Update Dockerfile

Dockerfile

@@ -5,7 +5,6 @@ FROM pytorch/pytorch:2.0.1-cuda11.7-cudnn8-runtime
 ENV DEBIAN_FRONTEND=noninteractive \
     MKL_THREADING_LAYER=GNU \
     HOME=/home/user \
-    PATH=/home/user/.local/bin:/usr/local/cuda/bin:$PATH \
     PYTHONPATH=/home/user/app \
     PYTHONUNBUFFERED=1 \
     GRADIO_ALLOW_FLAGGING=never \
@@ -16,30 +15,38 @@ ENV DEBIAN_FRONTEND=noninteractive \
     SYSTEM=spaces \
     CUDA_TOOLKIT_ROOT_DIR=/usr/local/cuda \
     CUDA_HOME=/usr/local/cuda \
-    LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH \
+    LD_LIBRARY_PATH=/usr/local/cuda/lib64 \
     TORCH_CUDA_ARCH_LIST="8.6" \
     CMAKE_PREFIX_PATH="/usr/local/cuda:/usr/lib/x86_64-linux-gnu/"
 
-# Install Python 3.9 and necessary dependencies
+# Override PATH so that the system's /usr/bin (with Python 3.9) is used instead of Conda's
+ENV PATH="/usr/local/cuda/bin:/usr/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/sbin"
+
+# Install Python 3.9 and build dependencies (including for NumPy)
 RUN apt-get update && \
     apt-get install -y --no-install-recommends \
     python3.9 python3.9-dev python3.9-venv \
     git wget libgl1-mesa-glx libglib2.0-0 ffmpeg libx264-dev pkg-config \
-    build-essential cmake g++ software-properties-common gnupg2 libopenblas-dev && \
+    build-essential gfortran libopenblas-dev liblapack-dev \
+    cmake g++ software-properties-common gnupg2 && \
     rm -rf /var/lib/apt/lists/*
 
-# Set Python 3.9 as the default python3 and install pip
+# Set Python 3.9 as the default python3 and install pip for it
 RUN update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.9 1 && \
     update-alternatives --set python3 /usr/bin/python3.9 && \
     curl -sS https://bootstrap.pypa.io/get-pip.py | python3.9 && \
     ln -sf /usr/bin/python3.9 /usr/bin/python && \
-    ln -sf /usr/local/bin/pip /usr/bin/pip3
+    ln -sf /usr/bin/pip3 /usr/bin/pip
+
+# Upgrade pip, setuptools, and wheel
+RUN python3.9 -m pip install --upgrade pip setuptools wheel
 
 # Add NVIDIA package repositories and install CUDA Toolkit and cuDNN
 RUN wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-keyring_1.0-1_all.deb && \
     dpkg -i cuda-keyring_1.0-1_all.deb && \
     apt-get update && \
-    apt-get install -y --no-install-recommends cuda-toolkit-11-7 libcudnn8 libcudnn8-dev && \
+    apt-get install -y --no-install-recommends \
+    cuda-toolkit-11-7 libcudnn8 libcudnn8-dev && \
     rm -rf /var/lib/apt/lists/*
 
 # Create a non-root user
@@ -59,17 +66,20 @@ RUN mkdir -p checkpoints && \
     wget https://huggingface.co/camenduru/dreamtalk/resolve/main/damo/dreamtalk/checkpoints/denoising_network.pth -O checkpoints/denoising_network.pth && \
     wget https://huggingface.co/camenduru/dreamtalk/resolve/main/damo/dreamtalk/checkpoints/renderer.pt -O checkpoints/renderer.pt
 
-# Copy and install Python dependencies
+# Install NumPy first (to help avoid build issues)
+RUN python3.9 -m pip install numpy
+
+# Copy and install remaining Python dependencies
 COPY requirements_HF.txt .
-RUN pip install --no-cache-dir -r requirements_HF.txt && \
-    pip install --no-cache-dir "moviepy<2" gradio
+RUN python3.9 -m pip install --no-cache-dir -r requirements_HF.txt && \
+    python3.9 -m pip install --no-cache-dir "moviepy<2" gradio
 
 # Copy the application file
 COPY app.py .
 
-# Set CUDA environment variables
+# Set CUDA environment variables (if needed)
 ENV CUDA_DEVICE_ORDER=PCI_BUS_ID \
     CUDA_VISIBLE_DEVICES=0
 
-# Run the application
-CMD ["python", "app.py"]
+# Run the application with Python 3.9 explicitly
+CMD ["python3.9", "app.py"]