Rework dashboard loading and cache entity metadata

CHANGELOG.md

@@ -1,5 +1,96 @@
 # Changelog
 
+## 0.7.21 - 2026-06-17
+- Dashboard-Ladepfad getrennt: beobachtete Geräte laden sofort über
+  `/v1/actuators/summary`; Status, Discovery und Vorschläge laufen unabhängig
+  nachgelagert und blockieren die Übersicht nicht mehr.
+- Systemstatus nutzt Timeouts und bleibt auch bei langsamem ML-/HA-Status
+  bedienbar.
+- HA-Entity-Metadaten werden als JSON-Cache gespeichert und für Friendly Name,
+  Raum und Gerät in schlanken Summaries wiederverwendet.
+- Anleitung, Gerätegruppen und manuelle Kontextauswahl sind aufklappbar und
+  kompakter für Smartphone- und Desktopansichten.
+
+## 0.7.20 - 2026-06-17
+- Dashboard-Übersicht ist kompatibel mit dem leichten Summary-Format und greift
+  nicht mehr auf `record.behavior.status` aus dem Vollformat zu.
+
+## 0.7.19 - 2026-06-17
+- Dashboard-Übersicht nutzt einen leichten `/v1/actuators/summary`-Endpunkt
+  statt voller Lernmuster und kompletter HA-Entityliste.
+- Nach Aktionen werden Dashboard-Caches gezielt invalidiert, damit keine
+  stale oder doppelt geladenen Einträge entstehen.
+
+## 0.7.18 - 2026-06-16
+- Dashboard lädt Aktoren, Entities und Discovery nur noch einmal pro Refresh und
+  rendert daraus Auswahl und Übersicht ohne doppelte API-Ladewege.
+- Manuelle Kontext-Evidenz wird dedupliziert, damit Hinweise wie
+  "Manuell vom Nutzer als relevant festgelegt" nicht mehrfach erscheinen.
+- Kontextauswahl ist vollständiger: Feuchte, Wetter, Licht-/Schalterzustände,
+  Bewegungs-/Tür-/Präsenzmelder, PV/Akku/Einspeisung und Helper werden sauberer
+  kategorisiert und per Suche/Kategorie erreichbar.
+- Domainspezifische Zuordnung geschärft: Lüftungen bevorzugen Feuchte/Temperatur,
+  Lichter Helligkeit/Bewegung/Tür/Präsenz, Heizungen Temperatur/Anwesenheit/Wetter.
+
+## 0.7.17 - 2026-06-16
+- WebSocket-Eventpfad ist schneller: irrelevante HA-State-Changes werden vor
+  dem teuren State-Cache-Listenbau verworfen.
+- WebSocket nutzt Keepalive und reconnectet nach Abbrüchen nach 1s statt 5s.
+
+## 0.7.16 - 2026-06-16
+- Beobachtete Aktoren werden in der Übersicht nach Raum oder Typ gruppiert und
+  mit Friendly Name angezeigt.
+
+## 0.7.15 - 2026-06-16
+- Add-on-Start ist robust gegen Home-Assistant-Core-502 beim Systemboot:
+  API und WebSocket-Listener starten trotzdem, Reconciliation/Training werden
+  im Hintergrund mit Retry nachgeholt.
+- Periodische Reconciliation und Fallback-Auswertung beenden den Dienst nicht
+  mehr bei temporären HA-Fehlern.
+- Add-on-Watchdog prüft `/health`, damit Supervisor den Dienst nach Absturz
+  wieder starten kann.
+
+## 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

addon/config.yaml

@@ -1,5 +1,5 @@
 name: SillyHome Next
-version: "0.7.8"
+version: "0.7.21"
 slug: sillyhome_next
 description: Lernt automatisch aus deinem Verhalten und steuert freigegebene Aktoren
 url: http://192.168.6.31:3000/pino/sillyhome-next
@@ -7,6 +7,7 @@ arch:
   - amd64
 startup: application
 boot: auto
+watchdog: http://[HOST]:[PORT:8000]/health
 init: false
 ingress: true
 ingress_port: 8000

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
@@ -72,38 +72,71 @@ _MANUAL_CONTEXT_DOMAINS = frozenset({
     "device_tracker",
     "fan",
     "humidifier",
+    "input_boolean",
+    "input_number",
+    "input_select",
     "light",
+    "media_player",
     "person",
+    "remote",
+    "scene",
     "sensor",
+    "sun",
     "switch",
     "weather",
 })
-_CONTEXT_SUGGESTION_LIMIT = 120
+_CONTEXT_SUGGESTION_LIMIT = 500
 _OUTDOOR_TOKENS = frozenset({"aussen", "außen", "outdoor", "garten", "terrasse", "balkon"})
 _DIAGNOSTIC_TOKENS = frozenset({
     "basic",
     "battery",
+    "bytes",
     "connect",
     "count",
+    "data",
     "diagnostic",
     "firmware",
     "gesehen",
+    "heat",
+    "inbytes",
+    "interface",
     "last",
     "linkquality",
     "knoten",
     "knotens",
     "mqtt",
     "node",
+    "outbytes",
+    "pfsense",
     "reason",
     "restart",
     "rssi",
     "signal",
     "ssid",
     "status",
+    "overheat",
+    "overheating",
+    "overload",
     "uptime",
+    "vpn",
+    "uberhitzung",
+    "ueberhitzung",
+    "ueberlast",
+    "überhitzung",
+    "überlast",
     "wifi",
     "zuletzt",
 })
+_AUTO_CONTEXT_CLASSES = frozenset({
+    "door",
+    "garage_door",
+    "illuminance",
+    "motion",
+    "occupancy",
+    "opening",
+    "presence",
+    "window",
+})
 
 
 class ActuatorReconciliationService:
@@ -156,13 +189,10 @@ class ActuatorReconciliationService:
             selected = entity.entity_id in selected_ids
             if selected:
                 score = max(score, 1.0)
-            if not selected and (
-                _is_diagnostic_context(entity)
-                or not _has_context_relationship(actuator, entity)
-            ):
-                continue
-            if not selected and score < 0.1:
+            if not selected and _is_diagnostic_context(entity):
                 continue
+            if not selected and not _has_context_relationship(actuator, entity):
+                score = max(score, 0.01)
             ranked.append((score, _context_sort_group(entity), entity))
         ranked.sort(
             key=lambda item: (
@@ -628,8 +658,12 @@ 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 +777,23 @@ 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,
@@ -809,12 +860,17 @@ def _merge_manual_candidates(
     for entity_id in selected_entity_ids:
         existing = by_id.get(entity_id)
         if existing is not None:
+            evidence = [
+                item
+                for item in existing.evidence
+                if item != "Manuell vom Nutzer als relevant festgelegt."
+            ]
             by_id[entity_id] = existing.model_copy(
                 update={
                     "auto_accepted": True,
                     "confidence": 1.0,
                     "evidence": [
-                        *existing.evidence,
+                        *evidence,
                         "Manuell vom Nutzer als relevant festgelegt.",
                     ],
                 }
@@ -843,13 +899,28 @@ def _merge_manual_candidates(
 
 def _preferred_device_classes(domain: str, *, context: bool) -> frozenset[str]:
     if context:
-        return frozenset({"door", "garage_door", "motion", "occupancy", "opening", "presence"})
+        mapping = {
+            "climate": {"occupancy", "presence", "window"},
+            "cover": {"illuminance", "wind_speed"},
+            "fan": {"humidity", "moisture", "occupancy", "presence", "temperature"},
+            "humidifier": {"humidity", "moisture", "temperature"},
+            "light": {"door", "garage_door", "motion", "occupancy", "opening", "presence", "window"},
+            "switch": {"door", "garage_door", "motion", "occupancy", "opening", "presence", "window"},
+        }
+        return frozenset(
+            mapping.get(
+                domain,
+                {"door", "garage_door", "motion", "occupancy", "opening", "presence"},
+            )
+        )
     mapping = {
-        "climate": {"temperature", "humidity", "power"},
+        "climate": {"temperature", "humidity"},
         "cover": {"illuminance", "temperature", "wind_speed"},
-        "fan": {"temperature", "humidity", "power"},
-        "humidifier": {"humidity", "temperature", "power"},
-        "light": {"illuminance", "power", "energy"},
+        "fan": {"temperature", "humidity", "moisture"},
+        "humidifier": {"humidity", "moisture", "temperature"},
+        "light": {"illuminance"},
+        "media_player": {"power", "energy"},
+        "remote": {"battery"},
         "switch": {"power", "energy", "current"},
         "valve": {"temperature", "pressure", "humidity"},
     }

app/api/v1/actuators.py

@@ -1,5 +1,10 @@
 from __future__ import annotations
 
+import json
+import os
+from datetime import datetime, timezone
+from pathlib import Path
+
 from fastapi import APIRouter, Depends, HTTPException, Query, Request, status
 from pydantic import BaseModel, Field
 
@@ -7,8 +12,9 @@ from app.actuators.lifecycle import ActuatorReconciliationService
 from app.actuators.models import ActuatorRecord, ReconciliationState
 from app.actuators.store import ActuatorStore
 from app.behavior.engine import BehaviorEngine
+from app.config import Settings
 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 +44,126 @@ 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
+
+
+class ActuatorSummary(BaseModel):
+    actuator_entity_id: str
+    domain: str
+    friendly_name: str | None = None
+    area_name: str | None = None
+    device_name: str | None = None
+    enabled: bool
+    behavior_mode: str
+    behavior_status: str
+    lifecycle_status: str
+    activation_ready: bool
+    activation_reason: str
+    sample_count: int
+    prediction_target_state: str | None = None
+    prediction_confidence: float | None = None
+    updated_at: str
+
+
 @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()}
+def discover_actuators(
+    request: Request,
+    refresh: bool = Query(default=False),
+    ha_reader: HaReader = Depends(get_ha_reader),
+) -> list[HaEntitySummary]:
+    cached_entities = [] if refresh else _load_cached_entities(request)
+    if cached_entities:
+        entities = {entity.entity_id: entity for entity in cached_entities}
+    else:
+        fresh_entities = list(ha_reader.read_entities())
+        _save_cached_entities(request, fresh_entities)
+        entities = {entity.entity_id: entity for entity in fresh_entities}
     discovered = ha_reader.discover()
-    actuator_ids = sorted(
-        entity.entity_id for entity in discovered if entity.role is EntityRole.ACTUATOR
+    actuator_ids = _deduplicate_actuator_ids(
+        [
+            (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,
@@ -61,6 +177,51 @@ def context_options(
         raise HTTPException(status_code=404, detail=str(exc)) from exc
 
 
+@router.get("/summary", response_model=list[ActuatorSummary])
+def list_configured_summary(request: Request) -> list[ActuatorSummary]:
+    entity_map = {entity.entity_id: entity for entity in _load_cached_entities(request)}
+    return [
+        ActuatorSummary(
+            actuator_entity_id=record.actuator_entity_id,
+            domain=record.actuator_entity_id.split(".", 1)[0],
+            friendly_name=(
+                entity_map[record.actuator_entity_id].friendly_name
+                if record.actuator_entity_id in entity_map
+                else None
+            ),
+            area_name=(
+                entity_map[record.actuator_entity_id].area_name
+                if record.actuator_entity_id in entity_map
+                else None
+            ),
+            device_name=(
+                entity_map[record.actuator_entity_id].device_name
+                if record.actuator_entity_id in entity_map
+                else None
+            ),
+            enabled=record.enabled,
+            behavior_mode=record.behavior.mode.value,
+            behavior_status=record.behavior.status.value,
+            lifecycle_status=record.lifecycle.status.value,
+            activation_ready=record.behavior.activation_ready,
+            activation_reason=record.behavior.activation_reason,
+            sample_count=record.behavior.sample_count,
+            prediction_target_state=(
+                record.behavior.prediction.target_state
+                if record.behavior.prediction is not None
+                else None
+            ),
+            prediction_confidence=(
+                record.behavior.prediction.confidence
+                if record.behavior.prediction is not None
+                else None
+            ),
+            updated_at=record.updated_at.isoformat(),
+        )
+        for record in _service(request).list_configured()
+    ]
+
+
 @router.get("", response_model=list[ActuatorRecord])
 def list_configured(request: Request) -> list[ActuatorRecord]:
     return _service(request).list_configured()
@@ -116,6 +277,22 @@ 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 +410,141 @@ def _behavior(request: Request) -> BehaviorEngine:
             detail="Verhaltenslernen ist nicht initialisiert.",
         )
     return engine
+
+
+def _entity_cache_path(request: Request) -> Path:
+    store = getattr(request.app.state, "actuator_store", None)
+    settings = getattr(request.app.state, "settings", None)
+    if isinstance(store, ActuatorStore):
+        base_dir = store._root
+    elif isinstance(settings, Settings):
+        base_dir = Path(settings.actuator_store).resolve().parent
+    else:
+        base_dir = Path(".").resolve()
+    return Path(os.getenv("SILLYHOME_ENTITY_CACHE", base_dir / "ha_entity_cache.json"))
+
+
+def _load_cached_entities(request: Request) -> list[HaEntitySummary]:
+    path = _entity_cache_path(request)
+    if not path.exists():
+        return []
+    try:
+        payload = json.loads(path.read_text(encoding="utf-8"))
+        raw_entities = payload.get("entities", [])
+        return [HaEntitySummary.model_validate(entity) for entity in raw_entities]
+    except (OSError, TypeError, ValueError):
+        return []
+
+
+def _save_cached_entities(request: Request, entities: list[HaEntitySummary]) -> None:
+    path = _entity_cache_path(request)
+    path.parent.mkdir(parents=True, exist_ok=True)
+    payload = {
+        "updated_at": datetime.now(timezone.utc).isoformat(),
+        "entities": [entity.model_dump(mode="json") for entity in entities],
+    }
+    temporary = path.with_suffix(".json.tmp")
+    temporary.write_text(
+        json.dumps(payload, ensure_ascii=True, sort_keys=True) + "\n",
+        encoding="utf-8",
+    )
+    os.replace(temporary, path)
+
+
+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:
-            entities = {entity.entity_id: entity for entity in self._ha_reader.read_entities()}
-        except HaClientError as exc:
-            logger.warning("Current HA state unavailable for %s: %s", actuator_entity_id, exc)
-            return self._save_behavior(
-                record,
-                record.behavior.model_copy(
-                    update={
-                        "last_evaluated_at": now,
-                        "prediction": None,
-                        "reason": f"Aktueller Home-Assistant-Zustand ist nicht verfügbar: {exc}",
-                    }
-                ),
-            )
+        if current_entities is None:
+            try:
+                current_entities = self._ha_reader.read_entities()
+            except HaClientError as exc:
+                logger.warning("Current HA state unavailable for %s: %s", actuator_entity_id, exc)
+                return self._save_behavior(
+                    record,
+                    record.behavior.model_copy(
+                        update={
+                            "last_evaluated_at": now,
+                            "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],
     *,
@@ -745,8 +898,10 @@ 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 == "scene":
+        return "turn_on" if target_state == "on" else None
     if domain == "cover":
         return {"open": "open_cover", "closed": "close_cover"}.get(target_state)
     return None
@@ -792,6 +947,20 @@ 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 +83,42 @@ _BINARY_CONTEXT_CLASSES = frozenset({
     "window",
 })
 _ACTUATOR_DOMAINS = frozenset({
+    "button",
+    "climate",
     "cover",
     "fan",
     "humidifier",
+    "input_boolean",
+    "input_button",
+    "lock",
     "light",
+    "media_player",
+    "number",
+    "remote",
+    "scene",
+    "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 +131,7 @@ 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 +140,7 @@ 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 +150,7 @@ 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 +163,7 @@ 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 +171,7 @@ 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 +196,7 @@ def _result(
     entity: HaEntitySummary,
     role: EntityRole,
     *,
+    category: str,
     learnable: bool,
     reason: str,
 ) -> DiscoveredEntity:
@@ -171,7 +206,66 @@ 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 == "scene":
+        return "scene"
+    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
@@ -41,6 +43,7 @@ class _WsStatus:
 async def lifespan(app: FastAPI) -> AsyncIterator[None]:
     settings = app.state.settings
     client: HaClient | None = None
+    startup_task: asyncio.Task[None] | None = None
     reconcile_task: asyncio.Task[None] | None = None
     event_listener_task: asyncio.Task[None] | None = None
     fallback_task: asyncio.Task[None] | None = None
@@ -72,15 +75,17 @@ async def lifespan(app: FastAPI) -> AsyncIterator[None]:
             settings=settings,
         )
         app.state.ws_status = _WsStatus()
-        await asyncio.to_thread(app.state.actuator_service.reconcile_all, "startup")
-        await asyncio.to_thread(app.state.behavior_engine.train_all)
-        await asyncio.to_thread(app.state.behavior_engine.evaluate_all)
+        startup_task = asyncio.create_task(_startup_reconciliation(app))
         reconcile_task = asyncio.create_task(_periodic_reconciliation(app))
         event_listener_task = asyncio.create_task(_ha_event_listener(app, client))
         fallback_task = asyncio.create_task(_fallback_prediction(app))
     try:
         yield
     finally:
+        if startup_task is not None:
+            startup_task.cancel()
+            with suppress(asyncio.CancelledError):
+                await startup_task
         if reconcile_task is not None:
             reconcile_task.cancel()
             with suppress(asyncio.CancelledError):
@@ -100,7 +105,7 @@ async def lifespan(app: FastAPI) -> AsyncIterator[None]:
 app = FastAPI(
     title="SillyHome Next API",
     description="Lokales Smart-Home-Intelligenzsystem für Home Assistant.",
-    version="0.7.8",
+    version="0.7.21",
     lifespan=lifespan,
 )
 app.state.settings = load_settings()
@@ -145,24 +150,59 @@ async def _periodic_reconciliation(app: FastAPI) -> None:
         service = getattr(app.state, "actuator_service", None)
         if not isinstance(service, ActuatorReconciliationService):
             continue
-        await asyncio.to_thread(service.reconcile_all, "scheduled")
+        try:
+            await asyncio.to_thread(service.reconcile_all, "scheduled")
+            engine = getattr(app.state, "behavior_engine", None)
+            if isinstance(engine, BehaviorEngine):
+                await asyncio.to_thread(engine.train_all)
+        except Exception:
+            logger.exception("Geplante Reconciliation fehlgeschlagen; nächster Lauf versucht es erneut.")
+
+
+async def _startup_reconciliation(app: FastAPI) -> None:
+    delay_seconds = 5
+    while True:
+        service = getattr(app.state, "actuator_service", None)
         engine = getattr(app.state, "behavior_engine", None)
-        if isinstance(engine, BehaviorEngine):
+        if not isinstance(service, ActuatorReconciliationService) or not isinstance(
+            engine,
+            BehaviorEngine,
+        ):
+            return
+        try:
+            await asyncio.to_thread(service.reconcile_all, "startup")
             await asyncio.to_thread(engine.train_all)
+            await asyncio.to_thread(engine.evaluate_all)
+            logger.info("Startup-Reconciliation erfolgreich abgeschlossen.")
+            return
+        except Exception as exc:
+            logger.warning(
+                "Startup-Reconciliation verschoben: %s. Neuer Versuch in %ss.",
+                exc,
+                delay_seconds,
+            )
+            await asyncio.sleep(delay_seconds)
+            delay_seconds = min(delay_seconds * 2, 60)
 
 
 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 +211,11 @@ 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, ping_interval=None) as websocket:
+            async with websockets.connect(
+                ws_url,
+                ping_interval=20,
+                ping_timeout=10,
+            ) 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 +238,7 @@ 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
@@ -220,29 +265,38 @@ 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)
+                        if not _is_relevant_state_change(store, str(entity_id)):
+                            continue
                         # 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")
                     except Exception as exc:
                         logger.exception("Fehler bei Event-Verarbeitung: %s", exc)
-        except (websockets.exceptions.ConnectionClosed, OSError) as exc:
-            logger.warning("WebSocket-Verbindung unterbrochen: %s. Wiederholung in 5s...", exc)
+        except (
+            websockets.exceptions.ConnectionClosed,
+            websockets.exceptions.InvalidStatus,
+            OSError,
+        ) as exc:
+            logger.warning("WebSocket-Verbindung unterbrochen: %s. Wiederholung in 1s...", exc)
             if ws_status is not None:
                 ws_status.status = "reconnecting"
                 ws_status.error = str(exc)
-            await asyncio.sleep(5)
+            await asyncio.sleep(1)
         except Exception as exc:
             logger.exception("Unerwarteter Fehler im Event-Listener: %s", exc)
             if ws_status is not None:
                 ws_status.status = "error"
                 ws_status.error = str(exc)
-            await asyncio.sleep(5)
+            await asyncio.sleep(1)
 
 
 # Fallback: periodische Vorhersage falls Event-Stream ausfällt
@@ -268,4 +322,82 @@ async def _fallback_prediction(app: FastAPI) -> None:
                     "Fallback-Vorhersage aktiv (WebSocket-Status: %s)",
                     ws_status.status if ws_status else "unavailable",
                 )
-                await asyncio.to_thread(engine.evaluate_all)
+                try:
+                    await asyncio.to_thread(engine.evaluate_all)
+                except Exception:
+                    logger.exception("Fallback-Vorhersage fehlgeschlagen.")
+
+
+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 _is_relevant_state_change(store: ActuatorStore, entity_id: str) -> bool:
+    for record in store.list():
+        if record.actuator_entity_id == entity_id:
+            return True
+        if record.assignment.selected_numeric_entity_id == entity_id:
+            return True
+        if entity_id in record.assignment.selected_context_entity_ids:
+            return True
+    return False
+
+
+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

@@ -6,27 +6,40 @@
   <title>SillyHome Next</title>
   <style>
     :root { color-scheme: dark; font-family: system-ui, sans-serif; background: #10151c; color: #eaf1f8; scroll-behavior:smooth; }
-    body { margin: 0; font-size:16px; }
-    header { padding: 22px; background: linear-gradient(135deg,#142b3a,#193f36); }
+    body { margin: 0; font-size:15px; }
+    header { padding: 18px 20px; background: linear-gradient(135deg,#142b3a,#193f36); }
     h1,h2,h3 { margin: 0 0 12px; }
     header p { margin: 5px 0; color: #c3d1dc; }
-    main { display: grid; grid-template-columns: repeat(auto-fit,minmax(320px,1fr)); gap: 14px; padding: 14px; }
-    section { background: #18212b; border: 1px solid #2d3a47; border-radius: 12px; padding: 16px; }
+    main { display: grid; grid-template-columns: minmax(280px,.85fr) minmax(0,1.35fr); gap: 12px; padding: 12px; max-width:1380px; margin:0 auto; }
+    section { background: #18212b; border: 1px solid #2d3a47; border-radius: 8px; padding: 12px; min-width:0; }
     section:target { outline:2px solid #66dfa9; outline-offset:2px; }
     .wide { grid-column: 1 / -1; }
     .quick-nav { position:sticky; top:0; z-index:10; display:flex; gap:8px; overflow-x:auto; padding:10px 14px; background:rgba(16,21,28,.94); border-bottom:1px solid #2d3a47; backdrop-filter:blur(8px); }
     .quick-nav a { flex:0 0 auto; padding:10px 12px; border-radius:999px; background:#22303c; border:1px solid #31404d; color:#eaf1f8; text-decoration:none; font-weight:700; font-size:.92rem; }
     .quick-nav a.primary { background:#23715b; }
-    .steps { display:grid; grid-template-columns:repeat(auto-fit,minmax(220px,1fr)); gap:12px; }
-    .step { background:#111a23; border:1px solid #31404d; border-radius:10px; padding:14px; }
+    details.collapsible > summary,
+    .manual-context > summary,
+    .group-panel > summary { cursor:pointer; font-weight:800; color:#eaf1f8; }
+    details.collapsible > summary { list-style:none; display:flex; justify-content:space-between; gap:10px; }
+    details.collapsible > summary::-webkit-details-marker,
+    .manual-context > summary::-webkit-details-marker,
+    .group-panel > summary::-webkit-details-marker { display:none; }
+    details.collapsible > summary::after,
+    .manual-context > summary::after,
+    .group-panel > summary::after { content:"aufklappen"; color:#9fb0be; font-weight:600; font-size:.86rem; }
+    details[open].collapsible > summary::after,
+    .manual-context[open] > summary::after,
+    .group-panel[open] > summary::after { content:"zuklappen"; }
+    .steps { display:grid; grid-template-columns:repeat(auto-fit,minmax(190px,1fr)); gap:10px; margin-top:12px; }
+    .step { background:#111a23; border:1px solid #31404d; border-radius:8px; padding:10px; }
     .step-number { display:inline-grid; place-items:center; width:28px; height:28px; border-radius:50%; background:#23715b; font-weight:700; margin-bottom:8px; }
     .step p { margin:5px 0; }
     .ok { color: #66dfa9; }
     .warn { color: #f3c969; }
     .bad { color: #ff8f8f; }
     label { display: block; margin: 9px 0 4px; color: #b9c9d6; }
-    select,input,button { box-sizing: border-box; width: 100%; border-radius: 10px; border: 1px solid #3b4b5b; padding: 12px; background: #101820; color: #fff; font:inherit; }
-    select[multiple] { min-height:190px; }
+    select,input,button { box-sizing: border-box; width: 100%; border-radius: 8px; border: 1px solid #3b4b5b; padding: 10px; background: #101820; color: #fff; font:inherit; min-width:0; }
+    select[multiple] { min-height:150px; }
     button { min-height:44px; margin-top: 10px; background: #23715b; border: 0; font-weight: 700; cursor: pointer; }
     button.secondary { background: #37495c; }
     button.danger { background: #7b3434; }
@@ -39,18 +52,18 @@
     .chips { display:flex; flex-wrap:wrap; gap:6px; margin-top:8px; }
     .chip { padding:4px 8px; border-radius:999px; background:#22303c; border:1px solid #31404d; font-size:.85rem; }
     .muted { color:#9fb0be; }
-    .card-list { display:grid; gap:12px; }
-    .actuator-card { background:#111a23; border:1px solid #31404d; border-radius:14px; padding:14px; }
+    .card-list { display:grid; grid-template-columns:repeat(auto-fit,minmax(260px,1fr)); gap:10px; }
+    .actuator-card { background:#111a23; border:1px solid #31404d; border-radius:8px; padding:10px; min-width:0; }
     .actuator-card.selected { border-color:#66dfa9; box-shadow:0 0 0 1px rgba(102,223,169,.3); }
     .card-title { display:flex; justify-content:space-between; gap:10px; align-items:flex-start; margin-bottom:8px; }
     .entity-id { overflow-wrap:anywhere; font-weight:800; }
-    .metric-grid { display:grid; grid-template-columns:repeat(auto-fit,minmax(150px,1fr)); gap:8px; margin:10px 0; }
-    .metric { background:#18212b; border:1px solid #2d3a47; border-radius:10px; padding:10px; }
+    .metric-grid { display:grid; grid-template-columns:repeat(auto-fit,minmax(120px,1fr)); gap:6px; margin:8px 0; }
+    .metric { background:#18212b; border:1px solid #2d3a47; border-radius:8px; padding:8px; min-width:0; }
     .metric strong { display:block; margin-bottom:4px; color:#cfe0ec; font-size:.84rem; }
     .actions { display:flex; flex-wrap:wrap; gap:8px; margin-top:10px; }
     .actions button { flex:1 1 180px; margin-top:0; }
     .detail-header { display:flex; justify-content:space-between; gap:12px; align-items:flex-start; flex-wrap:wrap; }
-    .manual-context { margin-top:14px; background:#111a23; border:1px solid #31404d; border-radius:14px; padding:14px; }
+    .manual-context { margin-top:12px; background:#111a23; border:1px solid #31404d; border-radius:8px; padding:10px; }
     .inline-controls { display:grid; grid-template-columns:repeat(auto-fit,minmax(160px,1fr)); gap:8px; margin:8px 0; }
     .manual-entry { min-height:80px; resize:vertical; }
     textarea { box-sizing:border-box; width:100%; border-radius:10px; border:1px solid #3b4b5b; padding:12px; background:#101820; color:#fff; font:inherit; }
@@ -59,11 +72,12 @@
     @media (max-width: 760px) {
       header { padding:18px 14px; }
       header h1 { font-size:1.55rem; }
-      main { display:block; padding:10px; }
-      section { margin-bottom:12px; padding:14px; border-radius:14px; }
+      main { display:block; padding:8px; }
+      section { margin-bottom:10px; padding:10px; border-radius:8px; }
       .steps { grid-template-columns:1fr; }
       .grid-two { grid-template-columns:1fr; }
       .metric-grid { grid-template-columns:1fr 1fr; }
+      .card-list { grid-template-columns:1fr; }
       .actions { display:grid; grid-template-columns:1fr; }
       .actions button, button.compact { width:100%; min-width:0; margin-right:0; }
       .quick-nav { padding:8px 10px; }
@@ -90,7 +104,8 @@
 </nav>
 <main>
   <section class="wide" id="guide">
-    <h2>So gehst du vor</h2>
+    <details class="collapsible">
+    <summary><span>So gehst du vor</span></summary>
     <div class="steps">
       <div class="step">
         <span class="step-number">1</span>
@@ -111,6 +126,7 @@
         <p><strong>Was passiert?</strong> Erst dann darf SillyHome passende Vorhersagen automatisch ausführen. Die Freigabe kann jederzeit gestoppt werden.</p>
       </div>
     </div>
+    </details>
   </section>
 
   <section id="status-section">
@@ -134,9 +150,19 @@
           <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="scene">Szenen</option>
+          <option value="number">Numerische Helper</option>
+          <option value="valve">Ventile</option>
         </select>
       </div>
       <div>
@@ -150,6 +176,7 @@
     </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 +202,21 @@ let currentActuatorId = null;
 let actuatorChoices = [];
 let contextOptions = [];
 let manualContextState = {options: [], selected: new Set()};
+let cachedActuators = null;
+let cachedEntities = null;
+let cachedDiscovery = null;
+const ACTUATOR_RESULT_LIMIT = 50;
+const STATUS_TIMEOUT_MS = 2500;
+
+function uniqueValues(values) {
+  return [...new Set(values.filter(Boolean))];
+}
+
+function invalidateDashboardCache() {
+  cachedActuators = null;
+  cachedEntities = null;
+  cachedDiscovery = null;
+}
 
 async function api(path, options = {}) {
   const response = await fetch(path, {headers: {"Content-Type": "application/json"}, ...options});
@@ -183,8 +225,20 @@ async function api(path, options = {}) {
   return body;
 }
 
+async function apiWithTimeout(path, timeoutMs = STATUS_TIMEOUT_MS) {
+  const controller = new AbortController();
+  const timeout = setTimeout(() => controller.abort(), timeoutMs);
+  try {
+    return await api(path, {signal: controller.signal});
+  } finally {
+    clearTimeout(timeout);
+  }
+}
+
 function lifecycleLabel(record) {
-  if (record.behavior.status === "trained") return "Kontext erkannt";
+  const behaviorStatus = record.behavior_status || record.behavior?.status;
+  const lifecycleStatus = record.lifecycle_status || record.lifecycle?.status;
+  if (behaviorStatus === "trained") return "Kontext erkannt";
   const labels = {
     trained: "lernt",
     pending_history: "sammelt Historie",
@@ -193,26 +247,32 @@ function lifecycleLabel(record) {
     archived: "wartet auf Kontext",
     orphaned: "Aktor nicht gefunden",
   };
-  return labels[record.lifecycle.status] || record.lifecycle.status;
+  return labels[lifecycleStatus] || lifecycleStatus;
 }
 
 function statusClass(record) {
-  if (record.behavior.status === "trained") return "ok";
-  if (record.lifecycle.status === "trained") return "ok";
-  if (["pending_history", "pending_assignment", "archived"].includes(record.lifecycle.status)) return "warn";
+  const behaviorStatus = record.behavior_status || record.behavior?.status;
+  const lifecycleStatus = record.lifecycle_status || record.lifecycle?.status;
+  if (behaviorStatus === "trained") return "ok";
+  if (lifecycleStatus === "trained") return "ok";
+  if (["pending_history", "pending_assignment", "archived"].includes(lifecycleStatus)) return "warn";
   return "bad";
 }
 
 function behaviorLabel(record) {
-  if (record.behavior.mode === "active") return "aktiv freigegeben";
-  if (record.behavior.status === "trained") return "Shadow-Vorhersage";
-  if (record.behavior.status === "blocked") return "Lernen blockiert";
+  const mode = record.behavior_mode || record.behavior?.mode;
+  const status = record.behavior_status || record.behavior?.status;
+  if (mode === "active") return "aktiv freigegeben";
+  if (status === "trained") return "Shadow-Vorhersage";
+  if (status === "blocked") return "Lernen blockiert";
   return "sammelt Handlungen";
 }
 
 function predictionLabel(record) {
-  return record.behavior.prediction
-    ? `${record.behavior.prediction.target_state} (${Math.round(record.behavior.prediction.confidence * 100)} %)`
+  const target = record.prediction_target_state || record.behavior?.prediction?.target_state;
+  const confidence = record.prediction_confidence ?? record.behavior?.prediction?.confidence;
+  return target
+    ? `${target} (${Math.round(confidence * 100)} %)`
     : "Keine fällige Aktion";
 }
 
@@ -240,14 +300,33 @@ function matchesSearch(entity, query) {
 
 function categoryForEntity(entity) {
   const cls = entity.device_class || "";
+  const text = normalizedSearch([
+    entity.entity_id,
+    entity.friendly_name,
+    entity.area_name,
+    entity.device_name,
+  ].filter(Boolean).join(" "));
+  if (["pv", "solar", "akku", "batterie", "battery", "einspeisung", "wechselrichter"].some(token => text.includes(token))) {
+    return "PV / Akku / Einspeisung";
+  }
+  if (entity.domain === "fan") return "Lüftung / Ventilatoren";
+  if (entity.domain === "climate") return "Heizung / Klima";
+  if (entity.domain === "weather") return "Wetter";
+  if (entity.domain === "person" || entity.domain === "device_tracker") return "Anwesenheit / Personen";
+  if (entity.domain === "cover") return "Rollläden / Cover";
   if (entity.domain === "light") return "Lichtzustände";
-  if (entity.domain === "switch") return "Schalter / Helper";
+  if (entity.domain === "switch") return "Schalter / Steckdosen";
+  if (entity.domain.startsWith("input_")) return "Helper";
+  if (entity.domain === "scene") return "Szenen";
+  if (entity.domain === "media_player" || entity.domain === "remote") return "TV / Medien";
   if (["motion", "occupancy", "presence"].includes(cls)) return "PIR / Präsenz";
   if (["illuminance"].includes(cls)) return "Helligkeit";
   if (["door", "garage_door", "opening", "window"].includes(cls)) return "Tür / Fenster";
+  if (["smoke", "safety", "problem"].includes(cls)) return "Sicherheit / Diagnose";
   if (["humidity", "moisture"].includes(cls)) return "Luftfeuchtigkeit";
   if (["temperature"].includes(cls)) return "Temperatur";
   if (["power", "energy", "current", "voltage"].includes(cls)) return "Strom / Energie";
+  if (["battery", "signal_strength"].includes(cls)) return "Batterie / Signal";
   if (entity.domain === "binary_sensor") return "Binäre Sensoren";
   if (entity.domain === "sensor") return "Weitere Messsensoren";
   return "Weitere Zustände";
@@ -272,39 +351,93 @@ function optionGroups(entities, selectedIds = new Set()) {
 }
 
 async function loadOverview() {
+  document.getElementById("configured-actuators").innerHTML = "<p class='muted'>Beobachtete Geräte werden geladen ...</p>";
+  await loadSummaryData();
+  renderConfiguredActuators();
+  void loadStatus();
+  void loadActuatorDiscovery();
+  void loadActuatorSuggestions();
+}
+
+async function loadStatus() {
   const status = document.getElementById("status");
   const chips = document.getElementById("status-chips");
+  status.innerHTML = "<p class='muted'>Status wird geprüft ...</p>";
   try {
-    const [health, websocket, ml, reconciliation, actuators] = await Promise.all([
-      api("health"),
-      api("health/websocket"),
-      api("ml/health"),
-      api("v1/actuators/reconciliation/state"),
-      api("v1/actuators"),
+    const [health, websocket, ml, reconciliation, actuators] = await Promise.allSettled([
+      apiWithTimeout("health"),
+      apiWithTimeout("health/websocket"),
+      apiWithTimeout("ml/health"),
+      apiWithTimeout("v1/actuators/reconciliation/state"),
+      apiWithTimeout("v1/actuators/summary"),
     ]);
-    status.innerHTML = `<p class="ok">System bereit</p><p>Letzte automatische Prüfung: ${escapeHtml(reconciliation.last_completed_at || "noch nie")}</p>`;
+    const values = [health, websocket, ml, reconciliation, actuators].map(result =>
+      result.status === "fulfilled" ? result.value : null
+    );
+    const [healthValue, websocketValue, mlValue, reconciliationValue, actuatorValue] = values;
+    const hasError = values.some(value => value === null);
+    status.innerHTML = hasError
+      ? "<p class='warn'>Status teilweise verfügbar. Das Dashboard bleibt bedienbar.</p>"
+      : `<p class="ok">System bereit</p><p>Letzte automatische Prüfung: ${escapeHtml(reconciliationValue.last_completed_at || "noch nie")}</p>`;
     chips.innerHTML = [
-      `<span class="chip">API: ${escapeHtml(health.status)}</span>`,
-      `<span class="chip">WebSocket: ${escapeHtml(websocket.status)}</span>`,
-      `<span class="chip">Lernsystem: ${escapeHtml(ml.status)}</span>`,
-      `<span class="chip">Aktoren: ${actuators.length}</span>`,
-      `<span class="chip">Lernbereite Geräte: ${reconciliation.trained_models}</span>`,
+      `<span class="chip">API: ${escapeHtml(healthValue?.status || "offen")}</span>`,
+      `<span class="chip">WebSocket: ${escapeHtml(websocketValue?.status || "offen")}</span>`,
+      `<span class="chip">Lernsystem: ${escapeHtml(mlValue?.status || "offen")}</span>`,
+      `<span class="chip">Aktoren: ${Array.isArray(actuatorValue) ? actuatorValue.length : "offen"}</span>`,
+      `<span class="chip">Lernbereite Geräte: ${escapeHtml(reconciliationValue?.trained_models ?? "offen")}</span>`,
     ].join("");
   } catch (error) {
     status.innerHTML = `<p class="bad">${escapeHtml(error.message)}</p>`;
     chips.innerHTML = "";
   }
-  await Promise.all([loadActuatorDiscovery(), loadConfiguredActuators()]);
+}
+
+async function loadSummaryData() {
+  const actuators = await api("v1/actuators/summary");
+  cachedActuators = actuators;
+  cachedEntities = [];
+}
+
+async function loadDashboardData() {
+  await loadSummaryData();
+  await loadDiscoveryData();
+}
+
+async function loadDiscoveryData() {
+  const discovery = await api("v1/actuators/discovery");
+  cachedDiscovery = discovery;
+}
+
+async function loadFullDashboardData() {
+  const [actuators, discovery] = await Promise.all([
+    api("v1/actuators/summary"),
+    api("v1/actuators/discovery"),
+  ]);
+  cachedActuators = actuators;
+  cachedEntities = [];
+  cachedDiscovery = discovery;
 }
 
 async function loadActuatorDiscovery() {
+  const select = document.getElementById("actuator-select");
+  if (select && !cachedDiscovery) {
+    select.innerHTML = `<option value="">Geräteliste lädt im Hintergrund ...</option>`;
+  }
+  if (!cachedActuators) {
+    await loadSummaryData();
+  }
+  if (!cachedDiscovery) {
+    await loadDiscoveryData();
+  }
+  renderActuatorDiscovery();
+}
+
+function renderActuatorDiscovery() {
   const options = document.getElementById("actuator-options");
   const select = document.getElementById("actuator-select");
   try {
-    const [available, configured] = await Promise.all([
-      api("v1/actuators/discovery"),
-      api("v1/actuators"),
-    ]);
+    const available = cachedDiscovery || [];
+    const configured = cachedActuators || [];
     const configuredIds = new Set(configured.map(record => record.actuator_entity_id));
     actuatorChoices = available.filter(entity => !configuredIds.has(entity.entity_id));
     options.innerHTML = actuatorChoices.slice(0, 120).map(entity =>
@@ -313,17 +446,53 @@ async function loadActuatorDiscovery() {
     renderActuatorSelect();
   } catch (error) {
     options.innerHTML = "";
-    select.innerHTML = `<option value="">Geräteliste konnte nicht geladen werden</option>`;
+    select.innerHTML = `<option value="">Geräteliste konnte nicht geladen werden: ${escapeHtml(error.message)}</option>`;
+  }
+}
+
+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",
+    scene: "Szenen",
+    switch: "Schalter / Steckdosen",
     cover: "Rollläden / Cover",
     fan: "Lüftung / Ventilatoren",
     humidifier: "Befeuchter / Entfeuchter",
+    valve: "Ventile",
   };
   return labels[domain] || domain;
 }
@@ -335,14 +504,17 @@ function renderActuatorSelect() {
   const query = normalizedSearch(document.getElementById("actuator-search")?.value || "");
   const filtered = actuatorChoices
     .filter(entity => !domain || entity.domain === domain)
-    .filter(entity => matchesSearch(entity, query))
-    .slice(0, 120);
-  const domains = [...new Set(filtered.map(entity => entity.domain))].sort();
+    .filter(entity => matchesSearch(entity, query));
+  const visible = filtered.slice(0, ACTUATOR_RESULT_LIMIT);
+  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("")}
@@ -413,37 +585,57 @@ async function configureActuator() {
 }
 
 async function loadConfiguredActuators() {
+  if (!cachedActuators) {
+    await loadSummaryData();
+  }
+  renderConfiguredActuators();
+}
+
+function renderConfiguredActuators() {
   const box = document.getElementById("configured-actuators");
   try {
-    const rows = await api("v1/actuators");
+    const rows = cachedActuators || [];
+    const groups = new Map();
+    for (const record of rows) {
+      const group = record.area_name || actuatorGroupLabel(record.domain || record.actuator_entity_id.split(".", 1)[0]);
+      if (!groups.has(group)) groups.set(group, []);
+      groups.get(group).push({record});
+    }
+    const groupedRows = [...groups.entries()].sort(([left], [right]) => left.localeCompare(right));
     box.innerHTML = rows.length ? `
-      <div class="card-list">
-        ${rows.map(record => `
+      ${groupedRows.map(([group, items]) => `
+        <details class="group-panel" open>
+        <summary>${escapeHtml(group)} (${items.length})</summary>
+        <div class="card-list">
+        ${items.map(({record}) => `
           <article class="actuator-card ${currentActuatorId === record.actuator_entity_id ? "selected" : ""}">
             <div class="card-title">
               <div>
+                <div><strong>${escapeHtml(record.friendly_name || record.device_name || record.actuator_entity_id)}</strong></div>
                 <div class="entity-id">${escapeHtml(record.actuator_entity_id)}</div>
-                <div class="${record.behavior.status === "trained" ? "ok" : "warn"}">${escapeHtml(behaviorLabel(record))}</div>
+                <div class="${(record.behavior_status || record.behavior?.status) === "trained" ? "ok" : "warn"}">${escapeHtml(behaviorLabel(record))}</div>
               </div>
               <span class="chip">${escapeHtml(lifecycleLabel(record))}</span>
             </div>
             <div class="metric-grid">
-              <div class="metric"><strong>Freigabe</strong><span class="${record.behavior.activation_ready ? "ok" : "warn"}">${escapeHtml(record.behavior.activation_ready ? "bereit" : record.behavior.activation_reason)}</span></div>
-              <div class="metric"><strong>Handlungen</strong>${record.behavior.sample_count}</div>
+              <div class="metric"><strong>Freigabe</strong><span class="${record.activation_ready ? "ok" : "warn"}">${escapeHtml(record.activation_ready ? "bereit" : record.activation_reason)}</span></div>
+              <div class="metric"><strong>Handlungen</strong>${record.sample_count}</div>
               <div class="metric"><strong>Vorhersage</strong>${escapeHtml(predictionLabel(record))}</div>
             </div>
             <div class="actions">
               <button onclick="showActuator('${escapeHtml(record.actuator_entity_id)}')">Details öffnen</button>
-              ${record.behavior.mode === "active"
+              ${record.behavior_mode === "active"
                 ? `<button class="danger" onclick="setActivation('${escapeHtml(record.actuator_entity_id)}', false, false, true)">Stoppen + HA-Automationen fortsetzen</button>`
-                : record.behavior.activation_ready
+                : record.activation_ready
                   ? `<button onclick="setActivation('${escapeHtml(record.actuator_entity_id)}', true, true, false)">SillyHome übernehmen lassen</button>`
                   : ""}
               <button class="danger" onclick="removeActuator('${escapeHtml(record.actuator_entity_id)}')">Entfernen</button>
             </div>
           </article>
         `).join("")}
-      </div>` : "<p>Noch keine Aktoren ausgewählt.</p>";
+        </div>
+        </details>
+      `).join("")}` : "<p>Noch keine Aktoren ausgewählt.</p>";
   } catch (error) {
     box.textContent = error.message;
   }
@@ -466,8 +658,16 @@ async function showActuator(actuatorId, evaluationMessage = "") {
     ].filter(Boolean);
     const evidence = [...record.numeric_candidates, ...record.context_candidates]
       .filter(candidate => contexts.includes(candidate.entity_id))
-      .map(candidate => `<li><strong>${escapeHtml(candidate.friendly_name || candidate.entity_id)}</strong>: ${candidate.evidence.map(escapeHtml).join(", ") || "statistisch relevanter Kandidat"}</li>`)
+      .map(candidate => `<li><strong>${escapeHtml(candidate.friendly_name || candidate.entity_id)}</strong>: ${uniqueValues(candidate.evidence).map(escapeHtml).join(", ") || "statistisch relevanter Kandidat"}</li>`)
       .join("");
+    const currentContextControls = contexts.length
+      ? `<ul>${contexts.map(entityId => `
+          <li>
+            <code>${escapeHtml(entityId)}</code>
+            <button class="secondary compact" onclick="removeContextEntity('${escapeHtml(record.actuator_entity_id)}', '${escapeHtml(entityId)}')">Entfernen</button>
+          </li>
+        `).join("")}</ul>`
+      : "<p class='muted'>Noch keine Kontext-Entity ausgewählt.</p>";
     const prediction = record.behavior.prediction;
     const learnedAutomationActions = record.behavior.patterns.filter(
       pattern => pattern.source === "automation",
@@ -489,8 +689,8 @@ async function showActuator(actuatorId, evaluationMessage = "") {
       selected: manualContextIds,
     };
     const manualAssignment = `
-      <div class="manual-context">
-        <h3>Kontext selbst festlegen</h3>
+      <details class="manual-context" open>
+        <summary>Kontext selbst festlegen</summary>
         <p class="muted">Die Vorschläge sind aktorbezogen vorsortiert. Wenn etwas fehlt, trage die Entity-ID unten manuell ein, z. B. PIR, Helligkeit außen, Luftfeuchtigkeit oder Lichtzustände.</p>
         <label for="manual-numeric-select">Optionaler Haupt-Messsensor</label>
         <select id="manual-numeric-select">
@@ -520,7 +720,7 @@ async function showActuator(actuatorId, evaluationMessage = "") {
           <button onclick="saveManualAssignment('${escapeHtml(record.actuator_entity_id)}')">Diese Kontext-Auswahl speichern</button>
           <button class="secondary" onclick="loadContextOptions('${escapeHtml(record.actuator_entity_id)}').then(() => showActuator('${escapeHtml(record.actuator_entity_id)}'))">Vorschläge neu laden</button>
         </div>
-      </div>
+      </details>
     `;
     const activationButton = record.behavior.mode === "active"
       ? `<button class="danger" onclick="setActivation('${escapeHtml(record.actuator_entity_id)}', false, false, true)">SillyHome stoppen und pausierte HA-Automationen fortsetzen</button>
@@ -574,11 +774,17 @@ 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"});
@@ -606,6 +812,7 @@ async function saveManualAssignment(actuatorId) {
         note: "Manuell im Dashboard gesetzt",
       }),
     });
+    invalidateDashboardCache();
     await loadConfiguredActuators();
     await showActuator(actuatorId, "Manuelle Kontext-Auswahl gespeichert.");
   } catch (error) {
@@ -613,6 +820,35 @@ 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`,
+      }),
+    });
+    invalidateDashboardCache();
+    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(
@@ -625,6 +861,7 @@ async function evaluateActuator(actuatorId) {
     const message = record.behavior.prediction
       ? `Prüfung ${checkedAt}: ${record.behavior.prediction.target_state} mit ${Math.round(record.behavior.prediction.confidence * 100)} % vorhergesagt.`
       : `Prüfung ${checkedAt}: Kein frischer passender Sensorwechsel erkannt; aktuell ist keine Aktion fällig.`;
+    invalidateDashboardCache();
     await loadConfiguredActuators();
     await showActuator(actuatorId, message);
   } catch (error) {
@@ -632,6 +869,24 @@ 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,
+      }),
+    });
+    invalidateDashboardCache();
+    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
@@ -650,6 +905,7 @@ async function setActivation(actuatorId, active, pauseMatchingAutomations, resto
         restore_paused_automations: restorePausedAutomations,
       }),
     });
+    invalidateDashboardCache();
     await loadConfiguredActuators();
     await showActuator(actuatorId);
   } catch (error) {
@@ -668,6 +924,7 @@ async function setRelatedAutomation(actuatorId, automationEntityId, enabled) {
         enabled,
       }),
     });
+    invalidateDashboardCache();
     await loadConfiguredActuators();
     await showActuator(actuatorId);
   } catch (error) {

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "sillyhome-next"
-version = "0.7.8"
+version = "0.7.21"
 description = "Lokales Smart-Home-Intelligenzsystem für Home Assistant"
 requires-python = ">=3.11"
 dependencies = [

tests/actuators/test_lifecycle.py

@@ -277,6 +277,81 @@ 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_fan_prefers_humidity_over_power_sensor(tmp_path: Path) -> None:
+    start = datetime(2026, 6, 1, tzinfo=timezone.utc)
+    entities = [
+        HaEntitySummary(
+            entity_id="fan.bad_lueftung",
+            domain="fan",
+            friendly_name="Bad Lüftung",
+            area_name="Bad",
+        ),
+        HaEntitySummary(
+            entity_id="sensor.bad_luftfeuchtigkeit",
+            domain="sensor",
+            device_class="humidity",
+            state_class="measurement",
+            unit_of_measurement="%",
+            friendly_name="Bad Luftfeuchtigkeit",
+            area_name="Bad",
+        ),
+        HaEntitySummary(
+            entity_id="sensor.bad_power",
+            domain="sensor",
+            device_class="power",
+            state_class="measurement",
+            unit_of_measurement="W",
+            friendly_name="Bad Leistung",
+            area_name="Bad",
+        ),
+    ]
+    service = _service(
+        tmp_path,
+        entities,
+        {
+            "sensor.bad_luftfeuchtigkeit": _points(8, start, 55.0),
+            "sensor.bad_power": _points(8, start, 5.0),
+        },
+    )
+
+    record = service.configure_actuator("fan.bad_lueftung")
+
+    assert record.assignment.selected_numeric_entity_id == "sensor.bad_luftfeuchtigkeit"
+
+
 def test_manual_assignment_persists_and_wins_over_automatic_mapping(tmp_path: Path) -> None:
     start = datetime(2026, 6, 1, tzinfo=timezone.utc)
     entities = [
@@ -325,3 +400,39 @@ def test_manual_assignment_persists_and_wins_over_automatic_mapping(tmp_path: Pa
     assert record.assignment.selected_context_entity_ids == ["sensor.abstellkammer_illuminance"]
     assert record.assignment.source is AssignmentSource.MANUAL
     assert record.manual_override is not None
+
+
+def test_manual_assignment_evidence_is_not_duplicated(tmp_path: Path) -> None:
+    entities = [
+        HaEntitySummary(
+            entity_id="light.abstellkammer",
+            domain="light",
+            friendly_name="Abstellkammer Licht",
+            area_name="Abstellkammer",
+        ),
+        HaEntitySummary(
+            entity_id="binary_sensor.abstellkammer_motion",
+            domain="binary_sensor",
+            device_class="motion",
+            friendly_name="Abstellkammer Bewegung",
+            area_name="Abstellkammer",
+        ),
+    ]
+    service = _service(tmp_path, entities, {})
+    service.configure_actuator("light.abstellkammer")
+    for _ in range(3):
+        service.set_manual_assignment(
+            "light.abstellkammer",
+            numeric_entity_id=None,
+            context_entity_ids=["binary_sensor.abstellkammer_motion"],
+            note="Manuell gesetzt",
+        )
+
+    record = service.get_actuator("light.abstellkammer")
+    candidate = next(
+        item
+        for item in record.context_candidates
+        if item.entity_id == "binary_sensor.abstellkammer_motion"
+    )
+
+    assert candidate.evidence.count("Manuell vom Nutzer als relevant festgelegt.") == 1

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 (
@@ -212,6 +213,23 @@ def test_manual_assignment_endpoint_updates_context(tmp_path: Path) -> None:
     ]
 
 
+def test_summary_is_lightweight_and_uses_cached_entity_metadata(tmp_path: Path) -> None:
+    with TestClient(app) as client:
+        _install_service(tmp_path)
+        client.get("/v1/actuators/discovery")
+        client.post("/v1/actuators", json={"actuator_entity_id": "light.abstellkammer"})
+
+        response = client.get("/v1/actuators/summary")
+
+    assert response.status_code == 200
+    payload = response.json()
+    assert payload[0]["actuator_entity_id"] == "light.abstellkammer"
+    assert payload[0]["friendly_name"] == "Abstellkammer Licht"
+    assert payload[0]["area_name"] == "Abstellkammer"
+    assert "behavior" not in payload[0]
+    assert "numeric_candidates" not in payload[0]
+
+
 def test_context_options_returns_learnable_entities(tmp_path: Path) -> None:
     with TestClient(app) as client:
         _install_service(tmp_path)
@@ -227,3 +245,37 @@ 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_dashboard.py

@@ -32,5 +32,12 @@ def test_dashboard_is_served_at_root() -> None:
     assert "Kein frischer passender Sensorwechsel erkannt" in response.text
     assert "Vorhersage jetzt prüfen" not in response.text
     assert "record.behavior.activation_ready" in response.text
+    assert "record.behavior.status ===" not in response.text
+    assert "record.behavior_status || record.behavior?.status" in response.text
+    assert 'api("v1/actuators")' not in response.text
+    assert 'api("v1/actuators/summary")' in response.text
+    assert 'api("v1/entities")' not in response.text
+    assert 'details class="collapsible"' in response.text
+    assert 'class="group-panel"' in response.text
     assert "Automation-Entwurf" not in response.text
     assert "Manuelle Overrides" not in response.text

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:
-        self.state_changes.append((entity_id, new_state))
+    def handle_state_change(
+        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:
@@ -69,7 +94,8 @@ def test_ha_event_listener_processes_state_change(tmp_path: Path) -> None:
 
         connect.assert_called_once_with(
             "ws://homeassistant:8123/api/websocket",
-            ping_interval=None,
+            ping_interval=20,
+            ping_timeout=10,
         )
         assert fake_ws.sent == [
             {"type": "auth", "access_token": "test-token"},
@@ -83,12 +109,20 @@ 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_store.configure("light.test")
     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