I’ve just published a new issue of my Cloud Native Diary. I talk about my book "Cloud Native Spring in Action", Spring AI and the new LLM Observability features I worked on, and news from KCD Munich, CNCF TAG App Delivery, and KCD Denmark ☀️ www.thomasvitale.com/cloud-native...
Observability is available in Spring AI, enhancing LLMs and vector stores. News from KCD Munich and CNCF.
Ollama has recently added support for tools/function calling, and you can already use the new feature with Spring AI in your Java applications 🤩 I can run all my LLM apps on local, open-source, and private models like Mistral now! Full example here: github.com/ThomasVitale...
We launched a new App Development Working Group within the CNCF TAG App Delivery. Join us to help us bridge the gap between developers and cloud native technologies. www.cncf.io/blog/2024/07...
TAG post from TAG App Delivery Calling all developers! We’re excited to announce the launch of the new App Development Working Group within the TAG App Delivery. This group is dedicated to bridging…
In my journey of fighting buzzwords and finding "The One Buzzword To Rule Them All", I introduce my solution and apply it to Generative AI: "The WHY Factor". I explain some use cases for infusing AI in existing apps using Spring AI, with live coding and live music 🎹 www.youtube.com/watch?v=3zTf...
Spring I/O 2024 - 30-31 May, Barcelona Slides: https://speakerdeck.com/thomasvitale/concerto-for-java-and-ai-building-production-ready-llm-applications Repo: https://github.com/ThomasVitale/concerto-for-java-and-ai Spring AI Examples: https://github.com/ThomasVitale/llm-apps-java-spring-ai Imagine you’re a music composer struggling to find inspiration for a pivotal movie scene. Then, you remember you’re also a software engineer, and the solution becomes suddenly obvious. Join me in this session, where I’ll demonstrate how I enhanced my music composition process by harnessing the power of Spring Boot and AI. This presentation will discuss the core architectural patterns for introducing AI capabilities into an existing software system, exploring concepts like templated prompts, agent tools, and integration of external knowledge. The Java ecosystem is getting more and more capabilities for building AI applications. But are they ready for production? Are there any gaps? Throughout the session, I’ll build a “composer assistant” application using Spring Boot and an AI Orchestrator (LangChain4J, Spring AI) to showcase how to make an LLM application production-ready. Is the developer experience affected when working locally with language models? How is observability different when it comes to tokens? Can we ensure resilience across the many integrations orchestrated by the AI? What strategies are available for deploying LLM applications? In a final twist, you’ll choose which movie scene to score, and I’ll compose and perform the music live for it, supported by AI. Will it meet the mark? There’s only one way to find out: join me in exploring the practical side of AI applications, where Java and Generative AI offer tangible solutions to real-world use cases. Aaaaand action!
A new episode of "A Bootiful Podcast" is out, recorded live at Spring I/O 🍃 I enjoyed a lot talking with my friend @starbuxman.joshlong.comspring.io/blog/2024/06...#Java#SpringBoot#SpringAI#CloudNative
Level up your Java code and explore what Spring can do for you.
Maybe in the future :)
I've just published an article on how to build a text classification system using Java, Spring AI, LLMs, Ollama, and Testcontainers. More advanced techniques will follow. Stay tuned! www.thomasvitale.com/text-classif...
This article will explain the main aspects of a text classification system and describe how to implement it with Java and Spring AI while leveraging the power of large language models (LLMs).
What a nice surprise 🤩 I've just found out that the Korean translation of my book "Cloud Native Spring in Action" is out 🎉 I'm so glad that my book can reach an even wider audience, being available now in English, Chinese, and Korean!
