The community member is looking for resources and tutorials beyond the official documentation to better understand the capabilities and use cases of llamaIndex. They want to know when to use a list index versus a keyword table index or a vector index. A community member responds that the documentation is being improved, and in the meantime, the community member can refer to the use cases guide which suggests using a list index for summarization queries and a vector index for fact-based retrieval queries.
Are there any ressources / tutorials beside the docs to get a better understanding of what llamaIndex does and what possibilities there are? I understand the docs but i want to know when to use a list index or if a keyword table index is better than a vector index and so on. This is my first time dipping into the ai area so i dont have a lot of background.
Hey @Tobi we're actively working on improving the documentation. in the meantime these docs should give you some sense of the different use cases: https://gpt-index.readthedocs.io/en/latest/guides/use_cases.html. Use a list index for summarization queries, use a vector index for fact-based retrieval queries
