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fix/addon-
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fix/contex
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16
CHANGELOG.md
16
CHANGELOG.md
@@ -1,5 +1,21 @@
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# Changelog
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## 0.5.4 - 2026-06-14
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- Tür-, Bewegungs- und andere belastbare Kontextsensoren werden auch ohne
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numerischen Sensor als vollständige automatische Kontextzuordnung angezeigt
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- Status und Zuordnungssicherheit bilden das aktive Verhaltenslernen ab statt
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eines optionalen numerischen Modells
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- Ausführungsfreigabe erscheint erst, wenn genügend eindeutig manuelle
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Bedienungen vorliegen; bis dahin nennt die Oberfläche die noch fehlende Anzahl
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## 0.5.3 - 2026-06-14
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- Verhindert fachlich falsche Sensorzuordnungen nur aufgrund generischer Namen wie
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`Licht` oder `Lichtschalter`
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- Übernimmt numerische Sensoren nur noch bei einem belastbaren absoluten Score und
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einer eindeutigen Abgrenzung zum zweitbesten Kandidaten
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- Begrenzt Zusatzkontext auf relevante Sensoren und bevorzugt bei Lichtaktoren
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echte Beleuchtungsstärke gegenüber fremden Leistungs- oder Energiezählern
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## 0.5.2 - 2026-06-14
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- Add-on-Build invalidiert den Docker-Cache bei jeder Versionsänderung, damit
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Versionsmetadaten und tatsächlich ausgelieferter Anwendungscode übereinstimmen
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@@ -1,5 +1,5 @@
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name: SillyHome Next
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version: "0.5.2"
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version: "0.5.4"
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slug: sillyhome_next
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description: Lernt automatisch aus deinem Verhalten und steuert freigegebene Aktoren
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url: http://192.168.6.31:3000/pino/sillyhome-next
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@@ -45,6 +45,8 @@ _STOPWORDS = frozenset(
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"humidity",
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"illuminance",
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"light",
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"licht",
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"lichtschalter",
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"power",
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"sensor",
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"state",
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@@ -54,8 +56,10 @@ _STOPWORDS = frozenset(
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}
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)
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_NUMERIC_AUTO_ACCEPT_SCORE = 0.82
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_NUMERIC_AUTO_ACCEPT_MIN_SCORE = 0.5
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_NUMERIC_MIN_MARGIN = 0.18
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_CONTEXT_AUTO_ACCEPT_SCORE = 0.78
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_CONTEXT_AUTO_ACCEPT_MIN_SCORE = 0.3
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_MAX_CONTEXT_SELECTIONS = 5
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_AUDIT_LIMIT = 20
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@@ -231,12 +235,29 @@ class ActuatorReconciliationService:
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numeric_candidates: list[AssignmentCandidate],
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context_candidates: list[AssignmentCandidate],
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) -> AssignmentSelection:
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top_numeric = numeric_candidates[0] if numeric_candidates else None
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top_contexts = [
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candidate.entity_id
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top_numeric = next(
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(candidate for candidate in numeric_candidates if candidate.auto_accepted),
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None,
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)
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accepted_contexts = [
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candidate
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for candidate in context_candidates
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if candidate.auto_accepted
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][: _MAX_CONTEXT_SELECTIONS]
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top_contexts = [candidate.entity_id for candidate in accepted_contexts]
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if top_numeric is None:
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if accepted_contexts:
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return AssignmentSelection(
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selected_numeric_entity_id=None,
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selected_context_entity_ids=top_contexts,
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source=AssignmentSource.AUTOMATIC,
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confidence=max(candidate.confidence for candidate in accepted_contexts),
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review_required=False,
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reason=(
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"Passender Schaltkontext automatisch erkannt. Für diese "
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"Verhaltensvorhersage ist kein numerischer Sensor erforderlich."
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),
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)
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return AssignmentSelection(
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selected_numeric_entity_id=None,
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selected_context_entity_ids=top_contexts,
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@@ -433,8 +454,15 @@ class ActuatorReconciliationService:
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confidence = candidate.score / highest if highest else 0.0
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margin = candidate.score - second_score if index == 0 else 0.0
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auto_score = _CONTEXT_AUTO_ACCEPT_SCORE if context else _NUMERIC_AUTO_ACCEPT_SCORE
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auto_accepted = confidence >= auto_score and (
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context or margin >= _NUMERIC_MIN_MARGIN
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minimum_score = (
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_CONTEXT_AUTO_ACCEPT_MIN_SCORE
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if context
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else _NUMERIC_AUTO_ACCEPT_MIN_SCORE
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)
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auto_accepted = (
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candidate.score >= minimum_score
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and confidence >= auto_score
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and (context or margin >= _NUMERIC_MIN_MARGIN)
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)
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sorted_candidates[index] = candidate.model_copy(
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update={
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@@ -510,6 +538,9 @@ def _score_candidate(
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if entity.device_class in preferred_device_classes:
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score += 0.2
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evidence.append(f"Passende device_class: {entity.device_class}")
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if not context and actuator.domain == "light" and entity.device_class == "illuminance":
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score += 0.2
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evidence.append("Beleuchtungsstärke wird für Lichtaktoren bevorzugt.")
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if not context and entity.unit_of_measurement is not None:
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score += 0.05
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evidence.append(f"Numerische Einheit vorhanden: {entity.unit_of_measurement}")
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@@ -112,6 +112,7 @@ async function api(path, options = {}) {
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}
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function lifecycleLabel(record) {
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if (record.behavior.status === "trained") return "Kontext erkannt";
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const labels = {
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trained: "lernt",
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pending_history: "sammelt Historie",
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@@ -124,6 +125,7 @@ function lifecycleLabel(record) {
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}
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function statusClass(record) {
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if (record.behavior.status === "trained") return "ok";
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if (record.lifecycle.status === "trained") return "ok";
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if (["pending_history", "pending_assignment", "archived"].includes(record.lifecycle.status)) return "warn";
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return "bad";
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@@ -237,11 +239,18 @@ async function showActuator(actuatorId) {
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.map(candidate => `<li><strong>${escapeHtml(candidate.friendly_name || candidate.entity_id)}</strong>: ${candidate.evidence.map(escapeHtml).join(", ") || "statistisch relevanter Kandidat"}</li>`)
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.join("");
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const prediction = record.behavior.prediction;
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const requiredUserActions = 3;
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const missingUserActions = Math.max(
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0,
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requiredUserActions - record.behavior.high_confidence_sample_count,
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);
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const activationButton = record.behavior.mode === "active"
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? `<button class="danger" onclick="setActivation('${escapeHtml(record.actuator_entity_id)}', false)">Autonomes Schalten stoppen</button>`
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: record.behavior.status === "trained"
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: record.behavior.status === "trained" && missingUserActions === 0
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? `<button onclick="setActivation('${escapeHtml(record.actuator_entity_id)}', true)">Lernen und Schalten freigeben</button>`
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: "<p class='muted'>Freigabe wird möglich, sobald genügend Handlungen gelernt wurden.</p>";
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: record.behavior.status === "trained"
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? `<p class='muted'>Freigabe noch gesperrt: ${missingUserActions} eindeutig manuelle Bedienung${missingUserActions === 1 ? "" : "en"} fehlen. Bediene das Licht dafür direkt über Home Assistant.</p>`
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: "<p class='muted'>Freigabe wird möglich, sobald genügend Handlungen gelernt wurden.</p>";
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box.innerHTML = `
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<div class="grid-two">
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<div>
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@@ -5,6 +5,7 @@ from pathlib import Path
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from app.actuators.lifecycle import ActuatorReconciliationService
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from app.actuators.models import (
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AssignmentSource,
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LifecycleStatus,
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ManualOverride,
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model_id_for_actuator,
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@@ -141,7 +142,7 @@ def test_reconciliation_auto_assigns_and_trains_numeric_model(tmp_path: Path) ->
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assert "binary_sensor.abstellkammer_motion" not in artifact.supported_sensors
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def test_reconciliation_uses_best_automatic_mapping_when_ambiguous(tmp_path: Path) -> None:
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def test_reconciliation_rejects_ambiguous_numeric_mapping(tmp_path: Path) -> None:
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start = datetime(2026, 6, 1, tzinfo=timezone.utc)
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entities = [
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HaEntitySummary(
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@@ -181,8 +182,62 @@ def test_reconciliation_uses_best_automatic_mapping_when_ambiguous(tmp_path: Pat
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record = service.configure_actuator("switch.garage_pump")
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assert record.assignment.review_required is True
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assert record.assignment.selected_numeric_entity_id == "sensor.garage_energy"
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assert record.lifecycle.status is LifecycleStatus.TRAINED
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assert record.assignment.selected_numeric_entity_id is None
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assert record.lifecycle.status is LifecycleStatus.ARCHIVED
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def test_reconciliation_does_not_cross_assign_other_room_light_energy(
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tmp_path: Path,
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) -> None:
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start = datetime(2026, 6, 1, tzinfo=timezone.utc)
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entities = [
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HaEntitySummary(
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entity_id=(
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"light.lichtschalter_abstellraum_"
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"lichtschalter_abstellraum_s1"
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),
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domain="light",
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friendly_name="Licht Abstellraum",
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),
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HaEntitySummary(
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entity_id="sensor.licht_badezimmer_energy",
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domain="sensor",
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device_class="energy",
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state_class="total_increasing",
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unit_of_measurement="kWh",
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friendly_name="Lichtschalter_Badezimmer Licht Badezimmer energy",
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),
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HaEntitySummary(
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entity_id="binary_sensor.abstellraum_ture",
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domain="binary_sensor",
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device_class="door",
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friendly_name="Abstellraum Türe",
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),
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HaEntitySummary(
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entity_id="binary_sensor.briefkasten_open",
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domain="binary_sensor",
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device_class="opening",
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friendly_name="Briefkasten open",
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),
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]
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service = _service(
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tmp_path,
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entities,
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{"sensor.licht_badezimmer_energy": _points(8, start, 1.0)},
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)
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record = service.configure_actuator(
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"light.lichtschalter_abstellraum_lichtschalter_abstellraum_s1"
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)
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assert record.assignment.selected_numeric_entity_id is None
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assert record.assignment.selected_context_entity_ids == [
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"binary_sensor.abstellraum_ture"
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]
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assert record.assignment.source is AssignmentSource.AUTOMATIC
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assert record.assignment.confidence == 1.0
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assert record.assignment.review_required is False
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assert record.lifecycle.status is LifecycleStatus.ARCHIVED
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def test_legacy_manual_override_is_cleared_and_automatic_mapping_wins(tmp_path: Path) -> None:
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@@ -14,5 +14,8 @@ def test_dashboard_is_served_at_root() -> None:
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assert "Wie gewohnt bedienen" in response.text
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assert "Ohne deine spätere Freigabe wird nichts geschaltet" in response.text
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assert "Du wählst keine Sensoren und erstellst keine Regeln" in response.text
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assert "Freigabe noch gesperrt" in response.text
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assert "Bediene das Licht dafür direkt über Home Assistant" in response.text
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assert 'record.behavior.status === "trained" && missingUserActions === 0' in response.text
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assert "Automation-Entwurf" not in response.text
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assert "Manuelle Overrides" not in response.text
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Reference in New Issue
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