The SaveImage class has been renamed to SaveImageLM to better reflect its purpose within the Lora Manager module. This change ensures consistent naming across import statements, class mappings, and the actual class definition, improving code readability and maintainability.
- Added threading import and optional `_rescan_thread` for background operations
- Simplified `_load_symlink_cache` to only validate path mappings, removing fingerprint checks
- Updated `_initialize_symlink_mappings` to rebuild preview roots and schedule rescan when cache is loaded
- Added `_schedule_symlink_rescan` method to perform background validation of symlinks
- Cleared `_path_mappings` at start of `_scan_symbolic_links` to prevent stale entries
- Background rescan improves performance by deferring symlink validation after cache load
- Add `time` import for performance measurement
- Change debug logs to info level for better visibility of cache operations
- Add detailed logging for cache validation failures and successes
- Include timing metrics for symlink initialization and scanning
- Log cache save/load operations with mapping counts
Updated vi.mock calls in test files to use async importOriginal pattern, ensuring original module exports are preserved while mocking specific functions. This prevents unintended side effects and maintains better test isolation.
- Import `escapeAttribute` and `escapeHtml` utilities from shared utils
- Remove duplicate `escapeAttribute` function from ModelModal.js
- Apply escaping to file path attributes in model modal and trigger words
- Escape folder path HTML content to prevent XSS vulnerabilities
- Ensure safe handling of user-controlled data in UI components
- Add `cardPath` parameter to `show` method in NsfwLevelSelector component
- Include `filePath` from card dataset when calling selector in ModelContextMenuMixin
- Clear `cardPath` from dataset when hiding selector to prevent stale data
This enables the NSFW level selector to access the file path context, which may be needed for backend operations when changing NSFW levels.
Update symlink traversal logic to always record path mappings before checking for visited directories. This prevents valid link->target pairs from being dropped when the target directory has already been visited via another path. Also correct path mapping lookup to properly replace link paths with their actual target paths.
Add a Python script step to verify that the CI environment supports directory symlinks before running tests. This ensures that symlink-dependent tests will not fail due to environment limitations.
Add new POST endpoint `/api/lm/example-images/set-nsfw-level` to allow updating NSFW classification for individual example images. The endpoint supports both regular and custom images, validates required parameters, and updates the corresponding model metadata. This enables users to manually adjust NSFW ratings for better content filtering.
- Simplify and consolidate the logic for processing trigger words and groups
- Remove redundant code paths and improve maintainability
- Ensure consistent behavior between list and string trigger data inputs
- Preserve existing functionality for strength adjustment and group mode
Introduce `relax_csp_for_remote_media` middleware that modifies Content Security Policy headers to permit loading media from trusted external domains (Civitai and Genur). This is necessary for LoRA Manager UI previews when ComfyUI runs with `--disable-api-nodes`, which otherwise blocks remote images and videos. The middleware is inserted after ComfyUI's `block_external_middleware` to properly extend the restrictive CSP header.
- 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 navigation section to locale files for model browsing functionality. Includes labels and tooltips for previous/next model navigation with keyboard shortcuts (←/→ arrows). Translations added for German, English, Spanish, French, Hebrew, Japanese, Korean, and Russian locales to support international users.
- Add update badge to versions tab button when model has updates
- Sync update status between modal and model cards in gallery
- Pass `onUpdateStatusChange` callback to versions tab for real-time updates
- Introduce `updateAvailabilityState` to track update status changes
- Improve user awareness of available model updates across UI components
- Add CSS for modal navigation buttons with hover and disabled states
- Implement keyboard shortcuts (arrow keys) for navigating between models
- Add navigation controls UI to modal header with previous/next buttons
- Store navigation state to enable sequential model browsing
- Clean up event handlers to prevent memory leaks when modal closes
Add support for parsing comma-separated and JSON-style commercial use permission values in both Python backend and JavaScript frontend. Implement helper functions to split aggregated values into individual permissions while preserving original values when no aggregation is detected.
Added comprehensive test coverage for the new parsing functionality to ensure correct handling of various input formats including strings, arrays, and iterable objects with aggregated commercial use values.
Add support for storing checkpoint information in image EXIF metadata. The checkpoint data is simplified and includes fields like model ID, version, name, hash, and base model. This allows for better tracking of AI model checkpoints used in image generation workflows.
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
Add new model constants for Flux.2 D and ZImageTurbo to the BASE_MODELS object,
along with their corresponding abbreviations in BASE_MODEL_ABBREVIATIONS. Also
include these new models in the appropriate categories within BASE_MODEL_CATEGORIES.
This update ensures the application can properly recognize and handle these
newly supported AI models in the system.
Refactor the test HTML structure to properly nest all model metadata elements within the model modal container. This improves test accuracy by matching the actual DOM structure used in the application, ensuring that element selection and event handling work correctly during testing.
Refactor updateModalFilePathReferences function to scope all DOM queries within the modal element. This prevents potential conflicts with other elements on the page that might have the same CSS selectors. Added helper functions scopedQuery and scopedQueryAll to limit element selection to the modal context, improving reliability and preventing unintended side effects.
Update metadata registry to remove cache entries when node metadata becomes empty instead of keeping stale data. This prevents accumulation of unused cache entries and ensures cache only contains valid metadata. Added test case to verify cache behavior when LoRA configurations are removed.
Add additional CivitAI image metadata fields to detection logic including generation parameters (prompt, steps, sampler, etc.) and model information. Also improve LoRA hash detection by checking both main metadata and nested meta objects. This ensures more comprehensive identification of CivitAI image metadata across different response formats.
- 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.
- Implement smarter update matching with base model grouping options
- Add flexible tag filtering with include/exclude functionality
- Display license icons and add license filtering controls
- Improve recipes with zero-LoRA imports and checkpoint references
- Enhance ZIP downloads with automatic model extraction
- Update template workflow with improved guidance
- Include various bug fixes and stability improvements
Only trigger autocomplete for embeddings when the current token starts with "emb:" prefix. This prevents interrupting normal prompt typing while maintaining quick manual access to embeddings suggestions.
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
- Add checkpoint hash parameter parsing to backend routes
- Implement checkpoint hash filtering in frontend API client
- Add click navigation from recipe modal to checkpoints page
- Update checkpoint items to use pointer cursor for better UX
Checkpoint items in recipe modal are now clickable and will navigate to the checkpoints page with appropriate hash filtering applied. This improves user workflow when wanting to view checkpoint details from recipes.
- Add CheckpointScanner dependency to RecipeScanner singleton
- Implement checkpoint enrichment in recipe data processing
- Add _enrich_checkpoint_entry method to enhance checkpoint metadata
- Update recipe formatting to include checkpoint information
- Extend get_instance, __new__, and __init__ methods to support checkpoint scanner
- Add _get_checkpoint_from_version_index method for cache lookup
This enables recipe scanner to handle checkpoint models alongside existing LoRA support, providing complete model metadata for recipes.
- 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 metadata service integration to automatically resolve base model information from checkpoint metadata during recipe import. This replaces the previous approach of relying solely on request parameters and provides more accurate base model information.
- Add _resolve_base_model_from_checkpoint method to fetch base model from metadata provider
- Update recipe import logic to use resolved base model when available
- Add comprehensive tests for base model resolution with fallback behavior
- Remove debug print statement from import parameters
- Import getBaseModelAbbreviation utility function
- Add fallback handling for missing base model values
- Display abbreviated base model names while keeping full name in tooltip
- Maintain "Unknown" label for recipes without base model specification
- Improve user experience by showing cleaner, more readable model identifiers
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.
