Applying a filename template to a large library re-did O(library) work for
every renamed file: a full natsort resort plus whole-table SQLite rewrite and
download-history resync after each rename, and a full scan plus resort of the
entire recipe collection per renamed LoRA. On a 20k-model library with 300k
recipes on a HDD this pushed "Apply to Library" into multi-day runs.
- ModelScanner.defer_cache_persist(): bulk loops update the in-memory entry
and indexes only; resort + persist + download-history sync run once at
context exit, forced even on cancellation/error since files are already
renamed on disk. Single-rename callers keep immediate per-call behavior.
- RecipeScanner.build_lora_hash_index(): one-shot hash -> recipes index so
per-file lookups are O(1); update_lora_filename_by_hash gains hash_index /
defer_maintenance params, with a single finalize_bulk_filename_updates()
resort at the end of a bulk session.
- ModelLifecycleService.bulk_rename_session() / BulkRenameContext wire the
deferred path through rename_model (hash index built lazily on first
recipe-touching rename).
- Blocking os.rename sequence offloaded via asyncio.to_thread so one file's
HDD I/O no longer stalls the event loop (no cross-file parallelism).
- Skip logic, per-batch WebSocket progress, cancellation, and result
counters unchanged.
Example videos added through the "Add examples" flow were stored with a
hardcoded 720x1280 entry. The dimension probe next to it only ran for
images (PIL cannot open .mp4/.webm files), so every video entry stayed
portrait regardless of the source. The showcase viewer then sizes its
container straight from that value (--media-aspect in showcase.css), so
landscape clips were letterboxed inside a 9:16 box. CivitAI-sourced
examples were unaffected because their dimensions come from the API.
PIL cannot read video containers, so add a dependency-free reader that
parses the container headers instead: moov/trak/tkhd for ISO base media
(with the sample description as a fallback), Segment/Tracks/Pixel* for
WebM/Matroska, and RIFF/WebP for animated examples saved with a video
extension. The sniffed signature decides which reader runs, so a .mp4
that is really WebM still reports the right size; the extension is only
a fallback. Both readers seek past mdat rather than reading it, so a
large file costs the same as a small one.
Imported entries now record the file's real size and keep the previous
placeholder only when the file cannot be parsed.
Existing libraries keep their wrong entries, so backfill them once via
the existing naming migration: bump CURRENT_NAMING_VERSION to 3 and
repair each model's empty-url entries from the files on disk, then sync
the scanner cache. Only entries with no remote url are touched -- those
have no other source, which makes the rewrite lossless -- and entries
already carrying the right size are left byte-identical, so the pass is
idempotent and a no-op for libraries that never imported a video.
Fix ~790 basedpyright errors across the test suite:
- Type stub subclasses of real production classes with super().__init__()
- Add missing generic type arguments and Dict[str, Any] annotations
- Add None guards before subscript/member access
- Adapt tests to production API changes (removed dead handlers,
PersistentModelCache.get_default, _i18n_filter_added location)
- Add missing mocks for comfy.sd and comfy.utils modules in conftest.py
- Fix i18n translation keys: use .help instead of .description for tooltip keys
- Add model_types parameter to ModelListingHandler to support filtering by model type
- Implement get_model_types endpoint in ModelQueryHandler to retrieve available model types
- Register new /api/lm/{prefix}/model-types route for model type queries
- Extend BaseModelService to handle model type filtering in queries
- Support both model_type and civitai_model_type query parameters for backward compatibility
This enables users to filter models by specific types, improving model discovery and organization capabilities.
Will Miao