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solutions/search/rag.md

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@@ -17,6 +17,7 @@ RAG is a form of [in-context learning](https://arxiv.org/abs/2301.00234), where
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:::{image} ../../images/elasticsearch-reference-rag-venn-diagram.svg
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:alt: RAG sits at the intersection of information retrieval and generative AI
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:width: 600px
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RAG sits at the intersection of [information retrieval](https://www.elastic.co/what-is/information-retrieval) and generative AI. {{es}} is an excellent tool for implementing RAG, because it offers various retrieval capabilities, such as full-text search, vector search, and hybrid search, as well as other tools like filtering, aggregations, and security features.

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