eval-runner

Automated AI evaluation in a CI pipeline uses deterministic tests to assess quality, detect hallucinations, and identify PII leakage. Integrating this as a quality gate prevents regressions by ensuring AI-generated content remains accurate and safe before deployment.

Red-teaming for AI safety identifies potential security risks like PII leakage and jailbreak attempts. It systematically probes AI features to expose vulnerabilities, ensuring models do not expose sensitive data or bypass safety guardrails.

Testing AI chatbots for medical Q&A accuracy involves running automated evaluations to verify factuality and grounding. This ensures health application responses are accurate and safe, preventing harmful misinformation from reaching users.

Yes, promptfoo is required to run these automated AI evaluations and red-teaming. It provides the underlying testing framework to execute deterministic tests and identify security risks within your AI features.

Yes, automated AI evaluation integrates directly into CI pipelines as a quality gate for health applications. It ensures AI-generated content for features like symptom chatbots is accurate, grounded, and safe before any code merges.

Using promptfoo for CI integration focuses on deterministic testing and red-teaming, meaning it evaluates predefined scenarios and security probes. It requires configured test cases and may not catch novel safety issues outside its defined evaluation parameters.