Add production diagnostics and planning features

.gitignore

@@ -11,3 +11,5 @@ __pycache__/
 .env
 .env.local
 .env.*
+/.actuator_store/
+/MagicMock/

CHANGELOG.md

@@ -1,5 +1,44 @@
 # Changelog
 
+## 1.7.0 - 2026-06-18
+- Produktiv-Ausbau fuer Schaltvertrauen: persistente Entscheidungs-Timeline,
+  Event-Latenzmessungen und Dry-run pro Aktor.
+- Backup-/Restore-API fuer Aktor-Konfigurationen, Reconciliation-Status und
+  sichtbare Job-Historie.
+- Feedback kann jetzt konkrete Korrekturtypen wie `too_early`, `too_late` und
+  `never_automate` speichern; `never_automate` setzt eine manuelle Sperre.
+- Planungs-Refresh erzeugt Raum-/Aktorgruppen, einfache Szenenvorschlaege und
+  lokale Agent-Insights aus vorhandenen Daten.
+- Event-Verarbeitung laedt Aktor-Konfigurationen nur noch einmal pro
+  Home-Assistant-State-Change.
+
+## 1.6.1 - 2026-06-18
+- Home-Assistant-WebSocket nutzt wieder keinen clientseitigen Keepalive-Ping.
+  Damit bleibt das Event-Verhalten aus 0.7.8 stabil und Sensorwechsel fuehren
+  nicht erst ueber Fallback oder manuelle Statusabfrage zu Schaltungen.
+
+## 1.6.0 - 2026-06-18
+- `/v1/actuators/dashboard/system` und `/dashboard/start` lesen fuer
+  Cache-Status nur noch SQLite-Metadaten statt den kompletten Entity-Cache zu
+  materialisieren.
+- Aktor-Summaries lesen benoetigte Entity-Metadaten gezielt aus SQLite anhand
+  der Aktor-IDs.
+- Ingress-Dashboard bereinigt: weniger Erklaertexte, kein Ablauf-Menue, kein
+  Versions-Chip im Einrichtungsbereich.
+- Detailansicht ergaenzt Zurueck-Navigation, Aktualisieren und Auswahl eines
+  anderen beobachteten Geraets.
+- Frontend bleibt Anzeige- und Bedienebene; Backend liefert schlanke
+  View-Daten, Worker aktualisieren HA-/Discovery-Cache im Hintergrund.
+
+## 1.5.4 - 2026-06-18
+- Add-on-Start vertraut Ingress-Proxy-Headern nicht mehr blind. Uvicorn loggt
+  damit den direkten Docker-/Ingress-Peer statt LAN-IPs aus `X-Forwarded-For`.
+- Dashboard behält bereits geladene System-, Lern- und Discovery-Daten beim
+  Wechseln der Ansichten und aktualisiert sie nur im Hintergrund.
+- Details sind kein eigener Menüpunkt mehr, sondern gehören zum ausgewählten
+  Aktor aus der Lernübersicht. Bereits geöffnete Details bleiben sichtbar und
+  laden nur bei expliziter Aktualisierung neu.
+
 ## 1.2.0 - 2026-06-17
 - Automatische Sensor-Gewichtungsanpassung aus Nutzerfeedback:
   korrektes Feedback staerkt aktuelle Kontextsignale leicht, falsches Feedback

README.md

@@ -31,6 +31,8 @@ nach einer ausdrücklichen Freigabe ausführen.
   [`docs/V1_5_2_OPERATING_GUIDE.md`](docs/V1_5_2_OPERATING_GUIDE.md)
 - Version 1.5.3 SQLite-Cache fuer Ingress-Dashboard:
   [`docs/V1_5_3_OPERATING_GUIDE.md`](docs/V1_5_3_OPERATING_GUIDE.md)
+- Version 1.7.0 Diagnose, Backup, Dry-run und Planung:
+  [`docs/V1_7_0_OPERATING_GUIDE.md`](docs/V1_7_0_OPERATING_GUIDE.md)
 - Arbeitsregeln für Coding-Agenten: [`AGENTS.md`](AGENTS.md)
 
 ## Reifegrad

addon/config.yaml

@@ -1,5 +1,5 @@
 name: SillyHome Next
-version: "1.5.3"
+version: "1.7.0"
 slug: sillyhome_next
 description: Lernt automatisch aus deinem Verhalten und steuert freigegebene Aktoren
 url: http://192.168.6.31:3000/pino/sillyhome-next

addon/run.sh

@@ -21,5 +21,4 @@ if [ -f /data/options.json ]; then
 fi
 
 mkdir -p "$SILLYHOME_MODEL_STORE" "$SILLYHOME_AUTOMATION_STORE" "$SILLYHOME_ACTUATOR_STORE"
-exec uvicorn app.main:app --app-dir /app --host 0.0.0.0 --port 8000 \
+exec uvicorn app.main:app --app-dir /app --host 0.0.0.0 --port 8000
-  --proxy-headers --forwarded-allow-ips='*'

app/actuators/cache_db.py

@@ -33,6 +33,38 @@ class DashboardCache:
             "entities": [json.loads(row[1]) for row in rows],
         }
 
+    def load_status(self) -> dict[str, object]:
+        with self._lock, self._connect() as connection:
+            updated_at = self._get_meta(connection, "ha_entities_updated_at")
+            groups_json = self._get_meta(connection, "discovery_groups") or "[]"
+            entity_count = connection.execute("select count(*) from ha_entities").fetchone()[0]
+        try:
+            groups = json.loads(groups_json)
+        except ValueError:
+            groups = []
+        return {
+            "updated_at": updated_at,
+            "discovery_groups": groups if isinstance(groups, list) else [],
+            "entity_count": int(entity_count or 0),
+        }
+
+    def load_entity_map(self, entity_ids: set[str]) -> dict[str, HaEntitySummary]:
+        if not entity_ids:
+            return {}
+        placeholders = ",".join("?" for _ in entity_ids)
+        with self._lock, self._connect() as connection:
+            rows = connection.execute(
+                f"select entity_id, payload from ha_entities where entity_id in ({placeholders})",
+                tuple(sorted(entity_ids)),
+            ).fetchall()
+        result: dict[str, HaEntitySummary] = {}
+        for entity_id, payload in rows:
+            try:
+                result[str(entity_id)] = HaEntitySummary.model_validate(json.loads(payload))
+            except (TypeError, ValueError):
+                continue
+        return result
+
     def save_entities_payload(
         self,
         *,

app/actuators/models.py

@@ -52,6 +52,14 @@ class JobStatus(StrEnum):
     FAILED = "failed"
 
 
+class FeedbackKind(StrEnum):
+    CORRECT = "correct"
+    WRONG = "wrong"
+    TOO_EARLY = "too_early"
+    TOO_LATE = "too_late"
+    NEVER_AUTOMATE = "never_automate"
+
+
 class AssignmentCandidate(BaseModel):
     entity_id: str
     domain: str
@@ -146,6 +154,30 @@ class DecisionFactor(BaseModel):
     evidence: list[str] = Field(default_factory=list)
 
 
+class DecisionTrace(BaseModel):
+    trace_id: str = Field(pattern=r"^[a-z0-9_.-]{1,120}$")
+    created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+    trigger_entity_id: str | None = None
+    trigger_state: str | None = None
+    target_state: str | None = None
+    confidence: float | None = Field(default=None, ge=0.0, le=1.0)
+    executed: bool = False
+    blocked: bool = False
+    reason: str = Field(default="", max_length=700)
+    blockers: list[str] = Field(default_factory=list)
+    duration_ms: int | None = Field(default=None, ge=0)
+
+
+class LatencyMeasurement(BaseModel):
+    measured_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+    trigger_entity_id: str | None = None
+    event_to_decision_ms: int | None = Field(default=None, ge=0)
+    decision_to_service_ms: int | None = Field(default=None, ge=0)
+    event_to_done_ms: int | None = Field(default=None, ge=0)
+    executed: bool = False
+    source: str = Field(default="manual", max_length=40)
+
+
 class AdaptiveWeightUpdate(BaseModel):
     entity_id: str
     previous_weight: float = Field(ge=0.0, le=1.0)
@@ -248,6 +280,32 @@ class RelatedAutomation(BaseModel):
     enabled: bool
 
 
+class ActuatorGroup(BaseModel):
+    group_id: str = Field(pattern=r"^[a-z0-9_-]{1,64}$")
+    name: str = Field(min_length=1, max_length=120)
+    area_name: str | None = Field(default=None, max_length=120)
+    member_entity_ids: list[str] = Field(default_factory=list)
+    reason: str = Field(default="", max_length=300)
+
+
+class SceneSuggestion(BaseModel):
+    scene_id: str = Field(pattern=r"^[a-z0-9_-]{1,64}$")
+    label: str = Field(min_length=1, max_length=120)
+    member_entity_ids: list[str] = Field(default_factory=list)
+    confidence: float = Field(default=0.0, ge=0.0, le=1.0)
+    reason: str = Field(default="", max_length=500)
+    last_seen_at: datetime | None = None
+
+
+class AgentInsight(BaseModel):
+    insight_id: str = Field(pattern=r"^[a-z0-9_.-]{1,120}$")
+    severity: str = Field(default="info", max_length=20)
+    title: str = Field(min_length=1, max_length=160)
+    detail: str = Field(min_length=1, max_length=700)
+    action: str | None = Field(default=None, max_length=300)
+    created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+
+
 class BehaviorState(BaseModel):
     mode: BehaviorMode = BehaviorMode.SHADOW
     status: BehaviorStatus = BehaviorStatus.COLLECTING
@@ -281,6 +339,16 @@ class BehaviorState(BaseModel):
     automation_conflicts: list[AutomationConflict] = Field(default_factory=list)
     time_profiles: list[TimeProfile] = Field(default_factory=list)
     anomalies: list[AnomalyEvent] = Field(default_factory=list)
+    decision_timeline: list[DecisionTrace] = Field(default_factory=list)
+    latency_measurements: list[LatencyMeasurement] = Field(default_factory=list)
+    feedback_log: list[FeedbackKind] = Field(default_factory=list)
+    dry_run_enabled: bool = False
+    dry_run_started_at: datetime | None = None
+    dry_run_sample_count: int = Field(default=0, ge=0)
+    dry_run_hit_count: int = Field(default=0, ge=0)
+    actuator_groups: list[ActuatorGroup] = Field(default_factory=list)
+    scene_suggestions: list[SceneSuggestion] = Field(default_factory=list)
+    agent_insights: list[AgentInsight] = Field(default_factory=list)
 
 
 class ActuatorRecord(BaseModel):

app/actuators/store.py

@@ -100,6 +100,11 @@ class ActuatorStore:
             except ValueError as exc:
                 raise ValueError("Ungültiger Job-Queue-Status.") from exc
 
+    def save_job_queue(self, queue: JobQueueState) -> JobQueueState:
+        with self._lock:
+            self._persist_job_queue(queue)
+            return queue
+
     def start_job(
         self,
         *,

app/api/v1/actuators.py

@@ -10,7 +10,7 @@ from pydantic import BaseModel, Field
 
 from app.actuators.cache_db import DashboardCache
 from app.actuators.lifecycle import ActuatorReconciliationService
-from app.actuators.models import ActuatorRecord, AnomalyEvent, ReconciliationState, SensorWeightGroup
+from app.actuators.models import ActuatorRecord, AnomalyEvent, FeedbackKind, ReconciliationState, SensorWeightGroup
 from app.actuators.models import JobQueueItem, JobQueueState, JobStatus, SafetyProfile
 from app.actuators.store import ActuatorStore
 from app.behavior.engine import BehaviorEngine
@@ -55,6 +55,29 @@ class WeightOverrideRequest(BaseModel):
 class FeedbackRequest(BaseModel):
     correct: bool
     expected_state: str | None = Field(default=None, max_length=100)
+    kind: FeedbackKind | None = None
+
+
+class DryRunRequest(BaseModel):
+    enabled: bool
+
+
+class BackupPayload(BaseModel):
+    exported_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+    records: list[ActuatorRecord] = Field(default_factory=list)
+    reconciliation: ReconciliationState = Field(default_factory=ReconciliationState)
+    jobs: JobQueueState = Field(default_factory=JobQueueState)
+
+
+class RestoreRequest(BaseModel):
+    backup: BackupPayload
+    replace_existing: bool = False
+
+
+class RestoreResult(BaseModel):
+    restored_records: int = 0
+    skipped_existing: int = 0
+    restored_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
 
 
 class SafetyProfileRequest(BaseModel):
@@ -326,13 +349,10 @@ def _dashboard_overview(
     include_background: bool,
     include_actuators: bool,
 ) -> DashboardOverview:
-    cache_payload = _load_entity_cache_payload(request)
+    cache_status = _load_entity_cache_status(request)
-    raw_entities = cache_payload.get("entities", [])
+    raw_updated_at = cache_status.get("updated_at")
-    if not isinstance(raw_entities, list):
-        raw_entities = []
-    raw_updated_at = cache_payload.get("updated_at")
     updated_at = raw_updated_at if isinstance(raw_updated_at, str) else None
-    raw_groups = cache_payload.get("discovery_groups", [])
+    raw_groups = cache_status.get("discovery_groups", [])
     cached_groups = [
         DashboardDiscoveryGroup.model_validate(group)
         for group in raw_groups
@@ -350,6 +370,9 @@ def _dashboard_overview(
     job_p95_duration_ms, slow_job_count, performance_status = _performance_status(jobs)
     anomaly_count = sum(record.anomaly_count for record in actuators)
     critical_anomaly_count = sum(record.critical_anomaly_count for record in actuators)
+    entity_count = cache_status.get("entity_count")
+    if not isinstance(entity_count, int):
+        entity_count = 0
     return DashboardOverview(
         system=DashboardSystemStatus(
             websocket_status=getattr(ws_status, "status", "unavailable"),
@@ -373,9 +396,9 @@ def _dashboard_overview(
             critical_anomaly_count=critical_anomaly_count,
         ),
         cache=EntityCacheStatus(
-            available=bool(raw_entities),
+            available=bool(entity_count),
             updated_at=updated_at,
-            entity_count=len(raw_entities),
+            entity_count=entity_count,
         ),
         actuators=actuators,
         discovery_groups=cached_groups,
@@ -406,6 +429,48 @@ def list_anomalies(request: Request) -> list[AnomalyOverview]:
     return overview
 
 
+@router.get("/backup/export", response_model=BackupPayload)
+def export_backup(request: Request) -> BackupPayload:
+    store = getattr(request.app.state, "actuator_store", None)
+    if not isinstance(store, ActuatorStore):
+        raise HTTPException(
+            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+            detail="Actuator Store nicht initialisiert.",
+        )
+    return BackupPayload(
+        records=store.list(),
+        reconciliation=store.load_reconciliation_state(),
+        jobs=store.load_job_queue(),
+    )
+
+
+@router.post("/backup/restore", response_model=RestoreResult)
+def restore_backup(payload: RestoreRequest, request: Request) -> RestoreResult:
+    store = getattr(request.app.state, "actuator_store", None)
+    if not isinstance(store, ActuatorStore):
+        raise HTTPException(
+            status_code=status.HTTP_503_SERVICE_UNAVAILABLE,
+            detail="Actuator Store nicht initialisiert.",
+        )
+    existing_ids = {record.actuator_entity_id for record in store.list()}
+    restored = 0
+    skipped = 0
+    for record in payload.backup.records:
+        if record.actuator_entity_id in existing_ids and not payload.replace_existing:
+            skipped += 1
+            continue
+        store.upsert(record)
+        restored += 1
+    store.save_reconciliation_state(payload.backup.reconciliation)
+    store.save_job_queue(payload.backup.jobs)
+    return RestoreResult(restored_records=restored, skipped_existing=skipped)
+
+
+@router.post("/planning/refresh", response_model=list[ActuatorRecord])
+def refresh_planning_insights(request: Request) -> list[ActuatorRecord]:
+    return _behavior(request).refresh_planning_insights()
+
+
 @router.get("", response_model=list[ActuatorRecord])
 def list_configured(request: Request) -> list[ActuatorRecord]:
     return _service(request).list_configured()
@@ -513,11 +578,24 @@ def record_feedback(
             actuator_entity_id,
             correct=payload.correct,
             expected_state=payload.expected_state,
+            kind=payload.kind,
         )
     except KeyError as exc:
         raise HTTPException(status_code=404, detail=str(exc)) from exc
 
 
+@router.post("/{actuator_entity_id}/dry-run", response_model=ActuatorRecord)
+def set_dry_run(
+    actuator_entity_id: str,
+    payload: DryRunRequest,
+    request: Request,
+) -> ActuatorRecord:
+    try:
+        return _behavior(request).set_dry_run(actuator_entity_id, enabled=payload.enabled)
+    except KeyError as exc:
+        raise HTTPException(status_code=404, detail=str(exc)) from exc
+
+
 @router.post("/{actuator_entity_id}/safety", response_model=ActuatorRecord)
 def set_safety_profile(
     actuator_entity_id: str,
@@ -846,6 +924,11 @@ def _load_cached_entity_map(
 ) -> dict[str, HaEntitySummary]:
     if not entity_ids:
         return {}
+    cache = getattr(request.app.state, "dashboard_cache", None)
+    if isinstance(cache, DashboardCache):
+        cached_result = cache.load_entity_map(entity_ids)
+        if cached_result:
+            return cached_result
     payload = _load_entity_cache_payload(request)
     raw_entities = payload.get("entities", [])
     if not isinstance(raw_entities, list):
@@ -864,6 +947,29 @@ def _load_cached_entity_map(
     return result
 
 
+def _load_entity_cache_status(request: Request) -> dict[str, object]:
+    cache = getattr(request.app.state, "dashboard_cache", None)
+    if isinstance(cache, DashboardCache):
+        status_payload = cache.load_status()
+        if status_payload.get("entity_count"):
+            return status_payload
+    path = _entity_cache_path(request)
+    if not path.exists():
+        return {}
+    try:
+        payload = json.loads(path.read_text(encoding="utf-8"))
+    except (OSError, TypeError, ValueError):
+        return {}
+    if not isinstance(payload, dict):
+        return {}
+    raw_entities = payload.get("entities", [])
+    return {
+        "updated_at": payload.get("updated_at"),
+        "discovery_groups": payload.get("discovery_groups", []),
+        "entity_count": len(raw_entities) if isinstance(raw_entities, list) else 0,
+    }
+
+
 def _load_entity_cache_payload(request: Request) -> dict[str, object]:
     cache = getattr(request.app.state, "dashboard_cache", None)
     if isinstance(cache, DashboardCache):

app/behavior/engine.py

@@ -3,12 +3,15 @@ from __future__ import annotations
 import logging
 from collections.abc import Sequence
 from datetime import datetime, timedelta, timezone
+from time import perf_counter
 from zoneinfo import ZoneInfo
 
 from app.actuators.models import (
     ActuatorRecord,
     AdaptiveWeightUpdate,
+    AgentInsight,
     AnomalyEvent,
+    ActuatorGroup,
     AutomationConflict,
     BehaviorMode,
     BehaviorPattern,
@@ -16,12 +19,16 @@ from app.actuators.models import (
     BehaviorState,
     BehaviorStatus,
     DecisionFactor,
+    DecisionTrace,
     ExecutionEvent,
+    FeedbackKind,
+    LatencyMeasurement,
     ManualOverride,
     ModelSnapshot,
     RelatedAutomation,
     SafetyProfile,
     SafetyStage,
+    SceneSuggestion,
     TimeProfile,
 )
 from app.actuators.store import ActuatorStore
@@ -35,6 +42,9 @@ _MAX_PATTERNS = 500
 _MAX_MODEL_SNAPSHOTS = 3
 _MAX_SNAPSHOT_PATTERNS = 120
 _MAX_EXECUTION_EVENTS = 100
+_MAX_DECISION_TRACES = 30
+_MAX_LATENCY_MEASUREMENTS = 50
+_MAX_FEEDBACK_LOG = 50
 _ACTION_LOGBOOK_TOLERANCE = timedelta(seconds=10)
 _CONTEXT_TRIGGER_TOLERANCE = timedelta(seconds=3)
 _OWN_ACTION_TOLERANCE = timedelta(seconds=20)
@@ -254,7 +264,11 @@ class BehaviorEngine:
         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,
+        trigger_entity_id: str | None = None,
+        trigger_state: str | None = None,
+        event_received_at: datetime | None = None,
     ) -> ActuatorRecord:
+        started_perf = perf_counter()
         record = self._store.get(actuator_entity_id)
         now = datetime.now(timezone.utc)
         if current_entities is None:
@@ -344,6 +358,7 @@ class BehaviorEngine:
         else:
             safety_allowed = False
             safety_blockers = ["Keine fällige Vorhersage."]
+        decision_to_service_ms: int | None = None
         decision_factors = _decision_factors_for(record, current_context, prediction)
         behavior = record.behavior.model_copy(
             update={
@@ -383,12 +398,47 @@ class BehaviorEngine:
             domain = actuator_entity_id.split(".", 1)[0]
             service = service_for_state(domain, prediction.target_state)
             if service is not None:
+                if record.behavior.dry_run_enabled:
+                    behavior = behavior.model_copy(
+                        update={
+                            "prediction": prediction.model_copy(
+                                update={
+                                    "executed": False,
+                                    "execution_reason": (
+                                        "Dry-run: Aktion wäre ausgeführt worden."
+                                    ),
+                                }
+                            ),
+                            "dry_run_sample_count": record.behavior.dry_run_sample_count + 1,
+                            "reason": (
+                                f"Dry-run hätte {prediction.target_state!r} mit "
+                                f"{prediction.confidence:.0%} Sicherheit ausgeführt."
+                            ),
+                        }
+                    )
+                    return self._save_behavior(
+                        record,
+                        _append_decision_trace(
+                            behavior,
+                            trigger_entity_id=trigger_entity_id,
+                            trigger_state=trigger_state,
+                            prediction=prediction,
+                            safety_blockers=safety_blockers,
+                            duration_ms=_elapsed_ms(started_perf),
+                            event_received_at=event_received_at,
+                            decision_to_service_ms=None,
+                            executed=False,
+                            source="event" if event_received_at is not None else "manual",
+                        ),
+                    )
                 try:
+                    service_started_perf = perf_counter()
                     self._ha_reader.call_service(
                         domain,
                         service,
                         {"entity_id": actuator_entity_id},
                     )
+                    decision_to_service_ms = _elapsed_ms(service_started_perf)
                 except (HaClientError, ValueError) as exc:
                     logger.error(
                         "Predicted action failed for %s: %s",
@@ -400,7 +450,21 @@ class BehaviorEngine:
                             "reason": f"Vorhersage wurde aus Sicherheitsgründen nicht ausgeführt: {exc}"
                         }
                     )
-                    return self._save_behavior(record, behavior)
+                    return self._save_behavior(
+                        record,
+                        _append_decision_trace(
+                            behavior,
+                            trigger_entity_id=trigger_entity_id,
+                            trigger_state=trigger_state,
+                            prediction=prediction,
+                            safety_blockers=[str(exc)],
+                            duration_ms=_elapsed_ms(started_perf),
+                            event_received_at=event_received_at,
+                            decision_to_service_ms=None,
+                            executed=False,
+                            source="event" if event_received_at is not None else "manual",
+                        ),
+                    )
                 event = ExecutionEvent(
                     target_state=prediction.target_state,
                     executed_at=now,
@@ -434,6 +498,20 @@ class BehaviorEngine:
                         )
                     }
                 )
+        behavior = _append_decision_trace(
+            behavior,
+            trigger_entity_id=trigger_entity_id,
+            trigger_state=trigger_state,
+            prediction=prediction,
+            safety_blockers=safety_blockers,
+            duration_ms=_elapsed_ms(started_perf),
+            event_received_at=event_received_at,
+            decision_to_service_ms=(
+                decision_to_service_ms
+            ),
+            executed=bool(prediction is not None and behavior.prediction is not None and behavior.prediction.executed),
+            source="event" if event_received_at is not None else "manual",
+        )
         return self._save_behavior(record, behavior)
 
     def record_feedback(
@@ -442,6 +520,7 @@ class BehaviorEngine:
         *,
         correct: bool,
         expected_state: str | None = None,
+        kind: FeedbackKind | None = None,
     ) -> ActuatorRecord:
         record = self._store.get(actuator_entity_id)
         now = datetime.now(timezone.utc)
@@ -485,6 +564,7 @@ class BehaviorEngine:
             reason = "Vorhersage wurde vom Nutzer als korrekt bestätigt."
             correct_count = record.behavior.correct_feedback_count + 1
             incorrect_count = record.behavior.incorrect_feedback_count
+            feedback_kind = kind or FeedbackKind.CORRECT
         else:
             target = prediction.target_state if prediction is not None else None
             if target:
@@ -515,11 +595,24 @@ class BehaviorEngine:
             reason = "Vorhersage wurde vom Nutzer als falsch markiert."
             correct_count = record.behavior.correct_feedback_count
             incorrect_count = record.behavior.incorrect_feedback_count + 1
+            feedback_kind = kind or FeedbackKind.WRONG
+            if feedback_kind is FeedbackKind.NEVER_AUTOMATE:
+                safety = record.behavior.safety.model_copy(
+                    update={
+                        "manual_block": True,
+                        "updated_at": now,
+                        "note": "Durch Nutzerfeedback dauerhaft blockiert.",
+                    }
+                )
+            else:
+                safety = record.behavior.safety
         adaptive_updates, manual_override = _adapt_sensor_weights(
             record,
             current_context,
             correct=correct,
         )
+        if correct and prediction is not None:
+            safety = record.behavior.safety
         behavior = record.behavior.model_copy(
             update={
                 "patterns": patterns[-_MAX_PATTERNS:],
@@ -532,6 +625,11 @@ class BehaviorEngine:
                 "last_trained_at": now,
                 "correct_feedback_count": correct_count,
                 "incorrect_feedback_count": incorrect_count,
+                "feedback_log": [
+                    *record.behavior.feedback_log,
+                    feedback_kind,
+                ][-_MAX_FEEDBACK_LOG:],
+                "safety": safety,
                 "adaptive_weight_updates": [
                     *record.behavior.adaptive_weight_updates,
                     *adaptive_updates,
@@ -557,6 +655,43 @@ class BehaviorEngine:
         )
         return self._save_behavior(record_for_save, behavior)
 
+    def set_dry_run(self, actuator_entity_id: str, *, enabled: bool) -> ActuatorRecord:
+        record = self._store.get(actuator_entity_id)
+        now = datetime.now(timezone.utc)
+        behavior = record.behavior.model_copy(
+            update={
+                "dry_run_enabled": enabled,
+                "dry_run_started_at": now if enabled else record.behavior.dry_run_started_at,
+                "reason": (
+                    "Dry-run aktiv; freigegebene Aktionen werden protokolliert, aber nicht geschaltet."
+                    if enabled
+                    else "Dry-run beendet."
+                ),
+            }
+        )
+        return self._save_behavior(record, behavior)
+
+    def refresh_planning_insights(self) -> list[ActuatorRecord]:
+        records = self._store.list()
+        groups = _derive_actuator_groups(records)
+        scenes = _derive_scene_suggestions(records)
+        insights_by_actuator = _derive_agent_insights(records)
+        updated: list[ActuatorRecord] = []
+        for record in records:
+            behavior = record.behavior.model_copy(
+                update={
+                    "actuator_groups": [
+                        group for group in groups if record.actuator_entity_id in group.member_entity_ids
+                    ],
+                    "scene_suggestions": [
+                        scene for scene in scenes if record.actuator_entity_id in scene.member_entity_ids
+                    ],
+                    "agent_insights": insights_by_actuator.get(record.actuator_entity_id, []),
+                }
+            )
+            updated.append(self._save_behavior(record, behavior))
+        return updated
+
     def rollback_model(
         self,
         actuator_entity_id: str,
@@ -966,11 +1101,19 @@ class BehaviorEngine:
         - Wenn current_entities gesetzt ist, kommt die Auswertung direkt aus dem
           WebSocket-State-Cache statt aus einer frischen REST-Abfrage.
         """
+        event_received_at = datetime.now(timezone.utc)
+        records = self._store.list()
         # Aktor direkt evaluieren
-        for record in self._store.list():
+        for record in records:
             if record.actuator_entity_id == entity_id:
                 try:
-                    self.evaluate(record.actuator_entity_id, current_entities=current_entities)
+                    self.evaluate(
+                        record.actuator_entity_id,
+                        current_entities=current_entities,
+                        trigger_entity_id=entity_id,
+                        trigger_state=_event_state(new_state),
+                        event_received_at=event_received_at,
+                    )
                 except Exception:
                     logger.exception("Event-basierte Vorhersage fehlgeschlagen für %s", record.actuator_entity_id)
                 return
@@ -979,7 +1122,7 @@ class BehaviorEngine:
         # Kontext-Entity: alle Aktoren finden, die diesen Kontext nutzen
         affected_actuators = [
             record.actuator_entity_id
-            for record in self._store.list()
+            for record in records
             if (
                 record.assignment.selected_numeric_entity_id == entity_id
                 or entity_id in record.assignment.selected_context_entity_ids
@@ -992,6 +1135,9 @@ class BehaviorEngine:
                     context_state_overrides={entity_id: event_state},
                     context_changed_at_overrides={entity_id: event_changed_at},
                     current_entities=current_entities,
+                    trigger_entity_id=entity_id,
+                    trigger_state=event_state,
+                    event_received_at=event_received_at,
                 )
             except Exception:
                 logger.exception("Event-basierte Vorhersage fehlgeschlagen für %s", actuator_entity_id)
@@ -1019,6 +1165,208 @@ def _event_changed_at(new_state: dict[str, object] | None) -> datetime | None:
     return parsed
 
 
+def _elapsed_ms(started_perf: float) -> int:
+    return max(0, int((perf_counter() - started_perf) * 1000))
+
+
+def _append_decision_trace(
+    behavior: BehaviorState,
+    *,
+    trigger_entity_id: str | None,
+    trigger_state: str | None,
+    prediction: BehaviorPrediction | None,
+    safety_blockers: list[str],
+    duration_ms: int,
+    event_received_at: datetime | None,
+    decision_to_service_ms: int | None,
+    executed: bool,
+    source: str,
+) -> BehaviorState:
+    now = datetime.now(timezone.utc)
+    blocked = prediction is None or bool(safety_blockers)
+    trace = DecisionTrace(
+        trace_id=f"{now.strftime('%Y%m%d%H%M%S%f')}.{trigger_entity_id or 'manual'}",
+        created_at=now,
+        trigger_entity_id=trigger_entity_id,
+        trigger_state=trigger_state,
+        target_state=prediction.target_state if prediction is not None else None,
+        confidence=prediction.confidence if prediction is not None else None,
+        executed=executed,
+        blocked=blocked,
+        reason=(
+            prediction.execution_reason
+            if prediction is not None
+            else behavior.reason
+        ),
+        blockers=safety_blockers if prediction is not None else ["Keine fällige Vorhersage."],
+        duration_ms=duration_ms,
+    )
+    updated = behavior.model_copy(
+        update={
+            "decision_timeline": [
+                *behavior.decision_timeline,
+                trace,
+            ][-_MAX_DECISION_TRACES:],
+        }
+    )
+    if event_received_at is None:
+        return updated
+    return _append_latency_measurement(
+        updated,
+        trigger_entity_id=trigger_entity_id,
+        event_received_at=event_received_at,
+        event_to_decision_ms=duration_ms,
+        decision_to_service_ms=decision_to_service_ms,
+        executed=executed,
+        source=source,
+    )
+
+
+def _append_latency_measurement(
+    behavior: BehaviorState,
+    *,
+    trigger_entity_id: str | None,
+    event_received_at: datetime | None,
+    event_to_decision_ms: int | None,
+    decision_to_service_ms: int | None,
+    executed: bool,
+    source: str,
+) -> BehaviorState:
+    if event_received_at is None:
+        return behavior
+    now = datetime.now(timezone.utc)
+    event_to_done_ms = max(0, int((now - event_received_at).total_seconds() * 1000))
+    measurement = LatencyMeasurement(
+        measured_at=now,
+        trigger_entity_id=trigger_entity_id,
+        event_to_decision_ms=event_to_decision_ms,
+        decision_to_service_ms=decision_to_service_ms,
+        event_to_done_ms=event_to_done_ms,
+        executed=executed,
+        source=source,
+    )
+    return behavior.model_copy(
+        update={
+            "latency_measurements": [
+                *behavior.latency_measurements,
+                measurement,
+            ][-_MAX_LATENCY_MEASUREMENTS:],
+        }
+    )
+
+
+def _derive_actuator_groups(records: list[ActuatorRecord]) -> list[ActuatorGroup]:
+    by_area: dict[str, list[str]] = {}
+    for record in records:
+        area = _area_hint(record)
+        if area:
+            by_area.setdefault(area, []).append(record.actuator_entity_id)
+    return [
+        ActuatorGroup(
+            group_id=_slug(f"area_{area}"),
+            name=f"Raum {area}",
+            area_name=area,
+            member_entity_ids=sorted(entity_ids),
+            reason="Aktor-Gruppe aus gemeinsamer Raum-/Kontextzuordnung abgeleitet.",
+        )
+        for area, entity_ids in sorted(by_area.items())
+        if len(entity_ids) >= 2
+    ]
+
+
+def _derive_scene_suggestions(records: list[ActuatorRecord]) -> list[SceneSuggestion]:
+    scenes: list[SceneSuggestion] = []
+    by_context: dict[tuple[str, str], list[str]] = {}
+    for record in records:
+        for pattern in record.behavior.patterns:
+            for entity_id, state in pattern.context_states.items():
+                by_context.setdefault((entity_id, state), []).append(record.actuator_entity_id)
+    for (entity_id, state), members in sorted(by_context.items()):
+        unique_members = sorted(set(members))
+        if len(unique_members) < 2:
+            continue
+        scenes.append(
+            SceneSuggestion(
+                scene_id=_slug(f"{entity_id}_{state}"),
+                label=f"{entity_id} ist {state}",
+                member_entity_ids=unique_members,
+                confidence=min(1.0, len(members) / max(3, len(unique_members) * 2)),
+                reason="Mehrere Aktoren reagieren historisch auf denselben Kontext.",
+                last_seen_at=max(
+                    (
+                        pattern.observed_at
+                        for record in records
+                        for pattern in record.behavior.patterns
+                        if pattern.context_states.get(entity_id) == state
+                    ),
+                    default=None,
+                ),
+            )
+        )
+    return scenes[-20:]
+
+
+def _derive_agent_insights(records: list[ActuatorRecord]) -> dict[str, list[AgentInsight]]:
+    result: dict[str, list[AgentInsight]] = {}
+    for record in records:
+        insights: list[AgentInsight] = []
+        if record.behavior.automation_conflicts:
+            insights.append(
+                AgentInsight(
+                    insight_id=f"{record.actuator_entity_id}.automation_conflict",
+                    severity="warning",
+                    title="Automation-Konflikt prüfen",
+                    detail="Eine passende HA-Automation kann parallel zu SillyHome schalten.",
+                    action="Automation pausieren oder SillyHome im Shadow-Modus lassen.",
+                )
+            )
+        if record.behavior.latency_measurements:
+            durations = [
+                item.event_to_done_ms
+                for item in record.behavior.latency_measurements
+                if item.event_to_done_ms is not None
+            ]
+            if durations and max(durations) > 1500:
+                insights.append(
+                    AgentInsight(
+                        insight_id=f"{record.actuator_entity_id}.latency",
+                        severity="warning",
+                        title="Schalt-Latenz beobachten",
+                        detail=f"Letzte maximale Event-Latenz: {max(durations)} ms.",
+                        action="WebSocket-Status, HA-Servicezeit und Sensor-Routing pruefen.",
+                    )
+                )
+        if record.behavior.incorrect_feedback_count > record.behavior.correct_feedback_count:
+            insights.append(
+                AgentInsight(
+                    insight_id=f"{record.actuator_entity_id}.feedback",
+                    severity="warning",
+                    title="Viele negative Feedbacks",
+                    detail="Das Modell trifft aktuell mehr falsche als richtige Entscheidungen.",
+                    action="Kontextzuordnung, Gewichtung oder Modell-Rollback pruefen.",
+                )
+            )
+        result[record.actuator_entity_id] = insights[:5]
+    return result
+
+
+def _area_hint(record: ActuatorRecord) -> str | None:
+    for candidate in [*record.context_candidates, *record.numeric_candidates]:
+        if candidate.area_name:
+            return candidate.area_name
+    return None
+
+
+def _slug(value: str) -> str:
+    result = []
+    for char in value.lower():
+        if char.isalnum():
+            result.append(char)
+        elif char in {".", "_", "-", " "}:
+            result.append("_")
+    return "".join(result).strip("_")[:64] or "item"
+
+
 def _confidence_threshold_for(profile: SafetyProfile, target_state: str) -> float:
     if target_state == "on" and profile.min_confidence_on is not None:
         return profile.min_confidence_on

app/main.py

@@ -117,7 +117,7 @@ async def lifespan(app: FastAPI) -> AsyncIterator[None]:
 app = FastAPI(
     title="SillyHome Next API",
     description="Lokales Smart-Home-Intelligenzsystem für Home Assistant.",
-    version="1.5.3",
+    version="1.7.0",
     lifespan=lifespan,
 )
 app.state.settings = load_settings()
@@ -259,11 +259,7 @@ async def _ha_event_listener(app: FastAPI, client: HaClient) -> None:
         if ws_status is not None:
             ws_status.status = "connecting"
         try:
-            async with websockets.connect(
+            async with websockets.connect(ws_url, ping_interval=None) as websocket:
-                ws_url,
-                ping_interval=30,
-                ping_timeout=30,
-            ) as websocket:
                 auth_required_msg = await websocket.recv()
                 auth_required_data = json.loads(auth_required_msg)
                 if auth_required_data.get("type") != "auth_required":
@@ -315,8 +311,6 @@ async def _ha_event_listener(app: FastAPI, client: HaClient) -> None:
                             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(

app/static/index.html

@@ -52,6 +52,8 @@
     .panel-title { display:flex; align-items:center; justify-content:space-between; gap:10px; margin-bottom:8px; }
     .toolbar { display:flex; flex-wrap:wrap; gap:8px; align-items:center; margin:10px 0; }
     .toolbar button { margin-top:0; }
+    .detail-tools { display:grid; grid-template-columns:repeat(auto-fit,minmax(180px,1fr)); gap:8px; margin:10px 0; align-items:end; }
+    .detail-tools button { margin-top:0; }
     details.collapsible > summary,
     .manual-context > summary,
     .group-panel > summary { cursor:pointer; font-weight:800; color:#eaf1f8; }
@@ -144,20 +146,17 @@
     <div class="brand">
       <div class="brand-row">
         <span class="brand-mark">SH</span>
-        <h1>SillyHome Next</h1>
+        <h1>SillyHome</h1>
       </div>
-      <p>Arbeitsdashboard für gelernte Home-Assistant-Bedienung: Geräte auswählen, Lernstand prüfen, Freigaben steuern.</p>
+      <p>Geräte, Lernen, Freigaben und Systemzustand.</p>
-      <p class="notice">Sicherer Start: Zuerst wird nur beobachtet und vorhergesagt. Ohne deine spätere Freigabe wird nichts geschaltet.</p>
     </div>
     <div class="header-actions">
       <label for="section-jump">Menü</label>
       <select id="section-jump" onchange="showView(this.value)">
         <option value="status-section">Startseite / System</option>
         <option value="observed">Lernen</option>
-        <option value="detail">Details</option>
         <option value="choose">Discovery & Einrichtung</option>
         <option value="settings">Einstellungen</option>
-        <option value="guide">Ablauf</option>
       </select>
       <div class="status-pill"><span class="dot"></span><span id="load-budget">Seite bereit, Status folgt ...</span></div>
     </div>
@@ -166,11 +165,9 @@
 <main>
   <section class="control-panel app-view" id="choose">
     <div class="panel-title">
-      <h2>Steuerung</h2>
+      <h2>Discovery & Einrichtung</h2>
-      <span class="chip">v1</span>
     </div>
-    <p class="muted">Wähle eine Lampe, einen Rollladen oder einen anderen unterstützten Aktor. Du wählst keine Sensoren und erstellst keine Regeln.</p>
+    <label for="actuator-input">Entity-ID</label>
-    <label for="actuator-input">Entitätsname oder Gerät aus Home Assistant</label>
     <input id="actuator-input" list="actuator-options" placeholder="z. B. light.licht_abstellraum" autocomplete="off">
     <datalist id="actuator-options"></datalist>
     <div class="inline-controls">
@@ -200,16 +197,15 @@
         <input id="actuator-search" placeholder="Raum, Gerät oder Entity" oninput="renderActuatorSelect()" onfocus="ensureActuatorDiscovery()" autocomplete="off">
       </div>
     </div>
-    <label for="actuator-select">Oder aus Liste wählen</label>
+    <label for="actuator-select">Geräteliste</label>
     <select id="actuator-select" onchange="selectActuatorFromList()" onfocus="ensureActuatorDiscovery()">
       <option value="">Geräteliste bei Bedarf laden</option>
     </select>
     <button onclick="configureActuator()">Gerät hinzufügen und Beobachtung starten</button>
     <button class="secondary" onclick="ensureActuatorDiscovery()">Geräteliste laden</button>
-    <p id="actuator-config-result" class="muted">Noch kein Aktor ausgewählt.</p>
+    <p id="actuator-config-result" class="muted">Bereit.</p>
     <details class="manual-context">
       <summary>Vorschläge anzeigen</summary>
-      <p class="muted">Vorschläge können Home Assistant stark abfragen und werden deshalb nicht beim Start geladen.</p>
       <button class="secondary" onclick="loadActuatorSuggestions()">Vorschläge laden</button>
     </details>
     <div id="actuator-suggestions" class="card-list"></div>
@@ -219,7 +215,6 @@
     <div class="panel-title">
       <div>
         <h2>Beobachtete Geräte</h2>
-        <p class="muted">Öffne „Details“, um Lernfortschritt, aktuelle Vorhersage und den automatisch gefundenen Kontext zu sehen.</p>
       </div>
       <button class="secondary compact" onclick="loadOverview()">Aktualisieren</button>
     </div>
@@ -227,8 +222,10 @@
   </section>
 
   <section class="detail-panel app-view" id="detail">
-    <h2>Lernfortschritt und Freigabe</h2>
+    <div class="panel-title">
-    <p class="muted">Die Freigabe erscheint erst, wenn genug eindeutig zugeordnete Handlungen gelernt wurden. Vorher bleibt das Gerät sicher im Beobachtungsmodus.</p>
+      <h2>Details</h2>
+      <button class="secondary compact" onclick="showView('observed')">Zurück</button>
+    </div>
     <div id="actuator-detail" class="muted">Öffne bei einem beobachteten Gerät die Details.</div>
   </section>
 
@@ -236,7 +233,6 @@
     <div class="panel-title">
       <div>
         <h2>System & Cache</h2>
-        <p class="muted">Die Startansicht nutzt lokale Summaries und Cache-Daten. Home-Assistant-Discovery lädt erst bei Bedarf.</p>
       </div>
       <button class="secondary compact" onclick="loadStatus()">Status prüfen</button>
     </div>
@@ -260,40 +256,9 @@
           <option value="de">Deutsch</option>
           <option value="en">English</option>
         </select>
-        <p class="muted">Die API speichert stabile technische Werte. Die Oberfläche übersetzt sie in die gewählte Sprache.</p>
-      </div>
-      <div>
-        <h3>Performance-Standard</h3>
-        <p>Startansichten dürfen maximal 3 Sekunden brauchen. Schwere Daten werden nur nach Menüwechsel oder bei Bearbeitung geladen.</p>
       </div>
     </div>
   </section>
-
-  <section class="guide-panel app-view" id="guide">
-    <details class="collapsible">
-    <summary><span>So gehst du vor</span></summary>
-    <div class="steps">
-      <div class="step">
-        <span class="step-number">1</span>
-        <h3>Aktor auswählen</h3>
-        <p><strong>Wo?</strong> Links im Feld „Gerät auswählen“.</p>
-        <p><strong>Was passiert?</strong> SillyHome ordnet Raum, Sensoren, Zustände und vorhandene Historie automatisch zu.</p>
-      </div>
-      <div class="step">
-        <span class="step-number">2</span>
-        <h3>Wie gewohnt bedienen</h3>
-        <p><strong>Wo?</strong> Weiterhin in Home Assistant, an Schaltern oder über deine bisherigen Bedienwege.</p>
-        <p><strong>Was passiert?</strong> SillyHome lernt deine Handlungen und zeigt Vorhersagen an, schaltet aber noch nicht selbst.</p>
-      </div>
-      <div class="step">
-        <span class="step-number">3</span>
-        <h3>Später freigeben</h3>
-        <p><strong>Wo?</strong> In den Details des ausgewählten Geräts, sobald genug Verhalten gelernt wurde.</p>
-        <p><strong>Was passiert?</strong> Erst dann darf SillyHome passende Vorhersagen automatisch ausführen. Die Freigabe kann jederzeit gestoppt werden.</p>
-      </div>
-    </div>
-    </details>
-  </section>
 </main>
 <script>
 const escapeHtml = value => String(value ?? "")
@@ -309,7 +274,12 @@ let manualContextState = {options: [], selected: new Set()};
 let cachedActuators = null;
 let cachedEntities = null;
 let cachedDiscovery = null;
+let cachedSystemOverview = null;
+let cachedDashboardOverview = null;
+let cachedDetailHtml = new Map();
 let discoveryLoadPromise = null;
+let overviewLoadPromise = null;
+let systemLoadPromise = null;
 let currentSensorWeightGroups = [];
 let visibleActuatorLimit = 24;
 const ACTUATOR_RESULT_LIMIT = 50;
@@ -465,14 +435,29 @@ function jumpToSection(target) {
 }
 
 function showView(viewId) {
+  if (viewId === "detail" && !currentActuatorId) {
+    viewId = "observed";
+  }
   for (const section of document.querySelectorAll(".app-view")) {
     section.classList.toggle("active", section.id === viewId);
   }
   localStorage.setItem("sillyhome.ui.view", viewId);
   if (viewId === "status-section") {
-    void loadSystemOverview();
+    if (cachedSystemOverview) {
+      renderDashboardStatus(cachedSystemOverview);
+      refreshSystemOverviewInBackground();
+    } else {
+      void loadSystemOverview();
+    }
   } else if (viewId === "observed") {
-    void loadOverview();
+    if (cachedActuators) {
+      renderConfiguredActuators();
+      refreshOverviewInBackground();
+    } else {
+      void loadOverview();
+    }
+  } else if (viewId === "choose") {
+    if (cachedDiscovery) renderActuatorDiscovery();
   } else if (viewId === "settings") {
     syncSettingsView();
   }
@@ -484,8 +469,10 @@ function setLanguage(language) {
   localStorage.setItem("sillyhome.ui.language", uiLang);
   syncSettingsView();
   if (cachedActuators) renderConfiguredActuators();
-  void loadSystemOverview();
+  if (cachedSystemOverview) renderDashboardStatus(cachedSystemOverview);
-  if (currentActuatorId) void showActuator(currentActuatorId);
+  if (currentActuatorId && cachedDetailHtml.has(currentActuatorId)) {
+    document.getElementById("actuator-detail").innerHTML = cachedDetailHtml.get(currentActuatorId);
+  }
 }
 
 function syncSettingsView() {
@@ -514,6 +501,9 @@ function invalidateDashboardCache() {
   cachedActuators = null;
   cachedEntities = null;
   cachedDiscovery = null;
+  cachedDashboardOverview = null;
+  cachedSystemOverview = null;
+  cachedDetailHtml.clear();
 }
 
 async function api(path, options = {}) {
@@ -654,13 +644,24 @@ function optionGroups(entities, selectedIds = new Set()) {
 }
 
 async function loadOverview() {
+  if (overviewLoadPromise) return overviewLoadPromise;
+  overviewLoadPromise = doLoadOverview().finally(() => {
+    overviewLoadPromise = null;
+  });
+  return overviewLoadPromise;
+}
+
+async function doLoadOverview() {
   const startedAt = performance.now();
   const budget = document.getElementById("load-budget");
   if (budget) budget.textContent = "Startdaten laden ...";
-  document.getElementById("configured-actuators").innerHTML = "<p class='muted'>Beobachtete Geräte werden geladen ...</p>";
+  if (!cachedActuators) {
+    document.getElementById("configured-actuators").innerHTML = "<p class='muted'>Beobachtete Geräte werden geladen ...</p>";
+  }
   try {
     const dashboard = await api("v1/actuators/dashboard/start");
     dashboard._load_elapsed_ms = Math.round(performance.now() - startedAt);
+    cachedDashboardOverview = dashboard;
     cachedActuators = dashboard.actuators || [];
     cachedEntities = [];
     renderDashboardStatus(dashboard);
@@ -685,12 +686,21 @@ async function loadOverview() {
 }
 
 async function loadSystemOverview() {
+  if (systemLoadPromise) return systemLoadPromise;
+  systemLoadPromise = doLoadSystemOverview().finally(() => {
+    systemLoadPromise = null;
+  });
+  return systemLoadPromise;
+}
+
+async function doLoadSystemOverview() {
   const startedAt = performance.now();
   const budget = document.getElementById("load-budget");
   if (budget) budget.textContent = "Systemübersicht lädt ...";
   try {
     const dashboard = await api("v1/actuators/dashboard/system");
     dashboard._load_elapsed_ms = Math.round(performance.now() - startedAt);
+    cachedSystemOverview = dashboard;
     cachedActuators = dashboard.actuators || cachedActuators;
     renderDashboardStatus(dashboard);
     if (budget) {
@@ -706,6 +716,22 @@ async function loadSystemOverview() {
   }
 }
 
+function refreshOverviewInBackground() {
+  if (!overviewLoadPromise) {
+    overviewLoadPromise = doLoadOverview().finally(() => {
+      overviewLoadPromise = null;
+    });
+  }
+}
+
+function refreshSystemOverviewInBackground() {
+  if (!systemLoadPromise) {
+    systemLoadPromise = doLoadSystemOverview().finally(() => {
+      systemLoadPromise = null;
+    });
+  }
+}
+
 function scheduleDashboardExtras() {
   const run = () => {
     void loadDashboardExtras();
@@ -1011,6 +1037,20 @@ function selectActuatorFromList() {
   if (value) document.getElementById("actuator-input").value = value;
 }
 
+function selectDetailActuator() {
+  const value = document.getElementById("detail-actuator-select")?.value;
+  if (value) void showActuator(value);
+}
+
+function detailActuatorOptions(selectedId) {
+  const rows = cachedActuators || [];
+  return rows.map(record => `
+    <option value="${escapeHtml(record.actuator_entity_id)}" ${record.actuator_entity_id === selectedId ? "selected" : ""}>
+      ${escapeHtml(record.friendly_name || record.device_name || record.actuator_entity_id)}
+    </option>
+  `).join("");
+}
+
 function renderManualContextSelect() {
   const select = document.getElementById("manual-context-select");
   if (!select) return;
@@ -1131,10 +1171,20 @@ async function showActuator(actuatorId, evaluationMessage = "") {
   for (const section of document.querySelectorAll(".app-view")) {
     section.classList.toggle("active", section.id === "detail");
   }
-  document.getElementById("section-jump").value = "detail";
+  document.getElementById("section-jump").value = "observed";
   localStorage.setItem("sillyhome.ui.view", "detail");
   const box = document.getElementById("actuator-detail");
-  renderActuatorDetailShell(actuatorId);
+  if (!evaluationMessage && cachedDetailHtml.has(actuatorId)) {
+    box.innerHTML = cachedDetailHtml.get(actuatorId);
+    document.getElementById("detail").scrollIntoView({behavior: "smooth", block: "start"});
+    renderConfiguredActuators();
+    return;
+  }
+  if (cachedDetailHtml.has(actuatorId)) {
+    box.innerHTML = cachedDetailHtml.get(actuatorId);
+  } else {
+    renderActuatorDetailShell(actuatorId);
+  }
   try {
     const record = await api(`v1/actuators/${encodeURIComponent(actuatorId)}/detail`);
     contextOptions = [];
@@ -1356,7 +1406,6 @@ async function showActuator(actuatorId, evaluationMessage = "") {
     const manualAssignment = `
       <details class="manual-context">
         <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">
           <option value="">Keinen numerischen Hauptsensor verwenden</option>
@@ -1403,13 +1452,21 @@ async function showActuator(actuatorId, evaluationMessage = "") {
             <button class="secondary compact" onclick="setRelatedAutomation('${escapeHtml(record.actuator_entity_id)}', '${escapeHtml(automation.entity_id)}', ${automation.enabled ? "false" : "true"})">${automation.enabled ? "Pausieren" : "Fortsetzen"}</button>
           </li>`).join("")}</ul>`
       : "<p class='muted'>Keine eindeutig passende HA-Automation gefunden.</p>";
-    box.innerHTML = `
+    const detailHtml = `
       <div class="detail-header">
         <div>
           <h3>${escapeHtml(record.actuator_entity_id)}</h3>
-          <p class="muted">Alle wichtigen Aktionen für dieses Gerät.</p>
         </div>
-        <button class="secondary compact" onclick="loadOverview()">Alles aktualisieren</button>
+      </div>
+      <div class="detail-tools">
+        <button class="secondary" onclick="showView('observed')">Zurück zur Übersicht</button>
+        <div>
+          <label for="detail-actuator-select">Anderes Gerät</label>
+          <select id="detail-actuator-select" onchange="selectDetailActuator()">
+            ${detailActuatorOptions(record.actuator_entity_id)}
+          </select>
+        </div>
+        <button class="secondary" onclick="showActuator('${escapeHtml(record.actuator_entity_id)}', 'Aktualisiert.')">Aktualisieren</button>
       </div>
       <div class="grid-two">
         <div>
@@ -1417,7 +1474,6 @@ async function showActuator(actuatorId, evaluationMessage = "") {
           <p><strong>Status:</strong> <span class="${statusClass(record)}">${escapeHtml(lifecycleLabel(record))}</span></p>
           <p><strong>Kontextzuordnung:</strong> automatisch erledigt</p>
           <p><strong>Zuordnungssicherheit:</strong> ${Math.round(record.assignment.confidence * 100)} %</p>
-          <p class="muted">Dieser Wert beschreibt, wie sicher Raum, Sensoren und Zustände zu diesem Gerät passen.</p>
           <p><strong>Ergebnis:</strong> ${escapeHtml(record.assignment.reason)}</p>
         </div>
         <div>
@@ -1427,11 +1483,10 @@ async function showActuator(actuatorId, evaluationMessage = "") {
           <p><strong>Davon eindeutig geregelt:</strong> ${record.behavior.high_confidence_sample_count}</p>
           <p><strong>Erkannte HA-Automationen:</strong> ${escapeHtml(learnedAutomationActions)}</p>
           <p><strong>Letztes Training:</strong> ${escapeHtml(formatDateTime(record.behavior.last_trained_at))}</p>
-          <p><strong>Was noch passiert:</strong> ${escapeHtml(record.behavior.reason)}</p>
+          <p><strong>Statusgrund:</strong> ${escapeHtml(record.behavior.reason)}</p>
           <p><strong>Freigabestatus:</strong> <span class="${record.behavior.activation_ready ? "ok" : "warn"}">${escapeHtml(record.behavior.activation_reason)}</span></p>
           <div class="actions">${activationButton}</div>
           <button class="secondary" onclick="evaluateActuator('${escapeHtml(record.actuator_entity_id)}')">Aktuelle Situation auswerten</button>
-          <p class="muted">Die Prüfung simuliert keinen Sensorwechsel und schaltet keinen Aktor.</p>
           ${evaluationMessage ? `<p class="ok">${escapeHtml(evaluationMessage)}</p>` : ""}
         </div>
       </div>
@@ -1448,20 +1503,21 @@ async function showActuator(actuatorId, evaluationMessage = "") {
       ${adaptivePanel}
       ${anomalyPanel}
       <h3>Passende Home-Assistant-Automationen</h3>
-      <p class="muted">Bei einer Übernahme pausiert SillyHome diese Automationen. Beim Stoppen können sie gezielt fortgesetzt werden.</p>
       <button class="secondary compact" onclick="refreshRelatedAutomations('${escapeHtml(record.actuator_entity_id)}')">Automationen neu suchen</button>
       ${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>Sensor-Gewichtung</h3>
-      <p class="muted">Automatische Relevanz kommt aus der Zuordnung. Die aktive Gewichtung kannst du korrigieren; Gruppen bündeln mehrere Sensoren/Zustände.</p>
       ${weightControls}
       ${weightGroupControls}
       <h3>Verwendete Sensoren/Zustände ändern</h3>
       ${currentContextControls}
       ${manualAssignment}
     `;
+    box.innerHTML = detailHtml;
+    cachedDetailHtml.set(actuatorId, detailHtml);
     document.getElementById("detail").scrollIntoView({behavior: "smooth", block: "start"});
+    renderConfiguredActuators();
   } catch (error) {
     box.textContent = error.message;
   }
@@ -1472,13 +1528,13 @@ function renderActuatorDetailShell(actuatorId) {
     <div class="detail-header">
       <div>
         <h3>${escapeHtml(actuatorId)}</h3>
-        <p class="muted">Basisdaten werden geladen ...</p>
+        <p class="muted">Lädt ...</p>
       </div>
     </div>
     <div class="metric-grid">
-      <div class="metric"><strong>Phase 1</strong>Aktuelle Einstellung</div>
+      <div class="metric"><strong>Status</strong>...</div>
-      <div class="metric"><strong>Phase 2</strong>Lernstand</div>
+      <div class="metric"><strong>Lernen</strong>...</div>
-      <div class="metric"><strong>Phase 3</strong>Kontextvorschläge</div>
+      <div class="metric"><strong>Kontext</strong>...</div>
     </div>
   `;
 }
@@ -1768,8 +1824,11 @@ async function startDashboard() {
   document.getElementById("configured-actuators").innerHTML = "<div class='empty-state'>Öffne „Lernen“, um Geräte zu laden.</div>";
   document.getElementById("actuator-detail").innerHTML = "<div class='empty-state'>Wähle später ein Gerät aus der Übersicht.</div>";
   syncSettingsView();
-  document.getElementById("section-jump").value = "status-section";
+  const initialView = localStorage.getItem("sillyhome.ui.view") === "detail"
-  showView("status-section");
+    ? "observed"
+    : (localStorage.getItem("sillyhome.ui.view") || "status-section");
+  document.getElementById("section-jump").value = initialView;
+  showView(initialView);
   await new Promise(resolve => requestAnimationFrame(resolve));
   setTimeout(() => void loadStatus(), 100);
 }

docs/V1_5_4_OPERATING_GUIDE.md

@@ -0,0 +1,35 @@
+# SillyHome Next v1.5.4 Operating Guide
+
+Diese Version korrigiert Ingress-Logging und Dashboard-Navigation.
+
+## Ingress-/Access-Logs
+
+- Das Add-on startet Uvicorn ohne `--proxy-headers` und ohne
+  `--forwarded-allow-ips='*'`.
+- Vorher konnte Uvicorn LAN-Adressen aus `X-Forwarded-For` anzeigen. Diese
+  Adresse war dann der urspruengliche Client oder Home-Assistant-Proxy, nicht
+  der direkte Container-Peer.
+- Nach dem Update sollten Access-Logs den direkten Docker-/Ingress-Peer zeigen.
+  `GET ... HTTP/1.1` bleibt normal und ist kein Hinweis auf fehlendes Streaming.
+
+## Dashboard-Verhalten
+
+- Die Startseite nutzt weiter `/v1/actuators/dashboard/system`.
+- Die Lernuebersicht nutzt weiter `/v1/actuators/dashboard/start`.
+- Bereits geladene System-, Lern- und Discovery-Daten bleiben beim Wechseln der
+  Ansichten im Browser erhalten und werden nur im Hintergrund aufgefrischt.
+- Details sind kein eigener Menuepunkt mehr. Sie werden nur ueber ein
+  ausgewaehltes beobachtetes Geraet geoeffnet.
+- Ein bereits geoeffneter Aktor zeigt seine Detaildaten sofort aus dem
+  Browser-Cache. Neue Detaildaten werden erst ueber `Details aktualisieren`
+  oder nach einer Speichern-/Schaltaktion geladen.
+
+## Pruefung
+
+1. Add-on aktualisieren und neu starten.
+2. Ingress hart neu laden.
+3. Zwischen Startseite, Lernen und Discovery wechseln.
+4. Erwartung: Bereits geladene Inhalte bleiben sichtbar; keine volle
+   Neuladung bei jedem Ansichtswechsel.
+5. Details eines Aktors oeffnen, wegwechseln und wieder Details oeffnen.
+   Erwartung: Die zuletzt geladene Detailansicht steht sofort wieder da.

docs/V1_6_0_OPERATING_GUIDE.md

@@ -0,0 +1,36 @@
+# SillyHome Next v1.6.0 Operating Guide
+
+v1.6.0 trennt Startansicht, Aktoruebersicht, Discovery und Detaildaten staerker.
+
+## API-Pfade
+
+- `GET /v1/actuators/dashboard/system`
+  - nur System- und Cache-Metadaten
+  - keine Aktorenliste
+  - kein vollstaendiges Entity-Payload aus SQLite
+- `GET /v1/actuators/dashboard/start`
+  - Aktor-Summaries
+  - Entity-Metadaten nur fuer konfigurierte Aktoren
+  - keine Discovery-Gruppen und keine Jobliste
+- `GET /v1/actuators/discovery`
+  - steuerbare HA-Entities
+  - nutzt SQLite-Cache, liest HA nur bei Cache-Miss oder `refresh=true`
+- `GET /v1/actuators/{id}/detail`
+  - genau ein ausgewaehlter Aktor
+  - kompakte Modell-/Kontextdaten
+
+## Dashboard
+
+- Frontend zeigt Daten an und loest gezielte Aktionen aus.
+- Backend liefert schlanke View-Daten.
+- Worker aktualisieren HA-Entity-/Discovery-Cache beim Start und danach
+  stündlich.
+- Die Detailansicht gehoert zu einem Aktor und hat eigene Navigation:
+  Zurueck, anderes Geraet, Aktualisieren.
+
+## Erwartete Wirkung
+
+- Systemstart muss ohne Entity-Materialisierung reagieren.
+- Lernen und Details laden nur ihren eigenen Datenkern.
+- Discovery bleibt ein eigener Bedarfspfad.
+- Texte im Dashboard sind kurz und handlungsnah.

docs/V1_7_0_OPERATING_GUIDE.md

@@ -0,0 +1,45 @@
+# SillyHome Next v1.7.0 Operating Guide
+
+v1.7.0 erweitert den Produktivbetrieb um Diagnose, Backup, Dry-run und
+Planungshilfen.
+
+## Diagnose
+
+- Jede Auswertung speichert eine kompakte `decision_timeline` am Aktor.
+- Event-basierte Auswertungen speichern zusaetzlich `latency_measurements`.
+- Die Timeline beantwortet: was war der Ausloeser, welches Ziel wurde
+  vorhergesagt, wurde geschaltet oder blockiert, und warum.
+
+## Backup und Restore
+
+- `GET /v1/actuators/backup/export` exportiert Aktoren, Reconciliation-Status
+  und Job-Historie als JSON.
+- `POST /v1/actuators/backup/restore` spielt diesen Stand wieder ein.
+- Ohne `replace_existing=true` werden vorhandene Aktoren nicht ueberschrieben.
+
+## Dry-run
+
+- `POST /v1/actuators/{entity_id}/dry-run` aktiviert oder beendet den Testmodus.
+- Im Dry-run werden freigegebene Aktionen bewertet und protokolliert, aber nicht
+  an Home Assistant gesendet.
+
+## Feedback
+
+Feedback akzeptiert neben `correct`/`expected_state` nun optionale Typen:
+
+- `correct`
+- `wrong`
+- `too_early`
+- `too_late`
+- `never_automate`
+
+`never_automate` setzt eine manuelle Sicherheitssperre am Aktor.
+
+## Planung
+
+`POST /v1/actuators/planning/refresh` berechnet lokale Hinweise:
+
+- Aktorgruppen aus gemeinsamen Raum-/Kontextdaten
+- einfache Szenenvorschlaege aus gemeinsamem Kontextverhalten
+- Agent-Insights fuer Konflikte, Latenz und auffaelliges Feedback
+

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "sillyhome-next"
-version = "1.5.3"
+version = "1.7.0"
 description = "Lokales Smart-Home-Intelligenzsystem für Home Assistant"
 requires-python = ">=3.11"
 dependencies = [

tests/api/test_actuators.py

@@ -1,18 +1,19 @@
 from __future__ import annotations
 
-from time import perf_counter
 from datetime import datetime, timedelta, timezone
 from pathlib import Path
+from time import perf_counter
 
+import pytest
 from fastapi.testclient import TestClient
 
+from app.api.v1.actuators import _deduplicate_actuator_ids
 from app.actuators.cache_db import DashboardCache
 from app.actuators.lifecycle import ActuatorReconciliationService
 from app.actuators.models import JobStatus, ModelSnapshot
 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 (
@@ -353,6 +354,51 @@ def test_feedback_adapts_sensor_weights_and_model_can_rollback(tmp_path: Path) -
     assert rollback.json()["behavior"]["active_model_version"] == version_id
 
 
+def test_feedback_never_automate_sets_manual_block(tmp_path: Path) -> None:
+    with TestClient(app) as client:
+        _install_service(tmp_path)
+        client.post(
+            "/v1/actuators",
+            json={"actuator_entity_id": "light.abstellkammer"},
+        )
+
+        feedback = client.post(
+            "/v1/actuators/light.abstellkammer/feedback",
+            json={"correct": False, "kind": "never_automate"},
+        )
+
+    assert feedback.status_code == 200
+    payload = feedback.json()
+    assert payload["behavior"]["safety"]["manual_block"] is True
+    assert payload["behavior"]["feedback_log"][-1] == "never_automate"
+
+
+def test_backup_export_restore_and_planning_refresh(tmp_path: Path) -> None:
+    with TestClient(app) as client:
+        _install_service(tmp_path)
+        client.post("/v1/actuators", json={"actuator_entity_id": "light.abstellkammer"})
+
+        backup = client.get("/v1/actuators/backup/export")
+        dry_run = client.post(
+            "/v1/actuators/light.abstellkammer/dry-run",
+            json={"enabled": True},
+        )
+        planning = client.post("/v1/actuators/planning/refresh")
+        restore = client.post(
+            "/v1/actuators/backup/restore",
+            json={"backup": backup.json(), "replace_existing": True},
+        )
+
+    assert backup.status_code == 200
+    assert backup.json()["records"][0]["actuator_entity_id"] == "light.abstellkammer"
+    assert dry_run.status_code == 200
+    assert dry_run.json()["behavior"]["dry_run_enabled"] is True
+    assert planning.status_code == 200
+    assert "agent_insights" in planning.json()[0]["behavior"]
+    assert restore.status_code == 200
+    assert restore.json()["restored_records"] == 1
+
+
 def test_summary_is_lightweight_and_uses_cached_entity_metadata(tmp_path: Path) -> None:
     with TestClient(app) as client:
         _install_service(tmp_path)
@@ -467,6 +513,30 @@ def test_dashboard_reports_performance_budget_and_anomalies(tmp_path: Path) -> N
     assert anomalies_response.json()
 
 
+def test_dashboard_system_and_start_do_not_materialize_entity_cache(
+    tmp_path: Path,
+    monkeypatch: pytest.MonkeyPatch,
+) -> 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"})
+
+        def fail_full_payload(self: DashboardCache) -> dict[str, object]:
+            raise AssertionError("full entity payload must not be loaded")
+
+        monkeypatch.setattr(DashboardCache, "load_entities_payload", fail_full_payload)
+
+        system_response = client.get("/v1/actuators/dashboard/system")
+        start_response = client.get("/v1/actuators/dashboard/start")
+
+    assert system_response.status_code == 200
+    assert system_response.json()["actuators"] == []
+    assert system_response.json()["cache"]["entity_count"] == 4
+    assert start_response.status_code == 200
+    assert start_response.json()["actuators"][0]["friendly_name"] == "Abstellkammer Licht"
+
+
 def test_actuator_detail_uses_compact_payload(tmp_path: Path) -> None:
     with TestClient(app) as client:
         _install_service(tmp_path)

tests/behavior/test_engine.py

@@ -778,3 +778,129 @@ def test_state_change_uses_event_cache_without_rest_state_query(
     assert reader.service_calls == [
         ("light", "turn_on", {"entity_id": "light.storage"})
     ]
+
+
+def test_event_evaluation_records_decision_timeline_and_latency(
+    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="on",
+                last_changed=now,
+            ),
+        ],
+        history=[],
+        logbook=[],
+    )
+    engine = BehaviorEngine(ha_reader=reader, store=store, settings=settings)
+
+    result = engine.evaluate(
+        "light.storage",
+        trigger_entity_id="binary_sensor.storage_door",
+        trigger_state="on",
+        event_received_at=now,
+    )
+
+    trace = result.behavior.decision_timeline[-1]
+    latency = result.behavior.latency_measurements[-1]
+    assert trace.trigger_entity_id == "binary_sensor.storage_door"
+    assert trace.target_state == "on"
+    assert trace.executed is True
+    assert latency.trigger_entity_id == "binary_sensor.storage_door"
+    assert latency.executed is True
+
+
+def test_dry_run_records_without_calling_service(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,
+                    "dry_run_enabled": 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="on",
+                last_changed=now,
+            ),
+        ],
+        history=[],
+        logbook=[],
+    )
+    engine = BehaviorEngine(ha_reader=reader, store=store, settings=settings)
+
+    result = engine.evaluate("light.storage")
+
+    assert reader.service_calls == []
+    assert result.behavior.dry_run_sample_count == 1
+    assert result.behavior.decision_timeline[-1].executed is False

tests/test_addon_config.py

@@ -16,3 +16,10 @@ def test_addon_version_invalidates_application_build_layer() -> None:
     config_copy = dockerfile.index("COPY config.yaml /tmp/addon-config.yaml")
     repository_clone = dockerfile.index("git clone --depth 1 --branch main")
     assert config_copy < repository_clone
+
+
+def test_addon_does_not_trust_forwarded_lan_ips() -> None:
+    run_script = Path("addon/run.sh").read_text(encoding="utf-8")
+
+    assert "--proxy-headers" not in run_script
+    assert "--forwarded-allow-ips" not in run_script

tests/test_dashboard.py

@@ -9,17 +9,18 @@ def test_dashboard_is_served_at_root() -> None:
 
     assert response.status_code == 200
     assert "SillyHome Next" in response.text
-    assert "Arbeitsdashboard für gelernte Home-Assistant-Bedienung" in response.text
+    assert "Geräte, Lernen, Freigaben und Systemzustand" in response.text
-    assert "So gehst du vor" in response.text
+    assert "So gehst du vor" not in response.text
-    assert "Steuerung" in response.text
+    assert "Discovery & Einrichtung" in response.text
-    assert "Entitätsname oder Gerät aus Home Assistant" in response.text
+    assert "Entity-ID" in response.text
-    assert "Oder aus Liste wählen" in response.text
+    assert "Geräteliste" in response.text
     assert "Liste durchsuchen" in response.text
     assert "Geräteliste bei Bedarf laden" in response.text
-    assert "Vorschläge können Home Assistant stark abfragen" in response.text
+    assert "Vorschläge können Home Assistant stark abfragen" not in response.text
-    assert "Wie gewohnt bedienen" in response.text
+    assert '<option value="detail">Details</option>' not in response.text
-    assert "Ohne deine spätere Freigabe wird nichts geschaltet" in response.text
+    assert "Wie gewohnt bedienen" not in response.text
-    assert "Du wählst keine Sensoren und erstellst keine Regeln" in response.text
+    assert "Ohne deine spätere Freigabe wird nichts geschaltet" not in response.text
+    assert "Du wählst keine Sensoren und erstellst keine Regeln" not in response.text
     assert "Freigabestatus" in response.text
     assert "SillyHome übernehmen lassen" in response.text
     assert "Passende Home-Assistant-Automationen" in response.text
@@ -28,10 +29,12 @@ def test_dashboard_is_served_at_root() -> None:
     assert "Aktuelle Situation auswerten" in response.text
     assert "Kontext selbst festlegen" in response.text
     assert "Entity-IDs manuell ergänzen" in response.text
+    assert "Zurück zur Übersicht" in response.text
+    assert "Anderes Gerät" in response.text
     assert "manual-context-freeform" in response.text
     assert "Diese Kontext-Auswahl speichern" in response.text
     assert "manual-context-select" in response.text
-    assert "Die Prüfung simuliert keinen Sensorwechsel" in response.text
+    assert "Die Prüfung simuliert keinen Sensorwechsel" not in response.text
     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
@@ -40,7 +43,9 @@ def test_dashboard_is_served_at_root() -> None:
     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 'details class="collapsible"' not in response.text
     assert 'class="group-panel"' in response.text
+    assert "cachedDetailHtml" in response.text
+    assert "refreshOverviewInBackground" in response.text
     assert "Automation-Entwurf" not in response.text
     assert "Manuelle Overrides" not in response.text

tests/test_main.py

@@ -94,8 +94,7 @@ def test_ha_event_listener_processes_state_change(tmp_path: Path) -> None:
 
             connect.assert_called_once_with(
                 "ws://homeassistant:8123/api/websocket",
-                ping_interval=30,
+                ping_interval=None,
-                ping_timeout=30,
             )
         assert fake_ws.sent == [
             {"type": "auth", "access_token": "test-token"},