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…val output Surfaces overall precision/recall/f1/accuracy (not just per-entity) and the PIIRemover config (entity types, threshold, NLP engine, model, on_fail) used for the run, so metrics.json is self-describing for external readers.
Clarifies that this is PII's overall detection-level score alongside entity_metrics, distinct from the shared compute_binary_metrics() helper used as the sole metric in other eval scripts.
…s output Mirrors the pii_remover eval script, which already records the config used (entity types, threshold, etc.) alongside the metrics for reproducibility. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
…valuations Introduces build_validator_config() in common/helper.py, which reads on_fail from validator.on_fail_descriptor (set by every guardrails Validator base class) and normalizes any extra constructor params passed in (enums -> their .value). PII and gender_assumption_bias now use it instead of hand-rolled dicts, and ban_list, lexical_slur, topic_relevance, and toxicity gain a config block in their metrics.json for the first time.
This was referenced Sep 23, 2026
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Summary
build_validator_config()helper inapp/evaluation/common/helper.pyand applies it across all evaluation scripts, so everymetrics.jsonrecords the validator config it was produced withcombined_metrics), alongside the existing per-entity metricsTest plan
python3 -m app.evaluation.pii.run— confirmmetrics.jsoncontainsconfigandcombined_metricspython3 -m app.evaluation.gender_assumption_bias.run— confirmconfigblock presentpython3 -m app.evaluation.lexical_slur.run,ban_list,topic_relevance— confirmconfigpresent and metrics otherwise unchanged🤖 Generated with Claude Code