Update Dockerfile

Dockerfile

@@ -1,33 +1,33 @@
-# Change this line to use the modern "Bookworm" base image
-FROM python:3.10-slim-bookworm
+# Use the CUDA 11.8 base image that we know works
+FROM nvidia/cuda:11.8.0-devel-ubuntu22.04
 
 # Set up the environment
 ENV DEBIAN_FRONTEND=noninteractive
 ENV PYTHONUNBUFFERED=1
 
-# Install system dependencies needed for OpenCV
-RUN apt-get update && apt-get install -y libgl1-mesa-glx && rm -rf /var/lib/apt/lists/*
+# Install Python 3.10
+RUN apt-get update && apt-get install -y \
+    python3.10 python3-pip libgl1-mesa-glx \
+    && rm -rf /var/lib/apt/lists/*
 
 # Set the working directory
 WORKDIR /app
 
 # Set a writable cache directory
 ENV HF_HOME=/app/cache
-
-# Create the cache directory
 RUN mkdir -p /app/cache && chmod 777 /app/cache
 
-# Install PyTorch for CUDA 11.3. It will link to the host's CUDA libraries at runtime.
-RUN pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cu113
+# Install the exact, known-good version of PyTorch for CUDA 11.8
+RUN pip3 install torch==2.1.2+cu118 torchvision==0.16.2+cu118 --extra-index-url https://download.pytorch.org/whl/cu118
 
-# Copy and install the rest of the Python dependencies
+# Copy and install the rest of the dependencies
 COPY requirements.txt .
-RUN pip install --no-cache-dir -r requirements.txt
+RUN pip3 install --no-cache-dir -r requirements.txt
 
 # Copy your main application code
 COPY main.py .
 
-# Expose the port your API will run on
+# Expose the port
 EXPOSE 8000
 
 # The command to start the Uvicorn server