Quarkus meets AI : Build your own LLM-powered application

In the dynamic landscape of artificial intelligence, the seamless integration of Large Language Models (LLMs) into applications is a key focus for application developers. While many initiatives have emerged to facilitate the integration of LLMs, the world of Java has seen limited options.

Enter Langchain4j, a powerful library designed to seamlessly integrate Java applications with LLMs. The excitement amplifies Langchain4j into Quarkus, a framework designed for building Cloud-Native applications in Java. Quarkus is tuned for Kubernetes environments boasting faster startup times and reduced memory usage compared to traditional Java applications. When Quarkus meets Langchain4j, the process of building a Java LLM-powered application becomes an enjoyable experience.

In this talk, we’ll delve into building AI applications powered by LLMs, using Quarkus and Langchain4j. We’ll leverage existing features from the ecosystem to create effective strategies for data ingestion. We’ll demonstrate how to seamlessly bring in information from a broader set of resources, with the power of Apache Camel.


Zineb Bendhiba

Zineb Bendhiba
Red Hat

With over 15 years of industry experience, I’m currently a Senior Software Engineer at Red Hat, specializing in Integration and Open Source technologies. My passion lies in addressing complex challenges within Cloud Native environments. Within the Apache Camel community, I actively contribute to various topics, aiming to enhance the integration capabilities of Cloud Native applications, particularly within the Quarkus framework.

Engaged in various open source and women in tech communities, I actively participate as a tech speaker, sharing insights and experiences with fellow enthusiasts.

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