Dockerfile

# Use an appropriate base image with Ubuntu
FROM nvidia/cuda:11.2.2-base-ubuntu20.04

# Set environment variables for CUDA
ENV CUDA_HOME=/usr/local/cuda
ENV PATH=$CUDA_HOME/bin:$PATH
ENV LD_LIBRARY_PATH=$CUDA_HOME/lib64:$LD_LIBRARY_PATH

RUN nvidia-smi

# # Set DEBIAN_FRONTEND to noninteractive to prevent interactive prompts
# ENV DEBIAN_FRONTEND=noninteractive

# # Install NVIDIA driver
# RUN apt-get update && apt-get install -y --no-install-recommends nvidia-driver-460

# RUN apt-get -y update \
#     && apt-get install -y software-properties-common

# RUN apt-get -y update \
#     && add-apt-repository ppa:deadsnakes/ppa

# RUN apt-get -y update \
#     && apt-get -y install python3.10 \
#     && apt-get -y install python3-pip

# RUN apt-get -y update \
#     && apt-get -y install git

# # Additional system dependencies
# RUN apt-get -y update \
#     && apt-get install -y ffmpeg \
#     && apt-get install -y yt-dlp

# # FROM python:3.10

# # Switch back to the root user to install Python packages
# USER root

# # Copy your requirements.txt and install Python packages
# COPY ./requirements.txt /code/requirements.txt
# RUN pip3 install --no-cache-dir --upgrade -r /code/requirements.txt

# # Create a non-root user and set environment variables
# RUN useradd -m -u 1000 user
# USER user
# ENV HOME=/home/user \
#     PATH=/home/user/.local/bin:$PATH

# # Set the working directory and copy your application files
# WORKDIR $HOME/app
# COPY --chown=user . $HOME/app

# # Specify the command to run your application
# CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"]