chat: fix ChatGPT after #1970

[cebtenzzre]

I'm actually not sure how certain parts of this were working before #1970, namely:

• processRestoreStateFromText() - My understanding is that the LLModel would generate a new reply to both the original prompt and the original reply, because we called LLModel::prompt with the default n_predict (not zero). We were simply not displaying the reply (empty callback), even though it ended up in the LLModel's conversation history (m_context in the case of ChatGPT). I added fakeReply in PR 1970 because the prompt and response now need to happen within the same LLModel::prompt invocation, but as a bonus it fixes this apparent issue.
• For ChatGPT, decrementing n_past to regenerate the reply meant the initial new reply would be based on only the previous context, but we never actually removed anything from m_context, so any further replies would see old messages. Now we resize m_context as needed.

[cebtenzzre]

Actually, I think my understanding of processRestoreStateFromText is accurate for ChatGPT, but not for other subclasses of LLModel: If responseCallback returns false, n_past is not incremented further. But it is still incremented the first time, so one token of the response would be generated by the LLM and recorded in the history. This was true even before 12f943e.

[cebtenzzre]

I tested a version of GPT4All before #1970 and it does indeed exhibit the behavior that I mentioned when you restore a chat session:

decode(n_past=0):
pos=0 1 ''
pos=1 16121 ' ###'
pos=2 9779 ' User'
pos=3 31871 ':'
pos=4 13 '
'
pos=5 10302 'Message'
pos=6 31843 '.'
pos=7 13 '
'
pos=8 8458 '##'
pos=9 31922 '#'
pos=10 13166 ' Response'
pos=11 31871 ':'
pos=12 13 '
'
decode(n_past=13):
pos=13 16644 ' Hello'
decode(n_past=14):
pos=14 16644 ' Hello'
pos=15 31905 '!'
pos=16 312 ' I'
pos=17 705 ' am'
pos=18 1048 ' here'
pos=19 289 ' to'
pos=20 2803 ' assist'
pos=21 365 ' you'

Notice how pos=13 is a token freshly generated by the model based on the current parameters, random state (for temperature sampling), etc. and then pos=14 and onward is what the model generated during the previous session.