Runnable, copyable examples of evaluating an AI system against a GOPAL policy.
Each example contains:
input.json— a sample AI-system payload (the thing being evaluated)run.sh— invokesopa evalagainst a GOPAL policy with that inputexpected-output.json— what the verdict should look likeREADME.md— what the example shows and how to adapt it
You need OPA on your PATH:
curl -L -o opa https://openpolicyagent.org/downloads/latest/opa_linux_amd64 \
&& chmod +x opa && sudo mv opa /usr/local/bin/| Example | Framework | Policy | Verdict |
|---|---|---|---|
eu-ai-act-transparency/ |
EU AI Act | international.eu_ai_act.v1.transparency |
passing |
nist-ai-rmf-govern/ |
NIST AI RMF | international.nist.v1.govern |
passing |
customer-support-llm/ |
Global content-safety | global.v1.toxicity |
passing |
education-proctoring/ |
Education (FERPA-aligned) | industry_specific.education.v1.assessment_and_evaluation.responsible_ai_proctoring |
passing |
Each run.sh is a one-liner you can copy into CI. To see a non-compliant verdict, edit input.json (e.g., lower a completeness score below 0.7, flip a governance boolean to false) and run again.
Open an issue with the framework and use case, or send a PR following the layout above. Examples should be:
- self-contained (no external services)
- runnable with
opa evalonly - minimal — one policy, one input, one verdict