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
toLLMBlueprint
. - Added a new class
HostedCustomMetricTemplate
for hosted custom metrics templates. UseHostedCustomMetricTemplate.get
to retrieve a hosted custom metric template. UseHostedCustomMetricTemplate.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.
- Use
- 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.
- Use
- 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.
- Use
- Added attribute
credential_type
toRuntimeParameter
. - 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 toProject.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
toDataStore
andDataSource
. - Added a new parameter
name
toDataStore.list
for searching data stores by name. - Added a new parameter
entity_type
to thecompute
andcreate
methods of the classesShapMatrix
,ShapImpact
,ShapPreview
. Insights can be computed for custom models if the parameterentity_type="customModel"
is passed.
Documentation changes¶
- Added usage of
external_llm_context_size
inllm_settings
ingenai_example.rst
. - Updated doc string for
llm_settings
to include attributeexternal_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
DataStore
that addsget_spark_session
for Databricksdatabricks-v1
data stores to get a Spark session. - Added attribute
chunking_type
toDatasetChunkDefinition
. - Added OTV attributes to
DatasourceDefinition
. - Added
DatasetChunkDefinition.patch_validation_dates
to patch validation dates of OTV datasource definitions after sampling job.
Updated January 8, 2025
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