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The request body must include a 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
- 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 cost

Available 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.