December 4, 2025 #

• Added an endpoint for removing a document from a user's favorites. If using an organization-scoped API key, requests can be made on behalf of a specific by including the userId query parameter (DELETE /api/v1/documents/{documentId}/favorite?userId={membershipId}).

• Added an endpoint for renaming documents. If the optional request body clearExistingDraft parameter is true, any existing draft will also be cleared.

• Added support for defining descriptions for topic groups. When the topic_group_descriptions parameter is set in a model file, group descriptions will display in the topic selector in workbooks.

• Added the ability to have the AI summarize a chat and automatically name it.

• Added two new skills to the AI Query Helper. Blobby can now search database schemas and generate Omni model extensions based on the results. Blobby will prompt for review before promoting its changes to the workbook.

December 3, 2025 #

• Added an endpoint for adding a document to a user's favorites. If using an organization-scoped API key, requests can be made on behalf of a specific by including the userId query parameter (PUT /api/v1/documents/{documentId}/favorite?userId={membershipId}).

• Improved error messages returned by the Run query API when a document is missing a dashboard. Responses will now include a Document with identifier "<identifier>" needs a dashboard to return queries message.

• Renamed the group_by parameter to level_of_detail.

December 2, 2025 #

• Added a View All link to the Favorites page.

• Added support for a few Snowflake and Databricks AI functions, which can be used in Omni as table calculations:

  • AI_SUMMARIZE(text) - Summarize text content

  • AI_COMPLETE(prompt) - Generate text completions (model selected automatically)

  • AI_EXTRACT(text, labels) - Extract structured data from text

  • AI_CLASSIFY(text, categories) - Classify text into categories

  • AI_SENTIMENT(text) - Analyze sentiment of text

  Note: These functions will only display as suggestions when workbooks are based on Snowflake or Databricks databases.