model_input dictionary (containing at least a system_prompt field or a user_prompt field), a model_output string to be evaluated, and a guardrail_metrics array specifying which metrics to evaluate against. Optionally, include the model_used, selected run_mode, and a human-readable nametag.Run modes determine the models that power evaluations
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precision_plus - Maximum accuracy using the most advanced models-
precision - High accuracy with optimized performance-
smart - Balanced speed and accuracy (default)-
economy - Fastest evaluation at lowest costAvailable guardrail metrics include
correctness, completeness, instruction_adherence, context_adherence, ground_truth_adherence, and comprehensive_safety. When you create a monitor event, you’ll receive an event ID. Use this ID to track the event’s progress and retrieve the evaluation results.
