"""Tests for PersistentLearningStore."""

import tempfile

from fusionagi.governance.adaptive_ethics import AdaptiveEthics
from fusionagi.governance.consequence_engine import ConsequenceEngine
from fusionagi.memory.persistent_learning import PersistentLearningStore


def test_save_and_load_consequences() -> None:
    with tempfile.TemporaryDirectory() as tmpdir:
        engine = ConsequenceEngine()
        engine.record_choice(
            choice_id="c1",
            actor="test",
            action_taken="act1",
            estimated_risk=0.3,
            estimated_reward=0.7,
        )
        engine.record_consequence("c1", outcome_positive=True, actual_risk_realized=0.1, actual_reward_gained=0.8)

        store = PersistentLearningStore(data_dir=tmpdir)
        path = store.save_consequences(engine)
        assert path.endswith("consequences.json")

        engine2 = ConsequenceEngine()
        loaded = store.load_consequences(engine2)
        assert loaded == 1


def test_save_and_load_ethics() -> None:
    with tempfile.TemporaryDirectory() as tmpdir:
        ethics = AdaptiveEthics()
        ethics.record_experience(
            action_type="file_read",
            context_summary="reading file outside scope",
            advisory_reason="out of scope",
            proceeded=True,
            outcome_positive=True,
        )

        store = PersistentLearningStore(data_dir=tmpdir)
        path = store.save_ethics(ethics)
        assert path.endswith("ethics.json")

        ethics2 = AdaptiveEthics()
        loaded = store.load_ethics(ethics2)
        assert loaded == 1


def test_save_risk_histories() -> None:
    with tempfile.TemporaryDirectory() as tmpdir:
        engine = ConsequenceEngine()
        engine.record_choice("c1", actor="t", action_taken="act1", estimated_risk=0.5, estimated_reward=0.5)
        engine.record_consequence("c1", outcome_positive=True, actual_risk_realized=0.2, actual_reward_gained=0.8)

        store = PersistentLearningStore(data_dir=tmpdir)
        path = store.save_risk_histories(engine)
        assert path.endswith("risk_histories.json")


def test_load_nonexistent_returns_zero() -> None:
    with tempfile.TemporaryDirectory() as tmpdir:
        store = PersistentLearningStore(data_dir=tmpdir)
        engine = ConsequenceEngine()
        assert store.load_consequences(engine) == 0
        ethics = AdaptiveEthics()
        assert store.load_ethics(ethics) == 0