4 Commits

Author SHA1 Message Date
e4b860571a Enable watchdog and localize dashboard 2026-06-18 14:26:26 +02:00
3c6fe24b03 Add production safety controls 2026-06-18 13:24:17 +02:00
01e5464ec1 Add dashboard control and learning editor 2026-06-18 13:08:58 +02:00
937c79a19b Batch unrouted HA state events 2026-06-18 13:00:57 +02:00
11 changed files with 895 additions and 34 deletions

View File

@@ -2,7 +2,7 @@ FROM python:3.13-slim
WORKDIR /app
ARG SILLYHOME_FUTURE_REF=v2.0.0-alpha.6
ARG SILLYHOME_FUTURE_REF=v2.0.0-alpha.10
RUN python -m pip install --no-cache-dir \
"http://192.168.6.31:3000/Otto/sillyhome-future/archive/${SILLYHOME_FUTURE_REF}.tar.gz"

View File

@@ -1,12 +1,12 @@
name: SillyHome Future
version: "2.0.0-alpha.6"
version: "2.0.0-alpha.10"
slug: sillyhome_future
description: Event-first SillyHome v2 test controller
url: http://192.168.6.31:3000/Otto/sillyhome-future
arch:
- amd64
startup: application
boot: manual
boot: auto
watchdog: http://[HOST]:[PORT:8099]/health
init: false
ingress: true

View File

@@ -27,6 +27,8 @@ class DecisionEngineV2:
blockers.append(f"Domain {domain} ist nicht fuer Active-Control freigegeben.")
if control.manual_block:
blockers.append("Manuelle Sicherheitssperre ist aktiv.")
if control.stage is SafetyStage.ACTIVE and not control.active_ready:
blockers.append("Active ist noch nicht freigegeben. Erst Dry-run-Reife erreichen.")
best = None
for pattern in learning.patterns:
if pattern.trigger_entity_id != trigger_entity_id:
@@ -63,4 +65,3 @@ class DecisionEngineV2:
blockers=blockers,
trigger_entity_id=trigger_entity_id,
)

View File

@@ -76,6 +76,17 @@ class EventCore:
learning=learning_profile,
control=control_profile,
)
if not control.global_enabled and decision.allowed:
decision = decision.model_copy(
update={
"allowed": False,
"reason": "Globaler Not-Aus ist aktiv.",
"blockers": [*decision.blockers, "Globaler Not-Aus ist aktiv."],
}
)
if decision.dry_run:
control_profile = _record_dry_run(control_profile, decision)
control.profiles[actuator_id] = control_profile
if callable(execute) and decision.allowed and not decision.dry_run:
decision = _execute_decision(decision, execute)
audit.append(
@@ -110,3 +121,25 @@ def _execute_decision(decision: Decision, execute: Callable[[Decision], bool]) -
}
)
return decision.model_copy(update={"executed": bool(result)})
def _record_dry_run(profile: ControlProfile, decision: Decision) -> ControlProfile:
events = profile.dry_run_events + 1
successes = profile.dry_run_successes + int(decision.allowed and not decision.blockers)
failures = profile.dry_run_failures + int(bool(decision.blockers))
success_rate = successes / events if events else 0.0
ready = events >= 5 and success_rate >= 0.8 and failures <= 1
reason = (
f"Dry-run {successes}/{events} erfolgreich."
if ready
else f"Dry-run braucht mindestens 5 Events und 80% Treffer; aktuell {successes}/{events}."
)
return profile.model_copy(
update={
"dry_run_events": events,
"dry_run_successes": successes,
"dry_run_failures": failures,
"active_ready": ready,
"active_readiness_reason": reason,
}
)

View File

@@ -67,6 +67,11 @@ class ControlProfile(BaseModel):
handoff_mode: HandoffMode = HandoffMode.SHADOW
related_automation_ids: list[str] = Field(default_factory=list)
paused_automation_ids: list[str] = Field(default_factory=list)
dry_run_events: int = Field(default=0, ge=0)
dry_run_successes: int = Field(default=0, ge=0)
dry_run_failures: int = Field(default=0, ge=0)
active_ready: bool = False
active_readiness_reason: str = "Noch nicht bewertet."
class RoomProfile(BaseModel):
@@ -120,6 +125,7 @@ class LearningState(BaseModel):
class ControlState(BaseModel):
profiles: dict[str, ControlProfile] = Field(default_factory=dict)
global_enabled: bool = True
class BackupBundle(BaseModel):
@@ -127,4 +133,3 @@ class BackupBundle(BaseModel):
runtime: RuntimeState
learning: LearningState
control: ControlState

View File

@@ -4,7 +4,7 @@ import json
import os
from pathlib import Path
from threading import RLock
from typing import TypeVar
from typing import cast, TypeVar
from pydantic import BaseModel
@@ -18,13 +18,20 @@ class JsonDocumentStore:
self.root = Path(root).resolve()
self.root.mkdir(parents=True, exist_ok=True)
self._lock = RLock()
self._cache: dict[str, BaseModel] = {}
def load(self, name: str, model: type[T], default: T) -> T:
path = self.root / name
with self._lock:
cached = self._cache.get(name)
if cached is not None:
return cast(T, cached)
if not path.exists():
self._cache[name] = default
return default
return model.model_validate_json(path.read_text(encoding="utf-8"))
value = model.model_validate_json(path.read_text(encoding="utf-8"))
self._cache[name] = value
return value
def save(self, name: str, value: T) -> T:
path = self.root / name
@@ -35,6 +42,7 @@ class JsonDocumentStore:
encoding="utf-8",
)
os.replace(temporary, path)
self._cache[name] = value
return value
@@ -71,4 +79,3 @@ class FutureStores:
self.save_runtime(bundle.runtime)
self.save_learning(bundle.learning)
self.save_control(bundle.control)

View File

@@ -7,18 +7,24 @@ from contextlib import asynccontextmanager, suppress
from fastapi import FastAPI
from fastapi.responses import HTMLResponse
from pydantic import BaseModel, Field
from app.core.decision import DecisionEngineV2
from app.core.event_core import EventCore
from app.core.ha_client import FutureHaClient, HaClientConfig, service_for_state
from app.core.handoff import HandoffMatrix
from app.core.models import (
AuditEvent,
BackupBundle,
BehaviorPatternV2,
ControlProfile,
ControlState,
EntityState,
HandoffMode,
LearningProfile,
LearningState,
RuntimeState,
SafetyStage,
StateEvent,
)
from app.core.stores import FutureStores
@@ -29,6 +35,57 @@ handoff = HandoffMatrix()
ha_client: FutureHaClient | None = None
class ControlStageUpdate(BaseModel):
stage: SafetyStage
min_confidence: float = Field(default=0.82, ge=0.0, le=1.0)
manual_block: bool = False
cooldown_seconds: int = Field(default=900, ge=0)
class PatternCreateRequest(BaseModel):
trigger_entity_id: str
trigger_state: str | None = None
target_state: str
confidence: float = Field(default=0.9, ge=0.0, le=1.0)
support: int = Field(default=3, ge=1)
source: str = Field(default="dashboard", max_length=40)
class GlobalControlUpdate(BaseModel):
enabled: bool
class SimulationRequest(BaseModel):
actuator_entity_id: str
trigger_entity_id: str
trigger_state: str | None = None
class ActiveReadiness(BaseModel):
actuator_entity_id: str
ready: bool
reason: str
dry_run_events: int
dry_run_successes: int
dry_run_failures: int
class FeedbackRequest(BaseModel):
kind: str = Field(default="correct", max_length=40)
expected_state: str | None = Field(default=None, max_length=100)
note: str | None = Field(default=None, max_length=500)
class ActuatorSummary(BaseModel):
actuator_entity_id: str
stage: SafetyStage
handoff_mode: HandoffMode
active_ready: bool
pattern_count: int
feedback_positive: int
feedback_negative: int
@asynccontextmanager
async def lifespan(app: FastAPI) -> AsyncIterator[None]:
global ha_client
@@ -49,7 +106,7 @@ async def lifespan(app: FastAPI) -> AsyncIterator[None]:
app = FastAPI(
title="SillyHome Future API",
description="SillyHome v2 event-core side project.",
version="2.0.0-alpha.6",
version="2.0.0-alpha.10",
lifespan=lifespan,
)
@@ -64,6 +121,21 @@ def health() -> dict[str, str]:
}
@app.get("/v2/health")
def detailed_health() -> dict[str, object]:
runtime = stores.runtime()
control = stores.control()
return {
"api": "ok",
"version": app.version,
"websocket": runtime.websocket_status,
"store": "ok",
"global_enabled": control.global_enabled,
"entities": len(runtime.entities),
"audit_events": len(runtime.audit),
}
@app.get("/", response_class=HTMLResponse)
def dashboard() -> str:
return _dashboard_html()
@@ -75,9 +147,16 @@ def dashboard_data() -> dict[str, object]:
learning = stores.learning()
control = stores.control()
latest_audit = runtime.audit[-20:]
actuator_entities = [
entity
for entity in runtime.entities.values()
if entity.domain in {"light", "switch", "fan", "cover", "humidifier"}
]
return {
"websocket_status": runtime.websocket_status,
"entity_count": len(runtime.entities),
"actuator_count": len(actuator_entities),
"global_enabled": control.global_enabled,
"learning_profiles": len(learning.profiles),
"control_profiles": len(control.profiles),
"rooms": list(learning.rooms.values()),
@@ -86,6 +165,37 @@ def dashboard_data() -> dict[str, object]:
}
@app.get("/v2/feature-parity")
def feature_parity() -> dict[str, object]:
return {
"baseline": "sillyhome-next",
"policy": "Future implementiert eigene v2-Funktionen, kein next-Code.",
"implemented": [
"HA REST/WebSocket",
"Service-Ausfuehrung",
"Dashboard",
"Aktor-Control",
"Lernmuster",
"Dry-run",
"Safety-Gates",
"Feedback",
"Backup/Restore",
"Raeume/Szenen",
"Not-Aus",
"Simulation",
"Audit",
"Health",
],
"next_to_expand": [
"automations-proposals",
"history-analysis",
"model-training",
"weight-overrides",
"job-queue",
],
}
@app.post("/v2/events/state", response_model=list[AuditEvent])
def ingest_state_event(event: StateEvent) -> list[AuditEvent]:
return event_core.process_state_event(event, execute=_execute_ha_decision)
@@ -96,6 +206,35 @@ def get_runtime() -> RuntimeState:
return stores.runtime()
@app.get("/v2/entities", response_model=list[EntityState])
def list_entities(domain: str | None = None, q: str | None = None) -> list[EntityState]:
entities = list(stores.runtime().entities.values())
if domain:
wanted = {item.strip() for item in domain.split(",") if item.strip()}
entities = [entity for entity in entities if entity.domain in wanted]
if q:
needle = q.casefold()
entities = [
entity
for entity in entities
if needle in entity.entity_id.casefold()
or (entity.friendly_name is not None and needle in entity.friendly_name.casefold())
]
return sorted(entities, key=lambda entity: entity.entity_id)[:500]
@app.get("/v2/entities/groups")
def entity_groups() -> dict[str, list[EntityState]]:
grouped: dict[str, list[EntityState]] = {}
for entity in stores.runtime().entities.values():
key = entity.area_name or entity.domain
grouped.setdefault(key, []).append(entity)
return {
key: sorted(values, key=lambda entity: entity.entity_id)[:250]
for key, values in sorted(grouped.items())
}
@app.get("/v2/learning", response_model=LearningState)
def get_learning() -> LearningState:
return stores.learning()
@@ -111,6 +250,57 @@ def get_control() -> ControlState:
return stores.control()
@app.get("/v2/actuators/summary", response_model=list[ActuatorSummary])
def actuator_summary() -> list[ActuatorSummary]:
learning = stores.learning()
control = stores.control()
ids = sorted(set(learning.profiles) | set(control.profiles))
return [
ActuatorSummary(
actuator_entity_id=actuator_id,
stage=control.profiles.get(
actuator_id,
ControlProfile(actuator_entity_id=actuator_id),
).stage,
handoff_mode=control.profiles.get(
actuator_id,
ControlProfile(actuator_entity_id=actuator_id),
).handoff_mode,
active_ready=control.profiles.get(
actuator_id,
ControlProfile(actuator_entity_id=actuator_id),
).active_ready,
pattern_count=len(
learning.profiles.get(
actuator_id,
LearningProfile(actuator_entity_id=actuator_id),
).patterns
),
feedback_positive=learning.profiles.get(
actuator_id,
LearningProfile(actuator_entity_id=actuator_id),
).feedback_positive,
feedback_negative=learning.profiles.get(
actuator_id,
LearningProfile(actuator_entity_id=actuator_id),
).feedback_negative,
)
for actuator_id in ids
]
@app.post("/v2/control/global", response_model=ControlState)
def set_global_control(update: GlobalControlUpdate) -> ControlState:
state = stores.control().model_copy(update={"global_enabled": update.enabled})
stores.save_control(state)
_append_audit(
"safety",
None,
"Globaler Not-Aus deaktiviert." if update.enabled else "Globaler Not-Aus aktiviert.",
)
return state
@app.put("/v2/control/{actuator_entity_id}", response_model=ControlProfile)
def put_control(actuator_entity_id: str, profile: ControlProfile) -> ControlProfile:
state = stores.control()
@@ -119,6 +309,222 @@ def put_control(actuator_entity_id: str, profile: ControlProfile) -> ControlProf
return profile
@app.post("/v2/control/{actuator_entity_id}/stage", response_model=ControlProfile)
def update_control_stage(
actuator_entity_id: str,
update: ControlStageUpdate,
) -> ControlProfile:
state = stores.control()
profile = state.profiles.get(
actuator_entity_id,
ControlProfile(actuator_entity_id=actuator_entity_id),
)
requested_stage = update.stage
if requested_stage is SafetyStage.ACTIVE and not profile.active_ready:
requested_stage = SafetyStage.DRY_RUN
updated = profile.model_copy(
update={
"stage": requested_stage,
"min_confidence": update.min_confidence,
"manual_block": update.manual_block,
"cooldown_seconds": update.cooldown_seconds,
"handoff_mode": handoff.classify(profile),
}
)
state.profiles[actuator_entity_id] = updated
stores.save_control(state)
_append_audit(
"safety",
actuator_entity_id,
f"Stage gesetzt auf {updated.stage}."
if updated.stage == update.stage
else f"Active blockiert: {updated.active_readiness_reason}",
)
return updated
@app.get("/v2/control/{actuator_entity_id}/readiness", response_model=ActiveReadiness)
def active_readiness(actuator_entity_id: str) -> ActiveReadiness:
profile = stores.control().profiles.get(
actuator_entity_id,
ControlProfile(actuator_entity_id=actuator_entity_id),
)
return ActiveReadiness(
actuator_entity_id=actuator_entity_id,
ready=profile.active_ready,
reason=profile.active_readiness_reason,
dry_run_events=profile.dry_run_events,
dry_run_successes=profile.dry_run_successes,
dry_run_failures=profile.dry_run_failures,
)
@app.post("/v2/learning/{actuator_entity_id}/patterns", response_model=LearningProfile)
def create_learning_pattern(
actuator_entity_id: str,
pattern: PatternCreateRequest,
) -> LearningProfile:
state = stores.learning()
profile = state.profiles.get(
actuator_entity_id,
LearningProfile(actuator_entity_id=actuator_entity_id),
)
updated = profile.model_copy(
update={
"patterns": [
*profile.patterns,
BehaviorPatternV2(
actuator_entity_id=actuator_entity_id,
target_state=pattern.target_state,
trigger_entity_id=pattern.trigger_entity_id,
trigger_state=pattern.trigger_state,
support=pattern.support,
confidence=pattern.confidence,
source=pattern.source,
),
],
"model_version": "dashboard-v1",
}
)
state.profiles[actuator_entity_id] = updated
stores.save_learning(state)
return updated
@app.post("/v2/control/{actuator_entity_id}/feedback", response_model=LearningProfile)
def record_feedback(actuator_entity_id: str, feedback: FeedbackRequest) -> LearningProfile:
state = stores.learning()
profile = state.profiles.get(
actuator_entity_id,
LearningProfile(actuator_entity_id=actuator_entity_id),
)
positive_kinds = {"correct", "too_late_fixed", "too_early_fixed"}
negative_kinds = {"wrong", "too_early", "too_late", "never_automate"}
updated = profile.model_copy(
update={
"feedback_positive": profile.feedback_positive
+ int(feedback.kind in positive_kinds),
"feedback_negative": profile.feedback_negative
+ int(feedback.kind in negative_kinds),
}
)
state.profiles[actuator_entity_id] = updated
stores.save_learning(state)
if feedback.kind == "never_automate":
control = stores.control()
control.profiles[actuator_entity_id] = control.profiles.get(
actuator_entity_id,
ControlProfile(actuator_entity_id=actuator_entity_id),
).model_copy(update={"manual_block": True, "stage": SafetyStage.BLOCKED})
stores.save_control(control)
_append_audit("feedback", actuator_entity_id, f"Feedback: {feedback.kind}")
return updated
@app.post("/v2/planning/refresh", response_model=LearningState)
def refresh_planning() -> LearningState:
state = stores.learning()
runtime = stores.runtime()
rooms = dict(state.rooms)
scenes = dict(state.scenes)
for entity in runtime.entities.values():
room_name = entity.area_name
if not room_name:
continue
room_id = room_name.lower().replace(" ", "_")
room = rooms.get(room_id)
actuator_ids = []
context_ids = []
if entity.domain in {"light", "switch", "fan", "cover", "humidifier"}:
actuator_ids.append(entity.entity_id)
else:
context_ids.append(entity.entity_id)
if room is None:
from app.core.models import RoomProfile
room = RoomProfile(room_id=room_id, name=room_name)
rooms[room_id] = room.model_copy(
update={
"actuator_entity_ids": sorted(
set(room.actuator_entity_ids) | set(actuator_ids)
),
"context_entity_ids": sorted(set(room.context_entity_ids) | set(context_ids)),
}
)
state = state.model_copy(update={"rooms": rooms, "scenes": scenes})
stores.save_learning(state)
_append_audit("planning", None, "Planung aktualisiert.")
return state
@app.get("/v2/anomalies")
def anomalies() -> list[dict[str, object]]:
runtime = stores.runtime()
result: list[dict[str, object]] = []
unavailable = [
entity.entity_id
for entity in runtime.entities.values()
if entity.state in {"unavailable", "unknown"}
][:100]
if unavailable:
result.append(
{
"kind": "unavailable_entities",
"severity": "warning",
"count": len(unavailable),
"entities": unavailable,
}
)
return result
@app.post("/v2/simulate")
def simulate_decision(request: SimulationRequest) -> dict[str, object]:
runtime = stores.runtime()
learning = stores.learning()
control = stores.control()
runtime.entities[request.trigger_entity_id] = EntityState(
entity_id=request.trigger_entity_id,
domain=request.trigger_entity_id.split(".", 1)[0],
state=request.trigger_state,
)
profile = learning.profiles.get(
request.actuator_entity_id,
LearningProfile(actuator_entity_id=request.actuator_entity_id),
)
control_profile = control.profiles.get(
request.actuator_entity_id,
ControlProfile(actuator_entity_id=request.actuator_entity_id),
)
decision = DecisionEngineV2().decide(
actuator_entity_id=request.actuator_entity_id,
trigger_entity_id=request.trigger_entity_id,
runtime=runtime,
learning=profile,
control=control_profile,
)
service = service_for_state(
request.actuator_entity_id.split(".", 1)[0],
decision.target_state,
)
return {
"decision": decision,
"would_call_service": service is not None and decision.allowed and not decision.dry_run,
"service": service,
}
@app.get("/v2/audit/{actuator_entity_id}", response_model=list[AuditEvent])
def actuator_audit(actuator_entity_id: str) -> list[AuditEvent]:
return [
item
for item in stores.runtime().audit
if item.entity_id == actuator_entity_id or (
item.decision is not None and item.decision.actuator_entity_id == actuator_entity_id
)
][-50:]
@app.post("/v2/handoff/{actuator_entity_id}/assume", response_model=ControlProfile)
def assume_control(actuator_entity_id: str) -> ControlProfile:
state = stores.control()
@@ -188,16 +594,34 @@ def _load_initial_ha_states(client: FutureHaClient) -> None:
async def _ha_listener_loop(client: FutureHaClient) -> None:
routed_triggers: set[str] = set()
next_route_refresh = 0.0
pending_unrouted: list[StateEvent] = []
last_unrouted_flush = 0.0
while True:
await asyncio.to_thread(_set_websocket_status, "connecting")
try:
async for event in client.listen_state_events():
loop_time = asyncio.get_running_loop().time()
if loop_time >= next_route_refresh:
routed_triggers = await asyncio.to_thread(_routed_trigger_ids)
next_route_refresh = loop_time + 5
await asyncio.to_thread(_set_websocket_status, "connected")
await asyncio.to_thread(
event_core.process_state_event,
event,
execute=_execute_ha_decision,
)
if event.entity_id in routed_triggers:
if pending_unrouted:
await asyncio.to_thread(_merge_unrouted_events, pending_unrouted)
pending_unrouted = []
await asyncio.to_thread(
event_core.process_state_event,
event,
execute=_execute_ha_decision,
)
else:
pending_unrouted.append(event)
if len(pending_unrouted) >= 100 or loop_time - last_unrouted_flush >= 2:
await asyncio.to_thread(_merge_unrouted_events, pending_unrouted)
pending_unrouted = []
last_unrouted_flush = loop_time
await asyncio.sleep(0)
except asyncio.CancelledError:
raise
@@ -214,6 +638,44 @@ def _set_websocket_status(status: str) -> None:
stores.save_runtime(runtime)
def _routed_trigger_ids() -> set[str]:
result: set[str] = set()
for profile in stores.learning().profiles.values():
for pattern in profile.patterns:
if pattern.trigger_entity_id is not None:
result.add(pattern.trigger_entity_id)
return result
def _merge_unrouted_events(events: list[StateEvent]) -> None:
if not events:
return
runtime = stores.runtime()
for event in events:
runtime.entities[event.entity_id] = EntityState(
entity_id=event.entity_id,
domain=event.entity_id.split(".", 1)[0],
state=event.new_state,
changed_at=event.changed_at,
area_name=event.attributes.get("area_name"),
device_id=event.attributes.get("device_id"),
friendly_name=event.attributes.get("friendly_name"),
)
stores.save_runtime(runtime)
def _append_audit(kind: str, entity_id: str | None, message: str) -> None:
runtime = stores.runtime()
event = AuditEvent(
event_id=f"{kind}-{len(runtime.audit) + 1}",
kind=kind,
entity_id=entity_id,
message=message,
)
runtime.audit = [*runtime.audit, event][-200:]
stores.save_runtime(runtime)
def _execute_ha_decision(decision: object) -> bool:
if ha_client is None or not hasattr(decision, "actuator_entity_id"):
return False
@@ -235,40 +697,245 @@ def _dashboard_html() -> str:
<meta name="viewport" content="width=device-width, initial-scale=1">
<title>SillyHome Future</title>
<style>
body { font-family: system-ui, sans-serif; margin: 0; background: #101418; color: #eef3f6; }
main { max-width: 1080px; margin: 0 auto; padding: 24px; }
:root { color-scheme: dark; --bg: #101418; --panel: #171d23; --line: #2c3640; --text: #eef3f6; --muted: #9fb0bd; --accent: #42d392; --warn: #f3c969; }
* { box-sizing: border-box; }
body { font-family: system-ui, sans-serif; margin: 0; background: var(--bg); color: var(--text); }
main { max-width: 1180px; margin: 0 auto; padding: 20px; }
h1 { font-size: 28px; margin: 0 0 18px; }
.grid { display: grid; grid-template-columns: repeat(auto-fit, minmax(180px, 1fr)); gap: 12px; }
.card { border: 1px solid #2c3640; border-radius: 8px; padding: 14px; background: #171d23; }
h2 { font-size: 18px; margin: 24px 0 10px; }
.grid { display: grid; grid-template-columns: repeat(auto-fit, minmax(170px, 1fr)); gap: 12px; }
.split { display: grid; grid-template-columns: minmax(260px, 1fr) minmax(320px, 1.2fr); gap: 14px; align-items: start; }
.card { border: 1px solid var(--line); border-radius: 8px; padding: 14px; background: var(--panel); }
.label { color: #9fb0bd; font-size: 13px; }
.value { font-size: 24px; margin-top: 4px; }
pre { white-space: pre-wrap; word-break: break-word; background: #0c1014; padding: 14px; border-radius: 8px; }
label { display: block; color: var(--muted); font-size: 13px; margin: 10px 0 5px; }
input, select, button { width: 100%; border: 1px solid var(--line); border-radius: 7px; background: #0c1014; color: var(--text); font: inherit; padding: 10px; }
button { cursor: pointer; background: #20303a; }
button:hover { border-color: var(--accent); }
.row { display: grid; grid-template-columns: repeat(2, minmax(0, 1fr)); gap: 10px; }
.stages { display: grid; grid-template-columns: repeat(4, 1fr); gap: 8px; margin-top: 8px; }
.stages button.active { border-color: var(--accent); color: var(--accent); }
.primary { background: #17402c; border-color: #256f4a; }
.status { min-height: 24px; color: var(--warn); margin-top: 10px; }
pre { max-height: 360px; overflow: auto; white-space: pre-wrap; word-break: break-word; background: #0c1014; padding: 14px; border-radius: 8px; }
@media (max-width: 800px) { .split, .row, .stages { grid-template-columns: 1fr; } }
</style>
</head>
<body>
<main>
<h1>SillyHome Future</h1>
<section class="grid" id="metrics"></section>
<h2>Audit</h2>
<section class="split">
<div class="card">
<h2>Steuerung</h2>
<label for="entitySearch">Suche</label>
<input id="entitySearch" placeholder="light., switch., sensor..." autocomplete="off">
<label for="actuator">Aktor</label>
<select id="actuator"></select>
<div class="row">
<div>
<label for="minConfidence">Mindest-Sicherheit</label>
<input id="minConfidence" type="number" min="0" max="1" step="0.01" value="0.82">
</div>
<div>
<label for="cooldown">Sperrzeit in Sekunden</label>
<input id="cooldown" type="number" min="0" step="30" value="900">
</div>
</div>
<label><input id="manualBlock" type="checkbox" style="width:auto;margin-right:6px"> Manuell blockieren</label>
<div class="stages" id="stages"></div>
<button class="primary" id="saveControl">Steuerung speichern</button>
<button id="globalToggle">Globaler Not-Aus</button>
<div class="status" id="readiness">Ready-Status wird geladen...</div>
<div class="status" id="controlStatus"></div>
</div>
<div class="card">
<h2>Lernmuster</h2>
<div class="row">
<div>
<label for="trigger">Trigger</label>
<select id="trigger"></select>
</div>
<div>
<label for="triggerState">Trigger-Zustand</label>
<input id="triggerState" placeholder="on, off, open...">
</div>
</div>
<div class="row">
<div>
<label for="targetState">Zielzustand</label>
<input id="targetState" value="on">
</div>
<div>
<label for="patternConfidence">Sicherheit</label>
<input id="patternConfidence" type="number" min="0" max="1" step="0.01" value="0.9">
</div>
</div>
<button class="primary" id="addPattern">Lernmuster anlegen</button>
<button id="simulatePattern">Lernmuster simulieren</button>
<div class="status" id="patternStatus"></div>
<h2>Aktuelles Profil</h2>
<pre id="profile">Lade...</pre>
</div>
</section>
<h2>Prüfprotokoll</h2>
<pre id="audit">Lade...</pre>
</main>
<script>
const stages = ['observe', 'dry_run', 'active', 'blocked'];
const stageLabels = {
observe: 'Beobachten',
dry_run: 'Testlauf',
active: 'Aktiv',
blocked: 'Gesperrt',
};
const state = { entities: [], control: {}, learning: {}, selectedStage: 'observe' };
function optionText(entity) {
const name = entity.friendly_name ? ` - ${entity.friendly_name}` : '';
const current = entity.state == null ? '' : ` (${entity.state})`;
return `${entity.entity_id}${current}${name}`;
}
function setStatus(id, text) {
document.getElementById(id).textContent = text;
if (text) setTimeout(() => document.getElementById(id).textContent = '', 4000);
}
function renderStages() {
document.getElementById('stages').innerHTML = stages.map(stage =>
`<button type="button" data-stage="${stage}" class="${stage === state.selectedStage ? 'active' : ''}">${stageLabels[stage]}</button>`
).join('');
document.querySelectorAll('[data-stage]').forEach(button => {
button.onclick = () => { state.selectedStage = button.dataset.stage; renderStages(); };
});
}
function renderEntities() {
const actuator = document.getElementById('actuator');
const trigger = document.getElementById('trigger');
const query = document.getElementById('entitySearch').value.toLowerCase();
const shown = state.entities.filter(entity =>
!query || optionText(entity).toLowerCase().includes(query)
);
const actuators = shown.filter(entity => ['light', 'switch', 'fan', 'cover', 'humidifier'].includes(entity.domain));
actuator.innerHTML = actuators.map(entity => `<option value="${entity.entity_id}">${optionText(entity)}</option>`).join('');
trigger.innerHTML = shown.map(entity => `<option value="${entity.entity_id}">${optionText(entity)}</option>`).join('');
renderProfile();
}
function renderProfile() {
const id = document.getElementById('actuator').value;
const profile = {
control: state.control.profiles?.[id] || null,
learning: state.learning.profiles?.[id] || null,
};
if (profile.control) {
state.selectedStage = profile.control.stage;
document.getElementById('minConfidence').value = profile.control.min_confidence;
document.getElementById('cooldown').value = profile.control.cooldown_seconds;
document.getElementById('manualBlock').checked = profile.control.manual_block;
renderStages();
}
document.getElementById('profile').textContent = JSON.stringify(profile, null, 2);
}
async function loadDashboard() {
const response = await fetch('/v2/dashboard');
const data = await response.json();
const [dashResponse, entitiesResponse, controlResponse, learningResponse] = await Promise.all([
fetch('/v2/dashboard'),
fetch('/v2/entities?domain=light,switch,fan,cover,humidifier,binary_sensor,sensor'),
fetch('/v2/control'),
fetch('/v2/learning'),
]);
const data = await dashResponse.json();
state.entities = await entitiesResponse.json();
state.control = await controlResponse.json();
state.learning = await learningResponse.json();
const metrics = [
['WebSocket', data.websocket_status],
['Entities', data.entity_count],
['Learning', data.learning_profiles],
['Control', data.control_profiles],
['Rooms', data.rooms.length],
['Scenes', data.scenes.length],
['Entitäten', data.entity_count],
['Aktoren', data.actuator_count],
['Not-Aus', data.global_enabled ? 'frei' : 'aktiv'],
['Lernen', data.learning_profiles],
['Steuerung', data.control_profiles],
['Räume', data.rooms.length],
['Szenen', data.scenes.length],
];
document.getElementById('metrics').innerHTML = metrics.map(([label, value]) =>
`<div class="card"><div class="label">${label}</div><div class="value">${value}</div></div>`
).join('');
renderEntities();
await loadReadiness();
document.getElementById('audit').textContent = JSON.stringify(data.audit, null, 2);
}
async function loadReadiness() {
const id = document.getElementById('actuator').value;
if (!id) return;
const response = await fetch(`/v2/control/${encodeURIComponent(id)}/readiness`);
const data = await response.json();
document.getElementById('readiness').textContent =
`${data.ready ? 'bereit fuer Aktiv' : 'nicht bereit fuer Aktiv'} - ${data.reason}`;
}
document.getElementById('entitySearch').oninput = renderEntities;
document.getElementById('actuator').onchange = () => { renderProfile(); loadReadiness(); };
document.getElementById('saveControl').onclick = async () => {
const id = document.getElementById('actuator').value;
const response = await fetch(`/v2/control/${encodeURIComponent(id)}/stage`, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
stage: state.selectedStage,
min_confidence: Number(document.getElementById('minConfidence').value),
manual_block: document.getElementById('manualBlock').checked,
cooldown_seconds: Number(document.getElementById('cooldown').value),
}),
});
if (!response.ok) throw new Error(await response.text());
setStatus('controlStatus', 'Gespeichert');
await loadDashboard();
await loadReadiness();
};
document.getElementById('addPattern').onclick = async () => {
const id = document.getElementById('actuator').value;
const response = await fetch(`/v2/learning/${encodeURIComponent(id)}/patterns`, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
trigger_entity_id: document.getElementById('trigger').value,
trigger_state: document.getElementById('triggerState').value || null,
target_state: document.getElementById('targetState').value,
confidence: Number(document.getElementById('patternConfidence').value),
}),
});
if (!response.ok) throw new Error(await response.text());
setStatus('patternStatus', 'Pattern angelegt');
await loadDashboard();
};
document.getElementById('simulatePattern').onclick = async () => {
const id = document.getElementById('actuator').value;
const response = await fetch('/v2/simulate', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
actuator_entity_id: id,
trigger_entity_id: document.getElementById('trigger').value,
trigger_state: document.getElementById('triggerState').value || null,
}),
});
document.getElementById('profile').textContent = JSON.stringify(await response.json(), null, 2);
};
document.getElementById('globalToggle').onclick = async () => {
const dash = await (await fetch('/v2/dashboard')).json();
await fetch('/v2/control/global', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({ enabled: !dash.global_enabled }),
});
await loadDashboard();
};
renderStages();
loadDashboard();
setInterval(loadDashboard, 5000);
</script>

View File

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
[project]
name = "sillyhome-future"
version = "2.0.0-alpha.6"
version = "2.0.0-alpha.10"
description = "SillyHome v2 event-core prototype"
requires-python = ">=3.11"
dependencies = [

View File

@@ -9,10 +9,12 @@ def test_addon_config_declares_future_addon() -> None:
config = yaml.safe_load(Path("addon/config.yaml").read_text(encoding="utf-8"))
assert config["slug"] == "sillyhome_future"
assert config["version"] == "2.0.0-alpha.6"
assert config["version"] == "2.0.0-alpha.10"
assert config["ingress"] is True
assert config["ingress_port"] == 8099
assert config["homeassistant_api"] is True
assert config["boot"] == "auto"
assert config["watchdog"] == "http://[HOST]:[PORT:8099]/health"
def test_repository_points_to_gitea_repo() -> None:

View File

@@ -2,20 +2,110 @@ from __future__ import annotations
from fastapi.testclient import TestClient
from app.main import app, stores
import app.main as main
from app.core.event_core import EventCore
from app.core.models import EntityState, RuntimeState
from app.core.stores import FutureStores
def test_health_and_backup_roundtrip(tmp_path, monkeypatch) -> None: # type: ignore[no-untyped-def]
monkeypatch.setenv("SILLYHOME_FUTURE_STORE", str(tmp_path))
client = TestClient(app)
test_stores = FutureStores(tmp_path)
monkeypatch.setattr(main, "stores", test_stores)
monkeypatch.setattr(main, "event_core", EventCore(test_stores))
client = TestClient(main.app)
health = client.get("/health")
backup = client.get("/v2/backup/export")
restore = client.post("/v2/backup/restore", json=backup.json())
assert stores is not None
assert health.status_code == 200
assert health.json()["version"] == "2.0.0-alpha.6"
assert health.json()["version"] == "2.0.0-alpha.10"
assert backup.status_code == 200
assert restore.status_code == 200
assert restore.json() == {"status": "restored"}
def test_dashboard_control_and_learning_endpoints(tmp_path, monkeypatch) -> None: # type: ignore[no-untyped-def]
test_stores = FutureStores(tmp_path)
test_stores.save_runtime(
RuntimeState(
entities={
"light.storage": EntityState(
entity_id="light.storage",
domain="light",
state="off",
),
"binary_sensor.storage_door": EntityState(
entity_id="binary_sensor.storage_door",
domain="binary_sensor",
state="off",
),
}
)
)
monkeypatch.setattr(main, "stores", test_stores)
monkeypatch.setattr(main, "event_core", EventCore(test_stores))
client = TestClient(main.app)
entities = client.get("/v2/entities?domain=light,binary_sensor")
control = client.post(
"/v2/control/light.storage/stage",
json={
"stage": "dry_run",
"min_confidence": 0.75,
"manual_block": False,
"cooldown_seconds": 120,
},
)
learning = client.post(
"/v2/learning/light.storage/patterns",
json={
"trigger_entity_id": "binary_sensor.storage_door",
"trigger_state": "on",
"target_state": "on",
"confidence": 0.91,
},
)
simulation = client.post(
"/v2/simulate",
json={
"actuator_entity_id": "light.storage",
"trigger_entity_id": "binary_sensor.storage_door",
"trigger_state": "on",
},
)
readiness = client.get("/v2/control/light.storage/readiness")
global_control = client.post("/v2/control/global", json={"enabled": False})
detailed_health = client.get("/v2/health")
feedback = client.post("/v2/control/light.storage/feedback", json={"kind": "wrong"})
summary = client.get("/v2/actuators/summary")
parity = client.get("/v2/feature-parity")
anomalies = client.get("/v2/anomalies")
dashboard = client.get("/v2/dashboard")
assert entities.status_code == 200
assert [item["entity_id"] for item in entities.json()] == [
"binary_sensor.storage_door",
"light.storage",
]
assert control.status_code == 200
assert control.json()["stage"] == "dry_run"
assert learning.status_code == 200
assert learning.json()["patterns"][0]["trigger_entity_id"] == "binary_sensor.storage_door"
assert simulation.status_code == 200
assert simulation.json()["decision"]["target_state"] == "on"
assert readiness.status_code == 200
assert readiness.json()["ready"] is False
assert global_control.status_code == 200
assert global_control.json()["global_enabled"] is False
assert detailed_health.status_code == 200
assert detailed_health.json()["global_enabled"] is False
assert feedback.status_code == 200
assert feedback.json()["feedback_negative"] == 1
assert summary.status_code == 200
assert summary.json()[0]["actuator_entity_id"] == "light.storage"
assert parity.status_code == 200
assert "Feedback" in parity.json()["implemented"]
assert anomalies.status_code == 200
assert dashboard.status_code == 200
assert dashboard.json()["actuator_count"] == 1

View File

@@ -134,6 +134,7 @@ def test_event_core_executes_allowed_active_decision(tmp_path: Path) -> None:
actuator_entity_id="light.storage",
stage=SafetyStage.ACTIVE,
min_confidence=0.8,
active_ready=True,
)
}
}
@@ -153,3 +154,58 @@ def test_event_core_executes_allowed_active_decision(tmp_path: Path) -> None:
decision = [item.decision for item in audit if item.decision is not None][0]
assert calls == ["light.storage"]
assert decision.executed is True
def test_active_requires_dry_run_readiness(tmp_path: Path) -> None:
stores = FutureStores(tmp_path)
stores.save_runtime(
RuntimeState(
entities={
"light.storage": EntityState(
entity_id="light.storage",
domain="light",
state="off",
)
}
)
)
stores.save_learning(
LearningState(
profiles={
"light.storage": LearningProfile(
actuator_entity_id="light.storage",
patterns=[
BehaviorPatternV2(
actuator_entity_id="light.storage",
target_state="on",
trigger_entity_id="binary_sensor.storage_door",
trigger_state="on",
support=3,
confidence=0.95,
)
],
)
}
)
)
stores.save_control(
stores.control().model_copy(
update={
"profiles": {
"light.storage": ControlProfile(
actuator_entity_id="light.storage",
stage=SafetyStage.ACTIVE,
min_confidence=0.8,
)
}
}
)
)
audit = EventCore(stores).process_state_event(
StateEvent(entity_id="binary_sensor.storage_door", new_state="on")
)
decision = [item.decision for item in audit if item.decision is not None][0]
assert decision.allowed is False
assert "Active ist noch nicht freigegeben" in decision.blockers[0]