Generative AI (GAI) using Elastic & Amazon SageMaker JumpStart - Elasticsearch Labs

This post details the implementation of a Retrieval Augmented Generation (RAG) system using Elasticsearch as a vector database and Amazon SageMaker JumpStart for hosting open-source LLMs. It outlines the architecture, offline data ingestion process (document ingestion, vectorization, storage in Elasticsearch), and real-time query flow (hybrid search in Elasticsearch, context passing to LLM, response generation). Specific setup steps for an Elasticsearch cluster, loading an embedding model, creating an index, and configuring a web crawler are provided. It also covers choosing and deploying an LLM from SageMaker JumpStart and integrating it with Elasticsearch for RAG.