Concerto for Java and AI - Building Production-Ready LLM Applications

Thomas Vitale - Systematic

Imagine you’re a music composer struggling to find inspiration for a pivotal movie scene. Then, you remember you’re also a software engineer, and the solution becomes suddenly obvious. Join me in this session, where I’ll demonstrate how I enhanced my music composition process by harnessing the power of Spring Boot and AI.

This presentation will discuss the core architectural patterns for introducing AI capabilities into an existing software system, exploring concepts like templated prompts, agent tools, and integration of external knowledge. The Java ecosystem is getting more and more capabilities for building AI applications. But are they ready for production? Are there any gaps?

Throughout the session, I’ll build a “composer assistant” application using Spring Boot and an AI Orchestrator (LangChain4J, Spring AI) to showcase how to make an LLM application production-ready. Is the developer experience affected when working locally with language models? How is observability different when it comes to tokens? Can we ensure resilience across the many integrations orchestrated by the AI? What strategies are available for deploying LLM applications?

In a final twist, you’ll choose which movie scene to score, and I’ll compose and perform the music live for it, supported by AI. Will it meet the mark? There’s only one way to find out: join me in exploring the practical side of AI applications, where Java and Generative AI offer tangible solutions to real-world use cases. Aaaaand action!