## Docker GROBID image using deep learning models and/or CRF models

## See https://grobid.readthedocs.io/en/latest/Grobid-docker/

## usage example with version 0.8.0:
## docker build -t grobid/grobid:0.8.0 --build-arg GROBID_VERSION=0.8.0 --file Dockerfile.delft .

## no GPU:
## docker run -t --rm --init -p 8070:8070 -p 8071:8071 -v /home/lopez/grobid/grobid-home/config/grobid.properties:/opt/grobid/grobid-home/config/grobid.properties:ro  grobid/grobid:0.8.0

## allocate all available GPUs (only Linux with proper nvidia driver installed on host machine):
## docker run --rm --gpus all --init -p 8070:8070 -p 8071:8071 -v /home/lopez/grobid/grobid-home/config/grobid.properties:/opt/grobid/grobid-home/config/grobid.properties:ro  grobid/grobid:0.8.0

# -------------------
# build builder image
# -------------------

FROM openjdk:17-jdk-slim as builder

USER root

RUN apt-get update && \
    apt-get -y --no-install-recommends install unzip

WORKDIR /opt/grobid-source

# gradle
COPY gradle/ ./gradle/
COPY gradlew ./
COPY gradle.properties ./
COPY build.gradle ./
COPY settings.gradle ./

# source
COPY grobid-home/ ./grobid-home/
COPY grobid-core/ ./grobid-core/
COPY grobid-service/ ./grobid-service/
COPY grobid-trainer/ ./grobid-trainer/

# cleaning unused native libraries before packaging
RUN rm -rf grobid-home/pdf2xml
RUN rm -rf grobid-home/pdfalto/lin-32
RUN rm -rf grobid-home/pdfalto/mac-64
RUN rm -rf grobid-home/pdfalto/mac_arm-64
RUN rm -rf grobid-home/pdfalto/win-*
RUN rm -rf grobid-home/lib/lin-32
RUN rm -rf grobid-home/lib/win-*
RUN rm -rf grobid-home/lib/mac-64

RUN ./gradlew clean assemble --no-daemon  --info --stacktrace

WORKDIR /opt/grobid
RUN unzip -o /opt/grobid-source/grobid-service/build/distributions/grobid-service-*.zip && \
    mv grobid-service* grobid-service
RUN unzip -o /opt/grobid-source/grobid-home/build/distributions/grobid-home-*.zip && \
    chmod -R 755 /opt/grobid/grobid-home/pdfalto
RUN rm -rf grobid-source

# -------------------
# build runtime image
# -------------------

# use NVIDIA Container Toolkit to automatically recognize possible GPU drivers on the host machine
FROM tensorflow/tensorflow:2.7.0-gpu

# setting locale is likely useless but to be sure
ENV LANG C.UTF-8

# update NVIDIA Cuda key (following a key rotation in April 2022)
RUN apt-get install -y wget
RUN apt-key del 7fa2af80
RUN rm /etc/apt/sources.list.d/cuda.list
RUN rm /etc/apt/sources.list.d/nvidia-ml.list
RUN wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-keyring_1.0-1_all.deb
RUN dpkg -i cuda-keyring_1.0-1_all.deb

# install JRE, python and other dependencies
RUN apt-get update && \
    apt-get -y --no-install-recommends install apt-utils build-essential gcc libxml2 libfontconfig unzip curl \
    openjdk-17-jre-headless ca-certificates-java \
    musl gfortran \
    python3 python3-pip python3-setuptools python3-dev \
    && apt-get clean \
    && rm -rf /var/lib/apt/lists/*

WORKDIR /opt/grobid

COPY --from=builder /opt/grobid .

RUN python3 -m pip install pip --upgrade

# install DeLFT via pypi
RUN pip3 install requests delft==0.3.3
# link the data directory to /data
# the current working directory will most likely be /opt/grobid
RUN mkdir -p /data \
    && ln -s /data /opt/grobid/data \
    && ln -s /data ./data

# disable python warnings (and fix logging)
ENV PYTHONWARNINGS="ignore"

WORKDIR /opt/grobid

ENV JAVA_OPTS=-Xmx4g

# install jep (and temporarily the matching JDK)
ENV JDK_URL=https://download.java.net/java/GA/jdk17.0.2/dfd4a8d0985749f896bed50d7138ee7f/8/GPL/openjdk-17.0.2_linux-x64_bin.tar.gz
RUN curl --fail --show-error --location -q ${JDK_URL} -o /tmp/openjdk.tar.gz 
RUN mkdir /tmp/jdk-17 
RUN tar xvfz /tmp/openjdk.tar.gz --directory /tmp/jdk-17 --strip-components 1 --no-same-owner 
RUN /tmp/jdk-17/bin/javac -version
RUN JAVA_HOME=/tmp/jdk-17 pip3 install jep==4.0.2 
RUN rm -f /tmp/openjdk.tar.gz 
RUN rm -rf /tmp/jdk-17
ENV LD_LIBRARY_PATH=/usr/local/lib/python3.8/dist-packages/jep:grobid-home/lib/lin-64:grobid-home/lib/lin-64/jep:${LD_LIBRARY_PATH}
# remove libjep.so because we are providing our own version in the virtual env above
RUN rm /opt/grobid/grobid-home/lib/lin-64/jep/libjep.so

# preload embeddings, for GROBID all the RNN models use glove-840B (default for the script), ELMo is currently not loaded 
# to be done: mechanism to download GROBID fine-tuned models based on SciBERT if selected (but not good enough for the moment)

COPY --from=builder /opt/grobid-source/grobid-home/scripts/preload_embeddings.py .
COPY --from=builder /opt/grobid-source/grobid-home/config/resources-registry.json .
RUN python3 preload_embeddings.py --registry ./resources-registry.json
RUN ln -s /opt/grobid /opt/delft

RUN mkdir delft
RUN cp ./resources-registry.json delft/

ENV GROBID_SERVICE_OPTS "--add-opens java.base/java.lang=ALL-UNNAMED"

CMD ["./grobid-service/bin/grobid-service"]

ARG GROBID_VERSION

LABEL \
    authors="The contributors" \
    org.label-schema.name="GROBID" \
    org.label-schema.description="Image with GROBID service" \
    org.label-schema.url="https://github.com/kermitt2/grobid" \
    org.label-schema.version=${GROBID_VERSION}