A service model runs alongside other models. Typically this can be a database which stores information as a workflow progresses. This example contains two models the service and a model which communicates with it, which we have called the client.
Each model contains:
- a Dockerfile - Builds the model container that will be run by DAFNI
- a model_definition.yaml_ - A machine-readable file used to define the model.
The service's model_definition.yaml file adds type: service to the meta section which defines it as a service, the other option is "model" which is also the default if not specifically added.
The service model simply starts and runs with an infinite loop, but also outputs the current second. The client model runs a ping command to show it is connecting to the service model.
The client model expects the service IP to be passed in to the parameter called MY_SERVICE_IP. When both of these models are added to a Workflow, the step name of the service can be added to the client parameter.
You can build the service model and test is with:
docker build -t service-example .
docker run service-exampleYou can build the client model and test it by also passing in an example IP:
docker build -t client-example .
docker run -e MY_SERVICE_IP=127.0.0.1 client-exampleYou will need to create a file from your docker image to upload it into DAFNI. Check out the detailed instructions online at Docs but the basic instructions are as follows:
docker save -o client-example.tar client-example
docker save -o service-example.tar service-exampleIf you wish you can also compress these file before uploading. This is not essential but for large images it will save you some time when uploading.
gzip client-example.tar
gzip service-example.tarThis will produce files called client-example.tar.gz and service-example.tar.gz
Once in DAFNI you can then upload each of these models by selecting the tar or tar.gz file and their associated mode_definition.yaml files on the "Add Model" page.