@yourbuddyconner I'm bummed I missed the chat with @Clayton yesterday. What I'm really struggling with is just understanding what GPT Index offers compared to just using the GPT3 API. More specifically I would love to just have a better understanding of how the different indexes work.

I'm trying to use GPT Index to index a bunch of construction project docs. Each document contains a mix of:
1 Free form text
2 Tables containing info like cost breakdown
3 Hierarchical lists containing info like the steps involved in each phase of the project
4 Biographies of the personnel leading the project. The bios are laid out like resumes and there can be multiple bios per document.

The documents can be anywhere from 50 to 350 pages.

At the moment, I'm just trying to understand what GTP Index is capable of and how to best use the different indexes. I don't mind manually breaking them the documents into logical chunks, if that will yield better results. We'll improve the ingestion process later.

So... my top level questions are:
1) How best to index just a few of these docs as a proof of concept.
2) Since I'm willing to manually chunk the documents, should I use different Index types for different chunks? Vector Index for text, Table Index for the Biographies.
3) How best to index hierarchical lists?
4) How best to maintain context across chunks