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Quarkus LangChain4j Workshop

Welcome to the Quarkus LangChain4j Workshop!
This workshop will guide you through building AI-infused applications and agentic systems using Quarkus and LangChain4j.

You will learn how to:

  • Integrate LLMs (Language Models) into your Quarkus application
  • Build a chatbot using Quarkus
  • Configure and send prompts to the LLM
  • Implement guardrails for safe interactions
  • Build simple and advanced RAG (Retrieval-Augmented Generation) patterns
  • Use remote tools via the Model Context Protocol (MCP)
  • Connect with remote agents using Agent-to-Agent (A2A) communication
  • Design agentic systems using workflow and supervisor patterns

Workshop Scenario

Throughout the workshop, you will create an LLM-powered customer support chatbot for a car rental company.

The workshop is divided into two sections:

  • Section 1 – AI-infused application (11 steps):
    You’ll progressively build a chatbot, starting with basic LLM integration and adding features such as structured outputs, guardrails, and RAG.

  • Section 2 – Agentic systems (4 steps):
    You’ll extend the chatbot into an agentic workflow, introducing planning, supervision, and collaboration patterns.

Each step builds on the previous one, with the results stored in separate directories (step-XX):

  • Final solution for Section 1: section-1/step-11
  • Final solution for Section 2: section-2/step-04

How to Work with Steps

Tip

We recommend starting with the main branch, then opening the project from step-01 in your IDE.
If you prefer, you can make a copy of the directory instead.

Note

To reset to a particular step, either overwrite your working directory with the content of that step,
or open the project directly from the desired step directory.

Quarkus LangChain4j Workshop Architecture

Let’s Get Started!

First, check the requirements page to prepare your environment.

Once ready, you can pick one of these entries points to start the workshop: