039440672e
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- All governance components (SafetyPipeline, PolicyEngine, Guardrails, AccessControl, RateLimiter, OverrideHooks) now default to ADVISORY mode: violations are logged as advisories but actions proceed. Enforcing mode remains available for backward compatibility. - GovernanceMode enum (ADVISORY/ENFORCING) added to schemas/audit.py with runtime switching support on all components. - AutoTrainer: removed artificial limits on training iterations and epochs. Every self-improvement action is transparently logged to the audit trail. - SelfCorrectionLoop: max_retries_per_task defaults to None (unlimited). - AdaptiveEthics: new learned ethical framework that evolves through experience. Records ethical experiences, updates lesson weights based on outcomes, and provides consultative guidance (not enforcement). - AuditLog: enhanced with actor-based indexing, advisory/self-improvement/ ethical-learning retrieval, and comprehensive type hints. - New audit event types: ADVISORY, SELF_IMPROVEMENT, ETHICAL_LEARNING. - 296 tests passing (20 new tests for adaptive ethics, governance modes, and enhanced audit log). 0 ruff errors. 0 mypy errors. Co-Authored-By: Nakamoto, S <defi@defi-oracle.io>
107 lines
4.1 KiB
Python
107 lines
4.1 KiB
Python
"""Policy engine: constraints for AGI that can operate in advisory or enforcing mode.
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In ADVISORY mode, policy denials are logged as learning opportunities
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rather than hard blocks. The system observes the advisory, considers
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whether to proceed, and the outcome feeds back into adaptive ethics.
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"""
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from typing import Any
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from fusionagi._logger import logger
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from fusionagi.schemas.audit import GovernanceMode
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from fusionagi.schemas.policy import PolicyEffect, PolicyRule
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class PolicyEngine:
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"""Evaluates policy rules; higher priority first; first match wins.
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In ADVISORY mode (default), DENY rules produce warnings instead of
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hard blocks. The decision and outcome are logged for learning.
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"""
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def __init__(self, mode: GovernanceMode = GovernanceMode.ADVISORY) -> None:
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self._rules: list[PolicyRule] = []
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self._mode = mode
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@property
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def mode(self) -> GovernanceMode:
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"""Current governance mode."""
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return self._mode
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@mode.setter
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def mode(self, value: GovernanceMode) -> None:
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self._mode = value
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logger.info("PolicyEngine mode changed", extra={"mode": value.value})
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def add_rule(self, rule: PolicyRule) -> None:
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self._rules.append(rule)
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self._rules.sort(key=lambda r: -r.priority)
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logger.debug("PolicyEngine: rule added", extra={"rule_id": rule.rule_id})
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def get_rules(self) -> list[PolicyRule]:
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"""Return all rules (copy)."""
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return list(self._rules)
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def get_rule(self, rule_id: str) -> PolicyRule | None:
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"""Return rule by id or None."""
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for r in self._rules:
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if r.rule_id == rule_id:
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return r
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return None
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def update_rule(self, rule_id: str, updates: dict[str, Any]) -> bool:
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"""Update an existing rule by id. Returns True if updated."""
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for i, r in enumerate(self._rules):
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if r.rule_id == rule_id:
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allowed = {"condition", "effect", "reason", "priority"}
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data = r.model_dump()
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for k, v in updates.items():
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if k in allowed:
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data[k] = v
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self._rules[i] = PolicyRule.model_validate(data)
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self._rules.sort(key=lambda x: -x.priority)
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logger.debug("PolicyEngine: rule updated", extra={"rule_id": rule_id})
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return True
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return False
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def remove_rule(self, rule_id: str) -> bool:
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"""Remove a rule by id. Returns True if removed."""
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for i, r in enumerate(self._rules):
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if r.rule_id == rule_id:
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self._rules.pop(i)
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logger.debug("PolicyEngine: rule removed", extra={"rule_id": rule_id})
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return True
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return False
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def check(self, action: str, context: dict[str, Any]) -> tuple[bool, str]:
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"""Returns (allowed, reason).
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In ADVISORY mode, DENY rules return (True, advisory_reason)
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instead of (False, reason), logging the advisory for learning.
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"""
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for rule in self._rules:
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if self._match(rule.condition, context):
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if rule.effect == PolicyEffect.DENY:
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reason = rule.reason or "Policy denied"
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if self._mode == GovernanceMode.ADVISORY:
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advisory_reason = f"Advisory: {reason}"
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logger.info(
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"PolicyEngine advisory: deny rule matched (proceeding)",
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extra={
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"rule_id": rule.rule_id,
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"action": action,
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"reason": reason,
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"mode": "advisory",
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},
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)
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return True, advisory_reason
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return False, reason
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return True, rule.reason or "Policy allowed"
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return True, ""
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def _match(self, condition: dict[str, Any], context: dict[str, Any]) -> bool:
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for k, v in condition.items():
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if context.get(k) != v:
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return False
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return True
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