Thanks!
Yes, this is enormously helpful. Thank you very much. I’m completely new to all of this, and I have a few questions.
file_path
What sort of files can you store your conversations in? 
store_message_to_file() / find_context()
This certainly is the million-dollar question. I’ve been thinking a lot about how to conserve tokens in conversations. It seems like there is an opportunity when you are storing the message.
What kind of file types can you store the conversation to? Is there some way to intelligently structure those files so that ChatGPT can more efficiently look up the information later?
So, lets say you have a long conversation on a given topic that would exceed your token limit. You’d summarize the output then save it. Does an embedding with find_context() know how to return to files its already made? Or can we help it along by providing more structure in the summaries provided.
What I am interested in is making it possible to have long conversations without loosing context about the earliest parts of the conversations. So I imagine ChatGPT intelligently retrieving summaries unless it needs more information.
Embeddings
Don’t embeddings result in biases in data retrieval? Is there a way to correct for these biases?
GPT 3.5 TURBO vs GPT 4.0
In your code you’re calling on gpt-3.5-turbo. Will any part of this code change significantly when you start using 4.0? Or does this just change the nature of the instructions you pass it? I understand, GPT4 understands conversation far better than 3.5. Which I’ve seen in action, and I think is responsible for a lot of the word-count questions getting asked in Prompting.
For example, I think I read somewhere that 3.5 has trouble with the “system message,” so will GPT4’s greater conversational capacity change how you can interact with it here? As in, only retrieving relevant summaries until it needs more information to try to keep within the token limit?