01 Install prerequisites - Red Hat AI Hackathon Java Code Generation
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Red Hat AI Combinator Hackathon entry
Smart Device API Code Generation with AI/ML hackathon
By Christopher Tate
Because reactive/asynchronous APIs are more efficient and scalable, but are much more complex to build by hand. We can use code generation to build extendable APIs consistently, faster, and more secure with AI/ML Code Generation based on the well established computate open source project. Increase Quarkus API and web developer productivity with OpenAPI Code Generation based on code comments. Easily deploy new edge device models and edge device models following open source FIWARE smart data model schemas with AI/ML predictive code generation.
Have you ever written an exciting piece of code, or automation, just to realize from somebody else that there's already an open source package available for that? That's how I felt when I first learned about Ansible automation, and how I had been wasting my time automating simple things that were already freely available to me. I want to set you up with the knowledge, and best tools available to easily deploy complex edge-to-cloud solutions like the Smart Village Platform. You can build your own solutions using the most up-to-date enterprise open source tools available, and I will show you how.
For the rest of the course material to run smooth, you will need to run this list of prerequisite commands the first time you run the course, and again if your course is shut down after being idle. The python environment and it's extra packages that are required are reset, when this workbench is shutdown and restarted. In case you are restarting the workbench, you should only need to run the second section Install prerequisite Ansible automation tools below.