Improve SillyHome discovery and feedback learning

This commit is contained in:
2026-06-16 11:38:32 +02:00
parent c5f42a39a9
commit e2826e92ec
12 changed files with 513 additions and 8 deletions

View File

@@ -356,6 +356,95 @@ class BehaviorEngine:
)
return self._save_behavior(record, behavior)
def record_feedback(
self,
actuator_entity_id: str,
*,
correct: bool,
expected_state: str | None = None,
) -> ActuatorRecord:
record = self._store.get(actuator_entity_id)
now = datetime.now(timezone.utc)
entities = {entity.entity_id: entity for entity in self._ha_reader.read_entities()}
actuator = entities.get(actuator_entity_id)
if actuator is None:
raise KeyError("Aktor ist aktuell nicht in Home Assistant verfügbar.")
context_ids = [
entity_id
for entity_id in [
record.assignment.selected_numeric_entity_id,
*record.assignment.selected_context_entity_ids,
]
if entity_id
]
current_context = {
entity_id: entities[entity_id].state
for entity_id in context_ids
if entity_id in entities and entities[entity_id].state is not None
}
prediction = record.behavior.prediction
patterns = list(record.behavior.patterns)
reason = "Nutzerfeedback gespeichert."
if correct and prediction is not None:
local = now.astimezone(ZoneInfo(self._settings.timezone))
patterns.append(
BehaviorPattern(
target_state=prediction.target_state,
minute_of_day=local.hour * 60 + local.minute,
weekday=local.weekday(),
context_states={
entity_id: state
for entity_id, state in current_context.items()
if state is not None
},
source="user_feedback",
weight=1.0,
observed_at=now,
)
)
reason = "Vorhersage wurde vom Nutzer als korrekt bestätigt."
else:
target = prediction.target_state if prediction is not None else None
if target:
patterns = [
pattern.model_copy(update={"weight": 0.1})
if pattern.target_state == target
and _pattern_context_matches(pattern, current_context)
else pattern
for pattern in patterns
]
if expected_state:
local = now.astimezone(ZoneInfo(self._settings.timezone))
patterns.append(
BehaviorPattern(
target_state=expected_state,
minute_of_day=local.hour * 60 + local.minute,
weekday=local.weekday(),
context_states={
entity_id: state
for entity_id, state in current_context.items()
if state is not None
},
source="user_correction",
weight=1.0,
observed_at=now,
)
)
reason = "Vorhersage wurde vom Nutzer als falsch markiert."
behavior = record.behavior.model_copy(
update={
"patterns": patterns[-_MAX_PATTERNS:],
"prediction": (
prediction.model_copy(update={"execution_reason": reason})
if prediction is not None
else None
),
"reason": reason,
"last_trained_at": now,
}
)
return self._save_behavior(record, behavior)
def refresh_related_automations(self, actuator_entity_id: str) -> ActuatorRecord:
record = self._store.get(actuator_entity_id)
related = [
@@ -856,6 +945,20 @@ def _matches_own_execution(
)
def _pattern_context_matches(
pattern: BehaviorPattern,
current_context: dict[str, str | None],
) -> bool:
comparable = [
(entity_id, expected)
for entity_id, expected in pattern.context_states.items()
if entity_id in current_context
]
if not comparable:
return False
return all(current_context[entity_id] == expected for entity_id, expected in comparable)
def _recent_context_transition(
history: dict[str, StateHistorySeries],
context_ids: list[str],