This is not in use anymore. It was made because A1111 refused to make an API in his popular SD implementation. In the meantime he changed his mind and so I switched over official A1111.

Stable Diffusion API

A headless server with REST API for Stable Diffusion and for Krita or Photoshop Plugins.

Installing and running

You need python and git installed to run this, and an NVidia videocard.

I tested the installation to work Windows with Python 3.8.10, and with Python 3.10.6. You may be able to have success with different versions.

You need model.ckpt, Stable Diffusion model checkpoint, a big file containing the neural network weights. You can obtain it from the following places:

official download
file storage
magnet:?xt=urn:btih:3a4a612d75ed088ea542acac52f9f45987488d1c&dn=sd-v1-4.ckpt&tr=udp%3a%2f%2ftracker.openbittorrent.com%3a6969%2fannounce&tr=udp%3a%2f%2ftracker.opentrackr.org%3a1337

You optionally can use GPFGAN to improve faces, then you'll need to download the model from here.

Automatic installation/launch

install Python 3.10.6 Best would be to activate global path checkbox in first dialog.
install git
install CUDA 11.3
place model.ckpt into webui directory, next to api.bat.
(optional) place GFPGANv1.3.pth into webui directory, next to api.bat.
run webui.bat from Windows Explorer.

Troublehooting:

According to reports, intallation currently does not work in a directory with spaces in filenames.
if your version of Python is not in PATH (or if another version is), edit api.bat, change the line set PYTHON=python to say the full path to your python executable: set PYTHON=B:\soft\Python310\python.exe. You can do this for python, but not for git.
if you get out of memory errors and your videocard has low amount of VRAM (4GB), edit webui.bat, change line 5 to from set COMMANDLINE_ARGS= to set COMMANDLINE_ARGS=--medvram (see below for other possible options)
installer creates python virtual environment, so none of installed modules will affect your system installation of python if you had one prior to installing this.
to prevent the creation of virtual environment and use your system python, edit api.bat replacing set VENV_DIR=venv with set VENV_DIR=.
api.bat installs requirements from files requirements_versions.txt, which lists versions for modules specifically compatible with Python 3.10.6. If you choose to install for a different version of python, editing api.bat to have set REQS_FILE=requirements.txt instead of set REQS_FILE=requirements_versions.txt may help (but I still reccomend you to just use the recommended version of python).
if you feel you broke something and want to reinstall from scratch, delete directories: venv, repositories.

Manual instructions

Alternatively, if you don't want to run api.bat, here are instructions for installing everything by hand:

:: crate a directory somewhere for stable diffusion and open cmd in it;
:: make sure you are in the right directory; the command must output the directory you chose
echo %cd%

:: install torch with CUDA support. See https://pytorch.org/get-started/locally/ for more instructions if this fails.
pip install torch --extra-index-url https://download.pytorch.org/whl/cu113

:: check if torch supports GPU; this must output "True". You need CUDA 11. installed for this. You might be able to use
:: a different version, but this is what I tested.
python -c "import torch; print(torch.cuda.is_available())"

:: clone Stable Diffusion repositories
git clone https://github.com/CompVis/stable-diffusion.git
git clone https://github.com/CompVis/taming-transformers

:: install requirements of Stable Diffusion
pip install transformers==4.19.2 diffusers invisible-watermark

:: install k-diffusion
pip install git+https://github.com/crowsonkb/k-diffusion.git

:: (optional) install GFPGAN to fix faces
pip install git+https://github.com/TencentARC/GFPGAN.git

:: go into stable diffusion's repo directory
cd stable-diffusion

:: clone web ui (API version)
git clone https://github.com/imperator-maximus/stable-diffusion-webui

:: install requirements of web ui
pip install -r stable-diffusion-webui/requirements.txt

:: update numpy to latest version
pip install -U numpy

:: (outside of command line) put stable diffusion model into models/ldm/stable-diffusion-v1/model.ckpt; you'll have
:: to create one missing directory;
:: the command below must output something like: 1 File(s) 4,265,380,512 bytes
dir models\ldm\stable-diffusion-v1\model.ckpt

:: (outside of command line) put the GFPGAN model into same directory as webui script
:: the command below must output something like: 1 File(s) 348,632,874 bytes
dir stable-diffusion-webui\GFPGANv1.3.pth

After that the installation is finished.

Run the command to start api:

python stable-diffusion-webui/api.py

If you have a 4GB video card, run the command with either --lowvram or --medvram argument:

python stable-diffusion-webui/api.py --medvram

After a while, you will get a message like this:

Running on local URL:  http://127.0.0.1:7860/

Put URL in Krita or Photoshop Plugin Config - that is all. WebUI also runs on same URL in browser.


If there is an issue - test URl in browser. You can  also see  API version at http://127.0.0.1:5000/api/version


### What options to use for low VRAM videocardsd?
- If you have 4GB VRAM and want to make 512x512 (or maybe up to 640x640) images, use `--medvram`.
- If you have 4GB VRAM and want to make 512x512 images, but you get an out of memory error with `--medvram`, use `--lowvram --always-batch-cond-uncond` instead.
- If you have 4GB VRAM and want to make images larger than you can with `--medvram`, use `--lowvram`.
- If you have more VRAM and want to make larger images than you can usually make, use `--medvram`. You can use `--lowvram`
also but the effect will likely be barely noticeable.
- Otherwise, do not use any of those.

Extra: if you get a green screen instead of generated pictures, you have a card that doesn't support half
precision floating point numbers. You must use `--precision full --no-half` in addition to other flags,
and the model will take much more space in VRAM.