Update Dockerfile

Dockerfile

@@ -25,9 +25,8 @@ ENV HOME=/home/user \
 # Set the working directory to the user's home directory
 WORKDIR $HOME/app
 
-# Install system dependencies as root
+# Install Conda and create the environment
 USER root
-# Install basic utilities, Python 3.9, graphical libraries, and add NVIDIA cuDNN repository
 RUN apt-get update && apt-get install -y \
     wget \
     curl \
@@ -36,34 +35,30 @@ RUN apt-get update && apt-get install -y \
     gnupg \
     libgl1-mesa-glx \
     libglib2.0-0 \
-    && add-apt-repository ppa:deadsnakes/ppa -y && \
-    apt-get update && apt-get install -y \
-    python3.9 \
-    python3.9-distutils \
-    python3.9-dev \
-    && curl -sS https://bootstrap.pypa.io/get-pip.py | python3.9 \
-    && update-alternatives --install /usr/bin/python python /usr/bin/python3.9 1 \
-    && update-alternatives --install /usr/bin/pip pip /usr/local/bin/pip 1 \
-    && curl -fsSL https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/3bf863cc.pub | gpg --batch --yes --dearmor -o /usr/share/keyrings/cuda-archive-keyring.gpg && \
-    echo "deb [signed-by=/usr/share/keyrings/cuda-archive-keyring.gpg] https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/ /" > /etc/apt/sources.list.d/cuda.list && \
-    apt-get update && apt-get install -y \
-    libcudnn8=8.9.3.0-1+cuda11.8 \
-    libcudnn8-dev=8.9.3.0-1+cuda11.8 \
-    libcudnn8-doc=8.9.3.0-1+cuda11.8 \
+    && wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh \
+    && bash miniconda.sh -b -p /opt/conda \
+    && rm miniconda.sh \
+    && /opt/conda/bin/conda init bash \
+    && /opt/conda/bin/conda update -n base -c defaults conda \
+    && /opt/conda/bin/conda install -y -c conda-forge mamba \
+    && /opt/conda/bin/mamba install -c nvidia -c pytorch -c conda-forge -c defaults python=3.9 pytorch=2.5.1 torchvision=0.20.1 torchaudio=2.5.1 pytorch-cuda=11.8 timm scikit-learn matplotlib pandas \
     && rm -rf /var/lib/apt/lists/*
 
-# Verify cuDNN installation
-RUN dpkg-query -W libcudnn8
-
-# Verify Python and pip versions
-RUN python --version && pip --version
+# Verify installation
+RUN /opt/conda/bin/conda --version
+RUN /opt/conda/bin/python --version
+RUN /opt/conda/bin/python -c "import torch; print(torch.__version__)"
 
 USER user
-# Copy dependencies and install them via pip
+# Create the environment and activate it
+RUN /opt/conda/bin/conda env create -f /home/user/app/environment.yaml
+RUN echo "conda activate gazelle" >> ~/.bashrc
+
+# Install additional Python dependencies
 COPY . .
-RUN pip install --upgrade pip
-RUN pip install -r requirements.txt
-RUN pip install gradio
+RUN /opt/conda/bin/pip install --upgrade pip
+RUN /opt/conda/bin/pip install -r requirements.txt
+RUN /opt/conda/bin/pip install gradio
 
 USER root
 # Configure git to trust the directory
@@ -77,4 +72,4 @@ ENV CUDA_DEVICE_ORDER=PCI_BUS_ID
 ENV CUDA_VISIBLE_DEVICES=0
 
 # Command to run your application
-CMD ["python", "app.py"]
+CMD ["/opt/conda/bin/python", "app.py"]