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Python API client changelog

Reference the changes introduced to new versions of DataRobot's Python API client.

Python client v3.3

New Features

  • Added support for Python 3.11.
  • Added new a library, "strenum", to add StrEnum support while maintaining backwards compatibility with Python 3.7-3.10. DataRobot does not use the native StrEnum class in Python 3.11.
  • Added a new class PredictionEnvironment for interacting with DataRobot prediction environments.
  • Extended the advanced options available when setting a target to include new parameters: modelGroupId, modelRegimeId, and modelBaselines (part of the AdvancedOptions object). These parameters allow you to specify the user columns required to run time series models without feature derivation in OTV projects.
  • Added a new method PredictionExplanations.create_on_training_data, for computing prediction explanation on training data.

  • Added a new class RegisteredModel for interacting with DataRobot registered models to support the following methods:

  • RegisteredModel.get to retrieve a RegisteredModel object by ID.
  • RegisteredModel.list to list all registered models.
  • RegisteredModel.archive to permanently archive registered model.
  • RegisteredModel.update to update registered model.
  • RegisteredModel.get_shared_roles to retrieve access control information for registered model.
  • RegisteredModel.share to share a registered model.
  • RegisteredModel.get_version to retrieve a RegisteredModelVersion object by ID.
  • RegisteredModel.list_versions to list registered model versions.
  • RegisteredModel.list_associated_deployments to list deployments associated with a registered model.

  • Added a new class RegisteredModelVersion for interacting with DataRobot registered model versions (also known as model packages) to support the following methods:

  • RegisteredModelVersion.create_for_external to create a new registered model version from an external model.
  • RegisteredModelVersion.list_associated_deployments to list deployments associated with a registered model version.
  • RegisteredModelVersion.create_for_leaderboard_item to create a new registered model version from a Leaderboard model.
  • RegisteredModelVersion.create_for_custom_model_version to create a new registered model version from a custom model version.

  • Added a new method Deployment.create_from_registered_model_version to support creating deployments from a registered model version.

  • Added a new method Deployment.download_model_package_file to support downloading model package files (.mlpkg) of the currently deployed model.

  • Added support for retrieving document thumbnails:

  • DocumentThumbnail <datarobot.models.documentai.document.DocumentThumbnail>
  • DocumentPageFile <datarobot.models.documentai.document.DocumentPageFile>

  • Added support to retrieve document text extraction samples using:

  • DocumentTextExtractionSample
  • DocumentTextExtractionSamplePage
  • DocumentTextExtractionSampleDocument

  • Added new fields to CustomTaskVersion for controlling network policies. The new fields were also added to the response. This can be set with datarobot.enums.CustomTaskOutgoingNetworkPolicy.

  • Added a new method BatchPredictionJob.score_with_leaderboard_model to run batch predictions using a Leaderboard model instead of a deployment.

  • Set :IntakeSettings and OutputSettings to use IntakeAdapters and OutputAdapters enum values respectively for the property type.

  • Added the method Deployment.get_predictions_vs_actuals_over_time to retrieve a deployment's predictions vs actuals over time data.

Bugfixes

  • Payload property subset renamed to source in Model.request_feature_effect
  • Fixed an issue where Context.trace_context was not being set from environment variables or DR config files.
  • Project.refresh no longer sets Project.advanced_options to a dictionary.
  • Fixed Dataset.modify to clarify behavior of when to preserve or clear categories.
  • Fixed an issue with enums in f-strings resulting in the enum class and property being printed instead of the enum property's value in Python 3.11 environments.

Deprecation Summary

  • Project.refresh will no longer set Project.advanced_options to a dictionary after version 3.5 is released. All interactions with Project.advanced_options should be expected to be through the AdvancedOptions class.

Experimental changes

  • Added a new class, VectorDatabase, for interacting with DataRobot vector databases.
  • VectorDatabase.get retrieves a VectorDatabase object by ID.
  • VectorDatabase.list lists all VectorDatabases available to the user.
  • VectorDatabase.create creates a new VectorDatabase.
  • VectorDatabase.create allows you to use a validated deployment of a custom model as your own Vector Database.
  • VectorDatabase.update updates the name of a VectorDatabase.
  • VectorDatabase.delete deletes a single VectorDatabase.
  • VectorDatabase.get_supported_embeddings retrieves all supported embedding models.
  • VectorDatabase.get_supported_text_chunkings retrieves all supported text chunking configurations.
  • VectorDatabase.download_text_and_embeddings_asset download a parquet file with internal vector database data.

  • Added a new class, CustomModelVectorDatabaseValidation, for validating custom model deployments for use as a vector database.

  • CustomModelVectorDatabaseValidation.get retrieves a CustomModelVectorDatabaseValidation object by ID.
  • CustomModelVectorDatabaseValidation.get_by_values retrieves a CustomModelVectorDatabaseValidation object by field values.
  • CustomModelVectorDatabaseValidation.create starts validation of the deployment.
  • CustomModelVectorDatabaseValidation.revalidate repairs an unlinked external vector database.

  • Added a new class, Playground, for interacting with DataRobot generative AI playgrounds.

  • Playground.get retrieves a playground object by ID.
  • Playground.list lists all playgrounds available to the user.
  • Playground.create creates a new playground.
  • Playground.update updates the name and description of a playground.
  • Playground.delete deletes a single playground.

  • Added a new class, LLMDefinition, for interacting with DataRobot generative AI LLMs.

  • LLMDefinition.list lists all LLMs available to the user.

  • Added a new class, LLMBlueprint, for interacting with DataRobot generative AI LLM blueprints.

  • LLMBlueprint.get retrieves an LLM blueprint object by ID.
  • LLMBlueprint.list lists all LLM blueprints available to the user.
  • LLMBlueprint.create creates a new LLM blueprint.
  • LLMBlueprint.create_from_llm_blueprint creates a new LLM blueprint from an existing one.
  • LLMBlueprint.update updates an LLM blueprint.
  • LLMBlueprint.delete deletes a single LLM blueprint.

  • Added a new class, ChatPrompt, for interacting with DataRobot generative AI chat prompts.

  • ChatPrompt.get retrieves a chat prompt object by ID.
  • ChatPrompt.list lists all chat prompts available to the user.
  • ChatPrompt.create creates a new chat prompt.
  • ChatPrompt.delete deletes a single chat prompt.

  • Added a new class, CustomModelLLMValidation, for validating custom model deployments for use as a custom model LLM.

  • CustomModelLLMValidation.get retrieves a CustomModelLLMValidation object by ID.
  • CustomModelLLMValidation.get_by_values retrieves a CustomModelLLMValidation object by field values.
  • CustomModelLLMValidation.create starts validation of the deployment.
  • CustomModelLLMValidation.revalidate repairs an unlinked external custom model LLM.

  • Added a new class, ComparisonPrompt, for interacting with DataRobot generative AI comparison prompts.

  • ComparisonPrompt.get retrieves a comparison prompt object by ID.
  • ComparisonPrompt.list lists all comparison prompts available to the user.
  • ComparisonPrompt.create creates a new comparison prompt.
  • ComparisonPrompt.update updates a comparison prompt.
  • ComparisonPrompt.delete deletes a single comparison prompt.

  • Extended UseCase, adding two new fields to represent the count of vector databases and playgrounds.

  • Added a new method, ChatPrompt.create_llm_blueprint, to create an LLM blueprint from a chat prompt.

  • Added a new method, CustomModelLLMValidation.delete, to delete a custom model LLM validation record.

  • Added a new method, LLMBlueprint.register_custom_model, for registering a custom model from a generative AI LLM blueprint.


Updated January 17, 2024