input: from typing import Dict
  
  def perform_simple_linear_regression() -> Dict:
      """Perform a simple linear regression on a dataset and return a dictionary containing
      the model, the predicted values, and the original data.
      
      Example:
      >>> perform_simple_linear_regression()
      {'model': LinearRegression(), 'predicted_values': np.array([...]), 'data': pd.DataFrame(...)}
      """
output:     import numpy as np
      import pandas as pd
      from sklearn.linear_model import LinearRegression
  
      # Sample data
      data = pd.DataFrame({
          'X': np.array([1, 2, 3, 4, 5]),
          'Y': np.array([2, 4, 5, 4, 5])
      })
  
      # Prepare the data
      X = data[['X']]
      Y = data['Y']
  
      # Create and fit the model
      model = LinearRegression()
      model.fit(X, Y)
  
      # Predict the values
      predicted_values = model.predict(X)
  
      # Return the result
      return {
          'model': model,
          'predicted_values': predicted_values,
          'data': data
      }