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 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.
- 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
- Replaced direct usage of Civitai client with a fallback metadata provider across all recipe parsers.
- Updated metadata service to improve initialization and error handling.
- Enhanced download manager to utilize a downloader service for file operations.
- Improved recipe scanner to fetch model information through the new metadata provider.
- Updated utility functions to streamline image downloading and processing.
- Added comprehensive logging and error handling for better debugging and reliability.
- Introduced `get_default_metadata_provider()` for simplified access to the default provider.
- Ensured backward compatibility with existing APIs and workflows.
- Implemented the base class `RecipeMetadataParser` for parsing recipe metadata from user comments.
- Created a factory class `RecipeParserFactory` to instantiate appropriate parser based on user comment content.
- Developed multiple parser classes: `ComfyMetadataParser`, `AutomaticMetadataParser`, `MetaFormatParser`, and `RecipeFormatParser` to handle different metadata formats.
- Introduced constants for generation parameters and valid LoRA types.
- Enhanced error handling and logging throughout the parsing process.
- Added functionality to populate LoRA and checkpoint information from Civitai API responses.
- Structured the output of parsed metadata to include prompts, LoRAs, generation parameters, and model information.