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

What this post added

This post details the implementation of Retrieval Augmented Generation (RAG) using Elasticsearch as a vector database and Amazon SageMaker JumpStart for hosting Large Language Models (LLMs). It outlines the architecture, data ingestion process (including converting text to vectors and storing them in Elasticsearch), and the real-time query flow where hybrid search (BM25 and kNN) is used to retrieve relevant documents. The LLM then uses these documents to generate domain-specific responses. The post also provides step-by-step instructions for setting up an Elasticsearch cluster, loading embedding models, configuring web crawling for data ingestion, and deploying LLMs via SageMaker.