input: from typing import List
  
  def predict_stock_price(stock_prices: List[float], model_creator) -> float:
      """ Given a list of stock prices representing a trajectory, and a function to create a neural network model,
      predict the stock price for the next day.
      
      >>> def example_model():
      ...     import tensorflow as tf
      ...     model = tf.keras.Sequential([
      ...         tf.keras.layers.Dense(64, activation='relu', input_shape=(7, )),
      ...         tf.keras.layers.Dense(1)
      ...     ])
      ...     model.compile(loss='mean_squared_error', optimizer='adam', metrics=['accuracy'])
      ...     return model
      >>> predict_stock_price([10, 10.4, 10.5, 10.6, 10.7, 10.9, 11], example_model)
      18.941
      """
      import numpy as np 
      model = model_creator()
      input_data = np.array([stock_prices])
      predictions = model.predict(input_data)
      return predictions[0][0]
output:     import numpy as np 
      model = model_creator()
      input_data = np.array([stock_prices])
      predictions = model.predict(input_data)
      return predictions[0][0]