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Updated 8 months ago

Hi, got more of a general question. So

aalexnn

Hi, got more of a general question. So there are at least 3 ways to work with summary based RAG in llama_index:

SummaryExtractor
SummaryIndex
DocumentSummaryIndex

What is the main difference in using those? Can someone provide some examples of use cases for each?

1 comment

LLogan M

A summary extractor just uses a summary index

A summary index gives all nodes to the LLM in an iterative process/response mode (usually I would use tree_summarize) to write a summary/answer a query

A document summary index summarizes each input document (using tree summarize), and then uses those summaries to select which documents should be used to answer a query

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