Bootstrap SillyHome Future v2 core

app/core/__init__.py

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+"""Core v2 modules."""
+

app/core/decision.py

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+from __future__ import annotations
+
+from app.core.models import ControlProfile, Decision, LearningProfile, RuntimeState, SafetyStage
+
+SAFE_DOMAINS = frozenset({"light", "switch", "fan", "cover", "humidifier"})
+
+
+class DecisionEngineV2:
+    def decide(
+        self,
+        *,
+        actuator_entity_id: str,
+        trigger_entity_id: str,
+        runtime: RuntimeState,
+        learning: LearningProfile,
+        control: ControlProfile,
+    ) -> Decision:
+        blockers: list[str] = []
+        actuator = runtime.entities.get(actuator_entity_id)
+        trigger = runtime.entities.get(trigger_entity_id)
+        if actuator is None:
+            blockers.append("Aktor ist im Runtime-State nicht bekannt.")
+        if trigger is None:
+            blockers.append("Trigger ist im Runtime-State nicht bekannt.")
+        domain = actuator_entity_id.split(".", 1)[0]
+        if domain not in SAFE_DOMAINS:
+            blockers.append(f"Domain {domain} ist nicht fuer Active-Control freigegeben.")
+        if control.manual_block:
+            blockers.append("Manuelle Sicherheitssperre ist aktiv.")
+        best = None
+        for pattern in learning.patterns:
+            if pattern.trigger_entity_id != trigger_entity_id:
+                continue
+            if trigger is not None and pattern.trigger_state != trigger.state:
+                continue
+            if best is None or pattern.confidence > best.confidence:
+                best = pattern
+        if best is None:
+            blockers.append("Kein passendes kausales Muster gefunden.")
+            return Decision(
+                actuator_entity_id=actuator_entity_id,
+                allowed=False,
+                reason="Keine Aktion faellig.",
+                blockers=blockers,
+                trigger_entity_id=trigger_entity_id,
+            )
+        if best.confidence < control.min_confidence:
+            blockers.append(
+                f"Confidence {best.confidence:.0%} liegt unter {control.min_confidence:.0%}."
+            )
+        if actuator is not None and actuator.state == best.target_state:
+            blockers.append("Zielzustand ist bereits erreicht.")
+        dry_run = control.stage is SafetyStage.DRY_RUN
+        allowed = not blockers and control.stage in {SafetyStage.ACTIVE, SafetyStage.DRY_RUN}
+        return Decision(
+            actuator_entity_id=actuator_entity_id,
+            target_state=best.target_state,
+            confidence=best.confidence,
+            allowed=allowed,
+            executed=False,
+            dry_run=dry_run,
+            reason="Ausfuehrung freigegeben." if allowed and not dry_run else "Dry-run oder blockiert.",
+            blockers=blockers,
+            trigger_entity_id=trigger_entity_id,
+        )
+

app/core/event_core.py

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+from __future__ import annotations
+
+from datetime import datetime, timezone
+
+from app.core.decision import DecisionEngineV2
+from app.core.handoff import HandoffMatrix
+from app.core.models import (
+    AuditEvent,
+    ControlProfile,
+    EntityState,
+    LearningProfile,
+    StateEvent,
+)
+from app.core.stores import FutureStores
+
+
+class RoutingIndex:
+    def affected_actuators(self, trigger_entity_id: str, learning: dict[str, LearningProfile]) -> list[str]:
+        result = [
+            actuator_id
+            for actuator_id, profile in learning.items()
+            if any(pattern.trigger_entity_id == trigger_entity_id for pattern in profile.patterns)
+        ]
+        return sorted(set(result))
+
+
+class EventCore:
+    def __init__(self, stores: FutureStores) -> None:
+        self._stores = stores
+        self._router = RoutingIndex()
+        self._decision = DecisionEngineV2()
+        self._handoff = HandoffMatrix()
+
+    def process_state_event(self, event: StateEvent) -> list[AuditEvent]:
+        runtime = self._stores.runtime()
+        learning = self._stores.learning()
+        control = self._stores.control()
+        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"),
+        )
+        audit: list[AuditEvent] = [
+            AuditEvent(
+                event_id=_event_id("state"),
+                kind="state",
+                entity_id=event.entity_id,
+                message=f"{event.entity_id} -> {event.new_state}",
+            )
+        ]
+        for actuator_id in self._router.affected_actuators(event.entity_id, learning.profiles):
+            learning_profile = learning.profiles[actuator_id]
+            control_profile = control.profiles.get(
+                actuator_id,
+                ControlProfile(actuator_entity_id=actuator_id),
+            )
+            control_profile = control_profile.model_copy(
+                update={"handoff_mode": self._handoff.classify(control_profile)}
+            )
+            control.profiles[actuator_id] = control_profile
+            decision = self._decision.decide(
+                actuator_entity_id=actuator_id,
+                trigger_entity_id=event.entity_id,
+                runtime=runtime,
+                learning=learning_profile,
+                control=control_profile,
+            )
+            audit.append(
+                AuditEvent(
+                    event_id=_event_id("decision"),
+                    kind="decision",
+                    entity_id=actuator_id,
+                    message=decision.reason,
+                    decision=decision,
+                )
+            )
+        runtime.audit = [*runtime.audit, *audit][-200:]
+        self._stores.save_runtime(runtime)
+        self._stores.save_control(control)
+        return audit
+
+
+def _event_id(prefix: str) -> str:
+    return f"{prefix}-{datetime.now(timezone.utc).strftime('%Y%m%d%H%M%S%f')}"
+

app/core/handoff.py

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+from __future__ import annotations
+
+from app.core.models import ControlProfile, HandoffMode
+
+
+class HandoffMatrix:
+    def classify(self, profile: ControlProfile) -> HandoffMode:
+        active_related = set(profile.related_automation_ids) - set(profile.paused_automation_ids)
+        if profile.handoff_mode is HandoffMode.CONTROLLED and active_related:
+            return HandoffMode.CONFLICT
+        if profile.paused_automation_ids:
+            return HandoffMode.CONTROLLED
+        if profile.related_automation_ids:
+            return HandoffMode.CANDIDATE
+        return profile.handoff_mode
+
+    def assume_control(self, profile: ControlProfile) -> ControlProfile:
+        return profile.model_copy(
+            update={
+                "handoff_mode": HandoffMode.CONTROLLED,
+                "paused_automation_ids": list(profile.related_automation_ids),
+            }
+        )
+
+    def rollback(self, profile: ControlProfile) -> ControlProfile:
+        return profile.model_copy(
+            update={
+                "handoff_mode": HandoffMode.ROLLBACK,
+                "paused_automation_ids": [],
+            }
+        )
+

app/core/models.py

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+from __future__ import annotations
+
+from datetime import datetime, timezone
+from enum import StrEnum
+
+from pydantic import BaseModel, Field
+
+
+class HandoffMode(StrEnum):
+    SHADOW = "shadow"
+    CANDIDATE = "candidate"
+    CONTROLLED = "controlled"
+    CONFLICT = "conflict"
+    ROLLBACK = "rollback"
+
+
+class SafetyStage(StrEnum):
+    OBSERVE = "observe"
+    DRY_RUN = "dry_run"
+    ACTIVE = "active"
+    BLOCKED = "blocked"
+
+
+class EntityState(BaseModel):
+    entity_id: str = Field(pattern=r"^[a-z0-9_]+\.[a-z0-9_]+$")
+    domain: str
+    state: str | None = None
+    changed_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+    area_name: str | None = None
+    device_id: str | None = None
+    friendly_name: str | None = None
+
+
+class StateEvent(BaseModel):
+    entity_id: str = Field(pattern=r"^[a-z0-9_]+\.[a-z0-9_]+$")
+    new_state: str | None = None
+    changed_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+    attributes: dict[str, str] = Field(default_factory=dict)
+
+
+class BehaviorPatternV2(BaseModel):
+    actuator_entity_id: str
+    target_state: str
+    trigger_entity_id: str | None = None
+    trigger_state: str | None = None
+    context: dict[str, str] = Field(default_factory=dict)
+    support: int = Field(default=1, ge=1)
+    confidence: float = Field(default=0.0, ge=0.0, le=1.0)
+    source: str = Field(default="observed", max_length=40)
+    updated_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+
+
+class LearningProfile(BaseModel):
+    actuator_entity_id: str
+    patterns: list[BehaviorPatternV2] = Field(default_factory=list)
+    feedback_positive: int = Field(default=0, ge=0)
+    feedback_negative: int = Field(default=0, ge=0)
+    model_version: str = "empty"
+
+
+class ControlProfile(BaseModel):
+    actuator_entity_id: str
+    stage: SafetyStage = SafetyStage.OBSERVE
+    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)
+    handoff_mode: HandoffMode = HandoffMode.SHADOW
+    related_automation_ids: list[str] = Field(default_factory=list)
+    paused_automation_ids: list[str] = Field(default_factory=list)
+
+
+class RoomProfile(BaseModel):
+    room_id: str = Field(pattern=r"^[a-z0-9_-]{1,64}$")
+    name: str
+    actuator_entity_ids: list[str] = Field(default_factory=list)
+    context_entity_ids: list[str] = Field(default_factory=list)
+
+
+class SceneProfile(BaseModel):
+    scene_id: str = Field(pattern=r"^[a-z0-9_-]{1,64}$")
+    name: str
+    actuator_entity_ids: list[str] = Field(default_factory=list)
+    trigger_entity_id: str | None = None
+    confidence: float = Field(default=0.0, ge=0.0, le=1.0)
+
+
+class Decision(BaseModel):
+    actuator_entity_id: str
+    target_state: str | None = None
+    confidence: float = Field(default=0.0, ge=0.0, le=1.0)
+    allowed: bool = False
+    executed: bool = False
+    dry_run: bool = False
+    reason: str
+    blockers: list[str] = Field(default_factory=list)
+    trigger_entity_id: str | None = None
+    created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+
+
+class AuditEvent(BaseModel):
+    event_id: str
+    kind: str = Field(max_length=40)
+    entity_id: str | None = None
+    message: str = Field(max_length=700)
+    decision: Decision | None = None
+    created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+
+
+class RuntimeState(BaseModel):
+    entities: dict[str, EntityState] = Field(default_factory=dict)
+    audit: list[AuditEvent] = Field(default_factory=list)
+    websocket_status: str = "unavailable"
+
+
+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)
+
+
+class ControlState(BaseModel):
+    profiles: dict[str, ControlProfile] = Field(default_factory=dict)
+
+
+class BackupBundle(BaseModel):
+    exported_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
+    runtime: RuntimeState
+    learning: LearningState
+    control: ControlState
+

app/core/stores.py

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+from __future__ import annotations
+
+import json
+import os
+from pathlib import Path
+from threading import RLock
+from typing import TypeVar
+
+from pydantic import BaseModel
+
+from app.core.models import BackupBundle, ControlState, LearningState, RuntimeState
+
+T = TypeVar("T", bound=BaseModel)
+
+
+class JsonDocumentStore:
+    def __init__(self, root: str | Path) -> None:
+        self.root = Path(root).resolve()
+        self.root.mkdir(parents=True, exist_ok=True)
+        self._lock = RLock()
+
+    def load(self, name: str, model: type[T], default: T) -> T:
+        path = self.root / name
+        with self._lock:
+            if not path.exists():
+                return default
+            return model.model_validate_json(path.read_text(encoding="utf-8"))
+
+    def save(self, name: str, value: T) -> T:
+        path = self.root / name
+        temporary = path.with_suffix(path.suffix + ".tmp")
+        with self._lock:
+            temporary.write_text(
+                json.dumps(value.model_dump(mode="json"), ensure_ascii=True, sort_keys=True) + "\n",
+                encoding="utf-8",
+            )
+            os.replace(temporary, path)
+        return value
+
+
+class FutureStores:
+    def __init__(self, root: str | Path = ".future_store") -> None:
+        self._docs = JsonDocumentStore(root)
+
+    def runtime(self) -> RuntimeState:
+        return self._docs.load("runtime.json", RuntimeState, RuntimeState())
+
+    def save_runtime(self, state: RuntimeState) -> RuntimeState:
+        return self._docs.save("runtime.json", state)
+
+    def learning(self) -> LearningState:
+        return self._docs.load("learning.json", LearningState, LearningState())
+
+    def save_learning(self, state: LearningState) -> LearningState:
+        return self._docs.save("learning.json", state)
+
+    def control(self) -> ControlState:
+        return self._docs.load("control.json", ControlState, ControlState())
+
+    def save_control(self, state: ControlState) -> ControlState:
+        return self._docs.save("control.json", state)
+
+    def export_backup(self) -> BackupBundle:
+        return BackupBundle(
+            runtime=self.runtime(),
+            learning=self.learning(),
+            control=self.control(),
+        )
+
+    def restore_backup(self, bundle: BackupBundle) -> None:
+        self.save_runtime(bundle.runtime)
+        self.save_learning(bundle.learning)
+        self.save_control(bundle.control)
+