Ollama on JAVAPRO International

Bring AI into your Jakarta EE apps with LangChain4J-CDI (formerly SmallRye-LLM)

Wed, 25 Feb 2026 07:00:01 +0000

Goal: This article will demonstrate how to add AI features to a Jakarta EE / MicroProfile application using LangChain4J‑CDI, with simple to implement examples that runs on Payara, WildFly, Open Liberty, Helidon, Quarkus or any CDI 4.x compatible runtime.

What is LangChain4J-CDI?

Langchain4J is a Java library that simplifies the integration of AI and LLMs easier, and with their feature of AI services it provides a declarative and type-safe API for developers to define interfaces that represent AI services, abstracting away the complexities of direct LLM communication

Tame Your Llama: Run AI in Java

Wed, 15 Oct 2025 07:00:01 +0000

Introduction to AI in Java

What is Llama?

Llama is an advanced open-source AI language model developed by Meta, designed for natural language understanding and generation. Unlike cloud-based AI models, Llama can be run locally, providing a powerful alternative for Java developers who want to integrate AI into their applications without relying on external services. The ability to run Llama models locally means developers can harness AI without exposing data to third-party providers, ensuring privacy and security.

Building Local LLM AI-Powered Applications with Quarkus, Ollama, and Testcontainers

Tue, 09 Sep 2025 07:00:01 +0000

Traditionally, many AI-powered applications rely on cloud-based APIs or centralized services for model hosting and execution. While this approach has its advantages, such as scalability and ease of use, it also introduces challenges around latency, data privacy, and dependency on third-party providers.

This is where local AI models shine. By running models directly within your application’s infrastructure, you gain greater control over performance, data security, and deployment flexibility. However, building such systems requires the right tools and frameworks to bridge the gap between traditional software development and AI model integration.

Local AI with Java: AI Integration Without Cloud Dependency

Fri, 02 May 2025 07:00:03 +0000

The future of artificial intelligence is local. Increasingly, companies are turning to local AI models to ensure data privacy, offline capabilities, and independence from cloud providers. At JCON EUROPE 2025, the two-hour “AI-based optimization in expedition planning – a practice-oriented workshop” with Sven Ruppert will demonstrate exactly how to implement this in Java: high-performance, privacy-friendly AI features – directly in your own application, entirely without cloud services.

Focus on the Open-Source Project “Expedition Planner”

At the center is the open-source project “Expedition Planner”, a Java-based web application designed for planning and organizing expeditions. However, this isn’t just theory: participants will work on real-world use cases, integrating local AI models with Ollama, utilizing Langchain4j and Retrieval Augmented Generation (RAG) to optimize task planning and equipment lists intelligently.