Generative AI has taken the world by storm, and it seems like every executive leader out there is telling us “regular” Java devs to “add AI” to our apps. Does that mean we need to drop everything we’ve built and become data scientists instead now?
Fortunately, we can infuse AI models built by actual AI experts into our applications in a fairly straightforward way. We promise it’s not as complicated as you might think! Thanks to the ease of use and superb developer experience of Quarkus and the nice AI integration capabilities that the LangChain4j libraries offer, it becomes trivial to start working with AI and make your stakeholders happy.
In this session, you’ll explore a variety of AI capabilities. We’ll start from the Quarkus DevUI where you can try out AI models before writing any code. Then we’ll get get into the code and explore LangChain4j features such as prompting, chaining, and preserving state; agents and function-calling; enriching your AI model’s knowledge with your own documents using retrieval augmented generation (RAG); and discovering ways to run (and train) models locally using tools like Ollama and/or Podman AI Lab. In addition, we’ll take a look at observability and fault tolerance of the AI integration. We might even try some new features, such as MCP.
Come to this session to learn how to build AI-infused applications in Java. This is also an opportunity to provide feedback to the maintainers of these projects and contribute back to the community.
Fortunately, we can infuse AI models built by actual AI experts into our applications in a fairly straightforward way. We promise it’s not as complicated as you might think! Thanks to the ease of use and superb developer experience of Quarkus and the nice AI integration capabilities that the LangChain4j libraries offer, it becomes trivial to start working with AI and make your stakeholders happy.
In this session, you’ll explore a variety of AI capabilities. We’ll start from the Quarkus DevUI where you can try out AI models before writing any code. Then we’ll get get into the code and explore LangChain4j features such as prompting, chaining, and preserving state; agents and function-calling; enriching your AI model’s knowledge with your own documents using retrieval augmented generation (RAG); and discovering ways to run (and train) models locally using tools like Ollama and/or Podman AI Lab. In addition, we’ll take a look at observability and fault tolerance of the AI integration. We might even try some new features, such as MCP.
Come to this session to learn how to build AI-infused applications in Java. This is also an opportunity to provide feedback to the maintainers of these projects and contribute back to the community.
Daniel Oh
Red Hat
Java Champion, CNCF Ambassador, Developer Advocate, Technical Marketing, International Speaker, Published Author
Kevin Dubois
Red Hat
Kevin is a Senior Principal Developer Advocate at Red Hat, where his deep passion for open source, Java, and cloud-native development shines through. As a recognized Java Champion, accomplished software engineer, author, and keynote speaker, Kevin is dedicated to pushing the boundaries of modern software development. His role at Red Hat allows him to immerse himself in cutting-edge open source projects while enhancing the developer experience across the globe.
A true advocate for the open source community, Kevin also contributes when he can to projects like Quarkus, Knative, Apache Camel, and Podman (Desktop). He’s also an organizing member of the Belgian CNCF and the Belgian Java User Group.
Multilingual and multicultural, Kevin speaks English, Dutch, French, and Italian fluently. Currently based in Belgium, he has lived in Italy and the USA as well.
A true advocate for the open source community, Kevin also contributes when he can to projects like Quarkus, Knative, Apache Camel, and Podman (Desktop). He’s also an organizing member of the Belgian CNCF and the Belgian Java User Group.
Multilingual and multicultural, Kevin speaks English, Dutch, French, and Italian fluently. Currently based in Belgium, he has lived in Italy and the USA as well.
Georgios Andrianakis
Red Hat
Georgios works for Red Hat as a Principal Software Engineer and is currently the most active contributor for Quarkus, where he works in all sorts of areas, including but not limited to LangChain4j, RESTEasy Reactive, Spring compatibility, Kubernetes support, testing, Kotlin and more.
He is also an enthusiastic promoter of Quarkus that never misses a chance to spread the Quarkus love!
He is also an enthusiastic promoter of Quarkus that never misses a chance to spread the Quarkus love!
Clement Escoffier
Red Hat
Clement Escoffier (@clementplop) is a distinguished engineer at Red Hat and co-lead of the Quarkus project. He is a Java Champion. Before joining Red Hat, Clement had several professional lives, from academic positions to management. He contributed to projects and products, touching many domains and technologies such as OSGi, mobile, continuous delivery, and DevOps. Clement has always been interested in software engineering, distributed systems, and event-driven architecture. He recently focused on Reactive Systems, Cloud-Native applications, and Kubernetes. Clement contributed to many open-source projects, such as Apache Felix, Eclipse Vert.x, SmallRye, Mutiny, and Quarkus. He also authored the "Reactive Systems in Java" book.