- Added `populate_lora_from_civitai` and `populate_checkpoint_from_civitai` methods to enhance the extraction of model information from Civitai API responses.
- These methods populate LoRA and checkpoint entries with relevant data such as model name, version, thumbnail URL, base model, download URL, and file details.
- Improved error handling and logging for scenarios where models are not found or data retrieval fails.
- Refactored existing code to utilize the new methods, streamlining the process of fetching and updating LoRA and checkpoint metadata.
- Added a new image metadata panel to display generation parameters and prompts for images and videos.
- Implemented styles for the metadata panel in lora-modal.css, ensuring it is responsive and visually integrated.
- Introduced functionality to copy prompts to the clipboard and handle metadata interactions within the modal.
- Updated media rendering logic in LoraModal.js to incorporate metadata display and improve user experience.
- Introduced MetaFormatParser class to parse metadata from images with Lora_N Model hash format.
- Implemented methods to validate metadata structure, extract prompts, negative prompts, and LoRA information.
- Enhanced error handling and logging for metadata parsing failures.
- Updated RecipeParserFactory to include MetaFormatParser for relevant user comments.
- Updated RETURN_TYPES and RETURN_NAMES to include active LoRAs.
- Introduced active_loras list to track active LoRAs and their strengths.
- Formatted active_loras for return as a string in the format <lora:lora_name:strength>.
- Introduced ComfyMetadataParser class to parse metadata from Civitai ComfyUI JSON format.
- Implemented methods to validate metadata structure, extract LoRA and checkpoint information, and retrieve additional model details from Civitai.
- Enhanced error handling and logging for metadata parsing failures.
- Updated RecipeParserFactory to prioritize ComfyMetadataParser for valid JSON inputs.
- Replaced the download function for images from Twitter to Civitai in recipe_routes.py.
- Updated metadata extraction from user comments to a more comprehensive image metadata extraction method in ExifUtils.
- Enhanced the appending of recipe metadata to utilize the new metadata extraction method.
- Added a new utility function to download images from Civitai.
- Removed the custom async_timeout function and replaced it with direct usage of the initialization lock.
- Simplified the cache initialization process by eliminating the dependency on the lora scanner.
- Enhanced error handling during cache initialization to ensure a fallback to an empty cache on failure.
- Updated RecipeModal.js to dynamically handle video and image previews based on the file type.
- Modified recipe-modal.css to ensure proper styling for both images and videos.
- Adjusted recipe_modal.html to accommodate the new media handling structure.
- Added a check to prevent saving if the base model value has not changed.
- Stored the original value during editing to compare with the new selection.
- Updated the saveBaseModel function to accept the original value for comparison.
- Introduced new styles for base model display and editing in lora-modal.css.
- Enhanced LoraModal.js to support editing of the base model with a dropdown selector.
- Implemented save functionality for the updated base model, including UI interactions for editing and saving changes.
- Added functionality to update the hash index by removing entries associated with the specified file path during cache management.
- Ensured that the cache is properly resorted after the removal of raw data items.
- Updated the early access condition checks in RecipeFormatParser, StandardMetadataParser, and A1111MetadataParser to use `get` method for improved readability and safety.
- Ensured consistent handling of early access status across different parser classes.
- Added error handling for early access restrictions in the API routes, returning appropriate status codes and messages.
- Enhanced the Civitai client to log unauthorized access attempts and provide user-friendly error messages.
- Updated the download manager to check for early access requirements and log warnings accordingly.
- Introduced UI elements to indicate early access status for LoRAs, including badges and warning messages in the import manager.
- Improved toast notifications to inform users about early access download failures and provide relevant information.
- Updated LoraFileHandler to utilize the passed event loop for time retrieval instead of the current thread's event loop.
- Changed error logging for extension loading in mappers from error to warning level for better clarity.
- Added new dependencies: piexif, Pillow, and requests to enhance image processing and HTTP request capabilities.
- Ensured consistency between pyproject.toml and requirements.txt by including the same set of dependencies.
- Updated LoraStackerMapper to handle multiple formats for lora_stack input, improving flexibility in processing existing stacks.
- Introduced caching for processed node results in WorkflowParser to optimize performance and prevent redundant processing.
- Added a new method to collect loras from model inputs, enhancing the ability to extract relevant data from the workflow.
- Improved handling of processed nodes to avoid cycles and ensure accurate results during workflow parsing.
- Improved reference handling in NodeMapper to support integer node IDs and added error logging for reference processing failures.
- Updated LoraLoaderMapper and LoraStackerMapper to handle lora_stack as a dictionary, ensuring compatibility with new data formats.
- Refactored trace_model_path utility to perform a depth-first search for LoRA nodes, improving the accuracy of model path tracing.
- Cleaned up unused code in parser.py related to LoRA processing, streamlining the workflow parsing logic.
- Introduced a new WorkflowParser class to streamline workflow parsing and manage node mappers.
- Added functionality to load external mappers dynamically from a specified directory.
- Refactored LoraLoaderMapper and LoraStackerMapper to handle new data formats for loras and trigger words.
- Updated recipe routes to utilize the new WorkflowParser for parsing workflows.
- Made adjustments to the flux_prompt.json to reflect changes in active states and class types.
- Deleted the `__init__.py`, `cli.py`, `extension_manager.py`, `integration_example.py`, `README.md`, `simple_test.py`, `test_parser.py`, `verify_workflow.py`, and `workflow_parser.py` files as they are no longer needed.
- Updated `.gitignore` to exclude new output files and test scripts.
- Cleaned up the node processors directory by removing all processor implementations and their registration logic.
- Introduced a new API route to fetch the Civitai URL for a specified LoRA file.
- Implemented error handling for missing LoRA names and absence of Civitai data.
- Added a "View on Civitai" option in the UI, allowing users to access the Civitai URL directly from the LoRA widget.
- Enhanced user feedback for successful and failed URL retrieval attempts.
- Introduced logging to track unexpected formats in LoRA and trigger word data.
- Refactored LoRA processing to support both old and new kwargs formats in LoraLoader and LoraStacker.
- Enhanced trigger word processing to handle different data formats in TriggerWordToggle.
- Improved code readability and maintainability by extracting common logic into helper methods.
- Updated CSS for the theme toggle component to ensure relative positioning for the container.
- Centered light and dark icons within the theme toggle using absolute positioning and transform properties.
- Added transition effects for opacity to enhance visual feedback during theme changes.
- Added functionality to load settings from localStorage in the SettingsManager, ensuring user preferences are retained across sessions.
- Updated the state management to initialize settings from localStorage, improving user experience.
- Refactored the UpdateService to streamline update notification preferences.
- Improved migration logic in storageHelpers to prevent duplicate migrations and ensure data integrity.
- Removed unnecessary console logs for cleaner output in various modules.
- Introduced a new storageHelpers module to centralize localStorage interactions, improving code maintainability and readability.
- Updated various components and managers to utilize the new storageHelpers functions for setting, getting, and removing items from localStorage.
- Added migration logic to handle localStorage items during application initialization, ensuring compatibility with the new storage structure.
- Enhanced logging during application initialization for better debugging.
- Changed logging from info to debug for parsed workflow in RecipeRoutes to reduce log verbosity.
- Added a refresh button in the recipe controls section of the HTML template to allow users to reload the recipe list easily.
- Updated add_path_mapping method to return a boolean indicating success or failure of mapping addition.
- Enhanced link scanning to only continue if a mapping was successfully added.
- Filtered paths to exclude those already mapped, improving efficiency in path handling.
- Added logging for existing mappings to provide better insights during execution.
- Updated CSS for recipe modal to improve layout and responsiveness, including adjustments to header and badge styles.
- Added tooltip positioning logic to ensure correct display of local-badge tooltips on hover.
- Refactored HTML structure for local status badges to enhance stability and positioning.
- Removed unnecessary console logs from recipe fetching process in JavaScript for cleaner output.
- Removed the logic for fetching and formatting recipes from the cache.
- Updated the response to return an empty list for recipes when no data is present, simplifying the flow.
- Adjusted comments for clarity regarding the new behavior.
- Updated the recipe saving logic to accept a workflow JSON input instead of individual fields like name, tags, and metadata.
- Implemented parsing of the workflow to extract generation parameters and Lora stack, improving the recipe creation process.
- Enhanced error handling for missing workflow data and invalid Lora formats.
- Removed deprecated code related to individual field handling, streamlining the recipe saving functionality.
- Updated the front-end widget to send the workflow JSON directly, simplifying the data preparation process.
- Expanded the prompt.json file with new configurations for KSampler, CheckpointLoaderSimple, and various CLIPTextEncode nodes.
- Introduced additional Lora management features, including a new Lora Stacker and improved trigger word handling.
- Enhanced the loras_widget.js to log the generated prompt when saving recipes directly, aiding in debugging and user feedback.
- Improved overall structure and organization of the prompt configurations for better maintainability.
- Updated the logic in ExifUtils to first identify KSampler nodes and store references to positive and negative prompt nodes.
- Added a helper function to follow these references and extract text content from CLIP Text Encode nodes.
- Implemented a fallback mechanism to extract prompts using traditional methods if references are not available.
- Improved code readability with additional comments and structured handling of node data.
- Introduced a new API endpoint to save recipes directly from the LoRAs widget.
- Implemented logic to handle recipe data, including image processing and metadata extraction.
- Enhanced error handling for missing fields and image retrieval.
- Updated the ExifUtils to extract generation parameters from images for recipe creation.
- Added a direct save option in the widget, improving user experience.
