Use order-insensitive token comparison in calculate_filename_confidence
so variant names with reordered tokens (e.g., int8_convrot vs convrot_int8)
score higher. Replace first-match partial matching in HuggingFace source with
best-match selection based on filename confidence, and surface confidence in
search results.
- Preserve HuggingFace textual model/version IDs in download metadata instead of coercing to integers
- Add convrot as a recognized model variant suffix
- Recognize numeric precision tokens with optional mixed/scaled suffixes (e.g. int8mixed, fp8scaled)
- Report partial batch search failures as informational notifications rather than errors
- Add run_in_background_thread() in __init__.py to unify success/cancel/error
handling for hash calculation and local metadata build progress
- Extract match_model_by_title_generic() in core/matcher.py and use it from
both CivitAI and CivArchive providers to remove duplicated version/file
selection logic
- Enable safetensors header SHA256 extraction by default and report hash source
through progress updates
- Update options_methods.js to match backend progress behavior
- Add tests/test_title_matching_hashing.py covering title matching and hashing
- Minor metadata updates
Replace duplicated filename-to-query logic with a single
\uild_filename_search_queries\ helper in matcher/civarchive/huggingface,
standardize Civitai URL generation in the frontend via \getCivitaiModelUrl\,
unify browser user-agent and response file-size extraction in the downloader
path, and derive workflow node-type category hints from widget categories
rather than maintaining a large static mapping.
Replace global log_* wrapper functions with create_module_logger(__name__)
instances across the codebase, enabling proper module-level logger
namespacing. Simplifies core/log_system/log_funcs.py by removing legacy
_normalize_module_path and cleaning up _normalize_module_name. Bumps
log_system config to 2.0.0 and introduces PROJECT_ALIASES for cleaner
log module prefix stripping.
Add core/type_utils.py with as_dict/as_list helpers, and
core/progress.py with a unified report_progress() callback.
Replace inline duplicated implementations of _json_safe_metadata(),
_as_list(), normalize_filename(), and per-source _report_progress()
with calls to the shared modules across downloader, matcher, resolver,
and all source modules (CivitAI, CivArchive, HuggingFace, LoRA Manager).
Extend filename normalization to include dots as separators.
- Add rapidfuzz as optional dependency with SequenceMatcher fallback
- Use stable path identity (realpath) for deduplication in scanner and resolver
- Prevent duplicate scans and duplicate model entries across symlinks/junctions
- Improve matching performance with RapidFuzz when available
Performance and correctness improvements across model scanning, matching, workflow analysis, and CivitAI URL handling:
- Add short-lived in-memory cache for get_model_files (with force_rescan and invalidate_model_files_cache) to reduce frequent directory scans.
- Pass scanned available_models into workflow analysis to avoid rescanning and build category-indexed lists plus an ordered-candidates cache for faster candidate ordering.
- Improve analyze_and_find_matches to special-case urn:air: URNs (use filename suffix when present) and skip fuzzy matching when appropriate.
- Rewrite find_matches to maintain only the top N results via heapq, cache normalized candidate path/filename values on candidate dicts, and early-exit on max_results<=0 to reduce allocations and CPU.
- Add helper functions in CivitAI source to extract/build stable image page URLs (_extract_civitai_image_id, _build_civitai_image_url) and use them when populating image metadata.
- Propagate available_models into get_node_model_info and analyze_workflow_models so subroutines reuse the same scanned list.
- Guard frontend and backend folder lookups to return early for unknown categories to avoid unnecessary work.
These changes aim to reduce IO/CPU during frequent matching operations and produce more accurate/efficient matching for URNs and local models.
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.
Dariusz L