Add HA history and model evaluation

app/core/models.py

@@ -123,6 +123,19 @@ class ModelRecord(BaseModel):
     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
@@ -144,6 +157,8 @@ class HistoryAnalysis(BaseModel):
     samples: int
     last_state: str | None = None
     changed_at: datetime | None = None
+    unique_states: int = 0
+    transitions: int = 0
     recommendation: str
 
 
@@ -181,6 +196,7 @@ class LearningState(BaseModel):
     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)