FROM tensorflow/tensorflow:2.2.0-gpu

# why 2.3 ? I looked it up on stack overflow
# https://stackoverflow.com/questions/50622525/which-tensorflow-and-cuda-version-combinations-are-compatible
# here is a nice list, which tf version is compatible with which cuda
# from the cmmand docker run --runtime=nvidia --rm nvidia/cuda:9.0-base nvidia-smi
# you get your installed cuda version running

#RUN useradd -ms /bin/bash pluritonian


#USER pluritonian

WORKDIR /home/pluritonian/Prototyp

RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub

RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub

RUN apt-get update && apt-get install nano

RUN pip install joblib scikit-learn==0.20.0 hickle==3.4.9 

RUN pip install idna==2.9 python-multipart==0.0.5 

RUN pip install nltk==3.4.1 spacy==2.0.18 pandas==0.23.4 ipywidgets==7.5.1 beautifulsoup4==4.6.3

RUN python -m spacy download de_core_news_sm

RUN pip install --upgrade pip && pip install fastapi uvicorn[standard] httpx asyncio

#COPY Prototyp/* /home/pluritonian/


# to let the container running:

CMD python -m uvicorn fastapi_server:app --reload --host 0.0.0.0 --port 8000

#CMD /bin/sh -c "while true; do sleep 30; done"

#ENTRYPOINT ["tail"]
#CMD ["-f","/dev/null"]