Advancements in Retrieval Augmented Generation

This chapter examines the evolution of retrieval augmented generation (RAG) within AI workflows, highlighting its foundational aspects and the challenges of traditional methods. It introduces advanced techniques like hybrid search and GraphRAG that enhance information retrieval by integrating graph-based relationships, ultimately improving the accuracy of large language models' outputs. The chapter also emphasizes practical implementation strategies, including data preparation and best practices for integrating vector embeddings with graph databases.

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