March 5, 2024

Release notes



  • Smart select (beta) in Catalog offers three different ways to curate your data within a dataset: random, ordered, and cluster-based. To access this feature, go to Catalog, select a dataset that is larger than 100 data rows, and select "Smart select".
  • Cluster view (beta) in Catalog is a new interface that helps you discover and find similar data rows as well as labeling or model mistakes. See Cluster view for more details.
  • Natural language search and similarity search in Catalog now support video and audio assets.
  • You can now 1) import custom metrics per prediction and 2) filter/sort by prediction-level custom metrics. These added functionalities make it easier to use our model error analysis tools in the Model product. To learn more about prediction-level metrics on model runs, see Filters.
  • You can now invoke Foundry models from within a project to generate pre-labels. In the project overview, you'll see "suggested models" to help you select the best model for generating predictions. This feature is in beta.
  • The new Audit trail feature provides a way for you to view all operations (create, update, and delete) on an annotation. This feature makes monitoring changes to annotations over time easier for auditing purposes.
  • The new enhanced video player (beta) in Catalog offers new capabilities to help you curate, evaluate, and visualize video data. These new capabilities include basic play/pause controls, support for predictions, pre-labels, ground truth (bounding boxes, polylines, and points), and support for comparing model runs.
  • If you export from an image or video labeling project that contains data rows labeled with segmentation masks, you will see a new property in the export file called composite_mask. Composite masks are a grouping of all segmentation masks on a label. To learn more, see Export image annotations.
  • If you export from a model run that contains segmentation mask predictions, you will see a new property in the export file called composite_mask. To learn more, see Export image annotations.
  • You can now have a workflow filter based on consensus average. For example, you can use this filter to send data rows with a consensus score over 80% straight to "Done". To do this, create a new workflow step and select consensus average from the workflow filters.
  • Boost express makes it easier for you to request help labeling data. Once you've set up a project, you can request up to fifteen labelers to work on your data. See our docs on Boost express to learn more.
  • The billing tab in your Workspace settings now has a button that enables you to easily unsubscribe from Foundry.


  • When you select a project in Annotate, you will see a new project overview UI that makes navigating your project easier.
  • We have disabled the ability to download videos from the preview mode for all users.
  • When you are in a project, you will now see a "Start" button with a dropdown menu containing options for labeling, reviewing, and any other tasks you have configured for your project.


  • Google SSO users that have a profile picture on their account can now log in as expected.
  • The issue causing large numbers of data rows to be stuck in the “To Label” task has been fixed.
  • The Enterprise dashboard now displays the correct information for your organization.
  • In the Data row details panel, the row data can no longer be displayed with the security token.


Python SDK

The latest version of our Python SDK is v3.65.0. See our full changelog in Github for more details on what was added recently.

Version 3.65.0 (2024-03-05)


  • Rerelease of 3.64.0

Version 3.64.0 (2024-02-29)


  • Client.get_catalog Add catalog schema class. Catalog exports can now be made without creating a slice first
  • last_activity_at filter added to export_v2, allowing users to specify a datetime window without a slice


  • Review related WebhookDataSource topics


  • Added get_catalog notebook
  • Update custom metrics notebook
  • Update notebooks for video and image annotation import

Version 3.63.0 (2024-02-19)


  • Ability for users to install and use sdk with pydantic v.2. while still maintaining support for pydantic v1.
  • ModelRun export() and export_v2() add model_run_details to support splits


  • Add composite mask notebook

Version 3.62.0 (2024-02-12)


  • Support custom metrics for predictions (all applicable annotation classes)
  • FoundryClient.run_app Add data_row identifier validation for running foundry app
  • Client.get_error_status_code Default to 500 error if a server error is unparseable instead of throwing an exception


  • DataRowMetadata, DataRowMetadataBatchResponse, _UpsertBatchDataRowMetadata Make data_row_id and global_key optional in all schema types


  • ExportTask.__str__ Fix returned type in ExportTask instance representation


  • Project.upsert_review_queue


  • Update notebooks to new export methods
  • Add model slice notebook
  • Added support for annotation import with img bytes
  • Update user prompts for huggingface colab