A recent post on Hacker News highlighted the benefits of detailed commit messages in git.

Usually, my git commits look something like this:

> git commit -m "fix: component missing configuration file"


…which isn’t all that helpful. (Related: see XKCD on git commit messages)

I decided to try and utilize this newfound knowledge in my own git commits and I quickly ran into an obstacle. Simply using > git commit opens up vim. Which, I really don’t want to use. (I’m sorry!)

This is something I should already know how to do, but I had to do a Google search to learn more. It turns out, you can change the default editor in git. This makes it much more convenient! How do you do it?

git config --global core.editor "nano"

Replace “nano” with your preferred editor of choice. Now, running > git commit opens up your editor and you can make detailed commit messages to your heart’s content!

My Mastodon landscape painting bot, Mr. RossBot keeps kicking along, generating some fun landscape art. It’s been powered by the AI Horde (the open source project behind ArtBot) and has tried to utilize whatever image models provided by the API to the best of its abilities.

For the most part, the code behind it is a bunch of spaghetti that looks like this:

An update to the AI Horde late last year added support for SDXL. However, the SDXL model on the Horde did not use a refiner. Because of this, images tended to come out a bit soft and lacked texture.

You can see examples of this in my announcement post about Mr. RossBot being back, here. See also:

More recently, the Horde added support for a new image model: AlbedoBaseXL. It’s an SDXL model that has a refiner baked in. Now images will come out a lot sharper looking.

Coincidentally, I was also playing around with various prompts and discovered I could get much better image results that look more painterly (rather than simple digital renderings) by utilizing the following prompt:

A beautiful oil painting of [LITERALLY_ANYTHING], with thick messy brush strokes.

And that is it! No more messy appending various junk to the end of the prompt to attempt to get what I want. The results speak for themselves and are pretty awesome, I think!

Various Stable Diffusion models massively benefit from verbose prompt descriptions that contain a variety of additional descriptors. Much recent research has gone into training text generation models for expanding existing Stable Diffusion prompts with relevant and context appropriate descriptors.

Since it isn’t feasible to run LLMs and text generation models inside most users’ web browsers at this time, I present my “Poor Man’s Prompt Expansion Model“. It uses a number of examples I’ve acquired from Fooocus and Hugging Face to generate completely random (and absolutely not context appropriate) prompt expansions.

(For those interested in following along at home, you can checkout the gist for this script on GitHub).

How does it work?

We iterate through a list of an absolute crap ton of prompt descriptors that I’ve sourced from other (smarter) systems that tokenize user prompts and attempt to come up with context appropriate responses. We’re not going to do that, because we’re going to go into full chaos mode:

1. Iterate through a list of source material and split up everything separated by a comma.
2. Add the resulting list to a new 1-dimensional array.
3. Now, build a new descriptive prompt by looping through the list until we get a random string of descriptors that are between 175 and 220 characters long.
4. Once that’s done, return the result to the user.
5. Create a new prompt.

For our experiment, we’re going to lock all image generation parameters and seed, so we theoretically get the same image given the exact same parameters.

Ready?

Here is our base prompt and the result:

Happy penguins having a beer

Not bad! Now, let’s go full chaos mode with a new prompt using the above rules and check out the result:

Happy penguins having a beer, silent, 4K UHD image, 8k, professional photography, clouds, gold, dramatic light, cinematic lighting, creative, pretty, artstation, award winning, pure, trending on artstation, airbrush, cgsociety, glowing

That’s fun! (I’m not sure what the “silent” descriptor means, but hey!) Let’s try another:

Happy penguins having a beer, 8k, redshift, illuminated, clear, elegant, creative, black and white, masterpiece, great power, pinterest, photorealistic, award winning, vray, enchanted, complex, excellent composition, beautiful composition

I think we just created an advertisement for a new type of beverage! It nailed the “black and white”, though I’m not sure how that penguin turned into a bottle. What else can we make?

Happy penguins having a beer, volumetric lighting, Digital, intricate, awesome, futuristic, cartoon artstyle, vector, solid, detailed, dramatic light, realistic photograph, wonderful colors, dramatic atmosphere

The dude in the middle is planning on having a good night. Definitely some “wonderful colors”. Not so much realistic photo or vector, but fun! One last try:

Happy penguins having a beer, 35mm, surreal, amazing, Trending on Artstation HQ, matte painting hyperrealistic, full focus, very inspirational, pixta.jp, aesthetic, 8k, black and white, reflected on the matrix studio background, awesome

As you can see, you can get a wide variety of image styles by simply mixing a bunch of descriptive elements to an image prompt.

I’ve wanted to implement a feature like this on ArtBot for a long time. (Essentially, if the user allows it, automatically append these descriptions behind the scenes when an image is requested). Perhaps this will come soon.

I recently got access to DALL-E 3 through OpenAI’s ChatGPT+ interface. One of the key features and improvements in their image model is the ability to generate coherent text within the image.

Let’s give it a try, based on one of the most popular StackOverflow questions: How do I exit Vim?

Using the following prompt: Oil painting of a hacker furiously typing commands into an old computer and muttering to himself, “how does one exit vim?”

That… is pretty good!

Alrighty, I updated the logic this weekend and have Mr. RossBot operating on the hairy elephant website (Mastodon). (It’s also posting on Threads, if you’re into that sort of thing.)

I also updated the image model to use Stability.ai’s swanky new SDXL model. I’m pretty impressed with the results.

Alright, this is pretty awesome! 🎉

Last night at 11:27PM, my little generative AI side project, ArtBot, crossed 10,000,000 images created. People have created some pretty cool stuff.

Some random stats from Google Analytics since it launched on October 9th, 2022 to now:

• 71,000 unique users
• 8.3 million page views.

My Steam Deck has to be one of my favorite gadgets in the last few years. Gaming aside, the fact that it’s running Linux opens up all sorts of interesting possibilities.

For example, let’s use it to add a new feature to ArtBot… while I’m on an airplane. The screen is tiny, but oh man, it actually worked.

Using a customized prompt, you can (for now, at least), get ChatGPT to misbehave a bit.

For example, I turned it into an angry programmer.

Thanks to Reddit, I recently stumbled upon a cool project called Stable Horde. It essentially lets you generate images using a distributed cluster of GPUs donated by community members.

I had been creating my own web interface to remotely interact with a Stable Diffusion instance running on my own machine. I decided to quickly repurpose the web app and connect to the Stable Horde API. The result?

ArtBot, a Stable Diffusion demonstration that allows you to generate images using the power of the Stable Horde. It is awesome!