❯ Guillaume Laforge

Java

URL slug or how to remove accents from strings in Java

In this article, we’ll figure out how to create slugs. Not the slobbery kind of little gastropods that crawls on the ground. Instead, we’ll see how to create the short hyphened text you can see in the URL of your web browser, and that is often a URL-friendly variation of the title of the article. Interestingly, one of the most popular posts on my blog is an almost 20 year old article that explains how to remove accents from a string. Read more...

Gemini Function Calling

A promising feature of the Gemini large language model released recently by Google DeepMind, is the support for function calls. It’s a way to supplement the model, by letting it know an external functions or APIs can be called. So you’re not limited by the knowledge cut-off of the model: instead, in the flow of the conversation with the model, you can pass a list of functions the model will know are available to get the information it needs, to complete the generation of its answer. Read more...

Hands on Codelabs to dabble with Large Language Models in Java

Hot on the heels of the release of Gemini, I’d like to share a couple of resources I created to get your hands on large language models, using LangChain4J, and the PaLM 2 model. Later on, I’ll also share with you articles and codelabs that take advantage of Gemini, of course. The PaLM 2 model supports 2 modes: text generation, and chat. In the 2 codelabs, you’ll need to have created an account on Google Cloud, and created a project. Read more...

Get Started with Gemini in Java

Google announced today the availability of Gemini, its latest and more powerful Large Language Model. Gemini is multimodal, which means it’s able to consume not only text, but also images or videos. I had the pleasure of working on the Java samples and help with the Java SDK, with wonderful engineer colleagues, and I’d like to share some examples of what you can do with Gemini, using Java! First of all, you’ll need to have an account on Google Cloud and created a project. Read more...

Generative AI in practice: Concrete LLM use cases in Java, with the PaLM API

Large Language Models, available through easy to use APIs, bring powerful machine learning tools in the hands of developers. Although Python is usually seen as the lingua franca of everything ML, with LLM APIs and LLM orchestration frameworks, complex tasks become easier to implement for enterprise developers. Abstract Large language models (LLMs) are a powerful new technology that can be used for a variety of tasks, including generating text, translating languages, and writing different kinds of creative content. Read more...

Tech Watch #5 — November, 15, 2023

Some friends shared this article from Uwe Friedrichsen, tilted back to the future, that talks about this feeling of “déjà-vu”, this impression that in IT we keep on reinventing the wheel. With references to mainframes, Uwe compared CICS to Lambda function scheduling, JCL to step functions, mainframe software development environments to the trendy platform engineering. There are two things I like about this article. First of all, it rings a bell with me, as we’ve seen the pendulum swing as we keep reinventing some patterns or rediscovering certain best practices, sometimes favoring an approach one day, and coming back to another approach the next day. Read more...

Tech Watch #3 — October, 20, 2023

Stop Using char in Java. And Code Points It’s a can of worms, when you start messing with chars, code points, and you’re likely going to get it wrong in the end. As much as possible, stay away from chars and code points, and instead, use as much as possible the String methods like indexOf() / substring(), and some regex when you really need to find grapheme clusters. Paul King shared his presentations on Why use Groovy in 2023 and an update on the Groovy 5 roadmapIt’s interesting to see how and where Groovy goes beyond what is offered by Java, sometimes thanks to its dynamic nature, sometimes because of its compile-time transformation capabilities. Read more...

Client-side consumption of a rate-limited API in Java

In the literature, you’ll easily find information on how to rate-limit your API. I even talked about Web API rate limitation years ago at a conference, covering the usage of HTTP headers like X-RateLimit-*. Rate limiting is important to help your service cope with too much load, or also to implement a tiered pricing scheme (the more you pay, the more requests you’re allowed to make in a certain amount of time). Read more...

Discovering LangChain4J, the Generative AI orchestration library for Java developers

As I started my journey with Generative AI and Large Language Models, I’ve been overwhelmed with the omnipresence of Python. Tons of resources are available with Python front and center. However, I’m a Java developer (with a penchant for Apache Groovy, of course). So what is there for me to create cool new Generative AI projects? When I built my first experiment with the PaLM API, using the integration within the Google Cloud’s Vertex AI offering, I called the available REST API, from my Micronaut application. Read more...

Creating kids stories with Generative AI

Last week, I wrote about how to get started with the PaLM API in the Java ecosystem, and particularly, how to overcome the lack of Java client libraries (at least for now) for the PaLM API, and how to properly authenticate. However, what I didn’t explain was what I was building! Let’s fix that today, by telling you a story, a kid story! Yes, I was using the trendy Generative AI approach to generate bedtime stories for kids. Read more...