Markovify - Markov chain : Seed and Condition to text generated based in input.

How can I condition the text generation given a previous input.

Example: After creating the model, I pass a 'seed' (a small string) so that the generated sentence is a response based on the text considering a 'seed' given by the user.

I tried to use the 'make_sentence' function passing a string and a list of strings but I got the error below

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/user/studyvenv/lib/python3.10/site-packages/markovify/text.py", line 231, in make_sentence
    words = prefix + self.chain.walk(init_state)
  File "/home/user/studyvenv/lib/python3.10/site-packages/markovify/chain.py", line 142, in walk
    return list(self.gen(init_state))
  File "/home/user/studyvenv/lib/python3.10/site-packages/markovify/chain.py", line 130, in gen
    next_word = self.move(state)
  File "/home/user/studyvenv/lib/python3.10/site-packages/markovify/chain.py", line 116, in move
    choices, weights = zip(*self.model[state].items())
KeyError: ('Hi.', 'How are you')

Start with markovify/text.py at make_sentence and follow the call into chain.py, especially walk, gen, and move, using the traceback as the entry point. Reproduce the reported seed input and inspect how the initial state is formed. Done means conditioning generation on a user-provided seed is supported without the shown KeyError, with the expected behavior covered by tests.