BEHAVIOR-003: learn causal shadow triggers
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@@ -76,6 +76,7 @@ def test_entities_returns_reader_data() -> None:
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"entity_id": "sensor.temperature",
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"domain": "sensor",
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"state": None,
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"last_changed": None,
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"state_class": None,
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"device_class": None,
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"unit_of_measurement": None,
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@@ -5,7 +5,7 @@ from pathlib import Path
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import pytest
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from app.actuators.models import BehaviorMode, BehaviorStatus
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from app.actuators.models import BehaviorMode, BehaviorPattern, BehaviorStatus
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from app.actuators.store import ActuatorStore
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from app.behavior.engine import BehaviorEngine, predict_behavior, service_for_state
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from app.config import Settings
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@@ -189,6 +189,98 @@ def test_engine_excludes_known_automation_actions(tmp_path: Path) -> None:
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assert {pattern.source for pattern in trained.behavior.patterns} == {"user"}
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def test_engine_learns_causal_automation_for_shadow_without_user_credit(
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tmp_path: Path,
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) -> None:
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now = datetime.now(timezone.utc).replace(second=0, microsecond=0)
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actuator_points: list[StateHistoryPoint] = []
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door_points: list[StateHistoryPoint] = []
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logbook: list[LogbookEntry] = []
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for days_ago in (3, 2, 1):
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action_at = now - timedelta(days=days_ago)
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actuator_points.extend(
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[
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StateHistoryPoint(
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timestamp=action_at - timedelta(minutes=1),
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state="off",
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),
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StateHistoryPoint(timestamp=action_at, state="on"),
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]
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)
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door_points.extend(
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[
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StateHistoryPoint(
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timestamp=action_at - timedelta(minutes=1),
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state="off",
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),
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StateHistoryPoint(
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timestamp=action_at - timedelta(seconds=1),
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state="on",
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),
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]
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)
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logbook.append(
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LogbookEntry(
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entity_id="light.storage",
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timestamp=action_at,
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message="turned on",
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context_domain="automation",
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context_service="trigger",
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)
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)
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actuator_points.sort(key=lambda point: point.timestamp)
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door_points.sort(key=lambda point: point.timestamp)
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settings = _settings(tmp_path)
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store = ActuatorStore(settings.actuator_store)
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record = store.configure("light.storage")
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store.upsert(
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record.model_copy(
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update={
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"assignment": record.assignment.model_copy(
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update={
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"selected_context_entity_ids": [
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"binary_sensor.storage_door"
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],
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}
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)
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}
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)
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)
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reader = FakeBehaviorReader(
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entities=[],
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history=[
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StateHistorySeries(
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entity_id="light.storage",
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points=actuator_points,
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),
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StateHistorySeries(
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entity_id="binary_sensor.storage_door",
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points=door_points,
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),
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],
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logbook=logbook,
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)
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engine = BehaviorEngine(ha_reader=reader, store=store, settings=settings)
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trained = engine.train("light.storage")
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automation_patterns = [
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pattern
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for pattern in trained.behavior.patterns
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if pattern.source == "automation"
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]
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assert len(automation_patterns) == 3
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assert trained.behavior.high_confidence_sample_count == 0
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assert {
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(
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pattern.trigger_entity_id,
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pattern.trigger_from_state,
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pattern.trigger_to_state,
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)
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for pattern in automation_patterns
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} == {("binary_sensor.storage_door", "off", "on")}
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def test_active_mode_rejects_unsafe_domains(tmp_path: Path) -> None:
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settings = _settings(tmp_path)
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store = ActuatorStore(settings.actuator_store)
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@@ -259,3 +351,66 @@ def test_prediction_requires_temporal_support() -> None:
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min_support=3,
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window_minutes=30,
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) is None
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def test_prediction_uses_fresh_causal_context_transition_outside_time_window() -> None:
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now = datetime.now(timezone.utc).replace(second=0, microsecond=0)
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patterns = [
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BehaviorPattern(
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target_state="on",
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minute_of_day=60,
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weekday=0,
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context_states={"binary_sensor.storage_door": "on"},
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trigger_entity_id="binary_sensor.storage_door",
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trigger_from_state="off",
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trigger_to_state="on",
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source="automation",
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weight=0.7,
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observed_at=now - timedelta(days=days_ago),
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)
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for days_ago in (3, 2, 1)
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]
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prediction = predict_behavior(
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patterns,
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current_context={"binary_sensor.storage_door": "on"},
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current_context_changed_at={
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"binary_sensor.storage_door": now - timedelta(seconds=10)
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},
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now=now,
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min_support=3,
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window_minutes=30,
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)
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assert prediction is not None
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assert prediction.target_state == "on"
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assert prediction.matching_patterns == 3
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assert prediction.confidence == 0.7
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assert "frischen Sensorwechsel" in prediction.reason
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def test_prediction_ignores_stale_causal_context_state() -> None:
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now = datetime.now(timezone.utc).replace(second=0, microsecond=0)
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pattern = BehaviorPattern(
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target_state="on",
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minute_of_day=60,
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weekday=0,
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context_states={"binary_sensor.storage_door": "on"},
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trigger_entity_id="binary_sensor.storage_door",
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trigger_from_state="off",
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trigger_to_state="on",
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source="automation",
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weight=0.7,
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observed_at=now - timedelta(days=1),
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)
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assert predict_behavior(
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[pattern],
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current_context={"binary_sensor.storage_door": "on"},
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current_context_changed_at={
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"binary_sensor.storage_door": now - timedelta(minutes=5)
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},
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now=now,
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min_support=1,
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window_minutes=30,
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) is None
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@@ -15,6 +15,7 @@ class FakeHaClient(HaClient):
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{
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"entity_id": "sensor.temperature",
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"state": "21.5",
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"last_changed": "2026-06-14T12:00:00+00:00",
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"attributes": {
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"state_class": "measurement",
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"device_class": "temperature",
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@@ -87,6 +88,7 @@ def test_ha_reader_returns_summaries() -> None:
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sensor = next(item for item in summaries if item.entity_id == "sensor.temperature")
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assert sensor.unit_of_measurement == "°C"
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assert sensor.state == "21.5"
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assert sensor.last_changed == datetime(2026, 6, 14, 12, 0, tzinfo=timezone.utc)
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assert sensor.area_name == "Kueche"
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assert sensor.device_name == "Thermometer"
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@@ -16,6 +16,7 @@ def test_dashboard_is_served_at_root() -> None:
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assert "Du wählst keine Sensoren und erstellst keine Regeln" in response.text
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assert "Freigabe noch gesperrt" in response.text
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assert "Bediene das Licht dafür direkt über Home Assistant" in response.text
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assert "Davon erkannte HA-Automationen" in response.text
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assert 'record.behavior.status === "trained" && missingUserActions === 0' in response.text
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assert "Automation-Entwurf" not in response.text
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assert "Manuelle Overrides" not in response.text
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