ByThorben JanssenMost Java developers encounter problems when learning how to integrate AI into their applications using SpringAI, Langchain4J, or some other library. AI introduces many new terms, acronyms, and techniques you must understand to build a good system. I ran into the same issue when I started learning about AI. In this article, I did my…
ByThorben JanssenRepositories are a commonly used pattern for persistence layers. They abstract from the underlying data store or persistence framework and hide the technical details from your business code. Using Jakarta Data, you can easily define such a repository as an interface, and you’ll get an implementation of it based on Jakarta Persistence or Jakarta NoSQL….
ByThorben JanssenJakarta Data standardizes stateless repositories based on Jakarta Persistence and Jakarta NoSQL so that you can concentrate on your business code instead of handling the technical details of simple queries. In this article, I will briefly introduce the new specification and give you an overview of its stateless repositories. In future articles, we will dive…
ByThorben JanssenDuring my Spring Data JPA workshops and talks, I often get asked if a test case should handle transactions, or not. And if it handles the transaction if it should commit it or roll it back. And as so often, the short answer is: it depends. The slightly longer answer is: it depends on the…
ByThorben JanssenWhen integrating AI into your application, you will most likely want to use a concept called RAG. This acronym stands for Retrieval Augmented Generation and is an absolute game changer. The idea is simple: By providing your own input data to your LLM, you can improve the quality of its response and let it include…