input: from typing import List
  
  def predict_next_day_stock_price(stock_prices: List[float]) -> float:
      """
      Given a trajectory of stock prices, create a neural network model using TensorFlow 
      to predict the stock price for the next day. 
      >>> predict_next_day_stock_price([10, 10.4, 10.5, 10.6, 10.7, 10.9, 11])
      11.1
      """
output:     import tensorflow as tf
      from tensorflow.keras.models import Sequential
      from tensorflow.keras.layers import Dense
  
      # Prepare the data
      X = stock_prices[:-1]
      y = stock_prices[1:]
  
      # Build the model
      model = Sequential()
      model.add(Dense(10, input_dim=1, activation='relu'))
      model.add(Dense(1))
  
      # Compile the model
      model.compile(optimizer='adam', loss='mean_squared_error')
  
      # Train the model
      model.fit(X, y, epochs=100, verbose=0)
  
      # Predict the next day's stock price
      next_day_price = model.predict([stock_prices[-1]])
  
      return next_day_price[0][0]