fix(test): update drag interaction test to match 454210a4's renderFunction→setValue change

Commit 454210a4 replaced renderFunction() with widget.value setter +
widget.callback() in endDrag, so the test assertion should verify
callback invocation instead of the removed renderSpy call.

.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())

data/supporters.json

@@ -12,33 +12,39 @@
     "2018cfh",
     "W+K+White",
     "wackop",
-    "Takkan",
+    "Phil",
     "Carl G.",
+    "Arlecchino Shion",
+    "stone9k",
     "$MetaSamsara",
     "itismyelement",
+    "Gingko Biloba",
     "onesecondinosaur",
-    "stone9k",
+    "Takkan",
+    "Charles Blakemore",
+    "Rob Williams",
     "Rosenthal",
     "Francisco Tatis",
+    "Tobi_Swagg",
     "Andrew Wilson",
     "Greybush",
-    "Gooohokrbe",
     "Ricky Carter",
     "JongWon Han",
-    "OldBones",
     "VantAI",
     "runte3221",
+    "Illrigger",
     "FreelancerZ",
     "Edgar Tejeda",
+    "Jorge Hussni",
     "Liam MacDougal",
     "Fraser Cross",
     "Polymorphic Indeterminate",
-    "Birdy",
     "Marc Whiffen",
-    "Jorge Hussni",
-    "Kiba",
+    "Birdy",
     "Skalabananen",
+    "Kiba",
     "Reno Lam",
+    "Mozzel",
     "sig",
     "Christian Byrne",
     "DM",
@@ -46,39 +52,41 @@
     "Estragon",
     "J\\B/ 8r0wns0n",
     "Snaggwort",
-    "Arlecchino Shion",
-    "Charles Blakemore",
-    "Rob Williams",
     "ClockDaemon",
+    "Jonathan Ross",
     "KD",
     "Omnidex",
+    "Nazono_hito",
     "Tyler Trebuchon",
     "Release Cabrakan",
-    "Tobi_Swagg",
+    "contrite831",
     "SG",
     "carozzz",
     "James Dooley",
     "zenbound",
     "Buzzard",
     "jmack",
+    "Adam Shaw",
     "Mark Corneglio",
     "SarcasticHashtag",
-    "Cosmosis",
+    "Anthony Rizzo",
     "iamresist",
+    "Gooohokrbe",
     "RedrockVP",
     "Wolffen",
-    "FloPro4Sho",
     "James Todd",
+    "OldBones",
     "Steven Pfeiffer",
     "Tim",
+    "Timmy",
+    "Johnny",
     "Lisster",
     "Michael Wong",
-    "Illrigger",
+    "whudunit",
     "Tom Corrigan",
+    "dl0901dm",
     "JackieWang",
     "fnkylove",
-    "Julian V",
-    "Steven Owens",
     "Yushio",
     "Vik71it",
     "Echo",
@@ -86,147 +94,137 @@
     "Robert Stacey",
     "PM",
     "Todd Keck",
-    "Mozzel",
-    "Gingko Biloba",
-    "Sterilized",
+    "Briton Heilbrun",
+    "Aleksander Wujczyk",
     "BadassArabianMofo",
+    "Sterilized",
     "Pascal Dahle",
     "quarz",
-    "Greg",
     "Penfore",
+    "Greg",
     "JSST",
-    "esthe",
     "lmsupporter",
-    "IamAyam",
+    "zounic",
     "wfpearl",
     "Baekdoosixt",
-    "Jonathan Ross",
     "Jack B Nimble",
-    "Nazono_hito",
     "Melville Parrish",
     "daniel dove",
     "Lustre",
     "JW Sin",
-    "contrite831",
     "Alex",
     "bh",
-    "confiscated Zyra",
     "Marlon Daniels",
     "Starkselle",
     "Aaron Bleuer",
     "LacesOut!",
     "greebles",
-    "Adam Shaw",
-    "Tee Gee",
-    "Anthony Rizzo",
-    "tarek helmi",
+    "Cosmosis",
     "M Postkasse",
+    "FloPro4Sho",
     "ASLPro3D",
     "Jacob Hoehler",
     "FinalyFree",
     "Weasyl",
-    "Timmy",
-    "Johnny",
+    "Lex Song",
     "Cory Paza",
     "Tak",
     "Gonzalo Andre Allendes Lopez",
     "Zach Gonser",
     "Big Red",
-    "whudunit",
+    "Jimmy Ledbetter",
     "Luc Job",
-    "dl0901dm",
     "Philip Hempel",
     "corde",
     "Nick Walker",
-    "lh qwe",
+    "Julian V",
+    "Steven Owens",
     "Bishoujoker",
-    "conner",
     "aai",
-    "Briton Heilbrun",
     "Tori",
     "wildnut",
-    "Princess Bright Eyes",
-    "AbstractAss",
-    "Felipe dos Santos",
-    "ViperC",
     "jean jahren",
-    "Aleksander Wujczyk",
     "AM Kuro",
-    "Markus",
-    "S Sang",
+    "ViperC",
+    "Ran C",
+    "Sangheili460",
+    "MagnaInsomnia",
     "Karl P.",
     "Akira_HentAI",
-    "MagnaInsomnia",
     "Gordon Cole",
     "yuxz69",
-    "Douglas Gaspar",
-    "AlexDuKaNa",
-    "George",
+    "esthe",
     "andrew.tappan",
-    "dw",
     "N/A",
     "The Spawn",
-    "Phil",
     "graysock",
+    "Pozadine1",
     "Greenmoustache",
-    "zounic",
     "fancypants",
+    "IamAyam",
+    "Eldithor",
+    "Joboshy",
     "Digital",
     "JaxMax",
     "takyamtom",
-    "奚明 刘",
+    "Bohemian Corporal",
+    "Dan",
+    "confiscated Zyra",
     "Jwk0205",
     "Bro Xie",
-    "준희 김",
+    "yer fey",
     "batblue",
     "carey6409",
     "Olive",
     "太郎 ゲーム",
+    "Tee Gee",
     "Some Guy Named Barry",
+    "jinxedx",
+    "tarek helmi",
     "Max Marklund",
-    "Tomohiro Baba",
-    "David Ortega",
     "AELOX",
+    "Dankin",
     "Nicfit23",
-    "Noora",
     "wamekukyouzin",
     "drum matthieu",
     "Dogmaster",
     "Matt Wenzel",
-    "Mattssn",
-    "Lex Song",
-    "John Saveas",
+    "Frank Nitty",
+    "Pronredn",
     "Christopher Michel",
     "Serge Bekenkamp",
-    "Jimmy Ledbetter",
+    "DougPeterson",
     "LeoZero",
     "Antonio Pontes",
     "ApathyJones",
     "nahinahi9",
+    "lh qwe",
+    "Kevin John Duck",
+    "conner",
     "Dustin Chen",
     "dan",
-    "Yaboi",
+    "Blackfish95",
     "Mouthlessman",
-    "Steam Steam",
-    "Damon Cunliffe",
-    "CryptoTraderJK",
-    "Davaitamin",
+    "Princess Bright Eyes",
+    "Paul Kroll",
+    "AbstractAss",
     "otaku fra",
-    "Ran C",
-    "tedcor",
-    "Fotek Design",
+    "Felipe dos Santos",
+    "Bas Imagineer",
+    "Markus",
+    "MiraiKuriyamaSy",
     "Adam Taylor",
+    "Douglas Gaspar",
     "Weird_With_A_Beard",
-    "MadSpin",
-    "Pozadine1",
+    "AlexDuKaNa",
+    "George",
+    "dw",
     "Qarob",
     "AIGooner",
-    "inbijiburu",
     "Luc",
     "ProtonPrince",
     "DiffDuck",
     "elu3199",
-    "Nick “Loadstone” D",
     "Hasturkun",
     "Jon Sandman",
     "Ubivis",
@@ -234,54 +232,45 @@
     "thesoftwaredruid",
     "wundershark",
     "mr_dinosaur",
+    "Tyrswood",
     "linnfrey",
-    "Gamalonia",
-    "Vir",
     "Pkrsky",
-    "Joboshy",
-    "Bohemian Corporal",
-    "Dan",
+    "奚明 刘",
     "Josef Lanzl",
-    "Seth Christensen",
+    "Nerezza",
     "Griffin Dahlberg",
-    "Draven T",
-    "yer fey",
+    "준희 김",
     "Error_Rule34_Not_found",
     "Gerald Welly",
     "Roslynd",
     "Geolog",
-    "jinxedx",
     "Neco28",
-    "Aquatic Coffee",
-    "Dankin",
-    "ethanfel",
+    "Tomohiro Baba",
+    "David Ortega",
+    "Noora",
     "Cristian Vazquez",
-    "Frank Nitty",
+    "Mattssn",
     "Magic Noob",
-    "Focuschannel",
-    "DougPeterson",
     "Jeff",
     "Bruce",
-    "Kevin John Duck",
-    "Anthony Faxlandez",
     "Kevin Christopher",
     "Ouro Boros",
-    "Blackfish95",
+    "Chad Idk",
+    "Yaboi",
     "dd",
-    "Paul Kroll",
-    "MiraiKuriyamaSy",
-    "semicolon drainpipe",
-    "Thesharingbrother",
-    "Bas Imagineer",
-    "Pat Hen",
+    "Steam Steam",
+    "CryptoTraderJK",
+    "Davaitamin",
+    "Dušan Ryban",
+    "tedcor",
+    "Fotek Design",
+    "sjon kreutz",
     "John Statham",
-    "ResidentDeviant",
-    "Nihongasuki",
-    "JC",
-    "Prompt Pirate",
-    "uwutismxd",
+    "MadSpin",
+    "Metryman55",
+    "inbijiburu",
     "decoy",
-    "Tyrswood",
+    "Nick “Loadstone” D",
     "Ray Wing",
     "Ranzitho",
     "Gus",
@@ -290,6 +279,7 @@
     "David LaVallee",
     "ae",
     "Tr4shP4nda",
+    "Gamalonia",
     "WRL_SPR",
     "capn",
     "Joseph",
@@ -302,77 +292,60 @@
     "Moon Knight",
     "몽타주",
     "Kland",
-    "zenobeus",
-    "Jackthemind",
-    "ryoma",
-    "Stryker",
-    "raf8osz",
-    "ElitaSSJ4",
-    "blikkies",
-    "Chris",
+    "Hailshem",
+    "kudari",
+    "Naomi Hale Danchi",
+    "dc7431",
+    "Vir",
     "Brian M",
-    "Nerezza",
     "sanborondon",
+    "Seth Christensen",
+    "Draven T",
     "Taylor Funk",
     "aezin",
     "Thought2Form",
     "jcay015",
     "Kevin Picco",
     "Erik Lopez",
-    "Shock Shockor",
     "Mateo Curić",
-    "Goldwaters",
-    "Zude",
+    "Aquatic Coffee",
     "Eris3D",
     "m",
+    "ethanfel",
     "Pierce McBride",
     "Joshua Gray",
-    "Kyler",
+    "Focuschannel",
     "Mikko Hemilä",
-    "aRtFuL_DodGeR",
     "Jamie Ogletree",
     "a _",
     "James Coleman",
-    "CrimsonDX",
     "Martial",
+    "Anthony Faxlandez",
     "battu",
     "Emil Andersson",
-    "Chad Idk",
-    "DarkSunset",
-    "Billy Gladky",
     "Yuji Kaneko",
-    "Probis",
-    "Dušan Ryban",
-    "ItsGeneralButtNaked",
+    "Pat Hen",
+    "semicolon drainpipe",
     "Jordan Shaw",
     "Rops Alot",
+    "Thesharingbrother",
     "Sam",
-    "sjon kreutz",
-    "Nimess",
-    "SRDB",
     "Ace Ventura",
-    "g unit",
-    "Youguang",
-    "Metryman55",
-    "andrewzpong",
-    "FrxzenSnxw",
-    "BossGame",
-    "lrdchs",
+    "ResidentDeviant",
+    "Nihongasuki",
+    "JC",
+    "Prompt Pirate",
+    "uwutismxd",
     "momokai",
-    "Hailshem",
-    "kudari",
-    "Naomi Hale Danchi",
-    "dc7431",
+    "zenobeus",
     "ken",
-    "Inversity",
-    "AIVORY3D",
     "epicgamer0020690",
     "Joshua Porrata",
     "keemun",
     "SuBu",
     "RedPIXel",
-    "Kevinj",
     "Wind",
+    "Jackthemind",
     "Nexus",
     "Ramneek“Guy”Ashok",
     "squid_actually",
@@ -385,80 +358,81 @@
     "emyth",
     "chriphost",
     "KitKatM",
+    "ryoma",
     "socrasteeze",
-    "ResidentDeviant",
+    "OrganicArtifact",
+    "Stryker",
+    "MudkipMedkitz",
     "gzmzmvp",
-    "Welkor",
-    "John Martin",
+    "raf8osz",
+    "ElitaSSJ4",
     "Richard",
+    "blikkies",
     "Andrew",
+    "Chris",
     "Robert Wegemund",
     "Littlehuggy",
-    "moranqianlong",
     "Gregory Kozhemiak",
     "mrjuan",
     "Brian Buie",
+    "Shock Shockor",
     "Sadlip",
-    "Haru Yotu",
+    "Goldwaters",
     "Eric Whitney",
     "Joey Callahan",
+    "Zude",
     "Ivan Tadic",
     "Mike Simone",
+    "John J Linehan",
+    "Kyler",
+    "Elliot E",
     "Morgandel",
-    "Kyron Mahan",
-    "Matura Arbeit",
+    "Theerat Jiramate",
+    "aRtFuL_DodGeR",
     "Noah",
     "Jacob McDaniel",
     "X",
     "Sloan Steddy",
-    "TBitz33",
-    "Anonym dkjglfleeoeldldldlkf",
     "Temikus",
     "Artokun",
     "Michael Taylor",
-    "SendingRavens",
     "Derek Baker",
+    "CrimsonDX",
     "Michael Anthony Scott",
+    "DarkSunset",
     "Atilla Berke Pekduyar",
-    "Michael Docherty",
     "Nathan",
+    "Billy Gladky",
+    "NICHOLAS BAXLEY",
     "Decx _",
-    "Paul Hartsuyker",
-    "elitassj",
-    "Jacob Winter",
+    "Probis",
+    "Ed Wang",
+    "ItsGeneralButtNaked",
+    "Nimess",
+    "SRDB",
+    "g unit",
     "Distortik",
-    "David",
-    "Meilo",
-    "Pen Bouryoung",
+    "Youguang",
     "四糸凜音",
-    "shinonomeiro",
-    "Snille",
-    "MaartenAlbers",
-    "khanh duy",
-    "xybrightsummer",
-    "jreedatchison",
-    "PhilW",
+    "Saya",
+    "andrewzpong",
+    "FrxzenSnxw",
+    "BossGame",
+    "lrdchs",
     "Tree Tagger",
-    "Janik",
+    "Inversity",
     "Crocket",
-    "Cruel",
-    "MRBlack",
+    "AIVORY3D",
+    "Kevinj",
     "Mitchell Robson",
-    "Kiyoe",
-    "humptynutz",
-    "michael.isaza",
-    "Kalnei",
     "Whitepinetrader",
-    "OrganicArtifact",
-    "Scott",
-    "MudkipMedkitz",
+    "ResidentDeviant",
     "deanbrian",
     "POPPIN",
     "Alex Wortman",
     "Cody",
     "Raku",
     "smart.edge5178",
-    "emadsultan",
     "InformedViewz",
     "CHKeeho80",
     "Bubbafett",
@@ -466,76 +440,152 @@
     "Menard",
     "Skyfire83",
     "Adam Rinehart",
-    "D",
     "Pitpe11",
     "TheD1rtyD03",
     "moonpetal",
     "SomeDude",
     "g9p0o",
-    "nanana",
     "TheHolySheep",
     "Monte Won",
     "SpringBootisTrash",
     "carsten",
     "ikok",
+    "Nathen+Choi",
+    "T",
+    "LarsesFPC",
+    "cocona",
+    "sfasdfasfdsa",
     "Buecyb99",
-    "4IXplr0r3r",
-    "dfklsjfkljslfjd",
-    "hayden",
-    "ahoystan",
-    "Leland Saunders",
+    "Welkor",
+    "David Schenck",
+    "John Martin",
     "Wolfe7D1",
     "Ink Temptation",
-    "Bob Barker",
-    "edk",
+    "moranqianlong",
     "Kalli Core",
-    "Aeternyx",
     "elleshar666",
-    "YOU SINWOO",
-    "ja s",
-    "Doug Mason",
+    "ACTUALLY_the_Real_Willem_Dafoe",
+    "Haru Yotu",
     "Kauffy",
-    "Jeremy Townsend",
     "EpicElric",
-    "Sean voets",
-    "Owen Gwosdz",
-    "John J Linehan",
-    "Elliot E",
-    "Thomas Wanner",
-    "Theerat Jiramate",
+    "Kyron Mahan",
     "Edward Kennedy",
     "Justin Blaylock",
-    "Devil Lude",
+    "Matura Arbeit",
     "Nick Kage",
-    "kevin stoddard",
-    "Jack Dole",
+    "TBitz33",
+    "Anonym dkjglfleeoeldldldlkf",
     "Vane Holzer",
     "psytrax",
+    "Cyrus Fett",
     "Ezokewn",
+    "SendingRavens",
     "hexxish",
-    "CptNeo",
     "notedfakes",
-    "Maso",
-    "Eric Ketchum",
-    "NICHOLAS BAXLEY",
+    "Michael Docherty",
     "Michael Scott",
-    "Kevin Wallace",
-    "Matheus Couto",
-    "Saya",
-    "ChicRic",
-    "mercur",
-    "J C",
-    "Ed Wang",
+    "Paul Hartsuyker",
+    "elitassj",
+    "Jacob Winter",
     "Ryan Presley Ng",
     "Wes Sims",
     "Donor4115",
+    "Lyavph",
+    "David",
+    "Meilo",
+    "Filippo Ferrari",
+    "Pen Bouryoung",
+    "shinonomeiro",
+    "Snille",
+    "MaartenAlbers",
+    "khanh duy",
+    "xybrightsummer",
+    "jreedatchison",
+    "PhilW",
+    "Janik",
+    "Cruel",
+    "MRBlack",
+    "Kiyoe",
+    "humptynutz",
+    "michael.isaza",
+    "Kalnei",
+    "Scott",
+    "Muratoraccio",
+    "Ginnie",
+    "emadsultan",
+    "D",
+    "nanana",
+    "Fthehappy",
+    "rsamerica",
+    "Alan+Cano",
+    "FeralOpticsAI",
+    "Pavlaki",
+    "generic404",
+    "Doug+Rintoul",
+    "Noor",
+    "Yorunai",
+    "quantenmecha",
+    "abattoirblues",
+    "Jason+Nash",
+    "BillyBoy84",
+    "zounik",
+    "DarkRoast",
+    "letzte",
+    "Nasty+Hobbit",
+    "Sora+Yori",
+    "lrdchs2",
+    "Duk3+Rand0m",
+    "4IXplr0r3r",
+    "hayden",
+    "ahoystan",
+    "Leland Saunders",
+    "Bob Barker",
+    "edk",
+    "JBsuede",
+    "Time Valentine",
+    "Aeternyx",
+    "YOU SINWOO",
+    "りん あめ",
+    "ja s",
+    "Михал Михалыч",
+    "Matt",
+    "Doug Mason",
+    "Jeremy Townsend",
+    "Frogmilk",
+    "Sean voets",
+    "Owen Gwosdz",
+    "SPJ",
+    "Thomas Wanner",
+    "Bryan Rutkowski",
+    "Devil Lude",
+    "David Murcko",
+    "kevin stoddard",
+    "Jack Dole",
+    "max blo",
+    "Xenon Xue",
+    "CptNeo",
+    "JackJohnnyJim",
+    "Dmitry Ryzhov",
+    "Maso",
+    "Edward Ten Eyck",
+    "Eric Ketchum",
+    "Kevin Wallace",
+    "Matheus Couto",
+    "ChicRic",
+    "Henrique Faiolli",
+    "mercur",
+    "Solixer",
+    "J C",
+    "jinksta187",
+    "Andrew Wilkinson",
+    "Manu Thetug",
+    "Karlanx",
     "Yves Poezevara",
+    "operationancut",
     "Teriak47",
     "Just me",
     "Raf Stahelin",
     "Вячеслав Маринин",
-    "Lyavph",
-    "Filippo Ferrari",
     "Cola Matthew",
     "OniNoKen",
     "Iain Wisely",
@@ -576,98 +626,121 @@
     "dg",
     "Maarten Harms",
     "Israel",
-    "Muratoraccio",
     "SelfishMedic",
-    "Ginnie",
     "adderleighn",
     "EnragedAntelope",
-    "Alan+Cano",
-    "FeralOpticsAI",
-    "Pavlaki",
-    "generic404",
+    "lighthawke",
+    "Terraformer",
+    "GDS+DEV",
+    "4rt+r3d",
+    "low9",
+    "Winged",
+    "you+halo9",
+    "YassineKhaled",
+    "YK12",
+    "MatteKey",
+    "Flob",
+    "ShiroSenpai",
+    "Somebody",
+    "Inkognito",
+    "Somebody",
+    "Gramer+Gumbyte",
+    "Crescent~San",
+    "Tan+Huynh",
+    "AiGirlTS",
+    "D",
+    "datasl4ve",
+    "Somebody",
+    "Dark_Pest",
+    "Aza",
+    "Jacky+Ho",
+    "koopa990",
+    "Karru",
+    "ChaChanoKo",
+    "null",
+    "bo",
+    "The+Forgetful+Dev",
+    "redcarrot",
+    "powerbot99",
     "Mateusz+Kosela",
-    "Doug+Rintoul",
-    "Noor",
-    "Yorunai",
     "Bula",
-    "quantenmecha",
-    "abattoirblues",
-    "Jason+Nash",
-    "BillyBoy84",
-    "DarkRoast",
-    "zounik",
-    "letzte",
-    "Nasty+Hobbit",
-    "SgtFluffles",
-    "lrdchs2",
-    "Duk3+Rand0m",
     "KUJYAKU",
-    "NathenChoi",
-    "Thomas+Reck",
-    "Larses",
-    "cocona",
     "Coeur+de+cochon",
-    "David Schenck",
     "han b",
     "Nico",
     "Banana Joe",
     "_ G3n",
     "Donovan Jenkins",
-    "JBsuede",
+    "Tú Nguyễn Lý Hoàng",
     "Michael Eid",
     "beersandbacon",
     "Maximilian Pyko",
     "Invis",
-    "Justin Houston",
-    "Time Valentine",
+    "Bob barker",
+    "Ben D",
+    "Garrett Wood",
+    "Ronan Delevacq",
     "james",
+    "Christian Schäfer",
     "OrochiNights",
     "Michael Zhu",
-    "ACTUALLY_the_Real_Willem_Dafoe",
     "gonzalo",
     "Seraphy",
-    "Михал Михалыч",
     "雨の心 落",
-    "Matt",
     "AllTimeNoobie",
     "jumpd",
     "John C",
     "Rim",
+    "Dave Abraham",
+    "Joaquin Hierrezuelo",
     "Dismem",
-    "Frogmilk",
-    "SPJ",
+    "Locrospiel",
+    "Jairus Knudsen",
+    "Jarrid Lee",
     "Xan Dionysus",
     "Nathan lee",
+    "Kor",
+    "Joseph Hanson",
     "Mewtora",
     "Middo",
     "Forbidden Atelier",
-    "Bryan Rutkowski",
+    "John Rednoulf",
+    "Spire",
     "Adictedtohumping",
+    "Boba Smith",
     "Towelie",
-    "Cyrus Fett",
+    "MR.Bear",
+    "dsffsdfsdfsdfsdfsdf",
     "Jean-françois SEMA",
     "Kurt",
-    "max blo",
-    "Xenon Xue",
-    "JackJohnnyJim",
-    "Edward Ten Eyck",
+    "ivistorm",
+    "Sauv",
+    "Steven",
+    "TenaciousD",
+    "Khánh Đặng",
     "Chase Kwon",
+    "Ted Cart",
     "Inyoshu",
     "Goober719",
     "Chad Barnes",
+    "Person Y",
+    "David Spearing",
     "James Ming",
     "vanditking",
     "kripitonga",
     "Rizzi",
     "nimin",
     "OMAR LUCIANO",
+    "Ken+Suzuki",
     "hannibal",
     "Jo+Example",
     "BrentBertram",
+    "Tigon",
     "eumelzocker",
     "dxjaymz",
     "L C",
-    "Dude"
+    "Dude",
+    "CK"
   ],
-  "totalCount": 666
+  "totalCount": 739
 }

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 +15,8 @@
             "settings": "Einstellungen",
             "help": "Hilfe",
             "add": "Hinzufügen",
-            "close": "Schließen"
+            "close": "Schließen",
+            "menu": "Menü"
         },
         "status": {
             "loading": "Wird geladen...",
@@ -175,6 +176,9 @@
             "success": "{count} Rezepte erfolgreich repariert.",
             "cancelled": "Reparatur abgebrochen. {count} Rezepte wurden repariert.",
             "error": "Recipe-Reparatur fehlgeschlagen: {message}"
+        },
+        "manageExcludedModels": {
+            "label": "Ausgeschlossene Modelle verwalten"
         }
     },
     "header": {
@@ -222,12 +226,14 @@
             "presetOverwriteConfirm": "Voreinstellung \"{name}\" existiert bereits. Überschreiben?",
             "presetNamePlaceholder": "Voreinstellungsname...",
             "baseModel": "Basis-Modell",
+            "baseModelSearchPlaceholder": "Basismodelle durchsuchen...",
             "modelTags": "Tags (Top 20)",
             "modelTypes": "Modelltypen",
             "license": "Lizenz",
             "noCreditRequired": "Kein Credit erforderlich",
             "allowSellingGeneratedContent": "Verkauf erlaubt",
             "noTags": "Keine Tags",
+            "noBaseModelMatches": "Keine Basismodelle entsprechen der aktuellen Suche.",
             "clearAll": "Alle Filter löschen",
             "any": "Beliebig",
             "all": "Alle",
@@ -250,6 +256,33 @@
         "civitaiApiKey": "Civitai API Key",
         "civitaiApiKeyPlaceholder": "Geben Sie Ihren Civitai API Key ein",
         "civitaiApiKeyHelp": "Wird für die Authentifizierung beim Herunterladen von Modellen von Civitai verwendet",
+        "civitaiHost": {
+            "label": "Civitai-Host",
+            "help": "Wählen Sie aus, welche Civitai-Seite geöffnet wird, wenn Sie „View on Civitai“-Links verwenden.",
+            "options": {
+                "com": "civitai.com (nur SFW)",
+                "red": "civitai.red (uneingeschränkt)"
+            }
+        },
+        "downloadBackend": {
+            "label": "Download-Backend",
+            "help": "Wähle aus, wie Modelldateien heruntergeladen werden. Python verwendet den eingebauten Downloader. aria2 verwendet den experimentellen externen Downloader-Prozess.",
+            "options": {
+                "python": "Python (integriert)",
+                "aria2": "aria2 (experimentell)"
+            }
+        },
+        "aria2cPath": {
+            "label": "aria2c-Pfad",
+            "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.",
+            "openSettings": "Einstellungen öffnen"
+        },
         "openSettingsFileLocation": {
             "label": "Einstellungsordner öffnen",
             "tooltip": "Den Ordner mit der settings.json öffnen",
@@ -260,6 +293,7 @@
         },
         "sections": {
             "contentFiltering": "Inhaltsfilterung",
+            "downloads": "Downloads",
             "videoSettings": "Video-Einstellungen",
             "layoutSettings": "Layout-Einstellungen",
             "misc": "Verschiedenes",
@@ -395,6 +429,8 @@
                 "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",
@@ -506,6 +542,21 @@
             "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",
@@ -636,7 +687,10 @@
             "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",
             "clear": "Auswahl löschen",
             "skipMetadataRefreshCount": "Überspringen（{count} Modelle）",
@@ -667,6 +721,7 @@
             "moveToFolder": "In Ordner verschieben",
             "repairMetadata": "Metadaten reparieren",
             "excludeModel": "Modell ausschließen",
+            "restoreModel": "Modell wiederherstellen",
             "deleteModel": "Modell löschen",
             "shareRecipe": "Rezept teilen",
             "viewAllLoras": "Alle LoRAs anzeigen",
@@ -957,6 +1012,8 @@
             "earlyAccess": "Early Access",
             "earlyAccessTooltip": "Early Access erforderlich",
             "inLibrary": "In Bibliothek",
+            "downloaded": "Heruntergeladen",
+            "downloadedTooltip": "Zuvor heruntergeladen, aber derzeit nicht in Ihrer Bibliothek.",
             "alreadyInLibrary": "Bereits in Bibliothek",
             "autoOrganizedPath": "[Automatisch organisiert durch Pfadvorlage]",
             "errors": {
@@ -1155,6 +1212,8 @@
                 "cancel": "Bearbeitung abbrechen",
                 "save": "Änderungen speichern",
                 "addPlaceholder": "Tippen zum Hinzufügen oder klicken Sie auf Vorschläge unten",
+                "editWord": "Trigger Word bearbeiten",
+                "editPlaceholder": "Trigger Word bearbeiten",
                 "copyWord": "Trigger Word kopieren",
                 "deleteWord": "Trigger Word löschen",
                 "suggestions": {
@@ -1226,17 +1285,33 @@
                     "days": "in {count}d"
                 },
                 "badges": {
-                    "current": "Aktuelle Version",
+                    "current": "Geöffnete Version",
+                    "currentTooltip": "Das ist die Version, mit der dieses Modal geöffnet wurde",
                     "inLibrary": "In der Bibliothek",
+                    "inLibraryTooltip": "Diese Version befindet sich in Ihrer lokalen Bibliothek",
+                    "downloaded": "Heruntergeladen",
+                    "downloadedTooltip": "Diese Version wurde bereits heruntergeladen, befindet sich aber derzeit nicht in Ihrer Bibliothek",
                     "newer": "Neuere Version",
+                    "newerTooltip": "Diese Version ist neuer als Ihre neueste lokale Version",
                     "earlyAccess": "Früher Zugriff",
-                    "ignored": "Ignoriert"
+                    "earlyAccessTooltip": "Für diese Version ist derzeit Civitai Early Access erforderlich",
+                    "ignored": "Ignoriert",
+                    "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",
                     "unignore": "Ignorierung aufheben",
+                    "ignoreTooltip": "Update-Benachrichtigungen für diese Version ignorieren",
+                    "unignoreTooltip": "Update-Benachrichtigungen für diese Version fortsetzen",
+                    "viewVersionOnCivitai": "Version auf Civitai anzeigen",
                     "earlyAccessTooltip": "Erfordert Early-Access-Kauf",
                     "resumeModelUpdates": "Aktualisierungen für dieses Modell fortsetzen",
                     "ignoreModelUpdates": "Aktualisierungen für dieses Modell ignorieren",
@@ -1392,6 +1467,10 @@
             "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.",
@@ -1623,6 +1702,11 @@
             "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",
@@ -1713,8 +1797,8 @@
         },
         "triggerWords": {
             "loadFailed": "Konnte trainierte Wörter nicht laden",
-            "tooLong": "Trigger Word sollte 100 Wörter nicht überschreiten",
-            "tooMany": "Maximal 30 Trigger Words erlaubt",
+            "tooLong": "Trigger Word sollte 500 Wörter nicht überschreiten",
+            "tooMany": "Maximal 100 Trigger Words erlaubt",
             "alreadyExists": "Dieses Trigger Word existiert bereits",
             "updateSuccess": "Trigger Words erfolgreich aktualisiert",
             "updateFailed": "Fehler beim Aktualisieren der Trigger Words",
@@ -1775,6 +1859,8 @@
             "deleteFailed": "Fehler beim Löschen von {type}: {message}",
             "excludeSuccess": "{type} erfolgreich ausgeschlossen",
             "excludeFailed": "Fehler beim Ausschließen von {type}: {message}",
+            "restoreSuccess": "{type} erfolgreich wiederhergestellt",
+            "restoreFailed": "{type} konnte nicht wiederhergestellt werden: {message}",
             "fileNameUpdated": "Dateiname erfolgreich aktualisiert",
             "fileRenameFailed": "Fehler beim Umbenennen der Datei: {error}",
             "previewUpdated": "Vorschau erfolgreich aktualisiert",
@@ -1832,7 +1918,9 @@
             "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}"
         }
     },
     "banners": {

locales/en.json

@@ -15,7 +15,8 @@
             "settings": "Settings",
             "help": "Help",
             "add": "Add",
-            "close": "Close"
+            "close": "Close",
+            "menu": "Menu"
         },
         "status": {
             "loading": "Loading...",
@@ -175,6 +176,9 @@
             "success": "Successfully repaired {count} recipes.",
             "cancelled": "Repair cancelled. {count} recipes were repaired.",
             "error": "Recipe repair failed: {message}"
+        },
+        "manageExcludedModels": {
+            "label": "Manage Excluded Models"
         }
     },
     "header": {
@@ -222,12 +226,14 @@
             "presetOverwriteConfirm": "Preset \"{name}\" already exists. Overwrite?",
             "presetNamePlaceholder": "Preset name...",
             "baseModel": "Base Model",
+            "baseModelSearchPlaceholder": "Search base models...",
             "modelTags": "Tags (Top 20)",
             "modelTypes": "Model Types",
             "license": "License",
             "noCreditRequired": "No Credit Required",
             "allowSellingGeneratedContent": "Allow Selling",
             "noTags": "No tags",
+            "noBaseModelMatches": "No base models match the current search.",
             "clearAll": "Clear All Filters",
             "any": "Any",
             "all": "All",
@@ -250,6 +256,33 @@
         "civitaiApiKey": "Civitai API Key",
         "civitaiApiKeyPlaceholder": "Enter your Civitai API key",
         "civitaiApiKeyHelp": "Used for authentication when downloading models from Civitai",
+        "civitaiHost": {
+            "label": "Civitai host",
+            "help": "Choose which Civitai site opens when using View on Civitai links.",
+            "options": {
+                "com": "civitai.com (SFW)",
+                "red": "civitai.red (unrestricted)"
+            }
+        },
+        "downloadBackend": {
+            "label": "Download backend",
+            "help": "Choose how model files are downloaded. Python uses the built-in downloader. aria2 uses the experimental external downloader process.",
+            "options": {
+                "python": "Python (built-in)",
+                "aria2": "aria2 (experimental)"
+            }
+        },
+        "aria2cPath": {
+            "label": "aria2c path",
+            "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.",
+            "openSettings": "Open Settings"
+        },
         "openSettingsFileLocation": {
             "label": "Open settings folder",
             "tooltip": "Open folder containing settings.json",
@@ -260,6 +293,7 @@
         },
         "sections": {
             "contentFiltering": "Content Filtering",
+            "downloads": "Downloads",
             "videoSettings": "Video Settings",
             "layoutSettings": "Layout Settings",
             "misc": "Miscellaneous",
@@ -395,6 +429,8 @@
                 "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",
@@ -506,6 +542,21 @@
             "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",
@@ -636,7 +687,10 @@
             "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",
             "clear": "Clear Selection",
             "skipMetadataRefreshCount": "Skip ({count} models)",
@@ -667,6 +721,7 @@
             "moveToFolder": "Move to Folder",
             "repairMetadata": "Repair metadata",
             "excludeModel": "Exclude Model",
+            "restoreModel": "Restore Model",
             "deleteModel": "Delete Model",
             "shareRecipe": "Share Recipe",
             "viewAllLoras": "View All LoRAs",
@@ -685,9 +740,9 @@
                 "title": "Import a recipe from image or URL",
                 "urlLocalPath": "URL / Local Path",
                 "uploadImage": "Upload Image",
-                "urlSectionDescription": "Input a Civitai image URL or local file path to import as a recipe.",
+                "urlSectionDescription": "Input a Civitai image URL from civitai.com or civitai.red, or a local file path, to import as a recipe.",
                 "imageUrlOrPath": "Image URL or File Path:",
-                "urlPlaceholder": "https://civitai.com/images/... or C:/path/to/image.png",
+                "urlPlaceholder": "https://civitai.com/images/... or https://civitai.red/images/... or C:/path/to/image.png",
                 "fetchImage": "Fetch Image",
                 "uploadSectionDescription": "Upload an image with LoRA metadata to import as a recipe.",
                 "selectImage": "Select Image",
@@ -957,6 +1012,8 @@
             "earlyAccess": "Early Access",
             "earlyAccessTooltip": "Early access required",
             "inLibrary": "In Library",
+            "downloaded": "Downloaded",
+            "downloadedTooltip": "Previously downloaded, but it is not currently in your library.",
             "alreadyInLibrary": "Already in Library",
             "autoOrganizedPath": "[Auto-organized by path template]",
             "errors": {
@@ -1088,9 +1145,9 @@
             },
             "proceedText": "Only proceed if you're sure this is what you want.",
             "urlLabel": "Civitai Model URL:",
-            "urlPlaceholder": "https://civitai.com/models/649516/model-name?modelVersionId=726676",
+            "urlPlaceholder": "https://civitai.com/models/649516/model-name?modelVersionId=726676 or https://civitai.red/models/649516/model-name?modelVersionId=726676",
             "helpText": {
-                "title": "Paste any Civitai model URL. Supported formats:",
+                "title": "Paste any Civitai model URL from civitai.com or civitai.red. Supported formats:",
                 "format1": "https://civitai.com/models/649516",
                 "format2": "https://civitai.com/models/649516?modelVersionId=726676",
                 "format3": "https://civitai.com/models/649516/model-name?modelVersionId=726676",
@@ -1155,6 +1212,8 @@
                 "cancel": "Cancel editing",
                 "save": "Save changes",
                 "addPlaceholder": "Type to add or click suggestions below",
+                "editWord": "Edit trigger word",
+                "editPlaceholder": "Edit trigger word",
                 "copyWord": "Copy trigger word",
                 "deleteWord": "Delete trigger word",
                 "suggestions": {
@@ -1226,17 +1285,33 @@
                     "days": "in {count}d"
                 },
                 "badges": {
-                    "current": "Current Version",
+                    "current": "Opened Version",
+                    "currentTooltip": "This is the version you opened this modal from",
                     "inLibrary": "In Library",
+                    "inLibraryTooltip": "This version exists in your local library",
+                    "downloaded": "Downloaded",
+                    "downloadedTooltip": "This version was downloaded before, but is not currently in your library",
                     "newer": "Newer Version",
+                    "newerTooltip": "This version is newer than your latest local version",
                     "earlyAccess": "Early Access",
-                    "ignored": "Ignored"
+                    "earlyAccessTooltip": "This version currently requires Civitai early access",
+                    "ignored": "Ignored",
+                    "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",
                     "unignore": "Unignore",
+                    "ignoreTooltip": "Ignore update notifications for this version",
+                    "unignoreTooltip": "Resume update notifications for this version",
+                    "viewVersionOnCivitai": "View version on Civitai",
                     "earlyAccessTooltip": "Requires early access purchase",
                     "resumeModelUpdates": "Resume updates for this model",
                     "ignoreModelUpdates": "Ignore updates for this model",
@@ -1392,6 +1467,10 @@
             "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.",
@@ -1623,6 +1702,11 @@
             "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)",
@@ -1713,8 +1797,8 @@
         },
         "triggerWords": {
             "loadFailed": "Could not load trained words",
-            "tooLong": "Trigger word should not exceed 100 words",
-            "tooMany": "Maximum 30 trigger words allowed",
+            "tooLong": "Trigger word should not exceed 500 words",
+            "tooMany": "Maximum 100 trigger words allowed",
             "alreadyExists": "This trigger word already exists",
             "updateSuccess": "Trigger words updated successfully",
             "updateFailed": "Failed to update trigger words",
@@ -1775,6 +1859,8 @@
             "deleteFailed": "Failed to delete {type}: {message}",
             "excludeSuccess": "{type} excluded successfully",
             "excludeFailed": "Failed to exclude {type}: {message}",
+            "restoreSuccess": "{type} restored successfully",
+            "restoreFailed": "Failed to restore {type}: {message}",
             "fileNameUpdated": "File name updated successfully",
             "fileRenameFailed": "Failed to rename file: {error}",
             "previewUpdated": "Preview updated successfully",
@@ -1832,7 +1918,9 @@
             "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}"
         }
     },
     "banners": {

locales/es.json

@@ -15,7 +15,8 @@
             "settings": "Configuración",
             "help": "Ayuda",
             "add": "Añadir",
-            "close": "Cerrar"
+            "close": "Cerrar",
+            "menu": "Menú"
         },
         "status": {
             "loading": "Cargando...",
@@ -175,6 +176,9 @@
             "success": "Se repararon con éxito {count} recetas.",
             "cancelled": "Reparación cancelada. {count} recetas fueron reparadas.",
             "error": "Error al reparar recetas: {message}"
+        },
+        "manageExcludedModels": {
+            "label": "Gestionar modelos excluidos"
         }
     },
     "header": {
@@ -222,12 +226,14 @@
             "presetOverwriteConfirm": "El preset \"{name}\" ya existe. ¿Sobrescribir?",
             "presetNamePlaceholder": "Nombre del preajuste...",
             "baseModel": "Modelo base",
+            "baseModelSearchPlaceholder": "Buscar modelos base...",
             "modelTags": "Etiquetas (Top 20)",
             "modelTypes": "Tipos de modelos",
             "license": "Licencia",
             "noCreditRequired": "Sin crédito requerido",
             "allowSellingGeneratedContent": "Venta permitida",
             "noTags": "Sin etiquetas",
+            "noBaseModelMatches": "Ningún modelo base coincide con la búsqueda actual.",
             "clearAll": "Limpiar todos los filtros",
             "any": "Cualquiera",
             "all": "Todos",
@@ -250,6 +256,33 @@
         "civitaiApiKey": "Clave API de Civitai",
         "civitaiApiKeyPlaceholder": "Introduce tu clave API de Civitai",
         "civitaiApiKeyHelp": "Utilizada para autenticación al descargar modelos de Civitai",
+        "civitaiHost": {
+            "label": "Host de Civitai",
+            "help": "Elige qué sitio de Civitai se abre al usar los enlaces de \"View on Civitai\".",
+            "options": {
+                "com": "civitai.com (solo SFW)",
+                "red": "civitai.red (sin restricciones)"
+            }
+        },
+        "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.",
+            "options": {
+                "python": "Python (integrado)",
+                "aria2": "aria2 (experimental)"
+            }
+        },
+        "aria2cPath": {
+            "label": "Ruta de aria2c",
+            "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.",
+            "openSettings": "Abrir ajustes"
+        },
         "openSettingsFileLocation": {
             "label": "Abrir carpeta de ajustes",
             "tooltip": "Abrir la carpeta que contiene settings.json",
@@ -260,6 +293,7 @@
         },
         "sections": {
             "contentFiltering": "Filtrado de contenido",
+            "downloads": "Descargas",
             "videoSettings": "Configuración de video",
             "layoutSettings": "Configuración de diseño",
             "misc": "Varios",
@@ -395,6 +429,8 @@
                 "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",
@@ -506,6 +542,21 @@
             "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",
@@ -636,7 +687,10 @@
             "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",
             "clear": "Limpiar selección",
             "skipMetadataRefreshCount": "Omitir（{count} modelos）",
@@ -667,6 +721,7 @@
             "moveToFolder": "Mover a carpeta",
             "repairMetadata": "Reparar metadatos",
             "excludeModel": "Excluir modelo",
+            "restoreModel": "Restaurar modelo",
             "deleteModel": "Eliminar modelo",
             "shareRecipe": "Compartir receta",
             "viewAllLoras": "Ver todos los LoRAs",
@@ -957,6 +1012,8 @@
             "earlyAccess": "Acceso temprano",
             "earlyAccessTooltip": "Acceso temprano requerido",
             "inLibrary": "En la biblioteca",
+            "downloaded": "Descargado",
+            "downloadedTooltip": "Descargado anteriormente, pero actualmente no está en tu biblioteca.",
             "alreadyInLibrary": "Ya en la biblioteca",
             "autoOrganizedPath": "[Auto-organizado por plantilla de ruta]",
             "errors": {
@@ -1155,6 +1212,8 @@
                 "cancel": "Cancelar edición",
                 "save": "Guardar cambios",
                 "addPlaceholder": "Escribe para añadir o haz clic en sugerencias de abajo",
+                "editWord": "Editar palabra de activación",
+                "editPlaceholder": "Editar palabra de activación",
                 "copyWord": "Copiar palabra clave",
                 "deleteWord": "Eliminar palabra clave",
                 "suggestions": {
@@ -1226,17 +1285,33 @@
                     "days": "en {count}d"
                 },
                 "badges": {
-                    "current": "Versión actual",
+                    "current": "Versión abierta",
+                    "currentTooltip": "Es la versión con la que abriste este modal",
                     "inLibrary": "En la biblioteca",
+                    "inLibraryTooltip": "Esta versión existe en tu biblioteca local",
+                    "downloaded": "Descargado",
+                    "downloadedTooltip": "Esta versión se descargó antes, pero ahora no está en tu biblioteca",
                     "newer": "Versión más reciente",
+                    "newerTooltip": "Esta versión es más reciente que tu última versión local",
                     "earlyAccess": "Acceso temprano",
-                    "ignored": "Ignorada"
+                    "earlyAccessTooltip": "Esta versión requiere actualmente acceso temprano de Civitai",
+                    "ignored": "Ignorada",
+                    "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",
                     "unignore": "Dejar de ignorar",
+                    "ignoreTooltip": "Ignorar las notificaciones de actualización de esta versión",
+                    "unignoreTooltip": "Reanudar las notificaciones de actualización de esta versión",
+                    "viewVersionOnCivitai": "Ver versión en Civitai",
                     "earlyAccessTooltip": "Requiere compra de acceso temprano",
                     "resumeModelUpdates": "Reanudar actualizaciones para este modelo",
                     "ignoreModelUpdates": "Ignorar actualizaciones para este modelo",
@@ -1392,6 +1467,10 @@
             "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.",
@@ -1623,6 +1702,11 @@
             "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",
@@ -1713,8 +1797,8 @@
         },
         "triggerWords": {
             "loadFailed": "No se pudieron cargar palabras entrenadas",
-            "tooLong": "La palabra clave no debe exceder 100 palabras",
-            "tooMany": "Máximo 30 palabras clave permitidas",
+            "tooLong": "La palabra clave no debe exceder 500 palabras",
+            "tooMany": "Máximo 100 palabras clave permitidas",
             "alreadyExists": "Esta palabra clave ya existe",
             "updateSuccess": "Palabras clave actualizadas exitosamente",
             "updateFailed": "Error al actualizar palabras clave",
@@ -1775,6 +1859,8 @@
             "deleteFailed": "Error al eliminar {type}: {message}",
             "excludeSuccess": "{type} excluido exitosamente",
             "excludeFailed": "Error al excluir {type}: {message}",
+            "restoreSuccess": "{type} restaurado correctamente",
+            "restoreFailed": "No se pudo restaurar {type}: {message}",
             "fileNameUpdated": "Nombre de archivo actualizado exitosamente",
             "fileRenameFailed": "Error al renombrar archivo: {error}",
             "previewUpdated": "Vista previa actualizada exitosamente",
@@ -1832,7 +1918,9 @@
             "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}"
         }
     },
     "banners": {

locales/fr.json

@@ -15,7 +15,8 @@
             "settings": "Paramètres",
             "help": "Aide",
             "add": "Ajouter",
-            "close": "Fermer"
+            "close": "Fermer",
+            "menu": "Menu"
         },
         "status": {
             "loading": "Chargement...",
@@ -175,6 +176,9 @@
             "success": "{count} recettes réparées avec succès.",
             "cancelled": "Réparation annulée. {count} recettes ont été réparées.",
             "error": "Échec de la réparation des recettes : {message}"
+        },
+        "manageExcludedModels": {
+            "label": "Gérer les modèles exclus"
         }
     },
     "header": {
@@ -222,12 +226,14 @@
             "presetOverwriteConfirm": "Le préréglage \"{name}\" existe déjà. Remplacer?",
             "presetNamePlaceholder": "Nom du préréglage...",
             "baseModel": "Modèle de base",
+            "baseModelSearchPlaceholder": "Rechercher des modèles de base...",
             "modelTags": "Tags (Top 20)",
             "modelTypes": "Types de modèles",
             "license": "Licence",
             "noCreditRequired": "Crédit non requis",
             "allowSellingGeneratedContent": "Vente autorisée",
             "noTags": "Aucun tag",
+            "noBaseModelMatches": "Aucun modèle de base ne correspond à la recherche actuelle.",
             "clearAll": "Effacer tous les filtres",
             "any": "N'importe quel",
             "all": "Tous",
@@ -250,6 +256,33 @@
         "civitaiApiKey": "Clé API Civitai",
         "civitaiApiKeyPlaceholder": "Entrez votre clé API Civitai",
         "civitaiApiKeyHelp": "Utilisée pour l'authentification lors du téléchargement de modèles depuis Civitai",
+        "civitaiHost": {
+            "label": "Hôte Civitai",
+            "help": "Choisissez quel site Civitai s'ouvre lorsque vous utilisez les liens « View on Civitai ».",
+            "options": {
+                "com": "civitai.com (SFW uniquement)",
+                "red": "civitai.red (sans restriction)"
+            }
+        },
+        "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.",
+            "options": {
+                "python": "Python (intégré)",
+                "aria2": "aria2 (expérimental)"
+            }
+        },
+        "aria2cPath": {
+            "label": "Chemin vers aria2c",
+            "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.",
+            "openSettings": "Ouvrir les paramètres"
+        },
         "openSettingsFileLocation": {
             "label": "Ouvrir le dossier des paramètres",
             "tooltip": "Ouvrir le dossier contenant settings.json",
@@ -260,6 +293,7 @@
         },
         "sections": {
             "contentFiltering": "Filtrage du contenu",
+            "downloads": "Téléchargements",
             "videoSettings": "Paramètres vidéo",
             "layoutSettings": "Paramètres d'affichage",
             "misc": "Divers",
@@ -395,6 +429,8 @@
                 "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",
@@ -506,6 +542,21 @@
             "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",
@@ -636,7 +687,10 @@
             "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",
             "clear": "Effacer la sélection",
             "skipMetadataRefreshCount": "Ignorer（{count} modèles）",
@@ -667,6 +721,7 @@
             "moveToFolder": "Déplacer vers un dossier",
             "repairMetadata": "Réparer les métadonnées",
             "excludeModel": "Exclure le modèle",
+            "restoreModel": "Restaurer le modèle",
             "deleteModel": "Supprimer le modèle",
             "shareRecipe": "Partager la recipe",
             "viewAllLoras": "Voir tous les LoRAs",
@@ -957,6 +1012,8 @@
             "earlyAccess": "Accès anticipé",
             "earlyAccessTooltip": "Accès anticipé requis",
             "inLibrary": "Dans la bibliothèque",
+            "downloaded": "Téléchargé",
+            "downloadedTooltip": "Déjà téléchargé, mais il n'est actuellement pas dans votre bibliothèque.",
             "alreadyInLibrary": "Déjà dans la bibliothèque",
             "autoOrganizedPath": "[Auto-organisé par modèle de chemin]",
             "errors": {
@@ -1155,6 +1212,8 @@
                 "cancel": "Annuler la modification",
                 "save": "Sauvegarder les modifications",
                 "addPlaceholder": "Tapez pour ajouter ou cliquez sur les suggestions ci-dessous",
+                "editWord": "Modifier le mot déclencheur",
+                "editPlaceholder": "Modifier le mot déclencheur",
                 "copyWord": "Copier le mot-clé",
                 "deleteWord": "Supprimer le mot-clé",
                 "suggestions": {
@@ -1226,17 +1285,33 @@
                     "days": "dans {count}j"
                 },
                 "badges": {
-                    "current": "Version actuelle",
+                    "current": "Version ouverte",
+                    "currentTooltip": "C'est la version à partir de laquelle cette fenêtre a été ouverte",
                     "inLibrary": "Dans la bibliothèque",
+                    "inLibraryTooltip": "Cette version existe dans votre bibliothèque locale",
+                    "downloaded": "Téléchargé",
+                    "downloadedTooltip": "Cette version a déjà été téléchargée, mais n'est pas actuellement dans votre bibliothèque",
                     "newer": "Version plus récente",
+                    "newerTooltip": "Cette version est plus récente que votre dernière version locale",
                     "earlyAccess": "Accès anticipé",
-                    "ignored": "Ignorée"
+                    "earlyAccessTooltip": "Cette version nécessite actuellement l'accès anticipé Civitai",
+                    "ignored": "Ignorée",
+                    "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",
                     "unignore": "Ne plus ignorer",
+                    "ignoreTooltip": "Ignorer les notifications de mise à jour pour cette version",
+                    "unignoreTooltip": "Reprendre les notifications de mise à jour pour cette version",
+                    "viewVersionOnCivitai": "Voir la version sur Civitai",
                     "earlyAccessTooltip": "Nécessite l'achat de l'accès anticipé",
                     "resumeModelUpdates": "Reprendre les mises à jour pour ce modèle",
                     "ignoreModelUpdates": "Ignorer les mises à jour pour ce modèle",
@@ -1392,6 +1467,10 @@
             "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.",
@@ -1623,6 +1702,11 @@
             "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",
@@ -1713,8 +1797,8 @@
         },
         "triggerWords": {
             "loadFailed": "Impossible de charger les mots entraînés",
-            "tooLong": "Le mot-clé ne doit pas dépasser 100 mots",
-            "tooMany": "Maximum 30 mots-clés autorisés",
+            "tooLong": "Le mot-clé ne doit pas dépasser 500 mots",
+            "tooMany": "Maximum 100 mots-clés autorisés",
             "alreadyExists": "Ce mot-clé existe déjà",
             "updateSuccess": "Mots-clés mis à jour avec succès",
             "updateFailed": "Échec de la mise à jour des mots-clés",
@@ -1775,6 +1859,8 @@
             "deleteFailed": "Échec de la suppression de {type} : {message}",
             "excludeSuccess": "{type} exclu avec succès",
             "excludeFailed": "Échec de l'exclusion de {type} : {message}",
+            "restoreSuccess": "{type} restauré avec succès",
+            "restoreFailed": "Échec de la restauration de {type} : {message}",
             "fileNameUpdated": "Nom de fichier mis à jour avec succès",
             "fileRenameFailed": "Échec du renommage du fichier : {error}",
             "previewUpdated": "Aperçu mis à jour avec succès",
@@ -1832,7 +1918,9 @@
             "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}"
         }
     },
     "banners": {

locales/he.json

@@ -15,7 +15,8 @@
             "settings": "הגדרות",
             "help": "עזרה",
             "add": "הוספה",
-            "close": "סגור"
+            "close": "סגור",
+            "menu": "תפריט"
         },
         "status": {
             "loading": "טוען...",
@@ -175,6 +176,9 @@
             "success": "תוקנו בהצלחה {count} מתכונים.",
             "cancelled": "תיקון בוטל. {count} מתכונים תוקנו.",
             "error": "תיקון המתכונים נכשל: {message}"
+        },
+        "manageExcludedModels": {
+            "label": "ניהול מודלים מוחרגים"
         }
     },
     "header": {
@@ -222,12 +226,14 @@
             "presetOverwriteConfirm": "הפריסט \"{name}\" כבר קיים. לדרוס?",
             "presetNamePlaceholder": "שם קביעה מראש...",
             "baseModel": "מודל בסיס",
+            "baseModelSearchPlaceholder": "חפש מודלי בסיס...",
             "modelTags": "תגיות (20 המובילות)",
             "modelTypes": "סוגי מודלים",
             "license": "רישיון",
             "noCreditRequired": "ללא קרדיט נדרש",
             "allowSellingGeneratedContent": "אפשר מכירה",
             "noTags": "ללא תגיות",
+            "noBaseModelMatches": "אין מודלי בסיס התואמים לחיפוש הנוכחי.",
             "clearAll": "נקה את כל המסננים",
             "any": "כלשהו",
             "all": "כל התגים",
@@ -250,6 +256,33 @@
         "civitaiApiKey": "מפתח API של Civitai",
         "civitaiApiKeyPlaceholder": "הזן את מפתח ה-API שלך מ-Civitai",
         "civitaiApiKeyHelp": "משמש לאימות בעת הורדת מודלים מ-Civitai",
+        "civitaiHost": {
+            "label": "מארח Civitai",
+            "help": "בחר איזה אתר של Civitai ייפתח בעת שימוש בקישורי \"View on Civitai\".",
+            "options": {
+                "com": "civitai.com (SFW בלבד)",
+                "red": "civitai.red (ללא הגבלות)"
+            }
+        },
+        "downloadBackend": {
+            "label": "מנגנון הורדה",
+            "help": "בחר כיצד יורדים קבצי המודל. Python משתמש במוריד המובנה. aria2 משתמש בתהליך הורדה חיצוני ניסיוני.",
+            "options": {
+                "python": "Python (מובנה)",
+                "aria2": "aria2 (ניסיוני)"
+            }
+        },
+        "aria2cPath": {
+            "label": "נתיב aria2c",
+            "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.",
+            "openSettings": "פתח הגדרות"
+        },
         "openSettingsFileLocation": {
             "label": "פתח תיקיית הגדרות",
             "tooltip": "פתח את התיקייה שמכילה את ‎settings.json",
@@ -260,6 +293,7 @@
         },
         "sections": {
             "contentFiltering": "סינון תוכן",
+            "downloads": "הורדות",
             "videoSettings": "הגדרות וידאו",
             "layoutSettings": "הגדרות פריסה",
             "misc": "שונות",
@@ -395,6 +429,8 @@
                 "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",
@@ -506,6 +542,21 @@
             "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",
@@ -636,7 +687,10 @@
             "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",
             "clear": "נקה בחירה",
             "skipMetadataRefreshCount": "דילוג（{count} מודלים）",
@@ -667,6 +721,7 @@
             "moveToFolder": "העבר לתיקייה",
             "repairMetadata": "תיקון מטא-דאטה",
             "excludeModel": "החרג מודל",
+            "restoreModel": "שחזור מודל",
             "deleteModel": "מחק מודל",
             "shareRecipe": "שתף מתכון",
             "viewAllLoras": "הצג את כל ה-LoRAs",
@@ -957,6 +1012,8 @@
             "earlyAccess": "גישה מוקדמת",
             "earlyAccessTooltip": "נדרשת גישה מוקדמת",
             "inLibrary": "בספרייה",
+            "downloaded": "הורד",
+            "downloadedTooltip": "הורד בעבר, אך הוא אינו נמצא כרגע בספרייה שלך.",
             "alreadyInLibrary": "כבר בספרייה",
             "autoOrganizedPath": "[מאורגן אוטומטית לפי תבנית נתיב]",
             "errors": {
@@ -1155,6 +1212,8 @@
                 "cancel": "בטל עריכה",
                 "save": "שמור שינויים",
                 "addPlaceholder": "הקלד להוספה או לחץ על הצעות למטה",
+                "editWord": "עריכת מילת טריגר",
+                "editPlaceholder": "עריכת מילת טריגר",
                 "copyWord": "העתק מילת טריגר",
                 "deleteWord": "מחק מילת טריגר",
                 "suggestions": {
@@ -1226,17 +1285,33 @@
                     "days": "בעוד {count} ימים"
                 },
                 "badges": {
-                    "current": "גרסה נוכחית",
+                    "current": "גרסה שנפתחה",
+                    "currentTooltip": "זוהי הגרסה שממנה נפתח החלון הזה",
                     "inLibrary": "בספרייה",
+                    "inLibraryTooltip": "גרסה זו קיימת בספרייה המקומית שלך",
+                    "downloaded": "הורד",
+                    "downloadedTooltip": "גרסה זו הורדה בעבר, אך אינה נמצאת כרגע בספרייה שלך",
                     "newer": "גרסה חדשה יותר",
+                    "newerTooltip": "גרסה זו חדשה יותר מהגרסה המקומית האחרונה שלך",
                     "earlyAccess": "גישה מוקדמת",
-                    "ignored": "התעלם"
+                    "earlyAccessTooltip": "גרסה זו דורשת כרגע גישת Early Access של Civitai",
+                    "ignored": "התעלם",
+                    "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",
                     "unignore": "בטל התעלמות",
+                    "ignoreTooltip": "התעלם מהתראות העדכון עבור גרסה זו",
+                    "unignoreTooltip": "חזור לקבל התראות עדכון עבור גרסה זו",
+                    "viewVersionOnCivitai": "הצג את הגרסה ב-Civitai",
                     "earlyAccessTooltip": "נדרש רכישת גישה מוקדמת",
                     "resumeModelUpdates": "המשך עדכונים עבור מודל זה",
                     "ignoreModelUpdates": "התעלם מעדכונים עבור מודל זה",
@@ -1392,6 +1467,10 @@
             "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.",
@@ -1623,6 +1702,11 @@
             "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",
@@ -1713,8 +1797,8 @@
         },
         "triggerWords": {
             "loadFailed": "לא ניתן היה לטעון מילים מאומנות",
-            "tooLong": "מילת טריגר לא תעלה על 100 מילים",
-            "tooMany": "מותרות עד 30 מילות טריגר",
+            "tooLong": "מילת טריגר לא תעלה על 500 מילים",
+            "tooMany": "מותרות עד 100 מילות טריגר",
             "alreadyExists": "מילת טריגר זו כבר קיימת",
             "updateSuccess": "מילות הטריגר עודכנו בהצלחה",
             "updateFailed": "עדכון מילות הטריגר נכשל",
@@ -1775,6 +1859,8 @@
             "deleteFailed": "מחיקת {type} נכשלה: {message}",
             "excludeSuccess": "{type} הוחרג בהצלחה",
             "excludeFailed": "החרגת {type} נכשלה: {message}",
+            "restoreSuccess": "{type} שוחזר בהצלחה",
+            "restoreFailed": "שחזור {type} נכשל: {message}",
             "fileNameUpdated": "שם הקובץ עודכן בהצלחה",
             "fileRenameFailed": "שינוי שם הקובץ נכשל: {error}",
             "previewUpdated": "התצוגה המקדימה עודכנה בהצלחה",
@@ -1832,7 +1918,9 @@
             "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}"
         }
     },
     "banners": {

locales/ja.json

@@ -15,7 +15,8 @@
             "settings": "設定",
             "help": "ヘルプ",
             "add": "追加",
-            "close": "閉じる"
+            "close": "閉じる",
+            "menu": "メニュー"
         },
         "status": {
             "loading": "読み込み中...",
@@ -175,6 +176,9 @@
             "success": "{count} 件のレシピを正常に修復しました。",
             "cancelled": "修復がキャンセルされました。{count}個のレシピが修復されました。",
             "error": "レシピの修復に失敗しました: {message}"
+        },
+        "manageExcludedModels": {
+            "label": "除外モデルを管理"
         }
     },
     "header": {
@@ -222,12 +226,14 @@
             "presetOverwriteConfirm": "プリセット「{name}」は既に存在します。上書きしますか？",
             "presetNamePlaceholder": "プリセット名...",
             "baseModel": "ベースモデル",
+            "baseModelSearchPlaceholder": "ベースモデルを検索...",
             "modelTags": "タグ（上位20）",
             "modelTypes": "モデルタイプ",
             "license": "ライセンス",
             "noCreditRequired": "クレジット不要",
             "allowSellingGeneratedContent": "販売許可",
             "noTags": "タグなし",
+            "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",
             "all": "すべて",
@@ -250,6 +256,33 @@
         "civitaiApiKey": "Civitai APIキー",
         "civitaiApiKeyPlaceholder": "Civitai APIキーを入力してください",
         "civitaiApiKeyHelp": "Civitaiからモデルをダウンロードするときの認証に使用されます",
+        "civitaiHost": {
+            "label": "Civitai ホスト",
+            "help": "「View on Civitai」リンクを使うときに開く Civitai サイトを選択します。",
+            "options": {
+                "com": "civitai.com（SFW のみ）",
+                "red": "civitai.red（制限なし）"
+            }
+        },
+        "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。",
+            "options": {
+                "python": "Python（内蔵）",
+                "aria2": "aria2（実験的）"
+            }
+        },
+        "aria2cPath": {
+            "label": "aria2c のパス",
+            "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。",
+            "openSettings": "設定を開く"
+        },
         "openSettingsFileLocation": {
             "label": "設定フォルダーを開く",
             "tooltip": "settings.json を含むフォルダーを開きます",
@@ -260,6 +293,7 @@
         },
         "sections": {
             "contentFiltering": "コンテンツフィルタリング",
+            "downloads": "ダウンロード",
             "videoSettings": "動画設定",
             "layoutSettings": "レイアウト設定",
             "misc": "その他",
@@ -395,6 +429,8 @@
                 "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",
@@ -506,6 +542,21 @@
             "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",
@@ -636,7 +687,10 @@
             "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",
             "clear": "選択をクリア",
             "skipMetadataRefreshCount": "スキップ（{count}モデル）",
@@ -667,6 +721,7 @@
             "moveToFolder": "フォルダに移動",
             "repairMetadata": "メタデータを修復",
             "excludeModel": "モデルを除外",
+            "restoreModel": "モデルを復元",
             "deleteModel": "モデルを削除",
             "shareRecipe": "レシピを共有",
             "viewAllLoras": "すべてのLoRAを表示",
@@ -957,6 +1012,8 @@
             "earlyAccess": "アーリーアクセス",
             "earlyAccessTooltip": "アーリーアクセスが必要",
             "inLibrary": "ライブラリ内",
+            "downloaded": "ダウンロード済み",
+            "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]",
             "errors": {
@@ -1155,6 +1212,8 @@
                 "cancel": "編集をキャンセル",
                 "save": "変更を保存",
                 "addPlaceholder": "入力して追加するか、下の提案をクリック",
+                "editWord": "トリガーワードを編集",
+                "editPlaceholder": "トリガーワードを編集",
                 "copyWord": "トリガーワードをコピー",
                 "deleteWord": "トリガーワードを削除",
                 "suggestions": {
@@ -1226,17 +1285,33 @@
                     "days": "{count}日後"
                 },
                 "badges": {
-                    "current": "現在のバージョン",
+                    "current": "開いたバージョン",
+                    "currentTooltip": "このモーダルを開くために選択したバージョンです",
                     "inLibrary": "ライブラリにあります",
+                    "inLibraryTooltip": "このバージョンはローカルライブラリに存在します",
+                    "downloaded": "ダウンロード済み",
+                    "downloadedTooltip": "このバージョンは以前ダウンロードされましたが、現在はライブラリにありません",
                     "newer": "新しいバージョン",
+                    "newerTooltip": "このバージョンはローカルの最新バージョンより新しいです",
                     "earlyAccess": "早期アクセス",
-                    "ignored": "無視中"
+                    "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",
+                    "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",
                     "unignore": "無視を解除",
+                    "ignoreTooltip": "このバージョンの更新通知を無視",
+                    "unignoreTooltip": "このバージョンの更新通知を再開",
+                    "viewVersionOnCivitai": "Civitai でバージョンを表示",
                     "earlyAccessTooltip": "早期アクセス購入が必要",
                     "resumeModelUpdates": "このモデルの更新を再開",
                     "ignoreModelUpdates": "このモデルの更新を無視",
@@ -1392,6 +1467,10 @@
             "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。",
@@ -1623,6 +1702,11 @@
             "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",
@@ -1713,8 +1797,8 @@
         },
         "triggerWords": {
             "loadFailed": "学習済みワードを読み込めませんでした",
-            "tooLong": "トリガーワードは100ワードを超えてはいけません",
-            "tooMany": "最大30トリガーワードまで許可されています",
+            "tooLong": "トリガーワードは500ワードを超えてはいけません",
+            "tooMany": "最大100トリガーワードまで許可されています",
             "alreadyExists": "このトリガーワードは既に存在します",
             "updateSuccess": "トリガーワードが正常に更新されました",
             "updateFailed": "トリガーワードの更新に失敗しました",
@@ -1775,6 +1859,8 @@
             "deleteFailed": "{type}の削除に失敗しました：{message}",
             "excludeSuccess": "{type}が正常に除外されました",
             "excludeFailed": "{type}の除外に失敗しました：{message}",
+            "restoreSuccess": "{type}を復元しました",
+            "restoreFailed": "{type}の復元に失敗しました: {message}",
             "fileNameUpdated": "ファイル名が正常に更新されました",
             "fileRenameFailed": "ファイル名の変更に失敗しました：{error}",
             "previewUpdated": "プレビューが正常に更新されました",
@@ -1832,7 +1918,9 @@
             "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}"
         }
     },
     "banners": {

locales/ko.json

@@ -15,7 +15,8 @@
             "settings": "설정",
             "help": "도움말",
             "add": "추가",
-            "close": "닫기"
+            "close": "닫기",
+            "menu": "메뉴"
         },
         "status": {
             "loading": "로딩 중...",
@@ -175,6 +176,9 @@
             "success": "{count}개의 레시피가 성공적으로 복구되었습니다.",
             "cancelled": "수리가 취소되었습니다. {count}개의 레시피가 수리되었습니다.",
             "error": "레시피 복구 실패: {message}"
+        },
+        "manageExcludedModels": {
+            "label": "제외된 모델 관리"
         }
     },
     "header": {
@@ -222,12 +226,14 @@
             "presetOverwriteConfirm": "프리셋 \"{name}\"이(가) 이미 존재합니다. 덮어쓰시겠습니까?",
             "presetNamePlaceholder": "프리셋 이름...",
             "baseModel": "베이스 모델",
+            "baseModelSearchPlaceholder": "베이스 모델 검색...",
             "modelTags": "태그 (상위 20개)",
             "modelTypes": "모델 유형",
             "license": "라이선스",
             "noCreditRequired": "크레딧 표기 없음",
             "allowSellingGeneratedContent": "판매 허용",
             "noTags": "태그 없음",
+            "noBaseModelMatches": "현재 검색과 일치하는 베이스 모델이 없습니다.",
             "clearAll": "모든 필터 지우기",
             "any": "아무",
             "all": "모두",
@@ -250,6 +256,33 @@
         "civitaiApiKey": "Civitai API 키",
         "civitaiApiKeyPlaceholder": "Civitai API 키를 입력하세요",
         "civitaiApiKeyHelp": "Civitai에서 모델을 다운로드할 때 인증에 사용됩니다",
+        "civitaiHost": {
+            "label": "Civitai 호스트",
+            "help": "\"View on Civitai\" 링크를 사용할 때 어떤 Civitai 사이트를 열지 선택합니다.",
+            "options": {
+                "com": "civitai.com(SFW 전용)",
+                "red": "civitai.red(무제한)"
+            }
+        },
+        "downloadBackend": {
+            "label": "다운로드 백엔드",
+            "help": "모델 파일을 다운로드하는 방식을 선택합니다. Python은 내장 다운로더를 사용하고, aria2는 실험적인 외부 다운로더 프로세스를 사용합니다.",
+            "options": {
+                "python": "Python(내장)",
+                "aria2": "aria2(실험적)"
+            }
+        },
+        "aria2cPath": {
+            "label": "aria2c 경로",
+            "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.",
+            "openSettings": "설정 열기"
+        },
         "openSettingsFileLocation": {
             "label": "설정 폴더 열기",
             "tooltip": "settings.json이 있는 폴더를 엽니다",
@@ -260,6 +293,7 @@
         },
         "sections": {
             "contentFiltering": "콘텐츠 필터링",
+            "downloads": "다운로드",
             "videoSettings": "비디오 설정",
             "layoutSettings": "레이아웃 설정",
             "misc": "기타",
@@ -395,6 +429,8 @@
                 "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",
@@ -506,6 +542,21 @@
             "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",
@@ -636,7 +687,10 @@
             "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",
             "clear": "선택 지우기",
             "skipMetadataRefreshCount": "건너뛰기（{count}개 모델）",
@@ -667,6 +721,7 @@
             "moveToFolder": "폴더로 이동",
             "repairMetadata": "메타데이터 복구",
             "excludeModel": "모델 제외",
+            "restoreModel": "모델 복원",
             "deleteModel": "모델 삭제",
             "shareRecipe": "레시피 공유",
             "viewAllLoras": "모든 LoRA 보기",
@@ -957,6 +1012,8 @@
             "earlyAccess": "얼리 액세스",
             "earlyAccessTooltip": "얼리 액세스 필요",
             "inLibrary": "라이브러리에 있음",
+            "downloaded": "다운로드됨",
+            "downloadedTooltip": "이전에 다운로드했지만 현재 라이브러리에 없습니다.",
             "alreadyInLibrary": "이미 라이브러리에 있음",
             "autoOrganizedPath": "[경로 템플릿으로 자동 정리됨]",
             "errors": {
@@ -1155,6 +1212,8 @@
                 "cancel": "편집 취소",
                 "save": "변경사항 저장",
                 "addPlaceholder": "입력하거나 아래 제안을 클릭하세요",
+                "editWord": "트리거 단어 편집",
+                "editPlaceholder": "트리거 단어 편집",
                 "copyWord": "트리거 단어 복사",
                 "deleteWord": "트리거 단어 삭제",
                 "suggestions": {
@@ -1226,17 +1285,33 @@
                     "days": "{count}일 후"
                 },
                 "badges": {
-                    "current": "현재 버전",
+                    "current": "열린 버전",
+                    "currentTooltip": "이 모달을 열 때 사용한 버전입니다",
                     "inLibrary": "라이브러리에 있음",
+                    "inLibraryTooltip": "이 버전은 로컬 라이브러리에 있습니다",
+                    "downloaded": "다운로드됨",
+                    "downloadedTooltip": "이 버전은 이전에 다운로드되었지만 현재는 라이브러리에 없습니다",
                     "newer": "최신 버전",
+                    "newerTooltip": "이 버전은 로컬의 최신 버전보다 더 새롭습니다",
                     "earlyAccess": "얼리 액세스",
-                    "ignored": "무시됨"
+                    "earlyAccessTooltip": "이 버전은 현재 Civitai 얼리 액세스가 필요합니다",
+                    "ignored": "무시됨",
+                    "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",
                     "unignore": "무시 해제",
+                    "ignoreTooltip": "이 버전의 업데이트 알림 무시",
+                    "unignoreTooltip": "이 버전의 업데이트 알림 다시 받기",
+                    "viewVersionOnCivitai": "Civitai에서 버전 보기",
                     "earlyAccessTooltip": "얼리 액세스 구매 필요",
                     "resumeModelUpdates": "이 모델 업데이트 재개",
                     "ignoreModelUpdates": "이 모델 업데이트 무시",
@@ -1392,6 +1467,10 @@
             "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.",
@@ -1623,6 +1702,11 @@
             "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",
@@ -1713,8 +1797,8 @@
         },
         "triggerWords": {
             "loadFailed": "학습된 단어를 로딩할 수 없습니다",
-            "tooLong": "트리거 단어는 100단어를 초과할 수 없습니다",
-            "tooMany": "최대 30개의 트리거 단어만 허용됩니다",
+            "tooLong": "트리거 단어는 500단어를 초과할 수 없습니다",
+            "tooMany": "최대 100개의 트리거 단어만 허용됩니다",
             "alreadyExists": "이 트리거 단어는 이미 존재합니다",
             "updateSuccess": "트리거 단어가 성공적으로 업데이트되었습니다",
             "updateFailed": "트리거 단어 업데이트에 실패했습니다",
@@ -1775,6 +1859,8 @@
             "deleteFailed": "{type} 삭제 실패: {message}",
             "excludeSuccess": "{type}이(가) 성공적으로 제외되었습니다",
             "excludeFailed": "{type} 제외 실패: {message}",
+            "restoreSuccess": "{type} 복원 완료",
+            "restoreFailed": "{type} 복원 실패: {message}",
             "fileNameUpdated": "파일명이 성공적으로 업데이트되었습니다",
             "fileRenameFailed": "파일 이름 변경 실패: {error}",
             "previewUpdated": "미리보기가 성공적으로 업데이트되었습니다",
@@ -1832,7 +1918,9 @@
             "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}"
         }
     },
     "banners": {

locales/ru.json

@@ -15,7 +15,8 @@
             "settings": "Настройки",
             "help": "Справка",
             "add": "Добавить",
-            "close": "Закрыть"
+            "close": "Закрыть",
+            "menu": "Меню"
         },
         "status": {
             "loading": "Загрузка...",
@@ -175,6 +176,9 @@
             "success": "Успешно восстановлено {count} рецептов.",
             "cancelled": "Восстановление отменено. {count} рецептов было восстановлено.",
             "error": "Ошибка восстановления рецептов: {message}"
+        },
+        "manageExcludedModels": {
+            "label": "Управление исключёнными моделями"
         }
     },
     "header": {
@@ -222,12 +226,14 @@
             "presetOverwriteConfirm": "Пресет \"{name}\" уже существует. Перезаписать?",
             "presetNamePlaceholder": "Имя пресета...",
             "baseModel": "Базовая модель",
+            "baseModelSearchPlaceholder": "Поиск базовых моделей...",
             "modelTags": "Теги (Топ 20)",
             "modelTypes": "Типы моделей",
             "license": "Лицензия",
             "noCreditRequired": "Без указания авторства",
             "allowSellingGeneratedContent": "Продажа разрешена",
             "noTags": "Без тегов",
+            "noBaseModelMatches": "Нет базовых моделей, соответствующих текущему поиску.",
             "clearAll": "Очистить все фильтры",
             "any": "Любой",
             "all": "Все",
@@ -250,6 +256,33 @@
         "civitaiApiKey": "Ключ API Civitai",
         "civitaiApiKeyPlaceholder": "Введите ваш ключ API Civitai",
         "civitaiApiKeyHelp": "Используется для аутентификации при загрузке моделей с Civitai",
+        "civitaiHost": {
+            "label": "Хост Civitai",
+            "help": "Выберите, какой сайт Civitai будет открываться при использовании ссылок «View on Civitai».",
+            "options": {
+                "com": "civitai.com (только SFW)",
+                "red": "civitai.red (без ограничений)"
+            }
+        },
+        "downloadBackend": {
+            "label": "Бэкенд загрузки",
+            "help": "Выберите способ загрузки файлов моделей. Python использует встроенный загрузчик. aria2 использует экспериментальный внешний процесс загрузки.",
+            "options": {
+                "python": "Python (встроенный)",
+                "aria2": "aria2 (экспериментальный)"
+            }
+        },
+        "aria2cPath": {
+            "label": "Путь к aria2c",
+            "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.",
+            "openSettings": "Открыть настройки"
+        },
         "openSettingsFileLocation": {
             "label": "Открыть папку настроек",
             "tooltip": "Открыть папку, содержащую settings.json",
@@ -260,6 +293,7 @@
         },
         "sections": {
             "contentFiltering": "Фильтрация контента",
+            "downloads": "Загрузки",
             "videoSettings": "Настройки видео",
             "layoutSettings": "Настройки макета",
             "misc": "Разное",
@@ -395,6 +429,8 @@
                 "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",
@@ -506,6 +542,21 @@
             "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",
@@ -636,7 +687,10 @@
             "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",
             "clear": "Очистить выбор",
             "skipMetadataRefreshCount": "Пропустить（{count} моделей）",
@@ -667,6 +721,7 @@
             "moveToFolder": "Переместить в папку",
             "repairMetadata": "Восстановить метаданные",
             "excludeModel": "Исключить модель",
+            "restoreModel": "Восстановить модель",
             "deleteModel": "Удалить модель",
             "shareRecipe": "Поделиться рецептом",
             "viewAllLoras": "Посмотреть все LoRAs",
@@ -957,6 +1012,8 @@
             "earlyAccess": "Ранний доступ",
             "earlyAccessTooltip": "Требуется ранний доступ",
             "inLibrary": "В библиотеке",
+            "downloaded": "Загружено",
+            "downloadedTooltip": "Ранее загружено, но сейчас этого нет в вашей библиотеке.",
             "alreadyInLibrary": "Уже в библиотеке",
             "autoOrganizedPath": "[Автоматически организовано по шаблону пути]",
             "errors": {
@@ -1155,6 +1212,8 @@
                 "cancel": "Отменить редактирование",
                 "save": "Сохранить изменения",
                 "addPlaceholder": "Введите для добавления или нажмите на предложения ниже",
+                "editWord": "Редактировать триггерное слово",
+                "editPlaceholder": "Редактировать триггерное слово",
                 "copyWord": "Копировать триггерное слово",
                 "deleteWord": "Удалить триггерное слово",
                 "suggestions": {
@@ -1226,17 +1285,33 @@
                     "days": "через {count}д"
                 },
                 "badges": {
-                    "current": "Текущая версия",
+                    "current": "Открытая версия",
+                    "currentTooltip": "Это версия, с которой было открыто это окно",
                     "inLibrary": "В библиотеке",
+                    "inLibraryTooltip": "Эта версия есть в вашей локальной библиотеке",
+                    "downloaded": "Загружено",
+                    "downloadedTooltip": "Эта версия уже загружалась, но сейчас отсутствует в вашей библиотеке",
                     "newer": "Более новая версия",
+                    "newerTooltip": "Эта версия новее вашей последней локальной версии",
                     "earlyAccess": "Ранний доступ",
-                    "ignored": "Игнорируется"
+                    "earlyAccessTooltip": "Для этой версии сейчас требуется ранний доступ Civitai",
+                    "ignored": "Игнорируется",
+                    "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",
                     "unignore": "Перестать игнорировать",
+                    "ignoreTooltip": "Игнорировать уведомления об обновлениях для этой версии",
+                    "unignoreTooltip": "Возобновить уведомления об обновлениях для этой версии",
+                    "viewVersionOnCivitai": "Посмотреть версию на Civitai",
                     "earlyAccessTooltip": "Требуется покупка раннего доступа",
                     "resumeModelUpdates": "Возобновить обновления для этой модели",
                     "ignoreModelUpdates": "Игнорировать обновления для этой модели",
@@ -1392,6 +1467,10 @@
             "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.",
@@ -1623,6 +1702,11 @@
             "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",
@@ -1713,8 +1797,8 @@
         },
         "triggerWords": {
             "loadFailed": "Не удалось загрузить обученные слова",
-            "tooLong": "Триггерное слово не должно превышать 100 слов",
-            "tooMany": "Максимум 30 триггерных слов разрешено",
+            "tooLong": "Триггерное слово не должно превышать 500 слов",
+            "tooMany": "Максимум 100 триггерных слов разрешено",
             "alreadyExists": "Это триггерное слово уже существует",
             "updateSuccess": "Триггерные слова успешно обновлены",
             "updateFailed": "Не удалось обновить триггерные слова",
@@ -1775,6 +1859,8 @@
             "deleteFailed": "Не удалось удалить {type}: {message}",
             "excludeSuccess": "{type} успешно исключен",
             "excludeFailed": "Не удалось исключить {type}: {message}",
+            "restoreSuccess": "{type} успешно восстановлен",
+            "restoreFailed": "Не удалось восстановить {type}: {message}",
             "fileNameUpdated": "Имя файла успешно обновлено",
             "fileRenameFailed": "Не удалось переименовать файл: {error}",
             "previewUpdated": "Превью успешно обновлено",
@@ -1832,7 +1918,9 @@
             "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}"
         }
     },
     "banners": {

locales/zh-CN.json

@@ -15,7 +15,8 @@
             "settings": "设置",
             "help": "帮助",
             "add": "添加",
-            "close": "关闭"
+            "close": "关闭",
+            "menu": "菜单"
         },
         "status": {
             "loading": "加载中...",
@@ -175,6 +176,9 @@
             "success": "成功修复了 {count} 个配方。",
             "cancelled": "修复已取消。已修复 {count} 个配方。",
             "error": "配方修复失败：{message}"
+        },
+        "manageExcludedModels": {
+            "label": "管理已排除的模型"
         }
     },
     "header": {
@@ -222,12 +226,14 @@
             "presetOverwriteConfirm": "预设 \"{name}\" 已存在。是否覆盖？",
             "presetNamePlaceholder": "预设名称...",
             "baseModel": "基础模型",
+            "baseModelSearchPlaceholder": "搜索基础模型...",
             "modelTags": "标签（前20）",
             "modelTypes": "模型类型",
             "license": "许可证",
             "noCreditRequired": "无需署名",
             "allowSellingGeneratedContent": "允许销售",
             "noTags": "无标签",
+            "noBaseModelMatches": "没有基础模型符合当前搜索。",
             "clearAll": "清除所有筛选",
             "any": "任一",
             "all": "全部",
@@ -250,6 +256,33 @@
         "civitaiApiKey": "Civitai API 密钥",
         "civitaiApiKeyPlaceholder": "请输入你的 Civitai API 密钥",
         "civitaiApiKeyHelp": "用于从 Civitai 下载模型时的身份验证",
+        "civitaiHost": {
+            "label": "Civitai 站点",
+            "help": "选择使用“在 Civitai 中查看”时默认打开的 Civitai 站点。",
+            "options": {
+                "com": "civitai.com（仅 SFW）",
+                "red": "civitai.red（无限制）"
+            }
+        },
+        "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。",
+            "options": {
+                "python": "Python（内置）",
+                "aria2": "aria2（实验性）"
+            }
+        },
+        "aria2cPath": {
+            "label": "aria2c 路径",
+            "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。",
+            "openSettings": "打开设置"
+        },
         "openSettingsFileLocation": {
             "label": "打开设置文件夹",
             "tooltip": "打开包含 settings.json 的文件夹",
@@ -260,6 +293,7 @@
         },
         "sections": {
             "contentFiltering": "内容过滤",
+            "downloads": "下载",
             "videoSettings": "视频设置",
             "layoutSettings": "布局设置",
             "misc": "其他",
@@ -395,6 +429,8 @@
                 "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",
@@ -506,6 +542,21 @@
             "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",
@@ -636,7 +687,10 @@
             "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",
             "clear": "清除选择",
             "skipMetadataRefreshCount": "跳过（{count} 个模型）",
@@ -667,6 +721,7 @@
             "moveToFolder": "移动到文件夹",
             "repairMetadata": "修复元数据",
             "excludeModel": "排除模型",
+            "restoreModel": "恢复模型",
             "deleteModel": "删除模型",
             "shareRecipe": "分享配方",
             "viewAllLoras": "查看所有 LoRA",
@@ -685,9 +740,9 @@
                 "title": "从图片或 URL 导入配方",
                 "urlLocalPath": "URL / 本地路径",
                 "uploadImage": "上传图片",
-                "urlSectionDescription": "输入 Civitai 图片 URL 或本地文件路径以导入为配方。",
+                "urlSectionDescription": "输入来自 civitai.com 或 civitai.red 的 Civitai 图片 URL，或本地文件路径以导入为配方。",
                 "imageUrlOrPath": "图片 URL 或文件路径：",
-                "urlPlaceholder": "https://civitai.com/images/... 或 C:/path/to/image.png",
+                "urlPlaceholder": "https://civitai.com/images/... 或 https://civitai.red/images/... 或 C:/path/to/image.png",
                 "fetchImage": "获取图片",
                 "uploadSectionDescription": "上传带有 LoRA 元数据的图片以导入为配方。",
                 "selectImage": "选择图片",
@@ -957,6 +1012,8 @@
             "earlyAccess": "早期访问",
             "earlyAccessTooltip": "需要早期访问权限",
             "inLibrary": "已在库中",
+            "downloaded": "已下载",
+            "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】",
             "errors": {
@@ -1088,9 +1145,9 @@
             },
             "proceedText": "仅在你确定需要此操作时继续。",
             "urlLabel": "Civitai 模型 URL：",
-            "urlPlaceholder": "https://civitai.com/models/649516/model-name?modelVersionId=726676",
+            "urlPlaceholder": "https://civitai.com/models/649516/model-name?modelVersionId=726676 或 https://civitai.red/models/649516/model-name?modelVersionId=726676",
             "helpText": {
-                "title": "粘贴任意 Civitai 模型 URL。支持格式：",
+                "title": "粘贴任意来自 civitai.com 或 civitai.red 的 Civitai 模型 URL。支持格式：",
                 "format1": "https://civitai.com/models/649516",
                 "format2": "https://civitai.com/models/649516?modelVersionId=726676",
                 "format3": "https://civitai.com/models/649516/model-name?modelVersionId=726676",
@@ -1155,6 +1212,8 @@
                 "cancel": "取消编辑",
                 "save": "保存更改",
                 "addPlaceholder": "输入或点击下方建议添加",
+                "editWord": "编辑触发词",
+                "editPlaceholder": "编辑触发词",
                 "copyWord": "复制触发词",
                 "deleteWord": "删除触发词",
                 "suggestions": {
@@ -1226,17 +1285,33 @@
                     "days": "{count}天后"
                 },
                 "badges": {
-                    "current": "当前版本",
+                    "current": "已打开版本",
+                    "currentTooltip": "这是你用来打开此弹窗的版本",
                     "inLibrary": "已在库中",
+                    "inLibraryTooltip": "此版本已存在于你的本地库中",
+                    "downloaded": "已下载",
+                    "downloadedTooltip": "此版本之前下载过，但当前不在你的本地库中",
                     "newer": "较新的版本",
+                    "newerTooltip": "此版本比你本地的最新版本更新",
                     "earlyAccess": "抢先体验",
-                    "ignored": "已忽略"
+                    "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",
+                    "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",
                     "unignore": "取消忽略",
+                    "ignoreTooltip": "忽略此版本的更新通知",
+                    "unignoreTooltip": "恢复此版本的更新通知",
+                    "viewVersionOnCivitai": "在 Civitai 上查看版本",
                     "earlyAccessTooltip": "需要购买抢先体验",
                     "resumeModelUpdates": "继续跟踪该模型的更新",
                     "ignoreModelUpdates": "忽略该模型的更新",
@@ -1392,6 +1467,10 @@
             "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。",
@@ -1623,6 +1702,11 @@
             "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",
@@ -1713,8 +1797,8 @@
         },
         "triggerWords": {
             "loadFailed": "无法加载训练词",
-            "tooLong": "触发词不能超过100个词",
-            "tooMany": "最多允许30个触发词",
+            "tooLong": "触发词不能超过500个词",
+            "tooMany": "最多允许100个触发词",
             "alreadyExists": "该触发词已存在",
             "updateSuccess": "触发词更新成功",
             "updateFailed": "触发词更新失败",
@@ -1775,6 +1859,8 @@
             "deleteFailed": "删除 {type} 失败：{message}",
             "excludeSuccess": "{type} 排除成功",
             "excludeFailed": "排除 {type} 失败：{message}",
+            "restoreSuccess": "{type} 已成功恢复",
+            "restoreFailed": "恢复 {type} 失败：{message}",
             "fileNameUpdated": "文件名更新成功",
             "fileRenameFailed": "重命名文件失败：{error}",
             "previewUpdated": "预览图片更新成功",
@@ -1832,7 +1918,9 @@
             "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}"
         }
     },
     "banners": {

locales/zh-TW.json

@@ -15,7 +15,8 @@
             "settings": "設定",
             "help": "說明",
             "add": "新增",
-            "close": "關閉"
+            "close": "關閉",
+            "menu": "選單"
         },
         "status": {
             "loading": "載入中...",
@@ -175,6 +176,9 @@
             "success": "成功修復 {count} 個配方。",
             "cancelled": "修復已取消。已修復 {count} 個配方。",
             "error": "配方修復失敗：{message}"
+        },
+        "manageExcludedModels": {
+            "label": "管理已排除的模型"
         }
     },
     "header": {
@@ -222,12 +226,14 @@
             "presetOverwriteConfirm": "預設 \"{name}\" 已存在。是否覆蓋？",
             "presetNamePlaceholder": "預設名稱...",
             "baseModel": "基礎模型",
+            "baseModelSearchPlaceholder": "搜尋基礎模型...",
             "modelTags": "標籤（前 20）",
             "modelTypes": "模型類型",
             "license": "授權",
             "noCreditRequired": "無需署名",
             "allowSellingGeneratedContent": "允許銷售",
             "noTags": "無標籤",
+            "noBaseModelMatches": "沒有基礎模型符合目前的搜尋。",
             "clearAll": "清除所有篩選",
             "any": "任一",
             "all": "全部",
@@ -250,6 +256,33 @@
         "civitaiApiKey": "Civitai API 金鑰",
         "civitaiApiKeyPlaceholder": "請輸入您的 Civitai API 金鑰",
         "civitaiApiKeyHelp": "用於從 Civitai 下載模型時的身份驗證",
+        "civitaiHost": {
+            "label": "Civitai 站點",
+            "help": "選擇使用「在 Civitai 中查看」時預設開啟的 Civitai 站點。",
+            "options": {
+                "com": "civitai.com（僅 SFW）",
+                "red": "civitai.red（無限制）"
+            }
+        },
+        "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。",
+            "options": {
+                "python": "Python（內建）",
+                "aria2": "aria2（實驗性）"
+            }
+        },
+        "aria2cPath": {
+            "label": "aria2c 路徑",
+            "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。",
+            "openSettings": "開啟設定"
+        },
         "openSettingsFileLocation": {
             "label": "開啟設定資料夾",
             "tooltip": "開啟包含 settings.json 的資料夾",
@@ -260,6 +293,7 @@
         },
         "sections": {
             "contentFiltering": "內容過濾",
+            "downloads": "下載",
             "videoSettings": "影片設定",
             "layoutSettings": "版面設定",
             "misc": "其他",
@@ -395,6 +429,8 @@
                 "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",
@@ -506,6 +542,21 @@
             "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",
@@ -636,7 +687,10 @@
             "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",
             "clear": "清除選取",
             "skipMetadataRefreshCount": "跳過（{count} 個模型）",
@@ -667,6 +721,7 @@
             "moveToFolder": "移動到資料夾",
             "repairMetadata": "修復元數據",
             "excludeModel": "排除模型",
+            "restoreModel": "還原模型",
             "deleteModel": "刪除模型",
             "shareRecipe": "分享配方",
             "viewAllLoras": "檢視全部 LoRA",
@@ -957,6 +1012,8 @@
             "earlyAccess": "早期存取",
             "earlyAccessTooltip": "需要早期存取",
             "inLibrary": "已在庫存",
+            "downloaded": "已下載",
+            "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]",
             "errors": {
@@ -1155,6 +1212,8 @@
                 "cancel": "取消編輯",
                 "save": "儲存變更",
                 "addPlaceholder": "輸入或點擊下方建議",
+                "editWord": "編輯觸發詞",
+                "editPlaceholder": "編輯觸發詞",
                 "copyWord": "複製觸發詞",
                 "deleteWord": "刪除觸發詞",
                 "suggestions": {
@@ -1226,17 +1285,33 @@
                     "days": "{count}天後"
                 },
                 "badges": {
-                    "current": "目前版本",
+                    "current": "已開啟版本",
+                    "currentTooltip": "這是你用來開啟此彈窗的版本",
                     "inLibrary": "已在庫中",
+                    "inLibraryTooltip": "此版本已存在於你的本地庫中",
+                    "downloaded": "已下載",
+                    "downloadedTooltip": "此版本之前下載過，但目前不在你的本地庫中",
                     "newer": "較新版本",
+                    "newerTooltip": "此版本比你本地的最新版本更新",
                     "earlyAccess": "搶先體驗",
-                    "ignored": "已忽略"
+                    "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",
+                    "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",
                     "unignore": "取消忽略",
+                    "ignoreTooltip": "忽略此版本的更新通知",
+                    "unignoreTooltip": "恢復此版本的更新通知",
+                    "viewVersionOnCivitai": "在 Civitai 上查看版本",
                     "earlyAccessTooltip": "需要購買搶先體驗",
                     "resumeModelUpdates": "恢復追蹤此模型的更新",
                     "ignoreModelUpdates": "忽略此模型的更新",
@@ -1392,6 +1467,10 @@
             "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。",
@@ -1623,6 +1702,11 @@
             "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",
@@ -1713,8 +1797,8 @@
         },
         "triggerWords": {
             "loadFailed": "無法載入訓練詞",
-            "tooLong": "觸發詞不可超過 100 個字",
-            "tooMany": "最多允許 30 個觸發詞",
+            "tooLong": "觸發詞不可超過 500 個字",
+            "tooMany": "最多允許 100 個觸發詞",
             "alreadyExists": "此觸發詞已存在",
             "updateSuccess": "觸發詞已更新",
             "updateFailed": "更新觸發詞失敗",
@@ -1775,6 +1859,8 @@
             "deleteFailed": "刪除 {type} 失敗：{message}",
             "excludeSuccess": "{type} 已成功排除",
             "excludeFailed": "排除 {type} 失敗：{message}",
+            "restoreSuccess": "{type} 已成功還原",
+            "restoreFailed": "還原 {type} 失敗：{message}",
             "fileNameUpdated": "檔案名稱已成功更新",
             "fileRenameFailed": "重新命名檔案失敗：{error}",
             "previewUpdated": "預覽圖片已成功更新",
@@ -1832,7 +1918,9 @@
             "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}"
         }
     },
     "banners": {

py/config.py

@@ -1,5 +1,6 @@
 import os
 import platform
+import posixpath
 import threading
 from pathlib import Path
 import folder_paths  # type: ignore
@@ -25,21 +26,57 @@ standalone_mode = (
 logger = logging.getLogger(__name__)
 
 
+def _normalize_root_identity(path: str) -> str:
+    """Normalize a root path for comparisons across slash styles."""
+
+    normalized = posixpath.normpath(path.strip().replace("\\", "/"))
+    if len(normalized) >= 2 and normalized[1] == ":":
+        return normalized.lower()
+    return normalized
+
+
 def _resolve_valid_default_root(
-    current: str, primary_paths: List[str], name: str
+    current: str, primary_paths: List[str], allowed_paths: List[str], name: str
 ) -> str:
-    """Return a valid default root from the current primary path set."""
+    """Return a valid default root from the current primary/extra path set."""
 
     valid_paths = [path for path in primary_paths if isinstance(path, str) and path.strip()]
-    if not valid_paths:
-        return ""
+    fallback_paths: List[str] = []
+    seen: Set[str] = set()
+    for path in allowed_paths:
+        if not isinstance(path, str):
+            continue
+        stripped = path.strip()
+        if not stripped:
+            continue
+        identity = _normalize_root_identity(stripped)
+        if identity in seen:
+            continue
+        seen.add(identity)
+        fallback_paths.append(stripped)
 
-    if current in valid_paths:
+    allowed = {_normalize_root_identity(path) for path in fallback_paths}
+
+    if current and _normalize_root_identity(current) in allowed:
         return current
 
+    if not valid_paths:
+        if not fallback_paths:
+            return ""
+        if current:
+            logger.info(
+                "Repaired stale %s from '%s' to '%s' because it is not present in primary or extra roots",
+                name,
+                current,
+                fallback_paths[0],
+            )
+        else:
+            logger.info("Auto-setting %s to '%s'", name, fallback_paths[0])
+        return fallback_paths[0]
+
     if current:
         logger.info(
-            "Repaired stale %s from '%s' to '%s'",
+            "Repaired stale %s from '%s' to '%s' because it is not present in primary or extra roots",
             name,
             current,
             valid_paths[0],
@@ -226,39 +263,76 @@ class Config:
             default_lora_root = _resolve_valid_default_root(
                 comfy_library.get("default_lora_root", ""),
                 list(self.loras_roots or []),
+                list(self.loras_roots or [])
+                + list(comfy_library.get("extra_folder_paths", {}).get("loras", []) or []),
                 "default_lora_root",
             )
 
             default_checkpoint_root = _resolve_valid_default_root(
                 comfy_library.get("default_checkpoint_root", ""),
                 list(self.checkpoints_roots or []),
+                list(self.checkpoints_roots or [])
+                + list(comfy_library.get("extra_folder_paths", {}).get("checkpoints", []) or []),
                 "default_checkpoint_root",
             )
 
             default_embedding_root = _resolve_valid_default_root(
                 comfy_library.get("default_embedding_root", ""),
                 list(self.embeddings_roots or []),
+                list(self.embeddings_roots or [])
+                + list(comfy_library.get("extra_folder_paths", {}).get("embeddings", []) or []),
                 "default_embedding_root",
             )
 
             metadata = dict(comfy_library.get("metadata", {}))
             metadata.setdefault("display_name", "ComfyUI")
             metadata["source"] = "comfyui"
+            extra_folder_paths = {}
+            if isinstance(comfy_library, Mapping):
+                existing_extra_paths = comfy_library.get("extra_folder_paths", {})
+                if isinstance(existing_extra_paths, Mapping):
+                    extra_folder_paths = {
+                        key: list(value) if isinstance(value, list) else []
+                        for key, value in existing_extra_paths.items()
+                    }
+
+            active_library_name = settings_service.get_active_library_name()
+            should_activate = (
+                active_library_name == "comfyui"
+                or self._should_activate_comfy_library(libraries, libraries_changed)
+            )
 
             settings_service.upsert_library(
                 "comfyui",
                 folder_paths=target_folder_paths,
+                extra_folder_paths=extra_folder_paths,
                 default_lora_root=default_lora_root,
                 default_checkpoint_root=default_checkpoint_root,
                 default_embedding_root=default_embedding_root,
                 metadata=metadata,
-                activate=True,
+                activate=should_activate,
             )
 
-            logger.info("Updated 'comfyui' library with current folder paths")
+            if should_activate:
+                logger.info("Updated 'comfyui' library with current folder paths")
+            else:
+                logger.info(
+                    "Updated 'comfyui' library with current folder paths without activating it"
+                )
         except Exception as e:
             logger.warning(f"Failed to save folder paths: {e}")
 
+    def _should_activate_comfy_library(
+        self, libraries: Mapping[str, Any], libraries_changed: bool
+    ) -> bool:
+        """Return whether startup sync should make the ComfyUI library active."""
+
+        if libraries_changed:
+            return True
+        if not libraries:
+            return True
+        return "comfyui" in libraries and len(libraries) == 1
+
     def _is_link(self, path: str) -> bool:
         try:
             if os.path.islink(path):

py/metadata_collector/metadata_processor.py

@@ -352,50 +352,101 @@ 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]):
-            
+            "pos_conditioning" in metadata[PROMPTS][sampler_id] or
+            "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 find_prompt_text_for_conditioning(conditioning_obj, is_positive=True):
+
+            def extend_unique(target, values):
+                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 "conditioning" in prompt_data:
-                        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)
-                    if is_positive and "positive_encoded" in prompt_data:
-                        if id(prompt_data["positive_encoded"]) == id(conditioning_obj):
-                            if "positive_text" in prompt_data:
-                                return prompt_data["positive_text"]
-                            else:
-                                orig_conditioning = prompt_data.get("orig_pos_cond", None)
-                                if orig_conditioning is not None:
-                                    # Recursively find the prompt text for the original conditioning
-                                    return find_prompt_text_for_conditioning(orig_conditioning, is_positive=True)
-                    
-                    if not is_positive and "negative_encoded" in prompt_data:
-                        if id(prompt_data["negative_encoded"]) == id(conditioning_obj):
-                            if "negative_text" in prompt_data:
-                                return prompt_data["negative_text"]
-                            else:
-                                orig_conditioning = prompt_data.get("orig_neg_cond", None)
-                                if orig_conditioning is not None:
-                                    # Recursively find the prompt text for the original conditioning
-                                    return find_prompt_text_for_conditioning(orig_conditioning, is_positive=False)
-                
-                return ""
-            
+                    if not isinstance(prompt_data, dict):
+                        continue
+
+                    # For CLIP text nodes with a single conditioning output.
+                    if id(prompt_data.get("conditioning")) == conditioning_id:
+                        text = prompt_data.get("text", "")
+                        if 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:
+                            extend_unique(
+                                prompt_texts,
+                                find_prompt_texts_for_conditioning(
+                                    prompt_data.get("orig_pos_cond"),
+                                    is_positive=True,
+                                    visited=visited,
+                                ),
+                            )
+
+                    if (
+                        not is_positive
+                        and id(prompt_data.get("negative_encoded")) == conditioning_id
+                    ):
+                        if prompt_data.get("negative_text"):
+                            extend_unique(prompt_texts, [prompt_data["negative_text"]])
+                        else:
+                            extend_unique(
+                                prompt_texts,
+                                find_prompt_texts_for_conditioning(
+                                    prompt_data.get("orig_neg_cond"),
+                                    is_positive=False,
+                                    visited=visited,
+                                ),
+                            )
+
+                return prompt_texts
+
             # Find prompt texts using the helper function
-            result["prompt"] = find_prompt_text_for_conditioning(pos_conditioning, is_positive=True)
-            result["negative_prompt"] = find_prompt_text_for_conditioning(neg_conditioning, is_positive=False)
+            result["prompt"] = ", ".join(
+                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
-        params["clip_skip"] = "1"  # Common default
+        # Extract clip_skip from any SAMPLING node that provides it
+        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/prompt.py

@@ -1,15 +1,38 @@
+from __future__ import annotations
+
 from typing import Any
 import inspect
 
+from ..services.wildcard_service import (
+    contains_dynamic_syntax,
+    get_wildcard_service,
+    is_trigger_words_input,
+)
 
-class _AllContainer:
-    """Container that accepts any key for dynamic input validation."""
 
-    def __contains__(self, item):
-        return True
+class _PromptOptionalInputs:
+    """Lookup that preserves explicit optional inputs and dynamic trigger slots."""
 
-    def __getitem__(self, key):
-        return ("STRING", {"forceInput": True})
+    def __init__(self, explicit_inputs: dict[str, tuple[str, dict[str, Any]]]) -> None:
+        self._explicit_inputs = explicit_inputs
+
+    def __contains__(self, item: object) -> bool:
+        if not isinstance(item, str):
+            return False
+        return item in self._explicit_inputs or is_trigger_words_input(item)
+
+    def __getitem__(self, key: str) -> tuple[str, dict[str, Any]]:
+        if key in self._explicit_inputs:
+            return self._explicit_inputs[key]
+        if is_trigger_words_input(key):
+            return (
+                "STRING",
+                {
+                    "forceInput": True,
+                    "tooltip": "Trigger words to prepend. Connect to add more inputs.",
+                },
+            )
+        raise KeyError(key)
 
 
 class PromptLM:
@@ -20,12 +43,19 @@ class PromptLM:
     DESCRIPTION = (
         "Encodes a text prompt using a CLIP model into an embedding that can be used "
         "to guide the diffusion model towards generating specific images. "
-        "Supports dynamic trigger words inputs."
+        "Supports dynamic trigger words inputs and runtime wildcard expansion."
     )
 
     @classmethod
     def INPUT_TYPES(cls):
-        dyn_inputs = {
+        optional_inputs: dict[str, tuple[str, dict[str, Any]]] = {
+            "seed": (
+                "INT",
+                {
+                    "forceInput": True,
+                    "tooltip": "Optional seed for wildcard generation. Leave unconnected for non-deterministic wildcard expansion.",
+                },
+            ),
             "trigger_words1": (
                 "STRING",
                 {
@@ -35,10 +65,9 @@ class PromptLM:
             ),
         }
 
-        # Bypass validation for dynamic inputs during graph execution
         stack = inspect.stack()
         if len(stack) > 2 and stack[2].function == "get_input_info":
-            dyn_inputs = _AllContainer()
+            optional_inputs = _PromptOptionalInputs(optional_inputs)  # type: ignore[assignment]
 
         return {
             "required": {
@@ -46,8 +75,8 @@ class PromptLM:
                     "AUTOCOMPLETE_TEXT_PROMPT,STRING",
                     {
                         "widgetType": "AUTOCOMPLETE_TEXT_PROMPT",
-                        "placeholder": "Enter prompt... /char, /artist for quick tag search",
-                        "tooltip": "The text to be encoded.",
+                        "placeholder": "Enter prompt... /character, /artist, /wildcard for quick search",
+                        "tooltip": "The text to be encoded. Wildcard references inserted with /wildcard are expanded at runtime.",
                     },
                 ),
                 "clip": (
@@ -55,7 +84,7 @@ class PromptLM:
                     {"tooltip": "The CLIP model used for encoding the text."},
                 ),
             },
-            "optional": dyn_inputs,
+            "optional": optional_inputs,
         }
 
     RETURN_TYPES = ("CONDITIONING", "STRING")
@@ -65,20 +94,39 @@ class PromptLM:
     )
     FUNCTION = "encode"
 
-    def encode(self, text: str, clip: Any, **kwargs):
-        # Collect all trigger words from dynamic inputs
+    @classmethod
+    def IS_CHANGED(
+        cls,
+        text: str,
+        clip: Any | None = None,
+        seed: int | None = None,
+        **kwargs: Any,
+    ):
+        del clip, kwargs
+        if contains_dynamic_syntax(text) and seed is None:
+            return float("NaN")
+        return False
+
+    def encode(
+        self,
+        text: str,
+        clip: Any,
+        seed: int | None = None,
+        **kwargs: Any,
+    ):
+        expanded_text = get_wildcard_service().expand_text(text, seed=seed)
+
         trigger_words = []
         for key, value in kwargs.items():
-            if key.startswith("trigger_words") and value:
+            if is_trigger_words_input(key) and value:
                 trigger_words.append(value)
 
-        # Build final prompt
         if trigger_words:
-            prompt = ", ".join(trigger_words + [text])
+            prompt = ", ".join(trigger_words + [expanded_text])
         else:
-            prompt = text
+            prompt = expanded_text
 
         from nodes import CLIPTextEncode  # type: ignore
 
         conditioning = CLIPTextEncode().encode(clip, prompt)[0]
-        return (conditioning, prompt)
+        return (conditioning, prompt)

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/text.py

@@ -1,10 +1,15 @@
+from __future__ import annotations
+
+from ..services.wildcard_service import contains_dynamic_syntax, get_wildcard_service
+
+
 class TextLM:
     """A simple text node with autocomplete support."""
 
     NAME = "Text (LoraManager)"
     CATEGORY = "Lora Manager/utils"
     DESCRIPTION = (
-        "A simple text input node with autocomplete support for tags and styles."
+        "A simple text input node with autocomplete support for tags, styles, and wildcard expansion."
     )
 
     @classmethod
@@ -15,8 +20,17 @@ class TextLM:
                     "AUTOCOMPLETE_TEXT_PROMPT,STRING",
                     {
                         "widgetType": "AUTOCOMPLETE_TEXT_PROMPT",
-                        "placeholder": "Enter text... /char, /artist for quick tag search",
-                        "tooltip": "The text output.",
+                        "placeholder": "Enter text... /character, /artist, /wildcard for quick search",
+                        "tooltip": "The text output. Wildcard references inserted with /wildcard are expanded at runtime.",
+                    },
+                ),
+            },
+            "optional": {
+                "seed": (
+                    "INT",
+                    {
+                        "forceInput": True,
+                        "tooltip": "Optional seed for wildcard generation. Leave unconnected for non-deterministic wildcard expansion.",
                     },
                 ),
             },
@@ -24,10 +38,14 @@ class TextLM:
 
     RETURN_TYPES = ("STRING",)
     RETURN_NAMES = ("STRING",)
-    OUTPUT_TOOLTIPS = (
-        "The text output.",
-    )
+    OUTPUT_TOOLTIPS = ("The text output.",)
     FUNCTION = "process"
 
-    def process(self, text: str):
-        return (text,)
+    @classmethod
+    def IS_CHANGED(cls, text: str, seed: int | None = None):
+        if contains_dynamic_syntax(text) and seed is None:
+            return float("NaN")
+        return False
+
+    def process(self, text: str, seed: int | None = None):
+        return (get_wildcard_service().expand_text(text, seed=seed),)

py/nodes/trigger_word_toggle.py

@@ -76,6 +76,9 @@ class TriggerWordToggleLM:
         # Filter out empty strings and return as set
         return set(word for word in words if word)
 
+    def _group_has_child_items(self, item):
+        return isinstance(item, dict) and isinstance(item.get("items"), list)
+
     def process_trigger_words(
         self,
         id,
@@ -112,7 +115,11 @@ class TriggerWordToggleLM:
 
                 if isinstance(trigger_data, list):
                     if group_mode:
-                        if allow_strength_adjustment:
+                        if any(self._group_has_child_items(item) for item in trigger_data):
+                            filtered_groups = self._process_group_items(
+                                trigger_data, allow_strength_adjustment
+                            )
+                        elif allow_strength_adjustment:
                             parsed_items = [
                                 self._parse_trigger_item(
                                     item, allow_strength_adjustment
@@ -174,6 +181,41 @@ class TriggerWordToggleLM:
 
         return (filtered_triggers,)
 
+    def _process_group_items(self, trigger_data, allow_strength_adjustment):
+        filtered_groups = []
+
+        for item in trigger_data:
+            group = self._parse_trigger_item(item, allow_strength_adjustment)
+            if not group["text"] or not group["active"]:
+                continue
+
+            raw_items = item.get("items") if isinstance(item, dict) else None
+            if isinstance(raw_items, list):
+                active_items = []
+                for raw_item in raw_items:
+                    child = self._parse_trigger_item(
+                        raw_item, allow_strength_adjustment=False
+                    )
+                    if child["text"] and child["active"]:
+                        active_items.append(child["text"])
+
+                if not active_items:
+                    continue
+
+                group_text = ", ".join(active_items)
+            else:
+                group_text = group["text"]
+
+            filtered_groups.append(
+                self._format_word_output(
+                    group_text,
+                    group["strength"],
+                    allow_strength_adjustment,
+                )
+            )
+
+        return filtered_groups
+
     def _parse_trigger_item(self, item, allow_strength_adjustment):
         text = (item.get("text") or "").strip()
         active = bool(item.get("active", False))

py/nodes/wanvideo_lora_select.py

@@ -1,10 +1,22 @@
-import folder_paths # type: ignore
-from ..utils.utils import get_lora_info
+import os
+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
-from ..utils.utils import get_lora_info
+import os
+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/enrichment.py

@@ -1,11 +1,11 @@
 import logging
 import json
-import re
 import os
 from typing import Any, Dict, Optional
 from .merger import GenParamsMerger
 from .base import RecipeMetadataParser
 from ..services.metadata_service import get_default_metadata_provider
+from ..utils.civitai_utils import extract_civitai_image_id
 
 logger = logging.getLogger(__name__)
 
@@ -39,11 +39,12 @@ class RecipeEnricher:
         source_url = recipe.get("source_url") or recipe.get("source_path", "")
         
         # Check if it's a Civitai image URL
-        image_id_match = re.search(r'civitai\.com/images/(\d+)', str(source_url))
-        if image_id_match:
-            image_id = image_id_match.group(1)
+        image_id = extract_civitai_image_id(str(source_url))
+        if image_id:
             try:
-                image_info = await civitai_client.get_image_info(image_id)
+                image_info = await civitai_client.get_image_info(
+                    image_id, source_url=str(source_url)
+                )
                 if image_info:
                     # Handle nested meta often found in Civitai API responses
                     raw_meta = image_info.get("meta")

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

@@ -13,6 +13,7 @@ import contextlib
 import io
 import json
 import logging
+import time
 import os
 import platform
 import re
@@ -32,15 +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,
 )
@@ -616,6 +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),
             ]
 
@@ -680,6 +685,145 @@ class DoctorHandler:
             status=status,
         )
 
+    async def resolve_filename_conflicts(self, request: web.Request) -> web.Response:
+        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()
@@ -845,6 +989,79 @@ class DoctorHandler:
             "actions": [{"id": "repair-cache", "label": "Rebuild Cache"}],
         }
 
+    async def _check_filename_conflicts(self) -> dict[str, Any]:
+        all_conflicts: list[dict[str, Any]] = []
+        total_conflict_groups = 0
+        total_conflict_files = 0
+
+        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 = 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,
+            }
+        ]
+        for conflict in all_conflicts:
+            details.append(
+                f"[{conflict['label']}] '{conflict['filename']}' "
+                f"found in {len(conflict['paths'])} locations"
+            )
+
+        return {
+            "id": "filename_conflicts",
+            "title": "Duplicate Filename Conflicts",
+            "status": "warning",
+            "summary": summary,
+            "details": details,
+            "actions": [
+                {
+                    "id": "resolve-filename-conflicts",
+                    "label": "Resolve Conflicts",
+                }
+            ],
+        }
+
     def _check_ui_version(self, client_version: str, app_version: str) -> dict[str, Any]:
         if client_version and client_version != app_version:
             return {
@@ -1575,29 +1792,33 @@ 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
-                if history_type:
-                    has_been_downloaded = await history_service.has_been_downloaded(
-                        history_type,
+                history_type = None
+                for candidate_type in ("lora", "checkpoint", "embedding"):
+                    if await history_service.has_been_downloaded(
+                        candidate_type,
                         model_version_id,
-                    )
-                else:
-                    for candidate_type in ("lora", "checkpoint", "embedding"):
-                        if await history_service.has_been_downloaded(
-                            candidate_type,
-                            model_version_id,
-                        ):
-                            has_been_downloaded = True
-                            history_type = candidate_type
-                            break
+                    ):
+                        has_been_downloaded = True
+                        history_type = candidate_type
+                        break
 
                 return web.json_response(
                     {
                         "success": True,
-                        "exists": exists,
-                        "modelType": model_type if exists else history_type,
+                        "exists": False,
+                        "modelType": history_type,
                         "hasBeenDownloaded": has_been_downloaded,
                     }
                 )
@@ -1617,40 +1838,46 @@ class ModelLibraryHandler:
             model_type = None
             versions = []
             downloaded_version_ids = []
-            history_service = await self._get_download_history_service()
             if lora_versions:
-                model_type = "lora"
-                versions = self._with_downloaded_flag(lora_versions)
-                downloaded_version_ids = await history_service.get_downloaded_version_ids(
-                    model_type,
-                    model_id,
+                return web.json_response(
+                    {
+                        "success": True,
+                        "modelType": "lora",
+                        "versions": self._with_downloaded_flag(lora_versions),
+                        "downloadedVersionIds": [],
+                    }
                 )
-            elif checkpoint_versions:
-                model_type = "checkpoint"
-                versions = self._with_downloaded_flag(checkpoint_versions)
-                downloaded_version_ids = await history_service.get_downloaded_version_ids(
-                    model_type,
-                    model_id,
+            if checkpoint_versions:
+                return web.json_response(
+                    {
+                        "success": True,
+                        "modelType": "checkpoint",
+                        "versions": self._with_downloaded_flag(checkpoint_versions),
+                        "downloadedVersionIds": [],
+                    }
                 )
-            elif embedding_versions:
-                model_type = "embedding"
-                versions = self._with_downloaded_flag(embedding_versions)
-                downloaded_version_ids = await history_service.get_downloaded_version_ids(
-                    model_type,
-                    model_id,
+            if embedding_versions:
+                return web.json_response(
+                    {
+                        "success": True,
+                        "modelType": "embedding",
+                        "versions": self._with_downloaded_flag(embedding_versions),
+                        "downloadedVersionIds": [],
+                    }
                 )
-            else:
-                for candidate_type in ("lora", "checkpoint", "embedding"):
-                    candidate_downloaded_version_ids = (
-                        await history_service.get_downloaded_version_ids(
-                            candidate_type,
-                            model_id,
-                        )
+
+            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(
+                        candidate_type,
+                        model_id,
                     )
-                    if candidate_downloaded_version_ids:
-                        model_type = candidate_type
-                        downloaded_version_ids = candidate_downloaded_version_ids
-                        break
+                )
+                if candidate_downloaded_version_ids:
+                    model_type = candidate_type
+                    downloaded_version_ids = candidate_downloaded_version_ids
+                    break
 
             return web.json_response(
                 {
@@ -1664,6 +1891,86 @@ 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:
@@ -1776,6 +2083,78 @@ 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()
+
+            history_service = await self._get_download_history_service()
+            await history_service.mark_not_downloaded(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")
@@ -2410,6 +2789,16 @@ class FileSystemHandler:
             logger.error("Failed to open backup location: %s", exc, exc_info=True)
             return web.json_response({"success": False, "error": str(exc)}, status=500)
 
+    async def open_wildcards_location(self, request: web.Request) -> web.Response:
+        try:
+            from ...services.wildcard_service import get_wildcards_dir
+
+            wildcards_dir = get_wildcards_dir(create=True)
+            return await self._open_path(wildcards_dir)
+        except Exception as exc:  # pragma: no cover - defensive logging
+            logger.error("Failed to open wildcards location: %s", exc, exc_info=True)
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
 
 class CustomWordsHandler:
     """Handler for autocomplete via TagFTSIndex."""
@@ -2489,6 +2878,41 @@ class CustomWordsHandler:
             return None
 
 
+class WildcardsHandler:
+    """Handler for wildcard autocomplete search."""
+
+    def __init__(self, *, service=None) -> None:
+        if service is None:
+            from ...services.wildcard_service import get_wildcard_service
+
+            service = get_wildcard_service()
+        self._service = service
+
+    async def search_wildcards(self, request: web.Request) -> web.Response:
+        """Search managed wildcard keys for autocomplete."""
+
+        try:
+            search_term = request.query.get("search", "")
+            limit = min(int(request.query.get("limit", "20")), 100)
+            offset = max(0, int(request.query.get("offset", "0")))
+            metadata = self._service.get_metadata(create_dir=True)
+            results = self._service.search_keys(search_term, limit=limit, offset=offset)
+            return web.json_response(
+                {
+                    "success": True,
+                    "words": results,
+                    "meta": {
+                        "has_wildcards": metadata.has_wildcards,
+                        "wildcards_dir": metadata.wildcards_dir,
+                        "supported_formats": list(metadata.supported_formats),
+                    },
+                }
+            )
+        except Exception as exc:
+            logger.error("Error searching wildcards: %s", exc, exc_info=True)
+            return web.json_response({"error": str(exc)}, status=500)
+
+
 class NodeRegistryHandler:
     def __init__(
         self,
@@ -2717,6 +3141,7 @@ class MiscHandlerSet:
         backup: BackupHandler,
         filesystem: FileSystemHandler,
         custom_words: CustomWordsHandler,
+        wildcards: WildcardsHandler,
         supporters: SupportersHandler,
         doctor: DoctorHandler,
         example_workflows: ExampleWorkflowsHandler,
@@ -2734,6 +3159,7 @@ class MiscHandlerSet:
         self.backup = backup
         self.filesystem = filesystem
         self.custom_words = custom_words
+        self.wildcards = wildcards
         self.supporters = supporters
         self.doctor = doctor
         self.example_workflows = example_workflows
@@ -2748,6 +3174,7 @@ 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,
@@ -2761,8 +3188,10 @@ 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,
@@ -2774,7 +3203,9 @@ class MiscHandlerSet:
             "open_file_location": self.filesystem.open_file_location,
             "open_settings_location": self.filesystem.open_settings_location,
             "open_backup_location": self.filesystem.open_backup_location,
+            "open_wildcards_location": self.filesystem.open_wildcards_location,
             "search_custom_words": self.custom_words.search_custom_words,
+            "search_wildcards": self.wildcards.search_wildcards,
             "get_supporters": self.supporters.get_supporters,
             "get_example_workflows": self.example_workflows.get_example_workflows,
             "get_example_workflow": self.example_workflows.get_example_workflow,

py/routes/handlers/model_handlers.py

@@ -16,9 +16,14 @@ import jinja2
 
 from ...config import config
 from ...services.download_coordinator import DownloadCoordinator
+from ...services.connectivity_guard import (
+    OFFLINE_FRIENDLY_MESSAGE,
+    is_expected_offline_error,
+)
 from ...services.metadata_sync_service import MetadataSyncService
 from ...services.model_file_service import ModelMoveService
 from ...services.preview_asset_service import PreviewAssetService
+from ...services.service_registry import ServiceRegistry
 from ...services.settings_manager import SettingsManager, get_settings_manager
 from ...services.tag_update_service import TagUpdateService
 from ...services.use_cases import (
@@ -223,6 +228,42 @@ class ModelListingHandler:
             )
             return web.json_response({"error": str(exc)}, status=500)
 
+    async def get_excluded_models(self, request: web.Request) -> web.Response:
+        start_time = time.perf_counter()
+        try:
+            params = self._parse_common_params(request)
+            result = await self._service.get_excluded_paginated_data(**params)
+
+            format_start = time.perf_counter()
+            formatted_result = {
+                "items": [
+                    await self._service.format_response(item)
+                    for item in result["items"]
+                ],
+                "total": result["total"],
+                "page": result["page"],
+                "page_size": result["page_size"],
+                "total_pages": result["total_pages"],
+            }
+            format_duration = time.perf_counter() - format_start
+
+            duration = time.perf_counter() - start_time
+            self._logger.debug(
+                "Request for %s/excluded took %.3fs (formatting: %.3fs)",
+                self._service.model_type,
+                duration,
+                format_duration,
+            )
+            return web.json_response(formatted_result)
+        except Exception as exc:
+            self._logger.error(
+                "Error retrieving excluded %ss: %s",
+                self._service.model_type,
+                exc,
+                exc_info=True,
+            )
+            return web.json_response({"error": str(exc)}, status=500)
+
     def _parse_common_params(self, request: web.Request) -> Dict:
         page = int(request.query.get("page", "1"))
         page_size = min(int(request.query.get("page_size", "20")), 100)
@@ -391,6 +432,21 @@ class ModelManagementHandler:
             self._logger.error("Error excluding model: %s", exc, exc_info=True)
             return web.Response(text=str(exc), status=500)
 
+    async def unexclude_model(self, request: web.Request) -> web.Response:
+        try:
+            data = await request.json()
+            file_path = data.get("file_path")
+            if not file_path:
+                return web.Response(text="Model path is required", status=400)
+
+            result = await self._lifecycle_service.unexclude_model(file_path)
+            return web.json_response(result)
+        except ValueError as exc:
+            return web.json_response({"success": False, "error": str(exc)}, status=400)
+        except Exception as exc:
+            self._logger.error("Error restoring model: %s", exc, exc_info=True)
+            return web.Response(text=str(exc), status=500)
+
     async def fetch_civitai(self, request: web.Request) -> web.Response:
         try:
             data = await request.json()
@@ -452,6 +508,11 @@ class ModelManagementHandler:
             formatted_metadata = await self._service.format_response(model_data)
             return web.json_response({"success": True, "metadata": formatted_metadata})
         except Exception as exc:
+            if is_expected_offline_error(str(exc)):
+                return web.json_response(
+                    {"success": False, "error": OFFLINE_FRIENDLY_MESSAGE},
+                    status=503,
+                )
             self._logger.error("Error fetching from CivitAI: %s", exc, exc_info=True)
             return web.json_response({"success": False, "error": str(exc)}, status=500)
 
@@ -498,6 +559,11 @@ class ModelManagementHandler:
                 }
             )
         except Exception as exc:
+            if is_expected_offline_error(str(exc)):
+                return web.json_response(
+                    {"success": False, "error": OFFLINE_FRIENDLY_MESSAGE},
+                    status=503,
+                )
             self._logger.error("Error re-linking to CivitAI: %s", exc, exc_info=True)
             return web.json_response({"success": False, "error": str(exc)}, status=500)
 
@@ -858,7 +924,7 @@ class ModelQueryHandler:
     async def get_base_models(self, request: web.Request) -> web.Response:
         try:
             limit = int(request.query.get("limit", "20"))
-            if limit < 1 or limit > 100:
+            if limit < 0 or limit > 100:
                 limit = 20
             base_models = await self._service.get_base_models(limit)
             return web.json_response({"success": True, "base_models": base_models})
@@ -1531,6 +1597,20 @@ class ModelCivitaiHandler:
 
             cache = await self._service.scanner.get_cached_data()
             version_index = cache.version_index
+            downloaded_version_ids: set[int] = set()
+            try:
+                history_service = await ServiceRegistry.get_downloaded_version_history_service()
+                downloaded_version_ids = set(
+                    await history_service.get_downloaded_version_ids(
+                        self._service.model_type,
+                        model_id,
+                    )
+                )
+            except Exception as exc:  # pragma: no cover - defensive logging
+                self._logger.debug(
+                    "Failed to load download history for CivitAI versions: %s",
+                    exc,
+                )
 
             for version in versions:
                 version_id = None
@@ -1547,6 +1627,9 @@ class ModelCivitaiHandler:
                     else None
                 )
                 version["existsLocally"] = cache_entry is not None
+                version["hasBeenDownloaded"] = (
+                    version_id in downloaded_version_ids if version_id is not None else False
+                )
                 if cache_entry and isinstance(cache_entry, Mapping):
                     local_path = cache_entry.get("file_path")
                     if local_path:
@@ -1789,6 +1872,11 @@ class ModelUpdateHandler:
                 status=429,
             )
         except Exception as exc:  # pragma: no cover - defensive log
+            if is_expected_offline_error(str(exc)):
+                return web.json_response(
+                    {"success": False, "error": OFFLINE_FRIENDLY_MESSAGE},
+                    status=503,
+                )
             self._logger.error("Failed to fetch license info: %s", exc, exc_info=True)
             return web.json_response({"success": False, "error": str(exc)}, status=500)
 
@@ -1877,9 +1965,12 @@ class ModelUpdateHandler:
                 {"success": False, "error": str(exc) or "Rate limited"}, status=429
             )
         except Exception as exc:  # pragma: no cover - defensive logging
-            self._logger.error(
-                "Failed to refresh model updates: %s", exc, exc_info=True
-            )
+            if is_expected_offline_error(str(exc)):
+                return web.json_response(
+                    {"success": False, "error": OFFLINE_FRIENDLY_MESSAGE},
+                    status=503,
+                )
+            self._logger.error("Failed to refresh model updates: %s", exc, exc_info=True)
             return web.json_response({"success": False, "error": str(exc)}, status=500)
 
         serialized_records = []
@@ -2265,7 +2356,7 @@ class ModelUpdateHandler:
         self,
         record,
         *,
-        version_context: Optional[Dict[int, Dict[str, Optional[str]]]] = None,
+        version_context: Optional[Dict[int, Dict[str, Any]]] = None,
     ) -> Dict:
         context = version_context or {}
         # Check user setting for hiding early access versions
@@ -2294,7 +2385,7 @@ class ModelUpdateHandler:
 
     @staticmethod
     def _serialize_version(
-        version, context: Optional[Dict[str, Optional[str]]]
+        version, context: Optional[Dict[str, Any]]
     ) -> Dict:
         context = context or {}
         preview_override = context.get("preview_override")
@@ -2328,17 +2419,42 @@ class ModelUpdateHandler:
             "sizeBytes": version.size_bytes,
             "previewUrl": preview_url,
             "isInLibrary": version.is_in_library,
+            "hasBeenDownloaded": bool(context.get("has_been_downloaded", False)),
             "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"),
         }
 
     async def _build_version_context(
         self, record
-    ) -> Dict[int, Dict[str, Optional[str]]]:
-        context: Dict[int, Dict[str, Optional[str]]] = {}
+    ) -> Dict[int, Dict[str, Any]]:
+        context: Dict[int, Dict[str, Any]] = {}
+        downloaded_version_ids: set[int] = set()
+        try:
+            history_service = await ServiceRegistry.get_downloaded_version_history_service()
+            downloaded_version_ids = set(
+                await history_service.get_downloaded_version_ids(
+                    record.model_type,
+                    record.model_id,
+                )
+            )
+        except Exception as exc:  # pragma: no cover - defensive logging
+            self._logger.debug(
+                "Failed to load download history while building version context: %s",
+                exc,
+            )
+
+        for version in record.versions:
+            context[version.version_id] = {
+                "file_path": None,
+                "file_name": None,
+                "preview_override": None,
+                "has_been_downloaded": version.version_id in downloaded_version_ids,
+            }
+
         try:
             cache = await self._service.scanner.get_cached_data()
         except Exception as exc:  # pragma: no cover - defensive logging
@@ -2357,16 +2473,21 @@ class ModelUpdateHandler:
             cache_entry = version_index.get(version.version_id)
             if isinstance(cache_entry, Mapping):
                 preview = cache_entry.get("preview_url")
-                context_entry: Dict[str, Optional[str]] = {
-                    "file_path": cache_entry.get("file_path"),
-                    "file_name": cache_entry.get("file_name"),
-                    "preview_override": None,
-                }
+                context_entry = context.setdefault(
+                    version.version_id,
+                    {
+                        "file_path": None,
+                        "file_name": None,
+                        "preview_override": None,
+                        "has_been_downloaded": version.version_id in downloaded_version_ids,
+                    },
+                )
+                context_entry["file_path"] = cache_entry.get("file_path")
+                context_entry["file_name"] = cache_entry.get("file_name")
                 if isinstance(preview, str) and preview:
                     context_entry["preview_override"] = config.get_preview_static_url(
                         preview
                     )
-                context[version.version_id] = context_entry
         return context
 
 
@@ -2390,8 +2511,10 @@ class ModelHandlerSet:
         return {
             "handle_models_page": self.page_view.handle,
             "get_models": self.listing.get_models,
+            "get_excluded_models": self.listing.get_excluded_models,
             "delete_model": self.management.delete_model,
             "exclude_model": self.management.exclude_model,
+            "unexclude_model": self.management.unexclude_model,
             "fetch_civitai": self.management.fetch_civitai,
             "fetch_all_civitai": self.civitai.fetch_all_civitai,
             "relink_civitai": self.management.relink_civitai,

py/routes/handlers/recipe_handlers.py

@@ -26,7 +26,7 @@ from ...services.recipes import (
     RecipeValidationError,
 )
 from ...services.metadata_service import get_default_metadata_provider
-from ...utils.civitai_utils import rewrite_preview_url
+from ...utils.civitai_utils import extract_civitai_image_id, rewrite_preview_url
 from ...utils.exif_utils import ExifUtils
 from ...recipes.merger import GenParamsMerger
 from ...recipes.enrichment import RecipeEnricher
@@ -329,6 +329,7 @@ class RecipeQueryHandler:
             if recipe_scanner is None:
                 raise RuntimeError("Recipe scanner unavailable")
 
+            limit = int(request.query.get("limit", "20"))
             cache = await recipe_scanner.get_cached_data()
 
             base_model_counts: Dict[str, int] = {}
@@ -344,6 +345,8 @@ class RecipeQueryHandler:
                 for model, count in base_model_counts.items()
             ]
             sorted_models.sort(key=lambda entry: entry["count"], reverse=True)
+            if limit > 0:
+                sorted_models = sorted_models[:limit]
             return web.json_response({"success": True, "base_models": sorted_models})
         except Exception as exc:
             self._logger.error("Error retrieving base models: %s", exc, exc_info=True)
@@ -1196,13 +1199,15 @@ class RecipeManagementHandler:
                 temp_path = temp_file.name
             download_url = image_url
             image_info = None
-            civitai_match = re.match(r"https://civitai\.com/images/(\d+)", image_url)
-            if civitai_match:
+            civitai_image_id = extract_civitai_image_id(image_url)
+            if civitai_image_id:
                 if civitai_client is None:
                     raise RecipeDownloadError(
                         "Civitai client unavailable for image download"
                     )
-                image_info = await civitai_client.get_image_info(civitai_match.group(1))
+                image_info = await civitai_client.get_image_info(
+                    civitai_image_id, source_url=image_url
+                )
                 if not image_info:
                     raise RecipeDownloadError(
                         "Failed to fetch image information from Civitai"
@@ -1236,7 +1241,7 @@ class RecipeManagementHandler:
                 return (
                     file_obj.read(),
                     extension,
-                    image_info.get("meta") if civitai_match and image_info else None,
+                    image_info.get("meta") if civitai_image_id and image_info else None,
                 )
         except RecipeDownloadError:
             raise

py/routes/misc_route_registrar.py

@@ -24,12 +24,15 @@ 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"),
     RouteDefinition("POST", "/api/lm/settings/libraries/activate", "activate_library"),
     RouteDefinition("GET", "/api/lm/health-check", "health_check"),
     RouteDefinition("GET", "/api/lm/supporters", "get_supporters"),
+    RouteDefinition("GET", "/api/lm/wildcards/search", "search_wildcards"),
+    RouteDefinition("POST", "/api/lm/wildcards/open-location", "open_wildcards_location"),
     RouteDefinition("POST", "/api/lm/open-file-location", "open_file_location"),
     RouteDefinition("POST", "/api/lm/update-usage-stats", "update_usage_stats"),
     RouteDefinition("GET", "/api/lm/get-usage-stats", "get_usage_stats"),
@@ -40,6 +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",
@@ -87,6 +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/misc_routes.py

@@ -35,6 +35,7 @@ from .handlers.misc_handlers import (
     SupportersHandler,
     TrainedWordsHandler,
     UsageStatsHandler,
+    WildcardsHandler,
     build_service_registry_adapter,
 )
 from .handlers.base_model_handlers import BaseModelHandlerSet
@@ -130,6 +131,7 @@ class MiscRoutes:
             metadata_provider_factory=self._metadata_provider_factory,
         )
         custom_words = CustomWordsHandler()
+        wildcards = WildcardsHandler()
         supporters = SupportersHandler()
         doctor = DoctorHandler(settings_service=self._settings)
         example_workflows = ExampleWorkflowsHandler()
@@ -148,6 +150,7 @@ class MiscRoutes:
             backup=backup,
             filesystem=filesystem,
             custom_words=custom_words,
+            wildcards=wildcards,
             supporters=supporters,
             doctor=doctor,
             example_workflows=example_workflows,

py/routes/model_route_registrar.py

@@ -22,8 +22,10 @@ class RouteDefinition:
 
 COMMON_ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
     RouteDefinition("GET", "/api/lm/{prefix}/list", "get_models"),
+    RouteDefinition("GET", "/api/lm/{prefix}/excluded", "get_excluded_models"),
     RouteDefinition("POST", "/api/lm/{prefix}/delete", "delete_model"),
     RouteDefinition("POST", "/api/lm/{prefix}/exclude", "exclude_model"),
+    RouteDefinition("POST", "/api/lm/{prefix}/unexclude", "unexclude_model"),
     RouteDefinition("POST", "/api/lm/{prefix}/fetch-civitai", "fetch_civitai"),
     RouteDefinition("POST", "/api/lm/{prefix}/fetch-all-civitai", "fetch_all_civitai"),
     RouteDefinition("POST", "/api/lm/{prefix}/relink-civitai", "relink_civitai"),

py/services/aria2_downloader.py

@@ -0,0 +1,570 @@
+from __future__ import annotations
+
+import asyncio
+import json
+import logging
+import os
+import secrets
+import shutil
+import socket
+from dataclasses import dataclass
+from datetime import datetime
+from pathlib import Path
+from typing import Any, Dict, Optional, Tuple
+
+import aiohttp
+
+from .downloader import DownloadProgress, get_downloader
+from .aria2_transfer_state import Aria2TransferStateStore
+from .settings_manager import get_settings_manager
+
+logger = logging.getLogger(__name__)
+
+CIVITAI_DOWNLOAD_URL_PREFIXES = (
+    "https://civitai.com/api/download/",
+    "https://civitai.red/api/download/",
+)
+
+
+class Aria2Error(RuntimeError):
+    """Raised when aria2 integration fails."""
+
+
+@dataclass
+class Aria2Transfer:
+    """Track an aria2 download registered by the Python coordinator."""
+
+    gid: str
+    save_path: str
+
+
+class Aria2Downloader:
+    """Manage an aria2 RPC daemon for experimental model downloads."""
+
+    _instance = None
+    _lock = asyncio.Lock()
+
+    @classmethod
+    async def get_instance(cls) -> "Aria2Downloader":
+        async with cls._lock:
+            if cls._instance is None:
+                cls._instance = cls()
+            return cls._instance
+
+    def __init__(self) -> None:
+        if hasattr(self, "_initialized"):
+            return
+
+        self._initialized = True
+        self._process: Optional[asyncio.subprocess.Process] = None
+        self._rpc_port: Optional[int] = None
+        self._rpc_secret = ""
+        self._rpc_url = ""
+        self._rpc_session: Optional[aiohttp.ClientSession] = None
+        self._rpc_session_lock = asyncio.Lock()
+        self._process_lock = asyncio.Lock()
+        self._transfers: Dict[str, Aria2Transfer] = {}
+        self._poll_interval = 0.5
+        self._state_store = Aria2TransferStateStore()
+
+    @property
+    def is_running(self) -> bool:
+        return self._process is not None and self._process.returncode is None
+
+    async def download_file(
+        self,
+        url: str,
+        save_path: str,
+        *,
+        download_id: str,
+        progress_callback=None,
+        headers: Optional[Dict[str, str]] = None,
+    ) -> Tuple[bool, str]:
+        """Download a file using aria2 RPC and wait for completion."""
+
+        await self._ensure_process()
+        save_path = os.path.abspath(save_path)
+        transfer = self._transfers.get(download_id)
+        if transfer is None or os.path.abspath(transfer.save_path) != save_path:
+            gid = await self._schedule_download(
+                url,
+                save_path,
+                download_id=download_id,
+                headers=headers,
+            )
+            transfer = Aria2Transfer(gid=gid, save_path=save_path)
+            self._transfers[download_id] = transfer
+
+        try:
+            while True:
+                status = await self.get_status(download_id)
+                if status is None:
+                    return False, "aria2 download not found"
+
+                snapshot = self._build_progress_snapshot(status)
+                if progress_callback is not None:
+                    await self._dispatch_progress(progress_callback, snapshot)
+
+                state = status.get("status", "")
+                if state == "complete":
+                    completed_path = self._resolve_completed_path(status, save_path)
+                    return True, completed_path
+                if state == "error":
+                    return False, status.get("errorMessage") or "aria2 download failed"
+                if state == "removed":
+                    return False, "Download was cancelled"
+
+                await asyncio.sleep(self._poll_interval)
+        finally:
+            self._transfers.pop(download_id, None)
+
+    async def _schedule_download(
+        self,
+        url: str,
+        save_path: str,
+        *,
+        download_id: str,
+        headers: Optional[Dict[str, str]] = None,
+    ) -> str:
+        save_dir = os.path.dirname(save_path)
+        out_name = os.path.basename(save_path)
+
+        Path(save_dir).mkdir(parents=True, exist_ok=True)
+
+        resolved_url = url
+        request_headers = headers
+        if headers and url.startswith(CIVITAI_DOWNLOAD_URL_PREFIXES):
+            resolved_url = await self._resolve_authenticated_redirect_url(url, headers)
+            if resolved_url != url:
+                request_headers = None
+                logger.debug(
+                    "Resolved Civitai download %s to signed URL for aria2",
+                    download_id,
+                )
+
+        options: Dict[str, str] = {
+            "dir": save_dir,
+            "out": out_name,
+            "continue": "true",
+            "max-connection-per-server": "4",
+            "split": "4",
+            "min-split-size": "1M",
+            "allow-overwrite": "true",
+            "auto-file-renaming": "false",
+            "file-allocation": "none",
+        }
+        if request_headers:
+            options["header"] = [
+                f"{key}: {value}" for key, value in request_headers.items()
+            ]
+
+        logger.debug(
+            "Submitting aria2 download %s -> %s (auth=%s, civitai_signed=%s)",
+            download_id,
+            save_path,
+            bool(request_headers),
+            resolved_url != url,
+        )
+
+        try:
+            gid = await self._rpc_call("aria2.addUri", [[resolved_url], options])
+        except Exception as exc:
+            raise Aria2Error(f"Failed to schedule aria2 download: {exc}") from exc
+
+        logger.debug("aria2 accepted download %s with gid %s", download_id, gid)
+        await self._state_store.upsert(
+            download_id,
+            {
+                "gid": gid,
+                "save_path": save_path,
+                "status": "downloading",
+                "url": url,
+            },
+        )
+        return gid
+
+    async def get_status(self, download_id: str) -> Optional[Dict[str, Any]]:
+        """Return the raw aria2 status payload for a known download."""
+
+        transfer = self._transfers.get(download_id)
+        if transfer is None:
+            return None
+
+        keys = [
+            "gid",
+            "status",
+            "totalLength",
+            "completedLength",
+            "downloadSpeed",
+            "errorMessage",
+            "files",
+        ]
+        try:
+            status = await self._rpc_call("aria2.tellStatus", [transfer.gid, keys])
+        except Exception as exc:
+            raise Aria2Error(f"Failed to query aria2 download status: {exc}") from exc
+
+        if isinstance(status, dict):
+            return status
+        return None
+
+    async def get_status_by_gid(self, gid: str) -> Optional[Dict[str, Any]]:
+        keys = [
+            "gid",
+            "status",
+            "totalLength",
+            "completedLength",
+            "downloadSpeed",
+            "errorMessage",
+            "files",
+        ]
+        try:
+            status = await self._rpc_call("aria2.tellStatus", [gid, keys])
+        except Exception as exc:
+            message = str(exc)
+            if "cannot be found" in message.lower() or "not found" in message.lower():
+                return None
+            raise Aria2Error(f"Failed to query aria2 download status: {exc}") from exc
+
+        if isinstance(status, dict):
+            return status
+        return None
+
+    async def restore_transfer(self, download_id: str, gid: str, save_path: str) -> None:
+        await self._ensure_process()
+        self._transfers[download_id] = Aria2Transfer(
+            gid=gid,
+            save_path=os.path.abspath(save_path),
+        )
+
+    async def reassign_transfer(
+        self, from_download_id: str, to_download_id: str
+    ) -> Optional[Aria2Transfer]:
+        transfer = self._transfers.get(from_download_id)
+        if transfer is None:
+            return None
+
+        self._transfers[to_download_id] = transfer
+        if from_download_id != to_download_id:
+            self._transfers.pop(from_download_id, None)
+        return transfer
+
+    async def has_transfer(self, download_id: str) -> bool:
+        return download_id in self._transfers
+
+    async def pause_download(self, download_id: str) -> Dict[str, Any]:
+        transfer = self._transfers.get(download_id)
+        if transfer is None:
+            return {"success": False, "error": "Download task not found"}
+
+        try:
+            await self._rpc_call("aria2.forcePause", [transfer.gid])
+        except Exception as exc:
+            return {"success": False, "error": str(exc)}
+
+        await self._state_store.upsert(download_id, {"status": "paused"})
+        return {"success": True, "message": "Download paused successfully"}
+
+    async def resume_download(self, download_id: str) -> Dict[str, Any]:
+        transfer = self._transfers.get(download_id)
+        if transfer is None:
+            return {"success": False, "error": "Download task not found"}
+
+        try:
+            await self._rpc_call("aria2.unpause", [transfer.gid])
+        except Exception as exc:
+            return {"success": False, "error": str(exc)}
+
+        await self._state_store.upsert(download_id, {"status": "downloading"})
+        return {"success": True, "message": "Download resumed successfully"}
+
+    async def cancel_download(self, download_id: str) -> Dict[str, Any]:
+        transfer = self._transfers.get(download_id)
+        if transfer is None:
+            return {"success": False, "error": "Download task not found"}
+
+        try:
+            await self._rpc_call("aria2.forceRemove", [transfer.gid])
+        except Exception as exc:
+            return {"success": False, "error": str(exc)}
+
+        await self._state_store.remove(download_id)
+        return {"success": True, "message": "Download cancelled successfully"}
+
+    async def close(self) -> None:
+        """Shut down the RPC process and session."""
+
+        if self._rpc_session is not None:
+            await self._rpc_session.close()
+            self._rpc_session = None
+
+        process = self._process
+        self._process = None
+        self._transfers.clear()
+
+        if process is None:
+            return
+
+        if process.returncode is None:
+            process.terminate()
+            try:
+                await asyncio.wait_for(process.wait(), timeout=5.0)
+            except asyncio.TimeoutError:
+                process.kill()
+                await process.wait()
+
+    async def _dispatch_progress(self, callback, snapshot: DownloadProgress) -> None:
+        try:
+            result = callback(snapshot, snapshot)
+        except TypeError:
+            result = callback(snapshot.percent_complete)
+
+        if asyncio.iscoroutine(result):
+            await result
+        elif hasattr(result, "__await__"):
+            await result
+
+    def _build_progress_snapshot(self, status: Dict[str, Any]) -> DownloadProgress:
+        completed = self._parse_int(status.get("completedLength"))
+        total = self._parse_int(status.get("totalLength"))
+        speed = float(self._parse_int(status.get("downloadSpeed")))
+        percent = 0.0
+        if total > 0:
+            percent = (completed / total) * 100.0
+
+        return DownloadProgress(
+            percent_complete=max(0.0, min(percent, 100.0)),
+            bytes_downloaded=completed,
+            total_bytes=total or None,
+            bytes_per_second=speed,
+            timestamp=datetime.now().timestamp(),
+        )
+
+    def _resolve_completed_path(self, status: Dict[str, Any], default_path: str) -> str:
+        files = status.get("files")
+        if isinstance(files, list) and files:
+            first = files[0]
+            if isinstance(first, dict):
+                candidate = first.get("path")
+                if isinstance(candidate, str) and candidate:
+                    return candidate
+        return default_path
+
+    @staticmethod
+    def _parse_int(value: Any) -> int:
+        try:
+            return int(value)
+        except (TypeError, ValueError):
+            return 0
+
+    async def _resolve_authenticated_redirect_url(
+        self,
+        url: str,
+        headers: Dict[str, str],
+    ) -> str:
+        downloader = await get_downloader()
+        session = await downloader.session
+        request_headers = dict(downloader.default_headers)
+        request_headers.update(headers)
+        request_headers["Accept-Encoding"] = "identity"
+
+        try:
+            async with session.get(
+                url,
+                headers=request_headers,
+                allow_redirects=False,
+                proxy=downloader.proxy_url,
+            ) as response:
+                if response.status in {301, 302, 303, 307, 308}:
+                    location = response.headers.get("Location")
+                    if location:
+                        return location
+                    raise Aria2Error(
+                        "Authenticated Civitai redirect did not include a Location header"
+                    )
+
+                if response.status == 200:
+                    return url
+
+                body = await response.text()
+                raise Aria2Error(
+                    f"Failed to resolve authenticated Civitai redirect: status={response.status} body={body[:300]}"
+                )
+        except aiohttp.ClientError as exc:
+            raise Aria2Error(
+                f"Failed to resolve authenticated Civitai redirect: {exc}"
+            ) from exc
+
+    async def _ensure_process(self) -> None:
+        async with self._process_lock:
+            if self.is_running and await self._ping():
+                return
+
+            await self.close()
+
+            executable = self._resolve_executable()
+            self._rpc_port = self._find_free_port()
+            self._rpc_secret = secrets.token_hex(16)
+            self._rpc_url = f"http://127.0.0.1:{self._rpc_port}/jsonrpc"
+
+            command = [
+                executable,
+                "--enable-rpc=true",
+                "--rpc-listen-all=false",
+                f"--rpc-listen-port={self._rpc_port}",
+                f"--rpc-secret={self._rpc_secret}",
+                "--check-certificate=true",
+                "--allow-overwrite=true",
+                "--auto-file-renaming=false",
+                "--file-allocation=none",
+                "--max-concurrent-downloads=5",
+                "--continue=true",
+                "--daemon=false",
+                "--quiet=true",
+                f"--stop-with-process={os.getpid()}",
+            ]
+
+            logger.info("Starting aria2 RPC daemon from %s", executable)
+            self._process = await asyncio.create_subprocess_exec(
+                *command,
+                stdout=asyncio.subprocess.DEVNULL,
+                stderr=asyncio.subprocess.PIPE,
+            )
+
+            await self._wait_until_ready()
+
+    def _resolve_executable(self) -> str:
+        settings = get_settings_manager()
+        configured_path = (settings.get("aria2c_path") or "").strip()
+        candidate = configured_path or "aria2c"
+
+        resolved = shutil.which(candidate)
+        if resolved:
+            return resolved
+
+        if configured_path and os.path.isfile(configured_path) and os.access(
+            configured_path, os.X_OK
+        ):
+            return configured_path
+
+        raise Aria2Error(
+            "aria2c executable was not found. Install aria2 or configure aria2c_path."
+        )
+
+    async def _wait_until_ready(self) -> None:
+        assert self._process is not None
+
+        start_time = asyncio.get_running_loop().time()
+        last_error = ""
+        while asyncio.get_running_loop().time() - start_time < 10.0:
+            if self._process.returncode is not None:
+                stderr_output = ""
+                if self._process.stderr is not None:
+                    try:
+                        stderr_output = (
+                            await asyncio.wait_for(self._process.stderr.read(), timeout=0.2)
+                        ).decode("utf-8", errors="replace")
+                    except Exception:
+                        stderr_output = ""
+                raise Aria2Error(
+                    f"aria2 RPC process exited early with code {self._process.returncode}: {stderr_output.strip()}"
+                )
+
+            try:
+                if await self._ping():
+                    return
+            except Exception as exc:  # pragma: no cover - startup race
+                last_error = str(exc)
+
+            await asyncio.sleep(0.2)
+
+        raise Aria2Error(
+            f"Timed out waiting for aria2 RPC to become ready{': ' + last_error if last_error else ''}"
+        )
+
+    async def _ping(self) -> bool:
+        try:
+            result = await self._rpc_call("aria2.getVersion", [])
+        except Exception:
+            return False
+
+        return isinstance(result, dict)
+
+    async def _rpc_call(self, method: str, params: list[Any]) -> Any:
+        if not self._rpc_url:
+            raise Aria2Error("aria2 RPC endpoint is not initialized")
+
+        session = await self._get_rpc_session()
+        payload = {
+            "jsonrpc": "2.0",
+            "id": secrets.token_hex(8),
+            "method": method,
+            "params": [f"token:{self._rpc_secret}", *params],
+        }
+
+        async with session.post(self._rpc_url, json=payload) as response:
+            text = await response.text()
+
+        try:
+            body = json.loads(text)
+        except json.JSONDecodeError:
+            body = None
+
+        if body is None:
+            if response.status != 200:
+                raise Aria2Error(
+                    f"aria2 RPC returned status {response.status} with non-JSON body: {text}"
+                )
+            raise Aria2Error(f"Invalid aria2 RPC response: {text}")
+
+        if "error" in body:
+            error = body["error"] or {}
+            code = error.get("code") if isinstance(error, dict) else None
+            message = error.get("message") if isinstance(error, dict) else str(error)
+            logger.error(
+                "aria2 RPC %s failed with HTTP %s, code=%s, message=%s",
+                method,
+                response.status,
+                code,
+                message,
+            )
+            status_message = (
+                f"aria2 RPC {method} failed with status {response.status}: {message}"
+                if response.status != 200
+                else message
+            )
+            raise Aria2Error(status_message or "Unknown aria2 RPC error")
+
+        if response.status != 200:
+            logger.error(
+                "aria2 RPC %s returned unexpected HTTP status %s without error payload: %s",
+                method,
+                response.status,
+                body,
+            )
+            raise Aria2Error(
+                f"aria2 RPC {method} returned unexpected status {response.status}"
+            )
+
+        return body.get("result")
+
+    async def _get_rpc_session(self) -> aiohttp.ClientSession:
+        if self._rpc_session is None or self._rpc_session.closed:
+            async with self._rpc_session_lock:
+                if self._rpc_session is None or self._rpc_session.closed:
+                    timeout = aiohttp.ClientTimeout(total=30)
+                    self._rpc_session = aiohttp.ClientSession(timeout=timeout)
+        return self._rpc_session
+
+    @staticmethod
+    def _find_free_port() -> int:
+        with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as sock:
+            sock.bind(("127.0.0.1", 0))
+            sock.listen(1)
+            return int(sock.getsockname()[1])
+
+
+async def get_aria2_downloader() -> Aria2Downloader:
+    """Get the singleton aria2 downloader."""
+
+    return await Aria2Downloader.get_instance()

py/services/aria2_transfer_state.py

@@ -0,0 +1,108 @@
+from __future__ import annotations
+
+import asyncio
+import json
+import os
+from copy import deepcopy
+from typing import Any, Dict, Optional
+
+from ..utils.cache_paths import get_cache_base_dir
+
+
+def get_aria2_state_path() -> str:
+    base_dir = get_cache_base_dir(create=True)
+    state_dir = os.path.join(base_dir, "aria2")
+    os.makedirs(state_dir, exist_ok=True)
+    return os.path.join(state_dir, "downloads.json")
+
+
+class Aria2TransferStateStore:
+    """Persist aria2 transfer metadata needed for restart recovery."""
+
+    _locks_by_path: Dict[str, asyncio.Lock] = {}
+
+    def __init__(self, state_path: Optional[str] = None) -> None:
+        self._state_path = os.path.abspath(state_path or get_aria2_state_path())
+        self._lock = self._locks_by_path.setdefault(self._state_path, asyncio.Lock())
+
+    def _read_all_unlocked(self) -> Dict[str, Dict[str, Any]]:
+        try:
+            with open(self._state_path, "r", encoding="utf-8") as handle:
+                data = json.load(handle)
+        except FileNotFoundError:
+            return {}
+        except json.JSONDecodeError:
+            return {}
+
+        if not isinstance(data, dict):
+            return {}
+
+        normalized: Dict[str, Dict[str, Any]] = {}
+        for download_id, entry in data.items():
+            if isinstance(download_id, str) and isinstance(entry, dict):
+                normalized[download_id] = entry
+        return normalized
+
+    def _write_all_unlocked(self, data: Dict[str, Dict[str, Any]]) -> None:
+        directory = os.path.dirname(self._state_path)
+        if directory:
+            os.makedirs(directory, exist_ok=True)
+
+        temp_path = f"{self._state_path}.tmp"
+        with open(temp_path, "w", encoding="utf-8") as handle:
+            json.dump(data, handle, ensure_ascii=True, indent=2, sort_keys=True)
+        os.replace(temp_path, self._state_path)
+
+    async def load_all(self) -> Dict[str, Dict[str, Any]]:
+        async with self._lock:
+            return deepcopy(self._read_all_unlocked())
+
+    async def get(self, download_id: str) -> Optional[Dict[str, Any]]:
+        async with self._lock:
+            return deepcopy(self._read_all_unlocked().get(download_id))
+
+    async def upsert(self, download_id: str, payload: Dict[str, Any]) -> Dict[str, Any]:
+        async with self._lock:
+            data = self._read_all_unlocked()
+            current = data.get(download_id, {})
+            current.update(payload)
+            data[download_id] = current
+            self._write_all_unlocked(data)
+            return deepcopy(current)
+
+    async def remove(self, download_id: str) -> None:
+        async with self._lock:
+            data = self._read_all_unlocked()
+            if download_id in data:
+                del data[download_id]
+                self._write_all_unlocked(data)
+
+    async def find_by_save_path(
+        self, save_path: str, *, exclude_download_id: Optional[str] = None
+    ) -> Optional[Dict[str, Any]]:
+        normalized_target = os.path.abspath(save_path)
+        async with self._lock:
+            data = self._read_all_unlocked()
+            for download_id, entry in data.items():
+                if exclude_download_id and download_id == exclude_download_id:
+                    continue
+                candidate = entry.get("save_path")
+                if isinstance(candidate, str) and os.path.abspath(candidate) == normalized_target:
+                    result = dict(entry)
+                    result["download_id"] = download_id
+                    return result
+        return None
+
+    async def reassign(self, from_download_id: str, to_download_id: str) -> Optional[Dict[str, Any]]:
+        async with self._lock:
+            data = self._read_all_unlocked()
+            existing = data.get(from_download_id)
+            if existing is None:
+                return None
+            updated = dict(existing)
+            updated["download_id"] = to_download_id
+            data[to_download_id] = updated
+            if from_download_id != to_download_id:
+                data.pop(from_download_id, None)
+            self._write_all_unlocked(data)
+            return deepcopy(updated)

py/services/base_model_service.py

@@ -20,6 +20,7 @@ from .model_query import (
     resolve_sub_type,
 )
 from .settings_manager import get_settings_manager
+from ..utils.civitai_utils import build_civitai_model_page_url
 
 logger = logging.getLogger(__name__)
 
@@ -178,6 +179,57 @@ class BaseModelService(ABC):
         )
         return paginated
 
+    async def get_excluded_paginated_data(
+        self,
+        page: int,
+        page_size: int,
+        sort_by: str = "name",
+        search: str = None,
+        fuzzy_search: bool = False,
+        search_options: dict = None,
+        **kwargs,
+    ) -> Dict:
+        """Get paginated excluded model data."""
+        excluded_paths = list(self.scanner.get_excluded_models())
+        excluded_entries: List[Dict[str, Any]] = []
+        stale_paths: List[str] = []
+
+        for file_path in excluded_paths:
+            if not file_path or not os.path.exists(file_path):
+                stale_paths.append(file_path)
+                continue
+
+            entry = await self._build_excluded_entry(file_path)
+            if entry:
+                excluded_entries.append(entry)
+            else:
+                stale_paths.append(file_path)
+
+        if stale_paths:
+            current_excluded = getattr(self.scanner, "_excluded_models", None)
+            if isinstance(current_excluded, list):
+                stale_set = set(stale_paths)
+                self.scanner._excluded_models = [
+                    path for path in current_excluded if path not in stale_set
+                ]
+                persist_current_cache = getattr(self.scanner, "_persist_current_cache", None)
+                if callable(persist_current_cache):
+                    await persist_current_cache()
+
+        excluded_entries = self._sort_entries(excluded_entries, sort_by)
+
+        if search:
+            excluded_entries = await self._apply_search_filters(
+                excluded_entries,
+                search,
+                fuzzy_search,
+                search_options,
+            )
+
+        paginated = self._paginate(excluded_entries, page, page_size)
+        paginated["items"] = await self._annotate_update_flags(paginated["items"])
+        return paginated
+
     async def _fetch_with_usage_sort(self, sort_params):
         """Fetch data sorted by usage count (desc/asc)."""
         cache = await self.cache_repository.get_cache()
@@ -217,6 +269,62 @@ class BaseModelService(ABC):
         )
         return annotated
 
+    def _sort_entries(self, data: List[Dict[str, Any]], sort_by: str) -> List[Dict[str, Any]]:
+        sort_params = self.cache_repository.parse_sort(sort_by)
+        key_name = sort_params.key
+
+        if key_name == "date":
+            key_fn = lambda item: (
+                float(item.get("modified", 0.0) or 0.0),
+                (item.get("model_name") or item.get("file_name") or "").lower(),
+                item.get("file_path", "").lower(),
+            )
+        elif key_name == "size":
+            key_fn = lambda item: (
+                int(item.get("size", 0) or 0),
+                (item.get("model_name") or item.get("file_name") or "").lower(),
+                item.get("file_path", "").lower(),
+            )
+        elif key_name == "usage":
+            key_fn = lambda item: (
+                int(item.get("usage_count", 0) or 0),
+                (item.get("model_name") or item.get("file_name") or "").lower(),
+                item.get("file_path", "").lower(),
+            )
+        else:
+            key_fn = lambda item: (
+                (item.get("model_name") or item.get("file_name") or "").lower(),
+                item.get("file_path", "").lower(),
+            )
+
+        return sorted(data, key=key_fn, reverse=sort_params.order == "desc")
+
+    async def _build_excluded_entry(self, file_path: str) -> Optional[Dict[str, Any]]:
+        root_path = self.scanner._find_root_for_file(file_path)
+        if not root_path:
+            return None
+
+        metadata, should_skip = await MetadataManager.load_metadata(
+            file_path,
+            self.metadata_class,
+        )
+        if should_skip:
+            return None
+
+        if metadata is None:
+            metadata = await self.scanner._create_default_metadata(file_path)
+            if metadata is None:
+                return None
+
+        metadata = self.scanner.adjust_metadata(metadata, file_path, root_path)
+        folder = os.path.dirname(os.path.relpath(file_path, root_path)).replace(
+            os.path.sep, "/"
+        )
+        entry = self.scanner._build_cache_entry(metadata, folder=folder)
+        entry = self.scanner.adjust_cached_entry(entry)
+        entry["exclude"] = True
+        return entry
+
     async def _apply_hash_filters(
         self, data: List[Dict], hash_filters: Dict
     ) -> List[Dict]:
@@ -774,9 +882,12 @@ class BaseModelService(ABC):
                 version_id = civitai_data.get("id")
 
                 if model_id:
-                    civitai_url = f"https://civitai.com/models/{model_id}"
-                    if version_id:
-                        civitai_url += f"?modelVersionId={version_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,

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

@@ -42,6 +42,7 @@ class CheckpointService(BaseModelService):
             "notes": checkpoint_data.get("notes", ""),
             "sub_type": sub_type,
             "favorite": checkpoint_data.get("favorite", False),
+            "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)

py/services/civitai_base_model_service.py

@@ -30,7 +30,7 @@ class CivitaiBaseModelService:
     DEFAULT_CACHE_TTL = 7 * 24 * 60 * 60
 
     # Civitai API endpoint for enums
-    CIVITAI_ENUMS_URL = "https://civitai.com/api/v1/enums"
+    CIVITAI_ENUMS_URL = "https://civitai.red/api/v1/enums"
 
     @classmethod
     async def get_instance(cls) -> CivitaiBaseModelService:
@@ -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

@@ -3,6 +3,11 @@ import copy
 import logging
 import os
 from typing import Any, Optional, Dict, Tuple, List, Sequence
+from .connectivity_guard import (
+    OFFLINE_FRIENDLY_MESSAGE,
+    is_expected_offline_error,
+    is_offline_cooldown_error,
+)
 from .model_metadata_provider import (
     CivitaiModelMetadataProvider,
     ModelMetadataProviderManager,
@@ -39,7 +44,10 @@ class CivitaiClient:
             return
         self._initialized = True
 
-        self.base_url = "https://civitai.com/api/v1"
+        self.base_url = "https://civitai.red/api/v1"
+
+    def _build_image_info_url(self, image_id: str) -> str:
+        return f"{self.base_url}/images?imageId={image_id}&nsfw=X"
 
     async def _make_request(
         self,
@@ -62,6 +70,8 @@ class CivitaiClient:
             if result.provider is None:
                 result.provider = "civitai_api"
             raise result
+        if not success and is_offline_cooldown_error(result):
+            return False, OFFLINE_FRIENDLY_MESSAGE
         return success, result
 
     @staticmethod
@@ -121,6 +131,8 @@ class CivitaiClient:
             )
             if not success:
                 message = str(version)
+                if is_expected_offline_error(message):
+                    return None, OFFLINE_FRIENDLY_MESSAGE
                 if "not found" in message.lower():
                     return None, "Model not found"
 
@@ -161,6 +173,9 @@ class CivitaiClient:
                 return True
             return False
         except Exception as e:
+            if is_expected_offline_error(str(e)):
+                logger.debug("Preview download skipped due to offline state.")
+                return False
             logger.error(f"Download Error: {str(e)}")
             return False
 
@@ -190,7 +205,9 @@ class CivitaiClient:
         """Get all versions of a model with local availability info"""
         try:
             success, result = await self._make_request(
-                "GET", f"{self.base_url}/models/{model_id}", use_auth=True
+                "GET",
+                f"{self.base_url}/models/{model_id}",
+                use_auth=True,
             )
             if success:
                 # Also return model type along with versions
@@ -202,6 +219,9 @@ class CivitaiClient:
             message = self._extract_error_message(result)
             if message and "not found" in message.lower():
                 raise ResourceNotFoundError(f"Resource not found for model {model_id}")
+            if is_expected_offline_error(message):
+                logger.info("Civitai request skipped: %s", OFFLINE_FRIENDLY_MESSAGE)
+                return None
             if message:
                 raise RuntimeError(message)
             return None
@@ -346,10 +366,14 @@ class CivitaiClient:
 
     async def _fetch_model_data(self, model_id: int) -> Optional[Dict]:
         success, data = await self._make_request(
-            "GET", f"{self.base_url}/models/{model_id}", use_auth=True
+            "GET",
+            f"{self.base_url}/models/{model_id}",
+            use_auth=True,
         )
         if success:
             return data
+        if is_expected_offline_error(data):
+            return None
         logger.warning(f"Failed to fetch model data for model {model_id}")
         return None
 
@@ -358,10 +382,14 @@ class CivitaiClient:
             return None
 
         success, version = await self._make_request(
-            "GET", f"{self.base_url}/model-versions/{version_id}", use_auth=True
+            "GET",
+            f"{self.base_url}/model-versions/{version_id}",
+            use_auth=True,
         )
         if success:
             return version
+        if is_expected_offline_error(version):
+            return None
 
         logger.warning(f"Failed to fetch version by id {version_id}")
         return None
@@ -371,10 +399,14 @@ class CivitaiClient:
             return None
 
         success, version = await self._make_request(
-            "GET", f"{self.base_url}/model-versions/by-hash/{model_hash}", use_auth=True
+            "GET",
+            f"{self.base_url}/model-versions/by-hash/{model_hash}",
+            use_auth=True,
         )
         if success:
             return version
+        if is_expected_offline_error(version):
+            return None
 
         logger.warning(f"Failed to fetch version by hash {model_hash}")
         return None
@@ -453,17 +485,17 @@ class CivitaiClient:
         try:
             url = f"{self.base_url}/model-versions/{version_id}"
 
-            logger.debug(f"Resolving DNS for model version info: {url}")
+            logger.debug("Resolving Civitai model version info: %s", url)
             success, result = await self._make_request("GET", url, use_auth=True)
 
             if success:
-                logger.debug(
-                    f"Successfully fetched model version info for: {version_id}"
-                )
+                logger.debug("Successfully fetched model version info for: %s", version_id)
                 self._remove_comfy_metadata(result)
                 return result, None
 
             # Handle specific error cases
+            if is_expected_offline_error(result):
+                return None, OFFLINE_FRIENDLY_MESSAGE
             if "not found" in str(result):
                 error_msg = f"Model not found"
                 logger.warning(f"Model version not found: {version_id} - {error_msg}")
@@ -479,48 +511,60 @@ class CivitaiClient:
             logger.error(error_msg)
             return None, error_msg
 
-    async def get_image_info(self, image_id: str) -> Optional[Dict]:
+    async def get_image_info(
+        self, image_id: str, source_url: str | None = None
+    ) -> Optional[Dict]:
         """Fetch image information from Civitai API
 
         Args:
             image_id: The Civitai image ID
+            source_url: Original image page URL. Accepted for caller compatibility;
+                API requests always target ``civitai.red``.
 
         Returns:
             Optional[Dict]: The image data or None if not found
         """
         try:
-            url = f"{self.base_url}/images?imageId={image_id}&nsfw=X"
             requested_id = int(image_id)
-
-            logger.debug(f"Fetching image info for ID: {image_id}")
+            url = self._build_image_info_url(image_id)
             success, result = await self._make_request("GET", url, use_auth=True)
 
-            if success:
-                if result and "items" in result and isinstance(result["items"], list):
-                    items = result["items"]
-
-                    # First, try to find the item with matching ID
-                    for item in items:
-                        if isinstance(item, dict) and item.get("id") == requested_id:
-                            logger.debug(f"Successfully fetched image info for ID: {image_id}")
-                            return item
-
-                    # No matching ID found - log warning with details about returned items
-                    returned_ids = [
-                        item.get("id") for item in items
-                        if isinstance(item, dict) and "id" in item
-                    ]
-                    logger.warning(
-                        f"CivitAI API returned no matching image for requested ID {image_id}. "
-                        f"Returned {len(items)} item(s) with IDs: {returned_ids}. "
-                        f"This may indicate the image was deleted, hidden, or there is a database lag."
-                    )
+            if not success:
+                if is_expected_offline_error(result):
                     return None
-
-                logger.warning(f"No image found with ID: {image_id}")
+                logger.error(
+                    "Failed to fetch image info for ID %s from civitai.red: %s",
+                    image_id,
+                    result,
+                )
                 return None
 
-            logger.error(f"Failed to fetch image info for ID: {image_id}: {result}")
+            if result and "items" in result and isinstance(result["items"], list):
+                items = result["items"]
+
+                for item in items:
+                    if isinstance(item, dict) and item.get("id") == requested_id:
+                        logger.debug(
+                            "Successfully fetched image info for ID %s from civitai.red",
+                            image_id,
+                        )
+                        return item
+
+                returned_ids = [
+                    item.get("id")
+                    for item in items
+                    if isinstance(item, dict) and "id" in item
+                ]
+
+                logger.warning(
+                    "CivitAI API returned no matching image for requested ID %s from civitai.red. Returned %d item(s) with IDs: %s. This may indicate the image was deleted, hidden, or there is a database lag.",
+                    image_id,
+                    len(items),
+                    returned_ids,
+                )
+                return None
+
+            logger.warning("No image found with ID: %s", image_id)
             return None
         except RateLimitError:
             raise
@@ -533,16 +577,76 @@ 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:
             return None
 
         try:
-            url = f"{self.base_url}/models?username={username}"
-            success, result = await self._make_request("GET", url, use_auth=True)
+            success, result = await self._make_request(
+                "GET",
+                f"{self.base_url}/models",
+                use_auth=True,
+                params={"username": username},
+            )
 
             if not success:
+                if is_expected_offline_error(result):
+                    logger.info("User model fetch skipped: %s", OFFLINE_FRIENDLY_MESSAGE)
+                    return None
                 logger.error("Failed to fetch models for %s: %s", username, result)
                 return None
 

py/services/connectivity_guard.py

@@ -0,0 +1,204 @@
+"""In-memory connectivity guard to suppress repeated network retries when offline."""
+
+from __future__ import annotations
+
+import asyncio
+import errno
+import logging
+import socket
+from dataclasses import dataclass
+from datetime import datetime, timedelta
+from typing import Any
+
+import aiohttp
+
+logger = logging.getLogger(__name__)
+
+OFFLINE_COOLDOWN_ERROR = "offline_cooldown"
+OFFLINE_FRIENDLY_MESSAGE = "Network offline, will retry automatically later"
+
+
+def is_offline_cooldown_error(value: Any) -> bool:
+    """Return True when a response payload represents guard short-circuit."""
+    return isinstance(value, str) and value == OFFLINE_COOLDOWN_ERROR
+
+
+def is_expected_offline_error(value: Any) -> bool:
+    """Return True when payload is an expected offline-related result."""
+    if is_offline_cooldown_error(value):
+        return True
+    if not isinstance(value, str):
+        return False
+    normalized = value.lower()
+    return "network offline" in normalized or "offline" in normalized
+
+
+class ConnectivityGuard:
+    """Tracks network failures and gates outbound requests during cooldown."""
+
+    _instance: "ConnectivityGuard | None" = None
+    _instance_lock = asyncio.Lock()
+
+    @classmethod
+    async def get_instance(cls) -> "ConnectivityGuard":
+        async with cls._instance_lock:
+            if cls._instance is None:
+                cls._instance = cls()
+            return cls._instance
+
+    def __init__(self) -> None:
+        if hasattr(self, "_initialized"):
+            return
+        self._initialized = True
+        self._default_destination = "__global__"
+        self._destination_states: dict[str, _DestinationState] = {
+            self._default_destination: _DestinationState()
+        }
+        self.base_backoff_seconds = 30
+        self.max_backoff_seconds = 300
+        self.failure_threshold = 3
+
+    @property
+    def online(self) -> bool:
+        return self._state_for_destination(None).online
+
+    @online.setter
+    def online(self, value: bool) -> None:
+        self._state_for_destination(None).online = value
+
+    @property
+    def failure_count(self) -> int:
+        return self._state_for_destination(None).failure_count
+
+    @failure_count.setter
+    def failure_count(self, value: int) -> None:
+        self._state_for_destination(None).failure_count = value
+
+    @property
+    def cooldown_until(self) -> datetime | None:
+        return self._state_for_destination(None).cooldown_until
+
+    @cooldown_until.setter
+    def cooldown_until(self, value: datetime | None) -> None:
+        self._state_for_destination(None).cooldown_until = value
+
+    def _now(self) -> datetime:
+        return datetime.now()
+
+    def _normalize_destination(self, destination: str | None) -> str:
+        if destination is None or not destination.strip():
+            return self._default_destination
+        return destination.lower().strip()
+
+    def _state_for_destination(self, destination: str | None) -> "_DestinationState":
+        destination_key = self._normalize_destination(destination)
+        if destination_key not in self._destination_states:
+            self._destination_states[destination_key] = _DestinationState()
+        return self._destination_states[destination_key]
+
+    def in_cooldown(self, destination: str | None = None) -> bool:
+        state = self._state_for_destination(destination)
+        if state.cooldown_until is None:
+            return False
+        return self._now() < state.cooldown_until
+
+    def cooldown_remaining_seconds(self, destination: str | None = None) -> float:
+        state = self._state_for_destination(destination)
+        if state.cooldown_until is None:
+            return 0.0
+        return max(0.0, (state.cooldown_until - self._now()).total_seconds())
+
+    def should_block_request(self, destination: str | None = None) -> bool:
+        return self.in_cooldown(destination)
+
+    def register_success(self, destination: str | None = None) -> None:
+        destination_key = self._normalize_destination(destination)
+        state = self._state_for_destination(destination_key)
+        was_offline = (not state.online) or state.cooldown_until is not None
+        state.online = True
+        state.failure_count = 0
+        state.cooldown_until = None
+        if was_offline:
+            logger.info(
+                "Connectivity restored for destination '%s'; requests resumed.",
+                destination_key,
+            )
+
+    def register_network_failure(
+        self, exc: Exception, destination: str | None = None
+    ) -> None:
+        destination_key = self._normalize_destination(destination)
+        state = self._state_for_destination(destination_key)
+        state.online = False
+        state.failure_count += 1
+
+        if state.failure_count < self.failure_threshold:
+            logger.debug(
+                "Network failure tracked for destination '%s' (%d/%d): %s",
+                destination_key,
+                state.failure_count,
+                self.failure_threshold,
+                exc,
+            )
+            return
+
+        retry_step = state.failure_count - self.failure_threshold
+        backoff = min(
+            self.max_backoff_seconds,
+            self.base_backoff_seconds * (2**retry_step),
+        )
+        should_log_warning = not self.in_cooldown(destination_key)
+        state.cooldown_until = self._now() + timedelta(seconds=backoff)
+
+        if should_log_warning:
+            logger.warning(
+                "Connectivity offline for destination '%s'; enter cooldown for %ss after %d network failures.",
+                destination_key,
+                int(backoff),
+                state.failure_count,
+            )
+        else:
+            logger.debug(
+                "Cooldown still active for destination '%s'; failure_count=%d, backoff=%ss.",
+                destination_key,
+                state.failure_count,
+                int(backoff),
+            )
+
+    @staticmethod
+    def is_network_unreachable_error(exc: Exception) -> bool:
+        """Return whether the exception should count as connectivity failure."""
+        if isinstance(exc, asyncio.CancelledError):
+            return False
+
+        if isinstance(
+            exc,
+            (
+                asyncio.TimeoutError,
+                TimeoutError,
+                ConnectionRefusedError,
+                socket.gaierror,
+                aiohttp.ServerTimeoutError,
+                aiohttp.ConnectionTimeoutError,
+                aiohttp.ClientConnectorError,
+                aiohttp.ClientConnectionError,
+            ),
+        ):
+            return True
+
+        if isinstance(exc, OSError) and exc.errno in {
+            errno.ENETUNREACH,
+            errno.EHOSTUNREACH,
+            errno.ETIMEDOUT,
+            errno.ECONNREFUSED,
+        }:
+            return True
+
+        return False
+
+
+@dataclass
+class _DestinationState:
+    online: bool = True
+    failure_count: int = 0
+    cooldown_until: datetime | None = None

py/services/custom_words_service.py

@@ -7,11 +7,13 @@ with category filtering and enriched results including post counts.
 from __future__ import annotations
 
 import logging
+import re
 from typing import List, Dict, Any, Optional
 
 logger = logging.getLogger(__name__)
 
 
+_EMBEDDED_COMMAND_PATTERN = re.compile(r"\s/\w")
 class CustomWordsService:
     """Service for autocomplete via TagFTSIndex.
 
@@ -77,12 +79,28 @@ class CustomWordsService:
         Returns:
             List of dicts with tag_name, category, and post_count.
         """
+        normalized_search = search_term.strip()
+        if not normalized_search:
+            return []
+
+        # Prompt widgets should only send the active token, but guard against
+        # accidental full-prompt queries reaching the FTS path.
+        if (
+            "__" in normalized_search
+            or "," in normalized_search
+            or ">" in normalized_search
+            or "\n" in normalized_search
+            or "\r" in normalized_search
+            or _EMBEDDED_COMMAND_PATTERN.search(normalized_search)
+        ):
+            logger.debug("Skipping prompt-like custom words query: %s", normalized_search)
+            return []
+
         tag_index = self._get_tag_index()
         if tag_index is not None:
-            results = tag_index.search(
-                search_term, categories=categories, limit=limit, offset=offset
+            return tag_index.search(
+                normalized_search, categories=categories, limit=limit, offset=offset
             )
-            return results
 
         logger.debug("TagFTSIndex not available, returning empty results")
         return []

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
@@ -116,33 +123,33 @@ class DownloadedVersionHistoryService:
         timestamp = time.time()
 
         async with self._lock:
-            with self._connect() as conn:
-                conn.execute(
-                    """
-                    INSERT INTO downloaded_model_versions (
-                        model_type, version_id, model_id, first_seen_at, last_seen_at,
-                        source, last_file_path, last_library_name, is_deleted_override
-                    ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, 0)
-                    ON CONFLICT(model_type, version_id) DO UPDATE SET
-                        model_id = COALESCE(excluded.model_id, downloaded_model_versions.model_id),
-                        last_seen_at = excluded.last_seen_at,
-                        source = excluded.source,
-                        last_file_path = COALESCE(excluded.last_file_path, downloaded_model_versions.last_file_path),
-                        last_library_name = COALESCE(excluded.last_library_name, downloaded_model_versions.last_library_name),
-                        is_deleted_override = 0
-                    """,
-                    (
-                        normalized_type,
-                        normalized_version_id,
-                        normalized_model_id,
-                        timestamp,
-                        timestamp,
-                        source,
-                        file_path,
-                        active_library_name,
-                    ),
-                )
-                conn.commit()
+            conn = self._get_conn()
+            conn.execute(
+                """
+                INSERT INTO downloaded_model_versions (
+                    model_type, version_id, model_id, first_seen_at, last_seen_at,
+                    source, last_file_path, last_library_name, is_deleted_override
+                ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, 0)
+                ON CONFLICT(model_type, version_id) DO UPDATE SET
+                    model_id = COALESCE(excluded.model_id, downloaded_model_versions.model_id),
+                    last_seen_at = excluded.last_seen_at,
+                    source = excluded.source,
+                    last_file_path = COALESCE(excluded.last_file_path, downloaded_model_versions.last_file_path),
+                    last_library_name = COALESCE(excluded.last_library_name, downloaded_model_versions.last_library_name),
+                    is_deleted_override = 0
+                """,
+                (
+                    normalized_type,
+                    normalized_version_id,
+                    normalized_model_id,
+                    timestamp,
+                    timestamp,
+                    source,
+                    file_path,
+                    active_library_name,
+                ),
+            )
+            conn.commit()
 
     async def mark_downloaded_bulk(
         self,
@@ -180,24 +187,24 @@ class DownloadedVersionHistoryService:
             return
 
         async with self._lock:
-            with self._connect() as conn:
-                conn.executemany(
-                    """
-                    INSERT INTO downloaded_model_versions (
-                        model_type, version_id, model_id, first_seen_at, last_seen_at,
-                        source, last_file_path, last_library_name, is_deleted_override
-                    ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, 0)
-                    ON CONFLICT(model_type, version_id) DO UPDATE SET
-                        model_id = COALESCE(excluded.model_id, downloaded_model_versions.model_id),
-                        last_seen_at = excluded.last_seen_at,
-                        source = excluded.source,
-                        last_file_path = COALESCE(excluded.last_file_path, downloaded_model_versions.last_file_path),
-                        last_library_name = COALESCE(excluded.last_library_name, downloaded_model_versions.last_library_name),
-                        is_deleted_override = 0
-                    """,
-                    payload,
-                )
-                conn.commit()
+            conn = self._get_conn()
+            conn.executemany(
+                """
+                INSERT INTO downloaded_model_versions (
+                    model_type, version_id, model_id, first_seen_at, last_seen_at,
+                    source, last_file_path, last_library_name, is_deleted_override
+                ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, 0)
+                ON CONFLICT(model_type, version_id) DO UPDATE SET
+                    model_id = COALESCE(excluded.model_id, downloaded_model_versions.model_id),
+                    last_seen_at = excluded.last_seen_at,
+                    source = excluded.source,
+                    last_file_path = COALESCE(excluded.last_file_path, downloaded_model_versions.last_file_path),
+                    last_library_name = COALESCE(excluded.last_library_name, downloaded_model_versions.last_library_name),
+                    is_deleted_override = 0
+                """,
+                payload,
+            )
+            conn.commit()
 
     async def mark_not_downloaded(self, model_type: str, version_id: int) -> None:
         normalized_type = _normalize_model_type(model_type)
@@ -208,28 +215,28 @@ class DownloadedVersionHistoryService:
         timestamp = time.time()
 
         async with self._lock:
-            with self._connect() as conn:
-                conn.execute(
-                    """
-                    INSERT INTO downloaded_model_versions (
-                        model_type, version_id, model_id, first_seen_at, last_seen_at,
-                        source, last_file_path, last_library_name, is_deleted_override
-                    ) VALUES (?, ?, NULL, ?, ?, 'manual', NULL, ?, 1)
-                    ON CONFLICT(model_type, version_id) DO UPDATE SET
-                        last_seen_at = excluded.last_seen_at,
-                        source = excluded.source,
-                        last_library_name = COALESCE(excluded.last_library_name, downloaded_model_versions.last_library_name),
-                        is_deleted_override = 1
-                    """,
-                    (
-                        normalized_type,
-                        normalized_version_id,
-                        timestamp,
-                        timestamp,
-                        self._get_active_library_name(),
-                    ),
-                )
-                conn.commit()
+            conn = self._get_conn()
+            conn.execute(
+                """
+                INSERT INTO downloaded_model_versions (
+                    model_type, version_id, model_id, first_seen_at, last_seen_at,
+                    source, last_file_path, last_library_name, is_deleted_override
+                ) VALUES (?, ?, NULL, ?, ?, 'manual', NULL, ?, 1)
+                ON CONFLICT(model_type, version_id) DO UPDATE SET
+                    last_seen_at = excluded.last_seen_at,
+                    source = excluded.source,
+                    last_library_name = COALESCE(excluded.last_library_name, downloaded_model_versions.last_library_name),
+                    is_deleted_override = 1
+                """,
+                (
+                    normalized_type,
+                    normalized_version_id,
+                    timestamp,
+                    timestamp,
+                    self._get_active_library_name(),
+                ),
+            )
+            conn.commit()
 
     async def has_been_downloaded(self, model_type: str, version_id: int) -> bool:
         normalized_type = _normalize_model_type(model_type)
@@ -238,15 +245,15 @@ class DownloadedVersionHistoryService:
             return False
 
         async with self._lock:
-            with self._connect() as conn:
-                row = conn.execute(
-                    """
-                    SELECT is_deleted_override
-                    FROM downloaded_model_versions
-                    WHERE model_type = ? AND version_id = ?
-                    """,
-                    (normalized_type, normalized_version_id),
-                ).fetchone()
+            conn = self._get_conn()
+            row = conn.execute(
+                """
+                SELECT is_deleted_override
+                FROM downloaded_model_versions
+                WHERE model_type = ? AND version_id = ?
+                """,
+                (normalized_type, normalized_version_id),
+            ).fetchone()
         return bool(row) and not bool(row["is_deleted_override"])
 
     async def get_downloaded_version_ids(
@@ -258,16 +265,16 @@ class DownloadedVersionHistoryService:
             return []
 
         async with self._lock:
-            with self._connect() as conn:
-                rows = conn.execute(
-                    """
-                    SELECT version_id
-                    FROM downloaded_model_versions
-                    WHERE model_type = ? AND model_id = ? AND is_deleted_override = 0
-                    ORDER BY version_id ASC
-                    """,
-                    (normalized_type, normalized_model_id),
-                ).fetchall()
+            conn = self._get_conn()
+            rows = conn.execute(
+                """
+                SELECT version_id
+                FROM downloaded_model_versions
+                WHERE model_type = ? AND model_id = ? AND is_deleted_override = 0
+                ORDER BY version_id ASC
+                """,
+                (normalized_type, normalized_model_id),
+            ).fetchall()
         return [int(row["version_id"]) for row in rows]
 
     async def get_downloaded_version_ids_bulk(
@@ -291,17 +298,17 @@ class DownloadedVersionHistoryService:
         params: list[object] = [normalized_type, *normalized_model_ids]
 
         async with self._lock:
-            with self._connect() as conn:
-                rows = conn.execute(
-                    f"""
-                    SELECT model_id, version_id
-                    FROM downloaded_model_versions
-                    WHERE model_type = ?
-                      AND model_id IN ({placeholders})
-                      AND is_deleted_override = 0
-                    """,
-                    params,
-                ).fetchall()
+            conn = self._get_conn()
+            rows = conn.execute(
+                f"""
+                SELECT model_id, version_id
+                FROM downloaded_model_versions
+                WHERE model_type = ?
+                  AND model_id IN ({placeholders})
+                  AND is_deleted_override = 0
+                """,
+                params,
+            ).fetchall()
 
         result: dict[int, set[int]] = {}
         for row in rows:

py/services/downloader.py

@@ -18,8 +18,14 @@ from collections import deque
 from dataclasses import dataclass
 from datetime import datetime, timedelta
 from email.utils import parsedate_to_datetime
+from urllib.parse import urlparse
 from typing import Optional, Dict, Tuple, Callable, Union, Awaitable
 from ..services.settings_manager import get_settings_manager
+from .connectivity_guard import (
+    OFFLINE_COOLDOWN_ERROR,
+    OFFLINE_FRIENDLY_MESSAGE,
+    ConnectivityGuard,
+)
 from .errors import RateLimitError
 
 logger = logging.getLogger(__name__)
@@ -138,7 +144,7 @@ class Downloader:
         self.chunk_size = (
             16 * 1024 * 1024
         )  # 16MB chunks to balance I/O reduction and memory usage
-        self.max_retries = 5
+        self.max_retries = self._resolve_max_retries()
         self.base_delay = 2.0  # Base delay for exponential backoff
         self.session_timeout = 300  # 5 minutes
         self.stall_timeout = self._resolve_stall_timeout()
@@ -192,6 +198,18 @@ class Downloader:
 
         return max(30.0, timeout_value)
 
+    def _resolve_max_retries(self) -> int:
+        """Determine max retry count from environment while preserving defaults."""
+        default_retries = 5
+        raw_value = os.environ.get("COMFYUI_DOWNLOAD_MAX_RETRIES")
+
+        try:
+            retries = int(raw_value)
+        except (TypeError, ValueError):
+            retries = default_retries
+
+        return max(0, retries)
+
     def _should_refresh_session(self) -> bool:
         """Check if session should be refreshed"""
         if self._session is None:
@@ -334,6 +352,7 @@ class Downloader:
             logger.info(f"Resuming download from offset {resume_offset} bytes")
 
         total_size = 0
+        range_redirect_retry_urls: set[str] = set()
 
         while retry_count <= self.max_retries:
             try:
@@ -372,6 +391,23 @@ class Downloader:
                     if response.status == 200:
                         # Full content response
                         if resume_offset > 0:
+                            redirected_url = str(response.url)
+                            if (
+                                allow_resume
+                                and response.history
+                                and redirected_url
+                                and redirected_url != url
+                                and redirected_url not in range_redirect_retry_urls
+                            ):
+                                range_redirect_retry_urls.add(redirected_url)
+                                logger.info(
+                                    "Range request was not honored after redirect; retrying final URL directly: %s",
+                                    redirected_url,
+                                )
+                                url = redirected_url
+                                response.release()
+                                continue
+
                             # Server doesn't support ranges, restart from beginning
                             logger.warning(
                                 "Server doesn't support range requests, restarting download"
@@ -571,37 +607,53 @@ class Downloader:
                     expected_size = total_size if total_size > 0 else None
 
                     integrity_error: Optional[str] = None
+                    resumable_incomplete = False
                     if final_size <= 0:
                         integrity_error = "Downloaded file is empty"
                     elif expected_size is not None and final_size != expected_size:
                         integrity_error = f"File size mismatch. Expected: {expected_size}, Got: {final_size}"
+                        resumable_incomplete = (
+                            allow_resume
+                            and part_path != save_path
+                            and final_size > 0
+                            and final_size < expected_size
+                        )
 
                     if integrity_error is not None:
-                        logger.error(
+                        log_fn = logger.warning if resumable_incomplete else logger.error
+                        log_fn(
                             "Download integrity check failed for %s: %s",
                             save_path,
                             integrity_error,
                         )
 
-                        # Remove the corrupted payload so future attempts start fresh
-                        if os.path.exists(part_path):
-                            try:
-                                os.remove(part_path)
-                            except OSError as remove_error:
-                                logger.warning(
-                                    "Failed to delete corrupted download %s: %s",
-                                    part_path,
-                                    remove_error,
-                                )
-                        if part_path != save_path and os.path.exists(save_path):
-                            try:
-                                os.remove(save_path)
-                            except OSError as remove_error:
-                                logger.warning(
-                                    "Failed to delete target file %s after integrity error: %s",
-                                    save_path,
-                                    remove_error,
-                                )
+                        if resumable_incomplete:
+                            logger.info(
+                                "Preserving incomplete download for resume: %s (%s/%s bytes)",
+                                part_path,
+                                final_size,
+                                expected_size,
+                            )
+                        else:
+                            # Remove corrupted payloads that cannot be safely resumed.
+                            if os.path.exists(part_path):
+                                try:
+                                    os.remove(part_path)
+                                except OSError as remove_error:
+                                    logger.warning(
+                                        "Failed to delete corrupted download %s: %s",
+                                        part_path,
+                                        remove_error,
+                                    )
+                            if part_path != save_path and os.path.exists(save_path):
+                                try:
+                                    os.remove(save_path)
+                                except OSError as remove_error:
+                                    logger.warning(
+                                        "Failed to delete target file %s after integrity error: %s",
+                                        save_path,
+                                        remove_error,
+                                    )
 
                         retry_count += 1
                         if retry_count <= self.max_retries:
@@ -611,8 +663,16 @@ class Downloader:
                                 delay,
                             )
                             await asyncio.sleep(delay)
-                            resume_offset = 0
-                            total_size = 0
+                            if resumable_incomplete and os.path.exists(part_path):
+                                resume_offset = os.path.getsize(part_path)
+                                total_size = expected_size or 0
+                                logger.info(
+                                    "Will resume incomplete download from byte %s",
+                                    resume_offset,
+                                )
+                            else:
+                                resume_offset = 0
+                                total_size = 0
                             await self._create_session()
                             continue
 
@@ -743,6 +803,11 @@ class Downloader:
         Returns:
             Tuple[bool, Union[bytes, str], Optional[Dict]]: (success, content or error message, response headers if requested)
         """
+        guard = await ConnectivityGuard.get_instance()
+        destination = self._guard_destination(url)
+        if guard.should_block_request(destination):
+            return False, OFFLINE_FRIENDLY_MESSAGE, None
+
         try:
             session = await self.session
             # Debug log for proxy mode at request time
@@ -765,6 +830,7 @@ class Downloader:
             ) as response:
                 if response.status == 200:
                     content = await response.read()
+                    guard.register_success(destination)
                     if return_headers:
                         return True, content, dict(response.headers)
                     else:
@@ -783,6 +849,12 @@ class Downloader:
                     return False, error_msg, None
 
         except Exception as e:
+            if guard.is_network_unreachable_error(e):
+                guard.register_network_failure(e, destination)
+                if guard.should_block_request(destination):
+                    return False, OFFLINE_FRIENDLY_MESSAGE, None
+                logger.debug("Network unavailable during memory download: %s", e)
+                return False, str(e), None
             logger.error(f"Error downloading to memory from {url}: {e}")
             return False, str(e), None
 
@@ -803,6 +875,11 @@ class Downloader:
         Returns:
             Tuple[bool, Union[Dict, str]]: (success, headers dict or error message)
         """
+        guard = await ConnectivityGuard.get_instance()
+        destination = self._guard_destination(url)
+        if guard.should_block_request(destination):
+            return False, OFFLINE_COOLDOWN_ERROR
+
         try:
             session = await self.session
             # Debug log for proxy mode at request time
@@ -824,11 +901,18 @@ class Downloader:
                 url, headers=headers, proxy=self.proxy_url
             ) as response:
                 if response.status == 200:
+                    guard.register_success(destination)
                     return True, dict(response.headers)
                 else:
                     return False, f"Head request failed with status {response.status}"
 
         except Exception as e:
+            if guard.is_network_unreachable_error(e):
+                guard.register_network_failure(e, destination)
+                if guard.should_block_request(destination):
+                    return False, OFFLINE_COOLDOWN_ERROR
+                logger.debug("Network unavailable during header probe: %s", e)
+                return False, str(e)
             logger.error(f"Error getting headers from {url}: {e}")
             return False, str(e)
 
@@ -853,6 +937,11 @@ class Downloader:
         Returns:
             Tuple[bool, Union[Dict, str]]: (success, response data or error message)
         """
+        guard = await ConnectivityGuard.get_instance()
+        destination = self._guard_destination(url)
+        if guard.should_block_request(destination):
+            return False, OFFLINE_COOLDOWN_ERROR
+
         try:
             session = await self.session
             # Debug log for proxy mode at request time
@@ -876,6 +965,7 @@ class Downloader:
                 method, url, headers=headers, **kwargs
             ) as response:
                 if response.status == 200:
+                    guard.register_success(destination)
                     # Try to parse as JSON, fall back to text
                     try:
                         data = await response.json()
@@ -906,6 +996,12 @@ class Downloader:
                     return False, f"Request failed with status {response.status}"
 
         except Exception as e:
+            if guard.is_network_unreachable_error(e):
+                guard.register_network_failure(e, destination)
+                if guard.should_block_request(destination):
+                    return False, OFFLINE_COOLDOWN_ERROR
+                logger.debug("Network unavailable for %s %s: %s", method, url, e)
+                return False, str(e)
             logger.error(f"Error making {method} request to {url}: {e}")
             return False, str(e)
 
@@ -956,6 +1052,14 @@ class Downloader:
         delta = retry_datetime - datetime.now(tz=retry_datetime.tzinfo)
         return max(0.0, delta.total_seconds())
 
+    @staticmethod
+    def _guard_destination(url: str) -> str:
+        """Build per-destination connectivity guard scope from request URL."""
+        parsed_url = urlparse(url)
+        if parsed_url.hostname:
+            return parsed_url.hostname.lower()
+        return "unknown"
+
 
 # Global instance accessor
 async def get_downloader() -> Downloader:

py/services/embedding_service.py

@@ -42,6 +42,7 @@ class EmbeddingService(BaseModelService):
             "notes": embedding_data.get("notes", ""),
             "sub_type": sub_type,
             "favorite": embedding_data.get("favorite", False),
+            "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)

py/services/lora_service.py

@@ -48,6 +48,7 @@ class LoraService(BaseModelService):
             "usage_tips": lora_data.get("usage_tips", ""),
             "notes": lora_data.get("notes", ""),
             "favorite": lora_data.get("favorite", False),
+            "exclude": bool(lora_data.get("exclude", False)),
             "update_available": bool(lora_data.get("update_available", False)),
             "skip_metadata_refresh": bool(
                 lora_data.get("skip_metadata_refresh", False)

py/services/metadata_sync_service.py

@@ -11,6 +11,7 @@ from typing import Any, Awaitable, Callable, Dict, Iterable, Optional
 from ..services.settings_manager import SettingsManager
 from ..utils.civitai_utils import resolve_license_payload
 from ..utils.model_utils import determine_base_model
+from .connectivity_guard import OFFLINE_FRIENDLY_MESSAGE, is_expected_offline_error
 from .errors import RateLimitError
 
 logger = logging.getLogger(__name__)
@@ -274,11 +275,18 @@ class MetadataSyncService:
                     else "No provider returned metadata"
                 )
 
+                resolved_error = last_error or default_error
+                if is_expected_offline_error(resolved_error):
+                    resolved_error = OFFLINE_FRIENDLY_MESSAGE
+
                 error_msg = (
-                    f"Error fetching metadata: {last_error or default_error} "
+                    f"Error fetching metadata: {resolved_error} "
                     f"(model_name={model_data.get('model_name', '')})"
                 )
-                logger.error(error_msg)
+                if is_expected_offline_error(resolved_error):
+                    logger.info(error_msg)
+                else:
+                    logger.error(error_msg)
                 return False, error_msg
 
             model_data["from_civitai"] = True
@@ -347,6 +355,9 @@ class MetadataSyncService:
             return False, error_msg
         except Exception as exc:  # pragma: no cover - error path
             error_msg = f"Error fetching metadata: {exc}"
+            if is_expected_offline_error(str(exc)):
+                logger.info(OFFLINE_FRIENDLY_MESSAGE)
+                return False, OFFLINE_FRIENDLY_MESSAGE
             logger.error(error_msg, exc_info=True)
             return False, error_msg
 

py/services/model_hash_index.py

@@ -79,6 +79,12 @@ 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

py/services/model_lifecycle_service.py

@@ -8,6 +8,7 @@ from typing import Any, Awaitable, Callable, Dict, Iterable, List, Mapping, Opti
 
 from ..services.service_registry import ServiceRegistry
 from ..utils.constants import PREVIEW_EXTENSIONS
+from ..utils.metadata_manager import MetadataManager
 
 logger = logging.getLogger(__name__)
 
@@ -207,11 +208,56 @@ class ModelLifecycleService:
 
         excluded = getattr(self._scanner, "_excluded_models", None)
         if isinstance(excluded, list):
-            excluded.append(file_path)
+            if file_path not in excluded:
+                excluded.append(file_path)
+
+        persist_current_cache = getattr(self._scanner, "_persist_current_cache", None)
+        if callable(persist_current_cache):
+            await persist_current_cache()
 
         message = f"Model {os.path.basename(file_path)} excluded"
         return {"success": True, "message": message}
 
+    async def unexclude_model(self, file_path: str) -> Dict[str, object]:
+        """Restore a previously excluded model to the active cache."""
+
+        if not file_path:
+            raise ValueError("Model path is required")
+
+        if not os.path.exists(file_path):
+            raise ValueError("Model file does not exist")
+
+        metadata_path = os.path.splitext(file_path)[0] + ".metadata.json"
+        metadata_payload = await self._metadata_loader(metadata_path)
+        metadata_payload["exclude"] = False
+
+        await self._metadata_manager.save_metadata(file_path, metadata_payload)
+
+        metadata, should_skip = await MetadataManager.load_metadata(
+            file_path,
+            self._scanner.model_class,
+        )
+        if should_skip:
+            metadata = None
+        if metadata is None:
+            metadata = metadata_payload
+
+        excluded = getattr(self._scanner, "_excluded_models", None)
+        if isinstance(excluded, list):
+            self._scanner._excluded_models = [
+                path for path in excluded if path != file_path
+            ]
+
+        await self._scanner.update_single_model_cache(
+            file_path,
+            file_path,
+            metadata,
+            recalculate_type=True,
+        )
+
+        message = f"Model {os.path.basename(file_path)} restored"
+        return {"success": True, "message": message}
+
     async def bulk_delete_models(self, file_paths: Iterable[str]) -> Dict[str, object]:
         """Delete a collection of models via the scanner bulk operation."""
 

py/services/model_metadata_provider.py

@@ -108,6 +108,18 @@ class ModelMetadataProvider(ABC):
     ) -> Optional[Dict[int, Dict]]:
         """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]:
@@ -140,6 +152,11 @@ class CivitaiModelMetadataProvider(ModelMetadataProvider):
         self, model_ids: Sequence[int]
     ) -> 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)
@@ -519,6 +536,32 @@ 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 +636,15 @@ 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 +721,17 @@ 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_scanner.py

@@ -1072,14 +1072,6 @@ class ModelScanner:
             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 +1097,31 @@ 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."""
+        if self._hash_index is None:
+            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]],
@@ -1535,7 +1552,7 @@ class ModelScanner:
         return sorted_tags[:limit]
         
     async def get_base_models(self, limit: int = 20) -> List[Dict[str, any]]:
-        """Get base models sorted by frequency"""
+        """Get base models sorted by count. If limit is 0, return all."""
         cache = await self.get_cached_data()
         
         base_model_counts = {}
@@ -1546,7 +1563,9 @@ class ModelScanner:
         
         sorted_models = [{'name': model, 'count': count} for model, count in base_model_counts.items()]
         sorted_models.sort(key=lambda x: x['count'], reverse=True)
-        
+
+        if limit == 0:
+            return sorted_models
         return sorted_models[:limit]
         
     async def get_model_info_by_name(self, name):

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():
@@ -965,6 +989,11 @@ 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:
@@ -1059,6 +1088,136 @@ 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 +1269,7 @@ class ModelUpdateService:
             len(aggregated),
             provider_name,
         )
+        await self._enrich_version_entries(metadata_provider, aggregated)
         return aggregated
 
     async def _collect_local_versions(
@@ -1237,6 +1397,7 @@ 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 +1496,7 @@ 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 +1510,7 @@ 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]:
@@ -1439,33 +1602,41 @@ class ModelUpdateService:
         if not model_ids:
             return {}
 
-        params = tuple(model_ids)
-        placeholders = ",".join("?" for _ in params)
+        ids = list(model_ids)
+        status_rows: list = []
+        version_rows: list = []
 
         with self._connect() as conn:
-            status_rows = conn.execute(
-                f"""
-                SELECT model_id, model_type, last_checked_at, should_ignore_model
-                FROM model_update_status
-                WHERE model_id IN ({placeholders})
-                """,
-                params,
-            ).fetchall()
+            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})
+                    """,
+                    chunk,
+                ).fetchall()
+                status_rows.extend(chunk_status)
+
+                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, usage_control
+                    FROM model_update_versions
+                    WHERE model_id IN ({placeholders})
+                    ORDER BY model_id ASC, sort_index ASC, version_id ASC
+                    """,
+                    chunk,
+                ).fetchall()
+                version_rows.extend(chunk_versions)
+
             if not status_rows:
                 return {}
 
-            version_rows = 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
-                FROM model_update_versions
-                WHERE model_id IN ({placeholders})
-                ORDER BY model_id ASC, sort_index ASC, version_id ASC
-                """,
-                params,
-            ).fetchall()
-
         versions_by_model: Dict[int, List[ModelVersionRecord]] = {}
         for row in version_rows:
             model_id = int(row["model_id"])
@@ -1482,6 +1653,7 @@ 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 +1710,8 @@ 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
-                    ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+                        is_early_access, usage_control
+                    ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
                     """,
                     (
                         version.version_id,
@@ -1554,6 +1726,7 @@ 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/recipe_scanner.py

@@ -1815,6 +1815,15 @@ 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,

py/services/recipes/analysis_service.py

@@ -5,7 +5,6 @@ from __future__ import annotations
 import base64
 import io
 import os
-import re
 import tempfile
 from dataclasses import dataclass
 from typing import Any, Callable, Optional
@@ -14,7 +13,7 @@ import numpy as np
 from PIL import Image
 
 from ...utils.utils import calculate_recipe_fingerprint
-from ...utils.civitai_utils import rewrite_preview_url
+from ...utils.civitai_utils import extract_civitai_image_id, rewrite_preview_url
 from .errors import (
     RecipeDownloadError,
     RecipeNotFoundError,
@@ -104,9 +103,11 @@ class RecipeAnalysisService:
         extension = ".jpg"  # Default
 
         try:
-            civitai_match = re.match(r"https://civitai\.com/images/(\d+)", url)
-            if civitai_match:
-                image_info = await civitai_client.get_image_info(civitai_match.group(1))
+            civitai_image_id = extract_civitai_image_id(url)
+            if civitai_image_id:
+                image_info = await civitai_client.get_image_info(
+                    civitai_image_id, source_url=url
+                )
                 if not image_info:
                     raise RecipeDownloadError(
                         "Failed to fetch image information from Civitai"

py/services/recipes/persistence_service.py

@@ -508,6 +508,10 @@ 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 +519,8 @@ 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 +528,8 @@ 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 +551,91 @@ 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/settings_manager.py

@@ -2,6 +2,7 @@ import asyncio
 import copy
 import json
 import os
+import posixpath
 import shutil
 import tempfile
 import logging
@@ -54,6 +55,9 @@ DEFAULT_KEYS_CLEANUP_THRESHOLD = 10
 
 DEFAULT_SETTINGS: Dict[str, Any] = {
     "civitai_api_key": "",
+    "civitai_host": "civitai.com",
+    "download_backend": "python",
+    "aria2c_path": "",
     "use_portable_settings": False,
     "hash_chunk_size_mb": DEFAULT_HASH_CHUNK_SIZE_MB,
     "language": "en",
@@ -77,6 +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,
@@ -90,6 +97,7 @@ DEFAULT_SETTINGS: Dict[str, Any] = {
     "priority_tags": DEFAULT_PRIORITY_TAG_CONFIG.copy(),
     "model_name_display": "model_name",
     "model_card_footer_action": "replace_preview",
+    "show_version_on_card": True,
     "update_flag_strategy": "same_base",
     "auto_organize_exclusions": [],
     "metadata_refresh_skip_paths": [],
@@ -100,6 +108,15 @@ DEFAULT_SETTINGS: Dict[str, Any] = {
 }
 
 
+def _normalize_root_identity(path: str) -> str:
+    """Normalize a root path for equality checks across slash styles."""
+
+    normalized = posixpath.normpath(path.strip().replace("\\", "/"))
+    if len(normalized) >= 2 and normalized[1] == ":":
+        return normalized.lower()
+    return normalized
+
+
 class SettingsManager:
     def __init__(self):
         self.settings_file = ensure_settings_file(logger)
@@ -760,34 +777,29 @@ class SettingsManager:
         if self._preserve_disk_template:
             return
 
-        folder_paths = self.settings.get("folder_paths", {})
         updated = False
 
         def _check_and_auto_set(key: str, setting_key: str) -> bool:
             """Repair default roots when empty or no longer present."""
             current = self.settings.get(setting_key, "")
-            candidates = folder_paths.get(key, [])
-            if not isinstance(candidates, list) or not candidates:
+            primary_candidates = self._get_valid_root_candidates(key)
+            if not primary_candidates:
                 return False
 
-            # Filter valid path strings
-            valid_paths = [p for p in candidates if isinstance(p, str) and p.strip()]
-            if not valid_paths:
+            allowed_roots = self._get_allowed_roots(key)
+            if current and _normalize_root_identity(current) in allowed_roots:
                 return False
 
-            if current in valid_paths:
-                return False
-
-            self.settings[setting_key] = valid_paths[0]
+            self.settings[setting_key] = primary_candidates[0]
             if current:
                 logger.info(
-                    "Repaired stale %s from '%s' to '%s'",
+                    "Repaired stale %s from '%s' to '%s' because it is not present in primary or extra roots",
                     setting_key,
                     current,
-                    valid_paths[0],
+                    primary_candidates[0],
                 )
             else:
-                logger.info("Auto-set %s to '%s'", setting_key, valid_paths[0])
+                logger.info("Auto-set %s to '%s'", setting_key, primary_candidates[0])
             return True
 
         # Process all model types
@@ -810,6 +822,36 @@ class SettingsManager:
             else:
                 self._save_settings()
 
+    def _get_valid_root_candidates(self, key: str) -> List[str]:
+        """Return stable root candidates, preferring primary roots over extra roots."""
+
+        candidates: List[str] = []
+        seen: set[str] = set()
+        for mapping_key in ("folder_paths", "extra_folder_paths"):
+            raw_paths = self.settings.get(mapping_key, {})
+            if not isinstance(raw_paths, Mapping):
+                continue
+            values = raw_paths.get(key, [])
+            if not isinstance(values, list):
+                continue
+            for value in values:
+                if not isinstance(value, str):
+                    continue
+                normalized = value.strip()
+                if not normalized:
+                    continue
+                identity = _normalize_root_identity(normalized)
+                if identity in seen:
+                    continue
+                seen.add(identity)
+                candidates.append(normalized)
+        return candidates
+
+    def _get_allowed_roots(self, key: str) -> set[str]:
+        """Return all valid roots for a model type, including extra roots."""
+
+        return {_normalize_root_identity(path) for path in self._get_valid_root_candidates(key)}
+
     def _check_environment_variables(self) -> None:
         """Check for environment variables and update settings if needed"""
         env_api_key = os.environ.get("CIVITAI_API_KEY")

py/services/tag_fts_index.py

@@ -450,9 +450,9 @@ class TagFTSIndex:
         the tag_name, the result will include a "matched_alias" field.
 
         Ranking is based on a combination of:
-        1. FTS5 bm25 relevance score (how well the text matches)
-        2. Post count (popularity)
-        3. Exact prefix match boost (tag_name starts with query)
+        1. Exact prefix match boost (tag_name starts with query)
+        2. Post count to preserve expected autocomplete ordering
+        3. FTS5 bm25 relevance score as a deterministic tie-breaker
 
         Args:
             query: The search query string.
@@ -484,65 +484,17 @@ class TagFTSIndex:
             with self._lock:
                 conn = self._connect(readonly=True)
                 try:
-                    # Build the SQL query with bm25 ranking
-                    # FTS5 bm25() returns negative scores, lower is better
-                    # We use -bm25() to get higher=better scores
-                    # Weights: -100.0 for exact matches, 1.0 for others
-                    # Add LOG10(post_count) weighting to boost popular tags
-                    # Use CASE to boost tag_name prefix matches above alias matches
-                    if categories:
-                        placeholders = ",".join("?" * len(categories))
-                        sql = f"""
-                            SELECT t.tag_name, t.category, t.post_count, t.aliases,
-                                   CASE 
-                                       WHEN t.tag_name LIKE ? ESCAPE '\\' THEN 1
-                                       ELSE 0
-                                   END AS is_tag_name_match,
-                                   bm25(tag_fts, -100.0, 1.0, 1.0) + LOG10(t.post_count + 1) * 10.0 AS rank_score
-                            FROM tag_fts
-                            JOIN tags t ON tag_fts.rowid = t.rowid
-                            WHERE tag_fts.searchable_text MATCH ?
-                            AND t.category IN ({placeholders})
-                            ORDER BY is_tag_name_match DESC, rank_score DESC
-                            LIMIT ? OFFSET ?
-                        """
-                        # Escape special LIKE characters and add wildcard
-                        query_escaped = (
-                            query_lower.lstrip("/")
-                            .replace("\\", "\\\\")
-                            .replace("%", "\\%")
-                            .replace("_", "\\_")
-                        )
-                        params = (
-                            [query_escaped + "%", fts_query]
-                            + categories
-                            + [limit, offset]
-                        )
-                    else:
-                        sql = """
-                            SELECT t.tag_name, t.category, t.post_count, t.aliases,
-                                   CASE 
-                                       WHEN t.tag_name LIKE ? ESCAPE '\\' THEN 1
-                                       ELSE 0
-                                   END AS is_tag_name_match,
-                                   bm25(tag_fts, -100.0, 1.0, 1.0) + LOG10(t.post_count + 1) * 10.0 AS rank_score
-                            FROM tag_fts
-                            JOIN tags t ON tag_fts.rowid = t.rowid
-                            WHERE tag_fts.searchable_text MATCH ?
-                            ORDER BY is_tag_name_match DESC, rank_score DESC
-                            LIMIT ? OFFSET ?
-                        """
-                        query_escaped = (
-                            query_lower.lstrip("/")
-                            .replace("\\", "\\\\")
-                            .replace("%", "\\%")
-                            .replace("_", "\\_")
-                        )
-                        params = [query_escaped + "%", fts_query, limit, offset]
-
+                    sql, params = self._build_search_statement(
+                        query_lower=query_lower,
+                        fts_query=fts_query,
+                        categories=categories,
+                        limit=limit,
+                        offset=offset,
+                    )
                     cursor = conn.execute(sql, params)
+                    rows = cursor.fetchall()
                     results = []
-                    for row in cursor.fetchall():
+                    for row in rows:
                         result = {
                             "tag_name": row[0],
                             "category": row[1],
@@ -571,6 +523,62 @@ class TagFTSIndex:
             logger.debug("Tag FTS search error for query '%s': %s", query, exc)
             return []
 
+    def _build_search_statement(
+        self,
+        query_lower: str,
+        fts_query: str,
+        categories: Optional[List[int]],
+        limit: int,
+        offset: int,
+    ) -> tuple[str, list[object]]:
+        """Build the SQL statement and params for a tag search."""
+        # Escape special LIKE characters and add wildcard
+        query_escaped = (
+            query_lower.lstrip("/")
+            .replace("\\", "\\\\")
+            .replace("%", "\\%")
+            .replace("_", "\\_")
+        )
+
+        # FTS5 bm25() returns negative scores, lower is better.
+        # We use -bm25() to get higher=better scores, but keep post_count as the
+        # primary sort within tag-name prefix matches so autocomplete ordering
+        # remains aligned with the existing popularity-first behavior.
+        if categories:
+            placeholders = ",".join("?" * len(categories))
+            sql = f"""
+                SELECT t.tag_name, t.category, t.post_count, t.aliases,
+                       CASE
+                           WHEN t.tag_name LIKE ? ESCAPE '\\' THEN 1
+                           ELSE 0
+                       END AS is_tag_name_match,
+                       bm25(tag_fts, -100.0, 1.0, 1.0) AS rank_score
+                FROM tag_fts
+                CROSS JOIN tags t ON t.rowid = tag_fts.rowid
+                WHERE tag_fts.searchable_text MATCH ?
+                  AND t.category IN ({placeholders})
+                ORDER BY is_tag_name_match DESC, t.post_count DESC, rank_score DESC
+                LIMIT ? OFFSET ?
+            """
+            params = [query_escaped + "%", fts_query] + categories + [limit, offset]
+        else:
+            sql = """
+                SELECT t.tag_name, t.category, t.post_count, t.aliases,
+                       CASE
+                           WHEN t.tag_name LIKE ? ESCAPE '\\' THEN 1
+                           ELSE 0
+                       END AS is_tag_name_match,
+                       bm25(tag_fts, -100.0, 1.0, 1.0) AS rank_score
+                FROM tag_fts
+                JOIN tags t ON tag_fts.rowid = t.rowid
+                WHERE tag_fts.searchable_text MATCH ?
+                ORDER BY is_tag_name_match DESC, t.post_count DESC, rank_score DESC
+                LIMIT ? OFFSET ?
+            """
+            params = [query_escaped + "%", fts_query, limit, offset]
+
+        return sql, params
+
     def _find_matched_alias(
         self, query: str, tag_name: str, aliases_str: str
     ) -> Optional[str]:

py/services/wildcard_service.py

@@ -0,0 +1,428 @@
+"""Managed wildcard loading, search, and text expansion."""
+
+from __future__ import annotations
+
+import json
+import logging
+import os
+import random
+import re
+from dataclasses import dataclass
+from typing import Any, Optional
+
+import yaml
+
+from ..utils.settings_paths import get_settings_dir
+
+logger = logging.getLogger(__name__)
+
+_WILDCARD_PATTERN = re.compile(r"__([\w\s.\-+/*\\]+?)__")
+_OPTION_PATTERN = re.compile(r"{([^{}]*?)}")
+_TRIGGER_WORD_PATTERN = re.compile(r"^trigger_words\d+$")
+_WEIGHTED_OPTION_PATTERN = re.compile(r"^\s*([0-9.]+)::")
+_NUMERIC_PATTERN = re.compile(r"^-?\d+(\.\d+)?$")
+
+
+def _normalize_wildcard_key(value: str) -> str:
+    return value.replace("\\", "/").strip("/").lower()
+
+
+def _is_numeric_string(value: str) -> bool:
+    return bool(_NUMERIC_PATTERN.match(value))
+
+
+def contains_dynamic_syntax(text: str) -> bool:
+    """Return True when text contains supported wildcard or option syntax."""
+
+    return isinstance(text, str) and bool(
+        _WILDCARD_PATTERN.search(text) or _OPTION_PATTERN.search(text)
+    )
+
+
+def get_wildcards_dir(create: bool = False) -> str:
+    """Return the managed wildcard directory inside the settings folder."""
+
+    settings_dir = get_settings_dir(create=create)
+    wildcards_dir = os.path.join(settings_dir, "wildcards")
+    if create:
+        os.makedirs(wildcards_dir, exist_ok=True)
+    return wildcards_dir
+
+
+@dataclass(frozen=True)
+class WildcardEntry:
+    key: str
+    values_count: int
+
+
+@dataclass(frozen=True)
+class WildcardMetadata:
+    has_wildcards: bool
+    wildcards_dir: str
+    supported_formats: tuple[str, ...]
+
+
+class WildcardService:
+    """Discover wildcard keys and expand wildcard syntax."""
+
+    _instance: Optional["WildcardService"] = None
+
+    def __new__(cls) -> "WildcardService":
+        if cls._instance is None:
+            cls._instance = super().__new__(cls)
+        return cls._instance
+
+    def __init__(self) -> None:
+        if getattr(self, "_initialized", False):
+            return
+        self._initialized = True
+        self._cached_signature: tuple[tuple[str, int, int], ...] | None = None
+        self._wildcard_dict: dict[str, list[str]] = {}
+
+    @classmethod
+    def get_instance(cls) -> "WildcardService":
+        return cls()
+
+    def search_keys(
+        self, search_term: str, limit: int = 20, offset: int = 0
+    ) -> list[str]:
+        """Search wildcard keys for autocomplete."""
+
+        normalized_term = _normalize_wildcard_key(search_term).strip()
+        if not normalized_term:
+            return []
+
+        ranked: list[tuple[int, str]] = []
+        compact_term = normalized_term.replace("/", "")
+        for key in self.get_wildcard_dict().keys():
+            score = self._score_entry(key, normalized_term, compact_term)
+            if score is not None:
+                ranked.append((score, key))
+
+        ranked.sort(key=lambda item: (-item[0], item[1]))
+        keys = [key for _, key in ranked]
+        return keys[offset : offset + limit]
+
+    def expand_text(self, text: str, seed: int | None = None) -> str:
+        """Expand wildcard and dynamic prompt syntax for a text value."""
+
+        if not isinstance(text, str) or not text:
+            return text
+
+        rng = random.Random(seed) if seed is not None else random.Random()
+        wildcard_dict = self.get_wildcard_dict()
+        if not wildcard_dict:
+            return self._expand_options_only(text, rng)
+
+        current = text
+        remaining_depth = 100
+
+        while remaining_depth > 0:
+            remaining_depth -= 1
+            after_options, options_replaced = self._replace_options(current, rng)
+            current, wildcards_replaced = self._replace_wildcards(
+                after_options, rng, wildcard_dict
+            )
+            if not options_replaced and not wildcards_replaced:
+                break
+
+        return current
+
+    def get_wildcard_dict(self) -> dict[str, list[str]]:
+        signature = self._build_signature()
+        if signature != self._cached_signature:
+            self._wildcard_dict = self._scan_wildcard_dict()
+            self._cached_signature = signature
+        return self._wildcard_dict
+
+    def get_entries(self) -> list[WildcardEntry]:
+        return [
+            WildcardEntry(key=key, values_count=len(values))
+            for key, values in sorted(self.get_wildcard_dict().items())
+        ]
+
+    def get_metadata(self, *, create_dir: bool = False) -> WildcardMetadata:
+        wildcards_dir = get_wildcards_dir(create=create_dir)
+        return WildcardMetadata(
+            has_wildcards=bool(self.get_wildcard_dict()),
+            wildcards_dir=wildcards_dir,
+            supported_formats=(".txt", ".yaml", ".yml", ".json"),
+        )
+
+    def _build_signature(self) -> tuple[tuple[str, int, int], ...]:
+        root = get_wildcards_dir(create=False)
+        if not os.path.isdir(root):
+            return ()
+
+        signature: list[tuple[str, int, int]] = []
+        for current_root, _dirs, files in os.walk(root, followlinks=True):
+            for file_name in sorted(files):
+                if not file_name.lower().endswith((".txt", ".yaml", ".yml", ".json")):
+                    continue
+                file_path = os.path.join(current_root, file_name)
+                try:
+                    stat = os.stat(file_path)
+                except OSError:
+                    continue
+                rel_path = os.path.relpath(file_path, root).replace("\\", "/")
+                signature.append((rel_path, int(stat.st_mtime_ns), int(stat.st_size)))
+        signature.sort()
+        return tuple(signature)
+
+    def _scan_wildcard_dict(self) -> dict[str, list[str]]:
+        root = get_wildcards_dir(create=False)
+        if not os.path.isdir(root):
+            return {}
+
+        collected: dict[str, list[str]] = {}
+        for current_root, _dirs, files in os.walk(root, followlinks=True):
+            for file_name in sorted(files):
+                file_path = os.path.join(current_root, file_name)
+                lower_name = file_name.lower()
+                try:
+                    if lower_name.endswith(".txt"):
+                        rel_path = os.path.relpath(file_path, root)
+                        key = _normalize_wildcard_key(os.path.splitext(rel_path)[0])
+                        values = self._read_txt(file_path)
+                        if values:
+                            collected[key] = values
+                    elif lower_name.endswith((".yaml", ".yml")):
+                        payload = self._read_yaml(file_path)
+                        self._merge_nested_entries(collected, payload)
+                    elif lower_name.endswith(".json"):
+                        payload = self._read_json(file_path)
+                        self._merge_nested_entries(collected, payload)
+                except Exception as exc:  # pragma: no cover - defensive logging
+                    logger.warning("Failed to load wildcard file %s: %s", file_path, exc)
+
+        return collected
+
+    def _read_txt(self, file_path: str) -> list[str]:
+        try:
+            with open(file_path, "r", encoding="utf-8", errors="ignore") as handle:
+                return [line.strip() for line in handle.read().splitlines() if line.strip()]
+        except OSError as exc:
+            logger.warning("Failed to read wildcard txt file %s: %s", file_path, exc)
+            return []
+
+    def _read_yaml(self, file_path: str) -> Any:
+        with open(file_path, "r", encoding="utf-8") as handle:
+            return yaml.safe_load(handle) or {}
+
+    def _read_json(self, file_path: str) -> Any:
+        with open(file_path, "r", encoding="utf-8") as handle:
+            return json.load(handle)
+
+    def _merge_nested_entries(
+        self, collected: dict[str, list[str]], payload: Any
+    ) -> None:
+        for key, values in self._flatten_payload(payload):
+            collected[key] = values
+
+    def _flatten_payload(
+        self, payload: Any, prefix: str = ""
+    ) -> list[tuple[str, list[str]]]:
+        entries: list[tuple[str, list[str]]] = []
+
+        if isinstance(payload, dict):
+            for key, value in payload.items():
+                next_prefix = f"{prefix}/{key}" if prefix else str(key)
+                entries.extend(self._flatten_payload(value, next_prefix))
+            return entries
+
+        if isinstance(payload, list):
+            normalized_prefix = _normalize_wildcard_key(prefix)
+            values = [value.strip() for value in payload if isinstance(value, str) and value.strip()]
+            if normalized_prefix and values:
+                entries.append((normalized_prefix, values))
+            return entries
+
+        return entries
+
+    def _score_entry(
+        self, key: str, normalized_term: str, compact_term: str
+    ) -> int | None:
+        key_compact = key.replace("/", "")
+        if key == normalized_term:
+            return 5000
+        if key.startswith(normalized_term):
+            return 4000
+        if f"/{normalized_term}" in key:
+            return 3500
+        if normalized_term in key:
+            return 3000
+        if compact_term and key_compact.startswith(compact_term):
+            return 2500
+        if compact_term and compact_term in key_compact:
+            return 2000
+        return None
+
+    def _expand_options_only(self, text: str, rng: random.Random) -> str:
+        current = text
+        remaining_depth = 100
+        while remaining_depth > 0:
+            remaining_depth -= 1
+            current, replaced = self._replace_options(current, rng)
+            if not replaced:
+                break
+        return current
+
+    def _replace_options(
+        self, text: str, rng: random.Random
+    ) -> tuple[str, bool]:
+        replaced_any = False
+
+        def replace_option(match: re.Match[str]) -> str:
+            nonlocal replaced_any
+            replacement = self._resolve_option_group(match.group(1), rng)
+            replaced_any = True
+            return replacement
+
+        return _OPTION_PATTERN.sub(replace_option, text), replaced_any
+
+    def _resolve_option_group(self, group_text: str, rng: random.Random) -> str:
+        options = group_text.split("|")
+        multi_select_pattern = options[0].split("$$")
+        select_range: tuple[int, int] | None = None
+        select_separator = " "
+
+        if len(multi_select_pattern) > 1:
+            count_spec = multi_select_pattern[0]
+            range_match = re.match(r"(\d+)(-(\d+))?$", count_spec)
+            shorthand_match = re.match(r"-(\d+)$", count_spec)
+            if range_match:
+                start_text = range_match.group(1)
+                end_text = range_match.group(3)
+                if end_text is not None and _is_numeric_string(start_text) and _is_numeric_string(end_text):
+                    select_range = (int(start_text), int(end_text))
+                elif _is_numeric_string(start_text):
+                    value = int(start_text)
+                    select_range = (value, value)
+            elif shorthand_match:
+                end_text = shorthand_match.group(1)
+                if _is_numeric_string(end_text):
+                    select_range = (1, int(end_text))
+
+            if select_range is not None and len(multi_select_pattern) == 2:
+                options[0] = multi_select_pattern[1]
+            elif select_range is not None and len(multi_select_pattern) >= 3:
+                select_separator = multi_select_pattern[1]
+                options[0] = multi_select_pattern[2]
+
+        weighted_options: list[tuple[float, str]] = []
+        for option in options:
+            weight = 1.0
+            parts = option.split("::", 1)
+            if len(parts) == 2 and _is_numeric_string(parts[0].strip()):
+                weight = float(parts[0].strip())
+            weighted_options.append((weight, option))
+
+        if select_range is None:
+            selection_count = 1
+        else:
+            selection_count = rng.randint(select_range[0], select_range[1])
+
+        if selection_count <= 1:
+            return self._strip_weight_prefix(self._weighted_choice(weighted_options, rng))
+
+        selection_count = min(selection_count, len(weighted_options))
+        selected: list[str] = []
+        used_indexes: set[int] = set()
+        while len(selected) < selection_count:
+            picked_index = self._weighted_choice_index(weighted_options, rng)
+            if picked_index in used_indexes:
+                if len(used_indexes) == len(weighted_options):
+                    break
+                continue
+            used_indexes.add(picked_index)
+            selected.append(
+                self._strip_weight_prefix(weighted_options[picked_index][1])
+            )
+
+        return select_separator.join(selected)
+
+    def _weighted_choice(
+        self, weighted_options: list[tuple[float, str]], rng: random.Random
+    ) -> str:
+        return weighted_options[self._weighted_choice_index(weighted_options, rng)][1]
+
+    def _weighted_choice_index(
+        self, weighted_options: list[tuple[float, str]], rng: random.Random
+    ) -> int:
+        total_weight = sum(max(weight, 0.0) for weight, _value in weighted_options)
+        if total_weight <= 0:
+            return rng.randrange(len(weighted_options))
+
+        threshold = rng.uniform(0, total_weight)
+        cumulative = 0.0
+        for index, (weight, _value) in enumerate(weighted_options):
+            cumulative += max(weight, 0.0)
+            if threshold <= cumulative:
+                return index
+        return len(weighted_options) - 1
+
+    def _strip_weight_prefix(self, value: str) -> str:
+        return _WEIGHTED_OPTION_PATTERN.sub("", value, count=1)
+
+    def _replace_wildcards(
+        self,
+        text: str,
+        rng: random.Random,
+        wildcard_dict: dict[str, list[str]],
+    ) -> tuple[str, bool]:
+        replaced_any = False
+
+        def replace_match(match: re.Match[str]) -> str:
+            nonlocal replaced_any
+            replacement = self._resolve_wildcard_match(match.group(1), rng, wildcard_dict)
+            if replacement is None:
+                return match.group(0)
+            replaced_any = True
+            return replacement
+
+        return _WILDCARD_PATTERN.sub(replace_match, text), replaced_any
+
+    def _resolve_wildcard_match(
+        self,
+        raw_key: str,
+        rng: random.Random,
+        wildcard_dict: dict[str, list[str]],
+    ) -> str | None:
+        keyword = _normalize_wildcard_key(raw_key)
+        if keyword in wildcard_dict:
+            return rng.choice(wildcard_dict[keyword])
+
+        if "*" in keyword:
+            regex_pattern = keyword.replace("*", ".*").replace("+", r"\+")
+            compiled = re.compile(f"^{regex_pattern}$")
+            aggregated: list[str] = []
+            for key, values in wildcard_dict.items():
+                if compiled.match(key):
+                    aggregated.extend(values)
+            if aggregated:
+                return rng.choice(aggregated)
+
+        if "/" not in keyword:
+            fallback_keyword = _normalize_wildcard_key(f"*/{keyword}")
+            if fallback_keyword != keyword:
+                return self._resolve_wildcard_match(fallback_keyword, rng, wildcard_dict)
+
+        return None
+
+
+def is_trigger_words_input(name: str) -> bool:
+    return bool(_TRIGGER_WORD_PATTERN.match(name))
+
+
+def get_wildcard_service() -> WildcardService:
+    return WildcardService.get_instance()
+
+
+__all__ = [
+    "WildcardService",
+    "WildcardMetadata",
+    "contains_dynamic_syntax",
+    "get_wildcard_service",
+    "get_wildcards_dir",
+    "is_trigger_words_input",
+]

py/utils/civitai_utils.py

@@ -2,10 +2,13 @@
 
 from __future__ import annotations
 
+import re
 from typing import Any, Dict, Iterable, Mapping, Sequence
-from urllib.parse import urlparse, urlunparse
+from urllib.parse import parse_qs, urlparse, urlunparse
 
 
+_SUPPORTED_CIVITAI_PAGE_HOSTS = frozenset({"civitai.com", "civitai.red"})
+DEFAULT_CIVITAI_PAGE_HOST = "civitai.com"
 _DEFAULT_ALLOW_COMMERCIAL_USE: Sequence[str] = ("Sell",)
 _LICENSE_DEFAULTS: Dict[str, Any] = {
     "allowNoCredit": True,
@@ -17,6 +20,133 @@ _COMMERCIAL_ALLOWED_VALUES = {"sell", "rent", "rentcivit", "image"}
 _COMMERCIAL_SHIFT = 1
 
 
+def is_supported_civitai_page_host(hostname: str | None) -> bool:
+    """Return whether the hostname is a supported Civitai page domain."""
+
+    if not hostname:
+        return False
+    return hostname.lower() in _SUPPORTED_CIVITAI_PAGE_HOSTS
+
+
+def normalize_civitai_page_host(hostname: str | None) -> str:
+    """Return a supported Civitai page host or the default host."""
+
+    if not isinstance(hostname, str):
+        return DEFAULT_CIVITAI_PAGE_HOST
+
+    normalized = hostname.strip().lower()
+    if is_supported_civitai_page_host(normalized):
+        return normalized
+
+    return DEFAULT_CIVITAI_PAGE_HOST
+
+
+def build_civitai_model_page_url(
+    model_id: str | int | None,
+    version_id: str | int | None = None,
+    *,
+    host: str | None = None,
+) -> str | None:
+    """Build a Civitai model or model-version page URL."""
+
+    normalized_host = normalize_civitai_page_host(host)
+    normalized_model_id = str(model_id).strip() if model_id is not None else ""
+    normalized_version_id = str(version_id).strip() if version_id is not None else ""
+
+    if normalized_model_id:
+        path = f"/models/{normalized_model_id}"
+        query = f"modelVersionId={normalized_version_id}" if normalized_version_id else ""
+        return urlunparse(("https", normalized_host, path, "", query, ""))
+
+    if normalized_version_id:
+        return urlunparse(
+            ("https", normalized_host, f"/model-versions/{normalized_version_id}", "", "", "")
+        )
+
+    return None
+
+
+def _parse_supported_civitai_page_url(url: str | None):
+    if not url:
+        return None
+
+    try:
+        parsed = urlparse(url)
+    except ValueError:
+        return None
+
+    if parsed.scheme not in {"http", "https"}:
+        return None
+
+    if not is_supported_civitai_page_host(parsed.hostname):
+        return None
+
+    return parsed
+
+
+def extract_civitai_model_url_parts(
+    url: str | None,
+) -> tuple[str | None, str | None]:
+    """Extract model and version identifiers from a supported Civitai model URL."""
+
+    parsed = _parse_supported_civitai_page_url(url)
+    if parsed is None:
+        return None, None
+
+    path_match = re.search(r"/models/(\d+)", parsed.path)
+    if not path_match:
+        return None, None
+
+    model_id = path_match.group(1)
+
+    query_params = parse_qs(parsed.query)
+    version_values = query_params.get("modelVersionId") or []
+    version_id = version_values[0] if version_values else None
+    return model_id, version_id
+
+
+def extract_civitai_image_id(url: str | None) -> str | None:
+    """Extract the image identifier from a supported Civitai image page URL."""
+
+    parsed = _parse_supported_civitai_page_url(url)
+    if parsed is None:
+        return None
+
+    path_match = re.search(r"/images/(\d+)", parsed.path)
+    if not path_match:
+        return None
+
+    return path_match.group(1)
+
+
+def normalize_civitai_download_url(url: str | None) -> str | None:
+    """Rewrite Civitai download URLs to the canonical authenticated host."""
+
+    if not url:
+        return url
+
+    try:
+        parsed = urlparse(url)
+    except ValueError:
+        return url
+
+    hostname = parsed.hostname.lower() if parsed.hostname else None
+    if hostname != "civitai.red" or not parsed.path.startswith("/api/download/"):
+        return url
+
+    return urlunparse(parsed._replace(netloc="civitai.com"))
+
+
+def extract_civitai_page_host(url: str | None) -> str | None:
+    """Extract the supported Civitai page host from a URL."""
+
+    parsed = _parse_supported_civitai_page_url(url)
+    if parsed is None:
+        return None
+
+    return parsed.hostname.lower() if parsed.hostname else None
+
+
 def _normalize_commercial_values(value: Any) -> Sequence[str]:
     """Return a normalized list of commercial permissions preserving source values."""
 
@@ -199,6 +329,10 @@ def rewrite_preview_url(
 
 __all__ = [
     "build_license_flags",
+    "extract_civitai_image_id",
+    "extract_civitai_page_host",
+    "extract_civitai_model_url_parts",
+    "is_supported_civitai_page_host",
     "resolve_license_payload",
     "resolve_license_info",
     "rewrite_preview_url",

py/utils/constants.py

@@ -100,6 +100,7 @@ DEFAULT_PRIORITY_TAG_CONFIG = {
 # These model types are incorrectly labeled as "checkpoint" by CivitAI but are actually diffusion models
 DIFFUSION_MODEL_BASE_MODELS = frozenset(
     [
+        "Anima",
         "ZImageTurbo",
         "ZImageBase",
         "Wan Video 1.3B t2v",
@@ -177,5 +178,8 @@ SUPPORTED_DOWNLOAD_SKIP_BASE_MODELS = frozenset(
         "Wan Video 2.5 I2V",
         "Hunyuan Video",
         "Anima",
+        "Ernie",
+        "Ernie Turbo",
+        "Nucleus",
     ]
 )

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'
@@ -66,20 +130,40 @@ class ExampleImagesFileManager:
                     'success': False,
                     'error': 'No example images found for this model. Download example images first.'
                 }, status=404)
-            
-            # Open folder in file explorer
-            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 web.json_response({
-                'success': True,
-                'message': f'Opened example images folder for model {model_hash}'
-            })
+
+            root_path = os.path.abspath(example_images_path)
+            relative_path = os.path.relpath(model_folder, root_path).replace("\\", "/")
+            open_mode = settings_manager.get("example_images_open_mode") or "system"
+
+            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,
+                    '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)
@@ -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}',
@@ -227,4 +311,4 @@ class ExampleImagesFileManager:
             return web.json_response({
                 'has_images': False,
                 'error': str(e)
-            })
+            })

py/utils/exif_utils.py

@@ -1,15 +1,142 @@
-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__)
 
 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]:
@@ -28,48 +155,12 @@ class ExifUtils:
                 if ext in ['.mp4', '.webm']:
                     return None
 
-            # First try to open the image
-            with Image.open(image_path) as img:
-                # Method 1: Check for parameters in image info
-                if hasattr(img, 'info') and 'parameters' in img.info:
-                    return img.info['parameters']
-                
-                # 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
-                
+            metadata = ExifUtils._load_structured_metadata(image_path)
+            return (
+                metadata.get("parameters")
+                or metadata.get("prompt")
+                or metadata.get("workflow")
+            )
         except Exception as e:
             logger.error(f"Error extracting image metadata: {e}", exc_info=True)
             return None
@@ -92,50 +183,26 @@ 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':
-                    # Use PngInfo instead of plain dictionary
-                    png_info = PngImagePlugin.PngInfo()
-                    png_info.add_text("parameters", metadata)
-                    img.save(image_path, format='PNG', pnginfo=png_info)
+
+                if img_format == "PNG":
+                    png_info = ExifUtils._build_pnginfo(img, metadata_fields)
+                    img.save(image_path, format="PNG", pnginfo=png_info)
                     return image_path
-                
-                # For WebP format, use PIL's exif parameter directly
-                elif img_format == 'WEBP':
-                    exif_dict = {'Exif': {piexif.ExifIFD.UserComment: b'UNICODE\0' + metadata.encode('utf-16be')}}
-                    exif_bytes = piexif.dump(exif_dict)
-                    
-                    # Save with the exif data
-                    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)
-                    
+
+                exif_bytes = ExifUtils._build_exif_bytes(
+                    metadata_fields, img.info.get("exif")
+                )
+                save_kwargs = {"exif": exif_bytes}
+                if img_format == "WEBP":
+                    save_kwargs["quality"] = 85
+
+                img.save(image_path, format=img_format, **save_kwargs)
+
             return image_path
         except Exception as e:
             logger.error(f"Error updating metadata in {image_path}: {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 = piexif.dump(exif_dict)
+                            exif_bytes = ExifUtils._build_exif_bytes(metadata_fields)
                             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(temp_path, metadata)
+                            ExifUtils.update_image_metadata(
+                                temp_path, metadata_fields.get("parameters") or ""
+                            )
                             # Read back the file
                             with open(temp_path, 'rb') as f:
                                 optimized_data = f.read()

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-lora-manager"
 description = "Revolutionize your workflow with the ultimate LoRA companion for ComfyUI!"
-version = "1.0.2"
+version = "1.0.5"
 license = {file = "LICENSE"}
 dependencies = [
     "aiohttp",
@@ -14,7 +14,8 @@ dependencies = [
     "natsort",
     "GitPython",
     "aiosqlite",
-    "platformdirs"
+    "platformdirs",
+    "pyyaml"
 ]
 
 [project.urls]

requirements.txt

@@ -11,3 +11,4 @@ GitPython
 aiosqlite
 beautifulsoup4
 platformdirs
+pyyaml

scripts/migrate_legacy_metadata.py

@@ -0,0 +1,354 @@
+#!/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
+
+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
+
+    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 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())

settings.json.example

@@ -15,5 +15,8 @@
       "C:/path/to/another/embeddings_folder"
     ]
   },
+  "example_images_open_mode": "system",
+  "example_images_local_root": "",
+  "example_images_open_uri_template": "",
   "auto_organize_exclusions": []
 }

static/css/components/banner.css

@@ -243,3 +243,58 @@
     -ms-user-select: none;
     user-select: none;
 }
+
+.excluded-view-banner {
+    margin-bottom: var(--space-2);
+    padding: 12px 16px;
+    border: 1px solid var(--border-color);
+    border-radius: var(--border-radius-sm);
+    background: linear-gradient(
+        135deg,
+        oklch(var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h) / 0.08),
+        var(--card-bg)
+    );
+}
+
+.excluded-view-banner__content {
+    display: flex;
+    align-items: center;
+    justify-content: space-between;
+    gap: 12px;
+}
+
+.excluded-view-banner__title {
+    display: inline-flex;
+    align-items: center;
+    gap: 10px;
+    font-weight: 600;
+    color: var(--text-color);
+}
+
+.excluded-view-banner__back {
+    display: inline-flex;
+    align-items: center;
+    gap: 8px;
+    border: 1px solid var(--border-color);
+    background: var(--card-bg);
+    color: var(--text-color);
+    border-radius: var(--border-radius-xs);
+    padding: 8px 12px;
+    cursor: pointer;
+}
+
+.excluded-view-banner__back:hover {
+    border-color: var(--lora-accent);
+    color: var(--lora-accent);
+}
+
+@media (max-width: 768px) {
+    .excluded-view-banner__content {
+        flex-direction: column;
+        align-items: stretch;
+    }
+
+    .excluded-view-banner__back {
+        justify-content: center;
+    }
+}

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

@@ -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;

static/css/components/card.css

@@ -22,6 +22,7 @@
     transition: transform 160ms 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;
@@ -328,7 +329,6 @@
 }
 
 .card-actions i {
-    margin-left: var(--space-1);
     cursor: pointer;
     color: white;
     transition: opacity 0.2s, transform 0.15s ease;
@@ -370,7 +370,16 @@
     text-shadow: 0 0 5px rgba(255, 193, 7, 0.5);
 }
 
-/* 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 */
@@ -378,6 +387,7 @@
     
     .model-card {
         max-width: 100%; /* Allow cards to fill available space on mobile */
+        min-width: 200px;
     }
 }
 
@@ -507,6 +517,11 @@
     font-size: 0.75em;
 }
 
+/* Hide civitai version name when setting is disabled */
+body.hide-card-version .civitai-version {
+    display: none;
+}
+
 /* Prevent text selection on cards and interactive elements */
 .model-card,
 .model-card *,
@@ -558,8 +573,13 @@
     position: absolute;
     box-sizing: border-box;
     transition: transform 160ms ease-out;
-    margin: 0; /* Remove margins, positioning is handled by VirtualScroller */
-    width: 100%; /* Allow width to be set by the VirtualScroller */
+    margin: 0;
+    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 +591,11 @@
 .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 */
 }
@@ -680,3 +700,22 @@
     margin-left: 0;
     line-height: 1;
 }
+
+.excluded-model {
+    border-style: dashed;
+}
+
+.model-excluded-badge {
+    width: 16px;
+    height: 16px;
+    padding: 0;
+    border-radius: 3px;
+    background: color-mix(in oklab, var(--warning-color, #d97706) 85%, white 15%);
+    color: white;
+    font-size: 0.65rem;
+    display: inline-flex;
+    align-items: center;
+    justify-content: center;
+    flex-shrink: 0;
+    opacity: 0.9;
+}

static/css/components/header.css

@@ -19,6 +19,23 @@
   align-items: center;
   justify-content: space-between;
   height: 100%;
+  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 */
@@ -65,7 +82,6 @@
   display: flex;
   gap: 0.5rem;
   flex-shrink: 0;
-  margin-right: 1rem;
 }
 
 .nav-item {
@@ -77,6 +93,7 @@
   align-items: center;
   gap: 0.5rem;
   font-size: 0.9rem;
+  white-space: nowrap;
 }
 
 .nav-item:hover,
@@ -97,14 +114,99 @@
   color: white;
 }
 
-/* Header search */
+/* Header search - Centered with VS Code command palette style */
 .header-search {
   flex: 1;
-  max-width: 400px;
-  margin: 0 1rem;
+  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: all 0.2s ease;
+  box-shadow: 0 2px 8px rgba(0, 0, 0, 0.08);
+  overflow: hidden;
+}
+
+.header-search .search-container:focus-within {
+  border-color: var(--lora-accent);
+  box-shadow: 0 2px 8px rgba(0, 0, 0, 0.08), 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: all 0.2s ease;
+}
+
+.header-search .search-options-toggle {
+  right: 2.25rem;
+}
+
+.header-search .search-options-toggle:hover,
+.header-search .search-filter-toggle:hover {
+  background: var(--lora-surface-hover, oklch(95% 0.02 256));
+  color: var(--lora-accent);
+}
+
+.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;
@@ -248,44 +350,207 @@
   opacity: 1;
 }
 
-/* Mobile adjustments */
-@media (max-width: 768px) {
-  .app-title {
-    display: none;
-    /* Hide text title on mobile */
+/* Hamburger menu button - hidden by default */
+.hamburger-menu-btn {
+  display: none;
+  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: all 0.2s ease;
+  flex-shrink: 0;
+}
+
+.hamburger-menu-btn:hover {
+  background: var(--lora-accent);
+  color: white;
+}
+
+/* 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: 0 4px 16px rgba(0, 0, 0, 0.15);
+  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: all 0.2s ease;
+  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;
-    height: 28px;
+  .header-controls > div {
+    width: 30px;
+    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;
-    /* Hide navigation on very small screens */
+    display: flex;
+    gap: 0.15rem;
+    margin-right: 0;
   }
 
-  .header-search {
-    flex: 1;
+  .nav-item {
+    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/lora-modal/lora-modal.css

@@ -140,9 +140,11 @@
 
 /* Add specific styles for notes content */
 .info-item.notes .editable-field [contenteditable] {
+    height: 60px; /* Keep initial modal layout stable regardless of note length */
     min-height: 60px; /* Increase height for multiple lines */
-    max-height: 150px; /* Limit maximum height */
-    overflow-y: auto; /* Add scrolling for long content */
+    max-height: 420px; /* Limit maximum height */
+    overflow: auto; /* Enable scrolling and resize handle for long content */
+    resize: vertical; /* Allow manual vertical resizing */
     white-space: pre-wrap; /* Preserve line breaks */
     line-height: 1.5; /* Improve readability */
     padding: 8px 12px; /* Slightly increase padding */

static/css/components/lora-modal/triggerwords.css

@@ -53,6 +53,10 @@
   position: relative;
 }
 
+.trigger-word-tag:not(.is-editing) {
+  transition: background-color 0.2s ease, border-color 0.2s ease;
+}
+
 .trigger-word-content {
   color: var(--lora-accent) !important;
   font-size: 0.85em;
@@ -65,6 +69,38 @@
   border-color: var(--lora-accent);
 }
 
+.trigger-words.edit-mode .trigger-word-tag {
+  cursor: text;
+}
+
+.trigger-word-tag.is-editing {
+  align-items: center;
+  flex: 0 1 min(var(--trigger-word-edit-width, 48ch), 100%);
+  width: min(var(--trigger-word-edit-width, 48ch), 100%);
+  height: var(--trigger-word-edit-height, auto);
+  border-color: var(--lora-accent);
+  transition: none;
+}
+
+.trigger-word-edit-input {
+  width: 100%;
+  height: 100%;
+  min-width: 0;
+  box-sizing: border-box;
+  padding: 1px 2px;
+  border: none;
+  resize: none;
+  overflow: auto;
+  outline: none;
+  background: transparent;
+  color: var(--lora-accent);
+  font: inherit;
+  font-size: 0.85em;
+  line-height: 1.4;
+  white-space: pre-wrap;
+  overflow-wrap: anywhere;
+}
+
 .trigger-word-copy {
   display: flex;
   align-items: center;
@@ -109,4 +145,4 @@
   padding: 2px 5px;
   border-radius: 8px;
   white-space: nowrap;
-}
+}

static/css/components/lora-modal/versions.css

@@ -163,6 +163,18 @@
     cursor: pointer;
 }
 
+.model-version-row.is-clickable .version-actions,
+.model-version-row.is-clickable .version-badges,
+.model-version-row.is-clickable .version-action,
+.model-version-row.is-clickable .version-civitai-link {
+    cursor: default;
+}
+
+.model-version-row.is-clickable .version-action,
+.model-version-row.is-clickable .version-civitai-link {
+    cursor: pointer;
+}
+
 .model-version-row.is-current {
     border-color: var(--lora-accent);
     box-shadow: 0 0 0 1px color-mix(in oklch, var(--lora-accent) 65%, transparent),
@@ -217,6 +229,7 @@
     gap: 8px;
     font-weight: 600;
     font-size: 0.95rem;
+    min-width: 0;
 }
 
 .versions-tab-version-name {
@@ -226,6 +239,27 @@
     max-width: 100%;
 }
 
+.version-civitai-link {
+    display: inline-flex;
+    align-items: center;
+    justify-content: center;
+    width: 24px;
+    height: 24px;
+    border-radius: 999px;
+    color: var(--text-muted);
+    text-decoration: none;
+    flex: 0 0 auto;
+    transition: color 0.2s ease, background-color 0.2s ease, transform 0.2s ease;
+}
+
+.version-civitai-link:hover,
+.version-civitai-link:focus-visible {
+    color: var(--lora-accent);
+    background: color-mix(in oklch, var(--lora-accent) 12%, transparent);
+    transform: translateY(-1px);
+    outline: none;
+}
+
 .version-badges {
     display: flex;
     flex-wrap: wrap;
@@ -340,11 +374,23 @@
     background: color-mix(in oklch, var(--lora-surface) 35%, transparent);
 }
 
+.version-action-disabled {
+    background: transparent;
+    border-color: var(--border-color);
+    color: var(--text-muted);
+    opacity: 0.6;
+    cursor: not-allowed;
+}
+
 .version-action:disabled {
     opacity: 0.6;
     cursor: not-allowed;
 }
 
+.version-action-disabled-wrapper {
+    display: inline-flex;
+}
+
 .versions-loading-state,
 .versions-empty,
 .versions-error {

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

@@ -346,11 +346,13 @@
 .api-key-input input {
     width: 100%;
     padding: 6px 40px 6px 10px; /* Add left padding */
-    height: 20px;
+    height: 32px;
+    box-sizing: border-box;
     border-radius: var(--border-radius-xs);
     border: 1px solid var(--border-color);
     background-color: var(--lora-surface);
     color: var(--text-color);
+    font-size: 0.95em;
 }
 
 .api-key-input .toggle-visibility {
@@ -379,7 +381,8 @@
 .text-input-wrapper input {
     width: 100%;
     padding: 6px 10px;
-    height: 20px;
+    height: 32px;
+    box-sizing: border-box;
     border-radius: var(--border-radius-xs);
     border: 1px solid var(--border-color);
     background-color: var(--lora-surface);
@@ -760,10 +763,12 @@
 }
 
 .setting-control {
-    width: 60%; /* Decreased slightly from 65% */
+    flex: 0 0 60%;
+    max-width: 60%;
     margin-bottom: 0;
     display: flex;
     justify-content: flex-end; /* Right-align all controls */
+    min-width: 0;
 }
 
 /* Select Control Styles */
@@ -773,6 +778,13 @@
     justify-content: flex-end;
 }
 
+.setting-control select,
+.setting-control input[type="text"],
+.setting-control input[type="password"],
+.setting-control input[type="number"] {
+    font-size: 0.95em;
+}
+
 .select-control select {
     width: 100%;
     max-width: 100%; /* Increased from 200px */
@@ -781,8 +793,8 @@
     border: 1px solid var(--border-color);
     background-color: var(--lora-surface);
     color: var(--text-color);
-    font-size: 0.95em;
     height: 32px;
+    box-sizing: border-box;
 }
 
 /* Fix dark theme select dropdown text color */
@@ -888,8 +900,8 @@ input:checked + .toggle-slider:before {
     border: 1px solid var(--border-color);
     background-color: var(--lora-surface);
     color: var(--text-color);
-    font-size: 0.95em;
     height: 32px;
+    box-sizing: border-box;
 }
 
 /* Add warning text style for settings */

static/css/components/search-filter.css

@@ -145,7 +145,7 @@
     position: fixed;
     right: 20px;
     top: 50px; /* Position below header */
-    width: 320px;
+    width: 366px;
     background-color: var(--card-bg);
     border: 1px solid var(--border-color);
     border-radius: var(--border-radius-base);
@@ -197,6 +197,31 @@
     margin-bottom: 16px;
 }
 
+.filter-search-input {
+    width: 100%;
+    box-sizing: border-box;
+    margin-bottom: 8px;
+    padding: 8px 10px;
+    border-radius: var(--border-radius-sm);
+    border: 1px solid var(--border-color);
+    background-color: var(--lora-surface);
+    color: var(--text-color);
+    font-size: 13px;
+}
+
+.filter-search-input:focus {
+    outline: none;
+    border-color: var(--lora-accent);
+    box-shadow: 0 0 0 2px rgba(var(--lora-accent-rgb, 76, 175, 80), 0.15);
+}
+
+.filter-empty-state {
+    margin-top: 8px;
+    font-size: 13px;
+    color: var(--text-color);
+    opacity: 0.7;
+}
+
 .filter-section h4 {
     margin: 0 0 8px 0;
     font-size: 14px;
@@ -733,4 +758,4 @@
         right: 20px;
         top: 160px; /* Adjusted for mobile layout */
     }
-}
+}

static/css/components/shared.css

@@ -21,6 +21,27 @@
     font-size: 0.9em;
 }
 
+.downloaded-badge {
+    display: inline-flex;
+    align-items: center;
+    background: color-mix(in oklch, var(--badge-update-bg, #4a90e2) 22%, transparent);
+    color: var(--badge-update-bg, #4a90e2);
+    border: 1px solid color-mix(in oklch, var(--badge-update-bg, #4a90e2) 50%, transparent);
+    padding: 4px 8px;
+    border-radius: var(--border-radius-xs);
+    font-size: 0.8em;
+    font-weight: 500;
+    white-space: nowrap;
+    flex-shrink: 0;
+    transform: translateZ(0);
+    will-change: transform;
+}
+
+.downloaded-badge i {
+    margin-right: 4px;
+    font-size: 0.9em;
+}
+
 /* Early Access Badge */
 .early-access-badge {
     display: inline-flex;
@@ -46,7 +67,6 @@
 
 .early-access-info {
     display: none;
-    position: absolute;
     top: 100%;
     right: 0;
     background: var(--card-bg);
@@ -76,7 +96,6 @@
 
 .local-path {
     display: none;
-    position: absolute;
     top: 100%;
     right: 0;
     background: var(--card-bg);
@@ -108,4 +127,4 @@
     color: var(--lora-error);
     font-size: 0.9em;
     margin-top: 4px;
-}
+}

static/css/components/sidebar.css

@@ -271,11 +271,16 @@
 
 /* Enhanced Sidebar Breadcrumb Styles */
 .sidebar-breadcrumb-container {
-    margin-top: 8px;
     padding: 8px 0;
     border-bottom: 1px solid var(--border-color);
     background: var(--bg-color);
     border-radius: var(--border-radius-xs);
+    /* Sticky positioning to stick below header when scrolling
+       top: 0 means stick at the top of the scroll container (page-content)
+       which is at header height (48px) from the viewport */
+    position: sticky;
+    top: 0;
+    z-index: calc(var(--z-header) - 1);
 }
 
 .sidebar-breadcrumb-nav {
@@ -284,7 +289,6 @@
     flex-wrap: wrap;
     gap: 4px;
     font-size: 0.85em;
-    padding: 0 8px;
 }
 
 .sidebar-breadcrumb-item {

static/css/layout.css

@@ -21,7 +21,7 @@
     top: -54px;
     z-index: calc(var(--z-header) - 1);
     background: var(--bg-color);
-    padding: var(--space-2) 0;
+    padding: var(--space-1) 0;
     box-shadow: 0 1px 3px rgba(0,0,0,0.05);
 }
 
@@ -371,6 +371,14 @@
     display: block;
 }
 
+/* Elevate the controls stacking context above breadcrumb nav when a dropdown is open,
+   so the dropdown menu isn't obscured. Only active when dropdown is shown to avoid
+   the entire controls bar (which can wrap to 2 rows on narrow viewports) covering
+   the sticky breadcrumb. */
+.controls:has(.dropdown-group.active) {
+    z-index: var(--z-header);
+}
+
 .dropdown-item {
     display: block;
     padding: 6px 15px;
@@ -397,6 +405,33 @@
     text-align: center;
 }
 
+/* Intermediate breakpoint: wrap controls-right to prevent overflow */
+@media (max-width: 1500px) {
+    .actions {
+        flex-wrap: wrap;
+        gap: var(--space-2);
+    }
+
+    .action-buttons {
+        flex-wrap: wrap;
+        gap: var(--space-1);
+    }
+
+    .controls-right {
+        width: 100%;
+        justify-content: flex-end;
+        margin-top: 8px;
+        padding-left: 0;
+    }
+
+    /* Reduce button sizes to fit better */
+    .control-group button {
+        min-width: 80px;
+        padding: 4px 8px;
+        font-size: 0.8em;
+    }
+}
+
 @media (max-width: 768px) {
     .actions {
         flex-wrap: wrap;

static/js/api/apiConfig.js

@@ -56,8 +56,10 @@ export function getApiEndpoints(modelType) {
     return {
         // Base CRUD operations
         list: `/api/lm/${modelType}/list`,
+        excluded: `/api/lm/${modelType}/excluded`,
         delete: `/api/lm/${modelType}/delete`,
         exclude: `/api/lm/${modelType}/exclude`,
+        unexclude: `/api/lm/${modelType}/unexclude`,
         rename: `/api/lm/${modelType}/rename`,
         save: `/api/lm/${modelType}/save-metadata`,
         cancelTask: `/api/lm/${modelType}/cancel-task`,

static/js/api/baseModelApi.js

@@ -51,6 +51,7 @@ export class BaseModelApiClient {
     async fetchModelsPage(page = 1, pageSize = null) {
         const pageState = this.getPageState();
         const actualPageSize = pageSize || pageState.pageSize || this.apiConfig.config.defaultPageSize;
+        const isExcludedView = pageState.viewMode === 'excluded';
 
         try {
             const params = this._buildQueryParams({
@@ -71,7 +72,10 @@ export class BaseModelApiClient {
                 };
             }
 
-            const response = await fetch(`${this.apiConfig.endpoints.list}?${params}`);
+            const endpoint = isExcludedView
+                ? this.apiConfig.endpoints.excluded
+                : this.apiConfig.endpoints.list;
+            const response = await fetch(`${endpoint}?${params}`);
             if (!response.ok) {
                 throw new Error(`Failed to fetch ${this.apiConfig.config.displayName}s: ${response.statusText}`);
             }
@@ -84,7 +88,7 @@ export class BaseModelApiClient {
                 totalPages: data.total_pages,
                 currentPage: page,
                 hasMore: page < data.total_pages,
-                folders: data.folders
+                folders: data.folders || []
             };
 
         } catch (error) {
@@ -212,6 +216,50 @@ export class BaseModelApiClient {
         }
     }
 
+    async unexcludeModel(filePath) {
+        try {
+            state.loadingManager.showSimpleLoading(`Restoring ${this.apiConfig.config.singularName}...`);
+
+            const response = await fetch(this.apiConfig.endpoints.unexclude, {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({ file_path: filePath })
+            });
+
+            if (!response.ok) {
+                throw new Error(`Failed to restore ${this.apiConfig.config.singularName}: ${response.statusText}`);
+            }
+
+            const data = await response.json();
+
+            if (data.success) {
+                if (state.virtualScroller) {
+                    state.virtualScroller.removeItemByFilePath(filePath);
+                }
+                showToast(
+                    'toast.api.restoreSuccess',
+                    { type: this.apiConfig.config.displayName },
+                    'success',
+                    `Restored ${this.apiConfig.config.displayName}`
+                );
+                return true;
+            }
+
+            throw new Error(data.error || `Failed to restore ${this.apiConfig.config.singularName}`);
+        } catch (error) {
+            console.error(`Error restoring ${this.apiConfig.config.singularName}:`, error);
+            showToast(
+                'toast.api.restoreFailed',
+                { type: this.apiConfig.config.singularName, message: error.message },
+                'error',
+                `Failed to restore ${this.apiConfig.config.singularName}: ${error.message}`
+            );
+            return false;
+        } finally {
+            state.loadingManager.hide();
+        }
+    }
+
     async renameModelFile(filePath, newFileName) {
         try {
             state.loadingManager.showSimpleLoading(`Renaming ${this.apiConfig.config.singularName} file...`);
@@ -883,20 +931,21 @@ export class BaseModelApiClient {
 
     _buildQueryParams(baseParams, pageState) {
         const params = new URLSearchParams(baseParams);
+        const isExcludedView = pageState.viewMode === 'excluded';
 
-        if (pageState.activeFolder !== null) {
+        if (!isExcludedView && pageState.activeFolder !== null) {
             params.append('folder', pageState.activeFolder);
         }
 
-        if (pageState.showFavoritesOnly) {
+        if (!isExcludedView && pageState.showFavoritesOnly) {
             params.append('favorites_only', 'true');
         }
 
-        if (pageState.showUpdateAvailableOnly) {
+        if (!isExcludedView && pageState.showUpdateAvailableOnly) {
             params.append('update_available_only', 'true');
         }
 
-        if (this.apiConfig.config.supportsLetterFilter && pageState.activeLetterFilter) {
+        if (!isExcludedView && this.apiConfig.config.supportsLetterFilter && pageState.activeLetterFilter) {
             params.append('first_letter', pageState.activeLetterFilter);
         }
 
@@ -918,7 +967,7 @@ export class BaseModelApiClient {
 
         params.append('recursive', pageState.searchOptions.recursive ? 'true' : 'false');
 
-        if (pageState.filters) {
+        if (!isExcludedView && pageState.filters) {
             if (pageState.filters.tags && Object.keys(pageState.filters.tags).length > 0) {
                 Object.entries(pageState.filters.tags).forEach(([tag, state]) => {
                     if (state === 'include') {
@@ -981,7 +1030,9 @@ export class BaseModelApiClient {
             }
         }
 
-        this._addModelSpecificParams(params, pageState);
+        if (!isExcludedView) {
+            this._addModelSpecificParams(params, pageState);
+        }
 
         return params;
     }

static/js/api/recipeApi.js

@@ -1,6 +1,7 @@
 import { RecipeCard } from '../components/RecipeCard.js';
 import { state, getCurrentPageState } from '../state/index.js';
 import { showToast } from '../utils/uiHelpers.js';
+import { captureScrollPosition, restoreScrollPosition } from '../utils/infiniteScroll.js';
 
 const RECIPE_ENDPOINTS = {
     list: '/api/lm/recipes',
@@ -182,10 +183,12 @@ export async function resetAndReloadWithVirtualScroll(options = {}) {
     const {
         modelType = 'lora',
         updateFolders = false,
-        fetchPageFunction
+        fetchPageFunction,
+        preserveScroll = false
     } = options;
 
     const pageState = getCurrentPageState();
+    const scrollSnapshot = preserveScroll ? captureScrollPosition() : null;
 
     try {
         pageState.isLoading = true;
@@ -207,6 +210,10 @@ export async function resetAndReloadWithVirtualScroll(options = {}) {
         pageState.hasMore = result.hasMore;
         pageState.currentPage = 2; // Next page will be 2
 
+        if (scrollSnapshot) {
+            await restoreScrollPosition(scrollSnapshot);
+        }
+
         return result;
     } catch (error) {
         console.error(`Error reloading ${modelType}s:`, error);
@@ -227,10 +234,12 @@ export async function loadMoreWithVirtualScroll(options = {}) {
         modelType = 'lora',
         resetPage = false,
         updateFolders = false,
-        fetchPageFunction
+        fetchPageFunction,
+        preserveScroll = false
     } = options;
 
     const pageState = getCurrentPageState();
+    const scrollSnapshot = preserveScroll ? captureScrollPosition() : null;
 
     try {
         // Start loading state
@@ -255,6 +264,10 @@ export async function loadMoreWithVirtualScroll(options = {}) {
         pageState.hasMore = result.hasMore;
         pageState.currentPage = 2; // Next page to load would be 2
 
+        if (scrollSnapshot) {
+            await restoreScrollPosition(scrollSnapshot);
+        }
+
         return result;
     } catch (error) {
         console.error(`Error loading ${modelType}s:`, error);
@@ -270,11 +283,12 @@ export async function loadMoreWithVirtualScroll(options = {}) {
  * @param {boolean} updateFolders - Whether to update folder tags
  * @returns {Promise<Object>} The fetch result
  */
-export async function resetAndReload(updateFolders = false) {
+export async function resetAndReload(updateFolders = false, options = {}) {
     return resetAndReloadWithVirtualScroll({
         modelType: 'recipe',
         updateFolders,
-        fetchPageFunction: fetchRecipesPage
+        fetchPageFunction: fetchRecipesPage,
+        preserveScroll: options.preserveScroll === true
     });
 }
 
@@ -286,7 +300,7 @@ export async function syncChanges() {
         state.loadingManager.showSimpleLoading('Syncing changes...');
 
         // Simply reload the recipes without rebuilding cache
-        await resetAndReload();
+        await resetAndReload(false, { preserveScroll: true });
 
         showToast('toast.recipes.syncComplete', {}, 'success');
     } catch (error) {
@@ -314,7 +328,7 @@ export async function refreshRecipes() {
         }
 
         // After successful cache rebuild, reload the recipes
-        await resetAndReload();
+        await resetAndReload(false, { preserveScroll: true });
 
         showToast('toast.recipes.refreshComplete', {}, 'success');
     } catch (error) {

static/js/components/ContextMenu/BulkContextMenu.js

@@ -74,6 +74,34 @@ export class BulkContextMenu extends BaseContextMenu {
         if (setContentRatingItem) {
             setContentRatingItem.style.display = config.setContentRating ? 'flex' : 'none';
         }
+
+        const setFavoriteItem = this.menu.querySelector('[data-action="set-favorite"]');
+
+        if (setFavoriteItem && config.setFavorite) {
+            setFavoriteItem.style.display = 'flex';
+
+            const total = state.selectedModels.size;
+            const favoritedCount = this.countFavoritedInSelection();
+            const allFavorited = total > 0 && favoritedCount === total;
+
+            const icon = setFavoriteItem.querySelector('i');
+            const label = setFavoriteItem.querySelector('span');
+
+            if (allFavorited) {
+                if (icon) { icon.className = 'far fa-star'; }
+                if (label) { label.textContent = translate('loras.bulkOperations.unfavorite'); }
+            } else {
+                if (icon) { icon.className = 'fas fa-star'; }
+                if (label) {
+                    label.textContent = favoritedCount > 0
+                        ? translate('loras.bulkOperations.setFavoriteCount', { favorited: favoritedCount, total })
+                        : translate('loras.bulkOperations.setFavorite');
+                }
+            }
+        } else if (setFavoriteItem) {
+            setFavoriteItem.style.display = 'none';
+        }
+
         if (downloadMissingLorasItem) {
             // Only show for recipes page
             downloadMissingLorasItem.style.display = currentModelType === 'recipes' ? 'flex' : 'none';
@@ -138,6 +166,20 @@ export class BulkContextMenu extends BaseContextMenu {
         return count;
     }
 
+    countFavoritedInSelection() {
+        let count = 0;
+        for (const filePath of state.selectedModels) {
+            const escapedPath = window.CSS && typeof window.CSS.escape === 'function'
+                ? window.CSS.escape(filePath)
+                : filePath.replace(/["\\]/g, '\\$&');
+            const card = document.querySelector(`.model-card[data-filepath="${escapedPath}"]`);
+            if (card && card.dataset.favorite === 'true') {
+                count++;
+            }
+        }
+        return count;
+    }
+
     showMenu(x, y, card) {
         this.updateMenuItemsForModelType();
         this.updateSelectedCountHeader();
@@ -185,6 +227,11 @@ export class BulkContextMenu extends BaseContextMenu {
             case 'delete-all':
                 bulkManager.showBulkDeleteModal();
                 break;
+            case 'set-favorite': {
+                const allFavorited = this.countFavoritedInSelection() === state.selectedModels.size;
+                bulkManager.setBulkFavorites(!allFavorited);
+                break;
+            }
             case 'download-missing-loras':
                 this.handleDownloadMissingLoras();
                 break;

static/js/components/ContextMenu/CheckpointContextMenu.js

@@ -24,6 +24,7 @@ export class CheckpointContextMenu extends BaseContextMenu {
 
     showMenu(x, y, card) {
         super.showMenu(x, y, card);
+        this.updateExcludeMenuItem();
 
         // Update the "Move to other root" label based on current model type
         const moveOtherItem = this.menu.querySelector('[data-action="move-other"]');
@@ -83,6 +84,9 @@ export class CheckpointContextMenu extends BaseContextMenu {
             case 'exclude':
                 showExcludeModal(this.currentCard.dataset.filepath);
                 break;
+            case 'restore':
+                this.restoreExcludedModel(this.currentCard.dataset.filepath);
+                break;
         }
     }
 

static/js/components/ContextMenu/EmbeddingContextMenu.js

@@ -18,6 +18,11 @@ export class EmbeddingContextMenu extends BaseContextMenu {
     async saveModelMetadata(filePath, data) {
         return getModelApiClient().saveModelMetadata(filePath, data);
     }
+
+    showMenu(x, y, card) {
+        super.showMenu(x, y, card);
+        this.updateExcludeMenuItem();
+    }
     
     handleMenuAction(action) {
         // First try to handle with common actions
@@ -56,6 +61,9 @@ export class EmbeddingContextMenu extends BaseContextMenu {
             case 'exclude':
                 showExcludeModal(this.currentCard.dataset.filepath);
                 break;
+            case 'restore':
+                this.restoreExcludedModel(this.currentCard.dataset.filepath);
+                break;
         }
     }
 }

static/js/components/ContextMenu/GlobalContextMenu.js

@@ -22,6 +22,7 @@ export class GlobalContextMenu extends BaseContextMenu {
         const licenseRefreshItem = this.menu.querySelector('[data-action="fetch-missing-licenses"]');
         const downloadExamplesItem = this.menu.querySelector('[data-action="download-example-images"]');
         const cleanupExamplesItem = this.menu.querySelector('[data-action="cleanup-example-images-folders"]');
+        const excludedModelsItem = this.menu.querySelector('[data-action="manage-excluded-models"]');
         const repairRecipesItem = this.menu.querySelector('[data-action="repair-recipes"]');
 
         if (isRecipesPage) {
@@ -29,12 +30,14 @@ export class GlobalContextMenu extends BaseContextMenu {
             licenseRefreshItem?.classList.add('hidden');
             downloadExamplesItem?.classList.add('hidden');
             cleanupExamplesItem?.classList.add('hidden');
+            excludedModelsItem?.classList.add('hidden');
             repairRecipesItem?.classList.remove('hidden');
         } else {
             modelUpdateItem?.classList.remove('hidden');
             licenseRefreshItem?.classList.remove('hidden');
             downloadExamplesItem?.classList.remove('hidden');
             cleanupExamplesItem?.classList.remove('hidden');
+            excludedModelsItem?.classList.remove('hidden');
             repairRecipesItem?.classList.add('hidden');
         }
 
@@ -68,12 +71,21 @@ export class GlobalContextMenu extends BaseContextMenu {
                     console.error('Failed to repair recipes:', error);
                 });
                 break;
+            case 'manage-excluded-models':
+                this.manageExcludedModels();
+                break;
             default:
                 console.warn(`Unhandled global context menu action: ${action}`);
                 break;
         }
     }
 
+    manageExcludedModels() {
+        window.pageControls?.enterExcludedView?.().catch((error) => {
+            console.error('Failed to open excluded models view:', error);
+        });
+    }
+
     async downloadExampleImages(menuItem) {
         const downloadPath = state?.global?.settings?.example_images_path;
         if (!downloadPath) {

static/js/components/ContextMenu/LoraContextMenu.js

@@ -20,6 +20,11 @@ export class LoraContextMenu extends BaseContextMenu {
         return getModelApiClient().saveModelMetadata(filePath, data);
     }
 
+    showMenu(x, y, card) {
+        super.showMenu(x, y, card);
+        this.updateExcludeMenuItem();
+    }
+
     handleMenuAction(action, menuItem) {
         // First try to handle with common actions
         if (ModelContextMenuMixin.handleCommonMenuActions.call(this, action)) {
@@ -61,6 +66,9 @@ export class LoraContextMenu extends BaseContextMenu {
             case 'exclude':
                 showExcludeModal(this.currentCard.dataset.filepath);
                 break;
+            case 'restore':
+                this.restoreExcludedModel(this.currentCard.dataset.filepath);
+                break;
         }
     }
 

static/js/components/ContextMenu/ModelContextMenuMixin.js

@@ -6,9 +6,43 @@ import { bulkManager } from '../../managers/BulkManager.js';
 import { MODEL_CONFIG } from '../../api/apiConfig.js';
 import { translate } from '../../utils/i18nHelpers.js';
 import { getNsfwLevelSelector } from '../shared/NsfwLevelSelector.js';
+import { extractCivitaiModelUrlParts } from '../../utils/civitaiUtils.js';
 
 // Mixin with shared functionality for LoraContextMenu and CheckpointContextMenu
 export const ModelContextMenuMixin = {
+    isExcludedView() {
+        return state?.pages?.[state.currentPageType]?.viewMode === 'excluded';
+    },
+
+    updateExcludeMenuItem() {
+        const excludeItem = this.menu?.querySelector('[data-action="exclude"], [data-action="restore"]');
+        if (!excludeItem) {
+            return;
+        }
+
+        const isExcludedView = this.isExcludedView();
+        excludeItem.dataset.action = isExcludedView ? 'restore' : 'exclude';
+        excludeItem.innerHTML = isExcludedView
+            ? `<i class="fas fa-undo"></i> <span>${translate('loras.contextMenu.restoreModel', {}, 'Restore model')}</span>`
+            : `<i class="fas fa-eye-slash"></i> <span>${translate('loras.contextMenu.excludeModel', {}, 'Exclude model')}</span>`;
+    },
+
+    async restoreExcludedModel(filePath) {
+        const restored = await getModelApiClient().unexcludeModel(filePath);
+        if (!restored) {
+            return;
+        }
+
+        if (window.pageControls?.exitExcludedView) {
+            await window.pageControls.exitExcludedView();
+        } else {
+            const resetFn = this.resetAndReload || resetAndReload;
+            if (typeof resetFn === 'function') {
+                await resetFn(true);
+            }
+        }
+    },
+
     // NSFW Selector methods
     initNSFWSelector() {
         if (this._nsfwSelectorInitialized) {
@@ -154,25 +188,7 @@ export const ModelContextMenuMixin = {
     },
 
     extractModelVersionId(url) {
-        try {
-            // Handle all three URL formats:
-            // 1. https://civitai.com/models/649516
-            // 2. https://civitai.com/models/649516?modelVersionId=726676
-            // 3. https://civitai.com/models/649516/cynthia-pokemon-diamond-and-pearl-pdxl-lora?modelVersionId=726676
-            
-            const parsedUrl = new URL(url);
-            
-            // Extract model ID from path
-            const pathMatch = parsedUrl.pathname.match(/\/models\/(\d+)/);
-            const modelId = pathMatch ? pathMatch[1] : null;
-            
-            // Extract model version ID from query parameters
-            const modelVersionId = parsedUrl.searchParams.get('modelVersionId');
-            
-            return { modelId, modelVersionId };
-        } catch (e) {
-            return { modelId: null, modelVersionId: null };
-        }
+        return extractCivitaiModelUrlParts(url);
     },
 
     parseModelId(value) {

static/js/components/ContextMenu/RecipeContextMenu.js

@@ -23,7 +23,7 @@ export class RecipeContextMenu extends BaseContextMenu {
     // Override resetAndReload for recipe context
     async resetAndReload() {
         const { resetAndReload } = await import('../../api/recipeApi.js');
-        return resetAndReload();
+        return resetAndReload(false, { preserveScroll: true });
     }
 
     showMenu(x, y, card) {

static/js/components/Header.js

@@ -129,6 +129,126 @@ export class HeaderManager {
       
       // Hide search functionality on Statistics page
       this.updateHeaderForPage();
+
+      // Initialize hamburger menu for mobile
+      this.initializeHamburgerMenu();
+    }
+
+    initializeHamburgerMenu() {
+      const hamburgerBtn = document.getElementById('hamburgerMenuBtn');
+      const hamburgerDropdown = document.getElementById('hamburgerDropdown');
+
+      if (!hamburgerBtn || !hamburgerDropdown) return;
+
+      // Toggle dropdown on hamburger button click
+      hamburgerBtn.addEventListener('click', (e) => {
+        e.stopPropagation();
+        hamburgerDropdown.classList.toggle('active');
+        const icon = hamburgerBtn.querySelector('i');
+        if (hamburgerDropdown.classList.contains('active')) {
+          icon.classList.remove('fa-bars');
+          icon.classList.add('fa-times');
+        } else {
+          icon.classList.remove('fa-times');
+          icon.classList.add('fa-bars');
+        }
+      });
+
+      // Handle dropdown item clicks
+      const dropdownItems = hamburgerDropdown.querySelectorAll('.dropdown-item');
+      dropdownItems.forEach(item => {
+        item.addEventListener('click', (e) => {
+          const action = item.dataset.action;
+          this.handleHamburgerAction(action);
+          hamburgerDropdown.classList.remove('active');
+          const icon = hamburgerBtn.querySelector('i');
+          icon.classList.remove('fa-times');
+          icon.classList.add('fa-bars');
+        });
+      });
+
+      // Close dropdown when clicking outside
+      document.addEventListener('click', (e) => {
+        if (!hamburgerDropdown.contains(e.target) && !hamburgerBtn.contains(e.target)) {
+          hamburgerDropdown.classList.remove('active');
+          const icon = hamburgerBtn.querySelector('i');
+          if (icon) {
+            icon.classList.remove('fa-times');
+            icon.classList.add('fa-bars');
+          }
+        }
+      });
+
+      // Update theme icon in hamburger menu based on current theme
+      this.updateHamburgerThemeIcon();
+    }
+
+    handleHamburgerAction(action) {
+      switch (action) {
+        case 'theme':
+          if (typeof toggleTheme === 'function') {
+            const newTheme = toggleTheme();
+            // Update theme toggle in header if it exists
+            const themeToggle = document.querySelector('.theme-toggle');
+            if (themeToggle) {
+              themeToggle.classList.remove('theme-light', 'theme-dark', 'theme-auto');
+              themeToggle.classList.add(`theme-${newTheme}`);
+              this.updateThemeTooltip(themeToggle, newTheme);
+            }
+            this.updateHamburgerThemeIcon();
+          }
+          break;
+        case 'settings':
+          if (window.settingsManager) {
+            window.settingsManager.toggleSettings();
+          }
+          break;
+        case 'help':
+          const helpToggle = document.getElementById('helpToggleBtn');
+          if (helpToggle) {
+            helpToggle.click();
+          }
+          break;
+        case 'notifications':
+          updateService.toggleUpdateModal();
+          break;
+        case 'support':
+          if (window.modalManager) {
+            window.modalManager.toggleModal('supportModal');
+            renderSupporters().catch(error => {
+              console.error('Error loading supporters:', error);
+            });
+          }
+          break;
+      }
+    }
+
+    updateHamburgerThemeIcon() {
+      const themeItem = document.querySelector('.dropdown-item[data-action="theme"]');
+      if (!themeItem) return;
+
+      const currentTheme = getStorageItem('theme') || 'auto';
+      const icon = themeItem.querySelector('i');
+      const text = themeItem.querySelector('span');
+
+      if (icon) {
+        icon.classList.remove('fa-moon', 'fa-sun', 'fa-adjust');
+        if (currentTheme === 'light') {
+          icon.classList.add('fa-sun');
+        } else if (currentTheme === 'dark') {
+          icon.classList.add('fa-moon');
+        } else {
+          icon.classList.add('fa-adjust');
+        }
+      }
+
+      // Update text based on current theme
+      if (text) {
+        const key = currentTheme === 'light' ? 'header.theme.switchToDark' :
+                    currentTheme === 'dark' ? 'header.theme.switchToLight' :
+                    'header.theme.toggle';
+        updateElementAttribute(themeItem, 'aria-label', key, {}, '');
+      }
     }
 
     updateHeaderForPage() {

static/js/components/ModelDuplicatesManager.js

@@ -121,6 +121,7 @@ export class ModelDuplicatesManager {
             }
 
             this.duplicateGroups = data.duplicates || [];
+            this._pruneVerificationState();
 
             // Update the badge with the current count
             this.updateDuplicatesBadge(this.duplicateGroups.length);
@@ -402,6 +403,44 @@ export class ModelDuplicatesManager {
             }
         });
     }
+
+    _getGroupFilePaths(group) {
+        return new Set((group?.models || []).map(model => model.file_path));
+    }
+
+    _clearMismatchStateForGroup(group) {
+        this._getGroupFilePaths(group).forEach(filePath => {
+            this.mismatchedFiles.delete(filePath);
+        });
+    }
+
+    _pruneVerificationState() {
+        const visiblePaths = new Set();
+        const visibleHashes = new Set();
+
+        this.duplicateGroups.forEach(group => {
+            visibleHashes.add(group.hash);
+            this._getGroupFilePaths(group).forEach(filePath => visiblePaths.add(filePath));
+        });
+
+        Array.from(this.mismatchedFiles.keys()).forEach(filePath => {
+            if (!visiblePaths.has(filePath)) {
+                this.mismatchedFiles.delete(filePath);
+            }
+        });
+
+        Array.from(this.selectedForDeletion).forEach(filePath => {
+            if (!visiblePaths.has(filePath)) {
+                this.selectedForDeletion.delete(filePath);
+            }
+        });
+
+        Array.from(this.verifiedGroups).forEach(hash => {
+            if (!visibleHashes.has(hash)) {
+                this.verifiedGroups.delete(hash);
+            }
+        });
+    }
     
     renderModelCard(model, groupHash) {
         // Create basic card structure
@@ -619,10 +658,11 @@ export class ModelDuplicatesManager {
     
     toggleSelectAllInGroup(hash) {
         const checkboxes = document.querySelectorAll(`.selector-checkbox[data-group-hash="${hash}"]`);
-        const allSelected = Array.from(checkboxes).every(checkbox => checkbox.checked);
+        const selectableCheckboxes = Array.from(checkboxes).filter(checkbox => !checkbox.disabled);
+        const allSelected = selectableCheckboxes.length > 0 && selectableCheckboxes.every(checkbox => checkbox.checked);
         
         // If all are selected, deselect all; otherwise select all
-        checkboxes.forEach(checkbox => {
+        selectableCheckboxes.forEach(checkbox => {
             checkbox.checked = !allSelected;
             const filePath = checkbox.dataset.filePath;
             const card = checkbox.closest('.model-card');
@@ -830,11 +870,14 @@ export class ModelDuplicatesManager {
             // Process verification results
             const verifiedAsDuplicates = data.verified_as_duplicates;
             const mismatchedFiles = data.mismatched_files || [];
+
+            this._clearMismatchStateForGroup(group);
             
             // Update mismatchedFiles map
             if (data.new_hash_map) {
                 Object.entries(data.new_hash_map).forEach(([path, hash]) => {
                     this.mismatchedFiles.set(path, hash);
+                    this.selectedForDeletion.delete(path);
                 });
             }
             
@@ -843,6 +886,7 @@ export class ModelDuplicatesManager {
             
             // Re-render the duplicate groups to show verification status
             this.renderDuplicateGroups();
+            this.updateSelectedCount();
             
             // Show appropriate toast message
             if (mismatchedFiles.length > 0) {

static/js/components/controls/PageControls.js

@@ -1,7 +1,7 @@
 // PageControls.js - Manages controls for both LoRAs and Checkpoints pages
 import { state, getCurrentPageState, setCurrentPageType } from '../../state/index.js';
 import { getStorageItem, setStorageItem, getSessionItem, setSessionItem } from '../../utils/storageHelpers.js';
-import { showToast } from '../../utils/uiHelpers.js';
+import { showToast, openCivitaiByMetadata } from '../../utils/uiHelpers.js';
 import { performModelUpdateCheck } from '../../utils/updateCheckHelpers.js';
 import { sidebarManager } from '../SidebarManager.js';
 
@@ -38,8 +38,12 @@ export class PageControls {
 
         // Initialize favorites filter button state
         this.initFavoritesFilter();
+
+        this.initExcludedViewControls();
+        this.syncExcludedViewState();
         
         console.log(`PageControls initialized for ${pageType} page`);
+        window.pageControls = this;
     }
     
     /**
@@ -56,6 +60,19 @@ export class PageControls {
         
         // Load sort preference
         this.loadSortPreference();
+
+        if (!this.pageState.viewMode) {
+            this.pageState.viewMode = 'active';
+        }
+        if (!this.pageState.excludedViewState) {
+            this.pageState.excludedViewState = {
+                sortBy: 'name:asc',
+                search: '',
+            };
+        }
+        if (!this.pageState.filters?.search) {
+            this.pageState.filters.search = '';
+        }
     }
     
     /**
@@ -116,6 +133,15 @@ export class PageControls {
         // Page-specific event listeners
         this.initPageSpecificListeners();
     }
+
+    initExcludedViewControls() {
+        const backButton = document.getElementById('excludedViewBackBtn');
+        if (backButton) {
+            backButton.addEventListener('click', async () => {
+                await this.exitExcludedView();
+            });
+        }
+    }
     
     /**
      * Initialize dropdown functionality
@@ -334,6 +360,13 @@ export class PageControls {
      * @param {string} sortValue - The sort value to save
      */
     saveSortPreference(sortValue) {
+        if (this.pageState.viewMode === 'excluded') {
+            this.pageState.excludedViewState = {
+                ...(this.pageState.excludedViewState || {}),
+                sortBy: sortValue,
+            };
+            return;
+        }
         setStorageItem(`${this.pageType}_sort`, sortValue);
     }
     
@@ -353,18 +386,8 @@ export class PageControls {
         const metaData = JSON.parse(card.dataset.meta);
         const civitaiId = metaData.modelId;
         const versionId = metaData.id;
-        
-        // Build URL
-        if (civitaiId) {
-            let url = `https://civitai.com/models/${civitaiId}`;
-            if (versionId) {
-                url += `?modelVersionId=${versionId}`;
-            }
-            window.open(url, '_blank');
-        } else {
-            // If no ID, try searching by name
-            window.open(`https://civitai.com/models?query=${encodeURIComponent(modelName)}`, '_blank');
-        }
+
+        openCivitaiByMetadata(civitaiId, versionId, modelName);
     }
     
     /**
@@ -483,6 +506,8 @@ export class PageControls {
             // Update app state
             this.pageState.showFavoritesOnly = showFavoritesOnly;
         }
+
+        this.updateActionButtonStates();
     }
 
     /**
@@ -499,12 +524,17 @@ export class PageControls {
         if (updateFilterBtn) {
             updateFilterBtn.classList.toggle('active', showUpdatesOnly);
         }
+
+        this.updateActionButtonStates();
     }
 
     /**
      * Toggle favorites-only filter and reload models
      */
     async toggleFavoritesOnly() {
+        if (this.pageState.viewMode === 'excluded') {
+            return;
+        }
         const favoriteFilterBtn = document.getElementById('favoriteFilterBtn');
         
         // Toggle the filter state in storage
@@ -531,6 +561,9 @@ export class PageControls {
      * Toggle update-available-only filter and reload models
      */
     async toggleUpdateAvailableOnly() {
+        if (this.pageState.viewMode === 'excluded') {
+            return;
+        }
         const updateFilterBtn = document.getElementById('updateFilterBtn');
         const storageKey = `show_update_available_only_${this.pageType}`;
         const newState = !this.pageState.showUpdateAvailableOnly;
@@ -545,6 +578,234 @@ export class PageControls {
 
         await this.resetAndReload(true);
     }
+
+    cloneFilters(filters = this.pageState.filters) {
+        return JSON.parse(JSON.stringify(filters || {}));
+    }
+
+    buildExcludedFilters(search = '') {
+        return {
+            baseModel: [],
+            tags: {},
+            license: {},
+            modelTypes: [],
+            search,
+            tagLogic: 'any',
+        };
+    }
+
+    applyFilterState(filters) {
+        this.pageState.filters = filters;
+
+        if (window.filterManager) {
+            window.filterManager.filters = window.filterManager.initializeFilters(filters);
+            window.filterManager.updateActiveFiltersCount();
+            if (typeof window.filterManager.updateSelections === 'function') {
+                window.filterManager.updateSelections();
+            }
+            window.filterManager.closeFilterPanel();
+        }
+    }
+
+    updateActionButtonStates() {
+        const favoriteFilterBtn = document.getElementById('favoriteFilterBtn');
+        if (favoriteFilterBtn) {
+            favoriteFilterBtn.classList.toggle('active', Boolean(this.pageState.showFavoritesOnly));
+        }
+
+        const updateFilterBtn = document.getElementById('updateFilterBtn');
+        if (updateFilterBtn) {
+            updateFilterBtn.classList.toggle('active', Boolean(this.pageState.showUpdateAvailableOnly));
+        }
+    }
+
+    syncExcludedViewState() {
+        const isExcludedView = this.pageState.viewMode === 'excluded';
+        const sortSelect = document.getElementById('sortSelect');
+        const searchInput = document.getElementById('searchInput');
+        const excludedBanner = document.getElementById('excludedViewBanner');
+        const filterButton = document.getElementById('filterButton');
+        const breadcrumbContainer = document.getElementById('breadcrumbContainer');
+        const duplicatesBanner = document.getElementById('duplicatesBanner');
+        const alphabetBarContainer = document.querySelector('.alphabet-bar-container');
+        const hiddenSelectors = [
+            '[data-action="fetch"]',
+            '[data-action="download"]',
+            '[data-action="bulk"]',
+            '[data-action="find-duplicates"]',
+            '#favoriteFilterBtn',
+            '.update-filter-group',
+        ];
+        const customFilterIndicator = document.getElementById('customFilterIndicator');
+
+        document.body.classList.toggle('excluded-view-active', isExcludedView);
+        excludedBanner?.classList.toggle('hidden', !isExcludedView);
+        breadcrumbContainer?.classList.toggle('hidden', isExcludedView);
+        alphabetBarContainer?.classList.toggle('hidden', isExcludedView);
+
+        if (duplicatesBanner && isExcludedView) {
+            duplicatesBanner.style.display = 'none';
+        }
+
+        hiddenSelectors.forEach((selector) => {
+            document.querySelectorAll(selector).forEach((element) => {
+                element.classList.toggle('hidden', isExcludedView);
+            });
+        });
+
+        if (customFilterIndicator && isExcludedView) {
+            customFilterIndicator.classList.add('hidden');
+        }
+
+        if (filterButton) {
+            filterButton.disabled = isExcludedView;
+            filterButton.classList.toggle('hidden', isExcludedView);
+        }
+
+        const activeFiltersCount = document.getElementById('activeFiltersCount');
+        if (activeFiltersCount && isExcludedView) {
+            activeFiltersCount.style.display = 'none';
+        }
+
+        if (sortSelect) {
+            sortSelect.value = this.pageState.sortBy;
+        }
+        if (searchInput) {
+            searchInput.value = this.pageState.filters?.search || '';
+        }
+
+        this.updateActionButtonStates();
+
+        if (this.sidebarManager) {
+            const shouldShowSidebar = !isExcludedView && state?.global?.settings?.show_folder_sidebar !== false;
+            this.sidebarManager.setSidebarEnabled(shouldShowSidebar).catch((error) => {
+                console.error('Failed to update sidebar visibility:', error);
+            });
+        }
+    }
+
+    suspendInteractiveModes() {
+        const snapshot = {
+            bulkMode: Boolean(state.bulkMode),
+            duplicatesMode: Boolean(this.pageState.duplicatesMode),
+        };
+
+        if (snapshot.bulkMode && window.bulkManager?.toggleBulkMode) {
+            window.bulkManager.toggleBulkMode();
+        }
+
+        if (snapshot.duplicatesMode && window.modelDuplicatesManager?.exitDuplicateMode) {
+            window.modelDuplicatesManager.exitDuplicateMode();
+        }
+
+        return snapshot;
+    }
+
+    async restoreInteractiveModes(snapshot = {}) {
+        if (snapshot.bulkMode && !state.bulkMode && window.bulkManager?.toggleBulkMode) {
+            window.bulkManager.toggleBulkMode();
+        }
+
+        if (!snapshot.duplicatesMode || this.pageState.duplicatesMode) {
+            return;
+        }
+
+        const duplicatesManager = window.modelDuplicatesManager;
+        if (!duplicatesManager) {
+            return;
+        }
+
+        if (typeof duplicatesManager.enterDuplicateMode === 'function' &&
+            Array.isArray(duplicatesManager.duplicateGroups) &&
+            duplicatesManager.duplicateGroups.length > 0) {
+            duplicatesManager.enterDuplicateMode();
+            return;
+        }
+
+        if (typeof duplicatesManager.findDuplicates === 'function') {
+            await duplicatesManager.findDuplicates();
+        }
+    }
+
+    syncCustomFilterIndicator() {
+        const indicator = document.getElementById('customFilterIndicator');
+        if (!indicator) {
+            return;
+        }
+
+        if (this.pageState.viewMode === 'excluded') {
+            indicator.classList.add('hidden');
+            return;
+        }
+
+        if (typeof this.checkCustomFilters === 'function') {
+            this.checkCustomFilters();
+        }
+    }
+
+    async enterExcludedView() {
+        if (this.pageState.viewMode === 'excluded') {
+            return;
+        }
+
+        const interactionSnapshot = this.suspendInteractiveModes();
+
+        this.pageState.activeViewSnapshot = {
+            sortBy: this.pageState.sortBy,
+            activeFolder: this.pageState.activeFolder,
+            activeLetterFilter: this.pageState.activeLetterFilter ?? null,
+            showFavoritesOnly: this.pageState.showFavoritesOnly,
+            showUpdateAvailableOnly: this.pageState.showUpdateAvailableOnly,
+            bulkMode: interactionSnapshot.bulkMode,
+            duplicatesMode: interactionSnapshot.duplicatesMode,
+            filters: this.cloneFilters(),
+        };
+
+        const excludedState = this.pageState.excludedViewState || {
+            sortBy: 'name:asc',
+            search: '',
+        };
+
+        this.pageState.viewMode = 'excluded';
+        this.pageState.sortBy = excludedState.sortBy || 'name:asc';
+        this.pageState.currentPage = 1;
+        this.pageState.activeFolder = null;
+        this.pageState.activeLetterFilter = null;
+        this.pageState.showFavoritesOnly = false;
+        this.pageState.showUpdateAvailableOnly = false;
+
+        this.applyFilterState(this.buildExcludedFilters(excludedState.search || ''));
+        this.syncExcludedViewState();
+        await this.resetAndReload(false);
+    }
+
+    async exitExcludedView() {
+        if (this.pageState.viewMode !== 'excluded') {
+            return;
+        }
+
+        this.pageState.excludedViewState = {
+            ...(this.pageState.excludedViewState || {}),
+            sortBy: this.pageState.sortBy,
+            search: this.pageState.filters?.search || '',
+        };
+
+        const snapshot = this.pageState.activeViewSnapshot || {};
+        this.pageState.viewMode = 'active';
+        this.pageState.sortBy = snapshot.sortBy || this.convertLegacySortFormat(getStorageItem(`${this.pageType}_sort`) || 'name:asc');
+        this.pageState.currentPage = 1;
+        this.pageState.activeFolder = snapshot.activeFolder ?? getStorageItem(`${this.pageType}_activeFolder`);
+        this.pageState.activeLetterFilter = snapshot.activeLetterFilter ?? null;
+        this.pageState.showFavoritesOnly = Boolean(snapshot.showFavoritesOnly);
+        this.pageState.showUpdateAvailableOnly = Boolean(snapshot.showUpdateAvailableOnly);
+        this.applyFilterState(snapshot.filters || this.buildExcludedFilters(''));
+        this.pageState.activeViewSnapshot = null;
+
+        this.syncExcludedViewState();
+        await this.resetAndReload(true);
+        this.syncCustomFilterIndicator();
+        await this.restoreInteractiveModes(snapshot);
+    }
     
     /**
      * Find duplicate models

static/js/components/shared/ModelCard.js

@@ -433,10 +433,11 @@ export function createModelCard(model, modelType) {
     card.dataset.usage_count = String(model.usage_count);
     card.dataset.notes = model.notes || '';
     card.dataset.base_model = model.base_model || 'Unknown';
-        card.dataset.favorite = model.favorite ? 'true' : 'false';
-        const hasUpdateAvailable = Boolean(model.update_available);
-        card.dataset.update_available = hasUpdateAvailable ? 'true' : 'false';
-        card.dataset.skip_metadata_refresh = model.skip_metadata_refresh ? 'true' : 'false';
+    card.dataset.favorite = model.favorite ? 'true' : 'false';
+    card.dataset.exclude = model.exclude ? 'true' : 'false';
+    const hasUpdateAvailable = Boolean(model.update_available);
+    card.dataset.update_available = hasUpdateAvailable ? 'true' : 'false';
+    card.dataset.skip_metadata_refresh = model.skip_metadata_refresh ? 'true' : 'false';
 
     // To only show usage_count when sorting by usage. 
     const pageState = getCurrentPageState();
@@ -487,6 +488,9 @@ export function createModelCard(model, modelType) {
     if (model.skip_metadata_refresh) {
         card.classList.add('skip-refresh');
     }
+    if (model.exclude) {
+        card.classList.add('excluded-model');
+    }
 
     // Apply selection state if in bulk mode and this card is in the selected set (LoRA only)
     if (modelType === MODEL_TYPES.LORA && state.bulkMode && state.selectedLoras.has(model.file_path)) {
@@ -619,6 +623,11 @@ export function createModelCard(model, modelType) {
                             <i class="fas fa-ban"></i>
                         </span>
                     ` : ''}
+                    ${model.exclude ? `
+                        <span class="model-excluded-badge" title="${translate('globalContextMenu.manageExcludedModels.label', {}, 'Excluded Models')}">
+                            <i class="fas fa-eye-slash"></i>
+                        </span>
+                    ` : ''}
                 </div>
                 <div class="card-actions">
                     ${actionIcons}
@@ -636,7 +645,7 @@ export function createModelCard(model, modelType) {
                 <div class="model-info">
                     <span class="model-name" title="${getDisplayName(model).replace(/"/g, '&quot;')}">${getDisplayName(model)}</span>
                     <div>
-                        ${model.civitai?.name ? `<span class="version-name">${model.civitai.name}</span>` : ''}
+                        ${model.civitai?.name ? `<span class="version-name civitai-version">${model.civitai.name}</span>` : ''}
                         ${hasUsageCount ? `<span class="version-name" title="${translate('modelCard.usage.timesUsed', {}, 'Times used')}">${model.usage_count}×</span>` : ''}
                     </div>
                 </div>

static/js/components/shared/ModelVersionsTab.js

@@ -1,26 +1,21 @@
 import { getModelApiClient } from '../../api/modelApiFactory.js';
 import { downloadManager } from '../../managers/DownloadManager.js';
 import { modalManager } from '../../managers/ModalManager.js';
-import { showToast } from '../../utils/uiHelpers.js';
+import { openCivitaiUrl, showToast } from '../../utils/uiHelpers.js';
 import { translate } from '../../utils/i18nHelpers.js';
 import { state } from '../../state/index.js';
+import { buildCivitaiModelUrl } from '../../utils/civitaiUtils.js';
 import { formatFileSize } from './utils.js';
 
 const VIDEO_EXTENSIONS = ['.mp4', '.webm', '.mov', '.mkv'];
 const PREVIEW_PLACEHOLDER_URL = '/loras_static/images/no-preview.png';
 
 function buildCivitaiVersionUrl(modelId, versionId) {
-    if (modelId == null || versionId == null) {
-        return null;
-    }
-    const normalizedModelId = String(modelId).trim();
-    const normalizedVersionId = String(versionId).trim();
-    if (!normalizedModelId || !normalizedVersionId) {
-        return null;
-    }
-    const encodedModelId = encodeURIComponent(normalizedModelId);
-    const encodedVersionId = encodeURIComponent(normalizedVersionId);
-    return `https://civitai.com/models/${encodedModelId}?modelVersionId=${encodedVersionId}`;
+    return buildCivitaiModelUrl(
+        modelId,
+        versionId,
+        state?.global?.settings?.civitai_host
+    );
 }
 
 function escapeHtml(value) {
@@ -186,6 +181,13 @@ function isEarlyAccessActive(version) {
     }
 }
 
+function isDownloadAllowed(version) {
+    if (!version.usageControl) {
+        return true;
+    }
+    return version.usageControl === 'Download';
+}
+
 function buildMetaMarkup(version, options = {}) {
     const segments = [];
     if (version.baseModel) {
@@ -220,8 +222,40 @@ function buildMetaMarkup(version, options = {}) {
         .join('<span class="version-meta-separator">•</span>');
 }
 
-function buildBadge(label, tone) {
-    return `<span class="version-badge version-badge-${tone}">${escapeHtml(label)}</span>`;
+function buildBadge(label, tone, options = {}) {
+    const attributes = [];
+    if (options.title) {
+        attributes.push(`title="${escapeHtml(options.title)}"`);
+    }
+    if (options.ariaLabel) {
+        attributes.push(`aria-label="${escapeHtml(options.ariaLabel)}"`);
+    }
+    const suffix = attributes.length ? ` ${attributes.join(' ')}` : '';
+    return `<span class="version-badge version-badge-${tone}"${suffix}>${escapeHtml(label)}</span>`;
+}
+
+function buildActionButton(label, variant, action, options = {}) {
+    const attributes = [
+        `class="version-action ${variant}"`,
+    ];
+    if (action) {
+        attributes.push(`data-version-action="${escapeHtml(action)}"`);
+    }
+    if (!options.disabled && options.title) {
+        attributes.push(`title="${escapeHtml(options.title)}"`);
+        attributes.push(`aria-label="${escapeHtml(options.title)}"`);
+    }
+    if (options.disabled) {
+        attributes.push('disabled');
+    }
+    if (options.extraAttributes) {
+        attributes.push(options.extraAttributes);
+    }
+    const buttonHtml = `<button ${attributes.join(' ')}>${options.iconMarkup || ''}${escapeHtml(label)}</button>`;
+    if (options.disabled && options.title) {
+        return `<span class="version-action-disabled-wrapper" title="${escapeHtml(options.title)}" aria-label="${escapeHtml(options.title)}">${buttonHtml}</span>`;
+    }
+    return buttonHtml;
 }
 
 const DISPLAY_FILTER_MODES = Object.freeze({
@@ -353,6 +387,9 @@ function resolveUpdateAvailability(record, baseModel, currentVersionId) {
         if (hideEarlyAccess && isEarlyAccessActive(version)) {
             return false;
         }
+        if (!isDownloadAllowed(version)) {
+            return false;
+        }
         const versionBase = normalizeBaseModelName(version.baseModel);
         if (versionBase !== normalizedBase) {
             return false;
@@ -426,23 +463,83 @@ function renderRow(version, options) {
         version.versionId > latestLibraryVersionId;
     const isEarlyAccess = isEarlyAccessActive(version);
     const badges = [];
+    const openedBadgeLabel = translate('modals.model.versions.badges.current', {}, 'Opened Version');
+    const inLibraryBadgeLabel = translate('modals.model.versions.badges.inLibrary', {}, 'In Library');
+    const downloadedBadgeLabel = translate('modals.model.versions.badges.downloaded', {}, 'Downloaded');
+    const newerBadgeLabel = translate('modals.model.versions.badges.newer', {}, 'Newer Version');
+    const earlyAccessBadgeLabel = translate('modals.model.versions.badges.earlyAccess', {}, 'Early Access');
+    const ignoredBadgeLabel = translate('modals.model.versions.badges.ignored', {}, 'Ignored');
+    const versionName = version.name || translate('modals.model.versions.labels.unnamed', {}, 'Untitled Version');
 
     if (isCurrent) {
-        badges.push(buildBadge(translate('modals.model.versions.badges.current', {}, 'Current Version'), 'current'));
+        badges.push(buildBadge(openedBadgeLabel, 'current', {
+            title: translate(
+                'modals.model.versions.badges.currentTooltip',
+                {},
+                'This is the version you opened this modal from'
+            ),
+        }));
     }
 
     if (version.isInLibrary) {
-        badges.push(buildBadge(translate('modals.model.versions.badges.inLibrary', {}, 'In Library'), 'success'));
-    } else if (isNewer && !version.shouldIgnore) {
-        badges.push(buildBadge(translate('modals.model.versions.badges.newer', {}, 'Newer Version'), 'info'));
+        badges.push(buildBadge(inLibraryBadgeLabel, 'success', {
+            title: translate(
+                'modals.model.versions.badges.inLibraryTooltip',
+                {},
+                'This version exists in your local library'
+            ),
+        }));
+    }
+
+    if (!version.isInLibrary && version.hasBeenDownloaded) {
+        badges.push(buildBadge(downloadedBadgeLabel, 'info', {
+            title: translate(
+                'modals.model.versions.badges.downloadedTooltip',
+                {},
+                'This version was downloaded before, but is not currently in your library'
+            ),
+        }));
+    }
+
+    if (!version.isInLibrary && isNewer && !version.shouldIgnore) {
+        badges.push(buildBadge(newerBadgeLabel, 'info', {
+            title: translate(
+                'modals.model.versions.badges.newerTooltip',
+                {},
+                'This version is newer than your latest local version'
+            ),
+        }));
     }
 
     if (isEarlyAccess) {
-        badges.push(buildBadge(translate('modals.model.versions.badges.earlyAccess', {}, 'Early Access'), 'early-access'));
+        badges.push(buildBadge(earlyAccessBadgeLabel, 'early-access', {
+            title: translate(
+                'modals.model.versions.badges.earlyAccessTooltip',
+                {},
+                'This version currently requires Civitai early access'
+            ),
+        }));
+    }
+
+    if (!isDownloadAllowed(version)) {
+        const onSiteOnlyBadgeLabel = translate('modals.model.versions.badges.onSiteOnly', {}, 'On-Site Only');
+        badges.push(buildBadge(onSiteOnlyBadgeLabel, 'info', {
+            title: translate(
+                'modals.model.versions.badges.onSiteOnlyTooltip',
+                {},
+                'This version is only available for on-site generation on Civitai'
+            ),
+        }));
     }
 
     if (version.shouldIgnore) {
-        badges.push(buildBadge(translate('modals.model.versions.badges.ignored', {}, 'Ignored'), 'muted'));
+        badges.push(buildBadge(ignoredBadgeLabel, 'muted', {
+            title: translate(
+                'modals.model.versions.badges.ignoredTooltip',
+                {},
+                'Update notifications are disabled for this version'
+            ),
+        }));
     }
 
     const downloadLabel = translate('modals.model.versions.actions.download', {}, 'Download');
@@ -457,31 +554,95 @@ function renderRow(version, options) {
 
     const actions = [];
     if (!version.isInLibrary) {
-        // Download button with optional EA bolt icon
+        const canDownload = isDownloadAllowed(version);
         const downloadIcon = isEarlyAccess ? '<i class="fas fa-bolt"></i> ' : '';
-        actions.push(
-            `<button class="version-action version-action-primary" data-version-action="download">${downloadIcon}${escapeHtml(downloadLabel)}</button>`
-        );
+        let downloadTitle;
+        if (!canDownload) {
+            downloadTitle = translate(
+                'modals.model.versions.actions.downloadNotAllowedTooltip',
+                {},
+                'This version is only available for on-site generation on Civitai'
+            );
+        } else if (isEarlyAccess) {
+            downloadTitle = translate(
+                'modals.model.versions.actions.downloadEarlyAccessTooltip',
+                {},
+                'Download this early access version from Civitai'
+            );
+        } else {
+            downloadTitle = translate(
+                'modals.model.versions.actions.downloadTooltip',
+                {},
+                'Download this version'
+            );
+        }
+        actions.push(buildActionButton(
+            downloadLabel,
+            canDownload ? 'version-action-primary' : 'version-action-disabled',
+            canDownload ? 'download' : '',
+            {
+                title: downloadTitle,
+                iconMarkup: downloadIcon,
+                disabled: !canDownload,
+            }
+        ));
     } else if (version.filePath) {
-        actions.push(
-            `<button class="version-action version-action-danger" data-version-action="delete">${escapeHtml(deleteLabel)}</button>`
-        );
+        actions.push(buildActionButton(
+            deleteLabel,
+            'version-action-danger',
+            'delete',
+            {
+                title: translate(
+                    'modals.model.versions.actions.deleteTooltip',
+                    {},
+                    'Delete this local version'
+                ),
+            }
+        ));
     }
-    actions.push(
-        `<button class="version-action version-action-ghost" data-version-action="toggle-ignore" data-ignore-state="${
-            version.shouldIgnore ? 'ignored' : 'active'
-        }">${escapeHtml(ignoreLabel)}</button>`
-    );
+    actions.push(buildActionButton(
+        ignoreLabel,
+        'version-action-ghost',
+        'toggle-ignore',
+        {
+            title: version.shouldIgnore
+                ? translate(
+                    'modals.model.versions.actions.unignoreTooltip',
+                    {},
+                    'Resume update notifications for this version'
+                )
+                : translate(
+                    'modals.model.versions.actions.ignoreTooltip',
+                    {},
+                    'Ignore update notifications for this version'
+                ),
+            extraAttributes: `data-ignore-state="${version.shouldIgnore ? 'ignored' : 'active'}"`,
+        }
+    ));
 
     const linkTarget = buildCivitaiVersionUrl(
         version.modelId || parentModelId,
         version.versionId
     );
     const civitaiTooltip = translate(
-        'modals.model.actions.viewOnCivitai',
+        'modals.model.versions.actions.viewVersionOnCivitai',
         {},
-        'View on Civitai'
+        'View version on Civitai'
     );
+    const civitaiLinkMarkup = linkTarget
+        ? `
+            <a
+                class="version-civitai-link"
+                href="${escapeHtml(linkTarget)}"
+                target="_blank"
+                rel="noopener noreferrer"
+                title="${escapeHtml(civitaiTooltip)}"
+                aria-label="${escapeHtml(civitaiTooltip)}"
+            >
+                <i class="fas fa-arrow-up-right-from-square" aria-hidden="true"></i>
+            </a>
+        `
+        : '';
 
     const rowAttributes = [
         `class="model-version-row${isCurrent ? ' is-current' : ''}${linkTarget ? ' is-clickable' : ''}${isEarlyAccess ? ' is-early-access' : ''}"`,
@@ -489,7 +650,6 @@ function renderRow(version, options) {
     ];
     if (linkTarget) {
         rowAttributes.push(`data-civitai-url="${escapeHtml(linkTarget)}"`);
-        rowAttributes.push(`title="${escapeHtml(civitaiTooltip)}"`);
     }
 
     return `
@@ -497,7 +657,8 @@ function renderRow(version, options) {
             ${renderMediaMarkup(version)}
             <div class="version-details">
                 <div class="version-title">
-                    <span class="versions-tab-version-name">${escapeHtml(version.name || translate('modals.model.versions.labels.unnamed', {}, 'Untitled Version'))}</span>
+                    <span class="versions-tab-version-name">${escapeHtml(versionName)}</span>
+                    ${civitaiLinkMarkup}
                 </div>
                 <div class="version-badges">${badges.join('')}</div>
                 <div class="version-meta">
@@ -1227,9 +1388,17 @@ export function initVersionsTab({
         }
 
         const row = event.target.closest('.model-version-row.is-clickable');
+        const civitaiLink = event.target.closest('.version-civitai-link');
+        if (civitaiLink) {
+            event.preventDefault();
+            openCivitaiUrl(civitaiLink.href);
+            return;
+        }
+
         if (!row) {
             return;
         }
+
         if (event.target.closest('button')) {
             return;
         }
@@ -1245,7 +1414,7 @@ export function initVersionsTab({
             return;
         }
         event.preventDefault();
-        window.open(targetUrl, '_blank', 'noopener,noreferrer');
+        openCivitaiUrl(targetUrl);
     });
 
     // Listen for extension-triggered refresh requests

static/js/components/shared/TriggerWords.js

@@ -8,6 +8,10 @@ import { translate } from '../../utils/i18nHelpers.js';
 import { getModelApiClient } from '../../api/modelApiFactory.js';
 import { escapeAttribute, escapeHtml } from './utils.js';
 
+const MAX_WORDS_PER_TRIGGER_GROUP = 500;
+const MAX_TRIGGER_WORD_GROUPS = 100;
+const TRIGGER_WORD_CLICK_DELAY_MS = 220;
+
 /**
  * Fetch trained words for a model
  * @param {string} filePath - Path to the model file
@@ -223,7 +227,7 @@ export function renderTriggerWords(words, filePath) {
         const escapedWord = escapeHtml(word);
         const escapedAttr = escapeAttribute(word);
         return `
-                        <div class="trigger-word-tag" data-word="${escapedAttr}" onclick="copyTriggerWord(this.dataset.word)" title="${translate('modals.model.triggerWords.copyWord')}">
+                        <div class="trigger-word-tag" data-word="${escapedAttr}" title="${translate('modals.model.triggerWords.copyWord')}">
                             <span class="trigger-word-content">${escapedWord}</span>
                             <span class="trigger-word-copy">
                                 <i class="fas fa-copy"></i>
@@ -261,6 +265,8 @@ export function setupTriggerWordsEditMode() {
     const editBtn = document.querySelector('.edit-trigger-words-btn');
     if (!editBtn) return;
 
+    document.querySelectorAll('.trigger-word-tag').forEach(setupDisplayTriggerWordTag);
+
     editBtn.addEventListener('click', async function () {
         const triggerWordsSection = this.closest('.trigger-words');
         const isEditMode = triggerWordsSection.classList.toggle('edit-mode');
@@ -293,7 +299,9 @@ export function setupTriggerWordsEditMode() {
 
             // Disable click-to-copy and show delete buttons
             triggerWordTags.forEach(tag => {
-                tag.onclick = null;
+                teardownDisplayTriggerWordTag(tag);
+                tag.addEventListener('click', startEditTriggerWord);
+                tag.title = translate('modals.model.triggerWords.editWord');
                 const copyIcon = tag.querySelector('.trigger-word-copy');
                 const deleteBtn = tag.querySelector('.metadata-delete-btn');
 
@@ -337,6 +345,12 @@ export function setupTriggerWordsEditMode() {
             // Focus the input
             addForm.querySelector('input').focus();
 
+            const pendingEditTag = triggerWordsSection._pendingTriggerWordEditTag;
+            delete triggerWordsSection._pendingTriggerWordEditTag;
+            if (pendingEditTag && document.contains(pendingEditTag)) {
+                startEditTriggerWord.call(pendingEditTag, { target: pendingEditTag, preventDefault() { }, stopPropagation() { } });
+            }
+
         } else {
             this.innerHTML = '<i class="fas fa-pencil-alt"></i>'; // Change back to edit icon
             this.title = translate('modals.model.triggerWords.edit');
@@ -350,6 +364,7 @@ export function setupTriggerWordsEditMode() {
                 // If canceling, restore original trigger words
                 restoreOriginalTriggerWords(triggerWordsSection, originalTriggerWords);
             } else {
+                commitActiveTriggerWordEdit(triggerWordsSection);
                 // If saving, reset UI state on current trigger words
                 resetTriggerWordsUIState(triggerWordsSection);
                 // Reset the skip restore flag
@@ -429,15 +444,18 @@ function deleteTriggerWord(e) {
  * @param {HTMLElement} section - The trigger words section
  */
 function resetTriggerWordsUIState(section) {
+    commitActiveTriggerWordEdit(section);
+
     const triggerWordTags = section.querySelectorAll('.trigger-word-tag');
 
     triggerWordTags.forEach(tag => {
-        const word = tag.dataset.word;
         const copyIcon = tag.querySelector('.trigger-word-copy');
         const deleteBtn = tag.querySelector('.metadata-delete-btn');
 
         // Restore click-to-copy functionality
-        tag.onclick = () => copyTriggerWord(tag.dataset.word);
+        tag.removeEventListener('click', startEditTriggerWord);
+        setupDisplayTriggerWordTag(tag);
+        tag.title = translate('modals.model.triggerWords.copyWord');
 
         // Show copy icon, hide delete button
         if (copyIcon) copyIcon.style.display = '';
@@ -471,25 +489,236 @@ function restoreOriginalTriggerWords(section, originalWords) {
 
     // Recreate original tags
     originalWords.forEach(word => {
-        const tag = document.createElement('div');
-        tag.className = 'trigger-word-tag';
-        tag.dataset.word = word;
-        tag.onclick = () => copyTriggerWord(tag.dataset.word);
-
-        const escapedWord = escapeHtml(word);
-        tag.innerHTML = `
-            <span class="trigger-word-content">${escapedWord}</span>
-            <span class="trigger-word-copy">
-                <i class="fas fa-copy"></i>
-            </span>
-            <button class="metadata-delete-btn" style="display:none;" onclick="event.stopPropagation();">
-                <i class="fas fa-times"></i>
-            </button>
-        `;
-        tagsContainer.appendChild(tag);
+        tagsContainer.appendChild(createTriggerWordTag(word, false));
     });
 }
 
+/**
+ * Create a trigger word tag element
+ * @param {string} word - Trigger word
+ * @param {boolean} isEditMode - Whether the tag should be editable
+ * @returns {HTMLElement} Tag element
+ */
+function createTriggerWordTag(word, isEditMode = false) {
+    const tag = document.createElement('div');
+    tag.className = 'trigger-word-tag';
+    tag.dataset.word = word;
+    tag.title = translate(isEditMode ? 'modals.model.triggerWords.editWord' : 'modals.model.triggerWords.copyWord');
+
+    const escapedWord = escapeHtml(word);
+    tag.innerHTML = `
+        <span class="trigger-word-content">${escapedWord}</span>
+        <span class="trigger-word-copy" style="${isEditMode ? 'display:none;' : ''}">
+            <i class="fas fa-copy"></i>
+        </span>
+        <button class="metadata-delete-btn" style="${isEditMode ? '' : 'display:none;'}" onclick="event.stopPropagation();" title="${translate('modals.model.triggerWords.deleteWord')}">
+            <i class="fas fa-times"></i>
+        </button>
+    `;
+
+    const deleteBtn = tag.querySelector('.metadata-delete-btn');
+    deleteBtn.addEventListener('click', deleteTriggerWord);
+
+    if (isEditMode) {
+        tag.addEventListener('click', startEditTriggerWord);
+    } else {
+        setupDisplayTriggerWordTag(tag);
+    }
+
+    return tag;
+}
+
+/**
+ * Set up display-mode click-to-copy and double-click-to-edit behavior
+ * @param {HTMLElement} tag - Trigger word tag
+ */
+function setupDisplayTriggerWordTag(tag) {
+    teardownDisplayTriggerWordTag(tag);
+
+    tag.addEventListener('click', handleDisplayTriggerWordClick);
+    tag.addEventListener('dblclick', handleDisplayTriggerWordDoubleClick);
+    tag.title = translate('modals.model.triggerWords.copyWord');
+}
+
+/**
+ * Remove display-mode handlers and pending copy action
+ * @param {HTMLElement} tag - Trigger word tag
+ */
+function teardownDisplayTriggerWordTag(tag) {
+    if (tag.dataset.copyTimerId) {
+        clearTimeout(Number(tag.dataset.copyTimerId));
+        delete tag.dataset.copyTimerId;
+    }
+    tag.onclick = null;
+    tag.removeEventListener('click', handleDisplayTriggerWordClick);
+    tag.removeEventListener('dblclick', handleDisplayTriggerWordDoubleClick);
+}
+
+/**
+ * Copy trigger word after a short delay so dblclick can cancel it
+ * @param {MouseEvent} e - Click event
+ */
+function handleDisplayTriggerWordClick(e) {
+    if (e.target.closest('.metadata-delete-btn') || e.target.closest('.trigger-word-edit-input')) return;
+
+    const tag = this.closest('.trigger-word-tag');
+    if (!tag || tag.closest('.trigger-words')?.classList.contains('edit-mode')) return;
+
+    e.stopPropagation();
+
+    if (tag.dataset.copyTimerId) {
+        clearTimeout(Number(tag.dataset.copyTimerId));
+    }
+
+    const timerId = window.setTimeout(() => {
+        delete tag.dataset.copyTimerId;
+        copyTriggerWord(tag.dataset.word);
+    }, TRIGGER_WORD_CLICK_DELAY_MS);
+    tag.dataset.copyTimerId = String(timerId);
+}
+
+/**
+ * Enter edit mode and start editing the double-clicked trigger word
+ * @param {MouseEvent} e - Double-click event
+ */
+function handleDisplayTriggerWordDoubleClick(e) {
+    if (e.target.closest('.metadata-delete-btn') || e.target.closest('.trigger-word-edit-input')) return;
+
+    const tag = this.closest('.trigger-word-tag');
+    const section = tag?.closest('.trigger-words');
+    const editBtn = section?.querySelector('.edit-trigger-words-btn');
+    if (!tag || !section || !editBtn) return;
+
+    e.preventDefault();
+    e.stopPropagation();
+
+    if (tag.dataset.copyTimerId) {
+        clearTimeout(Number(tag.dataset.copyTimerId));
+        delete tag.dataset.copyTimerId;
+    }
+
+    if (!section.classList.contains('edit-mode')) {
+        section._pendingTriggerWordEditTag = tag;
+        editBtn.click();
+        return;
+    }
+
+    startEditTriggerWord.call(tag, e);
+}
+
+/**
+ * Validate a trigger word against existing tags
+ * @param {string} word - Trigger word
+ * @param {HTMLElement} tagsContainer - Tags container
+ * @param {HTMLElement|null} currentTag - Tag being edited, if any
+ * @returns {boolean} Whether the word is valid
+ */
+function validateTriggerWord(word, tagsContainer, currentTag = null) {
+    if (word.split(/\s+/).length > MAX_WORDS_PER_TRIGGER_GROUP) {
+        showToast('toast.triggerWords.tooLong', {}, 'error');
+        return false;
+    }
+
+    const currentTags = tagsContainer.querySelectorAll('.trigger-word-tag');
+    const existingWords = Array.from(currentTags)
+        .filter(tag => tag !== currentTag)
+        .map(tag => tag.dataset.word);
+
+    if (existingWords.includes(word)) {
+        showToast('toast.triggerWords.alreadyExists', {}, 'error');
+        return false;
+    }
+
+    return true;
+}
+
+/**
+ * Start inline editing for a trigger word tag
+ * @param {Event} e - Click event
+ */
+function startEditTriggerWord(e) {
+    if (e.target.closest('.metadata-delete-btn') || e.target.closest('.trigger-word-edit-input')) return;
+
+    const tag = this.closest('.trigger-word-tag');
+    const section = tag?.closest('.trigger-words');
+    if (!tag || !section?.classList.contains('edit-mode') || tag.classList.contains('is-editing')) return;
+
+    e.preventDefault();
+    e.stopPropagation();
+
+    commitActiveTriggerWordEdit(section);
+
+    const content = tag.querySelector('.trigger-word-content');
+    const originalWord = tag.dataset.word;
+    const originalRect = tag.getBoundingClientRect();
+    if (originalRect.width > 0) {
+        tag.style.setProperty('--trigger-word-edit-width', `${Math.ceil(originalRect.width)}px`);
+    }
+    if (originalRect.height > 0) {
+        tag.style.setProperty('--trigger-word-edit-height', `${Math.ceil(originalRect.height)}px`);
+    }
+
+    const editor = document.createElement('textarea');
+    editor.className = 'trigger-word-edit-input';
+    editor.rows = 1;
+    editor.value = originalWord;
+    editor.setAttribute('aria-label', translate('modals.model.triggerWords.editWord'));
+    editor.placeholder = translate('modals.model.triggerWords.editPlaceholder');
+
+    let finished = false;
+    const finish = (shouldCommit) => {
+        if (finished) return;
+        finished = true;
+
+        const nextWord = editor.value.trim().replace(/\s*\n+\s*/g, ' ');
+        if (shouldCommit && nextWord && nextWord !== originalWord) {
+            const tagsContainer = tag.closest('.trigger-words-tags');
+            if (tagsContainer && validateTriggerWord(nextWord, tagsContainer, tag)) {
+                tag.dataset.word = nextWord;
+                content.textContent = nextWord;
+            }
+        }
+
+        editor.remove();
+        content.style.display = '';
+        tag.classList.remove('is-editing');
+        tag.style.removeProperty('--trigger-word-edit-width');
+        tag.style.removeProperty('--trigger-word-edit-height');
+        updateTrainedWordsDropdown();
+    };
+
+    editor.addEventListener('click', event => event.stopPropagation());
+    editor.addEventListener('keydown', event => {
+        if (event.key === 'Enter') {
+            event.preventDefault();
+            finish(true);
+        } else if (event.key === 'Escape') {
+            event.preventDefault();
+            finish(false);
+        }
+    });
+    editor.addEventListener('blur', () => finish(true));
+
+    editor.style.visibility = 'hidden';
+    content.after(editor);
+    tag.classList.add('is-editing');
+    content.style.display = 'none';
+    editor.style.visibility = '';
+    editor.focus();
+    editor.select();
+}
+
+/**
+ * Commit an active inline trigger word edit if one exists
+ * @param {HTMLElement} section - Trigger words section
+ */
+function commitActiveTriggerWordEdit(section) {
+    const input = section.querySelector('.trigger-word-edit-input');
+    if (input) {
+        input.dispatchEvent(new FocusEvent('blur'));
+    }
+}
+
 /**
  * Add a new trigger word
  * @param {string} word - Trigger word to add
@@ -522,46 +751,16 @@ function addNewTriggerWord(word) {
         noTriggerWordsMsg.style.display = 'none';
     }
 
-    // Validation: Check length
-    if (word.split(/\s+/).length > 100) {
-        showToast('toast.triggerWords.tooLong', {}, 'error');
-        return;
-    }
-
     // Validation: Check total number
     const currentTags = tagsContainer.querySelectorAll('.trigger-word-tag');
-    if (currentTags.length >= 100) {
+    if (currentTags.length >= MAX_TRIGGER_WORD_GROUPS) {
         showToast('toast.triggerWords.tooMany', {}, 'error');
         return;
     }
 
-    // Validation: Check for duplicates
-    const existingWords = Array.from(currentTags).map(tag => tag.dataset.word);
-    if (existingWords.includes(word)) {
-        showToast('toast.triggerWords.alreadyExists', {}, 'error');
-        return;
-    }
-
-    // Create new tag
-    const newTag = document.createElement('div');
-    newTag.className = 'trigger-word-tag';
-    newTag.dataset.word = word;
-
-    const escapedWord = escapeHtml(word);
-    newTag.innerHTML = `
-        <span class="trigger-word-content">${escapedWord}</span>
-        <span class="trigger-word-copy" style="display:none;">
-            <i class="fas fa-copy"></i>
-        </span>
-        <button class="metadata-delete-btn" onclick="event.stopPropagation();">
-            <i class="fas fa-times"></i>
-        </button>
-    `;
-
-    // Add event listener to delete button
-    const deleteBtn = newTag.querySelector('.metadata-delete-btn');
-    deleteBtn.addEventListener('click', deleteTriggerWord);
+    if (!validateTriggerWord(word, tagsContainer)) return;
 
+    const newTag = createTriggerWordTag(word, triggerWordsSection.classList.contains('edit-mode'));
     tagsContainer.appendChild(newTag);
 
     // Update status of items in the trained words dropdown
@@ -633,6 +832,8 @@ async function saveTriggerWords() {
     const filePath = editBtn.dataset.filePath;
     const triggerWordsSection = editBtn.closest('.trigger-words');
 
+    commitActiveTriggerWordEdit(triggerWordsSection);
+
     // Auto-commit any pending input to prevent data loss
     const input = triggerWordsSection.querySelector('.metadata-input');
     if (input && input.value.trim()) {

static/js/managers/BatchImportManager.js

@@ -432,7 +432,7 @@ export class BatchImportManager {
         
         // Refresh recipes list to show newly imported recipes
         if (window.recipeManager && typeof window.recipeManager.loadRecipes === 'function') {
-            window.recipeManager.loadRecipes();
+            window.recipeManager.loadRecipes({ preserveScroll: true });
         }
         
         // Show results step

static/js/managers/BulkManager.js

@@ -3,7 +3,7 @@ import { showToast, copyToClipboard, sendLoraToWorkflow, buildLoraSyntax, getNSF
 import { updateCardsForBulkMode } from '../components/shared/ModelCard.js';
 import { modalManager } from './ModalManager.js';
 import { getModelApiClient, resetAndReload } from '../api/modelApiFactory.js';
-import { RecipeSidebarApiClient } from '../api/recipeApi.js';
+import { RecipeSidebarApiClient, updateRecipeMetadata } from '../api/recipeApi.js';
 import { MODEL_TYPES, MODEL_CONFIG } from '../api/apiConfig.js';
 import { BASE_MODEL_CATEGORIES } from '../utils/constants.js';
 import { getPriorityTagSuggestions } from '../utils/priorityTagHelpers.js';
@@ -41,7 +41,9 @@ export class BulkManager {
                 autoOrganize: true,
                 deleteAll: true,
                 setContentRating: true,
-                skipMetadataRefresh: true
+                skipMetadataRefresh: true,
+                setFavorite: true,
+                unfavorite: true
             },
             [MODEL_TYPES.EMBEDDING]: {
                 addTags: true,
@@ -53,7 +55,9 @@ export class BulkManager {
                 autoOrganize: true,
                 deleteAll: true,
                 setContentRating: false,
-                skipMetadataRefresh: true
+                skipMetadataRefresh: true,
+                setFavorite: true,
+                unfavorite: true
             },
             [MODEL_TYPES.CHECKPOINT]: {
                 addTags: true,
@@ -65,7 +69,9 @@ export class BulkManager {
                 autoOrganize: true,
                 deleteAll: true,
                 setContentRating: true,
-                skipMetadataRefresh: true
+                skipMetadataRefresh: true,
+                setFavorite: true,
+                unfavorite: true
             },
             recipes: {
                 addTags: false,
@@ -77,7 +83,9 @@ export class BulkManager {
                 autoOrganize: false,
                 deleteAll: true,
                 setContentRating: false,
-                skipMetadataRefresh: false
+                skipMetadataRefresh: false,
+                setFavorite: true,
+                unfavorite: true
             }
         };
 
@@ -240,9 +248,7 @@ export class BulkManager {
      */
     handleGlobalKeyboard(e) {
         // Skip if modal is open (handled by event manager conditions)
-        // Skip if search input is focused
-        const searchInput = document.getElementById('searchInput');
-        if (searchInput && document.activeElement === searchInput) {
+        if (this.isEditingTextInputContext(e.target)) {
             return false; // Don't handle, allow default behavior
         }
 
@@ -266,6 +272,26 @@ export class BulkManager {
         return false; // Continue with other handlers
     }
 
+    isEditingTextInputContext(target) {
+        const activeElement = document.activeElement;
+        const candidate = target instanceof Element ? target : activeElement;
+        if (!candidate) {
+            return false;
+        }
+
+        const tagName = candidate.tagName?.toLowerCase();
+        if (
+            candidate.isContentEditable
+            || tagName === 'input'
+            || tagName === 'textarea'
+            || tagName === 'select'
+        ) {
+            return true;
+        }
+
+        return Boolean(candidate.closest?.('#filterPanel'));
+    }
+
     toggleBulkMode() {
         state.bulkMode = !state.bulkMode;
 
@@ -1072,6 +1098,60 @@ export class BulkManager {
         }
     }
 
+    async setBulkFavorites(value) {
+        if (state.selectedModels.size === 0) {
+            showToast('toast.models.noModelsSelected', {}, 'warning');
+            return;
+        }
+
+        const totalCount = state.selectedModels.size;
+        const isRecipesPage = state.currentPageType === 'recipes';
+
+        state.loadingManager.showSimpleLoading(
+            translate(value ? 'toast.models.bulkFavoriteUpdating' : 'toast.models.bulkUnfavoriteUpdating', { count: totalCount })
+        );
+        let cancelled = false;
+        state.loadingManager.showCancelButton(() => {
+            cancelled = true;
+        });
+
+        let successCount = 0;
+        let failureCount = 0;
+
+        try {
+            for (const filePath of state.selectedModels) {
+                if (cancelled) {
+                    showToast('toast.api.operationCancelled', {}, 'info');
+                    break;
+                }
+                try {
+                    if (isRecipesPage) {
+                        await updateRecipeMetadata(filePath, { favorite: value });
+                    } else {
+                        const apiClient = getModelApiClient();
+                        await apiClient.saveModelMetadata(filePath, { favorite: value });
+                    }
+                    successCount++;
+                } catch (error) {
+                    failureCount++;
+                    console.error(`Failed to set favorite=${value} for ${filePath}:`, error);
+                }
+            }
+        } finally {
+            state.loadingManager?.hide?.();
+        }
+
+        if (successCount === totalCount) {
+            const toastKey = value ? 'modelCard.favorites.added' : 'modelCard.favorites.removed';
+            showToast(toastKey, {}, 'success');
+        } else if (successCount > 0) {
+            const toastKey = value ? 'toast.models.bulkFavoritePartialAdded' : 'toast.models.bulkFavoritePartialRemoved';
+            showToast(toastKey, { success: successCount, failed: failureCount }, 'warning');
+        } else {
+            showToast('toast.models.bulkFavoriteFailed', {}, 'error');
+        }
+    }
+
     /**
      * Show bulk base model modal
      */

static/js/managers/BulkMissingLoraDownloadManager.js

@@ -311,7 +311,7 @@ export class BulkMissingLoraDownloadManager {
 
         // Refresh the recipes list to update LoRA status
         if (window.recipeManager) {
-            window.recipeManager.loadRecipes();
+            window.recipeManager.loadRecipes({ preserveScroll: true });
         }
     }
 

static/js/managers/DoctorManager.js

@@ -2,6 +2,7 @@ import { modalManager } from './ModalManager.js';
 import { showToast } from '../utils/uiHelpers.js';
 import { translate } from '../utils/i18nHelpers.js';
 import { escapeHtml } from '../components/shared/utils.js';
+import { state } from '../state/index.js';
 
 const MAX_CONSOLE_ENTRIES = 200;
 
@@ -258,6 +259,15 @@ export class DoctorManager {
     }
 
     renderInlineDetail(detail) {
+        if (detail.conflict_groups || detail.total_conflict_files) {
+            return `
+                <div class="doctor-inline-detail">
+                    <strong>${escapeHtml(translate('doctor.status.warning', {}, 'Conflicts'))}</strong>
+                    <div>${escapeHtml(`${detail.conflict_groups || 0} filenames, ${detail.total_conflict_files || 0} files`)}</div>
+                </div>
+            `;
+        }
+
         if (detail.client_version || detail.server_version) {
             return `
                 <div class="doctor-inline-detail">
@@ -317,6 +327,9 @@ export class DoctorManager {
             case 'repair-cache':
                 await this.repairCache();
                 break;
+            case 'resolve-filename-conflicts':
+                await this.resolveFilenameConflicts();
+                break;
             case 'reload-page':
                 this.reloadUi();
                 break;
@@ -345,6 +358,47 @@ export class DoctorManager {
         }
     }
 
+    async resolveFilenameConflicts() {
+        try {
+            this.setLoading(true);
+            const response = await fetch('/api/lm/doctor/resolve-filename-conflicts', { method: 'POST' });
+            const payload = await response.json();
+
+            if (!response.ok || payload.success === false) {
+                throw new Error(payload.error || 'Failed to resolve filename conflicts.');
+            }
+
+            const renamedCount = payload.count || 0;
+            showToast(
+                'doctor.toast.conflictsResolved',
+                { count: renamedCount },
+                'success'
+            );
+
+            // Update scroller items so model cards reflect new filenames immediately
+            if (state.virtualScroller && payload.renamed) {
+                for (const renamed of payload.renamed) {
+                    const baseName = renamed.new_filename.replace(/\.[^.]+$/, '');
+                    state.virtualScroller.updateSingleItem(renamed.old_path, {
+                        file_name: baseName,
+                        file_path: renamed.new_path,
+                    });
+                }
+            }
+
+            await this.refreshDiagnostics({ silent: true });
+        } catch (error) {
+            console.error('Doctor filename conflict resolution failed:', error);
+            showToast(
+                'doctor.toast.conflictsResolveFailed',
+                { message: error.message },
+                'error'
+            );
+        } finally {
+            this.setLoading(false);
+        }
+    }
+
     async exportBundle() {
         try {
             this.setLoading(true);