Load actuator suggestions asynchronously

CHANGELOG.md

@@ -1,5 +1,53 @@
 # Changelog
 
+## 0.7.14 - 2026-06-16
+- Onboarding-Vorschläge laden im Dashboard nachgelagert, damit Status,
+  Aktor-Auswahl und bestehende Geräte nicht auf Automation-Discovery warten.
+
+## 0.7.13 - 2026-06-16
+- Diagnose-/Schutzsensoren wie Überhitzung und Überlast werden nicht mehr nur
+  wegen gleicher Strom-/Monitoring-Bereiche automatisch als Lichtkontext
+  übernommen.
+- Verwendete Kontext-Entities können pro Aktor direkt entfernt und damit als
+  manuelle Zuordnung überschrieben werden.
+- Onboarding-Vorschläge zeigen passende, noch nicht eingerichtete Aktoren aus
+  bestehenden Automationen und naheliegenden Kontexten.
+- TV-/Medien-Aktoren über `media_player` und Fernbedienungen über `remote`
+  werden in Discovery und Auswahl berücksichtigt.
+
+## 0.7.12 - 2026-06-16
+- Aktor-Auswahlliste zeigt maximal 50 Treffer gleichzeitig und fordert bei
+  größeren Mengen zum Eingrenzen per Suche oder Typfilter auf.
+
+## 0.7.11 - 2026-06-16
+- Aktor-Discovery erkennt weitere steuerbare HA-Domains wie Buttons, Helper,
+  Heizungen, Schlösser, Ventile und numerische Helper.
+- Aktor-Auswahl dedupliziert Licht-/Schalter-Doppelungen pro Gerät und gruppiert
+  zusätzliche Typen im Dashboard.
+- Discovery liefert Kategorien für Mess-, Binär-, Kontext- und Aktor-Entities.
+- Nutzerfeedback kann Vorhersagen als korrekt oder falsch markieren und direkt
+  als Lernsignal speichern.
+
+## 0.7.10 - 2026-06-16
+- WebSocket-State-Changes aktualisieren einen internen Home-Assistant-State-
+  Cache und werten Aktoren direkt gegen diesen frischen Event-Zustand aus.
+- Event-Auswertungen lösen keine REST-Statusabfrage mehr aus, bevor sie
+  aktive Aktoren schalten.
+
+## 0.7.9 - 2026-06-15
+- Event-basierte Vorhersagen verwenden den frischen Sensorzustand direkt aus
+  dem Home-Assistant-WebSocket-Event, damit Kontextwechsel ohne REST-Race sofort
+  bewertet und geschaltet werden können
+- Regressionstest stellt sicher, dass ein Türsensor-Event trotz veraltetem
+  HA-Snapshot direkt `light.turn_on` auslöst
+
+## 0.7.8 - 2026-06-15
+- Home-Assistant-WebSocket-Listener deaktiviert den clientseitigen Keepalive-
+  Ping, damit stabile HA-Verbindungen nicht durch Ping-Timeouts ständig neu
+  aufgebaut werden
+- Fallback-Auswertung läuft bei getrenntem WebSocket kurzfristig alle 5 Sekunden,
+  damit übernommene Aktoren nicht ohne Steuerung bleiben
+
 ## 0.7.7 - 2026-06-15
 - WebSocket-State-Changes lesen jetzt das echte Home-Assistant-Eventformat
   (`event.data.entity_id`), damit Kontextwechsel wie Türsensoren sofort

addon/config.yaml

@@ -1,5 +1,5 @@
 name: SillyHome Next
-version: "0.7.7"
+version: "0.7.14"
 slug: sillyhome_next
 description: Lernt automatisch aus deinem Verhalten und steuert freigegebene Aktoren
 url: http://192.168.6.31:3000/pino/sillyhome-next

app/actuators/lifecycle.py

@@ -57,7 +57,7 @@ _STOPWORDS = frozenset(
         "value",
     }
 )
-_GENERIC_AREA_NAMES = frozenset({"monitoring", "system", "technik"})
+_GENERIC_AREA_NAMES = frozenset({"energie", "monitoring", "power", "strom", "system", "technik"})
 _NUMERIC_AUTO_ACCEPT_SCORE = 0.82
 _NUMERIC_AUTO_ACCEPT_MIN_SCORE = 0.5
 _NUMERIC_MIN_MARGIN = 0.18
@@ -88,6 +88,7 @@ _DIAGNOSTIC_TOKENS = frozenset({
     "diagnostic",
     "firmware",
     "gesehen",
+    "heat",
     "last",
     "linkquality",
     "knoten",
@@ -100,10 +101,28 @@ _DIAGNOSTIC_TOKENS = frozenset({
     "signal",
     "ssid",
     "status",
+    "overheat",
+    "overheating",
+    "overload",
     "uptime",
+    "uberhitzung",
+    "ueberhitzung",
+    "ueberlast",
+    "überhitzung",
+    "überlast",
     "wifi",
     "zuletzt",
 })
+_AUTO_CONTEXT_CLASSES = frozenset({
+    "door",
+    "garage_door",
+    "illuminance",
+    "motion",
+    "occupancy",
+    "opening",
+    "presence",
+    "window",
+})
 
 
 class ActuatorReconciliationService:
@@ -628,8 +647,12 @@ class ActuatorReconciliationService:
                 if context
                 else _NUMERIC_AUTO_ACCEPT_MIN_SCORE
             )
+            can_auto_accept_context = (
+                not context or _eligible_for_auto_context(actuator, candidate)
+            )
             auto_accepted = (
-                candidate.score >= minimum_score
+                can_auto_accept_context
+                and candidate.score >= minimum_score
                 and confidence >= auto_score
                 and (context or margin >= _NUMERIC_MIN_MARGIN)
             )
@@ -743,6 +766,23 @@ def _has_context_relationship(actuator: HaEntitySummary, entity: HaEntitySummary
     )
 
 
+def _eligible_for_auto_context(
+    actuator: HaEntitySummary,
+    candidate: AssignmentCandidate,
+) -> bool:
+    device_class = candidate.device_class or ""
+    if device_class in _AUTO_CONTEXT_CLASSES:
+        return True
+    if (
+        actuator.device_name
+        and candidate.device_name
+        and actuator.device_name == candidate.device_name
+        and candidate.domain in {"light", "switch"}
+    ):
+        return True
+    return False
+
+
 def _score_candidate(
     actuator: HaEntitySummary,
     entity: HaEntitySummary,

app/api/v1/actuators.py

@@ -8,7 +8,7 @@ from app.actuators.models import ActuatorRecord, ReconciliationState
 from app.actuators.store import ActuatorStore
 from app.behavior.engine import BehaviorEngine
 from app.dependencies import get_ha_reader
-from app.ha.discovery import EntityRole
+from app.ha.discovery import DiscoveredEntity, EntityRole
 from app.ha.exceptions import HaClientError
 from app.ha.models import HaEntitySummary
 from app.ha.reader import HaReader
@@ -38,16 +38,98 @@ class ManualAssignmentRequest(BaseModel):
     note: str | None = Field(default=None, max_length=500)
 
 
+class FeedbackRequest(BaseModel):
+    correct: bool
+    expected_state: str | None = Field(default=None, max_length=100)
+
+
+class ActuatorSuggestion(BaseModel):
+    entity_id: str
+    domain: str
+    friendly_name: str | None = None
+    area_name: str | None = None
+    device_name: str | None = None
+    confidence: float
+    reason: str
+    related_automation_count: int = 0
+    likely_context_count: int = 0
+
+
 @router.get("/discovery", response_model=list[HaEntitySummary])
 def discover_actuators(ha_reader: HaReader = Depends(get_ha_reader)) -> list[HaEntitySummary]:
     entities = {entity.entity_id: entity for entity in ha_reader.read_entities()}
     discovered = ha_reader.discover()
-    actuator_ids = sorted(
+    actuator_ids = _deduplicate_actuator_ids(
-        entity.entity_id for entity in discovered if entity.role is EntityRole.ACTUATOR
+        [
+            (entity.entity_id, entity.category)
+            for entity in discovered
+            if entity.role is EntityRole.ACTUATOR
+        ],
+        entities,
     )
     return [entities[entity_id] for entity_id in actuator_ids if entity_id in entities]
 
 
+@router.get("/suggestions", response_model=list[ActuatorSuggestion])
+def suggest_actuators(
+    request: Request,
+    ha_reader: HaReader = Depends(get_ha_reader),
+) -> list[ActuatorSuggestion]:
+    entities = {entity.entity_id: entity for entity in ha_reader.read_entities()}
+    discovered = {entity.entity_id: entity for entity in ha_reader.discover()}
+    configured_ids = {record.actuator_entity_id for record in _service(request).list_configured()}
+    actuator_ids = _deduplicate_actuator_ids(
+        [
+            (entity.entity_id, entity.category)
+            for entity in discovered.values()
+            if entity.role is EntityRole.ACTUATOR
+        ],
+        entities,
+    )
+    suggestions: list[ActuatorSuggestion] = []
+    for entity_id in actuator_ids:
+        if entity_id in configured_ids:
+            continue
+        entity = entities.get(entity_id)
+        if entity is None:
+            continue
+        try:
+            automations = ha_reader.find_automations_for_entity(entity_id)
+        except Exception:
+            automations = []
+        context_count = _likely_context_count(entity, entities, discovered)
+        if not automations and context_count == 0:
+            continue
+        confidence = 1.0 if automations else min(0.85, 0.35 + context_count * 0.1)
+        reason_parts = []
+        if automations:
+            reason_parts.append(f"{len(automations)} passende HA-Automation(en)")
+        if context_count:
+            reason_parts.append(f"{context_count} naheliegende Kontext-Entity(s)")
+        suggestions.append(
+            ActuatorSuggestion(
+                entity_id=entity.entity_id,
+                domain=entity.domain,
+                friendly_name=entity.friendly_name,
+                area_name=entity.area_name,
+                device_name=entity.device_name,
+                confidence=round(confidence, 4),
+                reason=", ".join(reason_parts),
+                related_automation_count=len(automations),
+                likely_context_count=context_count,
+            )
+        )
+    return sorted(
+        suggestions,
+        key=lambda item: (
+            -item.related_automation_count,
+            -item.confidence,
+            item.area_name or "",
+            item.friendly_name or item.entity_id,
+        ),
+    )[:30]
+
+
 @router.get("/context-options", response_model=list[HaEntitySummary])
 def context_options(
     request: Request,
@@ -116,6 +198,22 @@ def evaluate_actuator(
         raise HTTPException(status_code=404, detail=str(exc)) from exc
 
 
+@router.post("/{actuator_entity_id}/feedback", response_model=ActuatorRecord)
+def record_feedback(
+    actuator_entity_id: str,
+    payload: FeedbackRequest,
+    request: Request,
+) -> ActuatorRecord:
+    try:
+        return _behavior(request).record_feedback(
+            actuator_entity_id,
+            correct=payload.correct,
+            expected_state=payload.expected_state,
+        )
+    except KeyError as exc:
+        raise HTTPException(status_code=404, detail=str(exc)) from exc
+
+
 @router.post("/{actuator_entity_id}/activation", response_model=ActuatorRecord)
 def set_activation(
     actuator_entity_id: str,
@@ -233,3 +331,102 @@ def _behavior(request: Request) -> BehaviorEngine:
             detail="Verhaltenslernen ist nicht initialisiert.",
         )
     return engine
+
+
+def _deduplicate_actuator_ids(
+    discovered: list[tuple[str, str]],
+    entities: dict[str, HaEntitySummary],
+) -> list[str]:
+    priority = {
+        "light": 0,
+        "cover_shutter": 1,
+        "heating": 2,
+        "lock": 3,
+        "fan": 4,
+        "switch_socket": 5,
+        "button": 6,
+        "helper": 7,
+    }
+    selected: dict[str, tuple[int, str]] = {}
+    for entity_id, category in discovered:
+        entity = entities.get(entity_id)
+        if entity is None:
+            continue
+        key = _actuator_duplicate_key(entity, category)
+        rank = priority.get(category, 50)
+        current = selected.get(key)
+        if current is None or (rank, entity_id) < current:
+            selected[key] = (rank, entity_id)
+    return sorted(entity_id for _, entity_id in selected.values())
+
+
+def _actuator_duplicate_key(entity: HaEntitySummary, category: str) -> str:
+    if entity.device_id and category in {"light", "switch_socket", "button"}:
+        return f"device:{entity.device_id}:control"
+    if entity.device_name and category in {"light", "switch_socket", "button"}:
+        return f"device-name:{entity.device_name.lower()}:control"
+    return f"entity:{entity.entity_id}"
+
+
+def _likely_context_count(
+    actuator: HaEntitySummary,
+    entities: dict[str, HaEntitySummary],
+    discovered: dict[str, DiscoveredEntity],
+) -> int:
+    actuator_tokens = _tokens(actuator)
+    count = 0
+    for entity in entities.values():
+        if entity.entity_id == actuator.entity_id:
+            continue
+        descriptor = discovered.get(entity.entity_id)
+        role = descriptor.role if descriptor is not None else None
+        if role not in {
+            EntityRole.MEASUREMENT,
+            EntityRole.BINARY_CONTEXT,
+            EntityRole.CONTEXT,
+        }:
+            continue
+        if entity.device_class not in {
+            "door",
+            "energy",
+            "garage_door",
+            "humidity",
+            "illuminance",
+            "motion",
+            "occupancy",
+            "opening",
+            "power",
+            "presence",
+            "temperature",
+            "window",
+        }:
+            continue
+        same_area = bool(
+            actuator.area_name
+            and entity.area_name
+            and actuator.area_name == entity.area_name
+        )
+        same_device = bool(
+            actuator.device_id
+            and entity.device_id
+            and actuator.device_id == entity.device_id
+        )
+        token_match = bool(actuator_tokens.intersection(_tokens(entity)))
+        if same_area or same_device or token_match:
+            count += 1
+    return count
+
+
+def _tokens(entity: HaEntitySummary) -> set[str]:
+    values = [
+        entity.entity_id,
+        entity.friendly_name,
+        entity.area_name,
+        entity.device_name,
+    ]
+    tokens: set[str] = set()
+    for value in values:
+        if not value:
+            continue
+        tokens.update(token for token in value.lower().replace("_", " ").split() if len(token) > 2)
+    return tokens

app/behavior/engine.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 import logging
+from collections.abc import Sequence
 from datetime import datetime, timedelta, timezone
 from zoneinfo import ZoneInfo
 
@@ -18,6 +19,7 @@ from app.actuators.store import ActuatorStore
 from app.config import Settings
 from app.ha.exceptions import HaClientError
 from app.ha.history import LogbookEntry, StateHistoryPoint, StateHistorySeries
+from app.ha.models import HaEntitySummary
 from app.ha.reader import HaReader
 
 _MAX_PATTERNS = 500
@@ -187,23 +189,32 @@ class BehaviorEngine:
                 results.append(record)
         return results
 
-    def evaluate(self, actuator_entity_id: str) -> ActuatorRecord:
+    def evaluate(
+        self,
+        actuator_entity_id: str,
+        *,
+        context_state_overrides: dict[str, str | None] | None = None,
+        context_changed_at_overrides: dict[str, datetime | None] | None = None,
+        current_entities: Sequence[HaEntitySummary] | None = None,
+    ) -> ActuatorRecord:
         record = self._store.get(actuator_entity_id)
         now = datetime.now(timezone.utc)
-        try:
+        if current_entities is None:
-            entities = {entity.entity_id: entity for entity in self._ha_reader.read_entities()}
+            try:
-        except HaClientError as exc:
+                current_entities = self._ha_reader.read_entities()
-            logger.warning("Current HA state unavailable for %s: %s", actuator_entity_id, exc)
+            except HaClientError as exc:
-            return self._save_behavior(
+                logger.warning("Current HA state unavailable for %s: %s", actuator_entity_id, exc)
-                record,
+                return self._save_behavior(
-                record.behavior.model_copy(
+                    record,
-                    update={
+                    record.behavior.model_copy(
-                        "last_evaluated_at": now,
+                        update={
-                        "prediction": None,
+                            "last_evaluated_at": now,
-                        "reason": f"Aktueller Home-Assistant-Zustand ist nicht verfügbar: {exc}",
+                            "prediction": None,
-                    }
+                            "reason": f"Aktueller Home-Assistant-Zustand ist nicht verfügbar: {exc}",
-                ),
+                        }
-            )
+                    ),
+                )
+        entities = {entity.entity_id: entity for entity in current_entities}
         actuator = entities.get(actuator_entity_id)
         if actuator is None:
             return self._save_behavior(
@@ -230,6 +241,22 @@ class BehaviorEngine:
             entity_id: entities[entity_id].last_changed
             for entity_id in current_context
         }
+        selected_context_ids = {
+            entity_id
+            for entity_id in (
+                [
+                    record.assignment.selected_numeric_entity_id,
+                    *record.assignment.selected_context_entity_ids,
+                ]
+            )
+            if entity_id
+        }
+        for entity_id, state in (context_state_overrides or {}).items():
+            if entity_id in selected_context_ids and state is not None:
+                current_context[entity_id] = state
+        for entity_id, changed_at in (context_changed_at_overrides or {}).items():
+            if entity_id in current_context:
+                current_context_changed_at[entity_id] = changed_at or now
         prediction = predict_behavior(
             record.behavior.patterns,
             current_context=current_context,
@@ -329,6 +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 = [
@@ -608,20 +724,30 @@ class BehaviorEngine:
         )
         return self._store.upsert(updated)
 
-    def handle_state_change(self, entity_id: str, new_state: dict[str, object] | None) -> None:
+    def handle_state_change(
+        self,
+        entity_id: str,
+        new_state: dict[str, object] | None,
+        *,
+        current_entities: Sequence[HaEntitySummary] | None = None,
+    ) -> None:
         """Wird bei jedem HA-State-Change aufgerufen und löst sofortige Vorhersage aus.
 
         - Wenn entity_id ein Aktor ist: evaluate() direkt.
         - Wenn entity_id ein Kontext-Entity ist: alle betroffenen Aktoren evaluieren.
+        - Wenn current_entities gesetzt ist, kommt die Auswertung direkt aus dem
+          WebSocket-State-Cache statt aus einer frischen REST-Abfrage.
         """
         # Aktor direkt evaluieren
         for record in self._store.list():
             if record.actuator_entity_id == entity_id:
                 try:
-                    self.evaluate(record.actuator_entity_id)
+                    self.evaluate(record.actuator_entity_id, current_entities=current_entities)
                 except Exception:
                     logger.exception("Event-basierte Vorhersage fehlgeschlagen für %s", record.actuator_entity_id)
                 return
+        event_state = _event_state(new_state)
+        event_changed_at = _event_changed_at(new_state) or datetime.now(timezone.utc)
         # Kontext-Entity: alle Aktoren finden, die diesen Kontext nutzen
         affected_actuators = [
             record.actuator_entity_id
@@ -633,11 +759,38 @@ class BehaviorEngine:
         ]
         for actuator_entity_id in affected_actuators:
             try:
-                self.evaluate(actuator_entity_id)
+                self.evaluate(
+                    actuator_entity_id,
+                    context_state_overrides={entity_id: event_state},
+                    context_changed_at_overrides={entity_id: event_changed_at},
+                    current_entities=current_entities,
+                )
             except Exception:
                 logger.exception("Event-basierte Vorhersage fehlgeschlagen für %s", actuator_entity_id)
 
 
+def _event_state(new_state: dict[str, object] | None) -> str | None:
+    if not isinstance(new_state, dict):
+        return None
+    state = new_state.get("state")
+    return state if isinstance(state, str) else None
+
+
+def _event_changed_at(new_state: dict[str, object] | None) -> datetime | None:
+    if not isinstance(new_state, dict):
+        return None
+    value = new_state.get("last_changed") or new_state.get("last_updated")
+    if not isinstance(value, str):
+        return None
+    try:
+        parsed = datetime.fromisoformat(value.replace("Z", "+00:00"))
+    except ValueError:
+        return None
+    if parsed.tzinfo is None:
+        return parsed.replace(tzinfo=timezone.utc)
+    return parsed
+
+
 def predict_behavior(
     patterns: list[BehaviorPattern],
     *,
@@ -745,7 +898,7 @@ def predict_behavior(
 
 
 def service_for_state(domain: str, target_state: str) -> str | None:
-    if domain in {"fan", "humidifier", "light", "switch"}:
+    if domain in {"fan", "humidifier", "light", "media_player", "remote", "switch"}:
         return {"on": "turn_on", "off": "turn_off"}.get(target_state)
     if domain == "cover":
         return {"open": "open_cover", "closed": "close_cover"}.get(target_state)
@@ -792,6 +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],

app/ha/discovery.py

@@ -21,6 +21,7 @@ class DiscoveredEntity(BaseModel):
     device_class: str | None = None
     state_class: str | None = None
     unit_of_measurement: str | None = None
+    category: str
     role: EntityRole
     learnable: bool
     reason: str
@@ -82,14 +83,41 @@ _BINARY_CONTEXT_CLASSES = frozenset({
     "window",
 })
 _ACTUATOR_DOMAINS = frozenset({
+    "button",
+    "climate",
     "cover",
     "fan",
     "humidifier",
+    "input_boolean",
+    "input_button",
+    "lock",
     "light",
+    "media_player",
+    "number",
+    "remote",
+    "siren",
     "switch",
+    "valve",
+})
+_CONTEXT_DOMAINS = frozenset({
+    "device_tracker",
+    "input_boolean",
+    "input_datetime",
+    "input_number",
+    "input_select",
+    "person",
+    "sun",
+    "weather",
+    "zone",
+})
+_LEARNABLE_CONTEXT_DOMAINS = frozenset({
+    "device_tracker",
+    "input_boolean",
+    "input_number",
+    "input_select",
+    "person",
+    "weather",
 })
-_CONTEXT_DOMAINS = frozenset({"device_tracker", "person", "sun", "weather", "zone"})
-_LEARNABLE_CONTEXT_DOMAINS = frozenset({"device_tracker", "person", "weather"})
 _NUMERIC_STATE_CLASSES = frozenset({"measurement", "total", "total_increasing"})
 
 
@@ -102,6 +130,7 @@ def classify_entity(entity: HaEntitySummary) -> DiscoveredEntity:
         return _result(
             entity,
             EntityRole.MEASUREMENT,
+            category=_measurement_category(entity),
             learnable=True,
             reason="Numerischer Messsensor für Zeitreihen und Training.",
         )
@@ -110,6 +139,7 @@ def classify_entity(entity: HaEntitySummary) -> DiscoveredEntity:
         return _result(
             entity,
             EntityRole.BINARY_CONTEXT,
+            category=_binary_category(entity),
             learnable=True,
             reason="Binärer Kontextsensor für Zustands- und Anwesenheitsmuster.",
         )
@@ -119,6 +149,7 @@ def classify_entity(entity: HaEntitySummary) -> DiscoveredEntity:
         return _result(
             entity,
             EntityRole.CONTEXT,
+            category=_context_category(entity),
             learnable=learnable,
             reason=(
                 "Kontextquelle für Training und Erklärungen."
@@ -131,6 +162,7 @@ def classify_entity(entity: HaEntitySummary) -> DiscoveredEntity:
         return _result(
             entity,
             EntityRole.ACTUATOR,
+            category=_actuator_category(entity),
             learnable=False,
             reason="Aktor ist ein mögliches Automationsziel, aber kein Trainingssensor.",
         )
@@ -138,6 +170,7 @@ def classify_entity(entity: HaEntitySummary) -> DiscoveredEntity:
     return _result(
         entity,
         EntityRole.UNSUPPORTED,
+        category="unsupported",
         learnable=False,
         reason="Entity-Typ ist noch nicht für Lernen oder Automationen klassifiziert.",
     )
@@ -162,6 +195,7 @@ def _result(
     entity: HaEntitySummary,
     role: EntityRole,
     *,
+    category: str,
     learnable: bool,
     reason: str,
 ) -> DiscoveredEntity:
@@ -171,7 +205,64 @@ def _result(
         device_class=entity.device_class,
         state_class=entity.state_class,
         unit_of_measurement=entity.unit_of_measurement,
+        category=category,
         role=role,
         learnable=learnable,
         reason=reason,
     )
+
+
+def _actuator_category(entity: HaEntitySummary) -> str:
+    if entity.domain == "light":
+        return "light"
+    if entity.domain == "switch":
+        return "switch_socket"
+    if entity.domain == "button" or entity.domain == "input_button":
+        return "button"
+    if entity.domain == "cover":
+        return "cover_shutter"
+    if entity.domain == "climate":
+        return "heating"
+    if entity.domain == "lock":
+        return "lock"
+    if entity.domain == "fan":
+        return "fan"
+    if entity.domain in {"media_player", "remote"}:
+        return "media_tv"
+    if entity.domain in {"input_boolean", "number"}:
+        return "helper"
+    return entity.domain
+
+
+def _measurement_category(entity: HaEntitySummary) -> str:
+    device_class = entity.device_class or ""
+    if device_class == "illuminance":
+        return "brightness"
+    if device_class == "temperature":
+        return "temperature"
+    if device_class in {"humidity", "moisture"}:
+        return "humidity"
+    if device_class in {"power", "energy", "current", "voltage"}:
+        return "energy_power"
+    if device_class in {"battery", "signal_strength"}:
+        return "diagnostic"
+    return "measurement"
+
+
+def _binary_category(entity: HaEntitySummary) -> str:
+    device_class = entity.device_class or ""
+    if device_class in {"motion", "occupancy", "presence"}:
+        return "presence_motion"
+    if device_class in {"door", "garage_door", "opening", "window"}:
+        return "opening"
+    if device_class in {"smoke", "safety", "problem"}:
+        return "safety"
+    return "binary"
+
+
+def _context_category(entity: HaEntitySummary) -> str:
+    if entity.domain.startswith("input_"):
+        return "helper"
+    if entity.domain in {"person", "device_tracker", "zone"}:
+        return "presence_location"
+    return entity.domain

app/main.py

@@ -3,6 +3,7 @@ import json
 import logging
 from contextlib import asynccontextmanager, suppress
 from collections.abc import AsyncIterator
+from datetime import datetime, timezone
 from pathlib import Path
 from typing import cast
 
@@ -19,6 +20,7 @@ from app.behavior.engine import BehaviorEngine
 from app.config import load_settings
 from app.core.exception_handlers import register_exception_handlers
 from app.ha.client import HaClient, HaClientSettings
+from app.ha.models import HaEntitySummary
 from app.ha.reader import HaReader
 from app.ml.registry.model_registry import ModelRegistry
 from backend.routes.ml import init_ml_routes
@@ -100,7 +102,7 @@ async def lifespan(app: FastAPI) -> AsyncIterator[None]:
 app = FastAPI(
     title="SillyHome Next API",
     description="Lokales Smart-Home-Intelligenzsystem für Home Assistant.",
-    version="0.7.7",
+    version="0.7.14",
     lifespan=lifespan,
 )
 app.state.settings = load_settings()
@@ -155,14 +157,20 @@ async def _ha_event_listener(app: FastAPI, client: HaClient) -> None:
     """Hört auf Home-Assistant-Websocket-Events und löst sofortige Vorhersagen aus."""
     settings = app.state.settings
     engine = app.state.behavior_engine
+    ha_reader = getattr(app.state, "ha_reader", None)
     store = app.state.actuator_store
-    if not isinstance(engine, BehaviorEngine) or not isinstance(store, ActuatorStore):
+    if (
+        not isinstance(engine, BehaviorEngine)
+        or not isinstance(store, ActuatorStore)
+        or not isinstance(ha_reader, HaReader)
+    ):
         logger.error("BehaviorEngine oder ActuatorStore nicht initialisiert")
         ws_status = getattr(app.state, "ws_status", None)
         if ws_status is not None:
             ws_status.status = "error"
             ws_status.error = "BehaviorEngine oder ActuatorStore nicht initialisiert"
         return
+    state_cache: dict[str, HaEntitySummary] = {}
     ha_url = str(settings.ha_url).rstrip("/")
     ws_url = ha_url.replace("http://", "ws://").replace("https://", "wss://") + "/api/websocket"
     auth_token = cast(str, settings.ha_token)
@@ -171,7 +179,7 @@ async def _ha_event_listener(app: FastAPI, client: HaClient) -> None:
         if ws_status is not None:
             ws_status.status = "connecting"
         try:
-            async with websockets.connect(ws_url) as websocket:
+            async with websockets.connect(ws_url, ping_interval=None) as websocket:
                 auth_required_msg = await websocket.recv()
                 auth_required_data = json.loads(auth_required_msg)
                 if auth_required_data.get("type") != "auth_required":
@@ -194,6 +202,7 @@ async def _ha_event_listener(app: FastAPI, client: HaClient) -> None:
                     continue
 
                 logger.info("WebSocket-Verbindung zu Home Assistant hergestellt")
+                state_cache = await asyncio.to_thread(_load_ha_state_cache, ha_reader)
                 if ws_status is not None:
                     ws_status.status = "connected"
                     ws_status.error = None
@@ -220,12 +229,15 @@ async def _ha_event_listener(app: FastAPI, client: HaClient) -> None:
                         entity_id = event_data.get("entity_id")
                         if not entity_id:
                             continue
+                        new_state = event_data.get("new_state")
+                        _update_ha_state_cache(state_cache, entity_id, new_state)
                         # Prüfe, ob Entity ein Aktor oder relevanter Kontext ist
                         # Sofortige Vorhersage für betroffene Aktoren auslösen
                         await asyncio.to_thread(
                             engine.handle_state_change,
                             entity_id,
-                            event_data.get("new_state"),
+                            new_state,
+                            current_entities=list(state_cache.values()),
                         )
                     except json.JSONDecodeError:
                         logger.warning("Ungültige JSON-Nachricht von HA-WebSocket")
@@ -252,7 +264,13 @@ async def _fallback_prediction(app: FastAPI) -> None:
     Dies verhindert kompletten Ausfall der Vorhersagen bei Netzwerkproblemen.
     """
     while True:
-        await asyncio.sleep(app.state.settings.prediction_interval_seconds)
+        ws_status = getattr(app.state, "ws_status", None)
+        websocket_connected = ws_status is not None and ws_status.status == "connected"
+        await asyncio.sleep(
+            app.state.settings.prediction_interval_seconds
+            if websocket_connected
+            else min(5, app.state.settings.prediction_interval_seconds)
+        )
         # Nur ausführen, wenn WebSocket nicht verbunden ist
         ws_status = getattr(app.state, "ws_status", None)
         if ws_status is None or ws_status.status != "connected":
@@ -263,3 +281,67 @@ async def _fallback_prediction(app: FastAPI) -> None:
                     ws_status.status if ws_status else "unavailable",
                 )
                 await asyncio.to_thread(engine.evaluate_all)
+
+
+def _load_ha_state_cache(reader: HaReader) -> dict[str, HaEntitySummary]:
+    return {entity.entity_id: entity for entity in reader.read_entities()}
+
+
+def _update_ha_state_cache(
+    state_cache: dict[str, HaEntitySummary],
+    entity_id: str,
+    new_state: object,
+) -> None:
+    if not isinstance(new_state, dict):
+        state_cache.pop(entity_id, None)
+        return
+    state_cache[entity_id] = _ha_entity_from_event(
+        entity_id,
+        new_state,
+        state_cache.get(entity_id),
+    )
+
+
+def _ha_entity_from_event(
+    entity_id: str,
+    new_state: dict[str, object],
+    previous: HaEntitySummary | None,
+) -> HaEntitySummary:
+    attributes = new_state.get("attributes")
+    attr = attributes if isinstance(attributes, dict) else {}
+    state_class = _optional_event_string(attr.get("state_class"))
+    device_class = _optional_event_string(attr.get("device_class"))
+    unit_of_measurement = _optional_event_string(attr.get("unit_of_measurement"))
+    friendly_name = _optional_event_string(attr.get("friendly_name"))
+    return HaEntitySummary(
+        entity_id=entity_id,
+        domain=entity_id.split(".", 1)[0],
+        state=_optional_event_string(new_state.get("state")),
+        last_changed=_event_datetime(new_state.get("last_changed"))
+        or _event_datetime(new_state.get("last_updated")),
+        state_class=state_class or (previous.state_class if previous else None),
+        device_class=device_class or (previous.device_class if previous else None),
+        unit_of_measurement=unit_of_measurement
+        or (previous.unit_of_measurement if previous else None),
+        friendly_name=friendly_name or (previous.friendly_name if previous else None),
+        area_id=previous.area_id if previous else None,
+        area_name=previous.area_name if previous else None,
+        device_id=previous.device_id if previous else None,
+        device_name=previous.device_name if previous else None,
+    )
+
+
+def _optional_event_string(value: object) -> str | None:
+    return value if isinstance(value, str) else None
+
+
+def _event_datetime(value: object) -> datetime | None:
+    if not isinstance(value, str):
+        return None
+    try:
+        parsed = datetime.fromisoformat(value.replace("Z", "+00:00"))
+    except ValueError:
+        return None
+    if parsed.tzinfo is None:
+        return parsed.replace(tzinfo=timezone.utc)
+    return parsed

app/static/index.html

@@ -134,9 +134,18 @@
           <option value="">Alle steuerbaren Typen</option>
           <option value="light">Lichter</option>
           <option value="switch">Schalter / Helper</option>
+          <option value="button">Buttons</option>
+          <option value="input_button">Helper-Buttons</option>
+          <option value="input_boolean">Helper-Schalter</option>
           <option value="cover">Rollläden / Cover</option>
+          <option value="climate">Heizungen / Klima</option>
+          <option value="lock">Schlösser</option>
           <option value="fan">Lüftung / Ventilatoren</option>
           <option value="humidifier">Befeuchter / Entfeuchter</option>
+          <option value="media_player">TV / Medien</option>
+          <option value="remote">Fernbedienungen</option>
+          <option value="number">Numerische Helper</option>
+          <option value="valve">Ventile</option>
         </select>
       </div>
       <div>
@@ -150,6 +159,7 @@
     </select>
     <button onclick="configureActuator()">Gerät hinzufügen und Beobachtung starten</button>
     <p id="actuator-config-result" class="muted">Noch kein Aktor ausgewählt.</p>
+    <div id="actuator-suggestions" class="card-list"></div>
   </section>
 
   <section class="wide" id="observed">
@@ -175,6 +185,7 @@ let currentActuatorId = null;
 let actuatorChoices = [];
 let contextOptions = [];
 let manualContextState = {options: [], selected: new Set()};
+const ACTUATOR_RESULT_LIMIT = 50;
 
 async function api(path, options = {}) {
   const response = await fetch(path, {headers: {"Content-Type": "application/json"}, ...options});
@@ -295,6 +306,7 @@ async function loadOverview() {
     chips.innerHTML = "";
   }
   await Promise.all([loadActuatorDiscovery(), loadConfiguredActuators()]);
+  void loadActuatorSuggestions();
 }
 
 async function loadActuatorDiscovery() {
@@ -317,13 +329,48 @@ async function loadActuatorDiscovery() {
   }
 }
 
+async function loadActuatorSuggestions() {
+  const box = document.getElementById("actuator-suggestions");
+  if (!box) return;
+  try {
+    const suggestions = await api("v1/actuators/suggestions");
+    box.innerHTML = suggestions.length ? `
+      <h3>Vorschläge aus bestehenden Zusammenhängen</h3>
+      ${suggestions.slice(0, 8).map(item => `
+        <article class="actuator-card">
+          <div class="card-title">
+            <div>
+              <div class="entity-id">${escapeHtml(item.entity_id)}</div>
+              <div class="muted">${escapeHtml(item.area_name || item.device_name || item.domain)}</div>
+            </div>
+            <span class="chip">${Math.round(item.confidence * 100)} %</span>
+          </div>
+          <p class="muted">${escapeHtml(item.reason)}</p>
+          <button class="secondary" onclick="configureSuggestedActuator('${escapeHtml(item.entity_id)}')">Vorschlag übernehmen</button>
+        </article>
+      `).join("")}
+    ` : "";
+  } catch (_) {
+    box.innerHTML = "";
+  }
+}
+
 function actuatorGroupLabel(domain) {
   const labels = {
+    button: "Buttons",
+    climate: "Heizungen / Klima",
     light: "Lichter",
-    switch: "Schalter / Helper",
+    input_boolean: "Helper-Schalter",
+    input_button: "Helper-Buttons",
+    lock: "Schlösser",
+    media_player: "TV / Medien",
+    number: "Numerische Helper",
+    remote: "Fernbedienungen",
+    switch: "Schalter / Steckdosen",
     cover: "Rollläden / Cover",
     fan: "Lüftung / Ventilatoren",
     humidifier: "Befeuchter / Entfeuchter",
+    valve: "Ventile",
   };
   return labels[domain] || domain;
 }
@@ -335,14 +382,17 @@ function renderActuatorSelect() {
   const query = normalizedSearch(document.getElementById("actuator-search")?.value || "");
   const filtered = actuatorChoices
     .filter(entity => !domain || entity.domain === domain)
-    .filter(entity => matchesSearch(entity, query))
+    .filter(entity => matchesSearch(entity, query));
-    .slice(0, 120);
+  const visible = filtered.slice(0, ACTUATOR_RESULT_LIMIT);
-  const domains = [...new Set(filtered.map(entity => entity.domain))].sort();
+  const domains = [...new Set(visible.map(entity => entity.domain))].sort();
+  const limitLabel = filtered.length > visible.length
+    ? ` - ${visible.length} von ${filtered.length}; Suche oder Typ weiter eingrenzen`
+    : "";
   select.innerHTML = [
-    `<option value="">${filtered.length ? "Gerät auswählen ..." : "Keine passenden Geräte gefunden"}</option>`,
+    `<option value="">${filtered.length ? `Gerät auswählen${limitLabel}` : "Keine passenden Geräte gefunden"}</option>`,
     ...domains.map(group => `
       <optgroup label="${escapeHtml(actuatorGroupLabel(group))}">
-        ${filtered
+        ${visible
           .filter(entity => entity.domain === group)
           .map(entity => `<option value="${escapeHtml(entity.entity_id)}">${escapeHtml(entityLabel(entity))}</option>`)
           .join("")}
@@ -468,6 +518,14 @@ async function showActuator(actuatorId, evaluationMessage = "") {
       .filter(candidate => contexts.includes(candidate.entity_id))
       .map(candidate => `<li><strong>${escapeHtml(candidate.friendly_name || candidate.entity_id)}</strong>: ${candidate.evidence.map(escapeHtml).join(", ") || "statistisch relevanter Kandidat"}</li>`)
       .join("");
+    const currentContextControls = contexts.length
+      ? `<ul>${contexts.map(entityId => `
+          <li>
+            <code>${escapeHtml(entityId)}</code>
+            <button class="secondary compact" onclick="removeContextEntity('${escapeHtml(record.actuator_entity_id)}', '${escapeHtml(entityId)}')">Entfernen</button>
+          </li>
+        `).join("")}</ul>`
+      : "<p class='muted'>Noch keine Kontext-Entity ausgewählt.</p>";
     const prediction = record.behavior.prediction;
     const learnedAutomationActions = record.behavior.patterns.filter(
       pattern => pattern.source === "automation",
@@ -574,11 +632,17 @@ async function showActuator(actuatorId, evaluationMessage = "") {
       ${prediction
         ? `<p><strong>${escapeHtml(prediction.target_state)}</strong> mit ${Math.round(prediction.confidence * 100)} % Sicherheit. ${escapeHtml(prediction.reason)} <span class="${prediction.executed ? "ok" : "muted"}">${escapeHtml(prediction.execution_reason)}</span></p>`
         : "<p class='muted'>Aktuell ist kein gelerntes Handlungsmuster fällig.</p>"}
+      <div class="actions">
+        <button class="secondary" onclick="sendFeedback('${escapeHtml(record.actuator_entity_id)}', true)">Vorhersage korrekt</button>
+        <button class="secondary" onclick="sendFeedback('${escapeHtml(record.actuator_entity_id)}', false)">Vorhersage falsch</button>
+      </div>
       <h3>Passende Home-Assistant-Automationen</h3>
       <p class="muted">Bei einer Übernahme pausiert SillyHome diese Automationen. Beim Stoppen können sie gezielt fortgesetzt werden.</p>
       ${automationControls}
       <h3>Welche Zusammenhänge automatisch verwendet werden</h3>
       ${evidence ? `<ul>${evidence}</ul>` : "<p class='warn'>Noch kein geeigneter Kontext erkannt. SillyHome prüft bei neuen HA-Daten erneut.</p>"}
+      <h3>Verwendete Sensoren/Zustände ändern</h3>
+      ${currentContextControls}
       ${manualAssignment}
     `;
     document.getElementById("detail").scrollIntoView({behavior: "smooth", block: "start"});
@@ -613,6 +677,34 @@ async function saveManualAssignment(actuatorId) {
   }
 }
 
+async function removeContextEntity(actuatorId, entityId) {
+  try {
+    const record = await api(`v1/actuators/${encodeURIComponent(actuatorId)}`);
+    const numericEntityId = record.assignment.selected_numeric_entity_id === entityId
+      ? null
+      : record.assignment.selected_numeric_entity_id;
+    const contextEntityIds = (record.assignment.selected_context_entity_ids || [])
+      .filter(id => id !== entityId);
+    await api(`v1/actuators/${encodeURIComponent(actuatorId)}/assignment`, {
+      method: "POST",
+      body: JSON.stringify({
+        numeric_entity_id: numericEntityId,
+        context_entity_ids: contextEntityIds,
+        note: `Entity ${entityId} entfernt`,
+      }),
+    });
+    await loadConfiguredActuators();
+    await showActuator(actuatorId, "Kontext-Entity entfernt.");
+  } catch (error) {
+    alert(error.message);
+  }
+}
+
+async function configureSuggestedActuator(actuatorId) {
+  document.getElementById("actuator-input").value = actuatorId;
+  await configureActuator();
+}
+
 async function evaluateActuator(actuatorId) {
   try {
     const record = await api(
@@ -632,6 +724,23 @@ async function evaluateActuator(actuatorId) {
   }
 }
 
+async function sendFeedback(actuatorId, correct) {
+  const expectedState = correct ? null : prompt("Welcher Zustand wäre korrekt gewesen? Leer lassen, wenn nur abwerten.");
+  try {
+    await api(`v1/actuators/${encodeURIComponent(actuatorId)}/feedback`, {
+      method: "POST",
+      body: JSON.stringify({
+        correct,
+        expected_state: expectedState || null,
+      }),
+    });
+    await loadConfiguredActuators();
+    await showActuator(actuatorId, correct ? "Vorhersage als korrekt gelernt." : "Vorhersage als falsch markiert.");
+  } catch (error) {
+    alert(error.message);
+  }
+}
+
 async function setActivation(actuatorId, active, pauseMatchingAutomations, restorePausedAutomations) {
   const question = active
     ? pauseMatchingAutomations

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "sillyhome-next"
-version = "0.7.7"
+version = "0.7.14"
 description = "Lokales Smart-Home-Intelligenzsystem für Home Assistant"
 requires-python = ">=3.11"
 dependencies = [

tests/actuators/test_lifecycle.py

@@ -277,6 +277,39 @@ def test_reconciliation_ignores_generic_monitoring_area_for_automatic_context(
     assert record.lifecycle.status is LifecycleStatus.ARCHIVED
 
 
+def test_reconciliation_does_not_auto_select_overload_sensors_by_power_area(
+    tmp_path: Path,
+) -> None:
+    entities = [
+        HaEntitySummary(
+            entity_id="light.treppe_unten",
+            domain="light",
+            friendly_name="Licht Treppe Unten",
+            area_name="Strom",
+        ),
+        HaEntitySummary(
+            entity_id="binary_sensor.shelly_schrank_channel_1_overload",
+            domain="binary_sensor",
+            device_class="problem",
+            friendly_name="Shelly Schrank Channel 1 Überlast",
+            area_name="Strom",
+        ),
+        HaEntitySummary(
+            entity_id="binary_sensor.terrasse_terasse_overheating",
+            domain="binary_sensor",
+            device_class="problem",
+            friendly_name="Terrasse Terasse Überhitzung",
+            area_name="Strom",
+        ),
+    ]
+    service = _service(tmp_path, entities, {})
+
+    record = service.configure_actuator("light.treppe_unten")
+
+    assert record.assignment.selected_context_entity_ids == []
+    assert all(candidate.auto_accepted is False for candidate in record.context_candidates)
+
+
 def test_manual_assignment_persists_and_wins_over_automatic_mapping(tmp_path: Path) -> None:
     start = datetime(2026, 6, 1, tzinfo=timezone.utc)
     entities = [

tests/api/test_actuators.py

@@ -9,6 +9,7 @@ from app.actuators.lifecycle import ActuatorReconciliationService
 from app.actuators.store import ActuatorStore
 from app.behavior.engine import BehaviorEngine
 from app.config import Settings
+from app.api.v1.actuators import _deduplicate_actuator_ids
 from app.ha.discovery import DiscoveredEntity
 from app.ha.discovery import discover_entities
 from app.ha.history import (
@@ -227,3 +228,37 @@ def test_context_options_returns_learnable_entities(tmp_path: Path) -> None:
     assert "sensor.abstellkammer_illuminance" in entity_ids
     assert "binary_sensor.abstellkammer_motion" in entity_ids
     assert "sensor.pfsense_interface_vpn_inbytes" not in entity_ids
+
+
+def test_actuator_discovery_prefers_light_over_duplicate_switch() -> None:
+    entities = {
+        "light.schreibtisch": HaEntitySummary(
+            entity_id="light.schreibtisch",
+            domain="light",
+            friendly_name="Schreibtisch Licht",
+            device_id="device-1",
+        ),
+        "switch.schreibtisch": HaEntitySummary(
+            entity_id="switch.schreibtisch",
+            domain="switch",
+            friendly_name="Schreibtisch Schalter",
+            device_id="device-1",
+        ),
+        "cover.rollladen": HaEntitySummary(
+            entity_id="cover.rollladen",
+            domain="cover",
+            friendly_name="Rollladen",
+            device_id="device-2",
+        ),
+    }
+
+    result = _deduplicate_actuator_ids(
+        [
+            ("switch.schreibtisch", "switch_socket"),
+            ("light.schreibtisch", "light"),
+            ("cover.rollladen", "cover_shutter"),
+        ],
+        entities,
+    )
+
+    assert result == ["cover.rollladen", "light.schreibtisch"]

tests/api/test_entities.py

@@ -27,6 +27,7 @@ class FakeHaReader(HaReader):
             entity_id="sensor.temperature",
             domain="sensor",
             device_class="temperature",
+            category="temperature",
             role=EntityRole.MEASUREMENT,
             learnable=True,
             reason="Numerischer Messsensor für Zeitreihen und Training.",
@@ -116,6 +117,7 @@ def test_discovery_filters_entities() -> None:
             "device_class": "temperature",
             "state_class": None,
             "unit_of_measurement": None,
+            "category": "temperature",
             "role": "measurement",
             "learnable": True,
             "reason": "Numerischer Messsensor für Zeitreihen und Training.",

tests/behavior/test_engine.py

@@ -8,6 +8,7 @@ import pytest
 from app.actuators.models import (
     BehaviorMode,
     BehaviorPattern,
+    BehaviorPrediction,
     BehaviorState,
     BehaviorStatus,
     ExecutionEvent,
@@ -212,6 +213,125 @@ def test_engine_counts_known_automation_actions_like_manual_actions(
     assert {pattern.weight for pattern in trained.behavior.patterns} == {1.0}
 
 
+def test_feedback_marks_prediction_correct_as_learning_pattern(
+    tmp_path: Path,
+) -> None:
+    now = datetime.now(timezone.utc).replace(second=0, microsecond=0)
+    settings = _settings(tmp_path)
+    store = ActuatorStore(settings.actuator_store)
+    record = store.configure("light.office")
+    record = record.model_copy(
+        update={
+            "assignment": record.assignment.model_copy(
+                update={
+                    "selected_context_entity_ids": [
+                        "binary_sensor.office_presence"
+                    ],
+                }
+            ),
+            "behavior": record.behavior.model_copy(
+                update={
+                    "prediction": BehaviorPrediction(
+                        target_state="on",
+                        confidence=0.9,
+                        generated_at=now,
+                        reason="test",
+                    )
+                }
+            ),
+        }
+    )
+    store.upsert(record)
+    reader = FakeBehaviorReader(
+        entities=[
+            HaEntitySummary(entity_id="light.office", domain="light", state="off"),
+            HaEntitySummary(
+                entity_id="binary_sensor.office_presence",
+                domain="binary_sensor",
+                state="on",
+            ),
+        ],
+        history=[],
+        logbook=[],
+    )
+    engine = BehaviorEngine(ha_reader=reader, store=store, settings=settings)
+
+    result = engine.record_feedback("light.office", correct=True)
+
+    assert result.behavior.patterns[-1].target_state == "on"
+    assert result.behavior.patterns[-1].context_states == {
+        "binary_sensor.office_presence": "on"
+    }
+    assert result.behavior.patterns[-1].source == "user_feedback"
+    assert result.behavior.reason == "Vorhersage wurde vom Nutzer als korrekt bestätigt."
+
+
+def test_feedback_marks_prediction_wrong_and_adds_correction(
+    tmp_path: Path,
+) -> None:
+    now = datetime.now(timezone.utc).replace(second=0, microsecond=0)
+    settings = _settings(tmp_path)
+    store = ActuatorStore(settings.actuator_store)
+    record = store.configure("light.office")
+    record = record.model_copy(
+        update={
+            "assignment": record.assignment.model_copy(
+                update={
+                    "selected_context_entity_ids": [
+                        "binary_sensor.office_presence"
+                    ],
+                }
+            ),
+            "behavior": record.behavior.model_copy(
+                update={
+                    "patterns": [
+                        BehaviorPattern(
+                            target_state="on",
+                            minute_of_day=60,
+                            weekday=0,
+                            context_states={"binary_sensor.office_presence": "on"},
+                            source="automation",
+                            weight=1.0,
+                            observed_at=now - timedelta(days=1),
+                        )
+                    ],
+                    "prediction": BehaviorPrediction(
+                        target_state="on",
+                        confidence=0.9,
+                        generated_at=now,
+                        reason="test",
+                    ),
+                }
+            ),
+        }
+    )
+    store.upsert(record)
+    reader = FakeBehaviorReader(
+        entities=[
+            HaEntitySummary(entity_id="light.office", domain="light", state="off"),
+            HaEntitySummary(
+                entity_id="binary_sensor.office_presence",
+                domain="binary_sensor",
+                state="on",
+            ),
+        ],
+        history=[],
+        logbook=[],
+    )
+    engine = BehaviorEngine(ha_reader=reader, store=store, settings=settings)
+
+    result = engine.record_feedback(
+        "light.office",
+        correct=False,
+        expected_state="off",
+    )
+
+    assert result.behavior.patterns[0].weight == 0.1
+    assert result.behavior.patterns[-1].target_state == "off"
+    assert result.behavior.patterns[-1].source == "user_correction"
+    assert result.behavior.reason == "Vorhersage wurde vom Nutzer als falsch markiert."
+
+
 def test_engine_learns_causal_automation_with_activation_credit(
     tmp_path: Path,
 ) -> None:
@@ -438,6 +558,7 @@ def test_cooldown_allows_opposite_follow_up_action(tmp_path: Path) -> None:
     ("domain", "state", "service"),
     [
         ("light", "on", "turn_on"),
+        ("media_player", "off", "turn_off"),
         ("switch", "off", "turn_off"),
         ("cover", "open", "open_cover"),
         ("cover", "closed", "close_cover"),
@@ -523,3 +644,137 @@ def test_prediction_ignores_stale_causal_context_state() -> None:
         min_support=1,
         window_minutes=30,
     ) is None
+
+
+def test_state_change_uses_websocket_context_state_for_immediate_action(
+    tmp_path: Path,
+) -> None:
+    now = datetime.now(timezone.utc).replace(microsecond=0)
+    settings = _settings(tmp_path)
+    store = ActuatorStore(settings.actuator_store)
+    record = store.configure("light.storage")
+    record = record.model_copy(
+        update={
+            "assignment": record.assignment.model_copy(
+                update={
+                    "selected_context_entity_ids": ["binary_sensor.storage_door"],
+                }
+            ),
+            "behavior": record.behavior.model_copy(
+                update={
+                    "mode": BehaviorMode.ACTIVE,
+                    "status": BehaviorStatus.TRAINED,
+                    "activation_ready": True,
+                    "patterns": [
+                        BehaviorPattern(
+                            target_state="on",
+                            minute_of_day=60,
+                            weekday=0,
+                            context_states={"binary_sensor.storage_door": "on"},
+                            trigger_entity_id="binary_sensor.storage_door",
+                            trigger_from_state="off",
+                            trigger_to_state="on",
+                            source="automation",
+                            weight=1.0,
+                            observed_at=now - timedelta(days=days_ago),
+                        )
+                        for days_ago in (3, 2, 1)
+                    ],
+                }
+            ),
+        }
+    )
+    store.upsert(record)
+    reader = FakeBehaviorReader(
+        entities=[
+            HaEntitySummary(entity_id="light.storage", domain="light", state="off"),
+            HaEntitySummary(
+                entity_id="binary_sensor.storage_door",
+                domain="binary_sensor",
+                state="off",
+                last_changed=now - timedelta(minutes=5),
+            ),
+        ],
+        history=[],
+        logbook=[],
+    )
+    engine = BehaviorEngine(ha_reader=reader, store=store, settings=settings)
+
+    engine.handle_state_change(
+        "binary_sensor.storage_door",
+        {"state": "on", "last_changed": now.isoformat()},
+    )
+
+    assert reader.service_calls == [
+        ("light", "turn_on", {"entity_id": "light.storage"})
+    ]
+
+
+def test_state_change_uses_event_cache_without_rest_state_query(
+    tmp_path: Path,
+) -> None:
+    now = datetime.now(timezone.utc).replace(microsecond=0)
+    settings = _settings(tmp_path)
+    store = ActuatorStore(settings.actuator_store)
+    record = store.configure("light.storage")
+    record = record.model_copy(
+        update={
+            "assignment": record.assignment.model_copy(
+                update={
+                    "selected_context_entity_ids": ["binary_sensor.storage_door"],
+                }
+            ),
+            "behavior": record.behavior.model_copy(
+                update={
+                    "mode": BehaviorMode.ACTIVE,
+                    "status": BehaviorStatus.TRAINED,
+                    "activation_ready": True,
+                    "patterns": [
+                        BehaviorPattern(
+                            target_state="on",
+                            minute_of_day=60,
+                            weekday=0,
+                            context_states={"binary_sensor.storage_door": "on"},
+                            trigger_entity_id="binary_sensor.storage_door",
+                            trigger_from_state="off",
+                            trigger_to_state="on",
+                            source="automation",
+                            weight=1.0,
+                            observed_at=now - timedelta(days=days_ago),
+                        )
+                        for days_ago in (3, 2, 1)
+                    ],
+                }
+            ),
+        }
+    )
+    store.upsert(record)
+    reader = FakeBehaviorReader(
+        entities=[],
+        history=[],
+        logbook=[],
+    )
+
+    def fail_read_entities() -> list[HaEntitySummary]:
+        raise AssertionError("Event-Auswertung darf keinen REST-State lesen.")
+
+    reader.read_entities = fail_read_entities  # type: ignore[method-assign]
+    engine = BehaviorEngine(ha_reader=reader, store=store, settings=settings)
+
+    engine.handle_state_change(
+        "binary_sensor.storage_door",
+        {"state": "on", "last_changed": now.isoformat()},
+        current_entities=[
+            HaEntitySummary(entity_id="light.storage", domain="light", state="off"),
+            HaEntitySummary(
+                entity_id="binary_sensor.storage_door",
+                domain="binary_sensor",
+                state="on",
+                last_changed=now,
+            ),
+        ],
+    )
+
+    assert reader.service_calls == [
+        ("light", "turn_on", {"entity_id": "light.storage"})
+    ]

tests/ha/test_discovery.py

@@ -74,3 +74,60 @@ def test_discovery_filters_domain_and_learnable() -> None:
     result = discover_entities(entities, domains={" SENSOR "}, learnable=True)
 
     assert [item.entity_id for item in result] == ["sensor.temperature"]
+
+
+@pytest.mark.parametrize(
+    ("entity", "category"),
+    [
+        (
+            HaEntitySummary(entity_id="climate.bad", domain="climate"),
+            "heating",
+        ),
+        (
+            HaEntitySummary(entity_id="lock.front_door", domain="lock"),
+            "lock",
+        ),
+        (
+            HaEntitySummary(entity_id="input_boolean.sleep_mode", domain="input_boolean"),
+            "helper",
+        ),
+        (
+            HaEntitySummary(entity_id="media_player.tv", domain="media_player"),
+            "media_tv",
+        ),
+        (
+            HaEntitySummary(
+                entity_id="sensor.brightness",
+                domain="sensor",
+                device_class="illuminance",
+            ),
+            "brightness",
+        ),
+        (
+            HaEntitySummary(
+                entity_id="binary_sensor.motion",
+                domain="binary_sensor",
+                device_class="motion",
+            ),
+            "presence_motion",
+        ),
+    ],
+)
+def test_classify_entity_categories(entity: HaEntitySummary, category: str) -> None:
+    assert classify_entity(entity).category == category
+
+
+@pytest.mark.parametrize(
+    "entity",
+    [
+        HaEntitySummary(entity_id="automation.lights", domain="automation"),
+        HaEntitySummary(entity_id="update.core", domain="update"),
+    ],
+)
+def test_classify_excludes_non_actuator_management_entities(
+    entity: HaEntitySummary,
+) -> None:
+    result = classify_entity(entity)
+
+    assert result.role is EntityRole.UNSUPPORTED
+    assert result.learnable is False

tests/test_main.py

@@ -1,4 +1,5 @@
 import asyncio
+from collections.abc import Sequence
 from pathlib import Path
 from unittest.mock import MagicMock, patch
 
@@ -8,6 +9,8 @@ from fastapi.testclient import TestClient
 
 from app.actuators.store import ActuatorStore
 from app.behavior.engine import BehaviorEngine
+from app.ha.models import HaEntitySummary
+from app.ha.reader import HaReader
 from app.main import _ha_event_listener, app as fastapi_app, lifespan
 
 
@@ -41,10 +44,32 @@ class _RecordingBehaviorEngine(BehaviorEngine):
             store=ActuatorStore(tmp_path / "actuators"),
             settings=MagicMock(),
         )
-        self.state_changes: list[tuple[str, dict[str, object] | None]] = []
+        self.state_changes: list[
+            tuple[str, dict[str, object] | None, Sequence[HaEntitySummary] | None]
+        ] = []
 
-    def handle_state_change(self, entity_id: str, new_state: dict[str, object] | None) -> None:
+    def handle_state_change(
-        self.state_changes.append((entity_id, new_state))
+        self,
+        entity_id: str,
+        new_state: dict[str, object] | None,
+        *,
+        current_entities: Sequence[HaEntitySummary] | None = None,
+    ) -> None:
+        self.state_changes.append((entity_id, new_state, current_entities))
+
+
+class _FakeHaReader(HaReader):
+    def __init__(self) -> None:
+        pass
+
+    def read_entities(self) -> list[HaEntitySummary]:
+        return [
+            HaEntitySummary(
+                entity_id="light.test",
+                domain="light",
+                state="off",
+            )
+        ]
 
 
 def test_ha_event_listener_processes_state_change(tmp_path: Path) -> None:
@@ -61,12 +86,16 @@ def test_ha_event_listener_processes_state_change(tmp_path: Path) -> None:
             ]
         )
 
-        with patch("websockets.connect", return_value=fake_ws):
+        with patch("websockets.connect", return_value=fake_ws) as connect:
             try:
                 await _ha_event_listener(mock_app, mock_client)
             except asyncio.CancelledError:
                 pass
 
+        connect.assert_called_once_with(
+            "ws://homeassistant:8123/api/websocket",
+            ping_interval=None,
+        )
         assert fake_ws.sent == [
             {"type": "auth", "access_token": "test-token"},
             {"id": 1, "type": "subscribe_events", "event_type": "state_changed"},
@@ -79,12 +108,19 @@ def test_ha_event_listener_processes_state_change(tmp_path: Path) -> None:
     mock_app.state.ws_status = MagicMock()
     mock_engine = _RecordingBehaviorEngine(tmp_path)
     mock_app.state.behavior_engine = mock_engine
+    mock_app.state.ha_reader = _FakeHaReader()
     mock_store = ActuatorStore(tmp_path / "store")
     mock_app.state.actuator_store = mock_store
     mock_client = MagicMock()
 
     anyio.run(run_test)
-    assert mock_engine.state_changes == [("light.test", {"state": "on"})]
+    assert len(mock_engine.state_changes) == 1
+    entity_id, new_state, current_entities = mock_engine.state_changes[0]
+    assert entity_id == "light.test"
+    assert new_state == {"state": "on"}
+    assert current_entities == [
+        HaEntitySummary(entity_id="light.test", domain="light", state="on")
+    ]
     assert mock_app.state.ws_status.status == "connected"
     assert mock_app.state.ws_status.error is None