Start fixing forecast service API 12

services/training/app/schemas/training.py

@@ -352,11 +352,28 @@ class TrainingErrorUpdate(BaseModel):
     job_id: str = Field(..., description="Training job identifier")
     error: str = Field(..., description="Error message")
     timestamp: datetime = Field(default_factory=datetime.now, description="Error timestamp")
-
+    
+    
+class ModelMetricsResponse(BaseModel):
+    """Response schema for model performance metrics"""
+    model_id: str = Field(..., description="Unique model identifier")
+    accuracy: float = Field(..., description="Model accuracy (R2 score)", ge=0.0, le=1.0)
+    mape: float = Field(..., description="Mean Absolute Percentage Error")
+    mae: float = Field(..., description="Mean Absolute Error")
+    rmse: float = Field(..., description="Root Mean Square Error")
+    r2_score: float = Field(..., description="R-squared score")
+    training_samples: int = Field(..., description="Number of training samples used")
+    features_used: List[str] = Field(..., description="List of features used in training")
+    model_type: str = Field(..., description="Type of ML model")
+    created_at: Optional[str] = Field(None, description="Model creation timestamp")
+    last_used_at: Optional[str] = Field(None, description="Last time model was used")
+    
+    class Config:
+        from_attributes = True
 
 # Union type for all WebSocket messages
 TrainingWebSocketMessage = Union[
     TrainingProgressUpdate,
     TrainingCompletedUpdate,
     TrainingErrorUpdate
-]
+]