fix(assets): seed added_at past max(existing) to survive Windows clock collisions

The per-tag microsecond stagger preserves intra-batch order, but two
back-to-back write batches on the same reference (e.g.
set_reference_tags for path tags, then add_tags_to_reference for user
tags) call get_utc_now() independently. On Windows the system clock can
return the same datetime for both calls if no OS tick elapsed between
the commits — both batches end up sharing microseconds and
ORDER BY added_at, tag_name falls back to the alphabetic tiebreaker,
sorting user tags ahead of path tags they were meant to follow.

Add _next_added_at_base(reference_id) that reads max(existing added_at)
and returns max(existing + 1us, get_utc_now()), guaranteeing the new
batch sorts strictly after anything previously written for that
reference. Used by set_reference_tags and add_tags_to_reference;
batch_insert_seed_assets stays on raw get_utc_now() since seed inserts
are always the first writes for a new reference.

The accompanying regression test pins get_utc_now() to a frozen value
so the previously-Windows-only race becomes a platform-independent
failure mode under test.

app/assets/api/routes.py

@@ -401,12 +401,16 @@ async def upload_asset(request: web.Request) -> web.Response:
         )
 
     if spec.tags and spec.tags[0] == "models":
+        # tag[1] may be the standalone category ("checkpoints") or the
+        # slash-joined shape ("checkpoints/flux/...") that
+        # `get_name_and_tags_from_asset_path` and cloud both emit. Match
+        # `resolve_destination_from_tags` by extracting the first segment.
+        category = spec.tags[1].split("/", 1)[0] if len(spec.tags) >= 2 else ""
         if (
             len(spec.tags) < 2
-            or spec.tags[1] not in folder_paths.folder_names_and_paths
+            or category not in folder_paths.folder_names_and_paths
         ):
             delete_temp_file_if_exists(parsed.tmp_path)
-            category = spec.tags[1] if len(spec.tags) >= 2 else ""
             return _build_error_response(
                 400, "INVALID_BODY", f"unknown models category '{category}'"
             )

app/assets/database/queries/asset_reference.py

@@ -327,7 +327,12 @@ def list_references_page(
             select(AssetReferenceTag.asset_reference_id, Tag.name)
             .join(Tag, Tag.name == AssetReferenceTag.tag_name)
             .where(AssetReferenceTag.asset_reference_id.in_(id_list))
-            .order_by(AssetReferenceTag.tag_name.asc())
+            # Preserve insertion order so the structural first tag (the root
+            # category like "models") stays in position 0 and the path-derived
+            # sub-path tag stays in position 1, matching cloud's behavior.
+            # tag_name is a deterministic tiebreaker when multiple tags share
+            # an added_at (same-batch insert via set_reference_tags).
+            .order_by(AssetReferenceTag.added_at.asc(), AssetReferenceTag.tag_name.asc())
         )
         for ref_id, tag_name in rows.all():
             tag_map[ref_id].append(tag_name)
@@ -355,7 +360,8 @@ def fetch_reference_asset_and_tags(
             build_visible_owner_clause(owner_id),
         )
         .options(noload(AssetReference.tags))
-        .order_by(Tag.name.asc())
+        # See list_references_page for the rationale behind ordering by added_at.
+        .order_by(AssetReferenceTag.added_at.asc(), Tag.name.asc())
     )
 
     rows = session.execute(stmt).all()

app/assets/database/queries/tags.py

@@ -1,4 +1,5 @@
 from dataclasses import dataclass
+from datetime import datetime, timedelta
 from typing import Iterable, Sequence
 
 import sqlalchemy as sa
@@ -20,7 +21,12 @@ from app.assets.database.queries.common import (
     build_visible_owner_clause,
     iter_row_chunks,
 )
-from app.assets.helpers import escape_sql_like_string, get_utc_now, normalize_tags
+from app.assets.helpers import (
+    escape_sql_like_string,
+    expand_bucket_prefixes,
+    get_utc_now,
+    normalize_tags,
+)
 
 
 @dataclass(frozen=True)
@@ -44,6 +50,26 @@ class SetTagsResult:
     total: list[str]
 
 
+def _next_added_at_base(session: Session, reference_id: str) -> datetime:
+    """Return a timestamp strictly greater than any existing
+    `added_at` for this reference. On platforms where the wall clock
+    has insufficient resolution between back-to-back commits (notably
+    Windows), two write batches on the same reference can otherwise
+    share a microsecond — the `ORDER BY added_at, tag_name` retrieval
+    then falls back to the alphabetic tiebreaker and user-tier tags
+    sort ahead of path-tier tags they were meant to follow.
+    """
+    existing_max = session.execute(
+        sa.select(sa.func.max(AssetReferenceTag.added_at)).where(
+            AssetReferenceTag.asset_reference_id == reference_id
+        )
+    ).scalar()
+    now = get_utc_now()
+    if existing_max is None:
+        return now
+    return max(existing_max + timedelta(microseconds=1), now)
+
+
 def validate_tags_exist(session: Session, tags: list[str]) -> None:
     """Raise ValueError if any of the given tag names do not exist."""
     existing_tag_names = set(
@@ -77,7 +103,13 @@ def get_reference_tags(session: Session, reference_id: str) -> list[str]:
             session.execute(
                 select(AssetReferenceTag.tag_name)
                 .where(AssetReferenceTag.asset_reference_id == reference_id)
-                .order_by(AssetReferenceTag.tag_name.asc())
+                # Match the response-path ordering used by
+                # list_references_page / fetch_reference_asset_and_tags so
+                # upload responses and subsequent GETs agree on tag order.
+                .order_by(
+                    AssetReferenceTag.added_at.asc(),
+                    AssetReferenceTag.tag_name.asc(),
+                )
             )
         ).all()
     ]
@@ -89,7 +121,7 @@ def set_reference_tags(
     tags: Sequence[str],
     origin: str = "manual",
 ) -> SetTagsResult:
-    desired = normalize_tags(tags)
+    desired = expand_bucket_prefixes(normalize_tags(tags))
 
     current = set(get_reference_tags(session, reference_id))
 
@@ -98,15 +130,22 @@ def set_reference_tags(
 
     if to_add:
         ensure_tags_exist(session, to_add, tag_type="user")
+        # Stagger added_at by microsecond per tag so the retrieval ORDER BY
+        # added_at preserves input order. Per-tag get_utc_now() calls can
+        # collide at microsecond resolution on fast machines, dropping the
+        # query to the tag_name alphabetical tiebreaker — same fix as in
+        # batch_insert_seed_assets. Read max(existing) so this batch sorts
+        # strictly after any prior batch on the same reference.
+        base_ts = _next_added_at_base(session, reference_id)
         session.add_all(
             [
                 AssetReferenceTag(
                     asset_reference_id=reference_id,
                     tag_name=t,
                     origin=origin,
-                    added_at=get_utc_now(),
+                    added_at=base_ts + timedelta(microseconds=i),
                 )
-                for t in to_add
+                for i, t in enumerate(to_add)
             ]
         )
         session.flush()
@@ -136,7 +175,7 @@ def add_tags_to_reference(
         if not ref:
             raise ValueError(f"AssetReference {reference_id} not found")
 
-    norm = normalize_tags(tags)
+    norm = expand_bucket_prefixes(normalize_tags(tags))
     if not norm:
         total = get_reference_tags(session, reference_id=reference_id)
         return AddTagsResult(added=[], already_present=[], total_tags=total)
@@ -146,10 +185,17 @@ def add_tags_to_reference(
 
     current = set(get_reference_tags(session, reference_id))
 
+    # Preserve the caller's insertion order rather than alphabetizing —
+    # the retrieval ORDER BY added_at + microsecond stagger only meaningfully
+    # preserves insertion order if "the order we insert in" actually matches
+    # the caller's intent.
     want = set(norm)
-    to_add = sorted(want - current)
+    to_add = [t for t in norm if t not in current]
 
     if to_add:
+        # See set_reference_tags for the rationale behind the per-tag stagger
+        # and the max(existing) seed.
+        base_ts = _next_added_at_base(session, reference_id)
         with session.begin_nested() as nested:
             try:
                 session.add_all(
@@ -158,9 +204,9 @@ def add_tags_to_reference(
                             asset_reference_id=reference_id,
                             tag_name=t,
                             origin=origin,
-                            added_at=get_utc_now(),
+                            added_at=base_ts + timedelta(microseconds=i),
                         )
-                        for t in to_add
+                        for i, t in enumerate(to_add)
                     ]
                 )
                 session.flush()

app/assets/helpers.py

@@ -47,6 +47,50 @@ def normalize_tags(tags: list[str] | None) -> list[str]:
     return list(dict.fromkeys(t.strip().lower() for t in (tags or []) if (t or "").strip()))
 
 
+def _known_bucket_prefixes() -> set[str]:
+    """Lowercased model-category names eligible for standalone-prefix
+    expansion. Tags whose first slash segment matches one of these get
+    the bucket inserted as a separate token, so FE filters like
+    ``include_tags=models,checkpoints`` keep matching even when the
+    asset lives in a nested subfolder (`models/checkpoints/flux/foo`).
+
+    Bare user labels with slashes whose first segment is not a registered
+    bucket (e.g. ``my-org/team-a``) pass through unchanged.
+    """
+    try:
+        import folder_paths
+
+        return {
+            name.lower()
+            for name in folder_paths.folder_names_and_paths.keys()
+            if name != "custom_nodes"
+        }
+    except Exception:
+        return set()
+
+
+def expand_bucket_prefixes(tags: list[str]) -> list[str]:
+    """Insert standalone bucket tokens after any slash-joined tag whose
+    first segment is a registered model category. Preserves caller order
+    and is idempotent (existing bucket tokens are not duplicated).
+    """
+    if not tags:
+        return list(tags)
+    buckets = _known_bucket_prefixes()
+    if not buckets:
+        return list(tags)
+    seen = set(tags)
+    result: list[str] = []
+    for t in tags:
+        result.append(t)
+        if "/" in t:
+            prefix = t.split("/", 1)[0]
+            if prefix.lower() in buckets and prefix not in seen:
+                result.append(prefix)
+                seen.add(prefix)
+    return result
+
+
 def validate_blake3_hash(s: str) -> str:
     """Validate and normalize a blake3 hash string.
 

app/assets/services/bulk_ingest.py

@@ -3,7 +3,7 @@ from __future__ import annotations
 import os
 import uuid
 from dataclasses import dataclass
-from datetime import datetime
+from datetime import datetime, timedelta
 from typing import TYPE_CHECKING, Any, TypedDict
 
 from sqlalchemy.orm import Session
@@ -13,13 +13,14 @@ from app.assets.database.queries import (
     bulk_insert_references_ignore_conflicts,
     bulk_insert_tags_and_meta,
     delete_assets_by_ids,
+    ensure_tags_exist,
     get_existing_asset_ids,
     get_reference_ids_by_ids,
     get_references_by_paths_and_asset_ids,
     get_unreferenced_unhashed_asset_ids,
     restore_references_by_paths,
 )
-from app.assets.helpers import get_utc_now
+from app.assets.helpers import expand_bucket_prefixes, get_utc_now
 
 if TYPE_CHECKING:
     from app.assets.services.metadata_extract import ExtractedMetadata
@@ -233,13 +234,20 @@ def batch_insert_seed_assets(
             if ref_id not in inserted_ref_ids:
                 continue
 
-            for tag in ref_data["tags"]:
+            # Stagger added_at by microsecond per tag within a reference so
+            # the retrieval ORDER BY added_at preserves the input list order
+            # (the path-derived root category stays at position 0). Without
+            # this, every tag in a bulk-insert batch shares current_time and
+            # the tag_name tiebreaker sorts them alphabetically — putting the
+            # subpath tag ahead of "models" since "c"/"d"/"l" < "m".
+            ref_tags = expand_bucket_prefixes(ref_data["tags"])
+            for tag_idx, tag in enumerate(ref_tags):
                 tag_rows.append(
                     {
                         "asset_reference_id": ref_id,
                         "tag_name": tag,
                         "origin": "automatic",
-                        "added_at": current_time,
+                        "added_at": current_time + timedelta(microseconds=tag_idx),
                     }
                 )
 
@@ -261,6 +269,16 @@ def batch_insert_seed_assets(
                     }
                 )
 
+    if tag_rows:
+        # Bucket-prefix expansion may have introduced tags the caller did
+        # not register via the upstream tag_pool (e.g. `checkpoints` for a
+        # nested `checkpoints/flux/foo` path). Pre-register the full set so
+        # the AssetReferenceTag.tag_name FK is satisfied; the underlying
+        # insert is ON CONFLICT DO NOTHING so re-registration is idempotent.
+        ensure_tags_exist(
+            session, {row["tag_name"] for row in tag_rows}, tag_type="user"
+        )
+
     bulk_insert_tags_and_meta(session, tag_rows=tag_rows, meta_rows=metadata_rows)
 
     return BulkInsertResult(

app/assets/services/path_utils.py

@@ -3,7 +3,6 @@ from pathlib import Path
 from typing import Literal
 
 import folder_paths
-from app.assets.helpers import normalize_tags
 
 
 _NON_MODEL_FOLDER_NAMES = frozenset({"custom_nodes"})
@@ -27,27 +26,51 @@ def get_comfy_models_folders() -> list[tuple[str, list[str]]]:
 
 
 def resolve_destination_from_tags(tags: list[str]) -> tuple[str, list[str]]:
-    """Validates and maps tags -> (base_dir, subdirs_for_fs)"""
+    """Validates and maps tags -> (base_dir, subdirs_for_fs).
+
+    Accepts both the legacy one-tag-per-directory shape
+    (``["models", "diffusers", "Kolors", "text_encoder"]``) and the
+    slash-joined shape emitted by :func:`get_name_and_tags_from_asset_path`
+    (``["models", "diffusers/Kolors/text_encoder"]``). Hybrid shapes that
+    mix the two within a single call (e.g.
+    ``["models", "diffusers", "Kolors/text_encoder"]``) are also
+    accepted: each entry after ``tags[0]`` is split on ``/`` and
+    concatenated, so the two shapes — and any mix of them — resolve to
+    the same destination. The same safety checks are applied to each
+    component after expansion.
+    """
     if not tags:
         raise ValueError("tags must not be empty")
     root = tags[0].lower()
+
+    # Expand any slash-joined entries into individual path components so
+    # the rest of the function can treat both tag shapes uniformly. Each
+    # component is also stripped, so " a / b " behaves like ["a", "b"].
+    expanded: list[str] = []
+    for t in tags[1:]:
+        for part in str(t).split("/"):
+            part = part.strip()
+            if part:
+                expanded.append(part)
+
     if root == "models":
-        if len(tags) < 2:
+        if not expanded:
             raise ValueError("at least two tags required for model asset")
+        category = expanded[0]
         try:
-            bases = folder_paths.folder_names_and_paths[tags[1]][0]
+            bases = folder_paths.folder_names_and_paths[category][0]
         except KeyError:
-            raise ValueError(f"unknown model category '{tags[1]}'")
+            raise ValueError(f"unknown model category '{category}'")
         if not bases:
-            raise ValueError(f"no base path configured for category '{tags[1]}'")
+            raise ValueError(f"no base path configured for category '{category}'")
         base_dir = os.path.abspath(bases[0])
-        raw_subdirs = tags[2:]
+        raw_subdirs = expanded[1:]
     elif root == "input":
         base_dir = os.path.abspath(folder_paths.get_input_directory())
-        raw_subdirs = tags[1:]
+        raw_subdirs = expanded
     elif root == "output":
         base_dir = os.path.abspath(folder_paths.get_output_directory())
-        raw_subdirs = tags[1:]
+        raw_subdirs = expanded
     else:
         raise ValueError(f"unknown root tag '{tags[0]}'; expected 'models', 'input', or 'output'")
     _sep_chars = frozenset(("/", "\\", os.sep))
@@ -160,7 +183,21 @@ def get_name_and_tags_from_asset_path(file_path: str) -> tuple[str, list[str]]:
     """Return (name, tags) derived from a filesystem path.
 
     - name: base filename with extension
-    - tags: [root_category] + parent folder names in order
+    - tags: [root_category] for paths with no parent subdirectories,
+      [root_category, slash_joined_subpath] otherwise. The parent subpath
+      (everything between the root category and the filename) is collapsed
+      into a single tag rather than emitted as one tag per directory, so
+      consumers can use ``tags[1]`` as a stable category identifier that
+      survives nested directory layouts (e.g. diffusers components).
+
+      The subpath is lowercased to match the canonicalization applied by
+      :func:`ensure_tags_exist`; without that, the
+      ``asset_reference_tags.tag_name`` FK to the lowercased ``tags.name``
+      would fail for any path containing uppercase letters. The root
+      category is lowercase by construction in
+      :func:`get_asset_category_and_relative_path`, so no separate cast
+      is applied here. Consumers that need to look up providers keyed on
+      original-case paths should normalize their lookup key to lowercase.
 
     Raises:
         ValueError: path does not belong to any known root.
@@ -170,4 +207,7 @@ def get_name_and_tags_from_asset_path(file_path: str) -> tuple[str, list[str]]:
     parent_parts = [
         part for part in p.parent.parts if part not in (".", "..", p.anchor)
     ]
-    return p.name, list(dict.fromkeys(normalize_tags([root_category, *parent_parts])))
+    tags = [root_category]
+    if parent_parts:
+        tags.append("/".join(parent_parts).lower())
+    return p.name, list(dict.fromkeys(t.strip() for t in tags if t.strip()))

comfy_extras/nodes_audio.py

@@ -543,7 +543,7 @@ class AudioConcat(IO.ComfyNode):
         return IO.Schema(
             node_id="AudioConcat",
             search_aliases=["join audio", "combine audio", "append audio"],
-            display_name="Concatenate Audio",
+            display_name="Audio Concat",
             description="Concatenates the audio1 to audio2 in the specified direction.",
             category="audio",
             inputs=[
@@ -597,7 +597,7 @@ class AudioMerge(IO.ComfyNode):
         return IO.Schema(
             node_id="AudioMerge",
             search_aliases=["mix audio", "overlay audio", "layer audio"],
-            display_name="Merge Audio",
+            display_name="Audio Merge",
             description="Combine two audio tracks by overlaying their waveforms.",
             category="audio",
             inputs=[
@@ -667,9 +667,8 @@ class AudioAdjustVolume(IO.ComfyNode):
         return IO.Schema(
             node_id="AudioAdjustVolume",
             search_aliases=["audio gain", "loudness", "audio level"],
-            display_name="Adjust Audio Volume",
+            display_name="Audio Adjust Volume",
             category="audio",
-            description="Adjust the volume of the audio by a specified amount in decibels (dB).",
             inputs=[
                 IO.Audio.Input("audio"),
                 IO.Int.Input(

comfy_extras/nodes_dataset.py

@@ -47,10 +47,8 @@ class LoadImageDataSetFromFolderNode(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="LoadImageDataSetFromFolder",
-            search_aliases=["load folder", "load from folder", "load dataset", "load images", "import dataset"],
-            display_name="Load Image (from Folder)",
-            category="image",
-            description="Load a dataset of images from a specified folder and return a list of images. Supported formats: PNG, JPG, JPEG, WEBP.",
+            display_name="Load Image Dataset from Folder",
+            category="dataset",
             is_experimental=True,
             inputs=[
                 io.Combo.Input(
@@ -86,16 +84,14 @@ class LoadImageTextDataSetFromFolderNode(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="LoadImageTextDataSetFromFolder",
-            search_aliases=["load folder", "load from folder", "load dataset", "load images", "import dataset"],
-            display_name="Load Image-Text (from Folder)",
-            category="image",
-            description="Load a dataset of pairs of images and text captions from a specified folder and return them as a list. Supported formats: PNG, JPG, JPEG, WEBP.",
+            display_name="Load Image and Text Dataset from Folder",
+            category="dataset",
             is_experimental=True,
             inputs=[
                 io.Combo.Input(
                     "folder",
                     options=folder_paths.get_input_subfolders(),
-                    tooltip="The folder to load images and text captions from.",
+                    tooltip="The folder to load images from.",
                 )
             ],
             outputs=[
@@ -210,10 +206,8 @@ class SaveImageDataSetToFolderNode(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="SaveImageDataSetToFolder",
-            search_aliases=["save folder", "save to folder", "save dataset", "save images", "export dataset"],
-            display_name="Save Image (to Folder) (DEPRECATED)",
-            category="image",
-            description="Save a dataset of images to a specified folder. Supported formats: PNG.",
+            display_name="Save Image Dataset to Folder",
+            category="dataset",
             is_experimental=True,
             is_output_node=True,
             is_input_list=True,  # Receive images as list
@@ -232,7 +226,6 @@ class SaveImageDataSetToFolderNode(io.ComfyNode):
                 ),
             ],
             outputs=[],
-            is_deprecated=True,  # This node is redundant and superseded by existing Save Image nodes where the target folder can be specified in the filename_prefix
         )
 
     @classmethod
@@ -253,20 +246,14 @@ class SaveImageTextDataSetToFolderNode(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="SaveImageTextDataSetToFolder",
-            search_aliases=["save folder", "save to folder", "save dataset", "save images", "save text", "export dataset"],
-            display_name="Save Image-Text (to Folder)",
-            category="image",
-            description="Save a dataset of pairs of images and text captions to a specified folder. Images are saved as PNG files and captions are saved as TXT files with the same filename_prefix.",
+            display_name="Save Image and Text Dataset to Folder",
+            category="dataset",
             is_experimental=True,
             is_output_node=True,
             is_input_list=True,  # Receive both images and texts as lists
             inputs=[
                 io.Image.Input("images", tooltip="List of images to save."),
-                io.String.Input("texts",
-                    optional=True,
-                    force_input=True,
-                    tooltip="List of text captions to save."
-                ),
+                io.String.Input("texts", tooltip="List of text captions to save."),
                 io.String.Input(
                     "folder_name",
                     default="dataset",
@@ -283,7 +270,7 @@ class SaveImageTextDataSetToFolderNode(io.ComfyNode):
         )
 
     @classmethod
-    def execute(cls, images, folder_name, filename_prefix, texts=None):
+    def execute(cls, images, texts, folder_name, filename_prefix):
         # Extract scalar values
         folder_name = folder_name[0]
         filename_prefix = filename_prefix[0]
@@ -292,12 +279,11 @@ class SaveImageTextDataSetToFolderNode(io.ComfyNode):
         saved_files = save_images_to_folder(images, output_dir, filename_prefix)
 
         # Save captions
-        if texts:
-            for idx, (filename, caption) in enumerate(zip(saved_files, texts)):
-                caption_filename = filename.replace(".png", ".txt")
-                caption_path = os.path.join(output_dir, caption_filename)
-                with open(caption_path, "w", encoding="utf-8") as f:
-                    f.write(caption)
+        for idx, (filename, caption) in enumerate(zip(saved_files, texts)):
+            caption_filename = filename.replace(".png", ".txt")
+            caption_path = os.path.join(output_dir, caption_filename)
+            with open(caption_path, "w", encoding="utf-8") as f:
+                f.write(caption)
 
         logging.info(f"Saved {len(saved_files)} images and captions to {output_dir}.")
         return io.NodeOutput()
@@ -328,13 +314,11 @@ class ImageProcessingNode(io.ComfyNode):
 
     Child classes should set:
         node_id: Unique node identifier (required)
-        search_aliases: List of search aliases (optional)
         display_name: Display name (optional, defaults to node_id)
         description: Node description (optional)
         extra_inputs: List of additional io.Input objects beyond "images" (optional)
         is_group_process: None (auto-detect), True (group), or False (individual) (optional)
         is_output_list: True (list output) or False (single output) (optional, default True)
-        is_deprecated: True if the node is deprecated (optional, default False)
 
     Child classes must implement ONE of:
         _process(cls, image, **kwargs) -> tensor  (for single-item processing)
@@ -342,13 +326,12 @@ class ImageProcessingNode(io.ComfyNode):
     """
 
     node_id = None
-    search_aliases = []
     display_name = None
     description = None
     extra_inputs = []
     is_group_process = None  # None = auto-detect, True/False = explicit
     is_output_list = None  # None = auto-detect based on processing mode
-    is_deprecated = False
+
     @classmethod
     def _detect_processing_mode(cls):
         """Detect whether this node uses group or individual processing.
@@ -419,10 +402,8 @@ class ImageProcessingNode(io.ComfyNode):
 
         return io.Schema(
             node_id=cls.node_id,
-            search_aliases=cls.search_aliases,
             display_name=cls.display_name or cls.node_id,
-            category=cls.category,
-            description=cls.description,
+            category="dataset/image",
             is_experimental=True,
             is_input_list=is_group,  # True for group, False for individual
             inputs=inputs,
@@ -491,13 +472,11 @@ class TextProcessingNode(io.ComfyNode):
 
     Child classes should set:
         node_id: Unique node identifier (required)
-        search_aliases: List of search aliases (optional)
         display_name: Display name (optional, defaults to node_id)
         description: Node description (optional)
         extra_inputs: List of additional io.Input objects beyond "texts" (optional)
         is_group_process: None (auto-detect), True (group), or False (individual) (optional)
         is_output_list: True (list output) or False (single output) (optional, default True)
-        is_deprecated: True if the node is deprecated (optional, default False)
 
     Child classes must implement ONE of:
         _process(cls, text, **kwargs) -> str  (for single-item processing)
@@ -505,13 +484,12 @@ class TextProcessingNode(io.ComfyNode):
     """
 
     node_id = None
-    search_aliases = []
     display_name = None
     description = None
     extra_inputs = []
     is_group_process = None  # None = auto-detect, True/False = explicit
     is_output_list = None  # None = auto-detect based on processing mode
-    is_deprecated = False
+
     @classmethod
     def _detect_processing_mode(cls):
         """Detect whether this node uses group or individual processing.
@@ -649,17 +627,15 @@ class TextProcessingNode(io.ComfyNode):
 
 class ResizeImagesByShorterEdgeNode(ImageProcessingNode):
     node_id = "ResizeImagesByShorterEdge"
-    display_name = "Resize Images by Shorter Edge (DEPRECATED)"
-    category = "image/transform"
-    description = "Resize images so that the shorter edge matches the specified dimension while preserving aspect ratio."
-    is_deprecated = True  # This node is superseded by Resize Image/Mask with resize_type = scale shorter dimension
+    display_name = "Resize Images by Shorter Edge"
+    description = "Resize images so that the shorter edge matches the specified length while preserving aspect ratio."
     extra_inputs = [
         io.Int.Input(
             "shorter_edge",
             default=512,
             min=1,
             max=8192,
-            tooltip="Target dimension for the shorter edge.",
+            tooltip="Target length for the shorter edge.",
         ),
     ]
 
@@ -679,17 +655,15 @@ class ResizeImagesByShorterEdgeNode(ImageProcessingNode):
 
 class ResizeImagesByLongerEdgeNode(ImageProcessingNode):
     node_id = "ResizeImagesByLongerEdge"
-    display_name = "Resize Images by Longer Edge (DEPRECATED)"
-    category = "image/transform"
-    description = "Resize images so that the longer edge matches the specified dimension while preserving aspect ratio."
-    is_deprecated = True  # This node is superseded by Resize Image/Mask with resize_type = scale longer dimension
+    display_name = "Resize Images by Longer Edge"
+    description = "Resize images so that the longer edge matches the specified length while preserving aspect ratio."
     extra_inputs = [
         io.Int.Input(
             "longer_edge",
             default=1024,
             min=1,
             max=8192,
-            tooltip="Target dimension for the longer edge.",
+            tooltip="Target length for the longer edge.",
         ),
     ]
 
@@ -712,10 +686,8 @@ class ResizeImagesByLongerEdgeNode(ImageProcessingNode):
 
 class CenterCropImagesNode(ImageProcessingNode):
     node_id = "CenterCropImages"
-    search_aliases=["crop", "cut", "trim"]
-    display_name="Crop Image (Center)"
-    category="image/transform"
-    description = "Center crop an image to the specified dimensions."
+    display_name = "Center Crop Images"
+    description = "Center crop all images to the specified dimensions."
     extra_inputs = [
         io.Int.Input("width", default=512, min=1, max=8192, tooltip="Crop width."),
         io.Int.Input("height", default=512, min=1, max=8192, tooltip="Crop height."),
@@ -734,11 +706,10 @@ class CenterCropImagesNode(ImageProcessingNode):
 
 class RandomCropImagesNode(ImageProcessingNode):
     node_id = "RandomCropImages"
-    search_aliases=["crop", "cut", "trim"]
-    display_name = "Crop Image (Random)"
-    category="image/transform"
-    description = "Randomly crop an image to the specified dimensions."
-
+    display_name = "Random Crop Images"
+    description = (
+        "Randomly crop all images to the specified dimensions (for data augmentation)."
+    )
     extra_inputs = [
         io.Int.Input("width", default=512, min=1, max=8192, tooltip="Crop width."),
         io.Int.Input("height", default=512, min=1, max=8192, tooltip="Crop height."),
@@ -763,9 +734,7 @@ class RandomCropImagesNode(ImageProcessingNode):
 
 class NormalizeImagesNode(ImageProcessingNode):
     node_id = "NormalizeImages"
-    search_aliases=["normalize", "normalize colors"]
-    display_name = "Normalize Image Colors"
-    category = "image/color"
+    display_name = "Normalize Images"
     description = "Normalize images using mean and standard deviation."
     extra_inputs = [
         io.Float.Input(
@@ -793,10 +762,8 @@ class NormalizeImagesNode(ImageProcessingNode):
 
 class AdjustBrightnessNode(ImageProcessingNode):
     node_id = "AdjustBrightness"
-    search_aliases=["brightness"]
     display_name = "Adjust Brightness"
-    category="image/adjustments"
-    description = "Adjust the brightness of an image."
+    description = "Adjust brightness of all images."
     extra_inputs = [
         io.Float.Input(
             "factor",
@@ -814,10 +781,8 @@ class AdjustBrightnessNode(ImageProcessingNode):
 
 class AdjustContrastNode(ImageProcessingNode):
     node_id = "AdjustContrast"
-    search_aliases=["contrast"]
     display_name = "Adjust Contrast"
-    category="image/adjustments"
-    description = "Adjust the contrast of an image."
+    description = "Adjust contrast of all images."
     extra_inputs = [
         io.Float.Input(
             "factor",
@@ -835,10 +800,8 @@ class AdjustContrastNode(ImageProcessingNode):
 
 class ShuffleDatasetNode(ImageProcessingNode):
     node_id = "ShuffleDataset"
-    search_aliases=["shuffle", "randomize", "mix"]
-    display_name = "Shuffle Images List"
-    category = "image/batch"
-    description = "Randomly shuffle the order of images in a list."
+    display_name = "Shuffle Image Dataset"
+    description = "Randomly shuffle the order of images in the dataset."
     is_group_process = True  # Requires full list to shuffle
     extra_inputs = [
         io.Int.Input(
@@ -860,15 +823,13 @@ class ShuffleImageTextDatasetNode(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="ShuffleImageTextDataset",
-            search_aliases=["shuffle", "randomize", "mix"],
-            display_name = "Shuffle Pairs of Image-Text",
-            category = "image/batch",
-            description = "Randomly shuffle the order of pairs of image-text in a list.",
+            display_name="Shuffle Image-Text Dataset",
+            category="dataset/image",
             is_experimental=True,
             is_input_list=True,
             inputs=[
                 io.Image.Input("images", tooltip="List of images to shuffle."),
-                io.String.Input("texts", tooltip="List of texts to shuffle.", force_input=True),
+                io.String.Input("texts", tooltip="List of texts to shuffle."),
                 io.Int.Input(
                     "seed",
                     default=0,
@@ -904,11 +865,8 @@ class ShuffleImageTextDatasetNode(io.ComfyNode):
 
 class TextToLowercaseNode(TextProcessingNode):
     node_id = "TextToLowercase"
-    search_aliases=["lowercase"]
-    display_name = "Convert Text to Lowercase (DEPRECATED)"
-    category = "text"
-    description = "Convert text to lowercase."
-    is_deprecated = True  # This node is superseded by the Convert Text Case node
+    display_name = "Text to Lowercase"
+    description = "Convert all texts to lowercase."
 
     @classmethod
     def _process(cls, text):
@@ -917,11 +875,8 @@ class TextToLowercaseNode(TextProcessingNode):
 
 class TextToUppercaseNode(TextProcessingNode):
     node_id = "TextToUppercase"
-    search_aliases=["uppercase"]
-    display_name = "Convert Text to Uppercase (DEPRECATED)"
-    category = "text"
-    description = "Convert text to uppercase."
-    is_deprecated = True  # This node is superseded by the Convert Text Case node
+    display_name = "Text to Uppercase"
+    description = "Convert all texts to uppercase."
 
     @classmethod
     def _process(cls, text):
@@ -930,10 +885,8 @@ class TextToUppercaseNode(TextProcessingNode):
 
 class TruncateTextNode(TextProcessingNode):
     node_id = "TruncateText"
-    search_aliases=["truncate", "cut", "shorten"]
     display_name = "Truncate Text"
-    category = "text"
-    description = "Truncate text to a maximum length."
+    description = "Truncate all texts to a maximum length."
     extra_inputs = [
         io.Int.Input(
             "max_length", default=77, min=1, max=10000, tooltip="Maximum text length."
@@ -947,10 +900,8 @@ class TruncateTextNode(TextProcessingNode):
 
 class AddTextPrefixNode(TextProcessingNode):
     node_id = "AddTextPrefix"
-    display_name = "Add Text Prefix (DEPRECATED)"
-    category = "text"
+    display_name = "Add Text Prefix"
     description = "Add a prefix to all texts."
-    is_deprecated = True  # This node is superseded by the Concatenate Text node
     extra_inputs = [
         io.String.Input("prefix", default="", tooltip="Prefix to add."),
     ]
@@ -962,10 +913,8 @@ class AddTextPrefixNode(TextProcessingNode):
 
 class AddTextSuffixNode(TextProcessingNode):
     node_id = "AddTextSuffix"
-    display_name = "Add Text Suffix (DEPRECATED)"
-    category = "text"
+    display_name = "Add Text Suffix"
     description = "Add a suffix to all texts."
-    is_deprecated = True  # This node is superseded by the Concatenate Text node
     extra_inputs = [
         io.String.Input("suffix", default="", tooltip="Suffix to add."),
     ]
@@ -977,10 +926,8 @@ class AddTextSuffixNode(TextProcessingNode):
 
 class ReplaceTextNode(TextProcessingNode):
     node_id = "ReplaceText"
-    display_name = "Replace Text (DEPRECATED)"
-    category = "text"
+    display_name = "Replace Text"
     description = "Replace text in all texts."
-    is_deprecated = True  # This node is superseded by the other Replace Text node
     extra_inputs = [
         io.String.Input("find", default="", tooltip="Text to find."),
         io.String.Input("replace", default="", tooltip="Text to replace with."),
@@ -993,10 +940,8 @@ class ReplaceTextNode(TextProcessingNode):
 
 class StripWhitespaceNode(TextProcessingNode):
     node_id = "StripWhitespace"
-    display_name = "Strip Whitespace (DEPRECATED)"
-    category = "text"
+    display_name = "Strip Whitespace"
     description = "Strip leading and trailing whitespace from all texts."
-    is_deprecated = True  # This node is superseded by the Trim Text node
 
     @classmethod
     def _process(cls, text):
@@ -1007,13 +952,11 @@ class StripWhitespaceNode(TextProcessingNode):
 
 
 class ImageDeduplicationNode(ImageProcessingNode):
-    """Remove duplicate or very similar images from a list using perceptual hashing."""
+    """Remove duplicate or very similar images from the dataset using perceptual hashing."""
 
     node_id = "ImageDeduplication"
-    search_aliases=["deduplicate", "remove duplicates", "similarity filter"]
-    display_name = "Deduplicate Images"
-    category = "image/batch"
-    description = "Remove duplicate or very similar images from a list."
+    display_name = "Image Deduplication"
+    description = "Remove duplicate or very similar images from the dataset."
     is_group_process = True  # Requires full list to compare images
     extra_inputs = [
         io.Float.Input(
@@ -1083,9 +1026,7 @@ class ImageGridNode(ImageProcessingNode):
     """Combine multiple images into a single grid/collage."""
 
     node_id = "ImageGrid"
-    search_aliases=["grid", "collage", "combine"]
-    display_name = "Make Image Grid"
-    category="image/batch"
+    display_name = "Image Grid"
     description = "Arrange multiple images into a grid layout."
     is_group_process = True  # Requires full list to create grid
     is_output_list = False  # Outputs single grid image
@@ -1161,12 +1102,9 @@ class MergeImageListsNode(ImageProcessingNode):
     """Merge multiple image lists into a single list."""
 
     node_id = "MergeImageLists"
-    search_aliases=["list", "merge list", "make list"]
-    display_name = "Merge Image Lists (DEPRECATED)"
-    category = "image/batch"
+    display_name = "Merge Image Lists"
     description = "Concatenate multiple image lists into one."
     is_group_process = True  # Receives images as list
-    is_deprecated = True  # This node is superseded by the Create List node
 
     @classmethod
     def _group_process(cls, images):
@@ -1181,11 +1119,9 @@ class MergeTextListsNode(TextProcessingNode):
     """Merge multiple text lists into a single list."""
 
     node_id = "MergeTextLists"
-    display_name = "Merge Text Lists (DEPRECATED)"
-    category = "text"
+    display_name = "Merge Text Lists"
     description = "Concatenate multiple text lists into one."
     is_group_process = True  # Receives texts as list
-    is_deprecated = True  # This node is superseded by the Create List node
 
     @classmethod
     def _group_process(cls, texts):
@@ -1206,10 +1142,8 @@ class ResolutionBucket(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="ResolutionBucket",
-            search_aliases=["bucket by resolution", "group by resolution", "batch by resolution"],
             display_name="Resolution Bucket",
-            category="training",
-            description="Group latents and conditionings into buckets",
+            category="dataset",
             is_experimental=True,
             is_input_list=True,
             inputs=[
@@ -1302,8 +1236,7 @@ class MakeTrainingDataset(io.ComfyNode):
             node_id="MakeTrainingDataset",
             search_aliases=["encode dataset"],
             display_name="Make Training Dataset",
-            category="training",
-            description="Encode images with VAE and texts with CLIP to create a training dataset of latents and conditionings.",
+            category="dataset",
             is_experimental=True,
             is_input_list=True,  # images and texts as lists
             inputs=[
@@ -1318,7 +1251,6 @@ class MakeTrainingDataset(io.ComfyNode):
                     "texts",
                     optional=True,
                     tooltip="List of text captions. Can be length n (matching images), 1 (repeated for all), or omitted (uses empty string).",
-                    force_input=True
                 ),
             ],
             outputs=[
@@ -1388,10 +1320,9 @@ class SaveTrainingDataset(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="SaveTrainingDataset",
-            search_aliases=["export dataset", "save dataset"],
+            search_aliases=["export training data"],
             display_name="Save Training Dataset",
-            category="training",
-            description="Save encoded training dataset (latents + conditioning) to disk for efficient loading during training.",
+            category="dataset",
             is_experimental=True,
             is_output_node=True,
             is_input_list=True,  # Receive lists
@@ -1493,8 +1424,7 @@ class LoadTrainingDataset(io.ComfyNode):
             node_id="LoadTrainingDataset",
             search_aliases=["import dataset", "training data"],
             display_name="Load Training Dataset",
-            category="training",
-            description="Load encoded training dataset (latents + conditioning) from disk for use in training.",
+            category="dataset",
             is_experimental=True,
             inputs=[
                 io.String.Input(

comfy_extras/nodes_hunyuan3d.py

@@ -419,17 +419,15 @@ class VoxelToMeshBasic(IO.ComfyNode):
     def define_schema(cls):
         return IO.Schema(
             node_id="VoxelToMeshBasic",
-            display_name="Voxel to Mesh (Basic) (DEPRECATED)",
+            display_name="Voxel to Mesh (Basic)",
             category="3d",
-            description="Converts a voxel grid to a mesh.",
-            is_deprecated=True, # This node is superseded by the Voxel To Mesh node
             inputs=[
                 IO.Voxel.Input("voxel"),
                 IO.Float.Input("threshold", default=0.6, min=-1.0, max=1.0, step=0.01),
             ],
             outputs=[
                 IO.Mesh.Output(),
-            ],
+            ]
         )
 
     @classmethod
@@ -455,10 +453,9 @@ class VoxelToMesh(IO.ComfyNode):
             node_id="VoxelToMesh",
             display_name="Voxel to Mesh",
             category="3d",
-            description="Converts a voxel grid to a mesh.",
             inputs=[
                 IO.Voxel.Input("voxel"),
-                IO.Combo.Input("algorithm", options=["surface net", "basic"]),
+                IO.Combo.Input("algorithm", options=["surface net", "basic"], advanced=True),
                 IO.Float.Input("threshold", default=0.6, min=-1.0, max=1.0, step=0.01),
             ],
             outputs=[

comfy_extras/nodes_images.py

@@ -55,10 +55,9 @@ class ImageCropV2(IO.ComfyNode):
     def define_schema(cls):
         return IO.Schema(
             node_id="ImageCropV2",
-            search_aliases=["crop", "cut", "trim"],
+            search_aliases=["trim"],
             display_name="Crop Image",
             category="image/transform",
-            description = "Crop an image to the specified dimensions.",
             essentials_category="Image Tools",
             has_intermediate_output=True,
             inputs=[

comfy_extras/nodes_logic.py

@@ -15,7 +15,7 @@ class SwitchNode(io.ComfyNode):
         return io.Schema(
             node_id="ComfySwitchNode",
             display_name="Switch",
-            category="utils/logic",
+            category="logic",
             is_experimental=True,
             inputs=[
                 io.Boolean.Input("switch"),
@@ -46,7 +46,7 @@ class SoftSwitchNode(io.ComfyNode):
         return io.Schema(
             node_id="ComfySoftSwitchNode",
             display_name="Soft Switch",
-            category="utils/logic",
+            category="logic",
             is_experimental=True,
             inputs=[
                 io.Boolean.Input("switch"),
@@ -136,7 +136,7 @@ class DCTestNode(io.ComfyNode):
         return io.Schema(
             node_id="DCTestNode",
             display_name="DCTest",
-            category="utils/logic",
+            category="logic",
             is_output_node=True,
             inputs=[io.DynamicCombo.Input("combo", options=[
                 io.DynamicCombo.Option("option1", [io.String.Input("string")]),
@@ -174,7 +174,7 @@ class AutogrowNamesTestNode(io.ComfyNode):
         return io.Schema(
             node_id="AutogrowNamesTestNode",
             display_name="AutogrowNamesTest",
-            category="utils/logic",
+            category="logic",
             inputs=[
                 _io.Autogrow.Input("autogrow", template=template)
             ],
@@ -194,7 +194,7 @@ class AutogrowPrefixTestNode(io.ComfyNode):
         return io.Schema(
             node_id="AutogrowPrefixTestNode",
             display_name="AutogrowPrefixTest",
-            category="utils/logic",
+            category="logic",
             inputs=[
                 _io.Autogrow.Input("autogrow", template=template)
             ],
@@ -213,7 +213,7 @@ class ComboOutputTestNode(io.ComfyNode):
         return io.Schema(
             node_id="ComboOptionTestNode",
             display_name="ComboOptionTest",
-            category="utils/logic",
+            category="logic",
             inputs=[io.Combo.Input("combo", options=["option1", "option2", "option3"]),
                     io.Combo.Input("combo2", options=["option4", "option5", "option6"])],
             outputs=[io.Combo.Output(), io.Combo.Output()],
@@ -230,7 +230,7 @@ class ConvertStringToComboNode(io.ComfyNode):
             node_id="ConvertStringToComboNode",
             search_aliases=["string to dropdown", "text to combo"],
             display_name="Convert String to Combo",
-            category="utils/logic",
+            category="logic",
             inputs=[io.String.Input("string")],
             outputs=[io.Combo.Output()],
         )
@@ -246,7 +246,7 @@ class InvertBooleanNode(io.ComfyNode):
             node_id="InvertBooleanNode",
             search_aliases=["not", "toggle", "negate", "flip boolean"],
             display_name="Invert Boolean",
-            category="utils/logic",
+            category="logic",
             inputs=[io.Boolean.Input("boolean")],
             outputs=[io.Boolean.Output()],
         )

comfy_extras/nodes_lt_audio.py

@@ -11,8 +11,8 @@ class LTXVAudioVAELoader(io.ComfyNode):
     def define_schema(cls) -> io.Schema:
         return io.Schema(
             node_id="LTXVAudioVAELoader",
-            display_name="Load LTXV Audio VAE",
-            category="loaders",
+            display_name="LTXV Audio VAE Loader",
+            category="audio",
             inputs=[
                 io.Combo.Input(
                     "ckpt_name",
@@ -40,7 +40,7 @@ class LTXVAudioVAEEncode(VAEEncodeAudio):
         return io.Schema(
             node_id="LTXVAudioVAEEncode",
             display_name="LTXV Audio VAE Encode",
-            category="latent/audio",
+            category="audio",
             inputs=[
                 io.Audio.Input("audio", tooltip="The audio to be encoded."),
                 io.Vae.Input(
@@ -63,7 +63,7 @@ class LTXVAudioVAEDecode(io.ComfyNode):
         return io.Schema(
             node_id="LTXVAudioVAEDecode",
             display_name="LTXV Audio VAE Decode",
-            category="latent/audio",
+            category="audio",
             inputs=[
                 io.Latent.Input("samples", tooltip="The latent to be decoded."),
                 io.Vae.Input(

comfy_extras/nodes_math.py

@@ -70,7 +70,7 @@ class MathExpressionNode(io.ComfyNode):
         return io.Schema(
             node_id="ComfyMathExpression",
             display_name="Math Expression",
-            category="utils",
+            category="logic",
             search_aliases=[
                 "expression", "formula", "calculate", "calculator",
                 "eval", "math",

comfy_extras/nodes_mediapipe.py

@@ -28,7 +28,7 @@ from comfy_extras.mediapipe.face_landmarker import FaceLandmarker
 from comfy_extras.mediapipe.face_geometry import transformation_matrix_from_detection
 
 
-FaceDetectionType = io.Custom("FACE_DETECTION_MODEL")
+FaceLandmarkerType = io.Custom("FACE_LANDMARKER")
 FaceLandmarksType = io.Custom("FACE_LANDMARKS")
 
 _CANONICAL_KEYS = ("canonical_vertices", "procrustes_indices", "procrustes_weights")
@@ -204,19 +204,18 @@ class LoadMediaPipeFaceLandmarker(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="LoadMediaPipeFaceLandmarker",
-            search_aliases=["face", "facial", "mediapipe", "face landmark", "face mesh", "blazeface", "face detection"],
-            display_name="Load Face Detection Model (MediaPipe)",
+            display_name="Load MediaPipe Face Landmarker",
             category="loaders",
             inputs=[
-                io.Combo.Input("model_name", options=folder_paths.get_filename_list("detection"),
-                               tooltip="Face detection model from models/detection/."),
+                io.Combo.Input("model_name", options=folder_paths.get_filename_list("mediapipe"),
+                               tooltip="Face Landmarker safetensors from models/mediapipe/."),
             ],
-            outputs=[FaceDetectionType.Output()],
+            outputs=[FaceLandmarkerType.Output()],
         )
 
     @classmethod
     def execute(cls, model_name) -> io.NodeOutput:
-        sd = comfy.utils.load_torch_file(folder_paths.get_full_path_or_raise("detection", model_name), safe_load=True)
+        sd = comfy.utils.load_torch_file(folder_paths.get_full_path_or_raise("mediapipe", model_name), safe_load=True)
         wrapper = FaceLandmarkerModel(sd)
         return io.NodeOutput(wrapper)
 
@@ -235,12 +234,10 @@ class MediaPipeFaceLandmarker(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="MediaPipeFaceLandmarker",
-            search_aliases=["face", "facial", "mediapipe", "face landmark", "face mesh", "blazeface", "face detection"],
-            display_name="Detect Face Landmarks (MediaPipe)",
+            display_name="MediaPipe Face Landmarker",
             category="image/detection",
-            description="Detects facial landmarks using MediaPipe model.",
             inputs=[
-                FaceDetectionType.Input("face_detection_model"),
+                FaceLandmarkerType.Input("face_landmarker"),
                 io.Image.Input("image"),
                 io.Combo.Input("detector_variant", options=["short", "full", "both"], default="short",
                                tooltip="Face detector range. 'short' is tuned for close-up faces "
@@ -264,9 +261,9 @@ class MediaPipeFaceLandmarker(io.ComfyNode):
         )
 
     @classmethod
-    def execute(cls, face_detection_model, image, detector_variant, num_faces, min_confidence,
+    def execute(cls, face_landmarker, image, detector_variant, num_faces, min_confidence,
                 missing_frame_fallback) -> io.NodeOutput:
-        canonical = face_detection_model.canonical_data
+        canonical = face_landmarker.canonical_data
         img_np = _image_to_uint8(image)
         B, H, W = img_np.shape[:3]
         chunk = 16
@@ -279,7 +276,7 @@ class MediaPipeFaceLandmarker(io.ComfyNode):
             with tqdm(total=B, desc=f"MediaPipe Face Landmarker ({variant})") as tq:
                 for i in range(0, B, chunk):
                     end = min(i + chunk, B)
-                    res.extend(face_detection_model.detect_batch(
+                    res.extend(face_landmarker.detect_batch(
                         [img_np[bi] for bi in range(i, end)],
                         num_faces=int(num_faces),
                         score_thresh=float(min_confidence),
@@ -309,7 +306,7 @@ class MediaPipeFaceLandmarker(io.ComfyNode):
                 per_bb.append({"x": x1, "y": y1, "width": x2 - x1, "height": y2 - y1, "label": "face", "score": float(f["score"])})
             bboxes.append(per_bb)
         return io.NodeOutput({"frames": frames, "image_size": (H, W),
-                              "connection_sets": face_detection_model.connection_sets}, bboxes)
+                              "connection_sets": face_landmarker.connection_sets}, bboxes)
 
 
 # Topology keys unioned by the 'all' connections preset (contour parts + irises + nose).
@@ -335,10 +332,8 @@ class MediaPipeFaceMeshVisualize(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="MediaPipeFaceMeshVisualize",
-            search_aliases=["face", "facial", "mediapipe", "face landmark", "face mesh", "blazeface", "face detection", "visualize"],
-            display_name="Visualize Face Landmarks (MediaPipe)",
+            display_name="MediaPipe Face Mesh Visualize",
             category="image/detection",
-            description="Draws face landmarks mesh on the input image.",
             inputs=[
                 FaceLandmarksType.Input("face_landmarks"),
                 io.Image.Input("image", optional=True, tooltip="If not connected, a black canvas will be used."),
@@ -448,10 +443,8 @@ class MediaPipeFaceMask(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="MediaPipeFaceMask",
-            search_aliases=["face", "facial", "mediapipe", "face mask", "blazeface", "face detection", "visualize"],
-            display_name="Draw Face Mask (MediaPipe)",
+            display_name="MediaPipe Face Mask",
             category="image/detection",
-            description="Draws a mask from face landmarks.",
             inputs=[
                 FaceLandmarksType.Input("face_landmarks"),
                 io.DynamicCombo.Input(

comfy_extras/nodes_moge.py

@@ -103,10 +103,8 @@ class MoGePanoramaInference(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="MoGePanoramaInference",
-            search_aliases=["moge", "panorama", "depth", "geometry", "depth estimation", "geometry estimation"],
-            display_name="Run MoGe Panorama Inference",
+            display_name="MoGe Panorama Inference",
             category="image/geometry_estimation",
-            description="Run MoGe on an equirectangular panorama by splitting it into 12 perspective views, running inference on each, and merging the results into a single depth map.",
             inputs=[
                 MoGeModelType.Input("moge_model"),
                 io.Image.Input("image", tooltip="Equirectangular panorama (any aspect)."),
@@ -224,9 +222,7 @@ class MoGeInference(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="MoGeInference",
-            search_aliases=["moge", "depth", "geometry", "depth estimation", "geometry estimation"],
-            display_name="Run MoGe Inference",
-            description="Run MoGe on a single image to estimate depth and geometry.",
+            display_name="MoGe Inference",
             category="image/geometry_estimation",
             inputs=[
                 MoGeModelType.Input("moge_model"),
@@ -281,9 +277,7 @@ class MoGeRender(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="MoGeRender",
-            search_aliases=["moge", "render", "geometry", "depth", "normal"],
-            display_name="Render MoGe Geometry",
-            description="Render a depth map or normal map from geometry data",
+            display_name="MoGe Render",
             category="image/geometry_estimation",
             inputs=[
                 MoGeGeometry.Input("moge_geometry"),
@@ -348,9 +342,7 @@ class MoGePointMapToMesh(io.ComfyNode):
     def define_schema(cls):
         return io.Schema(
             node_id="MoGePointMapToMesh",
-            search_aliases=["moge", "mesh", "geometry", "point map"],
-            display_name="Convert MoGe Point Map to Mesh",
-            description="Convert a MoGe point map into a 3D mesh.",
+            display_name="MoGe Point Map to Mesh",
             category="image/geometry_estimation",
             inputs=[
                 MoGeGeometry.Input("moge_geometry"),

comfy_extras/nodes_toolkit.py

@@ -14,7 +14,7 @@ class CreateList(io.ComfyNode):
         return io.Schema(
             node_id="CreateList",
             display_name="Create List",
-            category="utils",
+            category="logic",
             is_input_list=True,
             search_aliases=["Image Iterator", "Text Iterator", "Iterator"],
             inputs=[io.Autogrow.Input("inputs", template=template_autogrow)],

folder_paths.py

@@ -60,7 +60,7 @@ folder_names_and_paths["geometry_estimation"] = ([os.path.join(models_dir, "geom
 
 folder_names_and_paths["optical_flow"] = ([os.path.join(models_dir, "optical_flow")], supported_pt_extensions)
 
-folder_names_and_paths["detection"] = ([os.path.join(models_dir, "detection")], supported_pt_extensions)
+folder_names_and_paths["mediapipe"] = ([os.path.join(models_dir, "mediapipe")], supported_pt_extensions)
 
 output_directory = os.path.join(base_path, "output")
 temp_directory = os.path.join(base_path, "temp")

openapi.yaml

@@ -1556,6 +1556,12 @@ paths:
             type: string
             enum: [asc, desc]
           description: Sort direction
+        - name: job_ids
+          in: query
+          schema:
+            type: string
+          x-runtime: [cloud]
+          description: "[cloud-only] Comma-separated UUIDs to filter assets by associated job."
         - name: include_public
           in: query
           schema:
@@ -2508,25 +2514,37 @@ paths:
 
   /api/assets/import:
     post:
-      operationId: importPublishedAssets
+      operationId: importAssets
       tags: [assets]
-      summary: "[cloud-only] Import published assets into the caller's library"
-      description: |
-        [cloud-only] Imports the specified published assets into the caller's asset library. New DB records reference the same storage objects; no file copying occurs. Assets the caller already owns (by hash) are deduplicated. The `id` field on each returned `AssetInfo` is the caller's newly-created private asset ID, not the published asset ID supplied in the request.
+      summary: Import assets from external URLs
+      description: "[cloud-only] Imports one or more assets from external URLs into the cloud asset store."
       x-runtime: [cloud]
       requestBody:
         required: true
         content:
           application/json:
             schema:
-              $ref: "#/components/schemas/ImportPublishedAssetsRequest"
+              type: object
+              required:
+                - imports
+              properties:
+                imports:
+                  type: array
+                  items:
+                    $ref: "#/components/schemas/AssetImportRequest"
+                  description: Assets to import
       responses:
         "200":
-          description: Successfully imported assets
+          description: Import initiated
           content:
             application/json:
               schema:
-                $ref: "#/components/schemas/ImportPublishedAssetsResponse"
+                type: object
+                properties:
+                  assets:
+                    type: array
+                    items:
+                      $ref: "#/components/schemas/Asset"
         "400":
           description: Bad request
           content:
@@ -3772,295 +3790,6 @@ paths:
               schema:
                 $ref: "#/components/schemas/JwksResponse"
 
-  # ---------------------------------------------------------------------------
-  # OAuth 2.1 / RFC 7591 Dynamic Client Registration (cloud)
-  # ---------------------------------------------------------------------------
-  /.well-known/oauth-authorization-server:
-    get:
-      operationId: getOAuthAuthorizationServer
-      tags: [auth]
-      summary: "[cloud-only] OAuth 2.1 authorization-server metadata (RFC 8414)"
-      description: "[cloud-only] Public metadata document for OAuth 2.1 clients. Cached 5 minutes."
-      x-runtime: [cloud]
-      security: []
-      responses:
-        "200":
-          description: Authorization-server metadata
-          content:
-            application/json:
-              schema:
-                $ref: "#/components/schemas/OAuthAuthorizationServerMetadata"
-        "404":
-          description: OAuth disabled
-          content:
-            application/json:
-              schema:
-                $ref: "#/components/schemas/CloudError"
-
-  /.well-known/oauth-protected-resource:
-    get:
-      operationId: getOAuthProtectedResource
-      tags: [auth]
-      summary: "[cloud-only] OAuth 2.1 protected-resource metadata (RFC 9728)"
-      description: "[cloud-only] Public metadata describing the currently advertised protected resource. Cached 5 minutes."
-      x-runtime: [cloud]
-      security: []
-      responses:
-        "200":
-          description: Protected-resource metadata
-          content:
-            application/json:
-              schema:
-                $ref: "#/components/schemas/OAuthProtectedResourceMetadata"
-        "404":
-          description: OAuth disabled or no active resource configured
-          content:
-            application/json:
-              schema:
-                $ref: "#/components/schemas/CloudError"
-
-  /oauth/authorize:
-    get:
-      operationId: getOAuthAuthorize
-      tags: [auth]
-      summary: "[cloud-only] Begin or resume an OAuth 2.1 authorization request"
-      description: |
-        [cloud-only] Two modes:
-        - **Initial entry** (OAuth params present): validates client/redirect/resource/scopes, persists a server-side authorization-request row, and either redirects (no session / unverified email) to the configured frontend login URL carrying only the opaque `oauth_request_id`, or returns the JSON consent challenge for the frontend to render.
-        - **Resume** (`oauth_request_id` present): loads the server-side row, fails closed if expired/consumed/unknown, returns the JSON consent challenge. Browser-replayed OAuth params are intentionally ignored.
-
-        The frontend renders the consent UI from the JSON payload and POSTs the user's decision back to this endpoint.
-      x-runtime: [cloud]
-      security: []
-      parameters:
-        - { name: response_type,         in: query, required: false, schema: { type: string } }
-        - { name: client_id,             in: query, required: false, schema: { type: string } }
-        - { name: redirect_uri,          in: query, required: false, schema: { type: string } }
-        - { name: scope,                 in: query, required: false, schema: { type: string } }
-        - name: state
-          in: query
-          required: false
-          schema: { type: string }
-          description: |
-            RFC 6749 §10.12 marks `state` as RECOMMENDED. Cloud hardening makes it REQUIRED on the initial-entry path (omitted only on the resume path where `oauth_request_id` is supplied instead). This parameter is `required: false` at the spec level only because the operation is dual-mode (initial entry vs. resume); the runtime rejects empty `state` on the initial-entry path with a stable `invalid_request` 400.
-        - { name: code_challenge,        in: query, required: false, schema: { type: string } }
-        - { name: code_challenge_method, in: query, required: false, schema: { type: string } }
-        - { name: resource,              in: query, required: false, schema: { type: string } }
-        - { name: oauth_request_id,      in: query, required: false, schema: { type: string } }
-      responses:
-        "200":
-          description: Consent challenge payload (session present, email verified). Frontend renders the consent UI from this payload and POSTs back to /oauth/authorize.
-          content:
-            application/json:
-              schema:
-                $ref: "#/components/schemas/OAuthConsentChallenge"
-        "302":
-          description: Redirect to login (no session / unverified email) or to registered redirect_uri (pre-validated client error)
-          headers:
-            Location:
-              schema:
-                type: string
-        "400":
-          description: Invalid authorize request (pre-redirect failure — unknown client, redirect mismatch, malformed params)
-          content:
-            application/json:
-              schema:
-                $ref: "#/components/schemas/CloudError"
-        "404":
-          description: OAuth disabled
-          content:
-            application/json:
-              schema:
-                $ref: "#/components/schemas/CloudError"
-    post:
-      operationId: postOAuthAuthorize
-      tags: [auth]
-      summary: "[cloud-only] Submit OAuth consent decision"
-      description: |
-        [cloud-only] JSON-only consent submission. The handler verifies the per-row CSRF token, atomically marks the authorization request consumed (single-use covers both allow and deny paths), then returns the redirect URL the browser must navigate to. The URL contains either `code` + original `state` for allow, or the RFC 6749 §5.2 error and `state` for deny.
-
-        Workspace membership is re-checked at submission time. Consent is persisted keyed by `(user_id, client_id, resource_id, workspace_id)`; broadening the previously approved scope set requires a fresh consent flow.
-      x-runtime: [cloud]
-      security: []
-      requestBody:
-        required: true
-        content:
-          application/json:
-            schema:
-              type: object
-              required: [oauth_request_id, csrf_token, decision, workspace_id]
-              properties:
-                oauth_request_id: { type: string, format: uuid }
-                csrf_token:       { type: string }
-                decision:         { type: string, enum: [allow, deny] }
-                workspace_id:     { type: string }
-      responses:
-        "200":
-          description: Redirect URL for the frontend to navigate to (allow → with code+state; deny → with error+state)
-          content:
-            application/json:
-              schema:
-                $ref: "#/components/schemas/OAuthAuthorizeRedirectResponse"
-        "400":
-          description: Bad request (CSRF mismatch, expired/consumed request, inaccessible workspace)
-          content:
-            application/json:
-              schema:
-                $ref: "#/components/schemas/CloudError"
-        "403":
-          description: Scope broadening on consent re-grant — fresh consent flow required
-          content:
-            application/json:
-              schema:
-                $ref: "#/components/schemas/CloudError"
-        "404":
-          description: OAuth disabled
-          content:
-            application/json:
-              schema:
-                $ref: "#/components/schemas/CloudError"
-
-  /oauth/token:
-    post:
-      operationId: postOAuthToken
-      tags: [auth]
-      summary: "[cloud-only] Exchange authorization code or refresh token for a resource-bound access token"
-      description: |
-        [cloud-only] OAuth 2.1 token endpoint (RFC 6749 §3.2). Public clients only — `client_secret` is rejected.
-
-        Two grant types are supported:
-        - `authorization_code` — exchanges the code minted by `/oauth/authorize` (with PKCE verifier) for an access token + first refresh token. Single-use; reuse fails closed.
-        - `refresh_token` — rotates the refresh token. Old token immediately invalid; presenting an already-rotated token revokes the entire token family and emits a security metric.
-
-        Both grant types re-validate canonical user state, current workspace membership, and the resource's active flag at every mint. A code or refresh token bound to a deactivated resource fails closed.
-
-        Errors follow RFC 6749 §5.2. Logs never contain raw codes, refresh tokens, or minted tokens.
-
-        Per RFC 6749 §5.1, every 200 and 400 response carries `Cache-Control: no-store` and `Pragma: no-cache` so intermediaries cannot cache token-bearing or state-change-reason responses.
-      x-runtime: [cloud]
-      security: []
-      requestBody:
-        required: true
-        content:
-          application/x-www-form-urlencoded:
-            schema:
-              type: object
-              required: [grant_type, client_id]
-              properties:
-                grant_type:    { type: string, enum: [authorization_code, refresh_token] }
-                client_id:     { type: string }
-                code:          { type: string }
-                redirect_uri:  { type: string }
-                code_verifier: { type: string }
-                refresh_token: { type: string }
-                scope:         { type: string }
-                client_secret: { type: string }
-      responses:
-        "200":
-          description: New token pair
-          headers:
-            Cache-Control:
-              schema:
-                type: string
-              description: 'Always "no-store" per RFC 6749 §5.1'
-            Pragma:
-              schema:
-                type: string
-              description: 'Always "no-cache" per RFC 6749 §5.1'
-          content:
-            application/json:
-              schema:
-                $ref: "#/components/schemas/OAuthTokenResponse"
-        "400":
-          description: RFC 6749 §5.2 error
-          headers:
-            Cache-Control:
-              schema:
-                type: string
-              description: 'Always "no-store" per RFC 6749 §5.1'
-            Pragma:
-              schema:
-                type: string
-              description: 'Always "no-cache" per RFC 6749 §5.1'
-          content:
-            application/json:
-              schema:
-                $ref: "#/components/schemas/OAuthTokenError"
-        "404":
-          description: OAuth disabled
-          content:
-            application/json:
-              schema:
-                $ref: "#/components/schemas/CloudError"
-
-  /oauth/register:
-    post:
-      operationId: postOAuthRegister
-      tags: [auth]
-      summary: "[cloud-only] Dynamic Client Registration (RFC 7591)"
-      description: |
-        [cloud-only] Public, unauthenticated, insert-only RFC 7591 §3.1 client registration. Used by MCP-spec-compliant clients to self-register a public OAuth client without operator involvement.
-
-        Policy:
-
-        - Public clients only — `token_endpoint_auth_method` is forced to `none`. Confidential-client registration is out of scope this phase.
-        - Server-owned `resource_grants`. Caller-supplied `scope` or `resource_grants` is rejected as `invalid_client_metadata` (would be a privilege-escalation surface). Dynamic clients receive the same scopes the active resource publishes.
-        - Application-type-aware redirect URI policy. `application_type=native` accepts loopback (`127.0.0.1`, `::1`, `localhost`) and reverse-DNS-shaped custom schemes; `application_type=web` accepts HTTPS to hosts in an operator-controlled allowlist only. `application_type` is REQUIRED on the request — missing or empty rejects with `invalid_client_metadata`.
-        - Anti-impersonation: reserved client names are rejected from third parties via NFKC-folded compare.
-        - Generated `client_id` carries a stable prefix to distinguish dynamic from seeded clients in audit logs.
-        - Cache-Control: `no-store` on every 201 and 400 response (the response carries fresh credentials and rejection reasons).
-      x-runtime: [cloud]
-      security: []
-      requestBody:
-        required: true
-        content:
-          application/json:
-            schema:
-              $ref: "#/components/schemas/OAuthRegisterRequest"
-      responses:
-        "201":
-          description: Registered. Body echoes the metadata RFC 7591 §3.2.1 requires.
-          headers:
-            Cache-Control:
-              schema:
-                type: string
-              description: 'Always "no-store"'
-            Pragma:
-              schema:
-                type: string
-              description: 'Always "no-cache"'
-          content:
-            application/json:
-              schema:
-                $ref: "#/components/schemas/OAuthRegisterResponse"
-        "400":
-          description: RFC 7591 §3.2.2 invalid client metadata
-          headers:
-            Cache-Control:
-              schema:
-                type: string
-              description: 'Always "no-store"'
-            Pragma:
-              schema:
-                type: string
-              description: 'Always "no-cache"'
-          content:
-            application/json:
-              schema:
-                $ref: "#/components/schemas/OAuthRegisterError"
-        "404":
-          description: OAuth disabled
-          content:
-            application/json:
-              schema:
-                $ref: "#/components/schemas/CloudError"
-        "503":
-          description: No active resource is configured — DCR cannot mint a usable client until an active resource row is seeded.
-          content:
-            application/json:
-              schema:
-                $ref: "#/components/schemas/CloudError"
-
   # ---------------------------------------------------------------------------
   # Billing (cloud)
   # ---------------------------------------------------------------------------
@@ -7361,35 +7090,24 @@ components:
           type: string
           description: Target path on the runtime filesystem
 
-    ImportPublishedAssetsRequest:
+    AssetImportRequest:
       type: object
       x-runtime: [cloud]
-      description: "[cloud-only] Request body for importing published assets into the caller's library."
+      description: "[cloud-only] A single asset to import from an external URL."
       required:
-        - published_asset_ids
+        - url
       properties:
-        published_asset_ids:
+        url:
+          type: string
+          format: uri
+          description: URL of the asset to import
+        name:
+          type: string
+          description: Display name for the imported asset
+        tags:
           type: array
-          description: IDs of published assets (inputs and models) to import.
           items:
             type: string
-        share_id:
-          type: string
-          nullable: true
-          description: |
-            Optional. Share ID of the published workflow these assets belong to. When provided (non-null, non-empty): all `published_asset_ids` must belong to this share's workflow version; returns 400 if the share is not found or any asset does not belong to it. When omitted, null, or empty string: no share-scoped validation is performed and the assets are validated only against global rules (preserved for clients that have not yet adopted `share_id`).
-
-    ImportPublishedAssetsResponse:
-      type: object
-      x-runtime: [cloud]
-      description: "[cloud-only] Response after importing published assets. Each returned `AssetInfo.id` is the caller's newly-created private asset ID, not the published asset ID supplied in the request."
-      required:
-        - assets
-      properties:
-        assets:
-          type: array
-          items:
-            $ref: "#/components/schemas/AssetInfo"
 
     RemoteAssetMetadata:
       type: object
@@ -7706,325 +7424,6 @@ components:
                 description: RSA exponent (base64url)
             additionalProperties: true
 
-    OAuthAuthorizationServerMetadata:
-      type: object
-      x-runtime: [cloud]
-      description: "[cloud-only] OAuth 2.1 authorization-server metadata (RFC 8414)."
-      required:
-        - issuer
-        - authorization_endpoint
-        - token_endpoint
-        - jwks_uri
-        - response_types_supported
-        - grant_types_supported
-        - code_challenge_methods_supported
-        - token_endpoint_auth_methods_supported
-      properties:
-        issuer:
-          type: string
-          format: uri
-        authorization_endpoint:
-          type: string
-          format: uri
-        token_endpoint:
-          type: string
-          format: uri
-        jwks_uri:
-          type: string
-          format: uri
-        registration_endpoint:
-          type: string
-          format: uri
-          description: "[cloud-only] RFC 7591 §3.1 Dynamic Client Registration endpoint. Advertised so MCP-spec-compliant clients can auto-discover and self-register without operator involvement. Present only when DCR is enabled."
-        response_types_supported:
-          type: array
-          items:
-            type: string
-        grant_types_supported:
-          type: array
-          items:
-            type: string
-        code_challenge_methods_supported:
-          type: array
-          items:
-            type: string
-        token_endpoint_auth_methods_supported:
-          type: array
-          items:
-            type: string
-        scopes_supported:
-          type: array
-          items:
-            type: string
-
-    OAuthProtectedResourceMetadata:
-      type: object
-      x-runtime: [cloud]
-      description: "[cloud-only] OAuth 2.1 protected-resource metadata (RFC 9728)."
-      required:
-        - resource
-        - authorization_servers
-        - scopes_supported
-      properties:
-        resource:
-          type: string
-          format: uri
-        authorization_servers:
-          type: array
-          items:
-            type: string
-            format: uri
-        scopes_supported:
-          type: array
-          items:
-            type: string
-        bearer_methods_supported:
-          type: array
-          items:
-            type: string
-
-    OAuthConsentChallenge:
-      type: object
-      x-runtime: [cloud]
-      description: "[cloud-only] Server-side state describing the OAuth consent decision the user is being asked to make. Returned by GET /oauth/authorize when a valid session exists; the frontend renders the consent UI from this payload and POSTs the decision back. Browser never sees the original OAuth params on resume."
-      required:
-        - oauth_request_id
-        - csrf_token
-        - client_display_name
-        - resource_display_name
-        - scopes
-        - workspaces
-      properties:
-        oauth_request_id:
-          type: string
-          format: uuid
-          description: Opaque server-side identifier for the authorization-request row. Carried back unchanged in the consent submission.
-        csrf_token:
-          type: string
-          description: Per-row CSRF token bound to this authorization request (not to the session). Must be echoed back on POST.
-        client_display_name:
-          type: string
-          description: Human-readable name of the OAuth client requesting authorization.
-        resource_display_name:
-          type: string
-          description: Human-readable name of the protected resource.
-        scopes:
-          type: array
-          description: Scopes the client is requesting for this resource. The frontend should present these for the user to approve.
-          items:
-            type: string
-        workspaces:
-          type: array
-          description: Workspaces the user can select from. Membership is re-checked on POST.
-          items:
-            $ref: "#/components/schemas/OAuthConsentChallengeWorkspace"
-
-    OAuthConsentChallengeWorkspace:
-      type: object
-      x-runtime: [cloud]
-      description: "[cloud-only] One workspace option presented in the OAuth consent challenge."
-      required: [id, name, type, role]
-      properties:
-        id:   { type: string }
-        name: { type: string }
-        type: { type: string, enum: [personal, team] }
-        role: { type: string, enum: [owner, member] }
-
-    OAuthAuthorizeRedirectResponse:
-      type: object
-      x-runtime: [cloud]
-      description: "[cloud-only] Redirect target produced after a JSON consent submission. The frontend must navigate the browser to this URL so custom-scheme client callbacks work without relying on fetch-visible 302 headers."
-      required:
-        - redirect_url
-      properties:
-        redirect_url:
-          type: string
-          format: uri
-          description: OAuth client redirect URI with either code+state for allow, or error+state for deny.
-
-    OAuthTokenResponse:
-      type: object
-      x-runtime: [cloud]
-      description: "[cloud-only] RFC 6749 §5.1 successful token response."
-      required: [access_token, token_type, expires_in, refresh_token, scope]
-      properties:
-        access_token:
-          type: string
-          description: Resource-bound access token (audience matches the protected resource).
-        token_type:
-          type: string
-          enum: [Bearer]
-        expires_in:
-          type: integer
-          description: Access token lifetime in seconds.
-        refresh_token:
-          type: string
-          description: Opaque refresh token. Rotates on every successful refresh; presenting an already-rotated token revokes the entire family.
-        scope:
-          type: string
-          description: Space-delimited scopes granted with this token.
-
-    OAuthTokenError:
-      type: object
-      x-runtime: [cloud]
-      description: "[cloud-only] RFC 6749 §5.2 error response."
-      required: [error]
-      properties:
-        error:
-          type: string
-          description: 'RFC 6749 §5.2 error code: invalid_request, invalid_client, invalid_grant, unauthorized_client, unsupported_grant_type, invalid_scope.'
-        error_description:
-          type: string
-          description: Human-readable, no leak of internal storage state.
-
-    OAuthRegisterRequest:
-      type: object
-      x-runtime: [cloud]
-      additionalProperties: false
-      description: "[cloud-only] RFC 7591 §2 client metadata document. Only the fields the server honors are listed; presence of `scope` or `resource_grants` in the request is rejected (`invalid_client_metadata`) because those are server-owned for dynamic clients."
-      required:
-        - redirect_uris
-        - application_type
-      properties:
-        redirect_uris:
-          type: array
-          items:
-            type: string
-          minItems: 1
-          maxItems: 5
-          description: 1–5 redirect URIs. Validated against `application_type` policy.
-        client_name:
-          type: string
-          maxLength: 100
-          description: Human-readable name shown in the consent UI. Reserved-name list rejects impersonation of major clients.
-        application_type:
-          type: string
-          enum: [native, web]
-          description: |
-            RFC 7591 §2 application_type. **REQUIRED** — clients MUST declare intent; the server does not default this field. `native` for desktop / CLI / MCP-spec-strict clients (loopback redirects); `web` for hosted clients (HTTPS only, host must be allowlisted). A missing or explicitly empty `application_type` rejects with `invalid_client_metadata`.
-        token_endpoint_auth_method:
-          type: string
-          enum: [none]
-          description: 'Public clients only this phase — must be `none` if present. The server forces `none` regardless.'
-        grant_types:
-          type: array
-          items:
-            type: string
-            enum: [authorization_code, refresh_token]
-          description: Optional. Defaults to `["authorization_code","refresh_token"]`.
-        response_types:
-          type: array
-          items:
-            type: string
-            enum: [code]
-          description: Optional. Defaults to `["code"]`.
-        scope:
-          type: string
-          nullable: true
-          description: "**REJECTED IF PRESENT.** Dynamic clients do not pick scopes — the server assigns scopes from the active resource's published list. Sending `scope` in the registration body is treated as a privilege-escalation attempt and returns `invalid_client_metadata`."
-        resource_grants:
-          type: object
-          nullable: true
-          additionalProperties:
-            type: array
-            items:
-              type: string
-          description: "**REJECTED IF PRESENT.** Same reason as `scope`. The set of resources and scopes a dynamic client may request is server-policy, not request-driven."
-        client_uri:
-          type: string
-          nullable: true
-          description: "**REJECTED IF PRESENT.** Unsupported RFC 7591 metadata for this public-client phase."
-        logo_uri:
-          type: string
-          nullable: true
-          description: "**REJECTED IF PRESENT.** Unsupported RFC 7591 metadata for this public-client phase."
-        tos_uri:
-          type: string
-          nullable: true
-          description: "**REJECTED IF PRESENT.** Unsupported RFC 7591 metadata for this public-client phase."
-        policy_uri:
-          type: string
-          nullable: true
-          description: "**REJECTED IF PRESENT.** Unsupported RFC 7591 metadata for this public-client phase."
-        software_id:
-          type: string
-          nullable: true
-          description: "**REJECTED IF PRESENT.** Unsupported RFC 7591 metadata for this public-client phase."
-        software_version:
-          type: string
-          nullable: true
-          description: "**REJECTED IF PRESENT.** Unsupported RFC 7591 metadata for this public-client phase."
-        contacts:
-          type: array
-          nullable: true
-          items:
-            type: string
-          description: "**REJECTED IF PRESENT.** Unsupported RFC 7591 metadata for this public-client phase."
-        jwks:
-          type: object
-          nullable: true
-          additionalProperties: true
-          description: "**REJECTED IF PRESENT.** Unsupported RFC 7591 metadata for this public-client phase."
-        jwks_uri:
-          type: string
-          nullable: true
-          description: "**REJECTED IF PRESENT.** Unsupported RFC 7591 metadata for this public-client phase."
-
-    OAuthRegisterResponse:
-      type: object
-      x-runtime: [cloud]
-      description: "[cloud-only] RFC 7591 §3.2.1 successful registration response."
-      required:
-        - client_id
-        - client_id_issued_at
-        - redirect_uris
-        - grant_types
-        - response_types
-        - token_endpoint_auth_method
-        - application_type
-      properties:
-        client_id:
-          type: string
-          description: Server-generated client_id.
-        client_id_issued_at:
-          type: integer
-          format: int64
-          description: Unix timestamp (seconds) when the client was registered.
-        client_name:
-          type: string
-        redirect_uris:
-          type: array
-          items:
-            type: string
-        grant_types:
-          type: array
-          items:
-            type: string
-        response_types:
-          type: array
-          items:
-            type: string
-        token_endpoint_auth_method:
-          type: string
-          enum: [none]
-        application_type:
-          type: string
-          enum: [native, web]
-
-    OAuthRegisterError:
-      type: object
-      x-runtime: [cloud]
-      description: "[cloud-only] RFC 7591 §3.2.2 error response."
-      required:
-        - error
-      properties:
-        error:
-          type: string
-          enum: [invalid_redirect_uri, invalid_client_metadata]
-        error_description:
-          type: string
-          nullable: true
-
     BillingBalance:
       type: object
       x-runtime: [cloud]

tests-unit/assets_test/queries/test_asset_info.py

@@ -21,6 +21,7 @@ from app.assets.database.queries import (
     get_reference_ids_by_ids,
     ensure_tags_exist,
     add_tags_to_reference,
+    set_reference_tags,
 )
 from app.assets.helpers import get_utc_now
 
@@ -159,6 +160,153 @@ class TestListReferencesPage:
         assert refs[0].name == "large"
 
 
+class TestTagRetrievalOrder:
+    """End-to-end check: tags written through the public write paths come
+    back from the public read paths in insertion order rather than the
+    composite-PK alphabetical order SQLite would otherwise impose.
+
+    Each test deliberately picks tag names that would sort differently
+    under alphabetical vs insertion order, so an alphabetical regression
+    fails loudly.
+    """
+
+    def _make_ref(self, session: Session) -> AssetReference:
+        asset = _make_asset(session, "h1")
+        return _make_reference(session, asset, name="x.bin")
+
+    def test_set_reference_tags_preserves_input_order_in_list(self, session: Session):
+        ref = self._make_ref(session)
+        # "checkpoints" < "models" alphabetically; if added_at stagger
+        # works, list_references_page returns insertion order.
+        set_reference_tags(session, reference_id=ref.id, tags=["models", "checkpoints"])
+        session.commit()
+
+        _, tag_map, _ = list_references_page(session)
+        assert tag_map[ref.id] == ["models", "checkpoints"]
+
+    def test_set_reference_tags_preserves_input_order_in_fetch(self, session: Session):
+        ref = self._make_ref(session)
+        # Subpath tag sorts before "models" alphabetically.
+        set_reference_tags(
+            session,
+            reference_id=ref.id,
+            tags=["models", "diffusers/kolors/text_encoder"],
+        )
+        session.commit()
+
+        result = fetch_reference_asset_and_tags(session, ref.id)
+        assert result is not None
+        _, _, tags = result
+        # Bucket-prefix expansion appends the standalone `diffusers` token
+        # at path-tier (microsecond stagger) so FE set-membership filters
+        # match nested category paths.
+        assert tags == ["models", "diffusers/kolors/text_encoder", "diffusers"]
+
+    def test_add_tags_to_reference_lands_after_path_tags(self, session: Session):
+        ref = self._make_ref(session)
+        set_reference_tags(session, reference_id=ref.id, tags=["models", "checkpoints"])
+        session.commit()
+
+        # "aaa-..." sorts before both path tags alphabetically. If added_at
+        # stagger is missing, alphabetic tiebreak would hoist it to tags[0].
+        add_tags_to_reference(
+            session, reference_id=ref.id, tags=["aaa-user-tag"], origin="manual"
+        )
+        session.commit()
+
+        _, tag_map, _ = list_references_page(session)
+        assert tag_map[ref.id] == ["models", "checkpoints", "aaa-user-tag"]
+
+    def test_multi_tag_batch_lands_after_path_tags(self, session: Session):
+        ref = self._make_ref(session)
+        set_reference_tags(session, reference_id=ref.id, tags=["models", "checkpoints"])
+        session.commit()
+
+        # Three user tags inserted in non-alphabetical input order. Per-tag
+        # microsecond stagger should preserve at least the "user batch is
+        # after path tags" property; within the user batch insertion order
+        # is also preserved.
+        add_tags_to_reference(
+            session,
+            reference_id=ref.id,
+            tags=["zzz-z", "favorite", "experiment-q4"],
+            origin="manual",
+        )
+        session.commit()
+
+        _, tag_map, _ = list_references_page(session)
+        tags = tag_map[ref.id]
+        assert tags[0:2] == ["models", "checkpoints"]
+        assert set(tags[2:]) == {"zzz-z", "favorite", "experiment-q4"}
+
+    def test_user_batch_lands_after_path_batch_under_clock_collision(
+        self, session: Session, monkeypatch: pytest.MonkeyPatch
+    ):
+        """Windows-specific race: when two back-to-back commits share the
+        same datetime.now() microsecond, the path-tier and user-tier
+        added_at values used to collide and alphabetic tiebreak would
+        hoist user tags ahead of path tags. The fix reads
+        max(existing_added_at) for the reference and seeds the next batch
+        past it, deterministically restoring insertion order.
+
+        This test simulates the collision by pinning get_utc_now() so the
+        platform-dependent race becomes a platform-independent failure.
+        """
+        ref = self._make_ref(session)
+
+        from datetime import datetime
+        from app.assets.database import queries as queries_pkg
+        from app.assets.database.queries import tags as tags_module
+
+        frozen = datetime(2026, 1, 1, 0, 0, 0)
+        monkeypatch.setattr(tags_module, "get_utc_now", lambda: frozen)
+        monkeypatch.setattr(queries_pkg, "get_utc_now", lambda: frozen, raising=False)
+
+        set_reference_tags(session, reference_id=ref.id, tags=["models", "checkpoints"])
+        session.commit()
+
+        # Same frozen timestamp — without the max(existing) seed, the
+        # user batch would share added_at with the path batch and
+        # `aaa-user-tag` would sort to position 0 via the alphabetic
+        # tiebreaker.
+        add_tags_to_reference(
+            session, reference_id=ref.id, tags=["aaa-user-tag"], origin="manual"
+        )
+        session.commit()
+
+        _, tag_map, _ = list_references_page(session)
+        assert tag_map[ref.id] == ["models", "checkpoints", "aaa-user-tag"]
+
+    def test_remove_then_add_does_not_disrupt_path_tag_positions(
+        self, session: Session
+    ):
+        ref = self._make_ref(session)
+        set_reference_tags(
+            session,
+            reference_id=ref.id,
+            tags=["models", "loras/my/custom/path"],
+        )
+        session.commit()
+        add_tags_to_reference(session, reference_id=ref.id, tags=["temp-tag"])
+        session.commit()
+        from app.assets.database.queries import remove_tags_from_reference
+
+        remove_tags_from_reference(session, reference_id=ref.id, tags=["temp-tag"])
+        session.commit()
+        add_tags_to_reference(session, reference_id=ref.id, tags=["second-tag"])
+        session.commit()
+
+        _, tag_map, _ = list_references_page(session)
+        # `loras` is expanded from the nested category path; user-added
+        # tags trail behind it via the microsecond stagger.
+        assert tag_map[ref.id] == [
+            "models",
+            "loras/my/custom/path",
+            "loras",
+            "second-tag",
+        ]
+
+
 class TestFetchReferenceAssetAndTags:
     def test_returns_none_for_nonexistent(self, session: Session):
         result = fetch_reference_asset_and_tags(session, "nonexistent")

tests-unit/assets_test/queries/test_tags.py

@@ -160,6 +160,120 @@ class TestAddTagsToReference:
             add_tags_to_reference(session, reference_id="nonexistent", tags=["x"])
 
 
+class TestBucketPrefixExpansion:
+    """The standalone bucket token must appear in the asset's tag set for
+    nested category paths so FE filters like
+    `include_tags=models,checkpoints` continue to match.
+    """
+
+    def test_set_reference_tags_inserts_bucket_for_nested_path(
+        self, session: Session
+    ):
+        asset = _make_asset(session, "hash-nested")
+        ref = _make_reference(session, asset)
+
+        result = set_reference_tags(
+            session,
+            reference_id=ref.id,
+            tags=["models", "checkpoints/flux"],
+        )
+        session.commit()
+
+        assert set(result.total) == {"models", "checkpoints/flux", "checkpoints"}
+        stored = get_reference_tags(session, reference_id=ref.id)
+        # tag[1] keeps the slash-joined positional contract; the standalone
+        # bucket lands after it via path-tier microsecond stagger so user
+        # tags remain at the tail.
+        assert stored[:3] == ["models", "checkpoints/flux", "checkpoints"]
+
+    def test_set_reference_tags_idempotent_on_replay(self, session: Session):
+        asset = _make_asset(session, "hash-replay")
+        ref = _make_reference(session, asset)
+
+        set_reference_tags(
+            session,
+            reference_id=ref.id,
+            tags=["models", "checkpoints/flux"],
+        )
+        # Replay with the same caller-supplied set; expansion is already
+        # baked in, so nothing should be added or removed.
+        result = set_reference_tags(
+            session,
+            reference_id=ref.id,
+            tags=["models", "checkpoints/flux"],
+        )
+        session.commit()
+
+        assert result.added == []
+        assert result.removed == []
+        assert set(result.total) == {"models", "checkpoints/flux", "checkpoints"}
+
+    def test_add_tags_to_reference_expands_bucket(self, session: Session):
+        asset = _make_asset(session, "hash-add")
+        ref = _make_reference(session, asset)
+
+        result = add_tags_to_reference(
+            session,
+            reference_id=ref.id,
+            tags=["loras/style/v2"],
+        )
+        session.commit()
+
+        assert set(result.added) == {"loras/style/v2", "loras"}
+        stored = get_reference_tags(session, reference_id=ref.id)
+        assert "loras" in stored
+        assert "loras/style/v2" in stored
+
+    def test_add_tags_does_not_duplicate_existing_bucket(self, session: Session):
+        asset = _make_asset(session, "hash-dedupe")
+        ref = _make_reference(session, asset)
+
+        add_tags_to_reference(
+            session, reference_id=ref.id, tags=["models", "checkpoints"]
+        )
+        result = add_tags_to_reference(
+            session, reference_id=ref.id, tags=["checkpoints/flux"]
+        )
+        session.commit()
+
+        # `checkpoints` was already there from the first add; only the
+        # slash-joined token is genuinely new.
+        assert result.added == ["checkpoints/flux"]
+        assert "checkpoints" in result.already_present
+
+    def test_flat_category_is_unaffected(self, session: Session):
+        asset = _make_asset(session, "hash-flat")
+        ref = _make_reference(session, asset)
+
+        result = set_reference_tags(
+            session,
+            reference_id=ref.id,
+            tags=["models", "checkpoints"],
+        )
+        session.commit()
+
+        assert set(result.total) == {"models", "checkpoints"}
+        assert get_reference_tags(session, reference_id=ref.id) == [
+            "models",
+            "checkpoints",
+        ]
+
+    def test_unknown_prefix_passes_through(self, session: Session):
+        asset = _make_asset(session, "hash-user")
+        ref = _make_reference(session, asset)
+
+        # `my-org` isn't a registered bucket — the slash-joined user tag
+        # should not trigger bucket expansion.
+        result = set_reference_tags(
+            session,
+            reference_id=ref.id,
+            tags=["my-org/team-a"],
+        )
+        session.commit()
+
+        assert result.total == ["my-org/team-a"]
+
+
 class TestRemoveTagsFromReference:
     def test_removes_tags(self, session: Session):
         asset = _make_asset(session, "hash1")

tests-unit/assets_test/services/test_bulk_ingest.py

@@ -4,7 +4,7 @@ from pathlib import Path
 
 from sqlalchemy.orm import Session
 
-from app.assets.database.models import Asset, AssetReference
+from app.assets.database.models import Asset, AssetReference, AssetReferenceTag
 from app.assets.services.bulk_ingest import SeedAssetSpec, batch_insert_seed_assets
 
 
@@ -102,6 +102,82 @@ class TestBatchInsertSeedAssets:
             assert asset.mime_type == expected_mime, f"Expected {expected_mime} for {filename}, got {asset.mime_type}"
 
 
+class TestBucketPrefixExpansionOnIngest:
+    """Path-scanning ingest must persist the standalone bucket token for
+    nested category paths so the FE set-membership filter
+    (`include_tags=models,checkpoints`) matches assets organized into
+    subfolders (`models/checkpoints/flux/foo.safetensors`).
+    """
+
+    def test_nested_path_inserts_standalone_bucket(
+        self, session: Session, temp_dir: Path
+    ):
+        file_path = temp_dir / "flux.safetensors"
+        file_path.write_bytes(b"content")
+
+        specs: list[SeedAssetSpec] = [
+            {
+                "abs_path": str(file_path),
+                "size_bytes": 7,
+                "mtime_ns": 1234567890000000000,
+                "info_name": "flux",
+                # Shape emitted by get_name_and_tags_from_asset_path for a
+                # nested model path.
+                "tags": ["models", "checkpoints/flux"],
+                "fname": "flux.safetensors",
+                "metadata": None,
+                "hash": None,
+                "mime_type": "application/safetensors",
+            }
+        ]
+
+        result = batch_insert_seed_assets(session, specs=specs, owner_id="")
+
+        assert result.inserted_refs == 1
+        ref = session.query(AssetReference).filter_by(name="flux").one()
+        stored = [
+            row.tag_name
+            for row in session.query(AssetReferenceTag)
+            .filter_by(asset_reference_id=ref.id)
+            .order_by(AssetReferenceTag.added_at.asc())
+            .all()
+        ]
+        assert stored == ["models", "checkpoints/flux", "checkpoints"]
+
+    def test_flat_path_remains_two_tags(
+        self, session: Session, temp_dir: Path
+    ):
+        file_path = temp_dir / "vanilla.safetensors"
+        file_path.write_bytes(b"content")
+
+        specs: list[SeedAssetSpec] = [
+            {
+                "abs_path": str(file_path),
+                "size_bytes": 7,
+                "mtime_ns": 1234567890000000000,
+                "info_name": "vanilla",
+                "tags": ["models", "checkpoints"],
+                "fname": "vanilla.safetensors",
+                "metadata": None,
+                "hash": None,
+                "mime_type": "application/safetensors",
+            }
+        ]
+
+        batch_insert_seed_assets(session, specs=specs, owner_id="")
+
+        ref = session.query(AssetReference).filter_by(name="vanilla").one()
+        stored = {
+            row.tag_name
+            for row in session.query(AssetReferenceTag)
+            .filter_by(asset_reference_id=ref.id)
+            .all()
+        }
+        # Dedupe means flat layouts don't pick up a redundant `checkpoints`
+        # row — tag[1] already serves both positional and set-membership.
+        assert stored == {"models", "checkpoints"}
+
+
 class TestMetadataExtraction:
     def test_extracts_mime_type_for_model_files(self, temp_dir: Path):
         """Verify metadata extraction returns correct mime_type for model files."""

tests-unit/assets_test/services/test_path_utils.py

@@ -6,7 +6,11 @@ from unittest.mock import patch
 
 import pytest
 
-from app.assets.services.path_utils import get_asset_category_and_relative_path
+from app.assets.services.path_utils import (
+    get_asset_category_and_relative_path,
+    get_name_and_tags_from_asset_path,
+    resolve_destination_from_tags,
+)
 
 
 @pytest.fixture
@@ -38,6 +42,50 @@ def fake_dirs():
                 }
 
 
+@pytest.fixture
+def fake_dirs_multi_bucket():
+    """Variant fixture with multiple model buckets (checkpoints + diffusers + loras)."""
+    with tempfile.TemporaryDirectory() as root:
+        root_path = Path(root)
+        input_dir = root_path / "input"
+        output_dir = root_path / "output"
+        temp_dir = root_path / "temp"
+        checkpoints_dir = root_path / "models" / "checkpoints"
+        diffusers_dir = root_path / "models" / "diffusers"
+        loras_dir = root_path / "models" / "loras"
+        for d in (
+            input_dir,
+            output_dir,
+            temp_dir,
+            checkpoints_dir,
+            diffusers_dir,
+            loras_dir,
+        ):
+            d.mkdir(parents=True)
+
+        with patch("app.assets.services.path_utils.folder_paths") as mock_fp:
+            mock_fp.get_input_directory.return_value = str(input_dir)
+            mock_fp.get_output_directory.return_value = str(output_dir)
+            mock_fp.get_temp_directory.return_value = str(temp_dir)
+
+            with patch(
+                "app.assets.services.path_utils.get_comfy_models_folders",
+                return_value=[
+                    ("checkpoints", [str(checkpoints_dir)]),
+                    ("diffusers", [str(diffusers_dir)]),
+                    ("loras", [str(loras_dir)]),
+                ],
+            ):
+                yield {
+                    "input": input_dir,
+                    "output": output_dir,
+                    "temp": temp_dir,
+                    "checkpoints": checkpoints_dir,
+                    "diffusers": diffusers_dir,
+                    "loras": loras_dir,
+                }
+
+
 class TestGetAssetCategoryAndRelativePath:
     def test_input_file(self, fake_dirs):
         f = fake_dirs["input"] / "photo.png"
@@ -79,3 +127,161 @@ class TestGetAssetCategoryAndRelativePath:
     def test_unknown_path_raises(self, fake_dirs):
         with pytest.raises(ValueError, match="not within"):
             get_asset_category_and_relative_path("/some/random/path.png")
+
+
+class TestGetNameAndTagsFromAssetPath:
+    """tags collapse the parent subpath into a single slash-joined tag.
+
+    Consumers should be able to read ``tags[1]`` as a stable category
+    identifier regardless of how deep the file lives in the bucket.
+    """
+
+    def test_flat_input(self, fake_dirs_multi_bucket):
+        f = fake_dirs_multi_bucket["input"] / "photo.png"
+        f.touch()
+        name, tags = get_name_and_tags_from_asset_path(str(f))
+        assert name == "photo.png"
+        assert tags == ["input"]
+
+    def test_flat_output(self, fake_dirs_multi_bucket):
+        f = fake_dirs_multi_bucket["output"] / "result_00001.png"
+        f.touch()
+        name, tags = get_name_and_tags_from_asset_path(str(f))
+        assert name == "result_00001.png"
+        assert tags == ["output"]
+
+    def test_flat_models_checkpoint(self, fake_dirs_multi_bucket):
+        f = fake_dirs_multi_bucket["checkpoints"] / "flux.safetensors"
+        f.touch()
+        name, tags = get_name_and_tags_from_asset_path(str(f))
+        assert name == "flux.safetensors"
+        assert tags == ["models", "checkpoints"]
+
+    def test_diffusers_nested_subpath_slash_joined(self, fake_dirs_multi_bucket):
+        """Diffusers components live in nested directories — the full subpath
+        must collapse into one tag so consumers can look up the model category
+        via tags[1] regardless of nesting depth.
+
+        The subpath is lowercased to match the canonicalization
+        :func:`ensure_tags_exist` applies on the write side; without that,
+        the asset_reference_tags.tag_name FK to tags.name would fail for
+        any path containing uppercase letters.
+        """
+        nested = (
+            fake_dirs_multi_bucket["diffusers"]
+            / "Kolors"
+            / "text_encoder"
+        )
+        nested.mkdir(parents=True)
+        f = nested / "model.safetensors"
+        f.touch()
+        name, tags = get_name_and_tags_from_asset_path(str(f))
+        assert name == "model.safetensors"
+        assert tags == ["models", "diffusers/kolors/text_encoder"]
+
+    def test_deep_lora_user_subpath_slash_joined(self, fake_dirs_multi_bucket):
+        """User-created subdirectories under a model bucket also collapse to a
+        single tag rather than one tag per directory."""
+        nested = (
+            fake_dirs_multi_bucket["loras"]
+            / "my"
+            / "custom"
+            / "path"
+        )
+        nested.mkdir(parents=True)
+        f = nested / "v0001.safetensors"
+        f.touch()
+        name, tags = get_name_and_tags_from_asset_path(str(f))
+        assert name == "v0001.safetensors"
+        assert tags == ["models", "loras/my/custom/path"]
+
+
+class TestResolveDestinationFromTags:
+    """resolve_destination_from_tags must accept both the legacy
+    one-tag-per-directory shape and the new slash-joined shape so that an
+    upload using the tags it just read back from /api/assets round-trips
+    to the right on-disk destination.
+    """
+
+    @pytest.fixture
+    def resolve_dirs(self):
+        with tempfile.TemporaryDirectory() as root:
+            root_path = Path(root)
+            input_dir = root_path / "input"
+            output_dir = root_path / "output"
+            checkpoints_dir = root_path / "models" / "checkpoints"
+            diffusers_dir = root_path / "models" / "diffusers"
+            loras_dir = root_path / "models" / "loras"
+            for d in (input_dir, output_dir, checkpoints_dir, diffusers_dir, loras_dir):
+                d.mkdir(parents=True)
+            with patch("app.assets.services.path_utils.folder_paths") as mock_fp:
+                mock_fp.get_input_directory.return_value = str(input_dir)
+                mock_fp.get_output_directory.return_value = str(output_dir)
+                mock_fp.folder_names_and_paths = {
+                    "checkpoints": ([str(checkpoints_dir)], None),
+                    "diffusers": ([str(diffusers_dir)], None),
+                    "loras": ([str(loras_dir)], None),
+                }
+                yield {
+                    "input": input_dir,
+                    "output": output_dir,
+                    "checkpoints": checkpoints_dir,
+                    "diffusers": diffusers_dir,
+                    "loras": loras_dir,
+                }
+
+    def test_models_flat_category(self, resolve_dirs):
+        base, subdirs = resolve_destination_from_tags(["models", "checkpoints"])
+        assert base == str(resolve_dirs["checkpoints"])
+        assert subdirs == []
+
+    def test_models_slash_joined_new_shape(self, resolve_dirs):
+        # The shape get_name_and_tags_from_asset_path now emits.
+        base, subdirs = resolve_destination_from_tags(
+            ["models", "diffusers/kolors/text_encoder"]
+        )
+        assert base == str(resolve_dirs["diffusers"])
+        assert subdirs == ["kolors", "text_encoder"]
+
+    def test_models_legacy_one_tag_per_dir(self, resolve_dirs):
+        # The legacy shape must still resolve identically.
+        base, subdirs = resolve_destination_from_tags(
+            ["models", "diffusers", "kolors", "text_encoder"]
+        )
+        assert base == str(resolve_dirs["diffusers"])
+        assert subdirs == ["kolors", "text_encoder"]
+
+    def test_models_loras_slash_joined(self, resolve_dirs):
+        base, subdirs = resolve_destination_from_tags(
+            ["models", "loras/my/custom/path"]
+        )
+        assert base == str(resolve_dirs["loras"])
+        assert subdirs == ["my", "custom", "path"]
+
+    def test_input_no_subdir(self, resolve_dirs):
+        base, subdirs = resolve_destination_from_tags(["input"])
+        assert base == str(resolve_dirs["input"])
+        assert subdirs == []
+
+    def test_input_slash_joined_subdir(self, resolve_dirs):
+        base, subdirs = resolve_destination_from_tags(["input", "portraits/2026"])
+        assert base == str(resolve_dirs["input"])
+        assert subdirs == ["portraits", "2026"]
+
+    def test_output_slash_joined_subdir(self, resolve_dirs):
+        base, subdirs = resolve_destination_from_tags(["output", "runs/abc"])
+        assert base == str(resolve_dirs["output"])
+        assert subdirs == ["runs", "abc"]
+
+    def test_unknown_category_rejected(self, resolve_dirs):
+        with pytest.raises(ValueError, match="unknown model category"):
+            resolve_destination_from_tags(["models", "not_a_real_category"])
+
+    def test_unknown_category_via_slash_joined(self, resolve_dirs):
+        # First segment of a slash-joined tag must still match a registered category.
+        with pytest.raises(ValueError, match="unknown model category 'bogus'"):
+            resolve_destination_from_tags(["models", "bogus/sub/path"])
+
+    def test_traversal_in_subdir_rejected(self, resolve_dirs):
+        with pytest.raises(ValueError, match="invalid path component"):
+            resolve_destination_from_tags(["models", "checkpoints/..", "evil"])

tests-unit/assets_test/test_assets_missing_sync.py

@@ -32,7 +32,7 @@ def test_seed_asset_removed_when_file_is_deleted(
     # Verify it is visible via API and carries no hash (seed)
     r1 = http.get(
         api_base + "/api/assets",
-        params={"include_tags": "unit-tests,syncseed", "name_contains": name},
+        params={"include_tags": "unit-tests/syncseed", "name_contains": name},
         timeout=120,
     )
     body1 = r1.json()
@@ -52,7 +52,7 @@ def test_seed_asset_removed_when_file_is_deleted(
     # It should disappear (AssetInfo and seed Asset gone)
     r2 = http.get(
         api_base + "/api/assets",
-        params={"include_tags": "unit-tests,syncseed", "name_contains": name},
+        params={"include_tags": "unit-tests/syncseed", "name_contains": name},
         timeout=120,
     )
     body2 = r2.json()
@@ -332,7 +332,7 @@ def test_fastpass_removes_stale_state_row_no_missing(
 
     rl = http.get(
         api_base + "/api/assets",
-        params={"include_tags": f"unit-tests,{scope}"},
+        params={"include_tags": f"unit-tests/{scope}"},
         timeout=120,
     )
     bl = rl.json()

tests-unit/assets_test/test_crud.py

@@ -280,9 +280,15 @@ def test_metadata_filename_is_set_for_seed_asset_without_hash(
 
     trigger_sync_seed_assets(http, api_base)
 
+    # Scanner emits tags as ``[root, "<dir1>/<dir2>/..."]`` — the second tag
+    # is the slash-joined parent subpath. For ``<root>/unit-tests/<scope>/a/b/<name>``
+    # the second tag is ``"unit-tests/<scope>/a/b"``.
     r1 = http.get(
         api_base + "/api/assets",
-        params={"include_tags": f"unit-tests,{scope}", "name_contains": name},
+        params={
+            "include_tags": f"unit-tests/{scope}/a/b",
+            "name_contains": name,
+        },
         timeout=120,
     )
     body = r1.json()

tests-unit/assets_test/test_helpers.py

@@ -0,0 +1,69 @@
+"""Unit tests for app.assets.helpers."""
+
+from app.assets.helpers import expand_bucket_prefixes
+
+
+class TestExpandBucketPrefixes:
+    def test_flat_category_unchanged(self):
+        # `checkpoints` is already a standalone token, no expansion needed.
+        assert expand_bucket_prefixes(["models", "checkpoints"]) == [
+            "models",
+            "checkpoints",
+        ]
+
+    def test_nested_category_inserts_bucket(self):
+        # Path-derived shape for `models/checkpoints/flux/foo.safetensors` —
+        # the standalone bucket has to be present so the FE set-membership
+        # filter (`include_tags=models,checkpoints`) matches the asset.
+        assert expand_bucket_prefixes(["models", "checkpoints/flux"]) == [
+            "models",
+            "checkpoints/flux",
+            "checkpoints",
+        ]
+
+    def test_deeply_nested_only_first_segment_expands(self):
+        # Only the FIRST slash segment ever gets emitted as a standalone —
+        # intermediate path segments don't have routing significance.
+        assert expand_bucket_prefixes(
+            ["models", "diffusers/kolors/text_encoder"]
+        ) == ["models", "diffusers/kolors/text_encoder", "diffusers"]
+
+    def test_unknown_prefix_does_not_expand(self):
+        # Free-form user labels with slashes whose first segment is not a
+        # registered bucket pass through opaquely.
+        assert expand_bucket_prefixes(["models", "my-org/team-a"]) == [
+            "models",
+            "my-org/team-a",
+        ]
+
+    def test_idempotent(self):
+        # Re-applying the helper is a no-op once the bucket is in the set.
+        expanded = expand_bucket_prefixes(["models", "checkpoints/flux"])
+        assert expand_bucket_prefixes(expanded) == expanded
+
+    def test_does_not_duplicate_existing_bucket(self):
+        # If the caller already supplied the standalone bucket, don't add a
+        # second copy.
+        assert expand_bucket_prefixes(
+            ["models", "checkpoints/flux", "checkpoints"]
+        ) == ["models", "checkpoints/flux", "checkpoints"]
+
+    def test_preserves_caller_order(self):
+        # User tags after path tags must stay after; the inserted bucket
+        # token slots in immediately after its slash-joined parent so the
+        # microsecond stagger lands it at path-tier before user-tier.
+        assert expand_bucket_prefixes(
+            ["models", "loras/style", "favorite", "v2"]
+        ) == ["models", "loras/style", "loras", "favorite", "v2"]
+
+    def test_empty_input(self):
+        assert expand_bucket_prefixes([]) == []
+
+    def test_input_root_with_subpath_no_expansion(self):
+        # `portraits` isn't a registered model category, so the input
+        # subpath stays opaque (FE filter doesn't have a checkpoint-loader
+        # analogue for input subfolders).
+        assert expand_bucket_prefixes(["input", "portraits/2026"]) == [
+            "input",
+            "portraits/2026",
+        ]

tests-unit/assets_test/test_prune_orphaned_assets.py

@@ -29,7 +29,10 @@ def create_seed_file(comfy_tmp_base_dir: Path):
 def find_asset(http: requests.Session, api_base: str):
     """Query API for assets matching scope and optional name."""
     def _find(scope: str, name: str | None = None) -> list[dict]:
-        params = {"include_tags": f"unit-tests,{scope}"}
+        # Scanner now emits tags as ``[root, "<dir1>/<dir2>/..."]`` rather than
+        # one tag per directory. For files at ``<root>/unit-tests/<scope>/...``
+        # the second tag is exactly ``"unit-tests/<scope>"``.
+        params = {"include_tags": f"unit-tests/{scope}"}
         if name:
             params["name_contains"] = name
         r = http.get(f"{api_base}/api/assets", params=params, timeout=120)
@@ -138,4 +141,7 @@ def test_special_chars_in_path_escaped_correctly(
     trigger_sync_seed_assets(http, api_base)
     trigger_sync_seed_assets(http, api_base)
 
-    assert find_asset(scope.split("/")[0], fp.name), "Asset with special chars should survive"
+    # Scanner emits the full parent subpath as a single slash-joined tag, so
+    # the lookup tag is ``unit-tests/<scope>`` even when <scope> itself
+    # contains a slash (parent + special-char dirname).
+    assert find_asset(scope, fp.name), "Asset with special chars should survive"

tests-unit/assets_test/test_user_tag_http_smoke.py

@@ -0,0 +1,135 @@
+"""HTTP-layer smoke test: user-added tags via POST /api/assets/{id}/tags
+land after path tags when read back via GET /api/assets.
+
+Exercises the full route handler -> service -> query path that the unit
+tests at tests-unit/assets_test/queries/test_asset_info.py only cover at
+the service layer.
+"""
+import json
+
+import pytest
+import requests
+
+
+@pytest.fixture
+def smoke_asset(http: requests.Session, api_base: str):
+    """Upload a single asset into models/checkpoints/unit-tests/smoke
+    and delete it on teardown."""
+    name = "smoke_user_tag.safetensors"
+    tags = ["models", "checkpoints", "unit-tests", "smoke"]
+    files = {"file": (name, b"S" * 4096, "application/octet-stream")}
+    form_data = {
+        "tags": json.dumps(tags),
+        "name": name,
+        "user_metadata": json.dumps({}),
+    }
+    r = http.post(api_base + "/api/assets", files=files, data=form_data, timeout=120)
+    assert r.status_code == 201, r.text
+    body = r.json()
+    yield body
+    http.delete(
+        f"{api_base}/api/assets/{body['id']}?delete_content=true", timeout=30
+    )
+
+
+def _fetch_asset_tags(http, api_base, ref_id):
+    r = http.get(f"{api_base}/api/assets/{ref_id}", timeout=30)
+    assert r.status_code == 200, r.text
+    return r.json()["tags"]
+
+
+def test_user_tag_lands_after_path_tags_via_http(
+    http: requests.Session, api_base: str, smoke_asset: dict
+):
+    ref_id = smoke_asset["id"]
+
+    initial_tags = _fetch_asset_tags(http, api_base, ref_id)
+    # Path tags should already be at the front in upload order.
+    assert initial_tags[:2] == ["models", "checkpoints"]
+
+    # Add a user tag that would jump to position 0 under alphabetical sort.
+    r = http.post(
+        f"{api_base}/api/assets/{ref_id}/tags",
+        json={"tags": ["aaa-user-tag"]},
+        timeout=30,
+    )
+    assert r.status_code in (200, 201), r.text
+
+    tags_after = _fetch_asset_tags(http, api_base, ref_id)
+    # Path tags must still be at the front; user tag goes to the end.
+    assert tags_after[0] == "models"
+    assert tags_after[1] == "checkpoints"
+    assert "aaa-user-tag" in tags_after
+    assert tags_after[-1] == "aaa-user-tag"
+
+
+def test_user_tag_batch_lands_after_path_tags_via_http(
+    http: requests.Session, api_base: str, smoke_asset: dict
+):
+    ref_id = smoke_asset["id"]
+
+    # Add three user tags in a single request, in non-alphabetical input
+    # order. They should all land after the path tags (microsecond stagger
+    # in set_reference_tags / add_tags_to_reference is what makes this
+    # work — without it, "aaa" would jump to position 0).
+    r = http.post(
+        f"{api_base}/api/assets/{ref_id}/tags",
+        json={"tags": ["zzz-z", "favorite", "aaa-experiment"]},
+        timeout=30,
+    )
+    assert r.status_code in (200, 201), r.text
+
+    tags_after = _fetch_asset_tags(http, api_base, ref_id)
+    assert tags_after[0] == "models"
+    assert tags_after[1] == "checkpoints"
+    user_tail = tags_after[len({"models", "checkpoints", "unit-tests", "smoke"}):]
+    assert set(user_tail) >= {"zzz-z", "favorite", "aaa-experiment"}
+    # Critically: alphabetical sort would put 'aaa-experiment' at position 0.
+    assert tags_after.index("aaa-experiment") > tags_after.index("models")
+    assert tags_after.index("aaa-experiment") > tags_after.index("checkpoints")
+
+
+@pytest.fixture
+def nested_checkpoint_asset(http: requests.Session, api_base: str):
+    """Upload a checkpoint at the slash-joined path shape cloud emits
+    (`models/checkpoints/flux/...`), then delete it on teardown.
+    """
+    name = "nested_checkpoint.safetensors"
+    tags = ["models", "checkpoints/flux"]
+    files = {"file": (name, b"S" * 4096, "application/octet-stream")}
+    form_data = {
+        "tags": json.dumps(tags),
+        "name": name,
+        "user_metadata": json.dumps({}),
+    }
+    r = http.post(api_base + "/api/assets", files=files, data=form_data, timeout=120)
+    assert r.status_code == 201, r.text
+    body = r.json()
+    yield body
+    http.delete(
+        f"{api_base}/api/assets/{body['id']}?delete_content=true", timeout=30
+    )
+
+
+def test_nested_checkpoint_satisfies_fe_set_filter(
+    http: requests.Session, api_base: str, nested_checkpoint_asset: dict
+):
+    """The case Simon flagged: a nested-path checkpoint must still match
+    `include_tags=models,checkpoints` — the FE combo-widget filter.
+    """
+    ref_id = nested_checkpoint_asset["id"]
+
+    stored = _fetch_asset_tags(http, api_base, ref_id)
+    # tag[1] keeps cloud's slash-joined positional contract; tag[2] holds
+    # the standalone bucket the FE filter looks for.
+    assert stored[:3] == ["models", "checkpoints/flux", "checkpoints"]
+
+    # The actual FE query — exact set-membership across both tokens.
+    r = http.get(
+        f"{api_base}/api/assets",
+        params=[("include_tags", "models"), ("include_tags", "checkpoints")],
+        timeout=30,
+    )
+    assert r.status_code == 200, r.text
+    returned_ids = {a["id"] for a in r.json()["assets"]}
+    assert ref_id in returned_ids