We try to use MLflow Model Serving, this service will enable realtime model serving behind a REST API interface; it will launch a single-node cluster that will host our model.

The issue happens when the single-node cluster try to get the environment ready base on a conda.yaml file that created when log the model using MLflow. But it looks like I can only specify a pip install but not a Maven package.

conda_env = _mlflow_conda_env(

additional_conda_deps=None,

additional_pip_deps=["cloudpickle=={}".format(cloudpickle.version), "scikit-learn=={}".format(sklearn.version),"pyspark==3.0.0".format(pyspark.version))],

additional_conda_channels=None,

)

how can I tell the cluster to install a maven jar file?