Dockerfile

# Dockerfile may have following Arguments:
# tag - tag for the Base image, (e.g. 2.9.1 for tensorflow)
# branch - user repository branch to clone, i.e. test (default: main)
#
# To build the image:
# $ docker build -t <dockerhub_user>/<dockerhub_repo> --build-arg arg=value .
# or using default args:
# $ docker build -t <dockerhub_user>/<dockerhub_repo> .
#
# Be Aware! For the Jenkins CI/CD pipeline, 
# input args are defined inside the JenkinsConstants.groovy, not here!

ARG tag=2.3.1-cuda11.8-cudnn8-runtime

# Base image, e.g. tensorflow/tensorflow:2.x.x-gpu
FROM pytorch/pytorch:${tag}

LABEL maintainer='Fahimeh Alibabaei '
LABEL version='0.0.1'
# Support for inference of the AI4LIFE model on the marketplace.

# What user branch to clone [!]
ARG branch=main

# Install Ubuntu packages
# - gcc is needed in Pytorch images because deepaas installation might break otherwise (see docs)
#   (it is already installed in tensorflow images)
# Install packages
RUN DEBIAN_FRONTEND=noninteractive apt-get update && \
    apt-get install -y --no-install-recommends \
    gcc \
    git \
    curl \
    && rm -rf /var/lib/apt/lists/*

# Update python packages
# [!] Remember: DEEP API V2 only works with python>=3.6
RUN python3 --version && \
    pip3 install --no-cache-dir --upgrade pip setuptools wheel

# Set LANG environment
ENV LANG=C.UTF-8

# Set the working directory
WORKDIR /srv

# Disable FLAAT authentication by default
ENV DISABLE_AUTHENTICATION_AND_ASSUME_AUTHENTICATED_USER=yes

# Initialization scripts
# deep-start can install JupyterLab or VSCode if requested
RUN git clone https://github.com/ai4os/deep-start /srv/.deep-start && \
    ln -s /srv/.deep-start/deep-start.sh /usr/local/bin/deep-start

# Necessary for the Jupyter Lab terminal
ENV SHELL=/bin/bash

# Install Data Version Control
RUN pip3 install --no-cache-dir dvc dvc-webdav

# Install rclone (needed if syncing with NextCloud for training; otherwise remove)
RUN curl -O https://downloads.rclone.org/rclone-current-linux-amd64.deb && \
    dpkg -i rclone-current-linux-amd64.deb && \
    apt install -f && \
    mkdir /srv/.rclone/ && \
    touch /srv/.rclone/rclone.conf && \
    rm rclone-current-linux-amd64.deb && \
    rm -rf /var/lib/apt/lists/*
ENV RCLONE_CONFIG=/srv/.rclone/rclone.conf

#TODO: use this variable to load the model in warm
ENV MODEL_NAME="affectionate-cow"
 
# Install user app #--no-cache-dir
RUN git clone -b $branch --depth 1 https://github.com/ai4os/ai4os-ai4life-loader.git && \
    cd ai4os-ai4life-loader && \
    pip3 install --no-cache-dir  -e . && \
   #curl -o ./models/all_versions.json https://uk1s3.embassy.ebi.ac.uk/public-datasets/bioimage.io/all_versions.json && \
    curl -o ./models/collection.json https://uk1s3.embassy.ebi.ac.uk/public-datasets/bioimage.io/collection.json  

    # Conditional cloning using shell commands
RUN if [ "$MODEL_NAME" = "affectionate-cow" ]; then \
    pip3 install git+https://github.com/m-team-kit/uSplit.git@main \
    ; fi
EXPOSE 5000 6006 8888

# Launch deepaas
ENTRYPOINT [ "deep-start" ]
CMD ["--deepaas"]