result["error"] = str(exc)
+        return result
+    try:
+        table_rows = conn.execute(
+            "SELECT name FROM sqlite_master WHERE type='table' ORDER BY name"
+        ).fetchall()
+        for table_row in table_rows:
+            table = table_row["name"]
+            columns = [
+                row["name"]
+                for row in conn.execute(f"PRAGMA table_info({quote_identifier(table)})").fetchall()
+            ]
+            table_info: dict[str, Any] = {"columns": columns}
+            try:
+                table_info["count"] = conn.execute(
+                    f"SELECT COUNT(*) FROM {quote_identifier(table)}"
+                ).fetchone()[0]
+            except sqlite3.Error as exc:
+                table_info["count_error"] = str(exc)
+            if limit > 0 and columns and not is_internal_sqlite_table(table):
+                try:
+                    rows = conn.execute(
+                        f"SELECT * FROM {quote_identifier(table)} LIMIT ?", (limit,)
+                    ).fetchall()
+                    table_info["sample"] = [redact(dict(row)) for row in rows]
+                except sqlite3.Error as exc:
+                    table_info["sample_error"] = str(exc)
+            result["tables"][table] = table_info
+    except sqlite3.Error as exc:
+        fallback = sqlite_copy_payload(path, limit, str(exc)) if allow_copy else None
+        if fallback is not None:
+            result.update(fallback)
+        else:
+            result["error"] = str(exc)
+    finally:
+        conn.close()
+    return result
+
+
+def connect_sqlite_readonly(path: Path) -> sqlite3.Connection:
+    errors: list[str] = []
+    for query in ("mode=ro", "mode=ro&immutable=1"):
+        try:
+            conn = sqlite3.connect(f"file:{path}?{query}", uri=True)
+            conn.row_factory = sqlite3.Row
+            return conn
+        except sqlite3.Error as exc:
+            errors.append(f"{query}: {exc}")
+    raise sqlite3.OperationalError("; ".join(errors))
+
+
+def sqlite_copy_payload(path: Path, limit: int, original_error: str) -> dict[str, Any] | None:
+    try:
+        with tempfile.TemporaryDirectory(prefix="lm-cache-inspect-") as temp_dir:
+            copy_path = Path(temp_dir) / path.name
+            shutil.copy2(path, copy_path)
+            payload = sqlite_payload(copy_path, limit, allow_copy=False)
+            payload["path"] = str(path)
+            payload["inspected_copy"] = True
+            payload["original_error"] = original_error
+            return payload
+    except Exception:
+        return None
+
+
+def json_file_summary(path: Path) -> dict[str, Any]:
+    if not path.exists():
+        return {"exists": False}
+    data = load_json(path)
+    return {"exists": True, "summary": redact(summarize_value(data))}
+
+
+def model_roots(settings: dict[str, Any], active_library: str) -> dict[str, list[str]]:
+    roots: dict[str, list[str]] = {}
+    sources = [settings]
+    library = settings.get("libraries", {}).get(active_library)
+    if isinstance(library, dict):
+        sources.insert(0, library)
+    for source in sources:
+        folder_paths = source.get("folder_paths")
+        if isinstance(folder_paths, dict):
+            for key, value in folder_paths.items():
+                roots.setdefault(key, []).extend(normalize_path_list(value))
+    for default_key, folder_key in (
+        ("default_lora_root", "loras"),
+        ("default_checkpoint_root", "checkpoints"),
+        ("default_embedding_root", "embeddings"),
+        ("default_unet_root", "unet"),
+    ):
+        value = settings.get(default_key)
+        if isinstance(value, str) and value:
+            roots.setdefault(folder_key, []).append(expand_path(value))
+    return {key: dedupe(values) for key, values in roots.items()}
+
+
+def resolve_recipes_root(settings: dict[str, Any], active_library: str) -> Path | None:
+    recipes_path = settings.get("recipes_path")
+    library = settings.get("libraries", {}).get(active_library)
+    if isinstance(library, dict) and isinstance(library.get("recipes_path"), str):
+        recipes_path = library["recipes_path"] or recipes_path
+    if isinstance(recipes_path, str) and recipes_path.strip():
+        return Path(expand_path(recipes_path.strip()))
+    lora_roots = model_roots(settings, active_library).get("loras") or []
+    return Path(lora_roots[0]) / "recipes" if lora_roots else None
+
+
+def example_images_payload(settings: dict[str, Any], active_library: str) -> dict[str, Any]:
+    root = settings.get("example_images_path") or ""
+    libraries = settings.get("libraries")
+    library_count = len(libraries) if isinstance(libraries, dict) else 0
+    scoped = library_count > 1
+    root_path = Path(expand_path(root)) if isinstance(root, str) and root else None
+    library_root = root_path / sanitize_library_name(active_library) if root_path and scoped else root_path
+    return {
+        "root": str(root_path or ""),
+        "uses_library_scoped_folders": scoped,
+        "library_root": str(library_root or ""),
+    }
+
+
+def count_recipe_files(root: Path | None) -> int:
+    if not root or not root.exists():
+        return 0
+    return sum(1 for _ in root.rglob("*.recipe.json"))
+
+
+def normalize_path_list(value: Any) -> list[str]:
+    if isinstance(value, str):
+        return [expand_path(value)] if value else []
+    if isinstance(value, list):
+        return [expand_path(item) for item in value if isinstance(item, str) and item]
+    return []
+
+
+def expand_path(value: str) -> str:
+    return str(Path(value).expanduser().resolve(strict=False))
+
+
+def sanitize_library_name(name: str) -> str:
+    safe = re.sub(r"[^A-Za-z0-9_.-]", "_", name or "default")
+    return safe or "default"
+
+
+def dedupe(values: list[str]) -> list[str]:
+    seen: set[str] = set()
+    result: list[str] = []
+    for value in values:
+        if value not in seen:
+            result.append(value)
+            seen.add(value)
+    return result
+
+
+def redact(value: Any, key: str = "") -> Any:
+    if key and SECRET_PATTERN.search(key):
+        return "<redacted>"
+    if isinstance(value, dict):
+        return {str(k): redact(v, str(k)) for k, v in value.items()}
+    if isinstance(value, list):
+        return [redact(item) for item in value]
+    return value
+
+
+def summarize_value(value: Any) -> Any:
+    if isinstance(value, dict):
+        return {key: summarize_value(item) for key, item in value.items()}
+    if isinstance(value, list):
+        return {
+            "type": "array",
+            "length": len(value),
+            "first": summarize_value(value[0]) if value else None,
+        }
+    return value
+
+
+def quote_identifier(identifier: str) -> str:
+    return '"' + identifier.replace('"', '""') + '"'
+
+
+def is_internal_sqlite_table(table: str) -> bool:
+    return table.startswith("sqlite_") or table.endswith(("_data", "_idx", "_docsize", "_config", "_content"))
+
+
+def print_json(payload: Any) -> None:
+    json.dump(payload, sys.stdout, indent=2, ensure_ascii=False)
+    sys.stdout.write("\n")
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())

.github/ISSUE_TEMPLATE/feature_request.md

@@ -13,8 +13,5 @@ A clear and concise description of what the problem is. Ex. I'm always frustrate
 **Describe the solution you'd like**
 A clear and concise description of what you want to happen.
 
-**Describe alternatives you've considered**
-A clear and concise description of any alternative solutions or features you've considered.
-
 **Additional context**
 Add any other context or screenshots about the feature request here.

.gitignore

@@ -15,7 +15,9 @@ model_cache/
 # agent
 .opencode/
 .claude/
+.sisyphus/
 .codex
+.omo
 
 # Vue widgets development cache (but keep build output)
 vue-widgets/node_modules/

.omo/plans/embeddings-hybrid-approach.md

@@ -0,0 +1,181 @@
+# Embeddings Usage Tracking — Hybrid Approach (Plan C)
+
+> **Status**: Reference document for future implementation
+> **Current implementation**: Plan A (prompt text parsing only, see `usage_stats.py:_process_embeddings`)
+> **Next step**: Add Plan B as a supplement when edge-case coverage is needed
+
+## Problem
+
+Embeddings in ComfyUI are not loaded through dedicated ComfyUI nodes like LoRAs or
+Checkpoints. They are resolved during CLIP tokenization when the prompt text contains
+`embedding:<name>` syntax (see `comfy/sd1_clip.py:SDTokenizer.tokenize_with_weights`).
+
+This means the existing metadata_collector hook (which intercepts node execution via
+`_map_node_over_list`) cannot capture embeddings the same way it captures LoRAs and
+checkpoints — there is no "EmbeddingLoader" node to intercept.
+
+## Solution Architecture
+
+The hybrid approach combines **two complementary mechanisms** to capture embedding
+usage from all possible paths.
+
+```
+┌─────────────────────────────────────────────────────────┐
+│                 Plan A (已实现)                          │
+│                                                         │
+│  MetadataRegistry.prompt_metadata["prompts"]            │
+│       │                                                  │
+│       ▼                                                  │
+│  _process_embeddings()                                   │
+│       │                                                  │
+│       ├─ Iterate all prompt node texts                   │
+│       ├─ regex extract "embedding:<name>"                │
+│       ├─ resolve name → sha256 via EmbeddingScanner      │
+│       └─ UsageStats.stats["embeddings"][sha256]++        │
+│                                                         │
+│  Coverage: ~95% — all CLIPTextEncode/Flux/etc nodes     │
+│                                                         │
+│  Gap: Custom nodes that load embeddings programmatically │
+│       without putting embedding:name in prompt text      │
+└─────────────────────────────────────────────────────────┘
+
+                         +
+                         ↓  (future: enable Plan B when needed)
+
+┌─────────────────────────────────────────────────────────┐
+│                 Plan B (未来 — monkey-patch)              │
+│                                                         │
+│  comfy/sd1_clip.py:load_embed()                         │
+│       │                                                  │
+│       ▼                                                  │
+│  Monkey-patch intercepts EVERY embedding file load       │
+│       │                                                  │
+│       ├─ Records embedding_name + success/failure        │
+│       ├─ Associates with current prompt_id (via registry)│
+│       └─ Feeds into UsageStats same as Plan A            │
+│                                                         │
+│  Coverage: 100% — catches ALL embedding loads            │
+│                                                         │
+│  Cost: Requires patching into ComfyUI internals          │
+│        (sd1_clip.py, sdxl_clip.py, some text_encoders)   │
+└─────────────────────────────────────────────────────────┘
+```
+
+## Plan B Detail — Monkey-patch `load_embed`
+
+### Target Function
+
+**`comfy.sd1_clip.load_embed(embedding_name, embedding_directory, embedding_size, embed_key=None)`**
+at line 415 of `sd1_clip.py`.
+
+This is the **single choke point** for all embedding file loads in ComfyUI. Every
+CLIP variant (SD1, SDXL, SD3, Flux) calls this same function.
+
+### Implementation Sketch
+
+```python
+# In metadata_collector/metadata_hook.py (or a new module)
+import comfy.sd1_clip as sd1_clip
+
+_original_load_embed = sd1_clip.load_embed
+
+def _patched_load_embed(embedding_name, embedding_directory, embedding_size, embed_key=None):
+    result = _original_load_embed(
+        embedding_name, embedding_directory, embedding_size, embed_key
+    )
+    if result is not None:
+        _record_embedding_usage(embedding_name)
+    return result
+
+sd1_clip.load_embed = _patched_load_embed
+```
+
+### Prompt ID Association
+
+The challenge is associating the `load_embed` call with the current `prompt_id`.
+Options:
+
+1. **Thread-local / contextvar**: Store current `prompt_id` in a `contextvars.ContextVar`
+   that the metadata_collector sets at the start of each prompt execution.
+
+2. **MetadataRegistry singleton**: The MetadataRegistry already has `current_prompt_id`.
+   The patch can read it directly since both run in the same thread.
+
+3. **Lazy aggregation**: Instead of associating with prompt_id at load time, collect
+   all loaded embedding names in a global set during execution, then flush to
+   UsageStats after the prompt completes.
+
+### Files to Patch
+
+| File | Function | Coverage |
+|------|----------|----------|
+| `comfy/sd1_clip.py:415` | `load_embed()` | Primary — SD1.x, SDXL, SD3, Flux |
+| `comfy/sdxl_clip.py` | Not needed (calls `sd1_clip.SDTokenizer`) | — |
+| `comfy/text_encoders/sd3_clip.py` | Not needed (calls `sd1_clip.SDTokenizer`) | — |
+| `comfy/text_encoders/flux.py` | Not needed (calls `sd1_clip.SDTokenizer`) | — |
+
+The SD1 tokenizer is the base class for all CLIP variants' tokenizers, so patching
+`load_embed` covers them all.
+
+### Edge Cases
+
+| Edge Case | Plan A | Plan B |
+|-----------|--------|--------|
+| `embedding:name` in CLIPTextEncode | ✅ | ✅ |
+| `embedding:name` in CLIPTextEncodeFlux | ✅ | ✅ |
+| `embedding:name` in PromptLM (LoRA Manager) | ✅ | ✅ |
+| `embedding:name` in WAS_Text_to_Conditioning | ✅ | ✅ |
+| Custom node that loads embedding programmatically | ❌ | ✅ |
+| Embedding loaded multiple times in same prompt | ✅ (dedup via set) | ✅ (dedup via set) |
+| Embedding file not found | N/A | ✅ (can log) |
+| Embedding dimension mismatch | N/A | ✅ (can log) |
+| Text encoder with non-standard tokenizer (LLaMA, T5...) | Partial | ✅ (if it calls load_embed) |
+
+## Migration Path: Standalone → Hybrid
+
+### Phase 1 — Plan A (当前状态)
+- Prompt text parsing only
+- No monkey-patching required
+- Covers all standard workflows
+
+### Phase 2 — Enable Plan B (未来工作)
+1. Add monkey-patch of `load_embed` in `metadata_collector/metadata_hook.py` (alongside
+   the existing `_map_node_over_list` hook)
+2. Collect loaded embedding names in a `set()` on the registry
+3. In `UsageStats._process_embeddings()`, merge the Plan A results (from prompt text)
+   with the Plan B results (from the patch)
+4. Add `prompt_data` field on MetadataRegistry to store loaded embeddings per prompt
+
+### Deduplication
+
+```python
+# Merge Plan A + Plan B results in _process_embeddings
+plan_a_names = extract_from_prompt_texts(prompts_data)
+plan_b_names = registry.get_loaded_embeddings(prompt_id)
+
+all_names = plan_a_names | plan_b_names
+```
+
+## Testing the Hybrid
+
+| Scenario | What to verify |
+|----------|---------------|
+| Standard `embedding:name` in prompt | Plan A captures it |
+| Embedding loaded by custom node script | Plan B captures it |
+| Both paths fire for same embedding | No double-counting (dedup) |
+| Embedding name resolves to hash | EmbeddingScanner.get_hash_by_filename works |
+| No embedding scanner available | Graceful skip, no crash |
+| Missing embedding file | Plan B logs warning, Plan A skips gracefully |
+| Empty prompt | No crash, no entries |
+| Standalone mode | Both plans disabled gracefully |
+
+## Key Files Reference
+
+| File | Role |
+|------|------|
+| `py/utils/usage_stats.py` | Core — `_process_embeddings()` for Plan A |
+| `py/metadata_collector/constants.py` | `EMBEDDINGS` category constant |
+| `py/metadata_collector/metadata_hook.py` | Future — monkey-patch for Plan B |
+| `py/services/embedding_scanner.py` | Hash resolution service |
+| `py/routes/stats_routes.py` | Already handles `usage_data.get('embeddings', {})` |
+| `comfy/sd1_clip.py` (ComfyUI) | `load_embed()` — Plan B target |

docs/LM-Extension-Wiki.md

@@ -1,183 +0,0 @@
-## Overview
-
-The **LoRA Manager Civitai Extension** is a Browser extension designed to work seamlessly with [LoRA Manager](https://github.com/willmiao/ComfyUI-Lora-Manager) to significantly enhance your browsing experience on [Civitai](https://civitai.com). With this extension, you can:
-
-✅ Instantly see which models are already present in your local library  
-✅ Download new models with a single click  
-✅ Manage downloads efficiently with queue and parallel download support  
-✅ Keep your downloaded models automatically organized according to your custom settings    
-
-![Civitai Models page](https://github.com/willmiao/ComfyUI-Lora-Manager/blob/main/wiki-images/civitai-models-page.png) 
-
-**Update:** It now also supports browsing on [CivArchive](https://civarchive.com/) (formerly CivitaiArchive). 
-
-![CivArchive Models page](https://github.com/willmiao/ComfyUI-Lora-Manager/blob/main/wiki-images/civarchive-models-page.png)  
-
----
-
-## Why Supporter Access?
-
-LoRA Manager is built with love for the Stable Diffusion and ComfyUI communities. Your support makes it possible for me to keep improving and maintaining the tool full-time.
-
-Supporter-exclusive features help ensure the long-term sustainability of LoRA Manager, allowing continuous updates, new features, and better performance for everyone.
-
-Every contribution directly fuels development and keeps the core LoRA Manager free and open-source. In addition to monthly supporters, one-time donation supporters will also receive a license key, with the duration scaling according to the contribution amount. Thank you for helping keep this project alive and growing. ❤️
-
-
----
-
-## Installation
-
-### Supported Browsers & Installation Methods
-
-| Browser            | Installation Method                                                                 |
-|--------------------|-------------------------------------------------------------------------------------|
-| **Google Chrome**   | [Chrome Web Store link](https://chromewebstore.google.com/detail/capigligggeijgmocnaflanlbghnamgm?utm_source=item-share-cb) |
-| **Microsoft Edge**  | Install via Chrome Web Store (compatible)                                          |
-| **Brave Browser**   | Install via Chrome Web Store (compatible)                                          |
-| **Opera**           | Install via Chrome Web Store (compatible)                                          |
-| **Firefox**         | <div id="firefox-install" class="install-ok"><a href="https://github.com/willmiao/lm-civitai-extension-firefox/releases/latest/download/extension.xpi">📦 Install Firefox Extension (reviewed and verified by Mozilla)</a></div>             |
-
-For non-Chrome browsers (e.g., Microsoft Edge), you can typically install extensions from the Chrome Web Store by following these steps: open the extension’s Chrome Web Store page, click 'Get extension', then click 'Allow' when prompted to enable installations from other stores, and finally click 'Add extension' to complete the installation.
-
----
-
-## Privacy & Security
-
-I understand concerns around browser extensions and privacy, and I want to be fully transparent about how the **LM Civitai Extension** works:
-
-- **Reviewed and Verified**  
-  This extension has been **manually reviewed and approved by the Chrome Web Store**. The Firefox version uses the **exact same code** (only the packaging format differs) and has passed **Mozilla’s Add-on review**.
-
-- **Minimal Network Access**  
-  The only external server this extension connects to is:  
-  **`https://willmiao.shop`** — used solely for **license validation**.
-
-  It does **not collect, transmit, or store any personal or usage data**.  
-  No browsing history, no user IDs, no analytics, no hidden trackers.
-
-- **Local-Only Model Detection**  
-  Model detection and LoRA Manager communication all happen **locally** within your browser, directly interacting with your local LoRA Manager backend.
-
-I value your trust and are committed to keeping your local setup private and secure. If you have any questions, feel free to reach out!
-
----
-
-## How to Use
-
-After installing the extension, you'll automatically receive a **7-day trial** to explore all features.
-
-When the extension is correctly installed and your license is valid:
-
-- Open **Civitai**, and you'll see visual indicators added by the extension on model cards, showing:
-  - ✅ Models already present in your local library  
-  - ⬇️ A download button for models not in your library  
-
-Clicking the download button adds the corresponding model version to the download queue, waiting to be downloaded. You can set up to **5 models to download simultaneously**.
-
-### Visual Indicators Appear On:
-
-- **Home Page** — Featured models  
-- **Models Page**  
-- **Creator Profiles** — If the creator has set their models to be visible  
-- **Recommended Resources** — On individual model pages  
-
-### Version Buttons on Model Pages
-
-On a specific model page, visual indicators also appear on version buttons, showing which versions are already in your local library.
-
-**Starting from v0.4.8**, model pages use a dedicated download button for better compatibility. When switching to a specific version by clicking a version button:
-
-- The new **dedicated download button** directly triggers download via **LoRA Manager**
-- The **original download button** remains unchanged for standard browser downloads
-
-![Civitai Model Page](https://github.com/willmiao/ComfyUI-Lora-Manager/blob/main/wiki-images/civitai-model-page.png)
-
-### Hide Models Already in Library (Beta)
-
-**New in v0.4.8**: A new **Hide models already in library (Beta)** option makes it easier to focus on models you haven't added yet. It can be enabled from Settings, or toggled quickly using **Ctrl + Shift + H** (macOS: **Command + Shift + H**).
-
-### Resources on Image Pages — now shows in-library indicators for image resources plus one-click recipe import
-
-- **One-Click Import Civitai Image as Recipe** — Import any Civitai image as a recipe with a single click in the Resources Used panel.
-- **Auto-Queue Missing Assets** — In Settings you can decide if LoRAs or checkpoints referenced by that image should automatically be added to your download queue.
-- **More Accurate Metadata** — Importing directly from the page is faster than copying inside LM and keeps on-site tags and other metadata perfectly aligned.
-
-![Civitai Image Page](https://github.com/willmiao/ComfyUI-Lora-Manager/blob/main/wiki-images/civitai-image-page.jpg)
-
-[![alt](url)](https://github.com/user-attachments/assets/41fd4240-c949-4f83-bde7-8f3124c09494)
-
----
-
-## Model Download Location & LoRA Manager Settings
-
-To use the **one-click download function**, you must first set:
-
-- Your **Default LoRAs Root**  
-- Your **Default Checkpoints Root**  
-
-These are set within LoRA Manager's settings.
-
-When everything is configured, downloaded model files will be placed in:  
-
-`<Default_Models_Root>/<Base_Model_of_the_Model>/<First_Tag_of_the_Model>`
-
-
-### Update: Default Path Customization (2025-07-21)  
-
-A new setting to customize the default download path has been added in the nightly version. You can now personalize where models are saved when downloading via the LM Civitai Extension.
-
-![Default Path Customization](https://github.com/willmiao/ComfyUI-Lora-Manager/blob/main/wiki-images/default-path-customization.png)
-
-The previous YAML path mapping file will be deprecated—settings will now be unified in settings.json to simplify configuration.
-
----
-
-## Backend Port Configuration
-
-If your **ComfyUI** or **LoRA Manager** backend is running on a port **other than the default 8188**, you must configure the backend port in the extension's settings.
-
-After correctly setting and saving the port, you'll see in the extension's header area:  
-- A **Healthy** status with the tooltip:  `Connected to LoRA Manager on port xxxx`
-
-
----
-
-## Advanced Usage
-
-### Connecting to a Remote LoRA Manager
-
-If your LoRA Manager is running on another computer, you can still connect from your browser using port forwarding.
-
-> **Why can't you set a remote IP directly?**
->
-> For privacy and security, the extension only requests access to `http://127.0.0.1/*`. Supporting remote IPs would require much broader permissions, which may be rejected by browser stores and could raise user concerns.
-
-**Solution: Port Forwarding with `socat`**
-
-On your browser computer, run:
-
-`socat TCP-LISTEN:8188,bind=127.0.0.1,fork TCP:REMOTE.IP.ADDRESS.HERE:8188`
-
-- Replace `REMOTE.IP.ADDRESS.HERE` with the IP of the machine running LoRA Manager.
-- Adjust the port if needed.
-
-This lets the extension connect to `127.0.0.1:8188` as usual, with traffic forwarded to your remote server.
-
-_Thanks to user **Temikus** for sharing this solution!_
-
----
-
-## Roadmap
-
-The extension will evolve alongside **LoRA Manager** improvements. Planned features include:
-
-- [x] Support for **additional model types** (e.g., embeddings)
-- [x] One-click **Recipe Import**
-- [x] Display of in-library status for all resources in the **Resources Used** section of the image page
-- [x] One-click **Auto-organize Models**
-- [x] **Hide models already in library (Beta)** - Focus on models you haven't added yet
-
-**Stay tuned — and thank you for your support!**
-
----

locales/de.json

@@ -15,7 +15,10 @@
             "settings": "Einstellungen",
             "help": "Hilfe",
             "add": "Hinzufügen",
-            "close": "Schließen"
+            "close": "Schließen",
+            "menu": "Menü",
+            "remove": "Entfernen",
+            "change": "Ändern"
         },
         "status": {
             "loading": "Wird geladen...",
@@ -110,6 +113,7 @@
             "replacePreview": "Vorschau ersetzen",
             "copyCheckpointName": "Checkpoint-Name kopieren",
             "copyEmbeddingName": "Embedding-Name kopieren",
+            "embeddingNameCopied": "Embedding-Syntax kopiert",
             "sendCheckpointToWorkflow": "An ComfyUI senden",
             "sendEmbeddingToWorkflow": "An ComfyUI senden"
         },
@@ -231,7 +235,10 @@
             "license": "Lizenz",
             "noCreditRequired": "Kein Credit erforderlich",
             "allowSellingGeneratedContent": "Verkauf erlaubt",
+            "allowSellingGeneratedContentTooltip": "Verkauf generierter Bilder erlauben",
+            "noCreditRequiredTooltip": "Modell ohne Nennung des Erstellers verwenden",
             "noTags": "Keine Tags",
+            "autoTags": "Auto-Tags",
             "noBaseModelMatches": "Keine Basismodelle entsprechen der aktuellen Suche.",
             "clearAll": "Alle Filter löschen",
             "any": "Beliebig",
@@ -265,10 +272,10 @@
         },
         "downloadBackend": {
             "label": "Download-Backend",
-            "help": "Wähle aus, wie Modelldateien heruntergeladen werden. Python verwendet den eingebauten Downloader. aria2 verwendet den experimentellen externen Downloader-Prozess.",
+            "help": "Wähle aus, wie Modelldateien heruntergeladen werden. Python verwendet den eingebauten Downloader. aria2 verwendet den empfohlenen externen Downloader-Prozess.",
             "options": {
                 "python": "Python (integriert)",
-                "aria2": "aria2 (experimentell)"
+                "aria2": "aria2 (empfohlen)"
             }
         },
         "aria2cPath": {
@@ -276,6 +283,7 @@
             "help": "Optionaler Pfad zur ausführbaren aria2c-Datei. Leer lassen, um aria2c aus dem System-PATH zu verwenden.",
             "placeholder": "Leer lassen, um aria2c aus dem PATH zu verwenden"
         },
+        "aria2HelpLink": "Erfahren Sie, wie Sie das aria2-Download-Backend einrichten",
         "civitaiHostBanner": {
             "title": "Civitai-Host-Einstellung verfügbar",
             "content": "Civitai verwendet jetzt civitai.com für SFW-Inhalte und civitai.red für uneingeschränkte Inhalte. In den Einstellungen können Sie ändern, welche Seite standardmäßig geöffnet wird.",
@@ -427,6 +435,8 @@
                 "hover": "Bei Hover anzeigen"
             },
             "cardInfoDisplayHelp": "Wählen Sie, wann Modellinformationen und Aktionsschaltflächen angezeigt werden sollen",
+            "showVersionOnCard": "Version auf Karte anzeigen",
+            "showVersionOnCardHelp": "Den Versionsnamen auf Modellkarten ein- oder ausblenden",
             "modelCardFooterAction": "Aktion der Modellkarten-Schaltfläche",
             "modelCardFooterActionOptions": {
                 "exampleImages": "Beispielbilder öffnen",
@@ -438,7 +448,9 @@
                 "modelName": "Modellname",
                 "fileName": "Dateiname"
             },
-            "modelNameDisplayHelp": "Wählen Sie aus, was in der Fußzeile der Modellkarte angezeigt werden soll"
+            "modelNameDisplayHelp": "Wählen Sie aus, was in der Fußzeile der Modellkarte angezeigt werden soll",
+            "cardBlurAmount": "Karten-Overlay-Unschärfe",
+            "cardBlurAmountHelp": "Passen Sie die Unschärfeintensität der Kopf- und Fußzeilen-Overlays auf Modell- und Rezeptkarten an (0 = keine Unschärfe, 20 = maximale Unschärfe)."
         },
         "folderSettings": {
             "activeLibrary": "Aktive Bibliothek",
@@ -538,6 +550,21 @@
             "downloadLocationHelp": "Geben Sie den Ordnerpfad ein, wo Beispielbilder von Civitai gespeichert werden",
             "autoDownload": "Beispielbilder automatisch herunterladen",
             "autoDownloadHelp": "Beispielbilder automatisch für Modelle herunterladen, die keine haben (erfordert gesetzten Download-Speicherort)",
+            "openMode": "Aktion für Beispielbilder öffnen",
+            "openModeHelp": "Wählen Sie, ob die Aktion auf dem Server geöffnet, ein zugeordneter lokaler Pfad kopiert oder eine benutzerdefinierte URI gestartet werden soll.",
+            "openModeOptions": {
+                "system": "Auf Server öffnen",
+                "clipboard": "Lokalen Pfad kopieren",
+                "uriTemplate": "Benutzerdefinierte URI öffnen"
+            },
+            "localRoot": "Lokales Stammverzeichnis für Beispielbilder",
+            "localRootHelp": "Optionales lokales oder eingebundenes Stammverzeichnis, das das Beispielbild-Verzeichnis des Servers widerspiegelt. Wenn leer, wird der Serverpfad wiederverwendet.",
+            "localRootPlaceholder": "Beispiel: /Volumes/ComfyUI/example_images",
+            "uriTemplate": "URI-Vorlage öffnen",
+            "uriTemplateHelp": "Verwenden Sie einen benutzerdefinierten Deeplink wie eine Datei-URI oder einen Shortcuts-Link.",
+            "uriTemplatePlaceholder": "Beispiel: shortcuts://run-shortcut?name=Open%20Finder&input=text&text={{encoded_local_path}}",
+            "uriTemplatePlaceholders": "Verfügbare Platzhalter: {{local_path}}, {{encoded_local_path}}, {{relative_path}}, {{encoded_relative_path}}, {{file_uri}}, {{encoded_file_uri}}",
+            "openModeWikiLink": "Mehr über Remote-Open-Modi erfahren",
             "optimizeImages": "Heruntergeladene Bilder optimieren",
             "optimizeImagesHelp": "Beispielbilder optimieren, um Dateigröße zu reduzieren und Ladegeschwindigkeit zu verbessern (Metadaten bleiben erhalten)",
             "download": "Herunterladen",
@@ -557,7 +584,13 @@
         },
         "misc": {
             "includeTriggerWords": "Trigger Words in LoRA-Syntax einschließen",
-            "includeTriggerWordsHelp": "Trainierte Trigger Words beim Kopieren der LoRA-Syntax in die Zwischenablage einschließen"
+            "includeTriggerWordsHelp": "Trainierte Trigger Words beim Kopieren der LoRA-Syntax in die Zwischenablage einschließen",
+            "loraSyntaxFormat": "LoRA-Syntaxformat",
+            "loraSyntaxFormatHelp": "LoRA-Syntaxformat. Der vollständige Pfad enthält den Unterordnerpfad (<lora:style/anime/x:1.0>) für verlustfreie Modellauflösung. Legacy verwendet nur den Dateinamen (<lora:x:1.0>) — A1111-Konvention, kann bei doppelten Dateinamen in verschiedenen Ordnern zu Mehrdeutigkeiten führen.",
+            "loraSyntaxFormatOptions": {
+                "full": "Vollständiger Pfad (Unterordner/Name)",
+                "legacy": "Legacy A1111 (nur Name)"
+            }
         },
         "metadataArchive": {
             "enableArchiveDb": "Metadaten-Archiv-Datenbank aktivieren",
@@ -621,8 +654,6 @@
             },
             "refresh": {
                 "title": "Modelliste aktualisieren",
-                "quick": "Änderungen synchronisieren",
-                "quickTooltip": "Nach neuen oder fehlenden Modelldateien suchen, damit die Liste aktuell bleibt.",
                 "full": "Cache neu aufbauen",
                 "fullTooltip": "Alle Modelldetails aus Metadatendateien neu laden – nutzen, wenn die Bibliothek veraltet wirkt oder nach manuellen Änderungen."
             },
@@ -663,16 +694,30 @@
             "setContentRating": "Inhaltsbewertung für alle festlegen",
             "copyAll": "Alle Syntax kopieren",
             "refreshAll": "Alle Metadaten aktualisieren",
+            "repairMetadata": "Metadaten der Auswahl reparieren",
+            "reimportMetadata": "Aus Quelle neu importieren",
             "checkUpdates": "Auswahl auf Updates prüfen",
             "moveAll": "Alle in Ordner verschieben",
             "autoOrganize": "Automatisch organisieren",
             "skipMetadataRefresh": "Metadaten-Aktualisierung für ausgewählte Modelle überspringen",
             "resumeMetadataRefresh": "Metadaten-Aktualisierung für ausgewählte Modelle fortsetzen",
-            "deleteAll": "Alle Modelle löschen",
+            "setFavorite": "Als Favorit setzen",
+            "setFavoriteCount": "Als Favorit setzen ({favorited}/{total})",
+            "unfavorite": "Aus Favoriten entfernen",
+            "deleteAll": "Ausgewählte löschen",
             "downloadMissingLoras": "Fehlende LoRAs herunterladen",
+            "downloadExamples": "Beispielbilder herunterladen",
             "clear": "Auswahl löschen",
             "skipMetadataRefreshCount": "Überspringen（{count} Modelle）",
             "resumeMetadataRefreshCount": "Fortsetzen（{count} Modelle）",
+            "sendToWorkflow": "An Workflow senden",
+            "sections": {
+                "workflow": "Workflow",
+                "metadata": "Metadaten",
+                "attributes": "Attribute",
+                "organize": "Organisieren",
+                "download": "Download"
+            },
             "autoOrganizeProgress": {
                 "initializing": "Automatische Organisation wird initialisiert...",
                 "starting": "Automatische Organisation für {type} wird gestartet...",
@@ -698,6 +743,7 @@
             "setContentRating": "Inhaltsbewertung festlegen",
             "moveToFolder": "In Ordner verschieben",
             "repairMetadata": "Metadaten reparieren",
+            "reimportMetadata": "Aus Quelle neu importieren",
             "excludeModel": "Modell ausschließen",
             "restoreModel": "Modell wiederherstellen",
             "deleteModel": "Modell löschen",
@@ -785,8 +831,6 @@
             },
             "refresh": {
                 "title": "Rezeptliste aktualisieren",
-                "quick": "Änderungen synchronisieren",
-                "quickTooltip": "Änderungen synchronisieren - schnelle Aktualisierung ohne Cache-Neubau",
                 "full": "Cache neu aufbauen",
                 "fullTooltip": "Cache neu aufbauen - vollständiger Rescan aller Rezeptdateien"
             },
@@ -827,6 +871,13 @@
                 "skipped": "Rezept bereits in der neuesten Version, keine Reparatur erforderlich",
                 "failed": "Rezept-Reparatur fehlgeschlagen: {message}",
                 "missingId": "Rezept kann nicht repariert werden: Fehlende Rezept-ID"
+            },
+            "reimport": {
+                "starting": "Rezept wird aus Quelle neu importiert...",
+                "success": "Rezept erfolgreich neu importiert",
+                "noSourceUrl": "Rezept hat keine Quell-URL, Neuimport nicht möglich",
+                "failed": "Neuimport des Rezepts fehlgeschlagen: {message}",
+                "missingId": "Neuimport nicht möglich: Rezept-ID fehlt"
             }
         },
         "batchImport": {
@@ -904,9 +955,13 @@
     },
     "sidebar": {
         "modelRoot": "Stammverzeichnis",
+        "moreOptions": "Weitere Optionen",
         "collapseAll": "Alle Ordner einklappen",
         "pinSidebar": "Sidebar anheften",
         "unpinSidebar": "Sidebar lösen",
+        "hideOnThisPage": "Seitenleiste auf dieser Seite ausblenden",
+        "showSidebar": "Seitenleiste anzeigen",
+        "sidebarHiddenNotification": "Seitenleiste auf der Seite {page} ausgeblendet",
         "switchToListView": "Zur Listenansicht wechseln",
         "switchToTreeView": "Zur Baumansicht wechseln",
         "recursiveOn": "Unterordner einbeziehen",
@@ -926,6 +981,13 @@
         "empty": {
             "noFolders": "Keine Ordner gefunden",
             "dragHint": "Elemente hierher ziehen, um Ordner zu erstellen"
+        },
+        "folderUpdateCheck": {
+            "label": "Auf Updates in diesem Ordner prüfen",
+            "loading": "Prüfe {type}-Updates in diesem Ordner...",
+            "success": "{count} Update(s) für {type}s in diesem Ordner gefunden",
+            "none": "Alle {type}s in diesem Ordner sind aktuell",
+            "error": "Fehler beim Prüfen des Ordners auf {type}-Updates: {message}"
         }
     },
     "statistics": {
@@ -970,9 +1032,9 @@
         "download": {
             "title": "Modell von URL herunterladen",
             "titleWithType": "{type} von URL herunterladen",
-            "url": "Civitai URL",
             "civitaiUrl": "Civitai URL:",
             "placeholder": "https://civitai.com/models/...",
+            "urlHint": "Geben Sie eine CivitAI- oder CivArchive-URL pro Zeile ein. Unterstützt mehrere URLs für den Batch-Download.",
             "locationPreview": "Download-Speicherort Vorschau",
             "useDefaultPath": "Standardpfad verwenden",
             "useDefaultPathTooltip": "Wenn aktiviert, werden Dateien automatisch mit konfigurierten Pfadvorlagen organisiert",
@@ -994,6 +1056,11 @@
             "downloadedTooltip": "Zuvor heruntergeladen, aber derzeit nicht in Ihrer Bibliothek.",
             "alreadyInLibrary": "Bereits in Bibliothek",
             "autoOrganizedPath": "[Automatisch organisiert durch Pfadvorlage]",
+            "fileSelection": {
+                "title": "Dateiformat auswählen",
+                "files": "Dateien",
+                "select": "Datei auswählen"
+            },
             "errors": {
                 "invalidUrl": "Ungültiges Civitai URL-Format",
                 "noVersions": "Keine Versionen für dieses Modell verfügbar"
@@ -1058,6 +1125,12 @@
             "countMessage": "Modelle werden dauerhaft gelöscht.",
             "action": "Alle löschen"
         },
+        "bulkDeleteRecipes": {
+            "title": "Mehrere Rezepte löschen",
+            "message": "Sind Sie sicher, dass Sie alle ausgewählten Rezepte und ihre zugehörigen Dateien löschen möchten?",
+            "countMessage": "Rezepte werden dauerhaft gelöscht.",
+            "action": "Alle löschen"
+        },
         "checkUpdates": {
             "title": "Alle {typePlural} auf Updates prüfen?",
             "message": "Damit werden alle {typePlural} in deiner Bibliothek auf Updates geprüft. Bei großen Sammlungen kann das etwas länger dauern.",
@@ -1138,6 +1211,7 @@
                 "editModelName": "Modellname bearbeiten",
                 "editFileName": "Dateiname bearbeiten",
                 "editBaseModel": "Basis-Modell bearbeiten",
+                "editVersionName": "Versionsname bearbeiten",
                 "viewOnCivitai": "Auf Civitai anzeigen",
                 "viewOnCivitaiText": "Auf Civitai anzeigen",
                 "viewCreatorProfile": "Ersteller-Profil anzeigen",
@@ -1169,7 +1243,9 @@
             },
             "notes": {
                 "saved": "Notizen erfolgreich gespeichert",
-                "saveFailed": "Fehler beim Speichern der Notizen"
+                "saveFailed": "Fehler beim Speichern der Notizen",
+                "showMore": "Mehr anzeigen",
+                "showLess": "Weniger anzeigen"
             },
             "usageTips": {
                 "addPresetParameter": "Voreingestellten Parameter hinzufügen...",
@@ -1274,12 +1350,15 @@
                     "earlyAccess": "Früher Zugriff",
                     "earlyAccessTooltip": "Für diese Version ist derzeit Civitai Early Access erforderlich",
                     "ignored": "Ignoriert",
-                    "ignoredTooltip": "Für diese Version sind Update-Benachrichtigungen deaktiviert"
+                    "ignoredTooltip": "Für diese Version sind Update-Benachrichtigungen deaktiviert",
+                    "onSiteOnly": "Nur On-Site",
+                    "onSiteOnlyTooltip": "Diese Version ist nur für die On-Site-Generierung auf Civitai verfügbar"
                 },
                 "actions": {
                     "download": "Herunterladen",
                     "downloadTooltip": "Diese Version herunterladen",
                     "downloadEarlyAccessTooltip": "Diese Early-Access-Version von Civitai herunterladen",
+                    "downloadNotAllowedTooltip": "Diese Version ist nur für die On-Site-Generierung auf Civitai verfügbar",
                     "delete": "Löschen",
                     "deleteTooltip": "Diese lokale Version löschen",
                     "ignore": "Ignorieren",
@@ -1428,11 +1507,14 @@
             "noMatchingNodes": "Keine kompatiblen Knoten im aktuellen Workflow verfügbar",
             "noTargetNodeSelected": "Kein Zielknoten ausgewählt",
             "modelUpdated": "Modell im Workflow aktualisiert",
-            "modelFailed": "Fehler beim Aktualisieren des Modellknotens"
+            "modelFailed": "Fehler beim Aktualisieren des Modellknotens",
+            "embeddingAdded": "Embedding zum Workflow hinzugefügt",
+            "embeddingFailed": "Fehler beim Hinzufügen des Embeddings"
         },
         "nodeSelector": {
             "recipe": "Rezept",
             "lora": "LoRA",
+            "embedding": "Embedding",
             "replace": "Ersetzen",
             "append": "Anhängen",
             "selectTargetNode": "Zielknoten auswählen",
@@ -1442,6 +1524,10 @@
             "opened": "Beispielbilder-Ordner geöffnet",
             "openingFolder": "Beispielbilder-Ordner wird geöffnet",
             "failedToOpen": "Fehler beim Öffnen des Beispielbilder-Ordners",
+            "copiedPath": "Pfad in Zwischenablage kopiert: {{path}}",
+            "clipboardFallback": "Pfad: {{path}}",
+            "copiedUri": "Link in Zwischenablage kopiert: {{uri}}",
+            "uriClipboardFallback": "Link: {{uri}}",
             "setupRequired": "Beispielbilder-Speicher",
             "setupDescription": "Um benutzerdefinierte Beispielbilder hinzuzufügen, müssen Sie zuerst einen Download-Speicherort festlegen.",
             "setupUsage": "Dieser Pfad wird sowohl für heruntergeladene als auch für benutzerdefinierte Beispielbilder verwendet.",
@@ -1605,6 +1691,10 @@
             "noRecipeId": "Keine Rezept-ID verfügbar",
             "sendToWorkflowFailed": "Fehler beim Senden des Rezepts an den Workflow: {message}",
             "copyFailed": "Fehler beim Kopieren der Rezept-Syntax: {message}",
+            "createError": "Fehler beim Erstellen des Rezepts：{message}",
+            "createFailed": "Fehler beim Erstellen des Rezepts：{error}",
+            "createMissingData": "Erforderliche Daten zum Erstellen des Rezepts fehlen",
+            "created": "Rezept erfolgreich erstellt",
             "noMissingLoras": "Keine fehlenden LoRAs zum Herunterladen",
             "missingLorasInfoFailed": "Fehler beim Abrufen der Informationen für fehlende LoRAs",
             "preparingForDownloadFailed": "Fehler beim Vorbereiten der LoRAs für den Download",
@@ -1643,6 +1733,13 @@
             "batchImportBrowseFailed": "Failed to browse directory: {message}",
             "batchImportDirectorySelected": "Directory selected: {path}",
             "noRecipesSelected": "Keine Rezepte ausgewählt",
+            "repairBulkComplete": "Reparatur abgeschlossen: {repaired} repariert, {skipped} übersprungen (von {total})",
+            "repairBulkSkipped": "Keine Reparatur für die {total} ausgewählten Rezepte erforderlich",
+            "repairBulkFailed": "Reparatur der ausgewählten Rezepte fehlgeschlagen: {message}",
+            "reimporting": "Rezept wird aus Quelle neu importiert...",
+            "reimportSuccess": "Rezept erfolgreich neu importiert",
+            "reimportBulkComplete": "Neuimport abgeschlossen: {completed} importiert, {failed} fehlgeschlagen (von {total})",
+            "reimportBulkFailed": "Neuimport einiger Rezepte fehlgeschlagen",
             "noMissingLorasInSelection": "Keine fehlenden LoRAs in ausgewählten Rezepten gefunden",
             "noLoraRootConfigured": "Kein LoRA-Stammverzeichnis konfiguriert. Bitte legen Sie ein Standard-LoRA-Stammverzeichnis in den Einstellungen fest."
         },
@@ -1673,6 +1770,11 @@
             "bulkContentRatingSet": "Inhaltsbewertung auf {level} für {count} Modell(e) gesetzt",
             "bulkContentRatingPartial": "Inhaltsbewertung auf {level} für {success} Modell(e) gesetzt, {failed} fehlgeschlagen",
             "bulkContentRatingFailed": "Inhaltsbewertung für ausgewählte Modelle konnte nicht aktualisiert werden",
+            "bulkFavoriteUpdating": "Füge {count} Modell(e) zu Favoriten hinzu...",
+            "bulkUnfavoriteUpdating": "Entferne {count} Modell(e) aus Favoriten...",
+            "bulkFavoritePartialAdded": "{success} Modell(e) zu Favoriten hinzugefügt, {failed} fehlgeschlagen",
+            "bulkFavoritePartialRemoved": "{success} Modell(e) aus Favoriten entfernt, {failed} fehlgeschlagen",
+            "bulkFavoriteFailed": "Fehler beim Aktualisieren des Favoritenstatus",
             "bulkUpdatesChecking": "Ausgewählte {type}-Modelle werden auf Updates geprüft...",
             "bulkUpdatesSuccess": "Updates für {count} ausgewählte {type}-Modelle verfügbar",
             "bulkUpdatesNone": "Keine Updates für ausgewählte {type}-Modelle gefunden",
@@ -1875,18 +1977,52 @@
             "warning": "Handlungsbedarf",
             "error": "Aktion erforderlich"
         },
+        "issues": {
+            "civitai_api_key": {
+                "title": "Civitai API Key"
+            },
+            "cache_health": {
+                "title": "Model Cache Health"
+            },
+            "filename_conflicts": {
+                "title": "Duplicate Filename Conflicts"
+            },
+            "ui_version": {
+                "title": "UI Version"
+            }
+        },
         "actions": {
             "runAgain": "Erneut ausführen",
-            "exportBundle": "Paket exportieren"
+            "exportBundle": "Paket exportieren",
+            "open-settings": "Open Settings",
+            "open-settings-syntax-format": "Switch to Full Path Syntax",
+            "repair-cache": "Rebuild Cache",
+            "resolve-filename-conflicts": "Resolve Conflicts",
+            "reload-page": "Reload UI"
+        },
+        "labels": {
+            "conflicts": "Conflicts",
+            "version": "Version"
         },
         "toast": {
             "loadFailed": "Diagnose konnte nicht geladen werden: {message}",
             "repairSuccess": "Cache-Neuaufbau abgeschlossen.",
             "repairFailed": "Cache-Neuaufbau fehlgeschlagen: {message}",
             "exportSuccess": "Diagnosepaket exportiert.",
-            "exportFailed": "Export des Diagnosepakets fehlgeschlagen: {message}"
+            "exportFailed": "Export des Diagnosepakets fehlgeschlagen: {message}",
+            "conflictsResolved": "{count} Dateinamenskonflikt(e) gelöst.",
+            "conflictsResolveFailed": "Auflösung der Dateinamenskonflikte fehlgeschlagen: {message}"
         }
     },
+    "conflictConfirm": {
+        "title": "Dateinamenskonflikte auflösen",
+        "message": "Umbenennen durch Anhängen eines 4-stelligen Hashs an jeden doppelten Dateinamen.",
+        "note": "Dieser Vorgang benennt Dateien auf der Festplatte um. Modellreferenzen in vorhandenen Workflows müssen möglicherweise aktualisiert werden, wenn Sie das A1111-Syntaxformat verwenden.",
+        "detail": "Beispiel: <code>filename_v1.2</code> → <code>filename_v1.2-ab3c</code>",
+        "impact": "Benennt <strong>{count}</strong> Datei(en) in <strong>{groups}</strong> Duplikatgruppe(n) um",
+        "confirm": "Dateien umbenennen",
+        "cancel": "Abbrechen"
+    },
     "banners": {
         "versionMismatch": {
             "title": "Anwendungs-Update erkannt",

locales/en.json

@@ -15,7 +15,10 @@
             "settings": "Settings",
             "help": "Help",
             "add": "Add",
-            "close": "Close"
+            "close": "Close",
+            "menu": "Menu",
+            "remove": "Remove",
+            "change": "Change"
         },
         "status": {
             "loading": "Loading...",
@@ -110,6 +113,7 @@
             "replacePreview": "Replace Preview",
             "copyCheckpointName": "Copy checkpoint name",
             "copyEmbeddingName": "Copy embedding name",
+            "embeddingNameCopied": "Embedding syntax copied",
             "sendCheckpointToWorkflow": "Send to ComfyUI",
             "sendEmbeddingToWorkflow": "Send to ComfyUI"
         },
@@ -231,7 +235,10 @@
             "license": "License",
             "noCreditRequired": "No Credit Required",
             "allowSellingGeneratedContent": "Allow Selling",
+            "allowSellingGeneratedContentTooltip": "Allow selling generated images",
+            "noCreditRequiredTooltip": "Use the model without crediting the creator",
             "noTags": "No tags",
+            "autoTags": "Auto Tags",
             "noBaseModelMatches": "No base models match the current search.",
             "clearAll": "Clear All Filters",
             "any": "Any",
@@ -265,10 +272,10 @@
         },
         "downloadBackend": {
             "label": "Download backend",
-            "help": "Choose how model files are downloaded. Python uses the built-in downloader. aria2 uses the experimental external downloader process.",
+            "help": "Choose how model files are downloaded. Python uses the built-in downloader. aria2 uses the recommended external downloader process.",
             "options": {
                 "python": "Python (built-in)",
-                "aria2": "aria2 (experimental)"
+                "aria2": "aria2 (recommended)"
             }
         },
         "aria2cPath": {
@@ -276,6 +283,7 @@
             "help": "Optional path to the aria2c executable. Leave empty to use aria2c from your system PATH.",
             "placeholder": "Leave empty to use aria2c from PATH"
         },
+        "aria2HelpLink": "Learn how to set up the aria2 download backend",
         "civitaiHostBanner": {
             "title": "Civitai host preference available",
             "content": "Civitai now uses civitai.com for SFW content and civitai.red for unrestricted content. You can change which site opens by default in Settings.",
@@ -427,6 +435,8 @@
                 "hover": "Reveal on Hover"
             },
             "cardInfoDisplayHelp": "Choose when to display model information and action buttons",
+            "showVersionOnCard": "Show Version on Card",
+            "showVersionOnCardHelp": "Show or hide the version name on model cards",
             "modelCardFooterAction": "Model Card Button Action",
             "modelCardFooterActionOptions": {
                 "exampleImages": "Open Example Images",
@@ -438,7 +448,9 @@
                 "modelName": "Model Name",
                 "fileName": "File Name"
             },
-            "modelNameDisplayHelp": "Choose what to display in the model card footer"
+            "modelNameDisplayHelp": "Choose what to display in the model card footer",
+            "cardBlurAmount": "Card Overlay Blur",
+            "cardBlurAmountHelp": "Adjust the blur intensity of the header and footer overlays on model and recipe cards (0 = no blur, 20 = maximum blur)."
         },
         "folderSettings": {
             "activeLibrary": "Active Library",
@@ -538,6 +550,21 @@
             "downloadLocationHelp": "Enter the folder path where example images from Civitai will be saved",
             "autoDownload": "Auto Download Example Images",
             "autoDownloadHelp": "Automatically download example images for models that don't have them (requires download location to be set)",
+            "openMode": "Open Example Images Action",
+            "openModeHelp": "Choose whether the action opens on the server, copies a mapped local path, or launches a custom URI.",
+            "openModeOptions": {
+                "system": "Open on server",
+                "clipboard": "Copy local path",
+                "uriTemplate": "Open custom URI"
+            },
+            "localRoot": "Local Example Images Root",
+            "localRootHelp": "Optional local or mounted root that mirrors the server example images directory. If blank, the server path is reused.",
+            "localRootPlaceholder": "Example: /Volumes/ComfyUI/example_images",
+            "uriTemplate": "Open URI Template",
+            "uriTemplateHelp": "Use a custom deep link such as a file URI or a Shortcuts link.",
+            "uriTemplatePlaceholder": "Example: shortcuts://run-shortcut?name=Open%20Finder&input=text&text={{encoded_local_path}}",
+            "uriTemplatePlaceholders": "Available placeholders: {{local_path}}, {{encoded_local_path}}, {{relative_path}}, {{encoded_relative_path}}, {{file_uri}}, {{encoded_file_uri}}",
+            "openModeWikiLink": "Learn more about remote open modes",
             "optimizeImages": "Optimize Downloaded Images",
             "optimizeImagesHelp": "Optimize example images to reduce file size and improve loading speed (metadata will be preserved)",
             "download": "Download",
@@ -557,7 +584,13 @@
         },
         "misc": {
             "includeTriggerWords": "Include Trigger Words in LoRA Syntax",
-            "includeTriggerWordsHelp": "Include trained trigger words when copying LoRA syntax to clipboard"
+            "includeTriggerWordsHelp": "Include trained trigger words when copying LoRA syntax to clipboard",
+            "loraSyntaxFormat": "LoRA Syntax Format",
+            "loraSyntaxFormatHelp": "LoRA syntax format. Full includes subfolder path (<lora:style/anime/x:1.0>) for lossless model resolution. Legacy uses filename only (<lora:x:1.0>) — A1111 convention, may be ambiguous with duplicate filenames across folders.",
+            "loraSyntaxFormatOptions": {
+                "full": "Full path (subfolder/name)",
+                "legacy": "Legacy A1111 (name only)"
+            }
         },
         "metadataArchive": {
             "enableArchiveDb": "Enable Metadata Archive Database",
@@ -621,8 +654,6 @@
             },
             "refresh": {
                 "title": "Refresh model list",
-                "quick": "Sync Changes",
-                "quickTooltip": "Scan for new or missing model files so the list stays current.",
                 "full": "Rebuild Cache",
                 "fullTooltip": "Reload all model details from metadata files—use if the library looks out of date or after manual edits."
             },
@@ -663,16 +694,30 @@
             "setContentRating": "Set Content Rating for Selected",
             "copyAll": "Copy Selected Syntax",
             "refreshAll": "Refresh Selected Metadata",
+            "repairMetadata": "Repair Metadata for Selected",
+            "reimportMetadata": "Re-import from Source",
             "checkUpdates": "Check Updates for Selected",
             "moveAll": "Move Selected to Folder",
             "autoOrganize": "Auto-Organize Selected",
             "skipMetadataRefresh": "Skip Metadata Refresh for Selected",
             "resumeMetadataRefresh": "Resume Metadata Refresh for Selected",
-            "deleteAll": "Delete Selected Models",
+            "setFavorite": "Set as Favorite",
+            "setFavoriteCount": "Set as Favorite ({favorited}/{total})",
+            "unfavorite": "Remove from Favorites",
+            "deleteAll": "Delete Selected",
             "downloadMissingLoras": "Download Missing LoRAs",
+            "downloadExamples": "Download Example Images",
             "clear": "Clear Selection",
             "skipMetadataRefreshCount": "Skip ({count} models)",
             "resumeMetadataRefreshCount": "Resume ({count} models)",
+            "sendToWorkflow": "Send to Workflow",
+            "sections": {
+                "workflow": "Workflow",
+                "metadata": "Metadata",
+                "attributes": "Attributes",
+                "organize": "Organize",
+                "download": "Download"
+            },
             "autoOrganizeProgress": {
                 "initializing": "Initializing auto-organize...",
                 "starting": "Starting auto-organize for {type}...",
@@ -698,6 +743,7 @@
             "setContentRating": "Set Content Rating",
             "moveToFolder": "Move to Folder",
             "repairMetadata": "Repair metadata",
+            "reimportMetadata": "Re-import from Source",
             "excludeModel": "Exclude Model",
             "restoreModel": "Restore Model",
             "deleteModel": "Delete Model",
@@ -785,8 +831,6 @@
             },
             "refresh": {
                 "title": "Refresh recipe list",
-                "quick": "Sync Changes",
-                "quickTooltip": "Sync changes - quick refresh without rebuilding cache",
                 "full": "Rebuild Cache",
                 "fullTooltip": "Rebuild cache - full rescan of all recipe files"
             },
@@ -827,6 +871,13 @@
                 "skipped": "Recipe already at latest version, no repair needed",
                 "failed": "Failed to repair recipe: {message}",
                 "missingId": "Cannot repair recipe: Missing recipe ID"
+            },
+            "reimport": {
+                "starting": "Re-importing recipe from source...",
+                "success": "Recipe re-imported successfully",
+                "noSourceUrl": "Recipe has no source URL, cannot re-import",
+                "failed": "Failed to re-import recipe: {message}",
+                "missingId": "Cannot re-import recipe: Missing recipe ID"
             }
         },
         "batchImport": {
@@ -904,9 +955,13 @@
     },
     "sidebar": {
         "modelRoot": "Root",
+        "moreOptions": "More options",
         "collapseAll": "Collapse All Folders",
         "pinSidebar": "Pin Sidebar",
         "unpinSidebar": "Unpin Sidebar",
+        "hideOnThisPage": "Hide sidebar on this page",
+        "showSidebar": "Show sidebar",
+        "sidebarHiddenNotification": "Folder sidebar hidden on {page} page",
         "switchToListView": "Switch to List View",
         "switchToTreeView": "Switch to Tree View",
         "recursiveOn": "Include subfolders",
@@ -926,6 +981,13 @@
         "empty": {
             "noFolders": "No folders found",
             "dragHint": "Drag items here to create folders"
+        },
+        "folderUpdateCheck": {
+            "label": "Check for updates in this folder",
+            "loading": "Checking {type} updates for this folder...",
+            "success": "Found {count} update(s) for {type}s in this folder",
+            "none": "All {type}s in this folder are up to date",
+            "error": "Failed to check folder for {type} updates: {message}"
         }
     },
     "statistics": {
@@ -970,9 +1032,9 @@
         "download": {
             "title": "Download Model from URL",
             "titleWithType": "Download {type} from URL",
-            "url": "Civitai URL",
+            "civitaiUrl": "Civitai URL(s):",
-            "civitaiUrl": "Civitai URL:",
             "placeholder": "https://civitai.com/models/...",
+            "urlHint": "Enter one CivitAI or CivArchive URL per line. Supports multiple URLs for batch download.",
             "locationPreview": "Download Location Preview",
             "useDefaultPath": "Use Default Path",
             "useDefaultPathTooltip": "When enabled, files are automatically organized using configured path templates",
@@ -994,6 +1056,11 @@
             "downloadedTooltip": "Previously downloaded, but it is not currently in your library.",
             "alreadyInLibrary": "Already in Library",
             "autoOrganizedPath": "[Auto-organized by path template]",
+            "fileSelection": {
+                "title": "Select File Format",
+                "files": "files",
+                "select": "Select File"
+            },
             "errors": {
                 "invalidUrl": "Invalid Civitai URL format",
                 "noVersions": "No versions available for this model"
@@ -1058,6 +1125,12 @@
             "countMessage": "models will be permanently deleted.",
             "action": "Delete All"
         },
+        "bulkDeleteRecipes": {
+            "title": "Delete Multiple Recipes",
+            "message": "Are you sure you want to delete all selected recipes and their associated files?",
+            "countMessage": "recipes will be permanently deleted.",
+            "action": "Delete All"
+        },
         "checkUpdates": {
             "title": "Check updates for all {typePlural}?",
             "message": "This checks every {typePlural} in your library for updates. Large collections may take a little longer.",
@@ -1138,6 +1211,7 @@
                 "editModelName": "Edit model name",
                 "editFileName": "Edit file name",
                 "editBaseModel": "Edit base model",
+                "editVersionName": "Edit version name",
                 "viewOnCivitai": "View on Civitai",
                 "viewOnCivitaiText": "View on Civitai",
                 "viewCreatorProfile": "View Creator Profile",
@@ -1169,7 +1243,9 @@
             },
             "notes": {
                 "saved": "Notes saved successfully",
-                "saveFailed": "Failed to save notes"
+                "saveFailed": "Failed to save notes",
+                "showMore": "Show more",
+                "showLess": "Show less"
             },
             "usageTips": {
                 "addPresetParameter": "Add preset parameter...",
@@ -1274,12 +1350,15 @@
                     "earlyAccess": "Early Access",
                     "earlyAccessTooltip": "This version currently requires Civitai early access",
                     "ignored": "Ignored",
-                    "ignoredTooltip": "Update notifications are disabled for this version"
+                    "ignoredTooltip": "Update notifications are disabled for this version",
+                    "onSiteOnly": "On-Site Only",
+                    "onSiteOnlyTooltip": "This version is only available for on-site generation on Civitai"
                 },
                 "actions": {
                     "download": "Download",
                     "downloadTooltip": "Download this version",
                     "downloadEarlyAccessTooltip": "Download this early access version from Civitai",
+                    "downloadNotAllowedTooltip": "This version is only available for on-site generation on Civitai",
                     "delete": "Delete",
                     "deleteTooltip": "Delete this local version",
                     "ignore": "Ignore",
@@ -1428,11 +1507,14 @@
             "noMatchingNodes": "No compatible nodes available in the current workflow",
             "noTargetNodeSelected": "No target node selected",
             "modelUpdated": "Model updated in workflow",
-            "modelFailed": "Failed to update model node"
+            "modelFailed": "Failed to update model node",
+            "embeddingAdded": "Embedding added to workflow",
+            "embeddingFailed": "Failed to add embedding"
         },
         "nodeSelector": {
             "recipe": "Recipe",
             "lora": "LoRA",
+            "embedding": "Embedding",
             "replace": "Replace",
             "append": "Append",
             "selectTargetNode": "Select target node",
@@ -1442,6 +1524,10 @@
             "opened": "Example images folder opened",
             "openingFolder": "Opening example images folder",
             "failedToOpen": "Failed to open example images folder",
+            "copiedPath": "Path copied to clipboard: {{path}}",
+            "clipboardFallback": "Path: {{path}}",
+            "copiedUri": "Link copied to clipboard: {{uri}}",
+            "uriClipboardFallback": "Link: {{uri}}",
             "setupRequired": "Example Images Storage",
             "setupDescription": "To add custom example images, you need to set a download location first.",
             "setupUsage": "This path is used for both downloaded and custom example images.",
@@ -1605,6 +1691,10 @@
             "noRecipeId": "No recipe ID available",
             "sendToWorkflowFailed": "Failed to send recipe to workflow: {message}",
             "copyFailed": "Error copying recipe syntax: {message}",
+            "createError": "Error creating recipe: {message}",
+            "createFailed": "Failed to create recipe: {error}",
+            "createMissingData": "Missing required data to create recipe",
+            "created": "Recipe created successfully",
             "noMissingLoras": "No missing LoRAs to download",
             "missingLorasInfoFailed": "Failed to get information for missing LoRAs",
             "preparingForDownloadFailed": "Error preparing LoRAs for download",
@@ -1643,6 +1733,13 @@
             "batchImportBrowseFailed": "Failed to browse directory: {message}",
             "batchImportDirectorySelected": "Directory selected: {path}",
             "noRecipesSelected": "No recipes selected",
+            "repairBulkComplete": "Repair complete: {repaired} repaired, {skipped} skipped (of {total})",
+            "repairBulkSkipped": "No repair needed for any of the {total} selected recipes",
+            "repairBulkFailed": "Failed to repair selected recipes: {message}",
+            "reimporting": "Re-importing recipe from source...",
+            "reimportSuccess": "Recipe re-imported successfully",
+            "reimportBulkComplete": "Re-import complete: {completed} re-imported, {failed} failed (of {total})",
+            "reimportBulkFailed": "Failed to re-import some recipes",
             "noMissingLorasInSelection": "No missing LoRAs found in selected recipes",
             "noLoraRootConfigured": "No LoRA root directory configured. Please set a default LoRA root in settings."
         },
@@ -1673,6 +1770,11 @@
             "bulkContentRatingSet": "Set content rating to {level} for {count} model(s)",
             "bulkContentRatingPartial": "Set content rating to {level} for {success} model(s), {failed} failed",
             "bulkContentRatingFailed": "Failed to update content rating for selected models",
+            "bulkFavoriteUpdating": "Adding {count} model(s) to favorites...",
+            "bulkUnfavoriteUpdating": "Removing {count} model(s) from favorites...",
+            "bulkFavoritePartialAdded": "Added {success} model(s) to favorites, {failed} failed",
+            "bulkFavoritePartialRemoved": "Removed {success} model(s) from favorites, {failed} failed",
+            "bulkFavoriteFailed": "Failed to update favorite status for selected models",
             "bulkUpdatesChecking": "Checking selected {type}(s) for updates...",
             "bulkUpdatesSuccess": "Updates available for {count} selected {type}(s)",
             "bulkUpdatesNone": "No updates found for selected {type}(s)",
@@ -1875,18 +1977,52 @@
             "warning": "Needs Attention",
             "error": "Action Required"
         },
+        "issues": {
+            "civitai_api_key": {
+                "title": "Civitai API Key"
+            },
+            "cache_health": {
+                "title": "Model Cache Health"
+            },
+            "filename_conflicts": {
+                "title": "Duplicate Filename Conflicts"
+            },
+            "ui_version": {
+                "title": "UI Version"
+            }
+        },
         "actions": {
             "runAgain": "Run Again",
-            "exportBundle": "Export Bundle"
+            "exportBundle": "Export Bundle",
+            "open-settings": "Open Settings",
+            "open-settings-syntax-format": "Switch to Full Path Syntax",
+            "repair-cache": "Rebuild Cache",
+            "resolve-filename-conflicts": "Resolve Conflicts",
+            "reload-page": "Reload UI"
+        },
+        "labels": {
+            "conflicts": "Conflicts",
+            "version": "Version"
         },
         "toast": {
             "loadFailed": "Failed to load diagnostics: {message}",
             "repairSuccess": "Cache rebuild completed.",
             "repairFailed": "Cache rebuild failed: {message}",
             "exportSuccess": "Diagnostics bundle exported.",
-            "exportFailed": "Failed to export diagnostics bundle: {message}"
+            "exportFailed": "Failed to export diagnostics bundle: {message}",
+            "conflictsResolved": "{count} filename conflict(s) resolved.",
+            "conflictsResolveFailed": "Failed to resolve filename conflicts: {message}"
         }
     },
+    "conflictConfirm": {
+        "title": "Resolve Filename Conflicts",
+        "message": "Renaming by appending a 4-character hash to each duplicate filename.",
+        "note": "This operation renames files on disk. Model references in existing workflows may need updating if you use the A1111 syntax format.",
+        "detail": "Example: <code>filename_v1.2</code> → <code>filename_v1.2-ab3c</code>",
+        "impact": "Will rename <strong>{count}</strong> file(s) across <strong>{groups}</strong> duplicate group(s).",
+        "confirm": "Rename Files",
+        "cancel": "Cancel"
+    },
     "banners": {
         "versionMismatch": {
             "title": "Application Update Detected",

locales/es.json

@@ -15,7 +15,10 @@
             "settings": "Configuración",
             "help": "Ayuda",
             "add": "Añadir",
-            "close": "Cerrar"
+            "close": "Cerrar",
+            "menu": "Menú",
+            "remove": "Eliminar",
+            "change": "Cambiar"
         },
         "status": {
             "loading": "Cargando...",
@@ -110,6 +113,7 @@
             "replacePreview": "Reemplazar vista previa",
             "copyCheckpointName": "Copiar nombre del checkpoint",
             "copyEmbeddingName": "Copiar nombre del embedding",
+            "embeddingNameCopied": "Sintaxis de embedding copiada",
             "sendCheckpointToWorkflow": "Enviar a ComfyUI",
             "sendEmbeddingToWorkflow": "Enviar a ComfyUI"
         },
@@ -231,7 +235,10 @@
             "license": "Licencia",
             "noCreditRequired": "Sin crédito requerido",
             "allowSellingGeneratedContent": "Venta permitida",
+            "allowSellingGeneratedContentTooltip": "Permitir la venta de imágenes generadas",
+            "noCreditRequiredTooltip": "Usar el modelo sin atribuir al creador",
             "noTags": "Sin etiquetas",
+            "autoTags": "Etiquetas automáticas",
             "noBaseModelMatches": "Ningún modelo base coincide con la búsqueda actual.",
             "clearAll": "Limpiar todos los filtros",
             "any": "Cualquiera",
@@ -265,10 +272,10 @@
         },
         "downloadBackend": {
             "label": "Backend de descarga",
-            "help": "Elige cómo se descargan los archivos del modelo. Python usa el descargador integrado. aria2 usa el proceso externo experimental de descarga.",
+            "help": "Elige cómo se descargan los archivos del modelo. Python usa el descargador integrado. aria2 usa el proceso externo recomendado de descarga.",
             "options": {
                 "python": "Python (integrado)",
-                "aria2": "aria2 (experimental)"
+                "aria2": "aria2 (recomendado)"
             }
         },
         "aria2cPath": {
@@ -276,6 +283,7 @@
             "help": "Ruta opcional al ejecutable aria2c. Déjalo vacío para usar aria2c desde el PATH del sistema.",
             "placeholder": "Déjalo vacío para usar aria2c desde el PATH"
         },
+        "aria2HelpLink": "Aprende a configurar el backend de descarga aria2",
         "civitaiHostBanner": {
             "title": "Preferencia de host de Civitai disponible",
             "content": "Civitai ahora usa civitai.com para contenido SFW y civitai.red para contenido sin restricciones. Puedes cambiar en Ajustes qué sitio se abre por defecto.",
@@ -427,6 +435,8 @@
                 "hover": "Mostrar al pasar el ratón"
             },
             "cardInfoDisplayHelp": "Elige cuándo mostrar información del modelo y botones de acción",
+            "showVersionOnCard": "Mostrar versión en la tarjeta",
+            "showVersionOnCardHelp": "Mostrar u ocultar el nombre de versión en las tarjetas de modelo",
             "modelCardFooterAction": "Acción del botón de tarjeta de modelo",
             "modelCardFooterActionOptions": {
                 "exampleImages": "Abrir imágenes de ejemplo",
@@ -438,7 +448,9 @@
                 "modelName": "Nombre del modelo",
                 "fileName": "Nombre del archivo"
             },
-            "modelNameDisplayHelp": "Elige qué mostrar en el pie de la tarjeta del modelo"
+            "modelNameDisplayHelp": "Elige qué mostrar en el pie de la tarjeta del modelo",
+            "cardBlurAmount": "Desenfoque de superposición de tarjetas",
+            "cardBlurAmountHelp": "Ajuste la intensidad de desenfoque de las superposiciones del encabezado y pie de página en las tarjetas de modelos y recetas (0 = sin desenfoque, 20 = desenfoque máximo)."
         },
         "folderSettings": {
             "activeLibrary": "Biblioteca activa",
@@ -538,6 +550,21 @@
             "downloadLocationHelp": "Introduce la ruta de la carpeta donde se guardarán las imágenes de ejemplo de Civitai",
             "autoDownload": "Descargar automáticamente imágenes de ejemplo",
             "autoDownloadHelp": "Descargar automáticamente imágenes de ejemplo para modelos que no las tengan (requiere que se establezca la ubicación de descarga)",
+            "openMode": "Acción al abrir imágenes de ejemplo",
+            "openModeHelp": "Elige si la acción se abre en el servidor, copia una ruta local asignada o lanza una URI personalizada.",
+            "openModeOptions": {
+                "system": "Abrir en el servidor",
+                "clipboard": "Copiar ruta local",
+                "uriTemplate": "Abrir URI personalizada"
+            },
+            "localRoot": "Raíz local de imágenes de ejemplo",
+            "localRootHelp": "Raíz local u montada opcional que refleja el directorio de imágenes de ejemplo del servidor. Si se deja en blanco, se reutiliza la ruta del servidor.",
+            "localRootPlaceholder": "Ejemplo: /Volumes/ComfyUI/example_images",
+            "uriTemplate": "Abrir plantilla de URI",
+            "uriTemplateHelp": "Usa un enlace profundo personalizado, como un URI de archivo o un enlace de Shortcuts.",
+            "uriTemplatePlaceholder": "Ejemplo: shortcuts://run-shortcut?name=Open%20Finder&input=text&text={{encoded_local_path}}",
+            "uriTemplatePlaceholders": "Marcadores disponibles: {{local_path}}, {{encoded_local_path}}, {{relative_path}}, {{encoded_relative_path}}, {{file_uri}}, {{encoded_file_uri}}",
+            "openModeWikiLink": "Más información sobre los modos de apertura remota",
             "optimizeImages": "Optimizar imágenes descargadas",
             "optimizeImagesHelp": "Optimizar imágenes de ejemplo para reducir el tamaño del archivo y mejorar la velocidad de carga (se preservarán los metadatos)",
             "download": "Descargar",
@@ -557,7 +584,13 @@
         },
         "misc": {
             "includeTriggerWords": "Incluir palabras clave en la sintaxis de LoRA",
-            "includeTriggerWordsHelp": "Incluir palabras clave entrenadas al copiar la sintaxis de LoRA al portapapeles"
+            "includeTriggerWordsHelp": "Incluir palabras clave entrenadas al copiar la sintaxis de LoRA al portapapeles",
+            "loraSyntaxFormat": "Formato de sintaxis LoRA",
+            "loraSyntaxFormatHelp": "Formato de sintaxis LoRA. El formato completo incluye la ruta de la subcarpeta (<lora:style/anime/x:1.0>) para una resolución de modelo sin pérdidas. El formato heredado usa solo el nombre del archivo (<lora:x:1.0>) — convención A1111, puede ser ambiguo con nombres de archivo duplicados entre carpetas.",
+            "loraSyntaxFormatOptions": {
+                "full": "Ruta completa (subcarpeta/nombre)",
+                "legacy": "A1111 heredado (solo nombre)"
+            }
         },
         "metadataArchive": {
             "enableArchiveDb": "Habilitar base de datos de archivo de metadatos",
@@ -621,8 +654,6 @@
             },
             "refresh": {
                 "title": "Actualizar lista de modelos",
-                "quick": "Sincronizar cambios",
-                "quickTooltip": "Busca archivos de modelo nuevos o faltantes para mantener la lista al día.",
                 "full": "Reconstruir caché",
                 "fullTooltip": "Vuelve a cargar todos los detalles desde los archivos de metadatos; úsalo si la biblioteca parece desactualizada o tras ediciones manuales."
             },
@@ -663,16 +694,30 @@
             "setContentRating": "Establecer clasificación de contenido para todos",
             "copyAll": "Copiar toda la sintaxis",
             "refreshAll": "Actualizar todos los metadatos",
+            "repairMetadata": "Reparar metadatos de la selección",
+            "reimportMetadata": "Reimportar desde origen",
             "checkUpdates": "Comprobar actualizaciones para la selección",
             "moveAll": "Mover todos a carpeta",
             "autoOrganize": "Auto-organizar seleccionados",
             "skipMetadataRefresh": "Omitir actualización de metadatos para seleccionados",
             "resumeMetadataRefresh": "Reanudar actualización de metadatos para seleccionados",
-            "deleteAll": "Eliminar todos los modelos",
+            "setFavorite": "Marcar como favorito",
+            "setFavoriteCount": "Marcar como favorito ({favorited}/{total})",
+            "unfavorite": "Quitar de favoritos",
+            "deleteAll": "Eliminar seleccionados",
             "downloadMissingLoras": "Descargar LoRAs faltantes",
+            "downloadExamples": "Descargar imágenes de ejemplo",
             "clear": "Limpiar selección",
             "skipMetadataRefreshCount": "Omitir（{count} modelos）",
             "resumeMetadataRefreshCount": "Reanudar（{count} modelos）",
+            "sendToWorkflow": "Enviar al workflow",
+            "sections": {
+                "workflow": "Workflow",
+                "metadata": "Metadatos",
+                "attributes": "Atributos",
+                "organize": "Organizar",
+                "download": "Descargar"
+            },
             "autoOrganizeProgress": {
                 "initializing": "Inicializando auto-organización...",
                 "starting": "Iniciando auto-organización para {type}...",
@@ -698,6 +743,7 @@
             "setContentRating": "Establecer clasificación de contenido",
             "moveToFolder": "Mover a carpeta",
             "repairMetadata": "Reparar metadatos",
+            "reimportMetadata": "Reimportar desde origen",
             "excludeModel": "Excluir modelo",
             "restoreModel": "Restaurar modelo",
             "deleteModel": "Eliminar modelo",
@@ -785,8 +831,6 @@
             },
             "refresh": {
                 "title": "Actualizar lista de recetas",
-                "quick": "Sincronizar cambios",
-                "quickTooltip": "Sincronizar cambios - actualización rápida sin reconstruir caché",
                 "full": "Reconstruir caché",
                 "fullTooltip": "Reconstruir caché - reescaneo completo de todos los archivos de recetas"
             },
@@ -827,6 +871,13 @@
                 "skipped": "La receta ya está en la última versión, no se necesita reparación",
                 "failed": "Error al reparar la receta: {message}",
                 "missingId": "No se puede reparar la receta: falta el ID de la receta"
+            },
+            "reimport": {
+                "starting": "Reimportando receta desde origen...",
+                "success": "Receta reimportada exitosamente",
+                "noSourceUrl": "La receta no tiene URL de origen, no se puede reimportar",
+                "failed": "Error al reimportar la receta: {message}",
+                "missingId": "No se puede reimportar la receta: falta el ID"
             }
         },
         "batchImport": {
@@ -904,9 +955,13 @@
     },
     "sidebar": {
         "modelRoot": "Raíz",
+        "moreOptions": "Más opciones",
         "collapseAll": "Colapsar todas las carpetas",
         "pinSidebar": "Fijar barra lateral",
         "unpinSidebar": "Desfijar barra lateral",
+        "hideOnThisPage": "Ocultar barra lateral en esta página",
+        "showSidebar": "Mostrar barra lateral",
+        "sidebarHiddenNotification": "Barra lateral oculta en la página {page}",
         "switchToListView": "Cambiar a vista de lista",
         "switchToTreeView": "Cambiar a vista de árbol",
         "recursiveOn": "Incluir subcarpetas",
@@ -926,6 +981,13 @@
         "empty": {
             "noFolders": "No se encontraron carpetas",
             "dragHint": "Arrastra elementos aquí para crear carpetas"
+        },
+        "folderUpdateCheck": {
+            "label": "Buscar actualizaciones en esta carpeta",
+            "loading": "Buscando actualizaciones de {type} en esta carpeta...",
+            "success": "Se encontraron {count} actualización(es) para {type}s en esta carpeta",
+            "none": "Todos los {type}s en esta carpeta están actualizados",
+            "error": "Error al buscar actualizaciones de {type} en la carpeta: {message}"
         }
     },
     "statistics": {
@@ -970,9 +1032,9 @@
         "download": {
             "title": "Descargar modelo desde URL",
             "titleWithType": "Descargar {type} desde URL",
-            "url": "URL de Civitai",
             "civitaiUrl": "URL de Civitai:",
             "placeholder": "https://civitai.com/models/...",
+            "urlHint": "Ingrese una URL de CivitAI o CivArchive por línea. Admite múltiples URLs para descarga por lotes.",
             "locationPreview": "Vista previa de ubicación de descarga",
             "useDefaultPath": "Usar ruta predeterminada",
             "useDefaultPathTooltip": "Cuando está habilitado, los archivos se organizan automáticamente usando plantillas de rutas configuradas",
@@ -994,6 +1056,11 @@
             "downloadedTooltip": "Descargado anteriormente, pero actualmente no está en tu biblioteca.",
             "alreadyInLibrary": "Ya en la biblioteca",
             "autoOrganizedPath": "[Auto-organizado por plantilla de ruta]",
+            "fileSelection": {
+                "title": "Seleccionar formato de archivo",
+                "files": "archivos",
+                "select": "Seleccionar archivo"
+            },
             "errors": {
                 "invalidUrl": "Formato de URL de Civitai inválido",
                 "noVersions": "No hay versiones disponibles para este modelo"
@@ -1058,6 +1125,12 @@
             "countMessage": "modelos serán eliminados permanentemente.",
             "action": "Eliminar todo"
         },
+        "bulkDeleteRecipes": {
+            "title": "Eliminar múltiples recetas",
+            "message": "¿Estás seguro de que quieres eliminar todas las recetas seleccionadas y sus archivos asociados?",
+            "countMessage": "recetas serán eliminadas permanentemente.",
+            "action": "Eliminar todo"
+        },
         "checkUpdates": {
             "title": "¿Comprobar actualizaciones para todos los {typePlural}?",
             "message": "Esto comprobará las actualizaciones de todos los {typePlural} de tu biblioteca. En colecciones grandes puede tardar un poco más.",
@@ -1138,6 +1211,7 @@
                 "editModelName": "Editar nombre del modelo",
                 "editFileName": "Editar nombre de archivo",
                 "editBaseModel": "Editar modelo base",
+                "editVersionName": "Editar nombre de versión",
                 "viewOnCivitai": "Ver en Civitai",
                 "viewOnCivitaiText": "Ver en Civitai",
                 "viewCreatorProfile": "Ver perfil del creador",
@@ -1169,7 +1243,9 @@
             },
             "notes": {
                 "saved": "Notas guardadas exitosamente",
-                "saveFailed": "Error al guardar notas"
+                "saveFailed": "Error al guardar notas",
+                "showMore": "Mostrar más",
+                "showLess": "Mostrar menos"
             },
             "usageTips": {
                 "addPresetParameter": "Añadir parámetro preestablecido...",
@@ -1274,12 +1350,15 @@
                     "earlyAccess": "Acceso temprano",
                     "earlyAccessTooltip": "Esta versión requiere actualmente acceso temprano de Civitai",
                     "ignored": "Ignorada",
-                    "ignoredTooltip": "Las notificaciones de actualización están desactivadas para esta versión"
+                    "ignoredTooltip": "Las notificaciones de actualización están desactivadas para esta versión",
+                    "onSiteOnly": "Solo en Sitio",
+                    "onSiteOnlyTooltip": "Esta versión solo está disponible para generación en el sitio de Civitai"
                 },
                 "actions": {
                     "download": "Descargar",
                     "downloadTooltip": "Descargar esta versión",
                     "downloadEarlyAccessTooltip": "Descargar esta versión de acceso temprano desde Civitai",
+                    "downloadNotAllowedTooltip": "Esta versión solo está disponible para generación en el sitio de Civitai",
                     "delete": "Eliminar",
                     "deleteTooltip": "Eliminar esta versión local",
                     "ignore": "Ignorar",
@@ -1428,11 +1507,14 @@
             "noMatchingNodes": "No hay nodos compatibles disponibles en el flujo de trabajo actual",
             "noTargetNodeSelected": "No se ha seleccionado ningún nodo de destino",
             "modelUpdated": "Modelo actualizado en el flujo de trabajo",
-            "modelFailed": "Error al actualizar nodo de modelo"
+            "modelFailed": "Error al actualizar nodo de modelo",
+            "embeddingAdded": "Embedding añadido al flujo de trabajo",
+            "embeddingFailed": "Error al añadir el embedding"
         },
         "nodeSelector": {
             "recipe": "Receta",
             "lora": "LoRA",
+            "embedding": "Embedding",
             "replace": "Reemplazar",
             "append": "Añadir",
             "selectTargetNode": "Seleccionar nodo de destino",
@@ -1442,6 +1524,10 @@
             "opened": "Carpeta de imágenes de ejemplo abierta",
             "openingFolder": "Abriendo carpeta de imágenes de ejemplo",
             "failedToOpen": "Error al abrir carpeta de imágenes de ejemplo",
+            "copiedPath": "Ruta copiada al portapapeles: {{path}}",
+            "clipboardFallback": "Ruta: {{path}}",
+            "copiedUri": "Enlace copiado al portapapeles: {{uri}}",
+            "uriClipboardFallback": "Enlace: {{uri}}",
             "setupRequired": "Almacenamiento de imágenes de ejemplo",
             "setupDescription": "Para agregar imágenes de ejemplo personalizadas, primero necesita establecer una ubicación de descarga.",
             "setupUsage": "Esta ruta se utiliza tanto para imágenes de ejemplo descargadas como personalizadas.",
@@ -1605,6 +1691,10 @@
             "noRecipeId": "No hay ID de receta disponible",
             "sendToWorkflowFailed": "Error al enviar la receta al flujo de trabajo: {message}",
             "copyFailed": "Error copiando sintaxis de receta: {message}",
+            "createError": "Error al crear la receta：{message}",
+            "createFailed": "Error al crear la receta：{error}",
+            "createMissingData": "Faltan datos necesarios para crear la receta",
+            "created": "Receta creada exitosamente",
             "noMissingLoras": "No hay LoRAs faltantes para descargar",
             "missingLorasInfoFailed": "Error al obtener información de LoRAs faltantes",
             "preparingForDownloadFailed": "Error preparando LoRAs para descarga",
@@ -1643,6 +1733,13 @@
             "batchImportBrowseFailed": "Failed to browse directory: {message}",
             "batchImportDirectorySelected": "Directory selected: {path}",
             "noRecipesSelected": "No se han seleccionado recetas",
+            "repairBulkComplete": "Reparación completa: {repaired} reparadas, {skipped} omitidas (de {total})",
+            "repairBulkSkipped": "No se necesita reparación para ninguna de las {total} recetas seleccionadas",
+            "repairBulkFailed": "Error al reparar las recetas seleccionadas: {message}",
+            "reimporting": "Reimportando receta desde origen...",
+            "reimportSuccess": "Receta reimportada exitosamente",
+            "reimportBulkComplete": "Reimportación completa: {completed} reimportadas, {failed} fallidas (de {total})",
+            "reimportBulkFailed": "Error al reimportar algunas recetas",
             "noMissingLorasInSelection": "No se encontraron LoRAs faltantes en las recetas seleccionadas",
             "noLoraRootConfigured": "No se ha configurado el directorio raíz de LoRA. Por favor, establezca un directorio raíz de LoRA predeterminado en la configuración."
         },
@@ -1673,6 +1770,11 @@
             "bulkContentRatingSet": "Clasificación de contenido establecida en {level} para {count} modelo(s)",
             "bulkContentRatingPartial": "Clasificación de contenido establecida en {level} para {success} modelo(s), {failed} fallaron",
             "bulkContentRatingFailed": "No se pudo actualizar la clasificación de contenido para los modelos seleccionados",
+            "bulkFavoriteUpdating": "Añadiendo {count} modelo(s) a favoritos...",
+            "bulkUnfavoriteUpdating": "Eliminando {count} modelo(s) de favoritos...",
+            "bulkFavoritePartialAdded": "{success} modelo(s) añadido(s) a favoritos, {failed} fallido(s)",
+            "bulkFavoritePartialRemoved": "{success} modelo(s) eliminado(s) de favoritos, {failed} fallido(s)",
+            "bulkFavoriteFailed": "Error al actualizar el estado de favorito",
             "bulkUpdatesChecking": "Comprobando actualizaciones para {type} seleccionados...",
             "bulkUpdatesSuccess": "Actualizaciones disponibles para {count} {type} seleccionados",
             "bulkUpdatesNone": "No se encontraron actualizaciones para los {type} seleccionados",
@@ -1875,18 +1977,52 @@
             "warning": "Requiere atención",
             "error": "Se requiere acción"
         },
+        "issues": {
+            "civitai_api_key": {
+                "title": "Civitai API Key"
+            },
+            "cache_health": {
+                "title": "Model Cache Health"
+            },
+            "filename_conflicts": {
+                "title": "Duplicate Filename Conflicts"
+            },
+            "ui_version": {
+                "title": "UI Version"
+            }
+        },
         "actions": {
             "runAgain": "Ejecutar de nuevo",
-            "exportBundle": "Exportar paquete"
+            "exportBundle": "Exportar paquete",
+            "open-settings": "Open Settings",
+            "open-settings-syntax-format": "Switch to Full Path Syntax",
+            "repair-cache": "Rebuild Cache",
+            "resolve-filename-conflicts": "Resolve Conflicts",
+            "reload-page": "Reload UI"
+        },
+        "labels": {
+            "conflicts": "Conflicts",
+            "version": "Version"
         },
         "toast": {
             "loadFailed": "Error al cargar los diagnósticos: {message}",
             "repairSuccess": "Reconstrucción de caché completada.",
             "repairFailed": "Error al reconstruir la caché: {message}",
             "exportSuccess": "Paquete de diagnósticos exportado.",
-            "exportFailed": "Error al exportar el paquete de diagnósticos: {message}"
+            "exportFailed": "Error al exportar el paquete de diagnósticos: {message}",
+            "conflictsResolved": "{count} conflicto(s) de nombre de archivo resuelto(s).",
+            "conflictsResolveFailed": "Error al resolver conflictos de nombre de archivo: {message}"
         }
     },
+    "conflictConfirm": {
+        "title": "Resolver conflictos de nombres de archivo",
+        "message": "Renombrar añadiendo un hash de 4 caracteres a cada nombre de archivo duplicado.",
+        "note": "Esta operación renombra archivos en el disco. Es posible que las referencias a modelos en flujos de trabajo existentes deban actualizarse si usas el formato de sintaxis A1111.",
+        "detail": "Ejemplo: <code>filename_v1.2</code> → <code>filename_v1.2-ab3c</code>",
+        "impact": "Renombrará <strong>{count}</strong> archivo(s) en <strong>{groups}</strong> grupo(s) de duplicados",
+        "confirm": "Renombrar archivos",
+        "cancel": "Cancelar"
+    },
     "banners": {
         "versionMismatch": {
             "title": "Actualización de la aplicación detectada",

locales/fr.json

@@ -15,7 +15,10 @@
             "settings": "Paramètres",
             "help": "Aide",
             "add": "Ajouter",
-            "close": "Fermer"
+            "close": "Fermer",
+            "menu": "Menu",
+            "remove": "Supprimer",
+            "change": "Modifier"
         },
         "status": {
             "loading": "Chargement...",
@@ -110,6 +113,7 @@
             "replacePreview": "Remplacer l'aperçu",
             "copyCheckpointName": "Copier le nom du checkpoint",
             "copyEmbeddingName": "Copier le nom de l'embedding",
+            "embeddingNameCopied": "Syntaxe dembedding copiée",
             "sendCheckpointToWorkflow": "Envoyer vers ComfyUI",
             "sendEmbeddingToWorkflow": "Envoyer vers ComfyUI"
         },
@@ -231,7 +235,10 @@
             "license": "Licence",
             "noCreditRequired": "Crédit non requis",
             "allowSellingGeneratedContent": "Vente autorisée",
+            "allowSellingGeneratedContentTooltip": "Autoriser la vente d\"images générées",
+            "noCreditRequiredTooltip": "Utiliser le modèle sans créditer le créateur",
             "noTags": "Aucun tag",
+            "autoTags": "Auto-Tags",
             "noBaseModelMatches": "Aucun modèle de base ne correspond à la recherche actuelle.",
             "clearAll": "Effacer tous les filtres",
             "any": "N'importe quel",
@@ -265,10 +272,10 @@
         },
         "downloadBackend": {
             "label": "Moteur de téléchargement",
-            "help": "Choisissez comment les fichiers de modèles sont téléchargés. Python utilise le téléchargeur intégré. aria2 utilise le processus externe expérimental de téléchargement.",
+            "help": "Choisissez comment les fichiers de modèles sont téléchargés. Python utilise le téléchargeur intégré. aria2 utilise le processus externe recommandé de téléchargement.",
             "options": {
                 "python": "Python (intégré)",
-                "aria2": "aria2 (expérimental)"
+                "aria2": "aria2 (recommandé)"
             }
         },
         "aria2cPath": {
@@ -276,6 +283,7 @@
             "help": "Chemin facultatif vers l’exécutable aria2c. Laissez vide pour utiliser aria2c depuis le PATH système.",
             "placeholder": "Laisser vide pour utiliser aria2c depuis le PATH"
         },
+        "aria2HelpLink": "Apprenez à configurer le backend de téléchargement aria2",
         "civitaiHostBanner": {
             "title": "Préférence d’hôte Civitai disponible",
             "content": "Civitai utilise désormais civitai.com pour le contenu SFW et civitai.red pour le contenu sans restriction. Vous pouvez modifier dans les paramètres le site ouvert par défaut.",
@@ -427,6 +435,8 @@
                 "hover": "Révéler au survol"
             },
             "cardInfoDisplayHelp": "Choisissez quand afficher les informations du modèle et les boutons d'action",
+            "showVersionOnCard": "Afficher la version sur la carte",
+            "showVersionOnCardHelp": "Afficher ou masquer le nom de version sur les cartes de modèle",
             "modelCardFooterAction": "Action du bouton de carte de modèle",
             "modelCardFooterActionOptions": {
                 "exampleImages": "Ouvrir les images d'exemple",
@@ -438,7 +448,9 @@
                 "modelName": "Nom du modèle",
                 "fileName": "Nom du fichier"
             },
-            "modelNameDisplayHelp": "Choisissez ce qui doit être affiché dans le pied de page de la carte du modèle"
+            "modelNameDisplayHelp": "Choisissez ce qui doit être affiché dans le pied de page de la carte du modèle",
+            "cardBlurAmount": "Flou de superposition des cartes",
+            "cardBlurAmountHelp": "Ajustez l'intensité du flou des superpositions d'en-tête et de pied de page sur les cartes de modèles et de recettes (0 = aucun flou, 20 = flou maximal)."
         },
         "folderSettings": {
             "activeLibrary": "Bibliothèque active",
@@ -538,6 +550,21 @@
             "downloadLocationHelp": "Entrez le chemin du dossier où les images d'exemple de Civitai seront sauvegardées",
             "autoDownload": "Téléchargement automatique des images d'exemple",
             "autoDownloadHelp": "Télécharger automatiquement les images d'exemple pour les modèles qui n'en ont pas (nécessite que l'emplacement de téléchargement soit défini)",
+            "openMode": "Action d’ouverture des images d’exemple",
+            "openModeHelp": "Choisissez si l’action s’ouvre sur le serveur, copie un chemin local mappé ou lance une URI personnalisée.",
+            "openModeOptions": {
+                "system": "Ouvrir sur le serveur",
+                "clipboard": "Copier le chemin local",
+                "uriTemplate": "Ouvrir une URI personnalisée"
+            },
+            "localRoot": "Racine locale des images d’exemple",
+            "localRootHelp": "Racine locale ou montée facultative qui reflète le répertoire des images d’exemple du serveur. Si vide, le chemin du serveur est réutilisé.",
+            "localRootPlaceholder": "Exemple : /Volumes/ComfyUI/example_images",
+            "uriTemplate": "Ouvrir le modèle d’URI",
+            "uriTemplateHelp": "Utilisez un lien profond personnalisé, tel qu’une URI de fichier ou un lien Shortcuts.",
+            "uriTemplatePlaceholder": "Exemple : shortcuts://run-shortcut?name=Open%20Finder&input=text&text={{encoded_local_path}}",
+            "uriTemplatePlaceholders": "Paramètres disponibles : {{local_path}}, {{encoded_local_path}}, {{relative_path}}, {{encoded_relative_path}}, {{file_uri}}, {{encoded_file_uri}}",
+            "openModeWikiLink": "En savoir plus sur les modes d'ouverture à distance",
             "optimizeImages": "Optimiser les images téléchargées",
             "optimizeImagesHelp": "Optimiser les images d'exemple pour réduire la taille du fichier et améliorer la vitesse de chargement (les métadonnées seront préservées)",
             "download": "Télécharger",
@@ -557,7 +584,13 @@
         },
         "misc": {
             "includeTriggerWords": "Inclure les mots-clés dans la syntaxe LoRA",
-            "includeTriggerWordsHelp": "Inclure les mots-clés d'entraînement lors de la copie de la syntaxe LoRA dans le presse-papiers"
+            "includeTriggerWordsHelp": "Inclure les mots-clés d'entraînement lors de la copie de la syntaxe LoRA dans le presse-papiers",
+            "loraSyntaxFormat": "Format de syntaxe LoRA",
+            "loraSyntaxFormatHelp": "Format de syntaxe LoRA. Le format complet inclut le chemin du sous-dossier (<lora:style/anime/x:1.0>) pour une résolution de modèle sans perte. Le format hérité utilise uniquement le nom du fichier (<lora:x:1.0>) — convention A1111, peut être ambiguë en cas de noms de fichiers en double dans différents dossiers.",
+            "loraSyntaxFormatOptions": {
+                "full": "Chemin complet (sous-dossier/nom)",
+                "legacy": "A1111 hérité (nom uniquement)"
+            }
         },
         "metadataArchive": {
             "enableArchiveDb": "Activer la base de données d'archive des métadonnées",
@@ -621,8 +654,6 @@
             },
             "refresh": {
                 "title": "Actualiser la liste des modèles",
-                "quick": "Synchroniser les changements",
-                "quickTooltip": "Analyse les nouveaux fichiers de modèle ou les fichiers manquants pour garder la liste à jour.",
                 "full": "Reconstruire le cache",
                 "fullTooltip": "Recharge tous les détails des modèles depuis les fichiers metadata — à utiliser si la bibliothèque paraît obsolète ou après des modifications manuelles."
             },
@@ -663,16 +694,30 @@
             "setContentRating": "Définir la classification du contenu pour tous",
             "copyAll": "Copier toute la syntaxe",
             "refreshAll": "Actualiser toutes les métadonnées",
+            "repairMetadata": "Réparer les métadonnées de la sélection",
+            "reimportMetadata": "Ré-importer depuis la source",
             "checkUpdates": "Vérifier les mises à jour pour la sélection",
             "moveAll": "Déplacer tout vers un dossier",
             "autoOrganize": "Auto-organiser la sélection",
             "skipMetadataRefresh": "Ignorer l'actualisation des métadonnées pour la sélection",
             "resumeMetadataRefresh": "Reprendre l'actualisation des métadonnées pour la sélection",
-            "deleteAll": "Supprimer tous les modèles",
+            "setFavorite": "Définir comme favori",
+            "setFavoriteCount": "Définir comme favori ({favorited}/{total})",
+            "unfavorite": "Retirer des favoris",
+            "deleteAll": "Supprimer la sélection",
             "downloadMissingLoras": "Télécharger les LoRAs manquants",
+            "downloadExamples": "Télécharger les images d'exemple",
             "clear": "Effacer la sélection",
             "skipMetadataRefreshCount": "Ignorer（{count} modèles）",
             "resumeMetadataRefreshCount": "Reprendre（{count} modèles）",
+            "sendToWorkflow": "Envoyer au workflow",
+            "sections": {
+                "workflow": "Workflow",
+                "metadata": "Métadonnées",
+                "attributes": "Attributs",
+                "organize": "Organiser",
+                "download": "Télécharger"
+            },
             "autoOrganizeProgress": {
                 "initializing": "Initialisation de l'auto-organisation...",
                 "starting": "Démarrage de l'auto-organisation pour {type}...",
@@ -698,6 +743,7 @@
             "setContentRating": "Définir la classification du contenu",
             "moveToFolder": "Déplacer vers un dossier",
             "repairMetadata": "Réparer les métadonnées",
+            "reimportMetadata": "Ré-importer depuis la source",
             "excludeModel": "Exclure le modèle",
             "restoreModel": "Restaurer le modèle",
             "deleteModel": "Supprimer le modèle",
@@ -785,8 +831,6 @@
             },
             "refresh": {
                 "title": "Actualiser la liste des recipes",
-                "quick": "Synchroniser les changements",
-                "quickTooltip": "Synchroniser les changements - actualisation rapide sans reconstruire le cache",
                 "full": "Reconstruire le cache",
                 "fullTooltip": "Reconstruire le cache - rescan complet de tous les fichiers de recipes"
             },
@@ -827,6 +871,13 @@
                 "skipped": "Recette déjà à la version la plus récente, aucune réparation nécessaire",
                 "failed": "Échec de la réparation de la recette : {message}",
                 "missingId": "Impossible de réparer la recette : ID de recette manquant"
+            },
+            "reimport": {
+                "starting": "Ré-import de la recette depuis la source...",
+                "success": "Recette ré-importée avec succès",
+                "noSourceUrl": "La recette n'a pas d'URL source, ré-import impossible",
+                "failed": "Échec du ré-import de la recette : {message}",
+                "missingId": "Impossible de ré-importer la recette : ID de recette manquant"
             }
         },
         "batchImport": {
@@ -904,9 +955,13 @@
     },
     "sidebar": {
         "modelRoot": "Racine",
+        "moreOptions": "Plus d'options",
         "collapseAll": "Réduire tous les dossiers",
         "pinSidebar": "Épingler la barre latérale",
         "unpinSidebar": "Désépingler la barre latérale",
+        "hideOnThisPage": "Masquer la barre latérale sur cette page",
+        "showSidebar": "Afficher la barre latérale",
+        "sidebarHiddenNotification": "Barre latérale masquée sur la page {page}",
         "switchToListView": "Passer en vue liste",
         "switchToTreeView": "Passer en vue arborescence",
         "recursiveOn": "Inclure les sous-dossiers",
@@ -926,6 +981,13 @@
         "empty": {
             "noFolders": "Aucun dossier trouvé",
             "dragHint": "Faites glisser des éléments ici pour créer des dossiers"
+        },
+        "folderUpdateCheck": {
+            "label": "Vérifier les mises à jour dans ce dossier",
+            "loading": "Vérification des mises à jour {type} dans ce dossier...",
+            "success": "{count} mise(s) à jour trouvée(s) pour les {type}s dans ce dossier",
+            "none": "Tous les {type}s dans ce dossier sont à jour",
+            "error": "Échec de la vérification des mises à jour {type} dans ce dossier : {message}"
         }
     },
     "statistics": {
@@ -970,9 +1032,9 @@
         "download": {
             "title": "Télécharger un modèle depuis une URL",
             "titleWithType": "Télécharger {type} depuis une URL",
-            "url": "URL Civitai",
             "civitaiUrl": "URL Civitai :",
             "placeholder": "https://civitai.com/models/...",
+            "urlHint": "Entrez une URL CivitAI ou CivArchive par ligne. Prend en charge plusieurs URLs pour le téléchargement par lot.",
             "locationPreview": "Aperçu de l'emplacement de téléchargement",
             "useDefaultPath": "Utiliser le chemin par défaut",
             "useDefaultPathTooltip": "Lorsque activé, les fichiers sont automatiquement organisés selon les modèles de chemin configurés",
@@ -994,6 +1056,11 @@
             "downloadedTooltip": "Déjà téléchargé, mais il n'est actuellement pas dans votre bibliothèque.",
             "alreadyInLibrary": "Déjà dans la bibliothèque",
             "autoOrganizedPath": "[Auto-organisé par modèle de chemin]",
+            "fileSelection": {
+                "title": "Choisir le format de fichier",
+                "files": "fichiers",
+                "select": "Choisir le fichier"
+            },
             "errors": {
                 "invalidUrl": "Format d'URL Civitai invalide",
                 "noVersions": "Aucune version disponible pour ce modèle"
@@ -1058,6 +1125,12 @@
             "countMessage": "modèles seront définitivement supprimés.",
             "action": "Tout supprimer"
         },
+        "bulkDeleteRecipes": {
+            "title": "Supprimer plusieurs recipes",
+            "message": "Êtes-vous sûr de vouloir supprimer toutes les recipes sélectionnées et leurs fichiers associés ?",
+            "countMessage": "recipes seront définitivement supprimées.",
+            "action": "Tout supprimer"
+        },
         "checkUpdates": {
             "title": "Vérifier les mises à jour pour tous les {typePlural} ?",
             "message": "Cette action vérifie les mises à jour pour tous les {typePlural} de votre bibliothèque. Les grandes collections peuvent prendre un peu plus de temps.",
@@ -1138,6 +1211,7 @@
                 "editModelName": "Modifier le nom du modèle",
                 "editFileName": "Modifier le nom de fichier",
                 "editBaseModel": "Modifier le modèle de base",
+                "editVersionName": "Modifier le nom de la version",
                 "viewOnCivitai": "Voir sur Civitai",
                 "viewOnCivitaiText": "Voir sur Civitai",
                 "viewCreatorProfile": "Voir le profil du créateur",
@@ -1169,7 +1243,9 @@
             },
             "notes": {
                 "saved": "Notes sauvegardées avec succès",
-                "saveFailed": "Échec de la sauvegarde des notes"
+                "saveFailed": "Échec de la sauvegarde des notes",
+                "showMore": "Afficher plus",
+                "showLess": "Afficher moins"
             },
             "usageTips": {
                 "addPresetParameter": "Ajouter un paramètre prédéfini...",
@@ -1274,12 +1350,15 @@
                     "earlyAccess": "Accès anticipé",
                     "earlyAccessTooltip": "Cette version nécessite actuellement l'accès anticipé Civitai",
                     "ignored": "Ignorée",
-                    "ignoredTooltip": "Les notifications de mise à jour sont désactivées pour cette version"
+                    "ignoredTooltip": "Les notifications de mise à jour sont désactivées pour cette version",
+                    "onSiteOnly": "Uniquement sur Site",
+                    "onSiteOnlyTooltip": "Cette version n'est disponible que pour la génération sur le site Civitai"
                 },
                 "actions": {
                     "download": "Télécharger",
                     "downloadTooltip": "Télécharger cette version",
                     "downloadEarlyAccessTooltip": "Télécharger cette version en accès anticipé depuis Civitai",
+                    "downloadNotAllowedTooltip": "Cette version n'est disponible que pour la génération sur le site Civitai",
                     "delete": "Supprimer",
                     "deleteTooltip": "Supprimer cette version locale",
                     "ignore": "Ignorer",
@@ -1428,11 +1507,14 @@
             "noMatchingNodes": "Aucun nœud compatible disponible dans le workflow actuel",
             "noTargetNodeSelected": "Aucun nœud cible sélectionné",
             "modelUpdated": "Modèle mis à jour dans le workflow",
-            "modelFailed": "Échec de la mise à jour du nœud modèle"
+            "modelFailed": "Échec de la mise à jour du nœud modèle",
+            "embeddingAdded": "Embedding ajouté au workflow",
+            "embeddingFailed": "Échec de l'ajout de l'embedding"
         },
         "nodeSelector": {
             "recipe": "Recipe",
             "lora": "LoRA",
+            "embedding": "Embedding",
             "replace": "Remplacer",
             "append": "Ajouter",
             "selectTargetNode": "Sélectionner le nœud cible",
@@ -1442,6 +1524,10 @@
             "opened": "Dossier d'images d'exemple ouvert",
             "openingFolder": "Ouverture du dossier d'images d'exemple",
             "failedToOpen": "Échec de l'ouverture du dossier d'images d'exemple",
+            "copiedPath": "Chemin copié dans le presse-papiers : {{path}}",
+            "clipboardFallback": "Chemin : {{path}}",
+            "copiedUri": "Lien copié dans le presse-papiers : {{uri}}",
+            "uriClipboardFallback": "Lien : {{uri}}",
             "setupRequired": "Stockage d'images d'exemple",
             "setupDescription": "Pour ajouter des images d'exemple personnalisées, vous devez d'abord définir un emplacement de téléchargement.",
             "setupUsage": "Ce chemin est utilisé pour les images d'exemple téléchargées et personnalisées.",
@@ -1605,6 +1691,10 @@
             "noRecipeId": "Aucun ID de recipe disponible",
             "sendToWorkflowFailed": "Échec de l'envoi de la recette vers le workflow : {message}",
             "copyFailed": "Erreur lors de la copie de la syntaxe de la recipe : {message}",
+            "createError": "Erreur lors de la création du Recipe ：{message}",
+            "createFailed": "Échec de la création du Recipe ：{error}",
+            "createMissingData": "Données requises manquantes pour créer le Recipe",
+            "created": "Recipe créé avec succès",
             "noMissingLoras": "Aucun LoRA manquant à télécharger",
             "missingLorasInfoFailed": "Échec de l'obtention des informations pour les LoRAs manquants",
             "preparingForDownloadFailed": "Erreur lors de la préparation des LoRAs pour le téléchargement",
@@ -1643,6 +1733,13 @@
             "batchImportBrowseFailed": "Failed to browse directory: {message}",
             "batchImportDirectorySelected": "Directory selected: {path}",
             "noRecipesSelected": "Aucune recette sélectionnée",
+            "repairBulkComplete": "Réparation terminée : {repaired} réparée(s), {skipped} ignorée(s) (sur {total})",
+            "repairBulkSkipped": "Aucune réparation nécessaire parmi les {total} recettes sélectionnées",
+            "repairBulkFailed": "Échec de la réparation des recettes sélectionnées : {message}",
+            "reimporting": "Ré-import de la recette depuis la source...",
+            "reimportSuccess": "Recette ré-importée avec succès",
+            "reimportBulkComplete": "Ré-import terminé : {completed} ré-importé(s), {failed} échec(s) (sur {total})",
+            "reimportBulkFailed": "Échec du ré-import de certaines recettes",
             "noMissingLorasInSelection": "Aucun LoRA manquant trouvé dans les recettes sélectionnées",
             "noLoraRootConfigured": "Aucun répertoire racine LoRA configuré. Veuillez définir un répertoire racine LoRA par défaut dans les paramètres."
         },
@@ -1673,6 +1770,11 @@
             "bulkContentRatingSet": "Classification du contenu définie sur {level} pour {count} modèle(s)",
             "bulkContentRatingPartial": "Classification du contenu définie sur {level} pour {success} modèle(s), {failed} échec(s)",
             "bulkContentRatingFailed": "Impossible de mettre à jour la classification du contenu pour les modèles sélectionnés",
+            "bulkFavoriteUpdating": "Ajout de {count} modèle(s) aux favoris...",
+            "bulkUnfavoriteUpdating": "Suppression de {count} modèle(s) des favoris...",
+            "bulkFavoritePartialAdded": "{success} modèle(s) ajouté(s) aux favoris, {failed} échec(s)",
+            "bulkFavoritePartialRemoved": "{success} modèle(s) retiré(s) des favoris, {failed} échec(s)",
+            "bulkFavoriteFailed": "Échec de la mise à jour du statut de favori",
             "bulkUpdatesChecking": "Vérification des mises à jour pour les {type} sélectionnés...",
             "bulkUpdatesSuccess": "Mises à jour disponibles pour {count} {type} sélectionnés",
             "bulkUpdatesNone": "Aucune mise à jour trouvée pour les {type} sélectionnés",
@@ -1875,18 +1977,52 @@
             "warning": "Nécessite une attention",
             "error": "Action requise"
         },
+        "issues": {
+            "civitai_api_key": {
+                "title": "Civitai API Key"
+            },
+            "cache_health": {
+                "title": "Model Cache Health"
+            },
+            "filename_conflicts": {
+                "title": "Duplicate Filename Conflicts"
+            },
+            "ui_version": {
+                "title": "UI Version"
+            }
+        },
         "actions": {
             "runAgain": "Relancer",
-            "exportBundle": "Exporter le lot"
+            "exportBundle": "Exporter le lot",
+            "open-settings": "Open Settings",
+            "open-settings-syntax-format": "Switch to Full Path Syntax",
+            "repair-cache": "Rebuild Cache",
+            "resolve-filename-conflicts": "Resolve Conflicts",
+            "reload-page": "Reload UI"
+        },
+        "labels": {
+            "conflicts": "Conflicts",
+            "version": "Version"
         },
         "toast": {
             "loadFailed": "Échec du chargement des diagnostics : {message}",
             "repairSuccess": "Reconstruction du cache terminée.",
             "repairFailed": "Échec de la reconstruction du cache : {message}",
             "exportSuccess": "Lot de diagnostics exporté.",
-            "exportFailed": "Échec de l'export du lot de diagnostics : {message}"
+            "exportFailed": "Échec de l'export du lot de diagnostics : {message}",
+            "conflictsResolved": "{count} conflit(s) de nom de fichier résolu(s).",
+            "conflictsResolveFailed": "Échec de la résolution des conflits de nom de fichier : {message}"
         }
     },
+    "conflictConfirm": {
+        "title": "Résoudre les conflits de noms de fichiers",
+        "message": "Renommer en ajoutant un hachage de 4 caractères à chaque nom de fichier en double.",
+        "note": "Cette opération renomme les fichiers sur le disque. Les références de modèle dans les workflows existants peuvent nécessiter une mise à jour si vous utilisez le format de syntaxe A1111.",
+        "detail": "Exemple : <code>filename_v1.2</code> → <code>filename_v1.2-ab3c</code>",
+        "impact": "Renommera <strong>{count}</strong> fichier(s) dans <strong>{groups}</strong> groupe(s) de doublons",
+        "confirm": "Renommer les fichiers",
+        "cancel": "Annuler"
+    },
     "banners": {
         "versionMismatch": {
             "title": "Mise à jour de l'application détectée",

locales/he.json

@@ -15,7 +15,10 @@
             "settings": "הגדרות",
             "help": "עזרה",
             "add": "הוספה",
-            "close": "סגור"
+            "close": "סגור",
+            "menu": "תפריט",
+            "remove": "הסר",
+            "change": "שנה"
         },
         "status": {
             "loading": "טוען...",
@@ -110,6 +113,7 @@
             "replacePreview": "החלף תצוגה מקדימה",
             "copyCheckpointName": "העתק שם Checkpoint",
             "copyEmbeddingName": "העתק שם Embedding",
+            "embeddingNameCopied": "תחביר Embedding הועתק",
             "sendCheckpointToWorkflow": "שלח ל-ComfyUI",
             "sendEmbeddingToWorkflow": "שלח ל-ComfyUI"
         },
@@ -231,7 +235,10 @@
             "license": "רישיון",
             "noCreditRequired": "ללא קרדיט נדרש",
             "allowSellingGeneratedContent": "אפשר מכירה",
+            "allowSellingGeneratedContentTooltip": "אפשר מכירת תמונות שנוצרו",
+            "noCreditRequiredTooltip": "שימוש במודל ללא מתן קרדיט ליוצר",
             "noTags": "ללא תגיות",
+            "autoTags": "תגיות אוטומטיות",
             "noBaseModelMatches": "אין מודלי בסיס התואמים לחיפוש הנוכחי.",
             "clearAll": "נקה את כל המסננים",
             "any": "כלשהו",
@@ -265,10 +272,10 @@
         },
         "downloadBackend": {
             "label": "מנגנון הורדה",
-            "help": "בחר כיצד יורדים קבצי המודל. Python משתמש במוריד המובנה. aria2 משתמש בתהליך הורדה חיצוני ניסיוני.",
+            "help": "בחר כיצד יורדים קבצי המודל. Python משתמש במוריד המובנה. aria2 משתמש בתהליך הורדה חיצוני מומלץ.",
             "options": {
                 "python": "Python (מובנה)",
-                "aria2": "aria2 (ניסיוני)"
+                "aria2": "aria2 (מומלץ)"
             }
         },
         "aria2cPath": {
@@ -276,6 +283,7 @@
             "help": "נתיב אופציונלי לקובץ ההפעלה aria2c. השאר ריק כדי להשתמש ב-aria2c מתוך ה-PATH של המערכת.",
             "placeholder": "השאר ריק כדי להשתמש ב-aria2c מתוך ה-PATH"
         },
+        "aria2HelpLink": "למד כיצד להגדיר את מנוע ההורדה aria2",
         "civitaiHostBanner": {
             "title": "העדפת מארח Civitai זמינה",
             "content": "Civitai משתמש כעת ב-civitai.com עבור תוכן SFW וב-civitai.red עבור תוכן ללא הגבלות. ניתן לשנות בהגדרות איזה אתר ייפתח כברירת מחדל.",
@@ -427,6 +435,8 @@
                 "hover": "חשוף בריחוף"
             },
             "cardInfoDisplayHelp": "בחר מתי להציג מידע על המודל וכפתורי פעולה",
+            "showVersionOnCard": "הצג גרסה בכרטיס",
+            "showVersionOnCardHelp": "הצג או הסתר את שם הגרסה בכרטיסי המודל",
             "modelCardFooterAction": "פעולת כפתור כרטיס מודל",
             "modelCardFooterActionOptions": {
                 "exampleImages": "פתח תמונות דוגמה",
@@ -438,7 +448,9 @@
                 "modelName": "שם מודל",
                 "fileName": "שם קובץ"
             },
-            "modelNameDisplayHelp": "בחר מה להציג בכותרת התחתונה של כרטיס המודל"
+            "modelNameDisplayHelp": "בחר מה להציג בכותרת התחתונה של כרטיס המודל",
+            "cardBlurAmount": "עוצמת טשטוש שכבת-על בכרטיס",
+            "cardBlurAmountHelp": "כוונן את עוצמת הטשטוש של שכבת-העל בכותרת ובכותרות תחתונה בכרטיסי מודל ומתכונים (0 = ללא טשטוש, 20 = טשטוש מקסימלי)."
         },
         "folderSettings": {
             "activeLibrary": "ספרייה פעילה",
@@ -538,6 +550,21 @@
             "downloadLocationHelp": "הזן את נתיב התיקייה שבו יישמרו תמונות דוגמה מ-Civitai",
             "autoDownload": "הורדה אוטומטית של תמונות דוגמה",
             "autoDownloadHelp": "הורד אוטומטית תמונות דוגמה למודלים שאין להם (דורש הגדרת מיקום הורדה)",
+            "openMode": "פעולת פתיחת תמונות דוגמה",
+            "openModeHelp": "בחר אם הפעולה תיפתח בשרת, תעתיק נתיב מקומי ממופה או תפעיל URI מותאם אישית.",
+            "openModeOptions": {
+                "system": "פתח בשרת",
+                "clipboard": "העתק נתיב מקומי",
+                "uriTemplate": "פתח URI מותאם אישית"
+            },
+            "localRoot": "שורש מקומי לתמונות דוגמה",
+            "localRootHelp": "שורש מקומי או ממופה אופציונלי שמשקף את תיקיית תמונות הדוגמה בשרת. אם השדה ריק, ייעשה שימוש חוזר בנתיב השרת.",
+            "localRootPlaceholder": "דוגמה: /Volumes/ComfyUI/example_images",
+            "uriTemplate": "תבנית URI לפתיחה",
+            "uriTemplateHelp": "השתמש בקישור עומק מותאם אישית כמו URI של קובץ או קישור Shortcuts.",
+            "uriTemplatePlaceholder": "דוגמה: shortcuts://run-shortcut?name=Open%20Finder&input=text&text={{encoded_local_path}}",
+            "uriTemplatePlaceholders": "מצייני מקום זמינים: {{local_path}}, {{encoded_local_path}}, {{relative_path}}, {{encoded_relative_path}}, {{file_uri}}, {{encoded_file_uri}}",
+            "openModeWikiLink": "למידע נוסף על מצבי פתיחה מרחוק",
             "optimizeImages": "מטב תמונות שהורדו",
             "optimizeImagesHelp": "מטב תמונות דוגמה כדי להקטין את גודל הקובץ ולשפר את מהירות הטעינה (מטא-דאטה תישמר)",
             "download": "הורד",
@@ -557,7 +584,13 @@
         },
         "misc": {
             "includeTriggerWords": "כלול מילות טריגר בתחביר LoRA",
-            "includeTriggerWordsHelp": "כלול מילות טריגר מאומנות בעת העתקת תחביר LoRA ללוח"
+            "includeTriggerWordsHelp": "כלול מילות טריגר מאומנות בעת העתקת תחביר LoRA ללוח",
+            "loraSyntaxFormat": "פורמט תחביר LoRA",
+            "loraSyntaxFormatHelp": "פורמט תחביר LoRA. נתיב מלא כולל תת-תיקייה (<lora:style/anime/x:1.0>) לפתרון מודל ללא אובדן. גרסה ישנה משתמשת בשם קובץ בלבד (<lora:x:1.0>) — מוסכמת A1111, עלולה להיות לא חד משמעית עם שמות קבצים כפולים בתיקיות שונות.",
+            "loraSyntaxFormatOptions": {
+                "full": "נתיב מלא (תת-תיקייה/שם)",
+                "legacy": "A1111 ישן (שם בלבד)"
+            }
         },
         "metadataArchive": {
             "enableArchiveDb": "הפעל מסד נתונים של ארכיון מטא-דאטה",
@@ -621,8 +654,6 @@
             },
             "refresh": {
                 "title": "רענן רשימת מודלים",
-                "quick": "סנכרון שינויים",
-                "quickTooltip": "סריקה לאיתור קבצי מודל חדשים או חסרים כדי לשמור את הרשימה מעודכנת.",
                 "full": "בניית מטמון מחדש",
                 "fullTooltip": "טוען מחדש את כל פרטי המודלים מקבצי המטא-דאטה – לשימוש אם הספרייה נראית לא מעודכנת או לאחר עריכות ידניות."
             },
@@ -663,16 +694,30 @@
             "setContentRating": "הגדר דירוג תוכן לכל המודלים",
             "copyAll": "העתק את כל התחבירים",
             "refreshAll": "רענן את כל המטא-דאטה",
+            "repairMetadata": "תקן מטא-דאטה עבור הנבחרים",
+            "reimportMetadata": "ייבא מחדש ממקור",
             "checkUpdates": "בדוק עדכונים לבחירה",
             "moveAll": "העבר הכל לתיקייה",
             "autoOrganize": "ארגן אוטומטית נבחרים",
             "skipMetadataRefresh": "דילוג על רענון מטא-נתונים לנבחרים",
             "resumeMetadataRefresh": "המשך רענון מטא-נתונים לנבחרים",
-            "deleteAll": "מחק את כל המודלים",
+            "setFavorite": "הגדר כמועדף",
+            "setFavoriteCount": "הגדר כמועדף ({favorited}/{total})",
+            "unfavorite": "הסר ממועדפים",
+            "deleteAll": "מחק נבחרים",
             "downloadMissingLoras": "הורדת LoRAs חסרים",
+            "downloadExamples": "הורד תמונות דוגמה",
             "clear": "נקה בחירה",
             "skipMetadataRefreshCount": "דילוג（{count} מודלים）",
             "resumeMetadataRefreshCount": "המשך（{count} מודלים）",
+            "sendToWorkflow": "שלח ל-Workflow",
+            "sections": {
+                "workflow": "Workflow",
+                "metadata": "מטא-נתונים",
+                "attributes": "מאפיינים",
+                "organize": "ארגן",
+                "download": "הורדה"
+            },
             "autoOrganizeProgress": {
                 "initializing": "מאתחל ארגון אוטומטי...",
                 "starting": "מתחיל ארגון אוטומטי עבור {type}...",
@@ -698,6 +743,7 @@
             "setContentRating": "הגדר דירוג תוכן",
             "moveToFolder": "העבר לתיקייה",
             "repairMetadata": "תיקון מטא-דאטה",
+            "reimportMetadata": "ייבא מחדש ממקור",
             "excludeModel": "החרג מודל",
             "restoreModel": "שחזור מודל",
             "deleteModel": "מחק מודל",
@@ -785,8 +831,6 @@
             },
             "refresh": {
                 "title": "רענן רשימת מתכונים",
-                "quick": "סנכרן שינויים",
-                "quickTooltip": "סנכרן שינויים - רענון מהיר ללא בניית מטמון מחדש",
                 "full": "בנה מטמון מחדש",
                 "fullTooltip": "בנה מטמון מחדש - סריקה מחדש מלאה של כל קבצי המתכונים"
             },
@@ -827,6 +871,13 @@
                 "skipped": "המתכון כבר בגרסה העדכנית ביותר, אין צורך בתיקון",
                 "failed": "תיקון המתכון נכשל: {message}",
                 "missingId": "לא ניתן לתקן את המתכון: חסר מזהה מתכון"
+            },
+            "reimport": {
+                "starting": "מייבא מתכון מחדש מהמקור...",
+                "success": "המתכון יובא מחדש בהצלחה",
+                "noSourceUrl": "למתכון אין כתובת מקור, לא ניתן לייבא מחדש",
+                "failed": "ייבוא המתכון מחדש נכשל: {message}",
+                "missingId": "לא ניתן לייבא מחדש: חסר מזהה מתכון"
             }
         },
         "batchImport": {
@@ -904,9 +955,13 @@
     },
     "sidebar": {
         "modelRoot": "שורש",
+        "moreOptions": "אפשרויות נוספות",
         "collapseAll": "כווץ את כל התיקיות",
         "pinSidebar": "נעל סרגל צד",
         "unpinSidebar": "שחרר סרגל צד",
+        "hideOnThisPage": "הסתר סרגל צד בדף זה",
+        "showSidebar": "הצג סרגל צד",
+        "sidebarHiddenNotification": "סרגל הצד מוסתר בדף {page}",
         "switchToListView": "עבור לתצוגת רשימה",
         "switchToTreeView": "תצוגת עץ",
         "recursiveOn": "כלול תיקיות משנה",
@@ -926,6 +981,13 @@
         "empty": {
             "noFolders": "לא נמצאו תיקיות",
             "dragHint": "גרור פריטים לכאן כדי ליצור תיקיות"
+        },
+        "folderUpdateCheck": {
+            "label": "בדוק עדכונים בתיקייה זו",
+            "loading": "בודק עדכוני {type} בתיקייה זו...",
+            "success": "נמצאו {count} עדכון/ים עבור {type}s בתיקייה זו",
+            "none": "כל ה-{type}s בתיקייה זו מעודכנים",
+            "error": "נכשל בבדיקת עדכוני {type} בתיקייה: {message}"
         }
     },
     "statistics": {
@@ -970,9 +1032,9 @@
         "download": {
             "title": "הורד מודל מכתובת URL",
             "titleWithType": "הורד {type} מכתובת URL",
-            "url": "כתובת URL של Civitai",
             "civitaiUrl": "כתובת URL של Civitai:",
             "placeholder": "https://civitai.com/models/...",
+            "urlHint": "יש להזין כתובת URL אחת של CivitAI או CivArchive בכל שורה. תומך במספר כתובות URL להורדה בבת אחת.",
             "locationPreview": "תצוגה מקדימה של מיקום ההורדה",
             "useDefaultPath": "השתמש בנתיב ברירת מחדל",
             "useDefaultPathTooltip": "כאשר מופעל, קבצים מאורגנים אוטומטית באמצעות תבניות נתיב מוגדרות",
@@ -994,6 +1056,11 @@
             "downloadedTooltip": "הורד בעבר, אך הוא אינו נמצא כרגע בספרייה שלך.",
             "alreadyInLibrary": "כבר בספרייה",
             "autoOrganizedPath": "[מאורגן אוטומטית לפי תבנית נתיב]",
+            "fileSelection": {
+                "title": "בחר פורמט קובץ",
+                "files": "קבצים",
+                "select": "בחר קובץ"
+            },
             "errors": {
                 "invalidUrl": "פורמט URL של Civitai לא חוקי",
                 "noVersions": "אין גרסאות זמינות למודל זה"
@@ -1058,6 +1125,12 @@
             "countMessage": "מודלים יימחקו לצמיתות.",
             "action": "מחק הכל"
         },
+        "bulkDeleteRecipes": {
+            "title": "מחק מספר מתכונים",
+            "message": "האם אתה בטוח שברצונך למחוק את כל המתכונים שנבחרו ואת הקבצים הנלווים אליהם?",
+            "countMessage": "מתכונים יימחקו לצמיתות.",
+            "action": "מחק הכל"
+        },
         "checkUpdates": {
             "title": "לבדוק עדכונים לכל ה-{typePlural}?",
             "message": "הפעולה תבדוק עדכונים עבור כל ה-{typePlural} בספרייה שלך. באוספים גדולים זה עלול לקחת מעט יותר זמן.",
@@ -1138,6 +1211,7 @@
                 "editModelName": "ערוך שם מודל",
                 "editFileName": "ערוך שם קובץ",
                 "editBaseModel": "ערוך מודל בסיס",
+                "editVersionName": "ערוך שם גרסה",
                 "viewOnCivitai": "הצג ב-Civitai",
                 "viewOnCivitaiText": "הצג ב-Civitai",
                 "viewCreatorProfile": "הצג פרופיל יוצר",
@@ -1169,7 +1243,9 @@
             },
             "notes": {
                 "saved": "הערות נשמרו בהצלחה",
-                "saveFailed": "שמירת ההערות נכשלה"
+                "saveFailed": "שמירת ההערות נכשלה",
+                "showMore": "הצג עוד",
+                "showLess": "הצג פחות"
             },
             "usageTips": {
                 "addPresetParameter": "הוסף פרמטר קבוע מראש...",
@@ -1274,12 +1350,15 @@
                     "earlyAccess": "גישה מוקדמת",
                     "earlyAccessTooltip": "גרסה זו דורשת כרגע גישת Early Access של Civitai",
                     "ignored": "התעלם",
-                    "ignoredTooltip": "התראות העדכון מושבתות עבור גרסה זו"
+                    "ignoredTooltip": "התראות העדכון מושבתות עבור גרסה זו",
+                    "onSiteOnly": "רק באתר",
+                    "onSiteOnlyTooltip": "גרסה זו זמינה רק ליצירה באתר Civitai"
                 },
                 "actions": {
                     "download": "הורדה",
                     "downloadTooltip": "הורד את הגרסה הזו",
                     "downloadEarlyAccessTooltip": "הורד את גרסת ה-Early Access הזו מ-Civitai",
+                    "downloadNotAllowedTooltip": "גרסה זו זמינה רק ליצירה באתר Civitai",
                     "delete": "מחיקה",
                     "deleteTooltip": "מחק את הגרסה המקומית הזו",
                     "ignore": "התעלם",
@@ -1428,11 +1507,14 @@
             "noMatchingNodes": "אין צמתים תואמים זמינים ב-workflow הנוכחי",
             "noTargetNodeSelected": "לא נבחר צומת יעד",
             "modelUpdated": "מודל עודכן ב-workflow",
-            "modelFailed": "עדכון צומת המודל נכשל"
+            "modelFailed": "עדכון צומת המודל נכשל",
+            "embeddingAdded": "Embedding נוסף ל-workflow",
+            "embeddingFailed": "הוספת Embedding נכשלה"
         },
         "nodeSelector": {
             "recipe": "מתכון",
             "lora": "LoRA",
+            "embedding": "Embedding",
             "replace": "החלף",
             "append": "הוסף",
             "selectTargetNode": "בחר צומת יעד",
@@ -1442,6 +1524,10 @@
             "opened": "תיקיית תמונות הדוגמה נפתחה",
             "openingFolder": "פותח תיקיית תמונות דוגמה",
             "failedToOpen": "פתיחת תיקיית תמונות הדוגמה נכשלה",
+            "copiedPath": "הנתיב הועתק ללוח: {{path}}",
+            "clipboardFallback": "נתיב: {{path}}",
+            "copiedUri": "הקישור הועתק ללוח: {{uri}}",
+            "uriClipboardFallback": "קישור: {{uri}}",
             "setupRequired": "אחסון תמונות דוגמה",
             "setupDescription": "כדי להוסיף תמונות דוגמה מותאמות אישית, עליך קודם להגדיר מיקום הורדה.",
             "setupUsage": "נתיב זה משמש הן עבור תמונות דוגמה שהורדו והן עבור תמונות מותאמות אישית.",
@@ -1605,6 +1691,10 @@
             "noRecipeId": "אין מזהה מתכון זמין",
             "sendToWorkflowFailed": "נכשל שליחת המתכון ל-workflow: {message}",
             "copyFailed": "שגיאה בהעתקת תחביר המתכון: {message}",
+            "createError": "שגיאה ביצירת המתכון：{message}",
+            "createFailed": "יצירת המתכון נכשלה：{error}",
+            "createMissingData": "חסרים נתונים נדרשים ליצירת המתכון",
+            "created": "המתכון נוצר בהצלחה",
             "noMissingLoras": "אין LoRAs חסרים להורדה",
             "missingLorasInfoFailed": "קבלת מידע עבור LoRAs חסרים נכשלה",
             "preparingForDownloadFailed": "שגיאה בהכנת LoRAs להורדה",
@@ -1643,6 +1733,13 @@
             "batchImportBrowseFailed": "Failed to browse directory: {message}",
             "batchImportDirectorySelected": "Directory selected: {path}",
             "noRecipesSelected": "לא נבחרו מתכונים",
+            "repairBulkComplete": "התיקון הושלם: {repaired} תוקנו, {skipped} דולגו (מתוך {total})",
+            "repairBulkSkipped": "אין צורך בתיקון עבור {total} המתכונים הנבחרים",
+            "repairBulkFailed": "תיקון המתכונים הנבחרים נכשל: {message}",
+            "reimporting": "מייבא מתכון מחדש מהמקור...",
+            "reimportSuccess": "המתכון יובא מחדש בהצלחה",
+            "reimportBulkComplete": "ייבוא מחדש הושלם: {completed} יובאו, {failed} נכשלו (מתוך {total})",
+            "reimportBulkFailed": "ייבוא מחדש של חלק מהמתכונים נכשל",
             "noMissingLorasInSelection": "לא נמצאו LoRAs חסרים במתכונים שנבחרו",
             "noLoraRootConfigured": "תיקיית השורש של LoRA לא מוגדרת. אנא הגדר תיקיית שורש LoRA ברירת מחדל בהגדרות."
         },
@@ -1673,6 +1770,11 @@
             "bulkContentRatingSet": "דירוג התוכן הוגדר ל-{level} עבור {count} מודלים",
             "bulkContentRatingPartial": "דירוג התוכן הוגדר ל-{level} עבור {success} מודלים, {failed} נכשלו",
             "bulkContentRatingFailed": "עדכון דירוג התוכן עבור המודלים שנבחרו נכשל",
+            "bulkFavoriteUpdating": "מוסיף {count} דגמים למועדפים...",
+            "bulkUnfavoriteUpdating": "מסיר {count} דגמים ממועדפים...",
+            "bulkFavoritePartialAdded": "{success} דגמים נוספו למועדפים, {failed} נכשלו",
+            "bulkFavoritePartialRemoved": "{success} דגמים הוסרו ממועדפים, {failed} נכשלו",
+            "bulkFavoriteFailed": "עדכון סטטוס מועדפים נכשל",
             "bulkUpdatesChecking": "בודק עדכונים עבור {type} שנבחרו...",
             "bulkUpdatesSuccess": "יש עדכונים עבור {count} {type} שנבחרו",
             "bulkUpdatesNone": "לא נמצאו עדכונים עבור {type} שנבחרו",
@@ -1875,18 +1977,52 @@
             "warning": "דורש תשומת לב",
             "error": "נדרשת פעולה"
         },
+        "issues": {
+            "civitai_api_key": {
+                "title": "Civitai API Key"
+            },
+            "cache_health": {
+                "title": "Model Cache Health"
+            },
+            "filename_conflicts": {
+                "title": "Duplicate Filename Conflicts"
+            },
+            "ui_version": {
+                "title": "UI Version"
+            }
+        },
         "actions": {
             "runAgain": "הפעל שוב",
-            "exportBundle": "ייצוא חבילה"
+            "exportBundle": "ייצוא חבילה",
+            "open-settings": "Open Settings",
+            "open-settings-syntax-format": "Switch to Full Path Syntax",
+            "repair-cache": "Rebuild Cache",
+            "resolve-filename-conflicts": "Resolve Conflicts",
+            "reload-page": "Reload UI"
+        },
+        "labels": {
+            "conflicts": "Conflicts",
+            "version": "Version"
         },
         "toast": {
             "loadFailed": "טעינת האבחון נכשלה: {message}",
             "repairSuccess": "בניית המטמון מחדש הושלמה.",
             "repairFailed": "בניית המטמון מחדש נכשלה: {message}",
             "exportSuccess": "חבילת האבחון יוצאה.",
-            "exportFailed": "ייצוא חבילת האבחון נכשל: {message}"
+            "exportFailed": "ייצוא חבילת האבחון נכשל: {message}",
+            "conflictsResolved": "נפתרו {count} התנגשויות בשמות קבצים.",
+            "conflictsResolveFailed": "פתרון התנגשויות שמות קבצים נכשל: {message}"
         }
     },
+    "conflictConfirm": {
+        "title": "פתור התנגשויות בשמות קבצים",
+        "message": "שינוי שם על ידי הוספת האש באורך 4 תווים לכל שם קובץ כפול.",
+        "note": "פעולה זו משנה שמות של קבצים בדיסק. ייתכן שיהיה צורך לעדכן הפניות למודלים בזרימות עבודה קיימות אם אתה משתמש בפורמט התחביר A1111.",
+        "detail": "דוגמה: <code>filename_v1.2</code> → <code>filename_v1.2-ab3c</code>",
+        "impact": "ישנה שם של <strong>{count}</strong> קבצים ב-<strong>{groups}</strong> קבוצות כפולות",
+        "confirm": "שנה שמות קבצים",
+        "cancel": "ביטול"
+    },
     "banners": {
         "versionMismatch": {
             "title": "זוהה עדכון יישום",

locales/ja.json

@@ -15,7 +15,10 @@
             "settings": "設定",
             "help": "ヘルプ",
             "add": "追加",
-            "close": "閉じる"
+            "close": "閉じる",
+            "menu": "メニュー",
+            "remove": "削除",
+            "change": "変更"
         },
         "status": {
             "loading": "読み込み中...",
@@ -110,6 +113,7 @@
             "replacePreview": "プレビューを置換",
             "copyCheckpointName": "checkpoint名をコピー",
             "copyEmbeddingName": "embedding名をコピー",
+            "embeddingNameCopied": "Embedding構文をコピーしました",
             "sendCheckpointToWorkflow": "ComfyUIに送信",
             "sendEmbeddingToWorkflow": "ComfyUIに送信"
         },
@@ -231,7 +235,10 @@
             "license": "ライセンス",
             "noCreditRequired": "クレジット不要",
             "allowSellingGeneratedContent": "販売許可",
+            "allowSellingGeneratedContentTooltip": "生成した画像の販売を許可",
+            "noCreditRequiredTooltip": "クレジット表記なしでモデルを使用可能",
             "noTags": "タグなし",
+            "autoTags": "自動タグ",
             "noBaseModelMatches": "現在の検索に一致するベースモデルはありません。",
             "clearAll": "すべてのフィルタをクリア",
             "any": "いずれか",
@@ -265,10 +272,10 @@
         },
         "downloadBackend": {
             "label": "ダウンロードバックエンド",
-            "help": "モデルファイルのダウンロード方法を選択します。Python は内蔵ダウンローダーを使用し、aria2 は実験的な外部ダウンローダープロセスを使用します。",
+            "help": "モデルファイルのダウンロード方法を選択します。Python は内蔵ダウンローダーを使用し、aria2 は推奨の外部ダウンローダープロセスを使用します。",
             "options": {
                 "python": "Python（内蔵）",
-                "aria2": "aria2（実験的）"
+                "aria2": "aria2（推奨）"
             }
         },
         "aria2cPath": {
@@ -276,6 +283,7 @@
             "help": "aria2c 実行ファイルへの任意のパスです。空欄のままにすると、システム PATH 上の aria2c を使用します。",
             "placeholder": "空欄のままにすると PATH 上の aria2c を使用します"
         },
+        "aria2HelpLink": "aria2 ダウンロードバックエンドの設定方法",
         "civitaiHostBanner": {
             "title": "Civitai ホスト設定を利用できます",
             "content": "Civitai は現在、SFW コンテンツには civitai.com、制限なしコンテンツには civitai.red を使用しています。設定で既定で開くサイトを変更できます。",
@@ -427,6 +435,8 @@
                 "hover": "ホバー時に表示"
             },
             "cardInfoDisplayHelp": "モデル情報とアクションボタンの表示タイミングを選択",
+            "showVersionOnCard": "カードにバージョンを表示",
+            "showVersionOnCardHelp": "モデルカード上のバージョン名の表示/非表示を切り替えます",
             "modelCardFooterAction": "モデルカードボタンのアクション",
             "modelCardFooterActionOptions": {
                 "exampleImages": "例画像を開く",
@@ -438,7 +448,9 @@
                 "modelName": "モデル名",
                 "fileName": "ファイル名"
             },
-            "modelNameDisplayHelp": "モデルカードのフッターに表示する内容を選択"
+            "modelNameDisplayHelp": "モデルカードのフッターに表示する内容を選択",
+            "cardBlurAmount": "カードオーバーレイのぼかし",
+            "cardBlurAmountHelp": "モデルカードとレシピカードのヘッダー・フッターオーバーレイのぼかし強度を調整します（0 = ぼかしなし、20 = 最大ぼかし）。"
         },
         "folderSettings": {
             "activeLibrary": "アクティブライブラリ",
@@ -538,6 +550,21 @@
             "downloadLocationHelp": "Civitaiからの例画像を保存するフォルダパスを入力してください",
             "autoDownload": "例画像の自動ダウンロード",
             "autoDownloadHelp": "例画像がないモデルの例画像を自動的にダウンロードします（ダウンロード場所の設定が必要）",
+            "openMode": "サンプル画像を開く動作",
+            "openModeHelp": "サーバー上で開くか、対応するローカルパスをコピーするか、カスタム URI を起動するかを選択します。",
+            "openModeOptions": {
+                "system": "サーバー上で開く",
+                "clipboard": "ローカルパスをコピー",
+                "uriTemplate": "カスタム URI を開く"
+            },
+            "localRoot": "ローカルのサンプル画像ルート",
+            "localRootHelp": "サーバーのサンプル画像ディレクトリを反映する任意のローカルまたはマウント済みルートです。空欄の場合はサーバーのパスを再利用します。",
+            "localRootPlaceholder": "例: /Volumes/ComfyUI/example_images",
+            "uriTemplate": "URI テンプレートを開く",
+            "uriTemplateHelp": "ファイル URI や Shortcuts リンクなどのカスタムディープリンクを使用します。",
+            "uriTemplatePlaceholder": "例: shortcuts://run-shortcut?name=Open%20Finder&input=text&text={{encoded_local_path}}",
+            "uriTemplatePlaceholders": "使用可能なプレースホルダー: {{local_path}}, {{encoded_local_path}}, {{relative_path}}, {{encoded_relative_path}}, {{file_uri}}, {{encoded_file_uri}}",
+            "openModeWikiLink": "リモートオープンモードの詳細",
             "optimizeImages": "ダウンロード画像の最適化",
             "optimizeImagesHelp": "例画像を最適化してファイルサイズを縮小し、読み込み速度を向上させます（メタデータは保持されます）",
             "download": "ダウンロード",
@@ -557,7 +584,13 @@
         },
         "misc": {
             "includeTriggerWords": "LoRA構文にトリガーワードを含める",
-            "includeTriggerWordsHelp": "LoRA構文をクリップボードにコピーする際、学習済みトリガーワードを含めます"
+            "includeTriggerWordsHelp": "LoRA構文をクリップボードにコピーする際、学習済みトリガーワードを含めます",
+            "loraSyntaxFormat": "LoRA構文形式",
+            "loraSyntaxFormatHelp": "LoRA構文形式。フルパスはサブフォルダパスを含み（<lora:style/anime/x:1.0>）、モデルをロスレスで解決します。レガシーはファイル名のみ（<lora:x:1.0>）— A1111規約ですが、フォルダ間でファイル名が重複する場合に曖昧になる可能性があります。",
+            "loraSyntaxFormatOptions": {
+                "full": "フルパス（サブフォルダ/名前）",
+                "legacy": "レガシーA1111（名前のみ）"
+            }
         },
         "metadataArchive": {
             "enableArchiveDb": "メタデータアーカイブデータベースを有効化",
@@ -621,8 +654,6 @@
             },
             "refresh": {
                 "title": "モデルリストを更新",
-                "quick": "変更を同期",
-                "quickTooltip": "新しいモデルファイルや欠けているファイルをスキャンして一覧を最新に保ちます。",
                 "full": "キャッシュを再構築",
                 "fullTooltip": "メタデータファイルから全モデル情報を再読み込みします。リストが古いと感じるときや手動編集後に使用してください。"
             },
@@ -663,16 +694,30 @@
             "setContentRating": "すべてのモデルのコンテンツレーティングを設定",
             "copyAll": "すべての構文をコピー",
             "refreshAll": "すべてのメタデータを更新",
+            "repairMetadata": "選択したレシピのメタデータを修復",
+            "reimportMetadata": "ソースから再インポート",
             "checkUpdates": "選択項目の更新を確認",
             "moveAll": "すべてをフォルダに移動",
             "autoOrganize": "自動整理を実行",
             "skipMetadataRefresh": "選択したモデルのメタデータ更新をスキップ",
             "resumeMetadataRefresh": "選択したモデルのメタデータ更新を再開",
-            "deleteAll": "すべてのモデルを削除",
+            "setFavorite": "お気に入りに設定",
+            "setFavoriteCount": "お気に入りに設定 ({favorited}/{total})",
+            "unfavorite": "お気に入りから削除",
+            "deleteAll": "選択したものを削除",
             "downloadMissingLoras": "不足している LoRA をダウンロード",
+            "downloadExamples": "例画像をダウンロード",
             "clear": "選択をクリア",
             "skipMetadataRefreshCount": "スキップ（{count}モデル）",
             "resumeMetadataRefreshCount": "再開（{count}モデル）",
+            "sendToWorkflow": "ワークフローに送信",
+            "sections": {
+                "workflow": "ワークフロー",
+                "metadata": "メタデータ",
+                "attributes": "属性",
+                "organize": "整理",
+                "download": "ダウンロード"
+            },
             "autoOrganizeProgress": {
                 "initializing": "自動整理を初期化中...",
                 "starting": "{type}の自動整理を開始中...",
@@ -698,6 +743,7 @@
             "setContentRating": "コンテンツレーティングを設定",
             "moveToFolder": "フォルダに移動",
             "repairMetadata": "メタデータを修復",
+            "reimportMetadata": "ソースから再インポート",
             "excludeModel": "モデルを除外",
             "restoreModel": "モデルを復元",
             "deleteModel": "モデルを削除",
@@ -785,8 +831,6 @@
             },
             "refresh": {
                 "title": "レシピリストを更新",
-                "quick": "変更を同期",
-                "quickTooltip": "変更を同期 - キャッシュを再構築せずにクイック更新",
                 "full": "キャッシュを再構築",
                 "fullTooltip": "キャッシュを再構築 - すべてのレシピファイルを完全に再スキャン"
             },
@@ -827,6 +871,13 @@
                 "skipped": "レシピはすでに最新バージョンです。修復は不要です",
                 "failed": "レシピの修復に失敗しました: {message}",
                 "missingId": "レシピを修復できません: レシピIDがありません"
+            },
+            "reimport": {
+                "starting": "ソースからレシピを再インポート中...",
+                "success": "レシピの再インポートが完了しました",
+                "noSourceUrl": "レシピにソースURLがありません。再インポートできません",
+                "failed": "レシピの再インポートに失敗しました: {message}",
+                "missingId": "レシピを再インポートできません: レシピIDがありません"
             }
         },
         "batchImport": {
@@ -904,9 +955,13 @@
     },
     "sidebar": {
         "modelRoot": "ルート",
+        "moreOptions": "その他のオプション",
         "collapseAll": "すべてのフォルダを折りたたむ",
         "pinSidebar": "サイドバーを固定",
         "unpinSidebar": "サイドバーの固定を解除",
+        "hideOnThisPage": "このページでサイドバーを非表示",
+        "showSidebar": "サイドバーを表示",
+        "sidebarHiddenNotification": "{page}ページでサイドバーが非表示になっています",
         "switchToListView": "リストビューに切り替え",
         "switchToTreeView": "ツリー表示に切り替え",
         "recursiveOn": "サブフォルダーを含める",
@@ -926,6 +981,13 @@
         "empty": {
             "noFolders": "フォルダが見つかりません",
             "dragHint": "ここへアイテムをドラッグしてフォルダを作成します"
+        },
+        "folderUpdateCheck": {
+            "label": "このフォルダのアップデートを確認",
+            "loading": "このフォルダの{type}アップデートを確認中...",
+            "success": "このフォルダの{type}sに{count}件のアップデートが見つかりました",
+            "none": "このフォルダのすべての{type}sは最新です",
+            "error": "フォルダの{type}アップデート確認に失敗しました: {message}"
         }
     },
     "statistics": {
@@ -970,9 +1032,9 @@
         "download": {
             "title": "URLからモデルをダウンロード",
             "titleWithType": "URLから{type}をダウンロード",
-            "url": "Civitai URL",
             "civitaiUrl": "Civitai URL：",
             "placeholder": "https://civitai.com/models/...",
+            "urlHint": "1行に1つのCivitAIまたはCivArchive URLを入力してください。複数のURLを一括ダウンロードできます。",
             "locationPreview": "ダウンロード場所プレビュー",
             "useDefaultPath": "デフォルトパスを使用",
             "useDefaultPathTooltip": "有効にすると、設定されたパステンプレートを使用してファイルが自動的に整理されます",
@@ -994,6 +1056,11 @@
             "downloadedTooltip": "以前にダウンロード済みですが、現在はライブラリにありません。",
             "alreadyInLibrary": "既にライブラリ内",
             "autoOrganizedPath": "[パステンプレートによる自動整理]",
+            "fileSelection": {
+                "title": "ファイル形式を選択",
+                "files": "ファイル",
+                "select": "ファイルを選択"
+            },
             "errors": {
                 "invalidUrl": "無効なCivitai URL形式",
                 "noVersions": "このモデルの利用可能なバージョンがありません"
@@ -1058,6 +1125,12 @@
             "countMessage": "モデルが完全に削除されます。",
             "action": "すべて削除"
         },
+        "bulkDeleteRecipes": {
+            "title": "複数のレシピを削除",
+            "message": "選択したすべてのレシピと関連ファイルを削除してもよろしいですか？",
+            "countMessage": "レシピが完全に削除されます。",
+            "action": "すべて削除"
+        },
         "checkUpdates": {
             "title": "すべての{type}の更新を確認しますか？",
             "message": "ライブラリ内のすべての{type}で更新を確認します。コレクションが大きい場合は時間がかかることがあります。",
@@ -1138,6 +1211,7 @@
                 "editModelName": "モデル名を編集",
                 "editFileName": "ファイル名を編集",
                 "editBaseModel": "ベースモデルを編集",
+                "editVersionName": "バージョン名を編集",
                 "viewOnCivitai": "Civitaiで表示",
                 "viewOnCivitaiText": "Civitaiで表示",
                 "viewCreatorProfile": "作成者プロフィールを表示",
@@ -1169,7 +1243,9 @@
             },
             "notes": {
                 "saved": "メモが正常に保存されました",
-                "saveFailed": "メモの保存に失敗しました"
+                "saveFailed": "メモの保存に失敗しました",
+                "showMore": "もっと見る",
+                "showLess": "折りたたむ"
             },
             "usageTips": {
                 "addPresetParameter": "プリセットパラメータを追加...",
@@ -1274,12 +1350,15 @@
                     "earlyAccess": "早期アクセス",
                     "earlyAccessTooltip": "このバージョンは現在 Civitai の早期アクセスが必要です",
                     "ignored": "無視中",
-                    "ignoredTooltip": "このバージョンの更新通知は無効です"
+                    "ignoredTooltip": "このバージョンの更新通知は無効です",
+                    "onSiteOnly": "サイト内のみ",
+                    "onSiteOnlyTooltip": "このバージョンはCivitaiサイト内でのみ利用可能で、ダウンロードはできません"
                 },
                 "actions": {
                     "download": "ダウンロード",
                     "downloadTooltip": "このバージョンをダウンロード",
                     "downloadEarlyAccessTooltip": "Civitai からこの早期アクセス版をダウンロード",
+                    "downloadNotAllowedTooltip": "このバージョンはCivitaiサイト内でのみ利用可能で、ダウンロードはできません",
                     "delete": "削除",
                     "deleteTooltip": "このローカルバージョンを削除",
                     "ignore": "無視",
@@ -1428,11 +1507,14 @@
             "noMatchingNodes": "現在のワークフローには互換性のあるノードがありません",
             "noTargetNodeSelected": "ターゲットノードが選択されていません",
             "modelUpdated": "モデルがワークフローで更新されました",
-            "modelFailed": "モデルノードの更新に失敗しました"
+            "modelFailed": "モデルノードの更新に失敗しました",
+            "embeddingAdded": "Embeddingをワークフローに追加しました",
+            "embeddingFailed": "Embeddingの追加に失敗しました"
         },
         "nodeSelector": {
             "recipe": "レシピ",
             "lora": "LoRA",
+            "embedding": "Embedding",
             "replace": "置換",
             "append": "追加",
             "selectTargetNode": "ターゲットノードを選択",
@@ -1442,6 +1524,10 @@
             "opened": "例画像フォルダが開かれました",
             "openingFolder": "例画像フォルダを開いています",
             "failedToOpen": "例画像フォルダを開くのに失敗しました",
+            "copiedPath": "パスをクリップボードにコピーしました: {{path}}",
+            "clipboardFallback": "パス: {{path}}",
+            "copiedUri": "リンクをクリップボードにコピーしました: {{uri}}",
+            "uriClipboardFallback": "リンク: {{uri}}",
             "setupRequired": "例画像ストレージ",
             "setupDescription": "カスタム例画像を追加するには、まずダウンロード場所を設定する必要があります。",
             "setupUsage": "このパスは、ダウンロードした例画像とカスタム画像の両方に使用されます。",
@@ -1605,6 +1691,10 @@
             "noRecipeId": "レシピIDが利用できません",
             "sendToWorkflowFailed": "ワークフローへのレシピ送信に失敗しました：{message}",
             "copyFailed": "レシピ構文のコピーエラー：{message}",
+            "createError": "レシピ作成中にエラーが発生しました：{message}",
+            "createFailed": "レシピの作成に失敗しました：{error}",
+            "createMissingData": "レシピ作成に必要なデータが不足しています",
+            "created": "レシピを作成しました",
             "noMissingLoras": "ダウンロードする不足LoRAがありません",
             "missingLorasInfoFailed": "不足LoRAの情報取得に失敗しました",
             "preparingForDownloadFailed": "ダウンロード用LoRAの準備中にエラーが発生しました",
@@ -1643,6 +1733,13 @@
             "batchImportBrowseFailed": "Failed to browse directory: {message}",
             "batchImportDirectorySelected": "Directory selected: {path}",
             "noRecipesSelected": "レシピが選択されていません",
+            "repairBulkComplete": "修復完了：{repaired} 件修復、{skipped} 件スキップ（合計 {total} 件）",
+            "repairBulkSkipped": "選択した {total} 件のレシピは修復不要です",
+            "repairBulkFailed": "選択したレシピの修復に失敗しました：{message}",
+            "reimporting": "ソースからレシピを再インポート中...",
+            "reimportSuccess": "レシピの再インポートが完了しました",
+            "reimportBulkComplete": "再インポート完了：{completed} 件成功、{failed} 件失敗（合計 {total} 件）",
+            "reimportBulkFailed": "一部のレシピの再インポートに失敗しました",
             "noMissingLorasInSelection": "選択したレシピに不足している LoRA が見つかりませんでした",
             "noLoraRootConfigured": "LoRA ルートディレクトリが設定されていません。設定でデフォルトの LoRA ルートを設定してください。"
         },
@@ -1673,6 +1770,11 @@
             "bulkContentRatingSet": "{count} 件のモデルのコンテンツレーティングを {level} に設定しました",
             "bulkContentRatingPartial": "{success} 件のモデルのコンテンツレーティングを {level} に設定、{failed} 件は失敗しました",
             "bulkContentRatingFailed": "選択したモデルのコンテンツレーティングを更新できませんでした",
+            "bulkFavoriteUpdating": "{count} 個のモデルをお気に入りに追加中...",
+            "bulkUnfavoriteUpdating": "{count} 個のモデルをお気に入りから削除中...",
+            "bulkFavoritePartialAdded": "{success} 個のモデルをお気に入りに追加、{failed} 個失敗",
+            "bulkFavoritePartialRemoved": "{success} 個のモデルをお気に入りから削除、{failed} 個失敗",
+            "bulkFavoriteFailed": "お気に入り状態の更新に失敗しました",
             "bulkUpdatesChecking": "選択された{type}の更新を確認しています...",
             "bulkUpdatesSuccess": "{count} 件の選択された{type}に利用可能な更新があります",
             "bulkUpdatesNone": "選択された{type}には更新が見つかりませんでした",
@@ -1875,18 +1977,52 @@
             "warning": "要注意",
             "error": "対応が必要"
         },
+        "issues": {
+            "civitai_api_key": {
+                "title": "Civitai API キー"
+            },
+            "cache_health": {
+                "title": "モデルキャッシュの健全性"
+            },
+            "filename_conflicts": {
+                "title": "ファイル名重複競合"
+            },
+            "ui_version": {
+                "title": "UI バージョン"
+            }
+        },
         "actions": {
             "runAgain": "再実行",
-            "exportBundle": "パッケージをエクスポート"
+            "exportBundle": "パッケージをエクスポート",
+            "open-settings": "設定を開く",
+            "open-settings-syntax-format": "フルパス構文に切り替え",
+            "repair-cache": "キャッシュを再構築",
+            "resolve-filename-conflicts": "競合を解決",
+            "reload-page": "UI をリロード"
+        },
+        "labels": {
+            "conflicts": "競合",
+            "version": "バージョン"
         },
         "toast": {
             "loadFailed": "診断の読み込みに失敗しました: {message}",
             "repairSuccess": "キャッシュの再構築が完了しました。",
             "repairFailed": "キャッシュの再構築に失敗しました: {message}",
             "exportSuccess": "診断パッケージをエクスポートしました。",
-            "exportFailed": "診断パッケージのエクスポートに失敗しました: {message}"
+            "exportFailed": "診断パッケージのエクスポートに失敗しました: {message}",
+            "conflictsResolved": "{count} 件のファイル名競合が解決されました。",
+            "conflictsResolveFailed": "ファイル名競合の解決に失敗しました: {message}"
         }
     },
+    "conflictConfirm": {
+        "title": "ファイル名の競合を解決",
+        "message": "重複したファイル名に4文字のハッシュを追加してリネームします。",
+        "note": "この操作はディスク上のファイルをリネームします。A1111 構文形式を使用している場合、既存のワークフロー内のモデル参照を更新する必要があるかもしれません。",
+        "detail": "例：<code>filename_v1.2</code> → <code>filename_v1.2-ab3c</code>",
+        "impact": "<strong>{groups}</strong> 組の重複にわたって <strong>{count}</strong> 個のファイルをリネームします",
+        "confirm": "ファイルをリネーム",
+        "cancel": "キャンセル"
+    },
     "banners": {
         "versionMismatch": {
             "title": "アプリケーション更新が検出されました",

locales/ko.json

@@ -15,7 +15,10 @@
             "settings": "설정",
             "help": "도움말",
             "add": "추가",
-            "close": "닫기"
+            "close": "닫기",
+            "menu": "메뉴",
+            "remove": "제거",
+            "change": "변경"
         },
         "status": {
             "loading": "로딩 중...",
@@ -110,6 +113,7 @@
             "replacePreview": "미리보기 교체",
             "copyCheckpointName": "Checkpoint 이름 복사",
             "copyEmbeddingName": "Embedding 이름 복사",
+            "embeddingNameCopied": "Embedding 구문 복사됨",
             "sendCheckpointToWorkflow": "ComfyUI로 전송",
             "sendEmbeddingToWorkflow": "ComfyUI로 전송"
         },
@@ -231,7 +235,10 @@
             "license": "라이선스",
             "noCreditRequired": "크레딧 표기 없음",
             "allowSellingGeneratedContent": "판매 허용",
+            "allowSellingGeneratedContentTooltip": "생성된 이미지 판매 허용",
+            "noCreditRequiredTooltip": "크리에이터 저작자 표시 없이 모델 사용 가능",
             "noTags": "태그 없음",
+            "autoTags": "자동 태그",
             "noBaseModelMatches": "현재 검색과 일치하는 베이스 모델이 없습니다.",
             "clearAll": "모든 필터 지우기",
             "any": "아무",
@@ -265,10 +272,10 @@
         },
         "downloadBackend": {
             "label": "다운로드 백엔드",
-            "help": "모델 파일을 다운로드하는 방식을 선택합니다. Python은 내장 다운로더를 사용하고, aria2는 실험적인 외부 다운로더 프로세스를 사용합니다.",
+            "help": "모델 파일을 다운로드하는 방식을 선택합니다. Python은 내장 다운로더를 사용하고, aria2는 권장되는 외부 다운로더 프로세스를 사용합니다.",
             "options": {
                 "python": "Python(내장)",
-                "aria2": "aria2(실험적)"
+                "aria2": "aria2(권장)"
             }
         },
         "aria2cPath": {
@@ -276,6 +283,7 @@
             "help": "aria2c 실행 파일의 선택적 경로입니다. 비워 두면 시스템 PATH의 aria2c를 사용합니다.",
             "placeholder": "비워 두면 PATH의 aria2c를 사용합니다"
         },
+        "aria2HelpLink": "aria2 다운로드 백엔드 설정 방법 알아보기",
         "civitaiHostBanner": {
             "title": "Civitai 호스트 기본 설정 사용 가능",
             "content": "이제 Civitai는 SFW 콘텐츠에 civitai.com을, 무제한 콘텐츠에 civitai.red를 사용합니다. 설정에서 기본으로 열 사이트를 변경할 수 있습니다.",
@@ -427,6 +435,8 @@
                 "hover": "호버 시 표시"
             },
             "cardInfoDisplayHelp": "모델 정보 및 액션 버튼을 언제 표시할지 선택하세요",
+            "showVersionOnCard": "카드에 버전 표시",
+            "showVersionOnCardHelp": "모델 카드에 버전 이름 표시 여부를 전환합니다",
             "modelCardFooterAction": "모델 카드 버튼 동작",
             "modelCardFooterActionOptions": {
                 "exampleImages": "예시 이미지 열기",
@@ -438,7 +448,9 @@
                 "modelName": "모델명",
                 "fileName": "파일명"
             },
-            "modelNameDisplayHelp": "모델 카드 하단에 표시할 내용을 선택하세요"
+            "modelNameDisplayHelp": "모델 카드 하단에 표시할 내용을 선택하세요",
+            "cardBlurAmount": "카드 오버레이 흐림 강도",
+            "cardBlurAmountHelp": "모델 및 레시피 카드의 헤더와 푸터 오버레이 흐림 강도를 조정합니다 (0 = 흐림 없음, 20 = 최대 흐림)."
         },
         "folderSettings": {
             "activeLibrary": "활성 라이브러리",
@@ -538,6 +550,21 @@
             "downloadLocationHelp": "Civitai의 예시 이미지가 저장될 폴더 경로를 입력하세요",
             "autoDownload": "예시 이미지 자동 다운로드",
             "autoDownloadHelp": "예시 이미지가 없는 모델의 예시 이미지를 자동으로 다운로드합니다 (다운로드 위치 설정 필요)",
+            "openMode": "예시 이미지 열기 동작",
+            "openModeHelp": "서버에서 열지, 매핑된 로컬 경로를 복사할지, 사용자 지정 URI를 실행할지 선택합니다.",
+            "openModeOptions": {
+                "system": "서버에서 열기",
+                "clipboard": "로컬 경로 복사",
+                "uriTemplate": "사용자 지정 URI 열기"
+            },
+            "localRoot": "로컬 예시 이미지 루트",
+            "localRootHelp": "서버 예시 이미지 디렉터리를 반영하는 선택적 로컬 또는 마운트된 루트입니다. 비워 두면 서버 경로를 재사용합니다.",
+            "localRootPlaceholder": "예: /Volumes/ComfyUI/example_images",
+            "uriTemplate": "URI 템플릿 열기",
+            "uriTemplateHelp": "파일 URI 또는 Shortcuts 링크 같은 사용자 지정 딥링크를 사용합니다.",
+            "uriTemplatePlaceholder": "예: shortcuts://run-shortcut?name=Open%20Finder&input=text&text={{encoded_local_path}}",
+            "uriTemplatePlaceholders": "사용 가능한 플레이스홀더: {{local_path}}, {{encoded_local_path}}, {{relative_path}}, {{encoded_relative_path}}, {{file_uri}}, {{encoded_file_uri}}",
+            "openModeWikiLink": "원격 열기 모드에 대해 자세히 알아보기",
             "optimizeImages": "다운로드된 이미지 최적화",
             "optimizeImagesHelp": "파일 크기를 줄이고 로딩 속도를 향상시키기 위해 예시 이미지를 최적화합니다 (메타데이터는 보존됨)",
             "download": "다운로드",
@@ -557,7 +584,13 @@
         },
         "misc": {
             "includeTriggerWords": "LoRA 문법에 트리거 단어 포함",
-            "includeTriggerWordsHelp": "LoRA 문법을 클립보드에 복사할 때 학습된 트리거 단어를 포함합니다"
+            "includeTriggerWordsHelp": "LoRA 문법을 클립보드에 복사할 때 학습된 트리거 단어를 포함합니다",
+            "loraSyntaxFormat": "LoRA 구문 형식",
+            "loraSyntaxFormatHelp": "LoRA 구문 형식. 전체 경로는 하위 폴더 경로(<lora:style/anime/x:1.0>)를 포함하여 손실 없는 모델 해상도를 제공합니다. 레거시는 파일 이름만(<lora:x:1.0>) 사용 — A1111 규칙이지만, 폴더 간 파일명 중복 시 모호할 수 있습니다.",
+            "loraSyntaxFormatOptions": {
+                "full": "전체 경로(하위 폴더/이름)",
+                "legacy": "레거시 A1111(이름만)"
+            }
         },
         "metadataArchive": {
             "enableArchiveDb": "메타데이터 아카이브 데이터베이스 활성화",
@@ -621,8 +654,6 @@
             },
             "refresh": {
                 "title": "모델 목록 새로고침",
-                "quick": "변경 사항 동기화",
-                "quickTooltip": "새로운 모델 파일이나 누락된 파일을 찾아 목록을 최신 상태로 유지합니다.",
                 "full": "캐시 재구성",
                 "fullTooltip": "메타데이터 파일에서 모든 모델 정보를 다시 불러옵니다. 라이브러리가 오래되어 보이거나 수동 수정 후에 사용하세요."
             },
@@ -663,16 +694,30 @@
             "setContentRating": "모든 모델에 콘텐츠 등급 설정",
             "copyAll": "모든 문법 복사",
             "refreshAll": "모든 메타데이터 새로고침",
+            "repairMetadata": "선택한 레시피 메타데이터 복구",
+            "reimportMetadata": "소스에서 다시 가져오기",
             "checkUpdates": "선택 항목 업데이트 확인",
             "moveAll": "모두 폴더로 이동",
             "autoOrganize": "자동 정리 선택",
             "skipMetadataRefresh": "선택한 모델의 메타데이터 새로고침 건너뛰기",
             "resumeMetadataRefresh": "선택한 모델의 메타데이터 새로고침 재개",
-            "deleteAll": "모든 모델 삭제",
+            "setFavorite": "즐겨찾기로 설정",
+            "setFavoriteCount": "즐겨찾기로 설정 ({favorited}/{total})",
+            "unfavorite": "즐겨찾기 해제",
+            "deleteAll": "선택된 항목 삭제",
             "downloadMissingLoras": "누락된 LoRA 다운로드",
+            "downloadExamples": "예시 이미지 다운로드",
             "clear": "선택 지우기",
             "skipMetadataRefreshCount": "건너뛰기（{count}개 모델）",
             "resumeMetadataRefreshCount": "재개（{count}개 모델）",
+            "sendToWorkflow": "워크플로우로 보내기",
+            "sections": {
+                "workflow": "워크플로우",
+                "metadata": "메타데이터",
+                "attributes": "속성",
+                "organize": "정리",
+                "download": "다운로드"
+            },
             "autoOrganizeProgress": {
                 "initializing": "자동 정리 초기화 중...",
                 "starting": "{type}에 대한 자동 정리 시작...",
@@ -698,6 +743,7 @@
             "setContentRating": "콘텐츠 등급 설정",
             "moveToFolder": "폴더로 이동",
             "repairMetadata": "메타데이터 복구",
+            "reimportMetadata": "소스에서 다시 가져오기",
             "excludeModel": "모델 제외",
             "restoreModel": "모델 복원",
             "deleteModel": "모델 삭제",
@@ -785,8 +831,6 @@
             },
             "refresh": {
                 "title": "레시피 목록 새로고침",
-                "quick": "변경 사항 동기화",
-                "quickTooltip": "변경 사항 동기화 - 캐시를 재구성하지 않고 빠른 새로고침",
                 "full": "캐시 재구성",
                 "fullTooltip": "캐시 재구성 - 모든 레시피 파일을 완전히 다시 스캔"
             },
@@ -827,6 +871,13 @@
                 "skipped": "레시피가 이미 최신 버전입니다. 복구가 필요하지 않습니다",
                 "failed": "레시피 복구 실패: {message}",
                 "missingId": "레시피를 복구할 수 없음: 레시피 ID 누락"
+            },
+            "reimport": {
+                "starting": "소스에서 레시피를 다시 가져오는 중...",
+                "success": "레시피를 다시 가져왔습니다",
+                "noSourceUrl": "레시피에 소스 URL이 없어 다시 가져올 수 없습니다",
+                "failed": "레시피 다시 가져오기 실패: {message}",
+                "missingId": "레시피를 다시 가져올 수 없음: 레시피 ID 누락"
             }
         },
         "batchImport": {
@@ -904,9 +955,13 @@
     },
     "sidebar": {
         "modelRoot": "루트",
+        "moreOptions": "더 많은 옵션",
         "collapseAll": "모든 폴더 접기",
         "pinSidebar": "사이드바 고정",
         "unpinSidebar": "사이드바 고정 해제",
+        "hideOnThisPage": "이 페이지에서 사이드바 숨기기",
+        "showSidebar": "사이드바 표시",
+        "sidebarHiddenNotification": "{page} 페이지에서 사이드바가 숨겨져 있습니다",
         "switchToListView": "목록 보기로 전환",
         "switchToTreeView": "트리 보기로 전환",
         "recursiveOn": "하위 폴더 포함",
@@ -926,6 +981,13 @@
         "empty": {
             "noFolders": "폴더를 찾을 수 없습니다",
             "dragHint": "항목을 여기로 드래그하여 폴더를 만듭니다"
+        },
+        "folderUpdateCheck": {
+            "label": "이 폴더의 업데이트 확인",
+            "loading": "이 폴더의 {type} 업데이트를 확인하는 중...",
+            "success": "이 폴더에서 {type}s에 대한 {count}개 업데이트를 찾았습니다",
+            "none": "이 폴더의 모든 {type}s가 최신 상태입니다",
+            "error": "폴더의 {type} 업데이트 확인 실패: {message}"
         }
     },
     "statistics": {
@@ -970,9 +1032,9 @@
         "download": {
             "title": "URL에서 모델 다운로드",
             "titleWithType": "URL에서 {type} 다운로드",
-            "url": "Civitai URL",
             "civitaiUrl": "Civitai URL:",
             "placeholder": "https://civitai.com/models/...",
+            "urlHint": "한 줄에 하나의 CivitAI 또는 CivArchive URL을 입력하세요. 여러 URL을 일괄 다운로드할 수 있습니다.",
             "locationPreview": "다운로드 위치 미리보기",
             "useDefaultPath": "기본 경로 사용",
             "useDefaultPathTooltip": "활성화하면 구성된 경로 템플릿을 사용하여 파일이 자동으로 정리됩니다",
@@ -994,6 +1056,11 @@
             "downloadedTooltip": "이전에 다운로드했지만 현재 라이브러리에 없습니다.",
             "alreadyInLibrary": "이미 라이브러리에 있음",
             "autoOrganizedPath": "[경로 템플릿으로 자동 정리됨]",
+            "fileSelection": {
+                "title": "파일 형식 선택",
+                "files": "개 파일",
+                "select": "파일 선택"
+            },
             "errors": {
                 "invalidUrl": "잘못된 Civitai URL 형식",
                 "noVersions": "이 모델에 사용 가능한 버전이 없습니다"
@@ -1058,6 +1125,12 @@
             "countMessage": "개의 모델이 영구적으로 삭제됩니다.",
             "action": "모두 삭제"
         },
+        "bulkDeleteRecipes": {
+            "title": "여러 레시피 삭제",
+            "message": "선택된 모든 레시피와 관련 파일을 삭제하시겠습니까?",
+            "countMessage": "개의 레시피가 영구적으로 삭제됩니다.",
+            "action": "모두 삭제"
+        },
         "checkUpdates": {
             "title": "{type} 전체 업데이트를 확인할까요?",
             "message": "라이브러리에 있는 모든 {type}의 업데이트를 확인합니다. 컬렉션이 클수록 시간이 조금 더 걸릴 수 있습니다.",
@@ -1138,6 +1211,7 @@
                 "editModelName": "모델명 편집",
                 "editFileName": "파일명 편집",
                 "editBaseModel": "베이스 모델 편집",
+                "editVersionName": "버전명 편집",
                 "viewOnCivitai": "Civitai에서 보기",
                 "viewOnCivitaiText": "Civitai에서 보기",
                 "viewCreatorProfile": "제작자 프로필 보기",
@@ -1169,7 +1243,9 @@
             },
             "notes": {
                 "saved": "메모가 성공적으로 저장됨",
-                "saveFailed": "메모 저장 실패"
+                "saveFailed": "메모 저장 실패",
+                "showMore": "더 보기",
+                "showLess": "접기"
             },
             "usageTips": {
                 "addPresetParameter": "프리셋 매개변수 추가...",
@@ -1274,12 +1350,15 @@
                     "earlyAccess": "얼리 액세스",
                     "earlyAccessTooltip": "이 버전은 현재 Civitai 얼리 액세스가 필요합니다",
                     "ignored": "무시됨",
-                    "ignoredTooltip": "이 버전은 업데이트 알림이 비활성화되어 있습니다"
+                    "ignoredTooltip": "이 버전은 업데이트 알림이 비활성화되어 있습니다",
+                    "onSiteOnly": "사이트 내 전용",
+                    "onSiteOnlyTooltip": "이 버전은 Civitai 사이트 내에서만 사용 가능하며 다운로드할 수 없습니다"
                 },
                 "actions": {
                     "download": "다운로드",
                     "downloadTooltip": "이 버전 다운로드",
                     "downloadEarlyAccessTooltip": "Civitai에서 이 얼리 액세스 버전 다운로드",
+                    "downloadNotAllowedTooltip": "이 버전은 Civitai 사이트 내에서만 사용 가능하며 다운로드할 수 없습니다",
                     "delete": "삭제",
                     "deleteTooltip": "이 로컬 버전 삭제",
                     "ignore": "무시",
@@ -1428,11 +1507,14 @@
             "noMatchingNodes": "현재 워크플로에서 호환되는 노드가 없습니다",
             "noTargetNodeSelected": "대상 노드가 선택되지 않았습니다",
             "modelUpdated": "모델이 워크플로에서 업데이트되었습니다",
-            "modelFailed": "모델 노드 업데이트 실패"
+            "modelFailed": "모델 노드 업데이트 실패",
+            "embeddingAdded": "Embedding을 워크플로에 추가했습니다",
+            "embeddingFailed": "Embedding 추가 실패"
         },
         "nodeSelector": {
             "recipe": "레시피",
             "lora": "LoRA",
+            "embedding": "임베딩",
             "replace": "교체",
             "append": "추가",
             "selectTargetNode": "대상 노드 선택",
@@ -1442,6 +1524,10 @@
             "opened": "예시 이미지 폴더가 열렸습니다",
             "openingFolder": "예시 이미지 폴더를 여는 중",
             "failedToOpen": "예시 이미지 폴더 열기 실패",
+            "copiedPath": "경로를 클립보드에 복사했습니다: {{path}}",
+            "clipboardFallback": "경로: {{path}}",
+            "copiedUri": "링크를 클립보드에 복사했습니다: {{uri}}",
+            "uriClipboardFallback": "링크: {{uri}}",
             "setupRequired": "예시 이미지 저장소",
             "setupDescription": "사용자 지정 예시 이미지를 추가하려면 먼저 다운로드 위치를 설정해야 합니다.",
             "setupUsage": "이 경로는 다운로드한 예시 이미지와 사용자 지정 이미지 모두에 사용됩니다.",
@@ -1605,6 +1691,10 @@
             "noRecipeId": "사용 가능한 레시피 ID가 없습니다",
             "sendToWorkflowFailed": "워크플로우에 레시피 보내기 실패: {message}",
             "copyFailed": "레시피 문법 복사 오류: {message}",
+            "createError": "레시피 생성 중 오류 발생：{message}",
+            "createFailed": "레시피 생성 실패：{error}",
+            "createMissingData": "레시피 생성에 필요한 데이터가 없습니다",
+            "created": "레시피가 생성되었습니다",
             "noMissingLoras": "다운로드할 누락된 LoRA가 없습니다",
             "missingLorasInfoFailed": "누락된 LoRA 정보를 가져오는데 실패했습니다",
             "preparingForDownloadFailed": "LoRA 다운로드 준비 오류",
@@ -1643,6 +1733,13 @@
             "batchImportBrowseFailed": "Failed to browse directory: {message}",
             "batchImportDirectorySelected": "Directory selected: {path}",
             "noRecipesSelected": "선택한 레시피가 없습니다",
+            "repairBulkComplete": "복구 완료: {repaired}개 복구, {skipped}개 건너뜀 (총 {total}개)",
+            "repairBulkSkipped": "선택한 {total}개 레시피는 복구가 필요하지 않습니다",
+            "repairBulkFailed": "선택한 레시피 복구 실패: {message}",
+            "reimporting": "소스에서 레시피를 다시 가져오는 중...",
+            "reimportSuccess": "레시피를 다시 가져왔습니다",
+            "reimportBulkComplete": "다시 가져오기 완료: {completed}개 성공, {failed}개 실패 (총 {total}개)",
+            "reimportBulkFailed": "일부 레시피를 다시 가져오지 못했습니다",
             "noMissingLorasInSelection": "선택한 레시피에서 누락된 LoRA를 찾을 수 없습니다",
             "noLoraRootConfigured": "LoRA 루트 디렉토리가 구성되지 않았습니다. 설정에서 기본 LoRA 루트를 설정하세요."
         },
@@ -1673,6 +1770,11 @@
             "bulkContentRatingSet": "{count}개 모델의 콘텐츠 등급을 {level}(으)로 설정했습니다",
             "bulkContentRatingPartial": "{success}개 모델의 콘텐츠 등급을 {level}(으)로 설정했고, {failed}개는 실패했습니다",
             "bulkContentRatingFailed": "선택한 모델의 콘텐츠 등급을 업데이트하지 못했습니다",
+            "bulkFavoriteUpdating": "{count}개 모델을 즐겨찾기에 추가 중...",
+            "bulkUnfavoriteUpdating": "{count}개 모델을 즐겨찾기에서 제거 중...",
+            "bulkFavoritePartialAdded": "{success}개 모델을 즐겨찾기에 추가, {failed}개 실패",
+            "bulkFavoritePartialRemoved": "{success}개 모델을 즐겨찾기에서 제거, {failed}개 실패",
+            "bulkFavoriteFailed": "즐겨찾기 상태 업데이트 실패",
             "bulkUpdatesChecking": "선택한 {type}의 업데이트를 확인하는 중...",
             "bulkUpdatesSuccess": "선택한 {count}개의 {type}에 사용할 수 있는 업데이트가 있습니다",
             "bulkUpdatesNone": "선택한 {type}에 대한 업데이트가 없습니다",
@@ -1875,18 +1977,52 @@
             "warning": "주의 필요",
             "error": "조치 필요"
         },
+        "issues": {
+            "civitai_api_key": {
+                "title": "Civitai API 키"
+            },
+            "cache_health": {
+                "title": "모델 캐시 상태"
+            },
+            "filename_conflicts": {
+                "title": "파일명 중복 충돌"
+            },
+            "ui_version": {
+                "title": "UI 버전"
+            }
+        },
         "actions": {
             "runAgain": "다시 실행",
-            "exportBundle": "번들 내보내기"
+            "exportBundle": "번들 내보내기",
+            "open-settings": "설정 열기",
+            "open-settings-syntax-format": "전체 경로 구문으로 전환",
+            "repair-cache": "캐시 재구축",
+            "resolve-filename-conflicts": "충돌 해결",
+            "reload-page": "UI 새로고침"
+        },
+        "labels": {
+            "conflicts": "충돌",
+            "version": "버전"
         },
         "toast": {
             "loadFailed": "진단 로드 실패: {message}",
             "repairSuccess": "캐시 재구성이 완료되었습니다.",
             "repairFailed": "캐시 재구성 실패: {message}",
             "exportSuccess": "진단 번들이 내보내졌습니다.",
-            "exportFailed": "진단 번들 내보내기 실패: {message}"
+            "exportFailed": "진단 번들 내보내기 실패: {message}",
+            "conflictsResolved": "{count}개 파일명 충돌이 해결되었습니다.",
+            "conflictsResolveFailed": "파일명 충돌 해결 실패: {message}"
         }
     },
+    "conflictConfirm": {
+        "title": "파일명 충돌 해결",
+        "message": "중복 파일명에 4자리 해시를 추가하여 이름을 변경합니다.",
+        "note": "이 작업은 디스크에 있는 파일의 이름을 변경합니다. A1111 구문 형식을 사용하는 경우 기존 워크플로우의 모델 참조를 업데이트해야 할 수 있습니다.",
+        "detail": "예시: <code>filename_v1.2</code> → <code>filename_v1.2-ab3c</code>",
+        "impact": "<strong>{groups}</strong>개 중복 그룹에서 <strong>{count}</strong>개 파일 이름을 변경합니다",
+        "confirm": "파일 이름 변경",
+        "cancel": "취소"
+    },
     "banners": {
         "versionMismatch": {
             "title": "애플리케이션 업데이트 감지",

locales/ru.json

@@ -15,7 +15,10 @@
             "settings": "Настройки",
             "help": "Справка",
             "add": "Добавить",
-            "close": "Закрыть"
+            "close": "Закрыть",
+            "menu": "Меню",
+            "remove": "Удалить",
+            "change": "Изменить"
         },
         "status": {
             "loading": "Загрузка...",
@@ -110,6 +113,7 @@
             "replacePreview": "Заменить превью",
             "copyCheckpointName": "Копировать имя checkpoint",
             "copyEmbeddingName": "Копировать имя embedding",
+            "embeddingNameCopied": "Синтаксис embedding скопирован",
             "sendCheckpointToWorkflow": "Отправить в ComfyUI",
             "sendEmbeddingToWorkflow": "Отправить в ComfyUI"
         },
@@ -231,7 +235,10 @@
             "license": "Лицензия",
             "noCreditRequired": "Без указания авторства",
             "allowSellingGeneratedContent": "Продажа разрешена",
+            "allowSellingGeneratedContentTooltip": "Разрешить продажу сгенерированных изображений",
+            "noCreditRequiredTooltip": "Использование модели без указания автора",
             "noTags": "Без тегов",
+            "autoTags": "Авто-теги",
             "noBaseModelMatches": "Нет базовых моделей, соответствующих текущему поиску.",
             "clearAll": "Очистить все фильтры",
             "any": "Любой",
@@ -265,10 +272,10 @@
         },
         "downloadBackend": {
             "label": "Бэкенд загрузки",
-            "help": "Выберите способ загрузки файлов моделей. Python использует встроенный загрузчик. aria2 использует экспериментальный внешний процесс загрузки.",
+            "help": "Выберите способ загрузки файлов моделей. Python использует встроенный загрузчик. aria2 использует рекомендуемый внешний процесс загрузки.",
             "options": {
                 "python": "Python (встроенный)",
-                "aria2": "aria2 (экспериментальный)"
+                "aria2": "aria2 (рекомендуемый)"
             }
         },
         "aria2cPath": {
@@ -276,6 +283,7 @@
             "help": "Необязательный путь к исполняемому файлу aria2c. Оставьте пустым, чтобы использовать aria2c из системного PATH.",
             "placeholder": "Оставьте пустым, чтобы использовать aria2c из PATH"
         },
+        "aria2HelpLink": "Узнайте, как настроить сервер загрузки aria2",
         "civitaiHostBanner": {
             "title": "Доступна настройка хоста Civitai",
             "content": "Теперь Civitai использует civitai.com для контента SFW и civitai.red для контента без ограничений. В настройках можно изменить, какой сайт открывать по умолчанию.",
@@ -427,6 +435,8 @@
                 "hover": "Показать при наведении"
             },
             "cardInfoDisplayHelp": "Выберите когда отображать информацию о модели и кнопки действий",
+            "showVersionOnCard": "Показывать версию на карточке",
+            "showVersionOnCardHelp": "Показать или скрыть название версии на карточках моделей",
             "modelCardFooterAction": "Действие кнопки карточки модели",
             "modelCardFooterActionOptions": {
                 "exampleImages": "Открыть примеры изображений",
@@ -438,7 +448,9 @@
                 "modelName": "Название модели",
                 "fileName": "Имя файла"
             },
-            "modelNameDisplayHelp": "Выберите, что отображать в нижней части карточки модели"
+            "modelNameDisplayHelp": "Выберите, что отображать в нижней части карточки модели",
+            "cardBlurAmount": "Размытие наложения карточек",
+            "cardBlurAmountHelp": "Настройте интенсивность размытия наложений верхнего и нижнего колонтитулов на карточках моделей и рецептов (0 = без размытия, 20 = максимальное размытие)."
         },
         "folderSettings": {
             "activeLibrary": "Активная библиотека",
@@ -538,6 +550,21 @@
             "downloadLocationHelp": "Введите путь к папке, где будут сохраняться примеры изображений с Civitai",
             "autoDownload": "Автозагрузка примеров изображений",
             "autoDownloadHelp": "Автоматически загружать примеры изображений для моделей, у которых их нет (требует настройки места загрузки)",
+            "openMode": "Действие открытия примеров изображений",
+            "openModeHelp": "Выберите, будет ли действие открывать папку на сервере, копировать сопоставленный локальный путь или запускать пользовательский URI.",
+            "openModeOptions": {
+                "system": "Открыть на сервере",
+                "clipboard": "Скопировать локальный путь",
+                "uriTemplate": "Открыть пользовательский URI"
+            },
+            "localRoot": "Локальный корень примеров изображений",
+            "localRootHelp": "Необязательный локальный или смонтированный корневой путь, отражающий каталог примеров изображений на сервере. Если оставить пустым, будет использован путь сервера.",
+            "localRootPlaceholder": "Пример: /Volumes/ComfyUI/example_images",
+            "uriTemplate": "Шаблон URI для открытия",
+            "uriTemplateHelp": "Используйте пользовательскую deep link-ссылку, например file URI или ссылку Shortcuts.",
+            "uriTemplatePlaceholder": "Пример: shortcuts://run-shortcut?name=Open%20Finder&input=text&text={{encoded_local_path}}",
+            "uriTemplatePlaceholders": "Доступные плейсхолдеры: {{local_path}}, {{encoded_local_path}}, {{relative_path}}, {{encoded_relative_path}}, {{file_uri}}, {{encoded_file_uri}}",
+            "openModeWikiLink": "Подробнее об удаленных режимах открытия",
             "optimizeImages": "Оптимизировать загруженные изображения",
             "optimizeImagesHelp": "Оптимизировать примеры изображений для уменьшения размера файла и улучшения скорости загрузки (метаданные будут сохранены)",
             "download": "Загрузить",
@@ -557,7 +584,13 @@
         },
         "misc": {
             "includeTriggerWords": "Включать триггерные слова в синтаксис LoRA",
-            "includeTriggerWordsHelp": "Включать обученные триггерные слова при копировании синтаксиса LoRA в буфер обмена"
+            "includeTriggerWordsHelp": "Включать обученные триггерные слова при копировании синтаксиса LoRA в буфер обмена",
+            "loraSyntaxFormat": "Формат синтаксиса LoRA",
+            "loraSyntaxFormatHelp": "Формат синтаксиса LoRA. Полный путь включает подпапку (<lora:style/anime/x:1.0>) для безпотерьного разрешения модели. Устаревший использует только имя файла (<lora:x:1.0>) — соглашение A1111, может быть неоднозначным при дублировании имён файлов в разных папках.",
+            "loraSyntaxFormatOptions": {
+                "full": "Полный путь (подпапка/имя)",
+                "legacy": "Устаревший A1111 (только имя)"
+            }
         },
         "metadataArchive": {
             "enableArchiveDb": "Включить архив метаданных",
@@ -621,8 +654,6 @@
             },
             "refresh": {
                 "title": "Обновить список моделей",
-                "quick": "Синхронизировать изменения",
-                "quickTooltip": "Находит новые или отсутствующие файлы моделей, чтобы список оставался актуальным.",
                 "full": "Перестроить кэш",
                 "fullTooltip": "Перечитывает все данные моделей из файлов метаданных — используйте, если библиотека выглядит устаревшей или после ручных правок."
             },
@@ -663,16 +694,30 @@
             "setContentRating": "Установить рейтинг контента для всех",
             "copyAll": "Копировать весь синтаксис",
             "refreshAll": "Обновить все метаданные",
+            "repairMetadata": "Восстановить метаданные для выбранных",
+            "reimportMetadata": "Переимпортировать из источника",
             "checkUpdates": "Проверить обновления для выбранных",
             "moveAll": "Переместить все в папку",
             "autoOrganize": "Автоматически организовать выбранные",
             "skipMetadataRefresh": "Пропустить обновление метаданных для выбранных",
             "resumeMetadataRefresh": "Возобновить обновление метаданных для выбранных",
-            "deleteAll": "Удалить все модели",
+            "setFavorite": "Добавить в избранное",
+            "setFavoriteCount": "Добавить в избранное ({favorited}/{total})",
+            "unfavorite": "Удалить из избранного",
+            "deleteAll": "Удалить выбранные",
             "downloadMissingLoras": "Скачать отсутствующие LoRAs",
+            "downloadExamples": "Загрузить примеры изображений",
             "clear": "Очистить выбор",
             "skipMetadataRefreshCount": "Пропустить（{count} моделей）",
             "resumeMetadataRefreshCount": "Возобновить（{count} моделей）",
+            "sendToWorkflow": "Отправить в Workflow",
+            "sections": {
+                "workflow": "Workflow",
+                "metadata": "Метаданные",
+                "attributes": "Атрибуты",
+                "organize": "Организовать",
+                "download": "Скачать"
+            },
             "autoOrganizeProgress": {
                 "initializing": "Инициализация автоматической организации...",
                 "starting": "Запуск автоматической организации для {type}...",
@@ -698,6 +743,7 @@
             "setContentRating": "Установить рейтинг контента",
             "moveToFolder": "Переместить в папку",
             "repairMetadata": "Восстановить метаданные",
+            "reimportMetadata": "Переимпортировать из источника",
             "excludeModel": "Исключить модель",
             "restoreModel": "Восстановить модель",
             "deleteModel": "Удалить модель",
@@ -785,8 +831,6 @@
             },
             "refresh": {
                 "title": "Обновить список рецептов",
-                "quick": "Синхронизировать изменения",
-                "quickTooltip": "Синхронизировать изменения - быстрое обновление без перестроения кэша",
                 "full": "Перестроить кэш",
                 "fullTooltip": "Перестроить кэш - полное повторное сканирование всех файлов рецептов"
             },
@@ -827,6 +871,13 @@
                 "skipped": "Рецепт уже последней версии, восстановление не требуется",
                 "failed": "Не удалось восстановить рецепт: {message}",
                 "missingId": "Не удалось восстановить рецепт: отсутствует ID рецепта"
+            },
+            "reimport": {
+                "starting": "Переимпорт рецепта из источника...",
+                "success": "Рецепт успешно переимпортирован",
+                "noSourceUrl": "У рецепта нет URL источника, переимпорт невозможен",
+                "failed": "Не удалось переимпортировать рецепт: {message}",
+                "missingId": "Невозможно переимпортировать рецепт: отсутствует ID"
             }
         },
         "batchImport": {
@@ -904,9 +955,13 @@
     },
     "sidebar": {
         "modelRoot": "Корень",
+        "moreOptions": "Дополнительные параметры",
         "collapseAll": "Свернуть все папки",
         "pinSidebar": "Закрепить боковую панель",
         "unpinSidebar": "Открепить боковую панель",
+        "hideOnThisPage": "Скрыть боковую панель на этой странице",
+        "showSidebar": "Показать боковую панель",
+        "sidebarHiddenNotification": "Боковая панель скрыта на странице {page}",
         "switchToListView": "Переключить на вид списка",
         "switchToTreeView": "Переключить на древовидный вид",
         "recursiveOn": "Включать вложенные папки",
@@ -926,6 +981,13 @@
         "empty": {
             "noFolders": "Папки не найдены",
             "dragHint": "Перетащите элементы сюда, чтобы создать папки"
+        },
+        "folderUpdateCheck": {
+            "label": "Проверить обновления в этой папке",
+            "loading": "Проверка обновлений {type} в этой папке...",
+            "success": "Найдено {count} обновление(й) для {type}s в этой папке",
+            "none": "Все {type}s в этой папке актуальны",
+            "error": "Не удалось проверить папку на наличие обновлений {type}: {message}"
         }
     },
     "statistics": {
@@ -970,9 +1032,9 @@
         "download": {
             "title": "Скачать модель по URL",
             "titleWithType": "Скачать {type} по URL",
-            "url": "Civitai URL",
             "civitaiUrl": "Civitai URL:",
             "placeholder": "https://civitai.com/models/...",
+            "urlHint": "Введите один URL CivitAI или CivArchive в каждой строке. Поддерживается пакетная загрузка нескольких URL.",
             "locationPreview": "Предпросмотр места загрузки",
             "useDefaultPath": "Использовать путь по умолчанию",
             "useDefaultPathTooltip": "При включении файлы автоматически организуются с использованием настроенных шаблонов путей",
@@ -994,6 +1056,11 @@
             "downloadedTooltip": "Ранее загружено, но сейчас этого нет в вашей библиотеке.",
             "alreadyInLibrary": "Уже в библиотеке",
             "autoOrganizedPath": "[Автоматически организовано по шаблону пути]",
+            "fileSelection": {
+                "title": "Выбрать формат файла",
+                "files": "файлов",
+                "select": "Выбрать файл"
+            },
             "errors": {
                 "invalidUrl": "Неверный формат URL Civitai",
                 "noVersions": "Нет доступных версий для этой модели"
@@ -1058,6 +1125,12 @@
             "countMessage": "моделей будут удалены навсегда.",
             "action": "Удалить все"
         },
+        "bulkDeleteRecipes": {
+            "title": "Удалить несколько рецептов",
+            "message": "Вы уверены, что хотите удалить все выбранные рецепты и связанные с ними файлы?",
+            "countMessage": "рецептов будут удалены навсегда.",
+            "action": "Удалить все"
+        },
         "checkUpdates": {
             "title": "Проверить обновления для всех {typePlural}?",
             "message": "Будут проверены обновления для всех {typePlural} в вашей библиотеке. Для больших коллекций это может занять немного больше времени.",
@@ -1138,6 +1211,7 @@
                 "editModelName": "Редактировать название модели",
                 "editFileName": "Редактировать имя файла",
                 "editBaseModel": "Редактировать базовую модель",
+                "editVersionName": "Редактировать название версии",
                 "viewOnCivitai": "Посмотреть на Civitai",
                 "viewOnCivitaiText": "Посмотреть на Civitai",
                 "viewCreatorProfile": "Посмотреть профиль создателя",
@@ -1169,7 +1243,9 @@
             },
             "notes": {
                 "saved": "Заметки успешно сохранены",
-                "saveFailed": "Не удалось сохранить заметки"
+                "saveFailed": "Не удалось сохранить заметки",
+                "showMore": "Показать больше",
+                "showLess": "Свернуть"
             },
             "usageTips": {
                 "addPresetParameter": "Добавить предустановленный параметр...",
@@ -1274,12 +1350,15 @@
                     "earlyAccess": "Ранний доступ",
                     "earlyAccessTooltip": "Для этой версии сейчас требуется ранний доступ Civitai",
                     "ignored": "Игнорируется",
-                    "ignoredTooltip": "Уведомления об обновлениях для этой версии отключены"
+                    "ignoredTooltip": "Уведомления об обновлениях для этой версии отключены",
+                    "onSiteOnly": "Только на Сайте",
+                    "onSiteOnlyTooltip": "Эта версия доступна только для генерации на сайте Civitai"
                 },
                 "actions": {
                     "download": "Скачать",
                     "downloadTooltip": "Скачать эту версию",
                     "downloadEarlyAccessTooltip": "Скачать эту версию раннего доступа с Civitai",
+                    "downloadNotAllowedTooltip": "Эта версия доступна только для генерации на сайте Civitai",
                     "delete": "Удалить",
                     "deleteTooltip": "Удалить эту локальную версию",
                     "ignore": "Игнорировать",
@@ -1428,11 +1507,14 @@
             "noMatchingNodes": "В текущем workflow нет совместимых узлов",
             "noTargetNodeSelected": "Целевой узел не выбран",
             "modelUpdated": "Модель обновлена в workflow",
-            "modelFailed": "Не удалось обновить узел модели"
+            "modelFailed": "Не удалось обновить узел модели",
+            "embeddingAdded": "Embedding добавлен в workflow",
+            "embeddingFailed": "Не удалось добавить embedding"
         },
         "nodeSelector": {
             "recipe": "Рецепт",
             "lora": "LoRA",
+            "embedding": "Эмбеддинг",
             "replace": "Заменить",
             "append": "Добавить",
             "selectTargetNode": "Выберите целевой узел",
@@ -1442,6 +1524,10 @@
             "opened": "Папка с примерами изображений открыта",
             "openingFolder": "Открытие папки с примерами изображений",
             "failedToOpen": "Не удалось открыть папку с примерами изображений",
+            "copiedPath": "Путь скопирован в буфер обмена: {{path}}",
+            "clipboardFallback": "Путь: {{path}}",
+            "copiedUri": "Ссылка скопирована в буфер обмена: {{uri}}",
+            "uriClipboardFallback": "Ссылка: {{uri}}",
             "setupRequired": "Хранилище примеров изображений",
             "setupDescription": "Чтобы добавить собственные примеры изображений, сначала нужно установить место загрузки.",
             "setupUsage": "Этот путь используется как для загруженных, так и для пользовательских примеров изображений.",
@@ -1605,6 +1691,10 @@
             "noRecipeId": "ID рецепта недоступен",
             "sendToWorkflowFailed": "Не удалось отправить рецепт в рабочий процесс: {message}",
             "copyFailed": "Ошибка копирования синтаксиса рецепта: {message}",
+            "createError": "Ошибка при создании рецепта：{message}",
+            "createFailed": "Не удалось создать рецепт：{error}",
+            "createMissingData": "Отсутствуют необходимые данные для создания рецепта",
+            "created": "Рецепт успешно создан",
             "noMissingLoras": "Нет отсутствующих LoRAs для загрузки",
             "missingLorasInfoFailed": "Не удалось получить информацию для отсутствующих LoRAs",
             "preparingForDownloadFailed": "Ошибка подготовки LoRAs для загрузки",
@@ -1643,6 +1733,13 @@
             "batchImportBrowseFailed": "Failed to browse directory: {message}",
             "batchImportDirectorySelected": "Directory selected: {path}",
             "noRecipesSelected": "Рецепты не выбраны",
+            "repairBulkComplete": "Восстановление завершено: {repaired} восстановлено, {skipped} пропущено (из {total})",
+            "repairBulkSkipped": "Ни один из {total} выбранных рецептов не требует восстановления",
+            "repairBulkFailed": "Не удалось восстановить выбранные рецепты: {message}",
+            "reimporting": "Переимпорт рецепта из источника...",
+            "reimportSuccess": "Рецепт успешно переимпортирован",
+            "reimportBulkComplete": "Переимпорт завершён: {completed} переимпортировано, {failed} ошибок (из {total})",
+            "reimportBulkFailed": "Не удалось переимпортировать некоторые рецепты",
             "noMissingLorasInSelection": "В выбранных рецептах не найдены отсутствующие LoRAs",
             "noLoraRootConfigured": "Корневой каталог LoRA не настроен. Пожалуйста, установите корневой каталог LoRA по умолчанию в настройках."
         },
@@ -1673,6 +1770,11 @@
             "bulkContentRatingSet": "Рейтинг контента установлен на {level} для {count} модель(ей)",
             "bulkContentRatingPartial": "Рейтинг контента {level} установлен для {success} модель(ей), {failed} не удалось",
             "bulkContentRatingFailed": "Не удалось обновить рейтинг контента для выбранных моделей",
+            "bulkFavoriteUpdating": "Добавление {count} моделей в избранное...",
+            "bulkUnfavoriteUpdating": "Удаление {count} моделей из избранного...",
+            "bulkFavoritePartialAdded": "{success} моделей добавлено в избранное, {failed} не удалось",
+            "bulkFavoritePartialRemoved": "{success} моделей удалено из избранного, {failed} не удалось",
+            "bulkFavoriteFailed": "Не удалось обновить статус избранного",
             "bulkUpdatesChecking": "Проверка обновлений для выбранных {type}...",
             "bulkUpdatesSuccess": "Доступны обновления для {count} выбранных {type}",
             "bulkUpdatesNone": "Обновления для выбранных {type} не найдены",
@@ -1875,18 +1977,52 @@
             "warning": "Требует внимания",
             "error": "Требуется действие"
         },
+        "issues": {
+            "civitai_api_key": {
+                "title": "Civitai API Key"
+            },
+            "cache_health": {
+                "title": "Model Cache Health"
+            },
+            "filename_conflicts": {
+                "title": "Duplicate Filename Conflicts"
+            },
+            "ui_version": {
+                "title": "UI Version"
+            }
+        },
         "actions": {
             "runAgain": "Запустить снова",
-            "exportBundle": "Экспортировать пакет"
+            "exportBundle": "Экспортировать пакет",
+            "open-settings": "Open Settings",
+            "open-settings-syntax-format": "Switch to Full Path Syntax",
+            "repair-cache": "Rebuild Cache",
+            "resolve-filename-conflicts": "Resolve Conflicts",
+            "reload-page": "Reload UI"
+        },
+        "labels": {
+            "conflicts": "Conflicts",
+            "version": "Version"
         },
         "toast": {
             "loadFailed": "Не удалось загрузить диагностику: {message}",
             "repairSuccess": "Перестройка кэша завершена.",
             "repairFailed": "Не удалось перестроить кэш: {message}",
             "exportSuccess": "Диагностический пакет экспортирован.",
-            "exportFailed": "Не удалось экспортировать диагностический пакет: {message}"
+            "exportFailed": "Не удалось экспортировать диагностический пакет: {message}",
+            "conflictsResolved": "Разрешено конфликтов имён файлов: {count}.",
+            "conflictsResolveFailed": "Не удалось разрешить конфликты имён файлов: {message}"
         }
     },
+    "conflictConfirm": {
+        "title": "Разрешить конфликты имён файлов",
+        "message": "Переименование с добавлением 4-символьного хеша к каждому дублирующемуся имени файла.",
+        "note": "Эта операция переименовывает файлы на диске. Если вы используете синтаксис A1111, ссылки на модели в существующих рабочих процессах могут потребовать обновления.",
+        "detail": "Пример: <code>filename_v1.2</code> → <code>filename_v1.2-ab3c</code>",
+        "impact": "Будет переименовано <strong>{count}</strong> файл(ов) в <strong>{groups}</strong> группе(ах) дубликатов",
+        "confirm": "Переименовать файлы",
+        "cancel": "Отмена"
+    },
     "banners": {
         "versionMismatch": {
             "title": "Обнаружено обновление приложения",

locales/zh-CN.json

@@ -15,7 +15,10 @@
             "settings": "设置",
             "help": "帮助",
             "add": "添加",
-            "close": "关闭"
+            "close": "关闭",
+            "menu": "菜单",
+            "remove": "移除",
+            "change": "更换"
         },
         "status": {
             "loading": "加载中...",
@@ -110,6 +113,7 @@
             "replacePreview": "替换预览",
             "copyCheckpointName": "复制 Checkpoint 名称",
             "copyEmbeddingName": "复制 Embedding 名称",
+            "embeddingNameCopied": "已复制 Embedding 语法",
             "sendCheckpointToWorkflow": "发送到 ComfyUI",
             "sendEmbeddingToWorkflow": "发送到 ComfyUI"
         },
@@ -231,7 +235,10 @@
             "license": "许可证",
             "noCreditRequired": "无需署名",
             "allowSellingGeneratedContent": "允许销售",
+            "allowSellingGeneratedContentTooltip": "允许出售生成的图片",
+            "noCreditRequiredTooltip": "使用模型时无需注明原作者",
             "noTags": "无标签",
+            "autoTags": "自动标签",
             "noBaseModelMatches": "没有基础模型符合当前搜索。",
             "clearAll": "清除所有筛选",
             "any": "任一",
@@ -265,10 +272,10 @@
         },
         "downloadBackend": {
             "label": "下载后端",
-            "help": "选择模型文件的下载方式。Python 使用内置下载器。aria2 使用实验性的外部下载进程。",
+            "help": "选择模型文件的下载方式。Python 使用内置下载器。aria2 使用推荐的外部下载进程。",
             "options": {
                 "python": "Python（内置）",
-                "aria2": "aria2（实验性）"
+                "aria2": "aria2（推荐）"
             }
         },
         "aria2cPath": {
@@ -276,6 +283,7 @@
             "help": "可选的 aria2c 可执行文件路径。留空则使用系统 PATH 中的 aria2c。",
             "placeholder": "留空则使用 PATH 中的 aria2c"
         },
+        "aria2HelpLink": "了解如何配置 aria2 下载后端",
         "civitaiHostBanner": {
             "title": "已提供 Civitai 站点偏好设置",
             "content": "Civitai 现在使用 civitai.com 提供 SFW 内容，使用 civitai.red 提供无限制内容。你可以在设置中更改默认打开的站点。",
@@ -427,6 +435,8 @@
                 "hover": "悬停时显示"
             },
             "cardInfoDisplayHelp": "选择何时显示模型信息和操作按钮",
+            "showVersionOnCard": "在卡片上显示版本",
+            "showVersionOnCardHelp": "在模型卡片上显示或隐藏版本名称",
             "modelCardFooterAction": "模型卡片按钮操作",
             "modelCardFooterActionOptions": {
                 "exampleImages": "打开示例图片",
@@ -438,7 +448,9 @@
                 "modelName": "模型名称",
                 "fileName": "文件名"
             },
-            "modelNameDisplayHelp": "选择在模型卡片底部显示的内容"
+            "modelNameDisplayHelp": "选择在模型卡片底部显示的内容",
+            "cardBlurAmount": "卡片叠加模糊强度",
+            "cardBlurAmountHelp": "调整模型和配方卡片上页眉和页脚叠加层的模糊强度（0 = 无模糊，20 = 最大模糊）。"
         },
         "folderSettings": {
             "activeLibrary": "活动库",
@@ -538,6 +550,21 @@
             "downloadLocationHelp": "输入保存从 Civitai 下载的示例图片的文件夹路径",
             "autoDownload": "自动下载示例图片",
             "autoDownloadHelp": "自动为没有示例图片的模型下载示例图片（需设置下载位置）",
+            "openMode": "打开示例图片操作",
+            "openModeHelp": "选择是在服务器上打开、复制映射后的本地路径，还是启动自定义 URI。",
+            "openModeOptions": {
+                "system": "在服务器上打开",
+                "clipboard": "复制本地路径",
+                "uriTemplate": "打开自定义 URI"
+            },
+            "localRoot": "本地示例图片根目录",
+            "localRootHelp": "可选的本地或挂载根目录，用于映射服务器上的示例图片目录。若留空，则复用服务器路径。",
+            "localRootPlaceholder": "例如：/Volumes/ComfyUI/example_images",
+            "uriTemplate": "打开 URI 模板",
+            "uriTemplateHelp": "使用自定义深链接，例如文件 URI 或 Shortcuts 链接。",
+            "uriTemplatePlaceholder": "例如：shortcuts://run-shortcut?name=Open%20Finder&input=text&text={{encoded_local_path}}",
+            "uriTemplatePlaceholders": "可用占位符：{{local_path}}、{{encoded_local_path}}、{{relative_path}}、{{encoded_relative_path}}、{{file_uri}}、{{encoded_file_uri}}",
+            "openModeWikiLink": "了解远程打开模式",
             "optimizeImages": "优化下载图片",
             "optimizeImagesHelp": "优化示例图片以减少文件大小并提升加载速度（保留元数据）",
             "download": "下载",
@@ -557,7 +584,13 @@
         },
         "misc": {
             "includeTriggerWords": "复制 LoRA 语法时包含触发词",
-            "includeTriggerWordsHelp": "复制 LoRA 语法到剪贴板时包含训练触发词"
+            "includeTriggerWordsHelp": "复制 LoRA 语法到剪贴板时包含训练触发词",
+            "loraSyntaxFormat": "LoRA 语法格式",
+            "loraSyntaxFormatHelp": "LoRA 语法格式。完整路径（Full）包含子文件夹路径 (<lora:style/anime/x:1.0>)，解析精确无歧义。旧版（Legacy）仅使用文件名 (<lora:x:1.0>)——A1111 原始约定，同名文件跨文件夹时可能产生歧义。",
+            "loraSyntaxFormatOptions": {
+                "full": "完整路径（子文件夹/名称）",
+                "legacy": "旧版 A1111（仅名称）"
+            }
         },
         "metadataArchive": {
             "enableArchiveDb": "启用元数据归档数据库",
@@ -621,8 +654,6 @@
             },
             "refresh": {
                 "title": "刷新模型列表",
-                "quick": "同步变更",
-                "quickTooltip": "扫描新的或缺失的模型文件，保持列表最新。",
                 "full": "重建缓存",
                 "fullTooltip": "从元数据文件重新加载所有模型信息；用于列表过时或手动编辑后。"
             },
@@ -663,16 +694,30 @@
             "setContentRating": "为所选中设置内容评级",
             "copyAll": "复制所选中语法",
             "refreshAll": "刷新所选中元数据",
+            "repairMetadata": "修复所选中元数据",
+            "reimportMetadata": "从源重新导入",
             "checkUpdates": "检查所选更新",
             "moveAll": "移动所选中到文件夹",
             "autoOrganize": "自动整理所选模型",
             "skipMetadataRefresh": "跳过所选模型的元数据刷新",
             "resumeMetadataRefresh": "恢复所选模型的元数据刷新",
-            "deleteAll": "删除选中模型",
+            "setFavorite": "设为收藏",
+            "setFavoriteCount": "设为收藏 ({favorited}/{total})",
+            "unfavorite": "取消收藏",
+            "deleteAll": "删除已选",
             "downloadMissingLoras": "下载缺失的 LoRAs",
+            "downloadExamples": "下载示例图片",
             "clear": "清除选择",
             "skipMetadataRefreshCount": "跳过（{count} 个模型）",
             "resumeMetadataRefreshCount": "恢复（{count} 个模型）",
+            "sendToWorkflow": "发送到工作流",
+            "sections": {
+                "workflow": "工作流",
+                "metadata": "元数据",
+                "attributes": "属性",
+                "organize": "整理",
+                "download": "下载"
+            },
             "autoOrganizeProgress": {
                 "initializing": "正在初始化自动整理...",
                 "starting": "正在为 {type} 启动自动整理...",
@@ -698,6 +743,7 @@
             "setContentRating": "设置内容评级",
             "moveToFolder": "移动到文件夹",
             "repairMetadata": "修复元数据",
+            "reimportMetadata": "从源重新导入",
             "excludeModel": "排除模型",
             "restoreModel": "恢复模型",
             "deleteModel": "删除模型",
@@ -785,8 +831,6 @@
             },
             "refresh": {
                 "title": "刷新配方列表",
-                "quick": "同步变更",
-                "quickTooltip": "同步变更 - 快速刷新而不重建缓存",
                 "full": "重建缓存",
                 "fullTooltip": "重建缓存 - 重新扫描所有配方文件"
             },
@@ -827,6 +871,13 @@
                 "skipped": "配方已是最新版本，无需修复",
                 "failed": "修复配方失败：{message}",
                 "missingId": "无法修复配方：缺少配方 ID"
+            },
+            "reimport": {
+                "starting": "正在从源重新导入配方...",
+                "success": "配方已从源重新导入成功",
+                "noSourceUrl": "配方没有源URL，无法重新导入",
+                "failed": "重新导入配方失败：{message}",
+                "missingId": "无法重新导入配方：缺少配方ID"
             }
         },
         "batchImport": {
@@ -904,9 +955,13 @@
     },
     "sidebar": {
         "modelRoot": "根目录",
+        "moreOptions": "更多选项",
         "collapseAll": "折叠所有文件夹",
         "pinSidebar": "固定侧边栏",
         "unpinSidebar": "取消固定侧边栏",
+        "hideOnThisPage": "隐藏此页面侧边栏",
+        "showSidebar": "显示侧边栏",
+        "sidebarHiddenNotification": "{page}页面的文件夹侧边栏已隐藏",
         "switchToListView": "切换到列表视图",
         "switchToTreeView": "切换到树状视图",
         "recursiveOn": "包含子文件夹",
@@ -926,6 +981,13 @@
         "empty": {
             "noFolders": "未找到文件夹",
             "dragHint": "拖拽项目到此处以创建文件夹"
+        },
+        "folderUpdateCheck": {
+            "label": "检查此文件夹的更新",
+            "loading": "正在检查此文件夹中的{type}更新...",
+            "success": "在此文件夹中找到 {count} 个{type}更新",
+            "none": "此文件夹中的所有{type}都是最新版本",
+            "error": "检查文件夹{type}更新失败: {message}"
         }
     },
     "statistics": {
@@ -970,9 +1032,9 @@
         "download": {
             "title": "从 URL 下载模型",
             "titleWithType": "从 URL 下载 {type}",
-            "url": "Civitai URL",
             "civitaiUrl": "Civitai URL:",
             "placeholder": "https://civitai.com/models/...",
+            "urlHint": "每行输入一个 CivitAI 或 CivArchive URL。支持批量下载多个 URL。",
             "locationPreview": "下载位置预览",
             "useDefaultPath": "使用默认路径",
             "useDefaultPathTooltip": "启用后，文件将自动按配置的路径模板进行整理",
@@ -994,6 +1056,11 @@
             "downloadedTooltip": "之前已下载，但当前不在你的库中。",
             "alreadyInLibrary": "已存在于库中",
             "autoOrganizedPath": "【已按路径模板自动整理】",
+            "fileSelection": {
+                "title": "选择文件格式",
+                "files": "个文件",
+                "select": "选择文件"
+            },
             "errors": {
                 "invalidUrl": "无效的 Civitai URL 格式",
                 "noVersions": "此模型没有可用版本"
@@ -1058,6 +1125,12 @@
             "countMessage": "模型将被永久删除。",
             "action": "全部删除"
         },
+        "bulkDeleteRecipes": {
+            "title": "删除多个配方",
+            "message": "你确定要删除所有选中的配方及其相关文件吗？",
+            "countMessage": "配方将被永久删除。",
+            "action": "全部删除"
+        },
         "checkUpdates": {
             "title": "检查所有 {type} 的更新？",
             "message": "这会为库中的每个 {type} 检查更新，大型集合可能需要一些时间。",
@@ -1138,6 +1211,7 @@
                 "editModelName": "编辑模型名称",
                 "editFileName": "编辑文件名",
                 "editBaseModel": "编辑基础模型",
+                "editVersionName": "编辑版本名称",
                 "viewOnCivitai": "在 Civitai 查看",
                 "viewOnCivitaiText": "在 Civitai 查看",
                 "viewCreatorProfile": "查看创作者主页",
@@ -1169,7 +1243,9 @@
             },
             "notes": {
                 "saved": "备注保存成功",
-                "saveFailed": "备注保存失败"
+                "saveFailed": "备注保存失败",
+                "showMore": "展开",
+                "showLess": "收起"
             },
             "usageTips": {
                 "addPresetParameter": "添加预设参数...",
@@ -1274,12 +1350,15 @@
                     "earlyAccess": "抢先体验",
                     "earlyAccessTooltip": "此版本当前需要 Civitai 抢先体验权限",
                     "ignored": "已忽略",
-                    "ignoredTooltip": "此版本已关闭更新通知"
+                    "ignoredTooltip": "此版本已关闭更新通知",
+                    "onSiteOnly": "仅站内生成",
+                    "onSiteOnlyTooltip": "此版本仅在 Civitai 站内可用，无法下载"
                 },
                 "actions": {
                     "download": "下载",
                     "downloadTooltip": "下载此版本",
                     "downloadEarlyAccessTooltip": "从 Civitai 下载此抢先体验版本",
+                    "downloadNotAllowedTooltip": "此版本仅在 Civitai 站内可用，无法下载",
                     "delete": "删除",
                     "deleteTooltip": "删除此本地版本",
                     "ignore": "忽略",
@@ -1428,11 +1507,14 @@
             "noMatchingNodes": "当前工作流中没有兼容的节点",
             "noTargetNodeSelected": "未选择目标节点",
             "modelUpdated": "模型已更新到工作流",
-            "modelFailed": "更新模型节点失败"
+            "modelFailed": "更新模型节点失败",
+            "embeddingAdded": "Embedding 已追加到工作流",
+            "embeddingFailed": "添加 Embedding 失败"
         },
         "nodeSelector": {
             "recipe": "配方",
             "lora": "LoRA",
+            "embedding": "Embedding",
             "replace": "替换",
             "append": "追加",
             "selectTargetNode": "选择目标节点",
@@ -1442,6 +1524,10 @@
             "opened": "示例图片文件夹已打开",
             "openingFolder": "正在打开示例图片文件夹",
             "failedToOpen": "打开示例图片文件夹失败",
+            "copiedPath": "路径已复制到剪贴板：{{path}}",
+            "clipboardFallback": "路径：{{path}}",
+            "copiedUri": "链接已复制到剪贴板：{{uri}}",
+            "uriClipboardFallback": "链接：{{uri}}",
             "setupRequired": "示例图片存储",
             "setupDescription": "要添加自定义示例图片，您需要先设置下载位置。",
             "setupUsage": "此路径用于存储下载的示例图片和自定义图片。",
@@ -1605,6 +1691,10 @@
             "noRecipeId": "无配方 ID",
             "sendToWorkflowFailed": "发送配方到工作流失败：{message}",
             "copyFailed": "复制配方语法出错：{message}",
+            "createError": "创建配方时出错：{message}",
+            "createFailed": "创建配方失败：{error}",
+            "createMissingData": "缺少创建配方所需的数据",
+            "created": "配方创建成功",
             "noMissingLoras": "没有缺失的 LoRA 可下载",
             "missingLorasInfoFailed": "获取缺失 LoRA 信息失败",
             "preparingForDownloadFailed": "准备下载 LoRA 时出错",
@@ -1643,6 +1733,13 @@
             "batchImportBrowseFailed": "浏览目录失败：{message}",
             "batchImportDirectorySelected": "已选择目录：{path}",
             "noRecipesSelected": "未选择任何配方",
+            "repairBulkComplete": "修复完成：{repaired} 个已修复，{skipped} 个已跳过（共 {total} 个）",
+            "repairBulkSkipped": "所选 {total} 个配方无需修复",
+            "repairBulkFailed": "修复所选配方失败：{message}",
+            "reimporting": "正在从源重新导入配方...",
+            "reimportSuccess": "配方已从源重新导入成功",
+            "reimportBulkComplete": "重新导入完成：{completed} 个已导入，{failed} 个失败（共 {total} 个）",
+            "reimportBulkFailed": "重新导入某些配方失败",
             "noMissingLorasInSelection": "在选定的配方中未找到缺失的 LoRAs",
             "noLoraRootConfigured": "未配置 LoRA 根目录。请在设置中设置默认的 LoRA 根目录。"
         },
@@ -1673,6 +1770,11 @@
             "bulkContentRatingSet": "已将 {count} 个模型的内容评级设置为 {level}",
             "bulkContentRatingPartial": "已将 {success} 个模型的内容评级设置为 {level}，{failed} 个失败",
             "bulkContentRatingFailed": "未能更新所选模型的内容评级",
+            "bulkFavoriteUpdating": "正在将 {count} 个模型添加到收藏...",
+            "bulkUnfavoriteUpdating": "正在将 {count} 个模型从收藏移除...",
+            "bulkFavoritePartialAdded": "已将 {success} 个模型添加到收藏，{failed} 个失败",
+            "bulkFavoritePartialRemoved": "已将 {success} 个模型从收藏移除，{failed} 个失败",
+            "bulkFavoriteFailed": "更新收藏状态失败",
             "bulkUpdatesChecking": "正在检查所选 {type} 的更新...",
             "bulkUpdatesSuccess": "{count} 个所选 {type} 有可用更新",
             "bulkUpdatesNone": "所选 {type} 未发现更新",
@@ -1875,18 +1977,52 @@
             "warning": "需要关注",
             "error": "需要处理"
         },
+        "issues": {
+            "civitai_api_key": {
+                "title": "Civitai API 密钥"
+            },
+            "cache_health": {
+                "title": "模型缓存健康状态"
+            },
+            "filename_conflicts": {
+                "title": "文件名重复冲突"
+            },
+            "ui_version": {
+                "title": "UI 版本"
+            }
+        },
         "actions": {
             "runAgain": "重新检查",
-            "exportBundle": "导出诊断包"
+            "exportBundle": "导出诊断包",
+            "open-settings": "打开设置",
+            "open-settings-syntax-format": "切换为完整路径语法",
+            "repair-cache": "重建缓存",
+            "resolve-filename-conflicts": "解决冲突",
+            "reload-page": "刷新 UI"
+        },
+        "labels": {
+            "conflicts": "冲突详情",
+            "version": "版本信息"
         },
         "toast": {
             "loadFailed": "加载诊断结果失败：{message}",
             "repairSuccess": "缓存重建完成。",
             "repairFailed": "缓存重建失败：{message}",
             "exportSuccess": "诊断包已导出。",
-            "exportFailed": "导出诊断包失败：{message}"
+            "exportFailed": "导出诊断包失败：{message}",
+            "conflictsResolved": "已解决 {count} 个文件名冲突。",
+            "conflictsResolveFailed": "解决文件名冲突失败：{message}"
         }
     },
+    "conflictConfirm": {
+        "title": "解决文件名冲突",
+        "message": "通过在每个重复文件名后附加 4 位哈希值来重命名文件。",
+        "note": "此操作会重命名磁盘上的文件。如果使用 A1111 语法格式，现有工作流中的模型引用可能需要更新。",
+        "detail": "示例：<code>filename_v1.2</code> → <code>filename_v1.2-ab3c</code>",
+        "impact": "将重命名 <strong>{count}</strong> 个文件（共 <strong>{groups}</strong> 组重复）",
+        "confirm": "重命名文件",
+        "cancel": "取消"
+    },
     "banners": {
         "versionMismatch": {
             "title": "检测到应用更新",

locales/zh-TW.json

@@ -15,7 +15,10 @@
             "settings": "設定",
             "help": "說明",
             "add": "新增",
-            "close": "關閉"
+            "close": "關閉",
+            "menu": "選單",
+            "remove": "移除",
+            "change": "更換"
         },
         "status": {
             "loading": "載入中...",
@@ -110,6 +113,7 @@
             "replacePreview": "更換預覽圖",
             "copyCheckpointName": "複製檢查點名稱",
             "copyEmbeddingName": "複製嵌入名稱",
+            "embeddingNameCopied": "已複製 Embedding 語法",
             "sendCheckpointToWorkflow": "傳送到 ComfyUI",
             "sendEmbeddingToWorkflow": "傳送到 ComfyUI"
         },
@@ -231,7 +235,10 @@
             "license": "授權",
             "noCreditRequired": "無需署名",
             "allowSellingGeneratedContent": "允許銷售",
+            "allowSellingGeneratedContentTooltip": "允許出售生成的圖片",
+            "noCreditRequiredTooltip": "使用模型時無需註明原作者",
             "noTags": "無標籤",
+            "autoTags": "自動標籤",
             "noBaseModelMatches": "沒有基礎模型符合目前的搜尋。",
             "clearAll": "清除所有篩選",
             "any": "任一",
@@ -265,10 +272,10 @@
         },
         "downloadBackend": {
             "label": "下載後端",
-            "help": "選擇模型檔案的下載方式。Python 使用內建下載器。aria2 使用實驗性的外部下載程序。",
+            "help": "選擇模型檔案的下載方式。Python 使用內建下載器。aria2 使用推薦的外部下載程序。",
             "options": {
                 "python": "Python（內建）",
-                "aria2": "aria2（實驗性）"
+                "aria2": "aria2（推薦）"
             }
         },
         "aria2cPath": {
@@ -276,6 +283,7 @@
             "help": "可選的 aria2c 可執行檔路徑。留空則使用系統 PATH 中的 aria2c。",
             "placeholder": "留空則使用 PATH 中的 aria2c"
         },
+        "aria2HelpLink": "了解如何設定 aria2 下載後端",
         "civitaiHostBanner": {
             "title": "已提供 Civitai 站點偏好設定",
             "content": "Civitai 現在使用 civitai.com 提供 SFW 內容，使用 civitai.red 提供無限制內容。你可以在設定中變更預設開啟的站點。",
@@ -427,6 +435,8 @@
                 "hover": "滑鼠懸停顯示"
             },
             "cardInfoDisplayHelp": "選擇何時顯示模型資訊與操作按鈕",
+            "showVersionOnCard": "在卡片上顯示版本",
+            "showVersionOnCardHelp": "在模型卡片上顯示或隱藏版本名稱",
             "modelCardFooterAction": "模型卡片按鈕操作",
             "modelCardFooterActionOptions": {
                 "exampleImages": "開啟範例圖片",
@@ -438,7 +448,9 @@
                 "modelName": "模型名稱",
                 "fileName": "檔案名稱"
             },
-            "modelNameDisplayHelp": "選擇在模型卡片底部顯示的內容"
+            "modelNameDisplayHelp": "選擇在模型卡片底部顯示的內容",
+            "cardBlurAmount": "卡片疊加模糊強度",
+            "cardBlurAmountHelp": "調整模型和配方卡片上頁首和頁尾疊加層的模糊強度（0 = 無模糊，20 = 最大模糊）。"
         },
         "folderSettings": {
             "activeLibrary": "使用中的資料庫",
@@ -538,6 +550,21 @@
             "downloadLocationHelp": "輸入從 Civitai 下載範例圖片要儲存的資料夾路徑",
             "autoDownload": "自動下載範例圖片",
             "autoDownloadHelp": "自動為沒有範例圖片的模型下載範例圖片（需設定下載位置）",
+            "openMode": "開啟範例圖片動作",
+            "openModeHelp": "選擇是在伺服器上開啟、複製對應的本機路徑，或啟動自訂 URI。",
+            "openModeOptions": {
+                "system": "在伺服器上開啟",
+                "clipboard": "複製本機路徑",
+                "uriTemplate": "開啟自訂 URI"
+            },
+            "localRoot": "本機範例圖片根目錄",
+            "localRootHelp": "可選的本機或掛載根目錄，用於對應伺服器上的範例圖片目錄。若留白，則會重用伺服器路徑。",
+            "localRootPlaceholder": "例如：/Volumes/ComfyUI/example_images",
+            "uriTemplate": "開啟 URI 範本",
+            "uriTemplateHelp": "使用自訂深層連結，例如檔案 URI 或 Shortcuts 連結。",
+            "uriTemplatePlaceholder": "例如：shortcuts://run-shortcut?name=Open%20Finder&input=text&text={{encoded_local_path}}",
+            "uriTemplatePlaceholders": "可用佔位符：{{local_path}}、{{encoded_local_path}}、{{relative_path}}、{{encoded_relative_path}}、{{file_uri}}、{{encoded_file_uri}}",
+            "openModeWikiLink": "了解遠端開啟模式",
             "optimizeImages": "最佳化下載圖片",
             "optimizeImagesHelp": "最佳化範例圖片以減少檔案大小並提升載入速度（會保留原有的 metadata）",
             "download": "下載",
@@ -557,7 +584,13 @@
         },
         "misc": {
             "includeTriggerWords": "在 LoRA 語法中包含觸發詞",
-            "includeTriggerWordsHelp": "複製 LoRA 語法到剪貼簿時包含訓練觸發詞"
+            "includeTriggerWordsHelp": "複製 LoRA 語法到剪貼簿時包含訓練觸發詞",
+            "loraSyntaxFormat": "LoRA 語法格式",
+            "loraSyntaxFormatHelp": "LoRA 語法格式。完整路徑（Full）包含子資料夾路徑 (<lora:style/anime/x:1.0>)，解析精確無歧義。舊版（Legacy）僅使用檔名 (<lora:x:1.0>)——A1111 原始約定，同名檔案跨資料夾時可能產生歧義。",
+            "loraSyntaxFormatOptions": {
+                "full": "完整路徑（子資料夾/名稱）",
+                "legacy": "舊版 A1111（僅名稱）"
+            }
         },
         "metadataArchive": {
             "enableArchiveDb": "啟用中繼資料封存資料庫",
@@ -621,8 +654,6 @@
             },
             "refresh": {
                 "title": "重新整理模型列表",
-                "quick": "同步變更",
-                "quickTooltip": "掃描新的或缺少的模型檔案，讓清單保持最新。",
                 "full": "重建快取",
                 "fullTooltip": "從中繼資料檔重新載入所有模型資訊；適用於清單過時或手動編輯後。"
             },
@@ -663,16 +694,30 @@
             "setContentRating": "為全部設定內容分級",
             "copyAll": "複製全部語法",
             "refreshAll": "刷新全部 metadata",
+            "repairMetadata": "修復所選中元數據",
+            "reimportMetadata": "從來源重新匯入",
             "checkUpdates": "檢查所選更新",
             "moveAll": "全部移動到資料夾",
             "autoOrganize": "自動整理所選模型",
             "skipMetadataRefresh": "跳過所選模型的元數據更新",
             "resumeMetadataRefresh": "恢復所選模型的元數據更新",
-            "deleteAll": "刪除全部模型",
+            "setFavorite": "設為收藏",
+            "setFavoriteCount": "設為收藏 ({favorited}/{total})",
+            "unfavorite": "取消收藏",
+            "deleteAll": "刪除所選",
             "downloadMissingLoras": "下載缺失的 LoRAs",
+            "downloadExamples": "下載範例圖片",
             "clear": "清除選取",
             "skipMetadataRefreshCount": "跳過（{count} 個模型）",
             "resumeMetadataRefreshCount": "恢復（{count} 個模型）",
+            "sendToWorkflow": "發送到工作流",
+            "sections": {
+                "workflow": "工作流",
+                "metadata": "元數據",
+                "attributes": "屬性",
+                "organize": "整理",
+                "download": "下載"
+            },
             "autoOrganizeProgress": {
                 "initializing": "正在初始化自動整理...",
                 "starting": "正在開始自動整理 {type}...",
@@ -698,6 +743,7 @@
             "setContentRating": "設定內容分級",
             "moveToFolder": "移動到資料夾",
             "repairMetadata": "修復元數據",
+            "reimportMetadata": "從來源重新匯入",
             "excludeModel": "排除模型",
             "restoreModel": "還原模型",
             "deleteModel": "刪除模型",
@@ -785,8 +831,6 @@
             },
             "refresh": {
                 "title": "重新整理配方列表",
-                "quick": "同步變更",
-                "quickTooltip": "同步變更 - 快速重新整理而不重建快取",
                 "full": "重建快取",
                 "fullTooltip": "重建快取 - 重新掃描所有配方檔案"
             },
@@ -827,6 +871,13 @@
                 "skipped": "配方已是最新版本，無需修復",
                 "failed": "修復配方失敗：{message}",
                 "missingId": "無法修復配方：缺少配方 ID"
+            },
+            "reimport": {
+                "starting": "正在從來源重新匯入配方...",
+                "success": "配方已從來源重新匯入成功",
+                "noSourceUrl": "配方沒有來源URL，無法重新匯入",
+                "failed": "重新匯入配方失敗：{message}",
+                "missingId": "無法重新匯入配方：缺少配方ID"
             }
         },
         "batchImport": {
@@ -904,9 +955,13 @@
     },
     "sidebar": {
         "modelRoot": "根目錄",
+        "moreOptions": "更多選項",
         "collapseAll": "全部摺疊資料夾",
         "pinSidebar": "固定側邊欄",
         "unpinSidebar": "取消固定側邊欄",
+        "hideOnThisPage": "隱藏此頁面側邊欄",
+        "showSidebar": "顯示側邊欄",
+        "sidebarHiddenNotification": "{page}頁面的資料夾側邊欄已隱藏",
         "switchToListView": "切換至列表檢視",
         "switchToTreeView": "切換到樹狀檢視",
         "recursiveOn": "包含子資料夾",
@@ -926,6 +981,13 @@
         "empty": {
             "noFolders": "未找到資料夾",
             "dragHint": "將項目拖到此處以建立資料夾"
+        },
+        "folderUpdateCheck": {
+            "label": "檢查此資料夾的更新",
+            "loading": "正在檢查此資料夾中的{type}更新...",
+            "success": "在此資料夾中找到 {count} 個{type}更新",
+            "none": "此資料夾中的所有{type}都是最新版本",
+            "error": "檢查資料夾{type}更新失敗: {message}"
         }
     },
     "statistics": {
@@ -970,9 +1032,9 @@
         "download": {
             "title": "從網址下載模型",
             "titleWithType": "從網址下載 {type}",
-            "url": "Civitai 網址",
             "civitaiUrl": "Civitai 網址：",
             "placeholder": "https://civitai.com/models/...",
+            "urlHint": "每行輸入一個 CivitAI 或 CivArchive URL。支援批量下載多個 URL。",
             "locationPreview": "下載位置預覽",
             "useDefaultPath": "使用預設路徑",
             "useDefaultPathTooltip": "啟用後，檔案將依照設定的路徑範本自動整理",
@@ -994,6 +1056,11 @@
             "downloadedTooltip": "先前已下載，但目前不在你的庫中。",
             "alreadyInLibrary": "已在庫存",
             "autoOrganizedPath": "[依路徑範本自動整理]",
+            "fileSelection": {
+                "title": "選擇檔案格式",
+                "files": "個檔案",
+                "select": "選擇檔案"
+            },
             "errors": {
                 "invalidUrl": "Civitai 網址格式無效",
                 "noVersions": "此模型無可用版本"
@@ -1058,6 +1125,12 @@
             "countMessage": "模型將被永久刪除。",
             "action": "全部刪除"
         },
+        "bulkDeleteRecipes": {
+            "title": "刪除多個配方",
+            "message": "您確定要刪除所有選取的配方及其相關檔案嗎？",
+            "countMessage": "配方將被永久刪除。",
+            "action": "全部刪除"
+        },
         "checkUpdates": {
             "title": "要檢查所有 {type} 的更新嗎？",
             "message": "這會為資料庫中的每個 {type} 檢查更新，大型收藏可能會花上一些時間。",
@@ -1138,6 +1211,7 @@
                 "editModelName": "編輯模型名稱",
                 "editFileName": "編輯檔案名稱",
                 "editBaseModel": "編輯基礎模型",
+                "editVersionName": "編輯版本名稱",
                 "viewOnCivitai": "在 Civitai 查看",
                 "viewOnCivitaiText": "在 Civitai 查看",
                 "viewCreatorProfile": "查看創作者個人檔案",
@@ -1169,7 +1243,9 @@
             },
             "notes": {
                 "saved": "備註已儲存",
-                "saveFailed": "儲存備註失敗"
+                "saveFailed": "儲存備註失敗",
+                "showMore": "展開",
+                "showLess": "收起"
             },
             "usageTips": {
                 "addPresetParameter": "新增預設參數...",
@@ -1274,12 +1350,15 @@
                     "earlyAccess": "搶先體驗",
                     "earlyAccessTooltip": "此版本目前需要 Civitai 搶先體驗權限",
                     "ignored": "已忽略",
-                    "ignoredTooltip": "此版本已關閉更新通知"
+                    "ignoredTooltip": "此版本已關閉更新通知",
+                    "onSiteOnly": "僅站內生成",
+                    "onSiteOnlyTooltip": "此版本僅在 Civitai 站內可用，無法下載"
                 },
                 "actions": {
                     "download": "下載",
                     "downloadTooltip": "下載此版本",
                     "downloadEarlyAccessTooltip": "從 Civitai 下載此搶先體驗版本",
+                    "downloadNotAllowedTooltip": "此版本僅在 Civitai 站內可用，無法下載",
                     "delete": "刪除",
                     "deleteTooltip": "刪除此本地版本",
                     "ignore": "忽略",
@@ -1428,11 +1507,14 @@
             "noMatchingNodes": "目前工作流程中沒有相容的節點",
             "noTargetNodeSelected": "未選擇目標節點",
             "modelUpdated": "模型已更新到工作流",
-            "modelFailed": "更新模型節點失敗"
+            "modelFailed": "更新模型節點失敗",
+            "embeddingAdded": "Embedding 已附加到工作流",
+            "embeddingFailed": "傳送 Embedding 到工作流失敗"
         },
         "nodeSelector": {
             "recipe": "配方",
             "lora": "LoRA",
+            "embedding": "Embedding",
             "replace": "取代",
             "append": "附加",
             "selectTargetNode": "選擇目標節點",
@@ -1442,6 +1524,10 @@
             "opened": "範例圖片資料夾已開啟",
             "openingFolder": "正在開啟範例圖片資料夾",
             "failedToOpen": "開啟範例圖片資料夾失敗",
+            "copiedPath": "路徑已複製到剪貼簿：{{path}}",
+            "clipboardFallback": "路徑：{{path}}",
+            "copiedUri": "連結已複製到剪貼簿：{{uri}}",
+            "uriClipboardFallback": "連結：{{uri}}",
             "setupRequired": "範例圖片儲存",
             "setupDescription": "要新增自訂範例圖片，您需要先設定下載位置。",
             "setupUsage": "此路徑用於儲存下載的範例圖片和自訂圖片。",
@@ -1605,6 +1691,10 @@
             "noRecipeId": "無配方 ID",
             "sendToWorkflowFailed": "傳送配方到工作流失敗：{message}",
             "copyFailed": "複製配方語法錯誤：{message}",
+            "createError": "建立配方時發生錯誤：{message}",
+            "createFailed": "建立配方失敗：{error}",
+            "createMissingData": "缺少建立配方所需的資料",
+            "created": "配方建立成功",
             "noMissingLoras": "無缺少的 LoRA 可下載",
             "missingLorasInfoFailed": "取得缺少 LoRA 資訊失敗",
             "preparingForDownloadFailed": "準備下載 LoRA 時發生錯誤",
@@ -1643,6 +1733,13 @@
             "batchImportBrowseFailed": "瀏覽目錄失敗：{message}",
             "batchImportDirectorySelected": "已選擇目錄：{path}",
             "noRecipesSelected": "未選取任何食譜",
+            "repairBulkComplete": "修復完成：{repaired} 個已修復，{skipped} 個已跳過（共 {total} 個）",
+            "repairBulkSkipped": "所選 {total} 個配方無需修復",
+            "repairBulkFailed": "修復所選配方失敗：{message}",
+            "reimporting": "正在從來源重新匯入配方...",
+            "reimportSuccess": "配方已從來源重新匯入成功",
+            "reimportBulkComplete": "重新匯入完成：{completed} 個已匯入，{failed} 個失敗（共 {total} 個）",
+            "reimportBulkFailed": "重新匯入某些配方失敗",
             "noMissingLorasInSelection": "在選取的食譜中未找到缺失的 LoRAs",
             "noLoraRootConfigured": "未配置 LoRA 根目錄。請在設定中設定預設的 LoRA 根目錄。"
         },
@@ -1673,6 +1770,11 @@
             "bulkContentRatingSet": "已將 {count} 個模型的內容分級設定為 {level}",
             "bulkContentRatingPartial": "已將 {success} 個模型的內容分級設定為 {level}，{failed} 個失敗",
             "bulkContentRatingFailed": "無法更新所選模型的內容分級",
+            "bulkFavoriteUpdating": "正在將 {count} 個模型加入收藏...",
+            "bulkUnfavoriteUpdating": "正在將 {count} 個模型從收藏移除...",
+            "bulkFavoritePartialAdded": "已將 {success} 個模型加入收藏，{failed} 個失敗",
+            "bulkFavoritePartialRemoved": "已將 {success} 個模型從收藏移除，{failed} 個失敗",
+            "bulkFavoriteFailed": "更新收藏狀態失敗",
             "bulkUpdatesChecking": "正在檢查所選 {type} 的更新...",
             "bulkUpdatesSuccess": "{count} 個所選 {type} 有可用更新",
             "bulkUpdatesNone": "所選 {type} 未找到更新",
@@ -1875,18 +1977,52 @@
             "warning": "需要注意",
             "error": "需要處理"
         },
+        "issues": {
+            "civitai_api_key": {
+                "title": "Civitai API 金鑰"
+            },
+            "cache_health": {
+                "title": "模型快取健康狀態"
+            },
+            "filename_conflicts": {
+                "title": "檔案名稱重複衝突"
+            },
+            "ui_version": {
+                "title": "UI 版本"
+            }
+        },
         "actions": {
             "runAgain": "重新執行",
-            "exportBundle": "匯出套件"
+            "exportBundle": "匯出套件",
+            "open-settings": "開啟設定",
+            "open-settings-syntax-format": "切換為完整路徑語法",
+            "repair-cache": "重建快取",
+            "resolve-filename-conflicts": "解決衝突",
+            "reload-page": "重新載入 UI"
+        },
+        "labels": {
+            "conflicts": "衝突詳情",
+            "version": "版本"
         },
         "toast": {
             "loadFailed": "載入診斷失敗：{message}",
             "repairSuccess": "快取重建完成。",
             "repairFailed": "快取重建失敗：{message}",
             "exportSuccess": "診斷套件已匯出。",
-            "exportFailed": "匯出診斷套件失敗：{message}"
+            "exportFailed": "匯出診斷套件失敗：{message}",
+            "conflictsResolved": "已解決 {count} 個檔案名稱衝突。",
+            "conflictsResolveFailed": "解決檔案名稱衝突失敗：{message}"
         }
     },
+    "conflictConfirm": {
+        "title": "解決檔案名稱衝突",
+        "message": "通過在每個重複檔案名稱後附加 4 位元哈希值來重新命名檔案。",
+        "note": "此操作會重新命名磁碟上的檔案。如果使用 A1111 語法格式，現有工作流程中的模型參考可能需要更新。",
+        "detail": "示例：<code>filename_v1.2</code> → <code>filename_v1.2-ab3c</code>",
+        "impact": "將重新命名 <strong>{count}</strong> 個檔案（共 <strong>{groups}</strong> 組重複）",
+        "confirm": "重新命名檔案",
+        "cancel": "取消"
+    },
     "banners": {
         "versionMismatch": {
             "title": "偵測到應用程式更新",

py/config.py

@@ -172,6 +172,12 @@ class Config:
         self.extra_unet_roots: List[str] = []
         self.extra_embeddings_roots: List[str] = []
         self.recipes_path: str = ""
+
+        # Load extra folder paths from active library settings before symlink scan
+        # so both primary and extra paths are discovered in a single pass.
+        if not standalone_mode:
+            self._load_extra_paths_from_settings()
+
         # Scan symbolic links during initialization
         self._initialize_symlink_mappings()
 
@@ -179,6 +185,96 @@ class Config:
             # Save the paths to settings.json when running in ComfyUI mode
             self.save_folder_paths_to_settings()
 
+    def _load_extra_paths_from_settings(self) -> None:
+        """Read extra folder paths from the active library and apply them.
+
+        Called during ``Config.__init__`` before the symlink scan so both primary and
+        extra paths are discovered in a single pass.  Mirrors the extra-path
+        portion of ``_apply_library_paths`` without replacing the primary roots
+        that were already resolved from ComfyUI's ``folder_paths``.
+        """
+        try:
+            from .services.settings_manager import get_settings_manager
+
+            settings_manager = get_settings_manager()
+            library_name = settings_manager.get_active_library_name()
+            libraries = settings_manager.get_libraries()
+
+            if not library_name or library_name not in libraries:
+                return
+
+            library_config = libraries[library_name]
+            if not isinstance(library_config, dict):
+                return
+
+            extra_folder_paths = library_config.get("extra_folder_paths")
+            if not isinstance(extra_folder_paths, dict):
+                return
+
+            extra_lora = extra_folder_paths.get("loras", []) or []
+            extra_checkpoint = extra_folder_paths.get("checkpoints", []) or []
+            extra_unet = extra_folder_paths.get("unet", []) or []
+            extra_embedding = extra_folder_paths.get("embeddings", []) or []
+
+            if not any([extra_lora, extra_checkpoint, extra_unet, extra_embedding]):
+                return
+
+            filtered_extra_lora = self._filter_overlapping_extra_lora_paths(
+                self.loras_roots, extra_lora
+            )
+            self.extra_loras_roots = self._prepare_lora_paths(filtered_extra_lora)
+            (
+                _,
+                self.extra_checkpoints_roots,
+                self.extra_unet_roots,
+            ) = self._prepare_checkpoint_paths(extra_checkpoint, extra_unet)
+            self.extra_embeddings_roots = self._prepare_embedding_paths(
+                extra_embedding
+            )
+
+            recipes_path = library_config.get("recipes_path", "")
+            if isinstance(recipes_path, str) and recipes_path:
+                self.recipes_path = recipes_path
+
+            if self.extra_loras_roots:
+                logger.info(
+                    "Found extra LoRA roots:"
+                    + "\n - "
+                    + "\n - ".join(self.extra_loras_roots)
+                )
+            if self.extra_checkpoints_roots:
+                logger.info(
+                    "Found extra checkpoint roots:"
+                    + "\n - "
+                    + "\n - ".join(self.extra_checkpoints_roots)
+                )
+            if self.extra_unet_roots:
+                logger.info(
+                    "Found extra diffusion model roots:"
+                    + "\n - "
+                    + "\n - ".join(self.extra_unet_roots)
+                )
+            if self.extra_embeddings_roots:
+                logger.info(
+                    "Found extra embedding roots:"
+                    + "\n - "
+                    + "\n - ".join(self.extra_embeddings_roots)
+                )
+
+            logger.info(
+                "Applied library settings for '%s' with extra paths: loras=%s, "
+                "checkpoints=%s, embeddings=%s",
+                library_name,
+                extra_lora,
+                extra_checkpoint,
+                extra_embedding,
+            )
+
+        except Exception as exc:
+            logger.debug(
+                "Could not load extra paths from library settings: %s", exc
+            )
+
     def save_folder_paths_to_settings(self):
         """Persist ComfyUI-derived folder paths to the multi-library settings."""
         try:

py/lora_manager.py

@@ -184,44 +184,15 @@ class LoraManager:
     async def _initialize_services(cls):
         """Initialize all services using the ServiceRegistry"""
         try:
-            # Apply library settings to load extra folder paths before scanning
-            # Only apply if extra paths haven't been loaded yet (preserves test mocks)
-            try:
-                from .services.settings_manager import get_settings_manager
-
-                settings_manager = get_settings_manager()
-                library_name = settings_manager.get_active_library_name()
-                libraries = settings_manager.get_libraries()
-                if library_name and library_name in libraries:
-                    library_config = libraries[library_name]
-                    # Only apply settings if extra paths are not already configured
-                    # This preserves values set by tests via monkeypatch
-                    extra_paths = library_config.get("extra_folder_paths", {})
-                    has_extra_paths = (
-                        config.extra_loras_roots
-                        or config.extra_checkpoints_roots
-                        or config.extra_unet_roots
-                        or config.extra_embeddings_roots
-                    )
-                    if not has_extra_paths and any(extra_paths.values()):
-                        config.apply_library_settings(library_config)
-                        logger.info(
-                            "Applied library settings for '%s' with extra paths: loras=%s, checkpoints=%s, embeddings=%s",
-                            library_name,
-                            extra_paths.get("loras", []),
-                            extra_paths.get("checkpoints", []),
-                            extra_paths.get("embeddings", []),
-                        )
-            except Exception as exc:
-                logger.warning(
-                    "Failed to apply library settings during initialization: %s", exc
-                )
-
             # Initialize CivitaiClient first to ensure it's ready for other services
             await ServiceRegistry.get_civitai_client()
 
             # Register DownloadManager with ServiceRegistry
             await ServiceRegistry.get_download_manager()
+
+            # Initialize DownloadQueueService for persistent queue/history
+            await ServiceRegistry.get_download_queue_service()
+
             await ServiceRegistry.get_backup_service()
 
             from .services.metadata_service import initialize_metadata_providers

py/metadata_collector/constants.py

@@ -5,9 +5,10 @@ MODELS = "models"
 PROMPTS = "prompts"
 SAMPLING = "sampling"
 LORAS = "loras"
+EMBEDDINGS = "embeddings"
 SIZE = "size"
 IMAGES = "images"
 IS_SAMPLER = "is_sampler"  # New constant to mark sampler nodes
 
 # Complete list of categories to track
-METADATA_CATEGORIES = [MODELS, PROMPTS, SAMPLING, LORAS, SIZE, IMAGES]
+METADATA_CATEGORIES = [MODELS, PROMPTS, SAMPLING, LORAS, EMBEDDINGS, SIZE, IMAGES]

py/metadata_collector/metadata_processor.py

@@ -353,49 +353,100 @@ class MetadataProcessor:
         # Check if we have stored conditioning objects for this sampler
         if sampler_id in metadata.get(PROMPTS, {}) and (
             "pos_conditioning" in metadata[PROMPTS][sampler_id] or
-            "neg_conditioning" in metadata[PROMPTS][sampler_id]):
+            "neg_conditioning" in metadata[PROMPTS][sampler_id]
-            
+        ):
             pos_conditioning = metadata[PROMPTS][sampler_id].get("pos_conditioning")
             neg_conditioning = metadata[PROMPTS][sampler_id].get("neg_conditioning")
 
-            # Helper function to recursively find prompt text for a conditioning object
+            def extend_unique(target, values):
-            def find_prompt_text_for_conditioning(conditioning_obj, is_positive=True):
+                for value in values:
+                    if value and value not in target:
+                        target.append(value)
+
+            # Helper function to recursively find prompt texts for a conditioning object.
+            # Transform nodes can map one output conditioning to multiple source conditionings.
+            def find_prompt_texts_for_conditioning(
+                conditioning_obj, is_positive=True, visited=None
+            ):
                 if conditioning_obj is None:
-                    return ""
+                    return []
+
+                if visited is None:
+                    visited = set()
+
+                conditioning_id = id(conditioning_obj)
+                if conditioning_id in visited:
+                    return []
+                visited.add(conditioning_id)
+
+                prompt_texts = []
 
                 # Try to match conditioning objects with those stored by extractors
                 for prompt_node_id, prompt_data in metadata[PROMPTS].items():
-                    # For nodes with single conditioning output
+                    if not isinstance(prompt_data, dict):
-                    if "conditioning" in prompt_data:
+                        continue
-                        if id(prompt_data["conditioning"]) == id(conditioning_obj):
-                            return prompt_data.get("text", "")
 
-                    # For nodes with separate pos_conditioning and neg_conditioning outputs (like TSC_EfficientLoader)
+                    # For CLIP text nodes with a single conditioning output.
-                    if is_positive and "positive_encoded" in prompt_data:
+                    if id(prompt_data.get("conditioning")) == conditioning_id:
-                        if id(prompt_data["positive_encoded"]) == id(conditioning_obj):
+                        text = prompt_data.get("text", "")
-                            if "positive_text" in prompt_data:
+                        if text:
-                                return prompt_data["positive_text"]
+                            extend_unique(prompt_texts, [text])
+
+                    # Generic provenance for passthrough/transform/combine nodes.
+                    for source in prompt_data.get("conditioning_sources", []):
+                        if id(source.get("output")) != conditioning_id:
+                            continue
+                        for input_conditioning in source.get("inputs", []):
+                            extend_unique(
+                                prompt_texts,
+                                find_prompt_texts_for_conditioning(
+                                    input_conditioning, is_positive, visited
+                                ),
+                            )
+
+                    # For nodes with separate pos_conditioning and neg_conditioning outputs
+                    # like TSC_EfficientLoader and existing ControlNet-style metadata.
+                    if (
+                        is_positive
+                        and id(prompt_data.get("positive_encoded")) == conditioning_id
+                    ):
+                        if prompt_data.get("positive_text"):
+                            extend_unique(prompt_texts, [prompt_data["positive_text"]])
                         else:
-                                orig_conditioning = prompt_data.get("orig_pos_cond", None)
+                            extend_unique(
-                                if orig_conditioning is not None:
+                                prompt_texts,
-                                    # Recursively find the prompt text for the original conditioning
+                                find_prompt_texts_for_conditioning(
-                                    return find_prompt_text_for_conditioning(orig_conditioning, is_positive=True)
+                                    prompt_data.get("orig_pos_cond"),
+                                    is_positive=True,
+                                    visited=visited,
+                                ),
+                            )
 
-                    if not is_positive and "negative_encoded" in prompt_data:
+                    if (
-                        if id(prompt_data["negative_encoded"]) == id(conditioning_obj):
+                        not is_positive
-                            if "negative_text" in prompt_data:
+                        and id(prompt_data.get("negative_encoded")) == conditioning_id
-                                return prompt_data["negative_text"]
+                    ):
+                        if prompt_data.get("negative_text"):
+                            extend_unique(prompt_texts, [prompt_data["negative_text"]])
                         else:
-                                orig_conditioning = prompt_data.get("orig_neg_cond", None)
+                            extend_unique(
-                                if orig_conditioning is not None:
+                                prompt_texts,
-                                    # Recursively find the prompt text for the original conditioning
+                                find_prompt_texts_for_conditioning(
-                                    return find_prompt_text_for_conditioning(orig_conditioning, is_positive=False)
+                                    prompt_data.get("orig_neg_cond"),
+                                    is_positive=False,
+                                    visited=visited,
+                                ),
+                            )
 
-                return ""
+                return prompt_texts
 
             # Find prompt texts using the helper function
-            result["prompt"] = find_prompt_text_for_conditioning(pos_conditioning, is_positive=True)
+            result["prompt"] = ", ".join(
-            result["negative_prompt"] = find_prompt_text_for_conditioning(neg_conditioning, is_positive=False)
+                find_prompt_texts_for_conditioning(pos_conditioning, is_positive=True)
+            )
+            result["negative_prompt"] = ", ".join(
+                find_prompt_texts_for_conditioning(neg_conditioning, is_positive=False)
+            )
             
         return result
     
@@ -509,8 +560,14 @@ class MetadataProcessor:
         
         params["loras"] = " ".join(lora_parts)
         
-        # Set default clip_skip value
+        # Extract clip_skip from any SAMPLING node that provides it
-        params["clip_skip"] = "1"  # Common default
+        for sampler_info in metadata.get(SAMPLING, {}).values():
+            clip_skip = sampler_info.get("parameters", {}).get("clip_skip")
+            if clip_skip is not None:
+                params["clip_skip"] = clip_skip
+                break
+        if params["clip_skip"] is None:
+            params["clip_skip"] = "1"
         
         return params
     

py/metadata_collector/node_extractors.py

@@ -144,6 +144,118 @@ class TSCCheckpointLoaderExtractor(NodeMetadataExtractor):
                 metadata[PROMPTS][node_id]["positive_encoded"] = positive_conditioning
                 metadata[PROMPTS][node_id]["negative_encoded"] = negative_conditioning
 
+
+class EasyComfyLoaderExtractor(NodeMetadataExtractor):
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs:
+            return
+
+        if "ckpt_name" in inputs:
+            _store_checkpoint_metadata(metadata, node_id, inputs["ckpt_name"])
+
+        # Only extract from optional_lora_stack — skip the single lora_name to
+        # avoid double-counting LoRAs that come through the LORA_STACK path.
+        active_loras = []
+        optional_lora_stack = inputs.get("optional_lora_stack")
+        if optional_lora_stack is not None and isinstance(optional_lora_stack, (list, tuple)):
+            for item in optional_lora_stack:
+                if isinstance(item, (list, tuple)) and len(item) >= 2:
+                    lora_path = item[0]
+                    model_strength = item[1]
+                    lora_name = os.path.splitext(os.path.basename(lora_path))[0]
+                    active_loras.append({
+                        "name": lora_name,
+                        "strength": model_strength
+                    })
+
+        if active_loras:
+            metadata[LORAS][node_id] = {
+                "lora_list": active_loras,
+                "node_id": node_id
+            }
+
+        positive_text = inputs.get("positive", "")
+        negative_text = inputs.get("negative", "")
+
+        if positive_text or negative_text:
+            if node_id not in metadata[PROMPTS]:
+                metadata[PROMPTS][node_id] = {"node_id": node_id}
+            metadata[PROMPTS][node_id]["positive_text"] = positive_text
+            metadata[PROMPTS][node_id]["negative_text"] = negative_text
+
+        if "clip_skip" in inputs:
+            clip_skip = inputs["clip_skip"]
+            if node_id not in metadata[SAMPLING]:
+                metadata[SAMPLING][node_id] = {"parameters": {}, "node_id": node_id}
+            metadata[SAMPLING][node_id]["parameters"]["clip_skip"] = clip_skip
+
+        width = inputs.get("empty_latent_width")
+        height = inputs.get("empty_latent_height")
+        if width is not None and height is not None:
+            if SIZE not in metadata:
+                metadata[SIZE] = {}
+            metadata[SIZE][node_id] = {
+                "width": int(width),
+                "height": int(height),
+                "node_id": node_id
+            }
+
+    @staticmethod
+    def update(node_id, outputs, metadata):
+        # outputs: [(pipe_dict, model, vae), ...]
+        if not outputs or not isinstance(outputs, list) or len(outputs) == 0:
+            return
+        first_output = outputs[0]
+        if not isinstance(first_output, tuple) or len(first_output) < 1:
+            return
+        pipe = first_output[0]
+        if not isinstance(pipe, dict):
+            return
+
+        positive_conditioning = pipe.get("positive")
+        negative_conditioning = pipe.get("negative")
+
+        if positive_conditioning is not None or negative_conditioning is not None:
+            if node_id not in metadata[PROMPTS]:
+                metadata[PROMPTS][node_id] = {"node_id": node_id}
+            if positive_conditioning is not None:
+                metadata[PROMPTS][node_id]["positive_encoded"] = positive_conditioning
+            if negative_conditioning is not None:
+                metadata[PROMPTS][node_id]["negative_encoded"] = negative_conditioning
+
+
+class EasyPreSamplingExtractor(NodeMetadataExtractor):
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs:
+            return
+
+        sampling_params = {}
+        for key in ("steps", "cfg", "sampler_name", "scheduler", "denoise", "seed"):
+            if key in inputs:
+                sampling_params[key] = inputs[key]
+
+        metadata[SAMPLING][node_id] = {
+            "parameters": sampling_params,
+            "node_id": node_id,
+            IS_SAMPLER: True
+        }
+
+
+class EasySeedExtractor(NodeMetadataExtractor):
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs or "seed" not in inputs:
+            return
+
+        metadata[SAMPLING][node_id] = {
+            "parameters": {"seed": inputs["seed"]},
+            "node_id": node_id,
+            IS_SAMPLER: False
+        }
+
+
 class CLIPTextEncodeExtractor(NodeMetadataExtractor):
     @staticmethod
     def extract(node_id, inputs, outputs, metadata):
@@ -163,6 +275,251 @@ class CLIPTextEncodeExtractor(NodeMetadataExtractor):
                 conditioning = outputs[0][0]
                 metadata[PROMPTS][node_id]["conditioning"] = conditioning
 
+
+class MyOriginalWaifuTextExtractor(NodeMetadataExtractor):
+    """Extractor for ComfyUI-MyOriginalWaifu TextProvider nodes."""
+
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs:
+            return
+
+        positive_text = inputs.get("positive", "")
+        negative_text = inputs.get("negative", "")
+
+        if positive_text or negative_text:
+            metadata[PROMPTS][node_id] = {
+                "positive_text": positive_text,
+                "negative_text": negative_text,
+                "node_id": node_id,
+            }
+
+    @staticmethod
+    def update(node_id, outputs, metadata):
+        output_tuple = _first_output_tuple(outputs)
+        if not output_tuple or len(output_tuple) < 2:
+            return
+
+        prompt_metadata = _ensure_prompt_metadata(metadata, node_id)
+        prompt_metadata["positive_text"] = output_tuple[0]
+        prompt_metadata["negative_text"] = output_tuple[1]
+
+
+class MyOriginalWaifuClipExtractor(NodeMetadataExtractor):
+    """Extractor for ComfyUI-MyOriginalWaifu ClipProvider nodes."""
+
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs:
+            return
+
+        positive_text = inputs.get("positive", "")
+        negative_text = inputs.get("negative", "")
+
+        if positive_text or negative_text:
+            metadata[PROMPTS][node_id] = {
+                "positive_text": positive_text,
+                "negative_text": negative_text,
+                "node_id": node_id,
+            }
+
+    @staticmethod
+    def update(node_id, outputs, metadata):
+        output_tuple = _first_output_tuple(outputs)
+        if not output_tuple or len(output_tuple) < 2:
+            return
+
+        prompt_metadata = _ensure_prompt_metadata(metadata, node_id)
+        prompt_metadata["positive_encoded"] = output_tuple[0]
+        prompt_metadata["negative_encoded"] = output_tuple[1]
+
+
+def _ensure_prompt_metadata(metadata, node_id):
+    if node_id not in metadata[PROMPTS]:
+        metadata[PROMPTS][node_id] = {"node_id": node_id}
+    return metadata[PROMPTS][node_id]
+
+
+def _first_output_tuple(outputs):
+    if not outputs or not isinstance(outputs, list) or len(outputs) == 0:
+        return None
+    first_output = outputs[0]
+    if isinstance(first_output, tuple):
+        return first_output
+    return None
+
+
+def _record_conditioning_source(
+    metadata, node_id, output_conditioning, input_conditionings
+):
+    if output_conditioning is None:
+        return
+
+    sources = [
+        conditioning for conditioning in input_conditionings if conditioning is not None
+    ]
+    if not sources:
+        return
+
+    prompt_metadata = _ensure_prompt_metadata(metadata, node_id)
+    prompt_metadata.setdefault("conditioning_sources", []).append(
+        {
+            "output": output_conditioning,
+            "inputs": sources,
+        }
+    )
+
+
+def _get_variable_name(inputs):
+    for key in ("key", "name", "variable_name", "tag", "text"):
+        value = inputs.get(key)
+        if isinstance(value, str) and value:
+            return value
+    return None
+
+
+def _get_node_variable_name(metadata, node_id, inputs):
+    variable_name = _get_variable_name(inputs)
+    if variable_name:
+        return variable_name
+
+    prompt = metadata.get("current_prompt")
+    original_prompt = getattr(prompt, "original_prompt", None)
+    if not original_prompt or node_id not in original_prompt:
+        return None
+
+    node_data = original_prompt[node_id]
+    variable_name = _get_variable_name(node_data.get("inputs", {}))
+    if variable_name:
+        return variable_name
+
+    widgets_values = node_data.get("widgets_values", [])
+    if widgets_values and isinstance(widgets_values[0], str):
+        return widgets_values[0]
+
+    return None
+
+
+class ControlNetApplyAdvancedExtractor(NodeMetadataExtractor):
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs:
+            return
+
+        prompt_metadata = _ensure_prompt_metadata(metadata, node_id)
+        if inputs.get("positive") is not None:
+            prompt_metadata["orig_pos_cond"] = inputs["positive"]
+        if inputs.get("negative") is not None:
+            prompt_metadata["orig_neg_cond"] = inputs["negative"]
+
+    @staticmethod
+    def update(node_id, outputs, metadata):
+        output_tuple = _first_output_tuple(outputs)
+        if not output_tuple:
+            return
+
+        prompt_metadata = _ensure_prompt_metadata(metadata, node_id)
+        positive_input = prompt_metadata.get("orig_pos_cond")
+        negative_input = prompt_metadata.get("orig_neg_cond")
+
+        if len(output_tuple) >= 1:
+            prompt_metadata["positive_encoded"] = output_tuple[0]
+            _record_conditioning_source(
+                metadata, node_id, output_tuple[0], [positive_input]
+            )
+        if len(output_tuple) >= 2:
+            prompt_metadata["negative_encoded"] = output_tuple[1]
+            _record_conditioning_source(
+                metadata, node_id, output_tuple[1], [negative_input]
+            )
+
+
+class ConditioningCombineExtractor(NodeMetadataExtractor):
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs:
+            return
+
+        input_conditionings = []
+        for input_name in inputs:
+            if (
+                input_name.startswith("conditioning")
+                and inputs[input_name] is not None
+            ):
+                input_conditionings.append(inputs[input_name])
+
+        if input_conditionings:
+            prompt_metadata = _ensure_prompt_metadata(metadata, node_id)
+            prompt_metadata["orig_conditionings"] = input_conditionings
+
+    @staticmethod
+    def update(node_id, outputs, metadata):
+        output_tuple = _first_output_tuple(outputs)
+        if not output_tuple or len(output_tuple) < 1:
+            return
+
+        prompt_metadata = _ensure_prompt_metadata(metadata, node_id)
+        output_conditioning = output_tuple[0]
+        prompt_metadata["conditioning"] = output_conditioning
+        _record_conditioning_source(
+            metadata,
+            node_id,
+            output_conditioning,
+            prompt_metadata.get("orig_conditionings", []),
+        )
+
+
+class SetNodeExtractor(NodeMetadataExtractor):
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs:
+            return
+
+        variable_name = _get_node_variable_name(metadata, node_id, inputs)
+        conditioning = inputs.get("CONDITIONING")
+        if conditioning is None:
+            conditioning = inputs.get("conditioning")
+        if conditioning is None:
+            return
+
+        prompt_metadata = _ensure_prompt_metadata(metadata, node_id)
+        prompt_metadata["conditioning"] = conditioning
+        if variable_name:
+            prompt_metadata["variable_name"] = variable_name
+            metadata[PROMPTS].setdefault("__conditioning_variables__", {})[
+                variable_name
+            ] = conditioning
+
+
+class GetNodeExtractor(NodeMetadataExtractor):
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        variable_name = _get_node_variable_name(metadata, node_id, inputs or {})
+        if variable_name:
+            prompt_metadata = _ensure_prompt_metadata(metadata, node_id)
+            prompt_metadata["variable_name"] = variable_name
+
+    @staticmethod
+    def update(node_id, outputs, metadata):
+        output_tuple = _first_output_tuple(outputs)
+        if not output_tuple or len(output_tuple) < 1:
+            return
+
+        prompt_metadata = _ensure_prompt_metadata(metadata, node_id)
+        output_conditioning = output_tuple[0]
+        prompt_metadata["conditioning"] = output_conditioning
+
+        variable_name = prompt_metadata.get("variable_name")
+        if not variable_name:
+            return
+
+        input_conditioning = metadata[PROMPTS].get("__conditioning_variables__", {}).get(
+            variable_name
+        )
+        _record_conditioning_source(
+            metadata, node_id, output_conditioning, [input_conditioning]
+        )
+
 # Base Sampler Extractor to reduce code redundancy
 class BaseSamplerExtractor(NodeMetadataExtractor):
     """Base extractor for sampler nodes with common functionality"""
@@ -768,9 +1125,12 @@ NODE_EXTRACTORS = {
     "KSamplerSelect": KSamplerSelectExtractor,  # Add KSamplerSelect
     "BasicScheduler": BasicSchedulerExtractor,  # Add BasicScheduler
     "AlignYourStepsScheduler": BasicSchedulerExtractor,  # Add AlignYourStepsScheduler
+    # ComfyUI-Easy-Use pre-sampling / seed
+    "samplerSettings": EasyPreSamplingExtractor,  # easy preSampling
+    "easySeed": EasySeedExtractor,  # easy seed
     # Loaders
     "CheckpointLoaderSimple": CheckpointLoaderExtractor,
-    "comfyLoader": CheckpointLoaderExtractor,  # easy comfyLoader
+    "comfyLoader": EasyComfyLoaderExtractor,  # ComfyUI-Easy-Use easy comfyLoader
     "CheckpointLoaderSimpleWithImages": CheckpointLoaderExtractor,  # CheckpointLoader|pysssss
     "TSC_EfficientLoader": TSCCheckpointLoaderExtractor,  # Efficient Nodes
     "NunchakuFluxDiTLoader": NunchakuFluxDiTLoaderExtractor,  # ComfyUI-Nunchaku
@@ -780,8 +1140,10 @@ NODE_EXTRACTORS = {
     "GGUFLoaderKJ": KJNodesModelLoaderExtractor,  # KJNodes
     "DiffusionModelLoaderKJ": KJNodesModelLoaderExtractor,  # KJNodes
     "CheckpointLoaderKJ": CheckpointLoaderExtractor,  # KJNodes
+    "CheckpointLoaderLM": CheckpointLoaderExtractor,  # LoRA Manager
     "UNETLoader": UNETLoaderExtractor,          # Updated to use dedicated extractor
     "UnetLoaderGGUF": UNETLoaderExtractor,  # Updated to use dedicated extractor
+    "UNETLoaderLM": UNETLoaderExtractor,  # LoRA Manager
     "LoraLoader": LoraLoaderExtractor,
     "LoraLoaderLM": LoraLoaderManagerExtractor,
     "RgthreePowerLoraLoader": RgthreePowerLoraLoaderExtractor,
@@ -796,6 +1158,12 @@ NODE_EXTRACTORS = {
     "smZ_CLIPTextEncode": CLIPTextEncodeExtractor,  # From https://github.com/shiimizu/ComfyUI_smZNodes
     "CR_ApplyControlNetStack": CR_ApplyControlNetStackExtractor,  # Add CR_ApplyControlNetStack
     "PCTextEncode": CLIPTextEncodeExtractor,  # From https://github.com/asagi4/comfyui-prompt-control
+    "TextProvider": MyOriginalWaifuTextExtractor,  # ComfyUI-MyOriginalWaifu
+    "ClipProvider": MyOriginalWaifuClipExtractor,  # ComfyUI-MyOriginalWaifu
+    "ControlNetApplyAdvanced": ControlNetApplyAdvancedExtractor,
+    "ConditioningCombine": ConditioningCombineExtractor,
+    "SetNode": SetNodeExtractor,
+    "GetNode": GetNodeExtractor,
     # Latent
     "EmptyLatentImage": ImageSizeExtractor,
     # Flux

py/nodes/lora_loader.py

@@ -9,6 +9,7 @@ from ..utils.utils import get_lora_info_absolute
 from .utils import (
     FlexibleOptionalInputType,
     any_type,
+    apply_lora_syntax_format,
     detect_nunchaku_model_kind,
     extract_lora_name,
     get_loras_list,
@@ -52,7 +53,7 @@ def _collect_widget_entries(kwargs):
     for lora in get_loras_list(kwargs):
         if not lora.get("active", False):
             continue
-        lora_name = lora["name"]
+        lora_name = apply_lora_syntax_format(lora["name"])
         model_strength = float(lora["strength"])
         clip_strength = float(lora.get("clipStrength", model_strength))
         lora_path, trigger_words = get_lora_info_absolute(lora_name)

py/nodes/lora_stacker.py

@@ -1,6 +1,6 @@
 import os
 from ..utils.utils import get_lora_info
-from .utils import FlexibleOptionalInputType, any_type, extract_lora_name, get_loras_list
+from .utils import FlexibleOptionalInputType, any_type, apply_lora_syntax_format, extract_lora_name, get_loras_list
 
 import logging
 
@@ -48,7 +48,7 @@ class LoraStackerLM:
             if not lora.get('active', False):
                 continue
                 
-            lora_name = lora['name']
+            lora_name = apply_lora_syntax_format(lora['name'])
             model_strength = float(lora['strength'])
             # Get clip strength - use model strength as default if not specified
             clip_strength = float(lora.get('clipStrength', model_strength))

py/nodes/save_image.py

@@ -1,12 +1,17 @@
 import json
 import os
 import re
+import time
+import uuid
 from typing import Any, Dict, Optional
 import numpy as np
 import folder_paths  # type: ignore
 from ..services.service_registry import ServiceRegistry
 from ..metadata_collector.metadata_processor import MetadataProcessor
 from ..metadata_collector import get_metadata
+from ..utils.constants import CARD_PREVIEW_WIDTH
+from ..utils.exif_utils import ExifUtils
+from ..utils.utils import calculate_recipe_fingerprint
 from PIL import Image, PngImagePlugin
 import piexif
 import logging
@@ -86,6 +91,13 @@ class SaveImageLM:
                         "tooltip": "Adds an incremental counter to filenames to prevent overwriting previous images.",
                     },
                 ),
+                "save_as_recipe": (
+                    "BOOLEAN",
+                    {
+                        "default": False,
+                        "tooltip": "Also saves each generated image as a LoRA Manager recipe.",
+                    },
+                ),
             },
             "hidden": {
                 "id": "UNIQUE_ID",
@@ -346,6 +358,203 @@ class SaveImageLM:
 
         return filename
 
+    @staticmethod
+    def _get_cached_model_by_name(scanner, name):
+        cache = getattr(scanner, "_cache", None)
+        if cache is None or not name:
+            return None
+
+        candidates = [
+            name,
+            os.path.basename(name),
+            os.path.splitext(os.path.basename(name))[0],
+        ]
+        for model in getattr(cache, "raw_data", []):
+            file_name = model.get("file_name")
+            if file_name in candidates:
+                return model
+        return None
+
+    def _build_recipe_loras(self, recipe_scanner, lora_stack):
+        lora_matches = re.findall(r"<lora:([^:]+):([^>]+)>", lora_stack or "")
+        lora_scanner = getattr(recipe_scanner, "_lora_scanner", None)
+        loras_data = []
+        base_model_counts = {}
+
+        for name, strength in lora_matches:
+            lora_info = self._get_cached_model_by_name(lora_scanner, name)
+            civitai = (lora_info or {}).get("civitai") or {}
+            civitai_model = civitai.get("model") or {}
+            try:
+                parsed_strength = float(strength)
+            except (TypeError, ValueError):
+                parsed_strength = 1.0
+
+            loras_data.append(
+                {
+                    "file_name": name,
+                    "strength": parsed_strength,
+                    "hash": ((lora_info or {}).get("sha256") or "").lower(),
+                    "modelVersionId": civitai.get("id", 0),
+                    "modelName": civitai_model.get("name", name) if lora_info else "",
+                    "modelVersionName": civitai.get("name", "") if lora_info else "",
+                    "isDeleted": False,
+                    "exclude": False,
+                }
+            )
+
+            base_model = (lora_info or {}).get("base_model")
+            if base_model:
+                base_model_counts[base_model] = base_model_counts.get(base_model, 0) + 1
+
+        return lora_matches, loras_data, base_model_counts
+
+    def _build_recipe_checkpoint(self, recipe_scanner, checkpoint_raw):
+        if not isinstance(checkpoint_raw, str) or not checkpoint_raw.strip():
+            return None
+
+        checkpoint_name = checkpoint_raw.strip()
+        file_name = os.path.splitext(os.path.basename(checkpoint_name))[0]
+        checkpoint_scanner = getattr(recipe_scanner, "_checkpoint_scanner", None)
+        checkpoint_info = self._get_cached_model_by_name(
+            checkpoint_scanner, checkpoint_name
+        )
+
+        if not checkpoint_info:
+            return {
+                "type": "checkpoint",
+                "name": checkpoint_name,
+                "file_name": file_name,
+                "hash": self.get_checkpoint_hash(checkpoint_name) or "",
+            }
+
+        civitai = checkpoint_info.get("civitai") or {}
+        civitai_model = civitai.get("model") or {}
+        file_path = checkpoint_info.get("file_path") or checkpoint_info.get("path") or ""
+        cached_file_name = (
+            checkpoint_info.get("file_name")
+            or (os.path.splitext(os.path.basename(file_path))[0] if file_path else "")
+            or file_name
+        )
+
+        return {
+            "type": "checkpoint",
+            "modelId": civitai_model.get("id", 0),
+            "modelVersionId": civitai.get("id", 0),
+            "name": civitai_model.get("name")
+            or checkpoint_info.get("model_name")
+            or checkpoint_name,
+            "version": civitai.get("name", ""),
+            "hash": (
+                checkpoint_info.get("sha256") or checkpoint_info.get("hash") or ""
+            ).lower(),
+            "file_name": cached_file_name,
+            "modelName": civitai_model.get("name", ""),
+            "modelVersionName": civitai.get("name", ""),
+            "baseModel": checkpoint_info.get("base_model")
+            or civitai.get("baseModel", ""),
+        }
+
+    @staticmethod
+    def _derive_recipe_name(lora_matches):
+        recipe_name_parts = [
+            f"{name.strip()}-{float(strength):.2f}" for name, strength in lora_matches[:3]
+        ]
+        return "_".join(recipe_name_parts) or "recipe"
+
+    @staticmethod
+    def _sync_recipe_cache(recipe_scanner, recipe_data, json_path):
+        cache = getattr(recipe_scanner, "_cache", None)
+        if cache is not None:
+            cache.raw_data.append(recipe_data)
+            cache.sorted_by_name = sorted(
+                cache.raw_data, key=lambda item: item.get("title", "").lower()
+            )
+            cache.sorted_by_date = sorted(
+                cache.raw_data,
+                key=lambda item: (
+                    item.get("modified", item.get("created_date", 0)),
+                    item.get("file_path", ""),
+                ),
+                reverse=True,
+            )
+            recipe_scanner._update_folder_metadata(cache)
+            recipe_scanner._update_fts_index_for_recipe(recipe_data, "add")
+
+        recipe_id = str(recipe_data.get("id", ""))
+        if recipe_id:
+            recipe_scanner._json_path_map[recipe_id] = json_path
+        persistent_cache = getattr(recipe_scanner, "_persistent_cache", None)
+        if persistent_cache:
+            persistent_cache.update_recipe(recipe_data, json_path)
+
+    def _save_image_as_recipe(self, file_path, metadata_dict):
+        if not metadata_dict:
+            raise ValueError("No generation metadata found")
+
+        recipe_scanner = ServiceRegistry.get_service_sync("recipe_scanner")
+        if recipe_scanner is None:
+            raise RuntimeError("Recipe scanner unavailable")
+
+        recipes_dir = recipe_scanner.recipes_dir
+        if not recipes_dir:
+            raise RuntimeError("Recipes directory unavailable")
+        os.makedirs(recipes_dir, exist_ok=True)
+
+        recipe_id = str(uuid.uuid4())
+        optimized_image, extension = ExifUtils.optimize_image(
+            image_data=file_path,
+            target_width=CARD_PREVIEW_WIDTH,
+            format="webp",
+            quality=85,
+            preserve_metadata=True,
+        )
+        image_path = os.path.normpath(os.path.join(recipes_dir, f"{recipe_id}{extension}"))
+        with open(image_path, "wb") as file_obj:
+            file_obj.write(optimized_image)
+
+        lora_stack = metadata_dict.get("loras", "")
+        lora_matches, loras_data, base_model_counts = self._build_recipe_loras(
+            recipe_scanner, lora_stack
+        )
+        checkpoint_entry = self._build_recipe_checkpoint(
+            recipe_scanner, metadata_dict.get("checkpoint")
+        )
+        most_common_base_model = (
+            max(base_model_counts.items(), key=lambda item: item[1])[0]
+            if base_model_counts
+            else ""
+        )
+        current_time = time.time()
+        recipe_data = {
+            "id": recipe_id,
+            "file_path": image_path,
+            "title": self._derive_recipe_name(lora_matches),
+            "modified": current_time,
+            "created_date": current_time,
+            "base_model": most_common_base_model
+            or (checkpoint_entry or {}).get("baseModel", ""),
+            "loras": loras_data,
+            "gen_params": {
+                key: value
+                for key, value in metadata_dict.items()
+                if key not in ["checkpoint", "loras"]
+            },
+            "loras_stack": lora_stack,
+            "fingerprint": calculate_recipe_fingerprint(loras_data),
+        }
+        if checkpoint_entry:
+            recipe_data["checkpoint"] = checkpoint_entry
+
+        json_path = os.path.normpath(
+            os.path.join(recipes_dir, f"{recipe_id}.recipe.json")
+        )
+        with open(json_path, "w", encoding="utf-8") as file_obj:
+            json.dump(recipe_data, file_obj, indent=4, ensure_ascii=False)
+
+        ExifUtils.append_recipe_metadata(image_path, recipe_data)
+        self._sync_recipe_cache(recipe_scanner, recipe_data, json_path)
+
     def save_images(
         self,
         images,
@@ -359,6 +568,7 @@ class SaveImageLM:
         embed_workflow=False,
         save_with_metadata=True,
         add_counter_to_filename=True,
+        save_as_recipe=False,
     ):
         """Save images with metadata"""
         results = []
@@ -477,6 +687,14 @@ class SaveImageLM:
 
                     img.save(file_path, format="WEBP", **save_kwargs)
 
+                if save_as_recipe:
+                    try:
+                        self._save_image_as_recipe(file_path, metadata_dict)
+                    except Exception as e:
+                        logger.warning(
+                            "Failed to save image as recipe: %s", e, exc_info=True
+                        )
+
                 results.append(
                     {"filename": file, "subfolder": subfolder, "type": self.type}
                 )
@@ -499,6 +717,7 @@ class SaveImageLM:
         embed_workflow=False,
         save_with_metadata=True,
         add_counter_to_filename=True,
+        save_as_recipe=False,
     ):
         """Process and save image with metadata"""
         # Make sure the output directory exists
@@ -527,6 +746,7 @@ class SaveImageLM:
             embed_workflow,
             save_with_metadata,
             add_counter_to_filename,
+            save_as_recipe,
         )
 
         return {

py/nodes/utils.py

@@ -44,11 +44,29 @@ import folder_paths  # type: ignore
 logger = logging.getLogger(__name__)
 
 
+def get_lora_syntax_format():
+    try:
+        from ..services.settings_manager import get_settings_manager
+        return get_settings_manager().get("lora_syntax_format", "legacy")
+    except Exception:
+        return "legacy"
+
+
+def apply_lora_syntax_format(name):
+    fmt = get_lora_syntax_format()
+    if fmt == "legacy":
+        return name.replace("\\", "/").rstrip("/").split("/")[-1]
+    return name
+
+
 def extract_lora_name(lora_path):
-    """Extract the lora name from a lora path (e.g., 'IL\\aorunIllstrious.safetensors' -> 'aorunIllstrious')"""
+    normalized = lora_path.replace("\\", "/")
-    # Get the basename without extension
+    basename = os.path.basename(normalized)
-    basename = os.path.basename(lora_path)
+    name_no_ext = os.path.splitext(basename)[0]
-    return os.path.splitext(basename)[0]
+    dirname = os.path.dirname(normalized)
+    if dirname and dirname not in (".", "/") and not normalized.startswith("/"):
+        return apply_lora_syntax_format(f"{dirname}/{name_no_ext}")
+    return apply_lora_syntax_format(name_no_ext)
 
 
 def get_loras_list(kwargs):

py/nodes/wanvideo_lora_select.py

@@ -1,10 +1,22 @@
-import folder_paths # type: ignore
+import os
-from ..utils.utils import get_lora_info
+from ..utils.utils import get_lora_info_absolute
+from ..config import config
 from .utils import FlexibleOptionalInputType, any_type, get_loras_list
 import logging
 
 logger = logging.getLogger(__name__)
 
+
+def _relpath_within_loras(abs_path):
+    """Return abs_path relative to the first matching lora root, or basename as fallback."""
+    all_roots = list(config.loras_roots or []) + list(config.extra_loras_roots or [])
+    for root in all_roots:
+        try:
+            return os.path.relpath(abs_path, root)
+        except ValueError:
+            continue
+    return os.path.basename(abs_path)
+
 class WanVideoLoraSelectLM:
     NAME = "WanVideo Lora Select (LoraManager)"
     CATEGORY = "Lora Manager/stackers"
@@ -56,13 +68,13 @@ class WanVideoLoraSelectLM:
             clip_strength = float(lora.get('clipStrength', model_strength))
             
             # Get lora path and trigger words
-            lora_path, trigger_words = get_lora_info(lora_name)
+            lora_path, trigger_words = get_lora_info_absolute(lora_name)
             
             # Create lora item for WanVideo format
             lora_item = {
-                "path": folder_paths.get_full_path("loras", lora_path),
+                "path": lora_path,
                 "strength": model_strength,
-                "name": lora_path.split(".")[0],
+                "name": os.path.splitext(_relpath_within_loras(lora_path))[0],
                 "blocks": selected_blocks,
                 "layer_filter": layer_filter,
                 "low_mem_load": low_mem_load,

py/nodes/wanvideo_lora_select_from_text.py

@@ -1,11 +1,23 @@
-import folder_paths # type: ignore
+import os
-from ..utils.utils import get_lora_info
+from ..utils.utils import get_lora_info_absolute
+from ..config import config
 from .utils import any_type 
 import logging
 
 # 初始化日志记录器
 logger = logging.getLogger(__name__)
 
+
+def _relpath_within_loras(abs_path):
+    """Return abs_path relative to the first matching lora root, or basename as fallback."""
+    all_roots = list(config.loras_roots or []) + list(config.extra_loras_roots or [])
+    for root in all_roots:
+        try:
+            return os.path.relpath(abs_path, root)
+        except ValueError:
+            continue
+    return os.path.basename(abs_path)
+
 # 定义新节点的类
 class WanVideoLoraTextSelectLM:
     # 节点在UI中显示的名称
@@ -87,12 +99,12 @@ class WanVideoLoraTextSelectLM:
             else:
                 continue
 
-            lora_path, trigger_words = get_lora_info(lora_name_raw)
+            lora_path, trigger_words = get_lora_info_absolute(lora_name_raw)
 
             lora_item = {
-                "path": folder_paths.get_full_path("loras", lora_path),
+                "path": lora_path,
                 "strength": model_strength,
-                "name": lora_path.split(".")[0],
+                "name": os.path.splitext(_relpath_within_loras(lora_path))[0],
                 "blocks": selected_blocks,
                 "layer_filter": layer_filter,
                 "low_mem_load": low_mem_load,

py/recipes/base.py

@@ -7,7 +7,7 @@ import re
 from typing import Dict, List, Any, Optional, Tuple
 from abc import ABC, abstractmethod
 from ..config import config
-from ..utils.constants import VALID_LORA_TYPES
+from ..utils.constants import VALID_LORA_TYPES, VALID_CHECKPOINT_SUB_TYPES
 from ..utils.civitai_utils import rewrite_preview_url
 
 logger = logging.getLogger(__name__)
@@ -58,7 +58,50 @@ class RecipeMetadataParser(ABC):
             civitai_info, error_msg = civitai_info_tuple if isinstance(civitai_info_tuple, tuple) else (civitai_info_tuple, None)
             
             if not civitai_info or error_msg == "Model not found":
-                # Model not found or deleted
+                # CivitAI may fail to resolve a hash that is still being
+                # computed (known CivitAI issue). Before marking as deleted,
+                # try to reconcile with a local model that has the same
+                # filename and matching AutoV3 hash.
+                reconciled = False
+                file_name = lora_entry.get("file_name")
+                if file_name and recipe_scanner and hash_value:
+                    lora_scanner = getattr(recipe_scanner, "_lora_scanner", None)
+                    if lora_scanner:
+                        try:
+                            # Local import to avoid circular dependency:
+                            # base.py → file_utils → settings_manager → ...
+                            #  → recipe_scanner → enrichment → base.py
+                            from ..utils.file_utils import calculate_autov3  # fmt: skip
+                            cache = await lora_scanner.get_cached_data()
+                            for item in getattr(cache, "raw_data", []):
+                                if item.get("file_name") == file_name:
+                                    local_path = item.get("file_path")
+                                    if local_path and os.path.exists(local_path):
+                                        local_autov3 = calculate_autov3(local_path)
+                                        if local_autov3 and local_autov3 == hash_value:
+                                            lora_entry["existsLocally"] = True
+                                            lora_entry["localPath"] = local_path
+                                            lora_entry["hash"] = item.get("sha256", hash_value)
+                                            if "preview_url" in item:
+                                                lora_entry["thumbnailUrl"] = config.get_preview_static_url(item["preview_url"])
+                                            civ = item.get("civitai") or {}
+                                            if isinstance(civ, dict):
+                                                if civ.get("id") is not None:
+                                                    lora_entry["id"] = civ["id"]
+                                                if civ.get("modelId") is not None:
+                                                    lora_entry["modelId"] = civ["modelId"]
+                                                if civ.get("name"):
+                                                    lora_entry["version"] = civ["name"]
+                                                # model_name is the CivitAI model display
+                                                # name stored directly in the cache column.
+                                                cached_model_name = item.get("model_name")
+                                                if cached_model_name:
+                                                    lora_entry["name"] = cached_model_name
+                                            reconciled = True
+                                            break
+                        except Exception:
+                            pass
+                if not reconciled:
                     lora_entry['isDeleted'] = True
                     lora_entry['thumbnailUrl'] = '/loras_static/images/no-preview.png'
                 return lora_entry
@@ -173,6 +216,20 @@ class RecipeMetadataParser(ABC):
                 checkpoint['isDeleted'] = True
                 return checkpoint
 
+            # Validate that the model type is actually a checkpoint.
+            # Unlike populate_lora_from_civitai which has this check,
+            # this function was missing type validation — allowing LoRA
+            # version data to be saved as the recipe's checkpoint when the
+            # wrong version ID was passed downstream (fixed in v2.7+).
+            model_type = civitai_data.get('model', {}).get('type', '').lower()
+            if model_type not in VALID_CHECKPOINT_SUB_TYPES:
+                logger.warning(
+                    f"Cannot populate checkpoint: model version {civitai_data.get('id')} "
+                    f"has type '{model_type}', expected one of {VALID_CHECKPOINT_SUB_TYPES}. "
+                    f"Skipping checkpoint enrichment."
+                )
+                return checkpoint
+
             if 'model' in civitai_data and 'name' in civitai_data['model']:
                 checkpoint['name'] = civitai_data['model']['name']
 

py/recipes/enrichment.py

@@ -16,7 +16,9 @@ class RecipeEnricher:
     async def enrich_recipe(
         recipe: Dict[str, Any],
         civitai_client: Any,
-        request_params: Optional[Dict[str, Any]] = None
+        request_params: Optional[Dict[str, Any]] = None,
+        prefetched_civitai_meta_raw: Optional[Dict[str, Any]] = None,
+        prefetched_model_version_id: Optional[int] = None,
     ) -> bool:
         """
         Enrich a recipe dictionary in-place with metadata from Civitai and embedded params.
@@ -25,6 +27,9 @@ class RecipeEnricher:
             recipe: The recipe dictionary to enrich. Must have 'gen_params' initialized.
             civitai_client: Authenticated Civitai client instance.
             request_params: (Optional) Parameters from a user request (e.g. import).
+            prefetched_civitai_meta_raw: (Optional) Pre-fetched raw meta from Civitai
+                get_image_info, avoiding a duplicate API call.
+            prefetched_model_version_id: (Optional) Pre-fetched model version ID.
 
         Returns:
             bool: True if the recipe was modified, False otherwise.
@@ -32,21 +37,27 @@ class RecipeEnricher:
         updated = False
         gen_params = recipe.get("gen_params", {})
 
-        # 1. Fetch Civitai Info if available
+        # 1. Obtain Civitai metadata
         civitai_meta = None
-        model_version_id = None
+        model_version_id = prefetched_model_version_id
 
-        source_url = recipe.get("source_url") or recipe.get("source_path", "")
+        source_path = recipe.get("source_path", "")
 
-        # Check if it's a Civitai image URL
+        if prefetched_civitai_meta_raw is not None:
-        image_id = extract_civitai_image_id(str(source_url))
+            raw_meta = prefetched_civitai_meta_raw
+            if isinstance(raw_meta, dict):
+                if "meta" in raw_meta and isinstance(raw_meta["meta"], dict):
+                    civitai_meta = raw_meta["meta"]
+                else:
+                    civitai_meta = raw_meta
+        else:
+            image_id = extract_civitai_image_id(str(source_path))
             if image_id:
                 try:
                     image_info = await civitai_client.get_image_info(
-                    image_id, source_url=str(source_url)
+                        image_id, source_url=str(source_path)
                     )
                     if image_info:
-                    # Handle nested meta often found in Civitai API responses
                         raw_meta = image_info.get("meta")
                         if isinstance(raw_meta, dict):
                             if "meta" in raw_meta and isinstance(raw_meta["meta"], dict):
@@ -55,16 +66,15 @@ class RecipeEnricher:
                                 civitai_meta = raw_meta
 
                         model_version_id = image_info.get("modelVersionId")
+                except Exception as e:
+                    logger.warning(f"Failed to fetch Civitai image info: {e}")
 
-                    # If not at top level, check resources in meta
         if not model_version_id and civitai_meta:
             resources = civitai_meta.get("civitaiResources", [])
             for res in resources:
                 if res.get("type") == "checkpoint":
                     model_version_id = res.get("modelVersionId")
                     break
-            except Exception as e:
-                logger.warning(f"Failed to fetch Civitai image info: {e}")
 
         # 2. Merge Parameters
         # Priority: request_params > civitai_meta > embedded (existing gen_params)
@@ -180,25 +190,40 @@ class RecipeEnricher:
             existing_cp = recipe.get("checkpoint")
             if existing_cp is None:
                 existing_cp = {}
+
+            # Extract baseModel from raw civitai_info before populate_checkpoint_from_civitai
+            # (populate may reject non-checkpoint types and lose this data)
+            base_model_from_civitai: str = ""
+            if isinstance(civitai_info, dict):
+                base_model_from_civitai = civitai_info.get("baseModel", "") or ""
+            elif isinstance(civitai_info, tuple) and len(civitai_info) > 0 and isinstance(civitai_info[0], dict):
+                base_model_from_civitai = civitai_info[0].get("baseModel", "") or ""
+
             checkpoint_data = await RecipeMetadataParser.populate_checkpoint_from_civitai(existing_cp, civitai_info)
-            # 1. First, resolve base_model using full data before we format it away
+
+            # 1. Resolve base_model from checkpoint_data first, then fall back to raw civitai_info
             current_base_model = recipe.get("base_model")
-            resolved_base_model = checkpoint_data.get("baseModel")
+            resolved_base_model = checkpoint_data.get("baseModel") or base_model_from_civitai
             if resolved_base_model:
-                # Update if empty OR if it matches our generic prefix but is less specific
                 is_generic = not current_base_model or current_base_model.lower() in ["flux", "sdxl", "sd15"]
                 if is_generic and resolved_base_model != current_base_model:
                     recipe["base_model"] = resolved_base_model
 
-            # 2. Format according to requirements: type, modelId, modelVersionId, modelName, modelVersionName
+            # 2. Only format and save checkpoint if it has real data (not just type after type rejection)
+            has_checkpoint_data = any([
+                checkpoint_data.get("modelId"),
+                checkpoint_data.get("id") or checkpoint_data.get("modelVersionId"),
+                checkpoint_data.get("name"),
+                checkpoint_data.get("version"),
+            ])
+            if has_checkpoint_data:
                 formatted_checkpoint = {
                     "type": "checkpoint",
                     "modelId": checkpoint_data.get("modelId"),
                     "modelVersionId": checkpoint_data.get("id") or checkpoint_data.get("modelVersionId"),
-                "modelName": checkpoint_data.get("name"), # In base.py, 'name' is populated from civitai_data['model']['name']
+                    "modelName": checkpoint_data.get("name"),
-                "modelVersionName": checkpoint_data.get("version") # In base.py, 'version' is populated from civitai_data['name']
+                    "modelVersionName": checkpoint_data.get("version"),
                 }
-            # Remove None values
                 recipe["checkpoint"] = {k: v for k, v in formatted_checkpoint.items() if v is not None}
 
             return True

py/recipes/parsers/civitai_image.py

@@ -6,6 +6,7 @@ from typing import Dict, Any, Union
 from ..base import RecipeMetadataParser
 from ..constants import GEN_PARAM_KEYS
 from ...services.metadata_service import get_default_metadata_provider
+from ...config import config
 
 logger = logging.getLogger(__name__)
 
@@ -73,7 +74,8 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
         return False
 
     async def parse_metadata(  # type: ignore[override]
-        self, user_comment, recipe_scanner=None, civitai_client=None
+        self, user_comment, recipe_scanner=None, civitai_client=None,
+        local_cache: dict[str, Any] | None = None,
     ) -> Dict[str, Any]:
         """Parse metadata from Civitai image format
 
@@ -81,6 +83,8 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
             user_comment: The metadata from the image (dict)
             recipe_scanner: Optional recipe scanner service
             civitai_client: Optional Civitai API client (deprecated, use metadata_provider instead)
+            local_cache: Optional dict mapping sha256/autov3 hash → scanner cache item.
+                         When provided, matching models skip CivitAI API calls.
 
         Returns:
             Dict containing parsed recipe data
@@ -185,8 +189,77 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
             # Process standard resources array
             if "resources" in metadata and isinstance(metadata["resources"], list):
                 for resource in metadata["resources"]:
+                    resource_type = resource.get("type", "lora")
+
+                    # Track resources with type "model" — these are checkpoint models.
+                    # The resources array is the most reliable source for checkpoint
+                    # identification because it has an explicit type field and hash,
+                    # unlike modelVersionIds which is a flat list with no type info.
+                    if resource_type == "model":
+                        checkpoint_entry = {
+                            "id": 0,
+                            "modelId": 0,
+                            "name": resource.get("name", "Unknown Model"),
+                            "version": "",
+                            "type": resource.get("type", "model"),
+                            "existsLocally": False,
+                            "localPath": None,
+                            "file_name": resource.get("name", ""),
+                            "hash": resource.get("hash", "") or "",
+                            "thumbnailUrl": "/loras_static/images/no-preview.png",
+                            "baseModel": "",
+                            "size": 0,
+                            "downloadUrl": "",
+                            "isDeleted": False,
+                        }
+
+                        # Try to look up base model from the checkpoint hash
+                        cp_hash = checkpoint_entry.get("hash")
+                        if cp_hash and metadata_provider:
+                            local_cached = local_cache.get(cp_hash) if local_cache else None
+                            if local_cached:
+                                self._populate_entry_from_cache(
+                                    checkpoint_entry, local_cached
+                                )
+                                bm = checkpoint_entry.get("baseModel", "")
+                                if bm and not result["base_model"]:
+                                    result["base_model"] = bm
+                            else:
+                                try:
+                                    civitai_info = (
+                                        await metadata_provider.get_model_by_hash(
+                                            cp_hash
+                                        )
+                                    )
+                                    civitai_data, error_msg = (
+                                        (civitai_info, None)
+                                        if not isinstance(civitai_info, tuple)
+                                        else civitai_info
+                                    )
+                                    if civitai_data and error_msg != "Model not found":
+                                        if 'model' in civitai_data and 'name' in civitai_data['model']:
+                                            checkpoint_entry['name'] = civitai_data['model']['name']
+                                        checkpoint_entry['id'] = civitai_data.get('id', 0)
+                                        checkpoint_entry['modelId'] = civitai_data.get('modelId', 0)
+                                        if 'name' in civitai_data:
+                                            checkpoint_entry['version'] = civitai_data['name']
+                                        base_model = civitai_data.get('baseModel', '')
+                                        if base_model:
+                                            checkpoint_entry['baseModel'] = base_model
+                                            if not result['base_model']:
+                                                result['base_model'] = base_model
+                                except Exception as e:
+                                    logger.error(
+                                        f"Error fetching checkpoint info for hash "
+                                        f"{cp_hash}: {e}"
+                                    )
+
+                        if result["model"] is None:
+                            result["model"] = checkpoint_entry
+                        continue
+
                     # Modified to process resources without a type field as potential LoRAs
-                    if resource.get("type", "lora") == "lora":
+                    if resource_type == "lora":
                         lora_hash = resource.get("hash", "")
 
                         # Try to get hash from the hashes field if not present in resource
@@ -220,7 +293,18 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
                         }
 
                         # Try to get info from Civitai if hash is available
-                        if lora_entry["hash"] and metadata_provider:
+                        if lora_hash and metadata_provider:
+                            local_cached = local_cache.get(lora_hash) if local_cache else None
+                            if local_cached:
+                                self._populate_entry_from_cache(
+                                    lora_entry, local_cached
+                                )
+                                # Track by version ID for deduplication
+                                if lora_entry.get("id"):
+                                    added_loras[str(lora_entry["id"])] = len(
+                                        result["loras"]
+                                    )
+                            else:
                                 try:
                                     civitai_info = (
                                         await metadata_provider.get_model_by_hash(lora_hash)
@@ -625,3 +709,41 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
         except Exception as e:
             logger.error(f"Error parsing Civitai image metadata: {e}", exc_info=True)
             return {"error": str(e), "loras": []}
+
+    @staticmethod
+    def _populate_entry_from_cache(
+        entry: dict[str, Any],
+        cache_item: dict[str, Any],
+    ) -> None:
+        """Fill a lora/checkpoint entry from a scanner cache item.
+
+        Avoids CivitAI API calls for models that exist locally.
+        Mirrors the population logic in
+        ``RecipeMetadataParser.populate_lora_from_civitai()`` but operates
+        entirely on cached data.
+        """
+        civ = cache_item.get("civitai") or {}
+        if isinstance(civ, dict):
+            if civ.get("id") is not None:
+                entry["id"] = civ["id"]
+            if civ.get("modelId") is not None:
+                entry["modelId"] = civ["modelId"]
+            if civ.get("name"):
+                entry["version"] = civ["name"]
+            cached_name = cache_item.get("model_name")
+            if cached_name:
+                entry["name"] = cached_name
+        entry["existsLocally"] = True
+        local_path = cache_item.get("file_path")
+        if local_path:
+            entry["localPath"] = local_path
+        sha256 = cache_item.get("sha256")
+        if sha256:
+            entry["hash"] = sha256
+        if "preview_url" in cache_item:
+            entry["thumbnailUrl"] = config.get_preview_static_url(
+                cache_item["preview_url"]
+            )
+        base_model = cache_item.get("base_model", "")
+        if base_model:
+            entry["baseModel"] = base_model

py/routes/base_model_routes.py

@@ -251,7 +251,7 @@ class BaseModelRoutes(ABC):
 
     def _find_model_file(self, files):
         """Find the appropriate model file from the files list - can be overridden by subclasses."""
-        return next((file for file in files if file.get("type") == "Model" and file.get("primary") is True), None)
+        return next((file for file in files if file.get("type") in ("Model", "Diffusion Model") and file.get("primary") is True), None)
 
     def get_handler(self, name: str) -> Callable[[web.Request], web.StreamResponse]:
         """Expose handlers for subclasses or tests."""

py/routes/handlers/misc_handlers.py

@@ -33,15 +33,18 @@ from ...services.metadata_service import (
     update_metadata_providers,
 )
 from ...services.service_registry import ServiceRegistry
+from ...services.model_lifecycle_service import delete_model_artifacts
 from ...services.settings_manager import get_settings_manager
 from ...services.websocket_manager import ws_manager
 from ...services.downloader import get_downloader
 from ...services.errors import ResourceNotFoundError
 from ...services.cache_health_monitor import CacheHealthMonitor, CacheHealthStatus
+from ...utils.models import BaseModelMetadata
 from ...utils.constants import (
     CIVITAI_USER_MODEL_TYPES,
     DEFAULT_NODE_COLOR,
     NODE_TYPES,
+    PREVIEW_EXTENSIONS,
     SUPPORTED_MEDIA_EXTENSIONS,
     VALID_LORA_TYPES,
 )
@@ -617,6 +620,7 @@ class DoctorHandler:
             diagnostics = [
                 await self._check_civitai_api_key(),
                 await self._check_cache_health(),
+                await self._check_filename_conflicts(),
                 self._check_ui_version(client_version, app_version),
             ]
 
@@ -681,6 +685,148 @@ class DoctorHandler:
             status=status,
         )
 
+    async def resolve_filename_conflicts(self, request: web.Request) -> web.Response:
+        if self._settings.get("lora_syntax_format", "legacy") == "full":
+            return web.json_response({"success": True, "renamed": [], "count": 0})
+
+        renamed: list[dict[str, Any]] = []
+
+        try:
+            for model_type, label, factory in self._scanner_factories:
+                try:
+                    scanner = await factory()
+                    hash_index = getattr(scanner, "_hash_index", None)
+                    if hash_index is None:
+                        continue
+                    duplicates = {
+                        filename: list(paths)
+                        for filename, paths in hash_index.get_duplicate_filenames().items()
+                    }
+                    if not duplicates:
+                        continue
+
+                    cache = await scanner.get_cached_data()
+                    path_to_model = {m["file_path"]: m for m in cache.raw_data}
+
+                    used_basenames: set[str] = set()
+                    for paths in duplicates.values():
+                        if paths:
+                            used_basenames.add(
+                                os.path.splitext(os.path.basename(paths[0]))[0]
+                            )
+
+                    for filename, paths in duplicates.items():
+                        for idx, path in enumerate(paths):
+                            if idx == 0:
+                                continue
+                            dirname = os.path.dirname(path)
+                            base_name = os.path.splitext(os.path.basename(path))[0]
+                            ext = os.path.splitext(path)[1]
+                            if not ext:
+                                continue
+
+                            model_data = path_to_model.get(path)
+                            sha256 = (
+                                model_data.get("sha256", "") if model_data else ""
+                            )
+                            hash_provider = (
+                                lambda s=sha256: s if s else "0000"
+                            )
+
+                            new_filename = (
+                                BaseModelMetadata.generate_unique_filename(
+                                    dirname,
+                                    base_name,
+                                    ext,
+                                    hash_provider=hash_provider,
+                                )
+                            )
+
+                            candidate_base = os.path.splitext(new_filename)[0]
+                            counter = 1
+                            original_base = candidate_base
+                            while candidate_base in used_basenames:
+                                candidate_base = f"{original_base}-{counter}"
+                                new_filename = f"{candidate_base}{ext}"
+                                counter += 1
+                            used_basenames.add(candidate_base)
+
+                            new_path = os.path.join(dirname, new_filename)
+
+                            if new_filename == os.path.basename(path):
+                                continue
+
+                            if not os.path.exists(path):
+                                continue
+
+                            old_base_no_ext = os.path.splitext(path)[0]
+                            new_base_no_ext = (
+                                os.path.splitext(new_path)[0]
+                            )
+
+                            os.rename(path, new_path)
+
+                            for suffix in (".metadata.json", ".civitai.info"):
+                                old_sidecar = old_base_no_ext + suffix
+                                new_sidecar = new_base_no_ext + suffix
+                                if os.path.exists(old_sidecar):
+                                    os.rename(old_sidecar, new_sidecar)
+
+                            for preview_ext in PREVIEW_EXTENSIONS:
+                                old_preview = old_base_no_ext + preview_ext
+                                new_preview = new_base_no_ext + preview_ext
+                                if os.path.exists(old_preview):
+                                    os.rename(old_preview, new_preview)
+
+                            entry = path_to_model.get(path)
+                            if entry:
+                                entry = dict(entry)
+                                entry["file_name"] = os.path.splitext(new_filename)[0]
+                                if entry.get("preview_url"):
+                                    old_preview_url = entry["preview_url"].replace("\\", "/")
+                                    preview_ext = os.path.splitext(old_preview_url)[1]
+                                    if preview_ext:
+                                        entry["preview_url"] = (new_base_no_ext + preview_ext).replace(os.sep, "/")
+                                await scanner.update_single_model_cache(
+                                    path, new_path, entry
+                                )
+
+                            logger.info(
+                                "Resolved duplicate filename '%s': "
+                                "renamed '%s' to '%s'",
+                                filename,
+                                path,
+                                new_path,
+                            )
+                            renamed.append({
+                                "model_type": model_type,
+                                "label": label,
+                                "filename": filename,
+                                "old_path": path,
+                                "new_path": new_path,
+                                "new_filename": new_filename,
+                            })
+                except Exception as exc:  # pragma: no cover - defensive
+                    logger.error(
+                        "Failed to resolve filename conflicts for %s: %s",
+                        model_type,
+                        exc,
+                        exc_info=True,
+                    )
+
+            return web.json_response({
+                "success": True,
+                "renamed": renamed,
+                "count": len(renamed),
+            })
+        except Exception as exc:
+            logger.error(
+                "Error resolving filename conflicts: %s", exc, exc_info=True
+            )
+            return web.json_response(
+                {"success": False, "error": str(exc)}, status=500
+            )
+
     async def export_doctor_bundle(self, request: web.Request) -> web.Response:
         try:
             payload = await request.json()
@@ -846,6 +992,111 @@ class DoctorHandler:
             "actions": [{"id": "repair-cache", "label": "Rebuild Cache"}],
         }
 
+    async def _check_filename_conflicts(self) -> dict[str, Any]:
+        # When full path syntax is active, duplicate filenames across subfolders
+        # are not ambiguous (<lora:subfolder/name:strength>), so skip the check.
+        if self._settings.get("lora_syntax_format", "legacy") == "full":
+            return {
+                "id": "filename_conflicts",
+                "title": "Duplicate Filename Conflicts",
+                "status": "ok",
+                "summary": "Full path syntax is active — duplicate filenames across folders are not ambiguous.",
+                "details": [],
+                "actions": [],
+            }
+
+        all_conflicts: list[dict[str, Any]] = []
+        total_conflict_groups = 0
+        total_conflict_files = 0
+
+        for model_type, label, factory in self._scanner_factories:
+            # Duplicate filename detection targets LoRAs which use basename-only
+            # syntax (<lora:name:strength>). Checkpoints/embeddings reference
+            # models via relative paths with extensions, so conflicts there would
+            # be false positives.
+            if model_type != "lora":
+                continue
+            try:
+                scanner = await factory()
+                hash_index = getattr(scanner, "_hash_index", None)
+                if hash_index is None:
+                    continue
+                duplicates = hash_index.get_duplicate_filenames()
+                if not duplicates:
+                    continue
+
+                total_conflict_groups += len(duplicates)
+                for filename, paths in duplicates.items():
+                    total_conflict_files += len(paths)
+                    all_conflicts.append({
+                        "model_type": model_type,
+                        "label": label,
+                        "filename": filename,
+                        "paths": paths,
+                    })
+            except Exception as exc:  # pragma: no cover - defensive
+                logger.error(
+                    "Doctor filename conflict check failed for %s: %s",
+                    model_type,
+                    exc,
+                    exc_info=True,
+                )
+
+        if not all_conflicts:
+            return {
+                "id": "filename_conflicts",
+                "title": "Duplicate Filename Conflicts",
+                "status": "ok",
+                "summary": "No duplicate filenames found across model directories.",
+                "details": [],
+                "actions": [],
+            }
+
+        summary = (
+            f"{total_conflict_groups} filename(s) shared by "
+            f"{total_conflict_files} files across your library. "
+            f"This causes ambiguity when loading LoRAs by name."
+        )
+        details: list[str | dict[str, Any]] = [
+            {
+                "conflict_groups": total_conflict_groups,
+                "total_conflict_files": total_conflict_files,
+            }
+        ]
+
+        # Show at most 5 conflict groups inline; note any remainder.
+        MAX_VISIBLE_CONFLICTS = 5
+        visible_conflicts = all_conflicts[:MAX_VISIBLE_CONFLICTS]
+        for conflict in visible_conflicts:
+            details.append(
+                f"'{conflict['filename']}' "
+                f"found in {len(conflict['paths'])} locations"
+            )
+
+        hidden_count = len(all_conflicts) - MAX_VISIBLE_CONFLICTS
+        if hidden_count > 0:
+            details.append(
+                f"...and {hidden_count} more duplicate filename group(s)"
+            )
+
+        return {
+            "id": "filename_conflicts",
+            "title": "Duplicate Filename Conflicts",
+            "status": "warning",
+            "summary": summary,
+            "details": details,
+            "actions": [
+                {
+                    "id": "resolve-filename-conflicts",
+                    "label": "Resolve Conflicts",
+                },
+                {
+                    "id": "open-settings-syntax-format",
+                    "label": "Switch to Full Path Syntax",
+                },
+            ],
+        }
+
     def _check_ui_version(self, client_version: str, app_version: str) -> dict[str, Any]:
         if client_version and client_version != app_version:
             return {
@@ -1576,15 +1827,19 @@ class ModelLibraryHandler:
                     exists = True
                     model_type = "embedding"
 
+                if exists:
+                    return web.json_response(
+                        {
+                            "success": True,
+                            "exists": True,
+                            "modelType": model_type,
+                            "hasBeenDownloaded": False,
+                        }
+                    )
+
                 history_service = await self._get_download_history_service()
                 has_been_downloaded = False
-                history_type = model_type
+                history_type = None
-                if history_type:
-                    has_been_downloaded = await history_service.has_been_downloaded(
-                        history_type,
-                        model_version_id,
-                    )
-                else:
                 for candidate_type in ("lora", "checkpoint", "embedding"):
                     if await history_service.has_been_downloaded(
                         candidate_type,
@@ -1597,8 +1852,8 @@ class ModelLibraryHandler:
                 return web.json_response(
                     {
                         "success": True,
-                        "exists": exists,
+                        "exists": False,
-                        "modelType": model_type if exists else history_type,
+                        "modelType": history_type,
                         "hasBeenDownloaded": has_been_downloaded,
                     }
                 )
@@ -1618,29 +1873,35 @@ class ModelLibraryHandler:
             model_type = None
             versions = []
             downloaded_version_ids = []
-            history_service = await self._get_download_history_service()
             if lora_versions:
-                model_type = "lora"
+                return web.json_response(
-                versions = self._with_downloaded_flag(lora_versions)
+                    {
-                downloaded_version_ids = await history_service.get_downloaded_version_ids(
+                        "success": True,
-                    model_type,
+                        "modelType": "lora",
-                    model_id,
+                        "versions": self._with_downloaded_flag(lora_versions),
+                        "downloadedVersionIds": [],
+                    }
                 )
-            elif checkpoint_versions:
+            if checkpoint_versions:
-                model_type = "checkpoint"
+                return web.json_response(
-                versions = self._with_downloaded_flag(checkpoint_versions)
+                    {
-                downloaded_version_ids = await history_service.get_downloaded_version_ids(
+                        "success": True,
-                    model_type,
+                        "modelType": "checkpoint",
-                    model_id,
+                        "versions": self._with_downloaded_flag(checkpoint_versions),
+                        "downloadedVersionIds": [],
+                    }
                 )
-            elif embedding_versions:
+            if embedding_versions:
-                model_type = "embedding"
+                return web.json_response(
-                versions = self._with_downloaded_flag(embedding_versions)
+                    {
-                downloaded_version_ids = await history_service.get_downloaded_version_ids(
+                        "success": True,
-                    model_type,
+                        "modelType": "embedding",
-                    model_id,
+                        "versions": self._with_downloaded_flag(embedding_versions),
+                        "downloadedVersionIds": [],
+                    }
                 )
-            else:
+
+            history_service = await self._get_download_history_service()
             for candidate_type in ("lora", "checkpoint", "embedding"):
                 candidate_downloaded_version_ids = (
                     await history_service.get_downloaded_version_ids(
@@ -1665,6 +1926,86 @@ class ModelLibraryHandler:
             logger.error("Failed to check model existence: %s", exc, exc_info=True)
             return web.json_response({"success": False, "error": str(exc)}, status=500)
 
+    async def check_models_exist(self, request: web.Request) -> web.Response:
+        try:
+            model_ids_raw = request.query.get("modelIds", "")
+            if not model_ids_raw:
+                return web.json_response(
+                    {"success": True, "results": []}
+                )
+
+            raw_ids = model_ids_raw.split(",")
+            seen: set[int] = set()
+            model_ids: list[int] = []
+            for raw in raw_ids:
+                stripped = raw.strip()
+                if not stripped:
+                    continue
+                try:
+                    mid = int(stripped)
+                except ValueError:
+                    continue
+                if mid not in seen:
+                    seen.add(mid)
+                    model_ids.append(mid)
+
+            if not model_ids:
+                return web.json_response(
+                    {"success": True, "results": []}
+                )
+
+            lora_scanner = await self._service_registry.get_lora_scanner()
+            checkpoint_scanner = await self._service_registry.get_checkpoint_scanner()
+            embedding_scanner = await self._service_registry.get_embedding_scanner()
+
+            results: list[dict] = []
+            for model_id in model_ids:
+                lora_versions = await lora_scanner.get_model_versions_by_id(model_id)
+                if lora_versions:
+                    results.append({
+                        "modelId": model_id,
+                        "modelType": "lora",
+                        "versions": self._with_downloaded_flag(lora_versions),
+                        "downloadedVersionIds": [],
+                    })
+                    continue
+
+                if checkpoint_scanner:
+                    checkpoint_versions = await checkpoint_scanner.get_model_versions_by_id(model_id)
+                    if checkpoint_versions:
+                        results.append({
+                            "modelId": model_id,
+                            "modelType": "checkpoint",
+                            "versions": self._with_downloaded_flag(checkpoint_versions),
+                            "downloadedVersionIds": [],
+                        })
+                        continue
+
+                if embedding_scanner:
+                    embedding_versions = await embedding_scanner.get_model_versions_by_id(model_id)
+                    if embedding_versions:
+                        results.append({
+                            "modelId": model_id,
+                            "modelType": "embedding",
+                            "versions": self._with_downloaded_flag(embedding_versions),
+                            "downloadedVersionIds": [],
+                        })
+                        continue
+
+                results.append({
+                    "modelId": model_id,
+                    "modelType": None,
+                    "versions": [],
+                    "downloadedVersionIds": [],
+                })
+
+            return web.json_response(
+                {"success": True, "results": results}
+            )
+        except Exception as exc:
+            logger.error("Failed to check models existence: %s", exc, exc_info=True)
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
     async def get_model_version_download_status(
         self, request: web.Request
     ) -> web.Response:
@@ -1759,7 +2100,7 @@ class ModelLibraryHandler:
                     file_path=file_path if isinstance(file_path, str) else None,
                 )
             else:
-                await history_service.mark_not_downloaded(model_type, model_version_id)
+                await history_service.mark_as_deleted(model_type, model_version_id)
 
             return web.json_response(
                 {
@@ -1777,6 +2118,89 @@ class ModelLibraryHandler:
             )
             return web.json_response({"success": False, "error": str(exc)}, status=500)
 
+    async def delete_model_version(self, request: web.Request) -> web.Response:
+        try:
+            model_version_id_str = request.query.get("modelVersionId")
+            if not model_version_id_str:
+                return web.json_response(
+                    {"success": False, "error": "Missing required parameter: modelVersionId"},
+                    status=400,
+                )
+            try:
+                model_version_id = int(model_version_id_str)
+            except ValueError:
+                return web.json_response(
+                    {"success": False, "error": "Parameter modelVersionId must be an integer"},
+                    status=400,
+                )
+
+            lora_scanner = await self._service_registry.get_lora_scanner()
+            checkpoint_scanner = await self._service_registry.get_checkpoint_scanner()
+            embedding_scanner = await self._service_registry.get_embedding_scanner()
+
+            found_type = None
+            file_path = None
+            found_cache = None
+
+            for model_type, scanner in (
+                ("lora", lora_scanner),
+                ("checkpoint", checkpoint_scanner),
+                ("embedding", embedding_scanner),
+            ):
+                cache = await scanner.get_cached_data()
+                if cache and model_version_id in cache.version_index:
+                    found_type = model_type
+                    found_cache = cache
+                    entry = cache.version_index[model_version_id]
+                    file_path = entry.get("file_path")
+                    break
+
+            if not file_path:
+                return web.json_response(
+                    {"success": False, "error": "Model version not found in any scanner cache"},
+                    status=404,
+                )
+
+            target_dir = os.path.dirname(file_path)
+            base_name = os.path.basename(file_path)
+            file_name, extension = os.path.splitext(base_name)
+            await delete_model_artifacts(target_dir, file_name, main_extension=extension)
+
+            if found_cache:
+                found_cache.raw_data = [
+                    item
+                    for item in found_cache.raw_data
+                    if item.get("file_path") != file_path
+                ]
+                await found_cache.resort()
+
+            scanner_map = {
+                "lora": lora_scanner,
+                "checkpoint": checkpoint_scanner,
+                "embedding": embedding_scanner,
+            }
+            scanner = scanner_map.get(found_type)
+            if scanner:
+                persist = getattr(scanner, "_persist_current_cache", None)
+                if callable(persist):
+                    await persist()
+
+            history_service = await self._get_download_history_service()
+            await history_service.mark_as_deleted(found_type, model_version_id)
+
+            return web.json_response(
+                {
+                    "success": True,
+                    "modelType": found_type,
+                    "modelVersionId": model_version_id,
+                }
+            )
+        except Exception as exc:
+            logger.error(
+                "Failed to delete model version: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
     async def get_model_versions_status(self, request: web.Request) -> web.Response:
         try:
             model_id_str = request.query.get("modelId")
@@ -2662,6 +3086,7 @@ class NodeRegistryHandler:
             data = await request.json()
             widget_name = data.get("widget_name")
             value = data.get("value")
+            mode = data.get("mode", "replace")
             node_ids = data.get("node_ids")
 
             if not isinstance(widget_name, str) or not widget_name:
@@ -2709,6 +3134,7 @@ class NodeRegistryHandler:
                     "id": parsed_node_id,
                     "widget_name": widget_name,
                     "value": value,
+                    "mode": mode,
                 }
 
                 if graph_identifier is not None:
@@ -2796,6 +3222,7 @@ class MiscHandlerSet:
             "update_settings": self.settings.update_settings,
             "get_doctor_diagnostics": self.doctor.get_doctor_diagnostics,
             "repair_doctor_cache": self.doctor.repair_doctor_cache,
+            "resolve_doctor_filename_conflicts": self.doctor.resolve_filename_conflicts,
             "export_doctor_bundle": self.doctor.export_doctor_bundle,
             "get_priority_tags": self.settings.get_priority_tags,
             "get_settings_libraries": self.settings.get_libraries,
@@ -2809,8 +3236,10 @@ class MiscHandlerSet:
             "update_node_widget": self.node_registry.update_node_widget,
             "get_registry": self.node_registry.get_registry,
             "check_model_exists": self.model_library.check_model_exists,
+            "check_models_exist": self.model_library.check_models_exist,
             "get_model_version_download_status": self.model_library.get_model_version_download_status,
             "set_model_version_download_status": self.model_library.set_model_version_download_status,
+            "delete_model_version": self.model_library.delete_model_version,
             "get_civitai_user_models": self.model_library.get_civitai_user_models,
             "download_metadata_archive": self.metadata_archive.download_metadata_archive,
             "remove_metadata_archive": self.metadata_archive.remove_metadata_archive,

py/routes/handlers/model_handlers.py

@@ -37,6 +37,7 @@ from ...services.use_cases import (
 )
 from ...services.websocket_manager import WebSocketManager
 from ...services.websocket_progress_callback import WebSocketProgressCallback
+from ...services.download_queue_service import DownloadQueueService
 from ...services.errors import RateLimitError, ResourceNotFoundError
 from ...utils.civitai_utils import resolve_license_payload
 from ...utils.file_utils import calculate_sha256
@@ -301,6 +302,15 @@ class ModelListingHandler:
         for tag in exclude_tags:
             if tag:
                 tag_filters[tag] = "exclude"
+
+        auto_tag_filters: Dict[str, str] = {}
+        for tag in request.query.getall("auto_tag_include", []):
+            if tag:
+                auto_tag_filters[tag] = "include"
+        for tag in request.query.getall("auto_tag_exclude", []):
+            if tag:
+                auto_tag_filters[tag] = "exclude"
+
         favorites_only = request.query.get("favorites_only", "false").lower() == "true"
 
         search_options = {
@@ -367,6 +377,7 @@ class ModelListingHandler:
             "fuzzy_search": fuzzy_search,
             "base_models": base_models,
             "tags": tag_filters,
+            "auto_tags": auto_tag_filters,
             "tag_logic": tag_logic,
             "search_options": search_options,
             "hash_filters": hash_filters,
@@ -778,7 +789,7 @@ class ModelManagementHandler:
 
             metadata_updates = {k: v for k, v in data.items() if k != "file_path"}
 
-            await self._metadata_sync.save_metadata_updates(
+            updated_metadata = await self._metadata_sync.save_metadata_updates(
                 file_path=file_path,
                 updates=metadata_updates,
                 metadata_loader=self._metadata_sync.load_local_metadata,
@@ -789,7 +800,12 @@ class ModelManagementHandler:
                 cache = await self._service.scanner.get_cached_data()
                 await cache.resort()
 
-            return web.json_response({"success": True})
+            from ...services.auto_tag_service import extract_auto_tags
+            auto_tags = extract_auto_tags(updated_metadata)
+
+            return web.json_response(
+                {"success": True, "auto_tags": auto_tags}
+            )
         except Exception as exc:
             self._logger.error("Error saving metadata: %s", exc, exc_info=True)
             return web.Response(text=str(exc), status=500)
@@ -806,14 +822,16 @@ class ModelManagementHandler:
             if not isinstance(new_tags, list):
                 return web.Response(text="Tags must be a list", status=400)
 
-            tags = await self._tag_update_service.add_tags(
+            tags, auto_tags = await self._tag_update_service.add_tags(
                 file_path=file_path,
                 new_tags=new_tags,
                 metadata_loader=self._metadata_sync.load_local_metadata,
                 update_cache=self._service.scanner.update_single_model_cache,
             )
 
-            return web.json_response({"success": True, "tags": tags})
+            return web.json_response(
+                {"success": True, "tags": tags, "auto_tags": auto_tags}
+            )
         except Exception as exc:
             self._logger.error("Error adding tags: %s", exc, exc_info=True)
             return web.Response(text=str(exc), status=500)
@@ -1160,6 +1178,12 @@ class ModelQueryHandler:
 
     async def find_filename_conflicts(self, request: web.Request) -> web.Response:
         try:
+            settings = get_settings_manager()
+            if settings.get("lora_syntax_format", "legacy") == "full":
+                return web.json_response(
+                    {"success": True, "conflicts": [], "count": 0}
+                )
+
             duplicates = self._service.find_duplicate_filenames()
             result = []
             cache = await self._service.scanner.get_cached_data()
@@ -1449,6 +1473,21 @@ class ModelDownloadHandler:
             )
             return web.Response(status=500, text=str(exc))
 
+    async def skip_download_get(self, request: web.Request) -> web.Response:
+        try:
+            download_id = request.query.get("download_id")
+            if not download_id:
+                return web.json_response(
+                    {"success": False, "error": "Download ID is required"}, status=400
+                )
+            result = await self._download_coordinator.skip_download(download_id)
+            return web.json_response(result)
+        except Exception as exc:
+            self._logger.error(
+                "Error skipping download via GET: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
     async def cancel_download_get(self, request: web.Request) -> web.Response:
         try:
             download_id = request.query.get("download_id")
@@ -1529,6 +1568,258 @@ class ModelDownloadHandler:
             )
             return web.json_response({"success": False, "error": str(exc)}, status=500)
 
+    # ------------------------------------------------------------------
+    # Download queue / history handlers
+    # ------------------------------------------------------------------
+
+    async def get_download_queue(self, request: web.Request) -> web.Response:
+        try:
+            service = await DownloadQueueService.get_instance()
+            queue = await service.get_queue()
+            stats = await service.get_stats()
+            return web.json_response({"success": True, "queue": queue, "stats": stats})
+        except Exception as exc:
+            self._logger.error(
+                "Error getting download queue: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def add_to_download_queue(self, request: web.Request) -> web.Response:
+        try:
+            import uuid
+
+            download_id = request.query.get("download_id") or str(uuid.uuid4())
+            model_id_str = request.query.get("model_id")
+            model_version_id_str = request.query.get("model_version_id")
+            model_name = request.query.get("model_name", "")
+            version_name = request.query.get("version_name", "")
+            thumbnail_url = request.query.get("thumbnail_url", "")
+            source = request.query.get("source")
+            file_params_json = request.query.get("file_params")
+
+            model_id = int(model_id_str) if model_id_str else None
+            model_version_id = int(model_version_id_str) if model_version_id_str else None
+            file_params = json.loads(file_params_json) if file_params_json else None
+
+            service = await DownloadQueueService.get_instance()
+            item = await service.add_to_queue(
+                download_id=download_id,
+                model_id=model_id,
+                model_version_id=model_version_id,
+                model_name=model_name,
+                version_name=version_name,
+                thumbnail_url=thumbnail_url,
+                source=source,
+                file_params=file_params,
+            )
+            return web.json_response({"success": True, "item": item})
+        except Exception as exc:
+            self._logger.error(
+                "Error adding to download queue: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def remove_from_download_queue(self, request: web.Request) -> web.Response:
+        try:
+            download_id = request.query.get("download_id")
+            if not download_id:
+                return web.json_response(
+                    {"success": False, "error": "download_id is required"}, status=400
+                )
+
+            service = await DownloadQueueService.get_instance()
+            removed = await service.remove_from_queue(download_id)
+            return web.json_response({"success": removed})
+        except Exception as exc:
+            self._logger.error(
+                "Error removing from download queue: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def move_queue_item_to_top(self, request: web.Request) -> web.Response:
+        try:
+            download_id = request.query.get("download_id")
+            if not download_id:
+                return web.json_response(
+                    {"success": False, "error": "download_id is required"}, status=400
+                )
+
+            service = await DownloadQueueService.get_instance()
+            moved = await service.move_to_top(download_id)
+            return web.json_response({"success": moved})
+        except Exception as exc:
+            self._logger.error(
+                "Error moving queue item to top: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def move_queue_item_to_end(self, request: web.Request) -> web.Response:
+        try:
+            download_id = request.query.get("download_id")
+            if not download_id:
+                return web.json_response(
+                    {"success": False, "error": "download_id is required"}, status=400
+                )
+
+            service = await DownloadQueueService.get_instance()
+            moved = await service.move_to_end(download_id)
+            return web.json_response({"success": moved})
+        except Exception as exc:
+            self._logger.error(
+                "Error moving queue item to end: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def clear_download_queue(self, request: web.Request) -> web.Response:
+        try:
+            status_filter = request.query.get("status") or None
+            service = await DownloadQueueService.get_instance()
+            cleared = await service.clear_queue(status_filter=status_filter)
+            return web.json_response({"success": True, "cleared": cleared})
+        except Exception as exc:
+            self._logger.error(
+                "Error clearing download queue: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def get_download_history(self, request: web.Request) -> web.Response:
+        try:
+            limit = min(int(request.query.get("limit", "50")), 500)
+            offset = int(request.query.get("offset", "0"))
+            status_filter = request.query.get("status") or None
+            service = await DownloadQueueService.get_instance()
+            result = await service.get_history(
+                limit=limit, offset=offset, status_filter=status_filter
+            )
+            return web.json_response(
+                {
+                    "success": True,
+                    "items": result["items"],
+                    "total": result["total"],
+                    "limit": result["limit"],
+                    "offset": result["offset"],
+                }
+            )
+        except Exception as exc:
+            self._logger.error(
+                "Error getting download history: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def clear_download_history(self, request: web.Request) -> web.Response:
+        try:
+            status_filter = request.query.get("status") or None
+            service = await DownloadQueueService.get_instance()
+            cleared = await service.clear_history(status_filter=status_filter)
+            return web.json_response({"success": True, "cleared": cleared})
+        except Exception as exc:
+            self._logger.error(
+                "Error clearing download history: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def delete_download_history_item(self, request: web.Request) -> web.Response:
+        try:
+            item_id = int(request.query.get("id", "0"))
+            if not item_id:
+                return web.json_response(
+                    {"success": False, "error": "id is required"}, status=400
+                )
+
+            service = await DownloadQueueService.get_instance()
+            deleted = await service.delete_history_item(item_id)
+            return web.json_response({"success": deleted})
+        except Exception as exc:
+            self._logger.error(
+                "Error deleting download history item: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def retry_download_from_history(self, request: web.Request) -> web.Response:
+        try:
+            item_id = int(request.query.get("id", "0"))
+            if not item_id:
+                return web.json_response(
+                    {"success": False, "error": "id is required"}, status=400
+                )
+
+            service = await DownloadQueueService.get_instance()
+            item = await service.retry_from_history(item_id)
+            if item is None:
+                return web.json_response(
+                    {"success": False, "error": "History item not found or not retryable"},
+                    status=404,
+                )
+            return web.json_response({"success": True, "item": item})
+        except Exception as exc:
+            self._logger.error(
+                "Error retrying download from history: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def retry_all_failed_downloads(self, request: web.Request) -> web.Response:
+        try:
+            service = await DownloadQueueService.get_instance()
+            retry_count = await service.retry_all_failed()
+            return web.json_response({"success": True, "retry_count": retry_count})
+        except Exception as exc:
+            self._logger.error(
+                "Error retrying all failed downloads: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def complete_download_in_queue(self, request: web.Request) -> web.Response:
+        """Atomically move a download from queue to history with terminal status."""
+        try:
+            download_id = request.query.get("download_id")
+            if not download_id:
+                return web.json_response(
+                    {"success": False, "error": "download_id is required"}, status=400
+                )
+            status = request.query.get("status", "completed")
+            error = request.query.get("error")
+            file_path = request.query.get("file_path")
+            try:
+                bytes_downloaded = int(request.query.get("bytes_downloaded", "0"))
+            except (TypeError, ValueError):
+                bytes_downloaded = 0
+            total_bytes_raw = request.query.get("total_bytes")
+            total_bytes = int(total_bytes_raw) if total_bytes_raw else None
+            completed_at_raw = request.query.get("completed_at")
+            completed_at = float(completed_at_raw) if completed_at_raw else None
+
+            service = await DownloadQueueService.get_instance()
+            item = await service.complete_download(
+                download_id=download_id,
+                status=status,
+                error=error,
+                file_path=file_path,
+                bytes_downloaded=bytes_downloaded,
+                total_bytes=total_bytes,
+                completed_at=completed_at,
+            )
+            if item is None:
+                return web.json_response(
+                    {"success": False, "error": "Download not found in queue"}, status=404
+                )
+            return web.json_response({"success": True, "item": item})
+        except Exception as exc:
+            self._logger.error(
+                "Error completing download: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
+    async def get_download_stats(self, request: web.Request) -> web.Response:
+        try:
+            service = await DownloadQueueService.get_instance()
+            stats = await service.get_stats()
+            return web.json_response({"success": True, "stats": stats})
+        except Exception as exc:
+            self._logger.error(
+                "Error getting download stats: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
 
 class ModelCivitaiHandler:
     """CivitAI integration endpoints."""
@@ -1937,6 +2228,10 @@ class ModelUpdateHandler:
         if target_model_ids:
             target_model_ids = sorted(set(target_model_ids))
 
+        folder_path: Optional[str] = payload.get("folder_path")
+        if folder_path is not None and not isinstance(folder_path, str):
+            folder_path = None
+
         provider = await self._get_civitai_provider()
         if provider is None:
             return web.json_response(
@@ -1951,6 +2246,7 @@ class ModelUpdateHandler:
                 provider,
                 force_refresh=force_refresh,
                 target_model_ids=target_model_ids or None,
+                folder_path=folder_path,
             )
             if self._service.scanner.is_cancelled():
                 return web.json_response(
@@ -1973,10 +2269,21 @@ class ModelUpdateHandler:
             self._logger.error("Failed to refresh model updates: %s", exc, exc_info=True)
             return web.json_response({"success": False, "error": str(exc)}, status=500)
 
+        hide_early_access = False
+        if self._settings is not None:
+            try:
+                hide_early_access = bool(
+                    self._settings.get("hide_early_access_updates", False)
+                )
+            except Exception:
+                pass
+
         serialized_records = []
         for record in records.values():
             has_update_fn = getattr(record, "has_update", None)
-            if callable(has_update_fn) and has_update_fn():
+            if callable(has_update_fn) and has_update_fn(
+                hide_early_access=hide_early_access
+            ):
                 serialized_records.append(self._serialize_record(record))
 
         return web.json_response(
@@ -2423,6 +2730,7 @@ class ModelUpdateHandler:
             "shouldIgnore": version.should_ignore,
             "earlyAccessEndsAt": version.early_access_ends_at,
             "isEarlyAccess": is_early_access,
+            "usageControl": version.usage_control,
             "filePath": context.get("file_path"),
             "fileName": context.get("file_name"),
         }
@@ -2537,9 +2845,23 @@ class ModelHandlerSet:
             "download_model": self.download.download_model,
             "download_model_get": self.download.download_model_get,
             "cancel_download_get": self.download.cancel_download_get,
+            "skip_download_get": self.download.skip_download_get,
             "pause_download_get": self.download.pause_download_get,
             "resume_download_get": self.download.resume_download_get,
             "get_download_progress": self.download.get_download_progress,
+            "get_download_queue": self.download.get_download_queue,
+            "add_to_download_queue": self.download.add_to_download_queue,
+            "remove_from_download_queue": self.download.remove_from_download_queue,
+            "move_queue_item_to_top": self.download.move_queue_item_to_top,
+            "move_queue_item_to_end": self.download.move_queue_item_to_end,
+            "clear_download_queue": self.download.clear_download_queue,
+            "get_download_history": self.download.get_download_history,
+            "clear_download_history": self.download.clear_download_history,
+            "delete_download_history_item": self.download.delete_download_history_item,
+            "retry_download_from_history": self.download.retry_download_from_history,
+            "retry_all_failed_downloads": self.download.retry_all_failed_downloads,
+            "complete_download_in_queue": self.download.complete_download_in_queue,
+            "get_download_stats": self.download.get_download_stats,
             "get_civitai_versions": self.civitai.get_civitai_versions,
             "get_civitai_model_by_version": self.civitai.get_civitai_model_by_version,
             "get_civitai_model_by_hash": self.civitai.get_civitai_model_by_hash,

py/routes/handlers/preview_handlers.py

@@ -3,6 +3,7 @@
 from __future__ import annotations
 
 import logging
+import mimetypes
 import urllib.parse
 from pathlib import Path
 
@@ -12,6 +13,12 @@ from ...config import config as global_config
 
 logger = logging.getLogger(__name__)
 
+_CHUNK_SIZE = 1024 * 1024  # 1 MB — balance between streaming iteration overhead and per-chunk memory
+
+# Video file extensions that bypass native sendfile on Windows
+# to avoid IOCP/ProactorEventLoop crashes during client disconnect.
+_VIDEO_EXTENSIONS = frozenset({".mp4", ".webm", ".mov", ".avi", ".mkv"})
+
 
 class PreviewHandler:
     """Serve preview assets for the active library at request time."""
@@ -48,8 +55,51 @@ class PreviewHandler:
             logger.debug("Preview file not found at %s", str(resolved))
             raise web.HTTPNotFound(text="Preview file not found")
 
-        # aiohttp's FileResponse handles range requests and content headers for us.
+        # aiohttp's FileResponse handles range requests, content headers, and
-        return web.FileResponse(path=resolved, chunk_size=256 * 1024)
+        # uses kernel sendfile (zero-copy DMA) on Linux/macOS. On Windows it
+        # uses IOCP-based _sendfile_native which can crash when the client
+        # disconnects mid-transfer during fast scrolling. The _stream_file()
+        # fallback is kept for a future compat toggle.
+        return web.FileResponse(path=resolved, chunk_size=_CHUNK_SIZE)
+
+    async def _stream_file(
+        self, request: web.Request, path: Path
+    ) -> web.StreamResponse:
+        """Stream a file chunk-by-chunk, bypassing native sendfile.
+
+        This avoids the Windows IOCP ``_sendfile_native`` crash that occurs
+        when the client disconnects during a large file transfer.
+        """
+        content_type, _ = mimetypes.guess_type(str(path))
+        if content_type is None:
+            content_type = "application/octet-stream"
+
+        file_size = path.stat().st_size
+        resp = web.StreamResponse()
+        resp.content_type = content_type
+        resp.content_length = file_size
+
+        # Allow browser caching: video previews rarely change during a session.
+        # The frontend already appends ?t={version} to bust cache on update.
+        resp.headers["Cache-Control"] = "public, max-age=86400"
+
+        await resp.prepare(request)
+
+        try:
+            with open(path, "rb") as f:
+                while True:
+                    chunk = f.read(_CHUNK_SIZE)
+                    if not chunk:
+                        break
+                    await resp.write(chunk)
+        except (ConnectionResetError, ConnectionAbortedError):
+            # Client disconnected during streaming — expected when scrolling
+            # rapidly through a library with animated previews.
+            pass
+        except OSError as exc:
+            logger.debug("I/O error streaming preview %s: %s", path, exc)
+
+        return resp
 
 
 __all__ = ["PreviewHandler"]

py/routes/misc_route_registrar.py

@@ -24,6 +24,7 @@ MISC_ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
     RouteDefinition("POST", "/api/lm/settings", "update_settings"),
     RouteDefinition("GET", "/api/lm/doctor/diagnostics", "get_doctor_diagnostics"),
     RouteDefinition("POST", "/api/lm/doctor/repair-cache", "repair_doctor_cache"),
+    RouteDefinition("POST", "/api/lm/doctor/resolve-filename-conflicts", "resolve_doctor_filename_conflicts"),
     RouteDefinition("POST", "/api/lm/doctor/export-bundle", "export_doctor_bundle"),
     RouteDefinition("GET", "/api/lm/priority-tags", "get_priority_tags"),
     RouteDefinition("GET", "/api/lm/settings/libraries", "get_settings_libraries"),
@@ -42,6 +43,7 @@ MISC_ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
     RouteDefinition("POST", "/api/lm/update-node-widget", "update_node_widget"),
     RouteDefinition("GET", "/api/lm/get-registry", "get_registry"),
     RouteDefinition("GET", "/api/lm/check-model-exists", "check_model_exists"),
+    RouteDefinition("GET", "/api/lm/check-models-exist", "check_models_exist"),
     RouteDefinition(
         "GET",
         "/api/lm/model-version-download-status",
@@ -89,6 +91,9 @@ MISC_ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
     RouteDefinition(
         "GET", "/api/lm/base-models/cache-status", "get_base_model_cache_status"
     ),
+    RouteDefinition(
+        "GET", "/api/lm/delete-model-version", "delete_model_version"
+    ),
 )
 
 

py/routes/model_route_registrar.py

@@ -101,11 +101,43 @@ COMMON_ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
     RouteDefinition("POST", "/api/lm/download-model", "download_model"),
     RouteDefinition("GET", "/api/lm/download-model-get", "download_model_get"),
     RouteDefinition("GET", "/api/lm/cancel-download-get", "cancel_download_get"),
+    RouteDefinition("GET", "/api/lm/skip-download", "skip_download_get"),
     RouteDefinition("GET", "/api/lm/pause-download", "pause_download_get"),
     RouteDefinition("GET", "/api/lm/resume-download", "resume_download_get"),
     RouteDefinition(
         "GET", "/api/lm/download-progress/{download_id}", "get_download_progress"
     ),
+    RouteDefinition("GET", "/api/lm/downloads/queue", "get_download_queue"),
+    RouteDefinition("GET", "/api/lm/downloads/queue/add", "add_to_download_queue"),
+    RouteDefinition(
+        "GET", "/api/lm/downloads/queue/remove", "remove_from_download_queue"
+    ),
+    RouteDefinition(
+        "GET", "/api/lm/downloads/queue/move-to-top", "move_queue_item_to_top"
+    ),
+    RouteDefinition(
+        "GET", "/api/lm/downloads/queue/move-to-end", "move_queue_item_to_end"
+    ),
+    RouteDefinition(
+        "GET", "/api/lm/downloads/queue/clear", "clear_download_queue"
+    ),
+    RouteDefinition("GET", "/api/lm/downloads/history", "get_download_history"),
+    RouteDefinition(
+        "GET", "/api/lm/downloads/history/clear", "clear_download_history"
+    ),
+    RouteDefinition(
+        "GET", "/api/lm/downloads/history/delete", "delete_download_history_item"
+    ),
+    RouteDefinition(
+        "GET", "/api/lm/downloads/history/retry", "retry_download_from_history"
+    ),
+    RouteDefinition(
+        "GET", "/api/lm/downloads/history/retry-all", "retry_all_failed_downloads"
+    ),
+    RouteDefinition("GET", "/api/lm/downloads/stats", "get_download_stats"),
+    RouteDefinition(
+        "GET", "/api/lm/downloads/queue/complete", "complete_download_in_queue"
+    ),
     RouteDefinition("POST", "/api/lm/{prefix}/cancel-task", "cancel_task"),
     RouteDefinition("GET", "/{prefix}", "handle_models_page"),
 )

py/routes/recipe_route_registrar.py

@@ -58,6 +58,7 @@ ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
     RouteDefinition("POST", "/api/lm/recipes/repair", "repair_recipes"),
     RouteDefinition("POST", "/api/lm/recipes/cancel-repair", "cancel_repair"),
     RouteDefinition("POST", "/api/lm/recipe/{recipe_id}/repair", "repair_recipe"),
+    RouteDefinition("POST", "/api/lm/recipes/repair-bulk", "repair_recipes_bulk"),
     RouteDefinition("GET", "/api/lm/recipes/repair-progress", "get_repair_progress"),
     RouteDefinition("POST", "/api/lm/recipes/batch-import/start", "start_batch_import"),
     RouteDefinition(
@@ -70,6 +71,16 @@ ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
         "POST", "/api/lm/recipes/batch-import/directory", "start_directory_import"
     ),
     RouteDefinition("POST", "/api/lm/recipes/browse-directory", "browse_directory"),
+    RouteDefinition(
+        "GET", "/api/lm/recipes/check-image-exists", "check_image_exists"
+    ),
+    RouteDefinition("GET", "/api/lm/recipes/import-from-url", "import_from_url"),
+    RouteDefinition(
+        "POST", "/api/lm/recipes/create-from-example", "create_from_example"
+    ),
+    RouteDefinition(
+        "POST", "/api/lm/recipe/{recipe_id}/reimport", "reimport_recipe"
+    ),
 )
 
 

py/routes/update_routes.py

@@ -1,7 +1,6 @@
 import os
 import logging
 import toml
-import git
 import zipfile
 import shutil
 import tempfile
@@ -11,6 +10,7 @@ from typing import Dict, List
 
 from ..utils.settings_paths import ensure_settings_file
 from ..services.downloader import get_downloader
+from ..services.service_registry import ServiceRegistry
 
 logger = logging.getLogger(__name__)
 
@@ -212,8 +212,19 @@ class UpdateRoutes:
 
             zip_path = tmp_zip_path
 
-            # Skip both settings.json, civitai and model cache folder
+            # Close the downloaded-versions SQLite connection before cleaning,
-            UpdateRoutes._clean_plugin_folder(plugin_root, skip_files=['settings.json', 'civitai', 'model_cache'])
+            # so that shutil.rmtree() does not fail on Windows (the process
+            # cannot delete a file with an outstanding open handle).
+            try:
+                history_svc = ServiceRegistry._services.get("downloaded_version_history_service")
+                if history_svc is not None:
+                    history_svc.close()
+                    logger.info("Closed downloaded-version history database connection")
+            except Exception:
+                logger.debug("Could not close downloaded-version history database", exc_info=True)
+
+            # Skip settings.json, civitai, model cache and runtime cache folders
+            UpdateRoutes._clean_plugin_folder(plugin_root, skip_files=['settings.json', 'civitai', 'model_cache', 'cache', 'wildcards', 'backups', 'stats'])
 
             # Extract ZIP to temp dir
             with tempfile.TemporaryDirectory() as tmp_dir:
@@ -222,16 +233,17 @@ class UpdateRoutes:
                     # Find extracted folder (GitHub ZIP contains a root folder)
                     extracted_root = next(os.scandir(tmp_dir)).path
 
-                    # Copy files, skipping settings.json and civitai folder
+                    # Copy files, skipping user data that should be preserved
+                    skip_items = {'settings.json', 'civitai', 'wildcards', 'backups', 'stats'}
                     for item in os.listdir(extracted_root):
-                        if item == 'settings.json' or item == 'civitai':
+                        if item in skip_items:
                             continue
                         src = os.path.join(extracted_root, item)
                         dst = os.path.join(plugin_root, item)
                         if os.path.isdir(src):
                             if os.path.exists(dst):
                                 shutil.rmtree(dst)
-                            shutil.copytree(src, dst, ignore=shutil.ignore_patterns('settings.json', 'civitai'))
+                            shutil.copytree(src, dst, ignore=shutil.ignore_patterns(*skip_items))
                         else:
                             shutil.copy2(src, dst)
 
@@ -239,15 +251,17 @@ class UpdateRoutes:
                     # for ComfyUI Manager to work properly
                     tracking_info_file = os.path.join(plugin_root, '.tracking')
                     tracking_files = []
+                    skip_tracked = {'civitai', 'wildcards', 'backups', 'stats'}
                     for root, dirs, files in os.walk(extracted_root):
-                        # Skip civitai folder and its contents
+                        # Skip user data directories and their contents
                         rel_root = os.path.relpath(root, extracted_root)
-                        if rel_root == 'civitai' or rel_root.startswith('civitai' + os.sep):
+                        top_dir = rel_root.split(os.sep)[0] if rel_root != '.' else ''
+                        if top_dir in skip_tracked:
                             continue
                         for file in files:
                             rel_path = os.path.relpath(os.path.join(root, file), extracted_root)
-                            # Skip settings.json and any file under civitai
+                            # Skip settings.json and any file under user data dirs
-                            if rel_path == 'settings.json' or rel_path.startswith('civitai' + os.sep):
+                            if rel_path == 'settings.json' or rel_path.split(os.sep)[0] in skip_tracked:
                                 continue
                             tracking_files.append(rel_path.replace("\\", "/"))
                     with open(tracking_info_file, "w", encoding='utf-8') as file:
@@ -342,6 +356,15 @@ class UpdateRoutes:
         Returns:
             tuple: (success, new_version)
         """
+        try:
+            import git
+        except ImportError:
+            logger.error(
+                "GitPython is not available: the git executable was not found in PATH. "
+                "Install git or set $GIT_PYTHON_GIT_EXECUTABLE to the git binary path."
+            )
+            return False, ""
+
         try:
             # Open the Git repository
             repo = git.Repo(plugin_root)
@@ -438,6 +461,7 @@ class UpdateRoutes:
             if not os.path.exists(os.path.join(plugin_root, '.git')):
                 return git_info
 
+            import git
             repo = git.Repo(plugin_root)
             commit = repo.head.commit
             git_info['commit_hash'] = commit.hexsha

py/services/aria2_downloader.py

@@ -14,12 +14,30 @@ from typing import Any, Dict, Optional, Tuple
 
 import aiohttp
 
-from .downloader import DownloadProgress, get_downloader
+from .downloader import DownloadProgress, get_downloader, is_ssl_cert_verify_error
 from .aria2_transfer_state import Aria2TransferStateStore
 from .settings_manager import get_settings_manager
 
 logger = logging.getLogger(__name__)
 
+def _try_certifi_ca_path() -> str | None:
+    """Return the certifi CA bundle path if available, else None."""
+    try:
+        import certifi  # type: ignore[import-untyped]
+
+        path = certifi.where()
+        if os.path.isfile(path):
+            logger.debug(
+                "aria2 --ca-certificate: using certifi CA bundle at %s", path
+            )
+            return path
+    except ImportError:
+        pass
+
+    logger.debug("aria2 --ca-certificate: certifi not available")
+    return None
+
+
 CIVITAI_DOWNLOAD_URL_PREFIXES = (
     "https://civitai.com/api/download/",
     "https://civitai.red/api/download/",
@@ -39,7 +57,7 @@ class Aria2Transfer:
 
 
 class Aria2Downloader:
-    """Manage an aria2 RPC daemon for experimental model downloads."""
+    """Manage an aria2 RPC daemon for recommended model downloads."""
 
     _instance = None
     _lock = asyncio.Lock()
@@ -391,6 +409,15 @@ class Aria2Downloader:
                     f"Failed to resolve authenticated Civitai redirect: status={response.status} body={body[:300]}"
                 )
         except aiohttp.ClientError as exc:
+            if is_ssl_cert_verify_error(exc):
+                logger.error(
+                    "SSL certificate verification failed during Civitai redirect "
+                    "resolution for %s. This is usually caused by an outdated CA "
+                    "certificate bundle. Recommended fixes:\n"
+                    "  1. pip install --upgrade certifi\n"
+                    "  2. pip install pip-system-certs",
+                    url,
+                )
             raise Aria2Error(
                 f"Failed to resolve authenticated Civitai redirect: {exc}"
             ) from exc
@@ -414,6 +441,11 @@ class Aria2Downloader:
                 f"--rpc-listen-port={self._rpc_port}",
                 f"--rpc-secret={self._rpc_secret}",
                 "--check-certificate=true",
+                # Point aria2 at certifi's CA bundle when available so it uses
+                # the same certificate store as Python downloads.
+                *((
+                    f"--ca-certificate={ca_cert}",
+                ) if (ca_cert := _try_certifi_ca_path()) else ()),
                 "--allow-overwrite=true",
                 "--auto-file-renaming=false",
                 "--file-allocation=none",

py/services/auto_tag_service.py

@@ -0,0 +1,139 @@
+"""
+Auto-tag extraction service for model cards.
+
+Extracts implicit model attributes (HIGH/LOW, I2V/T2V/TI2V, Lightning, Turbo)
+from filename, base_model, and CivitAI version name — no manual tagging required.
+"""
+
+from __future__ import annotations
+
+import re
+from typing import Dict, List, Set
+
+# ── Tag category definitions ──────────────────────────────────────────
+# Each category maps a display label to a regex pattern.
+# Patterns are case-insensitive and matched against filename, base_model,
+# and civitai version name.
+
+# Use (?<![a-zA-Z0-9]) and (?![a-zA-Z0-9]) instead of \b because
+# Python's \b treats underscore as a word character, so \bHIGH\b
+# won't match '_HIGH_' in filenames.
+_B = r"(?<![a-zA-Z0-9])"   # left boundary
+_E = r"(?![a-zA-Z0-9])"    # right boundary
+
+AUTO_TAG_CATEGORIES: Dict[str, str] = {
+    "HIGH":      _B + r"HIGH" + _E,
+    "LOW":       _B + r"(?<!F)LOW" + _E,
+    "I2V":       _B + r"I2V" + _E,
+    "T2V":       _B + r"T2V" + _E,
+    "TI2V":      _B + r"TI2V" + _E,
+    "Lightning": _B + r"Lightning" + _E,
+    "Turbo":     _B + r"Turbo" + _E,
+}
+
+# Tags that belong to the "mode" group (HIGH/LOW)
+MODE_TAGS = {"HIGH", "LOW"}
+
+# Tags that belong to the "video mode" group (I2V/T2V/TI2V)
+VIDEO_MODE_TAGS = {"I2V", "T2V", "TI2V"}
+
+# Tags that belong to the "speed/optimization" group
+SPEED_TAGS = {"Lightning", "Turbo"}
+
+# ── Display category groups (for settings UI) ─────────────────────────
+
+AUTO_TAG_GROUPS = {
+    "mode":   {"HIGH", "LOW"},
+    "video":  {"I2V", "T2V", "TI2V"},
+    "speed":  {"Lightning", "Turbo"},
+}
+
+# Default enabled categories
+DEFAULT_ENABLED_GROUPS = {"mode", "video"}
+
+
+def _collect_sources(model_data: Dict) -> List[str]:
+    """Collect all text sources from model data for tag matching."""
+    sources: List[str] = []
+
+    file_name = model_data.get("file_name", "")
+    if file_name:
+        sources.append(file_name)
+
+    base_model = model_data.get("base_model", "")
+    if base_model:
+        sources.append(base_model)
+
+    civitai = model_data.get("civitai", {})
+    if isinstance(civitai, dict):
+        version_name = civitai.get("name", "")
+        if version_name:
+            sources.append(version_name)
+
+    return sources
+
+
+def extract_auto_tags(model_data: Dict) -> List[str]:
+    """Extract auto-detected tags from model metadata.
+
+    Uses a two-layer approach:
+      Layer 1 — Regex-based detection against filename, base_model, and
+                CivitAI version name.
+      Layer 2 — Merge in any user-defined tags that overlap with known
+                auto-tag categories. This provides a manual fallback when
+                auto-detection fails (e.g. "I2V HN" or unlabeled models).
+
+    HIGH/LOW tags are only returned when the base_model indicates a Wan
+    family model — no other model architecture uses this distinction.
+
+    Args:
+        model_data: Model metadata dict with keys:
+            file_name, base_model, civitai (with optional 'name' field),
+            tags (user-defined tag list, used as fallback).
+
+    Returns:
+        Sorted list of unique auto-tag strings (e.g. ["I2V"]).
+    """
+    sources = _collect_sources(model_data)
+    base_model = model_data.get("base_model", "")
+    is_wan = "wan" in base_model.lower()
+
+    found: Set[str] = set()
+
+    # ── Layer 1: regex-based detection ────────────────────────────
+    if sources:
+        for label, pattern in AUTO_TAG_CATEGORIES.items():
+            # HIGH/LOW are Wan-specific — skip for non-Wan to avoid noise
+            if label in ("HIGH", "LOW"):
+                if not is_wan:
+                    continue
+                # Use case-insensitive character class + case-sensitive boundary,
+                # so "HighNoise" (camelCase) matches but "highlight" doesn't.
+                # Boundary: not followed by lowercase letter (= word has ended).
+                ci = "".join(f"[{c.lower()}{c.upper()}]" for c in label)
+                if label == "LOW":
+                    regex = re.compile(r"(?<![Ff])" + ci + r"(?![a-z])")
+                else:
+                    regex = re.compile(ci + r"(?![a-z])")
+            else:
+                regex = re.compile(pattern, re.IGNORECASE)
+            for source in sources:
+                if regex.search(source):
+                    found.add(label)
+                    break
+
+    # ── Layer 2: user-defined tags as manual fallback ─────────────
+    # When auto-detection fails (abbreviated names like "Hi"/"Lo",
+    # "I2V HN", or unlabeled models), users can add canonical tags
+    # (HIGH, LOW, I2V, etc.) to the model's regular tags for correct
+    # badge display and filtering. Matching is case-insensitive so
+    # "high"/"High"/"HIGH" all resolve to the canonical label.
+    user_tags = model_data.get("tags")
+    if user_tags:
+        label_map = {label.lower(): label for label in AUTO_TAG_CATEGORIES}
+        for t in user_tags:
+            canonical = label_map.get(t.lower())
+            if canonical:
+                found.add(canonical)
+
+    return sorted(found)

py/services/backup_service.py

@@ -141,6 +141,16 @@ class BackupService:
                     )
                 )
 
+        stats_path = os.path.join(get_settings_dir(create=True), "stats", "lora_manager_stats.json")
+        if os.path.exists(stats_path):
+            targets.append(
+                (
+                    "usage_stats",
+                    "stats/lora_manager_stats.json",
+                    stats_path,
+                )
+            )
+
         return targets
 
     @staticmethod
@@ -348,6 +358,8 @@ class BackupService:
         if kind == "model_update":
             filename = os.path.basename(archive_member)
             return str(Path(get_cache_file_path(CacheType.MODEL_UPDATE, create_dir=True)).parent / filename)
+        if kind == "usage_stats":
+            return os.path.join(get_settings_dir(create=True), "stats", "lora_manager_stats.json")
         return None
 
     async def create_auto_snapshot_if_due(self) -> Optional[dict[str, Any]]:

py/services/base_model_service.py

@@ -77,6 +77,7 @@ class BaseModelService(ABC):
         base_models: list = None,
         model_types: list = None,
         tags: Optional[Dict[str, str]] = None,
+        auto_tags: Optional[Dict[str, str]] = None,
         search_options: dict = None,
         hash_filters: dict = None,
         favorites_only: bool = False,
@@ -95,6 +96,11 @@ class BaseModelService(ABC):
             sorted_data = await self._fetch_with_usage_sort(sort_params)
         else:
             sorted_data = await self.cache_repository.fetch_sorted(sort_params)
+        # Pre-compute auto_tags for every item — needed for both filtering
+        # and display. Computation is cheap (string regex on 2-3 fields).
+        from .auto_tag_service import extract_auto_tags
+        for item in sorted_data:
+            item["auto_tags"] = extract_auto_tags(item)
         fetch_duration = time.perf_counter() - t0
         initial_count = len(sorted_data)
 
@@ -110,6 +116,7 @@ class BaseModelService(ABC):
                 base_models=base_models,
                 model_types=model_types,
                 tags=tags,
+                auto_tags=auto_tags,
                 favorites_only=favorites_only,
                 search_options=search_options,
                 tag_logic=tag_logic,
@@ -354,6 +361,7 @@ class BaseModelService(ABC):
         base_models: list = None,
         model_types: list = None,
         tags: Optional[Dict[str, str]] = None,
+        auto_tags: Optional[Dict[str, str]] = None,
         favorites_only: bool = False,
         search_options: dict = None,
         tag_logic: str = "any",
@@ -367,6 +375,7 @@ class BaseModelService(ABC):
             base_models=base_models,
             model_types=model_types,
             tags=tags,
+            auto_tags=auto_tags,
             favorites_only=favorites_only,
             search_options=normalized_options,
             tag_logic=tag_logic,
@@ -861,22 +870,75 @@ class BaseModelService(ABC):
         """Get the static preview URL for a model file"""
         cache = await self.scanner.get_cached_data()
 
+        name_normalized = model_name.replace("\\", "/")
+        name_no_ext = name_normalized
+        for ext in (".safetensors", ".ckpt", ".pt", ".bin"):
+            if name_no_ext.lower().endswith(ext):
+                name_no_ext = name_no_ext[: -len(ext)]
+                break
+
+        has_path = "/" in name_no_ext
+        basename = os.path.basename(name_no_ext) if has_path else name_no_ext
+        best_fallback = None
+
         for model in cache.raw_data:
-            if model["file_name"] == model_name:
+            file_name = model.get("file_name", "")
+            folder = model.get("folder", "")
+            file_name_no_ext = file_name
+            for ext in (".safetensors", ".ckpt", ".pt", ".bin"):
+                if file_name_no_ext.lower().endswith(ext):
+                    file_name_no_ext = file_name_no_ext[: -len(ext)]
+                    break
+            path_name = f"{folder}/{file_name_no_ext}".replace("\\", "/") if folder else file_name_no_ext
+
+            if name_no_ext == file_name_no_ext or name_no_ext == path_name:
                 preview_url = model.get("preview_url")
                 if preview_url:
                     from ..config import config
 
                     return config.get_preview_static_url(preview_url)
 
+            if has_path and file_name_no_ext == basename:
+                if folder and name_no_ext.startswith(folder.replace("\\", "/") + "/"):
+                    best_fallback = model
+                elif best_fallback is None:
+                    best_fallback = model
+
+        if best_fallback:
+            preview_url = best_fallback.get("preview_url")
+            if preview_url:
+                from ..config import config
+
+                return config.get_preview_static_url(preview_url)
+
         return "/loras_static/images/no-preview.png"
 
     async def get_model_civitai_url(self, model_name: str) -> Dict[str, Optional[str]]:
         """Get the Civitai URL for a model file"""
         cache = await self.scanner.get_cached_data()
 
+        name_normalized = model_name.replace("\\", "/")
+        name_no_ext = name_normalized
+        for ext in (".safetensors", ".ckpt", ".pt", ".bin"):
+            if name_no_ext.lower().endswith(ext):
+                name_no_ext = name_no_ext[: -len(ext)]
+                break
+
+        has_path = "/" in name_no_ext
+        basename = os.path.basename(name_no_ext) if has_path else name_no_ext
+        best_fallback = None
+
         for model in cache.raw_data:
-            if model["file_name"] == model_name:
+            file_name = model.get("file_name", "")
+            folder = model.get("folder", "")
+            file_name_no_ext = file_name
+            for ext in (".safetensors", ".ckpt", ".pt", ".bin"):
+                if file_name_no_ext.lower().endswith(ext):
+                    file_name_no_ext = file_name_no_ext[: -len(ext)]
+                    break
+            path_name = f"{folder}/{file_name_no_ext}".replace("\\", "/") if folder else file_name_no_ext
+
+            if name_no_ext == file_name_no_ext or name_no_ext == path_name:
                 civitai_data = model.get("civitai", {})
                 model_id = civitai_data.get("modelId")
                 version_id = civitai_data.get("id")
@@ -895,6 +957,27 @@ class BaseModelService(ABC):
                         "version_id": str(version_id) if version_id else None,
                     }
 
+            if has_path and file_name_no_ext == basename:
+                if folder and name_no_ext.startswith(folder.replace("\\", "/") + "/"):
+                    best_fallback = model
+                elif best_fallback is None:
+                    best_fallback = model
+
+        if best_fallback:
+            civitai_data = best_fallback.get("civitai", {})
+            model_id = civitai_data.get("modelId")
+            if model_id:
+                version_id = civitai_data.get("id")
+                civitai_host = self.settings.get("civitai_host", "civitai.com")
+                civitai_url = build_civitai_model_page_url(
+                    model_id, version_id, host=civitai_host
+                )
+                return {
+                    "civitai_url": civitai_url,
+                    "model_id": str(model_id),
+                    "version_id": str(version_id) if version_id else None,
+                }
+
         return {"civitai_url": None, "model_id": None, "version_id": None}
 
     async def get_model_metadata(self, file_path: str) -> Optional[Dict]:
@@ -908,6 +991,17 @@ class BaseModelService(ABC):
         )
         if should_skip or metadata is None:
             return None
+
+        # Prune stale example-image metadata entries whose files no longer
+        # exist on disk (e.g. a user deleted the files manually).
+        from ..utils.example_images_metadata import MetadataUpdater
+
+        was_modified = await MetadataUpdater.prune_stale_example_images(metadata)
+        if was_modified:
+            asyncio.create_task(
+                MetadataManager.save_metadata(file_path, metadata)
+            )
+
         return self.filter_civitai_data(metadata.to_dict().get("civitai", {}))
 
     async def get_model_description(self, file_path: str) -> Optional[str]:

py/services/batch_import_service.py

@@ -224,7 +224,7 @@ class BatchImportService:
                 return False
 
             for recipe in getattr(cache, "raw_data", []):
-                source_path = recipe.get("source_path") or recipe.get("source_url")
+                source_path = recipe.get("source_path")
                 if source_path and source_path == source:
                     return True
             return False

py/services/checkpoint_scanner.py

@@ -1,3 +1,4 @@
+import asyncio
 import json
 import logging
 import os
@@ -36,6 +37,9 @@ class CheckpointScanner(ModelScanner):
             file_extensions=file_extensions,
             hash_index=ModelHashIndex(),
         )
+        if not hasattr(self, "_hash_calculation_lock"):
+            self._hash_calculation_lock = asyncio.Lock()
+            self._hash_calculation_tasks: dict[str, asyncio.Task[Optional[str]]] = {}
 
     async def _create_default_metadata(
         self, file_path: str
@@ -88,7 +92,7 @@ class CheckpointScanner(ModelScanner):
             return None
 
     async def calculate_hash_for_model(self, file_path: str) -> Optional[str]:
-        """Calculate hash for a checkpoint on-demand.
+        """Calculate hash for a checkpoint on-demand with per-file singleflight.
 
         Args:
             file_path: Path to the model file
@@ -96,14 +100,65 @@ class CheckpointScanner(ModelScanner):
         Returns:
             SHA256 hash string, or None if calculation failed
         """
-        from ..utils.file_utils import calculate_sha256
-
         try:
             real_path = os.path.realpath(file_path)
             if not os.path.exists(real_path):
                 logger.error(f"File not found for hash calculation: {file_path}")
                 return None
 
+            metadata, _ = await MetadataManager.load_metadata(
+                file_path, self.model_class
+            )
+            if (
+                metadata is not None
+                and metadata.hash_status == "completed"
+                and metadata.sha256
+            ):
+                return metadata.sha256
+
+            async with self._hash_calculation_lock:
+                metadata, _ = await MetadataManager.load_metadata(
+                    file_path, self.model_class
+                )
+                if (
+                    metadata is not None
+                    and metadata.hash_status == "completed"
+                    and metadata.sha256
+                ):
+                    return metadata.sha256
+
+                task = self._hash_calculation_tasks.get(real_path)
+                if task is None:
+                    task = asyncio.create_task(
+                        self._run_hash_calculation_task(file_path, real_path)
+                    )
+                    self._hash_calculation_tasks[real_path] = task
+
+            return await asyncio.shield(task)
+
+        except Exception as e:
+            logger.error(f"Error calculating hash for {file_path}: {e}")
+            return None
+
+    async def _run_hash_calculation_task(
+        self, file_path: str, real_path: str
+    ) -> Optional[str]:
+        """Run a hash calculation task and remove it from the in-flight map."""
+        try:
+            return await self._calculate_hash_for_model_uncached(file_path, real_path)
+        finally:
+            task = asyncio.current_task()
+            async with self._hash_calculation_lock:
+                if self._hash_calculation_tasks.get(real_path) is task:
+                    del self._hash_calculation_tasks[real_path]
+
+    async def _calculate_hash_for_model_uncached(
+        self, file_path: str, real_path: str
+    ) -> Optional[str]:
+        """Calculate hash for a checkpoint without checking in-flight tasks."""
+        from ..utils.file_utils import calculate_sha256
+
+        try:
             # Load current metadata
             metadata, should_skip = await MetadataManager.load_metadata(
                 file_path, self.model_class

py/services/checkpoint_service.py

@@ -3,6 +3,7 @@ import logging
 from typing import Dict
 
 from .base_model_service import BaseModelService
+from .auto_tag_service import extract_auto_tags
 from ..utils.models import CheckpointMetadata
 from ..config import config
 
@@ -45,7 +46,8 @@ class CheckpointService(BaseModelService):
             "exclude": bool(checkpoint_data.get("exclude", False)),
             "update_available": bool(checkpoint_data.get("update_available", False)),
             "skip_metadata_refresh": bool(checkpoint_data.get("skip_metadata_refresh", False)),
-            "civitai": self.filter_civitai_data(checkpoint_data.get("civitai", {}), minimal=True)
+            "civitai": self.filter_civitai_data(checkpoint_data.get("civitai", {}), minimal=True),
+            "auto_tags": checkpoint_data.get("auto_tags") or extract_auto_tags(checkpoint_data),
         }
     
     def find_duplicate_hashes(self) -> Dict:

py/services/civarchive_client.py

@@ -186,6 +186,22 @@ class CivArchiveClient:
         if "metadata" in file_data:
             transformed["metadata"] = file_data["metadata"]
 
+        # Infer metadata.format from filename extension
+        name = transformed.get("name")
+        if name and isinstance(name, str):
+            lower_name = name.lower()
+            if lower_name.endswith(".safetensors"):
+                inferred_format = "SafeTensor"
+            elif lower_name.endswith(".ckpt"):
+                inferred_format = "PickleTensor"
+            else:
+                inferred_format = None
+            if inferred_format:
+                if "metadata" not in transformed:
+                    transformed["metadata"] = {}
+                if isinstance(transformed["metadata"], dict):
+                    transformed["metadata"].setdefault("format", inferred_format)
+
         if file_data.get("modelVersionId") is not None:
             transformed["modelVersionId"] = file_data.get("modelVersionId")
         elif file_data.get("model_version_id") is not None:
@@ -213,6 +229,20 @@ class CivArchiveClient:
         for file_data in candidates:
             if isinstance(file_data, dict):
                 transformed_files.append(self._transform_file_entry(file_data))
+
+        # Sort: .safetensors first, .ckpt second, others last
+        # so the backend fallback (no file_params) prefers safetensors
+        def _sort_key(f: Dict) -> int:
+            fname = f.get("name") or ""
+            if isinstance(fname, str):
+                lower = fname.lower()
+                if lower.endswith(".safetensors"):
+                    return 0
+                elif lower.endswith(".ckpt"):
+                    return 1
+            return 2
+
+        transformed_files.sort(key=_sort_key)
         return transformed_files
 
     def _transform_version(

py/services/civitai_base_model_service.py

@@ -193,6 +193,9 @@ class CivitaiBaseModelService:
             "zimageturbo": "ZIT",
             "zimagebase": "ZIB",
             "anima": "ANI",
+            "ernie": "ERNI",
+            "ernie turbo": "ETRB",
+            "nucleus": "NUCL",
             "svd": "SVD",
             "ltxv": "LTXV",
             "ltxv2": "LTV2",
@@ -418,6 +421,9 @@ class CivitaiBaseModelService:
                 "Kolors",
                 "NoobAI",
                 "Anima",
+                "Ernie",
+                "Ernie Turbo",
+                "Nucleus",
             ],
         }
 

py/services/civitai_client.py

@@ -2,6 +2,7 @@ import asyncio
 import copy
 import logging
 import os
+from collections import OrderedDict
 from typing import Any, Optional, Dict, Tuple, List, Sequence
 from .connectivity_guard import (
     OFFLINE_FRIENDLY_MESSAGE,
@@ -45,6 +46,14 @@ class CivitaiClient:
         self._initialized = True
 
         self.base_url = "https://civitai.red/api/v1"
+        # In-memory cache to avoid redundant get_model_version_info calls
+        # within the same import/scan flow. Only successful results are cached.
+        # Uses OrderedDict with LRU eviction at MAX_CACHE_ENTRIES to prevent
+        # unbounded growth in long-running server processes.
+        self._version_info_cache: OrderedDict[
+            str, Tuple[Optional[Dict], Optional[str]]
+        ] = OrderedDict()
+        self._MAX_CACHE_ENTRIES = 500
 
     def _build_image_info_url(self, image_id: str) -> str:
         return f"{self.base_url}/images?imageId={image_id}&nsfw=X"
@@ -57,8 +66,11 @@ class CivitaiClient:
         use_auth: bool = False,
         **kwargs,
     ) -> Tuple[bool, Dict | str]:
-        """Wrapper around downloader.make_request that surfaces rate limits."""
+        """Wrapper around downloader.make_request that surfaces rate limits,
+        with retry for transient server errors (5xx, Cloudflare 524, network flakiness)."""
 
+        max_retries = 3
+        for attempt in range(max_retries):
             downloader = await get_downloader()
             success, result = await downloader.make_request(
                 method,
@@ -66,13 +78,45 @@ class CivitaiClient:
                 use_auth=use_auth,
                 **kwargs,
             )
-        if not success and isinstance(result, RateLimitError):
+            if success:
+                return True, result
+
+            if isinstance(result, RateLimitError):
                 if result.provider is None:
                     result.provider = "civitai_api"
                 raise result
-        if not success and is_offline_cooldown_error(result):
+
+            if is_offline_cooldown_error(result):
                 return False, OFFLINE_FRIENDLY_MESSAGE
-        return success, result
+
+            # Transient server error — retry with exponential backoff
+            if self._is_transient_server_error(str(result)):
+                if attempt < max_retries - 1:
+                    wait = 2**attempt  # 1s, 2s, 4s
+                    logger.info(
+                        "Transient error on %s %s, retrying in %ds "
+                        "(attempt %d/%d): %s",
+                        method,
+                        url,
+                        wait,
+                        attempt + 1,
+                        max_retries,
+                        result,
+                    )
+                    await asyncio.sleep(wait)
+                    continue
+                logger.warning(
+                    "All %d retries exhausted for %s %s: %s",
+                    max_retries,
+                    method,
+                    url,
+                    result,
+                )
+                return False, result
+
+            return False, result
+
+        return False, "Unexpected error in _make_request"
 
     @staticmethod
     def _remove_comfy_metadata(model_version: Optional[Dict]) -> None:
@@ -201,6 +245,29 @@ class CivitaiClient:
 
         return _from_value(payload)
 
+    @staticmethod
+    def _is_transient_server_error(message: str) -> bool:
+        """Return True when the message indicates a transient upstream failure.
+
+        Recognises Cloudflare 524, generic 5xx, and connectivity-level flakiness
+        that should not be treated as a permanent failure.
+        """
+        normalized = message.lower()
+        if "status 5" in normalized or "status 524" in normalized:
+            return True
+        if any(
+            keyword in normalized
+            for keyword in (
+                "connection refused",
+                "connection reset",
+                "temporary failure",
+                "name resolution",
+                "connection closed",
+            )
+        ):
+            return True
+        return False
+
     async def get_model_versions(self, model_id: str) -> Optional[Dict]:
         """Get all versions of a model with local availability info"""
         try:
@@ -223,6 +290,13 @@ class CivitaiClient:
                 logger.info("Civitai request skipped: %s", OFFLINE_FRIENDLY_MESSAGE)
                 return None
             if message:
+                if self._is_transient_server_error(message):
+                    logger.info(
+                        "Transient server error for model %s: %s",
+                        model_id,
+                        message,
+                    )
+                    return None
                 raise RuntimeError(message)
             return None
         except RateLimitError:
@@ -257,7 +331,7 @@ class CivitaiClient:
                 "GET",
                 f"{self.base_url}/models",
                 use_auth=True,
-                params={"ids": query},
+                params={"ids": query, "nsfw": "true"},
             )
             if not success:
                 return None
@@ -336,6 +410,25 @@ class CivitaiClient:
             return None
 
         target_version = self._select_target_version(model_data, model_id, version_id)
+
+        # If modelVersions is empty (e.g. CivitAI cache lag for newly published
+        # models) but a specific version_id is known, fall back to fetching the
+        # version directly via the individual model-versions endpoint, then
+        # enrich it with the model-level data we already have.
+        if target_version is None and version_id is not None:
+            logger.info(
+                "modelVersions empty for model %s; falling back to direct "
+                "version lookup for %s",
+                model_id,
+                version_id,
+            )
+            version = await self._fetch_version_by_id(version_id)
+            if version:
+                self._enrich_version_with_model_data(version, model_data)
+                self._remove_comfy_metadata(version)
+                return version
+            return None
+
         if target_version is None:
             return None
 
@@ -482,6 +575,14 @@ class CivitaiClient:
                 - The model version data or None if not found
                 - An error message if there was an error, or None on success
         """
+        # In-memory cache avoids redundant API calls within the same
+        # import/scan flow (e.g. _resolve_base_model_from_checkpoint
+        # followed by _resolve_and_populate_checkpoint with the same id).
+        if version_id in self._version_info_cache:
+            logger.debug("Cache hit for model version info: %s", version_id)
+            self._version_info_cache.move_to_end(version_id)  # LRU bump
+            return self._version_info_cache[version_id]
+
         try:
             url = f"{self.base_url}/model-versions/{version_id}"
 
@@ -491,6 +592,11 @@ class CivitaiClient:
             if success:
                 logger.debug("Successfully fetched model version info for: %s", version_id)
                 self._remove_comfy_metadata(result)
+                self._version_info_cache[version_id] = (result, None)
+                self._version_info_cache.move_to_end(version_id)
+                # Evict oldest entry when over capacity
+                if len(self._version_info_cache) > self._MAX_CACHE_ENTRIES:
+                    self._version_info_cache.popitem(last=False)
                 return result, None
 
             # Handle specific error cases
@@ -532,6 +638,13 @@ class CivitaiClient:
             if not success:
                 if is_expected_offline_error(result):
                     return None
+                if self._is_transient_server_error(str(result)):
+                    logger.info(
+                        "Transient server error fetching image info for ID %s: %s",
+                        image_id,
+                        result,
+                    )
+                    return None
                 logger.error(
                     "Failed to fetch image info for ID %s from civitai.red: %s",
                     image_id,
@@ -577,6 +690,59 @@ class CivitaiClient:
             logger.error(error_msg)
             return None
 
+    async def get_model_versions_by_hashes(
+        self, hashes: List[str]
+    ) -> Optional[List[Dict]]:
+        """Fetch full version details for up to 100 SHA256 hashes via the batch endpoint.
+
+        Uses POST /api/v1/model-versions/by-hash which returns full version
+        details including ``usageControl`` and ``earlyAccessEndsAt`` that are
+        not available from the model-level API.
+
+        Args:
+            hashes: List of SHA256 hashes (max 100 per batch; auto-split).
+
+        Returns:
+            List of version dicts or None on failure.
+        """
+        if not hashes:
+            return []
+
+        BATCH_SIZE = 100
+        all_versions: List[Dict] = []
+
+        for start in range(0, len(hashes), BATCH_SIZE):
+            batch = hashes[start : start + BATCH_SIZE]
+            try:
+                success, result = await self._make_request(
+                    "POST",
+                    f"{self.base_url}/model-versions/by-hash",
+                    use_auth=True,
+                    json=batch,
+                )
+                if not success:
+                    logger.warning(
+                        "Batch by-hash request failed for %d hashes: %s",
+                        len(batch),
+                        result,
+                    )
+                    continue
+
+                if isinstance(result, list):
+                    all_versions.extend(result)
+                else:
+                    logger.debug(
+                        "Unexpected by-hash response type: %s", type(result)
+                    )
+            except RateLimitError:
+                raise
+            except Exception as exc:  # pragma: no cover - defensive logging
+                logger.error(
+                    "Error fetching model versions by hashes: %s", exc
+                )
+
+        return all_versions if all_versions else None
+
     async def get_user_models(self, username: str) -> Optional[List[Dict]]:
         """Fetch all models for a specific Civitai user."""
         if not username:
@@ -587,7 +753,7 @@ class CivitaiClient:
                 "GET",
                 f"{self.base_url}/models",
                 use_auth=True,
-                params={"username": username},
+                params={"username": username, "nsfw": "true"},
             )
 
             if not success:

py/services/download_coordinator.py

@@ -110,6 +110,23 @@ class DownloadCoordinator:
 
         return result
 
+    async def skip_download(self, download_id: str) -> Dict[str, Any]:
+        """Skip a download while preserving all partial files on disk."""
+        download_manager = await self._download_manager_factory()
+        result = await download_manager.skip_download(download_id)
+
+        await self._ws_manager.broadcast_download_progress(
+            download_id,
+            {
+                "status": "skipped",
+                "progress": 0,
+                "download_id": download_id,
+                "message": "Download skipped by user (partial files preserved)",
+            },
+        )
+
+        return result
+
     async def pause_download(self, download_id: str) -> Dict[str, Any]:
         """Pause an active download and notify listeners."""
 

py/services/download_manager.py

@@ -18,6 +18,7 @@ from ..utils.constants import (
     VALID_LORA_TYPES,
 )
 from ..utils.civitai_utils import normalize_civitai_download_url, rewrite_preview_url
+from ..utils.file_utils import calculate_sha256
 from ..utils.preview_selection import resolve_mature_threshold, select_preview_media
 from ..utils.utils import sanitize_folder_name
 from ..utils.exif_utils import ExifUtils
@@ -1364,7 +1365,7 @@ class DownloadManager:
                             f
                             for f in files
                             if f.get("primary")
-                            and f.get("type") in ("Model", "Negative")
+                            and f.get("type") in ("Model", "Negative", "Diffusion Model")
                         ),
                         None,
                     )
@@ -1395,7 +1396,7 @@ class DownloadManager:
                     (
                         f
                         for f in files
-                        if f.get("primary") and f.get("type") in ("Model", "Negative")
+                        if f.get("primary") and f.get("type") in ("Model", "Negative", "Diffusion Model")
                     ),
                     None,
                 )
@@ -2239,8 +2240,11 @@ class DownloadManager:
             entry.file_name = os.path.splitext(os.path.basename(file_path))[0]
             # Update size to actual downloaded file size
             entry.size = os.path.getsize(file_path)
-            # Use SHA256 from API metadata (already set in from_civitai_info)
+            # Compute SHA256 locally when the API response didn't include it
-            # Do not recalculate to avoid blocking during ComfyUI execution
+            if not entry.sha256:
+                sha256 = await calculate_sha256(file_path)
+                if sha256:
+                    entry.sha256 = sha256.lower()
             entries.append(entry)
 
         return entries
@@ -2400,6 +2404,89 @@ class DownloadManager:
                 self._download_tasks.pop(download_id, None)
                 await self._aria2_state_store.remove(download_id)
 
+    async def skip_download(self, download_id: str) -> Dict:
+        """Skip a download while preserving all partial files on disk.
+
+        Removes all in-memory tracking (asyncio task, semaphore, active/pause
+        state) but keeps partial files (.part / .aria2) on disk so that a
+        subsequent download-model-get request for the same save path can
+        auto-resume from the preserved partial download.
+
+        Args:
+            download_id: The unique identifier of the download task
+
+        Returns:
+            Dict: Status of the skip operation
+        """
+        await self._restore_persisted_downloads()
+
+        if download_id not in self._download_tasks and download_id not in self._active_downloads:
+            return {"success": False, "error": "Download task not found"}
+
+        download_info = self._active_downloads.get(download_id)
+        task = self._download_tasks.get(download_id)
+        active_statuses = {"queued", "waiting", "downloading", "paused", "cancelling"}
+        if task is None and (
+            not isinstance(download_info, dict)
+            or download_info.get("status") not in active_statuses
+        ):
+            return {"success": False, "error": "Download task not found"}
+
+        backend = (
+            self._active_downloads.get(download_id, {}).get("transfer_backend")
+            or "python"
+        )
+
+        try:
+            # For aria2: pause the transfer rather than force-removing it, so
+            # the .aria2 control file stays on disk for future resume
+            if backend == "aria2":
+                try:
+                    aria2_downloader = await get_aria2_downloader()
+                    pause_result = await aria2_downloader.pause_download(download_id)
+                    if not pause_result.get("success"):
+                        logger.warning(
+                            "Failed to pause aria2 transfer for %s during skip: %s",
+                            download_id,
+                            pause_result.get("error"),
+                        )
+                except Exception as exc:
+                    logger.warning(
+                        "Failed to pause aria2 transfer for %s during skip: %s",
+                        download_id,
+                        exc,
+                    )
+
+            # Cancel the asyncio task so the semaphore slot is released
+            if task is not None:
+                task.cancel()
+
+            # Resume pause event so the task can exit cleanly
+            pause_control = self._pause_events.get(download_id)
+            if pause_control is not None:
+                pause_control.resume()
+
+            # Wait briefly for task to acknowledge cancellation
+            if task is not None:
+                try:
+                    await asyncio.wait_for(asyncio.shield(task), timeout=2.0)
+                except (asyncio.CancelledError, asyncio.TimeoutError):
+                    pass
+
+            logger.info(f"Download skipped for task {download_id} (partial files preserved)")
+            return {"success": True, "message": "Download skipped successfully"}
+        except Exception as e:
+            logger.error(f"Error skipping download: {e}", exc_info=True)
+            return {"success": False, "error": str(e)}
+        finally:
+            # Clean up local in-memory tracking only - NO file deletion
+            self._pause_events.pop(download_id, None)
+            self._download_tasks.pop(download_id, None)
+            if download_id in self._active_downloads:
+                del self._active_downloads[download_id]
+            # Preserve aria2 state store entry so the partial download
+            # info survives restarts and can be resumed later
+
     async def pause_download(self, download_id: str) -> Dict:
         """Pause an active download without losing progress."""
 

py/services/download_queue_service.py

@@ -0,0 +1,734 @@
+from __future__ import annotations
+
+import asyncio
+import json
+import logging
+import os
+import sqlite3
+import time
+from typing import Any, Optional
+
+from ..utils.cache_paths import get_cache_base_dir
+
+logger = logging.getLogger(__name__)
+
+
+def _resolve_database_path() -> str:
+    base_dir = get_cache_base_dir(create=True)
+    history_dir = os.path.join(base_dir, "download_history")
+    os.makedirs(history_dir, exist_ok=True)
+    return os.path.join(history_dir, "download_queue.sqlite")
+
+
+class DownloadQueueService:
+    """Persistent download queue and history manager backed by SQLite.
+
+    Provides a singleton interface for managing a download queue and
+    corresponding history table, both stored in a single SQLite database
+    under the cache directory.
+    """
+
+    _instance: Optional[DownloadQueueService] = None
+    _class_lock: asyncio.Lock = asyncio.Lock()
+
+    _SCHEMA = """
+        CREATE TABLE IF NOT EXISTS download_queue (
+            download_id TEXT PRIMARY KEY,
+            model_id INTEGER,
+            model_version_id INTEGER,
+            model_name TEXT NOT NULL DEFAULT '',
+            version_name TEXT DEFAULT '',
+            thumbnail_url TEXT DEFAULT '',
+            source TEXT,
+            file_params TEXT,
+            status TEXT NOT NULL DEFAULT 'queued',
+            priority INTEGER DEFAULT 0,
+            progress INTEGER DEFAULT 0,
+            bytes_downloaded INTEGER DEFAULT 0,
+            total_bytes INTEGER,
+            bytes_per_second REAL DEFAULT 0.0,
+            error TEXT,
+            file_path TEXT,
+            added_at REAL NOT NULL,
+            started_at REAL,
+            completed_at REAL
+        );
+        CREATE INDEX IF NOT EXISTS idx_dq_status ON download_queue(status);
+        CREATE INDEX IF NOT EXISTS idx_dq_added ON download_queue(added_at);
+
+        CREATE TABLE IF NOT EXISTS download_history (
+            id INTEGER PRIMARY KEY AUTOINCREMENT,
+            download_id TEXT,
+            model_id INTEGER,
+            model_version_id INTEGER,
+            model_name TEXT NOT NULL DEFAULT '',
+            version_name TEXT DEFAULT '',
+            thumbnail_url TEXT DEFAULT '',
+            status TEXT NOT NULL,
+            error TEXT,
+            file_path TEXT,
+            bytes_downloaded INTEGER DEFAULT 0,
+            total_bytes INTEGER,
+            completed_at REAL NOT NULL,
+            is_already_exists INTEGER DEFAULT 0
+        );
+        CREATE INDEX IF NOT EXISTS idx_dh_completed ON download_history(completed_at DESC);
+        CREATE INDEX IF NOT EXISTS idx_dh_status ON download_history(status);
+    """
+
+    @classmethod
+    async def get_instance(cls) -> DownloadQueueService:
+        """Return the singleton instance, creating it if necessary."""
+        async with cls._class_lock:
+            if cls._instance is None:
+                cls._instance = cls()
+            return cls._instance
+
+    def __init__(self, db_path: Optional[str] = None) -> None:
+        self._db_path = db_path or _resolve_database_path()
+        self._lock = asyncio.Lock()
+        self._conn: Optional[sqlite3.Connection] = None
+        self._schema_initialized = False
+        self._ensure_directory()
+        self._initialize_schema()
+
+    def _ensure_directory(self) -> None:
+        directory = os.path.dirname(self._db_path)
+        if directory:
+            os.makedirs(directory, exist_ok=True)
+
+    def _connect(self) -> sqlite3.Connection:
+        conn = sqlite3.connect(self._db_path, check_same_thread=False)
+        conn.row_factory = sqlite3.Row
+        return conn
+
+    def _get_conn(self) -> sqlite3.Connection:
+        if self._conn is None:
+            self._conn = sqlite3.connect(self._db_path, check_same_thread=False)
+            self._conn.row_factory = sqlite3.Row
+        return self._conn
+
+    def _initialize_schema(self) -> None:
+        if self._schema_initialized:
+            return
+        with self._connect() as conn:
+            conn.executescript(self._SCHEMA)
+            conn.commit()
+        self._schema_initialized = True
+
+    def get_database_path(self) -> str:
+        """Return the resolved database file path."""
+        return self._db_path
+
+    def close(self) -> None:
+        """Close the persistent SQLite connection, if open.
+
+        This is called before plugin update operations to release the
+        database file lock on Windows, allowing ``shutil.rmtree()`` to
+        succeed when the cache resides inside the plugin directory.
+        """
+        if self._conn is not None:
+            try:
+                self._conn.close()
+            except Exception:
+                pass
+            finally:
+                self._conn = None
+
+    # ------------------------------------------------------------------
+    # Queue methods
+    # ------------------------------------------------------------------
+
+    async def add_to_queue(
+        self,
+        download_id: str,
+        model_id: Optional[int] = None,
+        model_version_id: Optional[int] = None,
+        model_name: str = "",
+        version_name: str = "",
+        thumbnail_url: str = "",
+        source: Optional[str] = None,
+        file_params: Optional[dict[str, Any]] = None,
+    ) -> dict[str, Any]:
+        """Insert a new download into the queue.
+
+        Returns the inserted row as a dict (or an empty dict if the
+        download_id already exists).
+        """
+        now = time.time()
+        file_params_json = json.dumps(file_params) if file_params is not None else None
+
+        async with self._lock:
+            conn = self._get_conn()
+            conn.execute(
+                """
+                INSERT OR IGNORE INTO download_queue (
+                    download_id, model_id, model_version_id, model_name,
+                    version_name, thumbnail_url, source, file_params,
+                    status, priority, added_at
+                ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, 'queued', 0, ?)
+                """,
+                (
+                    download_id,
+                    model_id,
+                    model_version_id,
+                    model_name,
+                    version_name,
+                    thumbnail_url,
+                    source,
+                    file_params_json,
+                    now,
+                ),
+            )
+            conn.commit()
+            row = conn.execute(
+                "SELECT * FROM download_queue WHERE download_id = ?",
+                (download_id,),
+            ).fetchone()
+
+        return dict(row) if row else {}
+
+    async def get_queue(self) -> list[dict[str, Any]]:
+        """Return all items in the queue ordered by priority then added time."""
+        async with self._lock:
+            conn = self._get_conn()
+            rows = conn.execute(
+                "SELECT * FROM download_queue ORDER BY priority DESC, added_at ASC"
+            ).fetchall()
+        return [dict(row) for row in rows]
+
+    async def get_queued_count(self) -> int:
+        """Return the number of items with status ``'queued'``."""
+        async with self._lock:
+            conn = self._get_conn()
+            row = conn.execute(
+                "SELECT COUNT(*) AS cnt FROM download_queue WHERE status = 'queued'"
+            ).fetchone()
+        return row["cnt"] if row else 0
+
+    async def update_status(
+        self,
+        download_id: str,
+        status: str,
+        **extra: Any,
+    ) -> bool:
+        """Update the status and/or extra fields of a queue item.
+
+        Accepted extra keyword arguments:
+        ``progress``, ``error``, ``file_path``, ``bytes_downloaded``,
+        ``total_bytes``, ``bytes_per_second``.
+
+        Returns ``True`` if a row was updated.
+        """
+        allowed_extra = {
+            "progress",
+            "error",
+            "file_path",
+            "bytes_downloaded",
+            "total_bytes",
+            "bytes_per_second",
+        }
+
+        set_clauses: list[str] = ["status = ?"]
+        params: list[Any] = [status]
+        now = time.time()
+
+        if status in ("downloading",):
+            set_clauses.append("started_at = COALESCE(started_at, ?)")
+            params.append(now)
+        if status in ("completed", "failed", "canceled"):
+            set_clauses.append("completed_at = ?")
+            params.append(now)
+
+        for key, value in extra.items():
+            if key in allowed_extra:
+                set_clauses.append(f"{key} = ?")
+                params.append(value)
+
+        params.append(download_id)
+
+        async with self._lock:
+            conn = self._get_conn()
+            cursor = conn.execute(
+                f"UPDATE download_queue SET {', '.join(set_clauses)} "
+                "WHERE download_id = ?",
+                params,
+            )
+            conn.commit()
+        return cursor.rowcount > 0
+
+    async def remove_from_queue(self, download_id: str) -> bool:
+        """Remove a single item from the queue by download_id.
+
+        Returns ``True`` if a row was deleted.
+        """
+        async with self._lock:
+            conn = self._get_conn()
+            cursor = conn.execute(
+                "DELETE FROM download_queue WHERE download_id = ?",
+                (download_id,),
+            )
+            conn.commit()
+        return cursor.rowcount > 0
+
+    async def move_to_top(self, download_id: str) -> bool:
+        """Move an item to the front of the queue (highest priority).
+
+        Returns ``True`` if the item was found and updated.
+        """
+        async with self._lock:
+            conn = self._get_conn()
+            row = conn.execute(
+                "SELECT priority FROM download_queue WHERE download_id = ?",
+                (download_id,),
+            ).fetchone()
+            if row is None:
+                return False
+
+            max_row = conn.execute(
+                "SELECT MAX(priority) AS mx FROM download_queue"
+            ).fetchone()
+            max_priority: int = max_row["mx"] if max_row["mx"] is not None else 0
+
+            conn.execute(
+                "UPDATE download_queue SET priority = ? WHERE download_id = ?",
+                (max_priority + 1, download_id),
+            )
+            conn.commit()
+        return True
+
+    async def move_to_end(self, download_id: str) -> bool:
+        """Move an item to the end of the queue (lowest priority).
+
+        Returns ``True`` if the item was found and updated.
+        """
+        async with self._lock:
+            conn = self._get_conn()
+            row = conn.execute(
+                "SELECT priority FROM download_queue WHERE download_id = ?",
+                (download_id,),
+            ).fetchone()
+            if row is None:
+                return False
+
+            min_row = conn.execute(
+                "SELECT MIN(priority) AS mn FROM download_queue"
+            ).fetchone()
+            min_priority: int = min_row["mn"] if min_row["mn"] is not None else 0
+
+            conn.execute(
+                "UPDATE download_queue SET priority = ? WHERE download_id = ?",
+                (min_priority - 1, download_id),
+            )
+            conn.commit()
+        return True
+
+    async def clear_queue(self, status_filter: Optional[str] = None) -> int:
+        """Remove items from the queue.
+
+        When *status_filter* is provided only items with that status are
+        deleted.  Returns the number of deleted rows.
+        """
+        async with self._lock:
+            conn = self._get_conn()
+            if status_filter is not None:
+                cursor = conn.execute(
+                    "DELETE FROM download_queue WHERE status = ?",
+                    (status_filter,),
+                )
+            else:
+                cursor = conn.execute("DELETE FROM download_queue")
+            conn.commit()
+        return cursor.rowcount
+
+    async def complete_download(
+        self,
+        download_id: str,
+        status: str = "completed",
+        error: Optional[str] = None,
+        file_path: Optional[str] = None,
+        bytes_downloaded: int = 0,
+        total_bytes: Optional[int] = None,
+        completed_at: Optional[float] = None,
+    ) -> Optional[dict[str, Any]]:
+        """Atomically move a download from the queue into the history table.
+
+        Looks up the queue record by ``download_id``, deletes it from the
+        queue, and inserts a corresponding history entry with the given
+        terminal status (``completed``, ``failed``, or ``canceled``).
+
+        When *completed_at* is provided it is used as the completion
+        timestamp; otherwise ``time.time()`` is used.
+
+        Returns the original queue record (before deletion) on success,
+        or ``None`` if the download was not found in the queue.
+        """
+        async with self._lock:
+            conn = self._get_conn()
+            row = conn.execute(
+                "SELECT * FROM download_queue WHERE download_id = ?",
+                (download_id,),
+            ).fetchone()
+            if row is None:
+                return None
+
+            now = completed_at if completed_at is not None else time.time()
+            conn.execute(
+                "DELETE FROM download_queue WHERE download_id = ?",
+                (download_id,),
+            )
+            conn.execute(
+                """
+                INSERT INTO download_history (
+                    download_id, model_id, model_version_id, model_name,
+                    version_name, thumbnail_url, status, error, file_path,
+                    bytes_downloaded, total_bytes, completed_at
+                ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+                """,
+                (
+                    row["download_id"],
+                    row["model_id"],
+                    row["model_version_id"],
+                    row["model_name"],
+                    row["version_name"],
+                    row["thumbnail_url"],
+                    status,
+                    error,
+                    file_path,
+                    bytes_downloaded,
+                    total_bytes,
+                    now,
+                ),
+            )
+            conn.commit()
+        return dict(row)
+
+    async def pop_next_download(self) -> Optional[dict[str, Any]]:
+        """Atomically fetch and mark the next queued item as ``downloading``.
+
+        The item with the highest priority (and earliest ``added_at``
+        among ties) whose status is ``'queued'`` is selected, set to
+        ``'downloading'``, and returned as a dict.  Returns ``None`` if
+        the queue is empty.
+        """
+        async with self._lock:
+            conn = self._get_conn()
+            row = conn.execute(
+                """
+                SELECT * FROM download_queue
+                WHERE status = 'queued'
+                ORDER BY priority DESC, added_at ASC
+                LIMIT 1
+                """
+            ).fetchone()
+            if row is None:
+                return None
+
+            download_id = row["download_id"]
+            now = time.time()
+            conn.execute(
+                "UPDATE download_queue SET status = 'downloading', "
+                "started_at = COALESCE(started_at, ?) "
+                "WHERE download_id = ?",
+                (now, download_id),
+            )
+            conn.commit()
+            updated = conn.execute(
+                "SELECT * FROM download_queue WHERE download_id = ?",
+                (download_id,),
+            ).fetchone()
+
+        return dict(updated) if updated else None
+
+    # ------------------------------------------------------------------
+    # History methods
+    # ------------------------------------------------------------------
+
+    async def add_to_history(
+        self,
+        download_id: Optional[str] = None,
+        model_id: Optional[int] = None,
+        model_version_id: Optional[int] = None,
+        model_name: str = "",
+        version_name: str = "",
+        thumbnail_url: str = "",
+        status: str = "completed",
+        error: Optional[str] = None,
+        file_path: Optional[str] = None,
+        bytes_downloaded: int = 0,
+        total_bytes: Optional[int] = None,
+        is_already_exists: int = 0,
+    ) -> int:
+        """Insert a record into the download history.
+
+        Returns the ``id`` (AUTOINCREMENT primary key) of the newly
+        inserted row.
+        """
+        now = time.time()
+
+        async with self._lock:
+            conn = self._get_conn()
+            cursor = conn.execute(
+                """
+                INSERT INTO download_history (
+                    download_id, model_id, model_version_id, model_name,
+                    version_name, thumbnail_url, status, error, file_path,
+                    bytes_downloaded, total_bytes, completed_at, is_already_exists
+                ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+                """,
+                (
+                    download_id,
+                    model_id,
+                    model_version_id,
+                    model_name,
+                    version_name,
+                    thumbnail_url,
+                    status,
+                    error,
+                    file_path,
+                    bytes_downloaded,
+                    total_bytes,
+                    now,
+                    is_already_exists,
+                ),
+            )
+            conn.commit()
+        return cursor.lastrowid or 0
+
+    async def get_history(
+        self,
+        limit: int = 50,
+        offset: int = 0,
+        status_filter: Optional[str] = None,
+    ) -> dict[str, Any]:
+        """Return a page of download history entries.
+
+        Returns a dict with keys ``items``, ``total``, ``limit``, and
+        ``offset``.
+        """
+        async with self._lock:
+            conn = self._get_conn()
+
+            if status_filter is not None:
+                count_row = conn.execute(
+                    "SELECT COUNT(*) AS cnt FROM download_history WHERE status = ?",
+                    (status_filter,),
+                ).fetchone()
+                rows = conn.execute(
+                    "SELECT * FROM download_history WHERE status = ? "
+                    "ORDER BY completed_at DESC LIMIT ? OFFSET ?",
+                    (status_filter, limit, offset),
+                ).fetchall()
+            else:
+                count_row = conn.execute(
+                    "SELECT COUNT(*) AS cnt FROM download_history"
+                ).fetchone()
+                rows = conn.execute(
+                    "SELECT * FROM download_history "
+                    "ORDER BY completed_at DESC LIMIT ? OFFSET ?",
+                    (limit, offset),
+                ).fetchall()
+
+        return {
+            "items": [dict(row) for row in rows],
+            "total": count_row["cnt"] if count_row else 0,
+            "limit": limit,
+            "offset": offset,
+        }
+
+    async def delete_history_item(self, id: int) -> bool:
+        """Delete a single history entry by its *id*.
+
+        Returns ``True`` if a row was deleted.
+        """
+        async with self._lock:
+            conn = self._get_conn()
+            cursor = conn.execute(
+                "DELETE FROM download_history WHERE id = ?",
+                (id,),
+            )
+            conn.commit()
+        return cursor.rowcount > 0
+
+    async def clear_history(
+        self,
+        status_filter: Optional[str] = None,
+        before_timestamp: Optional[float] = None,
+    ) -> int:
+        """Remove history entries matching the optional filters.
+
+        Both ``status_filter`` and ``before_timestamp`` can be combined
+        (AND logic).  Returns the number of deleted rows.
+        """
+        async with self._lock:
+            conn = self._get_conn()
+
+            clauses: list[str] = []
+            params: list[Any] = []
+
+            if status_filter is not None:
+                clauses.append("status = ?")
+                params.append(status_filter)
+            if before_timestamp is not None:
+                clauses.append("completed_at < ?")
+                params.append(before_timestamp)
+
+            where = ""
+            if clauses:
+                where = " WHERE " + " AND ".join(clauses)
+
+            cursor = conn.execute(
+                f"DELETE FROM download_history{where}",
+                params,
+            )
+            conn.commit()
+        return cursor.rowcount
+
+    async def get_history_count(self, status_filter: Optional[str] = None) -> int:
+        """Return the number of history entries, optionally filtered by status."""
+        async with self._lock:
+            conn = self._get_conn()
+            if status_filter is not None:
+                row = conn.execute(
+                    "SELECT COUNT(*) AS cnt FROM download_history WHERE status = ?",
+                    (status_filter,),
+                ).fetchone()
+            else:
+                row = conn.execute(
+                    "SELECT COUNT(*) AS cnt FROM download_history"
+                ).fetchone()
+        return row["cnt"] if row else 0
+
+    # ------------------------------------------------------------------
+    # Retry
+    # ------------------------------------------------------------------
+
+    async def retry_from_history(self, item_id: int) -> Optional[dict[str, Any]]:
+        """Re-queue a failed or canceled download from history.
+
+        Looks up the history record by its primary key.  If the status is
+        ``failed`` or ``canceled`` a new queue entry is created with the
+        same model metadata and a fresh download id.
+        """
+        async with self._lock:
+            conn = self._get_conn()
+            row = conn.execute(
+                "SELECT * FROM download_history WHERE id = ?",
+                (item_id,),
+            ).fetchone()
+            if row is None:
+                return None
+            status = str(row["status"])
+            if status not in ("failed", "canceled"):
+                return None
+
+            import uuid
+
+            new_id = str(uuid.uuid4())
+            now = time.time()
+            conn.execute(
+                """
+                INSERT INTO download_queue (
+                    download_id, model_id, model_version_id, model_name,
+                    version_name, thumbnail_url, source, file_params,
+                    status, priority, added_at
+                ) VALUES (?, ?, ?, ?, ?, ?, ?, NULL, 'queued', 0, ?)
+                """,
+                (
+                    new_id,
+                    row["model_id"],
+                    row["model_version_id"],
+                    row["model_name"],
+                    row["version_name"],
+                    row["thumbnail_url"],
+                    "retry",
+                    now,
+                ),
+            )
+            conn.commit()
+            queued = conn.execute(
+                "SELECT * FROM download_queue WHERE download_id = ?",
+                (new_id,),
+            ).fetchone()
+
+        return dict(queued) if queued else None
+
+    async def retry_all_failed(self) -> int:
+        """Re-queue all failed and canceled downloads from history.
+
+        Returns the number of items that were re-queued.
+        """
+        async with self._lock:
+            conn = self._get_conn()
+            rows = conn.execute(
+                "SELECT * FROM download_history WHERE status IN ('failed', 'canceled')"
+            ).fetchall()
+            if not rows:
+                return 0
+
+            import uuid
+
+            now = time.time()
+            count = 0
+            for row in rows:
+                new_id = str(uuid.uuid4())
+                conn.execute(
+                    """
+                    INSERT INTO download_queue (
+                        download_id, model_id, model_version_id, model_name,
+                        version_name, thumbnail_url, source, file_params,
+                        status, priority, added_at
+                    ) VALUES (?, ?, ?, ?, ?, ?, ?, NULL, 'queued', 0, ?)
+                    """,
+                    (
+                        new_id,
+                        row["model_id"],
+                        row["model_version_id"],
+                        row["model_name"],
+                        row["version_name"],
+                        row["thumbnail_url"],
+                        "retry",
+                        now,
+                    ),
+                )
+                count += 1
+            conn.commit()
+
+        return count
+
+    # ------------------------------------------------------------------
+    # Stats
+    # ------------------------------------------------------------------
+
+    async def get_stats(self) -> dict[str, int]:
+        """Return aggregate counts across both tables.
+
+        Returns a dict with keys ``queued``, ``downloading``, ``paused``
+        (all from the queue table) and ``completed``, ``failed``,
+        ``canceled`` (all from the history table).
+        """
+        async with self._lock:
+            conn = self._get_conn()
+
+            queue_rows = conn.execute(
+                "SELECT status, COUNT(*) AS cnt FROM download_queue GROUP BY status"
+            ).fetchall()
+            queue_stats: dict[str, int] = {}
+            for row in queue_rows:
+                queue_stats[str(row["status"])] = row["cnt"]
+
+            history_rows = conn.execute(
+                "SELECT status, COUNT(*) AS cnt FROM download_history GROUP BY status"
+            ).fetchall()
+            history_stats: dict[str, int] = {}
+            for row in history_rows:
+                history_stats[str(row["status"])] = row["cnt"]
+
+        return {
+            "queued": queue_stats.get("queued", 0),
+            "downloading": queue_stats.get("downloading", 0),
+            "paused": queue_stats.get("paused", 0),
+            "completed": history_stats.get("completed", 0),
+            "failed": history_stats.get("failed", 0),
+            "canceled": history_stats.get("canceled", 0),
+        }

py/services/downloaded_version_history_service.py

@@ -64,6 +64,7 @@ class DownloadedVersionHistoryService:
         self._db_path = db_path or _resolve_database_path()
         self._settings = settings_manager or get_settings_manager()
         self._lock = asyncio.Lock()
+        self._conn: sqlite3.Connection | None = None
         self._schema_initialized = False
         self._ensure_directory()
         self._initialize_schema()
@@ -78,6 +79,12 @@ class DownloadedVersionHistoryService:
         conn.row_factory = sqlite3.Row
         return conn
 
+    def _get_conn(self) -> sqlite3.Connection:
+        if self._conn is None:
+            self._conn = sqlite3.connect(self._db_path, check_same_thread=False)
+            self._conn.row_factory = sqlite3.Row
+        return self._conn
+
     def _initialize_schema(self) -> None:
         if self._schema_initialized:
             return
@@ -89,6 +96,21 @@ class DownloadedVersionHistoryService:
     def get_database_path(self) -> str:
         return self._db_path
 
+    def close(self) -> None:
+        """Close the persistent SQLite connection, if open.
+
+        This is called before plugin update operations to release the
+        database file lock on Windows, allowing ``shutil.rmtree()`` to
+        succeed when the cache resides inside the plugin directory.
+        """
+        if self._conn is not None:
+            try:
+                self._conn.close()
+            except Exception:
+                pass
+            finally:
+                self._conn = None
+
     def _get_active_library_name(self) -> str | None:
         try:
             value = self._settings.get_active_library_name()
@@ -116,7 +138,7 @@ class DownloadedVersionHistoryService:
         timestamp = time.time()
 
         async with self._lock:
-            with self._connect() as conn:
+            conn = self._get_conn()
             conn.execute(
                 """
                 INSERT INTO downloaded_model_versions (
@@ -180,7 +202,7 @@ class DownloadedVersionHistoryService:
             return
 
         async with self._lock:
-            with self._connect() as conn:
+            conn = self._get_conn()
             conn.executemany(
                 """
                 INSERT INTO downloaded_model_versions (
@@ -199,7 +221,7 @@ class DownloadedVersionHistoryService:
             )
             conn.commit()
 
-    async def mark_not_downloaded(self, model_type: str, version_id: int) -> None:
+    async def mark_as_deleted(self, model_type: str, version_id: int) -> None:
         normalized_type = _normalize_model_type(model_type)
         normalized_version_id = _normalize_int(version_id)
         if normalized_type is None or normalized_version_id is None:
@@ -208,7 +230,7 @@ class DownloadedVersionHistoryService:
         timestamp = time.time()
 
         async with self._lock:
-            with self._connect() as conn:
+            conn = self._get_conn()
             conn.execute(
                 """
                 INSERT INTO downloaded_model_versions (
@@ -238,7 +260,7 @@ class DownloadedVersionHistoryService:
             return False
 
         async with self._lock:
-            with self._connect() as conn:
+            conn = self._get_conn()
             row = conn.execute(
                 """
                 SELECT is_deleted_override
@@ -258,7 +280,7 @@ class DownloadedVersionHistoryService:
             return []
 
         async with self._lock:
-            with self._connect() as conn:
+            conn = self._get_conn()
             rows = conn.execute(
                 """
                 SELECT version_id
@@ -291,7 +313,7 @@ class DownloadedVersionHistoryService:
         params: list[object] = [normalized_type, *normalized_model_ids]
 
         async with self._lock:
-            with self._connect() as conn:
+            conn = self._get_conn()
             rows = conn.execute(
                 f"""
                 SELECT model_id, version_id

py/services/downloader.py

@@ -13,6 +13,7 @@ This module provides a centralized download service with:
 import os
 import logging
 import asyncio
+import ssl
 import aiohttp
 from collections import deque
 from dataclasses import dataclass
@@ -31,6 +32,20 @@ from .errors import RateLimitError
 logger = logging.getLogger(__name__)
 
 
+def is_ssl_cert_verify_error(exc: BaseException) -> bool:
+    """Check if an exception represents an SSL certificate verification failure.
+
+    Matches ``ssl.SSLCertVerificationError``, ``aiohttp.ClientConnectorCertificateError``
+    (which wraps the former), and falls back to the standard OpenSSL error text.
+    """
+    if isinstance(exc, ssl.SSLCertVerificationError):
+        return True
+    cert_error = getattr(exc, "certificate_error", None)
+    if isinstance(cert_error, ssl.SSLCertVerificationError):
+        return True
+    return "CERTIFICATE_VERIFY_FAILED" in str(exc)
+
+
 @dataclass(frozen=True)
 class DownloadProgress:
     """Snapshot of a download transfer at a moment in time."""
@@ -241,7 +256,9 @@ class Downloader:
                 self._session = None
 
         # Check for app-level proxy settings
-        proxy_url = None
+        proxy_url = None  # http(s) proxy, passed via the per-request `proxy=` kwarg
+        socks_proxy_url = None  # SOCKS proxy, handled via aiohttp-socks connector
+        app_proxy_active = False
         settings_manager = get_settings_manager()
         if settings_manager.get("proxy_enabled", False):
             proxy_host = settings_manager.get("proxy_host", "").strip()
@@ -253,9 +270,19 @@ class Downloader:
             if proxy_host and proxy_port:
                 # Build proxy URL
                 if proxy_username and proxy_password:
-                    proxy_url = f"{proxy_type}://{proxy_username}:{proxy_password}@{proxy_host}:{proxy_port}"
+                    full_proxy_url = f"{proxy_type}://{proxy_username}:{proxy_password}@{proxy_host}:{proxy_port}"
                 else:
-                    proxy_url = f"{proxy_type}://{proxy_host}:{proxy_port}"
+                    full_proxy_url = f"{proxy_type}://{proxy_host}:{proxy_port}"
+
+                app_proxy_active = True
+                # aiohttp cannot tunnel SOCKS via the per-request `proxy=` kwarg
+                # (it would send HTTP to the SOCKS port and fail parsing the
+                # SOCKS handshake reply). SOCKS must be handled by an
+                # aiohttp-socks ProxyConnector instead.
+                if proxy_type.startswith("socks"):
+                    socks_proxy_url = full_proxy_url
+                else:
+                    proxy_url = full_proxy_url
 
                 logger.debug(
                     f"Using app-level proxy: {proxy_type}://{proxy_host}:{proxy_port}"
@@ -265,14 +292,41 @@ class Downloader:
             logger.debug(
                 "Proxy mode: system-level proxy (trust_env) will be used if configured in environment."
             )
+        # Build SSL context: prefer certifi's CA bundle for broader
+        # CA coverage across different Python environments (especially
+        # embedded/compatibility Python builds).
+        try:
+            import certifi  # type: ignore[import-untyped]
+
+            ca_path = certifi.where()
+            ssl_context = ssl.create_default_context(cafile=ca_path)
+            logger.debug("SSL: using certifi CA bundle at %s", ca_path)
+        except (ImportError, FileNotFoundError, ValueError, OSError):
+            ssl_context = ssl.create_default_context()
+            logger.debug("SSL: certifi unavailable; using system default CA bundle")
+
         # Optimize TCP connection parameters
-        connector = aiohttp.TCPConnector(
+        connector_kwargs = dict(
-            ssl=True,
+            ssl=ssl_context,
             limit=8,  # Concurrent connections
             ttl_dns_cache=300,  # DNS cache timeout
             force_close=False,  # Keep connections for reuse
             enable_cleanup_closed=True,
         )
+        if socks_proxy_url:
+            # Route all traffic through the SOCKS proxy via aiohttp-socks. The
+            # connector tunnels every connection, so no per-request `proxy=` is
+            # used (and must not be — see self._proxy_url below).
+            try:
+                from aiohttp_socks import ProxyConnector
+            except ImportError as e:  # pragma: no cover
+                raise RuntimeError(
+                    "A SOCKS proxy is configured but the 'aiohttp-socks' package "
+                    "is not installed. Install it with: pip install aiohttp-socks"
+                ) from e
+            connector = ProxyConnector.from_url(socks_proxy_url, **connector_kwargs)
+        else:
+            connector = aiohttp.TCPConnector(**connector_kwargs)
 
         # Configure timeout parameters
         timeout = aiohttp.ClientTimeout(
@@ -283,12 +337,14 @@ class Downloader:
 
         self._session = aiohttp.ClientSession(
             connector=connector,
-            trust_env=proxy_url
+            # Only fall back to system/env proxy when no app-level proxy is active
-            is None,  # Only use system proxy if no app-level proxy is set
+            trust_env=not app_proxy_active,
             timeout=timeout,
         )
 
-        # Store proxy URL for use in requests
+        # Store proxy URL for per-request use. Stays None for SOCKS because the
+        # ProxyConnector already tunnels everything; passing proxy= for SOCKS
+        # would re-trigger the original aiohttp parse error.
         self._proxy_url = proxy_url
         self._session_created_at = datetime.now()
 
@@ -736,6 +792,17 @@ class Downloader:
                 DownloadRestartRequested,
             ) as e:
                 retry_count += 1
+
+                if is_ssl_cert_verify_error(e):
+                    logger.error(
+                        "SSL certificate verification failed when connecting to %s. "
+                        "This is usually caused by an outdated CA certificate bundle "
+                        "in the Python environment. Recommended fixes:\n"
+                        "  1. pip install --upgrade certifi\n"
+                        "  2. pip install pip-system-certs",
+                        url,
+                    )
+
                 logger.warning(
                     f"Network error during download (attempt {retry_count}/{self.max_retries + 1}): {e}"
                 )

py/services/embedding_service.py

@@ -3,6 +3,7 @@ import logging
 from typing import Dict
 
 from .base_model_service import BaseModelService
+from .auto_tag_service import extract_auto_tags
 from ..utils.models import EmbeddingMetadata
 from ..config import config
 
@@ -45,7 +46,8 @@ class EmbeddingService(BaseModelService):
             "exclude": bool(embedding_data.get("exclude", False)),
             "update_available": bool(embedding_data.get("update_available", False)),
             "skip_metadata_refresh": bool(embedding_data.get("skip_metadata_refresh", False)),
-            "civitai": self.filter_civitai_data(embedding_data.get("civitai", {}), minimal=True)
+            "civitai": self.filter_civitai_data(embedding_data.get("civitai", {}), minimal=True),
+            "auto_tags": embedding_data.get("auto_tags") or extract_auto_tags(embedding_data),
         }
     
     def find_duplicate_hashes(self) -> Dict:

py/services/lora_service.py

@@ -5,6 +5,7 @@ from typing import Dict, List, Optional
 
 from .base_model_service import BaseModelService
 from .model_query import resolve_sub_type
+from .auto_tag_service import extract_auto_tags
 from ..utils.models import LoraMetadata
 from ..config import config
 
@@ -57,6 +58,7 @@ class LoraService(BaseModelService):
             "civitai": self.filter_civitai_data(
                 lora_data.get("civitai", {}), minimal=True
             ),
+            "auto_tags": lora_data.get("auto_tags") or extract_auto_tags(lora_data),
         }
 
     async def _apply_specific_filters(self, data: List[Dict], **kwargs) -> List[Dict]:
@@ -310,8 +312,23 @@ class LoraService(BaseModelService):
         """Return cached raw metadata for a LoRA matching the given filename."""
         cache = await self.scanner.get_cached_data(force_refresh=False)
 
+        fn_normalized = filename.replace("\\", "/")
+        fn_no_ext = fn_normalized
+        for ext in (".safetensors", ".ckpt", ".pt", ".bin"):
+            if fn_no_ext.lower().endswith(ext):
+                fn_no_ext = fn_no_ext[: -len(ext)]
+                break
+
         for lora in cache.raw_data if cache else []:
-            if lora.get("file_name") == filename:
+            file_name = lora.get("file_name", "")
+            folder = lora.get("folder", "")
+            file_name_no_ext = file_name
+            for ext in (".safetensors", ".ckpt", ".pt", ".bin"):
+                if file_name_no_ext.lower().endswith(ext):
+                    file_name_no_ext = file_name_no_ext[: -len(ext)]
+                    break
+            path_name = f"{folder}/{file_name_no_ext}".replace("\\", "/") if folder else file_name_no_ext
+            if fn_no_ext in (file_name_no_ext, path_name):
                 return lora
 
         return None
@@ -399,7 +416,10 @@ class LoraService(BaseModelService):
             locked_loras = locked_loras[:target_count]
 
         # Filter out locked LoRAs from available pool
-        locked_names = {lora["name"] for lora in locked_loras}
+        locked_names = {
+            os.path.basename(lora["name"]) if "/" in str(lora.get("name", "")) else lora["name"]
+            for lora in locked_loras
+        }
         available_pool = [
             l for l in available_loras if l["file_name"] not in locked_names
         ]
@@ -454,7 +474,7 @@ class LoraService(BaseModelService):
 
             result_loras.append(
                 {
-                    "name": lora["file_name"],
+                    "name": f"{lora['folder']}/{lora['file_name']}" if lora.get("folder") else lora["file_name"],
                     "strength": model_str,
                     "clipStrength": clip_str,
                     "active": True,
@@ -670,8 +690,9 @@ class LoraService(BaseModelService):
         # Return minimal data needed for cycling
         return [
             {
-                "file_name": lora["file_name"],
+                "file_name": f"{lora['folder']}/{lora['file_name']}" if lora.get("folder") else lora["file_name"],
                 "model_name": lora.get("model_name", lora["file_name"]),
+                "folder": lora.get("folder", ""),
             }
             for lora in available_loras
         ]

py/services/model_hash_index.py

@@ -7,6 +7,7 @@ class ModelHashIndex:
     def __init__(self):
         self._hash_to_path: Dict[str, str] = {}
         self._filename_to_hash: Dict[str, str] = {}
+        self._autov2_to_path: Dict[str, str] = {}
         # New data structures for tracking duplicates
         self._duplicate_hashes: Dict[str, List[str]] = {}  # sha256 -> list of paths
         self._duplicate_filenames: Dict[str, List[str]] = {}  # filename -> list of paths
@@ -63,6 +64,9 @@ class ModelHashIndex:
         # Add new mappings
         self._hash_to_path[sha256] = file_path
         self._filename_to_hash[filename] = sha256
+        # AutoV2 = first 10 chars of SHA256
+        if len(sha256) >= 10:
+            self._autov2_to_path[sha256[:10]] = file_path
     
     def _get_filename_from_path(self, file_path: str) -> str:
         """Extract filename without extension from path"""
@@ -79,6 +83,12 @@ class ModelHashIndex:
                     hash_val = h
                     break
         
+        if hash_val is None:
+            for h, paths in self._duplicate_hashes.items():
+                if file_path in paths:
+                    hash_val = h
+                    break
+        
         # If we didn't find a hash, nothing to do
         if not hash_val:
             return
@@ -152,6 +162,11 @@ class ModelHashIndex:
                 if filename in self._filename_to_hash:
                     del self._filename_to_hash[filename]
 
+        # Remove from AutoV2 index
+        autov2_keys_to_remove = [k for k, v in self._autov2_to_path.items() if v == file_path]
+        for k in autov2_keys_to_remove:
+            del self._autov2_to_path[k]
+
     def remove_by_hash(self, sha256: str) -> None:
         """Remove entry by hash"""
         sha256 = sha256.lower()
@@ -171,6 +186,10 @@ class ModelHashIndex:
         # Remove hash-to-path mapping
         del self._hash_to_path[sha256]
         
+        autov2_key = sha256[:10]
+        if autov2_key in self._autov2_to_path:
+            del self._autov2_to_path[autov2_key]
+        
         # Update filename-to-hash and duplicate filenames for all paths
         for path_to_remove in paths_to_remove:
             fname = self._get_filename_from_path(path_to_remove)
@@ -189,13 +208,24 @@ class ModelHashIndex:
                     # If only one entry remains, it's no longer a duplicate
                     del self._duplicate_filenames[fname]
     
-    def has_hash(self, sha256: str) -> bool:
+    def has_hash(self, hash_value: str) -> bool:
-        """Check if hash exists in index"""
+        """Check if hash exists in index (SHA256 or AutoV2)"""
-        return sha256.lower() in self._hash_to_path
+        normalized = hash_value.lower()
+        if normalized in self._hash_to_path:
+            return True
+        if len(normalized) == 10:
+            return normalized in self._autov2_to_path
+        return False
 
-    def get_path(self, sha256: str) -> Optional[str]:
+    def get_path(self, hash_value: str) -> Optional[str]:
-        """Get file path for a hash"""
+        """Get file path for a hash (SHA256 or AutoV2)"""
-        return self._hash_to_path.get(sha256.lower())
+        normalized = hash_value.lower()
+        path = self._hash_to_path.get(normalized)
+        if path is not None:
+            return path
+        if len(normalized) == 10:
+            return self._autov2_to_path.get(normalized)
+        return None
     
     def get_hash(self, file_path: str) -> Optional[str]:
         """Get hash for a file path"""
@@ -203,13 +233,16 @@ class ModelHashIndex:
         return self._filename_to_hash.get(filename)
     
     def get_hash_by_filename(self, filename: str) -> Optional[str]:
-        """Get hash for a filename without extension"""
+        """Get hash for a filename (bare basename or path-prefixed name)"""
+        if "/" in filename or "\\" in filename:
+            filename = os.path.splitext(os.path.basename(filename.replace("\\", "/")))[0]
         return self._filename_to_hash.get(filename)
     
     def clear(self) -> None:
         """Clear all entries"""
         self._hash_to_path.clear()
         self._filename_to_hash.clear()
+        self._autov2_to_path.clear()
         self._duplicate_hashes.clear()
         self._duplicate_filenames.clear()
     

py/services/model_lifecycle_service.py

@@ -111,6 +111,11 @@ class ModelLifecycleService:
             self._scanner._hash_index.remove_by_path(file_path)
 
         await self._sync_update_for_model(model_id)
+
+        persist_current_cache = getattr(self._scanner, "_persist_current_cache", None)
+        if callable(persist_current_cache):
+            await persist_current_cache()
+
         return {"success": True, "deleted_files": deleted_files}
 
     @staticmethod

py/services/model_metadata_provider.py

@@ -5,7 +5,7 @@ import logging
 import random
 from typing import Optional, Dict, Tuple, Any, List, Sequence
 from .downloader import get_downloader
-from .errors import RateLimitError
+from .errors import RateLimitError, ResourceNotFoundError
 
 try:
     from bs4 import BeautifulSoup
@@ -81,7 +81,11 @@ class _RateLimitRetryHelper:
 
     def _calculate_delay(self, retry_after: Optional[float], attempt: int) -> float:
         if retry_after is not None:
-            return min(self._max_delay, max(0.0, retry_after))
+            # Cap at 1800s (30 min) as a safety ceiling. The old 30s cap was
+            # too low — CivArchive can return retry_after ~1500s, causing all
+            # retries to fail. A generous ceiling protects against pathological
+            # server values while still respecting the server's guidance.
+            return min(1800.0, max(0.0, retry_after))
 
         base_delay = self._base_delay * (2 ** max(0, attempt - 1))
         jitter_span = base_delay * self._jitter_ratio
@@ -109,6 +113,18 @@ class ModelMetadataProvider(ABC):
         """Fetch model versions for multiple model ids when supported."""
         raise NotImplementedError
 
+    async def get_model_versions_by_hashes(
+        self, hashes: List[str]
+    ) -> Optional[List[Dict]]:
+        """Fetch full version details for multiple SHA256 hashes.
+
+        Used specifically to retrieve ``usageControl`` which is only
+        available from the per-version / by-hash API, not from model-level
+        responses.  Providers that cannot resolve hashes should let the
+        default ``NotImplementedError`` propagate.
+        """
+        raise NotImplementedError
+        
     @abstractmethod
     async def get_model_version(self, model_id: int = None, version_id: int = None) -> Optional[Dict]:
         """Get specific model version with additional metadata"""
@@ -141,6 +157,11 @@ class CivitaiModelMetadataProvider(ModelMetadataProvider):
     ) -> Optional[Dict[int, Dict]]:
         return await self.client.get_model_versions_bulk(model_ids)
 
+    async def get_model_versions_by_hashes(
+        self, hashes: List[str]
+    ) -> Optional[List[Dict]]:
+        return await self.client.get_model_versions_by_hashes(hashes)
+        
     async def get_model_version(self, model_id: int = None, version_id: int = None) -> Optional[Dict]:
         return await self.client.get_model_version(model_id, version_id)
         
@@ -465,6 +486,7 @@ class FallbackMetadataProvider(ModelMetadataProvider):
         return None, "Model not found"
 
     async def get_model_versions(self, model_id: str) -> Optional[Dict]:
+        not_found_confirmed = False
         for provider, label in self._iter_providers():
             try:
                 result = await self._call_with_rate_limit(
@@ -475,8 +497,24 @@ class FallbackMetadataProvider(ModelMetadataProvider):
                 if result:
                     return result
             except RateLimitError as exc:
+                if not_found_confirmed:
+                    logger.debug(
+                        "Suppressing rate limit from %s for model %s: "
+                        "already confirmed as not found by another provider",
+                        label,
+                        model_id,
+                    )
+                    return None
                 exc.provider = exc.provider or label
                 raise exc
+            except ResourceNotFoundError:
+                not_found_confirmed = True
+                logger.debug(
+                    "Provider %s reports model %s as not found",
+                    label,
+                    model_id,
+                )
+                continue
             except Exception as e:
                 logger.debug("Provider %s failed for get_model_versions: %s", label, e)
                 continue
@@ -519,6 +557,32 @@ class FallbackMetadataProvider(ModelMetadataProvider):
                 continue
         return None, "No provider could retrieve the data"
 
+    async def get_model_versions_by_hashes(
+        self, hashes: List[str]
+    ) -> Optional[List[Dict]]:
+        for provider, label in self._iter_providers():
+            try:
+                result = await self._call_with_rate_limit(
+                    label,
+                    provider.get_model_versions_by_hashes,
+                    hashes,
+                )
+                if result is not None:
+                    return result
+            except NotImplementedError:
+                continue
+            except RateLimitError as exc:
+                exc.provider = exc.provider or label
+                raise exc
+            except Exception as e:
+                logger.debug(
+                    "Provider %s failed for get_model_versions_by_hashes: %s",
+                    label,
+                    e,
+                )
+                continue
+        return None
+
     async def get_user_models(self, username: str) -> Optional[List[Dict]]:
         for provider, label in self._iter_providers():
             try:
@@ -593,6 +657,15 @@ class RateLimitRetryingProvider(ModelMetadataProvider):
             model_ids,
         )
 
+    async def get_model_versions_by_hashes(
+        self, hashes: List[str]
+    ) -> Optional[List[Dict]]:
+        return await self._rate_limit_helper.run(
+            self._label,
+            self._provider.get_model_versions_by_hashes,
+            hashes,
+        )
+
     async def get_model_version(self, model_id: int = None, version_id: int = None) -> Optional[Dict]:
         return await self._rate_limit_helper.run(
             self._label,
@@ -669,6 +742,17 @@ class ModelMetadataProviderManager:
         provider = self._get_provider(provider_name)
         return await provider.get_model_version_info(version_id)
 
+    async def get_model_versions_by_hashes(
+        self,
+        hashes: List[str],
+        provider_name: str = None,
+    ) -> Optional[List[Dict]]:
+        provider = self._get_provider(provider_name)
+        try:
+            return await provider.get_model_versions_by_hashes(hashes)
+        except NotImplementedError:
+            return None
+
     async def get_user_models(self, username: str, provider_name: str = None) -> Optional[List[Dict]]:
         """Fetch models owned by the specified user"""
         provider = self._get_provider(provider_name)

py/services/model_query.py

@@ -96,6 +96,7 @@ class FilterCriteria:
     folder_exclude: Optional[Sequence[str]] = None
     base_models: Optional[Sequence[str]] = None
     tags: Optional[Dict[str, str]] = None
+    auto_tags: Optional[Dict[str, str]] = None
     favorites_only: bool = False
     search_options: Optional[Dict[str, Any]] = None
     model_types: Optional[Sequence[str]] = None
@@ -359,10 +360,37 @@ class ModelFilterSet:
                 ]
             model_types_duration = time.perf_counter() - t0
 
+        auto_tags_duration = 0
+        auto_tag_filters = criteria.auto_tags or {}
+        if auto_tag_filters:
+            t0 = time.perf_counter()
+            include_at = set()
+            exclude_at = set()
+            for tag, state in auto_tag_filters.items():
+                if not tag:
+                    continue
+                if state == "exclude":
+                    exclude_at.add(tag)
+                else:
+                    include_at.add(tag)
+
+            if include_at:
+                items = [
+                    item for item in items
+                    if any(tag in include_at for tag in (item.get("auto_tags") or []))
+                ]
+
+            if exclude_at:
+                items = [
+                    item for item in items
+                    if not any(tag in exclude_at for tag in (item.get("auto_tags") or []))
+                ]
+            auto_tags_duration = time.perf_counter() - t0
+
         duration = time.perf_counter() - overall_start
         if duration > 0.1:  # Only log if it's potentially slow
             logger.debug(
-                "ModelFilterSet.apply took %.3fs (sfw: %.3fs, fav: %.3fs, folder: %.3fs, base: %.3fs, tags: %.3fs, types: %.3fs). "
+                "ModelFilterSet.apply took %.3fs (sfw: %.3fs, fav: %.3fs, folder: %.3fs, base: %.3fs, tags: %.3fs, types: %.3fs, auto_tags: %.3fs). "
                 "Count: %d -> %d",
                 duration,
                 sfw_duration,
@@ -371,6 +399,7 @@ class ModelFilterSet:
                 base_models_duration,
                 tags_duration,
                 model_types_duration,
+                auto_tags_duration,
                 initial_count,
                 len(items),
             )

py/services/model_scanner.py

@@ -9,7 +9,7 @@ from typing import Any, Awaitable, Callable, Dict, List, Mapping, Optional, Set,
 
 from ..utils.models import BaseModelMetadata
 from ..config import config
-from ..utils.file_utils import find_preview_file, get_preview_extension
+from ..utils.file_utils import find_preview_file, get_preview_extension, calculate_sha256
 from ..utils.metadata_manager import MetadataManager
 from ..utils.civitai_utils import resolve_license_info
 from .model_cache import ModelCache
@@ -1067,19 +1067,24 @@ class ModelScanner:
 
         model_data = self._build_cache_entry(metadata, folder=normalized_folder)
 
+        # Compute SHA256 hash when metadata provided none (e.g., CivitAI API response has empty hashes)
+        if not model_data.get('sha256') and file_path:
+            try:
+                logger.info(f"Computing SHA256 hash for {file_path} (was empty from metadata)")
+                sha256 = await calculate_sha256(file_path)
+                if sha256:
+                    model_data['sha256'] = sha256.lower()
+                    if isinstance(metadata, BaseModelMetadata):
+                        metadata.sha256 = sha256.lower()
+                    await MetadataManager.save_metadata(file_path, metadata)
+            except Exception as e:
+                logger.error(f"Failed to compute SHA256 for {file_path}: {e}")
+
         # Skip excluded models
         if model_data.get('exclude', False):
             excluded_models.append(model_data['file_path'])
             return None
 
-        # Check for duplicate filename before adding to hash index
-        # filename = os.path.splitext(os.path.basename(file_path))[0]
-        # existing_hash = hash_index.get_hash_by_filename(filename)
-        # if existing_hash and existing_hash != model_data.get('sha256', '').lower():
-        #     existing_path = hash_index.get_path(existing_hash)
-        #     if existing_path and existing_path != file_path:
-        #         logger.warning(f"Duplicate filename detected: '{filename}' - files: '{existing_path}' and '{file_path}'")
-
         return model_data
 
     async def _apply_scan_result(self, scan_result: CacheBuildResult) -> None:
@@ -1105,6 +1110,39 @@ class ModelScanner:
 
         await self._cache.resort()
 
+        self._log_duplicate_filename_summary()
+
+    def _log_duplicate_filename_summary(self) -> None:
+        """Log a batched summary of duplicate filename conflicts once per scan."""
+        # Duplicate filename detection is only relevant for LoRAs, which use
+        # basename-only syntax (<lora:name:strength>). Checkpoints and embeddings
+        # use full relative paths for resolution, so conflicts are not ambiguous.
+        if self._hash_index is None or self.model_type != "lora":
+            return
+
+        # When full path syntax is active, duplicate filenames across subfolders
+        # are fully qualified, so there is no ambiguity — skip the warning.
+        if get_settings_manager().get("lora_syntax_format", "legacy") == "full":
+            return
+
+        duplicates = self._hash_index.get_duplicate_filenames()
+        if not duplicates:
+            return
+
+        total_files = sum(len(paths) for paths in duplicates.values())
+        conflict_count = len(duplicates)
+        model_type_label = self.model_type or "model"
+
+        logger.warning(
+            "Duplicate filename conflict detected: %d %s filename(s) "
+            "are shared by %d files total, causing ambiguity in %s resolution. "
+            "Open the Doctor panel to resolve one-click.",
+            conflict_count,
+            model_type_label,
+            total_files,
+            model_type_label.capitalize(),
+        )
+
     async def _sync_download_history(
         self,
         raw_data: List[Mapping[str, Any]],
@@ -1456,6 +1494,15 @@ class ModelScanner:
                 file_path_override=normalized_new_path,
             )
 
+            # Ensure sha256 is populated even when metadata doesn't have it
+            if not cache_entry.get('sha256') and normalized_new_path and os.path.exists(normalized_new_path):
+                try:
+                    sha256 = await calculate_sha256(normalized_new_path)
+                    if sha256:
+                        cache_entry['sha256'] = sha256.lower()
+                except Exception as e:
+                    logger.error(f"Failed to compute SHA256 for {normalized_new_path}: {e}")
+
             if recalculate_type:
                 cache_entry = self.adjust_cached_entry(cache_entry)
 
@@ -1556,11 +1603,38 @@ class ModelScanner:
         try:
             cache = await self.get_cached_data()
 
+            name_normalized = name.replace("\\", "/")
+            name_no_ext = name_normalized
+            for ext in (".safetensors", ".ckpt", ".pt", ".bin"):
+                if name_no_ext.lower().endswith(ext):
+                    name_no_ext = name_no_ext[: -len(ext)]
+                    break
+
+            has_path = "/" in name_no_ext
+            basename = os.path.basename(name_no_ext) if has_path else name_no_ext
+            best_fallback = None
+
             for model in cache.raw_data:
-                if model.get("file_name") == name:
+                file_name = model.get("file_name", "")
+                folder = model.get("folder", "")
+                file_name_no_ext = file_name
+                for ext in (".safetensors", ".ckpt", ".pt", ".bin"):
+                    if file_name_no_ext.lower().endswith(ext):
+                        file_name_no_ext = file_name_no_ext[: -len(ext)]
+                        break
+                path_name = f"{folder}/{file_name_no_ext}".replace("\\", "/") if folder else file_name_no_ext
+
+                if name_no_ext == file_name_no_ext or name_no_ext == path_name:
                     return model
 
-            return None
+                if has_path and file_name_no_ext == basename:
+                    if folder and name_no_ext.startswith(folder.replace("\\", "/") + "/"):
+                        best_fallback = model
+                    elif best_fallback is None:
+                        best_fallback = model
+
+            return best_fallback
+
         except Exception as e:
             logger.error(f"Error getting model info by name: {e}", exc_info=True)
             return None

py/services/model_update_service.py

@@ -69,6 +69,7 @@ class ModelVersionRecord:
     early_access_ends_at: Optional[str] = None
     sort_index: int = 0
     is_early_access: bool = False
+    usage_control: Optional[str] = None  # "Download", "Generation", "InternalGeneration"
 
 
 @dataclass
@@ -101,11 +102,14 @@ class ModelUpdateRecord:
 
         return [version.version_id for version in self.versions if version.is_in_library]
 
-    def has_update(self, hide_early_access: bool = False) -> bool:
+    def has_update(
+        self, hide_early_access: bool = False, hide_non_downloadable: bool = True
+    ) -> bool:
         """Return True when a non-ignored remote version newer than the newest local copy is available.
 
         Args:
             hide_early_access: If True, exclude early access versions from update check.
+            hide_non_downloadable: If True, exclude versions that don't allow downloads.
         """
 
         if self.should_ignore_model:
@@ -121,6 +125,7 @@ class ModelUpdateRecord:
                 not version.is_in_library
                 and not version.should_ignore
                 and not (hide_early_access and ModelUpdateRecord._is_early_access_active(version))
+                and not (hide_non_downloadable and not ModelUpdateRecord._is_downloadable(version))
                 for version in self.versions
             )
 
@@ -129,6 +134,8 @@ class ModelUpdateRecord:
                 continue
             if hide_early_access and ModelUpdateRecord._is_early_access_active(version):
                 continue
+            if hide_non_downloadable and not ModelUpdateRecord._is_downloadable(version):
+                continue
             if version.version_id > max_in_library:
                 return True
         return False
@@ -155,11 +162,18 @@ class ModelUpdateRecord:
         # Phase 1: Basic EA flag from bulk API
         return version.is_early_access
 
+    @staticmethod
+    def _is_downloadable(version: ModelVersionRecord) -> bool:
+        if version.usage_control is None:
+            return True
+        return version.usage_control == "Download"
+
     def has_update_for_base(
         self,
         local_version_id: Optional[int],
         local_base_model: Optional[str],
         hide_early_access: bool = False,
+        hide_non_downloadable: bool = True,
     ) -> bool:
         """Return True when a newer remote version with the same base model exists.
 
@@ -167,6 +181,7 @@ class ModelUpdateRecord:
             local_version_id: The current local version id.
             local_base_model: The base model to filter by.
             hide_early_access: If True, exclude early access versions from update check.
+            hide_non_downloadable: If True, exclude versions that don't allow downloads.
         """
 
         if self.should_ignore_model:
@@ -197,6 +212,8 @@ class ModelUpdateRecord:
                 continue
             if hide_early_access and ModelUpdateRecord._is_early_access_active(version):
                 continue
+            if hide_non_downloadable and not ModelUpdateRecord._is_downloadable(version):
+                continue
             version_base = _normalize_base_model(version.base_model)
             if version_base != normalized_base:
                 continue
@@ -209,6 +226,8 @@ class ModelUpdateRecord:
 class ModelUpdateService:
     """Persist and query remote model version metadata."""
 
+    _SQLITE_MAX_VARIABLES = 500
+
     _SCHEMA = """
         PRAGMA foreign_keys = ON;
         CREATE TABLE IF NOT EXISTS model_update_status (
@@ -228,6 +247,7 @@ class ModelUpdateService:
             preview_url TEXT,
             is_in_library INTEGER NOT NULL DEFAULT 0,
             should_ignore INTEGER NOT NULL DEFAULT 0,
+            usage_control TEXT,
             PRIMARY KEY (model_id, version_id),
             FOREIGN KEY(model_id) REFERENCES model_update_status(model_id) ON DELETE CASCADE
         );
@@ -463,6 +483,10 @@ class ModelUpdateService:
                 "ALTER TABLE model_update_versions "
                 "ADD COLUMN is_early_access INTEGER NOT NULL DEFAULT 0"
             ),
+            "usage_control": (
+                "ALTER TABLE model_update_versions "
+                "ADD COLUMN usage_control TEXT"
+            ),
         }
 
         for column, statement in migrations.items():
@@ -665,6 +689,7 @@ class ModelUpdateService:
         *,
         force_refresh: bool = False,
         target_model_ids: Optional[Sequence[int]] = None,
+        folder_path: Optional[str] = None,
     ) -> Dict[int, ModelUpdateRecord]:
         """Refresh update information for every model present in the cache."""
         scanner.reset_cancellation()
@@ -679,6 +704,7 @@ class ModelUpdateService:
         local_versions = await self._collect_local_versions(
             scanner,
             target_model_ids=target_filter,
+            folder_path=folder_path,
         )
         total_models = len(local_versions)
         if total_models == 0:
@@ -965,18 +991,22 @@ class ModelUpdateService:
                 fallback_attempted = True
                 try:
                     response = await metadata_provider.get_model_versions(model_id)
+                    if response is not None:
+                        await self._enrich_version_entries(
+                            metadata_provider,
+                            {model_id: response},
+                        )
                 except RateLimitError:
                     raise
                 except ResourceNotFoundError as exc:
                     fallback_error_message = str(exc) or "resource not found"
                     mark_model_as_ignored = True
                 except Exception as exc:  # pragma: no cover - defensive log
-                    logger.error(
+                    logger.warning(
                         "Failed to fetch versions for model %s (%s): %s",
                         model_id,
                         model_type,
                         exc,
-                        exc_info=True,
                     )
                     fallback_error_message = str(exc)
             if response is not None:
@@ -1059,6 +1089,136 @@ class ModelUpdateService:
             self._upsert_record(record)
             return record
 
+    async def _enrich_version_entries(
+        self,
+        metadata_provider,
+        responses_by_model_id: Dict[int, Mapping],
+    ) -> None:
+        """Enrich version entries with ``usageControl`` via batch hash endpoint.
+
+        The model-level API does not include ``usageControl`` on version
+        entries. This method collects SHA256 hashes from every version's
+        primary model file, calls ``POST /api/v1/model-versions/by-hash``
+        (up to 100 hashes per request), and injects ``usageControl`` +
+        ``earlyAccessEndsAt`` into each version entry dict in-place.
+        """
+        if not metadata_provider or not responses_by_model_id:
+            return
+
+        hashes_by_version: Dict[int, str] = {}
+        for response in responses_by_model_id.values():
+            hashes_by_version.update(
+                self._collect_hashes_from_response(response)
+            )
+
+        if not hashes_by_version:
+            return
+
+        version_ids_by_hash: Dict[str, List[int]] = {}
+        for version_id, sha256 in hashes_by_version.items():
+            version_ids_by_hash.setdefault(sha256, []).append(version_id)
+
+        all_hashes = list(version_ids_by_hash.keys())
+        BATCH_SIZE = 100
+
+        enrichment: Dict[int, Dict] = {}
+        try:
+            for start in range(0, len(all_hashes), BATCH_SIZE):
+                batch = all_hashes[start : start + BATCH_SIZE]
+                try:
+                    enriched = await metadata_provider.get_model_versions_by_hashes(
+                        batch
+                    )
+                except NotImplementedError:
+                    return
+                except RateLimitError:
+                    raise
+                except Exception:
+                    continue
+
+                if not enriched:
+                    continue
+
+                for entry in enriched:
+                    if not isinstance(entry, dict):
+                        continue
+                    version_id = entry.get("id")
+                    if version_id is None:
+                        continue
+                    enrichment[version_id] = {
+                        "usageControl": _normalize_string(
+                            entry.get("usageControl")
+                        ),
+                        "earlyAccessEndsAt": _normalize_string(
+                            entry.get("earlyAccessEndsAt")
+                        ),
+                    }
+        except RateLimitError:
+            raise
+
+        if not enrichment:
+            return
+
+        for response in responses_by_model_id.values():
+            versions = response.get("modelVersions")
+            if not isinstance(versions, list):
+                continue
+            for version in versions:
+                if not isinstance(version, dict):
+                    continue
+                version_id = version.get("id")
+                if version_id not in enrichment:
+                    continue
+                extra = enrichment[version_id]
+                if extra.get("usageControl") and not version.get("usageControl"):
+                    version["usageControl"] = extra["usageControl"]
+                if extra.get("earlyAccessEndsAt") and not version.get(
+                    "earlyAccessEndsAt"
+                ):
+                    version["earlyAccessEndsAt"] = extra["earlyAccessEndsAt"]
+
+    @staticmethod
+    def _collect_hashes_from_response(response: Mapping) -> Dict[int, str]:
+        """Extract ``{version_id: sha256}`` from a model-level API response.
+
+        Returns an empty dict if the response structure is unexpected.
+        """
+        result: Dict[int, str] = {}
+        versions = response.get("modelVersions")
+        if not isinstance(versions, list):
+            return result
+        for entry in versions:
+            if not isinstance(entry, dict):
+                continue
+            version_id = _normalize_int(entry.get("id"))
+            if version_id is None:
+                continue
+            sha256 = ModelUpdateService._extract_sha256_from_version_entry(entry)
+            if sha256:
+                result[version_id] = sha256
+        return result
+
+    @staticmethod
+    def _extract_sha256_from_version_entry(entry: Mapping) -> Optional[str]:
+        """Return the SHA256 hash from the primary model file of a version entry."""
+        files = entry.get("files")
+        if not isinstance(files, list):
+            return None
+        for file_info in files:
+            if not isinstance(file_info, dict):
+                continue
+            if file_info.get("type") != "Model":
+                continue
+            primary = file_info.get("primary")
+            if primary is not True and str(primary).strip().lower() != "true":
+                continue
+            hashes = file_info.get("hashes")
+            if isinstance(hashes, dict):
+                sha256 = hashes.get("SHA256")
+                if sha256:
+                    return sha256
+        return None
+
     async def _fetch_model_versions_bulk(
         self,
         metadata_provider,
@@ -1110,6 +1270,7 @@ class ModelUpdateService:
             len(aggregated),
             provider_name,
         )
+        await self._enrich_version_entries(metadata_provider, aggregated)
         return aggregated
 
     async def _collect_local_versions(
@@ -1117,6 +1278,7 @@ class ModelUpdateService:
         scanner,
         *,
         target_model_ids: Optional[Sequence[int]] = None,
+        folder_path: Optional[str] = None,
     ) -> Dict[int, List[int]]:
         cache = await scanner.get_cached_data()
         mapping: Dict[int, set[int]] = {}
@@ -1129,7 +1291,19 @@ class ModelUpdateService:
             if not target_set:
                 return {}
 
+        normalized_folder = None
+        if folder_path is not None:
+            normalized_folder = folder_path.replace("\\", "/").strip("/")
+
         for item in cache.raw_data:
+            # Apply folder filter first (cheapest check)
+            if normalized_folder is not None:
+                if not isinstance(item, dict):
+                    continue
+                item_folder = (item.get("folder") or "").replace("\\", "/").strip("/")
+                if item_folder != normalized_folder and not item_folder.startswith(normalized_folder + "/"):
+                    continue
+
             civitai = item.get("civitai") if isinstance(item, dict) else None
             if not isinstance(civitai, dict):
                 continue
@@ -1237,6 +1411,7 @@ class ModelUpdateService:
                     sort_index=sort_map.get(version_id, index),
                     early_access_ends_at=remote_version.early_access_ends_at,
                     is_early_access=remote_version.is_early_access,
+                    usage_control=remote_version.usage_control,
                 )
             )
 
@@ -1335,6 +1510,7 @@ class ModelUpdateService:
         # Check availability field from bulk API for basic EA detection
         availability = _normalize_string(entry.get("availability"))
         is_early_access = availability == "EarlyAccess"
+        usage_control = _normalize_string(entry.get("usageControl"))
 
         return ModelVersionRecord(
             version_id=version_id,
@@ -1348,6 +1524,7 @@ class ModelUpdateService:
             early_access_ends_at=early_access_ends_at,
             sort_index=index,
             is_early_access=is_early_access,
+            usage_control=usage_control,
         )
 
     def _extract_size_bytes(self, files) -> Optional[int]:
@@ -1439,32 +1616,40 @@ class ModelUpdateService:
         if not model_ids:
             return {}
 
-        params = tuple(model_ids)
+        ids = list(model_ids)
-        placeholders = ",".join("?" for _ in params)
+        status_rows: list = []
+        version_rows: list = []
 
         with self._connect() as conn:
-            status_rows = conn.execute(
+            for start in range(0, len(ids), self._SQLITE_MAX_VARIABLES):
+                chunk = tuple(ids[start : start + self._SQLITE_MAX_VARIABLES])
+                placeholders = ",".join("?" for _ in chunk)
+
+                chunk_status = conn.execute(
                     f"""
                     SELECT model_id, model_type, last_checked_at, should_ignore_model
                     FROM model_update_status
                     WHERE model_id IN ({placeholders})
                     """,
-                params,
+                    chunk,
                 ).fetchall()
-            if not status_rows:
+                status_rows.extend(chunk_status)
-                return {}
 
-            version_rows = conn.execute(
+                chunk_versions = conn.execute(
                     f"""
                     SELECT model_id, version_id, sort_index, name, base_model, released_at,
                            size_bytes, preview_url, is_in_library, should_ignore, early_access_ends_at,
-                       is_early_access
+                           is_early_access, usage_control
                     FROM model_update_versions
                     WHERE model_id IN ({placeholders})
                     ORDER BY model_id ASC, sort_index ASC, version_id ASC
                     """,
-                params,
+                    chunk,
                 ).fetchall()
+                version_rows.extend(chunk_versions)
+
+            if not status_rows:
+                return {}
 
         versions_by_model: Dict[int, List[ModelVersionRecord]] = {}
         for row in version_rows:
@@ -1482,6 +1667,7 @@ class ModelUpdateService:
                     early_access_ends_at=row["early_access_ends_at"],
                     sort_index=_normalize_int(row["sort_index"]) or 0,
                     is_early_access=bool(row["is_early_access"]),
+                    usage_control=row["usage_control"],
                 )
             )
 
@@ -1538,8 +1724,8 @@ class ModelUpdateService:
                     INSERT INTO model_update_versions (
                         version_id, model_id, sort_index, name, base_model, released_at,
                         size_bytes, preview_url, is_in_library, should_ignore, early_access_ends_at,
-                        is_early_access
+                        is_early_access, usage_control
-                    ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+                    ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
                     """,
                     (
                         version.version_id,
@@ -1554,6 +1740,7 @@ class ModelUpdateService:
                         1 if version.should_ignore else 0,
                         version.early_access_ends_at,
                         1 if version.is_early_access else 0,
+                        version.usage_control,
                     ),
                 )
             conn.commit()

py/services/persistent_recipe_cache.py

@@ -12,7 +12,7 @@ import logging
 import os
 import sqlite3
 import threading
-from dataclasses import dataclass
+from dataclasses import dataclass, field
 from typing import Dict, List, Optional, Set, Tuple
 
 from ..utils.cache_paths import CacheType, resolve_cache_path_with_migration
@@ -26,6 +26,8 @@ class PersistedRecipeData:
 
     raw_data: List[Dict]
     file_stats: Dict[str, Tuple[float, int]]  # json_path -> (mtime, size)
+    image_id_map: Dict[str, str] = field(default_factory=dict)
+    """Precomputed mapping of civitai image_id → recipe_id."""
 
 
 class PersistentRecipeCache:
@@ -38,6 +40,7 @@ class PersistentRecipeCache:
         "json_path",
         "title",
         "folder",
+        "source_path",
         "base_model",
         "fingerprint",
         "created_date",
@@ -115,6 +118,20 @@ class PersistentRecipeCache:
                     if not rows:
                         return None
 
+                    # Restore precomputed image_id_map if available
+                    image_id_map: Dict[str, str] = {}
+                    try:
+                        meta_row = conn.execute(
+                            "SELECT value FROM cache_metadata WHERE key = ?",
+                            ("image_id_map",),
+                        ).fetchone()
+                        if meta_row:
+                            parsed = json.loads(meta_row["value"])
+                            if isinstance(parsed, dict):
+                                image_id_map = parsed
+                    except Exception:
+                        pass  # missing or corrupt — rebuilt on next cache refresh
+
                 finally:
                     conn.close()
         except FileNotFoundError:
@@ -137,14 +154,24 @@ class PersistentRecipeCache:
                     row["file_size"] or 0,
                 )
 
-        return PersistedRecipeData(raw_data=raw_data, file_stats=file_stats)
+        return PersistedRecipeData(
+            raw_data=raw_data,
+            file_stats=file_stats,
+            image_id_map=image_id_map,
+        )
 
-    def save_cache(self, recipes: List[Dict], json_paths: Optional[Dict[str, str]] = None) -> None:
+    def save_cache(
+        self,
+        recipes: List[Dict],
+        json_paths: Optional[Dict[str, str]] = None,
+        image_id_map: Optional[Dict[str, str]] = None,
+    ) -> None:
         """Save all recipes to SQLite cache.
 
         Args:
             recipes: List of recipe dictionaries to persist.
             json_paths: Optional mapping of recipe_id -> json_path for file stats.
+            image_id_map: Optional precomputed civitai image_id → recipe_id mapping.
         """
         if not self.is_enabled():
             return
@@ -185,6 +212,12 @@ class PersistentRecipeCache:
                             recipe_rows,
                         )
 
+                    # Persist image_id_map for O(1) lookups on cache load
+                    conn.execute(
+                        "INSERT OR REPLACE INTO cache_metadata (key, value) VALUES (?, ?)",
+                        ("image_id_map", json.dumps(image_id_map or {})),
+                    )
+
                     conn.commit()
                     logger.debug("Persisted %d recipes to cache", len(recipe_rows))
                 finally:
@@ -272,6 +305,29 @@ class PersistentRecipeCache:
         except Exception as exc:
             logger.debug("Failed to remove recipe %s from cache: %s", recipe_id, exc)
 
+    def save_image_id_map(self, image_id_map: Dict[str, str]) -> None:
+        """Persist the image_id_map to cache_metadata without rewriting the full cache.
+
+        This is called after ``add_recipe`` / ``remove_recipe`` mutations so
+        the persistent copy does not go stale between full ``save_cache`` calls.
+        """
+        if not self.is_enabled() or not self._schema_initialized:
+            return
+
+        try:
+            with self._db_lock:
+                conn = self._connect()
+                try:
+                    conn.execute(
+                        "INSERT OR REPLACE INTO cache_metadata (key, value) VALUES (?, ?)",
+                        ("image_id_map", json.dumps(image_id_map)),
+                    )
+                    conn.commit()
+                finally:
+                    conn.close()
+        except Exception as exc:
+            logger.debug("Failed to persist image_id_map: %s", exc)
+
     def get_indexed_recipe_ids(self) -> Set[str]:
         """Return all recipe IDs in the cache.
 
@@ -334,6 +390,7 @@ class PersistentRecipeCache:
                             json_path TEXT,
                             title TEXT,
                             folder TEXT,
+                            source_path TEXT,
                             base_model TEXT,
                             fingerprint TEXT,
                             created_date REAL,
@@ -358,6 +415,13 @@ class PersistentRecipeCache:
                         );
                         """
                     )
+                    # Migration: add source_path column to existing databases
+                    try:
+                        conn.execute(
+                            "ALTER TABLE recipes ADD COLUMN source_path TEXT"
+                        )
+                    except Exception:
+                        pass  # column already exists
                     conn.commit()
                 self._schema_initialized = True
             except Exception as exc:
@@ -406,6 +470,7 @@ class PersistentRecipeCache:
             json_path,
             recipe.get("title"),
             recipe.get("folder"),
+            recipe.get("source_path"),
             recipe.get("base_model"),
             recipe.get("fingerprint"),
             float(recipe.get("created_date") or 0.0),
@@ -456,6 +521,7 @@ class PersistentRecipeCache:
             "file_path": row["file_path"] or "",
             "title": row["title"] or "",
             "folder": row["folder"] or "",
+            "source_path": row["source_path"] or "",
             "base_model": row["base_model"] or "",
             "fingerprint": row["fingerprint"] or "",
             "created_date": row["created_date"] or 0.0,

py/services/recipe_cache.py

@@ -1,6 +1,6 @@
 import asyncio
 from typing import Iterable, List, Dict, Optional
-from dataclasses import dataclass
+from dataclasses import dataclass, field
 from operator import itemgetter
 from natsort import natsorted
 
@@ -14,6 +14,15 @@ class RecipeCache:
     sorted_by_date: List[Dict]
     folders: List[str] | None = None
     folder_tree: Dict | None = None
+    image_id_map: Dict[str, str] = field(default_factory=dict)
+    """Mapping of civitai image_id → recipe_id, precomputed at cache build time.
+
+    Built once during cache initialization (O(n)) so that
+    ``check_image_exists`` and ``import_from_url`` duplicate checks
+    can look up image_id in O(1) instead of scanning all recipes.
+    Recipes imported from local files have no valid civitai image_id
+    and are naturally excluded from this map.
+    """
 
     def __post_init__(self):
         self._lock = asyncio.Lock()

py/services/recipe_scanner.py

@@ -20,6 +20,7 @@ from .metadata_service import get_default_metadata_provider
 from .checkpoint_scanner import CheckpointScanner
 from .settings_manager import get_settings_manager
 from .recipes.errors import RecipeNotFoundError
+from ..utils.civitai_utils import extract_civitai_image_id
 from ..utils.utils import calculate_recipe_fingerprint, fuzzy_match
 from natsort import natsorted
 import sys
@@ -65,7 +66,7 @@ class RecipeScanner:
             cls._instance._civitai_client = None  # Will be lazily initialized
         return cls._instance
 
-    REPAIR_VERSION = 3
+    REPAIR_VERSION = 4
 
     def __init__(
         self,
@@ -292,6 +293,32 @@ class RecipeScanner:
         if recipe.get("repair_version", 0) >= self.REPAIR_VERSION:
             return False
 
+        # 1.5 Detect and clear corrupted checkpoint (LoRA data saved as checkpoint).
+        #     A checkpoint whose modelVersionId also appears in a LoRA entry is
+        #     definitely wrong — the CivitAI import code used to pick
+        #     modelVersionIds[0] as the checkpoint, which was often a LoRA.
+        #     Clearing it lets the enrichment flow re-resolve the correct
+        #     checkpoint from CivitAI image metadata.
+        cp = recipe.get("checkpoint")
+        lora_mvids = {
+            l.get("modelVersionId")
+            for l in recipe.get("loras", [])
+            if l.get("modelVersionId")
+        }
+        if cp and cp.get("modelVersionId") and cp["modelVersionId"] in lora_mvids:
+            cp_mvid = cp["modelVersionId"]
+            logger.info(
+                "Recipe %s: checkpoint modelVersionId %s matches a LoRA — "
+                "clearing corrupted checkpoint and removing matching LoRA entry",
+                recipe.get("id"),
+                cp_mvid,
+            )
+            recipe["checkpoint"] = None
+            recipe["loras"] = [
+                l for l in recipe.get("loras", [])
+                if l.get("modelVersionId") != cp_mvid
+            ]
+
         # 2. Identification: Is repair needed?
         has_checkpoint = (
             "checkpoint" in recipe
@@ -504,6 +531,23 @@ class RecipeScanner:
                     self._cache.raw_data = recipes
                     self._update_folder_metadata(self._cache)
                     self._sort_cache_sync()
+                    # Backfill source_path from JSON files if missing (schema migration)
+                    if self._backfill_source_path_if_needed(recipes, json_paths):
+                        self._cache.image_id_map = self._build_image_id_map()
+                        self._persistent_cache.save_cache(
+                            recipes, json_paths, self._cache.image_id_map
+                        )
+                    else:
+                        # Use persisted map, or rebuild if empty (e.g. first startup
+                        # after deploying the image_id_map feature).
+                        if persisted.image_id_map:
+                            self._cache.image_id_map = dict(persisted.image_id_map)
+                        else:
+                            self._cache.image_id_map = self._build_image_id_map()
+                            if self._cache.image_id_map:
+                                self._persistent_cache.save_image_id_map(
+                                    self._cache.image_id_map
+                                )
                     return self._cache
                 else:
                     # Partial update: some files changed
@@ -514,8 +558,13 @@ class RecipeScanner:
                     self._cache.raw_data = recipes
                     self._update_folder_metadata(self._cache)
                     self._sort_cache_sync()
+                    # Backfill source_path from JSON files if missing (schema migration)
+                    self._backfill_source_path_if_needed(recipes, json_paths)
+                    self._cache.image_id_map = self._build_image_id_map()
                     # Persist updated cache
-                    self._persistent_cache.save_cache(recipes, json_paths)
+                    self._persistent_cache.save_cache(
+                        recipes, json_paths, self._cache.image_id_map
+                    )
                     return self._cache
 
             # Fall back to full directory scan
@@ -527,9 +576,12 @@ class RecipeScanner:
             self._cache.raw_data = recipes
             self._update_folder_metadata(self._cache)
             self._sort_cache_sync()
+            self._cache.image_id_map = self._build_image_id_map()
 
             # Persist for next startup
-            self._persistent_cache.save_cache(recipes, json_paths)
+            self._persistent_cache.save_cache(
+                recipes, json_paths, self._cache.image_id_map
+            )
 
             return self._cache
         except Exception as e:
@@ -642,6 +694,34 @@ class RecipeScanner:
 
         return recipes, changed, json_paths
 
+    def _backfill_source_path_if_needed(
+        self,
+        recipes: List[Dict],
+        json_paths: Dict[str, str],
+    ) -> bool:
+        """Backfill source_path from recipe JSON files if missing from cache.
+
+        Returns True if any recipes were updated (caller should persist cache).
+        """
+        updated = False
+        for recipe in recipes:
+            if recipe.get("source_path"):
+                continue
+            recipe_id = str(recipe.get("id", ""))
+            json_path = json_paths.get(recipe_id)
+            if not json_path or not os.path.exists(json_path):
+                continue
+            try:
+                with open(json_path, "r", encoding="utf-8") as f:
+                    json_data = json.load(f)
+                file_source_path = json_data.get("source_path")
+                if file_source_path:
+                    recipe["source_path"] = file_source_path
+                    updated = True
+            except Exception:
+                pass
+        return updated
+
     def _full_directory_scan_sync(
         self, recipes_dir: str
     ) -> Tuple[List[Dict], Dict[str, str]]:
@@ -773,6 +853,28 @@ class RecipeScanner:
         except Exception as e:
             logger.error(f"Error sorting recipe cache: {e}")
 
+    def _build_image_id_map(self) -> Dict[str, str]:
+        """Build civitai image_id → recipe_id mapping from cached recipes.
+
+        Only recipes with a valid CivitAI image URL source_path produce an
+        entry.  Recipes imported from local files are naturally excluded.
+        """
+        mapping: Dict[str, str] = {}
+        if not self._cache:
+            return mapping
+        for recipe in getattr(self._cache, "raw_data", []):
+            if not isinstance(recipe, dict):
+                continue
+            source = recipe.get("source_path")
+            if not source:
+                continue
+            image_id = extract_civitai_image_id(source)
+            if image_id and image_id not in mapping:
+                recipe_id = recipe.get("id")
+                if recipe_id is not None:
+                    mapping[image_id] = str(recipe_id)
+        return mapping
+
     async def _wait_for_lora_scanner(self) -> None:
         """Ensure the LoRA scanner has initialized before recipe enrichment."""
 
@@ -1237,11 +1339,20 @@ class RecipeScanner:
         # Update FTS index
         self._update_fts_index_for_recipe(recipe_data, "add")
 
+        source = recipe_data.get("source_path")
+        if source:
+            image_id = extract_civitai_image_id(source)
+            if image_id:
+                recipe_id_value = recipe_data.get("id")
+                if recipe_id_value is not None:
+                    cache.image_id_map[image_id] = str(recipe_id_value)
+
         # Persist to SQLite cache
         if self._persistent_cache:
             recipe_id = str(recipe_data.get("id", ""))
             json_path = self._json_path_map.get(recipe_id, "")
             self._persistent_cache.update_recipe(recipe_data, json_path)
+            self._persistent_cache.save_image_id_map(cache.image_id_map)
 
     async def remove_recipe(self, recipe_id: str) -> bool:
         """Remove a recipe from the cache by ID."""
@@ -1260,9 +1371,15 @@ class RecipeScanner:
         # Update FTS index
         self._update_fts_index_for_recipe(recipe_id, "remove")
 
+        # Remove any image_id entry pointing to this recipe
+        stale = [k for k, v in cache.image_id_map.items() if v == recipe_id]
+        for k in stale:
+            del cache.image_id_map[k]
+
         # Remove from SQLite cache
         if self._persistent_cache:
             self._persistent_cache.remove_recipe(recipe_id)
+            self._persistent_cache.save_image_id_map(cache.image_id_map)
             self._json_path_map.pop(recipe_id, None)
 
         return True
@@ -1273,14 +1390,21 @@ class RecipeScanner:
         cache = await self.get_cached_data()
         removed = await cache.bulk_remove(recipe_ids, resort=False)
         if removed:
+            removed_ids = {str(r.get("id", "")) for r in removed}
+            stale = [k for k, v in cache.image_id_map.items() if v in removed_ids]
+            for k in stale:
+                del cache.image_id_map[k]
+
             self._schedule_resort()
-            # Update FTS index and persistent cache for each removed recipe
             for recipe in removed:
                 recipe_id = str(recipe.get("id", ""))
                 self._update_fts_index_for_recipe(recipe_id, "remove")
                 if self._persistent_cache:
                     self._persistent_cache.remove_recipe(recipe_id)
                     self._json_path_map.pop(recipe_id, None)
+
+            if self._persistent_cache:
+                self._persistent_cache.save_image_id_map(cache.image_id_map)
         return len(removed)
 
     async def scan_all_recipes(self) -> List[Dict]:
@@ -1815,6 +1939,15 @@ class RecipeScanner:
 
         return await self._lora_scanner.get_model_info_by_name(name)
 
+    async def get_local_checkpoint(self, name: str) -> Optional[Dict[str, Any]]:
+        """Lookup a local checkpoint model by name."""
+
+        checkpoint_scanner = getattr(self, "_checkpoint_scanner", None)
+        if not checkpoint_scanner or not name:
+            return None
+
+        return await checkpoint_scanner.get_model_info_by_name(name)
+
     async def get_paginated_data(
         self,
         page: int,
@@ -2475,6 +2608,7 @@ class RecipeScanner:
                 continue
 
             file_name = None
+            folder = ""
             hash_value = (lora.get("hash") or "").lower()
             if (
                 hash_value
@@ -2484,6 +2618,11 @@ class RecipeScanner:
                 file_path = self._lora_scanner._hash_index.get_path(hash_value)
                 if file_path:
                     file_name = os.path.splitext(os.path.basename(file_path))[0]
+                    if lora_cache is not None:
+                        for cached_lora in getattr(lora_cache, "raw_data", []):
+                            if cached_lora.get("file_path") == file_path:
+                                folder = cached_lora.get("folder", "")
+                                break
 
             if not file_name and lora.get("modelVersionId") and lora_cache is not None:
                 for cached_lora in getattr(lora_cache, "raw_data", []):
@@ -2498,13 +2637,16 @@ class RecipeScanner:
                             file_name = os.path.splitext(os.path.basename(cached_path))[
                                 0
                             ]
+                            folder = cached_lora.get("folder", "")
                         break
 
             if not file_name:
                 file_name = lora.get("file_name", "unknown-lora")
+                folder = lora.get("folder", "")
 
+            lora_name = f"{folder}/{file_name}" if folder else file_name
             strength = lora.get("strength", 1.0)
-            syntax_parts.append(f"<lora:{file_name}:{strength}>")
+            syntax_parts.append(f"<lora:{lora_name}:{strength}>")
 
         return syntax_parts
 

py/services/recipes/analysis_service.py

@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+import asyncio
 import base64
 import io
 import os
@@ -14,6 +15,7 @@ from PIL import Image
 
 from ...utils.utils import calculate_recipe_fingerprint
 from ...utils.civitai_utils import extract_civitai_image_id, rewrite_preview_url
+from ...recipes.enrichment import RecipeEnricher
 from .errors import (
     RecipeDownloadError,
     RecipeNotFoundError,
@@ -170,9 +172,29 @@ class RecipeAnalysisService:
                 await self._download_image(url, temp_path)
 
             if metadata is None and not is_video:
-                metadata = self._exif_utils.extract_image_metadata(temp_path)
+                metadata = await asyncio.to_thread(
+                    self._exif_utils.extract_image_metadata, temp_path
+                )
 
-            return await self._parse_metadata(
+            if not metadata and civitai_image_id and image_info:
+                original_url = image_info.get("url")
+                if original_url:
+                    self._logger.debug(
+                        "Optimized image lacks embedded metadata, "
+                        "falling back to original image: %s",
+                        original_url,
+                    )
+                    orig_temp_path = self._create_temp_path(suffix=".png")
+                    try:
+                        await self._download_image(original_url, orig_temp_path)
+                        metadata = await asyncio.to_thread(
+                            self._exif_utils.extract_image_metadata,
+                            orig_temp_path,
+                        )
+                    finally:
+                        self._safe_cleanup(orig_temp_path)
+
+            result = await self._parse_metadata(
                 metadata or {},
                 recipe_scanner=recipe_scanner,
                 image_path=temp_path,
@@ -180,6 +202,37 @@ class RecipeAnalysisService:
                 is_video=is_video,
                 extension=extension,
             )
+
+            if civitai_image_id and image_info and not result.payload.get("error"):
+                mvid = image_info.get("modelVersionId")
+                if not mvid:
+                    mvids = image_info.get("modelVersionIds")
+                    if isinstance(mvids, list) and mvids:
+                        mvid = mvids[0]
+
+                recipe_for_enrich = {
+                    "gen_params": result.payload.get("gen_params", {}),
+                    "loras": result.payload.get("loras", []),
+                    "base_model": result.payload.get("base_model", "") or "",
+                    "checkpoint": result.payload.get("checkpoint") or result.payload.get("model"),
+                    "source_path": url,
+                }
+
+                await RecipeEnricher.enrich_recipe(
+                    recipe=recipe_for_enrich,
+                    civitai_client=civitai_client,
+                    request_params=None,
+                    prefetched_civitai_meta_raw=image_info.get("meta"),
+                    prefetched_model_version_id=mvid,
+                )
+
+                result.payload["gen_params"] = recipe_for_enrich["gen_params"]
+                if recipe_for_enrich.get("checkpoint"):
+                    result.payload["checkpoint"] = recipe_for_enrich["checkpoint"]
+                if recipe_for_enrich.get("base_model"):
+                    result.payload["base_model"] = recipe_for_enrich["base_model"]
+
+            return result
         finally:
             if temp_path:
                 self._safe_cleanup(temp_path)
@@ -199,7 +252,9 @@ class RecipeAnalysisService:
         if not os.path.isfile(normalized_path):
             raise RecipeNotFoundError("File not found")
 
-        metadata = self._exif_utils.extract_image_metadata(normalized_path)
+        metadata = await asyncio.to_thread(
+            self._exif_utils.extract_image_metadata, normalized_path
+        )
         if not metadata:
             return self._metadata_not_found_response(normalized_path)
 

py/services/recipes/persistence_service.py

@@ -49,8 +49,18 @@ class RecipePersistenceService:
         tags: Iterable[str],
         metadata: Optional[dict[str, Any]],
         extension: str | None = None,
+        recipe_id: str | None = None,
+        target_dir: str | None = None,
     ) -> PersistenceResult:
-        """Persist a user uploaded recipe."""
+        """Persist a user uploaded recipe.
+
+        Args:
+            recipe_id: If provided, reuse this ID instead of generating a new
+                UUID. Used by re-import to preserve the original recipe identity.
+            target_dir: If provided, save recipe files to this directory instead
+                of the default recipes_dir. Used by re-import to preserve the
+                original folder location.
+        """
 
         missing_fields = []
         if not name:
@@ -63,10 +73,10 @@ class RecipePersistenceService:
             )
 
         resolved_image_bytes = self._resolve_image_bytes(image_bytes, image_base64)
-        recipes_dir = recipe_scanner.recipes_dir
+        recipes_dir = target_dir or recipe_scanner.recipes_dir
         os.makedirs(recipes_dir, exist_ok=True)
 
-        recipe_id = str(uuid.uuid4())
+        recipe_id = recipe_id or str(uuid.uuid4())
         
         # Handle video formats by bypassing optimization and metadata embedding
         is_video = extension in [".mp4", ".webm"]
@@ -115,6 +125,22 @@ class RecipePersistenceService:
         if metadata.get("source_path"):
             recipe_data["source_path"] = metadata.get("source_path")
 
+        nsfw_level = metadata.get("preview_nsfw_level")
+        if nsfw_level is not None and isinstance(nsfw_level, int):
+            recipe_data["preview_nsfw_level"] = nsfw_level
+
+        # Compute recipe folder relative to recipes root, mirroring
+        # RecipeScanner._calculate_folder() which is only called during scan/load.
+        if recipe_scanner.recipes_dir:
+            recipe_file_dir = os.path.dirname(normalized_image_path)
+            try:
+                relative_folder = os.path.relpath(recipe_file_dir, recipe_scanner.recipes_dir)
+                if relative_folder in (".", ""):
+                    relative_folder = ""
+                recipe_data["folder"] = relative_folder.replace(os.path.sep, "/")
+            except Exception:
+                recipe_data["folder"] = ""
+
         json_filename = f"{recipe_id}.recipe.json"
         json_path = os.path.join(recipes_dir, json_filename)
         json_path = os.path.normpath(json_path)
@@ -508,6 +534,10 @@ class RecipePersistenceService:
         most_common_base_model = (
             max(base_model_counts.items(), key=lambda item: item[1])[0] if base_model_counts else ""
         )
+        checkpoint_entry = await self._build_widget_checkpoint_entry(
+            recipe_scanner,
+            metadata.get("checkpoint"),
+        )
 
         recipe_data = {
             "id": recipe_id,
@@ -515,9 +545,8 @@ class RecipePersistenceService:
             "title": recipe_name,
             "modified": time.time(),
             "created_date": time.time(),
-            "base_model": most_common_base_model,
+            "base_model": most_common_base_model or (checkpoint_entry or {}).get("baseModel", ""),
             "loras": loras_data,
-            "checkpoint": self._sanitize_checkpoint_entry(metadata.get("checkpoint", "")),
             "gen_params": {
                 key: value
                 for key, value in metadata.items()
@@ -525,6 +554,8 @@ class RecipePersistenceService:
             },
             "loras_stack": lora_stack,
         }
+        if checkpoint_entry:
+            recipe_data["checkpoint"] = checkpoint_entry
 
         json_filename = f"{recipe_id}.recipe.json"
         json_path = os.path.join(recipes_dir, json_filename)
@@ -546,6 +577,91 @@ class RecipePersistenceService:
 
     # Helper methods ---------------------------------------------------
 
+    async def _build_widget_checkpoint_entry(
+        self,
+        recipe_scanner,
+        checkpoint_raw: Any,
+    ) -> Optional[dict[str, Any]]:
+        """Build recipe checkpoint metadata from widget generation metadata."""
+
+        if isinstance(checkpoint_raw, dict):
+            return self._sanitize_checkpoint_entry(checkpoint_raw)
+
+        if not isinstance(checkpoint_raw, str):
+            return None
+
+        checkpoint_name = checkpoint_raw.strip()
+        if not checkpoint_name:
+            return None
+
+        file_name = os.path.splitext(os.path.basename(checkpoint_name))[0]
+        checkpoint_info = await self._lookup_widget_checkpoint(
+            recipe_scanner,
+            checkpoint_name,
+        )
+        if not checkpoint_info:
+            return {
+                "type": "checkpoint",
+                "name": checkpoint_name,
+                "file_name": file_name,
+                "hash": "",
+            }
+
+        civitai = checkpoint_info.get("civitai") or {}
+        civitai_model = civitai.get("model") or {}
+        file_path = checkpoint_info.get("file_path") or checkpoint_info.get("path") or ""
+        cached_file_name = (
+            checkpoint_info.get("file_name")
+            or (os.path.splitext(os.path.basename(file_path))[0] if file_path else "")
+            or file_name
+        )
+
+        return {
+            "type": "checkpoint",
+            "modelId": civitai_model.get("id", 0),
+            "modelVersionId": civitai.get("id", 0),
+            "name": civitai_model.get("name") or checkpoint_info.get("model_name") or checkpoint_name,
+            "version": civitai.get("name", ""),
+            "hash": (checkpoint_info.get("sha256") or checkpoint_info.get("hash") or "").lower(),
+            "file_name": cached_file_name,
+            "modelName": civitai_model.get("name", ""),
+            "modelVersionName": civitai.get("name", ""),
+            "baseModel": checkpoint_info.get("base_model") or civitai.get("baseModel", ""),
+        }
+
+    async def _lookup_widget_checkpoint(
+        self,
+        recipe_scanner,
+        checkpoint_name: str,
+    ) -> Optional[dict[str, Any]]:
+        lookup = getattr(recipe_scanner, "get_local_checkpoint", None)
+        if not callable(lookup):
+            return None
+
+        candidates = []
+        for candidate in (
+            checkpoint_name,
+            os.path.basename(checkpoint_name),
+            os.path.splitext(os.path.basename(checkpoint_name))[0],
+        ):
+            if candidate and candidate not in candidates:
+                candidates.append(candidate)
+
+        for candidate in candidates:
+            try:
+                checkpoint_info = await lookup(candidate)
+            except Exception as exc:
+                self._logger.debug(
+                    "Failed to lookup checkpoint %s while saving widget recipe: %s",
+                    candidate,
+                    exc,
+                )
+                continue
+            if checkpoint_info:
+                return checkpoint_info
+
+        return None
+
     def _extract_checkpoint_entry(self, metadata: dict[str, Any]) -> Optional[dict[str, Any]]:
         """Pull a checkpoint entry from various metadata locations."""
 

py/services/service_registry.py

@@ -188,6 +188,25 @@ class ServiceRegistry:
             logger.debug(f"Created and registered {service_name}")
             return service
 
+    @classmethod
+    async def get_download_queue_service(cls):
+        """Get or create the download queue service."""
+        service_name = "download_queue_service"
+
+        if service_name in cls._services:
+            return cls._services[service_name]
+
+        async with cls._get_lock(service_name):
+            if service_name in cls._services:
+                return cls._services[service_name]
+
+            from .download_queue_service import DownloadQueueService
+
+            service = await DownloadQueueService.get_instance()
+            cls._services[service_name] = service
+            logger.debug(f"Created and registered {service_name}")
+            return service
+
     @classmethod
     async def get_backup_service(cls):
         """Get or create the backup service."""

py/services/settings_manager.py

@@ -81,6 +81,9 @@ DEFAULT_SETTINGS: Dict[str, Any] = {
     "folder_paths": {},
     "extra_folder_paths": {},
     "example_images_path": "",
+    "example_images_open_mode": "system",
+    "example_images_local_root": "",
+    "example_images_open_uri_template": "",
     "optimize_example_images": True,
     "auto_download_example_images": False,
     "blur_mature_content": True,
@@ -93,7 +96,9 @@ DEFAULT_SETTINGS: Dict[str, Any] = {
     "compact_mode": False,
     "priority_tags": DEFAULT_PRIORITY_TAG_CONFIG.copy(),
     "model_name_display": "model_name",
+    "lora_syntax_format": "legacy",
     "model_card_footer_action": "replace_preview",
+    "show_version_on_card": True,
     "update_flag_strategy": "same_base",
     "auto_organize_exclusions": [],
     "metadata_refresh_skip_paths": [],

py/services/tag_update_service.py

@@ -4,7 +4,9 @@ from __future__ import annotations
 
 import os
 
-from typing import Awaitable, Callable, Dict, List, Sequence
+from typing import Awaitable, Callable, Dict, List, Sequence, Tuple
+
+from .auto_tag_service import extract_auto_tags
 
 
 class TagUpdateService:
@@ -20,9 +22,8 @@ class TagUpdateService:
         new_tags: Sequence[str],
         metadata_loader: Callable[[str], Awaitable[Dict[str, object]]],
         update_cache: Callable[[str, str, Dict[str, object]], Awaitable[bool]],
-    ) -> List[str]:
+    ) -> Tuple[List[str], List[str]]:
-        """Add tags to a metadata entry while keeping case-insensitive uniqueness."""
+        """Add tags to a metadata entry and return updated tags and auto_tags."""
-
         base, _ = os.path.splitext(file_path)
         metadata_path = f"{base}.metadata.json"
         metadata = await metadata_loader(metadata_path)
@@ -44,5 +45,6 @@ class TagUpdateService:
         await self._metadata_manager.save_metadata(file_path, metadata)
         await update_cache(file_path, file_path, metadata)
 
-        return existing_tags
+        auto_tags = extract_auto_tags(metadata)
+        return existing_tags, auto_tags
 

py/utils/civitai_utils.py

@@ -7,7 +7,7 @@ from typing import Any, Dict, Iterable, Mapping, Sequence
 from urllib.parse import parse_qs, urlparse, urlunparse
 
 
-_SUPPORTED_CIVITAI_PAGE_HOSTS = frozenset({"civitai.com", "civitai.red"})
+_SUPPORTED_CIVITAI_PAGE_HOSTS = frozenset({"civitai.com", "civitai.red", "civitai.green"})
 DEFAULT_CIVITAI_PAGE_HOST = "civitai.com"
 _DEFAULT_ALLOW_COMMERCIAL_USE: Sequence[str] = ("Sell",)
 _LICENSE_DEFAULTS: Dict[str, Any] = {
@@ -66,6 +66,46 @@ def build_civitai_model_page_url(
     return None
 
 
+_RE_CDN_IMAGE_ID = re.compile(r"/(\d+)\.(?:jpeg|jpg|png|webp|gif)(?:\?|#|$)")
+
+
+def extract_civitai_image_id_from_cdn_url(url: str | None) -> str | None:
+    """Extract the numeric image ID from a Cloudflare CDN image URL.
+
+    CivitAI image CDN URLs follow the pattern::
+
+        https://image.civitai.com/{cf_uuid}/{params}/{image_id}.{ext}
+
+    The image database ID is always the last path segment (minus extension)
+    because ``getEdgeUrl(…, name=id.toString())`` embeds it explicitly
+    in the model-versions REST API response.
+    """
+    if not url:
+        return None
+    match = _RE_CDN_IMAGE_ID.search(url)
+    return match.group(1) if match else None
+
+
+def build_civitai_image_page_url(
+    image_id: str | int | None,
+    *,
+    host: str | None = None,
+) -> str | None:
+    """Build a Civitai image page URL.
+
+    Returns something like ``https://civitai.com/images/12345``.
+    The host is resolved through :func:`normalize_civitai_page_host` and
+    therefore respects the user's ``civitai_host`` setting.
+    """
+    if not image_id:
+        return None
+    normalized_host = normalize_civitai_page_host(host)
+    normalized_id = str(image_id).strip()
+    if not normalized_id:
+        return None
+    return urlunparse(("https", normalized_host, f"/images/{normalized_id}", "", "", ""))
+
+
 def _parse_supported_civitai_page_url(url: str | None):
     if not url:
         return None
@@ -239,9 +279,9 @@ def _resolve_commercial_bits(values: Sequence[str]) -> int:
             normalized_values.add(normalized)
 
     has_sell = "sell" in normalized_values
-    has_rent = has_sell or "rent" in normalized_values
+    has_rent = "rent" in normalized_values
-    has_rentcivit = has_rent or "rentcivit" in normalized_values
+    has_rentcivit = "rentcivit" in normalized_values
-    has_image = has_sell or "image" in normalized_values
+    has_image = "image" in normalized_values
 
     commercial_bits = (
         (1 if has_sell else 0) << 3
@@ -328,8 +368,10 @@ def rewrite_preview_url(
 
 
 __all__ = [
+    "build_civitai_image_page_url",
     "build_license_flags",
     "extract_civitai_image_id",
+    "extract_civitai_image_id_from_cdn_url",
     "extract_civitai_page_host",
     "extract_civitai_model_url_parts",
     "is_supported_civitai_page_host",

py/utils/constants.py

@@ -100,8 +100,35 @@ DEFAULT_PRIORITY_TAG_CONFIG = {
 # These model types are incorrectly labeled as "checkpoint" by CivitAI but are actually diffusion models
 DIFFUSION_MODEL_BASE_MODELS = frozenset(
     [
-        "ZImageTurbo",
+        "Anima",
-        "ZImageBase",
+        # Flux series — DiT architecture, loaded via UNETLoader in ComfyUI
+        "Flux.1 D",
+        "Flux.1 S",
+        "Flux.1 Krea",
+        "Flux.1 Kontext",
+        "Flux.2 D",
+        "Flux.2 Klein 9B",
+        "Flux.2 Klein 9B-base",
+        "Flux.2 Klein 4B",
+        "Flux.2 Klein 4B-base",
+        # Non-UNet / DiT image diffusion models
+        "AuraFlow",
+        "Chroma",
+        "HiDream",
+        "Hunyuan 1",
+        "Kolors",
+        "Lumina",
+        "PixArt a",
+        "PixArt E",
+        # Video diffusion models
+        "CogVideoX",
+        "Hunyuan Video",
+        "LTXV",
+        "LTXV2",
+        "LTXV 2.3",
+        "Mochi",
+        "SVD",
+        "Wan Video",
         "Wan Video 1.3B t2v",
         "Wan Video 14B t2v",
         "Wan Video 14B i2v 480p",
@@ -111,9 +138,13 @@ DIFFUSION_MODEL_BASE_MODELS = frozenset(
         "Wan Video 2.2 T2V-A14B",
         "Wan Video 2.5 T2V",
         "Wan Video 2.5 I2V",
-        "CogVideoX",
+        # Other diffusion models
-        "Mochi",
+        "Ernie",
+        "Ernie Turbo",
+        "Nucleus",
         "Qwen",
+        "ZImageBase",
+        "ZImageTurbo",
     ]
 )
 
@@ -177,5 +208,8 @@ SUPPORTED_DOWNLOAD_SKIP_BASE_MODELS = frozenset(
         "Wan Video 2.5 I2V",
         "Hunyuan Video",
         "Anima",
+        "Ernie",
+        "Ernie Turbo",
+        "Nucleus",
     ]
 )

py/utils/example_images_download_manager.py

@@ -397,13 +397,12 @@ class DownloadManager:
 
             models_with_hash = len(all_models_with_hash)
 
-            # Calculate pending count: check which models actually need processing
+            # Calculate pending count: check which models actually need processing.
-            # A model is pending if it has a hash, is not in processed_models,
+            # A model is pending if it has a hash, is not already processed or known-failed,
-            # and its folder doesn't exist or is empty
+            # and its folder doesn't exist or is empty.
             pending_hashes = set()
             for model_hash, model_name in all_models_with_hash:
-                if model_hash not in processed_models:
+                if model_hash not in processed_models and model_hash not in failed_models:
-                    # Check if model folder exists with files
                     model_dir = ExampleImagePathResolver.get_model_folder(
                         model_hash, active_library
                     )

py/utils/example_images_file_manager.py

@@ -1,17 +1,81 @@
 import logging
 import os
-import sys
+import re
 import subprocess
+import sys
+from urllib.parse import quote
+
 from aiohttp import web
 from ..services.settings_manager import get_settings_manager
 from ..utils.example_images_paths import (
     get_model_folder,
-    get_model_relative_path,
 )
 from ..utils.constants import SUPPORTED_MEDIA_EXTENSIONS
 
 logger = logging.getLogger(__name__)
 
+
+_WINDOWS_DRIVE_PATTERN = re.compile(r"^[A-Za-z]:/")
+
+
+def _is_within_root(path: str, root: str) -> bool:
+    try:
+        return os.path.commonpath([os.path.abspath(path), os.path.abspath(root)]) == os.path.abspath(root)
+    except ValueError:
+        return False
+
+
+def _join_local_example_path(local_root: str, relative_path: str) -> str:
+    separator = "\\" if "\\" in local_root and "/" not in local_root else "/"
+    normalized_root = local_root.rstrip("\\/")
+    normalized_relative = relative_path.replace("/", separator)
+    if not normalized_root:
+        return normalized_relative
+    return f"{normalized_root}{separator}{normalized_relative}"
+
+
+def _build_file_uri(path: str) -> str:
+    normalized = path.replace("\\", "/")
+    if _WINDOWS_DRIVE_PATTERN.match(normalized):
+        return f"file:///{quote(normalized, safe='/:')}"
+    if normalized.startswith("/"):
+        return f"file://{quote(normalized, safe='/:')}"
+    return f"file:///{quote(normalized.lstrip('/'), safe='/:')}"
+
+
+def _render_open_uri_template(template: str, local_path: str, relative_path: str) -> str:
+    file_uri = _build_file_uri(local_path)
+    replacements = {
+        "{{local_path}}": local_path,
+        "{{encoded_local_path}}": quote(local_path, safe=""),
+        "{{relative_path}}": relative_path,
+        "{{encoded_relative_path}}": quote(relative_path, safe=""),
+        "{{file_uri}}": file_uri,
+        "{{encoded_file_uri}}": quote(file_uri, safe=""),
+    }
+
+    rendered = template
+    for placeholder, value in replacements.items():
+        rendered = rendered.replace(placeholder, value)
+    return rendered
+
+
+def _open_system_folder(model_folder: str) -> dict[str, object]:
+    if os.name == "nt":  # Windows
+        os.startfile(model_folder)
+    elif os.name == "posix":  # macOS and Linux
+        if sys.platform == "darwin":  # macOS
+            subprocess.Popen(["open", model_folder])
+        else:  # Linux
+            subprocess.Popen(["xdg-open", model_folder])
+
+    return {
+        "success": True,
+        "message": f"Opened example images folder for {model_folder}",
+        "path": model_folder,
+    }
+
+
 class ExampleImagesFileManager:
     """Manages access and operations for example image files"""
     
@@ -54,7 +118,7 @@ class ExampleImagesFileManager:
                 }, status=500)
 
             # Path validation: ensure model_folder is under example_images_path
-            if not model_folder.startswith(os.path.abspath(example_images_path)):
+            if not _is_within_root(model_folder, example_images_path):
                 return web.json_response({
                     'success': False,
                     'error': 'Invalid model folder path'
@@ -67,20 +131,40 @@ class ExampleImagesFileManager:
                     'error': 'No example images found for this model. Download example images first.'
                 }, status=404)
 
-            # Open folder in file explorer
+            root_path = os.path.abspath(example_images_path)
-            if os.name == 'nt':  # Windows
+            relative_path = os.path.relpath(model_folder, root_path).replace("\\", "/")
-                os.startfile(model_folder)
+            open_mode = settings_manager.get("example_images_open_mode") or "system"
-            elif os.name == 'posix':  # macOS and Linux
-                if sys.platform == 'darwin':  # macOS
-                    subprocess.Popen(['open', model_folder])
-                else:  # Linux
-                    subprocess.Popen(['xdg-open', model_folder])
 
+            if open_mode == "clipboard":
+                local_root = settings_manager.get("example_images_local_root") or root_path
+                local_path = _join_local_example_path(local_root, relative_path)
                 return web.json_response({
                     'success': True,
-                'message': f'Opened example images folder for model {model_hash}'
+                    'mode': 'clipboard',
+                    'path': local_path,
+                    'relative_path': relative_path,
                 })
 
+            if open_mode == "uri_template":
+                local_root = settings_manager.get("example_images_local_root") or root_path
+                uri_template = settings_manager.get("example_images_open_uri_template") or ""
+                if not uri_template.strip():
+                    return web.json_response({
+                        'success': False,
+                        'error': 'No example image open URI template configured.'
+                    }, status=400)
+
+                local_path = _join_local_example_path(local_root, relative_path)
+                return web.json_response({
+                    'success': True,
+                    'mode': 'uri',
+                    'path': local_path,
+                    'relative_path': relative_path,
+                    'uri': _render_open_uri_template(uri_template, local_path, relative_path),
+                })
+
+            return web.json_response(_open_system_folder(model_folder))
+            
         except Exception as e:
             logger.error(f"Failed to open example images folder: {e}", exc_info=True)
             return web.json_response({
@@ -143,7 +227,7 @@ class ExampleImagesFileManager:
                     file_ext = os.path.splitext(file)[1].lower()
                     if (file_ext in SUPPORTED_MEDIA_EXTENSIONS['images'] or 
                         file_ext in SUPPORTED_MEDIA_EXTENSIONS['videos']):
-                        relative_path = get_model_relative_path(model_hash)
+                        relative_path = os.path.relpath(model_folder, os.path.abspath(example_images_path)).replace("\\", "/")
                         files.append({
                             'name': file,
                             'path': f'/example_images_static/{relative_path}/{file}',

py/utils/example_images_metadata.py

@@ -452,3 +452,111 @@ class MetadataUpdater:
         except Exception as e:
             logger.error(f"Error parsing image metadata: {e}", exc_info=True)
             return None
+
+    @staticmethod
+    async def prune_stale_example_images(metadata) -> bool:
+        """Remove example-image metadata entries whose files no longer exist on disk.
+
+        Checks ``civitai.customImages`` (by ``id``) and ``civitai.images`` entries
+        that have an empty ``url`` (no remote fallback) against actual files in
+        the model's example-image folder.  Stale entries are removed in-place so
+        the caller can persist the cleaned metadata afterwards.
+
+        Args:
+            metadata: A ``BaseModelMetadata`` instance (modified in place).
+
+        Returns:
+            True if at least one entry was removed.
+        """
+        from ..utils.example_images_paths import get_model_folder
+
+        model_hash = getattr(metadata, "sha256", None)
+        if not model_hash:
+            return False
+
+        model_folder = get_model_folder(model_hash)
+        if not model_folder:
+            return False
+
+        civitai = getattr(metadata, "civitai", None)
+        if not isinstance(civitai, dict):
+            return False
+
+        has_changes = False
+
+        custom_images = civitai.get("customImages")
+        if isinstance(custom_images, list) and custom_images:
+            stale: list[int] = []
+
+            for idx, img in enumerate(custom_images):
+                img_id = img.get("id", "")
+                if not img_id:
+                    continue
+
+                if not os.path.isdir(model_folder):
+                    stale.append(idx)
+                else:
+                    found = False
+                    try:
+                        prefix = f"custom_{img_id}"
+                        for fname in os.listdir(model_folder):
+                            if fname.startswith(prefix) and os.path.isfile(
+                                os.path.join(model_folder, fname)
+                            ):
+                                found = True
+                                break
+                    except OSError:
+                        stale.append(idx)
+                        continue
+
+                    if not found:
+                        stale.append(idx)
+
+            if stale:
+                for idx in reversed(stale):
+                    custom_images.pop(idx)
+                has_changes = True
+                logger.info(
+                    "Pruned %d stale custom image(s) for %s",
+                    len(stale),
+                    getattr(metadata, "model_name", model_hash),
+                )
+
+        images = civitai.get("images")
+        if isinstance(images, list) and images:
+            stale: list[int] = []
+
+            for idx, img in enumerate(images):
+                if img.get("url", ""):
+                    # Has a remote fallback – keep it even if the local copy
+                    # is gone.
+                    continue
+
+                if not os.path.isdir(model_folder):
+                    stale.append(idx)
+                else:
+                    found = False
+                    try:
+                        prefix = f"image_{idx}."
+                        for fname in os.listdir(model_folder):
+                            if fname.startswith(prefix):
+                                found = True
+                                break
+                    except OSError:
+                        stale.append(idx)
+                        continue
+
+                    if not found:
+                        stale.append(idx)
+
+            if stale:
+                for idx in reversed(stale):
+                    images.pop(idx)
+                has_changes = True
+                logger.info(
+                    "Pruned %d stale image entry(ies) for %s",
+                    len(stale),
+                    getattr(metadata, "model_name", model_hash),
+                )
+
+        return has_changes

py/utils/exif_utils.py

@@ -1,9 +1,10 @@
-import piexif
 import json
 import logging
-from typing import Optional
-from io import BytesIO
 import os
+from io import BytesIO
+from typing import Any, Optional
+
+import piexif
 from PIL import Image, PngImagePlugin
 
 logger = logging.getLogger(__name__)
@@ -11,6 +12,132 @@ logger = logging.getLogger(__name__)
 class ExifUtils:
     """Utility functions for working with EXIF data in images"""
 
+    @staticmethod
+    def _decode_user_comment(user_comment: Any) -> Optional[str]:
+        if user_comment is None:
+            return None
+        if isinstance(user_comment, bytes):
+            if user_comment.startswith(b"UNICODE\0"):
+                return user_comment[8:].decode("utf-16be", errors="ignore")
+            return user_comment.decode("utf-8", errors="ignore")
+        if isinstance(user_comment, str):
+            return user_comment
+        return str(user_comment)
+
+    @staticmethod
+    def _decode_exif_text(value: Any) -> Optional[str]:
+        if value is None:
+            return None
+        if isinstance(value, bytes):
+            return value.decode("utf-8", errors="ignore")
+        if isinstance(value, str):
+            return value
+        return str(value)
+
+    @staticmethod
+    def _load_structured_metadata(image_path: str) -> dict[str, Optional[str]]:
+        metadata = {
+            "parameters": None,
+            "prompt": None,
+            "workflow": None,
+            "comment": None,
+        }
+
+        with Image.open(image_path) as img:
+            info = getattr(img, "info", {}) or {}
+
+            if "parameters" in info:
+                metadata["parameters"] = info["parameters"]
+            if "prompt" in info:
+                metadata["prompt"] = info["prompt"]
+            if "workflow" in info:
+                metadata["workflow"] = info["workflow"]
+
+            if img.format not in ["JPEG", "TIFF", "WEBP"]:
+                exif = img.getexif()
+                if exif and piexif.ExifIFD.UserComment in exif:
+                    metadata["comment"] = ExifUtils._decode_user_comment(
+                        exif[piexif.ExifIFD.UserComment]
+                    )
+
+            try:
+                exif_dict = piexif.load(image_path)
+            except Exception as e:
+                logger.debug(f"Error loading EXIF data: {e}")
+                exif_dict = {}
+
+            if piexif.ExifIFD.UserComment in exif_dict.get("Exif", {}):
+                metadata["comment"] = ExifUtils._decode_user_comment(
+                    exif_dict["Exif"][piexif.ExifIFD.UserComment]
+                )
+
+            image_description = ExifUtils._decode_exif_text(
+                exif_dict.get("0th", {}).get(piexif.ImageIFD.ImageDescription)
+            )
+            if image_description:
+                if image_description.startswith("Workflow:"):
+                    metadata["workflow"] = image_description[len("Workflow:") :]
+                elif not metadata["prompt"]:
+                    metadata["prompt"] = image_description
+
+        if not metadata["parameters"] and metadata["comment"]:
+            metadata["parameters"] = metadata["comment"]
+
+        return metadata
+
+    @staticmethod
+    def _build_pnginfo(img: Image.Image, metadata_fields: dict[str, Optional[str]]) -> PngImagePlugin.PngInfo:
+        png_info = PngImagePlugin.PngInfo()
+        existing_info = getattr(img, "info", {}) or {}
+        managed_keys = {"parameters", "prompt", "workflow"}
+
+        for key, value in existing_info.items():
+            if key in {"exif", "dpi", "transparency", "gamma", "aspect"}:
+                continue
+            if key in managed_keys:
+                continue
+            if isinstance(value, str):
+                png_info.add_text(key, value)
+
+        for key in managed_keys:
+            value = metadata_fields.get(key)
+            if value:
+                png_info.add_text(key, value)
+
+        return png_info
+
+    @staticmethod
+    def _build_exif_bytes(
+        metadata_fields: dict[str, Optional[str]], existing_exif: bytes | None = None
+    ) -> bytes:
+        try:
+            exif_dict = piexif.load(existing_exif or b"")
+        except Exception:
+            exif_dict = {"0th": {}, "Exif": {}, "GPS": {}, "Interop": {}, "1st": {}}
+
+        exif_dict.setdefault("0th", {})
+        exif_dict.setdefault("Exif", {})
+
+        parameters = metadata_fields.get("parameters")
+        workflow = metadata_fields.get("workflow")
+        prompt = metadata_fields.get("prompt")
+
+        if parameters:
+            exif_dict["Exif"][piexif.ExifIFD.UserComment] = (
+                b"UNICODE\0" + parameters.encode("utf-16be")
+            )
+        else:
+            exif_dict["Exif"].pop(piexif.ExifIFD.UserComment, None)
+
+        if workflow:
+            exif_dict["0th"][piexif.ImageIFD.ImageDescription] = f"Workflow:{workflow}"
+        elif prompt:
+            exif_dict["0th"][piexif.ImageIFD.ImageDescription] = prompt
+        else:
+            exif_dict["0th"].pop(piexif.ImageIFD.ImageDescription, None)
+
+        return piexif.dump(exif_dict)
+    
     @staticmethod
     def extract_image_metadata(image_path: str) -> Optional[str]:
         """Extract metadata from image including UserComment or parameters field
@@ -28,48 +155,12 @@ class ExifUtils:
                 if ext in ['.mp4', '.webm']:
                     return None
 
-            # First try to open the image
+            metadata = ExifUtils._load_structured_metadata(image_path)
-            with Image.open(image_path) as img:
+            return (
-                # Method 1: Check for parameters in image info
+                metadata.get("parameters")
-                if hasattr(img, 'info') and 'parameters' in img.info:
+                or metadata.get("prompt")
-                    return img.info['parameters']
+                or metadata.get("workflow")
-                
+            )
-                # Method 2: Check EXIF UserComment field
-                if img.format not in ['JPEG', 'TIFF', 'WEBP']:
-                    # For non-JPEG/TIFF/WEBP images, try to get EXIF through PIL
-                    exif = img.getexif()
-                    if exif and piexif.ExifIFD.UserComment in exif:
-                        user_comment = exif[piexif.ExifIFD.UserComment]
-                        if isinstance(user_comment, bytes):
-                            if user_comment.startswith(b'UNICODE\0'):
-                                return user_comment[8:].decode('utf-16be')
-                            return user_comment.decode('utf-8', errors='ignore')
-                        return user_comment
-                
-                # For JPEG/TIFF/WEBP, use piexif
-                try:
-                    exif_dict = piexif.load(image_path)
-                    
-                    if piexif.ExifIFD.UserComment in exif_dict.get('Exif', {}):
-                        user_comment = exif_dict['Exif'][piexif.ExifIFD.UserComment]
-                        if isinstance(user_comment, bytes):
-                            if user_comment.startswith(b'UNICODE\0'):
-                                user_comment = user_comment[8:].decode('utf-16be')
-                            else:
-                                user_comment = user_comment.decode('utf-8', errors='ignore')
-                        return user_comment
-                except Exception as e:
-                    logger.debug(f"Error loading EXIF data: {e}")
-                
-                # Method 3: Check PNG metadata for workflow info (for ComfyUI images)
-                if img.format == 'PNG':
-                    # Look for workflow or prompt metadata in PNG chunks
-                    for key in img.info:
-                        if key in ['workflow', 'prompt', 'parameters']:
-                            return img.info[key]
-                
-                return None
-                
         except Exception as e:
             logger.error(f"Error extracting image metadata: {e}", exc_info=True)
             return None
@@ -92,49 +183,25 @@ class ExifUtils:
                 if ext in ['.mp4', '.webm']:
                     return image_path
 
-            # Load the image and check its format
+            metadata_fields = ExifUtils._load_structured_metadata(image_path)
+            metadata_fields["parameters"] = metadata
+
             with Image.open(image_path) as img:
                 img_format = img.format
 
-                # For PNG, try to update parameters directly
+                if img_format == "PNG":
-                if img_format == 'PNG':
+                    png_info = ExifUtils._build_pnginfo(img, metadata_fields)
-                    # Use PngInfo instead of plain dictionary
+                    img.save(image_path, format="PNG", pnginfo=png_info)
-                    png_info = PngImagePlugin.PngInfo()
-                    png_info.add_text("parameters", metadata)
-                    img.save(image_path, format='PNG', pnginfo=png_info)
                     return image_path
 
-                # For WebP format, use PIL's exif parameter directly
+                exif_bytes = ExifUtils._build_exif_bytes(
-                elif img_format == 'WEBP':
+                    metadata_fields, img.info.get("exif")
-                    exif_dict = {'Exif': {piexif.ExifIFD.UserComment: b'UNICODE\0' + metadata.encode('utf-16be')}}
+                )
-                    exif_bytes = piexif.dump(exif_dict)
+                save_kwargs = {"exif": exif_bytes}
+                if img_format == "WEBP":
+                    save_kwargs["quality"] = 85
 
-                    # Save with the exif data
+                img.save(image_path, format=img_format, **save_kwargs)
-                    img.save(image_path, format='WEBP', exif=exif_bytes, quality=85)
-                    return image_path
-                
-                # For other formats, use standard EXIF approach
-                else:
-                    try:
-                        exif_dict = piexif.load(img.info.get('exif', b''))
-                    except:
-                        exif_dict = {'0th':{}, 'Exif':{}, 'GPS':{}, 'Interop':{}, '1st':{}}
-                    
-                    # If no Exif dictionary exists, create one
-                    if 'Exif' not in exif_dict:
-                        exif_dict['Exif'] = {}
-                    
-                    # Update the UserComment field - use UNICODE format
-                    unicode_bytes = metadata.encode('utf-16be')
-                    metadata_bytes = b'UNICODE\0' + unicode_bytes
-                    
-                    exif_dict['Exif'][piexif.ExifIFD.UserComment] = metadata_bytes
-                    
-                    # Convert EXIF dict back to bytes
-                    exif_bytes = piexif.dump(exif_dict)
-                    
-                    # Save the image with updated EXIF data
-                    img.save(image_path, exif=exif_bytes)
 
             return image_path
         except Exception as e:
@@ -297,12 +364,12 @@ class ExifUtils:
                     raise ValueError(f"Cannot process corrupt image data: {e}")
 
             # Extract metadata if needed and valid
-            metadata = None
+            metadata_fields = None
             if preserve_metadata:
                 try:
                     if isinstance(image_data, str) and os.path.exists(image_data):
                         # For file path, extract directly
-                        metadata = ExifUtils.extract_image_metadata(image_data)
+                        metadata_fields = ExifUtils._load_structured_metadata(image_data)
                     else:
                         # For binary data, save to temp file first
                         import tempfile
@@ -310,7 +377,7 @@ class ExifUtils:
                             temp_path = temp_file.name
                             temp_file.write(image_data)
                         try:
-                            metadata = ExifUtils.extract_image_metadata(temp_path)
+                            metadata_fields = ExifUtils._load_structured_metadata(temp_path)
                         except Exception as e:
                             logger.warning(f"Failed to extract metadata from temp file: {e}")
                         finally:
@@ -363,14 +430,13 @@ class ExifUtils:
             optimized_data = output.getvalue()
             
             # Handle metadata preservation if requested and available
-            if preserve_metadata and metadata:
+            if preserve_metadata and metadata_fields:
                 try:
                     if save_format == 'WEBP':
                         # For WebP format, directly save with metadata
                         try:
                             output_with_metadata = BytesIO()
-                            exif_dict = {'Exif': {piexif.ExifIFD.UserComment: b'UNICODE\0' + metadata.encode('utf-16be')}}
+                            exif_bytes = ExifUtils._build_exif_bytes(metadata_fields)
-                            exif_bytes = piexif.dump(exif_dict)
                             resized_img.save(output_with_metadata, format='WEBP', exif=exif_bytes, quality=quality)
                             optimized_data = output_with_metadata.getvalue()
                         except Exception as e:
@@ -383,8 +449,9 @@ class ExifUtils:
                             temp_file.write(optimized_data)
                         
                         try:
-                            # Add metadata
+                            ExifUtils.update_image_metadata(
-                            ExifUtils.update_image_metadata(temp_path, metadata)
+                                temp_path, metadata_fields.get("parameters") or ""
+                            )
                             # Read back the file
                             with open(temp_path, 'rb') as f:
                                 optimized_data = f.read()

py/utils/file_utils.py

@@ -1,7 +1,10 @@
 
 import hashlib
+import json
 import logging
 import os
+import struct
+from typing import Any
 
 from .constants import (
     CARD_PREVIEW_WIDTH,
@@ -31,7 +34,7 @@ def _get_hash_chunk_size_bytes() -> int:
 
 
 async def calculate_sha256(file_path: str) -> str:
-    """Calculate SHA256 hash of a file"""
+    """Calculate SHA256 hash of a file (full file content)."""
     sha256_hash = hashlib.sha256()
     chunk_size = _get_hash_chunk_size_bytes()
     with open(file_path, "rb") as f:
@@ -39,6 +42,79 @@ async def calculate_sha256(file_path: str) -> str:
             sha256_hash.update(byte_block)
     return sha256_hash.hexdigest()
 
+
+def calculate_autov2(file_path: str) -> str:
+    """Calculate CivitAI AutoV2 hash.
+
+    AutoV2 is the first 10 characters of the full file SHA256.
+    Used by CivitAI as a shortened file identifier.
+
+    Reference: https://developer.civitai.com/site/reference/model-versions
+    """
+    full_hash = hashlib.sha256()
+    chunk_size = _get_hash_chunk_size_bytes()
+    with open(file_path, "rb") as f:
+        for byte_block in iter(lambda: f.read(chunk_size), b""):
+            full_hash.update(byte_block)
+    return full_hash.hexdigest()[:10]
+
+
+def read_safetensors_metadata(file_path: str) -> dict[str, Any]:
+    """Read the ``__metadata__`` dict from a safetensors file header.
+
+    Safetensors file format:
+      - 8 bytes: header length (little-endian 64-bit)
+      - N bytes: UTF-8 JSON header
+      - The header JSON contains a ``__metadata__`` key holding arbitrary metadata.
+
+    Returns an empty dict if the file is not a valid safetensors file or has no
+    metadata.
+    """
+    try:
+        with open(file_path, "rb") as f:
+            header_len_bytes = f.read(8)
+            if len(header_len_bytes) < 8:
+                return {}
+            header_len = struct.unpack("<Q", header_len_bytes)[0]
+            header_bytes = f.read(header_len)
+            if len(header_bytes) < header_len:
+                return {}
+            header = json.loads(header_bytes.decode("utf-8"))
+            return header.get("__metadata__", {})
+    except (OSError, json.JSONDecodeError, UnicodeDecodeError, struct.error, MemoryError, Exception):
+        return {}
+
+
+def calculate_autov3(file_path: str) -> str | None:
+    """Calculate CivitAI AutoV3 hash from a safetensors file.
+
+    AutoV3 is extracted from the safetensors file's embedded metadata, not
+    computed from the file bytes directly. The orchestrator reads the
+    ``sshs_model_hash`` (kohya-ss format) or ``modelspec.hash_sha256`` field
+    from the safetensors header and stores the first 12 characters.
+
+    The embedded hash itself is the SHA256 of the file after skipping the
+    8-byte header length + JSON header (a.k.a. the addnet hash / tensor-only
+    hash).
+
+    Reference:
+      - CivitAI DB trigger: ``SUBSTRING(NEW.hash FROM 1 FOR 12)``
+      - https://developer.civitai.com/site/reference/model-versions
+
+    Returns ``None`` when no AutoV3 hash can be determined (e.g. the file is
+    not safetensors, or the metadata doesn't contain a recognised hash field).
+    """
+    metadata = read_safetensors_metadata(file_path)
+    if not metadata:
+        return None
+
+    embedded_hash = metadata.get("sshs_model_hash") or metadata.get("modelspec.hash_sha256")
+    if embedded_hash and isinstance(embedded_hash, str) and len(embedded_hash) >= 12:
+        return embedded_hash[:12]
+
+    return None
+
+
 def find_preview_file(base_name: str, dir_path: str) -> str:
     """Find preview file for given base name in directory.
 

py/utils/session_logging.py

@@ -64,6 +64,27 @@ def _build_log_file_path(settings_file: str | None, started_at: datetime) -> str
     return os.path.join(log_dir, f"standalone-session-{timestamp}.log")
 
 
+_KEEP_LOG_COUNT = 3
+
+
+def _prune_old_logs(log_dir: str) -> None:
+    """Remove older session log files, keeping only the ``_KEEP_LOG_COUNT`` newest."""
+    try:
+        files = [
+            os.path.join(log_dir, name)
+            for name in os.listdir(log_dir)
+            if name.startswith("standalone-session-") and name.endswith(".log")
+        ]
+    except OSError:
+        return
+    files.sort(key=os.path.getmtime, reverse=True)
+    for path in files[_KEEP_LOG_COUNT:]:
+        try:
+            os.remove(path)
+        except OSError:
+            pass
+
+
 def setup_standalone_session_logging(settings_file: str | None) -> StandaloneSessionLogState:
     global _session_state
 
@@ -90,6 +111,7 @@ def setup_standalone_session_logging(settings_file: str | None) -> StandaloneSes
             file_handler.set_name(_FILE_HANDLER_NAME)
             file_handler.setFormatter(formatter)
             root_logger.addHandler(file_handler)
+            _prune_old_logs(os.path.dirname(log_file_path))
 
         _session_state = StandaloneSessionLogState(
             started_at=started_at,

py/utils/usage_stats.py

@@ -1,4 +1,5 @@
 import os
+import re
 import json
 import time
 import asyncio
@@ -9,6 +10,7 @@ from typing import Dict, Set
 
 from ..config import config
 from ..services.service_registry import ServiceRegistry
+from ..utils.settings_paths import get_settings_dir
 
 # Check if running in standalone mode
 standalone_mode = os.environ.get("LORA_MANAGER_STANDALONE", "0") == "1" or os.environ.get("HF_HUB_DISABLE_TELEMETRY", "0") == "0"
@@ -16,14 +18,18 @@ standalone_mode = os.environ.get("LORA_MANAGER_STANDALONE", "0") == "1" or os.en
 # Define constants locally to avoid dependency on conditional imports
 MODELS = "models"
 LORAS = "loras"
+EMBEDDINGS = "embeddings"
+PROMPTS = "prompts"
 
 if not standalone_mode:
     from ..metadata_collector.metadata_registry import MetadataRegistry
     # Import constants from metadata_collector to ensure consistency, but we have fallbacks defined above
     try:
-        from ..metadata_collector.constants import MODELS as _MODELS, LORAS as _LORAS
+        from ..metadata_collector.constants import MODELS as _MODELS, LORAS as _LORAS, EMBEDDINGS as _EMBEDDINGS, PROMPTS as _PROMPTS
         MODELS = _MODELS
         LORAS = _LORAS
+        EMBEDDINGS = _EMBEDDINGS
+        PROMPTS = _PROMPTS
     except ImportError:
         pass  # Use the local definitions
 
@@ -65,6 +71,7 @@ class UsageStats:
         self.stats = {
             "checkpoints": {},  # sha256 -> { total: count, history: { date: count } }
             "loras": {},        # sha256 -> { total: count, history: { date: count } }
+            "embeddings": {},   # sha256 -> { total: count, history: { date: count } }
             "total_executions": 0,
             "last_save_time": 0
         }
@@ -77,6 +84,7 @@ class UsageStats:
         
         # Load existing stats if available
         self._stats_file_path = self._get_stats_file_path()
+        self._migrate_from_old_location()
         self._load_stats()
         
         # Save interval in seconds
@@ -89,14 +97,38 @@ class UsageStats:
         logger.debug("Usage statistics tracker initialized")
     
     def _get_stats_file_path(self) -> str:
-        """Get the path to the stats JSON file"""
+        """Get the path to the stats JSON file in the settings directory."""
-        if not config.loras_roots or len(config.loras_roots) == 0:
+        settings_dir = get_settings_dir(create=True)
-            # If no lora roots are available, we can't save stats
+        return os.path.join(settings_dir, "stats", self.STATS_FILENAME)
-            # This will be handled by the caller
-            raise RuntimeError("No LoRA root directories configured. Cannot initialize usage statistics.")
 
-        # Use the first lora root
+    @staticmethod
-        return os.path.join(config.loras_roots[0], self.STATS_FILENAME)
+    def _get_old_stats_file_path() -> str:
+        """Get the legacy stats file path in the first lora root directory."""
+        if not config.loras_roots or len(config.loras_roots) == 0:
+            return ""
+        return os.path.join(config.loras_roots[0], UsageStats.STATS_FILENAME)
+
+    def _migrate_from_old_location(self) -> None:
+        """Migrate stats file from old location (first lora root) to new location (settings_dir/stats/)."""
+        new_path = self._stats_file_path
+        if os.path.exists(new_path):
+            return
+
+        old_path = self._get_old_stats_file_path()
+        if not old_path or not os.path.exists(old_path):
+            return
+
+        try:
+            os.makedirs(os.path.dirname(new_path), exist_ok=True)
+            shutil.copy2(old_path, new_path)
+            logger.info("Migrated usage stats from %s to %s", old_path, new_path)
+            try:
+                os.remove(old_path)
+                logger.info("Cleaned up old stats file: %s", old_path)
+            except Exception as e:
+                logger.warning("Failed to remove old stats file %s: %s", old_path, e)
+        except Exception as e:
+            logger.error("Failed to migrate usage stats from %s to %s: %s", old_path, new_path, e)
     
     def _backup_old_stats(self):
         """Backup the old stats file before conversion"""
@@ -115,6 +147,7 @@ class UsageStats:
         new_stats = {
             "checkpoints": {},
             "loras": {},
+            "embeddings": {},
             "total_executions": old_stats.get("total_executions", 0),
             "last_save_time": old_stats.get("last_save_time", time.time())
         }
@@ -142,19 +175,25 @@ class UsageStats:
                     }
                 }
         
+        # Convert embedding stats (if present in old format)
+        if "embeddings" in old_stats and isinstance(old_stats["embeddings"], dict):
+            for hash_id, count in old_stats["embeddings"].items():
+                new_stats["embeddings"][hash_id] = {
+                    "total": count,
+                    "history": {
+                        today: count
+                    }
+                }
+        
         logger.info("Successfully converted stats from old format to new format with history")
         return new_stats
     
     def _is_old_format(self, stats):
         """Check if the stats are in the old format (direct count values)"""
         # Check if any lora or checkpoint entry is a direct number instead of an object
-        if "loras" in stats and isinstance(stats["loras"], dict):
+        for category in ("loras", "checkpoints", "embeddings"):
-            for hash_id, data in stats["loras"].items():
+            if category in stats and isinstance(stats[category], dict):
-                if isinstance(data, (int, float)):
+                for hash_id, data in stats[category].items():
-                    return True
-                
-        if "checkpoints" in stats and isinstance(stats["checkpoints"], dict):
-            for hash_id, data in stats["checkpoints"].items():
                     if isinstance(data, (int, float)):
                         return True
         
@@ -182,6 +221,9 @@ class UsageStats:
                         if "loras" in loaded_stats and isinstance(loaded_stats["loras"], dict):
                             self.stats["loras"] = loaded_stats["loras"]
                         
+                        if "embeddings" in loaded_stats and isinstance(loaded_stats["embeddings"], dict):
+                            self.stats["embeddings"] = loaded_stats["embeddings"]
+                        
                         if "total_executions" in loaded_stats:
                             self.stats["total_executions"] = loaded_stats["total_executions"]
                         
@@ -304,6 +346,10 @@ class UsageStats:
         if LORAS in metadata and isinstance(metadata[LORAS], dict):
             await self._process_loras(metadata[LORAS], today)
 
+        # Process embeddings — parse prompt text for embedding:name references
+        if PROMPTS in metadata and isinstance(metadata[PROMPTS], dict):
+            await self._process_embeddings(metadata[PROMPTS], today)
+
     def _increment_usage_counter(self, category: str, stat_key: str, today_date: str) -> None:
         """Increment usage counters for a resolved stats key."""
         if stat_key not in self.stats[category]:
@@ -510,6 +556,55 @@ class UsageStats:
         except Exception as e:
             logger.error(f"Error processing LoRA usage: {e}", exc_info=True)
     
+    @staticmethod
+    def _extract_embedding_names(prompt_text: str) -> set:
+        """Parse embedding:name references from prompt text.
+
+        ComfyUI's SDTokenizer resolves ``embedding:<name>`` during tokenization
+        (see ``sd1_clip.py _try_get_embedding``).  This mirrors the same pattern
+        to extract embedding file names from the captured prompt strings.
+        """
+        if not prompt_text:
+            return set()
+        # Matches ``embedding:name`` where name is alphanumeric plus _ . - /
+        names = re.findall(r"embedding:([a-zA-Z0-9_.\-/]+)", prompt_text)
+        return set(names)
+
+    async def _process_embeddings(self, prompts_data, today_date):
+        """Extract embedding usage from prompt texts and record it.
+
+        Iterates every prompt node's text field captured by the metadata
+        collector, extracts ``embedding:<name>`` references, resolves each
+        name to its SHA256 hash via the embedding scanner, and increments
+        usage counters.
+        """
+        try:
+            embedding_scanner = await ServiceRegistry.get_embedding_scanner()
+            if not embedding_scanner:
+                logger.warning("Embedding scanner not available for usage tracking")
+                return
+
+            seen_names = set()
+            for _node_id, prompt_data in prompts_data.items():
+                if not isinstance(prompt_data, dict):
+                    continue
+                for text_field in ("text", "positive_text", "negative_text"):
+                    text = prompt_data.get(text_field)
+                    if isinstance(text, str):
+                        seen_names.update(self._extract_embedding_names(text))
+
+            for emb_name in seen_names:
+                emb_hash = embedding_scanner.get_hash_by_filename(emb_name)
+                if emb_hash:
+                    self._increment_usage_counter("embeddings", emb_hash, today_date)
+                else:
+                    logger.debug(
+                        "No hash found for embedding '%s', skipping usage tracking",
+                        emb_name,
+                    )
+        except Exception as e:
+            logger.error("Error processing embedding usage: %s", e, exc_info=True)
+
     async def get_stats(self):
         """Get current usage statistics"""
         return self.stats
@@ -522,6 +617,9 @@ class UsageStats:
         elif model_type == "lora":
             if sha256 in self.stats["loras"]:
                 return self.stats["loras"][sha256]["total"]
+        elif model_type == "embedding":
+            if sha256 in self.stats["embeddings"]:
+                return self.stats["embeddings"][sha256]["total"]
         return 0
     
     async def process_execution(self, prompt_id):

py/utils/utils.py

@@ -15,11 +15,39 @@ def get_lora_info(lora_name):
         scanner = await ServiceRegistry.get_lora_scanner()
         cache = await scanner.get_cached_data()
 
+        lora_name_normalized = lora_name.replace("\\", "/")
+        lora_name_no_ext = lora_name_normalized
+        for ext in (".safetensors", ".ckpt", ".pt", ".bin"):
+            if lora_name_no_ext.lower().endswith(ext):
+                lora_name_no_ext = lora_name_no_ext[: -len(ext)]
+                break
+
+        has_path = "/" in lora_name_no_ext
+        basename = os.path.basename(lora_name_no_ext) if has_path else lora_name_no_ext
+        best_fallback = None
+
         for item in cache.raw_data:
-            if item.get("file_name") == lora_name:
+            file_name = item.get("file_name", "")
+            folder = item.get("folder", "")
+            file_name_no_ext = file_name
+            for ext in (".safetensors", ".ckpt", ".pt", ".bin"):
+                if file_name_no_ext.lower().endswith(ext):
+                    file_name_no_ext = file_name_no_ext[: -len(ext)]
+                    break
+            path_name = f"{folder}/{file_name_no_ext}".replace("\\", "/") if folder else file_name_no_ext
+
+            if lora_name_no_ext not in (file_name_no_ext, path_name):
+                if has_path and file_name_no_ext == basename:
+                    if folder and lora_name_no_ext.startswith(folder.replace("\\", "/") + "/"):
+                        best_fallback = item
+                    elif best_fallback is None:
+                        best_fallback = item
+                continue
+
             file_path = item.get("file_path")
-                if file_path:
+            if not file_path:
-                    # Check all lora roots including extra paths
+                continue
+
             all_roots = list(config.loras_roots or []) + list(
                 config.extra_loras_roots or []
             )
@@ -29,16 +57,22 @@ def get_lora_info(lora_name):
                     relative_path = os.path.relpath(file_path, root).replace(
                         os.sep, "/"
                     )
-                            # Get trigger words from civitai metadata
                     civitai = item.get("civitai", {})
                     trigger_words = (
                         civitai.get("trainedWords", []) if civitai else []
                     )
                     return relative_path, trigger_words
-                    # If not found in any root, return path with trigger words from cache
             civitai = item.get("civitai", {})
             trigger_words = civitai.get("trainedWords", []) if civitai else []
             return file_path, trigger_words
+
+        if best_fallback:
+            file_path = best_fallback.get("file_path")
+            if file_path:
+                civitai = best_fallback.get("civitai", {})
+                trigger_words = civitai.get("trainedWords", []) if civitai else []
+                return file_path, trigger_words
+
         return lora_name, []
 
     try:
@@ -77,15 +111,54 @@ def get_lora_info_absolute(lora_name):
         scanner = await ServiceRegistry.get_lora_scanner()
         cache = await scanner.get_cached_data()
 
+        lora_name_normalized = lora_name.replace("\\", "/")
+        lora_name_no_ext = lora_name_normalized
+        for ext in (".safetensors", ".ckpt", ".pt", ".bin"):
+            if lora_name_no_ext.lower().endswith(ext):
+                lora_name_no_ext = lora_name_no_ext[: -len(ext)]
+                break
+
+        has_path = "/" in lora_name_no_ext
+        basename = os.path.basename(lora_name_no_ext) if has_path else lora_name_no_ext
+        best_fallback = None
+
         for item in cache.raw_data:
-            if item.get("file_name") == lora_name:
+            file_name = item.get("file_name", "")
+            folder = item.get("folder", "")
+            file_name_no_ext = file_name
+            for ext in (".safetensors", ".ckpt", ".pt", ".bin"):
+                if file_name_no_ext.lower().endswith(ext):
+                    file_name_no_ext = file_name_no_ext[: -len(ext)]
+                    break
+            path_name = f"{folder}/{file_name_no_ext}".replace("\\", "/") if folder else file_name_no_ext
+
+            if lora_name_no_ext == file_name_no_ext:
                 file_path = item.get("file_path")
                 if file_path:
-                    # Return absolute path directly
-                    # Get trigger words from civitai metadata
                     civitai = item.get("civitai", {})
                     trigger_words = civitai.get("trainedWords", []) if civitai else []
                     return file_path, trigger_words
+
+            if lora_name_no_ext == path_name:
+                file_path = item.get("file_path")
+                if file_path:
+                    civitai = item.get("civitai", {})
+                    trigger_words = civitai.get("trainedWords", []) if civitai else []
+                    return file_path, trigger_words
+
+            if has_path and file_name_no_ext == basename:
+                if folder and lora_name_no_ext.startswith(folder.replace("\\", "/") + "/"):
+                    best_fallback = item
+                elif best_fallback is None:
+                    best_fallback = item
+
+        if best_fallback:
+            file_path = best_fallback.get("file_path")
+            if file_path:
+                civitai = best_fallback.get("civitai", {})
+                trigger_words = civitai.get("trainedWords", []) if civitai else []
+                return file_path, trigger_words
+
         return lora_name, []
 
     try:

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-lora-manager"
 description = "Revolutionize your workflow with the ultimate LoRA companion for ComfyUI!"
-version = "1.0.5"
+version = "1.1.0"
 license = {file = "LICENSE"}
 dependencies = [
     "aiohttp",

requirements.txt

@@ -1,4 +1,5 @@
 aiohttp
+aiohttp-socks
 jinja2
 safetensors
 piexif

scripts/migrate_legacy_metadata.py

@@ -0,0 +1,353 @@
+#!/usr/bin/env python3
+"""
+Migrate metadata from old sidecar JSON format to LoRA Manager's metadata.json format.
+
+This script automatically discovers model folders from LoRA Manager's settings.json,
+finds JSON files with the same basename as model files (e.g., `model.json` for
+`model.safetensors`), and migrates their content to the corresponding `.metadata.json` files.
+
+Fields migrated:
+- "activation text" → civitai.trainedWords (array of trigger words)
+- "preferred weight" → usage_tips.strength (LoRA only, skipped for Checkpoint)
+- "notes" → notes (user-defined notes)
+
+Supported model types: LoRA, Checkpoint
+
+Usage:
+    python scripts/migrate_legacy_metadata.py [--dry-run] [--verbose]
+
+The script will:
+1. Read settings.json to find all configured model folders
+2. Recursively scan for model files (.safetensors, .ckpt, .pt, .pth, .bin)
+3. Find corresponding legacy metadata JSON files
+4. Migrate data to .metadata.json files
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import logging
+import os
+import re
+import sys
+from pathlib import Path
+from typing import Any
+
+from platformdirs import user_config_dir
+
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s - %(levelname)s - %(message)s",
+)
+logger = logging.getLogger(__name__)
+
+APP_NAME = "ComfyUI-LoRA-Manager"
+MODEL_EXTENSIONS = {".safetensors", ".ckpt", ".pt", ".pth", ".bin"}
+SECRET_PATTERN = re.compile(r"(key|token|secret|password|auth|credential)", re.IGNORECASE)
+
+
+def resolve_settings_path() -> Path:
+    repo_root = Path(__file__).parent.parent.resolve()
+    portable = repo_root / "settings.json"
+    if portable.exists():
+        payload = load_json(portable)
+        if isinstance(payload, dict) and payload.get("use_portable_settings") is True:
+            return portable
+
+    return Path(user_config_dir(APP_NAME, appauthor=False)) / "settings.json"
+
+
+def load_json(path: Path) -> dict[str, Any]:
+    try:
+        with path.open("r", encoding="utf-8") as f:
+            return json.load(f)
+    except FileNotFoundError:
+        return {}
+    except json.JSONDecodeError as exc:
+        logger.error(f"Invalid JSON in {path}: {exc}")
+        return {}
+    except OSError as exc:
+        logger.error(f"Cannot read {path}: {exc}")
+        return {}
+
+
+def expand_path(value: str) -> str:
+    return str(Path(value).expanduser().resolve(strict=False))
+
+
+def normalize_path_list(value: Any) -> list[str]:
+    if isinstance(value, str):
+        return [expand_path(value)] if value else []
+    if isinstance(value, list):
+        return [expand_path(item) for item in value if isinstance(item, str) and item]
+    return []
+
+
+def dedupe(values: list[str]) -> list[str]:
+    seen: set[str] = set()
+    result: list[str] = []
+    for value in values:
+        if value not in seen:
+            result.append(value)
+            seen.add(value)
+    return result
+
+
+def get_model_roots(settings: dict[str, Any]) -> dict[str, list[str]]:
+    roots: dict[str, list[str]] = {}
+    active_library = settings.get("active_library") or "default"
+    sources = [settings]
+    library = settings.get("libraries", {}).get(active_library)
+    if isinstance(library, dict):
+        sources.insert(0, library)
+    for source in sources:
+        folder_paths = source.get("folder_paths")
+        if isinstance(folder_paths, dict):
+            for key, value in folder_paths.items():
+                roots.setdefault(key, []).extend(normalize_path_list(value))
+    for default_key, folder_key in (
+        ("default_lora_root", "loras"),
+        ("default_checkpoint_root", "checkpoints"),
+        ("default_embedding_root", "embeddings"),
+        ("default_unet_root", "unet"),
+    ):
+        value = settings.get(default_key)
+        if isinstance(value, str) and value:
+            roots.setdefault(folder_key, []).append(expand_path(value))
+    return {key: dedupe(values) for key, values in roots.items()}
+
+
+def find_model_files(directory: Path) -> list[Path]:
+    model_files = []
+    for ext in MODEL_EXTENSIONS:
+        model_files.extend(directory.rglob(f"*{ext}"))
+    return model_files
+
+
+def find_legacy_metadata(model_path: Path) -> Path | None:
+    base_name = model_path.stem
+    legacy_path = model_path.with_name(f"{base_name}.json")
+    if legacy_path.exists() and legacy_path.is_file():
+        return legacy_path
+    return None
+
+
+def load_legacy_metadata(legacy_path: Path) -> dict[str, Any] | None:
+    try:
+        with open(legacy_path, "r", encoding="utf-8") as f:
+            return json.load(f)
+    except json.JSONDecodeError as e:
+        logger.error(f"Invalid JSON in legacy file {legacy_path}: {e}")
+        return None
+    except Exception as e:
+        logger.error(f"Error reading legacy file {legacy_path}: {e}")
+        return None
+
+
+def load_metadata(metadata_path: Path) -> dict[str, Any]:
+    if not metadata_path.exists():
+        return {}
+    try:
+        with open(metadata_path, "r", encoding="utf-8") as f:
+            return json.load(f)
+    except json.JSONDecodeError as e:
+        logger.warning(f"Invalid JSON in metadata file {metadata_path}: {e}. Starting fresh.")
+        return {}
+    except Exception as e:
+        logger.error(f"Error reading metadata file {metadata_path}: {e}")
+        return {}
+
+
+def save_metadata(metadata_path: Path, data: dict[str, Any], dry_run: bool = False) -> bool:
+    if dry_run:
+        logger.info(f"[DRY RUN] Would save metadata to: {metadata_path}")
+        return True
+    temp_path = metadata_path.with_suffix(".tmp")
+    try:
+        with open(temp_path, "w", encoding="utf-8") as f:
+            json.dump(data, f, indent=2, ensure_ascii=False)
+        os.replace(temp_path, metadata_path)
+        return True
+    except Exception as e:
+        logger.error(f"Error saving metadata to {metadata_path}: {e}")
+        if temp_path.exists():
+            try:
+                temp_path.unlink()
+            except:
+                pass
+        return False
+
+
+def migrate_metadata(
+    legacy_data: dict[str, Any],
+    existing_metadata: dict[str, Any],
+    model_type: str
+) -> dict[str, Any] | None:
+    metadata = existing_metadata.copy()
+    changes_made = False
+    if "civitai" not in metadata:
+        metadata["civitai"] = {}
+    activation_text = legacy_data.get("activation text")
+    if activation_text and isinstance(activation_text, str):
+        trigger_words = [
+            word.strip()
+            for word in activation_text.replace("\n", ",").split(",")
+            if word.strip()
+        ]
+        if trigger_words:
+            existing_trained = metadata["civitai"].get("trainedWords", [])
+            if not isinstance(existing_trained, list):
+                existing_trained = []
+            merged = list(dict.fromkeys(existing_trained + trigger_words))
+            if merged != existing_trained:
+                metadata["civitai"]["trainedWords"] = merged
+                changes_made = True
+                logger.debug(f"  Migrated activation text: {trigger_words}")
+    if model_type == "lora":
+        preferred_weight = legacy_data.get("preferred weight")
+        if preferred_weight is not None:
+            try:
+                weight_value = float(preferred_weight)
+                usage_tips_str = metadata.get("usage_tips", "{}")
+                if isinstance(usage_tips_str, str):
+                    try:
+                        usage_tips = json.loads(usage_tips_str)
+                    except json.JSONDecodeError:
+                        usage_tips = {}
+                elif isinstance(usage_tips_str, dict):
+                    usage_tips = usage_tips_str
+                else:
+                    usage_tips = {}
+                if "strength" not in usage_tips:
+                    usage_tips["strength"] = weight_value
+                    metadata["usage_tips"] = json.dumps(usage_tips, ensure_ascii=False)
+                    changes_made = True
+                    logger.debug(f"  Migrated preferred weight: {weight_value}")
+            except (ValueError, TypeError) as e:
+                logger.warning(f"  Could not parse preferred weight '{preferred_weight}': {e}")
+    else:
+        if legacy_data.get("preferred weight") is not None:
+            logger.debug("  Skipping 'preferred weight' for non-LoRA model")
+    notes = legacy_data.get("notes")
+    if notes and isinstance(notes, str) and notes.strip():
+        existing_notes = metadata.get("notes", "")
+        if not existing_notes:
+            metadata["notes"] = notes.strip()
+            changes_made = True
+            logger.debug("  Migrated notes")
+        elif notes.strip() not in existing_notes:
+            metadata["notes"] = f"{existing_notes}\n\n{notes.strip()}".strip()
+            changes_made = True
+            logger.debug("  Appended notes")
+    return metadata if changes_made else None
+
+
+def process_model(model_path: Path, model_type: str, dry_run: bool = False) -> bool:
+    legacy_path = find_legacy_metadata(model_path)
+    if not legacy_path:
+        return True
+    logger.info(f"Processing: {model_path.name} ({model_type})")
+    logger.info(f"  Found legacy metadata: {legacy_path.name}")
+    legacy_data = load_legacy_metadata(legacy_path)
+    if legacy_data is None:
+        return False
+    metadata_path = model_path.with_suffix(".metadata.json")
+    existing_metadata = load_metadata(metadata_path)
+    migrated = migrate_metadata(legacy_data, existing_metadata, model_type)
+    if migrated is None:
+        logger.info("  No changes needed (fields already exist or no migratable data)")
+        return True
+    if save_metadata(metadata_path, migrated, dry_run):
+        logger.info(f"  ✓ Successfully migrated metadata to: {metadata_path.name}")
+        return True
+    else:
+        logger.error("  ✗ Failed to save metadata")
+        return False
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(
+        description="Migrate legacy metadata JSON files to LoRA Manager's metadata.json format.",
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        epilog="""
+Examples:
+  python scripts/migrate_legacy_metadata.py
+  python scripts/migrate_legacy_metadata.py --dry-run
+  python scripts/migrate_legacy_metadata.py --verbose
+        """
+    )
+    parser.add_argument(
+        "--dry-run",
+        action="store_true",
+        help="Preview changes without modifying any files"
+    )
+    parser.add_argument(
+        "-v", "--verbose",
+        action="store_true",
+        help="Enable verbose output"
+    )
+    args = parser.parse_args()
+    if args.verbose:
+        logging.getLogger().setLevel(logging.DEBUG)
+    settings_path = resolve_settings_path()
+    logger.info(f"Using settings: {settings_path}")
+    settings = load_json(settings_path)
+    if not settings:
+        logger.error("Could not load settings.json. Please ensure LoRA Manager is configured.")
+        return 1
+    roots = get_model_roots(settings)
+    if not roots:
+        logger.error("No model folders configured in settings.json.")
+        return 1
+    lora_roots = roots.get("loras", [])
+    checkpoint_roots = roots.get("checkpoints", []) + roots.get("unet", [])
+    all_roots = []
+    for root_list in [lora_roots, checkpoint_roots]:
+        for root in root_list:
+            path = Path(root)
+            if path.exists() and path.is_dir():
+                all_roots.append((path, "lora" if root in lora_roots else "checkpoint"))
+    if not all_roots:
+        logger.error("No valid model folders found.")
+        return 1
+    logger.info(f"Found {len(lora_roots)} LoRA root(s), {len(checkpoint_roots)} Checkpoint root(s)")
+    processed = 0
+    migrated = 0
+    errors = 0
+    skipped = 0
+    lora_count = 0
+    checkpoint_count = 0
+    for root_path, model_type in all_roots:
+        logger.info(f"Scanning: {root_path} ({model_type})")
+        model_files = find_model_files(root_path)
+        logger.debug(f"  Found {len(model_files)} model files")
+        for model_path in model_files:
+            legacy_path = find_legacy_metadata(model_path)
+            if not legacy_path:
+                skipped += 1
+                continue
+            processed += 1
+            if process_model(model_path, model_type, dry_run=args.dry_run):
+                migrated += 1
+                if model_type == "lora":
+                    lora_count += 1
+                else:
+                    checkpoint_count += 1
+            else:
+                errors += 1
+    logger.info("\n" + "=" * 50)
+    logger.info("Migration Summary:")
+    logger.info(f"  Models with legacy metadata: {processed}")
+    logger.info(f"  Successfully migrated: {migrated}")
+    logger.info(f"    - LoRA models: {lora_count}")
+    logger.info(f"    - Checkpoint models: {checkpoint_count}")
+    logger.info(f"  Errors: {errors}")
+    logger.info(f"  Skipped (no legacy file): {skipped}")
+    if args.dry_run:
+        logger.info("\n  [DRY RUN MODE - No files were modified]")
+    return 0 if errors == 0 else 1
+
+
+if __name__ == "__main__":
+    sys.exit(main())

scripts/restore_suffixed_filenames.py

@@ -0,0 +1,403 @@
+#!/usr/bin/env python3
+"""
+Restore original filenames by removing leftover 4-char hash suffixes.
+
+When LoRA Manager's old duplicate filename resolver ran, it appended
+``-{first4ofSHA256}`` to duplicate filenames, e.g.::
+
+    my_lora.safetensors  →  my_lora-a3f7.safetensors
+
+With full-path LoRA syntax now available (``<lora:subfolder/name:1.0>``),
+these suffixes are unnecessary.  This script detects such files and, with
+your confirmation, restores their original names.
+
+The same suffix pattern is also used by the download conflict handler
+(``{name}-{hash}.{ext}``).  To avoid false positives, this script skips
+any file whose original name already exists in the same directory — those
+were likely added by a download conflict, not the old resolver.
+
+Usage::
+
+    # Detect only (dry-run, default)
+    python scripts/restore_suffixed_filenames.py
+
+    # Detect + restore (with confirmation prompt)
+    python scripts/restore_suffixed_filenames.py --apply
+
+After restoring filenames, run **Rebuild Cache** in the LoRA Manager
+Doctor panel to refresh the model cache.
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import logging
+import os
+import re
+import sys
+from pathlib import Path
+from typing import Any
+
+from platformdirs import user_config_dir
+
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(message)s",
+)
+logger = logging.getLogger(__name__)
+
+APP_NAME = "ComfyUI-LoRA-Manager"
+MODEL_EXTENSIONS = {".safetensors", ".ckpt", ".pt", ".pth", ".bin"}
+PREVIEW_EXTENSIONS = {
+    ".png", ".jpg", ".jpeg", ".webp", ".gif", ".bmp",
+    ".mp4", ".webm", ".mov",
+}
+
+# Matches filenames like "my_lora-a3f7.safetensors"
+# Groups: (base_name, 4-char-hex, extension)
+_SUFFIX_RE = re.compile(r"^(.+)-([0-9a-f]{4})(\.[^.]+)$")
+
+
+# ── helpers (copied from migrate_legacy_metadata.py for consistency) ──────────
+
+
+def resolve_settings_path() -> Path:
+    repo_root = Path(__file__).parent.parent.resolve()
+    portable = repo_root / "settings.json"
+    if portable.exists():
+        payload = _load_json(portable)
+        if isinstance(payload, dict) and payload.get("use_portable_settings") is True:
+            return portable
+
+    return Path(user_config_dir(APP_NAME, appauthor=False)) / "settings.json"
+
+
+def _load_json(path: Path) -> dict[str, Any]:
+    try:
+        with path.open("r", encoding="utf-8") as f:
+            return json.load(f)
+    except (FileNotFoundError, json.JSONDecodeError, OSError):
+        return {}
+
+
+def _expand_path(value: str) -> str:
+    return str(Path(value).expanduser().resolve(strict=False))
+
+
+def _normalize_path_list(value: Any) -> list[str]:
+    if isinstance(value, str):
+        return [_expand_path(value)] if value else []
+    if isinstance(value, list):
+        return [_expand_path(item) for item in value if isinstance(item, str) and item]
+    return []
+
+
+def _dedupe(values: list[str]) -> list[str]:
+    seen: set[str] = set()
+    result: list[str] = []
+    for value in values:
+        if value not in seen:
+            result.append(value)
+            seen.add(value)
+    return result
+
+
+def get_model_roots(settings: dict[str, Any]) -> dict[str, list[str]]:
+    """Extract model folder roots from LoRA Manager settings.
+
+    Returns ``{model_type: [path, ...]}`` where *model_type* is one of
+    ``loras``, ``checkpoints``, ``embeddings``, ``unet``, etc.
+
+    Both primary (``folder_paths``) and extra (``extra_folder_paths``)
+    paths are included.  Extra paths can be configured via the UI at
+    Settings → Model Libraries → Extra Folder Paths.
+    """
+    roots: dict[str, list[str]] = {}
+    active_library = settings.get("active_library") or "default"
+    sources = [settings]
+    library = settings.get("libraries", {}).get(active_library)
+    if isinstance(library, dict):
+        sources.insert(0, library)
+    for source in sources:
+        # Primary folder paths.
+        folder_paths = source.get("folder_paths")
+        if isinstance(folder_paths, dict):
+            for key, value in folder_paths.items():
+                roots.setdefault(key, []).extend(_normalize_path_list(value))
+        # Extra folder paths (Settings → Model Libraries → Extra Folder Paths).
+        extra_folder_paths = source.get("extra_folder_paths")
+        if isinstance(extra_folder_paths, dict):
+            for key, value in extra_folder_paths.items():
+                roots.setdefault(key, []).extend(_normalize_path_list(value))
+    for default_key, folder_key in (
+        ("default_lora_root", "loras"),
+        ("default_checkpoint_root", "checkpoints"),
+        ("default_unet_root", "unet"),
+        ("default_embedding_root", "embeddings"),
+    ):
+        value = settings.get(default_key)
+        if isinstance(value, str) and value:
+            roots.setdefault(folder_key, []).append(_expand_path(value))
+    return {key: _dedupe(values) for key, values in roots.items()}
+
+
+def find_model_files(directory: Path) -> list[Path]:
+    """Recursively find all model files in *directory*."""
+    files: list[Path] = []
+    for ext in MODEL_EXTENSIONS:
+        files.extend(directory.rglob(f"*{ext}"))
+    return files
+
+
+# ── core detection logic ──────────────────────────────────────────────────────
+
+
+def check_file(path: Path) -> tuple[str, str, str] | None:
+    """If *path* matches the suffix pattern, return ``(base_name, hex, ext)``.
+
+    Returns ``None`` when:
+    * The filename does not match the pattern, or
+    * The original name (without the suffix) already exists in the same
+      directory (likely a download-conflict rename, not a doctor rename).
+    """
+    match = _SUFFIX_RE.match(path.name)
+    if not match:
+        return None
+
+    base_name = match.group(1)
+    hex_part = match.group(2)
+    extension = match.group(3)
+    orig_name = base_name + extension
+    orig_path = path.with_name(orig_name)
+
+    # Safety: skip if the original name already exists.
+    if orig_path.exists():
+        return None
+
+    return base_name, hex_part, extension
+
+
+def scan_roots(
+    roots: dict[str, list[str]],
+) -> dict[str, list[tuple[Path, str, str, str]]]:
+    """Scan all model roots and return detected files grouped by model type.
+
+    Returns ``{model_type: [(full_path, base_name, hex, ext), ...]}``.
+    """
+    results: dict[str, list[tuple[Path, str, str, str]]] = {}
+
+    for model_type, root_list in roots.items():
+        type_results: list[tuple[Path, str, str, str]] = []
+        for root in root_list:
+            root_path = Path(root)
+            if not root_path.is_dir():
+                continue
+            for model_file in find_model_files(root_path):
+                match = check_file(model_file)
+                if match:
+                    type_results.append((model_file, *match))
+        if type_results:
+            results[model_type] = type_results
+
+    return results
+
+
+def rename_file(
+    path: Path, base_name: str, extension: str, dry_run: bool
+) -> bool:
+    """Rename *path* to ``{base_name}{extension}``.
+
+    Also renames sidecar files (``.metadata.json``, ``.civitai.info``) and
+    preview images.  Returns ``True`` on success.
+    """
+    new_path = path.with_name(base_name + extension)
+    old_stem = path.with_suffix("")  # /dir/base_name-hex  (no ext)
+    new_stem = new_path.with_suffix("")  # /dir/base_name  (no ext)
+
+    if dry_run:
+        logger.info("  would rename:  %s", path.name)
+        logger.info("             ->  %s", new_path.name)
+        return True
+
+    try:
+        os.rename(path, new_path)
+    except OSError as exc:
+        logger.error("  FAILED to rename %s: %s", path.name, exc)
+        return False
+
+    # Rename sidecar metadata files.
+    for suffix in (".metadata.json", ".civitai.info"):
+        old_sidecar = old_stem.with_name(old_stem.name + suffix)
+        new_sidecar = new_stem.with_name(new_stem.name + suffix)
+        if old_sidecar.exists():
+            try:
+                os.rename(old_sidecar, new_sidecar)
+            except OSError as exc:
+                logger.warning("  could not rename sidecar %s: %s", old_sidecar.name, exc)
+
+    # Rename preview images.
+    for preview_ext in PREVIEW_EXTENSIONS:
+        old_preview = old_stem.with_name(old_stem.name + preview_ext)
+        new_preview = new_stem.with_name(new_stem.name + preview_ext)
+        if old_preview.exists():
+            try:
+                os.rename(old_preview, new_preview)
+            except OSError as exc:
+                logger.warning("  could not rename preview %s: %s", old_preview.name, exc)
+
+    logger.info("  renamed: %s  ->  %s", path.name, new_path.name)
+    return True
+
+
+# ── report helpers ────────────────────────────────────────────────────────────
+
+
+def print_report(results: dict[str, list[tuple[Path, str, str, str]]]) -> int:
+    """Print a human-readable report of detected files.  Returns total count."""
+    if not results:
+        logger.info("No leftover suffixed filenames detected.")
+        return 0
+
+    total = 0
+    for model_type in sorted(results):
+        entries = results[model_type]
+        total += len(entries)
+        label = model_type.capitalize()
+        logger.info("")
+        logger.info("─" * 50)
+        logger.info("  %s  (%d file(s))", label, len(entries))
+        logger.info("─" * 50)
+        for path, base_name, hex_part, ext in sorted(entries):
+            logger.info("  %s  →  %s%s", path.name, base_name, ext)
+
+    logger.info("")
+    logger.info("=" * 50)
+    logger.info("  Total: %d file(s) with leftover suffixes.", total)
+    logger.info("=" * 50)
+    return total
+
+
+def prompt_user(count: int) -> bool:
+    """Ask the user whether to proceed with the rename."""
+    try:
+        answer = input(
+            f"\nRestore {count} file(s) to their original names? [y/N] "
+        ).strip().lower()
+    except (EOFError, KeyboardInterrupt):
+        print()
+        return False
+    return answer in ("y", "yes")
+
+
+# ── main ──────────────────────────────────────────────────────────────────────
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(
+        description=(
+            "Detect and restore model filenames that have leftover "
+            "4-character hash suffixes from the old conflict resolver."
+        ),
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        epilog=(
+            "Examples:\n"
+            "  python scripts/restore_suffixed_filenames.py\n"
+            "  python scripts/restore_suffixed_filenames.py --apply\n"
+            "  python scripts/restore_suffixed_filenames.py --apply --yes\n"
+        ),
+    )
+    parser.add_argument(
+        "--apply",
+        action="store_true",
+        help="Actually rename files (with confirmation prompt unless --yes is given)",
+    )
+    parser.add_argument(
+        "--yes", "-y",
+        action="store_true",
+        help="Skip confirmation prompt (implies --apply)",
+    )
+    parser.add_argument(
+        "--dry-run",
+        action="store_true",
+        help="Detect only — show what would be renamed without making changes",
+    )
+    parser.add_argument(
+        "-v", "--verbose",
+        action="store_true",
+        help="Enable debug-level logging",
+    )
+    args = parser.parse_args()
+
+    if args.verbose:
+        logging.getLogger().setLevel(logging.DEBUG)
+
+    # Resolve settings.
+    settings_path = resolve_settings_path()
+    logger.info("Settings: %s", settings_path)
+    settings = _load_json(settings_path)
+    if not settings:
+        logger.error("Could not load settings.json.  Is LoRA Manager configured?")
+        return 1
+
+    roots = get_model_roots(settings)
+    if not roots:
+        logger.error("No model folders found in settings.")
+        return 1
+
+    # Log which roots are being scanned.
+    for model_type, root_list in roots.items():
+        for root in root_list:
+            logger.info("Scanning %s: %s", model_type, root)
+
+    # Detect.
+    results = scan_roots(roots)
+    total = print_report(results)
+
+    if total == 0:
+        return 0
+
+    # Determine mode.
+    dry_run = not args.apply and not args.yes
+
+    if dry_run:
+        logger.info("\n[Dry-run mode — no files modified]")
+        logger.info("Run with --apply to restore filenames.")
+        return 0
+
+    # Confirm unless --yes.
+    if not args.yes:
+        if not prompt_user(total):
+            logger.info("Aborted.")
+            return 0
+
+    # Rename.
+    logger.info("")
+    success = 0
+    fail = 0
+    for model_type in sorted(results):
+        entries = results[model_type]
+        logger.info("")
+        logger.info("─" * 50)
+        logger.info("  Restoring %s  (%d file(s))", model_type, len(entries))
+        logger.info("─" * 50)
+        for path, base_name, hex_part, ext in sorted(entries):
+            ok = rename_file(path, base_name, ext, dry_run=False)
+            if ok:
+                success += 1
+            else:
+                fail += 1
+
+    logger.info("")
+    logger.info("=" * 50)
+    logger.info("  Done: %d restored, %d failed.", success, fail)
+    logger.info("=" * 50)
+    logger.info("")
+    logger.info("  ⚠  Please run Rebuild Cache in the LoRA Manager")
+    logger.info("     Doctor panel to refresh the model cache.")
+
+    return 0 if fail == 0 else 1
+
+
+if __name__ == "__main__":
+    sys.exit(main())

settings.json.example

@@ -10,6 +10,10 @@
       "C:/path/to/your/checkpoints_folder",
       "C:/path/to/another/checkpoints_folder"
     ],
+    "unet": [
+      "C:/path/to/your/diffusion_models_folder",
+      "C:/path/to/another/diffusion_models_folder"
+    ],
     "embeddings": [
       "C:/path/to/your/embeddings_folder",
       "C:/path/to/another/embeddings_folder"

static/css/base.css

@@ -1,21 +1,20 @@
+@import 'tokens/index.css';
+
 html,
 body {
     margin: 0;
     padding: 0;
     height: 100%;
     overflow: hidden;
-    /* Disable default scrolling */
 }
 
-/* 针对Firefox */
 * {
     scrollbar-width: thin;
-    scrollbar-color: var(--border-color) transparent;
+    scrollbar-color: var(--border-base) transparent;
 }
 
-/* 针对Webkit browsers (Chrome, Safari等) */
 ::-webkit-scrollbar {
-    width: 8px;
+    width: var(--scrollbar-width, 8px);
 }
 
 ::-webkit-scrollbar-track {
@@ -24,116 +23,128 @@ body {
 }
 
 ::-webkit-scrollbar-thumb {
-    background-color: var(--border-color);
+    background-color: var(--border-base);
-    border-radius: 4px;
+    border-radius: var(--radius-xs);
 }
 
 :root {
-    --bg-color: #ffffff;
-    --text-color: #333333;
-    --text-muted: #6c757d;
-    --card-bg: #ffffff;
-    --border-color: #e0e0e0;
     --header-height: 48px;
-
-    /* Color Components */
-    --lora-accent-l: 68%;
-    --lora-accent-c: 0.28;
-    --lora-accent-h: 256;
-    --lora-warning-l: 75%;
-    --lora-warning-c: 0.25;
-    --lora-warning-h: 80;
-    --lora-success-l: 70%;
-    --lora-success-c: 0.2;
-    --lora-success-h: 140;
-
-    /* Composed Colors */
-    --lora-accent: oklch(var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h));
-    --lora-surface: oklch(97% 0 0 / 0.95);
-    --lora-border: oklch(72% 0.03 256 / 0.45);
-    --lora-text: oklch(95% 0.02 256);
-    --lora-error: oklch(75% 0.32 29);
-    --lora-error-bg: color-mix(in oklch, var(--lora-error) 20%, transparent);
-    --lora-error-border: color-mix(in oklch, var(--lora-error) 50%, transparent);
-    --lora-warning: oklch(var(--lora-warning-l) var(--lora-warning-c) var(--lora-warning-h));
-    --lora-success: oklch(var(--lora-success-l) var(--lora-success-c) var(--lora-success-h));
-    --badge-update-bg: oklch(72% 0.2 220);
-    --badge-update-text: oklch(28% 0.03 220);
-    --badge-update-glow: oklch(72% 0.2 220 / 0.28);
-    --badge-skip-refresh-bg: oklch(82% 0.12 45);
-    --badge-skip-refresh-text: oklch(35% 0.02 45);
-    --badge-skip-refresh-glow: oklch(82% 0.12 45 / 0.15);
-
-    /* Spacing Scale */
-    --space-1: calc(8px * 1);
-    --space-2: calc(8px * 2);
-    --space-3: calc(8px * 3);
-    --space-4: calc(8px * 4);
-
-    /* Z-index Scale */
-    --z-base: 10;
-    --z-header: 100;
-    --z-modal: 1000;
-    --z-overlay: 2000;
-
-    /* Border Radius */
-    --border-radius-base: 12px;
-    --border-radius-md: 12px;
-    --border-radius-sm: 8px;
-    --border-radius-xs: 4px;
-
     --scrollbar-width: 8px;
-    /* 添加滚动条宽度变量 */
 
-    /* Shortcut styles */
+    --shortcut-bg: var(--color-accent-subtle);
-    --shortcut-bg: oklch(var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h) / 0.12);
+    --shortcut-border: var(--color-accent-border);
-    --shortcut-border: oklch(var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h) / 0.25);
+    --shortcut-text: var(--text-primary);
-    --shortcut-text: var(--text-color);
+
+    --lora-accent-transparent: var(--color-accent-transparent);
+
+    /* Legacy spacing aliases: 8px base grid to match existing component usage */
+    --space-1: 8px;
+    --space-2: 16px;
+    --space-3: 24px;
+    --space-4: 32px;
+
+    /* Legacy border-radius aliases to match existing component usage */
+    --border-radius-xs: 4px;
+    --border-radius-sm: 6px;
+    --border-radius-base: 8px;
+    --border-radius-md: 12px;
+    --border-radius-lg: 16px;
+}
+
+:root {
+    --bg-color: var(--bg-base);
+    --text-color: var(--text-primary);
+    --text-muted: var(--text-secondary);
+    --card-bg: var(--surface-base);
+    --border-color: var(--border-base);
+
+    --lora-accent: var(--color-accent);
+    --lora-surface: var(--bg-elevated);
+    --lora-border: var(--border-subtle);
+    --lora-text: var(--text-primary);
+    --lora-error: var(--color-error);
+    --lora-error-bg: var(--color-error-bg);
+    --lora-error-border: var(--color-error-border);
+    --lora-warning: var(--color-warning);
+    --lora-success: var(--color-success);
+
+    --badge-update-bg: var(--color-info-bg);
+    --badge-update-text: var(--color-info-text);
+    --badge-update-glow: var(--color-info-glow);
+    --badge-skip-refresh-bg: var(--color-skip-refresh-bg);
+    --badge-skip-refresh-text: var(--color-skip-refresh-text);
+    --badge-skip-refresh-glow: var(--color-skip-refresh-glow);
+}
+
+[data-theme="dark"] {
+    --bg-color: var(--bg-base);
+    --text-color: var(--text-primary);
+    --text-muted: var(--text-secondary);
+    --card-bg: var(--surface-base);
+    --border-color: var(--border-base);
+
+    --lora-accent: var(--color-accent);
+    --lora-surface: var(--bg-elevated);
+    --lora-border: var(--border-subtle);
+    --lora-text: var(--text-primary);
+    --lora-error: var(--color-error);
+    --lora-error-bg: var(--color-error-bg);
+    --lora-error-border: var(--color-error-border);
+    --lora-warning: var(--color-warning);
+    --lora-success: var(--color-success);
+
+    --badge-update-bg: var(--color-info-bg);
+    --badge-update-text: var(--color-info-text);
+    --badge-update-glow: var(--color-info-glow);
+    --badge-skip-refresh-bg: var(--color-skip-refresh-bg);
+    --badge-skip-refresh-text: var(--color-skip-refresh-text);
+    --badge-skip-refresh-glow: var(--color-skip-refresh-glow);
 }
 
 html[data-theme="dark"] {
-    background-color: #1a1a1a !important;
+    background-color: var(--bg-base) !important;
     color-scheme: dark;
 }
 
 html[data-theme="light"] {
-    background-color: #ffffff !important;
+    background-color: var(--bg-base) !important;
     color-scheme: light;
 }
 
-[data-theme="dark"] {
-    --bg-color: #1a1a1a;
-    --text-color: #e0e0e0;
-    --text-muted: #a0a0a0;
-    --card-bg: #2d2d2d;
-    --border-color: #404040;
-
-    --lora-accent: oklch(68% 0.28 256);
-    --lora-surface: oklch(25% 0.02 256 / 0.98);
-    --lora-border: oklch(90% 0.02 256 / 0.15);
-    --lora-text: oklch(98% 0.02 256);
-    --lora-warning: oklch(75% 0.25 80);
-    /* Modified to be used with oklch() */
-    --lora-error-bg: color-mix(in oklch, var(--lora-error) 15%, transparent);
-    --lora-error-border: color-mix(in oklch, var(--lora-error) 40%, transparent);
-    --badge-update-bg: oklch(62% 0.18 220);
-    --badge-update-text: oklch(98% 0.02 240);
-    --badge-update-glow: oklch(62% 0.18 220 / 0.4);
-    --badge-skip-refresh-bg: oklch(82% 0.12 45);
-    --badge-skip-refresh-text: oklch(98% 0.02 45);
-    --badge-skip-refresh-glow: oklch(82% 0.12 45 / 0.15);
-}
-
 body {
-    font-family: 'Segoe UI', sans-serif;
+    font-family: var(--font-body);
-    background: var(--bg-color);
+    background: var(--bg-base);
-    color: var(--text-color);
+    color: var(--text-primary);
     display: flex;
     flex-direction: column;
     padding-top: 0;
-    /* Remove the padding-top */
 }
 
 .hidden {
     display: none !important;
 }
+
+:focus-visible {
+    outline: 2px solid var(--color-accent);
+    outline-offset: 2px;
+}
+
+button:focus:not(:focus-visible),
+input:focus:not(:focus-visible),
+select:focus:not(:focus-visible) {
+    outline: none;
+}
+
+@media (prefers-reduced-motion: reduce) {
+    *,
+    *::before,
+    *::after {
+        animation-duration: 0.01ms !important;
+        animation-iteration-count: 1 !important;
+        transition-duration: 0.01ms !important;
+    }
+
+    html {
+        scroll-behavior: auto !important;
+    }
+}

static/css/components/alphabet-bar.css

@@ -46,7 +46,7 @@
     flex-direction: column;
     gap: 6px;
     align-items: center;
-    box-shadow: 2px 0 8px rgba(0, 0, 0, 0.1);
+    box-shadow: var(--shadow-side);
     max-height: 80vh;
     overflow-y: auto;
     scrollbar-width: thin;
@@ -75,7 +75,7 @@
     width: 20px;
     height: 40px;
     align-self: center;
-    box-shadow: 2px 0 8px rgba(0, 0, 0, 0.1);
+    box-shadow: var(--shadow-side);
 }
 
 .toggle-alphabet-bar:hover {
@@ -99,7 +99,7 @@
     min-width: 24px;
     text-align: center;
     font-size: 0.85em;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
     border: 1px solid var(--border-color);
 }
 
@@ -107,7 +107,7 @@
     background: var(--lora-accent);
     color: white;
     transform: scale(1.1);
-    box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
+    box-shadow: var(--shadow-md);
 }
 
 .letter-chip.active {

static/css/components/banner.css

@@ -68,7 +68,7 @@
     text-decoration: none;
     font-size: 0.85em;
     font-weight: 500;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
     white-space: nowrap;
     border: 1px solid transparent;
 }
@@ -102,7 +102,7 @@
     color: white;
     border-color: var(--lora-accent);
     transform: translateY(-1px);
-    box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
+    box-shadow: var(--shadow-md);
 }
 
 /* Tertiary Action Button */
@@ -133,7 +133,7 @@
     display: flex;
     align-items: center;
     justify-content: center;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
     font-size: 0.8em;
 }
 

static/css/components/batch-import-modal.css

@@ -76,7 +76,7 @@
     display: flex;
     align-items: center;
     justify-content: center;
-    transition: all 0.2s;
+    transition: var(--transition-base);
     background: var(--bg-color);
 }
 
@@ -87,7 +87,7 @@
 
 .checkbox-label input[type="checkbox"]:checked + .checkmark::after {
     content: '\f00c';
-    font-family: 'Font Awesome 6 Free';
+    font-family: 'Font Awesome 6 Free', sans-serif;
     font-weight: 900;
     color: var(--lora-text);
     font-size: 12px;
@@ -166,7 +166,7 @@
     background: var(--card-bg);
     color: var(--text-color);
     cursor: pointer;
-    transition: all 0.2s;
+    transition: var(--transition-base);
 }
 
 .back-btn:hover {
@@ -237,7 +237,7 @@
     padding: 8px 10px;
     border-radius: var(--border-radius-xs);
     cursor: pointer;
-    transition: all 0.2s;
+    transition: var(--transition-base);
     border: 1px solid transparent;
 }
 

static/css/components/card.css

@@ -1,12 +1,12 @@
-/* 卡片网格布局 */
+/* Card grid layout */
 .card-grid {
     display: grid;
     grid-template-columns: repeat(auto-fill, minmax(260px, 1fr)); /* Base size */
     gap: 12px; /* Consistent gap for both row and column spacing */
     row-gap: 20px; /* Increase vertical spacing between rows */
     margin-top: var(--space-2);
-    padding-top: 4px; /* 添加顶部内边距，为悬停动画提供空间 */
+    padding-top: 4px;
-    padding-bottom: 4px; /* 添加底部内边距，为悬停动画提供空间 */
+    padding-bottom: 4px;
     width: 100%; /* Ensure it takes full width of container */
     max-width: 1400px; /* Base container width */
     margin-left: auto;
@@ -19,9 +19,10 @@
     border: 1px solid var(--lora-border);
     border-radius: var(--border-radius-base);
     backdrop-filter: blur(16px);
-    transition: transform 160ms ease-out;
+    transition: transform var(--transition-fast) ease-out, box-shadow var(--transition-fast) ease-out, border-color var(--transition-fast) ease-out;
     aspect-ratio: 896/1152; /* Preserve aspect ratio */
     max-width: 260px; /* Base size */
+    min-width: 200px; /* Prevent cards from becoming too narrow */
     width: 100%;
     margin: 0 auto;
     cursor: pointer;
@@ -32,7 +33,8 @@
 
 .model-card:hover {
     transform: translateY(-2px);
-    background: oklch(100% 0 0 / 0.6);
+    box-shadow: var(--shadow-md);
+    border-color: var(--lora-accent);
 }
 
 .model-card:focus-visible {
@@ -276,7 +278,7 @@
     left: 0;
     right: 0;
     background: linear-gradient(transparent 15%, oklch(0% 0 0 / 0.75));
-    backdrop-filter: blur(8px);
+    backdrop-filter: blur(var(--card-blur-amount, 8px));
     color: white;
     padding: var(--space-1);
     display: flex;
@@ -292,7 +294,7 @@
     left: 0;
     right: 0;
     background: linear-gradient(oklch(0% 0 0 / 0.75), transparent 85%);
-    backdrop-filter: blur(8px);
+    backdrop-filter: blur(var(--card-blur-amount, 8px));
     color: white;
     padding: var(--space-1);
     display: flex;
@@ -328,7 +330,6 @@
 }
 
 .card-actions i {
-    margin-left: var(--space-1);
     cursor: pointer;
     color: white;
     transition: opacity 0.2s, transform 0.15s ease;
@@ -353,24 +354,38 @@
 }
 
 .card-actions {
+    flex-shrink: 0;
     display: flex;
-    gap: var(--space-1); /* Use gap instead of margin for spacing between icons */
+    gap: var(--space-1);
-    align-items: center;
+    align-items: flex-end;
+    align-self: flex-end;
 }
 
-.card-actions i:hover {
+.card-actions i:hover,
+.card-actions i:focus-visible {
     opacity: 0.9;
     transform: scale(1.1);
     background-color: rgba(255, 255, 255, 0.1);
+    outline: 2px solid var(--lora-accent);
+    outline-offset: 2px;
+    border-radius: var(--border-radius-xs);
 }
 
-/* Style for active favorites */
 .favorite-active {
-    color: #ffc107 !important; /* Gold color for favorites */
+    color: var(--favorite-color) !important;
-    text-shadow: 0 0 5px rgba(255, 193, 7, 0.5);
+    text-shadow: 0 0 5px var(--favorite-glow);
 }
 
-/* 响应式设计 */
+@media (max-width: 1200px) {
+    .card-grid {
+        grid-template-columns: repeat(auto-fill, minmax(220px, 1fr));
+    }
+    
+    .model-card {
+        max-width: 240px;
+        min-width: 180px;
+    }
+}
 @media (max-width: 768px) {
     .card-grid {
         grid-template-columns: minmax(260px, 1fr); /* Adjusted minimum size for mobile */
@@ -378,17 +393,10 @@
     
     .model-card {
         max-width: 100%; /* Allow cards to fill available space on mobile */
+        min-width: 200px;
     }
 }
 
-.card-actions {
-    flex-shrink: 0;  /* Prevent actions from shrinking */
-    display: flex;
-    gap: var(--space-1);
-    align-items: flex-end; /* 将图标靠下对齐 */
-    align-self: flex-end; /* 将整个actions容器靠下对齐 */
-}
-
 .model-link {
     margin-top: var(--space-1);
 }
@@ -401,9 +409,13 @@
     text-shadow: none;
 }
 
-.model-link a:hover {
+.model-link a:hover,
+.model-link a:focus-visible {
     opacity: 0.8;
     text-decoration: none;
+    outline: 2px solid var(--lora-accent);
+    outline-offset: 2px;
+    border-radius: var(--border-radius-xs);
 }
 
 /* Updated model name to fix text cutoff issues */
@@ -428,7 +440,7 @@
 
 .base-model {
     display: inline-block;
-    background: #f0f0f0;
+    background: var(--surface-hover, oklch(95% 0 0));
     padding: 2px 6px;
     border-radius: var(--border-radius-xs);
     margin-right: 6px;
@@ -497,11 +509,91 @@
     background: rgba(0,0,0,0.18); /* Optional: subtle background for contrast */
 }
 
+/* Version row — flex container for badges + version names */
+.version-row {
+    display: flex;
+    flex-wrap: wrap;
+    align-items: center;
+    gap: 3px;
+    margin-top: 2px;
+}
+
+/* Badge + version-name binding: they wrap as a single unit */
+.badge-version-unit {
+    display: inline-flex;
+    align-items: center;
+    gap: 3px;
+    min-width: 0;
+    flex-shrink: 0;
+}
+
 /* Medium density adjustments for version name */
 .medium-density .version-name {
     font-size: 0.8em;
 }
 
+.medium-density .badge-version-unit .version-name {
+    max-width: 90px;
+    white-space: nowrap;
+    overflow: hidden;
+    text-overflow: ellipsis;
+}
+
+/* Compact density adjustments for version name */
+.compact-density .version-name {
+    font-size: 0.75em;
+}
+
+.compact-density .badge-version-unit .version-name {
+    max-width: 70px;
+    white-space: nowrap;
+    overflow: hidden;
+    text-overflow: ellipsis;
+}
+
+.medium-density .version-row {
+    gap: 2px;
+}
+
+/* HIGH / LOW badges — shown inline before version name in card footer */
+.hl-badge {
+    display: inline-block;
+    font-size: 0.7em;
+    font-weight: 600;
+    line-height: 1.1;
+    padding: 1px 5px;
+    border-radius: var(--border-radius-xs);
+    border: 1px solid rgba(255, 255, 255, 0.2);
+    white-space: nowrap;
+}
+
+.hl-badge--high {
+    color: oklch(75% 0.12 230);
+    background: oklch(55% 0.15 240 / 0.25);
+    border-color: oklch(60% 0.18 250 / 0.3);
+}
+
+.hl-badge--low {
+    color: oklch(78% 0.10 185);
+    background: oklch(50% 0.10 190 / 0.25);
+    border-color: oklch(55% 0.12 195 / 0.3);
+}
+
+.medium-density .hl-badge {
+    font-size: 0.65em;
+}
+
+.compact-density .hl-badge {
+    font-size: 0.62em;
+    padding: 0px 4px;
+}
+
+/* Hide version-related elements when setting is disabled */
+body.hide-card-version .civitai-version,
+body.hide-card-version .hl-badge {
+    display: none;
+}
+
 /* Compact density adjustments for version name */
 .compact-density .version-name {
     font-size: 0.75em;
@@ -558,8 +650,13 @@
     position: absolute;
     box-sizing: border-box;
     transition: transform 160ms ease-out;
-    margin: 0; /* Remove margins, positioning is handled by VirtualScroller */
+    margin: 0;
-    width: 100%; /* Allow width to be set by the VirtualScroller */
+    width: 100%;
+}
+
+/* Allow cards to grow beyond 260px in virtual scroll mode */
+.virtual-scroll-item.model-card {
+    max-width: none;
 }
 
 .virtual-scroll-item:hover {
@@ -571,11 +668,11 @@
 .card-grid.virtual-scroll {
     display: block;
     position: relative;
-    margin: 0 auto;
+    margin: 0; /* Remove auto margins - positioning handled by VirtualScroller leftOffset */
     padding: 4px 0; /* Add top/bottom padding equivalent to card padding */
     height: auto;
     width: 100%;
-    max-width: 1400px; /* Keep the max-width from original grid */
+    max-width: none; /* Remove max-width constraint - handled by VirtualScroller */
     box-sizing: border-box; /* Include padding in width calculation */
     overflow-x: hidden; /* Prevent horizontal overflow */
 }

static/css/components/duplicates.css

@@ -11,8 +11,8 @@
     border-bottom: 1px solid oklch(var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h) / 0.4); /* Make bottom border stronger */
     z-index: var(--z-overlay);
     padding: 12px 0;
-    box-shadow: 0 3px 10px rgba(0, 0, 0, 0.2); /* Stronger shadow */
+    box-shadow: var(--shadow-lg); /* Stronger shadow */
-    transition: all 0.3s ease;
+    transition: var(--transition-slow);
     margin-bottom: 20px;
 }
 
@@ -65,7 +65,7 @@
     align-items: center;
     justify-content: center;
     gap: 6px;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
 }
 
 .duplicates-banner button.btn-exit-mode:hover {
@@ -86,16 +86,16 @@
     background: var(--card-bg);
     color: var(--text-color);
     font-size: 0.85em;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
     cursor: pointer;
-    box-shadow: 0 1px 2px rgba(0, 0, 0, 0.05);
+    box-shadow: var(--shadow-xs);
 }
 
 .duplicates-banner button:hover {
     border-color: var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h);
     background: var(--bg-color);
     transform: translateY(-1px);
-    box-shadow: 0 3px 5px rgba(0, 0, 0, 0.08);
+    box-shadow: var(--shadow-sm);
 }
 
 .duplicates-banner button.btn-exit {
@@ -122,7 +122,7 @@
     padding: 16px;
     margin-bottom: 24px;
     background: var(--card-bg);
-    box-shadow: 0 2px 6px rgba(0, 0, 0, 0.12); /* Add subtle shadow to groups */
+    box-shadow: var(--shadow-md); /* Add subtle shadow to groups */
     /* Add responsive width settings to match banner */
     max-width: 1400px;
     margin-left: auto;
@@ -173,9 +173,9 @@
     background: var(--card-bg);
     color: var(--text-color);
     font-size: 0.85em;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
     cursor: pointer;
-    box-shadow: 0 1px 2px rgba(0, 0, 0, 0.05);
+    box-shadow: var(--shadow-xs);
     margin-left: 8px;
 }
 
@@ -183,7 +183,7 @@
     border-color: var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h);
     background: var(--bg-color);
     transform: translateY(-1px);
-    box-shadow: 0 3px 5px rgba(0, 0, 0, 0.08);
+    box-shadow: var(--shadow-sm);
 }
 
 .card-group-container {
@@ -230,20 +230,20 @@
     justify-content: center;
     cursor: pointer;
     z-index: 1;
-    box-shadow: 0 1px 3px rgba(0, 0, 0, 0.1);
+    box-shadow: var(--shadow-sm);
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
 }
 
 .group-toggle-btn:hover {
     border-color: var(--lora-accent-l) var(--lora-accent-c) var (--lora-accent-h);
     transform: translateY(-1px);
-    box-shadow: 0 3px 5px rgba(0, 0, 0, 0.08);
+    box-shadow: var(--shadow-sm);
 }
 
 /* Duplicate card styling */
 .model-card.duplicate {
     position: relative;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
 }
 
 .model-card.duplicate:hover {
@@ -257,7 +257,7 @@
 
 .model-card.duplicate-selected {
     border: 2px solid oklch(var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h));
-    box-shadow: 0 0 8px rgba(0, 0, 0, 0.2);
+    box-shadow: var(--shadow-md);
 }
 
 .model-card .selector-checkbox {
@@ -290,7 +290,7 @@
     background-color: var(--card-bg);
     border: 1px solid var(--border-color);
     border-radius: var(--border-radius-sm);
-    box-shadow: 0 2px 10px rgba(0,0,0,0.2);
+    box-shadow: var(--shadow-lg);
     padding: 10px;
     z-index: 1000;
     max-width: 350px;
@@ -432,7 +432,7 @@
     border-radius: var(--border-radius-xs);
     font-size: 0.85em;
     cursor: pointer;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
 }
 
 .btn-verify-hashes:hover {
@@ -461,7 +461,7 @@
     position: absolute;
     top: -8px; /* Moved closer to button */
     right: -8px; /* Moved closer to button */
-    box-shadow: 0 1px 3px rgba(0, 0, 0, 0.15); /* Softer shadow */
+    box-shadow: var(--shadow-sm); /* Softer shadow */
     transition: transform 0.2s ease, opacity 0.2s ease;
 }
 
@@ -493,7 +493,7 @@
     cursor: help;
     font-size: 16px;
     margin-left: 8px;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
 }
 
 .help-icon:hover {
@@ -511,7 +511,7 @@
     border: 1px solid var(--border-color);
     border-radius: var(--border-radius-sm);
     padding: 12px 16px;
-    box-shadow: 0 4px 12px rgba(0, 0, 0, 0.15);
+    box-shadow: var(--shadow-elevated);
     z-index: var(--z-overlay);
     font-size: 0.9em;
     margin-top: 10px;
@@ -572,16 +572,16 @@
 
 /* In dark mode, add additional distinction */
 html[data-theme="dark"] .duplicates-banner {
-    box-shadow: 0 3px 12px rgba(0, 0, 0, 0.4); /* Stronger shadow in dark mode */
+    box-shadow: var(--shadow-dark-lg); /* Stronger shadow in dark mode */
     background-color: oklch(var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h) / 0.15); /* Slightly stronger background in dark mode */
 }
 
 html[data-theme="dark"] .duplicate-group {
-    box-shadow: 0 2px 8px rgba(0, 0, 0, 0.25); /* Stronger shadow in dark mode */
+    box-shadow: var(--shadow-lg); /* Stronger shadow in dark mode */
 }
 
 html[data-theme="dark"] .help-tooltip {
-    box-shadow: 0 4px 12px rgba(0, 0, 0, 0.3);
+    box-shadow: var(--shadow-elevated);
 }
 
 /* Styles for disabled controls during duplicates mode */

static/css/components/filter-indicator.css

@@ -7,22 +7,22 @@
     color: white;
     border-radius: var(--border-radius-xs);
     padding: 4px 10px;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
     border: 1px solid var(--lora-accent);
     cursor: pointer;
-    box-shadow: 0 1px 3px rgba(0, 0, 0, 0.1);
+    box-shadow: var(--shadow-sm);
     font-size: 0.85em;
 }
 
 .control-group .filter-active:hover {
     opacity: 0.92;
     transform: translateY(-1px);
-    box-shadow: 0 3px 5px rgba(0, 0, 0, 0.15);
+    box-shadow: var(--shadow-md);
 }
 
 .control-group .filter-active:active {
     transform: translateY(0);
-    box-shadow: 0 1px 3px rgba(0, 0, 0, 0.1);
+    box-shadow: var(--shadow-sm);
 }
 
 .control-group .filter-active i.fa-filter {
@@ -59,9 +59,9 @@
 
 /* Animation for filter indicator */
 @keyframes filterPulse {
-    0% { transform: scale(1); box-shadow: 0 1px 3px rgba(0, 0, 0, 0.1); }
+    0% { transform: scale(1); box-shadow: var(--shadow-sm); }
-    50% { transform: scale(1.03); box-shadow: 0 3px 8px rgba(0, 0, 0, 0.15); }
+    50% { transform: scale(1.03); box-shadow: var(--shadow-lg); }
-    100% { transform: scale(1); box-shadow: 0 1px 3px rgba(0, 0, 0, 0.1); }
+    100% { transform: scale(1); box-shadow: var(--shadow-sm); }
 }
 
 .filter-active.animate {

static/css/components/header.css

@@ -7,7 +7,7 @@
   height: 48px;
   /* Reduced height */
   width: 100%;
-  box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
+  box-shadow: var(--shadow-md);
   /* Slightly stronger shadow */
 }
 
@@ -22,6 +22,22 @@
   gap: 1rem;
 }
 
+/* Left section: Logo + Navigation */
+.header-left {
+  display: flex;
+  align-items: center;
+  gap: 1rem;
+  flex-shrink: 0;
+}
+
+/* Right section: Controls */
+.header-right {
+  display: flex;
+  align-items: center;
+  gap: 1rem;
+  flex-shrink: 0;
+}
+
 /* Responsive header container for larger screens */
 @media (min-width: 2150px) {
   .header-container {
@@ -77,6 +93,7 @@
   align-items: center;
   gap: 0.5rem;
   font-size: 0.9rem;
+  white-space: nowrap;
 }
 
 .nav-item:hover,
@@ -97,13 +114,101 @@
   color: white;
 }
 
-/* Header search */
+/* Header search - Centered with VS Code command palette style */
 .header-search {
   flex: 1;
-  max-width: 400px;
+  display: flex;
+  justify-content: center;
+  max-width: 600px;
+  margin: 0 auto;
   transition: opacity 0.2s ease;
 }
 
+/* VS Code command palette style search container */
+.header-search .search-container {
+  width: 100%;
+  max-width: 600px;
+  position: relative;
+  display: flex;
+  align-items: center;
+  background: var(--input-bg, var(--card-bg));
+  border: 1px solid var(--border-color);
+  border-radius: var(--border-radius-sm, 6px);
+  transition: border-color var(--transition-base), box-shadow var(--transition-base);
+  box-shadow: var(--shadow-header);
+  overflow: hidden;
+}
+
+.header-search .search-container:focus-within {
+  border-color: var(--lora-accent);
+  box-shadow: var(--shadow-header), 0 0 0 1px var(--lora-accent);
+}
+
+.header-search input {
+  flex: 1;
+  width: 100%;
+  padding: 0.5rem 0.75rem;
+  padding-left: 2.25rem !important;
+  padding-right: 5rem !important;
+  border: none;
+  background: transparent;
+  color: var(--text-color);
+  font-size: 0.95rem;
+  outline: none;
+}
+
+.header-search input::placeholder {
+  color: var(--text-muted);
+}
+
+.header-search .search-icon {
+  position: absolute;
+  left: 0.75rem;
+  color: var(--text-muted);
+  font-size: 0.9rem;
+  pointer-events: none;
+}
+
+.header-search .search-options-toggle,
+.header-search .search-filter-toggle {
+  position: absolute;
+  right: 0.5rem;
+  width: 28px;
+  height: 28px;
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  background: transparent;
+  border: none;
+  color: var(--text-muted);
+  cursor: pointer;
+  border-radius: var(--border-radius-xs, 4px);
+  transition: background-color var(--transition-base), color var(--transition-base);
+}
+
+.header-search .search-options-toggle {
+  right: 2.25rem;
+}
+
+.header-search .search-options-toggle:hover,
+.header-search .search-filter-toggle:hover,
+.header-search .search-filter-toggle:focus-visible {
+    background: var(--lora-surface-hover, oklch(95% 0.02 256));
+    color: var(--lora-accent);
+    outline: none;
+}
+
+.header-search .filter-badge {
+  position: absolute;
+  top: 2px;
+  right: 2px;
+  width: 8px;
+  height: 8px;
+  background: var(--lora-accent);
+  border-radius: 50%;
+  font-size: 0;
+}
+
 /* Disabled state for header search */
 .header-search.disabled {
   opacity: 0.5;
@@ -166,7 +271,7 @@
   align-items: center;
   justify-content: center;
   cursor: pointer;
-  transition: all 0.2s ease;
+  transition: background-color var(--transition-base), color var(--transition-base), transform var(--transition-base);
   position: relative;
 }
 
@@ -238,7 +343,7 @@
   background-color: var(--lora-error);
   border-radius: 50%;
   border: 2px solid var(--card-bg);
-  transition: all 0.2s ease;
+  transition: opacity var(--transition-base);
   pointer-events: none;
   opacity: 0;
 }
@@ -247,44 +352,216 @@
   opacity: 1;
 }
 
-/* Mobile adjustments */
+/* Hamburger menu button - hidden by default */
-@media (max-width: 768px) {
+.hamburger-menu-btn {
-  .app-title {
   display: none;
-    /* Hide text title on mobile */
+  width: 32px;
+  height: 32px;
+  border-radius: 50%;
+  background: var(--card-bg);
+  border: 1px solid var(--border-color);
+  color: var(--text-color);
+  align-items: center;
+  justify-content: center;
+  cursor: pointer;
+  transition: background-color var(--transition-base), color var(--transition-base);
+  flex-shrink: 0;
+}
+
+.hamburger-menu-btn:hover,
+.hamburger-menu-btn:focus-visible {
+    background: var(--lora-surface-hover, oklch(95% 0.02 256));
+    color: var(--lora-accent);
+    outline: none;
+}
+
+.hamburger-dropdown .dropdown-item:hover,
+.hamburger-dropdown .dropdown-item:focus-visible {
+    background: var(--lora-surface-hover, oklch(95% 0.02 256));
+    color: var(--lora-accent);
+    outline: none;
+}
+
+/* Hamburger dropdown menu */
+.hamburger-dropdown {
+  display: none;
+  position: absolute;
+  top: 100%;
+  right: 0;
+  margin-top: 8px;
+  background: var(--card-bg);
+  border: 1px solid var(--border-color);
+  border-radius: var(--border-radius-sm, 6px);
+  box-shadow: var(--shadow-toast);
+  padding: 0.5rem;
+  min-width: 160px;
+  z-index: var(--z-dropdown, 200);
+}
+
+.hamburger-dropdown.active {
+  display: flex;
+  flex-direction: column;
+  gap: 0.25rem;
+}
+
+.hamburger-dropdown .dropdown-item {
+  display: flex;
+  align-items: center;
+  gap: 0.75rem;
+  padding: 0.5rem 0.75rem;
+  border-radius: var(--border-radius-xs, 4px);
+  color: var(--text-color);
+  cursor: pointer;
+  transition: background-color var(--transition-base), color var(--transition-base);
+  font-size: 0.9rem;
+  white-space: nowrap;
+}
+
+.hamburger-dropdown .dropdown-item:hover {
+  background: var(--lora-surface-hover, oklch(95% 0.02 256));
+  color: var(--lora-accent);
+}
+
+.hamburger-dropdown .dropdown-item i {
+  width: 20px;
+  text-align: center;
+}
+
+.hamburger-dropdown .dropdown-divider {
+  height: 1px;
+  background: var(--border-color);
+  margin: 0.25rem 0;
+}
+
+/* Responsive: Early optimization at 1200px - reduce gaps and padding */
+@media (max-width: 1200px) {
+  .header-container {
+    gap: 0.75rem;
+    padding: 0 12px;
+  }
+
+  .main-nav {
+    gap: 0.25rem;
+  }
+
+  .nav-item {
+    padding: 0.25rem 0.5rem;
+    font-size: 0.85rem;
   }
 
   .header-controls {
-    gap: 4px;
+    gap: 6px;
   }
 
   .header-controls > div {
-    width: 28px;
+    width: 30px;
-    height: 28px;
+    height: 30px;
+  }
+}
+
+/* Responsive: Hide nav icons at 1100px to save space */
+@media (max-width: 1100px) {
+  .nav-item {
+    gap: 0;
+    padding: 0.25rem 0.4rem;
+  }
+
+  .nav-item i {
+    display: none;
+  }
+
+  .header-search {
+    max-width: 450px;
+  }
+}
+
+@media (max-width: 950px) {
+  .app-title {
+    display: none !important;
+  }
+
+  .header-container {
+    padding: 0 10px;
+    gap: 0.5rem;
+  }
+
+  .header-controls {
+    display: none !important;
+  }
+
+  .hamburger-menu-btn {
+    display: flex !important;
+  }
+
+  .hamburger-dropdown {
+    display: none;
+  }
+
+  .hamburger-dropdown.active {
+    display: flex;
   }
 
   .header-search {
     max-width: none;
-    margin: 0 0.5rem;
+    margin: 0;
+    flex: 1;
+    min-width: 200px;
   }
 
   .main-nav {
-    margin-right: 0.5rem;
+    gap: 0.25rem;
+    margin-right: 0;
+  }
+
+  .nav-item {
+    padding: 0.25rem 0.35rem;
+    font-size: 0.8rem;
   }
 }
 
-/* For very small screens */
+/* Responsive: Compact mode at 768px */
+@media (max-width: 768px) {
+  .header-search input {
+    padding: 0.4rem 0.6rem;
+    padding-left: 2rem !important;
+    padding-right: 4.5rem !important;
+    font-size: 0.9rem;
+  }
+
+  .header-search .search-container {
+    border-radius: var(--border-radius-xs, 4px);
+  }
+}
+
+/* For very small screens - switch nav to icons only */
 @media (max-width: 600px) {
   .header-container {
     padding: 0 8px;
+    gap: 0.4rem;
   }
 
   .main-nav {
-    display: none;
+    display: flex;
-    /* Hide navigation on very small screens */
+    gap: 0.15rem;
+    margin-right: 0;
   }
 
-  .header-search {
+  .nav-item {
-    flex: 1;
+    padding: 0.25rem;
+    font-size: 0.75rem;
+  }
+
+  .nav-item span {
+    display: none;
+  }
+
+  .nav-item i {
+    display: block;
+    font-size: 1rem;
   }
 }
+
+/* Position relative for hamburger menu positioning */
+.header-right {
+  position: relative;
+}

static/css/components/import-modal.css

@@ -757,7 +757,7 @@
     position: relative;
     border-radius: var(--border-radius-sm);
     overflow: hidden;
-    box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
+    box-shadow: var(--shadow-md);
     transition: transform 0.2s ease;
 }
 

static/css/components/initialization.css

@@ -176,7 +176,7 @@
   background: rgba(var(--lora-accent), 0.05);
   border-radius: var(--border-radius-base);
   padding: var(--space-2);
-  box-shadow: 0 2px 8px rgba(0, 0, 0, 0.05);
+  box-shadow: var(--shadow-sm);
 }
 
 .tips-header {

static/css/components/keyboard-nav.css

@@ -11,7 +11,7 @@
     border: 1px solid var(--border-color);
     color: var(--text-color);
     cursor: help;
-    transition: all 0.2s ease;
+    transition: var(--transition-base);
     margin-left: 8px;
 }
 
@@ -19,7 +19,7 @@
     background: var(--lora-accent);
     color: white;
     transform: translateY(-2px);
-    box-shadow: 0 3px 5px rgba(0, 0, 0, 0.08);
+    box-shadow: var(--shadow-sm);
 }
 
 .keyboard-nav-hint i {
@@ -46,7 +46,7 @@
     transform: translateY(-15%); /* Vertically center */
     opacity: 0;
     transition: opacity 0.3s;
-    box-shadow: 0 3px 8px rgba(0, 0, 0, 0.15);
+    box-shadow: var(--shadow-lg);
     border: 1px solid var(--lora-border);
     font-size: 0.85em;
     line-height: 1.4;
@@ -92,5 +92,5 @@
     border-radius: 3px;
     padding: 1px 5px;
     font-size: 0.8em;
-    box-shadow: 0 1px 2px rgba(0, 0, 0, 0.08);
+    box-shadow: var(--shadow-xs);
 }