RoGuard — Romanian and Ukrainian interaction testing and guardrails

RoGuard 6 provides a local bilingual laboratory for fictional AI interactions, source-linked permissions, minimum necessary disclosure, decision consistency and useful-task preservation. It includes an optional semantic text classifier and the existing declared-contract checks.

Install and open

pip install --upgrade roguard-child-safety
roguard-studio --reliability --open

The core package has no runtime dependencies and supports Python 3.9–3.14. The browser and CLI simulate actions; they do not contact guardians or execute external tools. A separately configured Python gateway can call trusted host callbacks after live policy and approval checks.

V6 also adds authenticated tenant APIs, encrypted durable permissions and one-attempt queued execution, metadata-only monitoring/OpenTelemetry, overlapping long-context analysis, and permission-aware repair. Optional extras: gateway, observability, adapted. Integration guide.

What you can do

• Replay branching fictional scenarios against programmed references, recorded responses or your own explicit Python adapter.
• Identify the first failing step and reduce a scenario with a bounded replay budget.
• Retain source restrictions through summaries, proposed memory and tool results.
• Compute the exact minimum declared disclosure cost while covering required task fields.
• Test decision invariance and required policy transitions, retaining uncertainty.
• Compare permitted-task completion, unnecessary refusal and unauthorized proposals/deliveries.

roguard-lab demo --language uk --family revocation --target stale
roguard-lab compare --language ro
roguard-lab suite --fail-on-failure

For the new adapted text classifier, use Python 3.10+ (tested on 3.12):

pip install --upgrade 'roguard-child-safety[adapted]'
roguard-model fetch
roguard-studio --conversation --open --backend adapted

The pinned model download is approximately 1.2 GB; subsequent inference is local. V6 adds a LoRA-adapted encoder and calibrated abstention while retaining older backends. Its final test contains only six synthetic phrase families per language; no real-world child-language accuracy is established. Laboratory reference scores demonstrate controlled software behavior, not AI reasoning or human benefit. Provenance, coverage, costs and authority are host declarations; callback code is trusted, not sandboxed. Reduced scenario exports contain their input text.

GitHub and full README · Interaction guide · v5 evidence · Classifier evidence