Building a Custom ML Service Image
In order to use Python libraries that are not included in the default ML service image, you will need to build a custom image that includes commands to install these additional libraries.
Docker installed in a local build machine
Docker Hub account with read access to official Lucidworks Fusion images
Write access to a Docker registry to publish your custom image
How to create a custom ML service image
Dockerfilebased on this template:
FROM lucidworks/ml-python-image:5.0.3-1 USER root \# Add any additional commands here, i.e. pip install gensim USER 8764
Log into Docker Hub with your credentials:
Build the image:
docker build -t my-org/ml-python-image .
Publish the image to Docker Hub or your internal Docker registry.