How are you solving for PDFs that are too large to fit in the token context? I know of a few approaches for that: - Ignore the problem and let it hallucinate answers to anything that's not in the first 5-10 pages - Attempt to recursively summarize the PDF at the start - so summarize e.g. pages 1-3, then 4-6 etc, then if the resulting summaries are still too long for the context window run a summary of those summaries…
> In the analyzing step, ChatPDF creates a semantic index over all paragraphs of the PDF. When answering a question, ChatPDF finds the most relevant parapgrahs from the PDF and uses the ChatGPT API from OpenAI to generate an answer.
Are you using OpenAI's embeddings to implement that?