Stop performing automatic online searches during scanning and matching: HuggingFace/CivitAI lookups are no longer done synchronously for each missing file. Core linker now marks URN entries for async resolution instead of calling CivitAI during scan, avoiding blocking network calls and reducing noise. Server-side /model_linker/search remains the on-demand endpoint; __init__.py adds resolve_urn import and tightens validation for URN requests (require model_id+version_id for URN-only requests). Frontend (web/linker.js) updated to show a loading indicator for URN entries and to fetch CivitAI info asynchronously via a new resolveUrnAsync() routine, then update the UI when results arrive. Also includes minor formatting/import grouping and UI label tweaks.
Bump logging version to 1.4.1 and improve module name detection by adding _find_project_root in log_funcs to locate the repository root (searches for a .git directory) and use its basename when LOG_MODULE_NAME is not set, with a fallback to the previous behavior. Also update the same version string in logger.py. Additionally, comment out two noisy debug log lines in core/scanner.py to reduce verbose output when directories are missing or after scanning.
Refactor AzLogsLogger instance methods (debug/info/warn/error/exception) and the module-level helper functions to call the central logger.log(...) with the appropriate LogLevel, and ensure exception() passes exc_info=True. Also add a standard library logger in core/log_system/log_funcs.py and emit an error if importing the custom logger fails to aid diagnosis.
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.
Enhance model linking with CivitAI integration and UI improvements.
- __init__.py: Expand model path resolution by building filename→path lookup (including no-ext keys) and using folder_paths to map common categories; add a /model_linker/civitai-search POST route that attempts metadata/hash-based lookup (or filename fallback) and returns CivitAI model/version info for the frontend.
- core/sources/civitai.py: Add hashing and metadata handling utilities: _get_sha256_hash, metadata discovery/reading, helpers to extract images/trained-words, get_model_info_by_hash and get_model_info_for_file (which prefers local metadata and otherwise queries CivitAI by hash). Also tidy/normalize existing search/resolve functions and add caching for hash lookups.
- web/linker.js: Add a right-click context menu for model chips with actions (Show Info, Open in CivitAI), implement dialog UI to display model info, and wire calls to the new civitai-search endpoint. Includes positioning/closing behavior and dialog population from returned data.
These changes enable accurate model identification via local metadata or sha256 lookups on CivitAI and provide convenient frontend actions to view model details or open CivitAI pages.
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.
Refactor and harden the Model Linker extension: normalize string quoting/formatting and improve logging and error responses across API routes. Make route registration more robust to missing PromptServer and dependencies. Add/expand download-related features: safer request parsing (including is_urn handling), CivitAI URN support & direct download URL resolution, popular/model-list/HuggingFace/CivitAI search fallbacks, improved header handling for HF/CivitAI, and better category/directory mapping. Improve downloader reliability and UX: folder_paths fallback, pre-initialize download progress entries, smoother speed calculation and CLI logging, cancellation cleanup on Windows, stronger exception handling, and consistent JSON responses from endpoints.
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.
Resolves ValueError: too many values to unpack when folder_paths returns 3-tuples.
- Handles both 2-tuple and 3-tuple formats from folder_paths
- Normalizes extensions to set with proper type handling
- Adds better error handling for unexpected formats
- Credit: @gontz
Dariusz L