Overview Use Cases Connectors Authentication Getting Started with the Python SDK API API Reference ai_agents ai_chat algorithm annotations application_connectors batch_prediction code_completion custom_loss_function custom_metric database_connectors dataset deployment deployment_conversations docstore document_retrievers documentation eda external_app feature_drift feature_group feature_group_row_process feature_group_template file_connectors graph_dashboard holdout_analysis llm_apps mcp_server_connections model createModelFromPython createTrainTestDataSplitFeatureGroup deleteModel deleteModelVersion describeModel describeModelArtifactsExport describeModelVersion describeTrainTestDataSplitFeatureGroup describeTrainTestDataSplitFeatureGroupVersion exportCustomModelVersion exportModelArtifactAsFeatureGroup getCustomTrainFunctionInfo getFeatureGroupSchemasForModelVersion getFeatureImportanceByModelVersion getModelMetrics getTrainingConfigOptions getTrainingDataLogs getTrainingLogs listModelArtifactsExports listModelVersions listModels renameModel retrainModel setDefaultModelAlgorithm setModelObjective setModelPredictionParams setModelTrainingConfig trainModel updatePythonModel updatePythonModelGit updatePythonModelZip model_monitoring module natural_language_explanation organization pipelines predict prediction_operator project project_scopes python_function refresh routellm secrets streaming streaming_connectors upload user webhooks API Classes API Inputs Documentation Chat Bot API Search How to

Method

getModelMetrics GET

Copy GET

Retrieves metrics for all the algorithms trained in this model version.

Arguments:

REQUIRED	KEY	TYPE	DESCRIPTION
Yes	modelId	str	Unique string identifier for the model.
No	modelVersion	str	Version of the model.
No	returnGraphs	bool	If true, will return the information used for the graphs on the model metrics page such as PR Curve per label.
No	validation	bool	If true, will return the validation metrics instead of the test metrics.

Note: The arguments for the API methods follow camelCase but for Python SDK underscore_case is followed.

Response:

KEY

TYPE

DESCRIPTION

success

Boolean

true if the call succeeded, false if there was an error

result

ModelMetrics

KEY	TYPE	Description
algoMetrics	dict	Dictionary mapping algorithm ID to algorithm name and algorithm metrics dictionary
selectedAlgorithm	str	The algorithm ID of the selected (default) algorithm that will be used in deployments of this Model Version
selectedAlgorithmName	str	The algorithm name of the selected (default) algorithm that will be used in deployments of this Model Version
modelId	str	The Model ID
modelVersion	str	The Model Version
metricNames	dict	Maps shorthand names of the metrics to their verbose names
targetColumn	str	The target feature that the model was trained to predict
trainValTestSplit	dict	Info on train, val and test split
trainingCompletedAt	datetime	Timestamp when training was completed

Exceptions:

TYPE	WHEN
DataNotFoundError	`modelId` is not found.

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