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. However, LLMs can be difficult to use, especially for developers who are not proficient in Python, the lingua franca for AI. So what about us Java developers? How can we make use of Generative AI?

This presentation will go through how to use LLMs in Java without the need for Python. We will use the PaLM API, provided by Google Cloud’s Vertex AI services, to perform a variety of tasks, such as searching through documentation, generating kids stories, summarizing content, extracting keywords or entities, and more. In our journey through demos, we’ll discover LangChain4J, a wonderful LLM orchetratore for Java developers that simplifies the implementation of advanced LLM use cases.

I had the chance to get this talk recorded at Devoxx Belgium:

And you can check the slides here: