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| """Base ML model interfaces.""" | |
| from abc import ABC, abstractmethod | |
| from typing import Any, Dict, List, Optional | |
| import numpy as np | |
| class MLModel(ABC): | |
| """Abstract base class for ML models.""" | |
| def __init__(self, model_name: str): | |
| self.model_name = model_name | |
| self._is_trained = False | |
| async def train(self, data: List[Dict], **kwargs) -> Dict: | |
| """Train the model.""" | |
| pass | |
| async def predict(self, data: List[Dict]) -> List[Dict]: | |
| """Make predictions.""" | |
| pass | |
| async def evaluate(self, data: List[Dict]) -> Dict: | |
| """Evaluate model performance.""" | |
| pass | |
| def is_trained(self) -> bool: | |
| """Check if model is trained.""" | |
| return self._is_trained |