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6 changed files with 125 additions and 11 deletions

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@@ -1,5 +1,21 @@
# Changelog
## 0.5.4 - 2026-06-14
- Tür-, Bewegungs- und andere belastbare Kontextsensoren werden auch ohne
numerischen Sensor als vollständige automatische Kontextzuordnung angezeigt
- Status und Zuordnungssicherheit bilden das aktive Verhaltenslernen ab statt
eines optionalen numerischen Modells
- Ausführungsfreigabe erscheint erst, wenn genügend eindeutig manuelle
Bedienungen vorliegen; bis dahin nennt die Oberfläche die noch fehlende Anzahl
## 0.5.3 - 2026-06-14
- Verhindert fachlich falsche Sensorzuordnungen nur aufgrund generischer Namen wie
`Licht` oder `Lichtschalter`
- Übernimmt numerische Sensoren nur noch bei einem belastbaren absoluten Score und
einer eindeutigen Abgrenzung zum zweitbesten Kandidaten
- Begrenzt Zusatzkontext auf relevante Sensoren und bevorzugt bei Lichtaktoren
echte Beleuchtungsstärke gegenüber fremden Leistungs- oder Energiezählern
## 0.5.2 - 2026-06-14
- Add-on-Build invalidiert den Docker-Cache bei jeder Versionsänderung, damit
Versionsmetadaten und tatsächlich ausgelieferter Anwendungscode übereinstimmen

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@@ -1,5 +1,5 @@
name: SillyHome Next
version: "0.5.2"
version: "0.5.4"
slug: sillyhome_next
description: Lernt automatisch aus deinem Verhalten und steuert freigegebene Aktoren
url: http://192.168.6.31:3000/pino/sillyhome-next

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@@ -45,6 +45,8 @@ _STOPWORDS = frozenset(
"humidity",
"illuminance",
"light",
"licht",
"lichtschalter",
"power",
"sensor",
"state",
@@ -54,8 +56,10 @@ _STOPWORDS = frozenset(
}
)
_NUMERIC_AUTO_ACCEPT_SCORE = 0.82
_NUMERIC_AUTO_ACCEPT_MIN_SCORE = 0.5
_NUMERIC_MIN_MARGIN = 0.18
_CONTEXT_AUTO_ACCEPT_SCORE = 0.78
_CONTEXT_AUTO_ACCEPT_MIN_SCORE = 0.3
_MAX_CONTEXT_SELECTIONS = 5
_AUDIT_LIMIT = 20
@@ -231,12 +235,29 @@ class ActuatorReconciliationService:
numeric_candidates: list[AssignmentCandidate],
context_candidates: list[AssignmentCandidate],
) -> AssignmentSelection:
top_numeric = numeric_candidates[0] if numeric_candidates else None
top_contexts = [
candidate.entity_id
top_numeric = next(
(candidate for candidate in numeric_candidates if candidate.auto_accepted),
None,
)
accepted_contexts = [
candidate
for candidate in context_candidates
if candidate.auto_accepted
][: _MAX_CONTEXT_SELECTIONS]
top_contexts = [candidate.entity_id for candidate in accepted_contexts]
if top_numeric is None:
if accepted_contexts:
return AssignmentSelection(
selected_numeric_entity_id=None,
selected_context_entity_ids=top_contexts,
source=AssignmentSource.AUTOMATIC,
confidence=max(candidate.confidence for candidate in accepted_contexts),
review_required=False,
reason=(
"Passender Schaltkontext automatisch erkannt. Für diese "
"Verhaltensvorhersage ist kein numerischer Sensor erforderlich."
),
)
return AssignmentSelection(
selected_numeric_entity_id=None,
selected_context_entity_ids=top_contexts,
@@ -433,8 +454,15 @@ class ActuatorReconciliationService:
confidence = candidate.score / highest if highest else 0.0
margin = candidate.score - second_score if index == 0 else 0.0
auto_score = _CONTEXT_AUTO_ACCEPT_SCORE if context else _NUMERIC_AUTO_ACCEPT_SCORE
auto_accepted = confidence >= auto_score and (
context or margin >= _NUMERIC_MIN_MARGIN
minimum_score = (
_CONTEXT_AUTO_ACCEPT_MIN_SCORE
if context
else _NUMERIC_AUTO_ACCEPT_MIN_SCORE
)
auto_accepted = (
candidate.score >= minimum_score
and confidence >= auto_score
and (context or margin >= _NUMERIC_MIN_MARGIN)
)
sorted_candidates[index] = candidate.model_copy(
update={
@@ -510,6 +538,9 @@ def _score_candidate(
if entity.device_class in preferred_device_classes:
score += 0.2
evidence.append(f"Passende device_class: {entity.device_class}")
if not context and actuator.domain == "light" and entity.device_class == "illuminance":
score += 0.2
evidence.append("Beleuchtungsstärke wird für Lichtaktoren bevorzugt.")
if not context and entity.unit_of_measurement is not None:
score += 0.05
evidence.append(f"Numerische Einheit vorhanden: {entity.unit_of_measurement}")

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@@ -112,6 +112,7 @@ async function api(path, options = {}) {
}
function lifecycleLabel(record) {
if (record.behavior.status === "trained") return "Kontext erkannt";
const labels = {
trained: "lernt",
pending_history: "sammelt Historie",
@@ -124,6 +125,7 @@ function lifecycleLabel(record) {
}
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";
return "bad";
@@ -237,11 +239,18 @@ async function showActuator(actuatorId) {
.map(candidate => `<li><strong>${escapeHtml(candidate.friendly_name || candidate.entity_id)}</strong>: ${candidate.evidence.map(escapeHtml).join(", ") || "statistisch relevanter Kandidat"}</li>`)
.join("");
const prediction = record.behavior.prediction;
const requiredUserActions = 3;
const missingUserActions = Math.max(
0,
requiredUserActions - record.behavior.high_confidence_sample_count,
);
const activationButton = record.behavior.mode === "active"
? `<button class="danger" onclick="setActivation('${escapeHtml(record.actuator_entity_id)}', false)">Autonomes Schalten stoppen</button>`
: record.behavior.status === "trained"
: record.behavior.status === "trained" && missingUserActions === 0
? `<button onclick="setActivation('${escapeHtml(record.actuator_entity_id)}', true)">Lernen und Schalten freigeben</button>`
: "<p class='muted'>Freigabe wird möglich, sobald genügend Handlungen gelernt wurden.</p>";
: record.behavior.status === "trained"
? `<p class='muted'>Freigabe noch gesperrt: ${missingUserActions} eindeutig manuelle Bedienung${missingUserActions === 1 ? "" : "en"} fehlen. Bediene das Licht dafür direkt über Home Assistant.</p>`
: "<p class='muted'>Freigabe wird möglich, sobald genügend Handlungen gelernt wurden.</p>";
box.innerHTML = `
<div class="grid-two">
<div>

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@@ -5,6 +5,7 @@ from pathlib import Path
from app.actuators.lifecycle import ActuatorReconciliationService
from app.actuators.models import (
AssignmentSource,
LifecycleStatus,
ManualOverride,
model_id_for_actuator,
@@ -141,7 +142,7 @@ def test_reconciliation_auto_assigns_and_trains_numeric_model(tmp_path: Path) ->
assert "binary_sensor.abstellkammer_motion" not in artifact.supported_sensors
def test_reconciliation_uses_best_automatic_mapping_when_ambiguous(tmp_path: Path) -> None:
def test_reconciliation_rejects_ambiguous_numeric_mapping(tmp_path: Path) -> None:
start = datetime(2026, 6, 1, tzinfo=timezone.utc)
entities = [
HaEntitySummary(
@@ -181,8 +182,62 @@ def test_reconciliation_uses_best_automatic_mapping_when_ambiguous(tmp_path: Pat
record = service.configure_actuator("switch.garage_pump")
assert record.assignment.review_required is True
assert record.assignment.selected_numeric_entity_id == "sensor.garage_energy"
assert record.lifecycle.status is LifecycleStatus.TRAINED
assert record.assignment.selected_numeric_entity_id is None
assert record.lifecycle.status is LifecycleStatus.ARCHIVED
def test_reconciliation_does_not_cross_assign_other_room_light_energy(
tmp_path: Path,
) -> None:
start = datetime(2026, 6, 1, tzinfo=timezone.utc)
entities = [
HaEntitySummary(
entity_id=(
"light.lichtschalter_abstellraum_"
"lichtschalter_abstellraum_s1"
),
domain="light",
friendly_name="Licht Abstellraum",
),
HaEntitySummary(
entity_id="sensor.licht_badezimmer_energy",
domain="sensor",
device_class="energy",
state_class="total_increasing",
unit_of_measurement="kWh",
friendly_name="Lichtschalter_Badezimmer Licht Badezimmer energy",
),
HaEntitySummary(
entity_id="binary_sensor.abstellraum_ture",
domain="binary_sensor",
device_class="door",
friendly_name="Abstellraum Türe",
),
HaEntitySummary(
entity_id="binary_sensor.briefkasten_open",
domain="binary_sensor",
device_class="opening",
friendly_name="Briefkasten open",
),
]
service = _service(
tmp_path,
entities,
{"sensor.licht_badezimmer_energy": _points(8, start, 1.0)},
)
record = service.configure_actuator(
"light.lichtschalter_abstellraum_lichtschalter_abstellraum_s1"
)
assert record.assignment.selected_numeric_entity_id is None
assert record.assignment.selected_context_entity_ids == [
"binary_sensor.abstellraum_ture"
]
assert record.assignment.source is AssignmentSource.AUTOMATIC
assert record.assignment.confidence == 1.0
assert record.assignment.review_required is False
assert record.lifecycle.status is LifecycleStatus.ARCHIVED
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:
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
assert "Freigabe noch gesperrt" in response.text
assert "Bediene das Licht dafür direkt über Home Assistant" in response.text
assert 'record.behavior.status === "trained" && missingUserActions === 0' in response.text
assert "Automation-Entwurf" not in response.text
assert "Manuelle Overrides" not in response.text