Learn how to implement RAG (retrieval-augmented generation) with Amazon Bedrock and LangChain. Set up Amazon Bedrock, interact with language models, understand pricing, load and split datasets with LangChain, store embeddings, and use a retriever. Discover how to construct a chatbot using Chains and prompts.
Table of contents
Getting Started With Amazon Bedrock for RAG ApplicationsSample DatasetVector Database: Embedding Storage and SearchChainsConclusion16 Impressions