input: Write a function to create and visualize a simple linear regression model using Python. The function should read data from a CSV file, train the model, make predictions, and display the results in a scatter plot with the regression line.
  assert create_linear_regression_model('data.csv')
  assert create_linear_regression_model('another_data.csv')
  assert create_linear_regression_model('test_data.csv')
output: import pandas as pd
  import numpy as np
  import matplotlib.pyplot as plt
  from sklearn.linear_model import LinearRegression
  
  def create_linear_regression_model(csv_file):
      data = pd.read_csv(csv_file)
      X = data.iloc[:, 0].values.reshape(-1, 1)
      y = data.iloc[:, 1].values
      
      model = LinearRegression()
      model.fit(X, y)
      
      y_pred = model.predict(X)
      
      plt.scatter(X, y, color='blue')
      plt.plot(X, y_pred, color='red')
      plt.xlabel('X')
      plt.ylabel('y')
      plt.title('Linear Regression')
      plt.show()