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Conclusion

Alright, this is the end! I hope you enjoyed this tutorial and gained valuable insights into building AI-infused applications.

In just a few hours, we built an intelligent chatbot using Quarkus and Quarkus LangChain4j, demonstrating how to integrate cutting-edge AI capabilities into a modern application. Throughout the process, we explored key concepts, including:

  • Integrating a large language model (LLM) seamlessly within a Quarkus application
  • Utilizing annotations to efficiently pass prompts and structure interactions
  • Implementing the Retrieval Augmented Generation (RAG) pattern to enrich responses with external data
  • Leveraging function calling to create agents—LLMs that can reason and interact with various system components
  • Implementing guardrails to safeguard against common risks, such as prompt injection and LLM misbehavior

By the end of this tutorial, you should now have a solid foundation for building AI-enhanced applications with Quarkus, using its powerful tools to create smarter, more responsive systems. If you have any questions or feedback, don’t hesitate to reach out to us on Zulip. We’re excited to see what you build next!