refactor(ui): group example image download actions into a submenu

Move the 'Download Missing' / 'Re-process All' example image actions
under a single 'Download Example Images' submenu item in the single-model
and bulk context menus, matching the existing send-to-workflow submenu
pattern. Shorten the submenu labels and update all locale translations.

AGENTS.md

@@ -137,7 +137,13 @@ npm run test:coverage       # Generate coverage report
 - Dual mode: ComfyUI plugin (folder_paths) vs standalone (settings.json)
 - Detection: `os.environ.get("LORA_MANAGER_STANDALONE", "0") == "1"`
 - Run `python scripts/sync_translation_keys.py` after adding UI strings to `locales/en.json`
-- Symlinks require normalized paths
+- Symlinks require normalized paths.
+  **Business paths vs real paths**: All stored paths and operation routing use the
+  original paths as they appear under configured model roots — symlinks are NOT
+  resolved. `os.path.realpath` is only for scanner dedup and the symlink cache.
+  Any path passed to `os.remove`/`os.rename`/`shutil.move` or validated by a
+  containment check MUST use the business path (i.e. `os.path.abspath`, not
+  `realpath`).
 
 ## Git / Commit Messages
 

__init__.py

@@ -17,6 +17,8 @@ try:  # pragma: no cover - import fallback for pytest collection
     from .py.nodes.lora_cycler import LoraCyclerLM
     from .py.nodes.lora_info import LoraInfoLM
     from .py.nodes.lora_syntax_to_path import LoraSyntaxToPath
+    from .py.nodes.create_hook_lora import CreateHookLoraLM
+    from .py.nodes.metadata_overwrite import MetadataOverwriteLM
     from .py.metadata_collector import init as init_metadata_collector
 except (
     ImportError
@@ -62,6 +64,12 @@ except (
     LoraSyntaxToPath = importlib.import_module(
         "py.nodes.lora_syntax_to_path"
     ).LoraSyntaxToPath
+    CreateHookLoraLM = importlib.import_module(
+        "py.nodes.create_hook_lora"
+    ).CreateHookLoraLM
+    MetadataOverwriteLM = importlib.import_module(
+        "py.nodes.metadata_overwrite"
+    ).MetadataOverwriteLM
     init_metadata_collector = importlib.import_module("py.metadata_collector").init
 
 NODE_CLASS_MAPPINGS = {
@@ -83,6 +91,8 @@ NODE_CLASS_MAPPINGS = {
     LoraCyclerLM.NAME: LoraCyclerLM,
     LoraInfoLM.NAME: LoraInfoLM,
     LoraSyntaxToPath.NAME: LoraSyntaxToPath,
+    CreateHookLoraLM.NAME: CreateHookLoraLM,
+    MetadataOverwriteLM.NAME: MetadataOverwriteLM,
 }
 
 WEB_DIRECTORY = "./web/comfyui"

locales/en.json

@@ -714,7 +714,9 @@
         "versionsCount": "Local Versions",
         "versionsCountDesc": "Most versions first",
         "versionsCountAsc": "Fewest versions first",
-        "versionIdDesc": "Newest version first"
+        "versionIdDesc": "Newest version first",
+        "random": "Random",
+        "randomAction": "Randomize (shuffle)"
       },
       "refresh": {
         "title": "Refresh model list",
@@ -771,6 +773,8 @@
       "deleteAll": "Delete Selected",
       "downloadMissingLoras": "Download Missing LoRAs",
       "downloadExamples": "Download Example Images",
+      "downloadMissingExamples": "Download Missing",
+      "reprocessExamples": "Re-process All",
       "clear": "Clear Selection",
       "skipMetadataRefreshCount": "Skip ({count} models)",
       "resumeMetadataRefreshCount": "Resume ({count} models)",
@@ -806,6 +810,8 @@
       "sendToWorkflowReplace": "Send to Workflow (Replace)",
       "openExamples": "Open Examples Folder",
       "downloadExamples": "Download Example Images",
+      "downloadMissingExamples": "Download Missing",
+      "reprocessExamples": "Re-process All",
       "replacePreview": "Replace Preview",
       "setContentRating": "Set Content Rating",
       "moveToFolder": "Move to Folder",
@@ -1548,6 +1554,7 @@
         "empty": "No version history available for this model yet.",
         "error": "Failed to load versions.",
         "missingModelId": "This model is missing a Civitai model id.",
+        "hfGroupInfo": "This is a HuggingFace model group. Open the library to see all versions in the grid.",
         "confirm": {
           "delete": "Delete this version from your library?"
         },
@@ -1751,6 +1758,12 @@
     "checkingMessage": "Please wait while we check for the latest version.",
     "showNotifications": "Show update notifications",
     "latestBadge": "Latest",
+    "latestMain": "Latest main",
+    "channel": "Update Channel",
+    "channels": {
+      "release": "Release",
+      "nightly": "Nightly"
+    },
     "updateProgress": {
       "preparing": "Preparing update...",
       "installing": "Installing update...",
@@ -1771,6 +1784,15 @@
       "warning": "Warning: Nightly builds may contain experimental features and could be unstable.",
       "enable": "Enable Nightly Updates"
     },
+    "channelSwitch": {
+      "nightlyTitle": "Switch to Nightly Channel",
+      "nightlyMessage": "Switching to Nightly will initialize a Git repository and track the latest main branch commits. Updates will be more frequent but may be unstable. You can switch back to Release at any time.",
+      "releaseTitle": "Switch to Release Channel",
+      "releaseMessage": "Switching to Release will checkout the latest stable release tag. You can switch back to Nightly at any time.",
+      "switching": "Switching to {channel} channel...",
+      "completed": "Successfully switched to {channel} channel",
+      "failed": "Failed to switch channel"
+    },
     "banners": {
       "recent": "Recent messages",
       "empty": "No recent banners yet.",

py/metadata_collector/constants.py

@@ -1,5 +1,11 @@
 """Constants used by the metadata collector"""
 
+# Sentinel value for clip_skip to distinguish "unconnected / widget default"
+# from "user wired value 0".  Both ComfyUI CLIPSetLastLayer (-24..-1) and
+# A1111 conventions treat 0 as meaningless for clip skipping, but users may
+# explicitly wire 0 to the overwrite node to express "no clip skip / default".
+CLIP_SKIP_SENTINEL = -25
+
 # Metadata categories
 MODELS = "models"
 PROMPTS = "prompts"
@@ -9,6 +15,14 @@ EMBEDDINGS = "embeddings"
 SIZE = "size"
 IMAGES = "images"
 IS_SAMPLER = "is_sampler"  # New constant to mark sampler nodes
+OVERWRITE = "overwrite"  # Manual metadata overwrite from MetadataOverwriteLM node
+
+# Field names that the MetadataOverwriteLM node and its extractor share
+METADATA_OVERWRITE_FIELDS = (
+    "prompt", "negative_prompt", "seed", "steps", "cfg_scale",
+    "sampler", "scheduler", "model", "loras", "size",
+    "clip_skip", "additional_data",
+)
 
 # Complete list of categories to track
-METADATA_CATEGORIES = [MODELS, PROMPTS, SAMPLING, LORAS, EMBEDDINGS, SIZE, IMAGES]
+METADATA_CATEGORIES = [MODELS, PROMPTS, SAMPLING, LORAS, EMBEDDINGS, SIZE, IMAGES, OVERWRITE]

py/metadata_collector/metadata_hook.py

@@ -83,7 +83,8 @@ class MetadataHook:
                         
                         # Record inputs before execution
                         if node_id is not None:
-                            registry.record_node_execution(node_id, class_type, input_data_all, None)
+                            return_types = getattr(obj, 'RETURN_TYPES', None)
+                            registry.record_node_execution(node_id, class_type, input_data_all, None, return_types=return_types)
                 except Exception as e:
                     logger.error(f"Error collecting metadata (pre-execution): {str(e)}")
             
@@ -114,7 +115,8 @@ class MetadataHook:
                         
                         # Record outputs after execution
                         if node_id is not None:
-                            registry.update_node_execution(node_id, class_type, results)
+                            return_types = getattr(obj, 'RETURN_TYPES', None)
+                            registry.update_node_execution(node_id, class_type, results, return_types=return_types)
                 except Exception as e:
                     logger.error(f"Error collecting metadata (post-execution): {str(e)}")
             
@@ -136,6 +138,9 @@ class MetadataHook:
                 if hasattr(prompt, 'original_prompt'):
                     registry.set_current_prompt(prompt)
 
+                # Store extra_data for accessing full workflow node properties
+                registry.set_extra_data(extra_data)
+
             # Execute the original function
             return original_execute(*args, **kwargs)
 
@@ -163,7 +168,8 @@ class MetadataHook:
                         class_type = obj.__class__.__name__
                         node_id = unique_id
                         if node_id is not None:
-                            registry.record_node_execution(node_id, class_type, input_data_all, None)
+                            return_types = getattr(obj, 'RETURN_TYPES', None)
+                            registry.record_node_execution(node_id, class_type, input_data_all, None, return_types=return_types)
                 except Exception as e:
                     logger.error(f"Error collecting metadata (pre-execution): {str(e)}")
 
@@ -180,7 +186,8 @@ class MetadataHook:
                         class_type = obj.__class__.__name__
                         node_id = unique_id
                         if node_id is not None:
-                            registry.update_node_execution(node_id, class_type, results)
+                            return_types = getattr(obj, 'RETURN_TYPES', None)
+                            registry.update_node_execution(node_id, class_type, results, return_types=return_types)
                 except Exception as e:
                     logger.error(f"Error collecting metadata (post-execution): {str(e)}")
 
@@ -202,6 +209,9 @@ class MetadataHook:
                 if hasattr(prompt, 'original_prompt'):
                     registry.set_current_prompt(prompt)
 
+                # Store extra_data for accessing full workflow node properties
+                registry.set_extra_data(extra_data)
+
             # Execute the original function
             return await original_execute(*args, **kwargs)
 

py/metadata_collector/metadata_processor.py

@@ -1,15 +1,68 @@
 import json
+import logging
 import os
 from .constants import IMAGES
 
 # Check if running in standalone mode
 standalone_mode = os.environ.get("LORA_MANAGER_STANDALONE", "0") == "1" or os.environ.get("HF_HUB_DISABLE_TELEMETRY", "0") == "0"
 
-from .constants import MODELS, PROMPTS, SAMPLING, LORAS, SIZE, IS_SAMPLER
+from .constants import MODELS, PROMPTS, SAMPLING, LORAS, SIZE, IS_SAMPLER, OVERWRITE
+from .node_extractors import NODE_EXTRACTORS
+
+logger = logging.getLogger(__name__)
+
+# Keys that identify metadata hint marks stored in node.properties.lm_marker_role
+_META_MARK_PREFIX = "meta_"
+_MARK_PRIMARY_MODEL = "primary_model"
+_MARK_PRIMARY_SAMPLER = "primary_sampler"
+_MARK_POSITIVE_PROMPT = "positive_prompt"
+_MARK_NEGATIVE_PROMPT = "negative_prompt"
 
 class MetadataProcessor:
     """Process and format collected metadata"""
 
+    @staticmethod
+    def _get_user_marks(metadata):
+        """Scan workflow nodes (from extra_data.extra_pnginfo.workflow) for user-assigned
+        metadata hint marks stored in node.properties.lm_marker_role.
+
+        Returns a dict mapping mark type keys to node IDs.
+        Example: {'primary_model': '42', 'primary_sampler': '17'}
+        """
+        marks: dict[str, str] = {}
+
+        # Primary source: extra_data.extra_pnginfo.workflow.nodes (has full properties)
+        extra_data = metadata.get("extra_data")
+        if extra_data and isinstance(extra_data, dict):
+            extra_pnginfo = extra_data.get("extra_pnginfo", {})
+            if isinstance(extra_pnginfo, dict):
+                workflow = extra_pnginfo.get("workflow", {})
+                nodes = workflow.get("nodes", [])
+                for node in nodes:
+                    node_id = str(node.get("id", ""))
+                    role = node.get("properties", {}).get("lm_marker_role", "")
+                    if role.startswith(_META_MARK_PREFIX):
+                        mark_type = role[len(_META_MARK_PREFIX):]
+                        if mark_type in marks:
+                            logger.warning(
+                                "Duplicate meta hint '%s': node %s (previous: %s), "
+                                "last match wins",
+                                mark_type, node_id, marks[mark_type],
+                            )
+                        marks[mark_type] = node_id
+
+        # Fallback: try prompt.original_prompt (API-only submissions may not have workflow)
+        if not marks:
+            prompt = metadata.get("current_prompt")
+            if prompt and getattr(prompt, "original_prompt", None):
+                for node_id, node_data in prompt.original_prompt.items():
+                    role = node_data.get("properties", {}).get("lm_marker_role", "")
+                    if role.startswith(_META_MARK_PREFIX):
+                        mark_type = role[len(_META_MARK_PREFIX):]
+                        marks[mark_type] = node_id
+
+        return marks
+
     @staticmethod
     def find_primary_sampler(metadata, downstream_id=None):
         """
@@ -471,20 +524,57 @@ class MetadataProcessor:
             "checkpoint": None,
             "loras": "",
             "size": None,
-            "clip_skip": None
+            "clip_skip": None,
+            "additional_data": "",
         }
         
         # Get the prompt object for node relationship tracing
         prompt = metadata.get("current_prompt")
 
-        # Find the primary KSampler node
+        # ---- User marks: override heuristic inference with user-assigned hints ----
-        primary_sampler_id, primary_sampler = MetadataProcessor.find_primary_sampler(metadata, id)
+        user_marks = MetadataProcessor._get_user_marks(metadata)
 
-        # Directly get checkpoint from metadata instead of tracing
+        # Find the primary KSampler node (user mark takes priority)
-        # Pass primary_sampler_id to avoid redundant calculation
+        primary_sampler_id = None
-        checkpoint = MetadataProcessor.find_primary_checkpoint(metadata, id, primary_sampler_id)
+        primary_sampler = None
-        if checkpoint:
+        if _MARK_PRIMARY_SAMPLER in user_marks:
-            params["checkpoint"] = checkpoint
+            marked_id = user_marks[_MARK_PRIMARY_SAMPLER]
+            sampler_data = metadata.get(SAMPLING, {}).get(marked_id)
+            if sampler_data and sampler_data.get(IS_SAMPLER):
+                primary_sampler_id = marked_id
+                primary_sampler = sampler_data
+            else:
+                logger.warning(
+                    "User-marked primary sampler %s has no runtime metadata, "
+                    "falling back to heuristic",
+                    marked_id,
+                )
+        if primary_sampler is None:
+            primary_sampler_id, primary_sampler = MetadataProcessor.find_primary_sampler(metadata, id)
+
+        # Resolve checkpoint / model (user mark takes priority)
+        if _MARK_PRIMARY_MODEL in user_marks:
+            marked_id = user_marks[_MARK_PRIMARY_MODEL]
+            if marked_id in metadata.get(MODELS, {}):
+                params["checkpoint"] = metadata[MODELS][marked_id].get("name")
+            else:
+                extra_data = metadata.get("extra_data")
+                extra_pnginfo = extra_data.get("extra_pnginfo", {}) if extra_data and isinstance(extra_data, dict) else {}
+                workflow = extra_pnginfo.get("workflow", {}) if isinstance(extra_pnginfo, dict) else {}
+                node_type = "unknown"
+                for n in workflow.get("nodes", []):
+                    if str(n.get("id", "")) == marked_id:
+                        node_type = n.get("type", "unknown")
+                        break
+                logger.warning(
+                    "User-marked primary model %s (type=%s, registered=%s) has no runtime metadata, "
+                    "falling back to heuristic",
+                    marked_id, node_type, node_type in NODE_EXTRACTORS,
+                )
+        if params["checkpoint"] is None:
+            checkpoint = MetadataProcessor.find_primary_checkpoint(metadata, id, primary_sampler_id)
+            if checkpoint:
+                params["checkpoint"] = checkpoint
         
         # Check if guidance parameter exists in any sampling node
         for node_id, sampler_info in metadata.get(SAMPLING, {}).items():
@@ -540,6 +630,21 @@ class MetadataProcessor:
                     # For SamplerCustom, handle any additional parameters
                     MetadataProcessor.handle_custom_advanced_sampler(metadata, prompt, primary_sampler_id, params)
 
+            # ---- User marks: override prompts with explicitly tagged nodes ----
+            prompts_data = metadata.get(PROMPTS, {})
+            if _MARK_POSITIVE_PROMPT in user_marks:
+                pos_id = user_marks[_MARK_POSITIVE_PROMPT]
+                if pos_id in prompts_data:
+                    prompt_text = prompts_data[pos_id].get("text") or prompts_data[pos_id].get("positive_text")
+                    if prompt_text:
+                        params["prompt"] = prompt_text
+            if _MARK_NEGATIVE_PROMPT in user_marks:
+                neg_id = user_marks[_MARK_NEGATIVE_PROMPT]
+                if neg_id in prompts_data:
+                    prompt_text = prompts_data[neg_id].get("text") or prompts_data[neg_id].get("negative_text")
+                    if prompt_text:
+                        params["negative_prompt"] = prompt_text
+
             # Size extraction is same for all sampler types
             # Check if the sampler itself has size information (from latent_image)
             if primary_sampler_id in metadata.get(SIZE, {}):
@@ -569,6 +674,25 @@ class MetadataProcessor:
         if params["clip_skip"] is None:
             params["clip_skip"] = "1"
 
+        # ---- Apply manual metadata overwrites ----
+        for overwrite_info in metadata.get(OVERWRITE, {}).values():
+            overwrite_params = overwrite_info.get("parameters", {})
+            for key, value in overwrite_params.items():
+                if key == "clip_skip":
+                    # Accept any value from overwrite node (sentinel -25 already
+                    # filtered upstream).  Needed because falsy check treats 0
+                    # as "not set" even though 0 is a valid wired input here.
+                    params[key] = value
+                elif value:  # truthy check — only overwrite when user provided a real value
+                    params[key] = value
+
+        # Bridge: the overwrite node exposes the field as "model" (more accurate),
+        # but the internal pipeline key remains "checkpoint" for backward compatibility
+        # with A1111 metadata format and downstream consumers.
+        if params.get("model"):
+            params["checkpoint"] = params["model"]
+            del params["model"]
+
         return params
     
     @staticmethod

py/metadata_collector/metadata_registry.py

@@ -1,7 +1,7 @@
 import time
 from nodes import NODE_CLASS_MAPPINGS  # type: ignore
 from .node_extractors import NODE_EXTRACTORS, GenericNodeExtractor
-from .constants import METADATA_CATEGORIES, IMAGES
+from .constants import METADATA_CATEGORIES, IMAGES, OVERWRITE
 
 
 class MetadataRegistry:
@@ -61,6 +61,7 @@ class MetadataRegistry:
             {
                 "execution_order": [],
                 "current_prompt": None,  # Will store the prompt object
+                "extra_data": None,  # Will store the API extra_data for workflow metadata
                 "timestamp": time.time(),
             }
         )
@@ -75,6 +76,11 @@ class MetadataRegistry:
             # Store the prompt in the metadata for later relationship tracing
             self.prompt_metadata[self.current_prompt_id]["current_prompt"] = prompt
 
+    def set_extra_data(self, extra_data):
+        """Store the API extra_data (contains extra_pnginfo.workflow with node properties)"""
+        if self.current_prompt_id and self.current_prompt_id in self.prompt_metadata:
+            self.prompt_metadata[self.current_prompt_id]["extra_data"] = extra_data
+
     def get_metadata(self, prompt_id=None):
         """Get collected metadata for a prompt"""
         key = prompt_id if prompt_id is not None else self.current_prompt_id
@@ -122,20 +128,28 @@ class MetadataRegistry:
             cache_key = f"{node_id}:{class_type}"
 
             # Check if this node type is relevant for metadata collection
-            if class_type in NODE_EXTRACTORS:
+            if class_type in NODE_EXTRACTORS or cache_key in self.node_cache:
                 # Check if we have cached metadata for this node
                 if cache_key in self.node_cache:
                     cached_data = self.node_cache[cache_key]
 
+                    # Detect bypass (mode=4) / mute (mode=2) — these nodes
+                    # were intentionally disabled and should not contribute
+                    # overwrite values from a previous execution's cache.
+                    node_mode = node_data.get("mode", 0)
+                    node_is_disabled = node_mode in (2, 4)
+
                     # Apply cached metadata to the current metadata
                     for category in self.metadata_categories:
+                        if category == OVERWRITE and node_is_disabled:
+                            continue
                         if category in cached_data and node_id in cached_data[category]:
                             if node_id not in metadata[category]:
                                 metadata[category][node_id] = cached_data[category][
                                     node_id
                                 ]
 
-    def record_node_execution(self, node_id, class_type, inputs, outputs):
+    def record_node_execution(self, node_id, class_type, inputs, outputs, return_types=None):
         """Record information about a node's execution"""
         if not self.current_prompt_id:
             return
@@ -158,17 +172,18 @@ class MetadataRegistry:
 
         # Extract node-specific metadata
         extractor = NODE_EXTRACTORS.get(class_type, GenericNodeExtractor)
-        extractor.extract(
+        if extractor is GenericNodeExtractor:
-            node_id,
+            extractor.extract(node_id, processed_inputs, outputs,
-            processed_inputs,
+                              self.prompt_metadata[self.current_prompt_id],
-            outputs,
+                              return_types=return_types)
-            self.prompt_metadata[self.current_prompt_id],
+        else:
-        )
+            extractor.extract(node_id, processed_inputs, outputs,
+                              self.prompt_metadata[self.current_prompt_id])
 
         # Cache this node's metadata
         self._cache_node_metadata(node_id, class_type)
 
-    def update_node_execution(self, node_id, class_type, outputs):
+    def update_node_execution(self, node_id, class_type, outputs, return_types=None):
         """Update node metadata with output information"""
         if not self.current_prompt_id:
             return
@@ -179,9 +194,17 @@ class MetadataRegistry:
         # Use the same extractor to update with outputs
         extractor = NODE_EXTRACTORS.get(class_type, GenericNodeExtractor)
         if hasattr(extractor, "update"):
-            extractor.update(
+            if extractor is GenericNodeExtractor:
-                node_id, processed_outputs, self.prompt_metadata[self.current_prompt_id]
+                extractor.update(
-            )
+                    node_id, processed_outputs,
+                    self.prompt_metadata[self.current_prompt_id],
+                    return_types=return_types,
+                )
+            else:
+                extractor.update(
+                    node_id, processed_outputs,
+                    self.prompt_metadata[self.current_prompt_id],
+                )
 
         # Update the cached metadata for this node
         self._cache_node_metadata(node_id, class_type)

py/metadata_collector/node_extractors.py

@@ -2,7 +2,8 @@ import json
 import os
 import re
 
-from .constants import MODELS, PROMPTS, SAMPLING, LORAS, SIZE, IMAGES, IS_SAMPLER
+from .constants import MODELS, PROMPTS, SAMPLING, LORAS, SIZE, IMAGES, IS_SAMPLER, OVERWRITE
+from .overwrite_utils import collect_overwrite_params
 
 
 def _store_checkpoint_metadata(metadata, node_id, model_name):
@@ -31,10 +32,77 @@ class NodeMetadataExtractor:
         pass
         
 class GenericNodeExtractor(NodeMetadataExtractor):
-    """Default extractor for nodes without specific handling"""
+    """Fallback extractor with type-signature-based detection.
+
+    When a node is not in the NODE_EXTRACTORS registry, the hook layer
+    passes ``return_types`` from ``obj.RETURN_TYPES``:
+
+    * ``MODEL`` output: common input fields (ckpt_name, unet_name, etc.)
+      are checked for a model file name and stored as checkpoint metadata.
+    * ``CONDITIONING`` output: common text input fields are checked for
+      prompt text and stored as prompt metadata.
+    """
+
+    # Input field names that carry a model path in loader-style nodes.
+    _MODEL_NAME_FIELDS = (
+        "ckpt_name", "unet_name", "model_path", "model_name", "gguf_name",
+    )
+
+    # Extensions used by checkpoint_scanner.py — only record values that look
+    # like real model filenames to avoid capturing unrelated string fields.
+    _MODEL_EXTENSIONS = {
+        ".ckpt", ".pt", ".pt2", ".bin", ".pth", ".safetensors", ".pkl", ".sft", ".gguf",
+    }
+
+    # Input field names that may carry prompt text in encoder-style nodes.
+    _TEXT_FIELDS = ("text", "clip_l", "t5xxl", "prompt", "positive", "negative")
+
     @staticmethod
-    def extract(node_id, inputs, outputs, metadata):
+    def extract(node_id, inputs, outputs, metadata, return_types=None):
-        pass
+        if return_types is None:
+            return
+
+        # — MODEL loader detection (checkpoint / UNET / GGUF) —
+        if "MODEL" in return_types or any("MODEL" in str(t) for t in return_types):
+            for field in GenericNodeExtractor._MODEL_NAME_FIELDS:
+                val = inputs.get(field)
+                if val and isinstance(val, str) and val.strip():
+                    name = val.strip()
+                    if not any(name.lower().endswith(ext) for ext in GenericNodeExtractor._MODEL_EXTENSIONS):
+                        continue
+                    _store_checkpoint_metadata(metadata, node_id, name)
+                    return
+
+        # — CONDITIONING encoder detection (CLIPTextEncode, Flux, custom) —
+        if "CONDITIONING" in return_types or any("CONDITIONING" in str(t) for t in return_types):
+            text = None
+            for field in GenericNodeExtractor._TEXT_FIELDS:
+                val = inputs.get(field)
+                if val and isinstance(val, str) and val.strip():
+                    text = val.strip()
+                    break
+            if text:
+                prompt_data = metadata.setdefault(PROMPTS, {})
+                prompt_data[node_id] = {
+                    "text": text,
+                    "node_id": node_id,
+                }
+
+    @staticmethod
+    def update(node_id, outputs, metadata, return_types=None):
+        if return_types is None:
+            return
+        if "CONDITIONING" not in return_types and not any(
+            "CONDITIONING" in str(t) for t in return_types
+        ):
+            return
+        if node_id not in metadata.get(PROMPTS, {}):
+            return
+        if outputs and isinstance(outputs, list) and len(outputs) > 0:
+            if isinstance(outputs[0], tuple) and len(outputs[0]) > 0:
+                cond = outputs[0][0]
+                if cond is not None:
+                    metadata[PROMPTS][node_id]["conditioning"] = cond
 
 class CheckpointLoaderExtractor(NodeMetadataExtractor):
     @staticmethod
@@ -1154,6 +1222,28 @@ class CR_ApplyControlNetStackExtractor(NodeMetadataExtractor):
                 metadata[PROMPTS][node_id]["positive_encoded"] = transformed_positive
                 metadata[PROMPTS][node_id]["negative_encoded"] = transformed_negative
 
+class MetadataOverwriteExtractor(NodeMetadataExtractor):
+    """Extract manually specified metadata from MetadataOverwriteLM node.
+
+    Stores truthy input values under the OVERWRITE category so that
+    extract_generation_params can merge them over the inferred params.
+    """
+
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs:
+            return
+
+        overwrite_params = collect_overwrite_params(inputs)
+
+        if overwrite_params:
+            metadata.setdefault(OVERWRITE, {})
+            metadata[OVERWRITE][node_id] = {
+                "parameters": overwrite_params,
+                "node_id": node_id,
+            }
+
+
 # Registry of node-specific extractors
 # Keys are node class names
 NODE_EXTRACTORS = {
@@ -1221,5 +1311,7 @@ NODE_EXTRACTORS = {
     "CFGGuider": CFGGuiderExtractor,            # Add CFGGuider
     # Image
     "VAEDecode": VAEDecodeExtractor,  # Added VAEDecode extractor
+    # Metadata overwrite
+    "MetadataOverwriteLM": MetadataOverwriteExtractor,
     # Add other nodes as needed
 }

py/metadata_collector/overwrite_utils.py

@@ -0,0 +1,42 @@
+"""Shared helpers for Metadata Overwrite node metadata collection.
+
+Used by both the MetadataOverwriteLM node (execution time) and the
+MetadataOverwriteExtractor (hook time) so the conversion/filtering logic
+cannot drift between the two paths.
+"""
+
+import logging
+from typing import Any, Dict
+
+from ..utils.utils import model_patcher_to_name
+from .constants import CLIP_SKIP_SENTINEL, METADATA_OVERWRITE_FIELDS
+
+logger = logging.getLogger(__name__)
+
+
+def collect_overwrite_params(values: Dict[str, Any]) -> Dict[str, Any]:
+    """Convert node input values into non-default overwrite parameters.
+
+    For most fields, a falsy value (empty string, 0) means "not set" and is
+    skipped.  clip_skip uses a dedicated sentinel (-25) so that a wired value
+    of 0 is preserved.  The ``model`` field accepts either a manual string or
+    a wired MODEL (ModelPatcher) connection; in the latter case the source
+    model name is extracted from the patcher's ``cached_patcher_init`` and
+    stored as a ComfyUI-style relative path.
+    """
+    result: Dict[str, Any] = {}
+    for key in METADATA_OVERWRITE_FIELDS:
+        value = values.get(key)
+        if key == "model" and not isinstance(value, str):
+            value = model_patcher_to_name(value)
+            if value is None:
+                logger.warning(
+                    "Could not extract model name from wired MODEL input "
+                    "(no cached_patcher_init); model metadata overwrite skipped"
+                )
+        if key == "clip_skip":
+            if value != CLIP_SKIP_SENTINEL:
+                result[key] = value
+        elif value:
+            result[key] = value
+    return result

py/nodes/create_hook_lora.py

@@ -0,0 +1,117 @@
+"""Create Hook LoRA (LoraManager) — multi-LoRA hook node compatible with ComfyUI's built-in hook pipeline.
+
+Produces ``("HOOKS",)`` output that chains seamlessly with downstream hook consumers
+(ConditioningSetProperties, SetHookKeyframes, CombineHooks, SetClipHooks, etc.).
+"""
+
+from __future__ import annotations
+
+import logging
+import os
+
+from ..utils.utils import get_lora_info_absolute
+from .utils import (
+    FlexibleOptionalInputType,
+    any_type,
+    apply_lora_syntax_format,
+    get_loras_list,
+)
+
+logger = logging.getLogger(__name__)
+
+
+class CreateHookLoraLM:
+    NAME = "Create Hook LoRA (LoraManager)"
+    CATEGORY = "Lora Manager/hooks"
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        return {
+            "required": {
+                "text": (
+                    "AUTOCOMPLETE_TEXT_LORAS",
+                    {
+                        "placeholder": "Search LoRAs to add...",
+                        "tooltip": (
+                            "Search and select LoRAs. Each LoRA gets its own "
+                            "model/clip strength. Hooks chain with prev_hooks."
+                        ),
+                    },
+                ),
+            },
+            "optional": FlexibleOptionalInputType(any_type),
+        }
+
+    RETURN_TYPES = ("HOOKS", "STRING", "STRING")
+    RETURN_NAMES = ("HOOKS", "trigger_words", "active_loras")
+    FUNCTION = "create_hook"
+
+    def create_hook(self, text: str, **kwargs):
+        """Create a HookGroup from the selected LoRAs, chained with prev_hooks.
+
+        Each active LoRA from the widget is loaded and wrapped in a WeightHook
+        via :func:`comfy.hooks.create_hook_lora`.  All hooks are combined into a
+        single group and returned alongside trigger words and a human-readable
+        summary of the active LoRAs.
+        """
+        del text  # used by the frontend widget only
+
+        # Lazy imports: comfy is not available in CI/test environment at module level
+        import comfy.hooks  # type: ignore  # noqa: C0415
+        import comfy.utils  # type: ignore  # noqa: C0415
+
+        prev_hooks: comfy.hooks.HookGroup | None = kwargs.get("prev_hooks")
+
+        hook_group = prev_hooks.clone() if prev_hooks is not None else comfy.hooks.HookGroup()
+
+        all_trigger_words: list[str] = []
+        active_loras: list[tuple[str, float, float]] = []
+
+        for lora in get_loras_list(kwargs):
+            if not lora.get("active", False):
+                continue
+
+            lora_name = apply_lora_syntax_format(lora["name"])
+            model_strength = float(lora["strength"])
+            clip_strength = float(lora.get("clipStrength", model_strength))
+
+            # Skip useless no-op entries (both strengths are zero)
+            if model_strength == 0.0 and clip_strength == 0.0:
+                continue
+
+            lora_path, trigger_words = get_lora_info_absolute(lora_name)
+            if not lora_path or not os.path.isfile(lora_path):
+                logger.warning("LoRA '%s' not found — skipping", lora_name)
+                continue
+
+            try:
+                lora_weights = comfy.utils.load_torch_file(lora_path, safe_load=True)
+
+                lora_hooks = comfy.hooks.create_hook_lora(
+                    lora=lora_weights,
+                    strength_model=model_strength,
+                    strength_clip=clip_strength,
+                )
+            except Exception:
+                logger.exception("Failed to load LoRA '%s' — skipping", lora_name)
+                continue
+            hook_group = hook_group.clone_and_combine(lora_hooks)
+
+            active_loras.append((lora_name, model_strength, clip_strength))
+            all_trigger_words.extend(trigger_words)
+
+        # Format trigger words (group mode separator)
+        trigger_words_text = ",, ".join(all_trigger_words) if all_trigger_words else ""
+
+        # Format active LoRAs summary
+        formatted_loras = []
+        for name, model_s, clip_s in active_loras:
+            if abs(model_s - clip_s) > 0.001:
+                formatted_loras.append(
+                    f"<lora:{name}:{model_s}:{clip_s}>"
+                )
+            else:
+                formatted_loras.append(f"<lora:{name}:{model_s}>")
+        active_loras_text = " ".join(formatted_loras)
+
+        return (hook_group, trigger_words_text, active_loras_text)

py/nodes/lora_stack_combiner.py

@@ -1,26 +1,102 @@
+from __future__ import annotations
+
+import inspect
+import re
+from typing import Any
+
+_STACK_INPUT_PATTERN = re.compile(r"^lora_stack(?:_([ab])|(\d+))$")
+
+
+def _is_stack_input(name: str) -> bool:
+    return bool(_STACK_INPUT_PATTERN.match(name))
+
+
+def _stack_slot_number(name: str) -> int:
+    """Numeric slot used to order stack inputs; legacy a/b map to 1/2."""
+    match = _STACK_INPUT_PATTERN.match(name)
+    if not match:
+        return -1
+    letter, digits = match.group(1), match.group(2)
+    if digits is not None:
+        return int(digits)
+    return 1 if letter == "a" else 2
+
+
+class _LoraStackOptionalInputs:
+    """Lookup that preserves explicit optional inputs and dynamic lora_stack slots."""
+
+    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_stack_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_stack_input(key):
+            return (
+                "LORA_STACK",
+                {
+                    "tooltip": "A LoRA stack to combine. Connect to add more inputs.",
+                },
+            )
+        raise KeyError(key)
+
+
 class LoraStackCombinerLM:
     NAME = "Lora Stack Combiner (LoraManager)"
     CATEGORY = "Lora Manager/stackers"
+    DESCRIPTION = (
+        "Combines multiple LoRA stacks into a single stack. "
+        "Supports dynamic inputs: connect a stack to add more inputs."
+    )
 
     @classmethod
     def INPUT_TYPES(cls):
+        optional_inputs: dict[str, tuple[str, dict[str, Any]]] = {
+            "lora_stack1": (
+                "LORA_STACK",
+                {
+                    "tooltip": "A LoRA stack to combine. Connect to add more inputs.",
+                },
+            ),
+            "lora_stack2": (
+                "LORA_STACK",
+                {
+                    "tooltip": "A LoRA stack to combine. Connect to add more inputs.",
+                },
+            ),
+        }
+
+        stack = inspect.stack()
+        if len(stack) > 2 and stack[2].function == "get_input_info":
+            optional_inputs = _LoraStackOptionalInputs(optional_inputs)  # type: ignore[assignment]
+
         return {
-            "required": {
+            "required": {},
-                "lora_stack_a": ("LORA_STACK",),
+            "optional": optional_inputs,
-                "lora_stack_b": ("LORA_STACK",),
-            },
         }
 
     RETURN_TYPES = ("LORA_STACK",)
     RETURN_NAMES = ("LORA_STACK",)
     FUNCTION = "combine_stacks"
 
-    def combine_stacks(self, lora_stack_a, lora_stack_b):
+    def combine_stacks(self, lora_stack1=None, lora_stack2=None, **kwargs):
-        combined_stack = []
+        stacks = {
+            "lora_stack1": lora_stack1,
+            "lora_stack2": lora_stack2,
+        }
+        for key, value in kwargs.items():
+            if _is_stack_input(key) and value is not None:
+                stacks[key] = value
 
-        if lora_stack_a:
+        combined_stack = []
-            combined_stack.extend(lora_stack_a)
+        for key in sorted(stacks, key=_stack_slot_number):
-        if lora_stack_b:
+            stack = stacks[key]
-            combined_stack.extend(lora_stack_b)
+            if stack:
+                combined_stack.extend(stack)
 
         return (combined_stack,)

py/nodes/metadata_overwrite.py

@@ -0,0 +1,169 @@
+"""Metadata Overwrite node — allows users to manually specify generation parameters
+that override the automatically collected/inferred metadata.
+
+Most inputs have falsy defaults (empty string / 0) which are skipped.
+clip_skip uses a sentinel default (-25) so that a wired value of 0 is
+preserved — both ComfyUI and A1111 conventions have no meaningful 0 value,
+but users may wire 0 to express "no clip skip / default".
+"""
+
+from typing import Any
+
+from ..metadata_collector.constants import CLIP_SKIP_SENTINEL as _CLIP_SKIP_SENTINEL
+from ..metadata_collector.overwrite_utils import collect_overwrite_params
+
+
+class MetadataOverwriteLM:
+    NAME = "Metadata Overwrite (LoraManager)"
+    CATEGORY = "Lora Manager/utils"
+    DESCRIPTION = (
+        "Manually specify generation parameters to override automatically collected "
+        "metadata. Only filled/connected inputs will take effect — empty defaults "
+        "are ignored."
+    )
+
+    @classmethod
+    def INPUT_TYPES(cls) -> dict[str, Any]:
+        return {
+            "optional": {
+                "prompt": (
+                    "STRING",
+                    {
+                        "default": "",
+                        "multiline": True,
+                        "tooltip": "Positive prompt. Only overwrites when non-empty.",
+                    },
+                ),
+                "negative_prompt": (
+                    "STRING",
+                    {
+                        "default": "",
+                        "multiline": True,
+                        "tooltip": "Negative prompt. Only overwrites when non-empty.",
+                    },
+                ),
+                "seed": (
+                    "INT",
+                    {
+                        "default": 0,
+                        "min": 0,
+                        "max": 0xFFFFFFFFFFFFFFFF,
+                        "control_after_generate": False,
+                        "tooltip": "Seed value. Only overwrites when > 0.",
+                    },
+                ),
+                "steps": (
+                    "INT",
+                    {
+                        "default": 0,
+                        "min": 0,
+                        "max": 10000,
+                        "tooltip": "Number of steps. Only overwrites when > 0.",
+                    },
+                ),
+                "cfg_scale": (
+                    "FLOAT",
+                    {
+                        "default": 0.0,
+                        "min": 0.0,
+                        "max": 100.0,
+                        "tooltip": "CFG scale. Only overwrites when > 0.",
+                    },
+                ),
+                "sampler": (
+                    "STRING",
+                    {
+                        "default": "",
+                        "tooltip": "Sampler name. Only overwrites when non-empty.",
+                    },
+                ),
+                "scheduler": (
+                    "STRING",
+                    {
+                        "default": "",
+                        "tooltip": "Scheduler name. Only overwrites when non-empty.",
+                    },
+                ),
+                "model": (
+                    "STRING,MODEL",
+                    {
+                        "default": "",
+                        "widgetType": "STRING",
+                        "tooltip": (
+                            "The checkpoint or diffusion model (UNet) used "
+                            "for generation. Fill in the name manually or "
+                            "connect a MODEL output — the model name is then "
+                            "extracted automatically. Only overwrites when "
+                            "non-empty."
+                        ),
+                    },
+                ),
+                "loras": (
+                    "STRING",
+                    {
+                        "default": "",
+                        "multiline": True,
+                        "tooltip": (
+                            "LoRA syntax, e.g. <lora:name:strength> "
+                            "or <lora:name:model_strength:clip_strength>, "
+                            "separated by spaces. Only overwrites when non-empty."
+                        ),
+                    },
+                ),
+                "size": (
+                    "STRING",
+                    {
+                        "default": "",
+                        "tooltip": (
+                            "Image size in WIDTHxHEIGHT format (e.g. 512x768). "
+                            "Only overwrites when non-empty."
+                        ),
+                    },
+                ),
+                "clip_skip": (
+                    "INT",
+                    {
+                        "default": _CLIP_SKIP_SENTINEL,
+                        "min": -25,
+                        "max": 24,
+                        "tooltip": (
+                            "Clip skip (ComfyUI: -24..-1, A1111: 1+). "
+                            "Default -25 means not set — any other value "
+                            "overwrites."
+                        ),
+                    },
+                ),
+                "additional_data": (
+                    "STRING",
+                    {
+                        "default": "",
+                        "multiline": True,
+                        "tooltip": (
+                            "Additional data to embed in the image metadata. "
+                            "Inserted between Clip skip and Model hash in the "
+                            "A1111-compatible parameters string. "
+                            'Example: "Copyright": "Some license info"'
+                        ),
+                    },
+                ),
+            },
+        }
+
+    RETURN_TYPES = ("METADATA",)
+    RETURN_NAMES = ("metadata",)
+    FUNCTION = "collect_metadata"
+    OUTPUT_NODE = True
+
+    def collect_metadata(self, **kwargs: Any) -> tuple[dict[str, Any]]:
+        """Collect non-default input values into a metadata dict.
+
+        For most fields, a falsy value (empty string, 0) means "not set"
+        and is skipped.  clip_skip uses a dedicated sentinel (-25) so that
+        a wired value of 0 is preserved and reaches the metadata pipeline.
+
+        The ``model`` field accepts either a manual string or a wired MODEL
+        (ModelPatcher) connection; in the latter case the underlying model
+        name is extracted from the patcher's ``cached_patcher_init`` and
+        stored as a ComfyUI-style relative path.
+        """
+        return (collect_overwrite_params(kwargs),)

py/nodes/save_image.py

@@ -16,6 +16,156 @@ from PIL import Image, PngImagePlugin
 import piexif
 import logging
 
+# Civitai-compatible sampler name mapping: ComfyUI internal → A1111 display name
+CIVITAI_SAMPLER_MAP = {
+    "euler": "Euler",
+    "euler_ancestral": "Euler a",
+    "lms": "LMS",
+    "heun": "Heun",
+    "dpm_2": "DPM2",
+    "dpm_2_ancestral": "DPM2 a",
+    "dpmpp_2s_ancestral": "DPM++ 2S a",
+    "dpmpp_2m": "DPM++ 2M",
+    "dpmpp_sde": "DPM++ SDE",
+    "dpmpp_sde_gpu": "DPM++ SDE",
+    "dpmpp_2m_sde": "DPM++ 2M SDE",
+    "dpmpp_2m_sde_gpu": "DPM++ 2M SDE",
+    "dpmpp_3m_sde": "DPM++ 3M SDE",
+    "dpm_fast": "DPM fast",
+    "dpm_adaptive": "DPM adaptive",
+    "ddim": "DDIM",
+    "plms": "PLMS",
+    "uni_pc_bh2": "UniPC",
+    "uni_pc": "UniPC",
+    "lcm": "LCM",
+}
+
+# Base model display name → AIR URN slug
+# Sourced from civitai source: src/shared/constants/basemodel.constants.ts
+BASE_MODEL_AIR_SLUG = {
+    # Stable Diffusion family
+    "SD 1.4": "sd1",
+    "SD 1.5": "sd1",
+    "SD 1.5 LCM": "sd1",
+    "SD 1.5 Hyper": "sd1",
+    "SD 2.0": "sd2",
+    "SD 2.0 768": "sd2",
+    "SD 2.1": "sd2",
+    "SD 2.1 768": "sd2",
+    "SD 2.1 Unclip": "sd2",
+    "SD 3.0": "sd3",
+    "SD 3.5": "sd35",
+    "SD 3.5 Large": "sd35",
+    "SD 3.5 Large Turbo": "sd35",
+    "SD 3.5 Medium": "sd35",
+    "SDXL 0.9": "sdxl",
+    "SDXL 1.0": "sdxl",
+    "SDXL 1.0 LCM": "sdxl",
+    "SDXL Lightning": "sdxl",
+    "SDXL Hyper": "sdxl",
+    "SDXL Turbo": "sdxl",
+    "SDXL Distilled": "sdxldistilled",
+    "Stable Cascade": "scascade",
+    "Stable Video Diffusion": "svd",
+    "SVD": "svd",
+    "SVD XT": "svdxt",
+
+    # SDXL community fine-tunes
+    "Pony": "pony",
+    "Pony Diffusion": "pony",
+    "Illustrious": "illustrious",
+    "NoobAI": "noobai",
+    "Animagine": "illustrious",
+
+    # Flux family
+    "Flux.1": "flux1",
+    "Flux.1 D": "flux1",
+    "Flux.1 S": "flux1",
+    "Flux.1 Krea": "fluxkrea",
+    "Flux.1 Kontext": "flux1kontext",
+    "Flux.2": "flux2",
+    "Flux.2 D": "flux2",
+    "Flux.2 Klein 9B": "flux2klein_9b",
+    "Flux.2 Klein 9B Base": "flux2klein_9b_base",
+    "Flux.2 Klein 4B": "flux2klein_4b",
+    "Flux.2 Klein 4B Base": "flux2klein_4b_base",
+
+    # Other image models (sorted alphabetically)
+    "AuraFlow": "auraflow",
+    "Chroma": "chroma",
+    "HiDream": "hidream",
+    "HiDream-O1": "hidream-o1",
+    "Hunyuan DiT": "hydit1",
+    "Hunyuan Video": "hyv1",
+    "Kolors": "kolors",
+    "Lumina": "lumina",
+    "Mochi": "mochi",
+    "ODOR": "odor",
+    "PixArt Alpha": "pixarta",
+    "PixArt Sigma": "pixarte",
+    "Playground v2": "playgroundv2",
+    "Playground v2.5": "playgroundv2",
+    "Pony Diffusion V7": "ponyv7",
+
+    # Video models
+    "CogVideoX": "cogvideox",
+    "LTX Video": "ltxv",
+    "LTX Video 2": "ltxv2",
+    "LTX Video 2.3": "ltxv23",
+    "Wan Video": "wanvideo",
+    "Wan Video 1.3B T2V": "wanvideo_13b_t2v",
+    "Wan Video 14B T2V": "wanvideo_14b_t2v",
+    "Wan Video 14B I2V 480p": "wanvideo_14b_i2v_480p",
+    "Wan Video 14B I2V 720p": "wanvideo_14b_i2v_720p",
+
+    # Third-party / proprietary image models
+    "Boogu": "boogu",
+    "Ernie": "ernie",
+    "Grok": "grok",
+    "HappyHorse": "happyhorse",
+    "Ideogram": "ideogram",
+    "Ideogram 4.0": "ideogram",
+    "Imagen": "imagen4",
+    "Imagen 4": "imagen4",
+    "Krea": "krea2",
+    "Krea 2": "krea2",
+    "Lens": "lens",
+    "MAI": "mai",
+    "Nano Banana": "nanobanana",
+    "OpenAI": "openai",
+    "Reve": "reve",
+    "Reve 2": "reve",
+    "Reve 2.1": "reve",
+    "Seedream": "seedream",
+    "Sora": "sora2",
+    "Sora 2": "sora2",
+    "Veo": "veo3",
+    "Veo 2": "veo3",
+    "Veo 3": "veo3",
+    "ZImageTurbo": "zimageturbo",
+    "ZImageBase": "zimagebase",
+    "ZImage": "zimagebase",
+
+    # Third-party video models
+    "Hailuo by MiniMax": "minimax",
+    "Haiper": "haiper",
+    "Kling": "kling",
+    "Lightricks": "lightricks",
+    "Seedance": "seedance",
+    "Vidu": "vidu",
+
+    # Qwen family
+    "Qwen": "qwen",
+    "Qwen 2": "qwen2",
+
+    # Anima
+    "Anima": "anima",
+
+    # Special
+    "Upscaler": "upscaler",
+    "Other": "other",
+}
+
 logger = logging.getLogger(__name__)
 
 
@@ -70,11 +220,29 @@ class SaveImageLM:
                         "tooltip": "Compression quality for JPEG and lossy WebP formats (1-100). Higher values mean better quality but larger files.",
                     },
                 ),
+                "webp_method": (
+                    "INT",
+                    {
+                        "default": 6,
+                        "min": 0,
+                        "max": 6,
+                        "tooltip": "WebP compression method (0-6). 0=fastest/largest, 6=slowest/smallest. Only applies when file_format is 'webp'.",
+                    },
+                ),
+                "jpeg_subsampling": (
+                    "INT",
+                    {
+                        "default": 0,
+                        "min": 0,
+                        "max": 2,
+                        "tooltip": "JPEG chroma subsampling level. 0=4:4:4 (best quality), 1=4:2:2, 2=4:2:0 (smallest files). Only applies when file_format is 'jpeg'.",
+                    },
+                ),
                 "embed_workflow": (
                     "BOOLEAN",
                     {
                         "default": False,
-                        "tooltip": "Embeds the complete workflow data into the image metadata. Only works with PNG and WebP formats.",
+                        "tooltip": "When enabled, saved images store the complete workflow. Drag the image back into ComfyUI to restore the original node graph. PNG and WebP only.",
                     },
                 ),
                 "save_with_metadata": (
@@ -142,148 +310,194 @@ class SaveImageLM:
 
         return None
 
-    def format_metadata(self, metadata_dict):
+    def _resolve_model_cache_entry(self, scanner_type: str, name: str):
-        """Format metadata in the requested format similar to userComment example"""
+        """Resolve model hash, civitai metadata, and base_model from scanner cache.
-        if not metadata_dict:
+        Returns (hash_str, civitai_dict, base_model_str). All values are empty defaults when not found."""
-            return ""
+        scanner = ServiceRegistry.get_service_sync(scanner_type)
+        if scanner is None or not name:
+            return "", {}, ""
 
-        # Helper function to only add parameter if value is not None
+        entry = self._get_cached_model_by_name(scanner, name)
-        def add_param_if_not_none(param_list, label, value):
+        if entry is None:
-            if value is not None:
+            basename = os.path.splitext(os.path.basename(name))[0]
-                param_list.append(f"{label}: {value}")
+            hash_val = scanner.get_hash_by_filename(basename)
+            return (hash_val or "").lower(), {}, ""
+
+        hash_val = (entry.get("sha256") or "").lower()
+        civitai = entry.get("civitai") or {}
+        base_model = entry.get("base_model") or ""
+        return hash_val, civitai, base_model
+
+    @staticmethod
+    def _get_civitai_sampler_name(sampler_name: str, scheduler: str) -> str:
+        if sampler_name in CIVITAI_SAMPLER_MAP:
+            civitai_name = CIVITAI_SAMPLER_MAP[sampler_name]
+            if scheduler == "karras":
+                civitai_name += " Karras"
+            elif scheduler == "exponential":
+                civitai_name += " Exponential"
+            return civitai_name
+        else:
+            if scheduler and scheduler != "normal":
+                return f"{sampler_name}_{scheduler}"
+            return sampler_name
+
+    @staticmethod
+    def _build_air_string(base_model: str, model_type: str, model_id: int, version_id: int) -> str:
+        slug = BASE_MODEL_AIR_SLUG.get(base_model, "other")
+        type_lower = model_type.lower() if model_type else "other"
+        return f"urn:air:{slug}:{type_lower}:civitai:{model_id}@{version_id}"
+
+    def format_metadata(self, metadata_dict: dict) -> str:
+        """Format metadata as A1111-compatible parameters string with Hashes JSON and Civitai resources."""
+        if not metadata_dict: return ""
 
-        # Extract the prompt and negative prompt
         prompt = metadata_dict.get("prompt", "")
         negative_prompt = metadata_dict.get("negative_prompt", "")
-
+        steps = metadata_dict.get("steps")
-        # Extract loras from the prompt if present
+        cfg = metadata_dict.get("guidance")
+        if cfg is None:
+            cfg = metadata_dict.get("cfg_scale")
+        if cfg is None:
+            cfg = metadata_dict.get("cfg")
+        seed = metadata_dict.get("seed")
+        size = metadata_dict.get("size")
+        sampler = metadata_dict.get("sampler") or ""
+        scheduler = metadata_dict.get("scheduler") or "normal"
+        checkpoint = metadata_dict.get("checkpoint") or ""
         loras_text = metadata_dict.get("loras", "")
-        lora_hashes = {}
+        clip_skip = metadata_dict.get("clip_skip")
 
-        # If loras are found, add them on a new line after the prompt
+        # Parse LoRA entries from <lora:name:strength> format
+        lora_entries: list[tuple[str, float]] = []
         if loras_text:
-            prompt_with_loras = f"{prompt}\n{loras_text}"
+            for match in re.findall(r"<lora:([^:]+):([^>]+)>", loras_text):
+                lora_name, strength_str = match
+                try:
+                    strength = float(strength_str)
+                except (ValueError, TypeError):
+                    strength = 1.0
+                lora_entries.append((lora_name, strength))
 
-            # Extract lora names from the format <lora:name:strength>
+        # Resolve checkpoint hash and Civitai data from local cache
-            lora_matches = re.findall(r"<lora:([^:]+):([^>]+)>", loras_text)
+        ckpt_hash, ckpt_civitai, ckpt_base_model = "", {}, ""
+        ckpt_display_name = ""
+        if checkpoint:
+            ckpt_hash, ckpt_civitai, ckpt_base_model = self._resolve_model_cache_entry(
+                "checkpoint_scanner", checkpoint
+            )
+            ckpt_display_name = os.path.splitext(os.path.basename(checkpoint))[0]
 
-            # Get hash for each lora
+        # Resolve LoRA hash and Civitai data from local cache
-            for lora_name, strength in lora_matches:
+        loras_data: list[dict] = []
-                hash_value = self.get_lora_hash(lora_name)
+        for lora_name, strength in lora_entries:
-                if hash_value:
+            lora_hash, lora_civitai, lora_base_model = self._resolve_model_cache_entry(
-                    lora_hashes[lora_name] = hash_value
+                "lora_scanner", lora_name
-        else:
+            )
-            prompt_with_loras = prompt
+            loras_data.append({
+                "name": lora_name,
+                "strength": strength,
+                "hash": lora_hash,
+                "civitai": lora_civitai,
+                "base_model": lora_base_model,
+            })
 
-        # Format the first part (prompt and loras)
+        # Build Hashes JSON (A1111 / Civitai standard format)
-        metadata_parts = [prompt_with_loras]
+        hashes: dict[str, str] = {}
+        if ckpt_hash:
+            hashes["model"] = ckpt_hash[:10].upper()
+        for lora in loras_data:
+            if lora["hash"]:
+                hashes[f"LORA:{lora['name']}"] = lora["hash"][:10].upper()
 
-        # Add negative prompt
+        # Build Civitai resources JSON array
+        civitai_resources: list[dict] = []
+        if ckpt_civitai.get("id", 0) > 0:
+            ckpt_resource: dict = {}
+            ckpt_type = (ckpt_civitai.get("model") or {}).get("type", "Checkpoint")
+            model_id = ckpt_civitai.get("modelId", 0)
+            version_id = ckpt_civitai.get("id", 0)
+            if model_id and version_id:
+                ckpt_resource["air"] = self._build_air_string(
+                    ckpt_base_model, ckpt_type, int(model_id), int(version_id)
+                )
+            elif version_id:
+                ckpt_resource["modelVersionId"] = int(version_id)
+            if ckpt_civitai.get("name"):
+                ckpt_resource["versionName"] = ckpt_civitai["name"]
+            if ckpt_resource:
+                civitai_resources.append(ckpt_resource)
+
+        for lora in loras_data:
+            lora_civitai = lora["civitai"]
+            if not lora_civitai or lora_civitai.get("id", 0) <= 0:
+                continue
+            lora_resource: dict = {"weight": lora["strength"]}
+            lora_type = (lora_civitai.get("model") or {}).get("type", "LORA")
+            model_id = lora_civitai.get("modelId", 0)
+            version_id = lora_civitai.get("id", 0)
+            if model_id and version_id:
+                lora_resource["air"] = self._build_air_string(
+                    lora["base_model"], lora_type, int(model_id), int(version_id)
+                )
+            elif version_id:
+                lora_resource["modelVersionId"] = int(version_id)
+            if lora_civitai.get("name"):
+                lora_resource["versionName"] = lora_civitai["name"]
+            civitai_resources.append(lora_resource)
+
+        sampler_name = CIVITAI_SAMPLER_MAP.get(sampler, sampler) if sampler else None
+
+        scheduler_mapping = {
+            "normal": "Normal",
+            "karras": "Karras",
+            "exponential": "Exponential",
+            "sgm_uniform": "SGM Uniform",
+            "sgm_quadratic": "SGM Quadratic",
+        }
+        scheduler_name = scheduler_mapping.get(scheduler, scheduler) if scheduler else None
+
+        # Build output lines
+        lines = [prompt] if prompt else [""]
         if negative_prompt:
-            metadata_parts.append(f"Negative prompt: {negative_prompt}")
+            lines.append(f"Negative prompt: {negative_prompt}")
 
-        # Format the second part (generation parameters)
+        params: list[str] = []
-        params = []
+        if steps is not None:
-
+            params.append(f"Steps: {steps}")
-        # Add standard parameters in the correct order
-        if "steps" in metadata_dict:
-            add_param_if_not_none(params, "Steps", metadata_dict.get("steps"))
-
-        # Combine sampler and scheduler information
-        sampler_name = None
-        scheduler_name = None
-
-        if "sampler" in metadata_dict:
-            sampler = metadata_dict.get("sampler")
-            # Convert ComfyUI sampler names to user-friendly names
-            sampler_mapping = {
-                "euler": "Euler",
-                "euler_ancestral": "Euler a",
-                "dpm_2": "DPM2",
-                "dpm_2_ancestral": "DPM2 a",
-                "heun": "Heun",
-                "dpm_fast": "DPM fast",
-                "dpm_adaptive": "DPM adaptive",
-                "lms": "LMS",
-                "dpmpp_2s_ancestral": "DPM++ 2S a",
-                "dpmpp_sde": "DPM++ SDE",
-                "dpmpp_sde_gpu": "DPM++ SDE",
-                "dpmpp_2m": "DPM++ 2M",
-                "dpmpp_2m_sde": "DPM++ 2M SDE",
-                "dpmpp_2m_sde_gpu": "DPM++ 2M SDE",
-                "ddim": "DDIM",
-            }
-            sampler_name = sampler_mapping.get(sampler, sampler)
-
-        if "scheduler" in metadata_dict:
-            scheduler = metadata_dict.get("scheduler")
-            scheduler_mapping = {
-                "normal": "Simple",
-                "karras": "Karras",
-                "exponential": "Exponential",
-                "sgm_uniform": "SGM Uniform",
-                "sgm_quadratic": "SGM Quadratic",
-            }
-            scheduler_name = scheduler_mapping.get(scheduler, scheduler)
-
-        # Add combined sampler and scheduler information
         if sampler_name:
             if scheduler_name:
                 params.append(f"Sampler: {sampler_name} {scheduler_name}")
             else:
                 params.append(f"Sampler: {sampler_name}")
+        if cfg is not None:
+            params.append(f"CFG scale: {cfg}")
+        if seed is not None:
+            params.append(f"Seed: {seed}")
+        if size:
+            params.append(f"Size: {size}")
+        if clip_skip is not None:
+            try:
+                params.append(f"Clip skip: {abs(int(clip_skip))}")
+            except (ValueError, TypeError):
+                pass
+        additional_data = metadata_dict.get("additional_data", "")
+        if additional_data:
+            params.append(additional_data)
+        if ckpt_hash:
+            params.append(f"Model hash: {ckpt_hash[:10].upper()}")
+        if ckpt_display_name:
+            params.append(f"Model: {ckpt_display_name}")
+        if hashes:
+            params.append(f"Hashes: {json.dumps(hashes, separators=(',', ':'))}")
+        params.append("Version: ComfyUI")
+        if civitai_resources:
+            params.append(
+                f"Civitai resources: {json.dumps(civitai_resources, separators=(',', ':'))}"
+            )
 
-        # CFG scale (Use guidance if available, otherwise fall back to cfg_scale or cfg)
+        lines.append(", ".join(params))
-        if "guidance" in metadata_dict:
+        return "\n".join(lines)
-            add_param_if_not_none(params, "CFG scale", metadata_dict.get("guidance"))
-        elif "cfg_scale" in metadata_dict:
-            add_param_if_not_none(params, "CFG scale", metadata_dict.get("cfg_scale"))
-        elif "cfg" in metadata_dict:
-            add_param_if_not_none(params, "CFG scale", metadata_dict.get("cfg"))
-
-        # Seed
-        if "seed" in metadata_dict:
-            add_param_if_not_none(params, "Seed", metadata_dict.get("seed"))
-
-        # Size
-        if "size" in metadata_dict:
-            add_param_if_not_none(params, "Size", metadata_dict.get("size"))
-
-        # Model info
-        if "checkpoint" in metadata_dict:
-            # Ensure checkpoint is a string before processing
-            checkpoint = metadata_dict.get("checkpoint")
-            if checkpoint is not None:
-                # Get model hash
-                model_hash = self.get_checkpoint_hash(checkpoint)
-
-                # Extract basename without path
-                checkpoint_name = os.path.basename(checkpoint)
-                # Remove extension if present
-                checkpoint_name = os.path.splitext(checkpoint_name)[0]
-
-                # Add model hash if available
-                if model_hash:
-                    params.append(
-                        f"Model hash: {model_hash[:10]}, Model: {checkpoint_name}"
-                    )
-                else:
-                    params.append(f"Model: {checkpoint_name}")
-
-        # Add LoRA hashes if available
-        if lora_hashes:
-            lora_hash_parts = []
-            for lora_name, hash_value in lora_hashes.items():
-                lora_hash_parts.append(f"{lora_name}: {hash_value[:10]}")
-
-            if lora_hash_parts:
-                params.append(f'Lora hashes: "{", ".join(lora_hash_parts)}"')
-
-        # Combine all parameters with commas
-        metadata_parts.append(", ".join(params))
-
-        # Join all parts with a new line
-        return "\n".join(metadata_parts)
 
     # credit to nkchocoai
     # Add format_filename method to handle pattern substitution
@@ -573,6 +787,8 @@ class SaveImageLM:
         extra_pnginfo=None,
         lossless_webp=True,
         quality=100,
+        webp_method=6,
+        jpeg_subsampling=0,
         embed_workflow=False,
         save_with_metadata=True,
         add_counter_to_filename=True,
@@ -627,15 +843,14 @@ class SaveImageLM:
             elif file_format == "jpeg":
                 file = base_filename + ".jpg"
                 file_extension = ".jpg"
-                save_kwargs = {"quality": quality, "optimize": True}
+                save_kwargs = {"quality": quality, "optimize": True, "subsampling": jpeg_subsampling}
             elif file_format == "webp":
                 file = base_filename + ".webp"
                 file_extension = ".webp"
-                # Add optimization param to control performance
                 save_kwargs = {
                     "quality": quality,
                     "lossless": lossless_webp,
-                    "method": 0,
+                    "method": webp_method,
                 }
             else:
                 raise ValueError(f"Unsupported file format: {file_format}")
@@ -722,6 +937,8 @@ class SaveImageLM:
         extra_pnginfo=None,
         lossless_webp=True,
         quality=100,
+        webp_method=6,
+        jpeg_subsampling=0,
         embed_workflow=False,
         save_with_metadata=True,
         add_counter_to_filename=True,
@@ -751,6 +968,8 @@ class SaveImageLM:
             extra_pnginfo,
             lossless_webp,
             quality,
+            webp_method,
+            jpeg_subsampling,
             embed_workflow,
             save_with_metadata,
             add_counter_to_filename,

py/nodes/unet_loader.py

@@ -7,6 +7,21 @@ from ..utils.utils import get_checkpoint_info_absolute, _format_model_name_for_c
 logger = logging.getLogger(__name__)
 
 
+def _reload_gguf_unet(
+    unet_path: str, weight_dtype: str, disable_dynamic: bool = False
+) -> object:
+    """Reload a GGUF diffusion model from disk (cached_patcher_init factory).
+
+    Mirrors the GGUF branch of UNETLoaderLM.load_unet so ModelPatcher
+    deepclone/dynamic machinery can rebuild GGUF models with the correct
+    GGMLOps. ``disable_dynamic`` is accepted for signature compatibility
+    with core ComfyUI loaders.
+    """
+    loader = UNETLoaderLM()
+    model, = loader._load_gguf_unet(unet_path, unet_path, weight_dtype)
+    return model
+
+
 class UNETLoaderLM:
     """UNET Loader with support for extra folder paths
 
@@ -196,6 +211,12 @@ class UNETLoaderLM:
             # Wrap with GGUFModelPatcher
             model = GGUFModelPatcher.clone(model)
 
+            # Register a reload factory so the MODEL carries its source path
+            # (cached_patcher_init) like core ComfyUI loaders do — required
+            # for model-name extraction downstream and for ModelPatcher
+            # deepclone/dynamic machinery.
+            model.cached_patcher_init = (_reload_gguf_unet, (unet_path, weight_dtype))
+
             return (model,)
 
         except Exception as e:

py/routes/handlers/misc_handlers.py

@@ -1562,6 +1562,11 @@ class SettingsHandler:
                             {"success": False, "error": validation_error}
                         )
 
+                if key == "update_channel" and value not in ("release", "nightly"):
+                    return web.json_response(
+                        {"success": False, "error": "update_channel must be 'release' or 'nightly'"}
+                    )
+
                 if value == "__DELETE__" and key in (
                     "proxy_username",
                     "proxy_password",
@@ -2585,6 +2590,8 @@ class ModelLibraryHandler:
                     status=400,
                 )
 
+            cursor = request.query.get("cursor")
+
             metadata_provider = await self._metadata_provider_factory()
             if not metadata_provider:
                 return web.json_response(
@@ -2593,7 +2600,7 @@ class ModelLibraryHandler:
                 )
 
             try:
-                models = await metadata_provider.get_user_models(username)
+                result = await metadata_provider.get_user_models(username, cursor)
             except NotImplementedError:
                 return web.json_response(
                     {
@@ -2603,14 +2610,35 @@ class ModelLibraryHandler:
                     status=501,
                 )
 
-            if models is None:
+            if result is None:
                 return web.json_response(
                     {"success": False, "error": "Failed to fetch user models"},
                     status=502,
                 )
 
+            if isinstance(result, dict):
+                models = result.get("items")
+                next_cursor = result.get("nextCursor")
+            else:
+                # Defensive: tolerate providers that still return a raw list
+                models = result
+                next_cursor = None
+
             if not isinstance(models, list):
                 models = []
+            if next_cursor is not None and not isinstance(next_cursor, str):
+                next_cursor = str(next_cursor)
+
+            estimated_total = None
+            if cursor is None:
+                get_count = getattr(metadata_provider, "get_creator_model_count", None)
+                if get_count is not None:
+                    try:
+                        estimated_total = await get_count(username)
+                    except Exception:  # best-effort only
+                        estimated_total = None
+                if not isinstance(estimated_total, int):
+                    estimated_total = None
 
             lora_scanner = await self._service_registry.get_lora_scanner()
             checkpoint_scanner = await self._service_registry.get_checkpoint_scanner()
@@ -2630,6 +2658,7 @@ class ModelLibraryHandler:
             versions: list[dict] = []
             history_service = await self._get_download_history_service()
             model_ids: list[int] = []
+            model_count = 0
             for model in models:
                 try:
                     model_ids.append(int(model.get("id")))
@@ -2663,6 +2692,8 @@ class ModelLibraryHandler:
                 if model_type not in normalized_allowed_types:
                     continue
 
+                model_count += 1
+
                 scanner = type_scanner_map.get(model_type)
                 if scanner is None:
                     return web.json_response(
@@ -2728,7 +2759,15 @@ class ModelLibraryHandler:
                     )
 
             return web.json_response(
-                {"success": True, "username": username, "versions": versions}
+                {
+                    "success": True,
+                    "username": username,
+                    "versions": versions,
+                    "modelCount": model_count,
+                    "nextCursor": next_cursor,
+                    "hasMore": next_cursor is not None,
+                    "estimatedTotal": estimated_total,
+                }
             )
         except Exception as exc:  # pragma: no cover - defensive logging
             logger.error("Failed to get Civitai user models: %s", exc, exc_info=True)

py/routes/handlers/model_handlers.py

@@ -394,12 +394,14 @@ class ModelListingHandler:
         )
 
         # View-local-versions filter: show all local versions of a specific model
+        # Accepts either a CivitAI modelId (int) or a HF group key like "hf:user/repo"
         civitai_model_id = request.query.get("civitai_model_id")
         if civitai_model_id is not None:
             try:
                 civitai_model_id = int(civitai_model_id)
             except (TypeError, ValueError):
-                civitai_model_id = None
+                # Keep as string — could be an HF group key (e.g. "hf:user/repo")
+                pass
 
         return {
             "page": page,
@@ -537,6 +539,7 @@ class ModelManagementHandler:
                     # Update model_data with new hash
                     model_data["sha256"] = sha256
                     model_data["hash_status"] = "completed"
+                    hash_status = "completed"
                 else:
                     return web.json_response(
                         {"success": False, "error": "No SHA256 hash found"}, status=400
@@ -544,6 +547,32 @@ class ModelManagementHandler:
 
             await MetadataManager.hydrate_model_data(model_data)
 
+            # hydrate_model_data replaces model_data with .metadata.json content,
+            # which may lack sha256. Restore from cache and persist the fix.
+            if not model_data.get("sha256"):
+                if sha256:
+                    model_data["sha256"] = sha256
+                    model_data["hash_status"] = model_data.get("hash_status", hash_status)
+                    data_to_save = model_data.copy()
+                    data_to_save.pop("folder", None)
+                    await MetadataManager.save_metadata(file_path, data_to_save)
+                else:
+                    sha256 = await calculate_sha256(file_path)
+                    if sha256:
+                        model_data["sha256"] = sha256.lower()
+                        model_data["hash_status"] = "completed"
+                        data_to_save = model_data.copy()
+                        data_to_save.pop("folder", None)
+                        await MetadataManager.save_metadata(file_path, data_to_save)
+                    else:
+                        return web.json_response(
+                            {
+                                "success": False,
+                                "error": "Failed to compute SHA256 hash for model",
+                            },
+                            status=500,
+                        )
+
             success, error = await self._metadata_sync.fetch_and_update_model(
                 sha256=model_data["sha256"],
                 file_path=file_path,
@@ -566,7 +595,12 @@ class ModelManagementHandler:
                     {"success": False, "error": OFFLINE_FRIENDLY_MESSAGE},
                     status=503,
                 )
-            self._logger.error("Error fetching from CivitAI: %s", exc, exc_info=True)
+            self._logger.error(
+                "Error fetching from CivitAI for %s: %s",
+                locals().get("file_path", "unknown"),
+                exc,
+                exc_info=True,
+            )
             return web.json_response({"success": False, "error": str(exc)}, status=500)
 
     async def relink_civitai(self, request: web.Request) -> web.Response:

py/routes/update_routes.py

@@ -38,6 +38,84 @@ def _clean_excludes() -> List[str]:
     return excludes
 
 
+def _stage_preserved_items(plugin_root: str) -> tuple[str, list[str]]:
+    """Move preserved user-data items to a temp directory outside *plugin_root*.
+
+    This ensures that ``git reset --hard``, ``git clean -fd``, and ZIP-based
+    replacement cannot touch these files even when ``-e`` exclusion patterns
+    are mishandled (e.g. on Windows where forward-slash patterns may not
+    match backslash-prefixed paths in some Git builds, or where file locks
+    prevent deletion/recreation).
+
+    Returns:
+        ``(backup_root, staged_names)``: the temp directory path and the
+        list of item names that were successfully moved.
+    """
+    backup_root = tempfile.mkdtemp(prefix='lora_manager_update_')
+    staged: list[str] = []
+    for name in _PRESERVE_DIRS:
+        src = os.path.join(plugin_root, name)
+        if not os.path.lexists(src):
+            continue
+        dst = os.path.join(backup_root, name)
+        try:
+            shutil.move(src, dst)
+            staged.append(name)
+            logger.debug("Staged '%s' for update safety", name)
+        except OSError:
+            # ``shutil.move`` may fail on Windows if a file handle inside
+            # the directory is still open (e.g. a SQLite WAL file). Fall
+            # back to copy-then-remove.
+            logger.debug("Move failed for '%s', falling back to copy", name)
+            try:
+                if os.path.isdir(src) and not os.path.islink(src):
+                    shutil.copytree(src, dst, symlinks=True)
+                    shutil.rmtree(src, ignore_errors=True)
+                else:
+                    shutil.copy2(src, dst)
+                    os.remove(src)
+                staged.append(name)
+                logger.info("Copied (then removed) '%s' for update safety", name)
+            except Exception as exc:
+                logger.warning(
+                    "Could not stage '%s': %s (will rely on git -e / skip lists)", name, exc
+                )
+    return backup_root, staged
+
+
+def _restore_preserved_items(plugin_root: str, backup_root: str, staged: list[str]) -> None:
+    """Move staged items back from *backup_root* into *plugin_root*.
+
+    Any leftover placeholder at the destination (created by git checkout or
+    ZIP extraction) is removed before the move.
+    """
+    for name in staged:
+        src = os.path.join(backup_root, name)
+        dst = os.path.join(plugin_root, name)
+        try:
+            if os.path.lexists(dst):
+                if os.path.isdir(dst) and not os.path.islink(dst):
+                    shutil.rmtree(dst, ignore_errors=True)
+                else:
+                    os.remove(dst)
+            shutil.move(src, dst)
+            logger.debug("Restored '%s' after update", name)
+        except OSError:
+            logger.debug("Move failed restoring '%s', falling back to copy", name)
+            try:
+                if os.path.isdir(src) and not os.path.islink(src):
+                    shutil.copytree(src, dst, symlinks=True, dirs_exist_ok=True)
+                    shutil.rmtree(src, ignore_errors=True)
+                else:
+                    shutil.copy2(src, dst)
+                    os.remove(src)
+                logger.info("Copied '%s' back after update", name)
+            except Exception as exc:
+                logger.error("Failed to restore '%s': %s", name, exc)
+    shutil.rmtree(backup_root, ignore_errors=True)
+
+
+
 class UpdateRoutes:
     """Routes for handling plugin update checks"""
     
@@ -47,6 +125,7 @@ class UpdateRoutes:
         app.router.add_get('/api/lm/check-updates', UpdateRoutes.check_updates)
         app.router.add_get('/api/lm/version-info', UpdateRoutes.get_version_info)
         app.router.add_post('/api/lm/perform-update', UpdateRoutes.perform_update)
+        app.router.add_post('/api/lm/switch-channel', UpdateRoutes.switch_channel)
     
     @staticmethod
     async def check_updates(request):
@@ -65,10 +144,17 @@ class UpdateRoutes:
 
             # Fetch remote version from GitHub
             if nightly:
-                remote_version, changelog = await UpdateRoutes._get_nightly_version()
+                local_hash = git_info.get('short_hash', '')
-                releases = None
+                nightly_version, releases_result = await asyncio.gather(
+                    UpdateRoutes._get_nightly_version(local_hash),
+                    UpdateRoutes._get_remote_version()
+                )
+                remote_version, _, behind_by, commit_date = nightly_version
+                _, changelog, releases = releases_result
             else:
                 remote_version, changelog, releases = await UpdateRoutes._get_remote_version()
+                behind_by = 0
+                commit_date = ''
             
             # Compare versions
             if nightly:
@@ -81,6 +167,10 @@ class UpdateRoutes:
                     remote_version.replace('v', '')
                 )
             
+            current_dir = os.path.dirname(os.path.abspath(__file__))
+            plugin_root = os.path.dirname(os.path.dirname(current_dir))
+            has_git = os.path.exists(os.path.join(plugin_root, '.git'))
+
             response_data = {
                 'success': True,
                 'current_version': local_version,
@@ -88,13 +178,13 @@ class UpdateRoutes:
                 'update_available': update_available,
                 'changelog': changelog,
                 'git_info': git_info,
-                'nightly': nightly
+                'nightly': nightly,
+                'has_git': has_git,
+                'releases': releases,
+                'behind_by': behind_by,
+                'commit_date': commit_date
             }
             
-            # Include releases list for stable mode
-            if releases is not None:
-                response_data['releases'] = releases
-            
             return web.json_response(response_data)
             
         except NETWORK_EXCEPTIONS as e:
@@ -126,9 +216,14 @@ class UpdateRoutes:
             # Format: version-short_hash
             version_string = f"{local_version}-{short_hash}"
             
+            current_dir = os.path.dirname(os.path.abspath(__file__))
+            plugin_root = os.path.dirname(os.path.dirname(current_dir))
+            has_git = os.path.exists(os.path.join(plugin_root, '.git'))
+
             return web.json_response({
                 'success': True,
-                'version': version_string
+                'version': version_string,
+                'has_git': has_git
             })
             
         except Exception as e:
@@ -156,20 +251,22 @@ class UpdateRoutes:
             if os.path.exists(settings_path):
                 with open(settings_path, 'r', encoding='utf-8') as f:
                     settings_backup = f.read()
-                logger.info("Backed up settings.json")
+                logger.debug("Backed up settings.json (%d bytes)", len(settings_backup))
 
-            git_folder = os.path.join(plugin_root, '.git')
+            staged_backup_dir, staged_items = _stage_preserved_items(plugin_root)
-            if os.path.exists(git_folder):
+            try:
-                # Git update
+                git_folder = os.path.join(plugin_root, '.git')
-                success, new_version = await UpdateRoutes._perform_git_update(plugin_root, nightly)
+                if os.path.exists(git_folder):
-            else:
+                    success, new_version = await UpdateRoutes._perform_git_update(plugin_root, nightly)
-                # Fallback: Download ZIP and replace files
+                else:
-                success, new_version = await UpdateRoutes._download_and_replace_zip(plugin_root)
+                    success, new_version = await UpdateRoutes._download_and_replace_zip(plugin_root)
+            finally:
+                _restore_preserved_items(plugin_root, staged_backup_dir, staged_items)
 
             if settings_backup and success:
                 with open(settings_path, 'w', encoding='utf-8') as f:
                     f.write(settings_backup)
-                logger.info("Restored settings.json")
+                logger.debug("Restored settings.json content (%d bytes)", len(settings_backup))
 
             if success:
                 return web.json_response({
@@ -190,6 +287,164 @@ class UpdateRoutes:
                 'error': str(e)
             })
 
+    @staticmethod
+    async def switch_channel(request):
+        """
+        Switch between release and nightly update channels.
+
+        ZIP/CNR install → Nightly: git init + checkout main (one-way upgrade)
+        Git install → Release:   git checkout latest tag (.git preserved)
+        ZIP/CNR install → Release: ZIP download (no .git, stays in ZIP mode)
+        Git install → Nightly:   git checkout main + pull
+        """
+        try:
+            body = await request.json() if request.has_body else {}
+            channel = body.get('channel', '')
+
+            if channel not in ('release', 'nightly'):
+                return web.json_response({
+                    'success': False,
+                    'error': f'Invalid channel: {channel}. Must be "release" or "nightly".'
+                })
+
+            current_dir = os.path.dirname(os.path.abspath(__file__))
+            plugin_root = os.path.dirname(os.path.dirname(current_dir))
+
+            settings_path = ensure_settings_file(logger)
+            settings_backup = None
+            if os.path.exists(settings_path):
+                with open(settings_path, 'r', encoding='utf-8') as f:
+                    settings_backup = f.read()
+                logger.debug("Backed up settings.json before channel switch (%d bytes)", len(settings_backup))
+
+            staged_backup_dir, staged_items = _stage_preserved_items(plugin_root)
+            try:
+                git_folder = os.path.join(plugin_root, '.git')
+
+                if channel == 'nightly':
+                    git_backup = None
+                    if os.path.exists(git_folder):
+                        git_backup = UpdateRoutes._backup_git(git_folder, 'nightly')
+
+                    success = False
+                    new_version = ''
+                    try:
+                        if os.path.exists(git_folder):
+                            success, new_version = await UpdateRoutes._perform_git_update(
+                                plugin_root, nightly=True
+                            )
+                        else:
+                            success, new_version = UpdateRoutes._init_git_repo(plugin_root)
+                    finally:
+                        UpdateRoutes._restore_git(git_backup, git_folder, success, 'nightly')
+                else:
+                    success = False
+                    new_version = ''
+                    if os.path.exists(git_folder):
+                        success, new_version = await UpdateRoutes._perform_git_update(
+                            plugin_root, nightly=False
+                        )
+                    else:
+                        tracking_file = os.path.join(plugin_root, '.tracking')
+                        if os.path.exists(tracking_file):
+                            os.remove(tracking_file)
+                        success, new_version = await UpdateRoutes._download_and_replace_zip(plugin_root)
+            finally:
+                _restore_preserved_items(plugin_root, staged_backup_dir, staged_items)
+
+            if settings_backup and success:
+                with open(settings_path, 'w', encoding='utf-8') as f:
+                    f.write(settings_backup)
+                logger.debug("Restored settings.json content after channel switch (%d bytes)", len(settings_backup))
+
+            if success:
+                return web.json_response({
+                    'success': True,
+                    'channel': channel,
+                    'new_version': new_version,
+                    'message': f'Switched to {channel} channel'
+                })
+            else:
+                return web.json_response({
+                    'success': False,
+                    'error': f'Failed to switch to {channel} channel'
+                })
+
+        except Exception as e:
+            logger.error("Failed to switch channel: %s", e, exc_info=True)
+            return web.json_response({
+                'success': False,
+                'error': str(e)
+            })
+
+    @staticmethod
+    def _init_git_repo(plugin_root: str) -> tuple[bool, str]:
+        """
+        Initialize a Git repository in a ZIP-installed plugin folder.
+        Clones the remote history and checks out main branch.
+        """
+        try:
+            import git
+        except ImportError:
+            logger.error(
+                "GitPython is not available: cannot initialize git repo. "
+                "Install git or set $GIT_PYTHON_GIT_EXECUTABLE to the git binary path."
+            )
+            return False, ""
+
+        clean_excludes = _clean_excludes()
+
+        try:
+            repo = git.Repo.init(plugin_root)
+            origin = repo.create_remote(
+                'origin',
+                'https://github.com/willmiao/ComfyUI-Lora-Manager.git'
+            )
+            origin.fetch()
+
+            repo.create_head('main', origin.refs.main)
+            repo.git.checkout('main', '--force')
+            repo.git.reset('--hard')
+            repo.git.clean('-fd', *clean_excludes)
+
+            tracking_file = os.path.join(plugin_root, '.tracking')
+            if os.path.exists(tracking_file):
+                os.remove(tracking_file)
+                logger.info("Removed .tracking file (now in git mode)")
+
+            new_version = f"main-{repo.head.commit.hexsha[:7]}"
+            logger.info("Initialized git repo on main branch: %s", new_version)
+            return True, new_version
+
+        except Exception as e:
+            logger.error("Failed to initialize git repo: %s", e, exc_info=True)
+            return False, ""
+
+    @staticmethod
+    def _backup_git(git_folder, label):
+        try:
+            backup_dir = tempfile.mkdtemp()
+            backup = os.path.join(backup_dir, '.git')
+            shutil.copytree(git_folder, backup)
+            logger.info("Backed up .git before switching to %s", label)
+            return backup
+        except Exception as e:
+            logger.error("Failed to backup .git before %s switch: %s", label, e)
+            return None
+
+    @staticmethod
+    def _restore_git(git_backup, git_folder, success, label):
+        if git_backup and not success:
+            try:
+                if os.path.exists(git_folder):
+                    shutil.rmtree(git_folder)
+                shutil.copytree(git_backup, git_folder)
+                logger.info("Restored .git after failed %s switch", label)
+            except Exception as e:
+                logger.error("Failed to restore .git after %s switch: %s", label, e)
+        if git_backup:
+            shutil.rmtree(os.path.dirname(git_backup), ignore_errors=True)
+
     @staticmethod
     async def _download_and_replace_zip(plugin_root: str) -> tuple[bool, str]:
         """
@@ -244,8 +499,7 @@ class UpdateRoutes:
             except Exception:
                 logger.debug("Could not close downloaded-version history database", exc_info=True)
 
-            # Skip settings.json, civitai, model cache and runtime cache folders
+            UpdateRoutes._clean_plugin_folder(plugin_root, skip_files=list(_PRESERVE_DIRS))
-            UpdateRoutes._clean_plugin_folder(plugin_root, skip_files=['settings.json', 'civitai', 'model_cache', 'cache', 'wildcards', 'backups', 'stats'])
 
             # Extract ZIP to temp dir
             with tempfile.TemporaryDirectory() as tmp_dir:
@@ -255,7 +509,7 @@ class UpdateRoutes:
                     extracted_root = next(os.scandir(tmp_dir)).path
 
                     # Copy files, skipping user data that should be preserved
-                    skip_items = {'settings.json', 'civitai', 'wildcards', 'backups', 'stats'}
+                    skip_items = set(_PRESERVE_DIRS)
                     for item in os.listdir(extracted_root):
                         if item in skip_items:
                             continue
@@ -272,7 +526,7 @@ class UpdateRoutes:
                     # for ComfyUI Manager to work properly
                     tracking_info_file = os.path.join(plugin_root, '.tracking')
                     tracking_files = []
-                    skip_tracked = {'civitai', 'wildcards', 'backups', 'stats'}
+                    skip_tracked = set(_PRESERVE_DIRS) - {'settings.json'}
                     for root, dirs, files in os.walk(extracted_root):
                         # Skip user data directories and their contents
                         rel_root = os.path.relpath(root, extracted_root)
@@ -296,6 +550,7 @@ class UpdateRoutes:
             logger.error(f"ZIP update failed: {e}", exc_info=True)
             return False, ""
 
+    @staticmethod
     def _clean_plugin_folder(plugin_root, skip_files=None):
         skip_files = skip_files or []
         for item in os.listdir(plugin_root):
@@ -308,41 +563,54 @@ class UpdateRoutes:
                 os.remove(path)
     
     @staticmethod
-    async def _get_nightly_version() -> tuple[str, List[str]]:
+    async def _get_nightly_version(local_hash: str = "") -> tuple[str, List[str], int, str]:
-        """
-        Fetch latest commit from main branch
-        """
         repo_owner = "willmiao"
         repo_name = "ComfyUI-Lora-Manager"
 
-        # Use GitHub API to fetch the latest commit from main branch
         github_url = f"https://api.github.com/repos/{repo_owner}/{repo_name}/commits/main"
 
         try:
             downloader = await get_downloader()
-            success, data = await downloader.make_request('GET', github_url, custom_headers={'Accept': 'application/vnd.github+json'})
+            success, data = await downloader.make_request(
+                'GET', github_url,
+                custom_headers={'Accept': 'application/vnd.github+json'}
+            )
 
             if not success:
-                logger.warning(f"Failed to fetch GitHub commit: {data}")
+                logger.warning("Failed to fetch GitHub commit: %s", data)
-                return "main", []
+                return "main", [], 0, ""
 
-            commit_sha = data.get('sha', '')[:7]  # Short hash
+            commit_sha = data.get('sha', '')[:7]
             commit_message = data.get('commit', {}).get('message', '')
+            commit_date = data.get('commit', {}).get('committer', {}).get('date', '')[:10]
 
-            # Format as "main-{short_hash}"
             version = f"main-{commit_sha}"
-            
-            # Use commit message as changelog
             changelog = [commit_message] if commit_message else []
 
-            return version, changelog
+            behind_by = 0
+            if local_hash and local_hash not in ('unknown', 'stable'):
+                compare_url = (
+                    f"https://api.github.com/repos/{repo_owner}/{repo_name}"
+                    f"/compare/{local_hash}...main"
+                )
+                c_ok, c_data = await downloader.make_request(
+                    'GET', compare_url,
+                    custom_headers={'Accept': 'application/vnd.github+json'}
+                )
+                if c_ok:
+                    if c_data.get('status') in ('ahead', 'diverged'):
+                        behind_by = c_data.get('ahead_by', 0)
+                    else:
+                        behind_by = c_data.get('behind_by', 0)
+
+            return version, changelog, behind_by, commit_date
 
         except NETWORK_EXCEPTIONS as e:
             logger.warning("Unable to reach GitHub for nightly version: %s", e)
-            return "main", []
+            return "main", [], 0, ""
         except Exception as e:
-            logger.error(f"Error fetching nightly version: {e}", exc_info=True)
+            logger.error("Error fetching nightly version: %s", e, exc_info=True)
-            return "main", []
+            return "main", [], 0, ""
     
     @staticmethod
     def _compare_nightly_versions(local_git_info: Dict[str, str], remote_version: str) -> bool:

py/services/base_model_service.py

@@ -1,7 +1,8 @@
 from abc import ABC, abstractmethod
 import asyncio
 import re
-from typing import Any, Dict, List, Optional, Type, TYPE_CHECKING
+import random
+from typing import Any, Dict, List, Optional, Type, Union, TYPE_CHECKING
 import logging
 import os
 import time
@@ -109,12 +110,15 @@ class BaseModelService(ABC):
         if civitai_model_id is not None:
             sorted_data = [
                 item for item in sorted_data
-                if self._extract_model_id(item) == civitai_model_id
+                if self._extract_group_key(item) == civitai_model_id
             ]
             # VLM mode: always sort by version ID descending (newest version first),
             # regardless of the current sort_by preference.
+            # Fall back to modified timestamp for non-CivitAI sources.
             sorted_data.sort(
-                key=lambda x: self._extract_version_id(x) or 0,
+                key=lambda x: self._extract_version_id(x)
+                or x.get("modified", 0)
+                or 0,
                 reverse=True,
             )
 
@@ -129,18 +133,21 @@ class BaseModelService(ABC):
             ufs = self.settings.get("version_grouping", "same_base")
             group_by_base = ufs == "same_base"
 
-            dedup_map = {}  # (modelId [,base_model]) -> (item, version_id)
+            dedup_map = {}  # (modelId [,base_model]) -> (item, version_or_modified)
             version_counter = {}  # same-key -> count
             standalone = []
             for item in sorted_data:
-                mid = self._extract_model_id(item)
+                mid = self._extract_group_key(item)
                 if mid is None:
                     standalone.append(item)
                     continue
                 key = (mid, item.get("base_model") or "") if group_by_base else mid
                 # Count all versions per key
                 version_counter[key] = version_counter.get(key, 0) + 1
-                vid = self._extract_version_id(item) or 0
+                # Prefer CivitAI version_id; fall back to modified timestamp
+                vid = self._extract_version_id(item)
+                if vid is None:
+                    vid = item.get("modified", 0) or 0
                 if key not in dedup_map or vid > dedup_map[key][1]:
                     dedup_map[key] = (item, vid)
             # Attach version_count to each surviving grouped item (shallow copy
@@ -174,16 +181,19 @@ class BaseModelService(ABC):
                 model_groups: Dict[Any, List[Dict]] = {}
                 ungrouped_standalone: List[Dict] = []
                 for item in sorted_data:
-                    mid = self._extract_model_id(item)
+                    mid = self._extract_group_key(item)
                     if mid is None:
                         ungrouped_standalone.append(item)
                         continue
                     key = (mid, item.get("base_model") or "") if group_by_base else mid
                     model_groups.setdefault(key, []).append(item)
-                # Sort versions within each group by version id descending
+                # Sort versions within each group by version id (descending);
+                # fall back to modified timestamp for non-CivitAI sources.
                 for items in model_groups.values():
                     items.sort(
-                        key=lambda x: self._extract_version_id(x) or 0,
+                        key=lambda x: self._extract_version_id(x)
+                        or x.get("modified", 0)
+                        or 0,
                         reverse=True,
                     )
                 # Sort groups by version count
@@ -381,6 +391,12 @@ class BaseModelService(ABC):
                 (item.get("model_name") or item.get("file_name") or "").lower(),
                 item.get("file_path", "").lower(),
             )
+        elif key_name == "random":
+            # Seeded random shuffle: same seed -> same order (stable pagination)
+            rng = random.Random(sort_params.seed or "random")
+            result = list(data)
+            rng.shuffle(result)
+            return result
         elif key_name == "size":
             key_fn = lambda item: (
                 int(item.get("size", 0) or 0),
@@ -697,6 +713,33 @@ class BaseModelService(ABC):
 
         return annotated
 
+    @staticmethod
+    def _extract_hf_group_key(item: Dict) -> Optional[str]:
+        """Extract `hf:{owner}/{repo}` from item's ``hf_url``, or None."""
+        hf_url = item.get("hf_url") if isinstance(item, dict) else None
+        if not hf_url or not isinstance(hf_url, str):
+            return None
+        m = re.match(
+            r"https?://huggingface\.co/([^/]+/[^/]+)", hf_url.strip()
+        )
+        if not m:
+            return None
+        return f"hf:{m.group(1)}"
+
+    @staticmethod
+    def _extract_group_key(item: Dict) -> Union[int, str, None]:
+        """Return the group identity key: CivitAI modelId (int) or HF repo (str).
+
+        Preference order:
+        1. CivitAI ``modelId`` (int)
+        2. HF repo identity ``hf:{owner}/{repo}`` (str)
+        3. ``None`` (no known grouping source)
+        """
+        mid = BaseModelService._extract_model_id(item)
+        if mid is not None:
+            return mid
+        return BaseModelService._extract_hf_group_key(item)
+
     @staticmethod
     def _extract_model_id(item: Dict) -> Optional[int]:
         civitai = item.get("civitai") if isinstance(item, dict) else None

py/services/civitai_client.py

@@ -2,6 +2,7 @@ import asyncio
 import copy
 import logging
 import os
+import time
 from collections import OrderedDict
 from typing import Any, Optional, Dict, Tuple, List, Sequence
 from .connectivity_guard import (
@@ -19,6 +20,12 @@ from ..utils.civitai_utils import resolve_license_payload
 
 logger = logging.getLogger(__name__)
 
+# Best-effort cache for creator model counts, keyed by lowercase username.
+# Values are (monotonic timestamp, count or None); None results are cached
+# too so repeated failures don't hammer the API.
+_CREATOR_COUNT_CACHE_TTL_SECONDS = 600
+_creator_model_count_cache: Dict[str, Tuple[float, Optional[int]]] = {}
+
 
 class CivitaiClient:
     _instance = None
@@ -743,17 +750,34 @@ class CivitaiClient:
 
         return all_versions if all_versions else None
 
-    async def get_user_models(self, username: str) -> Optional[List[Dict]]:
+    async def get_user_models(
-        """Fetch all models for a specific Civitai user."""
+        self, username: str, cursor: Optional[str] = None
+    ) -> Optional[Dict[str, Any]]:
+        """Fetch one page (up to 100 models) for a specific Civitai user.
+
+        Returns ``{"items": [...], "nextCursor": <str|None>}`` on success,
+        or None on failure. Pass ``cursor`` (from a previous response's
+        ``nextCursor``) to fetch subsequent pages.
+        """
         if not username:
             return None
 
+        params: Dict[str, Any] = {
+            "username": username,
+            "nsfw": "true",
+            "limit": 100,
+            "sort": "Newest",
+            "period": "AllTime",
+        }
+        if cursor:
+            params["cursor"] = cursor
+
         try:
             success, result = await self._make_request(
                 "GET",
                 f"{self.base_url}/models",
                 use_auth=True,
-                params={"username": username, "nsfw": "true"},
+                params=params,
             )
 
             if not success:
@@ -765,7 +789,7 @@ class CivitaiClient:
 
             items = result.get("items") if isinstance(result, dict) else None
             if not isinstance(items, list):
-                return []
+                items = []
 
             for model in items:
                 versions = model.get("modelVersions")
@@ -774,9 +798,68 @@ class CivitaiClient:
                 for version in versions:
                     self._remove_comfy_metadata(version)
 
-            return items
+            next_cursor: Optional[str] = None
+            metadata = result.get("metadata") if isinstance(result, dict) else None
+            if isinstance(metadata, dict):
+                raw_cursor = metadata.get("nextCursor")
+                if raw_cursor is not None:
+                    next_cursor = str(raw_cursor)
+
+            return {"items": items, "nextCursor": next_cursor}
         except RateLimitError:
             raise
         except Exception as exc:  # pragma: no cover - defensive logging
             logger.error("Error fetching models for %s: %s", username, exc)
             return None
+
+    async def get_creator_model_count(self, username: str) -> Optional[int]:
+        """Best-effort lookup of a creator's published model count.
+
+        Uses the ``/creators`` endpoint (a contains-match query), picking the
+        entry whose username matches exactly (case-insensitive). Returns None
+        on any failure; never raises. Results (including None) are cached
+        for ``_CREATOR_COUNT_CACHE_TTL_SECONDS``.
+        """
+        if not username:
+            return None
+
+        cache_key = username.lower()
+        cached = _creator_model_count_cache.get(cache_key)
+        if cached is not None:
+            cached_at, cached_count = cached
+            if time.monotonic() - cached_at < _CREATOR_COUNT_CACHE_TTL_SECONDS:
+                return cached_count
+
+        count: Optional[int] = None
+        try:
+            success, result = await self._make_request(
+                "GET",
+                f"{self.base_url}/creators",
+                use_auth=True,
+                params={"query": username, "limit": 10},
+            )
+
+            if success and isinstance(result, dict):
+                creators = result.get("items")
+                if isinstance(creators, list):
+                    for creator in creators:
+                        if not isinstance(creator, dict):
+                            continue
+                        creator_name = creator.get("username")
+                        if not isinstance(creator_name, str):
+                            continue
+                        if creator_name.lower() != cache_key:
+                            continue
+                        model_count = creator.get("modelCount")
+                        if isinstance(model_count, (int, float)) and not isinstance(
+                            model_count, bool
+                        ):
+                            count = int(model_count)
+                        break
+        except Exception as exc:  # best-effort only, never propagate
+            logger.debug(
+                "Failed to fetch creator model count for %s: %s", username, exc
+            )
+
+        _creator_model_count_cache[cache_key] = (time.monotonic(), count)
+        return count

py/services/download_manager.py

@@ -1389,7 +1389,17 @@ class DownloadManager:
 
             # Update save directory with relative path if provided
             if relative_path:
+                base_save_dir = save_dir
                 save_dir = os.path.join(save_dir, relative_path)
+                # Security: validate path containment after joining
+                resolved_dir = os.path.abspath(os.path.normpath(save_dir))
+                base_dir = os.path.abspath(os.path.normpath(base_save_dir))
+                if not resolved_dir.startswith(base_dir + os.sep) and resolved_dir != base_dir:
+                    logger.warning(
+                        "Path traversal detected: %s escapes %s",
+                        resolved_dir, base_dir,
+                    )
+                    return {"success": False, "error": "Download path is outside allowed directory"}
                 # Create directory if it doesn't exist
                 os.makedirs(save_dir, exist_ok=True)
 
@@ -1827,6 +1837,9 @@ class DownloadManager:
             model_tags, model_type
         )
 
+        if not first_tag:
+            first_tag = "no tags"  # Default if no tags available
+
         # Format the template with available data
         formatted_path = path_template
         formatted_path = formatted_path.replace("{base_model}", mapped_base_model)
@@ -1842,6 +1855,15 @@ class DownloadManager:
         if model_type == "embedding":
             formatted_path = formatted_path.replace(" ", "_")
 
+        # Sanitize the resolved path to prevent path traversal:
+        # - Strip leading slashes (prevents os.path.join from treating path as absolute)
+        # - Collapse double slashes from empty placeholder substitutions
+        # - Strip trailing slashes for cleanliness
+        formatted_path = formatted_path.lstrip("/")
+        while "//" in formatted_path:
+            formatted_path = formatted_path.replace("//", "/")
+        formatted_path = formatted_path.rstrip("/")
+
         return formatted_path
 
     async def _execute_download(

py/services/download_queue_service.py

@@ -31,7 +31,7 @@ class DownloadQueueService:
     _instance: Optional[DownloadQueueService] = None
     _class_lock: asyncio.Lock = asyncio.Lock()
 
-    _SCHEMA = """
+    _SCHEMA_TABLES = """
         CREATE TABLE IF NOT EXISTS download_queue (
             download_id TEXT PRIMARY KEY,
             model_id INTEGER,
@@ -74,6 +74,9 @@ class DownloadQueueService:
         );
         CREATE INDEX IF NOT EXISTS idx_dh_completed ON download_history(completed_at DESC);
         CREATE INDEX IF NOT EXISTS idx_dh_status ON download_history(status);
+    """
+
+    _CREATE_UNIQUE_INDEX = """
         CREATE UNIQUE INDEX IF NOT EXISTS idx_dh_download_id
             ON download_history(download_id) WHERE download_id IS NOT NULL;
     """
@@ -115,10 +118,39 @@ class DownloadQueueService:
         if self._schema_initialized:
             return
         with self._connect() as conn:
-            conn.executescript(self._SCHEMA)
+            conn.executescript(self._SCHEMA_TABLES)
+
+            # Creating the unique index on download_history.download_id can
+            # fail if pre-existing rows have duplicate values (e.g. from a
+            # previous version that lacked the index).  Deduplicate first so
+            # that the migration does not crash on startup.
+            if not self._index_exists(conn, "idx_dh_download_id"):
+                self._remove_duplicate_download_ids(conn)
+                conn.executescript(self._CREATE_UNIQUE_INDEX)
+
             conn.commit()
         self._schema_initialized = True
 
+    @staticmethod
+    def _index_exists(conn: sqlite3.Connection, name: str) -> bool:
+        return conn.execute(
+            "SELECT 1 FROM sqlite_master WHERE type='index' AND name=?",
+            (name,),
+        ).fetchone() is not None
+
+    @staticmethod
+    def _remove_duplicate_download_ids(conn: sqlite3.Connection) -> None:
+        conn.execute("""
+            DELETE FROM download_history
+            WHERE id NOT IN (
+                SELECT MIN(id)
+                FROM download_history
+                WHERE download_id IS NOT NULL
+                GROUP BY download_id
+            )
+            AND download_id IS NOT NULL
+        """)
+
     def get_database_path(self) -> str:
         """Return the resolved database file path."""
         return self._db_path

py/services/llm_service.py

@@ -566,18 +566,52 @@ class LLMService:
         if effective_max is None:
             effective_max = 4096
 
-        result = await self.chat_completion(
+        # Use json_schema (not json_object) for broader provider compatibility:
-            messages=messages,
+        # LM Studio and some other OpenAI-compatible servers reject
-            model=model,
+        # json_object but accept json_schema.  {"type": "object"} is
-            temperature=temperature,
+        # functionally equivalent — it accepts any JSON object without
-            response_format={"type": "json_object"},
+        # constraining specific fields.
-            max_tokens=effective_max,
+        response_format = {
-        )
+            "type": "json_schema",
+            "json_schema": {
+                "name": "metadata",
+                "schema": {"type": "object"},
+            },
+        }
+
+        try:
+            result = await self.chat_completion(
+                messages=messages,
+                model=model,
+                temperature=temperature,
+                response_format=response_format,
+                max_tokens=effective_max,
+            )
+        except LLMResponseError as e:
+            # Only fall back when the provider rejects the response_format
+            # type value (e.g. "'response_format.type' must be...").  Avoid
+            # catching unrelated 400 errors whose body happens to mention
+            # "response_format" (e.g. "model does not support
+            # response_format restrictions on this endpoint").
+            if "'response_format.type'" not in str(e).lower():
+                raise
+            logger.info(
+                "Provider rejected response_format, retrying without it. "
+                "Falling back to prompt-only JSON mode. Error: %s",
+                e,
+            )
+            result = await self.chat_completion(
+                messages=messages,
+                model=model,
+                temperature=temperature,
+                response_format=None,
+                max_tokens=effective_max,
+            )
 
         content = result.get("content", "") or ""
         if not content:
             raise LLMResponseError(
-                "LLM returned empty content in json_object mode. "
+                "LLM returned empty content. "
                 f"Raw response: {json.dumps(result)[:500]}"
             )
 

py/services/model_cache.py

@@ -1,6 +1,7 @@
 import asyncio
 import time
 import logging
+import random
 
 logger = logging.getLogger(__name__)
 from typing import Any, Dict, List, Optional, Tuple
@@ -38,8 +39,8 @@ class ModelCache:
 
     def __post_init__(self):
         self._lock = asyncio.Lock()
-        # Cache for last sort: (sort_key, order) -> sorted list
+        # Cache for last sort: (sort_key, order, seed) -> sorted list
-        self._last_sort: Tuple[str, str] = (None, None)
+        self._last_sort: Tuple[Optional[str], str, Optional[str]] = (None, "asc", None)
         self._last_sorted_data: List[Dict] = []
         self._normalize_raw_data()
         self.name_display_mode = self._normalize_display_mode(self.name_display_mode)
@@ -203,9 +204,9 @@ class ModelCache:
     async def resort(self):
         """Resort cached data according to last sort mode if set"""
         async with self._lock:
-            if self._last_sort != (None, None):
+            if self._last_sort[0] is not None:
-                sort_key, order = self._last_sort
+                sort_key, order, seed = self._last_sort
-                sorted_data = self._sort_data(self.raw_data, sort_key, order)
+                sorted_data = self._sort_data(self.raw_data, sort_key, order, seed)
                 self._last_sorted_data = sorted_data
                 # Update folder list
             # else: do nothing
@@ -218,7 +219,7 @@ class ModelCache:
             self.folders = sorted(list(all_folders), key=lambda x: x.lower())
             self.rebuild_version_index()
 
-    def _sort_data(self, data: List[Dict], sort_key: str, order: str) -> List[Dict]:
+    def _sort_data(self, data: List[Dict], sort_key: str, order: str, seed: Optional[str] = None) -> List[Dict]:
         """Sort data by sort_key and order"""
         start_time = time.perf_counter()
         reverse = (order == 'desc')
@@ -265,6 +266,13 @@ class ModelCache:
                 ),
                 reverse=reverse
             )
+        elif sort_key == 'random':
+            # Random shuffle seeded for stable pagination: the same seed
+            # always yields the same order, so successive page requests
+            # stay consistent while browsing.
+            rng = random.Random(seed or 'random')
+            result = list(data)
+            rng.shuffle(result)
         elif sort_key == 'versions_count':
             # Pre-dedup sort: fall back to name sort.
             # Actual re-sort by version_count happens in get_paginated_data after dedup.
@@ -285,15 +293,16 @@ class ModelCache:
             logger.debug("ModelCache._sort_data(%s, %s) for %d items took %.3fs", sort_key, order, len(data), duration)
         return result
 
-    async def get_sorted_data(self, sort_key: str = 'name', order: str = 'asc') -> List[Dict]:
+    async def get_sorted_data(self, sort_key: str = 'name', order: str = 'asc', seed: Optional[str] = None) -> List[Dict]:
         """Get sorted data by sort_key and order, using cache if possible"""
         async with self._lock:
-            if (sort_key, order) == self._last_sort:
+            cache_key = (sort_key, order, seed)
+            if cache_key == self._last_sort:
                 return self._last_sorted_data
             
             start_time = time.perf_counter()
-            sorted_data = self._sort_data(self.raw_data, sort_key, order)
+            sorted_data = self._sort_data(self.raw_data, sort_key, order, seed)
-            self._last_sort = (sort_key, order)
+            self._last_sort = cache_key
             self._last_sorted_data = sorted_data
             
             duration = time.perf_counter() - start_time
@@ -313,8 +322,8 @@ class ModelCache:
             self.name_display_mode = normalized
 
             if self._last_sort[0] == 'name':
-                sort_key, order = self._last_sort
+                sort_key, order, seed = self._last_sort
-                self._last_sorted_data = self._sort_data(self.raw_data, sort_key, order)
+                self._last_sorted_data = self._sort_data(self.raw_data, sort_key, order, seed)
 
     async def update_preview_url(self, file_path: str, preview_url: str, preview_nsfw_level: int) -> bool:
         """Update preview_url for a specific model in all cached data

py/services/model_file_service.py

@@ -8,6 +8,7 @@ from abc import ABC, abstractmethod
 from ..utils.utils import calculate_relative_path_for_model, remove_empty_dirs
 from ..utils.constants import AUTO_ORGANIZE_BATCH_SIZE
 from ..services.settings_manager import get_settings_manager
+from ..services.model_lifecycle_service import _require_path_in_library_roots
 
 logger = logging.getLogger(__name__)
 
@@ -493,6 +494,9 @@ class ModelMoveService:
             Dictionary with move result
         """
         try:
+            _require_path_in_library_roots(file_path, self.scanner, label="Source path")
+            _require_path_in_library_roots(target_path, self.scanner, label="Target path")
+
             if use_default_paths:
                 # Find the model in cache to get metadata
                 cache = await self.scanner.get_cached_data()

py/services/model_lifecycle_service.py

@@ -48,6 +48,36 @@ async def delete_model_artifacts(
     return deleted
 
 
+def _require_path_in_library_roots(file_path: str, scanner, *, label: str = "path") -> None:
+    """Raise ``ValueError`` if *file_path* is not inside a configured model root.
+
+    Uses ``os.path.abspath()`` (NOT ``realpath``) to resolve ``..`` and ``.``
+    while preserving symlinks — this keeps the check in business-path space.
+    Skips when the scanner does not expose ``get_model_roots`` or the list
+    is empty.
+    """
+
+    roots = None
+    if hasattr(scanner, "get_model_roots"):
+        try:
+            roots = scanner.get_model_roots()
+        except NotImplementedError:
+            roots = None
+    if not roots:
+        return
+
+    resolved = os.path.abspath(os.path.normpath(file_path))
+
+    for root in roots:
+        root_resolved = os.path.abspath(os.path.normpath(root))
+        if resolved == root_resolved or resolved.startswith(root_resolved + os.sep):
+            return
+
+    raise ValueError(
+        f"{label} '{file_path}' is outside configured library directories"
+    )
+
+
 class ModelLifecycleService:
     """Co-ordinate destructive and mutating model operations."""
 
@@ -74,6 +104,8 @@ class ModelLifecycleService:
         if not file_path:
             raise ValueError("Model path is required")
 
+        _require_path_in_library_roots(file_path, self._scanner, label="File path")
+
         cache = await self._scanner.get_cached_data()
 
         cached_entry = None
@@ -182,6 +214,8 @@ class ModelLifecycleService:
         if not file_path:
             raise ValueError("Model path is required")
 
+        _require_path_in_library_roots(file_path, self._scanner, label="File path")
+
         metadata_path = os.path.splitext(file_path)[0] + ".metadata.json"
         metadata = await self._metadata_loader(metadata_path)
         metadata["exclude"] = True
@@ -229,6 +263,8 @@ class ModelLifecycleService:
         if not file_path:
             raise ValueError("Model path is required")
 
+        _require_path_in_library_roots(file_path, self._scanner, label="File path")
+
         if not os.path.exists(file_path):
             raise ValueError("Model file does not exist")
 
@@ -270,6 +306,9 @@ class ModelLifecycleService:
         if not file_paths:
             raise ValueError("No file paths provided for deletion")
 
+        for path in file_paths:
+            _require_path_in_library_roots(path, self._scanner, label="File path")
+
         return await self._scanner.bulk_delete_models(file_paths)
 
     async def rename_model(
@@ -280,6 +319,8 @@ class ModelLifecycleService:
         if not file_path or not new_file_name:
             raise ValueError("File path and new file name are required")
 
+        _require_path_in_library_roots(file_path, self._scanner, label="File path")
+
         invalid_chars = {"/", "\\", ":", "*", "?", '"', "<", ">", "|"}
         if any(char in new_file_name for char in invalid_chars):
             raise ValueError("Invalid characters in file name")

py/services/model_metadata_provider.py

@@ -143,10 +143,18 @@ class ModelMetadataProvider(ABC):
         pass
 
     @abstractmethod
-    async def get_user_models(self, username: str) -> Optional[List[Dict]]:
+    async def get_user_models(self, username: str, cursor: Optional[str] = None) -> Optional[Dict]:
-        """Fetch models owned by the specified user"""
+        """Fetch one page of models owned by the specified user.
+
+        Returns ``{"items": [...], "nextCursor": <str|None>}`` on success,
+        or None when unsupported/failed. ``cursor`` continues a previous page.
+        """
         pass
 
+    async def get_creator_model_count(self, username: str) -> Optional[int]:
+        """Published model count for the user; None when unsupported."""
+        return None
+
 class CivitaiModelMetadataProvider(ModelMetadataProvider):
     """Provider that uses Civitai API for metadata"""
     
@@ -175,8 +183,11 @@ class CivitaiModelMetadataProvider(ModelMetadataProvider):
     async def get_model_version_info(self, version_id: str) -> Tuple[Optional[Dict], Optional[str]]:
         return await self.client.get_model_version_info(version_id)
 
-    async def get_user_models(self, username: str) -> Optional[List[Dict]]:
+    async def get_user_models(self, username: str, cursor: Optional[str] = None) -> Optional[Dict]:
-        return await self.client.get_user_models(username)
+        return await self.client.get_user_models(username, cursor)
+
+    async def get_creator_model_count(self, username: str) -> Optional[int]:
+        return await self.client.get_creator_model_count(username)
 
 class CivArchiveModelMetadataProvider(ModelMetadataProvider):
     """Provider that uses CivArchive API for metadata"""
@@ -196,7 +207,7 @@ class CivArchiveModelMetadataProvider(ModelMetadataProvider):
     async def get_model_version_info(self, version_id: str) -> Tuple[Optional[Dict], Optional[str]]:
         return await self.client.get_model_version_info(version_id)
 
-    async def get_user_models(self, username: str) -> Optional[List[Dict]]:
+    async def get_user_models(self, username: str, cursor: Optional[str] = None) -> Optional[Dict]:
         """Not supported by CivArchive provider"""
         return None
 
@@ -347,7 +358,7 @@ class SQLiteModelMetadataProvider(ModelMetadataProvider):
             version_data = await self._get_version_with_model_data(db, model_id, version_id)
             return version_data, None
 
-    async def get_user_models(self, username: str) -> Optional[List[Dict]]:
+    async def get_user_models(self, username: str, cursor: Optional[str] = None) -> Optional[Dict]:
         """Listing models by username is not supported for archive database"""
         return None
     
@@ -602,13 +613,14 @@ class FallbackMetadataProvider(ModelMetadataProvider):
                 continue
         return None
 
-    async def get_user_models(self, username: str) -> Optional[List[Dict]]:
+    async def get_user_models(self, username: str, cursor: Optional[str] = None) -> Optional[Dict]:
         for provider, label in self._iter_providers():
             try:
                 result = await self._call_with_rate_limit(
                     label,
                     provider.get_user_models,
                     username,
+                    cursor=cursor,
                 )
                 if result is not None:
                     return result
@@ -624,6 +636,19 @@ class FallbackMetadataProvider(ModelMetadataProvider):
                 continue
         return None
 
+    async def get_creator_model_count(self, username: str) -> Optional[int]:
+        for provider, label in self._iter_providers():
+            try:
+                result = await provider.get_creator_model_count(username)
+                if result is not None:
+                    return result
+            except Exception as e:
+                logger.debug(
+                    "Provider %s failed for get_creator_model_count: %s", label, e
+                )
+                continue
+        return None
+
     def _iter_providers(self):
         return zip(self.providers, self._provider_labels)
 
@@ -704,13 +729,17 @@ class RateLimitRetryingProvider(ModelMetadataProvider):
             version_id,
         )
 
-    async def get_user_models(self, username: str) -> Optional[List[Dict]]:
+    async def get_user_models(self, username: str, cursor: Optional[str] = None) -> Optional[Dict]:
         return await self._rate_limit_helper.run(
             self._label,
             self._provider.get_user_models,
             username,
+            cursor=cursor,
         )
 
+    async def get_creator_model_count(self, username: str) -> Optional[int]:
+        return await self._provider.get_creator_model_count(username)
+
 class ModelMetadataProviderManager:
     """Manager for selecting and using model metadata providers"""
     
@@ -776,10 +805,20 @@ class ModelMetadataProviderManager:
         except NotImplementedError:
             return None
 
-    async def get_user_models(self, username: str, provider_name: str = None) -> Optional[List[Dict]]:
+    async def get_user_models(
-        """Fetch models owned by the specified user"""
+        self,
+        username: str,
+        provider_name: str = None,
+        cursor: Optional[str] = None,
+    ) -> Optional[Dict]:
+        """Fetch one page of models owned by the specified user"""
         provider = self._get_provider(provider_name)
-        return await provider.get_user_models(username)
+        return await provider.get_user_models(username, cursor)
+
+    async def get_creator_model_count(self, username: str, provider_name: str = None) -> Optional[int]:
+        """Best-effort published model count for the specified user"""
+        provider = self._get_provider(provider_name)
+        return await provider.get_creator_model_count(username)
         
     def _get_provider(self, provider_name: str = None) -> ModelMetadataProvider:
         """Get provider by name or default provider"""

py/services/model_query.py

@@ -85,6 +85,7 @@ class SortParams:
 
     key: str
     order: str
+    seed: Optional[str] = None
 
 
 @dataclass(frozen=True)
@@ -116,7 +117,7 @@ class ModelCacheRepository:
     async def fetch_sorted(self, params: SortParams) -> List[Dict[str, Any]]:
         """Fetch cached data pre-sorted according to ``params``."""
         cache = await self.get_cache()
-        return await cache.get_sorted_data(params.key, params.order)
+        return await cache.get_sorted_data(params.key, params.order, params.seed)
 
     @staticmethod
     def parse_sort(sort_by: str) -> SortParams:
@@ -132,10 +133,17 @@ class ModelCacheRepository:
             sort_key = sort_by.strip().lower() or "name"
             order = "asc"
 
-        if order not in ("asc", "desc"):
+        seed = None
+        if sort_key == "random":
+            # Random sort: the portion after ':' is the shuffle seed.
+            # A stable seed keeps paginated requests consistent; order is
+            # meaningless for a random shuffle.
+            seed = order if order and order not in ("asc", "desc") else None
+            order = "asc"
+        elif order not in ("asc", "desc"):
             order = "asc"
 
-        return SortParams(key=sort_key, order=order)
+        return SortParams(key=sort_key, order=order, seed=seed)
 
 
 class ModelFilterSet:

py/services/model_scanner.py

@@ -14,7 +14,7 @@ from ..utils.metadata_manager import MetadataManager
 from ..utils.civitai_utils import resolve_license_info
 from .model_cache import ModelCache
 from .model_hash_index import ModelHashIndex
-from .model_lifecycle_service import delete_model_artifacts
+from .model_lifecycle_service import delete_model_artifacts, _require_path_in_library_roots
 from .service_registry import ServiceRegistry
 from .websocket_manager import ws_manager
 from .persistent_model_cache import get_persistent_cache
@@ -927,6 +927,25 @@ class ModelScanner:
                 # Update cache data
                 self._cache.raw_data = [item for item in self._cache.raw_data if item['file_path'] not in missing_files]
             
+            dedup_removed = 0
+            seen_paths: set = set()
+            deduped: list = []
+            for item in reversed(self._cache.raw_data):
+                path = item.get('file_path', '')
+                if path not in seen_paths:
+                    seen_paths.add(path)
+                    deduped.append(item)
+                else:
+                    for tag in item.get('tags', []):
+                        if tag in self._tags_count:
+                            self._tags_count[tag] = max(0, self._tags_count[tag] - 1)
+                            if self._tags_count[tag] == 0:
+                                del self._tags_count[tag]
+                    dedup_removed += 1
+            if dedup_removed > 0:
+                self._cache.raw_data = list(reversed(deduped))
+                total_removed += dedup_removed
+            
             # Resort cache if changes were made
             if total_added > 0 or total_removed > 0:
                 # Update folders list
@@ -1352,18 +1371,25 @@ class ModelScanner:
             # Update folder in metadata
             metadata_dict['folder'] = folder
             
-            # Add to cache
+            file_path = metadata_dict.get('file_path', '')
+            if file_path:
+                old_entries = [item for item in self._cache.raw_data if item.get('file_path') == file_path]
+                for old_entry in old_entries:
+                    for tag in old_entry.get('tags', []):
+                        if tag in self._tags_count:
+                            self._tags_count[tag] = max(0, self._tags_count[tag] - 1)
+                            if self._tags_count[tag] == 0:
+                                del self._tags_count[tag]
+                self._hash_index.remove_by_path(file_path)
+                self._cache.raw_data = [item for item in self._cache.raw_data if item.get('file_path') != file_path]
+
+            for tag in metadata_dict.get('tags', []):
+                self._tags_count[tag] = self._tags_count.get(tag, 0) + 1
+
             self._cache.raw_data.append(metadata_dict)
-            self._cache.add_to_version_index(metadata_dict)
 
-            # Resort cache data
             await self._cache.resort()
             
-            # Update folders list
-            all_folders = set(self._cache.folders)
-            all_folders.add(folder)
-            self._cache.folders = sorted(list(all_folders), key=lambda x: x.lower())
-            
             # Update the hash index
             self._hash_index.add_entry(metadata_dict['sha256'], metadata_dict['file_path'])
             await self._persist_current_cache()
@@ -1395,6 +1421,9 @@ class ModelScanner:
             base_name = os.path.splitext(os.path.basename(source_path))[0]
             source_dir = os.path.dirname(source_path)
 
+            _require_path_in_library_roots(source_path, self, label="Source path")
+            _require_path_in_library_roots(target_path, self, label="Target path")
+            
             os.makedirs(target_path, exist_ok=True)
             
             def get_source_hash():
@@ -1723,7 +1752,7 @@ class ModelScanner:
         # ---- Conditional resort (only when sort-key fields changed) ----
         need_resort = False
         _last = cache._last_sort
-        sort_key: Optional[str] = _last[0] if _last != (None, None) else None
+        sort_key: Optional[str] = _last[0] if _last[0] is not None else None
         if sort_key == "name":
             if (
                 old_model_name != desired_entry.get("model_name", "")
@@ -1971,6 +2000,8 @@ class ModelScanner:
                     break
 
                 try:
+                    _require_path_in_library_roots(file_path, self, label="File path")
+
                     target_dir = os.path.dirname(file_path)
                     base_name = os.path.basename(file_path)
                     file_name, main_extension = os.path.splitext(base_name)

py/services/recipe_scanner.py

@@ -21,7 +21,7 @@ from .checkpoint_scanner import CheckpointScanner
 from .settings_manager import get_settings_manager
 from .recipes.errors import RecipeNotFoundError
 from ..utils.civitai_utils import extract_civitai_image_id
-from ..utils.utils import calculate_recipe_fingerprint, fuzzy_match
+from ..utils.utils import calculate_recipe_fingerprint
 from natsort import natsorted
 import sys
 import re
@@ -1020,13 +1020,16 @@ class RecipeScanner:
 
         try:
             result = self._fts_index.search(search, fields)
-            # Return None if empty to trigger fuzzy fallback
+            # Return empty set for empty FTS results — do NOT fall back to
-            # Empty FTS results may indicate query syntax issues or need for fuzzy matching
+            # Python fuzzy matching, which freezes the server with 10k+ recipes.
+            # FTS5 prefix matching with unicode61 tokenizer correctly handles
+            # compound tokens (e.g. "illustrious" matches "path/illustrious/model").
+            # If FTS returns nothing, there are genuinely no matching recipes.
             if not result:
-                return None
+                return set()
             return result
         except Exception as exc:
-            logger.debug("FTS search failed, falling back to fuzzy search: %s", exc)
+            logger.debug("FTS search failed, falling back to title-only search: %s", exc)
             return None
 
     def _update_fts_index_for_recipe(
@@ -2079,49 +2082,14 @@ class RecipeScanner:
                         if str(item.get("id", "")) in fts_matching_ids
                     ]
                 else:
-                    # Fallback to fuzzy_match (slower but always available)
+                    # FTS index not yet built — return empty rather than
-                    # Build the search predicate based on search options
+                    # scanning 42k+ items in Python. The FTS background build
-                    def matches_search(item):
+                    # finishes in seconds; by the time a user navigates here
-                        # Search in title if enabled
+                    # and types a search, it is already available.
-                        if search_options.get("title", True):
+                    logger.debug(
-                            if fuzzy_match(str(item.get("title", "")), search):
+                        "FTS index not ready — search '%s' returning empty", search
-                                return True
+                    )
-
+                    filtered_data = []
-                        # Search in tags if enabled
-                        if search_options.get("tags", True) and "tags" in item:
-                            for tag in item["tags"]:
-                                if fuzzy_match(tag, search):
-                                    return True
-
-                        # Search in lora file names if enabled
-                        if search_options.get("lora_name", True) and "loras" in item:
-                            for lora in item["loras"]:
-                                if fuzzy_match(str(lora.get("file_name", "")), search):
-                                    return True
-
-                        # Search in lora model names if enabled
-                        if search_options.get("lora_model", True) and "loras" in item:
-                            for lora in item["loras"]:
-                                if fuzzy_match(str(lora.get("modelName", "")), search):
-                                    return True
-
-                        # Search in prompt and negative_prompt if enabled
-                        if search_options.get("prompt", True) and "gen_params" in item:
-                            gen_params = item["gen_params"]
-                            if fuzzy_match(str(gen_params.get("prompt", "")), search):
-                                return True
-                            if fuzzy_match(
-                                str(gen_params.get("negative_prompt", "")), search
-                            ):
-                                return True
-
-                        # No match found
-                        return False
-
-                    # Filter the data using the search predicate
-                    filtered_data = [
-                        item for item in filtered_data if matches_search(item)
-                    ]
 
             # Apply additional filters
             if filters:

py/services/use_cases/bulk_metadata_refresh_use_case.py

@@ -126,6 +126,7 @@ class BulkMetadataRefreshUseCase:
                         if sha256:
                             model["sha256"] = sha256
                             model["hash_status"] = "completed"
+                            hash_status = "completed"
                         else:
                             self._logger.error(f"Failed to calculate hash for {file_path}")
                             failures.append({"name": model.get("model_name", file_path or "Unknown"), "error": "Failed to calculate hash"})
@@ -148,6 +149,16 @@ class BulkMetadataRefreshUseCase:
                     continue
 
                 await MetadataManager.hydrate_model_data(model)
+
+                # hydrate_model_data replaces model with .metadata.json content,
+                # which may lack sha256. Restore from cache and persist the fix.
+                if not model.get("sha256"):
+                    model["sha256"] = sha256
+                    model["hash_status"] = model.get("hash_status", hash_status)
+                    data_to_save = model.copy()
+                    data_to_save.pop("folder", None)
+                    await MetadataManager.save_metadata(file_path, data_to_save)
+
                 result, error_msg = await self._metadata_sync.fetch_and_update_model(
                     sha256=model["sha256"],
                     file_path=model["file_path"],

py/services/wildcard_service.py

@@ -19,7 +19,7 @@ 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+$")
-_WEIGHTED_OPTION_PATTERN = re.compile(r"^\s*([0-9.]+)::")
+_WEIGHTED_OPTION_PATTERN = re.compile(r"^\s*-?\d+(\.\d+)?::")
 _NUMERIC_PATTERN = re.compile(r"^-?\d+(\.\d+)?$")
 
 
@@ -390,7 +390,7 @@ class WildcardService:
     ) -> str | None:
         keyword = _normalize_wildcard_key(raw_key)
         if keyword in wildcard_dict:
-            return rng.choice(wildcard_dict[keyword])
+            return self._pick_weighted_or_plain(wildcard_dict[keyword], rng)
 
         if "*" in keyword:
             regex_pattern = keyword.replace("*", ".*").replace("+", r"\+")
@@ -400,7 +400,7 @@ class WildcardService:
                 if compiled.match(key):
                     aggregated.extend(values)
             if aggregated:
-                return rng.choice(aggregated)
+                return self._pick_weighted_or_plain(aggregated, rng)
 
         if "/" not in keyword:
             fallback_keyword = _normalize_wildcard_key(f"*/{keyword}")
@@ -409,6 +409,39 @@ class WildcardService:
 
         return None
 
+    def _pick_weighted_or_plain(
+        self, values: list[str], rng: random.Random
+    ) -> str:
+        """Pick a value from the list, respecting N::weight prefix if present.
+
+        When any value in the list uses the ``N::value`` weighted syntax with a
+        weight different from 1, the pick uses weighted random selection.  When
+        no such weighting is present, a plain ``rng.choice`` is used (preserving
+        backward compatibility for unweighted wildcard files).
+
+        In either case the ``N::`` prefix is always stripped from the returned
+        value, matching the behaviour of ``{...}`` option groups.
+        """
+        # Fast path: skip weighting logic entirely when no :: syntax exists
+        if not any("::" in v for v in values):
+            return rng.choice(values)
+
+        weighted_options: list[tuple[float, str]] = []
+        for value in values:
+            weight = 1.0
+            parts = value.split("::", 1)
+            if len(parts) == 2 and _is_numeric_string(parts[0].strip()):
+                weight = float(parts[0].strip())
+            weighted_options.append((weight, value))
+
+        any_weighted = any(w != 1.0 for w, _ in weighted_options)
+        if any_weighted:
+            picked = self._weighted_choice(weighted_options, rng)
+        else:
+            picked = rng.choice(values)
+
+        return self._strip_weight_prefix(picked)
+
 
 def is_trigger_words_input(name: str) -> bool:
     return bool(_TRIGGER_WORD_PATTERN.match(name))

py/utils/constants.py

@@ -12,6 +12,7 @@ NODE_TYPES = {
     "Lora Loader (LoraManager)": 1,
     "Lora Stacker (LoraManager)": 2,
     "WanVideo Lora Select (LoraManager)": 3,
+    "Create Hook LoRA (LoraManager)": 4,
 }
 
 # Default ComfyUI node color when bgcolor is null

py/utils/example_images_download_manager.py

@@ -14,11 +14,16 @@ from ..services.service_registry import ServiceRegistry
 from ..utils.example_images_paths import (
     ExampleImagePathResolver,
     ensure_library_root_exists,
+    get_example_images_root,
+    is_hash_folder,
     uses_library_scoped_folders,
 )
 from ..utils.metadata_manager import MetadataManager
 from .example_images_processor import ExampleImagesProcessor
-from .example_images_metadata import MetadataUpdater
+from .example_images_metadata import (
+    MetadataUpdater,
+    update_cache_from_metadata,
+)
 from ..services.downloader import get_downloader
 from ..services.settings_manager import get_settings_manager
 
@@ -87,6 +92,13 @@ class _DownloadProgress(dict):
         return snapshot
 
 
+# When fewer candidates than this remain in check_pending_models, probe each
+# model folder directly (preserving legacy-folder migration semantics). Above
+# it, build a folder index with a single directory scan so libraries with
+# 100k+ models do not pay one syscall per candidate.
+_BULK_LOOKUP_THRESHOLD = 1000
+
+
 def _model_directory_has_files(path: str) -> bool:
     """Return True when the provided directory exists and contains entries."""
 
@@ -103,6 +115,36 @@ def _model_directory_has_files(path: str) -> bool:
     return False
 
 
+def _build_example_folder_index(output_dir: str) -> dict[str, bool]:
+    """Build a ``{hash: has_files}`` index for a library's example-image folders.
+
+    A single directory scan over the library root replaces ``O(candidates)``
+    per-folder ``os.scandir`` calls, which is required for libraries with
+    100k+ models. Each hash folder is classified by whether it contains any
+    entries, matching the semantics of ``_model_directory_has_files``.
+    """
+
+    index: dict[str, bool] = {}
+    if not output_dir or not os.path.isdir(output_dir):
+        return index
+
+    try:
+        with os.scandir(output_dir) as entries:
+            for entry in entries:
+                name = entry.name
+                if not entry.is_dir() or not is_hash_folder(name):
+                    continue
+                try:
+                    with os.scandir(entry.path) as subentries:
+                        index[name.lower()] = any(subentries)
+                except OSError:
+                    index[name.lower()] = False
+    except OSError:
+        pass
+
+    return index
+
+
 class DownloadManager:
     """Manages downloading example images for models."""
 
@@ -130,6 +172,7 @@ class DownloadManager:
         model_types = data.get("model_types", ["lora", "checkpoint"])
         delay = float(data.get("delay", 0.2))
         force = data.get("force", False)
+        model_hashes = data.get("model_hashes", [])
 
         # Step 2: Validate configuration (fast lookup)
         settings_manager = get_settings_manager()
@@ -199,6 +242,7 @@ class DownloadManager:
                         delay,
                         active_library,
                         force,
+                        model_hashes,
                     )
                 )
 
@@ -410,14 +454,49 @@ class DownloadManager:
             # Calculate pending count: check which models actually need processing.
             # A model is pending if it has a hash, is not already processed or known-failed,
             # and its folder doesn't exist or is empty.
-            pending_hashes = set()
+            candidate_hashes = [
-            for model_hash, model_name in all_models_with_hash:
+                model_hash
-                if model_hash not in processed_models and model_hash not in failed_models:
+                for model_hash, _ in all_models_with_hash
+                if model_hash not in processed_models
+                and model_hash not in failed_models
+            ]
+
+            pending_hashes: set[str] = set()
+            # For small candidate counts the existing per-folder check is fine
+            # and handles legacy folder migration.
+            # For large libraries, scan the library root once and do set lookups.
+            if len(candidate_hashes) <= _BULK_LOOKUP_THRESHOLD or not output_dir:
+                for model_hash in candidate_hashes:
                     model_dir = ExampleImagePathResolver.get_model_folder(
                         model_hash, active_library
                     )
                     if not _model_directory_has_files(model_dir):
                         pending_hashes.add(model_hash)
+            else:
+                folder_index = await asyncio.get_event_loop().run_in_executor(
+                    None, _build_example_folder_index, output_dir
+                )
+                # In multi-library mode, folders that have not been consolidated
+                # into the library root yet (startup migration skipped, failed
+                # move, or created at the legacy path afterwards) still live at
+                # the legacy root/<hash> location. Only scan that root when at
+                # least one candidate is missing from the library-root index, so
+                # the fully-consolidated case does not pay an extra directory
+                # pass on every call.
+                if uses_library_scoped_folders() and any(
+                    not folder_index.get(model_hash, False)
+                    for model_hash in candidate_hashes
+                ):
+                    legacy_root = get_example_images_root()
+                    if legacy_root and legacy_root != output_dir:
+                        legacy_index = await asyncio.get_event_loop().run_in_executor(
+                            None, _build_example_folder_index, legacy_root
+                        )
+                        for hash_key, has_files in legacy_index.items():
+                            folder_index.setdefault(hash_key, has_files)
+                for model_hash in candidate_hashes:
+                    if not folder_index.get(model_hash, False):
+                        pending_hashes.add(model_hash)
 
             pending_count = len(pending_hashes)
 
@@ -500,8 +579,9 @@ class DownloadManager:
         delay,
         library_name,
         force: bool = False,
+        model_hashes: list[str] | None = None,
     ):
-        """Download example images for all models."""
+        """Download example images for all models (or only the given hashes)."""
 
         downloader = await get_downloader()
 
@@ -529,6 +609,18 @@ class DownloadManager:
                         if model.get("sha256"):
                             all_models.append((scanner_type, model, scanner))
 
+            # Restrict to the requested hashes when provided (empty = all models).
+            # Explicit targets are a directed user request, so previously failed
+            # models are retried instead of skipped.
+            explicit_targets = bool(model_hashes)
+            if model_hashes:
+                hash_set = {h.lower() for h in model_hashes}
+                all_models = [
+                    (scanner_type, model, scanner)
+                    for scanner_type, model, scanner in all_models
+                    if model.get("sha256", "").lower() in hash_set
+                ]
+
             # Update total count
             self._progress["total"] = len(all_models)
             logger.debug(f"Found {self._progress['total']} models to process")
@@ -552,6 +644,7 @@ class DownloadManager:
                     downloader,
                     library_name,
                     force,
+                    explicit_targets,
                 )
 
                 # Update progress
@@ -648,6 +741,7 @@ class DownloadManager:
         downloader,
         library_name,
         force: bool = False,
+        explicit_targets: bool = False,
     ):
         """Process a single model download."""
 
@@ -670,8 +764,9 @@ class DownloadManager:
             self._progress["current_model"] = f"{model_name} ({model_hash[:8]})"
             await self._broadcast_progress(status="running")
 
-            # Skip if already in failed models (unless force mode is enabled)
+            # Skip if already in failed models (unless force mode is enabled or
-            if not force and model_hash in self._progress["failed_models"]:
+            # the model was explicitly targeted by hash)
+            if not force and not explicit_targets and model_hash in self._progress["failed_models"]:
                 logger.debug(f"Skipping known failed model: {model_name}")
                 return False
 
@@ -680,30 +775,34 @@ class DownloadManager:
             )
             existing_files = _model_directory_has_files(model_dir)
 
-            # Skip if already processed AND directory exists with files
+            # Model-level guard: a populated folder counts as done. Explicitly
-            if model_hash in self._progress["processed_models"]:
+            # targeted models bypass it so the per-image existence pre-check can
-                if existing_files:
+            # fill individual gaps without re-fetching existing files.
-                    logger.debug(f"Skipping already processed model: {model_name}")
+            if not explicit_targets:
+                # Skip if already processed AND directory exists with files
+                if model_hash in self._progress["processed_models"]:
+                    if existing_files:
+                        logger.debug(f"Skipping already processed model: {model_name}")
+                        return False
+
+                    logger.debug(
+                        "Model %s (%s) marked as processed but folder empty or missing, reprocessing triggered",
+                        model_name,
+                        model_hash,
+                    )
+                    # Track that we are reprocessing this model for summary logging
+                    self._progress["reprocessed_models"].add(model_hash)
+                    # Remove from processed models since we need to reprocess
+                    self._progress["processed_models"].discard(model_hash)
+
+                if existing_files and model_hash not in self._progress["processed_models"]:
+                    logger.debug(
+                        "Model folder already populated for %s, marking as processed without download",
+                        model_name,
+                    )
+                    self._progress["processed_models"].add(model_hash)
                     return False
 
-                logger.debug(
-                    "Model %s (%s) marked as processed but folder empty or missing, reprocessing triggered",
-                    model_name,
-                    model_hash,
-                )
-                # Track that we are reprocessing this model for summary logging
-                self._progress["reprocessed_models"].add(model_hash)
-                # Remove from processed models since we need to reprocess
-                self._progress["processed_models"].discard(model_hash)
-
-            if existing_files and model_hash not in self._progress["processed_models"]:
-                logger.debug(
-                    "Model folder already populated for %s, marking as processed without download",
-                    model_name,
-                )
-                self._progress["processed_models"].add(model_hash)
-                return False
-
             if not model_dir:
                 logger.warning(
                     "Unable to resolve example images folder for model %s (%s)",
@@ -807,7 +906,7 @@ class DownloadManager:
                         model_name,
                     )
                     # Clear failed_models so non-force runs can retry
-                    if force and model_hash in self._progress["failed_models"]:
+                    if (force or explicit_targets) and model_hash in self._progress["failed_models"]:
                         self._progress["failed_models"].discard(model_hash)
                         logger.info(
                             f"Removed {model_name} from failed_models after force retry with rate-limited images"
@@ -827,7 +926,7 @@ class DownloadManager:
                     )
                 elif success:
                     self._progress["processed_models"].add(model_hash)
-                    if force and model_hash in self._progress["failed_models"]:
+                    if (force or explicit_targets) and model_hash in self._progress["failed_models"]:
                         self._progress["failed_models"].discard(model_hash)
                         logger.info(
                             f"Removed {model_name} from failed_models after successful force retry"
@@ -1343,8 +1442,8 @@ class DownloadManager:
                 await MetadataManager.save_metadata(file_path, model_copy)
 
                 try:
-                    await scanner.update_single_model_cache(
+                    await update_cache_from_metadata(
-                        file_path, file_path, model_data
+                        scanner, file_path, model_copy
                     )
                 except AttributeError:
                     logger.debug(

py/utils/example_images_metadata.py

@@ -1,3 +1,4 @@
+import inspect
 import logging
 import os
 import re
@@ -28,6 +29,31 @@ if TYPE_CHECKING:  # pragma: no cover - import for type checkers only
     from ..services.settings_manager import SettingsManager
 
 
+async def update_cache_from_metadata(
+    scanner: Any, file_path: str, metadata: Dict[str, Any]
+) -> bool:
+    """Update the scanner cache from a metadata dict using the in-place sync path.
+
+    ``sync_cache_from_metadata`` patches the existing cache entry incrementally
+    (tag/hash/version indexes, targeted single-row SQL update) and only resorts
+    when a sort-key field changed. This avoids the ``O(n)`` full-list resort and
+    full cache rewrite that ``update_single_model_cache`` performs on every call,
+    which is critical for libraries with 100k+ models.
+
+    Falls back to the legacy full update when the scanner does not expose an
+    async ``sync_cache_from_metadata`` method.
+
+    Returns:
+        ``True`` if the cache entry was updated, ``False`` otherwise.
+    """
+
+    sync_method = getattr(scanner, "sync_cache_from_metadata", None)
+    if inspect.iscoroutinefunction(sync_method):
+        return await sync_method(file_path, metadata)
+
+    return await scanner.update_single_model_cache(file_path, file_path, metadata)
+
+
 def _build_metadata_sync_service(settings_manager: "SettingsManager") -> MetadataSyncService:
     """Construct a metadata sync service bound to the provided settings."""
 
@@ -103,7 +129,7 @@ class MetadataUpdater:
                 progress['refreshed_models'].add(model_hash)
             
             async def update_cache_func(old_path, new_path, metadata):
-                return await scanner.update_single_model_cache(old_path, new_path, metadata)
+                return await update_cache_from_metadata(scanner, new_path, metadata)
 
             await MetadataManager.hydrate_model_data(model_data)
             success, error = await _get_metadata_sync_service().fetch_and_update_model(
@@ -234,6 +260,7 @@ class MetadataUpdater:
                 
                 # Save metadata to .metadata.json file
                 file_path = model.get('file_path')
+                model_copy: Optional[Dict[str, Any]] = None
                 try:
                     model_copy = model.copy()
                     model_copy.pop('folder', None)
@@ -242,13 +269,17 @@ class MetadataUpdater:
                 except Exception as e:
                     logger.error(f"Failed to save metadata for {model.get('model_name')}: {str(e)}")
 
-                # Save updated metadata to scanner cache
+                # Save updated metadata to scanner cache. sync_cache_from_metadata
-                success = await scanner.update_single_model_cache(file_path, file_path, model)
+                # returns False both for "already in sync" and for actual failures,
-                if success:
+                # so the cache sync result is deliberately not treated as an error;
+                # the return value reflects whether the metadata was persisted.
+                if file_path and model_copy is not None:
+                    await update_cache_from_metadata(scanner, file_path, model_copy)
                     logger.info(f"Successfully updated metadata for {model.get('model_name')} with {len(images)} local examples")
                     return True
-                else:
+
-                    logger.warning(f"Failed to update metadata for {model.get('model_name')}")
+                logger.warning(f"Failed to update metadata for {model.get('model_name')}")
+                return False
             
             return False
         except Exception as e:
@@ -336,6 +367,7 @@ class MetadataUpdater:
             
             # Save metadata to .metadata.json file
             file_path = model_data.get('file_path')
+            model_copy: Optional[Dict[str, Any]] = None
             if file_path:
                 try:
                     model_copy = model_data.copy()
@@ -346,8 +378,8 @@ class MetadataUpdater:
                     logger.error(f"Failed to save metadata: {str(e)}")
 
             # Save updated metadata to scanner cache
-            if file_path:
+            if file_path and model_copy is not None:
-                await scanner.update_single_model_cache(file_path, file_path, model_data)
+                await update_cache_from_metadata(scanner, file_path, model_copy)
 
             # Get regular images array (might be None)
             regular_images = civitai_data.get('images', [])
@@ -475,13 +507,19 @@ class MetadataUpdater:
             return False
 
         model_folder = get_model_folder(model_hash)
-        if not model_folder:
+        if not model_folder or not os.path.isdir(model_folder):
             return False
 
         civitai = getattr(metadata, "civitai", None)
         if not isinstance(civitai, dict):
             return False
 
+        # Read the directory listing once so every image entry reuses it.
+        try:
+            dir_entries = os.listdir(model_folder)
+        except OSError:
+            dir_entries = []
+
         has_changes = False
 
         custom_images = civitai.get("customImages")
@@ -493,24 +531,15 @@ class MetadataUpdater:
                 if not img_id:
                     continue
 
-                if not os.path.isdir(model_folder):
+                prefix = f"custom_{img_id}"
+                found = any(
+                    f.startswith(prefix) and os.path.isfile(
+                        os.path.join(model_folder, f)
+                    )
+                    for f in dir_entries
+                )
+                if not found:
                     stale.append(idx)
-                else:
-                    found = False
-                    try:
-                        prefix = f"custom_{img_id}"
-                        for fname in os.listdir(model_folder):
-                            if fname.startswith(prefix) and os.path.isfile(
-                                os.path.join(model_folder, fname)
-                            ):
-                                found = True
-                                break
-                    except OSError:
-                        stale.append(idx)
-                        continue
-
-                    if not found:
-                        stale.append(idx)
 
             if stale:
                 for idx in reversed(stale):
@@ -532,22 +561,9 @@ class MetadataUpdater:
                     # is gone.
                     continue
 
-                if not os.path.isdir(model_folder):
+                prefix = f"image_{idx}."
+                if not any(f.startswith(prefix) for f in dir_entries):
                     stale.append(idx)
-                else:
-                    found = False
-                    try:
-                        prefix = f"image_{idx}."
-                        for fname in os.listdir(model_folder):
-                            if fname.startswith(prefix):
-                                found = True
-                                break
-                    except OSError:
-                        stale.append(idx)
-                        continue
-
-                    if not found:
-                        stale.append(idx)
 
             if stale:
                 for idx in reversed(stale):

py/utils/example_images_migration.py

@@ -3,11 +3,19 @@ import logging
 import os
 import re
 import json
+import shutil
 from ..services.settings_manager import get_settings_manager
 from ..services.service_registry import ServiceRegistry
-from ..utils.example_images_paths import iter_library_roots
+from ..utils.example_images_paths import (
+    get_example_images_root,
+    is_hash_folder,
+    iter_library_roots,
+    uses_library_scoped_folders,
+    _library_folder_has_only_hash_dirs,
+)
 from ..utils.metadata_manager import MetadataManager
 from ..utils.example_images_processor import ExampleImagesProcessor
+from ..utils.example_images_metadata import update_cache_from_metadata
 from ..utils.constants import SUPPORTED_MEDIA_EXTENSIONS
 
 logger = logging.getLogger(__name__)
@@ -36,6 +44,90 @@ settings = _SettingsProxy()
 class ExampleImagesMigration:
     """Handles migrations for example images naming conventions"""
     
+    @staticmethod
+    def _consolidate_library_folders():
+        """Move hash folders from library-named subdirectories back to root.
+
+        When a user switches from multi-library mode back to single-library
+        mode, example images previously stored under e.g.
+        ``<root>/default/<hash>/`` need to be moved back to
+        ``<root>/<hash>/``.  Running this once at startup removes the need
+        for ``get_model_folder()`` to perform directory scans on every
+        request.
+        """
+        if uses_library_scoped_folders():
+            return
+
+        root = get_example_images_root()
+        if not root or not os.path.isdir(root):
+            return
+
+        moved: list[str] = []
+        cleaned: list[str] = []
+
+        try:
+            for entry in os.listdir(root):
+                # Fast regex checks first — no filesystem I/O.
+                if is_hash_folder(entry) or entry == "_deleted":
+                    continue
+
+                entry_path = os.path.join(root, entry)
+                if not os.path.isdir(entry_path):
+                    continue
+                if not _library_folder_has_only_hash_dirs(entry_path):
+                    continue
+
+                try:
+                    for hash_entry in os.listdir(entry_path):
+                        hash_path = os.path.join(entry_path, hash_entry)
+                        if not os.path.isdir(hash_path) or not is_hash_folder(hash_entry):
+                            continue
+                        target = os.path.join(root, hash_entry)
+                        if not os.path.exists(target):
+                            try:
+                                shutil.move(hash_path, target)
+                                moved.append(hash_entry)
+                            except (OSError, shutil.Error) as exc:
+                                logger.error(
+                                    "Failed to move '%s' → '%s': %s",
+                                    hash_path, target, exc,
+                                )
+                except OSError as exc:
+                    logger.error(
+                        "Failed to list library subdirectory '%s': %s",
+                        entry_path, exc,
+                    )
+
+                try:
+                    remaining = os.listdir(entry_path)
+                except OSError:
+                    remaining = []
+                if not remaining:
+                    try:
+                        os.rmdir(entry_path)
+                        cleaned.append(entry)
+                    except OSError as exc:
+                        logger.debug(
+                            "Could not remove empty library dir '%s': %s",
+                            entry_path, exc,
+                        )
+        except OSError as exc:
+            logger.error(
+                "Failed to list example images root during consolidation: %s",
+                exc,
+            )
+
+        if moved:
+            logger.info(
+                "Consolidated %d example image folder(s) to root",
+                len(moved),
+            )
+        if cleaned:
+            logger.info(
+                "Removed %d empty library directories",
+                len(cleaned),
+            )
+
     @staticmethod
     async def check_and_run_migrations():
         """Check if migrations are needed and run them in background"""
@@ -44,6 +136,10 @@ class ExampleImagesMigration:
             logger.debug("No example images path configured or path doesn't exist, skipping migrations")
             return
 
+        # Run library-to-root consolidation once at startup so the hot
+        # path (get_model_folder) stays a pure-path computation.
+        ExampleImagesMigration._consolidate_library_folders()
+
         for library_name, library_path in iter_library_roots():
             if not library_path or not os.path.exists(library_path):
                 continue
@@ -326,7 +422,7 @@ class ExampleImagesMigration:
                         await MetadataManager.save_metadata(file_path, model_copy)
                         
                         # Update scanner cache
-                        await scanner.update_single_model_cache(file_path, file_path, model_metadata)
+                        await update_cache_from_metadata(scanner, file_path, model_copy)
                         
                         updated_models += 1
                     except Exception as e:

py/utils/example_images_paths.py

@@ -83,7 +83,12 @@ def ensure_library_root_exists(library_name: Optional[str] = None) -> str:
 
 
 def get_model_folder(model_hash: str, library_name: Optional[str] = None) -> str:
-    """Return the folder path for a model's example images."""
+    """Return the folder path for a model's example images.
+
+    Multi-library ↔ single-library consolidation is handled once at startup by
+    ``ExampleImagesMigration._consolidate_library_folders`` — this function is a
+    pure path computation on the hot path (no directory scans).
+    """
 
     if not model_hash:
         return ""
@@ -113,35 +118,6 @@ def get_model_folder(model_hash: str, library_name: Optional[str] = None) -> str
                     exc,
                 )
                 return legacy_folder
-    elif not os.path.exists(resolved_folder):
-        # Reverse migration: when consolidating from multi-library to
-        # single-library mode (e.g. after "default" was cleaned up), look
-        # for existing example images inside library-named subdirectories
-        # and bring them back to the root level.
-        root = get_example_images_root()
-        if root:
-            try:
-                for entry in os.listdir(root):
-                    entry_path = os.path.join(root, entry)
-                    if not os.path.isdir(entry_path):
-                        continue
-                    if is_hash_folder(entry) or entry == "_deleted":
-                        continue
-                    if not _library_folder_has_only_hash_dirs(entry_path):
-                        continue
-                    legacy = os.path.join(entry_path, normalized_hash)
-                    if os.path.exists(legacy):
-                        shutil.move(legacy, resolved_folder)
-                        logger.info(
-                            "Consolidated example images from '%s' to '%s'",
-                            legacy, resolved_folder,
-                        )
-                        break
-            except OSError as exc:
-                logger.error(
-                    "Failed to consolidate example images during "
-                    "library merge: %s", exc,
-                )
 
     return resolved_folder
 

py/utils/example_images_processor.py

@@ -9,7 +9,7 @@ from ..utils.constants import SUPPORTED_MEDIA_EXTENSIONS
 from ..services.service_registry import ServiceRegistry
 from ..services.settings_manager import get_settings_manager
 from ..utils.example_images_paths import get_model_folder, get_model_relative_path
-from .example_images_metadata import MetadataUpdater
+from .example_images_metadata import MetadataUpdater, update_cache_from_metadata
 from ..utils.metadata_manager import MetadataManager
 
 logger = logging.getLogger(__name__)
@@ -113,6 +113,26 @@ class ExampleImagesProcessor:
         message = str(error).lower()
         return '404' in message or 'file not found' in message
 
+    @staticmethod
+    def _example_image_file_exists(model_dir: str, index: int, media_type_hint: str | None = None) -> bool:
+        """Return True when the file that would be written for a media index already exists.
+
+        The final filename (``image_{index}{extension}``) depends on the downloaded
+        content, so the extension cannot be known ahead of time. The post-download
+        check skips the write when the exact target file exists; this pre-check
+        approximates that with the candidate extensions for the media type (videos
+        only when the metadata hints at a video) so the network request is avoided
+        for files that already exist on disk.
+        """
+        if media_type_hint == "video":
+            extensions = SUPPORTED_MEDIA_EXTENSIONS['videos']
+        else:
+            extensions = SUPPORTED_MEDIA_EXTENSIONS['images']
+        return any(
+            os.path.exists(os.path.join(model_dir, f"image_{index}{ext}"))
+            for ext in extensions
+        )
+
     @staticmethod
     async def download_model_images(model_hash, model_name, model_images, model_dir, optimize, downloader):
         """Download images for a single model
@@ -140,6 +160,11 @@ class ExampleImagesProcessor:
             if optimize and 'civitai.com' in image_url:
                 image_url = ExampleImagesProcessor.get_civitai_optimized_url(image_url)
 
+            # Skip the download when the file already exists on disk
+            if ExampleImagesProcessor._example_image_file_exists(model_dir, i, image.get("type")):
+                logger.debug("File already exists, skipping download for %s", image_url)
+                continue
+
             # Download the file first to determine the actual file type
             try:
                 logger.debug(f"Downloading media file {i} for {model_name}")
@@ -229,6 +254,11 @@ class ExampleImagesProcessor:
             if optimize and 'civitai.com' in image_url:
                 image_url = ExampleImagesProcessor.get_civitai_optimized_url(image_url)
 
+            # Skip the download when the file already exists on disk
+            if ExampleImagesProcessor._example_image_file_exists(model_dir, i, image.get("type")):
+                logger.debug("File already exists, skipping download for %s", image_url)
+                continue
+
             async def _attempt_download() -> tuple:
                 logger.debug("Downloading media file %s for %s", i, model_name)
                 return await downloader.download_to_memory(
@@ -644,7 +674,7 @@ class ExampleImagesProcessor:
                     }, status=500)
             
                 # Update cache
-                await scanner.update_single_model_cache(file_path, file_path, model_data)
+                await update_cache_from_metadata(scanner, file_path, model_data)
             
             # Get regular images array (might be None)
             regular_images = civitai_data.get('images', [])
@@ -759,7 +789,7 @@ class ExampleImagesProcessor:
                 model_copy = model_data.copy()
                 model_copy.pop('folder', None)
                 await MetadataManager.save_metadata(file_path, model_copy)
-                await scanner.update_single_model_cache(file_path, file_path, model_data)
+                await update_cache_from_metadata(scanner, file_path, model_copy)
 
             return web.json_response({
                 'success': True,

py/utils/utils.py

@@ -1,7 +1,7 @@
 from difflib import SequenceMatcher
 import os
 import re
-from typing import Dict
+from typing import Any, Dict, List, Optional
 from ..services.service_registry import ServiceRegistry
 from ..config import config
 from ..services.settings_manager import get_settings_manager
@@ -294,6 +294,53 @@ def _format_model_name_for_comfyui(file_path: str, model_roots: list) -> str:
     return os.path.basename(file_path)
 
 
+def model_patcher_to_name(model_patcher: Any) -> Optional[str]:
+    """Extract a ComfyUI-style model name from a MODEL (ModelPatcher) object.
+
+    Core ComfyUI loaders record the absolute weight file path on the patcher's
+    ``cached_patcher_init`` attribute:
+      - load_checkpoint_guess_config -> (fn, (ckpt_path, ...), index)
+      - load_diffusion_model -> (fn, (unet_path, model_options))
+    Patcher clones (LoRA loaders, model merges, ...) preserve the attribute,
+    so the name is recoverable anywhere downstream of a core loader — including
+    from LoRA Manager's own loaders (CheckpointLoaderLM / UNETLoaderLM), which
+    call the same core load functions.
+
+    The absolute path is converted to the ComfyUI-style relative name used by
+    the metadata pipeline (covering standard ComfyUI roots and LoRA Manager
+    extra folder paths).
+
+    Returns None when the path cannot be recovered (e.g. third-party loaders
+    that never set ``cached_patcher_init``).
+    """
+    init = getattr(model_patcher, "cached_patcher_init", None)
+    if not isinstance(init, (tuple, list)) or len(init) < 2:
+        return None
+    args = init[1]
+    abs_path = args[0] if args else None
+    if not isinstance(abs_path, str) or not abs_path:
+        return None
+    return _abs_model_path_to_name(abs_path)
+
+
+def _abs_model_path_to_name(abs_path: str) -> str:
+    """Convert an absolute model path to a ComfyUI-style relative name.
+
+    Tries standard ComfyUI model roots plus LoRA Manager extra folder paths;
+    falls back to the bare filename.
+    """
+    try:
+        roots: List[str] = list(config.base_models_roots or [])
+        roots.extend(config.extra_checkpoints_roots or [])
+        roots.extend(config.extra_unet_roots or [])
+        formatted = _format_model_name_for_comfyui(abs_path, roots)
+        if formatted:
+            return formatted
+    except Exception:
+        pass
+    return os.path.basename(abs_path)
+
+
 def fuzzy_match(text: str, pattern: str, threshold: float = 0.85) -> bool:
     """
     Check if text matches pattern using fuzzy matching.
@@ -488,6 +535,12 @@ def calculate_relative_path_for_model(
     if model_type == "embedding":
         formatted_path = formatted_path.replace(" ", "_")
 
+    # Sanitize the resolved path to prevent path traversal
+    formatted_path = formatted_path.lstrip("/")
+    while "//" in formatted_path:
+        formatted_path = formatted_path.replace("//", "/")
+    formatted_path = formatted_path.rstrip("/")
+
     return formatted_path
 
 

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-lora-manager"
 description = "Revolutionize your workflow with the ultimate LoRA companion for ComfyUI!"
-version = "1.1.8"
+version = "1.2.0"
 license = {file = "LICENSE"}
 dependencies = [
     "aiohttp",

static/css/components/modal/_base.css

@@ -151,6 +151,7 @@ body.modal-open {
 .support-section,
 .changelog-section,
 .update-info,
+.update-channels,
 .info-item,
 .path-preview {
     background: var(--surface-subtle);

static/css/components/modal/update-modal.css

@@ -93,15 +93,13 @@
 .update-content {
     display: flex;
     flex-direction: column;
-    gap: var(--space-3);
+    gap: var(--space-2);
 }
 
 .update-info {
     display: flex;
     justify-content: space-between;
     align-items: center;
-    border-radius: var(--border-radius-sm);
-    padding: var(--space-3);
 }
 
 .update-info .version-info {
@@ -175,7 +173,6 @@
     border: 1px solid var(--lora-border);
     border-radius: var(--border-radius-sm);
     padding: var(--space-2);
-    margin: var(--space-2) 0;
 }
 
 [data-theme="dark"] .update-progress {
@@ -233,11 +230,6 @@
 }
 
 /* Changelog section */
-.changelog-section {
-    border-radius: var(--border-radius-sm);
-    padding: var(--space-3);
-}
-
 .changelog-section h3 {
     margin-top: 0;
     margin-bottom: var(--space-2);
@@ -349,6 +341,131 @@
     text-decoration: underline;
 }
 
+/* Channel Toggle */
+.update-channels {
+}
+
+.channels-label {
+    font-size: 0.9em;
+    color: var(--text-color);
+    opacity: 0.8;
+    margin-bottom: 8px;
+}
+
+.channel-toggle {
+    display: flex;
+    gap: 0;
+    background: var(--lora-surface);
+    border-radius: 8px;
+    padding: 3px;
+    width: fit-content;
+}
+
+.channel-btn {
+    display: flex;
+    align-items: center;
+    gap: 6px;
+    padding: 8px 20px;
+    border: none;
+    border-radius: 6px;
+    background: transparent;
+    color: var(--text-secondary, #999);
+    cursor: pointer;
+    font-size: 0.9em;
+    font-weight: 500;
+    transition: all 0.2s ease;
+    white-space: nowrap;
+}
+
+.channel-btn:hover {
+    color: var(--text-primary, #ddd);
+    background: rgba(255, 255, 255, 0.04);
+}
+
+.channel-btn.active {
+    background: var(--lora-accent, #4285F4);
+    color: #fff;
+    box-shadow: 0 1px 3px rgba(0, 0, 0, 0.2);
+}
+
+.channel-btn.active i {
+    color: #fff;
+}
+
+.channel-btn i {
+    font-size: 0.85em;
+}
+
+/* Channel Switch Confirmation Overlay */
+.channel-switch-overlay {
+    position: fixed;
+    inset: 0;
+    background: rgba(0, 0, 0, 0.6);
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    z-index: 10000;
+    backdrop-filter: blur(2px);
+}
+
+.channel-switch-dialog {
+    background: var(--lora-surface);
+    border: 1px solid var(--border-color, rgba(255, 255, 255, 0.1));
+    border-radius: 12px;
+    padding: 28px 32px;
+    max-width: 420px;
+    width: 90%;
+    box-shadow: 0 8px 32px rgba(0, 0, 0, 0.4);
+}
+
+.channel-switch-dialog h3 {
+    margin: 0 0 12px;
+    font-size: 1.1em;
+    color: var(--text-primary, #eee);
+}
+
+.channel-switch-dialog p {
+    margin: 0 0 24px;
+    font-size: 0.9em;
+    color: var(--text-secondary, #aaa);
+    line-height: 1.6;
+}
+
+.channel-switch-actions {
+    display: flex;
+    justify-content: flex-end;
+    gap: 10px;
+}
+
+.channel-switch-cancel {
+    padding: 8px 18px;
+    border: 1px solid var(--border-color, rgba(255, 255, 255, 0.1));
+    border-radius: 6px;
+    background: transparent;
+    color: var(--text-secondary, #aaa);
+    cursor: pointer;
+    font-size: 0.9em;
+}
+
+.channel-switch-cancel:hover {
+    background: rgba(255, 255, 255, 0.04);
+}
+
+.channel-switch-confirm {
+    padding: 8px 18px;
+    border: none;
+    border-radius: 6px;
+    background: var(--lora-accent, #4285F4);
+    color: #fff;
+    cursor: pointer;
+    font-size: 0.9em;
+    font-weight: 500;
+}
+
+.channel-switch-confirm:hover {
+    opacity: 0.9;
+}
+
 /* Update preferences section */
 .update-preferences {
     border-top: 1px solid var(--lora-border);

static/js/api/apiConfig.js

@@ -49,10 +49,6 @@ export const MODEL_CONFIG = {
  * @returns {Object} Object containing all API endpoints for the model type
  */
 export function getApiEndpoints(modelType) {
-    if (!Object.values(MODEL_TYPES).includes(modelType)) {
-        throw new Error(`Invalid model type: ${modelType}`);
-    }
-
     return {
         // Base CRUD operations
         list: `/api/lm/${modelType}/list`,
@@ -188,7 +184,8 @@ export const DOWNLOAD_ENDPOINTS = {
     downloadGet: '/api/lm/download-model-get',
     cancelGet: '/api/lm/cancel-download-get',
     progress: '/api/lm/download-progress',
-    exampleImages: '/api/lm/force-download-example-images' // New endpoint for downloading example images
+    exampleImages: '/api/lm/force-download-example-images', // Re-process example images ignoring previous status
+    exampleImagesMissing: '/api/lm/download-example-images' // Download only missing example images
 };
 
 // Hugging Face API endpoints

static/js/api/baseModelApi.js

@@ -1641,7 +1641,7 @@ export class BaseModelApiClient {
         }
     }
 
-    async downloadExampleImages(modelHashes, modelTypes = null) {
+    async downloadExampleImages(modelHashes, modelTypes = null, { force = true } = {}) {
         let ws = null;
 
         await state.loadingManager.showWithProgress(async (loading) => {
@@ -1700,8 +1700,13 @@ export class BaseModelApiClient {
                 // Determine optimize setting
                 const optimize = state.global?.settings?.optimize_example_images ?? true;
 
+                // force=false routes to the regular endpoint, which skips already-processed models
+                const endpoint = force
+                    ? DOWNLOAD_ENDPOINTS.exampleImages
+                    : DOWNLOAD_ENDPOINTS.exampleImagesMissing;
+
                 // Make the API request to start the download process
-                const response = await fetch(DOWNLOAD_ENDPOINTS.exampleImages, {
+                const response = await fetch(endpoint, {
                     method: 'POST',
                     headers: {
                         'Content-Type': 'application/json'
@@ -1710,6 +1715,7 @@ export class BaseModelApiClient {
                         model_hashes: modelHashes,
                         output_dir: outputDir,
                         optimize: optimize,
+                        force: force,
                         model_types: modelTypes || [this.apiConfig.config.singularName]
                     })
                 });

static/js/components/ContextMenu/BulkContextMenu.js

@@ -137,11 +137,10 @@ export class BulkContextMenu extends BaseContextMenu {
             downloadMissingLorasItem.style.display = currentModelType === 'recipes' ? 'flex' : 'none';
         }
 
-        const downloadExampleImagesItem = this.menu.querySelector('[data-action="download-example-images"]');
+        const downloadExampleImagesSubmenu = this.menu.querySelector('[data-has-submenu="download-example-images"]');
-        if (downloadExampleImagesItem) {
+        if (downloadExampleImagesSubmenu) {
             // Show on model pages (loras, checkpoints, embeddings), hide on recipes
-            const modelPages = ['loras', 'checkpoints', 'embeddings'];
+            downloadExampleImagesSubmenu.style.display = ['loras', 'checkpoints', 'embeddings'].includes(currentModelType) ? 'flex' : 'none';
-            downloadExampleImagesItem.style.display = modelPages.includes(currentModelType) ? 'flex' : 'none';
         }
 
         const skipMetadataRefreshItem = this.menu.querySelector('[data-action="skip-metadata-refresh"]');
@@ -294,8 +293,11 @@ export class BulkContextMenu extends BaseContextMenu {
             case 'download-missing-loras':
                 this.handleDownloadMissingLoras();
                 break;
+            case 'download-missing-example-images':
+                this.handleDownloadExampleImages({ force: false });
+                break;
             case 'download-example-images':
-                this.handleDownloadExampleImages();
+                this.handleDownloadExampleImages({ force: true });
                 break;
             case 'clear':
                 bulkManager.clearSelection();
@@ -340,7 +342,7 @@ export class BulkContextMenu extends BaseContextMenu {
         await bulkMissingLoraDownloadManager.downloadMissingLoras(selectedRecipes);
     }
 
-    async handleDownloadExampleImages() {
+    async handleDownloadExampleImages({ force = true } = {}) {
         if (state.selectedModels.size === 0) {
             return;
         }
@@ -361,7 +363,7 @@ export class BulkContextMenu extends BaseContextMenu {
 
         try {
             const apiClient = getModelApiClient();
-            await apiClient.downloadExampleImages([...hashes]);
+            await apiClient.downloadExampleImages([...hashes], null, { force });
         } catch (error) {
             console.error('Bulk download example images failed:', error);
         }

static/js/components/ContextMenu/ModelContextMenuMixin.js

@@ -347,7 +347,10 @@ export const ModelContextMenuMixin = {
                 openExampleImagesFolder(this.currentCard.dataset.sha256);
                 return true;
             case 'download-examples':
-                this.downloadExampleImages();
+                this.downloadExampleImages(false);
+                return true;
+            case 'download-examples-force':
+                this.downloadExampleImages(true);
                 return true;
             case 'civitai':
                 if (this.currentCard.dataset.from_civitai === 'true') {
@@ -378,7 +381,7 @@ export const ModelContextMenuMixin = {
     },
 
     // Download example images method
-    async downloadExampleImages() {
+    async downloadExampleImages(force = false) {
         const modelHash = this.currentCard.dataset.sha256;
         if (!modelHash) {
             showToast('toast.contextMenu.missingHash', {}, 'error');
@@ -387,7 +390,7 @@ export const ModelContextMenuMixin = {
 
         try { 
             const apiClient = getModelApiClient();
-            await apiClient.downloadExampleImages([modelHash]);
+            await apiClient.downloadExampleImages([modelHash], null, { force });
         } catch (error) {
             console.error('Error downloading example images:', error);
         }

static/js/components/ContextMenu/RecipeContextMenu.js

@@ -260,8 +260,9 @@ export class RecipeContextMenu extends BaseContextMenu {
                         strength: lora.strength || 1.0,
 
                         // Model identifiers
+                        modelId: lora.modelId || lora.model_id || civitaiInfo.modelId,
                         hash: modelFile?.hashes?.SHA256?.toLowerCase() || lora.hash,
-                        modelVersionId: civitaiInfo.id || lora.modelVersionId,
+                        id: civitaiInfo.id || lora.modelVersionId,
 
                         // Metadata
                         thumbnailUrl: civitaiInfo.images?.[0]?.url || '',

static/js/components/RecipeModal.js

@@ -1421,6 +1421,7 @@ class RecipeModal {
                         strength: lora.strength || 1.0,
 
                         // Model identifiers
+                        modelId: lora.modelId || lora.model_id || civitaiInfo.modelId,
                         hash: modelFile?.hashes?.SHA256?.toLowerCase() || lora.hash,
                         id: civitaiInfo.id || lora.modelVersionId,
 

static/js/components/controls/PageControls.js

@@ -108,10 +108,20 @@ export class PageControls {
         const sortSelect = document.getElementById('sortSelect');
         if (sortSelect) {
             initSortDropdown(sortSelect);
-            sortSelect.value = this.pageState.sortBy;
+            this.applySortToSelect(this.pageState.sortBy);
             sortSelect.addEventListener('change', async (e) => {
-                this.pageState.sortBy = e.target.value;
+                let value = e.target.value;
-                this.saveSortPreference(e.target.value);
+                if (value.startsWith('random')) {
+                    // Every pick of Random reshuffles the list: generate a
+                    // fresh seed so the backend keeps a stable order across
+                    // paginated requests.
+                    value = this._randomizeSortValue();
+                }
+                this.pageState.sortBy = value;
+                this.saveSortPreference(value);
+                // Reset the seeded Random option when switching away from
+                // Random, or re-apply the fresh seed when picking it again.
+                this.applySortToSelect(value);
                 await this.resetAndReload();
             });
         }
@@ -312,6 +322,44 @@ export class PageControls {
         }
     }
     
+    /**
+     * Apply a sort value to the native sort <select>, keeping the Random
+     * option's value in sync when the persisted value carries a seed
+     * (e.g. "random:abc123"). Must be used instead of assigning
+     * sortSelect.value directly whenever the value may be a seeded random
+     * sort, otherwise the native select has no matching option.
+     * @param {string} sortValue - Sort value like "name:asc" or "random:<seed>"
+     */
+    applySortToSelect(sortValue) {
+        const sortSelect = document.getElementById('sortSelect');
+        if (!sortSelect) return;
+        const randomOpt = sortSelect.querySelector('option[value="random"], option[value^="random:"]');
+        if (randomOpt) {
+            randomOpt.value = String(sortValue).startsWith('random') ? sortValue : 'random';
+        }
+        sortSelect.value = sortValue;
+    }
+
+    /**
+     * Generate a fresh seeded random sort value ("random:<seed>") and keep
+     * the native <select> in sync so its value matches the persisted sort
+     * string and the dropdown shows the selected label.
+     * @returns {string} The new sort value, e.g. "random:abc123xyz"
+     */
+    _randomizeSortValue() {
+        const seed = Math.random().toString(36).slice(2, 12);
+        const value = `random:${seed}`;
+        const sortSelect = document.getElementById('sortSelect');
+        if (sortSelect) {
+            const randomOpt = sortSelect.querySelector('option[value="random"], option[value^="random:"]');
+            if (randomOpt) {
+                randomOpt.value = value;
+            }
+            sortSelect.value = value;
+        }
+        return value;
+    }
+
     /**
      * Load sort preference from storage
      */
@@ -326,10 +374,7 @@ export class PageControls {
             // Handle legacy format conversion
             const convertedSort = this.convertLegacySortFormat(savedSort);
             this.pageState.sortBy = convertedSort;
-            const sortSelect = document.getElementById('sortSelect');
+            this.applySortToSelect(convertedSort);
-            if (sortSelect) {
-                sortSelect.value = convertedSort;
-            }
         }
     }
     
@@ -523,9 +568,9 @@ export class PageControls {
         this.pageState.sortBy = restoredSort;
         this.saveSortPreference(restoredSort);
         this._removeVlmSortOption();
+        this.applySortToSelect(restoredSort);
         const sortSelect = document.getElementById('sortSelect');
         if (sortSelect) {
-            sortSelect.value = restoredSort;
             sortSelect.disabled = false;
         }
     }
@@ -575,10 +620,7 @@ export class PageControls {
             const savedGroupedSort = getStorageItem(groupedKey);
             if (savedGroupedSort) {
                 this.pageState.sortBy = savedGroupedSort;
-                const sortSelect = document.getElementById('sortSelect');
+                this.applySortToSelect(savedGroupedSort);
-                if (sortSelect) {
-                    sortSelect.value = savedGroupedSort;
-                }
             }
         } else {
             // Leaving group mode: persist current sort for next time, restore non-group sort
@@ -586,10 +628,7 @@ export class PageControls {
             const savedNormalSort = getStorageItem(`${this.pageType}_sort`);
             if (savedNormalSort) {
                 this.pageState.sortBy = savedNormalSort;
-                const sortSelect = document.getElementById('sortSelect');
+                this.applySortToSelect(savedNormalSort);
-                if (sortSelect) {
-                    sortSelect.value = savedNormalSort;
-                }
             }
         }
     }
@@ -874,7 +913,7 @@ export class PageControls {
         }
 
         if (sortSelect) {
-            sortSelect.value = this.pageState.sortBy;
+            this.applySortToSelect(this.pageState.sortBy);
         }
         if (searchInput) {
             searchInput.value = this.pageState.filters?.search || '';

static/js/components/controls/SortDropdown.js

@@ -96,7 +96,16 @@ export function initSortDropdown(select) {
     };
 
     const choose = (value) => {
-        if (select.value === value) return;
+        if (select.value === value) {
+            // Re-picking the already-selected option is normally a no-op,
+            // matching native <select> behavior. The seeded Random sort is
+            // the exception: clicking it again should reshuffle, so let the
+            // change handler (PageControls) generate a fresh seed.
+            if (String(value).startsWith('random')) {
+                select.dispatchEvent(new Event('change', { bubbles: true }));
+            }
+            return;
+        }
         select.value = value;
         select.dispatchEvent(new Event('change', { bubbles: true }));
     };
@@ -277,9 +286,10 @@ export function initSortDropdown(select) {
     }
 
     // Rebuild the menu when <option>s change (VLM adds/removes a temporary
-    // option at runtime).
+    // option at runtime, and the seeded Random sort option gets a new value
+    // attribute each time it is picked).
     const observer = new MutationObserver(() => buildMenu());
-    observer.observe(select, { childList: true });
+    observer.observe(select, { childList: true, subtree: true, attributes: true, attributeFilter: ['value'] });
 
     buildMenu();
     group.dataset.sortReady = '1';

static/js/components/shared/ModelCard.js

@@ -489,6 +489,12 @@ export function createModelCard(model, modelType) {
     const modelId = civitaiData?.modelId ?? civitaiData?.model_id;
     if (modelId !== undefined && modelId !== null && modelId !== '') {
         card.dataset.modelId = modelId;
+    } else if (model.hf_url) {
+        // For HF-only models, derive a group key from hf_url for version grouping
+        const match = model.hf_url.match(/https?:\/\/huggingface\.co\/([^/]+\/[^/]+)/);
+        if (match) {
+            card.dataset.modelId = 'hf:' + match[1];
+        }
     }
 
     // LoRA specific data

static/js/components/shared/ModelModal.js

@@ -473,7 +473,14 @@ export async function showModelModal(model, modelType) {
     const loadingExamplesText = translate('modals.model.loading.examples', {}, 'Loading examples...');
 
     const loadingVersionsText = translate('modals.model.loading.versions', {}, 'Loading versions...');
-    const civitaiModelId = modelWithFullData.civitai?.modelId || '';
+    // Use CivitAI modelId, or derive HF group key for HF-only models
+    let civitaiModelId = modelWithFullData.civitai?.modelId || '';
+    if (!civitaiModelId && modelWithFullData.hf_url) {
+        const match = modelWithFullData.hf_url.match(/https?:\/\/huggingface\.co\/([^/]+\/[^/]+)/);
+        if (match) {
+            civitaiModelId = 'hf:' + match[1];
+        }
+    }
     const civitaiVersionId = modelWithFullData.civitai?.id || '';
     const navAriaLabel = translate('modals.model.navigation.label', {}, 'Model navigation');
     const previousTitle = translate('modals.model.navigation.previousWithShortcut', {}, 'Previous model (←)');
@@ -885,7 +892,8 @@ function setupEventHandlers(filePath, modelType) {
             case 'view-creator':
                 const username = target.dataset.username;
                 if (username) {
-                    window.open(`https://civitai.com/user/${username}`, '_blank');
+                    const host = state.global.settings.civitai_host || 'civitai.com';
+                    window.open(`https://${host}/user/${username}`, '_blank');
                 }
                 break;
             case 'open-file-location':

static/js/components/shared/ModelVersionsTab.js

@@ -950,6 +950,26 @@ export function initVersionsTab({
             renderErrorState(container, translate('modals.model.versions.missingModelId', {}, 'This model is missing a Civitai model id.'));
             return;
         }
+        // HF group keys (e.g. "hf:user/repo") are not real CivitAI model IDs —
+        // skip the remote API call and show a helpful message instead.
+        const isHfGroupKey = typeof modelId === 'string' && modelId.startsWith('hf:');
+        if (isHfGroupKey) {
+            controller.isLoading = false;
+            controller.hasLoaded = true;
+            controller.record = null;
+            const hfMsg = translate(
+                'modals.model.versions.hfGroupInfo',
+                {},
+                'This is a HuggingFace model group. Open the library to see all versions in the grid.'
+            );
+            container.innerHTML = `
+                <div class="versions-empty-state">
+                    <i class="fas fa-info-circle"></i>
+                    <p>${escapeHtml(hfMsg)}</p>
+                </div>
+            `;
+            return;
+        }
         if (controller.hasLoaded && !forceRefresh) {
             return;
         }

static/js/managers/BulkManager.js

@@ -27,6 +27,8 @@ export class BulkManager {
 
         // Drag detection properties
         this.dragThreshold = 5; // Pixels to move before considering it a drag
+        this.dragDelayMs = 100; // Minimum hold time before a drag is treated as a marquee
+        this.minMarqueeSize = 10; // Minimum drag box (px) before a marquee counts as a selection
         this.mouseDownTime = 0;
         this.mouseDownPosition = { x: 0, y: 0 };
 
@@ -88,7 +90,7 @@ export class BulkManager {
                 moveAll: true,
                 autoOrganize: false,
                 deleteAll: true,
-                setContentRating: false,
+                setContentRating: true,
                 skipMetadataRefresh: false,
                 setFavorite: true,
                 unfavorite: true,
@@ -173,6 +175,19 @@ export class BulkManager {
         });
 
         eventManager.addHandler('mousemove', 'bulkManager-marquee-move', (e) => {
+            // Only track marquee/drag while the left button is physically held.
+            // mouseup can be missed (release outside the window, focus loss, driver quirks),
+            // so mousemove must verify the button state itself instead of relying on it.
+            if (!(e.buttons & 1)) {
+                if (this.isMarqueeActive) {
+                    this.endMarqueeSelection(e);
+                } else {
+                    this.mouseDownTime = 0;
+                    this.isDragging = false;
+                }
+                return false;
+            }
+
             if (this.isMarqueeActive) {
                 this.lastClientX = e.clientX;
                 this.lastClientY = e.clientY;
@@ -184,7 +199,10 @@ export class BulkManager {
                 const dy = e.clientY - this.mouseDownPosition.y;
                 const distance = Math.sqrt(dx * dx + dy * dy);
 
-                if (distance >= this.dragThreshold) {
+                // Require both enough movement AND enough hold time so quick
+                // click jitter from micro-movement input devices is not a marquee.
+                const heldTime = Date.now() - this.mouseDownTime;
+                if (heldTime >= this.dragDelayMs && distance >= this.dragThreshold) {
                     this.isDragging = true;
                     this.startMarqueeSelection(e, true);
                 }
@@ -1510,14 +1528,18 @@ export class BulkManager {
         let failureCount = 0;
 
         try {
-            const apiClient = getModelApiClient();
+            const isRecipesPage = state.currentPageType === 'recipes';
             for (const filePath of targets) {
                 if (cancelled) {
                     showToast('toast.api.operationCancelled', {}, 'info');
                     break;
                 }
                 try {
-                    await apiClient.saveModelMetadata(filePath, { preview_nsfw_level: level });
+                    if (isRecipesPage) {
+                        await updateRecipeMetadata(filePath, { preview_nsfw_level: level });
+                    } else {
+                        await getModelApiClient().saveModelMetadata(filePath, { preview_nsfw_level: level });
+                    }
                     successCount++;
                 } catch (error) {
                     failureCount++;
@@ -1958,9 +1980,31 @@ export class BulkManager {
         // Remove visual feedback class
         document.body.classList.remove('marquee-selecting');
 
+        // Compute the actual drag box size in document coordinates, matching how
+        // updateMarqueeSelectionFromPosition tracks the rectangle. Client-space
+        // size would wrongly flag auto-scroll marquees (tiny pointer movement,
+        // large document-space box) as accidental clicks.
+        const container = document.querySelector('.page-content');
+        const scrollX = container?.scrollLeft || 0;
+        const scrollY = container?.scrollTop || 0;
+        const dragWidth = Math.abs((e.clientX + scrollX) - this.marqueeStartDoc.x);
+        const dragHeight = Math.abs((e.clientY + scrollY) - this.marqueeStartDoc.y);
+        const isTinyMarquee = dragWidth < this.minMarqueeSize && dragHeight < this.minMarqueeSize;
+
         // Get selection count
         const selectionCount = state.selectedModels.size;
 
+        // A tiny box (e.g. click jitter that happened to graze a card) is treated
+        // as an accidental click: undo any selection and leave bulk mode.
+        if (isTinyMarquee) {
+            this.clearSelection();
+            if (state.bulkMode) {
+                this.toggleBulkMode();
+            }
+            this.initialSelectedModels.clear();
+            return;
+        }
+
         // If no models were selected, exit bulk mode
         if (selectionCount === 0) {
             if (state.bulkMode) {

static/js/managers/DownloadManager.js

@@ -158,6 +158,7 @@ export class DownloadManager {
         this.modelVersionId = null;
         this.source = null;
         this.selectedFile = null;
+        this._isDiffusionModel = false;
 
         this.selectedFolder = '';
         this.batchModels = [];
@@ -787,24 +788,40 @@ export class DownloadManager {
     async proceedToLocationContent() {
 
         try {
-            // Fetch model roots
+            const _isDiffusionModel = this.selectedFile
-            const rootsData = await this.apiClient.fetchModelRoots();
+                ? (this.selectedFile.type === 'UNet' || this.selectedFile.type === 'Diffusion Model')
+                : (this.currentVersion?.files || []).some(
+                    f => f.type === 'UNet' || f.type === 'Diffusion Model'
+                );
+            this._isDiffusionModel = _isDiffusionModel;
+
+            let rootsData;
+            if (this._isDiffusionModel && this.apiClient.modelType === 'checkpoints') {
+                rootsData = await this.apiClient.fetchModelRoots('diffusion_model');
+            } else {
+                rootsData = await this.apiClient.fetchModelRoots();
+            }
             const modelRoot = document.getElementById('modelRoot');
             modelRoot.innerHTML = rootsData.roots.map(root =>
                 `<option value="${root}">${root}</option>`
             ).join('');
 
-            // Set default root if available
+            const singularType = this._isDiffusionModel
-            const singularType = this.apiClient.modelType.replace(/s$/, '');
+                ? 'unet'
+                : this.apiClient.modelType.replace(/s$/, '');
             const defaultRootKey = `default_${singularType}_root`;
             const defaultRoot = state.global.settings[defaultRootKey];
-            console.log(`Default root for ${this.apiClient.modelType}:`, defaultRoot);
+            console.log(`Default root for ${singularType}:`, defaultRoot);
             console.log('Available roots:', rootsData.roots);
             if (defaultRoot && rootsData.roots.includes(defaultRoot)) {
                 console.log(`Setting default root: ${defaultRoot}`);
                 modelRoot.value = defaultRoot;
             }
 
+            const subtypeDisplay = this._isDiffusionModel ? 'Diffusion Model' : this.apiClient.apiConfig.config.displayName;
+            document.getElementById('modelRootLabel').textContent =
+                translate('modals.download.selectTypeRoot', { type: subtypeDisplay });
+
             // Set autocomplete="off" on folderPath input
             const folderPathInput = document.getElementById('folderPath');
             if (folderPathInput) {
@@ -1776,13 +1793,15 @@ export class DownloadManager {
         const modelRoot = document.getElementById('modelRoot').value;
         const config = this.apiClient.apiConfig.config;
 
-        let fullPath = modelRoot || translate('modals.download.selectTypeRoot', { type: config.displayName });
+        const subtypeDisplay = this._isDiffusionModel ? 'Diffusion Model' : config.displayName;
+        let fullPath = modelRoot || translate('modals.download.selectTypeRoot', { type: subtypeDisplay });
 
         if (modelRoot) {
             if (this.useDefaultPath) {
-                // Show actual template path
                 try {
-                    const singularType = this.apiClient.modelType.replace(/s$/, '');
+                    const singularType = this._isDiffusionModel
+                        ? 'unet'
+                        : this.apiClient.modelType.replace(/s$/, '');
                     const templates = state.global.settings.download_path_templates;
                     const template = templates[singularType];
                     fullPath += `/${template}`;

static/js/managers/FilterManager.js

@@ -729,10 +729,12 @@ export class FilterManager {
         const pageState = getCurrentPageState();
         const storageKey = `${this.currentPage}_filters`;
 
-        // Save filters to localStorage (exclude EMPTY_WILDCARD_MARKER)
+        // Save filters to localStorage (exclude EMPTY_WILDCARD_MARKER and transient search)
         const filtersSnapshot = this.cloneFilters();
         // Don't persist EMPTY_WILDCARD_MARKER - it's a runtime-only marker
         filtersSnapshot.baseModel = filtersSnapshot.baseModel.filter(m => m !== EMPTY_WILDCARD_MARKER);
+        // Don't persist search - it's transient and managed by SearchManager
+        delete filtersSnapshot.search;
         setStorageItem(storageKey, filtersSnapshot);
 
         // Update state with current filters
@@ -984,6 +986,7 @@ export class FilterManager {
     }
 
     cloneFilters() {
+        const pageState = getCurrentPageState();
         return {
             ...this.filters,
             baseModel: [...(this.filters.baseModel || [])],
@@ -991,7 +994,8 @@ export class FilterManager {
             autoTags: { ...(this.filters.autoTags || {}) },
             license: { ...(this.filters.license || {}) },
             modelTypes: [...(this.filters.modelTypes || [])],
-            tagLogic: this.filters.tagLogic || 'any'
+            tagLogic: this.filters.tagLogic || 'any',
+            search: pageState?.filters?.search ?? ''
         };
     }
 

static/js/managers/SettingsManager.js

@@ -1517,11 +1517,20 @@ export class SettingsManager {
         return data;
     }
 
-    async loadLoraRoots() {
+    showNoRootsPlaceholder(select) {
-        try {
+        select.innerHTML = '';
-            const defaultLoraRootSelect = document.getElementById('defaultLoraRoot');
+        const option = document.createElement('option');
-            if (!defaultLoraRootSelect) return;
+        option.value = '';
+        option.textContent = translate('settings.folderSettings.noDefault', {}, 'No Default');
+        select.appendChild(option);
+        select.disabled = true;
+    }
 
+    async loadLoraRoots() {
+        const defaultLoraRootSelect = document.getElementById('defaultLoraRoot');
+        if (!defaultLoraRootSelect) return;
+
+        try {
             // Fetch lora roots
             const response = await fetch('/api/lm/loras/roots');
             if (!response.ok) {
@@ -1530,10 +1539,12 @@ export class SettingsManager {
 
             const data = await response.json();
             if (!data.roots || data.roots.length === 0) {
-                throw new Error('No LoRA roots found');
+                this.showNoRootsPlaceholder(defaultLoraRootSelect);
+                return;
             }
 
             defaultLoraRootSelect.innerHTML = '';
+            defaultLoraRootSelect.disabled = false;
 
             // Add options for each root
             data.roots.forEach(root => {
@@ -1548,15 +1559,16 @@ export class SettingsManager {
 
         } catch (error) {
             console.error('Error loading LoRA roots:', error);
+            this.showNoRootsPlaceholder(defaultLoraRootSelect);
             showToast('toast.settings.loraRootsFailed', { message: error.message }, 'error');
         }
     }
 
     async loadCheckpointRoots() {
-        try {
+        const defaultCheckpointRootSelect = document.getElementById('defaultCheckpointRoot');
-            const defaultCheckpointRootSelect = document.getElementById('defaultCheckpointRoot');
+        if (!defaultCheckpointRootSelect) return;
-            if (!defaultCheckpointRootSelect) return;
 
+        try {
             // Fetch checkpoint roots (checkpoint paths only, not unet)
             const response = await fetch('/api/lm/checkpoints/checkpoints_roots');
             if (!response.ok) {
@@ -1565,10 +1577,12 @@ export class SettingsManager {
 
             const data = await response.json();
             if (!data.roots || data.roots.length === 0) {
-                throw new Error('No checkpoint roots found');
+                this.showNoRootsPlaceholder(defaultCheckpointRootSelect);
+                return;
             }
 
             defaultCheckpointRootSelect.innerHTML = '';
+            defaultCheckpointRootSelect.disabled = false;
 
             // Add options for each root
             data.roots.forEach(root => {
@@ -1583,15 +1597,16 @@ export class SettingsManager {
 
         } catch (error) {
             console.error('Error loading checkpoint roots:', error);
+            this.showNoRootsPlaceholder(defaultCheckpointRootSelect);
             showToast('toast.settings.checkpointRootsFailed', { message: error.message }, 'error');
         }
     }
 
     async loadUnetRoots() {
-        try {
+        const defaultUnetRootSelect = document.getElementById('defaultUnetRoot');
-            const defaultUnetRootSelect = document.getElementById('defaultUnetRoot');
+        if (!defaultUnetRootSelect) return;
-            if (!defaultUnetRootSelect) return;
 
+        try {
             // Fetch unet roots (diffusion model paths only)
             const response = await fetch('/api/lm/checkpoints/unet_roots');
             if (!response.ok) {
@@ -1600,10 +1615,12 @@ export class SettingsManager {
 
             const data = await response.json();
             if (!data.roots || data.roots.length === 0) {
-                throw new Error('No diffusion model roots found');
+                this.showNoRootsPlaceholder(defaultUnetRootSelect);
+                return;
             }
 
             defaultUnetRootSelect.innerHTML = '';
+            defaultUnetRootSelect.disabled = false;
 
             // Add options for each root
             data.roots.forEach(root => {
@@ -1618,15 +1635,16 @@ export class SettingsManager {
 
         } catch (error) {
             console.error('Error loading diffusion model roots:', error);
+            this.showNoRootsPlaceholder(defaultUnetRootSelect);
             showToast('toast.settings.unetRootsFailed', { message: error.message }, 'error');
         }
     }
 
     async loadEmbeddingRoots() {
-        try {
+        const defaultEmbeddingRootSelect = document.getElementById('defaultEmbeddingRoot');
-            const defaultEmbeddingRootSelect = document.getElementById('defaultEmbeddingRoot');
+        if (!defaultEmbeddingRootSelect) return;
-            if (!defaultEmbeddingRootSelect) return;
 
+        try {
             // Fetch embedding roots
             const response = await fetch('/api/lm/embeddings/roots');
             if (!response.ok) {
@@ -1635,10 +1653,12 @@ export class SettingsManager {
 
             const data = await response.json();
             if (!data.roots || data.roots.length === 0) {
-                throw new Error('No embedding roots found');
+                this.showNoRootsPlaceholder(defaultEmbeddingRootSelect);
+                return;
             }
 
             defaultEmbeddingRootSelect.innerHTML = '';
+            defaultEmbeddingRootSelect.disabled = false;
 
             // Add options for each root
             data.roots.forEach(root => {
@@ -1653,6 +1673,7 @@ export class SettingsManager {
 
         } catch (error) {
             console.error('Error loading embedding roots:', error);
+            this.showNoRootsPlaceholder(defaultEmbeddingRootSelect);
             showToast('toast.settings.embeddingRootsFailed', { message: error.message }, 'error');
         }
     }

static/js/managers/UpdateService.js

@@ -6,6 +6,7 @@ import {
     setStoredVersionInfo,
     isVersionMatch
 } from '../utils/storageHelpers.js';
+import { state } from '../state/index.js';
 import { bannerService } from './BannerService.js';
 import { translate } from '../utils/i18nHelpers.js';
 
@@ -24,7 +25,11 @@ export class UpdateService {
         this.updateNotificationsEnabled = getStorageItem('show_update_notifications', true);
         this.lastCheckTime = parseInt(getStorageItem('last_update_check') || '0');
         this.isUpdating = false;
-        this.nightlyMode = getStorageItem('nightly_updates', false);
+        this.channelMode = null;
+        this.hasGit = false;
+        this.nightlyNotifyDate = getStorageItem('nightly_notify_date', '');
+        this.nightlyBadgeShown = false;
+        this.progressKeepVisible = false;
         this.currentVersionInfo = null;
         this.versionMismatch = false;
         this.activeNotificationTab = 'updates';
@@ -49,43 +54,180 @@ export class UpdateService {
             updateBtn.addEventListener('click', () => this.performUpdate());
         }
         
-        // Register event listener for nightly update toggle
+        this.wireChannelButtons();
-        const nightlyCheckbox = document.getElementById('nightlyUpdateToggle');
-        if (nightlyCheckbox) {
-            nightlyCheckbox.checked = this.nightlyMode;
-            nightlyCheckbox.addEventListener('change', (e) => {
-                this.nightlyMode = e.target.checked;
-                setStorageItem('nightly_updates', e.target.checked);
-                this.updateNightlyWarning();
-                this.updateModalContent();
-                // Re-check for updates when switching channels
-                this.manualCheckForUpdates();
-            });
-            this.updateNightlyWarning();
-        }
 
         this.setupNotificationCenter();
         window.addEventListener('lm:banner-history-updated', this.handleBannerHistoryUpdated);
         this.updateTabBadges();
         
         // Perform update check if needed
-        this.checkForUpdates().then(() => {
+        this.checkVersionInfo().then(() => {
-            // Ensure badges are updated after checking
+            this.checkForUpdates().then(() => {
-            this.updateBadgeVisibility();
+                this.updateBadgeVisibility();
+            });
         });
 
-        // Immediately update modal content with current values (even if from default)
         this.updateModalContent();
-        
-        // Check version info for mismatch after loading basic info
-        this.checkVersionInfo();
     }
     
-    updateNightlyWarning() {
+    wireChannelButtons() {
-        const warning = document.getElementById('nightlyWarning');
+        const releaseBtn = document.getElementById('channelRelease');
-        if (warning) {
+        const nightlyBtn = document.getElementById('channelNightly');
-            warning.style.display = this.nightlyMode ? 'flex' : 'none';
+        if (releaseBtn) {
+            releaseBtn.addEventListener('click', () => this.switchChannel('release'));
         }
+        if (nightlyBtn) {
+            nightlyBtn.addEventListener('click', () => this.switchChannel('nightly'));
+        }
+    }
+
+    async switchChannel(channel) {
+        if (channel === this.channelMode) {
+            return;
+        }
+        if (this.isUpdating) {
+            return;
+        }
+        if (!this.hasGit && channel === 'nightly') {
+            const confirmed = await this._confirmChannelSwitch(
+                'update.channelSwitch.nightlyTitle',
+                'update.channelSwitch.nightlyMessage'
+            );
+            if (!confirmed) return;
+        }
+        if (this.hasGit && channel === 'release') {
+            const confirmed = await this._confirmChannelSwitch(
+                'update.channelSwitch.releaseTitle',
+                'update.channelSwitch.releaseMessage'
+            );
+            if (!confirmed) return;
+        }
+
+        try {
+            this.isUpdating = true;
+            this.showUpdateProgress(true);
+            this.updateProgress(10, translate('update.channelSwitch.switching', { channel }));
+
+            const response = await fetch('/api/lm/switch-channel', {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({ channel })
+            });
+
+            const data = await response.json();
+
+            if (data.success) {
+                this.channelMode = channel;
+                // Persist channel preference to settings.json
+                fetch('/api/lm/settings', {
+                    method: 'POST',
+                    headers: { 'Content-Type': 'application/json' },
+                    body: JSON.stringify({ update_channel: channel })
+                }).then(r => {
+                    if (!r.ok) console.warn('Failed to persist update channel:', r.status);
+                }).catch(e => console.warn('Failed to persist update channel:', e));
+                await this.checkForUpdates({ force: true });
+                this.updateModalContent();
+                this.updateChannelUI();
+                this._showSwitchCompleteMessage(data.new_version);
+                this.progressKeepVisible = true;
+            } else {
+                throw new Error(data.error || translate('update.channelSwitch.failed'));
+            }
+        } catch (error) {
+            console.error('Channel switch failed:', error);
+            this.updateProgress(0, translate('update.channelSwitch.failed'));
+        } finally {
+            if (this.progressKeepVisible) {
+                this.isUpdating = false;
+                this.progressKeepVisible = false;
+            } else {
+                setTimeout(() => {
+                    this.showUpdateProgress(false);
+                    this.isUpdating = false;
+                }, 2000);
+            }
+        }
+    }
+
+    updateChannelUI() {
+        const releaseBtn = document.getElementById('channelRelease');
+        const nightlyBtn = document.getElementById('channelNightly');
+
+        if (releaseBtn) {
+            releaseBtn.classList.toggle('active', this.channelMode === 'release');
+        }
+        if (nightlyBtn) {
+            nightlyBtn.classList.toggle('active', this.channelMode === 'nightly');
+        }
+    }
+
+    _resolveChannelFromSettings() {
+        const stored = state?.global?.settings?.update_channel;
+        if (stored === 'nightly' || stored === 'release') {
+            return stored;
+        }
+        if (!this.hasGit) {
+            return 'release';
+        }
+        if (this.gitInfo?.branch === 'detached') {
+            return 'release';
+        }
+        return 'nightly';
+    }
+
+    async _confirmChannelSwitch(titleKey, messageKey) {
+        return new Promise((resolve) => {
+            const title = translate(titleKey);
+            const message = translate(messageKey);
+            const cancelText = translate('common.cancel');
+            const confirmText = translate('common.confirm');
+
+            const overlay = document.createElement('div');
+            overlay.className = 'channel-switch-overlay';
+            overlay.innerHTML = `
+                <div class="channel-switch-dialog">
+                    <h3>${title}</h3>
+                    <p>${message}</p>
+                    <div class="channel-switch-actions">
+                        <button class="secondary-btn channel-switch-cancel">${cancelText}</button>
+                        <button class="primary-btn channel-switch-confirm">${confirmText}</button>
+                    </div>
+                </div>
+            `;
+
+            const dismiss = (result) => {
+                document.removeEventListener('keydown', onKeydown);
+                overlay.remove();
+                resolve(result);
+            };
+
+            const onKeydown = (e) => {
+                if (e.key === 'Escape') {
+                    e.stopPropagation();
+                    e.preventDefault();
+                    dismiss(false);
+                }
+            };
+
+            document.addEventListener('keydown', onKeydown, { capture: true });
+
+            overlay.addEventListener('click', (e) => {
+                if (e.target === overlay) {
+                    dismiss(false);
+                }
+            });
+
+            overlay.querySelector('.channel-switch-cancel').addEventListener('click', () => {
+                dismiss(false);
+            });
+
+            overlay.querySelector('.channel-switch-confirm').addEventListener('click', () => {
+                dismiss(true);
+            });
+
+            document.body.appendChild(overlay);
+        });
     }
 
     setupNotificationCenter() {
@@ -355,6 +497,18 @@ export class UpdateService {
     }
     
     async checkForUpdates({ force = false } = {}) {
+        let needsMigration = false;
+        if (this.channelMode === null) {
+            const stored = state?.global?.settings?.update_channel;
+            if (stored === 'nightly' || stored === 'release') {
+                this.channelMode = stored;
+            } else if (!this.hasGit) {
+                this.channelMode = 'release';
+                needsMigration = true;
+            }
+            // hasGit=true with no stored value: wait for gitInfo.branch
+        }
+
         if (!force && !this.updateNotificationsEnabled) {
             return;
         }
@@ -373,7 +527,8 @@ export class UpdateService {
 
         try {
             // Call backend API to check for updates with nightly flag
-            const response = await fetch(`/api/lm/check-updates?nightly=${this.nightlyMode}`);
+            const nightly = (this.channelMode ?? (this.hasGit ? 'nightly' : 'release')) === 'nightly';
+            const response = await fetch(`/api/lm/check-updates?nightly=${nightly}`);
             const data = await response.json();
             
             if (data.success) {
@@ -381,17 +536,35 @@ export class UpdateService {
                 this.latestVersion = data.latest_version || "v0.0.0";
                 this.updateInfo = data;
                 this.gitInfo = data.git_info || this.gitInfo;
+                this.hasGit = data.has_git || false;
 
-                // Explicitly set update availability based on version comparison
+                if (needsMigration || this.channelMode === null) {
-                this.updateAvailable = this.isNewerVersion(this.latestVersion, this.currentVersion);
+                    this.channelMode = this._resolveChannelFromSettings();
+                    if (state?.global?.settings) {
+                        state.global.settings.update_channel = this.channelMode;
+                    }
+                    fetch('/api/lm/settings', {
+                        method: 'POST',
+                        headers: { 'Content-Type': 'application/json' },
+                        body: JSON.stringify({ update_channel: this.channelMode })
+                    }).then(r => {
+                        if (!r.ok) console.warn('Failed to persist update channel:', r.status);
+                    }).catch(e => console.warn('Failed to persist update channel:', e));
+                }
+
+                this.updateAvailable = data.update_available;
+
+                // Nightly channel: surface the update badge at most once per calendar day.
+                if (this.updateAvailable && this.channelMode === 'nightly' && this.nightlyNotifyDate !== this._getTodayKey()) {
+                    this._markNightlyNotified();
+                }
 
-                // Update last check time
                 this.lastCheckTime = now;
                 setStorageItem('last_update_check', now.toString());
 
-                // Update UI
                 this.updateBadgeVisibility();
                 this.updateModalContent();
+                this.updateChannelUI();
 
                 console.log("Update check complete:", {
                     currentVersion: this.currentVersion,
@@ -436,6 +609,28 @@ export class UpdateService {
         return false;
     }
 
+    _getTodayKey() {
+        const now = new Date();
+        const month = String(now.getMonth() + 1).padStart(2, '0');
+        const day = String(now.getDate()).padStart(2, '0');
+        return `${now.getFullYear()}-${month}-${day}`;
+    }
+
+    _isNightlyBadgeAllowed() {
+        if (this.channelMode !== 'nightly') {
+            return true;
+        }
+        // Keep the badge visible for the rest of the session once shown, but do
+        // not show it again on later sessions within the same calendar day.
+        return this.nightlyNotifyDate !== this._getTodayKey() || this.nightlyBadgeShown;
+    }
+
+    _markNightlyNotified() {
+        this.nightlyNotifyDate = this._getTodayKey();
+        this.nightlyBadgeShown = true;
+        setStorageItem('nightly_notify_date', this.nightlyNotifyDate);
+    }
+    
     updateBadgeVisibility() {
         const updateToggle = document.querySelector('.update-toggle');
         const updateBadge = document.querySelector('.update-toggle .update-badge');
@@ -443,9 +638,12 @@ export class UpdateService {
             ? bannerService.getUnreadBannerCount()
             : 0;
 
+        // Force updating badges visibility based on current state
+        const shouldShowUpdate = this.updateNotificationsEnabled && this.updateAvailable && this._isNightlyBadgeAllowed();
+
         if (updateToggle) {
             let tooltipKey = 'header.actions.notifications';
-            if (this.updateNotificationsEnabled && this.updateAvailable) {
+            if (shouldShowUpdate) {
                 tooltipKey = 'update.updateAvailable';
             } else if (unreadBanners > 0) {
                 tooltipKey = 'update.tabs.messages';
@@ -453,8 +651,6 @@ export class UpdateService {
             updateToggle.title = translate(tooltipKey);
         }
 
-        // Force updating badges visibility based on current state
-        const shouldShowUpdate = this.updateNotificationsEnabled && this.updateAvailable;
         const shouldShow = shouldShowUpdate || unreadBanners > 0;
 
         if (updateBadge) {
@@ -482,8 +678,31 @@ export class UpdateService {
         
         if (currentVersionEl) currentVersionEl.textContent = this.currentVersion;
         
+        const newVersionLabel = modal.querySelector('.new-version .label');
+        if (newVersionLabel) {
+            newVersionLabel.textContent = (this.updateInfo?.nightly)
+                ? `${translate('update.latestMain')}:`
+                : `${translate('update.newVersion')}:`;
+        }
+
         if (newVersionEl) {
-            newVersionEl.textContent = this.latestVersion;
+            if (this.updateInfo?.nightly) {
+                const behind = this.updateInfo.behind_by || 0;
+                const remoteHash = this.latestVersion.replace('main-', '');
+                const localHash = this.gitInfo.short_hash || '';
+                const date = this.updateInfo.commit_date || '';
+                const datePart = date ? ` · ${date}` : '';
+
+                if (behind > 0) {
+                    newVersionEl.textContent = `${behind} commit${behind !== 1 ? 's' : ''} behind main (${remoteHash}${datePart})`;
+                } else if (localHash !== remoteHash) {
+                    newVersionEl.textContent = `Behind main (${remoteHash}${datePart})`;
+                } else {
+                    newVersionEl.textContent = `Up to date (${remoteHash}${datePart})`;
+                }
+            } else {
+                newVersionEl.textContent = this.latestVersion;
+            }
         }
         
         // Update update button state
@@ -599,8 +818,12 @@ export class UpdateService {
         // Update GitHub link to point to the specific release if available
         const githubLink = modal.querySelector('.update-link');
         if (githubLink && this.latestVersion) {
-            const versionTag = this.latestVersion.replace(/^v/, '');
+            if (this.updateInfo?.nightly) {
-            githubLink.href = `https://github.com/willmiao/ComfyUI-Lora-Manager/releases/tag/v${versionTag}`;
+                githubLink.href = 'https://github.com/willmiao/ComfyUI-Lora-Manager/commits/main';
+            } else {
+                const versionTag = this.latestVersion.replace(/^v/, '');
+                githubLink.href = `https://github.com/willmiao/ComfyUI-Lora-Manager/releases/tag/v${versionTag}`;
+            }
         }
     }
     
@@ -623,7 +846,7 @@ export class UpdateService {
                     'Content-Type': 'application/json'
                 },
                 body: JSON.stringify({
-                    nightly: this.nightlyMode
+                    nightly: this.channelMode === 'nightly'
                 })
             });
             
@@ -699,6 +922,25 @@ export class UpdateService {
         }
     }
 
+    _showSwitchCompleteMessage(version) {
+        this.showUpdateProgress(true);
+        this.updateProgress(100, '');
+        const progressText = document.getElementById('updateProgressText');
+        if (progressText) {
+            progressText.innerHTML = `
+                <div style="text-align: center; color: var(--lora-success);">
+                    <i class="fas fa-check-circle" style="margin-right: 8px;"></i>
+                    ${translate('update.completion.successMessage', { version })}
+                    <br><br>
+                    <div style="opacity: 0.95; color: var(--lora-error); font-size: 1em;">
+                        ${translate('update.completion.restartMessage')}<br>
+                        ${translate('update.completion.reloadMessage')}
+                    </div>
+                </div>
+            `;
+        }
+    }
+
     showUpdateCompleteMessage(newVersion) {
         const modal = document.getElementById('updateModal');
         if (!modal) return;
@@ -771,6 +1013,7 @@ export class UpdateService {
 
         // Update the modal content immediately with current data
         this.updateModalContent();
+        this.updateChannelUI();
         this.renderRecentBanners();
 
         // Show the modal with current data
@@ -801,8 +1044,8 @@ export class UpdateService {
             
             if (data.success) {
                 this.currentVersionInfo = data.version;
+                this.hasGit = data.has_git || false;
 
-                // Check if version matches stored version
                 this.versionMismatch = !isVersionMatch(this.currentVersionInfo);
                 
                 if (this.versionMismatch) {

static/js/managers/import/DownloadManager.js

@@ -3,6 +3,7 @@ import { translate } from '../../utils/i18nHelpers.js';
 import { getModelApiClient } from '../../api/modelApiFactory.js';
 import { MODEL_TYPES } from '../../api/apiConfig.js';
 import { getStorageItem } from '../../utils/storageHelpers.js';
+import { state } from '../../state/index.js';
 
 export class DownloadManager {
     constructor(importManager) {
@@ -125,11 +126,25 @@ export class DownloadManager {
                 showToast('toast.recipes.nameSaved', { name: this.importManager.recipeName }, 'success');
             }
 
-            // Close modal
             modalManager.closeModal('importModal');
 
-            // Refresh the recipe
+            if (isDownloadOnly && state.virtualScroller) {
-            window.recipeManager.loadRecipes(true);
+                const recipeId = this.importManager.recipeId;
+                try {
+                    const detailRes = await fetch(`/api/lm/recipe/${encodeURIComponent(recipeId)}`);
+                    if (detailRes.ok) {
+                        const updated = await detailRes.json();
+                        state.virtualScroller.updateSingleItem(updated.file_path, updated);
+                    } else {
+                        throw new Error(`API returned ${detailRes.status}`);
+                    }
+                } catch (e) {
+                    console.warn('Failed to update recipe card in-place, falling back to reload:', e);
+                    await window.recipeManager.loadRecipes({ resetPage: true, preserveScroll: true });
+                }
+            } else {
+                window.recipeManager.loadRecipes({ resetPage: true, preserveScroll: true });
+            }
 
         } catch (error) {
             console.error('Error:', error);

static/js/utils/constants.js

@@ -333,6 +333,7 @@ export const PATH_TEMPLATE_PLACEHOLDERS = [
 export const DEFAULT_PATH_TEMPLATES = {
     lora: '{base_model}/{first_tag}',
     checkpoint: '{base_model}',
+    unet: '{base_model}',
     embedding: '{first_tag}'
 };
 
@@ -369,21 +370,24 @@ export function getMatureBlurThreshold(settings = {}) {
 export const NODE_TYPES = {
     LORA_LOADER: 1,
     LORA_STACKER: 2,
-    WAN_VIDEO_LORA_SELECT: 3
+    WAN_VIDEO_LORA_SELECT: 3,
+    HOOK_LORA: 4
 };
 
 // Node type names to IDs mapping
 export const NODE_TYPE_NAMES = {
     "Lora Loader (LoraManager)": NODE_TYPES.LORA_LOADER,
     "Lora Stacker (LoraManager)": NODE_TYPES.LORA_STACKER,
-    "WanVideo Lora Select (LoraManager)": NODE_TYPES.WAN_VIDEO_LORA_SELECT
+    "WanVideo Lora Select (LoraManager)": NODE_TYPES.WAN_VIDEO_LORA_SELECT,
+    "Create Hook LoRA (LoraManager)": NODE_TYPES.HOOK_LORA
 };
 
 // Node type icons
 export const NODE_TYPE_ICONS = {
     [NODE_TYPES.LORA_LOADER]: "fas fa-l",
     [NODE_TYPES.LORA_STACKER]: "fas fa-s",
-    [NODE_TYPES.WAN_VIDEO_LORA_SELECT]: "fas fa-w"
+    [NODE_TYPES.WAN_VIDEO_LORA_SELECT]: "fas fa-w",
+    [NODE_TYPES.HOOK_LORA]: "fas fa-h"
 };
 
 // Default ComfyUI node color when bgcolor is null

templates/checkpoints.html

@@ -32,7 +32,12 @@
     <div class="context-menu-separator menu-section-break"></div>
     <!-- Media / Preview -->
     <div class="context-menu-item" data-action="preview"><i class="fas fa-folder-open"></i> {{ t('loras.contextMenu.openExamples') }}</div>
-    <div class="context-menu-item" data-action="download-examples"><i class="fas fa-download"></i> {{ t('loras.contextMenu.downloadExamples') }}</div>
+    <div class="context-menu-item has-submenu" data-has-submenu="download-examples"><i class="fas fa-download"></i> {{ t('loras.contextMenu.downloadExamples') }} <i class="fas fa-chevron-right submenu-arrow"></i>
+        <div class="context-submenu">
+            <div class="context-menu-item" data-action="download-examples"><i class="fas fa-download"></i> {{ t('loras.contextMenu.downloadMissingExamples') }}</div>
+            <div class="context-menu-item" data-action="download-examples-force"><i class="fas fa-redo-alt"></i> {{ t('loras.contextMenu.reprocessExamples') }}</div>
+        </div>
+    </div>
     <div class="context-menu-item" data-action="replace-preview"><i class="fas fa-image"></i> {{ t('loras.contextMenu.replacePreview') }}</div>
     <div class="context-menu-separator menu-section-break"></div>
     <!-- Attributes -->

templates/components/context_menu.html

@@ -44,8 +44,18 @@
     <div class="context-menu-item" data-action="preview">
         <i class="fas fa-folder-open"></i> <span>{{ t('loras.contextMenu.openExamples') }}</span>
     </div>
-    <div class="context-menu-item" data-action="download-examples">
+    <div class="context-menu-item has-submenu" data-has-submenu="download-examples">
-        <i class="fas fa-download"></i> <span>{{ t('loras.contextMenu.downloadExamples') }}</span>
+        <i class="fas fa-download"></i>
+        <span>{{ t('loras.contextMenu.downloadExamples') }}</span>
+        <i class="fas fa-chevron-right submenu-arrow"></i>
+        <div class="context-submenu">
+            <div class="context-menu-item" data-action="download-examples">
+                <i class="fas fa-download"></i> <span>{{ t('loras.contextMenu.downloadMissingExamples') }}</span>
+            </div>
+            <div class="context-menu-item" data-action="download-examples-force">
+                <i class="fas fa-redo-alt"></i> <span>{{ t('loras.contextMenu.reprocessExamples') }}</span>
+            </div>
+        </div>
     </div>
     <div class="context-menu-item" data-action="replace-preview">
         <i class="fas fa-image"></i> <span>{{ t('loras.contextMenu.replacePreview') }}</span>
@@ -136,8 +146,18 @@
     </div>
     <div class="context-menu-section" data-section="download">
         <div class="context-menu-section-header">{{ t('loras.bulkOperations.sections.download') }}</div>
-        <div class="context-menu-item" data-action="download-example-images">
+        <div class="context-menu-item has-submenu" data-has-submenu="download-example-images">
-            <i class="fas fa-download"></i> <span>{{ t('loras.bulkOperations.downloadExamples') }}</span>
+            <i class="fas fa-download"></i>
+            <span>{{ t('loras.bulkOperations.downloadExamples') }}</span>
+            <i class="fas fa-chevron-right submenu-arrow"></i>
+            <div class="context-submenu">
+                <div class="context-menu-item" data-action="download-missing-example-images">
+                    <i class="fas fa-download"></i> <span>{{ t('loras.bulkOperations.downloadMissingExamples') }}</span>
+                </div>
+                <div class="context-menu-item" data-action="download-example-images">
+                    <i class="fas fa-redo-alt"></i> <span>{{ t('loras.bulkOperations.reprocessExamples') }}</span>
+                </div>
+            </div>
         </div>
         <div class="context-menu-item" data-action="download-missing-loras">
             <i class="fas fa-download"></i> <span>{{ t('loras.bulkOperations.downloadMissingLoras') }}</span>

templates/components/controls.html

@@ -48,6 +48,11 @@
                             <option value="versions_count:asc">{{ t('loras.controls.sort.versionsCountAsc', default='Fewest versions first') }}</option>
                         </optgroup>
                     {% endif %}
+                    {% if page_id != 'recipes' %}
+                        <optgroup label="{{ t('loras.controls.sort.random', default='Random') }}">
+                            <option value="random">{{ t('loras.controls.sort.randomAction', default='Randomize (shuffle)') }}</option>
+                        </optgroup>
+                    {% endif %}
                     {% if page_id == 'recipes' %}
                         <optgroup label="{{ t('recipes.controls.sort.lorasCount') }}">
                             <option value="loras_count:desc">{{ t('recipes.controls.sort.lorasCountDesc') }}</option>

templates/components/modals/update_modal.html

@@ -19,6 +19,20 @@
         <div class="notification-panels">
             <div class="notification-panel active" id="updatesPanel" role="tabpanel" aria-labelledby="updatesTab" aria-hidden="false" tabindex="0" data-notification-panel="updates">
                 <div class="update-content">
+
+                    <!-- Channel Selector -->
+                    <div class="update-channels" id="updateChannels">
+                        <div class="channels-label">{{ t('update.channel') }}</div>
+                        <div class="channel-toggle">
+                            <button type="button" class="channel-btn" data-channel="release" id="channelRelease">
+                                <i class="fas fa-tag"></i> {{ t('update.channels.release') }}
+                            </button>
+                            <button type="button" class="channel-btn" data-channel="nightly" id="channelNightly">
+                                <i class="fas fa-moon"></i> {{ t('update.channels.nightly') }}
+                            </button>
+                        </div>
+                    </div>
+
                     <div class="update-info">
                         <div class="version-info">
                             <div class="current-version">

templates/embeddings.html

@@ -32,7 +32,12 @@
     <div class="context-menu-separator menu-section-break"></div>
     <!-- Media / Preview -->
     <div class="context-menu-item" data-action="preview"><i class="fas fa-folder-open"></i> {{ t('loras.contextMenu.openExamples') }}</div>
-    <div class="context-menu-item" data-action="download-examples"><i class="fas fa-download"></i> {{ t('loras.contextMenu.downloadExamples') }}</div>
+    <div class="context-menu-item has-submenu" data-has-submenu="download-examples"><i class="fas fa-download"></i> {{ t('loras.contextMenu.downloadExamples') }} <i class="fas fa-chevron-right submenu-arrow"></i>
+        <div class="context-submenu">
+            <div class="context-menu-item" data-action="download-examples"><i class="fas fa-download"></i> {{ t('loras.contextMenu.downloadMissingExamples') }}</div>
+            <div class="context-menu-item" data-action="download-examples-force"><i class="fas fa-redo-alt"></i> {{ t('loras.contextMenu.reprocessExamples') }}</div>
+        </div>
+    </div>
     <div class="context-menu-item" data-action="replace-preview"><i class="fas fa-image"></i> {{ t('loras.contextMenu.replacePreview') }}</div>
     <div class="context-menu-separator menu-section-break"></div>
     <!-- Attributes -->

tests/conftest.py

@@ -85,6 +85,7 @@ sys.modules['comfy.utils'] = comfy_mock.utils
 sys.modules['comfy.sd'] = comfy_mock.sd
 sys.modules['comfy.model_management'] = comfy_mock.model_management
 sys.modules['comfy.comfy_types'] = comfy_mock.comfy_types
+sys.modules['comfy.hooks'] = MockModule("comfy.hooks")
 
 execution_mock = MockModule("execution")
 execution_mock.PromptExecutor = mock.MagicMock()

tests/frontend/components/contextMenu.interactions.test.js

@@ -2155,4 +2155,35 @@ describe('Interaction-level regression coverage', () => {
     excludedItem.dispatchEvent(new Event('click', { bubbles: true }));
     expect(window.pageControls.enterExcludedView).toHaveBeenCalledTimes(1);
   });
+
+  it('routes single-model example downloads to missing-only and force paths', async () => {
+    document.body.innerHTML = `
+      <div id="loraContextMenu" class="context-menu">
+        <div class="context-menu-item has-submenu" data-has-submenu="download-examples">
+          <div class="context-submenu">
+            <div class="context-menu-item" data-action="download-examples"></div>
+            <div class="context-menu-item" data-action="download-examples-force"></div>
+          </div>
+        </div>
+      </div>
+    `;
+
+    const { LoraContextMenu } = await import('../../../static/js/components/ContextMenu/LoraContextMenu.js');
+    const contextMenu = new LoraContextMenu();
+
+    const card = document.createElement('div');
+    card.className = 'model-card';
+    card.dataset.filepath = '/models/test.safetensors';
+    card.dataset.sha256 = 'abc123hash';
+    document.body.appendChild(card);
+
+    contextMenu.showMenu(100, 100, card);
+
+    document.querySelector('[data-action="download-examples"]').dispatchEvent(new Event('click', { bubbles: true }));
+    expect(downloadExampleImagesApiMock).toHaveBeenCalledWith(['abc123hash'], null, { force: false });
+
+    contextMenu.showMenu(100, 100, card);
+    document.querySelector('[data-action="download-examples-force"]').dispatchEvent(new Event('click', { bubbles: true }));
+    expect(downloadExampleImagesApiMock).toHaveBeenCalledWith(['abc123hash'], null, { force: true });
+  });
 });

tests/frontend/components/pageControls.randomSort.test.js

@@ -0,0 +1,221 @@
+import { describe, it, beforeEach, afterEach, expect, vi } from 'vitest';
+
+const resetAndReloadMock = vi.fn();
+const getModelApiClientMock = vi.fn();
+
+vi.mock('../../../static/js/api/modelApiFactory.js', () => ({
+  getModelApiClient: getModelApiClientMock,
+  resetAndReload: resetAndReloadMock,
+}));
+
+vi.mock('../../../static/js/utils/uiHelpers.js', () => ({
+  showToast: vi.fn(),
+  openCivitaiByMetadata: vi.fn(),
+  updatePanelPositions: vi.fn(),
+}));
+
+vi.mock('../../../static/js/managers/DownloadManager.js', () => ({
+  downloadManager: { showDownloadModal: vi.fn() },
+}));
+
+vi.mock('../../../static/js/components/SidebarManager.js', () => ({
+  sidebarManager: {
+    setHostPageControls: vi.fn(),
+    initialize: vi.fn(async () => {}),
+    refresh: vi.fn(async () => {}),
+    cleanup: vi.fn(),
+    isInitialized: false,
+  },
+}));
+
+vi.mock('../../../static/js/components/alphabet/index.js', () => ({
+  createAlphabetBar: vi.fn(() => ({ destroy: vi.fn() })),
+}));
+
+vi.mock('../../../static/js/utils/updateCheckHelpers.js', () => ({
+  performModelUpdateCheck: vi.fn(async () => ({ status: 'success', displayName: 'LoRA', records: [] })),
+}));
+
+beforeEach(() => {
+  vi.resetModules();
+  vi.clearAllMocks();
+  localStorage.clear();
+  sessionStorage.clear();
+
+  resetAndReloadMock.mockResolvedValue(undefined);
+  getModelApiClientMock.mockReturnValue({});
+
+  global.fetch = vi.fn().mockResolvedValue({
+    ok: true,
+    json: async () => ({ success: true, base_models: [] }),
+  });
+});
+
+afterEach(() => {
+  delete window.bulkManager;
+  delete window.modelDuplicatesManager;
+  delete global.fetch;
+});
+
+function renderControlsDom(pageKey) {
+  document.body.dataset.page = pageKey;
+  document.body.innerHTML = `
+    <div class="controls">
+      <div id="excludedViewBanner" class="excluded-view-banner hidden">
+        <button id="excludedViewBackBtn">Back</button>
+      </div>
+      <div class="actions">
+        <div class="action-buttons">
+          <div class="control-group">
+            <select id="sortSelect">
+              <option value="name:asc">Name Asc</option>
+              <option value="name:desc">Name Desc</option>
+              <option value="random">Randomize (shuffle)</option>
+            </select>
+          </div>
+          <div class="control-group dropdown-group">
+            <button data-action="refresh" class="dropdown-main"></button>
+            <button class="dropdown-toggle"></button>
+            <div class="dropdown-menu">
+              <div class="dropdown-item" data-action="full-rebuild"></div>
+            </div>
+          </div>
+          <div class="control-group">
+            <button data-action="fetch"></button>
+          </div>
+          <div class="control-group">
+            <button data-action="download"></button>
+          </div>
+          <div class="control-group">
+            <button data-action="bulk"></button>
+          </div>
+          <div class="control-group">
+            <button data-action="find-duplicates"></button>
+          </div>
+          <div class="control-group">
+            <button id="favoriteFilterBtn" class="favorite-filter"></button>
+          </div>
+          <div class="control-group dropdown-group update-filter-group">
+            <button id="updateFilterBtn" class="dropdown-main update-filter" aria-busy="false">
+              <span>Updates</span>
+            </button>
+            <button id="updateFilterMenuToggle" class="dropdown-toggle"></button>
+            <div class="dropdown-menu">
+              <div id="checkUpdatesMenuItem" class="dropdown-item" data-action="check-updates">
+                <span>Check updates</span>
+              </div>
+            </div>
+          </div>
+        </div>
+      </div>
+    </div>
+    <div id="customFilterIndicator" class="control-group hidden">
+      <div class="filter-active">
+        <span class="customFilterText" title=""></span>
+        <i class="fas fa-times-circle clear-filter"></i>
+      </div>
+    </div>
+    <div id="breadcrumbContainer"></div>
+    <div id="duplicatesBanner" style="display: none;"></div>
+    <div class="alphabet-bar-container"></div>
+  `;
+}
+
+async function createControls() {
+  const stateModule = await import('../../../static/js/state/index.js');
+  stateModule.initPageState('loras');
+  const { LorasControls } = await import('../../../static/js/components/controls/LorasControls.js');
+  return { stateModule, controls: new LorasControls() };
+}
+
+describe('Random sort option', () => {
+  it('generates a seeded sort value when Random is picked', async () => {
+    renderControlsDom('loras');
+    const { controls } = await createControls();
+    const sortSelect = document.getElementById('sortSelect');
+    const randomOpt = sortSelect.querySelector('option[value="random"]');
+
+    sortSelect.value = 'random';
+    sortSelect.dispatchEvent(new Event('change', { bubbles: true }));
+    await Promise.resolve();
+
+    expect(controls.pageState.sortBy).toMatch(/^random:[a-z0-9]+$/);
+    expect(localStorage.getItem('lora_manager_loras_sort')).toBe(controls.pageState.sortBy);
+    expect(randomOpt.value).toBe(controls.pageState.sortBy);
+    expect(sortSelect.value).toBe(controls.pageState.sortBy);
+    expect(resetAndReloadMock).toHaveBeenCalled();
+  });
+
+  it('reshuffles with a fresh seed every time Random is picked again', async () => {
+    renderControlsDom('loras');
+    const { controls } = await createControls();
+    const sortSelect = document.getElementById('sortSelect');
+    const randomOpt = sortSelect.querySelector('option[value="random"]');
+
+    // First pick
+    sortSelect.value = 'random';
+    sortSelect.dispatchEvent(new Event('change', { bubbles: true }));
+    await Promise.resolve();
+    const firstSeed = controls.pageState.sortBy;
+
+    // Second pick: the option now carries the seeded value, like a menu click
+    sortSelect.value = randomOpt.value;
+    sortSelect.dispatchEvent(new Event('change', { bubbles: true }));
+    await Promise.resolve();
+
+    expect(controls.pageState.sortBy).toMatch(/^random:[a-z0-9]+$/);
+    expect(controls.pageState.sortBy).not.toBe(firstSeed);
+  });
+
+  it('restores a persisted seeded random sort on load', async () => {
+    renderControlsDom('loras');
+    const savedSort = 'random:persistedseed';
+    localStorage.setItem('lora_manager_loras_sort', savedSort);
+
+    const { controls } = await createControls();
+    const sortSelect = document.getElementById('sortSelect');
+
+    expect(controls.pageState.sortBy).toBe(savedSort);
+    expect(sortSelect.value).toBe(savedSort);
+    expect(sortSelect.querySelector('option[value="random:persistedseed"]')).not.toBeNull();
+  });
+
+  it('applies a non-random sort back to the plain random option', async () => {
+    renderControlsDom('loras');
+    const { controls } = await createControls();
+    const sortSelect = document.getElementById('sortSelect');
+    const randomOpt = sortSelect.querySelector('option[value="random"]');
+
+    // Seed a random sort, then switch to a normal sort
+    sortSelect.value = 'random';
+    sortSelect.dispatchEvent(new Event('change', { bubbles: true }));
+    await Promise.resolve();
+    controls.applySortToSelect('name:desc');
+
+    expect(sortSelect.value).toBe('name:desc');
+    expect(randomOpt.value).toBe('random');
+  });
+
+  it('resets the seeded option when switching away from Random via the dropdown change handler', async () => {
+    renderControlsDom('loras');
+    const { controls } = await createControls();
+    const sortSelect = document.getElementById('sortSelect');
+    const randomOpt = sortSelect.querySelector('option[value="random"]');
+
+    // Pick Random: the option is now seeded
+    sortSelect.value = 'random';
+    sortSelect.dispatchEvent(new Event('change', { bubbles: true }));
+    await Promise.resolve();
+    expect(randomOpt.value).toMatch(/^random:[a-z0-9]+$/);
+
+    // Switch to a non-random sort through the change handler (as a menu
+    // click does); the option must go back to the plain "random" value
+    sortSelect.value = 'name:desc';
+    sortSelect.dispatchEvent(new Event('change', { bubbles: true }));
+    await Promise.resolve();
+
+    expect(controls.pageState.sortBy).toBe('name:desc');
+    expect(sortSelect.value).toBe('name:desc');
+    expect(randomOpt.value).toBe('random');
+  });
+});

tests/frontend/components/sortDropdown.menuSync.test.js

@@ -0,0 +1,68 @@
+import { describe, it, beforeEach, expect } from 'vitest';
+import { initSortDropdown } from '../../../static/js/components/controls/SortDropdown.js';
+
+function renderSortDropdownDom() {
+    document.body.innerHTML = `
+    <div class="sort-dropdown-group">
+      <select id="sortSelect">
+        <option value="name:asc">Name Asc</option>
+        <option value="name:desc">Name Desc</option>
+        <option value="random" selected>Randomize (shuffle)</option>
+      </select>
+      <button class="sort-trigger" type="button">
+        <span class="sort-trigger__label"></span>
+      </button>
+      <div class="sort-dropdown-menu"></div>
+    </div>
+  `;
+    return {
+        select: document.getElementById('sortSelect'),
+        menu: document.querySelector('.sort-dropdown-menu'),
+        label: document.querySelector('.sort-trigger__label'),
+    };
+}
+
+describe('SortDropdown menu sync', () => {
+    let select;
+    let menu;
+    let label;
+
+    beforeEach(() => {
+        ({ select, menu, label } = renderSortDropdownDom());
+        initSortDropdown(select);
+    });
+
+    it('rebuilds the menu and highlights the selected item when an option value attribute changes', async () => {
+        // The seeded Random option gets a new value each time it is picked.
+        // The select's value getter follows the selected option's new value.
+        const randomOpt = select.querySelector('option[value="random"]');
+        randomOpt.value = 'random:abc123';
+        await Promise.resolve();
+
+        const items = [...menu.querySelectorAll('.sort-option')];
+        expect(items.map((el) => el.dataset.value)).toContain('random:abc123');
+        const seededItem = items.find((el) => el.dataset.value === 'random:abc123');
+        expect(seededItem.classList.contains('is-selected')).toBe(true);
+        expect(label.textContent).toBe('Randomize (shuffle)');
+    });
+
+    it('drops the stale seeded item and re-selects the plain random item when the option is reset', async () => {
+        const randomOpt = select.querySelector('option[value="random"]');
+        randomOpt.value = 'random:abc123';
+        await Promise.resolve();
+
+        // The rebuild must have happened: the seeded item is in the menu
+        const seededItems = [...menu.querySelectorAll('.sort-option')]
+            .filter((el) => el.dataset.value === 'random:abc123');
+        expect(seededItems).toHaveLength(1);
+
+        // PageControls resets the option to "random" when switching away
+        randomOpt.value = 'random';
+        await Promise.resolve();
+
+        const items = [...menu.querySelectorAll('.sort-option')];
+        expect(items.map((el) => el.dataset.value)).not.toContain('random:abc123');
+        const randomItem = items.find((el) => el.dataset.value === 'random');
+        expect(randomItem.classList.contains('is-selected')).toBe(true);
+    });
+});

tests/frontend/core/loraStackDynamicInputs.test.js

@@ -0,0 +1,195 @@
+import { beforeEach, describe, expect, it, vi } from "vitest";
+
+const { APP_MODULE, EXTENSION_MODULE, appMock, registeredExtensions } =
+  vi.hoisted(() => {
+    const registeredExtensions = [];
+    const appMock = {
+      configuringGraph: false,
+      registerExtension: (ext) => registeredExtensions.push(ext),
+    };
+    return {
+      APP_MODULE: new URL("../../../scripts/app.js", import.meta.url).pathname,
+      EXTENSION_MODULE: new URL(
+        "../../../web/comfyui/lora_stack_dynamic_inputs.js",
+        import.meta.url
+      ).pathname,
+      appMock,
+      registeredExtensions,
+    };
+  });
+
+vi.mock(APP_MODULE, () => ({
+  app: appMock,
+}));
+
+describe("Lora Stack Combiner dynamic inputs", () => {
+  let extension;
+
+  beforeEach(async () => {
+    vi.resetModules();
+    registeredExtensions.length = 0;
+    appMock.configuringGraph = false;
+    await import(EXTENSION_MODULE);
+    extension = registeredExtensions.find(
+      (ext) => ext.name === "Comfy.LoraManager.LoraStackCombiner"
+    );
+    expect(extension).toBeDefined();
+  });
+
+  function createNodeType() {
+    const nodeType = { prototype: {} };
+    extension.beforeRegisterNodeDef(
+      nodeType,
+      { name: "Lora Stack Combiner (LoraManager)" },
+      appMock
+    );
+    return nodeType;
+  }
+
+  function createNode(inputs = []) {
+    const node = {
+      comfyClass: "Lora Stack Combiner (LoraManager)",
+      inputs: inputs.map((name) => ({ name, type: "LORA_STACK" })),
+      addInput: vi.fn(function (name, type, opts) {
+        this.inputs.push({ name, type, ...opts });
+      }),
+      removeInput: vi.fn(function (index) {
+        this.inputs.splice(index, 1);
+      }),
+    };
+    return node;
+  }
+
+  function makeLinkInfo() {
+    return { id: 999, origin_id: 1, target_id: 2 };
+  }
+
+  it("adds a third input when the last slot gets connected", () => {
+    const nodeType = createNodeType();
+    const node = createNode(["lora_stack1", "lora_stack2"]);
+    node.onConnectionsChange = nodeType.prototype.onConnectionsChange;
+
+    node.onConnectionsChange(1, 1, true, makeLinkInfo());
+
+    expect(node.inputs.map((input) => input.name)).toEqual([
+      "lora_stack1",
+      "lora_stack2",
+      "lora_stack3",
+    ]);
+  });
+
+  it("does not add an input when a non-last slot gets connected", () => {
+    const nodeType = createNodeType();
+    const node = createNode(["lora_stack1", "lora_stack2", "lora_stack3"]);
+    node.onConnectionsChange = nodeType.prototype.onConnectionsChange;
+
+    node.onConnectionsChange(1, 0, true, makeLinkInfo());
+
+    expect(node.inputs.map((input) => input.name)).toEqual([
+      "lora_stack1",
+      "lora_stack2",
+      "lora_stack3",
+    ]);
+  });
+
+  it("removes a disconnected middle slot and renumbers", () => {
+    // Simulates a real LiteGraph disconnect event: it fires only for slots that
+    // had a link, and input.link has already been cleared before the event fires.
+    const nodeType = createNodeType();
+    const node = createNode(["lora_stack1", "lora_stack2", "lora_stack3"]);
+    node.inputs[0].link = 11;
+    node.inputs[1].link = null; // slot 2 was just disconnected
+    node.inputs[2].link = 13;
+    node.onConnectionsChange = nodeType.prototype.onConnectionsChange;
+
+    node.onConnectionsChange(1, 1, false, makeLinkInfo());
+
+    expect(node.inputs.map((input) => input.name)).toEqual([
+      "lora_stack1",
+      "lora_stack2",
+    ]);
+  });
+
+  it("keeps the last slot when it is disconnected", () => {
+    const nodeType = createNodeType();
+    const node = createNode(["lora_stack1", "lora_stack2", "lora_stack3"]);
+    node.inputs[0].link = 11;
+    node.inputs[1].link = 12;
+    node.inputs[2].link = null; // last slot was just disconnected
+    node.onConnectionsChange = nodeType.prototype.onConnectionsChange;
+
+    node.onConnectionsChange(1, 2, false, makeLinkInfo());
+
+    expect(node.inputs.map((input) => input.name)).toEqual([
+      "lora_stack1",
+      "lora_stack2",
+      "lora_stack3",
+    ]);
+    expect(node.removeInput).not.toHaveBeenCalled();
+  });
+
+  it("keeps at least two inputs when disconnecting", () => {
+    const nodeType = createNodeType();
+    const node = createNode(["lora_stack1", "lora_stack2"]);
+    node.inputs[0].link = 11;
+    node.inputs[1].link = null; // slot 2 was just disconnected
+    node.onConnectionsChange = nodeType.prototype.onConnectionsChange;
+
+    node.onConnectionsChange(1, 1, false, makeLinkInfo());
+
+    expect(node.inputs.map((input) => input.name)).toEqual([
+      "lora_stack1",
+      "lora_stack2",
+    ]);
+    expect(node.removeInput).not.toHaveBeenCalled();
+  });
+
+  it("does nothing while the graph is being configured", () => {
+    appMock.configuringGraph = true;
+    const nodeType = createNodeType();
+    const node = createNode(["lora_stack1", "lora_stack2"]);
+    node.onConnectionsChange = nodeType.prototype.onConnectionsChange;
+
+    node.onConnectionsChange(1, 1, true, makeLinkInfo());
+
+    expect(node.inputs.map((input) => input.name)).toEqual([
+      "lora_stack1",
+      "lora_stack2",
+    ]);
+    expect(node.addInput).not.toHaveBeenCalled();
+  });
+
+  it("leaves legacy lora_stack_a/b inputs untouched", () => {
+    const nodeType = createNodeType();
+    const node = createNode(["lora_stack_a", "lora_stack_b"]);
+    node.onConnectionsChange = nodeType.prototype.onConnectionsChange;
+
+    node.onConnectionsChange(1, 0, true, makeLinkInfo());
+
+    expect(node.inputs.map((input) => input.name)).toEqual([
+      "lora_stack_a",
+      "lora_stack_b",
+    ]);
+    expect(node.addInput).not.toHaveBeenCalled();
+  });
+
+  it("ensures two numbered inputs exist on creation", () => {
+    const node = createNode([]);
+    extension.nodeCreated(node, {});
+
+    expect(node.inputs.map((input) => input.name)).toEqual([
+      "lora_stack1",
+      "lora_stack2",
+    ]);
+  });
+
+  it("does not add numbered inputs to legacy workflows", () => {
+    const node = createNode(["lora_stack_a", "lora_stack_b"]);
+    extension.nodeCreated(node, {});
+
+    expect(node.inputs.map((input) => input.name)).toEqual([
+      "lora_stack_a",
+      "lora_stack_b",
+    ]);
+  });
+});

tests/frontend/managers/BulkManager.contentRating.test.js

@@ -0,0 +1,133 @@
+import { describe, it, beforeEach, expect, vi } from 'vitest';
+
+const showToastMock = vi.fn();
+const translateMock = vi.fn((key, params, fallback) => (typeof fallback === 'string' ? fallback : key));
+const getNSFWLevelNameMock = vi.fn((level) => {
+  if (level >= 16) return 'XXX';
+  if (level >= 8) return 'X';
+  if (level >= 4) return 'R';
+  if (level >= 2) return 'PG13';
+  if (level >= 1) return 'PG';
+  return 'Unknown';
+});
+
+const loadingManagerStub = {
+  showSimpleLoading: vi.fn(),
+  showCancelButton: vi.fn(),
+  hide: vi.fn(),
+};
+
+const stateStub = {
+  currentPageType: 'recipes',
+  bulkMode: false,
+  selectedModels: new Set(),
+  loadingManager: loadingManagerStub,
+  virtualScroller: { updateSingleItem: vi.fn() },
+  global: { settings: {} },
+};
+
+const saveModelMetadataMock = vi.fn();
+const getModelApiClientMock = vi.fn(() => ({ saveModelMetadata: saveModelMetadataMock }));
+const updateRecipeMetadataMock = vi.fn(() => Promise.resolve({ success: true }));
+
+vi.mock('../../../static/js/state/index.js', () => ({
+  state: stateStub,
+  getCurrentPageState: vi.fn(),
+}));
+
+vi.mock('../../../static/js/utils/uiHelpers.js', () => ({
+  showToast: showToastMock,
+  copyToClipboard: vi.fn(),
+  sendLoraToWorkflow: vi.fn(),
+  sendEmbeddingToWorkflow: vi.fn(),
+  buildLoraSyntax: vi.fn(),
+  getNSFWLevelName: getNSFWLevelNameMock,
+}));
+
+vi.mock('../../../static/js/api/modelApiFactory.js', () => ({
+  getModelApiClient: getModelApiClientMock,
+  resetAndReload: vi.fn(),
+}));
+
+vi.mock('../../../static/js/api/recipeApi.js', () => ({
+  RecipeSidebarApiClient: class {},
+  updateRecipeMetadata: updateRecipeMetadataMock,
+  extractRecipeId: vi.fn(),
+}));
+
+vi.mock('../../../static/js/api/apiConfig.js', () => ({
+  MODEL_TYPES: { LORA: 'loras', CHECKPOINT: 'checkpoints', EMBEDDING: 'embeddings' },
+  MODEL_CONFIG: {},
+}));
+
+vi.mock('../../../static/js/managers/ModalManager.js', () => ({
+  modalManager: { showModal: vi.fn(), closeModal: vi.fn() },
+}));
+
+vi.mock('../../../static/js/components/shared/ModelCard.js', () => ({
+  updateCardsForBulkMode: vi.fn(),
+}));
+
+vi.mock('../../../static/js/utils/i18nHelpers.js', () => ({
+  translate: translateMock,
+}));
+
+vi.mock('../../../static/js/utils/priorityTagHelpers.js', () => ({
+  getPriorityTagSuggestions: vi.fn(),
+}));
+
+vi.mock('../../../static/js/components/shared/NsfwLevelSelector.js', () => ({
+  getNsfwLevelSelector: vi.fn(),
+}));
+
+describe('BulkManager bulk content rating', () => {
+  beforeEach(() => {
+    vi.clearAllMocks();
+    stateStub.currentPageType = 'recipes';
+    stateStub.bulkMode = false;
+    stateStub.selectedModels.clear();
+    saveModelMetadataMock.mockResolvedValue(undefined);
+    updateRecipeMetadataMock.mockResolvedValue({ success: true });
+  });
+
+  async function createBulkManager() {
+    const { BulkManager } = await import('../../../static/js/managers/BulkManager.js');
+    return new BulkManager();
+  }
+
+  it('exposes the content rating action on the recipes page action config', async () => {
+    const bulk = await createBulkManager();
+    expect(bulk.actionConfig.recipes.setContentRating).toBe(true);
+  });
+
+  it('persists the rating through the recipe API when on the recipes page', async () => {
+    const bulk = await createBulkManager();
+    stateStub.currentPageType = 'recipes';
+    stateStub.selectedModels.add('/recipes/test.webp');
+
+    const ok = await bulk.setBulkContentRating(4, ['/recipes/test.webp']);
+
+    expect(ok).toBe(true);
+    expect(updateRecipeMetadataMock).toHaveBeenCalledWith('/recipes/test.webp', { preview_nsfw_level: 4 });
+    expect(updateRecipeMetadataMock).toHaveBeenCalledTimes(1);
+    expect(saveModelMetadataMock).not.toHaveBeenCalled();
+    expect(showToastMock).toHaveBeenCalledWith(
+      'toast.models.bulkContentRatingSet',
+      { count: 1, level: 'R' },
+      'success'
+    );
+  });
+
+  it('persists the rating through the model API on model pages', async () => {
+    const bulk = await createBulkManager();
+    stateStub.currentPageType = 'loras';
+    stateStub.selectedModels.add('/models/test.safetensors');
+
+    const ok = await bulk.setBulkContentRating(8, ['/models/test.safetensors']);
+
+    expect(ok).toBe(true);
+    expect(saveModelMetadataMock).toHaveBeenCalledWith('/models/test.safetensors', { preview_nsfw_level: 8 });
+    expect(saveModelMetadataMock).toHaveBeenCalledTimes(1);
+    expect(updateRecipeMetadataMock).not.toHaveBeenCalled();
+  });
+});

tests/frontend/managers/BulkManager.marquee.test.js

@@ -0,0 +1,186 @@
+import { describe, it, beforeEach, afterEach, expect, vi } from 'vitest';
+import { state } from '../../../static/js/state/index.js';
+import { MODEL_TYPES } from '../../../static/js/api/apiConfig.js';
+import { eventManager } from '../../../static/js/utils/EventManager.js';
+import { BulkManager } from '../../../static/js/managers/BulkManager.js';
+
+function fire(type, init = {}) {
+  return new MouseEvent(type, { bubbles: true, cancelable: true, ...init });
+}
+
+describe('BulkManager marquee guards', () => {
+  beforeEach(() => {
+    vi.useFakeTimers();
+    // jsdom may not provide requestAnimationFrame; stub it so the auto-scroll loop is a no-op.
+    window.requestAnimationFrame = vi.fn();
+    window.cancelAnimationFrame = vi.fn();
+
+    eventManager.cleanup();
+    state.currentPageType = MODEL_TYPES.LORA;
+    state.bulkMode = false;
+    state.selectedModels.clear();
+
+    document.body.innerHTML = '<div class="page-content"></div>';
+    const pageContent = document.querySelector('.page-content');
+    pageContent.getBoundingClientRect = () => ({
+      top: 0,
+      left: 0,
+      right: 1000,
+      bottom: 1000,
+      width: 1000,
+      height: 1000,
+      x: 0,
+      y: 0,
+      toJSON: () => ({}),
+    });
+    pageContent.scrollBy = vi.fn();
+  });
+
+  afterEach(() => {
+    eventManager.cleanup();
+    vi.useRealTimers();
+    document.body.innerHTML = '';
+  });
+
+  function createBulkManager() {
+    const bulk = new BulkManager();
+    bulk.initialize();
+    return bulk;
+  }
+
+  it('never starts a marquee when the left button is not held', () => {
+    const bulk = createBulkManager();
+    const pageContent = document.querySelector('.page-content');
+
+    pageContent.dispatchEvent(fire('mousedown', { button: 0, clientX: 10, clientY: 10 }));
+    document.dispatchEvent(fire('mousemove', { buttons: 0, clientX: 50, clientY: 50 }));
+
+    expect(bulk.mouseDownTime).toBe(0);
+    expect(bulk.isMarqueeActive).toBe(false);
+    expect(state.bulkMode).toBe(false);
+    expect(document.querySelector('.marquee-selection')).toBeNull();
+  });
+
+  it('requires holding the left button for the drag delay before starting a marquee', () => {
+    const bulk = createBulkManager();
+    const pageContent = document.querySelector('.page-content');
+
+    pageContent.dispatchEvent(fire('mousedown', { button: 0, clientX: 10, clientY: 10 }));
+
+    // Fast movement: far enough, but too soon after mousedown.
+    document.dispatchEvent(fire('mousemove', { buttons: 1, clientX: 30, clientY: 10 }));
+    expect(state.bulkMode).toBe(false);
+    expect(bulk.isMarqueeActive).toBe(false);
+
+    // Once the hold time has elapsed, the same drag qualifies.
+    vi.advanceTimersByTime(100);
+    document.dispatchEvent(fire('mousemove', { buttons: 1, clientX: 35, clientY: 12 }));
+    expect(state.bulkMode).toBe(true);
+    expect(bulk.isMarqueeActive).toBe(true);
+    expect(document.querySelector('.marquee-selection')).not.toBeNull();
+  });
+
+  it('ends an active marquee if the left button is released without a mouseup event', () => {
+    const bulk = createBulkManager();
+    bulk.mouseDownPosition = { x: 10, y: 10 };
+    bulk.startMarqueeSelection({}, true);
+    expect(state.bulkMode).toBe(true);
+    expect(document.querySelector('.marquee-selection')).not.toBeNull();
+
+    // No mouseup was dispatched; a plain move with the button released finalizes it.
+    document.dispatchEvent(fire('mousemove', { buttons: 0, clientX: 50, clientY: 50 }));
+
+    expect(bulk.isMarqueeActive).toBe(false);
+    expect(document.querySelector('.marquee-selection')).toBeNull();
+    expect(state.bulkMode).toBe(false); // zero selected -> auto-exit
+  });
+
+  it('treats a tiny marquee as an accidental click: clears selection and exits bulk mode', () => {
+    const bulk = createBulkManager();
+    const card = document.createElement('div');
+    card.className = 'model-card selected';
+    card.dataset.filepath = '/models/test.safetensors';
+    document.body.appendChild(card);
+    state.selectedModels.add('/models/test.safetensors');
+
+    bulk.mouseDownPosition = { x: 100, y: 100 };
+    bulk.startMarqueeSelection({}, true);
+    expect(state.bulkMode).toBe(true);
+
+    bulk.endMarqueeSelection({ clientX: 103, clientY: 104 });
+
+    expect(state.bulkMode).toBe(false);
+    expect(state.selectedModels.size).toBe(0);
+    expect(card.classList.contains('selected')).toBe(false);
+  });
+
+  it('keeps selection and bulk mode when the marquee is large enough', () => {
+    const bulk = createBulkManager();
+    const card = document.createElement('div');
+    card.className = 'model-card selected';
+    card.dataset.filepath = '/models/test.safetensors';
+    document.body.appendChild(card);
+    state.selectedModels.add('/models/test.safetensors');
+
+    bulk.mouseDownPosition = { x: 100, y: 100 };
+    bulk.startMarqueeSelection({}, true);
+
+    bulk.endMarqueeSelection({ clientX: 130, clientY: 140 });
+
+    expect(state.bulkMode).toBe(true);
+    expect(state.selectedModels.has('/models/test.safetensors')).toBe(true);
+    expect(card.classList.contains('selected')).toBe(true);
+  });
+
+  it('keeps auto-scroll marquee selections when the pointer only moved a few pixels', () => {
+    const bulk = createBulkManager();
+    const pageContent = document.querySelector('.page-content');
+
+    // Card just below the press point in document coordinates.
+    const card = document.createElement('div');
+    card.className = 'model-card';
+    card.dataset.filepath = '/models/off-screen.safetensors';
+    card.getBoundingClientRect = () => ({
+      top: 950,
+      left: 400,
+      right: 600,
+      bottom: 1050,
+      width: 200,
+      height: 100,
+      x: 400,
+      y: 950,
+      toJSON: () => ({}),
+    });
+    document.body.appendChild(card);
+
+    pageContent.dispatchEvent(fire('mousedown', { button: 0, clientX: 500, clientY: 900 }));
+    vi.advanceTimersByTime(100);
+
+    // Small pointer move: enough to start the marquee, but under minMarqueeSize.
+    document.dispatchEvent(fire('mousemove', { buttons: 1, clientX: 506, clientY: 906 }));
+    expect(bulk.isMarqueeActive).toBe(true);
+
+    // Auto-scroll grows the document-space box while the pointer stays nearly still.
+    pageContent.scrollTop = 200;
+    card.getBoundingClientRect = () => ({
+      top: 750,
+      left: 400,
+      right: 600,
+      bottom: 850,
+      width: 200,
+      height: 100,
+      x: 400,
+      y: 750,
+      toJSON: () => ({}),
+    });
+    document.dispatchEvent(fire('mousemove', { buttons: 1, clientX: 506, clientY: 906 }));
+
+    expect(state.selectedModels.has('/models/off-screen.safetensors')).toBe(true);
+
+    // Release: the client-space box is tiny, but the document-space box is not.
+    document.dispatchEvent(fire('mouseup', { button: 0, clientX: 506, clientY: 906 }));
+
+    expect(state.selectedModels.has('/models/off-screen.safetensors')).toBe(true);
+    expect(state.bulkMode).toBe(true);
+  });
+});

tests/frontend/managers/settingsManager.library.test.js

@@ -106,6 +106,118 @@ afterEach(() => {
     });
 });
 
+describe('SettingsManager root selects', () => {
+    const rootCases = [
+        {
+            method: 'loadLoraRoots',
+            selectId: 'defaultLoraRoot',
+            endpoint: '/api/lm/loras/roots',
+            errorKey: 'toast.settings.loraRootsFailed',
+        },
+        {
+            method: 'loadCheckpointRoots',
+            selectId: 'defaultCheckpointRoot',
+            endpoint: '/api/lm/checkpoints/checkpoints_roots',
+            errorKey: 'toast.settings.checkpointRootsFailed',
+        },
+        {
+            method: 'loadUnetRoots',
+            selectId: 'defaultUnetRoot',
+            endpoint: '/api/lm/checkpoints/unet_roots',
+            errorKey: 'toast.settings.unetRootsFailed',
+        },
+        {
+            method: 'loadEmbeddingRoots',
+            selectId: 'defaultEmbeddingRoot',
+            endpoint: '/api/lm/embeddings/roots',
+            errorKey: 'toast.settings.embeddingRootsFailed',
+        },
+    ];
+
+    const appendRootSelect = (id) => {
+        const select = document.createElement('select');
+        select.id = id;
+        document.body.appendChild(select);
+        return select;
+    };
+
+    it.each(rootCases)(
+        'populates the $method select with roots and keeps it enabled',
+        async ({ method, selectId, endpoint }) => {
+            const manager = createManager();
+            const select = appendRootSelect(selectId);
+            select.disabled = true;
+
+            global.fetch = vi.fn().mockResolvedValue({
+                ok: true,
+                json: async () => ({
+                    success: true,
+                    roots: ['/models/root-a', '/models/root-b'],
+                }),
+            });
+
+            await manager[method]();
+
+            expect(global.fetch).toHaveBeenCalledWith(endpoint);
+            expect(Array.from(select.options).map(option => option.value)).toEqual([
+                '/models/root-a',
+                '/models/root-b',
+            ]);
+            expect(select.disabled).toBe(false);
+            expect(showToast).not.toHaveBeenCalled();
+        }
+    );
+
+    it.each(rootCases)(
+        'shows a placeholder and no error toast when $method has empty roots',
+        async ({ method, selectId, endpoint }) => {
+            const manager = createManager();
+            const select = appendRootSelect(selectId);
+
+            global.fetch = vi.fn().mockResolvedValue({
+                ok: true,
+                json: async () => ({
+                    success: true,
+                    roots: [],
+                }),
+            });
+
+            await manager[method]();
+
+            expect(global.fetch).toHaveBeenCalledWith(endpoint);
+            expect(select.options).toHaveLength(1);
+            expect(select.options[0].value).toBe('');
+            expect(select.options[0].textContent).toBe('No Default');
+            expect(select.disabled).toBe(true);
+            expect(showToast).not.toHaveBeenCalled();
+        }
+    );
+
+    it.each(rootCases)(
+        'shows an error toast when the $method roots request fails',
+        async ({ method, selectId, errorKey }) => {
+            const manager = createManager();
+            const select = appendRootSelect(selectId);
+
+            global.fetch = vi.fn().mockResolvedValue({
+                ok: false,
+                status: 500,
+            });
+
+            await manager[method]();
+
+            expect(select.options).toHaveLength(1);
+            expect(select.options[0].value).toBe('');
+            expect(select.disabled).toBe(true);
+            expect(showToast).toHaveBeenCalledWith(
+                errorKey,
+                expect.objectContaining({ message: expect.any(String) }),
+                'error',
+            );
+        }
+    );
+});
+
 describe('SettingsManager library controls', () => {
     it('loads libraries and populates the select', async () => {
         const manager = createManager();

tests/frontend/managers/updateService.test.js

@@ -1,12 +1,26 @@
 import { describe, beforeEach, afterEach, expect, it, vi } from 'vitest';
 import { UpdateService } from '../../../static/js/managers/UpdateService.js';
+import { state } from '../../../static/js/state/index.js';
 
 function createFetchResponse(payload) {
     return {
-        json: vi.fn().mockResolvedValue(payload)
+        json: vi.fn().mockResolvedValue(payload),
+        ok: true,
     };
 }
 
+function stubSettingsUpdateChannel(channel) {
+    state.global = state.global || {};
+    state.global.settings = state.global.settings || {};
+    state.global.settings.update_channel = channel;
+}
+
+function clearSettingsUpdateChannel() {
+    if (state.global?.settings) {
+        delete state.global.settings.update_channel;
+    }
+}
+
 describe('UpdateService passive checks', () => {
     let service;
     let fetchMock;
@@ -16,10 +30,13 @@ describe('UpdateService passive checks', () => {
             success: true,
             current_version: 'v1.0.0',
             latest_version: 'v1.0.0',
-            git_info: { short_hash: 'abc123' }
+            git_info: { short_hash: 'abc123' },
+            has_git: true,
         }));
         global.fetch = fetchMock;
 
+        stubSettingsUpdateChannel('release');
+
         service = new UpdateService();
         service.updateNotificationsEnabled = false;
         service.lastCheckTime = 0;
@@ -28,6 +45,7 @@ describe('UpdateService passive checks', () => {
 
     afterEach(() => {
         delete global.fetch;
+        clearSettingsUpdateChannel();
     });
 
     it('skips passive update checks when notifications are disabled', async () => {
@@ -43,3 +61,106 @@ describe('UpdateService passive checks', () => {
         expect(fetchMock).toHaveBeenCalledWith('/api/lm/check-updates?nightly=false');
     });
 });
+
+describe('UpdateService nightly notification throttling', () => {
+    let fetchMock;
+    let updateToggle;
+    let updateBadge;
+
+    function stubUpdateBadgeDom() {
+        updateToggle = document.createElement('div');
+        updateToggle.className = 'update-toggle';
+        updateBadge = document.createElement('span');
+        updateBadge.className = 'update-badge';
+        updateToggle.appendChild(updateBadge);
+        document.body.appendChild(updateToggle);
+
+        vi.spyOn(document, 'querySelector').mockImplementation((selector) => {
+            if (selector === '.update-toggle') return updateToggle;
+            if (selector === '.update-toggle .update-badge') return updateBadge;
+            return null;
+        });
+    }
+
+    function makeUpdateResponse(channel) {
+        return {
+            success: true,
+            current_version: 'v1.0.0',
+            latest_version: channel === 'nightly' ? 'main-abc1234' : 'v1.1.0',
+            update_available: true,
+            git_info: { short_hash: 'abc123' },
+            has_git: true,
+            nightly: channel === 'nightly',
+            changelog: ['test: change'],
+            releases: [],
+            behind_by: 3,
+            commit_date: '2026-07-31',
+        };
+    }
+
+    beforeEach(() => {
+        fetchMock = vi.fn().mockResolvedValue(createFetchResponse(makeUpdateResponse('release')));
+        global.fetch = fetchMock;
+        stubUpdateBadgeDom();
+    });
+
+    afterEach(() => {
+        vi.restoreAllMocks();
+        delete global.fetch;
+    });
+
+    it('shows the nightly badge once and keeps it visible for the session', async () => {
+        stubSettingsUpdateChannel('nightly');
+        fetchMock.mockResolvedValue(createFetchResponse(makeUpdateResponse('nightly')));
+
+        const service = new UpdateService();
+        service.updateNotificationsEnabled = true;
+
+        await service.checkForUpdates({ force: true });
+
+        expect(service.updateAvailable).toBe(true);
+        expect(service.nightlyBadgeShown).toBe(true);
+        expect(service.nightlyNotifyDate).toBe(service._getTodayKey());
+        expect(updateBadge.classList.contains('visible')).toBe(true);
+
+        // A repeated check within the same session keeps the badge visible.
+        await service.checkForUpdates({ force: true });
+        expect(updateBadge.classList.contains('visible')).toBe(true);
+    });
+
+    it('suppresses the nightly badge on a later session in the same day', async () => {
+        stubSettingsUpdateChannel('nightly');
+        fetchMock.mockResolvedValue(createFetchResponse(makeUpdateResponse('nightly')));
+
+        const firstService = new UpdateService();
+        firstService.updateNotificationsEnabled = true;
+        await firstService.checkForUpdates({ force: true });
+        expect(updateBadge.classList.contains('visible')).toBe(true);
+
+        // Simulate a fresh page session on the same calendar day.
+        const secondService = new UpdateService();
+        secondService.updateNotificationsEnabled = true;
+        await secondService.checkForUpdates({ force: true });
+
+        expect(secondService.updateAvailable).toBe(true);
+        expect(secondService.nightlyBadgeShown).toBe(false);
+        expect(updateBadge.classList.contains('visible')).toBe(false);
+    });
+
+    it('is not affected by the daily limit on the release channel', async () => {
+        stubSettingsUpdateChannel('release');
+        fetchMock.mockResolvedValue(createFetchResponse(makeUpdateResponse('release')));
+
+        const firstService = new UpdateService();
+        firstService.updateNotificationsEnabled = true;
+        await firstService.checkForUpdates({ force: true });
+        expect(updateBadge.classList.contains('visible')).toBe(true);
+
+        const secondService = new UpdateService();
+        secondService.updateNotificationsEnabled = true;
+        await secondService.checkForUpdates({ force: true });
+
+        expect(secondService.updateAvailable).toBe(true);
+        expect(updateBadge.classList.contains('visible')).toBe(true);
+    });
+});

tests/metadata_collector/test_metadata_collector.py

@@ -30,10 +30,10 @@ def test_metadata_hook_installs_and_traces_execution(monkeypatch, metadata_regis
 
     calls = []
 
-    def record_stub(self, node_id, class_type, inputs, outputs):
+    def record_stub(self, node_id, class_type, inputs, outputs, return_types=None):
         calls.append(("record", node_id, class_type, inputs))
 
-    def update_stub(self, node_id, class_type, outputs):
+    def update_stub(self, node_id, class_type, outputs, return_types=None):
         calls.append(("update", node_id, class_type, outputs))
 
     monkeypatch.setattr(MetadataRegistry, "record_node_execution", record_stub)
@@ -820,3 +820,227 @@ def test_lora_manager_checkpoint_and_unet_loaders_extract_models(metadata_regist
         "type": "checkpoint",
         "node_id": "unet_node",
     }
+
+
+# ---------------------------------------------------------------------------
+# MetadataOverwriteExtractor & overwrite merge tests
+# ---------------------------------------------------------------------------
+
+from py.metadata_collector.constants import OVERWRITE, METADATA_OVERWRITE_FIELDS
+from py.metadata_collector.node_extractors import MetadataOverwriteExtractor
+
+
+def test_metadata_overwrite_extractor_stores_truthy_values(metadata_registry):
+    """Extractor should store truthy inputs under the OVERWRITE category."""
+    metadata_registry.start_collection("prompt-ow")
+    metadata = metadata_registry.prompt_metadata["prompt-ow"]
+
+    inputs = {
+        "prompt": "a beautiful landscape",
+        "negative_prompt": "",
+        "seed": 42,
+        "steps": 0,
+        "cfg_scale": 7.5,
+        "sampler": "",
+        "scheduler": "",
+        "model": "myModel.safetensors",
+        "loras": "<lora:detail:0.8>",
+        "size": "1024x768",
+        "clip_skip": 0,
+        "additional_data": '{"Copyright": "CC0"}',
+    }
+
+    MetadataOverwriteExtractor.extract("ow-1", inputs, None, metadata)
+
+    assert OVERWRITE in metadata
+    assert "ow-1" in metadata[OVERWRITE]
+    params = metadata[OVERWRITE]["ow-1"]["parameters"]
+
+    # Truthy values stored
+    assert params["prompt"] == "a beautiful landscape"
+    assert params["seed"] == 42
+    assert params["cfg_scale"] == 7.5
+    assert params["model"] == "myModel.safetensors"
+    assert params["loras"] == "<lora:detail:0.8>"
+    assert params["size"] == "1024x768"
+    assert params["additional_data"] == '{"Copyright": "CC0"}'
+
+    # Falsy values NOT stored
+    assert "negative_prompt" not in params
+    assert "steps" not in params
+    assert "sampler" not in params
+    assert "scheduler" not in params
+    # clip_skip=0 is now stored (0 != sentinel -25) — wired 0 is valid
+    assert params["clip_skip"] == 0
+
+    metadata_registry.clear_metadata()
+
+
+def test_metadata_overwrite_extractor_empty_inputs(metadata_registry):
+    """Extractor with all-falsy inputs should NOT create OVERWRITE category."""
+    metadata_registry.start_collection("prompt-ow2")
+    metadata = metadata_registry.prompt_metadata["prompt-ow2"]
+
+    from py.metadata_collector.constants import CLIP_SKIP_SENTINEL
+
+    inputs = {key: "" for key in METADATA_OVERWRITE_FIELDS}
+    inputs.update({"seed": 0, "steps": 0, "cfg_scale": 0.0, "clip_skip": CLIP_SKIP_SENTINEL})
+
+    MetadataOverwriteExtractor.extract("ow-2", inputs, None, metadata)
+
+    # start_collection pre-creates empty dicts for all categories,
+    # but no node should have populated OVERWRITE with any data
+    assert not metadata[OVERWRITE]
+
+    metadata_registry.clear_metadata()
+
+
+def test_extract_generation_params_applies_overwrite(metadata_registry, populated_registry, monkeypatch):
+    """overwrite values should replace inferred params in extract_generation_params."""
+    import py.metadata_collector.metadata_processor as mp
+
+    monkeypatch.setattr(mp, "standalone_mode", False)
+
+    metadata = populated_registry["metadata"]
+    registry_obj = populated_registry["registry"]
+
+    # Simulate the MetadataOverwriteLM node having been executed with overwrite values
+    registry_obj.start_collection("promptA")
+    # Re-populate with the same data (start_collection resets)
+    registry_obj.set_current_prompt(populated_registry["prompt"])
+    metadata2 = registry_obj.prompt_metadata["promptA"]
+
+    # Inject overwrite data into metadata
+    metadata2[OVERWRITE] = {
+        "ow-1": {
+            "parameters": {
+                "seed": 777,
+                "additional_data": '{"AuthorURL": "https://civitai.com/user/foo"}',
+            },
+            "node_id": "ow-1",
+        }
+    }
+    # Copy other categories from original populated metadata
+    for cat in ("models", "prompts", "sampling", "loras", "size", "images"):
+        if cat in metadata:
+            metadata2[cat] = metadata[cat]
+    metadata2["execution_order"] = metadata["execution_order"]
+
+    params = MetadataProcessor.extract_generation_params(metadata2, id="vae")
+
+    # Overwritten values
+    assert params["seed"] == 777
+    assert params["additional_data"] == '{"AuthorURL": "https://civitai.com/user/foo"}'
+
+    # Inferred values still present (not overwritten)
+    assert params["prompt"] == "A castle on a hill"
+    assert params["cfg_scale"] == 7.5
+    assert params["checkpoint"] == "model.safetensors"
+
+    registry_obj.clear_metadata()
+
+
+def test_extract_generation_params_overwrite_falsy_skipped(metadata_registry, populated_registry, monkeypatch):
+    """Overwrite entries with falsy values should NOT replace inferred params."""
+    import py.metadata_collector.metadata_processor as mp
+
+    monkeypatch.setattr(mp, "standalone_mode", False)
+
+    metadata = populated_registry["metadata"]
+    registry_obj = populated_registry["registry"]
+
+    registry_obj.start_collection("promptA")
+    registry_obj.set_current_prompt(populated_registry["prompt"])
+    metadata2 = registry_obj.prompt_metadata["promptA"]
+
+    # Inject overwrite with falsy values (except clip_skip=0 which is now
+    # treated as a valid wired input thanks to the -25 sentinel)
+    metadata2[OVERWRITE] = {
+        "ow-1": {
+            "parameters": {
+                "seed": 0,
+                "steps": 0,
+                "cfg_scale": 0.0,
+                "prompt": "",
+                "clip_skip": 0,
+            },
+            "node_id": "ow-1",
+        }
+    }
+    for cat in ("models", "prompts", "sampling", "loras", "size", "images"):
+        if cat in metadata:
+            metadata2[cat] = metadata[cat]
+    metadata2["execution_order"] = metadata["execution_order"]
+
+    params = MetadataProcessor.extract_generation_params(metadata2, id="vae")
+
+    # Falsy overwrites should NOT have replaced inferred values
+    assert params["prompt"] == "A castle on a hill"
+    assert params["cfg_scale"] == 7.5
+
+    # clip_skip=0 is a valid wired value (not the -25 sentinel) — should be applied
+    assert params["clip_skip"] == 0
+
+    registry_obj.clear_metadata()
+
+
+def test_fill_missing_metadata_skips_overwrite_for_bypassed_node(metadata_registry):
+    """Bypassed (mode=4) node should not have OVERWRITE filled from cache."""
+    metadata_registry.start_collection("prompt-bypass")
+
+    # Simulate a previous execution that cached overwrite data
+    metadata_registry.record_node_execution(
+        "ow-1",
+        "MetadataOverwriteLM",
+        {"seed": 99, "prompt": "test", "steps": 0, "cfg_scale": 0.0,
+         "negative_prompt": "", "sampler": "", "scheduler": "", "model": "",
+         "loras": "", "size": "", "clip_skip": 0, "additional_data": ""},
+        None,
+    )
+
+    # Now start a new prompt where the node is bypassed (mode=4)
+    metadata_registry.start_collection("prompt-bypass-2")
+    original_prompt = {
+        "ow-1": {"class_type": "MetadataOverwriteLM", "inputs": {}, "mode": 4},
+    }
+    metadata_registry.set_current_prompt(
+        SimpleNamespace(original_prompt=original_prompt)
+    )
+
+    metadata = metadata_registry.get_metadata("prompt-bypass-2")
+
+    # The overwrite data should NOT be present (node was bypassed, not
+    # a cache hit — it should not inherit previous execution's overwrite)
+    assert "ow-1" not in metadata.get(OVERWRITE, {})
+
+    metadata_registry.clear_metadata()
+
+
+def test_fill_missing_metadata_fills_overwrite_for_muted_node(metadata_registry):
+    """Muted (mode=2) node should also not have OVERWRITE filled from cache."""
+    metadata_registry.start_collection("prompt-mute")
+
+    # Simulate a previous execution that cached overwrite data
+    metadata_registry.record_node_execution(
+        "ow-1",
+        "MetadataOverwriteLM",
+        {"seed": 88, "prompt": "test2", "steps": 0, "cfg_scale": 0.0,
+         "negative_prompt": "", "sampler": "", "scheduler": "", "model": "",
+         "loras": "", "size": "", "clip_skip": 0, "additional_data": ""},
+        None,
+    )
+
+    # Start a new prompt where the node is muted (mode=2)
+    metadata_registry.start_collection("prompt-mute-2")
+    original_prompt = {
+        "ow-1": {"class_type": "MetadataOverwriteLM", "inputs": {}, "mode": 2},
+    }
+    metadata_registry.set_current_prompt(
+        SimpleNamespace(original_prompt=original_prompt)
+    )
+
+    metadata = metadata_registry.get_metadata("prompt-mute-2")
+
+    assert "ow-1" not in metadata.get(OVERWRITE, {})
+
+    metadata_registry.clear_metadata()

tests/nodes/test_lora_stack_combiner.py

@@ -1,4 +1,11 @@
-from py.nodes.lora_stack_combiner import LoraStackCombinerLM
+import types
+
+import pytest
+
+from py.nodes.lora_stack_combiner import (
+    LoraStackCombinerLM,
+    _LoraStackOptionalInputs,
+)
 
 
 def test_combine_stacks_preserves_order():
@@ -49,3 +56,109 @@ def test_combine_stacks_allows_duplicate_entries():
     (combined_stack,) = node.combine_stacks([duplicate_entry], [duplicate_entry])
 
     assert combined_stack == [duplicate_entry, duplicate_entry]
+
+
+def test_combine_stacks_returns_empty_when_both_unconnected():
+    node = LoraStackCombinerLM()
+
+    (combined_stack,) = node.combine_stacks()
+
+    assert combined_stack == []
+
+
+def test_combine_stacks_returns_other_when_one_unconnected():
+    node = LoraStackCombinerLM()
+    stack_a = [("folder/a.safetensors", 0.7, 0.6)]
+
+    (combined_stack_a,) = node.combine_stacks(lora_stack1=stack_a)
+    (combined_stack_b,) = node.combine_stacks(lora_stack2=stack_a)
+
+    assert combined_stack_a == stack_a
+    assert combined_stack_b == stack_a
+
+
+def test_combine_stacks_with_dynamic_third_slot():
+    node = LoraStackCombinerLM()
+    stack_a = [("folder/a.safetensors", 0.7, 0.6)]
+    stack_b = [("folder/b.safetensors", 0.8, 0.8)]
+    stack_c = [("folder/c.safetensors", 1.0, 0.9)]
+
+    (combined_stack,) = node.combine_stacks(
+        lora_stack1=stack_a, lora_stack2=stack_b, lora_stack3=stack_c
+    )
+
+    assert combined_stack == stack_a + stack_b + stack_c
+
+
+def test_combine_stacks_orders_by_slot_number_not_call_order():
+    node = LoraStackCombinerLM()
+    stack_a = [("folder/a.safetensors", 0.7, 0.6)]
+    stack_b = [("folder/b.safetensors", 0.8, 0.8)]
+    stack_c = [("folder/c.safetensors", 1.0, 0.9)]
+
+    (combined_stack,) = node.combine_stacks(
+        lora_stack3=stack_c, lora_stack2=stack_b, lora_stack1=stack_a
+    )
+
+    assert combined_stack == stack_a + stack_b + stack_c
+
+
+def test_combine_stacks_accepts_only_dynamic_slot():
+    node = LoraStackCombinerLM()
+    stack_c = [("folder/c.safetensors", 1.0, 0.9)]
+
+    (combined_stack,) = node.combine_stacks(lora_stack3=stack_c)
+
+    assert combined_stack == stack_c
+
+
+def test_combine_stacks_handles_legacy_input_names():
+    node = LoraStackCombinerLM()
+    stack_a = [("folder/a.safetensors", 0.7, 0.6)]
+    stack_b = [("folder/b.safetensors", 0.8, 0.8)]
+
+    (combined_stack,) = node.combine_stacks(lora_stack_a=stack_a, lora_stack_b=stack_b)
+
+    assert combined_stack == stack_a + stack_b
+
+
+def test_input_types_exposes_two_default_slots():
+    input_types = LoraStackCombinerLM.INPUT_TYPES()
+
+    assert set(input_types["optional"]) == {"lora_stack1", "lora_stack2"}
+    assert input_types["optional"]["lora_stack1"][0] == "LORA_STACK"
+    assert input_types["optional"]["lora_stack2"][0] == "LORA_STACK"
+
+
+def test_input_types_recognizes_dynamic_slots_from_get_input_info(monkeypatch):
+    frames = [None, None, types.SimpleNamespace(function="get_input_info")]
+    monkeypatch.setattr(
+        "py.nodes.lora_stack_combiner.inspect.stack", lambda: frames
+    )
+
+    input_types = LoraStackCombinerLM.INPUT_TYPES()
+    optional = input_types["optional"]
+
+    assert "lora_stack3" in optional
+    assert optional["lora_stack3"][0] == "LORA_STACK"
+    assert "lora_stack25" in optional
+    assert optional["lora_stack25"][0] == "LORA_STACK"
+
+
+def test_lora_stack_optional_inputs_proxy():
+    proxy = _LoraStackOptionalInputs({"lora_stack1": ("LORA_STACK", {})})
+
+    assert "lora_stack1" in proxy
+    assert "lora_stack2" in proxy
+    assert "lora_stack10" in proxy
+    assert "lora_stack_a" in proxy
+    assert "lora_stack" not in proxy
+    assert "lora_stacka" not in proxy
+    assert "lora_stack_1" not in proxy
+    assert "text" not in proxy
+
+    assert proxy["lora_stack1"][0] == "LORA_STACK"
+    assert proxy["lora_stack5"][0] == "LORA_STACK"
+
+    with pytest.raises(KeyError):
+        proxy["not_a_stack"]

tests/nodes/test_save_image.py

@@ -59,7 +59,7 @@ def test_save_image_defaults_to_writing_png_metadata(monkeypatch, tmp_path):
 
     image_path = tmp_path / "sample_00001_.png"
     with Image.open(image_path) as img:
-        assert img.info["parameters"] == "prompt text\nSeed: 123"
+        assert img.info["parameters"] == "prompt text\nSeed: 123, Version: ComfyUI"
 
 
 def test_save_image_skips_png_parameters_when_metadata_disabled_and_keeps_workflow(
@@ -363,3 +363,102 @@ def test_save_image_as_recipe_writes_recipe_without_async_scanner_calls(
     assert recipe["gen_params"] == {"prompt": "prompt text", "seed": 123}
     assert scanner._json_path_map[recipe["id"]] == os.path.normpath(str(recipe_files[0]))
     assert scanner.fts_updates == [(recipe["id"], "add")]
+
+
+# ---------------------------------------------------------------------------
+# Tests for webp_method and jpeg_subsampling parameters
+# ---------------------------------------------------------------------------
+
+def _capture_save_kwargs(monkeypatch):
+    """Monkeypatch Image.Image.save to capture kwargs while still saving to disk."""
+    real_save = Image.Image.save
+    captured_kwargs = {}
+
+    def _fake_save(self, fp, *args, **kwargs):
+        captured_kwargs.update(kwargs)
+        return real_save(self, fp, *args, **kwargs)
+
+    monkeypatch.setattr(Image.Image, "save", _fake_save)
+    return captured_kwargs
+
+
+def test_webp_method_default_passed_to_pillow_save(monkeypatch, tmp_path):
+    _configure_save_paths(monkeypatch, tmp_path)
+    _configure_metadata(monkeypatch, {"prompt": "test", "seed": 1})
+    captured = _capture_save_kwargs(monkeypatch)
+
+    node = SaveImageLM()
+    node.save_images([_make_image()], "ComfyUI", "webp", id="node-1")
+
+    assert "method" in captured
+    assert captured["method"] == 6
+
+
+def test_webp_method_custom_value_passed_to_pillow_save(monkeypatch, tmp_path):
+    _configure_save_paths(monkeypatch, tmp_path)
+    _configure_metadata(monkeypatch, {"prompt": "test", "seed": 1})
+    captured = _capture_save_kwargs(monkeypatch)
+
+    node = SaveImageLM()
+    node.save_images(
+        [_make_image()], "ComfyUI", "webp", id="node-1", webp_method=3
+    )
+
+    assert captured["method"] == 3
+
+
+def test_jpeg_subsampling_default_passed_to_pillow_save(monkeypatch, tmp_path):
+    _configure_save_paths(monkeypatch, tmp_path)
+    _configure_metadata(monkeypatch, {"prompt": "test", "seed": 1})
+    captured = _capture_save_kwargs(monkeypatch)
+
+    node = SaveImageLM()
+    node.save_images([_make_image()], "ComfyUI", "jpeg", id="node-1")
+
+    assert "subsampling" in captured
+    assert captured["subsampling"] == 0
+
+
+def test_jpeg_subsampling_custom_value_passed_to_pillow_save(monkeypatch, tmp_path):
+    _configure_save_paths(monkeypatch, tmp_path)
+    _configure_metadata(monkeypatch, {"prompt": "test", "seed": 1})
+    captured = _capture_save_kwargs(monkeypatch)
+
+    node = SaveImageLM()
+    node.save_images(
+        [_make_image()], "ComfyUI", "jpeg", id="node-1", jpeg_subsampling=1
+    )
+
+    assert captured["subsampling"] == 1
+
+
+class TestParameterDefaultConsistency:
+    """Verify defaults match across INPUT_TYPES, save_images(), and process_image()."""
+
+    def test_webp_method_defaults_are_consistent(self):
+        input_types = SaveImageLM.INPUT_TYPES()
+        optional = input_types["optional"]
+
+        assert optional["webp_method"][1]["default"] == 6
+        assert SaveImageLM.save_images.__defaults__[4] == 6  # positional: webp_method=6 is at index 4
+        assert SaveImageLM.process_image.__defaults__[6] == 6
+
+    def test_jpeg_subsampling_defaults_are_consistent(self):
+        input_types = SaveImageLM.INPUT_TYPES()
+        optional = input_types["optional"]
+
+        assert optional["jpeg_subsampling"][1]["default"] == 0
+        assert SaveImageLM.save_images.__defaults__[5] == 0
+        assert SaveImageLM.process_image.__defaults__[7] == 0
+
+
+def test_png_does_not_pass_webp_method_or_jpeg_subsampling(monkeypatch, tmp_path):
+    _configure_save_paths(monkeypatch, tmp_path)
+    _configure_metadata(monkeypatch, {"prompt": "test", "seed": 1})
+    captured = _capture_save_kwargs(monkeypatch)
+
+    node = SaveImageLM()
+    node.save_images([_make_image()], "ComfyUI", "png", id="node-1")
+
+    assert "method" not in captured
+    assert "subsampling" not in captured

tests/routes/test_misc_routes.py

@@ -900,18 +900,28 @@ class FakeMetadataProvider:
     async def get_model_versions(self, _model_id):
         return {"modelVersions": [], "name": "", "type": "lora"}
 
-    async def get_user_models(self, _username):
+    async def get_user_models(self, _username, cursor=None):
-        return []
+        return {"items": [], "nextCursor": None}
+
+    async def get_creator_model_count(self, _username):
+        return None
 
 
 class FakeUserModelsProvider(FakeMetadataProvider):
-    def __init__(self, models):
+    def __init__(self, models, next_cursor=None, estimated_total=None):
         self.models = models
+        self.next_cursor = next_cursor
+        self.estimated_total = estimated_total
         self.received_usernames: list[str] = []
+        self.received_cursors: list = []
 
-    async def get_user_models(self, username):
+    async def get_user_models(self, username, cursor=None):
         self.received_usernames.append(username)
-        return self.models
+        self.received_cursors.append(cursor)
+        return {"items": self.models, "nextCursor": self.next_cursor}
+
+    async def get_creator_model_count(self, _username):
+        return self.estimated_total
 
 
 async def fake_metadata_provider_factory():
@@ -1286,6 +1296,88 @@ async def test_get_civitai_user_models_requires_username():
     assert "username" in payload["error"].lower()
 
 
+@pytest.mark.asyncio
+async def test_get_civitai_user_models_returns_pagination_fields():
+    models = [
+        {
+            "id": 1,
+            "name": "Model A",
+            "type": "LORA",
+            "tags": [],
+            "modelVersions": [
+                {"id": 100, "name": "v1", "images": [{"url": "http://example.com/a.jpg"}]},
+            ],
+        },
+        {
+            "id": 2,
+            "name": "Unsupported",
+            "type": "Other",
+            "modelVersions": [{"id": 200, "name": "v1"}],
+        },
+    ]
+
+    provider = FakeUserModelsProvider(models, next_cursor="cursor-token", estimated_total=2140)
+
+    async def provider_factory():
+        return provider
+
+    handler = ModelLibraryHandler(
+        ServiceRegistryAdapter(
+            get_lora_scanner=fake_scanner_factory,
+            get_checkpoint_scanner=fake_scanner_factory,
+            get_embedding_scanner=fake_scanner_factory,
+            get_downloaded_version_history_service=fake_download_history_service_factory,
+        ),
+        metadata_provider_factory=provider_factory,
+    )
+
+    response = await handler.get_civitai_user_models(
+        FakeRequest(query={"username": "pixel"})
+    )
+    payload = json.loads(response.text)
+
+    assert response.status == 200
+    assert payload["success"] is True
+    # modelCount only counts models surviving the type filter
+    assert payload["modelCount"] == 1
+    assert payload["nextCursor"] == "cursor-token"
+    assert payload["hasMore"] is True
+    # first page includes the estimated total
+    assert payload["estimatedTotal"] == 2140
+    assert provider.received_cursors == [None]
+
+
+@pytest.mark.asyncio
+async def test_get_civitai_user_models_passes_cursor_and_omits_estimate():
+    provider = FakeUserModelsProvider([], next_cursor=None, estimated_total=999)
+
+    async def provider_factory():
+        return provider
+
+    handler = ModelLibraryHandler(
+        ServiceRegistryAdapter(
+            get_lora_scanner=fake_scanner_factory,
+            get_checkpoint_scanner=fake_scanner_factory,
+            get_embedding_scanner=fake_scanner_factory,
+            get_downloaded_version_history_service=fake_download_history_service_factory,
+        ),
+        metadata_provider_factory=provider_factory,
+    )
+
+    response = await handler.get_civitai_user_models(
+        FakeRequest(query={"username": "pixel", "cursor": "opaque-token"})
+    )
+    payload = json.loads(response.text)
+
+    assert response.status == 200
+    assert payload["success"] is True
+    assert payload["nextCursor"] is None
+    assert payload["hasMore"] is False
+    # cursor requests must not include the estimated total
+    assert payload["estimatedTotal"] is None
+    assert provider.received_cursors == ["opaque-token"]
+
+
 def test_ensure_handler_mapping_caches_result():
     call_records = []
 

tests/routes/test_update_routes.py

@@ -1,10 +1,33 @@
 import logging
+import os
+import shutil
 from aiohttp import ClientError
+from aiohttp import web
 import pytest
 
 from py.routes import update_routes
 
 
+def _fake_request(body=None, query_params=None):
+    from multidict import MultiDict
+
+    q = MultiDict(query_params or {})
+
+    req = type("Req", (), {
+        "has_body": body is not None,
+        "match_info": {},
+        "rel_url": type("U", (), {"query": q})(),
+        "query": q,
+        "app": {},
+    })()
+
+    async def _json():
+        return body or {}
+
+    req.json = _json
+    return req
+
+
 class OfflineDownloader:
     async def make_request(self, *_, **__):
         return False, "Cannot connect to host"
@@ -53,10 +76,12 @@ async def test_get_nightly_version_network_error_logs_warning(monkeypatch, caplo
     caplog.set_level(logging.WARNING)
     monkeypatch.setattr(update_routes, "get_downloader", lambda: _stub_downloader(RaisingDownloader()))
 
-    version, changelog = await update_routes.UpdateRoutes._get_nightly_version()
+    version, changelog, behind_by, commit_date = await update_routes.UpdateRoutes._get_nightly_version()
 
     assert version == "main"
     assert changelog == []
+    assert behind_by == 0
+    assert commit_date == ""
     assert "Unable to reach GitHub for nightly version" in caplog.text
     assert "Traceback" not in caplog.text
 
@@ -236,3 +261,305 @@ async def test_perform_git_update_stable_preserves_user_dirs(monkeypatch, tmp_pa
     clean_args = clean_calls[0][1]
     for name in update_routes._PRESERVE_DIRS:
         assert name in clean_args, f"{name} missing from git clean excludes (stable)"
+
+def test_init_git_repo_creates_valid_repo(tmp_path, monkeypatch):
+    if not shutil.which("git"):
+        pytest.skip("git executable not found")
+
+    plugin_root = tmp_path / "plugin"
+    plugin_root.mkdir()
+    (plugin_root / ".tracking").write_text("pyproject.toml")
+    (plugin_root / "settings.json").write_text('{"some": "value"}')
+
+    try:
+        success, version = update_routes.UpdateRoutes._init_git_repo(str(plugin_root))
+    except Exception as e:
+        pytest.skip(f"Network unavailable for git fetch: {e}")
+
+    assert success is True
+    assert version.startswith("main-")
+    assert len(version) > len("main-")
+    assert (plugin_root / ".git").is_dir()
+    assert not (plugin_root / ".tracking").exists()
+    assert (plugin_root / "settings.json").exists()
+    assert (plugin_root / "pyproject.toml").exists()
+
+
+@pytest.mark.asyncio
+async def test_switch_channel_invalid_channel_returns_error():
+    req = _fake_request({"channel": "bad_channel"})
+    resp = await update_routes.UpdateRoutes.switch_channel(req)
+
+    data = _raw_body(resp)
+    assert not data["success"]
+    assert "Invalid channel" in data["error"]
+
+
+@pytest.mark.asyncio
+async def test_switch_channel_to_nightly_without_git_inits_repo(monkeypatch, tmp_path):
+    routes_file = tmp_path / "py" / "routes" / "update_routes.py"
+    routes_file.parent.mkdir(parents=True)
+    routes_file.write_text("")
+    monkeypatch.setattr(update_routes, "__file__", str(routes_file))
+    monkeypatch.setattr(update_routes, "ensure_settings_file", lambda logger: str(tmp_path / "settings.json"))
+    monkeypatch.setattr(
+        update_routes.UpdateRoutes,
+        "_init_git_repo",
+        staticmethod(lambda plugin_root: (True, "main-fedcba9")),
+    )
+
+    req = _fake_request({"channel": "nightly"})
+    resp = await update_routes.UpdateRoutes.switch_channel(req)
+    data = _raw_body(resp)
+
+    assert data["success"] is True
+    assert data["channel"] == "nightly"
+    assert data["new_version"] == "main-fedcba9"
+
+
+@pytest.mark.asyncio
+async def test_switch_channel_to_nightly_with_git_calls_git_update(monkeypatch, tmp_path):
+    routes_file = tmp_path / "py" / "routes" / "update_routes.py"
+    routes_file.parent.mkdir(parents=True)
+    routes_file.write_text("")
+    monkeypatch.setattr(update_routes, "__file__", str(routes_file))
+    monkeypatch.setattr(update_routes, "ensure_settings_file", lambda logger: str(tmp_path / "settings.json"))
+
+    (tmp_path / ".git").mkdir()
+
+    async def _fake_git_update(*args, **kwargs):
+        return True, "main-1111111"
+
+    monkeypatch.setattr(
+        update_routes.UpdateRoutes, "_perform_git_update", _fake_git_update
+    )
+
+    req = _fake_request({"channel": "nightly"})
+    resp = await update_routes.UpdateRoutes.switch_channel(req)
+    data = _raw_body(resp)
+
+    assert data["success"] is True
+    assert data["channel"] == "nightly"
+    assert data["new_version"] == "main-1111111"
+
+
+@pytest.mark.asyncio
+async def test_switch_channel_to_release_with_git_calls_git_update(monkeypatch, tmp_path):
+    routes_file = tmp_path / "py" / "routes" / "update_routes.py"
+    routes_file.parent.mkdir(parents=True)
+    routes_file.write_text("")
+    monkeypatch.setattr(update_routes, "__file__", str(routes_file))
+    monkeypatch.setattr(update_routes, "ensure_settings_file", lambda logger: str(tmp_path / "settings.json"))
+
+    (tmp_path / ".git").mkdir()
+
+    async def _fake_git_update(*args, **kwargs):
+        return True, "v9.9.9"
+
+    monkeypatch.setattr(
+        update_routes.UpdateRoutes, "_perform_git_update", _fake_git_update
+    )
+
+    req = _fake_request({"channel": "release"})
+    resp = await update_routes.UpdateRoutes.switch_channel(req)
+    data = _raw_body(resp)
+
+    assert data["success"] is True
+    assert data["channel"] == "release"
+    assert data["new_version"] == "v9.9.9"
+
+
+@pytest.mark.asyncio
+async def test_switch_channel_to_release_without_git_still_downloads_zip(monkeypatch, tmp_path):
+    routes_file = tmp_path / "py" / "routes" / "update_routes.py"
+    routes_file.parent.mkdir(parents=True)
+    routes_file.write_text("")
+    monkeypatch.setattr(update_routes, "__file__", str(routes_file))
+    monkeypatch.setattr(update_routes, "ensure_settings_file", lambda logger: str(tmp_path / "settings.json"))
+
+    async def _fake_zip(*args, **kwargs):
+        return True, "v2.0.0"
+
+    monkeypatch.setattr(
+        update_routes.UpdateRoutes, "_download_and_replace_zip", _fake_zip
+    )
+
+    req = _fake_request({"channel": "release"})
+    resp = await update_routes.UpdateRoutes.switch_channel(req)
+    data = _raw_body(resp)
+
+    assert data["success"] is True
+    assert data["channel"] == "release"
+    assert data["new_version"] == "v2.0.0"
+
+
+class _NightlyDownloader:
+    """Returns a fake main-branch commit AND a compare response."""
+
+    commit_sha = "7777777"
+    commit_msg = "test: add nightly feature"
+    commit_date = "2026-07-27T12:00:00Z"
+    behind_by = 5
+
+    async def make_request(self, method, url, **kwargs):
+        if "/compare/" in url:
+            return True, {"behind_by": self.behind_by}
+        return True, {
+            "sha": self.commit_sha,
+            "commit": {
+                "message": self.commit_msg,
+                "committer": {"date": self.commit_date},
+            },
+        }
+
+
+@pytest.mark.asyncio
+async def test_get_nightly_version_parses_behind_by(monkeypatch):
+    monkeypatch.setattr(update_routes, "get_downloader", lambda: _stub_downloader(_NightlyDownloader()))
+
+    version, changelog, behind_by, commit_date = await update_routes.UpdateRoutes._get_nightly_version(
+        local_hash="abc1234"
+    )
+
+    assert version == "main-7777777"
+    assert behind_by == 5
+    assert commit_date == "2026-07-27"
+    assert len(changelog) == 1
+    assert changelog[0] == "test: add nightly feature"
+
+
+class _AheadCompareDownloader:
+    """Fake compare API response with status='ahead' (main is ahead of local)."""
+
+    commit_sha = "9999999"
+    commit_msg = "latest commit"
+    commit_date = "2026-07-28T00:00:00Z"
+    ahead_by = 3
+
+    async def make_request(self, method, url, **kwargs):
+        if "/compare/" in url:
+            return True, {"status": "ahead", "ahead_by": self.ahead_by, "behind_by": 0}
+        return True, {
+            "sha": self.commit_sha,
+            "commit": {
+                "message": self.commit_msg,
+                "committer": {"date": self.commit_date},
+            },
+        }
+
+
+@pytest.mark.asyncio
+async def test_get_nightly_version_reads_ahead_by_when_ahead(monkeypatch):
+    """compare/{local}...main returns status='ahead' → read ahead_by."""
+    monkeypatch.setattr(update_routes, "get_downloader", lambda: _stub_downloader(_AheadCompareDownloader()))
+
+    version, changelog, behind_by, commit_date = await update_routes.UpdateRoutes._get_nightly_version(
+        local_hash="oldhash"
+    )
+
+    assert version == "main-9999999"
+    assert behind_by == 3
+    assert commit_date == "2026-07-28"
+
+
+class _DivergedCompareDownloader:
+    """Fake compare API response with status='diverged' (both have unique commits)."""
+
+    commit_sha = "aaaaaaa"
+    commit_msg = "diverged test"
+    commit_date = "2026-07-29T00:00:00Z"
+
+    async def make_request(self, method, url, **kwargs):
+        if "/compare/" in url:
+            return True, {"status": "diverged", "ahead_by": 5, "behind_by": 2}
+        return True, {
+            "sha": self.commit_sha,
+            "commit": {
+                "message": self.commit_msg,
+                "committer": {"date": self.commit_date},
+            },
+        }
+
+
+@pytest.mark.asyncio
+async def test_get_nightly_version_reads_ahead_by_when_diverged(monkeypatch):
+    """compare/{local}...main returns status='diverged' → read ahead_by (remote ahead)."""
+    monkeypatch.setattr(update_routes, "get_downloader", lambda: _stub_downloader(_DivergedCompareDownloader()))
+
+    version, changelog, behind_by, commit_date = await update_routes.UpdateRoutes._get_nightly_version(
+        local_hash="divhash"
+    )
+
+    assert behind_by == 5
+
+
+class _CheckUpdatesDownloader:
+    """Fake downloader returning both a release list and a nightly commit + compare."""
+
+    commit_sha = "8888888"
+    commit_date = "2026-07-28T00:00:00Z"
+
+    async def make_request(self, method, url, **kwargs):
+        if "/releases" in url:
+            return True, [
+                {
+                    "tag_name": "v3.0.0",
+                    "body": "- Feature A\n- Feature B",
+                    "published_at": "2026-07-20T00:00:00Z",
+                }
+            ]
+        if "/compare/" in url:
+            return True, {"behind_by": 3}
+        return True, {
+            "sha": self.commit_sha + "0" * 33,
+            "commit": {
+                "message": "latest commit",
+                "committer": {"date": self.commit_date},
+            },
+        }
+
+
+@pytest.mark.asyncio
+async def test_check_updates_nightly_response_includes_behind_and_date(monkeypatch, tmp_path):
+    monkeypatch.setattr(update_routes, "get_downloader", lambda: _stub_downloader(_CheckUpdatesDownloader()))
+
+    monkeypatch.setattr(
+        update_routes.UpdateRoutes,
+        "_get_local_version",
+        staticmethod(lambda: "v1.0.0"),
+    )
+    monkeypatch.setattr(
+        update_routes.UpdateRoutes,
+        "_get_git_info",
+        staticmethod(lambda: {
+            "commit_hash": "abc1234",
+            "short_hash": "abc1234",
+            "branch": "main",
+            "commit_date": "2026-01-01",
+        }),
+    )
+
+    routes_file = tmp_path / "py" / "routes" / "update_routes.py"
+    routes_file.parent.mkdir(parents=True)
+    routes_file.write_text("")
+    monkeypatch.setattr(update_routes, "__file__", str(routes_file))
+    (tmp_path / ".git").mkdir()
+
+    req = _fake_request(query_params={"nightly": "true"})
+    resp = await update_routes.UpdateRoutes.check_updates(req)
+    data = _raw_body(resp)
+
+    assert data["success"] is True
+    assert data["nightly"] is True
+    assert data["has_git"] is True
+    assert data["behind_by"] == 3
+    assert data["commit_date"] == "2026-07-28"
+    assert data["latest_version"] == "main-8888888"
+    assert isinstance(data["releases"], list)
+    assert len(data["releases"]) == 1
+    assert data["releases"][0]["version"] == "v3.0.0"
+
+
+def _raw_body(response):
+    import json
+    return json.loads(response._body.decode())

tests/services/test_base_model_service.py

@@ -183,7 +183,7 @@ class FakeCache:
     def __init__(self, items):
         self.items = list(items)
 
-    async def get_sorted_data(self, sort_key, order):
+    async def get_sorted_data(self, sort_key, order, seed=None):
         if sort_key == "name":
             data = sorted(self.items, key=lambda x: x["model_name"].lower())
             if order == "desc":
@@ -1252,3 +1252,69 @@ async def test_get_model_civitai_url_falls_back_when_host_setting_is_not_a_strin
         "model_id": "123",
         "version_id": "456",
     }
+
+
+class TestHfGroupKey:
+    """Tests for _extract_hf_group_key and _extract_group_key."""
+
+    # --- _extract_hf_group_key ---
+
+    def test_hf_group_key_valid_url(self):
+        """Standard HF URL returns hf:user/repo."""
+        item = {"hf_url": "https://huggingface.co/unsloth/qwen-edit"}
+        assert BaseModelService._extract_hf_group_key(item) == "hf:unsloth/qwen-edit"
+
+    def test_hf_group_key_url_with_subpath(self):
+        """URL with subpath still extracts just owner/repo."""
+        item = {"hf_url": "https://huggingface.co/user/repo/resolve/main/file.safetensors"}
+        assert BaseModelService._extract_hf_group_key(item) == "hf:user/repo"
+
+    def test_hf_group_key_empty_url(self):
+        """Empty hf_url returns None."""
+        assert BaseModelService._extract_hf_group_key({"hf_url": ""}) is None
+
+    def test_hf_group_key_no_url(self):
+        """Missing hf_url key returns None."""
+        assert BaseModelService._extract_hf_group_key({}) is None
+
+    def test_hf_group_key_none_url(self):
+        """None hf_url returns None."""
+        assert BaseModelService._extract_hf_group_key({"hf_url": None}) is None
+
+    def test_hf_group_key_invalid_url(self):
+        """Malformed HF URL returns None."""
+        assert BaseModelService._extract_hf_group_key({"hf_url": "not-a-url"}) is None
+        assert BaseModelService._extract_hf_group_key({"hf_url": "https://example.com"}) is None
+
+    # --- _extract_group_key ---
+
+    def test_group_key_civitai_only(self):
+        """CivitAI modelId returned as int."""
+        item = {"civitai": {"modelId": 123}}
+        assert BaseModelService._extract_group_key(item) == 123
+
+    def test_group_key_hf_only(self):
+        """HF-only item returns hf:user/repo string."""
+        item = {"hf_url": "https://huggingface.co/user/repo"}
+        assert BaseModelService._extract_group_key(item) == "hf:user/repo"
+
+    def test_group_key_civitai_preferred(self):
+        """CivitAI modelId takes precedence over hf_url."""
+        item = {
+            "civitai": {"modelId": 456},
+            "hf_url": "https://huggingface.co/other/repo",
+        }
+        assert BaseModelService._extract_group_key(item) == 456
+
+    def test_group_key_neither(self):
+        """No CivitAI or HF returns None."""
+        assert BaseModelService._extract_group_key({}) is None
+        assert BaseModelService._extract_group_key({"some": "data"}) is None
+
+    def test_group_key_civitai_none_model_id(self):
+        """civitai.modelId=None falls through to HF."""
+        item = {
+            "civitai": {"modelId": None},
+            "hf_url": "https://huggingface.co/user/repo",
+        }
+        assert BaseModelService._extract_group_key(item) == "hf:user/repo"

tests/services/test_check_pending_models.py

@@ -363,6 +363,148 @@ async def test_check_pending_models_handles_corrupted_progress_file(
     assert result["pending_count"] == 1
 
 
+@pytest.mark.asyncio
+@pytest.mark.usefixtures("tmp_path")
+async def test_check_pending_models_uses_bulk_folder_index_for_large_libraries(
+    monkeypatch: pytest.MonkeyPatch,
+    tmp_path,
+    settings_manager,
+):
+    """For >1000 candidates the pre-check scans the library root once instead of
+    probing every folder individually."""
+
+    ws_manager = RecordingWebSocketManager()
+    manager = download_module.DownloadManager(ws_manager=ws_manager)
+
+    monkeypatch.setitem(settings_manager.settings, "example_images_path", str(tmp_path))
+
+    # 1500 unprocessed models triggers the bulk lookup path
+    models = [
+        {"sha256": f"{i:064x}", "model_name": f"Model {i}"}
+        for i in range(1500)
+    ]
+
+    # Create folders with files for the first 500 models
+    for i in range(500):
+        model_dir = tmp_path / f"{i:064x}"
+        model_dir.mkdir()
+        (model_dir / "image_0.png").write_text("data")
+
+    _patch_scanners(monkeypatch, lora_scanner=StubScanner(models))
+
+    per_model_checks = 0
+
+    def counting_model_directory_has_files(path: str) -> bool:
+        nonlocal per_model_checks
+        per_model_checks += 1
+        return False
+
+    monkeypatch.setattr(
+        download_module,
+        "_model_directory_has_files",
+        counting_model_directory_has_files,
+    )
+
+    result = await manager.check_pending_models(["lora"])
+
+    assert result["success"] is True
+    assert result["total_models"] == 1500
+    assert result["pending_count"] == 1000
+    assert result["needs_download"] is True
+    # The per-folder check should not be used once we cross the threshold.
+    assert per_model_checks == 0
+
+
+@pytest.mark.asyncio
+@pytest.mark.usefixtures("tmp_path")
+async def test_check_pending_models_uses_per_folder_check_for_small_candidate_sets(
+    monkeypatch: pytest.MonkeyPatch,
+    tmp_path,
+    settings_manager,
+):
+    """For <=1000 candidates the pre-check keeps the accurate per-folder path."""
+
+    ws_manager = RecordingWebSocketManager()
+    manager = download_module.DownloadManager(ws_manager=ws_manager)
+
+    monkeypatch.setitem(settings_manager.settings, "example_images_path", str(tmp_path))
+
+    models = [
+        {"sha256": f"{i:064x}", "model_name": f"Model {i}"}
+        for i in range(500)
+    ]
+
+    # Create folders with files for the first 200 models
+    for i in range(200):
+        model_dir = tmp_path / f"{i:064x}"
+        model_dir.mkdir()
+        (model_dir / "image_0.png").write_text("data")
+
+    _patch_scanners(monkeypatch, lora_scanner=StubScanner(models))
+
+    per_model_checks = 0
+    original_has_files = download_module._model_directory_has_files
+
+    def counting_model_directory_has_files(path: str) -> bool:
+        nonlocal per_model_checks
+        per_model_checks += 1
+        return original_has_files(path)
+
+    monkeypatch.setattr(
+        download_module,
+        "_model_directory_has_files",
+        counting_model_directory_has_files,
+    )
+
+    result = await manager.check_pending_models(["lora"])
+
+    assert result["success"] is True
+    assert result["total_models"] == 500
+    assert result["pending_count"] == 300
+    assert result["needs_download"] is True
+    # Per-folder path should run once per candidate.
+    assert per_model_checks == 500
+
+
+@pytest.mark.asyncio
+@pytest.mark.usefixtures("tmp_path")
+async def test_check_pending_models_bulk_index_includes_legacy_folders(
+    monkeypatch: pytest.MonkeyPatch,
+    tmp_path,
+    settings_manager,
+):
+    """In multi-library mode the bulk index also scans the legacy root so models
+    whose folders have not been consolidated yet are not reported pending."""
+
+    ws_manager = RecordingWebSocketManager()
+    manager = download_module.DownloadManager(ws_manager=ws_manager)
+
+    monkeypatch.setitem(settings_manager.settings, "example_images_path", str(tmp_path))
+    monkeypatch.setitem(settings_manager.settings, "libraries", {"default": {}, "extra": {}})
+    monkeypatch.setitem(settings_manager.settings, "active_library", "extra")
+
+    # 1500 unprocessed models triggers the bulk lookup path
+    models = [
+        {"sha256": f"{i:064x}", "model_name": f"Model {i}"}
+        for i in range(1500)
+    ]
+
+    # Folders live at the LEGACY root/<hash> path (not yet consolidated)
+    for i in range(500):
+        model_dir = tmp_path / f"{i:064x}"
+        model_dir.mkdir()
+        (model_dir / "image_0.png").write_text("data")
+
+    _patch_scanners(monkeypatch, lora_scanner=StubScanner(models))
+
+    result = await manager.check_pending_models(["lora"])
+
+    assert result["success"] is True
+    assert result["total_models"] == 1500
+    assert result["pending_count"] == 1000
+    assert result["needs_download"] is True
+
+
 @pytest.fixture
 def settings_manager():
     return get_settings_manager()

tests/services/test_civitai_client.py

@@ -35,9 +35,11 @@ class DummyDownloader:
 def reset_singletons():
     CivitaiClient._instance = None
     ModelMetadataProviderManager._instance = None
+    civitai_client_module._creator_model_count_cache.clear()
     yield
     CivitaiClient._instance = None
     ModelMetadataProviderManager._instance = None
+    civitai_client_module._creator_model_count_cache.clear()
 
 
 @pytest.fixture
@@ -622,3 +624,162 @@ async def test_get_image_info_handles_invalid_id(monkeypatch, downloader, caplog
 
     assert result is None
     assert "Invalid image ID format" in caplog.text
+
+
+async def test_get_user_models_requests_first_page_with_stable_params(downloader):
+    request_calls = []
+
+    async def fake_make_request(method, url, use_auth=True, **kwargs):
+        request_calls.append({"method": method, "url": url, "kwargs": kwargs})
+        return True, {
+            "items": [
+                {
+                    "id": 1,
+                    "modelVersions": [
+                        {"id": 100, "images": [{"meta": {"comfy": {"x": 1}}}]}
+                    ],
+                }
+            ],
+            "metadata": {"nextCursor": "next-token"},
+        }
+
+    downloader.make_request = fake_make_request
+
+    client = await CivitaiClient.get_instance()
+    result = await client.get_user_models("pixel")
+
+    assert result is not None
+    assert result["nextCursor"] == "next-token"
+    assert len(result["items"]) == 1
+    # comfy metadata is still stripped
+    assert "comfy" not in result["items"][0]["modelVersions"][0]["images"][0]["meta"]
+
+    call = request_calls[0]
+    assert call["method"] == "GET"
+    assert call["url"] == "https://civitai.red/api/v1/models"
+    params = call["kwargs"]["params"]
+    assert params["username"] == "pixel"
+    assert params["nsfw"] == "true"
+    assert params["limit"] == 100
+    assert params["sort"] == "Newest"
+    assert params["period"] == "AllTime"
+    assert "cursor" not in params
+
+
+async def test_get_user_models_passes_cursor_and_stringifies_next_cursor(downloader):
+    request_calls = []
+
+    async def fake_make_request(method, url, use_auth=True, **kwargs):
+        request_calls.append(kwargs)
+        return True, {"items": [], "metadata": {"nextCursor": 12345}}
+
+    downloader.make_request = fake_make_request
+
+    client = await CivitaiClient.get_instance()
+    result = await client.get_user_models("pixel", cursor="opaque-token")
+
+    assert request_calls[0]["params"]["cursor"] == "opaque-token"
+    assert result == {"items": [], "nextCursor": "12345"}
+
+
+async def test_get_user_models_without_next_cursor_returns_none_cursor(downloader):
+    async def fake_make_request(method, url, use_auth=True, **kwargs):
+        return True, {"items": [{"id": 1, "modelVersions": []}], "metadata": {}}
+
+    downloader.make_request = fake_make_request
+
+    client = await CivitaiClient.get_instance()
+    result = await client.get_user_models("pixel")
+
+    assert result == {"items": [{"id": 1, "modelVersions": []}], "nextCursor": None}
+
+
+async def test_get_user_models_failure_returns_none(downloader):
+    async def fake_make_request(method, url, use_auth=True, **kwargs):
+        return False, "500 server error"
+
+    downloader.make_request = fake_make_request
+
+    client = await CivitaiClient.get_instance()
+    result = await client.get_user_models("pixel")
+
+    assert result is None
+
+
+async def test_get_creator_model_count_matches_exact_username(downloader):
+    request_calls = []
+
+    async def fake_make_request(method, url, use_auth=True, **kwargs):
+        request_calls.append({"url": url, "kwargs": kwargs})
+        return True, {
+            "items": [
+                {"username": "pixelart", "modelCount": 5},
+                {"username": "Pixel", "modelCount": 2140},
+            ]
+        }
+
+    downloader.make_request = fake_make_request
+
+    client = await CivitaiClient.get_instance()
+    count = await client.get_creator_model_count("pixel")
+
+    assert count == 2140
+    assert request_calls[0]["url"] == "https://civitai.red/api/v1/creators"
+    assert request_calls[0]["kwargs"]["params"] == {"query": "pixel", "limit": 10}
+
+
+async def test_get_creator_model_count_without_exact_match_returns_none(downloader):
+    async def fake_make_request(method, url, use_auth=True, **kwargs):
+        return True, {"items": [{"username": "pixelart", "modelCount": 5}]}
+
+    downloader.make_request = fake_make_request
+
+    client = await CivitaiClient.get_instance()
+    count = await client.get_creator_model_count("pixel")
+
+    assert count is None
+
+
+async def test_get_creator_model_count_caches_results(downloader):
+    request_count = 0
+
+    async def fake_make_request(method, url, use_auth=True, **kwargs):
+        nonlocal request_count
+        request_count += 1
+        return True, {"items": [{"username": "pixel", "modelCount": 42}]}
+
+    downloader.make_request = fake_make_request
+
+    client = await CivitaiClient.get_instance()
+
+    assert await client.get_creator_model_count("pixel") == 42
+    # case-insensitive cache key, second call served from cache
+    assert await client.get_creator_model_count("Pixel") == 42
+    assert request_count == 1
+
+
+async def test_get_creator_model_count_caches_failures(downloader):
+    request_count = 0
+
+    async def fake_make_request(method, url, use_auth=True, **kwargs):
+        nonlocal request_count
+        request_count += 1
+        return False, "500 server error"
+
+    downloader.make_request = fake_make_request
+
+    client = await CivitaiClient.get_instance()
+
+    assert await client.get_creator_model_count("pixel") is None
+    assert await client.get_creator_model_count("pixel") is None
+    assert request_count == 1
+
+
+async def test_get_creator_model_count_never_raises(downloader):
+    async def fake_make_request(method, url, use_auth=True, **kwargs):
+        return True, "unexpected non-dict payload"
+
+    downloader.make_request = fake_make_request
+
+    client = await CivitaiClient.get_instance()
+    assert await client.get_creator_model_count("pixel") is None

tests/services/test_download_manager_basic.py

@@ -1189,6 +1189,109 @@ def test_relative_path_sanitizes_model_and_version_placeholders():
     assert relative_path == "Fancy_Model/Version_One"
 
 
+def test_relative_path_empty_first_tag_fallback():
+    """Test that empty first_tag falls back to 'no tags'."""
+    manager = DownloadManager()
+    settings_manager = get_settings_manager()
+    settings_manager.settings["download_path_templates"]["lora"] = (
+        "{base_model}/{first_tag}"
+    )
+
+    version_info = {
+        "baseModel": "SDXL",
+        "model": {"name": "Test Model", "tags": []},
+        "creator": {"username": "Author"},
+    }
+
+    relative_path = manager._calculate_relative_path(version_info, "lora")
+
+    assert relative_path == "SDXL/no tags"
+
+
+def test_relative_path_empty_base_model_and_first_tag():
+    """Test that empty base_model + empty first_tag does NOT produce a leading slash."""
+    manager = DownloadManager()
+    settings_manager = get_settings_manager()
+    settings_manager.settings["download_path_templates"]["lora"] = (
+        "{base_model}/{first_tag}"
+    )
+
+    version_info = {
+        "baseModel": "",
+        "model": {"name": "Test Model", "tags": []},
+        "creator": {"username": "Author"},
+    }
+
+    relative_path = manager._calculate_relative_path(version_info, "lora")
+
+    assert not relative_path.startswith("/")
+    assert relative_path == "no tags"
+
+
+def test_relative_path_sanitizes_double_slashes():
+    """Test that empty placeholder substitutions don't produce double slashes."""
+    manager = DownloadManager()
+    settings_manager = get_settings_manager()
+    settings_manager.settings["download_path_templates"]["lora"] = (
+        "{base_model}/{first_tag}/{author}"
+    )
+
+    version_info = {
+        "baseModel": "SDXL",
+        "model": {"name": "Test Model", "tags": []},
+        "creator": {"username": "Author"},
+    }
+
+    relative_path = manager._calculate_relative_path(version_info, "lora")
+
+    assert "//" not in relative_path
+    assert relative_path == "SDXL/no tags/Author"
+
+
+def test_download_containment_accepts_symlink_save_dir(tmp_path):
+    """Verify the download path containment check (download_manager.py:1395-1397)
+    accepts save directories reached through user-created symlinks inside the
+    library root — reproducing the symlink scenario from issue #1028."""
+    # Library root with a symlink subdirectory pointing to an external drive
+    lora_root = tmp_path / "loras"
+    lora_root.mkdir()
+
+    external_drive = tmp_path / "external" / "models"
+    external_drive.mkdir(parents=True)
+
+    symlink = lora_root / "Krea 2"
+    symlink.symlink_to(str(external_drive))
+
+    # Simulate a download: base_save_dir = library root,
+    # relative_path = "Krea 2/concept/NewModel"
+    base_save_dir = str(lora_root)
+    save_dir = os.path.join(base_save_dir, "Krea 2", "concept", "NewModel")
+
+    # Replicate the exact containment check from download_manager.py
+    resolved_dir = os.path.abspath(os.path.normpath(save_dir))
+    base_dir = os.path.abspath(os.path.normpath(base_save_dir))
+
+    # Must NOT be rejected — symlinks are legitimate business paths
+    assert resolved_dir.startswith(base_dir + os.sep)
+
+
+def test_download_containment_rejects_dot_dot_traversal(tmp_path):
+    """Verify the download path containment check still blocks ``..`` traversal
+    after the realpath → abspath change."""
+    lora_root = tmp_path / "loras"
+    lora_root.mkdir()
+
+    base_save_dir = str(lora_root)
+    save_dir = os.path.join(base_save_dir, "..", "..", "etc", "passwd")
+
+    resolved_dir = os.path.abspath(os.path.normpath(save_dir))
+    base_dir = os.path.abspath(os.path.normpath(base_save_dir))
+
+    # Must be rejected — dot-dot escapes the library root
+    assert not resolved_dir.startswith(base_dir + os.sep)
+    assert resolved_dir != base_dir
+
+
 def test_distribute_preview_to_entries_moves_and_copies(tmp_path):
     """Test that preview distribution moves file to first entry and copies to others."""
     manager = DownloadManager()

tests/services/test_example_images_download_manager_async.py

@@ -26,6 +26,7 @@ class StubScanner:
 
     def __init__(self, models: list[dict]) -> None:
         self._cache = SimpleNamespace(raw_data=models)
+        self.sync_calls: list[tuple[str, dict]] = []
 
     async def get_cached_data(self):
         return self._cache
@@ -38,6 +39,14 @@ class StubScanner:
                 break
         return True
 
+    async def sync_cache_from_metadata(self, file_path: str, metadata: dict) -> bool:
+        self.sync_calls.append((file_path, metadata))
+        for index, model in enumerate(self._cache.raw_data):
+            if model.get("file_path") == metadata.get("file_path"):
+                self._cache.raw_data[index] = metadata
+                break
+        return True
+
 
 def _patch_scanner(monkeypatch: pytest.MonkeyPatch, scanner: StubScanner) -> None:
     async def _get_lora_scanner(cls):
@@ -520,7 +529,8 @@ async def test_not_found_example_images_are_cleaned(
 
     model_dir = images_root / model_hash
     model_dir.mkdir(parents=True, exist_ok=True)
-    (model_dir / "image_0.png").write_bytes(b"first")
+    # Pre-existing file collides with the valid image index (1) so the
+    # pre-download existence check must skip it without a network request
     (model_dir / "image_1.png").write_bytes(b"second")
 
     async def fake_process_local_examples(*_args, **_kwargs):
@@ -588,6 +598,9 @@ async def test_not_found_example_images_are_cleaned(
     assert missing_url in downloader.calls
     assert manager._progress["failed_models"] == {model_hash}
     assert model_hash in manager._progress["processed_models"]
+    assert scanner.sync_calls
+    assert len(scanner.sync_calls) == 1
+    assert scanner.sync_calls[0][0] == str(model_path)
 
     remaining_images = model_metadata["civitai"]["images"]
     assert remaining_images == [
@@ -596,11 +609,188 @@ async def test_not_found_example_images_are_cleaned(
     ]
 
     files = sorted(p.name for p in model_dir.iterdir())
-    assert files == ["image_0.png", "image_1.png"]
+    assert files == ["image_1.png"]
-    assert (model_dir / "image_0.png").read_bytes() == b"first"
     assert (model_dir / "image_1.png").read_bytes() == b"second"
 
 
+async def test_failed_models_retried_when_explicitly_targeted(
+    monkeypatch: pytest.MonkeyPatch,
+    tmp_path,
+    settings_manager,
+):
+    ws_manager = RecordingWebSocketManager()
+    manager = download_module.DownloadManager(ws_manager=ws_manager)
+
+    images_root = tmp_path / "examples"
+    monkeypatch.setitem(settings_manager.settings, "example_images_path", str(images_root))
+
+    model_hash = "a" * 64
+    model_path = tmp_path / "model.safetensors"
+    model_path.write_text("data", encoding="utf-8")
+
+    model_metadata = {
+        "sha256": model_hash,
+        "model_name": "Failed Example",
+        "file_path": str(model_path),
+        "file_name": "model.safetensors",
+        "civitai": {"images": [{"url": "https://example.com/valid.png"}]},
+    }
+
+    scanner = StubScanner([model_metadata.copy()])
+    _patch_scanner(monkeypatch, scanner)
+
+    # Persist a previous failure so the skip path is exercised
+    images_root.mkdir(parents=True, exist_ok=True)
+    (images_root / ".download_progress.json").write_text(
+        json.dumps(
+            {
+                "failed_models": [model_hash],
+                "processed_models": [],
+                "rate_limited_models": [],
+            }
+        ),
+        encoding="utf-8",
+    )
+
+    async def fake_process_local_examples(*_args, **_kwargs):
+        return False
+
+    async def fake_get_updated_model(model_hash_arg, _scanner):
+        return model_metadata
+
+    class DownloaderStub:
+        def __init__(self):
+            self.calls: list[str] = []
+
+        async def download_to_memory(self, url, *_args, **_kwargs):
+            self.calls.append(url)
+            return True, b"\x89PNG\r\n\x1a\n", {"content-type": "image/png"}
+
+    downloader = DownloaderStub()
+
+    async def fake_get_downloader():
+        return downloader
+
+    monkeypatch.setattr(
+        download_module.ExampleImagesProcessor,
+        "process_local_examples",
+        staticmethod(fake_process_local_examples),
+    )
+    monkeypatch.setattr(
+        download_module.MetadataUpdater,
+        "get_updated_model",
+        staticmethod(fake_get_updated_model),
+    )
+    monkeypatch.setattr(download_module, "get_downloader", fake_get_downloader)
+
+    # Without explicit hashes the previously failed model is skipped
+    skipped_manager = download_module.DownloadManager(ws_manager=RecordingWebSocketManager())
+    result = await skipped_manager.start_download({"model_types": ["lora"], "delay": 0})
+    assert result["success"] is True
+    if skipped_manager._download_task is not None:
+        await asyncio.wait_for(skipped_manager._download_task, timeout=1)
+    assert downloader.calls == []
+
+    # With explicit hashes the previously failed model is retried and cleared
+    result = await manager.start_download(
+        {"model_types": ["lora"], "delay": 0, "model_hashes": [model_hash]}
+    )
+    assert result["success"] is True
+    if manager._download_task is not None:
+        await asyncio.wait_for(manager._download_task, timeout=1)
+    assert downloader.calls == ["https://example.com/valid.png"]
+    assert manager._progress["failed_models"] == set()
+    assert model_hash in manager._progress["processed_models"]
+
+
+async def test_explicit_targets_fill_partial_example_gaps(
+    monkeypatch: pytest.MonkeyPatch,
+    tmp_path,
+    settings_manager,
+):
+    ws_manager = RecordingWebSocketManager()
+
+    images_root = tmp_path / "examples"
+    monkeypatch.setitem(settings_manager.settings, "example_images_path", str(images_root))
+
+    model_hash = "b" * 64
+    model_path = tmp_path / "model.safetensors"
+    model_path.write_text("data", encoding="utf-8")
+
+    model_metadata = {
+        "sha256": model_hash,
+        "model_name": "Partial Example",
+        "file_path": str(model_path),
+        "file_name": "model.safetensors",
+        "civitai": {
+            "images": [
+                {"url": "https://example.com/first.png"},
+                {"url": "https://example.com/second.png"},
+            ]
+        },
+    }
+
+    scanner = StubScanner([model_metadata.copy()])
+    _patch_scanner(monkeypatch, scanner)
+
+    # Simulate a partially populated folder: index 0 already downloaded
+    model_dir = images_root / model_hash
+    model_dir.mkdir(parents=True, exist_ok=True)
+    (model_dir / "image_0.png").write_bytes(b"existing")
+
+    async def fake_process_local_examples(*_args, **_kwargs):
+        return False
+
+    async def fake_get_updated_model(model_hash_arg, _scanner):
+        return model_metadata
+
+    class DownloaderStub:
+        def __init__(self):
+            self.calls: list[str] = []
+
+        async def download_to_memory(self, url, *_args, **_kwargs):
+            self.calls.append(url)
+            return True, b"\x89PNG\r\n\x1a\n", {"content-type": "image/png"}
+
+    downloader = DownloaderStub()
+
+    async def fake_get_downloader():
+        return downloader
+
+    monkeypatch.setattr(
+        download_module.ExampleImagesProcessor,
+        "process_local_examples",
+        staticmethod(fake_process_local_examples),
+    )
+    monkeypatch.setattr(
+        download_module.MetadataUpdater,
+        "get_updated_model",
+        staticmethod(fake_get_updated_model),
+    )
+    monkeypatch.setattr(download_module, "get_downloader", fake_get_downloader)
+
+    # Untargeted run treats the populated folder as done
+    untargeted = download_module.DownloadManager(ws_manager=RecordingWebSocketManager())
+    result = await untargeted.start_download({"model_types": ["lora"], "delay": 0})
+    assert result["success"] is True
+    if untargeted._download_task is not None:
+        await asyncio.wait_for(untargeted._download_task, timeout=1)
+    assert downloader.calls == []
+
+    # Explicitly targeted run fills only the missing index, skipping the
+    # existing file without a network request
+    targeted = download_module.DownloadManager(ws_manager=ws_manager)
+    result = await targeted.start_download(
+        {"model_types": ["lora"], "delay": 0, "model_hashes": [model_hash]}
+    )
+    assert result["success"] is True
+    if targeted._download_task is not None:
+        await asyncio.wait_for(targeted._download_task, timeout=1)
+    assert downloader.calls == ["https://example.com/second.png"]
+    assert (model_dir / "image_1.png").exists()
+    assert (model_dir / "image_0.png").read_bytes() == b"existing"
+
+
 @pytest.fixture
 def settings_manager():
     return get_settings_manager()

tests/services/test_llm_service.py

@@ -243,6 +243,56 @@ class TestLLMServiceChatCompletionJson:
 
         assert result == {"key": "value"}
 
+    @pytest.mark.asyncio
+    async def test_chat_completion_json_falls_back_on_response_format_rejection(
+        self, llm_service,
+    ):
+        """Retry without response_format when provider rejects it (HTTP 400)."""
+        error_response = MockResponse(
+            400,
+            text_data=(
+                '{"error":"\'response_format.type\' must be '
+                '\'json_schema\' or \'text\'"}'
+            ),
+        )
+        success_response = MockResponse(
+            200,
+            json_data={
+                "choices": [{"message": {"content": '{"key": "value"}'}}],
+                "usage": {},
+                "model": "local-model",
+            },
+        )
+
+        call_index = 0
+
+        class FallbackMockSession:
+            def __init__(self):
+                self.last_url = None
+                self.last_json = None
+
+            def post(self, url, json=None, headers=None):
+                nonlocal call_index
+                self.last_url = url
+                self.last_json = json
+                call_index += 1
+                return error_response if call_index == 1 else success_response
+
+            async def __aenter__(self):
+                return self
+
+            async def __aexit__(self, *args):
+                pass
+
+        with mock.patch("aiohttp.ClientSession", return_value=FallbackMockSession()):
+            result = await llm_service.chat_completion_json(
+                system_prompt="You are helpful.",
+                user_prompt="Return JSON.",
+            )
+
+        assert result == {"key": "value"}
+        assert call_index == 2
+
     @pytest.mark.asyncio
     async def test_chat_completion_json_raises_on_non_json(self, llm_service):
         # Non-JSON content raises LLMResponseError (salvage also fails)

tests/services/test_model_lifecycle_service.py

@@ -1,13 +1,181 @@
 import json
+import os
 from pathlib import Path
 
 import pytest
 
-from py.services.model_lifecycle_service import ModelLifecycleService
+from py.services.model_lifecycle_service import ModelLifecycleService, _require_path_in_library_roots
 from py.utils.metadata_manager import MetadataManager
 from py.utils.models import LoraMetadata
 
 
+class ScannerWithRoots:
+    def __init__(self, roots):
+        self._roots = list(roots)
+
+    def get_model_roots(self):
+        return self._roots
+
+
+class TestRequirePathInLibraryRoots:
+    def test_accepts_path_within_root(self, tmp_path):
+        root = tmp_path / "loras"
+        root.mkdir()
+        model = root / "model.safetensors"
+        model.write_text("")
+
+        scanner = ScannerWithRoots([str(root)])
+        _require_path_in_library_roots(str(model), scanner)
+
+    def test_rejects_path_outside_roots(self, tmp_path):
+        root = tmp_path / "loras"
+        root.mkdir()
+        outside = tmp_path / "outside" / "model.safetensors"
+        outside.parent.mkdir(parents=True)
+        outside.write_text("")
+
+        scanner = ScannerWithRoots([str(root)])
+        with pytest.raises(ValueError, match="outside configured library"):
+            _require_path_in_library_roots(str(outside), scanner)
+
+    def test_passes_when_no_roots_configured(self, tmp_path):
+        f = tmp_path / "model.safetensors"
+        f.write_text("")
+
+        scanner = ScannerWithRoots([])
+        _require_path_in_library_roots(str(f), scanner)
+
+    def test_accepts_path_matching_root_exactly(self, tmp_path):
+        root = tmp_path / "loras"
+        root.mkdir()
+
+        scanner = ScannerWithRoots([str(root)])
+        _require_path_in_library_roots(str(root), scanner)
+
+    def test_accepts_symlink_within_root(self, tmp_path):
+        """Symlinks under a configured root are legitimate business paths
+        and should be accepted — containment works on business-path space,
+        not resolved physical paths."""
+        root = tmp_path / "loras"
+        root.mkdir()
+
+        outside_dir = tmp_path / "outside"
+        outside_dir.mkdir()
+        outside_file = outside_dir / "escaped.safetensors"
+        outside_file.write_text("")
+
+        symlink = root / "link.safetensors"
+        symlink.symlink_to(outside_file)
+
+        scanner = ScannerWithRoots([str(root)])
+        # Symlink path is under root in business-path space → accepted
+        _require_path_in_library_roots(str(symlink), scanner)
+
+    def test_rejects_dot_dot_traversal(self, tmp_path):
+        """Verify that ``..`` components are still resolved and blocked —
+        ``abspath`` normalises dot-dot but does not resolve symlinks."""
+        root = tmp_path / "loras"
+        root.mkdir()
+
+        # A path that traverses up out of the root via ..
+        escaped = os.path.join(str(root), "..", "..", "etc", "passwd")
+
+        scanner = ScannerWithRoots([str(root)])
+        with pytest.raises(ValueError, match="outside configured library"):
+            _require_path_in_library_roots(escaped, scanner)
+
+
+class ScannerForDelete:
+    def __init__(self, raw_data, roots, model_type="lora"):
+        self.model_type = model_type
+        self.cache = DummyCache(raw_data)
+        self._hash_index = DummyHashIndex()
+        self._roots = list(roots)
+        self._persist_calls = []
+
+    def get_model_roots(self):
+        return self._roots
+
+    async def get_cached_data(self):
+        return self.cache
+
+    async def _persist_current_cache(self):
+        self._persist_calls.append(True)
+
+
+@pytest.mark.asyncio
+async def test_delete_model_rejects_path_outside_roots(tmp_path: Path):
+    root = tmp_path / "loras"
+    root.mkdir()
+    model = root / "model.safetensors"
+    model.write_bytes(b"data")
+
+    scanner = ScannerForDelete(
+        raw_data=[{"file_path": str(model)}],
+        roots=[str(root)],
+    )
+    service = ModelLifecycleService(
+        scanner=scanner,
+        metadata_manager=DummyMetadataManager({"civitai": {"modelId": 1}}),
+        metadata_loader=lambda x: {},
+    )
+    # Path within root should work (model file exists)
+    result = await service.delete_model(str(model))
+    assert result["success"] is True
+
+    # Path outside root should be rejected
+    outside = tmp_path / "outside.safetensors"
+    outside.write_bytes(b"data")
+    scanner2 = ScannerForDelete(
+        raw_data=[],
+        roots=[str(root)],
+    )
+    service2 = ModelLifecycleService(
+        scanner=scanner2,
+        metadata_manager=DummyMetadataManager({}),
+        metadata_loader=lambda x: {},
+    )
+    with pytest.raises(ValueError, match="outside configured library"):
+        await service2.delete_model(str(outside))
+
+
+@pytest.mark.asyncio
+async def test_rename_model_rejects_path_outside_roots(tmp_path: Path):
+    root = tmp_path / "loras"
+    root.mkdir()
+
+    scanner = ScannerWithRoots([str(root)])
+    service = ModelLifecycleService(
+        scanner=scanner,
+        metadata_manager=DummyMetadataManager({}),
+        metadata_loader=lambda x: {},
+    )
+    outside = tmp_path / "outside.safetensors"
+    outside.write_bytes(b"data")
+
+    with pytest.raises(ValueError, match="outside configured library"):
+        await service.rename_model(file_path=str(outside), new_file_name="new_name")
+
+
+@pytest.mark.asyncio
+async def test_bulk_delete_rejects_any_path_outside_roots(tmp_path: Path):
+    root = tmp_path / "loras"
+    root.mkdir()
+    model_ok = root / "model.safetensors"
+    model_ok.write_bytes(b"data")
+    outside = tmp_path / "outside.safetensors"
+    outside.write_bytes(b"data")
+
+    scanner = ScannerWithRoots([str(root)])
+    service = ModelLifecycleService(
+        scanner=scanner,
+        metadata_manager=DummyMetadataManager({}),
+        metadata_loader=lambda x: {},
+    )
+    with pytest.raises(ValueError, match="outside configured library"):
+        await service.bulk_delete_models([str(model_ok), str(outside)])
+
+
 class DummyCache:
     def __init__(self, raw_data):
         self.raw_data = raw_data

tests/services/test_model_scanner.py

@@ -884,7 +884,7 @@ async def test_sync_cache_conditional_resort_skipped(tmp_path: Path, monkeypatch
         raw_data=[dict(entry)], folders=[], name_display_mode="model_name"
     )
     await scanner._cache.resort()
-    scanner._cache._last_sort = ("name", "asc")  # name sort is active
+    scanner._cache._last_sort = ("name", "asc", None)  # name sort is active
     scanner._tags_count = {"alpha": 1}
     scanner._hash_index.add_entry("abc123", "/m/a.safetensors")
 
@@ -935,7 +935,7 @@ async def test_sync_cache_conditional_resort_triggered(tmp_path: Path, monkeypat
         raw_data=[dict(entry)], folders=[], name_display_mode="model_name"
     )
     await scanner._cache.resort()
-    scanner._cache._last_sort = ("name", "asc")
+    scanner._cache._last_sort = ("name", "asc", None)
     scanner._tags_count = {"alpha": 1}
     scanner._hash_index.add_entry("abc123", "/m/a.safetensors")
 

tests/services/test_model_sort.py

@@ -0,0 +1,97 @@
+"""Tests for sort parsing and the seeded random sort mode."""
+
+import asyncio
+
+import pytest
+
+from py.services.model_cache import ModelCache
+from py.services.model_query import ModelCacheRepository, SortParams
+
+
+def _make_cache(items):
+    return ModelCache(
+        raw_data=[
+            {
+                "file_path": f"/models/{name}.safetensors",
+                "file_name": f"{name}.safetensors",
+                "model_name": name,
+                "folder": "",
+                "size": 100,
+                "modified": 0.0,
+            }
+            for name in items
+        ],
+        folders=[],
+    )
+
+
+class TestParseSort:
+    def test_random_with_seed(self):
+        params = ModelCacheRepository.parse_sort("random:abc123")
+        assert params == SortParams(key="random", order="asc", seed="abc123")
+
+    def test_random_without_seed(self):
+        params = ModelCacheRepository.parse_sort("random")
+        assert params == SortParams(key="random", order="asc", seed=None)
+
+    def test_random_empty_seed_falls_back_to_none(self):
+        params = ModelCacheRepository.parse_sort("random:")
+        assert params.seed is None
+
+    def test_regular_sorts_unaffected(self):
+        params = ModelCacheRepository.parse_sort("name:desc")
+        assert params == SortParams(key="name", order="desc", seed=None)
+
+
+class TestRandomShuffle:
+    @pytest.mark.asyncio
+    async def test_same_seed_yields_same_order(self):
+        cache = _make_cache(["a", "b", "c", "d", "e"])
+        await asyncio.sleep(0)  # allow background resort task to run
+
+        first = await cache.get_sorted_data("random", "asc", "seed1")
+        second = await cache.get_sorted_data("random", "asc", "seed1")
+
+        assert [item["model_name"] for item in first] == [
+            item["model_name"] for item in second
+        ]
+
+    @pytest.mark.asyncio
+    async def test_different_seeds_yield_different_orders(self):
+        cache = _make_cache([f"m{i}" for i in range(20)])
+        await asyncio.sleep(0)
+
+        first = await cache.get_sorted_data("random", "asc", "seed-a")
+        second = await cache.get_sorted_data("random", "asc", "seed-b")
+
+        assert [item["model_name"] for item in first] != [
+            item["model_name"] for item in second
+        ]
+
+    @pytest.mark.asyncio
+    async def test_shuffle_is_a_permutation(self):
+        cache = _make_cache(["a", "b", "c", "d", "e"])
+        await asyncio.sleep(0)
+
+        shuffled = await cache.get_sorted_data("random", "asc", "seed")
+
+        assert sorted(item["model_name"] for item in shuffled) == [
+            "a",
+            "b",
+            "c",
+            "d",
+            "e",
+        ]
+        assert len({item["file_path"] for item in shuffled}) == 5
+
+    @pytest.mark.asyncio
+    async def test_missing_seed_is_stable(self):
+        cache = _make_cache(["a", "b", "c", "d", "e"])
+        await asyncio.sleep(0)
+
+        first = await cache.get_sorted_data("random", "asc")
+        second = await cache.get_sorted_data("random", "asc")
+
+        assert [item["model_name"] for item in first] == [
+            item["model_name"] for item in second
+        ]

tests/services/test_recipe_scanner.py

@@ -77,7 +77,15 @@ def recipe_scanner(tmp_path: Path, monkeypatch):
     monkeypatch.setattr(config, "loras_roots", [str(tmp_path)])
     stub = StubLoraScanner()
     scanner = RecipeScanner(lora_scanner=stub)
-    asyncio.run(scanner.refresh_cache(force=True))
+
+    async def _init():
+        await scanner.refresh_cache(force=True)
+        # Wait for FTS index build to finish — asyncio.run()
+        # cancels background tasks on return, so we must await it here.
+        if scanner._fts_index_task:
+            await scanner._fts_index_task
+
+    asyncio.run(_init())
     yield scanner, stub
     RecipeScanner._instance = None
     settings_manager_module.reset_settings_manager()

tests/services/test_wildcard_service.py

@@ -139,3 +139,122 @@ def test_contains_dynamic_syntax_detects_wildcards_and_options():
     assert contains_dynamic_syntax("__flower__") is True
     assert contains_dynamic_syntax("{red|blue}") is True
     assert contains_dynamic_syntax("{2$$, $$red|blue|green}") is True
+
+
+# ---------------------------------------------------------------------------
+# _pick_weighted_or_plain
+# ---------------------------------------------------------------------------
+
+
+def test_pick_weighted_or_plain_plain_values(monkeypatch, tmp_path):
+    """Plain values without :: are picked via rng.choice (fast path)."""
+    service, _ = _make_service(monkeypatch, tmp_path)
+
+    import random
+    rng = random.Random(42)
+
+    result = service._pick_weighted_or_plain(["red", "green", "blue"], rng)
+    assert result in {"red", "green", "blue"}
+    assert "::" not in result
+
+
+def test_pick_weighted_or_plain_deterministic_with_seed(monkeypatch, tmp_path):
+    """Same seed produces the same result for plain values."""
+    service, _ = _make_service(monkeypatch, tmp_path)
+
+    import random
+    first = service._pick_weighted_or_plain(["a", "b", "c"], random.Random(99))
+    second = service._pick_weighted_or_plain(["a", "b", "c"], random.Random(99))
+    assert first == second
+
+
+def test_pick_weighted_or_plain_weighted_values(monkeypatch, tmp_path):
+    """Weighted values use weighted selection and strip the N:: prefix."""
+    service, _ = _make_service(monkeypatch, tmp_path)
+
+    import random
+    values = ["3::apple", "1::banana"]
+    results = {"apple": 0, "banana": 0}
+    for seed in range(4000):
+        result = service._pick_weighted_or_plain(values, random.Random(seed))
+        assert result in results, f"Unexpected result: {result!r}"
+        assert "::" not in result
+        results[result] += 1
+
+    total = results["apple"] + results["banana"]
+    # 3:1 weight → apple ≈ 75%, banana ≈ 25%
+    assert 2700 < results["apple"] < 3300, f"apple count out of range: {results['apple']}"
+    assert 700 < results["banana"] < 1300, f"banana count out of range: {results['banana']}"
+
+
+def test_pick_weighted_or_plain_weight_one_values(monkeypatch, tmp_path):
+    """Values with explicit 1:: prefix have prefix stripped but are not weighted."""
+    service, _ = _make_service(monkeypatch, tmp_path)
+
+    import random
+    # All weights are 1.0 → no actual weighting, but :: prefix is stripped
+    values = ["1::foo", "1::bar"]
+    rng = random.Random(42)
+    results = {service._pick_weighted_or_plain(values, rng) for _ in range(200)}
+    assert results == {"foo", "bar"}
+    # Ensure the prefix is always stripped
+    for result in results:
+        assert "::" not in result
+
+
+def test_pick_weighted_or_plain_mixed_weighted_and_plain(monkeypatch, tmp_path):
+    """Mixed list with some weighted and some unweighted values."""
+    service, _ = _make_service(monkeypatch, tmp_path)
+
+    import random
+    values = ["5::x", "y", "z"]  # x has weight 5, y/z have default weight 1
+    results = {"x": 0, "y": 0, "z": 0}
+    for seed in range(4000):
+        result = service._pick_weighted_or_plain(values, random.Random(seed))
+        assert result in results
+        assert "::" not in result
+        results[result] += 1
+
+    # x (5) vs combined y+z (1+1=2) → ~71% / ~29%
+    x_pct = results["x"] / sum(results.values())
+    assert 0.65 < x_pct < 0.78, f"x proportion out of range: {x_pct:.3f}"
+
+
+def test_pick_weighted_or_plain_invalid_weight_prefix(monkeypatch, tmp_path):
+    """Invalid numeric prefix (e.g. 1.2.3) is NOT treated as a weight and
+    the prefix is NOT stripped, matching the updated strict regex."""
+    service, _ = _make_service(monkeypatch, tmp_path)
+
+    import random
+    rng = random.Random(42)
+
+    # "1.2.3::a" is not a valid number → treated as plain text value
+    result = service._pick_weighted_or_plain(["1.2.3::a", "b"], rng)
+    # It should keep the full text including :: because the prefix isn't a
+    # valid numeric weight according to the strict regex
+    assert result == "1.2.3::a" or result == "b"
+
+
+def test_pick_weighted_or_plain_glob_aggregation(monkeypatch, tmp_path):
+    """Weighted wildcard resolution through glob aggregation (__*__)."""
+    service, wildcards_dir = _make_service(monkeypatch, tmp_path)
+    wildcards_dir.mkdir()
+
+    (wildcards_dir / "animals").mkdir()
+    (wildcards_dir / "animals" / "cat.txt").write_text("3::tabby\n1::persian\n", encoding="utf-8")
+    (wildcards_dir / "animals" / "dog.txt").write_text("retriever\npoodle\n", encoding="utf-8")
+
+    # __animals/*__ aggregates all values across both files
+    # Weighted values should have :: stripped
+    results = {"tabby": 0, "persian": 0, "retriever": 0, "poodle": 0}
+    for seed in range(4000):
+        expanded = service.expand_text("__animals/*__", seed=seed)
+        assert expanded in results, f"Unexpected result: {expanded!r}"
+        assert "::" not in expanded
+        results[expanded] += 1
+
+    # tabby (3) vs persian (1) → ~75% / ~25% within the cat subset
+    cat_total = results["tabby"] + results["persian"]
+    if cat_total > 0:
+        tabby_pct = results["tabby"] / cat_total
+        assert 0.65 < tabby_pct < 0.85, f"tabby proportion out of range: {tabby_pct:.3f}"