Practical Python AI on the JVM with GraalPy and Pyronaut

Projects such as LangChain4j, Spring AI, and llama3.java have generated significant interest in AI within the Java community. At the same time, Python offers a broad ecosystem of packages for AI, machine learning, data science, and more.

Imagine the possibilities if you could use Python libraries for natural language processing, model inference, data preparation, and visualization alongside Micronaut and Java libraries in a JVM application. This session explores two ways to use Python on the JVM.

First, we’ll embed Python in a Java application with GraalPy: add the runtime, install and bundle Python packages, and call Python code from Java. We’ll look at using Python capabilities in a Micronaut application.

Then we’ll introduce Pyronaut, a high-performance Python framework built on GraalPy and Micronaut. This gives teams another option when they want to write applications in Python while using Micronaut capabilities such as HTTP handling, dependency injection, configuration, validation, and testing.