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