Rectools

Added
- `CatalogCoverage` metric ([266](https://github.com/MobileTeleSystems/RecTools/pull/266), [#267](https://github.com/MobileTeleSystems/RecTools/pull/267))
- `divide_by_achievable` argument to `NDCG` metric ([266](https://github.com/MobileTeleSystems/RecTools/pull/266))

Changed
- Interactions extra columns are not dropped in `Dataset.filter_interactions` method [267](https://github.com/MobileTeleSystems/RecTools/pull/267)

Added
- `SASRecModel` and `BERT4RecModel` - models based on transformer architecture ([220](https://github.com/MobileTeleSystems/RecTools/pull/220))
- Transfomers extended theory & practice tutorial, advanced training guide and customization guide ([220](https://github.com/MobileTeleSystems/RecTools/pull/220))
- `use_gpu` for PureSVD ([229](https://github.com/MobileTeleSystems/RecTools/pull/229))
- `from_params` method for models and `model_from_params` function ([252](https://github.com/MobileTeleSystems/RecTools/pull/252))
- `TorchRanker` ranker which calculates scores using torch. Supports GPU. [251](https://github.com/MobileTeleSystems/RecTools/pull/251)
- `Ranker` ranker protocol which unify rankers call. [251](https://github.com/MobileTeleSystems/RecTools/pull/251)

Changed

- `ImplicitRanker` `rank` method compatible with `Ranker` protocol. `use_gpu` and `num_threads` params moved from `rank` method to `__init__`. [251](https://github.com/MobileTeleSystems/RecTools/pull/251)

Added
- `ImplicitBPRWrapperModel` model with algorithm description in extended baselines tutorial ([232](https://github.com/MobileTeleSystems/RecTools/pull/232), [#239](https://github.com/MobileTeleSystems/RecTools/pull/239))
- All vector models and `EASEModel` support for enabling ranking on GPU and selecting number of threads for CPU ranking. Added `recommend_n_threads` and `recommend_use_gpu_ranking` parameters to `EASEModel`, `ImplicitALSWrapperModel`, `ImplicitBPRWrapperModel`, `PureSVDModel` and `DSSMModel`. Added `recommend_use_gpu_ranking` to `LightFMWrapperModel`. GPU and CPU ranking may provide different ordering of items with identical scores in recommendation table, so this could change ordering items in recommendations since GPU ranking is now used as a default one. ([218](https://github.com/MobileTeleSystems/RecTools/pull/218))

Added
- `from_config`, `get_config` and `get_params` methods to all models except neural-net-based ([170](https://github.com/MobileTeleSystems/RecTools/pull/170))
- `fit_partial` implementation for `ImplicitALSWrapperModel` and `LightFMWrapperModel` ([203](https://github.com/MobileTeleSystems/RecTools/pull/203), [#210](https://github.com/MobileTeleSystems/RecTools/pull/210), [#223](https://github.com/MobileTeleSystems/RecTools/pull/223))
- `save` and `load` methods to all of the models ([206](https://github.com/MobileTeleSystems/RecTools/pull/206))
- Model configs example ([207](https://github.com/MobileTeleSystems/RecTools/pull/207),[#219](https://github.com/MobileTeleSystems/RecTools/pull/219))
- `use_gpu` argument to `ImplicitRanker.rank` method ([201](https://github.com/MobileTeleSystems/RecTools/pull/201))
- `keep_extra_cols` argument to `Dataset.construct` and `Interactions.from_raw` methods. `include_extra_cols` argument to `Dataset.get_raw_interactions` and `Interactions.to_external` methods ([208](https://github.com/MobileTeleSystems/RecTools/pull/208))
- dtype adjustment to `recommend`, `recommend_to_items` methods of `ModelBase` ([211](https://github.com/MobileTeleSystems/RecTools/pull/211))
- `load_model` function ([213](https://github.com/MobileTeleSystems/RecTools/pull/213))
- `model_from_config` function ([214](https://github.com/MobileTeleSystems/RecTools/pull/214))
- `get_cat_features` method to `SparseFeatures` ([221](https://github.com/MobileTeleSystems/RecTools/pull/221))
- LightFM Python 3.12+ support ([224](https://github.com/MobileTeleSystems/RecTools/pull/224))

Fixed
- Implicit ALS matrix zero assignment size ([228](https://github.com/MobileTeleSystems/RecTools/pull/228))

Removed
- Python 3.8 support ([222](https://github.com/MobileTeleSystems/RecTools/pull/222))

Added
- `Debias` mechanism for classification, ranking and auc metrics. New parameter `is_debiased` to `calc_from_confusion_df`, `calc_per_user_from_confusion_df` methods of classification metrics, `calc_from_fitted`, `calc_per_user_from_fitted` methods of auc and rankning (`MAP`) metrics, `calc_from_merged`, `calc_per_user_from_merged` methods of ranking (`NDCG`, `MRR`) metrics. ([152](https://github.com/MobileTeleSystems/RecTools/pull/152))
- `nbformat >= 4.2.0` dependency to `[visuals]` extra ([169](https://github.com/MobileTeleSystems/RecTools/pull/169))
- `filter_interactions` method of `Dataset` ([177](https://github.com/MobileTeleSystems/RecTools/pull/177))
- `on_unsupported_targets` parameter to `recommend` and `recommend_to_items` model methods ([177](https://github.com/MobileTeleSystems/RecTools/pull/177))
- Use nmslib-metabrainz for Python 3.11 and upper ([180](https://github.com/MobielTeleSystems/RecTools/pull/180))

Fixed
- `display()` method in `MetricsApp` ([169](https://github.com/MobileTeleSystems/RecTools/pull/169))
- `IntraListDiversity` metric computation in `cross_validate` ([177](https://github.com/MobileTeleSystems/RecTools/pull/177))
- Allow warp-kos loss for LightFMWrapperModel ([175](https://github.com/MobileTeleSystems/RecTools/pull/175))

Removed
- [Breaking] `assume_external_ids` parameter in `recommend` and `recommend_to_items` model methods ([177](https://github.com/MobileTeleSystems/RecTools/pull/177))

Added
- Extended Theory&Practice RecSys baselines tutorial ([139](https://github.com/MobileTeleSystems/RecTools/pull/139))
- `MetricsApp` to create plotly scatterplot widgets for metric-to-metric trade-off analysis ([140](https://github.com/MobileTeleSystems/RecTools/pull/140), [#154](https://github.com/MobileTeleSystems/RecTools/pull/154))
- `Intersection` metric ([148](https://github.com/MobileTeleSystems/RecTools/pull/148))
- `PartialAUC` and `PAP` metrics ([149](https://github.com/MobileTeleSystems/RecTools/pull/149))
- New params (`tol`, `maxiter`, `random_state`) to the `PureSVD` model ([130](https://github.com/MobileTeleSystems/RecTools/pull/130))
- Recommendations data quality metrics: `SufficientReco`, `UnrepeatedReco`, `CoveredUsers` ([155](https://github.com/MobileTeleSystems/RecTools/pull/155))
- `r_precision` parameter to `Precision` metric ([155](https://github.com/MobileTeleSystems/RecTools/pull/155))

Fixed
- Used `rectools-lightfm` instead of pure `lightfm` that allowed to install it using `poetry>=1.5.0` ([165](https://github.com/MobileTeleSystems/RecTools/pull/165))
- Added restriction to `pytorch` version for MacOSX + x86_64 that allows to install it on such platforms ([142](https://github.com/MobileTeleSystems/RecTools/pull/142))
- `PopularInCategoryModel` fitting for multiple times, `cross_validate` compatibility, behaviour with empty category interactions ([163](https://github.com/MobileTeleSystems/RecTools/pull/163))