LLM app dev using AWS Bedrock and Langchain

The post explains how to develop applications using Large Language Models (LLMs) with Amazon Bedrock and Langchain to perform tasks like Question Answering over large document corpora. It introduces the concept of retrieval-augmented generation (RAG), which uses document processing and vector embedding to fetch relevant document chunks for question answering. The process includes setting up LLM and embedding models, loading and splitting documents into chunks, creating a vector database using SingleStoreDB, and performing similarity searches to generate context-aware responses.