In this video, I will show you the quickest and easiest way to get started with the new n81 AI starter template. We will set up Windows Subsystem for Linux, we'll install a distribution of Ubuntu, we'll then install Docker Desktop and connect it to our Windows System for Linux. Next, we'll install VS Code and connect it to our Windows System for Linux. We will then clone the n810 AI starter template from GitHub. We use Docker Compose to deploy and run n810, meaning it will be accessible from my browser locally. This setup will allow you to run local AI models on your system and use them directly in n810. One of the main benefits of this setup is that you'll be able to utilize your system's GPU for local AI models if you have one. So let's get started. Okay, so the first thing we need to do to get n810 working on our system locally is install Windows Subsystem for Linux. So to do this, we will open a new terminal, simply press the Windows key, type in terminal, hit enter, and this will

open up our terminal window. Within our terminal window, we can type in this command, which is WSL D-install. This will install the Windows Subsystem for Linux. And then at this point, we're going to choose a distribution that we want them to store as well. So, distribution is a version of Linux that you want to run on the Windows Subsystem for Linux. In this case, we're choosing Ubuntu 24.4. So, we can hit enter, say yes to any prompts that arise, and this will install the Windows Subsystem for Linux Ubuntu. Okay, once we have successfully installed the Windows Subsystem for Linux with Ubuntu, we'll need to reboot our system. So, we'll do that now. Okay, so we have now rebooted our system, and the first thing it's going to do is ask you for a username. In this case, no code creative and a password. Then we can see our installation is successful, and we have successfully set up the Windows Subsystem for Linux with Ubuntu. Okay, so the next part of the process is to download and install Docker.

desktop. So, we'll come to Docker desktop.com and we will download for Windows. Once the download is complete, we open the file and then we'll go through the installation process. Ensure we have WSL2 turned on. Okay, now once the installation is complete, we will need to restart Windows, so we'll do that now. Okay, so we have now successfully restarted Windows, and we can see that Docker has opened up. If we just accept the service agreement, and then we can see the Docker engine will then start. Okay, Docker is now running. First thing that we'll want to do is make sure that Docker is connected to our Windows Subsystem for Linux. So, we'll click on the settings icon, we'll come down to resources, and WSL integration. If this isn't toggled on, do toggle it on, and then press apply and restart. Once that's done, open a new terminal, and at this stage, we can confirm that the Docker desktop is connected to our WSL2 system. And to do this, we can simply type in Docker, and it will give us all the

commands that are available, which verifies it's installed, and we can also type in Docker compose. We'll be using Docker compose to run N1, so let's confirm Docker compose is available, and it is great. So we have successfully set up our Windows subsystem for Linux. Okay, so the next part of the process is to come to code.visualstudio.com and download Visual Studio for Windows. There are multiple ways to interact with the Windows subsystem for Linux and to set up N1 and to use Docker compose. My preference is to use Visual Studio Code rather than doing it in a terminal, but of course, you are free to do this as you choose. But for this tutorial, we will use Visual Studio Code. So let's get it installed. So once we have installed and launched Visual Studio Code, the first thing that we want to do is come down to the Extensions tab, and we want to install our remote development tools, which will allow us to connect directly to the WSL system. So if you type in remote first.

option that should come up is remote development. Press install, and then we also want to install the Docker extension as well. Okay, now once this is done, if we come over to our remote explorer, from the drop-down up here, we can change it to WSL targets, and here we can see our rantu system, and then we can open the system M VS code. So we can now come over to explorer, open folder, and this will display the file structure for our ronto system. I'm going to open up the home folder, and then within the home folder, I'm going to create our file structure. So I'm going to create a parent folder, going to call it www, and then in here, I'm going to open the integrated terminal. Then the next step is to clone the GitHub repo for na1. So on this occasion, we're going to use the new na1 AI starter template. I will leave order commands in the description, but we want to type in git clone and then the URL of the repository in question, and then hit

enter and you can see we have the report cloned to our Linux system. We can come up here and go open an integrated terminal. Let's have a look. We can see what files are there. We can also see them here, and the reason I like to do this in VS Code is because we can easily navigate to files and edit them. So, in this case, we want to have a look at the Docker Compose file. I'm not going to go through Docker Compose in this video, but here you can see all the services that will be running when we pull and deploy this template. Okay, so the next thing we want to do is type in Docker Compose up -d. This will pull the images and everything that's in the Docker Compose file and start the services. We will then be able to access the interface by our local system. Okay, so we can see that all of the images have been successfully pulled, the containers have been created and started. If we head over to our Docker

extension um we can then see everything running here. Here, I have noticed this container has stopped, but it is an import container, so hopefully that won't make any difference to what we're trying to do. You can right-click on this and have a look at the composed logs, and it says the editor is now accessible, so everything appears to be up and running. We can copy this URL, or we can actually have a look at Docker desktop, and we can come to our containers, and you can see the stack that is running with the containers in it. You can have a look and can actually just click onto this link, and this should open up any 10. So, we now have successfully set up N1, and we are now in the n8n interface, so you're now ready to start experimenting and building automations with NM. Okay, so to find more about the na10 self-hosted AI starter kit, do head over to the na10 docs. Uh, I hope you've found this video useful. In this video, we have set up Windows Subsystem for Linux.

We've deployed a distribution of WEU. We've installed Docker desktop, and we've got everything working with VS Code. And we have set up any1 using Docker Compose, all on one short video. So, hope you found this useful. Do give the video a like and do subscribe for more similar content, where we will dive deeper into n8n in the near future.

Set Up the N8N AI Starter Kit with WSL, Docker, and VS Code: Complete Guide

Set Up the N8N AI Starter Kit with WSL, Docker, and VS Code: Complete Guide