| # read the doc: https://huggingface.co/docs/hub/spaces-sdks-docker | |
| # you will also find guides on how best to write your Dockerfile | |
| FROM debian:bullseye-slim | |
| # Install prerequisites | |
| #RUN apt-get update -y && \ | |
| # apt-get install -y apt-transport-https ca-certificates gnupg curl | |
| # Add the Cloud SDK distribution URI as a package source | |
| #RUN echo "deb [signed-by=/usr/share/keyrings/cloud.google.asc] https://packages.cloud.google.com/apt cloud-sdk main" | tee -a /etc/apt/sources.list.d/google-cloud-sdk.list | |
| # Import the Google Cloud public key | |
| #RUN curl https://packages.cloud.google.com/apt/doc/apt-key.gpg | tee /usr/share/keyrings/cloud.google.asc | |
| # Update the package list and install the Google Cloud CLI | |
| #RUN apt-get update -y && apt-get install -y google-cloud-sdk | |
| # You can include additional commands to configure or use the gcloud CLI here | |
| # For example, you can authenticate with your service account key file: | |
| #COPY your-service-account-key.json /tmp/key.json | |
| #ENV GOOGLE_APPLICATION_CREDENTIALS=/tmp/key.json | |
| #RUN gcloud auth activate-service-account --key-file=${GOOGLE_APPLICATION_CREDENTIALS} | |
| # ... further instructions ... | |
| ENV NVIDIA_VISIBLE_DEVICES all | |
| ENV NVIDIA_DRIVER_CAPABILITIES compute,utility | |
| ENV NVIDIA_REQUIRE_CUDA "cuda>=8.0" | |
| ENV LD_LIBRARY_PATH=/usr/local/cuda-11.8/targets/x86_64-linux/lib:/usr/local/cuda-11.8/targets/x86_64-linux/include:/usr/local/cuda/include:/usr/local/cuda-11.8:/usr/local/cuda/lib:/usr/local/cuda/lib64:$LD_LIBRARY_PATH | |
| #RUN dpkg --add-architecture amd64 | |
| #RUN apt-get update && \ | |
| # apt-get install -y --no-install-recommends gnupg2 curl ca-certificates | |
| #RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/debian11/x86_64/7fa2af80.pub | |
| # Import the NVIDIA GPG key | |
| #RUN apt-get update && apt-get install -y gnupg2 curl | |
| # Fetch the NVIDIA repository GPG key | |
| #RUN curl -fsSL https://developer.download.nvidia.com/compute/cuda/repos/debian11/x86_64/7fa2af80.pub | gpg --dearmor -o /usr/share/keyrings/cuda-archive-keyring.gpg | |
| # Add the NVIDIA repository to the APT sources list | |
| #RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub | |
| #RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub | |
| #RUN echo "deb https://developer.download.nvidia.com/compute/cuda/repos/debian11/x86_64 /" > /etc/apt/sources.list.d/cuda.list | |
| # Install FFmpeg | |
| RUN apt-get update && \ | |
| apt-get install -y python3-pip ffmpeg | |
| #libcublas-11-8 libcudnn8=8.6.0.163-1+cuda11.8 | |
| #libcudnn8=8.8.0.121-1+cuda11.8 | |
| # Set the working directory to /code | |
| WORKDIR /app | |
| # Copy the requirements file into the container at /code/ | |
| #COPY ./requirements.txt /app/requirements.txt | |
| # Copy the FastAP application code into the container | |
| COPY ./ /app | |
| #COPY ./interface.html /app/interface.html | |
| #COPY ./styles.css /app/styles.css | |
| # Install the required Python packages from requirements.txt | |
| RUN pip install --no-cache-dir --upgrade -r requirements.txt | |
| RUN pip install --upgrade fastapi authlib starlette | |
| # Create a non-root user (optional but recommended for security) | |
| RUN useradd -m -u 1000 user | |
| # Switch to the non-root user | |
| USER user | |
| # Define environment variables | |
| ENV HOME=/home/user \ | |
| PATH=/home/user/.local/bin:$PATH | |
| # Change the working directory to /home/user/app | |
| WORKDIR $HOME/app | |
| # Copy the rest of the application files into the container | |
| COPY --chown=user . $HOME/app | |
| # Expose port 80 for the FastAPI application | |
| EXPOSE 7860 | |
| # Specify the command to run your application (modify as needed) | |
| CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"] | |