<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>LangChain on JAVAPRO International</title><link>https://javapro-en.svenruppert.com/tags/langchain/</link><description>Recent content in LangChain on JAVAPRO International</description><generator>Hugo</generator><language>en-US</language><lastBuildDate>Fri, 02 May 2025 07:00:03 +0000</lastBuildDate><atom:link href="https://javapro-en.svenruppert.com/tags/langchain/index.xml" rel="self" type="application/rss+xml"/><item><title>Local AI with Java: AI Integration Without Cloud Dependency</title><link>https://javapro-en.svenruppert.com/local-ai-with-java-ai-integration-without-cloud-dependency/</link><pubDate>Fri, 02 May 2025 07:00:03 +0000</pubDate><guid>https://javapro-en.svenruppert.com/local-ai-with-java-ai-integration-without-cloud-dependency/</guid><description>&lt;p&gt;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 &lt;a href="https://2025.europe.jcon.one/"&gt;JCON EUROPE 2025&lt;/a&gt;, the two-hour “&lt;a href="https://schedule.jcon.one/session/894517"&gt;AI-based optimization in expedition planning – a practice-oriented workshop&lt;/a&gt;” 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.&lt;/p&gt;
&lt;h2 id="focus-on-the-open-source-project-expedition-planner"&gt;Focus on the Open-Source Project “Expedition Planner”&lt;/h2&gt;
&lt;p&gt;At the center is the open-source project &lt;strong&gt;“Expedition Planner&lt;/strong&gt;”, 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 &lt;strong&gt;Ollama&lt;/strong&gt;, utilizing &lt;strong&gt;Langchain4j&lt;/strong&gt; and &lt;strong&gt;Retrieval Augmented Generation (RAG)&lt;/strong&gt; to optimize task planning and equipment lists intelligently.&lt;/p&gt;</description></item></channel></rss>