Replace direct uses of the logging module and module-level loggers with the centralized log_system.log_funcs (log_debug/log_info/log_warn/log_error/log_exception) across multiple modules. Updated imports and removed unused logging.getLogger() instances in downloader, scanner, sources (civitai, huggingface, model_list, popular), workflow_analyzer, workflow_updater, and __init__.py. Minor message/text tweaks and import formatting applied; behavior unchanged aside from routing logs through the shared logging helpers.
Introduce a new logging subsystem under core/log_system (logger.py, config.py, log_funcs.py) implementing AzLogs (LogLevel enum, colored console output, optional file rotation) and a lightweight wrapper (log_debug/info/warn/error/exception) with safe fallback when AzLogs is unavailable. Integrate these log functions across many core modules (downloader, linker, matcher, scanner, workflow_analyzer, workflow_updater, sources and related files) and export logger and helper log functions from core.__init__. Replace several direct logging calls in linker with the new log_* helpers and update core.__init__ exports. Also include small code style and robustness tweaks (path/filename normalization, JSON/file handling, minor refactors and formatting fixes) to improve matching and model-list/popular lookups.
Add the "Lora Stacker (LoraManager)" node type to NODE_TYPE_TO_CATEGORY_HINTS and to the list of text-based Lora loader types so the analyzer treats the LoraManager Stacker as a lora loader and applies the same model-info extraction logic.
Add support for the gguf model format across the codebase and improve handling of nested/dict-type widget model references. Changes include:
- Add ".gguf" to model extension lists in core/linker.py, core/scanner.py, core/sources/huggingface.py, and core/workflow_analyzer.py so gguf files are detected and suggested.
- Update HuggingFace search/repo listing to consider gguf files and improve some request/response handling and logging.
- Improve scanner implementation: formatting/PEP8 cleanup, robust extension checks, normalized MODEL_EXTENSIONS set, safer path handling, and clearer logging.
- Add NESTED_MODEL_KEYS and logic in workflow_analyzer to detect model filenames stored inside dict-type widget values (e.g. rgthree Power Lora Loader) and record a nested_key for resolution.
- Propagate nested_key through apply_resolution mapping and update update_model_path to write resolved paths back into nested dict keys when present (instead of only replacing the top-level widget value).
- Update web UI (web/linker.js) regexes to strip/display gguf extensions in model name formatting.
These changes allow gguf models to be discovered, resolved and updated in workflows, and enable support for nodes that store model references inside nested dict fields.
Filter out LoraManager (LoraLoaderV2) entries that already exist locally so they don't appear as missing, and skip matching for those entries. Integrate scanner data to detect local lora files (full_path/exists) in workflow analysis. Add special handling in update_model_path/update_workflow_nodes to update LoraManager lora lists and the formatted lora text widget (widgets_values[2] and [1]) when a new lora is resolved, using mapping fields is_lora_v2 and original_lora_name. Improve convert_to_relative_path and get_base_directory_for_model to prefer folder_paths lookup and preserve exact ComfyUI filename formats. In the web UI, make resolve button IDs unique by including a missingIndex, avoid duplicate listeners, forward is_lora_v2/original_lora_name to the resolve API, and add extra logging for debugging.
Add support for text-based Lora loaders (LoraLoaderV2 / LoraManager) and mark model refs with activity/connection state, plus UI improvements.
- __init__.py: clarify comment and propagate new flags from refs (is_lora_v2, active, connected).
- core/workflow_analyzer.py: reformatting and small style changes; add LoraLoaderV2 and LoraManager node hints; detect node connected/bypassed state; parse text-based Lora widget lists (name/strength/active) and emit model refs with strength, is_lora_v2, active and connected flags; include connected flag for URN and file refs; keep existing URN/file resolution and dedup logic but annotate refs with subgraph/context info.
- web/linker.js: group loaded models into active/inactive per-category, add UI filter buttons (All / Active / Inactive), separate copy buttons for active/inactive/all, update display to indicate active vs inactive models and copy behavior, and add global helper functions for filtering and clipboard operations.
These changes enable accurate detection of LoraV2 loader states and provide a clearer UI for copying model spec strings while preserving existing behavior for standard loaders.
Detect ComfyUI-AIR URNs in workflows, resolve them to expected filenames via the CivitAI API, and prefer those filenames for matching.
Key changes:
- core/workflow_analyzer.py: added URN_REGEX, URN_TYPE_MAP, is_model_filename() now recognizes URNs, and get_node_model_info() emits structured URN info (is_urn, urn fields, category, exists=False).
- core/sources/civitai.py: added resolve_urn(model_id, version_id) with caching, API fetch of model/version and primary file, and result shaping (model_name, version_name, expected_filename, files).
- core/linker.py: import resolve_urn and call it for missing URNs, attach civitai_info/expected_filename, and prefer expected_filename as matching target; cleaned up deduplication logic.
- web/linker.js: UI shows URN original plus resolved CivitAI model/version labels where available.
- TODO.md: added plan/notes for URN detection and next steps.
This improves detection and fuzzy matching for models referenced by URNs so missing model resolution is more accurate. Further matcher and updater enhancements remain TODOs.
Dariusz L