Add a segmented toggle in the Filter Panel to switch between 'Any' (OR)
and 'All' (AND) logic when filtering by multiple include tags.
Changes:
- Backend: Add tag_logic field to FilterCriteria and ModelFilterSet
- Backend: Parse tag_logic parameter in model handlers
- Frontend: Add segmented toggle UI in filter panel header
- Frontend: Add interaction logic and state management for tag logic
- Add translations for all supported languages
- Add comprehensive tests for the new feature
Closes#802
- Use modelVersionId as fallback for all loras in fingerprint calculation (not just deleted)
- Add URL-based duplicate detection using source_path field
- Combine both fingerprint and URL-based duplicate detection in API response
- Fix _download_remote_media return type and unbound variable issue
When a deleted model is checked against the SQLite archive and not found, the `db_checked` flag was set in memory but never saved to disk. This occurred because the save operation was only triggered when `civitai_api_not_found` was True, which is not the case for deleted models (since the CivitAI API is not attempted). As a result, deleted models would be rechecked on every refresh instead of being skipped.
Changes:
- Introduce a `needs_save` flag to track when metadata state is updated
- Save metadata whenever `db_checked` is set to True, regardless of API status
- Ensure `last_checked_at` is set for SQLite-only attempts
- Add regression test to verify the fix
When enable_metadata_archive_db=True, the previous filter logic would
repeatedly try to fetch metadata for models that were already confirmed
to not exist on CivitAI (from_civitai=False, civitai_deleted=True).
The fix adds a skip condition to exclude models that:
1. Are confirmed not from CivitAI (from_civitai=False)
2. Are marked as deleted/not found on CivitAI (civitai_deleted=True)
3. Either have no archive DB enabled, or have already been checked (db_checked=True)
This prevents unnecessary API calls to CivArchive for user-trained models
or models from non-CivitAI sources.
Fixes repeated "Error fetching version of CivArchive model by hash" logs
for models that will never be found on CivitAI/CivArchive.
- Add /api/example-images/check-pending endpoint to quickly check models needing downloads
- Improve DownloadManager.start_download() to return immediately without blocking
- Add _handle_download_task_done callback for proper error handling and progress saving
- Add check_pending_models() method for lightweight pre-download validation
- Update frontend ExampleImagesManager to use new check-pending endpoint
- Add comprehensive tests for new functionality
- Add cache entry validator service for data integrity checks
- Add cache health monitor service for periodic health checks
- Enhance model cache and scanner with validation support
- Update websocket manager for health status broadcasting
- Add initialization banner service for cache health alerts
- Add comprehensive test coverage for new services
- Update translations across all locales
- Refactor sync translation keys script
- Remove backward compatibility code for `model_type` in `ModelScanner._build_cache_entry()`
- Update `CheckpointScanner` to only handle `sub_type` in `adjust_metadata()` and `adjust_cached_entry()`
- Delete deprecated aliases `resolve_civitai_model_type` and `normalize_civitai_model_type` from `model_query.py`
- Update frontend components (`RecipeModal.js`, `ModelCard.js`, etc.) to use `sub_type` instead of `model_type`
- Update API response format to return only `sub_type`, removing `model_type` from service responses
- Revise technical documentation to mark Phase 5 as completed and remove outdated TODO items
All cleanup tasks for the model type refactoring are now complete, ensuring consistent use of `sub_type` across the codebase.
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
- Centralize cache path resolution in new py/utils/cache_paths.py module
- Migrate legacy cache files to organized structure: {settings_dir}/cache/{model|recipe|fts|symlink}/
- Automatically clean up legacy files after successful migration with integrity verification
- Update Config symlink cache to use new path and migrate from old location
- Simplify service classes (PersistentModelCache, PersistentRecipeCache, RecipeFTSIndex, TagFTSIndex) to use centralized migration logic
- Add comprehensive test coverage for cache paths and automatic cleanup
Fixes a critical bug in FTS query building where multi-word searches
with field restrictions incorrectly used OR between all word+field
combinations instead of requiring ALL words to match within at least
one field.
Example: searching "cute cat" in {title, tags} previously produced:
title:cute* OR title:cat* OR tags:cute* OR tags:cat*
Which matched recipes with ANY word in ANY field.
Now produces:
(title:cute* title:cat*) OR (tags:cute* tags:cat*)
Which requires ALL words to match within at least one field.
Also adds fallback to fuzzy search when FTS returns empty results,
improving search reliability.
Co-Authored-By: Claude <noreply@anthropic.com>
Introduce a new RecipeFTSIndex class that provides fast prefix-based search across recipe fields (title, tags, LoRA names/models, prompts) using SQLite's FTS5 extension. The implementation supports sub-100ms search times for large datasets (20k+ recipes) and includes asynchronous indexing, incremental updates, and comprehensive unit tests.
When users paste CivArchive URLs, the system now fetches metadata from
CivArchive API first instead of Civitai. This prevents download failures
when a model has been deleted from Civitai but remains available on
CivArchive with alternative mirrors.
Changes:
- Source-aware metadata fetching: Uses CivArchive API when source='civarchive'
- URL prioritization: Prefers non-Civitai mirrors for CivArchive downloads
- Fallback mechanism: Falls back to default provider if CivArchive fails
Fixes#769
- Add folder_include parameter support in backend API handlers
- Add folder_include to FilterCriteria and implement multi-folder filtering logic
- Update frontend to send all include folders instead of only the first
- Add tests for single/multiple include folders, include with exclude, and non-recursive filtering
- Add blank line after module docstring for better PEP 8 compliance
- Reformat long lines to adhere to 88-character limit using Black-style formatting
- Improve string consistency by using double quotes consistently
- Enhance readability of complex list comprehensions and method calls
- Maintain all existing functionality while improving code structure
- Add `_preprocess_loras_input` method to handle different widget input formats
- Move core randomization logic to `LoraService` for better separation of concerns
- Update `_select_loras` method to use new service-based approach
- Add comprehensive test fixtures for license filtering scenarios
- Include debug print statement for pool config inspection during development
This refactor improves code organization by centralizing business logic in the service layer while maintaining backward compatibility with existing widget inputs.
- Update `is_civitai_api_metadata` to exclude both "archive_db" and "civarchive" sources
- Skip Civitai metadata updates when existing metadata is higher quality than incoming archive data
- Add test to verify API metadata is preserved when CivArchive provides lower-quality data
- Pass `version_info` parameter through download manager to model update service
- Enhance `_create_record` to use version info when creating records for missing versions
- Add `_extract_single_version` helper method for consistent version extraction
- Improve handling of version metadata during library synchronization
- Add GET /api/lm/recipes/roots endpoint to retrieve recipe root directories
- Add POST /api/lm/recipe/move endpoint to move recipes between directories
- Register new endpoints in route definitions
- Implement error handling for both new endpoints with proper status codes
- Enable recipe management operations for better file organization
Removed the forced normalization of path separators to forward slashes in BaseModelService to maintain platform-specific separators. Updated test cases to use os.sep for constructing expected paths, ensuring tests work correctly across different operating systems while preserving native path representations.
- Add `_get_supported_extensions_for_type` method to return allowed extensions per model type
- Rename `_extract_safetensors_from_archive` to `_extract_model_files_from_archive` and extend to filter by allowed extensions
- Update error message to list supported extensions when archive contains no valid files
- Add test for extracting .pt embedding files from zip archives
Add comprehensive local file matching for LoRA entries in recipe metadata:
- Add modelVersionId-based lookup via new _get_lora_from_version_index method
- Extend LoRA entry with additional fields: existsLocally, inLibrary, localPath, thumbnailUrl, size
- Improve local file detection by checking both SHA256 hash and modelVersionId
- Set default thumbnail URL and size values for missing LoRA files
- Add proper typing with Optional imports for better code clarity
This provides more accurate local file status and metadata for LoRA entries in recipes.
- Add MODEL_NAME_PATTERN regex to extract model names from parameters
- Extract model hash from parsed hashes when available in metadata
- Add checkpoint model hash and name extraction from parameters section
- Implement checkpoint resource processing from Civitai metadata
- Improve model information completeness for better recipe tracking
- Refactor metadata detection to handle nested "meta" objects
- Add support for lowercase "lora:" hash keys
- Extract metadata from nested "meta" field when present
- Update tests to verify nested metadata parsing
- Handle case-insensitive LORA hash detection
The changes ensure proper parsing of Civitai image metadata that may be wrapped in nested structures, improving compatibility with different API response formats.
Add _normalize_checkpoint_entry method to handle legacy checkpoint data formats (strings, tuples) by converting them to dictionaries. This prevents errors during enrichment when checkpoint data is not in the expected dictionary format. Invalid checkpoint entries are now removed instead of causing processing failures.
- Update get_paginated_data and get_recipe_by_id methods to use normalization
- Add test cases for legacy string and tuple checkpoint formats
- Ensure backward compatibility with existing checkpoint handling
Add _normalize_checkpoint_entry method to handle legacy and malformed checkpoint data by:
- Converting string entries to structured dict format
- Handling single-element lists/tuples recursively
- Dropping invalid entries with appropriate warnings
- Maintaining backward compatibility while improving data consistency
Add test case to verify string checkpoint conversion works correctly.
- Add token parsing to support include/exclude search terms using "-" prefix
- Implement token-based matching logic for relative path searches
- Improve search result sorting by prioritizing prefix matches and match position
- Add frontend test for multi-token highlighting with exclusion support
- Extract checkpoint entry from multiple metadata locations using helper method
- Sanitize checkpoint metadata by removing transient/local-only fields
- Remove checkpoint duplication from generation parameters to store only at top level
- Update frontend to properly populate checkpoint metadata during import
- Add tests for new checkpoint handling functionality
This ensures consistent checkpoint metadata structure and prevents data duplication across different storage locations.
Add _normalize_preview_url method to ensure preview URLs are properly formatted for browser access. The method handles absolute paths by converting them to static URLs via config.get_preview_static_url, while preserving API paths and other valid URLs. This ensures consistent preview image display across different URL formats.
Update _enrich_lora_entry to apply URL normalization to preview URLs obtained from both hash-based lookups and version entries. Add comprehensive test coverage for absolute path normalization scenarios.
Add _get_lora_from_version_index method to fetch cached LoRA entries by modelVersionId when hash is unavailable. This improves LoRA enrichment by using version index as fallback when hash is missing, ensuring proper library status, file paths, and preview URLs are set even without hash values.
Update test suite to include version_index in stub cache and add test coverage for version-based lookup functionality.
Add support for importing recipes from remote sources by:
- Adding import_remote_recipe endpoint to RecipeHandlerSet
- Injecting downloader_factory and civitai_client_getter dependencies
- Implementing image download and resource parsing logic
- Supporting Civitai resource payloads with checkpoints and LoRAs
- Adding required imports for regex and temporary file handling
This enables users to import recipes directly from external sources like Civitai without manual file downloads.
- Import rewrite_preview_url utility for optimized image URL handling
- Update thumbnail URL processing for both LoRA and checkpoint entries to use rewritten URLs
- Expand checkpoint metadata with modelId, file size, SHA256 hash, and file name
- Improve error handling and data validation for Civitai API responses
- Maintain backward compatibility with existing data structures
- Track when Civitai API returns "Model not found" for default provider
- Use dedicated flag instead of error string comparison for deletion detection
- Ensure archive-sourced models don't get marked as deleted
- Add test coverage for archive source deletion flag behavior
- Fix deletion flag logic to properly handle provider fallback scenarios
