Dockerfile

FROM python:3.12

#RUN pip install --no-cache-dir torch==2.2.2
#RUN pip install --no-cache-dir flash-attn

RUN apt-get update && \
    apt-get install -y \
      bash \
      git git-lfs \
      wget curl procps gnupg \
      build-essential cmake \
      htop vim nano && \
    rm -rf /var/lib/apt/lists/*

# NVIDIA CUDA Repository einbinden
RUN wget https://developer.download.nvidia.com/compute/cuda/repos/debian12/x86_64/cuda-debian12.pin && \
    mv cuda-debian12.pin /etc/apt/preferences.d/cuda-repository-pin-600 && \
    wget https://developer.download.nvidia.com/compute/cuda/12.2.2/local_installers/cuda-repo-debian12-12-2-local_12.2.2-1_amd64.deb && \
    dpkg -i cuda-repo-debian12-12-2-local_12.2.2-1_amd64.deb && \
    cp /var/cuda-repo-debian12-12-2-local/cuda-*-keyring.gpg /usr/share/keyrings/ && \
    apt-get update && \
    apt-get -y install cuda-toolkit-12-2

# CUDA ENV-Variablen setzen
ENV PATH=/usr/local/cuda/bin:${PATH}
ENV LD_LIBRARY_PATH=/usr/local/cuda/lib64:${LD_LIBRARY_PATH}
ENV CUDAToolkit_ROOT=/usr/local/cuda

RUN useradd -m -u 1000 user
USER user
ENV PATH="/home/user/.local/bin:$PATH"
# ^ when run as `user`, pip installs executables there

WORKDIR /app

COPY --chown=user . /app

RUN pip install --upgrade pip
RUN pip install --no-cache-dir -r requirements.txt
RUN CMAKE_ARGS="-DGGML_CUDA=on" pip install outetts --upgrade

#CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860", , "--ws", "auto", "--allow-websocket-origin", "*"]
CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]