244 lines
7.7 KiB
Python
244 lines
7.7 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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class HandoffMode(StrEnum):
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SHADOW = "shadow"
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CANDIDATE = "candidate"
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CONTROLLED = "controlled"
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CONFLICT = "conflict"
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ROLLBACK = "rollback"
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class SafetyStage(StrEnum):
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OBSERVE = "observe"
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DRY_RUN = "dry_run"
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ACTIVE = "active"
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BLOCKED = "blocked"
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class ProposalStatus(StrEnum):
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DRAFT = "draft"
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APPROVED = "approved"
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REJECTED = "rejected"
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class JobStatus(StrEnum):
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QUEUED = "queued"
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RUNNING = "running"
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SUCCEEDED = "succeeded"
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FAILED = "failed"
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class CandidateStatus(StrEnum):
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PROPOSED = "proposed"
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ACCEPTED = "accepted"
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DISMISSED = "dismissed"
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class EntityState(BaseModel):
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entity_id: str = Field(pattern=r"^[a-z0-9_]+\.[a-z0-9_]+$")
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domain: str
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state: str | None = None
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changed_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
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area_name: str | None = None
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device_id: str | None = None
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friendly_name: str | None = None
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class StateEvent(BaseModel):
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entity_id: str = Field(pattern=r"^[a-z0-9_]+\.[a-z0-9_]+$")
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new_state: str | None = None
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changed_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
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attributes: dict[str, str] = Field(default_factory=dict)
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class BehaviorPatternV2(BaseModel):
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actuator_entity_id: str
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target_state: str
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trigger_entity_id: str | None = None
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trigger_state: str | None = None
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context: dict[str, str] = Field(default_factory=dict)
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support: int = Field(default=1, ge=1)
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confidence: float = Field(default=0.0, ge=0.0, le=1.0)
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source: str = Field(default="observed", max_length=40)
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updated_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
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class LearningProfile(BaseModel):
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actuator_entity_id: str
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patterns: list[BehaviorPatternV2] = Field(default_factory=list)
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feedback_positive: int = Field(default=0, ge=0)
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feedback_negative: int = Field(default=0, ge=0)
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model_version: str = "empty"
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class ControlProfile(BaseModel):
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actuator_entity_id: str
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stage: SafetyStage = SafetyStage.OBSERVE
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min_confidence: float = Field(default=0.82, ge=0.0, le=1.0)
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manual_block: bool = False
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cooldown_seconds: int = Field(default=900, ge=0)
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handoff_mode: HandoffMode = HandoffMode.SHADOW
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related_automation_ids: list[str] = Field(default_factory=list)
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paused_automation_ids: list[str] = Field(default_factory=list)
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dry_run_events: int = Field(default=0, ge=0)
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dry_run_successes: int = Field(default=0, ge=0)
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dry_run_failures: int = Field(default=0, ge=0)
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active_ready: bool = False
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active_readiness_reason: str = "Noch nicht bewertet."
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class RoomProfile(BaseModel):
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room_id: str = Field(pattern=r"^[a-z0-9_-]{1,64}$")
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name: str
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actuator_entity_ids: list[str] = Field(default_factory=list)
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context_entity_ids: list[str] = Field(default_factory=list)
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class SceneProfile(BaseModel):
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scene_id: str = Field(pattern=r"^[a-z0-9_-]{1,64}$")
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name: str
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actuator_entity_ids: list[str] = Field(default_factory=list)
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trigger_entity_id: str | None = None
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confidence: float = Field(default=0.0, ge=0.0, le=1.0)
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class AutomationProposal(BaseModel):
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proposal_id: str
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name: str
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trigger_entity_id: str
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trigger_state: str | None = None
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actuator_entity_id: str
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target_state: str
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status: ProposalStatus = ProposalStatus.DRAFT
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revision: int = 1
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created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
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decided_at: datetime | None = None
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class ModelRecord(BaseModel):
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model_id: str
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actuator_entity_id: str
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pattern_count: int
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confidence: float = Field(default=0.0, ge=0.0, le=1.0)
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trained_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
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class ModelEvaluation(BaseModel):
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evaluation_id: str
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model_id: str
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actuator_entity_id: str
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score: float = Field(default=0.0, ge=0.0, le=1.0)
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coverage: float = Field(default=0.0, ge=0.0, le=1.0)
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dry_run_success_rate: float = Field(default=0.0, ge=0.0, le=1.0)
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feedback_score: float = Field(default=0.0, ge=0.0, le=1.0)
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verdict: str
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reasons: list[str] = Field(default_factory=list)
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evaluated_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
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class JobQueueItem(BaseModel):
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job_id: str
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kind: str
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status: JobStatus = JobStatus.QUEUED
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message: str = ""
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created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
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finished_at: datetime | None = None
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class SensorWeightOverride(BaseModel):
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actuator_entity_id: str
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sensor_weights: dict[str, float] = Field(default_factory=dict)
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note: str | None = Field(default=None, max_length=500)
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updated_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
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class AutopilotSettings(BaseModel):
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enabled: bool = True
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interval_seconds: int = Field(default=3600, ge=300)
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min_candidate_confidence: float = Field(default=0.65, ge=0.0, le=1.0)
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auto_train: bool = True
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auto_evaluate: bool = True
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auto_activate: bool = False
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last_run_at: datetime | None = None
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class CandidateRecommendation(BaseModel):
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candidate_id: str
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actuator_entity_id: str
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trigger_entity_id: str
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trigger_state: str | None = None
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target_state: str
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confidence: float = Field(default=0.0, ge=0.0, le=1.0)
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reason: str
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status: CandidateStatus = CandidateStatus.PROPOSED
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created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
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class HistoryAnalysis(BaseModel):
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entity_id: str
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samples: int
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last_state: str | None = None
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changed_at: datetime | None = None
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unique_states: int = 0
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transitions: int = 0
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recommendation: str
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class Decision(BaseModel):
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actuator_entity_id: str
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target_state: str | None = None
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confidence: float = Field(default=0.0, ge=0.0, le=1.0)
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allowed: bool = False
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executed: bool = False
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dry_run: bool = False
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reason: str
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blockers: list[str] = Field(default_factory=list)
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trigger_entity_id: str | None = None
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created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
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class AuditEvent(BaseModel):
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event_id: str
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kind: str = Field(max_length=40)
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entity_id: str | None = None
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message: str = Field(max_length=700)
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decision: Decision | None = None
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created_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
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class RuntimeState(BaseModel):
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entities: dict[str, EntityState] = Field(default_factory=dict)
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audit: list[AuditEvent] = Field(default_factory=list)
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websocket_status: str = "unavailable"
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class LearningState(BaseModel):
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profiles: dict[str, LearningProfile] = Field(default_factory=dict)
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rooms: dict[str, RoomProfile] = Field(default_factory=dict)
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scenes: dict[str, SceneProfile] = Field(default_factory=dict)
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automation_proposals: dict[str, AutomationProposal] = Field(default_factory=dict)
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models: dict[str, ModelRecord] = Field(default_factory=dict)
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model_evaluations: dict[str, ModelEvaluation] = Field(default_factory=dict)
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jobs: dict[str, JobQueueItem] = Field(default_factory=dict)
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weight_overrides: dict[str, SensorWeightOverride] = Field(default_factory=dict)
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candidates: dict[str, CandidateRecommendation] = Field(default_factory=dict)
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class ControlState(BaseModel):
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profiles: dict[str, ControlProfile] = Field(default_factory=dict)
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global_enabled: bool = True
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autopilot: AutopilotSettings = Field(default_factory=AutopilotSettings)
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class BackupBundle(BaseModel):
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exported_at: datetime = Field(default_factory=lambda: datetime.now(timezone.utc))
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runtime: RuntimeState
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learning: LearningState
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control: ControlState
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