Everything will be 200 OK :)

 Welcome back, and hope you having a wonderful day. Init's Part 6 of the series, we had a look at our first exciting chat application where we were finally able to get hands dirty and interact with the LLM that was running on our local machine. How exciting 😃was that to see it in action. In this part of the series we will be looking at an important concept of  "Observability" that will help us provide insight into token usage amongst other factors, so let's get into it.           Backend applications like the one we created previously require love from us engineers. This isn't the same type of love that was shared in Titanic by Leo and Kate, but more of a monitoring love that empowers us to know the state of our application from some fine grained metrics that is of interest to us so that we may have a behavioral sense of our running application. A typical example, in a Java application maybe wanting to know the amount of memory used in JVM (Java ...

      Welcome back and hope you having an absolutely marvelous day. I am so excited to finally get you coding your first very basic chat client application in Java using SpringAI. Don't worry, I promise this is not as scary as some of the Conjuring or Annabelle movies. In Part 4  and Part 5  of the series we had a brief look at the core composition of  a very important Java class "ChatClient", that is being offered by SpringAI, and some options at our disposal for working with LLM's, be it locally on your own machine or using third party providers. By the end of this one, we would connect it all together with mission to have our own chat client that we can interact with, and using this as the foundation for future articles as we embark like Bilbo Baggins on this adventurous journey. Let's get started Architecture     The architecture for our application for current and future posts (unless advised otherwise when we deal with Model Context Protocol...

       Welcome back, in Part 4  of this series we had a look at some of the options we can use to work with various foundation models. This varied from the ability of running the LLM's locally on our machine or using third party cloud providers or directly vendors themselves for which a developer API key would be required. This part of the series is an intermediary post that will discuss the framework and programming language that would form the basis for our upcoming series of articles as we play with it. It is vital we go through this before getting hands dirty, as it would all then start to make sense and where each element that we have learned fits in.      For our playground, we would be using Spring AI . Spring has continued to evolve and be adapted as the go to enterprise framework for wide variety of backend applications developed in the Java programming language. It offers us several benefits as we develop our applications, some of these ...