https://www.pinecone.io/learn/langchain-conversational-memor...
But aside from this, if I have a large document that I want to "chat" with, it looks like I am either chunking it and then selectively retrieving relevant subsections at question time, or I am naively dumping the whole document (that now fits in 32k) and then doing the chat, at a high cost. So 32k (and increased context size in general) does not look to be a huge gamechanger in patterns of use until cost comes down by an order of magnitude or two.
I think we may end up with first and second stage completions, where the first stage prepares the context for the second stage. The first stage can be a (tailored) gpt3.5 and the second stage can do the brainy work. That way you can actively control costs by making the first stage forward a context of a given maximum size.
TL;DR the puck should get there very soon, not just Really Soon Now.