this sounds like the right answer (and sth i need to keep in mind as well)

just as an FYI, this is one answer i found from a twitter thread

• the data that needs to be fed into the model is divided into chunks
• when a user asks a question, each of these chunks (likely less than 4k tokens) is reviewed
• when there is a section of the chunk that is relevant, that section is combined with the user question
• this combined text is fed as prompt, and GPT-3 is able to answer the user's question

there's a prebuilt openai notebook you can use to replicate it