Follow-up to the keyword-dump guard. The reported model's tag list is
["lora, character, ... face", "base model"], so skipping the dump left the
"base model" label to be picked as the folder name. That label describes
Civitai's listing rather than the model's content, which makes it as
meaningless as a folder as the blob was.
Add CIVITAI_META_TAGS and is_civitai_meta_tag(), and skip those labels in
the automatic fallback. An explicit priority entry still matches them, so a
user who does want a "base model" folder can configure one.
The reported model now resolves to "Krea 2/no tags" instead of
"Krea 2/base model".
Also correct a comment that listed ".civitai.info" among the files sitting
next to a model. LoRA Manager only reads that sidecar -- other tools write
it -- and writes ".metadata.json" itself.
CivitAI tags are normally short single-concept labels, but some uploaders
pack their entire keyword list into one tag. The model in #1119 carries
"lora, character, rosie, irish, ... face" as a single 181-character tag.
Priority resolution matches aliases by exact equality, so that tag matched
nothing and resolve_priority_tag_for_model fell back to tags[0] -- the blob.
With the default "{base_model}/{first_tag}" template the model was filed
under "Krea 2/<181-character blob>/", and the full path plus the
".civitai.info" sidecar and the preview images next to it ran into the
Windows MAX_PATH limit.
Tags also bypassed sanitization on the way into a path: both
calculate_relative_path_for_model and DownloadManager._calculate_relative_path
sanitized model_name and version_name but interpolated {first_tag} verbatim,
so a tag containing "/" or ":" silently produced nested or illegal folders.
Two changes:
- The fallback skips tags that cannot serve as a folder name.
is_usable_path_tag rejects comma-separated keyword dumps and tags longer
than MAX_PATH_TAG_LENGTH; the resolver returns "" when nothing usable is
left, which callers already render as "no tags". Whole-tag priority
matching is untouched, so existing priority configurations behave the
same.
- sanitize_folder_name gains an optional max_length, and every tag-derived
segment now goes through it. Tags are capped at MAX_PATH_TAG_LENGTH, model
and version names at MAX_FOLDER_NAME_LENGTH, and rendered filename stems at
MAX_FILENAME_STEM_LENGTH.
For the reported model the folder becomes "Krea 2/base model" instead of the
blob, and the full path drops from 235 to 64 characters.
Existing libraries are not migrated up front: a path is only recomputed on
download, on an auto-organize run or when a filename template is applied, and
values already inside the caps are left byte-identical. Models previously
filed under a keyword-dump folder move on the next auto-organize run.
Standalone users previously had to hand-edit settings.json to configure
primary folder_paths. Add a standalone-only Model Paths section to the
settings modal:
- Backend exposes standalone_mode, folder_paths (with template placeholder
values filtered out) and a data-driven folder_path_schema derived from
OTHER_MODEL_FOLDER_SUBTYPES via GET /api/lm/settings
- The new section renders multi-path editors per model type from the
schema, with inline enable_other_models / sub-type controls so other
model types are configured without leaving the tab
- Persistent restart-required cues after a save: nav dot, inline notice
and a global banner (unique id per change so dismissals don't mute
future reminders)
- The missing-model-paths startup banner and the Other Models no-paths
empty state now deep-link into the new section instead of pointing at
settings.json
DEFAULT_ENABLED_OTHER_SUB_TYPES managed vae, upscaler, text_encoder and
clip_vision while controlnet was the sole opt-in type. That split was not
defensible on demand breadth: ControlNet is the broader category by install
base, and clip_vision is the narrower one (IPAdapter/SVD image conditioning,
usually one to three files) whose CivitAI type is retired upstream.
Keep the default set to the dependency-style assets every pipeline needs and
where "which one am I actually using" is the real problem - VAE, upscalers
and text encoders - and treat clip_vision and controlnet symmetrically as
opt-in. The feature is still unreleased, so the change needs no migration.
- Sync all five surfaces holding a default: DEFAULT_ENABLED_OTHER_SUB_TYPES,
DEFAULT_SETTINGS, both DEFAULT_SETTINGS_BASE/createDefaultSettings lists,
updateOtherModelsControls()'s fallback and the Jinja fallback.
- The selection is persisted per user, so only the untouched default moves;
existing default_other_roots entries for a disabled sub_type are preserved.
- Fix the Jinja fallback using `or`, which treated an all-unchecked empty
allow-list as "unset" and re-checked every box on render; `is none` keeps
the empty list empty.
- Document the revised defaults and rationale in the plan.
Tests assert the new default trio, the normalize fallback, that both opt-in
types stay out of the default scan, and the auto-set iteration test now
enables clip_vision explicitly since it exercises the loop, not the default.
get_download_path_template() fell back to "{base_model}/{first_tag}" for any
unconfigured model type, so other-model downloads were silently nested under an
arbitrary CivitAI tag even though the settings UI exposes no template row for
"other" and priority_tags has no "other" entry (making {first_tag} resolve to
tags[0]).
Add DEFAULT_DOWNLOAD_PATH_TEMPLATES with other -> "" so unconfigured and
unknown types resolve to a flat layout under the already sub_type-scoped
default_other_roots; explicit settings.json values still win. Mirror the flat
default in the frontend DEFAULT_PATH_TEMPLATES and stop the download/move
default-path previews from rendering "/undefined" or a dangling slash.
Other Models management is now opt-in: enable_other_models (default false)
plus the enabled_other_sub_types allow-list replace the unreleased additive
enabled_other_folders key.
- config._get_enabled_other_folder_keys() is the single scan gate; a new
refresh_other_roots() rebuilds roots and preview roots on toggle.
- ModelScanner gains a _should_keep_cached_entry() hydration hook and
on_library_changed(reconcile=...) so switching a sub_type off drops its
entries (and hash/autov3 rows) at load time and switching it on rescans.
- OtherScanner filters location-derived entries accordingly.
- Other routes reject every other type while off (or a disabled sub_type) and
expose an "other_disabled" page flag; download routing returns a disabled
marker instead of guessing; the download manager refuses other-type
downloads and default-path routing for switched-off sub_types.
- Doctor / init-status / refresh-all skip the other scanner while off; the
scanner stays registered so staged pending-deletes still merge.
- Tests updated with explicit opt-in fixtures plus new gating coverage.
The SHA256 of an empty byte string (written by repackaging tools into
safetensors metadata, or produced by hashing an empty/unreadable file)
was previously resolved against CivitAI's by-hash API, which can contain
polluted entries for it (e.g. a broken SD 1.5 LoRA whose AutoV3 equals
the placeholder) and falsely attributed the wrong model to a recipe.
Guard all lookup paths for the 10/12/64-char AutoV2/AutoV3/full-SHA256
spellings: CivitaiClient.get_model_by_hash/_fetch_version_by_hash return
not-found without a request, and ModelHashIndex ignores the placeholder
in has_hash/get_path/add_autov3.
The Automatic1111 metadata parser keeps the LoRA item itself when its
hash is the placeholder: it matches by filename locally, or retains the
entry with an empty hash flagged hashInvalid (unresolvable-hash state in
the UI, with reconnect as the remedy) instead of dropping it or resolving
it to a polluted CivitAI entry.
Downloads failed with "No suitable file found in metadata" for models whose
only file uses newer CivitAI file types (e.g. 'Enhancement LoRA' for
Anima/AIR image-editing LoRAs) because the primary-file allowlist only
covered legacy types.
- unify the weights-type allowlist as MODEL_WEIGHT_FILE_TYPES
(py/utils/constants.py) and apply it across download, recipe and
metadata-refresh lookups
- mirror CivitAI's getPrimaryFile() semantics: prefer weights-type primary,
fall back to weights files, then trust CivitAI's primary flag (excluding
non-downloadable artifacts like Config/Archive/Workflow)
- mirror the allowlist in the frontend via shared isModelWeightFile() helper
- add regression tests for the Enhancement LoRA primary-file download,
primary-flag fallback and weights-over-non-weights-primary preference
- Three-state autov3 field (not-checked / checked-unavailable / 12-hex value)
in .metadata.json sidecars, in-memory ModelHashIndex, and SQLite
(models.autov3 column + autov3_index table) with column-presence migration
- Background self-terminating backfill for legacy rows: per-model-type
concurrency guard, executor-offloaded I/O, Civitai-first resolution
(SHA256-matched version file) falling back to the embedded safetensors
header hash
- Civitai-first propagation on metadata refresh, scan, and download paths;
reject the empty-string SHA256 placeholder and strip OneTrainer 0x prefix
- List API hash filters and hash index lookups accept 12-char AutoV3
- Cap safetensors header reads at 64 MiB to prevent crafted-file allocation
- Prevent stale AutoV3 mappings on file replacement while preserving them on
same-file re-registration (lazy-hash completion)
- Prefer file type (UNet/Diffusion Model) over baseModel name when
deciding whether a checkpoint routes to the unet folder
- Add UNet to backend primary file type whitelist
- Add Krea 2 to DIFFUSION_MODEL_BASE_MODELS
- Include UNet/Diffusion Model files in frontend file selection UI
- Use actual file type from CivitAI in download params instead of
hardcoded 'Model'
- Ernie & Anima: auto-fetched via CivitaiBaseModelService from Civitai API
- Ernie Turbo & Nucleus: pre-added as hardcoded constants (not yet in Civitai API)
- Added abbreviations (ERNI, ETRB, NUCL) and category entries across all layers
Implement automatic fetching of base models from Civitai API to keep
data up-to-date without manual updates.
Backend:
- Add CivitaiBaseModelService with 7-day TTL caching
- Add /api/lm/base-models endpoints for fetching and refreshing
- Merge hardcoded and remote models for backward compatibility
- Smart abbreviation generation for unknown models
Frontend:
- Add civitaiBaseModelApi client for API communication
- Dynamic base model loading on app initialization
- Update SettingsManager to use merged model lists
- Add support for 8 new models: Anima, CogVideoX, LTXV 2.3, Mochi,
Pony V7, Wan Video 2.5 T2V/I2V
API Endpoints:
- GET /api/lm/base-models - Get merged models
- POST /api/lm/base-models/refresh - Force refresh
- GET /api/lm/base-models/categories - Get categories
- GET /api/lm/base-models/cache-status - Check cache status
Closes#854
This commit resolves the semantic confusion around the model_type field by
clearly distinguishing between:
- scanner_type: architecture-level (lora/checkpoint/embedding)
- sub_type: business-level subtype (lora/locon/dora/checkpoint/diffusion_model/embedding)
Backend Changes:
- Rename model_type to sub_type in CheckpointMetadata and EmbeddingMetadata
- Add resolve_sub_type() and normalize_sub_type() in model_query.py
- Update checkpoint_scanner to use _resolve_sub_type()
- Update service format_response to include both sub_type and model_type
- Add VALID_*_SUB_TYPES constants with backward compatible aliases
Frontend Changes:
- Add MODEL_SUBTYPE_DISPLAY_NAMES constants
- Keep MODEL_TYPE_DISPLAY_NAMES as backward compatible alias
Testing:
- Add 43 new tests covering sub_type resolution and API response
Documentation:
- Add refactoring todo document to docs/technical/
BREAKING CHANGE: None - full backward compatibility maintained
- Normalize string quotes to double quotes across all constants for consistency
- Add trailing commas in dictionaries and lists to improve diff readability
- Expand DIFFUSION_MODEL_BASE_MODELS with additional Wan Video and Qwen models
- Fix comment spacing in NSFW_LEVELS dictionary
- Maintain all existing functionality while improving code style
CivitAI does not distinguish between checkpoint and diffusion model types -
both are labeled as "checkpoint". For certain base model types like
"ZImageTurbo", all models are actually diffusion models and should be
saved to the unet/diffusion model folder instead of the checkpoint folder.
- Add DIFFUSION_MODEL_BASE_MODELS constant for known diffusion model types
- Add default_unet_root setting with auto-set logic
- Route downloads to unet folder when baseModel matches known diffusion types
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Implemented the WanVideo Lora Select node in Python with input handling for low memory loading and LORA syntax processing.
- Updated the JavaScript side to register the new node and manage its widget interactions.
- Enhanced constants files to include the new node type and its corresponding ID.
- Modified existing Lora Loader and Stacker references to accommodate the new node in various workflows and UI components.
- Added example workflow JSON for the new node to demonstrate its usage.
Will Miao