1  # Build an image that can serve mlflow models.
 2  FROM python:${{ PYTHON_VERSION }}-slim
 3  
 4  RUN apt-get -y update && apt-get install -y --no-install-recommends nginx
 5  
 6  
 7  
 8  WORKDIR /opt/mlflow
 9  
10  # Install MLflow
11  RUN pip install ${{ MLFLOW_INSTALL }}
12  
13  # Copy model to image and install dependencies
14  COPY model_dir/model /opt/ml/model
15  RUN python -c "from mlflow.models import container as C; C._install_pyfunc_deps('/opt/ml/model', install_mlflow=False, enable_mlserver=False, env_manager='local');"
16  
17  ENV MLFLOW_DISABLE_ENV_CREATION=True
18  ENV ENABLE_MLSERVER=False
19  
20  # granting read/write access and conditional execution authority to all child directories
21  # and files to allow for deployment to AWS Sagemaker Serverless Endpoints
22  # (see https://docs.aws.amazon.com/sagemaker/latest/dg/serverless-endpoints.html)
23  RUN chmod o+rwX /opt/mlflow/
24  
25  # clean up apt cache to reduce image size
26  RUN rm -rf /var/lib/apt/lists/*
27  
28  ENTRYPOINT ["python", "-c", "from mlflow.models import container as C; C._serve('local')"]