Well, first, it was more for me.

I wanted to run all of my AI locally.

And I'm not just talking command line with Olama.

No, no, no.

We have a GUI, a beautiful chat interface.

And this thing's feature-filled.

It's got RBAC, chat histories, multiple models.

We can even add stable diffusion.

And I was able to add this to my notes application, Obsidian, and have my chat interface right there.

I'm gonna show you how to do this.

Now, you don't need something crazy like Terry.

That's what I named my AI server.

It can be something as simple as this, this laptop.

I'll actually demo the entire setup on this laptop.

So luckily, the computer you're using right now, the one you're watching this video on, will probably work.

And seriously, you're gonna love this.

It's customizable.

It's wicked fast, like way faster than anything else I've used.

Isn't that amazing?

And again, it's local.

It's private.

I control it, which is important because I'm giving it to my daughters.

I want them to be able to use AI to help with school, but I don't want them to cheat or do anything else weird.

But because I have control,

I can put in special model files that restrict what they can do, what they can ask.

And I'll show you how to do that.

So here we go.

We're about to dive in.

But first, let me have you meet Terry.

Now, Terry has a lot of muscle.

So for the case, I needed something big.

I got the Leon Lee 011 Dynamic Evo XL.

It's a full tower E-ATX case.

Perfect to hold my Asus X670-E Creator ProArt motherboard.

This thing's also a beast.

I'll put it in the description so you can look at it.

Now, I also gave Terry a big brain.

He's got the AMD Ryzen 9 7950X.

That's 4.2 gigahertz and 16 cores.

For memory, I went a little crazy.

I've got 128 gigabytes of the G.Skill Trident Z5 Neo.

It's DDR5-6000 and way overkill for what I'm doing.

I think.

I got a Leon Lee water cooler for the CPU.

I'm not sure if I'm saying Leon Lee right.

I don't know.

Correct me in the comments.

You always do.

And then for the stuff AI loves, I got two 4090s.

It's the MSI Supreme and they're liquid cooled so they could fit on my motherboard.

24 gigabytes of memory each, giving me plenty of muscle for my AI models.

For storage, we got two Samsung 990 Pros, two terabytes, which you can't see because they're behind stuff.

And also a Corsair AX1600i power supply.

1600 watts to power the entire build.

Terry is ready.

Now I'm surprised to say my system actually posted on the first attempt, which is amazing.

But what's not amazing is the fact that Ubuntu would not install.

I tried for hours, actually for a whole day.

And I almost gave up and installed Windows, but I said, no, Chuck, you're installing Linux.

So I tried something new, something I've never messed with before.

It's called Pop OS by System76.

This thing is awesome.

It worked the first time.

It even had a special image with NVIDIA drivers built in.

It just stinking worked.

So I sipped some coffee, didn't question the magic and moved on.

Now, if you do want to build something similar,

I've got all the links below.

But anyways, let's talk about how to build your very own local AI server.

First, what do you need?

Really, all you'll need is a computer.

That's it.

It can be any computer running Windows, Mac or Linux.

And if you have a GPU, you'll have a much better time.

Now, again, I have to emphasize this.

You won't need something as beefy as Terry, but the more powerful your computer is, the better time you'll have.

Don't come at me with a Chromebook, please.

Now, step one, Olama.

This is the foundation for all of our AI stuff and what we'll use to run AI models.

So we'll head on over to olama.ai and click on download.

And they get a flavor for every OS.

I love that.

Now, if you're on Mac, just download it right now and run it.

If you're on Windows, they do have a preview version, but I don't want you to do that.

Instead, I want you to try the Linux version.

We can install it with one command.

And yes, you can run Linux on Windows with WSL.

Let's get that going real quick.

First thing I'll do is go to the start bar and search for terminal.

I launched my terminal.

Now, this first bit is for Windows folks only,

Linux people, just hang on for a moment.

We got to get WSL installed or the Windows subsystem for Linux.

It's only one command, WSL dash dash install.

And that's it actually.

Hit enter, and it's gonna start doing some stuff.

When it's done, we'll set up a username and password.

I got a new keyboard, by the way.

Do you hear that?

Link below, it's my favorite keyboard in the entire world.

Now, some of you may have to reboot, that's fine.

Just pause the video and come back.

Mine is ready to go though, and we're rocking Ubuntu 22.04, which is still amazing to me that we're running Linux on Windows.

That's just magic, right?

Now, we're about to install Olama, but before we do that, you got to do some best practice stuff, like updating our packages.

So we'll do a sudo apt update, and then we'll do a sudo apt upgrade dash y to apply all those updates.

And actually, while it's updating, can I tell you something about our sponsor?

IT Pro by ACI Learning.

Now, in this video, we're gonna be doing lots of heavy Linux things.

I'm gonna walk you through it.

I'm gonna hold your hand, and you may not really understand what's happening.

That's where IT Pro comes in.

If you want to learn Linux or really anything in IT, they are your go-to.

That's what I use to learn new stuff.

So if you want to learn Linux to get better at this stuff, or you want to start making this whole hobby thing your career, actually learn some skills, get some certifications, get your A+, get your CCNA, get your AWS certifications, your Azure certifications, and go down this crazy IT path, which is incredible, and it's the whole reason I make this channel and make these videos.

Check out IT Pro.

They've got IT training that won't put you to sleep.

They have labs, they have practice exams, and if you use my code NetworkChuck right now, you'll get 30% off forever.

So go learn some Linux, and thank you to IT Pro for sponsoring this video and making things like this possible.

And speaking of, my updates are done.

And by the way, I will have a guide for this entire thing.

Every step, all the commands, you can find it at the free NetworkChuck Academy membership.

Click the link below to join and get some other cool stuff as well.

I can't wait to see you there.

Now we can install Olama with one command.

And again, all commands are below.

Just gonna paste this in.

A nice little curl command, little magic stuff, and this, I love how easy this is, watch.

You just sit there and let it happen.

Do you not feel like a wizard when you're installing stuff like this?

And the fact that you're installing AI right now, come on.

Now notice one thing real quick.

Olama did automatically find out that I have an NVIDIA GPU, and it's like, awesome, you're gonna have a great time.

If it didn't see that and you do have a GPU, you may have to install some NVIDIA CUDA drivers.

I'll put a link for that below, but not everyone will have to do that.

And if you're rocking a Mac with an M1 through M3 chip, you're gonna have a good time too.

They will use the embedded GPU.

Now at this point, our Mac users, our Linux users, and our Windows users are all converged.

We're on the same path.

Welcome, we can hold hands and sing.

It's getting weird.

Anyways, first we have to test a few things to make sure Olama is working.

And for that, we're gonna open our web browser.

I know, it's kind of weird.

Just stick with me.

I'm gonna launch Chrome here, and here in my address bar, I'm gonna type in localhost, which is looking right here at my computer, and port 11434.

Hit enter, and if you see this right here, this message, you're good to go, and you're about to find this out.

Port 11434 is what Olama's API service is running on, and it's how our other stuff is gonna interact with it.

It's so powerful, just check this out.

I'm so excited to show you this.

Now, before we move on, let's go ahead and add an AI model to Olama.

And we can do that right now with olama pull, and we'll pull down Lama 2, a very popular one.

Hit enter, and it's ready.

Now, let's test it out real quick.

We'll do olama run Lama 2.

And if this is your first time doing this, this is kind of magic.

We're about to interact with a chat GPT-like AI right here.

No internet required, it's all just happening in that five gigabyte file.

Tell me about the solar eclipse.

Boom, and you can actually control C that to stop it.

Now, I wanna show you this.

I'm gonna open up a new window.

This is actually an awesome command.

And with this WSL command,

I'm just connecting to the same instance again, a new window.

I'm gonna type in watch-n 0.5, not four, five, nvidia-smi.

This is going to watch the performance of my GPU right here in the terminal and keep refreshing.

So keep an eye on this right here as I chat with Lama 2.

Lama 2, give me a list of all Adam Sandler movies.

And look at that GPU go, ah, it's so fun.

Now, can I show you what Terry does real quick?

I gotta show you Terry.

Terry has two GPUs.

Here they are right here.

And olama can actually use both of them at the same time.

Check this out, it's so cool.

List all the Samuel L. Jackson movies.

And look at that.

Isn't that amazing?

And look how fast it went.

That's ridiculous.

This is just the beginning.

So anyways, I had to show you Terry.

So now we have olama installed.

That's just our base.

Remember, I'm gonna say bye.

So forward slash bye to end that session.

Step two is all about the web UI.

And this thing is amazing.

It's called OpenWebUI.

And it's actually one of many web UIs you can get for olama.

But I think OpenWebUI is the best.

Now OpenWebUI will be run inside a Docker container.

So you will need Docker installed.

And we'll do that right now.

So we'll just copy and paste the commands from Network Shrug Academy.

This is also available on Docker's website.

First step is updating our repositories and getting Docker's GPG key.

And then with one command, we'll install Docker and all its goodies.

Ready, set, go.

Yes, let's do it.

And now with Docker installed, we'll use it to deploy our OpenWebUI container.

There'll be one command.

You can simply copy and paste this.

This docker run command is going to pull this image to run this container from OpenWebUI.

It's looking at your local computer for the olama base URL, because it's going to integrate and use olama.

And it's going to be using the host network adapter to make things nice and easy.

Keeping in mind, this will use port 8080 on whatever system you're using.

Now all we have to do is hit enter after we add some sudo at the beginning, sudo docker run, and let it do its thing.

Let's verify it real quick.

We'll do a little sudo docker ps.

We can see that it is indeed running.

And now let's go log in.

It's kind of exciting.

Okay, let's go to our web browser and we'll simply type in localhost colon port 8080.