158 lines
5.2 KiB
Python
158 lines
5.2 KiB
Python
from __future__ import annotations
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from datetime import datetime, timezone
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from enum import StrEnum
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from pydantic import BaseModel, Field
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from app.ha.discovery import EntityRole
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class AssignmentSource(StrEnum):
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NONE = "none"
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AUTOMATIC = "automatic"
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MANUAL = "manual"
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class LifecycleStatus(StrEnum):
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PENDING_ASSIGNMENT = "pending_assignment"
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REVIEW_REQUIRED = "review_required"
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PENDING_HISTORY = "pending_history"
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TRAINED = "trained"
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STALE = "stale"
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INVALID = "invalid"
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ORPHANED = "orphaned"
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ARCHIVED = "archived"
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class BehaviorMode(StrEnum):
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SHADOW = "shadow"
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ACTIVE = "active"
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PAUSED = "paused"
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class BehaviorStatus(StrEnum):
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COLLECTING = "collecting"
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TRAINED = "trained"
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BLOCKED = "blocked"
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class AssignmentCandidate(BaseModel):
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entity_id: str
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domain: str
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role: EntityRole
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device_class: str | None = None
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state_class: str | None = None
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unit_of_measurement: str | None = None
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friendly_name: str | None = None
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area_name: str | None = None
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device_name: str | None = None
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score: float = Field(ge=0.0)
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confidence: float = Field(ge=0.0, le=1.0)
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auto_accepted: bool = False
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evidence: list[str] = Field(default_factory=list)
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class AssignmentSelection(BaseModel):
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selected_numeric_entity_id: str | None = None
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selected_context_entity_ids: list[str] = Field(default_factory=list)
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source: AssignmentSource = AssignmentSource.NONE
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confidence: float = Field(default=0.0, ge=0.0, le=1.0)
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review_required: bool = True
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reason: str = "Noch keine Zuordnung vorhanden."
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class ManualOverride(BaseModel):
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numeric_entity_id: str | None = None
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context_entity_ids: list[str] = Field(default_factory=list)
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updated_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
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note: str | None = None
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class LifecycleAuditEntry(BaseModel):
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at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
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action: str = Field(min_length=1, max_length=120)
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reason: str = Field(min_length=1, max_length=500)
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class ModelLifecycleState(BaseModel):
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model_id: str
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status: LifecycleStatus = LifecycleStatus.PENDING_ASSIGNMENT
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last_reconciled_at: datetime | None = None
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last_trained_at: datetime | None = None
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last_history_signature: str | None = None
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last_history_point_count: int = Field(default=0, ge=0)
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reason: str = "Noch keine Trainingsdaten ausgewertet."
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next_action: str = "Aktor auswählen; Kontext und Historie werden automatisch geprüft."
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audit: list[LifecycleAuditEntry] = Field(default_factory=list)
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class BehaviorPattern(BaseModel):
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target_state: str = Field(min_length=1, max_length=100)
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minute_of_day: int = Field(ge=0, le=1439)
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weekday: int = Field(ge=0, le=6)
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context_states: dict[str, str] = Field(default_factory=dict)
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trigger_entity_id: str | None = None
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trigger_from_state: str | None = None
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trigger_to_state: str | None = None
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source: str = Field(default="observed", max_length=40)
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weight: float = Field(default=1.0, ge=0.1, le=1.0)
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observed_at: datetime
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class BehaviorPrediction(BaseModel):
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target_state: str
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confidence: float = Field(ge=0.0, le=1.0)
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generated_at: datetime
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reason: str
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matching_patterns: int = Field(default=0, ge=0)
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executed: bool = False
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class ExecutionEvent(BaseModel):
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target_state: str
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executed_at: datetime
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class BehaviorState(BaseModel):
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mode: BehaviorMode = BehaviorMode.SHADOW
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status: BehaviorStatus = BehaviorStatus.COLLECTING
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approved_at: datetime | None = None
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sample_count: int = Field(default=0, ge=0)
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high_confidence_sample_count: int = Field(default=0, ge=0)
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patterns: list[BehaviorPattern] = Field(default_factory=list)
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prediction: BehaviorPrediction | None = None
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last_trained_at: datetime | None = None
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last_evaluated_at: datetime | None = None
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last_executed_at: datetime | None = None
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execution_events: list[ExecutionEvent] = Field(default_factory=list)
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reason: str = "Historische Aktorhandlungen werden analysiert."
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class ActuatorRecord(BaseModel):
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actuator_entity_id: str = Field(pattern=r"^[a-z0-9_]+\.[a-z0-9_]+$")
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enabled: bool = True
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created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
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updated_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
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assignment: AssignmentSelection = Field(default_factory=AssignmentSelection)
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manual_override: ManualOverride | None = None
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numeric_candidates: list[AssignmentCandidate] = Field(default_factory=list)
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context_candidates: list[AssignmentCandidate] = Field(default_factory=list)
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lifecycle: ModelLifecycleState
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behavior: BehaviorState = Field(default_factory=BehaviorState)
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class ReconciliationState(BaseModel):
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last_started_at: datetime | None = None
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last_completed_at: datetime | None = None
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last_trigger: str | None = None
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running: bool = False
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configured_actuators: int = Field(default=0, ge=0)
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review_required: int = Field(default=0, ge=0)
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trained_models: int = Field(default=0, ge=0)
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last_summary: str = "Noch keine Reconciliation ausgeführt."
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def model_id_for_actuator(actuator_entity_id: str) -> str:
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return f"actuator.{actuator_entity_id}"
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