Retrieval-Augmented Generation (RAG) is the key to making Large Language Models (LLMs) contextually aware of your private data. In this session, we show you how to build RAG applications using the combined power of MongoDB and Spring AI for Java.
We dive into optimizing retrieval workflows, integrating vector search, and utilizing Spring AI Advisors to enhance the performance of LLM-powered apps. You will learn how to bridge the gap between your real-time data and generative AI to create more accurate and reliable user experiences. Watch this session to start building production-ready AI applications.
Continue learning:
- Build & Learn Workshop: MongoDB for Java Spring Builders - MongoDB Overview
- Build & Learn Workshop: MongoDB for Java Spring Builders - MongoDB CRUD Operations in Java
- Build & Learn Workshop: MongoDB for Java Spring Builders - Aggregation Framework with Java
- Build & Learn Workshop: MongoDB for Java Spring Builders - Vector Search with Spring AI
- Build & Learn Workshop: MongoDB for Java Spring Builders - AI Agents with Spring AI
