Deployment/Setup of all ommr4all services
You can setup OMMR4all using docker
and docker-compose
.
- Download and install
docker-ce
anddocker-compose
for your platform. - Download the
docker-compose.yml
file. - Open
docker-compose.yml
and replace${STORAGE}
and the${PORT}
to your wishes (e.g., use/opt/ommr4all-storage
and8001
). - Build the container and bring it up:
docker-compose up -d
- Create a super user:
docker-compose run /opt/ommr4all/ommr4all-deploy-venv/bin/python /opt/ommr4all/ommr4all-deploy/modules/ommr4all-server/manage.py createsuperuser
docker-compose pull
docker-compuse up
You can run docker image prune -f
to clean all previous versions or older images that are currently unused.
Follow the instructions in the Dockerfile
.
You can also setup a gitlab-runner
for automatic deployment (Clone the project on github.com with CI-integration), create a runner with either
deployment-production
: redeploy if a new (version) tag was addeddeployment-master
: redeploy if the master is updated
These instructions are not complete yet.
- Download and install all requirements (node>=10, >=python3.6)
- Install the IDEs (IntelliJ, or PyCharm and WebStorm)
- Create a virtual environment, activate it, and install your desired tensorflow version (e.g.,
pip install tensorflow_gpu<2
) - Install all python submodules (located in the
modules
directure) but the server:python setup.py install
. - Install the server
requirements.txt
:pip install -r requirements.txt
. - Open the ommr4all-client directory in WebStorm and launch the
Angluar CLI Server
. - Open the ommr4all-sever directory in PyCharm and launch the
Django Server
. - In WebStorm launch the
Angular Application
which will open a browser.