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Author SHA1 Message Date
63b8684197 Document v1 acceptance and dashboard stats
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2026-06-17 07:45:30 +02:00
f8801e469a Polish v1 dashboard loading and layout
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2026-06-17 07:33:30 +02:00
787516ac67 Avoid per-request discovery classification in dashboard
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2026-06-17 01:19:59 +02:00
7ba9807a4e Prepare SillyHome Next 1.0.0 dashboard and API rework
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2026-06-17 01:13:43 +02:00
4db4276b95 Rework dashboard loading and cache entity metadata
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2026-06-17 00:41:50 +02:00
98a2b2cc38 Fix dashboard summary status rendering
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2026-06-17 00:21:14 +02:00
387e027fe2 Use lightweight actuator dashboard summaries
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2026-06-17 00:09:35 +02:00
f8bee92e64 Optimize dashboard categories and context loading
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2026-06-17 00:02:19 +02:00
9ddb065f62 Speed up HA event processing
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2026-06-16 13:58:58 +02:00
8222f24ebe Group configured actuator overview
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2026-06-16 13:51:02 +02:00
a7a2f8c78a Make SillyHome startup resilient
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2026-06-16 13:43:41 +02:00
faf4099756 Load actuator suggestions asynchronously
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2026-06-16 12:14:51 +02:00
1b2b76455a Tighten context onboarding and actuator suggestions
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2026-06-16 12:06:03 +02:00
18999ff68a Limit actuator picker results
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2026-06-16 11:43:00 +02:00
e2826e92ec Improve SillyHome discovery and feedback learning
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2026-06-16 11:38:32 +02:00
c5f42a39a9 Fix realtime HA state-change execution
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2026-06-16 10:50:28 +02:00
19 changed files with 2359 additions and 219 deletions

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@@ -1,5 +1,122 @@
# Changelog
## 1.0.2 - 2026-06-17
- v1.0-Abnahme als `docs/V1_0_ACCEPTANCE.md` dokumentiert: erledigte,
teilweise erledigte und offene v1.0.x-Punkte sind getrennt sichtbar.
- Dashboard-Startstatistik erweitert: Freigabebereitschaft, Aktiv/Shadow,
Gelernt/Wartet und gelernte Handlungen werden direkt im Startbereich
zusammengefasst.
## 1.0.1 - 2026-06-17
- Dashboard-UI nach v1-Korrektur neu strukturiert: feste Steuerungsleiste,
separate Geräteübersicht, klare Freigabe-/Detailfläche und Statusbereich.
- Orange bleibt Primärfarbe; Cyan ist die sichtbare Komplementärfarbe. Rote
Aktions- und Fehlerflächen wurden aus der Oberfläche entfernt.
- Startpfad weiter beschleunigt: Dashboard lädt nur noch lokale Startdaten.
HA-Discovery, Vorschläge und Automation-Refresh laufen erst nach Nutzeraktion.
- Detailansicht öffnet ohne automatische Automation-Discovery. Passende
Automationen können gezielt per Button neu gesucht werden.
## 1.0.0 - 2026-06-17
- Neuer blockweiser Dashboard-Start über `/v1/actuators/dashboard`: lokale
Store-/Cache-Daten laden sofort, HA-Discovery und Vorschläge laufen
nachgelagert.
- Discovery liest Entities pro Anfrage nur noch einmal und klassifiziert aus
diesem Snapshot weiter. Dadurch entfallen doppelte HA-Vollabfragen.
- Persistenter JSON-Entity-Cache wird für Friendly Name, Raum, Gerät,
Discovery-Gruppen und schnelle Summaries genutzt.
- Dashboard mit Orange als Primärfarbe, kompakter Navigation, aufklappbarer
Anleitung, aufklappbaren Gerätegruppen und Cache-/Systemstatistik.
- Aktor-/Sensor-Kategorien erweitert: Feuchte, Wetter, Helligkeit, Bewegung,
Tür/Fenster, Präsenz, Lichtzustände, Schalter, Steckdosen, Lüftung, Heizung,
Cover, Helper, PV/Akku/Einspeisung.
- Kontextvorschläge vermeiden weitere doppelte HA-Discovery und sortieren
aktortypbezogen nach relevanten Bereichen.
## 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

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@@ -11,6 +11,10 @@ nach einer ausdrücklichen Freigabe ausführen.
[`docs/CONTROL_HANDOFF.md`](docs/CONTROL_HANDOFF.md)
- Entwickeln, testen, veröffentlichen und installieren:
[`docs/OPERATIONS.md`](docs/OPERATIONS.md)
- Version 1.0.0 bedienen und prüfen:
[`docs/V1_0_0_OPERATING_GUIDE.md`](docs/V1_0_0_OPERATING_GUIDE.md)
- Version 1.0.x Abnahme und offene Punkte:
[`docs/V1_0_ACCEPTANCE.md`](docs/V1_0_ACCEPTANCE.md)
- Arbeitsregeln für Coding-Agenten: [`AGENTS.md`](AGENTS.md)
## Reifegrad
@@ -58,6 +62,8 @@ uvicorn app.main:app --reload
- `http://127.0.0.1:8000/v1/discovery` - klassifizierte, filterbare Entities
- `http://127.0.0.1:8000/v1/history` - normalisierte numerische Zeitreihen
- `http://127.0.0.1:8000/v1/actuators/discovery` - unterstützte Aktuatoren für den aktor-zentrierten Workflow
- `http://127.0.0.1:8000/v1/actuators/dashboard` - schnelle Dashboard-Startdaten aus Store und JSON-Cache
- `http://127.0.0.1:8000/v1/actuators/summary` - schlanke Liste beobachteter Aktoren
- `POST http://127.0.0.1:8000/v1/actuators` - Aktor freigeben; Kontextzuordnung und Modell-Lebenszyklus starten automatisch
- `POST http://127.0.0.1:8000/v1/actuators/{entity_id}/evaluate` - Shadow-Vorhersage aktualisieren
- `POST http://127.0.0.1:8000/v1/actuators/{entity_id}/activation` - autonomes Schalten pro Aktor freigeben oder stoppen

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@@ -1,5 +1,5 @@
name: SillyHome Next
version: "0.7.9"
version: "1.0.2"
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

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@@ -20,7 +20,7 @@ from app.actuators.models import (
)
from app.actuators.store import ActuatorStore
from app.config import Settings
from app.ha.discovery import DiscoveredEntity, EntityRole
from app.ha.discovery import DiscoveredEntity, EntityRole, discover_entities
from app.ha.history import EntityHistorySeries, NumericHistoryPoint
from app.ha.models import HaEntitySummary
from app.ha.reader import HaReader
@@ -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:
@@ -137,7 +170,7 @@ class ActuatorReconciliationService:
limit: int = _CONTEXT_SUGGESTION_LIMIT,
) -> list[HaEntitySummary]:
entities = {entity.entity_id: entity for entity in self._ha_reader.read_entities()}
discovered = {entity.entity_id: entity for entity in self._ha_reader.discover()}
discovered = {entity.entity_id: entity for entity in discover_entities(list(entities.values()))}
actuator = entities.get(actuator_entity_id)
if actuator is None:
raise KeyError("Aktuator-Konfiguration nicht gefunden.")
@@ -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)
)
@@ -702,6 +736,11 @@ def _manual_context_role(
def _context_sort_group(entity: HaEntitySummary) -> str:
device_class = entity.device_class or ""
text = " ".join(
value.lower().replace("_", " ")
for value in [entity.entity_id, entity.friendly_name, entity.area_name, entity.device_name]
if value
)
if device_class in {"motion", "occupancy", "presence"}:
return "01_presence"
if device_class in {"illuminance"}:
@@ -710,10 +749,26 @@ def _context_sort_group(entity: HaEntitySummary) -> str:
return "03_opening"
if device_class in {"humidity", "moisture"}:
return "04_humidity"
if device_class in {"temperature"}:
return "05_temperature"
if any(token in text for token in {"pv", "solar", "akku", "batterie", "battery", "einspeisung"}):
return "06_pv_battery"
if device_class in {"power", "energy", "current", "voltage"}:
return "05_power"
return "07_power"
if entity.domain in {"weather"}:
return "08_weather"
if entity.domain in {"fan", "humidifier"}:
return "09_ventilation"
if entity.domain in {"climate"}:
return "10_heating"
if entity.domain in {"cover"}:
return "11_cover"
if entity.domain in {"light", "switch"}:
return "06_states"
return "12_states"
if entity.domain.startswith("input_"):
return "13_helper"
if entity.domain in {"person", "device_tracker"}:
return "14_people"
return f"20_{entity.domain}_{device_class}"
@@ -743,6 +798,23 @@ 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 +881,17 @@ 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 +920,29 @@ 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": {"humidity", "illuminance", "occupancy", "presence", "temperature", "window"},
"cover": {"illuminance", "motion", "occupancy", "presence", "wind_speed"},
"fan": {"humidity", "moisture", "occupancy", "presence", "temperature"},
"humidifier": {"humidity", "moisture", "temperature"},
"light": {"door", "garage_door", "illuminance", "motion", "occupancy", "opening", "presence", "window"},
"media_player": {"occupancy", "presence"},
"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"},
}

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@@ -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, discover_entities
from app.ha.exceptions import HaClientError
from app.ha.models import HaEntitySummary
from app.ha.reader import HaReader
@@ -38,16 +44,155 @@ 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
class EntityCacheStatus(BaseModel):
available: bool
updated_at: str | None = None
entity_count: int = 0
class DashboardSystemStatus(BaseModel):
api_status: str = "ok"
websocket_status: str = "unavailable"
websocket_error: str | None = None
reconciliation_last_completed_at: str | None = None
configured_actuators: int = 0
trained_models: int = 0
review_required: int = 0
class DashboardDiscoveryGroup(BaseModel):
category: str
role: str
count: int
class DashboardOverview(BaseModel):
system: DashboardSystemStatus
cache: EntityCacheStatus
actuators: list[ActuatorSummary]
discovery_groups: list[DashboardDiscoveryGroup]
@router.get("/discovery", response_model=list[HaEntitySummary])
def discover_actuators(ha_reader: HaReader = Depends(get_ha_reader)) -> list[HaEntitySummary]:
entities = {entity.entity_id: entity for entity in ha_reader.read_entities()}
discovered = ha_reader.discover()
actuator_ids = sorted(
entity.entity_id for entity in discovered if entity.role is EntityRole.ACTUATOR
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 = discover_entities(list(entities.values()))
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 discover_entities(list(entities.values()))}
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 +206,95 @@ 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]:
records = _service(request).list_configured()
entity_map = _load_cached_entity_map(
request,
{record.actuator_entity_id for record in records},
)
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 records
]
@router.get("/dashboard", response_model=DashboardOverview)
def dashboard_overview(request: Request) -> DashboardOverview:
cache_payload = _load_entity_cache_payload(request)
raw_entities = cache_payload.get("entities", [])
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", [])
cached_groups = [
DashboardDiscoveryGroup.model_validate(group)
for group in raw_groups
if isinstance(group, dict)
] if isinstance(raw_groups, list) else []
reconciliation = _reconciliation_state_or_default(request)
ws_status = getattr(request.app.state, "ws_status", None)
actuators = list_configured_summary(request)
return DashboardOverview(
system=DashboardSystemStatus(
websocket_status=getattr(ws_status, "status", "unavailable"),
websocket_error=getattr(ws_status, "error", None),
reconciliation_last_completed_at=(
reconciliation.last_completed_at.isoformat()
if reconciliation.last_completed_at is not None
else None
),
configured_actuators=len(actuators),
trained_models=reconciliation.trained_models,
review_required=reconciliation.review_required,
),
cache=EntityCacheStatus(
available=bool(raw_entities),
updated_at=updated_at,
entity_count=len(raw_entities),
),
actuators=actuators,
discovery_groups=cached_groups,
)
@router.get("", response_model=list[ActuatorRecord])
def list_configured(request: Request) -> list[ActuatorRecord]:
return _service(request).list_configured()
@@ -116,6 +350,22 @@ 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 +483,193 @@ def _behavior(request: Request) -> BehaviorEngine:
detail="Verhaltenslernen ist nicht initialisiert.",
)
return engine
def _reconciliation_state_or_default(request: Request) -> ReconciliationState:
store = getattr(request.app.state, "actuator_store", None)
if not isinstance(store, ActuatorStore):
return ReconciliationState()
try:
return store.load_reconciliation_state()
except ValueError:
return ReconciliationState(last_summary="Reconciliation-Status ist unlesbar.")
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]:
payload = _load_entity_cache_payload(request)
raw_entities = payload.get("entities", [])
if not isinstance(raw_entities, list):
return []
try:
return [HaEntitySummary.model_validate(entity) for entity in raw_entities]
except ValueError:
return []
def _load_cached_entity_map(
request: Request,
entity_ids: set[str],
) -> dict[str, HaEntitySummary]:
if not entity_ids:
return {}
payload = _load_entity_cache_payload(request)
raw_entities = payload.get("entities", [])
if not isinstance(raw_entities, list):
return {}
result: dict[str, HaEntitySummary] = {}
for raw_entity in raw_entities:
if not isinstance(raw_entity, dict):
continue
entity_id = raw_entity.get("entity_id")
if not isinstance(entity_id, str) or entity_id not in entity_ids:
continue
try:
result[entity_id] = HaEntitySummary.model_validate(raw_entity)
except ValueError:
continue
return result
def _load_entity_cache_payload(request: Request) -> dict[str, object]:
path = _entity_cache_path(request)
if not path.exists():
return {}
try:
payload = json.loads(path.read_text(encoding="utf-8"))
return payload if isinstance(payload, dict) else {}
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)
group_counts: dict[tuple[str, str], int] = {}
for entity in discover_entities(entities):
key = (entity.category, entity.role.value)
group_counts[key] = group_counts.get(key, 0) + 1
payload = {
"updated_at": datetime.now(timezone.utc).isoformat(),
"discovery_groups": [
{"category": category, "role": role, "count": count}
for (category, role), count in sorted(group_counts.items())
],
"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

View File

@@ -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
@@ -193,23 +195,26 @@ 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,
) -> 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(
@@ -351,6 +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 = [
@@ -630,17 +724,25 @@ 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
@@ -661,6 +763,7 @@ class BehaviorEngine:
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)
@@ -795,8 +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
@@ -842,6 +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],

View File

@@ -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 +206,117 @@ 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:
text = _entity_text(entity)
if entity.domain == "light":
return "light"
if entity.domain == "switch":
if any(token in text for token in {"steckdose", "socket", "plug", "outlet", "shelly"}):
return "socket"
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 ""
text = _entity_text(entity)
if any(
token in text
for token in {
"pv",
"solar",
"photovoltaik",
"akku",
"batterie",
"battery",
"einspeisung",
"wechselrichter",
"inverter",
}
):
return "pv_battery_grid"
if entity.domain == "weather":
return "weather"
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", "apparent_power"}:
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"
if device_class in {"lock"}:
return "lock_state"
return "binary"
def _context_category(entity: HaEntitySummary) -> str:
text = _entity_text(entity)
if entity.domain.startswith("input_"):
return "helper"
if entity.domain in {"person", "device_tracker", "zone"}:
return "presence_location"
if entity.domain == "weather":
return "weather"
if entity.domain in {"light"}:
return "light_state"
if entity.domain in {"switch"}:
if any(token in text for token in {"steckdose", "socket", "plug", "outlet", "shelly"}):
return "socket_state"
return "switch_state"
if entity.domain in {"climate"}:
return "heating_state"
if entity.domain in {"fan", "humidifier"}:
return "ventilation_state"
if entity.domain in {"cover"}:
return "cover_state"
return entity.domain
def _entity_text(entity: HaEntitySummary) -> str:
return " ".join(
value.lower().replace("_", " ")
for value in [
entity.entity_id,
entity.friendly_name,
entity.area_name,
entity.device_name,
]
if value
)

View File

@@ -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="0.7.9",
version="1.0.2",
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

View File

@@ -5,65 +5,116 @@
<meta name="viewport" content="width=device-width,initial-scale=1">
<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); }
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; }
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; }
.step-number { display:inline-grid; place-items:center; width:28px; height:28px; border-radius:50%; background:#23715b; font-weight:700; margin-bottom:8px; }
:root {
color-scheme: dark;
font-family: Inter, ui-sans-serif, system-ui, sans-serif;
background:#0e1218;
color:#f4f7fb;
scroll-behavior:smooth;
--accent:#ff8a1c;
--accent-strong:#ffb45b;
--complement:#1cc7ff;
--complement-soft:#123447;
--panel:#171d25;
--panel-soft:#202833;
--panel-quiet:#111720;
--border:#314050;
--text-soft:#aebdcc;
--ok:#53e0a5;
--warn:#f3c969;
--bad:#8fb8ff;
}
* { box-sizing:border-box; }
body { margin:0; font-size:15px; background:var(--panel-quiet); }
h1,h2,h3 { margin:0 0 10px; letter-spacing:0; }
p { margin:6px 0; }
header { padding:18px 18px 14px; border-bottom:1px solid var(--border); background:#121821; }
.topbar { max-width:1480px; margin:0 auto; display:flex; align-items:flex-start; justify-content:space-between; gap:16px; }
.brand { display:grid; gap:5px; min-width:0; }
.brand-row { display:flex; align-items:center; gap:10px; flex-wrap:wrap; }
.brand-mark { width:34px; height:34px; border-radius:8px; display:grid; place-items:center; background:var(--accent); color:#201204; font-weight:900; }
header p { color:var(--text-soft); max-width:820px; }
.status-pill { display:flex; align-items:center; gap:8px; padding:8px 10px; border:1px solid var(--border); border-radius:8px; background:#101722; color:#d9e6f0; white-space:nowrap; }
.dot { width:9px; height:9px; border-radius:50%; background:var(--complement); box-shadow:0 0 0 3px rgba(28,199,255,.15); }
.quick-nav { position:sticky; top:0; z-index:10; display:flex; gap:8px; overflow-x:auto; padding:10px 18px; background:rgba(14,18,24,.96); border-bottom:1px solid var(--border); backdrop-filter:blur(8px); }
.quick-nav a { flex:0 0 auto; min-height:36px; display:grid; place-items:center; padding:8px 12px; border-radius:8px; background:#151c25; border:1px solid var(--border); color:#f3f7fb; text-decoration:none; font-weight:750; font-size:.92rem; }
.quick-nav a.primary { background:var(--accent); border-color:var(--accent); color:#211204; }
main { display:grid; grid-template-columns:minmax(270px,.72fr) minmax(0,1.58fr); grid-template-areas:"control board" "control detail" "status status" "guide guide"; gap:12px; padding:12px; max-width:1480px; margin:0 auto; }
section { background:var(--panel); border:1px solid var(--border); border-radius:8px; padding:12px; min-width:0; }
section:target { outline:2px solid var(--complement); outline-offset:2px; }
.control-panel { grid-area:control; align-self:start; position:sticky; top:58px; }
.board-panel { grid-area:board; }
.detail-panel { grid-area:detail; }
.status-panel { grid-area:status; }
.guide-panel { grid-area:guide; }
.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; }
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:#121922; border:1px solid var(--border); border-radius:8px; padding:10px; }
.step-number { display:inline-grid; place-items:center; width:28px; height:28px; border-radius:8px; background:var(--complement); color:#03151d; font-weight:900; margin-bottom:8px; }
.step p { margin:5px 0; }
.ok { color: #66dfa9; }
.ok { color: #73e0a9; }
.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; }
button { min-height:44px; margin-top: 10px; background: #23715b; border: 0; font-weight: 700; cursor: pointer; }
button.secondary { background: #37495c; }
button.danger { background: #7b3434; }
button.compact { width:auto; min-width:120px; margin-right:8px; }
.bad { color: var(--bad); }
label { display:block; margin:9px 0 4px; color:#c3d2df; font-weight:700; }
select,input,button { width:100%; border-radius:8px; border:1px solid #3b4b5b; padding:10px; background:#111821; color:#fff; font:inherit; min-width:0; }
select[multiple] { min-height:150px; }
button { min-height:42px; margin-top:10px; background:var(--accent); color:#211204; border:0; font-weight:850; cursor:pointer; }
button.secondary { background:var(--complement-soft); color:#dff6ff; border:1px solid #22607c; }
button.danger { background:#2a3441; color:#f2f6fb; border:1px solid #536273; }
button.compact { width:auto; min-width:112px; margin-right:8px; padding:8px 10px; min-height:36px; }
table { width: 100%; border-collapse: collapse; font-size: .92rem; }
td,th { padding: 8px; border-bottom: 1px solid #2d3a47; text-align: left; vertical-align: top; }
ul { margin: 8px 0; padding-left: 18px; }
.notice { border-left: 4px solid #66dfa9; padding-left: 10px; }
.notice { border-left:4px solid var(--complement); padding-left:10px; }
.grid-two { display:grid; grid-template-columns:repeat(auto-fit,minmax(240px,1fr)); gap:12px; }
.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; }
.actuator-card.selected { border-color:#66dfa9; box-shadow:0 0 0 1px rgba(102,223,169,.3); }
.chip { padding:4px 8px; border-radius:8px; background:#222b36; border:1px solid var(--border); font-size:.85rem; }
.muted { color:var(--text-soft); }
.card-list { display:grid; grid-template-columns:repeat(auto-fit,minmax(250px,1fr)); gap:10px; }
.actuator-card { background:#121922; border:1px solid var(--border); border-radius:8px; padding:10px; min-width:0; }
.actuator-card.selected { border-color:var(--complement); box-shadow:0 0 0 1px rgba(28,199,255,.35); }
.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:var(--panel-soft); border:1px solid var(--border); 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:#121922; border:1px solid var(--border); 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; }
textarea { width:100%; border-radius:8px; border:1px solid #3b4b5b; padding:12px; background:#101820; color:#fff; font:inherit; }
optgroup { color:#cfe0ec; background:#101820; }
code { color:#cfe0ec; overflow-wrap:anywhere; }
.empty-state { min-height:140px; display:grid; place-items:center; text-align:center; border:1px dashed var(--border); border-radius:8px; background:#111821; color:var(--text-soft); padding:16px; }
@media (max-width: 760px) {
header { padding:18px 14px; }
header { padding:16px 12px; }
header h1 { font-size:1.55rem; }
main { display:block; padding:10px; }
section { margin-bottom:12px; padding:14px; border-radius:14px; }
.topbar { display:grid; }
.status-pill { width:max-content; }
main { display:block; padding:8px; }
.control-panel { position:static; }
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; }
@@ -77,25 +128,115 @@
</head>
<body>
<header>
<h1>SillyHome Next</h1>
<p>Hier wählst du nur Geräte aus, deren Bedienung SillyHome lernen soll. Sensoren, Zusammenhänge und Modelle werden automatisch verwaltet.</p>
<p class="notice">Sicherer Start: Zuerst wird nur beobachtet und vorhergesagt. Ohne deine spätere Freigabe wird nichts geschaltet.</p>
<div class="topbar">
<div class="brand">
<div class="brand-row">
<span class="brand-mark">SH</span>
<h1>SillyHome Next</h1>
</div>
<p>Arbeitsdashboard für gelernte Home-Assistant-Bedienung: Geräte auswählen, Lernstand prüfen, Freigaben steuern.</p>
<p class="notice">Sicherer Start: Zuerst wird nur beobachtet und vorhergesagt. Ohne deine spätere Freigabe wird nichts geschaltet.</p>
</div>
<div class="status-pill"><span class="dot"></span><span id="load-budget">Startdaten laden ...</span></div>
</div>
</header>
<nav class="quick-nav" aria-label="Schnellnavigation">
<a class="primary" href="#choose">Gerät wählen</a>
<a href="#observed">Beobachtet</a>
<a href="#detail">Details</a>
<a href="#status-section">Status</a>
<a class="primary" href="#choose">Steuerung</a>
<a href="#observed">Geräte</a>
<a href="#detail">Freigabe</a>
<a href="#status-section">System</a>
<a href="#guide">Ablauf</a>
</nav>
<main>
<section class="wide" id="guide">
<h2>So gehst du vor</h2>
<section class="control-panel" id="choose">
<div class="panel-title">
<h2>Steuerung</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">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">
<div>
<label for="actuator-domain-filter">Typ</label>
<select id="actuator-domain-filter" onchange="renderActuatorSelect()">
<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>
<label for="actuator-search">Liste durchsuchen</label>
<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>
<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>
<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>
</section>
<section class="board-panel" id="observed">
<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>
<div id="configured-actuators">Noch nicht geladen.</div>
</section>
<section class="detail-panel" id="detail">
<h2>Lernfortschritt und Freigabe</h2>
<p class="muted">Die Freigabe erscheint erst, wenn genug eindeutig zugeordnete Handlungen gelernt wurden. Vorher bleibt das Gerät sicher im Beobachtungsmodus.</p>
<div id="actuator-detail" class="muted">Öffne bei einem beobachteten Gerät die Details.</div>
</section>
<section class="status-panel" id="status-section">
<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>
<div id="status">Prüfung läuft ...</div>
<div class="chips" id="status-chips"></div>
<div id="dashboard-stats" class="metric-grid"></div>
</section>
<section class="guide-panel" 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> Unten im Feld „Gerät auswählen“.</p>
<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">
@@ -111,57 +252,7 @@
<p><strong>Was passiert?</strong> Erst dann darf SillyHome passende Vorhersagen automatisch ausführen. Die Freigabe kann jederzeit gestoppt werden.</p>
</div>
</div>
</section>
<section id="status-section">
<h2>Systemstatus</h2>
<p class="muted">Zeigt, ob Verbindung, Lernsystem und automatische Prüfungen funktionieren. Hier musst du normalerweise nichts einstellen.</p>
<div id="status">Prüfung läuft ...</div>
<div class="chips" id="status-chips"></div>
<button class="secondary" onclick="loadOverview()">Status aktualisieren</button>
</section>
<section id="choose">
<h2>1. Gerät zum Lernen auswählen</h2>
<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">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">
<div>
<label for="actuator-domain-filter">Typ</label>
<select id="actuator-domain-filter" onchange="renderActuatorSelect()">
<option value="">Alle steuerbaren Typen</option>
<option value="light">Lichter</option>
<option value="switch">Schalter / Helper</option>
<option value="cover">Rollläden / Cover</option>
<option value="fan">Lüftung / Ventilatoren</option>
<option value="humidifier">Befeuchter / Entfeuchter</option>
</select>
</div>
<div>
<label for="actuator-search">Liste durchsuchen</label>
<input id="actuator-search" placeholder="Raum, Gerät oder Entity" oninput="renderActuatorSelect()" autocomplete="off">
</div>
</div>
<label for="actuator-select">Oder aus Liste wählen</label>
<select id="actuator-select" onchange="selectActuatorFromList()">
<option value="">Geräteliste wird geladen ...</option>
</select>
<button onclick="configureActuator()">Gerät hinzufügen und Beobachtung starten</button>
<p id="actuator-config-result" class="muted">Noch kein Aktor ausgewählt.</p>
</section>
<section class="wide" id="observed">
<h2>2. Beobachtete Geräte</h2>
<p class="muted">Öffne „Details“, um Lernfortschritt, aktuelle Vorhersage und den automatisch gefundenen Kontext zu sehen.</p>
<div id="configured-actuators">Noch nicht geladen.</div>
</section>
<section class="wide" id="detail">
<h2>3. Lernfortschritt und Freigabe</h2>
<p class="muted">Die Freigabe erscheint erst, wenn genug eindeutig zugeordnete Handlungen gelernt wurden. Vorher bleibt das Gerät sicher im Beobachtungsmodus.</p>
<div id="actuator-detail" class="muted">Öffne bei einem beobachteten Gerät die Details.</div>
</details>
</section>
</main>
<script>
@@ -175,6 +266,23 @@ let currentActuatorId = null;
let actuatorChoices = [];
let contextOptions = [];
let manualContextState = {options: [], selected: new Set()};
let cachedActuators = null;
let cachedEntities = null;
let cachedDiscovery = null;
let discoveryLoadPromise = null;
const ACTUATOR_RESULT_LIMIT = 50;
const STATUS_TIMEOUT_MS = 2000;
const DASHBOARD_TIMEOUT_MS = 4500;
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 +291,20 @@ 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 +313,32 @@ 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 +366,33 @@ 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 +417,166 @@ function optionGroups(entities, selectedIds = new Set()) {
}
async function loadOverview() {
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>";
try {
const dashboard = await apiWithTimeout("v1/actuators/dashboard", DASHBOARD_TIMEOUT_MS);
cachedActuators = dashboard.actuators || [];
cachedEntities = [];
renderDashboardStatus(dashboard);
renderConfiguredActuators();
if (budget) budget.textContent = `Bereit in ${Math.round(performance.now() - startedAt)} ms`;
} catch (error) {
document.getElementById("configured-actuators").innerHTML = `<p class="bad">${escapeHtml(error.message)}</p>`;
if (budget) budget.textContent = "Startdaten verzögert";
try {
await loadSummaryData();
renderConfiguredActuators();
} catch (_) {
document.getElementById("configured-actuators").innerHTML = "<div class='empty-state'>Startdaten sind gerade nicht verfügbar.</div>";
}
}
}
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()]);
}
function renderDashboardStatus(dashboard) {
const status = document.getElementById("status");
const chips = document.getElementById("status-chips");
const stats = document.getElementById("dashboard-stats");
const system = dashboard.system || {};
const cache = dashboard.cache || {};
const actuators = dashboard.actuators || [];
const discoveryGroups = dashboard.discovery_groups || [];
const activeCount = actuators.filter(record => record.behavior_mode === "active").length;
const shadowCount = actuators.filter(record => record.behavior_mode !== "active").length;
const readyCount = actuators.filter(record => record.activation_ready).length;
const pendingCount = actuators.filter(record =>
["pending_history", "pending_assignment", "archived"].includes(record.lifecycle_status)
).length;
const trainedCount = actuators.filter(record => record.behavior_status === "trained").length;
const sampleTotal = actuators.reduce((sum, record) => sum + Number(record.sample_count || 0), 0);
const cacheLabel = cache.available
? `Cache aktuell mit ${cache.entity_count} Entities`
: "Cache wird nach Discovery aufgebaut";
status.innerHTML = `
<p class="${system.websocket_status === "connected" ? "ok" : "warn"}">
Dashboard bereit. WebSocket: ${escapeHtml(system.websocket_status || "unbekannt")}
</p>
<p class="muted">Letzte automatische Prüfung: ${escapeHtml(system.reconciliation_last_completed_at || "noch nicht abgeschlossen")}</p>
`;
chips.innerHTML = [
`<span class="chip">API: ${escapeHtml(system.api_status || "ok")}</span>`,
`<span class="chip">Cache: ${escapeHtml(cacheLabel)}</span>`,
`<span class="chip">Aktoren: ${escapeHtml(system.configured_actuators ?? 0)}</span>`,
`<span class="chip">Lernbereit: ${escapeHtml(system.trained_models ?? 0)}</span>`,
`<span class="chip">Prüfen: ${escapeHtml(system.review_required ?? 0)}</span>`,
].join("");
stats.innerHTML = [
`<div class="metric"><strong>Geladene Startdaten</strong>${escapeHtml(actuators.length)} Geräte</div>`,
`<div class="metric"><strong>Freigabebereit</strong>${escapeHtml(readyCount)} Geräte</div>`,
`<div class="metric"><strong>Aktiv / Shadow</strong>${escapeHtml(activeCount)} / ${escapeHtml(shadowCount)}</div>`,
`<div class="metric"><strong>Gelernt / Wartet</strong>${escapeHtml(trainedCount)} / ${escapeHtml(pendingCount)}</div>`,
`<div class="metric"><strong>Gelernte Handlungen</strong>${escapeHtml(sampleTotal)}</div>`,
`<div class="metric"><strong>Discovery-Gruppen</strong>${escapeHtml(discoveryGroups.length)} Kategorien</div>`,
`<div class="metric"><strong>Cache-Zeitpunkt</strong>${escapeHtml(cache.updated_at || "noch offen")}</div>`,
].join("");
}
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();
}
async function ensureActuatorDiscovery() {
const select = document.getElementById("actuator-select");
if (cachedDiscovery) {
renderActuatorDiscovery();
return;
}
if (!discoveryLoadPromise) {
if (select) select.innerHTML = `<option value="">Geräteliste wird geladen ...</option>`;
discoveryLoadPromise = loadActuatorDiscovery().finally(() => {
discoveryLoadPromise = null;
});
}
await discoveryLoadPromise;
}
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 +585,53 @@ 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 +643,17 @@ 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("")}
@@ -395,7 +706,11 @@ async function configureActuator() {
|| document.getElementById("actuator-select").value.trim()
);
const result = document.getElementById("actuator-config-result");
if (!actuatorId) return;
if (!actuatorId) {
await ensureActuatorDiscovery();
result.textContent = "Wähle ein Gerät aus der geladenen Liste oder trage eine Entity-ID ein.";
return;
}
result.textContent = "Kontext wird automatisch analysiert ...";
try {
const record = await api("v1/actuators", {
@@ -413,37 +728,57 @@ 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;
}
@@ -453,12 +788,7 @@ async function showActuator(actuatorId, evaluationMessage = "") {
currentActuatorId = actuatorId;
const box = document.getElementById("actuator-detail");
try {
let record;
try {
record = await api(`v1/actuators/${encodeURIComponent(actuatorId)}/related-automations/refresh`, {method: "POST"});
} catch (_) {
record = await api(`v1/actuators/${encodeURIComponent(actuatorId)}`);
}
const record = await api(`v1/actuators/${encodeURIComponent(actuatorId)}`);
await loadContextOptions(actuatorId);
const contexts = [
record.assignment.selected_numeric_entity_id,
@@ -466,8 +796,16 @@ async function showActuator(actuatorId, evaluationMessage = "") {
].filter(Boolean);
const evidence = [...record.numeric_candidates, ...record.context_candidates]
.filter(candidate => contexts.includes(candidate.entity_id))
.map(candidate => `<li><strong>${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)}', '${escapeHtml(entityId)}')">Entfernen</button>
</li>
`).join("")}</ul>`
: "<p class='muted'>Noch keine Kontext-Entity ausgewählt.</p>";
const prediction = record.behavior.prediction;
const learnedAutomationActions = record.behavior.patterns.filter(
pattern => pattern.source === "automation",
@@ -489,8 +827,8 @@ async function showActuator(actuatorId, evaluationMessage = "") {
selected: manualContextIds,
};
const manualAssignment = `
<div class="manual-context">
<h3>Kontext selbst festlegen</h3>
<details class="manual-context" open>
<summary>Kontext selbst festlegen</summary>
<p class="muted">Die Vorschläge sind aktorbezogen vorsortiert. Wenn etwas fehlt, trage die Entity-ID unten manuell ein, z. B. PIR, Helligkeit außen, Luftfeuchtigkeit oder Lichtzustände.</p>
<label for="manual-numeric-select">Optionaler Haupt-Messsensor</label>
<select id="manual-numeric-select">
@@ -520,7 +858,7 @@ async function showActuator(actuatorId, evaluationMessage = "") {
<button onclick="saveManualAssignment('${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 +912,18 @@ 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('${escapeHtml(record.actuator_entity_id)}', false)">Vorhersage falsch</button>
</div>
<h3>Passende Home-Assistant-Automationen</h3>
<p class="muted">Bei einer Übernahme pausiert SillyHome diese Automationen. Beim Stoppen können sie gezielt fortgesetzt werden.</p>
<button class="secondary compact" onclick="refreshRelatedAutomations('${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>Verwendete Sensoren/Zustände ändern</h3>
${currentContextControls}
${manualAssignment}
`;
document.getElementById("detail").scrollIntoView({behavior: "smooth", block: "start"});
@@ -606,6 +951,7 @@ async function saveManualAssignment(actuatorId) {
note: "Manuell im Dashboard gesetzt",
}),
});
invalidateDashboardCache();
await loadConfiguredActuators();
await showActuator(actuatorId, "Manuelle Kontext-Auswahl gespeichert.");
} catch (error) {
@@ -613,6 +959,35 @@ async function saveManualAssignment(actuatorId) {
}
}
async function removeContextEntity(actuatorId, entityId) {
try {
const record = await api(`v1/actuators/${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 +1000,7 @@ 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 ${checkedAt}: Kein frischer passender Sensorwechsel erkannt; aktuell ist keine Aktion fällig.`;
invalidateDashboardCache();
await loadConfiguredActuators();
await showActuator(actuatorId, message);
} catch (error) {
@@ -632,6 +1008,24 @@ async function evaluateActuator(actuatorId) {
}
}
async function sendFeedback(actuatorId, correct) {
const expectedState = correct ? null : prompt("Welcher Zustand wäre korrekt gewesen? Leer lassen, wenn nur abwerten.");
try {
await api(`v1/actuators/${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 +1044,7 @@ async function setActivation(actuatorId, active, pauseMatchingAutomations, resto
restore_paused_automations: restorePausedAutomations,
}),
});
invalidateDashboardCache();
await loadConfiguredActuators();
await showActuator(actuatorId);
} catch (error) {
@@ -668,6 +1063,7 @@ async function setRelatedAutomation(actuatorId, automationEntityId, enabled) {
enabled,
}),
});
invalidateDashboardCache();
await loadConfiguredActuators();
await showActuator(actuatorId);
} catch (error) {
@@ -675,6 +1071,17 @@ async function setRelatedAutomation(actuatorId, automationEntityId, enabled) {
}
}
async function refreshRelatedAutomations(actuatorId) {
try {
await api(`v1/actuators/${encodeURIComponent(actuatorId)}/related-automations/refresh`, {method: "POST"});
invalidateDashboardCache();
await loadConfiguredActuators();
await showActuator(actuatorId, "Passende Home-Assistant-Automationen neu geprüft.");
} catch (error) {
alert(error.message);
}
}
async function removeActuator(actuatorId) {
if (!confirm(`${actuatorId} aus SillyHome entfernen?`)) return;
try {

View File

@@ -0,0 +1,111 @@
# SillyHome Next 1.0.0 Operating Guide
Diese Version stabilisiert den produktiven Kern: schnelle Dashboard-Nutzung,
lokales Caching, klare Aktor-/Sensor-Kategorien und nachvollziehbare Freigabe
gelernter Aktionen.
Die detaillierte Abnahme steht in
[`V1_0_ACCEPTANCE.md`](V1_0_ACCEPTANCE.md). Dort sind erledigte, teilweise
erledigte und fuer v1.0.x offene Punkte getrennt dokumentiert.
## Grundprinzip
- Home Assistant bleibt die Quelle fuer aktuelle States und Services.
- SillyHome cached schwere Entity-/Discovery-Metadaten lokal als JSON.
- Die Startansicht liest nur lokale Store-/Cache-Daten.
- Vollstaendige Discovery, Vorschlaege und Detailanalysen laden blockweise nach.
- Es gibt keine externen Pings oder Cloud-Abfragen im Dashboard-Startpfad.
## Wichtige Endpunkte
- `GET /health`
Lokaler API-Status ohne externe Abfrage.
- `GET /health/websocket`
Status des Home-Assistant-WebSocket-Listeners.
- `GET /v1/actuators/dashboard`
Schnelle Dashboard-Startdaten aus Store und JSON-Cache.
- `GET /v1/actuators/summary`
Schlanke Liste beobachteter Aktoren ohne Lernmuster-Payload.
- `GET /v1/actuators/discovery`
Aktor-Auswahl aus gecachten oder frisch geladenen HA-Entities.
- `GET /v1/actuators/context-options?actuator_entity_id=...`
Sensor-/Kontextvorschlaege fuer einen konkreten Aktor.
- `POST /v1/actuators/{entity_id}/assignment`
Manuelle Sensor-/Kontextzuordnung speichern.
- `POST /v1/actuators/{entity_id}/activation`
Freigabe oder Stop des automatischen Schaltens.
## Cache
Der Entity-Cache liegt neben dem Aktor-Store als `ha_entity_cache.json`.
Er enthaelt HA-Entity-Metadaten wie Friendly Name, Bereich, Device und
Kategoriegrundlagen.
Der Cache wird geschrieben, wenn Discovery frische HA-Entities liest. Danach
koennen Dashboard und Summary ohne erneute HA-Vollabfrage Namen, Raeume und
Gruppen anzeigen.
## Dashboard-Nutzung
1. Startansicht oeffnen.
2. `System & Cache` zeigt API, WebSocket, Cache-Groesse und geladene
Discovery-Gruppen.
3. `Geraet zum Lernen auswaehlen` nutzt Suche, Typfilter und direkte
Entity-ID-Eingabe.
4. `Beobachtete Geraete` zeigt gelernte Aktoren nach Raum oder Typ gruppiert.
5. `Details` zeigt Lernfortschritt, Freigabe, Vorhersage, verwendete
Sensoren/Zustaende und Entscheidungsgruende.
## Kategorien
Aktoren:
- Licht, LED, Lampen
- Schalter, Steckdosen, Helper
- Lueftung, Ventilatoren, Befeuchter/Entfeuchter
- Heizungen/Klima
- Rolllaeden/Cover
- TV/Medien/Fernbedienungen
- Szenen, Buttons, Schloesser, Ventile
Sensoren und Kontext:
- Luftfeuchtigkeit und Feuchte
- Temperatur
- Wetter
- Helligkeit/Lux
- Bewegung, Praesenz, Anwesenheit
- Tuer/Fenster/Oeffnung
- Licht-/Schalter-/Steckdosenstatus
- Strom, Leistung, Energie, Einspeisung
- PV, Akku, Wechselrichter
- Helper und Szenen
## Qualitaetspruefung
Vor Release:
```bash
.venv/bin/pytest -q
.venv/bin/ruff check .
.venv/bin/mypy app backend tests
git diff --check
```
Live nach Installation:
```bash
wget -qO- http://58adbe1e-sillyhome-next:8000/health
wget -qO- http://58adbe1e-sillyhome-next:8000/health/websocket
wget -qO /tmp/summary.json http://58adbe1e-sillyhome-next:8000/v1/actuators/summary
wget -qO /tmp/dashboard.json http://58adbe1e-sillyhome-next:8000/v1/actuators/dashboard
```
## Rollback
Der stabile Vor-1.0-Stand ist `v0.7.21`. Vor dem 1.0.0-Umbau wurde ein
Git-Bundle-Backup erstellt:
`/root/.openclaw/workspace/backups/sillyhome-next/`
Bei Problemen kann auf `v0.7.21` zurueck installiert werden.

80
docs/V1_0_ACCEPTANCE.md Normal file
View File

@@ -0,0 +1,80 @@
# SillyHome Next v1.0 Acceptance
Stand: 2026-06-17
Diese Abnahme trennt belegte Umsetzung von offenen v1.0.x-Nacharbeiten. Der
Funktionskern bleibt aktorzentriert: Nutzer waehlen Aktoren, SillyHome lernt
Kontext und Verhalten, laeuft zuerst im Shadow-Modus und schaltet erst nach
expliziter Freigabe.
## Erfuellt
- Versioniert, gepusht und installiert:
- `v1.0.0`: API-/Cache-Umbau
- `v1.0.1`: Dashboard-/Performance-Korrektur
- Startpfad:
- `/v1/actuators/dashboard` liefert lokale Startdaten aus Store und Cache.
- Dashboard blockiert nicht mehr auf Discovery, Vorschlaegen oder
Automation-Refresh.
- Frontend bricht den Startdaten-Request nach 4,5 Sekunden ab und bleibt
bedienbar.
- Cache:
- HA-Entity-Metadaten werden als `ha_entity_cache.json` gespeichert.
- Summary und Dashboard verwenden Friendly Name, Area und Device aus Cache.
- Keine externen Abfragen im Dashboard-Startpfad:
- Kein Cloud-Ping, keine Fremd-API.
- HA-Zugriffe bleiben lokal gegen Home Assistant.
- Dashboard:
- Orange ist Primaerfarbe.
- Cyan ist sichtbare Komplementaerfarbe.
- Rote UI-Flaechen wurden entfernt.
- Steuerung, beobachtete Geraete, Lernfortschritt/Freigabe und Systemstatus
sind getrennte Bereiche.
- Discovery, Vorschlaege und Automation-Suche laden erst bei Nutzeraktion.
- Lernfortschritt und Freigabe:
- Karten zeigen Modus, Status, Handlungen, Vorhersage und Freigabestatus.
- Detailansicht zeigt Zuordnung, Sicherheit, Lernstand, Vorhersage,
Feedback, passende HA-Automationen und verwendete Sensoren/Zustaende.
- Direkte HA-Nutzung:
- Aktor-Schaltungen laufen ueber Home-Assistant-Serviceaufrufe.
- Automation-Steuerung nutzt Home-Assistant-Endpunkte und gecachte
Automation-Metadaten.
- Qualitaet:
- `pytest -q`
- `ruff check .`
- `mypy app backend tests`
- `git diff --check`
## Teilweise Erfuellt
- Bessere Statistik:
- Startbereich zeigt Aktoren, Freigabebereitschaft, Aktiv/Shadow,
Gelernt/Wartet, gelernte Handlungen, Discovery-Gruppen und Cache-Zeitpunkt.
- Noch offen: Verlaufsgrafiken, p95-Latenzen und Trendstatistik je Aktor.
- Kontrollierte Abarbeitung und Queue:
- Reconciliation/Training laufen kontrolliert im Prozess und sind testbar.
- Noch offen: sichtbare Job-Queue mit Laufzeit, Fehlern und Retry-Status im
Dashboard.
- Saubere Issues:
- v1.0.0-Issues #41 bis #47 wurden geschlossen.
- Rueckblickend waren sie zu grob; v1.0.x bekommt feinere Folgeissues fuer
Statistik, Queue-Sichtbarkeit und Performance-Budgets.
## Offen Fuer v1.0.x
- Echte Dashboard-Performance-Budget-Tests, die Start-HTML und
`/v1/actuators/dashboard` gegen ein 5-Sekunden-Limit messen.
- Dashboard-Jobstatus fuer Reconciliation, Training, Discovery und
Automation-Refresh.
- Mehr Entscheidungsstatistik pro Aktor: welche Sensoren wie stark
beigetragen haben, wie sich Confidence und Sample Count entwickeln.
- Dokumentierte HA-Installationspruefung mit Supervisor-/Ingress-Hinweisen,
weil direkte Container-HTTP-Pruefung ausserhalb HA nicht immer routbar ist.
## Rollback
- Git-Bundle-Backups liegen unter
`/root/.openclaw/workspace/backups/sillyhome-next/`.
- Vor `v1.0.1` wurde ein Home-Assistant-Teilbackup des Add-ons angelegt.
Referenz: `18a5b387`.
- Letzter Vor-1.0-Stand: `v0.7.21`.

View File

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
[project]
name = "sillyhome-next"
version = "0.7.9"
version = "1.0.2"
description = "Lokales Smart-Home-Intelligenzsystem für Home Assistant"
requires-python = ">=3.11"
dependencies = [

View File

@@ -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

View File

@@ -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 (
@@ -27,8 +28,10 @@ class FakeHaReader(HaReader):
def __init__(self, entities: list[HaEntitySummary], history: dict[str, list[float]]) -> None:
self._entities = entities
self._history = history
self.read_entities_calls = 0
def read_entities(self) -> list[HaEntitySummary]:
self.read_entities_calls += 1
return list(self._entities)
def discover(
@@ -212,6 +215,53 @@ 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_dashboard_overview_uses_cache_without_ha_roundtrip(tmp_path: Path) -> None:
with TestClient(app) as client:
_install_service(tmp_path)
reader = app.state.ha_reader
client.get("/v1/actuators/discovery")
client.post("/v1/actuators", json={"actuator_entity_id": "light.abstellkammer"})
calls_before = reader.read_entities_calls
response = client.get("/v1/actuators/dashboard")
assert response.status_code == 200
assert reader.read_entities_calls == calls_before
payload = response.json()
assert payload["cache"]["available"] is True
assert payload["cache"]["entity_count"] == 4
assert payload["actuators"][0]["friendly_name"] == "Abstellkammer Licht"
assert payload["discovery_groups"]
def test_discovery_reads_entities_once_and_reuses_them(tmp_path: Path) -> None:
with TestClient(app) as client:
_install_service(tmp_path)
reader = app.state.ha_reader
response = client.get("/v1/actuators/discovery", params={"refresh": True})
assert response.status_code == 200
assert reader.read_entities_calls == 1
def test_context_options_returns_learnable_entities(tmp_path: Path) -> None:
with TestClient(app) as client:
_install_service(tmp_path)
@@ -227,3 +277,37 @@ 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"]

View File

@@ -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.",

View File

@@ -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"),
@@ -587,3 +708,73 @@ def test_state_change_uses_websocket_context_state_for_immediate_action(
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"})
]

View File

@@ -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

View File

@@ -9,11 +9,14 @@ 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 "So gehst du vor" in response.text
assert "Gerät zum Lernen auswählen" in response.text
assert "Steuerung" in response.text
assert "Entitätsname oder Gerät aus Home Assistant" in response.text
assert "Oder aus Liste wählen" 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 "Wie gewohnt bedienen" in response.text
assert "Ohne deine spätere Freigabe wird nichts geschaltet" in response.text
assert "Du wählst keine Sensoren und erstellst keine Regeln" in response.text
@@ -32,5 +35,12 @@ 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

View File

@@ -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