Learn More Retrieval-augmented generation (RAG) has become the de facto way of customizing large language models (LLMs) for bespoke information. However, RAG comes with upfront technical costs and ...

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This article outlines and defines various practices used across the RAG pipeline—full-text search, vector search, chunking, hybrid search, query rewriting, and re-ranking. What is full-text search?

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Retrieval augmentated generation (RAG) has grown increasingly popular as a way to improve the quality of text generated by large language models. Now that multimodal LLMs are in vouge, it's time to ...

RAG can improve the efficacy of large language model (LLM) applications by leveraging custom data AIChat has a built-in vector database and full-text search engine, eliminating reliance on third-party ...