Hi,
I'm trying to do QA on documents.
Those documents correspond to different countries, and each of them are divided in chapters (same chapters for each of the countries).
I followed https://gpt-index.readthedocs.io/en/latest/guides/building_a_chatbot.html and successfully converted it to my use case.
I'm therefore using

• a dictionary of GPTSimpleVectorIndex (one per country)
• a GPTListIndex of each of those GPTSimpleVectorIndex

And Langchain is deciding which tool to use (GPTSimpleVectorIndex for a specific country, and GPTListIndex if I want to compare countries)
I still have some problems. Among them, even after selecting the right tool (country), sometimes the right context will not be selected in this country and answer will be false.

Would it be possible to compose the indices differently to get better results?
By exemple, having :

• a GPTSimpleVectorIndex for each section/chapter (of each country)
• a GPTSimpleKeywordTableIndex per country, made of the GPTSimpleVectorIndex used for the sections
• a GPTListIndex made of the GPTSimpleKeywordTableIndex(es) and putting together all the countries

And then correctly defining the toolchain with those different indices.

Thank you