input: 
  import numpy as np
  from sklearn.linear_model import LinearRegression
  
  def linear_regression_predictor(X: np.ndarray, Y: np.ndarray, x_predict: float) -> float:
      """Given a dataset X and corresponding Y values, this function fits a linear 
      regression model and predicts the value of y for a given x_predict.
      >>> linear_regression_predictor(np.array([1,2,3,4,5]).reshape(-1,1), np.array([3,5,7,9,13]), 7)
      15.0
      """
      model = LinearRegression()
      model.fit(X, Y)
      return model.predict([[x_predict]])[0]
  
output:     model = LinearRegression()
      model.fit(X, Y)
      return model.predict([[x_predict]])[0]