Table of Contents VideoPodcast (audio only)Content Let’s have an AI Bingo and talk about ChatGPT, LLM, ML, RAG, MCP, GenAI, and more! This is part 3 of the interviews recorded at the JCON conference in May. In the previous parts, …
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Build a Sentiment Analysis API in Java with Quarkus and Local LLMs
Table of Contents What You’ll BuildPrerequisitesBootstrap Your Quarkus ProjectConfigure Ollama and Dev ServicesDefine the Sentiment EnumCreate the AI Classification ServiceExpose the Sentiment APIRun It!Test It!Final ThoughtsWhat’s Next? In a world full of opinions, tweets, reviews, chats, emails, understanding the tone …
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Ensuring Safe and Reliable AI Interactions with LLM Guardrails
Table of Contents Understanding LLM guardrailsHow guardrails workEasily implementing guardrails with QuarkusInput guardrailsOutput guardrailsSanitizing LLM input and output Integrating Large Language Models (LLMs) into our applications is becoming increasingly popular. These models are extremely useful for creating content, searching documentation, …
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Intro to RAG: Foundations of Retrieval Augmented Generation, part 1
Table of Contents Why RAG?Large Language Models (LLMs)Vector embeddingsVectors applied to wordsVectors applied to dataSimilarity searchWrapping up!Resources Retrieval Augmented Generation (RAG) may sound complex, but it accurately represents the process of the system. RAG is a method that enhances the …
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SummarizingTokenWindowChatMemory: Enhancing LLM’s Conversations with Efficient Summarization
Table of Contents SummarizingTokenWindowChatMemoryThe Summarizer InterfaceSummarization LogicLLM SummarizationWhy This MattersConclusion LLM chat models have become an integral part of many applications today. We are all experimenting and exploring the best ways to utilize them effectively. For Java developers, LangChain4j has …
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Building local LLM AI-Powered Applications with Quarkus, Ollama and Testcontainers
Table of Contents Project Overview1. Integrating Quarkus with OllamaWhy Ollama?Quarkus and Ollama Integration2. Using Testcontainers for Integration TestingWhy Testcontainers?Example: Setting up a Testcontainer for OllamaKey Points:3. Leveraging Quarkus Dev Services for OllamaWhat Are Quarkus Dev Services?Configuring Dev ServicesDevelopment WorkflowConclusionKey Takeaways: …
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Langchain4J Musings
Table of Contents Choosing a LLMQuick introduction to LangChain4J and OllamaGetting our feet wetThe LangChain4j appThe Ollama infrastructureEnhancing with streamingRemembering historyAdding Retrieval-Augmented GenerationConclusion I’m coming relatively late to the LLM party, but I rarely come very early in the hype …
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Calling Gemma with Ollama, TestContainers, and LangChain4j
Lately, for my Generative AI powered Java apps, I’ve used the Gemini multimodal large language model from Google. But there’s also Gemma, its little sister model.
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Search in Documentation with a JavaFX Chat LangChain4j Application
Let’s use an existing documentation set as the data for a ChatGPT-like application, created with JavaFX and LangChain4J.
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Book review: “Developing Apps with GPT-4 and ChatGPT”
Thorough, practical examples using a new & rapidly evolving tool. Pro or contra, it’s a very worthwhile read.
