Empowering Nx with AI

Hi, everyone. I'm Katerina Skrimpelou, and I'm from NX. Today, we're going to talk about empowering NX with the help of AI. I'm a senior engineer at NX. I'm a Google developer expert for Angular and Google Maps. I'm also a Women Techmakers ambassador, a speaker and instructor, and I really, really love cats, mountains, oatmeal, and chocolate. You can follow me at cybercity or cyber.city.

So, AI, sure, but what? NX is already smart, no? Well, first, for those who don't know, let's see a brief intro to NX. By the way, this is my cat, Malone, and he loves his pineapple hat. So, what is NX? NX is a powerful build system with a rich set of tools, making it easier to manage and scale projects. It enhances developer productivity, optimizes CI performance, and maintains code quality. With NX, you get features like smart project graph analysis, advanced dependency management, and much more. Some of our most notable features are the NX Replay, which is our cache, our NX Agents, the NX Atomizer, which breaks your test suites into individual files, which is better for granular results and rerunning. We also have automatically flaking, which detects flaky tasks and reruns them automatically, and much, much more. And you can find all these at our NX Cloud solution. You can add NX right now to your project, yes, to your React projects, by running npx nx init.

So, where does AI come into play then? Well, we have, at the moment, three AI features that I'm going to talk about. The NX Docs AI Assistant, the NX AI Error Explainer for the logs that you can see on NX Cloud, and a draft solution, the Resource Allocation Optimization on NX Cloud. So, the NX Docs AI Assistant is designed to streamline the navigation and utilization of NX documentation. By leveraging AI, the Assistant provides users with accurate answers for the NX Docs, making it easier to find relevant information quickly. And the Assistant enhances user experience by allowing complex, context-aware queries and providing intelligent, coherent responses. Why use AI for Docs, though? As I said, there are some challenges that search and retrieval of Docs poses. The volume and density of documentation, you are limited by static keyword matching, and your users need personalized and contextual search that maybe Algolio or some other search engine cannot offer in that way. In such a way. Potential benefits for the user is a user can go beyond simple queries, as you already know, since we're all GPT users for almost one and a half years now. You get feedback loops, follow-up questions on things you've already asked. You can mix and combine different parts of the documentation into one. You can get your personalized blog post, if you want, right? You get enhanced user experience and expanded documentation retrieval. Because sometimes vector search is very efficient, right? Potential benefits for us, the authors, we can identify what users are looking for, like, what questions they need answered, and we can add more Docs accordingly. We can identify potentially unclear parts of documentation, if the AI consistently gives bad answers to similar questions.

And more parts of the documentation may become more accessible through the links and sources provided. How do we build it? The steps are simple. You create embeddings for each section of the documentation. You store the embeddings on a database. We're using Superbase. The user asks a question. We create an embedding for that question, and then we do vector matching to find Docs similar to the question. We get back the relevant Docs. We combine them with the query of the user and a prompt, and send to GPT, get back answers from GPT. The tools that we're using, OpenAI, GPT, Superbase, and Vercells AI SDK. The AI slash React package is very, very helpful and powerful in building such applications, because it provides functions, like, that can really help with the streaming response or access the APIs and the endpoints that you have. I totally recommend it, if you're not using it already, which I assume maybe you already are.