Deploy a text-to-image web app with just one command
What is this about?
Stable Diffusion (SD) has quickly become one of the most popular text-to-image (a.k.a. “AI Art Generation”) models in 2022. One key factor contributing to its success is that it has been made available as open-source software. This spawned a vibrant community that quickly built tools to make SD more accessible to anyone interested in it, regardless of their technical knowledge.
One of those tools is the simple yet powerful web interface template to set up all the infrastructure required.
As always you will find the installed on your local machine makes things even easier, but I will also demonstrate how to follow the tutorial without it and just using the AWS console instead.
Quickstart Guide
As mentioned in the intro we will be using a CloudFormation (CF) template to set everything up with just one comand. After launching the template it will take 15–20 minutes until the app is ready, so here is my tip: Launch the template right now and then come back to this blog post to dive deeper into what is actually happening in the background 😉
Launching the app in AWS CLI
Copy the ) and run the command below on your local machine. This will create a CF stack called “sd-webui-stack” in your AWS account.
This template sets up a few resources that are required for the application. First we create a “Security Group” to specify which ports will be open on the EC2 instance. We choose port 22 because we want to be able to connect to the instance via SSH and port 7860 because that’s where our app will be listening.
Next we set up the EC2 instance that will host the application. In this template I chose a Ubuntu Server 22.04 LTS distribution (AMI ID ami-0574da719dca65348), simply because that’s what I’m most familiar with. You can change this to a different distribution if you’d like, but note that you would have to amend the setup script (discussed below) accordingly. We choose a g4dn.xlarge instance, as discussed above. We also provision 300 GB of disk space to make sure that we have enough space to host a number of different models. Finally we run the setup script on the EC2 instance, which we will discuss in the next section.
Next we create an Elastic IP address and assign it to our EC2 instance. This allows us to have a permanent IP address, so even when we shut down the EC2 instance and restart it at a later point our app will always be hosted on the same IP address.
The setup script
As mentioned, we are running a
This next section downloads and installs the CUDA driver so that we can access the GPU of the machine:
because we will download a Stable Diffusion model which is about 5 GB:Note that you can change the script to download a differenct version of Stable Diffusion, for example version 1.5. You can also add as many models you want into the UI at a later point by putting them into the odel directory.
In addition to the model we also need a configuration file that is read by the WebUI. We download a config file from the
Lastly, we change the ownership of the WebUI to the user ubuntu and kick off the the server as that user (because user root is not allowed to start the application):
We can also retrieve it by accessing the EC2 panel in the AWS console:
Once we have retrieved the IP address we can open the app by navigating in the browser to <IP address>:7860 (if the request times out the installation hasn’t finished yet). Once the installation is completed we can see that the app is up and running 🎉
Shutting down the EC2 instance and restart the app
Even with only $0.53 per hour we obviously don’t want to run the instance when we don’t use it. We can stop the instance in the AWS console and restart it when we need it again without losing any of the installed apps. Once we restarted the EC2 instance we can log into it via SSH and restart the app with the following command:
Limitations
I would like to stress that this tutorial is a mere starting point for anyone who wants to try out using Stable Diffusion via a Web UI. There are several limitations in this approach which could be addressed if one wants to use this app in production. In particular I did not address any security concerns (note that the app is running over http), scaling concerns (if this app is supposed to serve many users at the same time), and many other aspects.
If we wanted to use this app in production we could use the . Any contributions to the repo are more than welcome ☺️
Heiko Hotz
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