FROM ubuntu:16.04

# Set a docker label to advertise multi-model support on the container
LABEL com.amazonaws.sagemaker.capabilities.multi-models=true
# Set a docker label to enable container to use SAGEMAKER_BIND_TO_PORT environment variable if present
LABEL com.amazonaws.sagemaker.capabilities.accept-bind-to-port=true

# Install necessary dependencies for MMS and SageMaker Inference Toolkit
RUN apt-get update && \
    apt-get -y install --no-install-recommends \
    build-essential \
    ca-certificates \
    openjdk-8-jdk-headless \
    curl 
    
RUN echo 'installing miniconda' && \
    curl -LO http://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh && \
    bash Miniconda3-latest-Linux-x86_64.sh -bfp /miniconda3 && \
    rm Miniconda3-latest-Linux-x86_64.sh

ENV PATH=/miniconda3/bin:${PATH}

RUN conda install python=3.6 && \
    conda update -y conda && \
    conda install -c conda-forge pyarrow=0.14.1 && \
    conda install -c mlio -c conda-forge mlio-py=0.1

# Install latest version of sklearn
RUN pip install --no-cache -I scikit-learn==0.20

# Install latest version of XGBoost
RUN pip install --no-cache -I xgboost==0.90

# Install latest version of Tensorflow
RUN pip install --no-cache -I tensorflow

# Install MMS, and SageMaker Inference Toolkit to set up MMS
RUN pip --no-cache-dir install multi-model-server \
                               sagemaker-inference \
                               retrying

# Copy entrypoint script to the image
COPY dockerd-entrypoint.py /usr/local/bin/dockerd-entrypoint.py
RUN chmod +x /usr/local/bin/dockerd-entrypoint.py

RUN mkdir -p /home/model-server/

# Copy the default custom service file to handle incoming data and inference requests
COPY model_handler.py /home/model-server/model_handler.py

# Define an entrypoint script for the docker image
ENTRYPOINT ["python", "/usr/local/bin/dockerd-entrypoint.py"]

# Define command to be passed to the entrypoint
CMD ["serve"]