input: Write a function to create a neural network model that predicts the next day stock price based on a given trajectory of stock prices. The model should be built using TensorFlow and should take in an array of stock prices from the past 7 days and output the predicted stock price for the next day. If the input array is less than 7 days long, the function should raise an error.
  assert predict_next_day_price([10, 10.4, 10.5, 10.6, 10.7, 10.9, 11]) is not None
  assert len(predict_next_day_price([10, 10.4, 10.5, 10.6, 10.7, 10.9, 11]).shape) == 1
  assert predict_next_day_price([10, 10.4, 10.5]) is ValueError
  assert predict_next_day_price([]) is ValueError
output: def predict_next_day_price(stock_prices):
      if len(stock_prices) != 7:
          raise ValueError("Input array must be exactly 7 days long")
      
      import tensorflow as tf
      from tensorflow.keras.models import Sequential
      from tensorflow.keras.layers import Dense
      
      model = Sequential([
          Dense(10, input_shape=(7,), activation='relu'),
          Dense(1)
      ])
      
      model.compile(optimizer='adam', loss='mean_squared_error')
      
      model.fit(tf.expand_dims(stock_prices, axis=0), tf.expand_dims([0], axis=0), epochs=1, verbose=0)
      
      prediction = model.predict(tf.expand_dims(stock_prices, axis=0), verbose=0)
      
      return prediction[0]