Add autopilot light workflow

addon/Dockerfile

@@ -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.13
 RUN python -m pip install --no-cache-dir \
     "http://192.168.6.31:3000/Otto/sillyhome-future/archive/${SILLYHOME_FUTURE_REF}.tar.gz"
 

addon/config.yaml

@@ -1,12 +1,12 @@
 name: SillyHome Future
-version: "2.0.0-alpha.6"
+version: "2.0.0-alpha.13"
 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

app/core/decision.py

@@ -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,
         )
-

app/core/event_core.py

@@ -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,
+        }
+    )

app/core/ha_client.py

@@ -72,6 +72,46 @@ class FutureHaClient:
             )
             response.raise_for_status()
 
+    def read_history(
+        self,
+        entity_ids: list[str],
+        start_time: datetime,
+        end_time: datetime,
+    ) -> dict[str, list[StateEvent]]:
+        params = {
+            "filter_entity_id": ",".join(entity_ids),
+            "end_time": end_time.isoformat(),
+            "minimal_response": "1",
+        }
+        with httpx.Client(timeout=self._config.timeout_seconds) as client:
+            response = client.get(
+                f"{self._core_url}/api/history/period/{start_time.isoformat()}",
+                headers=self._headers,
+                params=params,
+            )
+            response.raise_for_status()
+            payload = response.json()
+        result: dict[str, list[StateEvent]] = {entity_id: [] for entity_id in entity_ids}
+        for series in payload if isinstance(payload, list) else []:
+            if not isinstance(series, list):
+                continue
+            for item in series:
+                if not isinstance(item, dict):
+                    continue
+                entity_id = item.get("entity_id")
+                if not isinstance(entity_id, str):
+                    continue
+                result.setdefault(entity_id, []).append(
+                    StateEvent(
+                        entity_id=entity_id,
+                        new_state=item.get("state") if isinstance(item.get("state"), str) else None,
+                        changed_at=_parse_datetime(
+                            item.get("last_changed") or item.get("last_updated")
+                        ),
+                    )
+                )
+        return result
+
     async def listen_state_events(self) -> AsyncIterator[StateEvent]:
         websocket_url = self._config.websocket_url or _default_websocket_url(self._core_url)
         async with websockets.connect(websocket_url, ping_interval=None) as websocket:
@@ -160,4 +200,3 @@ def _parse_datetime(value: object) -> datetime:
     if parsed.tzinfo is None:
         return parsed.replace(tzinfo=timezone.utc)
     return parsed
-

app/core/models.py

@@ -21,6 +21,25 @@ class SafetyStage(StrEnum):
     BLOCKED = "blocked"
 
 
+class ProposalStatus(StrEnum):
+    DRAFT = "draft"
+    APPROVED = "approved"
+    REJECTED = "rejected"
+
+
+class JobStatus(StrEnum):
+    QUEUED = "queued"
+    RUNNING = "running"
+    SUCCEEDED = "succeeded"
+    FAILED = "failed"
+
+
+class CandidateStatus(StrEnum):
+    PROPOSED = "proposed"
+    ACCEPTED = "accepted"
+    DISMISSED = "dismissed"
+
+
 class EntityState(BaseModel):
     entity_id: str = Field(pattern=r"^[a-z0-9_]+\.[a-z0-9_]+$")
     domain: str
@@ -67,6 +86,11 @@ 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):
@@ -84,6 +108,88 @@ class SceneProfile(BaseModel):
     confidence: float = Field(default=0.0, ge=0.0, le=1.0)
 
 
+class AutomationProposal(BaseModel):
+    proposal_id: str
+    name: str
+    trigger_entity_id: str
+    trigger_state: str | None = None
+    actuator_entity_id: str
+    target_state: str
+    status: ProposalStatus = ProposalStatus.DRAFT
+    revision: int = 1
+    created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+    decided_at: datetime | None = None
+
+
+class ModelRecord(BaseModel):
+    model_id: str
+    actuator_entity_id: str
+    pattern_count: int
+    confidence: float = Field(default=0.0, ge=0.0, le=1.0)
+    trained_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+
+
+class ModelEvaluation(BaseModel):
+    evaluation_id: str
+    model_id: str
+    actuator_entity_id: str
+    score: float = Field(default=0.0, ge=0.0, le=1.0)
+    coverage: float = Field(default=0.0, ge=0.0, le=1.0)
+    dry_run_success_rate: float = Field(default=0.0, ge=0.0, le=1.0)
+    feedback_score: float = Field(default=0.0, ge=0.0, le=1.0)
+    verdict: str
+    reasons: list[str] = Field(default_factory=list)
+    evaluated_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+
+
+class JobQueueItem(BaseModel):
+    job_id: str
+    kind: str
+    status: JobStatus = JobStatus.QUEUED
+    message: str = ""
+    created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+    finished_at: datetime | None = None
+
+
+class SensorWeightOverride(BaseModel):
+    actuator_entity_id: str
+    sensor_weights: dict[str, float] = Field(default_factory=dict)
+    note: str | None = Field(default=None, max_length=500)
+    updated_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+
+
+class AutopilotSettings(BaseModel):
+    enabled: bool = True
+    interval_seconds: int = Field(default=3600, ge=300)
+    min_candidate_confidence: float = Field(default=0.65, ge=0.0, le=1.0)
+    auto_train: bool = True
+    auto_evaluate: bool = True
+    auto_activate: bool = False
+    last_run_at: datetime | None = None
+
+
+class CandidateRecommendation(BaseModel):
+    candidate_id: str
+    actuator_entity_id: str
+    trigger_entity_id: str
+    trigger_state: str | None = None
+    target_state: str
+    confidence: float = Field(default=0.0, ge=0.0, le=1.0)
+    reason: str
+    status: CandidateStatus = CandidateStatus.PROPOSED
+    created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+
+
+class HistoryAnalysis(BaseModel):
+    entity_id: str
+    samples: int
+    last_state: str | None = None
+    changed_at: datetime | None = None
+    unique_states: int = 0
+    transitions: int = 0
+    recommendation: str
+
+
 class Decision(BaseModel):
     actuator_entity_id: str
     target_state: str | None = None
@@ -116,10 +222,18 @@ class LearningState(BaseModel):
     profiles: dict[str, LearningProfile] = Field(default_factory=dict)
     rooms: dict[str, RoomProfile] = Field(default_factory=dict)
     scenes: dict[str, SceneProfile] = Field(default_factory=dict)
+    automation_proposals: dict[str, AutomationProposal] = Field(default_factory=dict)
+    models: dict[str, ModelRecord] = Field(default_factory=dict)
+    model_evaluations: dict[str, ModelEvaluation] = Field(default_factory=dict)
+    jobs: dict[str, JobQueueItem] = Field(default_factory=dict)
+    weight_overrides: dict[str, SensorWeightOverride] = Field(default_factory=dict)
+    candidates: dict[str, CandidateRecommendation] = Field(default_factory=dict)
 
 
 class ControlState(BaseModel):
     profiles: dict[str, ControlProfile] = Field(default_factory=dict)
+    global_enabled: bool = True
+    autopilot: AutopilotSettings = Field(default_factory=AutopilotSettings)
 
 
 class BackupBundle(BaseModel):
@@ -127,4 +241,3 @@ class BackupBundle(BaseModel):
     runtime: RuntimeState
     learning: LearningState
     control: ControlState
-

app/core/stores.py

@@ -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)
-

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "sillyhome-future"
-version = "2.0.0-alpha.6"
+version = "2.0.0-alpha.13"
 description = "SillyHome v2 event-core prototype"
 requires-python = ">=3.11"
 dependencies = [

tests/test_addon_config.py

@@ -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.13"
     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:

tests/test_future_api.py

@@ -2,20 +2,170 @@ 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.13"
     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",
+                    area_name="Storage",
+                ),
+                "light.storage_door": EntityState(
+                    entity_id="light.storage_door",
+                    domain="light",
+                    state="off",
+                    area_name="Storage",
+                ),
+            }
+        )
+    )
+    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")
+    proposal = client.post(
+        "/v2/automations/proposals",
+        json={
+            "name": "Storage light",
+            "trigger_entity_id": "binary_sensor.storage_door",
+            "trigger_state": "on",
+            "actuator_entity_id": "light.storage",
+            "target_state": "on",
+        },
+    )
+    proposal_yaml = client.get("/v2/automations/proposals/proposal-1/yaml")
+    approved = client.post("/v2/automations/proposals/proposal-1/approve")
+    weights = client.post(
+        "/v2/control/light.storage/weights",
+        json={"sensor_weights": {"binary_sensor.storage_door": 1.0}, "note": "door"},
+    )
+    history = client.post(
+        "/v2/history/analyze",
+        json={"entity_ids": ["binary_sensor.storage_door"]},
+    )
+    models = client.post("/v2/models/train", json={"actuator_entity_id": "light.storage"})
+    evaluation = client.post("/v2/models/evaluate", json={"actuator_entity_id": "light.storage"})
+    evaluations = client.get("/v2/models/evaluations")
+    autopilot = client.post("/v2/autopilot/run")
+    candidates = client.get("/v2/autopilot/candidates")
+    accepted = client.post(
+        f"/v2/autopilot/candidates/{autopilot.json()['candidates'][0]['candidate_id']}/accept"
+    )
+    jobs = client.get("/v2/jobs")
+    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",
+        "light.storage_door",
+    ]
+    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 "Job-Queue" in parity.json()["implemented"]
+    assert anomalies.status_code == 200
+    assert proposal.status_code == 200
+    assert proposal.json()["status"] == "draft"
+    assert proposal_yaml.status_code == 200
+    assert "alias: Storage light" in proposal_yaml.text
+    assert approved.status_code == 200
+    assert approved.json()["status"] == "approved"
+    assert weights.status_code == 200
+    assert weights.json()["sensor_weights"]["binary_sensor.storage_door"] == 1.0
+    assert history.status_code == 200
+    assert history.json()[0]["entity_id"] == "binary_sensor.storage_door"
+    assert models.status_code == 200
+    assert models.json()[0]["actuator_entity_id"] == "light.storage"
+    assert evaluation.status_code == 200
+    assert evaluation.json()[0]["verdict"] in {"bereit", "weiter testen"}
+    assert evaluations.status_code == 200
+    assert evaluations.json()
+    assert autopilot.status_code == 200
+    assert autopilot.json()["candidates"]
+    assert candidates.status_code == 200
+    assert accepted.status_code == 200
+    assert jobs.status_code == 200
+    assert jobs.json()
+    assert dashboard.status_code == 200
+    assert dashboard.json()["actuator_count"] == 2
+    assert dashboard.json()["automation_proposals"] == 1

tests/test_future_core.py

@@ -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]