Author: Marcus Hellberg
In my previous article, I showed how to use an LLM to make sentiment analysis, draft responses to customer feedback, and create a chat-with-documents experience that uses your content.
Introducing file-based routing in Vaadin 24.4: Simplify Hilla app creation
With the release of Vaadin 24.4, developers building Hilla applications now have access to a powerful new feature: file-based routing. This enhancement streamlines the process of adding new views and configuring view properties directly within your React components. In this blog post, we'll explore ...
Building AI-Powered Java Applications
In the past few months, I've spoken about building AI-powered Java apps at tens of events around the world. What I’ve seen is that Java developers are curious and eager to learn, but AI can seem like a big and daunting new area to get into. Most of us have demanding jobs that occupy our time, and ...
The New Vaadin Forum is Live!
We're happy to announce that the new Vaadin Forum is now live on vaadin.com/forum. The Vaadin Forum is a central place for you to get help, share information, and connect with other Vaadin Community members. Forum and chat in one place. The Vaadin Forum brings both forums and chat together in one ...
Announcing the new Vaadin Forum
tl;dr: In early March, we are launching a new Vaadin Forum for all community discussions. It will replace the Vaadin Discord server and the old Vaadin Forum. At Vaadin, our community is at the heart of everything we do. As an open source company, we rely on feedback, contributions, and ...
Deploying a Spring Boot app as a native GraalVM image with Docker
In this final part of the Building an AI chatbot in Java series, we will deploy the Spring Boot AI chatbot application we've built as a GraalVM native image. Requirements The instructions in the article assume you are working with the Hilla Spring Boot application we've built in the series, but the ...
Building a ChatGPT-based AI bot using Spring Boot, React, and Hilla
In this article, we'll build a custom AI chatbot application using Hilla, Spring Boot, React, OpenAI (ChatGPT), and Pinecone. The chatbot is designed to answer Vaadin Flow and Hilla development questions using up-to-date documentation as reference material. My earlier blog post details the concept. ...
Enhancing ChatGPT with Prompt Engineering and Token Counting in Java
This article is part three of the Building an AI chatbot in Java series, where we're building a custom AI chatbot application using Hilla, Spring Boot, React, OpenAI (ChatGPT), and Pinecone. The chatbot is designed to answer Vaadin Flow and Hilla development questions using up-to-date documentation ...
Integrating Pinecone Vector Database into a Spring Boot Application
Dive into the process of integrating the Pinecone Vector database with a Spring Boot application using Java in this second installment of the Building an AI chatbot in Java series. Prerequisites The article assumes you have a Spring Boot application. The example project is a Spring Boot application ...