input: Write a python function to fit a polynomial model and plot the regression line.
  assert type(plot_regression(x1=[1,2,3], x2=[4,5,6])) == type(None)
  assert type(plot_regression(x1=[10,20,30], x2=[40,50,60])) == type(None)
output: def plot_regression(x1, x2):
      import numpy as np
      import matplotlib.pyplot as plt
      from numpy.polynomial.polynomial import Polynomial
  
      # Fit a polynomial model
      p = Polynomial.fit(x1, x2, deg=1)
  
      # Generate a range of values for plotting the regression line
      x_fit = np.linspace(min(x1), max(x1), 100)
      y_fit = p(x_fit)
  
      # Plot the original data points
      plt.scatter(x1, x2, color='blue', label='Data points')
  
      # Plot the regression line
      plt.plot(x_fit, y_fit, color='red', label='Regression line')
      
      # Add labels and a legend
      plt.xlabel('x1')
      plt.ylabel('x2')
      plt.legend()
  
      # Show the plot
      plt.show()