Please help

haha yeah that diagram could be more detailed 🙂

i think the "chain" is confusing. the high-level principle is that we divide up your document into a list of nodes. when you ask a query, we'll feed in the context information from each of the nodes in sequence in order to obtain a final answer

Thanks 😆
I understood that the core function is "list", not "chain"!

@jerryjliu0
I would like to know one more thing.
Is there any way to get 3 solutions in one query, as shown in the following diagram?

I feel "get_nodes_and_similarities_for_response" could work!
But I am not sure how to use it...

@やまかず do you mean 3 answers? ahhh currently we support outputting a single response per query. adding multiple responses is definitely a TODO.

In the meantime, you could try to manually do this yourself. if you manually query the top-level index and retrieve the relevant nodes, you can then try to retrieve each subindex, and query each subindex for a separate response

i can help you with that

Really? Thanks 😆😆😆 I'm glad.
Could you please share that code with me...?

I want the top level index to be a summary of each sub-index.
(I have the summary in set_text now)
I would like to know the "GPT Index" code to manually query the top-level index and get the relevant nodes.

I will then run it on the 3 sub-indexes in a parallel process and get separate responses