input: from typing import Any, Dict
  
  def simple_linear_regression_model(data: Dict[str, Any]) -> Any:
      """
      Implement a simple linear regression model using Python. The function should take a dictionary of data containing two lists: 'X' and 'Y'. It should train the model on this data and return the trained model.
  
      >>> data = {'X': [1, 2, 3, 4, 5], 'Y': [2, 4, 5, 4, 5]}
      >>> model = simple_linear_regression_model(data)
      >>> # Check the coefficients to verify the model
      >>> model.coef_
      array([0.6])
      >>> model.intercept_
      2.2
      """
      import pandas as pd
      import matplotlib.pyplot as plt
      from sklearn import linear_model
  
      # Convert data to DataFrame
      df = pd.DataFrame(data)
  
      # Set X and Y
      X = df[['X']]
      Y = df['Y']
  
      # Create linear regression model
      model = linear_model.LinearRegression()
  
      # Train the model
      model.fit(X, Y)
  
      # Make predictions
      Y_pred = model.predict(X)
  
      # Visualize the results (optional)
      # plt.scatter(X, Y)
      # plt.plot(X, Y_pred, color='red')
      # plt.show()
  
      return model
output:     import pandas as pd
      import matplotlib.pyplot as plt
      from sklearn import linear_model
  
      # Convert data to DataFrame
      df = pd.DataFrame(data)
  
      # Set X and Y
      X = df[['X']]
      Y = df['Y']
  
      # Create linear regression model
      model = linear_model.LinearRegression()
  
      # Train the model
      model.fit(X, Y)
  
      # Make predictions
      Y_pred = model.predict(X)
  
      # Visualize the results (optional)
      # plt.scatter(X, Y)
      # plt.plot(X, Y_pred, color='red')
      # plt.show()
  
      return model