input: from typing import Tuple
  import numpy as np
  import keras 
  from keras.layers import Dense
  from keras.models import Sequential
  
  def predict_annual_income(x_train: np.ndarray, y_train: np.ndarray, age: int, education: int) -> Tuple[np.ndarray, str]:
      """
      This function builds a neural network using Keras to predict a customer's annual income based on their age and education level.
      The neural network is trained on the given x_train and y_train data, and then predicts the annual income for a given age and education level.
      
      >>> x_train = np.array([[25, 0], [30, 0], [35, 0], [40, 0], [45, 1], [45, 2], [50, 1], [50, 2], [55, 1], [55, 2], [50, 3], [60, 3]])
      >>> y_train = [15000, 20000, 25000, 30000, 40000, 45000, 50000, 60000, 65000, 70000, 80000, 90000]
      >>> age = 50
      >>> education = 3
      >>> predicted_income, prediction_str = predict_annual_income(x_train, y_train, age, education)
      >>> print(predicted_income)
      [[80000]]
      >>> print(prediction_str)
      [[80000]]
      """
      # Build model
      model = Sequential()
      model.add(Dense(64, input_dim=2, activation='relu'))
      model.add(Dense(1))
  
      # Compile the model
      model.compile(loss='mean_squared_error', optimizer='adam')
  
      # Fit the model
      model.fit(x_train, y_train, epochs=150, batch_size=2)
  
      # Predict annual income
      annualIncome = model.predict(np.array([[age, education]]))
      annualIncomeStr = np.array2string(annualIncome)
      
      return annualIncome, annualIncomeStr
output:     # Build model
      model = Sequential()
      model.add(Dense(64, input_dim=2, activation='relu'))
      model.add(Dense(1))
  
      # Compile the model
      model.compile(loss='mean_squared_error', optimizer='adam')
  
      # Fit the model
      model.fit(x_train, y_train, epochs=150, batch_size=2)
  
      # Predict annual income
      annualIncome = model.predict(np.array([[age, education]]))
      annualIncomeStr = np.array2string(annualIncome)
      
      return annualIncome, annualIncomeStr