Crafting Your Own RAG System: Leveraging 30+ LLMs for Enhanced Performance

Discover how to build a powerful Retrieval-Augmented Generation (RAG) system using Java that leverages over 30 different Large Language Models. Learn the step-by-step process of ingesting documents, selecting optimal text splitter strategies, finding similar documents, answering questions, and creating a chatbot. Explore methods for testing and comparing various AI models, including open-source and private options, whether locally stored or accessed online. Gain valuable insights into setting up a well-balanced RAG system using Java, identifying the best-performing and most cost-effective LLMs for enhanced performance.