RAI & observability¶
Responsible AI (RAI) policy¶
Oris applies a default PolicyEnforcer at pipeline boundaries:
- Input checks — Blocked keys (e.g.
password,secret,token), basic prompt-injection heuristics, and simple PII-shaped patterns in string values. - Output checks — Blocked terms, plus stub hooks for toxicity/hallucination markers used in tests.
These checks align with InputGuard / OutputGuard hooks in the executor so behavior stays consistent whether you run a full pipeline or SafeRunner.
Layer your defenses
Default policy is a baseline, not a complete safety program. Combine Oris with org policies, model safeguards, and human review appropriate to your domain.
Tracing¶
Each run produces a RunTrace with ordered StepTrace records: timestamps, status, per-step latency_ms, flags, and optional metadata.
The stable JSON-oriented view is PipelineResult.to_run_summary()—used by the CLI and ideal for logs. See Runs, output & traces.
Audit logging¶
The tracing package includes audit helpers for redaction-aware logging—see oris.tracing.audit in the repository.
Related¶
- CLI reference —
--debugtrace lines on stderr - Security — reporting issues and secret handling