input: Write a function to create a neural network model that predicts the stock price for the next day given a trajectory of stock prices.
  assert create_model()
  if __name__ == "__main__":
      model = create_model()
      input_data = np.array([[10, 10.4, 10.5, 10.6, 10.7, 10.9, 11]])
      predictions = model.predict(input_data)
      output = f"Predicted stock price for the next day is: {predictions[0][0]}"
  assert output.startswith("Predicted stock price for the next day is: ")
output: def create_model():
      import tensorflow as tf
      from tensorflow.keras.models import Sequential
      from tensorflow.keras.layers import Dense, LSTM
      
      model = Sequential()
      model.add(LSTM(50, input_shape=(7, 1)))
      model.add(Dense(1))
      model.compile(optimizer='adam', loss='mse')
      return model