RAG Fundamentals: Hands on with LangChain, Spring AI, & LangChain4j

Description

RAG Unlocked 00:00 Introduction to Retrieval Augmented Generation (RAG) 00:27 Understanding RAG and Context Windows 01:43 RAG Process Overview 02:25 LangChain for J: A Practical Example 04:23 Spring AI and LangChain Frameworks 06:54 Embedding Concepts Explained 08:35 Hands-On with RAG Implementations 12:21 Java Implementations: Spring AI and LangChain for J 18:05 Python Implementation and Vector Stores 21:49 Advanced Topics and Recap Even though RAG is so 2023, many still haven't fully grasped its power. This session provides a simple demonstration of Retrieval Augmented Generation (RAG) and explains the basic concepts of a rag chatbot. We'll dive into what RAG is, how it works, and how it leverages a vector database to enhance large language models (llm) for more accurate responses. Join Ken Kousen as he offers a technical explained overview of this crucial artificial intelligence technique.