Expand room planning management

app/api/v1/actuators.py

@@ -194,6 +194,19 @@ class RoomManagementSensor(BaseModel):
     reason: str
 
 
+class RoomManagementAction(BaseModel):
+    action_id: str
+    category: str
+    actuator_entity_id: str
+    title: str
+    when: str
+    then: str
+    why: str
+    confidence: float = Field(default=0.0, ge=0.0, le=1.0)
+    learnable: bool = True
+    sort_key: str = ""
+
+
 class RoomManagementActuator(BaseModel):
     actuator_entity_id: str
     friendly_name: str | None = None
@@ -206,15 +219,20 @@ class RoomManagementActuator(BaseModel):
     selected_context_entity_ids: list[str] = Field(default_factory=list)
     sensors: list[RoomManagementSensor] = Field(default_factory=list)
     prediction_rules: list[str] = Field(default_factory=list)
+    suggested_actions: list[RoomManagementAction] = Field(default_factory=list)
     management_hint: str
 
 
 class RoomManagementGroup(BaseModel):
     room: str
     actuator_count: int
+    sensor_count: int = 0
+    action_count: int = 0
     sensors: list[RoomManagementSensor] = Field(default_factory=list)
     actuators: list[RoomManagementActuator] = Field(default_factory=list)
     prediction_rules: list[str] = Field(default_factory=list)
+    suggested_actions: list[RoomManagementAction] = Field(default_factory=list)
+    continuous_hint: str = "Wird bei Discovery, Reconciliation und Lernrefresh automatisch neu bewertet."
 
 
 class RoomManagementOverview(BaseModel):
@@ -511,8 +529,9 @@ def room_management_overview(request: Request) -> RoomManagementOverview:
                 if entity_id
             },
         )
+    discovered = {entity.entity_id: entity for entity in discover_entities(list(entities.values()))}
     configured_ids = {record.actuator_entity_id for record in records}
-    rooms: dict[str, RoomManagementGroup] = {}
+    rooms = _build_room_shells(entities, discovered)
     for record in records:
         actuator = entities.get(record.actuator_entity_id)
         room = (
@@ -558,6 +577,12 @@ def room_management_overview(request: Request) -> RoomManagementOverview:
             selected_context_entity_ids=record.assignment.selected_context_entity_ids,
             sensors=sensors,
             prediction_rules=_prediction_rule_lines(record, ranked_candidates),
+            suggested_actions=_suggest_room_actions(
+                actuator_id=record.actuator_entity_id,
+                domain=record.actuator_entity_id.split(".", 1)[0],
+                sensors=sensors,
+                configured=True,
+            ),
             management_hint=_management_hint(record, has_opening_context),
         )
         if room not in rooms:
@@ -569,6 +594,52 @@ def room_management_overview(request: Request) -> RoomManagementOverview:
             *actuator_group.prediction_rules,
         ])[:8]
         rooms[room].sensors = _merge_room_sensors(rooms[room].sensors, sensors)
+        rooms[room].suggested_actions = _merge_room_actions(
+            rooms[room].suggested_actions,
+            actuator_group.suggested_actions,
+        )
+    for entity_id, descriptor in discovered.items():
+        if descriptor.role is not EntityRole.ACTUATOR or entity_id in configured_ids:
+            continue
+        actuator = entities.get(entity_id)
+        if actuator is None:
+            continue
+        room = _entity_room(actuator)
+        if room not in rooms:
+            rooms[room] = RoomManagementGroup(room=room, actuator_count=0)
+        room_sensors = _room_sensors_for_actuator(actuator, rooms[room].sensors)
+        actions = _suggest_room_actions(
+            actuator_id=entity_id,
+            domain=actuator.domain,
+            sensors=room_sensors,
+            configured=False,
+        )
+        rooms[room].actuators.append(
+            RoomManagementActuator(
+                actuator_entity_id=entity_id,
+                friendly_name=actuator.friendly_name,
+                domain=actuator.domain,
+                behavior_mode="unmanaged",
+                behavior_status="suggested",
+                lifecycle_status="unconfigured",
+                sensors=room_sensors,
+                prediction_rules=[_action_rule_line(action) for action in actions[:5]],
+                suggested_actions=actions,
+                management_hint=(
+                    "Noch nicht verwaltet: übernehmen, wenn diese Handlung gelernt oder vorgeschlagen werden soll."
+                ),
+            )
+        )
+        rooms[room].actuator_count += 1
+        rooms[room].prediction_rules = _unique_lines([
+            *rooms[room].prediction_rules,
+            *[_action_rule_line(action) for action in actions],
+        ])[:8]
+        rooms[room].suggested_actions = _merge_room_actions(rooms[room].suggested_actions, actions)
+    for room in rooms.values():
+        room.sensors = _merge_room_sensors([], room.sensors)
+        room.sensor_count = len(room.sensors)
+        room.action_count = len(room.suggested_actions)
     unmanaged = [
         suggestion for suggestion in suggest_actuators(request, service._ha_reader)
         if suggestion.entity_id not in configured_ids
@@ -1057,6 +1128,119 @@ def _validate_weight_payload(payload: WeightOverrideRequest) -> None:
                 raise ValueError(f"Ungültige Entity-ID in Gruppe {group.name}: {entity_id}")
 
 
+def _build_room_shells(
+    entities: dict[str, HaEntitySummary],
+    discovered: dict[str, DiscoveredEntity],
+) -> dict[str, RoomManagementGroup]:
+    rooms: dict[str, RoomManagementGroup] = {}
+    for entity in entities.values():
+        room = _entity_room(entity)
+        if room not in rooms:
+            rooms[room] = RoomManagementGroup(room=room, actuator_count=0)
+        descriptor = discovered.get(entity.entity_id)
+        if descriptor is None or descriptor.role is EntityRole.ACTUATOR:
+            continue
+        sensor = _entity_management_sensor(entity, descriptor)
+        if sensor is not None:
+            rooms[room].sensors = _merge_room_sensors(rooms[room].sensors, [sensor])
+    return rooms
+
+
+def _entity_room(entity: HaEntitySummary) -> str:
+    room = entity.area_name or _room_from_text(entity.friendly_name or entity.device_name or entity.entity_id)
+    return room or "Ohne Raum"
+
+
+def _room_from_text(value: str) -> str | None:
+    normalized = value.replace("_", " ").replace("-", " ").strip()
+    if not normalized:
+        return None
+    known_rooms = {
+        "abstellkammer": "Abstellkammer",
+        "abstellraum": "Abstellkammer",
+        "bad": "Bad",
+        "badezimmer": "Bad",
+        "buro": "Büro",
+        "buero": "Büro",
+        "flur": "Flur",
+        "gaeste wc": "Gäste WC",
+        "gaste wc": "Gäste WC",
+        "keller": "Keller",
+        "kuche": "Küche",
+        "kueche": "Küche",
+        "schlafzimmer": "Schlafzimmer",
+        "terrasse": "Terrasse",
+        "wohnbereich": "Wohnbereich",
+        "wohnzimmer": "Wohnbereich",
+    }
+    lowered = normalized.lower()
+    for token, room in known_rooms.items():
+        if token in lowered:
+            return room
+    return None
+
+
+def _entity_management_sensor(
+    entity: HaEntitySummary,
+    descriptor: DiscoveredEntity,
+) -> RoomManagementSensor | None:
+    if descriptor.role not in {EntityRole.MEASUREMENT, EntityRole.BINARY_CONTEXT, EntityRole.CONTEXT}:
+        return None
+    candidate = AssignmentCandidate(
+        entity_id=entity.entity_id,
+        domain=entity.domain,
+        role=descriptor.role,
+        device_class=entity.device_class,
+        state_class=entity.state_class,
+        unit_of_measurement=entity.unit_of_measurement,
+        friendly_name=entity.friendly_name,
+        area_name=entity.area_name,
+        device_name=entity.device_name,
+        score=0.55,
+        confidence=0.55,
+        evidence=["Gehört laut Home Assistant zu diesem Bereich."],
+    )
+    return _management_sensor(
+        candidate,
+        entity,
+        active=False,
+        optional=descriptor.role is EntityRole.MEASUREMENT,
+        not_required=False,
+    )
+
+
+def _room_sensors_for_actuator(
+    actuator: HaEntitySummary,
+    sensors: list[RoomManagementSensor],
+) -> list[RoomManagementSensor]:
+    preferred = _preferred_sensor_categories(actuator.domain)
+    ranked = sorted(
+        sensors,
+        key=lambda sensor: (
+            sensor.category not in preferred,
+            preferred.index(sensor.category) if sensor.category in preferred else 99,
+            -sensor.confidence,
+            sensor.friendly_name or sensor.entity_id,
+        ),
+    )
+    return ranked[:12]
+
+
+def _preferred_sensor_categories(domain: str) -> list[str]:
+    mapping = {
+        "climate": ["Temperatur", "Luftfeuchtigkeit", "Tür/Fenster", "Präsenz", "Energie"],
+        "cover": ["Helligkeit", "Präsenz", "Tür/Fenster", "Temperatur"],
+        "fan": ["Luftfeuchtigkeit", "Präsenz", "Temperatur", "Tür/Fenster", "Energie"],
+        "humidifier": ["Luftfeuchtigkeit", "Temperatur", "Präsenz"],
+        "light": ["Präsenz", "Tür/Fenster", "Helligkeit", "Zone/Person"],
+        "lock": ["Tür/Fenster", "Präsenz", "Zone/Person"],
+        "siren": ["Sicherheit", "Tür/Fenster", "Präsenz"],
+        "switch": ["Präsenz", "Tür/Fenster", "Energie", "Luftfeuchtigkeit", "Helligkeit"],
+        "valve": ["Wasser", "Luftfeuchtigkeit", "Temperatur", "Tür/Fenster"],
+    }
+    return mapping.get(domain, ["Präsenz", "Tür/Fenster", "Energie", "Kontext"])
+
+
 def _candidate_room(record: ActuatorRecord) -> str | None:
     for candidate in [*record.context_candidates, *record.numeric_candidates]:
         if candidate.area_name:
@@ -1147,8 +1331,14 @@ def _sensor_category_label(candidate: AssignmentCandidate) -> str:
         return "Helligkeit"
     if device_class in {"humidity", "moisture"}:
         return "Luftfeuchtigkeit"
+    if device_class == "temperature":
+        return "Temperatur"
     if device_class in {"power", "energy", "current", "voltage"}:
         return "Energie"
+    if device_class in {"gas", "water"} or candidate.unit_of_measurement in {"m3", "L", "l"}:
+        return "Wasser"
+    if device_class in {"problem", "safety", "smoke", "vibration"}:
+        return "Sicherheit"
     if candidate.domain in {"cover"}:
         return "Rollo/Cover"
     if candidate.domain in {"zone", "person", "device_tracker"}:
@@ -1220,6 +1410,116 @@ def _prediction_rule_lines(
     return _unique_lines(result)[:8] or ["Noch keine stabile Vorhersage; erst Kontext prüfen und weiter beobachten."]
 
 
+def _suggest_room_actions(
+    *,
+    actuator_id: str,
+    domain: str,
+    sensors: list[RoomManagementSensor],
+    configured: bool,
+) -> list[RoomManagementAction]:
+    sensor_categories = {sensor.category for sensor in sensors}
+    sensor_labels = {
+        sensor.category: sensor.friendly_name or sensor.entity_id
+        for sensor in sensors
+    }
+    confidence_base = 0.78 if configured else 0.58
+    actions: list[RoomManagementAction] = []
+
+    def add(category: str, title: str, when: str, then: str, why: str, confidence: float) -> None:
+        actions.append(
+            RoomManagementAction(
+                action_id=f"{actuator_id}:{category}:{len(actions)}",
+                category=category,
+                actuator_entity_id=actuator_id,
+                title=title,
+                when=when,
+                then=then,
+                why=why,
+                confidence=round(min(1.0, confidence), 4),
+                learnable=True,
+                sort_key=f"{category}:{actuator_id}:{len(actions):02d}",
+            )
+        )
+
+    presence = sensor_labels.get("Präsenz")
+    opening = sensor_labels.get("Tür/Fenster")
+    brightness = sensor_labels.get("Helligkeit")
+    humidity = sensor_labels.get("Luftfeuchtigkeit")
+    temperature = sensor_labels.get("Temperatur")
+    energy = sensor_labels.get("Energie")
+    water = sensor_labels.get("Wasser")
+    safety = sensor_labels.get("Sicherheit")
+    zone = sensor_labels.get("Zone/Person")
+
+    if domain == "light":
+        if opening:
+            add("licht", "Türlicht", f"{opening} öffnet oder schließt", "Licht passend an/aus schalten.", "Türkontakt erklärt kleine Räume ohne Helligkeitssensor.", confidence_base + 0.12)
+        if presence:
+            when = f"{presence} erkennt Anwesenheit"
+            if brightness:
+                when += f" und {brightness} ist dunkel"
+            add("licht", "Präsenzlicht", when, "Licht gedimmt einschalten und bei Abwesenheit verzögert ausschalten.", "Anwesenheit plus Helligkeit vermeidet unnötiges Licht.", confidence_base + (0.12 if brightness else 0.04))
+        if zone:
+            add("licht", "Zonenstimmung", f"{zone} wird betreten oder verlassen", "Beim Betreten dimmen, beim Aufstehen heller/weiß stellen und später vorherige Stimmung wiederherstellen.", "Zonen wie Sofa brauchen andere Helligkeit als Durchgang oder Aktivität.", confidence_base)
+    elif domain in {"switch", "input_boolean"}:
+        if energy:
+            add("strom", "Verbrauchssteuerung", f"{energy} zeigt Standby oder Last", "Steckdose/Schalter bei Bedarf schalten oder Standby reduzieren.", "Stromwerte zeigen, ob ein Verbraucher wirklich gebraucht wird.", confidence_base + 0.1)
+        if presence:
+            add("strom", "Anwesenheitsschalter", f"{presence} aus", "Verbraucher verzögert ausschalten.", "Schalter und Steckdosen sollen Räume nicht unnötig versorgen.", confidence_base)
+        if opening:
+            add("schalter", "Kontaktlogik", f"{opening} wechselt", "Schalter passend zum Öffnen/Schließen setzen.", "Kontaktzustände sind direkte, leicht prüfbare Auslöser.", confidence_base)
+    elif domain == "climate":
+        if temperature:
+            add("heizung", "Temperaturregelung", f"{temperature} weicht vom Ziel ab", "Heizung nach Lernprofil anpassen.", "Temperaturverlauf und Anwesenheit erklären Heizbedarf.", confidence_base + 0.12)
+        if opening:
+            add("heizung", "Fenster-Offen-Schutz", f"{opening} offen", "Heizung pausieren oder Sollwert senken.", "Offene Fenster/Türen sollen nicht gegen die Heizung arbeiten.", confidence_base + 0.1)
+        if presence:
+            add("heizung", "Anwesenheitswärme", f"{presence} an/aus", "Komforttemperatur nur bei Nutzung halten.", "Anwesenheit macht Heizprofile einfacher und sparsamer.", confidence_base)
+    elif domain in {"fan", "humidifier"}:
+        if humidity:
+            add("belueftung", "Feuchteführung", f"{humidity} steigt oder bleibt hoch", "Lüftung/Entfeuchtung einschalten, später zurücknehmen.", "Feuchtigkeit ist der wichtigste Kontext für Lüftung.", confidence_base + 0.16)
+        if presence:
+            add("belueftung", "Nutzungsabhängige Lüftung", f"{presence} aktiv", "Lüftung leise/bedarfsgerecht führen.", "Nutzung erklärt Gerüche, Feuchte und Komfort.", confidence_base)
+    elif domain == "cover":
+        if brightness:
+            add("rollo", "Sonnen-/Dunkellogik", f"{brightness} sehr hell oder dunkel", "Rollo passend beschatten oder öffnen.", "Helligkeit steuert Blendung, Wärme und Tageslicht.", confidence_base + 0.12)
+        if presence:
+            add("rollo", "Privatsphäre", f"{presence} und Abend/Dunkelheit", "Rollo für Privatsphäre schließen.", "Anwesenheit und Lichtlage erklären Rollo-Bedarf.", confidence_base)
+    elif domain in {"valve"}:
+        if water or humidity:
+            add("wasser", "Wasser-/Leckschutz", f"{water or humidity} auffällig", "Ventil schließen oder Sperre vorschlagen.", "Wasser- und Feuchtesensoren sind Sicherheitskontext.", confidence_base + 0.14)
+    elif domain in {"lock", "siren"}:
+        if opening or safety:
+            add("sicherheit", "Sicherheitszustand", f"{opening or safety} meldet Änderung", "Sicherheitsaktion vorschlagen, aber nicht ohne Freigabe aktiv ausführen.", "Sicherheitsaktionen brauchen hohe Sicherheit und klare Erklärung.", confidence_base)
+
+    if not actions:
+        add(
+            domain,
+            "Allgemeine Lernregel",
+            "passende Sensoren in diesem Raum ändern sich",
+            "Aktor im Shadow-Modus beobachten und Vorschläge sammeln.",
+            "Noch fehlen eindeutige Kontextsensoren; Discovery prüft den Raum weiter.",
+            max(0.35, confidence_base - 0.18),
+        )
+    return sorted(actions, key=lambda item: (-item.confidence, item.sort_key))[:8]
+
+
+def _merge_room_actions(
+    existing: list[RoomManagementAction],
+    incoming: list[RoomManagementAction],
+) -> list[RoomManagementAction]:
+    by_key = {action.action_id: action for action in existing}
+    for action in incoming:
+        current = by_key.get(action.action_id)
+        if current is None or action.confidence > current.confidence:
+            by_key[action.action_id] = action
+    return sorted(by_key.values(), key=lambda item: (-item.confidence, item.sort_key))[:18]
+
+
+def _action_rule_line(action: RoomManagementAction) -> str:
+    return f"{action.when} -> {action.then}"
+
+
 def _pattern_rule_lines(patterns: list[BehaviorPattern]) -> list[str]:
     buckets: dict[tuple[str, tuple[tuple[str, str], ...]], int] = {}
     attrs: dict[tuple[str, tuple[tuple[str, str], ...]], dict[str, object]] = {}