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How to create a Docker image and a release/deployment package for your jac program

In this guide, we will walk through our recommended way of packaging up everything required to deploy your jac program in one package. The package should include:

  • A docker image for the jaseci server (w/ pre-trained AI models built-in if applicable)
  • A jsctl script to intialize your server
  • A README with instructions on how to use the docker image and jsctl script

Docker image

Select the right base image

Before building our custom docker image, we first need to select a base docker image. We provide a set of base docker images, hosted on docker hub.

  • jaseci/jaseci conatins only jaseci_core and jaseci_serv. It does not contain any modules from jaseci_ai_kit. So if your jac program does not require any modules from AI kit, you can use this base image.
  • jaseci/jac-* are the base images with jaseci_core, jaseci_serv and the corresponding AI kit package built-in.
    • jaseci/jac-nlp contains the natural language processing modules in the jac-nlp group of AI kit.
    • jaseci/jac-vision contains the computer vision modules in the jac-vision group
    • jaseci/jac-speech contains the speech modules in the jac-speech group.
    • jaseci/jac-misc contains the modules in the jac-misc group.

Check out docs for jaseci ai kit for a table of the modules included in each of the group. Select the base images that contain the modules your Jac application needs. A quick way to do that is to look at all the can statements in your jac code. In the case where your application needs modules from two or more groups, (e.g. use_enc from jac_nlp and cluster from jac_misc), we recommend you select the base image that covers the most of the modules you need and then install the other necessary modules in the Dockerfile shown below.

Create dockerfile for our custom image

Now that we have selected the right base image (we will use jaseci/jac-nlp for this guide), we will now create a custom dockerfile for our custom image.

Here is a template dockerfile to start with:

# Specify your base image
FROM jac-nlp:

# Set working directory. / is fine for most scenarios.

# Install any linux dependencies
RUN apt -y update; apt -y install --no-install-recommends CUSTOM_APT_PACKAGES_GO_HERE

# Install any additional jaseci_ai_kit modules that are not covered by the base image
RUN pip install jac_misc[cluster]

# Install any additional python dependencies

# Copy any pre-trained models required for the jac program.
COPY ./pretrained_bi_enc /pretrained_bi_enc

Save the docker file to a file and let's call it my_jac.Dockerfile.

For additional questions on the syntax in this dockerfile, refer to the Docker documentation.

Build the image

To build the image, run

docker build -t {IMAGE_NAME} -f my_jac.Dockerfile .

Note that there is a period . at the end of this command.

Also, replace {IMAGE_NAME} with what you want to name your docker image.

Test your image

Once the image is built, you can test it by using it to launch a running jaseci server.

docker run -p 8000:8000 {IMAGE_NAME} jsserv runserver

This will launch a new container using the image and running jsserv inside it. This also expose it at port 8000 on your local machine. Go to http://localhost:8000 and you should see something like this.

Share the image

After the build finishes, you can check the size of your docker image with

docker image ls

There are multiple ways to share a docker image. The most common and recommended way is through a docker image registry (e.g., dockerhub). You can also share the image directly as a file. Here is a short tutorial on how that.

JSCTL script

Deploying a jac program on a fresh Jaseci server requires a few setup steps. To facilities this, we recommend setting up a JSCTL script as a companion to the docker image.

A JSCTL script is simply a plain text file with a list of jsctl commands.

For example, the follow series of commands (or similar) are commonly needed to initialize a jac program.

jac build main.jac
login JASECI_URL ---username USERNAME --password PW
sentinel register -mode jir main.jir
actions load module jac_nlp.use_enc

Save this in a file and name it init_script. To use this script, run

jsctl script init_script


A should be packaged together with the docker image and the jsctl script.

This README should contain, at minimum, the following:

  • Manifest of the content of this package (the docker image, jsctl script, etc.)
  • Description of the docker image. For example, what it contains.
  • Instructions on using the docker image to deploy a jsserv server.
    • This part can vary depending on the desired deployment environment and approach (e.g. docker vs k8s vs cloud). What we should explain at the minimum, is that the docker image contains all the dependencies of Jaseci and AI models required for the application and the the following commands start a jsserv server
      jsserv makemigrations base
      jsserv makemigrations
      jsserv migrate
      jsserv runserver
    • Here is an example kubernetes manifest yaml file that can be shared as a reference if kuberentes deployment is desired.
  • Instructions on how to use the JSCTL script. The section above in this guide is sufficient in most cases.
  • Expected behavior of the application. What should a new user try to test if their deployment is successful? Example walker runs and expected response should be included.
  • Any additional information you would like to include about the application.