Build LLM-Powered Apps with Quarkus and LangChain4j

Join us for a guided tour through the possibilities of the LangChain4j framework! Chat with virtually any LLM provider (OpenAI, Gemini, HuggingFace, Azure, AWS, ...)? Generate AI images straight from your Java application with Dall-E and Gemini? Have LLMs return POJOs? Interact with local models on your machine? LangChain4j makes it a piece of cake! We will explain the fundamental building blocks of LLM-powered applications, show you how to chain them together into AI Services, and how to interact with your knowledge base using advanced RAG.

Then, we take a deeper dive into the Quarkus LangChain4j integration. We'll show how little code is needed when using Quarkus, how live reload makes experimenting with prompts a breeze and finally, we'll look at its native image generation capabilities, aiming to get your AI-powered app deployment-ready in no time.

Eric Deandra is a Java Champion and Senior Principal Software Engineer with over 26 years of experience in designing and building Java-based solutions. Specializes in application development technologies including Quarkus and Spring Boot. Passionate about open-source software, prolific contributor to open-source projects, and an active speaker at industry events and user group meetups around the world. Published author of “Quarkus for Spring Developers” book and numerous industry articles on sites such as DZone, InfoQ, Red Hat Developer, and quarkus.io. Primary maintainer of the Quarkus Superheroes sample/reference application, created in 2021 and continually evolving. Boston Java Users ACM Chapter board member.