Leverage LLMs in Java with LangChain4j and Quarkus

Friday 22.Nov

THEME: AI

In this session, we’ll explore how to infuse AI capabilites into Java applications, using LangChain4j and its Quarkus integration. We’ll start from the Quarkus DevUI where you can try out AI models even before writing any code. Then we’ll 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 and compile the app to a native binary.

Building LLM-Powered Applications with Quarkus and Langchain4j

Friday 22.Nov / 15:45

THEME: AI

LLMs are poised to play an important role in our daily lives and as such, place an increasingly large burden on developers to integrate them into the software they build. In this session we will demonstrate how easy it is to create AI powered applications using the combination of Quarkus and Langchain4j.

#AI #LLMs # Quarkus #Langchain4j