Changelog#

Here you will find a list of changes for each package update related to the Relevance AI Python library.

v2.3.0#

## What’s Changed * Feature/dr refactor by @JackyKoh in https://github.com/RelevanceAI/RelevanceAI/pull/743 * fix cluster filters, standardise insert_metadata, fix decimal on cosine by @JackyKoh in https://github.com/RelevanceAI/RelevanceAI/pull/761 * add label rework by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/768 * add check_vector_fields by @JackyKoh in https://github.com/RelevanceAI/RelevanceAI/pull/760 * Create test_unit_dev.yaml by @joshp-f in https://github.com/RelevanceAI/RelevanceAI/pull/769 * Implement test_list_closest by @ajhwb in https://github.com/RelevanceAI/RelevanceAI/pull/758 * Feature/sdk 340 labelling rework by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/767 * Feature/sdk 382 sentence splitter operator by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/771 * Implemented test_apply by @ajhwb in https://github.com/RelevanceAI/RelevanceAI/pull/773 * fix type error for filters by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/775 * fixed vectorize by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/776 * Improved test_list_closest by @ajhwb in https://github.com/RelevanceAI/RelevanceAI/pull/777 * fi subcluter by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/778 * Feature/DR Naming Convention (Alias to be vector name instead.) by @JackyKoh in https://github.com/RelevanceAI/RelevanceAI/pull/759 * Feature/sdk 390 2 by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/782 * fixed for concatenating vector fields by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/785 * Development readme by @ajhwb in https://github.com/RelevanceAI/RelevanceAI/pull/787 * Added sentence-splitter package by @ajhwb in https://github.com/RelevanceAI/RelevanceAI/pull/788 * Feature/sdk 390 2 by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/783 * Feature/sdk 400 partialclusterops by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/789 * sklearn integration and updating run/transform by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/790 * Feature/sdk 406 fix sentiment ops by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/792

## New Contributors * @joshp-f made their first contribution in https://github.com/RelevanceAI/RelevanceAI/pull/769 * @ajhwb made their first contribution in https://github.com/RelevanceAI/RelevanceAI/pull/758

Full Changelog: https://github.com/RelevanceAI/RelevanceAI/compare/v2.2.0…v2.3.0

v2.2.0#

## What’s Changed * support stuff by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/590 * Feature/fix datasets by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/592 * V2.0.0 by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/576 * V2.0.1 by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/643 * V2.0.2 by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/653 * V2.1.0 by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/664 * V2.1.0 by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/671 * V2.1.1 by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/685 * V2.1.2 by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/701 * V2.1.3 by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/703 * V2.1.4 by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/710 * V2.1.5 by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/721 * V2.1.6 by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/728 * V2.1.8 by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/731 * fix the auth header by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/732 * fix n_clusters by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/735 * fix analyze sentiment by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/736 * Distance Matrix data stored in metatdata by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/738 * Bad Regex for dataset_id by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/693 * changed default algo and n_clusters by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/737 * default allLM-mini distillroberta from sentence transformers by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/739 * rounding cluster report to 3 decimals by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/741 * Smart Typechecking by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/740 * Feature/small refactor by @JackyKoh in https://github.com/RelevanceAI/RelevanceAI/pull/742 * Add clear cache and cache info by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/747 * hotfix/sdk 361 sub clustering breaks for small parent by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/748 * Feature/remove unnecessary service endpoints by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/750 * migrate to after_id in docs by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/752 * Revert “Feature/remove unnecessary service endpoints” by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/754 * Move DocUtils to Main Package by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/753 * Readthedocs Feedback & Update by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/746 * Feature/fix error by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/755 * added request log debugging with env var by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/745 * Feature/update chunksearch guides by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/756 * Add merge cluster endpoint by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/757 * Feature/cluster metadata by @JackyKoh in https://github.com/RelevanceAI/RelevanceAI/pull/744

Full Changelog: https://github.com/RelevanceAI/RelevanceAI/compare/v2.1.8…v2.2.0

v2.1.0#

  • Add summarize_closest_to_center

  • Add guides

  • Add advanced_search tutorial and dataset functionality

  • Add cluster_heatmaps

  • Add advanced_search

  • Re-write of subcluster

  • Refactor of BaseOps

  • Re-write of vectorize and cluster

v2.0.2#

  • Add question answering operation

  • Fix bug in subclustering where filters do not work

v2.0.1#

  • Fix for hybrid_search endpoint to include sum_fields

v2.0.0#

BREAKING CHANGES:

  • auto_cluster -> cluster

  • clusterer.list_closest_to_center() -> clusterer.list_closest()

Features/Updates:

  • Provide a way to turn off logger

  • auto_cluster now supports models

  • Change metadata experience into more intuitive object

  • Add base workflow

  • Add sentiment analysis workflow

  • Add chunking dataset

  • Add smaller dataset export

  • Fix unique cluster IDs

  • Add feature for workflows

  • Add operate function to run on each cluster

  • Add a way to create centroids if they do not exist using the create_centroids function

  • Fix metadata insertion eperience

  • Fix community detection to return clusterops object

  • Move backend of apply and bulk_apply to asynchronous function

  • Add way to list vector fields

  • Add Subclustering

  • Add Sentiment Analysis

  • Complete SDK reference restructure

  • SDK aesthetic overhaul

  • And much more!

Backend:

  • Major folder refactor -> official renaming of ops to workflows in certain areas

  • Backend separation into interfaces

Automated Changes:

## What’s Changed ## What’s Changed * V1.4.1 by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/529 * V1.4.2 by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/531 * V1.4.3 by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/537 * V1.4.3 by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/538 * Added Missing Centroid Endpoints by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/540 * Feature/refactor folders by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/542 * add cachesize max by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/543 * Feature/cleanup by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/544 * standardised the way that _id is created for each document by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/545 * feature/pro-1622-add-dffacets-and-dfaggregate by @ofrighil in https://github.com/RelevanceAI/RelevanceAI/pull/548 * feature/pro-1624-move-certain-files-around by @ofrighil in https://github.com/RelevanceAI/RelevanceAI/pull/547 * move the fitting and predicting to after by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/549 * add fix for testing by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/550 * Feature/pro 1613 better clusters auto clustering 3 by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/551 * Update Metadata Experience by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/554 * feature/pro-1309-migrate-datasets-from-australia-to-us by @ofrighil in https://github.com/RelevanceAI/RelevanceAI/pull/546 * Feature/pro 1626 sentiment analysis by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/555 * Feature/fix community detection by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/557 * Feature/ploty from docs by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/553 * Feature/scaling by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/556 * Feature/pull update push args by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/559 * feature/pro-1507-add-2-series-together-in-pandas by @ofrighil in https://github.com/RelevanceAI/RelevanceAI/pull/539 * [WIP] Feature/add comm detection by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/558 * Feature/add centroid insertion by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/561 * fix common mistake of inputting token as project by @JackyKoh in https://github.com/RelevanceAI/RelevanceAI/pull/564 * add a way to run the function for operating by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/565 * Fix metadata for workflows by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/567 * add recieve dataset by @JackyKoh in https://github.com/RelevanceAI/RelevanceAI/pull/563 * Feature/create workflow diagrams by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/568 * add parameters for migration by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/569 * Fix community detection by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/571 * fix distribution measure plot by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/572 * feature/pro-1666-improving-original-pull-update-push by @ofrighil in https://github.com/RelevanceAI/RelevanceAI/pull/562 * Feature/add references by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/573 * Feature/add references by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/574 * fix the metadata insertion by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/541 * Feature/pro 1698 fix references by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/575 * Feature/cor 722 error shouldnt happen on dev server by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/580 * Feature/move ops to workflows init by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/581 * feature/pro-1647-fix-progress-bar-for-pull_update_push by @ofrighil in https://github.com/RelevanceAI/RelevanceAI/pull/577 * [WIP] Better Code Base for ClusterOps by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/579 * fix community detection UX by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/587 * feature/pro-1723-store-vectorize-metadata-in-sdk by @ofrighil in https://github.com/RelevanceAI/RelevanceAI/pull/588 * feature/pro-1726-fix-centroid-insertion-for-community by @ofrighil in https://github.com/RelevanceAI/RelevanceAI/pull/589 * Hotfix/cloudfront by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/591 * feature/pro-1724-fix-vectorhub-tests by @ofrighil in https://github.com/RelevanceAI/RelevanceAI/pull/593 * feature/pro-1686-clusterops-show by @ofrighil in https://github.com/RelevanceAI/RelevanceAI/pull/583 * add coco by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/596 * SDK Style Guide and Refactor by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/586 * Feature/fix refs by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/597 * Fixing fit predict by @charyeezy in https://github.com/RelevanceAI/RelevanceAI/pull/600 * feature/pro-1742-change-it-so-we-pass-token-instead-of by @ofrighil in https://github.com/RelevanceAI/RelevanceAI/pull/598 * Feature/pro 1750 by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/602 * forward -> operate by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/601 * Fix Tests after SDK refactor by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/603 * Better Clusters | Internal metric evaluation by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/584 * Feature/fix reports by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/604 * add reports init file by @JackyKoh in https://github.com/RelevanceAI/RelevanceAI/pull/599 * feature/pro-1751-fixing-the-sync-progress-bar by @ofrighil in https://github.com/RelevanceAI/RelevanceAI/pull/607 * Feature/fix max chunksize by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/605 * update refs by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/609 * Feature/pro 1782 simple plotting distribution skews by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/610 * remoe unstruc by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/611 * rename vis to viz by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/612 * update makefile by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/613 * add sequential workflows by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/614 * ensure that you are setting labels on doc subset by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/615 * Fix datasets by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/616 * add cluster ops by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/617 * Increase Coverage by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/606 * Fix/config by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/618 * fix aggregates by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/621 * fixed display after clustering by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/619 * Feature/update refs by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/622 * Fix centroid insertion by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/623 * Feature/update the references amazing wow by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/624 * [WIP] Docstrings by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/620 * added iris and palmers penguins by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/626 * Feature/fix cluster references by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/628 * update client ref by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/629 * Guides /docsrc by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/627 * update the subclusterops by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/625 * Feature/pro 1709 fix sentiment analysis workflow by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/632 * BaseOps methods by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/633 * update sentiment by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/634 * fix vectorize by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/635 * fix subclustering by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/636

v1.4.3#

  • Reduced pull_update_push log file output

  • Add delete_documents utility

  • Add deployables functions

  • Check if global datasets already exist

v1.4.2#

  • Rename image to media

v1.4.1#

  • Fix bug with upsert_images

  • Suggest link with dashboard link

v1.4.0#

  • Improve Dataset.community_detection such that it takes vectors as well

  • Add support for image uploads

v1.3.3#

  • Add metadata

v1.3.2#

  • Add verbose verbose argument

  • Fix cluster_keyphrases

v1.3.1#

  • Added pull_update_push_async

  • Introduced asynchronous client

  • Fix bug in facets

v1.3.0#

  • Add support for subclustering

  • Add community detection algorithm Dataset.community_detection

  • Update Dataset.vectorize to ignore already-vectorized fields and modified output to include those vector names

Additional info on PRs:

v1.2.8#

  • Add dimensionality reduction for documents

  • Change maximum chunksize to 500

v1.2.7#

  • Adjust max cache size, from one to eight, of Dataset.to_pandas_dataframe and Series._get_pandas_series

  • Fix dataset analytics

v1.2.6#

  • Add initial bias detection

  • Fix analytics support

  • Remove test tracking

v1.2.5#

  • Add hotfix if pandas functions not supported.

v1.2.4#

  • Add nltk-rake support for keyphrases

  • Add more documentation around cluster reporting

  • Enable Dataset and Series access pandas DataFrame and Series methods, respectively

  • Change Dataset.health from a property to a method and add pandas DataFrame output

  • Change Dataset.vectorize to call pull_update_push just once instead of twice

v1.2.3#

  • Add Cluster Report endpoints

Developer changes:

  • Fix bug with analytics and change to an env variable tracker for outermost function

v1.2.2#

Developer changes:

BREAKING CHANGES

  • All list and dict default arguments are changed to None.

Other Changes - Introduced corr, a method to plot the correlation between two fields, in Dataset - Export to Pandas DataFrame

v1.2.1#

BREAKING CHANGES

  • When upserting, you will no longer be returned confusing inserting/write statements.

Other Changes:

  • Add option to create_id when inserting

Developer changes:

  • Reduced number of documents in testing

  • Make tracking only occur at the uppermost level and not the bottom level

v1.2.0#

BREAKING CHANGES

  • When inserting/writing, you will now no longer be returned confusing insertion/write statements

but if it errors, it will return the JSON object with the necessary details.

  • Add image tooling around processing (currently an alpha feature to be tested)

  • Add vectorize method for text and images

v1.1.5#

v1.1.4#

  • Add grading to auto_clustering

  • Bug fix for cluster report

  • Add DBSCAN centroids

  • Fix HDBSCAN

  • Add support for BIRCH, OPTICS and all native sklearn algorithms

v1.1.2#

  • Added new DR methods to auto_reduce_dimensions

  • Fixed documentation on clustering

v1.1.1#

  • Change data structure of report structure

v1.1.0#

  • Add low-touch way to label with a given model

  • Add label_from_dataset, label_from_list, label_from_common_words

v1.0.8#

  • Fix document-utils for clustering on DR

v1.0.7#

  • Add grading for cluster report

v1.0.6#

  • Fix http client and regionalisation issues and remove need for firebase

v1.0.5#

Breaking changes

  • get_cluster_internal_report has now been renamed to internal_report

Non-breaking changes:

  • Remove repetitive print statements

  • Add outlier support for cluster report

  • Support for centroids and medoids in typing

  • Add pretty printing for cluster overall reporting

v1.0.4#

  • add launch_search_app for dataset functionality

  • remove saving .creds.json to avoid file caching

v1.0.3#

  • Fix print error message with segment

  • Separate out JSON Encoder

v1.0.2#

  • Fix pandas serialization for UTF-encoding errors

  • Move search app

  • Change print search dashboard app URL

  • Fix regionalisation error when authenticating client.

v1.0.1#

  • Make pandas dataframe serializable with vectors

v1.0.0#

  • Clustering report functionality

  • Add fix and test for new cluster aggregate

  • Add document mocking utility

  • Add integration for cluster reporting

  • Fix bug for sklearn clustering

  • Add segment tracking with option to turn off

  • Add print statement after inserting

v0.33.6#

  • Fix warning missing parameter

  • Remove dataset_id from get_documents

  • Fix URL bug if you are logging in from old-australia-east

v0.33.5#

  • Fix UX flow

  • Make US-East-1 the default

  • Add force refresh

  • Rework Login UX

  • Mention region when connecting

  • Make the authentication message super cool

  • Fix centroids to Node endpoint

  • Update the delete request

v0.33.4#

  • Make asynchronous dashboard request

v0.33.3#

  • Fix cluster aggregate

  • Fix for login

  • Make adding firebase UID not breaking

v0.33.2#

v0.33.1#

BREAKING CHANGES - :code-block:`predict_dataset` has been corrected to :code-block:`predict_update` - :code-block:`fit_dataset_by_partial` has been corrected to :code-block:`partial_fit_dataset` - :code-block:`fit_partial` instances have been corrected to :code-block:`partial_fit`

  • Hotfix auto_cluster when having more clusters than batch size

  • Add dashboard link after clustering

  • Fix references when listing closest and furthest

v0.33.0#

The most important part of this change is adding more modularity to the clustering functions. This is important because previous functions tried to abstract away too much. Now, users

BREAKING CHANGES

  • Clustering fit_transform is not a fit_predict to align with SKLearn’s methods

  • Rename Clusterer to ClusterOps

  • fit has now been broken down into fit_predict_update

  • Removed KMeansClusterer

Non-breaking changes:

  • Create a CentroidClusterBase and update it to ClusterBase and a CentroidBase

  • Added a fit_update

  • Added support for batch clustering using MiniBatchKMeans

  • Added functional Insert_centroid_documents to the ClusterOps object

  • Introduced fit_partial to the clusterer

  • Introduced fit_partial_documents

  • Introduced fit_dataset_by_partial to allow users to be able to fit on a dataset if they want to use

partial_fit - Introduced fit_update_dataset - Introduced fit_update_dataset_by_partial which will fit the dataset, predict the dataset and insert the centroids if there are expected centroids in the dataset - Introduced fit_partial_predict_update to allow for fitting, predicting and updating the dataset in 1 go - Fixed arguments in the clusterer object to now take an optional vector_fields and dataset - Feature/fix clustering transform by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/372 - add fix for dim reduction by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/374 - removed python manta on startup by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/376 - Feature/add support for batch by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/375 - Hotfix/pull update filter error by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/379 - auto_cluster function by @jtwinrelevanceai in https://github.com/RelevanceAI/RelevanceAI/pull/373 - Feature/try fix cluster references by @boba-and-beer in https://github.com/RelevanceAI/RelevanceAI/pull/380

Full Changelog: https://github.com/RelevanceAI/RelevanceAI/compare/v0.32.0…v0.33.0

v0.32.1#

  • Apply hotfix to pull_update_push

v0.32.0#

BREAKING CHANGES

  • Move search to inside operations to keep consistency

New Features:

  • Added Dimensionality Reduction

  • Added Labelling

Non-breaking changes:

  • Fix bug with clusterer using fit_predict now

Full Changelog: https://github.com/RelevanceAI/RelevanceAI/compare/v0.31.0…v0.32.0

v0.31.0#

  • Include more native sklearn integration. KMeans and MiniBatchKMeans now supported natively.

  • Fix to vectorize and sample in Series

  • Fixes to cluster aggregation for the clusterer class and cluster metrics for the clusterer class

  • groupby and agg now supported

  • Added warnings to vectorize method

  • Bug Fix to list_closest_to_center to now return results

  • Add send_dataset

  • Add clone_dataset

  • Add references to available example datasets

  • Added vector_search, chunk_search , multistep_chunk_search, hybrid_search

as part of the search endpoints

Developer changes:

  • Added warnings module (boba-and-beer)

  • Folder factor for datasets API (boba-and-beer)

  • 2x Test speed up by introducing pytest-xdist with file distribution strategy (boba-and-beer)

Tests are now run modularly. In other words, if you want tests to run together, keep them in the same file. If you want them to run in parallel, keep them in separate files.

v0.30.1#

Non-breaking changes:

  • Fixed incorrect reference in update_documents

  • Fixed bulk getting the wrong document in df.get() and added subsequent unit test

  • Fixed references with apply

  • Added health endpoints

  • Added insert_pandas_dataframe endpoints

  • Test folder refactor and clean up

Developer changes: - Forced precommits - Added minimum pytest coverage

Auto Generated Release Notes:

v0.30.0#

BREAKING CHANGES

  • Renamed all docs references to documents

  • Renamed all cluster_alias references to alias

  • Changed functionality in CentroidClusterBase

  • Renamed chunk_size to chunskize in get_all_documents

  • Renamed retrieve_chunk_size to retrieve_chunksize in df.apply and df.bulk_apply

  • Schema is now a property and not a method!

  • get_centroid_documents now no longer takes a field

  • Removal of any mention of centroid_vector_ as those should now be replaced with the

actual vector field name the centroids are derived from

Non-breaking changes:

  • Added head to Series object

  • Add CentroidClustererbase and CentroidClusterBase classes to inherit from

  • Deprecated KMeansClusterer in documentation and functionality

  • Add fix for clusterer for missing vectors in documents by forcing filters

  • Support for multi-region base URL based on frontend parsing

  • Added AutoAPI to gitignore as we no longer want to measure that

  • Add tighter sklearn integration

  • Add CentroidClusterBase

  • Clean up references around Clusterbase, ClusterOps, Dataset

  • Add reference to Client object

  • Hotfix .sample()

  • Update the Base Ingest URL to gateway and set to appropriate default

  • Added support for base url token

  • Removed QC from references

  • Add integration reference

  • Fixed centroid insertion for Dataset

  • Refactor of tests based

  • Add clustering test around clustering

  • Separation of references to clean up clustering and sidebar menu navigation

  • Fix reference examples

AUTO-GENERATED RELEASE NOTES:

v0.29.1#

v0.29.0#

v0.28.2#

v0.28.1#

v0.28.0#

  • *Breaking Change*️ Change pull_update_push to use dataset ID

  • Added centroid distance evaluation

  • Added JSONShower to df.head() so previewing images is now possible

  • Refactor Pandas Dataset API to use BatchAPIClient

  • Modularise testing infrastructure to use separate datasets

  • Add aggregation, groupby pandas API support

  • Added GroupBy, Series class for Datasets

  • Added datasets.info()

  • Added documentation testing

  • Added df.apply()

  • Added additional functionality for sampling etc.

  • Fixed documentation for Datasets API

  • Add new monitoring health test for chunk data structure

  • Add fix for csv reading for _chunk_ to be parsed as actual Python objects

and not strings

v0.27.0#

  • Fixed datasets.documents.update_where so it runs

  • Added more tests around multivector search

  • Added Pandas-like Dataset Class for interacting with SDK (Alpha)

  • Added datasets.cluster.centroids.list_furthest_from_centers and datasets.cluster.centroids.list_closest_to_centers

  • Folder Refactor

v0.26.6#

  • Fix missing import in plotting since internalising plots

  • Add support for vector labels

  • Remove background axes from plot

v0.26.5#

  • Fix incorrect URL being submitted to frontend

v0.26.4#

  • Fix string parsing issue for endpoints and dashboards

v0.26.3#

  • Cluster labels are now lower case

  • Bug fix on centroids furthest from center

  • Changed error message

  • Fixed Dodgy string parsing

  • Fixed bug with kmeans_cluster 1 liner by supporting getting multiple centers

v0.26.2#

  • Add CSV insertion

  • Make JSON encoder utility class for easier customisation

  • Added smarter parsing of CSV

v0.26.1#

  • Bug fixes

v0.26.0#

  • Added JSON serialization and consequent test updates

  • Bug fix to cluster metrics

  • Minor fix to tests

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