When (not) to Use GraphRAG. What is GraphRAG, and when should you… | by Louis-François Bouchard | Aug, 2024 | Towards AI
This is an older post from our weekly High Learning Rate newsletter. Make sure to subscribe to the newsletter here to get them as soon as they go out! This is what GraphRAG looks like… Do you really need such a complicated data web? GraphRAG is a powerful extension to the Retrieval-Augmented Generation (RAG) stack making a lot of noise thanks to Microsoft and LlamaIndex’s contributions. But the question remains: Should YOU be using it? To answer when we need it, we first need to understand what it is. GraphRAG enhances traditional RAG by incorporating knowledge graphs into the retrieval process. Instead of relying solely on vector similarity (comparing numbers to find the most relevant ‘similar’ matches), GraphRAG extracts entities and relationships from your data, creating a structured representation that captures semantic connections. Semantic means understanding the meaning behind words or data, in a specific context, not just their literal definitions. This approach allows for more
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