input: Write a function to create a natural language response generation system in Python using TensorFlow Keras. The function should define the model layers, compile the model, and train it on sample data. It should also generate a response for a given query.
  assert generate_response_system()==None
  assert generate_response_system().predict("What time is it?")==prediction
  assert generate_response_system().fit([inputs], [outputs], epochs=10, batch_size=32)==None
output: def generate_response_system():
      from tensorflow.keras.models import Sequential
      from tensorflow.keras.layers import Dense, LSTM, Embedding
      from tensorflow.keras.optimizers import Adam
  
      model = Sequential()
      model.add(Embedding(input_dim=10000, output_dim=128, input_length=10))
      model.add(LSTM(128))
      model.add(Dense(128, activation='relu'))
      model.add(Dense(1, activation='linear'))
      model.compile(optimizer=Adam(), loss='mean_squared_error')
      return model