Install and Run

• From Release File (Windows)
• From Github
  • Run the server
  • Notes
• From PyPI installation
• From Docker image
  • Compose example

General info

NOTE!!: Since version v0.6, python (or at least) pip needs to be installed on the system. (See https://www.python.org/downloads/)

NOTE!!: Use python 3.10 or 3.11 (Currently 3.12 is incompatible due to the version of numpy used)

Most of the server behavior the behavior of the server (eg: model/plugin/db install locations and allowed hosts) can be customized using Environment variables

SuperUser

Following the described procedures, the server will be created with a admin user admin:password.

The username and password can be changed by setting the environment variables DJANGO_SUPERUSER_USERNAME and DJANGO_SUPERUSER_PASSWORD respectively. (See Environment variables)

You can login to the admin interface at http://SERVER_ADDRESS:SERVER_PORT/admin/ (eg: http://127.0.0.1:4000/admin/) in order to manage the database. The main idea is to use this to manually add new models (with the appropriate entrypoint) if you want to test out, model that are not yet available. (If you find good models, please do share).

GPU

By default the run_server.py will attempt to use a specific device following:

• If the environment variable DEVICE is set, it will use the device specified by the value.

• If nvidia-smi is available the server will try running in GPU mode.

• If none of the above is available, the server will run in CPU mode.

Independent of the configured specified/found DEVICE, if torch is already installed it will be used to determine if it can run with CUDA.

As of v0.6 no device specific dependencies are included by default, but some plugins will install/use different dependencies based on the device used.