input: Write a function to create a Python neural network model that takes in a given trajectory of stock prices and predicts the stock price for the next day. The function should be named `create_model` and return a compiled TensorFlow model. If run as a script, it should use the model to predict the next day's stock price from a given input array and print the prediction.
  
  assert create_model() is not None
  assert np.isclose(predictions[0][0], 11.1, atol=0.5)
  input_data = np.array([[10, 10.4, 10.5, 10.6, 10.7, 10.9, 11]])
  predictions = model.predict(input_data)
output: 
  import tensorflow as tf
  from tensorflow.keras.models import Sequential
  from tensorflow.keras.layers import Dense
  
  def create_model():
      model = Sequential([
          Dense(64, activation='relu', input_shape=(7,)),
          Dense(32, activation='relu'),
          Dense(1)
      ])
      model.compile(optimizer='adam', loss='mse')
      return model
  