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Datarobot Create Genai Evaluation Dataset Configurations

Tool to create a GenAI evaluation dataset configuration for testing LLM applications. Use when you need to set up evaluation datasets with prompt columns and optional response/tool call columns for assessing GenAI playground outputs. Required for running AI robustness tests on G…

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Use Datarobot Create Genai Evaluation Dataset Configurations

Pricing and limits

Pricing
Free
Unified payment
Not currently supported

Inputs

  • namestring
    Custom configuration name for the evaluation dataset (max 5000 characters). If omitted, DataRobot will auto-generate a name.
  • datasetIdstring
    Required
    The evaluation dataset identifier (24-character hex string). Use DATAROBOT_LIST_DATASETS to find available datasets.
  • useCaseIdstring
    Required
    The use case identifier (24-character hex string). This links the evaluation dataset to a specific use case.
  • playgroundIdstring
    Required
    The playground identifier (24-character hex string). This links the evaluation to a specific GenAI playground.
  • promptColumnNamestring
    Required
    The name of the dataset column containing prompt text. This column provides the input prompts for evaluation.
  • correctnessEnabledboolean
    Enable legacy correctness evaluation. This flag controls whether to use DataRobot's built-in correctness metrics.
  • isSyntheticDatasetboolean
    Indicates whether the dataset contains synthetic data (default: false). Set to true if using AI-generated evaluation data.
  • responseColumnNamestring
    The name of the dataset column containing expected response text. Use this to compare actual LLM responses against ground truth.
  • toolCallsColumnNamestring
    The name of the dataset column containing expected tool calls for agentic workflows. Use this for evaluating agents that call external tools.
  • agentGoalsColumnNamestring
    The name of the dataset column containing expected agent goals for agentic workflows. Use this for evaluating multi-step agent behavior.

Observable output

  • data
    Required
    Data from the action execution
  • errorstring
    Error if any occurred during the execution of the action
  • successfulboolean
    Required
    Whether or not the action execution was successful or not

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