| """Governance — classroom / boardroom / dojo. | |
| A clean-room reimplementation (from the behaviour of github.com/openmindx/openmind — | |
| Boardroom multi-model consensus + Dojo head-to-head evaluation) of the decision layer | |
| that governs training: | |
| - **Classroom** — where an actor trains; it *graduates* when imprint/quality criteria pass. | |
| - **Boardroom** — a panel of **any number** of role-based members that convenes on a motion | |
| (e.g. "promote the graduated actor") and produces a consensus. Governs the classroom. | |
| - **Dojo** — the boardroom's dispute-settlement extension. When the boardroom is split, a dojo | |
| of a **prime number** of judges settles it head-to-head; prime guarantees a strict majority, | |
| so a dispute always resolves with no tie. | |
| Pure stdlib + pydantic; importable on a base install. Members vote via supplied callables / | |
| scores, so the whole layer is testable without any LLM, and can later be backed by real models. | |
| """ | |
| from __future__ import annotations | |
| from mindxtrain.governance.boardroom import ( | |
| PRESET_BOARDS, | |
| ROLES, | |
| Boardroom, | |
| BoardroomDecision, | |
| Member, | |
| Vote, | |
| ) | |
| from mindxtrain.governance.classroom import Graduation, graduate | |
| from mindxtrain.governance.dojo import Dojo, DojoVerdict, settle_dispute | |
| from mindxtrain.governance.panel import ( | |
| Deliberation, | |
| deliberate, | |
| model_ballot, | |
| model_judge_ballot, | |
| ) | |
| from mindxtrain.governance.primes import is_prime, nearest_prime, next_prime | |
| __all__ = [ | |
| "PRESET_BOARDS", | |
| "ROLES", | |
| "Boardroom", | |
| "BoardroomDecision", | |
| "Deliberation", | |
| "Dojo", | |
| "DojoVerdict", | |
| "Graduation", | |
| "Member", | |
| "Vote", | |
| "deliberate", | |
| "graduate", | |
| "is_prime", | |
| "model_ballot", | |
| "model_judge_ballot", | |
| "nearest_prime", | |
| "next_prime", | |
| "settle_dispute", | |
| ] | |