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DataRobot API resources > API reference documentation > API changelogs > Python client changelog > v3.5 changelog

v3.5 changelog

Reference the changes introduced to v3.5 of DataRobot's Python API client.

Python client v3.5

New features

  • Added support for BYO LLMs using serverless predictions in CustomModelLLMValidation.
  • Added the attribute creation_user_name to LLMBlueprint.
  • Added a new class HostedCustomMetricTemplate for hosted custom metrics templates. Use HostedCustomMetricTemplate.get to retrieve a hosted custom metric template. Use HostedCustomMetricTemplate.list to list hosted custom metric templates.
  • Added Job.create_from_custom_metric_gallery_template to create a job from a custom metric gallery template.
  • Added a new class HostedCustomMetricTemplate for hosted custom metrics.
    • Use HostedCustomMetric.list to list hosted custom metrics.
    • Use HostedCustomMetric.update to update a hosted custom metrics.
    • Use HostedCustomMetric.delete to delete a hosted custom metric.
    • Use HostedCustomMetric.create_from_custom_job to create a hosted custom metric from an existing custom job.
    • Use HostedCustomMetric.create_from_template to create a hosted custom metric from a template.
  • Added a new class datarobot.models.deployment.custom_metrics.HostedCustomMetricBlueprint for hosted custom metric blueprints.
    • Use HostedCustomMetricBlueprint.get to get a hosted custom metric blueprint.
    • Use HostedCustomMetricBlueprint.create to create a hosted custom metric blueprint.
    • Use HostedCustomMetricBlueprint.update to update a hosted custom metric blueprint.
  • Added Job.list_schedules to list job schedules.
  • Added a new class JobSchedule for the registry job schedule.
    • Use JobSchedule.create to create a job schedule.
    • Use JobSchedule.update to update a job schedule.
    • Use JobSchedule.delete to delete a job schedule.
  • Added attribute credential_type to RuntimeParameter.
  • Added Deployment.get_segment_attributes to retrieve segment attributes.
  • Added Deployment.get_segment_values to retrieve segment values.

Enhancements

  • Updated black version to 23.1.0.
  • Removed dependency for the package mock, since it is part of the standard library.
  • Added number_of_clusters parameter to Project.get_model_records to filter models by number of clusters in unsupervised clustering projects.
  • Remove an unsupported NETWORK_EGRESS_POLICY.DR_API_ACCESS value for custom models.
  • Implemented support for dr-connector-v1 to DataStore and DataSource.
  • Added a new parameter name to DataStore.list for searching data stores by name.
  • Added a new parameter entity_type to the compute and create methods of the classes ShapMatrix, ShapImpact, ShapPreview. Insights can be computed for custom models if the parameter entity_type="customModel" is passed.

Documentation changes

  • Added usage of external_llm_context_size in llm_settings in genai_example.rst.
  • Updated doc string for llm_settings to include attribute external_llm_context_size for external LLMs.
  • Updated genai_example.rst to link to DataRobot doc pages for external vector database and external LLM deployment creation.

Experimental changes

  • Added experimental api support for Data Wrangling. See Recipe.
  • Use Recipe.from_data_store to create a Recipe from data store.
  • Use Recipe.retrieve_preview to get a sample of the data after recipe is applied.
  • Use Recipe.set_inputs to set inputs to the recipe.
  • Use Recipe.set_operations to set operations to the recipe.
  • Added new experimental DataStorethat adds get_spark_session for Databricks databricks-v1 data stores to get a Spark session.
  • Added attribute chunking_type to DatasetChunkDefinition.
  • Added OTV attributes to DatasourceDefinition.
  • Added DatasetChunkDefinition.patch_validation_dates to patch validation dates of OTV datasource definitions after sampling job.