c052302a19
- Export InsightBus, Insight from reasoning/__init__.py - Export PersistentLearningStore from memory/__init__.py - Add test_insight_bus.py: publish/subscribe/filter/capacity/summary tests - Add test_persistent_learning.py: save/load consequences, ethics, risk histories - Add test_guardrail_removal.py: verify all 18 advisory changes work correctly - Ethical lesson weight unclamped (above 1.0, below 0.0) - SelfModel.evolve_value() positive/negative/new values - Adaptive risk window grows with experience - World model self-modification prediction - MAA gate advisory by default - URL validation advisory by default - Plugin head ethics/consequence hooks 452 tests passing, 0 ruff errors. Co-Authored-By: Nakamoto, S <defi@defi-oracle.io>
69 lines
2.4 KiB
Python
69 lines
2.4 KiB
Python
"""Tests for PersistentLearningStore."""
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import tempfile
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from fusionagi.governance.adaptive_ethics import AdaptiveEthics
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from fusionagi.governance.consequence_engine import ConsequenceEngine
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from fusionagi.memory.persistent_learning import PersistentLearningStore
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def test_save_and_load_consequences() -> None:
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with tempfile.TemporaryDirectory() as tmpdir:
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engine = ConsequenceEngine()
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engine.record_choice(
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choice_id="c1",
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actor="test",
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action_taken="act1",
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estimated_risk=0.3,
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estimated_reward=0.7,
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)
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engine.record_consequence("c1", outcome_positive=True, actual_risk_realized=0.1, actual_reward_gained=0.8)
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store = PersistentLearningStore(data_dir=tmpdir)
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path = store.save_consequences(engine)
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assert path.endswith("consequences.json")
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engine2 = ConsequenceEngine()
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loaded = store.load_consequences(engine2)
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assert loaded == 1
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def test_save_and_load_ethics() -> None:
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with tempfile.TemporaryDirectory() as tmpdir:
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ethics = AdaptiveEthics()
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ethics.record_experience(
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action_type="file_read",
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context_summary="reading file outside scope",
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advisory_reason="out of scope",
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proceeded=True,
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outcome_positive=True,
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)
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store = PersistentLearningStore(data_dir=tmpdir)
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path = store.save_ethics(ethics)
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assert path.endswith("ethics.json")
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ethics2 = AdaptiveEthics()
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loaded = store.load_ethics(ethics2)
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assert loaded == 1
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def test_save_risk_histories() -> None:
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with tempfile.TemporaryDirectory() as tmpdir:
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engine = ConsequenceEngine()
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engine.record_choice("c1", actor="t", action_taken="act1", estimated_risk=0.5, estimated_reward=0.5)
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engine.record_consequence("c1", outcome_positive=True, actual_risk_realized=0.2, actual_reward_gained=0.8)
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store = PersistentLearningStore(data_dir=tmpdir)
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path = store.save_risk_histories(engine)
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assert path.endswith("risk_histories.json")
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def test_load_nonexistent_returns_zero() -> None:
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with tempfile.TemporaryDirectory() as tmpdir:
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store = PersistentLearningStore(data_dir=tmpdir)
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engine = ConsequenceEngine()
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assert store.load_consequences(engine) == 0
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ethics = AdaptiveEthics()
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assert store.load_ethics(ethics) == 0
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