RAG (Retriever-Augmented Generation) architecture helps solve the issue of missing contextualization in LLMs (Large Language Models) without the need for fine-tuning. While Vector RAGs offer some contextualization, graph-based RAGs capture more intricate relationships, making them more effective. This post discusses how to

8m read timeFrom pub.towardsai.net
Post cover image
Table of contents
Building Graph RAG for structured and unstructured data.Building Knowledge GraphsLLM Response

Sort: