"""
Generalized wrapper for any custom ML model in OptiFlowX.
This wrapper allows arbitrary hyperparameters and is compatible with scikit-learn API.
"""
from sklearn.base import BaseEstimator

class CustomModel(BaseEstimator):
    def __init__(self, **kwargs):
        """
        Accepts any number of keyword arguments as hyperparameters.
        Example: CustomModel(param1=..., param2=..., ...)
        """
        for k, v in kwargs.items():
            setattr(self, k, v)

    def fit(self, X, y):
        # Dummy fit logic (replace with your own)
        return self

    def predict(self, X):
        # Dummy predict logic: returns zeros
        return [0] * len(X)
